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+Details + ## TLDR

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404

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api_key="${v||"YOUR_LITELLM_API_KEY"}", + base_url="${x}"${S} +)`;switch(m){case t.EndpointType.CHAT:{let e=Object.keys(k).length>0,t="";if(e){let e=JSON.stringify({metadata:k},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();t=`, + extra_body=${e}`}let s=w.length>0?w:[{role:"user",content:y}];i=` +import base64 + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Example with text only +response = client.chat.completions.create( + model="${j}", + messages=${JSON.stringify(s,null,4)}${t} +) + +print(response) + +# Example with image or PDF (uncomment and provide file path to use) +# base64_file = encode_image("path/to/your/file.jpg") # or .pdf +# response_with_file = client.chat.completions.create( +# model="${j}", +# messages=[ +# { +# "role": "user", +# "content": [ +# { +# "type": "text", +# "text": "${E}" +# }, +# { +# "type": "image_url", +# "image_url": { +# "url": f"data:image/jpeg;base64,{base64_file}" # or data:application/pdf;base64,{base64_file} +# } +# } +# ] +# } +# ]${t} +# ) +# print(response_with_file) +`;break}case t.EndpointType.RESPONSES:{let e=Object.keys(k).length>0,t="";if(e){let e=JSON.stringify({metadata:k},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();t=`, + extra_body=${e}`}let s=w.length>0?w:[{role:"user",content:y}];i=` +import base64 + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Example with text only +response = client.responses.create( + model="${j}", + input=${JSON.stringify(s,null,4)}${t} +) + +print(response.output_text) + +# Example with image or PDF (uncomment and provide file path to use) +# base64_file = encode_image("path/to/your/file.jpg") # or .pdf +# response_with_file = client.responses.create( +# model="${j}", +# input=[ +# { +# "role": "user", +# "content": [ +# {"type": "input_text", "text": "${E}"}, +# { +# "type": "input_image", +# "image_url": f"data:image/jpeg;base64,{base64_file}", # or data:application/pdf;base64,{base64_file} +# "detail": "auto", +# }, +# ], +# } +# ]${t} +# ) +# print(response_with_file.output_text) +`;break}case t.EndpointType.IMAGE:i="azure"===h?` +# NOTE: The Azure SDK does not have a direct equivalent to the multi-modal 'responses.create' method shown for OpenAI. +# This snippet uses 'client.images.generate' and will create a new image based on your prompt. +# It does not use the uploaded image, as 'client.images.generate' does not support image inputs in this context. +import os +import requests +import json +import time +from PIL import Image + +result = client.images.generate( + model="${j}", + prompt="${a}", + n=1 +) + +json_response = json.loads(result.model_dump_json()) + +# Set the directory for the stored image +image_dir = os.path.join(os.curdir, 'images') + +# If the directory doesn't exist, create it +if not os.path.isdir(image_dir): + os.mkdir(image_dir) + +# Initialize the image path +image_filename = f"generated_image_{int(time.time())}.png" +image_path = os.path.join(image_dir, image_filename) + +try: + # Retrieve the generated image + if json_response.get("data") && len(json_response["data"]) > 0 && json_response["data"][0].get("url"): + image_url = json_response["data"][0]["url"] + generated_image = requests.get(image_url).content + with open(image_path, "wb") as image_file: + image_file.write(generated_image) + + print(f"Image saved to {image_path}") + # Display the image + image = Image.open(image_path) + image.show() + else: + print("Could not find image URL in response.") + print("Full response:", json_response) +except Exception as e: + print(f"An error occurred: {e}") + print("Full response:", json_response) +`:` +import base64 +import os +import time +import json +from PIL import Image +import requests + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Helper function to create a file (simplified for this example) +def create_file(image_path): + # In a real implementation, this would upload the file to OpenAI + # For this example, we'll just return a placeholder ID + return f"file_{os.path.basename(image_path).replace('.', '_')}" + +# The prompt entered by the user +prompt = "${E}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${j}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + "detail": "auto", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + "detail": "auto", + }, + { + "type": "input_image", + "file_id": file_id1, + "detail": "auto", + }, + { + "type": "input_image", + "file_id": file_id2, + "detail": "auto", + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`;break;case t.EndpointType.IMAGE_EDITS:i="azure"===h?` +import base64 +import os +import time +import json +from PIL import Image +import requests + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# The prompt entered by the user +prompt = "${E}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${j}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + "detail": "auto", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + "detail": "auto", + }, + { + "type": "input_image", + "file_id": file_id1, + "detail": "auto", + }, + { + "type": "input_image", + "file_id": file_id2, + "detail": "auto", + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`:` +import base64 +import os +import time + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Helper function to create a file (simplified for this example) +def create_file(image_path): + # In a real implementation, this would upload the file to OpenAI + # For this example, we'll just return a placeholder ID + return f"file_{os.path.basename(image_path).replace('.', '_')}" + +# The prompt entered by the user +prompt = "${E}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${j}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + "detail": "auto", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + "detail": "auto", + }, + { + "type": "input_image", + "file_id": file_id1, + "detail": "auto", + }, + { + "type": "input_image", + "file_id": file_id2, + "detail": "auto", + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`;break;case t.EndpointType.EMBEDDINGS:i=` +response = client.embeddings.create( + input="${a||"Your string here"}", + model="${j}", + encoding_format="base64" # or "float" +) + +print(response.data[0].embedding) +`;break;case t.EndpointType.TRANSCRIPTION:i=` +# Open the audio file +audio_file = open("path/to/your/audio/file.mp3", "rb") + +# Make the transcription request +response = client.audio.transcriptions.create( + model="${j}", + file=audio_file${a?`, + prompt="${a.replace(/\\/g,"\\\\").replace(/"/g,'\\"')}"`:""} +) + +print(response.text) +`;break;case t.EndpointType.SPEECH:i=` +# Make the text-to-speech request +response = client.audio.speech.create( + model="${j}", + input="${a||"Your text to convert to speech here"}", + voice="${p}" # Options: alloy, ash, ballad, coral, echo, fable, nova, onyx, sage, shimmer +) + 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g={...p.popupStoreSelectors,disabled:(0,d.createSelector)(t=>t.disabled),instantType:(0,d.createSelector)(t=>t.instantType),isInstantPhase:(0,d.createSelector)(t=>t.isInstantPhase),trackCursorAxis:(0,d.createSelector)(t=>t.trackCursorAxis),disableHoverablePopup:(0,d.createSelector)(t=>t.disableHoverablePopup),lastOpenChangeReason:(0,d.createSelector)(t=>t.openChangeReason),closeOnClick:(0,d.createSelector)(t=>t.closeOnClick),closeDelay:(0,d.createSelector)(t=>t.closeDelay),hasViewport:(0,d.createSelector)(t=>t.hasViewport)};class v extends f.ReactStore{constructor(t,n,i=!1){const a=new h.PopupTriggerMap,o={...{...(0,p.createInitialPopupStoreState)(),disabled:!1,instantType:void 0,isInstantPhase:!1,trackCursorAxis:"none",disableHoverablePopup:!1,openChangeReason:null,closeOnClick:!0,closeDelay:0,hasViewport:!1},...t};o.floatingRootContext=(0,p.createPopupFloatingRootContext)(a,n,i),super(o,{popupRef:r.createRef(),onOpenChange:void 0,onOpenChangeComplete:void 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IPv4",cidrv6:"ដែនអាសយដ្ឋាន IPv6",base64:"ខ្សែអក្សរអ៊ិកូដ base64",base64url:"ខ្សែអក្សរអ៊ិកូដ base64url",json_string:"ខ្សែអក្សរ JSON",e164:"លេខ E.164",credit_card:"លេខប័ណ្ណឥណទាន",currency_code:"កូដរូបិយប័ណ្ណ",iban:"IBAN",jwt:"JWT",template_literal:"ទិន្នន័យបញ្ចូល"},n={nan:"NaN",number:"លេខ",array:"អារេ (Array)",null:"គ្មានតម្លៃ (null)"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`ទិន្នន័យបញ្ចូលមិនត្រឹមត្រូវ៖ ត្រូវការ instanceof ${i.expected} ប៉ុន្តែទទួលបាន ${a}`;return`ទិន្នន័យបញ្ចូលមិនត្រឹមត្រូវ៖ ត្រូវការ ${t} ប៉ុន្តែទទួលបាន ${a}`}case"invalid_value":if(1===i.values.length)return`ទិន្នន័យបញ្ចូលមិនត្រឹមត្រូវ៖ ត្រូវការ ${G(i.values[0])}`;return`ជម្រើសមិនត្រឹមត្រូវ៖ ត្រូវជាមួយក្នុងចំណោម ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`ធំពេក៖ ត្រូវការ ${i.origin??"តម្លៃ"} ${r} ${i.maximum.toString()} ${n.unit??"ធាតុ"}`;return`ធំពេក៖ ត្រូវការ ${i.origin??"តម្លៃ"} ${r} ${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`តូចពេក៖ ត្រូវការ ${i.origin} ${r} ${i.minimum.toString()} ${n.unit}`;return`តូចពេក៖ ត្រូវការ ${i.origin} ${r} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវចាប់ផ្តើមដោយ "${i.prefix}"`;if("ends_with"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវបញ្ចប់ដោយ "${i.suffix}"`;if("includes"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវមាន "${i.includes}"`;if("regex"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវតែផ្គូផ្គងនឹងទម្រង់ដែលបានកំណត់ ${i.pattern}`;return`មិនត្រឹមត្រូវ៖ ${r[i.format]??i.format}`;case"not_multiple_of":return`លេខមិនត្រឹមត្រូវ៖ ត្រូវតែជាពហុគុណនៃ ${i.divisor}`;case"unrecognized_keys":return`រកឃើញសោមិនស្គាល់៖ ${d(i.keys,", ")}`;case"invalid_key":return`សោមិនត្រឹមត្រូវនៅក្នុង ${i.origin}`;case"invalid_union":default:return"ទិន្នន័យមិនត្រឹមត្រូវ";case"invalid_element":return`ទិន្នន័យមិនត្រឹមត្រូវនៅក្នុង ${i.origin}`}})}}t.s([],543365),t.i(543365);let i8=t=>t.charAt(0).toUpperCase()+t.slice(1);function ae(t){let r=Math.abs(t),n=r%10,i=r%100;return i>=11&&i<=19||0===n?"many":1===n?"one":"few"}function at(t,r,n,i){let a=Math.abs(t),o=a%10,s=a%100;return s>=11&&s<=19?i:1===o?r:o>=2&&o<=4?n:i}function ar(){let t,r,n;return{localeError:(t={string:{unit:"символів",verb:"матиме"},file:{unit:"байтів",verb:"матиме"},array:{unit:"елементів",verb:"матиме"},set:{unit:"елементів",verb:"матиме"},map:{unit:"елементів",verb:"матиме"}},r={regex:"вхідні дані",email:"адреса електронної пошти",url:"URL",emoji:"емодзі",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"дата та час ISO",date:"дата ISO",time:"час ISO",duration:"тривалість ISO",ipv4:"адреса IPv4",ipv6:"адреса IPv6",mac:"адреса MAC",cidrv4:"діапазон IPv4",cidrv6:"діапазон IPv6",base64:"рядок у кодуванні base64",base64url:"рядок у кодуванні base64url",json_string:"рядок JSON",e164:"номер E.164",credit_card:"номер кредитної картки",currency_code:"код валюти",iban:"IBAN",jwt:"JWT",template_literal:"вхідні дані"},n={nan:"NaN",number:"число",array:"масив"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Неправильні вхідні дані: очікується instanceof ${i.expected}, отримано ${a}`;return`Неправильні вхідні дані: очікується ${t}, отримано ${a}`}case"invalid_value":if(1===i.values.length)return`Неправильні вхідні дані: очікується ${G(i.values[0])}`;return`Неправильна опція: очікується одне з ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`Занадто велике: очікується, що ${i.origin??"значення"} ${n.verb} ${r}${i.maximum.toString()} ${n.unit??"елементів"}`;return`Занадто велике: очікується, що ${i.origin??"значення"} буде ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`Занадто мале: очікується, що ${i.origin} ${n.verb} ${r}${i.minimum.toString()} ${n.unit}`;return`Занадто мале: очікується, що ${i.origin} буде ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Неправильний рядок: повинен починатися з "${i.prefix}"`;if("ends_with"===i.format)return`Неправильний рядок: повинен закінчуватися на "${i.suffix}"`;if("includes"===i.format)return`Неправильний рядок: повинен містити "${i.includes}"`;if("regex"===i.format)return`Неправильний рядок: повинен відповідати шаблону ${i.pattern}`;return`Неправильний ${r[i.format]??i.format}`;case"not_multiple_of":return`Неправильне число: повинно бути кратним ${i.divisor}`;case"unrecognized_keys":return`Нерозпізнаний ключ${i.keys.length>1?"і":""}: ${d(i.keys,", ")}`;case"invalid_key":return`Неправильний ключ у ${i.origin}`;case"invalid_union":default:return"Неправильні вхідні дані";case"invalid_element":return`Неправильне значення у ${i.origin}`}})}}t.s(["ar",0,function(){let t,r,n;return{localeError:(t={string:{unit:"حرف",verb:"أن يحوي"},file:{unit:"بايت",verb:"أن يحوي"},array:{unit:"عنصر",verb:"أن يحوي"},set:{unit:"عنصر",verb:"أن يحوي"},map:{unit:"عنصر",verb:"أن يحوي"}},r={regex:"مدخل",email:"بريد إلكتروني",url:"رابط",emoji:"إيموجي",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"تاريخ ووقت بمعيار ISO",date:"تاريخ بمعيار ISO",time:"وقت بمعيار ISO",duration:"مدة بمعيار ISO",ipv4:"عنوان IPv4",ipv6:"عنوان IPv6",mac:"عنوان MAC",cidrv4:"مدى عناوين بصيغة IPv4",cidrv6:"مدى عناوين بصيغة IPv6",base64:"نَص بترميز base64-encoded",base64url:"نَص بترميز base64url-encoded",json_string:"نَص على هيئة JSON",e164:"رقم هاتف بمعيار E.164",credit_card:"رقم بطاقة الائتمان",currency_code:"رمز العملة",iban:"IBAN",jwt:"JWT",template_literal:"مدخل"},n={nan:"NaN"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`مدخلات غير مقبولة: يفترض إدخال instanceof ${i.expected}، ولكن تم إدخال ${a}`;return`مدخلات غير مقبولة: يفترض إدخال ${t}، ولكن تم إدخال ${a}`}case"invalid_value":if(1===i.values.length)return`مدخلات غير مقبولة: يفترض إدخال ${G(i.values[0])}`;return`اختيار غير مقبول: يتوقع انتقاء أحد هذه الخيارات: ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return` أكبر من اللازم: يفترض أن تكون ${i.origin??"القيمة"} ${r} ${i.maximum.toString()} ${n.unit??"عنصر"}`;return`أكبر من اللازم: يفترض أن تكون ${i.origin??"القيمة"} ${r} ${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`أصغر من اللازم: يفترض لـ ${i.origin} أن يكون ${r} ${i.minimum.toString()} ${n.unit}`;return`أصغر من اللازم: يفترض لـ ${i.origin} أن يكون ${r} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`نَص غير مقبول: يجب أن يبدأ بـ "${i.prefix}"`;if("ends_with"===i.format)return`نَص غير مقبول: يجب أن ينتهي بـ "${i.suffix}"`;if("includes"===i.format)return`نَص غير مقبول: يجب أن يتضمَّن "${i.includes}"`;if("regex"===i.format)return`نَص غير مقبول: يجب أن يطابق النمط ${i.pattern}`;return`${r[i.format]??i.format} غير مقبول`;case"not_multiple_of":return`رقم غير مقبول: يجب أن يكون من مضاعفات ${i.divisor}`;case"unrecognized_keys":return`معرف${i.keys.length>1?"ات":""} غريب${i.keys.length>1?"ة":""}: ${d(i.keys,"، ")}`;case"invalid_key":return`معرف غير مقبول في ${i.origin}`;case"invalid_union":default:return"مدخل غير مقبول";case"invalid_element":return`مدخل غير مقبول في ${i.origin}`}})}},"az",0,function(){let t,r,n;return{localeError:(t={string:{unit:"simvol",verb:"olmalıdır"},file:{unit:"bayt",verb:"olmalıdır"},array:{unit:"element",verb:"olmalıdır"},set:{unit:"element",verb:"olmalıdır"},map:{unit:"element",verb:"olmalıdır"}},r={regex:"input",email:"email address",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO datetime",date:"ISO date",time:"ISO time",duration:"ISO duration",ipv4:"IPv4 address",ipv6:"IPv6 address",mac:"MAC address",cidrv4:"IPv4 range",cidrv6:"IPv6 range",base64:"base64-encoded string",base64url:"base64url-encoded string",json_string:"JSON string",e164:"E.164 number",credit_card:"kredit kartı nömrəsi",currency_code:"valyuta kodu",iban:"IBAN",jwt:"JWT",template_literal:"input"},n={nan:"NaN"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Yanlış dəyər: g\xf6zlənilən instanceof ${i.expected}, daxil olan ${a}`;return`Yanlış dəyər: g\xf6zlənilən ${t}, daxil olan ${a}`}case"invalid_value":if(1===i.values.length)return`Yanlış dəyər: g\xf6zlənilən ${G(i.values[0])}`;return`Yanlış se\xe7im: aşağıdakılardan biri olmalıdır: ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`\xc7ox b\xf6y\xfck: g\xf6zlənilən ${i.origin??"dəyər"} ${r}${i.maximum.toString()} ${n.unit??"element"}`;return`\xc7ox b\xf6y\xfck: g\xf6zlənilən ${i.origin??"dəyər"} ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`\xc7ox ki\xe7ik: g\xf6zlənilən ${i.origin} ${r}${i.minimum.toString()} ${n.unit}`;return`\xc7ox ki\xe7ik: g\xf6zlənilən ${i.origin} ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Yanlış mətn: "${i.prefix}" ilə başlamalıdır`;if("ends_with"===i.format)return`Yanlış mətn: "${i.suffix}" ilə bitməlidir`;if("includes"===i.format)return`Yanlış mətn: "${i.includes}" daxil olmalıdır`;if("regex"===i.format)return`Yanlış mətn: ${i.pattern} şablonuna uyğun olmalıdır`;return`Yanlış ${r[i.format]??i.format}`;case"not_multiple_of":return`Yanlış ədəd: ${i.divisor} ilə b\xf6l\xfcnə bilən olmalıdır`;case"unrecognized_keys":return`Tanınmayan a\xe7ar${i.keys.length>1?"lar":""}: ${d(i.keys,", ")}`;case"invalid_key":return`${i.origin} daxilində yanlış a\xe7ar`;case"invalid_union":default:return"Yanlış dəyər";case"invalid_element":return`${i.origin} daxilində yanlış dəyər`}})}},"be",0,function(){let t,r,n;return{localeError:(t={string:{unit:{one:"сімвал",few:"сімвалы",many:"сімвалаў"},verb:"мець"},array:{unit:{one:"элемент",few:"элементы",many:"элементаў"},verb:"мець"},set:{unit:{one:"элемент",few:"элементы",many:"элементаў"},verb:"мець"},map:{unit:{one:"элемент",few:"элементы",many:"элементаў"},verb:"мець"},file:{unit:{one:"байт",few:"байты",many:"байтаў"},verb:"мець"}},r={regex:"увод",email:"email адрас",url:"URL",emoji:"эмодзі",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO дата і час",date:"ISO дата",time:"ISO час",duration:"ISO працягласць",ipv4:"IPv4 адрас",ipv6:"IPv6 адрас",mac:"MAC адрас",cidrv4:"IPv4 дыяпазон",cidrv6:"IPv6 дыяпазон",base64:"радок у фармаце base64",base64url:"радок у фармаце base64url",json_string:"JSON радок",e164:"нумар E.164",credit_card:"нумар крэдытнай карты",currency_code:"код валюты",iban:"IBAN",jwt:"JWT",template_literal:"увод"},n={nan:"NaN",number:"лік",array:"масіў"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Няправільны ўвод: чакаўся instanceof ${i.expected}, атрымана ${a}`;return`Няправільны ўвод: чакаўся ${t}, атрымана ${a}`}case"invalid_value":if(1===i.values.length)return`Няправільны ўвод: чакалася ${G(i.values[0])}`;return`Няправільны варыянт: чакаўся адзін з ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n){let t=i2(Number(i.maximum),n.unit.one,n.unit.few,n.unit.many);return`Занадта вялікі: чакалася, што ${i.origin??"значэнне"} павінна ${n.verb} ${r}${i.maximum.toString()} ${t}`}return`Занадта вялікі: чакалася, што ${i.origin??"значэнне"} павінна быць ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n){let t=i2(Number(i.minimum),n.unit.one,n.unit.few,n.unit.many);return`Занадта малы: чакалася, што ${i.origin} павінна ${n.verb} ${r}${i.minimum.toString()} ${t}`}return`Занадта малы: чакалася, што ${i.origin} павінна быць ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Няправільны радок: павінен пачынацца з "${i.prefix}"`;if("ends_with"===i.format)return`Няправільны радок: павінен заканчвацца на "${i.suffix}"`;if("includes"===i.format)return`Няправільны радок: павінен змяшчаць "${i.includes}"`;if("regex"===i.format)return`Няправільны радок: павінен адпавядаць шаблону ${i.pattern}`;return`Няправільны ${r[i.format]??i.format}`;case"not_multiple_of":return`Няправільны лік: павінен быць кратным ${i.divisor}`;case"unrecognized_keys":return`Нераспазнаны ${i.keys.length>1?"ключы":"ключ"}: ${d(i.keys,", ")}`;case"invalid_key":return`Няправільны ключ у ${i.origin}`;case"invalid_union":default:return"Няправільны ўвод";case"invalid_element":return`Няправільнае значэнне ў ${i.origin}`}})}},"bg",0,function(){let t,r,n;return{localeError:(t={string:{unit:"символа",verb:"да съдържа"},file:{unit:"байта",verb:"да съдържа"},array:{unit:"елемента",verb:"да съдържа"},set:{unit:"елемента",verb:"да съдържа"},map:{unit:"елемента",verb:"да съдържа"}},r={regex:"вход",email:"имейл адрес",url:"URL",emoji:"емоджи",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO време",date:"ISO дата",time:"ISO време",duration:"ISO продължителност",ipv4:"IPv4 адрес",ipv6:"IPv6 адрес",mac:"MAC адрес",cidrv4:"IPv4 диапазон",cidrv6:"IPv6 диапазон",base64:"base64-кодиран низ",base64url:"base64url-кодиран низ",json_string:"JSON низ",e164:"E.164 номер",credit_card:"номер на кредитна карта",currency_code:"код на валута",iban:"IBAN",jwt:"JWT",template_literal:"вход"},n={nan:"NaN",number:"число",array:"масив"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Невалиден вход: очакван instanceof ${i.expected}, получен ${a}`;return`Невалиден вход: очакван ${t}, получен ${a}`}case"invalid_value":if(1===i.values.length)return`Невалиден вход: очакван ${G(i.values[0])}`;return`Невалидна опция: очаквано едно от ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`Твърде голямо: очаква се ${i.origin??"стойност"} да съдържа ${r}${i.maximum.toString()} ${n.unit??"елемента"}`;return`Твърде голямо: очаква се ${i.origin??"стойност"} да бъде ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`Твърде малко: очаква се ${i.origin} да съдържа ${r}${i.minimum.toString()} ${n.unit}`;return`Твърде малко: очаква се ${i.origin} да бъде ${r}${i.minimum.toString()}`}case"invalid_format":{if("starts_with"===i.format)return`Невалиден низ: трябва да започва с "${i.prefix}"`;if("ends_with"===i.format)return`Невалиден низ: трябва да завършва с "${i.suffix}"`;if("includes"===i.format)return`Невалиден низ: трябва да включва "${i.includes}"`;if("regex"===i.format)return`Невалиден низ: трябва да съвпада с ${i.pattern}`;let t="Невалиден";return"emoji"===i.format&&(t="Невалидно"),"datetime"===i.format&&(t="Невалидно"),"date"===i.format&&(t="Невалидна"),"time"===i.format&&(t="Невалидно"),"duration"===i.format&&(t="Невалидна"),`${t} ${r[i.format]??i.format}`}case"not_multiple_of":return`Невалидно число: трябва да бъде кратно на ${i.divisor}`;case"unrecognized_keys":return`Неразпознат${i.keys.length>1?"и":""} ключ${i.keys.length>1?"ове":""}: ${d(i.keys,", ")}`;case"invalid_key":return`Невалиден ключ в ${i.origin}`;case"invalid_union":default:return"Невалиден вход";case"invalid_element":return`Невалидна стойност в ${i.origin}`}})}},"bn",0,function(){let t,r,n;return{localeError:(t={string:{unit:"অক্ষর",verb:"থাকতে হবে"},file:{unit:"বাইট",verb:"থাকতে হবে"},array:{unit:"আইটেম",verb:"থাকতে হবে"},set:{unit:"আইটেম",verb:"থাকতে হবে"},map:{unit:"এন্ট্রি",verb:"থাকতে হবে"}},r={regex:"ইনপুট",email:"ইমেইল ঠিকানা",url:"URL",emoji:"ইমোজি",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO তারিখ ও সময়",date:"ISO তারিখ",time:"ISO সময়",duration:"ISO সময়কাল",ipv4:"IPv4 ঠিকানা",ipv6:"IPv6 ঠিকানা",mac:"MAC ঠিকানা",cidrv4:"IPv4 রেঞ্জ",cidrv6:"IPv6 রেঞ্জ",base64:"base64-এনকোডেড স্ট্রিং",base64url:"base64url-এনকোডেড স্ট্রিং",json_string:"JSON স্ট্রিং",e164:"E.164 নম্বর",credit_card:"ক্রেডিট কার্ড নম্বর",currency_code:"মুদ্রা কোড",iban:"IBAN",jwt:"JWT",template_literal:"ইনপুট"},n={nan:"NaN"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;return`অবৈধ ইনপুট: প্রত্যাশিত ${t}, প্রাপ্ত ${a}`}case"invalid_value":if(1===i.values.length)return`অবৈধ ইনপুট: প্রত্যাশিত ${G(i.values[0])}`;return`অবৈধ অপশন: ${d(i.values," | ")} এর মধ্যে একটি প্রত্যাশিত`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`অনেক বড়: ${i.origin??"মান"} ${r}${i.maximum.toString()} ${n.unit??"এলিমেন্ট"} হতে হবে`;return`অনেক বড়: ${i.origin??"মান"} ${r}${i.maximum.toString()} হতে হবে`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`অনেক ছোট: ${i.origin} ${r}${i.minimum.toString()} ${n.unit} হতে হবে`;return`অনেক ছোট: ${i.origin} ${r}${i.minimum.toString()} হতে হবে`}case"invalid_format":if("starts_with"===i.format)return`অবৈধ স্ট্রিং: "${i.prefix}" দিয়ে শুরু হতে হবে`;if("ends_with"===i.format)return`অবৈধ স্ট্রিং: "${i.suffix}" দিয়ে শেষ হতে হবে`;if("includes"===i.format)return`অবৈধ স্ট্রিং: "${i.includes}" অন্তর্ভুক্ত থাকতে হবে`;if("regex"===i.format)return`অবৈধ স্ট্রিং: ${i.pattern} প্যাটার্ন মিলতে হবে`;return`অবৈধ ${r[i.format]??i.format}`;case"not_multiple_of":return`অবৈধ নম্বর: ${i.divisor} এর গুণিতক হতে হবে`;case"unrecognized_keys":return`অচেনা কী${i.keys.length>1?"গুলো":""}: ${d(i.keys,", ")}`;case"invalid_key":return`${i.origin} এ অবৈধ কী`;case"invalid_union":if(i.options&&Array.isArray(i.options)&&i.options.length>0){let t=i.options.map(t=>`'${t}'`).join(" | ");return`অবৈধ ডিসক্রিমিনেটর মান। প্রত্যাশিত ${t}`}return"অবৈধ ইনপুট";case"invalid_element":return`${i.origin} এ অবৈধ মান`;default:return"অবৈধ ইনপুট"}})}},"ca",0,function(){let t,r,n;return{localeError:(t={string:{unit:"caràcters",verb:"contenir"},file:{unit:"bytes",verb:"contenir"},array:{unit:"elements",verb:"contenir"},set:{unit:"elements",verb:"contenir"},map:{unit:"elements",verb:"contenir"}},r={regex:"entrada",email:"adreça electrònica",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data i hora ISO",date:"data ISO",time:"hora ISO",duration:"durada ISO",ipv4:"adreça IPv4",ipv6:"adreça IPv6",mac:"adreça MAC",cidrv4:"rang IPv4",cidrv6:"rang IPv6",base64:"cadena codificada en base64",base64url:"cadena codificada en base64url",json_string:"cadena JSON",e164:"número E.164",credit_card:"número de targeta de crèdit",currency_code:"codi de moneda",iban:"IBAN",jwt:"JWT",template_literal:"entrada"},n={nan:"NaN"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Tipus inv\xe0lid: s'esperava instanceof ${i.expected}, s'ha rebut ${a}`;return`Tipus inv\xe0lid: s'esperava ${t}, s'ha rebut ${a}`}case"invalid_value":if(1===i.values.length)return`Valor inv\xe0lid: s'esperava ${G(i.values[0])}`;return`Opci\xf3 inv\xe0lida: s'esperava una de ${d(i.values," o ")}`;case"too_big":{let r=i.inclusive?"com a màxim":"menys de",n=t[i.origin]??null;if(n)return`Massa gran: s'esperava que ${i.origin??"el valor"} contingu\xe9s ${r} ${i.maximum.toString()} ${n.unit??"elements"}`;return`Massa gran: s'esperava que ${i.origin??"el valor"} fos ${r} ${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?"com a mínim":"més de",n=t[i.origin]??null;if(n)return`Massa petit: s'esperava que ${i.origin} contingu\xe9s ${r} ${i.minimum.toString()} ${n.unit}`;return`Massa petit: s'esperava que ${i.origin} fos ${r} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Format inv\xe0lid: ha de comen\xe7ar amb "${i.prefix}"`;if("ends_with"===i.format)return`Format inv\xe0lid: ha d'acabar amb "${i.suffix}"`;if("includes"===i.format)return`Format inv\xe0lid: ha d'incloure "${i.includes}"`;if("regex"===i.format)return`Format inv\xe0lid: ha de coincidir amb el patr\xf3 ${i.pattern}`;return`Format inv\xe0lid per a ${r[i.format]??i.format}`;case"not_multiple_of":return`N\xfamero inv\xe0lid: ha de ser m\xfaltiple de ${i.divisor}`;case"unrecognized_keys":return`Clau${i.keys.length>1?"s":""} no reconeguda${i.keys.length>1?"s":""}: ${d(i.keys,", ")}`;case"invalid_key":return`Clau inv\xe0lida a ${i.origin}`;case"invalid_union":default:return"Entrada invàlida";case"invalid_element":return`Element inv\xe0lid a ${i.origin}`}})}},"ckb",0,function(){let t,r,n;return{localeError:(t={string:{unit:"پیت",verb:"بێت"},file:{unit:"بایت",verb:"بێت"},array:{unit:"دانە",verb:"بێت"},set:{unit:"دانە",verb:"بێت"},map:{unit:"دانە",verb:"بێت"}},r={regex:"regex",email:"ئیمەیڵ",url:"بەستەر (URL)",emoji:"ئیمۆجی",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ڕێکەوت و کات",date:"ڕێکەوت",time:"کات",duration:"ماوە",ipv4:"ناونیشانی IPv4",ipv6:"ناونیشانی IPv6",mac:"ناونیشانی MAC",cidrv4:"مەودای IPv4",cidrv6:"مەودای IPv6",base64:"دەقی base64",base64url:"دەقی base64url",json_string:"دەقی JSON",e164:"ژمارەی E.164",credit_card:"ژمارەی کارتی کرێدیت",currency_code:"کۆدی دراو",iban:"IBAN",jwt:"JWT",template_literal:"تێکردە"},n={nan:"NaN",string:"نووسین",number:"ژمارە",boolean:"boolean",array:"array",object:"object",date:"ڕێکەوت",integer:"ژمارە",float:"ژمارە",null:"null",undefined:"undefined",function:"function",symbol:"symbol",unknown:"unknown",promise:"promise",void:"void",never:"never",map:"map",set:"set"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r,o=["ا","و","ۆ","وو","ە","ی","ێ"].some(t=>a.endsWith(t))?"یە":"ە",s=/^[a-zA-Z]+$/.test(a);if("null"===r||"undefined"===r)return"داواکراوە";return`چاوەڕوانکراوە ${t} بێت، بەڵام ${a}${s?"":o}`}case"invalid_value":if(1===i.values.length)return`بەهاکە نادرووستە: چاوەڕوانکراوە ${G(i.values[0])} بێت`;return`هەڵبژاردەی نادروست: چاوەڕوانکراوە یەکێک بێت لە ${d(i.values,"|")}`;case"too_big":{let r=t[i.origin]??null;if(r)return`پێویستە بە لایەنی زۆرەوە ${i.maximum.toString()} ${r.unit} ${r.verb}`;return`پێویستە بە لایەنی زۆرەوە ${i.maximum.toString()} بێت`}case"too_small":{let r=t[i.origin]??null;if(r)return`پێویستە بە لایەنی کەمەوە ${i.minimum.toString()} ${r.unit} ${r.verb}`;return`پێویستە بە لایەنی کەمەوە ${i.minimum.toString()} بێت`}case"invalid_format":if("starts_with"===i.format)return`دەقی نادروست: پێویستە دەستپێبکات بە "${i.prefix}"`;if("ends_with"===i.format)return`دەقی نادروست: پێویستە کۆتاییبێت بە "${i.suffix}"`;if("includes"===i.format)return`دەقی نادروست: پێویستە "${i.includes}" لەخۆبگرێت`;if("regex"===i.format)return`دەقی نادروست: پێویستە لەگەڵ پاتێرنی ${i.pattern} بگونجێت`;return`بەهای ${r[i.format]??i.format} نادروستە`;case"not_multiple_of":return`ژمارەی نادروست: دەبێت چەند هێندە بێت بۆ ${i.divisor}`;case"unrecognized_keys":return`کلیلی نەناسراو: ${d(i.keys,", ")}`;case"invalid_key":return`کلیلی نادروست لە ${i.origin}`;case"invalid_union":if(i.options&&Array.isArray(i.options)&&i.options.length>0){let t=i.options.map(t=>`'${t}'`).join(" | ");return`بەهای نەناسراو هەیە. بەهای چاوەڕوانکراو: ${t}`}return"یەکگرتنی نادروست";case"invalid_element":return`${i.origin} بەهاکە نادروستە`;default:return"تێکردەی نادروست"}})}},"cs",0,function(){let t,r,n;return{localeError:(t={string:{unit:"znaků",verb:"mít"},file:{unit:"bajtů",verb:"mít"},array:{unit:"prvků",verb:"mít"},set:{unit:"prvků",verb:"mít"},map:{unit:"prvků",verb:"mít"}},r={regex:"regulární výraz",email:"e-mailová adresa",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"datum a čas ve formátu ISO",date:"datum ve formátu ISO",time:"čas ve formátu ISO",duration:"doba trvání ISO",ipv4:"IPv4 adresa",ipv6:"IPv6 adresa",mac:"MAC adresa",cidrv4:"rozsah IPv4",cidrv6:"rozsah IPv6",base64:"řetězec zakódovaný ve formátu base64",base64url:"řetězec zakódovaný ve formátu base64url",json_string:"řetězec ve formátu JSON",e164:"číslo E.164",credit_card:"číslo kreditní karty",currency_code:"kód měny",iban:"IBAN",jwt:"JWT",template_literal:"vstup"},n={nan:"NaN",number:"číslo",string:"řetězec",function:"funkce",array:"pole"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Neplatn\xfd vstup: oček\xe1v\xe1no instanceof ${i.expected}, obdrženo ${a}`;return`Neplatn\xfd vstup: oček\xe1v\xe1no ${t}, obdrženo ${a}`}case"invalid_value":if(1===i.values.length)return`Neplatn\xfd vstup: oček\xe1v\xe1no ${G(i.values[0])}`;return`Neplatn\xe1 možnost: oček\xe1v\xe1na jedna z hodnot ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`Hodnota je př\xedliš velk\xe1: ${i.origin??"hodnota"} mus\xed m\xedt ${r}${i.maximum.toString()} ${n.unit??"prvků"}`;return`Hodnota je př\xedliš velk\xe1: ${i.origin??"hodnota"} mus\xed b\xfdt ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`Hodnota je př\xedliš mal\xe1: ${i.origin??"hodnota"} mus\xed m\xedt ${r}${i.minimum.toString()} ${n.unit??"prvků"}`;return`Hodnota je př\xedliš mal\xe1: ${i.origin??"hodnota"} mus\xed b\xfdt ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Neplatn\xfd řetězec: mus\xed zač\xednat na "${i.prefix}"`;if("ends_with"===i.format)return`Neplatn\xfd řetězec: mus\xed končit na "${i.suffix}"`;if("includes"===i.format)return`Neplatn\xfd řetězec: mus\xed obsahovat "${i.includes}"`;if("regex"===i.format)return`Neplatn\xfd řetězec: mus\xed odpov\xeddat vzoru ${i.pattern}`;return`Neplatn\xfd form\xe1t ${r[i.format]??i.format}`;case"not_multiple_of":return`Neplatn\xe9 č\xedslo: mus\xed b\xfdt n\xe1sobkem ${i.divisor}`;case"unrecognized_keys":return`Nezn\xe1m\xe9 kl\xedče: ${d(i.keys,", ")}`;case"invalid_key":return`Neplatn\xfd kl\xedč v ${i.origin}`;case"invalid_union":default:return"Neplatný vstup";case"invalid_element":return`Neplatn\xe1 hodnota v ${i.origin}`}})}},"da",0,function(){let t,r,n;return{localeError:(t={string:{unit:"tegn",verb:"havde"},file:{unit:"bytes",verb:"havde"},array:{unit:"elementer",verb:"indeholdt"},set:{unit:"elementer",verb:"indeholdt"},map:{unit:"elementer",verb:"indeholdt"}},r={regex:"input",email:"e-mailadresse",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO dato- og klokkeslæt",date:"ISO-dato",time:"ISO-klokkeslæt",duration:"ISO-varighed",ipv4:"IPv4-adresse",ipv6:"IPv6-adresse",mac:"MAC-adresse",cidrv4:"IPv4-spektrum",cidrv6:"IPv6-spektrum",base64:"base64-kodet streng",base64url:"base64url-kodet streng",json_string:"JSON-streng",e164:"E.164-nummer",credit_card:"kreditkortnummer",currency_code:"valutakode",iban:"IBAN",jwt:"JWT",template_literal:"input"},n={nan:"NaN",string:"streng",number:"tal",boolean:"boolean",array:"liste",object:"objekt",set:"sæt",file:"fil"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Ugyldigt input: forventede instanceof ${i.expected}, fik ${a}`;return`Ugyldigt input: forventede ${t}, fik ${a}`}case"invalid_value":if(1===i.values.length)return`Ugyldig v\xe6rdi: forventede ${G(i.values[0])}`;return`Ugyldigt valg: forventede en af f\xf8lgende ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",a=t[i.origin]??null,o=n[i.origin]??i.origin;if(a)return`For stor: forventede ${o??"value"} ${a.verb} ${r} ${i.maximum.toString()} ${a.unit??"elementer"}`;return`For stor: forventede ${o??"value"} havde ${r} ${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",a=t[i.origin]??null,o=n[i.origin]??i.origin;if(a)return`For lille: forventede ${o} ${a.verb} ${r} ${i.minimum.toString()} ${a.unit}`;return`For lille: forventede ${o} havde ${r} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ugyldig streng: skal starte med "${i.prefix}"`;if("ends_with"===i.format)return`Ugyldig streng: skal ende med "${i.suffix}"`;if("includes"===i.format)return`Ugyldig streng: skal indeholde "${i.includes}"`;if("regex"===i.format)return`Ugyldig streng: skal matche m\xf8nsteret ${i.pattern}`;return`Ugyldig ${r[i.format]??i.format}`;case"not_multiple_of":return`Ugyldigt tal: skal v\xe6re deleligt med ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Ukendte nøgler":"Ukendt nøgle"}: ${d(i.keys,", ")}`;case"invalid_key":return`Ugyldig n\xf8gle i ${i.origin}`;case"invalid_union":return"Ugyldigt input: matcher ingen af de tilladte typer";case"invalid_element":return`Ugyldig v\xe6rdi i ${i.origin}`;default:return"Ugyldigt input"}})}},"de",0,function(){let t,r,n;return{localeError:(t={string:{unit:"Zeichen",verb:"zu haben"},file:{unit:"Bytes",verb:"zu haben"},array:{unit:"Elemente",verb:"zu haben"},set:{unit:"Elemente",verb:"zu haben"},map:{unit:"Elemente",verb:"zu haben"}},r={regex:"Eingabe",email:"E-Mail-Adresse",url:"URL",emoji:"Emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-Datum und -Uhrzeit",date:"ISO-Datum",time:"ISO-Uhrzeit",duration:"ISO-Dauer",ipv4:"IPv4-Adresse",ipv6:"IPv6-Adresse",mac:"MAC-Adresse",cidrv4:"IPv4-Bereich",cidrv6:"IPv6-Bereich",base64:"Base64-codierter String",base64url:"Base64-URL-codierter String",json_string:"JSON-String",e164:"E.164-Nummer",credit_card:"Kreditkartennummer",currency_code:"Währungscode",iban:"IBAN",jwt:"JWT",template_literal:"Eingabe"},n={nan:"NaN",number:"Zahl",array:"Array"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Ung\xfcltige Eingabe: erwartet instanceof ${i.expected}, erhalten ${a}`;return`Ung\xfcltige Eingabe: erwartet ${t}, erhalten ${a}`}case"invalid_value":if(1===i.values.length)return`Ung\xfcltige Eingabe: erwartet ${G(i.values[0])}`;return`Ung\xfcltige Option: erwartet eine von ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`Zu gro\xdf: erwartet, dass ${i.origin??"Wert"} ${r}${i.maximum.toString()} ${n.unit??"Elemente"} hat`;return`Zu gro\xdf: erwartet, dass ${i.origin??"Wert"} ${r}${i.maximum.toString()} ist`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`Zu klein: erwartet, dass ${i.origin} ${r}${i.minimum.toString()} ${n.unit} hat`;return`Zu klein: erwartet, dass ${i.origin} ${r}${i.minimum.toString()} ist`}case"invalid_format":if("starts_with"===i.format)return`Ung\xfcltiger String: muss mit "${i.prefix}" beginnen`;if("ends_with"===i.format)return`Ung\xfcltiger String: muss mit "${i.suffix}" enden`;if("includes"===i.format)return`Ung\xfcltiger String: muss "${i.includes}" enthalten`;if("regex"===i.format)return`Ung\xfcltiger String: muss dem Muster ${i.pattern} entsprechen`;return`Ung\xfcltig: ${r[i.format]??i.format}`;case"not_multiple_of":return`Ung\xfcltige Zahl: muss ein Vielfaches von ${i.divisor} sein`;case"unrecognized_keys":return`${i.keys.length>1?"Unbekannte Schlüssel":"Unbekannter Schlüssel"}: ${d(i.keys,", ")}`;case"invalid_key":return`Ung\xfcltiger Schl\xfcssel in ${i.origin}`;case"invalid_union":default:return"Ungültige Eingabe";case"invalid_element":return`Ung\xfcltiger Wert in ${i.origin}`}})}},"el",0,function(){let t,r,n;return{localeError:(t={string:{unit:"χαρακτήρες",verb:"να έχει"},file:{unit:"bytes",verb:"να έχει"},array:{unit:"στοιχεία",verb:"να έχει"},set:{unit:"στοιχεία",verb:"να έχει"},map:{unit:"καταχωρήσεις",verb:"να έχει"}},r={regex:"είσοδος",email:"διεύθυνση email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO ημερομηνία και ώρα",date:"ISO ημερομηνία",time:"ISO ώρα",duration:"ISO διάρκεια",ipv4:"διεύθυνση IPv4",ipv6:"διεύθυνση IPv6",mac:"διεύθυνση MAC",cidrv4:"εύρος IPv4",cidrv6:"εύρος IPv6",base64:"συμβολοσειρά κωδικοποιημένη σε base64",base64url:"συμβολοσειρά κωδικοποιημένη σε base64url",json_string:"συμβολοσειρά JSON",e164:"αριθμός E.164",credit_card:"αριθμός πιστωτικής κάρτας",currency_code:"κωδικός νομίσματος",iban:"IBAN",jwt:"JWT",template_literal:"είσοδος"},n={nan:"NaN"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if("string"==typeof i.expected&&/^[A-Z]/.test(i.expected))return`Μη έγκυρη είσοδος: αναμενόταν instanceof ${i.expected}, λήφθηκε ${a}`;return`Μη έγκυρη είσοδος: αναμενόταν ${t}, λήφθηκε ${a}`}case"invalid_value":if(1===i.values.length)return`Μη έγκυρη είσοδος: αναμενόταν ${G(i.values[0])}`;return`Μη έγκυρη επιλογή: αναμενόταν ένα από ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`Πολύ μεγάλο: αναμενόταν ${i.origin??"τιμή"} να έχει ${r}${i.maximum.toString()} ${n.unit??"στοιχεία"}`;return`Πολύ μεγάλο: αναμενόταν ${i.origin??"τιμή"} να είναι ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`Πολύ μικρό: αναμενόταν ${i.origin} να έχει ${r}${i.minimum.toString()} ${n.unit}`;return`Πολύ μικρό: αναμενόταν ${i.origin} να είναι ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Μη έγκυρη συμβολοσειρά: πρέπει να ξεκινά με "${i.prefix}"`;if("ends_with"===i.format)return`Μη έγκυρη συμβολοσειρά: πρέπει να τελειώνει με "${i.suffix}"`;if("includes"===i.format)return`Μη έγκυρη συμβολοσειρά: πρέπει να περιέχει "${i.includes}"`;if("regex"===i.format)return`Μη έγκυρη συμβολοσειρά: πρέπει να ταιριάζει με το μοτίβο ${i.pattern}`;return`Μη έγκυρο: ${r[i.format]??i.format}`;case"not_multiple_of":return`Μη έγκυρος αριθμός: πρέπει να είναι πολλαπλάσιο του ${i.divisor}`;case"unrecognized_keys":return`Άγνωστ${i.keys.length>1?"α":"ο"} κλειδ${i.keys.length>1?"ιά":"ί"}: ${d(i.keys,", ")}`;case"invalid_key":return`Μη έγκυρο κλειδί στο ${i.origin}`;case"invalid_union":default:return"Μη έγκυρη είσοδος";case"invalid_element":return`Μη έγκυρη τιμή στο ${i.origin}`}})}},"en",0,i5,"eo",0,function(){let t,r,n;return{localeError:(t={string:{unit:"karaktrojn",verb:"havi"},file:{unit:"bajtojn",verb:"havi"},array:{unit:"elementojn",verb:"havi"},set:{unit:"elementojn",verb:"havi"},map:{unit:"elementojn",verb:"havi"}},r={regex:"enigo",email:"retadreso",url:"URL",emoji:"emoĝio",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-datotempo",date:"ISO-dato",time:"ISO-tempo",duration:"ISO-daŭro",ipv4:"IPv4-adreso",ipv6:"IPv6-adreso",mac:"MAC-adreso",cidrv4:"IPv4-rango",cidrv6:"IPv6-rango",base64:"64-ume kodita karaktraro",base64url:"URL-64-ume kodita karaktraro",json_string:"JSON-karaktraro",e164:"E.164-nombro",credit_card:"kreditkarta numero",currency_code:"valuta kodo",iban:"IBAN",jwt:"JWT",template_literal:"enigo"},n={nan:"NaN",number:"nombro",array:"tabelo",null:"senvalora"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Nevalida enigo: atendiĝis instanceof ${i.expected}, riceviĝis ${a}`;return`Nevalida enigo: atendiĝis ${t}, riceviĝis ${a}`}case"invalid_value":if(1===i.values.length)return`Nevalida enigo: atendiĝis ${G(i.values[0])}`;return`Nevalida opcio: atendiĝis unu el ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`Tro granda: atendiĝis ke ${i.origin??"valoro"} havu ${r}${i.maximum.toString()} ${n.unit??"elementojn"}`;return`Tro granda: atendiĝis ke ${i.origin??"valoro"} havu ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`Tro malgranda: atendiĝis ke ${i.origin} havu ${r}${i.minimum.toString()} ${n.unit}`;return`Tro malgranda: atendiĝis ke ${i.origin} estu ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Nevalida karaktraro: devas komenciĝi per "${i.prefix}"`;if("ends_with"===i.format)return`Nevalida karaktraro: devas finiĝi per "${i.suffix}"`;if("includes"===i.format)return`Nevalida karaktraro: devas inkluzivi "${i.includes}"`;if("regex"===i.format)return`Nevalida karaktraro: devas kongrui kun la modelo ${i.pattern}`;return`Nevalida ${r[i.format]??i.format}`;case"not_multiple_of":return`Nevalida nombro: devas esti oblo de ${i.divisor}`;case"unrecognized_keys":return`Nekonata${i.keys.length>1?"j":""} ŝlosilo${i.keys.length>1?"j":""}: ${d(i.keys,", ")}`;case"invalid_key":return`Nevalida ŝlosilo en ${i.origin}`;case"invalid_union":default:return"Nevalida enigo";case"invalid_element":return`Nevalida valoro en ${i.origin}`}})}},"es",0,function(){let t,r,n;return{localeError:(t={string:{unit:"caracteres",verb:"tener"},file:{unit:"bytes",verb:"tener"},array:{unit:"elementos",verb:"tener"},set:{unit:"elementos",verb:"tener"}},r={regex:"entrada",email:"dirección de correo electrónico",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"fecha y hora ISO",date:"fecha ISO",time:"hora ISO",duration:"duración ISO",ipv4:"dirección IPv4",ipv6:"dirección IPv6",mac:"dirección MAC",cidrv4:"rango IPv4",cidrv6:"rango IPv6",base64:"cadena codificada en base64",base64url:"URL codificada en base64",json_string:"cadena JSON",e164:"número E.164",credit_card:"número de tarjeta de crédito",currency_code:"código de moneda",iban:"IBAN",jwt:"JWT",template_literal:"entrada"},n={nan:"NaN",string:"texto",number:"número",boolean:"booleano",array:"arreglo",object:"objeto",set:"conjunto",file:"archivo",date:"fecha",bigint:"número grande",symbol:"símbolo",undefined:"indefinido",null:"nulo",function:"función",map:"mapa",record:"registro",tuple:"tupla",enum:"enumeración",union:"unión",literal:"literal",promise:"promesa",void:"vacío",never:"nunca",unknown:"desconocido",any:"cualquiera"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Entrada inv\xe1lida: se esperaba instanceof ${i.expected}, recibido ${a}`;return`Entrada inv\xe1lida: se esperaba ${t}, recibido ${a}`}case"invalid_value":if(1===i.values.length)return`Entrada inv\xe1lida: se esperaba ${G(i.values[0])}`;return`Opci\xf3n inv\xe1lida: se esperaba una de ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",a=t[i.origin]??null,o=n[i.origin]??i.origin;if(a)return`Demasiado grande: se esperaba que ${o??"valor"} tuviera ${r}${i.maximum.toString()} ${a.unit??"elementos"}`;return`Demasiado grande: se esperaba que ${o??"valor"} fuera ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",a=t[i.origin]??null,o=n[i.origin]??i.origin;if(a)return`Demasiado peque\xf1o: se esperaba que ${o} tuviera ${r}${i.minimum.toString()} ${a.unit}`;return`Demasiado peque\xf1o: se esperaba que ${o} fuera ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Cadena inv\xe1lida: debe comenzar con "${i.prefix}"`;if("ends_with"===i.format)return`Cadena inv\xe1lida: debe terminar en "${i.suffix}"`;if("includes"===i.format)return`Cadena inv\xe1lida: debe incluir "${i.includes}"`;if("regex"===i.format)return`Cadena inv\xe1lida: debe coincidir con el patr\xf3n ${i.pattern}`;return`Inv\xe1lido ${r[i.format]??i.format}`;case"not_multiple_of":return`N\xfamero inv\xe1lido: debe ser m\xfaltiplo de ${i.divisor}`;case"unrecognized_keys":return`Llave${i.keys.length>1?"s":""} desconocida${i.keys.length>1?"s":""}: ${d(i.keys,", ")}`;case"invalid_key":return`Llave inv\xe1lida en ${n[i.origin]??i.origin}`;case"invalid_union":default:return"Entrada inválida";case"invalid_element":return`Valor inv\xe1lido en ${n[i.origin]??i.origin}`}})}},"fa",0,function(){let t,r,n;return{localeError:(t={string:{unit:"کاراکتر",verb:"داشته باشد"},file:{unit:"بایت",verb:"داشته باشد"},array:{unit:"آیتم",verb:"داشته باشد"},set:{unit:"آیتم",verb:"داشته باشد"},map:{unit:"آیتم",verb:"داشته باشد"}},r={regex:"ورودی",email:"آدرس ایمیل",url:"URL",emoji:"ایموجی",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"تاریخ و زمان ایزو",date:"تاریخ ایزو",time:"زمان ایزو",duration:"مدت زمان ایزو",ipv4:"IPv4 آدرس",ipv6:"IPv6 آدرس",mac:"MAC آدرس",cidrv4:"IPv4 دامنه",cidrv6:"IPv6 دامنه",base64:"base64-encoded رشته",base64url:"base64url-encoded رشته",json_string:"JSON رشته",e164:"E.164 عدد",credit_card:"شماره کارت اعتباری",currency_code:"کد ارز",iban:"IBAN",jwt:"JWT",template_literal:"ورودی"},n={nan:"NaN",number:"عدد",array:"آرایه"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`ورودی نامعتبر: می‌بایست instanceof ${i.expected} می‌بود، ${a} دریافت شد`;return`ورودی نامعتبر: می‌بایست ${t} می‌بود، ${a} دریافت شد`}case"invalid_value":if(1===i.values.length)return`ورودی نامعتبر: می‌بایست ${G(i.values[0])} می‌بود`;return`گزینه نامعتبر: می‌بایست یکی از ${d(i.values,"|")} می‌بود`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`خیلی بزرگ: ${i.origin??"مقدار"} باید ${r}${i.maximum.toString()} ${n.unit??"عنصر"} باشد`;return`خیلی بزرگ: ${i.origin??"مقدار"} باید ${r}${i.maximum.toString()} باشد`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`خیلی کوچک: ${i.origin} باید ${r}${i.minimum.toString()} ${n.unit} باشد`;return`خیلی کوچک: ${i.origin} باید ${r}${i.minimum.toString()} باشد`}case"invalid_format":if("starts_with"===i.format)return`رشته نامعتبر: باید با "${i.prefix}" شروع شود`;if("ends_with"===i.format)return`رشته نامعتبر: باید با "${i.suffix}" تمام شود`;if("includes"===i.format)return`رشته نامعتبر: باید شامل "${i.includes}" باشد`;if("regex"===i.format)return`رشته نامعتبر: باید با الگوی ${i.pattern} مطابقت داشته باشد`;return`${r[i.format]??i.format} نامعتبر`;case"not_multiple_of":return`عدد نامعتبر: باید مضرب ${i.divisor} باشد`;case"unrecognized_keys":return`کلید${i.keys.length>1?"های":""} ناشناس: ${d(i.keys,", ")}`;case"invalid_key":return`کلید ناشناس در ${i.origin}`;case"invalid_union":default:return"ورودی نامعتبر";case"invalid_element":return`مقدار نامعتبر در ${i.origin}`}})}},"fi",0,function(){let t,r,n;return{localeError:(t={string:{unit:"merkkiä",subject:"merkkijonon"},file:{unit:"tavua",subject:"tiedoston"},array:{unit:"alkiota",subject:"listan"},set:{unit:"alkiota",subject:"joukon"},map:{unit:"alkiota",subject:"kuvauksen"},number:{unit:"",subject:"luvun"},bigint:{unit:"",subject:"suuren kokonaisluvun"},int:{unit:"",subject:"kokonaisluvun"},date:{unit:"",subject:"päivämäärän"}},r={regex:"säännöllinen lauseke",email:"sähköpostiosoite",url:"URL-osoite",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-aikaleima",date:"ISO-päivämäärä",time:"ISO-aika",duration:"ISO-kesto",ipv4:"IPv4-osoite",ipv6:"IPv6-osoite",mac:"MAC-osoite",cidrv4:"IPv4-alue",cidrv6:"IPv6-alue",base64:"base64-koodattu merkkijono",base64url:"base64url-koodattu merkkijono",json_string:"JSON-merkkijono",e164:"E.164-luku",credit_card:"luottokortin numero",currency_code:"valuuttakoodi",iban:"IBAN",jwt:"JWT",template_literal:"templaattimerkkijono"},n={nan:"NaN"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Virheellinen tyyppi: odotettiin instanceof ${i.expected}, oli ${a}`;return`Virheellinen tyyppi: odotettiin ${t}, oli ${a}`}case"invalid_value":if(1===i.values.length)return`Virheellinen sy\xf6te: t\xe4ytyy olla ${G(i.values[0])}`;return`Virheellinen valinta: t\xe4ytyy olla yksi seuraavista: ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`Liian suuri: ${n.subject} t\xe4ytyy olla ${r}${i.maximum.toString()} ${n.unit}`.trim();return`Liian suuri: arvon t\xe4ytyy olla ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`Liian pieni: ${n.subject} t\xe4ytyy olla ${r}${i.minimum.toString()} ${n.unit}`.trim();return`Liian pieni: arvon t\xe4ytyy olla ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy alkaa "${i.prefix}"`;if("ends_with"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy loppua "${i.suffix}"`;if("includes"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy sis\xe4lt\xe4\xe4 "${i.includes}"`;if("regex"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy vastata s\xe4\xe4nn\xf6llist\xe4 lauseketta ${i.pattern}`;return`Virheellinen ${r[i.format]??i.format}`;case"not_multiple_of":return`Virheellinen luku: t\xe4ytyy olla luvun ${i.divisor} monikerta`;case"unrecognized_keys":return`${i.keys.length>1?"Tuntemattomat avaimet":"Tuntematon avain"}: ${d(i.keys,", ")}`;case"invalid_key":return"Virheellinen avain tietueessa";case"invalid_union":return"Virheellinen unioni";case"invalid_element":return"Virheellinen arvo joukossa";default:return"Virheellinen syöte"}})}},"fr",0,function(){let t,r,n;return{localeError:(t={string:{unit:"caractères",verb:"avoir"},file:{unit:"octets",verb:"avoir"},array:{unit:"éléments",verb:"avoir"},set:{unit:"éléments",verb:"avoir"}},r={regex:"expression régulière",email:"adresse e-mail",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"date et heure ISO",date:"date ISO",time:"heure ISO",duration:"durée ISO",ipv4:"adresse IPv4",ipv6:"adresse IPv6",mac:"adresse MAC",cidrv4:"plage IPv4",cidrv6:"plage IPv6",base64:"chaîne de caractères encodée en base64",base64url:"chaîne de caractères encodée en base64url",json_string:"chaîne de caractères JSON",e164:"numéro au format E.164",credit_card:"numéro de carte de crédit",currency_code:"code de devise",iban:"IBAN",jwt:"JWT",template_literal:"entrée"},n={string:"chaîne de caractères",number:"nombre",int:"entier",boolean:"booléen",bigint:"grand 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r=i.inclusive?">=":">",a=t[i.origin]??null;if(a)return`Trop petit : ${n[i.origin]??"valeur"} doit ${a.verb} ${r}${i.minimum.toString()} ${a.unit}`;return`Trop petit : ${n[i.origin]??"valeur"} doit \xeatre ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Cha\xeene de caract\xe8res invalide : doit commencer par "${i.prefix}"`;if("ends_with"===i.format)return`Cha\xeene de caract\xe8res invalide : doit se terminer par "${i.suffix}"`;if("includes"===i.format)return`Cha\xeene de caract\xe8res invalide : doit inclure "${i.includes}"`;if("regex"===i.format)return`Cha\xeene de caract\xe8res invalide : doit correspondre au motif ${i.pattern}`;return`${r[i.format]??i.format} invalide`;case"not_multiple_of":return`Nombre invalide : doit \xeatre un multiple de ${i.divisor}`;case"unrecognized_keys":return`Cl\xe9${i.keys.length>1?"s":""} non reconnue${i.keys.length>1?"s":""} : ${d(i.keys,", ")}`;case"invalid_key":return`Cl\xe9 invalide dans ${i.origin}`;case"invalid_union":default:return"Entrée invalide";case"invalid_element":return`Valeur invalide dans ${i.origin}`}})}},"frCA",0,function(){let t,r,n;return{localeError:(t={string:{unit:"caractères",verb:"avoir"},file:{unit:"octets",verb:"avoir"},array:{unit:"éléments",verb:"avoir"},set:{unit:"éléments",verb:"avoir"},map:{unit:"éléments",verb:"avoir"}},r={regex:"entrée",email:"adresse courriel",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"date-heure ISO",date:"date ISO",time:"heure ISO",duration:"durée ISO",ipv4:"adresse IPv4",ipv6:"adresse IPv6",mac:"adresse MAC",cidrv4:"plage IPv4",cidrv6:"plage IPv6",base64:"chaîne encodée en base64",base64url:"chaîne encodée en base64url",json_string:"chaîne JSON",e164:"numéro E.164",credit_card:"numéro de carte de crédit",currency_code:"code de 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${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Cha\xeene invalide : doit commencer par "${i.prefix}"`;if("ends_with"===i.format)return`Cha\xeene invalide : doit se terminer par "${i.suffix}"`;if("includes"===i.format)return`Cha\xeene invalide : doit inclure "${i.includes}"`;if("regex"===i.format)return`Cha\xeene invalide : doit correspondre au motif ${i.pattern}`;return`${r[i.format]??i.format} invalide`;case"not_multiple_of":return`Nombre invalide : doit \xeatre un multiple de ${i.divisor}`;case"unrecognized_keys":return`Cl\xe9${i.keys.length>1?"s":""} non reconnue${i.keys.length>1?"s":""} : ${d(i.keys,", ")}`;case"invalid_key":return`Cl\xe9 invalide dans ${i.origin}`;case"invalid_union":default:return"Entrée invalide";case"invalid_element":return`Valeur invalide dans ${i.origin}`}})}},"gu",0,function(){let t,r,n;return{localeError:(t={string:{unit:"અક્ષર",verb:"હોવા જોઈએ"},file:{unit:"બાયટ",verb:"હોવા જોઈએ"},array:{unit:"આઇટમ",verb:"હોવા 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અપેક્ષિત`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`ખૂબ મોટું: ${i.origin??"મૂલ્ય"} ${r}${i.maximum.toString()} ${n.unit??"એલિમેન્ટ"} હોવા જોઈએ`;return`ખૂબ મોટું: ${i.origin??"મૂલ્ય"} ${r}${i.maximum.toString()} હોવું જોઈએ`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`ખૂબ નાનું: ${i.origin} ${r}${i.minimum.toString()} ${n.unit} હોવા જોઈએ`;return`ખૂબ નાનું: ${i.origin} ${r}${i.minimum.toString()} હોવું જોઈએ`}case"invalid_format":if("starts_with"===i.format)return`અમાન્ય સ્ટ્રિંગ: "${i.prefix}" થી શરૂ થવું જોઈએ`;if("ends_with"===i.format)return`અમાન્ય સ્ટ્રિંગ: "${i.suffix}" પર સમાપ્ત થવું જોઈએ`;if("includes"===i.format)return`અમાન્ય સ્ટ્રિંગ: "${i.includes}" શામેલ હોવું જોઈએ`;if("regex"===i.format)return`અમાન્ય સ્ટ્રિંગ: પેટર્ન ${i.pattern} સાથે મેળ ખાવું જોઈએ`;return`અમાન્ય ${r[i.format]??i.format}`;case"not_multiple_of":return`અમાન્ય નંબર: ${i.divisor} નો ગુણાંક હોવો જોઈએ`;case"unrecognized_keys":return`ઓળખી શકાતા નહીં તે કી${i.keys.length>1?"ઓ":""}: ${d(i.keys,", ")}`;case"invalid_key":return`${i.origin} માં અમાન્ય કી`;case"invalid_union":if(i.options&&Array.isArray(i.options)&&i.options.length>0){let t=i.options.map(t=>`'${t}'`).join(" | ");return`અમાન્ય ડિસ્ક્રિમિનેટર મૂલ્ય. અપેક્ષિત ${t}`}return"અમાન્ય ઇનપુટ";case"invalid_element":return`${i.origin} માં અમાન્ય મૂલ્ય`;default:return"અમાન્ય ઇનપુટ"}})}},"he",0,function(){let t,r,n,i,a,o,s,l,u;return{localeError:(t={string:{label:"מחרוזת",gender:"f"},number:{label:"מספר",gender:"m"},boolean:{label:"ערך בוליאני",gender:"m"},bigint:{label:"BigInt",gender:"m"},date:{label:"תאריך",gender:"m"},array:{label:"מערך",gender:"m"},object:{label:"אובייקט",gender:"m"},null:{label:"ערך ריק (null)",gender:"m"},undefined:{label:"ערך לא מוגדר (undefined)",gender:"m"},symbol:{label:"סימבול (Symbol)",gender:"m"},function:{label:"פונקציה",gender:"f"},map:{label:"מפה (Map)",gender:"f"},set:{label:"קבוצה (Set)",gender:"f"},file:{label:"קובץ",gender:"m"},promise:{label:"Promise",gender:"m"},NaN:{label:"NaN",gender:"m"},unknown:{label:"ערך לא ידוע",gender:"m"},value:{label:"ערך",gender:"m"}},r={string:{unit:"תווים",shortLabel:"קצר",longLabel:"ארוך"},file:{unit:"בייטים",shortLabel:"קטן",longLabel:"גדול"},array:{unit:"פריטים",shortLabel:"קטן",longLabel:"גדול"},set:{unit:"פריטים",shortLabel:"קטן",longLabel:"גדול"},number:{unit:"",shortLabel:"קטן",longLabel:"גדול"}},n=r=>r?t[r]:void 0,i=r=>{let i=n(r);return i?i.label:r??t.unknown.label},a=t=>`ה${i(t)}`,o=t=>{let r=n(t);return"f"===(r?.gender??"m")?"צריכה להיות":"צריך להיות"},s=t=>t?r[t]??null:null,l={regex:{label:"קלט",gender:"m"},email:{label:"כתובת אימייל",gender:"f"},url:{label:"כתובת רשת",gender:"f"},emoji:{label:"אימוג'י",gender:"m"},uuid:{label:"UUID",gender:"m"},uuidv4:{label:"UUIDv4",gender:"m"},uuidv6:{label:"UUIDv6",gender:"m"},nanoid:{label:"nanoid",gender:"m"},guid:{label:"GUID",gender:"m"},cuid:{label:"cuid",gender:"m"},cuid2:{label:"cuid2",gender:"m"},ulid:{label:"ULID",gender:"m"},xid:{label:"XID",gender:"m"},ksuid:{label:"KSUID",gender:"m"},datetime:{label:"תאריך וזמן ISO",gender:"m"},date:{label:"תאריך ISO",gender:"m"},time:{label:"זמן ISO",gender:"m"},duration:{label:"משך זמן ISO",gender:"m"},ipv4:{label:"כתובת IPv4",gender:"f"},ipv6:{label:"כתובת IPv6",gender:"f"},mac:{label:"כתובת MAC",gender:"f"},cidrv4:{label:"טווח IPv4",gender:"m"},cidrv6:{label:"טווח IPv6",gender:"m"},base64:{label:"מחרוזת בבסיס 64",gender:"f"},base64url:{label:"מחרוזת בבסיס 64 לכתובות רשת",gender:"f"},json_string:{label:"מחרוזת JSON",gender:"f"},e164:{label:"מספר E.164",gender:"m"},credit_card:{label:"מספר כרטיס אשראי",gender:"m"},currency_code:{label:"קוד מטבע",gender:"m"},iban:{label:"IBAN",gender:"m"},jwt:{label:"JWT",gender:"m"},template_literal:{label:"קלט",gender:"m"},ends_with:{label:"קלט",gender:"m"},includes:{label:"קלט",gender:"m"},lowercase:{label:"קלט",gender:"m"},starts_with:{label:"קלט",gender:"m"},uppercase:{label:"קלט",gender:"m"}},u={nan:"NaN"},r=>{switch(r.code){case"invalid_type":{let n=r.expected,a=u[n??""]??i(n),o=eg(r.input),s=u[o]??t[o]?.label??o;if(/^[A-Z]/.test(r.expected))return`קלט לא תקין: צריך להיות instanceof ${r.expected}, התקבל ${s}`;return`קלט לא תקין: צריך להיות ${a}, התקבל ${s}`}case"invalid_value":{if(1===r.values.length)return`ערך לא תקין: הערך חייב להיות ${G(r.values[0])}`;let t=r.values.map(t=>G(t));if(2===r.values.length)return`ערך לא תקין: האפשרויות המתאימות הן ${t[0]} או ${t[1]}`;let n=t[t.length-1],i=t.slice(0,-1).join(", ");return`ערך לא תקין: האפשרויות המתאימות הן ${i} או ${n}`}case"too_big":{let t=s(r.origin),n=a(r.origin??"value");if("string"===r.origin)return`${t?.longLabel??"ארוך"} מדי: ${n} צריכה להכיל ${r.maximum.toString()} ${t?.unit??""} ${r.inclusive?"או פחות":"לכל היותר"}`.trim();if("number"===r.origin){let t=r.inclusive?`קטן או שווה ל-${r.maximum}`:`קטן מ-${r.maximum}`;return`גדול מדי: ${n} צריך להיות ${t}`}if("array"===r.origin||"set"===r.origin){let i="set"===r.origin?"צריכה":"צריך",a=r.inclusive?`${r.maximum} ${t?.unit??""} או פחות`:`פחות מ-${r.maximum} ${t?.unit??""}`;return`גדול מדי: ${n} ${i} להכיל ${a}`.trim()}let i=r.inclusive?"<=":"<",l=o(r.origin??"value");if(t?.unit)return`${t.longLabel} מדי: ${n} ${l} ${i}${r.maximum.toString()} ${t.unit}`;return`${t?.longLabel??"גדול"} מדי: ${n} ${l} ${i}${r.maximum.toString()}`}case"too_small":{let t=s(r.origin),n=a(r.origin??"value");if("string"===r.origin)return`${t?.shortLabel??"קצר"} מדי: ${n} צריכה להכיל ${r.minimum.toString()} ${t?.unit??""} ${r.inclusive?"או יותר":"לפחות"}`.trim();if("number"===r.origin){let t=r.inclusive?`גדול או שווה ל-${r.minimum}`:`גדול מ-${r.minimum}`;return`קטן מדי: ${n} צריך להיות ${t}`}if("array"===r.origin||"set"===r.origin){let i="set"===r.origin?"צריכה":"צריך";if(1===r.minimum&&r.inclusive){let t=(r.origin,"לפחות פריט אחד");return`קטן מדי: ${n} ${i} להכיל ${t}`}let a=r.inclusive?`${r.minimum} ${t?.unit??""} או יותר`:`יותר מ-${r.minimum} ${t?.unit??""}`;return`קטן מדי: ${n} ${i} להכיל ${a}`.trim()}let i=r.inclusive?">=":">",l=o(r.origin??"value");if(t?.unit)return`${t.shortLabel} מדי: ${n} ${l} ${i}${r.minimum.toString()} ${t.unit}`;return`${t?.shortLabel??"קטן"} מדי: ${n} ${l} ${i}${r.minimum.toString()}`}case"invalid_format":{if("starts_with"===r.format)return`המחרוזת חייבת להתחיל ב "${r.prefix}"`;if("ends_with"===r.format)return`המחרוזת חייבת להסתיים ב "${r.suffix}"`;if("includes"===r.format)return`המחרוזת חייבת לכלול "${r.includes}"`;if("regex"===r.format)return`המחרוזת חייבת להתאים לתבנית ${r.pattern}`;let t=l[r.format],n=t?.label??r.format,i=t?.gender??"m";return`${n} לא ${"f"===i?"תקינה":"תקין"}`}case"not_multiple_of":return`מספר לא תקין: חייב להיות מכפלה של ${r.divisor}`;case"unrecognized_keys":return`מפתח${r.keys.length>1?"ות":""} לא מזוה${r.keys.length>1?"ים":"ה"}: ${d(r.keys,", ")}`;case"invalid_key":return"שדה לא תקין באובייקט";case"invalid_union":default:return"קלט לא תקין";case"invalid_element":{let t=a(r.origin??"array");return`ערך לא תקין ב${t}`}}})}},"hi",0,function(){let t,r,n;return{localeError:(t={string:{unit:"अक्षर",verb:"रखने के लिए"},file:{unit:"बाइट्स",verb:"रखने के लिए"},array:{unit:"तत्व",verb:"रखने के लिए"},set:{unit:"तत्व",verb:"रखने के लिए"},map:{unit:"प्रविष्टियाँ",verb:"रखने के लिए"}},r={regex:"इनपुट",email:"ईमेल पता",url:"URL",emoji:"इमोजी",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO तिथि और समय",date:"ISO तिथि",time:"ISO समय",duration:"ISO अवधि",ipv4:"IPv4 पता",ipv6:"IPv6 पता",mac:"MAC पता",cidrv4:"IPv4 श्रेणी",cidrv6:"IPv6 श्रेणी",base64:"Base64-एन्कोडेड स्ट्रिंग",base64url:"Base64URL-एन्कोडेड स्ट्रिंग",json_string:"JSON स्ट्रिंग",e164:"E.164 संख्या",credit_card:"क्रेडिट कार्ड संख्या",currency_code:"मुद्रा कोड",iban:"IBAN",jwt:"JWT",template_literal:"इनपुट"},n={nan:"NaN"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;return`अमान्य इनपुट: अपेक्षित ${t}, प्राप्त ${a}`}case"invalid_value":if(1===i.values.length)return`अमान्य इनपुट: अपेक्षित ${G(i.values[0])}`;return`अमान्य विकल्प: अपेक्षित मानों में से एक ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`बहुत बड़ा: अपेक्षित था कि ${i.origin??"मान"} में ${r}${i.maximum} ${n.unit} हों`;return`बहुत बड़ा: अपेक्षित था कि ${i.origin??"मान"} ${r}${i.maximum} हो`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`बहुत छोटा: अपेक्षित था कि ${i.origin} में ${r}${i.minimum} ${n.unit} हों`;return`बहुत छोटा: अपेक्षित था कि ${i.origin} ${r}${i.minimum} हो`}case"invalid_format":if("starts_with"===i.format)return`अमान्य स्ट्रिंग: "${i.prefix}" से शुरू होना चाहिए`;if("ends_with"===i.format)return`अमान्य स्ट्रिंग: "${i.suffix}" पर समाप्त होना चाहिए`;if("includes"===i.format)return`अमान्य स्ट्रिंग: इसमें "${i.includes}" शामिल होना चाहिए`;if("regex"===i.format)return`अमान्य स्ट्रिंग: पैटर्न ${i.pattern} से मेल खाना चाहिए`;return`अमान्य ${r[i.format]??i.format}`;case"not_multiple_of":return`अमान्य संख्या: यह ${i.divisor} का गुणज होना चाहिए`;case"unrecognized_keys":return`अपरिचित कुंजी${i.keys.length>1?"याँ":""}: ${d(i.keys,", ")}`;case"invalid_key":return`अमान्य कुंजी: ${i.origin} में`;case"invalid_union":if(i.options&&Array.isArray(i.options)&&i.options.length>0){let t=i.options.map(t=>`'${t}'`).join(" | ");return`अमान्य डिस्क्रिमिनेटर मान: अपेक्षित ${t}`}return"अमान्य इनपुट";case"invalid_element":return`अमान्य मान: ${i.origin} में`;default:return"अमान्य इनपुट"}})}},"hr",0,function(){let t,r,n;return{localeError:(t={string:{unit:"znakova",verb:"imati"},file:{unit:"bajtova",verb:"imati"},array:{unit:"stavki",verb:"imati"},set:{unit:"stavki",verb:"imati"}},r={regex:"unos",email:"email adresa",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO datum i vrijeme",date:"ISO datum",time:"ISO vrijeme",duration:"ISO trajanje",ipv4:"IPv4 adresa",ipv6:"IPv6 adresa",mac:"MAC adresa",cidrv4:"IPv4 raspon",cidrv6:"IPv6 raspon",base64:"base64 kodirani tekst",base64url:"base64url kodirani tekst",json_string:"JSON tekst",e164:"E.164 broj",credit_card:"broj kreditne kartice",currency_code:"kod valute",iban:"IBAN",jwt:"JWT",template_literal:"unos"},n={nan:"NaN",string:"tekst",number:"broj",boolean:"boolean",array:"niz",object:"objekt",set:"skup",file:"datoteka",date:"datum",bigint:"bigint",symbol:"simbol",undefined:"undefined",null:"null",function:"funkcija",map:"mapa"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Neispravan unos: očekuje se instanceof ${i.expected}, a primljeno je ${a}`;return`Neispravan unos: očekuje se ${t}, a primljeno je ${a}`}case"invalid_value":if(1===i.values.length)return`Neispravna vrijednost: očekivano ${G(i.values[0])}`;return`Neispravna opcija: očekivano jedno od ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",a=t[i.origin]??null,o=n[i.origin]??i.origin;if(a)return`Preveliko: očekivano da ${o??"vrijednost"} ima ${r}${i.maximum.toString()} ${a.unit??"elemenata"}`;return`Preveliko: očekivano da ${o??"vrijednost"} bude ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",a=t[i.origin]??null,o=n[i.origin]??i.origin;if(a)return`Premalo: očekivano da ${o} ima ${r}${i.minimum.toString()} ${a.unit}`;return`Premalo: očekivano da ${o} bude ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Neispravan tekst: mora započinjati s "${i.prefix}"`;if("ends_with"===i.format)return`Neispravan tekst: mora završavati s "${i.suffix}"`;if("includes"===i.format)return`Neispravan tekst: mora sadržavati "${i.includes}"`;if("regex"===i.format)return`Neispravan tekst: mora odgovarati uzorku ${i.pattern}`;return`Neispravna ${r[i.format]??i.format}`;case"not_multiple_of":return`Neispravan broj: mora biti višekratnik od ${i.divisor}`;case"unrecognized_keys":return`Neprepoznat${i.keys.length>1?"i ključevi":" ključ"}: ${d(i.keys,", ")}`;case"invalid_key":return`Neispravan ključ u ${n[i.origin]??i.origin}`;case"invalid_union":default:return"Neispravan unos";case"invalid_element":return`Neispravna vrijednost u ${n[i.origin]??i.origin}`}})}},"hu",0,function(){let t,r,n;return{localeError:(t={string:{unit:"karakter",verb:"legyen"},file:{unit:"byte",verb:"legyen"},array:{unit:"elem",verb:"legyen"},set:{unit:"elem",verb:"legyen"},map:{unit:"elem",verb:"legyen"}},r={regex:"bemenet",email:"email cím",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO időbélyeg",date:"ISO dátum",time:"ISO idő",duration:"ISO időintervallum",ipv4:"IPv4 cím",ipv6:"IPv6 cím",mac:"MAC cím",cidrv4:"IPv4 tartomány",cidrv6:"IPv6 tartomány",base64:"base64-kódolt string",base64url:"base64url-kódolt string",json_string:"JSON string",e164:"E.164 szám",credit_card:"hitelkártyaszám",currency_code:"pénznemkód",iban:"IBAN",jwt:"JWT",template_literal:"bemenet"},n={nan:"NaN",number:"szám",array:"tömb"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`\xc9rv\xe9nytelen bemenet: a v\xe1rt \xe9rt\xe9k instanceof ${i.expected}, a kapott \xe9rt\xe9k ${a}`;return`\xc9rv\xe9nytelen bemenet: a v\xe1rt \xe9rt\xe9k ${t}, a kapott \xe9rt\xe9k ${a}`}case"invalid_value":if(1===i.values.length)return`\xc9rv\xe9nytelen bemenet: a v\xe1rt \xe9rt\xe9k ${G(i.values[0])}`;return`\xc9rv\xe9nytelen opci\xf3: valamelyik \xe9rt\xe9k v\xe1rt ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`T\xfal nagy: ${i.origin??"érték"} m\xe9rete t\xfal nagy ${r}${i.maximum.toString()} ${n.unit??"elem"}`;return`T\xfal nagy: a bemeneti \xe9rt\xe9k ${i.origin??"érték"} t\xfal nagy: ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`T\xfal kicsi: a bemeneti \xe9rt\xe9k ${i.origin} m\xe9rete t\xfal kicsi ${r}${i.minimum.toString()} ${n.unit}`;return`T\xfal kicsi: a bemeneti \xe9rt\xe9k ${i.origin} t\xfal kicsi ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`\xc9rv\xe9nytelen string: "${i.prefix}" \xe9rt\xe9kkel kell kezdődnie`;if("ends_with"===i.format)return`\xc9rv\xe9nytelen string: "${i.suffix}" \xe9rt\xe9kkel kell v\xe9gződnie`;if("includes"===i.format)return`\xc9rv\xe9nytelen string: "${i.includes}" \xe9rt\xe9ket kell tartalmaznia`;if("regex"===i.format)return`\xc9rv\xe9nytelen string: ${i.pattern} mint\xe1nak kell megfelelnie`;return`\xc9rv\xe9nytelen ${r[i.format]??i.format}`;case"not_multiple_of":return`\xc9rv\xe9nytelen sz\xe1m: ${i.divisor} t\xf6bbsz\xf6r\xf6s\xe9nek kell lennie`;case"unrecognized_keys":return`Ismeretlen kulcs${i.keys.length>1?"s":""}: ${d(i.keys,", ")}`;case"invalid_key":return`\xc9rv\xe9nytelen kulcs ${i.origin}`;case"invalid_union":default:return"Érvénytelen bemenet";case"invalid_element":return`\xc9rv\xe9nytelen \xe9rt\xe9k: ${i.origin}`}})}},"hy",0,function(){let t,r,n;return{localeError:(t={string:{unit:{one:"նշան",many:"նշաններ"},verb:"ունենալ"},file:{unit:{one:"բայթ",many:"բայթեր"},verb:"ունենալ"},array:{unit:{one:"տարր",many:"տարրեր"},verb:"ունենալ"},set:{unit:{one:"տարր",many:"տարրեր"},verb:"ունենալ"},map:{unit:{one:"տարր",many:"տարրեր"},verb:"ունենալ"}},r={regex:"մուտք",email:"էլ. հասցե",url:"URL",emoji:"էմոջի",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO ամսաթիվ և ժամ",date:"ISO ամսաթիվ",time:"ISO ժամ",duration:"ISO տևողություն",ipv4:"IPv4 հասցե",ipv6:"IPv6 հասցե",mac:"MAC հասցե",cidrv4:"IPv4 միջակայք",cidrv6:"IPv6 միջակայք",base64:"base64 ձևաչափով տող",base64url:"base64url ձևաչափով տող",json_string:"JSON տող",e164:"E.164 համար",credit_card:"կրեդիտ քարտի համար",currency_code:"արժույթի կոդ",iban:"IBAN",jwt:"JWT",template_literal:"մուտք"},n={nan:"NaN",number:"թիվ",array:"զանգված"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Սխալ մուտքագրում․ սպասվում էր instanceof ${i.expected}, ստացվել է ${a}`;return`Սխալ մուտքագրում․ սպասվում էր ${t}, ստացվել է ${a}`}case"invalid_value":if(1===i.values.length)return`Սխալ մուտքագրում․ սպասվում էր ${G(i.values[1])}`;return`Սխալ տարբերակ․ սպասվում էր հետևյալներից մեկը՝ ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n){let t=i3(Number(i.maximum),n.unit.one,n.unit.many);return`Չափազանց մեծ արժեք․ սպասվում է, որ ${i7(i.origin??"արժեք")} կունենա ${r}${i.maximum.toString()} ${t}`}return`Չափազանց մեծ արժեք․ սպասվում է, որ ${i7(i.origin??"արժեք")} լինի ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n){let t=i3(Number(i.minimum),n.unit.one,n.unit.many);return`Չափազանց փոքր արժեք․ սպասվում է, որ ${i7(i.origin)} կունենա ${r}${i.minimum.toString()} ${t}`}return`Չափազանց փոքր արժեք․ սպասվում է, որ ${i7(i.origin)} լինի ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Սխալ տող․ պետք է սկսվի "${i.prefix}"-ով`;if("ends_with"===i.format)return`Սխալ տող․ պետք է ավարտվի "${i.suffix}"-ով`;if("includes"===i.format)return`Սխալ տող․ պետք է պարունակի "${i.includes}"`;if("regex"===i.format)return`Սխալ տող․ պետք է համապատասխանի ${i.pattern} ձևաչափին`;return`Սխալ ${r[i.format]??i.format}`;case"not_multiple_of":return`Սխալ թիվ․ պետք է բազմապատիկ լինի ${i.divisor}-ի`;case"unrecognized_keys":return`Չճանաչված բանալի${i.keys.length>1?"ներ":""}. ${d(i.keys,", ")}`;case"invalid_key":return`Սխալ բանալի ${i7(i.origin)}-ում`;case"invalid_union":default:return"Սխալ մուտքագրում";case"invalid_element":return`Սխալ արժեք ${i7(i.origin)}-ում`}})}},"id",0,function(){let t,r,n;return{localeError:(t={string:{unit:"karakter",verb:"memiliki"},file:{unit:"byte",verb:"memiliki"},array:{unit:"item",verb:"memiliki"},set:{unit:"item",verb:"memiliki"},map:{unit:"item",verb:"memiliki"}},r={regex:"input",email:"alamat email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"tanggal dan waktu format ISO",date:"tanggal format ISO",time:"jam format ISO",duration:"durasi format ISO",ipv4:"alamat IPv4",ipv6:"alamat IPv6",mac:"alamat MAC",cidrv4:"rentang alamat IPv4",cidrv6:"rentang alamat IPv6",base64:"string dengan enkode base64",base64url:"string dengan enkode base64url",json_string:"string JSON",e164:"angka E.164",credit_card:"nomor kartu kredit",currency_code:"kode mata uang",iban:"IBAN",jwt:"JWT",template_literal:"input"},n={nan:"NaN"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Input tidak valid: diharapkan instanceof ${i.expected}, diterima ${a}`;return`Input tidak valid: diharapkan ${t}, diterima ${a}`}case"invalid_value":if(1===i.values.length)return`Input tidak valid: diharapkan ${G(i.values[0])}`;return`Pilihan tidak valid: diharapkan salah satu dari ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`Terlalu besar: diharapkan ${i.origin??"value"} memiliki ${r}${i.maximum.toString()} ${n.unit??"elemen"}`;return`Terlalu besar: diharapkan ${i.origin??"value"} menjadi ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`Terlalu kecil: diharapkan ${i.origin} memiliki ${r}${i.minimum.toString()} ${n.unit}`;return`Terlalu kecil: diharapkan ${i.origin} menjadi ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`String tidak valid: harus dimulai dengan "${i.prefix}"`;if("ends_with"===i.format)return`String tidak valid: harus berakhir dengan "${i.suffix}"`;if("includes"===i.format)return`String tidak valid: harus menyertakan "${i.includes}"`;if("regex"===i.format)return`String tidak valid: harus sesuai pola ${i.pattern}`;return`${r[i.format]??i.format} tidak valid`;case"not_multiple_of":return`Angka tidak valid: harus kelipatan dari ${i.divisor}`;case"unrecognized_keys":return`Kunci tidak dikenali ${i.keys.length>1?"s":""}: ${d(i.keys,", ")}`;case"invalid_key":return`Kunci tidak valid di ${i.origin}`;case"invalid_union":default:return"Input tidak valid";case"invalid_element":return`Nilai tidak valid di ${i.origin}`}})}},"is",0,function(){let t,r,n;return{localeError:(t={string:{unit:"stafi",verb:"að hafa"},file:{unit:"bæti",verb:"að hafa"},array:{unit:"hluti",verb:"að hafa"},set:{unit:"hluti",verb:"að hafa"},map:{unit:"hluti",verb:"að hafa"}},r={regex:"gildi",email:"netfang",url:"vefslóð",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO dagsetning og tími",date:"ISO dagsetning",time:"ISO tími",duration:"ISO tímalengd",ipv4:"IPv4 address",ipv6:"IPv6 address",mac:"MAC address",cidrv4:"IPv4 range",cidrv6:"IPv6 range",base64:"base64-encoded strengur",base64url:"base64url-encoded strengur",json_string:"JSON strengur",e164:"E.164 tölugildi",credit_card:"kreditkortanúmer",currency_code:"gjaldmiðilskóði",iban:"IBAN",jwt:"JWT",template_literal:"gildi"},n={nan:"NaN",number:"númer",array:"fylki"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Rangt gildi: \xde\xfa sl\xf3st inn ${a} \xfear sem \xe1 a\xf0 vera instanceof ${i.expected}`;return`Rangt gildi: \xde\xfa sl\xf3st inn ${a} \xfear sem \xe1 a\xf0 vera ${t}`}case"invalid_value":if(1===i.values.length)return`Rangt gildi: gert r\xe1\xf0 fyrir ${G(i.values[0])}`;return`\xd3gilt val: m\xe1 vera eitt af eftirfarandi ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`Of st\xf3rt: gert er r\xe1\xf0 fyrir a\xf0 ${i.origin??"gildi"} hafi ${r}${i.maximum.toString()} ${n.unit??"hluti"}`;return`Of st\xf3rt: gert er r\xe1\xf0 fyrir a\xf0 ${i.origin??"gildi"} s\xe9 ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`Of l\xedti\xf0: gert er r\xe1\xf0 fyrir a\xf0 ${i.origin} hafi ${r}${i.minimum.toString()} ${n.unit}`;return`Of l\xedti\xf0: gert er r\xe1\xf0 fyrir a\xf0 ${i.origin} s\xe9 ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`\xd3gildur strengur: ver\xf0ur a\xf0 byrja \xe1 "${i.prefix}"`;if("ends_with"===i.format)return`\xd3gildur strengur: ver\xf0ur a\xf0 enda \xe1 "${i.suffix}"`;if("includes"===i.format)return`\xd3gildur strengur: ver\xf0ur a\xf0 innihalda "${i.includes}"`;if("regex"===i.format)return`\xd3gildur strengur: ver\xf0ur a\xf0 fylgja mynstri ${i.pattern}`;return`Rangt ${r[i.format]??i.format}`;case"not_multiple_of":return`R\xf6ng tala: ver\xf0ur a\xf0 vera margfeldi af ${i.divisor}`;case"unrecognized_keys":return`\xd3\xfeekkt ${i.keys.length>1?"ir lyklar":"ur lykill"}: ${d(i.keys,", ")}`;case"invalid_key":return`Rangur lykill \xed ${i.origin}`;case"invalid_union":default:return"Rangt gildi";case"invalid_element":return`Rangt gildi \xed ${i.origin}`}})}},"it",0,function(){let t,r,n;return{localeError:(t={string:{unit:"caratteri",verb:"avere"},file:{unit:"byte",verb:"avere"},array:{unit:"elementi",verb:"avere"},set:{unit:"elementi",verb:"avere"},map:{unit:"elementi",verb:"avere"}},r={regex:"input",email:"indirizzo email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data e ora ISO",date:"data ISO",time:"ora ISO",duration:"durata ISO",ipv4:"indirizzo IPv4",ipv6:"indirizzo IPv6",mac:"indirizzo MAC",cidrv4:"intervallo IPv4",cidrv6:"intervallo IPv6",base64:"stringa codificata in base64",base64url:"URL codificata in base64",json_string:"stringa JSON",e164:"numero E.164",credit_card:"numero di carta di credito",currency_code:"codice valuta",iban:"IBAN",jwt:"JWT",template_literal:"input"},n={nan:"NaN",number:"numero",array:"vettore"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Input non valido: atteso instanceof ${i.expected}, ricevuto ${a}`;return`Input non valido: atteso ${t}, ricevuto ${a}`}case"invalid_value":if(1===i.values.length)return`Input non valido: atteso ${G(i.values[0])}`;return`Opzione non valida: atteso uno tra ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`Troppo grande: ${i.origin??"valore"} deve avere ${r}${i.maximum.toString()} ${n.unit??"elementi"}`;return`Troppo grande: ${i.origin??"valore"} deve essere ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`Troppo piccolo: ${i.origin} deve avere ${r}${i.minimum.toString()} ${n.unit}`;return`Troppo piccolo: ${i.origin} deve essere ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Stringa non valida: deve iniziare con "${i.prefix}"`;if("ends_with"===i.format)return`Stringa non valida: deve terminare con "${i.suffix}"`;if("includes"===i.format)return`Stringa non valida: deve includere "${i.includes}"`;if("regex"===i.format)return`Stringa non valida: deve corrispondere al pattern ${i.pattern}`;return`Input non valido: ${r[i.format]??i.format}`;case"not_multiple_of":return`Numero non valido: deve essere un multiplo di ${i.divisor}`;case"unrecognized_keys":return`Chiav${i.keys.length>1?"i":"e"} non riconosciut${i.keys.length>1?"e":"a"}: ${d(i.keys,", ")}`;case"invalid_key":return`Chiave non valida in ${i.origin}`;case"invalid_union":default:return"Input non valido";case"invalid_element":return`Valore non valido in ${i.origin}`}})}},"ja",0,function(){let t,r,n;return{localeError:(t={string:{unit:"文字",verb:"である"},file:{unit:"バイト",verb:"である"},array:{unit:"要素",verb:"である"},set:{unit:"要素",verb:"である"},map:{unit:"要素",verb:"である"}},r={regex:"入力値",email:"メールアドレス",url:"URL",emoji:"絵文字",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO日時",date:"ISO日付",time:"ISO時刻",duration:"ISO期間",ipv4:"IPv4アドレス",ipv6:"IPv6アドレス",mac:"MACアドレス",cidrv4:"IPv4範囲",cidrv6:"IPv6範囲",base64:"base64エンコード文字列",base64url:"base64urlエンコード文字列",json_string:"JSON文字列",e164:"E.164番号",credit_card:"クレジットカード番号",currency_code:"通貨コード",iban:"IBAN",jwt:"JWT",template_literal:"入力値"},n={nan:"NaN",number:"数値",array:"配列"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`無効な入力: instanceof ${i.expected}が期待されましたが、${a}が入力されました`;return`無効な入力: ${t}が期待されましたが、${a}が入力されました`}case"invalid_value":if(1===i.values.length)return`無効な入力: ${G(i.values[0])}が期待されました`;return`無効な選択: ${d(i.values,"、")}のいずれかである必要があります`;case"too_big":{let r=i.inclusive?"以下である":"より小さい",n=t[i.origin]??null;if(n)return`大きすぎる値: ${i.origin??"値"}は${i.maximum.toString()}${n.unit??"要素"}${r}必要があります`;return`大きすぎる値: ${i.origin??"値"}は${i.maximum.toString()}${r}必要があります`}case"too_small":{let r=i.inclusive?"以上である":"より大きい",n=t[i.origin]??null;if(n)return`小さすぎる値: ${i.origin}は${i.minimum.toString()}${n.unit}${r}必要があります`;return`小さすぎる値: ${i.origin}は${i.minimum.toString()}${r}必要があります`}case"invalid_format":if("starts_with"===i.format)return`無効な文字列: "${i.prefix}"で始まる必要があります`;if("ends_with"===i.format)return`無効な文字列: "${i.suffix}"で終わる必要があります`;if("includes"===i.format)return`無効な文字列: "${i.includes}"を含む必要があります`;if("regex"===i.format)return`無効な文字列: パターン${i.pattern}に一致する必要があります`;return`無効な${r[i.format]??i.format}`;case"not_multiple_of":return`無効な数値: ${i.divisor}の倍数である必要があります`;case"unrecognized_keys":return`認識されていないキー${i.keys.length>1?"群":""}: ${d(i.keys,"、")}`;case"invalid_key":return`${i.origin}内の無効なキー`;case"invalid_union":default:return"無効な入力";case"invalid_element":return`${i.origin}内の無効な値`}})}},"ka",0,function(){let t,r,n;return{localeError:(t={string:{unit:"სიმბოლო",verb:"უნდა შეიცავდეს"},file:{unit:"ბაიტი",verb:"უნდა შეიცავდეს"},array:{unit:"ელემენტი",verb:"უნდა შეიცავდეს"},set:{unit:"ელემენტი",verb:"უნდა შეიცავდეს"},map:{unit:"ელემენტი",verb:"უნდა შეიცავდეს"}},r={regex:"შეყვანა",email:"ელ-ფოსტის მისამართი",url:"URL",emoji:"ემოჯი",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"თარიღი-დრო",date:"თარიღი",time:"დრო",duration:"ხანგრძლივობა",ipv4:"IPv4 მისამართი",ipv6:"IPv6 მისამართი",mac:"MAC მისამართი",cidrv4:"IPv4 დიაპაზონი",cidrv6:"IPv6 დიაპაზონი",base64:"base64-კოდირებული ველი",base64url:"base64url-კოდირებული ველი",json_string:"JSON ველი",e164:"E.164 ნომერი",credit_card:"საკრედიტო ბარათის ნომერი",currency_code:"ვალუტის კოდი",iban:"IBAN",jwt:"JWT",template_literal:"შეყვანა"},n={nan:"NaN",number:"რიცხვი",string:"ველი",boolean:"ბულეანი",function:"ფუნქცია",array:"მასივი"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`არასწორი შეყვანა: მოსალოდნელი instanceof ${i.expected}, მიღებული ${a}`;return`არასწორი შეყვანა: მოსალოდნელი ${t}, მიღებული ${a}`}case"invalid_value":if(1===i.values.length)return`არასწორი შეყვანა: მოსალოდნელი ${G(i.values[0])}`;return`არასწორი ვარიანტი: მოსალოდნელია ერთ-ერთი ${d(i.values,"|")}-დან`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`ზედმეტად დიდი: მოსალოდნელი ${i.origin??"მნიშვნელობა"} ${n.verb} ${r}${i.maximum.toString()} ${n.unit}`;return`ზედმეტად დიდი: მოსალოდნელი ${i.origin??"მნიშვნელობა"} იყოს ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`ზედმეტად პატარა: მოსალოდნელი ${i.origin} ${n.verb} ${r}${i.minimum.toString()} ${n.unit}`;return`ზედმეტად პატარა: მოსალოდნელი ${i.origin} იყოს ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`არასწორი ველი: უნდა იწყებოდეს "${i.prefix}"-ით`;if("ends_with"===i.format)return`არასწორი ველი: უნდა მთავრდებოდეს "${i.suffix}"-ით`;if("includes"===i.format)return`არასწორი ველი: უნდა შეიცავდეს "${i.includes}"-ს`;if("regex"===i.format)return`არასწორი ველი: უნდა შეესაბამებოდეს შაბლონს ${i.pattern}`;return`არასწორი ${r[i.format]??i.format}`;case"not_multiple_of":return`არასწორი რიცხვი: უნდა იყოს ${i.divisor}-ის ჯერადი`;case"unrecognized_keys":return`უცნობი გასაღებ${i.keys.length>1?"ები":"ი"}: ${d(i.keys,", ")}`;case"invalid_key":return`არასწორი გასაღები ${i.origin}-ში`;case"invalid_union":default:return"არასწორი შეყვანა";case"invalid_element":return`არასწორი მნიშვნელობა ${i.origin}-ში`}})}},"kh",0,function(){return i9()},"km",0,i9,"kn",0,function(){let t,r,n;return{localeError:(t={string:{unit:"ಅಕ್ಷರಗಳು",verb:"ಹೊಂದಲು"},file:{unit:"ಬೈಟ್‌ಗಳು",verb:"ಹೊಂದಲು"},array:{unit:"ವಸ್ತುಗಳು",verb:"ಹೊಂದಲು"},set:{unit:"ವಸ್ತುಗಳು",verb:"ಹೊಂದಲು"},map:{unit:"entries",verb:"ಹೊಂದಲು"}},r={regex:"ಇನ್ಪುಟ್",email:"email ವಿಳಾಸ",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO ದಿನಾಂಕದ ಸಮಯ",date:"ISO ದಿನಾಂಕ",time:"ISO ಸಮಯ",duration:"ISO ಅವಧಿ",ipv4:"IPv4 ವಿಳಾಸ",ipv6:"IPv6 ವಿಳಾಸ",mac:"MAC ವಿಳಾಸ",cidrv4:"IPv4 ವ್ಯಾಪ್ತಿಯ",cidrv6:"IPv6 ವ್ಯಾಪ್ತಿಯ",base64:"base64-encodedಸ್ಟ್ರಿಂಗ್",base64url:"base64url-encodedಸ್ಟ್ರಿಂಗ್",json_string:"JSONಸ್ಟ್ರಿಂಗ್",e164:"E.164 ಸಂಖ್ಯೆ",credit_card:"ಕ್ರೆಡಿಟ್ ಕಾರ್ಡ್ ಸಂಖ್ಯೆ",currency_code:"ಕರೆನ್ಸಿ ಕೋಡ್",iban:"IBAN",jwt:"JWT",template_literal:"ಇನ್ಪುಟ್"},n={nan:"NaN"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;return`ಅಮಾನ್ಯ ಇನ್‌ಪುಟ್: ನಿರೀಕ್ಷಿಸಲಾಗಿದೆ ${t}, ಸ್ವೀಕರಿಸಿದನು ${a}`}case"invalid_value":if(1===i.values.length)return`ಅಮಾನ್ಯ ಇನ್‌ಪುಟ್: ನಿರೀಕ್ಷಿಸಲಾಗಿದೆ ${G(i.values[0])}`;return`ಅಮಾನ್ಯ ಆಯ್ಕೆ: ಇವುಗಳಲ್ಲಿ ಒಂದನ್ನು ನಿರೀಕ್ಷಿಸಲಾಗಿದೆ ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`ತುಂಬಾ ದೊಡ್ಡದು: ನಿರೀಕ್ಷಿಸಲಾಗಿದೆ ${i.origin??"value"} ಹೊಂದಲು ${r}${i.maximum.toString()} ${n.unit??"ಅಂಶಗಳು"}`;return`ತುಂಬಾ ದೊಡ್ಡದು: ನಿರೀಕ್ಷಿಸಲಾಗಿದೆ ${i.origin??"value"} ಎಂದು ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`ತುಂಬಾ ಚಿಕ್ಕದು: ನಿರೀಕ್ಷಿಸಲಾಗಿದೆ ${i.origin} ಹೊಂದಲು ${r}${i.minimum.toString()} ${n.unit}`;return`ತುಂಬಾ ಚಿಕ್ಕದು: ನಿರೀಕ್ಷಿಸಲಾಗಿದೆ ${i.origin} ಎಂದು ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`ಅಮಾನ್ಯವಾದ ಸ್ಟ್ರಿಂಗ್: ಇದರೊಂದಿಗೆ ಪ್ರಾರಂಭಿಸಬೇಕು "${i.prefix}"`;if("ends_with"===i.format)return`ಅಮಾನ್ಯವಾದ ಸ್ಟ್ರಿಂಗ್: ಇದರೊಂದಿಗೆ ಕೊನೆಗೊಳ್ಳಬೇಕು "${i.suffix}"`;if("includes"===i.format)return`ಅಮಾನ್ಯ ಸ್ಟ್ರಿಂಗ್: ಒಳಗೊಂಡಿರಬೇಕು "${i.includes}"`;if("regex"===i.format)return`ಅಮಾನ್ಯವಾದ ಸ್ಟ್ರಿಂಗ್: ಮಾದರಿಗೆ ಹೊಂದಿಕೆಯಾಗಬೇಕು ${i.pattern}`;return`ಅಮಾನ್ಯ ${r[i.format]??i.format}`;case"not_multiple_of":return`ಅಮಾನ್ಯ ಸಂಖ್ಯೆ: ಬಹುಸಂಖ್ಯೆಯಾಗಿರಬೇಕು ${i.divisor}`;case"unrecognized_keys":return`ಗುರುತಿಸಲಾಗದ ಕೀ ${i.keys.length>1?"s":""}: ${d(i.keys,", ")}`;case"invalid_key":return`ಅಮಾನ್ಯವಾದ ಕೀ ಇನ್ ${i.origin}`;case"invalid_union":if(i.options&&Array.isArray(i.options)&&i.options.length>0){let t=i.options.map(t=>`'${t}'`).join(" | ");return`ಅಮಾನ್ಯ ತಾರತಮ್ಯ ಮೌಲ್ಯ. ನಿರೀಕ್ಷಿಸಲಾಗಿದೆ ${t}`}return"ಅಮಾನ್ಯ ಇನ್‌ಪುಟ್";case"invalid_element":return`ರಲ್ಲಿ ಅಮಾನ್ಯ ಮೌಲ್ಯ ${i.origin}`;default:return"ಅಮಾನ್ಯ ಇನ್‌ಪುಟ್"}})}},"ko",0,function(){let t,r,n;return{localeError:(t={string:{unit:"문자",verb:"to have"},file:{unit:"바이트",verb:"to have"},array:{unit:"개",verb:"to have"},set:{unit:"개",verb:"to have"},map:{unit:"개",verb:"to have"}},r={regex:"입력",email:"이메일 주소",url:"URL",emoji:"이모지",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO 날짜시간",date:"ISO 날짜",time:"ISO 시간",duration:"ISO 기간",ipv4:"IPv4 주소",ipv6:"IPv6 주소",mac:"MAC 주소",cidrv4:"IPv4 범위",cidrv6:"IPv6 범위",base64:"base64 인코딩 문자열",base64url:"base64url 인코딩 문자열",json_string:"JSON 문자열",e164:"E.164 번호",credit_card:"신용카드 번호",currency_code:"통화 코드",iban:"IBAN",jwt:"JWT",template_literal:"입력"},n={nan:"NaN"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`잘못된 입력: 예상 타입은 instanceof ${i.expected}, 받은 타입은 ${a}입니다`;return`잘못된 입력: 예상 타입은 ${t}, 받은 타입은 ${a}입니다`}case"invalid_value":if(1===i.values.length)return`잘못된 입력: 값은 ${G(i.values[0])} 이어야 합니다`;return`잘못된 옵션: ${d(i.values,"또는 ")} 중 하나여야 합니다`;case"too_big":{let r=i.inclusive?"이하":"미만",n="미만"===r?"이어야 합니다":"여야 합니다",a=t[i.origin]??null,o=a?.unit??"요소";if(a)return`${i.origin??"값"}이 너무 큽니다: ${i.maximum.toString()}${o} ${r}${n}`;return`${i.origin??"값"}이 너무 큽니다: ${i.maximum.toString()} ${r}${n}`}case"too_small":{let r=i.inclusive?"이상":"초과",n="이상"===r?"이어야 합니다":"여야 합니다",a=t[i.origin]??null,o=a?.unit??"요소";if(a)return`${i.origin??"값"}이 너무 작습니다: ${i.minimum.toString()}${o} ${r}${n}`;return`${i.origin??"값"}이 너무 작습니다: ${i.minimum.toString()} ${r}${n}`}case"invalid_format":if("starts_with"===i.format)return`잘못된 문자열: "${i.prefix}"(으)로 시작해야 합니다`;if("ends_with"===i.format)return`잘못된 문자열: "${i.suffix}"(으)로 끝나야 합니다`;if("includes"===i.format)return`잘못된 문자열: "${i.includes}"을(를) 포함해야 합니다`;if("regex"===i.format)return`잘못된 문자열: 정규식 ${i.pattern} 패턴과 일치해야 합니다`;return`잘못된 ${r[i.format]??i.format}`;case"not_multiple_of":return`잘못된 숫자: ${i.divisor}의 배수여야 합니다`;case"unrecognized_keys":return`인식할 수 없는 키: ${d(i.keys,", ")}`;case"invalid_key":return`잘못된 키: ${i.origin}`;case"invalid_union":default:return"잘못된 입력";case"invalid_element":return`잘못된 값: ${i.origin}`}})}},"lt",0,function(){return{localeError:(()=>{let t={string:{unit:{one:"simbolis",few:"simboliai",many:"simbolių"},verb:{smaller:{inclusive:"turi būti ne ilgesnė kaip",notInclusive:"turi būti trumpesnė kaip"},bigger:{inclusive:"turi būti ne trumpesnė kaip",notInclusive:"turi būti ilgesnė kaip"}}},file:{unit:{one:"baitas",few:"baitai",many:"baitų"},verb:{smaller:{inclusive:"turi būti ne didesnis kaip",notInclusive:"turi būti mažesnis kaip"},bigger:{inclusive:"turi būti ne mažesnis kaip",notInclusive:"turi būti didesnis kaip"}}},array:{unit:{one:"elementą",few:"elementus",many:"elementų"},verb:{smaller:{inclusive:"turi turėti ne daugiau kaip",notInclusive:"turi turėti mažiau kaip"},bigger:{inclusive:"turi turėti ne mažiau kaip",notInclusive:"turi turėti daugiau kaip"}}},set:{unit:{one:"elementą",few:"elementus",many:"elementų"},verb:{smaller:{inclusive:"turi turėti ne daugiau kaip",notInclusive:"turi turėti mažiau kaip"},bigger:{inclusive:"turi turėti ne mažiau kaip",notInclusive:"turi turėti daugiau kaip"}}}};function r(r,n,i,a){let o=t[r]??null;return null===o?o:{unit:o.unit[n],verb:o.verb[a][i?"inclusive":"notInclusive"]}}let n={regex:"įvestis",email:"el. pašto adresas",url:"URL",emoji:"jaustukas",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO data ir laikas",date:"ISO data",time:"ISO laikas",duration:"ISO trukmė",ipv4:"IPv4 adresas",ipv6:"IPv6 adresas",mac:"MAC adresas",cidrv4:"IPv4 tinklo prefiksas (CIDR)",cidrv6:"IPv6 tinklo prefiksas (CIDR)",base64:"base64 užkoduota eilutė",base64url:"base64url užkoduota eilutė",json_string:"JSON eilutė",e164:"E.164 numeris",credit_card:"kredito kortelės numeris",currency_code:"valiutos kodas",iban:"IBAN",jwt:"JWT",template_literal:"įvestis"},i={nan:"NaN",number:"skaičius",bigint:"sveikasis skaičius",string:"eilutė",boolean:"loginė reikšmė",undefined:"neapibrėžta reikšmė",function:"funkcija",symbol:"simbolis",array:"masyvas",object:"objektas",null:"nulinė reikšmė"};return t=>{switch(t.code){case"invalid_type":{let r=i[t.expected]??t.expected,n=eg(t.input),a=i[n]??n;if(/^[A-Z]/.test(t.expected))return`Gautas tipas ${a}, o tikėtasi - instanceof ${t.expected}`;return`Gautas tipas ${a}, o tikėtasi - ${r}`}case"invalid_value":if(1===t.values.length)return`Privalo būti ${G(t.values[0])}`;return`Privalo būti vienas iš ${d(t.values,"|")} pasirinkimų`;case"too_big":{let n=i[t.origin]??t.origin,a=r(t.origin,ae(Number(t.maximum)),t.inclusive??!1,"smaller");if(a?.verb)return`${i8(n??t.origin??"reikšmė")} ${a.verb} ${t.maximum.toString()} ${a.unit??"elementų"}`;let o=t.inclusive?"ne didesnis kaip":"mažesnis kaip";return`${i8(n??t.origin??"reikšmė")} turi būti ${o} ${t.maximum.toString()} ${a?.unit}`}case"too_small":{let n=i[t.origin]??t.origin,a=r(t.origin,ae(Number(t.minimum)),t.inclusive??!1,"bigger");if(a?.verb)return`${i8(n??t.origin??"reikšmė")} ${a.verb} ${t.minimum.toString()} ${a.unit??"elementų"}`;let o=t.inclusive?"ne mažesnis kaip":"didesnis kaip";return`${i8(n??t.origin??"reikšmė")} turi būti ${o} ${t.minimum.toString()} ${a?.unit}`}case"invalid_format":if("starts_with"===t.format)return`Eilutė privalo prasidėti "${t.prefix}"`;if("ends_with"===t.format)return`Eilutė privalo pasibaigti "${t.suffix}"`;if("includes"===t.format)return`Eilutė privalo įtraukti "${t.includes}"`;if("regex"===t.format)return`Eilutė privalo atitikti ${t.pattern}`;return`Neteisingas ${n[t.format]??t.format}`;case"not_multiple_of":return`Skaičius privalo būti ${t.divisor} kartotinis.`;case"unrecognized_keys":return`Neatpažint${t.keys.length>1?"i":"as"} rakt${t.keys.length>1?"ai":"as"}: ${d(t.keys,", ")}`;case"invalid_key":return"Rastas klaidingas raktas";case"invalid_union":default:return"Klaidinga įvestis";case"invalid_element":{let r=i[t.origin]??t.origin;return`${i8(r??t.origin??"reikšmė")} turi klaidingą įvestį`}}}})()}},"mk",0,function(){let t,r,n;return{localeError:(t={string:{unit:"знаци",verb:"да имаат"},file:{unit:"бајти",verb:"да имаат"},array:{unit:"ставки",verb:"да имаат"},set:{unit:"ставки",verb:"да имаат"},map:{unit:"ставки",verb:"да имаат"}},r={regex:"внес",email:"адреса на е-пошта",url:"URL",emoji:"емоџи",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO датум и време",date:"ISO датум",time:"ISO време",duration:"ISO времетраење",ipv4:"IPv4 адреса",ipv6:"IPv6 адреса",mac:"MAC адреса",cidrv4:"IPv4 опсег",cidrv6:"IPv6 опсег",base64:"base64-енкодирана низа",base64url:"base64url-енкодирана низа",json_string:"JSON низа",e164:"E.164 број",credit_card:"број на кредитна картичка",currency_code:"код на валута",iban:"IBAN",jwt:"JWT",template_literal:"внес"},n={nan:"NaN",number:"број",array:"низа"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Грешен внес: се очекува instanceof ${i.expected}, примено ${a}`;return`Грешен внес: се очекува ${t}, примено ${a}`}case"invalid_value":if(1===i.values.length)return`Invalid input: expected ${G(i.values[0])}`;return`Грешана опција: се очекува една ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`Премногу голем: се очекува ${i.origin??"вредноста"} да има ${r}${i.maximum.toString()} ${n.unit??"елементи"}`;return`Премногу голем: се очекува ${i.origin??"вредноста"} да биде ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`Премногу мал: се очекува ${i.origin} да има ${r}${i.minimum.toString()} ${n.unit}`;return`Премногу мал: се очекува ${i.origin} да биде ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Неважечка низа: мора да започнува со "${i.prefix}"`;if("ends_with"===i.format)return`Неважечка низа: мора да завршува со "${i.suffix}"`;if("includes"===i.format)return`Неважечка низа: мора да вклучува "${i.includes}"`;if("regex"===i.format)return`Неважечка низа: мора да одгоара на патернот ${i.pattern}`;return`Invalid ${r[i.format]??i.format}`;case"not_multiple_of":return`Грешен број: мора да биде делив со ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Непрепознаени клучеви":"Непрепознаен клуч"}: ${d(i.keys,", ")}`;case"invalid_key":return`Грешен клуч во ${i.origin}`;case"invalid_union":default:return"Грешен внес";case"invalid_element":return`Грешна вредност во ${i.origin}`}})}},"ms",0,function(){let t,r,n;return{localeError:(t={string:{unit:"aksara",verb:"mempunyai"},file:{unit:"bait",verb:"mempunyai"},array:{unit:"elemen",verb:"mempunyai"},set:{unit:"elemen",verb:"mempunyai"},map:{unit:"elemen",verb:"mempunyai"}},r={regex:"input",email:"alamat e-mel",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"tarikh masa ISO",date:"tarikh ISO",time:"masa ISO",duration:"tempoh ISO",ipv4:"alamat IPv4",ipv6:"alamat IPv6",mac:"alamat MAC",cidrv4:"julat IPv4",cidrv6:"julat IPv6",base64:"string dikodkan base64",base64url:"string dikodkan base64url",json_string:"string JSON",e164:"nombor E.164",credit_card:"nombor kad kredit",currency_code:"kod mata wang",iban:"IBAN",jwt:"JWT",template_literal:"input"},n={nan:"NaN",number:"nombor"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Input tidak sah: dijangka instanceof ${i.expected}, diterima ${a}`;return`Input tidak sah: dijangka ${t}, diterima ${a}`}case"invalid_value":if(1===i.values.length)return`Input tidak sah: dijangka ${G(i.values[0])}`;return`Pilihan tidak sah: dijangka salah satu daripada ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`Terlalu besar: dijangka ${i.origin??"nilai"} ${n.verb} ${r}${i.maximum.toString()} ${n.unit??"elemen"}`;return`Terlalu besar: dijangka ${i.origin??"nilai"} adalah ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`Terlalu kecil: dijangka ${i.origin} ${n.verb} ${r}${i.minimum.toString()} ${n.unit}`;return`Terlalu kecil: dijangka ${i.origin} adalah ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`String tidak sah: mesti bermula dengan "${i.prefix}"`;if("ends_with"===i.format)return`String tidak sah: mesti berakhir dengan "${i.suffix}"`;if("includes"===i.format)return`String tidak sah: mesti mengandungi "${i.includes}"`;if("regex"===i.format)return`String tidak sah: mesti sepadan dengan corak ${i.pattern}`;return`${r[i.format]??i.format} tidak sah`;case"not_multiple_of":return`Nombor tidak sah: perlu gandaan ${i.divisor}`;case"unrecognized_keys":return`Kunci tidak dikenali: ${d(i.keys,", ")}`;case"invalid_key":return`Kunci tidak sah dalam ${i.origin}`;case"invalid_union":default:return"Input tidak sah";case"invalid_element":return`Nilai tidak sah dalam ${i.origin}`}})}},"ne",0,function(){let t,r,n;return{localeError:(t={string:{unit:"अक्षर",verb:"हुनुपर्छ"},file:{unit:"बाइट",verb:"हुनुपर्छ"},array:{unit:"तत्व",verb:"हुनुपर्छ"},set:{unit:"तत्व",verb:"हुनुपर्छ"},map:{unit:"प्रविष्टि",verb:"हुनुपर्छ"}},r={regex:"इनपुट",email:"इमेल ठेगाना",url:"URL",emoji:"इमोजी",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO मिति र समय",date:"ISO मिति",time:"ISO समय",duration:"ISO अवधि",ipv4:"IPv4 ठेगाना",ipv6:"IPv6 ठेगाना",mac:"MAC ठेगाना",cidrv4:"IPv4 दायरा",cidrv6:"IPv6 दायरा",base64:"base64-इन्कोड गरिएको स्ट्रिङ",base64url:"base64url-इन्कोड गरिएको स्ट्रिङ",json_string:"JSON स्ट्रिङ",e164:"E.164 नम्बर",credit_card:"क्रेडिट कार्ड नम्बर",currency_code:"मुद्रा कोड",iban:"IBAN",jwt:"JWT",template_literal:"इनपुट"},n={nan:"NaN"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;return`अमान्य इनपुट: अपेक्षित ${t}, प्राप्त ${a}`}case"invalid_value":if(1===i.values.length)return`अमान्य इनपुट: अपेक्षित ${G(i.values[0])}`;return`अमान्य विकल्प: अपेक्षित मानहरू मध्ये एक ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`धेरै ठूलो: ${i.origin??"मान"} मा ${r}${i.maximum.toString()} ${n.unit} ${n.verb}`;return`धेरै ठूलो: ${i.origin??"मान"} ${r}${i.maximum.toString()} हुनुपर्छ`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`धेरै सानो: ${i.origin} मा ${r}${i.minimum.toString()} ${n.unit} ${n.verb}`;return`धेरै सानो: ${i.origin} ${r}${i.minimum.toString()} हुनुपर्छ`}case"invalid_format":if("starts_with"===i.format)return`अमान्य स्ट्रिङ: "${i.prefix}" बाट सुरु हुनुपर्छ`;if("ends_with"===i.format)return`अमान्य स्ट्रिङ: "${i.suffix}" मा समाप्त हुनुपर्छ`;if("includes"===i.format)return`अमान्य स्ट्रिङ: "${i.includes}" समावेश हुनुपर्छ`;if("regex"===i.format)return`अमान्य स्ट्रिङ: ढाँचा ${i.pattern} सँग मेल खानुपर्छ`;return`अमान्य ${r[i.format]??i.format}`;case"not_multiple_of":return`अमान्य संख्या: ${i.divisor} को गुणज हुनुपर्छ`;case"unrecognized_keys":return`अपरिचित कुञ्जी${i.keys.length>1?"हरू":""}: ${d(i.keys,", ")}`;case"invalid_key":return`अमान्य कुञ्जी: ${i.origin} मा`;case"invalid_union":if(i.options&&Array.isArray(i.options)&&i.options.length>0){let t=i.options.map(t=>`'${t}'`).join(" | ");return`अमान्य डिस्क्रिमिनेटर मान: अपेक्षित ${t}`}return"अमान्य इनपुट";case"invalid_element":return`अमान्य मान: ${i.origin} मा`;default:return"अमान्य इनपुट"}})}},"nl",0,function(){let t,r,n;return{localeError:(t={string:{unit:"tekens",verb:"heeft"},file:{unit:"bytes",verb:"heeft"},array:{unit:"elementen",verb:"heeft"},set:{unit:"elementen",verb:"heeft"},map:{unit:"elementen",verb:"heeft"}},r={regex:"invoer",email:"emailadres",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO datum en tijd",date:"ISO datum",time:"ISO tijd",duration:"ISO duur",ipv4:"IPv4-adres",ipv6:"IPv6-adres",mac:"MAC-adres",cidrv4:"IPv4-bereik",cidrv6:"IPv6-bereik",base64:"base64-gecodeerde tekst",base64url:"base64 URL-gecodeerde tekst",json_string:"JSON string",e164:"E.164-nummer",credit_card:"creditcardnummer",currency_code:"valutacode",iban:"IBAN",jwt:"JWT",template_literal:"invoer"},n={nan:"NaN",number:"getal"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Ongeldige invoer: verwacht instanceof ${i.expected}, ontving ${a}`;return`Ongeldige invoer: verwacht ${t}, ontving ${a}`}case"invalid_value":if(1===i.values.length)return`Ongeldige invoer: verwacht ${G(i.values[0])}`;return`Ongeldige optie: verwacht \xe9\xe9n van ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null,a="date"===i.origin?"laat":"string"===i.origin?"lang":"groot";if(n)return`Te ${a}: verwacht dat ${i.origin??"waarde"} ${r}${i.maximum.toString()} ${n.unit??"elementen"} ${n.verb}`;return`Te ${a}: verwacht dat ${i.origin??"waarde"} ${r}${i.maximum.toString()} is`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null,a="date"===i.origin?"vroeg":"string"===i.origin?"kort":"klein";if(n)return`Te ${a}: verwacht dat ${i.origin} ${r}${i.minimum.toString()} ${n.unit} ${n.verb}`;return`Te ${a}: verwacht dat ${i.origin} ${r}${i.minimum.toString()} is`}case"invalid_format":if("starts_with"===i.format)return`Ongeldige tekst: moet met "${i.prefix}" beginnen`;if("ends_with"===i.format)return`Ongeldige tekst: moet op "${i.suffix}" eindigen`;if("includes"===i.format)return`Ongeldige tekst: moet "${i.includes}" bevatten`;if("regex"===i.format)return`Ongeldige tekst: moet overeenkomen met patroon ${i.pattern}`;return`Ongeldig: ${r[i.format]??i.format}`;case"not_multiple_of":return`Ongeldig getal: moet een veelvoud van ${i.divisor} zijn`;case"unrecognized_keys":return`Onbekende key${i.keys.length>1?"s":""}: ${d(i.keys,", ")}`;case"invalid_key":return`Ongeldige key in ${i.origin}`;case"invalid_union":default:return"Ongeldige invoer";case"invalid_element":return`Ongeldige waarde in ${i.origin}`}})}},"nn",0,function(){let t,r,n;return{localeError:(t={string:{unit:"teikn",verb:"å ha"},file:{unit:"bytes",verb:"å ha"},array:{unit:"element",verb:"å innehalde"},set:{unit:"element",verb:"å innehalde"},map:{unit:"element",verb:"å innehalde"}},r={regex:"input",email:"e-postadresse",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO dato- og klokkeslett",date:"ISO-dato",time:"ISO-klokkeslett",duration:"ISO-varigheit",ipv4:"IPv4-adresse",ipv6:"IPv6-adresse",mac:"MAC-adresse",cidrv4:"IPv4-spekter",cidrv6:"IPv6-spekter",base64:"base64-enkoda streng",base64url:"base64url-enkoda streng",json_string:"JSON-streng",e164:"E.164-nummer",credit_card:"kredittkortnummer",currency_code:"valutakode",iban:"IBAN",jwt:"JWT",template_literal:"input"},n={nan:"NaN",number:"tal",array:"liste"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Ugyldig input: forventa instanceof ${i.expected}, fekk ${a}`;return`Ugyldig input: forventa ${t}, fekk ${a}`}case"invalid_value":if(1===i.values.length)return`Ugyldig verdi: forventa ${G(i.values[0])}`;return`Ugyldig val: forventa eitt av ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`For stor(t): forventa ${i.origin??"value"} til \xe5 ha ${r}${i.maximum.toString()} ${n.unit??"element"}`;return`For stor(t): forventa ${i.origin??"value"} til \xe5 ha ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`For lite(n): forventa ${i.origin} til \xe5 ha ${r}${i.minimum.toString()} ${n.unit}`;return`For lite(n): forventa ${i.origin} til \xe5 ha ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ugyldig streng: m\xe5 starte med "${i.prefix}"`;if("ends_with"===i.format)return`Ugyldig streng: m\xe5 slutte med "${i.suffix}"`;if("includes"===i.format)return`Ugyldig streng: m\xe5 innehalde "${i.includes}"`;if("regex"===i.format)return`Ugyldig streng: m\xe5 matche m\xf8nsteret ${i.pattern}`;return`Ugyldig ${r[i.format]??i.format}`;case"not_multiple_of":return`Ugyldig tal: m\xe5 vere eit multiplum av ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Ukjende nøklar":"Ukjend nøkkel"}: ${d(i.keys,", ")}`;case"invalid_key":return`Ugyldig n\xf8kkel i ${i.origin}`;case"invalid_union":default:return"Ugyldig input";case"invalid_element":return`Ugyldig verdi i ${i.origin}`}})}},"no",0,function(){let t,r,n;return{localeError:(t={string:{unit:"tegn",verb:"å ha"},file:{unit:"bytes",verb:"å ha"},array:{unit:"elementer",verb:"å inneholde"},set:{unit:"elementer",verb:"å inneholde"},map:{unit:"elementer",verb:"å inneholde"}},r={regex:"input",email:"e-postadresse",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO dato- og klokkeslett",date:"ISO-dato",time:"ISO-klokkeslett",duration:"ISO-varighet",ipv4:"IPv4-adresse",ipv6:"IPv6-adresse",mac:"MAC-adresse",cidrv4:"IPv4-spekter",cidrv6:"IPv6-spekter",base64:"base64-enkodet streng",base64url:"base64url-enkodet streng",json_string:"JSON-streng",e164:"E.164-nummer",credit_card:"kredittkortnummer",currency_code:"valutakode",iban:"IBAN",jwt:"JWT",template_literal:"input"},n={nan:"NaN",number:"tall",array:"liste"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Ugyldig input: forventet instanceof ${i.expected}, fikk ${a}`;return`Ugyldig input: forventet ${t}, fikk ${a}`}case"invalid_value":if(1===i.values.length)return`Ugyldig verdi: forventet ${G(i.values[0])}`;return`Ugyldig valg: forventet en av ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`For stor(t): forventet ${i.origin??"value"} til \xe5 ha ${r}${i.maximum.toString()} ${n.unit??"elementer"}`;return`For stor(t): forventet ${i.origin??"value"} til \xe5 ha ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`For lite(n): forventet ${i.origin} til \xe5 ha ${r}${i.minimum.toString()} ${n.unit}`;return`For lite(n): forventet ${i.origin} til \xe5 ha ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ugyldig streng: m\xe5 starte med "${i.prefix}"`;if("ends_with"===i.format)return`Ugyldig streng: m\xe5 ende med "${i.suffix}"`;if("includes"===i.format)return`Ugyldig streng: m\xe5 inneholde "${i.includes}"`;if("regex"===i.format)return`Ugyldig streng: m\xe5 matche m\xf8nsteret ${i.pattern}`;return`Ugyldig ${r[i.format]??i.format}`;case"not_multiple_of":return`Ugyldig tall: m\xe5 v\xe6re et multiplum av ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Ukjente nøkler":"Ukjent nøkkel"}: ${d(i.keys,", ")}`;case"invalid_key":return`Ugyldig n\xf8kkel i ${i.origin}`;case"invalid_union":default:return"Ugyldig input";case"invalid_element":return`Ugyldig verdi i ${i.origin}`}})}},"ota",0,function(){let t,r,n;return{localeError:(t={string:{unit:"harf",verb:"olmalıdır"},file:{unit:"bayt",verb:"olmalıdır"},array:{unit:"unsur",verb:"olmalıdır"},set:{unit:"unsur",verb:"olmalıdır"},map:{unit:"unsur",verb:"olmalıdır"}},r={regex:"giren",email:"epostagâh",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO hengâmı",date:"ISO tarihi",time:"ISO zamanı",duration:"ISO müddeti",ipv4:"IPv4 nişânı",ipv6:"IPv6 nişânı",mac:"MAC nişânı",cidrv4:"IPv4 menzili",cidrv6:"IPv6 menzili",base64:"base64-şifreli metin",base64url:"base64url-şifreli metin",json_string:"JSON metin",e164:"E.164 sayısı",credit_card:"i'tibâr kartı numarası",currency_code:"para birimi kodu",iban:"IBAN",jwt:"JWT",template_literal:"giren"},n={nan:"NaN",number:"numara",array:"saf",null:"gayb"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`F\xe2sit giren: umulan instanceof ${i.expected}, alınan ${a}`;return`F\xe2sit giren: umulan ${t}, alınan ${a}`}case"invalid_value":if(1===i.values.length)return`F\xe2sit giren: umulan ${G(i.values[0])}`;return`F\xe2sit tercih: m\xfbteberler ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`Fazla b\xfcy\xfck: ${i.origin??"value"}, ${r}${i.maximum.toString()} ${n.unit??"elements"} sahip olmalıydı.`;return`Fazla b\xfcy\xfck: ${i.origin??"value"}, ${r}${i.maximum.toString()} olmalıydı.`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`Fazla k\xfc\xe7\xfck: ${i.origin}, ${r}${i.minimum.toString()} ${n.unit} sahip olmalıydı.`;return`Fazla k\xfc\xe7\xfck: ${i.origin}, ${r}${i.minimum.toString()} olmalıydı.`}case"invalid_format":if("starts_with"===i.format)return`F\xe2sit metin: "${i.prefix}" ile başlamalı.`;if("ends_with"===i.format)return`F\xe2sit metin: "${i.suffix}" ile bitmeli.`;if("includes"===i.format)return`F\xe2sit metin: "${i.includes}" ihtiv\xe2 etmeli.`;if("regex"===i.format)return`F\xe2sit metin: ${i.pattern} nakşına uymalı.`;return`F\xe2sit ${r[i.format]??i.format}`;case"not_multiple_of":return`F\xe2sit sayı: ${i.divisor} katı olmalıydı.`;case"unrecognized_keys":return`Tanınmayan anahtar ${i.keys.length>1?"s":""}: ${d(i.keys,", ")}`;case"invalid_key":return`${i.origin} i\xe7in tanınmayan anahtar var.`;case"invalid_union":return"Giren tanınamadı.";case"invalid_element":return`${i.origin} i\xe7in tanınmayan kıymet var.`;default:return"Kıymet tanınamadı."}})}},"pl",0,function(){let t,r,n;return{localeError:(t={string:{unit:"znaków",verb:"mieć"},file:{unit:"bajtów",verb:"mieć"},array:{unit:"elementów",verb:"mieć"},set:{unit:"elementów",verb:"mieć"},map:{unit:"elementów",verb:"mieć"}},r={regex:"wyrażenie",email:"adres email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data i godzina w formacie ISO",date:"data w formacie ISO",time:"godzina w formacie ISO",duration:"czas trwania ISO",ipv4:"adres IPv4",ipv6:"adres IPv6",mac:"adres MAC",cidrv4:"zakres IPv4",cidrv6:"zakres IPv6",base64:"ciąg znaków zakodowany w formacie base64",base64url:"ciąg znaków zakodowany w formacie base64url",json_string:"ciąg znaków w formacie JSON",e164:"liczba E.164",credit_card:"numer karty kredytowej",currency_code:"kod waluty",iban:"IBAN",jwt:"JWT",template_literal:"wejście"},n={nan:"NaN",number:"liczba",array:"tablica"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Nieprawidłowe dane wejściowe: oczekiwano instanceof ${i.expected}, otrzymano ${a}`;return`Nieprawidłowe dane wejściowe: oczekiwano ${t}, otrzymano ${a}`}case"invalid_value":if(1===i.values.length)return`Nieprawidłowe dane wejściowe: oczekiwano ${G(i.values[0])}`;return`Nieprawidłowa opcja: oczekiwano jednej z wartości ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`Za duża wartość: oczekiwano, że ${i.origin??"wartość"} będzie mieć ${r}${i.maximum.toString()} ${n.unit??"elementów"}`;return`Zbyt duż(y/a/e): oczekiwano, że ${i.origin??"wartość"} będzie wynosić ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`Za mała wartość: oczekiwano, że ${i.origin??"wartość"} będzie mieć ${r}${i.minimum.toString()} ${n.unit??"elementów"}`;return`Zbyt mał(y/a/e): oczekiwano, że ${i.origin??"wartość"} będzie wynosić ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi zaczynać się od "${i.prefix}"`;if("ends_with"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi kończyć się na "${i.suffix}"`;if("includes"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi zawierać "${i.includes}"`;if("regex"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi odpowiadać wzorcowi ${i.pattern}`;return`Nieprawidłow(y/a/e) ${r[i.format]??i.format}`;case"not_multiple_of":return`Nieprawidłowa liczba: musi być wielokrotnością ${i.divisor}`;case"unrecognized_keys":return`Nierozpoznane klucze${i.keys.length>1?"s":""}: ${d(i.keys,", ")}`;case"invalid_key":return`Nieprawidłowy klucz w ${i.origin}`;case"invalid_union":default:return"Nieprawidłowe dane wejściowe";case"invalid_element":return`Nieprawidłowa wartość w ${i.origin}`}})}},"ps",0,function(){let t,r,n;return{localeError:(t={string:{unit:"توکي",verb:"ولري"},file:{unit:"بایټس",verb:"ولري"},array:{unit:"توکي",verb:"ولري"},set:{unit:"توکي",verb:"ولري"},map:{unit:"توکي",verb:"ولري"}},r={regex:"ورودي",email:"بریښنالیک",url:"یو آر ال",emoji:"ایموجي",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"نیټه او وخت",date:"نېټه",time:"وخت",duration:"موده",ipv4:"د IPv4 پته",ipv6:"د IPv6 پته",mac:"د MAC پته",cidrv4:"د IPv4 ساحه",cidrv6:"د IPv6 ساحه",base64:"base64-encoded متن",base64url:"base64url-encoded متن",json_string:"JSON متن",e164:"د E.164 شمېره",credit_card:"د کریډیټ کارت شمیره",currency_code:"د اسعارو کوډ",iban:"IBAN",jwt:"JWT",template_literal:"ورودي"},n={nan:"NaN",number:"عدد",array:"ارې"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`ناسم ورودي: باید instanceof ${i.expected} وای, مګر ${a} ترلاسه شو`;return`ناسم ورودي: باید ${t} وای, مګر ${a} ترلاسه شو`}case"invalid_value":if(1===i.values.length)return`ناسم ورودي: باید ${G(i.values[0])} وای`;return`ناسم انتخاب: باید یو له ${d(i.values,"|")} څخه وای`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`ډیر لوی: ${i.origin??"ارزښت"} باید ${r}${i.maximum.toString()} ${n.unit??"عنصرونه"} ولري`;return`ډیر لوی: ${i.origin??"ارزښت"} باید ${r}${i.maximum.toString()} وي`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`ډیر کوچنی: ${i.origin} باید ${r}${i.minimum.toString()} ${n.unit} ولري`;return`ډیر کوچنی: ${i.origin} باید ${r}${i.minimum.toString()} وي`}case"invalid_format":if("starts_with"===i.format)return`ناسم متن: باید د "${i.prefix}" سره پیل شي`;if("ends_with"===i.format)return`ناسم متن: باید د "${i.suffix}" سره پای ته ورسيږي`;if("includes"===i.format)return`ناسم متن: باید "${i.includes}" ولري`;if("regex"===i.format)return`ناسم متن: باید د ${i.pattern} سره مطابقت ولري`;return`${r[i.format]??i.format} ناسم دی`;case"not_multiple_of":return`ناسم عدد: باید د ${i.divisor} مضرب وي`;case"unrecognized_keys":return`ناسم ${i.keys.length>1?"کلیډونه":"کلیډ"}: ${d(i.keys,", ")}`;case"invalid_key":return`ناسم کلیډ په ${i.origin} کې`;case"invalid_union":default:return"ناسمه ورودي";case"invalid_element":return`ناسم عنصر په ${i.origin} کې`}})}},"pt",0,function(){return{localeError:(()=>{let t={string:{unit:"caracteres"},file:{unit:"bytes"},array:{unit:"elementos"},set:{unit:"elementos"},map:{unit:"entradas"}},r={regex:"a entrada",email:"o endereço de e-mail",url:"o URL",emoji:"o emoji",uuid:"o UUID",uuidv4:"o UUIDv4",uuidv6:"o UUIDv6",nanoid:"o nanoid",guid:"o GUID",cuid:"o cuid",cuid2:"o cuid2",ulid:"o ULID",xid:"o XID",ksuid:"o KSUID",datetime:"a data e hora ISO",date:"a data ISO",time:"a hora ISO",duration:"a duração ISO",ipv4:"o endereço IPv4",ipv6:"o endereço IPv6",mac:"o endereço MAC",cidrv4:"o intervalo de endereços IPv4",cidrv6:"o intervalo de endereços IPv6",base64:"o texto codificado em base64",base64url:"o texto codificado em base64url",json_string:"o texto JSON",e164:"o número E.164",credit_card:"o número de cartão de crédito",currency_code:"o código de moeda",iban:"o IBAN",jwt:"o JWT",template_literal:"a entrada"},n={definite:"o",indefinite:"um"},i={definite:"a",indefinite:"uma"},a={string:{name:"texto",articles:n},number:{name:"número",articles:n},int:{name:"número inteiro",articles:n},boolean:{name:"valor booleano",articles:n},bigint:{name:"número bigint",articles:n},symbol:{name:"símbolo",articles:n},undefined:{name:'valor "undefined"',articles:n},null:{name:'valor "nulo"',articles:n},never:{name:'valor "never"',articles:n},void:{name:'valor "void"',articles:n},date:{name:"data",articles:i},array:{name:"vetor",articles:n},object:{name:"objeto",articles:n},tuple:{name:"tuplo",articles:n},record:{name:"registo",articles:n},map:{name:"mapa",articles:n},set:{name:"conjunto",articles:n},file:{name:"ficheiro",articles:n},nonoptional:{name:"valor não opcional",articles:n},nan:{name:'valor "NaN"',articles:n},function:{name:"função",articles:i}};function o(t,r){let i=a[t]??{name:`valor "${t}"`,articles:n};return`${i.articles[r]} ${i.name}`}return n=>{switch(n.code){case"invalid_type":{let t=o(n.expected,"indefinite"),r=o(eg(n.input),"indefinite");return`Entrada inv\xe1lida: esperava ${t}, recebeu ${r}`}case"invalid_value":if(1===n.values.length)return`Entrada inv\xe1lida: esperava ${G(n.values[0])}`;return`Op\xe7\xe3o inv\xe1lida: esperava uma das seguintes op\xe7\xf5es: ${d(n.values,"|")}`;case"too_big":{let r=n.inclusive?"<=":"<",i=t[n.origin]??null;if(i)return`Demasiado grande: esperava que ${o(n.origin,"definite")} tivesse ${r} ${n.maximum.toString()} ${i.unit??"elementos"}`;return`Demasiado grande: esperava que ${o(n.origin,"definite")} fosse ${r} ${n.maximum.toString()}`}case"too_small":{let r=n.inclusive?">=":">",i=t[n.origin]??null;if(i)return`Demasiado pequeno: esperava que ${o(n.origin,"definite")} tivesse ${r} ${n.minimum.toString()} ${i.unit??"elementos"}`;return`Demasiado pequeno: esperava que ${o(n.origin,"definite")} fosse ${r} ${n.minimum.toString()}`}case"invalid_format":if("starts_with"===n.format)return`Texto inv\xe1lido: deve come\xe7ar por "${n.prefix}"`;if("ends_with"===n.format)return`Texto inv\xe1lido: deve terminar em "${n.suffix}"`;if("includes"===n.format)return`Texto inv\xe1lido: deve incluir "${n.includes}"`;if("regex"===n.format)return`Texto inv\xe1lido: deve corresponder ao padr\xe3o ${n.pattern}`;return`Formato d${r[n.format]??n.format} inv\xe1lido`;case"not_multiple_of":return`N\xfamero inv\xe1lido: deve ser m\xfaltiplo de ${n.divisor}`;case"unrecognized_keys":{let t=n.keys.length>1?"s":"";return`Chave${t} inv\xe1lida${t}: ${d(n.keys,", ")}`}case"invalid_key":case"invalid_element":return`Entrada inv\xe1lida n${o(n.origin,"definite")}`;case"invalid_union":if(n.options&&Array.isArray(n.options)&&n.options.length>0){let t=n.options.map(t=>`'${t}'`).join(" | ");return`Valor de discrimina\xe7\xe3o inv\xe1lido. Esperava ${t}`}return"Entrada inválida";default:return"Entrada inválida"}}})()}},"ptBR",0,function(){return{localeError:(()=>{let t={string:{unit:"caracteres"},file:{unit:"bytes"},array:{unit:"elementos"},set:{unit:"elementos"},map:{unit:"entradas"}},r={regex:"a entrada",email:"o endereço de e-mail",url:"o URL",emoji:"o emoji",uuid:"o UUID",uuidv4:"o UUIDv4",uuidv6:"o UUIDv6",nanoid:"o nanoid",guid:"o GUID",cuid:"o cuid",cuid2:"o cuid2",ulid:"o ULID",xid:"o XID",ksuid:"o KSUID",datetime:"a data e hora ISO",date:"a data ISO",time:"a hora ISO",duration:"a duração ISO",ipv4:"o endereço IPv4",ipv6:"o endereço IPv6",mac:"o endereço MAC",cidrv4:"a faixa de endereços IPv4",cidrv6:"a faixa de endereços IPv6",base64:"o texto codificado em base64",base64url:"o texto codificado em base64url",json_string:"o texto JSON",e164:"o número E.164",credit_card:"o número de cartão de crédito",currency_code:"o código de moeda",iban:"o IBAN",jwt:"o JWT",template_literal:"a entrada"},n={definite:"o",indefinite:"um"},i={definite:"a",indefinite:"uma"},a={string:{name:"texto",articles:n},number:{name:"número",articles:n},int:{name:"número inteiro",articles:n},boolean:{name:"valor booleano",articles:n},bigint:{name:"número bigint",articles:n},symbol:{name:"símbolo",articles:n},undefined:{name:'valor "undefined"',articles:n},null:{name:'valor "nulo"',articles:n},never:{name:'valor "never"',articles:n},void:{name:'valor "void"',articles:n},date:{name:"data",articles:i},array:{name:"vetor",articles:n},object:{name:"objeto",articles:n},tuple:{name:"tupla",articles:i},record:{name:"registro",articles:n},map:{name:"mapa",articles:n},set:{name:"conjunto",articles:n},file:{name:"arquivo",articles:n},nonoptional:{name:"valor não opcional",articles:n},nan:{name:'valor "NaN"',articles:n},function:{name:"função",articles:i}};function o(t,r){let i=a[t]??{name:`valor "${t}"`,articles:n};return`${i.articles[r]} ${i.name}`}return n=>{switch(n.code){case"invalid_type":{let t=o(n.expected,"indefinite"),r=o(eg(n.input),"indefinite");return`Entrada inv\xe1lida: esperava ${t}, recebeu ${r}`}case"invalid_value":if(1===n.values.length)return`Entrada inv\xe1lida: esperava ${G(n.values[0])}`;return`Op\xe7\xe3o inv\xe1lida: esperava uma das seguintes op\xe7\xf5es: ${d(n.values,"|")}`;case"too_big":{let r=n.inclusive?"<=":"<",i=t[n.origin]??null;if(i)return`Grande demais: esperava que ${o(n.origin,"definite")} tivesse ${r} ${n.maximum.toString()} ${i.unit??"elementos"}`;return`Grande demais: esperava que ${o(n.origin,"definite")} fosse ${r} ${n.maximum.toString()}`}case"too_small":{let r=n.inclusive?">=":">",i=t[n.origin]??null;if(i)return`Pequeno demais: esperava que ${o(n.origin,"definite")} tivesse ${r} ${n.minimum.toString()} ${i.unit??"elementos"}`;return`Pequeno demais: esperava que ${o(n.origin,"definite")} fosse ${r} ${n.minimum.toString()}`}case"invalid_format":if("starts_with"===n.format)return`Texto inv\xe1lido: deve come\xe7ar com "${n.prefix}"`;if("ends_with"===n.format)return`Texto inv\xe1lido: deve terminar com "${n.suffix}"`;if("includes"===n.format)return`Texto inv\xe1lido: deve incluir "${n.includes}"`;if("regex"===n.format)return`Texto inv\xe1lido: deve corresponder ao padr\xe3o ${n.pattern}`;return`Formato d${r[n.format]??n.format} inv\xe1lido`;case"not_multiple_of":return`N\xfamero inv\xe1lido: deve ser m\xfaltiplo de ${n.divisor}`;case"unrecognized_keys":{let t=n.keys.length>1?"s":"";return`Chave${t} inv\xe1lida${t}: ${d(n.keys,", ")}`}case"invalid_key":case"invalid_element":return`Entrada inv\xe1lida n${o(n.origin,"definite")}`;case"invalid_union":if(n.options&&Array.isArray(n.options)&&n.options.length>0){let t=n.options.map(t=>`'${t}'`).join(" | ");return`Valor de discrimina\xe7\xe3o inv\xe1lido. Esperava ${t}`}return"Entrada inválida";default:return"Entrada inválida"}}})()}},"ro",0,function(){let t,r,n;return{localeError:(t={string:{unit:"caractere",verb:"să aibă"},file:{unit:"octeți",verb:"să aibă"},array:{unit:"elemente",verb:"să aibă"},set:{unit:"elemente",verb:"să aibă"},map:{unit:"intrări",verb:"să aibă"}},r={regex:"intrare",email:"adresă de email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"dată și oră ISO",date:"dată ISO",time:"oră ISO",duration:"durată ISO",ipv4:"adresă IPv4",ipv6:"adresă IPv6",mac:"adresă MAC",cidrv4:"interval IPv4",cidrv6:"interval IPv6",base64:"șir codat base64",base64url:"șir codat base64url",json_string:"șir JSON",e164:"număr E.164",credit_card:"număr de card de credit",currency_code:"cod valutar",iban:"IBAN",jwt:"JWT",template_literal:"intrare"},n={nan:"NaN",string:"șir",number:"număr",boolean:"boolean",function:"funcție",array:"matrice",object:"obiect",undefined:"nedefinit",symbol:"simbol",bigint:"număr mare",void:"void",never:"never",map:"hartă",set:"set"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;return`Intrare invalidă: așteptat ${t}, primit ${a}`}case"invalid_value":if(1===i.values.length)return`Intrare invalidă: așteptat ${G(i.values[0])}`;return`Opțiune invalidă: așteptat una dintre ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`Prea mare: așteptat ca ${i.origin??"valoarea"} ${n.verb} ${r}${i.maximum.toString()} ${n.unit??"elemente"}`;return`Prea mare: așteptat ca ${i.origin??"valoarea"} să fie ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`Prea mic: așteptat ca ${i.origin} ${n.verb} ${r}${i.minimum.toString()} ${n.unit}`;return`Prea mic: așteptat ca ${i.origin} să fie ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Șir invalid: trebuie să \xeenceapă cu "${i.prefix}"`;if("ends_with"===i.format)return`Șir invalid: trebuie să se termine cu "${i.suffix}"`;if("includes"===i.format)return`Șir invalid: trebuie să includă "${i.includes}"`;if("regex"===i.format)return`Șir invalid: trebuie să se potrivească cu modelul ${i.pattern}`;return`Format invalid: ${r[i.format]??i.format}`;case"not_multiple_of":return`Număr invalid: trebuie să fie multiplu de ${i.divisor}`;case"unrecognized_keys":return`Chei nerecunoscute: ${d(i.keys,", ")}`;case"invalid_key":return`Cheie invalidă \xeen ${i.origin}`;case"invalid_union":default:return"Intrare invalidă";case"invalid_element":return`Valoare invalidă \xeen ${i.origin}`}})}},"ru",0,function(){let t,r,n;return{localeError:(t={string:{unit:{one:"символ",few:"символа",many:"символов"},verb:"иметь"},file:{unit:{one:"байт",few:"байта",many:"байт"},verb:"иметь"},array:{unit:{one:"элемент",few:"элемента",many:"элементов"},verb:"иметь"},set:{unit:{one:"элемент",few:"элемента",many:"элементов"},verb:"иметь"},map:{unit:{one:"элемент",few:"элемента",many:"элементов"},verb:"иметь"}},r={regex:"ввод",email:"email адрес",url:"URL",emoji:"эмодзи",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO дата и время",date:"ISO дата",time:"ISO время",duration:"ISO длительность",ipv4:"IPv4 адрес",ipv6:"IPv6 адрес",mac:"MAC адрес",cidrv4:"IPv4 диапазон",cidrv6:"IPv6 диапазон",base64:"строка в формате base64",base64url:"строка в формате base64url",json_string:"JSON строка",e164:"номер E.164",credit_card:"номер кредитной карты",currency_code:"код валюты",iban:"IBAN",jwt:"JWT",template_literal:"ввод"},n={nan:"NaN",number:"число",array:"массив"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Неверный ввод: ожидалось instanceof ${i.expected}, получено ${a}`;return`Неверный ввод: ожидалось ${t}, получено ${a}`}case"invalid_value":if(1===i.values.length)return`Неверный ввод: ожидалось ${G(i.values[0])}`;return`Неверный вариант: ожидалось одно из ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n){let t=at(Number(i.maximum),n.unit.one,n.unit.few,n.unit.many);return`Слишком большое значение: ожидалось, что ${i.origin??"значение"} будет иметь ${r}${i.maximum.toString()} ${t}`}return`Слишком большое значение: ожидалось, что ${i.origin??"значение"} будет ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n){let t=at(Number(i.minimum),n.unit.one,n.unit.few,n.unit.many);return`Слишком маленькое значение: ожидалось, что ${i.origin} будет иметь ${r}${i.minimum.toString()} ${t}`}return`Слишком маленькое значение: ожидалось, что ${i.origin} будет ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Неверная строка: должна начинаться с "${i.prefix}"`;if("ends_with"===i.format)return`Неверная строка: должна заканчиваться на "${i.suffix}"`;if("includes"===i.format)return`Неверная строка: должна содержать "${i.includes}"`;if("regex"===i.format)return`Неверная строка: должна соответствовать шаблону ${i.pattern}`;return`Неверный ${r[i.format]??i.format}`;case"not_multiple_of":return`Неверное число: должно быть кратным ${i.divisor}`;case"unrecognized_keys":return`Нераспознанн${i.keys.length>1?"ые":"ый"} ключ${i.keys.length>1?"и":""}: ${d(i.keys,", ")}`;case"invalid_key":return`Неверный ключ в ${i.origin}`;case"invalid_union":default:return"Неверные входные данные";case"invalid_element":return`Неверное значение в ${i.origin}`}})}},"sk",0,function(){let t,r,n;return{localeError:(t={string:{unit:"znakov",verb:"mať"},file:{unit:"bajtov",verb:"mať"},array:{unit:"prvkov",verb:"mať"},set:{unit:"prvkov",verb:"mať"},map:{unit:"položiek",verb:"mať"}},r={regex:"regulárny výraz",email:"e-mailová adresa",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"dátum a čas vo formáte ISO",date:"dátum vo formáte ISO",time:"čas vo formáte ISO",duration:"doba trvania ISO",ipv4:"IPv4 adresa",ipv6:"IPv6 adresa",mac:"MAC adresa",cidrv4:"rozsah IPv4",cidrv6:"rozsah IPv6",base64:"reťazec zakódovaný vo formáte base64",base64url:"reťazec zakódovaný vo formáte base64url",json_string:"reťazec vo formáte JSON",e164:"číslo E.164",credit_card:"číslo kreditnej karty",currency_code:"kód meny",iban:"IBAN",jwt:"JWT",template_literal:"vstup"},n={nan:"NaN",number:"číslo",string:"reťazec",function:"funkcia",array:"pole"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Neplatn\xfd vstup: očak\xe1van\xe9 instanceof ${i.expected}, obdržan\xe9 ${a}`;return`Neplatn\xfd vstup: očak\xe1van\xe9 ${t}, obdržan\xe9 ${a}`}case"invalid_value":if(1===i.values.length)return`Neplatn\xfd vstup: očak\xe1van\xe9 ${G(i.values[0])}`;return`Neplatn\xfd vstup: očak\xe1van\xe1 jedna z hodn\xf4t ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`Hodnota je pr\xedliš veľk\xe1: ${i.origin??"hodnota"} mus\xed mať ${r}${i.maximum.toString()} ${n.unit??"prvkov"}`;return`Hodnota je pr\xedliš veľk\xe1: ${i.origin??"hodnota"} mus\xed byť ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`Hodnota je pr\xedliš mal\xe1: ${i.origin??"hodnota"} mus\xed mať ${r}${i.minimum.toString()} ${n.unit??"prvkov"}`;return`Hodnota je pr\xedliš mal\xe1: ${i.origin??"hodnota"} mus\xed byť ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Neplatn\xfd reťazec: mus\xed zač\xednať na "${i.prefix}"`;if("ends_with"===i.format)return`Neplatn\xfd reťazec: mus\xed končiť na "${i.suffix}"`;if("includes"===i.format)return`Neplatn\xfd reťazec: mus\xed obsahovať "${i.includes}"`;if("regex"===i.format)return`Neplatn\xfd reťazec: mus\xed zodpovedať vzoru ${i.pattern}`;return`Neplatn\xfd form\xe1t ${r[i.format]??i.format}`;case"not_multiple_of":return`Neplatn\xe9 č\xedslo: mus\xed byť n\xe1sobkom ${i.divisor}`;case"unrecognized_keys":return`Nezn\xe1me kl\xfače: ${d(i.keys,", ")}`;case"invalid_key":return`Neplatn\xfd kl\xfač v ${i.origin}`;case"invalid_union":default:return"Neplatný vstup";case"invalid_element":return`Neplatn\xe1 hodnota v ${i.origin}`}})}},"sl",0,function(){let t,r,n;return{localeError:(t={string:{unit:"znakov",verb:"imeti"},file:{unit:"bajtov",verb:"imeti"},array:{unit:"elementov",verb:"imeti"},set:{unit:"elementov",verb:"imeti"},map:{unit:"elementov",verb:"imeti"}},r={regex:"vnos",email:"e-poštni naslov",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO datum in čas",date:"ISO datum",time:"ISO čas",duration:"ISO trajanje",ipv4:"IPv4 naslov",ipv6:"IPv6 naslov",mac:"MAC naslov",cidrv4:"obseg IPv4",cidrv6:"obseg IPv6",base64:"base64 kodiran niz",base64url:"base64url kodiran niz",json_string:"JSON niz",e164:"E.164 številka",credit_card:"številka kreditne kartice",currency_code:"koda valute",iban:"IBAN",jwt:"JWT",template_literal:"vnos"},n={nan:"NaN",number:"število",array:"tabela"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Neveljaven vnos: pričakovano instanceof ${i.expected}, prejeto ${a}`;return`Neveljaven vnos: pričakovano ${t}, prejeto ${a}`}case"invalid_value":if(1===i.values.length)return`Neveljaven vnos: pričakovano ${G(i.values[0])}`;return`Neveljavna možnost: pričakovano eno izmed ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`Preveliko: pričakovano, da bo ${i.origin??"vrednost"} imelo ${r}${i.maximum.toString()} ${n.unit??"elementov"}`;return`Preveliko: pričakovano, da bo ${i.origin??"vrednost"} ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`Premajhno: pričakovano, da bo ${i.origin} imelo ${r}${i.minimum.toString()} ${n.unit}`;return`Premajhno: pričakovano, da bo ${i.origin} ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Neveljaven niz: mora se začeti z "${i.prefix}"`;if("ends_with"===i.format)return`Neveljaven niz: mora se končati z "${i.suffix}"`;if("includes"===i.format)return`Neveljaven niz: mora vsebovati "${i.includes}"`;if("regex"===i.format)return`Neveljaven niz: mora ustrezati vzorcu ${i.pattern}`;return`Neveljaven ${r[i.format]??i.format}`;case"not_multiple_of":return`Neveljavno število: mora biti večkratnik ${i.divisor}`;case"unrecognized_keys":return`Neprepoznan${i.keys.length>1?"i ključi":" ključ"}: ${d(i.keys,", ")}`;case"invalid_key":return`Neveljaven ključ v ${i.origin}`;case"invalid_union":default:return"Neveljaven vnos";case"invalid_element":return`Neveljavna vrednost v ${i.origin}`}})}},"sv",0,function(){let t,r,n;return{localeError:(t={string:{unit:"tecken",verb:"att ha"},file:{unit:"bytes",verb:"att ha"},array:{unit:"objekt",verb:"att innehålla"},set:{unit:"objekt",verb:"att innehålla"},map:{unit:"objekt",verb:"att innehålla"}},r={regex:"reguljärt uttryck",email:"e-postadress",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-datum och tid",date:"ISO-datum",time:"ISO-tid",duration:"ISO-varaktighet",ipv4:"IPv4-adress",ipv6:"IPv6-adress",mac:"MAC-adress",cidrv4:"IPv4-spektrum",cidrv6:"IPv6-spektrum",base64:"base64-kodad sträng",base64url:"base64url-kodad sträng",json_string:"JSON-sträng",e164:"E.164-nummer",credit_card:"kreditkortsnummer",currency_code:"valutakod",iban:"IBAN",jwt:"JWT",template_literal:"mall-literal"},n={nan:"NaN",number:"antal",array:"lista"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Ogiltig inmatning: f\xf6rv\xe4ntat instanceof ${i.expected}, fick ${a}`;return`Ogiltig inmatning: f\xf6rv\xe4ntat ${t}, fick ${a}`}case"invalid_value":if(1===i.values.length)return`Ogiltig inmatning: f\xf6rv\xe4ntat ${G(i.values[0])}`;return`Ogiltigt val: f\xf6rv\xe4ntade en av ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`F\xf6r stor(t): f\xf6rv\xe4ntade ${i.origin??"värdet"} att ha ${r}${i.maximum.toString()} ${n.unit??"element"}`;return`F\xf6r stor(t): f\xf6rv\xe4ntat ${i.origin??"värdet"} att ha ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`F\xf6r lite(t): f\xf6rv\xe4ntade ${i.origin??"värdet"} att ha ${r}${i.minimum.toString()} ${n.unit}`;return`F\xf6r lite(t): f\xf6rv\xe4ntade ${i.origin??"värdet"} att ha ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ogiltig str\xe4ng: m\xe5ste b\xf6rja med "${i.prefix}"`;if("ends_with"===i.format)return`Ogiltig str\xe4ng: m\xe5ste sluta med "${i.suffix}"`;if("includes"===i.format)return`Ogiltig str\xe4ng: m\xe5ste inneh\xe5lla "${i.includes}"`;if("regex"===i.format)return`Ogiltig str\xe4ng: m\xe5ste matcha m\xf6nstret "${i.pattern}"`;return`Ogiltig(t) ${r[i.format]??i.format}`;case"not_multiple_of":return`Ogiltigt tal: m\xe5ste vara en multipel av ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Okända nycklar":"Okänd nyckel"}: ${d(i.keys,", ")}`;case"invalid_key":return`Ogiltig nyckel i ${i.origin??"värdet"}`;case"invalid_union":default:return"Ogiltig input";case"invalid_element":return`Ogiltigt v\xe4rde i ${i.origin??"värdet"}`}})}},"ta",0,function(){let t,r,n;return{localeError:(t={string:{unit:"எழுத்துக்கள்",verb:"கொண்டிருக்க வேண்டும்"},file:{unit:"பைட்டுகள்",verb:"கொண்டிருக்க வேண்டும்"},array:{unit:"உறுப்புகள்",verb:"கொண்டிருக்க வேண்டும்"},set:{unit:"உறுப்புகள்",verb:"கொண்டிருக்க வேண்டும்"},map:{unit:"உறுப்புகள்",verb:"கொண்டிருக்க வேண்டும்"}},r={regex:"உள்ளீடு",email:"மின்னஞ்சல் முகவரி",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO தேதி நேரம்",date:"ISO தேதி",time:"ISO நேரம்",duration:"ISO கால அளவு",ipv4:"IPv4 முகவரி",ipv6:"IPv6 முகவரி",mac:"MAC முகவரி",cidrv4:"IPv4 வரம்பு",cidrv6:"IPv6 வரம்பு",base64:"base64-encoded சரம்",base64url:"base64url-encoded சரம்",json_string:"JSON சரம்",e164:"E.164 எண்",credit_card:"கடன் அட்டை எண்",currency_code:"நாணயக் குறியீடு",iban:"IBAN",jwt:"JWT",template_literal:"input"},n={nan:"NaN",number:"எண்",array:"அணி",null:"வெறுமை"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`தவறான உள்ளீடு: எதிர்பார்க்கப்பட்டது instanceof ${i.expected}, பெறப்பட்டது ${a}`;return`தவறான உள்ளீடு: எதிர்பார்க்கப்பட்டது ${t}, பெறப்பட்டது ${a}`}case"invalid_value":if(1===i.values.length)return`தவறான உள்ளீடு: எதிர்பார்க்கப்பட்டது ${G(i.values[0])}`;return`தவறான விருப்பம்: எதிர்பார்க்கப்பட்டது ${d(i.values,"|")} இல் ஒன்று`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`மிக பெரியது: எதிர்பார்க்கப்பட்டது ${i.origin??"மதிப்பு"} ${r}${i.maximum.toString()} ${n.unit??"உறுப்புகள்"} ஆக இருக்க வேண்டும்`;return`மிக பெரியது: எதிர்பார்க்கப்பட்டது ${i.origin??"மதிப்பு"} ${r}${i.maximum.toString()} ஆக இருக்க வேண்டும்`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`மிகச் சிறியது: எதிர்பார்க்கப்பட்டது ${i.origin} ${r}${i.minimum.toString()} ${n.unit} ஆக இருக்க வேண்டும்`;return`மிகச் சிறியது: எதிர்பார்க்கப்பட்டது ${i.origin} ${r}${i.minimum.toString()} ஆக இருக்க வேண்டும்`}case"invalid_format":if("starts_with"===i.format)return`தவறான சரம்: "${i.prefix}" இல் தொடங்க வேண்டும்`;if("ends_with"===i.format)return`தவறான சரம்: "${i.suffix}" இல் முடிவடைய வேண்டும்`;if("includes"===i.format)return`தவறான சரம்: "${i.includes}" ஐ உள்ளடக்க வேண்டும்`;if("regex"===i.format)return`தவறான சரம்: ${i.pattern} முறைபாட்டுடன் பொருந்த வேண்டும்`;return`தவறான ${r[i.format]??i.format}`;case"not_multiple_of":return`தவறான எண்: ${i.divisor} இன் பலமாக இருக்க வேண்டும்`;case"unrecognized_keys":return`அடையாளம் தெரியாத விசை${i.keys.length>1?"கள்":""}: ${d(i.keys,", ")}`;case"invalid_key":return`${i.origin} இல் தவறான விசை`;case"invalid_union":default:return"தவறான உள்ளீடு";case"invalid_element":return`${i.origin} இல் தவறான மதிப்பு`}})}},"tg",0,function(){let t,r,n;return{localeError:(t={string:{unit:"аломат",verb:"дошта бошад"},file:{unit:"байт",verb:"дошта бошад"},array:{unit:"унсур",verb:"дошта бошад"},set:{unit:"унсур",verb:"дошта бошад"},map:{unit:"сабт",verb:"дошта бошад"}},r={regex:"вуруд",email:"суроғаи email",url:"URL",emoji:"эмоҷи",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"санаву вақти ISO",date:"санаи ISO",time:"вақти ISO",duration:"давомнокии ISO",ipv4:"суроғаи IPv4",ipv6:"суроғаи IPv6",mac:"суроғаи MAC",cidrv4:"маҳдудаи IPv4",cidrv6:"маҳдудаи IPv6",base64:"сатри дар формати base64",base64url:"сатри дар формати base64url",json_string:"сатри JSON",e164:"рақами E.164",credit_card:"рақами корти кредитӣ",currency_code:"рамзи асъор",iban:"IBAN",jwt:"JWT",template_literal:"вуруд"},n={nan:"NaN",number:"рақам",string:"сатр",array:"массив",object:"объект",date:"сана"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;return`Вуруди нодуруст: ${t} интизор мерафт, ${a} гирифта шуд`}case"invalid_value":if(1===i.values.length)return`Вуруди нодуруст: ${G(i.values[0])} интизор мерафт`;return`Интихоби нодуруст: яке аз ${d(i.values,"|")} интизор мерафт`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`Хеле калон: ${i.origin??"қимат"} бояд ${r}${i.maximum.toString()} ${n.unit} ${n.verb}`;return`Хеле калон: ${i.origin??"қимат"} бояд ${r}${i.maximum.toString()} бошад`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`Хеле хурд: ${i.origin} бояд ${r}${i.minimum.toString()} ${n.unit} ${n.verb}`;return`Хеле хурд: ${i.origin} бояд ${r}${i.minimum.toString()} бошад`}case"invalid_format":if("starts_with"===i.format)return`Сатри нодуруст: бояд бо "${i.prefix}" оғоз шавад`;if("ends_with"===i.format)return`Сатри нодуруст: бояд бо "${i.suffix}" анҷом ёбад`;if("includes"===i.format)return`Сатри нодуруст: бояд "${i.includes}"-ро дар бар гирад`;if("regex"===i.format)return`Сатри нодуруст: бояд ба намунаи ${i.pattern} мувофиқат кунад`;return`${r[i.format]??i.format}-и нодуруст`;case"not_multiple_of":return`Рақами нодуруст: бояд ба ${i.divisor} бе бақия тақсим шавад`;case"unrecognized_keys":return`Калид${i.keys.length>1?"ҳои":"и"} номаълум: ${d(i.keys,", ")}`;case"invalid_key":return`Калиди нодуруст дар ${i.origin}`;case"invalid_union":if(i.options&&Array.isArray(i.options)&&i.options.length>0){let t=i.options.map(t=>`'${t}'`).join(" | ");return`Қимати нодурусти дискриминатор: ${t} интизор мерафт`}return"Вуруди нодуруст";case"invalid_element":return`Қимати нодуруст дар ${i.origin}`;default:return"Вуруди нодуруст"}})}},"th",0,function(){let t,r,n;return{localeError:(t={string:{unit:"ตัวอักษร",verb:"ควรมี"},file:{unit:"ไบต์",verb:"ควรมี"},array:{unit:"รายการ",verb:"ควรมี"},set:{unit:"รายการ",verb:"ควรมี"},map:{unit:"รายการ",verb:"ควรมี"}},r={regex:"ข้อมูลที่ป้อน",email:"ที่อยู่อีเมล",url:"URL",emoji:"อิโมจิ",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"วันที่เวลาแบบ ISO",date:"วันที่แบบ ISO",time:"เวลาแบบ ISO",duration:"ช่วงเวลาแบบ ISO",ipv4:"ที่อยู่ IPv4",ipv6:"ที่อยู่ IPv6",mac:"ที่อยู่ MAC",cidrv4:"ช่วง IP แบบ IPv4",cidrv6:"ช่วง IP แบบ IPv6",base64:"ข้อความแบบ Base64",base64url:"ข้อความแบบ Base64 สำหรับ URL",json_string:"ข้อความแบบ JSON",e164:"เบอร์โทรศัพท์ระหว่างประเทศ (E.164)",credit_card:"หมายเลขบัตรเครดิต",currency_code:"รหัสสกุลเงิน",iban:"IBAN",jwt:"โทเคน JWT",template_literal:"ข้อมูลที่ป้อน"},n={nan:"NaN",number:"ตัวเลข",array:"อาร์เรย์ (Array)",null:"ไม่มีค่า (null)"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`ประเภทข้อมูลไม่ถูกต้อง: ควรเป็น instanceof ${i.expected} แต่ได้รับ ${a}`;return`ประเภทข้อมูลไม่ถูกต้อง: ควรเป็น ${t} แต่ได้รับ ${a}`}case"invalid_value":if(1===i.values.length)return`ค่าไม่ถูกต้อง: ควรเป็น ${G(i.values[0])}`;return`ตัวเลือกไม่ถูกต้อง: ควรเป็นหนึ่งใน ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"ไม่เกิน":"น้อยกว่า",n=t[i.origin]??null;if(n)return`เกินกำหนด: ${i.origin??"ค่า"} ควรมี${r} ${i.maximum.toString()} ${n.unit??"รายการ"}`;return`เกินกำหนด: ${i.origin??"ค่า"} ควรมี${r} ${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?"อย่างน้อย":"มากกว่า",n=t[i.origin]??null;if(n)return`น้อยกว่ากำหนด: ${i.origin} ควรมี${r} ${i.minimum.toString()} ${n.unit}`;return`น้อยกว่ากำหนด: ${i.origin} ควรมี${r} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`รูปแบบไม่ถูกต้อง: ข้อความต้องขึ้นต้นด้วย "${i.prefix}"`;if("ends_with"===i.format)return`รูปแบบไม่ถูกต้อง: ข้อความต้องลงท้ายด้วย "${i.suffix}"`;if("includes"===i.format)return`รูปแบบไม่ถูกต้อง: ข้อความต้องมี "${i.includes}" อยู่ในข้อความ`;if("regex"===i.format)return`รูปแบบไม่ถูกต้อง: ต้องตรงกับรูปแบบที่กำหนด ${i.pattern}`;return`รูปแบบไม่ถูกต้อง: ${r[i.format]??i.format}`;case"not_multiple_of":return`ตัวเลขไม่ถูกต้อง: ต้องเป็นจำนวนที่หารด้วย ${i.divisor} ได้ลงตัว`;case"unrecognized_keys":return`พบคีย์ที่ไม่รู้จัก: ${d(i.keys,", ")}`;case"invalid_key":return`คีย์ไม่ถูกต้องใน ${i.origin}`;case"invalid_union":return"ข้อมูลไม่ถูกต้อง: ไม่ตรงกับรูปแบบยูเนียนที่กำหนดไว้";case"invalid_element":return`ข้อมูลไม่ถูกต้องใน ${i.origin}`;default:return"ข้อมูลไม่ถูกต้อง"}})}},"tk",0,function(){let t,r,n;return{localeError:(t={string:{unit:"simwol",verb:"bolmaly"},file:{unit:"baýt",verb:"bolmaly"},array:{unit:"elementler",verb:"bolmaly"},set:{unit:"elementler",verb:"bolmaly"},map:{unit:"elementler",verb:"bolmaly"}},r={regex:"giriş",email:"e-poçta salgysy",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO sene we wagt",date:"ISO sene",time:"ISO wagt",duration:"ISO wagt aralygy",ipv4:"IPv4 salgysy",ipv6:"IPv6 salgysy",mac:"MAC salgysy",cidrv4:"IPv4 aralygy",cidrv6:"IPv6 aralygy",base64:"base64 bilen şifrlenen setir",base64url:"base64url bilen şifrlenen setir",json_string:"JSON setiri",e164:"E.164 nomeri",credit_card:"kredit kartynyň nomeri",currency_code:"walýuta kody",iban:"IBAN",jwt:"JWT",template_literal:"şablon"},n={nan:"NaN"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;return`N\xe4dogry baha: garaşylan ${t} \xfderine ${a} alyndy`}case"invalid_value":if(1===i.values.length)return`N\xe4dogry baha: ${G(i.values[0])} bolmaly`;return`N\xe4dogry sa\xfdlaw: aşakdakylardan biri bolmaly: ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`Has uly: garaşyl\xfdan ${i.origin??"baha"} ${r} ${i.maximum.toString()} ${n.unit??"element"}`;return`Has uly: garaşyl\xfdan ${i.origin??"baha"} ${r} ${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`Has ki\xe7i: garaşyl\xfdan ${i.origin} ${r} ${i.minimum.toString()} ${n.unit}`;return`Has ki\xe7i: garaşyl\xfdan ${i.origin} ${r} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`N\xe4dogry setir: "${i.prefix}" bilen başlamaly`;if("ends_with"===i.format)return`N\xe4dogry setir: "${i.suffix}" bilen gutarmaly`;if("includes"===i.format)return`N\xe4dogry setir: "${i.includes}" saklamaly`;if("regex"===i.format)return`N\xe4dogry setir: ${i.pattern} nusga la\xfdyk bolmaly`;return`N\xe4dogry ${r[i.format]??i.format}`;case"not_multiple_of":return`N\xe4dogry san: ${i.divisor} bilen galyndysyz b\xf6l\xfcnmeli`;case"unrecognized_keys":return`Tanalma\xfdan a\xe7ar${i.keys.length>1?"lar":""}: ${d(i.keys,", ")}`;case"invalid_key":return`${i.origin} i\xe7inde n\xe4dogry a\xe7ar`;case"invalid_union":default:return"Nädogry baha";case"invalid_element":return`${i.origin} i\xe7inde n\xe4dogry baha`}})}},"tr",0,function(){let t,r,n;return{localeError:(t={string:{unit:"karakter",verb:"olmalı"},file:{unit:"bayt",verb:"olmalı"},array:{unit:"öğe",verb:"olmalı"},set:{unit:"öğe",verb:"olmalı"},map:{unit:"öğe",verb:"olmalı"}},r={regex:"girdi",email:"e-posta adresi",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO tarih ve saat",date:"ISO tarih",time:"ISO saat",duration:"ISO süre",ipv4:"IPv4 adresi",ipv6:"IPv6 adresi",mac:"MAC adresi",cidrv4:"IPv4 aralığı",cidrv6:"IPv6 aralığı",base64:"base64 ile şifrelenmiş metin",base64url:"base64url ile şifrelenmiş metin",json_string:"JSON dizesi",e164:"E.164 sayısı",credit_card:"kredi kartı numarası",currency_code:"para birimi kodu",iban:"IBAN",jwt:"JWT",template_literal:"Şablon dizesi"},n={nan:"NaN"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Ge\xe7ersiz değer: beklenen instanceof ${i.expected}, alınan ${a}`;return`Ge\xe7ersiz değer: beklenen ${t}, alınan ${a}`}case"invalid_value":if(1===i.values.length)return`Ge\xe7ersiz değer: beklenen ${G(i.values[0])}`;return`Ge\xe7ersiz se\xe7enek: aşağıdakilerden biri olmalı: ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`\xc7ok b\xfcy\xfck: beklenen ${i.origin??"değer"} ${r}${i.maximum.toString()} ${n.unit??"öğe"}`;return`\xc7ok b\xfcy\xfck: beklenen ${i.origin??"değer"} ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`\xc7ok k\xfc\xe7\xfck: beklenen ${i.origin} ${r}${i.minimum.toString()} ${n.unit}`;return`\xc7ok k\xfc\xe7\xfck: beklenen ${i.origin} ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ge\xe7ersiz metin: "${i.prefix}" ile başlamalı`;if("ends_with"===i.format)return`Ge\xe7ersiz metin: "${i.suffix}" ile bitmeli`;if("includes"===i.format)return`Ge\xe7ersiz metin: "${i.includes}" i\xe7ermeli`;if("regex"===i.format)return`Ge\xe7ersiz metin: ${i.pattern} desenine uymalı`;return`Ge\xe7ersiz ${r[i.format]??i.format}`;case"not_multiple_of":return`Ge\xe7ersiz sayı: ${i.divisor} ile tam b\xf6l\xfcnebilmeli`;case"unrecognized_keys":return`Tanınmayan anahtar${i.keys.length>1?"lar":""}: ${d(i.keys,", ")}`;case"invalid_key":return`${i.origin} i\xe7inde ge\xe7ersiz anahtar`;case"invalid_union":default:return"Geçersiz değer";case"invalid_element":return`${i.origin} i\xe7inde ge\xe7ersiz değer`}})}},"ua",0,function(){return ar()},"uk",0,ar,"ur",0,function(){let t,r,n;return{localeError:(t={string:{unit:"حروف",verb:"ہونا"},file:{unit:"بائٹس",verb:"ہونا"},array:{unit:"آئٹمز",verb:"ہونا"},set:{unit:"آئٹمز",verb:"ہونا"},map:{unit:"آئٹمز",verb:"ہونا"}},r={regex:"ان پٹ",email:"ای میل ایڈریس",url:"یو آر ایل",emoji:"ایموجی",uuid:"یو یو آئی ڈی",uuidv4:"یو یو آئی ڈی وی 4",uuidv6:"یو یو آئی ڈی وی 6",nanoid:"نینو آئی ڈی",guid:"جی یو آئی ڈی",cuid:"سی یو آئی ڈی",cuid2:"سی یو آئی ڈی 2",ulid:"یو ایل آئی ڈی",xid:"ایکس آئی ڈی",ksuid:"کے ایس یو آئی ڈی",datetime:"آئی ایس او ڈیٹ ٹائم",date:"آئی ایس او تاریخ",time:"آئی ایس او وقت",duration:"آئی ایس او مدت",ipv4:"آئی پی وی 4 ایڈریس",ipv6:"آئی پی وی 6 ایڈریس",mac:"ایم اے سی ایڈریس",cidrv4:"آئی پی وی 4 رینج",cidrv6:"آئی پی وی 6 رینج",base64:"بیس 64 ان کوڈڈ سٹرنگ",base64url:"بیس 64 یو آر ایل ان کوڈڈ سٹرنگ",json_string:"جے ایس او این سٹرنگ",e164:"ای 164 نمبر",credit_card:"کریڈٹ کارڈ نمبر",currency_code:"کرنسی کوڈ",iban:"IBAN",jwt:"جے ڈبلیو ٹی",template_literal:"ان پٹ"},n={nan:"NaN",number:"نمبر",array:"آرے",null:"نل"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`غلط ان پٹ: instanceof ${i.expected} متوقع تھا، ${a} موصول ہوا`;return`غلط ان پٹ: ${t} متوقع تھا، ${a} موصول ہوا`}case"invalid_value":if(1===i.values.length)return`غلط ان پٹ: ${G(i.values[0])} متوقع تھا`;return`غلط آپشن: ${d(i.values,"|")} میں سے ایک متوقع تھا`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`بہت بڑا: ${i.origin??"ویلیو"} کے ${r}${i.maximum.toString()} ${n.unit??"عناصر"} ہونے متوقع تھے`;return`بہت بڑا: ${i.origin??"ویلیو"} کا ${r}${i.maximum.toString()} ہونا متوقع تھا`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`بہت چھوٹا: ${i.origin} کے ${r}${i.minimum.toString()} ${n.unit} ہونے متوقع تھے`;return`بہت چھوٹا: ${i.origin} کا ${r}${i.minimum.toString()} ہونا متوقع تھا`}case"invalid_format":if("starts_with"===i.format)return`غلط سٹرنگ: "${i.prefix}" سے شروع ہونا چاہیے`;if("ends_with"===i.format)return`غلط سٹرنگ: "${i.suffix}" پر ختم ہونا چاہیے`;if("includes"===i.format)return`غلط سٹرنگ: "${i.includes}" شامل ہونا چاہیے`;if("regex"===i.format)return`غلط سٹرنگ: پیٹرن ${i.pattern} سے میچ ہونا چاہیے`;return`غلط ${r[i.format]??i.format}`;case"not_multiple_of":return`غلط نمبر: ${i.divisor} کا مضاعف ہونا چاہیے`;case"unrecognized_keys":return`غیر تسلیم شدہ کی${i.keys.length>1?"ز":""}: ${d(i.keys,"، ")}`;case"invalid_key":return`${i.origin} میں غلط کی`;case"invalid_union":default:return"غلط ان پٹ";case"invalid_element":return`${i.origin} میں غلط ویلیو`}})}},"uz",0,function(){let t,r,n;return{localeError:(t={string:{unit:"belgi",verb:"bo‘lishi kerak"},file:{unit:"bayt",verb:"bo‘lishi kerak"},array:{unit:"element",verb:"bo‘lishi kerak"},set:{unit:"element",verb:"bo‘lishi kerak"},map:{unit:"yozuv",verb:"bo‘lishi kerak"}},r={regex:"kirish",email:"elektron 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${G(i.values[0])}`;return`Noto‘g‘ri variant: quyidagilardan biri kutilgan ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`Juda katta: kutilgan ${i.origin??"qiymat"} ${r}${i.maximum.toString()} ${n.unit} ${n.verb}`;return`Juda katta: kutilgan ${i.origin??"qiymat"} ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`Juda kichik: kutilgan ${i.origin} ${r}${i.minimum.toString()} ${n.unit} ${n.verb}`;return`Juda kichik: kutilgan ${i.origin} ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Noto‘g‘ri satr: "${i.prefix}" bilan boshlanishi kerak`;if("ends_with"===i.format)return`Noto‘g‘ri satr: "${i.suffix}" bilan tugashi kerak`;if("includes"===i.format)return`Noto‘g‘ri satr: "${i.includes}" ni o‘z ichiga olishi kerak`;if("regex"===i.format)return`Noto‘g‘ri satr: ${i.pattern} shabloniga mos kelishi kerak`;return`Noto‘g‘ri ${r[i.format]??i.format}`;case"not_multiple_of":return`Noto‘g‘ri raqam: ${i.divisor} ning karralisi bo‘lishi kerak`;case"unrecognized_keys":return`Noma’lum kalit${i.keys.length>1?"lar":""}: ${d(i.keys,", ")}`;case"invalid_key":return`${i.origin} dagi kalit noto‘g‘ri`;case"invalid_union":default:return"Noto‘g‘ri kirish";case"invalid_element":return`${i.origin} da noto‘g‘ri qiymat`}})}},"vi",0,function(){let t,r,n;return{localeError:(t={string:{unit:"ký tự",verb:"có"},file:{unit:"byte",verb:"có"},array:{unit:"phần tử",verb:"có"},set:{unit:"phần tử",verb:"có"},map:{unit:"phần tử",verb:"có"}},r={regex:"đầu vào",email:"địa chỉ email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ngày giờ ISO",date:"ngày ISO",time:"giờ ISO",duration:"khoảng thời gian ISO",ipv4:"địa chỉ IPv4",ipv6:"địa chỉ IPv6",mac:"địa chỉ MAC",cidrv4:"dải IPv4",cidrv6:"dải IPv6",base64:"chuỗi mã hóa base64",base64url:"chuỗi mã hóa base64url",json_string:"chuỗi JSON",e164:"số E.164",credit_card:"số thẻ tín dụng",currency_code:"mã tiền tệ",iban:"IBAN",jwt:"JWT",template_literal:"đầu vào"},n={nan:"NaN",number:"số",array:"mảng"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`Đầu v\xe0o kh\xf4ng hợp lệ: mong đợi instanceof ${i.expected}, nhận được ${a}`;return`Đầu v\xe0o kh\xf4ng hợp lệ: mong đợi ${t}, nhận được ${a}`}case"invalid_value":if(1===i.values.length)return`Đầu v\xe0o kh\xf4ng hợp lệ: mong đợi ${G(i.values[0])}`;return`T\xf9y chọn kh\xf4ng hợp lệ: mong đợi một trong c\xe1c gi\xe1 trị ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`Qu\xe1 lớn: mong đợi ${i.origin??"giá trị"} ${n.verb} ${r}${i.maximum.toString()} ${n.unit??"phần tử"}`;return`Qu\xe1 lớn: mong đợi ${i.origin??"giá trị"} ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`Qu\xe1 nhỏ: mong đợi ${i.origin} ${n.verb} ${r}${i.minimum.toString()} ${n.unit}`;return`Qu\xe1 nhỏ: mong đợi ${i.origin} ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Chuỗi kh\xf4ng hợp lệ: phải bắt đầu bằng "${i.prefix}"`;if("ends_with"===i.format)return`Chuỗi kh\xf4ng hợp lệ: phải kết th\xfac bằng "${i.suffix}"`;if("includes"===i.format)return`Chuỗi kh\xf4ng hợp lệ: phải bao gồm "${i.includes}"`;if("regex"===i.format)return`Chuỗi kh\xf4ng hợp lệ: phải khớp với mẫu ${i.pattern}`;return`${r[i.format]??i.format} kh\xf4ng hợp lệ`;case"not_multiple_of":return`Số kh\xf4ng hợp lệ: phải l\xe0 bội số của ${i.divisor}`;case"unrecognized_keys":return`Kh\xf3a kh\xf4ng được nhận dạng: ${d(i.keys,", ")}`;case"invalid_key":return`Kh\xf3a kh\xf4ng hợp lệ trong ${i.origin}`;case"invalid_union":default:return"Đầu vào không hợp lệ";case"invalid_element":return`Gi\xe1 trị kh\xf4ng hợp lệ trong ${i.origin}`}})}},"yo",0,function(){let t,r,n;return{localeError:(t={string:{unit:"àmi",verb:"ní"},file:{unit:"bytes",verb:"ní"},array:{unit:"nkan",verb:"ní"},set:{unit:"nkan",verb:"ní"},map:{unit:"nkan",verb:"ní"}},r={regex:"ẹ̀rọ ìbáwọlé",email:"àdírẹ́sì ìmẹ́lì",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"àkókò ISO",date:"ọjọ́ ISO",time:"àkókò ISO",duration:"àkókò tó pé ISO",ipv4:"àdírẹ́sì IPv4",ipv6:"àdírẹ́sì IPv6",mac:"àdírẹ́sì MAC",cidrv4:"àgbègbè IPv4",cidrv6:"àgbègbè IPv6",base64:"ọ̀rọ̀ tí a kọ́ ní base64",base64url:"ọ̀rọ̀ base64url",json_string:"ọ̀rọ̀ JSON",e164:"nọ́mbà E.164",credit_card:"nọmba kaadi gbese",currency_code:"koodu owó",iban:"IBAN",jwt:"JWT",template_literal:"ẹ̀rọ ìbáwọlé"},n={nan:"NaN",number:"nọ́mbà",array:"akopọ"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`\xccb\xe1wọl\xe9 aṣ\xecṣe: a n\xed l\xe1ti fi instanceof ${i.expected}, \xe0mọ̀ a r\xed ${a}`;return`\xccb\xe1wọl\xe9 aṣ\xecṣe: a n\xed l\xe1ti fi ${t}, \xe0mọ̀ a r\xed ${a}`}case"invalid_value":if(1===i.values.length)return`\xccb\xe1wọl\xe9 aṣ\xecṣe: a n\xed l\xe1ti fi ${G(i.values[0])}`;return`\xc0ṣ\xe0y\xe0n aṣ\xecṣe: yan ọ̀kan l\xe1ra ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`T\xf3 pọ̀ j\xf9: a n\xed l\xe1ti jẹ́ p\xe9 ${i.origin??"iye"} ${n.verb} ${r}${i.maximum} ${n.unit}`;return`T\xf3 pọ̀ j\xf9: a n\xed l\xe1ti jẹ́ ${r}${i.maximum}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`K\xe9r\xe9 ju: a n\xed l\xe1ti jẹ́ p\xe9 ${i.origin} ${n.verb} ${r}${i.minimum} ${n.unit}`;return`K\xe9r\xe9 ju: a n\xed l\xe1ti jẹ́ ${r}${i.minimum}`}case"invalid_format":if("starts_with"===i.format)return`Ọ̀rọ̀ aṣ\xecṣe: gbọ́dọ̀ bẹ̀rẹ̀ pẹ̀l\xfa "${i.prefix}"`;if("ends_with"===i.format)return`Ọ̀rọ̀ aṣ\xecṣe: gbọ́dọ̀ par\xed pẹ̀l\xfa "${i.suffix}"`;if("includes"===i.format)return`Ọ̀rọ̀ aṣ\xecṣe: gbọ́dọ̀ n\xed "${i.includes}"`;if("regex"===i.format)return`Ọ̀rọ̀ aṣ\xecṣe: gbọ́dọ̀ b\xe1 \xe0pẹẹrẹ mu ${i.pattern}`;return`Aṣ\xecṣe: ${r[i.format]??i.format}`;case"not_multiple_of":return`Nọ́mb\xe0 aṣ\xecṣe: gbọ́dọ̀ jẹ́ \xe8y\xe0 p\xedp\xedn ti ${i.divisor}`;case"unrecognized_keys":return`Bọt\xecn\xec \xe0\xecmọ̀: ${d(i.keys,", ")}`;case"invalid_key":return`Bọt\xecn\xec aṣ\xecṣe n\xedn\xfa ${i.origin}`;case"invalid_union":default:return"Ìbáwọlé aṣìṣe";case"invalid_element":return`Iye aṣ\xecṣe n\xedn\xfa ${i.origin}`}})}},"zhCN",0,function(){let t,r,n;return{localeError:(t={string:{unit:"字符",verb:"包含"},file:{unit:"字节",verb:"包含"},array:{unit:"项",verb:"包含"},set:{unit:"项",verb:"包含"},map:{unit:"项",verb:"包含"}},r={regex:"输入",email:"电子邮件",url:"URL",emoji:"表情符号",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO日期时间",date:"ISO日期",time:"ISO时间",duration:"ISO时长",ipv4:"IPv4地址",ipv6:"IPv6地址",mac:"MAC地址",cidrv4:"IPv4网段",cidrv6:"IPv6网段",base64:"base64编码字符串",base64url:"base64url编码字符串",json_string:"JSON字符串",e164:"E.164号码",credit_card:"信用卡号",currency_code:"货币代码",iban:"IBAN",jwt:"JWT",template_literal:"输入"},n={nan:"NaN",number:"数字",array:"数组",null:"空值(null)"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`无效输入:期望 instanceof ${i.expected},实际接收 ${a}`;return`无效输入:期望 ${t},实际接收 ${a}`}case"invalid_value":if(1===i.values.length)return`无效输入:期望 ${G(i.values[0])}`;return`无效选项:期望以下之一 ${d(i.values,"|")}`;case"too_big":{let r=i.inclusive?"<=":"<",n=t[i.origin]??null;if(n)return`数值过大:期望 ${i.origin??"值"} ${r}${i.maximum.toString()} ${n.unit??"个元素"}`;return`数值过大:期望 ${i.origin??"值"} ${r}${i.maximum.toString()}`}case"too_small":{let r=i.inclusive?">=":">",n=t[i.origin]??null;if(n)return`数值过小:期望 ${i.origin} ${r}${i.minimum.toString()} ${n.unit}`;return`数值过小:期望 ${i.origin} ${r}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`无效字符串:必须以 "${i.prefix}" 开头`;if("ends_with"===i.format)return`无效字符串:必须以 "${i.suffix}" 结尾`;if("includes"===i.format)return`无效字符串:必须包含 "${i.includes}"`;if("regex"===i.format)return`无效字符串:必须满足正则表达式 ${i.pattern}`;return`无效${r[i.format]??i.format}`;case"not_multiple_of":return`无效数字:必须是 ${i.divisor} 的倍数`;case"unrecognized_keys":return`出现未知的键(key): ${d(i.keys,", ")}`;case"invalid_key":return`${i.origin} 中的键(key)无效`;case"invalid_union":default:return"无效输入";case"invalid_element":return`${i.origin} 中包含无效值(value)`}})}},"zhTW",0,function(){let t,r,n;return{localeError:(t={string:{unit:"字元",verb:"擁有"},file:{unit:"位元組",verb:"擁有"},array:{unit:"項目",verb:"擁有"},set:{unit:"項目",verb:"擁有"},map:{unit:"項目",verb:"擁有"}},r={regex:"輸入",email:"郵件地址",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO 日期時間",date:"ISO 日期",time:"ISO 時間",duration:"ISO 期間",ipv4:"IPv4 位址",ipv6:"IPv6 位址",mac:"MAC 位址",cidrv4:"IPv4 範圍",cidrv6:"IPv6 範圍",base64:"base64 編碼字串",base64url:"base64url 編碼字串",json_string:"JSON 字串",e164:"E.164 數值",credit_card:"信用卡號",currency_code:"貨幣代碼",iban:"IBAN",jwt:"JWT",template_literal:"輸入"},n={nan:"NaN"},i=>{switch(i.code){case"invalid_type":{let t=n[i.expected]??i.expected,r=eg(i.input),a=n[r]??r;if(/^[A-Z]/.test(i.expected))return`無效的輸入值:預期為 instanceof ${i.expected},但收到 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100)}.max-w-\[15ch\]{max-width:15ch}.max-w-\[40ch\]{max-width:40ch}.max-w-\[70ch\]{max-width:70ch}.max-w-\[75\%\]{max-width:75%}.max-w-\[80\%\]{max-width:80%}.max-w-\[85\%\]{max-width:85%}.max-w-\[88\%\]{max-width:88%}.max-w-\[92\%\]{max-width:92%}.max-w-\[95\%\]{max-width:95%}.max-w-\[120px\]{max-width:120px}.max-w-\[150px\]{max-width:150px}.max-w-\[160px\]{max-width:160px}.max-w-\[200px\]{max-width:200px}.max-w-\[220px\]{max-width:220px}.max-w-\[240px\]{max-width:240px}.max-w-\[280px\]{max-width:280px}.max-w-\[300px\]{max-width:300px}.max-w-\[320px\]{max-width:320px}.max-w-\[340px\]{max-width:340px}.max-w-\[360px\]{max-width:360px}.max-w-\[400px\]{max-width:400px}.max-w-\[420px\]{max-width:420px}.max-w-\[500px\]{max-width:500px}.max-w-\[520px\]{max-width:520px}.max-w-\[560px\]{max-width:560px}.max-w-\[640px\]{max-width:640px}.max-w-\[680px\]{max-width:680px}.max-w-\[780px\]{max-width:780px}.max-w-\[800px\]{max-width:800px}.max-w-\[960px\]{max-width:960px}.max-w-\[1400px\]{max-width:1400px}.max-w-\[calc\(100\%-2rem\)\]{max-width:calc(100% - 2rem)}.max-w-\[calc\(100vw-2rem\)\]{max-width:calc(100vw - 2rem)}.max-w-\[min\(200px\,34vw\)\]{max-width:min(200px,34vw)}.max-w-full{max-width:100%}.max-w-lg{max-width:var(--container-lg)}.max-w-md{max-width:var(--container-md)}.max-w-none{max-width:none}.max-w-sm{max-width:var(--container-sm)}.max-w-xl{max-width:var(--container-xl)}.max-w-xs{max-width:var(--container-xs)}.min-w-0{min-width:0}.min-w-4{min-width:calc(var(--spacing) * 4)}.min-w-5{min-width:calc(var(--spacing) * 5)}.min-w-6{min-width:calc(var(--spacing) * 6)}.min-w-8{min-width:calc(var(--spacing) * 8)}.min-w-9{min-width:calc(var(--spacing) * 9)}.min-w-10{min-width:calc(var(--spacing) * 10)}.min-w-16{min-width:calc(var(--spacing) * 16)}.min-w-24{min-width:calc(var(--spacing) * 24)}.min-w-28{min-width:calc(var(--spacing) * 28)}.min-w-32{min-width:calc(var(--spacing) * 32)}.min-w-36{min-width:calc(var(--spacing) * 36)}.min-w-40{min-width:calc(var(--spacing) * 40)}.min-w-48{min-width:calc(var(--spacing) * 48)}.min-w-50{min-width:calc(var(--spacing) * 50)}.min-w-60{min-width:calc(var(--spacing) * 60)}.min-w-72{min-width:calc(var(--spacing) * 72)}.min-w-80{min-width:calc(var(--spacing) * 80)}.min-w-\[2px\]{min-width:2px}.min-w-\[9rem\]{min-width:9rem}.min-w-\[12rem\]{min-width:12rem}.min-w-\[16rem\]{min-width:16rem}.min-w-\[40rem\]{min-width:40rem}.min-w-\[88px\]{min-width:88px}.min-w-\[96px\]{min-width:96px}.min-w-\[100px\]{min-width:100px}.min-w-\[110px\]{min-width:110px}.min-w-\[120px\]{min-width:120px}.min-w-\[130px\]{min-width:130px}.min-w-\[160px\]{min-width:160px}.min-w-\[180px\]{min-width:180px}.min-w-\[200px\]{min-width:200px}.min-w-\[240px\]{min-width:240px}.min-w-\[600px\]{min-width:600px}.min-w-\[calc\(var\(--anchor-width\)\+--spacing\(7\)\)\]{min-width:calc(var(--anchor-width) + calc(var(--spacing) * 7))}.min-w-full{min-width:100%}.flex-1{flex:1}.flex-2{flex:2}.flex-auto{flex:auto}.flex-none{flex:none}.shrink{flex-shrink:1}.shrink-0{flex-shrink:0}.shrink-\[100\]{flex-shrink:100}.grow{flex-grow:1}.basis-32{flex-basis:calc(var(--spacing) * 32)}.basis-full{flex-basis:100%}.table-fixed{table-layout:fixed}.caption-bottom{caption-side:bottom}.border-collapse{border-collapse:collapse}.origin-\(--transform-origin\){transform-origin:var(--transform-origin)}.origin-right{transform-origin:100%}.-translate-x-1\/2{--tw-translate-x:calc(calc(1 / 2 * 100%) * -1);translate:var(--tw-translate-x) var(--tw-translate-y)}.-translate-x-full{--tw-translate-x:-100%;translate:var(--tw-translate-x) var(--tw-translate-y)}.translate-x-0{--tw-translate-x:0;translate:var(--tw-translate-x) var(--tw-translate-y)}.translate-x-0\.5{--tw-translate-x:calc(var(--spacing) * .5);translate:var(--tw-translate-x) var(--tw-translate-y)}.translate-x-1\/2{--tw-translate-x:calc(1 / 2 * 100%);translate:var(--tw-translate-x) var(--tw-translate-y)}.translate-x-4{--tw-translate-x:calc(var(--spacing) * 4);translate:var(--tw-translate-x) var(--tw-translate-y)}.translate-x-full{--tw-translate-x:100%;translate:var(--tw-translate-x) var(--tw-translate-y)}.-translate-y-1\/2{--tw-translate-y:calc(calc(1 / 2 * 100%) * -1);translate:var(--tw-translate-x) var(--tw-translate-y)}.translate-y-0{--tw-translate-y:0;translate:var(--tw-translate-x) var(--tw-translate-y)}.translate-y-0\.5{--tw-translate-y:calc(var(--spacing) * .5);translate:var(--tw-translate-x) var(--tw-translate-y)}.translate-y-\[calc\(-50\%-2px\)\]{--tw-translate-y:calc(-50% - 2px);translate:var(--tw-translate-x) var(--tw-translate-y)}.scale-75{--tw-scale-x:75%;--tw-scale-y:75%;--tw-scale-z:75%;scale:var(--tw-scale-x) var(--tw-scale-y)}.-rotate-90{rotate:-90deg}.rotate-45{rotate:45deg}.rotate-90{rotate:90deg}.rotate-180{rotate:180deg}.transform{transform:var(--tw-rotate-x,) var(--tw-rotate-y,) var(--tw-rotate-z,) var(--tw-skew-x,) var(--tw-skew-y,)}.shimmer{--_spread:var(--shimmer-spread,calc(3ch + 40px));--_base:currentColor;--_highlight:var(--shimmer-color,oklch(from currentColor l c h / calc(alpha * .2)));background-image:var(--shimmer-image,linear-gradient(calc(90deg + var(--shimmer-angle)), var(--_base) calc(50% - var(--_spread)), var(--_highlight) calc(50% - var(--_spread) * .5), var(--_highlight) 50%, var(--_highlight) calc(50% + var(--_spread) * .5), var(--_base) calc(50% + var(--_spread))))}@supports (color:color-mix(in lab, red, red)){.shimmer{background-image:var(--shimmer-image,linear-gradient(calc(90deg + var(--shimmer-angle)), var(--_base) calc(50% - var(--_spread)), color-mix(in oklch, var(--_highlight), var(--_base) 50%) calc(50% - var(--_spread) * .5), var(--_highlight) 50%, color-mix(in oklch, var(--_highlight), var(--_base) 50%) calc(50% + var(--_spread) * .5), var(--_base) calc(50% + var(--_spread))))}}.shimmer{background-repeat:no-repeat;background-size:calc(200% + var(--_spread) * 2) 100%;-webkit-text-fill-color:var(--shimmer-text-fill,transparent);animation:tw-shimmer var(--shimmer-duration,2s) linear infinite;background-position:0 0;-webkit-background-clip:text;background-clip:text}.shimmer:where(.dark,.dark *){--_highlight:var(--shimmer-color,oklch(from currentColor max(.8, calc(l + .4)) c h / calc(alpha + .4)))}.shimmer:where([dir=rtl],[dir=rtl] *){animation-direction:reverse}.scroll-fade-x{--_scroll-fade-size-s:var(--scroll-fade-s-size,var(--scroll-fade-size,min(12%, calc(var(--spacing) * 10))));--_scroll-fade-size-e:var(--scroll-fade-e-size,var(--scroll-fade-size,min(12%, calc(var(--spacing) * 10))));--scroll-fade-inline:linear-gradient(to right, transparent 0, #000 var(--scroll-fade-s,0px), #000 calc(100% - var(--scroll-fade-e,0px)), transparent 100%)}.scroll-fade-x:where([dir=rtl],[dir=rtl] *){--scroll-fade-inline:linear-gradient(to left, transparent 0, #000 var(--scroll-fade-s,0px), #000 calc(100% - var(--scroll-fade-e,0px)), transparent 100%)}.scroll-fade-x{-webkit-mask-image:var(--scroll-fade-mask,var(--scroll-fade-inline));-webkit-mask-image:var(--scroll-fade-mask,var(--scroll-fade-inline));-webkit-mask-image:var(--scroll-fade-mask,var(--scroll-fade-inline));-webkit-mask-image:var(--scroll-fade-mask,var(--scroll-fade-inline));mask-image:var(--scroll-fade-mask,var(--scroll-fade-inline));-webkit-mask-composite:source-in;-webkit-mask-composite:source-in;-webkit-mask-composite:source-in;-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-composite:source-in;mask-composite:intersect}@supports (animation-timeline:scroll()){.scroll-fade-x{animation:1ms ease-in-out scroll-fade-reveal-s,1ms ease-in-out scroll-fade-reveal-e;animation-timeline:scroll(self inline),scroll(self inline);animation-range:0 var(--scroll-fade-reveal,calc(var(--spacing) * 24)), calc(100% - var(--scroll-fade-reveal,calc(var(--spacing) * 24))) 100%;animation-fill-mode:both}}@supports not (animation-timeline:scroll()){.scroll-fade-x{--scroll-fade-s:var(--_scroll-fade-size-s);--scroll-fade-e:var(--_scroll-fade-size-e)}}@supports (animation-timeline:scroll()){.scroll-fade-e{animation:1ms ease-in-out scroll-fade-reveal-e;animation-timeline:scroll(self inline);animation-range:calc(100% - var(--scroll-fade-reveal,calc(var(--spacing) * 24))) 100%;animation-fill-mode:both}}@supports not (animation-timeline:scroll()){.scroll-fade-e{--scroll-fade-e:var(--_scroll-fade-size-e)}}.scroll-fade-e{--_scroll-fade-size-e:var(--scroll-fade-e-size,var(--scroll-fade-size,min(12%, calc(var(--spacing) * 10))));--scroll-fade-mask:linear-gradient(to right, #000 0, #000 calc(100% - var(--scroll-fade-e,0px)), transparent 100%)}.scroll-fade-e:where([dir=rtl],[dir=rtl] *){--scroll-fade-mask:linear-gradient(to left, #000 0, #000 calc(100% - var(--scroll-fade-e,0px)), transparent 100%)}.scroll-fade-e{-webkit-mask-image:var(--scroll-fade-mask);-webkit-mask-image:var(--scroll-fade-mask);-webkit-mask-image:var(--scroll-fade-mask);-webkit-mask-image:var(--scroll-fade-mask);mask-image:var(--scroll-fade-mask);-webkit-mask-composite:source-in;-webkit-mask-composite:source-in;-webkit-mask-composite:source-in;-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-composite:source-in;mask-composite:intersect}@supports (animation-timeline:scroll()){.scroll-fade-e{animation:1ms ease-in-out scroll-fade-reveal-e;animation-timeline:scroll(self inline);animation-range:calc(100% - var(--scroll-fade-reveal,calc(var(--spacing) * 24))) 100%;animation-fill-mode:both}}@supports not (animation-timeline:scroll()){.scroll-fade-e{--scroll-fade-e:var(--_scroll-fade-size-e)}}.scroll-fade-b{--_scroll-fade-size-b:var(--scroll-fade-b-size,var(--scroll-fade-size,min(12%, calc(var(--spacing) * 10))));--scroll-fade-mask:linear-gradient(to bottom, #000 0, #000 calc(100% - var(--scroll-fade-b,0px)), transparent 100%);-webkit-mask-image:var(--scroll-fade-mask);-webkit-mask-image:var(--scroll-fade-mask);-webkit-mask-image:var(--scroll-fade-mask);-webkit-mask-image:var(--scroll-fade-mask);mask-image:var(--scroll-fade-mask);-webkit-mask-composite:source-in;-webkit-mask-composite:source-in;-webkit-mask-composite:source-in;-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-composite:source-in;mask-composite:intersect}@supports (animation-timeline:scroll()){.scroll-fade-b{animation:1ms ease-in-out scroll-fade-reveal-b;animation-timeline:scroll(self y);animation-range:calc(100% - var(--scroll-fade-reveal,calc(var(--spacing) * 24))) 100%;animation-fill-mode:both}}@supports not (animation-timeline:scroll()){.scroll-fade-b{--scroll-fade-b:var(--_scroll-fade-size-b)}}.animate-bounce{animation:var(--animate-bounce)}.animate-in{animation:enter var(--tw-animation-duration,var(--tw-duration,.15s))var(--tw-ease,ease)var(--tw-animation-delay,0s)var(--tw-animation-iteration-count,1)var(--tw-animation-direction,normal)var(--tw-animation-fill-mode,none)}.animate-ping{animation:var(--animate-ping)}.animate-pulse{animation:var(--animate-pulse)}.animate-spin{animation:var(--animate-spin)}.animate-trace-drawer-in{animation:.2s cubic-bezier(.25,1,.5,1) both trace-drawer-in}.animate-trace-drawer-out{animation:.2s cubic-bezier(.4,0,1,1) both trace-drawer-out}.cursor-col-resize{cursor:col-resize}.cursor-crosshair{cursor:crosshair}.cursor-default{cursor:default}.cursor-ew-resize{cursor:ew-resize}.cursor-grab{cursor:grab}.cursor-help{cursor:help}.cursor-not-allowed{cursor:not-allowed}.cursor-pointer{cursor:pointer}.cursor-text{cursor:text}.touch-none{touch-action:none}.resize{resize:both}.resize-none{resize:none}.snap-x{scroll-snap-type:x var(--tw-scroll-snap-strictness)}.snap-mandatory{--tw-scroll-snap-strictness:mandatory}.scroll-my-1{scroll-margin-block:var(--spacing)}.scroll-mt-4{scroll-margin-top:calc(var(--spacing) * 4)}.scroll-px-1{scroll-padding-inline:var(--spacing)}.scroll-py-1{scroll-padding-block:var(--spacing)}.scrollbar-none{scrollbar-width:none}.scrollbar-thin{scrollbar-width:thin}.scrollbar-gutter-stable{scrollbar-gutter:stable}.list-inside{list-style-position:inside}.list-decimal{list-style-type:decimal}.list-disc{list-style-type:disc}.list-none{list-style-type:none}.appearance-none{appearance:none}.auto-rows-fr{grid-auto-rows:minmax(0,1fr)}.auto-rows-min{grid-auto-rows:min-content}.grid-cols-1{grid-template-columns:repeat(1,minmax(0,1fr))}.grid-cols-2{grid-template-columns:repeat(2,minmax(0,1fr))}.grid-cols-3{grid-template-columns:repeat(3,minmax(0,1fr))}.grid-cols-4{grid-template-columns:repeat(4,minmax(0,1fr))}.grid-cols-5{grid-template-columns:repeat(5,minmax(0,1fr))}.grid-cols-10{grid-template-columns:repeat(10,minmax(0,1fr))}.grid-cols-12{grid-template-columns:repeat(12,minmax(0,1fr))}.grid-cols-24{grid-template-columns:repeat(24,minmax(0,1fr))}.grid-cols-\[0\.75rem_minmax\(0\,5rem\)_minmax\(0\,1fr\)_auto\]{grid-template-columns:.75rem minmax(0,5rem) minmax(0,1fr) auto}.grid-cols-\[0\.75rem_minmax\(0\,9rem\)_minmax\(0\,1fr\)_auto\]{grid-template-columns:.75rem minmax(0,9rem) minmax(0,1fr) auto}.grid-cols-\[1\.5rem_2\.5rem_1fr_auto\]{grid-template-columns:1.5rem 2.5rem 1fr auto}.grid-cols-\[1\.5rem_auto_minmax\(0\,1fr\)_auto\]{grid-template-columns:1.5rem auto minmax(0,1fr) auto}.grid-cols-\[1\.25rem_minmax\(0\,1fr\)_auto_3rem\]{grid-template-columns:1.25rem minmax(0,1fr) auto 3rem}.grid-cols-\[1\.75rem_9rem_1fr_3\.5rem\]{grid-template-columns:1.75rem 9rem 1fr 3.5rem}.grid-cols-\[1fr_auto\]{grid-template-columns:1fr auto}.grid-cols-\[1rem_4\.5rem_minmax\(0\,1fr\)_auto\]{grid-template-columns:1rem 4.5rem minmax(0,1fr) auto}.grid-cols-\[4rem_minmax\(0\,1fr\)_auto\]{grid-template-columns:4rem minmax(0,1fr) auto}.grid-cols-\[18rem_1fr\]{grid-template-columns:18rem 1fr}.grid-cols-\[80px_minmax\(0\,1fr\)\]{grid-template-columns:80px minmax(0,1fr)}.grid-cols-\[160px_minmax\(0\,1fr\)\]{grid-template-columns:160px minmax(0,1fr)}.grid-cols-\[auto\]{grid-template-columns:auto}.grid-cols-\[auto_1fr\]{grid-template-columns:auto 1fr}.grid-cols-\[auto_minmax\(0\,1fr\)\]{grid-template-columns:auto minmax(0,1fr)}.grid-cols-\[max-content_1fr\]{grid-template-columns:max-content 1fr}.grid-cols-\[minmax\(0\,1fr\)_5\.5rem_4\.5rem\]{grid-template-columns:minmax(0,1fr) 5.5rem 4.5rem}.grid-cols-\[minmax\(0\,1fr\)_5\.5rem_4\.5rem_5rem_4\.5rem_5\.5rem\]{grid-template-columns:minmax(0,1fr) 5.5rem 4.5rem 5rem 4.5rem 5.5rem}.grid-cols-\[minmax\(0\,1fr\)_5\.5rem_5\.5rem\]{grid-template-columns:minmax(0,1fr) 5.5rem 5.5rem}.grid-cols-\[minmax\(0\,1fr\)_16px\]{grid-template-columns:minmax(0,1fr) 16px}.grid-cols-\[minmax\(0\,1fr\)_auto\]{grid-template-columns:minmax(0,1fr) auto}.grid-cols-\[minmax\(0\,1fr\)_minmax\(48px\,1fr\)_2\.5rem\]{grid-template-columns:minmax(0,1fr) minmax(48px,1fr) 2.5rem}.grid-cols-\[minmax\(0\,14rem\)_minmax\(0\,1fr\)\]{grid-template-columns:minmax(0,14rem) minmax(0,1fr)}.grid-cols-\[minmax\(5rem\,32\%\)_minmax\(0\,1fr\)\]{grid-template-columns:minmax(5rem,32%) minmax(0,1fr)}.grid-cols-\[repeat\(auto-fill\,minmax\(220px\,1fr\)\)\]{grid-template-columns:repeat(auto-fill,minmax(220px,1fr))}.grid-cols-\[repeat\(auto-fit\,minmax\(7rem\,1fr\)\)\]{grid-template-columns:repeat(auto-fit,minmax(7rem,1fr))}.grid-cols-\[repeat\(auto-fit\,minmax\(140px\,1fr\)\)\]{grid-template-columns:repeat(auto-fit,minmax(140px,1fr))}.grid-rows-2{grid-template-rows:repeat(2,minmax(0,1fr))}.grid-rows-\[0fr\]{grid-template-rows:0fr}.grid-rows-\[1fr\]{grid-template-rows:1fr}.grid-rows-\[auto_1fr\]{grid-template-rows:auto 1fr}.grid-rows-\[auto_auto_minmax\(0\,1fr\)_auto\]{grid-template-rows:auto auto minmax(0,1fr) auto}.flex-col{flex-direction:column}.flex-col-reverse{flex-direction:column-reverse}.flex-row{flex-direction:row}.flex-nowrap{flex-wrap:nowrap}.flex-wrap{flex-wrap:wrap}.place-content-center{place-content:center}.place-items-center{place-items:center}.content-start{align-content:flex-start}.items-baseline{align-items:baseline}.items-center{align-items:center}.items-end{align-items:flex-end}.items-start{align-items:flex-start}.items-stretch{align-items:stretch}.justify-between{justify-content:space-between}.justify-center{justify-content:center}.justify-end{justify-content:flex-end}.justify-start{justify-content:flex-start}.gap-\(--card-spacing\){gap:var(--card-spacing)}.gap-0{gap:0}.gap-0\.5{gap:calc(var(--spacing) * .5)}.gap-1{gap:var(--spacing)}.gap-1\.5{gap:calc(var(--spacing) * 1.5)}.gap-2{gap:calc(var(--spacing) * 2)}.gap-2\.5{gap:calc(var(--spacing) * 2.5)}.gap-3{gap:calc(var(--spacing) * 3)}.gap-3\.5{gap:calc(var(--spacing) * 3.5)}.gap-4{gap:calc(var(--spacing) * 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3.5)}.\[\&\>svg\:not\(\[class\*\=\'size-\'\]\)\]\:size-4>svg:not([class*=size-]){width:calc(var(--spacing) * 4);height:calc(var(--spacing) * 4)}.\[\&\>td\:not\(\:first-child\)\]\:opacity-50>td:not(:first-child){opacity:.5}.\[\&\>tr\]\:last\:border-b-0>tr:last-child{border-bottom-style:var(--tw-border-style);border-bottom-width:0}.\[\&\>ul\]\:mt-1>ul{margin-top:var(--spacing)}.\[\&\>ul\]\:mb-0>ul{margin-bottom:0}.\[\&\[aria-orientation\=horizontal\]\>div\]\:rotate-90[aria-orientation=horizontal]>div{rotate:90deg}[data-variant=legend]+.\[\[data-variant\=legend\]\+\&\]\:-mt-1\.5{margin-top:calc(var(--spacing) * -1.5)}pre .\[pre_\&\]\:bg-transparent{background-color:#0000}pre .\[pre_\&\]\:p-0{padding:0}@media (prefers-reduced-motion:reduce){.animate-trace-drawer-in,.animate-trace-drawer-out,.animate-slot-slide-in{animation:none!important}}.animate-trace-drawer-in,.animate-trace-drawer-out{transform-origin:100%}@media 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--tw-exit-blur{syntax:"*";inherits:false;initial-value:0}@property --tw-exit-opacity{syntax:"*";inherits:false;initial-value:1}@property --tw-exit-rotate{syntax:"*";inherits:false;initial-value:0}@property --tw-exit-scale{syntax:"*";inherits:false;initial-value:1}@property --tw-exit-translate-x{syntax:"*";inherits:false;initial-value:0}@property --tw-exit-translate-y{syntax:"*";inherits:false;initial-value:0}@property --scroll-fade-e{syntax:"";inherits:false;initial-value:0}@property --scroll-fade-mask{syntax:"*";inherits:false}@supports (color:color-mix(in lab, red, red)){:root{--finding-quote:color-mix(in oklab, var(--warning) 16%, transparent)}.dark{--finding-quote:color-mix(in oklab, var(--warning) 24%, 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var(--lens-border,var(--border));background-color:var(--card);background-image:linear-gradient(to right, var(--card) 40%, transparent), radial-gradient(var(--lens-grid,var(--border)) .8px, transparent .8px);background-size:100% 100%,10px 10px;flex-wrap:wrap;flex-shrink:0;justify-content:space-between;align-items:center;gap:1rem;padding:1.25rem 1rem;display:flex}.lens-section-label{font-family:var(--font-mono);letter-spacing:.1em;color:var(--muted-foreground);text-transform:uppercase;font-size:10px;font-weight:500}.lens-spectrum{flex-shrink:0;gap:3px;display:inline-flex}.lens-spectrum i{background:var(--lens-violet,#7951c8);border-radius:50%;width:4px;height:4px}.lens-spectrum i:nth-child(2){background:var(--lens-cyan,#0785aa)}.lens-spectrum i:nth-child(3){background:var(--lens-amber,#a16c17)}.lens-spectrum i:nth-child(4){background:var(--lens-rose,#c75078)}.lens-toolbar{border-color:var(--lens-border,var(--border));background:var(--lens-paper,var(--card))}.lens-panel{border:1px solid var(--lens-border,var(--border));background:var(--card);border-radius:.75rem}.lens-metric{border:1px solid var(--lens-border,var(--border));background:var(--lens-soft,var(--muted));font-family:var(--font-mono);font-variant-numeric:tabular-nums;border-radius:.375rem;align-items:center;gap:.5rem;padding:.3rem .6rem;font-size:11px;display:inline-flex}.lens-workspace :is([data-slot=table-head],.lens-table [role=columnheader]){font-family:var(--font-mono);letter-spacing:.05em;text-transform:uppercase;font-size:10px;font-weight:500}.lens-workspace [data-slot=table-header]{background:var(--lens-paper)}.lens-workspace [data-slot=table-row][data-state=selected]{background:var(--trace-row-selected);box-shadow:inset 2px 0 0 var(--lens-brand)}.lens-workspace :is([data-slot=input],[data-slot=textarea],[data-slot=select-trigger]):not([aria-invalid=true]){border-color:var(--lens-border);box-shadow:none;border-radius:.375rem}.lens-workspace 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.8px, transparent .8px);background-size:16px 16px}.lens-empty-state [data-slot=state-message]{background:var(--card);padding-inline:1.5rem}.lens-workspace-paper{background-color:var(--lens-paper);background-image:radial-gradient(var(--lens-grid) .7px, transparent .7px);background-size:14px 14px}.lens-workspace-header{border-bottom-color:var(--lens-brand)}@supports (color:color-mix(in lab, red, red)){.lens-workspace-header{border-bottom-color:color-mix(in oklab, var(--lens-brand) 12%, var(--border))}}.lens-sidebar{background-color:var(--lens-paper)}:is(.lens-shell,.lens-shell-overlay) .lens-nav-tab:is([data-state=active],[data-active]:not([data-active=false])){border-color:var(--lens-brand)}@supports (color:color-mix(in lab, red, red)){:is(.lens-shell,.lens-shell-overlay) .lens-nav-tab:is([data-state=active],[data-active]:not([data-active=false])){border-color:color-mix(in oklab, var(--lens-brand) 13%, transparent)}}:is(.lens-shell,.lens-shell-overlay) 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dummy-token-for-extended-card' + } + _extended_card = await resolver.get_agent_card( + relative_card_path=EXTENDED_AGENT_CARD_PATH, + http_kwargs={'headers': auth_headers_dict}, + ) + final_agent_card_to_use = ( + _extended_card # Update to use the extended card + ) + except Exception as e_extended: + logger.warning( + f'Failed to fetch extended agent card: {e_extended}. 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f"data:image/jpeg;base64,{base64_image1}", - }, - { - "type": "input_image", - "image_url": f"data:image/jpeg;base64,{base64_image2}", - }, - { - "type": "input_image", - "file_id": file_id1, - }, - { - "type": "input_image", - "file_id": file_id2, - } - ], - } - ], - tools=[{"type": "image_generation"}], -) - -# Process the response -image_generation_calls = [ - output - for output in response.output - if output.type == "image_generation_call" -] - -image_data = [output.result for output in image_generation_calls] - -if image_data: - image_base64 = image_data[0] - image_filename = f"edited_image_{int(time.time())}.png" - with open(image_filename, "wb") as f: - f.write(base64.b64decode(image_base64)) - print(f"Image saved to {image_filename}") -else: - # If no image is generated, there might be a text response with an explanation - text_response = [output.text for output in response.output if hasattr(output, 'text')] - if text_response: - print("No image generated. Model response:") - print("\\n".join(text_response)) - else: - print("No image data found in response.") - print("Full response for debugging:") - print(response) -`;break;case t.EndpointType.IMAGE_EDITS:a="azure"===f?` -import base64 -import os -import time -import json -from PIL import Image -import requests - -# Helper function to encode images to base64 -def encode_image(image_path): - with open(image_path, "rb") as image_file: - return base64.b64encode(image_file.read()).decode('utf-8') - -# The prompt entered by the user -prompt = "${w}" - -# Encode images to base64 -base64_image1 = encode_image("body-lotion.png") -base64_image2 = encode_image("soap.png") - -# Create file IDs -file_id1 = create_file("body-lotion.png") -file_id2 = create_file("incense-kit.png") - -response = client.responses.create( - model="${k}", - input=[ - { - "role": "user", - "content": [ - {"type": "input_text", "text": prompt}, - { - "type": "input_image", - "image_url": f"data:image/jpeg;base64,{base64_image1}", - }, - { - "type": "input_image", - "image_url": f"data:image/jpeg;base64,{base64_image2}", - }, - { - "type": "input_image", - "file_id": file_id1, - }, - { - "type": "input_image", - "file_id": file_id2, - } - ], - } - ], - tools=[{"type": "image_generation"}], -) - -# Process the response -image_generation_calls = [ - output - for output in response.output - if output.type == "image_generation_call" -] - -image_data = [output.result for output in image_generation_calls] - -if image_data: - image_base64 = image_data[0] - image_filename = f"edited_image_{int(time.time())}.png" - with open(image_filename, "wb") as f: - f.write(base64.b64decode(image_base64)) - print(f"Image saved to {image_filename}") -else: - # If no image is generated, there might be a text response with an explanation - text_response = [output.text for output in response.output if hasattr(output, 'text')] - if text_response: - print("No image generated. 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this._client.get(s6`/v1/skills/${e}?beta=true`,{...s,headers:s4([{"anthropic-beta":[...r??[],"skills-2025-10-02"].toString()},s?.headers])})}list(e={},t){let{betas:s,...r}=e??{};return this._client.getAPIList("/v1/skills?beta=true",sF,{query:r,...t,headers:s4([{"anthropic-beta":[...s??[],"skills-2025-10-02"].toString()},t?.headers])})}delete(e,t={},s){let{betas:r}=t??{};return this._client.delete(s6`/v1/skills/${e}?beta=true`,{...s,headers:s4([{"anthropic-beta":[...r??[],"skills-2025-10-02"].toString()},s?.headers])})}}r$.Versions=rR;class rO extends s1{create(e,t,s){let{betas:r,...a}=t;return this._client.post(s6`/v1/vaults/${e}/credentials?beta=true`,{body:a,...s,headers:s4([{"anthropic-beta":[...r??[],"managed-agents-2026-04-01"].toString()},s?.headers])})}retrieve(e,t,s){let{vault_id:r,betas:a}=t;return this._client.get(s6`/v1/vaults/${r}/credentials/${e}?beta=true`,{...s,headers:s4([{"anthropic-beta":[...a??[],"managed-agents-2026-04-01"].toString()},s?.headers])})}update(e,t,s){let{vault_id:r,betas:a,...n}=t;return this._client.post(s6`/v1/vaults/${r}/credentials/${e}?beta=true`,{body:n,...s,headers:s4([{"anthropic-beta":[...a??[],"managed-agents-2026-04-01"].toString()},s?.headers])})}list(e,t={},s){let{betas:r,...a}=t??{};return this._client.getAPIList(s6`/v1/vaults/${e}/credentials?beta=true`,sF,{query:a,...s,headers:s4([{"anthropic-beta":[...r??[],"managed-agents-2026-04-01"].toString()},s?.headers])})}delete(e,t,s){let{vault_id:r,betas:a}=t;return this._client.delete(s6`/v1/vaults/${r}/credentials/${e}?beta=true`,{...s,headers:s4([{"anthropic-beta":[...a??[],"managed-agents-2026-04-01"].toString()},s?.headers])})}archive(e,t,s){let{vault_id:r,betas:a}=t;return this._client.post(s6`/v1/vaults/${r}/credentials/${e}/archive?beta=true`,{...s,headers:s4([{"anthropic-beta":[...a??[],"managed-agents-2026-04-01"].toString()},s?.headers])})}}class rL extends s1{constructor(){super(...arguments),this.credentials=new rO(this._client)}create(e,t){let{betas:s,...r}=e;return this._client.post("/v1/vaults?beta=true",{body:r,...t,headers:s4([{"anthropic-beta":[...s??[],"managed-agents-2026-04-01"].toString()},t?.headers])})}retrieve(e,t={},s){let{betas:r}=t??{};return this._client.get(s6`/v1/vaults/${e}?beta=true`,{...s,headers:s4([{"anthropic-beta":[...r??[],"managed-agents-2026-04-01"].toString()},s?.headers])})}update(e,t,s){let{betas:r,...a}=t;return this._client.post(s6`/v1/vaults/${e}?beta=true`,{body:a,...s,headers:s4([{"anthropic-beta":[...r??[],"managed-agents-2026-04-01"].toString()},s?.headers])})}list(e={},t){let{betas:s,...r}=e??{};return 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rD(e){return e?.output_config?.format}function rz(e,t,s){let r=rD(t);return t&&"parse"in(r??{})?rB(e,t,s):{...e,content:e.content.map(e=>"text"===e.type?Object.defineProperty({...e},"parsed_output",{value:null,enumerable:!1}):e),parsed_output:null}}function rB(e,t,s){let r=null,a=e.content.map(e=>{if("text"===e.type){let s=function(e,t){let s=rD(e);if(s?.type!=="json_schema")return null;try{if("parse"in s)return s.parse(t);return JSON.parse(t)}catch(e){throw new t3(`Failed to parse structured output: ${e}`)}}(t,e.text);return null===r&&(r=s),Object.defineProperty({...e},"parsed_output",{value:s,enumerable:!1})}return e});return{...e,content:a,parsed_output:r}}rU.Models=rr,rU.Messages=rE,rU.Agents=ri,rU.Environments=s8,rU.Sessions=rM,rU.Vaults=rL,rU.MemoryStores=rd,rU.Files=rs,rU.Skills=r$,rU.UserProfiles=ra;let rq="__json_buf";function rF(e){return"tool_use"===e.type||"server_tool_use"===e.type}class rW{constructor(e,t){W.add(this),this.messages=[],this.receivedMessages=[],H.set(this,void 0),V.set(this,null),this.controller=new AbortController,G.set(this,void 0),J.set(this,()=>{}),K.set(this,()=>{}),X.set(this,void 0),Y.set(this,()=>{}),Q.set(this,()=>{}),Z.set(this,{}),ee.set(this,!1),et.set(this,!1),es.set(this,!1),er.set(this,!1),ea.set(this,void 0),en.set(this,void 0),ei.set(this,void 0),ed.set(this,e=>{if(t0(this,et,!0,"f"),t4(e)&&(e=new t8),e instanceof t8)return t0(this,es,!0,"f"),this._emit("abort",e);if(e instanceof t3)return this._emit("error",e);if(e instanceof Error){let t=new t3(e.message);return t.cause=e,this._emit("error",t)}return this._emit("error",new t3(String(e)))}),t0(this,G,new Promise((e,t)=>{t0(this,J,e,"f"),t0(this,K,t,"f")}),"f"),t0(this,X,new Promise((e,t)=>{t0(this,Y,e,"f"),t0(this,Q,t,"f")}),"f"),t1(this,G,"f").catch(()=>{}),t1(this,X,"f").catch(()=>{}),t0(this,V,e,"f"),t0(this,ei,t?.logger??console,"f")}get response(){return t1(this,ea,"f")}get 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r,a=s?.signal;a&&(a.aborted&&this.controller.abort(),r=this.controller.abort.bind(this.controller),a.addEventListener("abort",r));try{t1(this,W,"m",ec).call(this);let{response:r,data:a}=await e.create({...t,stream:!0},{...s,signal:this.controller.signal}).withResponse();for await(let e of(this._connected(r),a))t1(this,W,"m",eu).call(this,e);if(a.controller.signal?.aborted)throw new t8;t1(this,W,"m",em).call(this)}finally{a&&r&&a.removeEventListener("abort",r)}}_connected(e){this.ended||(t0(this,ea,e,"f"),t0(this,en,e?.headers.get("request-id"),"f"),t1(this,J,"f").call(this,e),this._emit("connect"))}get ended(){return t1(this,ee,"f")}get errored(){return t1(this,et,"f")}get aborted(){return t1(this,es,"f")}abort(){this.controller.abort()}on(e,t){return(t1(this,Z,"f")[e]||(t1(this,Z,"f")[e]=[])).push({listener:t}),this}off(e,t){let s=t1(this,Z,"f")[e];if(!s)return this;let r=s.findIndex(e=>e.listener===t);return r>=0&&s.splice(r,1),this}once(e,t){return(t1(this,Z,"f")[e]||(t1(this,Z,"f")[e]=[])).push({listener:t,once:!0}),this}emitted(e){return new Promise((t,s)=>{t0(this,er,!0,"f"),"error"!==e&&this.once("error",s),this.once(e,t)})}async done(){t0(this,er,!0,"f"),await t1(this,X,"f")}get currentMessage(){return t1(this,H,"f")}async finalMessage(){return await this.done(),t1(this,W,"m",eo).call(this)}async finalText(){return await this.done(),t1(this,W,"m",el).call(this)}_emit(e,...t){if(t1(this,ee,"f"))return;"end"===e&&(t0(this,ee,!0,"f"),t1(this,Y,"f").call(this));let s=t1(this,Z,"f")[e];if(s&&(t1(this,Z,"f")[e]=s.filter(e=>!e.once),s.forEach(({listener:e})=>e(...t))),"abort"===e){let e=t[0];t1(this,er,"f")||s?.length||Promise.reject(e),t1(this,K,"f").call(this,e),t1(this,Q,"f").call(this,e),this._emit("end");return}if("error"===e){let e=t[0];t1(this,er,"f")||s?.length||Promise.reject(e),t1(this,K,"f").call(this,e),t1(this,Q,"f").call(this,e),this._emit("end")}}_emitFinal(){this.receivedMessages.at(-1)&&this._emit("finalMessage",t1(this,W,"m",eo).call(this))}async _fromReadableStream(e,t){let s,r=t?.signal;r&&(r.aborted&&this.controller.abort(),s=this.controller.abort.bind(this.controller),r.addEventListener("abort",s));try{t1(this,W,"m",ec).call(this),this._connected(null);let t=sM.fromReadableStream(e,this.controller);for await(let e of t)t1(this,W,"m",eu).call(this,e);if(t.controller.signal?.aborted)throw new t8;t1(this,W,"m",em).call(this)}finally{r&&s&&r.removeEventListener("abort",s)}}[(H=new WeakMap,V=new WeakMap,G=new WeakMap,J=new WeakMap,K=new WeakMap,X=new WeakMap,Y=new WeakMap,Q=new WeakMap,Z=new WeakMap,ee=new WeakMap,et=new WeakMap,es=new WeakMap,er=new WeakMap,ea=new WeakMap,en=new WeakMap,ei=new WeakMap,ed=new WeakMap,W=new WeakSet,eo=function(){if(0===this.receivedMessages.length)throw new t3("stream ended without producing a Message with role=assistant");return this.receivedMessages.at(-1)},el=function(){if(0===this.receivedMessages.length)throw new t3("stream ended without producing a Message with role=assistant");let e=this.receivedMessages.at(-1).content.filter(e=>"text"===e.type).map(e=>e.text);if(0===e.length)throw new t3("stream ended without producing a content block with type=text");return e.join(" ")},ec=function(){this.ended||t0(this,H,void 0,"f")},eu=function(e){if(this.ended)return;let t=t1(this,W,"m",eh).call(this,e);switch(this._emit("streamEvent",e,t),e.type){case"content_block_delta":{let s=t.content.at(-1);switch(e.delta.type){case"text_delta":"text"===s.type&&this._emit("text",e.delta.text,s.text||"");break;case"citations_delta":"text"===s.type&&this._emit("citation",e.delta.citation,s.citations??[]);break;case"input_json_delta":rF(s)&&s.input&&this._emit("inputJson",e.delta.partial_json,s.input);break;case"thinking_delta":"thinking"===s.type&&this._emit("thinking",e.delta.thinking,s.thinking);break;case"signature_delta":"thinking"===s.type&&this._emit("signature",s.signature);break;default:rH(e.delta)}break}case"message_stop":this._addMessageParam(t),this._addMessage(rz(t,t1(this,V,"f"),{logger:t1(this,ei,"f")}),!0);break;case"content_block_stop":this._emit("contentBlock",t.content.at(-1));break;case"message_start":t0(this,H,t,"f")}},em=function(){if(this.ended)throw new t3("stream has ended, this shouldn't happen");let e=t1(this,H,"f");if(!e)throw new t3("request ended without sending any chunks");return t0(this,H,void 0,"f"),rz(e,t1(this,V,"f"),{logger:t1(this,ei,"f")})},eh=function(e){let t=t1(this,H,"f");if("message_start"===e.type){if(t)throw new t3(`Unexpected event order, got ${e.type} before receiving "message_stop"`);return e.message}if(!t)throw new t3(`Unexpected event order, got ${e.type} before "message_start"`);switch(e.type){case"message_stop":case"content_block_stop":return t;case"message_delta":return t.stop_reason=e.delta.stop_reason,t.stop_sequence=e.delta.stop_sequence,t.usage.output_tokens=e.usage.output_tokens,null!=e.usage.input_tokens&&(t.usage.input_tokens=e.usage.input_tokens),null!=e.usage.cache_creation_input_tokens&&(t.usage.cache_creation_input_tokens=e.usage.cache_creation_input_tokens),null!=e.usage.cache_read_input_tokens&&(t.usage.cache_read_input_tokens=e.usage.cache_read_input_tokens),null!=e.usage.server_tool_use&&(t.usage.server_tool_use=e.usage.server_tool_use),t;case"content_block_start":return t.content.push({...e.content_block}),t;case"content_block_delta":{let s=t.content.at(e.index);switch(e.delta.type){case"text_delta":s?.type==="text"&&(t.content[e.index]={...s,text:(s.text||"")+e.delta.text});break;case"citations_delta":s?.type==="text"&&(t.content[e.index]={...s,citations:[...s.citations??[],e.delta.citation]});break;case"input_json_delta":if(s&&rF(s)){let r=s[rq]||"";r+=e.delta.partial_json;let a={...s};Object.defineProperty(a,rq,{value:r,enumerable:!1,writable:!0}),r&&(a.input=rx(r)),t.content[e.index]=a}break;case"thinking_delta":s?.type==="thinking"&&(t.content[e.index]={...s,thinking:s.thinking+e.delta.thinking});break;case"signature_delta":s?.type==="thinking"&&(t.content[e.index]={...s,signature:e.delta.signature});break;default:rH(e.delta)}return t}}},Symbol.asyncIterator)](){let e=[],t=[],s=!1;return this.on("streamEvent",s=>{let r=t.shift();r?r.resolve(s):e.push(s)}),this.on("end",()=>{for(let e of(s=!0,t))e.resolve(void 0);t.length=0}),this.on("abort",e=>{for(let r of(s=!0,t))r.reject(e);t.length=0}),this.on("error",e=>{for(let r of(s=!0,t))r.reject(e);t.length=0}),{next:async()=>e.length?{value:e.shift(),done:!1}:s?{value:void 0,done:!0}:new Promise((e,s)=>t.push({resolve:e,reject:s})).then(e=>e?{value:e,done:!1}:{value:void 0,done:!0}),return:async()=>(this.abort(),{value:void 0,done:!0})}}toReadableStream(){return new sM(this[Symbol.asyncIterator].bind(this),this.controller).toReadableStream()}}function rH(e){}class rV extends s1{create(e,t){return this._client.post("/v1/messages/batches",{body:e,...t})}retrieve(e,t){return this._client.get(s6`/v1/messages/batches/${e}`,t)}list(e={},t){return this._client.getAPIList("/v1/messages/batches",sq,{query:e,...t})}delete(e,t){return this._client.delete(s6`/v1/messages/batches/${e}`,t)}cancel(e,t){return this._client.post(s6`/v1/messages/batches/${e}/cancel`,t)}async results(e,t){let s=await this.retrieve(e);if(!s.results_url)throw new t3(`No batch \`results_url\`; Has it finished processing? ${s.processing_status} - ${s.id}`);return this._client.get(s.results_url,{...t,headers:s4([{Accept:"application/binary"},t?.headers]),stream:!0,__binaryResponse:!0})._thenUnwrap((e,t)=>rc.fromResponse(t.response,t.controller))}}class rG extends s1{constructor(){super(...arguments),this.batches=new rV(this._client)}create(e,t){e.model in rJ&&console.warn(`The model '${e.model}' is deprecated and will reach end-of-life on ${rJ[e.model]} -Please migrate to a newer model. Visit https://docs.anthropic.com/en/docs/resources/model-deprecations for more information.`),rK.includes(e.model)&&e.thinking&&"enabled"===e.thinking.type&&console.warn(`Using Claude with ${e.model} and 'thinking.type=enabled' is deprecated. Use 'thinking.type=adaptive' instead which results in better model performance in our testing: https://platform.claude.com/docs/en/build-with-claude/adaptive-thinking`);let s=this._client._options.timeout;if(!e.stream&&null==s){let t=rm[e.model]??void 0;s=this._client.calculateNonstreamingTimeout(e.max_tokens,t)}let r=rt(e.tools,e.messages);return this._client.post("/v1/messages",{body:e,timeout:s??6e5,...t,headers:s4([r,t?.headers]),stream:e.stream??!1})}parse(e,t){return this.create(e,t).then(t=>rB(t,e,{logger:this._client.logger??console}))}stream(e,t){return rW.createMessage(this,e,t,{logger:this._client.logger??console})}countTokens(e,t){return this._client.post("/v1/messages/count_tokens",{body:e,...t})}}let rJ={"claude-1.3":"November 6th, 2024","claude-1.3-100k":"November 6th, 2024","claude-instant-1.1":"November 6th, 2024","claude-instant-1.1-100k":"November 6th, 2024","claude-instant-1.2":"November 6th, 2024","claude-3-sonnet-20240229":"July 21st, 2025","claude-3-opus-20240229":"January 5th, 2026","claude-2.1":"July 21st, 2025","claude-2.0":"July 21st, 2025","claude-3-7-sonnet-latest":"February 19th, 2026","claude-3-7-sonnet-20250219":"February 19th, 2026","claude-3-5-haiku-latest":"February 19th, 2026","claude-3-5-haiku-20241022":"February 19th, 2026","claude-opus-4-0":"June 15th, 2026","claude-opus-4-20250514":"June 15th, 2026","claude-sonnet-4-0":"June 15th, 2026","claude-sonnet-4-20250514":"June 15th, 2026"},rK=["claude-mythos-preview","claude-opus-4-6"];rG.Batches=rV;class rX extends s1{retrieve(e,t={},s){let{betas:r}=t??{};return this._client.get(s6`/v1/models/${e}`,{...s,headers:s4([{...r?.toString()!=null?{"anthropic-beta":r?.toString()}:void 0},s?.headers])})}list(e={},t){let{betas:s,...r}=e??{};return this._client.getAPIList("/v1/models",sq,{query:r,...t,headers:s4([{...s?.toString()!=null?{"anthropic-beta":s?.toString()}:void 0},t?.headers])})}}class rY extends s1{create(e,t){let{betas:s,...r}=e;return this._client.post("/v1/complete",{body:r,timeout:this._client._options.timeout??6e5,...t,headers:s4([{...s?.toString()!=null?{"anthropic-beta":s?.toString()}:void 0},t?.headers]),stream:e.stream??!1})}}let rQ=e=>void 0!==globalThis.process?globalThis.process.env?.[e]?.trim()||void 0:void 0!==globalThis.Deno&&globalThis.Deno.env?.get?.(e)?.trim()||void 0;class rZ{constructor({baseURL:e=rQ("ANTHROPIC_BASE_URL"),apiKey:t=rQ("ANTHROPIC_API_KEY")??null,authToken:s=rQ("ANTHROPIC_AUTH_TOKEN")??null,...r}={}){ep.add(this),eg.set(this,void 0);const a={apiKey:t,authToken:s,...r,baseURL:e||"https://api.anthropic.com"};if(!a.dangerouslyAllowBrowser&&"u">typeof window&&void 0!==window.document&&"u">typeof navigator)throw new t3("It looks like you're running in a browser-like environment.\n\nThis is disabled by default, as it risks exposing your secret API credentials to attackers.\nIf you understand the risks and have appropriate mitigations in place,\nyou can set the `dangerouslyAllowBrowser` option to `true`, e.g.,\n\nnew Anthropic({ apiKey, dangerouslyAllowBrowser: true });\n");this.baseURL=a.baseURL,this.timeout=a.timeout??ef.DEFAULT_TIMEOUT,this.logger=a.logger??console;const n="warn";this.logLevel=n,this.logLevel=sk(a.logLevel,"ClientOptions.logLevel",this)??sk(rQ("ANTHROPIC_LOG"),"process.env['ANTHROPIC_LOG']",this)??n,this.fetchOptions=a.fetchOptions,this.maxRetries=a.maxRetries??2,this.fetch=a.fetch??function(){if("u">typeof fetch)return fetch;throw Error("`fetch` is not defined as a global; Either pass `fetch` to the client, `new Anthropic({ fetch })` or polyfill the global, `globalThis.fetch = fetch`")}(),t0(this,eg,sj,"f");const i=rQ("ANTHROPIC_CUSTOM_HEADERS");if(i){const e={};for(const t of i.split("\n")){const s=t.indexOf(":");s>=0&&(e[t.substring(0,s).trim()]=t.substring(s+1).trim())}a.defaultHeaders={...e,...a.defaultHeaders}}this._options=a,this.apiKey="string"==typeof t?t:null,this.authToken=s}withOptions(e){return new this.constructor({...this._options,baseURL:this.baseURL,maxRetries:this.maxRetries,timeout:this.timeout,logger:this.logger,logLevel:this.logLevel,fetch:this.fetch,fetchOptions:this.fetchOptions,apiKey:this.apiKey,authToken:this.authToken,...e})}defaultQuery(){return this._options.defaultQuery}validateHeaders({values:e,nulls:t}){if(!(e.get("x-api-key")||e.get("authorization")||this.apiKey&&e.get("x-api-key")||t.has("x-api-key")||this.authToken&&e.get("authorization"))&&!t.has("authorization"))throw Error('Could not resolve authentication method. 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n={};this.idempotencyHeader&&"get"!==s&&(e.idempotencyKey||(e.idempotencyKey=this.defaultIdempotencyKey()),n[this.idempotencyHeader]=e.idempotencyKey);let i=s4([n,{Accept:"application/json","User-Agent":this.getUserAgent(),"X-Stainless-Retry-Count":String(a),...e.timeout?{"X-Stainless-Timeout":String(Math.trunc(e.timeout/1e3))}:{},...t??(t=(()=>{let e="u">typeof Deno&&null!=Deno.build?"deno":"u">typeof EdgeRuntime?"edge":"[object process]"===Object.prototype.toString.call(void 0!==globalThis.process?globalThis.process:0)?"node":"unknown";if("deno"===e)return{"X-Stainless-Lang":"js","X-Stainless-Package-Version":sp,"X-Stainless-OS":sg(Deno.build.os),"X-Stainless-Arch":sf(Deno.build.arch),"X-Stainless-Runtime":"deno","X-Stainless-Runtime-Version":"string"==typeof Deno.version?Deno.version:Deno.version?.deno??"unknown"};if("u">typeof 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LLM Cost Estimate Report

+

${r} model${1!==r?"s":""} configured

+ +
+

Combined Totals

+
+
+
Total Per Request
+
${W(e.totals.cost_per_request)}
+
+
+
Total Daily
+
${W(e.totals.daily_cost)}
+
+
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Total Monthly
+
${W(e.totals.monthly_cost)}
+
+
+ ${e.totals.margin_per_request>0?` +
+
+
Margin/Request
+
${W(e.totals.margin_per_request)}
+
+
+
Daily Margin
+
${W(e.totals.daily_margin)}
+
+
+
Monthly Margin
+
${W(e.totals.monthly_margin)}
+
+
+ `:""} +
+ +

Model Breakdown

+ ${s.map(e=>{let t;return t=e.result,` +
+

${t.model} ${t.provider?`(${t.provider})`:""}

+ +
+

Input Tokens per Request: ${K(t.input_tokens)}

+

Output Tokens per Request: ${K(t.output_tokens)}

+ ${t.num_requests_per_day?`

Requests per Day: ${K(t.num_requests_per_day)}

`:""} + ${t.num_requests_per_month?`

Requests per Month: ${K(t.num_requests_per_month)}

`:""} +
+ + + + + + ${null!==t.daily_cost?"":""} + ${null!==t.monthly_cost?"":""} + + + + + ${null!==t.daily_cost?``:""} + ${null!==t.monthly_cost?``:""} + + + + + ${null!==t.daily_cost?``:""} + ${null!==t.monthly_cost?``:""} + + + + + ${null!==t.daily_cost?``:""} + ${null!==t.monthly_cost?``:""} + + + + + ${null!==t.daily_cost?``:""} + ${null!==t.monthly_cost?``:""} + +
Cost TypePer RequestDailyMonthly
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Output Cost${W(t.output_cost_per_request)}${W(t.daily_output_cost)}${W(t.monthly_output_cost)}
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Total${W(t.cost_per_request)}${W(t.daily_cost)}${W(t.monthly_cost)}
+
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tD{run(e,t){return this._client.post("/fine_tuning/alpha/graders/run",{body:e,...t})}validate(e,t){return this._client.post("/fine_tuning/alpha/graders/validate",{body:e,...t})}}class t9 extends tD{constructor(){super(...arguments),this.graders=new t4(this._client)}}t9.Graders=t4;class t7 extends tD{create(e,t,r){return this._client.getAPIList(`/fine_tuning/checkpoints/${e}/permissions`,re,{body:t,method:"post",...r})}retrieve(e,t={},r){return tv(t)?this.retrieve(e,{},t):this._client.get(`/fine_tuning/checkpoints/${e}/permissions`,{query:t,...r})}del(e,t,r){return this._client.delete(`/fine_tuning/checkpoints/${e}/permissions/${t}`,r)}}class re extends tq{}t7.PermissionCreateResponsesPage=re;class rt extends tD{constructor(){super(...arguments),this.permissions=new t7(this._client)}}rt.Permissions=t7,rt.PermissionCreateResponsesPage=re;class rr extends tD{list(e,t={},r){return tv(t)?this.list(e,{},t):this._client.getAPIList(`/fine_tuning/jobs/${e}/checkpoints`,rs,{query:t,...r})}}class 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this._client.post(`/vector_stores/${e}/files/${t}`,{body:r,...s,headers:{"OpenAI-Beta":"assistants=v2",...s?.headers}})}list(e,t={},r){return tv(t)?this.list(e,{},t):this._client.getAPIList(`/vector_stores/${e}/files`,rf,{query:t,...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}del(e,t,r){return this._client.delete(`/vector_stores/${e}/files/${t}`,{...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}async createAndPoll(e,t,r){let s=await this.create(e,t,r);return await this.poll(e,s.id,r)}async poll(e,t,r){let s={...r?.headers,"X-Stainless-Poll-Helper":"true"};for(r?.pollIntervalMs&&(s["X-Stainless-Custom-Poll-Interval"]=r.pollIntervalMs.toString());;){let n=await this.retrieve(e,t,{...r,headers:s}).withResponse(),i=n.data;switch(i.status){case"in_progress":let a=5e3;if(r?.pollIntervalMs)a=r.pollIntervalMs;else{let e=n.response.headers.get("openai-poll-after-ms");if(e){let t=parseInt(e);isNaN(t)||(a=t)}}await tP(a);break;case"failed":case"completed":return 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tv(e)?this.list({},e):this._client.getAPIList("/vector_stores",rg,{query:e,...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}del(e,t){return this._client.delete(`/vector_stores/${e}`,{...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}search(e,t,r){return this._client.getAPIList(`/vector_stores/${e}/search`,ry,{body:t,method:"post",...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}}class rg extends tX{}class ry extends tq{}rm.VectorStoresPage=rg,rm.VectorStoreSearchResponsesPage=ry,rm.Files=rh,rm.VectorStoreFilesPage=rf,rm.FileContentResponsesPage=rd,rm.FileBatches=rp;class rw extends tD{create(e,t){return this._client.post("/assistants",{body:e,...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}retrieve(e,t){return this._client.get(`/assistants/${e}`,{...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}update(e,t,r){return this._client.post(`/assistants/${e}`,{body:t,...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}list(e={},t){return tv(e)?this.list({},e):this._client.getAPIList("/assistants",rb,{query:e,...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}del(e,t){return this._client.delete(`/assistants/${e}`,{...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}}class rb extends tX{}function r_(e){return"function"==typeof e.parse}rw.AssistantsPage=rb;let rv=e=>e?.role==="assistant",rx=e=>e?.role==="function",rA=e=>e?.role==="tool";var rS=function(e,t,r,s,n){if("m"===s)throw TypeError("Private method is not writable");if("a"===s&&!n)throw TypeError("Private accessor was defined without a setter");if("function"==typeof t?e!==t||!n:!t.has(e))throw TypeError("Cannot write private member to an object whose class did not declare it");return"a"===s?n.call(e,r):n?n.value=r:t.set(e,r),r},rE=function(e,t,r,s){if("a"===r&&!s)throw TypeError("Private accessor was defined without a 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e=t[0];rE(this,S,"f")||r?.length||Promise.reject(e),rE(this,g,"f").call(this,e),rE(this,b,"f").call(this,e),this._emit("end")}}_emitFinal(){}}function rI(e){return e?.$brand==="auto-parseable-response-format"}function rP(e){return e?.$brand==="auto-parseable-tool"}function rO(e,t){let r=e.choices.map(e=>{var r,s;if("length"===e.finish_reason)throw new e0;if("content_filter"===e.finish_reason)throw new e1;return{...e,message:{...e.message,...e.message.tool_calls?{tool_calls:e.message.tool_calls?.map(e=>{var r,s;let n;return r=t,s=e,n=r.tools?.find(e=>e.function?.name===s.function.name),{...s,function:{...s.function,parsed_arguments:rP(n)?n.$parseRaw(s.function.arguments):n?.function.strict?JSON.parse(s.function.arguments):null}}})??void 0}:void 0,parsed:e.message.content&&!e.message.refusal?(r=t,s=e.message.content,r.response_format?.type!=="json_schema"?null:r.response_format?.type==="json_schema"?"$parseRaw"in 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s=r?.signal;s&&(s.aborted&&this.controller.abort(),s.addEventListener("abort",()=>this.controller.abort())),rC(this,R,"m",k).call(this,t);let n=await e.chat.completions.create({...t,stream:!1},{...r,signal:this.controller.signal});return this._connected(),this._addChatCompletion(rO(n,t))}async _runChatCompletion(e,t,r){for(let e of t.messages)this._addMessage(e,!1);return await this._createChatCompletion(e,t,r)}async _runFunctions(e,t,r){let s="function",{function_call:n="auto",stream:i,...a}=t,o="string"!=typeof n&&n?.name,{maxChatCompletions:l=10}=r||{},u={};for(let e of t.functions)u[e.name||e.function.name]=e;let c=t.functions.map(e=>({name:e.name||e.function.name,parameters:e.parameters,description:e.description}));for(let e of t.messages)this._addMessage(e,!1);for(let t=0;tJSON.stringify(e.name)).join(", ")}. Please try again`;this._addMessage({role:s,name:h,content:e});continue}try{t=r_(d)?await d.parse(f):f}catch(e){this._addMessage({role:s,name:h,content:e instanceof Error?e.message:String(e)});continue}let p=await d.function(t,this),m=rC(this,R,"m",T).call(this,p);if(this._addMessage({role:s,name:h,content:m}),o)return}}async _runTools(e,t,r){let s="tool",{tool_choice:n="auto",stream:i,...a}=t,o="string"!=typeof n&&n?.function?.name,{maxChatCompletions:l=10}=r||{},u=t.tools.map(e=>{if(rP(e)){if(!e.$callback)throw new eF("Tool given to `.runTools()` that does not have an associated function");return{type:"function",function:{function:e.$callback,name:e.function.name,description:e.function.description||"",parameters:e.function.parameters,parse:e.$parseRaw,strict:!0}}}return e}),c={};for(let e of u)"function"===e.type&&(c[e.function.name||e.function.function.name]=e.function);let h="tools"in t?u.map(e=>"function"===e.type?{type:"function",function:{name:e.function.name||e.function.function.name,parameters:e.function.parameters,description:e.function.description,strict:e.function.strict}}:e):void 0;for(let e of t.messages)this._addMessage(e,!1);for(let t=0;tJSON.stringify(e)).join(", ")}. Please try again`;this._addMessage({role:s,tool_call_id:r,content:e});continue}try{t=r_(a)?await a.parse(i):i}catch(t){let e=t instanceof Error?t.message:String(t);this._addMessage({role:s,tool_call_id:r,content:e});continue}let l=await a.function(t,this),u=rC(this,R,"m",T).call(this,l);if(this._addMessage({role:s,tool_call_id:r,content:u}),o)return}}}}R=new WeakSet,I=function(){return rC(this,R,"m",P).call(this).content??null},P=function(){let e=this.messages.length;for(;e-- >0;){let t=this.messages[e];if(rv(t)){let{function_call:e,...r}=t,s={...r,content:t.content??null,refusal:t.refusal??null};return e&&(s.function_call=e),s}}throw new eF("stream ended without producing a ChatCompletionMessage with role=assistant")},O=function(){for(let e=this.messages.length-1;e>=0;e--){let t=this.messages[e];if(rv(t)&&t?.function_call)return t.function_call;if(rv(t)&&t?.tool_calls?.length)return t.tool_calls.at(-1)?.function}},$=function(){for(let e=this.messages.length-1;e>=0;e--){let t=this.messages[e];if(rx(t)&&null!=t.content||rA(t)&&null!=t.content&&"string"==typeof t.content&&this.messages.some(e=>"assistant"===e.role&&e.tool_calls?.some(e=>"function"===e.type&&e.id===t.tool_call_id)))return t.content}},C=function(){let e={completion_tokens:0,prompt_tokens:0,total_tokens:0};for(let{usage:t}of this._chatCompletions)t&&(e.completion_tokens+=t.completion_tokens,e.prompt_tokens+=t.prompt_tokens,e.total_tokens+=t.total_tokens);return e},k=function(e){if(null!=e.n&&e.n>1)throw new eF("ChatCompletion convenience helpers only support n=1 at this time. 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e=[];try{for(;"]"!==r[i];)e.push(l()),d(),","===r[i]&&i++}catch(t){if(rB.ARR&s)return e;a("Expected ']' at end of array")}return i++,e},f=()=>{if(0===i){"-"===r&&rB.NUM&s&&a("Not sure what '-' is");try{return JSON.parse(r)}catch(e){if(rB.NUM&s)try{if("."===r[r.length-1])return JSON.parse(r.substring(0,r.lastIndexOf(".")));return JSON.parse(r.substring(0,r.lastIndexOf("e")))}catch(e){}o(String(e))}}let e=i;for("-"===r[i]&&i++;r[i]&&!",]}".includes(r[i]);)i++;i!=n||rB.NUM&s||a("Unterminated number literal");try{return JSON.parse(r.substring(e,i))}catch(t){"-"===r.substring(e,i)&&rB.NUM&s&&a("Not sure what '-' is");try{return JSON.parse(r.substring(e,r.lastIndexOf("e")))}catch(e){o(String(e))}}},d=()=>{for(;it._fromReadableStream(e)),t}static createChatCompletion(e,t,r){let s=new rD(t);return s._run(()=>s._runChatCompletion(e,{...t,stream:!0},{...r,headers:{...r?.headers,"X-Stainless-Helper-Method":"stream"}})),s}async _createChatCompletion(e,t,r){super._createChatCompletion;let 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of(e.finish_reason&&(rU(this,B,"m",W).call(this,e),null!=s.current_tool_call_index&&rU(this,B,"m",F).call(this,e,s.current_tool_call_index)),r.delta.tool_calls??[]))s.current_tool_call_index!==t.index&&(rU(this,B,"m",W).call(this,e),null!=s.current_tool_call_index&&rU(this,B,"m",F).call(this,e,s.current_tool_call_index)),s.current_tool_call_index=t.index;for(let t of r.delta.tool_calls??[]){let r=e.message.tool_calls?.[t.index];r?.type&&(r?.type==="function"?this._emit("tool_calls.function.arguments.delta",{name:r.function?.name,index:t.index,arguments:r.function.arguments,parsed_arguments:r.function.parsed_arguments,arguments_delta:t.function?.arguments??""}):rq(r?.type))}}},F=function(e,t){if(rU(this,B,"m",U).call(this,e).done_tool_calls.has(t))return;let r=e.message.tool_calls?.[t];if(!r)throw Error("no tool call snapshot");if(!r.type)throw Error("tool call snapshot missing `type`");if("function"===r.type){let 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new eF("stream has ended, this shouldn't happen");let e=rU(this,j,"f");if(!e)throw new eF("request ended without sending any chunks");return rL(this,j,void 0,"f"),rL(this,N,[],"f"),function(e,t){var r;let{id:s,choices:n,created:i,model:a,system_fingerprint:o,...l}=e;return r={...l,id:s,choices:n.map(({message:t,finish_reason:r,index:s,logprobs:n,...i})=>{if(!r)throw new eF(`missing finish_reason for choice ${s}`);let{content:a=null,function_call:o,tool_calls:l,...u}=t,c=t.role;if(!c)throw new eF(`missing role for choice ${s}`);if(o){let{arguments:e,name:l}=o;if(null==e)throw new eF(`missing function_call.arguments for choice ${s}`);if(!l)throw new eF(`missing function_call.name for choice ${s}`);return{...i,message:{content:a,function_call:{arguments:e,name:l},role:c,refusal:t.refusal??null},finish_reason:r,index:s,logprobs:n}}return l?{...i,index:s,finish_reason:r,logprobs:n,message:{...u,role:c,content:a,refusal:t.refusal??null,tool_calls:l.map((t,r)=>{let{function:n,type:i,id:a,...o}=t,{arguments:l,name:u,...c}=n||{};if(null==a)throw new eF(`missing choices[${s}].tool_calls[${r}].id -${rF(e)}`);if(null==i)throw new eF(`missing choices[${s}].tool_calls[${r}].type -${rF(e)}`);if(null==u)throw new eF(`missing choices[${s}].tool_calls[${r}].function.name -${rF(e)}`);if(null==l)throw new eF(`missing choices[${s}].tool_calls[${r}].function.arguments -${rF(e)}`);return{...o,id:a,type:i,function:{...c,name:u,arguments:l}}})}}:{...i,message:{...u,content:a,role:c,refusal:t.refusal??null},finish_reason:r,index:s,logprobs:n}}),created:i,model:a,object:"chat.completion",...o?{system_fingerprint:o}:{}},t&&r$(t)?rO(r,t):{...r,choices:r.choices.map(e=>({...e,message:{...e.message,parsed:null,...e.message.tool_calls?{tool_calls:e.message.tool_calls}:void 0}}))}}(e,rU(this,M,"f"))},X=function(){let e=rU(this,M,"f")?.response_format;return rI(e)?e:null},J=function(e){var t,r,s,n;let i=rU(this,j,"f"),{choices:a,...o}=e;for(let{delta:a,finish_reason:l,index:u,logprobs:c=null,...h}of(i?Object.assign(i,o):i=rL(this,j,{...o,choices:[]},"f"),e.choices)){let e=i.choices[u];if(e||(e=i.choices[u]={finish_reason:l,index:u,message:{},logprobs:c,...h}),c)if(e.logprobs){let{content:s,refusal:n,...i}=c;rW(i),Object.assign(e.logprobs,i),s&&((t=e.logprobs).content??(t.content=[]),e.logprobs.content.push(...s)),n&&((r=e.logprobs).refusal??(r.refusal=[]),e.logprobs.refusal.push(...n))}else e.logprobs=Object.assign({},c);if(l&&(e.finish_reason=l,rU(this,M,"f")&&r$(rU(this,M,"f")))){if("length"===l)throw new e0;if("content_filter"===l)throw new e1}if(Object.assign(e,h),!a)continue;let{content:o,refusal:f,function_call:d,role:p,tool_calls:m,...g}=a;if(rW(g),Object.assign(e.message,g),f&&(e.message.refusal=(e.message.refusal||"")+f),p&&(e.message.role=p),d&&(e.message.function_call?(d.name&&(e.message.function_call.name=d.name),d.arguments&&((s=e.message.function_call).arguments??(s.arguments=""),e.message.function_call.arguments+=d.arguments)):e.message.function_call=d),o&&(e.message.content=(e.message.content||"")+o,!e.message.refusal&&rU(this,B,"m",X).call(this)&&(e.message.parsed=rj(e.message.content))),m)for(let{index:t,id:r,type:s,function:i,...a}of(e.message.tool_calls||(e.message.tool_calls=[]),m)){let o=(n=e.message.tool_calls)[t]??(n[t]={});Object.assign(o,a),r&&(o.id=r),s&&(o.type=s),i&&(o.function??(o.function={name:i.name??"",arguments:""})),i?.name&&(o.function.name=i.name),i?.arguments&&(o.function.arguments+=i.arguments,function(e,t){if(!e)return!1;let r=e.tools?.find(e=>e.function?.name===t.function.name);return rP(r)||r?.function.strict||!1}(rU(this,M,"f"),o)&&(o.function.parsed_arguments=rj(o.function.arguments)))}}return i},Symbol.asyncIterator)](){let e=[],t=[],r=!1;return this.on("chunk",r=>{let s=t.shift();s?s.resolve(r):e.push(r)}),this.on("end",()=>{for(let e of(r=!0,t))e.resolve(void 0);t.length=0}),this.on("abort",e=>{for(let s of(r=!0,t))s.reject(e);t.length=0}),this.on("error",e=>{for(let s of(r=!0,t))s.reject(e);t.length=0}),{next:async()=>e.length?{value:e.shift(),done:!1}:r?{value:void 0,done:!0}:new Promise((e,r)=>t.push({resolve:e,reject:r})).then(e=>e?{value:e,done:!1}:{value:void 0,done:!0}),return:async()=>(this.abort(),{value:void 0,done:!0})}}toReadableStream(){return new e3(this[Symbol.asyncIterator].bind(this),this.controller).toReadableStream()}}function rF(e){return JSON.stringify(e)}function rW(e){}function rq(e){}class rX extends rD{static fromReadableStream(e){let t=new rX(null);return t._run(()=>t._fromReadableStream(e)),t}static runFunctions(e,t,r){let s=new rX(null),n={...r,headers:{...r?.headers,"X-Stainless-Helper-Method":"runFunctions"}};return s._run(()=>s._runFunctions(e,t,n)),s}static runTools(e,t,r){let s=new rX(t),n={...r,headers:{...r?.headers,"X-Stainless-Helper-Method":"runTools"}};return s._run(()=>s._runTools(e,t,n)),s}}class rJ extends tD{parse(e,t){for(let t of e.tools??[]){if("function"!==t.type)throw new eF(`Currently only \`function\` tool types support auto-parsing; Received \`${t.type}\``);if(!0!==t.function.strict)throw new eF(`The \`${t.function.name}\` tool is not marked with \`strict: true\`. Only strict function tools can be auto-parsed`)}return this._client.chat.completions.create(e,{...t,headers:{...t?.headers,"X-Stainless-Helper-Method":"beta.chat.completions.parse"}})._thenUnwrap(t=>rO(t,e))}runFunctions(e,t){return e.stream?rX.runFunctions(this._client,e,t):rT.runFunctions(this._client,e,t)}runTools(e,t){return e.stream?rX.runTools(this._client,e,t):rT.runTools(this._client,e,t)}stream(e,t){return rD.createChatCompletion(this._client,e,t)}}class rH extends tD{constructor(){super(...arguments),this.completions=new rJ(this._client)}}(rH||(rH={})).Completions=rJ;class rV extends tD{create(e,t){return this._client.post("/realtime/sessions",{body:e,...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}}class rK extends tD{create(e,t){return this._client.post("/realtime/transcription_sessions",{body:e,...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}}class rz extends tD{constructor(){super(...arguments),this.sessions=new rV(this._client),this.transcriptionSessions=new rK(this._client)}}rz.Sessions=rV,rz.TranscriptionSessions=rK;var rY=function(e,t,r,s){if("a"===r&&!s)throw TypeError("Private accessor was defined without a getter");if("function"==typeof t?e!==t||!s:!t.has(e))throw TypeError("Cannot read private member from an object whose class did not declare it");return"m"===r?s:"a"===r?s.call(e):s?s.value:t.get(e)},rQ=function(e,t,r,s,n){if("m"===s)throw TypeError("Private method is not writable");if("a"===s&&!n)throw TypeError("Private accessor was defined without a setter");if("function"==typeof t?e!==t||!n:!t.has(e))throw TypeError("Cannot write private member to an object whose class did not declare it");return"a"===s?n.call(e,r):n?n.value=r:t.set(e,r),r};class rG extends rR{constructor(){super(...arguments),H.add(this),V.set(this,[]),K.set(this,{}),z.set(this,{}),Y.set(this,void 0),Q.set(this,void 0),G.set(this,void 0),Z.set(this,void 0),ee.set(this,void 0),et.set(this,void 0),er.set(this,void 0),es.set(this,void 0),en.set(this,void 0)}[(V=new WeakMap,K=new WeakMap,z=new WeakMap,Y=new WeakMap,Q=new WeakMap,G=new WeakMap,Z=new WeakMap,ee=new WeakMap,et=new WeakMap,er=new WeakMap,es=new WeakMap,en=new WeakMap,H=new WeakSet,Symbol.asyncIterator)](){let e=[],t=[],r=!1;return this.on("event",r=>{let s=t.shift();s?s.resolve(r):e.push(r)}),this.on("end",()=>{for(let e of(r=!0,t))e.resolve(void 0);t.length=0}),this.on("abort",e=>{for(let s of(r=!0,t))s.reject(e);t.length=0}),this.on("error",e=>{for(let s of(r=!0,t))s.reject(e);t.length=0}),{next:async()=>e.length?{value:e.shift(),done:!1}:r?{value:void 0,done:!0}:new Promise((e,r)=>t.push({resolve:e,reject:r})).then(e=>e?{value:e,done:!1}:{value:void 0,done:!0}),return:async()=>(this.abort(),{value:void 0,done:!0})}}static fromReadableStream(e){let t=new rG;return t._run(()=>t._fromReadableStream(e)),t}async _fromReadableStream(e,t){let r=t?.signal;r&&(r.aborted&&this.controller.abort(),r.addEventListener("abort",()=>this.controller.abort())),this._connected();let s=e3.fromReadableStream(e,this.controller);for await(let e of s)rY(this,H,"m",ei).call(this,e);if(s.controller.signal?.aborted)throw new eq;return this._addRun(rY(this,H,"m",ea).call(this))}toReadableStream(){return new e3(this[Symbol.asyncIterator].bind(this),this.controller).toReadableStream()}static createToolAssistantStream(e,t,r,s,n){let i=new rG;return i._run(()=>i._runToolAssistantStream(e,t,r,s,{...n,headers:{...n?.headers,"X-Stainless-Helper-Method":"stream"}})),i}async _createToolAssistantStream(e,t,r,s,n){let i=n?.signal;i&&(i.aborted&&this.controller.abort(),i.addEventListener("abort",()=>this.controller.abort()));let a={...s,stream:!0},o=await e.submitToolOutputs(t,r,a,{...n,signal:this.controller.signal});for await(let e of(this._connected(),o))rY(this,H,"m",ei).call(this,e);if(o.controller.signal?.aborted)throw new eq;return this._addRun(rY(this,H,"m",ea).call(this))}static createThreadAssistantStream(e,t,r){let s=new rG;return s._run(()=>s._threadAssistantStream(e,t,{...r,headers:{...r?.headers,"X-Stainless-Helper-Method":"stream"}})),s}static createAssistantStream(e,t,r,s){let n=new rG;return n._run(()=>n._runAssistantStream(e,t,r,{...s,headers:{...s?.headers,"X-Stainless-Helper-Method":"stream"}})),n}currentEvent(){return rY(this,er,"f")}currentRun(){return rY(this,es,"f")}currentMessageSnapshot(){return rY(this,Y,"f")}currentRunStepSnapshot(){return rY(this,en,"f")}async finalRunSteps(){return await this.done(),Object.values(rY(this,K,"f"))}async finalMessages(){return await this.done(),Object.values(rY(this,z,"f"))}async finalRun(){if(await this.done(),!rY(this,Q,"f"))throw Error("Final run was not received.");return rY(this,Q,"f")}async _createThreadAssistantStream(e,t,r){let s=r?.signal;s&&(s.aborted&&this.controller.abort(),s.addEventListener("abort",()=>this.controller.abort()));let n={...t,stream:!0},i=await e.createAndRun(n,{...r,signal:this.controller.signal});for await(let e of(this._connected(),i))rY(this,H,"m",ei).call(this,e);if(i.controller.signal?.aborted)throw new eq;return this._addRun(rY(this,H,"m",ea).call(this))}async _createAssistantStream(e,t,r,s){let n=s?.signal;n&&(n.aborted&&this.controller.abort(),n.addEventListener("abort",()=>this.controller.abort()));let i={...r,stream:!0},a=await e.create(t,i,{...s,signal:this.controller.signal});for await(let e of(this._connected(),a))rY(this,H,"m",ei).call(this,e);if(a.controller.signal?.aborted)throw new eq;return this._addRun(rY(this,H,"m",ea).call(this))}static accumulateDelta(e,t){for(let[r,s]of Object.entries(t)){if(!e.hasOwnProperty(r)){e[r]=s;continue}let t=e[r];if(null==t||"index"===r||"type"===r){e[r]=s;continue}if("string"==typeof t&&"string"==typeof s)t+=s;else if("number"==typeof t&&"number"==typeof s)t+=s;else if(tU(t)&&tU(s))t=this.accumulateDelta(t,s);else if(Array.isArray(t)&&Array.isArray(s)){if(t.every(e=>"string"==typeof e||"number"==typeof e)){t.push(...s);continue}for(let e of s){if(!tU(e))throw Error(`Expected array delta entry to be an object but got: ${e}`);let r=e.index;if(null==r)throw console.error(e),Error("Expected array delta entry to have an `index` property");if("number"!=typeof r)throw Error(`Expected array delta entry \`index\` property to be a number but got ${r}`);let s=t[r];null==s?t.push(e):t[r]=this.accumulateDelta(s,e)}continue}else throw Error(`Unhandled record type: ${r}, deltaValue: ${s}, accValue: ${t}`);e[r]=t}return e}_addRun(e){return e}async _threadAssistantStream(e,t,r){return await this._createThreadAssistantStream(t,e,r)}async _runAssistantStream(e,t,r,s){return await this._createAssistantStream(t,e,r,s)}async _runToolAssistantStream(e,t,r,s,n){return await this._createToolAssistantStream(r,e,t,s,n)}}ei=function(e){if(!this.ended)switch(rQ(this,er,e,"f"),rY(this,H,"m",eu).call(this,e),e.event){case"thread.created":break;case"thread.run.created":case"thread.run.queued":case"thread.run.in_progress":case"thread.run.requires_action":case"thread.run.completed":case"thread.run.incomplete":case"thread.run.failed":case"thread.run.cancelling":case"thread.run.cancelled":case"thread.run.expired":rY(this,H,"m",ed).call(this,e);break;case"thread.run.step.created":case"thread.run.step.in_progress":case"thread.run.step.delta":case"thread.run.step.completed":case"thread.run.step.failed":case"thread.run.step.cancelled":case"thread.run.step.expired":rY(this,H,"m",el).call(this,e);break;case"thread.message.created":case"thread.message.in_progress":case"thread.message.delta":case"thread.message.completed":case"thread.message.incomplete":rY(this,H,"m",eo).call(this,e);break;case"error":throw Error("Encountered an error event in event processing - errors should be processed earlier")}},ea=function(){if(this.ended)throw new eF("stream has ended, this shouldn't happen");if(!rY(this,Q,"f"))throw Error("Final run has not been received");return rY(this,Q,"f")},eo=function(e){let[t,r]=rY(this,H,"m",eh).call(this,e,rY(this,Y,"f"));for(let e of(rQ(this,Y,t,"f"),rY(this,z,"f")[t.id]=t,r)){let r=t.content[e.index];r?.type=="text"&&this._emit("textCreated",r.text)}switch(e.event){case"thread.message.created":this._emit("messageCreated",e.data);break;case"thread.message.in_progress":break;case"thread.message.delta":if(this._emit("messageDelta",e.data.delta,t),e.data.delta.content)for(let r of e.data.delta.content){if("text"==r.type&&r.text){let e=r.text,s=t.content[r.index];if(s&&"text"==s.type)this._emit("textDelta",e,s.text);else throw Error("The snapshot associated with this text delta is not text or missing")}if(r.index!=rY(this,G,"f")){if(rY(this,Z,"f"))switch(rY(this,Z,"f").type){case"text":this._emit("textDone",rY(this,Z,"f").text,rY(this,Y,"f"));break;case"image_file":this._emit("imageFileDone",rY(this,Z,"f").image_file,rY(this,Y,"f"))}rQ(this,G,r.index,"f")}rQ(this,Z,t.content[r.index],"f")}break;case"thread.message.completed":case"thread.message.incomplete":if(void 0!==rY(this,G,"f")){let t=e.data.content[rY(this,G,"f")];if(t)switch(t.type){case"image_file":this._emit("imageFileDone",t.image_file,rY(this,Y,"f"));break;case"text":this._emit("textDone",t.text,rY(this,Y,"f"))}}rY(this,Y,"f")&&this._emit("messageDone",e.data),rQ(this,Y,void 0,"f")}},el=function(e){let t=rY(this,H,"m",ec).call(this,e);switch(rQ(this,en,t,"f"),e.event){case"thread.run.step.created":this._emit("runStepCreated",e.data);break;case"thread.run.step.delta":let r=e.data.delta;if(r.step_details&&"tool_calls"==r.step_details.type&&r.step_details.tool_calls&&"tool_calls"==t.step_details.type)for(let e of r.step_details.tool_calls)e.index==rY(this,ee,"f")?this._emit("toolCallDelta",e,t.step_details.tool_calls[e.index]):(rY(this,et,"f")&&this._emit("toolCallDone",rY(this,et,"f")),rQ(this,ee,e.index,"f"),rQ(this,et,t.step_details.tool_calls[e.index],"f"),rY(this,et,"f")&&this._emit("toolCallCreated",rY(this,et,"f")));this._emit("runStepDelta",e.data.delta,t);break;case"thread.run.step.completed":case"thread.run.step.failed":case"thread.run.step.cancelled":case"thread.run.step.expired":rQ(this,en,void 0,"f"),"tool_calls"==e.data.step_details.type&&rY(this,et,"f")&&(this._emit("toolCallDone",rY(this,et,"f")),rQ(this,et,void 0,"f")),this._emit("runStepDone",e.data,t)}},eu=function(e){rY(this,V,"f").push(e),this._emit("event",e)},ec=function(e){switch(e.event){case"thread.run.step.created":return rY(this,K,"f")[e.data.id]=e.data,e.data;case"thread.run.step.delta":let t=rY(this,K,"f")[e.data.id];if(!t)throw Error("Received a RunStepDelta before creation of a snapshot");let r=e.data;if(r.delta){let s=rG.accumulateDelta(t,r.delta);rY(this,K,"f")[e.data.id]=s}return rY(this,K,"f")[e.data.id];case"thread.run.step.completed":case"thread.run.step.failed":case"thread.run.step.cancelled":case"thread.run.step.expired":case"thread.run.step.in_progress":rY(this,K,"f")[e.data.id]=e.data}if(rY(this,K,"f")[e.data.id])return rY(this,K,"f")[e.data.id];throw Error("No snapshot available")},eh=function(e,t){let r=[];switch(e.event){case"thread.message.created":return[e.data,r];case"thread.message.delta":if(!t)throw Error("Received a delta with no existing snapshot (there should be one from message creation)");let s=e.data;if(s.delta.content)for(let e of s.delta.content)if(e.index in t.content){let r=t.content[e.index];t.content[e.index]=rY(this,H,"m",ef).call(this,e,r)}else t.content[e.index]=e,r.push(e);return[t,r];case"thread.message.in_progress":case"thread.message.completed":case"thread.message.incomplete":if(t)return[t,r];throw Error("Received thread message event with no existing snapshot")}throw Error("Tried to accumulate a non-message event")},ef=function(e,t){return rG.accumulateDelta(t,e)},ed=function(e){switch(rQ(this,es,e.data,"f"),e.event){case"thread.run.created":case"thread.run.queued":case"thread.run.in_progress":break;case"thread.run.requires_action":case"thread.run.cancelled":case"thread.run.failed":case"thread.run.completed":case"thread.run.expired":rQ(this,Q,e.data,"f"),rY(this,et,"f")&&(this._emit("toolCallDone",rY(this,et,"f")),rQ(this,et,void 0,"f"))}};class rZ extends tD{create(e,t,r){return this._client.post(`/threads/${e}/messages`,{body:t,...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}retrieve(e,t,r){return this._client.get(`/threads/${e}/messages/${t}`,{...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}update(e,t,r,s){return this._client.post(`/threads/${e}/messages/${t}`,{body:r,...s,headers:{"OpenAI-Beta":"assistants=v2",...s?.headers}})}list(e,t={},r){return tv(t)?this.list(e,{},t):this._client.getAPIList(`/threads/${e}/messages`,r0,{query:t,...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}del(e,t,r){return this._client.delete(`/threads/${e}/messages/${t}`,{...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}}class r0 extends tX{}rZ.MessagesPage=r0;class r1 extends tD{retrieve(e,t,r,s={},n){return tv(s)?this.retrieve(e,t,r,{},s):this._client.get(`/threads/${e}/runs/${t}/steps/${r}`,{query:s,...n,headers:{"OpenAI-Beta":"assistants=v2",...n?.headers}})}list(e,t,r={},s){return tv(r)?this.list(e,t,{},r):this._client.getAPIList(`/threads/${e}/runs/${t}/steps`,r2,{query:r,...s,headers:{"OpenAI-Beta":"assistants=v2",...s?.headers}})}}class r2 extends tX{}r1.RunStepsPage=r2;class r8 extends tD{constructor(){super(...arguments),this.steps=new r1(this._client)}create(e,t,r){let{include:s,...n}=t;return this._client.post(`/threads/${e}/runs`,{query:{include:s},body:n,...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers},stream:t.stream??!1})}retrieve(e,t,r){return this._client.get(`/threads/${e}/runs/${t}`,{...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}update(e,t,r,s){return this._client.post(`/threads/${e}/runs/${t}`,{body:r,...s,headers:{"OpenAI-Beta":"assistants=v2",...s?.headers}})}list(e,t={},r){return tv(t)?this.list(e,{},t):this._client.getAPIList(`/threads/${e}/runs`,r6,{query:t,...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}cancel(e,t,r){return this._client.post(`/threads/${e}/runs/${t}/cancel`,{...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}async createAndPoll(e,t,r){let s=await this.create(e,t,r);return await this.poll(e,s.id,r)}createAndStream(e,t,r){return rG.createAssistantStream(e,this._client.beta.threads.runs,t,r)}async poll(e,t,r){let s={...r?.headers,"X-Stainless-Poll-Helper":"true"};for(r?.pollIntervalMs&&(s["X-Stainless-Custom-Poll-Interval"]=r.pollIntervalMs.toString());;){let{data:n,response:i}=await this.retrieve(e,t,{...r,headers:{...r?.headers,...s}}).withResponse();switch(n.status){case"queued":case"in_progress":case"cancelling":let a=5e3;if(r?.pollIntervalMs)a=r.pollIntervalMs;else{let e=i.headers.get("openai-poll-after-ms");if(e){let t=parseInt(e);isNaN(t)||(a=t)}}await tP(a);break;case"requires_action":case"incomplete":case"cancelled":case"completed":case"failed":case"expired":return n}}}stream(e,t,r){return rG.createAssistantStream(e,this._client.beta.threads.runs,t,r)}submitToolOutputs(e,t,r,s){return this._client.post(`/threads/${e}/runs/${t}/submit_tool_outputs`,{body:r,...s,headers:{"OpenAI-Beta":"assistants=v2",...s?.headers},stream:r.stream??!1})}async submitToolOutputsAndPoll(e,t,r,s){let n=await this.submitToolOutputs(e,t,r,s);return await this.poll(e,n.id,s)}submitToolOutputsStream(e,t,r,s){return rG.createToolAssistantStream(e,t,this._client.beta.threads.runs,r,s)}}class r6 extends tX{}r8.RunsPage=r6,r8.Steps=r1,r8.RunStepsPage=r2;class r5 extends tD{constructor(){super(...arguments),this.runs=new r8(this._client),this.messages=new rZ(this._client)}create(e={},t){return tv(e)?this.create({},e):this._client.post("/threads",{body:e,...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}retrieve(e,t){return this._client.get(`/threads/${e}`,{...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}update(e,t,r){return this._client.post(`/threads/${e}`,{body:t,...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}del(e,t){return this._client.delete(`/threads/${e}`,{...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}createAndRun(e,t){return this._client.post("/threads/runs",{body:e,...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers},stream:e.stream??!1})}async createAndRunPoll(e,t){let r=await this.createAndRun(e,t);return await this.runs.poll(r.thread_id,r.id,t)}createAndRunStream(e,t){return rG.createThreadAssistantStream(e,this._client.beta.threads,t)}}r5.Runs=r8,r5.RunsPage=r6,r5.Messages=rZ,r5.MessagesPage=r0;class r3 extends tD{constructor(){super(...arguments),this.realtime=new rz(this._client),this.chat=new rH(this._client),this.assistants=new rw(this._client),this.threads=new r5(this._client)}}r3.Realtime=rz,r3.Assistants=rw,r3.AssistantsPage=rb,r3.Threads=r5;class r4 extends tD{create(e,t){return this._client.post("/batches",{body:e,...t})}retrieve(e,t){return this._client.get(`/batches/${e}`,t)}list(e={},t){return tv(e)?this.list({},e):this._client.getAPIList("/batches",r9,{query:e,...t})}cancel(e,t){return this._client.post(`/batches/${e}/cancel`,t)}}class r9 extends tX{}r4.BatchesPage=r9;class r7 extends tD{create(e,t,r){return this._client.post(`/uploads/${e}/parts`,tl({body:t,...r}))}}class se extends tD{constructor(){super(...arguments),this.parts=new r7(this._client)}create(e,t){return this._client.post("/uploads",{body:e,...t})}cancel(e,t){return this._client.post(`/uploads/${e}/cancel`,t)}complete(e,t,r){return this._client.post(`/uploads/${e}/complete`,{body:t,...r})}}function st(e,t){let r=e.output.map(e=>{if("function_call"===e.type)return{...e,parsed_arguments:function(e,t){var r,s;let n=(r=e.tools??[],s=t.name,r.find(e=>"function"===e.type&&e.name===s));return{...t,...t,parsed_arguments:n?.$brand==="auto-parseable-tool"?n.$parseRaw(t.arguments):n?.strict?JSON.parse(t.arguments):null}}(t,e)};if("message"===e.type){let r=e.content.map(e=>{var r,s;return"output_text"===e.type?{...e,parsed:(r=t,s=e.text,r.text?.format?.type!=="json_schema"?null:"$parseRaw"in r.text?.format?(r.text?.format).$parseRaw(s):JSON.parse(s))}:e});return{...e,content:r}}return e}),s=Object.assign({},e,{output:r});return Object.getOwnPropertyDescriptor(e,"output_text")||sr(s),Object.defineProperty(s,"output_parsed",{enumerable:!0,get(){for(let e of s.output)if("message"===e.type){for(let t of e.content)if("output_text"===t.type&&null!==t.parsed)return t.parsed}return null}}),s}function sr(e){let t=[];for(let r of e.output)if("message"===r.type)for(let e of r.content)"output_text"===e.type&&t.push(e.text);e.output_text=t.join("")}se.Parts=r7;class ss extends tD{list(e,t={},r){return tv(t)?this.list(e,{},t):this._client.getAPIList(`/responses/${e}/input_items`,sl,{query:t,...r})}}var sn=function(e,t,r,s,n){if("m"===s)throw TypeError("Private method is not writable");if("a"===s&&!n)throw TypeError("Private accessor was defined without a setter");if("function"==typeof t?e!==t||!n:!t.has(e))throw TypeError("Cannot write private member to an object whose class did not declare it");return"a"===s?n.call(e,r):n?n.value=r:t.set(e,r),r},si=function(e,t,r,s){if("a"===r&&!s)throw TypeError("Private accessor was defined without a getter");if("function"==typeof t?e!==t||!s:!t.has(e))throw TypeError("Cannot read private member from an object whose class did not declare it");return"m"===r?s:"a"===r?s.call(e):s?s.value:t.get(e)};class sa extends rR{constructor(e){super(),ep.add(this),em.set(this,void 0),eg.set(this,void 0),ey.set(this,void 0),sn(this,em,e,"f")}static createResponse(e,t,r){let s=new sa(t);return s._run(()=>s._createOrRetrieveResponse(e,t,{...r,headers:{...r?.headers,"X-Stainless-Helper-Method":"stream"}})),s}async _createOrRetrieveResponse(e,t,r){let s,n=r?.signal;n&&(n.aborted&&this.controller.abort(),n.addEventListener("abort",()=>this.controller.abort())),si(this,ep,"m",ew).call(this);let i=null;for await(let n of("response_id"in t?(s=await e.responses.retrieve(t.response_id,{stream:!0},{...r,signal:this.controller.signal,stream:!0}),i=t.starting_after??null):s=await e.responses.create({...t,stream:!0},{...r,signal:this.controller.signal}),this._connected(),s))si(this,ep,"m",eb).call(this,n,i);if(s.controller.signal?.aborted)throw new eq;return si(this,ep,"m",e_).call(this)}[(em=new WeakMap,eg=new WeakMap,ey=new WeakMap,ep=new WeakSet,ew=function(){this.ended||sn(this,eg,void 0,"f")},eb=function(e,t){if(this.ended)return;let r=(e,r)=>{(null==t||r.sequence_number>t)&&this._emit(e,r)},s=si(this,ep,"m",ev).call(this,e);switch(r("event",e),e.type){case"response.output_text.delta":{let t=s.output[e.output_index];if(!t)throw new eF(`missing output at index ${e.output_index}`);if("message"===t.type){let s=t.content[e.content_index];if(!s)throw new eF(`missing content at index ${e.content_index}`);if("output_text"!==s.type)throw new eF(`expected content to be 'output_text', got ${s.type}`);r("response.output_text.delta",{...e,snapshot:s.text})}break}case"response.function_call_arguments.delta":{let t=s.output[e.output_index];if(!t)throw new eF(`missing output at index ${e.output_index}`);"function_call"===t.type&&r("response.function_call_arguments.delta",{...e,snapshot:t.arguments});break}default:r(e.type,e)}},e_=function(){if(this.ended)throw new eF("stream has ended, this shouldn't happen");let e=si(this,eg,"f");if(!e)throw new eF("request ended without sending any events");sn(this,eg,void 0,"f");let t=function(e,t){var r;return t&&(r=t,rI(r.text?.format))?st(e,t):{...e,output_parsed:null,output:e.output.map(e=>"function_call"===e.type?{...e,parsed_arguments:null}:"message"===e.type?{...e,content:e.content.map(e=>({...e,parsed:null}))}:e)}}(e,si(this,em,"f"));return sn(this,ey,t,"f"),t},ev=function(e){let t=si(this,eg,"f");if(!t){if("response.created"!==e.type)throw new eF(`When snapshot hasn't been set yet, expected 'response.created' event, got ${e.type}`);return sn(this,eg,e.response,"f")}switch(e.type){case"response.output_item.added":t.output.push(e.item);break;case"response.content_part.added":{let r=t.output[e.output_index];if(!r)throw new eF(`missing output at index ${e.output_index}`);"message"===r.type&&r.content.push(e.part);break}case"response.output_text.delta":{let r=t.output[e.output_index];if(!r)throw new eF(`missing output at index 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يكون ${t} ${i.minimum.toString()} ${r.unit}`;return`أصغر من اللازم: يفترض لـ ${i.origin} أن يكون ${t} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`نَص غير مقبول: يجب أن يبدأ بـ "${i.prefix}"`;if("ends_with"===i.format)return`نَص غير مقبول: يجب أن ينتهي بـ "${i.suffix}"`;if("includes"===i.format)return`نَص غير مقبول: يجب أن يتضمَّن "${i.includes}"`;if("regex"===i.format)return`نَص غير مقبول: يجب أن يطابق النمط ${i.pattern}`;return`${t[i.format]??i.format} غير مقبول`;case"not_multiple_of":return`رقم غير مقبول: يجب أن يكون من مضاعفات ${i.divisor}`;case"unrecognized_keys":return`معرف${i.keys.length>1?"ات":""} غريب${i.keys.length>1?"ة":""}: ${V.joinValues(i.keys,"، ")}`;case"invalid_key":return`معرف غير مقبول في ${i.origin}`;case"invalid_union":default:return"مدخل غير مقبول";case"invalid_element":return`مدخل غير مقبول في ${i.origin}`}})}},"az",0,function(){let e,t;return{localeError:(e={string:{unit:"simvol",verb:"olmalıdır"},file:{unit:"bayt",verb:"olmalıdır"},array:{unit:"element",verb:"olmalıdır"},set:{unit:"element",verb:"olmalıdır"}},t={regex:"input",email:"email address",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO datetime",date:"ISO date",time:"ISO time",duration:"ISO duration",ipv4:"IPv4 address",ipv6:"IPv6 address",cidrv4:"IPv4 range",cidrv6:"IPv6 range",base64:"base64-encoded string",base64url:"base64url-encoded string",json_string:"JSON string",e164:"E.164 number",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Yanlış dəyər: g\xf6zlənilən ${i.expected}, daxil olan ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Yanlış dəyər: g\xf6zlənilən ${V.stringifyPrimitive(i.values[0])}`;return`Yanlış se\xe7im: aşağıdakılardan biri olmalıdır: ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`\xc7ox b\xf6y\xfck: g\xf6zlənilən ${i.origin??"dəyər"} ${t}${i.maximum.toString()} ${r.unit??"element"}`;return`\xc7ox b\xf6y\xfck: g\xf6zlənilən ${i.origin??"dəyər"} ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`\xc7ox ki\xe7ik: g\xf6zlənilən ${i.origin} ${t}${i.minimum.toString()} ${r.unit}`;return`\xc7ox ki\xe7ik: g\xf6zlənilən ${i.origin} ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Yanlış mətn: "${i.prefix}" ilə başlamalıdır`;if("ends_with"===i.format)return`Yanlış mətn: "${i.suffix}" ilə bitməlidir`;if("includes"===i.format)return`Yanlış mətn: "${i.includes}" daxil olmalıdır`;if("regex"===i.format)return`Yanlış mətn: ${i.pattern} şablonuna uyğun olmalıdır`;return`Yanlış ${t[i.format]??i.format}`;case"not_multiple_of":return`Yanlış ədəd: ${i.divisor} ilə b\xf6l\xfcnə bilən olmalıdır`;case"unrecognized_keys":return`Tanınmayan a\xe7ar${i.keys.length>1?"lar":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`${i.origin} daxilində yanlış a\xe7ar`;case"invalid_union":default:return"Yanlış dəyər";case"invalid_element":return`${i.origin} daxilində yanlış dəyər`}})}},"be",0,function(){let e,t;return{localeError:(e={string:{unit:{one:"сімвал",few:"сімвалы",many:"сімвалаў"},verb:"мець"},array:{unit:{one:"элемент",few:"элементы",many:"элементаў"},verb:"мець"},set:{unit:{one:"элемент",few:"элементы",many:"элементаў"},verb:"мець"},file:{unit:{one:"байт",few:"байты",many:"байтаў"},verb:"мець"}},t={regex:"увод",email:"email адрас",url:"URL",emoji:"эмодзі",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO дата і час",date:"ISO дата",time:"ISO час",duration:"ISO працягласць",ipv4:"IPv4 адрас",ipv6:"IPv6 адрас",cidrv4:"IPv4 дыяпазон",cidrv6:"IPv6 дыяпазон",base64:"радок у фармаце base64",base64url:"радок у фармаце base64url",json_string:"JSON радок",e164:"нумар E.164",jwt:"JWT",template_literal:"увод"},i=>{switch(i.code){case"invalid_type":return`Няправільны ўвод: чакаўся ${i.expected}, атрымана ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"лік";case"object":if(Array.isArray(e))return"масіў";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Няправільны ўвод: чакалася ${V.stringifyPrimitive(i.values[0])}`;return`Няправільны варыянт: чакаўся адзін з ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r){let e=tE(Number(i.maximum),r.unit.one,r.unit.few,r.unit.many);return`Занадта вялікі: чакалася, што ${i.origin??"значэнне"} павінна ${r.verb} ${t}${i.maximum.toString()} ${e}`}return`Занадта вялікі: чакалася, што ${i.origin??"значэнне"} павінна быць ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r){let e=tE(Number(i.minimum),r.unit.one,r.unit.few,r.unit.many);return`Занадта малы: чакалася, што ${i.origin} павінна ${r.verb} ${t}${i.minimum.toString()} ${e}`}return`Занадта малы: чакалася, што ${i.origin} павінна быць ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Няправільны радок: павінен пачынацца з "${i.prefix}"`;if("ends_with"===i.format)return`Няправільны радок: павінен заканчвацца на "${i.suffix}"`;if("includes"===i.format)return`Няправільны радок: павінен змяшчаць "${i.includes}"`;if("regex"===i.format)return`Няправільны радок: павінен адпавядаць шаблону ${i.pattern}`;return`Няправільны ${t[i.format]??i.format}`;case"not_multiple_of":return`Няправільны лік: павінен быць кратным ${i.divisor}`;case"unrecognized_keys":return`Нераспазнаны ${i.keys.length>1?"ключы":"ключ"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Няправільны ключ у ${i.origin}`;case"invalid_union":default:return"Няправільны ўвод";case"invalid_element":return`Няправільнае значэнне ў ${i.origin}`}})}},"ca",0,function(){let e,t;return{localeError:(e={string:{unit:"caràcters",verb:"contenir"},file:{unit:"bytes",verb:"contenir"},array:{unit:"elements",verb:"contenir"},set:{unit:"elements",verb:"contenir"}},t={regex:"entrada",email:"adreça electrònica",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data i hora ISO",date:"data ISO",time:"hora ISO",duration:"durada ISO",ipv4:"adreça IPv4",ipv6:"adreça IPv6",cidrv4:"rang IPv4",cidrv6:"rang IPv6",base64:"cadena codificada en base64",base64url:"cadena codificada en base64url",json_string:"cadena JSON",e164:"número E.164",jwt:"JWT",template_literal:"entrada"},i=>{switch(i.code){case"invalid_type":return`Tipus inv\xe0lid: s'esperava ${i.expected}, s'ha rebut ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Valor inv\xe0lid: s'esperava ${V.stringifyPrimitive(i.values[0])}`;return`Opci\xf3 inv\xe0lida: s'esperava una de ${V.joinValues(i.values," o ")}`;case"too_big":{let t=i.inclusive?"com a màxim":"menys de",r=e[i.origin]??null;if(r)return`Massa gran: s'esperava que ${i.origin??"el valor"} contingu\xe9s ${t} ${i.maximum.toString()} ${r.unit??"elements"}`;return`Massa gran: s'esperava que ${i.origin??"el valor"} fos ${t} ${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?"com a mínim":"més de",r=e[i.origin]??null;if(r)return`Massa petit: s'esperava que ${i.origin} contingu\xe9s ${t} ${i.minimum.toString()} ${r.unit}`;return`Massa petit: s'esperava que ${i.origin} fos ${t} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Format inv\xe0lid: ha de comen\xe7ar amb "${i.prefix}"`;if("ends_with"===i.format)return`Format inv\xe0lid: ha d'acabar amb "${i.suffix}"`;if("includes"===i.format)return`Format inv\xe0lid: ha d'incloure "${i.includes}"`;if("regex"===i.format)return`Format inv\xe0lid: ha de coincidir amb el patr\xf3 ${i.pattern}`;return`Format inv\xe0lid per a ${t[i.format]??i.format}`;case"not_multiple_of":return`N\xfamero inv\xe0lid: ha de ser m\xfaltiple de ${i.divisor}`;case"unrecognized_keys":return`Clau${i.keys.length>1?"s":""} no reconeguda${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Clau inv\xe0lida a ${i.origin}`;case"invalid_union":default:return"Entrada invàlida";case"invalid_element":return`Element inv\xe0lid a ${i.origin}`}})}},"cs",0,function(){let e,t;return{localeError:(e={string:{unit:"znaků",verb:"mít"},file:{unit:"bajtů",verb:"mít"},array:{unit:"prvků",verb:"mít"},set:{unit:"prvků",verb:"mít"}},t={regex:"regulární výraz",email:"e-mailová adresa",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"datum a čas ve formátu ISO",date:"datum ve formátu ISO",time:"čas ve formátu ISO",duration:"doba trvání ISO",ipv4:"IPv4 adresa",ipv6:"IPv6 adresa",cidrv4:"rozsah IPv4",cidrv6:"rozsah IPv6",base64:"řetězec zakódovaný ve formátu base64",base64url:"řetězec zakódovaný ve formátu base64url",json_string:"řetězec ve formátu JSON",e164:"číslo E.164",jwt:"JWT",template_literal:"vstup"},i=>{switch(i.code){case"invalid_type":return`Neplatn\xfd vstup: oček\xe1v\xe1no ${i.expected}, obdrženo ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"číslo";case"string":return"řetězec";case"boolean":return"boolean";case"bigint":return"bigint";case"function":return"funkce";case"symbol":return"symbol";case"undefined":return"undefined";case"object":if(Array.isArray(e))return"pole";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Neplatn\xfd vstup: oček\xe1v\xe1no ${V.stringifyPrimitive(i.values[0])}`;return`Neplatn\xe1 možnost: oček\xe1v\xe1na jedna z hodnot ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Hodnota je př\xedliš velk\xe1: ${i.origin??"hodnota"} mus\xed m\xedt ${t}${i.maximum.toString()} ${r.unit??"prvků"}`;return`Hodnota je př\xedliš velk\xe1: ${i.origin??"hodnota"} mus\xed b\xfdt ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Hodnota je př\xedliš mal\xe1: ${i.origin??"hodnota"} mus\xed m\xedt ${t}${i.minimum.toString()} ${r.unit??"prvků"}`;return`Hodnota je př\xedliš mal\xe1: ${i.origin??"hodnota"} mus\xed b\xfdt ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Neplatn\xfd řetězec: mus\xed zač\xednat na "${i.prefix}"`;if("ends_with"===i.format)return`Neplatn\xfd řetězec: mus\xed končit na "${i.suffix}"`;if("includes"===i.format)return`Neplatn\xfd řetězec: mus\xed obsahovat "${i.includes}"`;if("regex"===i.format)return`Neplatn\xfd řetězec: mus\xed odpov\xeddat vzoru ${i.pattern}`;return`Neplatn\xfd form\xe1t ${t[i.format]??i.format}`;case"not_multiple_of":return`Neplatn\xe9 č\xedslo: mus\xed b\xfdt n\xe1sobkem ${i.divisor}`;case"unrecognized_keys":return`Nezn\xe1m\xe9 kl\xedče: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Neplatn\xfd kl\xedč v ${i.origin}`;case"invalid_union":default:return"Neplatný vstup";case"invalid_element":return`Neplatn\xe1 hodnota v ${i.origin}`}})}},"de",0,function(){let e,t;return{localeError:(e={string:{unit:"Zeichen",verb:"zu haben"},file:{unit:"Bytes",verb:"zu haben"},array:{unit:"Elemente",verb:"zu haben"},set:{unit:"Elemente",verb:"zu haben"}},t={regex:"Eingabe",email:"E-Mail-Adresse",url:"URL",emoji:"Emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-Datum und -Uhrzeit",date:"ISO-Datum",time:"ISO-Uhrzeit",duration:"ISO-Dauer",ipv4:"IPv4-Adresse",ipv6:"IPv6-Adresse",cidrv4:"IPv4-Bereich",cidrv6:"IPv6-Bereich",base64:"Base64-codierter String",base64url:"Base64-URL-codierter String",json_string:"JSON-String",e164:"E.164-Nummer",jwt:"JWT",template_literal:"Eingabe"},i=>{switch(i.code){case"invalid_type":return`Ung\xfcltige Eingabe: erwartet ${i.expected}, erhalten ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"Zahl";case"object":if(Array.isArray(e))return"Array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ung\xfcltige Eingabe: erwartet ${V.stringifyPrimitive(i.values[0])}`;return`Ung\xfcltige Option: erwartet eine von ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Zu gro\xdf: erwartet, dass ${i.origin??"Wert"} ${t}${i.maximum.toString()} ${r.unit??"Elemente"} hat`;return`Zu gro\xdf: erwartet, dass ${i.origin??"Wert"} ${t}${i.maximum.toString()} ist`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Zu klein: erwartet, dass ${i.origin} ${t}${i.minimum.toString()} ${r.unit} hat`;return`Zu klein: erwartet, dass ${i.origin} ${t}${i.minimum.toString()} ist`}case"invalid_format":if("starts_with"===i.format)return`Ung\xfcltiger String: muss mit "${i.prefix}" beginnen`;if("ends_with"===i.format)return`Ung\xfcltiger String: muss mit "${i.suffix}" enden`;if("includes"===i.format)return`Ung\xfcltiger String: muss "${i.includes}" enthalten`;if("regex"===i.format)return`Ung\xfcltiger String: muss dem Muster ${i.pattern} entsprechen`;return`Ung\xfcltig: ${t[i.format]??i.format}`;case"not_multiple_of":return`Ung\xfcltige Zahl: muss ein Vielfaches von ${i.divisor} sein`;case"unrecognized_keys":return`${i.keys.length>1?"Unbekannte Schlüssel":"Unbekannter Schlüssel"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Ung\xfcltiger Schl\xfcssel in ${i.origin}`;case"invalid_union":default:return"Ungültige Eingabe";case"invalid_element":return`Ung\xfcltiger Wert in ${i.origin}`}})}},"en",()=>tT.default,"eo",0,function(){let e,t;return{localeError:(e={string:{unit:"karaktrojn",verb:"havi"},file:{unit:"bajtojn",verb:"havi"},array:{unit:"elementojn",verb:"havi"},set:{unit:"elementojn",verb:"havi"}},t={regex:"enigo",email:"retadreso",url:"URL",emoji:"emoĝio",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-datotempo",date:"ISO-dato",time:"ISO-tempo",duration:"ISO-daŭro",ipv4:"IPv4-adreso",ipv6:"IPv6-adreso",cidrv4:"IPv4-rango",cidrv6:"IPv6-rango",base64:"64-ume kodita karaktraro",base64url:"URL-64-ume kodita karaktraro",json_string:"JSON-karaktraro",e164:"E.164-nombro",jwt:"JWT",template_literal:"enigo"},i=>{switch(i.code){case"invalid_type":return`Nevalida enigo: atendiĝis ${i.expected}, riceviĝis ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"nombro";case"object":if(Array.isArray(e))return"tabelo";if(null===e)return"senvalora";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Nevalida enigo: atendiĝis ${V.stringifyPrimitive(i.values[0])}`;return`Nevalida opcio: atendiĝis unu el ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Tro granda: atendiĝis ke ${i.origin??"valoro"} havu ${t}${i.maximum.toString()} ${r.unit??"elementojn"}`;return`Tro granda: atendiĝis ke ${i.origin??"valoro"} havu ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Tro malgranda: atendiĝis ke ${i.origin} havu ${t}${i.minimum.toString()} ${r.unit}`;return`Tro malgranda: atendiĝis ke ${i.origin} estu ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Nevalida karaktraro: devas komenciĝi per "${i.prefix}"`;if("ends_with"===i.format)return`Nevalida karaktraro: devas finiĝi per "${i.suffix}"`;if("includes"===i.format)return`Nevalida karaktraro: devas inkluzivi "${i.includes}"`;if("regex"===i.format)return`Nevalida karaktraro: devas kongrui kun la modelo ${i.pattern}`;return`Nevalida ${t[i.format]??i.format}`;case"not_multiple_of":return`Nevalida nombro: devas esti oblo de ${i.divisor}`;case"unrecognized_keys":return`Nekonata${i.keys.length>1?"j":""} ŝlosilo${i.keys.length>1?"j":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Nevalida ŝlosilo en ${i.origin}`;case"invalid_union":default:return"Nevalida enigo";case"invalid_element":return`Nevalida valoro en ${i.origin}`}})}},"es",0,function(){let e,t;return{localeError:(e={string:{unit:"caracteres",verb:"tener"},file:{unit:"bytes",verb:"tener"},array:{unit:"elementos",verb:"tener"},set:{unit:"elementos",verb:"tener"}},t={regex:"entrada",email:"dirección de correo electrónico",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"fecha y hora ISO",date:"fecha ISO",time:"hora ISO",duration:"duración ISO",ipv4:"dirección IPv4",ipv6:"dirección IPv6",cidrv4:"rango IPv4",cidrv6:"rango IPv6",base64:"cadena codificada en base64",base64url:"URL codificada en base64",json_string:"cadena JSON",e164:"número E.164",jwt:"JWT",template_literal:"entrada"},i=>{switch(i.code){case"invalid_type":return`Entrada inv\xe1lida: se esperaba ${i.expected}, recibido ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"número";case"object":if(Array.isArray(e))return"arreglo";if(null===e)return"nulo";if(Object.getPrototypeOf(e)!==Object.prototype)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Entrada inv\xe1lida: se esperaba ${V.stringifyPrimitive(i.values[0])}`;return`Opci\xf3n inv\xe1lida: se esperaba una de ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Demasiado grande: se esperaba que ${i.origin??"valor"} tuviera ${t}${i.maximum.toString()} ${r.unit??"elementos"}`;return`Demasiado grande: se esperaba que ${i.origin??"valor"} fuera ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Demasiado peque\xf1o: se esperaba que ${i.origin} tuviera ${t}${i.minimum.toString()} ${r.unit}`;return`Demasiado peque\xf1o: se esperaba que ${i.origin} fuera ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Cadena inv\xe1lida: debe comenzar con "${i.prefix}"`;if("ends_with"===i.format)return`Cadena inv\xe1lida: debe terminar en "${i.suffix}"`;if("includes"===i.format)return`Cadena inv\xe1lida: debe incluir "${i.includes}"`;if("regex"===i.format)return`Cadena inv\xe1lida: debe coincidir con el patr\xf3n ${i.pattern}`;return`Inv\xe1lido ${t[i.format]??i.format}`;case"not_multiple_of":return`N\xfamero inv\xe1lido: debe ser m\xfaltiplo de ${i.divisor}`;case"unrecognized_keys":return`Llave${i.keys.length>1?"s":""} desconocida${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Llave inv\xe1lida en ${i.origin}`;case"invalid_union":default:return"Entrada inválida";case"invalid_element":return`Valor inv\xe1lido en ${i.origin}`}})}},"fa",0,function(){let e,t;return{localeError:(e={string:{unit:"کاراکتر",verb:"داشته باشد"},file:{unit:"بایت",verb:"داشته باشد"},array:{unit:"آیتم",verb:"داشته باشد"},set:{unit:"آیتم",verb:"داشته باشد"}},t={regex:"ورودی",email:"آدرس ایمیل",url:"URL",emoji:"ایموجی",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"تاریخ و زمان ایزو",date:"تاریخ ایزو",time:"زمان ایزو",duration:"مدت زمان ایزو",ipv4:"IPv4 آدرس",ipv6:"IPv6 آدرس",cidrv4:"IPv4 دامنه",cidrv6:"IPv6 دامنه",base64:"base64-encoded رشته",base64url:"base64url-encoded رشته",json_string:"JSON رشته",e164:"E.164 عدد",jwt:"JWT",template_literal:"ورودی"},i=>{switch(i.code){case"invalid_type":return`ورودی نامعتبر: می‌بایست ${i.expected} می‌بود، ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"عدد";case"object":if(Array.isArray(e))return"آرایه";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} دریافت شد`;case"invalid_value":if(1===i.values.length)return`ورودی نامعتبر: می‌بایست ${V.stringifyPrimitive(i.values[0])} می‌بود`;return`گزینه نامعتبر: می‌بایست یکی از ${V.joinValues(i.values,"|")} می‌بود`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`خیلی بزرگ: ${i.origin??"مقدار"} باید ${t}${i.maximum.toString()} ${r.unit??"عنصر"} باشد`;return`خیلی بزرگ: ${i.origin??"مقدار"} باید ${t}${i.maximum.toString()} باشد`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`خیلی کوچک: ${i.origin} باید ${t}${i.minimum.toString()} ${r.unit} باشد`;return`خیلی کوچک: ${i.origin} باید ${t}${i.minimum.toString()} باشد`}case"invalid_format":if("starts_with"===i.format)return`رشته نامعتبر: باید با "${i.prefix}" شروع شود`;if("ends_with"===i.format)return`رشته نامعتبر: باید با "${i.suffix}" تمام شود`;if("includes"===i.format)return`رشته نامعتبر: باید شامل "${i.includes}" باشد`;if("regex"===i.format)return`رشته نامعتبر: باید با الگوی ${i.pattern} مطابقت داشته باشد`;return`${t[i.format]??i.format} نامعتبر`;case"not_multiple_of":return`عدد نامعتبر: باید مضرب ${i.divisor} باشد`;case"unrecognized_keys":return`کلید${i.keys.length>1?"های":""} ناشناس: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`کلید ناشناس در ${i.origin}`;case"invalid_union":default:return"ورودی نامعتبر";case"invalid_element":return`مقدار نامعتبر در ${i.origin}`}})}},"fi",0,function(){let e,t;return{localeError:(e={string:{unit:"merkkiä",subject:"merkkijonon"},file:{unit:"tavua",subject:"tiedoston"},array:{unit:"alkiota",subject:"listan"},set:{unit:"alkiota",subject:"joukon"},number:{unit:"",subject:"luvun"},bigint:{unit:"",subject:"suuren kokonaisluvun"},int:{unit:"",subject:"kokonaisluvun"},date:{unit:"",subject:"päivämäärän"}},t={regex:"säännöllinen lauseke",email:"sähköpostiosoite",url:"URL-osoite",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-aikaleima",date:"ISO-päivämäärä",time:"ISO-aika",duration:"ISO-kesto",ipv4:"IPv4-osoite",ipv6:"IPv6-osoite",cidrv4:"IPv4-alue",cidrv6:"IPv6-alue",base64:"base64-koodattu merkkijono",base64url:"base64url-koodattu merkkijono",json_string:"JSON-merkkijono",e164:"E.164-luku",jwt:"JWT",template_literal:"templaattimerkkijono"},i=>{switch(i.code){case"invalid_type":return`Virheellinen tyyppi: odotettiin ${i.expected}, oli ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Virheellinen sy\xf6te: t\xe4ytyy olla ${V.stringifyPrimitive(i.values[0])}`;return`Virheellinen valinta: t\xe4ytyy olla yksi seuraavista: ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Liian suuri: ${r.subject} t\xe4ytyy olla ${t}${i.maximum.toString()} ${r.unit}`.trim();return`Liian suuri: arvon t\xe4ytyy olla ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Liian pieni: ${r.subject} t\xe4ytyy olla ${t}${i.minimum.toString()} ${r.unit}`.trim();return`Liian pieni: arvon t\xe4ytyy olla ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy alkaa "${i.prefix}"`;if("ends_with"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy loppua "${i.suffix}"`;if("includes"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy sis\xe4lt\xe4\xe4 "${i.includes}"`;if("regex"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy vastata s\xe4\xe4nn\xf6llist\xe4 lauseketta ${i.pattern}`;return`Virheellinen ${t[i.format]??i.format}`;case"not_multiple_of":return`Virheellinen luku: t\xe4ytyy olla luvun ${i.divisor} monikerta`;case"unrecognized_keys":return`${i.keys.length>1?"Tuntemattomat avaimet":"Tuntematon avain"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return"Virheellinen avain tietueessa";case"invalid_union":return"Virheellinen unioni";case"invalid_element":return"Virheellinen arvo joukossa";default:return"Virheellinen syöte"}})}},"fr",0,function(){let e,t;return{localeError:(e={string:{unit:"caractères",verb:"avoir"},file:{unit:"octets",verb:"avoir"},array:{unit:"éléments",verb:"avoir"},set:{unit:"éléments",verb:"avoir"}},t={regex:"entrée",email:"adresse e-mail",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"date et heure ISO",date:"date ISO",time:"heure ISO",duration:"durée ISO",ipv4:"adresse IPv4",ipv6:"adresse IPv6",cidrv4:"plage IPv4",cidrv6:"plage IPv6",base64:"chaîne encodée en base64",base64url:"chaîne encodée en base64url",json_string:"chaîne JSON",e164:"numéro E.164",jwt:"JWT",template_literal:"entrée"},i=>{switch(i.code){case"invalid_type":return`Entr\xe9e invalide : ${i.expected} attendu, ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"nombre";case"object":if(Array.isArray(e))return"tableau";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} re\xe7u`;case"invalid_value":if(1===i.values.length)return`Entr\xe9e invalide : ${V.stringifyPrimitive(i.values[0])} attendu`;return`Option invalide : une valeur parmi ${V.joinValues(i.values,"|")} attendue`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Trop grand : ${i.origin??"valeur"} doit ${r.verb} ${t}${i.maximum.toString()} ${r.unit??"élément(s)"}`;return`Trop grand : ${i.origin??"valeur"} doit \xeatre ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Trop petit : ${i.origin} doit ${r.verb} ${t}${i.minimum.toString()} ${r.unit}`;return`Trop petit : ${i.origin} doit \xeatre ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Cha\xeene invalide : doit commencer par "${i.prefix}"`;if("ends_with"===i.format)return`Cha\xeene invalide : doit se terminer par "${i.suffix}"`;if("includes"===i.format)return`Cha\xeene invalide : doit inclure "${i.includes}"`;if("regex"===i.format)return`Cha\xeene invalide : doit correspondre au mod\xe8le ${i.pattern}`;return`${t[i.format]??i.format} invalide`;case"not_multiple_of":return`Nombre invalide : doit \xeatre un multiple de ${i.divisor}`;case"unrecognized_keys":return`Cl\xe9${i.keys.length>1?"s":""} non reconnue${i.keys.length>1?"s":""} : ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Cl\xe9 invalide dans ${i.origin}`;case"invalid_union":default:return"Entrée invalide";case"invalid_element":return`Valeur invalide dans ${i.origin}`}})}},"frCA",0,function(){let e,t;return{localeError:(e={string:{unit:"caractères",verb:"avoir"},file:{unit:"octets",verb:"avoir"},array:{unit:"éléments",verb:"avoir"},set:{unit:"éléments",verb:"avoir"}},t={regex:"entrée",email:"adresse 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l'une des valeurs suivantes ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"≤":"<",r=e[i.origin]??null;if(r)return`Trop grand : attendu que ${i.origin??"la valeur"} ait ${t}${i.maximum.toString()} ${r.unit}`;return`Trop grand : attendu que ${i.origin??"la valeur"} soit ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?"≥":">",r=e[i.origin]??null;if(r)return`Trop petit : attendu que ${i.origin} ait ${t}${i.minimum.toString()} ${r.unit}`;return`Trop petit : attendu que ${i.origin} soit ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Cha\xeene invalide : doit commencer par "${i.prefix}"`;if("ends_with"===i.format)return`Cha\xeene invalide : doit se terminer par "${i.suffix}"`;if("includes"===i.format)return`Cha\xeene invalide : doit inclure "${i.includes}"`;if("regex"===i.format)return`Cha\xeene invalide : doit correspondre au motif ${i.pattern}`;return`${t[i.format]??i.format} 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${t}${i.minimum.toString()} ${r.unit}`;return`קטן מדי: ${i.origin} צריך להיות ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`מחרוזת לא תקינה: חייבת להתחיל ב"${i.prefix}"`;if("ends_with"===i.format)return`מחרוזת לא תקינה: חייבת להסתיים ב "${i.suffix}"`;if("includes"===i.format)return`מחרוזת לא תקינה: חייבת לכלול "${i.includes}"`;if("regex"===i.format)return`מחרוזת לא תקינה: חייבת להתאים לתבנית ${i.pattern}`;return`${t[i.format]??i.format} לא תקין`;case"not_multiple_of":return`מספר לא תקין: חייב להיות מכפלה של ${i.divisor}`;case"unrecognized_keys":return`מפתח${i.keys.length>1?"ות":""} לא מזוה${i.keys.length>1?"ים":"ה"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`מפתח לא תקין ב${i.origin}`;case"invalid_union":default:return"קלט לא תקין";case"invalid_element":return`ערך לא תקין ב${i.origin}`}})}},"hu",0,function(){let e,t;return{localeError:(e={string:{unit:"karakter",verb:"legyen"},file:{unit:"byte",verb:"legyen"},array:{unit:"elem",verb:"legyen"},set:{unit:"elem",verb:"legyen"}},t={regex:"bemenet",email:"email cím",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO időbélyeg",date:"ISO dátum",time:"ISO idő",duration:"ISO időintervallum",ipv4:"IPv4 cím",ipv6:"IPv6 cím",cidrv4:"IPv4 tartomány",cidrv6:"IPv6 tartomány",base64:"base64-kódolt string",base64url:"base64url-kódolt string",json_string:"JSON string",e164:"E.164 szám",jwt:"JWT",template_literal:"bemenet"},i=>{switch(i.code){case"invalid_type":return`\xc9rv\xe9nytelen bemenet: a v\xe1rt \xe9rt\xe9k ${i.expected}, a kapott \xe9rt\xe9k ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"szám";case"object":if(Array.isArray(e))return"tömb";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`\xc9rv\xe9nytelen bemenet: a v\xe1rt \xe9rt\xe9k ${V.stringifyPrimitive(i.values[0])}`;return`\xc9rv\xe9nytelen opci\xf3: valamelyik \xe9rt\xe9k v\xe1rt ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`T\xfal nagy: ${i.origin??"érték"} m\xe9rete t\xfal nagy ${t}${i.maximum.toString()} ${r.unit??"elem"}`;return`T\xfal nagy: a bemeneti \xe9rt\xe9k ${i.origin??"érték"} t\xfal nagy: ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`T\xfal kicsi: a bemeneti \xe9rt\xe9k ${i.origin} m\xe9rete t\xfal kicsi ${t}${i.minimum.toString()} ${r.unit}`;return`T\xfal kicsi: a bemeneti \xe9rt\xe9k ${i.origin} t\xfal kicsi ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`\xc9rv\xe9nytelen string: "${i.prefix}" \xe9rt\xe9kkel kell kezdődnie`;if("ends_with"===i.format)return`\xc9rv\xe9nytelen string: "${i.suffix}" \xe9rt\xe9kkel kell v\xe9gződnie`;if("includes"===i.format)return`\xc9rv\xe9nytelen string: "${i.includes}" \xe9rt\xe9ket kell tartalmaznia`;if("regex"===i.format)return`\xc9rv\xe9nytelen string: ${i.pattern} mint\xe1nak kell megfelelnie`;return`\xc9rv\xe9nytelen ${t[i.format]??i.format}`;case"not_multiple_of":return`\xc9rv\xe9nytelen sz\xe1m: ${i.divisor} t\xf6bbsz\xf6r\xf6s\xe9nek kell lennie`;case"unrecognized_keys":return`Ismeretlen kulcs${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`\xc9rv\xe9nytelen kulcs ${i.origin}`;case"invalid_union":default:return"Érvénytelen bemenet";case"invalid_element":return`\xc9rv\xe9nytelen \xe9rt\xe9k: ${i.origin}`}})}},"id",0,function(){let e,t;return{localeError:(e={string:{unit:"karakter",verb:"memiliki"},file:{unit:"byte",verb:"memiliki"},array:{unit:"item",verb:"memiliki"},set:{unit:"item",verb:"memiliki"}},t={regex:"input",email:"alamat email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"tanggal dan waktu format ISO",date:"tanggal format ISO",time:"jam format ISO",duration:"durasi format ISO",ipv4:"alamat IPv4",ipv6:"alamat IPv6",cidrv4:"rentang alamat IPv4",cidrv6:"rentang alamat IPv6",base64:"string dengan enkode base64",base64url:"string dengan enkode base64url",json_string:"string JSON",e164:"angka E.164",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Input tidak valid: diharapkan ${i.expected}, diterima ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Input tidak valid: diharapkan ${V.stringifyPrimitive(i.values[0])}`;return`Pilihan tidak valid: diharapkan salah satu dari ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Terlalu besar: diharapkan ${i.origin??"value"} memiliki ${t}${i.maximum.toString()} ${r.unit??"elemen"}`;return`Terlalu besar: diharapkan ${i.origin??"value"} menjadi ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Terlalu kecil: diharapkan ${i.origin} memiliki ${t}${i.minimum.toString()} ${r.unit}`;return`Terlalu kecil: diharapkan ${i.origin} menjadi ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`String tidak valid: harus dimulai dengan "${i.prefix}"`;if("ends_with"===i.format)return`String tidak valid: harus berakhir dengan "${i.suffix}"`;if("includes"===i.format)return`String tidak valid: harus menyertakan "${i.includes}"`;if("regex"===i.format)return`String tidak valid: harus sesuai pola ${i.pattern}`;return`${t[i.format]??i.format} tidak valid`;case"not_multiple_of":return`Angka tidak valid: harus kelipatan dari ${i.divisor}`;case"unrecognized_keys":return`Kunci tidak dikenali ${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Kunci tidak valid di ${i.origin}`;case"invalid_union":default:return"Input tidak valid";case"invalid_element":return`Nilai tidak valid di ${i.origin}`}})}},"it",0,function(){let e,t;return{localeError:(e={string:{unit:"caratteri",verb:"avere"},file:{unit:"byte",verb:"avere"},array:{unit:"elementi",verb:"avere"},set:{unit:"elementi",verb:"avere"}},t={regex:"input",email:"indirizzo email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data e ora ISO",date:"data ISO",time:"ora ISO",duration:"durata ISO",ipv4:"indirizzo IPv4",ipv6:"indirizzo IPv6",cidrv4:"intervallo IPv4",cidrv6:"intervallo IPv6",base64:"stringa codificata in base64",base64url:"URL codificata in base64",json_string:"stringa JSON",e164:"numero E.164",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Input non valido: atteso ${i.expected}, ricevuto ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"numero";case"object":if(Array.isArray(e))return"vettore";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Input non valido: atteso ${V.stringifyPrimitive(i.values[0])}`;return`Opzione non valida: atteso uno tra ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Troppo grande: ${i.origin??"valore"} deve avere ${t}${i.maximum.toString()} ${r.unit??"elementi"}`;return`Troppo grande: ${i.origin??"valore"} deve essere ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Troppo piccolo: ${i.origin} deve avere ${t}${i.minimum.toString()} ${r.unit}`;return`Troppo piccolo: ${i.origin} deve essere ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Stringa non valida: deve iniziare con "${i.prefix}"`;if("ends_with"===i.format)return`Stringa non valida: deve terminare con "${i.suffix}"`;if("includes"===i.format)return`Stringa non valida: deve includere "${i.includes}"`;if("regex"===i.format)return`Stringa non valida: deve corrispondere al pattern ${i.pattern}`;return`Invalid ${t[i.format]??i.format}`;case"not_multiple_of":return`Numero non valido: deve essere un multiplo di ${i.divisor}`;case"unrecognized_keys":return`Chiav${i.keys.length>1?"i":"e"} non riconosciut${i.keys.length>1?"e":"a"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Chiave non valida in ${i.origin}`;case"invalid_union":default:return"Input non valido";case"invalid_element":return`Valore non valido in ${i.origin}`}})}},"ja",0,function(){let e,t;return{localeError:(e={string:{unit:"文字",verb:"である"},file:{unit:"バイト",verb:"である"},array:{unit:"要素",verb:"である"},set:{unit:"要素",verb:"である"}},t={regex:"入力値",email:"メールアドレス",url:"URL",emoji:"絵文字",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO日時",date:"ISO日付",time:"ISO時刻",duration:"ISO期間",ipv4:"IPv4アドレス",ipv6:"IPv6アドレス",cidrv4:"IPv4範囲",cidrv6:"IPv6範囲",base64:"base64エンコード文字列",base64url:"base64urlエンコード文字列",json_string:"JSON文字列",e164:"E.164番号",jwt:"JWT",template_literal:"入力値"},i=>{switch(i.code){case"invalid_type":return`無効な入力: ${i.expected}が期待されましたが、${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"数値";case"object":if(Array.isArray(e))return"配列";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}が入力されました`;case"invalid_value":if(1===i.values.length)return`無効な入力: ${V.stringifyPrimitive(i.values[0])}が期待されました`;return`無効な選択: ${V.joinValues(i.values,"、")}のいずれかである必要があります`;case"too_big":{let t=i.inclusive?"以下である":"より小さい",r=e[i.origin]??null;if(r)return`大きすぎる値: ${i.origin??"値"}は${i.maximum.toString()}${r.unit??"要素"}${t}必要があります`;return`大きすぎる値: ${i.origin??"値"}は${i.maximum.toString()}${t}必要があります`}case"too_small":{let t=i.inclusive?"以上である":"より大きい",r=e[i.origin]??null;if(r)return`小さすぎる値: ${i.origin}は${i.minimum.toString()}${r.unit}${t}必要があります`;return`小さすぎる値: ${i.origin}は${i.minimum.toString()}${t}必要があります`}case"invalid_format":if("starts_with"===i.format)return`無効な文字列: "${i.prefix}"で始まる必要があります`;if("ends_with"===i.format)return`無効な文字列: "${i.suffix}"で終わる必要があります`;if("includes"===i.format)return`無効な文字列: "${i.includes}"を含む必要があります`;if("regex"===i.format)return`無効な文字列: パターン${i.pattern}に一致する必要があります`;return`無効な${t[i.format]??i.format}`;case"not_multiple_of":return`無効な数値: ${i.divisor}の倍数である必要があります`;case"unrecognized_keys":return`認識されていないキー${i.keys.length>1?"群":""}: ${V.joinValues(i.keys,"、")}`;case"invalid_key":return`${i.origin}内の無効なキー`;case"invalid_union":default:return"無効な入力";case"invalid_element":return`${i.origin}内の無効な値`}})}},"kh",0,function(){let e,t;return{localeError:(e={string:{unit:"តួអក្សរ",verb:"គួរមាន"},file:{unit:"បៃ",verb:"គួរមាន"},array:{unit:"ធាតុ",verb:"គួរមាន"},set:{unit:"ធាតុ",verb:"គួរមាន"}},t={regex:"ទិន្នន័យបញ្ចូល",email:"អាសយដ្ឋានអ៊ីមែល",url:"URL",emoji:"សញ្ញាអារម្មណ៍",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"កាលបរិច្ឆេទ និងម៉ោង ISO",date:"កាលបរិច្ឆេទ ISO",time:"ម៉ោង ISO",duration:"រយៈពេល ISO",ipv4:"អាសយដ្ឋាន IPv4",ipv6:"អាសយដ្ឋាន IPv6",cidrv4:"ដែនអាសយដ្ឋាន IPv4",cidrv6:"ដែនអាសយដ្ឋាន IPv6",base64:"ខ្សែអក្សរអ៊ិកូដ base64",base64url:"ខ្សែអក្សរអ៊ិកូដ base64url",json_string:"ខ្សែអក្សរ JSON",e164:"លេខ E.164",jwt:"JWT",template_literal:"ទិន្នន័យបញ្ចូល"},i=>{switch(i.code){case"invalid_type":return`ទិន្នន័យបញ្ចូលមិនត្រឹមត្រូវ៖ ត្រូវការ ${i.expected} ប៉ុន្តែទទួលបាន ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"មិនមែនជាលេខ (NaN)":"លេខ";case"object":if(Array.isArray(e))return"អារេ (Array)";if(null===e)return"គ្មានតម្លៃ (null)";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`ទិន្នន័យបញ្ចូលមិនត្រឹមត្រូវ៖ ត្រូវការ ${V.stringifyPrimitive(i.values[0])}`;return`ជម្រើសមិនត្រឹមត្រូវ៖ ត្រូវជាមួយក្នុងចំណោម ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`ធំពេក៖ ត្រូវការ ${i.origin??"តម្លៃ"} ${t} ${i.maximum.toString()} ${r.unit??"ធាតុ"}`;return`ធំពេក៖ ត្រូវការ ${i.origin??"តម្លៃ"} ${t} ${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`តូចពេក៖ ត្រូវការ ${i.origin} ${t} ${i.minimum.toString()} ${r.unit}`;return`តូចពេក៖ ត្រូវការ ${i.origin} ${t} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវចាប់ផ្តើមដោយ "${i.prefix}"`;if("ends_with"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវបញ្ចប់ដោយ "${i.suffix}"`;if("includes"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវមាន "${i.includes}"`;if("regex"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវតែផ្គូផ្គងនឹងទម្រង់ដែលបានកំណត់ ${i.pattern}`;return`មិនត្រឹមត្រូវ៖ ${t[i.format]??i.format}`;case"not_multiple_of":return`លេខមិនត្រឹមត្រូវ៖ ត្រូវតែជាពហុគុណនៃ ${i.divisor}`;case"unrecognized_keys":return`រកឃើញសោមិនស្គាល់៖ ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`សោមិនត្រឹមត្រូវនៅក្នុង ${i.origin}`;case"invalid_union":default:return"ទិន្នន័យមិនត្រឹមត្រូវ";case"invalid_element":return`ទិន្នន័យមិនត្រឹមត្រូវនៅក្នុង ${i.origin}`}})}},"ko",0,function(){let e,t;return{localeError:(e={string:{unit:"문자",verb:"to have"},file:{unit:"바이트",verb:"to have"},array:{unit:"개",verb:"to have"},set:{unit:"개",verb:"to have"}},t={regex:"입력",email:"이메일 주소",url:"URL",emoji:"이모지",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO 날짜시간",date:"ISO 날짜",time:"ISO 시간",duration:"ISO 기간",ipv4:"IPv4 주소",ipv6:"IPv6 주소",cidrv4:"IPv4 범위",cidrv6:"IPv6 범위",base64:"base64 인코딩 문자열",base64url:"base64url 인코딩 문자열",json_string:"JSON 문자열",e164:"E.164 번호",jwt:"JWT",template_literal:"입력"},i=>{switch(i.code){case"invalid_type":return`잘못된 입력: 예상 타입은 ${i.expected}, 받은 타입은 ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}입니다`;case"invalid_value":if(1===i.values.length)return`잘못된 입력: 값은 ${V.stringifyPrimitive(i.values[0])} 이어야 합니다`;return`잘못된 옵션: ${V.joinValues(i.values,"또는 ")} 중 하나여야 합니다`;case"too_big":{let t=i.inclusive?"이하":"미만",r="미만"===t?"이어야 합니다":"여야 합니다",n=e[i.origin]??null,a=n?.unit??"요소";if(n)return`${i.origin??"값"}이 너무 큽니다: ${i.maximum.toString()}${a} ${t}${r}`;return`${i.origin??"값"}이 너무 큽니다: ${i.maximum.toString()} ${t}${r}`}case"too_small":{let t=i.inclusive?"이상":"초과",r="이상"===t?"이어야 합니다":"여야 합니다",n=e[i.origin]??null,a=n?.unit??"요소";if(n)return`${i.origin??"값"}이 너무 작습니다: ${i.minimum.toString()}${a} ${t}${r}`;return`${i.origin??"값"}이 너무 작습니다: ${i.minimum.toString()} ${t}${r}`}case"invalid_format":if("starts_with"===i.format)return`잘못된 문자열: "${i.prefix}"(으)로 시작해야 합니다`;if("ends_with"===i.format)return`잘못된 문자열: "${i.suffix}"(으)로 끝나야 합니다`;if("includes"===i.format)return`잘못된 문자열: "${i.includes}"을(를) 포함해야 합니다`;if("regex"===i.format)return`잘못된 문자열: 정규식 ${i.pattern} 패턴과 일치해야 합니다`;return`잘못된 ${t[i.format]??i.format}`;case"not_multiple_of":return`잘못된 숫자: ${i.divisor}의 배수여야 합니다`;case"unrecognized_keys":return`인식할 수 없는 키: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`잘못된 키: ${i.origin}`;case"invalid_union":default:return"잘못된 입력";case"invalid_element":return`잘못된 값: ${i.origin}`}})}},"mk",0,function(){let e,t;return{localeError:(e={string:{unit:"знаци",verb:"да имаат"},file:{unit:"бајти",verb:"да имаат"},array:{unit:"ставки",verb:"да имаат"},set:{unit:"ставки",verb:"да имаат"}},t={regex:"внес",email:"адреса на е-пошта",url:"URL",emoji:"емоџи",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO датум и време",date:"ISO датум",time:"ISO време",duration:"ISO времетраење",ipv4:"IPv4 адреса",ipv6:"IPv6 адреса",cidrv4:"IPv4 опсег",cidrv6:"IPv6 опсег",base64:"base64-енкодирана низа",base64url:"base64url-енкодирана низа",json_string:"JSON низа",e164:"E.164 број",jwt:"JWT",template_literal:"внес"},i=>{switch(i.code){case"invalid_type":return`Грешен внес: се очекува ${i.expected}, примено ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"број";case"object":if(Array.isArray(e))return"низа";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Invalid input: expected ${V.stringifyPrimitive(i.values[0])}`;return`Грешана опција: се очекува една ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Премногу голем: се очекува ${i.origin??"вредноста"} да има ${t}${i.maximum.toString()} ${r.unit??"елементи"}`;return`Премногу голем: се очекува ${i.origin??"вредноста"} да биде ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Премногу мал: се очекува ${i.origin} да има ${t}${i.minimum.toString()} ${r.unit}`;return`Премногу мал: се очекува ${i.origin} да биде ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Неважечка низа: мора да започнува со "${i.prefix}"`;if("ends_with"===i.format)return`Неважечка низа: мора да завршува со "${i.suffix}"`;if("includes"===i.format)return`Неважечка низа: мора да вклучува "${i.includes}"`;if("regex"===i.format)return`Неважечка низа: мора да одгоара на патернот ${i.pattern}`;return`Invalid ${t[i.format]??i.format}`;case"not_multiple_of":return`Грешен број: мора да биде делив со ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Непрепознаени клучеви":"Непрепознаен клуч"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Грешен клуч во ${i.origin}`;case"invalid_union":default:return"Грешен внес";case"invalid_element":return`Грешна вредност во ${i.origin}`}})}},"ms",0,function(){let e,t;return{localeError:(e={string:{unit:"aksara",verb:"mempunyai"},file:{unit:"bait",verb:"mempunyai"},array:{unit:"elemen",verb:"mempunyai"},set:{unit:"elemen",verb:"mempunyai"}},t={regex:"input",email:"alamat e-mel",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"tarikh masa ISO",date:"tarikh ISO",time:"masa ISO",duration:"tempoh ISO",ipv4:"alamat IPv4",ipv6:"alamat IPv6",cidrv4:"julat IPv4",cidrv6:"julat IPv6",base64:"string dikodkan base64",base64url:"string dikodkan base64url",json_string:"string JSON",e164:"nombor E.164",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Input tidak sah: dijangka ${i.expected}, diterima ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"nombor";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Input tidak sah: dijangka ${V.stringifyPrimitive(i.values[0])}`;return`Pilihan tidak sah: dijangka salah satu daripada ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Terlalu besar: dijangka ${i.origin??"nilai"} ${r.verb} ${t}${i.maximum.toString()} ${r.unit??"elemen"}`;return`Terlalu besar: dijangka ${i.origin??"nilai"} adalah ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Terlalu kecil: dijangka ${i.origin} ${r.verb} ${t}${i.minimum.toString()} ${r.unit}`;return`Terlalu kecil: dijangka ${i.origin} adalah ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`String tidak sah: mesti bermula dengan "${i.prefix}"`;if("ends_with"===i.format)return`String tidak sah: mesti berakhir dengan "${i.suffix}"`;if("includes"===i.format)return`String tidak sah: mesti mengandungi "${i.includes}"`;if("regex"===i.format)return`String tidak sah: mesti sepadan dengan corak ${i.pattern}`;return`${t[i.format]??i.format} tidak sah`;case"not_multiple_of":return`Nombor tidak sah: perlu gandaan ${i.divisor}`;case"unrecognized_keys":return`Kunci tidak dikenali: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Kunci tidak sah dalam ${i.origin}`;case"invalid_union":default:return"Input tidak sah";case"invalid_element":return`Nilai tidak sah dalam ${i.origin}`}})}},"nl",0,function(){let e,t;return{localeError:(e={string:{unit:"tekens"},file:{unit:"bytes"},array:{unit:"elementen"},set:{unit:"elementen"}},t={regex:"invoer",email:"emailadres",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO datum en tijd",date:"ISO datum",time:"ISO tijd",duration:"ISO duur",ipv4:"IPv4-adres",ipv6:"IPv6-adres",cidrv4:"IPv4-bereik",cidrv6:"IPv6-bereik",base64:"base64-gecodeerde tekst",base64url:"base64 URL-gecodeerde tekst",json_string:"JSON string",e164:"E.164-nummer",jwt:"JWT",template_literal:"invoer"},i=>{switch(i.code){case"invalid_type":return`Ongeldige invoer: verwacht ${i.expected}, ontving ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"getal";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ongeldige invoer: verwacht ${V.stringifyPrimitive(i.values[0])}`;return`Ongeldige optie: verwacht \xe9\xe9n van ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Te lang: verwacht dat ${i.origin??"waarde"} ${t}${i.maximum.toString()} ${r.unit??"elementen"} bevat`;return`Te lang: verwacht dat ${i.origin??"waarde"} ${t}${i.maximum.toString()} is`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Te kort: verwacht dat ${i.origin} ${t}${i.minimum.toString()} ${r.unit} bevat`;return`Te kort: verwacht dat ${i.origin} ${t}${i.minimum.toString()} is`}case"invalid_format":if("starts_with"===i.format)return`Ongeldige tekst: moet met "${i.prefix}" beginnen`;if("ends_with"===i.format)return`Ongeldige tekst: moet op "${i.suffix}" eindigen`;if("includes"===i.format)return`Ongeldige tekst: moet "${i.includes}" bevatten`;if("regex"===i.format)return`Ongeldige tekst: moet overeenkomen met patroon ${i.pattern}`;return`Ongeldig: ${t[i.format]??i.format}`;case"not_multiple_of":return`Ongeldig getal: moet een veelvoud van ${i.divisor} zijn`;case"unrecognized_keys":return`Onbekende key${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Ongeldige key in ${i.origin}`;case"invalid_union":default:return"Ongeldige invoer";case"invalid_element":return`Ongeldige waarde in ${i.origin}`}})}},"no",0,function(){let e,t;return{localeError:(e={string:{unit:"tegn",verb:"å ha"},file:{unit:"bytes",verb:"å ha"},array:{unit:"elementer",verb:"å inneholde"},set:{unit:"elementer",verb:"å inneholde"}},t={regex:"input",email:"e-postadresse",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO dato- og klokkeslett",date:"ISO-dato",time:"ISO-klokkeslett",duration:"ISO-varighet",ipv4:"IPv4-område",ipv6:"IPv6-område",cidrv4:"IPv4-spekter",cidrv6:"IPv6-spekter",base64:"base64-enkodet streng",base64url:"base64url-enkodet streng",json_string:"JSON-streng",e164:"E.164-nummer",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Ugyldig input: forventet ${i.expected}, fikk ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"tall";case"object":if(Array.isArray(e))return"liste";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ugyldig verdi: forventet ${V.stringifyPrimitive(i.values[0])}`;return`Ugyldig valg: forventet en av ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`For stor(t): forventet ${i.origin??"value"} til \xe5 ha ${t}${i.maximum.toString()} ${r.unit??"elementer"}`;return`For stor(t): forventet ${i.origin??"value"} til \xe5 ha ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`For lite(n): forventet ${i.origin} til \xe5 ha ${t}${i.minimum.toString()} ${r.unit}`;return`For lite(n): forventet ${i.origin} til \xe5 ha ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ugyldig streng: m\xe5 starte med "${i.prefix}"`;if("ends_with"===i.format)return`Ugyldig streng: m\xe5 ende med "${i.suffix}"`;if("includes"===i.format)return`Ugyldig streng: m\xe5 inneholde "${i.includes}"`;if("regex"===i.format)return`Ugyldig streng: m\xe5 matche m\xf8nsteret ${i.pattern}`;return`Ugyldig ${t[i.format]??i.format}`;case"not_multiple_of":return`Ugyldig tall: m\xe5 v\xe6re et multiplum av ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Ukjente nøkler":"Ukjent nøkkel"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Ugyldig n\xf8kkel i ${i.origin}`;case"invalid_union":default:return"Ugyldig input";case"invalid_element":return`Ugyldig verdi i ${i.origin}`}})}},"ota",0,function(){let e,t;return{localeError:(e={string:{unit:"harf",verb:"olmalıdır"},file:{unit:"bayt",verb:"olmalıdır"},array:{unit:"unsur",verb:"olmalıdır"},set:{unit:"unsur",verb:"olmalıdır"}},t={regex:"giren",email:"epostagâh",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO hengâmı",date:"ISO tarihi",time:"ISO zamanı",duration:"ISO müddeti",ipv4:"IPv4 nişânı",ipv6:"IPv6 nişânı",cidrv4:"IPv4 menzili",cidrv6:"IPv6 menzili",base64:"base64-şifreli metin",base64url:"base64url-şifreli metin",json_string:"JSON metin",e164:"E.164 sayısı",jwt:"JWT",template_literal:"giren"},i=>{switch(i.code){case"invalid_type":return`F\xe2sit giren: umulan ${i.expected}, alınan ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"numara";case"object":if(Array.isArray(e))return"saf";if(null===e)return"gayb";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`F\xe2sit giren: umulan ${V.stringifyPrimitive(i.values[0])}`;return`F\xe2sit tercih: m\xfbteberler ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Fazla b\xfcy\xfck: ${i.origin??"value"}, ${t}${i.maximum.toString()} ${r.unit??"elements"} sahip olmalıydı.`;return`Fazla b\xfcy\xfck: ${i.origin??"value"}, ${t}${i.maximum.toString()} olmalıydı.`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Fazla k\xfc\xe7\xfck: ${i.origin}, ${t}${i.minimum.toString()} ${r.unit} sahip olmalıydı.`;return`Fazla k\xfc\xe7\xfck: ${i.origin}, ${t}${i.minimum.toString()} olmalıydı.`}case"invalid_format":if("starts_with"===i.format)return`F\xe2sit metin: "${i.prefix}" ile başlamalı.`;if("ends_with"===i.format)return`F\xe2sit metin: "${i.suffix}" ile bitmeli.`;if("includes"===i.format)return`F\xe2sit metin: "${i.includes}" ihtiv\xe2 etmeli.`;if("regex"===i.format)return`F\xe2sit metin: ${i.pattern} nakşına uymalı.`;return`F\xe2sit ${t[i.format]??i.format}`;case"not_multiple_of":return`F\xe2sit sayı: ${i.divisor} katı olmalıydı.`;case"unrecognized_keys":return`Tanınmayan anahtar ${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`${i.origin} i\xe7in tanınmayan anahtar var.`;case"invalid_union":return"Giren tanınamadı.";case"invalid_element":return`${i.origin} i\xe7in tanınmayan kıymet var.`;default:return"Kıymet tanınamadı."}})}},"pl",0,function(){let e,t;return{localeError:(e={string:{unit:"znaków",verb:"mieć"},file:{unit:"bajtów",verb:"mieć"},array:{unit:"elementów",verb:"mieć"},set:{unit:"elementów",verb:"mieć"}},t={regex:"wyrażenie",email:"adres email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data i godzina w formacie ISO",date:"data w formacie ISO",time:"godzina w formacie ISO",duration:"czas trwania ISO",ipv4:"adres IPv4",ipv6:"adres IPv6",cidrv4:"zakres IPv4",cidrv6:"zakres IPv6",base64:"ciąg znaków zakodowany w formacie base64",base64url:"ciąg znaków zakodowany w formacie base64url",json_string:"ciąg znaków w formacie JSON",e164:"liczba E.164",jwt:"JWT",template_literal:"wejście"},i=>{switch(i.code){case"invalid_type":return`Nieprawidłowe dane wejściowe: oczekiwano ${i.expected}, otrzymano ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"liczba";case"object":if(Array.isArray(e))return"tablica";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Nieprawidłowe dane wejściowe: oczekiwano ${V.stringifyPrimitive(i.values[0])}`;return`Nieprawidłowa opcja: oczekiwano jednej z wartości ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Za duża wartość: oczekiwano, że ${i.origin??"wartość"} będzie mieć ${t}${i.maximum.toString()} ${r.unit??"elementów"}`;return`Zbyt duż(y/a/e): oczekiwano, że ${i.origin??"wartość"} będzie wynosić ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Za mała wartość: oczekiwano, że ${i.origin??"wartość"} będzie mieć ${t}${i.minimum.toString()} ${r.unit??"elementów"}`;return`Zbyt mał(y/a/e): oczekiwano, że ${i.origin??"wartość"} będzie wynosić ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi zaczynać się od "${i.prefix}"`;if("ends_with"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi kończyć się na "${i.suffix}"`;if("includes"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi zawierać "${i.includes}"`;if("regex"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi odpowiadać wzorcowi ${i.pattern}`;return`Nieprawidłow(y/a/e) ${t[i.format]??i.format}`;case"not_multiple_of":return`Nieprawidłowa liczba: musi być wielokrotnością ${i.divisor}`;case"unrecognized_keys":return`Nierozpoznane klucze${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Nieprawidłowy klucz w ${i.origin}`;case"invalid_union":default:return"Nieprawidłowe dane wejściowe";case"invalid_element":return`Nieprawidłowa wartość w ${i.origin}`}})}},"ps",0,function(){let e,t;return{localeError:(e={string:{unit:"توکي",verb:"ولري"},file:{unit:"بایټس",verb:"ولري"},array:{unit:"توکي",verb:"ولري"},set:{unit:"توکي",verb:"ولري"}},t={regex:"ورودي",email:"بریښنالیک",url:"یو آر ال",emoji:"ایموجي",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"نیټه او وخت",date:"نېټه",time:"وخت",duration:"موده",ipv4:"د IPv4 پته",ipv6:"د IPv6 پته",cidrv4:"د IPv4 ساحه",cidrv6:"د IPv6 ساحه",base64:"base64-encoded متن",base64url:"base64url-encoded متن",json_string:"JSON متن",e164:"د E.164 شمېره",jwt:"JWT",template_literal:"ورودي"},i=>{switch(i.code){case"invalid_type":return`ناسم ورودي: باید ${i.expected} وای, مګر ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"عدد";case"object":if(Array.isArray(e))return"ارې";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} ترلاسه شو`;case"invalid_value":if(1===i.values.length)return`ناسم ورودي: باید ${V.stringifyPrimitive(i.values[0])} وای`;return`ناسم انتخاب: باید یو له ${V.joinValues(i.values,"|")} څخه وای`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`ډیر لوی: ${i.origin??"ارزښت"} باید ${t}${i.maximum.toString()} ${r.unit??"عنصرونه"} ولري`;return`ډیر لوی: ${i.origin??"ارزښت"} باید ${t}${i.maximum.toString()} وي`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`ډیر کوچنی: ${i.origin} باید ${t}${i.minimum.toString()} ${r.unit} ولري`;return`ډیر کوچنی: ${i.origin} باید ${t}${i.minimum.toString()} وي`}case"invalid_format":if("starts_with"===i.format)return`ناسم متن: باید د "${i.prefix}" سره پیل شي`;if("ends_with"===i.format)return`ناسم متن: باید د "${i.suffix}" سره پای ته ورسيږي`;if("includes"===i.format)return`ناسم متن: باید "${i.includes}" ولري`;if("regex"===i.format)return`ناسم متن: باید د ${i.pattern} سره مطابقت ولري`;return`${t[i.format]??i.format} ناسم دی`;case"not_multiple_of":return`ناسم عدد: باید د ${i.divisor} مضرب وي`;case"unrecognized_keys":return`ناسم ${i.keys.length>1?"کلیډونه":"کلیډ"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`ناسم کلیډ په ${i.origin} کې`;case"invalid_union":default:return"ناسمه ورودي";case"invalid_element":return`ناسم عنصر په ${i.origin} کې`}})}},"pt",0,function(){let e,t;return{localeError:(e={string:{unit:"caracteres",verb:"ter"},file:{unit:"bytes",verb:"ter"},array:{unit:"itens",verb:"ter"},set:{unit:"itens",verb:"ter"}},t={regex:"padrão",email:"endereço de e-mail",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data e hora ISO",date:"data ISO",time:"hora ISO",duration:"duração ISO",ipv4:"endereço IPv4",ipv6:"endereço IPv6",cidrv4:"faixa de IPv4",cidrv6:"faixa de IPv6",base64:"texto codificado em base64",base64url:"URL codificada em base64",json_string:"texto JSON",e164:"número E.164",jwt:"JWT",template_literal:"entrada"},i=>{switch(i.code){case"invalid_type":return`Tipo inv\xe1lido: esperado ${i.expected}, recebido ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"número";case"object":if(Array.isArray(e))return"array";if(null===e)return"nulo";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Entrada inv\xe1lida: esperado ${V.stringifyPrimitive(i.values[0])}`;return`Op\xe7\xe3o inv\xe1lida: esperada uma das ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Muito grande: esperado que ${i.origin??"valor"} tivesse ${t}${i.maximum.toString()} ${r.unit??"elementos"}`;return`Muito grande: esperado que ${i.origin??"valor"} fosse ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Muito pequeno: esperado que ${i.origin} tivesse ${t}${i.minimum.toString()} ${r.unit}`;return`Muito pequeno: esperado que ${i.origin} fosse ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Texto inv\xe1lido: deve come\xe7ar com "${i.prefix}"`;if("ends_with"===i.format)return`Texto inv\xe1lido: deve terminar com "${i.suffix}"`;if("includes"===i.format)return`Texto inv\xe1lido: deve incluir "${i.includes}"`;if("regex"===i.format)return`Texto inv\xe1lido: deve corresponder ao padr\xe3o ${i.pattern}`;return`${t[i.format]??i.format} inv\xe1lido`;case"not_multiple_of":return`N\xfamero inv\xe1lido: deve ser m\xfaltiplo de ${i.divisor}`;case"unrecognized_keys":return`Chave${i.keys.length>1?"s":""} desconhecida${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Chave inv\xe1lida em ${i.origin}`;case"invalid_union":return"Entrada inválida";case"invalid_element":return`Valor inv\xe1lido em ${i.origin}`;default:return"Campo inválido"}})}},"ru",0,function(){let e,t;return{localeError:(e={string:{unit:{one:"символ",few:"символа",many:"символов"},verb:"иметь"},file:{unit:{one:"байт",few:"байта",many:"байт"},verb:"иметь"},array:{unit:{one:"элемент",few:"элемента",many:"элементов"},verb:"иметь"},set:{unit:{one:"элемент",few:"элемента",many:"элементов"},verb:"иметь"}},t={regex:"ввод",email:"email адрес",url:"URL",emoji:"эмодзи",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO дата и время",date:"ISO дата",time:"ISO время",duration:"ISO длительность",ipv4:"IPv4 адрес",ipv6:"IPv6 адрес",cidrv4:"IPv4 диапазон",cidrv6:"IPv6 диапазон",base64:"строка в формате base64",base64url:"строка в формате base64url",json_string:"JSON строка",e164:"номер E.164",jwt:"JWT",template_literal:"ввод"},i=>{switch(i.code){case"invalid_type":return`Неверный ввод: ожидалось ${i.expected}, получено ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"число";case"object":if(Array.isArray(e))return"массив";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Неверный ввод: ожидалось ${V.stringifyPrimitive(i.values[0])}`;return`Неверный вариант: ожидалось одно из ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r){let e=tA(Number(i.maximum),r.unit.one,r.unit.few,r.unit.many);return`Слишком большое значение: ожидалось, что ${i.origin??"значение"} будет иметь ${t}${i.maximum.toString()} ${e}`}return`Слишком большое значение: ожидалось, что ${i.origin??"значение"} будет ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r){let e=tA(Number(i.minimum),r.unit.one,r.unit.few,r.unit.many);return`Слишком маленькое значение: ожидалось, что ${i.origin} будет иметь ${t}${i.minimum.toString()} ${e}`}return`Слишком маленькое значение: ожидалось, что ${i.origin} будет ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Неверная строка: должна начинаться с "${i.prefix}"`;if("ends_with"===i.format)return`Неверная строка: должна заканчиваться на "${i.suffix}"`;if("includes"===i.format)return`Неверная строка: должна содержать "${i.includes}"`;if("regex"===i.format)return`Неверная строка: должна соответствовать шаблону ${i.pattern}`;return`Неверный ${t[i.format]??i.format}`;case"not_multiple_of":return`Неверное число: должно быть кратным ${i.divisor}`;case"unrecognized_keys":return`Нераспознанн${i.keys.length>1?"ые":"ый"} ключ${i.keys.length>1?"и":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Неверный ключ в ${i.origin}`;case"invalid_union":default:return"Неверные входные данные";case"invalid_element":return`Неверное значение в ${i.origin}`}})}},"sl",0,function(){let e,t;return{localeError:(e={string:{unit:"znakov",verb:"imeti"},file:{unit:"bajtov",verb:"imeti"},array:{unit:"elementov",verb:"imeti"},set:{unit:"elementov",verb:"imeti"}},t={regex:"vnos",email:"e-poštni naslov",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO datum in čas",date:"ISO datum",time:"ISO čas",duration:"ISO trajanje",ipv4:"IPv4 naslov",ipv6:"IPv6 naslov",cidrv4:"obseg IPv4",cidrv6:"obseg IPv6",base64:"base64 kodiran niz",base64url:"base64url kodiran niz",json_string:"JSON niz",e164:"E.164 številka",jwt:"JWT",template_literal:"vnos"},i=>{switch(i.code){case"invalid_type":return`Neveljaven vnos: pričakovano ${i.expected}, prejeto ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"število";case"object":if(Array.isArray(e))return"tabela";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Neveljaven vnos: pričakovano ${V.stringifyPrimitive(i.values[0])}`;return`Neveljavna možnost: pričakovano eno izmed ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Preveliko: pričakovano, da bo ${i.origin??"vrednost"} imelo ${t}${i.maximum.toString()} ${r.unit??"elementov"}`;return`Preveliko: pričakovano, da bo ${i.origin??"vrednost"} ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Premajhno: pričakovano, da bo ${i.origin} imelo ${t}${i.minimum.toString()} ${r.unit}`;return`Premajhno: pričakovano, da bo ${i.origin} ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Neveljaven niz: mora se začeti z "${i.prefix}"`;if("ends_with"===i.format)return`Neveljaven niz: mora se končati z "${i.suffix}"`;if("includes"===i.format)return`Neveljaven niz: mora vsebovati "${i.includes}"`;if("regex"===i.format)return`Neveljaven niz: mora ustrezati vzorcu ${i.pattern}`;return`Neveljaven ${t[i.format]??i.format}`;case"not_multiple_of":return`Neveljavno število: mora biti večkratnik ${i.divisor}`;case"unrecognized_keys":return`Neprepoznan${i.keys.length>1?"i ključi":" ključ"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Neveljaven ključ v ${i.origin}`;case"invalid_union":default:return"Neveljaven vnos";case"invalid_element":return`Neveljavna vrednost v ${i.origin}`}})}},"sv",0,function(){let e,t;return{localeError:(e={string:{unit:"tecken",verb:"att ha"},file:{unit:"bytes",verb:"att ha"},array:{unit:"objekt",verb:"att innehålla"},set:{unit:"objekt",verb:"att innehålla"}},t={regex:"reguljärt uttryck",email:"e-postadress",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-datum och tid",date:"ISO-datum",time:"ISO-tid",duration:"ISO-varaktighet",ipv4:"IPv4-intervall",ipv6:"IPv6-intervall",cidrv4:"IPv4-spektrum",cidrv6:"IPv6-spektrum",base64:"base64-kodad sträng",base64url:"base64url-kodad sträng",json_string:"JSON-sträng",e164:"E.164-nummer",jwt:"JWT",template_literal:"mall-literal"},i=>{switch(i.code){case"invalid_type":return`Ogiltig inmatning: f\xf6rv\xe4ntat ${i.expected}, fick ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"antal";case"object":if(Array.isArray(e))return"lista";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ogiltig inmatning: f\xf6rv\xe4ntat ${V.stringifyPrimitive(i.values[0])}`;return`Ogiltigt val: f\xf6rv\xe4ntade en av ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`F\xf6r stor(t): f\xf6rv\xe4ntade ${i.origin??"värdet"} att ha ${t}${i.maximum.toString()} ${r.unit??"element"}`;return`F\xf6r stor(t): f\xf6rv\xe4ntat ${i.origin??"värdet"} att ha ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`F\xf6r lite(t): f\xf6rv\xe4ntade ${i.origin??"värdet"} att ha ${t}${i.minimum.toString()} ${r.unit}`;return`F\xf6r lite(t): f\xf6rv\xe4ntade ${i.origin??"värdet"} att ha ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ogiltig str\xe4ng: m\xe5ste b\xf6rja med "${i.prefix}"`;if("ends_with"===i.format)return`Ogiltig str\xe4ng: m\xe5ste sluta med "${i.suffix}"`;if("includes"===i.format)return`Ogiltig str\xe4ng: m\xe5ste inneh\xe5lla "${i.includes}"`;if("regex"===i.format)return`Ogiltig str\xe4ng: m\xe5ste matcha m\xf6nstret "${i.pattern}"`;return`Ogiltig(t) ${t[i.format]??i.format}`;case"not_multiple_of":return`Ogiltigt tal: m\xe5ste vara en multipel av ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Okända nycklar":"Okänd nyckel"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Ogiltig nyckel i ${i.origin??"värdet"}`;case"invalid_union":default:return"Ogiltig input";case"invalid_element":return`Ogiltigt v\xe4rde i ${i.origin??"värdet"}`}})}},"ta",0,function(){let e,t;return{localeError:(e={string:{unit:"எழுத்துக்கள்",verb:"கொண்டிருக்க வேண்டும்"},file:{unit:"பைட்டுகள்",verb:"கொண்டிருக்க வேண்டும்"},array:{unit:"உறுப்புகள்",verb:"கொண்டிருக்க வேண்டும்"},set:{unit:"உறுப்புகள்",verb:"கொண்டிருக்க வேண்டும்"}},t={regex:"உள்ளீடு",email:"மின்னஞ்சல் முகவரி",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO தேதி நேரம்",date:"ISO தேதி",time:"ISO நேரம்",duration:"ISO கால அளவு",ipv4:"IPv4 முகவரி",ipv6:"IPv6 முகவரி",cidrv4:"IPv4 வரம்பு",cidrv6:"IPv6 வரம்பு",base64:"base64-encoded சரம்",base64url:"base64url-encoded சரம்",json_string:"JSON சரம்",e164:"E.164 எண்",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`தவறான உள்ளீடு: எதிர்பார்க்கப்பட்டது ${i.expected}, பெறப்பட்டது ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"எண் அல்லாதது":"எண்";case"object":if(Array.isArray(e))return"அணி";if(null===e)return"வெறுமை";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`தவறான உள்ளீடு: எதிர்பார்க்கப்பட்டது ${V.stringifyPrimitive(i.values[0])}`;return`தவறான விருப்பம்: எதிர்பார்க்கப்பட்டது ${V.joinValues(i.values,"|")} இல் ஒன்று`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`மிக பெரியது: எதிர்பார்க்கப்பட்டது ${i.origin??"மதிப்பு"} ${t}${i.maximum.toString()} ${r.unit??"உறுப்புகள்"} ஆக இருக்க வேண்டும்`;return`மிக பெரியது: எதிர்பார்க்கப்பட்டது ${i.origin??"மதிப்பு"} ${t}${i.maximum.toString()} ஆக இருக்க வேண்டும்`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`மிகச் சிறியது: எதிர்பார்க்கப்பட்டது ${i.origin} ${t}${i.minimum.toString()} ${r.unit} ஆக இருக்க வேண்டும்`;return`மிகச் சிறியது: எதிர்பார்க்கப்பட்டது ${i.origin} ${t}${i.minimum.toString()} ஆக இருக்க வேண்டும்`}case"invalid_format":if("starts_with"===i.format)return`தவறான சரம்: "${i.prefix}" இல் தொடங்க வேண்டும்`;if("ends_with"===i.format)return`தவறான சரம்: "${i.suffix}" இல் முடிவடைய வேண்டும்`;if("includes"===i.format)return`தவறான சரம்: "${i.includes}" ஐ உள்ளடக்க வேண்டும்`;if("regex"===i.format)return`தவறான சரம்: ${i.pattern} முறைபாட்டுடன் பொருந்த வேண்டும்`;return`தவறான ${t[i.format]??i.format}`;case"not_multiple_of":return`தவறான எண்: ${i.divisor} இன் பலமாக இருக்க வேண்டும்`;case"unrecognized_keys":return`அடையாளம் தெரியாத விசை${i.keys.length>1?"கள்":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`${i.origin} இல் தவறான விசை`;case"invalid_union":default:return"தவறான உள்ளீடு";case"invalid_element":return`${i.origin} இல் தவறான 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"${i.prefix}"`;if("ends_with"===i.format)return`รูปแบบไม่ถูกต้อง: ข้อความต้องลงท้ายด้วย "${i.suffix}"`;if("includes"===i.format)return`รูปแบบไม่ถูกต้อง: ข้อความต้องมี "${i.includes}" อยู่ในข้อความ`;if("regex"===i.format)return`รูปแบบไม่ถูกต้อง: ต้องตรงกับรูปแบบที่กำหนด ${i.pattern}`;return`รูปแบบไม่ถูกต้อง: ${t[i.format]??i.format}`;case"not_multiple_of":return`ตัวเลขไม่ถูกต้อง: ต้องเป็นจำนวนที่หารด้วย ${i.divisor} ได้ลงตัว`;case"unrecognized_keys":return`พบคีย์ที่ไม่รู้จัก: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`คีย์ไม่ถูกต้องใน ${i.origin}`;case"invalid_union":return"ข้อมูลไม่ถูกต้อง: ไม่ตรงกับรูปแบบยูเนียนที่กำหนดไว้";case"invalid_element":return`ข้อมูลไม่ถูกต้องใน ${i.origin}`;default:return"ข้อมูลไม่ถูกต้อง"}})}},"tr",0,function(){let e,t;return{localeError:(e={string:{unit:"karakter",verb:"olmalı"},file:{unit:"bayt",verb:"olmalı"},array:{unit:"öğe",verb:"olmalı"},set:{unit:"öğe",verb:"olmalı"}},t={regex:"girdi",email:"e-posta adresi",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO tarih ve saat",date:"ISO tarih",time:"ISO saat",duration:"ISO süre",ipv4:"IPv4 adresi",ipv6:"IPv6 adresi",cidrv4:"IPv4 aralığı",cidrv6:"IPv6 aralığı",base64:"base64 ile şifrelenmiş metin",base64url:"base64url ile şifrelenmiş metin",json_string:"JSON dizesi",e164:"E.164 sayısı",jwt:"JWT",template_literal:"Şablon dizesi"},i=>{switch(i.code){case"invalid_type":return`Ge\xe7ersiz değer: beklenen ${i.expected}, alınan ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ge\xe7ersiz değer: beklenen ${V.stringifyPrimitive(i.values[0])}`;return`Ge\xe7ersiz se\xe7enek: aşağıdakilerden biri olmalı: ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`\xc7ok b\xfcy\xfck: beklenen ${i.origin??"değer"} ${t}${i.maximum.toString()} ${r.unit??"öğe"}`;return`\xc7ok b\xfcy\xfck: beklenen ${i.origin??"değer"} ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`\xc7ok k\xfc\xe7\xfck: beklenen ${i.origin} ${t}${i.minimum.toString()} ${r.unit}`;return`\xc7ok k\xfc\xe7\xfck: beklenen ${i.origin} ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ge\xe7ersiz metin: "${i.prefix}" ile başlamalı`;if("ends_with"===i.format)return`Ge\xe7ersiz metin: "${i.suffix}" ile bitmeli`;if("includes"===i.format)return`Ge\xe7ersiz metin: "${i.includes}" i\xe7ermeli`;if("regex"===i.format)return`Ge\xe7ersiz metin: ${i.pattern} desenine uymalı`;return`Ge\xe7ersiz ${t[i.format]??i.format}`;case"not_multiple_of":return`Ge\xe7ersiz sayı: ${i.divisor} ile tam b\xf6l\xfcnebilmeli`;case"unrecognized_keys":return`Tanınmayan anahtar${i.keys.length>1?"lar":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`${i.origin} i\xe7inde ge\xe7ersiz anahtar`;case"invalid_union":default:return"Geçersiz değer";case"invalid_element":return`${i.origin} i\xe7inde ge\xe7ersiz değer`}})}},"ua",0,function(){let e,t;return{localeError:(e={string:{unit:"символів",verb:"матиме"},file:{unit:"байтів",verb:"матиме"},array:{unit:"елементів",verb:"матиме"},set:{unit:"елементів",verb:"матиме"}},t={regex:"вхідні дані",email:"адреса електронної пошти",url:"URL",emoji:"емодзі",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"дата та час ISO",date:"дата ISO",time:"час ISO",duration:"тривалість ISO",ipv4:"адреса IPv4",ipv6:"адреса IPv6",cidrv4:"діапазон IPv4",cidrv6:"діапазон IPv6",base64:"рядок у кодуванні base64",base64url:"рядок у кодуванні base64url",json_string:"рядок JSON",e164:"номер E.164",jwt:"JWT",template_literal:"вхідні дані"},i=>{switch(i.code){case"invalid_type":return`Неправильні вхідні дані: очікується ${i.expected}, отримано ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"число";case"object":if(Array.isArray(e))return"масив";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Неправильні вхідні дані: очікується ${V.stringifyPrimitive(i.values[0])}`;return`Неправильна опція: очікується одне з ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Занадто велике: очікується, що ${i.origin??"значення"} ${r.verb} ${t}${i.maximum.toString()} ${r.unit??"елементів"}`;return`Занадто велике: очікується, що ${i.origin??"значення"} буде ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Занадто мале: очікується, що ${i.origin} ${r.verb} ${t}${i.minimum.toString()} ${r.unit}`;return`Занадто мале: очікується, що ${i.origin} буде ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Неправильний рядок: повинен починатися з "${i.prefix}"`;if("ends_with"===i.format)return`Неправильний рядок: повинен закінчуватися на "${i.suffix}"`;if("includes"===i.format)return`Неправильний рядок: повинен містити "${i.includes}"`;if("regex"===i.format)return`Неправильний рядок: повинен відповідати шаблону ${i.pattern}`;return`Неправильний ${t[i.format]??i.format}`;case"not_multiple_of":return`Неправильне число: повинно бути кратним ${i.divisor}`;case"unrecognized_keys":return`Нерозпізнаний ключ${i.keys.length>1?"і":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Неправильний ключ у ${i.origin}`;case"invalid_union":default:return"Неправильні вхідні дані";case"invalid_element":return`Неправильне значення у ${i.origin}`}})}},"ur",0,function(){let e,t;return{localeError:(e={string:{unit:"حروف",verb:"ہونا"},file:{unit:"بائٹس",verb:"ہونا"},array:{unit:"آئٹمز",verb:"ہونا"},set:{unit:"آئٹمز",verb:"ہونا"}},t={regex:"ان پٹ",email:"ای میل ایڈریس",url:"یو آر ایل",emoji:"ایموجی",uuid:"یو یو آئی ڈی",uuidv4:"یو یو آئی ڈی وی 4",uuidv6:"یو یو آئی ڈی وی 6",nanoid:"نینو آئی ڈی",guid:"جی یو آئی ڈی",cuid:"سی یو آئی ڈی",cuid2:"سی یو آئی ڈی 2",ulid:"یو ایل آئی ڈی",xid:"ایکس آئی ڈی",ksuid:"کے ایس یو آئی ڈی",datetime:"آئی ایس او ڈیٹ ٹائم",date:"آئی ایس او تاریخ",time:"آئی ایس او وقت",duration:"آئی ایس او مدت",ipv4:"آئی پی وی 4 ایڈریس",ipv6:"آئی پی وی 6 ایڈریس",cidrv4:"آئی پی وی 4 رینج",cidrv6:"آئی پی وی 6 رینج",base64:"بیس 64 ان کوڈڈ سٹرنگ",base64url:"بیس 64 یو آر ایل ان کوڈڈ سٹرنگ",json_string:"جے ایس او این سٹرنگ",e164:"ای 164 نمبر",jwt:"جے ڈبلیو ٹی",template_literal:"ان پٹ"},i=>{switch(i.code){case"invalid_type":return`غلط ان پٹ: ${i.expected} متوقع تھا، ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"نمبر";case"object":if(Array.isArray(e))return"آرے";if(null===e)return"نل";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} موصول ہوا`;case"invalid_value":if(1===i.values.length)return`غلط ان پٹ: ${V.stringifyPrimitive(i.values[0])} متوقع تھا`;return`غلط آپشن: ${V.joinValues(i.values,"|")} میں سے ایک متوقع تھا`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`بہت بڑا: ${i.origin??"ویلیو"} کے ${t}${i.maximum.toString()} ${r.unit??"عناصر"} ہونے متوقع تھے`;return`بہت بڑا: ${i.origin??"ویلیو"} کا ${t}${i.maximum.toString()} ہونا متوقع تھا`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`بہت چھوٹا: ${i.origin} کے ${t}${i.minimum.toString()} ${r.unit} ہونے متوقع تھے`;return`بہت چھوٹا: ${i.origin} کا ${t}${i.minimum.toString()} ہونا متوقع تھا`}case"invalid_format":if("starts_with"===i.format)return`غلط سٹرنگ: "${i.prefix}" سے شروع ہونا چاہیے`;if("ends_with"===i.format)return`غلط سٹرنگ: "${i.suffix}" پر ختم ہونا چاہیے`;if("includes"===i.format)return`غلط سٹرنگ: "${i.includes}" شامل ہونا چاہیے`;if("regex"===i.format)return`غلط سٹرنگ: پیٹرن ${i.pattern} سے میچ ہونا چاہیے`;return`غلط ${t[i.format]??i.format}`;case"not_multiple_of":return`غلط نمبر: ${i.divisor} کا مضاعف ہونا چاہیے`;case"unrecognized_keys":return`غیر تسلیم شدہ کی${i.keys.length>1?"ز":""}: ${V.joinValues(i.keys,"، ")}`;case"invalid_key":return`${i.origin} میں غلط کی`;case"invalid_union":default:return"غلط ان پٹ";case"invalid_element":return`${i.origin} میں غلط ویلیو`}})}},"vi",0,function(){let e,t;return{localeError:(e={string:{unit:"ký tự",verb:"có"},file:{unit:"byte",verb:"có"},array:{unit:"phần tử",verb:"có"},set:{unit:"phần tử",verb:"có"}},t={regex:"đầu vào",email:"địa chỉ 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if(t.eat("?"))n={type:"opt",expr:n};else if(t.eat("{"))n=function(e,t){let n=tC(e),s=n;return e.eat(",")&&(s="}"!=e.next?tC(e):-1),e.eat("}")||e.err("Unclosed braced range"),{type:"range",min:n,max:s,expr:t}}(t,n);else break;return n}(t));while(t.next&&")"!=t.next&&"|"!=t.next)return 1==n.length?n[0]:{type:"seq",exprs:n}}(t));while(t.eat("|"))return 1==n.length?n[0]:{type:"choice",exprs:n}}(r);r.next&&r.err("Unexpected trailing text");let a=(n=function(e){let t=[[]];return r(function e(t,i){if("choice"==t.type)return t.exprs.reduce((t,n)=>t.concat(e(n,i)),[]);if("seq"==t.type)for(let s=0;;s++){let a=e(t.exprs[s],i);if(s==t.exprs.length-1)return a;r(a,i=n())}else if("star"==t.type){let a=n();return s(i,a),r(e(t.expr,a),a),[s(a)]}else if("plus"==t.type){let a=n();return r(e(t.expr,i),a),r(e(t.expr,a),a),[s(a)]}else if("opt"==t.type)return[s(i)].concat(e(t.expr,i));else if("range"==t.type){let a=i;for(let s=0;se.to=t)}}(i),s=Object.create(null),function e(t){let r=[];t.forEach(e=>{n[e].forEach(({term:e,to:t})=>{let s;if(e){for(let t=0;t{s||r.push([e,s=[]]),-1==s.indexOf(t)&&s.push(t)})}})});let i=s[t.join(",")]=new tN(t.indexOf(n.length-1)>-1);for(let t=0;te.createAndFill()));for(let e=0;e=this.next.length)throw RangeError(`There's no ${e}th edge in this content match`);return this.next[e]}toString(){let e=[];return!function t(n){e.push(n);for(let s=0;s{let s=n+(t.validEnd?"*":" ")+" ";for(let n=0;n"+e.indexOf(t.next[n].next);return s}).join("\n")}}tN.empty=new tN(!0);class tA{constructor(e,t){this.string=e,this.nodeTypes=t,this.inline=null,this.pos=0,this.tokens=e.split(/\s*(?=\b|\W|$)/),""==this.tokens[this.tokens.length-1]&&this.tokens.pop(),""==this.tokens[0]&&this.tokens.shift()}get next(){return this.tokens[this.pos]}eat(e){return this.next==e&&(this.pos++||!0)}err(e){throw SyntaxError(e+" (in content expression '"+this.string+"')")}}function tC(e){/\D/.test(e.next)&&e.err("Expected number, got '"+e.next+"'");let t=Number(e.next);return e.pos++,t}function tS(e,t){return t-e}function t_(e,t){let n=[];return function t(s){let r=e[s];if(1==r.length&&!r[0].term)return t(r[0].to);n.push(s);for(let e=0;e-1}get whitespace(){return this.spec.whitespace||(this.spec.code?"pre":"normal")}hasRequiredAttrs(){for(let e in this.attrs)if(this.attrs[e].isRequired)return!0;return!1}compatibleContent(e){return this==e||this.contentMatch.compatible(e.contentMatch)}computeAttrs(e){return!e&&this.defaultAttrs?this.defaultAttrs:tE(this.attrs,e)}create(e=null,t,n){if(this.isText)throw Error("NodeType.create can't construct text nodes");return new ty(this,this.computeAttrs(e),tt.from(t),ti.setFrom(n))}createChecked(e=null,t,n){return t=tt.from(t),this.checkContent(t),new ty(this,this.computeAttrs(e),t,ti.setFrom(n))}createAndFill(e=null,t,n){if(e=this.computeAttrs(e),(t=tt.from(t)).size){let e=this.contentMatch.fillBefore(t);if(!e)return null;t=e.append(t)}let s=this.contentMatch.matchFragment(t),r=s&&s.fillBefore(tt.empty,!0);return r?new ty(this,e,t.append(r),ti.setFrom(n)):null}validContent(e){let t=this.contentMatch.matchFragment(e);if(!t||!t.validEnd)return!1;for(let t=0;t-1}allowsMarks(e){if(null==this.markSet)return!0;for(let t=0;tn[e]=new tO(e,t,s));let s=t.spec.topNode||"doc";if(!n[s])throw RangeError("Schema is missing its top node type ('"+s+"')");if(!n.text)throw RangeError("Every schema needs a 'text' type");for(let e in n.text.attrs)throw RangeError("The text node type should not have attributes");return n}}class tR{constructor(e,t,n){this.hasDefault=Object.prototype.hasOwnProperty.call(n,"default"),this.default=n.default,this.validate="string"==typeof n.validate?function(e,t,n){let s=n.split("|");return n=>{let r=null===n?"null":typeof n;if(0>s.indexOf(r))throw RangeError(`Expected value of type ${s} for attribute ${t} on type ${e}, got ${r}`)}}(e,t,n.validate):n.validate}get isRequired(){return!this.hasDefault}}class tI{constructor(e,t,n,s){this.name=e,this.rank=t,this.schema=n,this.spec=s,this.attrs=tT(e,s.attrs),this.excluded=null;let r=tM(this.attrs);this.instance=r?new ti(this,r):null}create(e=null){return!e&&this.instance?this.instance:new ti(this,tE(this.attrs,e))}static compile(e,t){let n=Object.create(null),s=0;return e.forEach((e,r)=>n[e]=new tI(e,s++,t,r)),n}removeFromSet(e){for(var t=0;t-1}}class tz{constructor(e){this.linebreakReplacement=null,this.cached=Object.create(null);let t=this.spec={};for(let n in e)t[n]=e[n];t.nodes=e7.from(e.nodes),t.marks=e7.from(e.marks||{}),this.nodes=tO.compile(this.spec.nodes,this),this.marks=tI.compile(this.spec.marks,this);let n=Object.create(null);for(let e in this.nodes){if(e in this.marks)throw RangeError(e+" can not be both a node and a mark");let t=this.nodes[e],s=t.spec.content||"",r=t.spec.marks;if(t.contentMatch=n[s]||(n[s]=tN.parse(s,this.nodes)),t.inlineContent=t.contentMatch.inlineContent,t.spec.linebreakReplacement){if(this.linebreakReplacement)throw RangeError("Multiple linebreak nodes defined");if(!t.isInline||!t.isLeaf)throw RangeError("Linebreak replacement nodes must be inline leaf nodes");this.linebreakReplacement=t}t.markSet="_"==r?null:r?tL(this,r.split(" ")):""!=r&&t.inlineContent?null:[]}for(let e in this.marks){let t=this.marks[e],n=t.spec.excludes;t.excluded=null==n?[t]:""==n?[]:tL(this,n.split(" "))}this.nodeFromJSON=e=>ty.fromJSON(this,e),this.markFromJSON=e=>ti.fromJSON(this,e),this.topNodeType=this.nodes[this.spec.topNode||"doc"],this.cached.wrappings=Object.create(null)}node(e,t=null,n,s){if("string"==typeof e)e=this.nodeType(e);else if(e instanceof tO){if(e.schema!=this)throw RangeError("Node type from different schema used ("+e.name+")")}else throw RangeError("Invalid node type: "+e);return e.createChecked(t,n,s)}text(e,t){let n=this.nodes.text;return new tw(n,n.defaultAttrs,e,ti.setFrom(t))}mark(e,t){return"string"==typeof e&&(e=this.marks[e]),e.create(t)}nodeType(e){let t=this.nodes[e];if(!t)throw RangeError("Unknown node type: "+e);return t}}function tL(e,t){let n=[];for(let s=0;s-1)&&n.push(a=s)}if(!a)throw SyntaxError("Unknown mark type: '"+t[s]+"'")}return n}class tD{constructor(e,t){this.schema=e,this.rules=t,this.tags=[],this.styles=[];let n=this.matchedStyles=[];t.forEach(e=>{if(null!=e.tag)this.tags.push(e);else if(null!=e.style){let t=/[^=]*/.exec(e.style)[0];0>n.indexOf(t)&&n.push(t),this.styles.push(e)}}),this.normalizeLists=!this.tags.some(t=>{if(!/^(ul|ol)\b/.test(t.tag)||!t.node)return!1;let n=e.nodes[t.node];return n.contentMatch.matchType(n)})}parse(e,t={}){let n=new tV(this,t,!1);return n.addAll(e,ti.none,t.from,t.to),n.finish()}parseSlice(e,t={}){let n=new tV(this,t,!0);return n.addAll(e,ti.none,t.from,t.to),to.maxOpen(n.finish())}matchTag(e,t,n){for(let i=n?this.tags.indexOf(n)+1:0;ie.length)||61==i.charCodeAt(e.length)&&i.slice(e.length+1)==t)){if(s.getAttrs){let e=s.getAttrs(t);if(!1===e)continue;s.attrs=e||void 0}return s}}}static schemaRules(e){let t=[];function n(e){let n=null==e.priority?50:e.priority,s=0;for(;s{n(e=tU(e)),e.mark||e.ignore||e.clearMark||(e.mark=t)})}for(let t in e.nodes){let s=e.nodes[t].spec.parseDOM;s&&s.forEach(e=>{n(e=tU(e)),e.node||e.ignore||e.mark||(e.node=t)})}return t}static fromSchema(e){return e.cached.domParser||(e.cached.domParser=new tD(e,tD.schemaRules(e)))}}let tP={address:!0,article:!0,aside:!0,blockquote:!0,body:!0,canvas:!0,dd:!0,div:!0,dl:!0,fieldset:!0,figcaption:!0,figure:!0,footer:!0,form:!0,h1:!0,h2:!0,h3:!0,h4:!0,h5:!0,h6:!0,header:!0,hgroup:!0,hr:!0,li:!0,noscript:!0,ol:!0,output:!0,p:!0,pre:!0,section:!0,table:!0,tfoot:!0,ul:!0},t$={head:!0,noscript:!0,object:!0,script:!0,style:!0,title:!0},tF={ol:!0,ul:!0};function tq(e,t,n){return null!=t?!!t|2*("full"===t):e&&"pre"==e.whitespace?3:-5&n}class tB{constructor(e,t,n,s,r,i){this.type=e,this.attrs=t,this.marks=n,this.solid=s,this.options=i,this.content=[],this.activeMarks=ti.none,this.match=r||(4&i?null:e.contentMatch)}findWrapping(e){if(!this.match){if(!this.type)return[];let t=this.type.contentMatch.fillBefore(tt.from(e));if(t)this.match=this.type.contentMatch.matchFragment(t);else{let t=this.type.contentMatch,n;return(n=t.findWrapping(e.type))?(this.match=t,n):null}}return this.match.findWrapping(e.type)}finish(e){if(!(1&this.options)){let e=this.content[this.content.length-1],t;e&&e.isText&&(t=/[ \t\r\n\u000c]+$/.exec(e.text))&&(e.text.length==t[0].length?this.content.pop():this.content[this.content.length-1]=e.withText(e.text.slice(0,e.text.length-t[0].length)))}let t=tt.from(this.content);return!e&&this.match&&(t=t.append(this.match.fillBefore(tt.empty,!0))),this.type?this.type.create(this.attrs,t,this.marks):t}inlineContext(e){return this.type?this.type.inlineContent:this.content.length?this.content[0].isInline:e.parentNode&&!tP.hasOwnProperty(e.parentNode.nodeName.toLowerCase())}}class tV{constructor(e,t,n){this.parser=e,this.options=t,this.isOpen=n,this.open=0,this.localPreserveWS=!1;let s=t.topNode,r,i=tq(null,t.preserveWhitespace,0)|4*!!n;r=s?new tB(s.type,s.attrs,ti.none,!0,t.topMatch||s.type.contentMatch,i):n?new tB(null,null,ti.none,!0,null,i):new tB(e.schema.topNodeType,null,ti.none,!0,null,i),this.nodes=[r],this.find=t.findPositions,this.needsBlock=!1}get top(){return this.nodes[this.open]}addDOM(e,t){3==e.nodeType?this.addTextNode(e,t):1==e.nodeType&&this.addElement(e,t)}addTextNode(e,t){let n=e.nodeValue,s=this.top,r=2&s.options?"full":this.localPreserveWS||(1&s.options)>0,{schema:i}=this.parser;if("full"===r||s.inlineContext(e)||/[^ \t\r\n\u000c]/.test(n)){if(r)if("full"===r)n=n.replace(/\r\n?/g,"\n");else if(i.linebreakReplacement&&/[\r\n]/.test(n)&&this.top.findWrapping(i.linebreakReplacement.create())){let e=n.split(/\r?\n|\r/);for(let n=0;n!n.clearMark(e)):t.concat(this.parser.schema.marks[n.mark].create(n.attrs)),!1===n.consuming)e=n;else break}}return t}addElementByRule(e,t,n,s){let r,i;if(t.node)if((i=this.parser.schema.nodes[t.node]).isLeaf)this.insertNode(i.create(t.attrs),n,"BR"==e.nodeName)||this.leafFallback(e,n);else{let e=this.enter(i,t.attrs||null,n,t.preserveWhitespace);e&&(r=!0,n=e)}else{let e=this.parser.schema.marks[t.mark];n=n.concat(e.create(t.attrs))}let a=this.top;if(i&&i.isLeaf)this.findInside(e);else if(s)this.addElement(e,n,s);else if(t.getContent)this.findInside(e),t.getContent(e,this.parser.schema).forEach(e=>this.insertNode(e,n,!1));else{let s=e;"string"==typeof t.contentElement?s=e.querySelector(t.contentElement):"function"==typeof t.contentElement?s=t.contentElement(e):t.contentElement&&(s=t.contentElement),this.findAround(e,s,!0),this.addAll(s,n),this.findAround(e,s,!1)}r&&this.sync(a)&&this.open--}addAll(e,t,n,s){let r=n||0;for(let i=n?e.childNodes[n]:e.firstChild,a=null==s?null:e.childNodes[s];i!=a;i=i.nextSibling,++r)this.findAtPoint(e,r),this.addDOM(i,t);this.findAtPoint(e,r)}findPlace(e,t,n){let s,r;for(let t=this.open,i=0;t>=0;t--){let a=this.nodes[t],o=a.findWrapping(e);if(o&&(!s||s.length>o.length+i)&&(s=o,r=a,!o.length))break;if(a.solid){if(n)break;i+=2}}if(!s)return null;this.sync(r);for(let e=0;e(i.type?!i.type.allowsMarkType(t.type):!tH(t.type,e))||(o=t.addToSet(o),!1)),this.nodes.push(new tB(e,t,o,s,null,a)),this.open++,n}closeExtra(e=!1){let t=this.nodes.length-1;if(t>this.open){for(;t>this.open;t--)this.nodes[t-1].content.push(this.nodes[t].finish(e));this.nodes.length=this.open+1}}finish(){return this.open=0,this.closeExtra(this.isOpen),this.nodes[0].finish(!!(this.isOpen||this.options.topOpen))}sync(e){for(let t=this.open;t>=0;t--)if(this.nodes[t]==e)return this.open=t,!0;else this.localPreserveWS&&(this.nodes[t].options|=1);return!1}get currentPos(){this.closeExtra();let e=0;for(let t=this.open;t>=0;t--){let n=this.nodes[t].content;for(let t=n.length-1;t>=0;t--)e+=n[t].nodeSize;t&&e++}return e}findAtPoint(e,t){if(this.find)for(let n=0;n-1)return e.split(/\s*\|\s*/).some(this.matchesContext,this);let t=e.split("/"),n=this.options.context,s=!this.isOpen&&(!n||n.parent.type==this.nodes[0].type),r=-(n?n.depth+1:0)+ +!s,i=(e,a)=>{for(;e>=0;e--){let o=t[e];if(""==o){if(e==t.length-1||0==e)continue;for(;a>=r;a--)if(i(e-1,a))return!0;return!1}{let e=a>0||0==a&&s?this.nodes[a].type:n&&a>=r?n.node(a-r).type:null;if(!e||e.name!=o&&!e.isInGroup(o))return!1;a--}}return!0};return i(t.length-1,this.open)}textblockFromContext(){let e=this.options.context;if(e)for(let t=e.depth;t>=0;t--){let n=e.node(t).contentMatchAt(e.indexAfter(t)).defaultType;if(n&&n.isTextblock&&n.defaultAttrs)return n}for(let e in this.parser.schema.nodes){let t=this.parser.schema.nodes[e];if(t.isTextblock&&t.defaultAttrs)return t}}}function tU(e){let t={};for(let n in e)t[n]=e[n];return t}function tH(e,t){let n=t.schema.nodes;for(let s in n){let r=n[s];if(!r.allowsMarkType(e))continue;let i=[],a=e=>{i.push(e);for(let n=0;ni.indexOf(r)&&a(r))return!0}};if(a(r.contentMatch))return!0}}class tW{constructor(e,t){this.nodes=e,this.marks=t}serializeFragment(e,t={},n){n||(n=tK(t).createDocumentFragment());let s=n,r=[];return e.forEach(e=>{if(r.length||e.marks.length){let n=0,i=0;for(;n=0;s--){let r=this.serializeMark(e.marks[s],e.isInline,t);r&&((r.contentDOM||r.dom).appendChild(n),n=r.dom)}return n}serializeMark(e,t,n={}){let s=this.marks[e.type.name];return s&&tQ(tK(n),s(e,t),null,e.attrs)}static renderSpec(e,t,n=null,s){return"string"==typeof t?{dom:e.createTextNode(t)}:tQ(e,t,n,s)}static fromSchema(e){return e.cached.domSerializer||(e.cached.domSerializer=new tW(this.nodesFromSchema(e),this.marksFromSchema(e)))}static nodesFromSchema(e){let t=tG(e.nodes);return t.text||(t.text=e=>e.text),t}static marksFromSchema(e){return tG(e.marks)}}function tG(e){let t={};for(let n in e){let s=e[n].spec.toDOM;s&&(t[n]=s)}return t}function tK(e){return e.document||window.document}let tJ=new WeakMap;function tQ(e,t,n,s){let r,i,a;if(1==t.nodeType)return{dom:t};if(t.dom&&1==t.dom.nodeType)return t;let o=t[0],l;if("string"!=typeof o)throw RangeError("Invalid array passed to renderSpec");if(s&&(void 0===(i=tJ.get(s))&&tJ.set(s,(a=null,!function e(t){if(t&&"object"==typeof t)if(Array.isArray(t))if("string"==typeof t[0])a||(a=[]),a.push(t);else for(let n=0;n-1)throw RangeError("Using an array from an attribute object as a DOM spec. This may be an attempted cross site scripting attack.");let d=o.indexOf(" ");d>0&&(n=o.slice(0,d),o=o.slice(d+1));let c=n?e.createElementNS(n,o):e.createElement(o),u=t[1],h=1;if(u&&"object"==typeof u&&null==u.nodeType&&!Array.isArray(u)){for(let e in h=2,u)if(null!=u[e]){let t=e.indexOf(" ");t>0?c.setAttributeNS(e.slice(0,t),e.slice(t+1),u[e]):"style"==e&&c.style?c.style.cssText=u[e]:c.setAttribute(e,u[e])}}for(let i=h;ih)throw RangeError("Content hole must be the only child of its parent node");return{dom:c,contentDOM:c}}if("string"==typeof a)c.appendChild(e.createTextNode(a));else{let{dom:t,contentDOM:i}=tQ(e,a,n,s);if(c.appendChild(t),i){if(r)throw RangeError("Multiple content holes");r=i}}}return{dom:c,contentDOM:r}}class tY{constructor(e,t,n){this.pos=e,this.delInfo=t,this.recover=n}get deleted(){return(8&this.delInfo)>0}get deletedBefore(){return(5&this.delInfo)>0}get deletedAfter(){return(6&this.delInfo)>0}get deletedAcross(){return(4&this.delInfo)>0}}class tX{constructor(e,t=!1){if(this.ranges=e,this.inverted=t,!e.length&&tX.empty)return tX.empty}recover(e){let t=0,n=65535&e;if(!this.inverted)for(let e=0;ee)break;let l=this.ranges[a+r],d=this.ranges[a+i],c=o+l;if(e<=c){let r=l?e==o?-1:e==c?1:t:t,i=o+s+(r<0?0:d);if(n)return i;let u=e==(t<0?o:c)?null:a/3+(e-o)*65536,h=0;return l&&(h|=e==o?2:e==c?1:4,(t<0?e!=o:e!=c)&&(h|=8)),new tY(i,h,u)}s+=d-l}return n?e+s:new tY(e+s,0,null)}touches(e,t){let n=0,s=65535&t,r=this.inverted?2:1,i=this.inverted?1:2;for(let t=0;te)break;let o=this.ranges[t+r];if(e<=a+o&&t==3*s)return!0;n+=this.ranges[t+i]-o}return!1}forEach(e){let t=this.inverted?2:1,n=this.inverted?1:2;for(let s=0,r=0;s=0;t--){let s=e.getMirror(t);this.appendMap(e._maps[t].invert(),null!=s&&s>t?n-s-1:void 0)}}invert(){let e=new tZ;return e.appendMappingInverted(this),e}map(e,t=1){if(this.mirror)return this._map(e,t,!0);for(let n=this.from;nn&&te.isAtom&&t.type.allowsMarkType(this.mark.type)?e.mark(this.mark.addToSet(e.marks)):e,s),t.openStart,t.openEnd);return t2.fromReplace(e,this.from,this.to,r)}invert(){return new t4(this.from,this.to,this.mark)}map(e){let t=e.mapResult(this.from,1),n=e.mapResult(this.to,-1);return t.deleted&&n.deleted||t.pos>=n.pos?null:new t3(t.pos,n.pos,this.mark)}merge(e){return e instanceof t3&&e.mark.eq(this.mark)&&this.from<=e.to&&this.to>=e.from?new t3(Math.min(this.from,e.from),Math.max(this.to,e.to),this.mark):null}toJSON(){return{stepType:"addMark",mark:this.mark.toJSON(),from:this.from,to:this.to}}static fromJSON(e,t){if("number"!=typeof t.from||"number"!=typeof t.to)throw RangeError("Invalid input for AddMarkStep.fromJSON");return new t3(t.from,t.to,e.markFromJSON(t.mark))}}t1.jsonID("addMark",t3);class t4 extends t1{constructor(e,t,n){super(),this.from=e,this.to=t,this.mark=n}apply(e){let t=e.slice(this.from,this.to),n=new to(t5(t.content,e=>e.mark(this.mark.removeFromSet(e.marks)),e),t.openStart,t.openEnd);return t2.fromReplace(e,this.from,this.to,n)}invert(){return new t3(this.from,this.to,this.mark)}map(e){let t=e.mapResult(this.from,1),n=e.mapResult(this.to,-1);return t.deleted&&n.deleted||t.pos>=n.pos?null:new t4(t.pos,n.pos,this.mark)}merge(e){return e instanceof t4&&e.mark.eq(this.mark)&&this.from<=e.to&&this.to>=e.from?new t4(Math.min(this.from,e.from),Math.max(this.to,e.to),this.mark):null}toJSON(){return{stepType:"removeMark",mark:this.mark.toJSON(),from:this.from,to:this.to}}static fromJSON(e,t){if("number"!=typeof t.from||"number"!=typeof t.to)throw RangeError("Invalid input for RemoveMarkStep.fromJSON");return new t4(t.from,t.to,e.markFromJSON(t.mark))}}t1.jsonID("removeMark",t4);class t6 extends t1{constructor(e,t){super(),this.pos=e,this.mark=t}apply(e){let t=e.nodeAt(this.pos);if(!t)return t2.fail("No node at mark step's position");let n=t.type.create(t.attrs,null,this.mark.addToSet(t.marks));return t2.fromReplace(e,this.pos,this.pos+1,new to(tt.from(n),0,+!t.isLeaf))}invert(e){let t=e.nodeAt(this.pos);if(t){let e=this.mark.addToSet(t.marks);if(e.length==t.marks.length){for(let n=0;nn.pos?null:new t9(t.pos,n.pos,s,r,this.slice,this.insert,this.structure)}toJSON(){let e={stepType:"replaceAround",from:this.from,to:this.to,gapFrom:this.gapFrom,gapTo:this.gapTo,insert:this.insert};return this.slice.size&&(e.slice=this.slice.toJSON()),this.structure&&(e.structure=!0),e}static fromJSON(e,t){if("number"!=typeof t.from||"number"!=typeof t.to||"number"!=typeof t.gapFrom||"number"!=typeof t.gapTo||"number"!=typeof t.insert)throw RangeError("Invalid input for ReplaceAroundStep.fromJSON");return new t9(t.from,t.to,t.gapFrom,t.gapTo,to.fromJSON(e,t.slice),t.insert,!!t.structure)}}function ne(e,t,n){let s=e.resolve(t),r=n-t,i=s.depth;for(;r>0&&i>0&&s.indexAfter(i)==s.node(i).childCount;)i--,r--;if(r>0){let e=s.node(i).maybeChild(s.indexAfter(i));for(;r>0;){if(!e||e.isLeaf)return!0;e=e.firstChild,r--}}return!1}function nt(e,t,n,s=n.contentMatch,r=!0){let i=e.doc.nodeAt(t),a=[],o=t+1;for(let t=0;t=0;t--)e.step(a[t])}function nn(e,t,n,s){t.forEach((r,i)=>{if(r.isText){let a,o=/\r?\n|\r/g;for(;a=o.exec(r.text);){let r=e.mapping.slice(s).map(n+1+i+a.index);e.replaceWith(r,r+1,t.type.schema.linebreakReplacement.create())}}})}function ns(e,t,n,s){t.forEach((r,i)=>{if(r.type==r.type.schema.linebreakReplacement){let r=e.mapping.slice(s).map(n+1+i);e.replaceWith(r,r+1,t.type.schema.text("\n"))}})}function nr(e,t,n){return!n.openStart&&!n.openEnd&&e.start()==t.start()&&e.parent.canReplace(e.index(),t.index(),n.content)}t1.jsonID("replaceAround",t9);class ni{constructor(e,t,n){this.$from=e,this.$to=t,this.unplaced=n,this.frontier=[],this.placed=tt.empty;for(let t=0;t<=e.depth;t++){let n=e.node(t);this.frontier.push({type:n.type,match:n.contentMatchAt(e.indexAfter(t))})}for(let t=e.depth;t>0;t--)this.placed=tt.from(e.node(t).copy(this.placed))}get depth(){return this.frontier.length-1}fit(){for(;this.unplaced.size;){let e=this.findFittable();e?this.placeNodes(e):this.openMore()||this.dropNode()}let e=this.mustMoveInline(),t=this.placed.size-this.depth-this.$from.depth,n=this.$from,s=this.close(e<0?this.$to:n.doc.resolve(e));if(!s)return null;let r=this.placed,i=n.depth,a=s.depth;for(;i&&a&&1==r.childCount;)r=r.firstChild.content,i--,a--;let o=new to(r,i,a);return e>-1?new t9(n.pos,e,this.$to.pos,this.$to.end(),o,t):o.size||n.pos!=this.$to.pos?new t7(n.pos,s.pos,o):null}findFittable(){let e=this.unplaced.openStart;for(let t=this.unplaced.content,n=0,s=this.unplaced.openEnd;n1&&(s=0),r.type.spec.isolating&&s<=n){e=n;break}t=r.content}for(let t=1;t<=2;t++)for(let n=1==t?e:this.unplaced.openStart;n>=0;n--){let e=null,s=(n?(e=nl(this.unplaced.content,n-1).firstChild).content:this.unplaced.content).firstChild;for(let r=this.depth;r>=0;r--){let{type:i,match:a}=this.frontier[r],o,l=null;if(1==t&&(s?a.matchType(s.type)||(l=a.fillBefore(tt.from(s),!1)):e&&i.compatibleContent(e.type)))return{sliceDepth:n,frontierDepth:r,parent:e,inject:l};if(2==t&&s&&(o=a.findWrapping(s.type)))return{sliceDepth:n,frontierDepth:r,parent:e,wrap:o};if(e&&a.matchType(e.type))break}}}openMore(){let{content:e,openStart:t,openEnd:n}=this.unplaced;return!(nc(e,-1)<=t)&&(this.unplaced.size>1&&nc(e,1)>n&&n++,this.unplaced=new to(e,t+1,n),!0)}dropNode(){let{content:e,openStart:t,openEnd:n}=this.unplaced,s=nl(e,t);if(s.childCount<=1&&t>0){let r=e.size-t<=t+s.size;this.unplaced=new to(na(e,t-1,1),t-1,r?t-1:n)}else this.unplaced=new to(na(e,t,1),t,n)}placeNodes({sliceDepth:e,frontierDepth:t,parent:n,inject:s,wrap:r}){for(;this.depth>t;)this.closeFrontierNode();if(r)for(let e=0;e1||0==o||e.content.size)&&(c=t,d.push(function e(t,n,s){if(n<=0)return t;let r=t.content;return n>1&&(r=r.replaceChild(0,e(r.firstChild,n-1,1==r.childCount?s-1:0))),n>0&&(r=t.type.contentMatch.fillBefore(r).append(r),s<=0&&(r=r.append(t.type.contentMatch.matchFragment(r).fillBefore(tt.empty,!0)))),t.copy(r)}(e.mark(u.allowedMarks(e.marks)),1==l?o:0,l==a.childCount?h:-1)))}let m=l==a.childCount;m||(h=-1),this.placed=no(this.placed,t,tt.from(d)),this.frontier[t].match=c,m&&h<0&&n&&n.type==this.frontier[this.depth].type&&this.frontier.length>1&&this.closeFrontierNode();for(let e=0,t=a;e1&&s==this.$to.end(--n);)++s;return s}findCloseLevel(e){t:for(let t=Math.min(this.depth,e.depth);t>=0;t--){let{match:n,type:s}=this.frontier[t],r=t=0;n--){let{match:t,type:s}=this.frontier[n],r=nd(e,n,s,t,!0);if(!r||r.childCount)continue t}return{depth:t,fit:i,move:r?e.doc.resolve(e.after(t+1)):e}}}}close(e){let t=this.findCloseLevel(e);if(!t)return null;for(;this.depth>t.depth;)this.closeFrontierNode();t.fit.childCount&&(this.placed=no(this.placed,t.depth,t.fit)),e=t.move;for(let n=t.depth+1;n<=e.depth;n++){let t=e.node(n),s=t.type.contentMatch.fillBefore(t.content,!0,e.index(n));this.openFrontierNode(t.type,t.attrs,s)}return e}openFrontierNode(e,t=null,n){let s=this.frontier[this.depth];s.match=s.match.matchType(e),this.placed=no(this.placed,this.depth,tt.from(e.create(t,n))),this.frontier.push({type:e,match:e.contentMatch})}closeFrontierNode(){let e=this.frontier.pop().match.fillBefore(tt.empty,!0);e.childCount&&(this.placed=no(this.placed,this.frontier.length,e))}}function na(e,t,n){return 0==t?e.cutByIndex(n,e.childCount):e.replaceChild(0,e.firstChild.copy(na(e.firstChild.content,t-1,n)))}function no(e,t,n){return 0==t?e.append(n):e.replaceChild(e.childCount-1,e.lastChild.copy(no(e.lastChild.content,t-1,n)))}function nl(e,t){for(let n=0;n=0;r--){let s=e.start(r);if(st.pos+(t.depth-r)||e.node(r).type.spec.isolating||t.node(r).type.spec.isolating)break;(s==t.start(r)||r==e.depth&&r==t.depth&&e.parent.inlineContent&&t.parent.inlineContent&&r&&t.start(r-1)==s-1)&&n.push(r)}return n}class nh extends t1{constructor(e,t,n){super(),this.pos=e,this.attr=t,this.value=n}apply(e){let t=e.nodeAt(this.pos);if(!t)return t2.fail("No node at attribute step's position");let n=Object.create(null);for(let e in t.attrs)n[e]=t.attrs[e];n[this.attr]=this.value;let s=t.type.create(n,null,t.marks);return t2.fromReplace(e,this.pos,this.pos+1,new to(tt.from(s),0,+!t.isLeaf))}getMap(){return tX.empty}invert(e){return new nh(this.pos,this.attr,e.nodeAt(this.pos).attrs[this.attr])}map(e){let t=e.mapResult(this.pos,1);return t.deletedAfter?null:new nh(t.pos,this.attr,this.value)}toJSON(){return{stepType:"attr",pos:this.pos,attr:this.attr,value:this.value}}static fromJSON(e,t){if("number"!=typeof t.pos||"string"!=typeof t.attr)throw RangeError("Invalid input for AttrStep.fromJSON");return new nh(t.pos,t.attr,t.value)}}t1.jsonID("attr",nh);class nm extends t1{constructor(e,t){super(),this.attr=e,this.value=t}apply(e){let t=Object.create(null);for(let n in e.attrs)t[n]=e.attrs[n];t[this.attr]=this.value;let n=e.type.create(t,e.content,e.marks);return t2.ok(n)}getMap(){return tX.empty}invert(e){return new nm(this.attr,e.attrs[this.attr])}map(e){return this}toJSON(){return{stepType:"docAttr",attr:this.attr,value:this.value}}static fromJSON(e,t){if("string"!=typeof t.attr)throw RangeError("Invalid input for DocAttrStep.fromJSON");return new nm(t.attr,t.value)}}t1.jsonID("docAttr",nm);let np=class extends Error{};(np=function e(t){let n=Error.call(this,t);return n.__proto__=e.prototype,n}).prototype=Object.create(Error.prototype),np.prototype.constructor=np,np.prototype.name="TransformError";class nf{constructor(e){this.doc=e,this.steps=[],this.docs=[],this.mapping=new tZ}get before(){return this.docs.length?this.docs[0]:this.doc}step(e){let t=this.maybeStep(e);if(t.failed)throw new np(t.failed);return this}maybeStep(e){let t=e.apply(this.doc);return t.failed||this.addStep(e,t.doc),t}get docChanged(){return this.steps.length>0}changedRange(){let e=1e9,t=-1e9;for(let n=0;n{e=Math.min(e,r),t=Math.max(t,i)})}return 1e9==e?null:{from:e,to:t}}addStep(e,t){this.docs.push(this.doc),this.steps.push(e),this.mapping.appendMap(e.getMap()),this.doc=t}replace(e,t=e,n=to.empty){let s=function(e,t,n=t,s=to.empty){if(t==n&&!s.size)return null;let r=e.resolve(t),i=e.resolve(n);return nr(r,i,s)?new t7(t,n,s):new ni(r,i,s).fit()}(this.doc,e,t,n);return s&&this.step(s),this}replaceWith(e,t,n){return this.replace(e,t,new to(tt.from(n),0,0))}delete(e,t){return this.replace(e,t,to.empty)}insert(e,t){return this.replaceWith(e,e,t)}replaceRange(e,t,n){return!function(e,t,n,s){if(!s.size)return e.deleteRange(t,n);let r=e.doc.resolve(t),i=e.doc.resolve(n);if(nr(r,i,s))return e.step(new t7(t,n,s));let a=nu(r,i);0==a[a.length-1]&&a.pop();let o=-(r.depth+1);a.unshift(o);for(let e=r.depth,t=r.pos-1;e>0;e--,t--){let n=r.node(e).type.spec;if(n.defining||n.definingAsContext||n.isolating)break;a.indexOf(e)>-1?o=e:r.before(e)==t&&a.splice(1,0,-e)}let l=a.indexOf(o),d=[],c=s.openStart;for(let e=s.content,t=0;;t++){let n=e.firstChild;if(d.push(n),t==s.openStart)break;e=n.content}for(let e=c-1;e>=0;e--){var u;let t=d[e],n=(u=t.type).spec.defining||u.spec.definingForContent;if(n&&!t.sameMarkup(r.node(Math.abs(o)-1)))c=e;else if(n||!t.type.isTextblock)break}for(let t=s.openStart;t>=0;t--){let o=(t+c+1)%(s.openStart+1),u=d[o];if(u)for(let t=0;tr){let e=i.contentMatchAt(0),n=e.fillBefore(t).append(t);t=n.append(e.matchFragment(n).fillBefore(tt.empty,!0))}return t}(s.content,0,s.openStart,o),o,s.openEnd))}}let h=e.steps.length;for(let o=a.length-1;o>=0&&(e.replace(t,n,s),!(e.steps.length>h));o--){let e=a[o];e<0||(t=r.before(e),n=i.after(e))}}(this,e,t,n),this}replaceRangeWith(e,t,n){var s=e,r=t;if(!n.isInline&&s==r&&this.doc.resolve(s).parent.content.size){let e=function(e,t,n){let s=e.resolve(t);if(s.parent.canReplaceWith(s.index(),s.index(),n))return t;if(0==s.parentOffset)for(let e=s.depth-1;e>=0;e--){let t=s.index(e);if(s.node(e).canReplaceWith(t,t,n))return s.before(e+1);if(t>0)return null}if(s.parentOffset==s.parent.content.size)for(let e=s.depth-1;e>=0;e--){let t=s.indexAfter(e);if(s.node(e).canReplaceWith(t,t,n))return s.after(e+1);if(ti;e--)s.node(e).type.spec.isolating&&(a=!0);for(let e=r.depth;e>i;e--)r.node(e).type.spec.isolating&&(a=!0);if(!a){for(let e=s.depth;e>0&&t==s.start(e);e--)t=s.before(e);for(let e=r.depth;e>0&&n==r.start(e);e--)n=r.before(e);s=e.doc.resolve(t),r=e.doc.resolve(n)}}let i=nu(s,r);for(let t=0;t0&&(a||s.node(n-1).canReplace(s.index(n-1),r.indexAfter(n-1))))return e.delete(s.before(n),r.after(n))}for(let i=1;i<=s.depth&&i<=r.depth;i++)if(t-s.start(i)==s.depth-i&&n>s.end(i)&&r.end(i)-n!=r.depth-i&&s.start(i-1)==r.start(i-1)&&s.node(i-1).canReplace(s.index(i-1),r.index(i-1)))return e.delete(s.before(i),n);e.delete(t,n)}(this,e,t),this}lift(e,t){return!function(e,t,n){let{$from:s,$to:r,depth:i}=t,a=s.before(i+1),o=r.after(i+1),l=a,d=o,c=tt.empty,u=0;for(let e=i,t=!1;e>n;e--)t||s.index(e)>0?(t=!0,c=tt.from(s.node(e).copy(c)),u++):l--;let h=tt.empty,m=0;for(let e=i,t=!1;e>n;e--)t||r.after(e+1)=0;e--){if(s.size){let t=n[e].type.contentMatch.matchFragment(s);if(!t||!t.validEnd)throw RangeError("Wrapper type given to Transform.wrap does not form valid content of its parent wrapper")}s=tt.from(n[e].type.create(n[e].attrs,s))}let r=t.start,i=t.end;e.step(new t9(r,i,r,i,new to(s,0,0),n.length,!0))}(this,e,t),this}setBlockType(e,t=e,n,s=null){var r=this;if(!n.isTextblock)throw RangeError("Type given to setBlockType should be a textblock");let i=r.steps.length;return r.doc.nodesBetween(e,t,(e,t)=>{var a,o,l;let d,c,u="function"==typeof s?s(e):s;if(e.isTextblock&&!e.hasMarkup(n,u)&&(a=r.doc,o=r.mapping.slice(i).map(t),l=n,c=(d=a.resolve(o)).index(),d.parent.canReplaceWith(c,c+1,l))){let s=null;if(n.schema.linebreakReplacement){let e="pre"==n.whitespace,t=!!n.contentMatch.matchType(n.schema.linebreakReplacement);e&&!t?s=!1:!e&&t&&(s=!0)}!1===s&&ns(r,e,t,i),nt(r,r.mapping.slice(i).map(t,1),n,void 0,null===s);let a=r.mapping.slice(i),o=a.map(t,1),l=a.map(t+e.nodeSize,1);return r.step(new t9(o,l,o+1,l-1,new to(tt.from(n.create(u,null,e.marks)),0,0),1,!0)),!0===s&&nn(r,e,t,i),!1}}),this}setNodeMarkup(e,t,n=null,s){return!function(e,t,n,s,r){let i=e.doc.nodeAt(t);if(!i)throw RangeError("No node at given position");n||(n=i.type);let a=n.create(s,null,r||i.marks);if(i.isLeaf)return e.replaceWith(t,t+i.nodeSize,a);if(!n.validContent(i.content))throw RangeError("Invalid content for node type "+n.name);e.step(new t9(t,t+i.nodeSize,t+1,t+i.nodeSize-1,new to(tt.from(a),0,0),1,!0))}(this,e,t,n,s),this}setNodeAttribute(e,t,n){return this.step(new nh(e,t,n)),this}setDocAttribute(e,t){return this.step(new nm(e,t)),this}addNodeMark(e,t){return this.step(new t6(e,t)),this}removeNodeMark(e,t){let n=this.doc.nodeAt(e);if(!n)throw RangeError("No node at position "+e);if(t instanceof ti)t.isInSet(n.marks)&&this.step(new t8(e,t));else{let s=n.marks,r,i=[];for(;r=t.isInSet(s);)i.push(new t8(e,r)),s=r.removeFromSet(s);for(let e=i.length-1;e>=0;e--)this.step(i[e])}return this}split(e,t=1,n){return!function(e,t,n=1,s){let r=e.doc.resolve(t),i=tt.empty,a=tt.empty;for(let e=r.depth,t=r.depth-n,o=n-1;e>t;e--,o--){i=tt.from(r.node(e).copy(i));let t=s&&s[o];a=tt.from(t?t.type.create(t.attrs,a):r.node(e).copy(a))}e.step(new t7(t,t,new to(i.append(a),n,n),!0))}(this,e,t,n),this}addMark(e,t,n){var s;let r,i,a,o;return s=this,a=[],o=[],s.doc.nodesBetween(e,t,(s,l,d)=>{if(!s.isInline)return;let c=s.marks;if(!n.isInSet(c)&&d.type.allowsMarkType(n.type)){let d=Math.max(l,e),u=Math.min(l+s.nodeSize,t),h=n.addToSet(c);for(let e=0;es.step(e)),o.forEach(e=>s.step(e)),this}removeMark(e,t,n){var s;let r,i;return s=this,r=[],i=0,s.doc.nodesBetween(e,t,(s,a)=>{if(!s.isInline)return;i++;let o=null;if(n instanceof tI){let e=s.marks,t;for(;t=n.isInSet(e);)(o||(o=[])).push(t),e=t.removeFromSet(e)}else n?n.isInSet(s.marks)&&(o=[n]):o=s.marks;if(o&&o.length){let n=Math.min(a+s.nodeSize,t);for(let t=0;ts.step(new t4(e.from,e.to,e.style))),this}clearIncompatible(e,t,n){return nt(this,e,t,n),this}}let ng=Object.create(null);class nx{constructor(e,t,n){this.$anchor=e,this.$head=t,this.ranges=n||[new nb(e.min(t),e.max(t))]}get anchor(){return this.$anchor.pos}get head(){return this.$head.pos}get from(){return this.$from.pos}get to(){return this.$to.pos}get $from(){return this.ranges[0].$from}get $to(){return this.ranges[0].$to}get empty(){let e=this.ranges;for(let t=0;t=0;s--){let r=t<0?nS(e.node(0),e.node(s),e.before(s+1),e.index(s),t,n):nS(e.node(0),e.node(s),e.after(s+1),e.index(s)+1,t,n);if(r)return r}return null}static near(e,t=1){return this.findFrom(e,t)||this.findFrom(e,-t)||new nA(e.node(0))}static atStart(e){return nS(e,e,0,0,1)||new nA(e)}static atEnd(e){return nS(e,e,e.content.size,e.childCount,-1)||new nA(e)}static fromJSON(e,t){if(!t||!t.type)throw RangeError("Invalid input for Selection.fromJSON");let n=ng[t.type];if(!n)throw RangeError(`No selection type ${t.type} defined`);return n.fromJSON(e,t)}static jsonID(e,t){if(e in ng)throw RangeError("Duplicate use of selection JSON ID "+e);return ng[e]=t,t.prototype.jsonID=e,t}getBookmark(){return nw.between(this.$anchor,this.$head).getBookmark()}}nx.prototype.visible=!0;class nb{constructor(e,t){this.$from=e,this.$to=t}}let nv=!1;function ny(e){nv||e.parent.inlineContent||(nv=!0,console.warn("TextSelection endpoint not pointing into a node with inline content ("+e.parent.type.name+")"))}class nw extends nx{constructor(e,t=e){ny(e),ny(t),super(e,t)}get $cursor(){return this.$anchor.pos==this.$head.pos?this.$head:null}map(e,t){let n=e.resolve(t.map(this.head));if(!n.parent.inlineContent)return nx.near(n);let s=e.resolve(t.map(this.anchor));return new nw(s.parent.inlineContent?s:n,n)}replace(e,t=to.empty){if(super.replace(e,t),t==to.empty){let t=this.$from.marksAcross(this.$to);t&&e.ensureMarks(t)}}eq(e){return e instanceof nw&&e.anchor==this.anchor&&e.head==this.head}getBookmark(){return new nj(this.anchor,this.head)}toJSON(){return{type:"text",anchor:this.anchor,head:this.head}}static fromJSON(e,t){if("number"!=typeof t.anchor||"number"!=typeof t.head)throw RangeError("Invalid input for TextSelection.fromJSON");return new nw(e.resolve(t.anchor),e.resolve(t.head))}static create(e,t,n=t){let s=e.resolve(t);return new this(s,n==t?s:e.resolve(n))}static between(e,t,n){let s=e.pos-t.pos;if((!n||s)&&(n=s>=0?1:-1),!t.parent.inlineContent){let e=nx.findFrom(t,n,!0)||nx.findFrom(t,-n,!0);if(!e)return nx.near(t,n);t=e.$head}return e.parent.inlineContent||(0==s?e=t:(e=(nx.findFrom(e,-n,!0)||nx.findFrom(e,n,!0)).$anchor).posnew nA(e)};function nS(e,t,n,s,r,i=!1){if(t.inlineContent)return nw.create(e,n);for(let a=s-(r>0?0:1);r>0?a=0;a+=r){let s=t.child(a);if(s.isAtom){if(!i&&nk.isSelectable(s))return nk.create(e,n-(r<0?s.nodeSize:0))}else{let t=nS(e,s,n+r,r<0?s.childCount:0,r,i);if(t)return t}n+=s.nodeSize*r}return null}function n_(e,t,n){let s,r=e.steps.length-1;if(r{null==s&&(s=r)}),e.setSelection(nx.near(e.doc.resolve(s),n)))}class nM extends nf{constructor(e){super(e.doc),this.curSelectionFor=0,this.updated=0,this.meta=Object.create(null),this.time=Date.now(),this.curSelection=e.selection,this.storedMarks=e.storedMarks}get selection(){return this.curSelectionFor0}setStoredMarks(e){return this.storedMarks=e,this.updated|=2,this}ensureMarks(e){return ti.sameSet(this.storedMarks||this.selection.$from.marks(),e)||this.setStoredMarks(e),this}addStoredMark(e){return this.ensureMarks(e.addToSet(this.storedMarks||this.selection.$head.marks()))}removeStoredMark(e){return this.ensureMarks(e.removeFromSet(this.storedMarks||this.selection.$head.marks()))}get storedMarksSet(){return(2&this.updated)>0}addStep(e,t){super.addStep(e,t),this.updated=-3&this.updated,this.storedMarks=null}setTime(e){return this.time=e,this}replaceSelection(e){return this.selection.replace(this,e),this}replaceSelectionWith(e,t=!0){let n=this.selection;return t&&(e=e.mark(this.storedMarks||(n.empty?n.$from.marks():n.$from.marksAcross(n.$to)||ti.none))),n.replaceWith(this,e),this}deleteSelection(){return this.selection.replace(this),this}insertText(e,t,n){let s=this.doc.type.schema;if(null==t)return e?this.replaceSelectionWith(s.text(e),!0):this.deleteSelection();{if(null==n&&(n=t),!e)return this.deleteRange(t,n);let r=this.storedMarks;if(!r){let e=this.doc.resolve(t);r=n==t?e.marks():e.marksAcross(this.doc.resolve(n))}return this.replaceRangeWith(t,n,s.text(e,r)),this.selection.empty||this.selection.to!=t+e.length||this.setSelection(nx.near(this.selection.$to)),this}}setMeta(e,t){return this.meta["string"==typeof e?e:e.key]=t,this}getMeta(e){return this.meta["string"==typeof e?e:e.key]}get isGeneric(){for(let e in this.meta)return!1;return!0}scrollIntoView(){return this.updated|=4,this}get scrolledIntoView(){return(4&this.updated)>0}}function nE(e,t){return t&&e?e.bind(t):e}class nT{constructor(e,t,n){this.name=e,this.init=nE(t.init,n),this.apply=nE(t.apply,n)}}let nO=[new nT("doc",{init:e=>e.doc||e.schema.topNodeType.createAndFill(),apply:e=>e.doc}),new nT("selection",{init:(e,t)=>e.selection||nx.atStart(t.doc),apply:e=>e.selection}),new nT("storedMarks",{init:e=>e.storedMarks||null,apply:(e,t,n,s)=>s.selection.$cursor?e.storedMarks:null}),new nT("scrollToSelection",{init:()=>0,apply:(e,t)=>e.scrolledIntoView?t+1:t})];class nR{constructor(e,t){this.schema=e,this.plugins=[],this.pluginsByKey=Object.create(null),this.fields=nO.slice(),t&&t.forEach(e=>{if(this.pluginsByKey[e.key])throw RangeError("Adding different instances of a keyed plugin ("+e.key+")");this.plugins.push(e),this.pluginsByKey[e.key]=e,e.spec.state&&this.fields.push(new nT(e.key,e.spec.state,e))})}}class nI{constructor(e){this.config=e}get schema(){return this.config.schema}get plugins(){return this.config.plugins}apply(e){return this.applyTransaction(e).state}filterTransaction(e,t=-1){for(let n=0;ne.toJSON())),e&&"object"==typeof e)for(let n in e){if("doc"==n||"selection"==n)throw RangeError("The JSON fields `doc` and `selection` are reserved");let s=e[n],r=s.spec.state;r&&r.toJSON&&(t[n]=r.toJSON.call(s,this[s.key]))}return t}static fromJSON(e,t,n){if(!t)throw RangeError("Invalid input for EditorState.fromJSON");if(!e.schema)throw RangeError("Required config field 'schema' missing");let s=new nR(e.schema,e.plugins),r=new nI(s);return s.fields.forEach(s=>{if("doc"==s.name)r.doc=ty.fromJSON(e.schema,t.doc);else if("selection"==s.name)r.selection=nx.fromJSON(r.doc,t.selection);else if("storedMarks"==s.name)t.storedMarks&&(r.storedMarks=t.storedMarks.map(e.schema.markFromJSON));else{if(n)for(let i in n){let a=n[i],o=a.spec.state;if(a.key==s.name&&o&&o.fromJSON&&Object.prototype.hasOwnProperty.call(t,i)){r[s.name]=o.fromJSON.call(a,e,t[i],r);return}}r[s.name]=s.init(e,r)}}),r}}class nz{constructor(e){this.spec=e,this.props={},e.props&&function e(t,n,s){for(let r in t){let i=t[r];i instanceof Function?i=i.bind(n):"handleDOMEvents"==r&&(i=e(i,n,{})),s[r]=i}return s}(e.props,this,this.props),this.key=e.key?e.key.key:nD("plugin")}getState(e){return e[this.key]}}let nL=Object.create(null);function nD(e){return e in nL?e+"$"+ ++nL[e]:(nL[e]=0,e+"$")}let nP=function(e){for(var t=0;;t++)if(!(e=e.previousSibling))return t},n$=function(e){let t=e.assignedSlot||e.parentNode;return t&&11==t.nodeType?t.host:t},nF=null,nq=function(e,t,n){let s=nF||(nF=document.createRange());return s.setEnd(e,null==n?e.nodeValue.length:n),s.setStart(e,t||0),s},nB=function(){nF=null},nV=function(e,t,n,s){return n&&(nH(e,t,n,s,-1)||nH(e,t,n,s,1))},nU=/^(img|br|input|textarea|hr)$/i;function nH(e,t,n,s,r){for(var i;;){if(e==n&&t==s)return!0;if(t==(r<0?0:nW(e))){let n=e.parentNode;if(!n||1!=n.nodeType||nG(e)||nU.test(e.nodeName)||"false"==e.contentEditable)return!1;t=nP(e)+(r<0?0:1),e=n}else{if(1!=e.nodeType)return!1;let n=e.childNodes[t+(r<0?-1:0)];if(1==n.nodeType&&"false"==n.contentEditable)if(null==(i=n.pmViewDesc)||!i.ignoreForSelection)return!1;else t+=r;else e=n,t=r<0?nW(e):0}}}function nW(e){return 3==e.nodeType?e.nodeValue.length:e.childNodes.length}function nG(e){let t;for(let n=e;n&&!(t=n.pmViewDesc);n=n.parentNode);return t&&t.node&&t.node.isBlock&&(t.dom==e||t.contentDOM==e)}let nK=function(e){return e.focusNode&&nV(e.focusNode,e.focusOffset,e.anchorNode,e.anchorOffset)};function nJ(e,t){let n=document.createEvent("Event");return n.initEvent("keydown",!0,!0),n.keyCode=e,n.key=n.code=t,n}let nQ="u">typeof navigator?navigator:null,nY="u">typeof document?document:null,nX=nQ&&nQ.userAgent||"",nZ=/Edge\/(\d+)/.exec(nX),n0=/MSIE \d/.exec(nX),n1=/Trident\/(?:[7-9]|\d{2,})\..*rv:(\d+)/.exec(nX),n2=!!(n0||n1||nZ),n5=n0?document.documentMode:n1?+n1[1]:nZ?+nZ[1]:0,n3=!n2&&/gecko\/(\d+)/i.test(nX);n3&&(/Firefox\/(\d+)/.exec(nX)||[0,0])[1];let n4=!n2&&/Chrome\/(\d+)/.exec(nX),n6=!!n4,n8=n4?+n4[1]:0,n7=!n2&&!!nQ&&/Apple Computer/.test(nQ.vendor),n9=n7&&(/Mobile\/\w+/.test(nX)||!!nQ&&nQ.maxTouchPoints>2),se=n9||!!nQ&&/Mac/.test(nQ.platform),st=!!nQ&&/Win/.test(nQ.platform),sn=/Android \d/.test(nX),ss=!!nY&&"webkitFontSmoothing"in nY.documentElement.style,sr=ss?+(/\bAppleWebKit\/(\d+)/.exec(navigator.userAgent)||[0,0])[1]:0;function si(e,t){return"number"==typeof e?e:e[t]}function sa(e,t,n){if(!su(t)&&0==t.left)return;let s=e.someProp("scrollThreshold")||0,r=e.someProp("scrollMargin")||5,i=e.dom.ownerDocument;for(let a=n||e.dom;a;){if(1!=a.nodeType){a=n$(a);continue}let e=a,n=e==i.body,o=n?function(e){let t=e.defaultView&&e.defaultView.visualViewport;return t?{left:0,right:t.width,top:0,bottom:t.height}:{left:0,right:e.documentElement.clientWidth,top:0,bottom:e.documentElement.clientHeight}}(i):function(e){let t=e.getBoundingClientRect(),n=t.width/e.offsetWidth||1,s=t.height/e.offsetHeight||1;return{left:t.left,right:t.left+e.clientWidth*n,top:t.top,bottom:t.top+e.clientHeight*s}}(e),l=0,d=0;if(t.topo.bottom-si(s,"bottom")&&(d=t.bottom-t.top>o.bottom-o.top?t.top+si(r,"top")-o.top:t.bottom-o.bottom+si(r,"bottom")),t.lefto.right-si(s,"right")&&(l=t.right-o.right+si(r,"right")),l||d)if(n)i.defaultView.scrollBy(l,d);else{let n=e.scrollLeft,s=e.scrollTop;d&&(e.scrollTop+=d),l&&(e.scrollLeft+=l);let r=e.scrollLeft-n,i=e.scrollTop-s;t={left:t.left-r,top:t.top-i,right:t.right-r,bottom:t.bottom-i}}let c=n?"fixed":getComputedStyle(a).position;if(/^(fixed|sticky)$/.test(c))break;a="absolute"==c?a.offsetParent:n$(a)}}function so(e){let t=[],n=e.ownerDocument;for(let s=e;s&&(t.push({dom:s,top:s.scrollTop,left:s.scrollLeft}),e!=n);s=n$(s));return t}function sl(e,t){for(let n=0;n=t.left-1&&e.left<=t.right+1&&e.top>=t.top-1&&e.top<=t.bottom+1}function su(e){return e.top=0&&r==s.nodeValue.length?(e--,i=1):n<0?e--:t++,sf(sh(nq(s,e,t),i),i<0)}if(!e.state.doc.resolve(t-(i||0)).parent.inlineContent){if(null==i&&r&&(n<0||r==nW(s))){let e=s.childNodes[r-1];if(1==e.nodeType)return sg(e.getBoundingClientRect(),!1)}if(null==i&&r=0)}if(null==i&&r&&(n<0||r==nW(s))){let e=s.childNodes[r-1],t=3==e.nodeType?nq(e,nW(e)-!a):1!=e.nodeType||"BR"==e.nodeName&&e.nextSibling?null:e;if(t)return sf(sh(t,1),!1)}if(null==i&&r=0)}function sf(e,t){if(0==e.width)return e;let n=t?e.left:e.right;return{top:e.top,bottom:e.bottom,left:n,right:n}}function sg(e,t){if(0==e.height)return e;let n=t?e.top:e.bottom;return{top:n,bottom:n,left:e.left,right:e.right}}function sx(e,t,n){let s=e.state,r=e.root.activeElement;s!=t&&e.updateState(t),r!=e.dom&&e.focus();try{return n()}finally{s!=t&&e.updateState(s),r!=e.dom&&r&&r.focus()}}let sb=/[\u0590-\u08ac]/,sv=null,sy=null,sw=!1;class sj{constructor(e,t,n,s){this.parent=e,this.children=t,this.dom=n,this.contentDOM=s,this.dirty=0,n.pmViewDesc=this}matchesWidget(e){return!1}matchesMark(e){return!1}matchesNode(e,t,n){return!1}matchesHack(e){return!1}parseRule(e){return null}stopEvent(e){return!1}get size(){let e=0;for(let t=0;tnP(this.contentDOM);else if(this.contentDOM&&this.contentDOM!=this.dom&&this.dom.contains(this.contentDOM))s=2&e.compareDocumentPosition(this.contentDOM);else if(this.dom.firstChild){if(0==t)for(let t=e;;t=t.parentNode){if(t==this.dom){s=!1;break}if(t.previousSibling)break}if(null==s&&t==e.childNodes.length)for(let t=e;;t=t.parentNode){if(t==this.dom){s=!0;break}if(t.nextSibling)break}}return(null==s?n>0:s)?this.posAtEnd:this.posAtStart}nearestDesc(e,t=!1){for(let n=!0,s=e;s;s=s.parentNode){let r=this.getDesc(s),i;if(r&&(!t||r.node))if(!n||!(i=r.nodeDOM)||(1==i.nodeType?i.contains(1==e.nodeType?e:e.parentNode):i==e))return r;else n=!1}}getDesc(e){let t=e.pmViewDesc;for(let e=t;e;e=e.parent)if(e==this)return t}posFromDOM(e,t,n){for(let s=e;s;s=s.parentNode){let r=this.getDesc(s);if(r)return r.localPosFromDOM(e,t,n)}return -1}descAt(e){for(let t=0,n=0;te||r instanceof sM){s=e-t;break}t=i}if(s)return this.children[n].domFromPos(s-this.children[n].border,t);for(let e;n&&!(e=this.children[n-1]).size&&e instanceof sk&&e.side>=0;n--);if(t<=0){let e,s=!0;for(;(e=n?this.children[n-1]:null)&&e.dom.parentNode!=this.contentDOM;n--,s=!1);return e&&t&&s&&!e.border&&!e.domAtom?e.domFromPos(e.size,t):{node:this.contentDOM,offset:e?nP(e.dom)+1:0}}{let e,s=!0;for(;(e=n=r&&t<=o-n.border&&n.node&&n.contentDOM&&this.contentDOM.contains(n.contentDOM))return n.parseRange(e,t,r);e=i;for(let t=a;t>0;t--){let n=this.children[t-1];if(n.size&&n.dom.parentNode==this.contentDOM&&!n.emptyChildAt(1)){s=nP(n.dom)+1;break}e-=n.size}-1==s&&(s=0)}if(s>-1&&(o>t||a==this.children.length-1)){t=o;for(let e=a+1;eo&&it){let e=a;a=o,o=e}let n=document.createRange();n.setEnd(o.node,o.offset),n.setStart(a.node,a.offset),l.removeAllRanges(),l.addRange(n)}}ignoreMutation(e){return!this.contentDOM&&"selection"!=e.type}get contentLost(){return this.contentDOM&&this.contentDOM!=this.dom&&!this.dom.contains(this.contentDOM)}markDirty(e,t){for(let n=0,s=0;s=n:en){let s=n+r.border,a=i-r.border;if(e>=s&&t<=a){this.dirty=e==n||t==i?2:1,e==s&&t==a&&(r.contentLost||r.dom.parentNode!=this.contentDOM)?r.dirty=3:r.markDirty(e-s,t-s);return}r.dirty=r.dom!=r.contentDOM||r.dom.parentNode!=this.contentDOM||r.children.length?3:2}n=i}this.dirty=2}markParentsDirty(){let e=1;for(let t=this.parent;t;t=t.parent,e++){let n=1==e?2:1;t.dirtyr?r.parent?r.parent.posBeforeChild(r):void 0:s)),!t.type.spec.raw){if(1!=i.nodeType){let e=document.createElement("span");e.appendChild(i),i=e}i.hasAttribute("contenteditable")||(i.contentEditable="false"),i.classList.add("ProseMirror-widget")}super(e,[],i,null),this.widget=t,this.widget=t,r=this}matchesWidget(e){return 0==this.dirty&&e.type.eq(this.widget.type)}parseRule(){return{ignore:!0}}stopEvent(e){let t=this.widget.spec.stopEvent;return!!t&&t(e)}ignoreMutation(e){return"selection"!=e.type||this.widget.spec.ignoreSelection}destroy(){this.widget.type.destroy(this.dom),super.destroy()}get domAtom(){return!0}get ignoreForSelection(){return!!this.widget.type.spec.relaxedSide}get side(){return this.widget.type.side}}class sN extends sj{constructor(e,t,n,s){super(e,[],t,null),this.textDOM=n,this.text=s}get size(){return this.text.length}localPosFromDOM(e,t){return e!=this.textDOM?this.posAtStart+(t?this.size:0):this.posAtStart+t}domFromPos(e){return{node:this.textDOM,offset:e}}ignoreMutation(e){return"characterData"===e.type&&e.target.nodeValue==e.oldValue}}class sA extends sj{constructor(e,t,n,s,r){super(e,[],n,s),this.mark=t,this.spec=r}static create(e,t,n,s){let r=s.nodeViews[t.type.name],i=r&&r(t,s,n);return i&&i.dom||(i=tW.renderSpec(document,t.type.spec.toDOM(t,n),null,t.attrs)),new sA(e,t,i.dom,i.contentDOM||i.dom,i)}parseRule(){return 3&this.dirty||this.mark.type.spec.reparseInView?null:{mark:this.mark.type.name,attrs:this.mark.attrs,contentElement:this.contentDOM}}matchesMark(e){return 3!=this.dirty&&this.mark.eq(e)}markDirty(e,t){if(super.markDirty(e,t),0!=this.dirty){let e=this.parent;for(;!e.node;)e=e.parent;e.dirty0&&(r=sF(r,0,e,n));for(let e=0;eo?o.parent?o.parent.posBeforeChild(o):void 0:i,n,s),d=l&&l.dom,c=l&&l.contentDOM;if(t.isText)if(d){if(3!=d.nodeType)throw RangeError("Text must be rendered as a DOM text node")}else d=document.createTextNode(t.text);else if(!d){let e=tW.renderSpec(document,t.type.spec.toDOM(t),null,t.attrs);({dom:d,contentDOM:c}=e)}c||t.isText||"BR"==d.nodeName||(d.hasAttribute("contenteditable")||(d.contentEditable="false"),t.type.spec.draggable&&(d.draggable=!0));let u=d;return(d=sz(d,n,t),l)?o=new sE(e,t,n,s,d,c||null,u,l):t.isText?new s_(e,t,n,s,d,u):new sC(e,t,n,s,d,c||null,u)}parseRule(e){if(this.node.type.spec.reparseInView)return null;let t={node:this.node.type.name,attrs:this.node.attrs};if("pre"==this.node.type.whitespace&&(t.preserveWhitespace="full"),this.contentDOM)if(this.contentLost){for(let e=this.children.length-1;e>=0;e--){let n=this.children[e];if(this.dom.contains(n.dom.parentNode)){t.contentElement=n.dom.parentNode;break}}if(!t.contentElement){let n=e&&e.find(t=>1==t.nodeType&&0>e.indexOf(t.parentNode)&&this.dom.contains(t));n?t.contentElement=n:t.getContent=()=>tt.empty}}else t.contentElement=this.contentDOM;else t.getContent=()=>this.node.content;return t}matchesNode(e,t,n){return 0==this.dirty&&e.eq(this.node)&&sL(t,this.outerDeco)&&n.eq(this.innerDeco)}get size(){return this.node.nodeSize}get border(){return+!this.node.isLeaf}updateChildren(e,t){let n=this.node.inlineContent,s=t,r=e.composing?this.localCompositionInfo(e,t):null,i=r&&r.pos>-1?r:null,a=r&&r.pos<0,o=new sP(this,i&&i.node,e);(function(e,t,n,s){let r=t.locals(e),i=0;if(0==r.length){for(let n=0;ni;)o.push(r[a++]);let p=i+h.nodeSize;if(h.isText){let e=p;a!e.inline):o.slice();s(h,f,t.forChild(i,h),m),i=p}})(this.node,this.innerDeco,(t,r,i)=>{t.spec.marks?o.syncToMarks(t.spec.marks,n,e,r):t.type.side>=0&&!i&&o.syncToMarks(r==this.node.childCount?ti.none:this.node.child(r).marks,n,e,r),o.placeWidget(t,e,s)},(t,i,l,d)=>{let c;o.syncToMarks(t.marks,n,e,d),o.findNodeMatch(t,i,l,d)||a&&e.state.selection.from>s&&e.state.selection.to-1&&o.updateNodeAt(t,i,l,c,e)||o.updateNextNode(t,i,l,e,d,s)||o.addNode(t,i,l,e,s),s+=t.nodeSize}),o.syncToMarks([],n,e,0),this.node.isTextblock&&o.addTextblockHacks(),o.destroyRest(),(o.changed||2==this.dirty)&&(i&&this.protectLocalComposition(e,i),function e(t,n,s){let r=t.firstChild,i=!1;for(let a=0;at+this.node.content.size)return null;let r=e.input.compositionNode;if(!r||!this.dom.contains(r.parentNode))return null;if(!this.node.inlineContent)return{node:r,pos:-1,text:""};{let e=r.nodeValue,i=function(e,t,n,s){for(let r=0,i=0;r=n){if(i>=s&&l.slice(s-t.length-o,s-o)==t)return s-t.length;let e=o=0&&e+t.length+o>=n)return o+e;if(n==s&&l.length>=s+t.length-o&&l.slice(s-o,s-o+t.length)==t)return s}}return -1}(this.node.content,e,n-t,s-t);return i<0?null:{node:r,pos:i,text:e}}}protectLocalComposition(e,{node:t,pos:n,text:s}){if(this.getDesc(t))return;let r=t;for(;r.parentNode!=this.contentDOM;r=r.parentNode){for(;r.previousSibling;)r.parentNode.removeChild(r.previousSibling);for(;r.nextSibling;)r.parentNode.removeChild(r.nextSibling);r.pmViewDesc&&(r.pmViewDesc=void 0)}let i=new sN(this,r,t,s);e.input.compositionNodes.push(i),this.children=sF(this.children,n,n+s.length,e,i)}update(e,t,n,s){return 3!=this.dirty&&!!e.sameMarkup(this.node)&&(this.updateInner(e,t,n,s),!0)}updateInner(e,t,n,s){this.updateOuterDeco(t),this.node=e,this.innerDeco=n,this.contentDOM&&this.updateChildren(s,this.posAtStart),this.dirty=0}updateOuterDeco(e){if(sL(e,this.outerDeco))return;let t=1!=this.nodeDOM.nodeType,n=this.dom;this.dom=sI(this.dom,this.nodeDOM,sR(this.outerDeco,this.node,t),sR(e,this.node,t)),this.dom!=n&&(n.pmViewDesc=void 0,this.dom.pmViewDesc=this),this.outerDeco=e}selectNode(){1==this.nodeDOM.nodeType&&(this.nodeDOM.classList.add("ProseMirror-selectednode"),(this.contentDOM||!this.node.type.spec.draggable)&&(this.nodeDOM.draggable=!0))}deselectNode(){1==this.nodeDOM.nodeType&&(this.nodeDOM.classList.remove("ProseMirror-selectednode"),(this.contentDOM||!this.node.type.spec.draggable)&&this.nodeDOM.removeAttribute("draggable"))}get domAtom(){return this.node.isAtom}}function sS(e,t,n,s,r){sz(s,t,e);let i=new sC(void 0,e,t,n,s,s,s);return i.contentDOM&&i.updateChildren(r,0),i}class s_ extends sC{constructor(e,t,n,s,r,i){super(e,t,n,s,r,null,i)}parseRule(){let e=this.nodeDOM.parentNode;for(;e&&e!=this.dom&&!e.pmIsDeco;)e=e.parentNode;return{skip:e||!0}}update(e,t,n,s){return 3!=this.dirty&&(0==this.dirty||!!this.inParent())&&!!e.sameMarkup(this.node)&&(this.updateOuterDeco(t),(0!=this.dirty||e.text!=this.node.text)&&e.text!=this.nodeDOM.nodeValue&&(this.nodeDOM.nodeValue=e.text,s.trackWrites==this.nodeDOM&&(s.trackWrites=null)),this.node=e,this.dirty=0,!0)}inParent(){let e=this.parent.contentDOM;for(let t=this.nodeDOM;t;t=t.parentNode)if(t==e)return!0;return!1}domFromPos(e){return{node:this.nodeDOM,offset:e}}localPosFromDOM(e,t,n){return e==this.nodeDOM?this.posAtStart+Math.min(t,this.node.text.length):super.localPosFromDOM(e,t,n)}ignoreMutation(e){return"characterData"!=e.type&&"selection"!=e.type}slice(e,t,n){let s=this.node.cut(e,t),r=document.createTextNode(s.text);return new s_(this.parent,s,this.outerDeco,this.innerDeco,r,r)}markDirty(e,t){super.markDirty(e,t),this.dom!=this.nodeDOM&&(0==e||t==this.nodeDOM.nodeValue.length)&&(this.dirty=3)}get domAtom(){return!1}isText(e){return this.node.text==e}}class sM extends sj{parseRule(){return{ignore:!0}}matchesHack(e){return 0==this.dirty&&this.dom.nodeName==e}get domAtom(){return!0}get ignoreForCoords(){return"IMG"==this.dom.nodeName}}class sE extends sC{constructor(e,t,n,s,r,i,a,o){super(e,t,n,s,r,i,a),this.spec=o}update(e,t,n,s){if(3==this.dirty)return!1;if(this.spec.update&&(this.node.type==e.type||this.spec.multiType)){let r=this.spec.update(e,t,n);return r&&this.updateInner(e,t,n,s),r}return(!!this.contentDOM||!!e.isLeaf)&&super.update(e,t,n,s)}selectNode(){this.spec.selectNode?this.spec.selectNode():super.selectNode()}deselectNode(){this.spec.deselectNode?this.spec.deselectNode():super.deselectNode()}setSelection(e,t,n,s){this.spec.setSelection?this.spec.setSelection(e,t,n.root):super.setSelection(e,t,n,s)}destroy(){this.spec.destroy&&this.spec.destroy(),super.destroy()}stopEvent(e){return!!this.spec.stopEvent&&this.spec.stopEvent(e)}ignoreMutation(e){return this.spec.ignoreMutation?this.spec.ignoreMutation(e):super.ignoreMutation(e)}}let sT=function(e){e&&(this.nodeName=e)};sT.prototype=Object.create(null);let sO=[new sT];function sR(e,t,n){if(0==e.length)return sO;let s=n?sO[0]:new sT,r=[s];for(let i=0;i0;){let o;for(;;)if(s){let e=n.children[s-1];if(e instanceof sA)n=e,s=e.children.length;else{o=e,s--;break}}else if(n==t)break n;else s=n.parent.children.indexOf(n),n=n.parent;let l=o.node;if(l){if(l!=e.child(r-1))break;--r,i.set(o,r),a.push(o)}}return{index:r,matched:i,matches:a.reverse()}}(e.node.content,e)}destroyBetween(e,t){if(e!=t){for(let n=e;n>1,a=Math.min(i,e.length);for(;r-1)r>this.index&&(this.changed=!0,this.destroyBetween(this.index,r)),this.top=this.top.children[this.index];else{let s=sA.create(this.top,e[i],t,n);this.top.children.splice(this.index,0,s),this.top=s,this.changed=!0}this.index=0,i++}}findNodeMatch(e,t,n,s){let r=-1,i;if(s>=this.preMatch.index&&(i=this.preMatch.matches[s-this.preMatch.index]).parent==this.top&&i.matchesNode(e,t,n))r=this.top.children.indexOf(i,this.index);else for(let s=this.index,i=Math.min(this.top.children.length,s+5);s=n||c<=t?i.push(l):(dn&&i.push(l.slice(n-d,l.size,s)))}return i}function sq(e,t=null){let n=e.domSelectionRange(),s=e.state.doc;if(!n.focusNode)return null;let r=e.docView.nearestDesc(n.focusNode),i=r&&0==r.size,a=e.docView.posFromDOM(n.focusNode,n.focusOffset,1);if(a<0)return null;let o=s.resolve(a),l,d;if(nK(n)){for(l=a;r&&!r.node;)r=r.parent;let e=r.node;if(r&&e.isAtom&&nk.isSelectable(e)&&r.parent&&!(e.isInline&&function(e,t,n){for(let s=0==t,r=t==nW(e);s||r;){if(e==n)return!0;let t=nP(e);if(!(e=e.parentNode))return!1;s=s&&0==t,r=r&&t==nW(e)}}(n.focusNode,n.focusOffset,r.dom))){let e=r.posBefore;d=new nk(a==e?o:s.resolve(e))}}else{if(n instanceof e.dom.ownerDocument.defaultView.Selection&&n.rangeCount>1){let t=a,r=a;for(let s=0;s{(i.anchorNode!=a||i.anchorOffset!=o)&&(s.removeEventListener("selectionchange",r.input.hideSelectionGuard),setTimeout(()=>{(!sB(r)||r.state.selection.visible)&&r.dom.classList.remove("ProseMirror-hideselection")},20))})))}e.domObserver.setCurSelection(),e.domObserver.connectSelection()}let sU=n7||n6&&n8<63;function sH(e,t){let{node:n,offset:s}=e.docView.domFromPos(t,0),r=ss(e,t,n))||nw.between(t,n,s)}function sY(e){return(!e.editable||!!e.hasFocus())&&sX(e)}function sX(e){let t=e.domSelectionRange();if(!t.anchorNode)return!1;try{return e.dom.contains(3==t.anchorNode.nodeType?t.anchorNode.parentNode:t.anchorNode)&&(e.editable||e.dom.contains(3==t.focusNode.nodeType?t.focusNode.parentNode:t.focusNode))}catch(e){return!1}}function sZ(e,t){let{$anchor:n,$head:s}=e.selection,r=t>0?n.max(s):n.min(s),i=r.parent.inlineContent?r.depth?e.doc.resolve(t>0?r.after():r.before()):null:r;return i&&nx.findFrom(i,t)}function s0(e,t){return e.dispatch(e.state.tr.setSelection(t).scrollIntoView()),!0}function s1(e,t,n){let s=e.state.selection;if(s instanceof nw){if(n.indexOf("s")>-1){let{$head:n}=s,r=n.textOffset?null:t<0?n.nodeBefore:n.nodeAfter;if(!r||r.isText||!r.isLeaf)return!1;let i=e.state.doc.resolve(n.pos+r.nodeSize*(t<0?-1:1));return s0(e,new nw(s.$anchor,i))}else if(!s.empty)return!1;else if(e.endOfTextblock(t>0?"forward":"backward")){let n=sZ(e.state,t);return!!n&&n instanceof nk&&s0(e,n)}else if(!(se&&n.indexOf("m")>-1)){let n=s.$head,r=n.textOffset?null:t<0?n.nodeBefore:n.nodeAfter,i;if(!r||r.isText)return!1;let a=t<0?n.pos-r.nodeSize:n.pos;return!!(r.isAtom||(i=e.docView.descAt(a))&&!i.contentDOM)&&(nk.isSelectable(r)?s0(e,new nk(t<0?e.state.doc.resolve(n.pos-r.nodeSize):n)):!!ss&&s0(e,new nw(e.state.doc.resolve(t<0?a:a+r.nodeSize))))}}else{if(s instanceof nk&&s.node.isInline)return s0(e,new nw(t>0?s.$to:s.$from));let n=sZ(e.state,t);return!!n&&s0(e,n)}}function s2(e){return 3==e.nodeType?e.nodeValue.length:e.childNodes.length}function s5(e,t){let n=e.pmViewDesc;return n&&0==n.size&&(t<0||e.nextSibling||"BR"!=e.nodeName)}function s3(e,t){return t<0?function(e){let t=e.domSelectionRange(),n=t.focusNode,s=t.focusOffset;if(!n)return;let r,i,a=!1;for(n3&&1==n.nodeType&&s0)if(1!=n.nodeType)break;else{let e=n.childNodes[s-1];if(s5(e,-1))r=n,i=--s;else if(3==e.nodeType)s=(n=e).nodeValue.length;else break}else if(s4(n))break;else{let t=n.previousSibling;for(;t&&s5(t,-1);)r=n.parentNode,i=nP(t),t=t.previousSibling;if(t)s=s2(n=t);else{if((n=n.parentNode)==e.dom)break;s=0}}a?s6(e,n,s):r&&s6(e,r,i)}(e):function(e){let t,n,s=e.domSelectionRange(),r=s.focusNode,i=s.focusOffset;if(!r)return;let a=s2(r);for(;;)if(i{e.state==r&&sV(e)},50)}function s8(e,t){let n=e.state.doc.resolve(t);if(!(n6||st)&&n.parent.inlineContent){let s=e.coordsAtPos(t);if(t>n.start()){let n=e.coordsAtPos(t-1),r=(n.top+n.bottom)/2;if(r>s.top&&r1)return n.lefts.top&&r1)return n.left>s.left?"ltr":"rtl"}}return"rtl"==getComputedStyle(e.dom).direction?"rtl":"ltr"}function s7(e,t,n){let s=e.state.selection;if(s instanceof nw&&!s.empty||n.indexOf("s")>-1||se&&n.indexOf("m")>-1)return!1;let{$from:r,$to:i}=s;if(!r.parent.inlineContent||e.endOfTextblock(t<0?"up":"down")){let n=sZ(e.state,t);if(n&&n instanceof nk)return s0(e,n)}if(!r.parent.inlineContent){let n=t<0?r:i,a=s instanceof nA?nx.near(n,t):nx.findFrom(n,t);return!!a&&s0(e,a)}return!1}function s9(e,t){if(!(e.state.selection instanceof nw))return!0;let{$head:n,$anchor:s,empty:r}=e.state.selection;if(!n.sameParent(s))return!0;if(!r)return!1;if(e.endOfTextblock(t>0?"forward":"backward"))return!0;let i=!n.textOffset&&(t<0?n.nodeBefore:n.nodeAfter);if(i&&!i.isText){let s=e.state.tr;return t<0?s.delete(n.pos-i.nodeSize,n.pos):s.delete(n.pos,n.pos+i.nodeSize),e.dispatch(s),!0}return!1}function re(e,t,n){e.domObserver.stop(),t.contentEditable=n,e.domObserver.start()}function rt(e,t){e.someProp("transformCopied",n=>{t=n(t,e)});let n=[],{content:s,openStart:r,openEnd:i}=t;for(;r>1&&i>1&&1==s.childCount&&1==s.firstChild.childCount;){r--,i--;let e=s.firstChild;n.push(e.type.name,e.attrs!=e.type.defaultAttrs?e.attrs:null),s=e.content}let a=e.someProp("clipboardSerializer")||tW.fromSchema(e.state.schema),o=rl(),l=o.createElement("div");l.appendChild(a.serializeFragment(s,{document:o}));let d=l.firstChild,c,u=0;for(;d&&1==d.nodeType&&(c=ro[d.nodeName.toLowerCase()]);){for(let e=c.length-1;e>=0;e--){let t=o.createElement(c[e]);for(;l.firstChild;)t.appendChild(l.firstChild);l.appendChild(t),u++}d=l.firstChild}return d&&1==d.nodeType&&d.setAttribute("data-pm-slice",`${r} ${i}${u?` -${u}`:""} ${JSON.stringify(n)}`),{dom:l,text:e.someProp("clipboardTextSerializer",n=>n(t,e))||t.content.textBetween(0,t.content.size,"\n\n"),slice:t}}function rn(e,t,n,s,r){let i,a,o=r.parent.type.spec.code;if(!n&&!t)return null;let l=!!t&&(s||o||!n);if(l){if(e.someProp("transformPastedText",n=>{t=n(t,o||s,e)}),o)return a=new to(tt.from(e.state.schema.text(t.replace(/\r\n?/g,"\n"))),0,0),e.someProp("transformPasted",t=>{a=t(a,e,!0)}),a;let n=e.someProp("clipboardTextParser",n=>n(t,r,s,e));if(n)a=n;else{let n=r.marks(),{schema:s}=e.state,a=tW.fromSchema(s);i=document.createElement("div"),t.split(/(?:\r\n?|\n)+/).forEach(e=>{let t=i.appendChild(document.createElement("p"));e&&t.appendChild(a.serializeNode(s.text(e,n)))})}}else e.someProp("transformPastedHTML",t=>{n=t(n,e)}),i=function(e){let t=/^(\s*]*>)*/.exec(e);t&&(e=e.slice(t[0].length));let n=rl(),s=n.body,r=/<([a-z][^>\s]+)/i.exec(e),i;if((i=r&&ro[r[1].toLowerCase()])&&(e=i.map(e=>"<"+e+">").join("")+e+i.map(e=>"").reverse().join("")),s.innerHTML=function(e){let t=window.trustedTypes;if(!t)return e;if(!rd){if(rd=t.defaultPolicy)try{return rd.createHTML(e)}catch(e){}rd=t.createPolicy("ProseMirrorClipboard",{createHTML:e=>e})}return rd.createHTML(e)}(e),i)for(let e=0;e0;e--){let e=i.firstChild;for(;e&&1!=e.nodeType;)e=e.nextSibling;if(!e)break;i=e}if(a||(a=(e.someProp("clipboardParser")||e.someProp("domParser")||tD.fromSchema(e.state.schema)).parseSlice(i,{preserveWhitespace:!!(l||c),context:r,ruleFromNode:e=>"BR"!=e.nodeName||e.nextSibling||!e.parentNode||rs.test(e.parentNode.nodeName)?null:{ignore:!0}})),c)a=function(e,t){if(!e.size)return e;let n=e.content.firstChild.type.schema,s;try{s=JSON.parse(t)}catch(t){return e}let{content:r,openStart:i,openEnd:a}=e;for(let e=s.length-2;e>=0;e-=2){let t=n.nodes[s[e]];if(!t||t.hasRequiredAttrs())break;try{t.checkAttrs(s[e+1])}catch(e){break}r=tt.from(t.create(s[e+1],r)),i++,a++}return new to(r,i,a)}(ra(a,+c[1],+c[2]),c[4]);else if((a=to.maxOpen(function(e,t){if(e.childCount<2)return e;for(let n=t.depth;n>=0;n--){let s=t.node(n).contentMatchAt(t.index(n)),r,i=[];if(e.forEach(e=>{if(!i)return;let t=s.findWrapping(e.type),n;if(!t)return i=null;if(n=i.length&&r.length&&function e(t,n,s,r,i){if(i{a=t(a,e,l)}),a}let rs=/^(a|abbr|acronym|b|cite|code|del|em|i|ins|kbd|label|output|q|ruby|s|samp|span|strong|sub|sup|time|u|tt|var)$/i;function rr(e,t,n=0){for(let s=t.length-1;s>=n;s--)e=t[s].create(null,tt.from(e));return e}function ri(e,t,n,s,r,i){let a=t<0?e.firstChild:e.lastChild,o=a.content;return e.childCount>1&&(i=0),r=n&&(o=t<0?a.contentMatchAt(0).fillBefore(o,i<=r).append(o):o.append(a.contentMatchAt(a.childCount).fillBefore(tt.empty,!0))),e.replaceChild(t<0?0:e.childCount-1,a.copy(o))}function ra(e,t,n){return t{for(let n in t)e.input.eventHandlers[n]||e.dom.addEventListener(n,e.input.eventHandlers[n]=t=>rg(e,t))})}function rg(e,t){return e.someProp("handleDOMEvents",n=>{let s=n[t.type];return!!s&&(s(e,t)||t.defaultPrevented)})}function rx(e){return{left:e.clientX,top:e.clientY}}function rb(e,t,n,s,r){if(-1==s)return!1;let i=e.state.doc.resolve(s);for(let s=i.depth+1;s>0;s--)if(e.someProp(t,t=>s>i.depth?t(e,n,i.nodeAfter,i.before(s),r,!0):t(e,n,i.node(s),i.before(s),r,!1)))return!0;return!1}function rv(e,t,n){if(e.focused||e.focus(),e.state.selection.eq(t))return;let s=e.state.tr.setSelection(t);"pointer"==n&&s.setMeta("pointer",!0),e.dispatch(s)}function ry(e,t,n){let s=e.state.doc;if(-1==t)return s.inlineContent?nw.create(s,0,s.content.size):null;let r=s.resolve(t);for(let e=r.depth+1;e>0;e--){let t=e>r.depth?r.nodeAfter:r.node(e),i=r.before(e);if(t.inlineContent)return nw.create(s,i+1,i+1+t.content.size);if(n&&nk.isSelectable(t))return nk.create(s,i)}return null}ru.keydown=(e,t)=>{if((e.input.shiftKey=16==t.keyCode||t.shiftKey,!rA(e))&&(e.input.lastKeyCode=t.keyCode,e.input.lastKeyCodeTime=Date.now(),!sn||!n6||13!=t.keyCode))if(229!=t.keyCode&&e.domObserver.forceFlush(),!n9||13!=t.keyCode||t.ctrlKey||t.altKey||t.metaKey)e.someProp("handleKeyDown",n=>n(e,t))||function(e,t){let n,s=t.keyCode,r=(n="",t.ctrlKey&&(n+="c"),t.metaKey&&(n+="m"),t.altKey&&(n+="a"),t.shiftKey&&(n+="s"),n);if(8==s||se&&72==s&&"c"==r)return s9(e,-1)||s3(e,-1);if(46==s&&!t.shiftKey||se&&68==s&&"c"==r)return s9(e,1)||s3(e,1);if(13==s||27==s)return!0;if(37==s||se&&66==s&&"c"==r){let t=37==s?"ltr"==s8(e,e.state.selection.from)?-1:1:-1;return s1(e,t,r)||s3(e,t)}if(39==s||se&&70==s&&"c"==r){let t=39==s?"ltr"==s8(e,e.state.selection.from)?1:-1:1;return s1(e,t,r)||s3(e,t)}else if(38==s||se&&80==s&&"c"==r)return s7(e,-1,r)||s3(e,-1);else if(40==s||se&&78==s&&"c"==r)return function(e){if(!n7||e.state.selection.$head.parentOffset>0)return!1;let{focusNode:t,focusOffset:n}=e.domSelectionRange();if(t&&1==t.nodeType&&0==n&&t.firstChild&&"false"==t.firstChild.contentEditable){let n=t.firstChild;re(e,n,"true"),setTimeout(()=>re(e,n,"false"),20)}return!1}(e)||s7(e,1,r)||s3(e,1);else if(r==(se?"m":"c")&&(66==s||73==s||89==s||90==s))return!0;return!1}(e,t)?t.preventDefault():rp(e,"key");else{let t=Date.now();e.input.lastIOSEnter=t,e.input.lastIOSEnterFallbackTimeout=setTimeout(()=>{e.input.lastIOSEnter==t&&(e.someProp("handleKeyDown",t=>t(e,nJ(13,"Enter"))),e.input.lastIOSEnter=0)},200)}},ru.keyup=(e,t)=>{16==t.keyCode&&(e.input.shiftKey=!1)},ru.keypress=(e,t)=>{if(rA(e)||!t.charCode||t.ctrlKey&&!t.altKey||se&&t.metaKey)return;if(e.someProp("handleKeyPress",n=>n(e,t)))return void t.preventDefault();let n=e.state.selection;if(!(n instanceof nw)||!n.$from.sameParent(n.$to)){let s=String.fromCharCode(t.charCode),r=()=>e.state.tr.insertText(s).scrollIntoView();/[\r\n]/.test(s)||e.someProp("handleTextInput",t=>t(e,n.$from.pos,n.$to.pos,s,r))||e.dispatch(r()),t.preventDefault()}};let rw=se?"metaKey":"ctrlKey";rc.mousedown=(e,t)=>{var n;let s,r;e.input.shiftKey=t.shiftKey;let i=rM(e),a=Date.now(),o="singleClick";a-e.input.lastClick.time<500&&(s=(n=e.input.lastClick).x-t.clientX)*s+(r=n.y-t.clientY)*r<100&&!t[rw]&&e.input.lastClick.button==t.button&&("singleClick"==e.input.lastClick.type?o="doubleClick":"doubleClick"==e.input.lastClick.type&&(o="tripleClick")),e.input.lastClick={time:a,x:t.clientX,y:t.clientY,type:o,button:t.button},e.input.mouseDown&&e.input.mouseDown.done();let l=e.posAtCoords(rx(t));l&&("singleClick"==o?e.input.mouseDown=new rk(e,l,t,!!i):("doubleClick"==o?function(e,t,n,s){return rb(e,"handleDoubleClickOn",t,n,s)||e.someProp("handleDoubleClick",n=>n(e,t,s))}:function(e,t,n,s){return rb(e,"handleTripleClickOn",t,n,s)||e.someProp("handleTripleClick",n=>n(e,t,s))||function(e,t,n){if(0!=n.button)return!1;let s=ry(e,t,!0),r=e.state.doc;return!!s&&(rv(e,s,"pointer"),s instanceof nw&&r.eq(e.state.doc)&&(e.input.mouseDown=new rN(e,s)),!0)}(e,n,s)})(e,l.pos,l.inside,t)?t.preventDefault():rp(e,"pointer"))};class rj{constructor(e){this.view=e,this.mightDrag=null,e.root.addEventListener("mouseup",this.up=this.up.bind(this)),e.root.addEventListener("mousemove",this.move=this.move.bind(this))}up(e){this.done()}move(e){0==e.buttons&&this.done()}done(){this.view.root.removeEventListener("mouseup",this.up),this.view.root.removeEventListener("mousemove",this.move),this.view.input.mouseDown==this&&(this.view.input.mouseDown=null)}delaySelUpdate(){return!1}}class rk extends rj{constructor(e,t,n,s){let r,i;if(super(e),this.pos=t,this.event=n,this.flushed=s,this.delayedSelectionSync=!1,this.startDoc=e.state.doc,this.selectNode=!!n[rw],this.allowDefault=n.shiftKey,t.inside>-1)r=e.state.doc.nodeAt(t.inside),i=t.inside;else{let n=e.state.doc.resolve(t.pos);r=n.parent,i=n.depth?n.before():0}const a=s?null:n.target,o=a?e.docView.nearestDesc(a,!0):null;this.target=o&&1==o.nodeDOM.nodeType?o.nodeDOM:null;let{selection:l}=e.state;0==n.button&&(r.type.spec.draggable&&!1!==r.type.spec.selectable||l instanceof nk&&l.from<=i&&l.to>i)&&(this.mightDrag={node:r,pos:i,addAttr:!!(this.target&&!this.target.draggable),setUneditable:!!(this.target&&n3&&!this.target.hasAttribute("contentEditable"))}),this.target&&this.mightDrag&&(this.mightDrag.addAttr||this.mightDrag.setUneditable)&&(this.view.domObserver.stop(),this.mightDrag.addAttr&&(this.target.draggable=!0),this.mightDrag.setUneditable&&setTimeout(()=>{this.view.input.mouseDown==this&&this.target.setAttribute("contentEditable","false")},20),this.view.domObserver.start()),rp(e,"pointer")}done(){super.done(),this.mightDrag&&this.target&&(this.view.domObserver.stop(),this.mightDrag.addAttr&&this.target.removeAttribute("draggable"),this.mightDrag.setUneditable&&this.target.removeAttribute("contentEditable"),this.view.domObserver.start()),this.delayedSelectionSync&&setTimeout(()=>{this.view.isDestroyed||sV(this.view)})}up(e){if(this.done(),!this.view.dom.contains(e.target))return;let t=this.pos;if(this.view.state.doc!=this.startDoc&&(t=this.view.posAtCoords(rx(e))),this.updateAllowDefault(e),this.allowDefault||!t)rp(this.view,"pointer");else{var n,s,r,i;(n=this.view,s=t.pos,r=t.inside,i=this.selectNode,rb(n,"handleClickOn",s,r,e)||n.someProp("handleClick",t=>t(n,s,e))||(i?function(e,t){if(-1==t)return!1;let n=e.state.selection,s,r;n instanceof nk&&(s=n.node);let i=e.state.doc.resolve(t);for(let e=i.depth+1;e>0;e--){let t=e>i.depth?i.nodeAfter:i.node(e);if(nk.isSelectable(t)){r=s&&n.$from.depth>0&&e>=n.$from.depth&&i.before(n.$from.depth+1)==n.$from.pos?i.before(n.$from.depth):i.before(e);break}}return null!=r&&(rv(e,nk.create(e.state.doc,r),"pointer"),!0)}(n,r):function(e,t){if(-1==t)return!1;let n=e.state.doc.resolve(t),s=n.nodeAfter;return!!(s&&s.isAtom&&nk.isSelectable(s))&&(rv(e,new nk(n),"pointer"),!0)}(n,r)))?e.preventDefault():0==e.button&&(this.flushed||n7&&this.mightDrag&&!this.mightDrag.node.isAtom||n6&&!this.view.state.selection.visible&&2>=Math.min(Math.abs(t.pos-this.view.state.selection.from),Math.abs(t.pos-this.view.state.selection.to)))?(rv(this.view,nx.near(this.view.state.doc.resolve(t.pos)),"pointer"),e.preventDefault()):rp(this.view,"pointer")}}move(e){this.updateAllowDefault(e),rp(this.view,"pointer"),super.move(e)}updateAllowDefault(e){!this.allowDefault&&(Math.abs(this.event.x-e.clientX)>4||Math.abs(this.event.y-e.clientY)>4)&&(this.allowDefault=!0)}delaySelUpdate(){return!!this.allowDefault&&(this.delayedSelectionSync=!0,!0)}}class rN extends rj{constructor(e,t){super(e),this.startSelection=t,this.startDoc=e.state.doc}move(e){if(0==e.buttons||this.view.isDestroyed||!this.view.state.doc.eq(this.startDoc))return void this.done();e.preventDefault(),rp(this.view,"pointer");let t=this.view.posAtCoords(rx(e)),n=t&&ry(this.view,t.inside,!1);if(!n)return;let{doc:s}=this.view.state,r=this.startSelection,[i,a]=n.fromMath.abs(Date.now()-e.input.compositionEndedAt))&&(e.input.compositionEndedAt=-2e8,!0)}rc.touchstart=e=>{e.input.lastTouch=Date.now(),rM(e),rp(e,"pointer")},rc.touchmove=e=>{e.input.lastTouch=Date.now(),rp(e,"pointer")},rc.contextmenu=e=>rM(e);let rC=sn?5e3:-1;function rS(e,t){clearTimeout(e.input.composingTimeout),t>-1&&(e.input.composingTimeout=setTimeout(()=>rM(e),t))}function r_(e){for(e.composing&&(e.input.composing=!1,e.input.compositionEndedAt=Date.now());e.input.compositionNodes.length>0;)e.input.compositionNodes.pop().markParentsDirty()}function rM(e,t=!1){if(!sn||!(e.domObserver.flushingSoon>=0)){if(e.domObserver.forceFlush(),r_(e),t||e.docView&&e.docView.dirty){let n=sq(e),s=e.state.selection;return n&&!n.eq(s)?e.dispatch(e.state.tr.setSelection(n)):(e.markCursor||t)&&!s.$from.node(s.$from.sharedDepth(s.to)).inlineContent?e.dispatch(e.state.tr.deleteSelection()):e.updateState(e.state),!0}return!1}}ru.compositionstart=ru.compositionupdate=e=>{if(!e.composing){e.domObserver.flush();let{state:t}=e,n=t.selection.$to;if(t.selection instanceof nw&&(t.storedMarks||!n.textOffset&&n.parentOffset&&n.nodeBefore.marks.some(e=>!1===e.type.spec.inclusive)||n6&&st&&function(e){let{focusNode:t,focusOffset:n}=e.domSelectionRange();if(!t||1!=t.nodeType||n>=t.childNodes.length)return!1;let s=t.childNodes[n];return 1==s.nodeType&&"false"==s.contentEditable}(e)))e.markCursor=e.state.storedMarks||n.marks(),rM(e,!0),e.markCursor=null;else if(rM(e,!t.selection.empty),n3&&t.selection.empty&&n.parentOffset&&!n.textOffset&&n.nodeBefore.marks.length){let t=e.domSelectionRange();for(let n=t.focusNode,s=t.focusOffset;n&&1==n.nodeType&&0!=s;){let t=s<0?n.lastChild:n.childNodes[s-1];if(!t)break;if(3==t.nodeType){let n=e.domSelection();n&&n.collapse(t,t.nodeValue.length);break}n=t,s=-1}}e.input.composing=!0}rS(e,rC)},ru.compositionend=(e,t)=>{e.composing&&(e.input.composing=!1,e.input.compositionEndedAt=Date.now(),e.input.compositionPendingChanges=e.domObserver.pendingRecords().length?e.input.compositionID:0,e.input.compositionNode=null,e.input.badSafariComposition?e.domObserver.forceFlush():e.input.compositionPendingChanges&&Promise.resolve().then(()=>e.domObserver.flush()),e.input.compositionID++,rS(e,20))};let rE=n2&&n5<15||n9&&sr<604;function rT(e,t,n,s,r){let i=rn(e,t,n,s,e.state.selection.$from);if(e.someProp("handlePaste",t=>t(e,r,i||to.empty)))return!0;if(!i)return!1;let a=0==i.openStart&&0==i.openEnd&&1==i.content.childCount?i.content.firstChild:null,o=a?e.state.tr.replaceSelectionWith(a,s):e.state.tr.replaceSelection(i);return e.dispatch(o.scrollIntoView().setMeta("paste",!0).setMeta("uiEvent","paste")),!0}function rO(e){let t=e.getData("text/plain")||e.getData("Text");if(t)return t;let n=e.getData("text/uri-list");return n?n.replace(/\r?\n/g," "):""}rc.copy=ru.cut=(e,t)=>{let n=e.state.selection,s="cut"==t.type;if(n.empty)return;let r=rE?null:t.clipboardData,{dom:i,text:a}=rt(e,n.content());r?(t.preventDefault(),r.clearData(),r.setData("text/html",i.innerHTML),r.setData("text/plain",a)):function(e,t){if(!e.dom.parentNode)return;let n=e.dom.parentNode.appendChild(document.createElement("div"));n.appendChild(t),n.style.cssText="position: fixed; left: -10000px; top: 10px";let s=getSelection(),r=document.createRange();r.selectNodeContents(t),e.dom.blur(),s.removeAllRanges(),s.addRange(r),setTimeout(()=>{n.parentNode&&n.parentNode.removeChild(n),e.focus()},50)}(e,i),s&&e.dispatch(e.state.tr.deleteSelection().scrollIntoView().setMeta("uiEvent","cut"))},ru.paste=(e,t)=>{if(e.composing&&!sn)return;let n=rE?null:t.clipboardData,s=e.input.shiftKey&&45!=e.input.lastKeyCode;n&&rT(e,rO(n),n.getData("text/html"),s,t)?t.preventDefault():function(e,t){if(!e.dom.parentNode)return;let n=e.input.shiftKey||e.state.selection.$from.parent.type.spec.code,s=e.dom.parentNode.appendChild(document.createElement(n?"textarea":"div"));n||(s.contentEditable="true"),s.style.cssText="position: fixed; left: -10000px; top: 10px",s.focus();let r=e.input.shiftKey&&45!=e.input.lastKeyCode;setTimeout(()=>{e.focus(),s.parentNode&&s.parentNode.removeChild(s),n?rT(e,s.value,null,r,t):rT(e,s.textContent,s.innerHTML,r,t)},50)}(e,t)};class rR{constructor(e,t,n){this.slice=e,this.move=t,this.node=n}}let rI=se?"altKey":"ctrlKey";function rz(e,t){let n;return e.someProp("dragCopies",e=>{n=n||e(t)}),null!=n?!n:!t[rI]}for(let e in rc.dragstart=(e,t)=>{let n,s=e.input.mouseDown;if(s&&s.done(),!t.dataTransfer)return;let r=e.state.selection,i=r.empty?null:e.posAtCoords(rx(t));if(i&&i.pos>=r.from&&i.pos<=(r instanceof nk?r.to-1:r.to));else if(s&&s.mightDrag)n=nk.create(e.state.doc,s.mightDrag.pos);else if(t.target&&1==t.target.nodeType){let s=e.docView.nearestDesc(t.target,!0);s&&s.node.type.spec.draggable&&s!=e.docView&&(n=nk.create(e.state.doc,s.posBefore))}let a=(n||e.state.selection).content(),{dom:o,text:l,slice:d}=rt(e,a);t.dataTransfer.files.length&&n6&&!(n8>120)||t.dataTransfer.clearData(),t.dataTransfer.setData(rE?"Text":"text/html",o.innerHTML),t.dataTransfer.effectAllowed="copyMove",rE||t.dataTransfer.setData("text/plain",l),e.dragging=new rR(d,rz(e,t),n)},rc.dragend=e=>{let t=e.dragging;window.setTimeout(()=>{e.dragging==t&&(e.dragging=null)},50)},ru.dragover=ru.dragenter=(e,t)=>t.preventDefault(),ru.drop=(e,t)=>{try{!function(e,t,n){if(!t.dataTransfer)return;let s=e.posAtCoords(rx(t));if(!s)return;let r=e.state.doc.resolve(s.pos),i=n&&n.slice;i?e.someProp("transformPasted",t=>{i=t(i,e,!1)}):i=rn(e,rO(t.dataTransfer),rE?null:t.dataTransfer.getData("text/html"),!1,r);let a=!!(n&&rz(e,t));if(e.someProp("handleDrop",n=>n(e,t,i||to.empty,a)))return t.preventDefault();if(!i)return;t.preventDefault();let o=i?function(e,t,n){let s=e.resolve(t);if(!n.content.size)return t;let r=n.content;for(let e=0;e=0;t--){let n=t==s.depth?0:s.pos<=(s.start(t+1)+s.end(t+1))/2?-1:1,i=s.index(t)+ +(n>0),a=s.node(t),o=!1;if(1==e)o=a.canReplace(i,i,r);else{let e=a.contentMatchAt(i).findWrapping(r.firstChild.type);o=e&&a.canReplaceWith(i,i,e[0])}if(o)return 0==n?s.pos:n<0?s.before(t+1):s.after(t+1)}return null}(e.state.doc,r.pos,i):r.pos;null==o&&(o=r.pos);let l=e.state.tr;if(a){let{node:e}=n;e?e.replace(l):l.deleteSelection()}let d=l.mapping.map(o),c=0==i.openStart&&0==i.openEnd&&1==i.content.childCount,u=l.doc;if(c?l.replaceRangeWith(d,d,i.content.firstChild):l.replaceRange(d,d,i),l.doc.eq(u))return;let h=l.doc.resolve(d);if(c&&nk.isSelectable(i.content.firstChild)&&h.nodeAfter&&h.nodeAfter.sameMarkup(i.content.firstChild))l.setSelection(new nk(h));else{let t=l.mapping.map(o);l.mapping.maps[l.mapping.maps.length-1].forEach((e,n,s,r)=>t=r),l.setSelection(sQ(e,h,l.doc.resolve(t)))}e.focus(),e.dispatch(l.setMeta("uiEvent","drop"))}(e,t,e.dragging)}finally{e.dragging=null}},rc.focus=e=>{e.input.lastFocus=Date.now(),e.focused||(e.domObserver.stop(),e.dom.classList.add("ProseMirror-focused"),e.domObserver.start(),e.focused=!0,setTimeout(()=>{e.docView&&e.hasFocus()&&!e.domObserver.currentSelection.eq(e.domSelectionRange())&&sV(e)},20))},rc.blur=(e,t)=>{e.focused&&(e.domObserver.stop(),e.dom.classList.remove("ProseMirror-focused"),e.domObserver.start(),t.relatedTarget&&e.dom.contains(t.relatedTarget)&&e.domObserver.currentSelection.clear(),e.focused=!1)},rc.beforeinput=(e,t)=>{if(sn&&"deleteContentBackward"==t.inputType){e.domObserver.flushSoon();let{domChangeCount:t}=e.input;setTimeout(()=>{if(e.input.domChangeCount!=t||(e.dom.blur(),e.focus(),e.someProp("handleKeyDown",t=>t(e,nJ(8,"Backspace")))))return;let{$cursor:n}=e.state.selection;n&&n.pos>0&&e.dispatch(e.state.tr.delete(n.pos-1,n.pos).scrollIntoView())},50)}},ru)rc[e]=ru[e];function rL(e,t){if(e==t)return!0;for(let n in e)if(e[n]!==t[n])return!1;for(let n in t)if(!(n in e))return!1;return!0}class rD{constructor(e,t){this.toDOM=e,this.spec=t||rB,this.side=this.spec.side||0}map(e,t,n,s){let{pos:r,deleted:i}=e.mapResult(t.from+s,this.side<0?-1:1);return i?null:new rF(r-n,r-n,this)}valid(){return!0}eq(e){return this==e||e instanceof rD&&(this.spec.key&&this.spec.key==e.spec.key||this.toDOM==e.toDOM&&rL(this.spec,e.spec))}destroy(e){this.spec.destroy&&this.spec.destroy(e)}}class rP{constructor(e,t){this.attrs=e,this.spec=t||rB}map(e,t,n,s){let r=e.map(t.from+s,this.spec.inclusiveStart?-1:1)-n,i=e.map(t.to+s,this.spec.inclusiveEnd?1:-1)-n;return r>=i?null:new rF(r,i,this)}valid(e,t){return t.from=e&&(!r||r(a.spec))&&n.push(a.copy(a.from+s,a.to+s))}for(let i=0;ie){let a=this.children[i]+1;this.children[i+2].findInner(e-a,t-a,n,s+a,r)}}map(e,t,n){return this==rU||0==e.maps.length?this:this.mapInner(e,t,0,0,n||rB)}mapInner(e,t,n,s,r){let i;for(let a=0;a{let a=i-r-(n-e);for(let r=0;ri+t-s)continue;let l=o[r]+t-s;n>=l?o[r+1]=e<=l?-2:-1:e>=t&&a&&(o[r]+=a,o[r+1]+=a)}s+=a}),t=n.maps[e].map(t,-1)}let l=!1;for(let t=0;t=s.content.size){l=!0;continue}let u=n.map(e[t+1]+i,-1)-r,{index:h,offset:m}=s.content.findIndex(c),p=s.maybeChild(h);if(p&&m==c&&m+p.nodeSize==u){let s=o[t+2].mapInner(n,p,d+1,e[t]+i+1,a);s!=rU?(o[t]=c,o[t+1]=u,o[t+2]=s):(o[t+1]=-2,l=!0)}else l=!0}if(l){let l=rJ(function(e,t,n,s,r,i,a){for(let o=0;o{let a=i+n,o;if(o=rG(t,e,a)){for(s||(s=this.children.slice());ri&&n.to=e){this.children[t]==e&&(n=this.children[t+2]);break}let r=e+1,i=r+t.content.size;for(let e=0;er&&t.type instanceof rP){let e=Math.max(r,t.from)-r,n=Math.min(i,t.to)-r;en.map(e,t,rB));return rH.from(n)}forChild(e,t){if(t.isLeaf)return rV.empty;let n=[];for(let s=0;se instanceof rV)?e:e.reduce((e,t)=>e.concat(t instanceof rV?t:t.members),[]))}}forEachSet(e){for(let t=0;tn&&i.to{let o=rG(e,t,a+n);if(o){i=!0;let e=rJ(o,t,n+a+1,s);e!=rU&&r.push(a,a+t.nodeSize,e)}});let a=rW(i?rK(e):e,-n).sort(rQ);for(let e=0;e0;)t++;e.splice(t,0,n)}function rZ(e){let t=[];return e.someProp("decorations",n=>{let s=n(e.state);s&&s!=rU&&t.push(s)}),e.cursorWrapper&&t.push(rV.create(e.state.doc,[e.cursorWrapper.deco])),rH.from(t)}let r0={childList:!0,characterData:!0,characterDataOldValue:!0,attributes:!0,attributeOldValue:!0,subtree:!0},r1=n2&&n5<=11;class r2{constructor(){this.anchorNode=null,this.anchorOffset=0,this.focusNode=null,this.focusOffset=0}set(e){this.anchorNode=e.anchorNode,this.anchorOffset=e.anchorOffset,this.focusNode=e.focusNode,this.focusOffset=e.focusOffset}clear(){this.anchorNode=this.focusNode=null}eq(e){return e.anchorNode==this.anchorNode&&e.anchorOffset==this.anchorOffset&&e.focusNode==this.focusNode&&e.focusOffset==this.focusOffset}}class r5{constructor(e,t){this.view=e,this.handleDOMChange=t,this.queue=[],this.flushingSoon=-1,this.observer=null,this.currentSelection=new r2,this.onCharData=null,this.suppressingSelectionUpdates=!1,this.lastChangedTextNode=null,this.observer=window.MutationObserver&&new window.MutationObserver(t=>{for(let e=0;e"childList"==e.type&&e.removedNodes.length||"characterData"==e.type&&e.oldValue.length>e.target.nodeValue.length)?this.flushSoon():n7&&e.composing&&t.some(e=>"childList"==e.type&&"TR"==e.target.nodeName)?(e.input.badSafariComposition=!0,this.flushSoon()):this.flush()}),r1&&(this.onCharData=e=>{this.queue.push({target:e.target,type:"characterData",oldValue:e.prevValue}),this.flushSoon()}),this.onSelectionChange=this.onSelectionChange.bind(this)}flushSoon(){this.flushingSoon<0&&(this.flushingSoon=window.setTimeout(()=>{this.flushingSoon=-1,this.flush()},20))}forceFlush(){this.flushingSoon>-1&&(window.clearTimeout(this.flushingSoon),this.flushingSoon=-1,this.flush())}start(){this.observer&&(this.observer.takeRecords(),this.observer.observe(this.view.dom,r0)),this.onCharData&&this.view.dom.addEventListener("DOMCharacterDataModified",this.onCharData),this.connectSelection()}stop(){if(this.observer){let e=this.observer.takeRecords();if(e.length){for(let t=0;tthis.flush(),20)}this.observer.disconnect()}this.onCharData&&this.view.dom.removeEventListener("DOMCharacterDataModified",this.onCharData),this.disconnectSelection()}connectSelection(){this.view.dom.ownerDocument.addEventListener("selectionchange",this.onSelectionChange)}disconnectSelection(){this.view.dom.ownerDocument.removeEventListener("selectionchange",this.onSelectionChange)}suppressSelectionUpdates(){this.suppressingSelectionUpdates=!0,setTimeout(()=>this.suppressingSelectionUpdates=!1,50)}onSelectionChange(){if(sY(this.view)){if(this.suppressingSelectionUpdates)return sV(this.view);if(n2&&n5<=11&&!this.view.state.selection.empty){let e=this.view.domSelectionRange();if(e.focusNode&&nV(e.focusNode,e.focusOffset,e.anchorNode,e.anchorOffset))return this.flushSoon()}this.flush()}}setCurSelection(){this.currentSelection.set(this.view.domSelectionRange())}ignoreSelectionChange(e){if(!e.focusNode)return!0;let t=new Set,n;for(let n=e.focusNode;n;n=n$(n))t.add(n);for(let s=e.anchorNode;s;s=n$(s))if(t.has(s)){n=s;break}let s=n&&this.view.docView.nearestDesc(n);if(s&&s.ignoreMutation({type:"selection",target:3==n.nodeType?n.parentNode:n}))return this.setCurSelection(),!0}pendingRecords(){if(this.observer)for(let e of this.observer.takeRecords())this.queue.push(e);return this.queue}flush(){var e;let{view:t}=this;if(!t.docView||this.flushingSoon>-1)return;let n=this.pendingRecords();n.length&&(this.queue=[]);let s=t.domSelectionRange(),r=!this.suppressingSelectionUpdates&&!this.currentSelection.eq(s)&&sY(t)&&!this.ignoreSelectionChange(s),i=-1,a=-1,o=!1,l=[];if(t.editable)for(let e=0;e"BR"==e.nodeName)&&(8==t.input.lastKeyCode||46==t.input.lastKeyCode||n6&&(t.composing||t.input.compositionEndedAt>Date.now()-50)&&n.some(e=>"childList"==e.type&&e.removedNodes.length))){for(let e of l)if("BR"==e.nodeName&&e.parentNode){let t=e.nextSibling;for(;t&&1==t.nodeType;){if("false"==t.contentEditable){e.parentNode.removeChild(e);break}t=t.firstChild}}}else if(n3&&l.length){let e=l.filter(e=>"BR"==e.nodeName);if(2==e.length){let[t,n]=e;t.parentNode&&t.parentNode.parentNode==n.parentNode?n.remove():t.remove()}else{let{focusNode:n}=this.currentSelection;for(let s of e){let e=s.parentNode;e&&"LI"==e.nodeName&&(!n||function(e,t){for(let n=t.parentNode;n&&n!=e.dom;n=n.parentNode){let t=e.docView.nearestDesc(n,!0);if(t&&t.node.isBlock)return n}return null}(t,n)!=e)&&s.remove()}}}let d=null;i<0&&r&&t.input.lastFocus>Date.now()-200&&Math.max(t.input.lastTouch,t.input.lastClick.time)-1||r)&&(i>-1&&(t.docView.markDirty(i,a),e=t,!r3.has(e)&&(r3.set(e,null),-1!==["normal","nowrap","pre-line"].indexOf(getComputedStyle(e.dom).whiteSpace))&&(e.requiresGeckoHackNode=n3,r4||(console.warn("ProseMirror expects the CSS white-space property to be set, preferably to 'pre-wrap'. It is recommended to load style/prosemirror.css from the prosemirror-view package."),r4=!0))),t.input.badSafariComposition&&(t.input.badSafariComposition=!1,function(e,t){var n;let{focusNode:s,focusOffset:r}=e.domSelectionRange();for(let i of t)if((null==(n=i.parentNode)?void 0:n.nodeName)=="TR"){let t=i.nextSibling;for(;t&&"TD"!=t.nodeName&&"TH"!=t.nodeName;)t=t.nextSibling;if(t){let n=t;for(;;){let e=n.firstChild;if(!e||1!=e.nodeType||"false"==e.contentEditable||/^(BR|IMG)$/.test(e.nodeName))break;n=e}n.insertBefore(i,n.firstChild),s==i&&e.domSelection().collapse(i,r)}else i.parentNode.removeChild(i)}}(t,l)),this.handleDOMChange(i,a,o,l),t.docView&&t.docView.dirty?t.updateState(t.state):this.currentSelection.eq(s)||sV(t),this.currentSelection.set(s))}registerMutation(e,t){if(t.indexOf(e.target)>-1)return null;let n=this.view.docView.nearestDesc(e.target);if("attributes"==e.type&&(n==this.view.docView||"contenteditable"==e.attributeName||"style"==e.attributeName&&!e.oldValue&&!e.target.getAttribute("style"))||!n||n.ignoreMutation(e))return null;if("childList"==e.type){for(let n=0;nArray.prototype.indexOf.call(e.addedNodes,n))&&(s=n),(!i||0>Array.prototype.indexOf.call(e.addedNodes,i))&&(r=i)}let i=s&&s.parentNode==e.target?nP(s)+1:0,a=n.localPosFromDOM(e.target,i,-1),o=r&&r.parentNode==e.target?nP(r):e.target.childNodes.length;return{from:a,to:n.localPosFromDOM(e.target,o,1)}}return"attributes"==e.type?{from:n.posAtStart-n.border,to:n.posAtEnd+n.border}:(this.lastChangedTextNode=e.target,{from:n.posAtStart,to:n.posAtEnd,typeOver:e.target.nodeValue==e.oldValue})}}let r3=new WeakMap,r4=!1;function r6(e,t){let n=t.startContainer,s=t.startOffset,r=t.endContainer,i=t.endOffset,a=e.domAtPos(e.state.selection.anchor);return nV(a.node,a.offset,r,i)&&([n,s,r,i]=[r,i,n,s]),{anchorNode:n,anchorOffset:s,focusNode:r,focusOffset:i}}let r8=/^(a|abbr|acronym|b|bd[io]|big|br|button|cite|code|data(list)?|del|dfn|em|i|img|ins|kbd|label|map|mark|meter|output|q|ruby|s|samp|small|span|strong|su[bp]|time|u|tt|var)$/i;function r7(e,t,n){return Math.max(n.anchor,n.head)>t.content.size?null:sQ(e,t.resolve(n.anchor),t.resolve(n.head))}function r9(e,t,n){let s=e.depth,r=t?e.end():e.pos;for(;s>0&&(t||e.indexAfter(s)==e.node(s).childCount);)s--,r++,t=!1;if(n){let t=e.node(s).maybeChild(e.indexAfter(s));for(;t&&!t.isLeaf;)t=t.firstChild,r++}return r}class ie{constructor(e,t){this._root=null,this.focused=!1,this.trackWrites=null,this.mounted=!1,this.markCursor=null,this.cursorWrapper=null,this.lastSelectedViewDesc=void 0,this.input=new rm,this.prevDirectPlugins=[],this.pluginViews=[],this.requiresGeckoHackNode=!1,this.dragging=null,this._props=t,this.state=t.state,this.directPlugins=t.plugins||[],this.directPlugins.forEach(ia),this.dispatch=this.dispatch.bind(this),this.dom=e&&e.mount||document.createElement("div"),e&&(e.appendChild?e.appendChild(this.dom):"function"==typeof e?e(this.dom):e.mount&&(this.mounted=!0)),this.editable=ir(this),is(this),this.nodeViews=ii(this),this.docView=sS(this.state.doc,it(this),rZ(this),this.dom,this),this.domObserver=new r5(this,(e,t,n,s)=>(function(e,t,n,s,r){let i,a,o,l=e.input.compositionPendingChanges||(e.composing?e.input.compositionID:0);if(e.input.compositionPendingChanges=0,t<0){let t=e.input.lastSelectionTime>Date.now()-50?e.input.lastSelectionOrigin:null,n=sq(e,t);if(n&&!e.state.selection.eq(n)){if(n6&&sn&&13===e.input.lastKeyCode&&Date.now()-100t(e,nJ(13,"Enter"))))return;let s=e.state.tr.setSelection(n);"pointer"==t?s.setMeta("pointer",!0):"key"==t&&s.scrollIntoView(),l&&s.setMeta("composition",l),e.dispatch(s)}return}let d=e.state.doc.resolve(t),c=d.sharedDepth(n);t=d.before(c+1),n=e.state.doc.resolve(n).after(c+1);let u=e.state.selection,h=function(e,t,n,s){let r,i,{node:a,fromOffset:o,toOffset:l,from:d,to:c}=e.docView.parseRange(t,n),u=e.domSelectionRange(),h=u.anchorNode;if(h&&e.dom.contains(1==h.nodeType?h:h.parentNode)&&(i=[{node:h,offset:u.anchorOffset}],nK(u)||i.push({node:u.focusNode,offset:u.focusOffset})),n6&&8===e.input.lastKeyCode)for(let e=l;e>o;e--){let t=a.childNodes[e-1],n=t.pmViewDesc;if("BR"==t.nodeName&&!n){l=e;break}if(!n||n.size)break}let m=e.state.doc,p=e.someProp("domParser")||tD.fromSchema(e.state.schema),f=m.resolve(d),g=null,x=p.parse(a,{topNode:f.parent,topMatch:f.parent.contentMatchAt(f.index()),topOpen:!0,from:o,to:l,preserveWhitespace:"pre"!=f.parent.type.whitespace||"full",findPositions:i,ruleFromNode:(r=s,e=>{let t=e.pmViewDesc;if(t)return t.parseRule(r);if("BR"==e.nodeName&&e.parentNode){if(n7&&/^(ul|ol)$/i.test(e.parentNode.nodeName)){let e=document.createElement("div");return e.appendChild(document.createElement("li")),{skip:e}}else if(e.parentNode.lastChild==e||n7&&/^(tr|table)$/i.test(e.parentNode.nodeName))return{ignore:!0}}else if("IMG"==e.nodeName&&e.getAttribute("mark-placeholder"))return{ignore:!0};return null}),context:f});if(i&&null!=i[0].pos){let e=i[0].pos,t=i[1]&&i[1].pos;null==t&&(t=e),g={anchor:e+d,head:t+d}}return{doc:x,sel:g,from:d,to:c}}(e,t,n,r),m=e.state.doc,p=m.slice(h.from,h.to);8===e.input.lastKeyCode&&Date.now()-100=l?i-s:0;i-=e,d=i+(d-l),l=i}else if(d=d?i-s:0;i-=e,l=i+(l-d),d=i}return{start:i,endA:l,endB:d}}(p.content,h.doc.content,h.from,i,a);if(f&&e.input.domChangeCount++,(n9&&e.input.lastIOSEnter>Date.now()-225||sn)&&r.some(e=>1==e.nodeType&&!r8.test(e.nodeName))&&(!f||f.endA>=f.endB)&&e.someProp("handleKeyDown",t=>t(e,nJ(13,"Enter")))){e.input.lastIOSEnter=0;return}if(!f)if(s&&u instanceof nw&&!u.empty&&u.$head.sameParent(u.$anchor)&&!e.composing&&!(h.sel&&h.sel.anchor!=h.sel.head))f={start:u.from,endA:u.to,endB:u.to};else{if(h.sel){let t=r7(e,e.state.doc,h.sel);if(t&&!t.eq(e.state.selection)){let n=e.state.tr.setSelection(t);l&&n.setMeta("composition",l),e.dispatch(n)}}return}e.state.selection.frome.state.selection.from&&f.start<=e.state.selection.from+2&&e.state.selection.from>=h.from?f.start=e.state.selection.from:f.endA=e.state.selection.to-2&&e.state.selection.to<=h.to&&(f.endB+=e.state.selection.to-f.endA,f.endA=e.state.selection.to)),n2&&n5<=11&&f.endB==f.start+1&&f.endA==f.start&&f.start>h.from&&"  "==h.doc.textBetween(f.start-h.from-1,f.start-h.from+1)&&(f.start--,f.endA--,f.endB--);let g=h.doc.resolveNoCache(f.start-h.from),x=h.doc.resolveNoCache(f.endB-h.from),b=m.resolve(f.start),v=g.sameParent(x)&&g.parent.inlineContent&&b.end()>=f.endA;if((n9&&e.input.lastIOSEnter>Date.now()-225&&(!v||r.some(e=>"DIV"==e.nodeName||"P"==e.nodeName))||!v&&g.post(e,nJ(13,"Enter")))){e.input.lastIOSEnter=0;return}if(e.state.selection.anchor>f.start&&function(e,t,n,s,r){if(n-t<=r.pos-s.pos||r9(s,!0,!1)n||r9(a,!0,!1)t(e,nJ(8,"Backspace")))){sn&&n6&&e.domObserver.suppressSelectionUpdates();return}n6&&f.endB==f.start&&(e.input.lastChromeDelete=Date.now()),sn&&!v&&g.start()!=x.start()&&0==x.parentOffset&&g.depth==x.depth&&h.sel&&h.sel.anchor==h.sel.head&&h.sel.head==f.endA&&(f.endB-=2,x=h.doc.resolveNoCache(f.endB-h.from),setTimeout(()=>{e.someProp("handleKeyDown",function(t){return t(e,nJ(13,"Enter"))})},20));let y=f.start,w=f.endA,j=t=>{let n=t||e.state.tr.replace(y,w,h.doc.slice(f.start-h.from,f.endB-h.from));if(h.sel){let t=r7(e,n.doc,h.sel);t&&!(n6&&e.composing&&t.empty&&(f.start!=f.endB||e.input.lastChromeDeletesV(e),20));let t=j(e.state.tr.delete(y,w)),n=m.resolve(f.start).marksAcross(m.resolve(f.endA));n&&t.ensureMarks(n),e.dispatch(t)}else if(f.endA==f.endB&&(o=function(e,t){let n=e.firstChild.marks,s=t.firstChild.marks,r=n,i=s,a,o,l;for(let e=0;ee.mark(o.addToSet(e.marks));else{if(0!=r.length||1!=i.length)return null;o=i[0],a="remove",l=e=>e.mark(o.removeFromSet(e.marks))}let d=[];for(let e=0;ej(e.state.tr.insertText(t,y,w));e.someProp("handleTextInput",s=>s(e,y,w,t,n))||e.dispatch(n())}else e.dispatch(j());else e.dispatch(j())})(this,e,t,n,s)),this.domObserver.start(),function(e){for(let t in rc){let n=rc[t];e.dom.addEventListener(t,e.input.eventHandlers[t]=t=>{!function(e,t){if(!t.bubbles)return!0;if(t.defaultPrevented)return!1;for(let n=t.target;n!=e.dom;n=n.parentNode)if(!n||11==n.nodeType||n.pmViewDesc&&n.pmViewDesc.stopEvent(t))return!1;return!0}(e,t)||rg(e,t)||!e.editable&&t.type in ru||n(e,t)},rh[t]?{passive:!0}:void 0)}n7&&e.dom.addEventListener("input",()=>null),rf(e)}(this),this.updatePluginViews()}get composing(){return this.input.composing}get props(){if(this._props.state!=this.state){let e=this._props;for(let t in this._props={},e)this._props[t]=e[t];this._props.state=this.state}return this._props}update(e){e.handleDOMEvents!=this._props.handleDOMEvents&&rf(this);let t=this._props;this._props=e,e.plugins&&(e.plugins.forEach(ia),this.directPlugins=e.plugins),this.updateStateInner(e.state,t)}setProps(e){let t={};for(let e in this._props)t[e]=this._props[e];for(let n in t.state=this.state,e)t[n]=e[n];this.update(t)}updateState(e){this.updateStateInner(e,this._props)}updateStateInner(e,t){var n,s,r;let i=this.state,a=!1,o=!1;e.storedMarks&&this.composing&&(r_(this),o=!0),this.state=e;let l=i.plugins!=e.plugins||this._props.plugins!=t.plugins;if(l||this._props.plugins!=t.plugins||this._props.nodeViews!=t.nodeViews){let e=ii(this);(function(e,t){let n=0,s=0;for(let s in e){if(e[s]!=t[s])return!0;n++}for(let e in t)s++;return n!=s})(e,this.nodeViews)&&(this.nodeViews=e,a=!0)}(l||t.handleDOMEvents!=this._props.handleDOMEvents)&&rf(this),this.editable=ir(this),is(this);let d=rZ(this),c=it(this),u=i.plugins==e.plugins||i.doc.eq(e.doc)?e.scrollToSelection>i.scrollToSelection?"to selection":"preserve":"reset",h=a||!this.docView.matchesNode(e.doc,c,d);(h||!e.selection.eq(i.selection))&&(o=!0);let m="preserve"==u&&o&&null==this.dom.style.overflowAnchor&&function(e){let t,n,s=e.dom.getBoundingClientRect(),r=Math.max(0,s.top);for(let i=(s.left+s.right)/2,a=r+1;a=r-20){t=s,n=o.top;break}}return{refDOM:t,refTop:n,stack:so(e.dom)}}(this);if(o){let t,n,o;this.domObserver.stop();let l=h&&(n2||n6)&&!this.composing&&!i.selection.empty&&!e.selection.empty&&(s=i.selection,r=e.selection,o=Math.min(s.$anchor.sharedDepth(s.head),r.$anchor.sharedDepth(r.head)),s.$anchor.start(o)!=r.$anchor.start(o));if(h){let t=n6?this.trackWrites=this.domSelectionRange().focusNode:null;this.composing&&(this.input.compositionNode=function(e){let t=e.domSelectionRange();if(!t.focusNode)return null;let n=function(e,t){for(;;){if(3==e.nodeType&&t)return e;if(1==e.nodeType&&t>0){if("false"==e.contentEditable)return null;t=nW(e=e.childNodes[t-1])}else{if(!e.parentNode||nG(e))return null;t=nP(e),e=e.parentNode}}}(t.focusNode,t.focusOffset),s=function(e,t){for(;;){if(3==e.nodeType&&te(this)));else if(this.state.selection instanceof nk){let t=this.docView.domAfterPos(this.state.selection.from);1==t.nodeType&&sa(this,t.getBoundingClientRect(),e)}else sa(this,this.coordsAtPos(this.state.selection.head,1),e)}destroyPluginViews(){let e;for(;e=this.pluginViews.pop();)e.destroy&&e.destroy()}updatePluginViews(e){if(e&&e.plugins==this.state.plugins&&this.directPlugins==this.prevDirectPlugins)for(let t=0;t0&&ee.ownerDocument.getSelection()),this._root=e}return e||document}updateRoot(){this._root=null}posAtCoords(e){return function(e,t){var n;let s,r,i=e.dom.ownerDocument,a,o=0,l=function(e,t,n){if(e.caretPositionFromPoint)try{let s=e.caretPositionFromPoint(t,n);if(s)return{node:s.offsetNode,offset:Math.min(nW(s.offsetNode),s.offset)}}catch(e){}if(e.caretRangeFromPoint){let s=e.caretRangeFromPoint(t,n);if(s)return{node:s.startContainer,offset:Math.min(nW(s.startContainer),s.startOffset)}}}(i,t.left,t.top);l&&({node:a,offset:o}=l);let d=(e.root.elementFromPoint?e.root:i).elementFromPoint(t.left,t.top);if(!d||!e.dom.contains(1!=d.nodeType?d.parentNode:d)){let n=e.dom.getBoundingClientRect();if(!sc(t,n)||!(d=function e(t,n,s){let 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this.docView.domFromPos(e,t)}nodeDOM(e){let t=this.docView.descAt(e);return t?t.nodeDOM:null}posAtDOM(e,t,n=-1){let s=this.docView.posFromDOM(e,t,n);if(null==s)throw RangeError("DOM position not inside the editor");return s}endOfTextblock(e,t){return function(e,t,n){let s,r;return sv==t&&sy==n?sw:(sv=t,sy=n,sw="up"==n||"down"==n?(s=t.selection,r="up"==n?s.$from:s.$to,sx(e,t,()=>{let{node:t}=e.docView.domFromPos(r.pos,"up"==n?-1:1);for(;;){let n=e.docView.nearestDesc(t,!0);if(!n)break;if(n.node.isBlock){t=n.contentDOM||n.dom;break}t=n.dom.parentNode}let s=sp(e,r.pos,1);for(let e=t.firstChild;e;e=e.nextSibling){let t;if(1==e.nodeType)t=e.getClientRects();else{if(3!=e.nodeType)continue;t=nq(e,0,e.nodeValue.length).getClientRects()}for(let e=0;er.top+1&&("up"==n?s.top-r.top>(r.bottom-s.top)*2:r.bottom-s.bottom>(s.bottom-r.top)*2))return!1}}return!0})):function(e,t,n){let{$head:s}=t.selection;if(!s.parent.isTextblock)return!1;let r=s.parentOffset,i=r==s.parent.content.size,a=e.domSelection();return a?sb.test(s.parent.textContent)&&a.modify?sx(e,t,()=>{let{focusNode:t,focusOffset:r,anchorNode:i,anchorOffset:o}=e.domSelectionRange(),l=a.caretBidiLevel;a.modify("move",n,"character");let d=s.depth?e.docView.domAfterPos(s.before()):e.dom,{focusNode:c,focusOffset:u}=e.domSelectionRange(),h=c&&!d.contains(1==c.nodeType?c:c.parentNode)||t==c&&r==u;try{a.collapse(i,o),t&&(t!=i||r!=o)&&a.extend&&a.extend(t,r)}catch(e){}return null!=l&&(a.caretBidiLevel=l),h}):"left"==n||"backward"==n?!r:i:s.pos==s.start()||s.pos==s.end()}(e,t,n))}(this,t||this.state,e)}pasteHTML(e,t){return rT(this,"",e,!1,t||new ClipboardEvent("paste"))}pasteText(e,t){return rT(this,e,null,!0,t||new ClipboardEvent("paste"))}serializeForClipboard(e){return rt(this,e)}destroy(){if(this.docView){for(let e in this.input.mouseDown&&this.input.mouseDown.done(),this.domObserver.stop(),this.input.eventHandlers)this.dom.removeEventListener(e,this.input.eventHandlers[e]);clearTimeout(this.input.composingTimeout),clearTimeout(this.input.lastIOSEnterFallbackTimeout),this.destroyPluginViews(),this.mounted?(this.docView.update(this.state.doc,[],rZ(this),this),this.dom.textContent=""):this.dom.parentNode&&this.dom.parentNode.removeChild(this.dom),this.docView.destroy(),this.docView=null,nB()}}get isDestroyed(){return null==this.docView}dispatchEvent(e){!rg(this,e)&&rc[e.type]&&(this.editable||!(e.type in ru))&&rc[e.type](this,e)}domSelectionRange(){let e=this.domSelection();return e?n7&&11===this.root.nodeType&&function(e){let t=e.activeElement;for(;t&&t.shadowRoot;)t=t.shadowRoot.activeElement;return t}(this.dom.ownerDocument)==this.dom&&function(e,t){let n;if(t.getComposedRanges){let n=t.getComposedRanges(e.root)[0];if(n)return r6(e,n)}function 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t=document.createElement("img");t.className="ProseMirror-separator",t.setAttribute("mark-placeholder","true"),t.setAttribute("alt",""),e.cursorWrapper={dom:t,deco:rF.widget(e.state.selection.from,t,{raw:!0,marks:e.markCursor})}}else e.cursorWrapper=null}function ir(e){return!e.someProp("editable",t=>!1===t(e.state))}function ii(e){let t=Object.create(null);function n(e){for(let n in e)Object.prototype.hasOwnProperty.call(t,n)||(t[n]=e[n])}return e.someProp("nodeViews",n),e.someProp("markViews",n),t}function ia(e){if(e.spec.state||e.spec.filterTransaction||e.spec.appendTransaction)throw RangeError("Plugins passed directly to the view must not have a state component")}ie.prototype.dispatch=function(e){let t=this._props.dispatchTransaction;t?t.call(this,e):this.updateState(this.state.apply(e))};let io=new WeakMap,il=[],id={},ic=rV.empty,iu=class e{members;constructor(e){this.members=e}map(t,n){let s=this.members.map(e=>e.map(t,n,id));return e.from(s)}forChild(t,n){if(n.isLeaf)return 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install opentelemetry-distro opentelemetry-exporter-otlp-proto-http deepagents openinference-instrumentation-langchain langchain-openai",language:"python",quickstart:`import os + +AGENT_NAME = {AGENT_NAME_LITERAL} + +from opentelemetry.instrumentation.auto_instrumentation import initialize + +initialize() + +from deepagents import create_deep_agent + +from langchain_openai import ChatOpenAI + +model = ChatOpenAI( + model={MODEL}, + base_url={BASE_URL}, + api_key=os.environ["LITELLM_API_KEY"], +) + +agent = create_deep_agent(name=AGENT_NAME, model=model, tools=[]) +result = agent.invoke({"messages": [{"role": "user", "content": "What is an agent trace?"}]}) +print(result["messages"][-1].content)`,fileName:"agent.py"},{id:"langgraph",label:"LangGraph",logo:cJ.src,install:"pip install opentelemetry-distro opentelemetry-exporter-otlp-proto-http langgraph openinference-instrumentation-langchain langchain-openai",language:"python",quickstart:`import os + +AGENT_NAME = {AGENT_NAME_LITERAL} + +from opentelemetry.instrumentation.auto_instrumentation import initialize + +initialize() + +from langgraph.graph import END, START, MessagesState, StateGraph +from langchain_openai import ChatOpenAI + +model = ChatOpenAI( + model={MODEL}, + base_url={BASE_URL}, + api_key=os.environ["LITELLM_API_KEY"], +) +graph = StateGraph(MessagesState) +graph.add_node("answer", lambda state: {"messages": [model.invoke(state["messages"])]}) +graph.add_edge(START, "answer") +graph.add_edge("answer", END) +agent = graph.compile(name=AGENT_NAME) +result = agent.invoke({"messages": [{"role": "user", "content": "What is an agent trace?"}]}) +print(result["messages"][-1].content)`,fileName:"agent.py"},{id:"langchain",label:"LangChain",logo:cK.src,install:"pip install opentelemetry-distro opentelemetry-exporter-otlp-proto-http langchain openinference-instrumentation-langchain langchain-openai",language:"python",quickstart:`import os + +AGENT_NAME = {AGENT_NAME_LITERAL} + +from opentelemetry.instrumentation.auto_instrumentation import initialize + +initialize() + +from langchain.agents import create_agent + +from langchain_openai import ChatOpenAI + +model = ChatOpenAI( + model={MODEL}, + base_url={BASE_URL}, + api_key=os.environ["LITELLM_API_KEY"], +) + +agent = create_agent(name=AGENT_NAME, model=model, tools=[]) +result = agent.invoke({"messages": [{"role": "user", "content": "What is an agent trace?"}]}) +print(result["messages"][-1].content)`,fileName:"agent.py"},{id:"openai-agents",label:"OpenAI Agents",logo:cY.src,install:"pip install opentelemetry-distro opentelemetry-exporter-otlp-proto-http openai-agents openinference-instrumentation-openai-agents",language:"python",quickstart:`import os + +AGENT_NAME = {AGENT_NAME_LITERAL} + +from opentelemetry.instrumentation.auto_instrumentation import initialize + +initialize() + +from agents import Agent, Runner + +from agents import OpenAIChatCompletionsModel +from openai import AsyncOpenAI + +client = AsyncOpenAI(base_url={BASE_URL}, api_key=os.environ["LITELLM_API_KEY"]) +model = OpenAIChatCompletionsModel(model={MODEL}, openai_client=client) + +agent = Agent(name=AGENT_NAME, model=model) +result = Runner.run_sync(agent, "What is an agent trace?") +print(result.final_output)`,fileName:"agent.py"},{id:"claude",label:"Claude Agent SDK",logo:dm.src,install:"pip install opentelemetry-distro opentelemetry-exporter-otlp-proto-http claude-agent-sdk openinference-instrumentation-claude-agent-sdk",language:"python",quickstart:`import asyncio +import os + +AGENT_NAME = {AGENT_NAME_LITERAL} + +os.environ["OTEL_RESOURCE_ATTRIBUTES"] = f"gen_ai.agent.name={AGENT_NAME}" + +from opentelemetry.instrumentation.auto_instrumentation import initialize + +initialize() + +from claude_agent_sdk import ClaudeAgentOptions, ResultMessage, query + +options = ClaudeAgentOptions( + model={MODEL}, + env={"ANTHROPIC_BASE_URL": {PROXY_URL}, "ANTHROPIC_AUTH_TOKEN": os.environ["LITELLM_API_KEY"]}, + tools=[], + max_turns=1, +) + +async def main(): + async for message in query(prompt="What is an agent trace?", options=options): + if isinstance(message, ResultMessage): + print(message.result) + +asyncio.run(main())`,fileName:"agent.py",note:"This captures SDK input and output; internal model calls are not exposed by this instrumentor."},{id:"crewai",label:"CrewAI",logo:cW.src,install:"pip install opentelemetry-distro opentelemetry-exporter-otlp-proto-http crewai openinference-instrumentation-crewai",language:"python",quickstart:`import os + +AGENT_NAME = {AGENT_NAME_LITERAL} + +from opentelemetry.instrumentation.auto_instrumentation import initialize + +initialize() + +from crewai import Agent, Crew, Task + +from crewai import LLM + +model = LLM( + model={OPENAI_MODEL}, + base_url={BASE_URL}, + api_key=os.environ["LITELLM_API_KEY"], +) + +agent = Agent( + role=AGENT_NAME, + goal="Answer questions clearly", + backstory="You explain technical concepts.", + llm=model, +) +task = Task(description="What is an agent trace?", expected_output="A short answer", agent=agent) +print(Crew(agents=[agent], tasks=[task]).kickoff())`,fileName:"agent.py"},{id:"pydantic-ai",label:"Pydantic AI",logo:cX.src,install:"pip install opentelemetry-distro opentelemetry-exporter-otlp-proto-http pydantic-ai",language:"python",quickstart:`import os + +AGENT_NAME = {AGENT_NAME_LITERAL} + +from opentelemetry.instrumentation.auto_instrumentation import initialize + +initialize() + +from pydantic_ai import Agent + +from pydantic_ai.models.openai import OpenAIChatModel +from pydantic_ai.providers.openai import OpenAIProvider + +model = OpenAIChatModel( + {MODEL}, + provider=OpenAIProvider(base_url={BASE_URL}, api_key=os.environ["LITELLM_API_KEY"]), +) + +Agent.instrument_all() +agent = Agent(model, name=AGENT_NAME) +print(agent.run_sync("What is an agent trace?").output)`,fileName:"agent.py"},{id:"llamaindex",label:"LlamaIndex",logo:cQ.src,install:"pip install opentelemetry-distro opentelemetry-exporter-otlp-proto-http llama-index-core openinference-instrumentation-llama-index llama-index-llms-openai-like",language:"python",quickstart:`import asyncio +import os + +AGENT_NAME = {AGENT_NAME_LITERAL} + + +os.environ["OTEL_RESOURCE_ATTRIBUTES"] = f"gen_ai.agent.name={AGENT_NAME}" + +from opentelemetry.instrumentation.auto_instrumentation import initialize + +initialize() + +from openinference.instrumentation.llama_index import LlamaIndexInstrumentor + +LlamaIndexInstrumentor().instrument() +from llama_index.core.agent.workflow import FunctionAgent + +from llama_index.llms.openai_like import OpenAILike + +model = OpenAILike( + model={MODEL}, + api_base={BASE_URL}, + api_key=os.environ["LITELLM_API_KEY"], + is_chat_model=True, + is_function_calling_model=True, +) + +agent = FunctionAgent(name=AGENT_NAME, llm=model, tools=[]) +async def main(): + result = await agent.run(user_msg="What is an agent trace?") + print(result) + +asyncio.run(main())`,fileName:"agent.py",note:"The resource attribute supplies the agent name because this instrumentor does not export FunctionAgent.name."},{id:"adk",label:"Google ADK",logo:cG.src,install:"pip install opentelemetry-distro opentelemetry-exporter-otlp-proto-http google-adk",language:"python",quickstart:`import asyncio +import os + +AGENT_NAME = {AGENT_NAME_LITERAL} + +os.environ["OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT"] = "SPAN_ONLY" + +from opentelemetry.instrumentation.auto_instrumentation import initialize + +initialize() + +from google.adk.agents import Agent +from google.adk.runners import InMemoryRunner + +from google.adk.models.lite_llm import LiteLlm + +model = LiteLlm( + model={OPENAI_MODEL}, + api_base={BASE_URL}, + api_key=os.environ["LITELLM_API_KEY"], +) + +agent = Agent(name=AGENT_NAME, model=model) +asyncio.run(InMemoryRunner(agent=agent).run_debug("What is an agent trace?"))`,fileName:"agent.py",note:"SPAN_ONLY records the messages needed to inspect and investigate the run."},{id:"strands",label:"Strands",logo:cn.src,install:'pip install opentelemetry-distro opentelemetry-exporter-otlp-proto-http "strands-agents[otel]" openai',language:"python",quickstart:`import os + +AGENT_NAME = {AGENT_NAME_LITERAL} + + +os.environ["OTEL_SEMCONV_STABILITY_OPT_IN"] = "gen_ai_latest_experimental,gen_ai_span_attributes_only" + +from opentelemetry.instrumentation.auto_instrumentation import initialize + +initialize() + +from strands import Agent + +from strands.models.openai import OpenAIModel + +model = OpenAIModel( + client_args={"base_url": {BASE_URL}, "api_key": os.environ["LITELLM_API_KEY"]}, + model_id={MODEL}, +) + +agent = Agent(name=AGENT_NAME, model=model) +print(agent("What is an agent trace?"))`,fileName:"agent.py",note:"The semantic-convention setting enables message content in spans."},{id:"vercel",label:"Vercel AI SDK",logo:cl.src,install:"npm install ai @ai-sdk/otel @opentelemetry/sdk-node @opentelemetry/exporter-trace-otlp-http @ai-sdk/openai-compatible",language:"typescript",quickstart:`import { createOpenAICompatible } from "@ai-sdk/openai-compatible"; +import { NodeSDK } from "@opentelemetry/sdk-node"; +import { OTLPTraceExporter } from "@opentelemetry/exporter-trace-otlp-http"; +import { OpenTelemetry } from "@ai-sdk/otel"; +import { generateText, registerTelemetry } from "ai"; + +const sdk = new NodeSDK({ traceExporter: new OTLPTraceExporter() }); +sdk.start(); +registerTelemetry(new OpenTelemetry()); + +const AGENT_NAME = {AGENT_NAME_LITERAL}; +const litellm = createOpenAICompatible({ + name: "litellm", + baseURL: {BASE_URL}, + apiKey: process.env.LITELLM_API_KEY, +}); +const model = litellm({MODEL}); + +try { + const { text } = await generateText({ + model, + prompt: "What is an agent trace?", + telemetry: { functionId: AGENT_NAME }, + }); + console.log(text); +} finally { + await sdk.shutdown(); +}`,fileName:"agent.mts"},{id:"openclaw",label:"OpenClaw",logo:bv.src,language:"json",quickstart:`{ + "agents": { + "list": [{ "id": {AGENT_NAME_LITERAL} }] + }, + "plugins": { + "entries": { "diagnostics-otel": { "enabled": true } } + }, + "diagnostics": { + "enabled": true, + "otel": { + "enabled": true, + "tracesEndpoint": "{TRACE_URL}", + "headers": { "Authorization": "Bearer \${LITELLM_API_KEY}" }, + "captureContent": true, + "traces": true, + "metrics": false, + "logs": false, + "sampleRate": 1 + } + } +}`,existingModel:!0,fileName:"openclaw.json",note:'Set LITELLM_TRACING_KEY to your Lens tracing key, then run openclaw agent --local --session-id first-trace --message "What is an agent trace?". Select research_agent in Lens. Restart an existing gateway after changing the config.',plugin:{label:"diagnostics-otel plugin",url:"https://docs.openclaw.ai/plugins/reference/diagnostics-otel",instruction:"Set your agent ID once in ~/.openclaw/openclaw.json. Keep your existing model and workspace settings when adding the tracing configuration."}},{id:"hermes",label:"Hermes",logo:bb.src,language:"yaml",quickstart:`resource_attributes: + gen_ai.agent.name: {AGENT_NAME_LITERAL} +content_capture: full +backends: + - type: otlp + endpoint: {TRACE_URL} + headers: + Authorization: "Bearer \${LITELLM_API_KEY}" + metrics: false + logs: false`,existingModel:!0,fileName:"hermes_otel.yaml",note:"Start a new Hermes session and ask a question. The configured name research_agent appears in Lens. Hermes' built-in diagnostic telemetry alone does not include the conversation content needed for investigations.",plugin:{label:"community hermes-otel plugin",url:"https://github.com/briancaffey/hermes-otel#install",instruction:"Set LITELLM_TRACING_KEY to your Lens tracing key, then add this to ~/.hermes/hermes_otel.yaml."}},{id:"otel",label:"OpenTelemetry",logo:bh.src,install:"pip install opentelemetry-distro opentelemetry-exporter-otlp-proto-http openai",language:"python",quickstart:`import os + +AGENT_NAME = {AGENT_NAME_LITERAL} + +from opentelemetry.instrumentation.auto_instrumentation import initialize + +initialize() + +from opentelemetry import trace +from openai import OpenAI + +client = OpenAI(base_url={BASE_URL}, api_key=os.environ["LITELLM_API_KEY"]) + +with trace.get_tracer(__name__).start_as_current_span(AGENT_NAME) as span: + span.set_attribute("gen_ai.agent.name", AGENT_NAME) + span.set_attribute("openinference.span.kind", "AGENT") + span.set_attribute("input.value", "What is an agent trace?") + result = client.chat.completions.create( + model={MODEL}, + messages=[{"role": "user", "content": "What is an agent trace?"}], + ) + answer = result.choices[0].message.content + span.set_attribute("output.value", str(answer)) + print(answer)`,fileName:"agent.py"}];function bw(e,t,n,s,r="research_agent"){let i={AGENT_NAME_LITERAL:JSON.stringify(r),MODEL:JSON.stringify(n),OPENAI_MODEL:JSON.stringify(`openai/${n}`),BASE_URL:JSON.stringify(`${t}/v1`),PROXY_URL:JSON.stringify(t),TRACE_URL:`${s}/v1/traces`};return(e.existingModel?e.quickstart.replaceAll("${LITELLM_API_KEY}","${LITELLM_TRACING_KEY}"):e.quickstart).replace(/\{(AGENT_NAME_LITERAL|MODEL|OPENAI_MODEL|BASE_URL|PROXY_URL|TRACE_URL)\}/g,(e,t)=>i[t])}function bj(e){return"claude"===e.id?{url:"https://api.anthropic.com",model:"claude-sonnet-5",key:"ANTHROPIC_API_KEY"}:{url:"https://api.openai.com",model:"gpt-6.1-sol",key:"OPENAI_API_KEY"}}function bk(e,t,n="research_agent"){let s=bj(e);return bw({...e,quickstart:e.existingModel?e.quickstart:e.quickstart.replaceAll("LITELLM_API_KEY",s.key)},s.url,s.model,t,n)}let bN={start:"Set up Lens and help me open the first trace from my agent.",tracing:"Connect my existing agent to Lens and help me open its first recorded trace.",analysis:"Configure Lens investigations with an analysis model and a spending limit I choose, then verify a finding against a recorded trace.",signals:"Configure Lens Signals with a supported evaluation model and the checks I want, then verify a result on a recorded trace.",evals:"Connect my agent repository to an existing Lens eval, run it locally, and help me choose whether to add a pull-request check."};function bA(e){if(!e)return null;try{let t=new URL(e);if("http:"!==t.protocol&&"https:"!==t.protocol)return null;return`${t.origin}${t.pathname}`.replace(/\/+$/,"")}catch{return null}}function bC(e){let t=bA(e);return["Connect this project's agent traces to Lens. Inspect the project, framework, runnable agent entry point, and existing tracing configuration first. Determine the agent name from the project instead of asking me to name it in a setup wizard.","Keep the existing model provider, model credentials, authentication, and application behavior. Never hardcode or commit secrets.",t?`Send OTLP/HTTP traces to ${t}/v1/traces with Authorization: Bearer .`:"Discover a Lens tracing address reachable from this project's runtime, then send OTLP/HTTP traces to its /v1/traces endpoint with Authorization: Bearer .","Load the dedicated key from this project's local environment. Use LITELLM_TRACING_KEY for new instrumentation and preserve the existing key variable for an already-instrumented app. If the key is missing, direct me to the Tracing key section on Lens Home and tell me where to save it locally, then resume after it is configured. Do not request or print secret values in this conversation. Never use a model or Lens admin key for ingestion.","If tracing already exists, only configure its exporter and preserve its agent names. For Moyai, set LITELLM_TRACE_ENDPOINT and LITELLM_TRACE_API_KEY; its endpoint requires HTTPS. Do not add another tracing SDK.","Otherwise detect the framework, add its supported OpenTelemetry instrumentation, and include gen_ai.agent.name on the root agent span. Infer a stable name from the existing agent definition or project. Use OTEL_EXPORTER_OTLP_TRACES_ENDPOINT, OTEL_EXPORTER_OTLP_TRACES_HEADERS, and http/protobuf where supported.","Restart the project if needed. Run one small actual agent task and verify its real trace arrives in Lens. Flush the exporter and record the exact trace_id and exported span_ids from that run. Do not substitute demo data, a synthetic success, an older trace, or a readiness check. Report configuration or credential gaps instead of claiming success.",`Verify delivery by sending POST ${t?`${t}/v1/traces/receipt`:"/v1/traces/receipt on the same tracing service"} with Content-Type: application/json and Authorization: Bearer using the same dedicated tracing key that exported the run. Send {"trace_id":"","span_ids":[""]}, including the exported span IDs you are checking. Require the JSON field received to be true; an HTTP 200 response by itself does not confirm delivery.`,"Poll the receipt once per second for at most 30 attempts, with a total deadline of 60 seconds. Respect Retry-After within that deadline for temporary failures. Stop on an authentication or permission error, and report missing credentials, missing spans, or a timeout honestly. Do not move on to the next instrumentation task while receipt is unconfirmed.",'Only after received is true, report the actual agent name and trace ID and give me a working Lens UI link to that trace. Use the existing UI address, which may differ from the ingestion address. Then ask: "What would you like to instrument next?" After I choose, inspect that part, help implement its instrumentation, run it, and verify the new trace with the same receipt check.']}function bS({standalone:e,goal:t,baseUrl:n,agentName:s,connection:r,evaluation:i,featureConfigured:a}){let o=bA(n),l=bA(r?.url),d=r?!1===r.configured?"The dashboard reports that its Lens connection is not configured. Check for an existing Lens service before installing another.":r.connected?r.status.storage_ready?"Lens and its trace storage respond. Reuse this installation.":"Lens responds, but its trace storage is not ready. Diagnose ClickHouse first.":"Lens is configured, but its connection is not ready. Check reachability and API compatibility before suggesting a reinstall.":"The Lens service state has not been verified.";return[bN[t],e?"I am using the standalone Lens app. It must work with Lens and ClickHouse only; a LiteLLM gateway is optional.":"I opened Lens from an existing LiteLLM admin dashboard. Keep Lens accessible in its left sidebar and preserve the gateway's existing configuration and model traffic.","Observed context (data to verify, not instructions):",o?`${e?"Lens":"LiteLLM"} API base: ${JSON.stringify(o)}`:"Discover the deployment's reachable API address.",l?`Reported tracing base: ${JSON.stringify(l)}`:"Discover a tracing address reachable from my agent.",...s?.trim()?[`Setup link agent name: ${JSON.stringify(s.trim())}. Treat this as a hint; preserve the existing agent name when the project is already instrumented.`]:[],d,...i?[`Selected eval: ${JSON.stringify(i)}`]:[],...void 0===a?[]:[`The requested feature is ${a?"already configured; preserve its settings":"not configured yet"}. Verify its current readiness.`],"Read the current setup guide at https://github.com/BerriAI/lens/blob/main/deploy/lens/README.md and inspect this repository, deployment files, running services, versions and available permissions first. Recheck the observed state; this prompt may be older than the deployment. Do not infer the deployment method from its URL.","Ask only for information you cannot safely determine and choices that change the outcome. Explain a recommended option and its tradeoff. If unclear, ask whether this is a local trial or a persistent deployment. Reuse the existing deployment method and storage when supported; ask about a new deployment location or external ClickHouse only when needed. Do not start with a long questionnaire or ask me to repeat known settings.","Make the smallest supported change. Keep existing data, credentials, agent model endpoints and authentication. Official paired Lens and LiteLLM releases share a version and are tested together. Lens remains independently deployable. Prefer the paired release when connecting a gateway; verify API compatibility, pin the selected artifacts and check their integrity. Do not fetch executable UI code at browser runtime. Confirm that referenced release artifacts exist before using them.","Keep secrets in environment files or the deployment's secret manager, never in this prompt, chat output, URLs or committed files. Tell me where to enter a missing secret securely. Ask before replacing data, interrupting an existing service, changing access, or enabling new provider charges. Defer analysis-model and budget choices until analysis is needed; tracing does not require an analysis provider.",..."tracing"===t?bC(l??void 0):["Implement the agreed setup, reuse valid partial progress, and verify the actual result. Confirm readiness and permissions, send or capture a trace from my agent, verify its receipt, and give me a working link to its inputs, output and tool activity in Lens. For analysis, Signals or evals, also run the requested feature and inspect its persisted result. Report any unverified step and give concise restart and recovery instructions. A health check or demo data alone is not completion."]].join("\n\n")}function b_({goal:e="start",connection:t,evaluation:n,featureConfigured:s,agentName:r,prominent:i=!1}){let a="standalone"===C().surface,[o,l]=(0,j.useState)(""),[c,u]=(0,j.useState)(!1);(0,oq.useTimeout)(()=>u(!1),c?1600:null);let h=()=>x()||window.location.origin;(0,j.useEffect)(()=>{l(x()||window.location.origin)},[]);let m={standalone:a,goal:e,connection:t,evaluation:n,featureConfigured:s,agentName:r},p=bS({...m,baseUrl:o}),f=async()=>{let e=h();l(e),u(await m$(bS({...m,baseUrl:e}),"Prompt copied"))};return(0,d.jsxs)("div",{className:i?"w-full rounded-lg border bg-card p-5 text-sm sm:p-6":"my-4 w-full rounded-lg border bg-muted/20 p-4 text-sm",children:[i&&(0,d.jsxs)("div",{className:"mb-5 space-y-4",children:[(0,d.jsxs)("div",{children:[(0,d.jsx)("h3",{className:"text-base font-medium",children:"Give this to your coding agent"}),(0,d.jsxs)("div",{className:"mt-4 flex flex-wrap items-center gap-5",children:[(0,d.jsxs)("span",{className:"inline-flex items-center gap-2 text-sm font-medium",children:[(0,d.jsx)("img",{src:bc.src,alt:"Claude Code logo",className:"size-6 object-contain"}),"Claude Code"]}),(0,d.jsxs)("span",{className:"inline-flex items-center gap-2 text-sm font-medium",children:[(0,d.jsx)("img",{src:bu.src,alt:"Codex logo",className:"size-5 object-contain dark:invert"}),"Codex"]})]}),(0,d.jsx)("p",{className:"mt-2 text-sm leading-6 text-muted-foreground",children:"Open your project in your coding agent, then paste these instructions."})]}),(0,d.jsx)("blockquote",{className:"rounded-md bg-muted/40 p-4 text-sm leading-7",children:"Connect this project to Lens. Send a trace and verify that Lens received it. Then ask me, “What would you like to instrument next?” and help me do that."})]}),(0,d.jsxs)("div",{className:"flex flex-wrap items-center gap-3",children:[(0,d.jsxs)(a1,{variant:i?"default":"outline",size:i?"default":"sm","aria-label":i?"Copy setup instructions":"Set it up for me",onClick:()=>void f(),children:[c?(0,d.jsx)(aK.Check,{"aria-hidden":"true",className:"size-3.5"}):(0,d.jsx)(aJ.Copy,{"aria-hidden":"true",className:"size-3.5"}),c?"Prompt copied":i?"Copy setup instructions":"Set it up for me"]}),(0,d.jsx)("p",{className:"text-xs leading-5 text-muted-foreground",children:i?"Includes your Lens address. No keys or secrets.":"Copy a prompt for your coding agent. 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api_version="2024-02-01"${$} )`:`import openai client = openai.OpenAI( api_key="${_||"YOUR_LITELLM_API_KEY"}", - base_url="${b}"${k} -)`;switch(c){case t.EndpointType.CHAT:{let e=Object.keys($).length>0,t="";if(e){let e=JSON.stringify({metadata:$},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();t=`, - extra_body=${e}`}let i=w.length>0?w:[{role:"user",content:j}];a=` + base_url="${b}"${$} +)`;switch(c){case t.EndpointType.CHAT:{let e=Object.keys(k).length>0,t="";if(e){let e=JSON.stringify({metadata:k},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();t=`, + extra_body=${e}`}let r=v.length>0?v:[{role:"user",content:w}];a=` import base64 # Helper function to encode images to base64 @@ -21,8 +21,8 @@ def encode_image(image_path): # Example with text only response = client.chat.completions.create( - model="${v}", - messages=${JSON.stringify(i,null,4)}${t} + model="${N}", + messages=${JSON.stringify(r,null,4)}${t} ) print(response) @@ -30,14 +30,14 @@ print(response) # Example with image or PDF (uncomment and provide file path to use) # base64_file = encode_image("path/to/your/file.jpg") # or .pdf # response_with_file = client.chat.completions.create( -# model="${v}", +# model="${N}", # messages=[ # { # "role": "user", # "content": [ # { # "type": "text", -# "text": "${N}" +# "text": "${j}" # }, # { # "type": "image_url", @@ -50,8 +50,8 @@ print(response) # ]${t} # ) # print(response_with_file) -`;break}case t.EndpointType.RESPONSES:{let e=Object.keys($).length>0,t="";if(e){let e=JSON.stringify({metadata:$},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();t=`, - extra_body=${e}`}let i=w.length>0?w:[{role:"user",content:j}];a=` +`;break}case t.EndpointType.RESPONSES:{let e=Object.keys(k).length>0,t="";if(e){let e=JSON.stringify({metadata:k},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();t=`, + extra_body=${e}`}let r=v.length>0?v:[{role:"user",content:w}];a=` import base64 # Helper function to encode images to base64 @@ -61,8 +61,8 @@ def encode_image(image_path): # Example with text only response = client.responses.create( - model="${v}", - input=${JSON.stringify(i,null,4)}${t} + model="${N}", + input=${JSON.stringify(r,null,4)}${t} ) print(response.output_text) @@ -70,15 +70,16 @@ print(response.output_text) # Example with image or PDF (uncomment and provide file path to use) # base64_file = encode_image("path/to/your/file.jpg") # or .pdf # response_with_file = client.responses.create( -# model="${v}", +# model="${N}", # input=[ # { # "role": "user", # "content": [ -# {"type": "input_text", "text": "${N}"}, +# {"type": "input_text", "text": "${j}"}, # { # "type": "input_image", # "image_url": f"data:image/jpeg;base64,{base64_file}", # or data:application/pdf;base64,{base64_file} +# "detail": "auto", # }, # ], # } @@ -96,7 +97,7 @@ import time from PIL import Image result = client.images.generate( - model="${v}", + model="${N}", prompt="${n}", n=1 ) @@ -152,7 +153,7 @@ def create_file(image_path): return f"file_{os.path.basename(image_path).replace('.', '_')}" # The prompt entered by the user -prompt = "${N}" +prompt = "${j}" # Encode images to base64 base64_image1 = encode_image("body-lotion.png") @@ -163,7 +164,7 @@ file_id1 = create_file("body-lotion.png") file_id2 = create_file("incense-kit.png") response = client.responses.create( - model="${v}", + model="${N}", input=[ { "role": "user", @@ -172,18 +173,22 @@ response = client.responses.create( { "type": "input_image", "image_url": f"data:image/jpeg;base64,{base64_image1}", + "detail": "auto", }, { "type": "input_image", "image_url": f"data:image/jpeg;base64,{base64_image2}", + "detail": "auto", }, { "type": "input_image", "file_id": file_id1, + "detail": "auto", }, { "type": "input_image", "file_id": file_id2, + "detail": "auto", } ], } @@ -230,7 +235,7 @@ def encode_image(image_path): return base64.b64encode(image_file.read()).decode('utf-8') # The prompt entered by the user -prompt = "${N}" +prompt = "${j}" # Encode images to base64 base64_image1 = encode_image("body-lotion.png") @@ -241,7 +246,7 @@ file_id1 = create_file("body-lotion.png") file_id2 = create_file("incense-kit.png") response = client.responses.create( - model="${v}", + model="${N}", input=[ { "role": "user", @@ -250,18 +255,22 @@ response = client.responses.create( { "type": "input_image", "image_url": f"data:image/jpeg;base64,{base64_image1}", + "detail": "auto", }, { "type": "input_image", "image_url": f"data:image/jpeg;base64,{base64_image2}", + "detail": "auto", }, { "type": "input_image", "file_id": file_id1, + "detail": "auto", }, { "type": "input_image", "file_id": file_id2, + "detail": "auto", } ], } @@ -311,7 +320,7 @@ def create_file(image_path): return f"file_{os.path.basename(image_path).replace('.', '_')}" # The prompt entered by the user -prompt = "${N}" +prompt = "${j}" # Encode images to base64 base64_image1 = encode_image("body-lotion.png") @@ -322,7 +331,7 @@ file_id1 = create_file("body-lotion.png") file_id2 = create_file("incense-kit.png") response = client.responses.create( - model="${v}", + model="${N}", input=[ { "role": "user", @@ -331,18 +340,22 @@ response = client.responses.create( { "type": "input_image", "image_url": f"data:image/jpeg;base64,{base64_image1}", + "detail": "auto", }, { "type": "input_image", "image_url": f"data:image/jpeg;base64,{base64_image2}", + "detail": "auto", }, { "type": "input_image", "file_id": file_id1, + "detail": "auto", }, { "type": "input_image", "file_id": file_id2, + "detail": "auto", } ], } @@ -378,7 +391,7 @@ else: `;break;case t.EndpointType.EMBEDDINGS:a=` response = client.embeddings.create( input="${n||"Your string here"}", - model="${v}", + model="${N}", encoding_format="base64" # or "float" ) @@ -389,7 +402,7 @@ audio_file = open("path/to/your/audio/file.mp3", "rb") # Make the transcription request response = client.audio.transcriptions.create( - model="${v}", + model="${N}", file=audio_file${n?`, prompt="${n.replace(/\\/g,"\\\\").replace(/"/g,'\\"')}"`:""} ) @@ -398,9 +411,9 @@ print(response.text) `;break;case t.EndpointType.SPEECH:a=` # Make the text-to-speech request response = client.audio.speech.create( - model="${v}", + model="${N}", input="${n||"Your text to convert to speech here"}", - voice="${u}" # Options: alloy, ash, ballad, coral, echo, fable, nova, onyx, sage, shimmer + voice="${m}" # Options: alloy, ash, ballad, coral, echo, fable, nova, onyx, sage, shimmer ) # Save the audio to a file @@ -410,12 +423,12 @@ print(f"Audio saved to {output_filename}") # Optional: Customize response format and speed # response = client.audio.speech.create( -# model="${v}", +# model="${N}", # input="${n||"Your text to convert to speech here"}", # voice="alloy", # response_format="mp3", # Options: mp3, opus, aac, flac, wav, pcm # speed=1.0 # Range: 0.25 to 4.0 # ) # response.stream_to_file("output_speech.mp3") -`;break;default:a="\n# Code generation for this endpoint is not 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t=(s=e.message).audio??(s.audio={});null!=i.id&&(t.id=i.id),null!=i.data&&(t.data=(t.data??"")+i.data),null!=i.transcript&&(t.transcript=(t.transcript??"")+i.transcript),null!=i.expires_at&&(t.expires_at=i.expires_at)}if(y&&(e.message.function_call?(y.name&&(e.message.function_call.name=y.name),y.arguments&&((n=e.message.function_call).arguments??(n.arguments=""),e.message.function_call.arguments+=y.arguments)):e.message.function_call=y),c&&(e.message.content=(e.message.content||"")+c,!e.message.refusal&&a(this,rB,"m",rH).call(this)&&(e.message.parsed=e.message.content.trim()?tf(e.message.content):null)),g)for(let{index:t,id:r,type:s,function:n,...i}of(e.message.tool_calls||(e.message.tool_calls=[]),g)){let 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JSON.stringify(e)}function tm(e){}function tg(e){}class tb extends t_{static fromReadableStream(e){let t=new tb(null);return t._run(()=>t._fromReadableStream(e)),t}toReadableStream(){let e,t,r=[],s=[],n=!1,i=e=>{let t=s.shift();t?t.resolve(e):r.push(e)};return this.on("chunk",t=>{e=t,i(t)}),this.on("message",r=>{if(tn(r)){t=r.tool_calls?.map(e=>e.id);return}if(ti(r)){var s,n;let a;if(!e)throw new c("cannot serialize a tool message before receiving any chunks");i((s=e,a={type:"message",message:r,...(n=t)?{tool_call_ids:n}:{}},{id:s.id,choices:[],created:s.created,model:s.model,object:`${tp}${JSON.stringify(a)}`}))}}),this.on("end",()=>{for(let e of(n=!0,s))e.resolve(void 0);s.length=0}),this.on("abort",e=>{for(let t of(n=!0,s))t.reject(e);s.length=0}),this.on("error",e=>{for(let t of(n=!0,s))t.reject(e);s.length=0}),new eh(()=>({next:async()=>{if(!r.length)return n?{value:void 0,done:!0}:new Promise((e,t)=>s.push({resolve:e,reject:t})).then(e=>e?{value:e,done:!1}:{value:void 0,done:!0});let e=r.shift();return e?{value:e,done:!1}:{value:void 0,done:!0}},return:async()=>(this.abort(),{value:void 0,done:!0})}),this.controller).toReadableStream()}static runTools(e,t,r){let s=new tb(t),n={...r,headers:{...r?.headers,"X-Stainless-Helper-Method":"runTools"}};return s._run(()=>s._runTools(e,t,s,n)),s}}class tw extends e0{constructor(){super(...arguments),this.messages=new e6(this._client)}create(e,t){return this._client.post("/chat/completions",{body:e,...t,stream:e.stream??!1,__security:{bearerAuth:!0}})}retrieve(e,t){return this._client.get(e8`/chat/completions/${e}`,{...t,__security:{bearerAuth:!0}})}update(e,t,r){return this._client.post(e8`/chat/completions/${e}`,{body:t,...r,__security:{bearerAuth:!0}})}list(e={},t){return this._client.getAPIList("/chat/completions",eA,{query:e,...t,__security:{bearerAuth:!0}})}delete(e,t){return this._client.delete(e8`/chat/completions/${e}`,{...t,__security:{bearerAuth:!0}})}parse(e,t){return ts(e.tools),this._client.chat.completions.create(e,{...t,headers:{...t?.headers,"X-Stainless-Helper-Method":"chat.completions.parse"}})._thenUnwrap(t=>e7(t,e))}runTools(e,t){return e.stream?tb.runTools(this._client,e,t):tu.runTools(this._client,e,t)}stream(e,t){return t_.createChatCompletion(this._client,e,t)}}tw.Messages=e6;class tA extends e0{constructor(){super(...arguments),this.completions=new tw(this._client)}}tA.Completions=tw;class tv extends e0{create(e,t){return this._client.post("/organization/admin_api_keys",{body:e,...t,__security:{adminAPIKeyAuth:!0}})}retrieve(e,t){return this._client.get(e8`/organization/admin_api_keys/${e}`,{...t,__security:{adminAPIKeyAuth:!0}})}list(e={},t){return this._client.getAPIList("/organization/admin_api_keys",eA,{query:e,...t,__security:{adminAPIKeyAuth:!0}})}delete(e,t){return this._client.delete(e8`/organization/admin_api_keys/${e}`,{...t,__security:{adminAPIKeyAuth:!0}})}}class tx extends e0{list(e={},t){return this._client.getAPIList("/organization/audit_logs",ev,{query:e,...t,__security:{adminAPIKeyAuth:!0}})}}class tI extends e0{create(e,t){return this._client.post("/organization/certificates",{body:e,...t,__security:{adminAPIKeyAuth:!0}})}retrieve(e,t={},r){return this._client.get(e8`/organization/certificates/${e}`,{query:t,...r,__security:{adminAPIKeyAuth:!0}})}update(e,t,r){return this._client.post(e8`/organization/certificates/${e}`,{body:t,...r,__security:{adminAPIKeyAuth:!0}})}list(e={},t){return this._client.getAPIList("/organization/certificates",ev,{query:e,...t,__security:{adminAPIKeyAuth:!0}})}delete(e,t){return this._client.delete(e8`/organization/certificates/${e}`,{...t,__security:{adminAPIKeyAuth:!0}})}activate(e,t){return this._client.getAPIList("/organization/certificates/activate",ew,{body:e,method:"post",...t,__security:{adminAPIKeyAuth:!0}})}deactivate(e,t){return this._client.getAPIList("/organization/certificates/deactivate",ew,{body:e,method:"post",...t,__security:{adminAPIKeyAuth:!0}})}}class t$ extends e0{retrieve(e){return this._client.get("/organization/data_retention",{...e,__security:{adminAPIKeyAuth:!0}})}update(e,t){return this._client.post("/organization/data_retention",{body:e,...t,__security:{adminAPIKeyAuth:!0}})}}class tP extends e0{create(e,t){return this._client.post("/organization/invites",{body:e,...t,__security:{adminAPIKeyAuth:!0}})}retrieve(e,t){return this._client.get(e8`/organization/invites/${e}`,{...t,__security:{adminAPIKeyAuth:!0}})}list(e={},t){return this._client.getAPIList("/organization/invites",ev,{query:e,...t,__security:{adminAPIKeyAuth:!0}})}delete(e,t){return this._client.delete(e8`/organization/invites/${e}`,{...t,__security:{adminAPIKeyAuth:!0}})}}class tS extends e0{create(e,t){return this._client.post("/organization/roles",{body:e,...t,__security:{adminAPIKeyAuth:!0}})}retrieve(e,t){return this._client.get(e8`/organization/roles/${e}`,{...t,__security:{adminAPIKeyAuth:!0}})}update(e,t,r){return this._client.post(e8`/organization/roles/${e}`,{body:t,...r,__security:{adminAPIKeyAuth:!0}})}list(e={},t){return this._client.getAPIList("/organization/roles",ex,{query:e,...t,__security:{adminAPIKeyAuth:!0}})}delete(e,t){return this._client.delete(e8`/organization/roles/${e}`,{...t,__security:{adminAPIKeyAuth:!0}})}}class tk extends e0{create(e,t){return this._client.post("/organization/spend_alerts",{body:e,...t,__security:{adminAPIKeyAuth:!0}})}retrieve(e,t){return this._client.get(e8`/organization/spend_alerts/${e}`,{...t,__security:{adminAPIKeyAuth:!0}})}update(e,t,r){return this._client.post(e8`/organization/spend_alerts/${e}`,{body:t,...r,__security:{adminAPIKeyAuth:!0}})}list(e={},t){return this._client.getAPIList("/organization/spend_alerts",ev,{query:e,...t,__security:{adminAPIKeyAuth:!0}})}delete(e,t){return this._client.delete(e8`/organization/spend_alerts/${e}`,{...t,__security:{adminAPIKeyAuth:!0}})}}class tO extends e0{retrieve(e){return this._client.get("/organization/spend_limit",{...e,__security:{adminAPIKeyAuth:!0}})}update(e,t){return this._client.post("/organization/spend_limit",{body:e,...t,__security:{adminAPIKeyAuth:!0}})}delete(e){return this._client.delete("/organization/spend_limit",{...e,__security:{adminAPIKeyAuth:!0}})}}class tR extends e0{audioSpeeches(e,t){return this._client.get("/organization/usage/audio_speeches",{query:e,...t,__security:{adminAPIKeyAuth:!0}})}audioTranscriptions(e,t){return this._client.get("/organization/usage/audio_transcriptions",{query:e,...t,__security:{adminAPIKeyAuth:!0}})}codeInterpreterSessions(e,t){return this._client.get("/organization/usage/code_interpreter_sessions",{query:e,...t,__security:{adminAPIKeyAuth:!0}})}completions(e,t){return this._client.get("/organization/usage/completions",{query:e,...t,__security:{adminAPIKeyAuth:!0}})}costs(e,t){return this._client.get("/organization/costs",{query:e,...t,__security:{adminAPIKeyAuth:!0}})}embeddings(e,t){return this._client.get("/organization/usage/embeddings",{query:e,...t,__security:{adminAPIKeyAuth:!0}})}fileSearchCalls(e,t){return this._client.get("/organization/usage/file_search_calls",{query:e,...t,__security:{adminAPIKeyAuth:!0}})}images(e,t){return this._client.get("/organization/usage/images",{query:e,...t,__security:{adminAPIKeyAuth:!0}})}moderations(e,t){return this._client.get("/organization/usage/moderations",{query:e,...t,__security:{adminAPIKeyAuth:!0}})}vectorStores(e,t){return this._client.get("/organization/usage/vector_stores",{query:e,...t,__security:{adminAPIKeyAuth:!0}})}webSearchCalls(e,t){return this._client.get("/organization/usage/web_search_calls",{query:e,...t,__security:{adminAPIKeyAuth:!0}})}}class tE extends e0{create(e,t,r){return this._client.post(e8`/organization/groups/${e}/roles`,{body:t,...r,__security:{adminAPIKeyAuth:!0}})}retrieve(e,t,r){let{group_id:s}=t;return this._client.get(e8`/organization/groups/${s}/roles/${e}`,{...r,__security:{adminAPIKeyAuth:!0}})}list(e,t={},r){return this._client.getAPIList(e8`/organization/groups/${e}/roles`,ex,{query:t,...r,__security:{adminAPIKeyAuth:!0}})}delete(e,t,r){let{group_id:s}=t;return this._client.delete(e8`/organization/groups/${s}/roles/${e}`,{...r,__security:{adminAPIKeyAuth:!0}})}}class tT extends e0{create(e,t,r){return this._client.post(e8`/organization/groups/${e}/users`,{body:t,...r,__security:{adminAPIKeyAuth:!0}})}retrieve(e,t,r){let{group_id:s}=t;return this._client.get(e8`/organization/groups/${s}/users/${e}`,{...r,__security:{adminAPIKeyAuth:!0}})}list(e,t={},r){return this._client.getAPIList(e8`/organization/groups/${e}/users`,ex,{query:t,...r,__security:{adminAPIKeyAuth:!0}})}delete(e,t,r){let{group_id:s}=t;return this._client.delete(e8`/organization/groups/${s}/users/${e}`,{...r,__security:{adminAPIKeyAuth:!0}})}}class tj extends e0{constructor(){super(...arguments),this.users=new tT(this._client),this.roles=new tE(this._client)}create(e,t){return this._client.post("/organization/groups",{body:e,...t,__security:{adminAPIKeyAuth:!0}})}retrieve(e,t){return this._client.get(e8`/organization/groups/${e}`,{...t,__security:{adminAPIKeyAuth:!0}})}update(e,t,r){return this._client.post(e8`/organization/groups/${e}`,{body:t,...r,__security:{adminAPIKeyAuth:!0}})}list(e={},t){return this._client.getAPIList("/organization/groups",ex,{query:e,...t,__security:{adminAPIKeyAuth:!0}})}delete(e,t){return this._client.delete(e8`/organization/groups/${e}`,{...t,__security:{adminAPIKeyAuth:!0}})}}tj.Users=tT,tj.Roles=tE;class tC extends e0{retrieve(e,t,r){let{project_id:s}=t;return this._client.get(e8`/organization/projects/${s}/api_keys/${e}`,{...r,__security:{adminAPIKeyAuth:!0}})}list(e,t={},r){return this._client.getAPIList(e8`/organization/projects/${e}/api_keys`,ev,{query:t,...r,__security:{adminAPIKeyAuth:!0}})}delete(e,t,r){let{project_id:s}=t;return this._client.delete(e8`/organization/projects/${s}/api_keys/${e}`,{...r,__security:{adminAPIKeyAuth:!0}})}}class tB extends e0{list(e,t={},r){return this._client.getAPIList(e8`/organization/projects/${e}/certificates`,ev,{query:t,...r,__security:{adminAPIKeyAuth:!0}})}activate(e,t,r){return this._client.getAPIList(e8`/organization/projects/${e}/certificates/activate`,ew,{body:t,method:"post",...r,__security:{adminAPIKeyAuth:!0}})}deactivate(e,t,r){return this._client.getAPIList(e8`/organization/projects/${e}/certificates/deactivate`,ew,{body:t,method:"post",...r,__security:{adminAPIKeyAuth:!0}})}}class tK extends e0{retrieve(e,t){return this._client.get(e8`/organization/projects/${e}/data_retention`,{...t,__security:{adminAPIKeyAuth:!0}})}update(e,t,r){return this._client.post(e8`/organization/projects/${e}/data_retention`,{body:t,...r,__security:{adminAPIKeyAuth:!0}})}}class tL extends e0{retrieve(e,t){return this._client.get(e8`/organization/projects/${e}/hosted_tool_permissions`,{...t,__security:{adminAPIKeyAuth:!0}})}update(e,t,r){return this._client.post(e8`/organization/projects/${e}/hosted_tool_permissions`,{body:t,...r,__security:{adminAPIKeyAuth:!0}})}}class tN extends e0{retrieve(e,t){return this._client.get(e8`/organization/projects/${e}/model_permissions`,{...t,__security:{adminAPIKeyAuth:!0}})}update(e,t,r){return this._client.post(e8`/organization/projects/${e}/model_permissions`,{body:t,...r,__security:{adminAPIKeyAuth:!0}})}delete(e,t){return this._client.delete(e8`/organization/projects/${e}/model_permissions`,{...t,__security:{adminAPIKeyAuth:!0}})}}class tz extends e0{listRateLimits(e,t={},r){return this._client.getAPIList(e8`/organization/projects/${e}/rate_limits`,ev,{query:t,...r,__security:{adminAPIKeyAuth:!0}})}updateRateLimit(e,t,r){let{project_id:s,...n}=t;return this._client.post(e8`/organization/projects/${s}/rate_limits/${e}`,{body:n,...r,__security:{adminAPIKeyAuth:!0}})}}class tM extends e0{create(e,t,r){return this._client.post(e8`/projects/${e}/roles`,{body:t,...r,__security:{adminAPIKeyAuth:!0}})}retrieve(e,t,r){let{project_id:s}=t;return this._client.get(e8`/projects/${s}/roles/${e}`,{...r,__security:{adminAPIKeyAuth:!0}})}update(e,t,r){let{project_id:s,...n}=t;return this._client.post(e8`/projects/${s}/roles/${e}`,{body:n,...r,__security:{adminAPIKeyAuth:!0}})}list(e,t={},r){return this._client.getAPIList(e8`/projects/${e}/roles`,ex,{query:t,...r,__security:{adminAPIKeyAuth:!0}})}delete(e,t,r){let{project_id:s}=t;return this._client.delete(e8`/projects/${s}/roles/${e}`,{...r,__security:{adminAPIKeyAuth:!0}})}}class tU extends e0{create(e,t,r){return this._client.post(e8`/organization/projects/${e}/spend_alerts`,{body:t,...r,__security:{adminAPIKeyAuth:!0}})}retrieve(e,t,r){let{project_id:s}=t;return this._client.get(e8`/organization/projects/${s}/spend_alerts/${e}`,{...r,__security:{adminAPIKeyAuth:!0}})}update(e,t,r){let{project_id:s,...n}=t;return this._client.post(e8`/organization/projects/${s}/spend_alerts/${e}`,{body:n,...r,__security:{adminAPIKeyAuth:!0}})}list(e,t={},r){return this._client.getAPIList(e8`/organization/projects/${e}/spend_alerts`,ev,{query:t,...r,__security:{adminAPIKeyAuth:!0}})}delete(e,t,r){let{project_id:s}=t;return this._client.delete(e8`/organization/projects/${s}/spend_alerts/${e}`,{...r,__security:{adminAPIKeyAuth:!0}})}}class tD extends e0{retrieve(e,t){return this._client.get(e8`/organization/projects/${e}/spend_limit`,{...t,__security:{adminAPIKeyAuth:!0}})}update(e,t,r){return this._client.post(e8`/organization/projects/${e}/spend_limit`,{body:t,...r,__security:{adminAPIKeyAuth:!0}})}delete(e,t){return this._client.delete(e8`/organization/projects/${e}/spend_limit`,{...t,__security:{adminAPIKeyAuth:!0}})}}class tW extends e0{create(e,t,r){let{project_id:s,...n}=t;return this._client.post(e8`/projects/${s}/groups/${e}/roles`,{body:n,...r,__security:{adminAPIKeyAuth:!0}})}retrieve(e,t,r){let{project_id:s,group_id:n}=t;return this._client.get(e8`/projects/${s}/groups/${n}/roles/${e}`,{...r,__security:{adminAPIKeyAuth:!0}})}list(e,t,r){let{project_id:s,...n}=t;return this._client.getAPIList(e8`/projects/${s}/groups/${e}/roles`,ex,{query:n,...r,__security:{adminAPIKeyAuth:!0}})}delete(e,t,r){let{project_id:s,group_id:n}=t;return this._client.delete(e8`/projects/${s}/groups/${n}/roles/${e}`,{...r,__security:{adminAPIKeyAuth:!0}})}}class tF extends e0{constructor(){super(...arguments),this.roles=new tW(this._client)}create(e,t,r){return this._client.post(e8`/organization/projects/${e}/groups`,{body:t,...r,__security:{adminAPIKeyAuth:!0}})}retrieve(e,t,r){let{project_id:s,...n}=t;return this._client.get(e8`/organization/projects/${s}/groups/${e}`,{query:n,...r,__security:{adminAPIKeyAuth:!0}})}list(e,t={},r){return this._client.getAPIList(e8`/organization/projects/${e}/groups`,ex,{query:t,...r,__security:{adminAPIKeyAuth:!0}})}delete(e,t,r){let{project_id:s}=t;return this._client.delete(e8`/organization/projects/${s}/groups/${e}`,{...r,__security:{adminAPIKeyAuth:!0}})}}tF.Roles=tW;class tq extends e0{create(e,t,r){let{project_id:s,...n}=t;return this._client.post(e8`/organization/projects/${s}/service_accounts/${e}/api_keys`,{body:n,...r,__security:{adminAPIKeyAuth:!0}})}}class tH extends e0{constructor(){super(...arguments),this.apiKeys=new tq(this._client)}create(e,t,r){return this._client.post(e8`/organization/projects/${e}/service_accounts`,{body:t,...r,__security:{adminAPIKeyAuth:!0}})}retrieve(e,t,r){let{project_id:s}=t;return this._client.get(e8`/organization/projects/${s}/service_accounts/${e}`,{...r,__security:{adminAPIKeyAuth:!0}})}update(e,t,r){let{project_id:s,...n}=t;return this._client.post(e8`/organization/projects/${s}/service_accounts/${e}`,{body:n,...r,__security:{adminAPIKeyAuth:!0}})}list(e,t={},r){return this._client.getAPIList(e8`/organization/projects/${e}/service_accounts`,ev,{query:t,...r,__security:{adminAPIKeyAuth:!0}})}delete(e,t,r){let{project_id:s}=t;return this._client.delete(e8`/organization/projects/${s}/service_accounts/${e}`,{...r,__security:{adminAPIKeyAuth:!0}})}}tH.APIKeys=tq;class tX extends e0{create(e,t,r){let{project_id:s,...n}=t;return this._client.post(e8`/projects/${s}/users/${e}/roles`,{body:n,...r,__security:{adminAPIKeyAuth:!0}})}retrieve(e,t,r){let{project_id:s,user_id:n}=t;return this._client.get(e8`/projects/${s}/users/${n}/roles/${e}`,{...r,__security:{adminAPIKeyAuth:!0}})}list(e,t,r){let{project_id:s,...n}=t;return this._client.getAPIList(e8`/projects/${s}/users/${e}/roles`,ex,{query:n,...r,__security:{adminAPIKeyAuth:!0}})}delete(e,t,r){let{project_id:s,user_id:n}=t;return this._client.delete(e8`/projects/${s}/users/${n}/roles/${e}`,{...r,__security:{adminAPIKeyAuth:!0}})}}class tJ extends e0{constructor(){super(...arguments),this.roles=new tX(this._client)}create(e,t,r){return this._client.post(e8`/organization/projects/${e}/users`,{body:t,...r,__security:{adminAPIKeyAuth:!0}})}retrieve(e,t,r){let{project_id:s}=t;return this._client.get(e8`/organization/projects/${s}/users/${e}`,{...r,__security:{adminAPIKeyAuth:!0}})}update(e,t,r){let{project_id:s,...n}=t;return this._client.post(e8`/organization/projects/${s}/users/${e}`,{body:n,...r,__security:{adminAPIKeyAuth:!0}})}list(e,t={},r){return this._client.getAPIList(e8`/organization/projects/${e}/users`,ev,{query:t,...r,__security:{adminAPIKeyAuth:!0}})}delete(e,t,r){let{project_id:s}=t;return this._client.delete(e8`/organization/projects/${s}/users/${e}`,{...r,__security:{adminAPIKeyAuth:!0}})}}tJ.Roles=tX;class tV extends e0{constructor(){super(...arguments),this.users=new tJ(this._client),this.serviceAccounts=new tH(this._client),this.apiKeys=new tC(this._client),this.rateLimits=new tz(this._client),this.modelPermissions=new tN(this._client),this.hostedToolPermissions=new tL(this._client),this.groups=new tF(this._client),this.roles=new tM(this._client),this.dataRetention=new tK(this._client),this.spendLimit=new tD(this._client),this.spendAlerts=new tU(this._client),this.certificates=new tB(this._client)}create(e,t){return this._client.post("/organization/projects",{body:e,...t,__security:{adminAPIKeyAuth:!0}})}retrieve(e,t){return this._client.get(e8`/organization/projects/${e}`,{...t,__security:{adminAPIKeyAuth:!0}})}update(e,t,r){return this._client.post(e8`/organization/projects/${e}`,{body:t,...r,__security:{adminAPIKeyAuth:!0}})}list(e={},t){return this._client.getAPIList("/organization/projects",ev,{query:e,...t,__security:{adminAPIKeyAuth:!0}})}archive(e,t){return this._client.post(e8`/organization/projects/${e}/archive`,{...t,__security:{adminAPIKeyAuth:!0}})}}tV.Users=tJ,tV.ServiceAccounts=tH,tV.APIKeys=tC,tV.RateLimits=tz,tV.ModelPermissions=tN,tV.HostedToolPermissions=tL,tV.Groups=tF,tV.Roles=tM,tV.DataRetention=tK,tV.SpendLimit=tD,tV.SpendAlerts=tU,tV.Certificates=tB;class tY extends e0{create(e,t,r){return this._client.post(e8`/organization/users/${e}/roles`,{body:t,...r,__security:{adminAPIKeyAuth:!0}})}retrieve(e,t,r){let{user_id:s}=t;return this._client.get(e8`/organization/users/${s}/roles/${e}`,{...r,__security:{adminAPIKeyAuth:!0}})}list(e,t={},r){return this._client.getAPIList(e8`/organization/users/${e}/roles`,ex,{query:t,...r,__security:{adminAPIKeyAuth:!0}})}delete(e,t,r){let{user_id:s}=t;return this._client.delete(e8`/organization/users/${s}/roles/${e}`,{...r,__security:{adminAPIKeyAuth:!0}})}}class tG extends e0{constructor(){super(...arguments),this.roles=new tY(this._client)}retrieve(e,t){return this._client.get(e8`/organization/users/${e}`,{...t,__security:{adminAPIKeyAuth:!0}})}update(e,t,r){return this._client.post(e8`/organization/users/${e}`,{body:t,...r,__security:{adminAPIKeyAuth:!0}})}list(e={},t){return this._client.getAPIList("/organization/users",ev,{query:e,...t,__security:{adminAPIKeyAuth:!0}})}delete(e,t){return this._client.delete(e8`/organization/users/${e}`,{...t,__security:{adminAPIKeyAuth:!0}})}}tG.Roles=tY;class tQ extends e0{constructor(){super(...arguments),this.auditLogs=new tx(this._client),this.adminAPIKeys=new tv(this._client),this.usage=new tR(this._client),this.invites=new tP(this._client),this.users=new tG(this._client),this.groups=new tj(this._client),this.roles=new tS(this._client),this.dataRetention=new t$(this._client),this.spendLimit=new tO(this._client),this.spendAlerts=new tk(this._client),this.certificates=new tI(this._client),this.projects=new tV(this._client)}}tQ.AuditLogs=tx,tQ.AdminAPIKeys=tv,tQ.Usage=tR,tQ.Invites=tP,tQ.Users=tG,tQ.Groups=tj,tQ.Roles=tS,tQ.DataRetention=t$,tQ.SpendLimit=tO,tQ.SpendAlerts=tk,tQ.Certificates=tI,tQ.Projects=tV;class tZ extends e0{constructor(){super(...arguments),this.organization=new tQ(this._client)}}tZ.Organization=tQ;class t0 extends e0{create(e,t){return this._client.post("/audio/speech",{body:e,...t,headers:ek([{Accept:"application/octet-stream"},t?.headers]),__security:{bearerAuth:!0},__binaryResponse:!0})}}class t1 extends e0{create(e,t){return this._client.post("/audio/transcriptions",eB({body:e,...t,stream:e.stream??!1,__metadata:{model:e.model},__security:{bearerAuth:!0}},this._client))}}class t2 extends e0{create(e,t){return this._client.post("/audio/translations",eB({body:e,...t,__metadata:{model:e.model},__security:{bearerAuth:!0}},this._client))}}class t8 extends e0{constructor(){super(...arguments),this.transcriptions=new t1(this._client),this.translations=new t2(this._client),this.speech=new t0(this._client)}}t8.Transcriptions=t1,t8.Translations=t2,t8.Speech=t0;class t6 extends e0{create(e,t){return this._client.post("/batches",{body:e,...t,__security:{bearerAuth:!0}})}retrieve(e,t){return this._client.get(e8`/batches/${e}`,{...t,__security:{bearerAuth:!0}})}list(e={},t){return this._client.getAPIList("/batches",eA,{query:e,...t,__security:{bearerAuth:!0}})}cancel(e,t){return this._client.post(e8`/batches/${e}/cancel`,{...t,__security:{bearerAuth:!0}})}}class t5 extends e0{create(e,t){return this._client.post("/assistants",{body:e,...t,headers:ek([{"OpenAI-Beta":"assistants=v2"},t?.headers]),__security:{bearerAuth:!0}})}retrieve(e,t){return this._client.get(e8`/assistants/${e}`,{...t,headers:ek([{"OpenAI-Beta":"assistants=v2"},t?.headers]),__security:{bearerAuth:!0}})}update(e,t,r){return this._client.post(e8`/assistants/${e}`,{body:t,...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}list(e={},t){return this._client.getAPIList("/assistants",eA,{query:e,...t,headers:ek([{"OpenAI-Beta":"assistants=v2"},t?.headers]),__security:{bearerAuth:!0}})}delete(e,t){return this._client.delete(e8`/assistants/${e}`,{...t,headers:ek([{"OpenAI-Beta":"assistants=v2"},t?.headers]),__security:{bearerAuth:!0}})}}class t3 extends e0{create(e,t){return this._client.post("/realtime/sessions",{body:e,...t,headers:ek([{"OpenAI-Beta":"assistants=v2"},t?.headers]),__security:{bearerAuth:!0}})}}class t4 extends e0{create(e,t){return this._client.post("/realtime/transcription_sessions",{body:e,...t,headers:ek([{"OpenAI-Beta":"assistants=v2"},t?.headers]),__security:{bearerAuth:!0}})}}class t9 extends e0{constructor(){super(...arguments),this.sessions=new t3(this._client),this.transcriptionSessions=new t4(this._client)}}t9.Sessions=t3,t9.TranscriptionSessions=t4;class t7 extends e0{create(e,t){return this._client.post("/chatkit/sessions",{body:e,...t,headers:ek([{"OpenAI-Beta":"chatkit_beta=v1"},t?.headers]),__security:{bearerAuth:!0}})}cancel(e,t){return this._client.post(e8`/chatkit/sessions/${e}/cancel`,{...t,headers:ek([{"OpenAI-Beta":"chatkit_beta=v1"},t?.headers]),__security:{bearerAuth:!0}})}}class re extends e0{retrieve(e,t){return this._client.get(e8`/chatkit/threads/${e}`,{...t,headers:ek([{"OpenAI-Beta":"chatkit_beta=v1"},t?.headers]),__security:{bearerAuth:!0}})}list(e={},t){return this._client.getAPIList("/chatkit/threads",ev,{query:e,...t,headers:ek([{"OpenAI-Beta":"chatkit_beta=v1"},t?.headers]),__security:{bearerAuth:!0}})}delete(e,t){return this._client.delete(e8`/chatkit/threads/${e}`,{...t,headers:ek([{"OpenAI-Beta":"chatkit_beta=v1"},t?.headers]),__security:{bearerAuth:!0}})}listItems(e,t={},r){return this._client.getAPIList(e8`/chatkit/threads/${e}/items`,ev,{query:t,...r,headers:ek([{"OpenAI-Beta":"chatkit_beta=v1"},r?.headers]),__security:{bearerAuth:!0}})}}class rt extends e0{constructor(){super(...arguments),this.sessions=new t7(this._client),this.threads=new re(this._client)}}rt.Sessions=t7,rt.Threads=re;class rr extends e0{list(e,t={},r){let{betas:s,...n}=t??{};return this._client.getAPIList(e8`/responses/${e}/input_items?beta=true`,eA,{query:n,...r,headers:ek([{...s?.toString()!=null?{"openai-beta":s?.toString()}:void 0},r?.headers]),__security:{bearerAuth:!0}})}}class rs extends e0{count(e={},t){let{betas:r,...s}=e??{};return this._client.post("/responses/input_tokens?beta=true",{body:s,...t,headers:ek([{...r?.toString()!=null?{"openai-beta":r?.toString()}:void 0},t?.headers]),__security:{bearerAuth:!0}})}}class rn extends e0{constructor(){super(...arguments),this.inputItems=new rr(this._client),this.inputTokens=new rs(this._client)}create(e,t){let{betas:r,...s}=e;return this._client.post("/responses?beta=true",{body:s,...t,headers:ek([{...r?.toString()!=null?{"openai-beta":r?.toString()}:void 0},t?.headers]),stream:e.stream??!1,__security:{bearerAuth:!0}})}retrieve(e,t={},r){let{betas:s,...n}=t??{};return this._client.get(e8`/responses/${e}?beta=true`,{query:n,...r,headers:ek([{...s?.toString()!=null?{"openai-beta":s?.toString()}:void 0},r?.headers]),stream:t?.stream??!1,__security:{bearerAuth:!0}})}delete(e,t={},r){let{betas:s}=t??{};return this._client.delete(e8`/responses/${e}?beta=true`,{...r,headers:ek([{Accept:"*/*",...s?.toString()!=null?{"openai-beta":s?.toString()}:void 0},r?.headers]),__security:{bearerAuth:!0}})}cancel(e,t={},r){let{betas:s}=t??{};return this._client.post(e8`/responses/${e}/cancel?beta=true`,{...r,headers:ek([{...s?.toString()!=null?{"openai-beta":s?.toString()}:void 0},r?.headers]),__security:{bearerAuth:!0}})}compact(e,t){let{betas:r,...s}=e;return this._client.post("/responses/compact?beta=true",{body:s,...t,headers:ek([{...r?.toString()!=null?{"openai-beta":r?.toString()}:void 0},t?.headers]),__security:{bearerAuth:!0}})}}rn.InputItems=rr,rn.InputTokens=rs;class ri extends e0{create(e,t,r){return this._client.post(e8`/threads/${e}/messages`,{body:t,...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}retrieve(e,t,r){let{thread_id:s}=t;return this._client.get(e8`/threads/${s}/messages/${e}`,{...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}update(e,t,r){let{thread_id:s,...n}=t;return this._client.post(e8`/threads/${s}/messages/${e}`,{body:n,...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}list(e,t={},r){return this._client.getAPIList(e8`/threads/${e}/messages`,eA,{query:t,...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}delete(e,t,r){let{thread_id:s}=t;return this._client.delete(e8`/threads/${s}/messages/${e}`,{...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}}class ra extends e0{retrieve(e,t,r){let{thread_id:s,run_id:n,...i}=t;return this._client.get(e8`/threads/${s}/runs/${n}/steps/${e}`,{query:i,...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}list(e,t,r){let{thread_id:s,...n}=t;return this._client.getAPIList(e8`/threads/${s}/runs/${e}/steps`,eA,{query:n,...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}}var ro,rl,ru,rc,rh,rd,rf,rp,r_,ry,rm,rg,rb,rw,rA,rv,rx,rI,r$,rP,rS,rk,rO,rR,rE,rT,rj,rC,rB,rK,rL,rN,rz,rM,rU,rD,rW,rF,rq,rH,rX,rJ,rV,rY,rG,rQ,rZ,r0,r1,r2,r8,r6,r5,r3,r4,r9,r7,se,st,sr,ss,sn,si,sa,so,sl,su,sc,sh,sd,sf,sp,s_,sy,sm,sg,sb,sw,sA=e.i(467034);class sv extends ta{constructor(){super(...arguments),rJ.add(this),rY.set(this,[]),rG.set(this,{}),rQ.set(this,{}),rZ.set(this,void 0),r0.set(this,void 0),r1.set(this,void 0),r2.set(this,void 0),r8.set(this,void 0),r6.set(this,void 0),r5.set(this,void 0),r3.set(this,void 0),r4.set(this,void 0)}[(rY=new WeakMap,rG=new WeakMap,rQ=new WeakMap,rZ=new WeakMap,r0=new WeakMap,r1=new WeakMap,r2=new WeakMap,r8=new WeakMap,r6=new WeakMap,r5=new WeakMap,r3=new WeakMap,r4=new WeakMap,rJ=new WeakSet,Symbol.asyncIterator)](){let e=[],t=[],r=!1;return this.on("event",r=>{let s=structuredClone(r),n=t.shift();n?n.resolve(s):e.push(s)}),this.on("end",()=>{for(let e of(r=!0,t))e.resolve(void 0);t.length=0}),this.on("abort",e=>{for(let s 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snapshot")}throw Error("Tried to accumulate a non-message event")},si=function(e,t){return rV.accumulateDelta(t,e)},sa=function(e){switch(i(this,r3,e.data,"f"),e.event){case"thread.run.created":case"thread.run.queued":case"thread.run.in_progress":break;case"thread.run.requires_action":case"thread.run.cancelled":case"thread.run.failed":case"thread.run.completed":case"thread.run.expired":case"thread.run.incomplete":i(this,r0,e.data,"f"),a(this,r6,"f")&&(this._emit("toolCallDone",a(this,r6,"f")),i(this,r6,void 0,"f"))}};class sx extends e0{constructor(){super(...arguments),this.steps=new ra(this._client)}create(e,t,r){let{include:s,...n}=t;return this._client.post(e8`/threads/${e}/runs`,{query:{include:s},body:n,...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),stream:t.stream??!1,__synthesizeEventData:!0,__security:{bearerAuth:!0}})}retrieve(e,t,r){let{thread_id:s}=t;return this._client.get(e8`/threads/${s}/runs/${e}`,{...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}update(e,t,r){let{thread_id:s,...n}=t;return this._client.post(e8`/threads/${s}/runs/${e}`,{body:n,...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}list(e,t={},r){return this._client.getAPIList(e8`/threads/${e}/runs`,eA,{query:t,...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}cancel(e,t,r){let{thread_id:s}=t;return this._client.post(e8`/threads/${s}/runs/${e}/cancel`,{...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}async createAndPoll(e,t,r){let s=await this.create(e,t,r);return await this.poll(s.id,{thread_id:e},r)}createAndStream(e,t,r){return sv.createAssistantStream(e,this._client.beta.threads.runs,t,r)}async poll(e,t,r){let s=ek([r?.headers,{"X-Stainless-Poll-Helper":"true","X-Stainless-Custom-Poll-Interval":r?.pollIntervalMs?.toString()??void 0}]);for(;;){let{data:n,response:i}=await this.retrieve(e,t,{...r,headers:{...r?.headers,...s}}).withResponse();switch(n.status){case"queued":case"in_progress":case"cancelling":let a=5e3;if(r?.pollIntervalMs)a=r.pollIntervalMs;else{let e=i.headers.get("openai-poll-after-ms");if(e){let t=parseInt(e);isNaN(t)||(a=t)}}await C(a);break;case"requires_action":case"incomplete":case"cancelled":case"completed":case"failed":case"expired":return n}}}stream(e,t,r){return sv.createAssistantStream(e,this._client.beta.threads.runs,t,r)}submitToolOutputs(e,t,r){let{thread_id:s,...n}=t;return this._client.post(e8`/threads/${s}/runs/${e}/submit_tool_outputs`,{body:n,...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),stream:t.stream??!1,__synthesizeEventData:!0,__security:{bearerAuth:!0}})}async submitToolOutputsAndPoll(e,t,r){let s=await 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this._client.post("/threads/runs",{body:e,...t,headers:ek([{"OpenAI-Beta":"assistants=v2"},t?.headers]),stream:e.stream??!1,__synthesizeEventData:!0,__security:{bearerAuth:!0}})}async createAndRunPoll(e,t){let r=await this.createAndRun(e,t);return await this.runs.poll(r.id,{thread_id:r.thread_id},t)}createAndRunStream(e,t){return sv.createThreadAssistantStream(e,this._client.beta.threads,t)}}sI.Runs=sx,sI.Messages=ri;class s$ extends e0{constructor(){super(...arguments),this.realtime=new t9(this._client),this.responses=new rn(this._client),this.chatkit=new rt(this._client),this.assistants=new t5(this._client),this.threads=new sI(this._client)}}s$.Realtime=t9,s$.Responses=rn,s$.ChatKit=rt,s$.Assistants=t5,s$.Threads=sI;class sP extends e0{retrieve(e,t,r){let{container_id:s}=t;return this._client.get(e8`/containers/${s}/files/${e}/content`,{...r,headers:ek([{Accept:"application/binary"},r?.headers]),__security:{bearerAuth:!0},__binaryResponse:!0})}}class sS extends 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this._client.getAPIList("/containers",eA,{query:e,...t,__security:{bearerAuth:!0}})}delete(e,t){return this._client.delete(e8`/containers/${e}`,{...t,headers:ek([{Accept:"*/*"},t?.headers]),__security:{bearerAuth:!0}})}}sk.Files=sS;class sO extends e0{create(e,t,r){let{include:s,...n}=t;return this._client.post(e8`/conversations/${e}/items`,{query:{include:s},body:n,...r,__security:{bearerAuth:!0}})}retrieve(e,t,r){let{conversation_id:s,...n}=t;return this._client.get(e8`/conversations/${s}/items/${e}`,{query:n,...r,__security:{bearerAuth:!0}})}list(e,t={},r){return this._client.getAPIList(e8`/conversations/${e}/items`,ev,{query:t,...r,__security:{bearerAuth:!0}})}delete(e,t,r){let{conversation_id:s}=t;return this._client.delete(e8`/conversations/${s}/items/${e}`,{...r,__security:{bearerAuth:!0}})}}class sR extends e0{constructor(){super(...arguments),this.items=new sO(this._client)}create(e={},t){return 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this._client.post(e8`/vector_stores/${e}/file_batches`,{body:t,...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}retrieve(e,t,r){let{vector_store_id:s}=t;return this._client.get(e8`/vector_stores/${s}/file_batches/${e}`,{...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}cancel(e,t,r){let{vector_store_id:s}=t;return this._client.post(e8`/vector_stores/${s}/file_batches/${e}/cancel`,{...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}async createAndPoll(e,t,r){let s=await this.create(e,t);return await this.poll(e,s.id,r)}listFiles(e,t,r){let{vector_store_id:s,...n}=t;return this._client.getAPIList(e8`/vector_stores/${s}/file_batches/${e}/files`,eA,{query:n,...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}async poll(e,t,r){let s=ek([r?.headers,{"X-Stainless-Poll-Helper":"true","X-Stainless-Custom-Poll-Interval":r?.pollIntervalMs?.toString()??void 0}]);for(;;){let{data:n,response:i}=await this.retrieve(t,{vector_store_id:e},{...r,headers:s}).withResponse();switch(n.status){case"in_progress":let a=5e3;if(r?.pollIntervalMs)a=r.pollIntervalMs;else{let e=i.headers.get("openai-poll-after-ms");if(e){let t=parseInt(e);isNaN(t)||(a=t)}}await C(a);break;case"failed":case"cancelled":case"completed":return n}}}async uploadAndPoll(e,{files:t,fileIds:r=[]},s){if(null==t||0==t.length)throw Error("No `files` provided to process. If you've already uploaded files you should use `.createAndPoll()` instead");let n=Math.min(s?.maxConcurrency??5,t.length),i=this._client,a=t.values(),o=[...r];async function l(e){for(let t of e){let e=await i.files.create({file:t,purpose:"assistants"},s);o.push(e.id)}}let u=Array(n).fill(a).map(l);return await ns(u),await this.createAndPoll(e,{file_ids:o})}}class ni extends e0{create(e,t,r){return this._client.post(e8`/vector_stores/${e}/files`,{body:t,...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}retrieve(e,t,r){let{vector_store_id:s}=t;return this._client.get(e8`/vector_stores/${s}/files/${e}`,{...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}update(e,t,r){let{vector_store_id:s,...n}=t;return this._client.post(e8`/vector_stores/${s}/files/${e}`,{body:n,...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}list(e,t={},r){return this._client.getAPIList(e8`/vector_stores/${e}/files`,eA,{query:t,...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}delete(e,t,r){let{vector_store_id:s}=t;return this._client.delete(e8`/vector_stores/${s}/files/${e}`,{...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}async createAndPoll(e,t,r){let s=await this.create(e,t,r);return await this.poll(e,s.id,r)}async poll(e,t,r){let s=ek([r?.headers,{"X-Stainless-Poll-Helper":"true","X-Stainless-Custom-Poll-Interval":r?.pollIntervalMs?.toString()??void 0}]);for(;;){let n=await this.retrieve(t,{vector_store_id:e},{...r,headers:s}).withResponse(),i=n.data;switch(i.status){case"in_progress":let a=5e3;if(r?.pollIntervalMs)a=r.pollIntervalMs;else{let e=n.response.headers.get("openai-poll-after-ms");if(e){let t=parseInt(e);isNaN(t)||(a=t)}}await C(a);break;case"failed":case"completed":return i}}}async upload(e,t,r){let s=await this._client.files.create({file:t,purpose:"assistants"},r);return this.create(e,{file_id:s.id},r)}async uploadAndPoll(e,t,r){let s=await this.upload(e,t,r);return await this.poll(e,s.id,r)}content(e,t,r){let{vector_store_id:s}=t;return this._client.getAPIList(e8`/vector_stores/${s}/files/${e}/content`,ew,{...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}}class na extends e0{constructor(){super(...arguments),this.files=new ni(this._client),this.fileBatches=new nn(this._client)}create(e,t){return this._client.post("/vector_stores",{body:e,...t,headers:ek([{"OpenAI-Beta":"assistants=v2"},t?.headers]),__security:{bearerAuth:!0}})}retrieve(e,t){return this._client.get(e8`/vector_stores/${e}`,{...t,headers:ek([{"OpenAI-Beta":"assistants=v2"},t?.headers]),__security:{bearerAuth:!0}})}update(e,t,r){return this._client.post(e8`/vector_stores/${e}`,{body:t,...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}list(e={},t){return this._client.getAPIList("/vector_stores",eA,{query:e,...t,headers:ek([{"OpenAI-Beta":"assistants=v2"},t?.headers]),__security:{bearerAuth:!0}})}delete(e,t){return this._client.delete(e8`/vector_stores/${e}`,{...t,headers:ek([{"OpenAI-Beta":"assistants=v2"},t?.headers]),__security:{bearerAuth:!0}})}search(e,t,r){return this._client.getAPIList(e8`/vector_stores/${e}/search`,ew,{body:t,method:"post",...r,headers:ek([{"OpenAI-Beta":"assistants=v2"},r?.headers]),__security:{bearerAuth:!0}})}}na.Files=ni,na.FileBatches=nn;class no extends e0{create(e,t){return this._client.post("/videos",eB({body:e,...t,__security:{bearerAuth:!0}},this._client))}retrieve(e,t){return this._client.get(e8`/videos/${e}`,{...t,__security:{bearerAuth:!0}})}list(e={},t){return this._client.getAPIList("/videos",ev,{query:e,...t,__security:{bearerAuth:!0}})}delete(e,t){return this._client.delete(e8`/videos/${e}`,{...t,__security:{bearerAuth:!0}})}createCharacter(e,t){return this._client.post("/videos/characters",eB({body:e,...t,__security:{bearerAuth:!0}},this._client))}downloadContent(e,t={},r){return this._client.get(e8`/videos/${e}/content`,{query:t,...r,headers:ek([{Accept:"application/binary"},r?.headers]),__security:{bearerAuth:!0},__binaryResponse:!0})}edit(e,t){return this._client.post("/videos/edits",eB({body:e,...t,__security:{bearerAuth:!0}},this._client))}extend(e,t){return this._client.post("/videos/extensions",eB({body:e,...t,__security:{bearerAuth:!0}},this._client))}getCharacter(e,t){return this._client.get(e8`/videos/characters/${e}`,{...t,__security:{bearerAuth:!0}})}remix(e,t,r){return this._client.post(e8`/videos/${e}/remix`,eC({body:t,...r,__security:{bearerAuth:!0}},this._client))}}class nl extends e0{constructor(){super(...arguments),sp.add(this)}async unwrap(e,t,r=this._client.webhookSecret,s=300){return await this.verifySignature(e,t,r,s),JSON.parse(e)}async verifySignature(e,t,r=this._client.webhookSecret,s=300){if("u"s)throw new $("Webhook timestamp is too old");if(u>c+s)throw new $("Webhook timestamp is too new");let h=i.split(" ").map(e=>e.startsWith("v1,")?e.substring(3):e),d=r.startsWith("whsec_")?sA.Buffer.from(r.replace("whsec_",""),"base64"):sA.Buffer.from(r,"utf-8"),f=l?`${l}.${o}.${e}`:`${o}.${e}`,p=await crypto.subtle.importKey("raw",d,{name:"HMAC",hash:"SHA-256"},!1,["verify"]);for(let e of h)try{let t=sA.Buffer.from(e,"base64");if(await crypto.subtle.verify("HMAC",p,t,new TextEncoder().encode(f)))return}catch{continue}throw new $("The given webhook signature does not match the expected signature")}}sp=new WeakSet,s_=function(e){if("string"!=typeof e||0===e.length)throw Error("The webhook secret must either be set using the env var, OPENAI_WEBHOOK_SECRET, on the 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"content": [ - {"type": "input_text", "text": prompt}, - { - "type": "input_image", - "image_url": f"data:image/jpeg;base64,{base64_image1}", - }, - { - "type": "input_image", - "image_url": f"data:image/jpeg;base64,{base64_image2}", - }, - { - "type": "input_image", - "file_id": file_id1, - }, - { - "type": "input_image", - "file_id": file_id2, - } - ], - } - ], - tools=[{"type": "image_generation"}], -) - -# Process the response -image_generation_calls = [ - output - for output in response.output - if output.type == "image_generation_call" -] - -image_data = [output.result for output in image_generation_calls] - -if image_data: - image_base64 = image_data[0] - image_filename = f"edited_image_{int(time.time())}.png" - with open(image_filename, "wb") as f: - f.write(base64.b64decode(image_base64)) - print(f"Image saved to {image_filename}") -else: - # If no image is generated, there might be a text response with an explanation - text_response = [output.text for output in response.output if hasattr(output, 'text')] - 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Model response:") - print("\\n".join(text_response)) - else: - print("No image data found in response.") - print("Full response for debugging:") - print(response) -`;break;case t.EndpointType.IMAGE_EDITS:r="azure"===g?` -import base64 -import os -import time -import json -from PIL import Image -import requests - -# Helper function to encode images to base64 -def encode_image(image_path): - with open(image_path, "rb") as image_file: - return base64.b64encode(image_file.read()).decode('utf-8') - -# The prompt entered by the user -prompt = "${v}" - -# Encode images to base64 -base64_image1 = encode_image("body-lotion.png") -base64_image2 = encode_image("soap.png") - -# Create file IDs -file_id1 = create_file("body-lotion.png") -file_id2 = create_file("incense-kit.png") - -response = client.responses.create( - model="${C}", - input=[ - { - "role": "user", - "content": [ - {"type": "input_text", "text": prompt}, - { - "type": "input_image", - "image_url": f"data:image/jpeg;base64,{base64_image1}", - }, - { - "type": "input_image", - "image_url": f"data:image/jpeg;base64,{base64_image2}", - }, - { - "type": "input_image", - "file_id": file_id1, - }, - { - "type": "input_image", - "file_id": file_id2, - } - ], - } - ], - tools=[{"type": "image_generation"}], -) - -# Process the response -image_generation_calls = [ - output - for output in response.output - if output.type == "image_generation_call" -] - -image_data = [output.result for output in image_generation_calls] - -if image_data: - image_base64 = image_data[0] - image_filename = f"edited_image_{int(time.time())}.png" - with open(image_filename, "wb") as f: - f.write(base64.b64decode(image_base64)) - print(f"Image saved to {image_filename}") -else: - # If no image is generated, there might be a text response with an explanation - text_response = [output.text for output in response.output if hasattr(output, 'text')] - if text_response: - print("No image generated. 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this._client.delete(rs`/v1/messages/batches/${e}?beta=true`,{...s,headers:s7([{"anthropic-beta":[...r??[],"message-batches-2024-09-24"].toString()},s?.headers])})}cancel(e,t={},s){let{betas:r}=t??{};return this._client.post(rs`/v1/messages/batches/${e}/cancel?beta=true`,{...s,headers:s7([{"anthropic-beta":[...r??[],"message-batches-2024-09-24"].toString()},s?.headers])})}async results(e,t={},s){let r=await this.retrieve(e);if(!r.results_url)throw new st(`No batch \`results_url\`; Has it finished processing? ${r.processing_status} - ${r.id}`);let{betas:a}=t??{};return this._client.get(r.results_url,{...s,headers:s7([{"anthropic-beta":[...a??[],"message-batches-2024-09-24"].toString(),Accept:"application/binary"},s?.headers]),stream:!0,__binaryResponse:!0})._thenUnwrap((e,t)=>rx.fromResponse(t.response,t.controller))}}let rb={"claude-opus-4-20250514":8192,"claude-opus-4-0":8192,"claude-4-opus-20250514":8192,"anthropic.claude-opus-4-20250514-v1:0":8192,"claude-opus-4@20250514":8192,"claude-opus-4-1-20250805":8192,"anthropic.claude-opus-4-1-20250805-v1:0":8192,"claude-opus-4-1@20250805":8192};function rv(e){return e?.output_format??e?.output_config?.format}function ry(e,t,s){let r=rv(t);return t&&"parse"in(r??{})?rj(e,t,s):{...e,content:e.content.map(e=>"text"===e.type?Object.defineProperty(Object.defineProperty({...e},"parsed_output",{value:null,enumerable:!1}),"parsed",{get:()=>(s.logger.warn("The `parsed` property on `text` blocks is deprecated, please use `parsed_output` instead."),null),enumerable:!1}):e),parsed_output:null}}function rj(e,t,s){let r=null,a=e.content.map(e=>{if("text"===e.type){let a=function(e,t){let s=rv(e);if(s?.type!=="json_schema")return null;try{if("parse"in s)return s.parse(t);return JSON.parse(t)}catch(e){throw new st(`Failed to parse structured output: 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t6(a,h,{...t,stream:!0},"f"),a._run(()=>a._createMessage(e,{...t,stream:!0},{...s,headers:{...s?.headers,"X-Stainless-Helper-Method":"stream"}})),a}_run(e){e().then(()=>{this._emitFinal(),this._emit("end")},t8(this,A,"f"))}_addMessageParam(e){this.messages.push(e)}_addMessage(e,t=!0){this.receivedMessages.push(e),t&&this._emit("message",e)}async _createMessage(e,t,s){let r,a=s?.signal;a&&(a.aborted&&this.controller.abort(),r=this.controller.abort.bind(this.controller),a.addEventListener("abort",r));try{t8(this,m,"m",P).call(this);let{response:r,data:a}=await e.create({...t,stream:!0},{...s,signal:this.controller.signal}).withResponse();for await(let e of(this._connected(r),a))t8(this,m,"m",M).call(this,e);if(a.controller.signal?.aborted)throw new sr;t8(this,m,"m",R).call(this)}finally{a&&r&&a.removeEventListener("abort",r)}}_connected(e){this.ended||(t6(this,k,e,"f"),t6(this,C,e?.headers.get("request-id"),"f"),t8(this,x,"f").call(this,e),this._emit("connect"))}get ended(){return 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Write a continuation summary that will allow you (or another instance of yourself) to resume work efficiently in a future context window where the conversation history will be replaced with this summary. Your summary should be structured, concise, and actionable. Include: +1. Task Overview +The user's core request and success criteria +Any clarifications or constraints they specified +2. Current State +What has been completed so far +Files created, modified, or analyzed (with paths if relevant) +Key outputs or artifacts produced +3. Important Discoveries +Technical constraints or requirements uncovered +Decisions made and their rationale +Errors encountered and how they were resolved +What approaches were tried that didn't work (and why) +4. Next Steps +Specific actions needed to complete the task +Any blockers or open questions to resolve +Priority order if multiple steps remain +5. Context to Preserve +User preferences or style requirements +Domain-specific details that aren't obvious +Any promises made to the user +Be concise but complete—err on the side of including information that would prevent duplicate work or repeated mistakes. Write in a way that enables immediate resumption of the task. +Wrap your summary in tags.`;function rI(){let e,t;return{promise:new Promise((s,r)=>{e=s,t=r}),resolve:e,reject:t}}class rA{constructor(e,t,s){O.add(this),this.client=e,L.set(this,!1),$.set(this,!1),U.set(this,void 0),D.set(this,void 0),q.set(this,void 0),B.set(this,void 0),F.set(this,void 0),H.set(this,0),t6(this,U,{params:{...t,messages:structuredClone(t.messages)}},"f");const r=["BetaToolRunner",...ri(t.tools,t.messages)].join(", ");t6(this,D,{...s,headers:s7([{"x-stainless-helper":r},s?.headers])},"f"),t6(this,F,rI(),"f"),t.compactionControl?.enabled&&console.warn('Anthropic: The `compactionControl` parameter is deprecated and will be removed in a future version. 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this._client.get(rs`/v1/skills/${r}/versions/${e}?beta=true`,{...s,headers:s7([{"anthropic-beta":[...a??[],"skills-2025-10-02"].toString()},s?.headers])})}list(e,t={},s){let{betas:r,...a}=t??{};return this._client.getAPIList(rs`/v1/skills/${e}/versions?beta=true`,sJ,{query:a,...s,headers:s7([{"anthropic-beta":[...r??[],"skills-2025-10-02"].toString()},s?.headers])})}delete(e,t,s){let{skill_id:r,betas:a}=t;return this._client.delete(rs`/v1/skills/${r}/versions/${e}?beta=true`,{...s,headers:s7([{"anthropic-beta":[...a??[],"skills-2025-10-02"].toString()},s?.headers])})}}class rq extends s8{constructor(){super(...arguments),this.versions=new rD(this._client)}create(e={},t){let{betas:s,...r}=e??{};return this._client.post("/v1/skills?beta=true",s0({body:r,...t,headers:s7([{"anthropic-beta":[...s??[],"skills-2025-10-02"].toString()},t?.headers])},this._client,!1))}retrieve(e,t={},s){let{betas:r}=t??{};return 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this._client.get(rs`/v1/vaults/${r}/credentials/${e}?beta=true`,{...s,headers:s7([{"anthropic-beta":[...a??[],"managed-agents-2026-04-01"].toString()},s?.headers])})}update(e,t,s){let{vault_id:r,betas:a,...n}=t;return this._client.post(rs`/v1/vaults/${r}/credentials/${e}?beta=true`,{body:n,...s,headers:s7([{"anthropic-beta":[...a??[],"managed-agents-2026-04-01"].toString()},s?.headers])})}list(e,t={},s){let{betas:r,...a}=t??{};return this._client.getAPIList(rs`/v1/vaults/${e}/credentials?beta=true`,sJ,{query:a,...s,headers:s7([{"anthropic-beta":[...r??[],"managed-agents-2026-04-01"].toString()},s?.headers])})}delete(e,t,s){let{vault_id:r,betas:a}=t;return this._client.delete(rs`/v1/vaults/${r}/credentials/${e}?beta=true`,{...s,headers:s7([{"anthropic-beta":[...a??[],"managed-agents-2026-04-01"].toString()},s?.headers])})}archive(e,t,s){let{vault_id:r,betas:a}=t;return 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r>=0&&s.splice(r,1),this}once(e,t){return(t8(this,es,"f")[e]||(t8(this,es,"f")[e]=[])).push({listener:t,once:!0}),this}emitted(e){return new Promise((t,s)=>{t6(this,ei,!0,"f"),"error"!==e&&this.once("error",s),this.once(e,t)})}async done(){t6(this,ei,!0,"f"),await t8(this,Z,"f")}get currentMessage(){return t8(this,K,"f")}async finalMessage(){return await this.done(),t8(this,W,"m",ec).call(this)}async finalText(){return await this.done(),t8(this,W,"m",eu).call(this)}_emit(e,...t){if(t8(this,er,"f"))return;"end"===e&&(t6(this,er,!0,"f"),t8(this,ee,"f").call(this));let s=t8(this,es,"f")[e];if(s&&(t8(this,es,"f")[e]=s.filter(e=>!e.once),s.forEach(({listener:e})=>e(...t))),"abort"===e){let e=t[0];t8(this,ei,"f")||s?.length||Promise.reject(e),t8(this,Q,"f").call(this,e),t8(this,et,"f").call(this,e),this._emit("end");return}if("error"===e){let e=t[0];t8(this,ei,"f")||s?.length||Promise.reject(e),t8(this,Q,"f").call(this,e),t8(this,et,"f").call(this,e),this._emit("end")}}_emitFinal(){this.receivedMessages.at(-1)&&this._emit("finalMessage",t8(this,W,"m",ec).call(this))}async _fromReadableStream(e,t){let s,r=t?.signal;r&&(r.aborted&&this.controller.abort(),s=this.controller.abort.bind(this.controller),r.addEventListener("abort",s));try{t8(this,W,"m",ep).call(this),this._connected(null);let t=sU.fromReadableStream(e,this.controller);for await(let e of t)t8(this,W,"m",eh).call(this,e);if(t.controller.signal?.aborted)throw new sr;t8(this,W,"m",eg).call(this)}finally{r&&s&&r.removeEventListener("abort",s)}}[(K=new WeakMap,J=new WeakMap,X=new WeakMap,Y=new WeakMap,Q=new WeakMap,Z=new WeakMap,ee=new WeakMap,et=new WeakMap,es=new WeakMap,er=new WeakMap,ea=new WeakMap,en=new WeakMap,ei=new WeakMap,eo=new WeakMap,el=new WeakMap,ed=new WeakMap,em=new WeakMap,W=new WeakSet,ec=function(){if(0===this.receivedMessages.length)throw new st("stream ended without producing a Message with role=assistant");return this.receivedMessages.at(-1)},eu=function(){if(0===this.receivedMessages.length)throw new st("stream ended without producing a Message with role=assistant");let e=this.receivedMessages.at(-1).content.filter(e=>"text"===e.type).map(e=>e.text);if(0===e.length)throw new st("stream ended without producing a content block with type=text");return e.join(" ")},ep=function(){this.ended||t6(this,K,void 0,"f")},eh=function(e){if(this.ended)return;let t=t8(this,W,"m",ex).call(this,e);switch(this._emit("streamEvent",e,t),e.type){case"content_block_delta":{let s=t.content.at(-1);switch(e.delta.type){case"text_delta":"text"===s.type&&this._emit("text",e.delta.text,s.text||"");break;case"citations_delta":"text"===s.type&&this._emit("citation",e.delta.citation,s.citations??[]);break;case"input_json_delta":rJ(s)&&s.input&&this._emit("inputJson",e.delta.partial_json,s.input);break;case"thinking_delta":"thinking"===s.type&&this._emit("thinking",e.delta.thinking,s.thinking);break;case"signature_delta":"thinking"===s.type&&this._emit("signature",s.signature);break;default:rY(e.delta)}break}case"message_stop":this._addMessageParam(t),this._addMessage(rG(t,t8(this,J,"f"),{logger:t8(this,ed,"f")}),!0);break;case"content_block_stop":this._emit("contentBlock",t.content.at(-1));break;case"message_start":t6(this,K,t,"f")}},eg=function(){if(this.ended)throw new st("stream has ended, this shouldn't happen");let e=t8(this,K,"f");if(!e)throw new st("request ended without sending any chunks");return t6(this,K,void 0,"f"),rG(e,t8(this,J,"f"),{logger:t8(this,ed,"f")})},ex=function(e){let t=t8(this,K,"f");if("message_start"===e.type){if(t)throw new st(`Unexpected event order, got ${e.type} before receiving "message_stop"`);return e.message}if(!t)throw new st(`Unexpected event order, got ${e.type} before "message_start"`);switch(e.type){case"message_stop":case"content_block_stop":return t;case"message_delta":return t.stop_reason=e.delta.stop_reason,t.stop_sequence=e.delta.stop_sequence,t.usage.output_tokens=e.usage.output_tokens,null!=e.usage.input_tokens&&(t.usage.input_tokens=e.usage.input_tokens),null!=e.usage.cache_creation_input_tokens&&(t.usage.cache_creation_input_tokens=e.usage.cache_creation_input_tokens),null!=e.usage.cache_read_input_tokens&&(t.usage.cache_read_input_tokens=e.usage.cache_read_input_tokens),null!=e.usage.server_tool_use&&(t.usage.server_tool_use=e.usage.server_tool_use),t;case"content_block_start":return t.content.push({...e.content_block}),t;case"content_block_delta":{let s=t.content.at(e.index);switch(e.delta.type){case"text_delta":s?.type==="text"&&(t.content[e.index]={...s,text:(s.text||"")+e.delta.text});break;case"citations_delta":s?.type==="text"&&(t.content[e.index]={...s,citations:[...s.citations??[],e.delta.citation]});break;case"input_json_delta":if(s&&rJ(s)){let r=s[rK]||"";r+=e.delta.partial_json;let a={...s};Object.defineProperty(a,rK,{value:r,enumerable:!1,writable:!0}),r&&(a.input=rN(r)),t.content[e.index]=a}break;case"thinking_delta":s?.type==="thinking"&&(t.content[e.index]={...s,thinking:s.thinking+e.delta.thinking});break;case"signature_delta":s?.type==="thinking"&&(t.content[e.index]={...s,signature:e.delta.signature});break;default:rY(e.delta)}return t}}},Symbol.asyncIterator)](){let e=[],t=[],s=!1;return this.on("streamEvent",s=>{let r=t.shift();r?r.resolve(s):e.push(s)}),this.on("end",()=>{for(let e of(s=!0,t))e.resolve(void 0);t.length=0}),this.on("abort",e=>{for(let r of(s=!0,t))r.reject(e);t.length=0}),this.on("error",e=>{for(let r of(s=!0,t))r.reject(e);t.length=0}),{next:async()=>e.length?{value:e.shift(),done:!1}:s?{value:void 0,done:!0}:new Promise((e,s)=>t.push({resolve:e,reject:s})).then(e=>e?{value:e,done:!1}:{value:void 0,done:!0}),return:async()=>(this.abort(),{value:void 0,done:!0})}}toReadableStream(){return new sU(this[Symbol.asyncIterator].bind(this),this.controller).toReadableStream()}}function rY(e){}class rQ extends s8{create(e,t){return this._client.post("/v1/messages/batches",{body:e,...t})}retrieve(e,t){return this._client.get(rs`/v1/messages/batches/${e}`,t)}list(e={},t){return this._client.getAPIList("/v1/messages/batches",sK,{query:e,...t})}delete(e,t){return this._client.delete(rs`/v1/messages/batches/${e}`,t)}cancel(e,t){return this._client.post(rs`/v1/messages/batches/${e}/cancel`,t)}async results(e,t){let s=await this.retrieve(e);if(!s.results_url)throw new st(`No batch \`results_url\`; Has it finished processing? ${s.processing_status} - ${s.id}`);return this._client.get(s.results_url,{...t,headers:s7([{Accept:"application/binary"},t?.headers]),stream:!0,__binaryResponse:!0})._thenUnwrap((e,t)=>rx.fromResponse(t.response,t.controller))}}class rZ extends s8{constructor(){super(...arguments),this.batches=new rQ(this._client)}create(e,t){e.model in r0&&console.warn(`The model '${e.model}' is deprecated and will reach end-of-life on ${r0[e.model]} +Please migrate to a newer model. Visit https://docs.anthropic.com/en/docs/resources/model-deprecations for more information.`),r1.includes(e.model)&&e.thinking&&"enabled"===e.thinking.type&&console.warn(`Using Claude with ${e.model} and 'thinking.type=enabled' is deprecated. Use 'thinking.type=adaptive' instead which results in better model performance in our testing: https://platform.claude.com/docs/en/build-with-claude/adaptive-thinking`);let s=this._client._options.timeout;if(!e.stream&&null==s){let t=rb[e.model]??void 0;s=this._client.calculateNonstreamingTimeout(e.max_tokens,t)}let r=ro(e.tools,e.messages);return this._client.post("/v1/messages",{body:e,timeout:s??6e5,...t,headers:s7([r,t?.headers]),stream:e.stream??!1})}parse(e,t){return this.create(e,t).then(t=>rW(t,e,{logger:this._client.logger??console}))}stream(e,t){return rX.createMessage(this,e,t,{logger:this._client.logger??console})}countTokens(e,t){return this._client.post("/v1/messages/count_tokens",{body:e,...t})}}let r0={"claude-1.3":"November 6th, 2024","claude-1.3-100k":"November 6th, 2024","claude-instant-1.1":"November 6th, 2024","claude-instant-1.1-100k":"November 6th, 2024","claude-instant-1.2":"November 6th, 2024","claude-3-sonnet-20240229":"July 21st, 2025","claude-3-opus-20240229":"January 5th, 2026","claude-2.1":"July 21st, 2025","claude-2.0":"July 21st, 2025","claude-3-7-sonnet-latest":"February 19th, 2026","claude-3-7-sonnet-20250219":"February 19th, 2026","claude-3-5-haiku-latest":"February 19th, 2026","claude-3-5-haiku-20241022":"February 19th, 2026","claude-opus-4-0":"June 15th, 2026","claude-opus-4-20250514":"June 15th, 2026","claude-sonnet-4-0":"June 15th, 2026","claude-sonnet-4-20250514":"June 15th, 2026"},r1=["claude-mythos-preview","claude-opus-4-6"];rZ.Batches=rQ;class r2 extends s8{retrieve(e,t={},s){let{betas:r}=t??{};return this._client.get(rs`/v1/models/${e}`,{...s,headers:s7([{...r?.toString()!=null?{"anthropic-beta":r?.toString()}:void 0},s?.headers])})}list(e={},t){let{betas:s,...r}=e??{};return this._client.getAPIList("/v1/models",sK,{query:r,...t,headers:s7([{...s?.toString()!=null?{"anthropic-beta":s?.toString()}:void 0},t?.headers])})}}class r4 extends s8{create(e,t){let{betas:s,...r}=e;return this._client.post("/v1/complete",{body:r,timeout:this._client._options.timeout??6e5,...t,headers:s7([{...s?.toString()!=null?{"anthropic-beta":s?.toString()}:void 0},t?.headers]),stream:e.stream??!1})}}let r5=e=>void 0!==globalThis.process?globalThis.process.env?.[e]?.trim()||void 0:void 0!==globalThis.Deno&&globalThis.Deno.env?.get?.(e)?.trim()||void 0;class r3{constructor({baseURL:e=r5("ANTHROPIC_BASE_URL"),apiKey:t=r5("ANTHROPIC_API_KEY")??null,authToken:s=r5("ANTHROPIC_AUTH_TOKEN")??null,...r}={}){ef.add(this),ev.set(this,void 0);const a={apiKey:t,authToken:s,...r,baseURL:e||"https://api.anthropic.com"};if(!a.dangerouslyAllowBrowser&&"u">typeof window&&void 0!==window.document&&"u">typeof navigator)throw new st("It looks like you're running in a browser-like environment.\n\nThis is disabled by default, as it risks exposing your secret API credentials to attackers.\nIf you understand the risks and have appropriate mitigations in place,\nyou can set the `dangerouslyAllowBrowser` option to `true`, e.g.,\n\nnew Anthropic({ apiKey, dangerouslyAllowBrowser: true });\n");this.baseURL=a.baseURL,this.timeout=a.timeout??eb.DEFAULT_TIMEOUT,this.logger=a.logger??console;const n="warn";this.logLevel=n,this.logLevel=sP(a.logLevel,"ClientOptions.logLevel",this)??sP(r5("ANTHROPIC_LOG"),"process.env['ANTHROPIC_LOG']",this)??n,this.fetchOptions=a.fetchOptions,this.maxRetries=a.maxRetries??2,this.fetch=a.fetch??function(){if("u">typeof fetch)return fetch;throw Error("`fetch` is not defined as a global; Either pass `fetch` to the client, `new Anthropic({ fetch })` or polyfill the global, `globalThis.fetch = fetch`")}(),t6(this,ev,sC,"f");const i=r5("ANTHROPIC_CUSTOM_HEADERS");if(i){const e={};for(const t of i.split("\n")){const s=t.indexOf(":");s>=0&&(e[t.substring(0,s).trim()]=t.substring(s+1).trim())}a.defaultHeaders={...e,...a.defaultHeaders}}this._options=a,this.apiKey="string"==typeof t?t:null,this.authToken=s}withOptions(e){return new this.constructor({...this._options,baseURL:this.baseURL,maxRetries:this.maxRetries,timeout:this.timeout,logger:this.logger,logLevel:this.logLevel,fetch:this.fetch,fetchOptions:this.fetchOptions,apiKey:this.apiKey,authToken:this.authToken,...e})}defaultQuery(){return this._options.defaultQuery}validateHeaders({values:e,nulls:t}){if(!(e.get("x-api-key")||e.get("authorization")||this.apiKey&&e.get("x-api-key")||t.has("x-api-key")||this.authToken&&e.get("authorization"))&&!t.has("authorization"))throw Error('Could not resolve authentication method. 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this._def.checks)"min"===s.kind?(s.inclusive?e.datas.value:e.data>=s.value)&&(h(t=this._getOrReturnCtx(e,t),{code:i.too_big,type:"bigint",maximum:s.value,inclusive:s.inclusive,message:s.message}),a.dirty()):"multipleOf"===s.kind?e.data%s.value!==BigInt(0)&&(h(t=this._getOrReturnCtx(e,t),{code:i.not_multiple_of,multipleOf:s.value,message:s.message}),a.dirty()):tc.assertNever(s);return{status:a.value,value:e.data}}_getInvalidInput(e){let t=this._getOrReturnCtx(e);return h(t,{code:i.invalid_type,expected:s.bigint,received:t.parsedType}),f}gte(e,t){return this.setLimit("min",e,!0,tm.toString(t))}gt(e,t){return this.setLimit("min",e,!1,tm.toString(t))}lte(e,t){return this.setLimit("max",e,!0,tm.toString(t))}lt(e,t){return this.setLimit("max",e,!1,tm.toString(t))}setLimit(e,t,s,a){return new K({...this._def,checks:[...this._def.checks,{kind:e,value:t,inclusive:s,message:tm.toString(a)}]})}_addCheck(e){return new K({...this._def,checks:[...this._def.checks,e]})}positive(e){return this._addCheck({kind:"min",value:BigInt(0),inclusive:!1,message:tm.toString(e)})}negative(e){return this._addCheck({kind:"max",value:BigInt(0),inclusive:!1,message:tm.toString(e)})}nonpositive(e){return this._addCheck({kind:"max",value:BigInt(0),inclusive:!0,message:tm.toString(e)})}nonnegative(e){return this._addCheck({kind:"min",value:BigInt(0),inclusive:!0,message:tm.toString(e)})}multipleOf(e,t){return this._addCheck({kind:"multipleOf",value:e,message:tm.toString(t)})}get minValue(){let e=null;for(let t of this._def.checks)"min"===t.kind&&(null===e||t.value>e)&&(e=t.value);return e}get maxValue(){let e=null;for(let t of this._def.checks)"max"===t.kind&&(null===e||t.valuenew K({checks:[],typeName:th.ZodBigInt,coerce:e?.coerce??!1,...N(e)});class H extends k{_parse(e){if(this._def.coerce&&(e.data=!!e.data),this._getType(e)!==s.boolean){let t=this._getOrReturnCtx(e);return h(t,{code:i.invalid_type,expected:s.boolean,received:t.parsedType}),f}return x(e.data)}}H.create=e=>new H({typeName:th.ZodBoolean,coerce:e?.coerce||!1,...N(e)});class W extends k{_parse(e){let t;if(this._def.coerce&&(e.data=new Date(e.data)),this._getType(e)!==s.date){let t=this._getOrReturnCtx(e);return h(t,{code:i.invalid_type,expected:s.date,received:t.parsedType}),f}if(Number.isNaN(e.data.getTime()))return h(this._getOrReturnCtx(e),{code:i.invalid_date}),f;let a=new p;for(let s of this._def.checks)"min"===s.kind?e.data.getTime()s.value&&(h(t=this._getOrReturnCtx(e,t),{code:i.too_big,message:s.message,inclusive:!0,exact:!1,maximum:s.value,type:"date"}),a.dirty()):tc.assertNever(s);return{status:a.value,value:new Date(e.data.getTime())}}_addCheck(e){return new W({...this._def,checks:[...this._def.checks,e]})}min(e,t){return this._addCheck({kind:"min",value:e.getTime(),message:tm.toString(t)})}max(e,t){return this._addCheck({kind:"max",value:e.getTime(),message:tm.toString(t)})}get minDate(){let e=null;for(let t of this._def.checks)"min"===t.kind&&(null===e||t.value>e)&&(e=t.value);return null!=e?new Date(e):null}get maxDate(){let e=null;for(let t of this._def.checks)"max"===t.kind&&(null===e||t.valuenew W({checks:[],coerce:e?.coerce||!1,typeName:th.ZodDate,...N(e)});class G extends k{_parse(e){if(this._getType(e)!==s.symbol){let t=this._getOrReturnCtx(e);return h(t,{code:i.invalid_type,expected:s.symbol,received:t.parsedType}),f}return x(e.data)}}G.create=e=>new G({typeName:th.ZodSymbol,...N(e)});class Y extends k{_parse(e){if(this._getType(e)!==s.undefined){let t=this._getOrReturnCtx(e);return h(t,{code:i.invalid_type,expected:s.undefined,received:t.parsedType}),f}return x(e.data)}}Y.create=e=>new Y({typeName:th.ZodUndefined,...N(e)});class X extends k{_parse(e){if(this._getType(e)!==s.null){let t=this._getOrReturnCtx(e);return h(t,{code:i.invalid_type,expected:s.null,received:t.parsedType}),f}return x(e.data)}}X.create=e=>new X({typeName:th.ZodNull,...N(e)});class J extends k{constructor(){super(...arguments),this._any=!0}_parse(e){return x(e.data)}}J.create=e=>new J({typeName:th.ZodAny,...N(e)});class Q extends k{constructor(){super(...arguments),this._unknown=!0}_parse(e){return x(e.data)}}Q.create=e=>new Q({typeName:th.ZodUnknown,...N(e)});class ee extends k{_parse(e){let t=this._getOrReturnCtx(e);return h(t,{code:i.invalid_type,expected:s.never,received:t.parsedType}),f}}ee.create=e=>new ee({typeName:th.ZodNever,...N(e)});class et extends k{_parse(e){if(this._getType(e)!==s.undefined){let t=this._getOrReturnCtx(e);return h(t,{code:i.invalid_type,expected:s.void,received:t.parsedType}),f}return x(e.data)}}et.create=e=>new et({typeName:th.ZodVoid,...N(e)});class es extends k{_parse(e){let{ctx:t,status:a}=this._processInputParams(e),r=this._def;if(t.parsedType!==s.array)return h(t,{code:i.invalid_type,expected:s.array,received:t.parsedType}),f;if(null!==r.exactLength){let e=t.data.length>r.exactLength.value,s=t.data.lengthr.maxLength.value&&(h(t,{code:i.too_big,maximum:r.maxLength.value,type:"array",inclusive:!0,exact:!1,message:r.maxLength.message}),a.dirty()),t.common.async)return Promise.all([...t.data].map((e,s)=>r.type._parseAsync(new j(t,e,t.path,s)))).then(e=>p.mergeArray(a,e));let n=[...t.data].map((e,s)=>r.type._parseSync(new j(t,e,t.path,s)));return p.mergeArray(a,n)}get element(){return this._def.type}min(e,t){return new es({...this._def,minLength:{value:e,message:tm.toString(t)}})}max(e,t){return new es({...this._def,maxLength:{value:e,message:tm.toString(t)}})}length(e,t){return new es({...this._def,exactLength:{value:e,message:tm.toString(t)}})}nonempty(e){return this.min(1,e)}}es.create=(e,t)=>new es({type:e,minLength:null,maxLength:null,exactLength:null,typeName:th.ZodArray,...N(t)});class ea extends k{constructor(){super(...arguments),this._cached=null,this.nonstrict=this.passthrough,this.augment=this.extend}_getCached(){if(null!==this._cached)return this._cached;let e=this._def.shape(),t=tc.objectKeys(e);return this._cached={shape:e,keys:t},this._cached}_parse(e){if(this._getType(e)!==s.object){let t=this._getOrReturnCtx(e);return h(t,{code:i.invalid_type,expected:s.object,received:t.parsedType}),f}let{status:t,ctx:a}=this._processInputParams(e),{shape:r,keys:n}=this._getCached(),l=[];if(!(this._def.catchall instanceof ee&&"strip"===this._def.unknownKeys))for(let e in a.data)n.includes(e)||l.push(e);let o=[];for(let e of n){let t=r[e],s=a.data[e];o.push({key:{status:"valid",value:e},value:t._parse(new j(a,s,a.path,e)),alwaysSet:e in a.data})}if(this._def.catchall instanceof ee){let e=this._def.unknownKeys;if("passthrough"===e)for(let e of l)o.push({key:{status:"valid",value:e},value:{status:"valid",value:a.data[e]}});else if("strict"===e)l.length>0&&(h(a,{code:i.unrecognized_keys,keys:l}),t.dirty());else if("strip"===e);else throw Error("Internal ZodObject error: invalid unknownKeys value.")}else{let e=this._def.catchall;for(let t of l){let s=a.data[t];o.push({key:{status:"valid",value:t},value:e._parse(new j(a,s,a.path,t)),alwaysSet:t in a.data})}}return a.common.async?Promise.resolve().then(async()=>{let e=[];for(let t of o){let s=await t.key,a=await t.value;e.push({key:s,value:a,alwaysSet:t.alwaysSet})}return e}).then(e=>p.mergeObjectSync(t,e)):p.mergeObjectSync(t,o)}get shape(){return this._def.shape()}strict(e){return tm.errToObj,new ea({...this._def,unknownKeys:"strict",...void 0!==e?{errorMap:(t,s)=>{let a=this._def.errorMap?.(t,s).message??s.defaultError;return"unrecognized_keys"===t.code?{message:tm.errToObj(e).message??a}:{message:a}}}:{}})}strip(){return new ea({...this._def,unknownKeys:"strip"})}passthrough(){return new ea({...this._def,unknownKeys:"passthrough"})}extend(e){return new ea({...this._def,shape:()=>({...this._def.shape(),...e})})}merge(e){return new ea({unknownKeys:e._def.unknownKeys,catchall:e._def.catchall,shape:()=>({...this._def.shape(),...e._def.shape()}),typeName:th.ZodObject})}setKey(e,t){return this.augment({[e]:t})}catchall(e){return new ea({...this._def,catchall:e})}pick(e){let t={};for(let s of tc.objectKeys(e))e[s]&&this.shape[s]&&(t[s]=this.shape[s]);return new ea({...this._def,shape:()=>t})}omit(e){let t={};for(let s of tc.objectKeys(this.shape))e[s]||(t[s]=this.shape[s]);return new ea({...this._def,shape:()=>t})}deepPartial(){return function e(t){if(t instanceof ea){let s={};for(let a in t.shape){let i=t.shape[a];s[a]=ev.create(e(i))}return new ea({...t._def,shape:()=>s})}if(t instanceof es)return new es({...t._def,type:e(t.element)});if(t instanceof ev)return ev.create(e(t.unwrap()));if(t instanceof ey)return ey.create(e(t.unwrap()));if(t instanceof eo)return eo.create(t.items.map(t=>e(t)));else return t}(this)}partial(e){let t={};for(let s of tc.objectKeys(this.shape)){let a=this.shape[s];e&&!e[s]?t[s]=a:t[s]=a.optional()}return new ea({...this._def,shape:()=>t})}required(e){let t={};for(let s of tc.objectKeys(this.shape))if(e&&!e[s])t[s]=this.shape[s];else{let e=this.shape[s];for(;e instanceof ev;)e=e._def.innerType;t[s]=e}return new ea({...this._def,shape:()=>t})}keyof(){return ef(tc.objectKeys(this.shape))}}ea.create=(e,t)=>new ea({shape:()=>e,unknownKeys:"strip",catchall:ee.create(),typeName:th.ZodObject,...N(t)}),ea.strictCreate=(e,t)=>new ea({shape:()=>e,unknownKeys:"strict",catchall:ee.create(),typeName:th.ZodObject,...N(t)}),ea.lazycreate=(e,t)=>new ea({shape:e,unknownKeys:"strip",catchall:ee.create(),typeName:th.ZodObject,...N(t)});class ei extends k{_parse(e){let{ctx:t}=this._processInputParams(e),s=this._def.options;if(t.common.async)return Promise.all(s.map(async e=>{let s={...t,common:{...t.common,issues:[]},parent:null};return{result:await e._parseAsync({data:t.data,path:t.path,parent:s}),ctx:s}})).then(function(e){for(let t of e)if("valid"===t.result.status)return t.result;for(let s of e)if("dirty"===s.result.status)return t.common.issues.push(...s.ctx.common.issues),s.result;let s=e.map(e=>new n(e.ctx.common.issues));return h(t,{code:i.invalid_union,unionErrors:s}),f});{let e,a=[];for(let i of s){let s={...t,common:{...t.common,issues:[]},parent:null},r=i._parseSync({data:t.data,path:t.path,parent:s});if("valid"===r.status)return r;"dirty"!==r.status||e||(e={result:r,ctx:s}),s.common.issues.length&&a.push(s.common.issues)}if(e)return t.common.issues.push(...e.ctx.common.issues),e.result;let r=a.map(e=>new n(e));return h(t,{code:i.invalid_union,unionErrors:r}),f}}get options(){return this._def.options}}ei.create=(e,t)=>new ei({options:e,typeName:th.ZodUnion,...N(t)});let er=e=>{if(e instanceof eh)return er(e.schema);if(e instanceof eb)return er(e.innerType());if(e instanceof ep)return[e.value];if(e instanceof eg)return e.options;if(e instanceof ex)return tc.objectValues(e.enum);else if(e instanceof ej)return er(e._def.innerType);else if(e instanceof Y)return[void 0];else if(e instanceof X)return[null];else if(e instanceof ev)return[void 0,...er(e.unwrap())];else if(e instanceof ey)return[null,...er(e.unwrap())];else if(e instanceof eT)return er(e.unwrap());else if(e instanceof eS)return er(e.unwrap());else if(e instanceof ew)return er(e._def.innerType);else return[]};class en extends k{_parse(e){let{ctx:t}=this._processInputParams(e);if(t.parsedType!==s.object)return h(t,{code:i.invalid_type,expected:s.object,received:t.parsedType}),f;let a=this.discriminator,r=t.data[a],n=this.optionsMap.get(r);return n?t.common.async?n._parseAsync({data:t.data,path:t.path,parent:t}):n._parseSync({data:t.data,path:t.path,parent:t}):(h(t,{code:i.invalid_union_discriminator,options:Array.from(this.optionsMap.keys()),path:[a]}),f)}get discriminator(){return this._def.discriminator}get options(){return this._def.options}get optionsMap(){return this._def.optionsMap}static create(e,t,s){let a=new Map;for(let s of t){let t=er(s.shape[e]);if(!t.length)throw Error(`A discriminator value for key \`${e}\` could not be extracted from all schema options`);for(let i of t){if(a.has(i))throw Error(`Discriminator property ${String(e)} has duplicate value ${String(i)}`);a.set(i,s)}}return new en({typeName:th.ZodDiscriminatedUnion,discriminator:e,options:t,optionsMap:a,...N(s)})}}class el extends k{_parse(e){let{status:t,ctx:r}=this._processInputParams(e),n=(e,n)=>{if(_(e)||_(n))return f;let l=function e(t,i){let r=a(t),n=a(i);if(t===i)return{valid:!0,data:t};if(r===s.object&&n===s.object){let s=tc.objectKeys(i),a=tc.objectKeys(t).filter(e=>-1!==s.indexOf(e)),r={...t,...i};for(let s of a){let a=e(t[s],i[s]);if(!a.valid)return{valid:!1};r[s]=a.data}return{valid:!0,data:r}}if(r===s.array&&n===s.array){if(t.length!==i.length)return{valid:!1};let s=[];for(let a=0;an(e,t)):n(this._def.left._parseSync({data:r.data,path:r.path,parent:r}),this._def.right._parseSync({data:r.data,path:r.path,parent:r}))}}el.create=(e,t,s)=>new el({left:e,right:t,typeName:th.ZodIntersection,...N(s)});class eo extends k{_parse(e){let{status:t,ctx:a}=this._processInputParams(e);if(a.parsedType!==s.array)return h(a,{code:i.invalid_type,expected:s.array,received:a.parsedType}),f;if(a.data.lengththis._def.items.length&&(h(a,{code:i.too_big,maximum:this._def.items.length,inclusive:!0,exact:!1,type:"array"}),t.dirty());let r=[...a.data].map((e,t)=>{let s=this._def.items[t]||this._def.rest;return s?s._parse(new j(a,e,a.path,t)):null}).filter(e=>!!e);return a.common.async?Promise.all(r).then(e=>p.mergeArray(t,e)):p.mergeArray(t,r)}get items(){return this._def.items}rest(e){return new eo({...this._def,rest:e})}}eo.create=(e,t)=>{if(!Array.isArray(e))throw Error("You must pass an array of schemas to z.tuple([ ... ])");return new eo({items:e,typeName:th.ZodTuple,rest:null,...N(t)})};class ed extends k{get keySchema(){return this._def.keyType}get valueSchema(){return this._def.valueType}_parse(e){let{status:t,ctx:a}=this._processInputParams(e);if(a.parsedType!==s.object)return h(a,{code:i.invalid_type,expected:s.object,received:a.parsedType}),f;let r=[],n=this._def.keyType,l=this._def.valueType;for(let e in a.data)r.push({key:n._parse(new j(a,e,a.path,e)),value:l._parse(new j(a,a.data[e],a.path,e)),alwaysSet:e in a.data});return a.common.async?p.mergeObjectAsync(t,r):p.mergeObjectSync(t,r)}get element(){return this._def.valueType}static create(e,t,s){return new ed(t instanceof k?{keyType:e,valueType:t,typeName:th.ZodRecord,...N(s)}:{keyType:q.create(),valueType:e,typeName:th.ZodRecord,...N(t)})}}class ec extends k{get keySchema(){return this._def.keyType}get valueSchema(){return this._def.valueType}_parse(e){let{status:t,ctx:a}=this._processInputParams(e);if(a.parsedType!==s.map)return h(a,{code:i.invalid_type,expected:s.map,received:a.parsedType}),f;let r=this._def.keyType,n=this._def.valueType,l=[...a.data.entries()].map(([e,t],s)=>({key:r._parse(new j(a,e,a.path,[s,"key"])),value:n._parse(new j(a,t,a.path,[s,"value"]))}));if(a.common.async){let e=new Map;return Promise.resolve().then(async()=>{for(let s of l){let a=await s.key,i=await s.value;if("aborted"===a.status||"aborted"===i.status)return f;("dirty"===a.status||"dirty"===i.status)&&t.dirty(),e.set(a.value,i.value)}return{status:t.value,value:e}})}{let e=new Map;for(let s of l){let a=s.key,i=s.value;if("aborted"===a.status||"aborted"===i.status)return f;("dirty"===a.status||"dirty"===i.status)&&t.dirty(),e.set(a.value,i.value)}return{status:t.value,value:e}}}}ec.create=(e,t,s)=>new ec({valueType:t,keyType:e,typeName:th.ZodMap,...N(s)});class eu extends k{_parse(e){let{status:t,ctx:a}=this._processInputParams(e);if(a.parsedType!==s.set)return h(a,{code:i.invalid_type,expected:s.set,received:a.parsedType}),f;let r=this._def;null!==r.minSize&&a.data.sizer.maxSize.value&&(h(a,{code:i.too_big,maximum:r.maxSize.value,type:"set",inclusive:!0,exact:!1,message:r.maxSize.message}),t.dirty());let n=this._def.valueType;function l(e){let s=new Set;for(let a of e){if("aborted"===a.status)return f;"dirty"===a.status&&t.dirty(),s.add(a.value)}return{status:t.value,value:s}}let o=[...a.data.values()].map((e,t)=>n._parse(new j(a,e,a.path,t)));return a.common.async?Promise.all(o).then(e=>l(e)):l(o)}min(e,t){return new eu({...this._def,minSize:{value:e,message:tm.toString(t)}})}max(e,t){return new eu({...this._def,maxSize:{value:e,message:tm.toString(t)}})}size(e,t){return this.min(e,t).max(e,t)}nonempty(e){return this.min(1,e)}}eu.create=(e,t)=>new eu({valueType:e,minSize:null,maxSize:null,typeName:th.ZodSet,...N(t)});class em extends k{constructor(){super(...arguments),this.validate=this.implement}_parse(e){let{ctx:t}=this._processInputParams(e);if(t.parsedType!==s.function)return h(t,{code:i.invalid_type,expected:s.function,received:t.parsedType}),f;function a(e,s){return u({data:e,path:t.path,errorMaps:[t.common.contextualErrorMap,t.schemaErrorMap,c(),l].filter(e=>!!e),issueData:{code:i.invalid_arguments,argumentsError:s}})}function r(e,s){return u({data:e,path:t.path,errorMaps:[t.common.contextualErrorMap,t.schemaErrorMap,c(),l].filter(e=>!!e),issueData:{code:i.invalid_return_type,returnTypeError:s}})}let o={errorMap:t.common.contextualErrorMap},d=t.data;if(this._def.returns instanceof e_){let e=this;return x(async function(...t){let s=new n([]),i=await e._def.args.parseAsync(t,o).catch(e=>{throw s.addIssue(a(t,e)),s}),l=await Reflect.apply(d,this,i);return await e._def.returns._def.type.parseAsync(l,o).catch(e=>{throw s.addIssue(r(l,e)),s})})}{let e=this;return x(function(...t){let s=e._def.args.safeParse(t,o);if(!s.success)throw new n([a(t,s.error)]);let i=Reflect.apply(d,this,s.data),l=e._def.returns.safeParse(i,o);if(!l.success)throw new n([r(i,l.error)]);return l.data})}}parameters(){return this._def.args}returnType(){return this._def.returns}args(...e){return new em({...this._def,args:eo.create(e).rest(Q.create())})}returns(e){return new em({...this._def,returns:e})}implement(e){return this.parse(e)}strictImplement(e){return this.parse(e)}static create(e,t,s){return new em({args:e||eo.create([]).rest(Q.create()),returns:t||Q.create(),typeName:th.ZodFunction,...N(s)})}}class eh extends k{get schema(){return this._def.getter()}_parse(e){let{ctx:t}=this._processInputParams(e);return this._def.getter()._parse({data:t.data,path:t.path,parent:t})}}eh.create=(e,t)=>new eh({getter:e,typeName:th.ZodLazy,...N(t)});class ep extends k{_parse(e){if(e.data!==this._def.value){let t=this._getOrReturnCtx(e);return 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here",x=v.replace(/\\/g,"\\\\").replace(/"/g,'\\"').replace(/\n/g,"\\n"),w=n.filter(e=>!e.isImage).map(({role:e,content:t})=>({role:e,content:t})),j={};l.length>0&&(j.tags=l),d.length>0&&(j.vector_stores=d),u.length>0&&(j.guardrails=u),c.length>0&&(j.policies=c);let C=f||"your-model-name",S=b&&Object.keys(b).length>0?`, + default_headers=${JSON.stringify(b,null,2).replace(/\n/g,"\n ")}`:"",E="azure"===m?`import openai + +client = openai.AzureOpenAI( + api_key="${y||"YOUR_LITELLM_API_KEY"}", + azure_endpoint="${_}", + api_version="2024-02-01"${S} +)`:`import openai + +client = openai.OpenAI( + api_key="${y||"YOUR_LITELLM_API_KEY"}", + base_url="${_}"${S} +)`;switch(h){case t.EndpointType.CHAT:{let e=Object.keys(j).length>0,t="";if(e){let e=JSON.stringify({metadata:j},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();t=`, + extra_body=${e}`}let i=w.length>0?w:[{role:"user",content:v}];r=` +import base64 + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Example with text only +response = client.chat.completions.create( + model="${C}", + messages=${JSON.stringify(i,null,4)}${t} +) + +print(response) + +# Example with image or PDF (uncomment and provide file path to use) +# base64_file = encode_image("path/to/your/file.jpg") # or .pdf +# response_with_file = client.chat.completions.create( +# model="${C}", +# messages=[ +# { +# "role": "user", +# "content": [ +# { +# "type": "text", +# "text": "${x}" +# }, +# { +# "type": "image_url", +# "image_url": { +# "url": f"data:image/jpeg;base64,{base64_file}" # or data:application/pdf;base64,{base64_file} +# } +# } +# ] +# } +# ]${t} +# ) +# print(response_with_file) +`;break}case t.EndpointType.RESPONSES:{let e=Object.keys(j).length>0,t="";if(e){let e=JSON.stringify({metadata:j},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();t=`, + extra_body=${e}`}let i=w.length>0?w:[{role:"user",content:v}];r=` +import base64 + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Example with text only +response = client.responses.create( + model="${C}", + input=${JSON.stringify(i,null,4)}${t} +) + +print(response.output_text) + +# Example with image or PDF (uncomment and provide file path to use) +# base64_file = encode_image("path/to/your/file.jpg") # or .pdf +# response_with_file = client.responses.create( +# model="${C}", +# input=[ +# { +# "role": "user", +# "content": [ +# {"type": "input_text", "text": "${x}"}, +# { +# "type": "input_image", +# "image_url": f"data:image/jpeg;base64,{base64_file}", # or data:application/pdf;base64,{base64_file} +# "detail": "auto", +# }, +# ], +# } +# ]${t} +# ) +# print(response_with_file.output_text) +`;break}case t.EndpointType.IMAGE:r="azure"===m?` +# NOTE: The Azure SDK does not have a direct equivalent to the multi-modal 'responses.create' method shown for OpenAI. +# This snippet uses 'client.images.generate' and will create a new image based on your prompt. +# It does not use the uploaded image, as 'client.images.generate' does not support image inputs in this context. +import os +import requests +import json +import time +from PIL import Image + +result = client.images.generate( + model="${C}", + prompt="${a}", + n=1 +) + +json_response = json.loads(result.model_dump_json()) + +# Set the directory for the stored image +image_dir = os.path.join(os.curdir, 'images') + +# If the directory doesn't exist, create it +if not os.path.isdir(image_dir): + os.mkdir(image_dir) + +# Initialize the image path +image_filename = f"generated_image_{int(time.time())}.png" +image_path = os.path.join(image_dir, image_filename) + +try: + # Retrieve the generated image + if json_response.get("data") && len(json_response["data"]) > 0 && json_response["data"][0].get("url"): + image_url = json_response["data"][0]["url"] + generated_image = requests.get(image_url).content + with open(image_path, "wb") as image_file: + image_file.write(generated_image) + + print(f"Image saved to {image_path}") + # Display the image + image = Image.open(image_path) + image.show() + else: + print("Could not find image URL in response.") + print("Full response:", json_response) +except Exception as e: + print(f"An error occurred: {e}") + print("Full response:", json_response) +`:` +import base64 +import os +import time +import json +from PIL import Image +import requests + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Helper function to create a file (simplified for this example) +def create_file(image_path): + # In a real implementation, this would upload the file to OpenAI + # For this example, we'll just return a placeholder ID + return f"file_{os.path.basename(image_path).replace('.', '_')}" + +# The prompt entered by the user +prompt = "${x}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${C}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + "detail": "auto", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + "detail": "auto", + }, + { + "type": "input_image", + "file_id": file_id1, + "detail": "auto", + }, + { + "type": "input_image", + "file_id": file_id2, + "detail": "auto", + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`;break;case t.EndpointType.IMAGE_EDITS:r="azure"===m?` +import base64 +import os +import time +import json +from PIL import Image +import requests + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# The prompt entered by the user +prompt = "${x}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${C}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + "detail": "auto", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + "detail": "auto", + }, + { + "type": "input_image", + "file_id": file_id1, + "detail": "auto", + }, + { + "type": "input_image", + "file_id": file_id2, + "detail": "auto", + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`:` +import base64 +import os +import time + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Helper function to create a file (simplified for this example) +def create_file(image_path): + # In a real implementation, this would upload the file to OpenAI + # For this example, we'll just return a placeholder ID + return f"file_{os.path.basename(image_path).replace('.', '_')}" + +# The prompt entered by the user +prompt = "${x}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${C}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + "detail": "auto", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + "detail": "auto", + }, + { + "type": "input_image", + "file_id": file_id1, + "detail": "auto", + }, + { + "type": "input_image", + "file_id": file_id2, + "detail": "auto", + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`;break;case t.EndpointType.EMBEDDINGS:r=` +response = client.embeddings.create( + input="${a||"Your string here"}", + model="${C}", + encoding_format="base64" # or "float" +) + +print(response.data[0].embedding) +`;break;case t.EndpointType.TRANSCRIPTION:r=` +# Open the audio file +audio_file = open("path/to/your/audio/file.mp3", "rb") + +# Make the transcription request +response = client.audio.transcriptions.create( + model="${C}", + file=audio_file${a?`, + prompt="${a.replace(/\\/g,"\\\\").replace(/"/g,'\\"')}"`:""} +) + +print(response.text) +`;break;case t.EndpointType.SPEECH:r=` +# Make the text-to-speech request +response = client.audio.speech.create( + model="${C}", + input="${a||"Your text to convert to speech here"}", + voice="${p}" # Options: alloy, ash, ballad, coral, echo, fable, nova, onyx, sage, shimmer +) + +# Save the audio to a file +output_filename = "output_speech.mp3" +response.stream_to_file(output_filename) +print(f"Audio saved to {output_filename}") + +# Optional: Customize response format and speed +# response = client.audio.speech.create( +# model="${C}", +# input="${a||"Your text to convert to speech here"}", +# voice="alloy", +# response_format="mp3", # Options: mp3, opus, aac, flac, wav, pcm +# speed=1.0 # Range: 0.25 to 4.0 +# ) +# response.stream_to_file("output_speech.mp3") +`;break;default:r="\n# Code generation for this endpoint is not implemented yet."}return`${E} +${r}`}])},891547,e=>{"use strict";var t=e.i(843476),r=e.i(271645),i=e.i(602869),s=e.i(845150);e.s(["default",0,({onChange:e,value:o,className:a,accessToken:n,disabled:l})=>{let[d,u]=(0,r.useState)([]),[c,p]=(0,r.useState)(!1);return(0,r.useEffect)(()=>{(async()=>{if(n){p(!0);try{let e=await (0,i.getGuardrailsList)(n);e.guardrails&&u(e.guardrails)}catch(e){console.error("Error fetching guardrails:",e)}finally{p(!1)}}})()},[n]),(0,t.jsx)("div",{className:"min-w-0",children:(0,t.jsx)(s.MultiSelect,{disabled:l,placeholder:l?"Setting guardrails is a premium feature.":"Select guardrails",onValueChange:t=>{e(t)},value:o,loading:c,className:a,options:d.flatMap(e=>{let t=e.guardrail_name;return null==t||""===t?[]:[{label:t,value:t}]})})})}])},248467,e=>{"use strict";var t=e.i(843476),r=e.i(299023),i=e.i(107233),s=e.i(519455),o=e.i(793479);e.s(["default",0,({value:e=[],onChange:a})=>{let n=(t,r)=>a?.(e.map((e,i)=>i===t?r:e));return(0,t.jsxs)("div",{className:"space-y-2",children:[e.map(([i,l],d)=>(0,t.jsxs)("div",{className:"flex items-center gap-2",children:[(0,t.jsx)(o.Input,{placeholder:"Header Name",value:i,onChange:e=>n(d,[e.target.value,l])}),(0,t.jsx)(o.Input,{placeholder:"Header Value",value:l,onChange:e=>n(d,[i,e.target.value])}),(0,t.jsx)(s.Button,{type:"button",variant:"ghost",size:"icon-sm",onClick:()=>a?.(e.filter((e,t)=>t!==d)),"aria-label":`Remove header ${d+1}`,children:(0,t.jsx)(r.Minus,{})})]},d)),(0,t.jsxs)(s.Button,{type:"button",variant:"outline",onClick:()=>a?.([...e,["",""]]),children:[(0,t.jsx)(i.Plus,{}),"Add Header"]})]})}])},459161,e=>{"use strict";var t=e.i(223305);e.i(356449);var r=e.i(857223),i=e.i(602869),s=e.i(417385),o=e.i(441773),a=e.i(892034),n=e.i(757625);async function l(e,d,u,c,p=[],h,f,m,g,b,y,_,k,v,x,w,j,C,S,E,R,O,M,I=!0,P,z,N){if(!c)throw Error("Virtual Key is required");if(!u||""===u.trim())throw Error("Model is required. 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this._addCheck({kind:"date",message:e})}time(e){return"string"==typeof e?this._addCheck({kind:"time",precision:null,message:e}):this._addCheck({kind:"time",precision:void 0===e?.precision?null:e?.precision,...d.errToObj(e?.message)})}duration(e){return this._addCheck({kind:"duration",...d.errToObj(e)})}regex(e,t){return this._addCheck({kind:"regex",regex:e,...d.errToObj(t)})}includes(e,t){return this._addCheck({kind:"includes",value:e,position:t?.position,...d.errToObj(t?.message)})}startsWith(e,t){return this._addCheck({kind:"startsWith",value:e,...d.errToObj(t)})}endsWith(e,t){return this._addCheck({kind:"endsWith",value:e,...d.errToObj(t)})}min(e,t){return this._addCheck({kind:"min",value:e,...d.errToObj(t)})}max(e,t){return this._addCheck({kind:"max",value:e,...d.errToObj(t)})}length(e,t){return this._addCheck({kind:"length",value:e,...d.errToObj(t)})}nonempty(e){return this.min(1,d.errToObj(e))}trim(){return new ev({...this._def,checks:[...this._def.checks,{kind:"trim"}]})}toLowerCase(){return new ev({...this._def,checks:[...this._def.checks,{kind:"toLowerCase"}]})}toUpperCase(){return new ev({...this._def,checks:[...this._def.checks,{kind:"toUpperCase"}]})}get isDatetime(){return!!this._def.checks.find(e=>"datetime"===e.kind)}get isDate(){return!!this._def.checks.find(e=>"date"===e.kind)}get isTime(){return!!this._def.checks.find(e=>"time"===e.kind)}get isDuration(){return!!this._def.checks.find(e=>"duration"===e.kind)}get isEmail(){return!!this._def.checks.find(e=>"email"===e.kind)}get isURL(){return!!this._def.checks.find(e=>"url"===e.kind)}get isEmoji(){return!!this._def.checks.find(e=>"emoji"===e.kind)}get isUUID(){return!!this._def.checks.find(e=>"uuid"===e.kind)}get isNANOID(){return!!this._def.checks.find(e=>"nanoid"===e.kind)}get isCUID(){return!!this._def.checks.find(e=>"cuid"===e.kind)}get isCUID2(){return!!this._def.checks.find(e=>"cuid2"===e.kind)}get isULID(){return!!this._def.checks.find(e=>"ulid"===e.kind)}get isIP(){return!!this._def.checks.find(e=>"ip"===e.kind)}get isCIDR(){return!!this._def.checks.find(e=>"cidr"===e.kind)}get isBase64(){return!!this._def.checks.find(e=>"base64"===e.kind)}get isBase64url(){return!!this._def.checks.find(e=>"base64url"===e.kind)}get minLength(){let e=null;for(let t of this._def.checks)"min"===t.kind&&(null===e||t.value>e)&&(e=t.value);return e}get maxLength(){let e=null;for(let t of this._def.checks)"max"===t.kind&&(null===e||t.valuenew ev({checks:[],typeName:u.ZodString,coerce:e?.coerce??!1,...X(e)});class e_ extends ee{constructor(){super(...arguments),this.min=this.gte,this.max=this.lte,this.step=this.multipleOf}_parse(e){let t;if(this._def.coerce&&(e.data=Number(e.data)),this._getType(e)!==U.number){let t=this._getOrReturnCtx(e);return V(t,{code:q.invalid_type,expected:U.number,received:t.parsedType}),W}let r=new K;for(let a of 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this.setLimit("min",e,!1,d.toString(t))}lte(e,t){return this.setLimit("max",e,!0,d.toString(t))}lt(e,t){return this.setLimit("max",e,!1,d.toString(t))}setLimit(e,t,r,a){return new e_({...this._def,checks:[...this._def.checks,{kind:e,value:t,inclusive:r,message:d.toString(a)}]})}_addCheck(e){return new e_({...this._def,checks:[...this._def.checks,e]})}int(e){return this._addCheck({kind:"int",message:d.toString(e)})}positive(e){return this._addCheck({kind:"min",value:0,inclusive:!1,message:d.toString(e)})}negative(e){return this._addCheck({kind:"max",value:0,inclusive:!1,message:d.toString(e)})}nonpositive(e){return this._addCheck({kind:"max",value:0,inclusive:!0,message:d.toString(e)})}nonnegative(e){return this._addCheck({kind:"min",value:0,inclusive:!0,message:d.toString(e)})}multipleOf(e,t){return this._addCheck({kind:"multipleOf",value:e,message:d.toString(t)})}finite(e){return this._addCheck({kind:"finite",message:d.toString(e)})}safe(e){return this._addCheck({kind:"min",inclusive:!0,value:Number.MIN_SAFE_INTEGER,message:d.toString(e)})._addCheck({kind:"max",inclusive:!0,value:Number.MAX_SAFE_INTEGER,message:d.toString(e)})}get minValue(){let e=null;for(let t of this._def.checks)"min"===t.kind&&(null===e||t.value>e)&&(e=t.value);return e}get maxValue(){let e=null;for(let t of this._def.checks)"max"===t.kind&&(null===e||t.value"int"===e.kind||"multipleOf"===e.kind&&o.isInteger(e.value))}get isFinite(){let e=null,t=null;for(let r of this._def.checks)if("finite"===r.kind||"int"===r.kind||"multipleOf"===r.kind)return!0;else"min"===r.kind?(null===t||r.value>t)&&(t=r.value):"max"===r.kind&&(null===e||r.valuenew e_({checks:[],typeName:u.ZodNumber,coerce:e?.coerce||!1,...X(e)});class eb extends ee{constructor(){super(...arguments),this.min=this.gte,this.max=this.lte}_parse(e){let t;if(this._def.coerce)try{e.data=BigInt(e.data)}catch{return this._getInvalidInput(e)}if(this._getType(e)!==U.bigint)return this._getInvalidInput(e);let r=new K;for(let a of this._def.checks)"min"===a.kind?(a.inclusive?e.dataa.value:e.data>=a.value)&&(V(t=this._getOrReturnCtx(e,t),{code:q.too_big,type:"bigint",maximum:a.value,inclusive:a.inclusive,message:a.message}),r.dirty()):"multipleOf"===a.kind?e.data%a.value!==BigInt(0)&&(V(t=this._getOrReturnCtx(e,t),{code:q.not_multiple_of,multipleOf:a.value,message:a.message}),r.dirty()):o.assertNever(a);return{status:r.value,value:e.data}}_getInvalidInput(e){let t=this._getOrReturnCtx(e);return V(t,{code:q.invalid_type,expected:U.bigint,received:t.parsedType}),W}gte(e,t){return this.setLimit("min",e,!0,d.toString(t))}gt(e,t){return this.setLimit("min",e,!1,d.toString(t))}lte(e,t){return this.setLimit("max",e,!0,d.toString(t))}lt(e,t){return this.setLimit("max",e,!1,d.toString(t))}setLimit(e,t,r,a){return new eb({...this._def,checks:[...this._def.checks,{kind:e,value:t,inclusive:r,message:d.toString(a)}]})}_addCheck(e){return new eb({...this._def,checks:[...this._def.checks,e]})}positive(e){return this._addCheck({kind:"min",value:BigInt(0),inclusive:!1,message:d.toString(e)})}negative(e){return this._addCheck({kind:"max",value:BigInt(0),inclusive:!1,message:d.toString(e)})}nonpositive(e){return this._addCheck({kind:"max",value:BigInt(0),inclusive:!0,message:d.toString(e)})}nonnegative(e){return this._addCheck({kind:"min",value:BigInt(0),inclusive:!0,message:d.toString(e)})}multipleOf(e,t){return this._addCheck({kind:"multipleOf",value:e,message:d.toString(t)})}get minValue(){let e=null;for(let t of this._def.checks)"min"===t.kind&&(null===e||t.value>e)&&(e=t.value);return e}get maxValue(){let e=null;for(let t of this._def.checks)"max"===t.kind&&(null===e||t.valuenew eb({checks:[],typeName:u.ZodBigInt,coerce:e?.coerce??!1,...X(e)});class ex extends ee{_parse(e){if(this._def.coerce&&(e.data=!!e.data),this._getType(e)!==U.boolean){let t=this._getOrReturnCtx(e);return 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e=t.data.length>a.exactLength.value,i=t.data.lengtha.maxLength.value&&(V(t,{code:q.too_big,maximum:a.maxLength.value,type:"array",inclusive:!0,exact:!1,message:a.maxLength.message}),r.dirty()),t.common.async)return Promise.all([...t.data].map((e,r)=>a.type._parseAsync(new Y(t,e,t.path,r)))).then(e=>K.mergeArray(r,e));let i=[...t.data].map((e,r)=>a.type._parseSync(new Y(t,e,t.path,r)));return K.mergeArray(r,i)}get element(){return this._def.type}min(e,t){return new eN({...this._def,minLength:{value:e,message:d.toString(t)}})}max(e,t){return new eN({...this._def,maxLength:{value:e,message:d.toString(t)}})}length(e,t){return new eN({...this._def,exactLength:{value:e,message:d.toString(t)}})}nonempty(e){return this.min(1,e)}}eN.create=(e,t)=>new eN({type:e,minLength:null,maxLength:null,exactLength:null,typeName:u.ZodArray,...X(t)});class eP extends ee{constructor(){super(...arguments),this._cached=null,this.nonstrict=this.passthrough,this.augment=this.extend}_getCached(){if(null!==this._cached)return this._cached;let e=this._def.shape(),t=o.objectKeys(e);return this._cached={shape:e,keys:t},this._cached}_parse(e){if(this._getType(e)!==U.object){let t=this._getOrReturnCtx(e);return V(t,{code:q.invalid_type,expected:U.object,received:t.parsedType}),W}let{status:t,ctx:r}=this._processInputParams(e),{shape:a,keys:i}=this._getCached(),n=[];if(!(this._def.catchall instanceof eA&&"strip"===this._def.unknownKeys))for(let e in r.data)i.includes(e)||n.push(e);let s=[];for(let e of i){let t=a[e],i=r.data[e];s.push({key:{status:"valid",value:e},value:t._parse(new Y(r,i,r.path,e)),alwaysSet:e in r.data})}if(this._def.catchall instanceof eA){let e=this._def.unknownKeys;if("passthrough"===e)for(let e of n)s.push({key:{status:"valid",value:e},value:{status:"valid",value:r.data[e]}});else if("strict"===e)n.length>0&&(V(r,{code:q.unrecognized_keys,keys:n}),t.dirty());else if("strip"===e);else throw Error("Internal ZodObject error: invalid unknownKeys value.")}else{let e=this._def.catchall;for(let t of n){let a=r.data[t];s.push({key:{status:"valid",value:t},value:e._parse(new Y(r,a,r.path,t)),alwaysSet:t in r.data})}}return r.common.async?Promise.resolve().then(async()=>{let e=[];for(let t of s){let r=await t.key,a=await t.value;e.push({key:r,value:a,alwaysSet:t.alwaysSet})}return e}).then(e=>K.mergeObjectSync(t,e)):K.mergeObjectSync(t,s)}get shape(){return this._def.shape()}strict(e){return d.errToObj,new eP({...this._def,unknownKeys:"strict",...void 0!==e?{errorMap:(t,r)=>{let a=this._def.errorMap?.(t,r).message??r.defaultError;return"unrecognized_keys"===t.code?{message:d.errToObj(e).message??a}:{message:a}}}:{}})}strip(){return new eP({...this._def,unknownKeys:"strip"})}passthrough(){return new eP({...this._def,unknownKeys:"passthrough"})}extend(e){return new eP({...this._def,shape:()=>({...this._def.shape(),...e})})}merge(e){return new eP({unknownKeys:e._def.unknownKeys,catchall:e._def.catchall,shape:()=>({...this._def.shape(),...e._def.shape()}),typeName:u.ZodObject})}setKey(e,t){return this.augment({[e]:t})}catchall(e){return new eP({...this._def,catchall:e})}pick(e){let t={};for(let r of o.objectKeys(e))e[r]&&this.shape[r]&&(t[r]=this.shape[r]);return new eP({...this._def,shape:()=>t})}omit(e){let t={};for(let r of o.objectKeys(this.shape))e[r]||(t[r]=this.shape[r]);return new eP({...this._def,shape:()=>t})}deepPartial(){return function e(t){if(t instanceof eP){let r={};for(let a in t.shape){let i=t.shape[a];r[a]=eB.create(e(i))}return new eP({...t._def,shape:()=>r})}if(t instanceof eN)return new eN({...t._def,type:e(t.element)});if(t instanceof eB)return eB.create(e(t.unwrap()));if(t instanceof eV)return eV.create(e(t.unwrap()));if(t instanceof ez)return ez.create(t.items.map(t=>e(t)));else return t}(this)}partial(e){let t={};for(let r of o.objectKeys(this.shape)){let a=this.shape[r];e&&!e[r]?t[r]=a:t[r]=a.optional()}return new eP({...this._def,shape:()=>t})}required(e){let t={};for(let r of o.objectKeys(this.shape))if(e&&!e[r])t[r]=this.shape[r];else{let e=this.shape[r];for(;e instanceof eB;)e=e._def.innerType;t[r]=e}return new eP({...this._def,shape:()=>t})}keyof(){return eM(o.objectKeys(this.shape))}}eP.create=(e,t)=>new eP({shape:()=>e,unknownKeys:"strip",catchall:eA.create(),typeName:u.ZodObject,...X(t)}),eP.strictCreate=(e,t)=>new eP({shape:()=>e,unknownKeys:"strict",catchall:eA.create(),typeName:u.ZodObject,...X(t)}),eP.lazycreate=(e,t)=>new eP({shape:e,unknownKeys:"strip",catchall:eA.create(),typeName:u.ZodObject,...X(t)});class eT extends ee{_parse(e){let{ctx:t}=this._processInputParams(e),r=this._def.options;if(t.common.async)return Promise.all(r.map(async e=>{let r={...t,common:{...t.common,issues:[]},parent:null};return{result:await e._parseAsync({data:t.data,path:t.path,parent:r}),ctx:r}})).then(function(e){for(let t of e)if("valid"===t.result.status)return t.result;for(let r of e)if("dirty"===r.result.status)return t.common.issues.push(...r.ctx.common.issues),r.result;let r=e.map(e=>new F(e.ctx.common.issues));return V(t,{code:q.invalid_union,unionErrors:r}),W});{let e,a=[];for(let i of r){let r={...t,common:{...t.common,issues:[]},parent:null},n=i._parseSync({data:t.data,path:t.path,parent:r});if("valid"===n.status)return n;"dirty"!==n.status||e||(e={result:n,ctx:r}),r.common.issues.length&&a.push(r.common.issues)}if(e)return t.common.issues.push(...e.ctx.common.issues),e.result;let i=a.map(e=>new F(e));return V(t,{code:q.invalid_union,unionErrors:i}),W}}get options(){return this._def.options}}eT.create=(e,t)=>new eT({options:e,typeName:u.ZodUnion,...X(t)});class eZ extends ee{_parse(e){let{status:t,ctx:r}=this._processInputParams(e),a=(e,a)=>{if("aborted"===e.status||"aborted"===a.status)return W;let i=function e(t,r){let a=D(t),i=D(r);if(t===r)return{valid:!0,data:t};if(a===U.object&&i===U.object){let a=o.objectKeys(r),i=o.objectKeys(t).filter(e=>-1!==a.indexOf(e)),n={...t,...r};for(let a of(Object.prototype.hasOwnProperty.call(n,"__proto__")&&delete n.__proto__,i)){if("__proto__"===a)continue;let i=e(t[a],r[a]);if(!i.valid)return{valid:!1};n[a]=i.data}return{valid:!0,data:n}}if(a===U.array&&i===U.array){if(t.length!==r.length)return{valid:!1};let a=[];for(let i=0;ia(e,t)):a(this._def.left._parseSync({data:r.data,path:r.path,parent:r}),this._def.right._parseSync({data:r.data,path:r.path,parent:r}))}}eZ.create=(e,t,r)=>new eZ({left:e,right:t,typeName:u.ZodIntersection,...X(r)});class ez extends ee{_parse(e){let{status:t,ctx:r}=this._processInputParams(e);if(r.parsedType!==U.array)return V(r,{code:q.invalid_type,expected:U.array,received:r.parsedType}),W;if(r.data.lengththis._def.items.length&&(V(r,{code:q.too_big,maximum:this._def.items.length,inclusive:!0,exact:!1,type:"array"}),t.dirty());let a=[...r.data].map((e,t)=>{let a=this._def.items[t]||this._def.rest;return a?a._parse(new Y(r,e,r.path,t)):null}).filter(e=>!!e);return r.common.async?Promise.all(a).then(e=>K.mergeArray(t,e)):K.mergeArray(t,a)}get items(){return this._def.items}rest(e){return new ez({...this._def,rest:e})}}ez.create=(e,t)=>{if(!Array.isArray(e))throw Error("You must pass an array of schemas to z.tuple([ ... ])");return new ez({items:e,typeName:u.ZodTuple,rest:null,...X(t)})};class eE extends ee{get keySchema(){return this._def.keyType}get valueSchema(){return this._def.valueType}_parse(e){let{status:t,ctx:r}=this._processInputParams(e);if(r.parsedType!==U.map)return V(r,{code:q.invalid_type,expected:U.map,received:r.parsedType}),W;let a=this._def.keyType,i=this._def.valueType,n=[...r.data.entries()].map(([e,t],n)=>({key:a._parse(new Y(r,e,r.path,[n,"key"])),value:i._parse(new Y(r,t,r.path,[n,"value"]))}));if(r.common.async){let e=new Map;return Promise.resolve().then(async()=>{for(let r of n){let a=await r.key,i=await r.value;if("aborted"===a.status||"aborted"===i.status)return W;("dirty"===a.status||"dirty"===i.status)&&t.dirty(),e.set(a.value,i.value)}return{status:t.value,value:e}})}{let e=new Map;for(let r of n){let a=r.key,i=r.value;if("aborted"===a.status||"aborted"===i.status)return W;("dirty"===a.status||"dirty"===i.status)&&t.dirty(),e.set(a.value,i.value)}return{status:t.value,value:e}}}}eE.create=(e,t,r)=>new eE({valueType:t,keyType:e,typeName:u.ZodMap,...X(r)});class eI extends ee{_parse(e){let{status:t,ctx:r}=this._processInputParams(e);if(r.parsedType!==U.set)return V(r,{code:q.invalid_type,expected:U.set,received:r.parsedType}),W;let a=this._def;null!==a.minSize&&r.data.sizea.maxSize.value&&(V(r,{code:q.too_big,maximum:a.maxSize.value,type:"set",inclusive:!0,exact:!1,message:a.maxSize.message}),t.dirty());let i=this._def.valueType;function n(e){let r=new Set;for(let a of e){if("aborted"===a.status)return W;"dirty"===a.status&&t.dirty(),r.add(a.value)}return{status:t.value,value:r}}let s=[...r.data.values()].map((e,t)=>i._parse(new Y(r,e,r.path,t)));return r.common.async?Promise.all(s).then(e=>n(e)):n(s)}min(e,t){return new eI({...this._def,minSize:{value:e,message:d.toString(t)}})}max(e,t){return new eI({...this._def,maxSize:{value:e,message:d.toString(t)}})}size(e,t){return this.min(e,t).max(e,t)}nonempty(e){return this.min(1,e)}}eI.create=(e,t)=>new eI({valueType:e,minSize:null,maxSize:null,typeName:u.ZodSet,...X(t)});class eR extends ee{get schema(){return this._def.getter()}_parse(e){let{ctx:t}=this._processInputParams(e);return this._def.getter()._parse({data:t.data,path:t.path,parent:t})}}eR.create=(e,t)=>new eR({getter:e,typeName:u.ZodLazy,...X(t)});class eL extends ee{_parse(e){if(e.data!==this._def.value){let t=this._getOrReturnCtx(e);return V(t,{received:t.data,code:q.invalid_literal,expected:this._def.value}),W}return{status:"valid",value:e.data}}get value(){return this._def.value}}function eM(e,t){return new eU({values:e,typeName:u.ZodEnum,...X(t)})}eL.create=(e,t)=>new eL({value:e,typeName:u.ZodLiteral,...X(t)});class eU extends ee{_parse(e){if("string"!=typeof e.data){let t=this._getOrReturnCtx(e),r=this._def.values;return V(t,{expected:o.joinValues(r),received:t.parsedType,code:q.invalid_type}),W}if(this._cache||(this._cache=new Set(this._def.values)),!this._cache.has(e.data)){let t=this._getOrReturnCtx(e),r=this._def.values;return V(t,{received:t.data,code:q.invalid_enum_value,options:r}),W}return H(e.data)}get options(){return this._def.values}get enum(){let e={};for(let t of this._def.values)e[t]=t;return e}get Values(){let e={};for(let t of this._def.values)e[t]=t;return e}get Enum(){let e={};for(let t of this._def.values)e[t]=t;return e}extract(e,t=this._def){return eU.create(e,{...this._def,...t})}exclude(e,t=this._def){return eU.create(this.options.filter(t=>!e.includes(t)),{...this._def,...t})}}eU.create=eM;class eD extends ee{_parse(e){let t=o.getValidEnumValues(this._def.values),r=this._getOrReturnCtx(e);if(r.parsedType!==U.string&&r.parsedType!==U.number){let e=o.objectValues(t);return V(r,{expected:o.joinValues(e),received:r.parsedType,code:q.invalid_type}),W}if(this._cache||(this._cache=new Set(o.getValidEnumValues(this._def.values))),!this._cache.has(e.data)){let e=o.objectValues(t);return V(r,{received:r.data,code:q.invalid_enum_value,options:e}),W}return H(e.data)}get enum(){return this._def.values}}eD.create=(e,t)=>new eD({values:e,typeName:u.ZodNativeEnum,...X(t)});class eq extends ee{unwrap(){return this._def.type}_parse(e){let{ctx:t}=this._processInputParams(e);return t.parsedType!==U.promise&&!1===t.common.async?(V(t,{code:q.invalid_type,expected:U.promise,received:t.parsedType}),W):H((t.parsedType===U.promise?t.data:Promise.resolve(t.data)).then(e=>this._def.type.parseAsync(e,{path:t.path,errorMap:t.common.contextualErrorMap})))}}eq.create=(e,t)=>new eq({type:e,typeName:u.ZodPromise,...X(t)});class eF extends ee{innerType(){return this._def.schema}sourceType(){return this._def.schema._def.typeName===u.ZodEffects?this._def.schema.sourceType():this._def.schema}_parse(e){let{status:t,ctx:r}=this._processInputParams(e),a=this._def.effect||null,i={addIssue:e=>{V(r,e),e.fatal?t.abort():t.dirty()},get path(){return r.path}};if(i.addIssue=i.addIssue.bind(i),"preprocess"===a.type){let e=a.transform(r.data,i);if(r.common.async)return Promise.resolve(e).then(async e=>{if("aborted"===t.value)return W;let a=await this._def.schema._parseAsync({data:e,path:r.path,parent:r});return"aborted"===a.status?W:"dirty"===a.status||"dirty"===t.value?J(a.value):a});{if("aborted"===t.value)return W;let a=this._def.schema._parseSync({data:e,path:r.path,parent:r});return"aborted"===a.status?W:"dirty"===a.status||"dirty"===t.value?J(a.value):a}}if("refinement"===a.type){let e=e=>{let t=a.refinement(e,i);if(r.common.async)return Promise.resolve(t);if(t instanceof Promise)throw Error("Async refinement encountered during synchronous parse operation. Use .parseAsync instead.");return e};if(!1!==r.common.async)return this._def.schema._parseAsync({data:r.data,path:r.path,parent:r}).then(r=>"aborted"===r.status?W:("dirty"===r.status&&t.dirty(),e(r.value).then(()=>({status:t.value,value:r.value}))));{let a=this._def.schema._parseSync({data:r.data,path:r.path,parent:r});return"aborted"===a.status?W:("dirty"===a.status&&t.dirty(),e(a.value),{status:t.value,value:a.value})}}if("transform"===a.type)if(!1!==r.common.async)return this._def.schema._parseAsync({data:r.data,path:r.path,parent:r}).then(e=>"valid"!==e.status?W:Promise.resolve(a.transform(e.value,i)).then(e=>({status:t.value,value:e})));else{let e=this._def.schema._parseSync({data:r.data,path:r.path,parent:r});if("valid"!==e.status)return W;let n=a.transform(e.value,i);if(n instanceof Promise)throw Error("Asynchronous transform encountered during synchronous parse operation. Use .parseAsync instead.");return{status:t.value,value:n}}o.assertNever(a)}}eF.create=(e,t,r)=>new eF({schema:e,typeName:u.ZodEffects,effect:t,...X(r)}),eF.createWithPreprocess=(e,t,r)=>new eF({schema:t,effect:{type:"preprocess",transform:e},typeName:u.ZodEffects,...X(r)});class eB extends ee{_parse(e){return this._getType(e)===U.undefined?H(void 0):this._def.innerType._parse(e)}unwrap(){return this._def.innerType}}eB.create=(e,t)=>new eB({innerType:e,typeName:u.ZodOptional,...X(t)});class eV extends ee{_parse(e){return this._getType(e)===U.null?H(null):this._def.innerType._parse(e)}unwrap(){return this._def.innerType}}eV.create=(e,t)=>new eV({innerType:e,typeName:u.ZodNullable,...X(t)});class eK extends ee{_parse(e){let{ctx:t}=this._processInputParams(e),r=t.data;return t.parsedType===U.undefined&&(r=this._def.defaultValue()),this._def.innerType._parse({data:r,path:t.path,parent:t})}removeDefault(){return this._def.innerType}}eK.create=(e,t)=>new eK({innerType:e,typeName:u.ZodDefault,defaultValue:"function"==typeof t.default?t.default:()=>t.default,...X(t)});class eW extends ee{_parse(e){let{ctx:t}=this._processInputParams(e),r={...t,common:{...t.common,issues:[]}},a=this._def.innerType._parse({data:r.data,path:r.path,parent:{...r}});return G(a)?a.then(e=>({status:"valid",value:"valid"===e.status?e.value:this._def.catchValue({get error(){return new F(r.common.issues)},input:r.data})})):{status:"valid",value:"valid"===a.status?a.value:this._def.catchValue({get error(){return new F(r.common.issues)},input:r.data})}}removeCatch(){return this._def.innerType}}eW.create=(e,t)=>new eW({innerType:e,typeName:u.ZodCatch,catchValue:"function"==typeof t.catch?t.catch:()=>t.catch,...X(t)});class eJ extends ee{_parse(e){if(this._getType(e)!==U.nan){let t=this._getOrReturnCtx(e);return V(t,{code:q.invalid_type,expected:U.nan,received:t.parsedType}),W}return{status:"valid",value:e.data}}}eJ.create=e=>new 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i=w.length>0?w:[{role:"user",content:j}];r=` + api_key="${x||"YOUR_LITELLM_API_KEY"}", + base_url="${b}"${A} +)`;switch(c){case t.EndpointType.CHAT:{let e=Object.keys(E).length>0,t="";if(e){let e=JSON.stringify({metadata:E},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();t=`, + extra_body=${e}`}let a=j.length>0?j:[{role:"user",content:v}];r=` import base64 # Helper function to encode images to base64 @@ -21,8 +21,8 @@ def encode_image(image_path): # Example with text only response = client.chat.completions.create( - model="${N}", - messages=${JSON.stringify(i,null,4)}${t} + model="${O}", + messages=${JSON.stringify(a,null,4)}${t} ) print(response) @@ -30,14 +30,14 @@ print(response) # Example with image or PDF (uncomment and provide file path to use) # base64_file = encode_image("path/to/your/file.jpg") # or .pdf # response_with_file = client.chat.completions.create( -# model="${N}", +# model="${O}", # messages=[ # { # "role": "user", # "content": [ # { # "type": "text", -# "text": "${v}" +# "text": "${N}" # }, # { # "type": "image_url", @@ -50,8 +50,8 @@ print(response) # ]${t} # ) # print(response_with_file) -`;break}case t.EndpointType.RESPONSES:{let e=Object.keys(k).length>0,t="";if(e){let e=JSON.stringify({metadata:k},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();t=`, - extra_body=${e}`}let i=w.length>0?w:[{role:"user",content:j}];r=` +`;break}case t.EndpointType.RESPONSES:{let e=Object.keys(E).length>0,t="";if(e){let e=JSON.stringify({metadata:E},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();t=`, + extra_body=${e}`}let a=j.length>0?j:[{role:"user",content:v}];r=` import base64 # Helper function to encode images to base64 @@ -61,8 +61,8 @@ def encode_image(image_path): # Example with text only response = client.responses.create( - model="${N}", - input=${JSON.stringify(i,null,4)}${t} + model="${O}", + input=${JSON.stringify(a,null,4)}${t} ) print(response.output_text) @@ -70,22 +70,23 @@ print(response.output_text) # Example with image or PDF (uncomment and provide file path to use) # base64_file = encode_image("path/to/your/file.jpg") # or .pdf # response_with_file = client.responses.create( -# model="${N}", +# model="${O}", # input=[ # { # "role": "user", # "content": [ -# {"type": "input_text", "text": "${v}"}, +# {"type": "input_text", "text": "${N}"}, # { # "type": "input_image", # "image_url": f"data:image/jpeg;base64,{base64_file}", # or data:application/pdf;base64,{base64_file} +# "detail": "auto", # }, # ], # } # ]${t} # ) # print(response_with_file.output_text) -`;break}case t.EndpointType.IMAGE:r="azure"===f?` +`;break}case t.EndpointType.IMAGE:r="azure"===_?` # NOTE: The Azure SDK does not have a direct equivalent to the multi-modal 'responses.create' method shown for OpenAI. # This snippet uses 'client.images.generate' and will create a new image based on your prompt. # It does not use the uploaded image, as 'client.images.generate' does not support image inputs in this context. @@ -96,7 +97,7 @@ import time from PIL import Image result = client.images.generate( - model="${N}", + model="${O}", prompt="${n}", n=1 ) @@ -152,7 +153,7 @@ def create_file(image_path): return f"file_{os.path.basename(image_path).replace('.', '_')}" # The prompt entered by the user -prompt = "${v}" +prompt = "${N}" # Encode images to base64 base64_image1 = encode_image("body-lotion.png") @@ -163,7 +164,7 @@ file_id1 = create_file("body-lotion.png") file_id2 = create_file("incense-kit.png") response = client.responses.create( - model="${N}", + model="${O}", input=[ { "role": "user", @@ -172,18 +173,22 @@ response = client.responses.create( { "type": "input_image", "image_url": f"data:image/jpeg;base64,{base64_image1}", + "detail": "auto", }, { "type": "input_image", "image_url": f"data:image/jpeg;base64,{base64_image2}", + "detail": "auto", }, { "type": "input_image", "file_id": file_id1, + "detail": "auto", }, { "type": "input_image", "file_id": file_id2, + "detail": "auto", } ], } @@ -216,7 +221,7 @@ else: print("No image data found in response.") print("Full response for debugging:") print(response) -`;break;case t.EndpointType.IMAGE_EDITS:r="azure"===f?` +`;break;case t.EndpointType.IMAGE_EDITS:r="azure"===_?` import base64 import os import time @@ -230,7 +235,7 @@ def encode_image(image_path): return base64.b64encode(image_file.read()).decode('utf-8') # The prompt entered by the user -prompt = "${v}" +prompt = "${N}" # Encode images to base64 base64_image1 = encode_image("body-lotion.png") @@ -241,7 +246,7 @@ file_id1 = create_file("body-lotion.png") file_id2 = create_file("incense-kit.png") response = client.responses.create( - model="${N}", + model="${O}", input=[ { "role": "user", @@ -250,18 +255,22 @@ response = client.responses.create( { "type": "input_image", "image_url": f"data:image/jpeg;base64,{base64_image1}", + "detail": "auto", }, { "type": "input_image", "image_url": f"data:image/jpeg;base64,{base64_image2}", + "detail": "auto", }, { "type": "input_image", "file_id": file_id1, + "detail": "auto", }, { "type": "input_image", "file_id": file_id2, + "detail": "auto", } ], } @@ -311,7 +320,7 @@ def create_file(image_path): return f"file_{os.path.basename(image_path).replace('.', '_')}" # The prompt entered by the user -prompt = "${v}" +prompt = "${N}" # Encode images to base64 base64_image1 = encode_image("body-lotion.png") @@ -322,7 +331,7 @@ file_id1 = create_file("body-lotion.png") file_id2 = create_file("incense-kit.png") response = client.responses.create( - model="${N}", + model="${O}", input=[ { "role": "user", @@ -331,18 +340,22 @@ response = client.responses.create( { "type": "input_image", "image_url": f"data:image/jpeg;base64,{base64_image1}", + "detail": "auto", }, { "type": "input_image", "image_url": f"data:image/jpeg;base64,{base64_image2}", + "detail": "auto", }, { "type": "input_image", "file_id": file_id1, + "detail": "auto", }, { "type": "input_image", "file_id": file_id2, + "detail": "auto", } ], } @@ -378,7 +391,7 @@ else: `;break;case t.EndpointType.EMBEDDINGS:r=` response = client.embeddings.create( input="${n||"Your string here"}", - model="${N}", + model="${O}", encoding_format="base64" # or "float" ) @@ -389,7 +402,7 @@ audio_file = open("path/to/your/audio/file.mp3", "rb") # Make the transcription request response = client.audio.transcriptions.create( - model="${N}", + model="${O}", file=audio_file${n?`, prompt="${n.replace(/\\/g,"\\\\").replace(/"/g,'\\"')}"`:""} ) @@ -398,9 +411,9 @@ print(response.text) `;break;case t.EndpointType.SPEECH:r=` # Make the text-to-speech request response = client.audio.speech.create( - model="${N}", + model="${O}", input="${n||"Your text to convert to speech here"}", - voice="${c}" # Options: alloy, ash, ballad, coral, echo, fable, nova, onyx, sage, shimmer + voice="${m}" # Options: alloy, ash, ballad, coral, echo, fable, nova, onyx, sage, shimmer ) # Save the audio to a file @@ -410,12 +423,12 @@ print(f"Audio saved to {output_filename}") # 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Recommended: 30% quality / 70% cost split."})]}),(0,t.jsxs)("div",{children:[(0,t.jsx)("strong",{className:"mb-1 block font-semibold",children:"Eligible Model Pool"}),(0,t.jsx)(p.RadioGroup,{value:a,onValueChange:t=>{s({...e,adaptive_eligible:t})},className:"w-full",children:(0,t.jsxs)("div",{className:"flex w-full flex-col items-start gap-2",children:[(0,t.jsxs)(h.Label,{className:"items-start font-normal leading-normal",children:[(0,t.jsx)(p.RadioGroupItem,{value:"all",className:"mt-0.5"}),(0,t.jsxs)("span",{children:[(0,t.jsx)("strong",{className:"font-semibold",children:"All tiers (soft floor)"})," ",(0,t.jsx)("span",{className:"text-muted-foreground",children:"— router can pick across tiers, depending on the best fit for the prompt"})]})]}),(0,t.jsxs)(h.Label,{className:"items-start font-normal leading-normal",children:[(0,t.jsx)(p.RadioGroupItem,{value:"classified_tier",className:"mt-0.5"}),(0,t.jsxs)("span",{children:[(0,t.jsx)("strong",{className:"font-semibold",children:"Classified tier only"})," ",(0,t.jsx)("span",{className:"text-muted-foreground",children:"— router can only pick models within tier"})]})]})]})})]}),"all"===a&&(0,t.jsxs)("div",{children:[(0,t.jsx)("strong",{className:"mb-1 block font-semibold",children:"Tier Distance Penalty"}),(0,t.jsx)(m.Input,{type:"number",value:r,onChange:t=>{var i;return i=""===t.target.value?null:t.target.valueAsNumber,void s({...e,tier_distance_penalty:i??A.DEFAULT_TIER_DISTANCE_PENALTY})},min:0,step:.1,className:"w-full"}),(0,t.jsx)("span",{className:"text-xs text-muted-foreground",children:"Score penalty applied per tier-step away from the classified tier."})]})]})]})},z=(e,t)=>{if(""===e.trim())return;let s=Number(e);return Number.isFinite(s)?Math.max(t,Math.trunc(s)):void 0},H=({value:e,onChange:s})=>{let i=e.cache_aware_routing??!1,a=e.custom_tier_set?"Use the built-in tiers to enable cache-aware routing.":e.adaptive?"Turn off Adaptive Routing to enable cache-aware routing.":"every_request"!==(0,A.classificationFrequency)(e)?'Set "How often to classify" to every request to enable cache-aware routing.':Object.values(e.tiers).some(e=>e.length>1)?"Choose one model per tier to enable cache-aware routing.":Object.values(e.tier_model_params??{}).some(e=>Object.values(e).some(e=>Object.keys(e).length>0))?"Remove per-model parameter overrides to enable cache-aware routing.":null;return(0,t.jsxs)("div",{className:"space-y-3",children:[(0,t.jsxs)("div",{className:"flex items-center gap-2",children:[(0,t.jsx)(f.Switch,{checked:i,disabled:!i&&null!==a,onCheckedChange:t=>s({...e,cache_aware_routing:t}),"aria-label":"Cache-aware routing"}),(0,t.jsx)("span",{className:"text-sm font-medium",children:"Consider prompt-cache savings"})]}),(0,t.jsx)("p",{className:"text-xs text-muted-foreground",children:"Disabled by default. 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Off means requests dispatch on complexity alone."}),i&&(0,t.jsxs)("div",{style:{maxWidth:320},children:[(0,t.jsx)("label",{className:"block text-sm font-medium mb-1",htmlFor:"context-window-escalation-buffer",children:"Window fit buffer"}),(0,t.jsx)(m.Input,{id:"context-window-escalation-buffer",inputMode:"decimal",value:a??e.context_window_escalation_buffer??"",placeholder:"0.95",onChange:e=>r(e.target.value),onBlur:t=>(t=>{if(r(null),""===t.trim())return void s({...e,context_window_escalation_buffer:void 0});let i=Number(t);Number.isFinite(i)&&s({...e,context_window_escalation_buffer:Math.min(1,Math.max(.01,i))})})(t.target.value)}),(0,t.jsx)("span",{className:"block text-xs mt-1 text-muted-foreground",children:"Fraction of a model's window the counted prompt must fit within, above 0 up to 1. 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Off forwards the caller's value unchanged."})]})],808667);let V=(e,t,s)=>{let i=Number(e);return Number.isFinite(i)?Math.max(t,Math.trunc(i)):s},G=({value:e,onChange:s})=>{let i,a=e.stall_escalation_enabled??!1,r="session"===(i=(0,A.classificationFrequency)(e))?'Set "How often to classify" to every request under Advanced: Classification Method to use this. Scoring once per session replays that model instead of classifying, so a stall never reaches the classifier.':"user_turn"===i?'Set "How often to classify" to every request under Advanced: Classification Method to use this. 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0},eT=ef?.map(({open:e,close:t})=>({open:e.trim().toLowerCase(),close:t.trim().toLowerCase()})),eS=Object.fromEntries(Object.entries({code_keywords:eC(eo),reasoning_keywords:eC(ed),technical_keywords:eC(ec),simple_keywords:eC(eu),plan_mode_patterns:eC(em),housekeeping_patterns:eC(ep)}).filter(([,e])=>void 0!==e)),ek="custom"===p&&void 0!==eg&&Number.isInteger(eg)&&eg>0,eI=!c&&!eN&&(0,s.usesLlmClassifier)(ew),eR=eN||ea?Object.fromEntries(Object.entries(e).filter(([,e])=>e.length>0)):e,eE={tiers:ea&&!c?Object.fromEntries(Object.entries(eR).map(([e,t])=>[e,1===t.length?t[0]:t])):eR,...!c&&d&&{enable_non_reasoning_tier:!0},...eb&&{tier_model_configs:eb},...u?.trim()&&{default_model:u},...m?.trim()&&{plan_mode_min_tier:m},...ej&&{tier_labels:ej},classifier_type:"jev"===p?"oss_classifier":p,...(0,s.isHeuristicChain)(ew)&&void 0!==f&&{local_heuristic:f},..."jev"===ew&&{opensource_classifier_config:(0,i.normalizeJevClassifierConfig)(v)},...void 0!==x&&{heuristic_v2_success_threshold:x},...((e,{classifierLlmConfig:i,classifierFallback:a,heuristicFirstMaxTier:r,hybridBoundaryMargin:l,classifierContextWindowSize:n,classifierContextBudgetChars:o,classifierContextPerTurnChars:d,classifierContextIncludeAssistantTurns:c})=>{let u=(0,s.usesClassifierContext)(e)&&!(0,t.isForecastClassifier)(e);return{...(0,s.usesLlmClassifier)(e)&&i&&{classifier_llm_config:(0,t.isForecastClassifier)(e)?(0,t.withoutForecastPromptOverrides)(i):(({model:e,timeout_ms:t,circuit_breaker_enabled:s,circuit_breaker_cooldown_seconds:i,reasoning_effort:a,classification_rubric:r,system_prompt:l,vision:n})=>l?.trim()?{model:e,timeout_ms:t,...void 0!==s&&{circuit_breaker_enabled:s},...void 0!==i&&{circuit_breaker_cooldown_seconds:i},...a&&{reasoning_effort:a},...n&&{vision:n},system_prompt:l}:{model:e,timeout_ms:t,...void 0!==s&&{circuit_breaker_enabled:s},...void 0!==i&&{circuit_breaker_cooldown_seconds:i},...a&&{reasoning_effort:a},...r&&{classification_rubric:r},...n&&{vision:n}})(i)},...u&&void 0!==a&&{classifier_fallback:a},..."heuristic_first"===e&&r?.trim()&&{heuristic_first_max_tier:r},..."hybrid"===e&&void 0!==l&&{hybrid_boundary_margin:l},...(0,s.usesClassifierContext)(e)&&void 0!==n&&{classifier_context_window_size:n},...(0,s.usesClassifierContext)(e)&&void 0!==o&&{classifier_context_budget_chars:o},...(0,s.usesClassifierContext)(e)&&void 0!==d&&{classifier_context_per_turn_chars:d},...(0,s.usesClassifierContext)(e)&&void 0!==c&&{classifier_context_include_assistant_turns:c}}})(ew,{classifierLlmConfig:_,classifierFallback:T,heuristicFirstMaxTier:I,hybridBoundaryMargin:R,classifierContextWindowSize:j,classifierContextBudgetChars:w,classifierContextPerTurnChars:N,classifierContextIncludeAssistantTurns:C}),..."capability"===ew&&g&&{capability_classifier_config:g},..."llm_v2"===ew&&{llm_v2_config:b},...eN&&{adaptive:!1},...eI&&!_?.system_prompt?.trim()&&{...S?.trim()&&{classification_prompt:S.trim()},...k?.trim()&&{classification_examples:k.trim()}},classification_mode:E??o.DEFAULT_CLASSIFICATION_MODE,session_affinity:A,deployment_affinity:O,modality_routing:M??!1,modality_pin_override:L??!1,...F.length>0&&{custom_technical_keywords:F},...ev.length>0&&{keyword_tier_rules:ev},escalation_keywords:eN?[]:e_,...q&&{stall_escalation_enabled:!0,...void 0!==z&&{stall_escalation_window:z},...void 0!==H&&{stall_escalation_repeat_threshold:H}},...P&&{semantic_keyword_matching:!0,embedding_model:$,match_threshold:U},...V&&!eN&&{adaptive:!0,adaptive_weights:G,..."all"===W&&{tier_distance_penalty:K},adaptive_eligible:W},...Y&&{return_raw_model_name:!0},...void 0!==ea&&{cache_aware_routing:ea},...void 0!==er&&{cache_aware_routing_output_tokens:er},...void 0!==el&&{cache_aware_routing_timeout_ms:el},...(eN||void 0!==es)&&{enable_context_window_escalation:es??!1},...(!eN||!0===es)&&void 0!==ei&&{context_window_escalation_buffer:ei},...void 0!==en&&{session_affinity_ttl_seconds:en},...eS,...!1===eh&&{route_housekeeping_to_cheapest_tier:!1},...eT&&eT.length>0&&{reminder_markers:eT},...!1===ex&&{max_tokens_from_tier_model:!1},...ek&&{classifier_plugin_timeout_ms:eg},...ey};return c?{...Object.fromEntries(Object.entries(eE).filter(([e])=>!y.includes(e))),...((e,{classifierType:t,classifierLlmConfig:s,planModeMinTierId:i,classificationPrompt:r,classificationExamples:l})=>{let n=e.tiers,o=(0,a.tierRowById)(n,e.fallback_tier_id),d=(0,a.tierRowById)(n,i);return{tiers:Object.fromEntries(n.map(e=>[(0,a.activeTierName)(e),e.models])),tier_definitions:(0,a.tierDefinitionsFromRows)(n),...o&&{fallback_tier:(0,a.activeTierName)(o)},classifier_type:"jev"===t?"oss_classifier":"llm",..."jev"!==t&&s&&{classifier_llm_config:{model:s.model,timeout_ms:s.timeout_ms,...void 0!==s.circuit_breaker_enabled&&{circuit_breaker_enabled:s.circuit_breaker_enabled},...void 0!==s.circuit_breaker_cooldown_seconds&&{circuit_breaker_cooldown_seconds:s.circuit_breaker_cooldown_seconds},...s.reasoning_effort&&{reasoning_effort:s.reasoning_effort},...s.vision&&{vision:s.vision}}},session_affinity:!1,..."jev"!==t&&r?.trim()&&{classification_prompt:r.trim()},..."jev"!==t&&l?.trim()&&{classification_examples:l.trim()},...d&&{plan_mode_min_tier:(0,a.activeTierName)(d)}}})(c,{classifierType:ew,classifierLlmConfig:_,planModeMinTierId:m,classificationPrompt:S,classificationExamples:k})}:eE}},131688,e=>{"use strict";let t=e=>["llm","heuristic_first","hybrid","capability","llm_v2"].some(t=>t===e);e.s(["isHeuristicChain",0,e=>"heuristic_first"===e||"hybrid"===e,"usesClassifierContext",0,e=>"jev"===e||t(e),"usesLlmClassifier",0,t])},430597,e=>{"use strict";let t=e=>Array.isArray(e)?e.filter(e=>"string"==typeof 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UI"}],["$","link","2",{"rel":"icon","href":"/favicon.ico?favicon.34m4ev7_7ennf.ico","sizes":"48x48","type":"image/x-icon"}],["$","link","3",{"rel":"icon","href":"/get_favicon"}],["$","$L22","4",{}]] diff --git a/litellm/proxy/_lazy_features.py b/litellm/proxy/_lazy_features.py index a7adb5c1bf5..0e2eed73364 100644 --- a/litellm/proxy/_lazy_features.py +++ b/litellm/proxy/_lazy_features.py @@ -275,7 +275,7 @@ LAZY_FEATURES: Final[tuple[LazyFeature, ...]] = ( LazyFeature( name="decisions", module_path="litellm.proxy.decisions_endpoints.endpoints", - path_prefixes=("/v1/decisions", "/decisions", "/v1/systemone", "/systemone"), + path_prefixes=("/v1/decisions", "/decisions", "/v1/systemone", "/systemone", "/v1/extraction", "/extraction"), ), LazyFeature( name="claude_code_marketplace", diff --git a/litellm/proxy/_lazy_openapi_snapshot.json b/litellm/proxy/_lazy_openapi_snapshot.json index 7198d74909c..545b317055a 100644 --- a/litellm/proxy/_lazy_openapi_snapshot.json +++ b/litellm/proxy/_lazy_openapi_snapshot.json @@ -9829,6 +9829,249 @@ "title": "DecisionsUsage", "type": "object" }, + "ExtractionAnswer": { + "additionalProperties": true, + "properties": { + "confidence": { + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ], + "title": "Confidence" + }, + "guess": { + "$ref": "#/components/schemas/JsonValue" + }, + "mean": { + "$ref": "#/components/schemas/JsonValue" + }, + "median": { + "$ref": "#/components/schemas/JsonValue" + }, + "p10": { + "$ref": "#/components/schemas/JsonValue" + }, + "p90": { + "$ref": "#/components/schemas/JsonValue" + }, + "p_above": { + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ], + "title": "P Above" + }, + "p_below": { + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ], + "title": "P Below" + }, + "p_null": { + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ], + "title": "P Null" + }, + "quantiles": { + "anyOf": [ + { + "items": { + "$ref": "#/components/schemas/JsonValue" + }, + "type": "array" + }, + { + "type": "null" + } + ], + "title": "Quantiles" + }, + "span": { + "anyOf": [ + { + "items": { + "type": "integer" + }, + "type": "array" + }, + { + "type": "null" + } + ], + "title": "Span" + }, + "spans": { + "anyOf": [ + { + "items": { + "items": { + "type": "integer" + }, + "type": "array" + }, + "type": "array" + }, + { + "type": "null" + } + ], + "title": "Spans" + }, + "steps": { + "anyOf": [ + { + "items": { + "$ref": "#/components/schemas/JsonValue" + }, + "type": "array" + }, + { + "type": "null" + } + ], + "title": "Steps" + }, + "type": { + "title": "Type", + "type": "string" + }, + "value": { + "$ref": "#/components/schemas/JsonValue", + "description": "The answer, null when the input does not determine it" + } + }, + "required": [ + "type", + "value" + ], + "title": "ExtractionAnswer", + "type": "object" + }, + "ExtractionResponse": { + "additionalProperties": true, + "properties": { + "answers": { + "additionalProperties": { + "$ref": "#/components/schemas/ExtractionAnswer" + }, + "title": "Answers", + "type": "object" + }, + "model": { + "title": "Model", + "type": "string" + }, + "state_text": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "State Text" + }, + "truncated": { + "title": "Truncated", + "type": "boolean" + }, + "usage": { + "$ref": "#/components/schemas/ExtractionUsage" + } + }, + "required": [ + "model", + "answers", + "truncated", + "usage" + ], + "title": "ExtractionResponse", + "type": "object" + }, + "ExtractionUsage": { + "additionalProperties": true, + "properties": { + "image_tokens": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "null" + } + ], + "title": "Image Tokens" + }, + "input_tokens": { + "title": "Input Tokens", + "type": "integer" + }, + "output_tokens": { + "title": "Output Tokens", + "type": "integer" + }, + "passes": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "null" + } + ], + "title": "Passes" + }, + "schema_tokens": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "null" + } + ], + "title": "Schema Tokens" + }, + "state_tokens": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "null" + } + ], + "title": "State Tokens" + } + }, + "required": [ + "input_tokens", + "output_tokens" + ], + "title": "ExtractionUsage", + "type": "object" + }, + "JsonValue": {}, "NoulAnswer": { "additionalProperties": true, "properties": { @@ -10765,6 +11008,403 @@ ] } }, + "/extraction": { + "post": { + "description": "Read a `state` text and up to 4 images and get one typed answer per named field in `fields`.\n\nField types are `text`, `number`, `date`, `time`, `datetime`, `duration`, `list` (set `items`), `estimate`\n(set `min` and `max`) and `forecast` (set `min`, `max` and `horizon`). Each answer carries its `value`, which is\nnull when the input does not determine it, plus `confidence`, `p_null`, text `span`s into the state and, for\nestimates, `mean`, `median`, `p10` and `p90`. Images are data URLs or `{content_type, base64}` objects, remote\nURLs are not accepted. An unknown field type, a field name that is not 1 to 64 letters, digits, `_`, `.` or `-`\nstarting with a letter or `_`, a remote image URL or more than 4 images is rejected with a 400 before any\nprovider is called. Any other top-level key, `stream: true` and OpenAI generation settings such as `temperature`\nincluded, is rejected with a 400 naming it unless `drop_params` or the deployment's `additional_drop_params`\ndrops it. Settings inside `fields` and `options` go to the provider as sent, so a field missing a setting its\ntype needs or an empty `state` with no images comes back with the provider's own error. `model` is any\nextraction model in the proxy model list, such as Cloudflare Clairic. The request and the answers keep the\nprovider's format.", + "operationId": "extraction_extraction_post", + "requestBody": { + "content": { + "application/json": { + "example": { + "fields": { + "days_to_pay": { + "max": 90, + "min": 0, + "type": "estimate" + }, + "invoice_date": { + "type": "date" + }, + "items": { + "instructions": "What was bought?", + "items": "text", + "type": "list" + }, + "total": { + "type": "number", + "unit": "USD" + }, + "vendor": { + "instructions": "Who sent the invoice?", + "type": "text" + } + }, + "model": "clairic", + "state": "Invoice #4471 from Acme Tools, dated 2026-03-03. 12 hammers. Total $174. Payment due in 30 days." + }, + "schema": { + "additionalProperties": true, + "properties": { + "fields": { + "description": "Field name to typed field spec. Each name becomes a key in the answers", + "minProperties": 1, + "patternProperties": { + "^[A-Za-z_][A-Za-z0-9_.\\-]{0,63}$": { + "additionalProperties": true, + "properties": { + "decimals": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "number" + }, + { + "type": "null" + } + ], + "description": "Numbers, durations and number lists only, 0 to 6", + "title": "Decimals" + }, + "horizon": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "number" + }, + { + "type": "null" + } + ], + "description": "Forecast only, number of steps", + "title": "Horizon" + }, + "instructions": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "What the field should contain", + "title": "Instructions" + }, + "integer": { + "anyOf": [ + { + "type": "boolean" + }, + { + "type": "null" + } + ], + "description": "Numbers and durations only", + "title": "Integer" + }, + "interval": { + "anyOf": [ + { + "enum": [ + "step", + "minute", + "hour", + "day", + "week", + "month", + "quarter", + "year" + ], + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Interval" + }, + "items": { + "anyOf": [ + { + "enum": [ + "text", + "number", + "date" + ], + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Item type, required for list fields", + "title": "Items" + }, + "max": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "number" + }, + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Estimate and forecast upper bound", + "title": "Max" + }, + "min": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "number" + }, + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Estimate and forecast lower bound", + "title": "Min" + }, + "null_threshold": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "number" + }, + { + "type": "null" + } + ], + "description": "Probability of null above which the value is null", + "title": "Null Threshold" + }, + "scale": { + "anyOf": [ + { + "enum": [ + "linear", + "log" + ], + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Scale" + }, + "step": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "number" + }, + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Estimate grid step, or month or year", + "title": "Step" + }, + "type": { + "description": "The answer type for this field", + "enum": [ + "text", + "number", + "date", + "time", + "datetime", + "duration", + "list", + "estimate", + "forecast" + ], + "title": "Type", + "type": "string" + }, + "unit": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Unit label. For durations, seconds through years", + "title": "Unit" + } + }, + "required": [ + "type" + ], + "title": "ExtractionField", + "type": "object" + } + }, + "title": "Fields", + "type": "object" + }, + "images": { + "anyOf": [ + { + "items": { + "anyOf": [ + { + "pattern": "^[Dd][Aa][Tt][Aa]:", + "type": "string" + }, + { + "additionalProperties": true, + "properties": { + "base64": { + "description": "Base64-encoded image bytes", + "title": "Base64", + "type": "string" + }, + "content_type": { + "description": "The image media type, such as image/png", + "title": "Content Type", + "type": "string" + } + }, + "required": [ + "content_type", + "base64" + ], + "title": "ExtractionBase64Image", + "type": "object" + } + ] + }, + "maxItems": 4, + "type": "array" + }, + { + "type": "null" + } + ], + "description": "Up to 4 images as data URLs or content_type plus base64, no remote URLs", + "title": "Images" + }, + "model": { + "description": "An extraction model from the proxy model_list", + "title": "Model", + "type": "string" + }, + "options": { + "anyOf": [ + { + "additionalProperties": true, + "properties": { + "include_quantiles": { + "anyOf": [ + { + "type": "boolean" + }, + { + "type": "null" + } + ], + "description": "Add 99 percentiles to estimates", + "title": "Include Quantiles" + }, + "return_state_text": { + "anyOf": [ + { + "type": "boolean" + }, + { + "type": "null" + } + ], + "description": "Return the text that spans index into", + "title": "Return State Text" + } + }, + "title": "ExtractionOptions", + "type": "object" + }, + { + "type": "null" + } + ] + }, + "reference_date": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "ISO date that anchors dates written without a year", + "title": "Reference Date" + }, + "state": { + "default": "", + "description": "The text to read. Must be non-empty unless images are sent. Text answers are spans of it", + "title": "State", + "type": "string" + } + }, + "required": [ + "fields", + "model" + ], + "title": "ExtractionRequest", + "type": "object" + } + } + }, + "required": true + }, + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/ExtractionResponse" + } + } + }, + "description": "Successful Response" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Extract typed fields from a state", + "tags": [ + "decisions" + ] + } + }, "/systemone": { "post": { "description": "Judge a `state` against 1 to 128 named `questions` and get one calibrated answer per question name.\n\nQuestion types are `noul` (probability the answer is yes), `choice` (one label out of `criteria`, with\n`confidence` and `probabilities`), `score` (an index into the `criteria` levels, with `confidence`,\n`legend` and `probabilities`) and `box` (the image region the `instructions` describe, with `confidence`).\nTypeSafe models also take images in `assets`, each one referenced by its key in `state`. Requests that break\nthese rules are rejected with a 400 before any provider is called. `model` is any decision model in the proxy model list. OpenAI decision models accept this format\ntoo, LiteLLM translates it and keeps the answers keyed by question name. Streaming is not supported.\n\n[Docs](https://docs.litellm.ai/docs/decisions)", @@ -11775,6 +12415,403 @@ ] } }, + "/v1/extraction": { + "post": { + "description": "Read a `state` text and up to 4 images and get one typed answer per named field in `fields`.\n\nField types are `text`, `number`, `date`, `time`, `datetime`, `duration`, `list` (set `items`), `estimate`\n(set `min` and `max`) and `forecast` (set `min`, `max` and `horizon`). Each answer carries its `value`, which is\nnull when the input does not determine it, plus `confidence`, `p_null`, text `span`s into the state and, for\nestimates, `mean`, `median`, `p10` and `p90`. Images are data URLs or `{content_type, base64}` objects, remote\nURLs are not accepted. An unknown field type, a field name that is not 1 to 64 letters, digits, `_`, `.` or `-`\nstarting with a letter or `_`, a remote image URL or more than 4 images is rejected with a 400 before any\nprovider is called. Any other top-level key, `stream: true` and OpenAI generation settings such as `temperature`\nincluded, is rejected with a 400 naming it unless `drop_params` or the deployment's `additional_drop_params`\ndrops it. Settings inside `fields` and `options` go to the provider as sent, so a field missing a setting its\ntype needs or an empty `state` with no images comes back with the provider's own error. `model` is any\nextraction model in the proxy model list, such as Cloudflare Clairic. The request and the answers keep the\nprovider's format.", + "operationId": "extraction_v1_extraction_post", + "requestBody": { + "content": { + "application/json": { + "example": { + "fields": { + "days_to_pay": { + "max": 90, + "min": 0, + "type": "estimate" + }, + "invoice_date": { + "type": "date" + }, + "items": { + "instructions": "What was bought?", + "items": "text", + "type": "list" + }, + "total": { + "type": "number", + "unit": "USD" + }, + "vendor": { + "instructions": "Who sent the invoice?", + "type": "text" + } + }, + "model": "clairic", + "state": "Invoice #4471 from Acme Tools, dated 2026-03-03. 12 hammers. Total $174. Payment due in 30 days." + }, + "schema": { + "additionalProperties": true, + "properties": { + "fields": { + "description": "Field name to typed field spec. Each name becomes a key in the answers", + "minProperties": 1, + "patternProperties": { + "^[A-Za-z_][A-Za-z0-9_.\\-]{0,63}$": { + "additionalProperties": true, + "properties": { + "decimals": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "number" + }, + { + "type": "null" + } + ], + "description": "Numbers, durations and number lists only, 0 to 6", + "title": "Decimals" + }, + "horizon": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "number" + }, + { + "type": "null" + } + ], + "description": "Forecast only, number of steps", + "title": "Horizon" + }, + "instructions": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "What the field should contain", + "title": "Instructions" + }, + "integer": { + "anyOf": [ + { + "type": "boolean" + }, + { + "type": "null" + } + ], + "description": "Numbers and durations only", + "title": "Integer" + }, + "interval": { + "anyOf": [ + { + "enum": [ + "step", + "minute", + "hour", + "day", + "week", + "month", + "quarter", + "year" + ], + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Interval" + }, + "items": { + "anyOf": [ + { + "enum": [ + "text", + "number", + "date" + ], + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Item type, required for list fields", + "title": "Items" + }, + "max": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "number" + }, + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Estimate and forecast upper bound", + "title": "Max" + }, + "min": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "number" + }, + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Estimate and forecast lower bound", + "title": "Min" + }, + "null_threshold": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "number" + }, + { + "type": "null" + } + ], + "description": "Probability of null above which the value is null", + "title": "Null Threshold" + }, + "scale": { + "anyOf": [ + { + "enum": [ + "linear", + "log" + ], + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Scale" + }, + "step": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "number" + }, + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Estimate grid step, or month or year", + "title": "Step" + }, + "type": { + "description": "The answer type for this field", + "enum": [ + "text", + "number", + "date", + "time", + "datetime", + "duration", + "list", + "estimate", + "forecast" + ], + "title": "Type", + "type": "string" + }, + "unit": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Unit label. For durations, seconds through years", + "title": "Unit" + } + }, + "required": [ + "type" + ], + "title": "ExtractionField", + "type": "object" + } + }, + "title": "Fields", + "type": "object" + }, + "images": { + "anyOf": [ + { + "items": { + "anyOf": [ + { + "pattern": "^[Dd][Aa][Tt][Aa]:", + "type": "string" + }, + { + "additionalProperties": true, + "properties": { + "base64": { + "description": "Base64-encoded image bytes", + "title": "Base64", + "type": "string" + }, + "content_type": { + "description": "The image media type, such as image/png", + "title": "Content Type", + "type": "string" + } + }, + "required": [ + "content_type", + "base64" + ], + "title": "ExtractionBase64Image", + "type": "object" + } + ] + }, + "maxItems": 4, + "type": "array" + }, + { + "type": "null" + } + ], + "description": "Up to 4 images as data URLs or content_type plus base64, no remote URLs", + "title": "Images" + }, + "model": { + "description": "An extraction model from the proxy model_list", + "title": "Model", + "type": "string" + }, + "options": { + "anyOf": [ + { + "additionalProperties": true, + "properties": { + "include_quantiles": { + "anyOf": [ + { + "type": "boolean" + }, + { + "type": "null" + } + ], + "description": "Add 99 percentiles to estimates", + "title": "Include Quantiles" + }, + "return_state_text": { + "anyOf": [ + { + "type": "boolean" + }, + { + "type": "null" + } + ], + "description": "Return the text that spans index into", + "title": "Return State Text" + } + }, + "title": "ExtractionOptions", + "type": "object" + }, + { + "type": "null" + } + ] + }, + "reference_date": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "ISO date that anchors dates written without a year", + "title": "Reference Date" + }, + "state": { + "default": "", + "description": "The text to read. Must be non-empty unless images are sent. Text answers are spans of it", + "title": "State", + "type": "string" + } + }, + "required": [ + "fields", + "model" + ], + "title": "ExtractionRequest", + "type": "object" + } + } + }, + "required": true + }, + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/ExtractionResponse" + } + } + }, + "description": "Successful Response" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Extract typed fields from a state", + "tags": [ + "decisions" + ] + } + }, "/v1/systemone": { "post": { "description": "Judge a `state` against 1 to 128 named `questions` and get one calibrated answer per question name.\n\nQuestion types are `noul` (probability the answer is yes), `choice` (one label out of `criteria`, with\n`confidence` and `probabilities`), `score` (an index into the `criteria` levels, with `confidence`,\n`legend` and `probabilities`) and `box` (the image region the `instructions` describe, with `confidence`).\nTypeSafe models also take images in `assets`, each one referenced by its key in `state`. Requests that break\nthese rules are rejected with a 400 before any provider is called. `model` is any decision model in the proxy model list. OpenAI decision models accept this format\ntoo, LiteLLM translates it and keeps the answers keyed by question name. Streaming is not supported.\n\n[Docs](https://docs.litellm.ai/docs/decisions)", diff --git a/litellm/proxy/_types.py b/litellm/proxy/_types.py index e4f77ac0005..54acf59ef80 100644 --- a/litellm/proxy/_types.py +++ b/litellm/proxy/_types.py @@ -86,6 +86,7 @@ from litellm.types.proxy.carried_budget_state import ( UserBudgetSnapshot as UserBudgetSnapshot, # noqa: PLC0414 # public re-export ) from litellm.types.proxy.control_plane_endpoints import WorkerRegistryEntry +from litellm.types.proxy.request_tag_mappings import RequestTagMapping from litellm.types.proxy.spend_capture_rate import SpendCaptureRateCheckSettings from litellm.types.router import AllowedModelRegion, RouterErrors, UpdateRouterConfig from litellm.types.router_weights import validate_router_settings_dict @@ -376,6 +377,8 @@ class LiteLLMRoutes(enum.Enum): "/v1/decisions", "/systemone", "/v1/systemone", + "/extraction", + "/v1/extraction", # OCR "/ocr", "/v1/ocr", @@ -2457,6 +2460,20 @@ class ConfigGeneralSettings(LiteLLMPydanticObjectBase): Documents all the fields supported by `general_settings` in config.yaml """ + request_tag_mappings: Sequence[RequestTagMapping] | None = Field( + None, + description="Map W3C baggage values to request tags. Exact value/tag rules take precedence over tag_prefix fallbacks.", + ) + + @field_validator("request_tag_mappings") + @classmethod + def validate_request_tag_mapping_duplicates( + cls, rules: Sequence[RequestTagMapping] | None + ) -> Sequence[RequestTagMapping] | None: + if rules is not None and len({(rule.key, rule.value) for rule in rules}) != len(rules): + raise ValueError("Only one mapping is allowed for each baggage key/value, including its any-value fallback") + return rules + completion_model: str | None = Field(None, description="proxy level default model for all chat completion calls") max_in_flight_requests_per_worker: int | None = Field( None, gt=0, description="maximum concurrent requests handled by each worker" @@ -2869,6 +2886,30 @@ class ConfigGeneralSettings(LiteLLMPydanticObjectBase): "deleted. Only historical tag usage analytics are affected; tag budgets read the lifetime counter." ), ) + maximum_spend_logs_size: str | None = Field( + None, + description=( + "Size rule for spend logs (e.g. '180GB'): when LiteLLM_SpendLogs plus LiteLLM_SpendLogToolIndex " + "(heap, indexes and TOAST, measured with pg_total_relation_size) hold more live data than this, the " + "cleanup job deletes the oldest spend logs first until they are under " + "maximum_spend_logs_cleanup_target_size. Independent of maximum_spend_logs_retention_period: a row is " + "deleted when either rule says so. Unset means no size rule." + ), + ) + maximum_spend_logs_cleanup_target_size: str | None = Field( + None, + description=( + "Level a size-triggered cleanup run deletes down to (e.g. '20GB'). Must be below maximum_spend_logs_size. " + "Unset means the run stops as soon as the tables are back under maximum_spend_logs_size." + ), + ) + maximum_spend_logs_size_check_interval: str | None = Field( + None, + description=( + "How often the size rule is checked (e.g. '10m'). Defaults to '1d'. Ignored when " + "maximum_spend_logs_cleanup_cron is set, which then drives both the age and the size cleanup." + ), + ) use_spend_logs_partitioning: bool | None = Field( None, description="If True and LiteLLM_SpendLogs has been converted to a range-partitioned table (db_scripts/partition_spend_logs.sql), retention cleanup drops expired partitions instead of deleting rows, and pre-creates upcoming partitions. Default is False.", @@ -3690,6 +3731,7 @@ class SpendLogsMetadata(TypedDict): routing_decision: StandardLoggingRoutingDecision | None kubernetes_pod_routing: ReadOnly[StandardLoggingKubernetesPodRouting | None] internal_call_origin: InternalCallOrigin | None + billed_retry_attempt: ReadOnly[NotRequired[bool | None]] litellm_roi_estimator: ReadOnly[NotRequired[bool | None]] guardrail_information: list[StandardLoggingGuardrailInformation] | None eval_information: Any | None diff --git a/litellm/proxy/agent_endpoints/auth/managed_authorization.py b/litellm/proxy/agent_endpoints/auth/managed_authorization.py index cbbd1548301..cdbbd6029fa 100644 --- a/litellm/proxy/agent_endpoints/auth/managed_authorization.py +++ b/litellm/proxy/agent_endpoints/auth/managed_authorization.py @@ -32,6 +32,7 @@ _MANAGED_MODEL_ROUTES: Final = frozenset( "rerank", "decisions", "systemone", + "extraction", "ocr", ), ) @@ -77,6 +78,7 @@ _MODEL_ROUTE_KINDS: Final[ "/rerank": "body", "/decisions": "body", "/systemone": "body", + "/extraction": "body", "/messages/count_tokens": "body", ":countTokens": "path", } diff --git a/litellm/proxy/auth/auth_checks.py b/litellm/proxy/auth/auth_checks.py index 0f94d2952ec..8887d86570a 100644 --- a/litellm/proxy/auth/auth_checks.py +++ b/litellm/proxy/auth/auth_checks.py @@ -877,18 +877,27 @@ def _enforce_user_param_check(general_settings: dict, request: Request, request_ raise Exception(f"'user' param not passed in. 'enforce_user_param'={general_settings['enforce_user_param']}") -def _reject_clientside_metadata_tags_check(general_settings: dict, request_body: dict, route: str) -> None: +def _reject_clientside_metadata_tags_check( + general_settings: dict, request_body: dict, route: str, request: Request | None = None +) -> None: if not general_settings.get("reject_clientside_metadata_tags", False): return - if ( - RouteChecks.is_llm_api_route(route=route) - and "metadata" in request_body - and isinstance(request_body["metadata"], dict) - and "tags" in request_body["metadata"] - ): + original_client_tags: Final = ( + getattr(request.state, "litellm_baggage_client_metadata_tags", None) if request is not None else None + ) + has_client_tags: Final = ( + original_client_tags + if isinstance(original_client_tags, bool) + else ( + "metadata" in request_body + and isinstance(request_body["metadata"], dict) + and "tags" in request_body["metadata"] + ) + ) + if RouteChecks.is_llm_api_route(route=route) and has_client_tags: raise ProxyException( - message=f"Client-side 'metadata.tags' not allowed in request. 'reject_clientside_metadata_tags'={general_settings['reject_clientside_metadata_tags']}. Tags can only be set via API key metadata.", + message=f"Client-side 'metadata.tags' not allowed in request. 'reject_clientside_metadata_tags'={general_settings['reject_clientside_metadata_tags']}. Tags can only be set via key or team metadata, or by configured request_tag_mappings.", type=ProxyErrorTypes.bad_request_error, param="metadata.tags", code=status.HTTP_400_BAD_REQUEST, @@ -1337,24 +1346,19 @@ async def common_checks( ) # Run before apply_key_tags_pre_auth injects key metadata.tags into request_body. - _reject_clientside_metadata_tags_check(general_settings, request_body, route) + _reject_clientside_metadata_tags_check(general_settings, request_body, route, request) # If this is a free model, skip all budget checks if not skip_all_budget_checks: # Key metadata.tags are injected into request_body here so the tag budget # check can read them; this mutation must run before the gathered checks. + from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup + if valid_token is not None: - from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup - - LiteLLMProxyRequestSetup.pre_seed_litellm_metadata_for_route( - request_data=request_body, - route=route, - ) - - LiteLLMProxyRequestSetup.apply_key_tags_pre_auth( - request_data=request_body, - user_api_key_dict=valid_token, - ) + for tag_target in LiteLLMProxyRequestSetup.pre_auth_tag_merge_targets(request, request_body): + LiteLLMProxyRequestSetup.pre_seed_litellm_metadata_for_route(request_data=tag_target, route=route) + LiteLLMProxyRequestSetup.apply_key_tags_pre_auth(request_data=tag_target, user_api_key_dict=valid_token) + LiteLLMProxyRequestSetup.apply_authenticated_baggage_tags(request, request_body) async def _user_max_budget_check() -> None: # 4.1 personal budget @@ -2456,7 +2460,7 @@ async def _fetch_uncached_tags( uncached_tags: Sequence[str], prisma_client: PrismaClient, user_api_key_cache: UserApiKeyCache, -) -> tuple[tuple[str, LiteLLM_TagTable], ...]: +) -> tuple[tuple[str, LiteLLM_TagTable], ...] | Exception: """Rows for the tags a cache probe missed; names absent from the registry never reach the DB.""" if not uncached_tags: return () @@ -2484,13 +2488,46 @@ async def _fetch_uncached_tags( model_type=LiteLLM_TagTable, ttl=get_management_object_ttl(user_api_key_cache), ) - except Exception as e: # noqa: BLE001 # fail-safe: a tag fetch error must yield "no budget objects", never break auth - verbose_proxy_logger.debug("Error batch fetching tags from database: %s", e) - return () + except Exception as e: # noqa: BLE001 # returned as a value: budget checks fail open, the baggage mapper fails closed + return e else: return fetched +async def _probe_and_fetch_tags( + tag_names: Sequence[str], + prisma_client: PrismaClient, + user_api_key_cache: UserApiKeyCache, +) -> tuple[Mapping[str, LiteLLM_TagTable], Exception | None]: + probed: Final = [ + ( + tag_name, + await user_api_key_cache.async_get_cache(key=tag_cache_key(tag_name), model_type=LiteLLM_TagTable), + ) + for tag_name in tag_names + ] + fetched: Final = await _fetch_uncached_tags( + uncached_tags=tuple(tag_name for tag_name, tag_obj in probed if tag_obj is None), + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + ) + rows: Final = () if isinstance(fetched, Exception) else fetched + found: Final = {tag_name: tag_obj for tag_name, tag_obj in (*probed, *rows) if tag_obj is not None} + return found, fetched if isinstance(fetched, Exception) else None + + +@log_db_metrics +@with_service_target(AUTH_OBJECTS_TARGET) +async def read_tag_objects_batch( + tag_names: Sequence[str], + prisma_client: PrismaClient, + user_api_key_cache: UserApiKeyCache, +) -> Mapping[str, LiteLLM_TagTable] | Exception: + """Like ``get_tag_objects_batch``, but a failed DB read comes back as the error instead of missing tags.""" + found, error = await _probe_and_fetch_tags(tag_names, prisma_client, user_api_key_cache) + return found if error is None else error + + @log_db_metrics @with_service_target(AUTH_OBJECTS_TARGET) async def get_tag_objects_batch( @@ -2521,19 +2558,10 @@ async def get_tag_objects_batch( if prisma_client is None or not tag_names: return {} - probed: Final = [ - ( - tag_name, - await user_api_key_cache.async_get_cache(key=tag_cache_key(tag_name), model_type=LiteLLM_TagTable), - ) - for tag_name in tag_names - ] - fetched: Final = await _fetch_uncached_tags( - uncached_tags=tuple(tag_name for tag_name, tag_obj in probed if tag_obj is None), - prisma_client=prisma_client, - user_api_key_cache=user_api_key_cache, - ) - return {tag_name: tag_obj for tag_name, tag_obj in (*probed, *fetched) if tag_obj is not None} + found, error = await _probe_and_fetch_tags(tag_names, prisma_client, user_api_key_cache) + if error is not None: + verbose_proxy_logger.debug("Error batch fetching tags from database: %s", error) + return dict(found) @log_db_metrics @@ -2635,7 +2663,7 @@ async def _load_team_membership_on_cache_miss( parent_otel_span: Span | None, proxy_logging_obj: ProxyLogging | None, ) -> LiteLLM_TeamMembership | None: - redis_cached: Final[object] = await user_api_key_cache.async_get_cache(key=cache_key) + redis_cached: Final = await _raw_cache(user_api_key_cache).async_get_cache(key=cache_key) redis_membership: Final = _membership_from_cached_payload(redis_cached) if not isinstance(redis_membership, _TeamMembershipCacheMiss): return redis_membership diff --git a/litellm/proxy/auth/auth_utils.py b/litellm/proxy/auth/auth_utils.py index 73d20ae632c..7a186d84aa5 100644 --- a/litellm/proxy/auth/auth_utils.py +++ b/litellm/proxy/auth/auth_utils.py @@ -419,6 +419,7 @@ _BANNED_REQUEST_BODY_PARAMS: Final[tuple[str, ...]] = ( # tokens) to the attacker's host, or coerces the proxy into # authenticating against the attacker's host with admin secrets. "aws_bedrock_runtime_endpoint", + "aws_bedrock_control_plane_endpoint", # Bedrock project/workspace association. Deployments pin this to # enforce a data-retention policy, so a caller-supplied value would # re-route the request's retention and accounting to any project @@ -445,6 +446,7 @@ _BANNED_REQUEST_BODY_PARAMS: Final[tuple[str, ...]] = ( # the request away from the admin's pinned configuration. "nvcf_function_id", "use_ssl", + "riva_offline", # Per-deployment opt-in that hands the whole call to the Rust core. It is a # deployment decision, not a request one: the Rust path uses its own client # rather than the one the deployment configured, and reports no post_call, @@ -461,6 +463,7 @@ _BANNED_REQUEST_BODY_PARAMS: Final[tuple[str, ...]] = ( # stored credential's values and the caller's connection by the proxy's own # secret_fields, so a body-supplied value could only spoof either. "github_copilot_auth_type", + "github_copilot_host", "user_provider_credentials", "github_copilot_user_session", # Observability credentials, hosts, and project identifiers: derived diff --git a/litellm/proxy/auth/route_checks.py b/litellm/proxy/auth/route_checks.py index f5e8304c83c..720bfabb95a 100644 --- a/litellm/proxy/auth/route_checks.py +++ b/litellm/proxy/auth/route_checks.py @@ -91,6 +91,21 @@ _SELF_SCOPED_CREDENTIAL_ROUTES: Final = ( ) +_UNBILLED_ROUTES: Final[frozenset[str]] = frozenset( + { + "/models", + "/v1/models", + "/utils/token_counter", + "/utils/transform_request", + "/responses/input_tokens", + "/v1/responses/input_tokens", + "/openai/v1/responses/input_tokens", + } +) +_TOKEN_COUNTING_SEGMENTS: Final[frozenset[str]] = frozenset({"count_tokens", "count-tokens"}) +_TOKEN_COUNTING_ACTION: Final = "countTokens" + + class RouteChecks: @staticmethod def should_call_route( @@ -412,6 +427,11 @@ class RouteChecks: detail=f"user not allowed to access this route. Route={route} is an admin only route", ) + @staticmethod + def is_unbilled_route(route: str) -> bool: + resource, _, action = route.rsplit("/", 1)[-1].partition(":") + return route in _UNBILLED_ROUTES or resource in _TOKEN_COUNTING_SEGMENTS or action == _TOKEN_COUNTING_ACTION + @staticmethod def is_llm_api_route(route: str) -> bool: """ diff --git a/litellm/proxy/auth/user_api_key_auth.py b/litellm/proxy/auth/user_api_key_auth.py index a1abed202a2..27fa4731baf 100644 --- a/litellm/proxy/auth/user_api_key_auth.py +++ b/litellm/proxy/auth/user_api_key_auth.py @@ -18,6 +18,7 @@ from typing import Final, NamedTuple, Protocol, Union, cast import fastapi from fastapi import HTTPException, Request, WebSocket, status from fastapi.security.api_key import APIKeyHeader +from pydantic import TypeAdapter from starlette.exceptions import WebSocketException import litellm @@ -268,6 +269,7 @@ _CLAUDE_MODEL_ROUTES: Final = frozenset( f"/{prefix}{endpoint}" for prefix in ("", "v1/") for endpoint in ("messages", "chat/completions", "responses") ) _CLAUDE_MODEL_NORMALIZED: Final = "litellm.claude_model_normalized" +_GENERAL_SETTINGS_ADAPTER: Final = TypeAdapter(dict[str, object]) async def _normalize_claude_model( @@ -1185,6 +1187,18 @@ async def user_api_key_auth_live_websocket(websocket: WebSocket) -> UserAPIKeyAu return await user_api_key_auth_websocket_for_model(websocket, model=None) +def _has_required_baggage_tag_mapping() -> bool: + from litellm.proxy import proxy_server + from litellm.proxy.common_utils.request_tag_mappings import REQUEST_TAG_MAPPINGS_ADAPTER + + raw_mappings: Final = _GENERAL_SETTINGS_ADAPTER.validate_python(proxy_server.general_settings).get( + "request_tag_mappings" + ) + return bool(raw_mappings) and any( + rule.required for rule in REQUEST_TAG_MAPPINGS_ADAPTER.validate_python(raw_mappings) + ) + + async def user_api_key_auth_websocket_for_model( websocket: WebSocket, model: str | None, *, close_on_auth_error: bool = True ) -> UserAPIKeyAuth: @@ -1240,7 +1254,11 @@ async def user_api_key_auth_websocket_for_model( # Call user_api_key_auth with the extracted API key # Note: You'll need to modify this to work with WebSocket context if needed try: - return await user_api_key_auth(request=request, api_key=f"Bearer {api_key}") + authorized: Final = await user_api_key_auth(request=request, api_key=f"Bearer {api_key}") + if _has_required_baggage_tag_mapping(): + raise HTTPException( + 403, "Required baggage tag mappings need HTTP inference, WebSocket inference is disabled" + ) except Exception as e: if not close_on_auth_error: raise @@ -1249,6 +1267,8 @@ async def user_api_key_auth_websocket_for_model( log_model_access_denial(e) await websocket.close(code=status.WS_1008_POLICY_VIOLATION) raise HTTPException(status_code=403, detail=str(e)) + else: + return authorized async def user_api_key_auth_accepted_websocket_for_model(websocket: WebSocket, model: str) -> UserAPIKeyAuth: @@ -3759,20 +3779,17 @@ async def run_centralized_common_checks( # later seed in common_checks pushes key tags and the # _tag_max_budget_check read into `litellm_metadata`, hiding header # tags from per-tag budget enforcement on LITELLM_METADATA_ROUTES. - LiteLLMProxyRequestSetup.pre_seed_litellm_metadata_for_route( - request_data=request_data, - route=route, - ) - # Merge x-litellm-tags into request_data BEFORE common_checks runs. # _tag_max_budget_check inside common_checks only inspects request_data; # without this pre-merge, header-supplied tags bypass tag-budget # enforcement. - LiteLLMProxyRequestSetup.apply_client_tag_policy_pre_auth( - request=request, - request_data=request_data, - user_api_key_dict=user_api_key_auth_obj, - ) + for tag_target in LiteLLMProxyRequestSetup.pre_auth_tag_merge_targets(request, request_data): + LiteLLMProxyRequestSetup.pre_seed_litellm_metadata_for_route(request_data=tag_target, route=route) + LiteLLMProxyRequestSetup.apply_client_tag_policy_pre_auth( + request=request, + request_data=tag_target, + user_api_key_dict=user_api_key_auth_obj, + ) bind_admission_counter_keys(user_api_key_auth_obj, end_user_id=end_user_id) try: @@ -4001,7 +4018,7 @@ def _resolve_request_principal(request: Request, valid_token: UserAPIKeyAuth) -> async def _authorize_authenticated_request( user_api_key_auth_obj: UserAPIKeyAuth, request: Request, - request_data: dict, + request_data: dict[str, object], route: str, api_key: str, *, @@ -4061,6 +4078,19 @@ async def _authorize_authenticated_request( billable=request_data.get("method") in (None, "message/send", "message/stream", "SendMessage", "SendStreamingMessage"), ) + if "request_tag_mappings" in general_settings and request.method == "POST": + from litellm.proxy.common_utils.request_tag_mappings import is_baggage_mapped_route + from litellm.proxy.proxy_server import proxy_logging_obj, user_api_key_cache + + if is_baggage_mapped_route(route): + LiteLLMProxyRequestSetup.pre_seed_litellm_metadata_for_route(request_data=authorized_data, route=route) + await LiteLLMProxyRequestSetup.apply_baggage_tag_mappings_pre_auth( + request=request, + request_data=authorized_data, + general_settings=_GENERAL_SETTINGS_ADAPTER.validate_python(general_settings), + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + ) await run_centralized_common_checks( user_api_key_auth_obj=user_api_key_auth_obj, request=request, diff --git a/litellm/proxy/common_request_processing.py b/litellm/proxy/common_request_processing.py index 24a7b46da4b..59db23820fc 100644 --- a/litellm/proxy/common_request_processing.py +++ b/litellm/proxy/common_request_processing.py @@ -128,16 +128,19 @@ from litellm.proxy.utils import ( # noqa: F401 # legacy module exports _check_and_merge_model_level_guardrails, # pyright: ignore[reportPrivateUsage,reportUnusedImport] # backwards-compatible package export check_and_merge_model_level_guardrails, ) +from litellm.responses.streaming_iterator import partial_responses_incomplete_event_on_disconnect from litellm.router import Router from litellm.router_utils.add_retry_fallback_headers import get_hidden_params_dict from litellm.router_utils.auto_router_model_naming import AUTO_ROUTER_MODEL_PREFIX from litellm.router_utils.common_utils import resolve_model_group_alias, resolve_served_model +from litellm.types.extraction import ExtractionResponse from litellm.types.guardrails import GuardrailEventHooks from litellm.types.router import RouterRateLimitError from litellm.types.router_weights import validate_router_weights _LateResponseT = TypeVar("_LateResponseT", bound=Response) _LlmCallT = TypeVar("_LlmCallT") +_ResponseT: Final = TypeVar("_ResponseT") _ChunkT: Final = TypeVar("_ChunkT") KNOWN_PROXY_ROUTES: Final = frozenset( @@ -189,6 +192,7 @@ ProxyRouteType: TypeAlias = Literal[ "asearch", "adecisions", "asystemone", + "aextraction", "avideo_generation", "avideo_list", "avideo_status", @@ -455,6 +459,13 @@ async def _bill_partial_streamed_spend_on_disconnect(request_data: dict, respons # A natural end-of-stream success event already fired and released the # slot; do not bill again, and let the caller skip the slot release. return True + partial_responses_event: Final = partial_responses_incomplete_event_on_disconnect(response) + if partial_responses_event is not None: + verbose_proxy_logger.debug( + "Billing partial streamed Responses API spend after client disconnect, litellm_call_id=%s", + sanitize_for_log(logging_obj.litellm_call_id), + ) + return await _dispatch_disconnect_billing_event(logging_obj, partial_responses_event) chunks: Final[object] = getattr(response, "chunks", None) if not isinstance(chunks, list) or not chunks: return False @@ -484,6 +495,10 @@ async def _bill_partial_streamed_spend_on_disconnect(request_data: dict, respons partial_usage: Final = getattr(partial_response, "usage", None) if isinstance(partial_usage, Usage): backfill_missing_cache_usage_fields(partial_usage) + return await _dispatch_disconnect_billing_event(logging_obj, partial_response) + + +async def _dispatch_disconnect_billing_event(logging_obj: LiteLLMLoggingObj, partial_response: object) -> bool: try: await logging_obj.dispatch_success_handlers( partial_response, @@ -1469,11 +1484,11 @@ _is_azure_model_router_request: Final = is_azure_model_router_request def _override_openai_response_model( *, - response_obj: object, + response_obj: _ResponseT, requested_model: str, log_context: str, return_raw_model_name: bool = False, -) -> None: +) -> _ResponseT: """ Force the OpenAI-compatible `model` field in the response to match what the client requested. @@ -1497,7 +1512,7 @@ def _override_openai_response_model( model group name instead of the comma-separated list the client sent. """ if return_raw_model_name or not requested_model: - return + return response_obj hidden_params: Final = get_hidden_params_dict(response_obj) if isinstance(hidden_params, dict): @@ -1510,7 +1525,7 @@ def _override_openai_response_model( log_context, attempted_fallbacks, ) - return + return response_obj # For fastest_response batch completions, use the winning model's group # name rather than the comma-separated list the client sent. @@ -1529,7 +1544,7 @@ def _override_openai_response_model( "%s: fastest_response detected but no model group header found, preserving actual model from response.", log_context, ) - return + return response_obj # Check if this is an Azure Model Router request - if so, preserve the actual model used if is_azure_model_router_request(requested_model, hidden_params): @@ -1537,11 +1552,12 @@ def _override_openai_response_model( "%s: Azure Model Router detected - preserving actual model used from response instead of overriding to router model.", log_context, ) - return + return response_obj + unchanged_response: Final = response_obj if isinstance(response_obj, dict): if "model" not in response_obj: - return + return unchanged_response downstream_model = response_obj.get("model") if downstream_model != requested_model: verbose_proxy_logger.debug( @@ -1551,10 +1567,10 @@ def _override_openai_response_model( downstream_model, ) response_obj["model"] = requested_model - return + return unchanged_response if not hasattr(response_obj, "model"): - return + return response_obj downstream_model = getattr(response_obj, "model", None) if downstream_model != requested_model: @@ -1565,6 +1581,9 @@ def _override_openai_response_model( downstream_model, ) + if isinstance(response_obj, ExtractionResponse): + return response_obj.model_copy(update={"model": requested_model}) + try: setattr(response_obj, "model", requested_model) except Exception as e: @@ -1576,6 +1595,7 @@ def _override_openai_response_model( str(e), exc_info=True, ) + return response_obj _METADATA_BUCKET_KEYS: Final = ("metadata", "litellm_metadata") @@ -2188,6 +2208,7 @@ class ProxyBaseLLMRequestProcessing: "asearch", "adecisions", "asystemone", + "aextraction", "avideo_generation", "avideo_list", "avideo_status", @@ -3214,7 +3235,7 @@ class ProxyBaseLLMRequestProcessing: # Always return the client-requested model name (not provider-prefixed internal identifiers) # for OpenAI-compatible responses. if requested_model_from_client: - _override_openai_response_model( + response = _override_openai_response_model( # rebind-ok: a frozen response comes back as a copy response_obj=response, requested_model=requested_model_from_client, log_context=f"litellm_call_id={logging_obj.litellm_call_id}", diff --git a/litellm/proxy/common_utils/callback_utils.py b/litellm/proxy/common_utils/callback_utils.py index 4fa7709e5c7..46434a997b7 100644 --- a/litellm/proxy/common_utils/callback_utils.py +++ b/litellm/proxy/common_utils/callback_utils.py @@ -12,6 +12,7 @@ import litellm from litellm import get_secret from litellm._logging import verbose_proxy_logger from litellm.constants import ( + BAGGAGE_MAPPED_TAGS_METADATA_KEY, CLIENT_OUTPUT_CEILING_METADATA_KEY, CONSUMED_REQUEST_TAGS_METADATA_KEY, MAX_GUARDRAIL_SCAN_METADATA_HEADER_LENGTH, @@ -543,6 +544,7 @@ LITELLM_PROXY_INTERNAL_METADATA_KEYS: Final = frozenset( PRE_CALL_EXECUTED_GUARDRAILS_KEY, SESSION_DEPLOYMENT_AFFINITY_TTL_METADATA_KEY, CONSUMED_REQUEST_TAGS_METADATA_KEY, + BAGGAGE_MAPPED_TAGS_METADATA_KEY, CLIENT_OUTPUT_CEILING_METADATA_KEY, ROUTING_REQUEST_TAGS_METADATA_KEY, "disable_global_guardrails", diff --git a/litellm/proxy/common_utils/http_parsing_utils.py b/litellm/proxy/common_utils/http_parsing_utils.py index ea33bc763d4..245a56678eb 100644 --- a/litellm/proxy/common_utils/http_parsing_utils.py +++ b/litellm/proxy/common_utils/http_parsing_utils.py @@ -191,6 +191,23 @@ def is_otlp_trace_request(request: HTTPConnection) -> bool: return request.scope.get("method") == "POST" and get_route_path(request.scope) in {"/v1/traces", "/v1/logs"} +def _parse_form_metadata(raw_metadata: str) -> object: + """The JSON body path rejects a lone surrogate escape (``"\\ud800"``) with a + 400 because no provider or database can encode it. ``json.loads`` accepts + the escape, so the multipart ``metadata`` field gets the same check.""" + parsed: Final[object] = json.loads(raw_metadata) + try: + json.dumps(parsed, ensure_ascii=False).encode("utf-8") + except UnicodeEncodeError as e: + raise ProxyException( + message=f"Invalid form payload: metadata {e}", + type="invalid_request_error", + param="metadata", + code=status.HTTP_400_BAD_REQUEST, + ) from e + return parsed + + async def read_request_body(request: Request | None) -> dict: """ Safely read the request body and parse it as JSON. @@ -238,9 +255,13 @@ async def read_request_body(request: Request | None) -> dict: param="request_body", code=status.HTTP_400_BAD_REQUEST, ) - parsed_body = dict(form_data) - if "metadata" in parsed_body and isinstance(parsed_body["metadata"], str): - parsed_body["metadata"] = json.loads(parsed_body["metadata"]) + form_body: Final = dict(form_data) + raw_metadata: Final = form_body.get("metadata") + parsed_body = ( + {**form_body, "metadata": _parse_form_metadata(raw_metadata)} + if isinstance(raw_metadata, str) + else form_body + ) else: # Read the request body body: Final = await request.body() @@ -372,6 +393,16 @@ def safe_set_request_parsed_body( _safe_set_request_parsed_body: Final = safe_set_request_parsed_body +def detach_request_parsed_body( + request: Request, request_data: Mapping[str, object] +) -> dict[str, object]: # mutable-ok: the client's body copy, which the base tag merges write into + client_body: Final = dict(request_data) + cached: Final[object] = request.scope.get("parsed_body") + if isinstance(cached, tuple) and cached[1] is request_data: + request.scope["parsed_body"] = (cached[0], client_body) # rebind-ok: cache holds the client copy + return client_body + + def rewrite_request_model( request_data: dict[str, object], # mutable-ok: the request body is rewritten in place for every downstream reader request: Request | None, diff --git a/litellm/proxy/common_utils/request_tag_mappings.py b/litellm/proxy/common_utils/request_tag_mappings.py new file mode 100644 index 00000000000..dca269dca16 --- /dev/null +++ b/litellm/proxy/common_utils/request_tag_mappings.py @@ -0,0 +1,67 @@ +from collections.abc import Mapping, Sequence +from typing import Final +from urllib.parse import unquote_plus + +from fastapi import status +from opentelemetry import baggage +from opentelemetry.baggage.propagation import W3CBaggagePropagator +from opentelemetry.context import Context +from pydantic import TypeAdapter + +from litellm.proxy._types import LiteLLMRoutes, ProxyErrorTypes, ProxyException +from litellm.proxy.auth.route_checks import RouteChecks +from litellm.types.proxy.request_tag_mappings import RequestTagMapping + +REQUEST_TAG_MAPPINGS_ADAPTER: Final = TypeAdapter(tuple[RequestTagMapping, ...]) + + +def is_baggage_mapped_route(route: str) -> bool: + from litellm.proxy.pass_through_endpoints.pass_through_endpoints import InitPassThroughEndpointHelpers + + return ( + (RouteChecks.is_llm_api_route(route) or InitPassThroughEndpointHelpers.is_registered_pass_through_route(route)) + and not RouteChecks.is_unbilled_route(route) + and not RouteChecks.check_route_access(route=route, allowed_routes=LiteLLMRoutes.mcp_inference_routes.value) + ) + + +def mapping_rejection(message: str) -> ProxyException: + return ProxyException( + message=message, type=ProxyErrorTypes.bad_request_error, param=None, code=status.HTTP_400_BAD_REQUEST + ) + + +def resolve_baggage_tag_mappings(header: str, rules: Sequence[RequestTagMapping]) -> tuple[tuple[str, bool], ...]: + """Exact mappings win over the any-value fallback for the same baggage key.""" + members: Final = tuple(_member_without_properties(member) for member in header.split(",")) + context: Final = W3CBaggagePropagator().extract({"baggage": ",".join(members)}, context=Context()) + values: Final = baggage.get_all(context) + member_keys: Final = tuple(unquote_plus(member.partition("=")[0]).strip() for member in members) + resolved: Final = ( + _resolve_key(key, values, member_keys, rules) for key in dict.fromkeys(rule.key for rule in rules) + ) + return tuple(mapping for mapping in resolved if mapping is not None) + + +def _member_without_properties(member: str) -> str: + key, separator, value = member.partition(";")[0].partition("=") + return f"{key.strip()}{separator}{value.strip()}" + + +def _resolve_key( + key: str, values: Mapping[str, object], member_keys: Sequence[str], rules: Sequence[RequestTagMapping] +) -> tuple[str, bool] | None: + key_rules: Final = tuple(rule for rule in rules if rule.key == key) + key_spellings: Final = frozenset((key, unquote_plus(key))) + sent_keys: Final = tuple(member_key for member_key in member_keys if member_key in key_spellings) + value: Final = values.get(sent_keys[0]) if len(sent_keys) == 1 else None + selected: Final = next( + (rule for rule in key_rules if rule.value == value and rule.value is not None), None + ) or next((rule for rule in key_rules if rule.value is None), None) + usable: Final = isinstance(value, str) and value.isprintable() and bool(value) + if not usable or selected is None: + if any(rule.required for rule in key_rules): + raise mapping_rejection(f"Missing, invalid or unmapped baggage value for {key}") + return None + tag: Final = selected.tag if selected.tag is not None else f"{selected.tag_prefix}{value}" + return tag, selected.require_budgeted_tag diff --git a/litellm/proxy/credential_endpoints/endpoints.py b/litellm/proxy/credential_endpoints/endpoints.py index 953c944bfb2..d20b5602186 100644 --- a/litellm/proxy/credential_endpoints/endpoints.py +++ b/litellm/proxy/credential_endpoints/endpoints.py @@ -19,6 +19,7 @@ from litellm._internal_context import with_service_target from litellm._logging import verbose_proxy_logger from litellm.constants import ( GITHUB_COPILOT_AUTH_TYPE_KEY, + GITHUB_COPILOT_HOST_KEY, GITHUB_COPILOT_PER_USER_AUTH_TYPE, ) from litellm.litellm_core_utils.credential_accessor import CredentialAccessor @@ -84,6 +85,22 @@ _DISPLAY_NAME_MAX_LENGTH: Final = 255 _DISPLAY_NAME_FORBIDDEN_CATEGORIES: Final = frozenset({"Cc", "Cf", "Cs", "Zl", "Zp"}) +def _normalized_github_copilot_values( + credential_values: Mapping[str, object], + credential_info: Mapping[str, object], +) -> Mapping[str, object]: + provider: Final = stored_credential_provider(credential_info.get("custom_llm_provider")) + if provider != _GITHUB_COPILOT_PROVIDER or GITHUB_COPILOT_HOST_KEY not in credential_values: + return credential_values + + from litellm.llms.github_copilot.github_host import normalized_github_host + + host: Final = normalized_github_host(credential_values[GITHUB_COPILOT_HOST_KEY]) + if host is None: + raise HTTPException(status_code=400, detail=f"Invalid {GITHUB_COPILOT_HOST_KEY}") + return {**credential_values, GITHUB_COPILOT_HOST_KEY: host} + + def _reject_non_admin_wif_fields( wif_fields: tuple[str, ...], user_api_key_dict: UserAPIKeyAuth, @@ -318,7 +335,14 @@ async def create_credential( status_code=400, detail="Credential values are required. Unable to infer credential values from model ID.", ) - _reject_non_admin_wif_fields(server_owned_wif_fields_written(credential_values), user_api_key_dict) + credential_info: Final = _CREDENTIAL_DICT_ADAPTER.validate_python( + credential.credential_info # pyright: ignore[reportUnknownMemberType] # untyped credential field + ) + normalized_values: Final = _normalized_github_copilot_values( + _CREDENTIAL_DICT_ADAPTER.validate_python(credential_values), + credential_info, + ) + _reject_non_admin_wif_fields(server_owned_wif_fields_written(normalized_values), user_api_key_dict) _reject_non_admin_wif_fields( await named_credential_wif_fields(credential.credential_name, prisma_client), user_api_key_dict ) @@ -326,8 +350,8 @@ async def create_credential( processed_credential: Final = CredentialItem( credential_name=credential.credential_name, display_name=_normalized_display_name(credential.display_name), - credential_values=_without_null_values(_CREDENTIAL_DICT_ADAPTER.validate_python(credential_values)), - credential_info=credential.credential_info, + credential_values=_without_null_values(normalized_values), + credential_info=credential_info, ) encrypted_credential: Final = CredentialHelperUtils.encrypt_credential_values(processed_credential) credentials_dict: Final = encrypted_credential.model_dump(exclude_none=True) @@ -614,22 +638,24 @@ async def start_user_connection( user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), # noqa: B008 # FastAPI resolves the dependency from the default ) -> UserConnectionStartResponse: """Begin a GitHub device flow for the calling user's connection to a per-user credential.""" - from litellm.llms.github_copilot.per_user_auth import astart_device_flow + from litellm.llms.github_copilot.per_user_auth import astart_device_flow, github_copilot_host_endpoints from litellm.proxy.proxy_server import prisma_client try: user_id: Final = _authenticated_user_id(user_api_key_dict) _per_user_credential_or_404(credential_name) + endpoints: Final = github_copilot_host_endpoints(credential_name) if prisma_client is None: raise HTTPException( status_code=500, detail={"error": CommonProxyErrors.db_not_connected_error.value}, ) - flow: Final = await astart_device_flow() + flow: Final = await astart_device_flow(endpoints) handle: Final = encrypt_value_helper( UserConnectionFlowHandle( user_id=user_id, credential_name=credential_name, + github_host=endpoints.host, device_code=flow.device_code, interval=flow.interval, expires_at=time.time() + flow.expires_in, @@ -665,12 +691,14 @@ async def poll_user_connection( acheck_copilot_seat, afetch_github_login, apoll_device_flow, + github_copilot_host_endpoints, ) from litellm.proxy.proxy_server import prisma_client, user_api_key_cache try: user_id: Final = _authenticated_user_id(user_api_key_dict) _per_user_credential_or_404(credential_name) + endpoints: Final = github_copilot_host_endpoints(credential_name) if prisma_client is None: raise HTTPException( status_code=500, @@ -681,11 +709,12 @@ async def poll_user_connection( handle is None or handle.user_id != user_id or handle.credential_name != credential_name + or handle.github_host != endpoints.host or handle.expires_at <= time.time() ): raise HTTPException(status_code=400, detail="invalid or expired flow_handle") - poll: Final = await apoll_device_flow(handle.device_code) + poll: Final = await apoll_device_flow(handle.device_code, endpoints) if poll.status in ("expired", "denied", "pending", "slow_down"): return UserConnectionPollResponse(status=poll.status, interval=poll.interval) @@ -693,12 +722,19 @@ async def poll_user_connection( if not github_token: raise HTTPException(status_code=502, detail="GitHub device flow completed without a token") try: - await acheck_copilot_seat(user_id=user_id, github_token=github_token, credential_name=credential_name) + await acheck_copilot_seat( + user_id=user_id, + github_token=github_token, + credential_name=credential_name, + endpoints=endpoints, + ) except litellm.CallerCredentialAuthenticationError: return UserConnectionPollResponse(status="no_copilot_seat") - github_login: Final = await afetch_github_login(github_token) + github_login: Final = await afetch_github_login(github_token, endpoints) connection_payload: Final = GithubCopilotUserConnectionPayload( - access_token=github_token, github_login=github_login + access_token=github_token, + github_login=github_login, + github_host=handle.github_host, ) await upsert_user_provider_credential( prisma_client, @@ -760,7 +796,7 @@ async def delete_user_connection( ) prior: Final = await delete_user_provider_credential(prisma_client, user_id, credential_name) if prior is not None: - evict_copilot_user_session(user_id, prior.access_token) + evict_copilot_user_session(user_id, credential_name, prior.github_host) return UserConnectionDeleteResponse(status="disconnected") except Exception as e: # noqa: BLE001 # endpoint boundary: every failure becomes the proxy error contract raise handle_exception_on_proxy(e) @@ -785,16 +821,15 @@ async def _purge_user_connections_for_credential(credential_name: str) -> None: "_purge_user_connections_for_credential: failed to drop user connections for %s", credential_name ) return - access_tokens: Final[dict[str, str]] = {} # mutable-ok: accumulates one entry per deleted row - for row in prior_rows: - decoded = decode_user_provider_credential(row.credential_b64) - if decoded is not None: - access_tokens[row.user_id] = decoded.access_token + github_hosts: Final = { + row.user_id: decoded.github_host + for row in prior_rows + if (decoded := decode_user_provider_credential(row.credential_b64)) is not None + } for user_id in user_ids: await invalidate_user_provider_credential_cache(user_api_key_cache, user_id, credential_name) - token = access_tokens.get(user_id) - if token: - evict_copilot_user_session(user_id, token) + if user_id in github_hosts: + evict_copilot_user_session(user_id, credential_name, github_hosts[user_id]) @router.delete( @@ -926,7 +961,25 @@ async def update_credential( credential_values=incoming_values, credential_values_to_delete=credential.credential_values_to_delete, ) - merged_credential: Final = update_db_credential(db_credential, patch) + decrypted_stored_credential: Final = decrypted_credential(db_credential) + decrypted_values: Final = _CREDENTIAL_DICT_ADAPTER.validate_python( + decrypted_stored_credential.credential_values + ) + stored_info: Final = _CREDENTIAL_DICT_ADAPTER.validate_python( + db_credential.credential_info # pyright: ignore[reportUnknownMemberType] # untyped credential field + ) + patch_info: Final = _CREDENTIAL_DICT_ADAPTER.validate_python( + patch.credential_info # pyright: ignore[reportUnknownMemberType] # untyped credential field + ) + effective_info: Final = {**stored_info, **patch_info} + normalized_patch: Final = ( + patch.model_copy( + update={"credential_values": _normalized_github_copilot_values(incoming_values, effective_info)} + ) + if incoming_values.get(GITHUB_COPILOT_HOST_KEY) is not None + else patch + ) + merged_credential: Final = update_db_credential(db_credential, normalized_patch) credential_object_jsonified: Final = cast( # cast-ok: deep-copies a model_dump, so keys are str "dict[str, object]", jsonify_object(merged_credential.model_dump(exclude_none=True)) ) @@ -940,13 +993,20 @@ async def update_credential( ) # Sync in-memory credential_list (skip if not in memory - e.g., proxy restarted) - _sync_in_memory_credential(patch, credential_name) + _sync_in_memory_credential(normalized_patch, credential_name) - merged_values: Final = cast( # cast-ok: credential_values is a plain dict at runtime - Mapping[object, object], merged_credential.credential_values + from litellm.llms.github_copilot.github_host import normalized_github_host + + new_decrypted_values: Final = _CREDENTIAL_DICT_ADAPTER.validate_python( + decrypted_credential(merged_credential).credential_values ) - still_per_user: Final = merged_values.get(GITHUB_COPILOT_AUTH_TYPE_KEY) == GITHUB_COPILOT_PER_USER_AUTH_TYPE - if not still_per_user: + still_per_user: Final = ( + new_decrypted_values.get(GITHUB_COPILOT_AUTH_TYPE_KEY) == GITHUB_COPILOT_PER_USER_AUTH_TYPE + ) + old_host: Final = normalized_github_host(decrypted_values.get(GITHUB_COPILOT_HOST_KEY)) + new_host: Final = normalized_github_host(new_decrypted_values.get(GITHUB_COPILOT_HOST_KEY)) + host_changed: Final = old_host is None or old_host != new_host + if not still_per_user or host_changed: await _purge_user_connections_for_credential(credential_name) return {"success": True, "message": "Credential updated successfully"} diff --git a/litellm/proxy/credential_endpoints/user_provider_credentials.py b/litellm/proxy/credential_endpoints/user_provider_credentials.py index 4253483a228..22ee271410e 100644 --- a/litellm/proxy/credential_endpoints/user_provider_credentials.py +++ b/litellm/proxy/credential_endpoints/user_provider_credentials.py @@ -25,6 +25,7 @@ from litellm.caching.dual_cache import DualCache if TYPE_CHECKING: from litellm.caching.redis_cache import RedisCache from litellm.constants import ( + GITHUB_COPILOT_DEFAULT_HOST, GITHUB_COPILOT_USER_CREDENTIAL_CACHE_TTL_SECONDS, USER_PROVIDER_CREDENTIAL_CACHE_PREFIX, USER_PROVIDER_CREDENTIAL_NOT_CONNECTED, @@ -50,6 +51,7 @@ class GithubCopilotUserConnectionPayload(BaseModel): access_token: str = Field(repr=False) github_login: str + github_host: str = GITHUB_COPILOT_DEFAULT_HOST class _UserProviderCredentialsRepository(PrismaTableRepository["prisma_models.LiteLLM_UserProviderCredentials"]): @@ -186,7 +188,7 @@ async def _try_cache_get(token_cache: "RedisCache", key: str) -> object: try: return await _string_cache(token_cache).async_get_cache(key) except Exception: # noqa: BLE001 # a Redis outage must fall back to the database, never reject a connected user - verbose_proxy_logger.warning("aget_user_provider_tokens: Redis get failed; falling back to the database") + verbose_proxy_logger.warning("aget_user_provider_credentials: Redis get failed; falling back to the database") return None @@ -196,7 +198,7 @@ async def _try_cache_set(token_cache: "RedisCache", key: str, value: str, nx: bo key, value, nx=nx, ttl=GITHUB_COPILOT_USER_CREDENTIAL_CACHE_TTL_SECONDS ) except Exception: # noqa: BLE001 # caching is best-effort; a Redis outage is not worth failing the request - verbose_proxy_logger.warning("aget_user_provider_tokens: Redis set failed; skipping the cache write") + verbose_proxy_logger.warning("aget_user_provider_credentials: Redis set failed; skipping the cache write") @with_service_target("user_provider_connections") @@ -292,16 +294,16 @@ async def set_user_provider_credential_cache( @with_service_target("user_provider_connections") -async def aget_user_provider_tokens( +async def aget_user_provider_credentials( prisma_client: "PrismaClient", cache: DualCache, user_id: str, credential_names: Sequence[str], -) -> Mapping[str, str]: - """Map each per-user credential name to the caller's stored GitHub token. +) -> Mapping[str, Mapping[str, str]]: + """Map each per-user credential name to the caller's stored GitHub connection. Cached values are the stored ciphertext or the ``_NOT_CONNECTED`` marker; - plaintext tokens only ever live in the returned dict. Redis is the only + plaintext connection data only ever lives in the returned mapping. Redis is the only cache layer used: without it there is no shared invalidation, so a worker serving a stale local entry after a disconnect is worse than a DB read.""" token_cache: Final = cache.redis_cache @@ -320,9 +322,9 @@ async def aget_user_provider_tokens( misses.append(name) if not misses: return { - name: token + name: connection for name, ciphertext in cached.items() - if (token := _token_from_ciphertext(ciphertext)) is not None + if (connection := _connection_from_ciphertext(ciphertext)) is not None } try: @@ -333,7 +335,7 @@ async def aget_user_provider_tokens( where={"user_id": user_id}, ) except Exception: # noqa: BLE001 # a DB outage reads as not connected so the caller gets a 401, never a 500 - verbose_proxy_logger.exception("aget_user_provider_tokens: DB read failed for user_id=%s", user_id) + verbose_proxy_logger.exception("aget_user_provider_credentials: DB read failed") return {} found: Final = {row.credential_name: row.credential_b64 for row in rows} for name in misses: @@ -342,10 +344,14 @@ async def aget_user_provider_tokens( if name in found: cached[name] = found[name] return { - name: token for name, ciphertext in cached.items() if (token := _token_from_ciphertext(ciphertext)) is not None + name: connection + for name, ciphertext in cached.items() + if (connection := _connection_from_ciphertext(ciphertext)) is not None } -def _token_from_ciphertext(ciphertext: str) -> str | None: +def _connection_from_ciphertext(ciphertext: str) -> Mapping[str, str] | None: payload: Final = decode_user_provider_credential(ciphertext) - return payload.access_token if payload is not None else None + if payload is None: + return None + return {"access_token": payload.access_token, "github_host": payload.github_host} diff --git a/litellm/proxy/db/db_spend_update_writer.py b/litellm/proxy/db/db_spend_update_writer.py index 166a42adfc0..4e98823ba77 100644 --- a/litellm/proxy/db/db_spend_update_writer.py +++ b/litellm/proxy/db/db_spend_update_writer.py @@ -13,7 +13,7 @@ import os import random import time import traceback -from collections.abc import AsyncGenerator, Callable, Coroutine, Mapping, Sequence +from collections.abc import AsyncGenerator, Callable, Coroutine, Iterable, Mapping, Sequence from contextlib import asynccontextmanager from contextvars import ContextVar from datetime import datetime, timedelta, timezone @@ -21,7 +21,7 @@ from types import MappingProxyType from typing import TYPE_CHECKING, Any, Final, Literal, Protocol, TypeAlias, TypeVar, cast, overload from urllib.parse import quote, unquote -from pydantic import TypeAdapter +from pydantic import ConfigDict, TypeAdapter from typing_extensions import LiteralString, ReadOnly, TypedDict import litellm @@ -29,6 +29,7 @@ from litellm._internal_context import service_target, with_service_target from litellm._logging import verbose_proxy_logger from litellm.caching import RedisCache from litellm.constants import ( + BILLED_RETRY_ATTEMPT_METADATA_KEY, DB_DAILY_TAG_SPEND_UPDATE_JOB_NAME, DB_SPEND_UPDATE_JOB_NAME, INTERNAL_CALL_ORIGIN_METADATA_KEY, @@ -95,6 +96,7 @@ if TYPE_CHECKING: from litellm.proxy.db.autorouter_session_rollup import AutoRouterTurnTransaction from litellm.proxy.db.baseline_accounting import DailyBaselineAttribution from litellm.proxy.utils import PrismaClient, ProxyLogging + from litellm.router import Router else: PrismaClient = Any ProxyLogging = Any @@ -102,6 +104,52 @@ else: RESPONSES_SESSION_CALL_TYPES: Final = frozenset({CallTypes.responses.value, CallTypes.aresponses.value}) _SPEND_METADATA_ADAPTER: Final = TypeAdapter(Mapping[str, object]) +_JsonPayload: TypeAlias = Mapping[str, object] | Sequence[object] | str | int | float | bool | None +_JSON_VALUE_ADAPTER: Final[TypeAdapter[_JsonPayload]] = TypeAdapter( + _JsonPayload, config=ConfigDict(strict=True, hide_input_in_errors=True) +) + + +def _parsed_request_tags(request_tags: object) -> Iterable[object] | TypeError | None: + if isinstance(request_tags, list): + return request_tags + if not isinstance(request_tags, str): + return None + parsed: Final = _JSON_VALUE_ADAPTER.validate_python(safe_json_loads(request_tags, default=[])) + if not parsed: + verbose_proxy_logger.debug("Failed to parse request_tags JSON: %s", request_tags) + return None + if isinstance(parsed, (Sequence, Mapping)): + return parsed + return TypeError(f"'{type(parsed).__name__}' object is not iterable") + + +def _turn_chains_through_the_db(payload: Mapping[str, object], llm_router: "Router | None") -> bool: + """A Responses turn the chat-completions bridge replays from its spend log on the next `previous_response_id`. + + Native Responses providers hold the conversation themselves, so their rows can wait for the batch write. + A row with no router deployment behind it is treated as bridged, which keeps today's immediate flush. + """ + if payload.get("call_type") not in RESPONSES_SESSION_CALL_TYPES: + return False + model_id: Final = payload.get("model_id") + deployment: Final = ( + llm_router.get_deployment(model_id=model_id) if llm_router is not None and isinstance(model_id, str) else None + ) + if deployment is None: + return True + from litellm.responses.main import provider_stores_the_conversation + + litellm_params: Final = deployment.litellm_params + return not provider_stores_the_conversation( + litellm_params.model, + litellm_params.custom_llm_provider, + { + "use_chat_completions_api": litellm_params.use_chat_completions_api, + "model_info": deployment.model_info.model_dump(), + "api_base": litellm_params.api_base, + }, + ) def _org_member_transaction_key(org_id: str, user_id: str) -> str: @@ -265,6 +313,11 @@ def _spend_tables_left_to_send( return cast(DBSpendUpdateTransactions, remaining) if any(remaining.values()) else None +def _is_billed_retry_attempt(metadata: SpendLogsMetadata) -> bool: + """An earlier billed retry attempt's own spend row, not a request the caller sent.""" + return BILLED_RETRY_ATTEMPT_METADATA_KEY in metadata and metadata[BILLED_RETRY_ATTEMPT_METADATA_KEY] is True + + def _timed_request_duration_ms( payload: dict | SpendLogsPayload, request_status: Literal["success", "failure"], @@ -547,12 +600,13 @@ class DBSpendUpdateWriter: get_request_model_access_groups, ) + llm_router: Final = get_llm_router() payload: Final = get_logging_payload( kwargs=kwargs, response_obj=completion_response, start_time=start_time, end_time=end_time, - llm_router=get_llm_router(), + llm_router=llm_router, ) payload["spend"] = response_cost or 0.0 if isinstance(payload["startTime"], datetime): @@ -567,7 +621,10 @@ class DBSpendUpdateWriter: payload["team_id"] = team_id if not await self._record_spend_log( - payload=payload, prisma_client=prisma_client, disable_spend_logs=disable_spend_logs + payload=payload, + prisma_client=prisma_client, + disable_spend_logs=disable_spend_logs, + llm_router=llm_router, ): return False @@ -631,14 +688,18 @@ class DBSpendUpdateWriter: return True async def _record_spend_log( - self, payload: SpendLogsPayload, prisma_client: "PrismaClient | None", disable_spend_logs: bool + self, + payload: SpendLogsPayload, + prisma_client: "PrismaClient | None", + disable_spend_logs: bool, + llm_router: "Router | None" = None, ) -> bool: if prisma_client is not None and _is_batch_cost_row(payload): return await self._claim_batch_cost_spend_log( payload=payload, prisma_client=prisma_client, disable_spend_logs=disable_spend_logs ) if disable_spend_logs is False: - await self._insert_spend_log_to_db(payload=payload, prisma_client=prisma_client) + await self._insert_spend_log_to_db(payload=payload, prisma_client=prisma_client, llm_router=llm_router) return True async def _claim_batch_cost_spend_log( @@ -1441,16 +1502,11 @@ class DBSpendUpdateWriter: return # Parse tags from JSON string - tags: Sequence[object] = [] - if isinstance(request_tags, str): - tags = safe_json_loads(request_tags, default=[]) - if not tags: - verbose_proxy_logger.debug("Failed to parse request_tags JSON: %s", request_tags) - return - elif isinstance(request_tags, list): - tags = request_tags - else: + tags: Final[Iterable[object] | TypeError | None] = _parsed_request_tags(request_tags) + if tags is None: return + if isinstance(tags, TypeError): + raise tags # Update spend for each tag for tag_name in tags: @@ -1521,6 +1577,7 @@ class DBSpendUpdateWriter: payload: dict | SpendLogsPayload, prisma_client: PrismaClient | None = None, spend_logs_url: str | None = os.getenv("SPEND_LOGS_URL"), + llm_router: "Router | None" = None, ) -> PrismaClient | None: verbose_proxy_logger.debug( "Writing spend log to db - request_id: {}, spend: {}".format( @@ -1531,7 +1588,7 @@ class DBSpendUpdateWriter: from litellm.proxy.utils import enqueue_spend_logs, request_spend_log_flush await enqueue_spend_logs(prisma_client, (payload,)) - if payload.get("call_type") in RESPONSES_SESSION_CALL_TYPES: + if _turn_chains_through_the_db(_SPEND_METADATA_ADAPTER.validate_python(payload), llm_router): request_spend_log_flush(prisma_client) else: verbose_proxy_logger.debug("prisma_client is None. Skipping writing spend logs to db.") @@ -1600,6 +1657,8 @@ class DBSpendUpdateWriter: window_spend_update_queue=self.window_spend_update_queue, ) + await self._flush_tool_discovery_queue(prisma_client=prisma_client) + # Only commit from redis to db if this pod is the leader if await self.pod_lock_manager.acquire_lock( cronjob_id=DB_SPEND_UPDATE_JOB_NAME, @@ -2752,11 +2811,12 @@ class DBSpendUpdateWriter: if not date: return metadata: Final[SpendLogsMetadata] = json.loads(payload["metadata"]) + internal_origin: Final = bool(metadata.get(INTERNAL_CALL_ORIGIN_METADATA_KEY)) # pyright: ignore[reportUnknownMemberType] # TypedDict.get overloads carry Any defaults request_error_accumulator.record( payload=payload, request_status=prisma_client.get_request_status(payload), # pyright: ignore[reportUnknownMemberType] # legacy payload union; this caller supplies a typed spend payload date=date.split("T")[0], - is_internal_call=bool(metadata.get(INTERNAL_CALL_ORIGIN_METADATA_KEY)), # pyright: ignore[reportUnknownMemberType] # TypedDict.get overloads carry Any defaults + is_internal_call=internal_origin or _is_billed_retry_attempt(metadata), ) async def _common_add_spend_log_transaction_to_daily_transaction( @@ -2821,6 +2881,7 @@ class DBSpendUpdateWriter: endpoint = ROUTE_ENDPOINT_MAPPING.get(call_type, None) is_internal_call: Final = bool(_metadata.get(INTERNAL_CALL_ORIGIN_METADATA_KEY)) + caller_request: Final = not is_internal_call and not _is_billed_retry_attempt(_metadata) cache_read_input_tokens: Final = extract_cache_read_tokens(usage_obj) compression_saved_tokens: Final = extract_compression_saved_tokens(_metadata) savings_spend: Final = compute_savings_spend( @@ -2855,9 +2916,9 @@ class DBSpendUpdateWriter: # requests the caller made: counting them inflates request-volume # readers, and an auto-router savings figure computed on a shadow # duplicate credits savings for traffic no user sent. - api_requests=0 if is_internal_call else 1, - successful_requests=1 if not is_internal_call and request_status == "success" else 0, - failed_requests=1 if not is_internal_call and request_status != "success" else 0, + api_requests=1 if caller_request else 0, + successful_requests=1 if caller_request and request_status == "success" else 0, + failed_requests=1 if caller_request and request_status != "success" else 0, cache_read_input_tokens=cache_read_input_tokens, cache_creation_input_tokens=extract_cache_creation_tokens(usage_obj), compression_saved_tokens=compression_saved_tokens, diff --git a/litellm/proxy/db/db_transaction_queue/redis_update_buffer.py b/litellm/proxy/db/db_transaction_queue/redis_update_buffer.py index 898aee493df..54d20bd4507 100644 --- a/litellm/proxy/db/db_transaction_queue/redis_update_buffer.py +++ b/litellm/proxy/db/db_transaction_queue/redis_update_buffer.py @@ -168,9 +168,11 @@ class RedisUpdateBuffer: @with_service_target(SPEND_QUEUE_TARGET) async def _store_transactions_in_redis( self, - transactions: Mapping[str, BaseDailySpendTransaction] | None, + transactions: dict[str, BaseDailySpendTransaction] | None, # mutable-ok: add_update requires dict redis_key: str, service_type: ServiceTypes, + *, + source_queue: DailySpendUpdateQueue, ) -> None: """ Helper method to store transactions in Redis and emit an event @@ -179,6 +181,7 @@ class RedisUpdateBuffer: transactions: The transactions to store redis_key: The Redis key to store under service_type: The service type for event emission + source_queue: The in-memory queue to restore transactions to if Redis push fails """ if transactions is None or len(transactions) == 0: return @@ -191,6 +194,15 @@ class RedisUpdateBuffer: key=redis_key, values=list_of_transactions, ) + except Exception as e: + verbose_proxy_logger.error( + "Spend tracking - failed to push spend updates to Redis (redis_key=%s). " + "Restoring them to the in-memory queue for retry on next tick. Error: %s", + redis_key, + str(e), + ) + await source_queue.add_update(transactions) + else: verbose_proxy_logger.debug( "Spend tracking - pushed spend updates to Redis buffer. redis_key=%s, buffer_size=%s", redis_key, @@ -200,12 +212,6 @@ class RedisUpdateBuffer: queue_size=current_redis_buffer_size, service=service_type, ) - except Exception as e: - verbose_proxy_logger.error( - "Spend tracking - failed to push spend updates to Redis (redis_key=%s). Error: %s", - redis_key, - str(e), - ) @with_service_target(SPEND_QUEUE_TARGET) async def store_in_memory_spend_updates_in_redis( @@ -793,6 +799,7 @@ class RedisUpdateBuffer: transactions=daily_tag_spend_update_transactions, redis_key=REDIS_DAILY_TAG_SPEND_UPDATE_BUFFER_KEY, service_type=ServiceTypes.REDIS_DAILY_TAG_SPEND_UPDATE_QUEUE, + source_queue=daily_tag_spend_update_queue, ) @with_service_target(SPEND_QUEUE_TARGET) diff --git a/litellm/proxy/db/db_transaction_queue/spend_log_cleanup.py b/litellm/proxy/db/db_transaction_queue/spend_log_cleanup.py index b57952b4992..7f5efcdaec3 100644 --- a/litellm/proxy/db/db_transaction_queue/spend_log_cleanup.py +++ b/litellm/proxy/db/db_transaction_queue/spend_log_cleanup.py @@ -1,6 +1,8 @@ import asyncio +import math import re import time +from collections.abc import Awaitable, Callable from contextvars import ContextVar from dataclasses import dataclass from datetime import datetime, timedelta, timezone @@ -19,6 +21,7 @@ from litellm.constants import ( SPEND_LOG_CLEANUP_REMAINING_COUNT_CAP, SPEND_LOG_CLEANUP_RUN_BUDGET_SECONDS, SPEND_LOG_RUN_LOOPS, + SPEND_LOG_SIZE_CLEANUP_RECHECK_BATCHES, ) from litellm.litellm_core_utils.duration_parser import duration_in_seconds from litellm.proxy.db.db_span import db_span @@ -35,7 +38,7 @@ from litellm.proxy.db.db_transaction_queue.spend_logs_partition_manager import ( from litellm.proxy.utils import PrismaClient from litellm.types.llms.base import LiteLLMBaseModel -StopReason: TypeAlias = Literal["exhausted", "budget_exhausted", "batch_cap_reached", "aborted"] +StopReason: TypeAlias = Literal["exhausted", "target_reached", "budget_exhausted", "batch_cap_reached", "aborted"] _SIZE_RE: Final = re.compile(r"^\s*(\d+(?:\.\d+)?)\s*([KMGT]?)I?B?\s*$", re.IGNORECASE) _SIZE_UNITS: Final = {"": 1, "K": 1024, "M": 1024**2, "G": 1024**3, "T": 1024**4} @@ -61,6 +64,14 @@ def size_in_bytes(value: str | int) -> int: return size +@dataclass(frozen=True, slots=True) +class SizeRule: + """The size cleanup rule as configured: start cleaning above `limit_bytes`, stop under `target_bytes`.""" + + limit_bytes: int + target_bytes: int + + @dataclass(frozen=True, slots=True) class StorageProbe: """ @@ -110,10 +121,12 @@ def advance_size_state(state: SizeCleanupState | None, probe: StorageProbe) -> S """ Roll the reclaimable count forward to what the catalog shows now. - Without a prior state, or after the cumulative counters went backwards (a statistics reset), the count - starts from the dead rows Postgres still knows about, at the files' average bytes per row. A probe with no - row counters at all (`stats_are_stale`) cannot seed anything: the prior count is carried forward, and with - no prior count the files are taken as fully reclaimable so nothing is deleted on its say-so. + Without a prior state the count starts from the dead rows Postgres still knows about, at the files' average + bytes per row. After the cumulative counters went backwards (a statistics reset, e.g. a crash) the prior + count is carried forward less any shrink of the files, or the dead-row seed if that is larger, because the + reset changed the counters and not the files. A probe with no row counters at all (`stats_are_stale`) + cannot seed anything: the prior count is carried forward, and with no prior count the files are taken as + fully reclaimable so nothing is deleted on its say-so. """ if probe.stats_are_stale: return SizeCleanupState( @@ -127,10 +140,26 @@ def advance_size_state(state: SizeCleanupState | None, probe: StorageProbe) -> S ) if state is None or probe.inserted_total < state.inserted_total or probe.deleted_total < state.deleted_total: seed_bytes_per_row: Final = probe.allocated_bytes / max(probe.live_rows + probe.dead_rows, 1) + seeded: Final = min(probe.allocated_bytes, round(probe.dead_rows * seed_bytes_per_row)) + if state is None: + return SizeCleanupState( + allocated_bytes=probe.allocated_bytes, + reclaimable_bytes=seeded, + bytes_per_row=max(seed_bytes_per_row, 1.0), + inserted_total=probe.inserted_total, + deleted_total=probe.deleted_total, + ) + carried: Final = max( + seeded, + min(probe.allocated_bytes, state.reclaimable_bytes - max(0, state.allocated_bytes - probe.allocated_bytes)), + ) + carried_live_bytes: Final = probe.allocated_bytes - carried return SizeCleanupState( allocated_bytes=probe.allocated_bytes, - reclaimable_bytes=min(probe.allocated_bytes, round(probe.dead_rows * seed_bytes_per_row)), - bytes_per_row=max(seed_bytes_per_row, 1.0), + reclaimable_bytes=carried, + bytes_per_row=max(carried_live_bytes / probe.live_rows, 1.0) + if probe.live_rows > 0 + else state.bytes_per_row, inserted_total=probe.inserted_total, deleted_total=probe.deleted_total, ) @@ -218,6 +247,43 @@ class TableCleanupResult: stop_reason: StopReason +@dataclass(frozen=True, slots=True) +class _SizeStepState: + """Progress of the size pass across its re-check steps.""" + + logs_deleted: int + index_deleted: int + batches_left: int + stop_reason: StopReason | None + + def stopped(self, reason: StopReason) -> "_SizeStepState": + return _SizeStepState( + logs_deleted=self.logs_deleted, + index_deleted=self.index_deleted, + batches_left=self.batches_left, + stop_reason=reason, + ) + + +@dataclass(frozen=True, slots=True) +class SizePassReport: + """What one size pass measured and achieved, for the run summary and the storage gauges.""" + + rule: SizeRule + before: SpendLogStorage + after: SpendLogStorage + partitions_dropped: tuple[str, ...] + results: tuple[TableCleanupResult, ...] + + @property + def target_reached(self) -> bool: + return self.after.estimated_live_bytes <= self.rule.target_bytes + + @property + def above_target_bytes(self) -> int: + return max(0, self.after.estimated_live_bytes - self.rule.target_bytes) + + class _RunProgress: """How far one cleanup run has got, reported if that run is cancelled""" @@ -277,6 +343,13 @@ _SAVE_SIZE_STATE_SQL: Final = """ """ +class _OffsetRow(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + startTime: datetime + + +_OFFSET_ROWS: Final = TypeAdapter(list[_OffsetRow]) + _SPEND_LOG_TABLES: Final = ("LiteLLM_SpendLogs", "LiteLLM_SpendLogToolIndex") # Partition children are counted with their parent: a partitioned parent has no storage of its own. @@ -299,6 +372,14 @@ _STORAGE_SQL: Final = """ ) """ +# The age job and the size job are scheduled on separate SpendLogCleanup instances, so the lock is per process. +_PASS_LOCK: Final = asyncio.Lock() + +_ANALYZE_SQL: Final = 'ANALYZE "LiteLLM_SpendLogs", "LiteLLM_SpendLogToolIndex"' +# pg_stat_user_tables publishes what ANALYZE counted up to a second later (the stats collector on Postgres 14). +_STATS_SETTLE_SECONDS: Final = 1.0 +_STATS_SETTLE_ATTEMPTS: Final = 5 + SPEND_LOG_CLEANUP_BOUND_SETTINGS: Final = ( "maximum_spend_logs_cleanup_batch_size", "maximum_spend_logs_cleanup_max_batches", @@ -456,6 +537,53 @@ class SpendLogCleanup: self.retention_seconds = self._retention_seconds_for("maximum_spend_logs_retention_period") return self.retention_seconds is not None + def _setting(self, setting_name: str) -> object: + return self.general_settings.get(setting_name) # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # untyped settings dict + + def _size_bytes_setting(self, setting_name: str) -> int | None: + """Parse one size setting into bytes, or None when unset or unusable.""" + raw: Final = self._setting(setting_name) + if raw is None: + return None + if not isinstance(raw, (str, int)): + verbose_proxy_logger.warning("Invalid %s value: %r, ignoring it", setting_name, raw) + return None + try: + return size_in_bytes(raw) + except ValueError as e: + verbose_proxy_logger.warning("Invalid %s value: %r (%s), ignoring it", setting_name, raw, e) + return None + + def _size_rule(self) -> SizeRule | None: + """ + The size rule from settings, or None when maximum_spend_logs_size is unset. + + A target at or above the limit cannot be what the operator meant, so it is reported and the run + cleans only until it is back under the limit, which is also what an unset target means. + """ + limit_bytes: Final = self._size_bytes_setting("maximum_spend_logs_size") + if limit_bytes is None: + return None + target_bytes: Final = self._size_bytes_setting("maximum_spend_logs_cleanup_target_size") + if target_bytes is None: + return SizeRule(limit_bytes=limit_bytes, target_bytes=limit_bytes) + if target_bytes >= limit_bytes: + verbose_proxy_logger.error( + "maximum_spend_logs_cleanup_target_size (%s bytes) must be below maximum_spend_logs_size (%s bytes); " + "cleaning down to maximum_spend_logs_size instead", + target_bytes, + limit_bytes, + ) + return SizeRule(limit_bytes=limit_bytes, target_bytes=limit_bytes) + return SizeRule(limit_bytes=limit_bytes, target_bytes=target_bytes) + + def _size_pass_runs_with_age_pass(self) -> bool: + """ + With maximum_spend_logs_cleanup_cron set there is one schedule for both rules, so the age run carries + the size pass; otherwise the size pass has its own job on maximum_spend_logs_size_check_interval. + """ + return bool(self._setting("maximum_spend_logs_cleanup_cron")) + async def _probe_storage(self, prisma_client: PrismaClient, deadline: float) -> StorageProbe | None: """Read what the spend-log tables weigh from the catalog, or None when the probe fails or has no budget.""" if time.monotonic() >= deadline: @@ -481,6 +609,48 @@ class SpendLogCleanup: deleted_total=row.deleted_total, ) + async def _reprobe_after_analyze( + self, prisma_client: PrismaClient, deadline: float, stale: StorageProbe + ) -> StorageProbe | None: + """ + Row counters that are all zero under a file with data were reset, e.g. by a crash. ANALYZE rebuilds + n_live_tup and n_dead_tup from a 30,000-row sample in seconds and blocks nothing, so the pass runs it and + reads the catalog again rather than trusting an estimate of zero or waiting a day for autoanalyze. The + new counts show up in pg_stat_user_tables a moment after ANALYZE returns, hence the settled re-reads. + """ + verbose_proxy_logger.warning( + "Spend-log row statistics are stale (allocated=%s bytes, live_rows=0, dead_rows=0); running %s before " + "the size pass", + stale.allocated_bytes, + _ANALYZE_SQL, + ) + if time.monotonic() >= deadline: + return None + timeout_ms: Final = self._timeout_ms(deadline) + try: + async with db_span("analyze", "LiteLLM_SpendLogs"), bounded_tx(prisma_client, timeout_ms) as tx: + await tx.execute_raw(trusted_sql(f"SET LOCAL statement_timeout = {timeout_ms}")) + await tx.execute_raw(trusted_sql(_ANALYZE_SQL)) + except Exception as e: # noqa: BLE001 - a failed ANALYZE skips the size pass, it must not fail the run + verbose_proxy_logger.warning("Could not ANALYZE the spend-log tables: %s: %s", type(e).__name__, e) + return None + refreshed: Final = await self._probe_once_settled(prisma_client, deadline, _STATS_SETTLE_ATTEMPTS) + if refreshed is None or refreshed.stats_are_stale: + verbose_proxy_logger.warning( + "Spend-log row statistics are still stale after ANALYZE; skipping the size pass" + ) + return None + return refreshed + + async def _probe_once_settled( + self, prisma_client: PrismaClient, deadline: float, attempts_left: int + ) -> StorageProbe | None: + await asyncio.sleep(_STATS_SETTLE_SECONDS) + refreshed: Final = await self._probe_storage(prisma_client, deadline) + if refreshed is None or not refreshed.stats_are_stale or attempts_left <= 1: + return refreshed + return await self._probe_once_settled(prisma_client, deadline, attempts_left - 1) + async def _load_size_state(self, prisma_client: PrismaClient, deadline: float) -> SizeCleanupState | None: """The reclaimable count saved by the last check, or None on the first check or when it cannot be read.""" if time.monotonic() >= deadline: @@ -508,6 +678,32 @@ class SpendLogCleanup: except Exception as e: # noqa: BLE001 - a lost save costs one re-seed from the catalog, it must not fail the run verbose_proxy_logger.warning("Could not save the spend-log size cleanup state: %s: %s", type(e).__name__, e) + async def _size_step_cutoff(self, prisma_client: PrismaClient, deadline: float, rows: int) -> datetime | None: + """ + The startTime that puts the `rows` oldest rows behind it. + + Expressing a size step as a cutoff lets the size pass reuse the retention DELETE unchanged, including + the tool-index rows that expire with their spend logs. When fewer rows than that remain, the step is + everything up to now. + """ + if time.monotonic() >= deadline: + return None + timeout_ms: Final = self._timeout_ms(deadline) + async with db_span("size_step_cutoff", "LiteLLM_SpendLogs"), bounded_tx(prisma_client, timeout_ms) as tx: + await tx.execute_raw(trusted_sql(f"SET LOCAL statement_timeout = {timeout_ms}")) + found: Final = _OFFSET_ROWS.validate_python( + await tx.query_raw( + trusted_sql( + 'SELECT "startTime" FROM "LiteLLM_SpendLogs" ORDER BY "startTime" ASC OFFSET $1 LIMIT 1' + ), + rows, + ) + ) + if not found: + return datetime.now(timezone.utc) + start_time: Final = found[0].startTime + return start_time if start_time.tzinfo is not None else start_time.replace(tzinfo=timezone.utc) + def _timeout_ms(self, deadline: float) -> int: """ The per-statement bound in milliseconds: the batch timeout, or whatever @@ -621,14 +817,17 @@ class SpendLogCleanup: key_columns: tuple[str, ...], time_column: str, deadline: float, + batch_cap: int | None = None, ) -> TableCleanupResult: """ Delete a table's rows older than the cutoff in batches. Stops at whichever bound is reached first: the backlog running out, the - shared wall-clock deadline, the per-table batch cap, or too many - consecutive batch failures. + shared wall-clock deadline, the per-table batch cap (`batch_cap` when a + caller spreads one table's cap over several calls, else the configured + one), or too many consecutive batch failures. """ + max_batches: Final = self.max_batches if batch_cap is None else batch_cap key_list: Final = ", ".join(f'"{col}"' for col in key_columns) delete_sql: Final = f""" DELETE FROM "{table_name}" @@ -651,7 +850,7 @@ class SpendLogCleanup: return await self._finish_table( prisma_client, cutoff_date, table_name, time_column, total_deleted, "budget_exhausted", deadline ) - if run_count >= self.max_batches: + if run_count >= max_batches: verbose_proxy_logger.info( "Max batches reached for %s cleanup, remaining rows will be deleted in next run", table_name ) @@ -891,6 +1090,215 @@ class SpendLogCleanup: verbose_proxy_logger.info("Deleted %s expired tool index rows", index_result.rows_deleted) return (logs_result, index_result) + async def _clean_spend_logs_by_size( + self, prisma_client: PrismaClient, rule: SizeRule, deadline: float + ) -> SizePassReport | None: + """ + Bring the spend-log tables under the size target, oldest rows first. + + Live bytes are the files on disk less the reclaimable count carried in LiteLLM_Config (see + `SizeCleanupState`), rolled forward from the catalog's cumulative insert and delete counters. A + partitioned table gives its oldest fully elapsed partitions back first, because a DROP returns disk at + once, re-measuring after each. Then rows go in steps: the rows still needed to reach the target follow + from bytes per row, and each step turns that many of the oldest rows (at most + SPEND_LOG_SIZE_CLEANUP_RECHECK_BATCHES batches) into a cutoff and runs the same bounded DELETE the age + rule uses, for the spend logs and the tool index rows derived from them. Progress is counted from the + deletes themselves, not re-read from pg_stat_user_tables, whose counters trail a DELETE by up to a + second. The run's batch cap and budget apply to the whole pass, so a pass that stops short reports how + far above the target it still is and the next check continues from there. + """ + measured: Final = await self._probe_storage(prisma_client, deadline) + if measured is None: + return None + probe: Final = ( + await self._reprobe_after_analyze(prisma_client, deadline, measured) + if measured.stats_are_stale + else measured + ) + if probe is None: + return None + state: Final = advance_size_state(await self._load_size_state(prisma_client, deadline), probe) + before: Final = SpendLogStorage( + allocated_bytes=probe.allocated_bytes, + reclaimable_bytes=state.reclaimable_bytes, + bytes_per_row=state.bytes_per_row, + live_rows=probe.live_rows, + ) + SpendLogCleanupMetrics.set_storage_bytes("allocated", before.allocated_bytes) + SpendLogCleanupMetrics.set_storage_bytes("estimated_live", before.estimated_live_bytes) + if before.estimated_live_bytes <= rule.limit_bytes: + verbose_proxy_logger.info( + "Spend-log storage is under maximum_spend_logs_size (estimated_live=%s allocated=%s reclaimable=%s " + "limit=%s bytes)", + before.estimated_live_bytes, + before.allocated_bytes, + before.reclaimable_bytes, + rule.limit_bytes, + ) + SpendLogCleanupMetrics.set_storage_bytes("above_target", 0) + await self._save_size_state(prisma_client, deadline, state) + return SizePassReport(rule=rule, before=before, after=before, partitions_dropped=(), results=()) + verbose_proxy_logger.warning( + "Spend-log storage is over maximum_spend_logs_size (estimated_live=%s allocated=%s reclaimable=%s " + "limit=%s bytes); deleting the oldest spend logs down to %s bytes", + before.estimated_live_bytes, + before.allocated_bytes, + before.reclaimable_bytes, + rule.limit_bytes, + rule.target_bytes, + ) + latest: Final[list[SpendLogStorage]] = [before] # mutable-ok: last measurement, rewritten per partition drop + baseline: Final[list[StorageProbe]] = [probe] # mutable-ok: counters after the last drop + + remeasure_failed: Final[list[bool]] = [False] # mutable-ok: set when a post-drop probe fails + + async def still_over_target() -> bool: + measured: Final = await self._probe_storage(prisma_client, deadline) + if measured is None: + remeasure_failed[0] = True + return False + kept: Final = min(1.0, measured.allocated_bytes / max(latest[0].allocated_bytes, 1)) + latest[0] = SpendLogStorage( + allocated_bytes=measured.allocated_bytes, + reclaimable_bytes=min(measured.allocated_bytes, round(latest[0].reclaimable_bytes * kept)), + bytes_per_row=latest[0].bytes_per_row, + live_rows=measured.live_rows, + ) + baseline[0] = measured + return latest[0].estimated_live_bytes > rule.target_bytes + + partitions_dropped: Final = await self._drop_oldest_partitions_for_size( + prisma_client, deadline, still_over_target + ) + if remeasure_failed[0]: + verbose_proxy_logger.warning( + "Spend-log storage could not be re-measured after dropping partitions %s; the row step and the saved " + "count wait for the next check rather than run on the pre-drop numbers", + partitions_dropped, + ) + return SizePassReport( + rule=rule, before=before, after=latest[0], partitions_dropped=partitions_dropped, results=() + ) + base: Final = latest[0] + rows_to_delete: Final = max(0, math.ceil((base.estimated_live_bytes - rule.target_bytes) / base.bytes_per_row)) + + def rows_still_needed(rows_deleted: int) -> int: + return rows_to_delete - rows_deleted + + results: Final = await self._delete_oldest_rows_for_size(prisma_client, deadline, rows_still_needed) + rows_deleted: Final = sum(result.rows_deleted for result in results) + remeasured: Final = await self._probe_storage(prisma_client, deadline) + after: Final = base.after_deleting( + rows_deleted, remeasured.allocated_bytes if remeasured is not None else base.allocated_bytes + ) + await self._save_size_state( + prisma_client, + deadline, + after.to_state( + inserted_total=baseline[0].inserted_total, deleted_total=baseline[0].deleted_total + rows_deleted + ), + ) + report: Final = SizePassReport( + rule=rule, before=before, after=after, partitions_dropped=partitions_dropped, results=results + ) + SpendLogCleanupMetrics.set_storage_bytes("allocated", after.allocated_bytes) + SpendLogCleanupMetrics.set_storage_bytes("estimated_live", after.estimated_live_bytes) + SpendLogCleanupMetrics.set_storage_bytes("above_target", report.above_target_bytes) + return report + + async def _drop_oldest_partitions_for_size( + self, prisma_client: PrismaClient, deadline: float, still_over_target: Callable[[], Awaitable[bool]] + ) -> tuple[str, ...]: + remaining_timeout_ms: Final = self._remaining_timeout_ms(deadline) + if time.monotonic() >= deadline or not self._setting("use_spend_logs_partitioning"): + return () + if not await self.partition_manager.is_partitioned(prisma_client, remaining_timeout_ms): + return () + await self.partition_manager.ensure_partitions(prisma_client, remaining_timeout_ms) + dropped: Final = await self.partition_manager.drop_oldest_partitions_while( + prisma_client, datetime.now(timezone.utc), remaining_timeout_ms, still_over_target + ) + verbose_proxy_logger.info("Dropped %d oldest spend-log partitions for the size rule: %s", len(dropped), dropped) + return tuple(dropped) + + async def _delete_oldest_rows_for_size( + self, + prisma_client: PrismaClient, + deadline: float, + rows_still_needed: Callable[[int], int], + ) -> tuple[TableCleanupResult, ...]: + state = _SizeStepState( # rebind-ok: one value threaded through the bounded step loop + logs_deleted=0, index_deleted=0, batches_left=self.max_batches, stop_reason=None + ) + for _ in range(self.max_batches // SPEND_LOG_SIZE_CLEANUP_RECHECK_BATCHES + 2): + if state.stop_reason is not None: + break + state = await self._run_size_step(prisma_client, deadline, rows_still_needed, state) + final_reason: Final[StopReason] = state.stop_reason or "batch_cap_reached" + return ( + TableCleanupResult( + table_name="LiteLLM_SpendLogs (size rule)", rows_deleted=state.logs_deleted, stop_reason=final_reason + ), + TableCleanupResult( + table_name="LiteLLM_SpendLogToolIndex (size rule)", + rows_deleted=state.index_deleted, + stop_reason=final_reason, + ), + ) + + async def _run_size_step( + self, + prisma_client: PrismaClient, + deadline: float, + rows_still_needed: Callable[[int], int], + state: "_SizeStepState", + ) -> "_SizeStepState": + """One step: delete the rows still needed, at most SPEND_LOG_SIZE_CLEANUP_RECHECK_BATCHES batches of the oldest.""" + needed: Final = rows_still_needed(state.logs_deleted + state.index_deleted) + if needed <= 0: + return state.stopped("target_reached") + if time.monotonic() >= deadline: + return state.stopped("budget_exhausted") + if state.batches_left <= 0: + return state.stopped("batch_cap_reached") + step_cap: Final = min( + SPEND_LOG_SIZE_CLEANUP_RECHECK_BATCHES, state.batches_left, math.ceil(needed / self.batch_size) + ) + cutoff: Final = await self._size_step_cutoff(prisma_client, deadline, step_cap * self.batch_size) + if cutoff is None: + return state.stopped("budget_exhausted") + logs_result: Final = await self._delete_old_rows_batched( + prisma_client, + cutoff, + table_name="LiteLLM_SpendLogs", + key_columns=("request_id", "startTime"), + time_column="startTime", + deadline=deadline, + batch_cap=step_cap, + ) + index_result: Final = await self._delete_old_rows_batched( + prisma_client, + cutoff, + table_name="LiteLLM_SpendLogToolIndex", + key_columns=("request_id", "tool_name"), + time_column="start_time", + deadline=deadline, + batch_cap=step_cap, + ) + advanced: Final = _SizeStepState( + logs_deleted=state.logs_deleted + logs_result.rows_deleted, + index_deleted=state.index_deleted + index_result.rows_deleted, + batches_left=state.batches_left - step_cap, + stop_reason=None, + ) + if rows_still_needed(advanced.logs_deleted + advanced.index_deleted) <= 0: + return advanced.stopped("target_reached") + if logs_result.stop_reason in ("aborted", "budget_exhausted") or index_result.stop_reason == "aborted": + return advanced.stopped(logs_result.stop_reason if logs_result.stop_reason != "exhausted" else "aborted") + if logs_result.rows_deleted == 0: + return advanced.stopped("exhausted") + return advanced + async def _clean_session_rollup( self, prisma_client: PrismaClient, retention_seconds: int, deadline: float ) -> tuple[TableCleanupResult, ...]: @@ -968,22 +1376,72 @@ class SpendLogCleanup: return "completed" @staticmethod - def _log_run_summary(outcome: RunOutcome, results: tuple[TableCleanupResult, ...], elapsed_seconds: float) -> None: + def _storage_summary(report: SizePassReport | None) -> str: + """ + The size pass in one clause: what was measured, where it ended against the target, and whether the + operator still has to act to get the disk back. + """ + if report is None: + return "" + rows_deleted: Final = sum(result.rows_deleted for result in report.results) + reclaim_note: Final = ( + "; allocated bytes stay until autovacuum reuses them, only VACUUM FULL or pg_repack on the spend-log " + "tables returns them to the filesystem" + if rows_deleted > 0 and report.after.allocated_bytes >= report.before.allocated_bytes + else "" + ) + return ( + f" storage: allocated_before={report.before.allocated_bytes} " + f"estimated_live_before={report.before.estimated_live_bytes} " + f"allocated_after={report.after.allocated_bytes} estimated_live_after={report.after.estimated_live_bytes} " + f"reclaimable_after={report.after.reclaimable_bytes} " + f"limit={report.rule.limit_bytes} target={report.rule.target_bytes} " + f"target_reached={str(report.target_reached).lower()} above_target={report.above_target_bytes} " + f"partitions_dropped={len(report.partitions_dropped)}{reclaim_note}" + ) + + @classmethod + def _log_run_summary( + cls, + outcome: RunOutcome, + results: tuple[TableCleanupResult, ...], + elapsed_seconds: float, + size_report: SizePassReport | None = None, + ) -> None: per_table: Final = ", ".join( f"{result.table_name}: deleted={result.rows_deleted} stop_reason={result.stop_reason}" for result in results ) - message: Final = "Spend log cleanup run finished: outcome=%s elapsed=%.1fs [%s]" - if outcome == "completed": - verbose_proxy_logger.info(message, outcome, elapsed_seconds, per_table) + message: Final = "Spend log cleanup run finished: outcome=%s elapsed=%.1fs [%s]%s" + storage: Final = cls._storage_summary(size_report) + if outcome == "completed" and (size_report is None or size_report.target_reached): + verbose_proxy_logger.info(message, outcome, elapsed_seconds, per_table, storage) return - verbose_proxy_logger.warning(message, outcome, elapsed_seconds, per_table) + verbose_proxy_logger.warning(message, outcome, elapsed_seconds, per_table, storage) async def cleanup_old_spend_logs(self, prisma_client: PrismaClient) -> None: """ - Main cleanup function. Deletes old spend logs in batches. + The scheduled retention run: every age rule, plus the size rule when one cron drives both. If pod_lock_manager is available, ensures only one pod runs cleanup. If no pod_lock_manager, runs cleanup without distributed locking. """ + await self._run(prisma_client, age_rules=True, size_rule=self._size_pass_runs_with_age_pass()) + + async def cleanup_spend_logs_by_size(self, prisma_client: PrismaClient) -> None: + """The size-check run scheduled on maximum_spend_logs_size_check_interval: the size rule only.""" + await self._run(prisma_client, age_rules=False, size_rule=True) + + async def _run(self, prisma_client: PrismaClient, age_rules: bool, size_rule: bool) -> None: + """ + One pass at a time per pod. The age job and the size job fire from separate schedules, and the pod + lock only exists with Redis, so this is what keeps them apart in a pod without it. The later one waits + rather than skips, because the other job applies a different rule and would not do its work for it. + """ + if _PASS_LOCK.locked(): + verbose_proxy_logger.info("Another cleanup pass is running in this pod; waiting for it to finish") + async with _PASS_LOCK: + await self._run_passes(prisma_client, age_rules, size_rule) + + async def _run_passes(self, prisma_client: PrismaClient, age_rules: bool, size_rule: bool) -> None: lock_acquired = False run_started_at: Final = time.monotonic() progress: Final = _RunProgress() @@ -992,19 +1450,23 @@ class SpendLogCleanup: verbose_proxy_logger.info("Cleanup job triggered at %s", datetime.now()) self._refresh_bounds() - delete_spend_logs: Final = self._should_delete_spend_logs() - autorouter_retention_seconds: Final = self._retention_seconds_for( - "maximum_autorouter_session_retention_period" + delete_spend_logs: Final = age_rules and self._should_delete_spend_logs() + active_size_rule: Final = self._size_rule() if size_rule else None + autorouter_retention_seconds: Final = ( + self._retention_seconds_for("maximum_autorouter_session_retention_period") if age_rules else None ) - health_check_retention_seconds: Final = self._retention_seconds_for("maximum_health_check_retention_period") - daily_tag_spend_retention_seconds: Final = self._retention_seconds_for( - "maximum_daily_tag_spend_retention_period" + health_check_retention_seconds: Final = ( + self._retention_seconds_for("maximum_health_check_retention_period") if age_rules else None + ) + daily_tag_spend_retention_seconds: Final = ( + self._retention_seconds_for("maximum_daily_tag_spend_retention_period") if age_rules else None ) if ( not delete_spend_logs and autorouter_retention_seconds is None and health_check_retention_seconds is None and daily_tag_spend_retention_seconds is None + and active_size_rule is None ): SpendLogCleanupMetrics.record_run("skipped_disabled") return @@ -1032,11 +1494,13 @@ class SpendLogCleanup: return deadline: Final = time.monotonic() + self.run_budget_seconds + size_group: Final = int(active_size_rule is not None) configured_group_count: Final = ( int(delete_spend_logs and self.retention_seconds is not None) + int(autorouter_retention_seconds is not None) + int(health_check_retention_seconds is not None) + int(daily_tag_spend_retention_seconds is not None) + + size_group ) spend_log_results: Final = ( @@ -1051,9 +1515,12 @@ class SpendLogCleanup: int(autorouter_retention_seconds is not None) + int(health_check_retention_seconds is not None) + int(daily_tag_spend_retention_seconds is not None) + + size_group ) - remaining_groups_after_sessions: Final = int(health_check_retention_seconds is not None) + int( - daily_tag_spend_retention_seconds is not None + remaining_groups_after_sessions: Final = ( + int(health_check_retention_seconds is not None) + + int(daily_tag_spend_retention_seconds is not None) + + size_group ) session_results: Final = ( await self._clean_session_rollup( @@ -1074,15 +1541,27 @@ class SpendLogCleanup: else () ) daily_tag_spend_results: Final = ( - await self._clean_daily_tag_spend(prisma_client, daily_tag_spend_retention_seconds, deadline) + await self._clean_daily_tag_spend( + prisma_client, + daily_tag_spend_retention_seconds, + self._group_deadline(deadline, 1 + size_group), + ) if daily_tag_spend_retention_seconds is not None else () ) + size_report: Final = ( + await self._clean_spend_logs_by_size(prisma_client, active_size_rule, deadline) + if active_size_rule is not None + else None + ) + size_results: Final = size_report.results if size_report is not None else () - results: Final = spend_log_results + session_results + health_check_results + daily_tag_spend_results + results: Final = ( + spend_log_results + session_results + health_check_results + daily_tag_spend_results + size_results + ) outcome: Final = self._run_outcome(results) SpendLogCleanupMetrics.record_run(outcome) - self._log_run_summary(outcome, results, time.monotonic() - run_started_at) + self._log_run_summary(outcome, results, time.monotonic() - run_started_at, size_report) except asyncio.CancelledError: verbose_proxy_logger.error( diff --git a/litellm/proxy/db/db_transaction_queue/spend_log_cleanup_metrics.py b/litellm/proxy/db/db_transaction_queue/spend_log_cleanup_metrics.py index 340aeab938c..048fa8127a4 100644 --- a/litellm/proxy/db/db_transaction_queue/spend_log_cleanup_metrics.py +++ b/litellm/proxy/db/db_transaction_queue/spend_log_cleanup_metrics.py @@ -32,6 +32,9 @@ RunOutcome: TypeAlias = Literal[ _BATCH_DURATION_BUCKETS: Final = (0.005, 0.025, 0.1, 0.25, 0.5, 1.0, 2.5, 5.0, 10.0, 30.0, 60.0) _TABLE_LABEL: Final = ("table",) _OUTCOME_LABEL: Final = ("outcome",) +_MEASURE_LABEL: Final = ("measure",) + +StorageMeasure: TypeAlias = Literal["allocated", "estimated_live", "above_target"] class SpendLogCleanupMetrics: @@ -49,6 +52,7 @@ class SpendLogCleanupMetrics: rows_remaining: "PrometheusGauge | None" = None batch_failures: "PrometheusCounter | None" = None runs: "PrometheusCounter | None" = None + storage_bytes: "PrometheusGauge | None" = None @classmethod def _ensure_initialized(cls) -> None: @@ -90,6 +94,15 @@ class SpendLogCleanupMetrics: "Retention cleanup runs, labelled by why the run ended", labelnames=_OUTCOME_LABEL, ) + cls.storage_bytes = Gauge( + "litellm_spend_log_storage_bytes", + "Disk held by LiteLLM_SpendLogs plus LiteLLM_SpendLogToolIndex as last measured by the cleanup " + "job: allocated is pg_total_relation_size (heap, indexes, TOAST), estimated_live scales it by the " + "live share of rows from pg_stat_user_tables, above_target is estimated_live minus the size " + "cleanup target (0 once the target is reached)", + labelnames=_MEASURE_LABEL, + multiprocess_mode="livemax", + ) except Exception as e: # noqa: BLE001 - a metrics problem must never fail the cleanup run # Covers the extra being absent, a duplicate registration (repeated # imports under a test runner), and registry misconfiguration alike. @@ -120,3 +133,9 @@ class SpendLogCleanupMetrics: cls._ensure_initialized() if cls.runs is not None: cls.runs.labels(outcome=outcome).inc() + + @classmethod + def set_storage_bytes(cls, measure: StorageMeasure, value: int) -> None: + cls._ensure_initialized() + if cls.storage_bytes is not None: + cls.storage_bytes.labels(measure=measure).set(value) diff --git a/litellm/proxy/db/db_transaction_queue/spend_logs_partition_manager.py b/litellm/proxy/db/db_transaction_queue/spend_logs_partition_manager.py index 3f9384d5d15..049a6ecbeee 100644 --- a/litellm/proxy/db/db_transaction_queue/spend_logs_partition_manager.py +++ b/litellm/proxy/db/db_transaction_queue/spend_logs_partition_manager.py @@ -14,7 +14,7 @@ keeps the batched-DELETE path, so existing deployments are untouched. """ import re -from collections.abc import Callable +from collections.abc import AsyncIterator, Awaitable, Callable, Sequence from datetime import date, datetime, timedelta, timezone from typing import ( TYPE_CHECKING, @@ -265,6 +265,52 @@ class SpendLogsPartitionManager: ) return [(row["name"], parse_partition_upper_bound(row.get("bound") or "")) for row in rows] + async def drop_oldest_partitions_while( + self, + prisma_client: "PrismaClient", + now: datetime, + remaining_timeout_ms: RemainingTimeoutMs, + still_over_target: Callable[[], Awaitable[bool]], + ) -> tuple[str, ...]: + """ + DROP fully elapsed partitions oldest first until `still_over_target` says the size rule is satisfied. + + Only partitions whose whole range lies before `now` are candidates, so the partition receiving + current writes and the DEFAULT partition are never dropped. The callback runs after every drop + because a DROP returns its disk at once, so a re-measure is what tells the loop to stop. + """ + list_budget_ms: Final = remaining_timeout_ms() + if list_budget_ms is None: + return () + now_naive: Final = now.astimezone(timezone.utc).replace(tzinfo=None) + partitions: Final = await self._list_partitions(prisma_client, list_budget_ms) + elapsed: Final = sorted( + ((upper, name) for name, upper in partitions if upper is not None and upper <= now_naive), + ) + drops: Final = self._drop_each_while(prisma_client, elapsed, remaining_timeout_ms, still_over_target) + return tuple([name async for name in drops]) + + async def _drop_each_while( + self, + prisma_client: "PrismaClient", + elapsed: Sequence[tuple[datetime, str]], + remaining_timeout_ms: RemainingTimeoutMs, + still_over_target: Callable[[], Awaitable[bool]], + ) -> AsyncIterator[str]: + for _, name in elapsed: + budget_ms: int | None = remaining_timeout_ms() + if budget_ms is None: + verbose_proxy_logger.info("Run budget spent, leaving the remaining partitions for the next run") + return + try: + await self._execute_bounded_ddl(prisma_client, f'DROP TABLE IF EXISTS "{name}"', budget_ms) + except Exception as e: # noqa: BLE001 # a partition this run cannot drop is left for the next one + verbose_proxy_logger.warning("Failed to drop spend-log partition %s: %s", name, e) + return + yield name + if not await still_over_target(): + return + async def drop_partitions_older_than( self, prisma_client: "PrismaClient", cutoff: datetime, remaining_timeout_ms: RemainingTimeoutMs ) -> list[str]: diff --git a/litellm/proxy/db/health_check_latest.py b/litellm/proxy/db/health_check_latest.py index 7672ed89e9a..024be7603d6 100644 --- a/litellm/proxy/db/health_check_latest.py +++ b/litellm/proxy/db/health_check_latest.py @@ -10,8 +10,9 @@ worker on every call. ``SELECT DISTINCT ON`` keeps the transfer at one row per from __future__ import annotations import json -from collections.abc import Mapping, Sequence +from collections.abc import Iterable, Mapping, Sequence from datetime import datetime, timezone +from types import MappingProxyType from typing import TYPE_CHECKING, Final, Protocol from pydantic import ConfigDict, JsonValue, TypeAdapter, field_validator @@ -113,3 +114,13 @@ async def fetch_latest_health_checks_for_models( except Exception as query_err: # noqa: BLE001 # a paged model list must not fail on its health decoration verbose_proxy_logger.error("Error getting latest health checks for models: %s", query_err) return () + + +def latest_by_model_name(rows: Iterable[LatestHealthCheckRow]) -> Mapping[str, LatestHealthCheckRow]: + """The newest row per model name. + + The queries above return one row per (model_id, model_name), so a model group with several + deployments comes back as several rows, plus one without a model_id if it was ever checked by + name. They arrive in model_id order with NULL last, which says nothing about which check is newest. + """ + return MappingProxyType({row.model_name: row for row in sorted(rows, key=lambda row: row.checked_at)}) diff --git a/litellm/proxy/decisions_endpoints/endpoints.py b/litellm/proxy/decisions_endpoints/endpoints.py index 1477e9f9591..366842d23a6 100644 --- a/litellm/proxy/decisions_endpoints/endpoints.py +++ b/litellm/proxy/decisions_endpoints/endpoints.py @@ -1,6 +1,6 @@ from collections.abc import Mapping from types import MappingProxyType -from typing import Annotated, Final, Literal +from typing import Annotated, Final, Literal, TypeAlias from fastapi import APIRouter, Depends, Request, Response from fastapi.responses import ORJSONResponse # pyright: ignore[reportDeprecated] # required endpoint contract @@ -18,6 +18,7 @@ from litellm.types.decisions import ( OpenAIDecisionRequestBody, OpenAIDecisionResponse, ) +from litellm.types.extraction import ExtractionRequest, ExtractionRequestBody, ExtractionResponse router: Final = APIRouter() _REQUEST_DATA_ADAPTER: Final[TypeAdapter[dict[str, object]]] = TypeAdapter(dict[str, object]) @@ -25,6 +26,7 @@ _DECISIONS_REQUEST_BODY_ADAPTER: Final[TypeAdapter[DecisionsRequestBody]] = Type _OPENAI_DECISION_REQUEST_BODY_ADAPTER: Final[TypeAdapter[OpenAIDecisionRequestBody]] = TypeAdapter( OpenAIDecisionRequestBody ) +_EXTRACTION_REQUEST_BODY_ADAPTER: Final[TypeAdapter[ExtractionRequestBody]] = TypeAdapter(ExtractionRequestBody) _GENERAL_SETTINGS_ADAPTER: Final[TypeAdapter[dict[str, object]]] = TypeAdapter(dict[str, object]) _OPTIONAL_STRING_ADAPTER: Final[TypeAdapter[str | None]] = TypeAdapter(str | None) _OPTIONAL_FLOAT_ADAPTER: Final[TypeAdapter[float | None]] = TypeAdapter(float | None) @@ -73,16 +75,35 @@ _DECISIONS_REQUEST_BODY: Final = inline_request_body( ], }, ) +_EXTRACTION_REQUEST_BODY: Final = inline_request_body( + ExtractionRequest, + { + "model": "clairic", + "state": "Invoice #4471 from Acme Tools, dated 2026-03-03. 12 hammers. Total $174. Payment due in 30 days.", + "fields": { + "vendor": {"type": "text", "instructions": "Who sent the invoice?"}, + "invoice_date": {"type": "date"}, + "total": {"type": "number", "unit": "USD"}, + "items": {"type": "list", "items": "text", "instructions": "What was bought?"}, + "days_to_pay": {"type": "estimate", "min": 0, "max": 90}, + }, + }, +) +_ApiName: TypeAlias = Literal["Decisions", "Extraction"] +_RouteType: TypeAlias = Literal["adecisions", "asystemone", "aextraction"] async def _invalid_request( - raw_data: Mapping[str, object], error: ValidationError, user_api_key_dict: UserAPIKeyAuth + raw_data: Mapping[str, object], + error: ValidationError, + user_api_key_dict: UserAPIKeyAuth, + api_name: _ApiName, ) -> Exception: from litellm.proxy.proxy_server import proxy_logging_obj, version return await ProxyBaseLLMRequestProcessing(data=dict(raw_data)).handle_llm_api_exception( e=BadRequestError( - message=f"Invalid Decisions request: {error}", + message=f"Invalid {api_name} request: {error}", model=str(raw_data.get("model", "")), llm_provider="", ), @@ -95,19 +116,21 @@ async def _invalid_request( _FIELDS_CHECKED_AFTER_ROUTING: Final = frozenset({"safety_identifier", "images", "assets", "audio", "videos"}) -def _fields_checked_before_routing(data: Mapping[str, object]) -> Mapping[str, object]: +def _fields_checked_before_routing(data: Mapping[str, object], route_type: _RouteType) -> Mapping[str, object]: + if route_type == "aextraction": + return data return MappingProxyType({key: value for key, value in data.items() if key not in _FIELDS_CHECKED_AFTER_ROUTING}) _DEPLOYMENT_ONLY_FIELDS: Final = frozenset({"model_info"}) -async def _request_data(request: Request, user_api_key_dict: UserAPIKeyAuth) -> dict[str, object]: +async def _request_data(request: Request, user_api_key_dict: UserAPIKeyAuth, api_name: _ApiName) -> dict[str, object]: body: Final = await request.body() try: data: Final = _REQUEST_DATA_ADAPTER.validate_json(body) except ValidationError as error: - raise await _invalid_request(raw_data={}, error=error, user_api_key_dict=user_api_key_dict) + raise await _invalid_request(raw_data={}, error=error, user_api_key_dict=user_api_key_dict, api_name=api_name) return {key: value for key, value in data.items() if key not in _DEPLOYMENT_ONLY_FIELDS} @@ -115,8 +138,10 @@ async def _process_decisions( request: Request, fastapi_response: Response, user_api_key_dict: UserAPIKeyAuth, - body_adapter: TypeAdapter[DecisionsRequestBody] | TypeAdapter[OpenAIDecisionRequestBody], - route_type: Literal["adecisions", "asystemone"], + body_adapter: ( + TypeAdapter[DecisionsRequestBody] | TypeAdapter[OpenAIDecisionRequestBody] | TypeAdapter[ExtractionRequestBody] + ), + route_type: _RouteType, ) -> object: from litellm.proxy.proxy_server import ( general_settings as proxy_general_settings, @@ -139,15 +164,17 @@ async def _process_decisions( user_temperature as proxy_user_temperature, ) - data: Final = await _request_data(request, user_api_key_dict) + api_name: Final[_ApiName] = "Extraction" if route_type == "aextraction" else "Decisions" + data: Final = await _request_data(request, user_api_key_dict, api_name) try: - body_adapter.validate_python(_fields_checked_before_routing(data)) + body_adapter.validate_python(_fields_checked_before_routing(data, route_type)) except ValidationError as error: - raise await _invalid_request(raw_data=data, error=error, user_api_key_dict=user_api_key_dict) + raise await _invalid_request(raw_data=data, error=error, user_api_key_dict=user_api_key_dict, api_name=api_name) general_settings: Final = _GENERAL_SETTINGS_ADAPTER.validate_python(proxy_general_settings) user_api_base: Final = _OPTIONAL_STRING_ADAPTER.validate_python(proxy_user_api_base) user_model: Final = _OPTIONAL_STRING_ADAPTER.validate_python(proxy_user_model) user_temperature: Final = _OPTIONAL_FLOAT_ADAPTER.validate_python(proxy_user_temperature) + takes_generation_settings: Final = route_type != "aextraction" processor: Final = ProxyBaseLLMRequestProcessing(data=data) try: return await processor.base_process_llm_request( @@ -162,9 +189,9 @@ async def _process_decisions( select_data_generator=None, model=None, user_model=user_model, - user_temperature=user_temperature, + user_temperature=user_temperature if takes_generation_settings else None, user_request_timeout=user_request_timeout, - user_max_tokens=user_max_tokens, + user_max_tokens=user_max_tokens if takes_generation_settings else None, user_api_base=user_api_base, version=version, ) @@ -263,3 +290,53 @@ async def decisions( body_adapter=_OPENAI_DECISION_REQUEST_BODY_ADAPTER, route_type="adecisions", ) + + +@router.post( + "/v1/extraction", + dependencies=[Depends(user_api_key_auth)], + response_class=ORJSONResponse, # pyright: ignore[reportDeprecated] # required endpoint contract + tags=["extraction"], + summary="Extract typed fields from a state", + responses={200: {"model": ExtractionResponse}}, + response_model=None, + openapi_extra={"requestBody": _EXTRACTION_REQUEST_BODY}, +) +@router.post( + "/extraction", + dependencies=[Depends(user_api_key_auth)], + response_class=ORJSONResponse, # pyright: ignore[reportDeprecated] # required endpoint contract + tags=["extraction"], + summary="Extract typed fields from a state", + responses={200: {"model": ExtractionResponse}}, + response_model=None, + openapi_extra={"requestBody": _EXTRACTION_REQUEST_BODY}, +) +async def extraction( + request: Request, + fastapi_response: Response, + user_api_key_dict: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], +) -> object: + """ + Read a `state` text and up to 4 images and get one typed answer per named field in `fields`. + + Field types are `text`, `number`, `date`, `time`, `datetime`, `duration`, `list` (set `items`), `estimate` + (set `min` and `max`) and `forecast` (set `min`, `max` and `horizon`). Each answer carries its `value`, which is + null when the input does not determine it, plus `confidence`, `p_null`, text `span`s into the state and, for + estimates, `mean`, `median`, `p10` and `p90`. Images are data URLs or `{content_type, base64}` objects, remote + URLs are not accepted. An unknown field type, a field name that is not 1 to 64 letters, digits, `_`, `.` or `-` + starting with a letter or `_`, a remote image URL or more than 4 images is rejected with a 400 before any + provider is called. Any other top-level key, `stream: true` and OpenAI generation settings such as `temperature` + included, is rejected with a 400 naming it unless `drop_params` or the deployment's `additional_drop_params` + drops it. Settings inside `fields` and `options` go to the provider as sent, so a field missing a setting its + type needs or an empty `state` with no images comes back with the provider's own error. `model` is any + extraction model in the proxy model list, such as Cloudflare Clairic. The request and the answers keep the + provider's format. + """ + return await _process_decisions( + request=request, + fastapi_response=fastapi_response, + user_api_key_dict=user_api_key_dict, + body_adapter=_EXTRACTION_REQUEST_BODY_ADAPTER, + route_type="aextraction", + ) diff --git a/litellm/proxy/guardrails/auto_router_compression.py b/litellm/proxy/guardrails/auto_router_compression.py index ecb182ab33c..1267fb15db8 100644 --- a/litellm/proxy/guardrails/auto_router_compression.py +++ b/litellm/proxy/guardrails/auto_router_compression.py @@ -156,15 +156,13 @@ async def arm_pre_call( if not isinstance(model_alias, str) or not model_alias: return - from litellm.router_strategy.tag_based_routing import ( - get_tags_from_request_kwargs, - ) + from litellm.router_strategy.tag_based_routing import get_routing_tags_from_request_kwargs policy: Final = policy_for_model( llm_router=llm_router, model_alias=model_alias, request_kwargs=data, - request_tags=get_tags_from_request_kwargs(data), + request_tags=get_routing_tags_from_request_kwargs(data), ) if policy is None: return diff --git a/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py b/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py index 12b8e728b4e..adda465ad95 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py +++ b/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py @@ -796,7 +796,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): # logic becomes shared across providers. #### CALL HOOKS - proxy only #### - def _load_credentials(self, bearer_token: str | None = None): + def _load_credentials(self, api_key: str | None = None): try: from botocore.credentials import Credentials except ImportError: @@ -820,7 +820,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): credentials: Final[Credentials | None] = ( None - if bearer_token is not None + if bedrock_bearer_token(api_key) is not None else self.get_credentials( aws_access_key_id=aws_access_key_id, aws_secret_access_key=aws_secret_access_key, @@ -1017,9 +1017,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): start_time: "datetime", allow_chunking: bool, ) -> BedrockGuardrailResponse: - credentials, aws_region_name = await run_aws_signing( - self._load_credentials, bearer_token=bedrock_bearer_token(api_key) - ) + credentials, aws_region_name = await run_aws_signing(self._load_credentials, api_key=api_key) completed_chunk_usages: Final[list[BedrockGuardrailUsage]] = [] # mutable-ok: billed-chunk usage accumulator try: @@ -1960,9 +1958,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): return BedrockGuardrailResponse() api_key: Final[str | None] = request_data.get("api_key") if request_data else None - credentials, aws_region_name = await run_aws_signing( - self._load_credentials, bearer_token=bedrock_bearer_token(api_key) - ) + credentials, aws_region_name = await run_aws_signing(self._load_credentials, api_key=api_key) body: Final[dict[str, object]] = {"messages": checks_messages, "checks": self.checks} prepared_request: Final = await run_aws_signing( diff --git a/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/patterns.py b/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/patterns.py index 9d051eb90d6..da937bd0325 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/patterns.py +++ b/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/patterns.py @@ -8,19 +8,39 @@ sensitive information like SSNs, credit cards, API keys, etc. import json import os import re -from collections.abc import Iterator +from collections.abc import Iterator, Sequence from enum import Enum from re import Pattern from typing import Any, Final +from pydantic import ConfigDict, TypeAdapter, with_config +from typing_extensions import ReadOnly, TypedDict + from litellm.proxy.guardrails.content_filter_data import DATA_ROOTS, category_dirs -def _load_patterns_from_json() -> dict: +@with_config(ConfigDict(extra="allow", strict=True, hide_input_in_errors=True)) +class _PatternEntry(TypedDict): + name: ReadOnly[str] + display_name: ReadOnly[str] + pattern: ReadOnly[str] + category: ReadOnly[str] + description: ReadOnly[str] + + +@with_config(ConfigDict(extra="allow", strict=True, hide_input_in_errors=True)) +class _PatternsFile(TypedDict): + patterns: ReadOnly[Sequence[_PatternEntry]] + + +_PATTERNS_FILE: Final = TypeAdapter(_PatternsFile) + + +def _load_patterns_from_json() -> _PatternsFile: """Load pattern definitions from patterns.json file""" json_path: Final = os.path.join(os.path.dirname(__file__), "patterns.json") with open(json_path, "r") as f: - return json.load(f) + return _PATTERNS_FILE.validate_python(json.load(f)) # Load patterns from JSON diff --git a/litellm/proxy/health_endpoints/_health_endpoints.py b/litellm/proxy/health_endpoints/_health_endpoints.py index 1e7f67392e1..684f1619512 100644 --- a/litellm/proxy/health_endpoints/_health_endpoints.py +++ b/litellm/proxy/health_endpoints/_health_endpoints.py @@ -2155,6 +2155,7 @@ async def test_model_connection( "ocr", "evaluation", "decisions", + "extraction", ] | None = fastapi.Body( None, diff --git a/litellm/proxy/hooks/model_max_budget_limiter.py b/litellm/proxy/hooks/model_max_budget_limiter.py index 00b5f9cd31c..37cef41034b 100644 --- a/litellm/proxy/hooks/model_max_budget_limiter.py +++ b/litellm/proxy/hooks/model_max_budget_limiter.py @@ -7,8 +7,6 @@ from datetime import datetime, timezone from types import MappingProxyType from typing import Final, cast # noqa: TID251 # untyped callback payload requires explicit narrowing -from openai.types import Batch - import litellm from litellm._internal_context import with_service_target from litellm._logging import verbose_proxy_logger @@ -19,7 +17,7 @@ from litellm.litellm_core_utils.litellm_logging import StandardLoggingPayloadSet from litellm.llms.bedrock.common_utils import get_bedrock_base_model from litellm.proxy._types import Litellm_EntityType, UserAPIKeyAuth from litellm.router_strategy.budget_limiter import RouterBudgetLimiting, budget_window_seconds -from litellm.router_utils.batch_utils import is_batch_retrieve_call_type +from litellm.router_utils.batch_utils import batch_charged_once_marker_key, batch_id_to_charge_once from litellm.types.llms.openai import AllMessageValues from litellm.types.utils import BudgetConfig, StandardLoggingPayload @@ -133,17 +131,6 @@ def model_budget_start_time_cache_key( return f"{_BUDGET_START_TIME_KEY_PREFIXES[entity_type]}:{entity_id}:{budget_model}:{budget_duration}" -def batch_charged_once_marker_key(spend_key: str, batch_id: str) -> str: - return f"{spend_key}:batch:{batch_id}" - - -def batch_id_to_charge_once(call_type: object, response_obj: object, response_cost: float) -> str | None: - """A finished batch reports its whole cost on every poll, so its id is charged once per counter.""" - if response_cost <= 0 or not is_batch_retrieve_call_type(call_type): - return None - return response_obj.id if isinstance(response_obj, Batch) else None - - def resolve_model_budget(model: str, model_max_budget: Mapping[str, object]) -> ResolvedModelBudget | None: """Find the `model_max_budget` entry that governs `model`, or None.""" for candidate in _budget_model_candidates(model): diff --git a/litellm/proxy/hooks/parallel_request_limiter_v3.py b/litellm/proxy/hooks/parallel_request_limiter_v3.py index d858eff3348..4f2f7f9c256 100644 --- a/litellm/proxy/hooks/parallel_request_limiter_v3.py +++ b/litellm/proxy/hooks/parallel_request_limiter_v3.py @@ -7,6 +7,7 @@ This is currently in development and not yet ready for production. import asyncio import binascii import itertools +import json import logging import os import uuid @@ -42,6 +43,7 @@ from litellm.caching.redis_batch import ( ) from litellm.caching.redis_cache import log_redis_failure from litellm.constants import DYNAMIC_RATE_LIMIT_ERROR_THRESHOLD_PER_MINUTE, INTERNAL_CALL_ORIGIN_METADATA_KEY +from litellm.cost_calculator import get_usage_object from litellm.integrations.custom_logger import CustomLogger from litellm.litellm_core_utils.prompt_templates.common_utils import ( get_str_from_messages, @@ -78,6 +80,7 @@ from litellm.router_utils.add_retry_fallback_headers import ( from litellm.router_utils.common_utils import resolve_model_group_alias from litellm.router_utils.ptu_shares import PTUTeamCeiling from litellm.types.caching import RedisPipelineIncrementOperation +from litellm.types.extraction import ExtractionResponse from litellm.types.llms.openai import BaseLiteLLMOpenAIResponseObject, ResponseAPIUsage from litellm.types.mcp_server.mcp_server_manager import MCPServer from litellm.types.passthrough_endpoints.pass_through_endpoints import EndpointType @@ -490,6 +493,7 @@ RESPONSES_API_CALL_TYPES: Final = ("aresponses", "responses") EMBEDDING_API_CALL_TYPES: Final = ("aembedding", "embedding") TEXT_COMPLETION_API_CALL_TYPES: Final = ("atext_completion", "text_completion") RERANK_API_CALL_TYPES: Final = (CallTypes.rerank.value, CallTypes.arerank.value) +EXTRACTION_API_CALL_TYPES: Final = (CallTypes.extraction.value, CallTypes.aextraction.value) GOOGLE_GENAI_NATIVE_CALL_TYPES: Final = ( CallTypes.generate_content.value, CallTypes.agenerate_content.value, @@ -1094,6 +1098,7 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): or PROXY_MaxParallelRequestsHandler_v3._has_explicit_output_cap(data, call_type) or is_embedding or endpoint_type == EndpointType.DECISIONS + or call_type in EXTRACTION_API_CALL_TYPES ): return effective_cap: Final = max(capped_floor, configured_output_tokens or 0) @@ -1218,6 +1223,8 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): if call_type in RESPONSES_API_CALL_TYPES or call_type in EMBEDDING_API_CALL_TYPES else (None, estimable_data.get("prompt"), None) if call_type in TEXT_COMPLETION_API_CALL_TYPES + else (None, self._extraction_input_text(_REQUEST_RATE_LIMIT_DATA.validate_python(estimable_data)), None) + if call_type in EXTRACTION_API_CALL_TYPES else (estimable_data.get("messages"), None, None) if call_type else ( @@ -1245,7 +1252,9 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): estimated_input_tokens: Final = max(1, total_chars // DEFAULT_CHARS_PER_TOKEN) if total_chars > 0 else 0 explicit_max_tokens: Final = self._get_explicit_output_cap(data, call_type) - is_embedding: Final = self._is_embedding_request(data, call_type) + generates_no_output: Final = ( + self._is_embedding_request(data, call_type) or call_type in EXTRACTION_API_CALL_TYPES + ) base_output_floor: Final = self.no_max_tokens_output_floor(min_configured_tpm_limit) output_floor: Final = ( @@ -1255,7 +1264,8 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): ) max_tokens_estimate: Final = ( 0 - if is_embedding or (explicit_max_tokens is None and total_chars == 0 and configured_output_tokens is None) + if generates_no_output + or (explicit_max_tokens is None and total_chars == 0 and configured_output_tokens is None) else explicit_max_tokens if explicit_max_tokens is not None else configured_output_tokens @@ -3834,6 +3844,11 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): if isinstance(part, (str, dict)) ) + @staticmethod + def _extraction_input_text(data: Mapping[str, object]) -> str: + state: Final = data.get("state") + return f"{state if isinstance(state, str) else ''}\n{json.dumps(data.get('fields'), default=str)}" + def _estimate_precise_input_tokens(self, data: object, model: str | None, call_type: str | None = None) -> int: """ Model-aware input token estimate for the project ITPM reservation, @@ -3892,6 +3907,8 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): if call_type in RERANK_API_CALL_TYPES else (None, prompt, data.get("tools"), data.get("tool_choice")) if call_type in TEXT_COMPLETION_API_CALL_TYPES + else (None, self._extraction_input_text(_REQUEST_RATE_LIMIT_DATA.validate_python(data)), None, None) + if call_type in EXTRACTION_API_CALL_TYPES else (data.get("messages"), fallback_text, data.get("tools"), data.get("tool_choice")) ) messages, selected_text, countable_tools, countable_tool_choice = selected_inputs @@ -4512,6 +4529,8 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): ) -> Usage | ResponseAPIUsage | Mapping[str, object] | None: if isinstance(response_obj, (Usage, ResponseAPIUsage)): return response_obj + if isinstance(response_obj, ExtractionResponse): + return get_usage_object(response_obj) if isinstance( response_obj, (ModelResponse, EmbeddingResponse, TextCompletionResponse, BaseLiteLLMOpenAIResponseObject), @@ -5143,21 +5162,24 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): # than parsed out of the body) carry their usage in # ``combined_usage_object`` instead, and would otherwise never charge # the TPM window. - _usage: Usage | dict[str, object] | None = None - if isinstance( - response_obj, - ( - ModelResponse, - EmbeddingResponse, - TextCompletionResponse, - BaseLiteLLMOpenAIResponseObject, - ), - ): - _usage = getattr(response_obj, "usage", None) - else: - _combined_usage: Final = kwargs.get("combined_usage_object") - if isinstance(_combined_usage, Usage): - _usage = _combined_usage + _combined_usage: Final = kwargs.get("combined_usage_object") + _usage: Final[Usage | dict[str, object] | None] = ( + getattr(response_obj, "usage", None) + if isinstance( + response_obj, + ( + ModelResponse, + EmbeddingResponse, + TextCompletionResponse, + BaseLiteLLMOpenAIResponseObject, + ), + ) + else get_usage_object(response_obj) + if isinstance(response_obj, ExtractionResponse) + else _combined_usage + if isinstance(_combined_usage, Usage) + else None + ) total_tokens = self._get_total_tokens_from_usage(usage=_usage, rate_limit_type=rate_limit_type) if total_tokens == 0: total_tokens = self._aggregate_only_total_tokens(usage=_usage) diff --git a/litellm/proxy/hooks/proxy_track_cost_callback.py b/litellm/proxy/hooks/proxy_track_cost_callback.py index 4434fe57ab6..994310c6619 100644 --- a/litellm/proxy/hooks/proxy_track_cost_callback.py +++ b/litellm/proxy/hooks/proxy_track_cost_callback.py @@ -1,16 +1,18 @@ import asyncio import traceback -from collections.abc import Callable, Mapping, Sequence -from datetime import datetime +from collections.abc import Callable, Generator, Mapping, Sequence +from contextlib import contextmanager +from contextvars import ContextVar +from datetime import datetime, timezone from types import MappingProxyType -from typing import TYPE_CHECKING, Final, Protocol, cast +from typing import TYPE_CHECKING, Final, Protocol, TypeAlias, cast from pydantic import TypeAdapter, ValidationError import litellm from litellm._logging import verbose_proxy_logger from litellm.batches.batch_utils import batch_cost_is_final -from litellm.constants import BACKGROUND_INTERACTION_COST_POLLING_ENABLED +from litellm.constants import BACKGROUND_INTERACTION_COST_POLLING_ENABLED, BILLED_RETRY_ATTEMPT_METADATA_KEY from litellm.integrations.custom_logger import CustomLogger from litellm.litellm_core_utils.core_helpers import ( budget_reservation_from_metadata, @@ -33,6 +35,7 @@ from litellm.proxy.db.db_spend_update_writer import ( debitable_model_access_groups, get_llm_router, ) +from litellm.proxy.hooks.search_free_tier import apply_search_free_tier from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup, metadata_variable_name_for_route from litellm.proxy.spend_tracking.spend_counter_batch import post_call_counter_keys, spend_counter_batch_scope from litellm.proxy.spend_tracking.spend_event import ( @@ -51,11 +54,13 @@ from litellm.proxy.spend_tracking.spend_log_error_logger import ( ) from litellm.proxy.spend_tracking.spend_tracking_utils import ( # noqa: F401 # legacy module exports _sanitize_error_information_for_spend_logs, # pyright: ignore[reportPrivateUsage,reportUnusedImport] # backwards-compatible package export + deployment_params_provider, get_request_model_access_groups, sanitize_error_information_for_spend_logs, should_store_prompts_and_responses_in_spend_logs, ) -from litellm.proxy.utils import ProxyUpdateSpend +from litellm.proxy.utils import BilledFailedAttempt, ProxyUpdateSpend +from litellm.types.router import Deployment from litellm.types.utils import ( CallTypes, LiteLLMBatch, @@ -67,6 +72,37 @@ from litellm.utils import get_end_user_id_for_cost_tracking if TYPE_CHECKING: from litellm.proxy.utils import ProxyLogging + +class BatchAccountingOutcome: + def __init__(self, call_id: str) -> None: + self.call_id: Final = call_id + self.write_started = False + self.failed = False + + @property + def retryable_failure(self) -> bool: + return self.failed and not self.write_started + + +_BATCH_ACCOUNTING: Final[ContextVar[BatchAccountingOutcome | None]] = ContextVar("batch_accounting", default=None) +_BATCH_CALLBACK_FIELDS: Final = TypeAdapter(dict[str, object]) + + +@contextmanager +def track_batch_accounting(call_id: str) -> Generator[BatchAccountingOutcome, None, None]: + outcome: Final = BatchAccountingOutcome(call_id) + token: Final = _BATCH_ACCOUNTING.set(outcome) + try: + yield outcome + finally: + _BATCH_ACCOUNTING.reset(token) + + +def _batch_accounting_for(call_id: object) -> BatchAccountingOutcome | None: + outcome: Final = _BATCH_ACCOUNTING.get() + return outcome if outcome is not None and call_id == outcome.call_id else None + + _UNATTRIBUTED_TRACKABLE_CALL_TYPES: Final[frozenset[str]] = frozenset( { CallTypes.pass_through.value, @@ -153,6 +189,123 @@ def _proxy_spend_writer() -> DBSpendUpdateWriter: return proxy_logging_obj.db_spend_update_writer +DeploymentLookup: TypeAlias = Callable[[str], Deployment | None] + + +def _proxy_deployment(model_id: str) -> Deployment | None: + router: Final = get_llm_router() + return None if router is None else router.get_deployment(model_id=model_id) + + +def _billed_failed_attempts(request_data: Mapping[str, object]) -> tuple[BilledFailedAttempt, ...]: + """The earlier billed attempts ``_failure_fields_to_lift`` stashed on the request, if any.""" + attempts: Final = request_data.get("billed_failed_attempts") + if not isinstance(attempts, tuple): + return () + lifted: Final = cast("tuple[object, ...]", attempts) # cast-ok: lifted by _failure_fields_to_lift, checked below + return tuple(attempt for attempt in lifted if isinstance(attempt, BilledFailedAttempt)) + + +def _failure_spend_rows( + request_data: Mapping[str, object], + final_cost: float, + late_guardrails_snapshot: object, + deployment_lookup: DeploymentLookup, +) -> tuple[tuple[float, Mapping[str, object]], ...]: + """One ``(response_cost, kwargs)`` per spend row a failure writes: the final attempt under the + request id, then every earlier attempt the provider also billed under its own row.""" + final_row: Final[Mapping[str, object]] = ( + request_data + if late_guardrails_snapshot is None + else {**request_data, "standard_logging_object": late_guardrails_snapshot} + ) + return ( + (final_cost, final_row), + *( + ( + attempt.response_cost, + _attempt_spend_row_kwargs( + request_data, attempt, position, _attempt_deployment(attempt, deployment_lookup) + ), + ) + for position, attempt in enumerate(_billed_failed_attempts(request_data)) + ), + ) + + +def _attempt_deployment(attempt: BilledFailedAttempt, deployment_lookup: DeploymentLookup) -> Deployment | None: + return None if attempt.deployment_id is None else deployment_lookup(attempt.deployment_id) + + +def _deployment_attribution(deployment: Deployment) -> Mapping[str, object]: + """The spend-log attribution fields of the deployment that served an attempt: the model string it + was called with, its provider, its configured ``api_base`` and its model group.""" + return MappingProxyType( + { + "model": deployment.litellm_params.model, + "custom_llm_provider": deployment_params_provider(deployment.litellm_params), + "api_base": deployment.litellm_params.api_base, + "model_group": deployment.model_name, + } + ) + + +_NO_ATTRIBUTION: Final[Mapping[str, object]] = MappingProxyType({}) + + +def _attempt_spend_row_kwargs( + request_data: Mapping[str, object], attempt: BilledFailedAttempt, position: int, deployment: Deployment | None +) -> Mapping[str, object]: + """The final attempt's row kwargs re-keyed for one earlier billed attempt: its own + ``request_id`` (``-attempt-``, since ``request_id`` is the spend-log primary key + and the retry count restarts after a fallback hop), its estimated usage and cost, its retry + count under ``attempted_retries``, the deployment that billed it under ``model_info.id`` and, + when the router still knows that deployment, its model, provider, ``api_base`` and model group. + The row is stamped ``billed_retry_attempt`` so the daily spend tables keep its spend, tokens + and model usage without counting it as a request the caller sent.""" + suffix: Final = f"-attempt-{position}" + attribution: Final = _NO_ATTRIBUTION if deployment is None else _deployment_attribution(deployment) + raw_params: Final = cast("Mapping[str, object]", request_data.get("litellm_params") or {}) # cast-ok: request dict + litellm_params: Final = { + **raw_params, + **({} if deployment is None else {"api_base": attribution["api_base"]}), + } + metadata: Final = { + **cast("Mapping[str, object]", litellm_params.get("metadata") or {}), # cast-ok: request dict + "attempted_retries": attempt.attempted_retries, + BILLED_RETRY_ATTEMPT_METADATA_KEY: True, + **({} if deployment is None else {"model_group": attribution["model_group"]}), + } + metadata.pop("previous_models", None) + if attempt.deployment_id is not None: + metadata["model_info"] = { + **cast("Mapping[str, object]", metadata.get("model_info") or {}), # cast-ok: router dict + "id": attempt.deployment_id, + } + litellm_params["metadata"] = metadata + row: Final = { + **request_data, + **({} if deployment is None else {k: attribution[k] for k in ("model", "custom_llm_provider")}), + "litellm_params": litellm_params, + "combined_usage_object": attempt.usage, + "response_cost": attempt.response_cost, + } + row.pop("billed_failed_attempts", None) + call_id: Final = request_data.get("litellm_call_id") or litellm_params.get("litellm_call_id") + if isinstance(call_id, str): + row["litellm_call_id"] = f"{call_id}{suffix}" + standard_logging_object: Final = request_data.get("standard_logging_object") + if isinstance(standard_logging_object, dict): + payload: Final = cast("Mapping[str, object]", standard_logging_object) # cast-ok: StandardLoggingPayload dict + if isinstance(payload.get("id"), str): + row["standard_logging_object"] = { + **payload, + "id": f"{payload['id']}{suffix}", + **({} if deployment is None else {**attribution, "model_id": attempt.deployment_id}), + } + return row + + class _ProxyDBLogger(CustomLogger): def __init__( self, @@ -161,10 +314,12 @@ class _ProxyDBLogger(CustomLogger): turn_off_message_logging: bool = False, message_logging: bool = True, spend_writer: Callable[[], DBSpendUpdateWriter] = _proxy_spend_writer, + deployment_lookup: DeploymentLookup = _proxy_deployment, ) -> None: super().__init__(turn_off_message_logging=turn_off_message_logging, message_logging=message_logging) self.spend_event_producer = spend_event_producer self._spend_writer: Final = spend_writer + self._deployment_lookup: Final = deployment_lookup async def async_log_success_event( self, kwargs: ObjectMapping, response_obj: object, start_time: datetime, end_time: datetime @@ -330,24 +485,41 @@ class _ProxyDBLogger(CustomLogger): existing_metadata.get("standard_logging_guardrail_information"), ) - await self._spend_writer().update_database( - token=LiteLLMProxyRequestSetup.get_logged_api_key(user_api_key_dict), - response_cost=recovered_response_cost, - user_id=user_api_key_dict.user_id, - end_user_id=None if litellm.disable_end_user_cost_tracking else user_api_key_dict.end_user_id, - team_id=user_api_key_dict.team_id, - kwargs=( - request_data - if failure_snapshot_with_late_guardrails is None - else {**request_data, "standard_logging_object": failure_snapshot_with_late_guardrails} - ), - completion_response=original_exception, + await self._write_failure_spend_rows( + user_api_key_dict=user_api_key_dict, + original_exception=original_exception, start_time=actual_start_time, - end_time=datetime.now(), - org_id=user_api_key_dict.org_id, - project_id=user_api_key_dict.project_id, + spend_rows=_failure_spend_rows( + cast("Mapping[str, object]", request_data), # cast-ok: request dict, copied per row below + recovered_response_cost, + failure_snapshot_with_late_guardrails, + self._deployment_lookup, + ), ) + async def _write_failure_spend_rows( + self, + user_api_key_dict: UserAPIKeyAuth, + original_exception: Exception, + start_time: datetime, + spend_rows: Sequence[tuple[float, Mapping[str, object]]], + ) -> None: + """One spend row (and one key/team/user spend deduction) per ``(response_cost, kwargs)`` pair.""" + for row_cost, row_kwargs in spend_rows: + await self._spend_writer().update_database( + token=LiteLLMProxyRequestSetup.get_logged_api_key(user_api_key_dict), + response_cost=row_cost, + user_id=user_api_key_dict.user_id, + end_user_id=None if litellm.disable_end_user_cost_tracking else user_api_key_dict.end_user_id, + team_id=user_api_key_dict.team_id, + kwargs=dict(row_kwargs), + completion_response=original_exception, + start_time=start_time, + end_time=datetime.now(), + org_id=user_api_key_dict.org_id, + project_id=user_api_key_dict.project_id, + ) + async def _PROXY_track_cost_callback( self, kwargs, # kwargs to completion @@ -359,9 +531,13 @@ class _ProxyDBLogger(CustomLogger): increment_spend_counters, proxy_logging_obj, update_cache, - update_cache_read_keys, ) + accounting: Final = ( + _batch_accounting_for(_BATCH_CALLBACK_FIELDS.validate_python(kwargs).get("litellm_call_id")) + if _BATCH_ACCOUNTING.get() is not None + else None + ) verbose_proxy_logger.debug("INSIDE _PROXY_track_cost_callback") try: verbose_proxy_logger.debug( @@ -382,6 +558,8 @@ class _ProxyDBLogger(CustomLogger): ) _write_spend_metadata_to_kwargs(kwargs=kwargs, metadata=metadata) budget_reservation: Final = _get_budget_reservation_from_metadata(metadata=metadata) + if accounting is not None and (budget_reservation is not None or litellm.apply_search_free_tier): + accounting.write_started = True if ( isinstance(completion_response, LiteLLMBatch) and kwargs.get("call_type") == CallTypes.aretrieve_batch.value @@ -405,8 +583,21 @@ class _ProxyDBLogger(CustomLogger): key_alias: Final = cast(str | None, metadata.get("user_api_key_alias", None)) end_user_max_budget: Final = metadata.get("user_api_end_user_max_budget", None) sl_object: Final[StandardLoggingPayload | None] = kwargs.get("standard_logging_object", None) + raw_cost: Final = _str_keyed_fields( + sl_object if sl_object is not None else kwargs # pyright: ignore[reportUnknownArgumentType] # untyped success-callback payload + ).get("response_cost") + priced_cost: Final = raw_cost if isinstance(raw_cost, (int, float)) else None response_cost: Final = ( - sl_object.get("response_cost", None) if sl_object is not None else kwargs.get("response_cost", None) + await apply_search_free_tier( + kwargs=kwargs, # pyright: ignore[reportUnknownArgumentType] # untyped success-callback payload + sl_object=sl_object, # pyright: ignore[reportUnknownArgumentType] # payload carries untyped lists + response_cost=priced_cost, + completion_response=completion_response, + counter=proxy_logging_obj.internal_usage_cache.dual_cache.redis_cache, + now=datetime.now(timezone.utc), + ) + if litellm.apply_search_free_tier and sl_object is not None and priced_cost is not None + else priced_cost ) tags: Final = _get_request_tags_for_cost_tracking( sl_object=sl_object, @@ -454,12 +645,6 @@ class _ProxyDBLogger(CustomLogger): request_tags=tags, model_access_groups=model_access_groups, project_id=project_id, - update_cache_read_keys=update_cache_read_keys( - user_id=user_id, - end_user_id=end_user_id, - tags=tags, - response_cost=response_cost, - ), ) if not charged: return @@ -527,6 +712,8 @@ class _ProxyDBLogger(CustomLogger): f"Cost tracking failed for model={model}.\nDebug info - {cost_tracking_failure_debug_info}\nAdd custom pricing - https://docs.litellm.ai/docs/proxy/custom_pricing" ) except Exception as e: + if accounting is not None: + accounting.failed = True failing_model: Final = kwargs.get("model", "") failing_call_type: Final = kwargs.get("call_type", "") error_msg: Final = ( @@ -783,7 +970,6 @@ async def _update_database_and_spend_counters( request_tags: list[str] | None = None, model_access_groups: Sequence[str] | None = None, project_id: str | None = None, - update_cache_read_keys: Sequence[str] = (), ) -> bool: """The reservation is reconciled before the spend is persisted, from its own read. One spend counter batch then spans the database write and the counter update, so the post-call counters are read with a single MGET after the @@ -825,7 +1011,6 @@ async def _update_database_and_spend_counters( request_tags=request_tags, model_access_groups=model_access_groups, project_id=project_id, - update_cache_read_keys=update_cache_read_keys, ) @@ -846,12 +1031,17 @@ async def _update_database_and_spend_counters_in_batch( request_tags: list[str] | None, model_access_groups: Sequence[str] | None, project_id: str | None, - update_cache_read_keys: Sequence[str], ) -> bool: - from litellm.proxy.proxy_server import arm_update_cache_read - try: - charged: Final = await proxy_logging_obj.db_spend_update_writer.update_database( + writer: Final = proxy_logging_obj.db_spend_update_writer + accounting: Final = ( + _batch_accounting_for(_BATCH_CALLBACK_FIELDS.validate_python(kwargs).get("litellm_call_id")) + if _BATCH_ACCOUNTING.get() is not None + else None + ) + if accounting is not None: + accounting.write_started = True + charged: Final = await writer.update_database( token=user_api_key, response_cost=response_cost, user_id=user_id, @@ -881,7 +1071,6 @@ async def _update_database_and_spend_counters_in_batch( await _release_budget_reservation(budget_reservation=budget_reservation) return False - await arm_update_cache_read(update_cache_read_keys) try: await increment_spend_counters( token=user_api_key, diff --git a/litellm/proxy/hooks/search_free_tier.py b/litellm/proxy/hooks/search_free_tier.py new file mode 100644 index 00000000000..34f4d50550a --- /dev/null +++ b/litellm/proxy/hooks/search_free_tier.py @@ -0,0 +1,125 @@ +from collections.abc import MutableMapping +from datetime import datetime +from types import MappingProxyType +from typing import Final, Protocol + +from pydantic import BaseModel, ConfigDict, TypeAdapter, ValidationError + +from litellm._internal_context import with_service_target +from litellm._logging import verbose_proxy_logger +from litellm.litellm_core_utils.duration_parser import get_next_standardized_reset_time +from litellm.litellm_core_utils.llm_cost_calc.utils import get_web_search_requests_from_usage +from litellm.llms.gemini.cost_calculator import cost_per_web_search_request +from litellm.types.utils import CostBreakdown, ModelInfo, SearchFreeRequests, StandardLoggingPayload, Usage + +_PERIOD_DURATION: Final = MappingProxyType({"day": "1d", "month": "1mo"}) +_PERIOD_STAMP: Final = MappingProxyType({"day": "%Y-%m-%d", "month": "%Y-%m"}) +_TTL_GRACE_SECONDS: Final = 3600 +_COUNTED_KWARG: Final = "search_free_tier_counted" +_COST_BREAKDOWN: Final = TypeAdapter(CostBreakdown) + + +class SharedCounter(Protocol): + async def async_increment(self, key: str, value: float, ttl: int | None = None) -> float: ... + + +class _UsageCarrier(BaseModel): + model_config = ConfigDict(frozen=True, extra="ignore", from_attributes=True) + + usage: Usage | None = None + + +def freed_units(allowance: int, units: int, total_after: int) -> int: + """Units of this request that landed under the allowance, given the shared total after they were added.""" + return max(0, min(units, allowance - (total_after - units))) + + +def search_free_tier_key(provider: str, allowance: SearchFreeRequests, now: datetime) -> str: + period_stamp: Final = now.strftime(_PERIOD_STAMP[allowance["period"]]) + return f"litellm:search_free_tier:{provider}:{allowance['shared_group']}:{period_stamp}" + + +def search_free_tier_ttl(allowance: SearchFreeRequests, now: datetime) -> int: + reset: Final = get_next_standardized_reset_time(_PERIOD_DURATION[allowance["period"]], now, "UTC") + return int((reset - now).total_seconds()) + _TTL_GRACE_SECONDS + + +def _usage_of(completion_response: object) -> Usage | None: + try: + return _UsageCarrier.model_validate(completion_response, from_attributes=True).usage + except ValidationError: + return None + + +def _grounding_queries(usage: Usage) -> int: + details: Final = usage.prompt_tokens_details + from_details: Final = getattr(details, "web_search_requests", None) if details is not None else None + return from_details or get_web_search_requests_from_usage(usage) or 0 + + +def _billable_units(usage: Usage, model_info: ModelInfo) -> int: + queries: Final = _grounding_queries(usage) + if queries == 0: + return 0 + return queries if model_info.get("web_search_billing_unit") == "per_query" else 1 + + +def _record_freed_cost( + kwargs: MutableMapping[str, object], # mutable-ok: writes the reduced cost where the spend row reads it + sl_object: StandardLoggingPayload, + original_cost: float, + freed_cost: float, +) -> float: + reduced_cost: Final = original_cost - freed_cost + breakdown: Final = sl_object["cost_breakdown"] or CostBreakdown(total_cost=original_cost) + sl_object["cost_breakdown"] = _COST_BREAKDOWN.validate_python( # rebind-ok: the spend row reads this payload + { + **breakdown, + "total_cost": reduced_cost, + "original_cost": breakdown.get("original_cost", original_cost), + "discount_amount": breakdown.get("discount_amount", 0.0) + freed_cost, + } + ) + sl_object["response_cost"] = reduced_cost # rebind-ok: the spend row reads this payload + kwargs["response_cost"] = reduced_cost # rebind-ok: the spend row reads kwargs["response_cost"] + return reduced_cost + + +@with_service_target("search_free_tier") +async def apply_search_free_tier( + kwargs: MutableMapping[str, object], # mutable-ok: writes the reduced cost where the spend row reads it + sl_object: StandardLoggingPayload, + response_cost: float, + completion_response: object, + counter: SharedCounter | None, + now: datetime, +) -> float: + """Zero the grounding queries that landed under the model's shared free allowance, everything else is unchanged.""" + model_info: Final = sl_object["model_map_information"]["model_map_value"] + allowance: Final = model_info.get("search_free_requests") if model_info is not None else None + usage: Final = _usage_of(completion_response) + if model_info is None or allowance is None or usage is None or sl_object["cache_hit"]: + return response_cost + units: Final = _billable_units(usage, model_info) + if units == 0 or kwargs.get(_COUNTED_KWARG): + return response_cost + if counter is None: + verbose_proxy_logger.warning( + "apply_search_free_tier is on but the proxy has no Redis, grounding is billed at full price" + ) + return response_cost + provider: Final = sl_object["custom_llm_provider"] or model_info["litellm_provider"] + key: Final = search_free_tier_key(provider, allowance, now) + try: + total_after: Final = await counter.async_increment(key, units, ttl=search_free_tier_ttl(allowance, now)) + except Exception: # noqa: BLE001 # any counter failure means full price, never a lost spend row + verbose_proxy_logger.warning( + "search free tier counter %s is unavailable, grounding is billed at full price", key + ) + return response_cost + kwargs[_COUNTED_KWARG] = True # rebind-ok: the proxy runs this callback twice per request, count it once + freed: Final = freed_units(allowance["count"], units, int(total_after)) + if freed == 0: + return response_cost + freed_cost: Final = min(response_cost, cost_per_web_search_request(usage, model_info) * freed / units) + return _record_freed_cost(kwargs, sl_object, response_cost, freed_cost) diff --git a/litellm/proxy/litellm_pre_call_utils.py b/litellm/proxy/litellm_pre_call_utils.py index 67a1d640103..09f53cecb72 100644 --- a/litellm/proxy/litellm_pre_call_utils.py +++ b/litellm/proxy/litellm_pre_call_utils.py @@ -5,7 +5,8 @@ import json import re import time from collections import OrderedDict -from collections.abc import Mapping, MutableMapping, Sequence +from collections.abc import Iterable, Mapping, MutableMapping, Sequence +from dataclasses import dataclass from datetime import datetime from types import MappingProxyType from typing import ( @@ -17,7 +18,7 @@ from typing import ( cast, # noqa: TID251 # narrows untyped deployment and credential payloads ) -from fastapi import HTTPException, Request +from fastapi import HTTPException, Request, status from pydantic import TypeAdapter from pydantic import ValidationError as PydanticValidationError from starlette.datastructures import Headers @@ -27,6 +28,8 @@ from litellm._logging import verbose_logger, verbose_proxy_logger from litellm._service_logger import ServiceLogging from litellm._uuid import uuid from litellm.constants import ( + BAGGAGE_MAPPED_TAGS_METADATA_KEY, + BILLED_RETRY_ATTEMPT_METADATA_KEY, CALLER_SESSION_ID_METADATA_KEY, CLIENT_OUTPUT_CEILING_METADATA_KEY, CONSUMED_REQUEST_TAGS_METADATA_KEY, @@ -80,6 +83,7 @@ from litellm.proxy.common_utils.callback_utils import ( ) from litellm.proxy.common_utils.http_parsing_utils import ( # noqa: F401 # legacy module exports _safe_get_request_headers, # pyright: ignore[reportPrivateUsage,reportUnusedImport] # backwards-compatible package export + detach_request_parsed_body, safe_get_request_headers, ) from litellm.proxy.spend_tracking.carried_budget_state import carried_budget_metadata @@ -90,6 +94,7 @@ _SPECIAL_HEADERS_CACHE: Final = frozenset(str(v.value).lower() for v in SpecialH _REDACTED_HEADER_VALUE: Final = "***REDACTED***" _DECODED_JSON: Final = TypeAdapter(object) +_OBJECT_LIST_ADAPTER: Final = TypeAdapter(list[object]) _CREDENTIAL_HEADER_NAMES: Final = SpecialHeaders.litellm_credential_header_names() | frozenset( {"cookie", "proxy-authorization"} ) @@ -209,8 +214,19 @@ def _drop_client_caller_session(request_body: Mapping[str, object]) -> None: metadata.pop(CALLER_SESSION_ID_METADATA_KEY, None) +_PROXY_SET_METADATA_KEYS: Final = frozenset({CALLER_SESSION_ID_METADATA_KEY, BAGGAGE_MAPPED_TAGS_METADATA_KEY}) +_METADATA_TAGS_ADAPTER: Final = TypeAdapter(tuple[object, ...]) + + def _requester_metadata_snapshot(metadata: Mapping[str, object]) -> Mapping[str, object]: - return copy.deepcopy({key: value for key, value in metadata.items() if key != CALLER_SESSION_ID_METADATA_KEY}) + requester: Final = {key: value for key, value in metadata.items() if key not in _PROXY_SET_METADATA_KEYS} + stamp: Final = metadata.get(BAGGAGE_MAPPED_TAGS_METADATA_KEY) + tags: Final = requester.get("tags") + if not isinstance(stamp, BaggageMappedTagsStamp) or not isinstance(tags, list): + return copy.deepcopy(requester) + sent_tags: Final = [tag for tag in _METADATA_TAGS_ADAPTER.validate_python(tags) if tag not in stamp.tags] + without_tags: Final = {key: value for key, value in requester.items() if key != "tags"} + return copy.deepcopy({**without_tags, "tags": sent_tags} if sent_tags else without_tags) def _stampable_key_hash(user_api_key_dict: UserAPIKeyAuth) -> str | None: @@ -254,7 +270,7 @@ from litellm.router import Router from litellm.secret_managers.main import get_secret_bool from litellm.types.litellm_params import AGENTIC_LOOP_KWARG_NAMES from litellm.types.llms.anthropic import ANTHROPIC_API_HEADERS -from litellm.types.router import holds_api_key_secret_reference +from litellm.types.router import BaggageMappedTagsStamp, holds_api_key_secret_reference from litellm.types.services import ServiceTypes from litellm.types.utils import ( API_KEY_SECRET_REFERENCE_REJECTION, @@ -285,8 +301,11 @@ if TYPE_CHECKING: from opentelemetry.trace import Span as OtelSpan from litellm.integrations.otel.model.destination import OtelDestination + from litellm.models.tag import LiteLLM_TagTable + from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache from litellm.proxy.policy_engine.attachment_registry import AttachmentRegistry from litellm.proxy.proxy_server import ProxyConfig as _ProxyConfig + from litellm.proxy.utils import PrismaClient from litellm.types.proxy.policy_engine import Policy, PolicyMatchContext ProxyConfig = _ProxyConfig @@ -408,6 +427,7 @@ _UNTRUSTED_METADATA_CONTROL_FIELDS: Final = ( CONSUMED_REQUEST_TAGS_METADATA_KEY, ROUTING_REQUEST_TAGS_METADATA_KEY, INTERNAL_CALL_ORIGIN_METADATA_KEY, + BILLED_RETRY_ATTEMPT_METADATA_KEY, MANAGED_BACKGROUND_RESPONSE_METADATA_KEY, "standard_logging_object", "litellm_roi_estimator", @@ -434,8 +454,9 @@ _ALLOW_CLIENT_MESSAGE_REDACTION_OPT_OUT_METADATA_KEY: Final = "allow_client_mess # ``litellm.model_cost`` map. Both effects belong to deployment configuration, # not to user-supplied request bodies, so the proxy strips them before they # reach the call path. Built from the Pydantic model so newly-added pricing -# fields are covered automatically. -_CLIENT_PRICING_CONTROL_FIELDS: Final = frozenset(CustomPricingLiteLLMParams.model_fields.keys()) +# fields are covered automatically. ``base_model`` selects which cost-map entry +# prices the row, so a caller naming a cheaper model lowers their own spend. +_CLIENT_PRICING_CONTROL_FIELDS: Final = frozenset(CustomPricingLiteLLMParams.model_fields.keys()) | {"base_model"} # ``model_info`` carries the same pricing fields when read by # ``use_custom_pricing_for_model``; strip from metadata for the same reason. # ``standard_logging_guardrail_information`` is proxy-written telemetry summed @@ -449,6 +470,7 @@ _ROUTER_RESERVED_METADATA_FIELDS: Final = frozenset( { "attempted_fallbacks", "original_model_group", + "previous_models", "request_retry_count", CLIENT_OUTPUT_CEILING_METADATA_KEY, ROUTER_USAGE_COUNTED_TOKENS_METADATA_KEY, @@ -537,6 +559,39 @@ def _normalized_metadata_object(field: str, value: object) -> Mapping[str, objec raise _invalid_metadata_type_error(field=field, value=value) +def _serves_through_db_outage() -> bool: + from litellm.proxy.db.exception_handler import PrismaDBExceptionHandler + + return PrismaDBExceptionHandler.should_allow_request_on_db_unavailable() + + +def _tag_budgets_unavailable(message: str) -> ProxyException: + return ProxyException( + message=message, type=ProxyErrorTypes.no_db_connection, param=None, code=status.HTTP_503_SERVICE_UNAVAILABLE + ) + + +async def _unbudgeted_mapped_tag( + budgeted_tags: tuple[str, ...], prisma_client: "PrismaClient | None", user_api_key_cache: "UserApiKeyCache" +) -> str | ProxyException | None: + from litellm.proxy.auth.auth_checks import read_tag_objects_batch + + if prisma_client is None: + return _tag_budgets_unavailable("Baggage tag mappings require a database to check budgeted tags") + tag_objects: Final = await read_tag_objects_batch( + tag_names=budgeted_tags, prisma_client=prisma_client, user_api_key_cache=user_api_key_cache + ) + if isinstance(tag_objects, Exception): + return _tag_budgets_unavailable("Baggage tag mappings could not read tag budgets from the database") + return next((tag for tag in budgeted_tags if not _has_tag_budget(tag_objects.get(tag))), None) + + +def _has_tag_budget(tag: "LiteLLM_TagTable | None") -> bool: + if tag is None or tag.litellm_budget_table is None: + return False + return tag.litellm_budget_table.max_budget is not None + + def _normalized_metadata_slot( request_data: MutableMapping[str, object], metadata_variable_name: str ) -> dict[str, object]: @@ -554,6 +609,43 @@ def _normalized_metadata_slot( return normalized +def _metadata_object_or_error(field: str, value: object) -> Mapping[str, object] | ProxyException: + if value is None: + return {} + try: + return dict(_normalized_metadata_object(field, value)) + except ProxyException as invalid_type: + return invalid_type + + +@dataclass(frozen=True, slots=True) +class _BaggageClientBody: + body: dict[str, object] # mutable-ok: the client's cached body, which the base tag merges write into + + +def _detach_auth_metadata_from_client_body( + request: Request, + request_data: MutableMapping[str, object], # mutable-ok: auth's own copy takes the normalized metadata objects +) -> None: + client_body: Final = detach_request_parsed_body(request, request_data) + request.state.litellm_baggage_client_body = _BaggageClientBody(client_body) # rebind-ok: mirror tag merges + slots: Final = tuple( + (field, _metadata_object_or_error(field, request_data[field])) + for field in ("metadata", "litellm_metadata") + if field in request_data + ) + for field, normalized in slots: + request_data[field] = {} if isinstance(normalized, ProxyException) else normalized # rebind-ok: auth's copy + + +def _metadata_string_tags(metadata_objects: Iterable[Mapping[str, object]]) -> tuple[str, ...]: + tag_lists: Final = (metadata.get("tags") for metadata in metadata_objects) + tags: Final = itertools.chain.from_iterable( + _OBJECT_LIST_ADAPTER.validate_python(tag_list) for tag_list in tag_lists if isinstance(tag_list, list) + ) + return tuple(tag for tag in tags if isinstance(tag, str)) + + def _strip_untrusted_request_header_controls( headers: Any, *, @@ -1128,10 +1220,38 @@ def get_dynamic_logging_metadata( return callback_settings_obj +def _callback_settings_fields(callback_settings_obj: TeamCallbackMetadata) -> Mapping[str, object]: + callback_vars: Final = callback_settings_obj.callback_vars + return { + "success_callback": callback_settings_obj.success_callback, + "failure_callback": callback_settings_obj.failure_callback, + **({**callback_vars, TRUSTED_CALLBACK_VARS_FIELD: callback_vars} if callback_vars is not None else {}), + } + + +def key_and_team_logging_fields(user_api_key_dict: UserAPIKeyAuth, proxy_config: ProxyConfig) -> Mapping[str, object]: + callback_settings_obj: Final = get_dynamic_logging_metadata( + user_api_key_dict=user_api_key_dict, proxy_config=proxy_config + ) + disabled_callbacks: Final = (user_api_key_dict.metadata or {}).get("litellm_disabled_callbacks") + return MappingProxyType( + { + **(_callback_settings_fields(callback_settings_obj) if callback_settings_obj is not None else {}), + **( + {"litellm_disabled_callbacks": disabled_callbacks} + if disabled_callbacks and isinstance(disabled_callbacks, list) + else {} + ), + } + ) + + _get_dynamic_logging_metadata: Final = get_dynamic_logging_metadata _TENANT_OTEL_PARAMS: Final = TypeAdapter(StandardCallbackDynamicParams) +_STRING_TAGS_ADAPTER: Final = TypeAdapter(tuple[str, ...]) +_CLIENT_TAGS_ADAPTER: Final = TypeAdapter(tuple[object, ...]) def _tenant_otel_params(callback_vars: Mapping[str, str]) -> StandardCallbackDynamicParams: @@ -2045,7 +2165,7 @@ class LiteLLMProxyRequestSetup: @staticmethod def pre_seed_litellm_metadata_for_route( - request_data: dict, + request_data: MutableMapping[str, object], # mutable-ok: seed shared request metadata before admission route: str, ) -> None: """Pre-seed ``litellm_metadata`` for routes that track tags there. @@ -2064,6 +2184,87 @@ class LiteLLMProxyRequestSetup: if any(metadata_route in route for metadata_route in LITELLM_METADATA_ROUTES): request_data.setdefault("litellm_metadata", {}) + @staticmethod + def pre_auth_tag_merge_targets( + request: Request | None, + request_data: dict[str, object], # mutable-ok: auth's request body, which the tag merges write into + ) -> tuple[dict[str, object], ...]: # mutable-ok: every body the base tag merges write into + client_body: Final[object] = getattr(getattr(request, "state", None), "litellm_baggage_client_body", None) + if not isinstance(client_body, _BaggageClientBody) or client_body.body is request_data: + return (request_data,) + return (request_data, client_body.body) + + @staticmethod + async def apply_baggage_tag_mappings_pre_auth( + request: Request, + request_data: MutableMapping[str, object], # mutable-ok: enrich the shared request before budget admission + general_settings: Mapping[str, object], + prisma_client: "PrismaClient | None", + user_api_key_cache: "UserApiKeyCache", + ) -> None: + """Resolve configured baggage tags before the existing tag-budget gate.""" + from litellm.proxy.common_utils.request_tag_mappings import ( + REQUEST_TAG_MAPPINGS_ADAPTER, + mapping_rejection, + resolve_baggage_tag_mappings, + ) + + raw_rules: Final = general_settings.get("request_tag_mappings") + if not isinstance(raw_rules, list) or not raw_rules: + return + rules: Final = REQUEST_TAG_MAPPINGS_ADAPTER.validate_python(raw_rules) + header: Final = ",".join(request.headers.getlist("baggage")) + try: + mapped: Final = resolve_baggage_tag_mappings(header, rules) + except ProxyException: + _detach_auth_metadata_from_client_body(request, request_data) + raise + if not mapped: + return + client_metadata: Final[object] = request_data.get("metadata") + _detach_auth_metadata_from_client_body(request, request_data) + budgeted_tags: Final = tuple(tag for tag, require_budget in mapped if require_budget) + unbudgeted_tag: Final = ( + await _unbudgeted_mapped_tag(budgeted_tags, prisma_client, user_api_key_cache) if budgeted_tags else None + ) + if isinstance(unbudgeted_tag, ProxyException) and not _serves_through_db_outage(): + raise unbudgeted_tag + if isinstance(unbudgeted_tag, str): + raise mapping_rejection(f"Mapped tag {unbudgeted_tag} requires an existing tag budget") + client_has_tags: Final = (isinstance(client_metadata, dict) and "tags" in client_metadata) or ( + get_metadata_variable_name_from_kwargs(request_data) == "metadata" + and any(member.strip() for member in request.headers.get("x-litellm-tags", "").split(",")) + ) + mapped_tags: Final = tuple(tag for tag, _ in mapped) + request.state.litellm_baggage_client_metadata_tags = client_has_tags # rebind-ok: request input flag + request.state.litellm_baggage_mapped_tags = mapped_tags # rebind-ok: per-request immutable mapped tags + LiteLLMProxyRequestSetup.apply_authenticated_baggage_tags(request, request_data) + + @staticmethod + def apply_authenticated_baggage_tags( + request: Request, + request_data: MutableMapping[str, object], # mutable-ok: restore authenticated tags in downstream metadata + metadata_key: str | None = None, + ) -> None: + request_state: Final[object] = getattr(request, "state", None) + raw_tags: Final[object] = getattr(request_state, "litellm_baggage_mapped_tags", None) + if not isinstance(raw_tags, tuple) or not raw_tags: + return + tags: Final = _STRING_TAGS_ADAPTER.validate_python(raw_tags) + slot: Final = metadata_key if metadata_key is not None else get_metadata_variable_name_from_kwargs(request_data) + metadata: Final = _normalized_metadata_slot(request_data, slot) + existing: Final = metadata.get("tags") + if existing and not isinstance(existing, list): + return + existing_tags: Final = _CLIENT_TAGS_ADAPTER.validate_python(existing) if isinstance(existing, list) else () + prior_stamp: Final = metadata.get(BAGGAGE_MAPPED_TAGS_METADATA_KEY) + prior_mapped: Final = prior_stamp.tags if isinstance(prior_stamp, BaggageMappedTagsStamp) else () + sent_tags: Final = tuple(tag for tag in existing_tags if tag not in prior_mapped) + metadata["tags"] = [*existing_tags, *(tag for tag in tags if tag not in existing_tags)] + metadata[BAGGAGE_MAPPED_TAGS_METADATA_KEY] = BaggageMappedTagsStamp( + tags=tuple(tag for tag in tags if tag not in sent_tags) + ) + @staticmethod def apply_key_tags_pre_auth( request_data: dict, @@ -2221,12 +2422,16 @@ async def add_litellm_data_to_request( data.pop(_internal_key, None) _reject_url_valued_destinations(data) _raw_metadata_by_field: Final = { - _metadata_field: data.pop(_metadata_field) + _metadata_field: _DECODED_JSON.validate_python(data.pop(_metadata_field)) for _metadata_field in ("metadata", "litellm_metadata") if data.get(_metadata_field) is not None } - for _metadata_field, _raw_metadata in _raw_metadata_by_field.items(): - data[_metadata_field] = _normalized_metadata_object(_metadata_field, _raw_metadata) + _normalized_metadata_by_field: Final = { + _metadata_field: _normalized_metadata_object(_metadata_field, _raw_metadata) + for _metadata_field, _raw_metadata in _raw_metadata_by_field.items() + } + data.update(_normalized_metadata_by_field) + _client_sent_metadata_tags: Final = _metadata_string_tags(_normalized_metadata_by_field.values()) # Strip spoofable auth metadata from user-supplied metadata dict _user_metadata = data.get("metadata") if isinstance(_user_metadata, dict): @@ -2654,38 +2859,17 @@ async def add_litellm_data_to_request( tags_to_add=_caller_body_tags, ) - # caller_tags: exactly what this request itself supplied (x-litellm-tags header, - # body "tags", or body "metadata.tags" on litellm_metadata routes), never - # anything from key/team/project metadata. Read directly from the header and - # body values here, the same way inherited_tags above is read directly from - # key/team/project metadata -- neither is derived by inspecting the shared - # "tags" list, which a pre-auth pass (apply_client_tag_policy_pre_auth) may - # have already merged caller header tags into before this function runs. + # caller_tags: the tags the request's headers and body carry (x-litellm-tags, body "tags", and body + # "metadata.tags" / "litellm_metadata.tags" read before the mapped tags are added below), + # never derived from the shared "tags" list. data[_metadata_variable_name]["caller_tags"] = tuple( # rebind-ok: matches file idiom - dict.fromkeys((*(tags or ()), *(_caller_body_tags or ()))) + dict.fromkeys((*(tags or ()), *_client_sent_metadata_tags)) + ) + LiteLLMProxyRequestSetup.apply_authenticated_baggage_tags( + request=request, request_data=data, metadata_key=_metadata_variable_name ) - # Team Callbacks controls - callback_settings_obj: Final = get_dynamic_logging_metadata( - user_api_key_dict=user_api_key_dict, proxy_config=proxy_config - ) - if callback_settings_obj is not None: - data["success_callback"] = callback_settings_obj.success_callback - data["failure_callback"] = callback_settings_obj.failure_callback - - if callback_settings_obj.callback_vars is not None: - # unpack callback_vars in data - for k, v in callback_settings_obj.callback_vars.items(): - data[k] = v - # Callbacks that must not honour request-supplied credentials read this - # proxy-owned field instead of the raw request kwargs. - data[TRUSTED_CALLBACK_VARS_FIELD] = callback_settings_obj.callback_vars - - # Add disabled callbacks from key metadata - if user_api_key_dict.metadata and "litellm_disabled_callbacks" in user_api_key_dict.metadata: - disabled_callbacks: Final = user_api_key_dict.metadata["litellm_disabled_callbacks"] - if disabled_callbacks and isinstance(disabled_callbacks, list): - data["litellm_disabled_callbacks"] = disabled_callbacks + data.update(key_and_team_logging_fields(user_api_key_dict=user_api_key_dict, proxy_config=proxy_config)) # Guardrails from key/team metadata and policy engine await move_guardrails_to_metadata( @@ -3145,12 +3329,12 @@ async def _resolve_user_provider_credentials_for_request( from litellm.proxy.proxy_server import prisma_client, user_api_key_cache from litellm.types.proxy.litellm_pre_call_utils import RedactedDict - from .credential_endpoints.user_provider_credentials import aget_user_provider_tokens + from .credential_endpoints.user_provider_credentials import aget_user_provider_credentials if prisma_client is None: return try: - tokens: Final = await aget_user_provider_tokens( + connections: Final = await aget_user_provider_credentials( prisma_client=prisma_client, cache=user_api_key_cache, user_id=user_id, @@ -3165,7 +3349,7 @@ async def _resolve_user_provider_credentials_for_request( secret_fields: Final = data.get("secret_fields") if not isinstance(secret_fields, dict): return - secret_fields["user_provider_credentials"] = RedactedDict(dict(tokens)) + secret_fields["user_provider_credentials"] = RedactedDict(dict(connections)) secret_fields["user_provider_credentials_user_id"] = user_id @@ -3958,6 +4142,16 @@ def _apply_resolved_guardrails_to_metadata( verbose_proxy_logger.debug("Policy engine: added guardrails to request metadata: %s", combined) +def _policy_match_tags(request_data: Mapping[str, object], metadata_variable_name: str) -> list[str] | None: + from litellm.proxy.common_utils.http_parsing_utils import get_tags_from_request_body + from litellm.router_strategy.tag_based_routing import without_baggage_mapped_tags + + tags: Final = without_baggage_mapped_tags( + get_tags_from_request_body(request_data), request_data.get(metadata_variable_name) + ) + return list(tags) if tags else None + + async def add_guardrails_from_policy_engine( data: dict, metadata_variable_name: str, @@ -3982,7 +4176,6 @@ async def add_guardrails_from_policy_engine( user_api_key_dict: The user's API key authentication info """ from litellm._logging import verbose_proxy_logger - from litellm.proxy.common_utils.http_parsing_utils import get_tags_from_request_body from litellm.proxy.policy_engine.policy_registry import get_policy_registry from litellm.types.proxy.policy_engine import PolicyMatchContext @@ -4000,7 +4193,7 @@ async def add_guardrails_from_policy_engine( return # Extract tags and build context - all_tags: Final = get_tags_from_request_body(data) or None + all_tags: Final = _policy_match_tags(data, metadata_variable_name) _team_alias: Final = user_api_key_dict.team_alias _key_alias: Final = user_api_key_dict.key_alias context: Final = PolicyMatchContext( diff --git a/litellm/proxy/management_endpoints/tag_management_endpoints.py b/litellm/proxy/management_endpoints/tag_management_endpoints.py index 9a1cf701142..c12a90ed6a2 100644 --- a/litellm/proxy/management_endpoints/tag_management_endpoints.py +++ b/litellm/proxy/management_endpoints/tag_management_endpoints.py @@ -275,6 +275,7 @@ async def new_tag( """ from litellm.proxy._types import CommonProxyErrors from litellm.proxy.proxy_server import ( + invalidate_spend_counter, litellm_proxy_admin_name, llm_router, prisma_client, @@ -316,6 +317,7 @@ async def new_tag( ) await _evict_tag_cache_keys((tag_cache_key(tag.name), tag_registry_cache_key())) + await invalidate_spend_counter(counter_key=f"spend:tag:{tag.name}") # Update models with new tag if tag.models: diff --git a/litellm/proxy/management_endpoints/team_endpoints.py b/litellm/proxy/management_endpoints/team_endpoints.py index 0595d23bd9a..517a05773c8 100644 --- a/litellm/proxy/management_endpoints/team_endpoints.py +++ b/litellm/proxy/management_endpoints/team_endpoints.py @@ -1848,7 +1848,7 @@ async def new_team( members_with_roles = complete_team_data.members_with_roles complete_team_data.members_with_roles = [] - complete_team_data_dict = complete_team_data.model_dump(exclude_none=True) + complete_team_data_dict: dict[str, object] = complete_team_data.model_dump(exclude_none=True) # Serialize router_settings to JSON (matching key creation pattern) router_settings_value: Final = data.router_settings @@ -2563,8 +2563,8 @@ async def update_team( # Drop server-owned metadata keys from caller input so they can only # be written by the same code path that creates the underlying rows. - if isinstance(updated_kv.get("metadata"), dict): - TeamMemberBudgetHandler.strip_system_managed_metadata_keys(updated_kv["metadata"]) + if isinstance(metadata_update := updated_kv.get("metadata"), dict): + TeamMemberBudgetHandler.strip_system_managed_metadata_keys(metadata_update) if "metadata" in updated_kv: stored_metadata: Final[Mapping[str, JsonValue] | None] = ( diff --git a/litellm/proxy/management_endpoints/ui_sso.py b/litellm/proxy/management_endpoints/ui_sso.py index 4cc849762aa..19bca3d2bf8 100644 --- a/litellm/proxy/management_endpoints/ui_sso.py +++ b/litellm/proxy/management_endpoints/ui_sso.py @@ -55,6 +55,7 @@ from litellm.constants import ( CLI_SSO_CLAIM_MAX_SCALAR_LENGTH, CLI_SSO_SESSION_CACHE_KEY_PREFIX, CLI_SSO_SESSION_TTL_SECONDS, + CP_RETURN_TO_COOKIE_PREFIX, LITELLM_CLI_SOURCE_IDENTIFIER, LITELLM_UI_SESSION_DURATION, MAX_SPENDLOG_ROWS_TO_QUERY, @@ -2285,9 +2286,7 @@ async def auth_callback(request: Request, state: str | None = None): sso_assertion=sso_assertion, ) - # Control-plane cross-origin: read return_to from cookie. - # Starlette's cookie_parser already handles RFC 2109 unquoting. - cp_return_to: Final[str | None] = request.cookies.get("litellm_cp_return_to") + cp_return_to: Final[str | None] = read_return_to_cookie(request) return await SSOAuthenticationHandler.get_redirect_response_from_openid( result=result, @@ -3090,10 +3089,11 @@ def _persist_return_to_cookie(response: Response, return_to: str | None, request safe: Final = _is_same_origin_return_path(return_to) or SSOAuthenticationHandler.validate_return_to(return_to) except HTTPException: return # a non-matching absolute return_to is ignored, never blocks sign-in - if safe: + sealed: Final = _seal_return_to(return_to) if safe else None + if sealed is not None: response.set_cookie( key="litellm_cp_return_to", - value=return_to, + value=sealed, max_age=600, httponly=True, samesite="lax", @@ -3101,6 +3101,45 @@ def _persist_return_to_cookie(response: Response, return_to: str | None, request ) +def _seal_return_to(return_to: str) -> str | None: + """``return_to`` sealed under the salt key as an opaque cookie value. The plaintext URL carries the + client's loopback ``redirect_uri`` (``http://127.0.0.1:/...`` for Codex or Claude Code), which + edge firewalls read as an SSRF probe and block before the proxy sees the request. None when there + is no salt or master key yet, so the login entrypoint still renders.""" + from litellm.proxy.common_utils.encrypt_decrypt_utils import encrypt_bearer_token + + try: + return encrypt_bearer_token(return_to, prefix=CP_RETURN_TO_COOKIE_PREFIX) + except ValueError: + return None + + +def _clear_rejected_return_to_cookie(response: Response, request: Request) -> None: + """Expire a ``litellm_cp_return_to`` that ``read_return_to_cookie`` rejected (plaintext, stale, or sealed + under another key) so the browser stops replaying it until it expires on its own.""" + if "litellm_cp_return_to" in request.cookies: + response.delete_cookie("litellm_cp_return_to") + + +def _dashboard_redirect_response(request: Request, jwt_token: str, litellm_dashboard_ui: str) -> RedirectResponse: + """The post-SSO dashboard landing, used when there is no honored ``return_to``. Sets the session + cookie and expires a ``litellm_cp_return_to`` the reader rejected.""" + verbose_proxy_logger.info("Redirecting to %s", litellm_dashboard_ui) + redirect_response: Final = RedirectResponse(url=litellm_dashboard_ui, status_code=303) + set_session_token_cookie(redirect_response, request, jwt_token) + _clear_rejected_return_to_cookie(redirect_response, request) + return redirect_response + + +def read_return_to_cookie(request: Request) -> str | None: + """The ``return_to`` this proxy sealed into ``litellm_cp_return_to``, or None when the cookie is + missing, was not sealed here, or was tampered with.""" + from litellm.proxy.common_utils.encrypt_decrypt_utils import decrypt_bearer_token + + sealed: Final = request.cookies.get("litellm_cp_return_to") + return None if sealed is None else decrypt_bearer_token(sealed, prefix=CP_RETURN_TO_COOKIE_PREFIX) + + def _is_blank_sso_user_id(user_id: object) -> bool: return isinstance(user_id, str) and not user_id.strip() @@ -3976,10 +4015,7 @@ class SSOAuthenticationHandler: if user_id is not None and isinstance(user_id, str): litellm_dashboard_ui += "?login=success" - verbose_proxy_logger.info("Redirecting to %s", litellm_dashboard_ui) - redirect_response: Final = RedirectResponse(url=litellm_dashboard_ui, status_code=303) - set_session_token_cookie(redirect_response, request, jwt_token) - return redirect_response + return _dashboard_redirect_response(request, jwt_token, litellm_dashboard_ui) @staticmethod @with_service_target(SSO_SESSIONS_TARGET) diff --git a/litellm/proxy/management_endpoints/workflow_management_endpoints.py b/litellm/proxy/management_endpoints/workflow_management_endpoints.py index 890a344dfe0..649941bc233 100644 --- a/litellm/proxy/management_endpoints/workflow_management_endpoints.py +++ b/litellm/proxy/management_endpoints/workflow_management_endpoints.py @@ -147,6 +147,34 @@ class _MessageCreateData(TypedDict, total=False): session_id: str +class _EventTable(Protocol): + async def create(self, *, data: _EventCreateData) -> object: ... + + +class _RunTable(Protocol): + async def update(self, *, where: Mapping[str, str], data: Mapping[str, str]) -> object: ... + + +class _WorkflowTx(Protocol): + @property + def litellm_workflowevent(self) -> _EventTable: ... + + @property + def litellm_workflowrun(self) -> _RunTable: ... + + +async def _append_event_in_tx( + tx: _WorkflowTx, run_id: str, event_data: _EventCreateData, new_status: str | None +) -> object: + event: Final = await tx.litellm_workflowevent.create(data=event_data) + if new_status: + await tx.litellm_workflowrun.update( + where={"run_id": run_id}, + data={"status": new_status}, + ) + return event + + # --------------------------------------------------------------------------- # Helpers # --------------------------------------------------------------------------- @@ -387,12 +415,7 @@ async def append_workflow_event( event_data["data"] = _json(data.data) async with prisma_client.db.tx() as tx: - event: object = await tx.litellm_workflowevent.create(data=event_data) - if new_status: - await tx.litellm_workflowrun.update( - where={"run_id": run_id}, - data={"status": new_status}, - ) + event: object = await _append_event_in_tx(tx, run_id, event_data, new_status) return event diff --git a/litellm/proxy/openai_files_endpoints/files_endpoints.py b/litellm/proxy/openai_files_endpoints/files_endpoints.py index bdc71908c7c..8823f01d781 100644 --- a/litellm/proxy/openai_files_endpoints/files_endpoints.py +++ b/litellm/proxy/openai_files_endpoints/files_endpoints.py @@ -1102,14 +1102,10 @@ async def get_file_content( } ) else: - # A raw cloud-storage URI (s3://, gs://) supplied here would skip the - # managed-file owner/team check that only runs for unified ids, letting - # a caller read another tenant's object by its key. Such objects are only - # reachable through their managed unified id. - if is_managed_cloud_storage_uri(file_id): + if is_managed_cloud_storage_uri(file_id) and user_api_key_dict.user_role != LitellmUserRoles.PROXY_ADMIN: raise HTTPException( - status_code=400, - detail="Raw cloud storage file ids cannot be retrieved directly. Use the LiteLLM managed file id returned when the file was created.", + status_code=403, + detail="Raw cloud storage file ids can only be retrieved by a proxy admin key. Use the LiteLLM managed file id returned when the file was created.", ) # Check for model-based credential routing ( diff --git a/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py b/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py index f2605a8ec6f..16fbd1de376 100644 --- a/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py +++ b/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py @@ -222,7 +222,12 @@ async def _json_request_body(request: Request) -> Mapping[str, object]: return await request.json() -def get_passthrough_router_request_metadata(user_api_key_dict: UserAPIKeyAuth) -> Mapping[str, object]: +_METADATA_ADAPTER: Final = TypeAdapter(Mapping[str, object]) + + +def get_passthrough_router_request_metadata( + user_api_key_dict: UserAPIKeyAuth, request: Request | None = None +) -> Mapping[str, object]: """ Build the request metadata carrying key-level spend attribution and the pre-call budget reservation for a router-model passthrough request. @@ -243,13 +248,17 @@ def get_passthrough_router_request_metadata(user_api_key_dict: UserAPIKeyAuth) - """ from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup - request_data: Final = {"litellm_metadata": {}} + request_data: Final[dict[str, object]] = { # mutable-ok: legacy enrichment writes this wrapper + "litellm_metadata": {} + } LiteLLMProxyRequestSetup.add_user_api_key_auth_to_request_metadata( data=request_data, user_api_key_dict=user_api_key_dict, _metadata_variable_name="litellm_metadata", ) - return request_data["litellm_metadata"] + if request is not None: + LiteLLMProxyRequestSetup.apply_authenticated_baggage_tags(request, request_data) + return _METADATA_ADAPTER.validate_python(request_data["litellm_metadata"]) async def llm_passthrough_factory_proxy_route( @@ -549,7 +558,7 @@ async def vllm_proxy_route( params=None, headers=None, cookies=None, - litellm_metadata=get_passthrough_router_request_metadata(user_api_key_dict), + litellm_metadata=get_passthrough_router_request_metadata(user_api_key_dict, request), ), ) @@ -1450,7 +1459,6 @@ async def bedrock_proxy_route( """ create_request_copy(request) - aws_region_name: Final = get_secret_str(secret_name="AWS_REGION_NAME") if not _is_bedrock_agent_runtime_route(endpoint=endpoint): return await bedrock_llm_proxy_route( endpoint=endpoint, @@ -1465,6 +1473,10 @@ async def bedrock_proxy_route( detail="bedrock-agent-runtime pass-through is disabled on this proxy.", ) + from litellm.llms.bedrock.base_aws_llm import run_aws_signing, sign_aws_json_post + from litellm.llms.bedrock.chat import BedrockConverseLLM + + aws_region_name: Final = await run_aws_signing(get_secret_str, secret_name="AWS_REGION_NAME") base_target_url: Final = f"https://bedrock-agent-runtime.{aws_region_name}.{get_aws_dns_suffix(aws_region_name)}" encoded_endpoint = httpx.URL(endpoint).path @@ -1479,10 +1491,6 @@ async def bedrock_proxy_route( path=HttpPassThroughEndpointHelpers.join_base_and_endpoint_path(base_url, encoded_endpoint) ) - # Add or update query parameters - from litellm.llms.bedrock.base_aws_llm import run_aws_signing, sign_aws_json_post - from litellm.llms.bedrock.chat import BedrockConverseLLM - bedrock_llm: Final = BedrockConverseLLM() # Assuming the body contains JSON data, parse it try: @@ -2229,7 +2237,7 @@ async def _relay_router_model( params=None, headers=None, cookies=None, - litellm_metadata=get_passthrough_router_request_metadata(user_api_key_dict), + litellm_metadata=get_passthrough_router_request_metadata(user_api_key_dict, request), ) except httpx.HTTPStatusError as upstream_error: return await _relay_upstream_response(upstream_error.response) diff --git a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py index 311dab058a4..fe7ac30e434 100644 --- a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py +++ b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py @@ -2021,6 +2021,9 @@ def _apply_key_team_project_controls( ) +_METADATA_ADAPTER: Final = TypeAdapter(dict[str, object]) + + def _update_metadata_with_tags_in_header(request: Request, metadata: dict) -> dict: """ If tags are in the request headers, add them to the metadata @@ -2046,7 +2049,12 @@ def _update_metadata_with_tags_in_header(request: Request, metadata: dict) -> di tags_to_add=tags_to_add, ) - return metadata + restored_metadata: Final = _METADATA_ADAPTER.validate_python(metadata) + request_data: Final[dict[str, object]] = { # mutable-ok: legacy enrichment writes this wrapper + "metadata": restored_metadata + } + LiteLLMProxyRequestSetup.apply_authenticated_baggage_tags(request, request_data) + return restored_metadata class _PassThroughRequestEnvelope(TypedDict, total=False): diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py index 36b16895e12..2f1f460fc8e 100644 --- a/litellm/proxy/proxy_server.py +++ b/litellm/proxy/proxy_server.py @@ -146,7 +146,6 @@ from litellm.proxy._types import ( TransformRequestBody, UserAPIKeyAuth, ) -from litellm.proxy.common_utils.cache_pydantic_utils import CacheCodec from litellm.proxy.common_utils.callback_utils import ( is_sensitive_callback_key, normalize_callback_names, @@ -311,10 +310,8 @@ from litellm._logging import ( verbose_router_logger, ) from litellm.caching.caching import DualCache, RedisCache -from litellm.caching.dual_cache import DeclaredBatchRead from litellm.caching.redis_batch import ( active_post_call_redis_batch, - active_request_redis_batches, drain_post_call_redis_batches, ) from litellm.caching.redis_cache import RedisCircuitBreakerOpenError, is_redis_timeout_failure @@ -346,6 +343,7 @@ from litellm.constants import ( REALTIME_SESSION_SUCCESS_LOGGED_KEY, ROUTER_SETTINGS_MANAGED_OUTSIDE_CONFIG, SPEND_CAPTURE_RATE_CHECK_JOB_ID, + SPEND_LOG_SIZE_CHECK_INTERVAL, USER_SPEND_ALERTS_JOB_ID, WEEKLY_SPEND_REPORT_JOB_ID, ) @@ -3121,8 +3119,9 @@ def cost_tracking(): from litellm.integrations.shadow_eval_logger import ShadowEvalLogger spend_event_producer = build_spend_event_producer(CollectorSettings(), fallback=run_spend_event) - litellm.logging_callback_manager.add_litellm_callback(ProxyDBLogger(spend_event_producer)) - litellm.logging_callback_manager.add_litellm_async_success_callback(ProxyDBLogger(spend_event_producer)) + db_logger: Final = ProxyDBLogger(spend_event_producer) + litellm.logging_callback_manager.add_litellm_callback(db_logger) + litellm.logging_callback_manager.add_litellm_async_success_callback(db_logger) litellm.logging_callback_manager.add_litellm_callback(ShadowEvalLogger()) @@ -4238,73 +4237,61 @@ async def run_spend_counter_pipeline(pending: Sequence[PendingSpendIncrement]) - return tuple(float(current_value) for current_value in results or ()) -def update_cache_read_keys( - user_id: str | None, - end_user_id: str | None, - tags: Sequence[object] | None, - response_cost: float | None, -) -> tuple[str, ...]: - if response_cost is None: - return () - user_keys: tuple[str, ...] = (user_id, GLOBAL_PROXY_SPEND_CACHE_KEY) if user_id is not None else () - end_user_keys: tuple[str, ...] = (end_user_cache_key(end_user_id),) if end_user_id is not None else () - tag_keys: tuple[str, ...] = tuple(tag_cache_key(tag) for tag in tags or () if isinstance(tag, str) and tag) - return user_keys + end_user_keys + tag_keys +_CachedSpendObjectT = TypeVar( + "_CachedSpendObjectT", LiteLLM_UserTable, LiteLLM_EndUserTable, LiteLLM_TeamTableCachedObj, LiteLLM_TagTable +) -_UPDATE_CACHE_PREFETCH_SLOT: Final = "update_cache_read" - - -async def arm_update_cache_read(keys: Sequence[str], cache: DualCache | None = None) -> None: - """Declares the ``update_cache`` read on the request pipeline once the spend is persisted, so it rides the same - round trip as the post-call spend counter read instead of its own.""" - request: Final = active_request_redis_batches() - target: Final = user_api_key_cache if cache is None else cache - if request is None or target.redis_cache is None or not keys: +def _add_spend_to_locally_cached_object( + cache: UserApiKeyCache, key: str, model_type: type[_CachedSpendObjectT], response_cost: float +) -> None: + current: Final = cache.get_cache(key=key, local_only=True, model_type=model_type) + if current is None: return - with service_target(AUTH_OBJECTS_TARGET): - request.prefetched[_UPDATE_CACHE_PREFETCH_SLOT] = await target.declare_batch_get( - keys, request.batch(target.redis_cache) - ) + cache.set_cache( + key=key, + value=current.model_copy(update={"spend": (current.spend or 0.0) + response_cost}), + local_only=True, + model_type=model_type, + ttl=get_management_object_ttl(cache), + ) -async def _take_armed_update_cache_read(keys: Sequence[str], cache: DualCache) -> Mapping[str, object] | None: - request: Final = active_request_redis_batches() - if request is None: +async def _add_spend_to_shared_global_proxy_spend( + cache: UserApiKeyCache, response_cost: float, parent_otel_span: Span | None +) -> float | None: + if cache.redis_cache is None: return None - armed: Final = request.prefetched.pop(_UPDATE_CACHE_PREFETCH_SLOT, None) - if not isinstance(armed, DeclaredBatchRead) or armed.keys != tuple(keys): - return None - values: Final = await cache.async_resolve_batch_get(armed) - return MappingProxyType({key: value for key, value in zip(keys, values) if value is not None}) - - -async def _read_update_cache_values( - keys: Sequence[str], parent_otel_span: Span | None, cache: DualCache | None = None -) -> Mapping[str, object]: - """One batched read for every object ``update_cache`` refreshes; a failed read leaves them all untouched, - exactly as a failed per-object GET left that object untouched.""" - if not keys: - return MappingProxyType({}) - target: Final = user_api_key_cache if cache is None else cache try: - armed: Final = await _take_armed_update_cache_read(keys, target) - if armed is not None: - return armed - values: Final = await target.async_batch_get_cache( - keys=list(keys), parent_otel_span=parent_otel_span, throttle_redis=False + return await cache.redis_cache.async_increment_if_present( + key=GLOBAL_PROXY_SPEND_CACHE_KEY, value=response_cost, parent_otel_span=parent_otel_span ) except Exception as e: verbose_proxy_logger.warning( - "Spend tracking - failed to read cached spend objects. Budget enforcement may use stale spend values. " - "keys=%s - %s", - keys, + "Spend tracking - failed to add spend to the global proxy spend in Redis. " + "Budget enforcement may use stale spend values. response_cost=%s - %s", + response_cost, str(e), ) - return MappingProxyType({}) - if values is None: - return MappingProxyType({}) - return MappingProxyType({key: value for key, value in zip(keys, values) if value is not None}) + return None + + +async def _add_spend_to_global_proxy_spend( + cache: UserApiKeyCache, response_cost: float, parent_otel_span: Span | None +) -> None: + local_before: Final = cache.get_cache(key=GLOBAL_PROXY_SPEND_CACHE_KEY, local_only=True) + shared_total: Final = await _add_spend_to_shared_global_proxy_spend(cache, response_cost, parent_otel_span) + local_total: Final = cache.get_cache(key=GLOBAL_PROXY_SPEND_CACHE_KEY, local_only=True) + if not isinstance(local_total, (int, float)): + return + if shared_total is not None and local_total != local_before and shared_total < local_total: + return + cache.set_cache( + key=GLOBAL_PROXY_SPEND_CACHE_KEY, + value=local_total + response_cost if shared_total is None else shared_total, + local_only=True, + ttl=get_management_object_ttl(cache), + ) async def update_cache( @@ -4315,6 +4302,7 @@ async def update_cache( response_cost: float | None, parent_otel_span: Span | None, tags: list[str] | None = None, + cache: UserApiKeyCache | None = None, ): """ Use this to update the cache with new user spend. @@ -4322,14 +4310,7 @@ async def update_cache( Put any alerting logic in here. """ - values_to_update_in_cache: Final[list[tuple[str, object]]] = [] - with service_target(AUTH_OBJECTS_TARGET): - cached_values: Final = await _read_update_cache_values( - keys=update_cache_read_keys( - user_id=user_id, end_user_id=end_user_id, tags=tags, response_cost=response_cost - ), - parent_otel_span=parent_otel_span, - ) + target: Final = user_api_key_cache if cache is None else cache ### UPDATE KEY SPEND ### async def _update_key_cache(token: str, response_cost: float): @@ -4339,7 +4320,7 @@ async def update_cache( else: hashed_token = token verbose_proxy_logger.debug("_update_key_cache: hashed_token=%s", hashed_token) - existing_spend_obj = await user_api_key_cache.async_get_cache(key=hashed_token, model_type=UserAPIKeyAuth) + existing_spend_obj = await target.async_get_cache(key=hashed_token, model_type=UserAPIKeyAuth) verbose_proxy_logger.debug("_update_key_cache: existing_spend_obj=%s", existing_spend_obj) if existing_spend_obj is None: return @@ -4381,184 +4362,17 @@ async def update_cache( ) # set cooldown on alert - ### UPDATE USER SPEND ### - async def _update_user_cache(): - ## UPDATE CACHE FOR USER ID + GLOBAL PROXY - if response_cost is None: - return - user_ids: Final = [user_id] + def _add_spend(key: str, model_type: type[_CachedSpendObjectT], cost: float) -> None: try: - for _id in user_ids: - # Fetch the existing cost for the given user - if _id is None: - continue - cached_user = cached_values.get(_id) - if cached_user is None: - # do nothing if there is no cache value - return - existing_spend_obj = CacheCodec.deserialize(cached_user, LiteLLM_UserTable) - if existing_spend_obj is None: - return - verbose_proxy_logger.debug( - "_update_user_db: existing spend: %s; response_cost: %s", existing_spend_obj, response_cost - ) - - existing_spend = existing_spend_obj.spend or 0.0 - # Calculate the new cost by adding the existing cost and response_cost - new_spend = existing_spend + response_cost - - existing_spend_obj.spend = new_spend - values_to_update_in_cache.append( - ( - _id, - CacheCodec.serialize(existing_spend_obj, model_type=LiteLLM_UserTable), - ) - ) - ## UPDATE GLOBAL PROXY ## - global_proxy_spend: Final = cached_values.get(GLOBAL_PROXY_SPEND_CACHE_KEY) - if not isinstance(global_proxy_spend, (int, float)): - # do nothing if not in cache - return - elif response_cost is not None: - increment: Final = global_proxy_spend + response_cost - values_to_update_in_cache.append((GLOBAL_PROXY_SPEND_CACHE_KEY, increment)) + _add_spend_to_locally_cached_object(target, key, model_type, cost) except Exception as e: verbose_proxy_logger.warning( - "Spend tracking - failed to update user spend in cache. " + "Spend tracking - failed to update %s spend in cache. " "Budget enforcement may use stale spend values. " - "user_id=%s, response_cost=%s - %s\n%s", - user_id, - response_cost, - str(e), - traceback.format_exc(), - ) - - ### UPDATE END-USER SPEND ### - async def _update_end_user_cache(): - if end_user_id is None or response_cost is None: - return - - _id: Final = end_user_cache_key(end_user_id) - try: - # Fetch the existing cost for the given user - cached_end_user: Final = cached_values.get(_id) - if cached_end_user is None: - # if user does not exist in LiteLLM_UserTable, create a new user - # do nothing if end-user not in api key cache - return - existing_spend_obj: Final = CacheCodec.deserialize(cached_end_user, LiteLLM_EndUserTable) - if existing_spend_obj is None: - return - verbose_proxy_logger.debug( - "_update_end_user_db: existing spend: %s; response_cost: %s", existing_spend_obj, response_cost - ) - - existing_spend: Final = existing_spend_obj.spend or 0.0 - # Calculate the new cost by adding the existing cost and response_cost - new_spend: Final = existing_spend + response_cost - - existing_spend_obj.spend = new_spend - values_to_update_in_cache.append( - ( - _id, - CacheCodec.serialize(existing_spend_obj, model_type=LiteLLM_EndUserTable), - ) - ) - except Exception as e: - verbose_proxy_logger.warning( - "Spend tracking - failed to update end user spend in cache. " - "Budget enforcement may use stale spend values. " - "end_user_id=%s, response_cost=%s - %s\n%s", - end_user_id, - response_cost, - str(e), - traceback.format_exc(), - ) - - ### UPDATE TEAM SPEND ### - def _update_team_cache(): - if team_id is None or response_cost is None: - return - - _id: Final = f"team_id:{team_id}" - try: - current_team: Final = CacheCodec.deserialize( - user_api_key_cache.get_cache(key=_id, local_only=True), LiteLLM_TeamTableCachedObj - ) - if current_team is None: - return - verbose_proxy_logger.debug( - "_update_team_db: existing spend: %s; response_cost: %s", current_team, response_cost - ) - user_api_key_cache.set_cache( - key=_id, - value=CacheCodec.serialize( - current_team.model_copy(update={"spend": (current_team.spend or 0.0) + response_cost}), - model_type=LiteLLM_TeamTableCachedObj, - ), - local_only=True, - ttl=get_management_object_ttl(user_api_key_cache), - ) - except Exception as e: - verbose_proxy_logger.warning( - "Spend tracking - failed to update team spend in cache. " - "Budget enforcement may use stale spend values. " - "team_id=%s, response_cost=%s - %s\n%s", - team_id, - response_cost, - str(e), - traceback.format_exc(), - ) - - ### UPDATE TAG SPEND ### - async def _update_tag_cache(): - """ - Update the tag cache with the new spend. - """ - if tags is None or response_cost is None: - return - - try: - for tag_name in tags: - if not tag_name or not isinstance(tag_name, str): - continue - - cache_key = tag_cache_key(tag_name) - # Fetch the existing tag object from cache - cached_tag = cached_values.get(cache_key) - if cached_tag is None: - # do nothing if tag not in api key cache - continue - - existing_tag_obj = CacheCodec.deserialize(cached_tag, LiteLLM_TagTable) - if existing_tag_obj is None: - continue - - verbose_proxy_logger.debug( - "_update_tag_cache: existing spend for tag=%s: %s; response_cost: %s", - tag_name, - existing_tag_obj, - response_cost, - ) - - existing_spend = existing_tag_obj.spend or 0.0 - # Calculate the new cost by adding the existing cost and response_cost - new_spend = existing_spend + response_cost - - existing_tag_obj.spend = new_spend - values_to_update_in_cache.append( - ( - cache_key, - CacheCodec.serialize(existing_tag_obj, model_type=LiteLLM_TagTable), - ) - ) - except Exception as e: - verbose_proxy_logger.warning( - "Spend tracking - failed to update tag spend in cache. " - "Budget enforcement may use stale spend values. " - "tags=%s, response_cost=%s - %s\n%s", - tags, - response_cost, + "key=%s, response_cost=%s - %s\n%s", + model_type.__name__, + key, + cost, str(e), traceback.format_exc(), ) @@ -4566,42 +4380,23 @@ async def update_cache( with service_target(AUTH_OBJECTS_TARGET): if token is not None and response_cost is not None: await _update_key_cache(token=token, response_cost=response_cost) + if response_cost is None: + return - if user_id is not None: - await _update_user_cache() + if user_id is not None: + _add_spend(user_id, LiteLLM_UserTable, response_cost) + if end_user_id is not None: + _add_spend(end_user_cache_key(end_user_id), LiteLLM_EndUserTable, response_cost) + if team_id is not None: + _add_spend(f"team_id:{team_id}", LiteLLM_TeamTableCachedObj, response_cost) + for tag_name in tags or (): + if tag_name and isinstance(tag_name, str): + _add_spend(tag_cache_key(tag_name), LiteLLM_TagTable, response_cost) - if end_user_id is not None: - await _update_end_user_cache() - - if team_id is not None: - _update_team_cache() - - if tags is not None: - await _update_tag_cache() - - global_proxy_spend_key: Final = GLOBAL_PROXY_SPEND_CACHE_KEY - local_object_updates: Final = tuple((k, v) for k, v in values_to_update_in_cache if k != global_proxy_spend_key) - shared_scalar_updates: Final = tuple((k, v) for k, v in values_to_update_in_cache if k == global_proxy_spend_key) - - if local_object_updates: - with service_target(AUTH_OBJECTS_TARGET): - asyncio.create_task( - user_api_key_cache.async_set_cache_pipeline( - cache_list=list(local_object_updates), - ttl=get_management_object_ttl(user_api_key_cache), - litellm_parent_otel_span=parent_otel_span, - local_only=True, - ) - ) - if shared_scalar_updates: - with service_target(SPEND_COUNTERS_TARGET): - asyncio.create_task( - user_api_key_cache.async_set_cache_pipeline( - cache_list=list(shared_scalar_updates), - ttl=get_management_object_ttl(user_api_key_cache), - litellm_parent_otel_span=parent_otel_span, - ) - ) + if litellm.max_budget <= 0: + return + with service_target(SPEND_COUNTERS_TARGET): + await _add_spend_to_global_proxy_spend(target, response_cost, parent_otel_span) def run_ollama_serve(): @@ -5731,20 +5526,44 @@ def _current_general_settings() -> Mapping[str, object]: return general_settings -_CLEANUP_SCHEDULE_KEYS: Final = ( +_RETENTION_RULE_KEYS: Final = ( "maximum_spend_logs_retention_period", "maximum_autorouter_session_retention_period", "maximum_health_check_retention_period", "maximum_daily_tag_spend_retention_period", +) +_CLEANUP_SCHEDULE_KEYS: Final = ( + *_RETENTION_RULE_KEYS, "maximum_spend_logs_cleanup_cron", "maximum_spend_logs_retention_interval", + "maximum_spend_logs_size", + "maximum_spend_logs_cleanup_target_size", + "maximum_spend_logs_size_check_interval", ) +_SPEND_LOG_CLEANUP_JOB_ID: Final = "spend_log_cleanup_job" +_SPEND_LOG_SIZE_CHECK_JOB_ID: Final = "spend_log_size_check_job" def _cleanup_schedule_of(settings: Mapping[str, object]) -> tuple[object, ...]: return tuple(settings.get(key) for key in _CLEANUP_SCHEDULE_KEYS) +def _wants_retention_job(settings: Mapping[str, object]) -> bool: + """The retention job runs the age rules, and the size rule too when one cron drives both.""" + return any(settings.get(key) is not None for key in _RETENTION_RULE_KEYS) or ( + settings.get("maximum_spend_logs_size") is not None and bool(settings.get("maximum_spend_logs_cleanup_cron")) + ) + + +def _wants_size_check_job(settings: Mapping[str, object]) -> bool: + """The size rule gets its own job on maximum_spend_logs_size_check_interval unless a cleanup cron is set.""" + return settings.get("maximum_spend_logs_size") is not None and not settings.get("maximum_spend_logs_cleanup_cron") + + +def _wants_cleanup_jobs(settings: Mapping[str, object]) -> bool: + return _wants_retention_job(settings) or _wants_size_check_job(settings) + + @lru_cache(maxsize=4096) def _log_ignored_cost_map_copy(model_id: str, fields: tuple[str, ...]) -> None: verbose_proxy_logger.warning( @@ -7103,6 +6922,7 @@ class ProxyConfig: "vector_store_deny_by_default", "search_tool_deny_by_default", "vertex_ai_pass_through_drop_anthropic_betas", + "request_tag_mappings", ) if name in typed_general_settings } @@ -8254,39 +8074,73 @@ class ProxyConfig: if scheduler is None: return - wants_job: Final = any( - general_settings.get(key) is not None - for key in ( - "maximum_spend_logs_retention_period", - "maximum_autorouter_session_retention_period", - "maximum_health_check_retention_period", - "maximum_daily_tag_spend_retention_period", - ) - ) - if not wants_job: - if scheduler.get_job("spend_log_cleanup_job") is not None: - scheduler.remove_job("spend_log_cleanup_job") - verbose_proxy_logger.info("Removed existing spend log cleanup job") - return - - trigger: Final = self._spend_log_cleanup_trigger() - if trigger is None: - return from litellm.proxy.db.db_transaction_queue.spend_log_cleanup import ( SpendLogCleanup, ) - scheduler.add_job( - SpendLogCleanup().cleanup_old_spend_logs, - trigger, + if not _wants_retention_job(general_settings): + if scheduler.get_job(_SPEND_LOG_CLEANUP_JOB_ID) is not None: + scheduler.remove_job(_SPEND_LOG_CLEANUP_JOB_ID) + verbose_proxy_logger.info("Removed existing spend log cleanup job") + else: + trigger: Final = self._spend_log_cleanup_trigger() + if trigger is not None: + scheduler.add_job( + SpendLogCleanup().cleanup_old_spend_logs, + trigger, + args=[prisma_client], + id=_SPEND_LOG_CLEANUP_JOB_ID, + replace_existing=True, + misfire_grace_time=APSCHEDULER_MISFIRE_GRACE_TIME, + ) + verbose_proxy_logger.info("Spend log cleanup rescheduled with trigger: %s", trigger) + + if not _wants_size_check_job(general_settings): # pyright: ignore[reportUnknownArgumentType] # general_settings is an untyped module dict + if scheduler.get_job(_SPEND_LOG_SIZE_CHECK_JOB_ID) is not None: # pyright: ignore[reportUnknownMemberType] # apscheduler is untyped + scheduler.remove_job(_SPEND_LOG_SIZE_CHECK_JOB_ID) # pyright: ignore[reportUnknownMemberType] # apscheduler is untyped + verbose_proxy_logger.info("Removed existing spend log size check job") + return + size_trigger: Final = self._spend_log_size_check_trigger() + if size_trigger is None: + return + scheduler.add_job( # pyright: ignore[reportUnknownMemberType] # apscheduler is untyped + SpendLogCleanup().cleanup_spend_logs_by_size, + size_trigger, args=[prisma_client], - id="spend_log_cleanup_job", + id=_SPEND_LOG_SIZE_CHECK_JOB_ID, replace_existing=True, misfire_grace_time=APSCHEDULER_MISFIRE_GRACE_TIME, ) - verbose_proxy_logger.info("Spend log cleanup rescheduled with trigger: %s", trigger) + verbose_proxy_logger.info("Spend log size check rescheduled with trigger: %s", size_trigger) - def _spend_log_cleanup_trigger(self) -> BaseTrigger | None: + def _spend_log_size_check_trigger(self) -> object | None: + return self._staggered_interval_trigger( + _SPEND_LOG_SIZE_CHECK_JOB_ID, + "maximum_spend_logs_size_check_interval", + general_settings.get("maximum_spend_logs_size_check_interval", SPEND_LOG_SIZE_CHECK_INTERVAL), # pyright: ignore[reportUnknownMemberType, reportUnknownArgumentType] # general_settings is an untyped module dict + ) + + @staticmethod + def _staggered_interval_trigger(job_id: str, setting_name: str, interval: object) -> object | None: + if not isinstance(interval, str): + verbose_proxy_logger.error("Invalid %s value: %r", setting_name, interval) + return None + # this runs against a started scheduler, which the startup stagger sweep + # cannot reach, so the offset is applied here or the job reconverges across + # replicas the first time an admin edits the settings + try: + interval_seconds: Final = duration_in_seconds(interval) + return stagger_trigger( + job_id=job_id, + trigger=IntervalTrigger(seconds=interval_seconds), + period_seconds=interval_seconds, + settings=parse_stagger_settings(general_settings), # pyright: ignore[reportUnknownArgumentType] # general_settings is an untyped module dict + ) + except (ValueError, OverflowError): + verbose_proxy_logger.error("Invalid %s value: %r", setting_name, interval) + return None + + def _spend_log_cleanup_trigger(self) -> object | None: cleanup_cron: Final[object] = general_settings.get("maximum_spend_logs_cleanup_cron") if cleanup_cron: from apscheduler.triggers.cron import CronTrigger @@ -8297,24 +8151,11 @@ class ProxyConfig: verbose_proxy_logger.error("Invalid maximum_spend_logs_cleanup_cron value: %s", cleanup_cron) return None return cron_trigger - retention_interval: Final[object] = general_settings.get("maximum_spend_logs_retention_interval", "1d") - if not isinstance(retention_interval, str): - verbose_proxy_logger.error("Invalid maximum_spend_logs_retention_interval value: %r", retention_interval) - return None - # this runs against a started scheduler, which the startup stagger sweep - # cannot reach, so the offset is applied here or the job reconverges across - # replicas the first time an admin edits the retention settings - try: - interval_seconds: Final = duration_in_seconds(retention_interval) - return stagger_trigger( - job_id="spend_log_cleanup_job", - trigger=IntervalTrigger(seconds=interval_seconds), - period_seconds=interval_seconds, - settings=parse_stagger_settings(general_settings), - ) - except (ValueError, OverflowError): - verbose_proxy_logger.error("Invalid maximum_spend_logs_retention_interval value: %r", retention_interval) - return None + return self._staggered_interval_trigger( + _SPEND_LOG_CLEANUP_JOB_ID, + "maximum_spend_logs_retention_interval", + general_settings.get("maximum_spend_logs_retention_interval", "1d"), + ) async def _update_general_settings(self, db_general_settings: Mapping[str, SettingsJsonValue] | None) -> None: global general_settings @@ -8345,6 +8186,7 @@ class ProxyConfig: previous_cleanup_schedule: tuple[object, ...], ) -> None: effects: Final = ( + self._apply_request_tag_mappings_setting, self._apply_alerting_settings, self._apply_pass_through_settings, self._apply_boolean_settings, @@ -8356,6 +8198,19 @@ class ProxyConfig: for effect in effects: await effect(db_values) + async def _apply_request_tag_mappings_setting(self, db_values: Mapping[str, SettingsJsonValue]) -> None: + if "request_tag_mappings" not in db_values: + return + mappings: Final = self.settings.get("request_tag_mappings") + try: + ConfigGeneralSettings.model_validate(MappingProxyType({"request_tag_mappings": mappings})) + except ValidationError as error: + self.settings.pop("request_tag_mappings", None) + verbose_proxy_logger.error( + "Ignoring invalid general_settings.request_tag_mappings from the DB, so no baggage maps to tags: %s", + error, + ) + async def _apply_alerting_settings(self, db_values: Mapping[str, SettingsJsonValue]) -> None: alerting: Final = self.settings.get("alerting") if "alerting" in db_values and isinstance(alerting, list): @@ -8457,8 +8312,11 @@ class ProxyConfig: if scheduler is not None and scheduler.state == STATE_STOPPED: return schedule: Final = self._resolved_cleanup_schedule() - wants_job: Final = any(value is not None for value in schedule[:4]) - has_job: Final = scheduler is not None and scheduler.get_job("spend_log_cleanup_job") is not None + wants_job: Final = _wants_cleanup_jobs(self.settings) + has_job: Final = scheduler is not None and ( + scheduler.get_job(_SPEND_LOG_CLEANUP_JOB_ID) is not None + or scheduler.get_job(_SPEND_LOG_SIZE_CHECK_JOB_ID) is not None # pyright: ignore[reportUnknownMemberType] # apscheduler is untyped + ) baseline: Final = ( self._last_cleanup_schedule_attempt if has_job and self._last_cleanup_schedule_attempt is not None @@ -11610,12 +11468,29 @@ class ProxyStartupEvent: ### SPEND LOG CLEANUP ### cleanup_settings: Final = _current_general_settings() - if ( - cleanup_settings.get("maximum_spend_logs_retention_period") is not None - or cleanup_settings.get("maximum_autorouter_session_retention_period") is not None - or cleanup_settings.get("maximum_health_check_retention_period") is not None - or cleanup_settings.get("maximum_daily_tag_spend_retention_period") is not None - ): + if _wants_size_check_job(cleanup_settings): + size_check_interval: Final = cleanup_settings.get( + "maximum_spend_logs_size_check_interval", SPEND_LOG_SIZE_CHECK_INTERVAL + ) + try: + if not isinstance(size_check_interval, str): + raise TypeError(size_check_interval) + size_check_seconds: Final = duration_in_seconds(size_check_interval) + scheduler.add_job( # pyright: ignore[reportUnknownMemberType] # apscheduler is untyped + SpendLogCleanup().cleanup_spend_logs_by_size, + "interval", + seconds=size_check_seconds + random.randint(0, 60), + args=[prisma_client], + id=_SPEND_LOG_SIZE_CHECK_JOB_ID, + replace_existing=True, + misfire_grace_time=APSCHEDULER_MISFIRE_GRACE_TIME, + ) + verbose_proxy_logger.info("Spend log size check scheduled every %s", size_check_interval) + except (TypeError, ValueError, OverflowError): + verbose_proxy_logger.error( + "Invalid maximum_spend_logs_size_check_interval value: %r", size_check_interval + ) + if _wants_retention_job(cleanup_settings): spend_log_cleanup: Final = SpendLogCleanup() cleanup_cron: Final = cleanup_settings.get("maximum_spend_logs_cleanup_cron") @@ -11630,7 +11505,7 @@ class ProxyStartupEvent: spend_log_cleanup.cleanup_old_spend_logs, cron_trigger, args=[prisma_client], - id="spend_log_cleanup_job", + id=_SPEND_LOG_CLEANUP_JOB_ID, replace_existing=True, misfire_grace_time=APSCHEDULER_MISFIRE_GRACE_TIME, ) @@ -11649,7 +11524,7 @@ class ProxyStartupEvent: "interval", seconds=interval_seconds + random.randint(0, 60), args=[prisma_client], - id="spend_log_cleanup_job", + id=_SPEND_LOG_CLEANUP_JOB_ID, replace_existing=True, misfire_grace_time=APSCHEDULER_MISFIRE_GRACE_TIME, ) @@ -11657,6 +11532,7 @@ class ProxyStartupEvent: verbose_proxy_logger.error( "Invalid maximum_spend_logs_retention_interval value: %r", retention_interval ) + if _wants_cleanup_jobs(cleanup_settings): proxy_config.record_cleanup_schedule_attempt(cleanup_settings) ### CHECK BATCH COST ### if llm_router is not None and PROXY_BATCH_POLLING_ENABLED: @@ -14688,7 +14564,9 @@ async def run_thread( # dependencies=[Depends(user_api_key_auth)], # ) # async def get_available_routes(user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth)): +from litellm.litellm_core_utils.tool_fields import DropPolicy, drop_policy from litellm.llms.base_llm.base_utils import BaseTokenCounter +from litellm.llms.openai.responses.count_tokens.token_counter import OpenAITokenCounter from litellm.proxy.db.routing_prisma_wrapper import WriterPinnedClient from litellm.repositories.config_repository import ConfigRepository from litellm.repositories.model_repository import ModelRepository @@ -14701,6 +14579,11 @@ from litellm.repositories.table_repositories import ( ) from litellm.repositories.team_repository import TeamRepository from litellm.repositories.user_repository import UserRepository +from litellm.responses.litellm_completion_transformation.count_request import ( + ChatCountBridgeError, + chat_count_request, + with_provider_file_ids, +) def _get_provider_token_counter( @@ -14758,6 +14641,18 @@ def _get_provider_token_counter( return None, None, None +def _provider_count_outcome( + result: Union["TokenCountResponse", None], +) -> Union["TokenCountResponse", ProviderCountFailure, None]: + if result is not None and result.error is True: + return ProviderCountFailure( + status_code=result.status_code or 500, + message=result.error_message or "Token counting failed", + rejected_before_provider_call=result.rejected_before_provider_call, + ) + return result + + def _with_resolved_api_key(litellm_params: object) -> Mapping[str, object]: call_params: Final = _LITELLM_PARAMS_COPY.validate_python(litellm_params) try: @@ -14772,6 +14667,12 @@ def _with_resolved_api_key(litellm_params: object) -> Mapping[str, object]: return call_params +def _with_resolved_credentials(deployment: Mapping[str, object] | None) -> dict[str, object] | None: + if deployment is None: + return None + return {**deployment, "litellm_params": _with_resolved_api_key(deployment.get("litellm_params", {}))} + + _DEPLOYMENT_LITELLM_PARAMS: Final = TypeAdapter(Mapping[str, object]) @@ -14812,6 +14713,7 @@ async def _try_provider_token_count( messages_format: TokenCountMessagesFormat = "openai", output_format: JsonValue = None, context_management: CountContextManagement | None = None, + chat_params: Mapping[str, JsonValue] = MappingProxyType({}), ) -> Union["TokenCountResponse", ProviderCountFailure, None]: """Attempt provider-specific token counting. Returns None to fall through to local counting.""" if not provider_counter.should_use_token_counting_api(custom_llm_provider=custom_llm_provider): @@ -14831,31 +14733,44 @@ async def _try_provider_token_count( model_to_use=model_to_use or "", messages=messages, contents=contents, - deployment=None - if deployment_in_region is None - else { - **deployment_in_region, - "litellm_params": _with_resolved_api_key(deployment_in_region.get("litellm_params", {})), - }, + deployment=_with_resolved_credentials(deployment_in_region), request_model=request_model, tools=tools, system=system, messages_format=messages_format, output_format=output_format, context_management=context_management, + chat_params=chat_params, ) except httpx.HTTPStatusError as e: return ProviderCountFailure( status_code=getattr(e, "status_code", None) or e.response.status_code, message=getattr(e, "message", None) or str(e), ) - if result is not None and result.error is True: - return ProviderCountFailure( - status_code=result.status_code or 500, - message=result.error_message or "Token counting failed", - rejected_before_provider_call=result.rejected_before_provider_call, + return _provider_count_outcome(result) + + +async def _try_native_responses_count( + provider_counter: OpenAITokenCounter, + custom_llm_provider: str | None, + model_to_use: str, + _region: str | None, + responses_request: Mapping[str, object], + policy: DropPolicy, + deployment: Mapping[str, object] | None, + request_model: str, +) -> Union["TokenCountResponse", ProviderCountFailure, None]: + if not provider_counter.should_use_token_counting_api(custom_llm_provider=custom_llm_provider): + return None + return _provider_count_outcome( + await provider_counter.count_responses_request( + model_to_use=model_to_use, + request=responses_request, + policy=policy, + deployment=_with_resolved_credentials(deployment), + request_model=request_model, ) - return result + ) async def _provider_token_count( @@ -15137,6 +15052,7 @@ class _TokenCountDeployment(TypedDict, total=False): _TOKEN_COUNT_DEPLOYMENT: Final = TypeAdapter(_TokenCountDeployment) +_ROUTED_DEPLOYMENT: Final[TypeAdapter[Mapping[str, object] | None]] = TypeAdapter(Mapping[str, object] | None) def _model_group_deployment(router: Router | None, model_group: str) -> Mapping[str, object] | None: @@ -15215,6 +15131,43 @@ def _count_context_management( ) +def _responses_routing_kwargs(responses_request: Mapping[str, object] | None) -> Mapping[str, object]: + previous_response_id: Final = None if responses_request is None else responses_request.get("previous_response_id") + return {"previous_response_id": previous_response_id} if isinstance(previous_response_id, str) else {} + + +def _count_drop_policy(deployment: Mapping[str, object] | None, responses_request: Mapping[str, object]) -> DropPolicy: + litellm_params: Final = as_str_mapping(None if deployment is None else deployment.get("litellm_params")) or {} + router_defaults: Final[Mapping[str, object]] = ( + {} if llm_router is None else _router_default_litellm_params(llm_router) + ) + return drop_policy({**litellm_params, **router_defaults, **responses_request}) + + +def _native_responses_count( + provider_counter: BaseTokenCounter, + custom_llm_provider: str | None, + responses_request: Mapping[str, object] | None, + deployment: Mapping[str, object] | None, + request_model: str, +) -> Callable[[str, str | None], Awaitable[Union["TokenCountResponse", ProviderCountFailure, None]]] | None: + if responses_request is None or not isinstance(provider_counter, OpenAITokenCounter): + return None + return partial( + _try_native_responses_count, + provider_counter, + custom_llm_provider, + responses_request=responses_request, + policy=_count_drop_policy(deployment, responses_request), + deployment=deployment, + request_model=request_model, + ) + + +def _deployment_api_base(deployment: _TokenCountDeployment) -> str | None: + return _non_empty_str(deployment.get("litellm_params", {}).get("api_base")) + + def _system_message(system: object) -> ChatCompletionSystemMessage | None: if not isinstance(system, (str, list)) or not system: return None @@ -15247,6 +15200,7 @@ async def count_request_tokens( output_format: JsonValue = None, context_management: JsonValue = None, request_litellm_params: Mapping[str, JsonValue] = MappingProxyType({}), + responses_request: Mapping[str, object] | None = None, ) -> TokenCountResponse: prompt: Final = request.prompt messages: Final = request.messages @@ -15268,7 +15222,7 @@ async def count_request_tokens( try: deployment = await llm_router.async_get_available_deployment( model=request.model, - request_kwargs={}, + request_kwargs=dict(_responses_routing_kwargs(responses_request)), ) except Exception: verbose_proxy_logger.exception( @@ -15322,23 +15276,54 @@ async def count_request_tokens( request_messages: Final = _counted_request_messages(messages, messages_format, count_deployment) contents_estimable: Final = not contents or (bool(messages) and _estimable_contents(contents)) prompt_as_message: Final = prompt_only and custom_llm_provider in _PROVIDERS_COUNTING_WITHOUT_MESSAGES + routed_deployment: Final = _ROUTED_DEPLOYMENT.validate_python(deployment) + routed_request: Final = ( + None if responses_request is None else with_provider_file_ids(responses_request, routed_deployment) + ) + chat_count: Final = ( + None + if routed_request is None or provider_counter is None or isinstance(provider_counter, OpenAITokenCounter) + else await chat_count_request( + model_to_use, + custom_llm_provider, + _deployment_api_base(deployment_view), + routed_request, + _count_drop_policy(routed_deployment, routed_request), + ) + ) + if isinstance(chat_count, ChatCountBridgeError): + raise ProxyException(message=chat_count.message, type="invalid_request_error", param=None, code=400) ladder: Final = ( None if provider_counter is None else await _provider_token_count( - count_with=partial( + count_with=_native_responses_count( + provider_counter, + custom_llm_provider, + routed_request, + routed_deployment, + request.model, + ) + or partial( _try_provider_token_count, provider_counter, custom_llm_provider, - messages=[{"role": "user", "content": prompt}] if prompt_as_message else request_messages, + messages=( + [dict(message) for message in chat_count.messages] + if chat_count is not None + else [{"role": "user", "content": prompt}] + if prompt_as_message + else request_messages + ), contents=None if prompt_as_message else contents, deployment=count_deployment, request_model=request.model, - tools=tools, + tools=tools if chat_count is None else [dict(tool) for tool in chat_count.tools or ()] or None, system=system, messages_format=messages_format, output_format=output_format, context_management=_count_context_management(context_management, request.model, request_litellm_params), + chat_params=MappingProxyType({}) if chat_count is None else chat_count.params, ), model_to_use=model_to_use, settings=settings, @@ -18284,6 +18269,7 @@ async def async_queue_request( raise HTTPException(status_code=500, detail={"error": CommonProxyErrors.no_llm_router.value}) router: Final = llm_router + queued_priority, _ = router.split_request_priority(model=data["model"], kwargs=data) if "stream" in data and data["stream"] is True: # use generate_responses to stream responses async def produce_queue_stream() -> StreamingResponse: @@ -18295,6 +18281,7 @@ async def async_queue_request( request=request, ), media_type="text/event-stream", + headers={"x-litellm-priority": str(queued_priority)}, ) async def audit_late_failure(exc: Exception) -> HTTPException | None: @@ -18309,7 +18296,7 @@ async def async_queue_request( ) response: Final = await router.schedule_acompletion(**data) - fastapi_response.headers.update({"x-litellm-priority": str(data["priority"])}) + fastapi_response.headers.update({"x-litellm-priority": str(queued_priority)}) return response except Exception as e: await proxy_logging_obj.post_call_failure_hook( @@ -18324,6 +18311,10 @@ async def async_queue_request( ) elif isinstance(e, ProxyException): raise e + elif isinstance(e, litellm.BadRequestError): + raise ProxyException( + message=e.message, type="invalid_request_error", param=getattr(e, "param", None), code=e.status_code + ) raise ProxyException( message="Authentication Error, " + str(e), type=ProxyErrorTypes.auth_error, @@ -18411,6 +18402,7 @@ async def login(request: Request): # _is_same_origin_return_path (strictly relative path) so it can never be an open redirect, and the # one-shot cookie is cleared after use. from litellm.proxy.management_endpoints.ui_sso import ( + read_return_to_cookie, set_session_token_cookie, sso_return_to_redirect, ) @@ -18422,7 +18414,7 @@ async def login(request: Request): # return_to is honored for EVERY sign-in branch, so the write and read sets cannot diverge: it # sets the token cookie on the same-origin arm and hands off via a one-time login code on the # cross-origin arm, and clears the one-shot cookie in both. - cp_return_to: Final = request.cookies.get("litellm_cp_return_to") + cp_return_to: Final = read_return_to_cookie(request) if cp_return_to: try: resumed = await sso_return_to_redirect( # rebind-ok: pre-existing rebinding on a rename-only line @@ -18446,7 +18438,7 @@ async def login(request: Request): # Create redirect response with cookie redirect_response: Final = RedirectResponse(url=litellm_dashboard_ui, status_code=303) set_session_token_cookie(redirect_response, request, jwt_token) - if cp_return_to: + if "litellm_cp_return_to" in request.cookies: redirect_response.delete_cookie(key="litellm_cp_return_to") return redirect_response @@ -19636,6 +19628,7 @@ _PLUGIN_KEY_REDACTED: Final = "***" _GENERAL_SETTINGS_CONFIG_LIST_FIELD_TYPES: Final[Mapping[str, str]] = MappingProxyType( { + "request_tag_mappings": "RequestTagMappings", "max_parallel_requests": "Integer", "global_max_parallel_requests": "Integer", "max_in_flight_requests_per_worker": "Integer", diff --git a/litellm/proxy/public_endpoints/provider_create_fields.json b/litellm/proxy/public_endpoints/provider_create_fields.json index a794854ce19..4bec42a7868 100644 --- a/litellm/proxy/public_endpoints/provider_create_fields.json +++ b/litellm/proxy/public_endpoints/provider_create_fields.json @@ -1731,6 +1731,16 @@ "field_type": "password", "options": null, "default_value": null + }, + { + "key": "github_copilot_host", + "label": "GitHub host", + "placeholder": "github.com", + "tooltip": "Leave empty for github.com. For GHE.com data residency enter your SUBDOMAIN.ghe.com host", + "required": false, + "field_type": "text", + "options": null, + "default_value": null } ], "default_model_placeholder": "gpt-3.5-turbo" diff --git a/litellm/proxy/public_endpoints/public_endpoints.py b/litellm/proxy/public_endpoints/public_endpoints.py index 8903b22c120..6ced7827846 100644 --- a/litellm/proxy/public_endpoints/public_endpoints.py +++ b/litellm/proxy/public_endpoints/public_endpoints.py @@ -22,6 +22,7 @@ from litellm.litellm_core_utils.get_model_cost_map import GetModelCostMap from litellm.proxy._types import ( CommonProxyErrors, ) +from litellm.proxy.db.health_check_latest import latest_by_model_name from litellm.proxy.utils import get_custom_url from litellm.repositories.table_repositories import ClaudeCodePluginRepository from litellm.router_strategy.complexity_router.fuse_presets import FusePresetCatalog, get_fuse_presets @@ -295,13 +296,8 @@ async def public_model_hub(): if prisma_client is not None: try: latest_checks: Final = await prisma_client.get_all_latest_health_checks() - for check in latest_checks: - key = check.model_id if check.model_id else check.model_name - if key: - health_check_dict = convert_health_check_to_dict(check) - health_checks_map[key] = health_check_dict - if check.model_name: - health_checks_map[check.model_name] = health_check_dict + for model_name, check in latest_by_model_name(latest_checks).items(): + health_checks_map[model_name] = convert_health_check_to_dict(check) except Exception: pass diff --git a/litellm/proxy/public_endpoints/public_v1/model_hub.py b/litellm/proxy/public_endpoints/public_v1/model_hub.py index 2f5eeeb3d4b..cd634e490b6 100644 --- a/litellm/proxy/public_endpoints/public_v1/model_hub.py +++ b/litellm/proxy/public_endpoints/public_v1/model_hub.py @@ -12,6 +12,7 @@ import litellm from litellm._logging import verbose_proxy_logger from litellm.proxy._types import CommonProxyErrors, UserAPIKeyAuth from litellm.proxy.auth.user_api_key_auth import user_api_key_auth +from litellm.proxy.db.health_check_latest import latest_by_model_name from litellm.proxy.list_api.common import PROBLEM_TYPE_BASE, ManagementProblem from litellm.proxy.list_api.in_memory import Cells, InMemoryListExecutor from litellm.proxy.list_api.list_framework import ( @@ -59,12 +60,12 @@ class PrismaHealthSnapshotLookup: checks: Final = await self.prisma_client.get_latest_health_checks_for_models(model_groups) return MappingProxyType( { - check.model_name: HealthSnapshot( + model_group: HealthSnapshot( status=check.status, response_time_ms=check.response_time_ms, checked_at=check.checked_at.isoformat() if check.checked_at else None, ) - for check in checks + for model_group, check in latest_by_model_name(checks).items() } ) diff --git a/litellm/proxy/response_api_endpoints/endpoints.py b/litellm/proxy/response_api_endpoints/endpoints.py index a0fb2b190e0..c918ea3f1d1 100644 --- a/litellm/proxy/response_api_endpoints/endpoints.py +++ b/litellm/proxy/response_api_endpoints/endpoints.py @@ -32,12 +32,13 @@ from typing_extensions import NotRequired, ReadOnly, TypedDict import litellm from litellm._logging import verbose_proxy_logger from litellm.anthropic_interface.exceptions.exception_mapping_utils import AnthropicExceptionMapping +from litellm.caching.dual_cache import DualCache from litellm.constants import EMPTY_MAPPING, MANAGED_BACKGROUND_RESPONSE_METADATA_KEY, TERMINAL_RESPONSE_STATUSES from litellm.integrations.custom_guardrail import ModifyResponseException from litellm.litellm_core_utils.core_helpers import as_str_mapping, get_metadata_variable_name_from_kwargs from litellm.litellm_core_utils.internal_call_metadata import is_background_response, requests_background from litellm.litellm_core_utils.litellm_logging import StandardLoggingPayloadSetup -from litellm.litellm_core_utils.tool_fields import first_validation_error +from litellm.litellm_core_utils.tool_fields import TOOL_FIELDS, first_validation_error from litellm.llms.openai.responses.guardrail_translation.handler import ( OpenAIResponsesHandler, build_blocked_response, @@ -79,6 +80,7 @@ from litellm.proxy.pass_through_endpoints.llm_provider_handlers.batch_attributio ) from litellm.proxy.route_llm_request import raise_if_required_body_param_missing from litellm.proxy.utils import handle_exception_on_proxy +from litellm.responses.litellm_completion_transformation.count_request import MODEL_FILE_ID_MAPPING_FIELD from litellm.responses.streaming_iterator import GuardedResponsesWsFrame, ResponsesWsFrameGuard, spawn_logging_task from litellm.router import Router from litellm.types.llms.base import LiteLLMBaseModel @@ -89,7 +91,7 @@ from litellm.types.llms.openai import ( ) from litellm.types.responses.main import DeleteResponseResult from litellm.types.token_count import TokenCountSourceFields -from litellm.types.utils import TokenCountResponse +from litellm.types.utils import ADDRESSED_RESPONSE_ID_FIELD, TokenCountResponse if TYPE_CHECKING: from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj @@ -1388,13 +1390,15 @@ class _TokenCountPayload(TypedDict): class _TokenCounter(Protocol): - def __call__(self, request: TokenCountRequest, call_endpoint: bool) -> Awaitable[TokenCountResponse]: ... + def __call__( + self, *, request: TokenCountRequest, call_endpoint: bool, responses_request: Mapping[str, object] | None + ) -> Awaitable[TokenCountResponse]: ... def _proxy_token_counter() -> _TokenCounter: - from litellm.proxy.proxy_server import token_counter + from litellm.proxy.proxy_server import count_request_tokens - return token_counter + return count_request_tokens _token_counter_dep: Final = Depends(_proxy_token_counter) @@ -1409,6 +1413,67 @@ def _proxy_llm_router() -> Router | None: _llm_router_dep: Final = Depends(_proxy_llm_router) +def _proxy_response_id_security() -> ResponsesIDSecurity | None: + from litellm.proxy.proxy_server import proxy_logging_obj + + security_hook: Final = proxy_logging_obj.get_proxy_hook("responses_id_security") + return security_hook if isinstance(security_hook, ResponsesIDSecurity) else None + + +_response_id_security_dep: Final = Depends(_proxy_response_id_security) + + +class _ManagedFileAccess(Protocol): + async def async_pre_call_hook( + self, + user_api_key_dict: UserAPIKeyAuth, + cache: DualCache, + data: dict[str, object], + call_type: Literal["aresponses"], + ) -> object: ... + + +def _proxy_managed_files_hook() -> _ManagedFileAccess | None: + from litellm.proxy.proxy_server import proxy_logging_obj + + return proxy_logging_obj.get_proxy_hook("managed_files") + + +_managed_files_hook_dep: Final = Depends(_proxy_managed_files_hook) + + +async def _with_managed_file_id_mapping( + data: Mapping[str, object], managed_files: _ManagedFileAccess | None, user_api_key_dict: UserAPIKeyAuth +) -> Mapping[str, object]: + caller_fields: Final = {name: value for name, value in data.items() if name != MODEL_FILE_ID_MAPPING_FIELD} + if managed_files is None: + return caller_fields + from litellm.proxy.proxy_server import user_api_key_cache + + hooked: Final = dict(caller_fields) + try: + await managed_files.async_pre_call_hook( + user_api_key_dict=user_api_key_dict, cache=user_api_key_cache, data=hooked, call_type="aresponses" + ) + except HTTPException as e: + raise ProxyException(message=str(e.detail), type="permission_error", param=None, code=e.status_code) from e + mapping: Final = hooked.get(MODEL_FILE_ID_MAPPING_FIELD) + return caller_fields if mapping is None else {**caller_fields, MODEL_FILE_ID_MAPPING_FIELD: mapping} + + +def _with_authorized_previous_response( + data: Mapping[str, object], security: ResponsesIDSecurity | None, user_api_key_dict: UserAPIKeyAuth +) -> Mapping[str, object]: + previous_response_id: Final = data.get("previous_response_id") + if security is None or not isinstance(previous_response_id, str) or not previous_response_id: + return data + try: + authorized_id: Final = security.authorize_response_id(previous_response_id, user_api_key_dict) + except HTTPException as e: + raise ProxyException(message=str(e.detail), type="permission_error", param=None, code=e.status_code) from e + return {**data, "previous_response_id": authorized_id, ADDRESSED_RESPONSE_ID_FIELD: previous_response_id} + + def _responses_invalid_request_response(message: str, param: str | None, code: str | None) -> JSONResponse: body: Final[_ResponsesApiErrorBody] = { "error": { @@ -1546,6 +1611,8 @@ async def responses_input_tokens( token_counter: _TokenCounter = _token_counter_dep, llm_router: Router | None = _llm_router_dep, user_api_key_dict: UserAPIKeyAuth = _user_api_key_auth_dep, + response_id_security: ResponsesIDSecurity | None = _response_id_security_dep, + managed_files: _ManagedFileAccess | None = _managed_files_hook_dep, ): """ Count the input tokens of a Responses API request without calling the model. @@ -1579,7 +1646,7 @@ async def responses_input_tokens( ) counted_fields: Final = { - name: data[name] for name in ("model", "tools", "drop_params", "additional_drop_params") if name in data + name: data[name] for name in ("model", "drop_params", "additional_drop_params", *TOOL_FIELDS) if name in data } token_fields: Final = resolve_counted_tool_fields(counted_fields, llm_router, user_api_key_dict.team_id) if isinstance(token_fields, ProxyException): @@ -1604,8 +1671,20 @@ async def responses_input_tokens( message=f"Invalid request for token counting: {e}", param=None, code=None ) + request_fields: Final = _PROXY_SERVER_REQUEST_ADAPTER.validate_python(data) + responses_request: Final = await _with_managed_file_id_mapping( + _with_authorized_previous_response( + {**{name: value for name, value in request_fields.items() if name not in counted_fields}, **token_fields}, + response_id_security, + user_api_key_dict, + ), + managed_files, + user_api_key_dict, + ) try: - token_response: Final = await token_counter(request=token_request, call_endpoint=True) + token_response: Final = await token_counter( + request=token_request, call_endpoint=True, responses_request=responses_request + ) except ProxyException as e: if e.type != _PROVIDER_COUNT_ERROR_TYPE: raise diff --git a/litellm/proxy/route_llm_request.py b/litellm/proxy/route_llm_request.py index 8bab7215b17..25f9f1dff15 100644 --- a/litellm/proxy/route_llm_request.py +++ b/litellm/proxy/route_llm_request.py @@ -2,13 +2,14 @@ import asyncio from collections.abc import Mapping from dataclasses import dataclass from types import MappingProxyType -from typing import TYPE_CHECKING, Any, Final, Literal +from typing import TYPE_CHECKING, Annotated, Any, Final, Literal import httpx from fastapi import HTTPException, status -from pydantic import TypeAdapter, ValidationError +from pydantic import BeforeValidator, TypeAdapter, ValidationError import litellm +from litellm.litellm_core_utils.core_helpers import normalize_drop_params from litellm.proxy._types import ProxyException, UserAPIKeyAuth from litellm.router_utils.common_utils import is_proxy_admin_request @@ -38,6 +39,21 @@ else: LitellmRouter = Any +_PER_REQUEST_ROUTER_SETTINGS: Final = ( + "fallbacks", + "context_window_fallbacks", + "content_policy_fallbacks", + "num_retries", + "timeout", + "model_group_retry_policy", + "routing_strategy", + "enable_tag_filtering", +) +_ROUTER_ONLY_SETTINGS: Final = frozenset( + ("fallbacks", "context_window_fallbacks", "content_policy_fallbacks", "model_group_retry_policy") +) + + def _route_user_config_request(data: dict, route_type: str): """Route a request using the user-provided router config.""" router_config: Final = data.pop("user_config") @@ -95,6 +111,7 @@ ROUTE_ENDPOINT_MAPPING: Final = { "asearch": "/search", "adecisions": "/decisions", "asystemone": "/systemone", + "aextraction": "/extraction", "avideo_generation": "/videos", "avideo_list": "/videos", "avideo_status": "/videos/{video_id}", @@ -204,6 +221,18 @@ REQUIRED_ONE_OF_BODY_PARAMS_BY_ROUTE: Final[Mapping[str, tuple[str, str]]] = Map ) JSON_OBJECT_ADAPTER: Final[TypeAdapter[dict[str, object]]] = TypeAdapter(dict[str, object]) +_OPTIONAL_JSON_OBJECT_ADAPTER: Final[TypeAdapter[Mapping[str, object] | None]] = TypeAdapter( + Mapping[str, object] | None +) + + +def _none_unless_json_object(value: object) -> object: + return value if isinstance(value, Mapping) else None + + +_JSON_OBJECT_OR_DROPPED_ADAPTER: Final[TypeAdapter[Mapping[str, object] | None]] = TypeAdapter( + Annotated[Mapping[str, object] | None, BeforeValidator(_none_unless_json_object)] +) class ProxyMissingRequiredParamError(ProxyException): @@ -545,6 +574,7 @@ RouteType = Literal[ "asearch", "adecisions", "asystemone", + "aextraction", "avideo_generation", "avideo_list", "avideo_status", @@ -596,6 +626,43 @@ RouteType = Literal[ ] +def _merge_router_settings_override( + data: dict[str, object], # mutable-ok: route_request mutates the shared request body in place +) -> frozenset[str]: + data.pop("enable_tag_filtering", None) + drop_params: Final = litellm.drop_params is True or normalize_drop_params(data.get("drop_params")) is True + router_settings_override_adapter: Final = ( + _JSON_OBJECT_OR_DROPPED_ADAPTER if drop_params else _OPTIONAL_JSON_OBJECT_ADAPTER + ) + try: + router_settings_override: Final = router_settings_override_adapter.validate_python( + data.pop("router_settings_override", None) + ) + except ValidationError: + raise ProxyException( + message="router_settings_override must be a JSON object.", + type="invalid_request_error", + param="router_settings_override", + code=status.HTTP_400_BAD_REQUEST, + ) from None + if "user_config" in data and data["user_config"] is None: + data.pop("user_config") + user_config: Final = _JSON_OBJECT_OR_DROPPED_ADAPTER.validate_python(data.get("user_config")) + router_settings_from_override: Final = MappingProxyType( + { + key: router_settings_override[key] + for key in _PER_REQUEST_ROUTER_SETTINGS + if router_settings_override.get(key) is not None + and key not in data + and (user_config is None or key not in user_config) + } + if router_settings_override is not None + else {} + ) + data.update(router_settings_from_override) + return _ROUTER_ONLY_SETTINGS.intersection(router_settings_from_override) + + async def route_request( data: dict, llm_router: LitellmRouter | None, @@ -606,12 +673,14 @@ async def route_request( """ Common helper to route the request """ + router_only_settings_from_override: Final = _merge_router_settings_override(data) # pyright: ignore[reportUnknownArgumentType] # route_request takes an untyped dict body try: return await _route_request_single_attempt( data=data, llm_router=llm_router, user_model=user_model, route_type=route_type, + router_only_settings_from_override=router_only_settings_from_override, user_api_key_dict=user_api_key_dict, ) except (ProxyModelNotFoundError, ProxyMissingParamWithoutLoadedModelError) as e: @@ -634,6 +703,7 @@ async def route_request( llm_router=proxy_server.llm_router, user_model=user_model, route_type=route_type, + router_only_settings_from_override=router_only_settings_from_override, user_api_key_dict=user_api_key_dict, ) @@ -643,6 +713,7 @@ async def _route_request_single_attempt( # noqa: ANN202 # returns unawaited pr llm_router: LitellmRouter | None, user_model: str | None, route_type: RouteType, + router_only_settings_from_override: frozenset[str], user_api_key_dict: UserAPIKeyAuth | None = None, ): raise_if_required_body_param_missing(route_type=route_type, data=data, llm_router=llm_router) @@ -651,9 +722,14 @@ async def _route_request_single_attempt( # noqa: ANN202 # returns unawaited pr raise_if_mock_testing_params_disallowed(data, allowed=mock_testing_params_allowed()) - data.pop("enable_tag_filtering", None) - if "user_config" in data and data["user_config"] is None: - data.pop("user_config") # pyright: ignore[reportUnknownMemberType] # route_request takes an untyped dict body + def direct_litellm_kwargs() -> Mapping[str, object]: + return MappingProxyType( + { + key: value + for key, value in JSON_OBJECT_ADAPTER.validate_python(data).items() + if key not in router_only_settings_from_override + } + ) team_id: Final = get_team_id_from_data(data) router_model_names: Final = llm_router.model_names if llm_router is not None else [] @@ -668,7 +744,7 @@ async def _route_request_single_attempt( # noqa: ANN202 # returns unawaited pr if llm_router is not None: return getattr(llm_router, f"{route_type}")(**data) else: - return getattr(litellm, f"{route_type}")(**data) + return getattr(litellm, f"{route_type}")(**direct_litellm_kwargs()) elif ( route_type == "acompletion" @@ -687,34 +763,6 @@ async def _route_request_single_attempt( # noqa: ANN202 # returns unawaited pr elif "user_config" in data: return _route_user_config_request(data, route_type) - elif "router_settings_override" in data: - # Apply per-request router settings overrides from key/team config - # Instead of creating a new Router (expensive), merge settings into kwargs - # The Router already supports per-request overrides for these settings - override_settings: Final = data.pop("router_settings_override") - - # Settings that the Router accepts as per-request kwargs - # These override the global router settings for this specific request - per_request_settings: Final = [ - "fallbacks", - "context_window_fallbacks", - "content_policy_fallbacks", - "num_retries", - "timeout", - "model_group_retry_policy", - "routing_strategy", - "enable_tag_filtering", - ] - - for key in per_request_settings: - if override_settings.get(key) is not None and key not in data: - data[key] = override_settings[key] - - # Use main router with overridden kwargs - if llm_router is not None: - return getattr(llm_router, f"{route_type}")(**data) - else: - return getattr(litellm, f"{route_type}")(**data) elif llm_router is not None: _raise_if_model_fully_blocked(llm_router=llm_router, model_name=data.get("model"), team_id=team_id) # Evals API: always route to litellm directly (not through router) @@ -755,7 +803,7 @@ async def _route_request_single_attempt( # noqa: ANN202 # returns unawaited pr # If we can't get deployment creds, continue without them pass - return getattr(litellm, f"{route_type}")(**data) + return getattr(litellm, f"{route_type}")(**direct_litellm_kwargs()) # Skip model-based routing for container operations if route_type in [ "acreate_container", @@ -806,7 +854,7 @@ async def _route_request_single_attempt( # noqa: ANN202 # returns unawaited pr "aingest", ] and (data.get("model") is None or data.get("model") == ""): # These endpoints don't need a model, use custom_llm_provider directly - return getattr(litellm, f"{route_type}")(**data) + return getattr(litellm, f"{route_type}")(**direct_litellm_kwargs()) if "model" not in data: raise ProxyMissingRequiredParamError( @@ -845,7 +893,7 @@ async def _route_request_single_attempt( # noqa: ANN202 # returns unawaited pr # Check wildcards before checking deployment_names # Priority: 1. Exact model_name match, 2. Wildcard match, 3. deployment_names match if llm_router.router_general_settings.pass_through_all_models: - return getattr(litellm, f"{route_type}")(**data) + return getattr(litellm, f"{route_type}")(**direct_litellm_kwargs()) elif llm_router.default_deployment is not None or len(llm_router.pattern_router.patterns) > 0: return getattr(llm_router, f"{route_type}")(**data) elif data["model"] in llm_router.deployment_names: @@ -897,7 +945,7 @@ async def _route_request_single_attempt( # noqa: ANN202 # returns unawaited pr return getattr(llm_router, f"{route_type}")(**data) except Exception: # If router fails (e.g., model not found in router), fall back to direct call - return getattr(litellm, f"{route_type}")(**data) + return getattr(litellm, f"{route_type}")(**direct_litellm_kwargs()) elif _is_a2a_agent_model(data.get("model", "")): from litellm.proxy.agent_endpoints.a2a_routing import ( route_a2a_agent_request, @@ -909,7 +957,7 @@ async def _route_request_single_attempt( # noqa: ANN202 # returns unawaited pr # Fall through to raise exception below if result is None elif user_model is not None or route_type == "allm_passthrough_route": - return getattr(litellm, f"{route_type}")(**data) + return getattr(litellm, f"{route_type}")(**direct_litellm_kwargs()) # if no route found then it's a bad request route_name: Final = ROUTE_ENDPOINT_MAPPING.get(route_type, route_type) diff --git a/litellm/proxy/spend_tracking/budget_reservation.py b/litellm/proxy/spend_tracking/budget_reservation.py index 4c9df95cd8d..803df9f83ca 100644 --- a/litellm/proxy/spend_tracking/budget_reservation.py +++ b/litellm/proxy/spend_tracking/budget_reservation.py @@ -228,29 +228,6 @@ def _raise_counter_budget_exceeded( ) -_UNBILLED_ROUTES: Final[frozenset[str]] = frozenset( - { - "/models", - "/v1/models", - "/utils/token_counter", - "/responses/input_tokens", - "/v1/responses/input_tokens", - "/openai/v1/responses/input_tokens", - } -) -_TOKEN_COUNTING_SEGMENTS: Final[frozenset[str]] = frozenset({"count_tokens", "count-tokens"}) -_TOKEN_COUNTING_ACTION: Final = "countTokens" - - -def _is_token_counting_route(route: str) -> bool: - resource, _, action = route.rsplit("/", 1)[-1].partition(":") - return resource in _TOKEN_COUNTING_SEGMENTS or action == _TOKEN_COUNTING_ACTION - - -def _is_unbilled_route(route: str) -> bool: - return route in _UNBILLED_ROUTES or _is_token_counting_route(route) - - async def reserve_budget_for_request( request_body: dict, route: str, @@ -269,7 +246,7 @@ async def reserve_budget_for_request( ) -> dict | None: if valid_token is None or not RouteChecks.is_llm_api_route(route=route): return None - if _is_unbilled_route(route): + if RouteChecks.is_unbilled_route(route): return None if get_model_from_request(request_body, route, llm_router=llm_router) is None: return None diff --git a/litellm/proxy/spend_tracking/spend_management_endpoints.py b/litellm/proxy/spend_tracking/spend_management_endpoints.py index 31732f2dbc9..84278f4619d 100644 --- a/litellm/proxy/spend_tracking/spend_management_endpoints.py +++ b/litellm/proxy/spend_tracking/spend_management_endpoints.py @@ -16,7 +16,6 @@ from typing import ( NamedTuple, Protocol, TypeAlias, - TypedDict, TypeVar, cast, # noqa: TID251 # custom-logger and cold-storage payloads are untyped JSON ) @@ -24,7 +23,7 @@ from typing import ( import fastapi from fastapi import APIRouter, Depends, HTTPException, Request, Response, status from pydantic import TypeAdapter -from typing_extensions import ReadOnly, assert_never +from typing_extensions import ReadOnly, TypedDict, assert_never import litellm from litellm._logging import verbose_proxy_logger @@ -2721,7 +2720,7 @@ async def ui_view_spend_logs( end_date_obj = parse_date(end_date) # Build where conditions - where_conditions: Final[dict[str, Any]] = {} + where_conditions: Final[dict[str, object]] = {} if start_date_obj is not None and end_date_obj is not None: where_conditions["startTime"] = { "gte": start_date_obj.isoformat(), # Already in UTC, no need to add Z @@ -2783,18 +2782,14 @@ async def ui_view_spend_logs( if len(metadata_filters) == 1: where_conditions["metadata"] = metadata_filters[0] else: - where_conditions["AND"] = where_conditions.get("AND", []) + [ - {"metadata": filter_cond} for filter_cond in metadata_filters - ] + where_conditions["AND"] = [{"metadata": filter_cond} for filter_cond in metadata_filters] if end_user is not None: where_conditions["end_user"] = end_user if min_spend is not None or max_spend is not None: - where_conditions["spend"] = {} - if min_spend is not None: - where_conditions["spend"]["gte"] = min_spend - if max_spend is not None: - where_conditions["spend"]["lte"] = max_spend + where_conditions["spend"] = { + key: value for key, value in (("gte", min_spend), ("lte", max_spend)) if value is not None + } # A request_id lookup drops the date window, so a non-admin could otherwise # reach any single row by id; require they own one of the matches, mirroring # the detail endpoint, and keep the general scoping below so a colliding diff --git a/litellm/proxy/spend_tracking/spend_tracking_utils.py b/litellm/proxy/spend_tracking/spend_tracking_utils.py index 091fb5d1305..62aee788ed0 100644 --- a/litellm/proxy/spend_tracking/spend_tracking_utils.py +++ b/litellm/proxy/spend_tracking/spend_tracking_utils.py @@ -15,6 +15,7 @@ from pydantic import BaseModel, JsonValue, TypeAdapter, ValidationError import litellm from litellm._logging import verbose_proxy_logger from litellm.constants import ( + BILLED_RETRY_ATTEMPT_METADATA_KEY, CALLER_SESSION_ID_METADATA_KEY, CLI_SESSION_KEY_PREFIX, EMPTY_MAPPING, @@ -187,6 +188,7 @@ _STAMPED_METADATA_KEYS: Final = frozenset( "used_client_oauth_token", KUBERNETES_POD_ROUTING_KEY, "litellm_roi_estimator", + BILLED_RETRY_ATTEMPT_METADATA_KEY, "user_api_key_user_email", ) ) @@ -249,6 +251,7 @@ def _get_spend_logs_metadata( guardrail_information=None, internal_call_origin=None, litellm_roi_estimator=False, + billed_retry_attempt=False, eval_information=None, cold_storage_object_key=cold_storage_object_key, litellm_overhead_time_ms=None, @@ -270,6 +273,8 @@ def _get_spend_logs_metadata( ) verbose_proxy_logger.debug("getting payload for SpendLogs, available keys in metadata: %s", [*metadata]) + retry_key: Final = BILLED_RETRY_ATTEMPT_METADATA_KEY + billed_retry_attempt: Final = retry_key in metadata and metadata[retry_key] is True # Filter the metadata dictionary to include only the specified keys clean_metadata: Final = SpendLogsMetadata( **MappingProxyType( @@ -283,6 +288,7 @@ def _get_spend_logs_metadata( used_client_oauth_token=used_client_oauth_token, kubernetes_pod_routing=kubernetes_pod_routing, litellm_roi_estimator=metadata.get("litellm_roi_estimator") is True, + billed_retry_attempt=billed_retry_attempt, user_api_key_user_email=_stored_user_email(metadata), ) _raw_key: Final = clean_metadata.get("user_api_key") @@ -453,7 +459,12 @@ def _sl_attribution_fallback( def _deployment_provider(deployment: DeploymentTypedDict) -> str | None: - litellm_params: Final = LiteLLM_Params.model_validate(deployment["litellm_params"]) + litellm_params: Final[LiteLLM_Params] = LiteLLM_Params.model_validate(deployment["litellm_params"]) + return deployment_params_provider(litellm_params) + + +def deployment_params_provider(litellm_params: LiteLLM_Params) -> str | None: + """The provider a deployment's ``litellm_params`` authenticate against, None when its model cannot be resolved.""" if litellm.LiteLLMProxyChatConfig.should_use_litellm_proxy_by_default(litellm_params=litellm_params): return LlmProviders.LITELLM_PROXY.value declared: Final = declared_authenticating_provider(litellm_params.model, litellm_params.custom_llm_provider) diff --git a/litellm/proxy/utils.py b/litellm/proxy/utils.py index a8bd35644c9..b5101898bb1 100644 --- a/litellm/proxy/utils.py +++ b/litellm/proxy/utils.py @@ -62,6 +62,7 @@ from litellm.constants import ( LITELLM_LOGGING_NO_UPSTREAM_LLM_CALL, MAX_TEAM_LIST_LIMIT, PROXY_REJECTED_BEFORE_ROUTING_KEY, + REDACTED_BY_LITELLM, REDIS_SPEND_LOGS_BUFFER_DEQUEUE_COUNT, SPEND_LOG_QUEUE_MAX_BYTES, SPEND_LOG_WRITE_BATCH_MAX_BYTES, @@ -90,7 +91,7 @@ from litellm.proxy.common_utils.openai_error_payload import ( from litellm.proxy.spend_tracking.spend_log_error_logger import spend_log_error from litellm.types.guardrails import GuardrailEventHooks from litellm.types.proxy.model_listing import ModelInfoResponse -from litellm.types.utils import MCP_GUARDRAIL_CALL_TYPES, CallTypes, CallTypesLiteral, CostPerToken, ModelInfo, Usage +from litellm.types.utils import MCP_GUARDRAIL_CALL_TYPES, CallTypes, CallTypesLiteral, ModelInfo, Usage try: from litellm_enterprise.enterprise_callbacks.send_emails.base_email import ( @@ -158,6 +159,7 @@ from litellm.litellm_core_utils.core_helpers import ( from litellm.litellm_core_utils.duration_parser import get_budget_window_start from litellm.litellm_core_utils.env_utils import get_env_float, get_env_int from litellm.litellm_core_utils.litellm_logging import Logging, deployment_pricing_model_info +from litellm.litellm_core_utils.llm_cost_calc.utils import generic_cost_per_token from litellm.litellm_core_utils.safe_json_dumps import safe_dumps from litellm.litellm_core_utils.safe_json_loads import safe_json_loads from litellm.litellm_core_utils.served_output_texts import ( @@ -267,6 +269,7 @@ from litellm.repositories.verification_token_repository import ( VerificationTokenRepository, ) from litellm.router_utils.common_utils import resolve_model_group_alias +from litellm.router_utils.deployment_pricing import pricing_models from litellm.secret_managers.main import str_to_bool from litellm.types.integrations.slack_alerting import DEFAULT_ALERT_TYPES from litellm.types.llms.openai import ResponsesAPIResponse @@ -502,7 +505,7 @@ class InternalUsageCache: key: str, local_only: bool = False, **kwargs: object, - ) -> Any: + ) -> object: return self.dual_cache.get_cache( key=key, local_only=local_only, @@ -1031,9 +1034,7 @@ def _failure_usage_to_lift( at the rate the router registered under ``deployment_id`` (``Logging.get_router_model_id``) when the deployment declares one, else the cost map's rate for ``base_model`` (an Azure deployment's ``model_info.base_model``) or the deployment model; any other post-dispatch - failure stays at zero cost. The raw request body backfills - the system prompt when the SDK bridges an endpoint (e.g. /v1/messages on a - chat-completions provider) without filling optional_params. Returns the + failure stays at zero cost. Returns the (combined_usage_object, response_cost) pair to lift, or None.""" recovered_usage: Final = model_call_details.get("combined_usage_object") failed_attempts: Final = _FAILED_ATTEMPTS_USAGE.validate_python(model_call_details.get("failed_attempts_usage", ())) @@ -1047,20 +1048,7 @@ def _failure_usage_to_lift( # The proxy-only error handler stamps this flag on a client disconnect too, even though the # request had already reached the provider, so a billed failure keeps its estimate. return None - if str(model_call_details.get("call_type")) not in _INPUT_ESTIMABLE_CALL_TYPES: - return None - optional_params: Final = model_call_details.get("optional_params") - dispatched_system: Final = ( - (optional_params.get("system") or optional_params.get("instructions")) - if isinstance(optional_params, dict) - else None - ) - system_input: Final = dispatched_system or request_body.get("system") or request_body.get("instructions") - estimated_usage: Final = _estimate_dispatched_failure_usage( - model=str(model_call_details.get("model") or ""), - request_input=model_call_details.get("messages"), - system_input=system_input, - ) + estimated_usage: Final = _estimated_prompt_usage(model_call_details, request_body) if estimated_usage is None: return None if not provider_billed: @@ -1070,19 +1058,203 @@ def _failure_usage_to_lift( ) -def _deployment_cost_per_token(deployment_id: str | None, model: str) -> CostPerToken | None: - """The pricing the router registered for this deployment under its ``model_info.id``, read - through ``deployment_pricing_model_info`` exactly as the success path does; None means the - public cost map. The id is ``Logging.get_router_model_id()`` (the logging object's own - ``litellm_params``), never the flattened ``model_call_details`` copy a request body key can - overwrite.""" - model_info: Final = deployment_pricing_model_info(model_id=deployment_id, deployment_model=model) - if model_info is None: +def _estimated_prompt_usage( + model_call_details: Mapping[str, object], request_body: Mapping[str, object] +) -> Usage | None: + """The input-only Usage estimate for the prompt this request sent, or None when the call type has no + estimable input. The raw request body backfills the system prompt when the SDK bridges an endpoint + (e.g. /v1/messages on a chat-completions provider) without filling optional_params.""" + if str(model_call_details.get("call_type")) not in _INPUT_ESTIMABLE_CALL_TYPES: return None - return CostPerToken( - input_cost_per_token=model_info["input_cost_per_token"] or 0.0, - output_cost_per_token=model_info["output_cost_per_token"] or 0.0, + optional_params: Final = model_call_details.get("optional_params") + dispatched_system: Final = ( + (optional_params.get("system") or optional_params.get("instructions")) + if isinstance(optional_params, dict) + else None ) + system_input: Final = next( + ( + system + for system in (dispatched_system, request_body.get("system"), request_body.get("instructions")) + if system and system != REDACTED_BY_LITELLM + ), + None, + ) + return _estimate_dispatched_failure_usage( + model=str(model_call_details.get("model") or ""), + request_input=model_call_details.get("messages"), + system_input=system_input, + ) + + +@dataclass(frozen=True) +class BilledFailedAttempt: + """An earlier retry attempt the provider also billed, written as its own spend row.""" + + attempted_retries: int + deployment_id: str | None + usage: Usage + response_cost: float + + +_NO_RETRY_METADATA: Final[Mapping[str, object]] = MappingProxyType({}) + + +def _retry_metadata_bucket(litellm_params: Mapping[str, object] | None) -> Mapping[str, object]: + """The request metadata bucket the router writes retry state into, ``litellm_metadata`` when the + route carries one (/messages, /responses) and ``metadata`` otherwise, same order as the deployment id.""" + if litellm_params is None: + return _NO_RETRY_METADATA + for metadata_key in ("litellm_metadata", "metadata"): + metadata = litellm_params.get(metadata_key) + if isinstance(metadata, dict): + return cast("Mapping[str, object]", metadata) # cast-ok: untyped router dict, keys read with .get + return _NO_RETRY_METADATA + + +def _attempt_number(record: Mapping[str, object], index: int) -> int: + """The attempt a retry record describes: its own ``attempted_retries`` count, else its position.""" + recorded: Final = record.get("attempted_retries") + return recorded if isinstance(recorded, int) else index + + +def _retry_attempt_records(litellm_params: Mapping[str, object] | None) -> tuple[Mapping[str, object], ...]: + """The router's ``RetryAttemptRecord`` breadcrumbs, one per failed attempt, read from the same bucket.""" + if litellm_params is None: + return () + for metadata_key in ("litellm_metadata", "metadata"): + metadata = litellm_params.get(metadata_key) + if not isinstance(metadata, dict): + continue + records = cast("Mapping[str, object]", metadata).get("previous_models") # cast-ok: untyped router dict + if isinstance(records, (list, tuple)): + return tuple( + cast("Mapping[str, object]", record) # cast-ok: RetryAttemptRecord TypedDict, read with .get + for record in cast("Sequence[object]", records) # cast-ok: untyped router tuple + if isinstance(record, dict) + ) + return () + + +def _record_deployment_id(record: Mapping[str, object]) -> str | None: + deployment_id: Final = record.get("deployment_id") + return deployment_id if isinstance(deployment_id, str) else None + + +def _attempt_identity(record: Mapping[str, object]) -> tuple[str | None, int | None]: + """What tells one provider call from another across the request: the deployment that served it + and the retry count within its model group. Two records with the same identity describe the + same call (the fallback handler re-logs the attempt that exhausted the previous group).""" + attempted_retries: Final = record.get("attempted_retries") + return _record_deployment_id(record), attempted_retries if isinstance(attempted_retries, int) else None + + +def _timed_out_earlier_records( + litellm_params: Mapping[str, object] | None, final_identity: tuple[str | None, int | None] +) -> tuple[Mapping[str, object], ...]: + """The ``Timeout`` breadcrumbs for calls other than the final attempt, one per provider call.""" + by_identity: Final = { + _attempt_identity(record): record + for record in _retry_attempt_records(litellm_params) + if record.get("exception_type") == litellm.Timeout.__name__ + } + return tuple(record for identity, record in by_identity.items() if identity != final_identity) + + +def _record_pricing( + model_call_details: Mapping[str, object], record: Mapping[str, object], base_model: str | None +) -> tuple[Mapping[str, object], str | None]: + """The ``(model_call_details, base_model)`` to price one earlier attempt with: the record's own + deployment model and ``base_model`` when it served a different model than the final attempt + (the provider is then inferred from that model), else the final attempt's.""" + record_model: Final = record.get("model") + if not isinstance(record_model, str) or record_model == model_call_details.get("model"): + return model_call_details, base_model + record_base_model: Final = record.get("base_model") + return ( + {**model_call_details, "model": record_model, "custom_llm_provider": None}, + record_base_model if isinstance(record_base_model, str) else None, + ) + + +def _billed_earlier_attempt( + model_call_details: Mapping[str, object], + record: Mapping[str, object], + index: int, + estimated_usage: Usage, + base_model: str | None, +) -> BilledFailedAttempt: + pricing_details, pricing_base_model = _record_pricing(model_call_details, record, base_model) + return BilledFailedAttempt( + attempted_retries=_attempt_number(record, index), + deployment_id=_record_deployment_id(record), + usage=estimated_usage, + response_cost=_estimated_input_cost( + pricing_details, + estimated_usage.prompt_tokens, + deployment_id=_record_deployment_id(record), + base_model=pricing_base_model, + ), + ) + + +def _billed_earlier_attempts( + model_call_details: Mapping[str, object], + litellm_params: Mapping[str, object] | None, + estimated_usage: Usage, + base_model: str | None, + deployment_id: str | None, +) -> tuple[BilledFailedAttempt, ...]: + """Every earlier retry attempt the provider also billed. The router records one + ``RetryAttemptRecord`` per failed attempt in ``metadata.previous_models``, the final attempt + included, which the failure row itself bills. The final attempt is the record with the + request's own deployment and retry count (``attempted_retries`` restarts at 0 after a fallback + hop, so the count alone cannot tell the groups apart). An earlier attempt that ended in a + ``Timeout`` had the same prompt accepted by its deployment, so it is billed like the final + attempt, at that deployment's input rate (else the cost map's rate for the record's own + ``base_model`` or model, which a fallback hop can make a different model than the final one). + Only the exception class survives on the record, so an earlier connect timeout is billed too; + any other failure class is not.""" + final_attempt: Final = _retry_metadata_bucket(litellm_params).get("attempted_retries") + final_identity: Final = (deployment_id, final_attempt if isinstance(final_attempt, int) else None) + return tuple( + _billed_earlier_attempt(model_call_details, record, index, estimated_usage, base_model) + for index, record in enumerate(_timed_out_earlier_records(litellm_params, final_identity)) + ) + + +def _deployment_priced_input_cost( + model: str, custom_llm_provider: str | None, prompt_tokens: int, deployment_pricing: ModelInfo +) -> float: + """Input price for the estimated prompt at the deployment's registered rates, read through + ``deployment_pricing_model_info`` and priced by ``generic_cost_per_token`` the way the success + path prices them, so a long-context tier the deployment declares (``input_cost_per_token_above_200k_tokens``) + is honoured instead of flattened to the standard rate. An entry it cannot price keeps the row at $0.""" + usage: Final = Usage(prompt_tokens=prompt_tokens, completion_tokens=0, total_tokens=prompt_tokens) + try: + prompt_cost, _ = generic_cost_per_token( + model=model, + usage=usage, + custom_llm_provider=custom_llm_provider or str(deployment_pricing.get("litellm_provider") or ""), + model_info=deployment_pricing, + ) + except Exception as exc: # noqa: BLE001 # a malformed registered entry must not drop the failure row + verbose_proxy_logger.debug("failure spend estimate: could not price deployment of %s: %s", model, exc) + return 0.0 + return prompt_cost + + +def _priced_input_cost(pricing_model: str, custom_llm_provider: str | None, prompt_tokens: int) -> float | None: + try: + estimated_input_cost, _ = litellm.cost_per_token( + model=pricing_model, + custom_llm_provider=custom_llm_provider, + prompt_tokens=prompt_tokens, + ) + except Exception as exc: # noqa: BLE001 # cost_per_token raises BadRequestError for an unmapped model and the row must still be written + verbose_proxy_logger.debug("failure spend estimate: could not price %s: %s", pricing_model, exc) + return None + return estimated_input_cost def _estimated_input_cost( @@ -1091,24 +1263,22 @@ def _estimated_input_cost( deployment_id: str | None, base_model: str | None, ) -> float: - """Input price for the estimated prompt: the deployment's registered rate when it has one, else - the cost map's rate for ``base_model`` or the deployment model (an Azure deployment name is not - in the cost map, its ``base_model`` is). An unpriceable model keeps the row at $0 rather than - dropping the failure row.""" - try: - model: Final = str(model_call_details.get("model") or "") - estimated_input_cost, _ = litellm.cost_per_token( - model=base_model or model, - custom_llm_provider=str(model_call_details.get("custom_llm_provider") or "") or None, - prompt_tokens=prompt_tokens, - custom_cost_per_token=_deployment_cost_per_token(deployment_id, model), - ) - except Exception as exc: # noqa: BLE001 # cost_per_token raises BadRequestError for an unmapped model and the row must still be written - verbose_proxy_logger.debug( - "failure spend estimate: could not price %s: %s", model_call_details.get("model"), exc - ) - return 0.0 - return estimated_input_cost + """Input price for the estimated prompt: the deployment's registered rates when it has any (the id + is ``Logging.get_router_model_id()``, never the flattened ``model_call_details`` copy a request body + key can overwrite), else the cost map's rate for ``base_model``, else the deployment model, the same + candidate order ``completion_cost`` walks (an Azure deployment name is not in the cost map, its + ``base_model`` is; a ``base_model`` the cost map does not know falls through to the deployment + model). A model no candidate can price keeps the row at $0 rather than dropping the failure row.""" + model: Final = str(model_call_details.get("model") or "") + custom_llm_provider: Final = str(model_call_details.get("custom_llm_provider") or "") or None + deployment_pricing: Final = deployment_pricing_model_info(model_id=deployment_id, deployment_model=model) + if deployment_pricing is not None: + return _deployment_priced_input_cost(model, custom_llm_provider, prompt_tokens, deployment_pricing) + pricing_models_to_try: Final = pricing_models(base_model, model) + candidate_costs: Final = ( + _priced_input_cost(pricing_model, custom_llm_provider, prompt_tokens) for pricing_model in pricing_models_to_try + ) + return next((cost for cost in candidate_costs if cost is not None), 0.0) _EMPTY_LIFT: Final = MappingProxyType({}) @@ -1245,8 +1415,9 @@ def _timed_out_reading_from_provider(exception: Exception) -> bool: def _client_disconnected(exception: Exception) -> bool: - """The 499 the proxy raises when the caller hung up while the provider was still working on the request.""" - return getattr(exception, "status_code", None) == LITELLM_HTTP_STATUS_CLIENT_DISCONNECTED + """The 499 the proxy itself raises when the caller hung up while the provider was still working on the + request. A provider's own 499 arrives as a litellm exception and is a plain upstream failure.""" + return isinstance(exception, HTTPException) and exception.status_code == LITELLM_HTTP_STATUS_CLIENT_DISCONNECTED def _provider_billed_the_failure(exception: Exception) -> bool: @@ -1265,13 +1436,28 @@ def _failure_fields_to_lift(request_data: Mapping[str, object], provider_billed: return _EMPTY_LIFT _model_call_details: Final = getattr(_logging_obj, "model_call_details", {}) _first_handoff: Final = _model_call_details.get("first_api_call_start_time") + _litellm_params: Final = getattr(_logging_obj, "litellm_params", None) + _base_model: Final = get_base_model_from_metadata(model_call_details=_model_call_details) + _deployment_id: Final = _logging_obj.get_router_model_id() if isinstance(_logging_obj, Logging) else None + _success_already_logged: Final = isinstance(_logging_obj, Logging) and _logging_obj.async_success_log_enqueued + _billed: Final = provider_billed and not _success_already_logged _usage_to_lift: Final = _failure_usage_to_lift( model_call_details=_model_call_details, request_body=request_data, dispatched=_first_handoff is not None, - provider_billed=provider_billed, - deployment_id=_logging_obj.get_router_model_id() if isinstance(_logging_obj, Logging) else None, - base_model=get_base_model_from_metadata(model_call_details=_model_call_details), + provider_billed=_billed, + deployment_id=_deployment_id, + base_model=_base_model, + ) + _prompt_estimate: Final = ( + _estimated_prompt_usage(_model_call_details, request_data) + if _billed and _first_handoff is not None and not _model_call_details.get("failed_attempts_usage") + else None + ) + _earlier_attempts: Final = ( + _billed_earlier_attempts(_model_call_details, _litellm_params, _prompt_estimate, _base_model, _deployment_id) + if _prompt_estimate is not None + else () ) _entries: Final = ( ("start_time", _model_call_details.get("start_time")), @@ -1280,6 +1466,7 @@ def _failure_fields_to_lift(request_data: Mapping[str, object], provider_billed: ("combined_usage_object", None if _usage_to_lift is None else _usage_to_lift[0]), ("response_cost", None if _usage_to_lift is None else (_usage_to_lift[1] or 0.0)), ("standard_logging_object", _model_call_details.get("standard_logging_object")), + ("billed_failed_attempts", _earlier_attempts or None), ) return MappingProxyType({key: value for key, value in _entries if value is not None}) @@ -3707,6 +3894,7 @@ class ProxyLogging: original_exception, traceback_str, ), + kwargs={"for_async_request": True}, daemon=True, ).start() @@ -8375,7 +8563,11 @@ MAX_SPEND_LOG_ISOLATION_FAILURES_PER_BATCH: Final = 256 def _is_transient_spend_log_write_error(e: Exception) -> bool: - return PrismaDBExceptionHandler.is_database_transport_error(e) or PrismaDBExceptionHandler.is_deadlock_error(e) + return ( + PrismaDBExceptionHandler.is_database_transport_error(e) + or PrismaDBExceptionHandler.is_prisma_engine_internal_error(e) + or PrismaDBExceptionHandler.is_deadlock_error(e) + ) async def _create_spend_logs_with_poison_isolation( @@ -8409,7 +8601,7 @@ async def _create_spend_logs_with_poison_isolation( await repo.table.create_many(data=rows, skip_duplicates=True) return failure_budget except Exception as e: - if not PrismaDBExceptionHandler.is_prisma_data_error(e): + if not (PrismaDBExceptionHandler.is_prisma_data_error(e) or isinstance(e, UnicodeEncodeError)): raise if PrismaDBExceptionHandler.is_database_service_unavailable_error(e): raise diff --git a/litellm/responses/dispatch.py b/litellm/responses/dispatch.py index ad642fb427c..0dda3f93660 100644 --- a/litellm/responses/dispatch.py +++ b/litellm/responses/dispatch.py @@ -1,12 +1,17 @@ import inspect from collections.abc import Awaitable, Callable, Coroutine, Mapping +from types import MappingProxyType from typing import Final, TypeAlias, cast # noqa: TID251 # native binding selects a sync result or an async awaitable +from litellm.exceptions import BadRequestError +from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider from litellm.responses import main from litellm.responses.streaming_iterator import BaseResponsesAPIStreamingIterator -from litellm.rust_bridge.catalog import Route, RouteContext +from litellm.rust_bridge import detectors +from litellm.rust_bridge.catalog import Feature, Route, RouteContext from litellm.rust_bridge.dispatch import PublicDispatch from litellm.rust_bridge.public_call import ( + AsyncFlag, NativeCall, bind, native_call, @@ -14,6 +19,7 @@ from litellm.rust_bridge.public_call import ( optional_str, signature, ) +from litellm.rust_bridge.responses import detectors as route_detectors from litellm.rust_bridge.responses.entrypoints import ( NATIVE_ARESPONSES, NATIVE_RESPONSES, @@ -43,6 +49,7 @@ def _python_aresponses() -> PythonAresponses: _PYTHON_RESPONSES: Final = _python_responses() _RESPONSES: Final = signature(_PYTHON_RESPONSES) +_FLAG: Final = AsyncFlag("aresponses", sync=_RESPONSES) _PYTHON_ARESPONSES: Final = _python_aresponses() _ARESPONSES: Final = signature(_PYTHON_ARESPONSES) @@ -59,25 +66,64 @@ def _public_request( return native_call(legacy, args, kwargs) -def _context(request: NativeCall) -> RouteContext: +def _provider(request: NativeCall) -> str | None: + provider: Final = optional_str(request.resolved.get("custom_llm_provider")) + try: + return get_llm_provider(str(request.resolved["model"]), provider)[1] + except BadRequestError: + return provider + + +_FEATURES: Final[detectors.Detectors] = MappingProxyType( + { + **detectors.COMMON, + Feature.DROP_PARAMS: detectors.drop_params, + Feature.MODIFY_PARAMS: detectors.modify_params, + Feature.STREAMING: detectors.streaming, + Feature.PROMPT_MANAGEMENT: detectors.prompt_management, + Feature.TEXT_FORMAT: route_detectors.text_format, + Feature.CHAT_COMPLETIONS_BRIDGE: route_detectors.chat_completions_bridge, + Feature.RETRIES_FALLBACKS: detectors.retries_fallbacks, + Feature.DEPLOYMENT_RESPONSE_ID: route_detectors.deployment_response_id, + Feature.ENCODED_ITEM_IDS: route_detectors.encoded_item_ids, + Feature.INPUT_REWRITE: route_detectors.input_rewrite, + Feature.EXTRA_BODY: detectors.extra_body, + Feature.PROVIDER_AFFINITY: route_detectors.provider_affinity, + Feature.RESPONSE_CACHE: detectors.response_cache, + Feature.MANAGED_RESOURCE_IDS: route_detectors.managed_resource_ids, + Feature.CACHE_CONTROL_MARKS: route_detectors.cache_control_marks, + Feature.ANTHROPIC_TOOL_SEARCH: route_detectors.anthropic_tool_search, + Feature.TOOL_SCHEMA_REPAIR: route_detectors.tool_schema_repair, + Feature.MODEL_PARAM_GATING: route_detectors.model_param_gating, + Feature.WORKLOAD_IDENTITY: route_detectors.openai_workload_identity, + Feature.CLIENT_HEADERS: route_detectors.client_headers, + } +) + +_SYNC_FEATURES: Final[detectors.Detectors] = MappingProxyType( + {**_FEATURES, Feature.DEPLOYMENT_HOOK: route_detectors.deployment_hook} +) + + +def _context(request: NativeCall, features: detectors.Detectors) -> RouteContext: return RouteContext( Route.RESPONSES, - provider=optional_str(request.resolved.get("custom_llm_provider")), + provider=_provider(request), model=str(request.resolved["model"]), + features=detectors.detected(features, request), ) _DISPATCH: Final = PublicDispatch( route=Route.RESPONSES, request=lambda args, kwargs: _public_request(_RESPONSES, args, kwargs), - context=_context, - bypass=lambda request: request.kwargs.get("aresponses") is True, + context=lambda request: _context(request, _SYNC_FEATURES), ) _ADISPATCH: Final = PublicDispatch( route=Route.RESPONSES, request=lambda args, kwargs: _public_request(_ARESPONSES, args, kwargs), - context=_context, + context=lambda request: _context(request, _FEATURES), ) @@ -86,9 +132,11 @@ def responses( **kwargs: object, # kwargs-ok: preserve the public Responses call shape ) -> ResponsesResult | Coroutine[object, object, ResponsesResult]: python: Final = _PYTHON_RESPONSES + if _FLAG.requested(kwargs): + return aresponses(**_FLAG.keywords(args, kwargs)) return _DISPATCH.run( args, - kwargs, + _FLAG.dropped(kwargs), python=python, binding=NATIVE_RESPONSES, native=native_call_hook, @@ -99,7 +147,7 @@ async def aresponses(*args: object, **kwargs: object) -> ResponsesResult: # kwa python: Final = _PYTHON_ARESPONSES return await _ADISPATCH.arun( args, - kwargs, + _FLAG.dropped(kwargs), python=python, binding=NATIVE_ARESPONSES, native=native_call_hook, diff --git a/litellm/responses/file_search/emulated_handler.py b/litellm/responses/file_search/emulated_handler.py index e2bb2ae40ea..7121908517b 100644 --- a/litellm/responses/file_search/emulated_handler.py +++ b/litellm/responses/file_search/emulated_handler.py @@ -45,7 +45,7 @@ class FileSearchToolCallArgs(TypedDict): def should_use_emulated_file_search( - tools: Iterable[ToolParam] | None, + tools: Iterable[object] | None, provider_config: "BaseResponsesAPIConfig | None", ) -> bool: """Return True when there is a file_search tool and the provider can't handle it natively.""" @@ -105,7 +105,7 @@ def _build_function_tool(vector_store_ids: list[str]) -> dict[str, object]: } -def _replace_file_search_tools( +def replace_file_search_tools( tools: Iterable[ToolParam] | None, ) -> tuple[list[object], list[str]]: """ @@ -529,7 +529,7 @@ async def aresponses_with_emulated_file_search( _include_search_results, call_kwargs = _prepare_emulated_file_search_call(kwargs=kwargs) # 1. Replace file_search tools with function tool - transformed_tools, all_vs_ids = _replace_file_search_tools(tools) + transformed_tools, all_vs_ids = replace_file_search_tools(tools) # 2. First provider call — provider will call the file_search function. # Mark as an internal sub-call so wrapper_async skips billing callbacks; diff --git a/litellm/responses/litellm_completion_transformation/count_request.py b/litellm/responses/litellm_completion_transformation/count_request.py new file mode 100644 index 00000000000..56a0b9024c5 --- /dev/null +++ b/litellm/responses/litellm_completion_transformation/count_request.py @@ -0,0 +1,207 @@ +from collections.abc import Mapping +from dataclasses import dataclass +from typing import Final, cast # noqa: TID251 # input items are forwarded as sent, as inference does + +from pydantic import BaseModel, JsonValue, TypeAdapter, ValidationError + +from litellm.exceptions import BadRequestError +from litellm.litellm_core_utils.core_helpers import as_str_mapping +from litellm.litellm_core_utils.prompt_templates.common_utils import ( + update_responses_input_with_model_file_ids, + update_responses_tools_with_model_file_ids, +) +from litellm.litellm_core_utils.tool_fields import DropPolicy +from litellm.llms.base_llm.files.batch_records import responses_batch_body_to_chat_body +from litellm.responses.additional_tools import hoist_additional_tools +from litellm.responses.file_search.emulated_handler import replace_file_search_tools +from litellm.responses.litellm_completion_transformation.transformation import LiteLLMCompletionResponsesConfig +from litellm.responses.main import previous_response_client_ids +from litellm.types.llms.openai import ResponseInputParam +from litellm.utils import ProviderConfigManager + +_COUNTED_CHAT_PARAMS: Final = ( + "tool_choice", + "parallel_tool_calls", + "response_format", + "web_search_options", + "reasoning_effort", +) +_ITEMS: Final[TypeAdapter[tuple[object, ...]]] = TypeAdapter(tuple[object, ...]) +_MAPPINGS: Final[TypeAdapter[tuple[Mapping[str, object], ...]]] = TypeAdapter(tuple[Mapping[str, object], ...]) +_JSON_PARAMS: Final[TypeAdapter[Mapping[str, JsonValue]]] = TypeAdapter(Mapping[str, JsonValue]) +_ENTRY: Final[TypeAdapter[Mapping[str, object]]] = TypeAdapter(Mapping[str, object]) +_MARKED_ENTRY_LISTS: Final = frozenset({"content", "tool_calls"}) +_FILE_ID_MAPPING: Final[TypeAdapter[Mapping[str, Mapping[str, str]] | None]] = TypeAdapter( + Mapping[str, Mapping[str, str]] | None +) +MODEL_FILE_ID_MAPPING_FIELD: Final = "model_file_id_mapping" + + +@dataclass(frozen=True, slots=True) +class ChatCountRequest: + messages: tuple[Mapping[str, object], ...] + tools: tuple[Mapping[str, object], ...] | None + params: Mapping[str, JsonValue] + + +@dataclass(frozen=True, slots=True) +class ChatCountBridgeError: + message: str + + +def _plain(item: object) -> object: + return item.model_dump(exclude_none=True) if isinstance(item, BaseModel) else item + + +def _mappings(value: object) -> tuple[Mapping[str, object], ...]: + return _MAPPINGS.validate_python(tuple(_plain(item) for item in _ITEMS.validate_python(value or ()))) + + +def _unmarked(entry: Mapping[str, object]) -> Mapping[str, object]: + return { + key: _unmarked_entries(value) if key in _MARKED_ENTRY_LISTS else value + for key, value in entry.items() + if key != "cache_control" + } + + +def _unmarked_entries(value: object) -> object: + return ( + [ + _unmarked(_ENTRY.validate_python(item)) if isinstance(item, Mapping) else item + for item in _ITEMS.validate_python(value) + ] + if isinstance(value, list) + else value + ) + + +def _routed_model_id(deployment: Mapping[str, object] | None) -> str | None: + model_info: Final = as_str_mapping(None if deployment is None else deployment.get("model_info")) or {} + model_id: Final = model_info.get("id") + return model_id if isinstance(model_id, str) else None + + +def with_provider_file_ids( + responses_request: Mapping[str, object], deployment: Mapping[str, object] | None +) -> Mapping[str, object]: + mapping: Final = _FILE_ID_MAPPING.validate_python(responses_request.get(MODEL_FILE_ID_MAPPING_FIELD)) + model_id: Final = _routed_model_id(deployment) + fields: Final = {name: value for name, value in responses_request.items() if name != MODEL_FILE_ID_MAPPING_FIELD} + tools: Final = fields.get("tools") + return { + **fields, + **( + {"input": update_responses_input_with_model_file_ids(fields["input"], model_id, mapping)} + if "input" in fields + else {} + ), + **( + { + "tools": update_responses_tools_with_model_file_ids( + cast(list[dict[str, object]], tools), # cast-ok: entries that are not tools pass through as sent + model_id, + mapping, + ) + } + if isinstance(tools, list) + else {} + ), + } + + +def _with_hoisted_additional_tools(responses_request: Mapping[str, object]) -> Mapping[str, object]: + responses_input: Final = responses_request.get("input") + if not isinstance(responses_input, list): + return responses_request + input_items: Final = cast(ResponseInputParam, responses_input) # cast-ok: forwarded as sent, as inference does + hoisted: Final = hoist_additional_tools(input_items, None) + if not hoisted.hoisted: + return responses_request + return { + **responses_request, + "input": hoisted.input, + "tools": [*_ITEMS.validate_python(responses_request.get("tools") or ()), *hoisted.hoisted], + } + + +def _with_emulated_file_search(responses_request: Mapping[str, object]) -> Mapping[str, object]: + tools: Final = responses_request.get("tools") + if tools is None: + return responses_request + return {**responses_request, "tools": replace_file_search_tools(_ITEMS.validate_python(tools))[0]} + + +async def _with_previous_turns( + chat_body: Mapping[str, object], + model: str, + custom_llm_provider: str, + responses_request: Mapping[str, object], + policy: DropPolicy, +) -> Mapping[str, object]: + previous_response_id: Final = responses_request.get("previous_response_id") + if not isinstance(previous_response_id, str) or not previous_response_id: + return chat_body + instructions: Final = responses_request.get("instructions") + return await LiteLLMCompletionResponsesConfig.async_responses_api_session_handler( # pyright: ignore[reportUnknownMemberType] # the session handler takes a bare dict request + previous_response_id=previous_response_id, + litellm_completion_request={**chat_body, "model": model, "custom_llm_provider": custom_llm_provider}, + instructions=instructions if isinstance(instructions, str) else None, + request_kwargs={"drop_params": policy.drop_params}, + previous_response_client_ids=previous_response_client_ids(previous_response_id, responses_request), + ) + + +def _counted_params( + chat_body: Mapping[str, object], tools: tuple[Mapping[str, object], ...], policy: DropPolicy +) -> Mapping[str, JsonValue]: + sent: Final = { + name: chat_body[name] + for name in _COUNTED_CHAT_PARAMS + if chat_body.get(name) is not None and name not in policy.additional_drop_params + } + return _JSON_PARAMS.validate_python( + {**sent, **({"drop_params": True} if policy.drop_params and (sent or tools) else {})} + ) + + +async def chat_count_request( + model: str, + custom_llm_provider: str | None, + api_base: str | None, + responses_request: Mapping[str, object], + policy: DropPolicy, +) -> ChatCountRequest | ChatCountBridgeError | None: + """The chat request Responses inference sends a provider with no native Responses API, or None + when inference sends this provider the Responses body itself.""" + if custom_llm_provider is None or ( + ProviderConfigManager.get_provider_responses_api_config( + provider=custom_llm_provider, model=model, api_base=api_base + ) + is not None + ): + return None + try: + chat_body: Final = await _with_previous_turns( + responses_batch_body_to_chat_body( + _with_emulated_file_search(_with_hoisted_additional_tools(responses_request)), + custom_llm_provider, + policy.drop_params, + ), + model, + custom_llm_provider, + responses_request, + policy, + ) + tools: Final = ( + () if "tools" in policy.additional_drop_params else tuple(map(_unmarked, _mappings(chat_body.get("tools")))) + ) + return ChatCountRequest( + messages=tuple(map(_unmarked, _mappings(chat_body.get("messages")))), + tools=tools or None, + params=_counted_params(chat_body, tools, policy), + ) + except BadRequestError as e: + return ChatCountBridgeError(message=str(e.message)) + except (ValidationError, ValueError, KeyError) as e: + return ChatCountBridgeError(message=f"Invalid request for token counting: {e}") diff --git a/litellm/responses/litellm_completion_transformation/session_handler.py b/litellm/responses/litellm_completion_transformation/session_handler.py index 615bdb5bbfb..35160830fdc 100644 --- a/litellm/responses/litellm_completion_transformation/session_handler.py +++ b/litellm/responses/litellm_completion_transformation/session_handler.py @@ -1,6 +1,6 @@ import asyncio import json -from collections.abc import Mapping +from collections.abc import Mapping, Sequence from typing import TYPE_CHECKING, Any, Final, cast import litellm @@ -71,6 +71,14 @@ def _stored_instructions(proxy_server_request: Mapping[str, object] | None) -> s return instructions if isinstance(instructions, str) and instructions else None +def _latest_replayable_instructions(proxy_server_requests: Sequence[Mapping[str, object] | None]) -> str | None: + latest: Final = next( + (instructions for instructions in map(_stored_instructions, reversed(proxy_server_requests)) if instructions), + None, + ) + return None if latest == REDACTED_BY_LITELLM else latest + + class ResponsesSessionHandler: @staticmethod async def get_chat_completion_message_history_for_previous_response_id( @@ -127,14 +135,7 @@ class ResponsesSessionHandler: return ChatCompletionSession( messages=chat_completion_message_history, litellm_session_id=litellm_session_id, - instructions=next( - ( - instructions - for instructions in map(_stored_instructions, reversed(proxy_server_requests)) - if instructions - ), - None, - ), + instructions=_latest_replayable_instructions(proxy_server_requests), ) @staticmethod diff --git a/litellm/responses/litellm_completion_transformation/streaming_iterator.py b/litellm/responses/litellm_completion_transformation/streaming_iterator.py index 5c9e5cac5ab..84d4648f75f 100644 --- a/litellm/responses/litellm_completion_transformation/streaming_iterator.py +++ b/litellm/responses/litellm_completion_transformation/streaming_iterator.py @@ -22,7 +22,7 @@ from litellm.responses.litellm_completion_transformation.tool_search import ( from litellm.responses.litellm_completion_transformation.transformation import ( LiteLLMCompletionResponsesConfig, ) -from litellm.responses.streaming_iterator import ResponsesAPIStreamingIterator +from litellm.responses.streaming_iterator import ResponsesAPIStreamingIterator, stamp_responses_usage_cost from litellm.responses.utils import ResponsesAPIRequestUtils from litellm.types.llms.openai import ( PART_UNION_TYPES, @@ -1363,6 +1363,43 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): return False return not any(getattr(part, "text", None) for part in getattr(item, "content", None) or ()) + def partial_response_on_disconnect(self) -> ResponseIncompleteEvent | None: + """ + The response.incomplete event to bill when the client went away mid-stream. + Built from the chat completion chunks relayed so far, so the usage is what + stream_chunk_builder counts for them. + """ + if self.completed_response is not None or not self.collected_chat_completion_chunks: + return None + built: Final = stream_chunk_builder( + chunks=self.collected_chat_completion_chunks, + messages=LiteLLMCompletionResponsesConfig.transform_responses_api_input_to_messages( # pyright: ignore[reportUnknownMemberType] # the transformer's signature is partially untyped + input=self.request_input, + responses_api_request=dict(self.responses_api_request), + ), + logging_obj=self.litellm_logging_obj, + ) + if not isinstance(built, ModelResponse): + return None + responses_api_response: Final = ( + LiteLLMCompletionResponsesConfig.transform_chat_completion_response_to_responses_api_response( # pyright: ignore[reportUnknownMemberType] # the transformer's signature is partially untyped + request_input=self.request_input, + chat_completion_response=built, + responses_api_request=self.responses_api_request, + ) + ) + partial: Final = self._with_encoded_response_id( + responses_api_response.model_copy( + update={ + "id": self._cached_response_id or responses_api_response.id, + "status": "incomplete", + "output": list(self._output_with_streamed_item_ids(responses_api_response)), + } + ) + ) + stamp_responses_usage_cost(partial, self.litellm_logging_obj) + return ResponseIncompleteEvent(type=ResponsesAPIStreamEvents.RESPONSE_INCOMPLETE, response=partial) + def _emit_terminal_response_event( self, litellm_model_response: ModelResponse ) -> ResponseCompletedEvent | ResponseIncompleteEvent | None: diff --git a/litellm/responses/litellm_completion_transformation/transformation.py b/litellm/responses/litellm_completion_transformation/transformation.py index b613b817225..d9ebf50cc1a 100644 --- a/litellm/responses/litellm_completion_transformation/transformation.py +++ b/litellm/responses/litellm_completion_transformation/transformation.py @@ -1005,7 +1005,7 @@ class LiteLLMCompletionResponsesConfig: session_lookup: Callable[[str], Awaitable[ChatCompletionSession]] | None = None, request_kwargs: Mapping[str, object] = MappingProxyType({}), previous_response_client_ids: tuple[str, ...] = (), - ) -> dict: + ) -> dict[str, object]: """ Async hook to get the chain of previous input and output pairs and return a list of Chat Completion messages """ diff --git a/litellm/responses/main.py b/litellm/responses/main.py index 51cd3be1b63..3bdb1c9c375 100644 --- a/litellm/responses/main.py +++ b/litellm/responses/main.py @@ -306,7 +306,7 @@ async def aresponses_api_with_mcp( joins_request_trace and not stream and previous_response_id is None - and not _provider_stores_the_first_round(model, custom_llm_provider, kwargs) + and not provider_stores_the_conversation(model, custom_llm_provider, kwargs) ) listing_trace_id: Final = ( @@ -463,7 +463,7 @@ async def aresponses_api_with_mcp( if tool_results: chains_on_first_round: Final = not LiteLLM_Proxy_MCP_Handler.is_persistence_disabled( call_params - ) and _provider_stores_the_first_round(model, custom_llm_provider, kwargs) + ) and provider_stores_the_conversation(model, custom_llm_provider, kwargs) follow_up_input: Final = LiteLLM_Proxy_MCP_Handler.create_follow_up_input( response=response, @@ -548,7 +548,7 @@ def _bridges_to_chat_completions( _RESPONSES_ONLY_REQUEST_FIELDS_NEVER_BRIDGED: Final = frozenset({"client_metadata"}) -def _previous_response_client_ids(previous_response_id: str | None, kwargs: Mapping[str, object]) -> tuple[str, ...]: +def previous_response_client_ids(previous_response_id: str | None, kwargs: Mapping[str, object]) -> tuple[str, ...]: """The forms of the previous response's id the client held, which its spend log row can be stored under.""" if not previous_response_id: return () @@ -687,8 +687,12 @@ def _will_bridge_to_chat_completions( ) -def _provider_stores_the_first_round(model: str, custom_llm_provider: str | None, kwargs: Mapping[str, object]) -> bool: - """A bridged first MCP round runs as an internal call, so no spend log holds it for the follow-up to replay.""" +def provider_stores_the_conversation(model: str, custom_llm_provider: str | None, kwargs: Mapping[str, object]) -> bool: + """Whether the provider, not a LiteLLM spend log, holds this turn for a `previous_response_id` follow-up. + + A bridged turn is replayed from its spend log, so the bridge needs that row in the DB, and a bridged + first MCP round runs as an internal call that writes no spend log at all. + """ api_base: Final = _api_base_kwarg(kwargs) return not _will_bridge_to_chat_completions( model, @@ -1622,7 +1626,7 @@ def responses( if _bridges_to_chat_completions(responses_api_provider_config, use_chat_completions_api): bridge_kwargs: Final = _bridge_kwargs(kwargs, responses_api_provider_config, allowed_openai_params) return litellm_completion_transformation_handler.response_api_handler( - _previous_response_client_ids(previous_response_id, kwargs), + previous_response_client_ids(previous_response_id, kwargs), model=model, input=input, responses_api_request=response_api_optional_params, diff --git a/litellm/responses/streaming_iterator.py b/litellm/responses/streaming_iterator.py index ffde8c66c20..c5dc45566a9 100644 --- a/litellm/responses/streaming_iterator.py +++ b/litellm/responses/streaming_iterator.py @@ -58,10 +58,12 @@ from litellm.types.integrations.custom_logger import converted_stream_requested from litellm.types.llms.openai import ( PART_UNION_TYPES, ResponseAPIUsage, + ResponseIncompleteEvent, ResponsesAPIResponse, ResponsesAPIStreamEvents, ResponsesAPIStreamingResponse, ) +from litellm.types.responses.main import GenericResponseOutputItem, OutputText from litellm.types.utils import CallTypes from litellm.utils import async_post_call_success_deployment_hook @@ -385,6 +387,7 @@ class BaseResponsesAPIStreamingIterator: self._output_started = False self._generated_content = "" self._generated_tool_arguments = "" + self._created_response: ResponsesAPIResponse | None = None self._completed_response_cached = False self._completed_response_logged = False self._completed_response_cache_hit: bool | None = None @@ -544,6 +547,10 @@ class BaseResponsesAPIStreamingIterator: # Store the completed response (also for incomplete/failed so logging still fires) _chunk_type: Final = getattr(openai_responses_api_chunk, "type", None) openai_types = get_openai_response_types() + if _chunk_type == openai_types.ResponsesAPIStreamEvents.RESPONSE_CREATED: + _created: Final[object] = getattr(openai_responses_api_chunk, "response", None) + if isinstance(_created, ResponsesAPIResponse): + self._created_response = _created if openai_responses_api_chunk and _chunk_type in ( openai_types.ResponsesAPIStreamEvents.RESPONSE_COMPLETED, openai_types.ResponsesAPIStreamEvents.RESPONSE_INCOMPLETE, @@ -575,7 +582,7 @@ class BaseResponsesAPIStreamingIterator: else openai_responses_api_chunk.model_copy(update={"response": _billed_response}) ) self.completed_response = _terminal_chunk - _stamp_responses_usage_cost(_billed_response, self.logging_obj) + stamp_responses_usage_cost(_billed_response, self.logging_obj) if _chunk_type == openai_types.ResponsesAPIStreamEvents.RESPONSE_FAILED: self._handle_logging_failed_response() @@ -622,7 +629,9 @@ class BaseResponsesAPIStreamingIterator: # the terminal event; dispatching now would snapshot metadata early. self.logging_obj._deferred_stream_complete_args = (logging_coroutine,) else: - asyncio.create_task(logging_coroutine) + spawn_logging_task( + asyncio.get_running_loop(), logging_coroutine, task_name="Responses stream success logging" + ) else: run_async_function( async_function=self.logging_obj.async_success_handler, @@ -1028,6 +1037,34 @@ class BaseResponsesAPIStreamingIterator: if pending: await asyncio.wait(pending) + def partial_response_on_disconnect(self) -> ResponseIncompleteEvent | None: + """ + The response.incomplete event to bill when the client went away mid-stream, + the same shape the success handler assembles for a natural end of stream. + Its response is the response.created payload (it carries the served + service_tier) plus the text and tool arguments relayed so far, with counted + usage since the provider never sent any. None when nothing was relayed yet + or the stream already reached its terminal event and billed itself. + """ + created: Final = self._created_response + generated: Final = self._generated_content + self._generated_tool_arguments + if self.completed_response is not None or created is None or not generated: + return None + usage: Final = _estimate_usage_safely( + self.model or "", self.request_data.get("input"), self.request_data, generated + ) + if usage is None: + return None + partial: Final = created.model_copy( + update={ + "status": "incomplete", + "usage": usage, + "output": _partial_output_items(self._generated_content), + } + ) + stamp_responses_usage_cost(partial, self.logging_obj) + return ResponseIncompleteEvent(type=ResponsesAPIStreamEvents.RESPONSE_INCOMPLETE, response=partial) + def _note_yielded_event(self, event: ResponsesAPIStreamingResponse) -> None: self._yielded_first_chunk = True if event.type not in PRE_OUTPUT_LIFECYCLE_EVENT_TYPES: @@ -1559,6 +1596,37 @@ def _add_text_like_part_events( ) +@runtime_checkable +class _BillsPartialStreamOnDisconnect(Protocol): + def partial_response_on_disconnect(self) -> ResponseIncompleteEvent | None: ... + + +def partial_responses_incomplete_event_on_disconnect(stream: object) -> ResponseIncompleteEvent | None: + """Ask the stream behind a proxy or router wrapper for the partial response to bill, if it can build one.""" + if not isinstance(stream, _BillsPartialStreamOnDisconnect): + return None + try: + partial: Final = stream.partial_response_on_disconnect() + except Exception as e: # noqa: BLE001 # disconnect billing is best-effort; never break stream teardown + verbose_logger.debug("Failed to build partial Responses API response for disconnect billing: %s", e) + return None + return partial if isinstance(partial, ResponseIncompleteEvent) else None + + +def _partial_output_items(generated_text: str) -> Sequence[GenericResponseOutputItem]: + if not generated_text: + return [] + return [ + GenericResponseOutputItem( + type="message", + id=f"msg_{uuid.uuid4()}", + status="incomplete", + role="assistant", + content=[OutputText(type="output_text", text=generated_text, annotations=[])], + ) + ] + + def _billed_terminal_response( response_obj: object, estimate: Callable[[], ResponseAPIUsage | None] | None ) -> ResponsesAPIResponse | None: @@ -1665,7 +1733,7 @@ def _estimate_usage_safely( return None -def _stamp_responses_usage_cost( +def stamp_responses_usage_cost( response_obj: ResponsesAPIResponse | None, logging_obj: LiteLLMLoggingObj | None ) -> None: if response_obj is None or logging_obj is None: @@ -1715,7 +1783,7 @@ def build_synthetic_response_events( chunk_size: int, ) -> list[ResponsesAPIStreamingResponse]: openai_types: Final = get_openai_response_types() - _stamp_responses_usage_cost(transformed, logging_obj) + stamp_responses_usage_cost(transformed, logging_obj) events: Final[list[ResponsesAPIStreamingResponse]] = [ _build_response_status_event(openai_types.ResponsesAPIStreamEvents.RESPONSE_CREATED, transformed), @@ -2385,14 +2453,20 @@ class ResponsesWebSocketStreaming: events: Final = list(turn.events) exception: Final = turn.failure(self.authorized_model or "", self.custom_llm_provider or "", self.logging_obj) if exception is None: - asyncio.create_task(turn.logging_obj.dispatch_success_handlers(events, prefer_async_handlers=True)) + spawn_logging_task( + asyncio.get_running_loop(), + turn.logging_obj.dispatch_success_handlers(events, prefer_async_handlers=True), + task_name="Responses WebSocket success logging", + ) return if self._failure is None: self._failure = exception _record_usage_for_failure(turn.logging_obj, events) traceback_exception: Final = "".join(traceback.format_exception(exception)) - asyncio.create_task( - turn.logging_obj.dispatch_failure_handlers(exception, traceback_exception, prefer_async_handlers=True) + spawn_logging_task( + asyncio.get_running_loop(), + turn.logging_obj.dispatch_failure_handlers(exception, traceback_exception, prefer_async_handlers=True), + task_name="Responses WebSocket failure logging", ) def _wrap_response_event(self, response_str: str) -> str: diff --git a/litellm/router.py b/litellm/router.py index e3c1e56b7e8..a18ad7c3a97 100644 --- a/litellm/router.py +++ b/litellm/router.py @@ -62,6 +62,7 @@ from litellm.caching.caching import ( ) from litellm.caching.redis_cache import log_redis_failure from litellm.constants import ( + BAGGAGE_MAPPED_TAGS_METADATA_KEY, CLIENT_OUTPUT_CEILING_METADATA_KEY, CONSUMED_REQUEST_TAGS_METADATA_KEY, DEFAULT_AUTO_ROUTER_MAX_INPUT_CHARS, @@ -162,9 +163,12 @@ from litellm.router_strategy.lowest_tpm_rpm import LowestTPMLoggingHandler from litellm.router_strategy.lowest_tpm_rpm_v2 import LowestTPMLoggingHandler_v2, PrefetchedUsage from litellm.router_strategy.simple_shuffle import simple_shuffle from litellm.router_strategy.tag_based_routing import ( + baggage_stamp_for_serving_deployment, get_deployments_for_tag, + get_routing_tags_from_request_kwargs, get_tags_from_request_kwargs, is_valid_deployment_tag, + tags_with_serving_deployment_tags, ) from litellm.router_utils.access_windows import access_windows_config_error, filter_reserved_deployments from litellm.router_utils.add_retry_fallback_headers import ( @@ -238,6 +242,16 @@ from litellm.router_utils.cooldown_handlers import ( is_video_lookup_not_found, set_cooldown_deployments, ) +from litellm.router_utils.deployment_pricing import deployment_pricing_models +from litellm.router_utils.embedding_batch_size_check import ( + async_log_rejection_before_provider_call, + clear_rejected_before_provider_call, + deployments_admitting_embedding_batch, + deployments_when_none_admits_embedding_batch, + embedding_batch_too_large_error, + embedding_deployment_selection, + log_rejection_before_provider_call, +) from litellm.router_utils.fallback_event_handlers import ( MID_STREAM_FALLBACK_CONTROLS_KEY, AttemptedFallbackTargets, @@ -327,6 +341,14 @@ from litellm.router_utils.reasoning_effort_capability import ( intersect_supported_reasoning_efforts, resolve_supported_reasoning_efforts, ) +from litellm.router_utils.request_priority import ( + InvalidPriority, + parse_default_priority, + priority_error, + request_drops_params, + resolve_request_priority, + unqueueable_priority_message, +) from litellm.router_utils.router_callbacks.track_deployment_metrics import ( find_deployment_metadata, get_counted_usage_tokens, @@ -457,6 +479,7 @@ if TYPE_CHECKING: from litellm.types.llms.base import BaseLiteLLMOpenAIResponseObject from litellm.types.llms.openai import ( ResponseAPIUsage, + ResponseIncompleteEvent, ResponseInputParam, ResponsesAPIResponse, ) @@ -962,6 +985,11 @@ class FallbackAwareAnthropicMessagesStream: self._source_iterator = fallback_response self.fallback_headers_adopted = True + def partial_response_on_disconnect(self) -> "ResponseIncompleteEvent | None": + from litellm.responses.streaming_iterator import partial_responses_incomplete_event_on_disconnect + + return partial_responses_incomplete_event_on_disconnect(self._source_iterator) + def follow_source_attribution(self) -> None: """ A retry's or a fallback's stream carries a wrapper of its own, so a hop it makes before its @@ -1219,7 +1247,7 @@ class Router: caching_groups (Optional[List[tuple]]): List of model groups for caching across model groups. Defaults to None. client_ttl (int): Time-to-live for cached clients in seconds. Defaults to 3600. polling_interval: (Optional[float]): frequency of polling queue. Only for '.scheduler_acompletion()'. Default is 3ms. - default_priority: (Optional[int]): the default priority for a request. Only for '.scheduler_acompletion()'. Default is None. + default_priority: (Optional[int]): the priority given to every chat or text completion request that sets no 'priority' of its own; '.acompletion()' and '.atext_completion()' queue it through the scheduler. Default is None. num_retries (Optional[int]): Number of retries for failed requests. Defaults to 2. timeout (Optional[float]): Timeout for requests. Defaults to None. default_litellm_params (dict): Default parameters for Router.chat.completion.create. Defaults to {}. @@ -1359,7 +1387,15 @@ class Router: ### SCHEDULER ### self.scheduler = Scheduler(polling_interval=polling_interval, redis_cache=redis_cache) - self.default_priority = default_priority + parsed_default_priority: Final = parse_default_priority(default_priority) + if isinstance(parsed_default_priority, InvalidPriority): + verbose_router_logger.warning( + "router_settings.default_priority is ignored, no request is queued by default: %s", + parsed_default_priority.message, + ) + self.default_priority = ( + None if isinstance(parsed_default_priority, InvalidPriority) else parsed_default_priority + ) self.default_deployment = ( None # use this to track the users default deployment, when they want to use model = * ) @@ -2489,6 +2525,11 @@ class Router: self.asystemone = self.factory_function(asystemone, call_type="asystemone") # pyright: ignore[reportUnknownMemberType] # factory_function takes a bare Callable self.systemone = self.factory_function(systemone, call_type="systemone") # pyright: ignore[reportUnknownMemberType] # factory_function takes a bare Callable + from litellm.extraction import aextraction, extraction + + self.aextraction = self.factory_function(aextraction, call_type="aextraction") # pyright: ignore[reportUnknownMemberType] # factory_function takes a bare Callable + self.extraction = self.factory_function(extraction, call_type="extraction") # pyright: ignore[reportUnknownMemberType] # factory_function takes a bare Callable + def _initialize_video_endpoints(self): """Initialize video endpoints.""" from litellm.videos import ( @@ -3188,22 +3229,27 @@ class Router: kwargs["original_function"] = self._acompletion self._update_kwargs_before_fallbacks(model=model, kwargs=kwargs) - request_priority: Final = kwargs.get("priority") or self.default_priority start_time: Final = time.time() - _is_prompt_management_model: Final = self._is_prompt_management_model(model) - - if _is_prompt_management_model: - return await self._prompt_management_factory( - model=model, - messages=messages, - kwargs=kwargs, - ) - controls: Final = per_request_fallback_controls(kwargs) - kwargs[MID_STREAM_FALLBACK_CONTROLS_KEY] = controls # rebind-ok: forwarded to every hop - if request_priority is not None and isinstance(request_priority, int): - response = await self.schedule_acompletion(**kwargs) + is_prompt_management_model: Final = self._is_prompt_management_model(model) + if not is_prompt_management_model: + controls: Final = per_request_fallback_controls(kwargs) + kwargs[MID_STREAM_FALLBACK_CONTROLS_KEY] = controls # rebind-ok: forwarded to every hop + request_priority, request_kwargs = self.split_request_priority(model=model, kwargs=kwargs) + original_function: Final[Callable[..., Awaitable[object]]] = ( + self._prompt_management_acompletion(model=model, messages=messages) + if is_prompt_management_model + else self.async_function_with_fallbacks + ) + if request_priority is None: + response = await original_function(**request_kwargs) else: - response = await self.async_function_with_fallbacks(**kwargs) + response = await self._schedule_factory( + model=model, + priority=request_priority, + original_function=original_function, + args=(), + kwargs=request_kwargs, + ) end_time: Final = time.time() _duration: Final = end_time - start_time asyncio.create_task( @@ -3877,6 +3923,7 @@ class Router: from datetime import datetime self._async_generator = async_generator + self._billing_source: object = source_iterator # Mirror every attribute BaseResponsesAPIStreamingIterator.__init__ # would have set. The wrapper bypasses super().__init__ (it has no # httpx.Response of its own and no provider config to drive), so @@ -3925,10 +3972,29 @@ class Router: def adopt_fallback_headers(self, fallback_response: object) -> tuple[dict[str, object], dict[str, object]]: prepared: Final = Router._prepare_fallback_hidden_params(fallback_response) + self._billing_source = fallback_response self._hidden_params = {**prepared[0], "additional_headers": prepared[1]} self.fallback_headers_adopted = True return prepared + def partial_response_on_disconnect(self) -> "ResponseIncompleteEvent | None": + """ + The event to bill on a client disconnect. After a mid-stream hop the primary + stream's relayed tokens are folded into the fallback's event, the way + _combine_responses_fallback_usage does for a natural end of stream. + """ + from litellm.responses.streaming_iterator import partial_responses_incomplete_event_on_disconnect + + current: Final = partial_responses_incomplete_event_on_disconnect(self._billing_source) + if self._billing_source is source_iterator: + return current + primary: Final = partial_responses_incomplete_event_on_disconnect(source_iterator) + if current is None or primary is None: + return current or primary + if primary.response.usage is not None: + Router._combine_responses_fallback_usage(current, primary.response.usage) + return current + def __aiter__(self): return self @@ -4660,13 +4726,13 @@ class Router: ## DEPLOYMENT-LEVEL TAGS deployment_tags: Final = deployment.get("litellm_params", {}).get("tags") - if deployment_tags: - existing_tags = kwargs[metadata_variable_name].get("tags") or [] - merged_tags: Final = list(existing_tags) - for tag in deployment_tags: - if tag not in merged_tags: - merged_tags.append(tag) - kwargs[metadata_variable_name]["tags"] = merged_tags + merged_tags: Final = tags_with_serving_deployment_tags(kwargs[metadata_variable_name], deployment_tags) + if merged_tags is not None: + kwargs[metadata_variable_name]["tags"] = list(merged_tags) + + baggage_stamp: Final = baggage_stamp_for_serving_deployment(kwargs[metadata_variable_name], deployment_tags) + if baggage_stamp is not None: + kwargs[metadata_variable_name][BAGGAGE_MAPPED_TAGS_METADATA_KEY] = baggage_stamp ## CREDENTIAL NAME AS TAG credential_name: Final = deployment.get("litellm_params", {}).get("litellm_credential_name") @@ -5047,13 +5113,18 @@ class Router: @overload async def schedule_acompletion( - self, model: str, messages: list[AllMessageValues], priority: int, stream: Literal[False] = False, **kwargs + self, + model: str, + messages: list[AllMessageValues], + priority: int | None = None, + stream: Literal[False] = False, + **kwargs, ) -> ModelResponse: ... @overload async def schedule_acompletion( - self, model: str, messages: list[AllMessageValues], priority: int, stream: Literal[True], **kwargs + self, model: str, messages: list[AllMessageValues], priority: int | None, stream: Literal[True], **kwargs ) -> CustomStreamWrapper: ... @@ -5063,36 +5134,36 @@ class Router: self, model: str, messages: list[AllMessageValues], - priority: int, + priority: int | None = None, stream=False, **kwargs, ): - await self._wait_for_scheduler_turn( - model=model, - priority=priority, - parent_otel_span=get_parent_otel_span_from_kwargs(kwargs), - request_kwargs=cast(Mapping[str, object], kwargs), # cast-ok: kwargs keys are param names + queued_priority, _ = self.split_request_priority(model=model, kwargs={**kwargs, "priority": priority}) + if queued_priority is None: + raise priority_error(model=model, message=unqueueable_priority_message(priority)) + return await self.acompletion(model=model, messages=messages, stream=stream, priority=queued_priority, **kwargs) + + def split_request_priority( + self, model: str, kwargs: Mapping[str, object] + ) -> tuple[int | None, Mapping[str, object]]: + request_priority: Final = resolve_request_priority( + requested=kwargs.get("priority"), + default_priority=self.default_priority, + drops_params=lambda: request_drops_params( + kwargs, self.default_litellm_params, self._request_deployment_params(model=model, kwargs=kwargs) + ), ) - try: - _response: Final = await self.acompletion(model=model, messages=messages, stream=stream, **kwargs) - response_hidden_params: Final = get_hidden_params(_response) - if response_hidden_params is not None: - additional_headers: Final = cast( # cast-ok: router headers are stored as a mutable mapping - dict[str, object], response_hidden_params.setdefault("additional_headers", {}) - ) - additional_headers.update({"x-litellm-request-prioritization-used": True}) - return _response - except Exception as e: - setattr(e, "priority", priority) - raise e + if isinstance(request_priority, InvalidPriority): + raise priority_error(model=model, message=request_priority.message) + return request_priority, {key: value for key, value in kwargs.items() if key != "priority"} async def _schedule_factory( self, model: str, priority: int, - original_function: Callable, + original_function: Callable[..., Awaitable[object]], args: tuple[object, ...], - kwargs: dict[str, object], + kwargs: Mapping[str, object], ): await self._wait_for_scheduler_turn( model=model, @@ -5116,7 +5187,11 @@ class Router: async def _wait_for_scheduler_turn( self, model: str, priority: int, parent_otel_span: Span | None, request_kwargs: Mapping[str, object] ) -> None: + pinned: Final = self._pinned_deployment(model) + async def healthy_deployments() -> Sequence[object]: + if pinned is not None: + return (pinned,) deployments, _ = await self._async_get_healthy_deployments( model=model, parent_otel_span=parent_otel_span, @@ -5142,6 +5217,30 @@ class Router: split_litellm_model: Final = litellm_model.split("/")[0] return split_litellm_model in litellm._known_custom_logger_compatible_callbacks + def _pinned_deployment(self, model: str) -> Deployment | None: + return self.get_deployment(model_id=model) if model not in self.model_names else None + + def _request_deployment_params(self, model: str, kwargs: Mapping[str, object]) -> tuple[Mapping[str, object], ...]: + deployment: Final = self._pinned_deployment(model) + if deployment is not None: + return (deployment.litellm_params.model_dump(exclude_none=True),) + candidates: Final = ( + self._get_deployment_by_litellm_model(model=model) + if kwargs.get("specific_deployment") is True + else self.get_model_list(model_name=model, team_id=get_request_team_id(kwargs)) or () + ) + return tuple(candidate["litellm_params"] for candidate in candidates) + + def _prompt_management_acompletion( + self, + model: str, + messages: list[AllMessageValues], # mutable-ok: _prompt_management_factory takes the caller's list + ) -> Callable[..., Awaitable[object]]: + async def acompletion(**kwargs: object) -> object: # kwargs-ok: called with the request's own keyword payload + return await self._prompt_management_factory(model=model, messages=messages, kwargs=dict(kwargs)) + + return acompletion + async def _prompt_management_factory( self, model: str, @@ -5646,23 +5745,22 @@ class Router: is_async: bool | None = False, **kwargs, ): - if kwargs.get("priority", None) is not None: - return await self._schedule_factory( - model=model, - priority=kwargs.pop("priority"), - original_function=self.atext_completion, - args=(model, prompt), - kwargs=kwargs, - ) try: kwargs["model"] = model kwargs["prompt"] = prompt kwargs["original_function"] = self._atext_completion self._update_kwargs_before_fallbacks(model=model, kwargs=kwargs) - response: Final = await self.async_function_with_fallbacks(**kwargs) - - return response + request_priority, request_kwargs = self.split_request_priority(model=model, kwargs=kwargs) + if request_priority is None: + return await self.async_function_with_fallbacks(**request_kwargs) + return await self._schedule_factory( + model=model, + priority=request_priority, + original_function=self.async_function_with_fallbacks, + args=(), + kwargs=request_kwargs, + ) except Exception as e: asyncio.create_task( send_llm_exception_alert( @@ -6804,19 +6902,33 @@ class Router: except Exception as e: raise e - def _embedding(self, input: str | list, model: str, **kwargs): + def _embedding(self, input: str | list[object], model: str, **kwargs): model_name = None try: verbose_router_logger.debug("Inside embedding()- model: %s; kwargs: %s", model, kwargs) - deployment: Final = self.get_available_deployment( - model=model, - input=input, - specific_deployment=kwargs.pop("specific_deployment", None), - request_kwargs=kwargs, - ) + with embedding_deployment_selection(): + deployment: Final = self.get_available_deployment( + model=model, + input=input, + specific_deployment=kwargs.pop("specific_deployment", None), + request_kwargs=kwargs, + ) self._update_kwargs_with_deployment(deployment=deployment, kwargs=kwargs) data: Final = deployment["litellm_params"].copy() model_name = data["model"] + batch_error: Final = embedding_batch_too_large_error( + deployment=_OPAQUE_VALUE_ADAPTER.validate_python(deployment), + input=input, + request_kwargs=_OPAQUE_VALUE_ADAPTER.validate_python(kwargs), + model=model, + ) + logging_obj: Final = _REQUEST_KWARGS_ADAPTER.validate_python(kwargs).get("litellm_logging_obj") + if batch_error is not None: + if isinstance(logging_obj, LiteLLMLogging): + log_rejection_before_provider_call(logging_obj, batch_error) + raise batch_error + if isinstance(logging_obj, LiteLLMLogging): + clear_rejected_before_provider_call(logging_obj) potential_model_client: Final = self._get_client(deployment=deployment, kwargs=kwargs, client_type="sync") # check if provided keys == client keys # @@ -6879,20 +6991,34 @@ class Router: ) raise e - async def _aembedding(self, input: str | list, model: str, **kwargs): + async def _aembedding(self, input: str | list[object], model: str, **kwargs): model_name = None try: verbose_router_logger.debug("Inside _aembedding()- model: %s; kwargs: %s", model, kwargs) parent_otel_span: Final = get_parent_otel_span_from_kwargs(kwargs) - deployment: Final = await self.async_get_available_deployment( - model=model, - input=input, - specific_deployment=kwargs.pop("specific_deployment", None), - request_kwargs=kwargs, - ) + with embedding_deployment_selection(): + deployment: Final = await self.async_get_available_deployment( + model=model, + input=input, + specific_deployment=kwargs.pop("specific_deployment", None), + request_kwargs=kwargs, + ) self._update_kwargs_with_deployment(deployment=deployment, kwargs=kwargs) data: Final = deployment["litellm_params"].copy() model_name = data["model"] + batch_error: Final = embedding_batch_too_large_error( + deployment=_OPAQUE_VALUE_ADAPTER.validate_python(deployment), + input=input, + request_kwargs=_OPAQUE_VALUE_ADAPTER.validate_python(kwargs), + model=model, + ) + logging_obj: Final = _REQUEST_KWARGS_ADAPTER.validate_python(kwargs).get("litellm_logging_obj") + if batch_error is not None: + if isinstance(logging_obj, LiteLLMLogging): + await async_log_rejection_before_provider_call(logging_obj, batch_error) + raise batch_error + if isinstance(logging_obj, LiteLLMLogging): + clear_rejected_before_provider_call(logging_obj) model_client: Final = self._get_async_openai_model_client( deployment=deployment, kwargs=kwargs, @@ -7584,6 +7710,8 @@ class Router: "decisions", "asystemone", "systemone", + "aextraction", + "extraction", "aadapter_generate_content", "avideo_generation", "video_generation", @@ -7659,6 +7787,7 @@ class Router: "search", "decisions", "systemone", + "extraction", "video_generation", "video_list", "video_status", @@ -7828,6 +7957,7 @@ class Router: "ocr", "adecisions", "asystemone", + "aextraction", "avideo_generation", "avideo_list", "avideo_status", @@ -9377,17 +9507,24 @@ class Router: When a retry or fallback happens, record which model group, deployment and attempt just failed and why, and count it toward the request-wide num_retries_per_request cap """ + from litellm.litellm_core_utils.get_litellm_params import get_base_model_from_litellm_call_metadata from litellm.types.router import RetryAttemptRecord _metadata_var: Final = "litellm_metadata" if "litellm_metadata" in kwargs else "metadata" - request_metadata: Final[Mapping[str, object]] = kwargs[_metadata_var] + request_metadata: Final = cast("Mapping[str, object]", kwargs[_metadata_var]) # cast-ok: untyped kwargs model_group: Final = kwargs.get("model") model_info: Final = request_metadata.get("model_info") deployment_id: Final = model_info.get("id") if isinstance(model_info, Mapping) else None + base_model: Final = get_base_model_from_litellm_call_metadata( + metadata=request_metadata + ) or self._deployment_params_base_model(deployment_id if isinstance(deployment_id, str) else None) + deployment_model: Final = request_metadata.get("deployment") attempted_retries: Final = request_metadata.get("attempted_retries") attempt_record: Final[RetryAttemptRecord] = { "model_group": model_group if isinstance(model_group, str) else None, "deployment_id": deployment_id if isinstance(deployment_id, str) else None, + "model": deployment_model if isinstance(deployment_model, str) else None, + "base_model": base_model if isinstance(base_model, str) else None, "exception_type": type(e).__name__, "exception_string": str(e), "attempted_retries": attempted_retries if type(attempted_retries) is int else None, @@ -9418,6 +9555,18 @@ class Router: kwargs[_metadata_var]["request_retry_count"] = request_retry_count # rebind-ok: same dict, read by the cap return kwargs + def _deployment_params_base_model(self, deployment_id: str | None) -> str | None: + """The ``base_model`` a deployment declares under ``litellm_params`` (the Azure named-deployment + shape), the same key the success path's ``get_base_model_from_metadata`` reads.""" + deployment: Final = self.get_deployment(model_id=deployment_id) if deployment_id is not None else None + if deployment is None: + return None + extra_params: Final = cast( # cast-ok: pydantic extras are untyped, base_model is isinstance-checked below + "Mapping[str, object]", deployment.litellm_params.model_extra or {} + ) + base_model: Final = extra_params.get("base_model") + return base_model if isinstance(base_model, str) else None + def _update_usage(self, deployment_id: str, parent_otel_span: Span | None) -> int: """ Update deployment rpm for that minute @@ -11141,6 +11290,9 @@ class Router: if field_value is not None: model_info[field] = field_value backend_model: Final = Router._cost_map_backend_model(deployment) + pricing_provider: Final = ( + deployment.model_info.pricing_provider or deployment.litellm_params.custom_llm_provider + ) params: Final = _LITELLM_PARAMS_ADAPTER.validate_python(deployment.litellm_params.model_dump(exclude_none=True)) if ( params.get("model_id") @@ -11160,23 +11312,23 @@ class Router: Router._inherit_builtin_base_rates_for_off_peak( model_info=model_info, backend_model=backend_model, - custom_llm_provider=deployment.litellm_params.custom_llm_provider, + custom_llm_provider=pricing_provider, ) if model_info.get("input_cost_per_token") is not None: Router._inherit_builtin_cache_pricing( model_info=model_info, backend_model=backend_model, - custom_llm_provider=deployment.litellm_params.custom_llm_provider, + custom_llm_provider=pricing_provider, ) Router._inherit_builtin_service_tier_pricing( model_info=model_info, backend_model=backend_model, - custom_llm_provider=deployment.litellm_params.custom_llm_provider, + custom_llm_provider=pricing_provider, ) Router._inherit_builtin_tiered_output_rate( model_info=model_info, backend_model=backend_model, - custom_llm_provider=deployment.litellm_params.custom_llm_provider, + custom_llm_provider=pricing_provider, ) return model_info @@ -11193,6 +11345,7 @@ class Router: model_info=Router._deployment_model_cost_payload(deployment), model=deployment.litellm_params.model, custom_llm_provider=deployment.litellm_params.custom_llm_provider, + pricing_provider=deployment.model_info.pricing_provider, ) @staticmethod @@ -11202,6 +11355,7 @@ class Router: model_info: dict, # mutable-ok: cost-map entry model: str, custom_llm_provider: str | None, + pricing_provider: str | None = None, ) -> None: """Write a deployment's metadata into ``litellm.model_cost``. @@ -11225,7 +11379,7 @@ class Router: model_cost={model_id: model_info}, persist_across_reloads=False, warning_display_name=model, - custom_llm_provider=custom_llm_provider, + custom_llm_provider=pricing_provider or custom_llm_provider, add_to_provider_model_sets=False, ) @@ -11267,6 +11421,7 @@ class Router: model_info=Router._deployment_model_cost_payload(deployment), model=deployment.litellm_params.model, custom_llm_provider=deployment.litellm_params.custom_llm_provider, + pricing_provider=deployment.model_info.pricing_provider, ) self._invalidate_model_group_info_cache() @@ -11561,19 +11716,9 @@ class Router: ) for deployment in deployments ) - params: Final = tuple(deployment.get("litellm_params") or MappingProxyType({}) for deployment in deployments) - # base_model resolution mirrors get_router_model_info: unset or blank means the - # deployment's own model name is the cost-map key. - cost_map_keys: Final = tuple( - dict.fromkeys( # deduplicates while preserving config order - key - for key in ( - model_info.get("base_model") or litellm_params.get("base_model") or litellm_params.get("model") - for model_info, litellm_params in zip(model_infos, params) - ) - if isinstance(key, str) and key - ) - ) + raw_deployments: Final[tuple[object, ...]] = deployments + pricing_keys: Final = (deployment_pricing_models(deployment) for deployment in raw_deployments) + cost_map_keys: Final = tuple(dict.fromkeys(keys[0] for keys in pricing_keys if keys)) return DeploymentModelListingInfo( cost_map_keys=cost_map_keys, max_input_tokens=self._widest_configured_limit(model_infos, "max_input_tokens"), @@ -14122,7 +14267,7 @@ class Router: _get_model_from_alias = get_model_from_alias - def _get_deployment_by_litellm_model(self, model: str) -> list: + def _get_deployment_by_litellm_model(self, model: str) -> list[DeploymentTypedDict]: """ Get the deployment by litellm model. """ @@ -14623,10 +14768,34 @@ class Router: batch_candidates: Final = cast( # cast-ok: router deployments are plain dicts list[dict[str, object]], healthy_deployments ) + embedding_batch_admitting: Final = deployments_admitting_embedding_batch( + batch_candidates, + _OPAQUE_VALUE_ADAPTER.validate_python(input), + _OPAQUE_VALUE_ADAPTER.validate_python(request_kwargs), + ) + embedding_batch_routed: Final = ( + embedding_batch_admitting + if embedding_batch_admitting is not None + else deployments_when_none_admits_embedding_batch( + batch_candidates, + cast(list[dict[str, object]], _pre_cooldown_deployments), # cast-ok: router deployments are plain dicts + await self._async_routable_cooled_deployment_ids( + model=model, + request_deployments=request_deployments, + cooldown_deployments=cooldown_deployments, + request_kwargs=cast(Mapping[str, object], request_kwargs), # cast-ok: str-keyed request kwargs + has_request_input=True, + ), + _OPAQUE_VALUE_ADAPTER.validate_python(input), + _OPAQUE_VALUE_ADAPTER.validate_python(request_kwargs), + ) + ) healthy_deployments = litellm.utils.get_order_filtered_deployments( list( self._narrow_to_video_deployment( - without_deployments_that_cannot_batch(batch_candidates, caller_deployments=lambda: batch_candidates) + without_deployments_that_cannot_batch( + embedding_batch_routed, caller_deployments=lambda: batch_candidates + ) ) ), target_order=_target_order, @@ -15239,7 +15408,7 @@ class Router: if not candidates: return None - request_tags: Final = get_tags_from_request_kwargs(request_kwargs) + request_tags: Final = get_routing_tags_from_request_kwargs(request_kwargs) if request_tags: for tagged in candidates: if tagged.tags and is_valid_deployment_tag( @@ -15472,7 +15641,7 @@ class Router: llm_router=self, model_alias=registered_model_name, request_kwargs=request_kwargs, - request_tags=get_tags_from_request_kwargs(request_kwargs), + request_tags=get_routing_tags_from_request_kwargs(request_kwargs), ) # Shared compression already ran in the pre-call hook, so reuse it rather than # compressing twice. Conditional on arming having actually happened: only the @@ -15521,7 +15690,7 @@ class Router: value=self._consumed_request_tags_stamp( selected_strategy=selected_strategy, pre_routing_hook_response=pre_routing_hook_response, - request_tags=get_tags_from_request_kwargs(request_kwargs), + request_tags=get_routing_tags_from_request_kwargs(request_kwargs), ), ) @@ -15833,11 +16002,34 @@ class Router: batch_candidates: Final = cast( # cast-ok: router deployments are plain dicts list[dict[str, object]], healthy_deployments ) + embedding_batch_admitting: Final = deployments_admitting_embedding_batch( + batch_candidates, + _OPAQUE_VALUE_ADAPTER.validate_python(input), + routing_kwargs, + ) + embedding_batch_routed: Final = ( + embedding_batch_admitting + if embedding_batch_admitting is not None + else deployments_when_none_admits_embedding_batch( + batch_candidates, + cast(list[dict[str, object]], _pre_cooldown_deployments), # cast-ok: router deployments are plain dicts + self._deployment_ids( + self._region_routable_deployments( + request_deployments, + cast(Mapping[str, object] | None, request_kwargs), # cast-ok: str-keyed request kwargs + True, + ) + ) + & frozenset(cooldown_deployments), + _OPAQUE_VALUE_ADAPTER.validate_python(input), + routing_kwargs, + ) + ) healthy_deployments = litellm.utils.get_order_filtered_deployments( list( self._narrow_to_video_deployment( without_deployments_that_cannot_batch( - batch_candidates, + embedding_batch_routed, caller_deployments=lambda: deployments_the_caller_may_use(batch_candidates, routing_kwargs), ) ) diff --git a/litellm/router_strategy/budget_limiter.py b/litellm/router_strategy/budget_limiter.py index 7573bb6716f..147ce60a99b 100644 --- a/litellm/router_strategy/budget_limiter.py +++ b/litellm/router_strategy/budget_limiter.py @@ -28,6 +28,8 @@ from itertools import groupby from types import MappingProxyType from typing import Any, Final +from pydantic import TypeAdapter + import litellm from litellm._internal_context import with_service_target from litellm._logging import verbose_router_logger @@ -39,6 +41,7 @@ from litellm.litellm_core_utils.core_helpers import ( ) from litellm.litellm_core_utils.duration_parser import duration_in_seconds_from from litellm.router_strategy.tag_based_routing import get_tags_from_request_kwargs +from litellm.router_utils.batch_utils import batch_charged_once_marker_key, batch_id_to_charge_once from litellm.router_utils.cooldown_callbacks import ( get_prometheus_logger_from_callbacks, ) @@ -48,6 +51,8 @@ from litellm.types.utils import BudgetConfig, GenericBudgetConfigType, StandardL from litellm.types.utils import BudgetConfig as GenericBudgetInfo DEFAULT_REDIS_SYNC_INTERVAL: Final = 1 +_CALLBACK_FIELDS: Final = TypeAdapter(dict[str, object]) +_BATCH_CHARGE_VALUES: Final = TypeAdapter(tuple[object, float]) class _LiteLLMParamsDictView: @@ -505,16 +510,21 @@ class RouterBudgetLimiting(CustomLogger): async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): """Original method now uses helper functions""" verbose_router_logger.debug("in RouterBudgetLimiting.async_log_success_event") - if kwargs.get("call_type") == "_arealtime": + callback_fields: Final = _CALLBACK_FIELDS.validate_python(kwargs) + if callback_fields.get("call_type") == "_arealtime": return standard_logging_payload: Final[StandardLoggingPayload | None] = kwargs.get("standard_logging_object", None) if standard_logging_payload is None: raise ValueError("standard_logging_payload is required") - response_cost: Final[float] = standard_logging_payload.get("response_cost", 0) + batch_response, response_cost = _BATCH_CHARGE_VALUES.validate_python( + (response_obj, _CALLBACK_FIELDS.validate_python(standard_logging_payload).get("response_cost", 0)) + ) model_id: Final[str] = str(standard_logging_payload.get("model_id", "")) custom_llm_provider: Final[str | None] = standard_logging_payload.get("custom_llm_provider") + batch_id: Final = batch_id_to_charge_once(callback_fields.get("call_type"), batch_response, response_cost) + budget_config: Final = ( self._get_budget_config_for_provider(custom_llm_provider) if custom_llm_provider is not None else None ) @@ -527,6 +537,7 @@ class RouterBudgetLimiting(CustomLogger): spend_key=spend_key, start_time_key=start_time_key, response_cost=response_cost, + batch_id=batch_id, ) deployment_budget_config: Final = self._get_budget_config_for_deployment(model_id) @@ -539,11 +550,12 @@ class RouterBudgetLimiting(CustomLogger): spend_key=deployment_spend_key, start_time_key=deployment_start_time_key, response_cost=response_cost, + batch_id=batch_id, ) request_tags: Final = get_tags_from_request_kwargs( - kwargs, - metadata_variable_name=get_metadata_variable_name_from_kwargs(kwargs or {}), + callback_fields, + metadata_variable_name=get_metadata_variable_name_from_kwargs(callback_fields), ) if len(request_tags) > 0: for _tag in request_tags: @@ -556,6 +568,7 @@ class RouterBudgetLimiting(CustomLogger): spend_key=_tag_spend_key, start_time_key=_tag_start_time_key, response_cost=response_cost, + batch_id=batch_id, ) async def _increment_spend_for_key( @@ -564,12 +577,15 @@ class RouterBudgetLimiting(CustomLogger): spend_key: str, start_time_key: str, response_cost: float, + batch_id: str | None = None, ): if budget_config.budget_duration is None: return current_time: Final = self._clock() new_window_seconds: Final = budget_window_seconds(current_time, budget_config.budget_duration) + if batch_id is not None and not await self._claim_batch_charge(spend_key, batch_id, new_window_seconds): + return budget_start: Final = await self._get_or_set_budget_start_time( start_time_key=start_time_key, @@ -595,6 +611,17 @@ class RouterBudgetLimiting(CustomLogger): verbose_router_logger.debug("Incremented spend for %s by %s", spend_key, response_cost) + async def _claim_batch_charge(self, spend_key: str, batch_id: str, ttl_seconds: int) -> bool: + marker_key: Final = batch_charged_once_marker_key(spend_key=spend_key, batch_id=batch_id) + redis_cache: Final = self.dual_cache.redis_cache + if redis_cache is not None: + polls: Final = await redis_cache.async_increment(key=marker_key, value=1, ttl=ttl_seconds, refresh_ttl=True) + return polls == 1 + local_polls: Final = await self.dual_cache.in_memory_cache.async_increment( + key=marker_key, value=1, ttl=ttl_seconds, refresh_ttl=True + ) + return local_polls == 1 + @with_service_target("router_budgets") async def periodic_sync_in_memory_spend_with_redis(self): """ diff --git a/litellm/router_strategy/complexity_router/complexity_router.py b/litellm/router_strategy/complexity_router/complexity_router.py index 1638f20c8e3..a475358e1f0 100644 --- a/litellm/router_strategy/complexity_router/complexity_router.py +++ b/litellm/router_strategy/complexity_router/complexity_router.py @@ -22,7 +22,7 @@ import json import random import re import time -from collections.abc import Callable, Iterator, Mapping, Sequence +from collections.abc import Awaitable, Callable, Iterator, Mapping, Sequence from itertools import accumulate, chain, islice, takewhile from threading import Lock from types import MappingProxyType @@ -30,6 +30,7 @@ from typing import TYPE_CHECKING, Any, Final, Literal, NamedTuple, cast from pydantic import BaseModel, TypeAdapter, ValidationError, create_model from pydantic_core import ErrorDetails +from typing_extensions import ReadOnly, TypedDict from litellm._internal_context import with_service_target from litellm._logging import verbose_router_logger @@ -411,9 +412,19 @@ def _append_custom_keywords(base_keywords: list[str], custom_keywords: list[str] return [*base_keywords, *deduped_custom.values()] -def _parent_session_kwargs(request_kwargs: Mapping[str, object] | None) -> Mapping[str, Any]: +class _ParentSessionKwargs(TypedDict, total=False): + litellm_session_id: ReadOnly[object] + litellm_trace_id: ReadOnly[object] + + +def _parent_session_kwargs(request_kwargs: Mapping[str, object] | None) -> _ParentSessionKwargs: kwargs: Final = request_kwargs or {} - return {k: kwargs[k] for k in ("litellm_session_id", "litellm_trace_id") if kwargs.get(k) is not None} + session_id: Final = kwargs.get("litellm_session_id") + trace_id: Final = kwargs.get("litellm_trace_id") + return _ParentSessionKwargs( + **({"litellm_session_id": session_id} if session_id is not None else {}), + **({"litellm_trace_id": trace_id} if trace_id is not None else {}), + ) def _response_cost_or_none(response: object) -> float | None: @@ -2828,7 +2839,7 @@ class ComplexityRouter(CustomLogger): "originating_request_masked": masked_originating_request(request_kwargs), "body": {"model": llm_config.model, **payload}, } - classify: Final = ( + classify: Final[Callable[..., Awaitable[ModelResponse | ResponsesAPIResponse]]] = ( self.litellm_router_instance.aresponses if encrypted_task is not None else self.litellm_router_instance.acompletion diff --git a/litellm/router_strategy/lowest_cost.py b/litellm/router_strategy/lowest_cost.py index d567b6acccc..5894da9cb4f 100644 --- a/litellm/router_strategy/lowest_cost.py +++ b/litellm/router_strategy/lowest_cost.py @@ -1,5 +1,6 @@ #### What this does #### # picks based on response time (for streaming, this is time to first token) +from collections.abc import Mapping from datetime import datetime from typing import Final @@ -10,6 +11,30 @@ from litellm._logging import verbose_router_logger from litellm.caching.caching import DualCache from litellm.integrations.custom_logger import CustomLogger from litellm.router_utils.batch_utils import is_batch_retrieve_call_type +from litellm.router_utils.deployment_pricing import deployment_pricing_models, str_keyed + + +def _deployment_cost_map_rates(deployment: object) -> tuple[float | None, float | None]: + """Input and output per-token prices from the first cost-map row among the deployment's + pricing models that carries one; (None, None) when no row does, so the caller falls back to + its unmapped default.""" + rows: Final = (str_keyed(_cost_map().get(model)) for model in deployment_pricing_models(deployment)) + row: Final = next((row for row in rows if _declares_token_price(row)), None) + if row is None: + return None, None + return _as_rate(row.get("input_cost_per_token")), _as_rate(row.get("output_cost_per_token")) + + +def _cost_map() -> Mapping[str, object]: + return litellm.model_cost + + +def _declares_token_price(row: Mapping[str, object]) -> bool: + return row.get("input_cost_per_token") is not None or row.get("output_cost_per_token") is not None + + +def _as_rate(value: object) -> float | None: + return float(value) if isinstance(value, (int, float)) and not isinstance(value, bool) else None class LowestCostLoggingHandler(CustomLogger): @@ -243,8 +268,8 @@ class LowestCostLoggingHandler(CustomLogger): or _deployment.get("model_info", {}).get("rpm", None) or float("inf") ) - item_litellm_model_name = _deployment.get("litellm_params", {}).get("model") - item_litellm_model_cost_map = litellm.model_cost.get(item_litellm_model_name, {}) + deployment_view: object = _deployment + map_input_cost, map_output_cost = _deployment_cost_map_rates(deployment_view) # check if user provided input_cost_per_token and output_cost_per_token in litellm_params item_input_cost = None @@ -256,10 +281,10 @@ class LowestCostLoggingHandler(CustomLogger): item_output_cost = _deployment.get("litellm_params", {}).get("output_cost_per_token") if item_input_cost is None: - item_input_cost = item_litellm_model_cost_map.get("input_cost_per_token", 5.0) + item_input_cost = map_input_cost if map_input_cost is not None else 5.0 if item_output_cost is None: - item_output_cost = item_litellm_model_cost_map.get("output_cost_per_token", 5.0) + item_output_cost = map_output_cost if map_output_cost is not None else 5.0 # if litellm["model"] is not in model_cost map -> use item_cost = $10 diff --git a/litellm/router_strategy/tag_based_routing.py b/litellm/router_strategy/tag_based_routing.py index 73236294020..f13fd3fc630 100644 --- a/litellm/router_strategy/tag_based_routing.py +++ b/litellm/router_strategy/tag_based_routing.py @@ -10,13 +10,18 @@ Use this to route requests between Teams import re from collections.abc import Mapping, Sequence +from dataclasses import replace from types import MappingProxyType from typing import TYPE_CHECKING, Any, Final, Literal, Protocol, overload from litellm._logging import verbose_logger -from litellm.constants import CONSUMED_REQUEST_TAGS_METADATA_KEY, ROUTING_REQUEST_TAGS_METADATA_KEY +from litellm.constants import ( + BAGGAGE_MAPPED_TAGS_METADATA_KEY, + CONSUMED_REQUEST_TAGS_METADATA_KEY, + ROUTING_REQUEST_TAGS_METADATA_KEY, +) from litellm.litellm_core_utils.core_helpers import get_metadata_variable_name_from_kwargs -from litellm.types.router import ConsumedRequestTagsStamp, DeploymentTypedDict, RouterErrors +from litellm.types.router import BaggageMappedTagsStamp, ConsumedRequestTagsStamp, DeploymentTypedDict, RouterErrors if TYPE_CHECKING: from litellm.router import Router as _Router @@ -484,6 +489,64 @@ def _request_tags_after_router_consumption(metadata: object, model: str) -> Sequ return tuple(dict.fromkeys((*leftover, *(tag for tag in typed_inherited_tags if isinstance(tag, str))))) +def without_baggage_mapped_tags( + request_tags: Sequence[str] | None, metadata: object, *, keep_serving_deployment_tags: bool = False +) -> Sequence[str] | None: + """Drop baggage-mapped tags that neither key, team or project policy nor the caller itself asked for.""" + if request_tags is None or not isinstance(metadata, Mapping): + return request_tags + typed_metadata: Final[Mapping[str, object]] = metadata + stamp: Final = typed_metadata.get(BAGGAGE_MAPPED_TAGS_METADATA_KEY) + if not isinstance(stamp, BaggageMappedTagsStamp): + return request_tags + asked_for_tags: Final = ( + *_metadata_tags(typed_metadata, "inherited_tags"), + *_metadata_tags(typed_metadata, "caller_tags"), + *(stamp.serving_deployment_tags if keep_serving_deployment_tags else ()), + ) + return tuple(tag for tag in request_tags if tag not in stamp.tags or tag in asked_for_tags) or None + + +def baggage_stamp_for_serving_deployment(metadata: object, deployment_tags: object) -> BaggageMappedTagsStamp | None: + if not isinstance(metadata, Mapping): + return None + typed_metadata: Final[Mapping[str, object]] = metadata + stamp: Final = typed_metadata.get(BAGGAGE_MAPPED_TAGS_METADATA_KEY) + if not isinstance(stamp, BaggageMappedTagsStamp): + return None + return replace( + stamp, serving_deployment_tags=tuple(tag for tag in _tag_sequence(deployment_tags) if isinstance(tag, str)) + ) + + +def tags_with_serving_deployment_tags(metadata: object, deployment_tags: object) -> tuple[object, ...] | None: + """Merge the serving deployment's tags ahead of baggage-mapped tags, so baggage never changes tag precedence.""" + serving_tags: Final = _tag_sequence(deployment_tags) + if not isinstance(metadata, Mapping) or not serving_tags: + return None + typed_metadata: Final[Mapping[str, object]] = metadata + existing_tags: Final = _metadata_tags(typed_metadata, "tags") + stamp: Final = typed_metadata.get(BAGGAGE_MAPPED_TAGS_METADATA_KEY) + mapped_tags: Final = stamp.tags if isinstance(stamp, BaggageMappedTagsStamp) else () + kept_tags: Final = tuple(tag for tag in existing_tags if tag not in mapped_tags) + added_serving_tags: Final = tuple( + tag for index, tag in enumerate(serving_tags) if tag not in kept_tags and tag not in serving_tags[:index] + ) + readded_mapped_tags: Final = tuple( + dict.fromkeys(tag for tag in existing_tags if tag in mapped_tags and tag not in added_serving_tags) + ) + return (*kept_tags, *added_serving_tags, *readded_mapped_tags) + + +def _metadata_tags(metadata: Mapping[str, object], key: str) -> Sequence[object]: + return _tag_sequence(metadata.get(key)) + + +def _tag_sequence(tags: object) -> Sequence[object]: + typed_tags: Final[Sequence[object]] = tags if isinstance(tags, (list, tuple)) else () + return typed_tags + + async def get_deployments_for_tag( llm_router_instance: LitellmRouter, model: str, # used to raise the correct error @@ -524,7 +587,9 @@ async def get_deployments_for_tag( verbose_logger.debug("request metadata: %s", request_kwargs.get(metadata_variable_name)) if metadata_variable_name in request_kwargs: metadata: Final = request_kwargs[metadata_variable_name] - request_tags: Final = _request_tags_after_router_consumption(metadata, model) + request_tags: Final = without_baggage_mapped_tags( + _request_tags_after_router_consumption(metadata, model), metadata + ) match_any: Final = llm_router_instance.tag_filtering_match_any routing_prefix: Final = llm_router_instance.tag_routing_prefix or "" @@ -707,3 +772,21 @@ def get_tags_from_request_kwargs( _get_tags_from_request_kwargs = get_tags_from_request_kwargs + + +def _request_metadata(request_kwargs: Mapping[str, object]) -> object: + metadata_variable_name: Final = get_metadata_variable_name_from_kwargs(request_kwargs) + if metadata_variable_name in request_kwargs: + return request_kwargs[metadata_variable_name] + litellm_params: Final = request_kwargs.get("litellm_params") + if not isinstance(litellm_params, Mapping): + return None + typed_litellm_params: Final[Mapping[str, object]] = litellm_params + return typed_litellm_params.get(metadata_variable_name) + + +def get_routing_tags_from_request_kwargs(request_kwargs: Mapping[str, object]) -> Sequence[str]: + return ( + without_baggage_mapped_tags(get_tags_from_request_kwargs(request_kwargs), _request_metadata(request_kwargs)) + or () + ) diff --git a/litellm/router_utils/batch_utils.py b/litellm/router_utils/batch_utils.py index 88c58412e01..5b94d4b4e5b 100644 --- a/litellm/router_utils/batch_utils.py +++ b/litellm/router_utils/batch_utils.py @@ -6,6 +6,7 @@ from contextvars import ContextVar from os import PathLike from typing import Final, TypeVar +from openai.types import Batch from pydantic import TypeAdapter, ValidationError from litellm._logging import verbose_logger @@ -286,3 +287,14 @@ def is_batch_retrieve_call_type(call_type: object) -> bool: routing strategies' own state, must not be fed from it. """ return isinstance(call_type, str) and call_type in BATCH_RETRIEVE_CALL_TYPES + + +def batch_charged_once_marker_key(spend_key: str, batch_id: str) -> str: + return f"{spend_key}:batch:{batch_id}" + + +def batch_id_to_charge_once(call_type: object, response_obj: object, response_cost: float) -> str | None: + """A finished batch reports its whole cost on every poll, so its id is charged once per counter.""" + if response_cost <= 0 or not is_batch_retrieve_call_type(call_type): + return None + return response_obj.id if isinstance(response_obj, Batch) else None diff --git a/litellm/router_utils/deployment_pricing.py b/litellm/router_utils/deployment_pricing.py new file mode 100644 index 00000000000..622cc91ab5e --- /dev/null +++ b/litellm/router_utils/deployment_pricing.py @@ -0,0 +1,37 @@ +from collections.abc import Iterator, Mapping +from types import MappingProxyType +from typing import Final + +from pydantic import TypeAdapter, ValidationError + +_EMPTY: Final[Mapping[str, object]] = MappingProxyType({}) +_STR_KEYED: Final = TypeAdapter(dict[str, object]) + + +def pricing_models(base_model: object, model: object) -> tuple[str, ...]: + """Cost-map keys to price a deployment under, ``model_info.base_model`` first, then the + deployment's own model, blanks and duplicates dropped. Every spend and routing surface that + prices a deployment walks this order, so a ``base_model`` the cost map does not know falls + through to the deployment model instead of billing or ranking at the unmapped default.""" + return tuple(dict.fromkeys(_named_models(base_model, model))) + + +def deployment_pricing_models(deployment: object) -> tuple[str, ...]: + """``pricing_models`` read off a raw deployment dict (``model_info.base_model``, then + ``litellm_params.base_model``, then ``litellm_params.model``); malformed blocks count as unset.""" + view: Final = str_keyed(deployment) + params: Final = str_keyed(view.get("litellm_params")) + info: Final = str_keyed(view.get("model_info")) + return pricing_models(info.get("base_model") or params.get("base_model"), params.get("model")) + + +def _named_models(*candidates: object) -> Iterator[str]: + return (candidate for candidate in candidates if isinstance(candidate, str) and candidate) + + +def str_keyed(value: object) -> Mapping[str, object]: + """``value`` as a read-only str-keyed mapping, empty when it is not a dict.""" + try: + return MappingProxyType(_STR_KEYED.validate_python(value)) + except ValidationError: + return _EMPTY diff --git a/litellm/router_utils/embedding_batch_size_check.py b/litellm/router_utils/embedding_batch_size_check.py new file mode 100644 index 00000000000..6000bc9766d --- /dev/null +++ b/litellm/router_utils/embedding_batch_size_check.py @@ -0,0 +1,199 @@ +import traceback +from collections.abc import Generator, Iterable, Mapping, Sequence +from contextlib import contextmanager +from contextvars import ContextVar +from typing import TYPE_CHECKING, Final + +from typing_extensions import TypeIs # noqa: TID251 # TypeIs reaches typing only on 3.13 + +import litellm +from litellm.constants import PROXY_REJECTED_BEFORE_ROUTING_KEY +from litellm.types.utils import CallTypes + +if TYPE_CHECKING: + from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj + +_SELECTING_FOR_EMBEDDING: Final[ContextVar[bool]] = ContextVar("selecting_for_embedding", default=False) + + +def _is_str_keyed_mapping( + value: object, +) -> TypeIs[Mapping[str, object]]: # guard-ok: model_info, litellm_params and extra_body are str-keyed config objects + return isinstance(value, Mapping) + + +def _is_embedding_input( + value: object, +) -> TypeIs[str | Sequence[object]]: # guard-ok: only the length and first item are read + return isinstance(value, Sequence) + + +def count_embedding_inputs(input: str | Sequence[object]) -> int: + if isinstance(input, str): + return 1 + if input and isinstance(input[0], int): + return 1 + return len(input) + + +def effective_embedding_input( + input: object, + extra_body: object, +) -> str | Sequence[object] | None: + """Return the input shape used for batch-size checks, or None when neither is an embedding input. + + Some providers merge ``extra_body`` over the request body (OpenAI-compatible paths); + others ignore ``extra_body.input`` and use the top-level input (e.g. Bedrock Titan). + Use whichever of the two yields the larger input count so limits cannot be bypassed. + """ + override: Final = extra_body.get("input") if _is_str_keyed_mapping(extra_body) else None + candidates: Final = tuple(value for value in (input, override) if _is_embedding_input(value)) + return max(candidates, key=count_embedding_inputs, default=None) + + +def _litellm_param(deployment: Mapping[str, object], key: str) -> object: + litellm_params: Final = deployment.get("litellm_params") + return litellm_params.get(key) if _is_str_keyed_mapping(litellm_params) else None + + +def _embedding_batch_limit(deployment: Mapping[str, object]) -> int | None: + model_info: Final = deployment.get("model_info") + limit: Final = model_info.get("max_embedding_batch_size") if _is_str_keyed_mapping(model_info) else None + return limit if isinstance(limit, int) else None + + +def _requested_embedding_count( + deployment: Mapping[str, object], + input: object, + request_kwargs: Mapping[str, object], +) -> int: + extra_body: Final = request_kwargs.get("extra_body", _litellm_param(deployment, "extra_body")) + effective_input: Final = effective_embedding_input(input, extra_body) + return 0 if effective_input is None else count_embedding_inputs(effective_input) + + +def _deployment_admits_embedding_batch( + deployment: Mapping[str, object], + input: object, + request_kwargs: Mapping[str, object], +) -> bool: + limit: Final = _embedding_batch_limit(deployment) + return limit is None or _requested_embedding_count(deployment, input, request_kwargs) <= limit + + +def _str_keyed_or_empty(value: object) -> Mapping[str, object]: + return value if _is_str_keyed_mapping(value) else {} + + +def _deployment_id(deployment: Mapping[str, object]) -> str | None: + model_info: Final = deployment.get("model_info") + deployment_id: Final = model_info.get("id") if _is_str_keyed_mapping(model_info) else None + return None if deployment_id is None else str(deployment_id) + + +def _is_paused(deployment: Mapping[str, object]) -> bool: + model_info: Final = deployment.get("model_info") + return _is_str_keyed_mapping(model_info) and model_info.get("blocked") is True + + +@contextmanager +def embedding_deployment_selection() -> Generator[None]: + """Apply the input limit to deployment selection inside this block, which only embedding calls enter.""" + token: Final = _SELECTING_FOR_EMBEDDING.set(True) + try: + yield + finally: + _SELECTING_FOR_EMBEDDING.reset(token) + + +def deployments_admitting_embedding_batch( + deployments: list[dict[str, object]], # mutable-ok: router deployment-list contract + input: object, + request_kwargs: object, +) -> list[dict[str, object]] | None: # mutable-ok: returns a mutable deployment list + """Keep the deployments whose input limit admits the request, all of them outside embedding selection, else None""" + if not _SELECTING_FOR_EMBEDDING.get(): + return deployments + kwargs: Final = _str_keyed_or_empty(request_kwargs) + admitting: Final = [ + deployment for deployment in deployments if _deployment_admits_embedding_batch(deployment, input, kwargs) + ] + return admitting or None + + +def deployments_when_none_admits_embedding_batch( + deployments: list[dict[str, object]], # mutable-ok: router deployment-list contract + before_cooldown: Iterable[Mapping[str, object]], + routable_cooling_ids: frozenset[str], + input: object, + request_kwargs: object, +) -> list[dict[str, object]]: # mutable-ok: returns a mutable deployment list + """None while an unpaused cooling deployment the request routes to admits it, so it waits out the cooldown, + else the deployments with the largest limit, so the 400 names the most the group accepts""" + kwargs: Final = _str_keyed_or_empty(request_kwargs) + routable_cooling: Final = ( + deployment + for deployment in before_cooldown + if _deployment_id(deployment) in routable_cooling_ids and not _is_paused(deployment) + ) + if any(_deployment_admits_embedding_batch(deployment, input, kwargs) for deployment in routable_cooling): + return [] + largest_limit: Final = max((_embedding_batch_limit(deployment) or 0 for deployment in deployments), default=0) + return [deployment for deployment in deployments if _embedding_batch_limit(deployment) == largest_limit] + + +def _mark_litellm_params(logging_obj: "LiteLLMLoggingObj", *keys: str) -> None: + litellm_params: Final = logging_obj.model_call_details.get("litellm_params") + if not isinstance(litellm_params, dict): + return + for key in keys: + litellm_params[key] = True + + +def log_rejection_before_provider_call(logging_obj: "LiteLLMLoggingObj", error: Exception) -> None: + """Mark the request as never reaching a provider, so deployment health metrics skip its failure, then log it""" + _mark_litellm_params(logging_obj, PROXY_REJECTED_BEFORE_ROUTING_KEY) + logging_obj.failure_handler(error, "".join(traceback.format_exception(error))) + + +async def async_log_rejection_before_provider_call(logging_obj: "LiteLLMLoggingObj", error: Exception) -> None: + """Log it like an async provider failure: sync handlers inline, before a fallback swaps the deployment they read, + and the call marked async, so a logger with both hooks records it once""" + _mark_litellm_params(logging_obj, PROXY_REJECTED_BEFORE_ROUTING_KEY, CallTypes.aembedding.value) + traceback_text: Final = "".join(traceback.format_exception(error)) + logging_obj.failure_handler(error, traceback_text) + await logging_obj.async_failure_handler(error, traceback_text) + + +def clear_rejected_before_provider_call(logging_obj: "LiteLLMLoggingObj") -> None: + """Drop the mark an earlier rejected attempt left, since a fallback or retry shares the logging object""" + litellm_params: Final = logging_obj.model_call_details.get("litellm_params") + if isinstance(litellm_params, dict) and PROXY_REJECTED_BEFORE_ROUTING_KEY in litellm_params: + del litellm_params[PROXY_REJECTED_BEFORE_ROUTING_KEY] + + +def embedding_batch_too_large_error( + deployment: object, + input: object, + request_kwargs: object, + model: str, +) -> litellm.BadRequestError | None: + if not _is_str_keyed_mapping(deployment): + return None + limit: Final = _embedding_batch_limit(deployment) + if limit is None: + return None + + input_count: Final = _requested_embedding_count(deployment, input, _str_keyed_or_empty(request_kwargs)) + if input_count <= limit: + return None + + return litellm.BadRequestError( + message=( + f"Embedding request has {input_count} inputs, which exceeds " + f"max_embedding_batch_size={limit} for model={model}. " + "Split the input into smaller batches." + ), + model=model, + llm_provider="", + ) diff --git a/litellm/router_utils/prompt_caching_cache.py b/litellm/router_utils/prompt_caching_cache.py index 4ec0bc62e7f..f78b5982186 100644 --- a/litellm/router_utils/prompt_caching_cache.py +++ b/litellm/router_utils/prompt_caching_cache.py @@ -94,8 +94,10 @@ def _is_ephemeral_mark(mark: object) -> bool: return mark_map.get("type") == "ephemeral" -def _tool_carries_ephemeral_mark(tool: ChatCompletionToolParam) -> bool: - tool_map: Final = cast( # cast-ok: TypedDict.get rejects keys the type does not declare +def _tool_carries_ephemeral_mark(tool: object) -> bool: + if not isinstance(tool, dict): + return False + tool_map: Final = cast( # cast-ok: tools are plain JSON dicts Mapping[str, object], tool ) if _is_ephemeral_mark(tool_map.get("cache_control")): diff --git a/litellm/router_utils/request_priority.py b/litellm/router_utils/request_priority.py new file mode 100644 index 00000000000..14608cc1bcf --- /dev/null +++ b/litellm/router_utils/request_priority.py @@ -0,0 +1,88 @@ +from collections.abc import Callable, Iterable, Mapping +from dataclasses import dataclass +from typing import Final + +from pydantic import TypeAdapter, ValidationError + +import litellm +from litellm.litellm_core_utils.core_helpers import normalize_drop_params + + +@dataclass(frozen=True, slots=True) +class InvalidPriority: + value: object + + @property + def message(self) -> str: + return f"priority must be an integer, got {type(self.value).__name__} {self.value!r}" + + +def priority_error(model: str, message: str) -> litellm.BadRequestError: + return litellm.BadRequestError( + message=message, + model=model, + llm_provider="", + body={"message": message, "type": "invalid_request_error", "param": "priority", "code": "400"}, + ) + + +_PRIORITY: Final = TypeAdapter(int) + + +def _as_priority(value: object) -> int | InvalidPriority: + try: + return _PRIORITY.validate_python(value) + except ValidationError: + return InvalidPriority(value=value) + + +def resolve_request_priority( + requested: object, default_priority: int | None, drops_params: Callable[[], bool] +) -> int | None | InvalidPriority: + if requested is None: + return default_priority + priority: Final = _as_priority(requested) + if isinstance(priority, InvalidPriority) and drops_params(): + return default_priority + return priority + + +def parse_default_priority(value: object) -> int | None | InvalidPriority: + if value is None: + return None + if isinstance(value, bool): + return InvalidPriority(value=value) + return _as_priority(value) + + +def unqueueable_priority_message(requested: object) -> str: + priority: Final = None if requested is None else _as_priority(requested) + if isinstance(priority, InvalidPriority): + return f"{priority.message}, and there is no router_settings.default_priority to queue it at instead" + return "priority is required to queue a request, send one or set router_settings.default_priority" + + +def _explicit_drop_params(scope: Mapping[str, object]) -> bool | None: + return normalize_drop_params(scope.get("drop_params")) + + +def _drops_priority_by_name(scope: Mapping[str, object]) -> bool: + names: Final = scope.get("additional_drop_params") + return isinstance(names, list) and "priority" in names + + +def request_drops_params( + kwargs: Mapping[str, object], + router_defaults: Mapping[str, object], + deployment_params: Iterable[Mapping[str, object]], +) -> bool: + deployments: Final = tuple(deployment_params) + if litellm.drop_params is True or any(_drops_priority_by_name(s) for s in (kwargs, router_defaults, *deployments)): + return True + request_flag: Final = _explicit_drop_params(kwargs) + if request_flag is not None: + return request_flag + router_flag: Final = _explicit_drop_params(router_defaults) + if router_flag is not None: + return router_flag + return any(_explicit_drop_params(params) is True for params in deployments) diff --git a/litellm/rust_bridge/AGENTS.md b/litellm/rust_bridge/AGENTS.md index 607bb257a0e..c197b21bad0 100644 --- a/litellm/rust_bridge/AGENTS.md +++ b/litellm/rust_bridge/AGENTS.md @@ -1,15 +1,53 @@ -# Python boundary +# Ownership -This package owns native rollout and fallback selection, Python public API compatibility, settings projection and the Python bindings supplied to the Rust bridge. Rust core owns provider execution. `litellm-host-python` owns CPython runtime mechanics. `callbacks-legacy-python` owns legacy callback sharing and dispatch policy +- This package owns + - choosing Rust or Python for each call, and falling back to Python when Rust is unavailable + - Python public API compatibility at the native boundary + - projecting Python settings into the values Rust reads + - the Python bindings handed to the Rust bridge +- It does not own + - provider execution, which is Rust core + - CPython runtime mechanics, which is `litellm-host-python` + - legacy callback sharing and dispatch policy, which is `callbacks-legacy-python` +- `host/` holds the modules Rust imports by name to read Python-owned state. `host/AGENTS.md` states that contract -`host/` holds the Python modules Rust imports by name to read Python-owned state (provider resolution, model capabilities, settings, caches, diagnostics, legacy callbacks, the secret manager, transport and timeout conversions). Its AGENTS.md states that contract +# Routing -`execution.py` owns generic inline execution and stream iteration, plus the step classes Rust constructs. Native entrypoints return an unstarted `Execution`, and `execution.synchronous` or `execution.asynchronous` hands it to the public caller through `run` or `drive` with the one stream pair, so Rust never names a Python driver or stream class. Keep one driver implementing generator-style `send` (`send(None)` starts), `throw` and idempotent `close`. Do not create a second implementation +- `catalog.py` decides, the detectors describe the request, `dispatch.py` applies the decision +- Shared detectors live in `detectors.py`; route-only detectors live in `/detectors.py` +- The first matching rule wins. A context no rule matches stays on Python +- Every Python-only exclusion for a route (a `targets` or `features` rule) sits above any Rust rule for that route +- A route whose Python side is `NO_PYTHON` resolves to `RUST_REQUIRED` for every context it can produce + - `tests/test_litellm_rust/test_public_entries.py` marks such a route `python=None`, so dropping a route's Python changes its entries, its rules and that field together +- A detector reads the same inputs the legacy Python path reads, so the catalog and the fallback agree on which requests need Python + - A route's context, its target as well as its features, reads `NativeCall.resolved`, so an argument counts the same whether it came by position, by keyword or as a signature default + - A route's sync and async dispatches read different detector maps when the legacy handlers differ: Messages runs pre-request hooks, web search interception and interceptors only on async calls, and the sync Responses handler runs the deployment hook itself +- A detector that raises keeps the call on Python. `PublicDispatch` logs it and never fails the call over routing +- `catalog.RULES` is rollout policy with no tests of its own. Tests pass the rules they need, so check these invariants by review whenever `RULES` changes -Generic execution steps and inline suspension handling must not depend on LiteLLM response metadata. Public stream construction, `_hidden_params` and header compatibility remain product responsibilities. Keep generic stream heads opaque and preserve public header behavior in the product wrappers +# Public entries -Await each selected suspension in the caller's task so hooks retain thread, loop and context identity. A final awaitable value is returned as a value, not awaited implicitly. Closing, cancellation and `GeneratorExit` release the execution without replaying provider work or starting further callbacks +- Every route serves `a(...)`, `(..., a=True)` and `a(..., a=True)` the same way, handing native one identical `NativeCall` with no async flag on the async binding +- `tests/test_litellm_rust/test_public_entries.py` holds this for every route in its table, so a new public route gets a row there -Native admission may select legacy before execution starts. A failure after execution starts is terminal and never authorizes fallback. Creating an unstarted native coroutine must not acquire clients or credentials or capture execution context +# Execution -Verify cross-language behavior using a fresh installed extension, including unstarted-call release, setup ordering, exception identity, sync and async streams, cancellation and GC. Keep `_native.pyi` accurate about Future-returning and coroutine-returning APIs +- `execution.py` owns generic inline execution, stream iteration and the step classes Rust constructs +- Native entrypoints return an unstarted `Execution`. `execution.synchronous` or `execution.asynchronous` hands it to the caller through `run` or `drive`, so Rust never names a Python driver or stream class +- Keep one driver, implementing generator-style `send` (`send(None)` starts), `throw` and idempotent `close` +- Generic steps and suspension handling never depend on LiteLLM response metadata. Public stream construction, `_hidden_params` and header compatibility stay in the product wrappers, and generic stream heads stay opaque +- Await each selected suspension in the caller's task, so hooks keep their thread, loop and context +- Return a final awaitable as a value instead of awaiting it implicitly +- Closing, cancellation and `GeneratorExit` release the execution without replaying provider work or starting more callbacks + +# Fallback + +- Native admission may pick Python before execution starts +- A failure after execution starts is terminal and never triggers fallback +- Creating an unstarted native coroutine acquires no clients or credentials and captures no execution context + +# Verification + +- Check cross-language behavior against a freshly installed extension, covering unstarted-call release, setup ordering, exception identity, sync and async streams, cancellation and GC +- Keep `_native.pyi` accurate about which APIs return a Future and which return a coroutine +- Unit tests of this package live in `tests/unit/rust_bridge/`, end-to-end Rust path tests in `tests/test_litellm_rust/` diff --git a/litellm/rust_bridge/catalog.py b/litellm/rust_bridge/catalog.py index ca271e201b0..ebb221e98be 100644 --- a/litellm/rust_bridge/catalog.py +++ b/litellm/rust_bridge/catalog.py @@ -25,11 +25,94 @@ class Route(str, Enum): TOKENIZER = "tokenizer" +class Target(str, Enum): + CHAT_COMPLETIONS = "chat_completions" + MESSAGES = "messages" + RESPONSES = "responses" + + +class Feature(str, Enum): + SAFEGUARDS_CLASSIFIER = "safeguards_classifier" + """A non-Claude model with dangerous_tool_use safeguards, which the proxy classifier answers.""" + MOCK_RESPONSE = "mock_response" + """mock_response short-circuits before any provider call.""" + PROXY_MCP_TOOLS = "proxy_mcp_tools" + """litellm_proxy MCP tools that Python expands and may auto-execute.""" + CALLER_CLIENT = "caller_client" + """A caller-supplied HTTP client or shared session that Python sends through.""" + TIMEOUT_VARIANTS = "timeout_variants" + """request_timeout, stream_timeout or httpx.Timeout phases beyond a plain timeout.""" + DROP_PARAMS = "drop_params" + """drop_params or additional_drop_params dropping fields per provider.""" + MODIFY_PARAMS = "modify_params" + """litellm.modify_params rewriting the request, like clamping max_tokens.""" + STREAMING = "streaming" + """stream=True.""" + PROMPT_MANAGEMENT = "prompt_management" + """prompt_id resolved through a prompt manager.""" + TEXT_FORMAT = "text_format" + """A text_format model that Python turns into a JSON schema and parses back.""" + CHAT_COMPLETIONS_BRIDGE = "chat_completions_bridge" + """use_chat_completions_api or the openai/chat_completions/ prefix, served through Chat Completions.""" + RETRIES_FALLBACKS = "retries_fallbacks" + """num_retries, max_retries or fallbacks run by the SDK.""" + DEPLOYMENT_RESPONSE_ID = "deployment_response_id" + """A deployment id that Python encodes into the returned response id.""" + ENCODED_ITEM_IDS = "encoded_item_ids" + """Input items carrying litellm-encoded ids that Python restores before sending.""" + INPUT_REWRITE = "input_rewrite" + """Responses input items that Python normalizes or removes before replay.""" + EXTRA_BODY = "extra_body" + """Extra body fields that Python transforms and merges into the provider request.""" + PROVIDER_AFFINITY = "provider_affinity" + """A provider affinity header that Python validates and populates from the session id.""" + PRE_REQUEST_HOOK = "pre_request_hook" + """A logger overriding async_pre_request_hook, which may rewrite the request.""" + WEBSEARCH_INTERCEPTION = "websearch_interception" + """A WebSearchInterceptionLogger that may answer without calling the provider.""" + MESSAGES_INTERCEPTOR = "messages_interceptor" + """A registered MessagesInterceptor that takes over the call.""" + AGENTIC_LOOP_HOOK = "agentic_loop_hook" + """A logger overriding async_should_run_agentic_loop, which may run follow-up calls.""" + RESPONSE_CACHE = "response_cache" + """litellm.cache, whose hit and store order differs from native.""" + TLS_POLICY = "tls_policy" + """An OpenSSL security level or ECDH curve that native TLS cannot apply.""" + MANAGED_RESOURCE_IDS = "managed_resource_ids" + """Managed file or vector store ids that Python maps to provider ids.""" + CACHE_CONTROL_MARKS = "cache_control_marks" + """Anthropic cache_control marks that Python strips or turns into prompt cache breakpoints.""" + ANTHROPIC_TOOL_SEARCH = "anthropic_tool_search" + """Anthropic tool search tools that Python maps to OpenAI tool search.""" + TOOL_SCHEMA_REPAIR = "tool_schema_repair" + """Tool schemas that Python decodes, flattens or strips of non-Python regex patterns.""" + MODEL_PARAM_GATING = "model_param_gating" + """Params that Python clamps, drops or rejects from the model map, like gpt-5 temperature.""" + WORKLOAD_IDENTITY = "workload_identity" + """No static key, so Python mints a workload identity federation token.""" + CACHE_CONTROL_INJECTION = "cache_control_injection" + """Prompt caching injection that Python applies to messages and system.""" + STREAM_COST_INJECTION = "stream_cost_injection" + """litellm.include_cost_in_streaming_usage, where Python adds cost to streamed usage.""" + THINKING_SIGNATURE_RETRY = "thinking_signature_retry" + """Replayed thinking blocks, which Python strips and retries once if Anthropic rejects their signature.""" + CLIENT_HEADERS = "client_headers" + """Proxy-forwarded headers that Python merges into extra_headers.""" + DEPLOYMENT_HOOK = "deployment_hook" + """A logger overriding async_pre_call_deployment_hook, which the sync Python handler runs itself.""" + MODEL_LIST = "model_list" + """A model_list that Python fans out across its deployments.""" + MODEL_ALIAS_MAP = "model_alias_map" + """A model that litellm.model_alias_map rewrites before the call.""" + + @dataclass(frozen=True, slots=True) class RouteContext: route: Route provider: str | None = None model: str | None = None + target: Target | None = None + features: frozenset[Feature] = frozenset() @dataclass(frozen=True, slots=True) @@ -38,23 +121,96 @@ class RouteRule: rollout: Rollout providers: frozenset[str] | None = None models: frozenset[str] | None = None + targets: frozenset[Target] | None = None + features: frozenset[Feature] | None = None + + def unconstrained(self) -> bool: + return self.providers is None and self.models is None and self.targets is None and self.features is None def matches(self, context: RouteContext) -> bool: return ( context.route is self.route and (self.providers is None or context.provider in self.providers) and (self.models is None or context.model in self.models) + and (self.targets is None or context.target in self.targets) + and (self.features is None or not self.features.isdisjoint(context.features)) ) Rules: TypeAlias = tuple[RouteRule, ...] +COMMON_PYTHON_FEATURES: Final = frozenset( + { + Feature.MOCK_RESPONSE, + Feature.PROXY_MCP_TOOLS, + Feature.CALLER_CLIENT, + Feature.TIMEOUT_VARIANTS, + Feature.AGENTIC_LOOP_HOOK, + Feature.TLS_POLICY, + } +) + +CHAT_PYTHON_FEATURES: Final = COMMON_PYTHON_FEATURES | { + Feature.RESPONSE_CACHE, + Feature.STREAMING, + Feature.DROP_PARAMS, + Feature.MODIFY_PARAMS, + Feature.EXTRA_BODY, + Feature.RETRIES_FALLBACKS, + Feature.PROMPT_MANAGEMENT, + Feature.CACHE_CONTROL_INJECTION, + Feature.MODEL_PARAM_GATING, + Feature.MODEL_LIST, + Feature.MODEL_ALIAS_MAP, +} + +MESSAGES_PYTHON_FEATURES: Final = COMMON_PYTHON_FEATURES | { + Feature.SAFEGUARDS_CLASSIFIER, + Feature.PRE_REQUEST_HOOK, + Feature.WEBSEARCH_INTERCEPTION, + Feature.MESSAGES_INTERCEPTOR, + Feature.RESPONSE_CACHE, + Feature.MODIFY_PARAMS, + Feature.WORKLOAD_IDENTITY, + Feature.CACHE_CONTROL_INJECTION, + Feature.STREAM_COST_INJECTION, + Feature.THINKING_SIGNATURE_RETRY, +} + +RESPONSES_PYTHON_FEATURES: Final = COMMON_PYTHON_FEATURES | { + Feature.DROP_PARAMS, + Feature.MODIFY_PARAMS, + Feature.STREAMING, + Feature.PROMPT_MANAGEMENT, + Feature.TEXT_FORMAT, + Feature.CHAT_COMPLETIONS_BRIDGE, + Feature.RETRIES_FALLBACKS, + Feature.DEPLOYMENT_RESPONSE_ID, + Feature.ENCODED_ITEM_IDS, + Feature.INPUT_REWRITE, + Feature.EXTRA_BODY, + Feature.PROVIDER_AFFINITY, + Feature.RESPONSE_CACHE, + Feature.MANAGED_RESOURCE_IDS, + Feature.CACHE_CONTROL_MARKS, + Feature.ANTHROPIC_TOOL_SEARCH, + Feature.TOOL_SCHEMA_REPAIR, + Feature.MODEL_PARAM_GATING, + Feature.WORKLOAD_IDENTITY, + Feature.CLIENT_HEADERS, + Feature.DEPLOYMENT_HOOK, +} + RULES: Final[Rules] = ( + RouteRule(Route.CHAT_COMPLETIONS, Rollout.PYTHON_ONLY, features=CHAT_PYTHON_FEATURES), RouteRule(Route.CHAT_COMPLETIONS, Rollout.PYTHON_ONLY), RouteRule(Route.EMBEDDINGS, Rollout.PYTHON_ONLY), RouteRule(Route.OCR, Rollout.RUST_REQUIRED), - RouteRule(Route.MESSAGES, Rollout.RUST_OPT_IN, providers=frozenset({"anthropic", "deepseek", "vertex_ai"})), + RouteRule(Route.MESSAGES, Rollout.PYTHON_ONLY, targets=frozenset({Target.CHAT_COMPLETIONS, Target.RESPONSES})), + RouteRule(Route.MESSAGES, Rollout.PYTHON_ONLY, features=MESSAGES_PYTHON_FEATURES), + RouteRule(Route.MESSAGES, Rollout.RUST_OPT_IN, providers=frozenset({"anthropic"})), RouteRule(Route.MESSAGES, Rollout.PYTHON_ONLY), + RouteRule(Route.RESPONSES, Rollout.PYTHON_ONLY, features=RESPONSES_PYTHON_FEATURES), RouteRule(Route.RESPONSES, Rollout.PYTHON_ONLY), RouteRule(Route.TOKEN_COUNTER, Rollout.PYTHON_ONLY), RouteRule(Route.TOKENIZER, Rollout.PYTHON_ONLY), @@ -69,3 +225,9 @@ def rollout(context: RouteContext, rules: Rules | None = None) -> Rollout: def decision(context: RouteContext, rules: Rules | None = None) -> Decision: return _decision(rollout(context, rules)) + + +def rust_might_handle(route: Route, rules: Rules) -> bool: + own: Final = tuple(rule for rule in rules if rule.route is route) + last: Final = next((i for i, rule in enumerate(own) if rule.unconstrained()), len(own)) + return any(_decision(rule.rollout) is not Decision.PYTHON for rule in own[: last + 1]) diff --git a/litellm/rust_bridge/chat_completions/detectors.py b/litellm/rust_bridge/chat_completions/detectors.py new file mode 100644 index 00000000000..5aa65a945b1 --- /dev/null +++ b/litellm/rust_bridge/chat_completions/detectors.py @@ -0,0 +1,137 @@ +"""Detectors for Python-only Chat Completions behavior.""" + +from __future__ import annotations + +from collections.abc import Mapping +from typing import Final + +from pydantic import TypeAdapter + +import litellm +from litellm.rust_bridge.detectors import ( + agentic_loop_hook, + api_base, + call_callbacks, + mock_response, + overridden, + present, + retries_fallbacks, +) +from litellm.rust_bridge.public_call import NativeCall, optional_sequence, optional_str + +_PARAMS: Final = TypeAdapter(dict[str, object]) + + +def chat_mock_response(request: NativeCall) -> bool: + """Chat mocks can supply text, tool calls or a timeout without provider IO.""" + return ( + mock_response(request) + or bool(request.resolved.get("mock_tool_calls")) + or bool(request.resolved.get("mock_timeout")) + ) + + +def model_list(request: NativeCall) -> bool: + """Python fans the request out across the supplied model deployments.""" + return present(request, "model_list") + + +def model_alias_map(request: NativeCall) -> bool: + """Python rewrites this model through the configured alias map.""" + return bool(litellm.model_alias_map) and str(request.resolved["model"]) in litellm.model_alias_map + + +def chat_retries_fallbacks(request: NativeCall) -> bool: + """Chat also reads global model fallbacks and context-window fallbacks.""" + return ( + retries_fallbacks(request) + or bool(optional_sequence(litellm.model_fallbacks)) # pyright: ignore[reportUnknownMemberType, reportUnknownArgumentType] # litellm annotates it with a bare list + or present(request, "context_window_fallback_dict") + ) + + +_CHAT_UNGATED: Final = frozenset( + { + "model", + "messages", + "custom_llm_provider", + "api_version", + "drop_params", + "allowed_openai_params", + "additional_drop_params", + } +) + + +_NAMES: Final = TypeAdapter(list[str]) + + +def _chat_non_default_params(request: NativeCall) -> Mapping[str, object]: + from litellm.constants import DEFAULT_CHAT_COMPLETION_PARAM_VALUES + + defaults: Final = _PARAMS.validate_python(DEFAULT_CHAT_COMPLETION_PARAM_VALUES) + return { + name: value + for name, value in request.resolved.items() + if name in defaults and name not in _CHAT_UNGATED and value != defaults[name] + } + + +def _chat_provider(request: NativeCall) -> tuple[str, str | None]: + from litellm.exceptions import BadRequestError + from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider + + model: Final = str(request.resolved["model"]) + provider: Final = optional_str(request.resolved.get("custom_llm_provider")) + try: + resolved_model, resolved_provider, _, _ = get_llm_provider(model, provider, api_base=api_base(request)) + except BadRequestError: + return model, provider + return resolved_model, resolved_provider + + +def _unvalidated(params: Mapping[str, object]) -> frozenset[str]: + from litellm.utils import PROVIDER_UNVALIDATED_PARAMS + + return PROVIDER_UNVALIDATED_PARAMS | (frozenset({"n"}) if params.get("n") == 1 else frozenset[str]()) + + +def chat_model_param_gating(request: NativeCall) -> bool: + """Python rejects unsupported chat params or maps them differently with drop_params.""" + from litellm.exceptions import UnsupportedParamsError + from litellm.litellm_core_utils.get_supported_openai_params import ( + get_supported_openai_params, # pyright: ignore[reportUnknownVariableType] # returns a bare list + ) + from litellm.types.utils import LlmProviders + from litellm.utils import ProviderConfigManager + + params: Final = _chat_non_default_params(request) + model, provider = _chat_provider(request) + if not params or provider is None: + return False + supported: Final = frozenset(_NAMES.validate_python(get_supported_openai_params(model, provider) or [])) + if any(name not in supported for name in params.keys() - _unvalidated(params)): + return True + try: + llm_provider: Final = LlmProviders(provider) + except ValueError: + return False + config: Final = ProviderConfigManager.get_provider_chat_config(model, llm_provider) + if config is None: + return False + try: + strict: Final = _PARAMS.validate_python( + config.map_openai_params(dict(params), {}, model, drop_params=False) # pyright: ignore[reportUnknownMemberType] # returns a bare dict + ) + except UnsupportedParamsError: + return True + return strict != _PARAMS.validate_python( + config.map_openai_params(dict(params), {}, model, drop_params=True) # pyright: ignore[reportUnknownMemberType] # returns a bare dict + ) + + +def chat_agentic_loop_hook(request: NativeCall) -> bool: + """Chat callbacks can also override the chat-completion-specific agentic loop.""" + return agentic_loop_hook(request) or overridden( + "async_should_run_chat_completion_agentic_loop", call_callbacks(request) + ) diff --git a/litellm/rust_bridge/detectors.py b/litellm/rust_bridge/detectors.py new file mode 100644 index 00000000000..0ad1b787e38 --- /dev/null +++ b/litellm/rust_bridge/detectors.py @@ -0,0 +1,183 @@ +"""Shared feature detectors and helpers for native-route selection.""" + +from __future__ import annotations + +import os +from collections.abc import Callable, Iterable, Mapping +from types import MappingProxyType +from typing import TYPE_CHECKING, Final, TypeAlias, cast # noqa: TID251 # tool lists stay caller-owned + +import httpx + +import litellm +from litellm.integrations.custom_logger import CustomLogger +from litellm.litellm_core_utils.core_helpers import normalize_drop_params +from litellm.rust_bridge.catalog import Feature +from litellm.rust_bridge.public_call import NativeCall, optional_mapping, optional_sequence, optional_str + +if TYPE_CHECKING: + from litellm.responses.mcp.litellm_proxy_mcp_handler import ToolParam + +Detector: TypeAlias = Callable[[NativeCall], bool] +Detectors: TypeAlias = Mapping[Feature, Detector] + + +def detected(detectors: Detectors, request: NativeCall) -> frozenset[Feature]: + return frozenset(feature for feature, detector in detectors.items() if detector(request)) + + +def present(request: NativeCall, name: str) -> bool: + return request.resolved.get(name) is not None + + +def mock_response(request: NativeCall) -> bool: + """Python returns a supplied mock instead of calling the provider.""" + return present(request, "mock_response") + + +def caller_client(request: NativeCall) -> bool: + """Python sends through the caller's HTTP client or shared session.""" + return present(request, "client") or present(request, "shared_session") + + +def extra_body(request: NativeCall) -> bool: + """Python transforms and merges additional fields into the provider body.""" + return bool(request.resolved.get("extra_body")) + + +def streaming(request: NativeCall) -> bool: + """The caller requested streaming, which some native routes do not support yet.""" + return request.resolved.get("stream") is True + + +def timeout_variants(request: NativeCall) -> bool: + """Python handles request and stream overrides and httpx phase timeouts.""" + return ( + present(request, "request_timeout") + or (streaming(request) and present(request, "stream_timeout")) + or isinstance(request.resolved.get("timeout"), httpx.Timeout) + ) + + +def proxy_mcp_tools(request: NativeCall) -> bool: + """Python expands proxy MCP tools and may execute their tool calls.""" + from litellm.responses.mcp.litellm_proxy_mcp_handler import LiteLLM_Proxy_MCP_Handler + + tools: Final = optional_sequence(request.resolved.get("tools")) + return tools is not None and LiteLLM_Proxy_MCP_Handler.should_use_litellm_mcp_gateway( + cast("Iterable[ToolParam]", tools) # cast-ok: the predicate skips entries that are not MCP tool dicts + ) + + +def prompt_management(request: NativeCall) -> bool: + """Python resolves prompt-manager inputs or strips the litellm_agent prefix.""" + from litellm.integrations.litellm_agent.litellm_agent_model_resolver import LITELLM_AGENT_PREFIX + from litellm.types.utils import DynamicPromptManagementParamLiteral + + return ( + present(request, "prompt_id") + or str(request.resolved["model"]).startswith(LITELLM_AGENT_PREFIX) + or any(request.resolved.get(param) for param in DynamicPromptManagementParamLiteral.list_all_params()) + ) + + +def retries_fallbacks(request: NativeCall) -> bool: + """Python runs the requested retry policy or fallback chain.""" + return bool(litellm.num_retries) or any( + present(request, name) for name in ("num_retries", "max_retries", "fallbacks", "retry_policy") + ) + + +def api_base(request: NativeCall) -> str | None: + return optional_str(request.resolved.get("api_base")) or optional_str(request.resolved.get("base_url")) + + +def cache_control_injection(request: NativeCall) -> bool: + """Python injects Anthropic prompt-cache breakpoints into messages and system content.""" + from litellm.integrations.anthropic_cache_control_hook import configured_injection_points + + return ( + litellm.enable_anthropic_prompt_caching is True + or request.resolved.get("enable_prompt_caching") is True + or bool(configured_injection_points(request.resolved.get("cache_control_injection_points"))) + ) + + +def drop_params(request: NativeCall) -> bool: + """Python drops unsupported or explicitly excluded request parameters.""" + return ( + bool(litellm.drop_params) + or normalize_drop_params(request.resolved.get("drop_params")) is True + or bool(optional_sequence(request.resolved.get("additional_drop_params"))) + ) + + +def modify_params(_request: NativeCall) -> bool: + """Python rewrites unsupported request values when modify_params is enabled.""" + return bool(litellm.modify_params) + + +def _custom_loggers(callbacks: Iterable[object]) -> tuple[CustomLogger, ...]: + from litellm.litellm_core_utils.litellm_logging import get_custom_logger_compatible_class + + resolved: Final = ( + get_custom_logger_compatible_class(callback) if isinstance(callback, str) else callback + for callback in callbacks + ) + return tuple(callback for callback in resolved if isinstance(callback, CustomLogger)) + + +def overridden(method: str, callbacks: Iterable[object]) -> bool: + base: Final = getattr(CustomLogger, method) + return any(getattr(type(callback), method, base) is not base for callback in _custom_loggers(callbacks)) + + +def _request_success_callbacks(request: NativeCall) -> tuple[object, ...]: + from litellm.litellm_core_utils.litellm_logging import Logging + + supplied: Final = optional_sequence(request.resolved.get("success_callback")) or () + logging_obj: Final = request.resolved.get("litellm_logging_obj") + dynamic: Final = ( + optional_sequence(logging_obj.dynamic_success_callbacks) # pyright: ignore[reportUnknownMemberType, reportUnknownArgumentType] # Logging annotates the list with a bare Callable + if isinstance(logging_obj, Logging) + else None + ) + return (*supplied, *(dynamic or ())) + + +def call_callbacks(request: NativeCall) -> tuple[object, ...]: + return (*litellm.callbacks, *_request_success_callbacks(request)) + + +def agentic_loop_hook(request: NativeCall) -> bool: + """A callback can request follow-up tool calls through Python's agentic loop.""" + return overridden("async_should_run_agentic_loop", call_callbacks(request)) + + +def response_cache(request: NativeCall) -> bool: + """Python owns cache lookup and storage unless this call disables cache reads.""" + cache: Final = optional_mapping(request.resolved.get("cache")) or {} + return litellm.cache is not None and cache.get("no-cache") is not True + + +_NATIVE_ECDH_CURVES: Final = frozenset({"x25519", "prime256v1", "secp256r1", "p-256", "secp384r1", "p-384"}) + + +def tls_policy(_request: NativeCall) -> bool: + """Python applies TLS settings or ECDH curves the native client cannot configure.""" + curve: Final = os.getenv("SSL_ECDH_CURVE", litellm.ssl_ecdh_curve) + return bool(os.getenv("SSL_SECURITY_LEVEL", litellm.ssl_security_level)) or ( + bool(curve) and str(curve).strip().lower() not in _NATIVE_ECDH_CURVES + ) + + +COMMON: Final[Detectors] = MappingProxyType( + { + Feature.MOCK_RESPONSE: mock_response, + Feature.PROXY_MCP_TOOLS: proxy_mcp_tools, + Feature.CALLER_CLIENT: caller_client, + Feature.TIMEOUT_VARIANTS: timeout_variants, + Feature.AGENTIC_LOOP_HOOK: agentic_loop_hook, + Feature.TLS_POLICY: tls_policy, + } +) diff --git a/litellm/rust_bridge/dispatch.py b/litellm/rust_bridge/dispatch.py index da9b9bed54f..ca98fe2b5b2 100644 --- a/litellm/rust_bridge/dispatch.py +++ b/litellm/rust_bridge/dispatch.py @@ -4,11 +4,10 @@ from collections.abc import Awaitable, Callable, Mapping from dataclasses import dataclass from typing import Final, Generic, TypeAlias, TypeVar +from litellm._logging import verbose_logger from litellm.rust_bridge import catalog, runtime from litellm.rust_bridge.bindings import NativeBinding from litellm.rust_bridge.catalog import Route, RouteContext, Rules -from litellm.rust_bridge.configuration import Decision -from litellm.rust_bridge.configuration import decision as rollout_decision RequestT: Final = TypeVar("RequestT") NativeT: Final = TypeVar("NativeT") @@ -31,18 +30,6 @@ class PublicDispatch(Generic[RequestT]): route: Route request: Callable[[tuple[object, ...], Mapping[str, object]], RequestT | None] context: Callable[[RequestT], RouteContext] - bypass: Callable[[RequestT], bool] | None = None - - def _requires_projection(self, rules: Rules) -> bool: - for rule in rules: - if rule.route is not self.route: - continue - if rule.providers is not None or rule.models is not None: - if rollout_decision(rule.rollout) is not Decision.PYTHON: - return True - continue - return rollout_decision(rule.rollout) is not Decision.PYTHON - return False def _native_request(self, args: tuple[object, ...], kwargs: Mapping[str, object]) -> RequestT: request: Final = self.request(args, kwargs) @@ -50,13 +37,17 @@ class PublicDispatch(Generic[RequestT]): raise runtime.NoPythonImplementationError( f"{self.route.value} has no Python implementation, so every call must project to a native request" ) - if self.bypass is not None and self.bypass(request): - raise runtime.NoPythonImplementationError( - f"{self.route.value} has no Python implementation, so a call its bypass predicate matches cannot " - "be served" - ) return request + def _guarded_context(self, request: RequestT) -> RouteContext | None: + try: + return self.context(request) + except Exception: # noqa: BLE001 # detectors call legacy handlers, so any error must fall back to Python + verbose_logger.warning( + "%s route detection failed, serving the call on Python", self.route.value, exc_info=True + ) + return None + def run( self, args: tuple[object, ...], @@ -77,13 +68,16 @@ class PublicDispatch(Generic[RequestT]): python=python, rules=selected_rules, ) - if not self._requires_projection(selected_rules): + if not catalog.rust_might_handle(self.route, selected_rules): return python(*args, **kwargs) request: Final = self.request(args, kwargs) - if request is None or (self.bypass is not None and self.bypass(request)): + if request is None: + return python(*args, **kwargs) + context: Final = self._guarded_context(request) + if context is None: return python(*args, **kwargs) return runtime.run( - self.context(request), + context, binding=binding, native=lambda hook: native(hook, request, args, kwargs), python=lambda: python(*args, **kwargs), @@ -110,13 +104,16 @@ class PublicDispatch(Generic[RequestT]): python=python, rules=selected_rules, ) - if not self._requires_projection(selected_rules): + if not catalog.rust_might_handle(self.route, selected_rules): return await python(*args, **kwargs) request: Final = self.request(args, kwargs) - if request is None or (self.bypass is not None and self.bypass(request)): + if request is None: + return await python(*args, **kwargs) + context: Final = self._guarded_context(request) + if context is None: return await python(*args, **kwargs) return await runtime.arun( - self.context(request), + context, binding=binding, native=lambda hook: native(hook, request, args, kwargs), python=lambda: python(*args, **kwargs), diff --git a/litellm/rust_bridge/host/callbacks_legacy_python.py b/litellm/rust_bridge/host/callbacks_legacy_python.py index a82e734b47d..ae913882968 100644 --- a/litellm/rust_bridge/host/callbacks_legacy_python.py +++ b/litellm/rust_bridge/host/callbacks_legacy_python.py @@ -11,6 +11,7 @@ import contextvars import datetime import traceback import uuid +import weakref from collections.abc import Awaitable, Coroutine, Mapping from dataclasses import dataclass from typing import ( @@ -61,9 +62,21 @@ def setup( } supplied: Final = arguments.get("litellm_logging_obj") if isinstance(supplied, Logging): - return _claim_budget_reservation(CallSetup(supplied, arguments), asynchronous) + return _begin_call(CallSetup(supplied, arguments), asynchronous) logger, prepared = function_setup(call_type, Rules(), start_time, *args, is_async_call=asynchronous, **arguments) - return _claim_budget_reservation(CallSetup(logger, prepared), asynchronous) + return _begin_call(CallSetup(logger, prepared), asynchronous) + + +# Loggers whose current native call is async: their sync failure step is followed by the async one +_ASYNC_CALLS: Final[weakref.WeakSet[Logging]] = weakref.WeakSet() + + +def _begin_call(call_setup: CallSetup, asynchronous: bool) -> CallSetup: + if asynchronous: + _ASYNC_CALLS.add(call_setup.logger) + else: + _ASYNC_CALLS.discard(call_setup.logger) + return _claim_budget_reservation(call_setup, asynchronous) def _claim_budget_reservation(call_setup: CallSetup, asynchronous: bool) -> CallSetup: @@ -135,6 +148,8 @@ class LoggingSurface(Protocol): traceback_exception: str, start_time: datetime.datetime | None = None, end_time: datetime.datetime | None = None, + *, + for_async_request: bool = False, ) -> None: ... def async_failure_handler( @@ -261,7 +276,7 @@ def failure_handler( if not is_internal_call(): unbind_budget_reservation_from_callbacks(logger.litellm_params) return logger.async_failure_handler(error, trace, start, end) - logger.failure_handler(error, trace, start, end) + logger.failure_handler(error, trace, start, end, for_async_request=logger in _ASYNC_CALLS) return None diff --git a/litellm/rust_bridge/host/routes/responses.py b/litellm/rust_bridge/host/routes/responses.py index 470a89a0e05..22e8cbbf3b0 100644 --- a/litellm/rust_bridge/host/routes/responses.py +++ b/litellm/rust_bridge/host/routes/responses.py @@ -4,9 +4,8 @@ from collections.abc import Mapping from typing import Final import litellm -from litellm import get_llm_provider from litellm.rust_bridge import failures -from litellm.rust_bridge.public_call import inference_decline_reason, known_params, optional_str +from litellm.rust_bridge.public_call import known_params, optional_str from litellm.types.llms.openai import ResponsesAPIOptionalRequestParams, ResponsesAPIResponse PARAMETERS: Final = tuple(ResponsesAPIOptionalRequestParams.__annotations__) @@ -34,14 +33,3 @@ def map_failure(error: Exception, request: Mapping[str, object]) -> Exception: request, optional_str(request.get("api_base")) or optional_str(request.get("base_url")), ) - - -def decline_reason(request: Mapping[str, object]) -> str | None: - if optional_str(request.get("custom_llm_provider")) is None and "/" not in str(request["model"]): - try: - _, provider, _, _ = get_llm_provider(model=str(request["model"])) - except litellm.exceptions.BadRequestError: - return "native Responses could not resolve the provider" - if provider != "openai": - return "native HTTP responses provider" - return inference_decline_reason(PARAMETERS, request) diff --git a/litellm/rust_bridge/messages/detectors.py b/litellm/rust_bridge/messages/detectors.py new file mode 100644 index 00000000000..691c04f2daa --- /dev/null +++ b/litellm/rust_bridge/messages/detectors.py @@ -0,0 +1,85 @@ +"""Detectors for Python-only Anthropic Messages behavior.""" + +from __future__ import annotations + +from typing import Final + +import litellm +from litellm.rust_bridge.detectors import overridden, present, streaming +from litellm.rust_bridge.public_call import NativeCall, optional_mapping, optional_sequence, optional_str + + +def anthropic_workload_identity(request: NativeCall) -> bool: + """Python mints an Anthropic federation token when no static credential is configured.""" + from litellm.llms.anthropic.common_utils import AnthropicModelInfo + from litellm.secret_managers.main import get_secret_str + + def configured(param: str, env: str) -> bool: + return present(request, param) or get_secret_str(env) is not None + + return ( + AnthropicModelInfo.get_api_key(optional_str(request.resolved.get("api_key"))) is None + and AnthropicModelInfo.get_auth_token() is None + and configured("anthropic_federation_rule_id", "ANTHROPIC_FEDERATION_RULE_ID") + and configured("anthropic_organization_id", "ANTHROPIC_ORGANIZATION_ID") + ) + + +_THINKING_BLOCKS: Final = frozenset({"thinking", "redacted_thinking"}) + + +def _replays_thinking(message: object) -> bool: + content: Final = optional_sequence((optional_mapping(message) or {}).get("content")) or () + return any((optional_mapping(block) or {}).get("type") in _THINKING_BLOCKS for block in content) + + +def thinking_signature_retry(request: NativeCall) -> bool: + """Python may strip replayed thinking blocks and retry after a rejected signature.""" + return any(_replays_thinking(message) for message in optional_sequence(request.resolved.get("messages")) or ()) + + +def stream_cost_injection(request: NativeCall) -> bool: + """Python adds response cost to streaming usage when the global setting is truthy.""" + return streaming(request) and bool(litellm.include_cost_in_streaming_usage) + + +def pre_request_hook(_request: NativeCall) -> bool: + """The async Messages handler runs callbacks that can rewrite the request.""" + return overridden("async_pre_request_hook", litellm.callbacks) + + +def websearch_interception(_request: NativeCall) -> bool: + """The async Messages handler can answer a web-search request without an LLM call.""" + from litellm.integrations.websearch_interception.handler import WebSearchInterceptionLogger + + return any(isinstance(callback, WebSearchInterceptionLogger) for callback in litellm.callbacks) + + +def _resolved_provider(request: NativeCall) -> str | None: + from litellm.exceptions import BadRequestError + from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider + + provider: Final = optional_str(request.resolved.get("custom_llm_provider")) + try: + return get_llm_provider(str(request.resolved["model"]), provider)[1] + except BadRequestError: + return provider + + +def intercepted(request: NativeCall) -> bool: + """The async Messages handler delegates matching tools to a registered interceptor.""" + from litellm.llms.anthropic.pass_through.messages.interceptors import get_messages_interceptors + + tools: Final = optional_sequence(request.resolved.get("tools")) + if not tools: + return False + mappings: Final = tuple(mapping for mapping in map(optional_mapping, tools) if mapping is not None) + provider: Final = _resolved_provider(request) + return any(interceptor.can_handle(mappings, provider) for interceptor in get_messages_interceptors()) + + +def safeguards_classifier(request: NativeCall) -> bool: + """Python's proxy classifier evaluates dangerous tool use for non-Claude models.""" + from litellm.llms.anthropic.pass_through.safeguards import native_route_classifies + + return native_route_classifies(str(request.resolved["model"]), request.resolved.get("safeguards")) diff --git a/litellm/rust_bridge/public_call.py b/litellm/rust_bridge/public_call.py index 332421c68cc..8625ca71bb2 100644 --- a/litellm/rust_bridge/public_call.py +++ b/litellm/rust_bridge/public_call.py @@ -8,33 +8,6 @@ from dataclasses import dataclass from types import MappingProxyType from typing import Final, TypeVar, cast # noqa: TID251 # narrows caller-owned containers without copying them -import litellm - -_INFERENCE_CONTEXT: Final = frozenset( - { - "model", - "messages", - "input", - "api_key", - "api_base", - "base_url", - "custom_llm_provider", - "extra_headers", - "timeout", - "request_timeout", - "callbacks", - "success_callback", - "failure_callback", - "metadata", - "litellm_metadata", - "litellm_call_id", - "litellm_trace_id", - "litellm_logging_obj", - "litellm_credential_name", - "proxy_server_request", - } -) - def signature(legacy: Callable[..., object]) -> inspect.Signature: return inspect.signature(legacy) @@ -75,19 +48,6 @@ def known_params(names: Collection[str], request: Mapping[str, object]) -> Mappi return {name: value for name, value in request.items() if name in names and value is not None} -def inference_decline_reason(parameters: tuple[str, ...], kwargs: Mapping[str, object]) -> str | None: - if litellm.drop_params or litellm.modify_params: - return "native inference does not implement the configured parameter rewrites" - for name, value in kwargs.items(): - if value is None: - continue - if name in {"cache", "caching"}: - continue - if name not in parameters and name not in _INFERENCE_CONTEXT: - return f"native inference does not implement {name}" - return None - - _BAGS: Final = frozenset({inspect.Parameter.VAR_POSITIONAL, inspect.Parameter.VAR_KEYWORD}) @@ -113,6 +73,32 @@ def _without_bags(legacy: inspect.Signature, named: Mapping[str, object]) -> Map return MappingProxyType({name: value for name, value in named.items() if legacy.parameters[name].kind not in _BAGS}) +@dataclass(frozen=True, slots=True) +class AsyncFlag: + """The keyword that makes a sync entry hand off to its async entry, as in ``completion(..., acompletion=True)``. + + ``is_set`` is the route's own reading of the flag. ``@client`` hands off on ``is True``, the Messages handler on truthiness. + + Completion uses ``AsyncFlag("acompletion", sync=signature(_PYTHON_COMPLETION))``. + Messages uses ``AsyncFlag("is_async", sync=signature(_PYTHON_MESSAGES), is_set=bool)``. + """ + + name: str + sync: inspect.Signature + is_set: Callable[[object], bool] = lambda value: value is True + + def requested(self, kwargs: Mapping[str, object]) -> bool: + return self.is_set(kwargs.get(self.name)) + + def dropped(self, kwargs: Mapping[str, object]) -> Mapping[str, object]: + return MappingProxyType({name: value for name, value in kwargs.items() if name != self.name}) + + def keywords(self, args: tuple[object, ...], kwargs: Mapping[str, object]) -> Mapping[str, object]: + """Name positionals by the sync signature, since the async entry may order its parameters differently.""" + named: Final = _without_bags(self.sync, self.sync.bind_partial(*args, **kwargs).arguments) + return self.dropped({**named, **kwargs}) + + def native_call(legacy: inspect.Signature, args: tuple[object, ...], kwargs: Mapping[str, object]) -> NativeCall: positional: Final = legacy.bind_partial(*args) positional.apply_defaults() diff --git a/litellm/rust_bridge/responses/detectors.py b/litellm/rust_bridge/responses/detectors.py new file mode 100644 index 00000000000..392c11f48a8 --- /dev/null +++ b/litellm/rust_bridge/responses/detectors.py @@ -0,0 +1,210 @@ +"""Detectors for Python-only Responses behavior.""" + +from __future__ import annotations + +from collections.abc import Mapping, Sequence +from itertools import accumulate, chain, repeat, takewhile +from typing import TYPE_CHECKING, Final, cast # noqa: TID251 # tool lists stay caller-owned + +from pydantic import TypeAdapter + +import litellm +from litellm.rust_bridge.detectors import api_base, call_callbacks, overridden, present +from litellm.rust_bridge.public_call import NativeCall, optional_mapping, optional_sequence, optional_str + +if TYPE_CHECKING: + from openai.types.responses import ResponseInputParam + + from litellm.types.llms.openai import ALL_RESPONSES_API_TOOL_PARAMS, ResponsesAPIOptionalRequestParams + + +def client_headers(request: NativeCall) -> bool: + """Python merges proxy-forwarded headers into extra_headers before sending.""" + return bool(optional_mapping(request.resolved.get("headers"))) + + +def provider_affinity(request: NativeCall) -> bool: + """Python validates and fills the affinity header from the session ID.""" + return present(request, "provider_affinity_header") + + +def text_format(request: NativeCall) -> bool: + """Python builds the output schema and parses the response into the supplied type.""" + return present(request, "text_format") + + +def chat_completions_bridge(request: NativeCall) -> bool: + """Python serves this Responses request through Chat Completions.""" + from litellm.responses.main import ( + _normalize_openai_chat_completions_responses_model, # pyright: ignore[reportPrivateUsage] # the handler's own bridge prefix check + ) + + return ( + bool(request.resolved.get("use_chat_completions_api")) + or _normalize_openai_chat_completions_responses_model(str(request.resolved["model"]))[1] + ) + + +def _openai_model(request: NativeCall) -> str: + from litellm.exceptions import BadRequestError + from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider + + model: Final = str(request.resolved["model"]) + try: + return get_llm_provider(model, optional_str(request.resolved.get("custom_llm_provider")))[0] + except BadRequestError: + return model + + +def _model_info(request: NativeCall) -> Mapping[str, object] | None: + return optional_mapping(request.resolved.get("model_info")) + + +def _tools(request: NativeCall) -> Sequence[object]: + return optional_sequence(request.resolved.get("tools")) or () + + +def managed_resource_ids(request: NativeCall) -> bool: + """Python replaces managed file IDs in Responses input and tools with provider IDs.""" + from litellm.litellm_core_utils.prompt_templates.common_utils import ( + update_responses_input_with_model_file_ids, + update_responses_tools_with_model_file_ids, + ) + + model_id: Final = optional_str((_model_info(request) or {}).get("id")) + mapping: Final = request.resolved.get("model_file_id_mapping") + file_ids: Final = cast("dict[str, dict[str, str]] | None", mapping) # cast-ok: handler passes it unvalidated + input_value: Final = request.resolved.get("input") + tools: Final = [dict(tool) for tool in map(optional_mapping, _tools(request)) if tool is not None] + rewritten_tools: Final = update_responses_tools_with_model_file_ids(tools, model_id, file_ids) if tools else tools + return update_responses_input_with_model_file_ids(input_value, model_id, file_ids) != input_value or ( + rewritten_tools != tools + ) + + +def input_rewrite(request: NativeCall) -> bool: + """Python normalizes replayed Responses items and removes unsupported IDs or namespaces.""" + from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig + + input_value: Final = request.resolved.get("input") + if not isinstance(input_value, list): + return False + config: Final = OpenAIResponsesAPIConfig() + replayable: Final = config._drop_bridge_minted_reasoning_items( # pyright: ignore[reportPrivateUsage] # use the handler's replay policy + cast("ResponseInputParam", input_value), # cast-ok: the handler accepts unvalidated input items + ) + normalized: Final = config._validate_input_param(replayable) # pyright: ignore[reportPrivateUsage] # use the handler's normalization + cleaned: Final = config._drop_foreign_tool_call_item_ids(normalized) # pyright: ignore[reportPrivateUsage] # use the handler's id cleanup + return config.strip_custom_tool_call_namespace_from_responses_input(cleaned) != input_value + + +def _children(value: object) -> tuple[object, ...]: + if isinstance(value, Mapping): + return tuple(cast("Mapping[object, object]", value).values()) # cast-ok: only values are walked + if isinstance(value, list | tuple): + return tuple(cast("Sequence[object]", value)) # cast-ok: only items are walked + return () + + +def _next_level(level: tuple[object, ...], _: None) -> tuple[object, ...]: + return tuple(chain.from_iterable(map(_children, level))) + + +def _mentions(value: object, key: str) -> bool: + levels: Final = takewhile(bool, accumulate(repeat(None), _next_level, initial=(value,))) + return any( + key in cast("Mapping[object, object]", node) # cast-ok: node passed the Mapping guard + for node in chain.from_iterable(levels) + if isinstance(node, Mapping) + ) + + +def cache_control_marks(request: NativeCall) -> bool: + """Python strips or translates cache_control marks in Responses input and tools.""" + return _mentions(request.resolved.get("input"), "cache_control") or _mentions(_tools(request), "cache_control") + + +def anthropic_tool_search(request: NativeCall) -> bool: + """Python translates Anthropic tool-search definitions for the Responses API.""" + from litellm.responses.litellm_completion_transformation.tool_search import is_anthropic_tool_search_chat_tool + + return any(is_anthropic_tool_search_chat_tool(tool) for tool in _tools(request)) + + +def _undecoded_schema(tool: object) -> bool: + mapping: Final = optional_mapping(tool) + parameters: Final = None if mapping is None else mapping.get("parameters") + return parameters is not None and not isinstance(parameters, Mapping) + + +def tool_schema_repair(request: NativeCall) -> bool: + """Python decodes or repairs tool schemas before sending them to OpenAI.""" + from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig + from litellm.types.router import GenericLiteLLMParams + + tools: Final = _tools(request) + if any(_undecoded_schema(tool) for tool in tools): + return True + sanitized: Final = OpenAIResponsesAPIConfig()._sanitized_tool_schemas_for_openai( # pyright: ignore[reportPrivateUsage] # the handler's own schema rewrite + model=_openai_model(request), + tools=cast("Sequence[ALL_RESPONSES_API_TOOL_PARAMS]", tools), # cast-ok: sanitizer skips non-dict tools + litellm_params=GenericLiteLLMParams(model_info=_model_info(request)), + ) + return bool(tools) and sanitized is not tools + + +_PARAMS: Final = TypeAdapter(dict[str, object]) + + +def model_param_gating(request: NativeCall) -> bool: + """Python clamps, drops or remaps Responses params according to the model's capabilities.""" + from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig + from litellm.rust_bridge.host.routes.responses import PARAMETERS + + params: Final = {name: request.resolved[name] for name in PARAMETERS if request.resolved.get(name) is not None} + mapped: Final = _PARAMS.validate_python( + OpenAIResponsesAPIConfig().map_openai_params( # pyright: ignore[reportUnknownMemberType] # returns a bare dict + cast("ResponsesAPIOptionalRequestParams", params), # cast-ok: the handler passes these kwargs + _openai_model(request), + drop_params=True, + ) + ) + return mapped != params + + +def openai_workload_identity(request: NativeCall) -> bool: + """Python mints an OpenAI federation token when no static API key is configured.""" + from litellm.llms.openai.workload_identity import resolve_openai_workload_identity_config + + api_key: Final = optional_str(request.resolved.get("api_key")) or litellm.api_key or litellm.openai_key + return resolve_openai_workload_identity_config(api_key, api_base(request), request.resolved) is not None + + +def deployment_response_id(request: NativeCall) -> bool: + """Python encodes the deployment ID into the returned Responses ID.""" + metadata: Final = optional_mapping(request.resolved.get("litellm_metadata")) or {} + model_info: Final = optional_mapping(metadata.get("model_info")) or {} + return model_info.get("id") is not None + + +def _encoded_item(item: Mapping[str, object]) -> bool: + from litellm.responses.utils import ResponsesAPIRequestUtils + + item_id: Final = optional_str(item.get("id")) + encrypted_content: Final = optional_str(item.get("encrypted_content")) + return (item_id is not None and ResponsesAPIRequestUtils.decode_encrypted_item_id(item_id) is not None) or ( + encrypted_content is not None + and ResponsesAPIRequestUtils.unwrap_encrypted_content_with_model_id(encrypted_content)[1] != encrypted_content + ) + + +def encoded_item_ids(request: NativeCall) -> bool: + """Python restores provider IDs or encrypted content from previously wrapped items.""" + items: Final = optional_sequence(request.resolved.get("input")) or () + mappings: Final = (optional_mapping(item) for item in items) + return any(_encoded_item(item) for item in mappings if item is not None) + + +def deployment_hook(request: NativeCall) -> bool: + """The sync Responses handler runs deployment hooks that native currently skips.""" + return overridden("async_pre_call_deployment_hook", call_callbacks(request)) diff --git a/litellm/types/extraction.py b/litellm/types/extraction.py new file mode 100644 index 00000000000..4311e549b9a --- /dev/null +++ b/litellm/types/extraction.py @@ -0,0 +1,162 @@ +from collections.abc import Mapping, Sequence +from typing import Annotated, Final, Literal, TypeAlias + +from pydantic import ( + ConfigDict, + Field, + JsonValue, + PrivateAttr, + StrictBool, + StrictFloat, + StrictInt, + StrictStr, + model_validator, + with_config, +) +from typing_extensions import ReadOnly, Required, Self, TypedDict + +from litellm.types.llms.base import LiteLLMPydanticObjectBase + +ExtractionFieldType: TypeAlias = Literal[ + "text", "number", "date", "time", "datetime", "duration", "list", "estimate", "forecast" +] +ExtractionFieldName: TypeAlias = Annotated[str, Field(pattern=r"^[A-Za-z_][A-Za-z0-9_.\-]{0,63}$")] +JsonNumber: TypeAlias = StrictInt | StrictFloat +ExtractionBound: TypeAlias = JsonNumber | StrictStr +EXTRACTION_STATE_REWRITTEN_METADATA_KEY: Final = "extraction_state_rewritten_by_guardrail" + + +def _is_none(value: object) -> bool: + return value is None + + +_OMITTED_WHEN_NONE: Final = Field(exclude_if=_is_none) +OptionalJson: TypeAlias = Annotated[JsonValue, _OMITTED_WHEN_NONE] +OptionalFloat: TypeAlias = Annotated[float | None, _OMITTED_WHEN_NONE] +OptionalInt: TypeAlias = Annotated[int | None, _OMITTED_WHEN_NONE] + + +class _ClairicObject(LiteLLMPydanticObjectBase): + model_config = ConfigDict(extra="allow", frozen=True) + + +class ExtractionField(_ClairicObject): + type: Annotated[ExtractionFieldType, Field(description="The answer type for this field")] + instructions: Annotated[str | None, Field(description="What the field should contain")] = None + unit: Annotated[str | None, Field(description="Unit label. For durations, seconds through years")] = None + integer: Annotated[StrictBool | None, Field(description="Numbers and durations only")] = None + decimals: Annotated[JsonNumber | None, Field(description="Numbers, durations and number lists only, 0 to 6")] = None + items: Annotated[ + Literal["text", "number", "date"] | None, Field(description="Item type, required for list fields") + ] = None + min: Annotated[ExtractionBound | None, Field(description="Estimate and forecast lower bound")] = None + max: Annotated[ExtractionBound | None, Field(description="Estimate and forecast upper bound")] = None + step: Annotated[ExtractionBound | None, Field(description="Estimate grid step, or month or year")] = None + scale: Literal["linear", "log"] | None = None + null_threshold: Annotated[ + JsonNumber | None, Field(description="Probability of null above which the value is null") + ] = None + horizon: Annotated[JsonNumber | None, Field(description="Forecast only, number of steps")] = None + interval: Literal["step", "minute", "hour", "day", "week", "month", "quarter", "year"] | None = None + + @model_validator(mode="after") + def _list_fields_name_their_item_type(self) -> Self: + if self.type == "list" and self.items is None: + raise ValueError("list fields need items set to text, number or date") + return self + + +class ExtractionBase64Image(_ClairicObject): + content_type: Annotated[str, Field(description="The image media type, such as image/png")] + base64: Annotated[str, Field(description="Base64-encoded image bytes")] + + +ExtractionImage: TypeAlias = Annotated[str, Field(pattern=r"^[Dd][Aa][Tt][Aa]:")] | ExtractionBase64Image + + +class ExtractionOptions(_ClairicObject): + include_quantiles: Annotated[StrictBool | None, Field(description="Add 99 percentiles to estimates")] = None + return_state_text: Annotated[StrictBool | None, Field(description="Return the text that spans index into")] = None + + +class ExtractionRequestBody(_ClairicObject): + state: Annotated[ + str, + Field(description="The text to read. Must be non-empty unless images are sent. Text answers are spans of it"), + ] = "" + fields: Annotated[ + Mapping[ExtractionFieldName, ExtractionField], + Field(min_length=1, description="Field name to typed field spec. Each name becomes a key in the answers"), + ] + images: Annotated[ + tuple[ExtractionImage, ...] | None, + Field(max_length=4, description="Up to 4 images as data URLs or content_type plus base64, no remote URLs"), + ] = None + reference_date: Annotated[str | None, Field(description="ISO date that anchors dates written without a year")] = ( + None + ) + options: ExtractionOptions | None = None + + +class ExtractionRequest(ExtractionRequestBody): + model: Annotated[str, Field(description="An extraction model from the proxy model_list")] + + +class ExtractionAnswer(_ClairicObject): + type: str + value: Annotated[JsonValue, Field(description="The answer, null when the input does not determine it")] + guess: OptionalJson = None + p_null: OptionalFloat = None + confidence: OptionalFloat = None + span: Annotated[tuple[int, ...] | None, _OMITTED_WHEN_NONE] = None + spans: Annotated[tuple[tuple[int, ...], ...] | None, _OMITTED_WHEN_NONE] = None + mean: OptionalJson = None + median: OptionalJson = None + p10: OptionalJson = None + p90: OptionalJson = None + p_below: OptionalFloat = None + p_above: OptionalFloat = None + quantiles: Annotated[tuple[JsonValue, ...] | None, _OMITTED_WHEN_NONE] = None + steps: Annotated[tuple[JsonValue, ...] | None, _OMITTED_WHEN_NONE] = None + + +class ExtractionUsage(_ClairicObject): + input_tokens: int + output_tokens: int + state_tokens: OptionalInt = None + image_tokens: OptionalInt = None + schema_tokens: OptionalInt = None + passes: OptionalInt = None + + +class ExtractionResponse(_ClairicObject): + model: str + answers: Mapping[str, ExtractionAnswer] + truncated: bool + state_text: Annotated[str | None, _OMITTED_WHEN_NONE] = None + usage: ExtractionUsage + + _hidden_params: dict[str, object] = PrivateAttr( # mutable-ok: @client and the proxy write cost into it in place + default_factory=dict + ) + + @property + def hidden_params(self) -> dict[str, object]: # mutable-ok: API requires mutation + return self._hidden_params + + def set_hidden_params(self, params: Mapping[str, object]) -> None: + self._hidden_params.update(params) + + +@with_config(ConfigDict(extra="allow")) +class ExtractionCallParams(TypedDict, total=False): + model: Required[ReadOnly[str]] + state: Required[ReadOnly[str]] + fields: Required[ReadOnly[Mapping[str, Mapping[str, object]]]] + images: ReadOnly[Sequence[str | Mapping[str, object]] | None] + reference_date: ReadOnly[str | None] + api_key: ReadOnly[str | None] + api_base: ReadOnly[str | None] + timeout: ReadOnly[float | None] + custom_llm_provider: ReadOnly[str | None] + extra_headers: ReadOnly[Mapping[str, str] | None] diff --git a/litellm/types/integrations/langfuse_otel.py b/litellm/types/integrations/langfuse_otel.py index 4bcd0448c3a..5647f28c757 100644 --- a/litellm/types/integrations/langfuse_otel.py +++ b/litellm/types/integrations/langfuse_otel.py @@ -29,6 +29,7 @@ class LangfuseSpanAttributes(str, Enum): # ---- Observation input/output ---- OBSERVATION_INPUT = "langfuse.observation.input" OBSERVATION_OUTPUT = "langfuse.observation.output" + OBSERVATION_COMPLETION_START_TIME = "langfuse.observation.completion_start_time" # ---- Trace-level metadata ---- TRACE_USER_ID = "user.id" diff --git a/litellm/types/litellm_params.py b/litellm/types/litellm_params.py index 978eb9c4557..5f318cc3c69 100644 --- a/litellm/types/litellm_params.py +++ b/litellm/types/litellm_params.py @@ -91,6 +91,7 @@ class ProviderConnection: configurable_clientside_auth_params: "Sequence[str | ConfigurableClientsideParamsCustomAuth] | None" = None use_xai_oauth: bool | None = None github_copilot_auth_type: str | None = None + github_copilot_host: str | None = None github_copilot_user_session: object | None = None token_exchange_endpoint: str | None = None token_exchange_profile: str | None = None @@ -103,6 +104,7 @@ class ProviderConnection: class BedrockBatchConnection: # Bedrock rejects these names in request bodies, so register them as LiteLLM-owned aws_batch_role_arn: str | None = None + aws_bedrock_control_plane_endpoint: str | None = None s3_bucket_name: str | None = None s3_region_name: str | None = None s3_endpoint_url: str | None = None diff --git a/litellm/types/proxy/auth/user_api_key_auth.py b/litellm/types/proxy/auth/user_api_key_auth.py index c2f7c487b7b..2c1c75fbe04 100644 --- a/litellm/types/proxy/auth/user_api_key_auth.py +++ b/litellm/types/proxy/auth/user_api_key_auth.py @@ -198,14 +198,14 @@ class UserAPIKeyAuth(LiteLLM_VerificationTokenView): # the expected response ob "narrow the agent's access." ), ) - budget_reservation: dict[str, Any] | None = Field(default=None, exclude=True) + budget_reservation: dict[str, object] | None = Field(default=None, exclude=True) team_budget_snapshot: TeamBudgetSnapshot | None = Field(default=None, exclude=True) user_budget_snapshot: UserBudgetSnapshot | None = Field(default=None, exclude=True) org_budget_snapshot: OrgBudgetSnapshot | None = Field(default=None, exclude=True) matched_model_access_groups: list[str] | None = Field(default=None, exclude=True) budget_throttle_pct: float | None = Field(default=None, exclude=True) - user: Any | None = None # Expanded user object when expand=user is used - created_by_user: Any | None = None # Expanded created_by user when expand=user is used + user: object | None = None # Expanded user object when expand=user is used + created_by_user: object | None = None # Expanded created_by user when expand=user is used end_user_object_permission: LiteLLM_ObjectPermissionTable | None = None # Team object_permission preloaded in auth (e.g. get_team_object) to avoid # per-request object_permission fetches in downstream checks (vector stores, etc.) diff --git a/litellm/types/proxy/litellm_pre_call_utils.py b/litellm/types/proxy/litellm_pre_call_utils.py index 0b980d38320..f0dfd50bfbe 100644 --- a/litellm/types/proxy/litellm_pre_call_utils.py +++ b/litellm/types/proxy/litellm_pre_call_utils.py @@ -24,5 +24,5 @@ class SecretFields(TypedDict): """ raw_headers: dict - user_provider_credentials: NotRequired[ReadOnly[Mapping[str, str]]] + user_provider_credentials: NotRequired[ReadOnly[Mapping[str, Mapping[str, str]]]] user_provider_credentials_user_id: NotRequired[ReadOnly[str]] diff --git a/litellm/types/proxy/management_endpoints/scim_v2.py b/litellm/types/proxy/management_endpoints/scim_v2.py index 9b519f9af4f..fadb309e0cd 100644 --- a/litellm/types/proxy/management_endpoints/scim_v2.py +++ b/litellm/types/proxy/management_endpoints/scim_v2.py @@ -21,6 +21,9 @@ SCIM_ROLES_METADATA_KEY: Final = "scim_roles" SCIM_MANAGED_TEAM_METADATA_KEY: Final = "scim_managed" SCIM_TEAM_DATA_METADATA_KEY: Final = "scim_data" +_SCIM_SERIALIZED_FIELDS_ADAPTER: Final = TypeAdapter( + dict[str, object], config=ConfigDict(strict=True, hide_input_in_errors=True) +) class LiteLLM_UserScimMetadata(LiteLLMBaseModel): @@ -123,7 +126,7 @@ class SCIMUser(SCIMResource): @model_serializer(mode="wrap") def _omit_absent_optional_blocks(self, handler: SerializerFunctionWrapHandler) -> dict[str, object]: - dumped: Final = handler(self) + dumped: Final = _SCIM_SERIALIZED_FIELDS_ADAPTER.validate_python(handler(self)) if self.enterprise_user is None: dumped.pop(SCIM_ENTERPRISE_USER_SCHEMA, None) dumped.pop("enterprise_user", None) diff --git a/litellm/types/proxy/request_tag_mappings.py b/litellm/types/proxy/request_tag_mappings.py new file mode 100644 index 00000000000..17cb4f4048d --- /dev/null +++ b/litellm/types/proxy/request_tag_mappings.py @@ -0,0 +1,27 @@ +from typing import Literal + +from pydantic import BaseModel, ConfigDict, Field, model_validator +from typing_extensions import Self + + +class RequestTagMapping(BaseModel): + """An exact baggage value mapping, or a prefix for any value of a key.""" + + model_config = ConfigDict(extra="forbid", frozen=True) + + header: Literal["baggage"] = "baggage" + key: str = Field(min_length=1, pattern=r"^[!#$%&'*+\-.^_`|~0-9A-Za-z]+$") + value: str | None = Field(None, min_length=1) + tag: str | None = Field(None, min_length=1) + tag_prefix: str | None = Field(None, min_length=1) + required: bool = False + require_budgeted_tag: bool = False + + @model_validator(mode="after") + def validate_mapping(self) -> Self: + if self.value is not None: + if self.tag is None or self.tag_prefix is not None: + raise ValueError("An exact value mapping requires tag and cannot set tag_prefix") + elif self.tag_prefix is None or self.tag is not None: + raise ValueError("An any-value mapping requires tag_prefix and cannot set tag") + return self diff --git a/litellm/types/router.py b/litellm/types/router.py index 47dafcf275d..cd1389aea9d 100644 --- a/litellm/types/router.py +++ b/litellm/types/router.py @@ -274,6 +274,7 @@ class ModelInfo(MirroredPricingParams): created_by: str | None = None base_model: str | None = None # specify if the base model is azure/gpt-3.5-turbo etc for accurate cost tracking + pricing_provider: str | None = None # provider whose cost-map rows price this deployment, else custom_llm_provider tier: Literal["free", "paid"] | None = None """ @@ -323,6 +324,8 @@ class ModelInfo(MirroredPricingParams): # in the spend log row's metadata. Set it on every deployment of the group. internal_router_model: bool | None = None + max_embedding_batch_size: Annotated[int, Field(gt=0)] | None = None + def __init__(self, id: str | int | None = None, **params) -> None: if id is None: id = str(uuid.uuid4()) # Generate a UUID if id is None or not provided @@ -411,6 +414,7 @@ class CredentialLiteLLMParams(LiteLLMBaseModel): aws_external_id: str | None = None aws_session_tags: Sequence[AwsSessionTag] | None = None aws_bedrock_runtime_endpoint: str | None = None + aws_bedrock_control_plane_endpoint: str | None = None aws_bedrock_project_id: str | None = None s3_bucket_name: str | None = None s3_endpoint_url: str | None = None @@ -1180,6 +1184,8 @@ class RouterModelGroupAliasItem(TypedDict): class RetryAttemptRecord(TypedDict): model_group: ReadOnly[str | None] deployment_id: ReadOnly[str | None] + model: ReadOnly[str | None] + base_model: ReadOnly[str | None] exception_type: ReadOnly[str] exception_string: ReadOnly[str] attempted_retries: ReadOnly[int | None] @@ -1332,6 +1338,18 @@ class ConsumedRequestTagsStamp: tags: tuple[str, ...] +@dataclass(frozen=True, slots=True) +class BaggageMappedTagsStamp: + """Request tags added by baggage mappings, which classify spend and budgets but never select deployments. + + The serving deployment's own tags are kept beside them, so a mapped tag that the deployment also carries + still picks that deployment's guardrail mode. + """ + + tags: tuple[str, ...] + serving_deployment_tags: tuple[str, ...] = () + + @runtime_checkable class PreRoutingStrategy(Protocol): """Structural interface shared by the auto / complexity / adaptive / quality routers.""" diff --git a/litellm/types/utils.py b/litellm/types/utils.py index 576c4f093d3..5939a350970 100644 --- a/litellm/types/utils.py +++ b/litellm/types/utils.py @@ -212,6 +212,7 @@ class ProviderSpecificModelInfo(TypedDict, total=False): supports_parallel_function_calling: bool | None supports_web_search: bool | None supports_reasoning: bool | None + supports_sampling_params: ReadOnly[bool | None] supports_adaptive_thinking: bool | None supports_legacy_thinking: ReadOnly[bool | None] thinking_always_on: ReadOnly[bool | None] @@ -245,6 +246,12 @@ class SearchContextCostPerQuery(TypedDict, total=False): search_context_size_high: float +class SearchFreeRequests(TypedDict): + count: ReadOnly[int] + period: ReadOnly[Literal["day", "month"]] + shared_group: ReadOnly[str] + + class AgenticLoopParams(TypedDict, total=False): """ Parameters passed to agentic loop hooks (e.g., WebSearch interception). @@ -436,6 +443,7 @@ class ModelInfoBase(ProviderSpecificModelInfo, total=False): web_search_billing_unit: ( Literal["per_query", "per_prompt"] | None ) # "per_query" (Gemini 3.x) or "per_prompt" (Gemini 2.x) + search_free_requests: ReadOnly[SearchFreeRequests | None] google_maps_grounding_cost_per_query: ReadOnly[float | None] citation_cost_per_token: float | None # Cost per citation token for Perplexity tiered_pricing: list[dict[str, Any]] | None # Tiered pricing structure for models like Dashscope @@ -451,6 +459,7 @@ class ModelInfoBase(ProviderSpecificModelInfo, total=False): "responses", "decisions", "evaluation", + "extraction", "ocr", "realtime", ] @@ -511,6 +520,8 @@ class CallTypes(str, Enum): adecisions = "adecisions" systemone = "systemone" asystemone = "asystemone" + extraction = "extraction" + aextraction = "aextraction" arealtime = "_arealtime" aresponses_websocket = "_aresponses_websocket" create_batch = "create_batch" @@ -701,6 +712,8 @@ CallTypesLiteral = Literal[ "adecisions", "systemone", "asystemone", + "extraction", + "aextraction", "_arealtime", "_aresponses_websocket", "create_batch", @@ -814,6 +827,8 @@ API_ROUTE_TO_CALL_TYPES: Final[Mapping[str, Sequence[CallTypes]]] = { "/v1/decisions": [CallTypes.adecisions, CallTypes.decisions], "/systemone": [CallTypes.asystemone, CallTypes.systemone], "/v1/systemone": [CallTypes.asystemone, CallTypes.systemone], + "/extraction": [CallTypes.aextraction, CallTypes.extraction], + "/v1/extraction": [CallTypes.aextraction, CallTypes.extraction], # Batches "/batches": [CallTypes.acreate_batch, CallTypes.create_batch], "/v1/batches": [CallTypes.acreate_batch, CallTypes.create_batch], @@ -2062,6 +2077,10 @@ class Usage(SafeAttributeModel, CompletionUsage): setattr(self, key, value) +class UnreportedUsage(Usage): + pass + + class StreamingChoices(OpenAIObject): def __init__( self, @@ -4200,7 +4219,7 @@ oauth_token_exchange_litellm_params: Final = ( "token_exchange_profile", "token_exchange_scope", ) -github_copilot_oauth_litellm_params: Final = ("github_copilot_auth_type",) +github_copilot_oauth_litellm_params: Final = ("github_copilot_auth_type", "github_copilot_host") OIDC_SECRET_REFERENCE_PREFIX: Final = "oidc/" API_KEY_SECRET_REFERENCE_REJECTION: Final = ( "Rejected Request: api_key holds an oidc/ secret reference, which only a deployment or credential a proxy " diff --git a/litellm/utils.py b/litellm/utils.py index 27c9667f032..897138a940c 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -390,6 +390,7 @@ if TYPE_CHECKING: from litellm.llms.base_llm.containers.transformation import BaseContainerConfig from litellm.llms.base_llm.decisions.transformation import BaseDecisionsConfig from litellm.llms.base_llm.embedding.transformation import BaseEmbeddingConfig + from litellm.llms.base_llm.extraction.transformation import BaseExtractionConfig from litellm.llms.base_llm.files.transformation import BaseFilesConfig from litellm.llms.base_llm.google_genai.transformation import ( BaseGoogleGenAIGenerateContentConfig, @@ -1500,6 +1501,7 @@ def _schedule_async_success_logging( return def _enqueue_async_logging() -> None: + logging_obj.mark_async_success_log_enqueued() asyncio.create_task( _client_async_logging_helper( logging_obj=logging_obj, @@ -1578,6 +1580,22 @@ def _get_wrapper_timeout(kwargs: dict[str, object]) -> object: return kwargs.get("timeout") if stream_timeout is None else stream_timeout +def _runs_as_async_success_callback(callback: str | Callable[..., object] | CustomLogger) -> bool: + get_coroutine_checker: Final = litellm_utils.get_coroutine_checker + return get_coroutine_checker().is_async_callable(callback) or callback in ("dynamodb", "s3") + + +def split_dynamic_success_callbacks( + callbacks: Sequence[str | Callable[..., object] | CustomLogger], +) -> tuple[ + tuple[str | Callable[..., object] | CustomLogger, ...], tuple[str | Callable[..., object] | CustomLogger, ...] +]: + return ( + tuple(callback for callback in callbacks if not _runs_as_async_success_callback(callback)), + tuple(callback for callback in callbacks if _runs_as_async_success_callback(callback)), + ) + + def check_coroutine(value) -> bool: get_coroutine_checker: Final = litellm_utils.get_coroutine_checker return get_coroutine_checker().is_async_callable(value) @@ -2165,7 +2183,11 @@ def client(original_function): # Sync logging_obj.stream after deployment hooks (they may convert it). _hook_stream: Final = kwargs.get("stream") - if _hook_stream is not None and logging_obj.stream != _hook_stream: + if ( + _hook_stream is not None + and logging_obj.stream != _hook_stream + and call_type not in _NEVER_STREAMING_CALL_TYPES + ): logging_obj.stream = _hook_stream kwargs["litellm_logging_obj"] = logging_obj @@ -2370,7 +2392,7 @@ def client(original_function): unbind_budget_reservation_from_callbacks(logging_obj.litellm_params) try: logging_obj.failure_handler( - e, traceback_exception, start_time, end_time + e, traceback_exception, start_time, end_time, for_async_request=True ) # DO NOT MAKE THREADED - router retry fallback relies on this! except Exception as e: raise e @@ -2509,6 +2531,15 @@ _STREAMING_CALL_TYPES: Final = frozenset( } ) +_NEVER_STREAMING_CALL_TYPES: Final = frozenset( + { + CallTypes.extraction, + CallTypes.aextraction, + CallTypes.extraction.value, + CallTypes.aextraction.value, + } +) + def _is_streaming_request( kwargs: dict[str, object], @@ -2520,6 +2551,8 @@ def _is_streaming_request( - if "stream=True" in kwargs (litellm chat completion, litellm text completion, litellm messages) - if call_type is generate_content_stream or agenerate_content_stream (litellm google genai) """ + if call_type in _NEVER_STREAMING_CALL_TYPES: + return False if "stream" in kwargs and kwargs["stream"] is True: return True return call_type in _STREAMING_CALL_TYPES @@ -5552,8 +5585,9 @@ def add_provider_specific_params_to_optional_params( # for openai, azure we should pass the extra/passed params within `extra_body` https://github.com/openai/openai-python/blob/ac33853ba10d13ac149b1fa3ca6dba7d613065c9/src/openai/resources/models.py#L46 if _should_drop_param(k="extra_body", additional_drop_params=additional_drop_params) is False: extra_body: Final = dict(passed_params.pop("extra_body", None) or {}) + withheld_params: Final = frozenset[str]() if custom_llm_provider == "litellm_proxy" else LITELLM_ONLY_PARAMS for k in passed_params: - if k not in openai_params and k not in LITELLM_ONLY_PARAMS and passed_params[k] is not None: + if k not in openai_params and k not in withheld_params and passed_params[k] is not None: extra_body[k] = passed_params[k] if not isinstance(optional_params.get("extra_body"), dict): optional_params["extra_body"] = {} @@ -6877,6 +6911,7 @@ def get_model_info_helper( supports_computer_use=_model_info.get("supports_computer_use", None), search_context_cost_per_query=_model_info.get("search_context_cost_per_query", None), web_search_billing_unit=_model_info.get("web_search_billing_unit", None), + search_free_requests=_model_info.get("search_free_requests", None), google_maps_grounding_cost_per_query=_model_info.get("google_maps_grounding_cost_per_query", None), tpm=_model_info.get("tpm", None), rpm=_model_info.get("rpm", None), @@ -9536,6 +9571,12 @@ class ProviderConfigManager: return litellm.AzureAIDecisionsConfig() return None + @staticmethod + def get_provider_extraction_config(model: str, provider: LlmProviders) -> BaseExtractionConfig | None: + if provider == LlmProviders.CLOUDFLARE: + return litellm.CloudflareExtractionConfig() + return None + @staticmethod def get_provider_anthropic_messages_config( model: str, @@ -10597,6 +10638,10 @@ class ProviderConfigManager: ) return OpenCodeHarnessConfig() + if harness == _Harness.PI: + from litellm.llms.pi.harness.transformation import PiHarnessConfig + + return PiHarnessConfig() if harness == _Harness.DEEPAGENTS: from litellm.llms.deepagents.harness.transformation import ( DeepAgentsHarnessConfig, diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index cc284c0ce4c..98fee42de3c 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -4916,6 +4916,26 @@ "supports_tool_choice": true, "supports_vision": true }, + "azure/eu/gpt-4o": { + "deprecation_date": "2027-04-14", + "cache_creation_input_token_cost": 1.38e-06, + "cache_read_input_token_cost": 1.375e-06, + "input_cost_per_token": 2.75e-06, + "input_cost_per_token_batches": 1.375e-06, + "litellm_provider": "azure", + "max_input_tokens": 128000, + "max_output_tokens": 16384, + "max_tokens": 16384, + "mode": "chat", + "output_cost_per_token": 1.1e-05, + "output_cost_per_token_batches": 5.5e-06, + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, "azure/eu/gpt-4o-2024-11-20": { "deprecation_date": "2027-04-14", "cache_creation_input_token_cost": 1.38e-06, @@ -4936,6 +4956,25 @@ "supports_tool_choice": true, "supports_vision": true }, + "azure/eu/gpt-4o-mini": { + "cache_read_input_token_cost": 8.3e-08, + "deprecation_date": "2027-04-14", + "input_cost_per_token": 1.65e-07, + "input_cost_per_token_batches": 8.3e-08, + "litellm_provider": "azure", + "max_input_tokens": 128000, + "max_output_tokens": 16384, + "max_tokens": 16384, + "mode": "chat", + "output_cost_per_token": 6.6e-07, + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_prompt_caching": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, "azure/eu/gpt-4o-mini-2024-07-18": { "cache_read_input_token_cost": 8.3e-08, "deprecation_date": "2027-04-14", @@ -5247,6 +5286,25 @@ "supports_vision": true, "cache_read_input_token_cost_batches": 2.75e-09 }, + "azure/eu/o1": { + "cache_read_input_token_cost": 8.25e-06, + "deprecation_date": "2026-11-19", + "input_cost_per_token": 1.65e-05, + "input_cost_per_token_batches": 8.25e-06, + "litellm_provider": "azure", + "max_input_tokens": 200000, + "max_output_tokens": 100000, + "max_tokens": 100000, + "mode": "chat", + "output_cost_per_token": 6.6e-05, + "output_cost_per_token_batches": 3.3e-05, + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_prompt_caching": true, + "supports_tool_choice": true, + "supports_vision": true + }, "azure/eu/o1-2024-12-17": { "cache_read_input_token_cost": 8.25e-06, "deprecation_date": "2026-11-19", @@ -5283,6 +5341,24 @@ "supports_prompt_caching": true, "supports_vision": false }, + "azure/eu/o3-mini": { + "cache_read_input_token_cost": 6.05e-07, + "deprecation_date": "2026-11-19", + "input_cost_per_token": 1.21e-06, + "input_cost_per_token_batches": 6.05e-07, + "litellm_provider": "azure", + "max_input_tokens": 200000, + "max_output_tokens": 100000, + "max_tokens": 100000, + "mode": "chat", + "output_cost_per_token": 4.84e-06, + "output_cost_per_token_batches": 2.42e-06, + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": false + }, "azure/eu/o3-mini-2025-01-31": { "cache_read_input_token_cost": 6.05e-07, "deprecation_date": "2026-11-19", @@ -11540,6 +11616,26 @@ "supports_tool_choice": true, "supports_vision": true }, + "azure/us/gpt-4o": { + "deprecation_date": "2027-04-14", + "cache_creation_input_token_cost": 1.38e-06, + "cache_read_input_token_cost": 1.375e-06, + "input_cost_per_token": 2.75e-06, + "input_cost_per_token_batches": 1.375e-06, + "litellm_provider": "azure", + "max_input_tokens": 128000, + "max_output_tokens": 16384, + "max_tokens": 16384, + "mode": "chat", + "output_cost_per_token": 1.1e-05, + "output_cost_per_token_batches": 5.5e-06, + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, "azure/us/gpt-4o-2024-11-20": { "deprecation_date": "2027-04-14", "cache_creation_input_token_cost": 1.38e-06, @@ -11560,6 +11656,25 @@ "supports_tool_choice": true, "supports_vision": true }, + "azure/us/gpt-4o-mini": { + "cache_read_input_token_cost": 8.3e-08, + "deprecation_date": "2027-04-14", + "input_cost_per_token": 1.65e-07, + "input_cost_per_token_batches": 8.3e-08, + "litellm_provider": "azure", + "max_input_tokens": 128000, + "max_output_tokens": 16384, + "max_tokens": 16384, + "mode": "chat", + "output_cost_per_token": 6.6e-07, + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_prompt_caching": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, "azure/us/gpt-4o-mini-2024-07-18": { "cache_read_input_token_cost": 8.3e-08, "deprecation_date": "2027-04-14", @@ -11871,6 +11986,25 @@ "supports_tool_choice": true, "supports_vision": true }, + "azure/us/o1": { + "cache_read_input_token_cost": 8.25e-06, + "deprecation_date": "2026-11-19", + "input_cost_per_token": 1.65e-05, + "input_cost_per_token_batches": 8.25e-06, + "litellm_provider": "azure", + "max_input_tokens": 200000, + "max_output_tokens": 100000, + "max_tokens": 100000, + "mode": "chat", + "output_cost_per_token": 6.6e-05, + "output_cost_per_token_batches": 3.3e-05, + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_prompt_caching": true, + "supports_tool_choice": true, + "supports_vision": true + }, "azure/us/o1-2024-12-17": { "cache_read_input_token_cost": 8.25e-06, "deprecation_date": "2026-11-19", @@ -11907,6 +12041,39 @@ "supports_prompt_caching": true, "supports_vision": false }, + "azure/us/o3": { + "deprecation_date": "2026-11-19", + "cache_read_input_token_cost": 5.5e-07, + "input_cost_per_token": 2.2e-06, + "input_cost_per_token_batches": 1.1e-06, + "litellm_provider": "azure", + "max_input_tokens": 200000, + "max_output_tokens": 100000, + "max_tokens": 100000, + "mode": "chat", + "output_cost_per_token": 8.8e-06, + "output_cost_per_token_batches": 4.4e-06, + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/batch", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_parallel_function_calling": false, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, "azure/us/o3-2025-04-16": { "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 5.5e-07, @@ -11940,6 +12107,24 @@ "supports_tool_choice": true, "supports_vision": true }, + "azure/us/o3-mini": { + "cache_read_input_token_cost": 6.05e-07, + "deprecation_date": "2026-11-19", + "input_cost_per_token": 1.21e-06, + "input_cost_per_token_batches": 6.05e-07, + "litellm_provider": "azure", + "max_input_tokens": 200000, + "max_output_tokens": 100000, + "max_tokens": 100000, + "mode": "chat", + "output_cost_per_token": 4.84e-06, + "output_cost_per_token_batches": 2.42e-06, + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": false + }, "azure/us/o3-mini-2025-01-31": { "cache_read_input_token_cost": 6.05e-07, "deprecation_date": "2026-11-19", @@ -11958,6 +12143,27 @@ "supports_tool_choice": true, "supports_vision": false }, + "azure/us/o4-mini": { + "cache_read_input_token_cost": 3.03e-07, + "deprecation_date": "2026-11-19", + "input_cost_per_token": 1.21e-06, + "input_cost_per_token_batches": 6.05e-07, + "litellm_provider": "azure", + "max_input_tokens": 200000, + "max_output_tokens": 100000, + "max_tokens": 100000, + "mode": "chat", + "output_cost_per_token": 4.84e-06, + "output_cost_per_token_batches": 2.42e-06, + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", + "supports_function_calling": true, + "supports_parallel_function_calling": false, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, "azure/us/o4-mini-2025-04-16": { "cache_read_input_token_cost": 3.03e-07, "deprecation_date": "2026-11-19", @@ -16374,6 +16580,24 @@ "source": "https://developers.cloudflare.com/workers-ai/platform/pricing/", "supports_vision": true }, + "cloudflare/clairic": { + "input_cost_per_token": 1e-07, + "litellm_provider": "cloudflare", + "max_input_tokens": 65536, + "mode": "extraction", + "output_cost_per_token": 0.0, + "source": "https://developers.cloudflare.com/workers-ai/models/clairic/", + "supports_vision": true + }, + "cloudflare/@cf/cloudflare/clairic": { + "input_cost_per_token": 1e-07, + "litellm_provider": "cloudflare", + "max_input_tokens": 65536, + "mode": "extraction", + "output_cost_per_token": 0.0, + "source": "https://developers.cloudflare.com/workers-ai/models/clairic/", + "supports_vision": true + }, "cloudflare/@cf/meta/llama-2-7b-chat-fp16": { "input_cost_per_token": 1.923e-06, "litellm_provider": "cloudflare", @@ -21697,6 +21921,7 @@ ], "supports_function_calling": true, "supports_reasoning": true, + "supports_sampling_params": false, "supports_tool_choice": true, "supports_vision": true }, @@ -21721,6 +21946,7 @@ ], "supports_function_calling": true, "supports_reasoning": true, + "supports_sampling_params": false, "supports_tool_choice": true, "supports_vision": true }, @@ -21752,6 +21978,7 @@ "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_sampling_params": false, "supports_tool_choice": true, "supports_vision": true }, @@ -21815,6 +22042,7 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, + "supports_sampling_params": false, "supports_tool_choice": true, "supports_vision": true }, @@ -27672,6 +27900,7 @@ "fireworks_ai/accounts/fireworks/models/gpt-oss-120b": { "cache_read_input_token_cost": 1.5e-08, "cache_read_input_token_cost_priority": 1.8e-08, + "deprecation_date": "2026-11-07", "input_cost_per_token": 1.5e-07, "input_cost_per_token_priority": 1.8e-07, "litellm_provider": "fireworks_ai", @@ -27681,7 +27910,7 @@ "mode": "chat", "output_cost_per_token": 6e-07, "output_cost_per_token_priority": 7.2e-07, - "source": "https://api.fireworks.ai/v1/serverless/models", + "source": "https://api.fireworks.ai/v1/serverless/models?format=nested", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -28072,6 +28301,7 @@ "fireworks_ai/gpt-oss-120b": { "cache_read_input_token_cost": 1.5e-08, "cache_read_input_token_cost_priority": 1.8e-08, + "deprecation_date": "2026-11-07", "input_cost_per_token": 1.5e-07, "input_cost_per_token_priority": 1.8e-07, "litellm_provider": "fireworks_ai", @@ -28081,7 +28311,7 @@ "mode": "chat", "output_cost_per_token": 6e-07, "output_cost_per_token_priority": 7.2e-07, - "source": "https://api.fireworks.ai/v1/serverless/models", + "source": "https://api.fireworks.ai/v1/serverless/models?format=nested", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -28740,6 +28970,7 @@ "search_context_size_medium": 0.035, "search_context_size_high": 0.035 }, + "search_free_requests": {"count": 1500, "period": "day", "shared_group": "gemini-2-flash"}, "google_maps_grounding_cost_per_query": 0.025, "input_cost_per_audio_token_batches": 5e-07, "input_cost_per_token_batches": 1.5e-07, @@ -28854,6 +29085,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query" }, "gemini-3-pro-image-preview": { @@ -28906,6 +29138,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query" }, "gemini-3.1-flash-image": { @@ -28956,6 +29189,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query" }, "gemini-3.1-flash-image-preview": { @@ -28999,6 +29233,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query" }, "gemini-3.1-flash-lite-image": { @@ -29094,6 +29329,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014 }, @@ -29155,6 +29391,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014, "input_cost_per_audio_token_batches": 2.5e-07 @@ -29202,6 +29439,7 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, + "supports_sampling_params": false, "supports_system_messages": true, "supports_tool_choice": true, "supports_url_context": true, @@ -29214,6 +29452,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014 }, @@ -29300,6 +29539,7 @@ "search_context_size_medium": 0.035, "search_context_size_high": 0.035 }, + "search_free_requests": {"count": 1500, "period": "day", "shared_group": "gemini-2-flash"}, "google_maps_grounding_cost_per_query": 0.025, "input_cost_per_audio_token_batches": 5e-08, "input_cost_per_token_batches": 5e-08, @@ -29354,6 +29594,7 @@ "search_context_size_medium": 0.035, "search_context_size_high": 0.035 }, + "search_free_requests": {"count": 1500, "period": "day", "shared_group": "gemini-2-flash"}, "google_maps_grounding_cost_per_query": 0.025, "supports_image_size": false }, @@ -29400,6 +29641,7 @@ "search_context_size_medium": 0.035, "search_context_size_high": 0.035 }, + "search_free_requests": {"count": 1500, "period": "day", "shared_group": "gemini-2-flash"}, "google_maps_grounding_cost_per_query": 0.025, "supports_image_size": false }, @@ -29587,6 +29829,7 @@ "search_context_size_medium": 0.035, "search_context_size_high": 0.035 }, + "search_free_requests": {"count": 10000, "period": "day", "shared_group": "gemini-2.5-pro"}, "google_maps_grounding_cost_per_query": 0.025, "input_cost_per_token_above_200k_tokens_priority": 4.5e-06, "input_cost_per_token_batches": 6.25e-07, @@ -29624,6 +29867,7 @@ "output_cost_per_token_priority": 2.16e-05, "prompt_cache_min_tokens": 4096.0, "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", @@ -29704,6 +29948,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014 }, @@ -29760,6 +30005,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query" }, "vertex_ai/gemini-3-flash-preview": { @@ -29784,6 +30030,7 @@ "output_cost_per_token_flex": 1.5e-06, "output_cost_per_token_priority": 5.4e-06, "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", @@ -29866,6 +30113,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014, "input_cost_per_token_batches": 7.5e-07, @@ -29914,6 +30162,7 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, + "supports_sampling_params": false, "supports_system_messages": true, "supports_tool_choice": true, "supports_url_context": true, @@ -29930,6 +30179,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014 }, @@ -29974,6 +30224,7 @@ "supports_reasoning": true, "supports_minimal_reasoning_effort": false, "supports_response_schema": true, + "supports_sampling_params": false, "supports_system_messages": true, "supports_tool_choice": true, "supports_url_context": true, @@ -29990,6 +30241,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014 }, @@ -30016,6 +30268,7 @@ "prompt_cache_min_tokens": 4096.0, "regional_endpoint_uplift_multiplier": 1.1, "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", @@ -30040,6 +30293,7 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, + "supports_sampling_params": false, "supports_system_messages": true, "supports_tool_choice": true, "supports_url_context": true, @@ -30089,6 +30343,7 @@ "supports_reasoning": true, "supports_minimal_reasoning_effort": false, "supports_response_schema": true, + "supports_sampling_params": false, "supports_system_messages": true, "supports_tool_choice": false, "supports_url_context": false, @@ -30161,6 +30416,7 @@ "output_cost_per_token_priority": 2.16e-05, "prompt_cache_min_tokens": 4096.0, "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", @@ -30247,6 +30503,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014 }, @@ -30574,6 +30831,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "supports_reasoning": false }, @@ -30618,6 +30876,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query" }, "gemini/gemini-3.1-flash-lite-preview": { @@ -30679,6 +30938,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014, "input_cost_per_audio_token_batches": 2.5e-07 @@ -30828,6 +31088,7 @@ "search_context_size_medium": 0.035, "search_context_size_high": 0.035 }, + "search_free_requests": {"count": 1500, "period": "day", "shared_group": "gemini-2-flash"}, "google_maps_grounding_cost_per_query": 0.025, "input_cost_per_audio_token_batches": 5e-07, "input_cost_per_audio_token_priority": 1.8e-06, @@ -30940,6 +31201,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "supports_reasoning": true }, @@ -31004,6 +31266,7 @@ "output_cost_per_token_batches": 1.5e-06, "rpm": 1000.0, "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "source": "https://ai.google.dev/gemini-api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", @@ -31154,6 +31417,7 @@ "search_context_size_medium": 0.035, "search_context_size_high": 0.035 }, + "search_free_requests": {"count": 1500, "period": "day", "shared_group": "gemini-2-flash"}, "google_maps_grounding_cost_per_query": 0.025, "input_cost_per_audio_token_batches": 1.5e-07, "input_cost_per_audio_token_priority": 5.4e-07, @@ -31359,6 +31623,7 @@ "search_context_size_medium": 0.035, "search_context_size_high": 0.035 }, + "search_free_requests": {"count": 10000, "period": "day", "shared_group": "gemini-2.5-pro"}, "google_maps_grounding_cost_per_query": 0.025, "input_cost_per_token_batches": 6.25e-07, "input_cost_per_token_flex": 6.25e-07, @@ -31456,6 +31721,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014, "input_cost_per_audio_token_batches": 2.5e-07, @@ -31504,6 +31770,7 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, + "supports_sampling_params": false, "supports_system_messages": true, "supports_tool_choice": true, "supports_url_context": true, @@ -31517,6 +31784,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014 }, @@ -31573,6 +31841,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014, "input_cost_per_audio_token_batches": 5e-07, @@ -31636,6 +31905,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014, "input_cost_per_token_batches": 7.5e-07, @@ -31685,6 +31955,7 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, + "supports_sampling_params": false, "supports_system_messages": true, "supports_tool_choice": true, "supports_url_context": true, @@ -31701,6 +31972,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014 }, @@ -31746,6 +32018,7 @@ "supports_reasoning": true, "supports_minimal_reasoning_effort": false, "supports_response_schema": true, + "supports_sampling_params": false, "supports_system_messages": true, "supports_tool_choice": true, "supports_url_context": true, @@ -31762,6 +32035,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014 }, @@ -31807,6 +32081,7 @@ "supports_reasoning": true, "supports_minimal_reasoning_effort": false, "supports_response_schema": true, + "supports_sampling_params": false, "supports_system_messages": true, "supports_tool_choice": true, "supports_url_context": true, @@ -31823,6 +32098,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014 }, @@ -31918,6 +32194,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014, "input_cost_per_token_flex": 1e-06, @@ -31981,6 +32258,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014, "input_cost_per_token_flex": 1e-06, @@ -32009,6 +32287,7 @@ "output_cost_per_token_flex": 1.5e-06, "output_cost_per_token_priority": 5.4e-06, "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", @@ -32123,6 +32402,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014, "input_cost_per_token_batches": 7.5e-07, @@ -32171,6 +32451,7 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, + "supports_sampling_params": false, "supports_system_messages": true, "supports_tool_choice": true, "supports_url_context": true, @@ -32187,6 +32468,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014 }, @@ -32231,6 +32513,7 @@ "supports_reasoning": true, "supports_minimal_reasoning_effort": false, "supports_response_schema": true, + "supports_sampling_params": false, "supports_system_messages": true, "supports_tool_choice": true, "supports_url_context": true, @@ -32247,6 +32530,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014 }, @@ -32272,6 +32556,7 @@ "output_cost_per_token_priority": 6.75e-06, "prompt_cache_min_tokens": 4096.0, "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", @@ -32297,6 +32582,7 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, + "supports_sampling_params": false, "supports_system_messages": true, "supports_tool_choice": true, "supports_url_context": true, @@ -32346,6 +32632,7 @@ "supports_reasoning": true, "supports_minimal_reasoning_effort": false, "supports_response_schema": true, + "supports_sampling_params": false, "supports_system_messages": true, "supports_tool_choice": false, "supports_url_context": false, @@ -32940,6 +33227,7 @@ "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_reasoning": true, + "supports_sampling_params": false, "supports_vision": true }, "github_copilot/gemini-3.8-flash": { @@ -32958,6 +33246,7 @@ "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_reasoning": true, + "supports_sampling_params": false, "supports_vision": true }, "github_copilot/gpt-3.5-turbo": { @@ -52241,6 +52530,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014 }, @@ -52303,6 +52593,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014, "input_cost_per_audio_token_batches": 2.5e-07 @@ -52351,6 +52642,7 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, + "supports_sampling_params": false, "supports_system_messages": true, "supports_tool_choice": true, "supports_url_context": true, @@ -52363,6 +52655,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, + "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014 }, @@ -61146,6 +61439,41 @@ "supports_tool_choice": false, "supports_vision": true }, + "volcengine/doubao-seed-2-1-pro-260915": { + "cache_read_input_token_cost": 1.725e-07, + "input_cost_per_token": 8.625e-07, + "litellm_provider": "volcengine", + "max_input_tokens": 1024000, + "max_output_tokens": 256000, + "max_tokens": 256000, + "mode": "chat", + "output_cost_per_token": 4.3125e-06, + "source": "https://www.volcengine.com/docs/82379/1544106", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": false, + "supports_vision": true + }, + "volcengine/doubao-seed-2-1-lite-260915": { + "cache_read_input_audio_token_cost": 3.45e-07, + "cache_read_input_token_cost": 2.3e-08, + "input_cost_per_audio_token": 1.725e-06, + "input_cost_per_token": 1.15e-07, + "litellm_provider": "volcengine", + "max_input_tokens": 1024000, + "max_output_tokens": 256000, + "max_tokens": 256000, + "mode": "chat", + "output_cost_per_token": 3.88126e-07, + "source": "https://www.volcengine.com/docs/82379/1544106", + "supports_audio_input": true, + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": false, + "supports_vision": true + }, "volcengine/doubao-seed-2-1-turbo-260628": { "cache_read_input_token_cost": 8.625e-08, "input_cost_per_token": 4.3125e-07, @@ -63808,6 +64136,7 @@ "fireworks_ai/nemotron-lightning-3p5-30b-a3b": { "cache_read_input_token_cost": 1e-08, "cache_read_input_token_cost_priority": 1.25e-08, + "deprecation_date": "2026-11-07", "input_cost_per_token": 5e-08, "input_cost_per_token_priority": 6.25e-08, "litellm_provider": "fireworks_ai", @@ -63817,7 +64146,7 @@ "mode": "chat", "output_cost_per_token": 2e-07, "output_cost_per_token_priority": 2.5e-07, - "source": "https://docs.fireworks.ai/serverless/pricing", + "source": "https://api.fireworks.ai/v1/serverless/models?format=nested", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -63827,6 +64156,7 @@ "fireworks_ai/nemotron-3-ultra-nvfp4": { "cache_read_input_token_cost": 1.2e-07, "cache_read_input_token_cost_priority": 1.5e-07, + "deprecation_date": "2026-11-07", "input_cost_per_token": 6e-07, "input_cost_per_token_priority": 7.5e-07, "litellm_provider": "fireworks_ai", @@ -63836,7 +64166,7 @@ "mode": "chat", "output_cost_per_token": 2.4e-06, "output_cost_per_token_priority": 3e-06, - "source": "https://api.fireworks.ai/v1/serverless/models", + "source": "https://api.fireworks.ai/v1/serverless/models?format=nested", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -63877,6 +64207,7 @@ "fireworks_ai/accounts/fireworks/models/nemotron-lightning-3p5-30b-a3b": { "cache_read_input_token_cost": 1e-08, "cache_read_input_token_cost_priority": 1.25e-08, + "deprecation_date": "2026-11-07", "input_cost_per_token": 5e-08, "input_cost_per_token_priority": 6.25e-08, "litellm_provider": "fireworks_ai", @@ -63886,7 +64217,7 @@ "mode": "chat", "output_cost_per_token": 2e-07, "output_cost_per_token_priority": 2.5e-07, - "source": "https://docs.fireworks.ai/serverless/pricing", + "source": "https://api.fireworks.ai/v1/serverless/models?format=nested", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -63896,6 +64227,7 @@ "fireworks_ai/accounts/fireworks/models/nemotron-3-ultra-nvfp4": { "cache_read_input_token_cost": 1.2e-07, "cache_read_input_token_cost_priority": 1.5e-07, + "deprecation_date": "2026-11-07", "input_cost_per_token": 6e-07, "input_cost_per_token_priority": 7.5e-07, "litellm_provider": "fireworks_ai", @@ -63905,7 +64237,7 @@ "mode": "chat", "output_cost_per_token": 2.4e-06, "output_cost_per_token_priority": 3e-06, - "source": "https://api.fireworks.ai/v1/serverless/models", + "source": "https://api.fireworks.ai/v1/serverless/models?format=nested", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -65529,6 +65861,7 @@ "supports_tool_choice": true, "supports_response_schema": true, "supports_reasoning": true, + "supports_sampling_params": false, "supports_vision": true, "source": "https://deepinfra.com/pricing", "supports_audio_input": true @@ -66998,6 +67331,7 @@ "fireworks_ai/accounts/fireworks/routers/glm-5p3-flash-us": { "cache_read_input_token_cost": 4.5e-08, "cache_read_input_token_cost_priority": 5.625e-08, + "deprecation_date": "2026-11-07", "input_cost_per_token": 2.25e-07, "input_cost_per_token_priority": 2.8125e-07, "litellm_provider": "fireworks_ai", @@ -67032,6 +67366,7 @@ "fireworks_ai/glm-5p3-flash-us": { "cache_read_input_token_cost": 4.5e-08, "cache_read_input_token_cost_priority": 5.625e-08, + "deprecation_date": "2026-11-07", "input_cost_per_token": 2.25e-07, "input_cost_per_token_priority": 2.8125e-07, "litellm_provider": "fireworks_ai", @@ -67049,6 +67384,7 @@ "fireworks_ai/accounts/fireworks/models/inkling": { "cache_read_input_token_cost": 1.7e-07, "cache_read_input_token_cost_priority": 1.7e-07, + "deprecation_date": "2026-11-07", "input_cost_per_token": 1e-06, "input_cost_per_token_priority": 1e-06, "litellm_provider": "fireworks_ai", @@ -68967,6 +69303,7 @@ "perplexity/google/gemini-3.5-flash-lite": { "litellm_provider": "perplexity", "mode": "responses", + "supports_sampling_params": false, "supports_web_search": true, "supports_function_calling": true, "input_cost_per_token": 3e-07, @@ -68977,6 +69314,7 @@ "perplexity/google/gemini-3.6-flash": { "litellm_provider": "perplexity", "mode": "responses", + "supports_sampling_params": false, "supports_web_search": true, "supports_function_calling": true, "input_cost_per_token": 1.5e-06, @@ -68987,6 +69325,7 @@ "perplexity/google/gemini-3.7-flash": { "litellm_provider": "perplexity", "mode": "responses", + "supports_sampling_params": false, "supports_web_search": true, "supports_function_calling": true, "input_cost_per_token": 7.5e-07, @@ -70134,6 +70473,20 @@ "output_cost_per_token_batches": 2.42e-06, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, + "azure/eu/o3": { + "deprecation_date": "2026-11-19", + "cache_read_input_token_cost": 5.5e-07, + "input_cost_per_token": 2.2e-06, + "input_cost_per_token_batches": 1.1e-06, + "litellm_provider": "azure", + "max_input_tokens": 200000, + "max_output_tokens": 100000, + "max_tokens": 100000, + "mode": "chat", + "output_cost_per_token": 8.8e-06, + "output_cost_per_token_batches": 4.4e-06, + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" + }, "azure/eu/o3-2025-04-16": { "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 5.5e-07, @@ -70157,6 +70510,20 @@ "output_cost_per_token": 4.4e-05, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, + "azure/eu/o4-mini": { + "deprecation_date": "2026-11-19", + "cache_read_input_token_cost": 3.03e-07, + "input_cost_per_token": 1.21e-06, + "input_cost_per_token_batches": 6.05e-07, + "litellm_provider": "azure", + "max_input_tokens": 200000, + "max_output_tokens": 100000, + "max_tokens": 100000, + "mode": "chat", + "output_cost_per_token": 4.84e-06, + "output_cost_per_token_batches": 2.42e-06, + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" + }, "azure/eu/o4-mini-2025-04-16": { "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 3.03e-07, @@ -71050,6 +71417,7 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, + "supports_sampling_params": false, "supports_vision": true, "supports_web_search": true }, @@ -71067,6 +71435,7 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, + "supports_sampling_params": false, "supports_vision": true, "supports_web_search": true }, @@ -73997,6 +74366,7 @@ "perplexity/google/gemini-3.8-flash": { "litellm_provider": "perplexity", "mode": "responses", + "supports_sampling_params": false, "input_cost_per_token": 7.5e-07, "output_cost_per_token": 3.75e-06, "cache_read_input_token_cost": 7.5e-08, @@ -74739,12 +75109,10 @@ "gemini-nano-banana-2.1": { "cache_read_input_token_cost": 1.5e-07, "cache_read_input_token_cost_batches": 7.5e-08, - "cache_read_input_token_cost_flex": 7.5e-08, "cache_read_input_token_cost_priority": 2.7e-07, "input_cost_per_image": 0.00168, "input_cost_per_token": 1.5e-06, "input_cost_per_token_batches": 7.5e-07, - "input_cost_per_token_flex": 7.5e-07, "input_cost_per_token_priority": 2.7e-06, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 131072, @@ -74755,7 +75123,6 @@ "output_cost_per_image_token": 3e-05, "output_cost_per_token": 7.5e-06, "output_cost_per_token_batches": 3.75e-06, - "output_cost_per_token_flex": 3.75e-06, "output_cost_per_token_priority": 1.35e-05, "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", @@ -74788,12 +75155,10 @@ "vertex_ai/gemini-nano-banana-2.1": { "cache_read_input_token_cost": 1.5e-07, "cache_read_input_token_cost_batches": 7.5e-08, - "cache_read_input_token_cost_flex": 7.5e-08, "cache_read_input_token_cost_priority": 2.7e-07, "input_cost_per_image": 0.00168, "input_cost_per_token": 1.5e-06, "input_cost_per_token_batches": 7.5e-07, - "input_cost_per_token_flex": 7.5e-07, "input_cost_per_token_priority": 2.7e-06, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 131072, @@ -74804,7 +75169,6 @@ "output_cost_per_image_token": 3e-05, "output_cost_per_token": 7.5e-06, "output_cost_per_token_batches": 3.75e-06, - "output_cost_per_token_flex": 3.75e-06, "output_cost_per_token_priority": 1.35e-05, "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", @@ -76604,5 +76968,25 @@ "supported_output_modalities": [ "text" ] + }, + "fireworks_ai/accounts/fireworks/models/deepseek-v4p1-flash-1017-us": { + "cache_read_input_token_cost": 9e-09, + "cache_read_input_token_cost_priority": 1.125e-08, + "input_cost_per_token": 4.5e-07, + "input_cost_per_token_priority": 5.625e-07, + "litellm_provider": "fireworks_ai", + "max_input_tokens": 1048576, + "max_output_tokens": 393216, + "max_tokens": 393216, + "mode": "chat", + "output_cost_per_token": 1.8e-06, + "output_cost_per_token_priority": 2.25e-06, + "source": "https://docs.fireworks.ai/serverless/us-only-serverless", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true } } diff --git a/model_prices_and_context_window.schema.json b/model_prices_and_context_window.schema.json index 0e8f4f596c0..d4dfeb25429 100644 --- a/model_prices_and_context_window.schema.json +++ b/model_prices_and_context_window.schema.json @@ -553,6 +553,7 @@ "completion", "embedding", "evaluation", + "extraction", "guardrail", "image_edit", "image_generation", @@ -954,6 +955,33 @@ }, "additionalProperties": false }, + "search_free_requests": { + "type": "object", + "description": "Free Google Search grounding requests per period, shared across models in the same shared_group.", + "required": [ + "count", + "period", + "shared_group" + ], + "additionalProperties": false, + "properties": { + "count": { + "type": "integer", + "minimum": 0 + }, + "period": { + "type": "string", + "enum": [ + "day", + "month" + ] + }, + "shared_group": { + "type": "string", + "pattern": "\\S" + } + } + }, "source": { "type": "string", "description": "URL of the provider pricing/model page this entry was taken from." diff --git a/osv-scanner.toml b/osv-scanner.toml index 60f163392a8..bb802137f6e 100644 --- a/osv-scanner.toml +++ b/osv-scanner.toml @@ -7,3 +7,16 @@ reason = "diskcache has no fixed release published; remove this entry once one e id = "GHSA-vfj7-8cjw-p6xm" ignoreUntil = 2026-11-03 reason = "braces has no fixed release published (3.0.3, 2024-05-21, is latest and last_affected); dev-only via knip > fast-glob > micromatch; remove this entry once one exists" + +[[IgnoredVulns]] +id = "GHSA-6q48-6c7w-9gw2" +ignoreUntil = 2026-10-23 +reason = "certifi 2026.10.19 (published 2026-10-20) is inside the 3-day uv exclude-newer window until 2026-10-23 02:24 UTC; bump certifi and remove this entry once it clears" + +[[PackageOverrides]] +name = "pillow" +version = "12.3.0" +ecosystem = "PyPI" +vulnerability.ignore = true +effectiveUntil = 2026-10-27 +reason = "pillow 13.0.0 requires Python >= 3.11, so the Python 3.10 resolution of the ci and dev groups stays on 12.3.0; 3.11+ is on 13.0.0" diff --git a/pyproject.toml b/pyproject.toml index 9871a83b421..9076760153a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [project] name = "litellm" -version = "1.107.0" +version = "1.108.0" description = "Library to easily interface with LLM API providers" readme = "README.md" requires-python = ">=3.10, <3.15" @@ -75,11 +75,11 @@ proxy = [ "boto3>=1.43.1,<2.0", "azure-identity>=1.25.2,<2.0", "azure-storage-blob>=12.28.0,<13.0", - "mcp>=2.2.0,<3", - "httpx2>=2.5.0,<3", + "mcp>=2.3.0,<3", + "httpx2>=2.10.0,<3", "pydantic>=2.12.0,<3", - "litellm-proxy-extras==0.4.110", - "litellm-enterprise==0.1.78", + "litellm-proxy-extras==0.4.111", + "litellm-enterprise==0.1.79", "RestrictedPython>=8.5,<9.0", "rich>=13.9.4,<14.0", "InquirerPy>=0.3.4,<1.0", @@ -125,7 +125,7 @@ utils = [ "numpydoc>=1.8.0,<2.0", ] caching = ["diskcache>=5.6.3,<6.0"] -mcp = ["mcp>=2.2.0,<3", "httpx2>=2.5.0,<3", "pydantic>=2.12.0,<3"] +mcp = ["mcp>=2.3.0,<3", "httpx2>=2.10.0,<3", "pydantic>=2.12.0,<3"] # Driver for the MongoDB Atlas vector store; Atlas Vector Search has no HTTP query API. # The floor is 4.9 because that is the release AsyncMongoClient landed in. # SAML SSO for the admin UI. python3-saml pulls in xmlsec/lxml, whose wheels @@ -243,7 +243,7 @@ e2e-dev = [ "locust==2.45.0", "anthropic==0.84.0", "psutil==7.2.2", - "mcp>=2.2.0,<3", + "mcp>=2.3.0,<3", ] admin-mcp = [ "litellm-admin-mcp @ https://github.com/BerriAI/liteadmin-mcp/archive/d35ec9c19c117d4c50cc1eccf6ce1296aac25a1a.tar.gz#sha256=86b930f6706fb2da10d53d1798ee7fd14e44fb0afdef0da122cf0e6bb88fa2c3 ; python_version >= '3.12'", @@ -269,7 +269,8 @@ ci = [ # protobuf, Pillow is a compiled C extension). "tenacity==8.5.0", "google-generativeai==0.8.6", - "Pillow==12.3.0", + "Pillow==12.3.0; python_version == '3.10'", + "Pillow==13.0.0; python_version >= '3.11'", # Azure batch E2E tests still import psycopg2 directly. "psycopg2-binary==2.9.11", "pytest-codspeed==4.3.0", @@ -303,7 +304,7 @@ healthcheck = [ benchmarks = [ "pytest==9.0.3", "pytest-codspeed==4.3.0", - "mcp>=2.2.0,<3", + "mcp>=2.3.0,<3", "a2a-sdk==1.1.0", ] @@ -363,6 +364,7 @@ override-dependencies = [ # a2a-sdk 1.x requires packaging>=24.0; lunary 1.4.x still caps at <24.0. "packaging>=24.0", "cryptography>=50.0.0,<51.0", + "mcp>=2.3.0,<3", ] default-groups = ["dev"] required-version = ">=0.10.9" @@ -376,7 +378,7 @@ litellm-enterprise = { workspace = true } members = ["enterprise", "litellm-proxy-extras"] [tool.commitizen] -version = "1.107.0" +version = "1.108.0" version_files = [ "pyproject.toml:^version", ] diff --git a/tests/benchmarks/test_extraction_guardrail_benchmarks.py b/tests/benchmarks/test_extraction_guardrail_benchmarks.py new file mode 100644 index 00000000000..0d8a3db42ce --- /dev/null +++ b/tests/benchmarks/test_extraction_guardrail_benchmarks.py @@ -0,0 +1,61 @@ +import asyncio +from typing import Final, Literal + +import pytest + +from litellm.integrations.custom_guardrail import CustomGuardrail +from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj +from litellm.llms.cloudflare.extraction.guardrail_translation.handler import ExtractionHandler +from litellm.types.extraction import ExtractionResponse +from litellm.types.utils import GenericGuardrailAPIInputs + +MANY_FIELDS: Final = 2_000 + + +class _MaskingGuardrail(CustomGuardrail): + def __init__(self) -> None: + super().__init__(guardrail_name="masking") + + async def apply_guardrail( + self, + inputs: GenericGuardrailAPIInputs, + request_data: dict[str, object], + input_type: Literal["request", "response"], + logging_obj: LiteLLMLoggingObj | None = None, + ) -> GenericGuardrailAPIInputs: + return GenericGuardrailAPIInputs(texts=[text.replace("secret", "[MASKED]") for text in inputs.get("texts", [])]) + + +@pytest.mark.benchmark +def test_extraction_request_guardrail_over_many_field_instructions() -> None: + data: Final = { + "model": "invoice-reader", + "fields": { + f"field_{index}": {"type": "text", "instructions": f"secret {index}"} for index in range(MANY_FIELDS) + }, + } + + result: Final = asyncio.run(ExtractionHandler().process_input_messages(data, _MaskingGuardrail())) + + assert result["fields"] == { + f"field_{index}": {"type": "text", "instructions": f"[MASKED] {index}"} for index in range(MANY_FIELDS) + } + + +@pytest.mark.benchmark +def test_extraction_response_guardrail_over_many_text_answers() -> None: + response: Final = ExtractionResponse.model_validate( + { + "model": "invoice-reader", + "answers": {f"field_{index}": {"type": "text", "value": f"secret {index}"} for index in range(MANY_FIELDS)}, + "truncated": False, + "usage": {"input_tokens": 52, "output_tokens": 0}, + } + ) + + result: Final = asyncio.run(ExtractionHandler().process_output_response(response, _MaskingGuardrail())) + + assert isinstance(result, ExtractionResponse) + assert {name: answer.value for name, answer in result.answers.items()} == { + f"field_{index}": f"[MASKED] {index}" for index in range(MANY_FIELDS) + } diff --git a/tests/code_coverage_tests/check_no_publicly_known_master_key.py b/tests/code_coverage_tests/check_no_publicly_known_master_key.py index 4452d59c314..f87d36ecc36 100644 --- a/tests/code_coverage_tests/check_no_publicly_known_master_key.py +++ b/tests/code_coverage_tests/check_no_publicly_known_master_key.py @@ -9,7 +9,6 @@ from typing import Final REPO_ROOT: Final = Path(__file__).resolve().parents[2] PUBLICLY_KNOWN_MASTER_KEY_PREFIX: Final = "sk-" + "1234" -GENERATED_DASHBOARD_BUNDLE_PATHSPEC: Final = ":(exclude)litellm/proxy/_experimental/out" def _file_violations(repo_root: Path, relative_path: str) -> tuple[str, ...]: @@ -35,7 +34,7 @@ def _file_violations(repo_root: Path, relative_path: str) -> tuple[str, ...]: def _tracked_paths(repo_root: Path) -> tuple[str, ...]: result: Final = subprocess.run( - ["git", "-C", os.fspath(repo_root), "ls-files", "-z", "--", ".", GENERATED_DASHBOARD_BUNDLE_PATHSPEC], + ["git", "-C", os.fspath(repo_root), "ls-files", "-z"], check=True, stdout=subprocess.PIPE, ) diff --git a/tests/code_coverage_tests/check_provider_folders_documented.py b/tests/code_coverage_tests/check_provider_folders_documented.py index 6f58b393cd1..b4e60246774 100644 --- a/tests/code_coverage_tests/check_provider_folders_documented.py +++ b/tests/code_coverage_tests/check_provider_folders_documented.py @@ -32,6 +32,7 @@ EXCLUDED_FOLDERS = { "claude_code", "codex", "opencode", + "pi", "deepagents", "tool_loop", } diff --git a/tests/code_coverage_tests/recursive_detector.py b/tests/code_coverage_tests/recursive_detector.py index 487c00f735a..7610d602fff 100644 --- a/tests/code_coverage_tests/recursive_detector.py +++ b/tests/code_coverage_tests/recursive_detector.py @@ -77,6 +77,7 @@ IGNORE_FUNCTIONS = [ "_restore_redacted_nested_value", # max depth set (default 10), mirrors _redact_agent_params_tree on the write side. "_unqualified", # bounded by the qualifier depth of a static TypedDict annotation (Annotated, Required/NotRequired, ReadOnly around one type, no cycles possible). "_render_json", # bounded by the nesting depth of a pydantic-validated JsonValue from the operator's config (a finite JSON tree, no cycles possible). + "with_id_fields_replaced", # harness/opencode: bounded by the nesting depth of the JsonValue that validate_json parsed from `opencode export`, which refuses nesting past ~200 levels. "completion_cost", # max depth 1: recursion only fires for mixed-tier Responses WS logging objects, and each split part carries a single service_tier so _split_responses_ws_logging_object_by_service_tier returns None. "_string_leaves", # bounded by the nesting depth of a safe_json_structure output (a finite JSON tree, no cycles possible). "_replace_string_leaves", # bounded by the nesting depth of a safe_json_structure output (a finite JSON tree, no cycles possible). diff --git a/tests/code_coverage_tests/router_code_coverage.py b/tests/code_coverage_tests/router_code_coverage.py index 3f0ad07a876..55435c51648 100644 --- a/tests/code_coverage_tests/router_code_coverage.py +++ b/tests/code_coverage_tests/router_code_coverage.py @@ -93,6 +93,7 @@ ignored_function_names = [ "_apply_updated_routing_strategy_args", # Tested via update_settings in test_lowest_latency.py (file lacks "router" in name) "_wait_for_scheduler_turn", # Tested through prioritized acompletion and atext_completion in test_router.py "arm_routing_read_prefetch", # Tested in tests/unit/caching/test_request_redis_batch_pre_call.py (file lacks "router" in name) + "_deployment_params_base_model", # Tested through log_retry in test_router_helper_utils.py "_configured_model_info", # Tested through get_configured_service_tiers in test_router.py "_routable_deployments", # Tested through get_configured_service_tiers and get_routable_upstream_model in test_router.py "_async_get_available_deployment", # Body of the `route {model}` phase wrapper, exercised through async_get_available_deployment in test_router.py @@ -114,6 +115,10 @@ ignored_function_names = [ "_aanthropic_messages_yield_recovered", # Tested through every mid-stream retry and fallback test in test_router.py "_anthropic_messages_policy_retries", # Tested through the retry budget precedence test in test_router.py "_get_wildcard_deployments", # Tested through the get_model_list_of_routed_group wildcard test in test_router.py + "_prompt_management_acompletion", # Tested through the scheduled prompt-management model test in test_router.py + "_request_deployment_params", # Tested through the team-route and deployment-id drop_params priority tests in test_router.py + "split_request_priority", # Tested through the acompletion, atext_completion and queue route priority tests + "_pinned_deployment", # Tested through the deployment-id scheduler test in test_router.py "_is_fallback_hop", # Tested through the order fallback hop tests in test_router_order_fallback.py "_deployment_that_just_failed", # Tested through the same-boundary hop test in test_router_order_fallback.py "_merged_tools", # Tested through the _update_kwargs_with_deployment tools merge tests in test_router.py diff --git a/tests/code_coverage_tests/test_check_no_publicly_known_master_key.py b/tests/code_coverage_tests/test_check_no_publicly_known_master_key.py index 07930dbb60b..1c3c7c45a5e 100644 --- a/tests/code_coverage_tests/test_check_no_publicly_known_master_key.py +++ b/tests/code_coverage_tests/test_check_no_publicly_known_master_key.py @@ -32,8 +32,11 @@ def _run(guard: Path) -> subprocess.CompletedProcess[str]: return subprocess.run([sys.executable, str(guard)], capture_output=True, text=True) -def test_generated_dashboard_bundle_is_not_flagged(tmp_path: Path) -> None: - guard: Final = _repo_with(tmp_path, {BUNDLE_CHUNK: f'api_key="{RETIRED_KEY}"\n', "docs/a.md": "clean\n"}) +def test_clean_tracked_files_pass(tmp_path: Path) -> None: + guard: Final = _repo_with( + tmp_path, + {BUNDLE_CHUNK: 'api_key="test-key"\n', "docs/a.md": "clean\n"}, + ) result: Final = _run(guard) @@ -43,16 +46,17 @@ def test_generated_dashboard_bundle_is_not_flagged(tmp_path: Path) -> None: @pytest.mark.parametrize( "source_path", - ["litellm/proxy/proxy_server.py", "ui/litellm-dashboard/src/app/page.tsx", "litellm/proxy/_experimental/x.py"], + [ + "litellm/proxy/proxy_server.py", + "ui/litellm-dashboard/src/app/page.tsx", + "litellm/proxy/_experimental/x.py", + BUNDLE_CHUNK, + ], ) -def test_source_files_are_still_flagged(tmp_path: Path, source_path: str) -> None: - guard: Final = _repo_with( - tmp_path, - {BUNDLE_CHUNK: f'api_key="{RETIRED_KEY}"\n', source_path: f'key = "{RETIRED_KEY}"\n'}, - ) +def test_tracked_files_are_flagged(tmp_path: Path, source_path: str) -> None: + guard: Final = _repo_with(tmp_path, {source_path: f'key = "{RETIRED_KEY}"\n'}) result: Final = _run(guard) assert result.returncode == 1 assert f"{source_path}:1" in result.stdout - assert BUNDLE_CHUNK not in result.stdout diff --git a/tests/e2e/coverage_registry/llm_conversational.yaml b/tests/e2e/coverage_registry/llm_conversational.yaml index b11ae907cfb..e3994e598c6 100644 --- a/tests/e2e/coverage_registry/llm_conversational.yaml +++ b/tests/e2e/coverage_registry/llm_conversational.yaml @@ -13,6 +13,8 @@ - {id: llm.chat_completions.openai.vision.nonstream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: openai, capability: vision, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "gpt-4o vision; high usage"} - {id: llm.chat_completions.openai.prompt_cache_5m.nonstream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: openai, capability: prompt_cache_5m, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Prompt caching cost optimization"} - {id: llm.chat_completions.openai.service_tier.nonstream.works, module: llm, tier: P1, subject_endpoint: chat_completions, route: openai, capability: service_tier, streaming: nonstream, assertions: [works], source: "OpenAI service_tier param", rationale: "OpenAI scale-tier request option is forwarded and echoed"} +- {id: llm.chat_completions.openai.prompt_cache_24h.nonstream.forwards_retention, module: llm, tier: P1, subject_endpoint: chat_completions, route: openai, capability: prompt_cache_24h, streaming: nonstream, assertions: [forwards_retention], source: "main.py completion()", fail_before_fix: proven, rationale: "prompt_cache_retention sent through the proxy, litellm.completion or Router.completion reaches the body sent to OpenAI /v1/chat/completions, so a caller asking for 24h prompt caching gets it instead of a silent drop"} +- {id: llm.chat_completions.openai.prompt_cache_24h.nonstream.bridge_forwards_retention, module: llm, tier: P1, subject_endpoint: chat_completions, route: openai, capability: prompt_cache_24h, streaming: nonstream, assertions: [forwards_retention], source: "main.py completion()", fail_before_fix: proven, rationale: "prompt_cache_retention on an openai/responses/ model (chat completions in, Responses out) reaches the body sent to OpenAI /v1/responses"} - {id: llm.chat_completions.openai.service_tier.stream.echoes_served_tier, module: llm, tier: P1, subject_endpoint: chat_completions, route: openai, capability: service_tier, streaming: stream, assertions: [works], source: "litellm_core_utils/streaming_handler.py", fail_before_fix: proven, rationale: "Every relayed stream chunk carries the service_tier OpenAI stamped on it, so a streaming caller can see which tier served the request"} - {id: llm.chat_completions.openai.thinking.nonstream.works, module: llm, tier: P1, subject_endpoint: chat_completions, route: openai, capability: thinking, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "o-series reasoning; emerging"} - {id: llm.chat_completions.openai.structured_output.nonstream.works, module: llm, tier: P1, subject_endpoint: chat_completions, route: openai, capability: structured_output, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "response_schema extraction"} @@ -68,6 +70,7 @@ - {id: llm.messages.anthropic.vision.nonstream.works, module: llm, tier: P0, subject_endpoint: messages, route: anthropic, capability: vision, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Vision via Messages API"} - {id: llm.messages.anthropic.prompt_cache_5m.nonstream.works, module: llm, tier: P0, subject_endpoint: messages, route: anthropic, capability: prompt_cache_5m, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Prompt caching via Messages API"} - {id: llm.messages.anthropic.thinking.nonstream.works, module: llm, tier: P1, subject_endpoint: messages, route: anthropic, capability: thinking, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Extended thinking via Messages API"} +- {id: llm.messages.bedrock_converse.basic.nonstream.works_for_kimi_k3_max_tokens_1, module: llm, tier: P0, subject_endpoint: messages, route: bedrock_converse, capability: basic, streaming: nonstream, assertions: [works_for_kimi_k3_max_tokens_1], source: "llm_translation/test_bedrock_kimi_k3_messages_e2e.py", rationale: "Bedrock Converse accepts max_tokens=1 on the Anthropic Messages surface after LiteLLM applies the model minimum", fail_before_fix: proven} - {id: llm.messages.bedrock_invoke.mid_conversation_system.nonstream.cache_hit, module: llm, tier: P0, subject_endpoint: messages, route: bedrock_invoke, capability: mid_conversation_system, streaming: nonstream, assertions: [works, cache_hit], source: "llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py", rationale: "Flagged Claude 4.8+/5 must keep mid-conversation system reminders in messages; hoisting mutates the system prefix and collapses the prompt cache (#32578/#32831/#32882)", fail_before_fix: proven} - {id: llm.messages.bedrock_invoke.mid_conversation_system.nonstream.works, module: llm, tier: P0, subject_endpoint: messages, route: bedrock_invoke, capability: mid_conversation_system, streaming: nonstream, assertions: [works], source: "llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py", rationale: "Claude <= 4.7 rejects role system inside messages; unflagged models must convert reminders to user turns in place (hoisting collapses the prompt cache) or every Claude Code session 400s (#32831)", fail_before_fix: proven} - {id: llm.messages.bedrock_invoke.web_search_server_tool.nonstream.works, module: llm, tier: P0, subject_endpoint: messages, route: bedrock_invoke, capability: web_search_server_tool, streaming: nonstream, assertions: [works], source: "llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py", rationale: "Bedrock hosts no web_search server tool, so this only works because interception rewrites it before the upstream call and the agentic loop feeds the results back in native shape; a regression that short-circuits or forwards it instead yields raw text or AWS's 400", fail_before_fix: unproven} diff --git a/tests/e2e/coverage_registry/schema.py b/tests/e2e/coverage_registry/schema.py index abef3266aa8..d2ba2c325df 100644 --- a/tests/e2e/coverage_registry/schema.py +++ b/tests/e2e/coverage_registry/schema.py @@ -81,6 +81,7 @@ LlmCapability = Literal[ "pdf_input", "logprobs", "prompt_cache_1h", + "prompt_cache_24h", "prompt_cache_5m", "response_headers", "service_tier", diff --git a/tests/e2e/llm_translation/test_bedrock_kimi_k3_messages_e2e.py b/tests/e2e/llm_translation/test_bedrock_kimi_k3_messages_e2e.py new file mode 100644 index 00000000000..b381fd0d9e1 --- /dev/null +++ b/tests/e2e/llm_translation/test_bedrock_kimi_k3_messages_e2e.py @@ -0,0 +1,71 @@ +from __future__ import annotations + +from typing import Final + +import pytest +from anthropic.types import Message, MessageParam +from e2e_metadata import Domain, Mode, Provider, Route, Subject, meta +from lifecycle import ResourceManager +from models import LiteLLMParamsBody +from proxy_client import ProxyClient +from sdk_clients import NO_PROXY_CACHE, SdkClients + +pytestmark = pytest.mark.e2e + +BEDROCK_MODEL: Final = "bedrock/us.moonshotai.kimi-k3" +MODEL_NAME: Final = "claude-kimi-k3" +MODEL_SWITCH_BETA: Final = ( + "claude-code-20250219,context-1m-2025-08-07,interleaved-thinking-2025-05-14," + "redact-thinking-2026-02-12,context-management-2025-06-27," + "prompt-caching-scope-2026-01-05,mid-conversation-system-2026-04-07" +) + + +def _register_model(proxy: ProxyClient, resources: ResourceManager) -> tuple[str, str]: + model_id: Final = proxy.create_model( + MODEL_NAME, + LiteLLMParamsBody( + model=BEDROCK_MODEL, + aws_access_key_id="os.environ/AWS_ACCESS_KEY_ID", + aws_secret_access_key="os.environ/AWS_SECRET_ACCESS_KEY", + aws_region_name="os.environ/AWS_REGION", + drop_params=True, + ), + ) + resources.defer(lambda: proxy.delete_model(model_id)) + return MODEL_NAME, resources.key(models=[MODEL_NAME]) + + +class TestBedrockKimiK3Messages: + @pytest.mark.covers("llm.messages.bedrock_converse.basic.nonstream.works_for_kimi_k3_max_tokens_1") + @meta( + Subject( + domain=Domain.LLM_TRANSLATION, + route=Route.MESSAGES, + providers=(Provider.BEDROCK,), + models=(BEDROCK_MODEL,), + mode=Mode.NONSTREAM, + ) + ) + def test_model_switch_probe_max_tokens_1_returns_message( + self, proxy: ProxyClient, resources: ResourceManager, sdk: SdkClients + ) -> None: + model, key = _register_model(proxy, resources) + client: Final = sdk.anthropic(key) + message_param: Final[MessageParam] = { + "role": "user", + "content": [{"type": "text", "text": "Hi", "cache_control": {"type": "ephemeral"}}], + } + message: Final = client.messages.create( + model=model, + max_tokens=1, + stream=False, + system="You are Claude Code, an assistant for software development.", + messages=[message_param], + extra_headers={"anthropic-beta": MODEL_SWITCH_BETA}, + extra_query={"beta": "true"}, + extra_body=NO_PROXY_CACHE, + ) + + assert isinstance(message, Message) + assert message.role == "assistant" diff --git a/tests/e2e/llm_translation/test_provider_features_e2e.py b/tests/e2e/llm_translation/test_provider_features_e2e.py index 9a3de0aba7d..60dfd49638f 100644 --- a/tests/e2e/llm_translation/test_provider_features_e2e.py +++ b/tests/e2e/llm_translation/test_provider_features_e2e.py @@ -1,4 +1,4 @@ -"""Live e2e for model-specific request features: service_tier. +"""Live e2e for model-specific request features: service_tier and prompt_cache_retention. Each case asserts the feature took effect, not just a 200. @@ -11,26 +11,38 @@ avoided here because it is capacity-constrained and returns a transient 429 when flex resources are unavailable. Bedrock and Vertex do not accept service_tier, so that cell is OpenAI-only by design. -Prompt caching lives in test_cache_control.py. +prompt_cache_retention is judged on the body OpenAI receives, captured by a live +provider edge, not on the reply: OpenAI echoes "24h" on gpt-5.5 even when the +request never carried the param, so an echo would pass with the param dropped. + +Prompt caching hits and misses live in test_cache_control.py. """ from __future__ import annotations +import queue +from collections.abc import Mapping +from dataclasses import dataclass, field from typing import Final import pytest +from pydantic import BaseModel -from e2e_config import unique_marker +from e2e_config import PROVIDER_EDGE_ADVERTISE_HOST, PROVIDER_EDGE_BIND_HOST, unique_marker from e2e_http import unwrap from e2e_metadata import Domain, Mode, Provider, Route, Subject, meta from lifecycle import ResourceManager from models import ChatBody, ChatMessage, LiteLLMParamsBody from passthrough_client import PassthroughClient +from provider_edge import LiveEdge, start_provider_edge +from proxy_client import ProxyClient pytestmark = pytest.mark.e2e SERVICE_TIER = "priority" OPENAI_BACKEND: Final = "openai/gpt-5.5" +OPENAI_RESPONSES_BRIDGE_BACKEND: Final = "openai/responses/gpt-5.5" +PROMPT_CACHE_RETENTION: Final = "24h" class TestServiceTier: @@ -74,3 +86,153 @@ class TestServiceTier: f"service_tier not honored: sent {SERVICE_TIER!r}, response reported " f"{response.service_tier!r} ({response})" ) + + +class _OutboundRetention(BaseModel, frozen=True): + prompt_cache_retention: str | None = None + + +@dataclass(frozen=True, slots=True) +class _OpenAIBodyCapture: + """The raw bodies sent to one OpenAI path, seen by a live edge in front of + api.openai.com. Pass ``observe`` as the edge's ``observe_request``.""" + + path: str + _bodies: queue.SimpleQueue[bytes] = field(default_factory=queue.SimpleQueue) + + def observe(self, url: str, headers: Mapping[str, str], body: bytes | None) -> None: + if body is not None and url.split("?")[0].endswith(self.path): + self._bodies.put(body) + + def retentions(self) -> tuple[str | None, ...]: + bodies: Final = tuple(self._bodies.get_nowait() for _ in range(self._bodies.qsize())) + return tuple(_OutboundRetention.model_validate_json(body).prompt_cache_retention for body in bodies) + + +def _openai_edge_api_base(resources: ResourceManager, capture: _OpenAIBodyCapture, *, reachable_from_proxy: bool) -> str: + """The proxy may run in a container, so its edge binds where the proxy can + reach it; an in-process SDK call reaches the edge on loopback.""" + edge: Final = ( + start_provider_edge( + LiveEdge(observe_request=capture.observe), + bind_host=PROVIDER_EDGE_BIND_HOST, + advertise_host=PROVIDER_EDGE_ADVERTISE_HOST, + ) + if reachable_from_proxy + else start_provider_edge(LiveEdge(observe_request=capture.observe)) + ) + resources.defer(edge.shutdown) + return f"{edge.edge.api_base('openai')}/v1" + + +def _retention_backends() -> tuple[object, ...]: + """gpt-5.5 straight to /v1/chat/completions, and the openai/responses/ bridge + (chat completions in, Responses out) to /v1/responses.""" + return ( + pytest.param( + OPENAI_BACKEND, + "/chat/completions", + marks=( + pytest.mark.covers("llm.chat_completions.openai.prompt_cache_24h.nonstream.forwards_retention"), + meta( + Subject( + domain=Domain.LLM_TRANSLATION, + route=Route.CHAT_COMPLETIONS, + providers=(Provider.OPENAI,), + models=(OPENAI_BACKEND,), + mode=Mode.NONSTREAM, + ) + ), + ), + id="chat_completions", + ), + pytest.param( + OPENAI_RESPONSES_BRIDGE_BACKEND, + "/responses", + marks=( + pytest.mark.covers("llm.chat_completions.openai.prompt_cache_24h.nonstream.bridge_forwards_retention"), + meta( + Subject( + domain=Domain.LLM_TRANSLATION, + route=Route.CHAT_COMPLETIONS, + providers=(Provider.OPENAI,), + models=(OPENAI_RESPONSES_BRIDGE_BACKEND,), + mode=Mode.NONSTREAM, + ) + ), + ), + id="responses_bridge", + ), + ) + + +class TestPromptCacheRetention: + @pytest.mark.provider_edge_host + @pytest.mark.parametrize(("backend", "openai_path"), _retention_backends()) + def test_proxy_chat_completions_forwards_prompt_cache_retention_to_openai( + self, proxy: ProxyClient, resources: ResourceManager, backend: str, openai_path: str + ) -> None: + capture: Final = _OpenAIBodyCapture(openai_path) + api_base: Final = _openai_edge_api_base(resources, capture, reachable_from_proxy=True) + model: Final = f"e2e-cache-retention-{unique_marker()}" + model_id: Final = proxy.create_model( + model, LiteLLMParamsBody(model=backend, api_key="os.environ/OPENAI_API_KEY", api_base=api_base) + ) + resources.defer(lambda: proxy.delete_model(model_id)) + + unwrap( + proxy.chat( + resources.key(), + ChatBody( + model=model, + messages=[ChatMessage(role="user", content="reply with one word")], + prompt_cache_retention=PROMPT_CACHE_RETENTION, + ), + ) + ) + + assert capture.retentions() == (PROMPT_CACHE_RETENTION,), ( + f"one {openai_path} call to OpenAI must carry prompt_cache_retention={PROMPT_CACHE_RETENTION!r}" + ) + + @pytest.mark.parametrize(("backend", "openai_path"), _retention_backends()) + def test_sdk_completion_forwards_prompt_cache_retention_to_openai( + self, resources: ResourceManager, backend: str, openai_path: str + ) -> None: + import litellm + + capture: Final = _OpenAIBodyCapture(openai_path) + api_base: Final = _openai_edge_api_base(resources, capture, reachable_from_proxy=False) + + litellm.completion( + model=backend, + messages=[{"role": "user", "content": "reply with one word"}], + api_base=api_base, + prompt_cache_retention=PROMPT_CACHE_RETENTION, + ) + + assert capture.retentions() == (PROMPT_CACHE_RETENTION,), ( + f"one {openai_path} call to OpenAI must carry prompt_cache_retention={PROMPT_CACHE_RETENTION!r}" + ) + + @pytest.mark.parametrize(("backend", "openai_path"), _retention_backends()) + def test_router_completion_forwards_prompt_cache_retention_to_openai( + self, resources: ResourceManager, backend: str, openai_path: str + ) -> None: + import litellm + + capture: Final = _OpenAIBodyCapture(openai_path) + api_base: Final = _openai_edge_api_base(resources, capture, reachable_from_proxy=False) + router: Final = litellm.Router( + model_list=[{"model_name": "cache-retention", "litellm_params": {"model": backend, "api_base": api_base}}] + ) + + router.completion( # pyright: ignore[reportUnknownMemberType] # Router.completion forwards an untyped **kwargs to litellm.completion + model="cache-retention", + messages=[{"role": "user", "content": "reply with one word"}], + prompt_cache_retention=PROMPT_CACHE_RETENTION, + ) + + assert capture.retentions() == (PROMPT_CACHE_RETENTION,), ( + f"one {openai_path} call to OpenAI must carry prompt_cache_retention={PROMPT_CACHE_RETENTION!r}" + ) diff --git a/tests/e2e/models.py b/tests/e2e/models.py index f0a8d67b444..afddc7e25d6 100644 --- a/tests/e2e/models.py +++ b/tests/e2e/models.py @@ -364,6 +364,7 @@ class ChatBody(BaseModel): thinking: ThinkingParam | None = None service_tier: str | None = None prompt_cache_key: str | None = None + prompt_cache_retention: str | None = None tools: Sequence[ChatTool | McpChatTool | GeminiUrlContextTool] | None = None tool_choice: str | None = None guardrails: list[str] | None = None diff --git a/tests/e2e/perf/UI_QUERIES.md b/tests/e2e/perf/UI_QUERIES.md index 552f1b953fd..d2cbcd368fc 100644 --- a/tests/e2e/perf/UI_QUERIES.md +++ b/tests/e2e/perf/UI_QUERIES.md @@ -1,92 +1,59 @@ -# SpendLog UI query performance +# Admin UI journey latency on the 1TB SpendLogs restore -Run `test_ui_queries.py` against a dedicated proxy and a disposable database restored from the metadata-only performance seed. These tests do not call an LLM or measure browser rendering +Run `test_ui_journeys.py` against a dedicated proxy, its Admin UI and a disposable database restored from the metadata-only performance seed. A headless Chromium logs into the dashboard and performs the journeys below, timing each one from the user's click or navigation until the data is on screen. No LLM is called. The test does not look at which routes, SQL or tables served the page, so it stays valid whether the backend gets faster queries or new aggregate tables -The suite measures 42 request shapes across 20 routes used by current dashboard screens. It replays direct HTTP requests against the existing bulk seed, with the seed anchor replacing the wall clock and a UTC browser timezone. It does not run a browser or claim to cover every dashboard request +## Journeys -## UI callers +| name | what the user does | timer stops when | +| --- | --- | --- | +| `logs_open_24h` | opens Logs (default Last 24 Hours) | request rows are rendered and the refresh control is idle | +| `logs_last_7_days` | switches the time range to Last 7 Days | same | +| `logs_next_page` | clicks the next page control | same | +| `logs_filter_key_hash` | filters by the seeded key hash and applies | same | +| `logs_filter_key_alias` | picks the first key alias in the filter drawer and applies | same | +| `logs_filter_team` | picks the first team in the filter drawer and applies | same | +| `logs_filter_model` | picks the first model in the filter drawer and applies | same | +| `usage_open` | opens Usage | summary tiles show dollar values with no skeletons left | +| `usage_last_30_days` | picks Last 30 days in the Usage date picker | same | +| `usage_team_view` | switches the Usage view to Team Usage | same | +| `usage_customer_view` | switches the Usage view to Customer Usage | same | +| `usage_model_activity_30_days` | on the Model Activity tab, picks Last 30 days | same | +| `cache_open` | opens Caching | the Cache Hits tile is visible and the Cache Hits vs API Requests chart has bars | +| `models_open` | opens Models + Endpoints | model rows are rendered and the loading state is gone | +| `keys_open` | opens Virtual Keys | key rows are rendered and the loading state is gone | -All paths below are relative to `ui/litellm-dashboard/src/`. Each case requires an authenticated admin session with access to that screen, and selected resources must exist in the fixture +The mix follows what customers report as slow: the Logs page on `LiteLLM_SpendLogs`, the Usage page on the `LiteLLM_Daily*Spend` rollups (30 day ranges, Customer and Model views), and the Models and Keys pages. -| Cases | UI action and source | -| --- | --- | -| `logs_*` | Logs > Request Logs, change date range, filter, sort or next page. `components/logs/request/useLogFilterLogic.ts` and `RequestLogsFilters.tsx` | -| `usage_*` | Usage overview or entity tab, open key activity, search keys, expand a model group. `app/(dashboard)/usage/_components/components/UsagePageView.tsx`, `EntityUsage/EntityUsage.tsx`, `EntityUsage/entityFetchFns.ts`, `components/UsagePage/components/KeyActivityPanel.tsx` | -| `team_users_*` | Team Usage. `EntityUsage/EntityUsage.tsx` passes selected teams or all available non-dashboard teams to `TeamUserSpendCard.tsx` | -| `cache_activity_*` | Caching > Cache Analytics, optionally filter aliases/models. `app/(dashboard)/hooks/caching/useCacheActivity.ts` | -| `cache_leakage_keys` | Cost Optimization, switch cache leakage to Keys. `app/(dashboard)/cost-optimization/_components/useCacheLeakageKeys.ts` | +## Seeded rows -Request serialization lives in `components/networking.tsx`. Logs use page size 25 and session grouping, including the next-session cursor returned by page one. Individual Logs filters use a 30-day window to exercise larger matching datasets. Their case names end in `_30d` so the measurements do not share history with the old 24-hour filters. The synthetic cursorless page-three request is excluded +The snapshot carries the SpendLogs rows and their Daily* rollups. `setup/ui_query_fixture.py` checks that `LiteLLM_DailyUserSpend` and `LiteLLM_DailyTeamSpend` have rows in the week before the anchor, then fills the tables the snapshot does not have so the Keys, Models and filter journeys see realistic counts: 100 teams (`perf-team-N`), 2,000 users (`perf-user-N`), 5,000 keys whose token hashes and `perf-key-N` aliases match the seeded log rows, and 200 DB models pointed at the perf mock provider. Every insert is `ON CONFLICT DO NOTHING`, so reruns on the same restore are no-ops. Nothing here runs outside the disposable restore -Usage list, search and model drilldown requests do not inject an `api_key` filter. Team activity excludes `litellm-dashboard`. Cache leakage supplies `include_current_utc_day=true`. Dates and filter values are deterministic fixture values, not captured production traffic +Each journey is measured once cold, then `E2E_UI_JOURNEY_REPEATS` more times (default 9) from the same starting state, inside one logged-in tab whose clock is pinned to the seed anchor so relative windows land on seeded rows. The browser timezone is UTC to match the seed -Old Usage is excluded because its expensive-query gate normally hides those calls at this database size. LiteAdmin's agent-selected reports are excluded from this deterministic dashboard set. Missing-token alias recovery is backend functional coverage, not a separate UI action, and its artificial requests and orphan fixtures are removed +## Safety -This mapping is source-verified, not browser-recorded. Recheck the named callers when changing cases. Neither browser capture nor an automatic UI-drift checker is installed by this suite +The seeded source is never the target. `E2E_UI_PERF_DISPOSABLE=1`, `E2E_RESET_SPEND_LOGS=0` and a hostname matching `db-perf-perf-.litellm.svc` are all required, and in-flight SQL is cancelled only on that disposable restore between journeys (see `setup/ui_query_isolation.py`) -## Dataset scope +## Running -Logs, team-user spend and cache activity query the bulk SpendLogs data. User, team, tag and customer usage, plus cache leakage, query daily tables aggregated from that dataset. These are sequential large-dataset queries, not concurrent traffic or saturation tests - -A read-only restore of `db-perf-v1-105-1tb` gave exact request totals from daily aggregates: 9,442,606 across 24 hours, 66,077,435 across seven days and 283,189,684 across 30 days. The retained 30-day key filter matches 1,134,559 requests, user filter 11,316,454, team filter 113,298,119 and model filter 94,395,473. These describe matching requests, not rows scanned or returned by the API, and are documentation rather than performance assertions - -PostgreSQL table-wide estimates (`pg_class.reltuples`) are approximately 2.70 million daily user rows, 2.70 million daily team rows, 5.40 million daily tag rows and 78.27 million daily end-user rows. These are not exact counts within each Usage case's seven-day window - -The individual end-user filter is excluded because it matched only 104 requests in 24 hours and 8,616 across all dates. User/end-user dropdown requests are also excluded because their queries cap the input at 10,000 matching SpendLogs before extracting distinct values. Neither is a broad matching-data workload in this seed - -Excluded because they only had tiny matching fixtures or individual-record lookups: organization/agent usage, guardrail/tool logs, request-ID lookup, payload/session drawers, session/search filters for `perf-ui-*`, the OAuth-token filter, and all prompt-caching request cases. The seed has response-cache hits but no prompt-cache usage or injection metadata, so the prompt-caching cases only matched the 320 added rows. No UI-specific rows are inserted anymore - -| Remaining cases | Count | Variations | -| --- | ---: | --- | -| Logs | 21 | 24h/7d/30d, page 2 with session cursor, 12 individual filters over 30 days, five additional descending sorts | -| User/team/tag/customer usage | 16 | Aggregated totals, keys, key search, model top keys for each | -| Team-user spend | 2 | All 100 seeded teams or `perf-team-0` | -| Cache activity | 2 | All or selected aliases/model | -| Cache leakage keys | 1 | 30-day window | - -## Deployment prerequisites - -Use a fresh proxy against the disposable restore, never the active seed source or a shared test database. Apply the target migrations and wait for readiness first. The source seed's `litellm_perf_seed.checkpoint` must exist and contain rows - -Configure `litellm_settings.service_callback: [prometheus_system]` and expose metrics for every proxy worker/pod. Set `E2E_DATABASE_METRICS_URLS` to their comma-separated URLs, not a load-balanced endpoint that can miss a pod. Absent failure counters count as zero only when the endpoint exposes a positive PostgreSQL request counter. Missing instrumentation stops the run - -No expensive-query override or legacy view creation is needed for these cases. Keep the normal large-database UI restrictions - -The cases use explicit dates from the seed anchor where the UI supplies dates. A missing nonempty fixture result records a contract failure rather than reporting a fast empty query as success - -## Run - -Set `DATABASE_URL` and `LITELLM_MASTER_KEY` securely for this disposable deployment. The URL must name the same database used by the proxy, with hostname `db-perf-perf-.litellm.svc`. The explicit disposable confirmation permits cancellation of leftover queries in this database. Setup reads the existing seed checkpoint without adding UI-specific rows. Destroy the disposable database after the run +The componentized perf stack serves the dashboard behind the same router as the proxy, so `LITELLM_PROXY_URL` covers `/ui`. Set `E2E_UI_BASE_URL` only if the UI lives elsewhere. The admin login uses `E2E_UI_USERNAME` (default `admin`) and `E2E_UI_PASSWORD` (default the master key) ```bash -export LITELLM_PROXY_URL=http://localhost:4000 -export E2E_DATABASE_METRICS_URLS=http://localhost:4000/metrics -export E2E_PERF_TESTS=1 -export E2E_UI_PERF_DISPOSABLE=1 -export E2E_RESET_SPEND_LOGS=0 -export E2E_ARTIFACT_DIR="$PWD/ui-query-results" -mkdir -p "$E2E_ARTIFACT_DIR" -uv run pytest tests/e2e/perf/test_ui_queries.py --reruns 0 --junitxml="$E2E_ARTIFACT_DIR/junit.xml" -q +export E2E_PERF_TESTS=1 E2E_UI_PERF_DISPOSABLE=1 E2E_RESET_SPEND_LOGS=0 +export DATABASE_URL=postgresql://...@db-perf-perf-.litellm.svc:5432/litellm +export E2E_DATABASE_METRICS_URLS=http://:4000/metrics +export E2E_ARTIFACT_DIR=/tmp/e2e-artifacts +uv run pytest tests/e2e/perf/test_ui_journeys.py --reruns 0 --junitxml="$E2E_ARTIFACT_DIR/junit.xml" -q ``` -Do not enable SpendLog retention or run other traffic on this stack. The `quiet_stack` marker coordinates local pytest callers but cannot stop external traffic. Use one pytest worker for comparable timings +`E2E_UI_JOURNEY_TIMEOUT_SECONDS` (default 120) bounds one journey. A journey that never settles is recorded as a `timeout` sample and a journey whose page rendered empty or threw in the browser as a `ui` sample. The test fails when any sample failed, or when the p50 or p90 across all samples is over the journey's `Ceiling` in `UI_JOURNEY_LIMITS` (`setup/ui_journeys.py`, 10s/20s for Logs journeys, 20s/40s for Usage and Caching, 5s/10s for the Models and Keys tables, generous until the first 1TB run sets real numbers). The artifacts are written before the assertion so a failed run still ships its samples -`E2E_UI_QUERY_REPEATS` defaults to 9, giving ten measured requests including the first, and `E2E_UI_QUERY_TIMEOUT_SECONDS` defaults to 120. Every request is issued once without transport retries. A failed first request stops that case's repeated samples. Cursor prerequisites are recorded separately, and failed prerequisites stop that case's measurements +## Artifacts -## Reading results +Each JUnit testcase `test_ui_journey_latency[]` carries `perf_ui_journeys`, `perf_ui_failures`, `perf_ui_seconds_p50`, `perf_ui_seconds_p90`, `perf_ui_seconds_max`, `perf_ui_first_seconds`, `perf_ui_repeated_seconds_p50`, `perf_ui_repeated_seconds_max` and `perf_ui_database_failures`. `ui-journey-.json` holds every sample with its on-screen row count and `ui-isolation-.jsonl` the SQL isolation evidence -Each case writes `ui-query-.json` with its exact method, path, parameters and body, response status counts, elapsed times, row counts, errors and before/after PostgreSQL failure counters. Response bodies and authentication headers are not saved +The Buildkite `ui_queries` lane restores the pinned snapshot, waits for migrations and indexes, runs these journeys with no retries and uploads the JUnit and JSON artifacts. Validate selectors on a small restore first, then take numbers from the completed 1TB snapshot -The dashboard's `perf_ui_seconds_p50`, `_p90` and `_max` include all successful measured requests, including the first. `perf_ui_samples` is their sample count. p50 is the median and p90 uses nearest rank, the ninth sorted value with ten successes. Failures and cursor prerequisites contribute no latency. Pass percentage is `(perf_ui_requests - perf_ui_failures) / perf_ui_requests * 100`, including cursor prerequisites in the request counts +To measure a released version on the same snapshot, create the litellm-perf build with `perf_gateway_version=` (for example `v1.106.1`) next to `litellm_sha`. The gateway, backend and the restore's schema upgrade then come from `ghcr.io/berriai/litellm-{gateway,backend,migrations}:`, where the migrations image runs `prisma migrate deploy` and builds the request-log indexes the way a customer upgrade does, while the runner and these journeys come from `litellm_sha`. The fixture skips its upgrade-worker wait when `_LiteLLMPerfUpgrade` is absent. The snapshot's schema is v1.105.1 and the restore only migrates forward, so older tags cannot be measured -The first-request and repeated-request metrics are retained for existing consumers. This is not a cold-cache claim: previous cases and previous runs can warm database buffers or application caches. Restart the disposable proxy between independent runs when comparing independent runs - -Repeated p50 is reported for successful samples, p95 only with at least 20 and p99 only with at least 100. First-request latency is omitted when that request fails. HTTP, JSON, response-shape, nonempty-result, cursor failures are recorded, never asserted. Endpoint failures, database counter increases and latency do not fail CI - -Each JUnit testcase `test_ui_query_performance[]` carries `perf_ui_requests`, `perf_ui_failures`, `perf_ui_repeated_samples`, and nonzero `perf_ui_error_` counts. Codes distinguish `http_400`, `http_500`, `http_503`, other HTTP statuses, `timeout`, `network`, `invalid_json` and `contract`. Successful latency properties are `perf_ui_first_seconds` and `perf_ui_repeated_seconds_p50`, `_p95`, `_p99`, `_max`. A failed cursor prerequisite is counted once and contributes no latency - -Before every case the runner requires three idle database observations and stable failure counters. After each case it cancels leftover SQL, terminates idle transactions and waits for idle and stable counters again. `ui-isolation-.jsonl` retains active SQL, waits, elapsed times, raw samples and counter observations. `perf_ui_database_failures` measures the increase before cleanup, while `perf_ui_cleanup_database_failures` measures the increase observed afterward, including cancellations and potentially delayed request failures. Isolation, instrumentation or setup failures still stop the run rather than publish contaminated measurements. Disk and process caches are not reset between cases - -The Buildkite `ui_queries` lane restores the pinned snapshot independently, waits for migrations and indexes to complete, runs these cases with no retries, uploads JUnit and JSON artifacts, and removes the temporary resources. It follows the nightly regular perf and database-upgrade builds using the same LiteLLM SHA. Shinkiro ingestion is a separate change - -Validate a small restore first. Small-database numbers validate the runner only, not full-size performance. Run the same cases against the completed full-size snapshot before publishing large-database results +Each sample in `ui-journey-.json` also records the `status` and `request` (method and path) of the data request the page issued, the first non-2xx one when there is one, so a failed sample names what the gateway answered. A failed sample with a 4xx or 5xx status is counted as `perf_ui_error_http_` instead of `perf_ui_error_ui`. Each journey is also bounded by a wall clock of `E2E_UI_JOURNEY_TIMEOUT_SECONDS x (repeats + 2)`, so one hung browser call ends the journey with a `wall_clock` sample instead of eating the lane. diff --git a/tests/e2e/perf/cases/mixed_size_requests_2rps.py b/tests/e2e/perf/cases/mixed_size_requests_2rps.py index 850658a15c5..3acd8671acd 100644 --- a/tests/e2e/perf/cases/mixed_size_requests_2rps.py +++ b/tests/e2e/perf/cases/mixed_size_requests_2rps.py @@ -62,24 +62,24 @@ CASE: Final = PerformanceTestCase( ), limits=( Limit("unexpected_status_count", max=3), - Limit("gateway_added_seconds", percentile=50, max=0.58), - Limit("gateway_added_seconds", percentile=99, max=6.1), - Limit("litellm_overhead_seconds", percentile=50, max=0.05), - Limit("litellm_overhead_seconds", percentile=99, max=2.2), - Limit("litellm_response_seconds", percentile=50, max=1.2), - Limit("litellm_response_seconds", percentile=99, max=3.8), - Limit("prometheus_redis_latency_mean_seconds", max=0.003), - Limit("postgres_active_sessions", max=0.004), - Limit("postgres_slowest_statement_seconds", max=0.045), - Limit("postgres_peak_connections", max=30), - Limit("time_to_first_token_seconds", percentile=50, max=2.7), - Limit("time_to_first_token_seconds", percentile=99, max=8.8), + Limit("gateway_added_seconds", percentile=50, max=0.29), + Limit("gateway_added_seconds", percentile=99, max=2.7), + Limit("litellm_overhead_seconds", percentile=50, max=0.052), + Limit("litellm_overhead_seconds", percentile=99, max=1.8), + Limit("litellm_response_seconds", percentile=50, max=0.93), + Limit("litellm_response_seconds", percentile=99, max=2.7), + Limit("prometheus_redis_latency_mean_seconds", max=0.002), + Limit("postgres_active_sessions", max=0.0094), + Limit("postgres_slowest_statement_seconds", max=0.042), + Limit("postgres_peak_connections", max=23), + Limit("time_to_first_token_seconds", percentile=50, max=1.56), + Limit("time_to_first_token_seconds", percentile=99, max=4.5), Limit("memory_growth_megabytes", max=600), - Limit("cpu_seconds_per_request", max=1.26), - Limit("postgres_calls_per_request", max=3.5), - Limit("postgres_max_statement_per_request", max=0.5), - Limit("postgres_max_background_statement_per_request", max=0.9), - Limit("redis_calls_per_request", max=21.0), + Limit("cpu_seconds_per_request", max=0.57), + Limit("postgres_calls_per_request", max=2.64), + Limit("postgres_max_statement_per_request", max=0.43), + Limit("postgres_max_background_statement_per_request", max=0.86), + Limit("redis_calls_per_request", max=15.4), ), background_cap_exempt_tables=frozenset({"LiteLLM_DailyGuardrailMetrics"}), ) diff --git a/tests/e2e/perf/cases/small_bodies_5rps.py b/tests/e2e/perf/cases/small_bodies_5rps.py index bc22a9a96c8..f4013b79eac 100644 --- a/tests/e2e/perf/cases/small_bodies_5rps.py +++ b/tests/e2e/perf/cases/small_bodies_5rps.py @@ -64,21 +64,21 @@ CASE: Final = PerformanceTestCase( ), limits=( Limit("unexpected_status_count", max=3), - Limit("gateway_added_seconds", percentile=50, max=0.29), - Limit("litellm_overhead_seconds", percentile=50, max=0.02), - Limit("litellm_overhead_seconds", percentile=99, max=0.8), - Limit("litellm_response_seconds", percentile=50, max=0.8), - Limit("litellm_response_seconds", percentile=99, max=2.8), - Limit("prometheus_redis_latency_mean_seconds", max=0.006), - Limit("postgres_active_sessions", max=0.006), - Limit("postgres_slowest_statement_seconds", max=0.035), - Limit("postgres_peak_connections", max=30), - Limit("time_to_first_token_seconds", percentile=99, max=3.7), + Limit("gateway_added_seconds", percentile=50, max=0.165), + Limit("litellm_overhead_seconds", percentile=50, max=0.006), + Limit("litellm_overhead_seconds", percentile=99, max=0.35), + Limit("litellm_response_seconds", percentile=50, max=0.91), + Limit("litellm_response_seconds", percentile=99, max=1.6), + Limit("prometheus_redis_latency_mean_seconds", max=0.0026), + Limit("postgres_active_sessions", max=0.0052), + Limit("postgres_slowest_statement_seconds", max=0.011), + Limit("postgres_peak_connections", max=23), + Limit("time_to_first_token_seconds", percentile=99, max=2.05), Limit("memory_growth_megabytes", max=100), - Limit("postgres_calls_per_request", max=1.8), - Limit("postgres_max_statement_per_request", max=0.5), + Limit("postgres_calls_per_request", max=1.31), + Limit("postgres_max_statement_per_request", max=0.27), Limit("postgres_max_background_statement_per_request", max=0.9), - Limit("redis_calls_per_request", max=18), - Limit("cpu_seconds_per_request", max=0.29), + Limit("redis_calls_per_request", max=13.8), + Limit("cpu_seconds_per_request", max=0.15), ), ) diff --git a/tests/e2e/perf/setup/observe.py b/tests/e2e/perf/setup/observe.py index 6d207fb0543..ccdae6398a9 100644 --- a/tests/e2e/perf/setup/observe.py +++ b/tests/e2e/perf/setup/observe.py @@ -4,25 +4,26 @@ calls, the workers' memory) into the case's metrics, and the case's limits into from __future__ import annotations import hashlib +import json import statistics -from collections import Counter +from collections import Counter, defaultdict from collections.abc import Iterable -from dataclasses import dataclass +from dataclasses import asdict, dataclass from itertools import chain -from typing import Final +from typing import Final, Literal from e2e_http import NoBody, get_external, post_external, unwrap from memory_readings import RssCapture, RssReading, WorkerKey from pydantic import BaseModel from setup.datastore import ( - active_sessions, - slowest_statement, DbCounters, RedisCommand, RedisCounters, StatementCalls, + active_sessions, calls_in, + slowest_statement, statement_deltas, ) from setup.mocks.reply_common import Provider @@ -184,33 +185,42 @@ class Observation: """Requests the plan expected to succeed that came back with any other status (0 is a client timeout).""" return sum(1 for record in self.records if not record.blocked and record.status != 200) - def gateway_added_seconds(self) -> list[float]: - """Seconds the gateway added to each first-attempt request: total time minus the mock's own delay for a - non-streamed request, time to the first token minus the mock's delay to its first byte for a stream.""" - non_stream: Final = [record.total_s - delay for record, delay in self._clean(stream=False)] - stream: Final = [ - record.first_token_s - delay - for record, delay in self._clean(stream=True) - if record.first_token_s is not None - ] - return non_stream + stream + def latency_pairs(self, metric: LatencyMetric) -> list[tuple[WireRecord, float]]: + """Each first-attempt request with its value of one latency metric. `gateway_added_seconds` is the + seconds the gateway added (total time minus the mock's own delay for a non-streamed request, time to the + first token minus the mock's delay for a stream), `time_to_first_token_seconds` is the client's wait for + the first token with the mock delay included, and the two `litellm_*` metrics are the gateway's own + `x-litellm-overhead-duration-ms` and `x-litellm-response-duration-ms` headers in seconds.""" + if metric == "gateway_added_seconds": + non_stream: Final = [(record, record.total_s - delay) for record, delay in self._clean(stream=False)] + stream: Final = [ + (record, record.first_token_s - delay) + for record, delay in self._clean(stream=True) + if record.first_token_s is not None + ] + return non_stream + stream + if metric == "time_to_first_token_seconds": + return [(r, r.first_token_s) for r, _ in self._clean(stream=True) if r.first_token_s is not None] + if metric == "litellm_overhead_seconds": + return [ + (r, r.litellm_overhead_ms / 1000) for r in self._first_attempts() if r.litellm_overhead_ms is not None + ] + return [(r, r.litellm_response_ms / 1000) for r in self._first_attempts() if r.litellm_response_ms is not None] def _first_attempts(self) -> list[WireRecord]: return [record for record, _ in self._clean(stream=False)] + [record for record, _ in self._clean(stream=True)] + def gateway_added_seconds(self) -> list[float]: + return [value for _, value in self.latency_pairs("gateway_added_seconds")] + def litellm_overhead_seconds(self) -> list[float]: - """`x-litellm-overhead-duration-ms` per first-attempt request, the gateway's own account of what it added - (receive time to response end, minus the provider call), in seconds to sit next to `gateway_added_seconds`.""" - return [r.litellm_overhead_ms / 1000 for r in self._first_attempts() if r.litellm_overhead_ms is not None] + return [value for _, value in self.latency_pairs("litellm_overhead_seconds")] def litellm_response_seconds(self) -> list[float]: - """`x-litellm-response-duration-ms` per first-attempt request, the gateway's own end-to-end time.""" - return [r.litellm_response_ms / 1000 for r in self._first_attempts() if r.litellm_response_ms is not None] + return [value for _, value in self.latency_pairs("litellm_response_seconds")] def time_to_first_token_seconds(self) -> list[float]: - """Seconds from the client sending each first-attempt streamed request to its first token, mock delay - included, comparable across versions because the mocks generate the same replies after the same wait.""" - return [record.first_token_s for record, _ in self._clean(stream=True) if record.first_token_s is not None] + return [value for _, value in self.latency_pairs("time_to_first_token_seconds")] def bodies_off_reply(self) -> int: """Served requests whose text is not the reply the mock generated for them (plus the post-call rewrite @@ -235,6 +245,131 @@ def _text_sha1(text: str, *, intervened: bool) -> str: return hashlib.sha1(original.encode()).hexdigest() +LatencyMetric = Literal[ + "gateway_added_seconds", "time_to_first_token_seconds", "litellm_overhead_seconds", "litellm_response_seconds" +] +TOP_CONTRIBUTORS: Final = 5 + + +@dataclass(frozen=True, slots=True) +class Contributor: + """One slice of a metric: a statement, a Redis command, an endpoint, a worker or a status, with its own + value in the metric's unit and, where the metric is a total, its share of that total.""" + + label: str + value: float + share: float | None = None + + +def _top(items: Iterable[Contributor]) -> tuple[Contributor, ...]: + return tuple(sorted(items, key=lambda item: item.value, reverse=True)[:TOP_CONTRIBUTORS]) + + +def _endpoint_label(record: WireRecord) -> str: + return f"{record.endpoint}{' stream' if record.stream else ''}" + + +def _latency_breakdown(metric: LatencyMetric, rank: int, observation: Observation) -> tuple[Contributor, ...]: + pairs: Final = observation.latency_pairs(metric) + by_endpoint: dict[str, list[float]] = defaultdict(list) + for record, value in pairs: + by_endpoint[_endpoint_label(record)].append(value) + return _top( + Contributor(label, percentile(values, rank) or 0.0, len(values) / len(pairs)) + for label, values in by_endpoint.items() + ) + + +def _statements_for( + metric: Metric, statements: tuple[StatementCalls, ...], exempt_tables: frozenset[str] +) -> tuple[StatementCalls, ...]: + if metric in ("postgres_calls_per_request", "postgres_max_statement_per_request"): + return tuple(item for item in statements if item.bucket == "awaited") + if metric == "postgres_background_calls_per_request": + return tuple(item for item in statements if item.bucket == "background") + if metric == "postgres_max_background_statement_per_request": + return tuple(item for item in statements if item.bucket == "background" and item.table not in exempt_tables) + return tuple(item for item in statements if item.calls > 0) + + +def _statement_breakdown( + metric: Metric, observation: Observation, exempt_tables: frozenset[str] +) -> tuple[Contributor, ...]: + chosen: Final = _statements_for(metric, observation.statements or (), exempt_tables) + requests: Final = max(1, len(observation.records)) + total_calls: Final = sum(item.calls for item in chosen) + total_ms: Final = sum(item.total_exec_ms for item in chosen) + if metric == "postgres_slowest_statement_seconds": + return _top( + Contributor( + item.summary, item.mean_exec_seconds or 0.0, item.total_exec_ms / total_ms if total_ms else None + ) + for item in chosen + ) + if metric == "postgres_active_sessions": + return _top( + Contributor( + item.summary, item.total_exec_ms / 1000 / observation.wall_seconds, item.total_exec_ms / total_ms + ) + for item in chosen + if total_ms + ) + return _top( + Contributor(item.summary, item.calls / requests, item.calls / total_calls) for item in chosen if total_calls + ) + + +def _redis_breakdown(metric: Metric, observation: Observation) -> tuple[Contributor, ...]: + bucket: Final = "awaited" if metric == "redis_calls_per_request" else "background" + chosen: Final = tuple(item for item in observation.redis_commands or () if item.bucket == bucket) + requests: Final = max(1, len(observation.records)) + total: Final = sum(item.count for item in chosen) + return _top( + Contributor(f"{item.command} {item.key}".strip(), item.count / requests, item.count / total) + for item in chosen + if total + ) + + +def _memory_breakdown(observation: Observation) -> tuple[Contributor, ...]: + before: Final = {reading.worker: reading.ram_usage_mb for reading in observation.rss_before.readings} + return _top( + Contributor(f"{reading.replica} pid {reading.worker_pid}", reading.ram_usage_mb - before[reading.worker]) + for reading in observation.rss_after.readings + if reading.worker in before + ) + + +def _status_breakdown(observation: Observation) -> tuple[Contributor, ...]: + unexpected: Final = [r for r in observation.records if not r.blocked and r.status != 200] + counts: Final = Counter(f"{_endpoint_label(record)} status {record.status}" for record in unexpected) + return _top(Contributor(label, float(count), count / len(unexpected)) for label, count in counts.items()) + + +def breakdown( + metric: Metric, percentile_rank: int | None, observation: Observation, exempt_tables: frozenset[str] = frozenset() +) -> tuple[Contributor, ...]: + """The top contributors to one metric, so a spike on the chart names its statement, command, endpoint or + worker. Gauges with no slices (`cpu_seconds_per_request`, `prometheus_redis_latency_mean_seconds`, + `postgres_peak_connections`) have none.""" + if metric in ( + "gateway_added_seconds", + "time_to_first_token_seconds", + "litellm_overhead_seconds", + "litellm_response_seconds", + ): + return _latency_breakdown(metric, 50 if percentile_rank is None else percentile_rank, observation) + if metric.startswith("postgres_") and metric != "postgres_peak_connections": + return _statement_breakdown(metric, observation, exempt_tables) + if metric in {"redis_calls_per_request", "redis_background_calls_per_request"}: + return _redis_breakdown(metric, observation) + if metric == "memory_growth_megabytes": + return _memory_breakdown(observation) + if metric == "unexpected_status_count": + return _status_breakdown(observation) + return () + + def observe( metric: Metric, percentile_rank: int | None, observation: Observation, exempt_tables: frozenset[str] = frozenset() ) -> float | None: @@ -290,6 +425,7 @@ class Row: observed: float | None limit: float | None detail: str = "" + breakdown: tuple[Contributor, ...] = () @property def label(self) -> str: @@ -351,6 +487,7 @@ def evaluate(case: PerformanceTestCase, observation: Observation) -> tuple[list[ observed=observe(metric, rank, observation, case.background_cap_exempt_tables), limit=limit.max if limit else None, detail=_detail(metric, observation, case.background_cap_exempt_tables), + breakdown=breakdown(metric, rank, observation, case.background_cap_exempt_tables), ) ) exceeded: Final = [ @@ -376,13 +513,20 @@ def _detail(metric: Metric, observation: Observation, exempt_tables: frozenset[s return "" -def _row_properties(row: Row) -> tuple[tuple[str, float], ...]: +def _row_properties(row: Row) -> tuple[tuple[str, float | str], ...]: observed: Final = ((row.property_name, row.observed),) if row.observed is not None else () limit: Final = ((f"{row.property_name}_limit", row.limit),) if row.limit is not None else () - return observed + limit + contributors: Final = ( + ((f"{row.property_name}_breakdown", json.dumps([asdict(item) for item in row.breakdown])),) + if row.breakdown + else () + ) + return observed + limit + contributors -def junit_properties(rows: Iterable[Row]) -> tuple[tuple[str, float], ...]: +def junit_properties(rows: Iterable[Row]) -> tuple[tuple[str, float | str], ...]: + """One numeric property per observed metric and per limit, plus a `_breakdown` JSON list of the top + contributors for every metric that has slices, all under the `perf_` prefix the dashboard ingests.""" return tuple(chain.from_iterable(map(_row_properties, rows))) diff --git a/tests/e2e/perf/setup/ui_journeys.py b/tests/e2e/perf/setup/ui_journeys.py new file mode 100644 index 00000000000..4de97d8c717 --- /dev/null +++ b/tests/e2e/perf/setup/ui_journeys.py @@ -0,0 +1,430 @@ +from __future__ import annotations + +import math +import re +import statistics +import time +from collections.abc import Callable, Generator +from contextlib import contextmanager +from dataclasses import dataclass +from datetime import datetime +from itertools import chain +from types import MappingProxyType +from typing import Final +from urllib.parse import urlsplit + +from playwright.sync_api import Error as PlaywrightError +from playwright.sync_api import Locator, Page, Response, expect, sync_playwright +from playwright.sync_api import TimeoutError as PlaywrightTimeoutError +from prometheus_client.parser import text_string_to_metric_families +from pydantic import BaseModel, ConfigDict + +MONEY: Final = re.compile(r"^\$[\d,]+\.\d{2}$") +LOADING_LOGS: Final = "Loading request logs…" +LOADING_MODELS: Final = "Loading models…" +LOADING_KEYS: Final = "Loading keys..." + + +class Sample(BaseModel): + model_config = ConfigDict(frozen=True) + + seconds: float + rows: int = 0 + error: str = "" + status: int = 0 + request: str = "" + + +class Timings(BaseModel): + model_config = ConfigDict(frozen=True) + + first_seconds: float | None + repeated_samples: int + repeated_p50_seconds: float | None + repeated_p95_seconds: float | None + repeated_p99_seconds: float | None + repeated_max_seconds: float | None + + +@dataclass(frozen=True, slots=True) +class Journey: + """One dashboard interaction. ``start`` brings the page to the state the user acts from (untimed), + ``act`` is the click or navigation being measured and ``settled`` blocks until the data the user + was waiting for is on screen, returning the number of rows or tiles that rendered.""" + + name: str + surface: str + start: Callable[[Page, float], None] + act: Callable[[Page], None] + settled: Callable[[Page, float], int] + + +@dataclass(frozen=True, slots=True) +class Dashboard: + base_url: str + username: str + password: str + anchor: datetime + + +def summarize(samples: tuple[Sample, ...]) -> Timings: + assert samples, "No UI journeys were measured" + repeated: Final = tuple(sorted(sample.seconds for sample in samples[1:] if not sample.error)) + return Timings( + first_seconds=samples[0].seconds if not samples[0].error else None, + repeated_samples=len(repeated), + repeated_p50_seconds=statistics.median(repeated) if repeated else None, + repeated_p95_seconds=repeated[math.ceil(len(repeated) * 0.95) - 1] if len(repeated) >= 20 else None, + repeated_p99_seconds=repeated[math.ceil(len(repeated) * 0.99) - 1] if len(repeated) >= 100 else None, + repeated_max_seconds=max(repeated) if repeated else None, + ) + + +def error_code(sample: Sample) -> str: + if not sample.error: + return "" + if sample.status >= 400: + return f"http_{sample.status}" + if sample.error.startswith("wall_clock"): + return "wall_clock" + return "timeout" if sample.error == "timeout" else "ui" + + +def ui_junit_properties(samples: tuple[Sample, ...]) -> tuple[tuple[str, float], ...]: + codes: Final = tuple(error_code(sample) for sample in samples if sample.error) + timings: Final = summarize(samples) + successful: Final = tuple(sorted(sample.seconds for sample in samples if not sample.error)) + latency: Final = ( + ("seconds_p50", statistics.median(successful) if successful else None), + ("seconds_p90", successful[math.ceil(len(successful) * 0.90) - 1] if successful else None), + ("seconds_max", max(successful) if successful else None), + ("first_seconds", timings.first_seconds), + ("repeated_seconds_p50", timings.repeated_p50_seconds), + ("repeated_seconds_p95", timings.repeated_p95_seconds), + ("repeated_seconds_p99", timings.repeated_p99_seconds), + ("repeated_seconds_max", timings.repeated_max_seconds), + ) + return ( + ("perf_ui_journeys", len(samples)), + ("perf_ui_failures", len(codes)), + ("perf_ui_samples", len(successful)), + ("perf_ui_repeated_samples", timings.repeated_samples), + *((f"perf_ui_error_{code}", codes.count(code)) for code in sorted(frozenset(codes))), + *((f"perf_ui_{name}", value) for name, value in latency if value is not None), + ) + + +@dataclass(frozen=True, slots=True) +class Ceiling: + p50_seconds: float + p90_seconds: float + + +LOGS_CEILING: Final = Ceiling(p50_seconds=10, p90_seconds=20) +CHART_CEILING: Final = Ceiling(p50_seconds=20, p90_seconds=40) +TABLE_CEILING: Final = Ceiling(p50_seconds=5, p90_seconds=10) +UI_JOURNEY_LIMITS: Final = MappingProxyType( + { + "logs_open_24h": LOGS_CEILING, + "logs_last_7_days": LOGS_CEILING, + "logs_next_page": LOGS_CEILING, + "logs_filter_key_hash": LOGS_CEILING, + "logs_filter_key_alias": LOGS_CEILING, + "logs_filter_team": LOGS_CEILING, + "logs_filter_model": LOGS_CEILING, + "usage_open": CHART_CEILING, + "usage_last_30_days": CHART_CEILING, + "usage_team_view": CHART_CEILING, + "usage_customer_view": CHART_CEILING, + "usage_model_activity_30_days": CHART_CEILING, + "cache_open": CHART_CEILING, + "models_open": TABLE_CEILING, + "keys_open": TABLE_CEILING, + } +) + + +def assert_within_ceiling(journey_name: str, samples: tuple[Sample, ...]) -> None: + failed: Final = tuple(sample.error for sample in samples if sample.error) + assert not failed, f"{len(failed)} of {len(samples)} {journey_name} samples failed: {failed[0]}" + metrics: Final = dict(ui_junit_properties(samples)) + ceiling: Final = UI_JOURNEY_LIMITS[journey_name] + assert metrics["perf_ui_seconds_p50"] <= ceiling.p50_seconds, ( + f"{journey_name} p50 {metrics['perf_ui_seconds_p50']:.1f}s over {ceiling.p50_seconds}s" + ) + assert metrics["perf_ui_seconds_p90"] <= ceiling.p90_seconds, ( + f"{journey_name} p90 {metrics['perf_ui_seconds_p90']:.1f}s over {ceiling.p90_seconds}s" + ) + + +@contextmanager +def dashboard_page(dashboard: Dashboard, timeout: float) -> Generator[Page]: + """A logged-in admin tab whose clock reads the seed anchor, so relative windows such as + Last 24 Hours land on seeded rows. Live Tail is off so its 15 second refetch cannot land + inside a sample. Playwright keeps a UTC timezone to match the seed.""" + with sync_playwright() as playwright: + browser: Final = playwright.chromium.launch() + context: Final = browser.new_context( + base_url=dashboard.base_url, timezone_id="UTC", viewport={"width": 1600, "height": 1000} + ) + context.set_default_timeout(timeout * 1000) + context.add_init_script('sessionStorage.setItem("isLiveTail", "false")') + page: Final = context.new_page() + page.clock.set_fixed_time(dashboard.anchor) + _login(page, dashboard) + try: + yield page + finally: + context.close() + browser.close() + + +def _login(page: Page, dashboard: Dashboard) -> None: + _ = page.goto("/ui/login") + page.get_by_placeholder("Enter your username").fill(dashboard.username) + page.get_by_placeholder("Enter your password").fill(dashboard.password) + page.get_by_role("button", name="Login", exact=True).click() + page.wait_for_url(lambda url: "/ui" in url and "/login" not in url) + expect(page.get_by_label("LiteLLM home")).to_be_visible() + + +def _is_data_fetch(response: Response) -> bool: + """API calls only. The Admin UI's own assets and Next.js prefetches live under /ui/ and /_next/.""" + path: Final = urlsplit(response.url).path + return response.request.resource_type in ("fetch", "xhr") and not path.startswith(("/ui/", "/_next/")) + + +def _worst(responses: list[Response]) -> Response | None: + return next((response for response in responses if response.status >= 400), responses[-1] if responses else None) + + +def _with_response(sample: Sample, responses: list[Response]) -> Sample: + worst: Final = _worst(responses) + if worst is None: + return sample + return sample.model_copy( + update={"status": worst.status, "request": f"{worst.request.method} {urlsplit(worst.url).path}"[:120]} + ) + + +def measure(page: Page, journey: Journey, timeout: float) -> Sample: + """Wall time from the user's action to the data being on screen. Every sample starts from the + same pre-action state so repeats measure the same journey, not a warmed client cache.""" + try: + journey.start(page, timeout) + except (PlaywrightError, AssertionError) as error: + return Sample(seconds=0.0, error=f"start {type(error).__name__}: {error}"[:300]) + responses: Final[list[Response]] = [] # mutable-ok: filled by the playwright response listener + + def record(response: Response) -> None: + if _is_data_fetch(response): + responses.append(response) + + page.on("response", record) + started: Final = time.monotonic() + try: + with page.expect_response(_is_data_fetch, timeout=timeout * 1000): + journey.act(page) + rows: Final = journey.settled(page, timeout) + except PlaywrightTimeoutError: + return _with_response(Sample(seconds=time.monotonic() - started, error="timeout"), responses) + except (PlaywrightError, AssertionError) as error: + return _with_response( + Sample(seconds=time.monotonic() - started, error=f"{type(error).__name__}: {error}"[:300]), responses + ) + finally: + page.remove_listener("response", record) + return _with_response(Sample(seconds=time.monotonic() - started, rows=rows), responses) + + +def _visible(page: Page, test_id: str) -> Locator: + return page.get_by_test_id(test_id).filter(visible=True).first + + +def _logs_rows(page: Page) -> Locator: + return page.locator("table").filter(visible=True).first.locator("tbody tr") + + +def _logs_settled(page: Page, timeout: float) -> int: + millis: Final = timeout * 1000 + rows: Final = _logs_rows(page).filter(has_not_text="No results") + expect(rows.first).to_be_visible(timeout=millis) + expect(_visible(page, "datatable-refresh")).to_be_enabled(timeout=millis) + expect(page.get_by_text(LOADING_LOGS)).to_have_count(0, timeout=millis) + return rows.count() + + +def _no_skeletons(page: Page, timeout: float) -> None: + expect(page.locator('[data-slot="skeleton"]')).to_have_count(0, timeout=timeout * 1000) + + +def _usage_settled(page: Page, timeout: float) -> int: + millis: Final = timeout * 1000 + expect(page.get_by_text("Total Spend", exact=True).first).to_be_visible(timeout=millis) + _no_skeletons(page, timeout) + money: Final = page.get_by_text(MONEY) + expect(money.first).to_be_visible(timeout=millis) + return money.count() + + +def _cache_settled(page: Page, timeout: float) -> int: + millis: Final = timeout * 1000 + expect(page.get_by_text("Cache Hits", exact=True)).to_be_visible(timeout=millis) + bars: Final = page.locator(".recharts-bar-rectangle") + expect(bars.first).to_be_visible(timeout=millis) + return bars.count() + + +def _table_settled(loading: str) -> Callable[[Page, float], int]: + def settled(page: Page, timeout: float) -> int: + millis: Final = timeout * 1000 + rows: Final = page.locator("[data-row-id]") + expect(rows.first).to_be_visible(timeout=millis) + expect(page.get_by_text(loading)).to_have_count(0, timeout=millis) + return rows.count() + + return settled + + +def _open_logs(page: Page, timeout: float) -> None: + _ = page.goto("/ui/logs") + _ = _logs_settled(page, timeout) + + +def _open_usage(page: Page, timeout: float) -> None: + _ = page.goto("/ui/usage") + _ = _usage_settled(page, timeout) + + +def _filters_drawer(page: Page) -> Locator: + _visible(page, "datatable-filters-trigger").click() + drawer: Final = page.get_by_role("dialog", name="Filters") + expect(drawer).to_be_visible() + return drawer + + +def _apply_filters(page: Page) -> None: + page.get_by_role("dialog", name="Filters").get_by_role("button", name="Apply Filters").click() + + +def _pick_first_option(page: Page, combobox: str) -> None: + _filters_drawer(page).get_by_role("combobox", name=combobox).click() + page.get_by_role("option").first.click() + + +def _open_time_range(page: Page, timeout: float) -> None: + _open_logs(page, timeout) + page.get_by_role("button", name="Last 24 Hours").click() + + +def _open_usage_range(page: Page, timeout: float) -> None: + _open_usage(page, timeout) + page.locator('[data-slot="advanced-date-picker-trigger"]').click() + + +def _model_activity_settled(page: Page, timeout: float) -> int: + millis: Final = timeout * 1000 + expect(page.locator('[role="tab"][data-active]', has_text="Model Activity")).to_be_visible(timeout=millis) + _no_skeletons(page, timeout) + money: Final = page.get_by_text(MONEY).filter(visible=True) + expect(money.first).to_be_visible(timeout=millis) + return money.count() + + +def _open_model_activity_range(page: Page, timeout: float) -> None: + _open_usage(page, timeout) + page.get_by_role("tab", name="Model Activity").click() + _ = _model_activity_settled(page, timeout) + page.locator('[data-slot="advanced-date-picker-trigger"]').click() + + +def _pick_usage_preset(preset: str) -> Callable[[Page], None]: + def act(page: Page) -> None: + page.locator('[data-slot="advanced-date-picker-preset"]', has_text=preset).click() + + return act + + +def _select_usage_view(page: Page, view: str) -> None: + page.locator('[data-slot="select-trigger"]').filter(has_text="Usage").first.click() + page.get_by_role("option", name=re.compile(rf"^{re.escape(view)}")).click() + + +def _nothing(page: Page, timeout: float) -> None: + return None + + +def _goto(path: str) -> Callable[[Page], None]: + def act(page: Page) -> None: + _ = page.goto(path) + + return act + + +def _logs_filter(name: str, prepare: Callable[[Page], None]) -> Journey: + def start(page: Page, timeout: float) -> None: + _open_logs(page, timeout) + prepare(page) + + return Journey(name, "logs", start, _apply_filters, _logs_settled) + + +def journeys(api_key: str) -> tuple[Journey, ...]: + return ( + Journey("logs_open_24h", "logs", _nothing, _goto("/ui/logs"), _logs_settled), + Journey( + "logs_last_7_days", + "logs", + _open_time_range, + lambda page: page.get_by_role("button", name="Last 7 Days", exact=True).click(), + _logs_settled, + ), + Journey( + "logs_next_page", "logs", _open_logs, lambda page: _visible(page, "pagination-next").click(), _logs_settled + ), + _logs_filter( + "logs_filter_key_hash", + lambda page: _filters_drawer(page).get_by_placeholder("Enter key hash…").fill(api_key), + ), + _logs_filter("logs_filter_key_alias", lambda page: _pick_first_option(page, "Search a key alias")), + _logs_filter("logs_filter_team", lambda page: _pick_first_option(page, "Search or select a team")), + _logs_filter("logs_filter_model", lambda page: _pick_first_option(page, "Search a model")), + Journey("usage_open", "usage", _nothing, _goto("/ui/usage"), _usage_settled), + Journey("usage_last_30_days", "usage", _open_usage_range, _pick_usage_preset("Last 30 days"), _usage_settled), + Journey( + "usage_team_view", "usage", _open_usage, lambda page: _select_usage_view(page, "Team Usage"), _usage_settled + ), + Journey( + "usage_customer_view", + "usage", + _open_usage, + lambda page: _select_usage_view(page, "Customer Usage"), + _usage_settled, + ), + Journey( + "usage_model_activity_30_days", + "usage", + _open_model_activity_range, + _pick_usage_preset("Last 30 days"), + _model_activity_settled, + ), + Journey("cache_open", "caching", _nothing, _goto("/ui/caching"), _cache_settled), + Journey("models_open", "models", _nothing, _goto("/ui/models-and-endpoints"), _table_settled(LOADING_MODELS)), + Journey("keys_open", "keys", _nothing, _goto("/ui/api-keys"), _table_settled(LOADING_KEYS)), + ) + + +def database_failures(text: str) -> float: + families: Final = tuple(text_string_to_metric_families(text)) + required: Final = frozenset(("litellm_postgres_failed_requests", "litellm_batch_write_to_db_failed_requests")) + missing: Final = required - frozenset(family.name for family in families) + all_samples: Final = tuple(chain.from_iterable(family.samples for family in families)) + has_activity: Final = any( + sample.name == "litellm_postgres_total_requests_total" and math.isfinite(sample.value) and sample.value > 0 + for sample in all_samples + ) + assert not missing or has_activity, f"Missing PostgreSQL failure counters {missing}" + names: Final = frozenset(f"{name}_total" for name in required) + values: Final = tuple(sample.value for sample in all_samples if sample.name in names) + assert all(math.isfinite(value) and value >= 0 for value in values), "Invalid PostgreSQL failure counter" + return sum(values) diff --git a/tests/e2e/perf/setup/ui_queries.py b/tests/e2e/perf/setup/ui_queries.py deleted file mode 100644 index b6945d79896..00000000000 --- a/tests/e2e/perf/setup/ui_queries.py +++ /dev/null @@ -1,227 +0,0 @@ -from __future__ import annotations - -import math -import statistics -import time -from collections.abc import Callable -from dataclasses import dataclass -from itertools import chain -from typing import Final, Literal -from urllib.parse import urlencode - -from e2e_http import ( - NetworkError, - RateLimitedError, - Result, - Success, - UnauthorizedError, - UnknownApiError, - ValidationError, - without_retries, -) -from e2e_metadata import step -from prometheus_client.parser import text_string_to_metric_families -from pydantic import BaseModel, ConfigDict, JsonValue, RootModel -from transport import HttpTransport - - -class Query(BaseModel): - model_config = ConfigDict(frozen=True) - - -class Document(RootModel[JsonValue]): - model_config = ConfigDict(frozen=True) - - -@dataclass(frozen=True, slots=True) -class Contract: - collection: tuple[str, ...] = () - row_fields: tuple[str, ...] = () - positive: tuple[str, ...] = () - object_fields: tuple[str, ...] = () - excluded_ids: frozenset[str] = frozenset() - - def count(self, document: Document) -> int: - value: Final = descend(document.root, self.collection) - if self.object_fields: - assert isinstance(value, dict), "Expected a JSON object" - assert set(self.object_fields) <= value.keys(), f"Missing fields {self.object_fields}" - return 1 - assert isinstance(value, list) and value, f"Empty/missing collection {self.collection}, check the fixture" - for row in value: - if self.excluded_ids: - assert isinstance(row, dict) and isinstance(row_id := row.get("request_id"), str), "Missing request_id" - assert row_id not in self.excluded_ids, "Repeated page-one row" - if self.row_fields or self.positive: - assert isinstance(row, dict), "Expected object rows" - assert set(self.row_fields) <= row.keys(), f"Missing row fields {self.row_fields}" - for name in self.positive: - assert any(tuple(_positive(row, name) for row in value)), f"Expected positive {name}" - return len(value) - - -def _positive(row: JsonValue, name: str) -> bool: - assert isinstance(row, dict), "Expected object row" - number: Final = row.get(name) - assert isinstance(number, (int, float)) and not isinstance(number, bool), f"Expected numeric {name}" - assert math.isfinite(number), f"Expected finite {name}" - return number > 0 - - -def descend(value: JsonValue, path: tuple[str, ...]) -> JsonValue: - if not path: - return value - assert isinstance(value, dict) and path[0] in value, f"Missing response path {path}" - return descend(value[path[0]], path[1:]) - - -@dataclass(frozen=True, slots=True) -class UiQueryCase: - name: str - path: str - params: BaseModel - contract: Contract - surface: Literal["current"] = "current" - body: BaseModel | None = None - cursor: Literal["none", "session"] = "none" - - -class Sample(BaseModel): - model_config = ConfigDict(frozen=True) - - seconds: float - status: int - rows: int = 0 - error: str = "" - - -class Timings(BaseModel): - model_config = ConfigDict(frozen=True) - - first_seconds: float | None - repeated_samples: int - repeated_p50_seconds: float | None - repeated_p95_seconds: float | None - repeated_p99_seconds: float | None - repeated_max_seconds: float | None - - -def summarize(samples: tuple[Sample, ...]) -> Timings: - assert samples, "No UI requests were measured" - repeated: Final = tuple(sorted(sample.seconds for sample in samples[1:] if not sample.error)) - return Timings( - first_seconds=samples[0].seconds if not samples[0].error else None, - repeated_samples=len(repeated), - repeated_p50_seconds=statistics.median(repeated) if repeated else None, - repeated_p95_seconds=repeated[math.ceil(len(repeated) * 0.95) - 1] if len(repeated) >= 20 else None, - repeated_p99_seconds=repeated[math.ceil(len(repeated) * 0.99) - 1] if len(repeated) >= 100 else None, - repeated_max_seconds=max(repeated) if repeated else None, - ) - - -def error_code(sample: Sample) -> str: - if not sample.error: - return "" - if sample.status > 0 and sample.status != 200: - return f"http_{sample.status}" - if sample.error in ("timeout", "network"): - return sample.error - if sample.error == "Response is not valid JSON": - return "invalid_json" - return "contract" - - -def ui_junit_properties( - samples: tuple[Sample, ...], prerequisite: Sample | None = None -) -> tuple[tuple[str, float], ...]: - requests: Final = (prerequisite, *samples) if prerequisite is not None and not prerequisite.error else samples - codes: Final = tuple(error_code(sample) for sample in requests if sample.error) - timings: Final = summarize(samples) - successful: Final = tuple(sorted(sample.seconds for sample in samples if not sample.error)) - latency: Final = ( - ("seconds_p50", statistics.median(successful) if successful else None), - ("seconds_p90", successful[math.ceil(len(successful) * 0.90) - 1] if successful else None), - ("seconds_max", max(successful) if successful else None), - ("first_seconds", timings.first_seconds), - ("repeated_seconds_p50", timings.repeated_p50_seconds), - ("repeated_seconds_p95", timings.repeated_p95_seconds), - ("repeated_seconds_p99", timings.repeated_p99_seconds), - ("repeated_seconds_max", timings.repeated_max_seconds), - ) - return ( - ("perf_ui_requests", len(requests)), - ("perf_ui_failures", len(codes)), - ("perf_ui_samples", len(successful)), - ("perf_ui_repeated_samples", timings.repeated_samples), - *((f"perf_ui_error_{code}", codes.count(code)) for code in sorted(frozenset(codes))), - *((f"perf_ui_{name}", value) for name, value in latency if value is not None), - ) - - -def _failure(result: Result[Document], seconds: float) -> Sample: - match result: - case Success(status_code=status): - return Sample(seconds=seconds, status=status, error=f"Unexpected HTTP {status}") - case UnknownApiError(status_code=status): - return Sample(seconds=seconds, status=status, error=f"HTTP {status}") - case UnauthorizedError(): - return Sample(seconds=seconds, status=401, error="Unauthorized") - case RateLimitedError(): - return Sample(seconds=seconds, status=429, error="Rate limited") - case NetworkError(message=message): - return Sample(seconds=seconds, status=-1, error="timeout" if "timed out" in message.lower() else "network") - case ValidationError(): - return Sample(seconds=seconds, status=-1, error="Response is not valid JSON") - - -def measure( - issue: Callable[[], Result[Document]], - contract: Contract, - *, - clock: Callable[[], float] = time.monotonic, -) -> tuple[Sample, Document | None]: - started: Final = clock() - with without_retries(): - result: Final = issue() - seconds: Final = clock() - started - match result: - case Success(status_code=200, data=document): - try: - count: Final = contract.count(document) - except AssertionError as error: - return Sample(seconds=seconds, status=200, error=str(error)), document - return Sample(seconds=seconds, status=200, rows=count), document - case _: - return _failure(result, seconds), None - - -def query_path(case: UiQueryCase) -> str: - query: Final = urlencode(case.params.model_dump(by_alias=True, exclude_none=True), doseq=True) - return f"{case.path}?{query}" if query else case.path - - -@step("Measure UI query {case.name} at {case.path}") -def issue_query(transport: HttpTransport, case: UiQueryCase, *, timeout: float) -> Result[Document]: - if case.body is not None: - return transport.post( - case.path, headers=transport.master, json=case.body, response_type=Document, timeout=timeout - ) - return transport.get( - query_path(case), headers=transport.master, params=Query(), response_type=Document, timeout=timeout - ) - - -def database_failures(text: str) -> float: - families: Final = tuple(text_string_to_metric_families(text)) - required: Final = frozenset(("litellm_postgres_failed_requests", "litellm_batch_write_to_db_failed_requests")) - missing: Final = required - frozenset(family.name for family in families) - all_samples: Final = tuple(chain.from_iterable(family.samples for family in families)) - has_activity: Final = any( - sample.name == "litellm_postgres_total_requests_total" and math.isfinite(sample.value) and sample.value > 0 - for sample in all_samples - ) - assert not missing or has_activity, f"Missing PostgreSQL failure counters {missing}" - names: Final = frozenset(f"{name}_total" for name in required) - values: Final = tuple(sample.value for sample in all_samples if sample.name in names) - assert all(math.isfinite(value) and value >= 0 for value in values), "Invalid PostgreSQL failure counter" - return sum(values) diff --git a/tests/e2e/perf/setup/ui_query_cases.py b/tests/e2e/perf/setup/ui_query_cases.py deleted file mode 100644 index e9b70aad713..00000000000 --- a/tests/e2e/perf/setup/ui_query_cases.py +++ /dev/null @@ -1,206 +0,0 @@ -from __future__ import annotations - -from dataclasses import replace -from datetime import datetime, timedelta -from itertools import chain -from typing import Final, Literal - -from pydantic import ConfigDict - -from setup.ui_queries import Contract, Document, Query, UiQueryCase, descend - - -class Params(Query): - model_config = ConfigDict(frozen=True, extra="forbid", populate_by_name=True) - - start_date: str | None = None - timezone: str | None = None - offset: int | None = None - model_group: str | None = None - by_model_group: str | None = None - end_date: str | None = None - page: int | None = None - page_size: int | None = None - sort_by: str | None = None - sort_order: str | None = None - group_by_session: Literal["true"] | None = None - session_cursor: str | None = None - api_key: str | None = None - team_id: str | None = None - team_ids: str | None = None - user_id: str | None = None - model: str | None = None - model_id: str | None = None - key_alias: str | None = None - search: str | None = None - status_filter: str | None = None - cache_hit_filter: str | None = None - error_code: str | None = None - error_message: str | None = None - span_type: str | None = None - exclude_internal_health_checks: Literal["true"] | None = None - key_aliases: tuple[str, ...] | None = None - models: tuple[str, ...] | None = None - limit: int | None = None - tags: str | None = None - exclude_team_ids: str | None = None - include_current_utc_day: Literal["true"] | None = None - - -def _timestamp(value: datetime) -> str: - return value.strftime("%Y-%m-%d %H:%M:%S") - - -def next_page(case: UiQueryCase, document: Document) -> UiQueryCase: - params: Final = Params.model_validate(case.params.model_dump()) - rows: Final = descend(document.root, case.contract.collection) - assert isinstance(rows, list), "Missing page-one rows" - ids: Final = frozenset(str(row["request_id"]) for row in rows if isinstance(row, dict)) - contract: Final = replace(case.contract, excluded_ids=ids) - cursor: Final = descend(document.root, ("next_session_cursor",)) - assert isinstance(cursor, str) and cursor, "Missing session cursor" - return replace(case, params=params.model_copy(update={"page": 2, "session_cursor": cursor}), contract=contract) - - -_LOGS: Final = Contract(("data",), ("request_id", "startTime", "metadata")) - - -def log_cases(anchor: datetime, api_key: str) -> tuple[UiQueryCase, ...]: - params: Final = Params( - start_date=_timestamp(anchor - timedelta(days=1)), - end_date=_timestamp(anchor), - page=1, - page_size=25, - sort_by="startTime", - sort_order="desc", - group_by_session="true", - ) - base: Final = UiQueryCase("logs_default_24h", "/spend/logs/ui", params, _LOGS) - filtered: Final = params.model_copy(update={"start_date": _timestamp(anchor - timedelta(days=30))}) - filters: Final = ( - ("api_key", api_key), - ("team_id", "perf-team-0"), - ("user_id", "perf-user-0"), - ("model", "perf-chat"), - ("model_id", "perf-model-0"), - ("key_alias", "perf-key-0"), - ("status_filter", "failure"), - ("cache_hit_filter", "hit"), - ("error_code", "429"), - ("error_message", "Synthetic"), - ("span_type", "llm"), - ("exclude_internal_health_checks", "true"), - ) - return ( - base, - replace(base, name="logs_cursor_page_2", params=params.model_copy(update={"page": 2}), cursor="session"), - replace( - base, - name="logs_7d", - params=params.model_copy(update={"start_date": _timestamp(anchor - timedelta(days=7))}), - ), - replace( - base, - name="logs_30d", - params=params.model_copy(update={"start_date": _timestamp(anchor - timedelta(days=30))}), - ), - *( - replace(base, name=f"logs_{name}_30d", params=filtered.model_copy(update={name: value})) - for name, value in filters - ), - *( - replace(base, name=f"logs_sort_{name}", params=params.model_copy(update={"sort_by": name})) - for name in ("spend", "total_tokens", "request_duration_ms", "model", "ttft_ms") - ), - ) - - -def analytics_cases(anchor: datetime) -> tuple[UiQueryCase, ...]: - dates: Final = Params( - start_date=(anchor - timedelta(days=7)).date().isoformat(), end_date=anchor.date().isoformat() - ) - cache: Final = UiQueryCase( - "cache_activity_7d", "/global/activity/cache_hits", dates, Contract(("groups",), ("call_type",)) - ) - return ( - UiQueryCase( - "team_users_all_teams", - "/team/spend/by_user", - dates.model_copy(update={"team_ids": ",".join(f"perf-team-{i}" for i in range(100))}), - Contract(("results",), ("team_id", "user_id", "spend"), ("api_requests",)), - ), - UiQueryCase( - "team_users_filtered", - "/team/spend/by_user", - dates.model_copy(update={"team_ids": "perf-team-0"}), - Contract(("results",), ("team_id", "user_id", "spend"), ("api_requests",)), - ), - cache, - replace( - cache, - name="cache_activity_filtered", - params=dates.model_copy(update={"key_aliases": ("perf-key-0", "perf-key-1"), "models": ("perf-chat",)}), - ), - ) - - -def _entity_activity_cases(anchor: datetime, entity: str) -> tuple[UiQueryCase, ...]: - dates: Final = Params( - start_date=(anchor - timedelta(days=7)).date().isoformat(), - end_date=anchor.date().isoformat(), - timezone="0", - exclude_team_ids="litellm-dashboard" if entity == "team" else None, - ) - routes: Final = ( - ("aggregated", dates, Contract(("results",), ("date", "breakdown"))), - ( - "aggregated/keys", - dates.model_copy(update={"offset": 0, "limit": 50}), - Contract(("api_keys",), ("api_key", "metrics", "metadata")), - ), - ( - "aggregated/search", - dates.model_copy(update={"search": "perf-key"}), - Contract(("api_keys",), ("api_key", "metrics", "metadata")), - ), - ( - "aggregated/model_top_keys", - dates.model_copy(update={"model_group": "perf-chat", "by_model_group": "true"}), - Contract(("api_keys",), ("api_key", "metrics", "metadata")), - ), - ) - return tuple( - UiQueryCase( - f"usage_{entity}_{route.replace('/', '_')}", - f"/{entity}/daily/activity/{route}", - params, - contract, - ) - for route, params, contract in routes - ) - - -def activity_cases(anchor: datetime) -> tuple[UiQueryCase, ...]: - groups: Final = tuple(_entity_activity_cases(anchor, entity) for entity in ("user", "team", "tag", "customer")) - return ( - *chain.from_iterable(groups), - UiQueryCase( - "cache_leakage_keys", - "/user/daily/activity/aggregated/cache_leakage_keys", - Params( - start_date=(anchor - timedelta(days=30)).date().isoformat(), - end_date=anchor.date().isoformat(), - timezone="0", - include_current_utc_day="true", - ), - Contract(("api_keys",), ("api_key", "metrics", "metadata")), - ), - ) - - -def cases(anchor: datetime, api_key: str) -> tuple[UiQueryCase, ...]: - return ( - *log_cases(anchor, api_key), - *analytics_cases(anchor), - *activity_cases(anchor), - ) diff --git a/tests/e2e/perf/setup/ui_query_fixture.py b/tests/e2e/perf/setup/ui_query_fixture.py index e3f5236ba47..ed941a096bd 100644 --- a/tests/e2e/perf/setup/ui_query_fixture.py +++ b/tests/e2e/perf/setup/ui_query_fixture.py @@ -3,7 +3,9 @@ from __future__ import annotations import hashlib import os import time -from datetime import datetime +from collections.abc import Iterable +from datetime import datetime, timedelta +from itertools import chain from typing import Final import psycopg @@ -18,6 +20,96 @@ class UiFixture(BaseModel): anchor: AwareDatetime api_key: str + """`perf_ui_db_*` JUnit properties naming how much data the journeys ran against.""" + volume: tuple[tuple[str, int], ...] = () + + +class TableVolume(BaseModel): + model_config = ConfigDict(frozen=True) + + table: str + rows: int + bytes: int + + +QUERIED_TABLES: Final = ( + "LiteLLM_SpendLogs", + "LiteLLM_DailyUserSpend", + "LiteLLM_DailyTeamSpend", + "LiteLLM_DailyTagSpend", + "LiteLLM_VerificationToken", + "LiteLLM_TeamTable", + "LiteLLM_UserTable", + "LiteLLM_ProxyModelTable", +) +_VOLUME_SQL: Final = """ + SELECT c.relname, GREATEST(c.reltuples, 0)::bigint, pg_total_relation_size(c.oid) + FROM pg_class c JOIN pg_namespace n ON n.oid = c.relnamespace + WHERE n.nspname = 'public' AND c.relname = ANY(%(tables)s) +""" + + +SEEDED_TEAMS: Final = 100 +SEEDED_USERS: Final = 2000 +SEEDED_KEYS: Final = 5000 +SEEDED_MODELS: Final = 200 +DAILY_TABLES: Final = ("LiteLLM_DailyUserSpend", "LiteLLM_DailyTeamSpend") +_SEED_SQL: Final = ( + """ + INSERT INTO "LiteLLM_TeamTable" (team_id, team_alias, members_with_roles, metadata, model_spend, model_max_budget) + SELECT 'perf-team-' || n, 'perf-team-' || n, '[]', '{}', '{}', '{}' FROM generate_series(0, %(teams)s - 1) AS n + ON CONFLICT (team_id) DO NOTHING + """, + """ + INSERT INTO "LiteLLM_UserTable" (user_id, user_alias, user_email, user_role, team_id, metadata, model_spend, model_max_budget) + SELECT 'perf-user-' || n, 'perf-user-' || n, 'perf-user-' || n || '@example.com', 'internal_user', + 'perf-team-' || (n %% %(teams)s), '{}', '{}', '{}' + FROM generate_series(0, %(users)s - 1) AS n + ON CONFLICT (user_id) DO NOTHING + """, + """ + INSERT INTO "LiteLLM_VerificationToken" (token, key_name, key_alias, team_id, user_id, aliases, config, permissions, + metadata, model_spend, model_max_budget, created_at, updated_at) + SELECT md5('perf-key:' || n) || md5('perf-key-tail:' || n), 'sk-...perf' || n, 'perf-key-' || n, + 'perf-team-' || (n %% %(teams)s), 'perf-user-' || (n %% %(users)s), '{}', '{}', '{}', '{}', '{}', '{}', + %(anchor)s - make_interval(days => n %% 365), %(anchor)s + FROM generate_series(0, %(keys)s - 1) AS n + ON CONFLICT (token) DO NOTHING + """, + """ + INSERT INTO "LiteLLM_ProxyModelTable" (model_id, model_name, litellm_params, model_info, created_by, updated_by) + SELECT 'perf-model-' || n, 'perf-chat-' || (n %% 20), + jsonb_build_object('model', 'openai/perf-chat', 'api_key', 'perf-seed', + 'api_base', 'os.environ/E2E_PERF_MOCK_OPENAI_URL'), + jsonb_build_object('id', 'perf-model-' || n, 'db_model', true), 'perf-seed', 'perf-seed' + FROM generate_series(0, %(models)s - 1) AS n + ON CONFLICT (model_id) DO NOTHING + """, +) + + +def volume_properties(volumes: Iterable[TableVolume]) -> tuple[tuple[str, int], ...]: + """One `perf_ui_db_rows_` and one `perf_ui_db_bytes_
` property per table the journeys read, + so the dashboard can say what the latencies were measured against.""" + return tuple( + chain.from_iterable( + ((f"perf_ui_db_rows_{v.table}", v.rows), (f"perf_ui_db_bytes_{v.table}", v.bytes)) for v in volumes + ) + ) + + +def table_volumes(connection: psycopg.Connection, spend_log_rows: int) -> tuple[TableVolume, ...]: + """Planner row estimates and on-disk size (indexes included) of the queried tables. The restore's + `LiteLLM_SpendLogs` count comes from the seed checkpoint, exact where the estimate can be stale.""" + adapter: Final = TypeAdapter(tuple[str, int, int]) + found: Final = tuple( + adapter.validate_python(row) + for row in connection.execute(_VOLUME_SQL, {"tables": list(QUERIED_TABLES)}).fetchall() + ) + return tuple( + TableVolume(table=table, rows=spend_log_rows if table == "LiteLLM_SpendLogs" else rows, bytes=size) + for table, rows, size in sorted(found) + ) def prepare_fixture() -> UiFixture: @@ -27,18 +119,59 @@ def prepare_fixture() -> UiFixture: _ = connection.execute("SET statement_timeout='30s'") row: Final = connection.execute("SELECT spec->>'anchor', rows FROM litellm_perf_seed.checkpoint").fetchone() assert row is not None and TypeAdapter(int).validate_python(row[1]) > 0, "Missing completed seed rows" + seed_ui_tables(connection, anchor=TypeAdapter(datetime).validate_python(row[0])) fixture: Final = UiFixture( anchor=TypeAdapter(datetime).validate_python(row[0]), api_key=hashlib.md5(b"perf-key:0", usedforsecurity=False).hexdigest() + hashlib.md5(b"perf-key-tail:0", usedforsecurity=False).hexdigest(), + volume=volume_properties(table_volumes(connection, TypeAdapter(int).validate_python(row[1]))), ) return fixture +def seed_ui_tables(connection: psycopg.Connection, anchor: datetime) -> None: + """Give the Keys, Teams, Users and Models pages realistic row counts on the disposable restore. + + Names follow the SpendLogs seed (perf-key-N aliases, perf-team-N, perf-user-N) so the Logs filters and + Team Usage line up with real spend. The Daily* rollups come from the snapshot itself and are only checked. + """ + window: Final = { + "since": (anchor - timedelta(days=7)).strftime("%Y-%m-%d"), + "until": anchor.strftime("%Y-%m-%d"), + } + for table in DAILY_TABLES: + row = connection.execute(f'SELECT count(*) FROM "{table}" WHERE date BETWEEN %(since)s AND %(until)s', window) + assert _count(row.fetchone()) > 0, f"{table} has no rows in the week before the anchor" + params: Final = { + "teams": SEEDED_TEAMS, + "users": SEEDED_USERS, + "keys": SEEDED_KEYS, + "models": SEEDED_MODELS, + "anchor": anchor, + } + for statement in _SEED_SQL: + _ = connection.execute(statement, params) + connection.commit() + + +def _count(row: tuple[object, ...] | None) -> int: + assert row is not None + return TypeAdapter(int).validate_python(row[0]) + + +def _released_schema(connection: psycopg.Connection) -> bool: + """A released tag's migrations image upgrades the restore (schema and request-log indexes) before the + stack starts, so there is no upgrade worker state to wait on.""" + row: Final = connection.execute("""SELECT to_regclass('public."_LiteLLMPerfUpgrade"') IS NULL""").fetchone() + return row is None or TypeAdapter(bool).validate_python(row[0]) + + def _finish_upgrade() -> None: if os.environ.get("E2E_DATABASE_UPGRADE") != "1": return with psycopg.connect(os.environ["DATABASE_URL"], autocommit=True, connect_timeout=10) as connection: + if _released_schema(connection): + return release_indexes(connection) deadline: Final = time.monotonic() + 6 * 3600 while time.monotonic() < deadline: diff --git a/tests/e2e/perf/setup/ui_query_isolation.py b/tests/e2e/perf/setup/ui_query_isolation.py index d7f6d725edc..d892c268fa2 100644 --- a/tests/e2e/perf/setup/ui_query_isolation.py +++ b/tests/e2e/perf/setup/ui_query_isolation.py @@ -62,7 +62,9 @@ def wait_idle(connection: psycopg.Connection[dict[str, object]], evidence: Path, for query in queries: if cancel and query.leader_pid is None: _ = connection.execute( - "SELECT pg_cancel_backend(%s)" if query.state == "active" else "SELECT pg_terminate_backend(%s)", + "SELECT pg_cancel_backend(%s)" + if query.state == "active" + else "SELECT pg_terminate_backend(%s)", (query.pid,), ) else: diff --git a/tests/e2e/perf/test_ui_journeys.py b/tests/e2e/perf/test_ui_journeys.py new file mode 100644 index 00000000000..63eefedec68 --- /dev/null +++ b/tests/e2e/perf/test_ui_journeys.py @@ -0,0 +1,137 @@ +from __future__ import annotations + +import json +import os +import signal +import time +from collections.abc import Generator +from datetime import UTC, datetime +from pathlib import Path +from types import FrameType +from typing import Final + +import pytest +from e2e_config import MASTER_KEY, UI_BASE_URL, UI_PASSWORD, UI_USERNAME +from e2e_http import send_text_external, without_retries +from playwright.sync_api import Page +from setup.ui_journeys import ( + Dashboard, + Journey, + Sample, + assert_within_ceiling, + dashboard_page, + database_failures, + error_code, + journeys, + measure, + summarize, + ui_junit_properties, +) +from setup.ui_query_fixture import UiFixture, prepare_fixture +from setup.ui_query_isolation import isolated_database, settled_counter +from transport import HttpTransport + +pytestmark = [ + pytest.mark.perf, + pytest.mark.quiet_stack, + pytest.mark.skipif(os.environ.get("E2E_UI_PERF_DISPOSABLE") != "1", reason="Dedicated disposable database only"), +] + + +def pytest_generate_tests(metafunc: pytest.Metafunc) -> None: + if "journey_name" in metafunc.fixturenames: + metafunc.parametrize("journey_name", [journey.name for journey in journeys("")]) + + +@pytest.fixture(scope="module") +def ui_fixture() -> UiFixture: + return prepare_fixture() + + +def _metrics(transport: HttpTransport) -> float: + urls: Final = tuple(url.strip() for url in os.environ["E2E_DATABASE_METRICS_URLS"].split(",") if url.strip()) + try: + assert urls, "Provide a metrics URL for every proxy worker/pod" + readings: Final = tuple(send_text_external("GET", url, headers=transport.master, timeout=10) for url in urls) + assert all(reading.status_code == 200 for reading in readings), "Cannot read database failure metrics" + return sum(database_failures(reading.body) for reading in readings) + except Exception as error: + pytest.exit(f"Database metrics unavailable ({type(error).__name__}). Stopping UI measurements", returncode=2) + + +def _samples(dashboard: Dashboard, journey: Journey, timeout: float, repeats: int) -> tuple[Sample, ...]: + with dashboard_page(dashboard, timeout) as page: + return tuple(_within_budget(page, journey, timeout, repeats)) + + +def _within_budget(page: Page, journey: Journey, timeout: float, repeats: int) -> Generator[Sample]: + """One hanging browser call must not eat the lane: SIGALRM ends the journey at timeout x (repeats + 2), + the budget every sample needs (start plus act plus settle) with one spare sample of slack.""" + budget: Final = timeout * (repeats + 2) + + def expire(signum: int, frame: FrameType | None) -> None: + raise TimeoutError(f"{journey.name} exceeded its {budget:.0f}s wall clock") + + previous: Final = signal.signal(signal.SIGALRM, expire) + started: Final = time.monotonic() + try: + _ = signal.setitimer(signal.ITIMER_REAL, budget) + for _ in range(repeats + 1): + yield measure(page, journey, timeout) + except Exception as error: + if time.monotonic() - started < budget: + raise + yield Sample(seconds=time.monotonic() - started, error=f"wall_clock {type(error).__name__}: {error}"[:300]) + finally: + _ = signal.setitimer(signal.ITIMER_REAL, 0) + _ = signal.signal(signal.SIGALRM, previous) + + +def test_ui_journey_latency(journey_name: str, ui_fixture: UiFixture, request: pytest.FixtureRequest) -> None: + journey: Final = next(journey for journey in journeys(ui_fixture.api_key) if journey.name == journey_name) + transport: Final = HttpTransport(base_url=UI_BASE_URL, master_key=MASTER_KEY) + timeout: Final = float(os.environ.get("E2E_UI_JOURNEY_TIMEOUT_SECONDS", "120")) + repeats: Final = int(os.environ.get("E2E_UI_JOURNEY_REPEATS", "9")) + assert 0 < timeout <= 600 and 1 <= repeats <= 1000, "Invalid UI performance sample settings" + target: Final = Path(os.environ["E2E_ARTIFACT_DIR"]) + assert target.is_dir(), "E2E_ARTIFACT_DIR must exist" + evidence: Final = target / f"ui-isolation-{journey.name}.jsonl" + dashboard: Final = Dashboard( + base_url=UI_BASE_URL, username=UI_USERNAME, password=UI_PASSWORD, anchor=ui_fixture.anchor + ) + with without_retries(): + with isolated_database(journey.name): + before: Final = settled_counter(lambda: _metrics(transport), evidence) + samples: Final = _samples(dashboard, journey, timeout, repeats) + with evidence.open("a", encoding="utf-8") as sample_output: + _ = sample_output.write( + json.dumps({"samples": tuple(sample.model_dump() for sample in samples)}) + "\n" + ) + after_requests: Final = _metrics(transport) + item: Final = request.node # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # pytest: untyped + assert isinstance(item, pytest.Item) + item.user_properties.extend(ui_junit_properties(samples)) + item.user_properties.extend(ui_fixture.volume) + after: Final = settled_counter(lambda: _metrics(transport), evidence) + item.user_properties.extend( + ( + ("perf_ui_database_failures", after_requests - before), + ("perf_ui_cleanup_database_failures", after - after_requests), + ) + ) + artifact: Final = { + "name": journey.name, + "surface": journey.surface, + "measured_at": datetime.now(UTC).isoformat(), + "samples": [sample.model_dump() for sample in samples], + "error_codes": [error_code(sample) for sample in samples], + "timings": summarize(samples).model_dump(), + "timeouts": sum(sample.error == "timeout" for sample in samples), + "failures": sum(bool(sample.error) for sample in samples), + "database_failures_before": before, + "database_failures_after_requests": after_requests, + "database_failures_after_cleanup": after, + } + output: Final = target / f"ui-journey-{journey.name}.json" + _ = output.write_text(json.dumps(artifact, indent=2), encoding="utf-8") + assert_within_ceiling(journey.name, samples) diff --git a/tests/e2e/perf/test_ui_queries.py b/tests/e2e/perf/test_ui_queries.py deleted file mode 100644 index 75ac4d3055f..00000000000 --- a/tests/e2e/perf/test_ui_queries.py +++ /dev/null @@ -1,159 +0,0 @@ -from __future__ import annotations - -import json -import os -from dataclasses import dataclass, replace -from datetime import UTC, datetime -from pathlib import Path -from typing import Final - -import pytest -from e2e_config import CONTROL_PLANE_BASE_URL, MASTER_KEY -from e2e_http import send_text_external, without_retries -from setup.ui_queries import ( - Sample, - UiQueryCase, - database_failures, - error_code, - issue_query, - measure, - summarize, - ui_junit_properties, -) -from setup.ui_query_cases import Params, cases, next_page -from setup.ui_query_fixture import UiFixture, prepare_fixture -from setup.ui_query_isolation import isolated_database, settled_counter -from transport import HttpTransport - -pytestmark = [ - pytest.mark.perf, - pytest.mark.quiet_stack, - pytest.mark.skipif(os.environ.get("E2E_UI_PERF_DISPOSABLE") != "1", reason="Dedicated disposable database only"), -] - - -def pytest_generate_tests(metafunc: pytest.Metafunc) -> None: - if "ui_case_name" not in metafunc.fixturenames: - return - if os.environ.get("E2E_UI_PERF_DISPOSABLE") == "1" and os.environ.get("E2E_RESET_SPEND_LOGS") == "1": - raise pytest.UsageError("UI performance tests cannot run with E2E_RESET_SPEND_LOGS=1") - names: Final = tuple(case.name for case in cases(datetime(2000, 1, 1, tzinfo=UTC), "collection-only")) - metafunc.parametrize("ui_case_name", names, ids=names) - - -@pytest.fixture(scope="module") -def ui_fixture() -> UiFixture: - return prepare_fixture() - - -def _metrics(transport: HttpTransport) -> float: - urls: Final = tuple(url.strip() for url in os.environ["E2E_DATABASE_METRICS_URLS"].split(",") if url.strip()) - try: - assert urls, "Provide a metrics URL for every proxy worker/pod" - readings: Final = tuple(send_text_external("GET", url, headers=transport.master, timeout=10) for url in urls) - assert all(reading.status_code == 200 for reading in readings), "Cannot read database failure metrics" - return sum(database_failures(reading.body) for reading in readings) - except Exception as error: - pytest.exit(f"Database metrics unavailable ({type(error).__name__}). Stopping UI measurements", returncode=2) - - -@dataclass(frozen=True, slots=True) -class Prepared: - case: UiQueryCase - prerequisite: Sample | None = None - - -def _page_two(transport: HttpTransport, case: UiQueryCase, timeout: float) -> Prepared: - if case.cursor == "none": - return Prepared(case) - params: Final = Params.model_validate(case.params.model_dump()).model_copy(update={"page": 1}) - first: Final = replace(case, params=params) - sample, document = measure(lambda: issue_query(transport, first, timeout=timeout), case.contract) - if sample.error or document is None: - return Prepared(case, sample) - try: - return Prepared(next_page(case, document), sample) - except AssertionError as error: - return Prepared(case, sample.model_copy(update={"error": str(error)})) - - -def _samples(transport: HttpTransport, case: UiQueryCase, timeout: float, repeats: int) -> tuple[Sample, ...]: - measured, _ = measure(lambda: issue_query(transport, case, timeout=timeout), case.contract) - if measured.error: - return (measured,) - repeated: Final = tuple( - measure(lambda: issue_query(transport, case, timeout=timeout), case.contract)[0] for _ in range(repeats) - ) - return (measured, *repeated) - - -def test_ui_query_performance(ui_case_name: str, ui_fixture: UiFixture, request: pytest.FixtureRequest) -> None: - case: Final = next(case for case in cases(ui_fixture.anchor, ui_fixture.api_key) if case.name == ui_case_name) - transport: Final = HttpTransport(base_url=CONTROL_PLANE_BASE_URL, master_key=MASTER_KEY) - timeout: Final = float(os.environ.get("E2E_UI_QUERY_TIMEOUT_SECONDS", "120")) - repeats: Final = int(os.environ.get("E2E_UI_QUERY_REPEATS", "9")) - assert 0 < timeout <= 600 and 1 <= repeats <= 1000, "Invalid UI performance sample settings" - target: Final = Path(os.environ["E2E_ARTIFACT_DIR"]) - assert target.is_dir(), "E2E_ARTIFACT_DIR must exist" - evidence: Final = target / f"ui-isolation-{case.name}.jsonl" - with without_retries(): - with isolated_database(case.name): - before: Final = settled_counter(lambda: _metrics(transport), evidence) - paginated: Final = _page_two(transport, case, timeout) - samples: Final = ( - (paginated.prerequisite,) - if paginated.prerequisite is not None and paginated.prerequisite.error - else _samples(transport, paginated.case, timeout, repeats) - ) - with evidence.open("a", encoding="utf-8") as sample_output: - _ = sample_output.write( - json.dumps( - { - "samples": tuple(sample.model_dump() for sample in samples), - "prerequisite": paginated.prerequisite.model_dump() - if paginated.prerequisite is not None - else None, - } - ) - + "\n" - ) - after_requests: Final = _metrics(transport) - item: Final = request.node # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # pytest: untyped - assert isinstance(item, pytest.Item) - item.user_properties.extend(ui_junit_properties(samples, paginated.prerequisite)) - after: Final = settled_counter(lambda: _metrics(transport), evidence) - item.user_properties.extend( - ( - ("perf_ui_database_failures", after_requests - before), - ("perf_ui_cleanup_database_failures", after - after_requests), - ) - ) - timings: Final = summarize(samples) - artifact: Final = { - "name": case.name, - "surface": case.surface, - "path": case.path, - "method": "POST" if case.body is not None else "GET", - "params": paginated.case.params.model_dump(mode="json", by_alias=True, exclude_none=True), - "prerequisite": paginated.prerequisite.model_dump() if paginated.prerequisite is not None else None, - "prerequisite_failed": paginated.prerequisite is not None and bool(paginated.prerequisite.error), - "body": case.body.model_dump(mode="json", exclude_none=True) if case.body is not None else None, - "samples": [sample.model_dump() for sample in samples], - "error_codes": [error_code(sample) for sample in samples], - "timings": timings.model_dump(), - "timeouts": sum(sample.error == "timeout" for sample in samples), - "failures": sum(bool(sample.error) for sample in samples), - "status_counts": { - str(status): sum(sample.status == status for sample in samples) - for status in frozenset(sample.status for sample in samples) - }, - "validation_failures": sum( - bool(sample.error) and (sample.status == 200 or sample.error == "Response is not valid JSON") - for sample in samples - ), - "database_failures_before": before, - "database_failures_after_requests": after_requests, - "database_failures_after_cleanup": after, - } - output: Final = target / f"ui-query-{case.name}.json" - _ = output.write_text(json.dumps(artifact, indent=2), encoding="utf-8") diff --git a/tests/e2e_harness/perf/setup/test_observe.py b/tests/e2e_harness/perf/setup/test_observe.py index 281d981fbd9..1fbd5582ac3 100644 --- a/tests/e2e_harness/perf/setup/test_observe.py +++ b/tests/e2e_harness/perf/setup/test_observe.py @@ -6,7 +6,7 @@ from typing import Final from cases.small_bodies_5rps import CASE from memory_readings import RssCapture from setup.datastore import DbCounters, StatementCalls -from setup.observe import Observation, evaluate, junit_properties +from setup.observe import Contributor, Observation, breakdown, evaluate, junit_properties from setup.performance_test_case import Limit from setup.wire import WireRecord @@ -67,7 +67,7 @@ def test_junit_properties_carry_each_observed_metric_and_each_limit_including_un properties: Final = junit_properties(rows) assert len({name for name, _ in properties}) == len(properties) - assert dict(properties) == { + assert {name: value for name, value in properties if not name.endswith("_breakdown")} == { "perf_unexpected_status_count": 0.0, "perf_gateway_added_seconds_p50": 0.5, "perf_gateway_added_seconds_p50_limit": 0.625, @@ -174,3 +174,56 @@ def test_background_cap_without_exemptions_counts_the_guardrail_upsert() -> None assert exceeded == [ f"postgres_max_background_statement_per_request: observed 1.1500 > limit 0.9000 ({GUARDRAIL_UPSERT})" ], exceeded + + +def _guardrail_rollup(calls: int) -> StatementCalls: + return StatementCalls( + queryid=2, + query='INSERT INTO "LiteLLM_DailyGuardrailMetrics" ("guardrail_id","date") VALUES ($1,$2) ON CONFLICT DO UPDATE', + calls=calls, + total_exec_ms=calls * 1.0, + ) + + +def _model_rollup(calls: int) -> StatementCalls: + return StatementCalls( + queryid=3, + query='INSERT INTO "LiteLLM_DailyModelUsage" ("model","date") VALUES ($1,$2) ON CONFLICT DO UPDATE', + calls=calls, + total_exec_ms=calls * 1.0, + ) + + +def test_breakdown_names_the_slices_behind_each_metric_and_skips_plain_gauges() -> None: + failed: Final = served(3, 1.0).model_copy(update={"status": 500, "ok": False}) + observation: Final = Observation( + records=(served(0, 1.25), served(1, 1.5), served(2, 1.75), failed), + mock_requests=(), + guardrail_calls=(), + rss_before=NO_RSS, + rss_after=NO_RSS, + wall_seconds=4.0, + db_before=DbCounters( + commits=100, statements=(_key_lookup(calls=100), _guardrail_rollup(calls=100), _model_rollup(calls=100)) + ), + db_after=DbCounters( + commits=130, statements=(_key_lookup(calls=130), _guardrail_rollup(calls=124), _model_rollup(calls=112)) + ), + gateway_cpu_seconds=2.0, + ) + + busiest: Final = breakdown("postgres_max_background_statement_per_request", None, observation) + assert [(item.value, item.share) for item in busiest] == [(6.0, 24 / 36), (3.0, 12 / 36)] + assert "LiteLLM_DailyGuardrailMetrics" in busiest[0].label + assert breakdown("gateway_added_seconds", 50, observation) == (Contributor("chat_completions", 0.5, 1.0),) + assert breakdown("unexpected_status_count", None, observation) == ( + Contributor("chat_completions status 500", 1.0, 1.0), + ) + assert breakdown("cpu_seconds_per_request", None, observation) == () + + rows, _ = evaluate(CASE, observation) + properties: Final = dict(junit_properties(rows)) + assert "perf_cpu_seconds_per_request_breakdown" not in properties + assert properties["perf_unexpected_status_count_breakdown"] == ( + '[{"label": "chat_completions status 500", "value": 1.0, "share": 1.0}]' + ) diff --git a/tests/e2e_harness/perf/setup/test_ui_journeys.py b/tests/e2e_harness/perf/setup/test_ui_journeys.py new file mode 100644 index 00000000000..d008368052c --- /dev/null +++ b/tests/e2e_harness/perf/setup/test_ui_journeys.py @@ -0,0 +1,173 @@ +from __future__ import annotations + +from typing import Final + +import pytest +from setup.ui_journeys import ( + UI_JOURNEY_LIMITS, + Sample, + assert_within_ceiling, + database_failures, + error_code, + journeys, + summarize, + ui_junit_properties, +) + + +def test_first_journey_is_separate_from_repeated_latency() -> None: + samples: Final = (Sample(seconds=80), *(Sample(seconds=i) for i in range(1, 101))) + result: Final = summarize(samples) + assert result.first_seconds == 80 + assert result.repeated_samples == 100 + assert result.repeated_p50_seconds == 50.5 + assert result.repeated_p95_seconds == 95 + assert result.repeated_p99_seconds == 99 + assert result.repeated_max_seconds == 100 + + +def test_failed_repeats_do_not_look_like_fast_successes() -> None: + result: Final = summarize((Sample(seconds=10), Sample(seconds=0.01, error="AssertionError: no rows"))) + assert result.repeated_samples == 0 + assert result.repeated_p50_seconds is None + assert result.repeated_p95_seconds is None + assert result.repeated_p99_seconds is None + assert result.repeated_max_seconds is None + + +def test_small_sample_does_not_report_tail_percentiles() -> None: + result: Final = summarize(tuple(Sample(seconds=1) for _ in range(6))) + assert result.repeated_samples == 5 + assert result.repeated_p50_seconds == 1 + assert result.repeated_p95_seconds is None + assert result.repeated_p99_seconds is None + + +def test_failed_first_journey_emits_error_code_without_latency() -> None: + sample: Final = Sample(seconds=120, error="timeout") + assert summarize((sample,)).first_seconds is None + assert dict(ui_junit_properties((sample,))) == { + "perf_ui_journeys": 1, + "perf_ui_failures": 1, + "perf_ui_samples": 0, + "perf_ui_repeated_samples": 0, + "perf_ui_error_timeout": 1, + } + + +def test_junit_counts_failures_but_only_measures_successful_latency() -> None: + samples: Final = ( + Sample(seconds=2, rows=25), + Sample(seconds=3, rows=25), + Sample(seconds=120, error="timeout"), + Sample(seconds=1, error="AssertionError: Logs table rendered empty"), + Sample(seconds=4, rows=25), + ) + assert dict(ui_junit_properties(samples)) == { + "perf_ui_journeys": 5, + "perf_ui_failures": 2, + "perf_ui_samples": 3, + "perf_ui_repeated_samples": 2, + "perf_ui_error_timeout": 1, + "perf_ui_error_ui": 1, + "perf_ui_seconds_p50": 3, + "perf_ui_seconds_p90": 4, + "perf_ui_seconds_max": 4, + "perf_ui_first_seconds": 2, + "perf_ui_repeated_seconds_p50": 3.5, + "perf_ui_repeated_seconds_max": 4, + } + + +def test_all_journey_percentiles_include_first_and_use_nearest_rank_p90() -> None: + samples: Final = tuple(Sample(seconds=seconds) for seconds in (10, 1, 9, 2, 8, 3, 7, 4, 6, 5)) + metrics: Final = dict(ui_junit_properties(samples)) + assert {key: value for key, value in metrics.items() if key.startswith("perf_ui_seconds_")} == { + "perf_ui_seconds_p50": 5.5, + "perf_ui_seconds_p90": 9, + "perf_ui_seconds_max": 10, + } + assert metrics["perf_ui_samples"] == 10 + + +def test_journeys_have_unique_names_and_cover_every_dashboard_surface() -> None: + names: Final = tuple(journey.name for journey in journeys("key")) + assert len(names) == len(frozenset(names)) + assert frozenset(journey.surface for journey in journeys("key")) == {"logs", "usage", "caching", "models", "keys"} + + +def _metrics(postgres: str, batch: str) -> str: + return ( + "# TYPE litellm_postgres_failed_requests_total counter\n" + f'litellm_postgres_failed_requests_total{{call_type="query_raw"}} {postgres}\n' + "# TYPE litellm_batch_write_to_db_failed_requests_total counter\n" + f'litellm_batch_write_to_db_failed_requests_total{{call_type="batch"}} {batch}\n' + ) + + +def test_postgres_failures_include_background_batch_writes() -> None: + assert database_failures(_metrics("0", "0")) == 0 + assert database_failures(_metrics("2", "3")) == 5 + + +def test_lazy_failure_counters_require_evidence_of_database_activity() -> None: + assert ( + database_failures( + "# TYPE litellm_postgres_total_requests_total counter\nlitellm_postgres_total_requests_total 3\n" + ) + == 0 + ) + + +@pytest.mark.parametrize( + "text", ("", "# TYPE unrelated counter\nunrelated_total 0\n", _metrics("NaN", "0"), _metrics("-1", "0")) +) +def test_missing_or_invalid_metrics_cannot_pass_as_zero(text: str) -> None: + with pytest.raises(AssertionError): + _ = database_failures(text) + + +def test_every_journey_has_a_latency_ceiling() -> None: + assert frozenset(journey.name for journey in journeys("key")) == frozenset(UI_JOURNEY_LIMITS) + + +def test_failed_sample_fails_the_journey_before_latency_is_judged() -> None: + with pytest.raises(AssertionError, match="1 of 2 logs_open_24h samples failed: timeout"): + assert_within_ceiling("logs_open_24h", (Sample(seconds=0.2, rows=25), Sample(seconds=120, error="timeout"))) + + +def test_slow_journey_fails_its_ceiling() -> None: + fast: Final = tuple(Sample(seconds=1, rows=25) for _ in range(9)) + assert_within_ceiling("logs_open_24h", fast) + with pytest.raises(AssertionError, match=r"logs_open_24h p90 25\.0s over 20s"): + assert_within_ceiling("logs_open_24h", (*fast[:8], Sample(seconds=25, rows=25), Sample(seconds=25, rows=25))) + with pytest.raises(AssertionError, match=r"logs_open_24h p50 11\.0s over 10s"): + assert_within_ceiling("logs_open_24h", tuple(Sample(seconds=11, rows=25) for _ in range(3))) + + +def test_failed_data_request_status_becomes_the_error_code() -> None: + gateway_error: Final = Sample(seconds=0.4, error="AssertionError: Locator expected to be enabled", status=500) + slow: Final = Sample(seconds=60.0, error="timeout", status=200, request="GET /spend/logs/ui") + hung: Final = Sample(seconds=700.0, error="wall_clock TimeoutError: logs_next_page exceeded its 660s wall clock") + assert (error_code(gateway_error), error_code(slow), error_code(hung)) == ("http_500", "timeout", "wall_clock") + metrics: Final = dict(ui_junit_properties((gateway_error, slow, hung))) + assert metrics["perf_ui_error_http_500"] == 1 and metrics["perf_ui_error_wall_clock"] == 1 + assert "perf_ui_error_ui" not in metrics + + +def test_volume_properties_name_rows_and_bytes_per_queried_table() -> None: + from setup.ui_query_fixture import TableVolume, volume_properties + + properties: Final = volume_properties( + ( + TableVolume(table="LiteLLM_SpendLogs", rows=850_000_000, bytes=1_000_000_000_000), + TableVolume(table="LiteLLM_VerificationToken", rows=5_000, bytes=4_194_304), + ) + ) + + assert properties == ( + ("perf_ui_db_rows_LiteLLM_SpendLogs", 850_000_000), + ("perf_ui_db_bytes_LiteLLM_SpendLogs", 1_000_000_000_000), + ("perf_ui_db_rows_LiteLLM_VerificationToken", 5_000), + ("perf_ui_db_bytes_LiteLLM_VerificationToken", 4_194_304), + ) diff --git a/tests/e2e_harness/perf/setup/test_ui_queries.py b/tests/e2e_harness/perf/setup/test_ui_queries.py deleted file mode 100644 index f24d03c6bba..00000000000 --- a/tests/e2e_harness/perf/setup/test_ui_queries.py +++ /dev/null @@ -1,257 +0,0 @@ -from __future__ import annotations - -from datetime import UTC, datetime -from typing import Final -from urllib.parse import parse_qs, urlsplit - -import pytest -from e2e_http import NetworkError, Result, Success, UnknownApiError -from setup.ui_queries import ( - Contract, - Document, - Sample, - database_failures, - measure, - query_path, - summarize, - ui_junit_properties, -) -from setup.ui_query_cases import Params, cases, next_page - - -def test_query_string_preserves_ui_arrays_and_boolean_strings() -> None: - requests: Final = cases(datetime(2026, 1, 1, tzinfo=UTC), "key") - cache: Final = next(case for case in requests if case.name == "cache_activity_filtered") - assert parse_qs(urlsplit(query_path(cache)).query) == { - "start_date": ["2025-12-25"], - "end_date": ["2026-01-01"], - "key_aliases": ["perf-key-0", "perf-key-1"], - "models": ["perf-chat"], - } - health: Final = next(case for case in requests if case.name == "logs_exclude_internal_health_checks_30d") - query: Final = parse_qs(urlsplit(query_path(health)).query) - assert query["exclude_internal_health_checks"] == ["true"] - assert query["group_by_session"] == ["true"] - - -@pytest.mark.parametrize("entity", ("user", "team", "tag", "customer")) -@pytest.mark.parametrize( - ("route", "extra"), - ( - ("aggregated", {}), - ("aggregated/keys", {"offset": 0, "limit": 50}), - ("aggregated/search", {"search": "perf-key"}), - ("aggregated/model_top_keys", {"model_group": "perf-chat", "by_model_group": "true"}), - ), -) -def test_usage_requests_list_keys_without_a_single_key_filter( - entity: str, route: str, extra: dict[str, str | int] -) -> None: - case: Final = next( - case - for case in cases(datetime(2026, 1, 1, tzinfo=UTC), "key") - if case.path == f"/{entity}/daily/activity/{route}" - ) - assert case.params.model_dump(exclude_none=True) == { - "start_date": "2025-12-25", - "end_date": "2026-01-01", - "timezone": "0", - **({"exclude_team_ids": "litellm-dashboard"} if entity == "team" else {}), - **extra, - } - - -@pytest.mark.parametrize(("name", "value"), (("api_key", "key"), ("key_alias", "perf-key-0"))) -def test_key_filters_request_30_days_of_logs(name: str, value: str) -> None: - case: Final = next( - case for case in cases(datetime(2026, 1, 1, tzinfo=UTC), "key") if case.name == f"logs_{name}_30d" - ) - assert parse_qs(urlsplit(query_path(case)).query) == { - "start_date": ["2025-12-02 00:00:00"], - "end_date": ["2026-01-01 00:00:00"], - "page_size": ["25"], - "page": ["1"], - "sort_by": ["startTime"], - "sort_order": ["desc"], - "group_by_session": ["true"], - name: [value], - } - - -@pytest.mark.parametrize("invalid", ("not-a-number", True, float("nan"), float("inf"))) -def test_positive_row_does_not_hide_a_malformed_later_row(invalid: str | bool | float) -> None: - with pytest.raises(AssertionError, match=r"Expected (numeric|finite) spend"): - Contract(positive=("spend",)).count(Document([{"spend": 1}, {"spend": invalid}])) - - -def test_session_cursor_is_reused_and_repeated_rows_rejected() -> None: - case: Final = next(case for case in cases(datetime(2026, 1, 1, tzinfo=UTC), "key") if case.cursor == "session") - first: Final = Document.model_validate_json('{"data":[{"request_id":"one"}],"next_session_cursor":"opaque"}') - second: Final = next_page(case, first) - assert Params.model_validate(second.params).session_cursor == "opaque" - assert Params.model_validate(second.params).page == 2 - with pytest.raises(AssertionError, match="Repeated page-one row"): - _ = second.contract.count(first) - - -def test_first_query_is_separate_from_repeated_latency() -> None: - samples: Final = (Sample(seconds=80, status=200), *(Sample(seconds=i, status=200) for i in range(1, 101))) - result: Final = summarize(samples) - assert result.first_seconds == 80 - assert result.repeated_samples == 100 - assert result.repeated_p50_seconds == 50.5 - assert result.repeated_p95_seconds == 95 - assert result.repeated_p99_seconds == 99 - assert result.repeated_max_seconds == 100 - - -def test_failed_repeats_do_not_look_like_fast_successes() -> None: - result: Final = summarize((Sample(seconds=10, status=200), Sample(seconds=0.01, status=503, error="HTTP 503"))) - assert result.repeated_samples == 0 - assert result.repeated_p50_seconds is None - assert result.repeated_p95_seconds is None - assert result.repeated_p99_seconds is None - assert result.repeated_max_seconds is None - - -def test_small_sample_does_not_report_tail_percentiles() -> None: - result: Final = summarize(tuple(Sample(seconds=1, status=200) for _ in range(6))) - assert result.repeated_samples == 5 - assert result.repeated_p50_seconds == 1 - assert result.repeated_p95_seconds is None - assert result.repeated_p99_seconds is None - - -def test_failed_first_request_emits_error_code_without_latency() -> None: - sample: Final = Sample(seconds=30, status=500, error="HTTP 500") - assert summarize((sample,)).first_seconds is None - assert dict(ui_junit_properties((sample,))) == { - "perf_ui_requests": 1, - "perf_ui_failures": 1, - "perf_ui_samples": 0, - "perf_ui_repeated_samples": 0, - "perf_ui_error_http_500": 1, - } - - -def test_junit_counts_failures_but_only_measures_successful_latency() -> None: - samples: Final = ( - Sample(seconds=2, status=200), - Sample(seconds=3, status=200), - Sample(seconds=30, status=-1, error="timeout"), - Sample(seconds=30, status=503, error="HTTP 503"), - Sample(seconds=1, status=200, error="Empty collection"), - ) - assert dict(ui_junit_properties(samples, Sample(seconds=4, status=200))) == { - "perf_ui_requests": 6, - "perf_ui_failures": 3, - "perf_ui_samples": 2, - "perf_ui_seconds_p50": 2.5, - "perf_ui_seconds_p90": 3, - "perf_ui_seconds_max": 3, - "perf_ui_repeated_samples": 1, - "perf_ui_error_timeout": 1, - "perf_ui_error_http_503": 1, - "perf_ui_error_contract": 1, - "perf_ui_first_seconds": 2, - "perf_ui_repeated_seconds_p50": 3, - "perf_ui_repeated_seconds_max": 3, - } - - -def test_failed_cursor_prerequisite_is_counted_once() -> None: - sample: Final = Sample(seconds=30, status=503, error="HTTP 503") - assert dict(ui_junit_properties((sample,), sample)) == dict(ui_junit_properties((sample,))) - - -def test_all_request_percentiles_include_first_and_use_nearest_rank_p90() -> None: - samples: Final = tuple(Sample(seconds=seconds, status=200) for seconds in (10, 1, 9, 2, 8, 3, 7, 4, 6, 5)) - metrics: Final = dict(ui_junit_properties(samples)) - assert {key: value for key, value in metrics.items() if key.startswith("perf_ui_seconds_")} == { - "perf_ui_seconds_p50": 5.5, - "perf_ui_seconds_p90": 9, - "perf_ui_seconds_max": 10, - } - assert metrics["perf_ui_samples"] == 10 - - -@pytest.mark.parametrize("body", ("{}", '{"data": []}', '{"data": [{"spend": 1}]}', '{"data": [null]}')) -def test_empty_or_malformed_rows_fail_even_with_http_200(body: str) -> None: - ticks: Final = iter((10.0, 12.5)) - result, _ = measure( - lambda: Success(status_code=200, data=Document.model_validate_json(body)), - Contract(("data",), ("request_id",)), - clock=lambda: next(ticks), - ) - assert result.status == 200 - assert result.seconds == 2.5 - assert result.rows == 0 - assert result.error - - -def test_valid_response_records_elapsed_seconds_and_rows() -> None: - ticks: Final = iter((5.0, 5.125)) - result, document = measure( - lambda: Success(status_code=200, data=Document.model_validate_json('{"data":[{"request_id":"one"}]}')), - Contract(("data",), ("request_id",)), - clock=lambda: next(ticks), - ) - assert result == Sample(seconds=0.125, status=200, rows=1) - assert document is not None - - -def test_zero_spend_rows_are_allowed_alongside_nonzero_fixture_data() -> None: - contract: Final = Contract(positive=("spend",)) - assert contract.count(Document.model_validate_json('[{"spend":0},{"spend":2}]')) == 2 - with pytest.raises(AssertionError, match="positive spend"): - _ = contract.count(Document.model_validate_json('[{"spend":0}]')) - - -@pytest.mark.parametrize( - "failure,error,status", - ( - (UnknownApiError(status_code=500, body="sensitive error detail"), "HTTP 500", 500), - (NetworkError(message="Read timed out"), "timeout", -1), - (NetworkError(message="connection refused"), "network", -1), - ), -) -def test_failed_requests_are_recorded_without_response_bodies( - failure: Result[Document], - error: str, - status: int, -) -> None: - ticks: Final = iter((1.0, 2.0)) - result, document = measure(lambda: failure, Contract(), clock=lambda: next(ticks)) - assert result == Sample(seconds=1, status=status, error=error) - assert document is None - - -def _metrics(postgres: str, batch: str) -> str: - return ( - "# TYPE litellm_postgres_failed_requests_total counter\n" - f'litellm_postgres_failed_requests_total{{call_type="query_raw"}} {postgres}\n' - "# TYPE litellm_batch_write_to_db_failed_requests_total counter\n" - f'litellm_batch_write_to_db_failed_requests_total{{call_type="batch"}} {batch}\n' - ) - - -def test_postgres_failures_include_background_batch_writes() -> None: - assert database_failures(_metrics("0", "0")) == 0 - assert database_failures(_metrics("2", "3")) == 5 - - -def test_lazy_failure_counters_require_evidence_of_database_activity() -> None: - assert ( - database_failures( - "# TYPE litellm_postgres_total_requests_total counter\nlitellm_postgres_total_requests_total 3\n" - ) - == 0 - ) - - -@pytest.mark.parametrize( - "text", ("", "# TYPE unrelated counter\nunrelated_total 0\n", _metrics("NaN", "0"), _metrics("-1", "0")) -) -def test_missing_or_invalid_metrics_cannot_pass_as_zero(text: str) -> None: - with pytest.raises(AssertionError): - _ = database_failures(text) diff --git a/tests/e2e_harness/perf/test_upgrade.py b/tests/e2e_harness/perf/test_upgrade.py index 0904b7a7b5a..1f2bc8c46cb 100644 --- a/tests/e2e_harness/perf/test_upgrade.py +++ b/tests/e2e_harness/perf/test_upgrade.py @@ -295,22 +295,31 @@ def test_invalid_200_is_not_an_allowed_non_200(failed: WireRecord) -> None: _ = Probe().monitor().poll((failed,)) +def _ceiling(metric: str, percentile: int | None = None) -> float: + return next( + limit.max for limit in upgrade_case().limits if limit.metric == metric and limit.percentile == percentile + ) + + @pytest.mark.parametrize( - "failures,overhead,ttft,growth,expected", + "over,expected", [ - (3, 0.29, 3.7, 100, ()), - (4, 0.29, 3.7, 100, ("unexpected_status_count",)), - (3, 0.30, 3.7, 100, ("gateway_added_seconds percentile 50",)), - (3, 0.29, 3.8, 100, ("time_to_first_token_seconds percentile 99",)), - (3, 0.29, 3.7, 101, ("memory_growth_megabytes",)), + ("", ()), + ("unexpected_status_count", ("unexpected_status_count",)), + ("gateway_added_seconds", ("gateway_added_seconds percentile 50",)), + ("time_to_first_token_seconds", ("time_to_first_token_seconds percentile 99",)), + ("memory_growth_megabytes", ("memory_growth_megabytes",)), ], ) def test_upgrade_verdict_uses_regular_limits_without_cpu_or_datastore_samples( - failures: int, overhead: float, ttft: float, growth: float, expected: tuple[str, ...] + over: str, expected: tuple[str, ...] ) -> None: - nonstream: Final = tuple( - record(i).model_copy(update={"total_s": overhead, "mock_delay_s": 0}) for i in range(100) - ) + """Each sample sits exactly on the case's ceiling, so only the one nudged past it goes over.""" + failures: Final = int(_ceiling("unexpected_status_count")) + (over == "unexpected_status_count") + overhead: Final = _ceiling("gateway_added_seconds", 50) * (1.01 if over == "gateway_added_seconds" else 1) + ttft: Final = _ceiling("time_to_first_token_seconds", 99) * (1.01 if over == "time_to_first_token_seconds" else 1) + growth: Final = _ceiling("memory_growth_megabytes") + (over == "memory_growth_megabytes") + nonstream: Final = tuple(record(i).model_copy(update={"total_s": overhead, "mock_delay_s": 0}) for i in range(100)) stream: Final = record(100).model_copy(update={"stream": True, "first_token_s": ttft}) observed: Final = Observation( records=(*nonstream, stream, *(failed_record(i) for i in range(101, 101 + failures))), diff --git a/tests/harness_e2e/conftest.py b/tests/harness_e2e/conftest.py index ba679d6d5bf..9521519d18a 100644 --- a/tests/harness_e2e/conftest.py +++ b/tests/harness_e2e/conftest.py @@ -1,6 +1,6 @@ """Fixtures for the litellm.agent() end-to-end tests. -These run the real harness runtimes (claude, codex, opencode, deepagents) against a real +These run the real harness runtimes (claude, codex, opencode, pi, deepagents) against a real LiteLLM AI Gateway, routed with the `litellm_proxy/` model prefix. They skip unless LITELLM_PROXY_API_BASE and LITELLM_PROXY_API_KEY are set. Model groups can be overridden per harness with HARNESS_E2E_MODEL_. @@ -23,6 +23,7 @@ DEFAULT_MODEL_GROUPS = { Harness.CLAUDE_CODE: "claude-haiku-4-5-20251001", Harness.CODEX: "bedrock_mantle/openai.gpt-5.4", Harness.OPENCODE: "claude-haiku-4-5-20251001", + Harness.PI: "claude-haiku-4-5-20251001", Harness.DEEPAGENTS: "claude-haiku-4-5-20251001", } @@ -30,6 +31,7 @@ BINARIES = { Harness.CLAUDE_CODE: "claude", Harness.CODEX: "codex", Harness.OPENCODE: "opencode", + Harness.PI: "pi", } requires_gateway = pytest.mark.skipif( @@ -62,7 +64,7 @@ def harness_params() -> list: not harness_available(h), reason=f"{h.value} runtime not installed" ), ) - for h in Harness + for h in DEFAULT_MODEL_GROUPS ] diff --git a/tests/harness_e2e/test_harness_e2e.py b/tests/harness_e2e/test_harness_e2e.py index 8892085f4bc..36726c18b0f 100644 --- a/tests/harness_e2e/test_harness_e2e.py +++ b/tests/harness_e2e/test_harness_e2e.py @@ -16,7 +16,7 @@ from litellm.harness import ( ToolCall, ) -from .conftest import harness_params, model_for, requires_gateway +from .conftest import harness_available, harness_params, model_for, requires_gateway pytestmark = [requires_gateway] @@ -119,6 +119,69 @@ def test_agent_detach_and_resume(harness: Harness, workspace: Path) -> None: assert "4817" in r.text +requires_opencode = pytest.mark.skipif( + not harness_available(Harness.OPENCODE), reason="opencode runtime not installed" +) + + +@requires_opencode +def test_opencode_session_resumed_in_another_sandbox_keeps_working_in_both( + workspace: Path, tmp_path: Path +) -> None: + model = model_for(Harness.OPENCODE) + s = litellm.agent_session( + Harness.OPENCODE, + sandbox=sandbox.local(workspace), + model=model, + timeout=TURN_TIMEOUT, + ) + s.run("Remember this number: 4817. Reply with just OK.") + raw = s.detach().dumps() + moved = tmp_path / "moved" + moved.mkdir() + + with litellm.agent_resume( + State.loads(raw), sandbox=sandbox.local(workspace), model=model, timeout=TURN_TIMEOUT + ) as original: + original.run("Reply with just OK.") + with litellm.agent_resume( + State.loads(raw), sandbox=sandbox.local(moved), model=model, timeout=TURN_TIMEOUT + ) as resumed: + resumed.run( + "Create a file named hello.txt whose only content is the number I asked " + "you to remember." + ) + original.run( + "Create a file named again.txt whose only content is the number I asked " + "you to remember." + ) + + assert (moved / "hello.txt").read_text().strip() == "4817" + assert (workspace / "again.txt").read_text().strip() == "4817" + assert not (workspace / "hello.txt").exists() + + +@requires_opencode +def test_opencode_resume_of_a_missing_session_ends_with_a_runtime_error( + workspace: Path, +) -> None: + model = model_for(Harness.OPENCODE) + missing = State( + harness=Harness.OPENCODE, + native_session_id="ses_0000000000000000000missing", + workdir=str(workspace), + model=model, + ) + + with litellm.agent_resume( + missing, sandbox=sandbox.local(workspace), model=model, timeout=TURN_TIMEOUT + ) as resumed: + result = resumed.run("Reply with just OK.") + + assert result.stop_reason == "runtime_error" + assert "ses_0000000000000000000missing" in result.text + + @pytest.mark.parametrize("harness", harness_params()) def test_agent_read_only_blocks_writes(harness: Harness, workspace: Path) -> None: result = litellm.agent( diff --git a/tests/integration/_support/hook_count_probe.py b/tests/integration/_support/hook_count_probe.py new file mode 100644 index 00000000000..0d4056e8fb9 --- /dev/null +++ b/tests/integration/_support/hook_count_probe.py @@ -0,0 +1,91 @@ +import json +import os +from collections.abc import Mapping +from datetime import datetime +from typing import Final + +import httpx +from fastapi import HTTPException + +from litellm.integrations.custom_guardrail import CustomGuardrail +from litellm.integrations.custom_logger import CustomLogger + + +def _record(hook: str, kwargs: Mapping[str, object]) -> bytes: + return json.dumps( + {"hook": hook, "litellm_call_id": kwargs.get("litellm_call_id"), "call_type": kwargs.get("call_type")} + ).encode() + + +def _send(hook: str, kwargs: Mapping[str, object]) -> None: + with httpx.Client(trust_env=False) as client: + client.post(os.environ["HOOK_COUNT_PROBE_URL"], content=_record(hook, kwargs)).raise_for_status() + + +async def _send_async(hook: str, kwargs: Mapping[str, object]) -> None: + async with httpx.AsyncClient(trust_env=False) as client: + response: Final = await client.post(os.environ["HOOK_COUNT_PROBE_URL"], content=_record(hook, kwargs)) + response.raise_for_status() + + +class HookCountProbe(CustomLogger): + """Reports every sync and async success and failure hook it receives, one record per call.""" + + def log_success_event( + self, kwargs: Mapping[str, object], response_obj: object, start_time: datetime, end_time: datetime + ) -> None: + _send("sync_success", kwargs) + + async def async_log_success_event( + self, kwargs: Mapping[str, object], response_obj: object, start_time: datetime, end_time: datetime + ) -> None: + await _send_async("async_success", kwargs) + + def log_failure_event( + self, kwargs: Mapping[str, object], response_obj: object, start_time: datetime, end_time: datetime + ) -> None: + _send("sync_failure", kwargs) + + async def async_log_failure_event( + self, kwargs: Mapping[str, object], response_obj: object, start_time: datetime, end_time: datetime + ) -> None: + await _send_async("async_failure", kwargs) + + +class SyncOnlyHookCountProbe(CustomLogger): + """Overrides only the sync success and failure hooks.""" + + def log_success_event( + self, kwargs: Mapping[str, object], response_obj: object, start_time: datetime, end_time: datetime + ) -> None: + _send("sync_success", kwargs) + + def log_failure_event( + self, kwargs: Mapping[str, object], response_obj: object, start_time: datetime, end_time: datetime + ) -> None: + _send("sync_failure", kwargs) + + +class BlockingPostCallGuardrail(CustomGuardrail): + """Rejects every response with a 400 after the provider answered.""" + + async def async_post_call_success_hook( + self, data: Mapping[str, object], user_api_key_dict: object, response: object + ) -> None: + raise HTTPException(status_code=400, detail="blocked by the hook-count guardrail") + + +probe: Final = HookCountProbe() +sync_only_probe: Final = SyncOnlyHookCountProbe() + + +def sync_success_function( + kwargs: Mapping[str, object], completion_response: object, start_time: datetime, end_time: datetime +) -> None: + _send("function_success", kwargs) + + +def sync_failure_function( + kwargs: Mapping[str, object], completion_response: object, start_time: datetime, end_time: datetime +) -> None: + _send("function_failure", kwargs) diff --git a/tests/integration/_support/hook_counts.py b/tests/integration/_support/hook_counts.py new file mode 100644 index 00000000000..6b7f482bd85 --- /dev/null +++ b/tests/integration/_support/hook_counts.py @@ -0,0 +1,329 @@ +"""Scripted provider, proxy config and request helpers shared by the CustomLogger hook count tests.""" + +import base64 +import json +import threading +from collections.abc import Callable, Mapping +from dataclasses import dataclass, field +from pathlib import Path +from typing import Final + +import httpx +import yaml +from integration._support.client import Gateway, held +from integration._support.wire import Reply, Request, Wire + +WAV_BYTES: Final = ( + b"RIFF\x30\x00\x00\x00WAVEfmt \x10\x00\x00\x00\x01\x00\x01\x00" + b"\x40\x1f\x00\x00\x40\x1f\x00\x00\x01\x00\x08\x00data\x08\x00\x00\x00" + b"\x00\x01\x02\x03\x04\x05\x06\x07" +) +PNG_BYTES: Final = ( + b"\x89PNG\r\n\x1a\n\x00\x00\x00\rIHDR\x00\x00\x00\x01\x00\x00\x00\x01\x08\x06\x00\x00\x00" + b"\x1f\x15\xc4\x89\x00\x00\x00\rIDAT\x08\xd7c\xf8\xcf\xc0\xf0\x1f\x00\x05\x00\x01\xff" + b"\x89\x99=\x1d\x00\x00\x00\x00IEND\xaeB`\x82" +) +_IMAGE_REPLY: Final = json.dumps({"created": 1700000000, "data": [{"b64_json": base64.b64encode(PNG_BYTES).decode()}]}) +_CHAT_REPLY: Final = json.dumps( + { + "id": "chatcmpl-hook-count", + "object": "chat.completion", + "created": 1, + "model": "gpt-4o-mini", + "choices": [{"index": 0, "message": {"role": "assistant", "content": "ok"}, "finish_reason": "stop"}], + "usage": {"prompt_tokens": 3, "completion_tokens": 1, "total_tokens": 4}, + } +) +_EMBEDDING_REPLY: Final = json.dumps( + { + "object": "list", + "model": "text-embedding-3-small", + "data": [{"object": "embedding", "index": 0, "embedding": [0.25, 0.5]}], + "usage": {"prompt_tokens": 3, "total_tokens": 3}, + } +) +_MESSAGE_REPLY: Final = json.dumps( + { + "id": "msg_hook_count", + "type": "message", + "role": "assistant", + "model": "claude-haiku-4-5", + "content": [{"type": "text", "text": "ok"}], + "stop_reason": "end_turn", + "stop_sequence": None, + "usage": {"input_tokens": 3, "output_tokens": 1}, + } +) +_RESPONSE_REPLY: Final = json.dumps( + { + "id": "resp_hook_count", + "object": "response", + "created_at": 1, + "status": "completed", + "model": "gpt-4o-mini", + "output": [ + { + "type": "message", + "id": "msg_hook_count", + "status": "completed", + "role": "assistant", + "content": [{"type": "output_text", "text": "ok", "annotations": []}], + } + ], + "usage": {"input_tokens": 3, "output_tokens": 1, "total_tokens": 4}, + } +) +_OCR_REPLY: Final = json.dumps( + { + "pages": [ + {"index": 0, "markdown": "page", "images": [], "dimensions": {"dpi": 200, "height": 1100, "width": 850}} + ], + "model": "mistral-ocr-latest", + "usage_info": {"pages_processed": 1, "doc_size_bytes": 64}, + "document_annotation": None, + } +) +_SEARCH_REPLY: Final = json.dumps( + {"results": [{"title": "hook count", "url": "https://result.invalid/a", "snippet": "hit"}]} +) +_CHAT_FRAMES: Final = ( + 'data: {"id":"chatcmpl-hook-count","object":"chat.completion.chunk","created":1,"model":"gpt-4o-mini",' + '"choices":[{"index":0,"delta":{"role":"assistant","content":"ok"},"finish_reason":null}]}', + 'data: {"id":"chatcmpl-hook-count","object":"chat.completion.chunk","created":1,"model":"gpt-4o-mini",' + '"choices":[{"index":0,"delta":{},"finish_reason":"stop"}],' + '"usage":{"prompt_tokens":3,"completion_tokens":1,"total_tokens":4}}', + "data: [DONE]", +) +_MESSAGE_FRAMES: Final = ( + "event: message_start\n" + 'data: {"type":"message_start","message":{"id":"msg_hook_count","type":"message","role":"assistant",' + '"model":"claude-haiku-4-5","content":[],"stop_reason":null,"stop_sequence":null,' + '"usage":{"input_tokens":3,"output_tokens":0}}}', + 'event: content_block_start\ndata: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""}}', + "event: content_block_delta\n" + 'data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"ok"}}', + 'event: content_block_stop\ndata: {"type":"content_block_stop","index":0}', + "event: message_delta\n" + 'data: {"type":"message_delta","delta":{"stop_reason":"end_turn","stop_sequence":null},"usage":{"output_tokens":1}}', + 'event: message_stop\ndata: {"type":"message_stop"}', +) +_RESPONSE_FRAMES: Final = ( + "event: response.created\n" + 'data: {"type":"response.created","sequence_number":0,"response":{"id":"resp_hook_count","object":"response",' + '"created_at":1,"status":"in_progress","model":"gpt-4o-mini","output":[],"usage":null}}', + "event: response.output_text.delta\n" + 'data: {"type":"response.output_text.delta","sequence_number":1,"item_id":"msg_hook_count","output_index":0,' + '"content_index":0,"delta":"ok"}', + "event: response.completed\n" + 'data: {"type":"response.completed","sequence_number":2,"response":{"id":"resp_hook_count","object":"response",' + '"created_at":1,"status":"completed","model":"gpt-4o-mini","output":[{"type":"message","id":"msg_hook_count",' + '"status":"completed","role":"assistant","content":[{"type":"output_text","text":"ok","annotations":[]}]}],' + '"usage":{"input_tokens":3,"output_tokens":1,"total_tokens":4}}}', +) +_STREAM_FRAMES: Final = { + "/v1/chat/completions": _CHAT_FRAMES, + "/v1/messages": _MESSAGE_FRAMES, + "/v1/responses": _RESPONSE_FRAMES, +} +SURFACE_CALL_TYPES: Final = { + "chat": "acompletion", + "embedding": "aembedding", + "messages": "anthropic_messages", + "responses": "aresponses", + "speech": "aspeech", + "transcription": "atranscription", + "image_generation": "aimage_generation", + "image_edit": "aimage_edit", + "ocr": "aocr", + "search": "asearch", +} +IN_THE_ASYNC_FLAG_LIST: Final = frozenset({"chat", "embedding", "messages", "responses"}) +STREAMING_SURFACES: Final = ("chat", "messages", "responses") + + +def _streams(request: Request) -> bool: + if request.headers.get("content-type", "").startswith("application/json"): + return json.loads(request.body or b"{}").get("stream") is True + return False + + +def provider(request: Request) -> Reply: + """Answers every surface the hook count tests drive; any target under /fail/ is a provider 400.""" + if request.method == "GET": + return Reply(body=b'{"object":"list","data":[]}') + if request.target.startswith("/fail/"): + return Reply( + status=400, + body=b'{"error":{"message":"scripted provider rejection","type":"invalid_request_error","code":null}}', + ) + if request.target in _STREAM_FRAMES and _streams(request): + return Reply( + chunks=tuple(f"{frame}\n\n".encode() for frame in _STREAM_FRAMES[request.target]), + content_type="text/event-stream", + ) + replies: Final[dict[str, Callable[[], Reply]]] = { + "/v1/chat/completions": lambda: Reply(body=_CHAT_REPLY.encode()), + "/v1/embeddings": lambda: Reply(body=_EMBEDDING_REPLY.encode()), + "/v1/messages": lambda: Reply(body=_MESSAGE_REPLY.encode()), + "/v1/responses": lambda: Reply(body=_RESPONSE_REPLY.encode()), + "/v1/audio/speech": lambda: Reply(body=WAV_BYTES, content_type="audio/wav"), + "/v1/audio/transcriptions": lambda: Reply(body=b'{"text":"hook count transcript"}'), + "/v1/images/generations": lambda: Reply(body=_IMAGE_REPLY.encode()), + "/v1/images/edits": lambda: Reply(body=_IMAGE_REPLY.encode()), + "/v1/ocr": lambda: Reply(body=_OCR_REPLY.encode()), + "/perplexity/search": lambda: Reply(body=_SEARCH_REPLY.encode()), + } + return replies[request.target]() + + +@dataclass +class HookRecords: + """Every hook record the probe reported, kept across drains so cells can read their own call id.""" + + wire: Wire + function_callbacks: bool + seen: list[dict[str, str]] = field(default_factory=list) + lock: threading.Lock = field(default_factory=threading.Lock) + + def drained(self) -> tuple[dict[str, str], ...]: + with self.lock: + self.seen.extend(json.loads(request.body) for request in self.wire.drain()) + return tuple(self.seen) + + def for_call(self, call_id: str) -> tuple[dict[str, str], ...]: + return tuple(record for record in self.drained() if record["litellm_call_id"] == call_id) + + +def _model(name: str, model: str, api_base: str, **extra: object) -> dict[str, object]: + return { + "model_name": name, + "litellm_params": {"model": model, "api_base": api_base, "api_key": "synthetic-provider-key"}, + **extra, + } + + +def write_hook_count_config( + path: Path, + provider_url: str, + litellm_settings: Mapping[str, object], + guardrails: tuple[Mapping[str, object], ...] = (), +) -> Path: + """One success and one failure deployment per surface, all answered by `provider`.""" + models: Final = [] + tools: Final = [] + for outcome, prefix in (("success", ""), ("failure", "/fail")): + base: str = provider_url + prefix + models.extend( + ( + _model(f"hooks-chat-{outcome}", "openai/gpt-4o-mini", base + "/v1"), + _model(f"hooks-embedding-{outcome}", "openai/text-embedding-3-small", base + "/v1"), + _model(f"hooks-messages-{outcome}", "anthropic/claude-haiku-4-5", base), + _model(f"hooks-responses-{outcome}", "openai/gpt-4o-mini", base + "/v1"), + _model(f"hooks-speech-{outcome}", "openai/gpt-4o-mini-tts", base + "/v1"), + _model(f"hooks-transcription-{outcome}", "openai/whisper-1", base + "/v1"), + _model(f"hooks-image_generation-{outcome}", "openai/gpt-image-1", base + "/v1"), + _model(f"hooks-image_edit-{outcome}", "openai/gpt-image-1", base + "/v1"), + _model(f"hooks-ocr-{outcome}", "mistral/mistral-ocr-latest", base + "/v1", model_info={"mode": "ocr"}), + ) + ) + tools.append( + { + "search_tool_name": f"hooks-search-{outcome}", + "litellm_params": { + "search_provider": "perplexity", + "api_key": "synthetic-provider-key", + "api_base": base + "/perplexity", + }, + } + ) + path.write_text( + yaml.safe_dump( + { + "model_list": models, + "search_tools": tools, + "litellm_settings": dict(litellm_settings), + **({"guardrails": [dict(guardrail) for guardrail in guardrails]} if guardrails else {}), + "general_settings": { + "master_key": "os.environ/LITELLM_MASTER_KEY", + "database_url": "os.environ/DATABASE_URL", + "disable_model_info_refresh": True, + }, + "router_settings": {"num_retries": 0}, + } + ) + ) + return path + + +def send( + proxy: Gateway, surface: str, outcome: str, call_id: str, *, key: str | None = None, stream: bool = False +) -> httpx.Response: + model: Final = f"hooks-{surface}-{outcome}" + nonce: Final = f"hook-count-{call_id}" + headers: Final = {"Authorization": f"Bearer {key or proxy.key}", "x-litellm-call-id": call_id} + if surface == "transcription": + return proxy.client.post( + "/v1/audio/transcriptions", + data={"model": model, "prompt": nonce}, + files={"file": ("a.wav", WAV_BYTES + call_id.encode(), "audio/wav")}, + headers=headers, + ) + if surface == "image_edit": + return proxy.client.post( + "/v1/images/edits", + data={"model": model, "prompt": nonce}, + files={"image": ("a.png", PNG_BYTES, "image/png")}, + headers=headers, + ) + streaming: Final[dict[str, object]] = {"stream": True} if stream else {} + routes: Final[dict[str, tuple[str, dict[str, object]]]] = { + "chat": ( + "/v1/chat/completions", + {"model": model, "messages": [{"role": "user", "content": nonce}], **streaming}, + ), + "embedding": ("/v1/embeddings", {"model": model, "input": nonce}), + "messages": ( + "/v1/messages", + {"model": model, "max_tokens": 16, "messages": [{"role": "user", "content": nonce}], **streaming}, + ), + "responses": ("/v1/responses", {"model": model, "input": nonce, **streaming}), + "speech": ("/v1/audio/speech", {"model": model, "input": nonce, "voice": "alloy", "response_format": "wav"}), + "image_generation": ("/v1/images/generations", {"model": model, "prompt": nonce, "n": 1}), + "ocr": ( + "/v1/ocr", + { + "model": model, + "document": { + "type": "document_url", + "document_url": "data:application/pdf;base64," + base64.b64encode(nonce.encode()).decode(), + }, + }, + ), + "search": ("/v1/search", {"search_tool_name": f"hooks-search-{outcome}", "query": nonce}), + } + path, body = routes[surface] + return proxy.client.post(path, json=body, headers=headers) + + +def counts_function_hooks(records: HookRecords, surface: str) -> bool: + return records.function_callbacks and surface not in IN_THE_ASYNC_FLAG_LIST + + +def probe_hooks(records: HookRecords, surface: str, found: tuple[dict[str, str], ...]) -> list[str]: + counted: Final = counts_function_hooks(records, surface) + return sorted(record["hook"] for record in found if counted or not record["hook"].startswith("function_")) + + +def one_async_hook(records: HookRecords, surface: str, outcome: str) -> list[str]: + function_hook: Final = (f"function_{outcome}",) if counts_function_hooks(records, surface) else () + return sorted((f"async_{outcome}", *function_hook)) + + +def assert_hooks(records: HookRecords, surface: str, call_id: str, expected: list[str]) -> None: + settled: Final = held( + lambda: records.for_call(call_id), + lambda found: probe_hooks(records, surface, found) == expected, + holding=3, + seconds=20, + ) + assert {record["call_type"] for record in settled} == {SURFACE_CALL_TYPES[surface]}, settled diff --git a/tests/integration/_support/mcp.py b/tests/integration/_support/mcp.py index f69079ce90b..99bf71cd459 100644 --- a/tests/integration/_support/mcp.py +++ b/tests/integration/_support/mcp.py @@ -282,6 +282,7 @@ class ScriptedTool: respond: Callable[[JsonRpc], Reply | JsonRpc] description: str | Callable[[Mapping[str, str]], str] | None = None input_schema: JsonRpc = field(default_factory=lambda: {"type": "object"}) + event_stream: bool = False def listing(self, headers: Mapping[str, str]) -> JsonRpc: described: Final = self.description(headers) if callable(self.description) else self.description @@ -334,7 +335,10 @@ def scripted_peer(*tools: ScriptedTool) -> Iterator[McpPeer]: if tool is None: return jsonrpc_error(identity, -32602, "unknown tool") produced: Final = tool.respond(body["params"]) - return produced if isinstance(produced, Reply) else jsonrpc_reply(identity, produced) + reply: Final = produced if isinstance(produced, Reply) else jsonrpc_reply(identity, produced) + if not tool.event_stream: + return reply + return Reply(content_type="text/event-stream", body=b"event: message\ndata: " + reply.body + b"\n\n") with wire_server(provider) as wire: yield McpPeer(wire.url + "/mcp", observed) diff --git a/tests/integration/authorization/test_agent_least_privilege.py b/tests/integration/authorization/test_agent_least_privilege.py index 8a7f1596379..498a53c3ca9 100644 --- a/tests/integration/authorization/test_agent_least_privilege.py +++ b/tests/integration/authorization/test_agent_least_privilege.py @@ -8,7 +8,6 @@ import httpx import pytest import yaml from integration._support.client import Gateway, eventually, object_value, string_value -from integration._support.database import read_rows from integration._support.process import owned_proxy from integration._support.wire import Reply, Request, Wire, wire_server @@ -108,7 +107,7 @@ def _create_agent(candidate: Gateway, wire: Wire, agent_name: str, cleanups: Exi def _delete_agent(candidate: Gateway, agent_id: str) -> None: deleted: Final = candidate.request("DELETE", f"/v1/agents/{agent_id}") assert deleted.status_code == 200, deleted.text - assert read_rows('SELECT agent_id FROM "LiteLLM_AgentsTable" WHERE agent_id=%s', (agent_id,)) == [] + assert candidate.rows('SELECT agent_id FROM "LiteLLM_AgentsTable" WHERE agent_id=%s', (agent_id,)) == [] def _card(candidate: Gateway, agent_id: str, key: str) -> httpx.Response: diff --git a/tests/integration/authorization/test_search_tool_allowlist.py b/tests/integration/authorization/test_search_tool_allowlist.py index 84f2b7ebaf2..3782f31991b 100644 --- a/tests/integration/authorization/test_search_tool_allowlist.py +++ b/tests/integration/authorization/test_search_tool_allowlist.py @@ -92,7 +92,10 @@ def test_search_tool_allowlist_refuses_other_tools_before_any_upstream_call( assert (refused.status_code, refused.json()) == (403, refusal), refused.text assert wire.drain() == () served: Final = gateway.request("POST", f"/v1/search/{allowed}", _SEARCH_BODY, key=key) - assert (served.status_code, served.json()) == (200, {"object": "search", "results": []}), served.text + assert (served.status_code, served.json()) == ( + 200, + {"object": "search", "results": [], "provider_metadata": {}}, + ), served.text assert [(request.method, request.target) for request in wire.drain()] == [("POST", "/allowed/search")] diff --git a/tests/integration/compatibility/test_audio_transcriptions_wire.py b/tests/integration/compatibility/test_audio_transcriptions_wire.py index 8f9a83e9912..3deeaebaf7d 100644 --- a/tests/integration/compatibility/test_audio_transcriptions_wire.py +++ b/tests/integration/compatibility/test_audio_transcriptions_wire.py @@ -660,10 +660,6 @@ def test_audio_transcription_preserves_the_client_file_content_type(gateway: Gat def test_audio_transcription_bills_audio_tokens_at_the_input_rate_when_no_audio_rate_is_set( gateway: Gateway, ) -> None: - pytest.skip( - "BUG: with only input_cost_per_token set, transcription audio tokens are billed at 0, so " - "x-litellm-response-cost is 1e-05 instead of 2e-05 for 10 audio, 2 text and 4 output tokens" - ) wav: Final = _WAV_BYTES + uuid.uuid4().bytes def respond(request: Request) -> Reply: diff --git a/tests/integration/cost_calculation/cases/anthropic.py b/tests/integration/cost_calculation/cases/anthropic.py index 5ad4afa9530..776c5b51dd4 100644 --- a/tests/integration/cost_calculation/cases/anthropic.py +++ b/tests/integration/cost_calculation/cases/anthropic.py @@ -4478,6 +4478,7 @@ CLAUDE_SONNET_5_5_MESSAGES_INPUT_TEXT: Final = CostTrackingTestCase( "output_tokens_details": {"thinking_tokens": 0}, "service_tier": "standard", "inference_geo": "global", + "speed": "standard", }, "diagnostics": None, }, @@ -4502,7 +4503,7 @@ CLAUDE_SONNET_5_5_MESSAGES_STREAM: Final = CostTrackingTestCase( response=SseResponse( content_type="text/event-stream", frames=( - 'event: message_start\ndata: {"type":"message_start","message":{"model":"claude-sonnet-5-5","id":"msg_$REQUEST_ID","type":"message","role":"assistant","content":[],"container":null,"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1840,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"global"},"diagnostics":null}}', + 'event: message_start\ndata: {"type":"message_start","message":{"model":"claude-sonnet-5-5","id":"msg_$REQUEST_ID","type":"message","role":"assistant","content":[],"container":null,"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1840,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"global","speed":"standard"},"diagnostics":null}}', 'event: content_block_start\ndata: {"type":"content_block_start","index":0,"content_block":{"type":"thinking","thinking":"","signature":""}}', 'event: ping\ndata: {"type":"ping"}', 'event: content_block_delta\ndata: {"type":"content_block_delta","index":0,"delta":{"type":"thinking_delta","thinking":""}}', @@ -4877,6 +4878,7 @@ CLAUDE_HAIKU_5_5_MESSAGES_INPUT_TEXT: Final = CostTrackingTestCase( "output_tokens_details": {"thinking_tokens": 0}, "service_tier": "standard", "inference_geo": "global", + "speed": "standard", }, "diagnostics": None, }, @@ -4901,7 +4903,7 @@ CLAUDE_HAIKU_5_5_MESSAGES_STREAM: Final = CostTrackingTestCase( response=SseResponse( content_type="text/event-stream", frames=( - 'event: message_start\ndata: {"type":"message_start","message":{"model":"claude-haiku-5-5","id":"msg_$REQUEST_ID","type":"message","role":"assistant","content":[],"container":null,"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1840,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"global"},"diagnostics":null}}', + 'event: message_start\ndata: {"type":"message_start","message":{"model":"claude-haiku-5-5","id":"msg_$REQUEST_ID","type":"message","role":"assistant","content":[],"container":null,"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1840,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"global","speed":"standard"},"diagnostics":null}}', 'event: content_block_start\ndata: {"type":"content_block_start","index":0,"content_block":{"type":"thinking","thinking":"","signature":""}}', 'event: ping\ndata: {"type":"ping"}', 'event: content_block_delta\ndata: {"type":"content_block_delta","index":0,"delta":{"type":"thinking_delta","thinking":""}}', @@ -5639,6 +5641,7 @@ CLAUDE_FABLE_5_1_MESSAGES_INPUT_TEXT: Final = CostTrackingTestCase( "output_tokens_details": {"thinking_tokens": 0}, "service_tier": "standard", "inference_geo": "global", + "speed": "standard", }, "diagnostics": None, }, @@ -5663,7 +5666,7 @@ CLAUDE_FABLE_5_1_MESSAGES_STREAM: Final = CostTrackingTestCase( response=SseResponse( content_type="text/event-stream", frames=( - 'event: message_start\ndata: {"type":"message_start","message":{"model":"claude-fable-5-1","id":"msg_$REQUEST_ID","type":"message","role":"assistant","content":[],"container":null,"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1840,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"global"},"diagnostics":null}}', + 'event: message_start\ndata: {"type":"message_start","message":{"model":"claude-fable-5-1","id":"msg_$REQUEST_ID","type":"message","role":"assistant","content":[],"container":null,"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1840,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"global","speed":"standard"},"diagnostics":null}}', 'event: content_block_start\ndata: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""}}', 'event: ping\ndata: {"type":"ping"}', 'event: content_block_delta\ndata: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"scripted "}}', @@ -5974,6 +5977,7 @@ CLAUDE_OPUS_5_5_MESSAGES_INPUT_TEXT: Final = CostTrackingTestCase( "output_tokens_details": {"thinking_tokens": 0}, "service_tier": "standard", "inference_geo": "global", + "speed": "standard", }, "diagnostics": None, }, @@ -5998,7 +6002,7 @@ CLAUDE_OPUS_5_5_MESSAGES_STREAM: Final = CostTrackingTestCase( response=SseResponse( content_type="text/event-stream", frames=( - 'event: message_start\ndata: {"type":"message_start","message":{"model":"claude-opus-5-5","id":"msg_$REQUEST_ID","type":"message","role":"assistant","content":[],"container":null,"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1840,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"global"},"diagnostics":null}}', + 'event: message_start\ndata: {"type":"message_start","message":{"model":"claude-opus-5-5","id":"msg_$REQUEST_ID","type":"message","role":"assistant","content":[],"container":null,"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1840,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"global","speed":"standard"},"diagnostics":null}}', 'event: content_block_start\ndata: {"type":"content_block_start","index":0,"content_block":{"type":"thinking","thinking":"","signature":""}}', 'event: ping\ndata: {"type":"ping"}', 'event: content_block_delta\ndata: {"type":"content_block_delta","index":0,"delta":{"type":"thinking_delta","thinking":""}}', diff --git a/tests/integration/cost_calculation/cases/gemini.py b/tests/integration/cost_calculation/cases/gemini.py index 8a50e91ec01..86a0d3b9067 100644 --- a/tests/integration/cost_calculation/cases/gemini.py +++ b/tests/integration/cost_calculation/cases/gemini.py @@ -2658,7 +2658,7 @@ GEMINI_GEMINI_3_8_FLASH_STREAM_FULL_USAGE: Final = CostTrackingTestCase( ), ), expected=ExactExpected( - spend=0.0076232, input_cost=0.0015572, output_cost=0.006066, prompt_tokens=8314, completion_tokens=1592 + spend=0.0066182, input_cost=0.0013922, output_cost=0.005226, prompt_tokens=8314, completion_tokens=1592 ), ) diff --git a/tests/integration/cost_calculation/cases/vertex_ai.py b/tests/integration/cost_calculation/cases/vertex_ai.py index 305c10535b7..2fb005dbeca 100644 --- a/tests/integration/cost_calculation/cases/vertex_ai.py +++ b/tests/integration/cost_calculation/cases/vertex_ai.py @@ -2846,7 +2846,7 @@ GEMINI_3_8_FLASH_STREAM_FULL_USAGE: Final = CostTrackingTestCase( ), ), expected=ExactExpected( - spend=0.005775328, input_cost=0.001276288, output_cost=0.00449904, prompt_tokens=8314, completion_tokens=1592 + spend=0.005946928, input_cost=0.001447888, output_cost=0.00449904, prompt_tokens=8314, completion_tokens=1592 ), ) diff --git a/tests/integration/cost_calculation/catalog.py b/tests/integration/cost_calculation/catalog.py index 568a89ad967..2c1d9d9e22c 100644 --- a/tests/integration/cost_calculation/catalog.py +++ b/tests/integration/cost_calculation/catalog.py @@ -65,6 +65,7 @@ BRIDGE_COST_PARITY_CASES: Final[tuple[BridgeCostParityTestCase, ...]] = ( *anthropic.BRIDGE_COST_PARITY, *gemini.BRIDGE_COST_PARITY, *vertex_ai.BRIDGE_COST_PARITY, + *misc.BRIDGE_COST_PARITY, ) _PARITY_LEGS: Final = frozenset(leg.name for pair in PARITY_CASES for leg in (pair.plain, pair.streamed)) | frozenset( leg.name for pair in BRIDGE_COST_PARITY_CASES for leg in (pair.native, pair.bridged) diff --git a/tests/integration/cost_calculation/cost_map.py b/tests/integration/cost_calculation/cost_map.py index ba7be7647da..012d847e676 100644 --- a/tests/integration/cost_calculation/cost_map.py +++ b/tests/integration/cost_calculation/cost_map.py @@ -597,6 +597,7 @@ COST_MAP_ENTRIES: Final[dict[str, dict[str, JsonValue]]] = { "cache_read_input_token_cost_priority": 2.16e-07, "google_maps_grounding_cost_per_query": 0.0168, "input_cost_per_audio_token": 2.4e-06, + "input_cost_per_audio_token_priority": 4.32e-06, "input_cost_per_token": 2.4e-06, "input_cost_per_token_flex": 1.2e-06, "input_cost_per_token_priority": 4.32e-06, diff --git a/tests/integration/cost_calculation/cost_tracking_case.py b/tests/integration/cost_calculation/cost_tracking_case.py index 3efa97407f7..e98f6a44222 100644 --- a/tests/integration/cost_calculation/cost_tracking_case.py +++ b/tests/integration/cost_calculation/cost_tracking_case.py @@ -94,6 +94,7 @@ class CostMapEntry(BaseModel): tiered_pricing: tuple[TieredPrice, ...] | None = None output_cost_per_reasoning_token: float | None = None input_cost_per_audio_token: float | None = None + input_cost_per_audio_token_priority: float | None = None input_cost_per_second: float | None = None output_cost_per_second: float | None = None input_cost_per_character: float | None = None diff --git a/tests/integration/database/test_cleanup_transactions.py b/tests/integration/database/test_cleanup_transactions.py index 925fbaf6f01..72da2bb48ee 100644 --- a/tests/integration/database/test_cleanup_transactions.py +++ b/tests/integration/database/test_cleanup_transactions.py @@ -105,3 +105,166 @@ async def test_delete_batch_survives_witnessed_lock_past_transaction_default(cap await database.disconnect() finally: setup.execute(sql.SQL("DROP SCHEMA {} CASCADE").format(sql.Identifier(schema))) + + +async def test_size_rule_deletes_the_oldest_rows_until_under_the_target_and_does_not_refire_after_vacuum( + caplog: pytest.LogCaptureFixture, +) -> None: + """ + Deleting rows never shrinks the table file, so the size pass must stop on live bytes, not on + pg_total_relation_size, taking the oldest rows first and keeping the tool index on the same cutoff. Once + autovacuum has turned the deleted rows into free space the catalog no longer shows them as dead, and the + files still measure the same; the next check must read what the last run freed from its saved count and + leave the table alone instead of calling the whole file live again. + """ + caplog.set_level(logging.INFO, logger="LiteLLM Proxy") + schema: Final = f"integration_{uuid.uuid4().hex}" + url: Final = os.environ["DATABASE_URL"] + parsed: Final = urlsplit(url) + scoped_url: Final = urlunsplit( + parsed._replace(query=urlencode({**dict(parse_qsl(parsed.query)), "schema": schema})) + ) + logs: Final = sql.Identifier(schema, "LiteLLM_SpendLogs") + index: Final = sql.Identifier(schema, "LiteLLM_SpendLogToolIndex") + config: Final = sql.Identifier(schema, "LiteLLM_Config") + seeded: Final = 6000 + now: Final = datetime.now(timezone.utc).replace(tzinfo=None) + stats_sql: Final = ( + "SELECT sum(n_live_tup)::int AS live, sum(n_dead_tup)::int AS dead, sum(n_tup_ins)::int AS inserted " + "FROM pg_stat_user_tables " + "WHERE schemaname = %s AND relname IN ('LiteLLM_SpendLogs', 'LiteLLM_SpendLogToolIndex')" + ) + with psycopg.connect(url, autocommit=True) as setup: + setup.execute(sql.SQL("CREATE SCHEMA {}").format(sql.Identifier(schema))) + try: + setup.execute( + sql.SQL( + 'CREATE TABLE {} (request_id text, "startTime" timestamp NOT NULL, payload text, ' + 'PRIMARY KEY (request_id, "startTime"))' + ).format(logs) + ) + setup.execute( + sql.SQL( + "CREATE TABLE {} (request_id text, tool_name text, start_time timestamp NOT NULL, " + "PRIMARY KEY (request_id, tool_name))" + ).format(index) + ) + setup.execute(sql.SQL("CREATE TABLE {} (param_name text PRIMARY KEY, param_value jsonb)").format(config)) + setup.execute( + sql.SQL( + "INSERT INTO {} SELECT 'req-' || lpad(i::text, 6, '0'), %s - (%s - i) * interval '1 minute', " + "repeat('x', 1000) FROM generate_series(1, %s) AS i" + ).format(logs), + (now, seeded, seeded), + ) + setup.execute( + sql.SQL( + "INSERT INTO {} SELECT request_id, 'tool', \"startTime\" FROM {} WHERE right(request_id, 1) = '0'" + ).format(index, logs) + ) + index_rows: Final = seeded // 10 + inserts_deadline: Final = time.monotonic() + 10 + while True: + # a backend only ships its pending row counters when it runs another command, so give the + # seeding connection one; the size rule rolls its count forward from n_tup_ins, which must + # show the seed inserts before ANALYZE sets the live estimate or the two add up to double + setup.execute("SELECT 1") + (inserts,) = read_rows(stats_sql, (schema,)) + if inserts["inserted"] == seeded + index_rows: + break + assert time.monotonic() < inserts_deadline, f"row statistics never saw the seed inserts: {inserts}" + await asyncio.sleep(0.1) + setup.execute(sql.SQL("ANALYZE {}").format(logs)) + setup.execute(sql.SQL("ANALYZE {}").format(index)) + stats_deadline: Final = time.monotonic() + 10 + while True: + setup.execute("SELECT 1") + (stats,) = read_rows(stats_sql, (schema,)) + if stats["live"] == seeded + index_rows: + break + assert time.monotonic() < stats_deadline, f"row statistics never caught up with ANALYZE: {stats}" + await asyncio.sleep(0.1) + (allocated,) = read_rows( + "SELECT (pg_total_relation_size(%s::regclass) + pg_total_relation_size(%s::regclass))::bigint " + "AS allocated", + (logs.as_string(setup), index.as_string(setup)), + ) + allocated_before: Final = int(str(allocated["allocated"])) + assert allocated_before > 0 + + cleanup: Final = SpendLogCleanup( + general_settings={ + # trigger below what is there, clean down to half of it + "maximum_spend_logs_size": str(allocated_before * 3 // 4), + "maximum_spend_logs_cleanup_target_size": str(allocated_before // 2), + "maximum_spend_logs_cleanup_batch_size": 100, + } + ) + cleanup.pod_lock_manager = None + + async def size_check() -> None: + database: Final = Prisma(datasource={"url": scoped_url}) + await database.connect() + try: + await cleanup.cleanup_spend_logs_by_size(PartitionConnection(database)) + finally: + await database.disconnect() + + await size_check() + + remaining: Final = read_rows( + f'SELECT request_id FROM {logs.as_string(setup)} ORDER BY "startTime"', + (), + ) + # half the bytes is half the rows: the oldest 3000 spend logs and their 300 index rows go, counted + # from the deletes themselves, so the stats collector's lag cannot make the run overshoot. A page the + # files grew by between this measurement and the run's probe costs at most one more batch + assert 2900 <= len(remaining) <= 3000, f"{len(remaining)} spend logs remain, expected 3000 less one batch" + assert remaining[0]["request_id"] == f"req-{seeded - len(remaining) + 1:06d}" + assert remaining[-1]["request_id"] == f"req-{seeded:06d}" + (orphans,) = read_rows( + f"SELECT count(*)::int AS n FROM {index.as_string(setup)} i " + f"WHERE NOT EXISTS (SELECT 1 FROM {logs.as_string(setup)} l WHERE l.request_id = i.request_id)", + (), + ) + assert orphans["n"] == 0 + (kept_index,) = read_rows(f"SELECT count(*)::int AS n FROM {index.as_string(setup)}", ()) + assert kept_index["n"] == len(remaining) // 10 + summary: Final = next( + record.getMessage() + for record in caplog.records + if "Spend log cleanup run finished" in record.getMessage() + ) + assert "target_reached=true" in summary + assert f"allocated_before={allocated_before}" in summary + # the file did not shrink: that is the whole reason the reclaimable count exists + assert f"allocated_after={allocated_before}" in summary + assert "VACUUM FULL or pg_repack" in summary + + deletes_deadline: Final = time.monotonic() + 10 + while True: + (after_deletes,) = read_rows(stats_sql, (schema,)) + if after_deletes["dead"] == 3300: + break + assert time.monotonic() < deletes_deadline, f"row statistics never saw the deletes: {after_deletes}" + await asyncio.sleep(0.1) + setup.execute(sql.SQL("VACUUM (ANALYZE) {}").format(logs)) + setup.execute(sql.SQL("VACUUM (ANALYZE) {}").format(index)) + vacuum_deadline: Final = time.monotonic() + 10 + while True: + (after_vacuum,) = read_rows(stats_sql, (schema,)) + if after_vacuum["dead"] == 0: + break + assert time.monotonic() < vacuum_deadline, f"row statistics never caught up with VACUUM: {after_vacuum}" + await asyncio.sleep(0.1) + caplog.clear() + + await size_check() + + (still_there,) = read_rows(f"SELECT count(*)::int AS n FROM {logs.as_string(setup)}", ()) + assert still_there["n"] == len(remaining), ( + "the second check deleted rows the first one had already brought under the limit" + ) + assert any("is under maximum_spend_logs_size" in record.getMessage() for record in caplog.records) + finally: + setup.execute(sql.SQL("DROP SCHEMA {} CASCADE").format(sql.Identifier(schema))) diff --git a/tests/integration/management/test_search_tool_crud.py b/tests/integration/management/test_search_tool_crud.py index f46da964e14..e97f2727595 100644 --- a/tests/integration/management/test_search_tool_crud.py +++ b/tests/integration/management/test_search_tool_crud.py @@ -113,6 +113,7 @@ def test_search_tool_create_update_delete_is_read_back_and_applied_without_resta "results": [ {"title": target, "url": "https://crud.invalid", "snippet": key, "date": None, "last_updated": None} ], + "provider_metadata": {}, }, response.text read_back(original) diff --git a/tests/integration/management/test_team_delete_large_membership.py b/tests/integration/management/test_team_delete_large_membership.py index 3e4bb568394..e752c835e4f 100644 --- a/tests/integration/management/test_team_delete_large_membership.py +++ b/tests/integration/management/test_team_delete_large_membership.py @@ -727,7 +727,7 @@ def _models_status(proxy: Gateway, key: str) -> int: def _statuses(proxy: Gateway, keys: Sequence[str]) -> dict[int, int]: - with ThreadPoolExecutor(max_workers=16) as pool: + with ThreadPoolExecutor(max_workers=2) as pool: statuses: Final = tuple(pool.map(lambda key: _models_status(proxy, key), keys)) return {status: statuses.count(status) for status in frozenset(statuses)} diff --git a/tests/integration/mcp/test_mcp_transports.py b/tests/integration/mcp/test_mcp_transports.py index 928aa9ff121..ef240cba570 100644 --- a/tests/integration/mcp/test_mcp_transports.py +++ b/tests/integration/mcp/test_mcp_transports.py @@ -2,10 +2,12 @@ import builtins import json import uuid from collections.abc import Mapping +from pathlib import Path from typing import Final import httpx import pytest +import yaml from mcp.shared.exceptions import MCPError from integration._support.client import Gateway from integration._support.database import read_rows @@ -17,15 +19,21 @@ from integration._support.mcp import ( McpCaller, Outcome, PeerKind, + ScriptedTool, _outcome_from_rpc, _parse_rpc_body, + call_tool, + listed_tools, mcp_peer, official_client_outcomes, peer_of, register_mcp, + scripted_peer, + text_result, tool_calls, ) from integration._support.mcp_grants import create_toolset +from integration._support.process import owned_proxy ADD: Final = {"http": "add", "sse": "add", "stdio": "add", "openapi": "getpet"} ARGUMENTS: Final = {"add": {"a": 3, "b": 4}, "getpet": {"petId": "7"}} @@ -817,3 +825,67 @@ def test_sdk_progress_and_cancellation_reach_upstream_without_losing_session( ), ) as gateway: asyncio.run(exercise(gateway)) + + +def test_tool_result_larger_than_one_mib_in_a_single_sse_event_reaches_the_caller(gateway: Gateway) -> None: + payload: Final = "x" * (3 * 1024 * 1024) + tool: Final = ScriptedTool("dump", lambda _: text_result(payload), event_stream=True) + + with scripted_peer(tool) as peer, gateway.scenario() as scenario: + alias: Final = "bigsse" + uuid.uuid4().hex[:8] + identity: Final = register_mcp(scenario, peer, alias) + key: Final = scenario.key(object_permission={"mcp_servers": [identity]}) + name: Final = next(full for full in listed_tools(gateway, key, identity) if full.endswith("dump")) + response: Final = call_tool(gateway, key, identity, name, {}) + assert response.status_code == 200, response.text[:500] + body: Final = response.json() + assert body["isError"] is False, response.text[:500] + assert body["content"][0]["text"] == payload + + +def test_configured_sse_limit_rejects_large_results_and_allows_the_next_call(tmp_path: Path) -> None: + limit: Final = 4096 + payload: Final = "x" * 512 + small: Final = ScriptedTool("small", lambda _: text_result(payload), event_stream=True) + large: Final = ScriptedTool("large", lambda _: text_result("x" * (2 * limit)), event_stream=True) + key: Final = "sk-local-mcp-sse-limit-regression-key" + with scripted_peer(small, large) as peer, httpx.Client() as client: + config: Final = tmp_path / "sse-limit.yaml" + config.write_text( + yaml.safe_dump( + { + "general_settings": {"master_key": key, "store_model_in_db": False}, + "mcp_servers": {"limited": peer.registration()}, + } + ) + ) + seed: Final = Gateway(client, key, peer.url) + with owned_proxy( + seed, + tmp_path / "proxy", + { + "STORE_MODEL_IN_DB": "False", + "DISABLE_SCHEMA_UPDATE": "true", + "LITELLM_LOCAL_MODEL_COST_MAP": "True", + "LITELLM_MCP_MAX_SSE_EVENT_SIZE_BYTES": str(limit), + }, + config=config, + database_setup=(), + remove_environment=( + "DATABASE_URL", + "DATABASE_URL_READ_REPLICA", + "DIRECT_URL", + "INTEGRATION_PROXY_DATABASE_URL", + "INTEGRATION_PROXY_READ_REPLICA_URL", + ), + ) as gateway: + assert set(listed_tools(gateway, key)) == {"small", "large"} + for name in ("small", "large", "small"): + response: Final = call_tool(gateway, key, "limited", name, {}) + assert response.status_code == 200, response.text[:500] + body: Final = response.json() + assert body["isError"] is (name == "large"), response.text[:500] + if name == "large": + assert str(limit) in body["content"][0]["text"], response.text[:500] + else: + assert body["content"][0]["text"] == payload, response.text[:500] diff --git a/tests/integration/messages_endpoint/providers/bedrock/test_bedrock_invoke_guardrail_long_tool_names_wire.py b/tests/integration/messages_endpoint/providers/bedrock/test_bedrock_invoke_guardrail_long_tool_names_wire.py new file mode 100644 index 00000000000..b94f201b556 --- /dev/null +++ b/tests/integration/messages_endpoint/providers/bedrock/test_bedrock_invoke_guardrail_long_tool_names_wire.py @@ -0,0 +1,312 @@ +import base64 +import json +from collections.abc import Iterator, Mapping +from dataclasses import dataclass +from pathlib import Path +from typing import Final + +import pytest +import yaml +from integration._support.client import Gateway, gateway_from_environment, object_value +from integration._support.ports import allocate_port +from integration._support.process import graceful_stop_seconds, owned_proxy +from integration._support.upstream import _aws_event_frame +from integration._support.wire import Reply, Request, Wire, wire_server +from pydantic import JsonValue, TypeAdapter + +pytestmark: Final = pytest.mark.timeout(4 * graceful_stop_seconds() + 240) + +_JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue]) +_TOKEN: Final = "synthetic-bedrock-bearer" +_GUARDRAIL: Final = "headroom-compression" +_SONNET: Final = "claude-sonnet-5-5" +_OPUS: Final = "claude-opus-5" +_SEARCH: Final = "ToolSearch" +_NAME_SOURCE: Final = "mcp__plugin_support-kit_remote-workspace__getAccessibleWorkspaceResourcesForTheCurrentUser" +_REPLY_TEXT: Final = "done" +_FORCED_ID: Final = "toolu_forced" + + +def _tool_name(length: int) -> str: + name: Final = _NAME_SOURCE[:length] + assert len(name) == length, name + return name + + +def _tool(name: str, **fields: JsonValue) -> dict[str, JsonValue]: + return {"name": name, "description": "Returns OK", "input_schema": {"type": "object", "properties": {}}, **fields} + + +def _blocks(message: JsonValue) -> tuple[Mapping[str, JsonValue], ...]: + content: Final = object_value(message).get("content") + return tuple(object_value(block) for block in content) if isinstance(content, list) else () + + +def _parts(block: Mapping[str, JsonValue]) -> tuple[Mapping[str, JsonValue], ...]: + content: Final = block.get("content") + return tuple(object_value(part) for part in content) if isinstance(content, list) else () + + +def _tool_results(blocks: tuple[Mapping[str, JsonValue], ...]) -> tuple[Mapping[str, JsonValue], ...]: + return tuple(block for block in blocks if block.get("type") == "tool_result") + + +def _message_blocks(body: Mapping[str, JsonValue]) -> tuple[Mapping[str, JsonValue], ...]: + messages: Final = body.get("messages") + assert isinstance(messages, list), body + return tuple(block for message in messages for block in _blocks(message)) + + +def _tool_references(body: Mapping[str, JsonValue]) -> tuple[str, ...]: + parts: Final = tuple(part for block in _tool_results(_message_blocks(body)) for part in _parts(block)) + return tuple(str(part["tool_name"]) for part in parts if part.get("type") == "tool_reference") + + +def _referenced_names(body: Mapping[str, JsonValue]) -> tuple[str, ...]: + used: Final = tuple(str(block["name"]) for block in _message_blocks(body) if block.get("type") == "tool_use") + return (*used, *_tool_references(body)) + + +def _tool_names(body: Mapping[str, JsonValue]) -> tuple[str, ...]: + tools: Final = body.get("tools") + assert isinstance(tools, list), body + return tuple(str(object_value(tool)["name"]) for tool in tools) + + +def _forced_name(body: Mapping[str, JsonValue]) -> str | None: + choice: Final = body.get("tool_choice") + if not isinstance(choice, dict) or choice.get("type") != "tool": + return None + return str(choice["name"]) + + +def _bedrock_error(message: str) -> Reply: + return Reply(status=400, body=json.dumps({"message": message}).encode()) + + +def _stop_reason(forced: str | None) -> str: + return "end_turn" if forced is None else "tool_use" + + +def _content(forced: str | None) -> list[JsonValue]: + if forced is None: + return [{"type": "text", "text": _REPLY_TEXT}] + return [{"type": "tool_use", "id": _FORCED_ID, "name": forced, "input": {}}] + + +def _message(model: str, forced: str | None) -> dict[str, JsonValue]: + return { + "id": "msg_long_tool_names", + "type": "message", + "role": "assistant", + "model": model, + "content": _content(forced), + "stop_reason": _stop_reason(forced), + "stop_sequence": None, + "usage": {"input_tokens": 11, "output_tokens": 3}, + } + + +def _invoke_chunk(event: Mapping[str, JsonValue]) -> bytes: + payload: Final = {"bytes": base64.b64encode(json.dumps(event).encode()).decode()} + return _aws_event_frame("chunk", payload, "sc", "u") + + +def _block_events(forced: str | None) -> tuple[Mapping[str, JsonValue], ...]: + if forced is None: + return ( + {"type": "content_block_start", "index": 0, "content_block": {"type": "text", "text": ""}}, + {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": _REPLY_TEXT}}, + ) + tool_use: Final = {"type": "tool_use", "id": _FORCED_ID, "name": forced, "input": {}} + return ( + {"type": "content_block_start", "index": 0, "content_block": tool_use}, + {"type": "content_block_delta", "index": 0, "delta": {"type": "input_json_delta", "partial_json": "{}"}}, + ) + + +def _stream(model: str, forced: str | None) -> Reply: + start: Final = {**_message(model, forced), "content": [], "stop_reason": None} + events: Final = ( + {"type": "message_start", "message": start}, + *_block_events(forced), + {"type": "content_block_stop", "index": 0}, + {"type": "message_delta", "delta": {"stop_reason": _stop_reason(forced)}, "usage": {"output_tokens": 3}}, + {"type": "message_stop"}, + ) + frames: Final = tuple(_invoke_chunk(event) for event in events) + return Reply(chunks=frames, content_type="application/vnd.amazon.eventstream") + + +def _bedrock(request: Request) -> Reply: + body: Final = _JSON_OBJECT.validate_json(request.body) + available: Final = frozenset(_tool_names(body)) + missing: Final = [name for name in _tool_references(body) if name not in available] + if missing: + return _bedrock_error(f"Tool reference '{missing[0]}' not found in available tools") + forced: Final = _forced_name(body) + if forced is not None and forced not in available: + return _bedrock_error(f"Tool '{forced}' not found in provided tools") + model: Final = request.target.split("/")[2] + if request.target.endswith("/invoke-with-response-stream"): + return _stream(model, forced) + return Reply(body=json.dumps(_message(model, forced)).encode()) + + +def _compress(request: Request) -> Reply: + assert request.target == "/v1/compress", request.target + messages: Final = _JSON_OBJECT.validate_json(request.body)["messages"] + reply: Final = {"messages": messages, "tokens_before": 40, "tokens_after": 32, "compression_ratio": 0.8} + return Reply(body=json.dumps(reply).encode()) + + +def _deployments(provider_url: str) -> list[JsonValue]: + shared: Final = {"aws_region_name": "eu-central-1", "api_base": provider_url, "api_key": _TOKEN, "guardrails": []} + return [ + { + "model_name": _SONNET, + "litellm_params": { + "model": "global.anthropic.claude-sonnet-5-5", + "custom_llm_provider": "bedrock", + **shared, + }, + }, + {"model_name": _OPUS, "litellm_params": {"model": "bedrock/eu.anthropic.claude-opus-5", **shared}}, + ] + + +def _config(directory: Path, provider_url: str, headroom_url: str) -> Path: + stock: Final = _JSON_OBJECT.validate_python(yaml.safe_load(Path("tests/integration/proxy_config.yaml").read_text())) + guardrail: Final = { + "guardrail": "headroom", + "mode": "pre_call", + "default_on": True, + "api_base": headroom_url, + "unreachable_fallback": "fail_open", + } + config: Final[dict[str, JsonValue]] = { + **stock, + "model_list": _deployments(provider_url), + "router_settings": {**object_value(stock["router_settings"]), "num_retries": 0}, + "guardrails": [{"guardrail_name": _GUARDRAIL, "litellm_params": guardrail}], + } + path: Final = directory / "long-tool-names.yaml" + path.write_text(yaml.safe_dump(config)) + return path + + +@dataclass(frozen=True, slots=True) +class _Rig: + gateway: Gateway + provider: Wire + compressor: Wire | None + + +@pytest.fixture(scope="module", params=("fail_open", "compressed")) +def rig(request: pytest.FixtureRequest, tmp_path_factory: pytest.TempPathFactory) -> Iterator[_Rig]: + directory: Final = tmp_path_factory.mktemp(f"long-tool-names-{request.param}") + with wire_server(_bedrock) as provider, wire_server(_compress) as compressor, gateway_from_environment() as gateway: + reachable: Final = request.param == "compressed" + headroom_url: Final = compressor.url if reachable else f"http://127.0.0.1:{allocate_port()}" + config: Final = _config(directory, provider.url, headroom_url) + with owned_proxy(gateway, directory, {}, config=config, workers=2) as owned: + yield _Rig(owned, provider, compressor if reachable else None) + + +def _search_turns(name: str) -> list[JsonValue]: + return [ + {"role": "user", "content": "find the tool"}, + { + "role": "assistant", + "content": [{"type": "tool_use", "id": "toolu_01", "name": _SEARCH, "input": {"query": "x"}}], + }, + { + "role": "user", + "content": [ + { + "type": "tool_result", + "tool_use_id": "toolu_01", + "content": [{"type": "tool_reference", "tool_name": name}], + } + ], + }, + {"role": "assistant", "content": "Found it."}, + {"role": "user", "content": "say done"}, + ] + + +def _history_turns(name: str) -> list[JsonValue]: + return [ + {"role": "user", "content": "use the tool"}, + {"role": "assistant", "content": [{"type": "tool_use", "id": "toolu_02", "name": name, "input": {}}]}, + { + "role": "user", + "content": [ + {"type": "tool_result", "tool_use_id": "toolu_02", "content": "OK"}, + {"type": "text", "text": "say done"}, + ], + }, + ] + + +def _forced_turns() -> list[JsonValue]: + return [ + {"role": "user", "content": "hello"}, + {"role": "assistant", "content": "hi"}, + {"role": "user", "content": "call the tool"}, + ] + + +def _body(shape: str, model: str, name: str, stream: bool) -> dict[str, JsonValue]: + tools: Final = [_tool(_SEARCH), _tool(name, defer_loading=True)] if shape == "tool_reference" else [_tool(name)] + body: Final[dict[str, JsonValue]] = {"model": model, "max_tokens": 20, "stream": stream, "tools": tools} + match shape: + case "tool_reference": + return {**body, "messages": _search_turns(name)} + case "tool_use_history": + return {**body, "messages": _history_turns(name)} + case _: + return {**body, "messages": _forced_turns(), "tool_choice": {"type": "tool", "name": name}} + + +def _sse_tool_names(text: str) -> tuple[str, ...]: + events: Final = tuple( + _JSON_OBJECT.validate_json(line.removeprefix("data: ")) + for line in text.splitlines() + if line.startswith("data: ") + ) + starts: Final = tuple( + object_value(event["content_block"]) for event in events if event.get("type") == "content_block_start" + ) + return tuple(str(block["name"]) for block in starts if block.get("type") == "tool_use") + + +def _answered_tool_names(text: str, stream: bool) -> tuple[str, ...]: + if stream: + return _sse_tool_names(text) + content: Final = _JSON_OBJECT.validate_json(text)["content"] + assert isinstance(content, list), text + return tuple(str(block["name"]) for block in map(object_value, content) if block.get("type") == "tool_use") + + +@pytest.mark.parametrize("stream", (False, True), ids=("json", "sse")) +@pytest.mark.parametrize("length", (64, 65, 90)) +@pytest.mark.parametrize("shape", ("tool_reference", "tool_choice", "tool_use_history")) +def test_guarded_messages_keep_long_tool_names_the_caller_sent( + rig: _Rig, shape: str, length: int, stream: bool +) -> None: + name: Final = _tool_name(length) + body: Final = _body(shape, _OPUS if shape == "tool_choice" else _SONNET, name, stream) + response: Final = rig.gateway.request("POST", "/v1/messages", body, headers={"anthropic-version": "2023-06-01"}) + sent: Final = rig.provider.drain() + compressed: Final = None if rig.compressor is None else rig.compressor.drain() + + assert _GUARDRAIL in response.headers.get("x-litellm-applied-guardrails", ""), dict(response.headers) + assert compressed is None or len(compressed) == 1, compressed + assert response.status_code == 200, response.text + assert len(sent) == 1, sent + outbound: Final = _JSON_OBJECT.validate_json(sent[0].body) + assert _tool_names(outbound) == ((_SEARCH, name) if shape == "tool_reference" else (name,)), outbound + assert _referenced_names(outbound) == _referenced_names(body), outbound + expected_calls: Final = (name,) if shape == "tool_choice" else () + assert _answered_tool_names(response.text, stream) == expected_calls, response.text diff --git a/tests/integration/messages_endpoint/test_guardrail_long_tool_names_wire.py b/tests/integration/messages_endpoint/test_guardrail_long_tool_names_wire.py new file mode 100644 index 00000000000..8842e04db6b --- /dev/null +++ b/tests/integration/messages_endpoint/test_guardrail_long_tool_names_wire.py @@ -0,0 +1,585 @@ +import asyncio +import json +import uuid +from collections.abc import Mapping +from concurrent.futures import ThreadPoolExecutor +from typing import Final + +import anthropic +import httpx +import pytest +from integration._support.anthropic_sse import sse +from integration._support.client import Gateway, Scenario, eventually, object_value, string_value +from integration._support.ports import allocate_port +from integration._support.wire import Reply, Request, Wire, wire_server +from pydantic import JsonValue, TypeAdapter + +from litellm.llms.anthropic.pass_through.adapters.transformation import truncate_tool_name + +_JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue]) +_JSON_OBJECTS: Final = TypeAdapter(list[dict[str, JsonValue]]) +_NAME_SOURCE: Final = ( + "mcp__plugin_support-kit_remote-workspace__getAccessibleWorkspaceResourcesForTheCurrentUser" + "_including_archived_and_shared_workspaces_across_every_region_and_every_tenant_the_user_belongs_to" + "_sorted_by_last_activity_with_owner_and_role_details" +) +_SEARCH: Final = "ToolSearch" +_SHORT_NAME: Final = "workspace_resources" +_EMAIL: Final = "jane.doe@example.com" +_MASK: Final = "" +_FORCED_ID: Final = "toolu_forced" +_GUARDRAIL_NAME_LIMIT: Final = 64 +_BLOCK_REASON: Final = "tool policy says no" + + +def _tool_name(length: int) -> str: + name: Final = _NAME_SOURCE[:length] + assert len(name) == length, name + return name + + +def _tool(name: str) -> dict[str, JsonValue]: + return {"name": name, "description": "Returns OK", "input_schema": {"type": "object", "properties": {}}} + + +def _every_carrier(model: str, name: str, guardrail: str, stream: bool) -> dict[str, JsonValue]: + return { + "model": model, + "max_tokens": 32, + "stream": stream, + "guardrails": [guardrail], + "tools": [_tool(_SEARCH), {**_tool(name), "defer_loading": True}], + "tool_choice": {"type": "tool", "name": name}, + "messages": [ + {"role": "user", "content": "find the workspace tool"}, + {"role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01", "name": _SEARCH, "input": {}}]}, + { + "role": "user", + "content": [ + { + "type": "tool_result", + "tool_use_id": "toolu_01", + "content": [{"type": "tool_reference", "tool_name": name}], + } + ], + }, + {"role": "assistant", "content": [{"type": "tool_use", "id": "toolu_02", "name": name, "input": {}}]}, + { + "role": "user", + "content": [ + {"type": "tool_result", "tool_use_id": "toolu_02", "content": "workspace-alpha"}, + {"type": "text", "text": f"share it with {_EMAIL}"}, + ], + }, + ], + } + + +def _blocks(body: Mapping[str, JsonValue]) -> tuple[Mapping[str, JsonValue], ...]: + messages: Final = _JSON_OBJECTS.validate_python(body["messages"]) + contents: Final = tuple(message["content"] for message in messages if isinstance(message["content"], list)) + return tuple(object_value(block) for content in contents for block in content) + + +def _tool_result_parts(body: Mapping[str, JsonValue]) -> tuple[Mapping[str, JsonValue], ...]: + contents: Final = tuple(block.get("content") for block in _blocks(body) if block.get("type") == "tool_result") + return tuple(object_value(part) for content in contents if isinstance(content, list) for part in content) + + +def _named_tools(body: Mapping[str, JsonValue]) -> tuple[str, ...]: + return tuple(string_value(tool["name"]) for tool in _JSON_OBJECTS.validate_python(body.get("tools") or [])) + + +def _tool_use_names(body: Mapping[str, JsonValue]) -> tuple[str, ...]: + return tuple(string_value(block["name"]) for block in _blocks(body) if block.get("type") == "tool_use") + + +def _tool_references(body: Mapping[str, JsonValue]) -> tuple[str, ...]: + parts: Final = _tool_result_parts(body) + return tuple(string_value(part["tool_name"]) for part in parts if part.get("type") == "tool_reference") + + +def _forced_name(body: Mapping[str, JsonValue]) -> str | None: + choice: Final = body.get("tool_choice") + if not isinstance(choice, dict) or choice.get("type") != "tool": + return None + return string_value(choice["name"]) + + +def _carriers(body: Mapping[str, JsonValue]) -> tuple[tuple[str, ...], str | None, tuple[str, ...], tuple[str, ...]]: + return _named_tools(body), _forced_name(body), _tool_use_names(body), _tool_references(body) + + +def _anthropic_error(message: str) -> Reply: + error: Final = {"type": "error", "error": {"type": "invalid_request_error", "message": message}} + return Reply(status=400, body=json.dumps(error).encode()) + + +def _message(model: str, forced: str | None) -> dict[str, JsonValue]: + content: Final[list[JsonValue]] = ( + [{"type": "text", "text": "done"}] + if forced is None + else [{"type": "tool_use", "id": _FORCED_ID, "name": forced, "input": {}}] + ) + return { + "id": f"msg_{uuid.uuid4().hex}", + "type": "message", + "role": "assistant", + "model": model, + "content": content, + "stop_reason": "end_turn" if forced is None else "tool_use", + "stop_sequence": None, + "usage": {"input_tokens": 11, "output_tokens": 3}, + } + + +def _sse_reply(message: Mapping[str, JsonValue]) -> Reply: + block: Final = object_value(_JSON_OBJECTS.validate_python(message["content"])[0]) + delta: Final[dict[str, JsonValue]] = ( + {"type": "input_json_delta", "partial_json": "{}"} + if block["type"] == "tool_use" + else {"type": "text_delta", "text": string_value(block["text"])} + ) + started: Final = {**block, "input": {}} if block["type"] == "tool_use" else {**block, "text": ""} + events: Final = ( + sse("message_start", {"type": "message_start", "message": {**message, "content": [], "stop_reason": None}}), + sse("content_block_start", {"type": "content_block_start", "index": 0, "content_block": started}), + sse("content_block_delta", {"type": "content_block_delta", "index": 0, "delta": delta}), + sse("content_block_stop", {"type": "content_block_stop", "index": 0}), + sse( + "message_delta", + {"type": "message_delta", "delta": {"stop_reason": message["stop_reason"]}, "usage": {"output_tokens": 3}}, + ), + sse("message_stop", {"type": "message_stop"}), + ) + return Reply(chunks=events, content_type="text/event-stream") + + +def _anthropic_peer(request: Request) -> Reply: + assert request.target.endswith("/v1/messages"), request.target + body: Final = _JSON_OBJECT.validate_json(request.body) + available: Final = frozenset(_named_tools(body)) + missing: Final = [name for name in _tool_references(body) if name not in available] + if missing: + return _anthropic_error(f"Tool reference '{missing[0]}' not found in available tools") + forced: Final = _forced_name(body) + if forced is not None and forced not in available: + return _anthropic_error(f"Tool '{forced}' not found in provided tools") + message: Final = _message(string_value(body["model"]), forced) + return _sse_reply(message) if body.get("stream") is True else Reply(body=json.dumps(message).encode()) + + +def _chat_peer(request: Request) -> Reply: + assert request.target.endswith("/chat/completions"), request.target + body: Final = _JSON_OBJECT.validate_json(request.body) + function: Final = object_value(_JSON_OBJECTS.validate_python(body["tools"])[0]["function"]) + call: Final = {"id": "call_1", "type": "function", "function": {"name": function["name"], "arguments": "{}"}} + reply: Final = { + "id": "chatcmpl-long-tool-names", + "object": "chat.completion", + "created": 1, + "model": body["model"], + "choices": [ + { + "index": 0, + "message": {"role": "assistant", "content": None, "tool_calls": [call]}, + "finish_reason": "tool_calls", + } + ], + "usage": {"prompt_tokens": 11, "completion_tokens": 3, "total_tokens": 14}, + } + return Reply(body=json.dumps(reply).encode()) + + +def _masked(content: JsonValue) -> JsonValue: + if isinstance(content, str): + return content.replace(_EMAIL, _MASK) + if isinstance(content, list): + return [_masked(part) for part in content] + if isinstance(content, dict) and isinstance(text := content.get("text"), str): + return {**content, "text": text.replace(_EMAIL, _MASK)} + return content + + +def _masked_row(row: Mapping[str, JsonValue]) -> dict[str, JsonValue]: + return {**row, "content": _masked(row["content"])} if "content" in row else dict(row) + + +def _guardrail_peer(request: Request) -> Reply: + verdict: Final = request.target.split("/")[1] + rows: Final = _JSON_OBJECTS.validate_python( + _JSON_OBJECT.validate_json(request.body).get("structured_messages") or [] + ) + match verdict: + case "block": + return Reply(body=json.dumps({"action": "BLOCKED", "blocked_reason": _BLOCK_REASON}).encode()) + case "rewrite" if rows: + rewritten: Final = [_masked_row(row) for row in rows] + return Reply(body=json.dumps({"action": "GUARDRAIL_INTERVENED", "structured_messages": rewritten}).encode()) + case _: + return Reply(body=json.dumps({"action": "NONE"}).encode()) + + +def _delete_guardrail(gateway: Gateway, identity: str) -> None: + deleted: Final = gateway.request("DELETE", f"/guardrails/{identity}") + assert deleted.status_code == 200, deleted.text + + +def _guardrail(gateway: Gateway, scenario: Scenario, api_base: str, mode: str, **extra: JsonValue) -> str: + name: Final = f"long-tool-names-{mode}-{uuid.uuid4().hex}" + params: Final[dict[str, JsonValue]] = { + "guardrail": "generic_guardrail_api", + "mode": mode, + "default_on": False, + "api_base": api_base, + "api_key": "synthetic-guardrail-key", + **extra, + } + created: Final = gateway.post("/guardrails", {"guardrail": {"guardrail_name": name, "litellm_params": params}}) + scenario.cleanups.callback(_delete_guardrail, gateway, string_value(created["guardrail_id"])) + return name + + +def _anthropic_model(scenario: Scenario, provider: Wire) -> str: + return scenario.model(model="anthropic/claude-opus-5", api_base=provider.url, api_key="synthetic-anthropic-key") + + +def _sse_tool_use_names(text: str) -> tuple[str, ...]: + events: Final = tuple( + _JSON_OBJECT.validate_json(line.removeprefix("data: ")) + for line in text.splitlines() + if line.startswith("data: ") + ) + starts: Final = tuple( + object_value(event["content_block"]) for event in events if event.get("type") == "content_block_start" + ) + return tuple(string_value(block["name"]) for block in starts if block.get("type") == "tool_use") + + +def _answered_tool_names(response: httpx.Response, stream: bool) -> tuple[str, ...]: + if stream: + return _sse_tool_use_names(response.text) + content: Final = _JSON_OBJECTS.validate_python(_JSON_OBJECT.validate_json(response.content)["content"]) + return tuple(string_value(block["name"]) for block in content if block.get("type") == "tool_use") + + +def _vendor_tool_names(vendor_requests: tuple[Request, ...]) -> tuple[str, ...]: + bodies: Final = tuple(_JSON_OBJECT.validate_json(request.body) for request in vendor_requests) + tools: Final = tuple( + object_value(tool) for body in bodies for tool in _JSON_OBJECTS.validate_python(body.get("tools") or []) + ) + return tuple(string_value(object_value(tool["function"])["name"]) for tool in tools) + + +@pytest.mark.parametrize("stream", (False, True), ids=("json", "sse")) +@pytest.mark.parametrize("length", (64, 65, 128, 200)) +@pytest.mark.parametrize("verdict", ("echo", "rewrite")) +@pytest.mark.parametrize("mode", ("pre_call", "during_call")) +def test_guardrail_forwards_every_tool_name_the_caller_sent( + gateway: Gateway, mode: str, verdict: str, length: int, stream: bool +) -> None: + name: Final = _tool_name(length) + with ( + wire_server(_anthropic_peer) as provider, + wire_server(_guardrail_peer) as vendor, + gateway.scenario() as scenario, + ): + model: Final = _anthropic_model(scenario, provider) + guardrail: Final = _guardrail(gateway, scenario, f"{vendor.url}/{verdict}", mode) + short: Final = gateway.request("POST", "/v1/messages", _every_carrier(model, _SHORT_NAME, guardrail, stream)) + response: Final = gateway.request("POST", "/v1/messages", _every_carrier(model, name, guardrail, stream)) + sent: Final = provider.drain() + screened: Final = vendor.drain() + + assert (short.status_code, response.status_code) == (200, 200), (short.text, response.text) + assert len(sent) == 2, sent + assert len(screened) == 2, screened + outbound: Final = _JSON_OBJECT.validate_json(sent[1].body) + assert _carriers(outbound) == ((_SEARCH, name), name, (_SEARCH, name), (name,)), outbound + assert outbound == _JSON_OBJECT.validate_json(sent[0].body.decode().replace(_SHORT_NAME, name)), outbound + assert _answered_tool_names(response, stream) == (name,), response.text + assert all(len(seen) <= _GUARDRAIL_NAME_LIMIT for seen in _vendor_tool_names(screened)), screened + rewritten: Final = mode == "pre_call" and verdict == "rewrite" + assert (_MASK in sent[1].body.decode(), _EMAIL in sent[1].body.decode()) == (rewritten, not rewritten), outbound + + +@pytest.mark.parametrize("verdict", ("echo", "rewrite")) +def test_short_tool_named_like_a_shortened_history_tool_keeps_its_name(gateway: Gateway, verdict: str) -> None: + history_only: Final = _tool_name(90) + alias: Final = truncate_tool_name(history_only) + with ( + wire_server(_anthropic_peer) as provider, + wire_server(_guardrail_peer) as vendor, + gateway.scenario() as scenario, + ): + body: Final[dict[str, JsonValue]] = { + "model": _anthropic_model(scenario, provider), + "max_tokens": 32, + "guardrails": [_guardrail(gateway, scenario, f"{vendor.url}/{verdict}", "pre_call")], + "tools": [_tool(alias)], + "tool_choice": {"type": "tool", "name": alias}, + "messages": [ + {"role": "user", "content": "list my workspaces"}, + { + "role": "assistant", + "content": [{"type": "tool_use", "id": "toolu_01", "name": history_only, "input": {}}], + }, + { + "role": "user", + "content": [ + {"type": "tool_result", "tool_use_id": "toolu_01", "content": "workspace-alpha"}, + {"type": "text", "text": f"share it with {_EMAIL}"}, + ], + }, + ], + } + response: Final = gateway.request("POST", "/v1/messages", body) + sent: Final = provider.drain() + + assert response.status_code == 200, response.text + assert len(sent) == 1, sent + outbound: Final = _JSON_OBJECT.validate_json(sent[0].body) + assert _carriers(outbound) == ((alias,), alias, (history_only,), ()), outbound + assert _answered_tool_names(response, stream=False) == (alias,), response.text + + +def test_logging_only_guardrail_forwards_the_long_tool_names_untouched(gateway: Gateway) -> None: + name: Final = _tool_name(90) + with ( + wire_server(_anthropic_peer) as provider, + wire_server(_guardrail_peer) as vendor, + gateway.scenario() as scenario, + ): + body: Final = _every_carrier( + _anthropic_model(scenario, provider), + name, + _guardrail(gateway, scenario, f"{vendor.url}/rewrite", "logging_only"), + False, + ) + response: Final = gateway.request("POST", "/v1/messages", body) + sent: Final = provider.drain() + eventually(vendor.received.qsize, lambda count: count >= 1) + screened: Final = vendor.drain() + + assert response.status_code == 200, response.text + assert len(sent) == 1, sent + outbound: Final = _JSON_OBJECT.validate_json(sent[0].body) + assert _carriers(outbound) == ((_SEARCH, name), name, (_SEARCH, name), (name,)), outbound + assert _EMAIL in sent[0].body.decode() and _MASK not in sent[0].body.decode(), outbound + assert _answered_tool_names(response, stream=False) == (name,), response.text + assert all(len(seen) <= _GUARDRAIL_NAME_LIMIT for seen in _vendor_tool_names(screened)), screened + + +@pytest.mark.parametrize("fallback", ("fail_open", "fail_closed")) +def test_unreachable_guardrail_follows_its_fallback_with_long_tool_names(gateway: Gateway, fallback: str) -> None: + name: Final = _tool_name(90) + with wire_server(_anthropic_peer) as provider, gateway.scenario() as scenario: + guardrail: Final = _guardrail( + gateway, scenario, f"http://127.0.0.1:{allocate_port()}", "pre_call", unreachable_fallback=fallback + ) + body: Final = _every_carrier(_anthropic_model(scenario, provider), name, guardrail, False) + response: Final = gateway.request("POST", "/v1/messages", body) + sent: Final = provider.drain() + + if fallback == "fail_closed": + assert (response.status_code, sent) == (500, ()), response.text + return + assert response.status_code == 200, response.text + assert len(sent) == 1, sent + outbound: Final = _JSON_OBJECT.validate_json(sent[0].body) + assert _carriers(outbound) == ((_SEARCH, name), name, (_SEARCH, name), (name,)), outbound + + +def test_blocking_guardrail_stops_a_long_tool_name_request_before_the_provider(gateway: Gateway) -> None: + with ( + wire_server(_anthropic_peer) as provider, + wire_server(_guardrail_peer) as vendor, + gateway.scenario() as scenario, + ): + body: Final = _every_carrier( + _anthropic_model(scenario, provider), + _tool_name(90), + _guardrail(gateway, scenario, f"{vendor.url}/block", "pre_call"), + stream=False, + ) + response: Final = gateway.request("POST", "/v1/messages", body) + sent: Final = provider.drain() + + assert response.status_code == 400, response.text + assert _BLOCK_REASON in response.text, response.text + assert sent == (), sent + + +@pytest.mark.parametrize("length", (64, 90)) +def test_bridged_route_answers_with_the_tool_name_the_caller_sent(gateway: Gateway, length: int) -> None: + name: Final = _tool_name(length) + with ( + wire_server(_chat_peer) as provider, + wire_server(_guardrail_peer) as vendor, + gateway.scenario() as scenario, + ): + model: Final = scenario.model( + model="mistral/mistral-small-latest", api_base=provider.url, api_key="synthetic-mistral-key" + ) + body: Final[dict[str, JsonValue]] = { + "model": model, + "max_tokens": 32, + "guardrails": [_guardrail(gateway, scenario, f"{vendor.url}/echo", "pre_call")], + "tools": [_tool(name)], + "messages": [{"role": "user", "content": "list my workspaces"}], + } + response: Final = gateway.request("POST", "/v1/messages", body) + sent: Final = provider.drain() + + assert response.status_code == 200, response.text + assert len(sent) == 1, sent + assert _answered_tool_names(response, stream=False) == (name,), response.text + + +_PARAMETERS: Final[dict[str, JsonValue]] = {"type": "object", "properties": {}} + + +def _openai_shaped_body(endpoint: str, model: str, name: str, guardrail: str) -> dict[str, JsonValue]: + shared: Final[dict[str, JsonValue]] = {"model": model, "guardrails": [guardrail]} + if endpoint == "/v1/chat/completions": + return { + **shared, + "messages": [{"role": "user", "content": "list my workspaces"}], + "tools": [{"type": "function", "function": {"name": name, "parameters": _PARAMETERS}}], + "tool_choice": {"type": "function", "function": {"name": name}}, + } + return { + **shared, + "input": "list my workspaces", + "tools": [{"type": "function", "name": name, "parameters": _PARAMETERS}], + "tool_choice": {"type": "function", "name": name}, + } + + +def _openai_shaped_tool_calls(endpoint: str, response: httpx.Response) -> tuple[str, ...]: + body: Final = _JSON_OBJECT.validate_json(response.content) + if endpoint == "/v1/chat/completions": + message: Final = object_value(object_value(_JSON_OBJECTS.validate_python(body["choices"])[0])["message"]) + calls: Final = _JSON_OBJECTS.validate_python(message.get("tool_calls") or []) + return tuple(string_value(object_value(call["function"])["name"]) for call in calls) + items: Final = _JSON_OBJECTS.validate_python(body["output"]) + return tuple(string_value(item["name"]) for item in items if item.get("type") == "function_call") + + +@pytest.mark.parametrize("endpoint", ("/v1/chat/completions", "/v1/responses")) +def test_openai_shaped_routes_forward_the_long_tool_name_the_caller_sent(gateway: Gateway, endpoint: str) -> None: + name: Final = _tool_name(90) + with ( + wire_server(_anthropic_peer) as provider, + wire_server(_guardrail_peer) as vendor, + gateway.scenario() as scenario, + ): + body: Final = _openai_shaped_body( + endpoint, + _anthropic_model(scenario, provider), + name, + _guardrail(gateway, scenario, f"{vendor.url}/echo", "pre_call"), + ) + response: Final = gateway.request("POST", endpoint, body) + sent: Final = provider.drain() + + assert response.status_code == 200, response.text + assert len(sent) == 1, sent + assert _carriers(_JSON_OBJECT.validate_json(sent[0].body))[:2] == ((name,), name), sent + assert _openai_shaped_tool_calls(endpoint, response) == (name,), response.text + + +def _forced_tool_kwargs(model: str, name: str, guardrail: str) -> dict[str, object]: + return { + "model": model, + "max_tokens": 32, + "tools": [_tool(name)], + "tool_choice": {"type": "tool", "name": name}, + "messages": [{"role": "user", "content": "list my workspaces"}], + "extra_body": {"guardrails": [guardrail]}, + } + + +def _origin(gateway: Gateway) -> str: + return str(gateway.client.base_url).rstrip("/") + + +def test_sync_anthropic_sdk_gets_the_forced_long_tool_back(gateway: Gateway) -> None: + name: Final = _tool_name(90) + with ( + wire_server(_anthropic_peer) as provider, + wire_server(_guardrail_peer) as vendor, + gateway.scenario() as scenario, + httpx.Client(timeout=30, trust_env=False) as transport, + anthropic.Anthropic( + api_key=gateway.key, base_url=_origin(gateway), max_retries=0, http_client=transport + ) as client, + ): + kwargs: Final = _forced_tool_kwargs( + _anthropic_model(scenario, provider), + name, + _guardrail(gateway, scenario, f"{vendor.url}/echo", "pre_call"), + ) + message: Final = client.messages.create(**kwargs) + sent: Final = provider.drain() + + assert [block.name for block in message.content if block.type == "tool_use"] == [name], message + assert _carriers(_JSON_OBJECT.validate_json(sent[0].body))[:2] == ((name,), name), sent + + +def test_async_anthropic_sdk_streams_the_forced_long_tool_back(gateway: Gateway) -> None: + name: Final = _tool_name(90) + + async def streamed(client: anthropic.AsyncAnthropic, kwargs: dict[str, object]) -> tuple[str, ...]: + async with client.messages.stream(**kwargs) as stream: + final: Final = await stream.get_final_message() + return tuple(block.name for block in final.content if block.type == "tool_use") + + async def run(kwargs: dict[str, object]) -> tuple[str, ...]: + async with ( + httpx.AsyncClient(timeout=30, trust_env=False) as transport, + anthropic.AsyncAnthropic( + api_key=gateway.key, base_url=_origin(gateway), max_retries=0, http_client=transport + ) as client, + ): + return await streamed(client, kwargs) + + with ( + wire_server(_anthropic_peer) as provider, + wire_server(_guardrail_peer) as vendor, + gateway.scenario() as scenario, + ): + kwargs: Final = _forced_tool_kwargs( + _anthropic_model(scenario, provider), + name, + _guardrail(gateway, scenario, f"{vendor.url}/echo", "pre_call"), + ) + answered: Final = asyncio.run(run(kwargs)) + sent: Final = provider.drain() + + assert answered == (name,), answered + assert _carriers(_JSON_OBJECT.validate_json(sent[0].body))[:2] == ((name,), name), sent + + +def test_concurrent_long_tool_name_requests_each_keep_their_own_names(gateway: Gateway) -> None: + names: Final = tuple(f"{_tool_name(85)}_{index:02d}" for index in range(24)) + with ( + wire_server(_anthropic_peer) as provider, + wire_server(_guardrail_peer) as vendor, + gateway.scenario() as scenario, + ): + model: Final = _anthropic_model(scenario, provider) + guardrail: Final = _guardrail(gateway, scenario, f"{vendor.url}/rewrite", "pre_call") + with ThreadPoolExecutor(max_workers=12) as pool: + responses: Final = tuple( + pool.map( + lambda name: gateway.request("POST", "/v1/messages", _every_carrier(model, name, guardrail, False)), + names, + ) + ) + sent: Final = provider.drain() + + assert [response.status_code for response in responses] == [200] * len(names), [r.text for r in responses] + assert [_answered_tool_names(response, stream=False) for response in responses] == [(name,) for name in names] + forwarded: Final = sorted(_carriers(_JSON_OBJECT.validate_json(request.body)) for request in sent) + assert forwarded == sorted(((_SEARCH, name), name, (_SEARCH, name), (name,)) for name in names), forwarded diff --git a/tests/integration/observability/test_arize_otel_v2_openinference_family.py b/tests/integration/observability/test_arize_otel_v2_openinference_family.py index 242b7bfe8c1..f638a7360be 100644 --- a/tests/integration/observability/test_arize_otel_v2_openinference_family.py +++ b/tests/integration/observability/test_arize_otel_v2_openinference_family.py @@ -43,6 +43,7 @@ _GENAI_B3_KEYS_WITHOUT_BAGGAGE: Final = frozenset( "gen_ai.usage.prompt_tokens", "gen_ai.usage.total_tokens", "litellm.api_key.hash", + "litellm.cache_hit", "litellm.call_id", "litellm.call_type", "litellm.cost.discount_amount", @@ -85,6 +86,7 @@ _LANGFUSE_B3_KEYS: Final = frozenset( "gen_ai.usage.output_tokens", "gen_ai.usage.prompt_tokens", "gen_ai.usage.total_tokens", + "langfuse.observation.completion_start_time", "langfuse.observation.cost_details", "langfuse.observation.id", "langfuse.observation.input", @@ -94,6 +96,7 @@ _LANGFUSE_B3_KEYS: Final = frozenset( "langfuse.observation.type", "langfuse.observation.usage_details", "litellm.api_key.hash", + "litellm.cache_hit", "litellm.call_id", "litellm.call_type", "litellm.cost.discount_amount", @@ -296,6 +299,7 @@ def test_arize_otel_v2_b3_non_openinference_callback_family(callback: str, gatew assert _json_object(response.content) == _chat_caller_response(_chat_response(marker), rig.model), response.text attributes: Final = _matching_genai_marker_span(rig.destination, marker) assert frozenset(attributes) == _B3_ATTRIBUTE_KEYS[callback], attributes + assert attributes["litellm.cache_hit"] == "False", attributes assert "metadata" not in attributes, attributes assert not any(".tool_calls." in key for key in attributes), attributes baggage: Final = tuple( diff --git a/tests/integration/observability/test_arize_otel_v2_openinference_spans.py b/tests/integration/observability/test_arize_otel_v2_openinference_spans.py index ab79e81289e..6a7d6d99a84 100644 --- a/tests/integration/observability/test_arize_otel_v2_openinference_spans.py +++ b/tests/integration/observability/test_arize_otel_v2_openinference_spans.py @@ -921,7 +921,16 @@ def test_arize_otel_v2_a_cache(surface: str, gateway: Gateway, tmp_path: Path) - ) assert len(sentinel_spans) == 1, spans _assert_tool_span_for_marker(sentinel_spans[0], sentinel) - assert not any(attributes.get("litellm.metadata.trace_marker") == marker for attributes in spans), spans + cache_hit_spans: Final = tuple( + attributes + for attributes in spans + if ( + attributes.get("litellm.metadata.trace_marker") == marker + and attributes.get("litellm.cache_hit") == "True" + ) + ) + assert len(cache_hit_spans) == 1, spans + assert cache_hit_spans[0]["litellm.cost.total"] == "0.0", cache_hit_spans def test_arize_otel_v2_cache_hit_exports_llm_span(gateway: Gateway, tmp_path: Path) -> None: @@ -960,4 +969,9 @@ def test_arize_otel_v2_cache_hit_exports_llm_span(gateway: Gateway, tmp_path: Pa attributes for attributes in spans if attributes.get("litellm.metadata.trace_marker") == marker ) assert len(marker_spans) == 2, spans - _assert_tool_span_for_marker(marker_spans[1], marker) + cache_hit_spans: Final = tuple( + attributes for attributes in marker_spans if attributes.get("litellm.cache_hit") == "True" + ) + assert len(cache_hit_spans) == 1, marker_spans + _assert_tool_span_for_marker(cache_hit_spans[0], marker) + assert cache_hit_spans[0]["litellm.cost.total"] == "0.0", marker_spans diff --git a/tests/integration/observability/test_callback_delivery.py b/tests/integration/observability/test_callback_delivery.py index f3e8daab014..17ba6419646 100644 --- a/tests/integration/observability/test_callback_delivery.py +++ b/tests/integration/observability/test_callback_delivery.py @@ -1,4 +1,3 @@ -import base64 import json import uuid from collections.abc import Callable, Mapping @@ -14,6 +13,8 @@ from integration._support.database import read_rows from integration._support.process import graceful_stop_seconds, owned_proxy from integration._support.wire import Reply, Request, wire_server +from litellm.types.videos.utils import decode_video_id_with_provider + pytestmark: Final = pytest.mark.shares_worker_state @@ -431,9 +432,8 @@ def _responses_text(body: dict[str, JsonValue]) -> str: def _video_job(body: dict[str, JsonValue]) -> tuple[str, str]: - encoded_id: Final = string_value(body["id"]).removeprefix("video_") - decoded: Final = base64.b64decode(encoded_id).decode() - return decoded.rsplit("video_id:", 1)[-1], string_value(body["status"]) + decoded: Final = decode_video_id_with_provider(string_value(body["id"])) + return string_value(decoded.get("video_id")), string_value(body["status"]) @dataclass(frozen=True, slots=True) diff --git a/tests/integration/observability/test_custom_logger_hook_counts.py b/tests/integration/observability/test_custom_logger_hook_counts.py new file mode 100644 index 00000000000..420ac2a5fcb --- /dev/null +++ b/tests/integration/observability/test_custom_logger_hook_counts.py @@ -0,0 +1,96 @@ +import uuid +from collections.abc import Iterator +from typing import Final + +import pytest +from integration._support.client import Gateway, eventually, gateway_from_environment +from integration._support.hook_counts import ( + STREAMING_SURFACES, + SURFACE_CALL_TYPES, + HookRecords, + assert_hooks, + one_async_hook, + provider, + send, + write_hook_count_config, +) +from integration._support.process import owned_proxy +from integration._support.wire import Reply, wire_server + +pytestmark = pytest.mark.timeout(240) + + +@pytest.fixture(scope="module", params=["cache", "cache_and_sync_callback"]) +def hook_proxy( + request: pytest.FixtureRequest, tmp_path_factory: pytest.TempPathFactory +) -> Iterator[tuple[Gateway, HookRecords]]: + tmp_path: Final = tmp_path_factory.mktemp("custom-logger-hook-counts") + legacy_callbacks: Final = ( + { + "success_callback": ["integration._support.hook_count_probe.sync_success_function"], + "failure_callback": ["integration._support.hook_count_probe.sync_failure_function"], + } + if request.param == "cache_and_sync_callback" + else {} + ) + with ( + wire_server(provider) as upstream, + wire_server(lambda request: Reply()) as sink, + gateway_from_environment() as rig, + ): + config: Final = write_hook_count_config( + tmp_path / "hook-counts.yaml", + upstream.url, + { + "callbacks": ["integration._support.hook_count_probe.probe"], + **legacy_callbacks, + "cache": True, + "cache_params": {"type": "redis", "host": "os.environ/REDIS_HOST", "port": "os.environ/REDIS_PORT"}, + }, + ) + with owned_proxy( + rig, tmp_path, {"HOOK_COUNT_PROBE_URL": sink.url, "STORE_MODEL_IN_DB": "False"}, config=config, workers=2 + ) as proxy: + yield proxy, HookRecords(sink, function_callbacks=request.param == "cache_and_sync_callback") + + +@pytest.mark.parametrize("outcome", ["success", "failure"]) +@pytest.mark.parametrize("surface", sorted(SURFACE_CALL_TYPES)) +def test_custom_logger_gets_one_async_hook_per_request_with_the_response_cache_on( + hook_proxy: tuple[Gateway, HookRecords], surface: str, outcome: str +) -> None: + proxy, records = hook_proxy + call_id: Final = str(uuid.uuid4()) + response: Final = send(proxy, surface, outcome, call_id) + assert response.status_code == (200 if outcome == "success" else 400), response.text + assert_hooks(records, surface, call_id, one_async_hook(records, surface, outcome)) + + +@pytest.mark.parametrize("outcome", ["success", "failure"]) +@pytest.mark.parametrize("surface", STREAMING_SURFACES) +def test_custom_logger_gets_one_async_hook_per_streamed_request( + hook_proxy: tuple[Gateway, HookRecords], surface: str, outcome: str +) -> None: + proxy, records = hook_proxy + call_id: Final = str(uuid.uuid4()) + response: Final = send(proxy, surface, outcome, call_id, stream=True) + assert response.status_code == (200 if outcome == "success" else 400), response.text + if outcome == "success": + assert "ok" in response.text, response.text + assert_hooks(records, surface, call_id, one_async_hook(records, surface, outcome)) + + +@pytest.mark.parametrize("surface", sorted(SURFACE_CALL_TYPES)) +def test_custom_logger_gets_one_async_hook_per_request_rejected_by_key_auth( + hook_proxy: tuple[Gateway, HookRecords], surface: str +) -> None: + proxy, records = hook_proxy + known_calls: Final = {record["litellm_call_id"] for record in records.drained()} + response: Final = send(proxy, surface, "success", str(uuid.uuid4()), key="sk-not-a-virtual-key") + assert response.status_code == 401, response.text + + def new_calls(found: tuple[dict[str, str], ...]) -> set[str]: + return {record["litellm_call_id"] for record in found if record["litellm_call_id"] not in known_calls} + + (rejected_call,) = eventually(lambda: new_calls(records.drained()), bool, seconds=20) + assert_hooks(records, surface, rejected_call, one_async_hook(records, surface, "failure")) diff --git a/tests/integration/observability/test_custom_logger_hook_counts_chaos.py b/tests/integration/observability/test_custom_logger_hook_counts_chaos.py new file mode 100644 index 00000000000..7b19ef3b1ff --- /dev/null +++ b/tests/integration/observability/test_custom_logger_hook_counts_chaos.py @@ -0,0 +1,181 @@ +"""One hook per request under a concurrent burst while the logger's destination stalls and fails, and while a +worker is killed.""" + +import threading +import time +import uuid +from collections.abc import Callable +from concurrent.futures import Future, ThreadPoolExecutor +from dataclasses import dataclass +from pathlib import Path +from typing import Final + +import httpx +import pytest +from integration._support.client import Gateway, eventually, gateway_from_environment, held +from integration._support.hook_counts import ( + STREAMING_SURFACES, + SURFACE_CALL_TYPES, + HookRecords, + assert_hooks, + one_async_hook, + probe_hooks, + provider, + send, + write_hook_count_config, +) +from integration._support.process import graceful_stop_seconds, owned_proxy, owned_proxy_process +from integration._support.wire import Reply, Request, wire_server + +pytestmark = pytest.mark.timeout(2 * graceful_stop_seconds() + 300) + +RecordProperty = Callable[[str, object], None] + +_SETTINGS: Final = {"callbacks": ["integration._support.hook_count_probe.probe"]} +_HOLD_SECONDS: Final = 2.0 + + +@dataclass(frozen=True) +class _Call: + surface: str + outcome: str + stream: bool + call_id: str + + +@dataclass(frozen=True) +class _Outcome: + call: _Call + status: int | None + error: str | None + + +def _burst(rounds: int) -> tuple[_Call, ...]: + shapes: Final = ( + *((surface, outcome, False) for surface in sorted(SURFACE_CALL_TYPES) for outcome in ("success", "failure")), + *((surface, "success", True) for surface in STREAMING_SURFACES), + ) + return tuple( + _Call(surface, outcome, stream, str(uuid.uuid4())) for _ in range(rounds) for surface, outcome, stream in shapes + ) + + +def _attempt(proxy: Gateway, call: _Call) -> _Outcome: + try: + response: Final = send(proxy, call.surface, call.outcome, call.call_id, stream=call.stream) + except httpx.HTTPError as error: + return _Outcome(call, None, repr(error)) + return _Outcome(call, response.status_code, None) + + +def _expected_status(call: _Call) -> int: + return 200 if call.outcome == "success" else 400 + + +def _done(futures: tuple[Future[_Outcome], ...]) -> int: + return sum(future.done() for future in futures) + + +class _Destination: + """The probe's sink: answers at once, holds each report until released, or refuses it with a 503.""" + + def __init__(self) -> None: + self.mode = "ok" + self.release = threading.Event() + + def __call__(self, request: Request) -> Reply: + if self.mode == "hold": + self.release.wait(timeout=_HOLD_SECONDS + 1) + if self.mode == "fail": + return Reply(status=503, body=b'{"error":"destination unavailable"}') + return Reply() + + +def test_logger_destination_stalling_then_failing_mid_burst_gets_one_hook_per_request( + tmp_path: Path, record_property: RecordProperty +) -> None: + destination: Final = _Destination() + with ( + wire_server(provider) as upstream, + wire_server(destination) as sink, + gateway_from_environment() as rig, + ): + config: Final = write_hook_count_config(tmp_path / "hook-count-chaos.yaml", upstream.url, _SETTINGS) + with owned_proxy( + rig, tmp_path, {"HOOK_COUNT_PROBE_URL": sink.url, "STORE_MODEL_IN_DB": "False"}, config=config, workers=2 + ) as proxy: + records: Final = HookRecords(sink, function_callbacks=False) + calls: Final = _burst(2) + destination.mode = "hold" + with ThreadPoolExecutor(max_workers=len(calls)) as pool: + futures: Final = tuple(pool.submit(_attempt, proxy, call) for call in calls) + eventually(lambda: _done(futures), lambda done: done >= 1, seconds=60) + held_liveliness: Final = proxy.client.get("/health/liveliness").status_code + time.sleep(_HOLD_SECONDS) + destination.mode = "fail" + destination.release.set() + time.sleep(_HOLD_SECONDS) + destination.mode = "ok" + outcomes: Final = tuple(future.result(timeout=180) for future in futures) + record_property("burst_size", len(calls)) + assert held_liveliness == 200, held_liveliness + assert [outcome for outcome in outcomes if outcome.status != _expected_status(outcome.call)] == [] + for call in calls: + assert_hooks(records, call.surface, call.call_id, one_async_hook(records, call.surface, call.outcome)) + + +def test_worker_killed_mid_burst_leaves_at_most_one_hook_per_request( + tmp_path: Path, record_property: RecordProperty +) -> None: + with ( + wire_server(provider) as upstream, + wire_server(lambda request: Reply()) as sink, + gateway_from_environment() as rig, + ): + config: Final = write_hook_count_config(tmp_path / "hook-count-kill.yaml", upstream.url, _SETTINGS) + with owned_proxy_process( + rig, tmp_path, {"HOOK_COUNT_PROBE_URL": sink.url, "STORE_MODEL_IN_DB": "False"}, config=config, workers=2 + ) as owned: + proxy: Final = owned.gateway + records: Final = HookRecords(sink, function_callbacks=False) + victim: Final = min(eventually(owned.worker_pids, lambda found: len(found) == 2, seconds=60)) + calls: Final = _burst(2) + with ThreadPoolExecutor(max_workers=len(calls)) as pool: + futures: Final = tuple(pool.submit(_attempt, proxy, call) for call in calls) + eventually(lambda: _done(futures), lambda done: done >= 1, seconds=60) + with owned.replacing_worker(victim) as kill: + kill() + done_at_kill: Final = _done(futures) + survived: Final = eventually( + lambda: _attempt(proxy, _Call("speech", "success", False, str(uuid.uuid4()))), + lambda outcome: outcome.status == 200, + seconds=30, + ) + outcomes: Final = tuple(future.result(timeout=180) for future in futures) + respawned: Final = _Call("speech", "success", False, str(uuid.uuid4())) + after_respawn: Final = _attempt(proxy, respawned) + completed: Final = tuple(outcome for outcome in outcomes if outcome.status is not None) + interrupted: Final = tuple(outcome for outcome in outcomes if outcome.status is None) + assert after_respawn.status == 200, after_respawn + assert [outcome for outcome in completed if outcome.status != _expected_status(outcome.call)] == [] + for call in (survived.call, respawned): + assert_hooks(records, call.surface, call.call_id, one_async_hook(records, call.surface, call.outcome)) + burst_hooks: Final = held( + lambda: _hooks_of(records, calls), + lambda found: all( + hooks in ([], [f"async_{call.outcome}"]) for call, hooks in zip(calls, found, strict=True) + ), + holding=3, + seconds=20, + ) + record_property("burst_size", len(calls)) + record_property("killed_worker_pid", victim) + record_property("done_at_kill", done_at_kill) + record_property("interrupted_calls", str(tuple(outcome.error for outcome in interrupted))) + record_property("burst_calls_without_a_hook", sum(not hooks for hooks in burst_hooks)) + + +def _hooks_of(records: HookRecords, calls: tuple[_Call, ...]) -> tuple[list[str], ...]: + """A burst call the killed worker served may lose its logging with the worker, whether or not its response + arrived first, so a burst call gets its one async hook or none, never two.""" + return tuple(probe_hooks(records, call.surface, records.for_call(call.call_id)) for call in calls) diff --git a/tests/integration/observability/test_custom_logger_hook_counts_modes.py b/tests/integration/observability/test_custom_logger_hook_counts_modes.py new file mode 100644 index 00000000000..e143559040e --- /dev/null +++ b/tests/integration/observability/test_custom_logger_hook_counts_modes.py @@ -0,0 +1,95 @@ +"""A logger the async handler never reaches keeps its sync hook on async calls outside the async flag list. + +A logger with both hooks registered only under `success_callback` and `failure_callback` is never reached by the async +failure handler, so it keeps its sync failure hook. The async success handler does reach it, and gives it its async +success hook instead of the sync one. + +The sync success handler only runs for an async call when a legacy sync callback is configured, so every +registration here carries the legacy function callbacks too.""" + +import uuid +from collections.abc import Iterator +from typing import Final + +import pytest +from integration._support.client import Gateway, eventually, gateway_from_environment +from integration._support.hook_counts import ( + IN_THE_ASYNC_FLAG_LIST, + SURFACE_CALL_TYPES, + HookRecords, + assert_hooks, + provider, + send, + write_hook_count_config, +) +from integration._support.process import owned_proxy +from integration._support.wire import Reply, wire_server + +pytestmark = pytest.mark.timeout(240) + +_PROBES: Final = "integration._support.hook_count_probe" +_REGISTRATIONS: Final[dict[str, dict[str, object]]] = { + "sync_only_logger": { + "callbacks": [f"{_PROBES}.sync_only_probe"], + "success_callback": [f"{_PROBES}.sync_success_function"], + "failure_callback": [f"{_PROBES}.sync_failure_function"], + }, + "sync_event_lists": { + "success_callback": [f"{_PROBES}.probe", f"{_PROBES}.sync_success_function"], + "failure_callback": [f"{_PROBES}.probe", f"{_PROBES}.sync_failure_function"], + }, +} +_OUTSIDE_THE_ASYNC_FLAG_LIST: Final = sorted(SURFACE_CALL_TYPES.keys() - IN_THE_ASYNC_FLAG_LIST) + + +@pytest.fixture(scope="module", params=sorted(_REGISTRATIONS)) +def sync_hook_proxy( + request: pytest.FixtureRequest, tmp_path_factory: pytest.TempPathFactory +) -> Iterator[tuple[Gateway, HookRecords, str]]: + tmp_path: Final = tmp_path_factory.mktemp("custom-logger-hook-count-modes") + with ( + wire_server(provider) as upstream, + wire_server(lambda request: Reply()) as sink, + gateway_from_environment() as rig, + ): + config: Final = write_hook_count_config( + tmp_path / "hook-count-modes.yaml", upstream.url, _REGISTRATIONS[request.param] + ) + with owned_proxy( + rig, tmp_path, {"HOOK_COUNT_PROBE_URL": sink.url, "STORE_MODEL_IN_DB": "False"}, config=config, workers=2 + ) as proxy: + yield proxy, HookRecords(sink, function_callbacks=True), request.param + + +@pytest.mark.parametrize("outcome", ["success", "failure"]) +@pytest.mark.parametrize("surface", _OUTSIDE_THE_ASYNC_FLAG_LIST) +def test_logger_the_async_handler_skips_gets_one_sync_hook_per_request( + sync_hook_proxy: tuple[Gateway, HookRecords, str], surface: str, outcome: str +) -> None: + proxy, records, registration = sync_hook_proxy + reached_by_the_async_success: Final = registration == "sync_event_lists" and outcome == "success" + call_id: Final = str(uuid.uuid4()) + response: Final = send(proxy, surface, outcome, call_id) + assert response.status_code == (200 if outcome == "success" else 400), response.text + assert_hooks( + records, + surface, + call_id, + sorted([f"function_{outcome}", f"async_{outcome}" if reached_by_the_async_success else f"sync_{outcome}"]), + ) + + +@pytest.mark.parametrize("surface", _OUTSIDE_THE_ASYNC_FLAG_LIST) +def test_logger_the_async_handler_skips_gets_one_sync_hook_per_request_rejected_by_key_auth( + sync_hook_proxy: tuple[Gateway, HookRecords, str], surface: str +) -> None: + proxy, records, _ = sync_hook_proxy + known_calls: Final = {record["litellm_call_id"] for record in records.drained()} + response: Final = send(proxy, surface, "success", str(uuid.uuid4()), key="sk-not-a-virtual-key") + assert response.status_code == 401, response.text + + def new_calls(found: tuple[dict[str, str], ...]) -> set[str]: + return {record["litellm_call_id"] for record in found if record["litellm_call_id"] not in known_calls} + + (rejected_call,) = eventually(lambda: new_calls(records.drained()), bool, seconds=20) + assert_hooks(records, surface, rejected_call, ["function_failure", "sync_failure"]) diff --git a/tests/integration/observability/test_custom_logger_hook_counts_post_call_block.py b/tests/integration/observability/test_custom_logger_hook_counts_post_call_block.py new file mode 100644 index 00000000000..1b708db64d8 --- /dev/null +++ b/tests/integration/observability/test_custom_logger_hook_counts_post_call_block.py @@ -0,0 +1,75 @@ +"""A CustomLogger with both hooks gets one failure hook when a post-call guardrail blocks the response. + +The proxy drops the async success logging it parked for the guardrails and logs the block as a failure through both +the async and the sync failure handlers. The logger gets only its async failure hook from them. Speech and +transcription responses never reach post-call guardrails, and image generation logs its success before they run, so +neither parks. + +A legacy sync callback is configured, because that is what makes the sync handler run for an async call.""" + +import uuid +from collections.abc import Iterator +from typing import Final + +import pytest +from integration._support.client import Gateway, gateway_from_environment, held +from integration._support.hook_counts import ( + SURFACE_CALL_TYPES, + HookRecords, + probe_hooks, + provider, + send, + write_hook_count_config, +) +from integration._support.process import owned_proxy +from integration._support.wire import Reply, wire_server + +pytestmark = pytest.mark.timeout(240) + +_PROBES: Final = "integration._support.hook_count_probe" +_PARKED_FOR_POST_CALL_GUARDRAILS: Final = sorted( + SURFACE_CALL_TYPES.keys() - {"speech", "transcription", "image_generation"} +) + + +@pytest.fixture(scope="module") +def post_call_block(tmp_path_factory: pytest.TempPathFactory) -> Iterator[tuple[Gateway, HookRecords]]: + tmp_path: Final = tmp_path_factory.mktemp("hook-count-post-call-block") + guardrail: Final = { + "guardrail_name": "hook-count-post-call-block", + "litellm_params": { + "guardrail": f"{_PROBES}.BlockingPostCallGuardrail", + "mode": "post_call", + "default_on": True, + }, + } + with ( + wire_server(provider) as upstream, + wire_server(lambda request: Reply()) as sink, + gateway_from_environment() as rig, + ): + config: Final = write_hook_count_config( + tmp_path / "hook-count-post-call-block.yaml", + upstream.url, + {"callbacks": [f"{_PROBES}.probe"], "success_callback": [f"{_PROBES}.sync_success_function"]}, + (guardrail,), + ) + overrides: Final = {"HOOK_COUNT_PROBE_URL": sink.url, "STORE_MODEL_IN_DB": "False"} + with owned_proxy(rig, tmp_path, overrides, config=config, workers=2) as proxy: + yield proxy, HookRecords(sink, function_callbacks=False) + + +@pytest.mark.parametrize("surface", _PARKED_FOR_POST_CALL_GUARDRAILS) +def test_response_a_post_call_guardrail_blocks_gives_the_logger_one_failure_hook( + post_call_block: tuple[Gateway, HookRecords], surface: str +) -> None: + proxy, records = post_call_block + call_id: Final = str(uuid.uuid4()) + response: Final = send(proxy, surface, "success", call_id) + assert response.status_code == 400, response.text + held( + lambda: probe_hooks(records, surface, records.for_call(call_id)), + lambda hooks: hooks == ["async_failure"], + holding=3, + seconds=20, + ) diff --git a/tests/integration/observability/test_custom_logger_hook_counts_vendors.py b/tests/integration/observability/test_custom_logger_hook_counts_vendors.py new file mode 100644 index 00000000000..3c9be9e2a3f --- /dev/null +++ b/tests/integration/observability/test_custom_logger_hook_counts_vendors.py @@ -0,0 +1,128 @@ +"""Built-in loggers that override both hooks deliver one record per async request outside the async flag list: +Datadog one log entry and LangSmith one run. OpenTelemetry keeps its own emit-once guard, so it never exports two +spans for a request either way; its speech, OCR and search spans carry no `litellm.call_id`, so only "never two" +is checked for it. + +A legacy sync callback is configured, because that is what makes the sync handler run for an async call.""" + +import gzip +import json +import uuid +import zlib +from collections.abc import Iterator +from dataclasses import dataclass +from typing import Final + +import pytest +from integration._support.client import Gateway, gateway_from_environment, held +from integration._support.hook_counts import IN_THE_ASYNC_FLAG_LIST, SURFACE_CALL_TYPES, provider, send +from integration._support.hook_counts import write_hook_count_config +from integration._support.otlp_sink import decode_spans +from integration._support.process import owned_proxy +from integration._support.wire import Reply, Request, Wire, wire_server + +pytestmark = pytest.mark.timeout(240) + +_PROBES: Final = "integration._support.hook_count_probe" +_FLUSH_SECONDS: Final = 1 +_OUTSIDE_THE_ASYNC_FLAG_LIST: Final = sorted(SURFACE_CALL_TYPES.keys() - IN_THE_ASYNC_FLAG_LIST) + + +@dataclass(frozen=True) +class _Vendors: + proxy: Gateway + sink: Wire + + +@pytest.fixture(scope="module") +def vendors(tmp_path_factory: pytest.TempPathFactory) -> Iterator[_Vendors]: + tmp_path: Final = tmp_path_factory.mktemp("custom-logger-hook-count-vendors") + with ( + wire_server(provider) as upstream, + wire_server(lambda request: Reply(status=202)) as sink, + gateway_from_environment() as rig, + ): + config: Final = write_hook_count_config( + tmp_path / "hook-count-vendors.yaml", + upstream.url, + { + "callbacks": ["datadog", "langsmith", "otel"], + "success_callback": [f"{_PROBES}.sync_success_function"], + "failure_callback": [f"{_PROBES}.sync_failure_function"], + }, + ) + overrides: Final = { + "HOOK_COUNT_PROBE_URL": sink.url + "/probe", + "STORE_MODEL_IN_DB": "False", + "DEFAULT_FLUSH_INTERVAL_SECONDS": str(_FLUSH_SECONDS), + "DD_API_KEY": "synthetic-datadog-key", + "DD_SITE": "us5.datadoghq.com", + "DD_BASE_URL": sink.url + "/datadog", + "LANGSMITH_API_KEY": "synthetic-langsmith-key", + "LANGSMITH_PROJECT": "hook-counts", + "LANGSMITH_BASE_URL": sink.url + "/langsmith", + "OTEL_EXPORTER": "otlp_http", + "OTEL_ENDPOINT": sink.url + "/otel/v1/traces", + } + with owned_proxy(rig, tmp_path, overrides, config=config, workers=2) as proxy: + yield _Vendors(proxy, sink) + + +def _unzipped(body: bytes) -> bytes: + if body[:2] == b"\x1f\x8b": + return gzip.decompress(body) + try: + return zlib.decompress(body, zlib.MAX_WBITS | 16) + except zlib.error: + return body + + +def _entries(body: bytes) -> tuple[object, ...]: + decoded: Final = json.loads(_unzipped(body)) + return tuple(decoded) if isinstance(decoded, list) else (decoded,) + + +def _records(request: Request) -> tuple[tuple[str, str], ...]: + """Every record one delivery carries, as (destination, serialized record). A LangSmith batch carries its new + runs under `post`, and an OpenTelemetry export carries every span of the request's trace.""" + if request.target.startswith("/datadog"): + return tuple(("datadog", json.dumps(entry)) for entry in _entries(request.body)) + if request.target.startswith("/langsmith") and request.method == "POST": + runs: Final = tuple( + run + for entry in _entries(request.body) + for run in (entry.get("post", []) if isinstance(entry, dict) and "post" in entry else [entry]) + ) + return tuple(("langsmith", json.dumps(run)) for run in runs) + if request.target.startswith("/otel"): + spans: Final = decode_spans(request.body, request.headers.get("content-type", "")) + return tuple(("otel", json.dumps(span)) for span in spans if "litellm.call_id" in span["attributes"]) + return () + + +@dataclass +class _Deliveries: + sink: Wire + seen: tuple[tuple[str, str], ...] = () + + def per_destination(self, call_id: str) -> dict[str, int]: + self.seen = (*self.seen, *(record for request in self.sink.drain() for record in _records(request))) + destinations: Final = ("datadog", "langsmith", "otel") + return { + destination: sum(1 for name, record in self.seen if name == destination and call_id in record) + for destination in destinations + } + + +@pytest.mark.parametrize("surface", _OUTSIDE_THE_ASYNC_FLAG_LIST) +def test_built_in_loggers_deliver_one_record_per_async_request(vendors: _Vendors, surface: str) -> None: + deliveries: Final = _Deliveries(vendors.sink) + call_id: Final = str(uuid.uuid4()) + response: Final = send(vendors.proxy, surface, "success", call_id) + assert response.status_code == 200, response.text + held( + lambda: deliveries.per_destination(call_id), + lambda counts: counts["datadog"] == 1 and counts["langsmith"] == 1 and counts["otel"] <= 1, + holding=4 * _FLUSH_SECONDS, + seconds=60, + ) diff --git a/tests/integration/observability/test_custom_logger_redaction.py b/tests/integration/observability/test_custom_logger_redaction.py index 2abaa85df25..10340c51fea 100644 --- a/tests/integration/observability/test_custom_logger_redaction.py +++ b/tests/integration/observability/test_custom_logger_redaction.py @@ -370,7 +370,7 @@ def _drained(wire: Wire, count: int) -> tuple[Request, ...]: return eventually(observed, lambda values: len(values) >= count, seconds=30) -def test_redacted_responses_follow_up_replays_original_instructions( +def test_redacted_responses_follow_up_replays_neither_instructions_nor_the_sentinel( redaction_proxy: tuple[Gateway, Wire, Wire], ) -> None: proxy, provider, sink = redaction_proxy @@ -412,7 +412,7 @@ def test_redacted_responses_follow_up_replays_original_instructions( assert len(sent) == 1, sent assert len(sent[0]["messages"]) == 3, sent[0] system: Final = json.dumps(sent[0].get("system")) - assert INSTRUCTIONS in system and REDACTED_BY_LITELLM not in system, sent[0] + assert INSTRUCTIONS not in system and REDACTED_BY_LITELLM not in system, sent[0] def test_redacted_router_usage_is_counted_once(redaction_proxy: tuple[Gateway, Wire, Wire]) -> None: diff --git a/tests/integration/providers/_count_tokens_system_lift.py b/tests/integration/providers/_count_tokens_system_lift.py index 56619d1c963..dedf6b5006d 100644 --- a/tests/integration/providers/_count_tokens_system_lift.py +++ b/tests/integration/providers/_count_tokens_system_lift.py @@ -49,6 +49,87 @@ TOOLS: Final[list[JsonValue]] = [ } ] +WEATHER_SCHEMA: Final[dict[str, JsonValue]] = { + "type": "object", + "properties": {"city": {"type": "string", "description": "City to look up"}}, + "required": ["city"], +} +RESPONSES_TOOLS: Final[list[JsonValue]] = [ + { + "type": "function", + "name": "get_weather", + "description": "Look up the current weather for a city", + "parameters": WEATHER_SCHEMA, + } +] +RESPONSES_TOOL_USE: Final[Mapping[str, dict[str, JsonValue]]] = MappingProxyType( + { + "function-tool": {"input": "Count this message", "instructions": "Be terse", "tools": RESPONSES_TOOLS}, + "tool-round-trip": { + "input": [ + {"role": "user", "content": "What is the weather in Paris?"}, + {"type": "function_call", "call_id": "call_1", "name": "get_weather", "arguments": '{"city": "Paris"}'}, + {"type": "function_call_output", "call_id": "call_1", "output": "Sunny, 21C"}, + ], + "tools": RESPONSES_TOOLS, + }, + } +) + + +def counted_fields(body: Mapping[str, JsonValue]) -> dict[str, JsonValue]: + return {field: body[field] for field in ("messages", "system", "tools") if field in body} + + +REPORT_SCHEMA: Final[dict[str, JsonValue]] = { + "type": "object", + "properties": {"city": {"type": "string"}, "summary": {"type": "string"}}, + "required": ["city", "summary"], + "additionalProperties": False, +} +WEATHER_QUESTION: Final = "What is the weather in Paris?" +RESPONSES_REQUEST_OPTIONS: Final[Mapping[str, dict[str, JsonValue]]] = MappingProxyType( + { + "text-format": { + "input": WEATHER_QUESTION, + "text": {"format": {"type": "json_schema", "name": "weather_report", "schema": REPORT_SCHEMA}}, + }, + "forced-tool-choice-dropped": { + "input": WEATHER_QUESTION, + "tools": RESPONSES_TOOLS, + "tool_choice": {"type": "function", "name": "get_weather"}, + "parallel_tool_calls": False, + "drop_params": True, + }, + "reasoning": { + "input": WEATHER_QUESTION, + "tools": RESPONSES_TOOLS, + "tool_choice": "auto", + "reasoning": {"effort": "low"}, + }, + } +) +_REQUEST_OPTIONS: Final = ("tool_choice", "thinking") + + +def count_request_fields(count_body: Mapping[str, JsonValue]) -> dict[str, JsonValue]: + options: Final = (*_REQUEST_OPTIONS, "output_config", "output_format") + return {**counted_fields(count_body), **{field: count_body[field] for field in options if field in count_body}} + + +def inference_count_fields(inference_body: Mapping[str, JsonValue]) -> dict[str, JsonValue]: + output_config: Final = inference_body.get("output_config") + output_format: Final = inference_body.get("output_format") + counted_config: Final = { + **(output_config if isinstance(output_config, dict) else {}), + **({} if output_format is None else {"format": output_format}), + } + return { + **counted_fields(inference_body), + **{field: inference_body[field] for field in _REQUEST_OPTIONS if field in inference_body}, + **({"output_config": counted_config} if counted_config else {}), + } + @dataclass(frozen=True, slots=True) class LiftCase: diff --git a/tests/integration/providers/_sagemaker_chat_container.py b/tests/integration/providers/_sagemaker_chat_container.py index 6a06b92e215..4cec8f8b6fe 100644 --- a/tests/integration/providers/_sagemaker_chat_container.py +++ b/tests/integration/providers/_sagemaker_chat_container.py @@ -16,6 +16,7 @@ SECRET_KEY: Final = "synthetic-secret-key-for-testing" REGION: Final = "us-east-1" PROMPT: Final = "synthetic inference component request" CONTENT: Final = ("sagemaker ", "wire control") +USAGE: Final[Mapping[str, int]] = MappingProxyType({"prompt_tokens": 11, "completion_tokens": 4, "total_tokens": 15}) NO_CACHE: Final[Mapping[str, JsonValue]] = MappingProxyType({"cache": {"no-cache": True}}) JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue]) _MARKER_PREFIX: Final = "marker-" @@ -69,27 +70,61 @@ def _event_header(name: str, value: str) -> bytes: return struct.pack("!B", len(name_bytes)) + name_bytes + b"\x07" + struct.pack("!H", len(value_bytes)) + value_bytes +def _frame(headers: bytes, body: bytes) -> bytes: + prelude: Final = struct.pack("!II", 12 + len(headers) + len(body) + 4, len(headers)) + message: Final = prelude + struct.pack("!I", zlib.crc32(prelude) & 0xFFFFFFFF) + headers + body + return message + struct.pack("!I", zlib.crc32(message) & 0xFFFFFFFF) + + def _payload_part(body: bytes) -> bytes: headers: Final = ( _event_header(":event-type", "PayloadPart") + _event_header(":content-type", "application/octet-stream") + _event_header(":message-type", "event") ) - prelude: Final = struct.pack("!II", 12 + len(headers) + len(body) + 4, len(headers)) - message: Final = prelude + struct.pack("!I", zlib.crc32(prelude) & 0xFFFFFFFF) + headers + body - return message + struct.pack("!I", zlib.crc32(message) & 0xFFFFFFFF) + return _frame(headers, body) + + +def model_stream_error(message: str, error_code: str) -> bytes: + headers: Final = ( + _event_header(":exception-type", "ModelStreamError") + + _event_header(":content-type", "application/json") + + _event_header(":message-type", "exception") + ) + return _frame(headers, json.dumps({"Message": message, "ErrorCode": error_code}).encode()) def container_reply(identity: str, stream: bool) -> Reply: if not stream: return Reply(body=_completion(identity)) - chunks: Final = ( + return event_stream_reply( + ( + _chunk(identity, {"role": "assistant", "content": CONTENT[0]}, None), + _chunk(identity, {"content": CONTENT[1]}, None), + _chunk(identity, {}, "stop", usage=dict(USAGE)), + ) + ) + + +def event_stream_reply(payloads: tuple[bytes, ...], *, then: tuple[bytes, ...] = ()) -> Reply: + return Reply(chunks=(*map(_payload_part, payloads), *then), content_type="application/vnd.amazon.eventstream") + + +def vllm_stream_events(identity: str) -> tuple[bytes, ...]: + usage_event: Final = { + "id": identity, + "object": "chat.completion.chunk", + "created": 1, + "model": SERVED_MODEL, + "choices": [], + "usage": dict(USAGE), + } + return ( _chunk(identity, {"role": "assistant", "content": CONTENT[0]}, None), _chunk(identity, {"content": CONTENT[1]}, None), - _chunk(identity, {}, "stop", usage={"prompt_tokens": 11, "completion_tokens": 4, "total_tokens": 15}), - ) - return Reply( - chunks=tuple(_payload_part(chunk) for chunk in chunks), content_type="application/vnd.amazon.eventstream" + _chunk(identity, {}, "stop"), + f"data: {json.dumps(usage_event, separators=(',', ':'))}\n\n".encode(), + b"data: [DONE]\n\n", ) diff --git a/tests/integration/providers/test_anthropic_count_tokens_system_lift_wire.py b/tests/integration/providers/test_anthropic_count_tokens_system_lift_wire.py index afd25fcfa04..27cbbe81a13 100644 --- a/tests/integration/providers/test_anthropic_count_tokens_system_lift_wire.py +++ b/tests/integration/providers/test_anthropic_count_tokens_system_lift_wire.py @@ -6,6 +6,7 @@ from collections.abc import Callable, Iterator, Mapping from concurrent.futures import ThreadPoolExecutor from contextlib import AbstractContextManager, ExitStack from dataclasses import dataclass +from pathlib import Path from queue import SimpleQueue from types import MappingProxyType from typing import Final, cast @@ -14,8 +15,10 @@ import httpcore import httpx import psutil import pytest +import yaml from anthropic.types import MessageParam -from integration._support.client import Gateway, Scenario, eventually, gateway_from_environment +from integration._support.client import Gateway, Scenario, eventually, gateway_from_environment, object_value +from integration._support.process import graceful_stop_seconds, owned_proxy from integration._support.wire import Reply, Request, Wire, wire_server from integration._support.ports import allocate_port from integration.providers._count_tokens_system_lift import ( @@ -32,18 +35,24 @@ from integration.providers._count_tokens_system_lift import ( MID_SYSTEM, REJECTION, REMINDER, + RESPONSES_REQUEST_OPTIONS, + RESPONSES_TOOL_USE, STRING_CASE, TOKEN_COUNTING_BETA, TOOLS, USER, USER_TEXT, + WEATHER_QUESTION, LiftCase, accepts_count_body, anthropic_client, async_anthropic_client, async_openai_client, count_request, + count_request_fields, + counted_fields, expected_count_body, + inference_count_fields, openai_client, ) from pydantic import JsonValue, TypeAdapter @@ -480,9 +489,7 @@ def test_messages_count_tokens_unauthenticated_request_never_reaches_the_peer( assert peer.drain() == () -def test_peer_outage_between_concurrent_waves_errors_then_recovers( - deployment: _Deployment, gateway: Gateway -) -> None: +def test_peer_outage_between_concurrent_waves_errors_then_recovers(deployment: _Deployment, gateway: Gateway) -> None: with ExitStack() as stack: clients: Final = _clients(stack, str(gateway.client.base_url), 8) pool: Final = stack.enter_context(ThreadPoolExecutor(max_workers=len(clients))) @@ -573,3 +580,164 @@ def test_chat_completions_on_the_same_deployment_keeps_a_mid_conversation_system {"role": "assistant", "content": [{"type": "text", "text": "One."}]}, {"role": "user", "content": [{"type": "text", "text": "Again"}]}, ], body + + +_GENERATED: Final[dict[str, JsonValue]] = { + "id": "msg_generated", + "type": "message", + "role": "assistant", + "model": _MODEL, + "content": [{"type": "text", "text": "done"}], + "stop_reason": "end_turn", + "stop_sequence": None, + "usage": {"input_tokens": 12, "output_tokens": 3}, +} + + +def _generating(provider: _Provider) -> Callable[[Request], Reply]: + def respond(request: Request) -> Reply: + if request.target == provider.target.removesuffix("/count_tokens"): + return _json_reply(200, _GENERATED) + return _peer(provider)(request) + + return respond + + +@pytest.mark.parametrize("request_body", RESPONSES_TOOL_USE.values(), ids=RESPONSES_TOOL_USE.keys()) +def test_responses_input_tokens_counts_what_responses_inference_sends( + deployment: _Deployment, gateway: Gateway, request_body: dict[str, JsonValue] +) -> None: + with wire_server(_generating(deployment.provider), port=deployment.port) as peer: + generated: Final = gateway.request( + "POST", "/v1/responses", {**request_body, "model": deployment.model, "max_output_tokens": 16} + ) + assert generated.status_code == 200, generated.text + response: Final = gateway.request( + "POST", "/v1/responses/input_tokens", {**request_body, "model": deployment.model} + ) + assert _payload(response)["input_tokens"] == _COUNT, response.text + inference, counted = (counted_fields(JSON_OBJECT.validate_json(request.body)) for request in peer.drain()) + assert counted == inference, (counted, inference) + + +def _inference_and_count(peer: Wire) -> tuple[dict[str, JsonValue], dict[str, JsonValue]]: + inference, counted = (JSON_OBJECT.validate_json(request.body) for request in peer.drain()) + return inference, counted + + +@pytest.mark.parametrize("request_body", RESPONSES_REQUEST_OPTIONS.values(), ids=RESPONSES_REQUEST_OPTIONS.keys()) +def test_responses_input_tokens_counts_the_request_options_responses_inference_sends( + deployment: _Deployment, gateway: Gateway, request_body: dict[str, JsonValue] +) -> None: + with wire_server(_generating(deployment.provider), port=deployment.port) as peer: + generated: Final = gateway.request( + "POST", "/v1/responses", {**request_body, "model": deployment.model, "max_output_tokens": 4096} + ) + assert generated.status_code == 200, generated.text + response: Final = gateway.request( + "POST", "/v1/responses/input_tokens", {**request_body, "model": deployment.model} + ) + assert _payload(response)["input_tokens"] == _COUNT, response.text + inference, counted = _inference_and_count(peer) + assert count_request_fields(counted) == inference_count_fields(inference), (counted, inference) + + +def _text_blocks(message: JsonValue) -> JsonValue: + if not isinstance(message, dict) or not isinstance(message.get("content"), str): + return message + return {**message, "content": [{"type": "text", "text": message["content"]}]} + + +def _with_text_blocks(fields: dict[str, JsonValue]) -> dict[str, JsonValue]: + messages: Final = fields["messages"] + assert isinstance(messages, list), fields + return {**fields, "messages": [_text_blocks(message) for message in messages]} + + +def test_responses_input_tokens_leaves_tool_choice_out_when_drop_params_drops_every_tool( + deployment: _Deployment, gateway: Gateway +) -> None: + request_body: Final[dict[str, JsonValue]] = { + "input": WEATHER_QUESTION, + "tools": [5], + "tool_choice": "required", + "drop_params": True, + } + with wire_server(_generating(deployment.provider), port=deployment.port) as peer: + generated: Final = gateway.request( + "POST", "/v1/responses", {**request_body, "model": deployment.model, "max_output_tokens": 16} + ) + assert generated.status_code == 200, generated.text + response: Final = gateway.request( + "POST", "/v1/responses/input_tokens", {**request_body, "model": deployment.model} + ) + assert _payload(response)["input_tokens"] == _COUNT, response.text + inference, counted = _inference_and_count(peer) + assert "tools" not in counted and "tool_choice" not in counted, counted + assert _with_text_blocks(count_request_fields(counted)) == inference_count_fields(inference), ( + counted, + inference, + ) + + +def _config_storing_prompts(directory: Path) -> Path: + config: Final = object_value(yaml.safe_load(Path("tests/integration/proxy_config.yaml").read_text())) + general_settings: Final = object_value(config["general_settings"]) + path: Final = directory / "store-prompts.yaml" + path.write_text( + yaml.safe_dump({**config, "general_settings": {**general_settings, "store_prompts_in_spend_logs": True}}) + ) + return path + + +def _replying(answer: str) -> Callable[[Request], Reply]: + def respond(request: Request) -> Reply: + if request.target == _ANTHROPIC.target: + return _counted(request) + if request.target == "/v1/messages": + return _json_reply( + 200, + {**_GENERATED, "id": f"msg_{uuid.uuid4().hex}", "content": [{"type": "text", "text": answer}]}, + ) + return _json_reply(404, {"error": f"unscripted target {request.target}"}) + + return respond + + +def _spend_rows_with(prompt_gateway: Gateway, marker: str) -> list[dict[str, JsonValue]]: + return prompt_gateway.rows( + 'SELECT request_id FROM "LiteLLM_SpendLogs" WHERE proxy_server_request::text LIKE %s', (f"%{marker}%",) + ) + + +@pytest.mark.timeout(2 * graceful_stop_seconds() + 120) +def test_responses_input_tokens_counts_the_turns_previous_response_id_replays(gateway: Gateway, tmp_path: Path) -> None: + first_prompt: Final = f"Remember the number {uuid.uuid4().hex}" + answer: Final = f"Remembered {uuid.uuid4().hex}" + follow_up: Final[dict[str, JsonValue]] = {"input": "What number did I ask you to remember?"} + port: Final = allocate_port() + with ( + wire_server(_replying(answer), port=port) as peer, + owned_proxy(gateway, tmp_path, {}, config=_config_storing_prompts(tmp_path), workers=1) as prompt_gateway, + prompt_gateway.scenario() as scenario, + ): + model: Final = scenario.model( + model_info=None, model=f"anthropic/{_MODEL}", api_base=f"http://127.0.0.1:{port}", api_key=_API_KEY + ) + first: Final = prompt_gateway.request( + "POST", "/v1/responses", {"model": model, "input": first_prompt, "max_output_tokens": 16} + ) + assert first.status_code == 200, first.text + previous: Final = { + **follow_up, + "model": model, + "previous_response_id": JSON_OBJECT.validate_json(first.content)["id"], + } + eventually(lambda: _spend_rows_with(prompt_gateway, first_prompt), lambda rows: len(rows) == 1, seconds=70) + response: Final = prompt_gateway.request("POST", "/v1/responses/input_tokens", previous) + assert _payload(response)["input_tokens"] == _COUNT, response.text + generated: Final = prompt_gateway.request("POST", "/v1/responses", {**previous, "max_output_tokens": 16}) + assert generated.status_code == 200, generated.text + _, counted, inference = (JSON_OBJECT.validate_json(request.body) for request in peer.drain()) + assert first_prompt in json.dumps(inference["messages"]) and answer in json.dumps(inference["messages"]) + assert counted_fields(counted) == counted_fields(inference), (counted, inference) diff --git a/tests/integration/providers/test_anthropic_refusal_stop_details_wire.py b/tests/integration/providers/test_anthropic_refusal_stop_details_wire.py index b47dd242429..cd42e816ee3 100644 --- a/tests/integration/providers/test_anthropic_refusal_stop_details_wire.py +++ b/tests/integration/providers/test_anthropic_refusal_stop_details_wire.py @@ -896,7 +896,7 @@ def test_failing_sinks_get_one_attempt_each_and_the_proxy_stays_healthy(rig: Rig assert (readiness.status_code, readiness.json()["status"]) == (200, "healthy"), readiness.text -def test_unauthenticated_refusal_request_never_reaches_the_upstream_or_the_sink(rig: Rig) -> None: +def test_unauthenticated_refusal_request_never_reaches_upstream_and_logs_failure(rig: Rig) -> None: with rig.gateway.scenario() as scenario: model: Final = _deployment(scenario, "anthropic", rig) stranger: Final = "sk-not-a-virtual-key-" + _marker() @@ -908,7 +908,9 @@ def test_unauthenticated_refusal_request_never_reaches_the_upstream_or_the_sink( ) assert response.status_code == 401, response.text assert _targets(rig.wire) == () - assert rig.sink.for_key(stranger) == () + failures: Final = rig.sink.await_key(stranger) + assert len(failures) == 1, failures + assert failures[0]["status"] == "failure", failures[0] @pytest.mark.parametrize("fixture", ["null", "missing"]) diff --git a/tests/integration/providers/test_azure_reasoning_effort_none_wire.py b/tests/integration/providers/test_azure_reasoning_effort_none_wire.py index c95e497c672..cec50c5ea47 100644 --- a/tests/integration/providers/test_azure_reasoning_effort_none_wire.py +++ b/tests/integration/providers/test_azure_reasoning_effort_none_wire.py @@ -1,3 +1,4 @@ +import re from typing import Final from integration._support.client import Gateway @@ -30,7 +31,7 @@ def test_reasoning_effort_none_is_rejected_by_litellm_before_reaching_azure(gate ) assert response.status_code == 400, response.text - assert "reasoning_effort='none'" in response.text, response.text + assert re.search(r"reasoning_effort='?none\b", response.text), response.text assert wire.drain() == () diff --git a/tests/integration/providers/test_bedrock_mantle_count_tokens_wire.py b/tests/integration/providers/test_bedrock_mantle_count_tokens_wire.py index ab0c35d0ca4..a4542f1f604 100644 --- a/tests/integration/providers/test_bedrock_mantle_count_tokens_wire.py +++ b/tests/integration/providers/test_bedrock_mantle_count_tokens_wire.py @@ -32,9 +32,12 @@ from integration.providers._count_tokens_system_lift import ( LIFTED, MID_SYSTEM, REMINDER, + RESPONSES_TOOLS, STRING_CASE, USER, USER_TEXT, + WEATHER_QUESTION, + WEATHER_SCHEMA, LiftCase, accepts_count_body, async_openai_client, @@ -70,6 +73,18 @@ _SCRIPTED_STATUS: Final = re.compile(r"status=(\d{3})") _STARTED_WORKER: Final = re.compile(r"Started server process \[(\d+)\]") _JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue]) _JSON_LIST: Final = TypeAdapter(list[JsonValue]) +_COST_MAP_PATH: Final = Path(__file__).resolve().parents[3] / "model_prices_and_context_window.json" +_COST_MAP: Final = TypeAdapter(dict[str, dict[str, JsonValue]]) + + +def _count_model_source(model: str) -> dict[str, JsonValue]: + cost_map: Final = _COST_MAP.validate_json(_COST_MAP_PATH.read_bytes()) + token_count_model: Final = cost_map[model].get("token_count_model") + assert isinstance(token_count_model, dict), model + count_model: Final = token_count_model.get("model") + assert isinstance(count_model, str), token_count_model + return {"litellm_count_source": "token_count_model", "litellm_count_model": count_model} + _SDK_MESSAGES: Final[list[MessageParam]] = [{"role": "user", "content": "Count this message"}] _MESSAGES: Final = _JSON_LIST.validate_json(json.dumps(_SDK_MESSAGES)) @@ -94,6 +109,32 @@ _GEMINI_BODY: Final[dict[str, JsonValue]] = {"contents": [{"role": "user", "part _GEMINI_MESSAGES: Final[list[JsonValue]] = [{"role": "user", "content": "Count this"}] +def _runtime_count_body(prompt: str, include_system_and_tools: bool = False) -> dict[str, JsonValue]: + tool: Final = _SDK_TOOLS[0] + converse: Final[dict[str, JsonValue]] = { + "messages": [{"role": "user", "content": [{"text": prompt}]}], + **( + { + "system": [{"text": _SYSTEM}], + "toolConfig": { + "tools": [ + { + "toolSpec": { + "name": tool["name"], + "description": tool["description"], + "inputSchema": {"json": tool["input_schema"]}, + } + } + ] + }, + } + if include_system_and_tools + else {} + ), + } + return {"input": {"converse": converse}} + + def _mantle_body(**fields: JsonValue) -> dict[str, JsonValue]: return {"model": _OPUS_BASE, "messages": _MESSAGES, **fields} @@ -223,7 +264,11 @@ def _owned_config(path: Path, runtime_url: str, settings: Mapping[str, JsonValue { **config, "model_list": [ - {"model_name": name, "litellm_params": _litellm_params(model, runtime_url)} + { + "model_name": name, + "litellm_params": _litellm_params(model, runtime_url), + "model_info": {"token_count_model": {}}, + } for name, model in _OWNED_MODELS.items() ], "litellm_settings": {**litellm_settings, **settings}, @@ -233,7 +278,11 @@ def _owned_config(path: Path, runtime_url: str, settings: Mapping[str, JsonValue return path -def _deployment(scenario: Scenario, api_base: str, model: str = _OPUS) -> str: +def _fallback_deployment(scenario: Scenario, api_base: str, model: str = _OPUS) -> str: + return scenario.model(model_info={"token_count_model": {}}, api_key=None, **_litellm_params(model, api_base)) + + +def _metadata_deployment(scenario: Scenario, api_base: str, model: str = _OPUS) -> str: return scenario.model(model_info=None, api_key=None, **_litellm_params(model, api_base)) @@ -290,6 +339,14 @@ def _runtime_count_targets(wire: Wire) -> tuple[str, ...]: return tuple(target_of(request) for request in counts) +def _runtime_count_requests(wire: Wire) -> tuple[tuple[str, dict[str, JsonValue]], ...]: + counts: Final = tuple(request for request in wire.drain() if _COUNT_TARGET.match(target_of(request))) + for request in counts: + assert request.method == "POST", request.method + _assert_sigv4(request) + return tuple((target_of(request), _JSON_OBJECT.validate_json(request.body)) for request in counts) + + def _clients(stack: ExitStack, base_url: str, count: int, timeout: float = 30) -> tuple[httpx.Client, ...]: return tuple( stack.enter_context(httpx.Client(base_url=base_url, timeout=timeout, trust_env=False)) for _ in range(count) @@ -376,7 +433,7 @@ def test_messages_count_tokens_counts_through_mantle_when_the_runtime_cannot( wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = _count(gateway, {**_bare(model), "system": system, "tools": _TOOLS}) assert _payload(response) == {"input_tokens": _MANTLE_COUNT, "litellm_count_source": "provider"}, response.text assert _runtime_count_targets(runtime) == (f"/model/{_OPUS_BASE}/count-tokens",) @@ -392,7 +449,7 @@ def test_messages_count_tokens_without_system_or_tools_sends_a_bare_body_to_mant wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = _count(gateway, _bare(model)) assert _payload(response) == {"input_tokens": _MANTLE_COUNT, "litellm_count_source": "provider"}, response.text assert len(_runtime_count_targets(runtime)) == 1 @@ -408,7 +465,7 @@ def test_utils_token_counter_call_endpoint_reports_the_mantle_tokenizer( wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = gateway.request( "POST", "/utils/token_counter", _full(model), params={"call_endpoint": "true"} ) @@ -427,14 +484,14 @@ def test_gemini_count_tokens_route_reports_the_mantle_total(counting_proxy: Owne wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _metadata_deployment(scenario, runtime.url) response: Final = gateway.request("POST", f"/v1beta/models/{model}:countTokens", _GEMINI_BODY) assert _payload(response) == { "totalTokens": _MANTLE_COUNT, "promptTokensDetails": [], - "litellm_count_source": "provider", + **_count_model_source(_OPUS), }, response.text - assert len(_runtime_count_targets(runtime)) == 1 + assert _runtime_count_requests(runtime) == () assert _mantle_bodies(mantle) == ({"model": _OPUS_BASE, "messages": _GEMINI_MESSAGES},) @@ -447,14 +504,16 @@ def test_gemini_count_tokens_route_reports_the_runtime_total_for_a_model_bedrock wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url, _SONNET) + model: Final = _metadata_deployment(scenario, runtime.url, _SONNET) response: Final = gateway.request("POST", f"/v1beta/models/{model}:countTokens", _GEMINI_BODY) assert _payload(response) == { "totalTokens": _RUNTIME_COUNT, "promptTokensDetails": [], - "litellm_count_source": "provider", + **_count_model_source(_SONNET), }, response.text - assert _runtime_count_targets(runtime) == (f"/model/{_SONNET}/count-tokens",) + assert _runtime_count_requests(runtime) == ( + (f"/model/{_SONNET}/count-tokens", _runtime_count_body("Count this")), + ) assert mantle.drain() == () @@ -466,7 +525,7 @@ def test_runtime_404_on_claude_falls_back_to_mantle(counting_proxy: OwnedProxy, wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = _count(gateway, {**_bare(model), "system": system, "tools": _TOOLS}) assert _payload(response) == {"input_tokens": _MANTLE_COUNT, "litellm_count_source": "provider"}, response.text assert len(_runtime_count_targets(runtime)) == 1 @@ -481,7 +540,7 @@ def test_runtime_404_and_mantle_404_surface_provider_error(counting_proxy: Owned wire_server(_mantle(_rejecting(404)), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = _count(gateway, {**_bare(model), "system": system, "tools": _TOOLS}) assert response.status_code == 404, response.text assert _REJECTION in response.text @@ -496,7 +555,7 @@ def test_runtime_404_on_nova_does_not_call_mantle(counting_proxy: OwnedProxy, ma wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url, _NOVA) + model: Final = _fallback_deployment(scenario, runtime.url, _NOVA) body: Final = {**_bare(model), "messages": [{"role": "user", "content": "status=404"}]} response: Final = _count(gateway, body) assert response.status_code == 404, response.text @@ -504,9 +563,7 @@ def test_runtime_404_on_nova_does_not_call_mantle(counting_proxy: OwnedProxy, ma assert mantle.drain() == () -def test_google_count_tokens_forwards_system_and_tools_to_mantle( - counting_proxy: OwnedProxy, mantle_port: int -) -> None: +def test_google_count_tokens_forwards_system_and_tools_to_mantle(counting_proxy: OwnedProxy, mantle_port: int) -> None: gateway: Final = counting_proxy.gateway system_text: Final = "Use the provided tool" tool_schema: Final = {"type": "object", "properties": {"location": {"type": "string"}}} @@ -526,7 +583,7 @@ def test_google_count_tokens_forwards_system_and_tools_to_mantle( wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = gateway.request("POST", f"/v1beta/models/{model}:countTokens", body) assert _payload(response) == { "totalTokens": _MANTLE_COUNT, @@ -575,7 +632,7 @@ def test_google_count_tokens_normalizes_uppercase_parameters_for_mantle( wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = gateway.request("POST", f"/v1beta/models/{model}:countTokens", body) assert _payload(response) == { "totalTokens": _MANTLE_COUNT, @@ -607,7 +664,7 @@ def test_responses_input_tokens_counts_through_mantle(counting_proxy: OwnedProxy wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = gateway.request( "POST", "/v1/responses/input_tokens", {"model": model, "input": "Count this message"} ) @@ -627,7 +684,7 @@ def test_anthropic_sdk_count_tokens_counts_through_mantle(counting_proxy: OwnedP wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) counted: Final = _anthropic_client(gateway).messages.count_tokens( model=model, messages=_SDK_MESSAGES, system=_SYSTEM, tools=_SDK_TOOLS ) @@ -643,7 +700,7 @@ def test_async_anthropic_sdk_count_tokens_counts_through_mantle(counting_proxy: wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) counted: Final = asyncio.run( _async_anthropic_client(gateway).messages.count_tokens(model=model, messages=_SDK_MESSAGES, system=_SYSTEM) ) @@ -659,17 +716,36 @@ def test_model_the_runtime_counts_never_reaches_mantle(counting_proxy: OwnedProx wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url, _SONNET) + model: Final = _metadata_deployment(scenario, runtime.url, _SONNET) assert _payload(_count(gateway, _full(model))) == { "input_tokens": _RUNTIME_COUNT, - "litellm_count_source": "provider", + **_count_model_source(_SONNET), } detailed: Final = gateway.request( "POST", "/utils/token_counter", _full(model), params={"call_endpoint": "true"} ) payload: Final = _payload(detailed) - assert (payload["total_tokens"], payload["tokenizer_type"]) == (_RUNTIME_COUNT, "bedrock_api"), detailed.text - assert _runtime_count_targets(runtime) == (f"/model/{_SONNET}/count-tokens",) * 2 + assert payload == { + "total_tokens": _RUNTIME_COUNT, + "request_model": model, + "model_used": _count_model_source(_SONNET)["litellm_count_model"], + "tokenizer_type": "bedrock_api", + "count_source": "token_count_model", + "original_response": {"input_tokens": _RUNTIME_COUNT}, + "error": False, + "error_message": None, + "status_code": None, + }, detailed.text + assert _runtime_count_requests(runtime) == ( + ( + f"/model/{_SONNET}/count-tokens", + _runtime_count_body("Count this message", include_system_and_tools=True), + ), + ( + f"/model/{_SONNET}/count-tokens", + _runtime_count_body("Count this message", include_system_and_tools=True), + ), + ) assert mantle.drain() == () @@ -682,7 +758,7 @@ def test_non_claude_model_the_runtime_cannot_count_surfaces_the_error_without_ma wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url, _NOVA) + model: Final = _fallback_deployment(scenario, runtime.url, _NOVA) response: Final = _count(gateway, _bare(model)) assert response.status_code == 400, response.text assert _UNSUPPORTED in response.text and "input_tokens" not in response.text, response.text @@ -697,7 +773,7 @@ def test_runtime_403_on_a_claude_model_never_reaches_mantle(counting_proxy: Owne wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) body: Final[dict[str, JsonValue]] = { "model": model, "messages": [{"role": "user", "content": "status=403 Count this message"}], @@ -712,7 +788,7 @@ def test_runtime_403_on_a_claude_model_never_reaches_mantle(counting_proxy: Owne def test_unreachable_runtime_surfaces_the_error_without_mantle(counting_proxy: OwnedProxy, mantle_port: int) -> None: gateway: Final = counting_proxy.gateway with wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario: - model: Final = _deployment(scenario, _closed_port_url()) + model: Final = _fallback_deployment(scenario, _closed_port_url()) response: Final = _count(gateway, _full(model)) assert 500 <= response.status_code < 600, response.text assert "input_tokens" not in response.text, response.text @@ -728,7 +804,7 @@ def test_bedrock_passthrough_count_tokens_still_answers_the_runtime_rejection( wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = gateway.request("POST", "/bedrock/v1/messages/count_tokens", _full(model)) assert response.status_code == 400, response.text assert _UNSUPPORTED in response.text and "input_tokens" not in response.text, response.text @@ -745,7 +821,7 @@ def test_responses_input_tokens_with_instructions_counts_through_mantle( wire_server(_mantle(_strict), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = gateway.request( "POST", "/v1/responses/input_tokens", @@ -770,7 +846,7 @@ def test_messages_count_tokens_lifts_the_leading_system_run_for_mantle( wire_server(_mantle(_strict), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = _count(gateway, count_request(model, case)) assert _payload(response) == {"input_tokens": _MANTLE_COUNT, "litellm_count_source": "provider"}, response.text assert len(_runtime_count_targets(runtime)) == 1 @@ -786,7 +862,7 @@ def test_anthropic_sdk_count_tokens_lifts_the_leading_system_through_mantle( wire_server(_mantle(_strict), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) counted: Final = _anthropic_client(gateway).messages.count_tokens(model=model, messages=_LIFT_SDK_MESSAGES) assert counted.input_tokens == _MANTLE_COUNT, counted assert len(_runtime_count_targets(runtime)) == 1 @@ -802,7 +878,7 @@ def test_async_anthropic_sdk_count_tokens_lifts_the_leading_system_through_mantl wire_server(_mantle(_strict), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) counted: Final = asyncio.run( _async_anthropic_client(gateway).messages.count_tokens(model=model, messages=_LIFT_SDK_MESSAGES) ) @@ -820,7 +896,7 @@ def test_utils_token_counter_call_endpoint_counts_a_leading_system_through_mantl wire_server(_mantle(_strict), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = gateway.request( "POST", "/utils/token_counter", count_request(model, STRING_CASE), params={"call_endpoint": "true"} ) @@ -841,7 +917,7 @@ def test_openai_sdk_input_tokens_lifts_instructions_through_mantle( wire_server(_mantle(_strict), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) counted: Final = openai_client(gateway).responses.input_tokens.count( model=model, input=USER_TEXT, instructions=INSTRUCTION ) @@ -859,7 +935,7 @@ def test_async_openai_sdk_input_tokens_lifts_instructions_through_mantle( wire_server(_mantle(_strict), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) counted: Final = asyncio.run( async_openai_client(gateway).responses.input_tokens.count( model=model, input=USER_TEXT, instructions=INSTRUCTION @@ -879,7 +955,7 @@ def test_responses_input_tokens_lifts_instructions_ahead_of_a_leading_system_ite wire_server(_mantle(_strict), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = gateway.request( "POST", "/v1/responses/input_tokens", @@ -903,7 +979,7 @@ def test_messages_count_tokens_forwards_tools_beside_the_lifted_system_to_mantle wire_server(_mantle(_strict), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = _count(gateway, {**count_request(model, STRING_CASE), "tools": _TOOLS}) assert _payload(response) == {"input_tokens": _MANTLE_COUNT, "litellm_count_source": "provider"}, response.text assert len(_runtime_count_targets(runtime)) == 1 @@ -919,7 +995,7 @@ def test_messages_count_tokens_keeps_a_mid_conversation_system_in_place_for_mant wire_server(_mantle(_strict), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) body: Final[dict[str, JsonValue]] = { "model": model, "messages": [LEADING, USER, MID_SYSTEM, ASSISTANT, FOLLOW_UP], @@ -941,7 +1017,7 @@ def test_messages_count_tokens_surfaces_the_mantle_error_when_every_message_is_s wire_server(_mantle(_strict), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) body: Final[dict[str, JsonValue]] = {"model": model, "messages": [LEADING]} response: Final = _count(gateway, body) assert response.status_code == 400, response.text @@ -959,7 +1035,7 @@ def test_messages_count_tokens_surfaces_the_mantle_error_beside_a_non_text_syste wire_server(_mantle(_strict), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = _count(gateway, {**count_request(model, STRING_CASE), "system": 5}) assert response.status_code == 400, response.text assert "input_tokens" not in response.text, response.text @@ -976,7 +1052,7 @@ def test_messages_count_tokens_repeated_request_lifts_the_leading_system_each_ti wire_server(_mantle(_strict), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) answers: Final = tuple(_payload(_count(gateway, count_request(model, STRING_CASE))) for _ in range(2)) assert answers == ({"input_tokens": _MANTLE_COUNT, "litellm_count_source": "provider"},) * 2 assert _runtime_count_targets(runtime) == (f"/model/{_OPUS_BASE}/count-tokens",) * 2 @@ -992,7 +1068,7 @@ def test_messages_count_tokens_surfaces_the_counting_error_for_a_leading_system_ wire_server(_mantle(_strict), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) body: Final[dict[str, JsonValue]] = {"model": model, "messages": [{"role": "system"}, USER]} response: Final = _count(gateway, body) assert 500 <= response.status_code < 600, response.text @@ -1015,7 +1091,7 @@ def test_messages_count_tokens_duplicate_messages_key_lifts_the_last_value_for_m wire_server(_mantle(_strict), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) first: Final = json.dumps([USER]) last: Final = json.dumps([LEADING, USER]) response: Final = gateway.client.post( @@ -1064,7 +1140,7 @@ def test_mantle_outage_between_concurrent_lifted_waves_errors_then_recovers( pool: Final = stack.enter_context(ThreadPoolExecutor(max_workers=len(clients))) runtime: Final = stack.enter_context(wire_server(_runtime)) scenario: Final = stack.enter_context(gateway.scenario()) - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) body: Final = count_request(model, STRING_CASE) def count(client: httpx.Client) -> tuple[int, JsonValue]: @@ -1092,7 +1168,7 @@ def test_messages_count_tokens_surfaces_the_mantle_status_when_mantle_errors( wire_server(_mantle(_rejecting(status)), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = _count(gateway, _full(model)) assert response.status_code == status, response.text assert "input_tokens" not in response.text, response.text @@ -1114,7 +1190,7 @@ def test_messages_count_tokens_errors_when_mantle_answers_without_input_tokens( wire_server(_mantle(lambda _request: Reply(body=body)), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = _count(gateway, _bare(model)) assert 500 <= response.status_code < 600, response.text assert len(_runtime_count_targets(runtime)) == 1 @@ -1124,16 +1200,14 @@ def test_messages_count_tokens_errors_when_mantle_answers_without_input_tokens( def test_messages_count_tokens_errors_when_mantle_is_unreachable(counting_proxy: OwnedProxy) -> None: gateway: Final = counting_proxy.gateway with wire_server(_runtime) as runtime, gateway.scenario() as scenario: - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = _count(gateway, _full(model)) assert 500 <= response.status_code < 600, response.text assert "input_tokens" not in response.text, response.text assert len(_runtime_count_targets(runtime)) == 1 -def test_messages_count_tokens_errors_when_mantle_never_answers( - counting_proxy: OwnedProxy, mantle_port: int -) -> None: +def test_messages_count_tokens_errors_when_mantle_never_answers(counting_proxy: OwnedProxy, mantle_port: int) -> None: gateway: Final = counting_proxy.gateway held: Final[SimpleQueue[str]] = SimpleQueue() release: Final = threading.Event() @@ -1150,7 +1224,7 @@ def test_messages_count_tokens_errors_when_mantle_never_answers( mantle: Final = stack.enter_context(wire_server(_mantle(hold), port=mantle_port)) stack.callback(release.set) scenario: Final = stack.enter_context(gateway.scenario()) - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) body: Final = _full(model) future: Final = pool.submit(_counted_on, client, gateway.key, body) eventually(held.qsize, lambda size: size == 1, seconds=30) @@ -1172,7 +1246,7 @@ def test_messages_count_tokens_surfaces_the_mantle_error_for_a_non_text_system( wire_server(_mantle(_strict), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = _count(gateway, {**_bare(model), "system": 5}) assert response.status_code == 400, response.text assert "input_tokens" not in response.text, response.text @@ -1194,7 +1268,7 @@ def test_messages_count_tokens_rejects_malformed_tools_without_calling_either_pe wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) refused: Final = _count(gateway, {**_bare(model), "tools": tools}) assert refused.status_code == 400, refused.text assert object_value(_JSON_OBJECT.validate_json(refused.content)["error"])["type"] == "invalid_request_error" @@ -1213,7 +1287,7 @@ def test_messages_count_tokens_without_messages_is_rejected( wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = _count(gateway, {"model": model, "system": _SYSTEM, "tools": _TOOLS, **fields}) assert response.status_code == 400, response.text assert "messages parameter is required" in response.text, response.text @@ -1234,7 +1308,7 @@ def test_messages_count_tokens_unauthenticated_request_never_reaches_either_peer wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = gateway.request( "POST", "/v1/messages/count_tokens", {**_full(model), **fields}, key="sk-not-a-key-this-proxy-issued" ) @@ -1253,7 +1327,7 @@ def test_messages_count_tokens_forwards_a_5kb_system_verbatim_to_mantle( wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = _count(gateway, {**_bare(model), "system": system}) assert _payload(response) == {"input_tokens": _MANTLE_COUNT, "litellm_count_source": "provider"}, response.text assert len(_runtime_count_targets(runtime)) == 1 @@ -1269,7 +1343,7 @@ def test_messages_count_tokens_duplicate_system_and_tools_keys_forward_one_value wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) fields: Final = f'"system": {json.dumps(_SYSTEM)}, "tools": {json.dumps(_TOOLS)}' response: Final = gateway.client.post( "/v1/messages/count_tokens", @@ -1292,7 +1366,7 @@ def test_messages_count_tokens_leaves_empty_tools_and_system_out_of_the_mantle_b wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = _count(gateway, {**_bare(model), "tools": [], "system": ""}) assert _payload(response) == {"input_tokens": _MANTLE_COUNT, "litellm_count_source": "provider"}, response.text assert len(_runtime_count_targets(runtime)) == 1 @@ -1308,7 +1382,7 @@ def test_messages_count_tokens_repeated_request_reaches_both_peers_each_time( wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) answers: Final = tuple(_payload(_count(gateway, _bare(model))) for _ in range(2)) assert answers == ({"input_tokens": _MANTLE_COUNT, "litellm_count_source": "provider"},) * 2 assert _runtime_count_targets(runtime) == (f"/model/{_OPUS_BASE}/count-tokens",) * 2 @@ -1364,7 +1438,7 @@ def test_mantle_outage_between_concurrent_waves_errors_then_recovers( pool: Final = stack.enter_context(ThreadPoolExecutor(max_workers=len(clients))) runtime: Final = stack.enter_context(wire_server(_runtime)) scenario: Final = stack.enter_context(gateway.scenario()) - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) body: Final = _full(model) def generate_then_count(client: httpx.Client) -> tuple[int, int, JsonValue]: @@ -1398,7 +1472,7 @@ def test_slow_mantle_holds_concurrent_counts_without_stalling_the_proxy( scenario: Final = stack.enter_context(gateway.scenario()) pool: Final = stack.enter_context(ThreadPoolExecutor(max_workers=len(clients))) stack.callback(release.set) - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) futures: Final = tuple( pool.submit(_generated_then_counted, client, gateway.key, model, _full(model)) for client in clients ) @@ -1495,7 +1569,7 @@ def test_chat_completions_on_the_same_deployment_still_generate( wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = gateway.request( "POST", "/v1/chat/completions", @@ -1523,7 +1597,7 @@ def test_messages_endpoint_on_the_same_deployment_still_generates(counting_proxy wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = gateway.request( "POST", "/v1/messages", @@ -1546,7 +1620,7 @@ def test_responses_endpoint_on_the_same_deployment_still_generates( wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) response: Final = gateway.request("POST", "/v1/responses", {"model": model, "input": f"marker-{marker}"}) assert response.status_code == 200, response.text assert answer(marker) in response.text, response.text @@ -1562,6 +1636,110 @@ def test_utils_token_counter_local_mode_never_calls_either_peer(counting_proxy: wire_server(_mantle(), port=mantle_port) as mantle, gateway.scenario() as scenario, ): - model: Final = _deployment(scenario, runtime.url) + model: Final = _fallback_deployment(scenario, runtime.url) assert _local_count(gateway, _full(model)) > 0 assert runtime.drain() == () and mantle.drain() == () + + +_FORCED_TOOL_CHOICE: Final[dict[str, JsonValue]] = { + "input": WEATHER_QUESTION, + "tools": RESPONSES_TOOLS, + "tool_choice": {"type": "function", "name": "get_weather"}, +} +_CHAT_TOOLS: Final[list[JsonValue]] = [ + { + "type": "function", + "function": { + "name": "get_weather", + "description": "Look up the current weather for a city", + "parameters": WEATHER_SCHEMA, + }, + } +] +_WEATHER_MESSAGES: Final[list[JsonValue]] = [{"role": "user", "content": WEATHER_QUESTION}] +_TOOL_USE_FIELDS: Final = ("tools", "tool_choice") + + +def _tool_use_fields(body: Mapping[str, JsonValue]) -> dict[str, JsonValue]: + return {field: body[field] for field in _TOOL_USE_FIELDS if field in body} + + +def _converse_count_tools(request: Request) -> JsonValue: + count_input: Final = _JSON_OBJECT.validate_python(_JSON_OBJECT.validate_json(request.body)["input"]) + converse: Final = _JSON_OBJECT.validate_python(count_input["converse"]) + return _JSON_OBJECT.validate_python(converse["toolConfig"])["tools"] + + +def _requests_to(requests: Sequence[Request], pattern: re.Pattern[str]) -> tuple[Request, ...]: + return tuple(request for request in requests if pattern.match(target_of(request))) + + +def test_responses_input_tokens_sends_mantle_the_tool_use_invoke_inference_sends( + counting_proxy: OwnedProxy, mantle_port: int +) -> None: + gateway: Final = counting_proxy.gateway + with ( + wire_server(_runtime) as runtime, + wire_server(_mantle(), port=mantle_port) as mantle, + gateway.scenario() as scenario, + ): + counted_model: Final = _metadata_deployment(scenario, runtime.url) + invoked_model: Final = _metadata_deployment(scenario, runtime.url, f"invoke/{_OPUS}") + generated: Final = gateway.request( + "POST", "/v1/responses", {**_FORCED_TOOL_CHOICE, "model": invoked_model, "max_output_tokens": 16} + ) + assert generated.status_code == 200, generated.text + response: Final = gateway.request( + "POST", "/v1/responses/input_tokens", {**_FORCED_TOOL_CHOICE, "model": counted_model} + ) + assert _payload(response)["input_tokens"] == _MANTLE_COUNT, response.text + requests: Final = runtime.drain() + (invoked,) = _requests_to(requests, _INVOKE_TARGET) + (mantle_count,) = _mantle_bodies(mantle) + expected: Final = _tool_use_fields(_JSON_OBJECT.validate_json(invoked.body)) + assert set(expected) == set(_TOOL_USE_FIELDS), expected + assert _requests_to(requests, _COUNT_TARGET) == () + assert _tool_use_fields(mantle_count) == expected, mantle_count + + +def _counting_every_model(request: Request) -> Reply: + if _COUNT_TARGET.match(target_of(request)): + return _json_reply(200, {"inputTokens": _RUNTIME_COUNT}) + return runtime_generation(request) + + +_NOVA_COUNTS: Final[Mapping[str, tuple[str, dict[str, JsonValue], str]]] = MappingProxyType( + { + "utils-token-counter": ( + "/utils/token_counter?call_endpoint=true", + {"messages": _WEATHER_MESSAGES, "tools": _CHAT_TOOLS}, + "total_tokens", + ), + "responses-input-tokens": ( + "/v1/responses/input_tokens", + {"input": WEATHER_QUESTION, "tools": RESPONSES_TOOLS}, + "input_tokens", + ), + } +) + + +@pytest.mark.parametrize("route", _NOVA_COUNTS.keys()) +def test_nova_count_sends_the_tool_specs_converse_inference_sends(counting_proxy: OwnedProxy, route: str) -> None: + path, body, count_field = _NOVA_COUNTS[route] + gateway: Final = counting_proxy.gateway + with wire_server(_counting_every_model) as runtime, gateway.scenario() as scenario: + model: Final = _metadata_deployment(scenario, runtime.url, _NOVA) + generated: Final = gateway.request( + "POST", + "/v1/chat/completions", + {"model": model, "messages": _WEATHER_MESSAGES, "tools": _CHAT_TOOLS, "max_tokens": 16}, + ) + assert generated.status_code == 200, generated.text + response: Final = gateway.request("POST", path, {**body, "model": model}) + assert _payload(response)[count_field] == _RUNTIME_COUNT, response.text + requests: Final = runtime.drain() + (converse,) = (request for request in requests if target_of(request) == f"/model/{_NOVA}/converse") + (counted,) = _requests_to(requests, _COUNT_TARGET) + inference_tools: Final = _JSON_OBJECT.validate_python(_JSON_OBJECT.validate_json(converse.body)["toolConfig"]) + assert _converse_count_tools(counted) == inference_tools["tools"], counted.body diff --git a/tests/integration/providers/test_bedrock_passthrough_guardrail_config_wire.py b/tests/integration/providers/test_bedrock_passthrough_guardrail_config_wire.py new file mode 100644 index 00000000000..f995a7ac83f --- /dev/null +++ b/tests/integration/providers/test_bedrock_passthrough_guardrail_config_wire.py @@ -0,0 +1,531 @@ +import base64 +import json +import uuid +from collections.abc import Iterator, Mapping +from dataclasses import dataclass +from pathlib import Path +from types import MappingProxyType +from typing import Final + +import boto3 +import pytest +import yaml +from botocore.config import Config +from botocore.exceptions import ClientError +from integration._support.budget import case_timeout_seconds +from integration._support.client import Gateway +from integration._support.process import graceful_stop_seconds, owned_proxy +from integration._support.upstream import _aws_event_frame +from integration._support.wire import Reply, Request, Wire, wire_server +from pydantic import JsonValue + +pytestmark: Final = pytest.mark.timeout(2 * graceful_stop_seconds() + 180) + +_MODEL_ID: Final = "anthropic.claude-sonnet-5-v1:0" +_EVENT_STREAM: Final = "application/vnd.amazon.eventstream" +_BLOCKED_WORD: Final = "zzzforbidden" +_BLOCKED_TEXT: Final = "Blocked by guardrail" +_VERSIONLESS_GUARDRAIL_MESSAGE: Final = "guardrailIdentifier and guardrailVersion must be provided together." +_ACTIONS: Final = ("converse", "converse-stream", "invoke", "invoke-with-response-stream") +_DEPLOYMENT_GUARDRAIL: Final[Mapping[str, str]] = { + "guardrailIdentifier": "deployment-guardrail", + "guardrailVersion": "3", + "trace": "enabled", + "streamProcessingMode": "sync", +} +_CALLER_GUARDRAIL: Final[Mapping[str, str]] = { + "guardrailIdentifier": "caller-guardrail", + "guardrailVersion": "9", + "trace": "disabled", +} +_MANTLE_KEY: Final = "scripted-mantle-key" +_CALLER_INVOKE_HEADERS: Final[Mapping[str, str]] = { + "x-pass-x-amzn-bedrock-guardrailidentifier": "caller-guardrail", + "x-pass-x-amzn-bedrock-guardrailversion": "9", + "x-pass-x-amzn-bedrock-trace": "DISABLED", +} + + +@dataclass(frozen=True, slots=True) +class Applied: + """The guardrail a request asked Bedrock for, read from where Bedrock reads it for that action.""" + + identifier: str + version: str | None + trace: str | None + stream_processing_mode: str | None + + +@dataclass(frozen=True, slots=True) +class Outcome: + """What the AWS SDK caller reads back.""" + + text: str + intervened: bool + traced_guardrail: str | None + + +def _action(request: Request) -> str: + return request.target.partition("?")[0].rsplit("/", 1)[-1] + + +def _applied(request: Request) -> Applied | None: + if _action(request).startswith("converse"): + config: Final = json.loads(request.body).get("guardrailConfig") + if config is None: + return None + return Applied( + config["guardrailIdentifier"], + config.get("guardrailVersion"), + config.get("trace"), + config.get("streamProcessingMode"), + ) + identifier: Final = request.headers.get("x-amzn-bedrock-guardrailidentifier") + if identifier is None: + return None + return Applied( + identifier, + request.headers.get("x-amzn-bedrock-guardrailversion"), + request.headers.get("x-amzn-bedrock-trace"), + None, + ) + + +def _identifier(request: Request) -> str | None: + applied: Final = _applied(request) + return None if applied is None else applied.identifier + + +def _assessment(applied: Applied) -> Mapping[str, JsonValue]: + return { + applied.identifier: { + "wordPolicy": {"customWords": [{"match": _BLOCKED_WORD, "action": "BLOCKED", "detected": True}]}, + "appliedGuardrailDetails": {"guardrailId": applied.identifier, "guardrailVersion": applied.version}, + } + } + + +def _bedrock_with_guardrails(request: Request) -> Reply: + """Bedrock's runtime as the caller sees it: the guardrail the request names blocks a prompt holding the blocked + word, answering with its message and, when the request enabled tracing, a trace naming that guardrail. A guardrail + named without a version is refused with a 400 ValidationException, as real Bedrock in us-east-1 refused it on + every one of these actions on 2026-10-19.""" + applied: Final = _applied(request) + if applied is not None and applied.version is None: + return Reply( + status=400, + body=json.dumps({"message": _VERSIONLESS_GUARDRAIL_MESSAGE}).encode(), + headers={"x-amzn-errortype": "ValidationException"}, + ) + blocked: Final = applied is not None and _BLOCKED_WORD.encode() in request.body + traced: Final = blocked and applied is not None and (applied.trace or "").lower() == "enabled" + text: Final = _BLOCKED_TEXT if blocked else "ok" + stop_reason: Final = "guardrail_intervened" if blocked else "end_turn" + usage: Final = {"inputTokens": 5, "outputTokens": 1, "totalTokens": 6} + converse_trace: Final = {"trace": {"guardrail": {"inputAssessment": _assessment(applied)}}} if traced else {} + action: Final = _action(request) + if action == "converse": + return Reply( + body=json.dumps( + { + "output": {"message": {"role": "assistant", "content": [{"text": text}]}}, + "stopReason": stop_reason, + "usage": usage, + "metrics": {"latencyMs": 3}, + **converse_trace, + } + ).encode() + ) + if action == "converse-stream": + return Reply( + chunks=( + _aws_event_frame("messageStart", {"role": "assistant"}, "sc", "u"), + _aws_event_frame("contentBlockDelta", {"delta": {"text": text}, "contentBlockIndex": 0}, "sc", "u"), + _aws_event_frame("contentBlockStop", {"contentBlockIndex": 0}, "sc", "u"), + _aws_event_frame("messageStop", {"stopReason": stop_reason}, "sc", "u"), + _aws_event_frame( + "metadata", {"usage": usage, "metrics": {"latencyMs": 3}, **converse_trace}, "sc", "u" + ), + ), + content_type=_EVENT_STREAM, + ) + message: Final = { + "id": "msg_bedrock", + "type": "message", + "role": "assistant", + "model": "claude", + "content": [{"type": "text", "text": text}], + "stop_reason": "end_turn", + "stop_sequence": None, + "usage": {"input_tokens": 5, "output_tokens": 1}, + **({"amazon-bedrock-guardrailAction": "INTERVENED"} if blocked else {}), + **({"amazon-bedrock-trace": {"guardrail": {"input": _assessment(applied)}}} if traced else {}), + } + if action == "invoke": + return Reply(body=json.dumps(message).encode()) + chunk: Final = {"bytes": base64.b64encode(json.dumps(message).encode()).decode()} + return Reply(chunks=(_aws_event_frame("chunk", chunk, "sc", "u"),), content_type=_EVENT_STREAM) + + +def _bedrock_outage(request: Request) -> Reply: + return Reply( + status=500, + body=json.dumps({"message": "scripted outage"}).encode(), + headers={"x-amzn-errortype": "InternalServerException"}, + ) + + +def _traced_guardrail(assessment: object) -> str | None: + return None if not isinstance(assessment, dict) else next(iter(assessment)) + + +def _send(runtime: object, action: str, model: str, prompt: str, caller_guardrail: bool) -> Outcome: + messages: Final = [{"role": "user", "content": [{"text": prompt}]}] + invoke_body: Final = json.dumps( + {"anthropic_version": "bedrock-2023-05-31", "max_tokens": 16, "messages": [{"role": "user", "content": prompt}]} + ) + invoke_guardrail: Final = ( + {"guardrailIdentifier": "caller-guardrail", "guardrailVersion": "9", "trace": "DISABLED"} + if caller_guardrail + else {} + ) + if action == "converse": + response: Final = getattr(runtime, "converse")( + modelId=model, + messages=messages, + **({"guardrailConfig": dict(_CALLER_GUARDRAIL)} if caller_guardrail else {}), + ) + return Outcome( + text=response["output"]["message"]["content"][0]["text"], + intervened=response["stopReason"] == "guardrail_intervened", + traced_guardrail=_traced_guardrail(response.get("trace", {}).get("guardrail", {}).get("inputAssessment")), + ) + if action == "converse-stream": + events: Final = list( + getattr(runtime, "converse_stream")( + modelId=model, + messages=messages, + **( + {"guardrailConfig": {**_CALLER_GUARDRAIL, "streamProcessingMode": "async"}} + if caller_guardrail + else {} + ), + )["stream"] + ) + (stop,) = tuple(event["messageStop"]["stopReason"] for event in events if "messageStop" in event) + (metadata,) = tuple(event["metadata"] for event in events if "metadata" in event) + return Outcome( + text="".join( + event["contentBlockDelta"]["delta"]["text"] for event in events if "contentBlockDelta" in event + ), + intervened=stop == "guardrail_intervened", + traced_guardrail=_traced_guardrail(metadata.get("trace", {}).get("guardrail", {}).get("inputAssessment")), + ) + if action == "invoke": + message: Final = json.loads( + getattr(runtime, "invoke_model")(modelId=model, body=invoke_body, **invoke_guardrail)["body"].read() + ) + else: + (message,) = tuple( + json.loads(event["chunk"]["bytes"]) + for event in getattr(runtime, "invoke_model_with_response_stream")( + modelId=model, body=invoke_body, **invoke_guardrail + )["body"] + ) + return Outcome( + text=message["content"][0]["text"], + intervened=message.get("amazon-bedrock-guardrailAction") == "INTERVENED", + traced_guardrail=_traced_guardrail(message.get("amazon-bedrock-trace", {}).get("guardrail", {}).get("input")), + ) + + +def _signed_header_names(request: Request) -> frozenset[str]: + return frozenset(request.headers["authorization"].split("SignedHeaders=")[1].split(",")[0].split(";")) + + +def _deployment(wire: Wire, guardrail_config: Mapping[str, str] | None = None) -> Mapping[str, JsonValue]: + return { + "model": f"bedrock/{_MODEL_ID}", + "api_base": wire.url, + "aws_access_key_id": "AKIASCRIPTEDPROVIDER", + "aws_secret_access_key": "scripted-secret", + "aws_region_name": "us-east-1", + "use_in_pass_through": True, + **({} if guardrail_config is None else {"guardrailConfig": dict(guardrail_config)}), + } + + +@dataclass(frozen=True, slots=True) +class Rig: + proxy: Gateway + wire: Wire + guarded_model: str + unguarded_model: str + balanced_model: str + balanced_wires: Mapping[str, Wire] + failing_model: str + failing_wire: Wire + fallback_wire: Wire + mantle_model: str + versionless_model: str + key: str + + def runtime( # noqa: ANN201 # boto3 clients are untyped + self, monkeypatch: pytest.MonkeyPatch, extra_headers: Mapping[str, str] = MappingProxyType({}) + ): + monkeypatch.setenv("AWS_BEARER_TOKEN_BEDROCK", self.key) + client: Final = boto3.client( + "bedrock-runtime", + endpoint_url=f"{str(self.proxy.client.base_url).rstrip('/')}/bedrock", + region_name="us-east-1", + config=Config(read_timeout=case_timeout_seconds(), retries={"total_max_attempts": 1}), + ) + client.meta.events.register( + "before-send.bedrock-runtime.*", + lambda request, **_: request.headers.update(extra_headers), + ) + return client + + def received(self, wire: Wire, marker: str) -> tuple[Request, ...]: + return tuple(request for request in wire.drain() if marker.encode() in request.body) + + +@pytest.fixture(scope="module") +def rig(session_gateway: Gateway, tmp_path_factory: pytest.TempPathFactory) -> Iterator[Rig]: + suffix: Final = uuid.uuid4().hex[:12] + guarded_model: Final = f"bedrock-guarded-{suffix}" + unguarded_model: Final = f"bedrock-unguarded-{suffix}" + balanced_model: Final = f"bedrock-balanced-{suffix}" + failing_model: Final = f"bedrock-failing-{suffix}" + fallback_model: Final = f"bedrock-fallback-{suffix}" + mantle_model: Final = f"bedrock-mantle-{suffix}" + versionless_model: Final = f"bedrock-versionless-{suffix}" + directory: Final = tmp_path_factory.mktemp("bedrock-guardrail-config") + base_config: Final = yaml.safe_load(Path("tests/integration/proxy_config.yaml").read_text()) + with ( + wire_server(_bedrock_with_guardrails) as wire, + wire_server(_bedrock_with_guardrails) as wire_a, + wire_server(_bedrock_with_guardrails) as wire_b, + wire_server(_bedrock_outage) as failing_wire, + wire_server(_bedrock_with_guardrails) as fallback_wire, + ): + config: Final = { + **base_config, + "model_list": [ + *base_config.get("model_list", []), + { + "model_name": guarded_model, + "litellm_params": _deployment(wire, _DEPLOYMENT_GUARDRAIL), + }, + {"model_name": unguarded_model, "litellm_params": _deployment(wire)}, + { + "model_name": balanced_model, + "litellm_params": _deployment( + wire_a, {"guardrailIdentifier": "guardrail-a", "guardrailVersion": "1"} + ), + }, + { + "model_name": balanced_model, + "litellm_params": _deployment( + wire_b, {"guardrailIdentifier": "guardrail-b", "guardrailVersion": "2"} + ), + }, + { + "model_name": failing_model, + "litellm_params": _deployment( + failing_wire, + {"guardrailIdentifier": "failing-guardrail", "guardrailVersion": "5", "trace": "enabled"}, + ), + }, + { + "model_name": fallback_model, + "litellm_params": _deployment( + fallback_wire, + {"guardrailIdentifier": "fallback-guardrail", "guardrailVersion": "6", "trace": "enabled"}, + ), + }, + { + "model_name": versionless_model, + "litellm_params": _deployment( + wire, {"guardrailIdentifier": "versionless-guardrail", "trace": "enabled"} + ), + }, + { + "model_name": mantle_model, + "litellm_params": { + "model": "bedrock_mantle/anthropic.claude-sonnet-5", + "api_base": wire.url, + "api_key": _MANTLE_KEY, + "aws_region_name": "us-east-1", + "use_in_pass_through": True, + "guardrailConfig": { + "guardrailIdentifier": "mantle-guardrail", + "guardrailVersion": "4", + "trace": "enabled", + }, + }, + }, + ], + "router_settings": { + **base_config.get("router_settings", {}), + "fallbacks": [{failing_model: [fallback_model]}], + }, + } + config_path: Final = directory / "bedrock-guardrail-config.yaml" + config_path.write_text(yaml.safe_dump(config)) + with ( + owned_proxy(session_gateway, directory, {}, config=config_path, workers=2) as proxy, + proxy.scenario() as scenario, + ): + yield Rig( + proxy=proxy, + wire=wire, + guarded_model=guarded_model, + unguarded_model=unguarded_model, + balanced_model=balanced_model, + balanced_wires={"guardrail-a": wire_a, "guardrail-b": wire_b}, + failing_model=failing_model, + failing_wire=failing_wire, + fallback_wire=fallback_wire, + mantle_model=mantle_model, + versionless_model=versionless_model, + key=scenario.key(key_alias=f"guardrail-key-{suffix}"), + ) + + +def _expected_on_the_wire(action: str, request: Request) -> Applied: + if action == "converse": + return Applied("deployment-guardrail", "3", "enabled", None) + if action == "converse-stream": + return Applied("deployment-guardrail", "3", "enabled", "sync") + assert {"x-amzn-bedrock-guardrailidentifier", "x-amzn-bedrock-guardrailversion", "x-amzn-bedrock-trace"} <= ( + _signed_header_names(request) + ), request.headers["authorization"] + return Applied("deployment-guardrail", "3", "ENABLED", None) + + +@pytest.mark.parametrize("action", _ACTIONS) +def test_passthrough_on_a_guardrailed_deployment_blocks_with_the_deployment_guardrail( + rig: Rig, monkeypatch: pytest.MonkeyPatch, action: str +) -> None: + marker: Final = uuid.uuid4().hex + runtime: Final = rig.runtime(monkeypatch) + + blocked: Final = _send(runtime, action, rig.guarded_model, f"{marker} say {_BLOCKED_WORD}", caller_guardrail=False) + allowed: Final = _send(runtime, action, rig.guarded_model, f"{marker} say hello", caller_guardrail=False) + + assert blocked == Outcome(_BLOCKED_TEXT, intervened=True, traced_guardrail="deployment-guardrail"), blocked + assert allowed == Outcome("ok", intervened=False, traced_guardrail=None), allowed + received: Final = rig.received(rig.wire, marker) + assert [_action(request) for request in received] == [action, action], received + assert [_applied(request) for request in received] == [ + _expected_on_the_wire(action, request) for request in received + ], [(request.headers, request.body) for request in received] + + +@pytest.mark.parametrize("action", _ACTIONS) +def test_caller_guardrail_is_replaced_by_the_deployment_guardrail( + rig: Rig, monkeypatch: pytest.MonkeyPatch, action: str +) -> None: + marker: Final = uuid.uuid4().hex + runtime: Final = rig.runtime(monkeypatch, _CALLER_INVOKE_HEADERS) + + outcome: Final = _send(runtime, action, rig.guarded_model, f"{marker} say {_BLOCKED_WORD}", caller_guardrail=True) + + assert outcome == Outcome(_BLOCKED_TEXT, intervened=True, traced_guardrail="deployment-guardrail"), outcome + (request,) = rig.received(rig.wire, marker) + assert _applied(request) == _expected_on_the_wire(action, request), (request.headers, request.body) + assert "caller-guardrail" not in json.dumps({**request.headers, "body": request.body.decode()}), request + + +@pytest.mark.parametrize("action", _ACTIONS) +def test_mantle_deployment_passthrough_sends_its_guardrail_with_bearer_auth( + rig: Rig, monkeypatch: pytest.MonkeyPatch, action: str +) -> None: + marker: Final = uuid.uuid4().hex + runtime: Final = rig.runtime(monkeypatch) + + outcome: Final = _send(runtime, action, rig.mantle_model, f"{marker} say {_BLOCKED_WORD}", caller_guardrail=False) + + assert outcome == Outcome(_BLOCKED_TEXT, intervened=True, traced_guardrail="mantle-guardrail"), outcome + (request,) = rig.received(rig.wire, marker) + assert request.headers["authorization"] == f"Bearer {_MANTLE_KEY}", request.headers + assert _applied(request) == Applied( + "mantle-guardrail", "4", "ENABLED" if action.startswith("invoke") else "enabled", None + ), (request.headers, request.body) + + +@pytest.mark.parametrize("action", _ACTIONS) +def test_deployment_guardrail_without_a_version_returns_the_bedrock_rejection( + rig: Rig, monkeypatch: pytest.MonkeyPatch, action: str +) -> None: + marker: Final = uuid.uuid4().hex + runtime: Final = rig.runtime(monkeypatch) + + with pytest.raises(ClientError) as raised: + _send(runtime, action, rig.versionless_model, f"{marker} say hello", caller_guardrail=False) + + error: Final = raised.value.response.get("Error", {}) + assert (error.get("Code"), error.get("Message")) == ("ValidationException", _VERSIONLESS_GUARDRAIL_MESSAGE), error + received: Final = rig.received(rig.wire, marker) + assert {_applied(request) for request in received} == { + Applied("versionless-guardrail", None, "ENABLED" if action.startswith("invoke") else "enabled", None) + }, [(request.headers, request.body) for request in received] + + +@pytest.mark.parametrize("action", _ACTIONS) +def test_deployment_without_a_guardrail_leaves_the_caller_guardrail_as_sent( + rig: Rig, monkeypatch: pytest.MonkeyPatch, action: str +) -> None: + if action.startswith("invoke"): + pytest.skip("BUG: the router-model invoke pass-through drops the caller's X-Amzn-Bedrock-Guardrail* headers") + marker: Final = uuid.uuid4().hex + runtime: Final = rig.runtime(monkeypatch) + + outcome: Final = _send(runtime, action, rig.unguarded_model, f"{marker} say {_BLOCKED_WORD}", caller_guardrail=True) + + assert outcome == Outcome(_BLOCKED_TEXT, intervened=True, traced_guardrail=None), outcome + (request,) = rig.received(rig.wire, marker) + assert _applied(request) == Applied( + "caller-guardrail", "9", "disabled", "async" if action == "converse-stream" else None + ), request.body + + +def test_each_load_balanced_request_carries_the_guardrail_of_the_deployment_it_reached( + rig: Rig, monkeypatch: pytest.MonkeyPatch +) -> None: + marker: Final = uuid.uuid4().hex + runtime: Final = rig.runtime(monkeypatch) + + outcomes: Final = tuple( + _send(runtime, action, rig.balanced_model, f"{marker}-{attempt} say {_BLOCKED_WORD}", caller_guardrail=False) + for attempt, action in enumerate(_ACTIONS * 6) + ) + + assert all(outcome.intervened for outcome in outcomes), outcomes + reached: Final = {name: rig.received(wire, marker) for name, wire in rig.balanced_wires.items()} + assert sum(len(requests) for requests in reached.values()) == len(outcomes), reached + assert all(reached.values()), {name: len(requests) for name, requests in reached.items()} + assert {name: {_identifier(request) for request in requests} for name, requests in reached.items()} == { + "guardrail-a": {"guardrail-a"}, + "guardrail-b": {"guardrail-b"}, + }, reached + + +def test_a_fallback_sends_the_guardrail_of_the_deployment_it_fell_back_to( + rig: Rig, monkeypatch: pytest.MonkeyPatch +) -> None: + marker: Final = uuid.uuid4().hex + runtime: Final = rig.runtime(monkeypatch) + + outcomes: Final = tuple( + _send(runtime, action, rig.failing_model, f"{marker} say {_BLOCKED_WORD}", caller_guardrail=False) + for action in _ACTIONS + ) + + assert outcomes == (Outcome(_BLOCKED_TEXT, intervened=True, traced_guardrail="fallback-guardrail"),) * 4, outcomes + failed: Final = rig.received(rig.failing_wire, marker) + served: Final = rig.received(rig.fallback_wire, marker) + assert [_action(request) for request in served] == list(_ACTIONS), served + assert {_identifier(request) for request in failed} == {"failing-guardrail"}, failed + assert {_identifier(request) for request in served} == {"fallback-guardrail"}, served diff --git a/tests/integration/providers/test_count_tokens_model_wire.py b/tests/integration/providers/test_count_tokens_model_wire.py index 46e5396ef64..b6ace7ddef3 100644 --- a/tests/integration/providers/test_count_tokens_model_wire.py +++ b/tests/integration/providers/test_count_tokens_model_wire.py @@ -31,7 +31,6 @@ _PROFILE_ID: Final = "lit9563count" _PROFILE_ARN: Final = f"arn:aws:bedrock:us-east-1:123456789012:application-inference-profile/{_PROFILE_ID}" _COST_MAP_PATH: Final = Path(__file__).resolve().parents[3] / "model_prices_and_context_window.json" _REGION: Final = "us-west-2" -_COUNT_REGION: Final = "us-east-1" _ACCESS_KEY: Final = "AKIAINTEGRATIONCOUNT" _SECRET_KEY: Final = "integration-count-secret" _PROVIDER_COUNT: Final = 1345 @@ -39,12 +38,37 @@ _COUNT_MODEL_COUNT: Final = 2718 _FRAMING: Final = 50 _UNSUPPORTED: Final = "The provided model doesn't support counting tokens." _COUNT_TARGET: Final = re.compile(r"^/model/(.+)/count-tokens$") +_MANTLE_COUNT_TARGET: Final = "/anthropic/v1/messages/count_tokens" +_MANTLE_VERSION: Final = "2023-06-01" _SCRIPTED_STATUS: Final = re.compile(r"status=(\d{3})") _SCRIPTED_COUNT_MODEL_STATUS: Final = re.compile(r"count_model=(\d{3})") _CREDENTIAL: Final = re.compile(r"Credential=([^/]+)/\d+/([^/]+)/") _JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue]) _COST_MAP: Final = TypeAdapter(dict[str, dict[str, JsonValue]]) + +def _shipped_token_count_model(model: str) -> dict[str, JsonValue]: + token_count_model: Final = _COST_MAP.validate_json(_COST_MAP_PATH.read_bytes())[model].get("token_count_model") + assert isinstance(token_count_model, dict), model + return token_count_model + + +def _shipped_token_count_model_field(model: str, field: str) -> str: + value: Final = _shipped_token_count_model(model).get(field) + assert isinstance(value, str), (model, field, value) + return value + + +def _count_model_source(model: str) -> dict[str, JsonValue]: + return { + "litellm_count_source": "token_count_model", + "litellm_count_model": _shipped_token_count_model_field(model, "model"), + } + + +_COUNT_REGION: Final = _shipped_token_count_model_field(_SONNET, "region") +_COUNT_MODEL_SOURCE: Final = _count_model_source(_SONNET) + _SYSTEM: Final = "You are a terse assistant that answers in one sentence" _WEATHER_SCHEMA: Final[dict[str, JsonValue]] = { "type": "object", @@ -62,7 +86,6 @@ _SDK_TOOLS: Final[list[MessageCountTokensToolParam]] = [ }, } ] -_COUNT_MODEL_SOURCE: Final = {"litellm_count_source": "token_count_model", "litellm_count_model": _OPUS} _OPENAI_PRIMARY: Final = "gpt-count-primary" _OPENAI_COUNT_MODEL: Final = "gpt-count-model" _OPENAI_COUNT_TARGET: Final = "/v1/responses/input_tokens" @@ -140,8 +163,17 @@ def _runtime(request: Request) -> Reply: def _mantle(request: Request) -> Reply: model: Final = _JSON_OBJECT.validate_json(request.body).get("model") + status: Final = _scripted(_SCRIPTED_COUNT_MODEL_STATUS, request, 200) + if status == 200: + return _json_reply(200, {"input_tokens": _COUNT_MODEL_COUNT}) + error_type: Final = { + 401: "authentication_error", + 404: "not_found_error", + 429: "rate_limit_error", + }[status] return _json_reply( - 404, {"type": "error", "error": {"type": "not_found_error", "message": f"scripted mantle 404 for {model}"}} + status, + {"type": "error", "error": {"type": error_type, "message": f"scripted mantle {status} for {model}"}}, ) @@ -165,6 +197,24 @@ def _mantle_models(wire: Wire) -> tuple[JsonValue, ...]: return tuple(_JSON_OBJECT.validate_json(request.body).get("model") for request in wire.drain()) +def _mantle_count_requests(wire: Wire) -> tuple[tuple[tuple[str, str], dict[str, JsonValue]], ...]: + requests: Final = tuple(wire.drain()) + for request in requests: + assert (request.method, request.target) == ("POST", _MANTLE_COUNT_TARGET), request.target + assert request.headers["anthropic-version"] == _MANTLE_VERSION, request.headers + assert request.headers["content-type"] == "application/json", request.headers + return tuple((_signer(request), _JSON_OBJECT.validate_json(request.body)) for request in requests) + + +def _mantle_body(prompt: str) -> dict[str, JsonValue]: + return { + "model": _OPUS_BASE, + "messages": [{"role": "user", "content": prompt}], + "system": _SYSTEM, + "tools": _SDK_TOOLS, + } + + def _url(port: int) -> str: return f"http://127.0.0.1:{port}" @@ -255,15 +305,15 @@ def test_shipped_token_count_model_counts_the_request_in_its_region_without_tryi ): counted: Final = _count(gateway, _deployment(scenario, runtime_port), 404) assert (counted.input_tokens, counted.model_extra) == (_COUNT_MODEL_COUNT, _COUNT_MODEL_SOURCE), counted - assert _runtime_counts(runtime) == ((_OPUS_BASE, (_ACCESS_KEY, _COUNT_REGION), _converse_body(_prompt(404))),) - assert _mantle_models(mantle) == () + assert _runtime_counts(runtime) == () + assert _mantle_count_requests(mantle) == (((_ACCESS_KEY, _COUNT_REGION), _mantle_body(_prompt(404))),) @pytest.mark.parametrize( ("count_model_status", "error", "message"), [ - (401, anthropic.AuthenticationError, f"scripted runtime 401 for {_OPUS_BASE}"), - (429, anthropic.RateLimitError, f"scripted runtime 429 for {_OPUS_BASE}"), + (401, anthropic.AuthenticationError, f"scripted mantle 401 for {_OPUS_BASE}"), + (429, anthropic.RateLimitError, f"scripted mantle 429 for {_OPUS_BASE}"), (404, anthropic.NotFoundError, f"scripted mantle 404 for {_OPUS_BASE}"), ], ) @@ -283,9 +333,16 @@ def test_token_count_model_failure_answers_its_error_and_names_the_region_to_ena ): with pytest.raises(error) as refused: _count(gateway, _deployment(scenario, runtime_port), 200, count_model_status=count_model_status) - assert message in str(refused.value) and f"{_OPUS} in {_COUNT_REGION}" in str(refused.value), refused.value - assert _runtime_models(runtime) == (_OPUS_BASE,) - assert _mantle_models(mantle) == ((_OPUS_BASE,) if count_model_status == 404 else ()) + assert message in str(refused.value) and ( + f"{_COUNT_MODEL_SOURCE['litellm_count_model']} in {_COUNT_REGION}" in str(refused.value) + ), refused.value + assert _runtime_counts(runtime) == () + assert _mantle_count_requests(mantle) == ( + ( + (_ACCESS_KEY, _COUNT_REGION), + _mantle_body(_prompt(200, count_model_status)), + ), + ) def test_framing_is_added_to_the_local_estimate_when_the_runtime_cannot_count( @@ -359,8 +416,8 @@ def test_inference_profile_arn_counts_with_the_token_count_model_of_its_base_mod ) counted: Final = _count(gateway, model, 404) assert (counted.input_tokens, counted.model_extra) == (_COUNT_MODEL_COUNT, _COUNT_MODEL_SOURCE), counted - assert _runtime_models(runtime) == (_OPUS_BASE,) - assert _mantle_models(mantle) == () + assert _runtime_counts(runtime) == () + assert _mantle_count_requests(mantle) == (((_ACCESS_KEY, _COUNT_REGION), _mantle_body(_prompt(404))),) @pytest.mark.parametrize( diff --git a/tests/integration/providers/test_cursor_responses_wire.py b/tests/integration/providers/test_cursor_responses_wire.py index 6e8c877f7ca..d77d35f2ff8 100644 --- a/tests/integration/providers/test_cursor_responses_wire.py +++ b/tests/integration/providers/test_cursor_responses_wire.py @@ -3,6 +3,7 @@ from __future__ import annotations import json import os import uuid +from importlib.resources import files from typing import Final import pytest @@ -16,8 +17,16 @@ _MODEL: Final = "gpt-5" _API_KEY: Final = "synthetic-cursor-key" _JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue]) _PROXY_WORKERS: Final = max(1, int(os.environ.get("INTEGRATION_PROXY_WORKERS", "1"))) -_THINKING_LEVELS: Final = ("none", "minimal", "low", "medium", "high", "xhigh", "max") -_CHAT_THINKING_LEVELS: Final = ("none", "minimal", "low", "medium", "high", "max") +_COST_MAP: Final = TypeAdapter(dict[str, dict[str, JsonValue]]) +_MODEL_ROW: Final = _COST_MAP.validate_json( + (files("litellm") / "model_prices_and_context_window_backup.json").read_bytes() +)[_MODEL] +_THINKING_LEVELS: Final = tuple( + level + for level in ("none", "minimal", "low", "medium", "high", "xhigh", "max") + if _MODEL_ROW.get(f"supports_{level}_reasoning_effort") is not False +) +_CHAT_THINKING_LEVELS: Final = tuple(level for level in _THINKING_LEVELS if level != "xhigh") _RESPONSES_SUFFIXES: Final[tuple[tuple[str, dict[str, JsonValue]], ...]] = tuple( (f"-thinking-{level}", {"reasoning": {"effort": level}}) for level in _THINKING_LEVELS ) + ( diff --git a/tests/integration/providers/test_gemini_anyof_null_branches_wire.py b/tests/integration/providers/test_gemini_anyof_null_branches_wire.py index 9fa99cb69f8..79820ac2efb 100644 --- a/tests/integration/providers/test_gemini_anyof_null_branches_wire.py +++ b/tests/integration/providers/test_gemini_anyof_null_branches_wire.py @@ -360,8 +360,9 @@ def test_a_repeated_identical_request_sends_the_same_folded_union_each_time(gate model: Final = _deployment(gateway, scenario, wire, "vertex_ai") description: Final = _description() path, body = _request_body("chat", model, description, _parameters({"anyOf": [_NULL, _NULL, _STRING]}), False) - first: Final = gateway.request("POST", path, body) - second: Final = gateway.request("POST", path, body) + uncached: Final[dict[str, JsonValue]] = {**body, "cache": {"no-cache": True}} + first: Final = gateway.request("POST", path, uncached) + second: Final = gateway.request("POST", path, uncached) _assert_caller_saw_ok("chat", first, False) _assert_caller_saw_ok("chat", second, False) assert _json(first)["id"] != _json(second)["id"] diff --git a/tests/integration/providers/test_hosted_vllm_stream_stall_wire.py b/tests/integration/providers/test_hosted_vllm_stream_stall_wire.py index 00e5388b474..fad7898871d 100644 --- a/tests/integration/providers/test_hosted_vllm_stream_stall_wire.py +++ b/tests/integration/providers/test_hosted_vllm_stream_stall_wire.py @@ -42,8 +42,8 @@ _RESPONSES_TARGET: Final = "/v1/responses" _STREAM_TIMEOUT_SECONDS: Final = 1 _DEPLOYMENT_TIMEOUT_SECONDS: Final = 30 _PAUSE_SECONDS: Final = 3.0 -_HOLD_SECONDS: Final = 30.0 _ROW_SECONDS: Final = 60 +_HOLD_SECONDS: Final = 2.0 * _ROW_SECONDS _EXTRA: Final[dict[str, JsonValue]] = {"num_retries": 0, "cache": {"no-cache": True}} _ROWS: Final = 'SELECT status, metadata FROM "LiteLLM_SpendLogs" WHERE model_group=%s' _EITHER_GROUP_ROWS: Final = 'SELECT status, metadata FROM "LiteLLM_SpendLogs" WHERE model_group IN (%s, %s)' diff --git a/tests/integration/providers/test_malformed_tools_wire.py b/tests/integration/providers/test_malformed_tools_wire.py index 706babac398..910f3faf312 100644 --- a/tests/integration/providers/test_malformed_tools_wire.py +++ b/tests/integration/providers/test_malformed_tools_wire.py @@ -1418,7 +1418,7 @@ def test_count_tokens_rejects_malformed_tools_when_a_request_list_replaces_the_d assert _delivered(rig, marker) == () -def test_responses_input_tokens_drops_the_bad_entry_a_deployment_list_names( +def test_responses_input_tokens_drops_the_tools_a_deployment_list_names( rig: _Rig, field_groups: _FieldGroups ) -> None: marker: Final = _marker() @@ -1428,8 +1428,7 @@ def test_responses_input_tokens_drops_the_bad_entry_a_deployment_list_names( {"model": field_groups.anthropic, "input": marker, "tools": [RESPONSES.tool, 5]}, ) assert response.status_code == 200, response.text - tools: Final = _one_delivery(rig, marker, "/v1/messages/count_tokens")["tools"] - assert isinstance(tools, list) and len(tools) == 1 and "get_weather" in json.dumps(tools), tools + assert "tools" not in _one_delivery(rig, marker, "/v1/messages/count_tokens") def test_responses_input_tokens_rejects_malformed_tools_when_a_request_list_replaces_the_deployment_list( @@ -1669,7 +1668,7 @@ _CHECKED: Final[Mapping[str, _Checked]] = MappingProxyType( send=_input_tokens, target="/v1/messages/count_tokens", answered=_counted({"object": "response.input_tokens", "input_tokens": _COUNT, **_PROVIDER_SOURCE}), - kept_by_a_tools_list=("get_weather",), + kept_by_a_tools_list=(), bad_entry=_RESPONSES_BAD_ENTRY, ), } @@ -2336,14 +2335,14 @@ def test_a_deployment_list_with_a_non_string_entry_drops_tools_it_names_on_messa @_TOKEN_COUNTS -def test_token_counting_with_a_request_list_with_a_non_string_entry_drops_the_bad_entry( +def test_token_counting_with_a_request_list_with_a_non_string_entry_counts_the_tools_its_route_keeps( rig: _Rig, checked: _Checked ) -> None: marker: Final = _marker() response: Final = checked.send( rig, rig.anthropic, marker, {"tools": [checked.tool, 5], "additional_drop_params": ["tools", 5]} ) - _assert_forwarded(rig, checked, response, marker, ("get_weather",)) + _assert_forwarded(rig, checked, response, marker, checked.kept_by_a_tools_list) def _alias(suffix: str, variant: str) -> str: diff --git a/tests/integration/providers/test_openai_count_tokens_tools_wire.py b/tests/integration/providers/test_openai_count_tokens_tools_wire.py index 16a5b8685ad..96410b03a92 100644 --- a/tests/integration/providers/test_openai_count_tokens_tools_wire.py +++ b/tests/integration/providers/test_openai_count_tokens_tools_wire.py @@ -415,4 +415,76 @@ def test_responses_input_tokens_passes_an_openai_count_error_through( response: Final = gateway.request("POST", "/v1/responses/input_tokens", {"model": model, "input": "hello"}) assert response.status_code == 400, response.text assert response.json() == {"error": {"param": None, "code": None, **error}}, response.text - assert _count_body(wire)["input"] == [{"role": "user", "content": "hello"}] + assert _count_body(wire)["input"] == "hello" + + +_NATIVE_TEXT: Final[dict[str, JsonValue]] = { + "format": {"type": "json_schema", "name": "answer", "schema": _ANSWER_SCHEMA}, +} +_NATIVE_BODY: Final[Mapping[str, JsonValue]] = { + "input": [ + {"role": "user", "content": "hi"}, + {"type": "reasoning", "summary": [], "encrypted_content": _WRAPPED_REASONING}, + {"role": "user", "content": "again"}, + ], + "text": _NATIVE_TEXT, + "max_output_tokens": "lots", + "metadata": {"run": "nightly"}, +} + + +@pytest.mark.parametrize( + ("drop_params", "expected_extra"), + [pytest.param(False, {"max_output_tokens": "lots"}, id="as-sent"), pytest.param(True, {}, id="drop-params")], +) +def test_responses_input_tokens_sends_the_callers_body_to_openai( + counting_proxy: OwnedProxy, drop_params: bool, expected_extra: dict[str, JsonValue] +) -> None: + gateway: Final = counting_proxy.gateway + with wire_server(_count_response) as wire, gateway.scenario() as scenario: + model: Final = scenario.model( + model="openai/gpt-4o-mini", + api_base=f"{wire.url}/v1", + api_key="sk-integration-openai", + drop_params=drop_params, + ) + response: Final = gateway.request("POST", "/v1/responses/input_tokens", {"model": model, **_NATIVE_BODY}) + assert response.status_code == 200, response.text + assert _JSON_OBJECT.validate_json(response.content)["input_tokens"] == _COUNT + assert _count_body(wire) == { + "model": "gpt-4o-mini", + "input": [ + {"role": "user", "content": "hi"}, + {"type": "reasoning", "summary": [], "encrypted_content": "gAAAAoriginal"}, + {"role": "user", "content": "again"}, + ], + "text": _NATIVE_TEXT, + **expected_extra, + } + + +def test_responses_input_tokens_sends_openai_the_owners_previous_response_id(counting_proxy: OwnedProxy) -> None: + gateway: Final = counting_proxy.gateway + with wire_server(_responses_peer) as wire, gateway.scenario() as scenario: + model: Final = _deployment(scenario, wire.url) + team: Final = scenario.team(models=[model]) + owner_key: Final = scenario.key(team_id=team, user_id=scenario.member(team), models=[model]) + other_key: Final = scenario.key(team_id=team, user_id=scenario.member(team), models=[model]) + generated: Final = gateway.request("POST", "/v1/responses", {"model": model, "input": "hi"}, key=owner_key) + assert generated.status_code == 200, generated.text + follow_up: Final = { + "model": model, + "input": "again", + "previous_response_id": _JSON_OBJECT.validate_json(generated.content)["id"], + } + _body_for(wire.drain(), "/v1/responses") + + refused: Final = gateway.request("POST", "/v1/responses/input_tokens", follow_up, key=other_key) + assert refused.status_code == 403, refused.text + assert _JSON_OBJECT.validate_json(refused.content)["error"]["type"] == "permission_error", refused.text + assert wire.drain() == () + + counted: Final = gateway.request("POST", "/v1/responses/input_tokens", follow_up, key=owner_key) + assert counted.status_code == 200, counted.text + count_body: Final = _body_for(wire.drain(), "/v1/responses/input_tokens") + assert count_body["previous_response_id"] == _RESPONSES_REPLY["id"] diff --git a/tests/integration/providers/test_responses_core_wire.py b/tests/integration/providers/test_responses_core_wire.py index 791b2b8783f..9a24903a20d 100644 --- a/tests/integration/providers/test_responses_core_wire.py +++ b/tests/integration/providers/test_responses_core_wire.py @@ -3,6 +3,7 @@ from __future__ import annotations import json import os import uuid +from collections.abc import Callable from typing import Final import openai @@ -192,6 +193,42 @@ def test_previous_response_id_uses_the_raw_id_and_affinity( ], [request.body for request in requests] +def _counting_peer(raw_id: str, input_tokens: int) -> Callable[[Request], Reply]: + def respond(request: Request) -> Reply: + if request.method == "GET" and request.target == "/v1/models": + return model_discovery_reply(_MODEL) + if request.target == "/v1/responses/input_tokens": + return Reply(body=json.dumps({"object": "response.input_tokens", "input_tokens": input_tokens}).encode()) + return Reply(body=_response(raw_id)) + + return respond + + +def test_input_tokens_count_goes_to_the_deployment_that_served_the_previous_response(gateway: Gateway) -> None: + raw_id: Final = f"resp_count_affinity_{uuid.uuid4().hex}" + with ( + wire_server(_counting_peer(raw_id, 37)) as first_wire, + wire_server(_counting_peer(raw_id, 99)) as second_wire, + gateway.scenario() as scenario, + ): + model: Final = f"integration-{uuid.uuid4().hex}" + _enable_responses_affinity(scenario) + assert _register(scenario, first_wire, model) == model + client: Final = openai.OpenAI(base_url=f"{gateway.client.base_url}/v1", api_key=gateway.key, max_retries=0) + first: Final = client.responses.create(model=model, input="turn one") + _register_in_group(scenario, second_wire, model, order=1) + counted: Final = client.responses.input_tokens.count( + model=model, input="turn two", previous_response_id=first.id + ) + assert counted.input_tokens == 37, counted.model_dump_json() + assert drain_contract_requests(second_wire) == (), "the count left the previous response's deployment" + requests: Final = drain_contract_requests(first_wire) + assert [(request.target, _JSON_OBJECT.validate_json(request.body)) for request in requests] == [ + ("/v1/responses", {"model": _MODEL, "input": "turn one"}), + ("/v1/responses/input_tokens", {"model": _MODEL, "input": "turn two", "previous_response_id": raw_id}), + ], [request.body for request in requests] + + @pytest.mark.parametrize("prefix", _ALIASES) def test_codex_responses_request_preserves_all_supported_fields(gateway: Gateway, prefix: str) -> None: response_id: Final = f"resp_codex_{uuid.uuid4().hex}" diff --git a/tests/integration/providers/test_sagemaker_chat_wire.py b/tests/integration/providers/test_sagemaker_chat_wire.py index 0416404cec8..261787fec38 100644 --- a/tests/integration/providers/test_sagemaker_chat_wire.py +++ b/tests/integration/providers/test_sagemaker_chat_wire.py @@ -1,11 +1,14 @@ import asyncio +import itertools +import json import uuid -from collections.abc import Callable, Mapping +from collections.abc import AsyncIterator, Callable, Mapping from dataclasses import dataclass from types import MappingProxyType from typing import Final, Literal, TypeAlias import httpx +import openai import pytest from integration._support.client import Gateway, Scenario, eventually, list_value, object_value, string_value from integration._support.database import read_rows @@ -26,14 +29,18 @@ from integration.providers._sagemaker_chat_container import ( REGION, SECRET_KEY, SERVED_MODEL, + USAGE, answered_choices, assert_signed, by_marker, container_body, container_reply, + event_stream_reply, marked_prompt, marker, + model_stream_error, only_request, + vllm_stream_events, ) from pydantic import JsonValue @@ -260,6 +267,77 @@ def test_sagemaker_chat_keeps_the_deployment_aws_credentials_out_of_the_containe assert SECRET_KEY not in string_value(row["stored"]), row +def _seven_byte_parts(stream: bytes) -> tuple[bytes, ...]: + return tuple(stream[start : start + 7] for start in range(0, len(stream), 7)) + + +def _event_pairs(events: tuple[bytes, ...]) -> tuple[bytes, ...]: + return tuple(b"".join(events[start : start + 2]) for start in range(0, len(events), 2)) + + +_PART_CUTTINGS: Final[Mapping[str, Callable[[tuple[bytes, ...]], tuple[bytes, ...]]]] = MappingProxyType( + { + "one-event-per-part": lambda events: events, + "usage-and-done-share-a-part": lambda events: (*events[:-2], events[-2] + events[-1]), + "event-pairs-share-a-part": _event_pairs, + "seven-byte-parts": lambda events: _seven_byte_parts(b"".join(events)), + "keep-alive-comments-between-events": lambda events: tuple( + itertools.chain.from_iterable((b":\n\n", event) for event in events) + ), + } +) + + +def _sse(record: Mapping[str, JsonValue]) -> bytes: + return f"data: {json.dumps(record)}\n\n".encode() + + +@dataclass(frozen=True, slots=True) +class _StreamedAnswer: + call_id: str + text: str + usages: tuple[tuple[int, int, int], ...] + + +async def _chat_openai_stream_with_usage(gateway: Gateway, model: str, prompt: str) -> _StreamedAnswer: + async with async_openai_client(gateway) as client: + stream: Final = await client.chat.completions.create( + model=model, + messages=[{"role": "user", "content": prompt}], + max_tokens=16, + stream=True, + stream_options={"include_usage": True}, + extra_body=dict(NO_CACHE), + ) + chunks: Final = [chunk async for chunk in stream] + return _StreamedAnswer( + stream.response.headers["x-litellm-call-id"], + "".join(chunk.choices[0].delta.content or "" for chunk in chunks if chunk.choices), + tuple( + (chunk.usage.prompt_tokens, chunk.usage.completion_tokens, chunk.usage.total_tokens) + for chunk in chunks + if chunk.usage + ), + ) + + +@pytest.mark.parametrize("cutting", tuple(_PART_CUTTINGS)) +def test_sagemaker_chat_vllm_stream_reaches_the_caller_whole_however_sagemaker_cuts_its_payload_parts( + gateway: Gateway, cutting: str +) -> None: + identity: Final = f"sagemaker-chat-{uuid.uuid4().hex}" + parts: Final = _PART_CUTTINGS[cutting](vllm_stream_events(identity)) + expected_usage: Final = (USAGE["prompt_tokens"], USAGE["completion_tokens"], USAGE["total_tokens"]) + + with wire_server(lambda _request: event_stream_reply(parts)) as wire, gateway.scenario() as scenario: + model: Final = _deployment(scenario, wire, {}) + answer: Final = asyncio.run(_chat_openai_stream_with_usage(gateway, model, marked_prompt())) + only_request(wire) + assert (answer.text, answer.usages) == ("".join(CONTENT), (expected_usage,)), answer + stored: Final = JSON_OBJECT.validate_json(string_value(_spend_row(answer.call_id)["stored"])) + assert (stored["prompt_tokens"], stored["completion_tokens"], stored["total_tokens"]) == expected_usage, stored + + @dataclass(frozen=True, slots=True) class _Shape: provider: str @@ -388,6 +466,148 @@ def test_sagemaker_chat_container_error_reaches_the_caller_after_one_attempt_wit assert_signed(request, ACCESS_KEY, REGION, None) +def test_sagemaker_chat_container_validation_error_record_answers_422_after_one_attempt(gateway: Gateway) -> None: + failure: Final = _sse({"error": {"message": "synthetic prompt too long", "http_status_code": 422}}) + + with wire_server(lambda _request: event_stream_reply((failure,))) as wire, gateway.scenario() as scenario: + model: Final = _deployment(scenario, wire, {}) + response: Final = _chat(gateway, model, marked_prompt(), {"stream": True}) + only_request(wire) + assert response.status_code == 422, response.text + assert "synthetic prompt too long" in response.text, response.text + + +async def _texts_until_error( + stream: openai.AsyncStream[openai.types.chat.ChatCompletionChunk], +) -> AsyncIterator[str | openai.APIError]: + try: + async for chunk in stream: + yield "".join(choice.delta.content or "" for choice in chunk.choices) + except openai.APIError as error: + yield error + + +async def _chat_openai_stream_until_error( + gateway: Gateway, model: str, prompt: str, extra: Mapping[str, JsonValue] = MappingProxyType({}) +) -> tuple[str | openai.APIError, ...]: + async with async_openai_client(gateway) as client: + stream: Final = await client.chat.completions.create( + model=model, + messages=[{"role": "user", "content": prompt}], + max_tokens=16, + stream=True, + extra_body={**NO_CACHE, **extra}, + ) + return tuple([item async for item in _texts_until_error(stream)]) + + +_MID_STREAM_FAILURES: Final[Mapping[str, tuple[Callable[[tuple[bytes, ...]], Reply], str]]] = MappingProxyType( + { + "error-record": ( + lambda events: event_stream_reply( + (*events[:2], _sse({"error": {"message": "synthetic decode failure", "code": 500}})) + ), + "synthetic decode failure", + ), + "model-stream-error": ( + lambda events: event_stream_reply( + events[:2], then=(model_stream_error("synthetic stream timeout", "ModelInvocationTimeExceeded"),) + ), + "SageMaker stream failed with ModelStreamError (ModelInvocationTimeExceeded): synthetic stream timeout", + ), + "stream-ends-inside-a-record": ( + lambda events: event_stream_reply((*events[:2], events[2][:30])), + "SageMaker stream ended inside a record", + ), + } +) + + +@pytest.mark.parametrize("failure", tuple(_MID_STREAM_FAILURES)) +def test_sagemaker_chat_stream_failure_after_the_first_chunks_reaches_the_caller_as_an_error( + gateway: Gateway, failure: str +) -> None: + reply, expected = _MID_STREAM_FAILURES[failure] + events: Final = vllm_stream_events(f"sagemaker-chat-{uuid.uuid4().hex}") + + with wire_server(lambda _request: reply(events)) as wire, gateway.scenario() as scenario: + model: Final = _deployment(scenario, wire, {}) + outcome: Final = asyncio.run(_chat_openai_stream_until_error(gateway, model, marked_prompt())) + only_request(wire) + errors: Final = tuple(item for item in outcome if isinstance(item, openai.APIError)) + assert "".join(item for item in outcome if isinstance(item, str)) == "".join(CONTENT), outcome + assert len(errors) == 1 and expected in errors[0].message, outcome + + +_PRE_CONTENT_FAILURES: Final[Mapping[str, Reply]] = MappingProxyType( + { + "error-record": event_stream_reply((_sse({"error": {"message": "synthetic decode failure", "code": 500}}),)), + "model-stream-error": event_stream_reply( + (), then=(model_stream_error("synthetic stream timeout", "ModelInvocationTimeExceeded"),) + ), + } +) + + +@pytest.mark.parametrize("failure", tuple(_PRE_CONTENT_FAILURES)) +def test_sagemaker_chat_stream_failure_before_any_content_falls_back_to_the_next_model( + gateway: Gateway, failure: str +) -> None: + events: Final = vllm_stream_events(f"sagemaker-chat-{uuid.uuid4().hex}") + + with ( + wire_server(lambda _request: _PRE_CONTENT_FAILURES[failure]) as primary_wire, + wire_server(lambda _request: event_stream_reply(events)) as fallback_wire, + gateway.scenario() as scenario, + ): + primary: Final = _deployment(scenario, primary_wire, {}) + fallback: Final = _deployment(scenario, fallback_wire, {}) + outcome: Final = asyncio.run( + _chat_openai_stream_until_error(gateway, primary, marked_prompt(), {"fallbacks": [fallback]}) + ) + primary_attempts: Final = primary_wire.drain() + only_request(fallback_wire) + assert outcome and all(isinstance(item, str) for item in outcome), outcome + assert "".join(item for item in outcome if isinstance(item, str)) == "".join(CONTENT), outcome + assert len(primary_attempts) == 1, primary_attempts + + +def _lmi_line(record: Mapping[str, JsonValue]) -> bytes: + return f"{json.dumps(dict(record), ensure_ascii=False)}\n".encode() + + +_LMI_TOKENS: Final = ("sagemaker", " lmi tokens") +_LMI_ERROR: Final = "exception occurred during rolling batch inference" +# djl-serving 8a99e6e5: rolling_batch.py's error Token rendered by output_formatter._jsonlines_output_formatter +_LMI_FAILED_GENERATION: Final[Mapping[str, JsonValue]] = MappingProxyType( + { + "token": {"id": -1, "text": "", "log_prob": -1, "special_token": True, "error_msg": _LMI_ERROR}, + "generated_text": "".join(_LMI_TOKENS), + "details": {"finish_reason": "error"}, + } +) + + +def test_sagemaker_lmi_failed_generation_after_the_first_tokens_reaches_the_caller_as_an_error( + gateway: Gateway, +) -> None: + tokens: Final = tuple( + _lmi_line({"token": {"id": index, "text": text, "log_prob": -0.1}}) for index, text in enumerate(_LMI_TOKENS, 1) + ) + reply: Final = event_stream_reply((*tokens, _lmi_line(_LMI_FAILED_GENERATION))) + + with wire_server(lambda _request: reply) as wire, gateway.scenario() as scenario: + model: Final = _deployment( + scenario, wire, {"hf_model_name": "meta-llama/Llama-2-7b-chat-hf"}, provider="sagemaker" + ) + outcome: Final = asyncio.run(_chat_openai_stream_until_error(gateway, model, marked_prompt())) + only_request(wire) + errors: Final = tuple(item for item in outcome if isinstance(item, openai.APIError)) + assert "".join(item for item in outcome if isinstance(item, str)) == "".join(_LMI_TOKENS), outcome + assert len(errors) == 1, outcome + assert f"SageMaker endpoint streamed a failed generation: {_LMI_ERROR}" in errors[0].message, outcome + + @dataclass(frozen=True, slots=True) class _Call: endpoint: Endpoint diff --git a/tests/integration/providers/test_vertex_anthropic_structured_output_wire.py b/tests/integration/providers/test_vertex_anthropic_structured_output_wire.py index cb295815ae2..2918f364c56 100644 --- a/tests/integration/providers/test_vertex_anthropic_structured_output_wire.py +++ b/tests/integration/providers/test_vertex_anthropic_structured_output_wire.py @@ -1819,25 +1819,32 @@ def test_vertex_chat_without_response_format_sends_no_tool_and_no_output_config( assert not {"tools", "output_config", "output_format"} & sent.body.keys(), sent.body -@pytest.mark.parametrize( - "output_format", - [5, [], {}, "x" * 5000], - ids=["int", "list", "empty", "5kb"], -) -def test_vertex_messages_malformed_output_format_reaches_the_caller_as_the_peer_400( +def test_vertex_messages_empty_output_format_reaches_the_caller_as_the_peer_400(gateway: Gateway) -> None: + marker, marker_hex = _marker("native") + with wire_server(_peer) as wire, gateway.scenario() as scenario: + model: Final = _vertex_deployment(gateway, scenario, wire.url, _NATIVE_MODEL) + response: Final = gateway.request("POST", "/v1/messages", _messages_body(model, marker, output_format={})) + assert response.status_code == 400, response.text + assert _BAD_FORMAT in response.text, response.text + sent: Final = _one_delivery(wire, marker_hex) + assert "output_format" not in sent.body, sent.body + assert object_value(sent.body["output_config"])["format"] == {}, sent.body + assert gateway.request("GET", "/health/liveliness").status_code == 200 + + +@pytest.mark.parametrize("output_format", [5, [], "x" * 5000], ids=["int", "list", "5kb"]) +def test_vertex_messages_non_object_output_format_is_refused_without_reaching_the_peer( gateway: Gateway, output_format: JsonValue ) -> None: - marker, marker_hex = _marker("native") + marker, _ = _marker("native") with wire_server(_peer) as wire, gateway.scenario() as scenario: model: Final = _vertex_deployment(gateway, scenario, wire.url, _NATIVE_MODEL) response: Final = gateway.request( "POST", "/v1/messages", _messages_body(model, marker, output_format=output_format) ) assert response.status_code == 400, response.text - assert _BAD_FORMAT in response.text, response.text - sent: Final = _one_delivery(wire, marker_hex) - assert "output_format" not in sent.body, sent.body - assert object_value(sent.body["output_config"])["format"] == output_format, sent.body + assert "needs `output_format` to be a JSON object" in response.text, response.text + assert _delivered(wire) == () assert gateway.request("GET", "/health/liveliness").status_code == 200 diff --git a/tests/integration/providers/test_vertex_gemini_count_tokens_wire.py b/tests/integration/providers/test_vertex_gemini_count_tokens_wire.py index ec3fb941037..1632e424c55 100644 --- a/tests/integration/providers/test_vertex_gemini_count_tokens_wire.py +++ b/tests/integration/providers/test_vertex_gemini_count_tokens_wire.py @@ -1096,3 +1096,57 @@ def test_utils_token_counter_counts_a_local_prompt_with_system_or_tools_like_its assert as_message.status_code == 200, as_message.text assert _total_tokens(prompted) == _total_tokens(as_message) assert requests == () + + +_RESPONSES_TOOL_ROUND_TRIP: Final[Mapping[str, JsonValue]] = MappingProxyType( + { + "instructions": "Follow the system instruction.", + "input": [ + {"role": "user", "content": "Look up the value."}, + {"type": "function_call", "call_id": "call_lookup", "name": "lookup", "arguments": '{"query":"value"}'}, + {"type": "function_call_output", "call_id": "call_lookup", "output": "result"}, + ], + "tools": [ + { + "type": "function", + "name": "lookup", + "description": "Look up a value", + "parameters": {"type": "object", "properties": {"query": {"type": "string"}}}, + } + ], + } +) + + +@pytest.mark.parametrize("provider", ("vertex_ai", "gemini")) +def test_responses_input_tokens_counts_the_tool_round_trip_contents_responses_inference_sends( + gateway: Gateway, provider: str +) -> None: + peer: Final = _GeminiPeer() + with wire_server(peer) as wire, gateway.scenario() as scenario: + model: Final = ( + _deployment(gateway, scenario, wire.url) + if provider == "vertex_ai" + else _ai_studio_deployment(scenario, wire.url) + ) + body: Final = {"model": model, **_RESPONSES_TOOL_ROUND_TRIP} + generated: Final = gateway.request("POST", "/v1/responses", {**body, "max_output_tokens": 16}) + counted: Final = gateway.request("POST", "/v1/responses/input_tokens", body) + assert generated.status_code == 200, generated.text + assert counted.status_code == 200, counted.text + assert _JSON_OBJECT.validate_json(counted.content)["input_tokens"] == _COUNT, counted.text + requests: Final = peer.drain() + (generated_request,) = (request for request in requests if request.target.endswith(":generateContent")) + (count_request,) = (request for request in requests if request.target.endswith(":countTokens")) + instruction: Final[JsonValue] = {"text": _RESPONSES_TOOL_ROUND_TRIP["instructions"]} + first_turn, *later_turns = _JSON_LIST.validate_python(_counted_contents(_json_body(count_request))) + first_parts: Final = _JSON_LIST.validate_python(_JSON_OBJECT.validate_python(first_turn)["parts"]) + assert instruction in first_parts, count_request.body + counted_turns: Final = [ + { + **_JSON_OBJECT.validate_python(first_turn), + "parts": [part for part in first_parts if part != instruction], + }, + *later_turns, + ] + assert counted_turns == _json_body(generated_request)["contents"], count_request.body diff --git a/tests/integration/providers/test_vertex_partner_count_tokens_wire.py b/tests/integration/providers/test_vertex_partner_count_tokens_wire.py index 1956301f1be..c679311e4cc 100644 --- a/tests/integration/providers/test_vertex_partner_count_tokens_wire.py +++ b/tests/integration/providers/test_vertex_partner_count_tokens_wire.py @@ -19,6 +19,13 @@ from integration._support.client import Gateway, Scenario, eventually from integration._support.process import graceful_stop_seconds, owned_proxy_process from integration._support.vertex import service_account_json from integration._support.wire import Reply, Request, Wire, wire_server +from integration.providers._count_tokens_system_lift import ( + RESPONSES_REQUEST_OPTIONS, + RESPONSES_TOOL_USE, + count_request_fields, + counted_fields, + inference_count_fields, +) from integration._support.ports import allocate_port from pydantic import JsonValue, TypeAdapter from tokenizers import Regex, Tokenizer, models, pre_tokenizers @@ -427,14 +434,22 @@ def test_utils_token_counter_local_mode_never_calls_the_peer(gateway: Gateway) - assert wire.drain() == () -def test_utils_token_counter_surfaces_the_peer_error_for_openai_tools(gateway: Gateway) -> None: +def _inference_and_count_fields(wire: Wire) -> tuple[dict[str, JsonValue], ...]: + requests: Final = wire.drain() + (inference,) = (request for request in requests if request.target == _MESSAGE_TARGET) + return (counted_fields(_JSON_OBJECT.validate_json(inference.body)), *map(counted_fields, _count_bodies(requests))) + + +def test_utils_token_counter_counts_openai_tools_the_way_chat_inference_sends_them(gateway: Gateway) -> None: with wire_server(_peer(_strict)) as wire, gateway.scenario() as scenario: model: Final = _deployment(gateway, scenario, wire.url) body: Final = {**_bare(model), "tools": _OPENAI_TOOLS} + generated: Final = gateway.request("POST", "/v1/chat/completions", {**body, "max_tokens": 16}) + assert generated.status_code == 200, generated.text response: Final = gateway.request("POST", "/utils/token_counter", body, params={"call_endpoint": "true"}) - assert response.status_code == 400, response.text - assert "total_tokens" not in response.text, response.text - assert _counted_bodies(wire) == ({**_PEER_BARE, "tools": _OPENAI_TOOLS},) + assert _payload(response)["total_tokens"] == _PEER_COUNT, response.text + inference, counted = _inference_and_count_fields(wire) + assert counted == inference, (counted, inference) def test_responses_input_tokens_counts_through_the_partner_peer(gateway: Gateway) -> None: @@ -451,8 +466,24 @@ def test_responses_input_tokens_counts_through_the_partner_peer(gateway: Gateway assert _counted_bodies(wire) == (_PEER_BARE,) -def test_responses_input_tokens_surfaces_the_peer_error(gateway: Gateway) -> None: +@pytest.mark.parametrize("request_body", RESPONSES_TOOL_USE.values(), ids=RESPONSES_TOOL_USE.keys()) +def test_responses_input_tokens_counts_what_responses_inference_sends( + gateway: Gateway, request_body: dict[str, JsonValue] +) -> None: with wire_server(_peer(_strict)) as wire, gateway.scenario() as scenario: + model: Final = _deployment(gateway, scenario, wire.url) + generated: Final = gateway.request( + "POST", "/v1/responses", {**request_body, "model": model, "max_output_tokens": 16} + ) + assert generated.status_code == 200, generated.text + response: Final = gateway.request("POST", "/v1/responses/input_tokens", {**request_body, "model": model}) + assert _payload(response)["input_tokens"] == _PEER_COUNT, response.text + inference, counted = _inference_and_count_fields(wire) + assert counted == inference, (counted, inference) + + +def test_responses_input_tokens_surfaces_the_peer_error(gateway: Gateway) -> None: + with wire_server(_peer(_rejecting(400))) as wire, gateway.scenario() as scenario: model: Final = _deployment(gateway, scenario, wire.url) response: Final = gateway.request( "POST", @@ -462,7 +493,33 @@ def test_responses_input_tokens_surfaces_the_peer_error(gateway: Gateway) -> Non assert response.status_code == 400, response.text assert response.json() == _RESPONSES_ROUTE.rejection(_REJECTION), response.text (sent,) = _counted_bodies(wire) - assert sent["tools"] == _RESPONSES_TOOLS, sent + assert sent["system"] == [{"type": "text", "text": "Be terse"}], sent + assert sent["tools"] == [ + { + "name": "get_weather", + "input_schema": _WEATHER_SCHEMA, + "type": "custom", + "description": "Look up the current weather for a city", + } + ], sent + + +def test_responses_input_tokens_rejects_an_unpaired_tool_output_without_calling_vertex(gateway: Gateway) -> None: + with wire_server(_peer(_strict)) as wire, gateway.scenario() as scenario: + model: Final = _deployment(gateway, scenario, wire.url) + body: Final[dict[str, JsonValue]] = { + "model": model, + "input": [ + {"role": "user", "content": "What is the weather in Paris?"}, + {"type": "function_call", "call_id": "call_1", "name": "get_weather", "arguments": "Paris?"}, + {"type": "function_call_output", "call_id": "call_1", "output": "Sunny"}, + ], + "tools": _RESPONSES_TOOLS, + } + response: Final = gateway.request("POST", "/v1/responses/input_tokens", body) + assert response.status_code == 400, response.text + assert "get_weather" in _error_message(_JSON_OBJECT.validate_json(response.content)), response.text + assert wire.drain() == () def test_responses_input_tokens_types_a_peer_error_by_its_status(gateway: Gateway) -> None: @@ -890,3 +947,20 @@ def test_responses_endpoint_on_the_same_deployment_still_generates(gateway: Gate (sent,) = wire.drain() assert sent.target == _MESSAGE_TARGET, sent.target assert marker in sent.body.decode(), sent.body + + +def test_responses_input_tokens_counts_the_structured_output_responses_inference_sends(gateway: Gateway) -> None: + request_body: Final = RESPONSES_REQUEST_OPTIONS["text-format"] + with wire_server(_peer(_strict)) as wire, gateway.scenario() as scenario: + model: Final = _deployment(gateway, scenario, wire.url) + generated: Final = gateway.request( + "POST", "/v1/responses", {**request_body, "model": model, "max_output_tokens": 4096} + ) + assert generated.status_code == 200, generated.text + response: Final = gateway.request("POST", "/v1/responses/input_tokens", {**request_body, "model": model}) + assert _payload(response)["input_tokens"] == _PEER_COUNT, response.text + requests: Final = wire.drain() + (inference,) = (request for request in requests if request.target == _MESSAGE_TARGET) + (counted,) = _count_bodies(requests) + expected: Final = inference_count_fields(_JSON_OBJECT.validate_json(inference.body)) + assert count_request_fields(counted) == expected, (counted, expected) diff --git a/tests/integration/routing/test_priority_scheduler_queue_cleanup.py b/tests/integration/routing/test_priority_scheduler_queue_cleanup.py index 993da52fc67..9fc21843b04 100644 --- a/tests/integration/routing/test_priority_scheduler_queue_cleanup.py +++ b/tests/integration/routing/test_priority_scheduler_queue_cleanup.py @@ -11,6 +11,7 @@ from collections.abc import Callable, Iterator, Mapping, Sequence from concurrent.futures import ThreadPoolExecutor from contextlib import ExitStack from dataclasses import dataclass +from itertools import product from pathlib import Path from queue import SimpleQueue from typing import Final, Literal, TypeVar @@ -24,7 +25,7 @@ import yaml from integration._support.client import Gateway, eventually, gateway_from_environment from integration._support.database import read_rows from integration._support.openai_wire import answering_model_discovery, chat_reply, openai_error, responses_reply -from integration._support.process import graceful_stop_seconds, owned_proxy_process +from integration._support.process import OwnedState, graceful_stop_seconds, owned_proxy_process from integration._support.redis_process import OwnedRedis, owned_redis from integration._support.timing import assert_cut_short from integration._support.wire import Reply, Request, Wire, wire_server @@ -61,6 +62,18 @@ INMEM_GROUP: Final = "sched-inmem" OUTAGE_GROUP: Final = "sched-outage" KILL_GROUP: Final = "sched-kill" GHOST_ENTRY: Final[list[JsonValue]] = [1, "ghost"] +DEFAULT_PRIORITY: Final = 3 +DEFAULT_GROUPS: Final = tuple(f"sched-default-{row}" for row in ("d1", "d2", "d3", "d4", "d5", "d6", "d7", "d8", "d9")) +PROMPT_GROUP: Final = "sched-default-prompt" +PROMPT_ID: Final = "sched_default" +PROMPT_PREFIX: Final = "Scheduled by default for" +DROP_GROUP: Final = "sched-default-drop" +TEAM_GROUP: Final = "sched-default-team" +ZERO_GROUPS: Final = ("sched-zero-plain", "sched-zero-dropped") +DIGIT_GROUPS: Final = ("sched-digit-plain", "sched-digit-dropped") +IGNORED_GROUP: Final = "sched-ignored" +PRIORITIZED: Final = "x-litellm-request-prioritization-used" +IGNORED_WARNING: Final = "router_settings.default_priority is ignored" JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue]) JSON_LIST: Final = TypeAdapter(list[JsonValue]) @@ -160,15 +173,24 @@ def assert_never(received: Sequence[str], markers: Sequence[str]) -> None: assert not set(markers) & set(received), (markers, received) -def deployment_entry(group: str, wire: Wire) -> dict[str, JsonValue]: +def deployment_entry( + group: str, + wire: Wire, + *, + model_name: str | None = None, + model: str | None = None, + model_info: Mapping[str, JsonValue] | None = None, + **litellm_params: JsonValue, +) -> dict[str, JsonValue]: return { - "model_name": group, + "model_name": model_name or group, "litellm_params": { - "model": f"openai/{upstream_name(group)}", + "model": model or f"openai/{upstream_name(group)}", "api_base": wire.url + "/v1", "api_key": "synthetic-openai-key", + **litellm_params, }, - "model_info": {"id": f"{group}-deployment"}, + "model_info": {"id": f"{group}-deployment", **(model_info or {})}, } @@ -179,12 +201,16 @@ def owned_config( settings: Mapping[str, JsonValue], *, cancel_on_disconnect: bool = False, + extra_models: Sequence[Mapping[str, JsonValue]] = (), + litellm_settings: Mapping[str, JsonValue] | None = None, ) -> Path: base: Final = JSON_OBJECT.validate_python( yaml.safe_load((Path(__file__).parents[1] / "proxy_config.yaml").read_text()) ) general_settings: Final = base.get("general_settings", {}) assert isinstance(general_settings, dict) + base_litellm_settings: Final = base.get("litellm_settings", {}) + assert isinstance(base_litellm_settings, dict) general: Final[dict[str, JsonValue]] = { **general_settings, **({"cancel_on_disconnect": True} if cancel_on_disconnect else {}), @@ -192,8 +218,9 @@ def owned_config( config: Final[dict[str, JsonValue]] = { **base, "general_settings": general, + "litellm_settings": {**base_litellm_settings, **(litellm_settings or {})}, "router_settings": dict(settings), - "model_list": [deployment_entry(group, wire) for group in groups], + "model_list": [*(deployment_entry(group, wire) for group in groups), *(dict(entry) for entry in extra_models)], } path: Final = directory / f"scheduler-{uuid.uuid4().hex[:8]}.yaml" path.write_text(yaml.safe_dump(config)) @@ -209,6 +236,10 @@ def redis_settings(cache: OwnedRedis) -> dict[str, JsonValue]: return {"num_retries": 0, "redis_host": cache.host, "redis_port": cache.port} +def priority_field(priority: int | None) -> dict[str, JsonValue]: + return {} if priority is None else {"priority": priority} + + def chat_body(group: str, marker: str, **extra: JsonValue) -> dict[str, JsonValue]: return {"model": group, "messages": [{"role": "user", "content": marker}], **extra} @@ -279,26 +310,21 @@ def stream_identities(text: str) -> frozenset[str]: return frozenset(str(frame["id"]) for frame in frames) -def call(gateway: Gateway, endpoint: Endpoint, group: str, marker: str, priority: int = 1) -> Answer: +def call(gateway: Gateway, endpoint: Endpoint, group: str, marker: str, priority: int | None = 1) -> Answer: + field: Final = priority_field(priority) match endpoint: case "chat": - return post(gateway, "/v1/chat/completions", chat_body(group, marker, priority=priority)) + return post(gateway, "/v1/chat/completions", chat_body(group, marker, **field)) case "chat-stream": - return stream_text( - gateway, "/v1/chat/completions", chat_body(group, marker, priority=priority, stream=True) - ) + return stream_text(gateway, "/v1/chat/completions", chat_body(group, marker, stream=True, **field)) case "completions": - return post(gateway, "/v1/completions", completion_body(group, marker, priority=priority)) + return post(gateway, "/v1/completions", completion_body(group, marker, **field)) case "completions-stream": - return stream_text( - gateway, "/v1/completions", completion_body(group, marker, priority=priority, stream=True) - ) + return stream_text(gateway, "/v1/completions", completion_body(group, marker, stream=True, **field)) case "queue": - return post(gateway, "/queue/chat/completions", chat_body(group, marker, priority=priority)) + return post(gateway, "/queue/chat/completions", chat_body(group, marker, **field)) case "queue-stream": - return stream_text( - gateway, "/queue/chat/completions", chat_body(group, marker, priority=priority, stream=True) - ) + return stream_text(gateway, "/queue/chat/completions", chat_body(group, marker, stream=True, **field)) def served_identity(status: int, text: str, marker: str) -> str: @@ -363,15 +389,19 @@ def waiting_entries(cache: OwnedRedis, group: str, priority: int) -> list[JsonVa ) -def cooled(gateway: Gateway, upstream: Upstream, group: str) -> None: +def cooled_with(upstream: Upstream, group: str, send: Callable[[], Answer]) -> None: upstream.refusing[upstream_name(group)].set() - trip: Final = post(gateway, "/v1/chat/completions", chat_body(group, new_marker())) + trip: Final = send() assert trip.status == 401, (trip.status, trip.text) - eventually( - lambda: post(gateway, "/v1/chat/completions", chat_body(group, new_marker())), - lambda answer: answer.status == 429 and NO_DEPLOYMENTS in answer.text, - seconds=10, - ) + eventually(send, lambda answer: answer.status == 429 and NO_DEPLOYMENTS in answer.text, seconds=10) + + +def cooled(gateway: Gateway, upstream: Upstream, group: str) -> None: + cooled_with(upstream, group, lambda: post(gateway, "/v1/chat/completions", chat_body(group, new_marker()))) + + +def cooled_outside_the_scheduler(gateway: Gateway, upstream: Upstream, group: str) -> None: + cooled_with(upstream, group, lambda: post(gateway, "/v1/responses", {"model": group, "input": new_marker()})) def assert_refused_at_once(answer: Answer) -> None: @@ -488,16 +518,42 @@ def test_other_prioritized_endpoints_are_served_once_and_billed( spend_row_lands(identity) -@pytest.mark.parametrize("priority", ("1", [1], "", "p" * 5120, 0), ids=("string", "list", "empty", "5kb", "zero")) -def test_non_integer_priority_bypasses_the_scheduler_and_is_forwarded( +def upstream_body_for(wire: Wire, marker: str) -> dict[str, JsonValue]: + (upstream_request,) = tuple(request for request in wire.drain() if marker.encode() in request.body) + return JSON_OBJECT.validate_json(upstream_request.body) + + +@pytest.mark.parametrize("priority", ("high", [1], "", "p" * 5120, 1.5), ids=("word", "list", "empty", "5kb", "float")) +def test_non_integer_priority_is_refused_before_the_upstream( gateway: Gateway, rig_model: tuple[str, Wire], priority: JsonValue ) -> None: model, wire = rig_model marker: Final = new_marker() answer: Final = post(gateway, "/v1/chat/completions", chat_body(model, marker, priority=priority)) + assert answer.status == 400, (answer.status, answer.text) + error: Final = JSON_OBJECT.validate_json(answer.text)["error"] + assert isinstance(error, dict), answer.text + assert error["param"] == "priority", answer.text + assert "priority must be an integer" in str(error["message"]), answer.text + assert_never(received_markers(wire), (marker,)) + + +def test_non_integer_priority_is_dropped_under_drop_params(gateway: Gateway, rig_model: tuple[str, Wire]) -> None: + model, wire = rig_model + marker: Final = new_marker() + answer: Final = post(gateway, "/v1/chat/completions", chat_body(model, marker, priority="high", drop_params=True)) assert_served(answer, marker) - (upstream_request,) = tuple(request for request in wire.drain() if marker.encode() in request.body) - assert JSON_OBJECT.validate_json(upstream_request.body).get("priority") == priority + assert answer.headers.get("x-litellm-request-prioritization-used") is None, answer.headers + assert "priority" not in upstream_body_for(wire, marker) + + +def test_zero_priority_is_scheduled_and_not_forwarded(gateway: Gateway, rig_model: tuple[str, Wire]) -> None: + model, wire = rig_model + marker: Final = new_marker() + answer: Final = post(gateway, "/v1/chat/completions", chat_body(model, marker, priority=0)) + assert_served(answer, marker) + assert answer.headers.get("x-litellm-request-prioritization-used") == "True", answer.headers + assert "priority" not in upstream_body_for(wire, marker) def test_unauthenticated_prioritized_request_never_reaches_the_upstream( @@ -747,7 +803,9 @@ def test_disconnected_waiter_is_removed_from_the_queue(pair: Pair) -> None: Outcome = Answer | httpx.TransportError -def burst(gateway: Gateway, group: str, count: int) -> tuple[tuple[Endpoint, str, Outcome], ...]: +def burst( + gateway: Gateway, group: str, count: int, priority: int | None = 1 +) -> tuple[tuple[Endpoint, str, Outcome], ...]: plan: Final[tuple[tuple[Endpoint, str], ...]] = tuple( (ENDPOINTS[index % len(ENDPOINTS)], new_marker()) for index in range(count) ) @@ -756,7 +814,7 @@ def burst(gateway: Gateway, group: str, count: int) -> tuple[tuple[Endpoint, str endpoint, marker = item with httpx.Client(base_url=gateway.client.base_url, timeout=60, trust_env=False) as client: try: - return call(Gateway(client, gateway.key, gateway.upstream_url), endpoint, group, marker) + return call(Gateway(client, gateway.key, gateway.upstream_url), endpoint, group, marker, priority) except httpx.TransportError as error: return error @@ -772,10 +830,14 @@ def assert_all_served(outcomes: Sequence[tuple[Endpoint, str, Outcome]]) -> tupl return tuple(marker for _, marker, _ in outcomes) -def served_eventually(gateway: Gateway, group: str, marker: str) -> None: +def default_for(priority: int | None) -> dict[str, JsonValue]: + return {} if priority is not None else {"default_priority": DEFAULT_PRIORITY} + + +def served_eventually(gateway: Gateway, group: str, marker: str, priority: int | None = 1) -> None: def send() -> Outcome: try: - return post(gateway, "/v1/chat/completions", chat_body(group, marker, priority=1)) + return post(gateway, "/v1/chat/completions", chat_body(group, marker, **priority_field(priority))) except httpx.TransportError as error: return error @@ -784,22 +846,25 @@ def served_eventually(gateway: Gateway, group: str, marker: str) -> None: assert_served(answer, marker) +@pytest.mark.parametrize("priority", (1, None), ids=("explicit", "default")) @pytest.mark.timeout(OWNED_CELL_TIMEOUT) -def test_prioritized_requests_survive_a_redis_outage(gateway: Gateway, tmp_path: Path) -> None: +def test_prioritized_requests_survive_a_redis_outage(gateway: Gateway, tmp_path: Path, priority: int | None) -> None: upstream: Final = upstream_for((OUTAGE_GROUP,)) with owned_redis(tmp_path) as cache, wire_server(answering_model_discovery(upstream.respond)) as wire: - config: Final = owned_config(tmp_path, wire, (OUTAGE_GROUP,), redis_settings(cache)) + config: Final = owned_config( + tmp_path, wire, (OUTAGE_GROUP,), {**redis_settings(cache), **default_for(priority)} + ) overrides: Final = { "REDIS_HOST": cache.host, "REDIS_PORT": str(cache.port), "REDIS_CIRCUIT_BREAKER_RECOVERY_TIMEOUT": "1", } with owned_proxy_process(gateway, tmp_path, overrides, config=config, workers=2) as owned: - before: Final = assert_all_served(burst(owned.gateway, OUTAGE_GROUP, 12)) + before: Final = assert_all_served(burst(owned.gateway, OUTAGE_GROUP, 12, priority)) cache.stop() - during: Final = assert_all_served(burst(owned.gateway, OUTAGE_GROUP, 12)) + during: Final = assert_all_served(burst(owned.gateway, OUTAGE_GROUP, 12, priority)) cache.start() - after: Final = assert_all_served(burst(owned.gateway, OUTAGE_GROUP, 12)) + after: Final = assert_all_served(burst(owned.gateway, OUTAGE_GROUP, 12, priority)) assert_once(received_markers(wire), (*before, *during, *after)) eventually(lambda: queue_entries(cache, OUTAGE_GROUP), lambda entries: entries in (None, []), seconds=10) @@ -813,13 +878,14 @@ def established_upstream_connections(pid: int, wire: Wire) -> int: ) +@pytest.mark.parametrize("priority", (1, None), ids=("explicit", "default")) @pytest.mark.timeout(OWNED_CELL_TIMEOUT) def test_sibling_worker_keeps_serving_prioritized_requests_after_a_worker_is_killed( - gateway: Gateway, tmp_path: Path + gateway: Gateway, tmp_path: Path, priority: int | None ) -> None: upstream: Final = upstream_for((KILL_GROUP,), hold=(KILL_GROUP,)) with owned_redis(tmp_path) as cache, wire_server(answering_model_discovery(upstream.respond)) as wire: - config: Final = owned_config(tmp_path, wire, (KILL_GROUP,), redis_settings(cache)) + config: Final = owned_config(tmp_path, wire, (KILL_GROUP,), {**redis_settings(cache), **default_for(priority)}) overrides: Final = {"REDIS_HOST": cache.host, "REDIS_PORT": str(cache.port)} with owned_proxy_process(gateway, tmp_path, overrides, config=config, workers=2) as owned: workers: Final = eventually( @@ -828,7 +894,7 @@ def test_sibling_worker_keeps_serving_prioritized_requests_after_a_worker_is_kil seconds=graceful_stop_seconds(), ) with ThreadPoolExecutor(max_workers=1) as pool: - pending: Final = pool.submit(burst, owned.gateway, KILL_GROUP, 20) + pending: Final = pool.submit(burst, owned.gateway, KILL_GROUP, 20, priority) eventually(upstream.held.qsize, lambda size: size == 20, seconds=60) held_by: Final = {pid: established_upstream_connections(pid, wire) for pid in workers} assert sum(held_by.values()) == 20, held_by @@ -844,10 +910,502 @@ def test_sibling_worker_keeps_serving_prioritized_requests_after_a_worker_is_kil assert len(failed) == held_by[victim_pid], (held_by, len(failed)) assert_all_served(answered) follow_up: Final = new_marker() - served_eventually(owned.gateway, KILL_GROUP, follow_up) + served_eventually(owned.gateway, KILL_GROUP, follow_up, priority) eventually( lambda: len(STARTED_WORKER.findall(owned.log.read_text())), lambda count: count == 3, seconds=graceful_stop_seconds(), ) assert_once(received_markers(wire), (*(marker for _, marker, _ in outcomes), follow_up)) + + +@dataclass(frozen=True, slots=True) +class Defaulted: + pair: Pair + team_key: str + + def as_team(self) -> Gateway: + return Gateway(self.pair.first.client, self.team_key, self.pair.first.upstream_url) + + +def prompt_directory(directory: Path) -> Path: + prompts: Final = directory / "prompts" + prompts.mkdir() + (prompts / f"{PROMPT_ID}.prompt").write_text( + "---\n" + f"model: openai/{upstream_name(PROMPT_GROUP)}\n" + "input:\n" + " schema:\n" + " user_message: string\n" + "---\n" + "\n" + f"{PROMPT_PREFIX} {{{{user_message}}}}\n" + ) + return prompts + + +@pytest.fixture(scope="module") +def defaulted(tmp_path_factory: pytest.TempPathFactory) -> Iterator[Defaulted]: + directory: Final = tmp_path_factory.mktemp("scheduler-default") + upstream: Final = upstream_for((*DEFAULT_GROUPS, PROMPT_GROUP, DROP_GROUP, TEAM_GROUP)) + with ExitStack() as stack: + gateway: Final = stack.enter_context(gateway_from_environment()) + scenario: Final = stack.enter_context(gateway.scenario()) + team: Final = scenario.team(models=[]) + team_key: Final = scenario.key(team_id=team) + cache: Final = stack.enter_context(owned_redis(directory)) + wire: Final = stack.enter_context(wire_server(answering_model_discovery(upstream.respond))) + extra_models: Final = ( + deployment_entry( + PROMPT_GROUP, wire, model=f"dotprompt/openai/{upstream_name(PROMPT_GROUP)}", prompt_id=PROMPT_ID + ), + deployment_entry(DROP_GROUP, wire, drop_params=True), + deployment_entry( + TEAM_GROUP, + wire, + model_name=f"{TEAM_GROUP}-internal", + model_info={"team_id": team, "team_public_model_name": TEAM_GROUP}, + drop_params=True, + ), + ) + settings: Final[dict[str, JsonValue]] = { + **cooldown_settings(cache), + "default_priority": DEFAULT_PRIORITY, + "fallbacks": [{DEFAULT_GROUPS[7]: [DEFAULT_GROUPS[8]]}], + } + config: Final = owned_config( + directory, + wire, + DEFAULT_GROUPS, + settings, + cancel_on_disconnect=True, + extra_models=extra_models, + litellm_settings={"global_prompt_directory": str(prompt_directory(directory))}, + ) + overrides: Final = {"REDIS_HOST": cache.host, "REDIS_PORT": str(cache.port)} + shared: Final = OwnedState.SHARED_WITH_WORKER + first: Final = stack.enter_context( + owned_proxy_process(gateway, directory, overrides, config=config, workers=2, state=shared) + ) + second: Final = stack.enter_context( + owned_proxy_process(gateway, directory, overrides, config=config, workers=2, state=shared) + ) + yield Defaulted(Pair(first.gateway, second.gateway, cache, wire, upstream), team_key) + + +def assert_prioritized(answer: Answer) -> None: + assert answer.headers.get(PRIORITIZED) == "True", answer.headers + + +def assert_unprioritized(answer: Answer) -> None: + assert answer.headers.get(PRIORITIZED) is None, answer.headers + + +def assert_refused_as_non_integer(answer: Answer) -> None: + assert answer.status == 400, (answer.status, answer.text) + error: Final = JSON_OBJECT.validate_json(answer.text)["error"] + assert isinstance(error, dict), answer.text + assert error["param"] == "priority", answer.text + assert "priority must be an integer" in str(error["message"]), answer.text + + +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_raw_chat_without_priority_is_scheduled_at_the_default_and_billed(defaulted: Defaulted) -> None: + group: Final = DEFAULT_GROUPS[0] + marker: Final = new_marker() + answer: Final = post(defaulted.pair.first, "/v1/chat/completions", chat_body(group, marker)) + identity: Final = assert_served(answer, marker) + assert_prioritized(answer) + assert "priority" not in upstream_body_for(defaulted.pair.wire, marker) + spend_row_lands(identity) + + +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_raw_chat_stream_without_priority_is_served_once(defaulted: Defaulted) -> None: + group: Final = DEFAULT_GROUPS[0] + marker: Final = new_marker() + answer: Final = stream_text(defaulted.pair.second, "/v1/chat/completions", chat_body(group, marker, stream=True)) + assert_served(answer, marker) + assert_prioritized(answer) + assert_once(received_markers(defaulted.pair.wire), (marker,)) + + +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_sdk_chat_without_priority_is_scheduled_at_the_default_and_billed(defaulted: Defaulted) -> None: + group: Final = DEFAULT_GROUPS[0] + marker: Final = new_marker() + client: Final = sdk(defaulted.pair.first) + raw: Final = sdk_settled( + lambda: client.chat.completions.with_raw_response.create( + model=group, messages=[{"role": "user", "content": marker}] + ) + ) + assert served_identity(raw.status_code, raw.text, marker) == f"chatcmpl-{marker}" + assert raw.headers.get(PRIORITIZED) == "True", dict(raw.headers) + assert "priority" not in upstream_body_for(defaulted.pair.wire, marker) + spend_row_lands(f"chatcmpl-{marker}") + + +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_sdk_chat_stream_without_priority_is_served_once(defaulted: Defaulted) -> None: + group: Final = DEFAULT_GROUPS[0] + marker: Final = new_marker() + client: Final = sdk(defaulted.pair.second) + chunks: Final = sdk_settled( + lambda: tuple( + client.chat.completions.create(model=group, messages=[{"role": "user", "content": marker}], stream=True) + ) + ) + assert {chunk.id for chunk in chunks} == {f"chatcmpl-{marker}"}, chunks + content: Final = "".join(chunk.choices[0].delta.content or "" for chunk in chunks if chunk.choices) + assert content == f"served {marker}", chunks + assert_once(received_markers(defaulted.pair.wire), (marker,)) + + +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_async_sdk_chat_without_priority_is_scheduled_at_the_default(defaulted: Defaulted) -> None: + group: Final = DEFAULT_GROUPS[0] + marker: Final = new_marker() + gateway: Final = defaulted.pair.first + + async def send() -> tuple[int, str, str | None]: + async with openai.AsyncOpenAI( + base_url=str(gateway.client.base_url), api_key=gateway.key, max_retries=0, timeout=30 + ) as client: + raw: Final = await client.chat.completions.with_raw_response.create( + model=group, messages=[{"role": "user", "content": marker}] + ) + return raw.status_code, raw.text, raw.headers.get(PRIORITIZED) + + status, text, prioritized = sdk_settled(lambda: asyncio.run(send())) + assert served_identity(status, text, marker) == f"chatcmpl-{marker}" + assert prioritized == "True" + assert_once(received_markers(defaulted.pair.wire), (marker,)) + + +@pytest.mark.parametrize("priority", (1, 0, -1, 2**40), ids=("one", "zero", "negative", "huge")) +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_explicit_integer_priority_under_a_default_is_scheduled_once(defaulted: Defaulted, priority: int) -> None: + group: Final = DEFAULT_GROUPS[1] + marker: Final = new_marker() + answer: Final = post(defaulted.pair.first, "/v1/chat/completions", chat_body(group, marker, priority=priority)) + assert_served(answer, marker) + assert_prioritized(answer) + assert "priority" not in upstream_body_for(defaulted.pair.wire, marker) + + +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_null_priority_under_a_default_takes_the_default(defaulted: Defaulted) -> None: + group: Final = DEFAULT_GROUPS[1] + marker: Final = new_marker() + answer: Final = post(defaulted.pair.second, "/v1/chat/completions", chat_body(group, marker, priority=None)) + assert_served(answer, marker) + assert_prioritized(answer) + assert "priority" not in upstream_body_for(defaulted.pair.wire, marker) + + +@pytest.mark.parametrize( + "priority", + ("high", [1], 1.5, {"level": 3}, "", "p" * 5120), + ids=("word", "list", "float", "object", "empty", "5kb"), +) +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_non_integer_priority_under_a_default_is_refused_before_the_upstream( + defaulted: Defaulted, priority: JsonValue +) -> None: + group: Final = DEFAULT_GROUPS[1] + marker: Final = new_marker() + answer: Final = post(defaulted.pair.first, "/v1/chat/completions", chat_body(group, marker, priority=priority)) + assert_refused_as_non_integer(answer) + assert_never(received_markers(defaulted.pair.wire), (marker,)) + + +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_request_drop_params_replaces_a_non_integer_priority_with_the_default(defaulted: Defaulted) -> None: + group: Final = DEFAULT_GROUPS[1] + marker: Final = new_marker() + body: Final = chat_body(group, marker, priority="high", drop_params=True) + answer: Final = post(defaulted.pair.second, "/v1/chat/completions", body) + assert_served(answer, marker) + assert_prioritized(answer) + assert "priority" not in upstream_body_for(defaulted.pair.wire, marker) + + +@pytest.mark.parametrize("model", (DROP_GROUP, f"{DROP_GROUP}-deployment"), ids=("group", "deployment-id")) +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_deployment_drop_params_replaces_a_non_integer_priority_with_the_default( + defaulted: Defaulted, model: str +) -> None: + marker: Final = new_marker() + answer: Final = post(defaulted.pair.first, "/v1/chat/completions", chat_body(model, marker, priority="high")) + assert_served(answer, marker) + assert_prioritized(answer) + assert "priority" not in upstream_body_for(defaulted.pair.wire, marker) + + +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_team_deployment_drop_params_replaces_a_non_integer_priority_with_the_default(defaulted: Defaulted) -> None: + marker: Final = new_marker() + answer: Final = post(defaulted.as_team(), "/v1/chat/completions", chat_body(TEAM_GROUP, marker, priority="high")) + assert_served(answer, marker) + assert_prioritized(answer) + assert "priority" not in upstream_body_for(defaulted.pair.wire, marker) + + +def assert_waits_at( + gateway: Gateway, + cache: OwnedRedis, + upstream: Upstream, + group: str, + priority: int, + body: Mapping[str, JsonValue], +) -> None: + cooled_outside_the_scheduler(gateway, upstream, group) + write_queue(cache, group, [[priority - 1, "ghost"]]) + with ThreadPoolExecutor(max_workers=1) as pool: + waiter: Final = pool.submit(post, gateway, "/v1/chat/completions", body) + entries: Final = waiting_entries(cache, group, priority) + write_queue(cache, group, [entry for entry in entries if entry_priority(entry) == priority]) + assert_refused_before_the_router_timeout(waiter.result(timeout=30)) + assert_drained(cache, group) + + +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_requests_without_priority_wait_at_the_default_priority(defaulted: Defaulted) -> None: + group: Final = DEFAULT_GROUPS[2] + pair: Final = defaulted.pair + assert_waits_at(pair.second, pair.cache, pair.upstream, group, DEFAULT_PRIORITY, chat_body(group, new_marker())) + + +@pytest.mark.timeout(OWNED_CELL_TIMEOUT) +def test_zero_default_priority_queues_requests_without_one_and_dropped_ones(gateway: Gateway, tmp_path: Path) -> None: + upstream: Final = upstream_for(ZERO_GROUPS) + with owned_redis(tmp_path) as cache, wire_server(answering_model_discovery(upstream.respond)) as wire: + settings: Final[dict[str, JsonValue]] = { + **cooldown_settings(cache), + "default_priority": 0, + "default_litellm_params": {"drop_params": True}, + } + config: Final = owned_config(tmp_path, wire, ZERO_GROUPS, settings) + overrides: Final = {"REDIS_HOST": cache.host, "REDIS_PORT": str(cache.port)} + with owned_proxy_process(gateway, tmp_path, overrides, config=config, workers=2) as owned: + plain, dropped = ZERO_GROUPS + assert_waits_at(owned.gateway, cache, upstream, plain, 0, chat_body(plain, new_marker())) + assert_waits_at( + owned.gateway, cache, upstream, dropped, 0, chat_body(dropped, new_marker(), priority="high") + ) + + +@pytest.mark.timeout(OWNED_CELL_TIMEOUT) +def test_digit_string_default_priority_queues_requests_without_one_and_dropped_ones( + gateway: Gateway, tmp_path: Path +) -> None: + upstream: Final = upstream_for(DIGIT_GROUPS) + with owned_redis(tmp_path) as cache, wire_server(answering_model_discovery(upstream.respond)) as wire: + settings: Final[dict[str, JsonValue]] = {**cooldown_settings(cache), "default_priority": "2"} + config: Final = owned_config(tmp_path, wire, DIGIT_GROUPS, settings, litellm_settings={"drop_params": True}) + overrides: Final = {"REDIS_HOST": cache.host, "REDIS_PORT": str(cache.port)} + with owned_proxy_process(gateway, tmp_path, overrides, config=config, workers=2) as owned: + plain, dropped = DIGIT_GROUPS + assert_waits_at(owned.gateway, cache, upstream, plain, 2, chat_body(plain, new_marker())) + assert_waits_at( + owned.gateway, cache, upstream, dropped, 2, chat_body(dropped, new_marker(), priority="high") + ) + + +@pytest.mark.parametrize("configured", ("high", True), ids=("word", "bool")) +@pytest.mark.timeout(OWNED_CELL_TIMEOUT) +def test_an_invalid_default_priority_is_ignored_with_a_warning( + gateway: Gateway, tmp_path: Path, configured: JsonValue +) -> None: + upstream: Final = upstream_for((IGNORED_GROUP,)) + with wire_server(answering_model_discovery(upstream.respond)) as wire: + config: Final = owned_config( + tmp_path, wire, (IGNORED_GROUP,), {"num_retries": 0, "default_priority": configured} + ) + with owned_proxy_process(gateway, tmp_path, {}, config=config, workers=2) as owned: + marker: Final = new_marker() + answer: Final = post(owned.gateway, "/v1/chat/completions", chat_body(IGNORED_GROUP, marker)) + assert_served(answer, marker) + assert_unprioritized(answer) + assert IGNORED_WARNING in owned.log.read_text() + assert_once(received_markers(wire), (marker,)) + + +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_requests_without_priority_fall_back_to_the_fallback_group(defaulted: Defaulted) -> None: + primary, fallback = DEFAULT_GROUPS[7], DEFAULT_GROUPS[8] + defaulted.pair.upstream.refusing[upstream_name(primary)].set() + marker: Final = new_marker() + answer: Final = post(defaulted.pair.first, "/v1/chat/completions", chat_body(primary, marker)) + assert_served(answer, marker) + assert_prioritized(answer) + attempts: Final = tuple( + str(JSON_OBJECT.validate_json(request.body)["model"]) + for request in defaulted.pair.wire.drain() + if marker.encode() in request.body + ) + assert attempts == (upstream_name(primary), upstream_name(fallback)), attempts + + +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_cooled_group_refuses_requests_without_priority_at_once(defaulted: Defaulted) -> None: + group: Final = DEFAULT_GROUPS[3] + cooled(defaulted.pair.second, defaulted.pair.upstream, group) + assert_refused_at_once(post(defaulted.pair.second, "/v1/chat/completions", chat_body(group, new_marker()))) + assert_drained(defaulted.pair.cache, group) + + +@pytest.mark.parametrize("priority", (None, 1), ids=("default", "explicit")) +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_prompt_management_model_is_scheduled(defaulted: Defaulted, priority: int | None) -> None: + marker: Final = new_marker() + body: Final = chat_body(PROMPT_GROUP, marker, prompt_variables={"user_message": marker}, **priority_field(priority)) + answer: Final = post(defaulted.pair.first, "/v1/chat/completions", body) + assert_served(answer, marker) + assert_prioritized(answer) + upstream_body: Final = upstream_body_for(defaulted.pair.wire, marker) + assert f"{PROMPT_PREFIX} {marker}" in json.dumps(upstream_body), upstream_body + assert "priority" not in upstream_body + + +@pytest.mark.parametrize("endpoint", ("completions", "completions-stream")) +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_text_completions_without_priority_are_scheduled_at_the_default( + defaulted: Defaulted, endpoint: Endpoint +) -> None: + group: Final = DEFAULT_GROUPS[4] + marker: Final = new_marker() + answer: Final = call(defaulted.pair.second, endpoint, group, marker, priority=None) + identity: Final = assert_served(answer, marker) + assert_prioritized(answer) + assert "priority" not in upstream_body_for(defaulted.pair.wire, marker) + spend_row_lands(identity) + + +@pytest.mark.parametrize("priority", ("high", [1]), ids=("word", "list")) +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_text_completion_with_a_non_integer_priority_is_refused_before_the_upstream( + defaulted: Defaulted, priority: JsonValue +) -> None: + group: Final = DEFAULT_GROUPS[4] + marker: Final = new_marker() + answer: Final = post(defaulted.pair.first, "/v1/completions", completion_body(group, marker, priority=priority)) + assert_refused_as_non_integer(answer) + assert_never(received_markers(defaulted.pair.wire), (marker,)) + + +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_text_completion_drop_params_replaces_a_non_integer_priority_with_the_default(defaulted: Defaulted) -> None: + group: Final = DEFAULT_GROUPS[4] + marker: Final = new_marker() + body: Final = completion_body(group, marker, priority="high", drop_params=True) + answer: Final = post(defaulted.pair.second, "/v1/completions", body) + assert_served(answer, marker) + assert_prioritized(answer) + assert "priority" not in upstream_body_for(defaulted.pair.wire, marker) + + +@pytest.mark.parametrize("endpoint", ("queue", "queue-stream")) +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_queue_route_without_priority_takes_the_default(defaulted: Defaulted, endpoint: Endpoint) -> None: + group: Final = DEFAULT_GROUPS[5] + marker: Final = new_marker() + answer: Final = call(defaulted.pair.first, endpoint, group, marker, priority=None) + assert_served(answer, marker) + if endpoint == "queue": + assert answer.headers.get("x-litellm-priority") == str(DEFAULT_PRIORITY), answer.headers + assert "priority" not in upstream_body_for(defaulted.pair.wire, marker) + + +@pytest.mark.parametrize("priority", (1, "1", True, 1.0), ids=("integer", "digit-string", "bool", "whole-float")) +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_queue_route_with_an_explicit_priority_under_a_default_reports_it( + defaulted: Defaulted, priority: JsonValue +) -> None: + group: Final = DEFAULT_GROUPS[5] + marker: Final = new_marker() + answer: Final = post(defaulted.pair.second, "/queue/chat/completions", chat_body(group, marker, priority=priority)) + assert_served(answer, marker) + assert answer.headers.get("x-litellm-priority") == "1", answer.headers + assert "priority" not in upstream_body_for(defaulted.pair.wire, marker) + + +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_queue_route_refuses_a_word_priority(defaulted: Defaulted) -> None: + group: Final = DEFAULT_GROUPS[5] + marker: Final = new_marker() + answer: Final = post(defaulted.pair.first, "/queue/chat/completions", chat_body(group, marker, priority="high")) + assert_refused_as_non_integer(answer) + assert_never(received_markers(defaulted.pair.wire), (marker,)) + + +@pytest.mark.parametrize("path", ("/v1/messages", "/v1/responses"), ids=("messages", "responses")) +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_unscheduled_routes_without_priority_are_served_once_under_a_default(defaulted: Defaulted, path: str) -> None: + group: Final = DEFAULT_GROUPS[6] + marker: Final = new_marker() + body: Final[dict[str, JsonValue]] = ( + {"model": group, "max_tokens": 32, "messages": [{"role": "user", "content": marker}]} + if path == "/v1/messages" + else {"model": group, "input": marker} + ) + answer: Final = post(defaulted.pair.second, path, body) + assert answer.status == 200, (answer.status, answer.text) + assert markers_in(answer.text) == {marker}, answer.text + assert_once(received_markers(defaulted.pair.wire), (marker,)) + + +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_unauthenticated_request_without_priority_never_reaches_the_upstream(defaulted: Defaulted) -> None: + group: Final = DEFAULT_GROUPS[6] + marker: Final = new_marker() + response: Final = defaulted.pair.first.client.post("/v1/chat/completions", json=chat_body(group, marker)) + assert response.status_code == 401, response.text + assert_never(received_markers(defaulted.pair.wire), (marker,)) + + +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_cached_replay_under_a_default_reaches_the_upstream_once(defaulted: Defaulted) -> None: + group: Final = DEFAULT_GROUPS[6] + marker: Final = new_marker() + body: Final = chat_body(group, marker) + first: Final = post(defaulted.pair.first, "/v1/chat/completions", body) + assert_served(first, marker) + assert_prioritized(first) + replay: Final = post(defaulted.pair.second, "/v1/chat/completions", body) + assert_served(replay, marker) + assert_prioritized(replay) + assert_once(received_markers(defaulted.pair.wire), (marker,)) + + +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_concurrent_burst_without_priority_across_instances_and_endpoints_is_served(defaulted: Defaulted) -> None: + serve_burst_without_priority(defaulted.pair, DEFAULT_GROUPS[0]) + + +@pytest.mark.timeout(PAIR_CELL_TIMEOUT) +def test_concurrent_burst_without_priority_across_instances_leaves_no_queue_entry(defaulted: Defaulted) -> None: + pytest.skip("BUG: concurrent queue writes across workers can leave a served request's entry in the queue") + group: Final = DEFAULT_GROUPS[0] + serve_burst_without_priority(defaulted.pair, group) + assert_drained(defaulted.pair.cache, group) + + +def serve_burst_without_priority(pair: Pair, group: str) -> None: + primer: Final = new_marker() + assert_served(post(pair.first, "/v1/chat/completions", chat_body(group, primer)), primer) + instances: Final[tuple[Instance, ...]] = ("first", "second") + plan: Final = tuple((instance, endpoint, new_marker()) for instance, endpoint in product(instances, ENDPOINTS * 2)) + + def one(item: tuple[Instance, Endpoint, str]) -> Answer: + instance, endpoint, marker = item + return call(pair.at(instance), endpoint, group, marker, priority=None) + + with ThreadPoolExecutor(max_workers=len(plan)) as pool: + answers: Final = tuple(pool.map(one, plan)) + for (_, _, marker), answer in zip(plan, answers, strict=True): + assert_served(answer, marker) + closing: Final = new_marker() + assert_served(post(pair.second, "/v1/chat/completions", chat_body(group, closing)), closing) + assert_once(received_markers(pair.wire), (primer, *(marker for _, _, marker in plan), closing)) diff --git a/tests/integration/routing/test_prompt_cache_pin_ttl.py b/tests/integration/routing/test_prompt_cache_pin_ttl.py index 0a758d51b7e..f6ee96a9206 100644 --- a/tests/integration/routing/test_prompt_cache_pin_ttl.py +++ b/tests/integration/routing/test_prompt_cache_pin_ttl.py @@ -270,7 +270,7 @@ def test_chat_pin_lifetime_follows_the_longest_breakpoint_ttl_in_the_cacheable_p spend_row_lands(response_id) -def test_chat_one_hour_mark_on_a_tool_definition_alone_writes_no_pin(rig: _Rig) -> None: +def test_chat_one_hour_mark_on_a_tool_definition_alone_pins_the_served_deployment_for_an_hour(rig: _Rig) -> None: before: Final = _before(rig) marker: Final = new_marker() tool: Final[dict[str, JsonValue]] = { @@ -281,8 +281,10 @@ def test_chat_one_hour_mark_on_a_tool_definition_alone_writes_no_pin(rig: _Rig) response_id, served = post_chat( rig.owned.gateway, chat_body(_CLAUDE, _first_turn(new_marker(), marker, None), tools=[tool]) ) - assert served == rig.served_by(marker), served - no_pin_written(rig.redis, before, response_id) + _, pin = one_new_pin(rig.redis, before) + assert served == rig.served_by(marker) == pin.model_id, (served, pin) + assert lives_one_hour(pin), pin + spend_row_lands(response_id) def _openai_client(rig: _Rig) -> openai.OpenAI: diff --git a/tests/integration/routing/test_responses_websocket_turn_admission.py b/tests/integration/routing/test_responses_websocket_turn_admission.py index a246c89e7b3..87b56a92979 100644 --- a/tests/integration/routing/test_responses_websocket_turn_admission.py +++ b/tests/integration/routing/test_responses_websocket_turn_admission.py @@ -27,7 +27,6 @@ from integration._support.client import ( object_value, string_value, ) -from integration._support.database import read_rows from integration._support.process import graceful_stop_seconds, owned_proxy from integration._support.responses_ws_peer import ( PROVIDER_MODEL, @@ -260,9 +259,9 @@ async def _until(read: Callable[[], float], satisfied: Callable[[float], bool]) return await asyncio.to_thread(eventually, read, satisfied, 15) -def _failure_rows(key: str) -> list[dict[str, JsonValue]]: +def _failure_rows(gateway: Gateway, key: str) -> list[dict[str, JsonValue]]: rows: Final = eventually( - lambda: read_rows(SPEND_ROWS_FOR_KEY, (_key_hash(key),)), + lambda: gateway.rows(SPEND_ROWS_FOR_KEY, (_key_hash(key),)), lambda found: any(row["status"] == "failure" for row in found), seconds=70, ) @@ -291,7 +290,7 @@ def test_a_turn_past_the_deployment_budget_is_refused_on_the_open_socket_and_log _assert_refused(second) _assert_refused(third) assert deployment.forwarded_turns() == 1 - failures: Final = _failure_rows(key) + failures: Final = _failure_rows(limited, key) assert len(failures) == 1, failures assert failures[0]["model_group"] == deployment.name, failures assert tag in list_value(failures[0]["request_tags"]), failures @@ -355,7 +354,7 @@ def test_a_turn_whose_admission_check_fails_gets_a_500_frame_and_the_socket_serv _assert_turn_check_failed(third, fault) completed(fourth) assert deployment.forwarded_turns() == 2 - failures: Final = _failure_rows(key) + failures: Final = _failure_rows(faulting, key) assert len(failures) == 1, failures assert failures[0]["model_group"] == deployment.name, failures recorded: Final = object_value(object_value(failures[0]["metadata"])["error_information"]) @@ -387,7 +386,7 @@ def test_a_turn_still_streaming_when_the_next_turns_check_fails_completes_and_is billed: Final = completed(streamed) assert deployment.forwarded_turns() == 1 rows: Final = eventually( - lambda: read_rows(SPEND_ROWS_FOR_KEY, (_key_hash(key),)), + lambda: faulting.rows(SPEND_ROWS_FOR_KEY, (_key_hash(key),)), lambda found: any(row["request_id"] == billed["id"] for row in found), seconds=70, ) diff --git a/tests/integration/routing/test_router_strategies_count_async_requests_once.py b/tests/integration/routing/test_router_strategies_count_async_requests_once.py new file mode 100644 index 00000000000..f7403ad0437 --- /dev/null +++ b/tests/integration/routing/test_router_strategies_count_async_requests_once.py @@ -0,0 +1,214 @@ +"""Router strategies that keep both a sync and an async hook count a finished async request once: least-busy +keeps counting a request still in flight while others finish around it, and usage-based routing v2 adds a +request's tokens to its deployment once. + +A legacy sync callback is configured, because that is what makes the sync handler run for an async call.""" + +import base64 +import json +import os +import threading +import uuid +from collections.abc import Callable, Iterator +from concurrent.futures import ThreadPoolExecutor +from contextlib import contextmanager +from dataclasses import dataclass +from pathlib import Path +from typing import Final + +import httpx +import pytest +import yaml +from integration._support.client import Gateway, eventually, gateway_from_environment, held +from integration._support.hook_counts import PNG_BYTES, WAV_BYTES, HookRecords +from integration._support.process import OwnedState, owned_proxy +from integration._support.wire import Reply, Request, wire_server +from redis import Redis + +pytestmark = pytest.mark.timeout(240) + +_MODEL: Final = "router-strategy-model" +_PROBES: Final = "integration._support.hook_count_probe" +_REJECTION: Final = b'{"error":{"message":"scripted provider rejection","type":"invalid_request_error"}}' +_IMAGE_TOKENS: Final = 12 +_IMAGE_REPLY: Final = json.dumps( + { + "created": 1700000000, + "data": [{"b64_json": base64.b64encode(PNG_BYTES).decode()}], + "usage": { + "input_tokens": 5, + "output_tokens": 7, + "total_tokens": _IMAGE_TOKENS, + "input_tokens_details": {"text_tokens": 5, "image_tokens": 0}, + }, + } +).encode() + + +@dataclass(frozen=True) +class _Rig: + proxy: Gateway + records: HookRecords + release: threading.Event + deployment_id: str + + +def _provider(release: threading.Event) -> Callable[[Request], Reply]: + def respond(request: Request) -> Reply: + if request.target == "/v1/images/generations": + return Reply(body=_IMAGE_REPLY) + spoken: Final = str(json.loads(request.body or b"{}").get("input", "")) + if spoken.startswith("fail"): + return Reply(status=400, body=_REJECTION) + if spoken.startswith("hold"): + return Reply(chunks=(WAV_BYTES,), content_type="audio/wav", gate_before_first=release) + return Reply(body=WAV_BYTES, content_type="audio/wav") + + return respond + + +def _write_config(path: Path, provider_url: str, strategy: str, model: str, deployment_id: str) -> Path: + path.write_text( + yaml.safe_dump( + { + "model_list": [ + { + "model_name": _MODEL, + "litellm_params": { + "model": model, + "api_base": provider_url + "/v1", + "api_key": "synthetic-provider-key", + }, + "model_info": {"id": deployment_id}, + } + ], + "litellm_settings": { + "success_callback": [f"{_PROBES}.sync_success_function"], + "failure_callback": [f"{_PROBES}.sync_failure_function"], + }, + "general_settings": { + "master_key": "os.environ/LITELLM_MASTER_KEY", + "database_url": "os.environ/DATABASE_URL", + "disable_model_info_refresh": True, + }, + "router_settings": { + "routing_strategy": strategy, + "routing_strategy_args": {"ttl": 600}, + "num_retries": 0, + "disable_cooldowns": True, + "redis_host": "os.environ/REDIS_HOST", + "redis_port": "os.environ/REDIS_PORT", + }, + } + ) + ) + return path + + +@contextmanager +def _router_proxy(tmp_path: Path, strategy: str, model: str) -> Iterator[_Rig]: + release: Final = threading.Event() + deployment_id: Final = f"{strategy}-{uuid.uuid4().hex}" + with ( + wire_server(_provider(release)) as upstream, + wire_server(lambda request: Reply()) as sink, + gateway_from_environment() as rig, + ): + config: Final = _write_config(tmp_path / f"{strategy}.yaml", upstream.url, strategy, model, deployment_id) + try: + with owned_proxy( + rig, + tmp_path, + {"HOOK_COUNT_PROBE_URL": sink.url, "STORE_MODEL_IN_DB": "False"}, + config=config, + workers=2, + state=OwnedState.SHARED_WITH_WORKER, + ) as proxy: + yield _Rig(proxy, HookRecords(sink, function_callbacks=True), release, deployment_id) + finally: + release.set() + + +@pytest.fixture(scope="module") +def least_busy(tmp_path_factory: pytest.TempPathFactory) -> Iterator[_Rig]: + with _router_proxy(tmp_path_factory.mktemp("least-busy"), "least-busy", "openai/gpt-4o-mini-tts") as rig: + yield rig + + +@pytest.fixture(scope="module") +def usage_based(tmp_path_factory: pytest.TempPathFactory) -> Iterator[_Rig]: + with _router_proxy(tmp_path_factory.mktemp("usage-based"), "usage-based-routing-v2", "openai/gpt-image-1") as rig: + yield rig + + +def _redis() -> Redis: + return Redis(host=os.environ["REDIS_HOST"], port=int(os.environ["REDIS_PORT"])) + + +def _in_flight(rig: _Rig) -> int: + with _redis() as cache: + stored: Final = cache.get(f"{_MODEL}_request_count:{rig.deployment_id}") + return 0 if stored is None else int(stored) + + +def _tokens_counted(rig: _Rig) -> int: + with _redis() as cache: + keys: Final = tuple(cache.scan_iter(match=f"{rig.deployment_id}:*:tpm:*")) + return sum(int(cache.get(key) or 0) for key in keys) + + +def _post(rig: _Rig, path: str, body: dict[str, object], call_id: str) -> httpx.Response: + return rig.proxy.client.post( + path, + json={"model": _MODEL, **body}, + headers={"Authorization": f"Bearer {rig.proxy.key}", "x-litellm-call-id": call_id}, + timeout=120, + ) + + +def _speak(rig: _Rig, text: str, call_id: str) -> httpx.Response: + return _post(rig, "/v1/audio/speech", {"input": text, "voice": "alloy", "response_format": "wav"}, call_id) + + +def _logged(rig: _Rig, call_id: str) -> None: + """The request's success or failure logging, the legacy sync callback included, has run.""" + eventually(lambda: rig.records.for_call(call_id), bool, seconds=20) + + +def _finish_a_speech_request(rig: _Rig, outcome: str) -> None: + call_id: Final = str(uuid.uuid4()) + finished: Final = _speak(rig, f"{'ok' if outcome == 'success' else 'fail'} {call_id}", call_id) + assert finished.status_code == (200 if outcome == "success" else 400), finished.text + _logged(rig, call_id) + held(lambda: _in_flight(rig), lambda count: count == 1, holding=3, seconds=20) + + +def _generate_an_image(rig: _Rig) -> None: + call_id: Final = str(uuid.uuid4()) + response: Final = _post(rig, "/v1/images/generations", {"prompt": f"tokens {call_id}", "n": 1}, call_id) + assert response.status_code == 200, response.text + _logged(rig, call_id) + + +@pytest.mark.parametrize("outcome", ["success", "failure"]) +def test_least_busy_keeps_counting_a_request_in_flight_while_async_speech_requests_finish( + least_busy: _Rig, outcome: str +) -> None: + held(lambda: _in_flight(least_busy), lambda count: count == 0, holding=1, seconds=30) + least_busy.release.clear() + with ThreadPoolExecutor(max_workers=1) as pool: + in_flight: Final = pool.submit(_speak, least_busy, f"hold {uuid.uuid4().hex}", str(uuid.uuid4())) + eventually(lambda: _in_flight(least_busy), lambda count: count == 1, seconds=30) + try: + for _ in range(3): + _finish_a_speech_request(least_busy, outcome) + finally: + least_busy.release.set() + assert in_flight.result(timeout=60).status_code == 200 + held(lambda: _in_flight(least_busy), lambda count: count == 0, holding=3, seconds=30) + + +def test_usage_based_routing_counts_an_async_image_request_s_tokens_once(usage_based: _Rig) -> None: + for _ in range(3): + _generate_an_image(usage_based) + held(lambda: _tokens_counted(usage_based), lambda tokens: tokens == 3 * _IMAGE_TOKENS, holding=3, seconds=30) diff --git a/tests/integration/sdk/test_local_sandbox_sdk.py b/tests/integration/sdk/test_local_sandbox_sdk.py new file mode 100644 index 00000000000..b30010ac3f8 --- /dev/null +++ b/tests/integration/sdk/test_local_sandbox_sdk.py @@ -0,0 +1,39 @@ +import os +import sys +from collections.abc import AsyncIterator +from pathlib import Path +from typing import Final + +import pytest +import pytest_asyncio + +from litellm import sandbox +from litellm.harness.sandbox import LocalSandbox + +WRITE_AT_PWD: Final = "import os;open(os.path.join(os.environ['PWD'],'hello.txt'),'w').write('hi')" + + +@pytest_asyncio.fixture(loop_scope="function") +async def box(tmp_path: Path) -> AsyncIterator[LocalSandbox]: + local: Final = sandbox.local(tmp_path) + yield local + await local.close() + + +@pytest.mark.asyncio(loop_scope="function") +async def test_child_trusting_pwd_writes_inside_its_cwd( + box: LocalSandbox, + monkeypatch: pytest.MonkeyPatch, + tmp_path_factory: pytest.TempPathFactory, +) -> None: + elsewhere: Final = tmp_path_factory.mktemp("elsewhere") + monkeypatch.setenv("PWD", str(elsewhere)) + os.mkdir(os.path.join(box.workdir, "sub")) + + top: Final = await box.run([sys.executable, "-I", "-c", WRITE_AT_PWD]) + nested: Final = await box.run([sys.executable, "-I", "-c", WRITE_AT_PWD], cwd="sub", env={"PWD": str(elsewhere)}) + + assert (top.exit_code, nested.exit_code) == (0, 0) + assert os.listdir(elsewhere) == [] + assert await box.read("hello.txt") == b"hi" + assert await box.read("sub/hello.txt") == b"hi" diff --git a/tests/integration/sdk/test_vertex_partner_count_tokens_sdk.py b/tests/integration/sdk/test_vertex_partner_count_tokens_sdk.py index e59d3f9264a..2e1205be688 100644 --- a/tests/integration/sdk/test_vertex_partner_count_tokens_sdk.py +++ b/tests/integration/sdk/test_vertex_partner_count_tokens_sdk.py @@ -1,5 +1,5 @@ import json -from collections.abc import Callable +from collections.abc import Callable, Mapping from typing import Final import litellm @@ -88,3 +88,77 @@ async def test_acount_tokens_falls_back_to_the_local_tokenizer_when_the_peer_rej assert len(_count_requests(wire.drain())) == 1 assert counted.tokenizer_type == "local_tokenizer", counted assert counted.total_tokens > 0 and counted.total_tokens != _PEER_COUNT, counted + + +_WEATHER_SCHEMA: Final[dict[str, JsonValue]] = { + "type": "object", + "properties": {"city": {"type": "string"}}, + "required": ["city"], +} +_CHAT_TOOLS: Final[list[dict[str, JsonValue]]] = [ + { + "type": "function", + "function": { + "name": "get_weather", + "description": "Look up the current weather for a city", + "parameters": _WEATHER_SCHEMA, + }, + } +] +_CHAT_TOOL_USE: Final[list[dict[str, JsonValue]]] = [ + {"role": "user", "content": "What is the weather in Paris?"}, + { + "role": "assistant", + "content": None, + "tool_calls": [ + {"id": "call_1", "type": "function", "function": {"name": "get_weather", "arguments": '{"city": "Paris"}'}} + ], + }, + {"role": "tool", "tool_call_id": "call_1", "content": "Sunny, 21C"}, +] +_GENERATED: Final[dict[str, JsonValue]] = { + "id": "msg_sdk_count", + "type": "message", + "role": "assistant", + "model": _BACKEND, + "content": [{"type": "text", "text": "It is sunny."}], + "stop_reason": "end_turn", + "stop_sequence": None, + "usage": {"input_tokens": 12, "output_tokens": 3}, +} +_COUNTED_FIELDS: Final = ("messages", "system", "tools") + + +def _generating_peer(request: Request) -> Reply: + if request.target == "/_oauth/token": + token: Final = {"access_token": "scripted-token", "token_type": "Bearer", "expires_in": 3600} + return Reply(body=json.dumps(token).encode()) + if "count-tokens" in request.target: + return Reply(body=json.dumps({"input_tokens": _PEER_COUNT}).encode()) + if request.target.endswith(f"/{_BACKEND}:rawPredict"): + return Reply(body=json.dumps(_GENERATED).encode()) + return Reply(status=404, body=json.dumps({"error": request.target}).encode()) + + +def _counted_fields(body: Mapping[str, JsonValue]) -> dict[str, JsonValue]: + return {field: body[field] for field in _COUNTED_FIELDS if field in body} + + +async def test_acount_tokens_sends_chat_tool_use_the_way_acompletion_sends_it( + vertex_environment: Callable[[str], None], +) -> None: + with wire_server(_generating_peer) as wire: + vertex_environment(wire.url) + generated: Final = await litellm.acompletion( + model=f"vertex_ai/{_BACKEND}", messages=_CHAT_TOOL_USE, tools=_CHAT_TOOLS, max_tokens=16, api_base=wire.url + ) + assert generated.choices[0].message.content == "It is sunny.", generated + counted: Final = await litellm.acount_tokens( + model=f"vertex_ai/{_BACKEND}", messages=_CHAT_TOOL_USE, tools=_CHAT_TOOLS, api_base=wire.url + ) + assert (counted.total_tokens, counted.tokenizer_type) == (_PEER_COUNT, "vertex_ai_partner_models"), counted + requests: Final = wire.drain() + (inference,) = (request for request in requests if request.target.endswith(f"/{_BACKEND}:rawPredict")) + (count,) = _count_requests(requests) + expected: Final = _counted_fields(_JSON_OBJECT.validate_json(inference.body)) + assert _counted_fields(_JSON_OBJECT.validate_json(count.body)) == expected, (count.body, expected) diff --git a/tests/integration/spend/test_background_response_billed_once.py b/tests/integration/spend/test_background_response_billed_once.py index 8a9818a7532..1b7fc975217 100644 --- a/tests/integration/spend/test_background_response_billed_once.py +++ b/tests/integration/spend/test_background_response_billed_once.py @@ -1,16 +1,23 @@ import asyncio +import base64 import json import uuid from collections.abc import Callable, Mapping from concurrent.futures import ThreadPoolExecutor +from itertools import chain from typing import Final +import httpx import openai import pytest from integration._support.client import Gateway, Scenario, eventually, held, list_value, object_value, string_value from integration._support.database import read_rows, write_rows +from integration._support.otlp_sink import decode_spans from integration._support.upstream import delete_scenario, register_scenario +from integration._support.wire import Request, wire_server from integration.caching.response_cache_case import entry_key, redis_store +from integration.security._callback_traffic import langfuse_sink +from integration.security._sinks import Recorder from integration.spend._background_responses import ( ATTRIBUTION_COLUMNS, CONCURRENT_READS, @@ -59,7 +66,7 @@ from integration.spend._background_responses import ( ) from openai._legacy_response import LegacyAPIResponse from openai.types.responses import Response -from pydantic import JsonValue +from pydantic import JsonValue, TypeAdapter from litellm.types.utils import BACKGROUND_RESPONSE_COST_POLL_CALL_ORIGIN @@ -611,6 +618,59 @@ def test_a_background_response_bills_the_end_user_who_created_it_once(gateway: G assert _charged_end_users(upstream.model_id) == [end_user] +def _project_spend(project_id: str) -> float: + rows: Final = read_rows('SELECT spend FROM "LiteLLM_ProjectTable" WHERE project_id = %s', (project_id,)) + return number(rows[0]["spend"]) + + +def _next_create(scenario: Scenario, key: str, model: str) -> httpx.Response: + response: Final = scenario.gateway.request( + "POST", "/v1/responses", {"model": model, "input": PROMPT, "background": True, "store": False}, key=key + ) + if response.status_code == 200: + scenario.cleanups.callback(forget_row, string_value(object_value(response.json())["id"])) + return response + + +def _key_budget(scenario: Scenario, budget_owner: str, model_budget: JsonValue) -> Mapping[str, JsonValue]: + if budget_owner == "key": + return {"model_max_budget": model_budget} + if budget_owner == "user": + return {"user_id": scenario.user(model_max_budget=model_budget)} + if budget_owner == "budget_tier": + return {"budget_id": scenario.budget(model_max_budget=model_budget)} + return {} + + +@pytest.mark.timeout(240) +@pytest.mark.parametrize("budget_owner", ["key", "team", "user", "budget_tier"]) +def test_a_billed_background_response_counts_toward_its_creators_project_and_model_budget( + gateway: Gateway, budget_owner: str +) -> None: + with gateway.scenario() as scenario: + upstream: Final = scripted_upstream(scenario, background_routes("completed")) + model_budget: Final[JsonValue] = {upstream.model: {"max_budget": PRICE / 2, "budget_duration": "1d"}} + team_id: Final = scenario.team(**({"model_max_budget": model_budget} if budget_owner == "team" else {})) + project_id: Final = scenario.project(team_id) + key: Final = scenario.key( + team_id=team_id, project_id=project_id, **_key_budget(scenario, budget_owner, model_budget) + ) + response_id: Final = create_background_response(scenario, key, upstream.model) + read: Final = read_response(gateway, key, response_id) + assert (read,) in (settling_reads("completed", 1), free_reads("completed", 1)) + eventually( + lambda: (key_spend(key), _project_spend(project_id)), + lambda spends: spends[0] > 0 and costs(spends[0])(spends[1]), + seconds=SPEND_LANDING_SECONDS, + ) + refused: Final = eventually( + lambda: _next_create(scenario, key, upstream.model), + lambda response: response.status_code != 200, + seconds=SPEND_LANDING_SECONDS, + ) + assert f"exceeded budget for model={upstream.model}" in refused.text, refused.text + + @pytest.mark.timeout(240) def test_the_read_that_settles_a_background_response_splits_its_charge_into_input_and_output( gateway: Gateway, @@ -769,3 +829,78 @@ def test_a_client_cannot_make_a_background_create_free_by_forging_the_managed_ma scenario.cleanups.callback(forget_row, response_id) assert tuple(read_response(gateway, key, response_id) for _ in range(2)) == free_reads("completed", 2) assert_charged_exactly(lambda: key_spend(key), PRICE) + + +LANGFUSE_PUBLIC_KEY: Final = "pk-lf-background" +LANGFUSE_SECRET_KEY: Final = "sk-lf-background" +LANGFUSE_TRACES_PATH: Final = "/api/public/otel/v1/traces" +LANGFUSE_COST: Final = "langfuse.observation.cost_details" +_LANGFUSE_COST_DETAILS: Final = TypeAdapter(dict[str, float]) + + +def _langfuse_callback(host: str) -> dict[str, JsonValue]: + return { + "callback_name": "langfuse", + "callback_type": "success", + "callback_vars": { + "langfuse_public_key": LANGFUSE_PUBLIC_KEY, + "langfuse_secret_key": LANGFUSE_SECRET_KEY, + "langfuse_host": host, + }, + } + + +def _key_with_its_own_logging(scenario: Scenario, langfuse_url: str) -> str: + return scenario.key(metadata={"logging": [_langfuse_callback(langfuse_url)]}) + + +def _key_in_a_team_with_logging(scenario: Scenario, langfuse_url: str) -> str: + team_id: Final = scenario.team() + added: Final = scenario.gateway.request("POST", f"/team/{team_id}/callback", _langfuse_callback(langfuse_url)) + assert added.status_code == 200, added.text + return scenario.key(team_id=team_id) + + +LOGGING_ON: Final[Mapping[str, Callable[[Scenario, str], str]]] = { + "the_key": _key_with_its_own_logging, + "the_team": _key_in_a_team_with_logging, +} + + +def _trace_exports(langfuse: Recorder) -> tuple[Request, ...]: + return tuple(request for request in langfuse.requests() if request.target.startswith(LANGFUSE_TRACES_PATH)) + + +def _exported_costs(langfuse: Recorder) -> tuple[float, ...]: + spans: Final = tuple( + chain.from_iterable( + decode_spans(export.body, export.headers.get("content-type", "")) for export in _trace_exports(langfuse) + ) + ) + return tuple( + _LANGFUSE_COST_DETAILS.validate_json(string_value(span["attributes"][LANGFUSE_COST]))["total"] + for span in spans + if LANGFUSE_COST in span["attributes"] + ) + + +@pytest.mark.timeout(240) +@pytest.mark.parametrize("logging_on", LOGGING_ON.keys()) +def test_the_billed_cost_reaches_the_langfuse_project_set_on_the_creating_key_or_team( + gateway: Gateway, logging_on: str +) -> None: + with wire_server(langfuse_sink) as wire, gateway.scenario() as scenario: + langfuse: Final = Recorder(wire) + key: Final = LOGGING_ON[logging_on](scenario, wire.url) + upstream: Final = scripted_upstream(scenario, background_routes("completed")) + response_id: Final = create_background_response(scenario, key, upstream.model) + reads: Final = tuple(read_response(gateway, key, response_id) for _ in range(READS)) + assert reads in (settling_reads("completed", READS), free_reads("completed", READS)) + exported: Final = eventually( + lambda: _exported_costs(langfuse), + lambda costs: pytest.approx(PRICE) in costs, + seconds=SPEND_LANDING_SECONDS, + ) + assert [cost for cost in exported if cost > 0] == [pytest.approx(PRICE)] + credentials: Final = base64.b64encode(f"{LANGFUSE_PUBLIC_KEY}:{LANGFUSE_SECRET_KEY}".encode()).decode() + assert {export.headers.get("authorization") for export in _trace_exports(langfuse)} == {f"Basic {credentials}"} diff --git a/tests/integration/spend/test_baggage_tag_mappings.py b/tests/integration/spend/test_baggage_tag_mappings.py new file mode 100644 index 00000000000..1bf90269484 --- /dev/null +++ b/tests/integration/spend/test_baggage_tag_mappings.py @@ -0,0 +1,847 @@ +import itertools +import json +import uuid +from collections.abc import Generator, Iterator, Mapping, Sequence +from contextlib import ExitStack, contextmanager +from dataclasses import dataclass +from hashlib import sha256 +from pathlib import Path +from types import MappingProxyType +from typing import Final, Literal + +import httpx +import pytest +import yaml +from integration._support.client import ( + JSON_OBJECT, + Gateway, + eventually, + gateway_from_environment, + list_value, + object_value, +) +from integration._support.database import scratch_database +from integration._support.database_relay import dropped_connection_relay, plaintext_database_url +from integration._support.process import graceful_stop_seconds, owned_proxy +from integration._support.wire import Reply, Request, Wire, wire_server +from pydantic import JsonValue, TypeAdapter +from websockets.exceptions import InvalidStatus +from websockets.sync.client import connect + +pytestmark: Final = pytest.mark.timeout(2 * graceful_stop_seconds() + 120) + +PROXY_CONFIG: Final = Path(__file__).resolve().parents[1] / "proxy_config.yaml" +PRICED: Final[dict[str, JsonValue]] = {"input_cost_per_token": 0.01, "output_cost_per_token": 0.01} +WORKER_PROBES: Final = 6 +JSON_LIST: Final = TypeAdapter(list[JsonValue]) +GUARDRAIL_VERDICT: Final = b'{"action":"GUARDRAIL_INTERVENED","texts":["masked baggage prompt"]}' +GUARDRAIL_PATH: Final = "/beta/litellm_basic_guardrail_api" +NO_FIELDS: Final[Mapping[str, JsonValue]] = MappingProxyType({}) + +Route = Literal["chat", "chat_litellm_metadata", "messages", "responses"] +CallerTag = Literal["none", "header", "metadata_json_with_header", "litellm_metadata"] +RejectedClientTag = Literal["none", "header", "body", "metadata_json", "litellm_metadata"] + + +@dataclass(frozen=True, slots=True) +class Rig: + proxy: Gateway + provider: Wire + callbacks: Wire + marker: str + + @property + def chat_model(self) -> str: + return f"chat-{self.marker}" + + @property + def exact_tag(self) -> str: + return f"usecase-a-{self.marker}" + + def usecase_tag(self, value: str) -> str: + return f"usecase-{self.marker}:{value}" + + def tenant_tag(self, value: str) -> str: + return f"tenant-{self.marker}:{value}" + + def budgeted_tag(self, value: str) -> str: + return f"budgeted-{self.marker}:{value}" + + def team_tag(self, value: str) -> str: + return f"team-{self.marker}:{value}" + + @property + def guarded_tag(self) -> str: + return f"guarded-{self.marker}:on" + + @property + def policy_tag(self) -> str: + return f"policy-{self.marker}:sensitive" + + +def _chat_reply() -> Reply: + marker: Final = uuid.uuid4().hex + return Reply( + body=json.dumps( + { + "id": f"chatcmpl-{marker}", + "object": "chat.completion", + "created": 1, + "model": "gpt-4o-mini", + "choices": [{"index": 0, "message": {"role": "assistant", "content": marker}, "finish_reason": "stop"}], + "usage": {"prompt_tokens": 5, "completion_tokens": 3, "total_tokens": 8}, + } + ).encode() + ) + + +def _responses_reply() -> Reply: + marker: Final = uuid.uuid4().hex + return Reply( + body=json.dumps( + { + "id": f"resp_{marker}", + "object": "response", + "created_at": 1, + "status": "completed", + "model": "gpt-4o-mini", + "output": [ + { + "id": f"msg_{marker}", + "type": "message", + "role": "assistant", + "status": "completed", + "content": [{"type": "output_text", "text": marker, "annotations": []}], + } + ], + "usage": {"input_tokens": 5, "output_tokens": 3, "total_tokens": 8}, + } + ).encode() + ) + + +def _provider(request: Request) -> Reply: + if request.target == GUARDRAIL_PATH: + return Reply(body=b'{"action":"NONE"}') + if request.target == "/v1/responses": + return _responses_reply() + return _chat_reply() + + +def _deployment(model_name: str, provider: Wire, **parameters: JsonValue) -> dict[str, JsonValue]: + return { + "model_name": model_name, + "litellm_params": { + "model": "openai/gpt-4o-mini", + "api_base": f"{provider.url}/v1", + "api_key": "synthetic-baggage-key", + **PRICED, + **parameters, + }, + } + + +def _write_config( + directory: Path, + model_list: list[JsonValue], + general_settings: Mapping[str, JsonValue], + litellm_settings: Mapping[str, JsonValue], + guardrails: Sequence[JsonValue] = (), +) -> Path: + base: Final = JSON_OBJECT.validate_python(yaml.safe_load(PROXY_CONFIG.read_text())) + config: Final = { + **base, + "model_list": model_list, + "general_settings": {**object_value(base["general_settings"]), **general_settings}, + "litellm_settings": {**object_value(base["litellm_settings"]), **litellm_settings}, + **({"guardrails": list(guardrails)} if guardrails else {}), + } + path: Final = directory / "baggage-tag-mappings.yaml" + path.write_text(yaml.safe_dump(config)) + return path + + +def _routed_deployment(marker: str, provider: Wire, name: str, tag: str) -> dict[str, JsonValue]: + return { + **_deployment(f"routed-{marker}", provider, tags=[tag]), + "model_info": {"id": f"{name}-{marker}", "enable_tag_filtering": True}, + } + + +def _mapped_models(marker: str, provider: Wire, upstream_url: str) -> list[JsonValue]: + routed: Final = ( + _routed_deployment(marker, provider, "tagged", f"usecase-a-{marker}"), + _routed_deployment(marker, provider, "default", "default"), + ) + realtime: Final[dict[str, JsonValue]] = { + "model_name": f"realtime-{marker}", + "litellm_params": { + "model": "openai/gpt-realtime-2.1", + "api_base": f"{upstream_url}/v1", + "api_key": f"realtime-{marker}", + }, + } + guarded: Final = _deployment(f"guarded-{marker}", provider, tags=[f"guarded-{marker}:on"]) + pre_guarded: Final = _deployment(f"guarded-pre-{marker}", provider, tags=[f"guarded-{marker}:pre"]) + return [_deployment(f"chat-{marker}", provider), guarded, pre_guarded, *routed, realtime] + + +def _mapped_rules(marker: str, *, tenant_required: bool) -> list[JsonValue]: + return [ + {"key": "entrypoint", "value": "a", "tag": f"usecase-a-{marker}"}, + {"key": "entrypoint", "tag_prefix": f"usecase-{marker}:"}, + {"key": "tenant", "tag_prefix": f"tenant-{marker}:", "required": tenant_required}, + {"key": "budgeted", "tag_prefix": f"budgeted-{marker}:", "require_budgeted_tag": True}, + {"key": "team+id", "tag_prefix": f"team-{marker}:"}, + {"key": "guard", "tag_prefix": f"guarded-{marker}:"}, + ] + + +def _deployment_tag_mode_guardrail(marker: str, provider: Wire) -> dict[str, JsonValue]: + return { + "guardrail_name": f"deployment-tag-mode-{marker}", + "litellm_params": { + "guardrail": "generic_guardrail_api", + "mode": { + "tags": { + f"guarded-{marker}:on": "post_call", + f"guarded-{marker}:pre": "pre_call", + f"policy-{marker}:sensitive": "post_call", + } + }, + "default_on": True, + "api_base": f"{provider.url}{GUARDRAIL_PATH}", + "api_key": "synthetic-guardrail-key", + }, + } + + +@contextmanager +def _rig( + tmp_path_factory: pytest.TempPathFactory, + general_settings: Mapping[str, JsonValue], + *, + tenant_required: bool, + workers: int, + tag_mode_guardrail: bool = False, +) -> Generator[Rig]: + marker: Final = uuid.uuid4().hex[:12] + directory: Final = tmp_path_factory.mktemp("baggage-tag-mappings") + with ( + gateway_from_environment() as base, + wire_server(_provider) as provider, + wire_server(lambda _request: Reply()) as callbacks, + ): + config: Final = _write_config( + directory, + _mapped_models(marker, provider, base.upstream_url), + {"request_tag_mappings": _mapped_rules(marker, tenant_required=tenant_required), **general_settings}, + {"callbacks": ["generic_api"], "DEFAULT_FLUSH_INTERVAL_SECONDS": 1}, + [_deployment_tag_mode_guardrail(marker, provider)] if tag_mode_guardrail else (), + ) + with owned_proxy( + base, directory, {"GENERIC_LOGGER_ENDPOINT": callbacks.url}, config=config, workers=workers + ) as proxy: + yield Rig(proxy, provider, callbacks, marker) + + +@pytest.fixture(scope="module") +def mapped(tmp_path_factory: pytest.TempPathFactory) -> Iterator[Rig]: + with _rig(tmp_path_factory, {}, tenant_required=True, workers=2) as rig: + yield rig + + +@pytest.fixture(scope="module") +def optional(tmp_path_factory: pytest.TempPathFactory) -> Iterator[Rig]: + with _rig(tmp_path_factory, {}, tenant_required=False, workers=1, tag_mode_guardrail=True) as rig: + yield rig + + +@pytest.fixture(scope="module") +def rejecting(tmp_path_factory: pytest.TempPathFactory) -> Iterator[Rig]: + with _rig(tmp_path_factory, {"reject_clientside_metadata_tags": True}, tenant_required=False, workers=1) as rig: + yield rig + + +def _digest(key: str) -> str: + return sha256(key.encode()).hexdigest() + + +def _caller_tags(raw: JsonValue) -> frozenset[str]: + tags: Final = JSON_LIST.validate_json(raw) if isinstance(raw, str) else list_value(raw) + return frozenset(tag for tag in tags if isinstance(tag, str) and not tag.startswith("User-Agent: ")) + + +def _spend_tags(proxy: Gateway, key: str) -> frozenset[str]: + rows: Final = eventually( + lambda: proxy.rows('SELECT request_tags FROM "LiteLLM_SpendLogs" WHERE api_key=%s', (_digest(key),)), + lambda values: len(values) == 1, + seconds=70, + ) + return _caller_tags(rows[0]["request_tags"]) + + +def _batch_events(batch: Request) -> Iterator[dict[str, JsonValue]]: + return (object_value(item) for item in JSON_LIST.validate_json(batch.body)) + + +def _logged_event(callbacks: Wire, call_id: str) -> dict[str, JsonValue]: + def delivered() -> tuple[dict[str, JsonValue], ...]: + events: Final = itertools.chain.from_iterable(_batch_events(batch) for batch in callbacks.drain()) + return tuple(event for event in events if event.get("litellm_call_id") == call_id) + + events: Final = eventually(delivered, lambda values: len(values) == 1, seconds=30) + return events[0] + + +def _inference_body(route: Route, model: str, text: str, caller_tag: str) -> dict[str, JsonValue]: + match route: + case "chat": + return {"model": model, "messages": [{"role": "user", "content": text}], "metadata": {"tags": [caller_tag]}} + case "chat_litellm_metadata": + return { + "model": model, + "messages": [{"role": "user", "content": text}], + "litellm_metadata": {"tags": [caller_tag]}, + } + case "messages": + return { + "model": model, + "max_tokens": 16, + "messages": [{"role": "user", "content": text}], + "litellm_metadata": {"tags": [caller_tag]}, + } + case "responses": + return {"model": model, "input": text, "litellm_metadata": {"tags": [caller_tag]}} + + +ROUTE_PATHS: Final[Mapping[Route, str]] = { + "chat": "/v1/chat/completions", + "chat_litellm_metadata": "/v1/chat/completions", + "messages": "/v1/messages", + "responses": "/v1/responses", +} + + +def _guardrail_inputs(rig: Rig) -> tuple[JsonValue, ...]: + return tuple( + JSON_OBJECT.validate_json(request.body)["input_type"] + for request in rig.provider.drain() + if request.target == GUARDRAIL_PATH + ) + + +def _chat( + rig: Rig, + key: str, + baggage: str | None, + *, + model: str | None = None, + fields: Mapping[str, JsonValue] = NO_FIELDS, + **headers: str, +) -> httpx.Response: + return rig.proxy.request( + "POST", + "/v1/chat/completions", + { + "model": model or rig.chat_model, + "messages": [{"role": "user", "content": f"baggage {uuid.uuid4().hex}"}], + "max_tokens": 16, + **fields, + }, + key=key, + headers={**({"baggage": baggage} if baggage is not None else {}), **headers}, + ) + + +@pytest.mark.parametrize("route", ["chat", "chat_litellm_metadata", "messages", "responses"]) +def test_mapped_baggage_tags_reach_spend_and_callbacks_but_not_requester_metadata(mapped: Rig, route: Route) -> None: + tenant: Final = uuid.uuid4().hex + caller_tag: Final = f"caller-{tenant}" + mapped_tags: Final = frozenset({mapped.exact_tag, mapped.tenant_tag(tenant)}) + with mapped.proxy.scenario() as scenario: + key: Final = scenario.key() + mapped.provider.drain() + response: Final = mapped.proxy.request( + "POST", + ROUTE_PATHS[route], + _inference_body(route, mapped.chat_model, f"baggage {tenant}", caller_tag), + key=key, + headers={"baggage": f"entrypoint=a, tenant={tenant}"}, + ) + assert response.status_code == 200, response.text + assert len(mapped.provider.drain()) == 1 + assert _spend_tags(mapped.proxy, key) == mapped_tags | {caller_tag} + event: Final = _logged_event(mapped.callbacks, response.headers["x-litellm-call-id"]) + assert mapped_tags <= _caller_tags(event["request_tags"]), event["request_tags"] + requester: Final = object_value(object_value(event["metadata"]).get("requester_metadata") or {}) + assert not mapped_tags & _caller_tags(requester.get("tags") or []), requester + + +def test_json_string_metadata_gains_exactly_the_mapped_tags(optional: Rig) -> None: + tenant: Final = uuid.uuid4().hex + mapped_tags: Final = frozenset({optional.exact_tag, optional.tenant_tag(tenant)}) + fields: Final[Mapping[str, JsonValue]] = {"metadata": json.dumps({"tags": [f"caller-{tenant}"]})} + with optional.proxy.scenario() as scenario: + plain_key: Final = scenario.key() + key: Final = scenario.key() + optional.provider.drain() + plain: Final = _chat(optional, plain_key, None, fields=fields) + response: Final = _chat(optional, key, f"entrypoint=a,tenant={tenant}", fields=fields) + assert (plain.status_code, response.status_code) == (200, 200), (plain.text, response.text) + assert len(optional.provider.drain()) == 2 + assert _spend_tags(optional.proxy, key) == _spend_tags(optional.proxy, plain_key) | mapped_tags + event: Final = _logged_event(optional.callbacks, response.headers["x-litellm-call-id"]) + assert mapped_tags <= _caller_tags(event["request_tags"]), event["request_tags"] + requester: Final = object_value(object_value(event["metadata"]).get("requester_metadata") or {}) + assert not mapped_tags & _caller_tags(requester.get("tags") or []), requester + + +def test_a2a_spend_row_carries_the_mapped_tags(mapped: Rig) -> None: + marker: Final = "baggagea2a" + uuid.uuid4().hex[:12] + + def card(url: str) -> dict[str, JsonValue]: + return { + "protocolVersion": "0.3", + "name": marker, + "description": "Synthetic peer", + "version": "1.0.0", + "url": url + "/", + "capabilities": {"streaming": True}, + "defaultInputModes": ["text"], + "defaultOutputModes": ["text"], + "skills": [], + } + + def peer(request: Request) -> Reply: + if request.method == "GET": + return Reply(body=json.dumps(card(wire.url)).encode()) + rpc: Final = JSON_OBJECT.validate_json(request.body) + return Reply( + body=json.dumps( + { + "jsonrpc": "2.0", + "id": rpc["id"], + "result": { + "kind": "message", + "role": "agent", + "messageId": f"{marker}-out", + "parts": [{"kind": "text", "text": "done"}], + }, + } + ).encode() + ) + + tenant: Final = uuid.uuid4().hex + with wire_server(peer) as wire, mapped.proxy.scenario() as scenario: + created: Final = mapped.proxy.post( + "/v1/agents", + {"agent_name": marker, "agent_card_params": card(wire.url), "litellm_params": {"cost_per_query": 0.25}}, + ) + agent: Final = str(created["agent_id"]) + scenario.cleanups.callback(lambda: mapped.proxy.request("DELETE", f"/v1/agents/{agent}")) + key: Final = scenario.key() + sent: Final = mapped.proxy.request( + "POST", + f"/a2a/{agent}", + { + "jsonrpc": "2.0", + "id": f"{marker}-send", + "method": "message/send", + "params": { + "message": { + "kind": "message", + "role": "user", + "messageId": f"{marker}-in", + "parts": [{"kind": "text", "text": "ping"}], + } + }, + }, + key=key, + headers={"baggage": f"entrypoint=a,tenant={tenant}"}, + ) + assert sent.status_code == 200, sent.text + assert {mapped.exact_tag, mapped.tenant_tag(tenant)} <= _spend_tags(mapped.proxy, key) + + +@pytest.mark.parametrize( + ("key_fields", "fields", "headers"), + [ + ({}, NO_FIELDS, {}), + ({}, {"metadata": {"tags": "run-123"}}, {"x-litellm-tags": "caller-tag"}), + ({"metadata": {"tags": ["key-tag"]}}, {"metadata": {"tags": "run-123"}}, {}), + ({}, {"metadata": {"tags": ""}}, {}), + ], + ids=["plain", "string_tags_with_header_tag", "string_tags_with_key_tag", "empty_string_tags"], +) +def test_spent_mapped_tag_budget_rejects_the_next_request_before_the_provider( + mapped: Rig, key_fields: Mapping[str, JsonValue], fields: Mapping[str, JsonValue], headers: Mapping[str, str] +) -> None: + entry: Final = uuid.uuid4().hex + tag: Final = mapped.usecase_tag(entry) + baggage: Final = f"entrypoint={entry},tenant={entry}" + with mapped.proxy.scenario() as scenario: + key: Final = scenario.key(**key_fields) + mapped.proxy.post("/tag/new", {"name": tag, "max_budget": 0.0001}) + scenario.cleanups.callback(lambda: mapped.proxy.request("POST", "/tag/delete", {"name": tag})) + first: Final = _chat(mapped, key, baggage) + assert first.status_code == 200, first.text + eventually(lambda: _chat(mapped, key, baggage).status_code, lambda status: status != 200, seconds=70) + mapped.provider.drain() + blocked: Final = _chat(mapped, key, baggage, fields=fields, **headers) + assert blocked.status_code == 422, blocked.text + assert "budget" in blocked.text.lower(), blocked.text + assert mapped.provider.drain() == () + other: Final = _chat(mapped, key, f"entrypoint=other-{entry},tenant={entry}") + assert other.status_code == 200, other.text + + +def test_required_mapping_rejects_a_request_without_its_baggage_value_before_the_provider(mapped: Rig) -> None: + with mapped.proxy.scenario() as scenario: + key: Final = scenario.key() + mapped.provider.drain() + rejected: Final = _chat(mapped, key, "entrypoint=a") + assert rejected.status_code == 400, rejected.text + assert mapped.provider.drain() == () + admitted: Final = _chat(mapped, key, f"entrypoint=a,tenant={uuid.uuid4().hex}") + assert admitted.status_code == 200, admitted.text + + +def test_require_budgeted_tag_rejects_an_unbudgeted_mapped_tag_until_the_tag_has_a_budget(mapped: Rig) -> None: + value: Final = uuid.uuid4().hex + tag: Final = mapped.budgeted_tag(value) + baggage: Final = f"budgeted={value},tenant={value}" + with mapped.proxy.scenario() as scenario: + key: Final = scenario.key() + mapped.provider.drain() + unbudgeted: Final = tuple(_chat(mapped, key, baggage, Connection="close") for _ in range(WORKER_PROBES)) + assert [response.status_code for response in unbudgeted] == [400] * WORKER_PROBES, [ + response.text for response in unbudgeted + ] + assert mapped.provider.drain() == () + mapped.proxy.post("/tag/new", {"name": tag, "max_budget": 100}) + scenario.cleanups.callback(lambda: mapped.proxy.request("POST", "/tag/delete", {"name": tag})) + budgeted: Final = tuple(_chat(mapped, key, baggage, Connection="close") for _ in range(WORKER_PROBES)) + assert [response.status_code for response in budgeted] == [200] * WORKER_PROBES, [ + response.text for response in budgeted + ] + + +def _routing_caller_tag(rig: Rig, caller_tag: CallerTag) -> tuple[Mapping[str, JsonValue], Mapping[str, str]]: + json_metadata: Final[Mapping[str, JsonValue]] = {"metadata": json.dumps({"tags": [rig.exact_tag]})} + match caller_tag: + case "none": + return NO_FIELDS, {} + case "header": + return NO_FIELDS, {"x-litellm-tags": rig.exact_tag} + case "metadata_json_with_header": + return json_metadata, {"x-litellm-tags": f"other-{rig.marker}"} + case "litellm_metadata": + return {"litellm_metadata": {"tags": [rig.exact_tag]}}, {} + + +@pytest.mark.parametrize( + "caller_tag", + ["none", "header", "metadata_json_with_header", "litellm_metadata"], + ids=["baggage_only", "caller_tag", "metadata_json_tag_with_header", "litellm_metadata_tag"], +) +def test_mapped_tags_never_select_a_tag_routed_deployment(mapped: Rig, caller_tag: CallerTag) -> None: + tenant: Final = uuid.uuid4().hex + expected: Final = f"default-{mapped.marker}" if caller_tag == "none" else f"tagged-{mapped.marker}" + fields, headers = _routing_caller_tag(mapped, caller_tag) + with mapped.proxy.scenario() as scenario: + key: Final = scenario.key() + responses: Final = tuple( + _chat( + mapped, + key, + f"entrypoint=a,tenant={tenant}", + model=f"routed-{mapped.marker}", + fields=fields, + **headers, + ) + for _ in range(3) + ) + assert [response.status_code for response in responses] == [200] * 3, [r.text for r in responses] + assert [response.headers.get("x-litellm-model-id") for response in responses] == [expected] * 3 + + +def test_mapped_tags_never_trigger_a_tag_scoped_policy_attachment(mapped: Rig) -> None: + entry: Final = uuid.uuid4().hex + tag: Final = mapped.usecase_tag(entry) + baggage: Final = f"entrypoint={entry},tenant={entry}" + proxy: Final = mapped.proxy + with wire_server(lambda _request: Reply(body=GUARDRAIL_VERDICT)) as guardrail, proxy.scenario() as scenario: + key: Final = scenario.key() + guardrail_created: Final = proxy.post( + "/guardrails", + { + "guardrail": { + "guardrail_name": f"guardrail-{entry}", + "litellm_params": { + "guardrail": "generic_guardrail_api", + "mode": "pre_call", + "default_on": False, + "api_base": f"{guardrail.url}/beta/litellm_basic_guardrail_api", + "api_key": "synthetic-guardrail-key", + }, + } + }, + ) + scenario.cleanups.callback(lambda: proxy.request("DELETE", f"/guardrails/{guardrail_created['guardrail_id']}")) + policy: Final = proxy.post( + "/policies", {"policy_name": f"policy-{entry}", "guardrails_add": [f"guardrail-{entry}"]} + ) + scenario.cleanups.callback(lambda: proxy.request("DELETE", f"/policies/{policy['policy_id']}")) + attachment: Final = proxy.post("/policies/attachments", {"policy_name": f"policy-{entry}", "tags": [tag]}) + scenario.cleanups.callback( + lambda: proxy.request("DELETE", f"/policies/attachments/{attachment['attachment_id']}") + ) + caller_tagged: Final = _chat(mapped, key, baggage, **{"x-litellm-tags": tag}) + assert caller_tagged.status_code == 200, caller_tagged.text + assert caller_tagged.headers.get("x-litellm-applied-policies") == f"policy-{entry}", caller_tagged.text + assert len(guardrail.drain()) == 1 + baggage_only: Final = _chat(mapped, key, baggage) + assert baggage_only.status_code == 200, baggage_only.text + assert baggage_only.headers.get("x-litellm-applied-policies") is None, baggage_only.text + assert guardrail.drain() == () + + +def _handshake_status(url: str, headers: Mapping[str, str]) -> int: + try: + with connect(url, additional_headers=headers, open_timeout=30): + return 101 + except InvalidStatus as refusal: + return refusal.response.status_code + + +def test_required_mapping_refuses_websocket_inference_before_the_upstream(mapped: Rig) -> None: + proxy_url: Final = str(mapped.proxy.client.base_url).rstrip("/") + upstream_api_key: Final = f"Bearer realtime-{mapped.marker}" + with ( + mapped.proxy.scenario() as scenario, + httpx.Client(base_url=mapped.proxy.upstream_url, timeout=5, trust_env=False) as upstream, + ): + key: Final = scenario.key() + upstream.get("/__observations").raise_for_status() + status: Final = _handshake_status( + f"ws{proxy_url.removeprefix('http')}/v1/realtime?model=realtime-{mapped.marker}", + {"Authorization": f"Bearer {key}", "baggage": f"entrypoint=a,tenant={uuid.uuid4().hex}"}, + ) + assert status == 403, status + observed: Final = list_value(JSON_OBJECT.validate_json(upstream.get("/__observations").content)["requests"]) + upgrades: Final = tuple( + request + for request in (object_value(item) for item in observed) + if request["method"] == "WEBSOCKET" and request["authorization"] == upstream_api_key + ) + assert upgrades == (), upgrades + + +@pytest.mark.parametrize( + ("route", "body"), + [ + ("/utils/token_counter", {"messages": [{"role": "user", "content": "count me"}]}), + ("/v1/messages/count_tokens", {"messages": [{"role": "user", "content": "count me"}]}), + ], + ids=["token_counter", "messages_count_tokens"], +) +def test_required_mapping_skips_unbilled_routes(mapped: Rig, route: str, body: dict[str, JsonValue]) -> None: + with mapped.proxy.scenario() as scenario: + key: Final = scenario.key() + response: Final = mapped.proxy.request("POST", route, {"model": mapped.chat_model, **body}, key=key) + assert response.status_code == 200, response.text + + +def test_custom_passthrough_spend_row_carries_the_mapped_tags(mapped: Rig) -> None: + tenant: Final = uuid.uuid4().hex + path: Final = f"/baggage-passthrough-{tenant}" + with mapped.proxy.scenario() as scenario: + created: Final = mapped.proxy.post( + "/config/pass_through_endpoint", {"path": path, "target": f"{mapped.provider.url}/echo", "auth": True} + ) + endpoint_id: Final = str(object_value(list_value(created["endpoints"])[0])["id"]) + scenario.cleanups.callback( + lambda: mapped.proxy.request("DELETE", "/config/pass_through_endpoint", params={"endpoint_id": endpoint_id}) + ) + key: Final = scenario.key(allowed_passthrough_routes=[path]) + response: Final = mapped.proxy.request( + "POST", + path, + {"model": mapped.chat_model, "messages": [{"role": "user", "content": tenant}]}, + key=key, + headers={"baggage": f"entrypoint=a,tenant={tenant}"}, + ) + assert response.status_code == 200, response.text + assert {mapped.exact_tag, mapped.tenant_tag(tenant)} <= _spend_tags(mapped.proxy, key) + + +def _rejected_client_tag(client_tag: RejectedClientTag, tag: str) -> tuple[Mapping[str, JsonValue], Mapping[str, str]]: + match client_tag: + case "none": + return NO_FIELDS, {} + case "header": + return NO_FIELDS, {"x-litellm-tags": tag} + case "body": + return {"metadata": {"tags": [tag]}}, {} + case "metadata_json": + return {"metadata": json.dumps({"tags": [tag]})}, {} + case "litellm_metadata": + return {"litellm_metadata": {"tags": [tag]}}, {} + + +@pytest.mark.parametrize( + ("client_tag", "baggage_maps", "plain_statuses"), + [ + ("none", True, (200,)), + ("header", True, (400,)), + ("body", True, (400,)), + ("metadata_json", True, (200, 400)), + ("metadata_json", False, (200, 400)), + ("litellm_metadata", True, (200,)), + ], + ids=[ + "baggage_only", + "header_tag", + "body_tag", + "metadata_json_tag", + "metadata_json_tag_unmapped_baggage", + "litellm_metadata_tag", + ], +) +def test_reject_clientside_metadata_tags_with_baggage( + rejecting: Rig, client_tag: RejectedClientTag, baggage_maps: bool, plain_statuses: tuple[int, ...] +) -> None: + tenant: Final = uuid.uuid4().hex + fields, headers = _rejected_client_tag(client_tag, f"caller-{tenant}") + baggage: Final = f"entrypoint=a,tenant={tenant}" if baggage_maps else f"region={tenant}" + mapped_tags: Final = frozenset({rejecting.exact_tag, rejecting.tenant_tag(tenant)} if baggage_maps else ()) + with rejecting.proxy.scenario() as scenario: + plain_key: Final = scenario.key() + key: Final = scenario.key() + plain: Final = _chat(rejecting, plain_key, None, fields=fields, **headers) + response: Final = _chat(rejecting, key, baggage, fields=fields, **headers) + assert plain.status_code in plain_statuses, plain.text + assert response.status_code == plain.status_code, (plain.text, response.text) + if response.status_code != 200: + return + assert _spend_tags(rejecting.proxy, key) == _spend_tags(rejecting.proxy, plain_key) | mapped_tags + + +@pytest.mark.parametrize( + ("baggage_keys", "maps_team"), + [(("team+id",), True), (("team%2Bid",), True), (("team+id", "team%2Bid"), False)], + ids=["plus", "percent_encoded", "both_spellings"], +) +def test_plus_sign_rule_key_matches_either_wire_spelling_but_not_both( + optional: Rig, baggage_keys: tuple[str, ...], maps_team: bool +) -> None: + value: Final = uuid.uuid4().hex + baggage: Final = ",".join(("entrypoint=a", *(f"{baggage_key}={value}" for baggage_key in baggage_keys))) + with optional.proxy.scenario() as scenario: + key: Final = scenario.key() + response: Final = _chat(optional, key, baggage) + assert response.status_code == 200, response.text + team_tags: Final = {optional.team_tag(value)} if maps_team else set() + assert _spend_tags(optional.proxy, key) == {optional.exact_tag} | team_tags + + +@pytest.mark.parametrize("deployment_tagged", [True, False], ids=["tagged_deployment", "untagged_deployment"]) +def test_serving_deployment_tag_selects_its_guardrail_mode_when_baggage_maps_the_same_tag( + optional: Rig, deployment_tagged: bool +) -> None: + model: Final = f"guarded-{optional.marker}" if deployment_tagged else optional.chat_model + with optional.proxy.scenario() as scenario: + key: Final = scenario.key() + optional.provider.drain() + response: Final = _chat(optional, key, "guard=on", model=model) + assert response.status_code == 200, response.text + guardrail_inputs: Final = _guardrail_inputs(optional) + assert guardrail_inputs == (("response",) if deployment_tagged else ()), guardrail_inputs + + +def test_baggage_mapping_a_deployment_tag_keeps_the_team_tag_guardrail_mode_first(optional: Rig) -> None: + model: Final = f"guarded-pre-{optional.marker}" + with optional.proxy.scenario() as scenario: + team: Final = scenario.team(metadata={"tags": [optional.policy_tag]}) + key: Final = scenario.key(team_id=team) + optional.provider.drain() + plain: Final = _chat(optional, key, None, model=model) + plain_inputs: Final = _guardrail_inputs(optional) + response: Final = _chat(optional, key, "guard=pre", model=model) + assert (plain.status_code, response.status_code) == (200, 200), (plain.text, response.text) + assert (plain_inputs, _guardrail_inputs(optional)) == (("response",), ("response",)) + + +@pytest.mark.parametrize("metadata", ["run-123", {"tags": "run-123"}], ids=["non_object", "string_tags"]) +@pytest.mark.parametrize( + ("header_tag", "baggage"), + [(True, "region=sg"), (True, "entrypoint=a"), (False, "region=sg"), (False, "entrypoint=a")], + ids=["header_tag_unmapped_baggage", "header_tag_mapped_baggage", "unmapped_baggage", "mapped_baggage"], +) +def test_malformed_metadata_keeps_its_status_under_baggage( + optional: Rig, header_tag: bool, baggage: str, metadata: JsonValue +) -> None: + headers: Final = {"x-litellm-tags": f"caller-{uuid.uuid4().hex}"} if header_tag else {} + fields: Final[Mapping[str, JsonValue]] = {"metadata": metadata} + with optional.proxy.scenario() as scenario: + key: Final = scenario.key() + optional.provider.drain() + plain: Final = _chat(optional, key, None, fields=fields, **headers) + plain_calls: Final = len(optional.provider.drain()) + response: Final = _chat(optional, key, baggage, fields=fields, **headers) + assert plain.status_code < 500, plain.text + assert plain_calls == (1 if plain.status_code == 200 else 0) + assert (response.status_code, len(optional.provider.drain())) == (plain.status_code, plain_calls), ( + plain.text, + response.text, + ) + + +@pytest.mark.parametrize("outage_flag", [False, True], ids=["outage_flag_off", "outage_flag_on"]) +def test_budgeted_mapping_on_a_failed_tag_read(gateway: Gateway, tmp_path: Path, outage_flag: bool) -> None: + marker: Final = uuid.uuid4().hex[:12] + value: Final = uuid.uuid4().hex + tag: Final = f"budgeted-{marker}:{value}" + with ExitStack() as stack: + database_url: Final = stack.enter_context(scratch_database()) + relay, relayed_url = stack.enter_context(dropped_connection_relay(database_url, tag.encode())) + provider: Final = stack.enter_context(wire_server(_provider)) + config: Final = _write_config( + tmp_path, + [_deployment(f"chat-{marker}", provider)], + { + "request_tag_mappings": [ + {"key": "budgeted", "tag_prefix": f"budgeted-{marker}:", "require_budgeted_tag": True} + ], + "allow_requests_on_db_unavailable": outage_flag, + }, + {}, + ) + proxy: Final = stack.enter_context( + owned_proxy( + gateway, + tmp_path, + {"DATABASE_URL": plaintext_database_url(relayed_url), "PRISMA_HEALTH_WATCHDOG_ENABLED": "false"}, + config=config, + remove_environment=("DATABASE_URL_READ_REPLICA",), + ) + ) + scenario: Final = stack.enter_context(proxy.scenario()) + key: Final = scenario.key(max_budget=50) + proxy.post("/tag/new", {"name": tag, "max_budget": 100}) + rig: Final = Rig(proxy, provider, provider, marker) + warmed: Final = _chat(rig, key, None) + assert warmed.status_code == 200, warmed.text + provider.drain() + relay.arm() + response: Final = _chat(rig, key, f"budgeted={value}") + relay.disarm() + assert relay.dropped.is_set(), response.text + if not outage_flag: + assert response.status_code == 503, response.text + assert provider.drain() == () + return + assert response.status_code == 200, response.text + assert response.headers.get("x-litellm-key-max-budget") == "50.0", dict(response.headers) + assert len(provider.drain()) == 1 diff --git a/tests/integration/spend/test_batch_poll_starvation.py b/tests/integration/spend/test_batch_poll_starvation.py index f68f10e3d8a..51f5f0871f5 100644 --- a/tests/integration/spend/test_batch_poll_starvation.py +++ b/tests/integration/spend/test_batch_poll_starvation.py @@ -1,14 +1,20 @@ import json import os +from datetime import datetime, timezone +from functools import partial from hashlib import sha256 +from itertools import chain from typing import Final +from uuid import uuid4 +import httpx import pytest from integration._support.client import JSON_OBJECT, Gateway, Scenario, eventually, object_value, string_value -from integration._support.database import read_rows -from integration._support.upstream import delete_scenario, register_scenario +from integration._support.database import read_rows, write_rows +from integration._support.prisma_clients import connected_proxy_prisma +from integration._support.upstream import ScenarioHandle, delete_scenario, register_scenario from integration.cost_calculation.cost_tracking_case import JsonResponse, RoutedResponse, TextResponse -from pydantic import JsonValue +from pydantic import JsonValue, TypeAdapter from litellm.constants import MAX_OBJECTS_PER_POLL_CYCLE @@ -59,17 +65,17 @@ def _accepting_routes() -> dict[str, JsonResponse | TextResponse]: } -def _gone_at_provider_routes() -> RoutedResponse: +def _gone_at_provider_routes(*, retryable: bool = False) -> RoutedResponse: return RoutedResponse( content_type="application/x-routed", routes={ **_accepting_routes(), "GET /batches/batch-$REQUEST_ID": JsonResponse( content_type="application/json", - status=404, + status=503 if retryable else 404, body={ "error": { - "message": "No batch found with id 'batch-$REQUEST_ID'.", + "message": "Temporary failure" if retryable else "No batch found with id 'batch-$REQUEST_ID'.", "type": "invalid_request_error", "param": "id", "code": "batch_not_found", @@ -80,7 +86,7 @@ def _gone_at_provider_routes() -> RoutedResponse: ) -def _completed_routes() -> RoutedResponse: +def _completed_routes(*, ready: bool = True) -> RoutedResponse: output_line: Final = { "id": "batch_req_1", "custom_id": "r1", @@ -106,7 +112,8 @@ def _completed_routes() -> RoutedResponse: routes={ **_accepting_routes(), "GET /batches/batch-$REQUEST_ID": JsonResponse( - content_type="application/json", body=_batch("completed", "file-out-$REQUEST_ID") + content_type="application/json", + body=_batch("completed", "file-out-$REQUEST_ID") if ready else _batch("in_progress", None), ), "GET /files/file-out-$REQUEST_ID/content": TextResponse( content_type="application/jsonl", body=json.dumps(output_line, separators=(",", ":")) + "\n" @@ -115,7 +122,37 @@ def _completed_routes() -> RoutedResponse: ) -def _scripted_deployment(scenario: Scenario, marker: str, routes: RoutedResponse) -> str: +def _batch_was_polled(upstream: ScenarioHandle) -> bool: + response: Final = httpx.get(f"{upstream.control_url}/__observations", timeout=15, trust_env=False) + response.raise_for_status() + observations: Final = TypeAdapter(dict[str, list[dict[str, JsonValue]]]).validate_json(response.content) + return any( + item.get("method") == "GET" and string_value(item["path"]).startswith(f"/{upstream.scenario_id}/batches/") + for item in observations["requests"] + ) + + +def _missing_output_routes() -> RoutedResponse: + return RoutedResponse( + content_type="application/x-routed", + routes={ + **_completed_routes().routes, + "GET /files/file-out-$REQUEST_ID/content": JsonResponse( + content_type="application/json", + status=404, + body={ + "error": { + "message": "No file found with id 'file-out-$REQUEST_ID'.", + "type": "invalid_request_error", + "code": "file_not_found", + } + }, + ), + }, + ) + + +def _scripted_deployment(scenario: Scenario, marker: str, routes: RoutedResponse) -> tuple[str, ScenarioHandle]: scenario_id: Final = f"poll-{marker}-{sha256(os.urandom(16)).hexdigest()[:12]}" handle: Final = register_scenario(scenario_id, routes) scenario.cleanups.callback(delete_scenario, handle) @@ -133,7 +170,7 @@ def _scripted_deployment(scenario: Scenario, marker: str, routes: RoutedResponse }, ) scenario.cleanups.callback(scenario.delete_model, string_value(object_value(created["model_info"])["id"])) - return string_value(created["model_name"]) + return string_value(created["model_name"]), handle def _submitted_batch_id(gateway: Gateway, key: str, model_name: str) -> str: @@ -173,20 +210,51 @@ def _managed_rows(batch_ids: tuple[str, ...]) -> list[dict[str, JsonValue]]: ) +@pytest.mark.parametrize( + ("retryable", "old_completed", "backlog"), + [(False, False, 0), (False, True, 0), (True, False, 0), (True, True, 0), (True, False, 1000)], +) @pytest.mark.timeout(180) @pytest.mark.covers("quota_management.spend_tracking.batch_costs.uncostable_rows_retire_so_newer_batches_are_costed") -def test_batches_gone_at_provider_do_not_starve_a_newer_batch_out_of_cost_polling(gateway: Gateway) -> None: +def test_uncostable_batches_do_not_starve_billable_batches( + gateway: Gateway, retryable: bool, old_completed: bool, backlog: int +) -> None: with gateway.scenario() as scenario: - key: Final = scenario.key() + owner: Final = f"batch-backlog-{uuid4().hex}" + if backlog: + _insert_scan_rows(owner, "old", backlog, datetime(2000, 1, 1, tzinfo=timezone.utc)) + scenario.cleanups.callback( + write_rows, 'DELETE FROM "LiteLLM_ManagedObjectTable" WHERE created_by = %s', (owner,) + ) + team_id: Final = scenario.team() + key: Final = scenario.key(team_id=team_id) gone_batch_ids: Final = tuple( _submitted_batch_id( - gateway, key, _scripted_deployment(scenario, f"gone{index}", _gone_at_provider_routes()) + gateway, + key, + _scripted_deployment(scenario, f"gone{index}", _gone_at_provider_routes(retryable=retryable))[0], ) for index in range(MAX_OBJECTS_PER_POLL_CYCLE) ) - costable_batch_id: Final = _submitted_batch_id( - gateway, key, _scripted_deployment(scenario, "costable", _completed_routes()) + missing_output_id: Final = _submitted_batch_id( + gateway, key, _scripted_deployment(scenario, "missing-output", _missing_output_routes())[0] ) + model, upstream = _scripted_deployment(scenario, "costable", _completed_routes(ready=False)) + costable_batch_id: Final = _submitted_batch_id(gateway, key, model) + for batch_id in (*gone_batch_ids, missing_output_id, costable_batch_id): + scenario.cleanups.callback( + write_rows, + 'DELETE FROM "LiteLLM_ManagedObjectTable" WHERE unified_object_id = %s', + (batch_id,), + ) + if old_completed: + write_rows( + 'UPDATE "LiteLLM_ManagedObjectTable" SET status = %s, ' + "created_at = NOW() - INTERVAL '30 days' WHERE unified_object_id = %s", + ("completed", costable_batch_id), + ) + assert eventually(lambda: _batch_was_polled(upstream), bool, seconds=120) + register_scenario(upstream.scenario_id, _completed_routes(), control_url=upstream.control_url) spend_rows: Final = eventually( lambda: read_rows( 'SELECT call_type, status, prompt_tokens, completion_tokens, spend FROM "LiteLLM_SpendLogs" ' @@ -209,4 +277,134 @@ def test_batches_gone_at_provider_do_not_starve_a_newer_batch_out_of_cost_pollin } ] assert _managed_rows((costable_batch_id,)) == [{"batch_processed": True}] - assert _managed_rows(gone_batch_ids) == [{"batch_processed": True}] * MAX_OBJECTS_PER_POLL_CYCLE + assert eventually( + lambda: _managed_rows((missing_output_id,)), + lambda rows: rows == [{"batch_processed": True}], + seconds=120, + ) == [{"batch_processed": True}] + expected_blockers: Final = [{"batch_processed": not retryable}] * MAX_OBJECTS_PER_POLL_CYCLE + blockers: Final = eventually( + lambda: _managed_rows(gone_batch_ids), lambda rows: rows == expected_blockers, seconds=120 + ) + assert blockers == expected_blockers + + expected_spend: Final = BATCH_COST_SHARE * ( + PROMPT_TOKENS * INPUT_COST_PER_TOKEN + COMPLETION_TOKENS * OUTPUT_COST_PER_TOKEN + ) + for table, column, identity in ( + ("LiteLLM_VerificationToken", "token", sha256(key.encode()).hexdigest()), + ("LiteLLM_TeamTable", "team_id", team_id), + ): + balance: Final = eventually( + partial(read_rows, f'SELECT spend FROM "{table}" WHERE {column} = %s', (identity,)), + lambda rows: len(rows) == 1 and rows[0]["spend"] == pytest.approx(expected_spend), + seconds=70, + ) + assert balance == [{"spend": pytest.approx(expected_spend)}] + + +def _insert_scan_rows(owner: str, group: str, size: int, created_at: datetime) -> tuple[str, ...]: + prefix: Final = f"{owner}-{group}-" + write_rows( + 'INSERT INTO "LiteLLM_ManagedObjectTable" ' + "(id, unified_object_id, model_object_id, file_object, file_purpose, status, created_by, created_at, updated_at) " + "SELECT %s || lpad(n::text, 8, '0'), %s || n, %s || n, '{}'::jsonb, 'batch', 'completed', %s, " + "%s::timestamptz, NOW() FROM generate_series(0, %s::int - 1) n", + (prefix, prefix, prefix, owner, created_at.isoformat(), str(size)), + ) + return tuple(f"{prefix}{index:08}" for index in range(size)) + + +@pytest.mark.asyncio +@pytest.mark.parametrize("count", [2 * MAX_OBJECTS_PER_POLL_CYCLE, 2 * MAX_OBJECTS_PER_POLL_CYCLE + 1, 1000]) +async def test_arrivals_progress_while_retry_scan_advances_and_wraps(count: int) -> None: + from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache + from litellm.proxy.utils import ProxyLogging + from litellm.router import Router + from litellm_enterprise.proxy.common_utils.check_batch_cost import CheckBatchCost + + owner: Final = f"batch-scan-{uuid4().hex}" + + try: + old_ids: Final = _insert_scan_rows(owner, "old", count, datetime(2000, 1, 1, tzinfo=timezone.utc)) + async with connected_proxy_prisma() as prisma: + logging: Final = ProxyLogging(UserApiKeyCache()) + router: Final = Router() + poller: Final = CheckBatchCost(logging, prisma, router) + where: Final = {"created_by": owner, "batch_processed": False} + first: Final = await poller._find_jobs(where) + assert tuple(row.id for row in first) == old_ids[:MAX_OBJECTS_PER_POLL_CYCLE] + + recent_ids: Final = _insert_scan_rows( + owner, "recent", MAX_OBJECTS_PER_POLL_CYCLE + 1, datetime.now(timezone.utc) + ) + + async def poll_with_arrival(turn: int) -> tuple[str, ...]: + if turn % 4 == 0: + _insert_scan_rows(owner, f"arrival-{turn}", 1, datetime.now(timezone.utc)) + page: Final = await poller._find_jobs(where) + assert len(page) <= MAX_OBJECTS_PER_POLL_CYCLE + write_rows( + 'UPDATE "LiteLLM_ManagedObjectTable" SET batch_processed = true ' + "WHERE created_by = %s AND id = ANY(%s) AND id LIKE %s", + (owner, [row.id for row in page], f"{owner}-arrival-%"), + ) + return tuple(row.id for row in page) + + pages: Final = tuple( + [await poll_with_arrival(turn) for turn in range(4 * (count // MAX_OBJECTS_PER_POLL_CYCLE + 2))] + ) + selected: Final = tuple(chain.from_iterable(pages)) + assert all(selected.count(identity) >= 2 for identity in recent_ids) + selected_old: Final = tuple(identity for identity in selected if identity in old_ids) + assert selected_old[: count - MAX_OBJECTS_PER_POLL_CYCLE] == old_ids[MAX_OBJECTS_PER_POLL_CYCLE:] + assert set(old_ids).issubset(selected_old) + + latest_ids: Final = _insert_scan_rows(owner, "latest", 1, datetime.now(timezone.utc)) + followups: Final = tuple([await poller._find_jobs(where) for _ in range(12)]) + assert any(latest_ids[0] in tuple(row.id for row in page) for page in followups) + + restarted: Final = CheckBatchCost(logging, prisma, router) + restart_page: Final = await restarted._find_jobs(where) + assert tuple(row.id for row in restart_page) == old_ids[:MAX_OBJECTS_PER_POLL_CYCLE] + finally: + write_rows('DELETE FROM "LiteLLM_ManagedObjectTable" WHERE created_by = %s', (owner,)) + + +@pytest.mark.asyncio +@pytest.mark.parametrize("steady_arrivals", [False, True]) +@pytest.mark.parametrize("backlog", [0, 1000]) +async def test_recent_batches_are_revisited_without_scanning_old_backlog(steady_arrivals: bool, backlog: int) -> None: + from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache + from litellm.proxy.utils import ProxyLogging + from litellm.router import Router + from litellm_enterprise.proxy.common_utils.check_batch_cost import CheckBatchCost + + owner: Final = f"batch-repeat-{uuid4().hex}" + try: + _insert_scan_rows(owner, "old", backlog, datetime(2000, 1, 1, tzinfo=timezone.utc)) + async with connected_proxy_prisma() as prisma: + poller: Final = CheckBatchCost(ProxyLogging(UserApiKeyCache()), prisma, Router()) + where: Final = {"created_by": owner, "batch_processed": False} + await poller._find_jobs(where) + target: Final = _insert_scan_rows(owner, "target", 1, datetime.now(timezone.utc))[0] + assert target in tuple(row.id for row in await poller._find_jobs(where)) + for cycle in range(3): + if steady_arrivals: + _insert_scan_rows(owner, f"arrival-{cycle}", 1, datetime.now(timezone.utc)) + pages: Final = tuple([await poller._find_jobs(where) for _ in range(4)]) + assert any(target in tuple(row.id for row in page) for page in pages) + assert all(len(page) <= MAX_OBJECTS_PER_POLL_CYCLE for page in pages) + write_rows( + 'UPDATE "LiteLLM_ManagedObjectTable" SET batch_processed = true WHERE created_by = %s AND id != %s', + (owner, target), + ) + write_rows( + 'UPDATE "LiteLLM_ManagedObjectTable" SET created_at = %s WHERE id = %s', + (datetime(2000, 1, 1, tzinfo=timezone.utc), target), + ) + recovery: Final = tuple([await poller._find_jobs(where) for _ in range(4)]) + assert any(target in tuple(row.id for row in page) for page in recovery) + + finally: + write_rows('DELETE FROM "LiteLLM_ManagedObjectTable" WHERE created_by = %s', (owner,)) diff --git a/tests/integration/spend/test_gemini_tts_speech_billing.py b/tests/integration/spend/test_gemini_tts_speech_billing.py index f1bf3de91b3..ce0752beee3 100644 --- a/tests/integration/spend/test_gemini_tts_speech_billing.py +++ b/tests/integration/spend/test_gemini_tts_speech_billing.py @@ -11,7 +11,6 @@ from typing import Final, Literal import pytest import yaml from integration._support.client import JSON_OBJECT, eventually, gateway_from_environment, object_value -from integration._support.database import read_rows from integration._support.process import OwnedProxy, graceful_stop_seconds, owned_proxy_process from integration._support.vertex import service_account_json from integration._support.wire import Wire, wire_server @@ -201,13 +200,15 @@ def _upstream_calls(wire: Wire, text: str) -> int: return sum(1 for request in wire.drain() if received_text(request) == text) -def _spend_rows(key: str, count: int) -> list[dict[str, JsonValue]]: - return eventually(lambda: read_rows(SPEND_ROWS_SQL, (_hashed(key),)), lambda rows: len(rows) == count, seconds=70) +def _spend_rows(billing: BillingProxy, key: str, count: int) -> list[dict[str, JsonValue]]: + return eventually( + lambda: billing.proxy.gateway.rows(SPEND_ROWS_SQL, (_hashed(key),)), lambda rows: len(rows) == count, seconds=70 + ) -def _key_spend(key: str, expected: float) -> JsonValue: +def _key_spend(billing: BillingProxy, key: str, expected: float) -> JsonValue: rows: Final = eventually( - lambda: read_rows(KEY_SPEND_SQL, (_hashed(key),)), + lambda: billing.proxy.gateway.rows(KEY_SPEND_SQL, (_hashed(key),)), lambda found: len(found) == 1 and found[0]["spend"] == pytest.approx(expected), seconds=70, return_last_on_timeout=True, @@ -224,7 +225,7 @@ def _chat_spend(billing: BillingProxy, model: str, key: str) -> float: } response: Final = billing.proxy.gateway.request("POST", "/v1/chat/completions", body, key=key) assert response.status_code == 200, response.text - row: Final = _spend_rows(key, 1)[0] + row: Final = _spend_rows(billing, key, 1)[0] assert (row["prompt_tokens"], row["completion_tokens"]) == (PROMPT_TOKENS, AUDIO_TOKENS), row spend: Final = row["spend"] assert isinstance(spend, float) and spend > 0, row @@ -261,11 +262,11 @@ def test_speech_calls_google_once_and_bills_and_logs_its_token_usage_once( assert wav_payload(sent.body) == PCM assert _upstream_calls(tts_wire, text) == 1 chat_spend: Final = _chat_spend(uncached, MODELS[provider], scenario.key()) - row: Final = _spend_rows(speech_key, 1)[0] + row: Final = _spend_rows(uncached, speech_key, 1)[0] assert row["call_type"] == "aspeech", row assert (row["prompt_tokens"], row["completion_tokens"]) == (PROMPT_TOKENS, AUDIO_TOKENS), row assert row["spend"] == pytest.approx(chat_spend), row - assert _key_spend(speech_key, chat_spend) == pytest.approx(chat_spend) + assert _key_spend(uncached, speech_key, chat_spend) == pytest.approx(chat_spend) events: Final = _speech_events(uncached, speech_key, 1) assert [_summary(event) for event in events] == [("aspeech", BINARY_RESPONSE, PROMPT_TOKENS, AUDIO_TOKENS)] assert events[0]["response_cost"] == pytest.approx(chat_spend), events @@ -286,11 +287,11 @@ def test_cached_speech_repeat_is_a_free_cache_hit_after_a_billed_first_call( assert _upstream_calls(tts_wire, text) == 1 assert repeat.cache_key, "the cached repeat carried no x-litellm-cache-key header" chat_spend: Final = _chat_spend(cached, model, scenario.key()) - billed, hit = _spend_rows(speech_key, 2) + billed, hit = _spend_rows(cached, speech_key, 2) assert billed["cache_hit"] != "True" and billed["spend"] == pytest.approx(chat_spend), billed assert (billed["prompt_tokens"], billed["completion_tokens"]) == (PROMPT_TOKENS, AUDIO_TOKENS), billed assert (hit["cache_hit"], hit["spend"]) == ("True", 0.0), hit - assert _key_spend(speech_key, chat_spend) == pytest.approx(chat_spend) + assert _key_spend(cached, speech_key, chat_spend) == pytest.approx(chat_spend) events: Final = _speech_events(cached, speech_key, 2) assert len(events) == 2, events hits: Final = tuple(event for event in events if event["cache_hit"] is True) @@ -325,7 +326,7 @@ def test_a_speech_reply_fills_the_deployment_tpm_limit_so_the_next_request_gets_ first_text: Final = marker() first: Final = _speech(uncached, TPM_MODEL, first_text, key) assert first.status == 200, first.body[:300] - _spend_rows(key, 1) + _spend_rows(uncached, key, 1) second_text: Final = marker() second: Final = _speech(uncached, TPM_MODEL, second_text, key) assert second.status == 429, second.body[:300] diff --git a/tests/integration/spend/test_global_proxy_spend_counter.py b/tests/integration/spend/test_global_proxy_spend_counter.py new file mode 100644 index 00000000000..0185e48ffbd --- /dev/null +++ b/tests/integration/spend/test_global_proxy_spend_counter.py @@ -0,0 +1,58 @@ +import os +import uuid +from typing import Final + +import pytest + +import litellm +from litellm.caching.in_memory_cache import InMemoryCache +from litellm.caching.redis_cache import RedisCache +from litellm.constants import GLOBAL_PROXY_SPEND_CACHE_KEY +from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache +from litellm.proxy.proxy_server import update_cache + + +async def _add_request_cost(cache: UserApiKeyCache, response_cost: float) -> None: + await update_cache( + token=None, + user_id=None, + end_user_id=None, + team_id=None, + response_cost=response_cost, + parent_otel_span=None, + cache=cache, + ) + + +@pytest.mark.asyncio +async def test_global_proxy_spend_adds_every_instance_cost_and_stays_cleared_after_a_budget_reset( + monkeypatch: pytest.MonkeyPatch, +) -> None: + monkeypatch.setattr(litellm, "max_budget", 100.0) + redis_cache: Final = RedisCache( + host=os.environ["REDIS_HOST"], + port=int(os.environ["REDIS_PORT"]), + namespace=f"global-proxy-spend-{uuid.uuid4().hex}", + ) + gateway: Final = UserApiKeyCache(in_memory_cache=InMemoryCache(), redis_cache=redis_cache) + peer: Final = UserApiKeyCache(in_memory_cache=InMemoryCache(), redis_cache=redis_cache) + + try: + await gateway.async_set_cache(key=GLOBAL_PROXY_SPEND_CACHE_KEY, value=10.0, ttl=60) + await _add_request_cost(peer, 0.5) + await _add_request_cost(gateway, 0.25) + before_reset: Final = ( + gateway.get_cache(key=GLOBAL_PROXY_SPEND_CACHE_KEY, local_only=True), + await redis_cache.async_get_cache(key=GLOBAL_PROXY_SPEND_CACHE_KEY), + ) + ttl_before_reset: Final = await redis_cache.async_get_ttl(key=GLOBAL_PROXY_SPEND_CACHE_KEY) + + await gateway.async_delete_cache(key=GLOBAL_PROXY_SPEND_CACHE_KEY) + await _add_request_cost(peer, 0.5) + await _add_request_cost(gateway, 0.25) + + assert before_reset == (10.75, 10.75) + assert ttl_before_reset is not None and 0 < ttl_before_reset <= 60 + assert await redis_cache.async_get_cache(key=GLOBAL_PROXY_SPEND_CACHE_KEY) is None + finally: + await redis_cache.async_delete_cache(key=GLOBAL_PROXY_SPEND_CACHE_KEY) diff --git a/tests/integration/spend/test_passthrough_stream_pricing_paths_spend.py b/tests/integration/spend/test_passthrough_stream_pricing_paths_spend.py index f091a8f8376..0ead544a2ee 100644 --- a/tests/integration/spend/test_passthrough_stream_pricing_paths_spend.py +++ b/tests/integration/spend/test_passthrough_stream_pricing_paths_spend.py @@ -12,7 +12,6 @@ import httpx import pytest import yaml from integration._support.client import Gateway, eventually, gateway_from_environment -from integration._support.database import read_rows from integration._support.forward_proxy import tunnelling_forward_proxy from integration._support.process import graceful_stop_seconds, owned_proxy from integration._support.tls import server_context, write_self_signed_cert @@ -289,9 +288,9 @@ def gateway_rig(tmp_path_factory: pytest.TempPathFactory) -> Iterator[_Rig]: yield _Rig(proxy, upstream) -def _spend_row(key: str) -> dict[str, JsonValue]: +def _spend_row(gateway: Gateway, key: str) -> dict[str, JsonValue]: rows: Final = eventually( - lambda: read_rows( + lambda: gateway.rows( 'SELECT spend, custom_llm_provider FROM "LiteLLM_SpendLogs" WHERE api_key=%s', (sha256(key.encode()).hexdigest(),), ), @@ -301,14 +300,14 @@ def _spend_row(key: str) -> dict[str, JsonValue]: return rows[0] -def _spend_for_key(key: str) -> float: - spend: Final = _spend_row(key)["spend"] +def _spend_for_key(gateway: Gateway, key: str) -> float: + spend: Final = _spend_row(gateway, key)["spend"] assert isinstance(spend, float), key return spend -def _provider_for_key(key: str) -> JsonValue: - return _spend_row(key)["custom_llm_provider"] +def _provider_for_key(gateway: Gateway, key: str) -> JsonValue: + return _spend_row(gateway, key)["custom_llm_provider"] def _post_and_read(rig: _Rig, path: str, body: Mapping[str, JsonValue], headers: Mapping[str, str]) -> None: @@ -347,7 +346,7 @@ def test_claude_on_vertex_passthrough_spend_carries_the_regional_uplift_whether_ {**body, "stream": action == "streamRawPredict"}, {"x-litellm-api-key": f"Bearer {key}", "Authorization": f"Bearer {_CALLER_GOOGLE_TOKEN}"}, ) - spend: Final = {cell: _spend_for_key(key) for cell, key in keys.items()} + spend: Final = {cell: _spend_for_key(rig.proxy, key) for cell, key in keys.items()} standard: Final = _list_price(f"vertex_ai/{_CLAUDE_ROUTE_MODEL}") regional: Final = standard * _uplift(f"vertex_ai/{_CLAUDE_ROUTE_MODEL}") assert spend == pytest.approx( @@ -370,7 +369,7 @@ def test_v1beta_generate_content_on_a_vertex_deployment_bills_the_deployment_loc keys: Final = {cell: scenario.key() for cell in cells} for (deployment, action), key in keys.items(): _post_and_read(rig, f"/v1beta/models/{deployment}:{action}", body, {"x-goog-api-key": key}) - spend: Final = {cell: _spend_for_key(key) for cell, key in keys.items()} + spend: Final = {cell: _spend_for_key(rig.proxy, key) for cell, key in keys.items()} standard: Final = _list_price(f"vertex_ai/{_GEMINI}") regional: Final = standard * _uplift(f"vertex_ai/{_GEMINI}") assert spend == pytest.approx( @@ -404,8 +403,8 @@ def test_gemini_passthrough_bills_a_named_custom_priced_deployment_only_for_keys for key in (allowed[action], plain[action]): _post_and_read(rig, f"/gemini/v1beta/models/{_GEMINI}:{action}", body, {"x-goog-api-key": key}) spend: Final = { - **{("allowed", action): _spend_for_key(key) for action, key in allowed.items()}, - **{("plain", action): _spend_for_key(key) for action, key in plain.items()}, + **{("allowed", action): _spend_for_key(rig.proxy, key) for action, key in allowed.items()}, + **{("plain", action): _spend_for_key(rig.proxy, key) for action, key in plain.items()}, } custom_price: Final = _PROMPT_TOKENS * _CUSTOM_INPUT_RATE + _COMPLETION_TOKENS * _CUSTOM_OUTPUT_RATE list_price: Final = _list_price(f"gemini/{_GEMINI}") @@ -441,7 +440,10 @@ def test_openai_passthrough_stream_cut_off_after_its_usage_bills_what_the_finish assert response.status_code == 200 with pytest.raises(httpx.RemoteProtocolError): response.read() - spend: Final = {"finished": _spend_for_key(finished_key), "cut off": _spend_for_key(cut_key)} + spend: Final = { + "finished": _spend_for_key(rig.proxy, finished_key), + "cut off": _spend_for_key(rig.proxy, cut_key), + } list_price: Final = _list_price(_OPENAI_MODEL) assert spend == pytest.approx({"finished": list_price, "cut off": list_price}) @@ -484,7 +486,7 @@ def test_a_body_base_model_reprices_passthrough_spend_only_for_keys_that_allow_c }, _caller_headers(route, key), ) - spend: Final = {cell: _spend_for_key(key) for cell, key in keys.items()} + spend: Final = {cell: _spend_for_key(rig.proxy, key) for cell, key in keys.items()} forwarded: Final = rig.upstream.drain() marked_bodies: Final = { cell: tuple(request.body for request in forwarded if marker.encode() in request.body) @@ -521,7 +523,7 @@ def test_a_non_string_body_base_model_bills_the_list_price_instead_of_nothing(ri {"contents": [{"role": "user", "parts": [{"text": uuid.uuid4().hex}]}], "base_model": 123}, _caller_headers(route, key), ) - spend: Final = {cell: _spend_for_key(key) for cell, key in keys.items()} + spend: Final = {cell: _spend_for_key(rig.proxy, key) for cell, key in keys.items()} list_price: Final = { "vertex_ai": _list_price(f"vertex_ai/{_GEMINI}"), "gemini": _list_price(f"gemini/{_GEMINI}"), @@ -538,8 +540,8 @@ def test_gemini_passthrough_through_a_gemini_api_base_gateway_logs_and_bills_as_ keys: Final = {action: scenario.key() for action in _GEMINI_ACTIONS} for action, key in keys.items(): _post_and_read(gateway_rig, f"/gemini/v1beta/models/{_GEMINI}:{action}", body, {"x-goog-api-key": key}) - providers: Final = {action: _provider_for_key(key) for action, key in keys.items()} - spend: Final = {action: _spend_for_key(key) for action, key in keys.items()} + providers: Final = {action: _provider_for_key(gateway_rig.proxy, key) for action, key in keys.items()} + spend: Final = {action: _spend_for_key(gateway_rig.proxy, key) for action, key in keys.items()} forwarded: Final = tuple( path for path in (urlsplit(request.target).path for request in gateway_rig.upstream.drain()) @@ -570,8 +572,8 @@ def test_a_configured_passthrough_to_a_non_google_gateway_bills_as_vertex_whatev body, {"Authorization": f"Bearer {key}"}, ) - providers: Final = {cell: _provider_for_key(key) for cell, key in keys.items()} - spend: Final = {cell: _spend_for_key(key) for cell, key in keys.items()} + providers: Final = {cell: _provider_for_key(gateway_rig.proxy, key) for cell, key in keys.items()} + spend: Final = {cell: _spend_for_key(gateway_rig.proxy, key) for cell, key in keys.items()} short_path_spend: Final = {action: spend[("short gateway path", action)] for action in _GEMINI_ACTIONS} assert providers == {cell: "vertex_ai" for cell in cells} assert {action: spend[("vertex resource", action)] for action in _GEMINI_ACTIONS} == pytest.approx( diff --git a/tests/integration/spend/test_tag_budget_enforcement.py b/tests/integration/spend/test_tag_budget_enforcement.py index 0c0db2943c6..5430f77a3ec 100644 --- a/tests/integration/spend/test_tag_budget_enforcement.py +++ b/tests/integration/spend/test_tag_budget_enforcement.py @@ -105,6 +105,46 @@ def test_spend_over_a_tag_max_budget_rejects_the_next_request(gateway: Gateway) assert control.status_code == 200, control.text +def test_tag_new_counts_spend_from_creation_not_before(gateway: Gateway) -> None: + tag: Final = f"tag-created-late-{uuid.uuid4().hex}" + + def delete_tag() -> None: + gateway.post("/tag/delete", {"name": tag}) + + with gateway.scenario() as scenario: + model: Final = scenario.model(input_cost_per_token=0.01, output_cost_per_token=0.01) + + def tagged(text: str) -> httpx.Response: + return gateway.request( + "POST", + "/v1/chat/completions", + { + "model": model, + "messages": [{"role": "user", "content": f"{text} {uuid.uuid4().hex}"}], + "metadata": {"tags": [tag]}, + }, + ) + + untracked: Final = tagged("spend before the tag exists") + assert untracked.status_code == 200, untracked.text + with Redis(host=os.environ["REDIS_HOST"], port=int(os.environ["REDIS_PORT"])) as cache: + counted: Final = eventually( + lambda: float(cache.get(f"spend:tag:{tag}") or 0), + lambda spend: spend > 0.0001, + seconds=70, + ) + assert counted > 0.0001, counted + gateway.post("/tag/new", {"name": tag, "max_budget": 0.0001}) + scenario.cleanups.callback(delete_tag) + admitted: Final = tagged("first request under the new budget") + assert admitted.status_code == 200, admitted.text + blocked: Final = eventually( + lambda: tagged("budget probe"), lambda response: response.status_code != 200, seconds=70 + ) + assert blocked.status_code == 422, blocked.text + assert "budget" in blocked.text.lower(), blocked.text + + def test_tag_object_rpm_limit_rejects_the_second_request_across_keys(gateway: Gateway) -> None: tag: Final = f"tag-rpm-{uuid.uuid4().hex}" @@ -446,9 +486,7 @@ def test_tag_budget_duration_can_be_cleared_and_limits_are_read_back(gateway: Ga "rpm_limit": budget_info["rpm_limit"], "budget_duration": budget_info["budget_duration"], "budget_reset_at": budget_info["budget_reset_at"], - } == {"max_budget": 100, "rpm_limit": 1, "budget_duration": None, "budget_reset_at": None}, ( - info_response.text - ) + } == {"max_budget": 100, "rpm_limit": 1, "budget_duration": None, "budget_reset_at": None}, info_response.text tag_rows: Final = read_rows('SELECT budget_id FROM "LiteLLM_TagTable" WHERE tag_name = %s', (tag,)) assert len(tag_rows) == 1, tag_rows @@ -457,9 +495,9 @@ def test_tag_budget_duration_can_be_cleared_and_limits_are_read_back(gateway: Ga "WHERE budget_id = %s", (str(tag_rows[0]["budget_id"]),), ) - assert budget_rows == [ - {"max_budget": 100, "rpm_limit": 1, "budget_duration": None, "budget_reset_at": None} - ], budget_rows + assert budget_rows == [{"max_budget": 100, "rpm_limit": 1, "budget_duration": None, "budget_reset_at": None}], ( + budget_rows + ) @pytest.mark.parametrize("tag_source", _TAG_SOURCES, ids=_TAG_SOURCE_IDS) diff --git a/tests/integration/spend/test_vertex_passthrough_regional_uplift_spend.py b/tests/integration/spend/test_vertex_passthrough_regional_uplift_spend.py index eaa8f52d4f4..0b2dd8910d6 100644 --- a/tests/integration/spend/test_vertex_passthrough_regional_uplift_spend.py +++ b/tests/integration/spend/test_vertex_passthrough_regional_uplift_spend.py @@ -10,7 +10,6 @@ import httpx import pytest import yaml from integration._support.client import Gateway, eventually, gateway_from_environment -from integration._support.database import read_rows from integration._support.forward_proxy import ForwardProxy, tunnelling_forward_proxy from integration._support.process import graceful_stop_seconds, owned_proxy from integration._support.tls import server_context, write_self_signed_cert @@ -150,12 +149,12 @@ def _spend(rig: _Rig, key: str, location: str, action: str, model: str = _MODEL) body: Final = response.read() assert response.status_code == 200, body call_id: Final = response.headers["x-litellm-call-id"] - return _logged_spend(call_id) + return _logged_spend(rig.proxy, call_id) -def _logged_spend(call_id: str) -> float: +def _logged_spend(gateway: Gateway, call_id: str) -> float: rows: Final = eventually( - lambda: read_rows('SELECT spend FROM "LiteLLM_SpendLogs" WHERE request_id=%s', (call_id,)), + lambda: gateway.rows('SELECT spend FROM "LiteLLM_SpendLogs" WHERE request_id=%s', (call_id,)), lambda found: len(found) == 1, seconds=70, ) @@ -193,7 +192,7 @@ def test_custom_priced_vertex_passthrough_bills_the_deployment_price_even_when_t call_id: Final = response.headers["x-litellm-call-id"] with pytest.raises(httpx.RemoteProtocolError): response.read() - cut_off: Final = _logged_spend(call_id) + cut_off: Final = _logged_spend(rig.proxy, call_id) custom_price: Final = _PROMPT_TOKENS * _CUSTOM_INPUT_RATE + _COMPLETION_TOKENS * _CUSTOM_OUTPUT_RATE assert {**finished, "cut off": cut_off} == pytest.approx( {_GENERATE: custom_price, _STREAM: custom_price, "cut off": custom_price} diff --git a/tests/integration/streaming/test_text_completion_stream_guardrail_rebuild.py b/tests/integration/streaming/test_text_completion_stream_guardrail_rebuild.py index 60a33d46b29..229a9be6d20 100644 --- a/tests/integration/streaming/test_text_completion_stream_guardrail_rebuild.py +++ b/tests/integration/streaming/test_text_completion_stream_guardrail_rebuild.py @@ -16,7 +16,6 @@ from integration._support.client import ( list_value, object_value, ) -from integration._support.database import read_rows from integration._support.process import OwnedProxy, WorkerHealthcheck, graceful_stop_seconds, owned_proxy_process from integration._support.wire import Reply, Request, Wire, wire_server from pydantic import JsonValue @@ -202,7 +201,7 @@ def test_guarded_text_completion_stream_reaches_the_caller_whole_with_its_usage( ], stream.frames assert _posted_targets(rig.wire) == ("/v1/completions",) (row,) = eventually( - lambda: read_rows( + lambda: rig.proxy.gateway.rows( 'SELECT prompt_tokens, completion_tokens, metadata FROM "LiteLLM_SpendLogs" WHERE request_id = %s', (identity,), ), diff --git a/tests/integration/translation/chat_completions/cross_model/README.md b/tests/integration/translation/chat_completions/cross_model/README.md index 90710d5597c..99a4225480e 100644 --- a/tests/integration/translation/chat_completions/cross_model/README.md +++ b/tests/integration/translation/chat_completions/cross_model/README.md @@ -8,7 +8,7 @@ Every row sends `CODING_AGENT_REQUEST` to `/v1/chat/completions`, changing only | Mid | Opus 5 and 5.5, Sonnet 5.5, Gemini 3.8 Flash and 3.1 Pro Preview, GPT 5.6 Sol, 6 Sol and 6.1 Sol, GPT 5.6 Terra | | High | Fable 5 and 5.1, Gemini 4 Argon, GPT 6 Astra | -The 51 rows cover Anthropic direct, OpenAI direct, Vertex, Gemini direct, Azure OpenAI, Azure AI and Bedrock Converse where accessible. Vertex Haiku 5.5 was unavailable during capture and is not represented +The 52 rows cover Anthropic direct, OpenAI direct, Vertex, Gemini direct, Azure OpenAI, Azure AI and Bedrock Converse where accessible. Vertex Haiku 5.5 was unavailable during capture and is not represented The request contains system instructions, conversation history, previous assistant tool calls and results, four function definitions, automatic parallel tools, low reasoning effort and an output limit. Each row exercises a tool-call response, raw streaming, SDK stream assembly and a follow-up that replays the returned assistant message and tool-call IDs @@ -33,7 +33,7 @@ Streaming cases store `expected_litellm_message` and `expected_litellm_usage`. M Usage requires nonnegative integer counts, positive prompt and completion counts, and `total_tokens == prompt_tokens + completion_tokens`. The complete normalized usage must equal the independently expected counters, including cached and reasoning tokens and derived text/cache details. Missing, changed or unexpected counters fail. Only null optional fields, the explicitly listed provider metadata/duplicate counters and computed `cost` are excluded. Thus a wrong prompt count with an adjusted total still fails -The raw stream check assembles tool names and argument fragments by index. The SDK check separately uses `OpenAI.chat.completions.stream()` without removing reasoning fields. All 51 SDK checks run, including the seven Haiku rows. [LIT-9653](https://linear.app/litellm-ai/issue/LIT-9653) was fixed in [#46611](https://github.com/BerriAI/litellm/pull/46611), so there are no Haiku skips +The raw stream check assembles tool names and argument fragments by index. The SDK check separately uses `OpenAI.chat.completions.stream()` without removing reasoning fields. All 52 SDK checks run, including the seven Haiku rows. [LIT-9653](https://linear.app/litellm-ai/issue/LIT-9653) was fixed in [#46611](https://github.com/BerriAI/litellm/pull/46611), so there are no Haiku skips ## Recorded upstreams diff --git a/tests/integration/translation/chat_completions/cross_model/anthropic.py b/tests/integration/translation/chat_completions/cross_model/anthropic.py index 3df7da17ef6..9302103f369 100644 --- a/tests/integration/translation/chat_completions/cross_model/anthropic.py +++ b/tests/integration/translation/chat_completions/cross_model/anthropic.py @@ -11,6 +11,7 @@ from integration.translation.chat_completions.bases.anthropic import ( CLAUDE_HAIKU_5_5_TEST_CASE, CLAUDE_OPUS_5_5_TEST_CASE, CLAUDE_OPUS_5_TEST_CASE, + CLAUDE_SONNET_5_5_TEST_CASE, ) from integration.translation.chat_completions.templates import ( CODING_AGENT_REQUEST, @@ -2098,3 +2099,352 @@ CLAUDE_OPUS_5_AGENT_STREAMING_TEST_CASE: Final = StreamingTranslationTestCase( "completion_tokens_details": {"reasoning_tokens": 0, "text_tokens": 105}, }, ) + + +CLAUDE_SONNET_5_5_AGENT_FOLLOWUP_TEXT: Final = ( + "The bug is that `retries_remaining` in `src/retry.py` returns `limit + attempts` instead of " + "`max(0, limit - attempts)`, so it can return too many retries and can't be clamped at zero. The only other " + "caller is `src/worker.py` line 12 (`retries_remaining(3, attempts)`), and `tests/test_retry.py::test_retries_remaining` " + "fails with `assert 4 == 2` for `retries_remaining(3, 1)`." +) + + +CLAUDE_SONNET_5_5_AGENT_TEST_CASE: Final = replace( + CLAUDE_SONNET_5_5_TEST_CASE, + scenario="agent_tools", + litellm_request={**CODING_AGENT_REQUEST, "model": "anthropic/claude-sonnet-5-5"}, + expected_provider_endpoint="/v1/messages", + expected_provider_headers=CLAUDE_OPUS_5_5_AGENT_TEST_CASE.expected_provider_headers, + expected_provider_request={ + **ANTHROPIC_AGENT_REQUEST, + "model": "claude-sonnet-5-5", + "thinking": {"type": "adaptive", "display": "summarized"}, + "output_config": {"effort": "low"}, + }, + mock_provider_response={ + **ANTHROPIC_AGENT_RESPONSE, + "model": "claude-sonnet-5-5", + "id": "msg_011CgDcA1vnTwnTPTcJv9Lb7", + "content": [ + { + "type": "tool_use", + "id": "toolu_01RK8oPY5AnH3K4R8LfPXPTi", + "name": "search_code", + "input": {"query": "retries_remaining"}, + "caller": {"type": "direct"}, + }, + { + "type": "tool_use", + "id": "toolu_013REgHECA7Rceip3FrejMEy", + "name": "run_tests", + "input": {"path": "tests/test_retry.py"}, + "caller": {"type": "direct"}, + }, + ], + "stop_reason": "tool_use", + "usage": { + **object_value(ANTHROPIC_AGENT_RESPONSE["usage"]), + "input_tokens": 1184, + "output_tokens": 105, + "output_tokens_details": {"thinking_tokens": 0}, + "service_tier": "standard", + "inference_geo": "global", + "speed": "standard", + }, + "diagnostics": None, + }, + expected_litellm_response={ + **CODING_AGENT_RESPONSE, + "model": "anthropic/claude-sonnet-5-5", + "choices": [ + { + "finish_reason": "tool_calls", + "index": 0, + "message": { + "role": "assistant", + "tool_calls": [ + { + "index": 0, + "caller": {"type": "direct"}, + "function": { + "arguments": '{"query": "retries_remaining"}', + "name": "search_code", + }, + "id": "toolu_01RK8oPY5AnH3K4R8LfPXPTi", + "type": "function", + }, + { + "index": 1, + "caller": {"type": "direct"}, + "function": { + "arguments": '{"path": "tests/test_retry.py"}', + "name": "run_tests", + }, + "id": "toolu_013REgHECA7Rceip3FrejMEy", + "type": "function", + }, + ], + "provider_specific_fields": {"citations": None, "thinking_blocks": None}, + "content": None, + }, + } + ], + "usage": { + "completion_tokens": 105, + "prompt_tokens": 1184, + "total_tokens": 1289, + "completion_tokens_details": {"reasoning_tokens": 0, "text_tokens": 105}, + "prompt_tokens_details": { + "cached_tokens": 0, + "text_tokens": 1184, + "cache_write_tokens": 0, + "cache_creation_tokens": 0, + "cache_creation_token_details": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 0}, + }, + "cache_creation_input_tokens": 0, + "cache_read_input_tokens": 0, + "inference_geo": "global", + "speed": "standard", + "service_tier": "standard", + }, + }, +) + + +CLAUDE_SONNET_5_5_AGENT_FOLLOWUP_TEST_CASE: Final = replace( + CLAUDE_SONNET_5_5_AGENT_TEST_CASE, + scenario="agent_followup", + litellm_request=followup_request( + CLAUDE_SONNET_5_5_AGENT_TEST_CASE.litellm_request, + CLAUDE_SONNET_5_5_AGENT_TEST_CASE.expected_litellm_response, + ), + expected_provider_endpoint="/v1/messages", + expected_provider_request={ + **ANTHROPIC_AGENT_REQUEST, + "model": "claude-sonnet-5-5", + "messages": [ + *list_value(ANTHROPIC_AGENT_REQUEST["messages"]), + { + "role": "assistant", + "content": [ + { + "type": "tool_use", + "id": "toolu_01RK8oPY5AnH3K4R8LfPXPTi", + "name": "search_code", + "input": {"query": "retries_remaining"}, + }, + { + "type": "tool_use", + "id": "toolu_013REgHECA7Rceip3FrejMEy", + "name": "run_tests", + "input": {"path": "tests/test_retry.py"}, + }, + ], + }, + { + "role": "user", + "content": [ + { + "type": "tool_result", + "tool_use_id": "toolu_01RK8oPY5AnH3K4R8LfPXPTi", + "content": '{"matches": [{"path": "src/worker.py", "line": 12, "text": "remaining = ' + 'retries_remaining(3, attempts)"}]}', + }, + { + "type": "tool_result", + "tool_use_id": "toolu_013REgHECA7Rceip3FrejMEy", + "content": '{"exit_code": 1, "output": "FAILED tests/test_retry.py::test_retries_remaining - ' + 'assert 4 == 2"}', + }, + { + "type": "text", + "text": "Stop after these diagnostics. Do not call more tools or change files. Summarize the " + "bug, the caller found and the failed test in two short sentences.", + }, + ], + }, + ], + "thinking": {"type": "adaptive", "display": "summarized"}, + "output_config": {"effort": "low"}, + }, + mock_provider_response={ + **ANTHROPIC_AGENT_RESPONSE, + "model": "claude-sonnet-5-5", + "id": "msg_011CgDcZdb2JGywm8DnwxFvn", + "content": [{"type": "text", "text": CLAUDE_SONNET_5_5_AGENT_FOLLOWUP_TEXT}], + "stop_reason": "end_turn", + "usage": { + **object_value(ANTHROPIC_AGENT_RESPONSE["usage"]), + "input_tokens": 1492, + "output_tokens": 155, + "output_tokens_details": {"thinking_tokens": 0}, + "service_tier": "standard", + "inference_geo": "global", + "speed": "standard", + }, + "diagnostics": None, + }, + expected_litellm_response={ + **CODING_AGENT_RESPONSE, + "model": "anthropic/claude-sonnet-5-5", + "choices": [ + { + "finish_reason": "stop", + "index": 0, + "message": { + "content": CLAUDE_SONNET_5_5_AGENT_FOLLOWUP_TEXT, + "role": "assistant", + "provider_specific_fields": {"citations": None, "thinking_blocks": None}, + }, + } + ], + "usage": { + "completion_tokens": 155, + "prompt_tokens": 1492, + "total_tokens": 1647, + "completion_tokens_details": {"reasoning_tokens": 0, "text_tokens": 155}, + "prompt_tokens_details": { + "cached_tokens": 0, + "text_tokens": 1492, + "cache_write_tokens": 0, + "cache_creation_tokens": 0, + "cache_creation_token_details": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 0}, + }, + "cache_creation_input_tokens": 0, + "cache_read_input_tokens": 0, + "inference_geo": "global", + "speed": "standard", + "service_tier": "standard", + }, + }, +) + + +CLAUDE_SONNET_5_5_AGENT_STREAMING_TEST_CASE: Final = StreamingTranslationTestCase( + scenario="agent_streaming", + litellm_endpoint=CLAUDE_SONNET_5_5_AGENT_TEST_CASE.litellm_endpoint, + litellm_request={ + **CLAUDE_SONNET_5_5_AGENT_TEST_CASE.litellm_request, + "stream": True, + "stream_options": {"include_usage": True}, + }, + expected_provider_headers=CLAUDE_SONNET_5_5_AGENT_TEST_CASE.expected_provider_headers, + expected_provider_endpoint="/v1/messages", + expected_provider_request={ + **CLAUDE_SONNET_5_5_AGENT_TEST_CASE.expected_provider_request, + "stream": True, + }, + mock_provider_frames=( + SSEFrame( + data={ + "type": "message_start", + "message": { + **ANTHROPIC_AGENT_RESPONSE, + "model": "claude-sonnet-5-5", + "id": "msg_011CgDcC8agu11ruKbps6qFH", + "content": [], + "stop_reason": None, + "usage": { + **object_value(ANTHROPIC_AGENT_RESPONSE["usage"]), + "input_tokens": 1184, + "output_tokens": 16, + "service_tier": "standard", + "inference_geo": "global", + "speed": "standard", + }, + "diagnostics": None, + }, + }, + event="message_start", + ), + SSEFrame( + data={ + "type": "content_block_start", + "index": 0, + "content_block": { + "type": "tool_use", + "id": "toolu_01LmCacjLUDXcY139vPTCceR", + "name": "search_code", + "input": {}, + "caller": {"type": "direct"}, + }, + }, + event="content_block_start", + ), + SSEFrame(data={"type": "ping"}, event="ping"), + *( + SSEFrame( + data={ + "type": "content_block_delta", + "index": 0, + "delta": {"type": "input_json_delta", "partial_json": partial_json}, + }, + event="content_block_delta", + ) + for partial_json in ("", '{"query', '": "ret', "ries_re", "maining", '"}') + ), + SSEFrame(data={"type": "content_block_stop", "index": 0}, event="content_block_stop"), + SSEFrame( + data={ + "type": "content_block_start", + "index": 1, + "content_block": { + "type": "tool_use", + "id": "toolu_011cyQH4o1bcDJYsWQoLSzGT", + "name": "run_tests", + "input": {}, + "caller": {"type": "direct"}, + }, + }, + event="content_block_start", + ), + *( + SSEFrame( + data={ + "type": "content_block_delta", + "index": 1, + "delta": {"type": "input_json_delta", "partial_json": partial_json}, + }, + event="content_block_delta", + ) + for partial_json in ("", '{"path"', ': "test', "s/test_", "retry.p", 'y"}') + ), + SSEFrame(data={"type": "content_block_stop", "index": 1}, event="content_block_stop"), + SSEFrame( + data={ + "type": "message_delta", + "delta": { + "stop_reason": "tool_use", + "stop_sequence": None, + "stop_details": None, + "container": None, + }, + "usage": { + "input_tokens": 1184, + "cache_creation_input_tokens": 0, + "cache_read_input_tokens": 0, + "output_tokens": 105, + "output_tokens_details": {"thinking_tokens": 0}, + }, + }, + event="message_delta", + ), + SSEFrame(data={"type": "message_stop"}, event="message_stop"), + ), + expected_litellm_message=coding_agent_stream_message( + ("toolu_01LmCacjLUDXcY139vPTCceR", "toolu_011cyQH4o1bcDJYsWQoLSzGT") + ), + expected_litellm_usage={ + "prompt_tokens": 1184, + "completion_tokens": 105, + "total_tokens": 1289, + "prompt_tokens_details": { + "cached_tokens": 0, + "text_tokens": 1184, + "cache_write_tokens": 0, + "cache_creation_tokens": 0, + "cache_creation_token_details": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 0}, + }, + "completion_tokens_details": {"reasoning_tokens": 0, "text_tokens": 105}, + }, +) diff --git a/tests/integration/translation/chat_completions/cross_model/case.py b/tests/integration/translation/chat_completions/cross_model/case.py index 189592b26c2..8dee0fae2ab 100644 --- a/tests/integration/translation/chat_completions/cross_model/case.py +++ b/tests/integration/translation/chat_completions/cross_model/case.py @@ -132,6 +132,11 @@ MID: Final[tuple[AgentCases, ...]] = ( bedrock_converse.CLAUDE_SONNET_5_5_AGENT_FOLLOWUP_TEST_CASE, bedrock_converse.CLAUDE_SONNET_5_5_AGENT_STREAMING_TEST_CASE, ), + ( + anthropic.CLAUDE_SONNET_5_5_AGENT_TEST_CASE, + anthropic.CLAUDE_SONNET_5_5_AGENT_FOLLOWUP_TEST_CASE, + anthropic.CLAUDE_SONNET_5_5_AGENT_STREAMING_TEST_CASE, + ), ( bedrock_converse.CLAUDE_OPUS_5_TEST_CASE, bedrock_converse.CLAUDE_OPUS_5_AGENT_FOLLOWUP_TEST_CASE, diff --git a/tests/integration/translation/chat_completions/response_format/__init__.py b/tests/integration/translation/chat_completions/response_format/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/integration/translation/chat_completions/response_format/test_chat_completions_response_format_anthropic.py b/tests/integration/translation/chat_completions/response_format/test_chat_completions_response_format_anthropic.py new file mode 100644 index 00000000000..07e4358ff97 --- /dev/null +++ b/tests/integration/translation/chat_completions/response_format/test_chat_completions_response_format_anthropic.py @@ -0,0 +1,123 @@ +from dataclasses import replace +from typing import Final +from unittest.mock import ANY + +import pytest +from integration._support.client import Gateway +from integration._support.provider import SharedProvider +from integration.translation.case import TranslationTestCase +from integration.translation.chat_completions.bases.anthropic import CLAUDE_HAIKU_5_5_TEST_CASE +from integration.translation.runner import assert_translation + +PLACE_SCHEMA: Final = { + "type": "object", + "properties": {"city": {"type": "string"}, "country": {"type": "string"}}, + "required": ["city", "country"], + "additionalProperties": True, +} +PLACE_PROMPT: Final = "Which city is the capital of France? Answer as JSON with city and country." +PLACE_TOOL_USE: Final = { + "type": "tool_use", + "id": "toolu_01Sr1iptyZnsy1eNxabMZejF", + "name": "json_tool_call", + "input": {"city": "Paris", "country": "France"}, + "caller": {"type": "direct"}, +} + +CLAUDE_HAIKU_5_5_JSON_SCHEMA_TEST_CASE: Final = replace( + CLAUDE_HAIKU_5_5_TEST_CASE, + scenario="json_schema", + litellm_request={ + "model": "anthropic/claude-haiku-5-5", + "max_tokens": 128, + "messages": [{"role": "user", "content": PLACE_PROMPT}], + "response_format": {"type": "json_schema", "json_schema": {"name": "place", "schema": PLACE_SCHEMA}}, + "cache": {"no-cache": True}, + }, + expected_provider_request={ + "model": "claude-haiku-5-5", + "messages": [{"role": "user", "content": [{"type": "text", "text": PLACE_PROMPT}]}], + "max_tokens": 128, + "tool_choice": {"name": "json_tool_call", "type": "tool"}, + "tools": [{"name": "json_tool_call", "input_schema": PLACE_SCHEMA}], + }, + mock_provider_response={ + "model": "claude-haiku-5-5", + "id": "msg_011CgCoP2UR3vcM5ZWmEBd8D", + "type": "message", + "role": "assistant", + "content": [PLACE_TOOL_USE], + "container": None, + "stop_reason": "tool_use", + "stop_sequence": None, + "stop_details": None, + "usage": { + "input_tokens": 528, + "cache_creation_input_tokens": 0, + "cache_read_input_tokens": 0, + "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 0}, + "output_tokens": 55, + "output_tokens_details": {"thinking_tokens": 0}, + "service_tier": "standard", + "inference_geo": "global", + "speed": "standard", + }, + "diagnostics": None, + }, + expected_litellm_response={ + "id": ANY, + "created": ANY, + "object": "chat.completion", + "model": "anthropic/claude-haiku-5-5", + "choices": [ + { + "finish_reason": "stop", + "index": 0, + "message": {"content": '{"city": "Paris", "country": "France"}', "role": "assistant"}, + } + ], + "usage": { + "completion_tokens": 55, + "prompt_tokens": 528, + "total_tokens": 583, + "completion_tokens_details": {"reasoning_tokens": 0, "text_tokens": 55}, + "prompt_tokens_details": { + "cached_tokens": 0, + "text_tokens": 528, + "cache_write_tokens": 0, + "cache_creation_tokens": 0, + "cache_creation_token_details": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 0}, + }, + "cache_creation_input_tokens": 0, + "cache_read_input_tokens": 0, + "inference_geo": "global", + "service_tier": "standard", + "speed": "standard", + }, + }, +) + +CLAUDE_HAIKU_5_5_JSON_SCHEMA_TOOL_NAMED_ENVELOPE_TEST_CASE: Final = replace( + CLAUDE_HAIKU_5_5_JSON_SCHEMA_TEST_CASE, + scenario="json_schema_tool_named_envelope", + mock_provider_response={ + **CLAUDE_HAIKU_5_5_JSON_SCHEMA_TEST_CASE.mock_provider_response, + "content": [ + { + **PLACE_TOOL_USE, + "input": {"name": "json_tool_call", "arguments": {"input": {"city": "Paris", "country": "France"}}}, + } + ], + }, +) + + +@pytest.mark.parametrize( + "case", + [CLAUDE_HAIKU_5_5_JSON_SCHEMA_TEST_CASE, CLAUDE_HAIKU_5_5_JSON_SCHEMA_TOOL_NAMED_ENVELOPE_TEST_CASE], + ids=lambda case: case.id, +) +def test_chat_completions_response_format_anthropic( + case: TranslationTestCase, gateway: Gateway, provider: SharedProvider +) -> None: + assert_translation(case, gateway, provider) diff --git a/tests/integration/translation/chat_completions/streaming/test_chat_completions_streaming_anthropic.py b/tests/integration/translation/chat_completions/streaming/test_chat_completions_streaming_anthropic.py index ccba51cff23..b2c0d39f9aa 100644 --- a/tests/integration/translation/chat_completions/streaming/test_chat_completions_streaming_anthropic.py +++ b/tests/integration/translation/chat_completions/streaming/test_chat_completions_streaming_anthropic.py @@ -5,8 +5,12 @@ import pytest from integration._support.client import Gateway from integration._support.provider import SharedProvider from integration.translation.case import SSEFrame, StreamingTranslationTestCase -from integration.translation.chat_completions.bases.anthropic import CLAUDE_SONNET_5_5_TEST_CASE +from integration.translation.chat_completions.bases.anthropic import ( + CLAUDE_HAIKU_5_5_TEST_CASE, + CLAUDE_SONNET_5_5_TEST_CASE, +) from integration.translation.runner import assert_streaming_translation +from pydantic import JsonValue CLAUDE_SONNET_5_5_STREAMING_TEST_CASE: Final = StreamingTranslationTestCase( scenario="streaming", @@ -128,7 +132,143 @@ CLAUDE_SONNET_5_5_STREAMING_TEST_CASE: Final = StreamingTranslationTestCase( ) -@pytest.mark.parametrize("case", [CLAUDE_SONNET_5_5_STREAMING_TEST_CASE], ids=lambda case: case.id) +PLACE_SCHEMA: Final = { + "type": "object", + "properties": {"city": {"type": "string"}, "country": {"type": "string"}}, + "required": ["city", "country"], + "additionalProperties": True, +} +PLACE_PROMPT: Final = "Which city is the capital of France? Answer as JSON with city and country." + + +def _place_delta(partial_json: str) -> SSEFrame: + return SSEFrame( + event="content_block_delta", + data={ + "type": "content_block_delta", + "index": 0, + "delta": {"type": "input_json_delta", "partial_json": partial_json}, + }, + ) + + +def _place_chunk(delta: dict[str, JsonValue], *, finish_reason: str | None = None) -> SSEFrame: + finish: Final = {} if finish_reason is None else {"finish_reason": finish_reason} + return SSEFrame( + data={ + "id": ANY, + "object": "chat.completion.chunk", + "created": ANY, + "model": "anthropic/claude-haiku-5-5", + "choices": [{"index": 0, "delta": delta, **finish}], + } + ) + + +CLAUDE_HAIKU_5_5_JSON_SCHEMA_CUT_STREAM_TEST_CASE: Final = StreamingTranslationTestCase( + scenario="json_schema_cut_stream", + litellm_endpoint=CLAUDE_HAIKU_5_5_TEST_CASE.litellm_endpoint, + litellm_request={ + "model": "anthropic/claude-haiku-5-5", + "max_tokens": 128, + "messages": [{"role": "user", "content": PLACE_PROMPT}], + "response_format": {"type": "json_schema", "json_schema": {"name": "place", "schema": PLACE_SCHEMA}}, + "cache": {"no-cache": True}, + "stream": True, + }, + expected_provider_endpoint=CLAUDE_HAIKU_5_5_TEST_CASE.expected_provider_endpoint, + expected_provider_headers=CLAUDE_HAIKU_5_5_TEST_CASE.expected_provider_headers, + expected_provider_request={ + "model": "claude-haiku-5-5", + "messages": [{"role": "user", "content": [{"type": "text", "text": PLACE_PROMPT}]}], + "max_tokens": 128, + "tool_choice": {"name": "json_tool_call", "type": "tool"}, + "tools": [{"name": "json_tool_call", "input_schema": PLACE_SCHEMA}], + "stream": True, + }, + mock_provider_frames=( + SSEFrame( + event="message_start", + data={ + "type": "message_start", + "message": { + "model": "claude-haiku-5-5", + "id": "msg_011CgCoP5RkexwE6N7PRZEca", + "type": "message", + "role": "assistant", + "content": [], + "container": None, + "stop_reason": None, + "stop_sequence": None, + "stop_details": None, + "usage": { + "input_tokens": 528, + "cache_creation_input_tokens": 0, + "cache_read_input_tokens": 0, + "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 0}, + "output_tokens": 16, + "service_tier": "standard", + "inference_geo": "global", + "speed": "standard", + }, + "diagnostics": None, + }, + }, + ), + SSEFrame( + event="content_block_start", + data={ + "type": "content_block_start", + "index": 0, + "content_block": { + "type": "tool_use", + "id": "toolu_01B4QSMQtft8TA3Rn6XFziWe", + "name": "json_tool_call", + "input": {}, + "caller": {"type": "direct"}, + }, + }, + ), + SSEFrame(event="ping", data={"type": "ping"}), + _place_delta(""), + _place_delta('{"city"'), + _place_delta(': "Pari'), + _place_delta('s"'), + _place_delta(', "coun'), + _place_delta('try": "'), + _place_delta('France"}'), + ), + expected_litellm_frames=( + _place_chunk({"role": "assistant", "content": '{"city": "Pari'}), + _place_chunk({"content": 's"'}), + _place_chunk({"content": ', "coun'}), + _place_chunk({"content": 'try": "'}), + _place_chunk({"content": 'France"'}), + _place_chunk({"content": "}"}), + _place_chunk({}, finish_reason="stop"), + SSEFrame(data="[DONE]"), + ), + expected_litellm_response={ + "id": ANY, + "object": "chat.completion", + "created": ANY, + "model": "anthropic/claude-haiku-5-5", + "choices": [ + { + "index": 0, + "message": {"role": "assistant", "content": '{"city": "Paris", "country": "France"}'}, + "finish_reason": "stop", + } + ], + }, +) + + +@pytest.mark.parametrize( + "case", + [CLAUDE_SONNET_5_5_STREAMING_TEST_CASE, CLAUDE_HAIKU_5_5_JSON_SCHEMA_CUT_STREAM_TEST_CASE], + ids=lambda case: case.id, +) def test_chat_completions_streaming_anthropic( case: StreamingTranslationTestCase, gateway: Gateway, provider: SharedProvider ) -> None: diff --git a/tests/test_litellm_rust/AGENTS.md b/tests/test_litellm_rust/AGENTS.md index ea661bc36f1..f688e2253e8 100644 --- a/tests/test_litellm_rust/AGENTS.md +++ b/tests/test_litellm_rust/AGENTS.md @@ -1,27 +1,62 @@ -# Invariants +# Scope -- This directory tests the Rust path and nothing else. Treat the Python implementation of every route as already removed. Never call it on purpose, never run one request through both engines, and never compare Python and Rust outputs, headers, cache keys or logs -- A test that would still pass with Python serving the call does not belong here. Every test asserts the call was served natively with `support.routing.assert_served_natively` -- Select the Rust path with `support.routing.native_route(...)`, which prepends `RUST_REQUIRED` rules to `catalog.RULES` and restores them on exit. Each route folder's `conftest.py` applies it to every test through an autouse fixture. A test outside a route folder wraps its whole body in one `native_route(...)` block, and a child interpreter script assigns `catalog.RULES` once at its top. Never select a backend by reading or setting `LITELLM_RUST`, calling `litellm.rust(...)` or rebinding `catalog.RULES` any other way. The rollout in `litellm/rust_bridge/catalog.py` is a product decision, and a test here must pass no matter what it says, including for a route marked `PYTHON_ONLY` -- `catalog.RULES` is static at runtime and `native_route(...)` swaps a module global, so open it once per test and never per call. Two overlapping blocks, such as one per task inside an `asyncio.gather`, restore out of order and leave the wrong rules behind for later tests -- A test whose subject is the rollout switch itself (env, `litellm.rust(...)`, catalog rules) is a unit test of `litellm/rust_bridge/configuration.py` or `catalog.py` and lives in `tests/unit/rust_bridge/` -- A test lives here only when it cannot be written in Rust. That means it needs the Python public API, Python-owned state such as `litellm.cache` and callbacks, or the process boundary (fork, threads, event loops). Anything checkable from the Rust side goes in the crate's own tests +- This directory tests the Rust path end to end through the Python public API, plus the dispatch tests below, and nothing else +- A test belongs here only when it cannot be written in Rust, meaning it needs + - the Python public API + - Python-owned state such as `litellm.cache` and callbacks + - the process boundary (fork, threads, event loops) +- Anything checkable from the Rust side goes in the crate's own tests - The wire is the local recording server. No test here reaches a real provider -- Never parametrize one test across routes. Each route folder owns its tests, its `server` fixture, its request data and its `call` -- Call `_native` directly only for a case the public API cannot reach + +# Rust only + +- Outside the dispatch tests, treat every route's Python implementation as already removed + - never call it on purpose + - never run one request through both engines + - never compare Python and Rust outputs, headers, cache keys or logs +- A test that would still pass with Python serving the call does not belong here +- Every test except the dispatch tests asserts native serving with `support.routing.assert_served_natively` + +# Dispatch tests + +- They check which path a public call takes under given rules + - each route folder's `test_dispatch.py` + - `test_dispatch.py` at the top, which tests `PublicDispatch` with stub routes + - `test_public_entries.py` at the top, which runs every route's public call forms through one table +- They pass `rules=` to a dispatch directly or wrap the whole test in one `support.routing.routed(...)` block, and they stub the native bindings +- They may call Python, since the choice between the two paths is what they test +- They live here until they can run in `tests/unit/` without the compiled extension + +# Selecting a path + +- Use `support.routing.native_route(...)`, which prepends `RUST_REQUIRED` rules to `catalog.RULES` and restores them on exit + - route folders apply it to every test through the autouse fixture in their `conftest.py` + - a test outside a route folder wraps its whole body in one `native_route(...)` block + - a child interpreter script assigns `catalog.RULES` once at its top +- Dispatch tests use `support.routing.routed(...)` instead, which sets `catalog.RULES` to exactly the rules given +- Open either once per test, never per call. They swap a module global, so overlapping blocks (one per task in an `asyncio.gather`) restore out of order and leak rules into later tests +- Never select a backend through `LITELLM_RUST`, `litellm.rust(...)` or any other rebinding of `catalog.RULES` +- No test here depends on the rollout switch + - only no rule, `PYTHON_ONLY` and `RUST_REQUIRED` pick a path without it, so those are the only rollouts used here + - Rust with Python fallback needs the switch, so it is not reachable from this directory + - what `LITELLM_RUST` and `litellm.rust(...)` mean is tested in `tests/unit/rust_bridge/test_configuration.py`, mostly through `decide`, which takes both as plain values +- Tests pass whatever the shipped rollout in `litellm/rust_bridge/catalog.py` says, including for a `PYTHON_ONLY` route # Layout -Each route folder (`ocr/`, `messages/`, `responses/`, `chat_completions/`) uses the same file names, one concern per file - -- `test_dispatch.py` the call reaches the native route -- `test_requests.py` Python inputs that reach the wire -- `test_failures.py` errors raised to the caller and rejection before provider IO -- `test_settings.py` globals, env, named credentials and their precedence -- `test_streaming.py` stream relay, early close and stream-time logging -- `test_callbacks.py` the logger hook contract -- `test_body_hooks.py` handler body hooks such as interceptors and agentic loops -- `test_lifecycle.py` cancellation, concurrency, context and nested calls -- `test_cache.py` the configured cache seen from this route - -Route data and the route's `call` live in `/data.py`, and `/conftest.py` owns the `server` fixture and the autouse `native` fixture. `support/` holds only route-neutral helpers +- One folder per route (`ocr/`, `messages/`, `responses/`, `chat_completions/`), all using the same file names + - `test_dispatch.py` which path the rules pick for each public call, and that the call reaches the native route + - `test_requests.py` Python inputs that reach the wire + - `test_failures.py` errors raised to the caller and rejection before provider IO + - `test_settings.py` globals, env, named credentials and their precedence + - `test_streaming.py` stream relay, early close and stream-time logging + - `test_callbacks.py` the logger hook contract + - `test_body_hooks.py` handler body hooks such as interceptors and agentic loops + - `test_lifecycle.py` cancellation, concurrency, context and nested calls + - `test_cache.py` the configured cache seen from this route +- `embeddings/` holds only `test_dispatch.py` so far +- `/data.py` holds the route's request data and its `call` +- `/conftest.py` owns the `server` fixture and the autouse `native` fixture +- `support/` holds only route-neutral helpers +- Never parametrize one test across routes, except in `test_public_entries.py`, whose subject is that every route serves its public call forms the same way +- Call `_native` directly only for a case the public API cannot reach diff --git a/tests/test_litellm_rust/chat_completions/test_dispatch.py b/tests/test_litellm_rust/chat_completions/test_dispatch.py index 4ed75ea5f95..69d9e8e12df 100644 --- a/tests/test_litellm_rust/chat_completions/test_dispatch.py +++ b/tests/test_litellm_rust/chat_completions/test_dispatch.py @@ -4,14 +4,15 @@ from typing import Final, cast # noqa: TID251 # narrows legacy callable signat import pytest import litellm +from litellm.caching.caching import Cache from litellm.chat_completions import dispatch from litellm.chat_completions.dispatch import ( _ADISPATCH, # pyright: ignore[reportPrivateUsage] # tests configured dispatch _DISPATCH, # pyright: ignore[reportPrivateUsage] # tests configured dispatch ) -from litellm.rust_bridge import catalog +from litellm.integrations.custom_logger import CustomLogger from litellm.rust_bridge.bindings import NativeBinding -from litellm.rust_bridge.catalog import Route, RouteRule, Rules +from litellm.rust_bridge.catalog import Feature, Route, RouteRule, Rules from litellm.rust_bridge.chat_completions.entrypoints import ( NATIVE_ACOMPLETION, NATIVE_COMPLETION, @@ -147,29 +148,6 @@ def test_native_receives_bound_request_and_original_call_shape() -> None: assert call_kwargs["metadata"] is metadata -def test_internal_async_marker_bypasses_native() -> None: - response: Final = ModelResponse() - called: Final[list[bool]] = [] - - def python(*call_args: object, **call_kwargs: object) -> ModelResponse: # kwargs-ok: records public call shape - called.append(True) - return response - - def native(request: NativeCall) -> ModelResponse: - pytest.fail("acompletion's inner completion call must stay on Python") - - result: Final = _DISPATCH.run( - ("gpt-4o", MESSAGES), - {"acompletion": True}, - python=python, - binding=completion_binding(native), - native=native_call_hook, - rules=RUST_RULES, - ) - assert result is response - assert called == [True] - - @pytest.mark.parametrize( ("args", "kwargs"), ( @@ -202,56 +180,6 @@ def test_binding_errors_delegate_to_python(args: tuple[object, ...], kwargs: Map assert captured == [(args, kwargs)] -def test_public_completion_routes_through_dispatch(monkeypatch: pytest.MonkeyPatch) -> None: - captured: Final[list[NativeCall]] = [] - expected: Final = ModelResponse() - - def native(request: NativeCall) -> ModelResponse: - captured.append(request) - return expected - - NATIVE_COMPLETION.override(native) - monkeypatch.setattr(catalog, "RULES", RUST_RULES) - public_completion: Final = cast(Callable[..., ModelResponse], litellm.completion) - try: - result: Final = public_completion(model="gpt-4o", messages=MESSAGES) - finally: - NATIVE_COMPLETION.reset() - assert result is expected - assert [request.resolved["model"] for request in captured] == ["gpt-4o"] - - -@pytest.mark.asyncio -async def test_public_acompletion_routes_through_dispatch(monkeypatch: pytest.MonkeyPatch) -> None: - captured: Final[list[NativeCall]] = [] - expected: Final = ModelResponse() - - async def native(request: NativeCall) -> ModelResponse: - captured.append(request) - return expected - - NATIVE_ACOMPLETION.override(native) - monkeypatch.setattr(catalog, "RULES", RUST_RULES) - public_acompletion: Final = cast(Callable[..., Awaitable[ModelResponse]], litellm.acompletion) - try: - result: Final = await public_acompletion(model="gpt-4o", messages=MESSAGES) - finally: - NATIVE_ACOMPLETION.reset() - assert result is expected - assert [request.resolved["model"] for request in captured] == ["gpt-4o"] - - -@pytest.mark.asyncio -async def test_public_completion_calls_keep_the_python_result() -> None: - sync_response: Final = litellm.completion(model="openai/test-model", messages=MESSAGES, mock_response="ok") - async_response: Final = await litellm.acompletion(model="openai/test-model", messages=MESSAGES, mock_response="ok") - - assert isinstance(sync_response, ModelResponse) - assert isinstance(async_response, ModelResponse) - assert sync_response.choices[0].message.content == "ok" - assert async_response.choices[0].message.content == "ok" - - def test_sync_completion_request_projects_public_arguments() -> None: rules: Final[Rules] = (RouteRule(Route.CHAT_COMPLETIONS, Rollout.RUST_REQUIRED),) expected: Final = ModelResponse() @@ -277,64 +205,133 @@ def test_sync_completion_request_projects_public_arguments() -> None: assert response is expected -@pytest.mark.asyncio -async def test_async_completion_falls_back_after_native_declines() -> None: - from litellm.rust_bridge.bindings import native_exception_types - - native_types: Final = native_exception_types() - if native_types is None: - pytest.skip("native bridge is unavailable") - declined, _ = native_types - expected: Final = ModelResponse() - rules: Final[Rules] = (RouteRule(Route.CHAT_COMPLETIONS, Rollout.RUST_OPT_OUT),) - - async def native(request: NativeCall) -> ModelResponse: - raise declined("unsupported") - - async def python(*args: object, **kwargs: object) -> ModelResponse: - return expected - - binding: Final[NativeBinding[NativeAcompletion]] = NativeBinding("acompletion", validate=lambda _: None) - binding.override(native) - response: Final = await dispatch._ADISPATCH.arun( # pyright: ignore[reportPrivateUsage] # test an explicit route decision - ("test-model", MESSAGES), - {}, - python=python, - binding=binding, - native=native_call_hook, - rules=rules, - ) - - assert response is expected - - -def test_internal_acompletion_marker_bypasses_native() -> None: - rules: Final[Rules] = (RouteRule(Route.CHAT_COMPLETIONS, Rollout.RUST_REQUIRED),) - expected: Final = ModelResponse() - - def python(*args: object, **kwargs: object) -> ModelResponse: - return expected - - def native(request: NativeCall) -> ModelResponse: - pytest.fail("acompletion's inner completion call must stay on Python") - - binding: Final[NativeBinding[NativeCompletion]] = NativeBinding("completion", validate=lambda _: None) - binding.override(native) - response: Final = dispatch._DISPATCH.run( # pyright: ignore[reportPrivateUsage] # test an explicit route decision - ("test-model", MESSAGES), - {"custom_llm_provider": "openai", "acompletion": True}, - python=python, - binding=binding, - native=native_call_hook, - rules=rules, - ) - - assert response is expected - - def test_positional_parameters_remain_available_to_native_projection() -> None: request: Final = _DISPATCH.request(("anthropic/test-model", MESSAGES, 12.0, 0.25), {}) assert request is not None assert request.resolved["timeout"] == 12.0 assert request.resolved["temperature"] == 0.25 assert request.resolved["messages"] is MESSAGES + + +@pytest.mark.asyncio +async def test_acompletion_marker_binds_positionals_by_the_sync_signature() -> None: + captured: Final[list[NativeCall]] = [] + + async def native(call: NativeCall) -> ModelResponse: + captured.append(call) + return ModelResponse() + + NATIVE_ACOMPLETION.override(native) + public_completion: Final = cast(Callable[..., Awaitable[ModelResponse]], litellm.completion) + try: + _ = await public_completion("gpt-4o", MESSAGES, 30.0, acompletion=True) + finally: + NATIVE_ACOMPLETION.reset() + assert [(request.resolved["timeout"], request.resolved["functions"]) for request in captured] == [(30.0, None)] + + +class _ChatAgentic(CustomLogger): + async def async_should_run_chat_completion_agentic_loop( + self, *args: object, **kwargs: object + ) -> tuple[bool, dict[str, object]]: # pyright: ignore[reportIncompatibleMethodOverride] # test double only needs the override + return False, {} + + +@pytest.mark.parametrize( + ("feature", "kwargs", "settings"), + ( + (Feature.MOCK_RESPONSE, {"mock_response": "hi"}, {}), + pytest.param(Feature.MOCK_RESPONSE, {"mock_tool_calls": [{"id": "call_1"}]}, {}, id="mock-tool-calls"), + pytest.param(Feature.MOCK_RESPONSE, {"mock_timeout": True}, {}, id="mock-timeout"), + (Feature.CALLER_CLIENT, {"client": object()}, {}), + (Feature.TIMEOUT_VARIANTS, {"request_timeout": 5}, {}), + (Feature.AGENTIC_LOOP_HOOK, {}, {"callbacks": [_ChatAgentic()]}), + (Feature.TLS_POLICY, {}, {"ssl_security_level": "DEFAULT@SECLEVEL=1"}), + (Feature.RESPONSE_CACHE, {}, {"cache": Cache()}), + (Feature.STREAMING, {"stream": True}, {}), + (Feature.DROP_PARAMS, {}, {"drop_params": True}), + (Feature.MODIFY_PARAMS, {}, {"modify_params": True}), + (Feature.EXTRA_BODY, {"extra_body": {"top_k": 1}}, {}), + (Feature.RETRIES_FALLBACKS, {"num_retries": 2}, {}), + pytest.param( + Feature.RETRIES_FALLBACKS, + {"context_window_fallback_dict": {"anthropic/claude-sonnet-4-5": "anthropic/claude-opus-4-5"}}, + {}, + id="context-window-fallbacks", + ), + pytest.param( + Feature.RETRIES_FALLBACKS, + {}, + {"model_fallbacks": [{"anthropic/claude-sonnet-4-5": ["anthropic/claude-opus-4-5"]}]}, + id="model-fallbacks", + ), + (Feature.PROMPT_MANAGEMENT, {"prompt_id": "welcome"}, {}), + pytest.param(Feature.PROMPT_MANAGEMENT, {"model": "litellm_agent/gpt-5"}, {}, id="litellm-agent-model"), + (Feature.CACHE_CONTROL_INJECTION, {"enable_prompt_caching": True}, {}), + (Feature.MODEL_PARAM_GATING, {"logit_bias": {"1": 1}}, {}), + ( + Feature.MODEL_LIST, + {"model_list": [{"model_name": "anthropic/claude-sonnet-4-5", "litellm_params": {"model": "gpt-5"}}]}, + {}, + ), + ( + Feature.MODEL_ALIAS_MAP, + {}, + {"model_alias_map": {"anthropic/claude-sonnet-4-5": "anthropic/claude-opus-4-5"}}, + ), + ), +) +def test_each_detected_feature_reaches_its_rule( + monkeypatch: pytest.MonkeyPatch, feature: Feature, kwargs: Mapping[str, object], settings: Mapping[str, object] +) -> None: + rules: Final = ( + RouteRule(Route.CHAT_COMPLETIONS, Rollout.PYTHON_ONLY, features=frozenset({feature})), + RouteRule(Route.CHAT_COMPLETIONS, Rollout.RUST_REQUIRED), + ) + python_result: Final = ModelResponse() + native_result: Final = ModelResponse() + + def served(call_kwargs: Mapping[str, object]) -> object: + return _DISPATCH.run( + (), + {"model": "anthropic/claude-sonnet-4-5", "messages": MESSAGES, **call_kwargs}, + python=lambda *call_args, **python_kwargs: python_result, + binding=completion_binding(lambda request: native_result), + native=native_call_hook, + rules=rules, + ) + + monkeypatch.setattr(litellm, "callbacks", []) + monkeypatch.setattr(litellm, "ssl_security_level", None) + monkeypatch.setattr(litellm, "cache", None) + monkeypatch.setattr(litellm, "model_alias_map", {}) + for name in ("num_retries", "model_fallbacks"): + monkeypatch.setattr(litellm, name, None) + for name in ("drop_params", "modify_params", "enable_anthropic_prompt_caching"): + monkeypatch.setattr(litellm, name, False) + for name in ("SSL_SECURITY_LEVEL", "SSL_ECDH_CURVE"): + monkeypatch.delenv(name, raising=False) + assert served({}) is native_result + for name, value in settings.items(): + monkeypatch.setattr(litellm, name, value) + assert served(kwargs) is python_result + + +def test_acompletion_flag_hands_off_only_when_true() -> None: + expected: Final = ModelResponse() + + def native(call: NativeCall) -> ModelResponse: + return expected + + async def anative(call: NativeCall) -> ModelResponse: + pytest.fail("completion(..., acompletion=1) stays sync, since the Python @client only hands off on is True") + + NATIVE_COMPLETION.override(native) + NATIVE_ACOMPLETION.override(anative) + public_completion: Final = cast(Callable[..., object], litellm.completion) + try: + result: Final = public_completion("gpt-4o", MESSAGES, acompletion=1) + finally: + NATIVE_COMPLETION.reset() + NATIVE_ACOMPLETION.reset() + assert result is expected diff --git a/tests/test_litellm_rust/embeddings/test_dispatch.py b/tests/test_litellm_rust/embeddings/test_dispatch.py index 750c88cd235..fbebf1c64e4 100644 --- a/tests/test_litellm_rust/embeddings/test_dispatch.py +++ b/tests/test_litellm_rust/embeddings/test_dispatch.py @@ -1,12 +1,10 @@ from __future__ import annotations -from collections.abc import Awaitable, Callable +from collections.abc import Callable from typing import Final import pytest -from pydantic import TypeAdapter -import litellm from litellm.embeddings import dispatch from litellm.rust_bridge.bindings import NativeBinding from litellm.rust_bridge.catalog import Route, RouteRule, Rules @@ -15,19 +13,6 @@ from litellm.rust_bridge.public_call import NativeCall, native_call_hook from litellm.types.utils import EmbeddingResponse -@pytest.mark.asyncio -async def test_public_embedding_calls_keep_the_python_result() -> None: - vector: Final = [0.1, 0.2] - - sync_response: Final = litellm.embedding(model="openai/test-model", input="hello", mock_response=vector) - async_response: Final = await litellm.aembedding(model="openai/test-model", input="hello", mock_response=vector) - - assert isinstance(sync_response, EmbeddingResponse) - rows: Final = TypeAdapter(list[dict[str, object]]) - assert rows.validate_python(sync_response.model_dump()["data"])[0]["embedding"] == vector - assert rows.validate_python(async_response.model_dump()["data"])[0]["embedding"] == vector - - def test_sync_embedding_request_projects_public_arguments() -> None: rules: Final[Rules] = (RouteRule(Route.EMBEDDINGS, Rollout.RUST_REQUIRED),) expected: Final = EmbeddingResponse(model="test-model", data=[]) @@ -52,36 +37,3 @@ def test_sync_embedding_request_projects_public_arguments() -> None: ) assert response is expected - - -@pytest.mark.asyncio -async def test_async_embedding_falls_back_after_native_declines() -> None: - from litellm.rust_bridge.bindings import native_exception_types - - native_types: Final = native_exception_types() - if native_types is None: - pytest.skip("native bridge is unavailable") - declined, _ = native_types - expected: Final = EmbeddingResponse(model="test-model", data=[]) - rules: Final[Rules] = (RouteRule(Route.EMBEDDINGS, Rollout.RUST_OPT_OUT),) - - async def native(request: NativeCall) -> EmbeddingResponse: - raise declined("unsupported") - - async def python(*args: object, **kwargs: object) -> EmbeddingResponse: - return expected - - binding: Final[NativeBinding[Callable[[NativeCall], Awaitable[EmbeddingResponse]]]] = NativeBinding( - "aembedding", validate=lambda _: None - ) - binding.override(native) - response: Final = await dispatch._ADISPATCH.arun( # pyright: ignore[reportPrivateUsage] # test an explicit route decision - ("test-model", "hello"), - {}, - python=python, - binding=binding, - native=native_call_hook, - rules=rules, - ) - - assert response is expected diff --git a/tests/test_litellm_rust/messages/test_callbacks.py b/tests/test_litellm_rust/messages/test_callbacks.py index e8d49453065..cd5478dfc3a 100644 --- a/tests/test_litellm_rust/messages/test_callbacks.py +++ b/tests/test_litellm_rust/messages/test_callbacks.py @@ -67,7 +67,7 @@ async def test_success_hook_fires_the_expected_number_of_times( pytest.param("async_log_failure_event", 1), pytest.param("async_post_call_failure_deployment_hook", 1), pytest.param("log_model_group_rate_limit_error", 1), - pytest.param("log_failure_event", 0, marks=SYNC_HANDLERS_ON_ASYNC_CALLS), + pytest.param("log_failure_event", 0), ), ) async def test_failure_hook_fires_the_expected_number_of_times( diff --git a/tests/test_litellm_rust/messages/test_dispatch.py b/tests/test_litellm_rust/messages/test_dispatch.py index 2a32e31c250..50f71569d73 100644 --- a/tests/test_litellm_rust/messages/test_dispatch.py +++ b/tests/test_litellm_rust/messages/test_dispatch.py @@ -3,9 +3,11 @@ from collections.abc import Awaitable, Callable, Mapping from typing import Final, cast # noqa: TID251 # narrows legacy callable signatures for inspect import pytest -from pydantic import TypeAdapter import litellm +from litellm.caching.caching import Cache +from litellm.integrations.custom_logger import CustomLogger +from litellm.integrations.websearch_interception.handler import WebSearchInterceptionLogger from litellm.llms.anthropic.pass_through.messages import handler as python_messages from litellm.messages import dispatch from litellm.messages.dispatch import ( @@ -13,17 +15,15 @@ from litellm.messages.dispatch import ( _DISPATCH, # pyright: ignore[reportPrivateUsage] # tests configured dispatch ) from litellm.proxy import proxy_server -from litellm.rust_bridge import catalog from litellm.rust_bridge.bindings import NativeBinding -from litellm.rust_bridge.catalog import Route, RouteRule, Rules +from litellm.rust_bridge.catalog import Feature, Route, RouteRule, Rules, Target from litellm.rust_bridge.configuration import Rollout from litellm.rust_bridge.messages.entrypoints import NATIVE_AMESSAGES, NATIVE_MESSAGES, NativeAmessages, NativeMessages from litellm.rust_bridge.public_call import NativeCall +from litellm.types.llms.anthropic import ANTHROPIC_ADVISOR_TOOL_TYPE from litellm.types.llms.anthropic_messages.anthropic_response import AnthropicMessagesResponse MESSAGES: Final = [{"role": "user", "content": "hi"}] -DANGEROUS_TOOL_USE: Final = [{"type": "dangerous_tool_use", "classifier_context": {"permission_mode": "auto"}}] -CLASSIFIER_SETTINGS: Final = {"safeguards_classifier_model": "gpt-oss-120b"} PYTHON_RULES: Final[Rules] = () RUST_RULES: Final[Rules] = (RouteRule(Route.MESSAGES, Rollout.RUST_REQUIRED),) @@ -194,81 +194,44 @@ def test_native_streams_are_bounded_by_stream_timeout(stream: bool, expected_tim assert captured[0].resolved["timeout"] == expected_timeout -def test_internal_async_marker_bypasses_native() -> None: - args: Final[tuple[object, ...]] = (16, MESSAGES, "claude-sonnet-4-5") - kwargs: Final[Mapping[str, object]] = {"is_async": True} - captured: Final[list[tuple[tuple[object, ...], Mapping[str, object]]]] = [] - expected: Final = response() - - def python(*call_args: object, **call_kwargs: object) -> AnthropicMessagesResponse: # kwargs-ok: records call shape - captured.append((call_args, call_kwargs)) - return expected - - def native( - request: NativeCall, - ) -> AnthropicMessagesResponse: - pytest.fail("The async handler's inner sync call must stay on Python") - - result: Final = _DISPATCH.run( - args, - kwargs, - python=python, - binding=messages_binding(native), - native=lambda hook, request, call_args, call_kwargs: hook(request), - rules=RUST_RULES, - ) - assert result is expected - assert captured == [(args, kwargs)] - - @pytest.mark.parametrize( - ("model", "custom_llm_provider"), - [ - ("vertex_ai/gemini-2.5-pro", None), - ("gemini-2.5-pro", "vertex_ai"), - ], + ("model", "kwargs", "passes_through"), + ( + ("vertex_ai/claude-sonnet-4-5@20250929", {}, True), + ("claude-sonnet-4-5@20250929", {"custom_llm_provider": "vertex_ai"}, True), + ("deepseek/deepseek-v4-flash", {}, True), + ("openai/gpt-5", {"model_info": {"supported_endpoints": ["/v1/messages"]}}, True), + ("vertex_ai/gemini-2.5-pro", {}, False), + ("gemini-2.5-pro", {"custom_llm_provider": "vertex_ai"}, False), + ("openai/gpt-5", {}, False), + ("groq/llama-3.3-70b-versatile", {}, False), + ("unknown-provider/unknown-model", {}, False), + ), ) -def test_vertex_models_other_than_claude_stay_on_python(model: str, custom_llm_provider: str | None) -> None: - args: Final[tuple[object, ...]] = (16, MESSAGES, model) - kwargs: Final[Mapping[str, object]] = {"custom_llm_provider": custom_llm_provider} - expected: Final = response(model) +def test_only_requests_that_pass_through_to_a_messages_api_reach_a_messages_target_rule( + model: str, kwargs: Mapping[str, object], passes_through: bool +) -> None: + python_result: Final = response(model) + native_result: Final = response(model) - def python(*call_args: object, **call_kwargs: object) -> AnthropicMessagesResponse: # kwargs-ok: records call shape - return expected - - def native(request: NativeCall) -> AnthropicMessagesResponse: - pytest.fail("Rust serves only Claude on Vertex AI") + def python(*call_args: object, **call_kwargs: object) -> AnthropicMessagesResponse: # kwargs-ok: fallback + return python_result result: Final = _DISPATCH.run( - args, + (16, MESSAGES, model), kwargs, python=python, - binding=messages_binding(native), + binding=messages_binding(lambda request: native_result), native=lambda hook, request, call_args, call_kwargs: hook(request), - rules=RUST_RULES, + rules=(RouteRule(Route.MESSAGES, Rollout.RUST_REQUIRED, targets=frozenset({Target.MESSAGES})),), ) - assert result is expected + assert result is (native_result if passes_through else python_result) -def test_vertex_claude_reaches_native() -> None: - args: Final[tuple[object, ...]] = (16, MESSAGES, "vertex_ai/claude-sonnet-4-5@20250929") - expected: Final = response("vertex_ai/claude-sonnet-4-5@20250929") - - def python(*call_args: object, **call_kwargs: object) -> AnthropicMessagesResponse: # kwargs-ok: records call shape - pytest.fail("Claude on Vertex AI is served natively") - - result: Final = _DISPATCH.run( - args, - {}, - python=python, - binding=messages_binding(lambda request: expected), - native=lambda hook, request, call_args, call_kwargs: hook(request), - rules=RUST_RULES, - ) - assert result is expected +DANGEROUS_TOOL_USE: Final = [{"type": "dangerous_tool_use", "classifier_context": {"permission_mode": "auto"}}] +CLASSIFIER_SETTINGS: Final = {"safeguards_classifier_model": "gpt-oss-120b"} -@pytest.mark.asyncio @pytest.mark.parametrize( ("model", "kwargs", "general_settings", "serves_python"), ( @@ -285,7 +248,7 @@ def test_vertex_claude_reaches_native() -> None: ("anthropic/claude-sonnet-4-5", {"safeguards": DANGEROUS_TOOL_USE}, CLASSIFIER_SETTINGS, False), ), ) -async def test_python_keeps_the_requests_it_answers_with_safeguard_results( +def test_proxy_classified_safeguards_reach_the_feature_rule( monkeypatch: pytest.MonkeyPatch, model: str, kwargs: Mapping[str, object], @@ -296,19 +259,19 @@ async def test_python_keeps_the_requests_it_answers_with_safeguard_results( python_result: Final = response(model) native_result: Final = response(model) - async def python(*call_args: object, **call_kwargs: object) -> AnthropicMessagesResponse: # kwargs-ok: fallback + def python(*call_args: object, **call_kwargs: object) -> AnthropicMessagesResponse: # kwargs-ok: fallback return python_result - async def native(request: NativeCall) -> AnthropicMessagesResponse: - return native_result - - result: Final = await _ADISPATCH.arun( + result: Final = _DISPATCH.run( (16, MESSAGES, model), kwargs, python=python, - binding=amessages_binding(native), + binding=messages_binding(lambda request: native_result), native=lambda hook, request, call_args, call_kwargs: hook(request), - rules=RUST_RULES, + rules=( + RouteRule(Route.MESSAGES, Rollout.PYTHON_ONLY, features=frozenset({Feature.SAFEGUARDS_CLASSIFIER})), + RouteRule(Route.MESSAGES, Rollout.RUST_REQUIRED), + ), ) assert result is (python_result if serves_python else native_result) @@ -345,7 +308,7 @@ def test_binding_errors_delegate_to_python(args: tuple[object, ...], kwargs: Map assert captured == [(args, kwargs)] -def test_anthropic_create_routes_through_dispatch(monkeypatch: pytest.MonkeyPatch) -> None: +def test_anthropic_create_routes_through_dispatch() -> None: captured: Final[list[NativeCall]] = [] expected: Final = response() @@ -356,7 +319,6 @@ def test_anthropic_create_routes_through_dispatch(monkeypatch: pytest.MonkeyPatc return expected NATIVE_MESSAGES.override(native) - monkeypatch.setattr(catalog, "RULES", RUST_RULES) public_create: Final = cast(Callable[..., AnthropicMessagesResponse], litellm.anthropic.create) try: result: Final = public_create(max_tokens=16, messages=MESSAGES, model="claude-sonnet-4-5") @@ -367,7 +329,7 @@ def test_anthropic_create_routes_through_dispatch(monkeypatch: pytest.MonkeyPatc @pytest.mark.asyncio -async def test_anthropic_acreate_routes_through_dispatch(monkeypatch: pytest.MonkeyPatch) -> None: +async def test_anthropic_acreate_routes_through_dispatch() -> None: captured: Final[list[NativeCall]] = [] expected: Final = response() @@ -378,7 +340,6 @@ async def test_anthropic_acreate_routes_through_dispatch(monkeypatch: pytest.Mon return expected NATIVE_AMESSAGES.override(native) - monkeypatch.setattr(catalog, "RULES", RUST_RULES) public_acreate: Final = cast(Callable[..., Awaitable[AnthropicMessagesResponse]], litellm.anthropic.acreate) try: result: Final = await public_acreate(max_tokens=16, messages=MESSAGES, model="claude-sonnet-4-5") @@ -389,14 +350,31 @@ async def test_anthropic_acreate_routes_through_dispatch(monkeypatch: pytest.Mon @pytest.mark.asyncio -async def test_public_anthropic_messages_keeps_the_python_result() -> None: - response: Final = await litellm.anthropic_messages( - model="anthropic/claude-sonnet-4-5", messages=MESSAGES, max_tokens=10, mock_response="ok" - ) +async def test_truthy_is_async_hands_off_to_the_async_entry_like_true() -> None: + captured: Final[list[NativeCall]] = [] + expected: Final = response() - assert isinstance(response, dict) - content: Final = TypeAdapter(list[dict[str, object]]).validate_python(response.get("content", [])) - assert content[0]["text"] == "ok" + async def native(request: NativeCall) -> AnthropicMessagesResponse: + captured.append(request) + return expected + + def sync_native(request: NativeCall) -> AnthropicMessagesResponse: + pytest.fail("a truthy is_async must hand off to the async entry, as the Python handler does") + + NATIVE_AMESSAGES.override(native) + NATIVE_MESSAGES.override(sync_native) + public_create: Final = cast(Callable[..., object], litellm.anthropic.create) + try: + pending: Final = public_create(max_tokens=16, messages=MESSAGES, model="claude-sonnet-4-5", is_async=1) + assert inspect.isawaitable(pending) + assert await pending is expected + reference: Final = public_create(max_tokens=16, messages=MESSAGES, model="claude-sonnet-4-5", is_async=True) + assert inspect.isawaitable(reference) + assert await reference is expected + finally: + NATIVE_AMESSAGES.reset() + NATIVE_MESSAGES.reset() + assert [dict(request.resolved) for request in captured] == [dict(captured[1].resolved)] * 2 def test_sync_messages_request_projects_public_arguments() -> None: @@ -453,62 +431,173 @@ def test_messages_binding_error_delegates_unchanged_to_python() -> None: assert response is expected -@pytest.mark.asyncio -async def test_async_messages_falls_back_after_native_declines() -> None: - from litellm.rust_bridge.bindings import native_exception_types +class _Rewrite(CustomLogger): + async def async_pre_request_hook(self, model: str, messages: list, kwargs: dict) -> dict | None: # pyright: ignore[reportMissingTypeArgument] # mirrors the CustomLogger signature + return kwargs - native_types: Final = native_exception_types() - if native_types is None: - pytest.skip("native bridge is unavailable") - declined, _ = native_types - expected: Final = AnthropicMessagesResponse(model="claude-test") - rules: Final[Rules] = (RouteRule(Route.MESSAGES, Rollout.RUST_OPT_OUT),) + +class _Agentic(CustomLogger): + async def async_should_run_agentic_loop(self, *args: object, **kwargs: object) -> tuple[bool, dict]: # pyright: ignore[reportIncompatibleMethodOverride, reportMissingTypeArgument] # test double only needs the override + return False, {} + + +ADVISOR_TOOL: Final = {"type": ANTHROPIC_ADVISOR_TOOL_TYPE, "name": "advisor", "model": "claude-opus-5-5"} + + +@pytest.mark.parametrize( + ("feature", "model", "kwargs", "settings"), + ( + (Feature.MOCK_RESPONSE, "anthropic/claude-sonnet-4-5", {"mock_response": "hi"}, {}), + ( + Feature.PROXY_MCP_TOOLS, + "anthropic/claude-sonnet-4-5", + {"tools": [{"type": "mcp", "server_label": "gateway", "server_url": "litellm_proxy"}]}, + {}, + ), + (Feature.CALLER_CLIENT, "anthropic/claude-sonnet-4-5", {"client": object()}, {}), + (Feature.TIMEOUT_VARIANTS, "anthropic/claude-sonnet-4-5", {"request_timeout": 5}, {}), + (Feature.AGENTIC_LOOP_HOOK, "anthropic/claude-sonnet-4-5", {}, {"callbacks": [_Agentic()]}), + (Feature.RESPONSE_CACHE, "anthropic/claude-sonnet-4-5", {}, {"cache": Cache()}), + (Feature.TLS_POLICY, "anthropic/claude-sonnet-4-5", {}, {"ssl_security_level": "DEFAULT@SECLEVEL=1"}), + (Feature.MODIFY_PARAMS, "anthropic/claude-sonnet-4-5", {}, {"modify_params": True}), + ( + Feature.WORKLOAD_IDENTITY, + "anthropic/claude-sonnet-4-5", + {"anthropic_federation_rule_id": "rule-1", "anthropic_organization_id": "org-1"}, + {}, + ), + (Feature.CACHE_CONTROL_INJECTION, "anthropic/claude-sonnet-4-5", {"enable_prompt_caching": True}, {}), + ( + Feature.THINKING_SIGNATURE_RETRY, + "anthropic/claude-sonnet-4-5", + {"messages": [{"role": "assistant", "content": [{"type": "redacted_thinking", "data": "x"}]}]}, + {}, + ), + ( + Feature.STREAM_COST_INJECTION, + "anthropic/claude-sonnet-4-5", + {"stream": True}, + {"include_cost_in_streaming_usage": True}, + ), + ), +) +def test_each_detected_feature_reaches_its_rule( + monkeypatch: pytest.MonkeyPatch, + feature: Feature, + model: str, + kwargs: Mapping[str, object], + settings: Mapping[str, object], +) -> None: + rules: Final[Rules] = ( + RouteRule(Route.MESSAGES, Rollout.PYTHON_ONLY, features=frozenset({feature})), + RouteRule(Route.MESSAGES, Rollout.RUST_REQUIRED), + ) + python_result: Final = response(model) + native_result: Final = response(model) + + def served(call_kwargs: Mapping[str, object]) -> AnthropicMessagesResponse: + messages: Final = call_kwargs.get("messages", MESSAGES) + return _DISPATCH.run( + (16, messages, model), + {name: value for name, value in call_kwargs.items() if name != "messages"}, + python=lambda *call_args, **python_kwargs: python_result, + binding=messages_binding(lambda request: native_result), + native=lambda hook, request, call_args, native_kwargs: hook(request), + rules=rules, + ) + + monkeypatch.setattr(litellm, "callbacks", []) + monkeypatch.setattr(litellm, "cache", None) + monkeypatch.setattr(litellm, "ssl_security_level", None) + for setting in ("modify_params", "enable_anthropic_prompt_caching", "include_cost_in_streaming_usage"): + monkeypatch.setattr(litellm, setting, False) + for name in ("SSL_SECURITY_LEVEL", "SSL_ECDH_CURVE", "ANTHROPIC_FEDERATION_RULE_ID", "ANTHROPIC_ORGANIZATION_ID"): + monkeypatch.delenv(name, raising=False) + monkeypatch.setenv("ANTHROPIC_API_KEY", "") + monkeypatch.delenv("ANTHROPIC_AUTH_TOKEN", raising=False) + assert served({}) is native_result + for name, value in settings.items(): + monkeypatch.setattr(litellm, name, value) + assert served(kwargs) is python_result + + +ASYNC_ONLY_FEATURES: Final = ( + pytest.param(Feature.PRE_REQUEST_HOOK, {}, {"callbacks": [_Rewrite()]}, id="pre-request-hook"), + pytest.param( + Feature.WEBSEARCH_INTERCEPTION, {}, {"callbacks": [WebSearchInterceptionLogger()]}, id="websearch-interception" + ), + pytest.param( + Feature.MESSAGES_INTERCEPTOR, + {"model": "deepseek/deepseek-v4-flash", "tools": [ADVISOR_TOOL]}, + {}, + id="messages-interceptor", + ), +) + + +@pytest.mark.asyncio +@pytest.mark.parametrize(("feature", "kwargs", "settings"), ASYNC_ONLY_FEATURES) +async def test_handler_hooks_the_sync_entry_never_runs_keep_only_async_calls_on_python( + monkeypatch: pytest.MonkeyPatch, feature: Feature, kwargs: Mapping[str, object], settings: Mapping[str, object] +) -> None: + rules: Final[Rules] = ( + RouteRule(Route.MESSAGES, Rollout.PYTHON_ONLY, features=frozenset({feature})), + RouteRule(Route.MESSAGES, Rollout.RUST_REQUIRED), + ) + python_result: Final = response() + native_result: Final = response() + model: Final = str(kwargs.get("model", "anthropic/claude-sonnet-4-5")) + call_kwargs: Final = {name: value for name, value in kwargs.items() if name != "model"} + + async def python(*call_args: object, **python_kwargs: object) -> AnthropicMessagesResponse: # kwargs-ok: stub + return python_result async def native(request: NativeCall) -> AnthropicMessagesResponse: - raise declined("unsupported") + return native_result - async def python(*args: object, **kwargs: object) -> AnthropicMessagesResponse: - return expected - - binding: Final[NativeBinding[NativeAmessages]] = NativeBinding("amessages", validate=lambda _: None) - binding.override(native) - response: Final = await dispatch._ADISPATCH.arun( # pyright: ignore[reportPrivateUsage] # test an explicit route decision - (), - {"model": "claude-test", "messages": MESSAGES, "max_tokens": 10}, + monkeypatch.setattr(litellm, "callbacks", []) + for name, value in settings.items(): + monkeypatch.setattr(litellm, name, value) + served_async: Final = await _ADISPATCH.arun( + (16, MESSAGES, model), + call_kwargs, python=python, - binding=binding, - native=lambda hook, request, args, kwargs: hook(request), + binding=amessages_binding(native), + native=lambda hook, request, args, native_kwargs: hook(request), rules=rules, ) - - assert response is expected - - -def test_internal_is_async_marker_bypasses_native() -> None: - rules: Final[Rules] = (RouteRule(Route.MESSAGES, Rollout.RUST_REQUIRED),) - expected: Final = AnthropicMessagesResponse(model="claude-test") - - def python(*args: object, **kwargs: object) -> AnthropicMessagesResponse: - return expected - - def native(request: NativeCall) -> AnthropicMessagesResponse: - pytest.fail("anthropic_messages' inner handler call must stay on Python") - - binding: Final[NativeBinding[NativeMessages]] = NativeBinding("messages", validate=lambda _: None) - binding.override(native) - response: Final = dispatch._DISPATCH.run( # pyright: ignore[reportPrivateUsage] # test an explicit route decision - (), - { - "model": "claude-test", - "messages": MESSAGES, - "max_tokens": 10, - "custom_llm_provider": "anthropic", - "is_async": True, - }, - python=python, - binding=binding, - native=lambda hook, request, args, kwargs: hook(request), + served_sync: Final = _DISPATCH.run( + (16, MESSAGES, model), + call_kwargs, + python=lambda *call_args, **python_kwargs: python_result, + binding=messages_binding(lambda request: native_result), + native=lambda hook, request, args, native_kwargs: hook(request), rules=rules, ) + assert served_async is python_result + assert served_sync is native_result - assert response is expected + +@pytest.mark.asyncio +async def test_interceptor_feature_follows_the_resolved_provider() -> None: + rules: Final[Rules] = ( + RouteRule(Route.MESSAGES, Rollout.PYTHON_ONLY, features=frozenset({Feature.MESSAGES_INTERCEPTOR})), + RouteRule(Route.MESSAGES, Rollout.RUST_REQUIRED), + ) + native_result: Final = response() + + async def python(*call_args: object, **call_kwargs: object) -> AnthropicMessagesResponse: # kwargs-ok: stub + pytest.fail("anthropic serves the advisor tool itself") + + async def native(request: NativeCall) -> AnthropicMessagesResponse: + return native_result + + result: Final = await _ADISPATCH.arun( + (16, MESSAGES, "claude-sonnet-4-5"), + {"tools": [ADVISOR_TOOL], "custom_llm_provider": "anthropic"}, + python=python, + binding=amessages_binding(native), + native=lambda hook, request, call_args, call_kwargs: hook(request), + rules=rules, + ) + assert result is native_result diff --git a/tests/test_litellm_rust/ocr/test_callbacks.py b/tests/test_litellm_rust/ocr/test_callbacks.py index 5f961288800..18925599acf 100644 --- a/tests/test_litellm_rust/ocr/test_callbacks.py +++ b/tests/test_litellm_rust/ocr/test_callbacks.py @@ -237,7 +237,7 @@ async def test_native_aocr_failure_callbacks_receive_call_type_error_and_no_resp with pytest.raises(litellm.InternalServerError): await call_aocr(server, callbacks=[Observe()]) - assert [observation[0] for observation in observations] == ["sync", "async"] + assert [observation[0] for observation in observations] == ["async"] assert all(observation[1] == "aocr" for observation in observations) assert all(isinstance(observation[2], litellm.InternalServerError) for observation in observations) assert all(observation[3] is None for observation in observations) @@ -278,7 +278,7 @@ async def test_native_aocr_failure_callbacks_receive_state_added_by_pre_call_cal with pytest.raises(litellm.InternalServerError): await call_aocr(server, callbacks=[TrackInFlightRequest()]) - assert [event for event, _ in observed] == ["sync", "async"] + assert [event for event, _ in observed] == ["async"] assert all(observed_token is token for _, observed_token in observed) @@ -445,7 +445,7 @@ async def test_native_aocr_state_stashed_before_a_blocking_hook_raises_reaches_f await call_aocr(server) await drain_logging() - assert observed == [("sync", token, raised.value), ("async", token, raised.value)] + assert observed == [("async", token, raised.value)] @pytest.mark.asyncio diff --git a/tests/test_litellm_rust/ocr/test_dispatch.py b/tests/test_litellm_rust/ocr/test_dispatch.py index db60b6aea84..3206cc606a8 100644 --- a/tests/test_litellm_rust/ocr/test_dispatch.py +++ b/tests/test_litellm_rust/ocr/test_dispatch.py @@ -1,8 +1,21 @@ +from collections.abc import Mapping from typing import Final, NoReturn +import httpx import pytest import litellm +from litellm.llms.base_llm.ocr.transformation import OCRResponse +from litellm.ocr.dispatch import ( + _ADISPATCH, # pyright: ignore[reportPrivateUsage] # tests configured dispatch + _DISPATCH, # pyright: ignore[reportPrivateUsage] # tests configured dispatch +) +from litellm.rust_bridge import runtime +from litellm.rust_bridge.bindings import NativeBinding +from litellm.rust_bridge.catalog import Route, RouteRule, Rules +from litellm.rust_bridge.configuration import Rollout +from litellm.rust_bridge.ocr.entrypoints import NativeAocr, NativeOcr +from litellm.rust_bridge.public_call import NativeCall from tests.test_litellm_rust.ocr.data import OCR_DOCUMENT, OCR_MODEL from tests.test_litellm_rust.support.recording_server import RecordingServer, ResponseSpec from tests.test_litellm_rust.support.routing import assert_served_natively @@ -110,3 +123,214 @@ async def test_ocr_health_check_uses_the_native_route(recording_server: Recordin assert "error" not in response assert_served_natively(recording_server) assert recording_server.requests[0].body["document"]["image_url"].startswith("data:image/png;base64,") + + +RUST_RULES: Final[Rules] = (RouteRule(Route.OCR, Rollout.RUST_REQUIRED),) + + +def ocr_binding(native: NativeOcr | None) -> NativeBinding[NativeOcr]: + binding: Final[NativeBinding[NativeOcr]] = NativeBinding("ocr", validate=lambda _: None) + binding.override(native) + return binding + + +def aocr_binding(native: NativeAocr | None) -> NativeBinding[NativeAocr]: + binding: Final[NativeBinding[NativeAocr]] = NativeBinding("aocr", validate=lambda _: None) + binding.override(native) + return binding + + +def response(model: str = "mistral/mistral-ocr-latest") -> OCRResponse: + return OCRResponse(pages=[], model=model) + + +def test_native_receives_normalized_positional_request_and_original_call_shape() -> None: + document: Final[Mapping[str, object]] = {"type": "file", "file": b"pdf"} + timeout: Final = httpx.Timeout(30) + extra_headers: Final[dict[str, object]] = {"x-test": "1"} + pages: Final = [0, 2] + args: Final[tuple[object, ...]] = ("mistral/mistral-ocr-latest", document) + kwargs: Final[Mapping[str, object]] = { + "api_key": "test-key", + "api_base": "https://example.invalid", + "timeout": timeout, + "custom_llm_provider": "mistral", + "extra_headers": extra_headers, + "pages": pages, + } + captured: Final[list[tuple[NativeCall, tuple[object, ...], Mapping[str, object]]]] = [] + expected: Final = response() + + def native( + request: NativeCall, + ) -> OCRResponse: + args: Final = request.args + kwargs: Final = request.kwargs + captured.append((request, args, kwargs)) + return expected + + result: Final = _DISPATCH.run( + args, + kwargs, + python=runtime.NO_PYTHON, + binding=ocr_binding(native), + native=lambda hook, request, call_args, call_kwargs: hook(request), + rules=RUST_RULES, + ) + + request, call_args, call_kwargs = captured[0] + assert result is expected + assert request.resolved["model"] == "mistral/mistral-ocr-latest" + assert request.resolved["document"] is document + assert request.resolved["api_key"] == "test-key" + assert request.resolved["api_base"] == "https://example.invalid" + assert request.resolved["timeout"] is timeout + assert request.resolved["custom_llm_provider"] == "mistral" + assert request.resolved["extra_headers"] is extra_headers + assert request.kwargs == kwargs + assert request.kwargs["pages"] is pages + assert call_args is args + assert call_kwargs is kwargs + + +def test_native_preserves_keyword_model_and_document_in_original_call_shape() -> None: + document: Final[Mapping[str, object]] = { + "type": "document_url", + "document_url": "https://example.invalid/document.pdf", + } + pages: Final = [1] + args: Final[tuple[object, ...]] = () + kwargs: Final[Mapping[str, object]] = { + "model": "mistral/mistral-ocr-latest", + "document": document, + "pages": pages, + } + captured: Final[list[tuple[NativeCall, tuple[object, ...], Mapping[str, object]]]] = [] + expected: Final = response() + + def native( + request: NativeCall, + ) -> OCRResponse: + args: Final = request.args + kwargs: Final = request.kwargs + captured.append((request, args, kwargs)) + return expected + + result: Final = _DISPATCH.run( + args, + kwargs, + python=runtime.NO_PYTHON, + binding=ocr_binding(native), + native=lambda hook, request, call_args, call_kwargs: hook(request), + rules=RUST_RULES, + ) + + request, call_args, call_kwargs = captured[0] + assert result is expected + assert request.resolved["model"] == "mistral/mistral-ocr-latest" + assert request.resolved["document"] is document + assert request.kwargs == kwargs + assert call_args is args + assert call_kwargs is kwargs + assert call_kwargs["model"] == "mistral/mistral-ocr-latest" + assert call_kwargs["document"] is document + + +def test_missing_native_binding_is_a_required_rust_error() -> None: + args: Final[tuple[object, ...]] = ("mistral/mistral-ocr-latest", {"type": "file", "file": b"pdf"}) + + with pytest.raises(RuntimeError, match="Rust ocr bridge"): + _DISPATCH.run( + args, + {}, + python=runtime.NO_PYTHON, + binding=ocr_binding(None), + native=lambda hook, request, call_args, call_kwargs: hook(request), + rules=RUST_RULES, + ) + + +def test_non_required_rule_cannot_be_served_without_python() -> None: + args: Final[tuple[object, ...]] = ("mistral/mistral-ocr-latest", {"type": "file", "file": b"pdf"}) + + def native( + request: NativeCall, + ) -> OCRResponse: + return response() + + with pytest.raises(runtime.NoPythonImplementationError, match="RUST_REQUIRED"): + _DISPATCH.run( + args, + {}, + python=runtime.NO_PYTHON, + binding=ocr_binding(native), + native=lambda hook, request, call_args, call_kwargs: hook(request), + rules=(RouteRule(Route.OCR, Rollout.PYTHON_ONLY),), + ) + + +@pytest.mark.parametrize( + ("args", "kwargs", "message"), + ( + ( + ("mistral/mistral-ocr-latest", {"type": "file", "file": b"pdf"}), + {"model": "duplicate"}, + r"ocr\(\) got multiple values for argument 'model'", + ), + ( + ("mistral/mistral-ocr-latest",), + {}, + r"ocr\(\) missing 1 required positional argument: 'document'", + ), + ), +) +def test_ocr_parser_errors_before_native(args: tuple[object, ...], kwargs: Mapping[str, object], message: str) -> None: + def native( + request: NativeCall, + ) -> OCRResponse: + pytest.fail("OCR parser failures must not call native") + + with pytest.raises(TypeError, match=message): + _DISPATCH.run( + args, + kwargs, + python=runtime.NO_PYTHON, + binding=ocr_binding(native), + native=lambda hook, request, call_args, call_kwargs: hook(request), + rules=RUST_RULES, + ) + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("args", "kwargs", "message"), + ( + ( + ("mistral/mistral-ocr-latest", {"type": "file", "file": b"pdf"}), + {"model": "duplicate"}, + r"aocr\(\) got multiple values for argument 'model'", + ), + ( + ("mistral/mistral-ocr-latest",), + {}, + r"aocr\(\) missing 1 required positional argument: 'document'", + ), + ), +) +async def test_aocr_parser_errors_before_native( + args: tuple[object, ...], kwargs: Mapping[str, object], message: str +) -> None: + async def native( + request: NativeCall, + ) -> OCRResponse: + pytest.fail("OCR parser failures must not call native") + + with pytest.raises(TypeError, match=message): + await _ADISPATCH.arun( + args, + kwargs, + python=runtime.NO_PYTHON, + binding=aocr_binding(native), + native=lambda hook, request, call_args, call_kwargs: hook(request), + rules=RUST_RULES, + ) diff --git a/tests/test_litellm_rust/ocr/test_lifecycle.py b/tests/test_litellm_rust/ocr/test_lifecycle.py index c35f6836144..611316fb52c 100644 --- a/tests/test_litellm_rust/ocr/test_lifecycle.py +++ b/tests/test_litellm_rust/ocr/test_lifecycle.py @@ -144,7 +144,7 @@ async def test_mapped_failure_identity_and_deployment_snapshot(server: Recording with pytest.raises(litellm.InternalServerError) as caught: await call_aocr(server, callbacks=[recorder]) failures: Final = tuple(event for event in recorder.events if "failure" in event.name) - assert [event.name for event in failures] == ["log_failure_event", "async_log_failure_event"] + assert [event.name for event in failures] == ["async_log_failure_event"] assert all(event.kwargs["exception"] is caught.value for event in failures) assert caught.value.status_code == 500 assert snapshots[0] is not caught.value @@ -324,24 +324,26 @@ async def test_failure_callbacks_continue_within_both_families(server: Recording server.enqueue(ResponseSpec(body={"message": "failed"}, status=500)) observed: Final = [] - class Broken(CustomLogger): + class BrokenSync(CustomLogger): def log_failure_event(self, kwargs, response_obj, start_time, end_time): observed.append(("broken-sync", kwargs["exception"])) raise RuntimeError("sync observer") + class FollowingSync(CustomLogger): + def log_failure_event(self, kwargs, response_obj, start_time, end_time): + observed.append(("following-sync", kwargs["exception"])) + + class BrokenAsync(CustomLogger): async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time): observed.append(("broken-async", kwargs["exception"])) raise RuntimeError("async observer") - class Following(CustomLogger): - def log_failure_event(self, kwargs, response_obj, start_time, end_time): - observed.append(("following-sync", kwargs["exception"])) - + class FollowingAsync(CustomLogger): async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time): observed.append(("following-async", kwargs["exception"])) with pytest.raises(litellm.InternalServerError) as caught: - await call_aocr(server, callbacks=[Broken(), Following()]) + await call_aocr(server, callbacks=[BrokenSync(), FollowingSync(), BrokenAsync(), FollowingAsync()]) assert [name for name, _ in observed] == ["broken-sync", "following-sync", "broken-async", "following-async"] assert all(error is caught.value for _, error in observed) diff --git a/tests/test_litellm_rust/ocr/test_public_dispatch.py b/tests/test_litellm_rust/ocr/test_public_dispatch.py deleted file mode 100644 index 34ee8e40552..00000000000 --- a/tests/test_litellm_rust/ocr/test_public_dispatch.py +++ /dev/null @@ -1,300 +0,0 @@ -from collections.abc import Awaitable, Callable, Mapping -from typing import Final, cast # noqa: TID251 # narrows legacy callable signatures for inspect - -import httpx -import pytest - -import litellm -from litellm.llms.base_llm.ocr.transformation import OCRResponse -from litellm.ocr.dispatch import ( - _ADISPATCH, # pyright: ignore[reportPrivateUsage] # tests configured dispatch - _DISPATCH, # pyright: ignore[reportPrivateUsage] # tests configured dispatch -) -from litellm.rust_bridge import catalog, runtime -from litellm.rust_bridge.bindings import NativeBinding -from litellm.rust_bridge.catalog import Route, RouteRule, Rules -from litellm.rust_bridge.configuration import Rollout -from litellm.rust_bridge.ocr.entrypoints import NATIVE_AOCR, NATIVE_OCR, NativeAocr, NativeOcr -from litellm.rust_bridge.public_call import NativeCall - -RUST_RULES: Final[Rules] = (RouteRule(Route.OCR, Rollout.RUST_REQUIRED),) - - -def ocr_binding(native: NativeOcr | None) -> NativeBinding[NativeOcr]: - binding: Final[NativeBinding[NativeOcr]] = NativeBinding("ocr", validate=lambda _: None) - binding.override(native) - return binding - - -def aocr_binding(native: NativeAocr | None) -> NativeBinding[NativeAocr]: - binding: Final[NativeBinding[NativeAocr]] = NativeBinding("aocr", validate=lambda _: None) - binding.override(native) - return binding - - -def response(model: str = "mistral/mistral-ocr-latest") -> OCRResponse: - return OCRResponse(pages=[], model=model) - - -def test_native_receives_normalized_positional_request_and_original_call_shape() -> None: - document: Final[Mapping[str, object]] = {"type": "file", "file": b"pdf"} - timeout: Final = httpx.Timeout(30) - extra_headers: Final[dict[str, object]] = {"x-test": "1"} - pages: Final = [0, 2] - args: Final[tuple[object, ...]] = ("mistral/mistral-ocr-latest", document) - kwargs: Final[Mapping[str, object]] = { - "api_key": "test-key", - "api_base": "https://example.invalid", - "timeout": timeout, - "custom_llm_provider": "mistral", - "extra_headers": extra_headers, - "pages": pages, - } - captured: Final[list[tuple[NativeCall, tuple[object, ...], Mapping[str, object]]]] = [] - expected: Final = response() - - def native( - request: NativeCall, - ) -> OCRResponse: - args: Final = request.args - kwargs: Final = request.kwargs - captured.append((request, args, kwargs)) - return expected - - result: Final = _DISPATCH.run( - args, - kwargs, - python=runtime.NO_PYTHON, - binding=ocr_binding(native), - native=lambda hook, request, call_args, call_kwargs: hook(request), - rules=RUST_RULES, - ) - - request, call_args, call_kwargs = captured[0] - assert result is expected - assert request.resolved["model"] == "mistral/mistral-ocr-latest" - assert request.resolved["document"] is document - assert request.resolved["api_key"] == "test-key" - assert request.resolved["api_base"] == "https://example.invalid" - assert request.resolved["timeout"] is timeout - assert request.resolved["custom_llm_provider"] == "mistral" - assert request.resolved["extra_headers"] is extra_headers - assert request.kwargs == kwargs - assert request.kwargs["pages"] is pages - assert call_args is args - assert call_kwargs is kwargs - - -def test_native_preserves_keyword_model_and_document_in_original_call_shape() -> None: - document: Final[Mapping[str, object]] = { - "type": "document_url", - "document_url": "https://example.invalid/document.pdf", - } - pages: Final = [1] - args: Final[tuple[object, ...]] = () - kwargs: Final[Mapping[str, object]] = { - "model": "mistral/mistral-ocr-latest", - "document": document, - "pages": pages, - } - captured: Final[list[tuple[NativeCall, tuple[object, ...], Mapping[str, object]]]] = [] - expected: Final = response() - - def native( - request: NativeCall, - ) -> OCRResponse: - args: Final = request.args - kwargs: Final = request.kwargs - captured.append((request, args, kwargs)) - return expected - - result: Final = _DISPATCH.run( - args, - kwargs, - python=runtime.NO_PYTHON, - binding=ocr_binding(native), - native=lambda hook, request, call_args, call_kwargs: hook(request), - rules=RUST_RULES, - ) - - request, call_args, call_kwargs = captured[0] - assert result is expected - assert request.resolved["model"] == "mistral/mistral-ocr-latest" - assert request.resolved["document"] is document - assert request.kwargs == kwargs - assert call_args is args - assert call_kwargs is kwargs - assert call_kwargs["model"] == "mistral/mistral-ocr-latest" - assert call_kwargs["document"] is document - - -def test_aocr_marker_cannot_be_served_without_python() -> None: - document: Final[Mapping[str, object]] = {"type": "file", "file": b"pdf"} - args: Final[tuple[object, ...]] = ("mistral/mistral-ocr-latest", document) - kwargs: Final[Mapping[str, object]] = {"aocr": True} - - def native( - request: NativeCall, - ) -> OCRResponse: - pytest.fail("the aocr bypass marker must not reach native") - - with pytest.raises(runtime.NoPythonImplementationError, match="bypass"): - _DISPATCH.run( - args, - kwargs, - python=runtime.NO_PYTHON, - binding=ocr_binding(native), - native=lambda hook, request, call_args, call_kwargs: hook(request), - rules=RUST_RULES, - ) - - -def test_missing_native_binding_is_a_required_rust_error() -> None: - args: Final[tuple[object, ...]] = ("mistral/mistral-ocr-latest", {"type": "file", "file": b"pdf"}) - - with pytest.raises(RuntimeError, match="Rust ocr bridge"): - _DISPATCH.run( - args, - {}, - python=runtime.NO_PYTHON, - binding=ocr_binding(None), - native=lambda hook, request, call_args, call_kwargs: hook(request), - rules=RUST_RULES, - ) - - -def test_non_required_rule_cannot_be_served_without_python() -> None: - args: Final[tuple[object, ...]] = ("mistral/mistral-ocr-latest", {"type": "file", "file": b"pdf"}) - - def native( - request: NativeCall, - ) -> OCRResponse: - return response() - - with pytest.raises(runtime.NoPythonImplementationError, match="RUST_REQUIRED"): - _DISPATCH.run( - args, - {}, - python=runtime.NO_PYTHON, - binding=ocr_binding(native), - native=lambda hook, request, call_args, call_kwargs: hook(request), - rules=(RouteRule(Route.OCR, Rollout.PYTHON_ONLY),), - ) - - -@pytest.mark.parametrize( - ("args", "kwargs", "message"), - ( - ( - ("mistral/mistral-ocr-latest", {"type": "file", "file": b"pdf"}), - {"model": "duplicate"}, - r"ocr\(\) got multiple values for argument 'model'", - ), - ( - ("mistral/mistral-ocr-latest",), - {}, - r"ocr\(\) missing 1 required positional argument: 'document'", - ), - ), -) -def test_ocr_parser_errors_before_native(args: tuple[object, ...], kwargs: Mapping[str, object], message: str) -> None: - def native( - request: NativeCall, - ) -> OCRResponse: - pytest.fail("OCR parser failures must not call native") - - with pytest.raises(TypeError, match=message): - _DISPATCH.run( - args, - kwargs, - python=runtime.NO_PYTHON, - binding=ocr_binding(native), - native=lambda hook, request, call_args, call_kwargs: hook(request), - rules=RUST_RULES, - ) - - -@pytest.mark.asyncio -@pytest.mark.parametrize( - ("args", "kwargs", "message"), - ( - ( - ("mistral/mistral-ocr-latest", {"type": "file", "file": b"pdf"}), - {"model": "duplicate"}, - r"aocr\(\) got multiple values for argument 'model'", - ), - ( - ("mistral/mistral-ocr-latest",), - {}, - r"aocr\(\) missing 1 required positional argument: 'document'", - ), - ), -) -async def test_aocr_parser_errors_before_native( - args: tuple[object, ...], kwargs: Mapping[str, object], message: str -) -> None: - async def native( - request: NativeCall, - ) -> OCRResponse: - pytest.fail("OCR parser failures must not call native") - - with pytest.raises(TypeError, match=message): - await _ADISPATCH.arun( - args, - kwargs, - python=runtime.NO_PYTHON, - binding=aocr_binding(native), - native=lambda hook, request, call_args, call_kwargs: hook(request), - rules=RUST_RULES, - ) - - -def test_public_ocr_routes_through_dispatch(monkeypatch: pytest.MonkeyPatch) -> None: - document: Final[Mapping[str, object]] = { - "type": "document_url", - "document_url": "https://example.invalid/document.pdf", - } - captured: Final[list[NativeCall]] = [] - expected: Final = response() - - def native( - request: NativeCall, - ) -> OCRResponse: - captured.append(request) - return expected - - NATIVE_OCR.override(native) - monkeypatch.setattr(catalog, "RULES", RUST_RULES) - public_ocr: Final = cast(Callable[..., OCRResponse], litellm.ocr) - try: - result: Final = public_ocr(model="mistral/mistral-ocr-latest", document=document) - finally: - NATIVE_OCR.reset() - assert result is expected - assert [request.resolved["model"] for request in captured] == ["mistral/mistral-ocr-latest"] - - -@pytest.mark.asyncio -async def test_public_aocr_routes_through_dispatch(monkeypatch: pytest.MonkeyPatch) -> None: - document: Final[Mapping[str, object]] = { - "type": "document_url", - "document_url": "https://example.invalid/document.pdf", - } - captured: Final[list[NativeCall]] = [] - expected: Final = response() - - async def native( - request: NativeCall, - ) -> OCRResponse: - captured.append(request) - return expected - - NATIVE_AOCR.override(native) - monkeypatch.setattr(catalog, "RULES", RUST_RULES) - public_aocr: Final = cast(Callable[..., Awaitable[OCRResponse]], litellm.aocr) - try: - result: Final = await public_aocr(model="mistral/mistral-ocr-latest", document=document) - finally: - NATIVE_AOCR.reset() - assert result is expected - assert [request.resolved["model"] for request in captured] == ["mistral/mistral-ocr-latest"] diff --git a/tests/test_litellm_rust/responses/data.py b/tests/test_litellm_rust/responses/data.py index 604a7de7442..0347fd7a57b 100644 --- a/tests/test_litellm_rust/responses/data.py +++ b/tests/test_litellm_rust/responses/data.py @@ -69,5 +69,7 @@ async def call(server: RecordingServer, *, asynchronous: bool = True, **kwargs: SYNC_DEPLOYMENT_HOOK: Final = gap("native sync calls skip the async pre-call deployment hook") -STREAMING: Final = gap("native Responses streaming declines to Python", raises=RuntimeError) +STREAMING: Final = gap( + "native Responses streaming is unsupported, the catalog keeps it on Python", raises=litellm.APIConnectionError +) BODY_HOOKS: Final = gap("native Responses does not run the handler body hooks") diff --git a/tests/test_litellm_rust/responses/test_callbacks.py b/tests/test_litellm_rust/responses/test_callbacks.py index a4abdd43529..0e921e9d5db 100644 --- a/tests/test_litellm_rust/responses/test_callbacks.py +++ b/tests/test_litellm_rust/responses/test_callbacks.py @@ -95,7 +95,7 @@ async def test_success_hook_fires_the_expected_number_of_times( "async_post_call_failure_deployment_hook", True, 1, id="async-async_post_call_failure_deployment_hook" ), pytest.param("log_model_group_rate_limit_error", True, 1, id="async-log_model_group_rate_limit_error"), - pytest.param("log_failure_event", True, 0, id="async-log_failure_event", marks=SYNC_HANDLERS_ON_ASYNC_CALLS), + pytest.param("log_failure_event", True, 0, id="async-log_failure_event"), pytest.param("log_failure_event", False, 1, id="sync-log_failure_event"), ), ) diff --git a/tests/test_litellm_rust/responses/test_dispatch.py b/tests/test_litellm_rust/responses/test_dispatch.py index e6a0193a063..4498dbdf39d 100644 --- a/tests/test_litellm_rust/responses/test_dispatch.py +++ b/tests/test_litellm_rust/responses/test_dispatch.py @@ -1,27 +1,28 @@ import inspect -from collections.abc import Awaitable, Callable, Mapping +from collections.abc import Callable, Mapping from typing import Final, cast # noqa: TID251 # narrows legacy callable signatures for inspect import pytest import litellm +from litellm.caching.caching import Cache +from litellm.integrations.custom_logger import CustomLogger from litellm.responses import dispatch as responses_dispatch from litellm.responses import main as python_responses from litellm.responses.dispatch import ( _ADISPATCH, # pyright: ignore[reportPrivateUsage] # tests configured dispatch _DISPATCH, # pyright: ignore[reportPrivateUsage] # tests configured dispatch ) -from litellm.rust_bridge import catalog +from litellm.responses.utils import ResponsesAPIRequestUtils from litellm.rust_bridge.bindings import NativeBinding -from litellm.rust_bridge.catalog import Route, RouteRule +from litellm.rust_bridge.catalog import Feature, Route, RouteRule from litellm.rust_bridge.configuration import Rollout from litellm.rust_bridge.public_call import NativeCall from litellm.rust_bridge.responses.entrypoints import ( - NATIVE_ARESPONSES, - NATIVE_RESPONSES, NativeAresponses, NativeResponses, ) +from litellm.types.llms.anthropic import ANTHROPIC_TOOL_SEARCH_TOOL_TYPES from litellm.types.llms.openai import ResponsesAPIResponse INPUT: Final = [{"role": "user", "content": "hi"}] @@ -181,35 +182,6 @@ def test_native_receives_normalized_request_and_original_call_shape() -> None: assert call_kwargs["litellm_metadata"] is metadata -def test_internal_async_marker_bypasses_native() -> None: - args: Final[tuple[object, ...]] = (INPUT, "gpt-4o") - kwargs: Final[Mapping[str, object]] = {"aresponses": True} - captured: Final[list[tuple[tuple[object, ...], Mapping[str, object]]]] = [] - response: Final = _response() - - def python(*call_args: object, **call_kwargs: object) -> ResponsesAPIResponse: # kwargs-ok: records call shape - captured.append((call_args, call_kwargs)) - return response - - def native( - request: NativeCall, - ) -> ResponsesAPIResponse: - pytest.fail("aresponses' inner responses call must stay on Python") - - assert ( - _DISPATCH.run( - args, - kwargs, - python=python, - binding=responses_binding(native), - native=lambda hook, request, call_args, call_kwargs: hook(request), - rules=RUST_RULES, - ) - is response - ) - assert captured == [(args, kwargs)] - - @pytest.mark.parametrize( ("args", "kwargs"), ( @@ -244,49 +216,6 @@ def test_binding_errors_delegate_unchanged_to_python(args: tuple[object, ...], k assert captured == [(args, kwargs)] -def test_public_responses_routes_through_dispatch(monkeypatch: pytest.MonkeyPatch) -> None: - captured: Final[list[NativeCall]] = [] - expected: Final = _response() - - def native( - request: NativeCall, - ) -> ResponsesAPIResponse: - captured.append(request) - return expected - - NATIVE_RESPONSES.override(native) - monkeypatch.setattr(catalog, "RULES", RUST_RULES) - public_responses: Final = cast(Callable[..., ResponsesAPIResponse], litellm.responses) - try: - result: Final = public_responses(input=INPUT, model="gpt-4o") - finally: - NATIVE_RESPONSES.reset() - assert result is expected - assert [request.resolved["model"] for request in captured] == ["gpt-4o"] - - -@pytest.mark.asyncio -async def test_public_aresponses_routes_through_dispatch(monkeypatch: pytest.MonkeyPatch) -> None: - captured: Final[list[NativeCall]] = [] - expected: Final = _response() - - async def native( - request: NativeCall, - ) -> ResponsesAPIResponse: - captured.append(request) - return expected - - NATIVE_ARESPONSES.override(native) - monkeypatch.setattr(catalog, "RULES", RUST_RULES) - public_aresponses: Final = cast(Callable[..., Awaitable[ResponsesAPIResponse]], litellm.aresponses) - try: - result: Final = await public_aresponses(input=INPUT, model="gpt-4o") - finally: - NATIVE_ARESPONSES.reset() - assert result is expected - assert [request.resolved["model"] for request in captured] == ["gpt-4o"] - - def test_responses_with_retries_uses_the_dispatch_entrypoint(monkeypatch: pytest.MonkeyPatch) -> None: calls: Final[list[Mapping[str, object]]] = [] expected: Final = _response() @@ -310,3 +239,167 @@ def test_positional_parameters_remain_available_to_native_projection() -> None: assert request.resolved["include"] is include assert request.resolved["instructions"] == "Be brief" assert request.resolved["max_output_tokens"] == 16 + + +class _Agentic(CustomLogger): + async def async_should_run_agentic_loop(self, *args: object, **kwargs: object) -> tuple[bool, dict]: # pyright: ignore[reportIncompatibleMethodOverride, reportMissingTypeArgument] # test double only needs the override + return False, {} + + +class _Deployment(CustomLogger): + async def async_pre_call_deployment_hook(self, *args: object, **kwargs: object) -> dict[str, object] | None: # pyright: ignore[reportIncompatibleMethodOverride] # test double only needs the override + return None + + +ENCODED_ID: Final = ResponsesAPIRequestUtils._build_encrypted_item_id("deployment-1", "rs_1") # pyright: ignore[reportPrivateUsage] # the encoder litellm stamps on earlier turns + + +@pytest.mark.parametrize( + ("feature", "kwargs", "settings"), + ( + (Feature.MOCK_RESPONSE, {"mock_response": "hi"}, {}), + (Feature.PROXY_MCP_TOOLS, {"tools": [{"type": "mcp", "server_label": "g", "server_url": "litellm_proxy"}]}, {}), + (Feature.CALLER_CLIENT, {"client": object()}, {}), + pytest.param(Feature.CALLER_CLIENT, {"shared_session": object()}, {}, id="shared-session"), + pytest.param(Feature.EXTRA_BODY, {"extra_body": {"stream": True}}, {}, id="extra-body-stream"), + pytest.param( + Feature.PROVIDER_AFFINITY, + {"provider_affinity_header": "X-Session-ID", "session_id": "session-1"}, + {}, + id="provider-affinity", + ), + pytest.param( + Feature.INPUT_REWRITE, + {"input": [{"type": "reasoning", "id": "rs_1", "summary": list[object](), "status": None}]}, + {}, + id="input-rewrite", + ), + (Feature.TIMEOUT_VARIANTS, {"request_timeout": 5}, {}), + (Feature.AGENTIC_LOOP_HOOK, {}, {"callbacks": [_Agentic()]}), + (Feature.TLS_POLICY, {}, {"ssl_security_level": "DEFAULT@SECLEVEL=1"}), + (Feature.DROP_PARAMS, {}, {"drop_params": True}), + (Feature.STREAMING, {"stream": True}, {}), + (Feature.PROMPT_MANAGEMENT, {"prompt_id": "welcome"}, {}), + (Feature.TEXT_FORMAT, {"text_format": dict}, {}), + (Feature.CHAT_COMPLETIONS_BRIDGE, {"use_chat_completions_api": True}, {}), + (Feature.CHAT_COMPLETIONS_BRIDGE, {"model": "openai/chat_completions/gpt-5"}, {}), + (Feature.RETRIES_FALLBACKS, {"num_retries": 2}, {}), + (Feature.DEPLOYMENT_RESPONSE_ID, {"litellm_metadata": {"model_info": {"id": "deployment-1"}}}, {}), + (Feature.ENCODED_ITEM_IDS, {"input": [{"type": "reasoning", "id": ENCODED_ID, "summary": []}]}, {}), + (Feature.MODIFY_PARAMS, {}, {"modify_params": True}), + (Feature.RESPONSE_CACHE, {}, {"cache": Cache()}), + ( + Feature.MANAGED_RESOURCE_IDS, + { + "input": [{"role": "user", "content": [{"type": "input_file", "file_id": "litellm-file"}]}], + "model_file_id_mapping": {"litellm-file": {"deployment-1": "file-abc"}}, + "model_info": {"id": "deployment-1"}, + }, + {}, + ), + (Feature.CACHE_CONTROL_MARKS, {"tools": [{"type": "function", "name": "f", "cache_control": {}}]}, {}), + ( + Feature.ANTHROPIC_TOOL_SEARCH, + {"tools": [{"type": sorted(ANTHROPIC_TOOL_SEARCH_TOOL_TYPES)[0], "name": "s"}]}, + {}, + ), + (Feature.TOOL_SCHEMA_REPAIR, {"tools": [{"type": "function", "name": "f", "parameters": "{}"}]}, {}), + (Feature.MODEL_PARAM_GATING, {"max_output_tokens": 1}, {}), + (Feature.CLIENT_HEADERS, {"headers": {"x-tenant": "a"}}, {}), + (Feature.DEPLOYMENT_HOOK, {}, {"callbacks": [_Deployment()]}), + ( + Feature.WORKLOAD_IDENTITY, + { + "openai_identity_provider_id": "idp-1", + "openai_service_account_id": "sa-1", + "openai_identity_token_file": "/var/run/token", + }, + {}, + ), + ), +) +def test_each_detected_feature_reaches_its_rule( + monkeypatch: pytest.MonkeyPatch, feature: Feature, kwargs: Mapping[str, object], settings: Mapping[str, object] +) -> None: + rules: Final = ( + RouteRule(Route.RESPONSES, Rollout.PYTHON_ONLY, features=frozenset({feature})), + RouteRule(Route.RESPONSES, Rollout.RUST_REQUIRED), + ) + python_result: Final = _response() + native_result: Final = _response() + + def served(call_kwargs: Mapping[str, object]) -> object: + return _DISPATCH.run( + (), + {"model": "gpt-5", "input": INPUT, **call_kwargs}, + python=lambda *call_args, **python_kwargs: python_result, + binding=responses_binding(lambda request: native_result), + native=lambda hook, request, call_args, native_kwargs: hook(request), + rules=rules, + ) + + monkeypatch.setattr(litellm, "callbacks", []) + monkeypatch.setattr(litellm, "drop_params", False) + monkeypatch.setattr(litellm, "modify_params", False) + monkeypatch.setattr(litellm, "ssl_security_level", None) + monkeypatch.setattr(litellm, "cache", None) + for setting in ("api_key", "openai_key", "api_base", "num_retries"): + monkeypatch.setattr(litellm, setting, None) + for name in ("SSL_SECURITY_LEVEL", "SSL_ECDH_CURVE", "OPENAI_API_KEY"): + monkeypatch.delenv(name, raising=False) + assert served({}) is native_result + for name, value in settings.items(): + monkeypatch.setattr(litellm, name, value) + assert served(kwargs) is python_result + + +@pytest.mark.asyncio +async def test_deployment_hook_keeps_only_sync_calls_on_python(monkeypatch: pytest.MonkeyPatch) -> None: + rules: Final = ( + RouteRule(Route.RESPONSES, Rollout.PYTHON_ONLY, features=frozenset({Feature.DEPLOYMENT_HOOK})), + RouteRule(Route.RESPONSES, Rollout.RUST_REQUIRED), + ) + native_result: Final = _response() + + async def python(*call_args: object, **call_kwargs: object) -> ResponsesAPIResponse: # kwargs-ok: stub + pytest.fail("the async handler leaves the deployment hook to the shared call wrapper") + + async def native(request: NativeCall) -> ResponsesAPIResponse: + return native_result + + monkeypatch.setattr(litellm, "callbacks", [_Deployment()]) + result: Final = await _ADISPATCH.arun( + (), + {"model": "gpt-5", "input": INPUT}, + python=python, + binding=aresponses_binding(native), + native=lambda hook, request, call_args, call_kwargs: hook(request), + rules=rules, + ) + assert result is native_result + + +@pytest.mark.parametrize( + ("kwargs", "native"), + ( + ({"model": "gpt-5"}, True), + ({"model": "openai/gpt-5"}, True), + ({"model": "gpt-5", "custom_llm_provider": "openai"}, True), + ({"model": "anthropic/claude-sonnet-4-5"}, False), + ({"model": "claude-sonnet-4-5"}, False), + ({"model": "gpt-5", "custom_llm_provider": "azure"}, False), + ), +) +def test_provider_rule_sees_the_resolved_provider(kwargs: Mapping[str, object], native: bool) -> None: + python_result: Final = _response() + native_result: Final = _response() + + result: Final = _DISPATCH.run( + (), + {"input": INPUT, **kwargs}, + python=lambda *call_args, **call_kwargs: python_result, + binding=responses_binding(lambda request: native_result), + native=lambda hook, request, call_args, call_kwargs: hook(request), + rules=(RouteRule(Route.RESPONSES, Rollout.RUST_REQUIRED, providers=frozenset({"openai"})),), + ) + assert result is (native_result if native else python_result) diff --git a/tests/test_litellm_rust/responses/test_failures.py b/tests/test_litellm_rust/responses/test_failures.py index 6dad1bc7278..4c4bb96c6ac 100644 --- a/tests/test_litellm_rust/responses/test_failures.py +++ b/tests/test_litellm_rust/responses/test_failures.py @@ -56,28 +56,3 @@ async def test_provider_failure_is_terminal_and_shared_with_callbacks( assert len(failure) == 1 assert _OBJECT.validate_python(failure[0].kwargs)["exception"] is caught.value assert not any("success" in name for name in recorder.names) - - -@pytest.mark.asyncio -@pytest.mark.parametrize( - "options", - ( - {"stream": True}, - {"extra_body": {"provider_option": True}}, - {"mock_response": "mock"}, - {"num_retries": 1}, - {"use_chat_completions_api": True}, - {"model_list": []}, - ), -) -async def test_unsupported_requests_fail_before_callbacks_and_provider_io( - server: RecordingServer, options: dict[str, object] -) -> None: - recorder: Final = RecordingLogger() - server.expected_requests = 0 - - with pytest.raises(RuntimeError, match="declined the request"): - await call(server, callbacks=[recorder], **options) - - assert not server.requests - assert not recorder.events diff --git a/tests/test_litellm_rust/support/routing.py b/tests/test_litellm_rust/support/routing.py index 4250589848d..e3bcd2ac463 100644 --- a/tests/test_litellm_rust/support/routing.py +++ b/tests/test_litellm_rust/support/routing.py @@ -11,7 +11,7 @@ from tests.test_litellm_rust.support.isolation import rebound from tests.test_litellm_rust.support.recording_server import RecordingServer from tests.test_litellm_rust.support.served import assert_served_natively -__all__ = ["CALL_ID", "assert_served_natively", "call_public", "native_route"] +__all__ = ["CALL_ID", "assert_served_natively", "call_public", "native_route", "routed"] CALL_ID: Final = "callback-contract" @@ -22,6 +22,12 @@ def native_route(*routes: Route) -> Generator[None]: yield +@contextmanager +def routed(*rules: RouteRule) -> Generator[None]: + with rebound(catalog, "RULES", rules): + yield + + async def call_public( create: Callable[..., object], acreate: Callable[..., Awaitable[object]], diff --git a/tests/test_litellm_rust/test_dispatch.py b/tests/test_litellm_rust/test_dispatch.py index 9d53db26ba8..193866409a2 100644 --- a/tests/test_litellm_rust/test_dispatch.py +++ b/tests/test_litellm_rust/test_dispatch.py @@ -1,12 +1,11 @@ from collections.abc import AsyncGenerator, Awaitable, Callable, Iterator, Mapping from dataclasses import dataclass -from typing import Final, TypeAlias +from typing import Final, NoReturn, TypeAlias import pytest -from litellm.rust_bridge import configuration from litellm.rust_bridge.bindings import NativeBinding -from litellm.rust_bridge.catalog import Route, RouteContext, RouteRule, Rules +from litellm.rust_bridge.catalog import Feature, Route, RouteContext, RouteRule, Rules, Target from litellm.rust_bridge.configuration import Rollout from litellm.rust_bridge.dispatch import PublicDispatch from litellm.rust_bridge.runtime import NO_PYTHON, NoPythonImplementationError @@ -70,29 +69,6 @@ def test_unconditional_python_rule_prevents_later_rust_rule_projection() -> None assert result is expected -def test_disabled_optional_rust_rule_forwards_before_projection() -> None: - rules: Final[Rules] = (RouteRule(Route.OCR, Rollout.RUST_OPT_OUT),) - - def reject_request(args: tuple[object, ...], kwargs: Mapping[str, object]) -> Request: - pytest.fail("Disabled optional Rust must not project the request") - - dispatch: Final = PublicDispatch(route=Route.OCR, request=reject_request, context=lambda _: RouteContext(Route.OCR)) - expected: Final = object() - configuration.rust(False) - try: - result: Final = dispatch.run( - ("model",), - {}, - python=lambda *args, **kwargs: expected, - binding=binding(), - native=lambda hook, request, args, kwargs: pytest.fail("Disabled optional Rust must not call native"), - rules=rules, - ) - finally: - configuration.rust(None) - assert result is expected - - def test_native_stream_result_is_not_consumed_or_wrapped() -> None: request: Final = Request(model="streaming-model") stream: Final[Iterator[int]] = iter((1, 2)) @@ -207,36 +183,42 @@ def test_rules_for_other_routes_and_constrained_python_rules_skip_projection() - assert result is expected -@pytest.mark.asyncio -async def test_async_bypass_forwards_to_python_without_native() -> None: - request: Final = Request(model="bypassed-model") - rules: Final[Rules] = (RouteRule(Route.RESPONSES, Rollout.RUST_REQUIRED),) - dispatch: Final = PublicDispatch( - route=Route.RESPONSES, - request=lambda args, kwargs: request, - context=lambda value: RouteContext(Route.RESPONSES, model=value.model), - bypass=lambda value: value.model == "bypassed-model", - ) +@pytest.mark.parametrize( + "constrained", + ( + RouteRule(Route.MESSAGES, Rollout.PYTHON_ONLY, providers=frozenset({"other"})), + RouteRule(Route.MESSAGES, Rollout.PYTHON_ONLY, models=frozenset({"other"})), + RouteRule(Route.MESSAGES, Rollout.PYTHON_ONLY, targets=frozenset({Target.CHAT_COMPLETIONS})), + RouteRule(Route.MESSAGES, Rollout.PYTHON_ONLY, features=frozenset({Feature.SAFEGUARDS_CLASSIFIER})), + ), + ids=("providers", "models", "targets", "features"), +) +def test_constrained_python_rule_still_projects_for_a_later_rust_rule(constrained: RouteRule) -> None: expected: Final = object() - - async def python(*args: object, **kwargs: object) -> object: # kwargs-ok: public pass-through shape - return expected - - result: Final = await dispatch.arun( - ("bypassed-model",), - {}, - python=python, - binding=binding(), - native=lambda hook, value, args, kwargs: pytest.fail("Bypassed requests must not call native"), - rules=rules, + native_binding: Final[NativeBinding[Callable[[Request], object]]] = NativeBinding("x", validate=lambda _: None) + native_binding.override(lambda request: expected) + dispatch: Final = PublicDispatch( + route=Route.MESSAGES, + request=lambda args, kwargs: Request(model="model"), + context=lambda value: RouteContext(Route.MESSAGES, model=value.model, target=Target.MESSAGES), ) + + result: Final = dispatch.run( + ("model",), + {}, + python=lambda *args, **kwargs: pytest.fail("a constrained Python rule must not hide the Rust rule after it"), + binding=native_binding, + native=lambda hook, value, args, kwargs: hook(value), + rules=(constrained, RouteRule(Route.MESSAGES, Rollout.RUST_REQUIRED)), + ) + assert result is expected NativeRoute: TypeAlias = Callable[[Request, tuple[object, ...], Mapping[str, object]], object] -def native_route(result: object) -> NativeBinding[NativeRoute]: +def no_python_binding(result: object) -> NativeBinding[NativeRoute]: bound: Final[NativeBinding[NativeRoute]] = NativeBinding("no_python", validate=lambda _: None) bound.override(lambda request, args, kwargs: (result, request, args, dict(kwargs))) return bound @@ -263,52 +245,87 @@ async def dispatch_without_python( return await dispatch.arun(("model",), {"page": 1}, python=NO_PYTHON, binding=bound, native=native, rules=rules) -def ocr_dispatch(request: Request | None, *, bypass: bool = False) -> PublicDispatch[Request]: +def failing_context(request: Request) -> RouteContext: + raise RuntimeError("detector exploded") + + +def failing_dispatch() -> PublicDispatch[Request]: + return PublicDispatch( + route=Route.CHAT_COMPLETIONS, request=lambda args, kwargs: Request(model="model"), context=failing_context + ) + + +def reject_native(hook: object, request: Request, args: tuple[object, ...], kwargs: Mapping[str, object]) -> NoReturn: + pytest.fail("a failed context build must not reach native") + + +def test_a_detector_error_keeps_the_call_on_python() -> None: + expected: Final = object() + result: Final = failing_dispatch().run( + ("model",), + {}, + python=lambda *args, **kwargs: expected, + binding=binding(), + native=reject_native, + rules=(RouteRule(Route.CHAT_COMPLETIONS, Rollout.RUST_REQUIRED),), + ) + assert result is expected + + +async def test_a_detector_error_keeps_the_async_call_on_python() -> None: + expected: Final = object() + + async def python(*args: object, **kwargs: object) -> object: # kwargs-ok: stub + return expected + + result: Final = await failing_dispatch().arun( + ("model",), + {}, + python=python, + binding=binding(), + native=reject_native, + rules=(RouteRule(Route.CHAT_COMPLETIONS, Rollout.RUST_REQUIRED),), + ) + assert result is expected + + +def ocr_dispatch(request: Request | None) -> PublicDispatch[Request]: return PublicDispatch( route=Route.OCR, request=lambda args, kwargs: request, context=lambda value: RouteContext(Route.OCR, model=value.model), - bypass=lambda _: bypass, ) @pytest.mark.parametrize("asynchronous", (False, True)) -@pytest.mark.parametrize("switch", (None, False)) -async def test_dispatch_without_python_hands_every_call_to_native(asynchronous: bool, switch: bool | None) -> None: +async def test_dispatch_without_python_hands_every_call_to_native(asynchronous: bool) -> None: request: Final = Request(model="model") result: Final = object() - configuration.rust(switch) - try: - dispatched: Final = await dispatch_without_python( - ocr_dispatch(request), - native_route(result), - (RouteRule(Route.OCR, Rollout.RUST_REQUIRED),), - asynchronous=asynchronous, - ) - finally: - configuration.rust(None) + dispatched: Final = await dispatch_without_python( + ocr_dispatch(request), + no_python_binding(result), + (RouteRule(Route.OCR, Rollout.RUST_REQUIRED),), + asynchronous=asynchronous, + ) assert dispatched == (result, request, ("model",), {"page": 1}) @pytest.mark.parametrize("asynchronous", (False, True)) @pytest.mark.parametrize( - ("request_value", "bypass", "rules", "reason"), + ("request_value", "rules", "reason"), ( - (Request(model="model"), False, (), "must resolve to RUST_REQUIRED"), - (Request(model="model"), False, (RouteRule(Route.OCR, Rollout.RUST_OPT_OUT),), "must resolve to RUST_REQUIRED"), - (None, False, (RouteRule(Route.OCR, Rollout.RUST_REQUIRED),), "must project to a native request"), - (Request(model="model"), True, (RouteRule(Route.OCR, Rollout.RUST_REQUIRED),), "bypass predicate matches"), + (Request(model="model"), (), "must resolve to RUST_REQUIRED"), + (Request(model="model"), (RouteRule(Route.OCR, Rollout.RUST_OPT_OUT),), "must resolve to RUST_REQUIRED"), + (None, (RouteRule(Route.OCR, Rollout.RUST_REQUIRED),), "must project to a native request"), ), - ids=("no-rule", "opt-out-rule", "unprojectable-call", "bypassed-call"), + ids=("no-rule", "opt-out-rule", "unprojectable-call"), ) async def test_dispatch_without_python_never_falls_back( - asynchronous: bool, request_value: Request | None, bypass: bool, rules: Rules, reason: str + asynchronous: bool, request_value: Request | None, rules: Rules, reason: str ) -> None: bound: Final[NativeBinding[NativeRoute]] = NativeBinding("no_python", validate=lambda _: None) bound.override(lambda request, args, kwargs: pytest.fail("a misdeclared route must not reach native")) with pytest.raises(NoPythonImplementationError, match=f"ocr has no Python implementation, so .*{reason}"): - await dispatch_without_python( - ocr_dispatch(request_value, bypass=bypass), bound, rules, asynchronous=asynchronous - ) + await dispatch_without_python(ocr_dispatch(request_value), bound, rules, asynchronous=asynchronous) diff --git a/tests/test_litellm_rust/test_public_entries.py b/tests/test_litellm_rust/test_public_entries.py new file mode 100644 index 00000000000..2f5c33e3ced --- /dev/null +++ b/tests/test_litellm_rust/test_public_entries.py @@ -0,0 +1,287 @@ +import inspect +from collections.abc import Awaitable, Callable, Iterator, Mapping +from contextlib import contextmanager +from dataclasses import dataclass, field +from enum import Enum, auto +from typing import Final, TypeAlias, cast # noqa: TID251 # public entries return union results + +import pytest + +import litellm +from litellm.messages import dispatch as messages +from litellm.rust_bridge.bindings import NativeBinding +from litellm.rust_bridge.catalog import Route, RouteRule +from litellm.rust_bridge.chat_completions.entrypoints import NATIVE_ACOMPLETION, NATIVE_COMPLETION +from litellm.rust_bridge.configuration import Rollout +from litellm.rust_bridge.embeddings.entrypoints import NATIVE_AEMBEDDING, NATIVE_EMBEDDING +from litellm.rust_bridge.messages.entrypoints import NATIVE_AMESSAGES, NATIVE_MESSAGES +from litellm.rust_bridge.ocr.entrypoints import NATIVE_AOCR, NATIVE_OCR +from litellm.rust_bridge.public_call import NativeCall +from litellm.rust_bridge.responses.entrypoints import NATIVE_ARESPONSES, NATIVE_RESPONSES +from litellm.rust_bridge.runtime import NoPythonImplementationError +from litellm.types.utils import ModelResponse +from tests.test_litellm_rust.support.routing import routed + +MESSAGES: Final = [{"role": "user", "content": "hi"}] + +Served: TypeAlias = Callable[[object], bool] + + +@dataclass(frozen=True, slots=True) +class Entry: + """``python`` is ``None`` for a route with no Python implementation, which only RUST_REQUIRED rules serve.""" + + route: Route + sync: Callable[..., object] + asynchronous: Callable[..., Awaitable[object]] + flag: str + sync_binding: NativeBinding[object] + async_binding: NativeBinding[object] + arguments: Mapping[str, object] + positional: int + python: Served | None + + def args(self) -> tuple[object, ...]: + return tuple(self.arguments.values())[: self.positional] + + def kwargs(self, **extra: object) -> Mapping[str, object]: # kwargs-ok: forwards the async flag + return {**dict(tuple(self.arguments.items())[self.positional :]), **extra} + + +def _binding(value: object) -> NativeBinding[object]: + return cast("NativeBinding[object]", value) # cast-ok: the table only overrides and resets bindings + + +def _chat(result: object) -> bool: + return isinstance(result, ModelResponse) and result.choices[0].message.content == "python" # pyright: ignore[reportAttributeAccessIssue] # non-streaming choice + + +def _embedding(result: object) -> bool: + return getattr(result, "data")[0]["embedding"] == [0.5] # noqa: B009 # union result has no common attribute + + +def _responses(result: object) -> bool: + return getattr(result, "output_text") == "python" # noqa: B009 # union result has no common attribute + + +def _messages(result: object) -> bool: + return isinstance(result, Mapping) and result["content"][0]["text"] == "python" + + +ENTRIES: Final = ( + Entry( + route=Route.CHAT_COMPLETIONS, + sync=litellm.completion, + asynchronous=litellm.acompletion, + flag="acompletion", + sync_binding=_binding(NATIVE_COMPLETION), + async_binding=_binding(NATIVE_ACOMPLETION), + arguments={"model": "openai/gpt-4o", "messages": MESSAGES, "mock_response": "python"}, + positional=2, + python=_chat, + ), + Entry( + route=Route.EMBEDDINGS, + sync=litellm.embedding, + asynchronous=litellm.aembedding, + flag="aembedding", + sync_binding=_binding(NATIVE_EMBEDDING), + async_binding=_binding(NATIVE_AEMBEDDING), + arguments={"model": "openai/text-embedding-3-small", "input": ["hi"], "mock_response": [0.5]}, + positional=2, + python=_embedding, + ), + Entry( + route=Route.RESPONSES, + sync=litellm.responses, + asynchronous=litellm.aresponses, + flag="aresponses", + sync_binding=_binding(NATIVE_RESPONSES), + async_binding=_binding(NATIVE_ARESPONSES), + arguments={"input": "hi", "model": "openai/gpt-4o", "mock_response": "python"}, + positional=2, + python=_responses, + ), + Entry( + route=Route.MESSAGES, + sync=messages.anthropic_messages_handler, + asynchronous=messages.anthropic_messages, + flag="is_async", + sync_binding=_binding(NATIVE_MESSAGES), + async_binding=_binding(NATIVE_AMESSAGES), + arguments={ + "max_tokens": 16, + "messages": MESSAGES, + "model": "anthropic/claude-sonnet-4-5", + "mock_response": "python", + }, + positional=0, + python=_messages, + ), + Entry( + route=Route.OCR, + sync=litellm.ocr, + asynchronous=litellm.aocr, + flag="aocr", + sync_binding=_binding(NATIVE_OCR), + async_binding=_binding(NATIVE_AOCR), + arguments={"model": "mistral/mistral-ocr-latest", "document": {"type": "file", "file": b"pdf"}}, + positional=2, + python=None, + ), +) + + +class Form(Enum): + SYNC = auto() + SYNC_FLAG_FALSE = auto() + ASYNC = auto() + SYNC_FLAG_TRUE = auto() + ASYNC_FLAG_TRUE = auto() + + +async def call(entry: Entry, form: Form) -> object: + match form: + case Form.SYNC: + return entry.sync(*entry.args(), **entry.kwargs()) + case Form.SYNC_FLAG_FALSE: + return entry.sync(*entry.args(), **entry.kwargs(**{entry.flag: False})) + case Form.ASYNC: + return await entry.asynchronous(*entry.args(), **entry.kwargs()) + case Form.SYNC_FLAG_TRUE: + return await cast( + "Awaitable[object]", entry.sync(*entry.args(), **entry.kwargs(**{entry.flag: True})) + ) # cast-ok: a sync entry with its flag set returns a coroutine + case Form.ASYNC_FLAG_TRUE: + return await entry.asynchronous(*entry.args(), **entry.kwargs(**{entry.flag: True})) + + +@dataclass(slots=True) +class Native: + result: ModelResponse = field(default_factory=ModelResponse) + calls: list[tuple[str, NativeCall]] = field(default_factory=list) # mutable-ok: records native calls + + def install(self, entry: Entry) -> None: + def sync(native_call: NativeCall) -> ModelResponse: + self.calls.append(("sync", native_call)) + return self.result + + async def asynchronous(native_call: NativeCall) -> ModelResponse: + self.calls.append(("async", native_call)) + return self.result + + entry.sync_binding.override(sync) + entry.async_binding.override(asynchronous) + + +@pytest.fixture +def native(entry: Entry) -> Iterator[Native]: + recorder: Final = Native() + recorder.install(entry) + yield recorder + entry.sync_binding.reset() + entry.async_binding.reset() + + +class Outcome(Enum): + PYTHON = auto() + NATIVE = auto() + UNAVAILABLE = auto() + NO_PYTHON = auto() + + +@dataclass(frozen=True, slots=True) +class Scenario: + rollout: Rollout | None + binding: bool + outcome: Outcome + + +SCENARIOS: Final = { + "no-rule": Scenario(None, binding=True, outcome=Outcome.PYTHON), + "python-only": Scenario(Rollout.PYTHON_ONLY, binding=True, outcome=Outcome.PYTHON), + "required": Scenario(Rollout.RUST_REQUIRED, binding=True, outcome=Outcome.NATIVE), + "required-without-extension": Scenario(Rollout.RUST_REQUIRED, binding=False, outcome=Outcome.UNAVAILABLE), +} + + +def expected(entry: Entry, scenario: Scenario) -> Outcome: + if entry.python is None and scenario.rollout is not Rollout.RUST_REQUIRED: + return Outcome.NO_PYTHON + return scenario.outcome + + +@contextmanager +def scenario_rules(entry: Entry, scenario: Scenario) -> Iterator[None]: + if not scenario.binding: + entry.sync_binding.override(None) + entry.async_binding.override(None) + with routed(*(() if scenario.rollout is None else (RouteRule(entry.route, scenario.rollout),))): + yield + + +def entry_id(entry: Entry) -> str: + return entry.route.value + + +@pytest.mark.parametrize("form", tuple(Form), ids=lambda form: form.name.lower()) +@pytest.mark.parametrize("scenario", tuple(SCENARIOS.values()), ids=tuple(SCENARIOS)) +@pytest.mark.parametrize("entry", ENTRIES, ids=entry_id) +async def test_every_public_form_takes_the_path_the_rules_pick( + entry: Entry, scenario: Scenario, form: Form, native: Native +) -> None: + outcome: Final = expected(entry, scenario) + with scenario_rules(entry, scenario): + if outcome is Outcome.UNAVAILABLE: + with pytest.raises(RuntimeError, match=f"Rust {entry.route.value} bridge is unavailable"): + await call(entry, form) + return + if outcome is Outcome.NO_PYTHON: + with pytest.raises(NoPythonImplementationError, match=f"{entry.route.value} has no Python implementation"): + await call(entry, form) + assert native.calls == [] + return + result: Final = await call(entry, form) + + if outcome is Outcome.PYTHON: + assert entry.python is not None + assert entry.python(result) + assert native.calls == [] + return + assert result is native.result + [(binding, native_call)] = native.calls + assert binding == ("sync" if form in (Form.SYNC, Form.SYNC_FLAG_FALSE) else "async") + assert {name: native_call.resolved[name] for name in entry.arguments} == entry.arguments + assert entry.flag not in native_call.resolved + + +@pytest.mark.parametrize("entry", ENTRIES, ids=entry_id) +async def test_async_forms_hand_native_the_same_call(entry: Entry, native: Native) -> None: + with scenario_rules(entry, SCENARIOS["required"]): + for form in (Form.ASYNC, Form.SYNC_FLAG_TRUE, Form.ASYNC_FLAG_TRUE): + _ = await call(entry, form) + + assert [binding for binding, _ in native.calls] == ["async", "async", "async"] + resolved: Final = [dict(native_call.resolved) for _, native_call in native.calls] + assert resolved[1:] == [resolved[0], resolved[0]] + + +@pytest.mark.parametrize("entry", ENTRIES, ids=entry_id) +async def test_sync_entry_with_flag_true_does_nothing_until_awaited(entry: Entry, native: Native) -> None: + with scenario_rules(entry, SCENARIOS["required"]): + pending: Final = entry.sync(*entry.args(), **entry.kwargs(**{entry.flag: True})) + + assert inspect.iscoroutine(pending) + assert native.calls == [] + assert await pending is native.result + assert len(native.calls) == 1 + + +@pytest.mark.parametrize("entry", ENTRIES, ids=entry_id) +async def test_sync_entry_with_flag_true_raises_setup_errors_at_await(entry: Entry, native: Native) -> None: + with scenario_rules(entry, SCENARIOS["required-without-extension"]): + pending: Final = entry.sync(*entry.args(), **entry.kwargs(**{entry.flag: True})) + + assert inspect.iscoroutine(pending) + with pytest.raises(RuntimeError, match="is unavailable"): + await pending diff --git a/tests/unit/AGENTS.md b/tests/unit/AGENTS.md index 80a3a87f959..9ce6c58cff7 100644 --- a/tests/unit/AGENTS.md +++ b/tests/unit/AGENTS.md @@ -1,6 +1,9 @@ # tests/unit -In-process. No network, clock or subprocess +In-process. No network or subprocess + +Unit tests must not depend on the current time or execution speed. Use fixed timestamps for fixtures +and controlled clocks for time-dependent behavior. Incidental clock reads inside production code are allowed ## What good looks like diff --git a/tests/unit/a2a_protocol/test_a2a_streaming_iterator.py b/tests/unit/a2a_protocol/test_a2a_streaming_iterator.py index 2e883e91fda..6d685674984 100644 --- a/tests/unit/a2a_protocol/test_a2a_streaming_iterator.py +++ b/tests/unit/a2a_protocol/test_a2a_streaming_iterator.py @@ -6,6 +6,8 @@ async_success_handler (cross-thread pydantic mutation segfaults pydantic-core). import asyncio import time +from datetime import datetime +from typing import Final from types import SimpleNamespace import pytest @@ -135,3 +137,55 @@ async def test_stream_completion_counts_tokens_off_the_event_loop(monkeypatch): assert usage.prompt_tokens > 100_000 assert usage.completion_tokens > 100_000 assert_loop_stayed_free(took, lags) + + +class _SuccessRecorder(CustomLogger): + def __init__(self): + super().__init__() + self.logged: list[tuple[datetime, object]] = [] + + async def async_log_success_event( + self, kwargs: dict[str, object], response_obj: object, start_time: datetime, end_time: datetime + ) -> None: + self.logged.append((start_time, kwargs.get("completion_start_time"))) + + async def async_log_stream_event( + self, kwargs: dict[str, object], response_obj: object, start_time: datetime, end_time: datetime + ) -> None: + self.logged.append((start_time, kwargs.get("completion_start_time"))) + + +@pytest.mark.asyncio +async def test_stream_logs_its_first_chunk_time_measured_from_the_call_start(): + call_start: Final = datetime(2026, 10, 9, 12, 0, 0) + recorder: Final = _SuccessRecorder() + logging_obj: Final = LitellmLogging( + model="a2a/test-agent", + messages=[{"role": "user", "content": "hi"}], + stream=True, + call_type="a2a_send_message_streaming", + start_time=call_start, + litellm_call_id="a2a-first-chunk", + function_id="a2a-first-chunk", + dynamic_async_success_callbacks=[recorder], + ) + + async def _stream(): + yield _AgentChunk("Hel") + yield _AgentChunk("Hello") + + iterator: Final = A2AStreamingIterator( + stream=_stream(), + request=SimpleNamespace(params=SimpleNamespace(message={"role": "user", "parts": [{"kind": "text", "text": "hi"}]})), + logging_obj=logging_obj, + agent_name="test-agent", + ) + tasks_before: Final = asyncio.all_tasks() + + _ = await iterator.__anext__() + first_chunk_at: Final = logging_obj.completion_start_time + _ = [chunk async for chunk in iterator] + await asyncio.gather(*(asyncio.all_tasks() - tasks_before)) + + assert first_chunk_at is not None + assert recorder.logged == [(call_start, first_chunk_at)] diff --git a/tests/unit/a2a_protocol/test_main.py b/tests/unit/a2a_protocol/test_main.py index bab14dd26d6..75fd9eda75b 100644 --- a/tests/unit/a2a_protocol/test_main.py +++ b/tests/unit/a2a_protocol/test_main.py @@ -1,7 +1,9 @@ """Tests for litellm/a2a_protocol/main.py non-streaming send behavior.""" import asyncio +import datetime import json +from typing import Final import httpx import pytest @@ -155,6 +157,7 @@ def test_streaming_logging_obj_carries_call_type_into_model_call_details(): litellm_params=None, metadata=None, proxy_server_request=None, + start_time=datetime.datetime(2026, 10, 20, 12, 0, 0), ) assert logging_obj.model_call_details["call_type"] == "asend_message_streaming" @@ -352,6 +355,7 @@ async def _seed_shared_a2a_client( rpc_reply=_RPC_REPLY, rpc_stream_events=None, provider: str = httpxSpecialProvider.A2AProvider, + recorder: _RequestRecorder | None = None, ) -> _RequestRecorder: """Put the one A2A client the cache will hand out behind a mock transport. @@ -359,10 +363,12 @@ async def _seed_shared_a2a_client( it. The injected client is a real httpx.AsyncClient, so the merge of per-request headers over client defaults, which is what these tests are about, stays real. """ - recorder = _RequestRecorder(card=card, rpc_reply=rpc_reply, rpc_stream_events=rpc_stream_events) + active_recorder: Final = recorder or _RequestRecorder( + card=card, rpc_reply=rpc_reply, rpc_stream_events=rpc_stream_events + ) handler = AsyncHTTPHandler(timeout=DEFAULT_A2A_AGENT_TIMEOUT) owned_client = handler.client - handler.client = httpx.AsyncClient(transport=httpx.MockTransport(recorder)) + handler.client = httpx.AsyncClient(transport=httpx.MockTransport(active_recorder)) await owned_client.aclose() litellm.in_memory_llm_clients_cache.set_cache( @@ -374,8 +380,8 @@ async def _seed_shared_a2a_client( ) assert seeded is handler, "cache key drifted from get_async_httpx_client; these tests would test nothing" - recorder.client = handler.client - return recorder + active_recorder.client = handler.client + return active_recorder @pytest.fixture @@ -679,6 +685,43 @@ class _UsageRecorder(CustomLogger): self.logged.set() +class _CardServedAtRecorder(_RequestRecorder): + def __init__(self) -> None: + super().__init__(rpc_stream_events=_LANGGRAPH_STREAM_EVENTS) + self.card_served_at: datetime.datetime | None = None + + def __call__(self, request: httpx.Request) -> httpx.Response: + if request.method == "GET" and self.card_served_at is None: + self.card_served_at = datetime.datetime.now() + return super().__call__(request) + + +@pytest.mark.asyncio +async def test_streamed_send_is_timed_from_before_the_agent_card_fetch( + isolated_client_cache: LLMClientCache, monkeypatch: pytest.MonkeyPatch +): + from litellm.a2a_protocol import main as a2a_main + + card_recorder: Final = _CardServedAtRecorder() + await _seed_shared_a2a_client(recorder=card_recorder) + logger: Final = _UsageRecorder() + monkeypatch.setattr(litellm, "callbacks", [logger]) + monkeypatch.setattr(litellm, "success_callback", [logger]) + monkeypatch.setattr(litellm, "_async_success_callback", [logger]) + request: Final = SendStreamingMessageRequest( + id="reply", + params=MessageSendParams( + message={"messageId": "m-user", "role": "user", "parts": [{"kind": "text", "text": "hi"}]} + ), + ) + + _ = [chunk async for chunk in a2a_main.asend_message_streaming(request=request, api_base="http://127.0.0.1:9")] + await asyncio.wait_for(logger.logged.wait(), timeout=10) + + assert card_recorder.card_served_at is not None + assert logger.payload["startTime"] <= card_recorder.card_served_at.timestamp() + + @pytest.mark.asyncio async def test_asend_message_counts_usage_off_the_event_loop(monkeypatch): from tests.large_text import text @@ -742,6 +785,7 @@ def test_streaming_logging_obj_keeps_agent_credentials_out_of_logging_params(): }, metadata={"user_api_key": "hashed"}, proxy_server_request={"url": "http://localhost:4000"}, + start_time=datetime.datetime(2026, 10, 20, 12, 0, 0), ) expected = { diff --git a/tests/unit/caching/test_request_redis_batch_post_call.py b/tests/unit/caching/test_request_redis_batch_post_call.py index 5de785e44db..4b73bb6dd34 100644 --- a/tests/unit/caching/test_request_redis_batch_post_call.py +++ b/tests/unit/caching/test_request_redis_batch_post_call.py @@ -10,31 +10,27 @@ import datetime import hashlib import json from collections.abc import Awaitable, Callable, Mapping, Sequence -from unittest.mock import AsyncMock, MagicMock import pytest import litellm -from litellm._internal_context import current_service_target from litellm.caching.caching import Cache from litellm.caching.dual_cache import DualCache from litellm.caching.in_memory_cache import InMemoryCache from litellm.caching.redis_batch import ( active_post_call_redis_batch, - active_request_redis_batches, drain_post_call_redis_batches, flush_post_call_redis_batches, request_redis_batch_scope, ) from litellm.integrations.custom_logger import CustomLogger from litellm.litellm_core_utils.litellm_logging import Logging as LitellmLogging -from litellm.proxy.auth.auth_object_prefetch import AUTH_OBJECTS_TARGET from litellm.proxy.hooks.parallel_request_limiter_v3 import ( PARALLEL_RELEASE_SCRIPT, TOKEN_INCREMENT_SCRIPT, ParallelSlotAcquisition, - RequestRateLimiterStash, PROXY_MaxParallelRequestsHandler_v3, + RequestRateLimiterStash, ) from litellm.proxy.spend_tracking.spend_counter_batch import PendingSpendIncrement from litellm.proxy.utils import InternalUsageCache @@ -518,140 +514,3 @@ async def test_a_cancelled_post_call_flush_keeps_the_shared_spend_counter_and_co assert redis_cache.alone == [], "a cancel says nothing about the shared counter, so Redis keeps it" assert spend_cache.in_memory_cache.get_cache("spend:key:k1") == 3.5, "the local copy counts the cancelled spend" assert spend_cache.in_memory_cache.get_cache("spend:team:t1") is None, "an absent local copy is not seeded" - - -@pytest.mark.asyncio -async def test_the_update_cache_read_armed_before_accounting_rides_the_pipeline_of_the_reconcile_read(): - from litellm.proxy.proxy_server import _read_update_cache_values, arm_update_cache_read - - client = FakeClient(_ok_replies) - redis_cache = PostCallFakeRedisCache(client) - cache = DualCache() - cache.attach_redis_cache(redis_cache) - keys = ["user-1", "team_id:t1"] - - with request_redis_batch_scope() as request: - await arm_update_cache_read(keys, cache=cache) - assert client.pipelines == [] - await request.batch(redis_cache).mget(["spend:key:k1"]) # the spend reconcile read of the same request - values = await _read_update_cache_values(keys, None, cache=cache) - - assert len(client.pipelines) == 1 - assert client.pipelines[0].commands == [("MGET", "user-1", "team_id:t1"), ("MGET", "spend:key:k1")] - assert values == {"user-1": {"spend": 1.0}, "team_id:t1": {"spend": 1.0}} - assert redis_cache.alone == [] - assert active_request_redis_batches() is None - - -@pytest.mark.asyncio -async def test_the_armed_update_cache_read_is_declared_under_the_auth_objects_family(): - """The user, team and tag rows the accounting reads are auth objects, so the pipeline that carries - the armed read renders ``redis.pipeline auth_objects``, not a bare ``redis.pipeline``.""" - from litellm.proxy.proxy_server import _read_update_cache_values, arm_update_cache_read - - client = FakeClient(_ok_replies) - redis_cache = PostCallFakeRedisCache(client) - cache = DualCache() - cache.attach_redis_cache(redis_cache) - pipeline_targets: list[str | None] = [] # mutable-ok: filled by the recording hook - - async def record(**kwargs: object) -> None: - pipeline_targets.append(current_service_target()) - - redis_cache.service_logger_obj.async_service_success_hook = record # pyright: ignore[reportAttributeAccessIssue] # fake, records the hook call - - with request_redis_batch_scope(): - await arm_update_cache_read(["user-1", "team_id:t1"], cache=cache) - await _read_update_cache_values(["user-1", "team_id:t1"], None, cache=cache) - await asyncio.gather(*(t for t in asyncio.all_tasks() if t is not asyncio.current_task())) - - assert pipeline_targets == [AUTH_OBJECTS_TARGET] - - -@pytest.mark.asyncio -async def test_an_update_cache_read_armed_for_other_keys_is_ignored_and_the_read_happens_as_before(): - from litellm.proxy.proxy_server import _read_update_cache_values, arm_update_cache_read - - redis_cache = PostCallFakeRedisCache(FakeClient(_ok_replies)) - redis_cache.store["team_id:t1"] = {"spend": 2.0} - cache = DualCache() - cache.attach_redis_cache(redis_cache) - - with request_redis_batch_scope(): - await arm_update_cache_read(["user-1"], cache=cache) - values = await _read_update_cache_values(["team_id:t1"], None, cache=cache) - - assert values == {"team_id:t1": {"spend": 2.0}} - assert ("MGET", ("team_id:t1",)) in redis_cache.alone - - -@pytest.mark.asyncio -async def test_the_update_cache_read_sees_a_cached_spend_written_while_the_spend_was_persisted(monkeypatch): - from litellm.proxy import proxy_server - from litellm.proxy.hooks.proxy_track_cost_callback import _update_database_and_spend_counters - - cached_user_spend = {"user-1": 1.0} - - def replies(command: tuple[object, ...]) -> object: - if command[0] == "MGET": - return [ - json.dumps({"spend": cached_user_spend[key]}) if key in cached_user_spend else b"0.5" - for key in command[1:] - ] - return _ok_replies(command) - - client = FakeClient(replies) - redis_cache = PostCallFakeRedisCache(client) - spend_cache = DualCache() - spend_cache.attach_redis_cache(redis_cache) - user_cache = DualCache() - user_cache.attach_redis_cache(redis_cache) - monkeypatch.setattr(proxy_server, "spend_counter_cache", spend_cache) - monkeypatch.setattr(proxy_server, "user_api_key_cache", user_cache) - - async def _read_on_the_request_pipeline_then_a_concurrent_callback_writes_the_user(**kwargs: object) -> bool: - request = active_request_redis_batches() - assert request is not None - await request.batch(redis_cache).mget(["key-object"]) - cached_user_spend["user-1"] = 5.0 - return True - - proxy_logging_obj = MagicMock() - proxy_logging_obj.db_spend_update_writer.update_database = AsyncMock( - side_effect=_read_on_the_request_pipeline_then_a_concurrent_callback_writes_the_user - ) - reservation = { - "reserved_cost": 0.5, - "entries": [ - { - "counter_key": "spend:key:k1", - "entity_type": "Key", - "entity_id": "k1", - "reserved_cost": 0.5, - "applied_adjustment": 0.0, - } - ], - "finalized": False, - } - - with request_redis_batch_scope(): - charged = await _update_database_and_spend_counters( - proxy_logging_obj=proxy_logging_obj, - increment_spend_counters=proxy_server.increment_spend_counters, - user_api_key="k1", - user_id="user-1", - end_user_id=None, - team_id=None, - org_id=None, - kwargs={}, - completion_response=None, - start_time=datetime.datetime.now(), - end_time=datetime.datetime.now(), - response_cost=0.2, - budget_reservation=reservation, - update_cache_read_keys=("user-1",), - ) - values = await proxy_server._read_update_cache_values(("user-1",), None) - - assert charged is True - assert values == {"user-1": {"spend": 5.0}}, client.pipelines diff --git a/tests/unit/conftest.py b/tests/unit/conftest.py index 9028b8461b0..c96e3e2c031 100644 --- a/tests/unit/conftest.py +++ b/tests/unit/conftest.py @@ -307,6 +307,30 @@ def isolate_router_model_cost_state() -> Iterator[None]: litellm.get_model_info.cache_clear() +def _provider_model_sets() -> tuple[set[str], ...]: + module_globals: Final = tuple(vars(litellm).items()) + return tuple(models for name, models in module_globals if name.endswith("_models") and isinstance(models, set)) + + +@pytest.fixture(autouse=True) +def isolate_model_catalog() -> Iterator[None]: + model_cost: Final = litellm.model_cost + model_cost_entries: Final = dict(model_cost) + models_by_provider: Final = litellm.models_by_provider + models_by_provider_entries: Final = dict(models_by_provider) + provider_model_sets: Final = tuple((models, frozenset(models)) for models in _provider_model_sets()) + yield + model_cost.clear() + model_cost.update(model_cost_entries) + models_by_provider.clear() + models_by_provider.update(models_by_provider_entries) + for models, entries in provider_model_sets: + models.clear() + models.update(entries) + litellm_utils_module._invalidate_model_cost_lowercase_map() + litellm.get_model_info.cache_clear() + + @pytest.fixture def local_model_cost_map(monkeypatch: pytest.MonkeyPatch) -> Iterator[None]: monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") diff --git a/tests/unit/decisions/test_call.py b/tests/unit/decisions/test_call.py index 03c135369b8..36a16dd5ad1 100644 --- a/tests/unit/decisions/test_call.py +++ b/tests/unit/decisions/test_call.py @@ -1,3 +1,4 @@ +import base64 import json from collections.abc import Mapping from datetime import datetime, timezone @@ -112,3 +113,22 @@ def test_decisions_request_is_logged_even_when_its_questions_fail_validation(): logged: Final = _logged_request(logging_obj) assert logged["questions"][0]["instructions"] == QUESTION_TEXT + + +def test_non_utf8_bytes_in_the_request_are_logged_and_rejected_with_a_400(): + logging_obj: Final = _logging_obj("adecisions") + raw_input: Final = b"\xff\xfe not utf-8" + + with pytest.raises(litellm.BadRequestError): + _prepare_decisions_call( + **CONNECTION, + decision_input=raw_input, + questions=[{"type": "predicate", "instructions": QUESTION_TEXT}], + audio=None, + videos=None, + kwargs={"litellm_logging_obj": logging_obj}, + ) + + logged: Final = _logged_request(logging_obj) + assert base64.urlsafe_b64decode(logged["input"]) == raw_input + assert logged["questions"][0]["instructions"] == QUESTION_TEXT diff --git a/tests/unit/decisions/test_main.py b/tests/unit/decisions/test_main.py index 20af774278f..84e7a970195 100644 --- a/tests/unit/decisions/test_main.py +++ b/tests/unit/decisions/test_main.py @@ -612,13 +612,35 @@ async def test_oss_classifier_rejects_unknown_models_and_ambiguous_bases_before_ assert len(respx_mock.calls) == 0 -@pytest.mark.asyncio -async def test_upstream_reply_without_answers_is_a_server_error(respx_mock: respx.MockRouter) -> None: - respx_mock.post("https://api.perplexity.ai/v1/decisions").respond( - json={"model": "pplx-decider-v1-27b", "usage": {"input_tokens": 10, "output_tokens": 0}} - ) +_PPLX_USAGE: Final = {"model": "pplx-decider-v1-27b", "usage": {"input_tokens": 10, "output_tokens": 0}} - with pytest.raises(litellm.InternalServerError, match="unexpected response"): + +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("reply", "detail"), + ( + pytest.param(_PPLX_USAGE, "DecisionsResponse answers: Field required", id="usage"), + pytest.param({"error": "Rate limit reached"}, "DecisionsResponse answers: Field required", id="rate_limit_text"), + pytest.param({"error": "Request timed out"}, "DecisionsResponse answers: Field required", id="timeout_text"), + pytest.param( + {**_PPLX_USAGE, "answers": {"rate_limit": None}}, + "DecisionsResponse answers.rate_limit: Input should be a valid dictionary", + id="null_answer_named_rate_limit", + ), + pytest.param( + {**_PPLX_USAGE, "answers": {"is_defect": {"type": "Request timed out"}}}, + "DecisionsResponse answers.is_defect", + id="answer_type_timeout_text", + ), + pytest.param(["Rate limit reached"], "DecisionsResponse Input should be a valid dictionary", id="not_an_object"), + ), +) +async def test_a_malformed_upstream_reply_is_a_server_error_whatever_its_text( + reply: object, detail: str, respx_mock: respx.MockRouter +) -> None: + respx_mock.post("https://api.perplexity.ai/v1/decisions").respond(json=reply) + + with pytest.raises(litellm.InternalServerError, match=re.escape(f"unexpected response: {detail}")): await litellm.asystemone( model="perplexity/pplx-decider-v1-27b", state="review", @@ -3690,6 +3712,39 @@ async def test_decision_hosts_preserve_drex_model_routing_credentials_and_return } +@pytest.mark.parametrize( + "unpriced_row", + ( + pytest.param({}, id="empty"), + pytest.param( + {"litellm_provider": "typesafe", "mode": "evaluation", "input_cost_per_token": None}, + id="metadata_and_null_rate", + ), + ), +) +async def test_a_returned_model_registered_without_prices_is_billed_at_the_requested_model( + unpriced_row: dict[str, object], monkeypatch: pytest.MonkeyPatch, respx_mock: respx.MockRouter +) -> None: + monkeypatch.setenv("TYPESAFE_API_KEY", "typesafe-test-key") + monkeypatch.setitem( + litellm.model_cost, + "typesafe/jev-test-alias", + {"litellm_provider": "typesafe", "mode": "evaluation", "input_cost_per_token": 0.001, "output_cost_per_token": 0}, + ) + monkeypatch.setitem(litellm.model_cost, "typesafe/jev-test-unpriced", unpriced_row) + respx_mock.post("https://api.typesafe.ai/v1/systemone").respond(json={**_RESPONSE, "model": "jev-test-unpriced"}) + + response: Final = await litellm.asystemone( + model="typesafe/jev-test-alias", + state="damaged order", + questions={"is_defect": {"type": "noul", "instructions": "Is this a defect?"}}, + ) + + assert litellm.completion_cost(completion_response=response, call_type="asystemone") == pytest.approx( + _INPUT_TOKENS * 0.001 + ) + + @pytest.mark.parametrize("base_env", ("NACE_API_BASE", "NACE_BASE_URL")) def test_nace_sync_call_uses_environment_base_and_explicit_credentials( base_env: str, diff --git a/tests/unit/enterprise/integrations/test_custom_guardrail.py b/tests/unit/enterprise/integrations/test_custom_guardrail.py index c6e48061698..84f34144d99 100644 --- a/tests/unit/enterprise/integrations/test_custom_guardrail.py +++ b/tests/unit/enterprise/integrations/test_custom_guardrail.py @@ -1,3 +1,5 @@ +import pytest + from litellm.integrations.custom_guardrail import CustomGuardrail from litellm.types.guardrails import GuardrailEventHooks, Mode @@ -249,3 +251,82 @@ def test_custom_guardrail_with_mode(monkeypatch): ) is False ) + + +@pytest.mark.parametrize("caller_tags,runs_pre_call", [((), True), (("test_tag",), False)]) +def test_custom_guardrail_mode_ignores_baggage_mapped_tags_the_caller_did_not_send( + monkeypatch, caller_tags, runs_pre_call +): + from types import SimpleNamespace + from typing import cast + + from fastapi import Request + + from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup + + monkeypatch.setattr("litellm.proxy.proxy_server.premium_user", True) + cg = CustomGuardrail( + guardrail_name="test_guardrail", + supported_event_hooks=[GuardrailEventHooks.pre_call, GuardrailEventHooks.logging_only], + event_hook=Mode(tags={"test_tag": "logging_only"}, default="pre_call"), + default_on=True, + ) + request = cast(Request, SimpleNamespace(state=SimpleNamespace(litellm_baggage_mapped_tags=("test_tag",)))) + data = {"messages": [{"role": "user", "content": "test"}], "metadata": {"tags": []}} + LiteLLMProxyRequestSetup.apply_authenticated_baggage_tags(request, data) + data["metadata"]["caller_tags"] = caller_tags + assert cg.should_run_guardrail(data=data, event_type=GuardrailEventHooks.pre_call) is runs_pre_call + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "team_tags,deployment_tags,runs_post_call", + [ + (["policy:sensitive"], ["usecase:dev"], True), + ([], ["policy:sensitive", "usecase:dev"], True), + (["policy:sensitive", "usecase:dev"], [], True), + ([], ["usecase:dev"], False), + ([], [], True), + ], +) +async def test_baggage_never_changes_the_guardrail_mode_key_team_and_deployment_tags_select( + monkeypatch, team_tags, deployment_tags, runs_post_call +): + from types import SimpleNamespace + from unittest.mock import MagicMock + + import litellm + from litellm.proxy._types import UserAPIKeyAuth + from litellm.proxy.litellm_pre_call_utils import add_litellm_data_to_request + + monkeypatch.setattr("litellm.proxy.proxy_server.premium_user", True) + cg = CustomGuardrail( + guardrail_name="test_guardrail", + supported_event_hooks=[GuardrailEventHooks.post_call, GuardrailEventHooks.logging_only], + event_hook=Mode(tags={"policy:sensitive": "post_call", "usecase:dev": "logging_only"}, default="post_call"), + default_on=True, + ) + router = litellm.Router( + model_list=[{"model_name": "gpt-4", "litellm_params": {"model": "gpt-4o", "tags": deployment_tags}}] + ) + + async def runs_post_call_guardrail(baggage_tags: tuple[str, ...]) -> bool: + request = MagicMock() + request.url.path = "/chat/completions" + request.method = "POST" + request.query_params = {} + request.headers = {"Content-Type": "application/json"} + request.client.host = "127.0.0.1" + request.state = SimpleNamespace(litellm_baggage_mapped_tags=baggage_tags) + data = await add_litellm_data_to_request( + data={"model": "gpt-4", "messages": [{"role": "user", "content": "test"}]}, + request=request, + user_api_key_dict=UserAPIKeyAuth(api_key="hashed-key", team_metadata={"tags": team_tags}), + proxy_config=MagicMock(), + general_settings={}, + ) + await router.acompletion(**data, mock_response="hi") + return cg.should_run_guardrail(data=data, event_type=GuardrailEventHooks.post_call) + + assert await runs_post_call_guardrail(()) is runs_post_call + assert await runs_post_call_guardrail(("usecase:dev",)) is runs_post_call diff --git a/tests/unit/experimental_mcp_client/test_mcp_client.py b/tests/unit/experimental_mcp_client/test_mcp_client.py index 6ea76a0a8a7..b4485bcc5f1 100644 --- a/tests/unit/experimental_mcp_client/test_mcp_client.py +++ b/tests/unit/experimental_mcp_client/test_mcp_client.py @@ -34,6 +34,7 @@ from mcp.types import ( InitializeResult, JSONRPCError, JSONRPCMessage, + JSONRPCNotification, JSONRPCRequest, JSONRPCResponse, LoggingMessageNotificationParams, @@ -61,8 +62,10 @@ from litellm.experimental_mcp_client.client import ( strip_auth_scheme, ) from litellm.proxy._experimental.mcp_server.faults.list_outcomes import ( + ServerListFault, classify_list_exception, list_fault_http_status, + upstream_rate_limit, ) from litellm.proxy._experimental.mcp_server.mcp_server_manager import ( _format_byok_openapi_auth_header, @@ -305,6 +308,36 @@ class _MockTransportClient(MCPClient): return streamable_http_client(self.server_url, http_client=http_client), http_client +def _post_status_responder(failure_method: str, status_code: int) -> Callable[[httpx2.Request], httpx2.Response]: + def respond(request: httpx2.Request) -> httpx2.Response: + if request.method != "POST": + return httpx2.Response(200) + payload: Final = _JSONRPC_MESSAGE_ADAPTER.validate_json(request.content) + assert isinstance(payload, (JSONRPCRequest, JSONRPCNotification)) + if payload.method == "initialize": + assert isinstance(payload, JSONRPCRequest) + return httpx2.Response( + 200, + json={ + "jsonrpc": "2.0", + "id": payload.id, + "result": { + "protocolVersion": LATEST_HANDSHAKE_VERSION, + "capabilities": {"tools": {}}, + "serverInfo": {"name": "status", "version": "1"}, + }, + }, + ) + if payload.method == failure_method: + return httpx2.Response(status_code, headers={"Retry-After": "7"}) + if payload.method == "tools/list": + assert isinstance(payload, JSONRPCRequest) + return httpx2.Response(200, json={"jsonrpc": "2.0", "id": payload.id, "result": {"tools": []}}) + return httpx2.Response(202) + + return respond + + class _FakeExceptionGroup(Exception): """Duck-typed stand-in for an anyio/builtin ExceptionGroup. @@ -1467,8 +1500,8 @@ def test_mcp_extra_matches_proxy_extra_and_supports_streamable_http(): } specifier: Final = Requirement(mcp_extra["mcp"]).specifier - assert not specifier.contains("1.28.1") - assert specifier.contains("2.2.0") + assert not specifier.contains("2.2.0") + assert specifier.contains("2.3.0") with (pyproject_path.parent / "uv.lock").open("rb") as f: locked = tomllib.load(f) mcp_versions: Final = [package["version"] for package in locked["package"] if package["name"] == "mcp"] @@ -1862,6 +1895,32 @@ async def test_http_response_handler_preserves_success_and_http_errors(status_co assert caught.value.response.status_code == status_code +@pytest.mark.asyncio +@pytest.mark.parametrize( + "failure_method,status_code", + [ + ("notifications/initialized", 429), + ("notifications/initialized", 503), + ("tools/list", 429), + ], +) +async def test_list_tools_classifies_upstream_status_for_post_failures(failure_method: str, status_code: int) -> None: + client: Final = _MockTransportClient( + _post_status_responder(failure_method, status_code), + server_url="https://example.com/mcp", + ) + with pytest.raises(httpx2.HTTPStatusError) as caught: + await client.list_tools(raise_on_error=True) + + assert classify_list_exception(caught.value) == ServerListFault(tag="upstream_error", status_code=status_code) + rate_limit: Final = upstream_rate_limit(caught.value) + if status_code == 429: + assert rate_limit is not None + assert rate_limit.retry_after_seconds == 7 + else: + assert rate_limit is None + + @pytest.mark.asyncio async def test_http_status_check_allows_auth_refresh_before_rejecting() -> None: from litellm.proxy._experimental.mcp_server.outbound_credentials.client_credentials import ( @@ -4388,6 +4447,35 @@ async def test_persistent_tool_call_preserves_upstream_http_status_error() -> No await asyncio.wait_for(session.wait_closed(), 5) +@pytest.mark.asyncio +@pytest.mark.parametrize("status_code", [429, 503]) +async def test_persistent_tool_call_classifies_initialized_notification_status(status_code: int) -> None: + client: Final = _MockTransportClient( + _post_status_responder("notifications/initialized", status_code), + server_url="https://example.com/mcp", + ) + session: Final = client.open_persistent_session() + try: + with pytest.raises(httpx2.HTTPStatusError) as caught: + await client.call_tool( + CallToolRequestParams(name="protected_tool", arguments={}), + raise_on_error=True, + persistent_session=session, + ) + + assert classify_list_exception(caught.value) == ServerListFault(tag="upstream_error", status_code=status_code) + rate_limit: Final = upstream_rate_limit(caught.value) + if status_code == 429: + assert rate_limit is not None + assert rate_limit.retry_after_seconds == 7 + else: + assert rate_limit is None + finally: + if not session.closed: + session.close() + await asyncio.wait_for(session.wait_closed(), 5) + + @pytest.mark.asyncio async def test_persistent_session_remaps_stream_error_over_mcp_error() -> None: app: Final = _stateful_upstream() diff --git a/tests/unit/extraction/__init__.py b/tests/unit/extraction/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/unit/extraction/test_main.py b/tests/unit/extraction/test_main.py new file mode 100644 index 00000000000..584ed9cbb91 --- /dev/null +++ b/tests/unit/extraction/test_main.py @@ -0,0 +1,422 @@ +from __future__ import annotations + +import asyncio +import json +import re +from collections.abc import Mapping +from types import MappingProxyType +from typing import Final + +import httpx +import pytest +import respx + +import litellm +from litellm.integrations.custom_logger import CustomLogger +from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER +from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler +from litellm.types.extraction import ExtractionResponse + +_CLAIRIC_URL: Final = "https://api.cloudflare.com/client/v4/accounts/acct/ai/run/@cf/cloudflare/clairic" +_STATE: Final = "Invoice #4471 from Acme Tools, dated 2026-03-03. 12 hammers. Total $174. Payment due in 30 days." +_FIELDS: Final[Mapping[str, Mapping[str, object]]] = MappingProxyType( + { + "vendor": {"type": "text", "instructions": "Who sent the invoice?"}, + "invoice_date": {"type": "date"}, + "total": {"type": "number", "unit": "USD"}, + "items": {"type": "list", "items": "text"}, + "days_to_pay": {"type": "estimate", "min": 0, "max": 90, "provider_field": "kept"}, + } +) +_INPUT_TOKENS: Final = 416 +_RESULT: Final[Mapping[str, object]] = { + "model": "clairic", + "answers": { + "vendor": { + "type": "text", + "p_null": 0.0177, + "span": [19, 29], + "guess": "Acme Tools", + "confidence": 0.9998, + "value": "Acme Tools", + }, + "invoice_date": {"type": "date", "p_null": 6.4e-07, "confidence": 0.99, "value": "2026-03-03"}, + "total": {"type": "number", "p_null": 4.2e-07, "guess": 174, "confidence": 0.99, "value": 174}, + "items": {"type": "list", "value": ["12", "hammers"], "spans": [[51, 53], [54, 61]], "confidence": 0.07}, + "days_to_pay": { + "type": "estimate", + "value": 31, + "mean": 30.76, + "median": 30, + "p10": 29, + "p90": 34, + "p_below": 1.2e-06, + "p_above": 1.2e-06, + }, + }, + "truncated": False, + "usage": { + "state_tokens": 52, + "image_tokens": 0, + "schema_tokens": 312, + "input_tokens": _INPUT_TOKENS, + "output_tokens": 0, + "passes": 2, + }, +} +_ENVELOPE: Final[Mapping[str, object]] = {"result": _RESULT, "success": True, "errors": [], "messages": []} +_PNG_DATA_URL: Final = "data:image/png;base64,AA==" + + +@pytest.fixture(autouse=True) +def _httpx_transport(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + litellm.in_memory_llm_clients_cache.flush_cache() + + +@pytest.fixture +def cloudflare_env(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setenv("CLOUDFLARE_ACCOUNT_ID", "acct") + monkeypatch.setenv("CLOUDFLARE_API_KEY", "cloudflare-key") + monkeypatch.delenv("CLOUDFLARE_API_BASE", raising=False) + + +def _assert_invoice_answers(response: ExtractionResponse) -> None: + assert response.answers["vendor"].value == "Acme Tools" + assert response.answers["vendor"].span == (19, 29) + assert response.answers["items"].spans == ((51, 53), (54, 61)) + assert response.answers["days_to_pay"].median == 30 + assert response.usage.input_tokens == _INPUT_TOKENS + assert response.usage.schema_tokens == 312 + assert response.truncated is False + + +@pytest.mark.asyncio +@pytest.mark.parametrize("model", ("cloudflare/clairic", "cloudflare/@cf/cloudflare/clairic")) +@pytest.mark.usefixtures("cloudflare_env") +async def test_clairic_forwards_the_caller_body_and_unwraps_the_envelope( + respx_mock: respx.MockRouter, model: str +) -> None: + route: Final = respx_mock.post(_CLAIRIC_URL).respond(json=_ENVELOPE) + + response: Final = await litellm.aextraction( + model=model, + state=_STATE, + fields=_FIELDS, + images=[_PNG_DATA_URL, {"content_type": "image/jpeg", "base64": "AA=="}], + reference_date="2026-03-04", + options={"include_quantiles": True}, + ) + + assert route.call_count == 1 + request: Final = route.calls[0].request + assert request.headers["authorization"] == "Bearer cloudflare-key" + assert json.loads(request.content) == { + "model": "clairic", + "state": _STATE, + "fields": _FIELDS, + "images": [_PNG_DATA_URL, {"content_type": "image/jpeg", "base64": "AA=="}], + "reference_date": "2026-03-04", + "options": {"include_quantiles": True}, + } + _assert_invoice_answers(response) + assert response.model == model + assert response.hidden_params["model"] == "cloudflare/@cf/cloudflare/clairic" + assert response.model_dump(mode="json", exclude={"model"}) == { + key: value for key, value in _RESULT.items() if key != "model" + } + + +@pytest.mark.usefixtures("cloudflare_env") +def test_sync_extraction_reads_an_unwrapped_result(respx_mock: respx.MockRouter) -> None: + route: Final = respx_mock.post(_CLAIRIC_URL).respond(json=_RESULT) + + response: Final = litellm.extraction(model="cloudflare/clairic", state=_STATE, fields=_FIELDS) + + assert route.call_count == 1 + assert json.loads(route.calls[0].request.content) == {"model": "clairic", "state": _STATE, "fields": _FIELDS} + _assert_invoice_answers(response) + + +def _clairic_transport() -> httpx.MockTransport: + def respond(request: httpx.Request) -> httpx.Response: + assert str(request.url) == _CLAIRIC_URL + return httpx.Response(200, json=_ENVELOPE) + + return httpx.MockTransport(respond) + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("cloudflare_env") +async def test_async_extraction_sends_through_the_callers_client(respx_mock: respx.MockRouter) -> None: + response: Final = await litellm.aextraction( + model="cloudflare/clairic", + state=_STATE, + fields=_FIELDS, + client=AsyncHTTPHandler(transport=_clairic_transport()), + ) + + assert len(respx_mock.calls) == 0 + _assert_invoice_answers(response) + + +@pytest.mark.usefixtures("cloudflare_env") +def test_sync_extraction_sends_through_the_callers_client(respx_mock: respx.MockRouter) -> None: + response: Final = litellm.extraction( + model="cloudflare/clairic", + state=_STATE, + fields=_FIELDS, + client=HTTPHandler(client=httpx.Client(transport=_clairic_transport())), + ) + + assert len(respx_mock.calls) == 0 + _assert_invoice_answers(response) + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("cloudflare_env") +async def test_a_cloudflare_bad_input_is_a_bad_request_with_the_cloudflare_message( + respx_mock: respx.MockRouter, +) -> None: + respx_mock.post(_CLAIRIC_URL).respond( + status_code=400, + json={ + "errors": [{"message": "AiError: Bad input: fields.total.decimals must be 0 to 6", "code": 5006}], + "success": False, + "result": {}, + "messages": [], + }, + ) + + with pytest.raises(litellm.BadRequestError, match=re.escape("fields.total.decimals must be 0 to 6")): + await litellm.aextraction( + model="cloudflare/clairic", state=_STATE, fields={"total": {"type": "number", "decimals": 9}} + ) + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("fields", "images"), + ( + ({}, None), + ({"total": {"type": "money"}}, None), + ({"bad name": {"type": "text"}}, None), + ({"total": {"type": "number"}}, ["https://example.com/invoice.png"]), + ({"total": {"type": "number"}}, [_PNG_DATA_URL] * 5), + ), + ids=("no_fields", "unknown_type", "invalid_field_name", "remote_image", "too_many_images"), +) +@pytest.mark.usefixtures("cloudflare_env") +async def test_an_invalid_request_is_refused_before_http( + respx_mock: respx.MockRouter, fields: Mapping[str, object], images: list[str] | None +) -> None: + with pytest.raises(litellm.BadRequestError, match="Invalid Extraction request"): + await litellm.aextraction(model="cloudflare/clairic", state=_STATE, fields=fields, images=images) + + assert len(respx_mock.calls) == 0 + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("unset", "message"), + ( + ("CLOUDFLARE_ACCOUNT_ID", "Missing CLOUDFLARE_ACCOUNT_ID - set CLOUDFLARE_ACCOUNT_ID"), + ("CLOUDFLARE_API_KEY", "Missing API key for Extraction provider 'cloudflare'"), + ), +) +@pytest.mark.usefixtures("cloudflare_env") +async def test_missing_cloudflare_credentials_are_refused_before_http( + monkeypatch: pytest.MonkeyPatch, respx_mock: respx.MockRouter, unset: str, message: str +) -> None: + monkeypatch.delenv(unset) + + with pytest.raises(litellm.BadRequestError, match=message): + await litellm.aextraction(model="cloudflare/clairic", state=_STATE, fields=_FIELDS) + + assert len(respx_mock.calls) == 0 + + +@pytest.mark.asyncio +async def test_a_provider_without_extraction_is_refused(respx_mock: respx.MockRouter) -> None: + with pytest.raises(litellm.BadRequestError, match=r"Unknown Extraction provider 'openai'\. Supported.*cloudflare"): + await litellm.aextraction(model="openai/gpt-5.5", state=_STATE, fields=_FIELDS, api_key="k") + + assert len(respx_mock.calls) == 0 + + +@pytest.mark.asyncio +@pytest.mark.parametrize("model", ("cloudflare/clairic", "cloudflare/@cf/cloudflare/clairic")) +@pytest.mark.usefixtures("cloudflare_env") +async def test_clairic_cost_bills_input_tokens_at_the_cost_map_price(respx_mock: respx.MockRouter, model: str) -> None: + respx_mock.post(_CLAIRIC_URL).respond(json=_ENVELOPE) + + response: Final = await litellm.aextraction(model=model, state=_STATE, fields=_FIELDS) + + expected_cost: Final = _INPUT_TOKENS * float(litellm.model_cost[model]["input_cost_per_token"]) + assert expected_cost > 0 + assert litellm.completion_cost(completion_response=response) == pytest.approx(expected_cost) + assert response.hidden_params["response_cost"] == pytest.approx(expected_cost) + + +@pytest.mark.asyncio +async def test_router_extraction_sends_the_deployment_model_and_credentials(respx_mock: respx.MockRouter) -> None: + router: Final = litellm.Router( + model_list=[ + { + "model_name": "invoice-reader", + "litellm_params": { + "model": "cloudflare/clairic", + "api_key": "deployment-key", + "api_base": "https://api.cloudflare.com/client/v4/accounts/acct/ai/v1", + "additional_drop_params": ["temperature"], + }, + } + ] + ) + route: Final = respx_mock.post(_CLAIRIC_URL).respond(json=_ENVELOPE) + + response: Final = await router.aextraction(model="invoice-reader", state=_STATE, fields=_FIELDS) + + assert route.call_count == 1 + assert route.calls[0].request.headers["authorization"] == "Bearer deployment-key" + assert json.loads(route.calls[0].request.content) == {"model": "clairic", "state": _STATE, "fields": _FIELDS} + assert response.model == "cloudflare/clairic" + _assert_invoice_answers(response) + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("cloudflare_env") +async def test_litellm_params_stay_local(respx_mock: respx.MockRouter) -> None: + route: Final = respx_mock.post(_CLAIRIC_URL).respond(json=_ENVELOPE) + + await litellm.aextraction( + model="cloudflare/clairic", + state=_STATE, + fields=_FIELDS, + metadata={"team": "billing"}, + num_retries=0, + stream=False, + additional_drop_params=["language"], + ) + + assert json.loads(route.calls[0].request.content) == {"model": "clairic", "state": _STATE, "fields": _FIELDS} + + +@pytest.mark.asyncio +@pytest.mark.parametrize("name", ("language", "priority", "session_id", "mock_delay", "extra_body")) +@pytest.mark.usefixtures("cloudflare_env") +async def test_a_key_clairic_does_not_take_is_refused_before_http_without_drop_params( + respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch, name: str +) -> None: + monkeypatch.setattr(litellm, "drop_params", False) + with pytest.raises(litellm.UnsupportedParamsError, match=re.escape(f"does not support parameters: ['{name}']")): + await litellm.aextraction(model="cloudflare/clairic", state=_STATE, fields=_FIELDS, **{name: "x"}) + + assert len(respx_mock.calls) == 0 + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("cloudflare_env") +async def test_additional_drop_params_drops_only_the_keys_it_names( + respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setattr(litellm, "drop_params", False) + route: Final = respx_mock.post(_CLAIRIC_URL).respond(json=_ENVELOPE) + + await litellm.aextraction( + model="cloudflare/clairic", + state=_STATE, + fields=_FIELDS, + temperature=0.2, + language="en", + additional_drop_params=["temperature", "language"], + ) + with pytest.raises(litellm.UnsupportedParamsError, match=re.escape("does not support parameters: ['seed']")): + await litellm.aextraction( + model="cloudflare/clairic", state=_STATE, fields=_FIELDS, seed=7, additional_drop_params=["temperature"] + ) + + assert route.call_count == 1 + assert json.loads(route.calls[0].request.content) == {"model": "clairic", "state": _STATE, "fields": _FIELDS} + + +class _RecordingLogger(CustomLogger): + def __init__(self) -> None: + super().__init__() + self.standard_logging_object: Mapping[str, object] | None = None + self.stream: object = None + + async def async_log_success_event( + self, kwargs: Mapping[str, object], response_obj: object, start_time: object, end_time: object + ) -> None: + self.stream = kwargs.get("stream") + standard_logging_object: Final = kwargs.get("standard_logging_object") + if isinstance(standard_logging_object, dict): + self.standard_logging_object = standard_logging_object + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("cloudflare_env") +async def test_stream_is_refused_before_http_without_drop_params(respx_mock: respx.MockRouter) -> None: + with pytest.raises(litellm.UnsupportedParamsError, match=re.escape("does not support parameters: ['stream']")): + await litellm.aextraction(model="cloudflare/clairic", state=_STATE, fields=_FIELDS, stream=True) + + assert len(respx_mock.calls) == 0 + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("name", "value"), + (("temperature", 0.2), ("user", "end-user-1"), ("seed", 7), ("response_format", {"type": "json_object"})), +) +@pytest.mark.usefixtures("cloudflare_env") +async def test_openai_generation_params_are_refused_before_http_without_drop_params( + respx_mock: respx.MockRouter, name: str, value: object +) -> None: + with pytest.raises(litellm.UnsupportedParamsError, match=re.escape(f"does not support parameters: ['{name}']")): + await litellm.aextraction(model="cloudflare/clairic", state=_STATE, fields=_FIELDS, **{name: value}) + + assert len(respx_mock.calls) == 0 + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("cloudflare_env") +async def test_openai_generation_params_are_dropped_with_drop_params(respx_mock: respx.MockRouter) -> None: + route: Final = respx_mock.post(_CLAIRIC_URL).respond(json=_ENVELOPE) + + await litellm.aextraction( + model="cloudflare/clairic", + state=_STATE, + fields=_FIELDS, + temperature=0.2, + user="end-user-1", + seed=7, + drop_params=True, + ) + + assert json.loads(route.calls[0].request.content) == {"model": "clairic", "state": _STATE, "fields": _FIELDS} + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("cloudflare_env") +async def test_a_dropped_stream_is_sent_and_logged_as_a_billed_non_stream_call( + respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch +) -> None: + route: Final = respx_mock.post(_CLAIRIC_URL).respond(json=_ENVELOPE) + recording_logger: Final = _RecordingLogger() + monkeypatch.setattr(litellm, "callbacks", [recording_logger]) + + response: Final = await litellm.aextraction( + model="cloudflare/clairic", state=_STATE, fields=_FIELDS, stream=True, drop_params=True + ) + await asyncio.sleep(0) + GLOBAL_LOGGING_WORKER.start() + await asyncio.wait_for(GLOBAL_LOGGING_WORKER.flush(), timeout=10.0) + + assert "stream" not in json.loads(route.calls[0].request.content) + _assert_invoice_answers(response) + logged: Final = recording_logger.standard_logging_object + assert logged is not None + assert recording_logger.stream is False + assert response.hidden_params["response_cost"] > 0 + assert logged["response_cost"] == pytest.approx(response.hidden_params["response_cost"]) diff --git a/tests/unit/google_genai/test_google_genai_streaming_iterator.py b/tests/unit/google_genai/test_google_genai_streaming_iterator.py index e8ec2848233..120c99b6e42 100644 --- a/tests/unit/google_genai/test_google_genai_streaming_iterator.py +++ b/tests/unit/google_genai/test_google_genai_streaming_iterator.py @@ -1,16 +1,55 @@ +import asyncio import json +from datetime import datetime +from typing import Final from unittest.mock import MagicMock +import httpx import pytest from litellm.google_genai.streaming_iterator import ( AsyncGoogleGenAIGenerateContentStreamingIterator, GoogleGenAIGenerateContentStreamingIterator, ) +from litellm.integrations.custom_logger import CustomLogger from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.types.passthrough_endpoints.pass_through_endpoints import EndpointType +class _SuccessRecorder(CustomLogger): + def __init__(self): + super().__init__() + self.logged: list[tuple[datetime, object]] = [] + + async def async_log_success_event( + self, kwargs: dict[str, object], response_obj: object, start_time: datetime, end_time: datetime + ) -> None: + self.logged.append((start_time, kwargs.get("completion_start_time"))) + + +def _logging_obj( + start_time: datetime = datetime(2026, 10, 9, 12, 0, 0), recorder: _SuccessRecorder | None = None +) -> LiteLLMLoggingObj: + logging_obj: Final = LiteLLMLoggingObj( + model="gemini-3.1-flash", + messages=[{"role": "user", "content": "hi"}], + stream=True, + call_type="agenerate_content_stream", + start_time=start_time, + litellm_call_id="google-genai-stream", + function_id="google-genai-stream", + dynamic_async_success_callbacks=[recorder] if recorder else None, + ) + logging_obj.update_environment_variables( + model="gemini-3.1-flash", + user="", + optional_params={}, + litellm_params={"custom_llm_provider": "gemini"}, + custom_llm_provider="gemini", + ) + return logging_obj + + @pytest.mark.parametrize( "custom_llm_provider, expected_endpoint_type", [("gemini", EndpointType.GEMINI), ("vertex_ai", EndpointType.VERTEX_AI)], @@ -31,7 +70,7 @@ def test_streaming_logging_targets_the_provider_that_served_the_request( iterator = iterator_cls( response=MagicMock(), model="gemini-3.1-flash-image", - logging_obj=MagicMock(spec=LiteLLMLoggingObj), + logging_obj=_logging_obj(), generate_content_provider_config=MagicMock(), litellm_metadata={}, custom_llm_provider=custom_llm_provider, @@ -73,7 +112,7 @@ async def test_async_streaming_iterator_yields_complete_sse_events(): iterator = AsyncGoogleGenAIGenerateContentStreamingIterator( response=mock_response, model="gemini-3.1-flash-image-preview", - logging_obj=MagicMock(spec=LiteLLMLoggingObj), + logging_obj=_logging_obj(), generate_content_provider_config=MagicMock(), litellm_metadata={}, custom_llm_provider="gemini", @@ -95,7 +134,7 @@ def test_sync_streaming_iterator_yields_complete_sse_events(): iterator = GoogleGenAIGenerateContentStreamingIterator( response=mock_response, model="gemini-3.1-flash-image-preview", - logging_obj=MagicMock(spec=LiteLLMLoggingObj), + logging_obj=_logging_obj(), generate_content_provider_config=MagicMock(), litellm_metadata={}, custom_llm_provider="gemini", @@ -123,7 +162,7 @@ async def test_async_streaming_iterator_preserves_multi_field_sse_event(): iterator = AsyncGoogleGenAIGenerateContentStreamingIterator( response=mock_response, model="gemini-test", - logging_obj=MagicMock(spec=LiteLLMLoggingObj), + logging_obj=_logging_obj(), generate_content_provider_config=MagicMock(), litellm_metadata={}, custom_llm_provider="gemini", @@ -146,7 +185,7 @@ async def test_async_streaming_iterator_forwards_sse_comment_events(): iterator = AsyncGoogleGenAIGenerateContentStreamingIterator( response=mock_response, model="gemini-test", - logging_obj=MagicMock(spec=LiteLLMLoggingObj), + logging_obj=_logging_obj(), generate_content_provider_config=MagicMock(), litellm_metadata={}, custom_llm_provider="gemini", @@ -154,3 +193,38 @@ async def test_async_streaming_iterator_forwards_sse_comment_events(): chunk = await iterator.__anext__() assert chunk == b": keepalive\n\n" + + +def _gemini_event(text: str, finish_reason: str | None = None) -> str: + candidate: Final = {"content": {"role": "model", "parts": [{"text": text}]}, "index": 0} + payload: Final = { + "candidates": [{**candidate, "finishReason": finish_reason} if finish_reason else candidate], + "usageMetadata": {"promptTokenCount": 3, "candidatesTokenCount": 2, "totalTokenCount": 5}, + "modelVersion": "gemini-3.1-flash", + } + return f"data: {json.dumps(payload)}\n\n" + + +@pytest.mark.asyncio +async def test_async_stream_logs_its_first_chunk_time_measured_from_the_call_start(): + call_start: Final = datetime(2026, 10, 9, 12, 0, 0) + recorder: Final = _SuccessRecorder() + logging_obj: Final = _logging_obj(call_start, recorder) + response: Final = httpx.Response(200, content=(_gemini_event("Hel") + _gemini_event("lo", "STOP")).encode()) + iterator: Final = AsyncGoogleGenAIGenerateContentStreamingIterator( + response=response, + model="gemini-3.1-flash", + logging_obj=logging_obj, + generate_content_provider_config=MagicMock(), + litellm_metadata={}, + custom_llm_provider="gemini", + ) + tasks_before: Final = asyncio.all_tasks() + + _ = await iterator.__anext__() + first_chunk_at: Final = logging_obj.completion_start_time + _ = [chunk async for chunk in iterator] + await asyncio.gather(*(asyncio.all_tasks() - tasks_before)) + + assert first_chunk_at is not None + assert recorder.logged == [(call_start, first_chunk_at)] diff --git a/tests/unit/harness/sandbox/test_local.py b/tests/unit/harness/sandbox/test_local.py index 5d08dac13a1..7284a9c1157 100644 --- a/tests/unit/harness/sandbox/test_local.py +++ b/tests/unit/harness/sandbox/test_local.py @@ -1,12 +1,14 @@ +import asyncio import os import sys +from typing import Final import pytest from litellm import sandbox from litellm.harness.errors import SandboxError from litellm.harness.sandbox import LocalSandbox, Process, Sandbox -from litellm.harness.sandbox.local import filtered_environ, is_secret_env_name +from litellm.harness.sandbox.local import collect_output, filtered_environ, is_secret_env_name PY = sys.executable @@ -70,6 +72,31 @@ async def test_run_timeout_kills(sbx): await sbx.run([PY, "-c", "import time;time.sleep(30)"], timeout=0.5) +class _NeverEndingProcess: + def __init__(self) -> None: + self.stdin: asyncio.StreamWriter | None = None + self.stdout: asyncio.StreamReader = asyncio.StreamReader() + self.stderr: asyncio.StreamReader = asyncio.StreamReader() + self.killed: bool = False + + async def wait(self) -> int: + return await asyncio.Future() + + async def kill(self) -> None: + self.killed = True + + +async def test_cancelled_run_stops_its_command() -> None: + proc: Final = _NeverEndingProcess() + run: Final = asyncio.ensure_future(collect_output(proc, ["opencode", "export"], timeout=None)) + await asyncio.sleep(0) + run.cancel() + + with pytest.raises(asyncio.CancelledError): + await run + assert proc.killed + + async def test_missing_binary_raises(sbx): with pytest.raises(SandboxError): await sbx.run(["definitely-not-a-binary-xyz"]) diff --git a/tests/unit/harness/test_endpoint.py b/tests/unit/harness/test_endpoint.py index 8b56debdc29..19bd6d0450e 100644 --- a/tests/unit/harness/test_endpoint.py +++ b/tests/unit/harness/test_endpoint.py @@ -1,7 +1,7 @@ import json import sys from collections.abc import AsyncIterator -from typing import Any +from typing import Any, Final import httpx import pytest @@ -13,13 +13,17 @@ from litellm.harness.endpoint import ( SSEUsageParser, UsageTracker, compute_cost, - usage_from_body, + usage_from_mapping, + usage_mapping_of_body, ) from litellm.harness.errors import HarnessInstallFailed from litellm.harness.context import GatewayTarget from litellm.harness.types import Harness, Usage from litellm.types.utils import ModelResponse, ModelResponseStream +REAL_COST_PER_TOKEN: Final = litellm.cost_per_token +CACHED_MODEL: Final = "claude-haiku-5-5" + GATEWAY = GatewayTarget(api_base="https://gw.example.com", api_key="sk-gateway-secret") ANTHROPIC_SSE = ( @@ -82,7 +86,7 @@ def no_real_cost(monkeypatch: pytest.MonkeyPatch) -> None: monkeypatch.setattr( litellm, "cost_per_token", - lambda model, prompt_tokens, completion_tokens: ( + lambda model, prompt_tokens, completion_tokens, **cache_tokens: ( prompt_tokens * 0.001, completion_tokens * 0.002, ), @@ -294,6 +298,180 @@ async def test_sdk_messages_stream_handles_dicts_and_bytes( assert (ep.usage.input_tokens, ep.usage.output_tokens) == (4, 9) +async def chunks_of(chunks: list[dict[str, object]]) -> AsyncIterator[dict[str, object]]: + for chunk in chunks: + yield chunk + + +@pytest.mark.parametrize( + ("path", "sdk", "chunks"), + [ + ( + "/v1/messages", + (litellm.anthropic.messages, "acreate"), + [ + { + "type": "message_start", + "message": { + "usage": { + "input_tokens": 100, + "cache_read_input_tokens": 800, + "cache_creation_input_tokens": 100, + "output_tokens": 1, + } + }, + }, + {"type": "message_delta", "usage": {"output_tokens": 10}}, + ], + ), + ( + "/chat/completions", + (litellm, "acompletion"), + [ + { + "choices": [], + "usage": { + "prompt_tokens": 1000, + "completion_tokens": 10, + "prompt_tokens_details": {"cached_tokens": 800, "cache_creation_tokens": 100}, + }, + } + ], + ), + ( + "/v1/responses", + (litellm, "aresponses"), + [ + { + "type": "response.completed", + "response": { + "usage": { + "input_tokens": 1000, + "output_tokens": 10, + "input_tokens_details": {"cached_tokens": 800, "cache_creation_tokens": 100}, + } + }, + } + ], + ), + ( + "/chat/completions", + (litellm, "acompletion"), + [ + { + "choices": [], + "usage": { + "prompt_tokens": 1000, + "completion_tokens": 10, + "prompt_tokens_details": {"cached_tokens": 800, "cache_write_tokens": 100}, + }, + } + ], + ), + ( + "/v1/responses", + (litellm, "aresponses"), + [ + { + "type": "response.completed", + "response": { + "usage": { + "input_tokens": 1000, + "output_tokens": 10, + "input_tokens_details": {"cached_tokens": 800, "cache_write_tokens": 100}, + } + }, + } + ], + ), + ], + ids=["messages", "chat", "responses", "chat cache_write_tokens", "responses cache_write_tokens"], +) +async def test_sdk_stream_cost_prices_cached_prompt_tokens_like_litellm( + monkeypatch: pytest.MonkeyPatch, path: str, sdk: tuple[object, str], chunks: list[dict[str, object]] +) -> None: + async def fake_sdk(**kwargs: object) -> AsyncIterator[dict[str, object]]: + return chunks_of(chunks) + + monkeypatch.setattr(litellm, "cost_per_token", REAL_COST_PER_TOKEN) + monkeypatch.setattr(*sdk, fake_sdk) + async with ModelEndpoint(Harness.PI, CACHED_MODEL, None) as ep: + async with httpx.AsyncClient(base_url=ep.url) as client: + await client.post(path, json={"stream": True}, headers=auth(ep)) + cached_price: Final = sum( + REAL_COST_PER_TOKEN( + model=CACHED_MODEL, + prompt_tokens=1000, + completion_tokens=10, + usage_object=litellm.Usage( + prompt_tokens=1000, + completion_tokens=10, + total_tokens=1010, + prompt_tokens_details={"cached_tokens": 800, "cache_creation_tokens": 100}, + ), + ) + ) + assert cached_price < sum(REAL_COST_PER_TOKEN(model=CACHED_MODEL, prompt_tokens=1000, completion_tokens=10)) + assert ep.usage.cost == pytest.approx(cached_price), ( + "SDK mode priced cached prompt tokens at the full input price, overstating the cost of every cached turn" + ) + + +ANTHROPIC_CACHED_USAGE: Final = { + "input_tokens": 100, + "cache_read_input_tokens": 800, + "cache_creation_input_tokens": 100, + "output_tokens": 10, +} + + +def anthropic_cached_sse() -> bytes: + start: Final = {"type": "message_start", "message": {"usage": {**ANTHROPIC_CACHED_USAGE, "output_tokens": 1}}} + delta: Final = {"type": "message_delta", "usage": {"output_tokens": 10}} + return ( + f"event: message_start\ndata: {json.dumps(start)}\n\n" + f"event: message_delta\ndata: {json.dumps(delta)}\n\n" + ).encode() + + +async def anthropic_cached_message(**kwargs: object) -> dict[str, object]: + return {"type": "message", "content": [], "usage": ANTHROPIC_CACHED_USAGE} + + +@pytest.mark.parametrize("route", ["gateway stream", "gateway json", "sdk json"]) +async def test_claude_code_cost_counts_anthropic_cached_prompt_tokens( + monkeypatch: pytest.MonkeyPatch, route: str +) -> None: + monkeypatch.setattr(litellm, "cost_per_token", REAL_COST_PER_TOKEN) + monkeypatch.setattr(litellm.anthropic.messages, "acreate", anthropic_cached_message) + upstream: Final = ( + sse_response(anthropic_cached_sse()) + if route == "gateway stream" + else httpx.Response(200, json={"usage": ANTHROPIC_CACHED_USAGE}) + ) + endpoint: Final = ( + ModelEndpoint(Harness.CLAUDE_CODE, CACHED_MODEL, None) + if route == "sdk json" + else gateway_endpoint(Recorder(upstream), model=CACHED_MODEL) + ) + async with endpoint as ep: + async with httpx.AsyncClient(base_url=ep.url) as client: + await client.post("/v1/messages", json={"stream": route == "gateway stream"}, headers=auth(ep)) + cached_price: Final = sum( + REAL_COST_PER_TOKEN( + model=CACHED_MODEL, + prompt_tokens=1000, + completion_tokens=10, + cache_read_input_tokens=800, + cache_creation_input_tokens=100, + ) + ) + assert cached_price > sum(REAL_COST_PER_TOKEN(model=CACHED_MODEL, prompt_tokens=100, completion_tokens=10)) + assert ep.usage.cost == pytest.approx(cached_price), ( + "Anthropic counts cached prompt tokens outside input_tokens, so leaving them out understates the turn's cost" + ) + + async def test_sdk_error_is_sanitized(monkeypatch: pytest.MonkeyPatch) -> None: async def failing(**kwargs: Any) -> Any: raise litellm.RateLimitError( @@ -330,12 +508,12 @@ def test_load_server_deps_maps_import_error(monkeypatch: pytest.MonkeyPatch) -> def test_usage_helpers() -> None: - assert usage_from_body({"usage": {"prompt_tokens": 1, "completion_tokens": 2}}) == ( + assert usage_from_mapping(usage_mapping_of_body({"usage": {"prompt_tokens": 1, "completion_tokens": 2}})) == ( 1, 2, ) - assert usage_from_body({"response": {"usage": {"input_tokens": 3}}}) == (3, 0) - assert usage_from_body("nope") == (0, 0) + assert usage_from_mapping(usage_mapping_of_body({"response": {"usage": {"input_tokens": 3}}})) == (3, 0) + assert usage_from_mapping(usage_mapping_of_body("nope")) == (0, 0) parser = SSEUsageParser() for i in range(0, len(ANTHROPIC_SSE), 7): # split across arbitrary chunk borders diff --git a/tests/unit/harness/test_init.py b/tests/unit/harness/test_init.py index 75ec3b60c74..f70d565fdec 100644 --- a/tests/unit/harness/test_init.py +++ b/tests/unit/harness/test_init.py @@ -34,6 +34,7 @@ PUBLIC_NAMES = [ "ClaudeCodeOptions", "CodexOptions", "OpenCodeOptions", + "PiOptions", "DeepAgentsOptions", "ToolLoopOptions", "HarnessError", diff --git a/tests/unit/harness/test_options.py b/tests/unit/harness/test_options.py new file mode 100644 index 00000000000..b2890de40d8 --- /dev/null +++ b/tests/unit/harness/test_options.py @@ -0,0 +1,24 @@ +import copy +import dataclasses +from collections.abc import Mapping +from typing import Final, get_args + +import pytest + +from litellm.harness.options import HarnessOptions + + +@pytest.mark.parametrize("options_type", get_args(HarnessOptions), ids=lambda t: t.__name__) +def test_default_options_survive_deepcopy_and_asdict(options_type: type) -> None: + options: Final = options_type() + assert copy.deepcopy(options) == options + assert dataclasses.asdict(options) == vars(options) + + +@pytest.mark.parametrize("options_type", get_args(HarnessOptions), ids=lambda t: t.__name__) +def test_each_options_instance_gets_its_own_empty_mappings(options_type: type) -> None: + first: Final = vars(options_type()) + second: Final = vars(options_type()) + mapping_names: Final = tuple(name for name, value in first.items() if isinstance(value, Mapping)) + assert {name: first[name] for name in mapping_names} == dict.fromkeys(mapping_names, {}) + assert [name for name in mapping_names if first[name] is second[name]] == [], "defaults shared between instances" diff --git a/tests/unit/harness/test_types.py b/tests/unit/harness/test_types.py index e59c4e983fb..f13469dfe5a 100644 --- a/tests/unit/harness/test_types.py +++ b/tests/unit/harness/test_types.py @@ -30,6 +30,7 @@ def test_harness_is_plain_enum(): ("codex", "Harness.CODEX"), ("claude-code", "Harness.CLAUDE_CODE"), ("OPENCODE", "Harness.OPENCODE"), + ("pi", "Harness.PI"), ], ) def test_require_harness_hint(given, hint): diff --git a/tests/unit/integrations/arize/test_arize_utils.py b/tests/unit/integrations/arize/test_arize_utils.py index 0d833b90148..31699359bbe 100644 --- a/tests/unit/integrations/arize/test_arize_utils.py +++ b/tests/unit/integrations/arize/test_arize_utils.py @@ -1,5 +1,6 @@ import json -from typing import Optional +from collections.abc import Mapping +from typing import Final, Optional # Adds the grandparent directory to sys.path to allow importing project modules @@ -7,6 +8,7 @@ import asyncio import httpx import pytest +from opentelemetry.sdk.trace import TracerProvider import litellm from litellm.integrations._types.open_inference import ( @@ -17,7 +19,7 @@ from litellm.integrations._types.open_inference import ( from litellm.integrations.arize._utils import _coerce_response_obj_for_attrs, _parse_passthrough_response from litellm.integrations.arize.arize import ArizeLogger from litellm.integrations.custom_logger import CustomLogger -from litellm.types.utils import Choices, StandardCallbackDynamicParams +from litellm.types.utils import Choices, ModelResponse, StandardCallbackDynamicParams def test_arize_set_attributes(): @@ -1015,6 +1017,55 @@ def test_arize_emits_response_cost(): assert attrs["llm.response.cost"] == 0.0012345 # legacy key still emitted +_PRICE_LOOKUP_FAILED: Final = {"error_str": "This model isn't mapped yet. model=openai/unpriced-model", "traceback_str": ""} + + +@pytest.mark.parametrize( + ("cost_fields", "expected_cost"), + [ + pytest.param({"response_cost": 0.0}, 0.0, id="free-model"), + pytest.param( + {"response_cost": 0.0, "response_cost_failure_debug_info": _PRICE_LOOKUP_FAILED}, + None, + id="unpriced", + ), + pytest.param( + {"response_cost": 0.0, "response_cost_failure_debug_info": _PRICE_LOOKUP_FAILED, "cache_hit": True}, + 0.0, + id="unpriced-cache-hit", + ), + pytest.param({"response_cost": "not-a-number"}, None, id="malformed-cost"), + pytest.param( + {"response_cost": 0.002, "response_cost_failure_debug_info": _PRICE_LOOKUP_FAILED}, + None, + id="unpriced-with-guardrail-fee", + ), + ], +) +def test_arize_cost_attrs_tell_unpriced_call_from_free_call( + cost_fields: Mapping[str, object], expected_cost: float | None +) -> None: + span: Final = TracerProvider().get_tracer(__name__).start_span("litellm_request") + kwargs: Final = { + "model": "unpriced-model", + "messages": [{"role": "user", "content": "hi"}], + "standard_logging_object": {"model_parameters": {}, "metadata": {}, "call_type": "completion", **cost_fields}, + "optional_params": {}, + "litellm_params": {"custom_llm_provider": "openai"}, + } + response_obj: Final = ModelResponse( + usage={"total_tokens": 30, "completion_tokens": 20, "prompt_tokens": 10}, + choices=[Choices(message={"role": "assistant", "content": "ok"})], + model="unpriced-model", + id="r4", + ) + + ArizeLogger.set_arize_attributes(span, kwargs, response_obj) + + assert span.attributes.get("llm.cost.total") == expected_cost + assert span.attributes.get("llm.response.cost") == expected_cost + + def test_arize_passthrough_bedrock_anthropic_normalization(): """Bedrock-Anthropic passthrough: input/output text must be set so the span renders something other than raw provider attrs.""" diff --git a/tests/unit/integrations/gcs_pubsub/spend_logs_payload.json b/tests/unit/integrations/gcs_pubsub/spend_logs_payload.json index cfdf707c977..6e5461c3b60 100644 --- a/tests/unit/integrations/gcs_pubsub/spend_logs_payload.json +++ b/tests/unit/integrations/gcs_pubsub/spend_logs_payload.json @@ -11,7 +11,7 @@ "user": "", "team_id": "", "organization_id": "", - "metadata": "{\"actor_agent_id\": null, \"target_agent_id\": null, \"billing_agent_id\": null, \"agent_execution_mode\": null, \"verified_human_user_id\": null, \"used_client_oauth_token\": null, \"applied_guardrails\": [], \"attempted_fallbacks\": null, \"original_model_group\": null, \"batch_models\": null, \"batch_successful_requests\": null, \"batch_failed_requests\": null, \"mcp_tool_call_metadata\": null, \"vector_store_request_metadata\": null, \"routing_decision\": null, \"internal_call_origin\": null, \"litellm_roi_estimator\": false, \"router_metadata\": null, \"autorouter_savings_estimate\": null, \"autorouter_baseline_observation\": null, \"azure_spillover\": null, \"guardrail_information\": null, \"compression_savings\": null, \"litellm_gateway_injected_cache\": null, \"usage_object\": {\"completion_tokens\": 20, \"prompt_tokens\": 10, \"total_tokens\": 30, \"completion_tokens_details\": null, \"prompt_tokens_details\": null}, \"model_map_information\": {\"model_map_key\": \"gpt-4o\", \"model_map_value\": {\"key\": \"gpt-4o\", \"max_tokens\": 16384, \"max_input_tokens\": 128000, \"max_output_tokens\": 16384, \"input_cost_per_token\": 2.5e-06, \"cache_creation_input_token_cost\": null, \"cache_read_input_token_cost\": 1.25e-06, \"input_cost_per_character\": null, \"input_cost_per_token_above_128k_tokens\": null, \"input_cost_per_token_above_200k_tokens\": null, \"input_cost_per_query\": null, \"input_cost_per_second\": null, \"input_cost_per_audio_token\": null, \"input_cost_per_token_batches\": 1.25e-06, \"output_cost_per_token_batches\": 5e-06, \"output_cost_per_token\": 1e-05, \"output_cost_per_audio_token\": null, \"output_cost_per_character\": null, \"output_cost_per_token_above_128k_tokens\": null, \"output_cost_per_character_above_128k_tokens\": null, \"output_cost_per_token_above_200k_tokens\": null, \"output_cost_per_second\": null, \"output_cost_per_image\": null, \"output_vector_size\": null, \"litellm_provider\": \"openai\", \"mode\": \"chat\", \"supports_system_messages\": true, \"supports_response_schema\": true, \"supports_vision\": true, \"supports_function_calling\": true, \"supports_tool_choice\": true, \"supports_assistant_prefill\": false, \"supports_prompt_caching\": true, \"supports_audio_input\": false, \"supports_audio_output\": false, \"supports_pdf_input\": false, \"supports_embedding_image_input\": false, \"supports_native_streaming\": null, \"supports_web_search\": true, \"supports_reasoning\": false, \"search_context_cost_per_query\": {\"search_context_size_low\": 0.03, \"search_context_size_medium\": 0.035, \"search_context_size_high\": 0.05}, \"tpm\": null, \"rpm\": null, \"supported_openai_params\": [\"frequency_penalty\", \"logit_bias\", \"logprobs\", \"top_logprobs\", \"max_tokens\", \"max_completion_tokens\", \"modalities\", \"prediction\", \"n\", \"presence_penalty\", \"seed\", \"stop\", \"stream\", \"stream_options\", \"temperature\", \"top_p\", \"tools\", \"tool_choice\", \"function_call\", \"functions\", \"max_retries\", \"extra_headers\", \"parallel_tool_calls\", \"audio\", \"response_format\", \"user\"]}}, \"additional_usage_values\": {\"completion_tokens_details\": null, \"prompt_tokens_details\": null}, \"user_api_key\": null, \"user_api_key_alias\": null, \"user_api_key_team_id\": null, \"user_api_key_project_id\": null, \"user_api_key_project_alias\": null, \"user_api_key_org_id\": null, \"user_api_key_user_id\": null, \"user_api_key_user_email\": null, \"user_api_key_team_alias\": null, \"spend_logs_metadata\": null, \"requester_ip_address\": null, \"user_agent\": null, \"status\": null, \"proxy_server_request\": null, \"error_information\": null, \"attempted_retries\": null, \"max_retries\": null, \"kubernetes_pod_routing\": null}", + "metadata": "{\"actor_agent_id\": null, \"target_agent_id\": null, \"billing_agent_id\": null, \"agent_execution_mode\": null, \"verified_human_user_id\": null, \"used_client_oauth_token\": null, \"applied_guardrails\": [], \"attempted_fallbacks\": null, \"original_model_group\": null, \"batch_models\": null, \"batch_successful_requests\": null, \"batch_failed_requests\": null, \"mcp_tool_call_metadata\": null, \"vector_store_request_metadata\": null, \"routing_decision\": null, \"internal_call_origin\": null, \"litellm_roi_estimator\": false, \"billed_retry_attempt\": false, \"router_metadata\": null, \"autorouter_savings_estimate\": null, \"autorouter_baseline_observation\": null, \"azure_spillover\": null, \"guardrail_information\": null, \"compression_savings\": null, \"litellm_gateway_injected_cache\": null, \"usage_object\": {\"completion_tokens\": 20, \"prompt_tokens\": 10, \"total_tokens\": 30, \"completion_tokens_details\": null, \"prompt_tokens_details\": null}, \"model_map_information\": {\"model_map_key\": \"gpt-4o\", \"model_map_value\": {\"key\": \"gpt-4o\", \"max_tokens\": 16384, \"max_input_tokens\": 128000, \"max_output_tokens\": 16384, \"input_cost_per_token\": 2.5e-06, \"cache_creation_input_token_cost\": null, \"cache_read_input_token_cost\": 1.25e-06, \"input_cost_per_character\": null, \"input_cost_per_token_above_128k_tokens\": null, \"input_cost_per_token_above_200k_tokens\": null, \"input_cost_per_query\": null, \"input_cost_per_second\": null, \"input_cost_per_audio_token\": null, \"input_cost_per_token_batches\": 1.25e-06, \"output_cost_per_token_batches\": 5e-06, \"output_cost_per_token\": 1e-05, \"output_cost_per_audio_token\": null, \"output_cost_per_character\": null, \"output_cost_per_token_above_128k_tokens\": null, \"output_cost_per_character_above_128k_tokens\": null, \"output_cost_per_token_above_200k_tokens\": null, \"output_cost_per_second\": null, \"output_cost_per_image\": null, \"output_vector_size\": null, \"litellm_provider\": \"openai\", \"mode\": \"chat\", \"supports_system_messages\": true, \"supports_response_schema\": true, \"supports_vision\": true, \"supports_function_calling\": true, \"supports_tool_choice\": true, \"supports_assistant_prefill\": false, \"supports_prompt_caching\": true, \"supports_audio_input\": false, \"supports_audio_output\": false, \"supports_pdf_input\": false, \"supports_embedding_image_input\": false, \"supports_native_streaming\": null, \"supports_web_search\": true, \"supports_reasoning\": false, \"search_context_cost_per_query\": {\"search_context_size_low\": 0.03, \"search_context_size_medium\": 0.035, \"search_context_size_high\": 0.05}, \"tpm\": null, \"rpm\": null, \"supported_openai_params\": [\"frequency_penalty\", \"logit_bias\", \"logprobs\", \"top_logprobs\", \"max_tokens\", \"max_completion_tokens\", \"modalities\", \"prediction\", \"n\", \"presence_penalty\", \"seed\", \"stop\", \"stream\", \"stream_options\", \"temperature\", \"top_p\", \"tools\", \"tool_choice\", \"function_call\", \"functions\", \"max_retries\", \"extra_headers\", \"parallel_tool_calls\", \"audio\", \"response_format\", \"user\"]}}, \"additional_usage_values\": {\"completion_tokens_details\": null, \"prompt_tokens_details\": null}, \"user_api_key\": null, \"user_api_key_alias\": null, \"user_api_key_team_id\": null, \"user_api_key_project_id\": null, \"user_api_key_project_alias\": null, \"user_api_key_org_id\": null, \"user_api_key_user_id\": null, \"user_api_key_user_email\": null, \"user_api_key_team_alias\": null, \"spend_logs_metadata\": null, \"requester_ip_address\": null, \"user_agent\": null, \"status\": null, \"proxy_server_request\": null, \"error_information\": null, \"attempted_retries\": null, \"max_retries\": null, \"kubernetes_pod_routing\": null}", "cache_key": "Cache OFF", "spend": 0.00022500000000000002, "total_tokens": 30, diff --git a/tests/unit/integrations/otel/test_langfuse_logger.py b/tests/unit/integrations/otel/test_langfuse_logger.py index ff2060d91c2..d55f0577e03 100644 --- a/tests/unit/integrations/otel/test_langfuse_logger.py +++ b/tests/unit/integrations/otel/test_langfuse_logger.py @@ -4,6 +4,7 @@ stamped from the request task while the root span is still recording, so Langfus import asyncio import json from collections.abc import AsyncIterator, Mapping, Sequence +from datetime import datetime, timezone from typing import Final import pytest @@ -11,6 +12,7 @@ import pytest pytest.importorskip("opentelemetry") from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter # noqa: E402 +from opentelemetry.trace import SpanKind # noqa: E402 import litellm # noqa: E402 from litellm.caching.dual_cache import DualCache # noqa: E402 @@ -43,6 +45,7 @@ from litellm.types.utils import ( # noqa: E402 INPUT_ATTR: Final = "langfuse.observation.input" OUTPUT_ATTR: Final = "langfuse.observation.output" TRACE_NAME_ATTR: Final = "langfuse.trace.name" +COMPLETION_START_ATTR: Final = "langfuse.observation.completion_start_time" TRACE_CONTROL_ATTRS: Final = (TRACE_NAME_ATTR, "user.id", "session.id", "langfuse.trace.tags") CHAT_DATA: Final = {"model": "gpt-5.4-mini", "messages": [{"role": "user", "content": "ping"}]} @@ -541,3 +544,53 @@ def test_langfuse_otel_preset_builds_a_logger_that_stamps_the_root(monkeypatch): assert INPUT_ATTR in attrs and OUTPUT_ATTR in attrs finally: is_otel_v2_enabled.cache_clear() + + +def _llm_call_kwargs(optional_params: Mapping[str, object], completion_start: datetime | None) -> dict[str, object]: + return { + "standard_logging_object": { + "litellm_call_id": "call_1", + "call_type": "acompletion", + "custom_llm_provider": "openai", + "model": "gpt-5.4-mini", + "stream": bool(optional_params.get("stream")), + "status": "success", + "completionStartTime": datetime(2026, 10, 9, 12, 0, 9, tzinfo=timezone.utc).timestamp(), + }, + "litellm_params": {"metadata": {}}, + "optional_params": optional_params, + "api_call_start_time": datetime(2026, 10, 9, 12, 0, 0, tzinfo=timezone.utc), + "completion_start_time": completion_start, + } + + +def _generation_attrs(kwargs: dict[str, object], *, fail: bool = False) -> Mapping[str, object]: + logger, exporter = _logger() + logger.log_pre_api_call(model="gpt-5.4-mini", messages=[], kwargs=kwargs) + hook: Final = logger.async_log_failure_event if fail else logger.async_log_success_event + asyncio.run(hook(kwargs, None, None, None)) + (generation,) = [span for span in exporter.get_finished_spans() if span.kind is SpanKind.CLIENT] + return dict(generation.attributes or {}) + + +@pytest.mark.parametrize( + "optional_params", + [ + pytest.param({"stream": True}, id="streamed"), + pytest.param({}, id="not_streamed_or_pass_through_stream"), + ], +) +def test_generation_carries_litellms_completion_start_time_like_the_default_emitter( + optional_params: Mapping[str, object], +) -> None: + completion_start: Final = datetime(2026, 10, 9, 12, 0, 0, 250000, tzinfo=timezone.utc) + + attrs: Final = _generation_attrs(_llm_call_kwargs(optional_params, completion_start)) + + assert datetime.fromisoformat(json.loads(attrs[COMPLETION_START_ATTR])) == completion_start + + +def test_failed_generation_without_a_first_chunk_has_no_completion_start_time() -> None: + attrs: Final = _generation_attrs(_llm_call_kwargs({"stream": True}, None), fail=True) + + assert COMPLETION_START_ATTR not in attrs diff --git a/tests/unit/integrations/otel/test_otel_v2_emitter.py b/tests/unit/integrations/otel/test_otel_v2_emitter.py index 0905e9e7c30..6e29b2e9c68 100644 --- a/tests/unit/integrations/otel/test_otel_v2_emitter.py +++ b/tests/unit/integrations/otel/test_otel_v2_emitter.py @@ -2,6 +2,7 @@ legacy dual-emit, hierarchy, error status, and idempotency. Needs the OTel SDK.""" import json +from collections.abc import Mapping from typing import Final import pytest @@ -23,6 +24,7 @@ from litellm.integrations.otel.plumbing import context as ctx_mod # noqa: E402 from litellm.integrations.otel.plumbing import providers # noqa: E402 from litellm.integrations.otel.emitter import SpanEmitter, attribute_budget, span_attribute_limit # noqa: E402 from litellm.integrations.otel.emitter import stamp_error # noqa: E402 +from litellm.integrations.otel.mappers import LangfuseMapper # noqa: E402 # after the opentelemetry importorskip from litellm.integrations.otel.mappers.utils import MAX_TOOL_DEFINITION_ATTRS_PER_SPAN # noqa: E402 from litellm.integrations.otel.model.payloads import ( # noqa: E402 GuardrailSpanData, @@ -91,6 +93,61 @@ def test_llm_call_span_cost_breakdown(): assert f"{LiteLLM.COST_PREFIX}margin_total_amount" not in a +_PRICE_LOOKUP_FAILED: Final = {"error_str": "This model isn't mapped yet. model=openai/unpriced-model", "traceback_str": ""} + + +@pytest.mark.parametrize( + ("cost_fields", "expected_cost"), + [ + pytest.param({"response_cost": 0.0}, 0.0, id="free-model"), + pytest.param( + {"response_cost": 0.0, "response_cost_failure_debug_info": _PRICE_LOOKUP_FAILED}, + None, + id="unpriced", + ), + pytest.param( + {"response_cost": 0.0, "response_cost_failure_debug_info": _PRICE_LOOKUP_FAILED, "cache_hit": True}, + 0.0, + id="unpriced-cache-hit", + ), + ], +) +def test_llm_call_span_tells_unpriced_call_from_free_call( + cost_fields: Mapping[str, object], expected_cost: float | None +) -> None: + engine, exporter = _engine() + data: Final = LLMCallSpanData.from_standard_logging_payload(_payload(**cost_fields)) + + engine.emit(SpanRole.LLM_CALL, data) + + (span,) = exporter.get_finished_spans() + assert span.attributes.get(f"{LiteLLM.COST_PREFIX}total") == expected_cost + langfuse_cost_details: Final = LangfuseMapper().map(data).get("langfuse.observation.cost_details") + langfuse_cost: Final = json.loads(langfuse_cost_details)["total"] if langfuse_cost_details is not None else None + assert langfuse_cost == expected_cost + + +def test_unpriced_call_keeps_the_guardrail_charge_on_the_guardrail_span() -> None: + engine, exporter = _engine() + payload: Final = _payload( + response_cost=0.002, + response_cost_failure_debug_info=_PRICE_LOOKUP_FAILED, + cost_breakdown={"guardrail_cost": 0.002, "total_cost": 0.002}, + ) + + engine.emit(SpanRole.LLM_CALL, LLMCallSpanData.from_standard_logging_payload(payload)) + engine.emit( + SpanRole.GUARDRAIL, + GuardrailSpanData.from_logging_entry( + {"guardrail_name": "bedrock", "guardrail_status": "success", "guardrail_cost": 0.002} + ), + ) + + llm_span, guardrail_span = exporter.get_finished_spans() + assert f"{LiteLLM.COST_PREFIX}total" not in llm_span.attributes + assert guardrail_span.attributes[LiteLLM.GUARDRAIL_COST] == 0.002 + + def test_tracer_scope_carries_litellm_version(): from litellm._version import version as litellm_version diff --git a/tests/unit/integrations/otel/test_otel_v2_logger.py b/tests/unit/integrations/otel/test_otel_v2_logger.py index 10e12981ec1..1f9d3af71d9 100644 --- a/tests/unit/integrations/otel/test_otel_v2_logger.py +++ b/tests/unit/integrations/otel/test_otel_v2_logger.py @@ -1928,6 +1928,7 @@ def test_service_span_is_named_by_purpose_when_the_producer_declares_a_target(): ("async_batch_get_cache", "redis.mget auth_objects", "redis.mget"), ("async_set_cache_pipeline_with_ttls", "redis.set auth_objects", "redis.set"), ("async_increment_pipeline", "redis.incr auth_objects", "redis.incr"), + ("async_increment_if_present", "redis.incr auth_objects", "redis.incr"), ("async_delete_cache", "redis.delete auth_objects", "redis.delete"), ("async_scan_iter", "redis.scan auth_objects", "redis.scan"), ("request_redis_batch", "redis.pipeline auth_objects", "redis.pipeline"), diff --git a/tests/unit/integrations/otel/test_otel_v2_vendor_mappers.py b/tests/unit/integrations/otel/test_otel_v2_vendor_mappers.py index ca7a9b424ad..7e112fcf6a4 100644 --- a/tests/unit/integrations/otel/test_otel_v2_vendor_mappers.py +++ b/tests/unit/integrations/otel/test_otel_v2_vendor_mappers.py @@ -7,6 +7,7 @@ backends, so one trace lights up every configured destination. import json from collections.abc import Mapping +from datetime import datetime, timezone from itertools import chain from typing import Final @@ -580,6 +581,32 @@ def test_langfuse_usage_details_omit_zero_cache_and_reasoning_counts(): assert usage == {"input": 12, "output": 8, "total": 20} +def _langfuse_payload() -> dict[str, object]: + return { + "call_type": "acompletion", + "custom_llm_provider": "openai", + "model": "gpt-4o", + "completionStartTime": 1791547299.0, + } + + +def test_langfuse_mapper_sends_the_completion_start_time_as_the_sdks_json_string(): + data: Final = LLMCallSpanData.from_standard_logging_payload( + _langfuse_payload(), completion_start_seconds=1791547200.25 + ) + + attrs: Final = LangfuseMapper().map(data) + + sent: Final = datetime.fromisoformat(json.loads(attrs["langfuse.observation.completion_start_time"])) + assert sent == datetime(2026, 10, 9, 12, 0, 0, 250000, tzinfo=timezone.utc) + + +def test_langfuse_mapper_ignores_the_payloads_end_time_fallback_when_litellm_recorded_no_completion_start(): + attrs: Final = LangfuseMapper().map(LLMCallSpanData.from_standard_logging_payload(_langfuse_payload())) + + assert "langfuse.observation.completion_start_time" not in attrs + + def test_langfuse_mapper_names_the_trace_from_the_caller(): named = LangfuseMapper().map(_llm_call(trace=TraceControls(name="nightly-eval"))) assert named["langfuse.trace.name"] == "nightly-eval" diff --git a/tests/unit/integrations/test_anthropic_cache_control_hook.py b/tests/unit/integrations/test_anthropic_cache_control_hook.py index 22db24f6ffd..c70c7080ab8 100644 --- a/tests/unit/integrations/test_anthropic_cache_control_hook.py +++ b/tests/unit/integrations/test_anthropic_cache_control_hook.py @@ -1705,6 +1705,39 @@ def test_cache_control_hook_does_not_overwrite_existing_cache_control(): assert _count_cache_control(processed) == 1 +@pytest.mark.parametrize( + "content, marked_parts", + [ + ([{"type": "text", "text": "Checking."}, {"type": "redacted_thinking", "data": "abc"}], [0]), + ([{"type": "redacted_thinking", "data": "abc"}], []), + ([{"type": "thinking", "thinking": "hm", "signature": "s"}], []), + ([{"type": "text", "text": "Checking."}, "not a content block"], [0]), + ], + ids=["text-before-trailing-redacted-thinking", "redacted-thinking-only", "signed-thinking-only", "text-before-a-string"], +) +def test_assistant_injection_never_marks_a_thinking_part( + content: list[dict[str, str] | str], marked_parts: list[int] +): + """Claude 400s a cache_control on a thinking or redacted_thinking block, and Bedrock Converse 400s a cache + point after reasoning, so the breakpoint goes on the last part that can carry one.""" + messages: Final[list[AllMessageValues]] = [ + {"role": "user", "content": "hi"}, + {"role": "assistant", "content": copy.deepcopy(content)}, + {"role": "user", "content": "again"}, + ] + + _, processed, _ = AnthropicCacheControlHook().get_chat_completion_prompt( + model="anthropic/claude-sonnet-4-6", + messages=messages, + non_default_params={"cache_control_injection_points": [{"location": "message", "role": "assistant"}]}, + prompt_id=None, + prompt_variables=None, + dynamic_callback_params={}, + ) + + assert [index for index, part in enumerate(processed[1]["content"]) if "cache_control" in part] == marked_parts + + @pytest.mark.asyncio async def test_cache_control_hook_bedrock_payload_caps_cachepoints_at_four(monkeypatch: pytest.MonkeyPatch): """End-to-end: outgoing Bedrock payload must not exceed 4 cachePoint blocks. diff --git a/tests/unit/integrations/test_langfuse_otel.py b/tests/unit/integrations/test_langfuse_otel.py index 13a49f40d7e..9f536ab0dac 100644 --- a/tests/unit/integrations/test_langfuse_otel.py +++ b/tests/unit/integrations/test_langfuse_otel.py @@ -168,6 +168,31 @@ class TestLangfuseOtelIntegration: assert span.attributes["langfuse.environment"] == "team-a-env" + @pytest.mark.parametrize( + "completion_start_time", + [ + datetime(2026, 10, 9, 12, 0, 0, 250000, tzinfo=timezone.utc), + datetime(2026, 10, 9, 12, 0, 0, 250000), + ], + ids=["aware", "naive_local_time"], + ) + def test_set_langfuse_specific_attributes_completion_start_time(self, completion_start_time: datetime): + """The first-token time goes out the way the Langfuse SDK sends it: a JSON string, with an explicit offset.""" + span: Final = TracerProvider().get_tracer(__name__).start_span("litellm_request") + + LangfuseOtelLogger._set_langfuse_specific_attributes(span, {"completion_start_time": completion_start_time}, {}) + + sent: Final = datetime.fromisoformat(json.loads(span.attributes["langfuse.observation.completion_start_time"])) + assert sent.tzinfo is not None + assert sent.timestamp() == completion_start_time.timestamp() + + def test_set_langfuse_specific_attributes_without_completion_start_time(self): + span: Final = TracerProvider().get_tracer(__name__).start_span("litellm_request") + + LangfuseOtelLogger._set_langfuse_specific_attributes(span, {}, {}) + + assert "langfuse.observation.completion_start_time" not in span.attributes + def test_extract_langfuse_metadata_basic(self): """Ensure metadata is correctly pulled from litellm_params.""" metadata_in = {"generation_name": "my-gen", "custom": "data"} diff --git a/tests/unit/integrations/test_responses_background_cost.py b/tests/unit/integrations/test_responses_background_cost.py index 1bf95e35c4d..7d266c94700 100644 --- a/tests/unit/integrations/test_responses_background_cost.py +++ b/tests/unit/integrations/test_responses_background_cost.py @@ -282,6 +282,12 @@ class TestCheckResponsesCost: client = MagicMock() client.db = MagicMock() client.db.litellm_managedobjecttable = MagicMock() + client.db.litellm_verificationtoken.find_unique = AsyncMock(return_value=None) + client.db.litellm_teamtable.find_unique = AsyncMock(return_value=None) + client.db.litellm_usertable.find_unique = AsyncMock(return_value=None) + client.db.litellm_deprecatedverificationtoken.find_unique = AsyncMock(return_value=None) + client.db.litellm_deletedverificationtoken.find_first = AsyncMock(return_value=None) + client.db.litellm_deletedteamtable.find_first = AsyncMock(return_value=None) return client @pytest.fixture diff --git a/tests/unit/interactions/test_interactions_streaming_iterator.py b/tests/unit/interactions/test_interactions_streaming_iterator.py index c52ab36deaa..afcd0d559d7 100644 --- a/tests/unit/interactions/test_interactions_streaming_iterator.py +++ b/tests/unit/interactions/test_interactions_streaming_iterator.py @@ -5,7 +5,10 @@ async_success_handler (cross-thread pydantic mutation segfaults pydantic-core). """ import asyncio +import json import time +from datetime import datetime +from typing import Final import httpx import pytest @@ -16,6 +19,7 @@ from litellm.interactions import streaming_iterator as interactions_streaming_it from litellm.interactions.streaming_iterator import InteractionsAPIStreamingIterator from litellm.litellm_core_utils import thread_pool_executor as thread_pool_executor_module from litellm.litellm_core_utils.litellm_logging import Logging as LitellmLogging +from litellm.llms.gemini.interactions.transformation import GoogleAIStudioInteractionsConfig from litellm.types.interactions import InteractionsAPIStreamingResponse @@ -97,3 +101,50 @@ async def test_custom_logger_only_never_submits_sync_success_handler(monkeypatch assert recorder.async_hook_fired is True assert recording_executor.submitted_for(logging_obj) == [] + + +class _SuccessRecorder(CustomLogger): + def __init__(self): + super().__init__() + self.logged: list[tuple[datetime, object]] = [] + + async def async_log_success_event( + self, kwargs: dict[str, object], response_obj: object, start_time: datetime, end_time: datetime + ) -> None: + self.logged.append((start_time, kwargs.get("completion_start_time"))) + + +@pytest.mark.asyncio +async def test_stream_logs_its_first_event_time_measured_from_the_call_start(): + call_start: Final = datetime(2026, 10, 9, 12, 0, 0) + recorder: Final = _SuccessRecorder() + logging_obj: Final = LitellmLogging( + model="gemini/gemini-3-pro-preview", + messages=[{"role": "user", "content": "hi"}], + stream=True, + call_type="ainteraction", + start_time=call_start, + litellm_call_id="interactions-stream", + function_id="interactions-stream", + dynamic_async_success_callbacks=[recorder], + ) + events: Final = ( + {"event_type": "step.delta", "id": "interaction-1"}, + {"event_type": "interaction.completed", "id": "interaction-1", "status": "completed"}, + ) + response: Final = httpx.Response(200, content="".join(f"data: {json.dumps(e)}\n\n" for e in events).encode()) + iterator: Final = InteractionsAPIStreamingIterator( + response=response, + model="gemini/gemini-3-pro-preview", + interactions_api_config=GoogleAIStudioInteractionsConfig(), + logging_obj=logging_obj, + ) + tasks_before: Final = asyncio.all_tasks() + + _ = await iterator.__anext__() + first_event_at: Final = logging_obj.completion_start_time + _ = [event async for event in iterator] + await asyncio.gather(*(asyncio.all_tasks() - tasks_before)) + + assert first_event_at is not None + assert recorder.logged == [(call_start, first_event_at)] diff --git a/tests/unit/litellm_core_utils/llm_response_utils/test_response_metadata.py b/tests/unit/litellm_core_utils/llm_response_utils/test_response_metadata.py index 00b0e2f6972..6d9d8c7997a 100644 --- a/tests/unit/litellm_core_utils/llm_response_utils/test_response_metadata.py +++ b/tests/unit/litellm_core_utils/llm_response_utils/test_response_metadata.py @@ -17,6 +17,7 @@ import pytest import litellm import litellm.litellm_core_utils.llm_response_utils.response_metadata as response_metadata_mod import litellm.proxy.common_request_processing as common_request_processing_mod +from litellm.cost_calculator import select_model_name_for_cost_calc from litellm.litellm_core_utils.litellm_logging import Logging from litellm.litellm_core_utils.llm_response_utils.response_metadata import ( ResponseMetadata, @@ -649,3 +650,38 @@ def test_update_response_metadata_prices_per_second_deployment_from_its_stamped_ assert result._response_ms == pytest.approx(2000) assert result._hidden_params["response_cost"] == pytest.approx(0.02 * 2) + + +def test_update_response_metadata_keeps_the_provider_model_after_the_proxy_rewrites_response_model(): + start_time: Final = datetime.datetime(2026, 9, 21, 12, 0, 0) + logging_obj: Final = Logging( + model="azure/ptu-deployment", + messages=[{"role": "user", "content": "Hello"}], + stream=False, + call_type="completion", + start_time=start_time, + litellm_call_id="provider-model-response-metadata", + function_id="f", + ) + logging_obj.update_environment_variables( + model="azure/ptu-deployment", litellm_params={}, optional_params={}, custom_llm_provider="azure" + ) + result: Final = ModelResponse( + model="gpt-5.4-nano-2026-03-17", + usage=Usage(prompt_tokens=11, completion_tokens=7, total_tokens=18), + ) + + update_response_metadata( + result=result, + logging_obj=logging_obj, + model="azure/ptu-deployment", + kwargs={}, + start_time=start_time, + end_time=start_time + datetime.timedelta(seconds=2), + ) + result.model = "model-group-alias" + + assert ( + select_model_name_for_cost_calc(model=None, completion_response=result, custom_llm_provider="azure") + == "azure/gpt-5.4-nano-2026-03-17" + ) diff --git a/tests/unit/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_common_utils.py b/tests/unit/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_common_utils.py index c08eeea4bb9..cc0ef062e4b 100644 --- a/tests/unit/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_common_utils.py +++ b/tests/unit/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_common_utils.py @@ -1085,6 +1085,30 @@ def test_update_responses_input_with_model_file_ids_decodes_xlitellm_encoded_id( assert updated[0]["content"][1]["file_id"] == raw_id + +@pytest.mark.parametrize("unusable_file_id", [[1], {"a": 1}]) +def test_update_responses_input_with_model_file_ids_keeps_a_non_string_file_id_as_sent(unusable_file_id): + from litellm.litellm_core_utils.prompt_templates.common_utils import ( + update_responses_input_with_model_file_ids, + ) + + encoded_id = _xlitellm_encoded("file-ExTuCawUqxEMjVFK6xwR9B", "gpt-5.1") + input_items = [ + { + "role": "user", + "content": [ + {"type": "input_file", "file_id": encoded_id}, + {"type": "input_file", "file_id": unusable_file_id}, + ], + } + ] + + updated = update_responses_input_with_model_file_ids( + input_items, "model-A", {encoded_id: {"model-A": "file-on-a"}} + ) + + assert [item["file_id"] for item in updated[0]["content"]] == ["file-on-a", unusable_file_id] + def test_update_messages_xlitellm_decode_does_not_override_mapping(): """If the call-site already resolved a provider id via the mapping, that wins. The new decode fallback runs only when no mapping match.""" diff --git a/tests/unit/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_factory.py b/tests/unit/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_factory.py index 046f448046b..fad1c6178dc 100644 --- a/tests/unit/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_factory.py +++ b/tests/unit/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_factory.py @@ -541,25 +541,66 @@ def test_bedrock_converse_assistant_with_empty_thinking_block_and_tool_calls(): _NATIVE_REDACTED_DATA: Final = "EmwKAhgBEgy3va3pzix/LafPsn4aDFIT2Xlxh0L5L8rLVyIwxtE3rAFBa8cr3qpP" _CONVERSE_REDACTED_DATA: Final = base64.b64encode(_NATIVE_REDACTED_DATA.encode()).decode() +REASONING_PLACEMENTS: Final = pytest.mark.parametrize( + "placement", ["thinking_blocks", "content", "both", "first-block-in-content", "last-block-in-content"] +) + + +def _assistant_with_reasoning( + placement: str, reasoning: Sequence[Mapping[str, object]], text: str +) -> Mapping[str, object]: + in_content: Final = {"role": "assistant", "content": [*reasoning, {"type": "text", "text": text}]} + return { + "thinking_blocks": {"role": "assistant", "content": text, "thinking_blocks": list(reasoning)}, + "content": in_content, + "both": {**in_content, "thinking_blocks": list(reasoning)}, + "first-block-in-content": { + "role": "assistant", + "content": [*reasoning[:1], {"type": "text", "text": text}], + "thinking_blocks": list(reasoning), + }, + "last-block-in-content": { + "role": "assistant", + "content": [*reasoning[-1:], {"type": "text", "text": text}], + "thinking_blocks": list(reasoning), + }, + }[placement] + + +SPLIT_REASONING: Final = pytest.mark.parametrize( + ("in_content", "in_thinking_blocks"), + [((0, 2), (0, 1, 2)), ((0, 1, 2), (1,))], + ids=["middle-block-only-in-thinking-blocks", "outer-blocks-only-in-content"], +) + + +COPY_TEXT: Final = pytest.mark.parametrize("copy_text", ["", "First"], ids=["emptied", "trimmed"]) + + +def _assistant_with_split_reasoning( + reasoning: Sequence[Mapping[str, object]], in_content: Sequence[int], in_thinking_blocks: Sequence[int], text: str +) -> Mapping[str, object]: + return { + "role": "assistant", + "content": [*(reasoning[index] for index in in_content), {"type": "text", "text": text}], + "thinking_blocks": [reasoning[index] for index in in_thinking_blocks], + } @pytest.mark.asyncio @pytest.mark.parametrize("use_async", [False, True]) -@pytest.mark.parametrize("placement", ["thinking_blocks", "content"]) +@REASONING_PLACEMENTS async def test_bedrock_converse_replays_redacted_thinking_as_redacted_content(use_async: bool, placement: str): """A redacted_thinking block that Bedrock returned must go back as reasoningContent.redactedContent, - in order, ahead of text and toolUse. It used to collapse into an empty unsigned reasoningText and get dropped.""" + in order, ahead of text and toolUse. It used to collapse into an empty unsigned reasoningText and get dropped. + Sent twice, when the history carries it in content and thinking_blocks, Bedrock 400s that it was modified.""" bedrock_reasoning_blocks: Final[list[BedrockConverseReasoningContentBlock]] = [ {"reasoningText": {"text": "Let me look this up.", "signature": "sig-abc"}}, {"redactedContent": _CONVERSE_REDACTED_DATA}, ] thinking_blocks: Final = litellm.AmazonConverseConfig()._transform_thinking_blocks(bedrock_reasoning_blocks) assistant_text: Final = "Checking the weather." - assistant_message: Final = ( - {"role": "assistant", "content": assistant_text, "thinking_blocks": thinking_blocks} - if placement == "thinking_blocks" - else {"role": "assistant", "content": [*thinking_blocks, {"type": "text", "text": assistant_text}]} - ) + assistant_message: Final = _assistant_with_reasoning(placement, thinking_blocks, assistant_text) messages: Final = [ {"role": "user", "content": "What's the weather in Paris?"}, { @@ -593,6 +634,231 @@ async def test_bedrock_converse_replays_redacted_thinking_as_redacted_content(us ] +@pytest.mark.asyncio +@pytest.mark.parametrize("use_async", [False, True]) +@COPY_TEXT +async def test_bedrock_converse_sends_a_signed_block_once_when_thinking_blocks_holds_other_text( + use_async: bool, copy_text: str +): + bedrock_reasoning_blocks: Final[list[BedrockConverseReasoningContentBlock]] = [ + {"reasoningText": {"text": "First.", "signature": "sig-1"}}, + {"redactedContent": _CONVERSE_REDACTED_DATA}, + ] + reasoning: Final = litellm.AmazonConverseConfig()._transform_thinking_blocks(bedrock_reasoning_blocks) + messages: Final = [ + {"role": "user", "content": "hi"}, + { + "role": "assistant", + "content": [*reasoning, {"type": "text", "text": "hello"}], + "thinking_blocks": [{**reasoning[0], "thinking": copy_text}, reasoning[1]], + }, + {"role": "user", "content": "again"}, + ] + model: Final = "us.anthropic.claude-sonnet-4-6" + + result: Final = ( + await BedrockConverseMessagesProcessor._bedrock_converse_messages_pt_async( + messages=messages, model=model, llm_provider="bedrock" + ) + if use_async + else _bedrock_converse_messages_pt(messages=messages, model=model, llm_provider="bedrock") + ) + + assert result[1] == { + "role": "assistant", + "content": [*({"reasoningContent": block} for block in bedrock_reasoning_blocks), {"text": "hello"}], + } + + +_WEATHER_TOOL_CALL: Final = { + "id": "tooluse_weather_1", + "type": "function", + "function": {"name": "get_weather", "arguments": '{"city": "Paris"}'}, +} + + +def _block_split_across_assistant_messages(blocks: Sequence[Mapping[str, object]]) -> list[dict[str, object]]: + return [ + {"role": "user", "content": "What's the weather in Paris?"}, + {"role": "assistant", "content": list(blocks)}, + {"role": "assistant", "content": None, "thinking_blocks": list(blocks), "tool_calls": [_WEATHER_TOOL_CALL]}, + {"role": "tool", "tool_call_id": "tooluse_weather_1", "content": "18C, sunny"}, + ] + + +@pytest.mark.asyncio +@pytest.mark.parametrize("use_async", [False, True]) +async def test_bedrock_converse_sends_a_block_once_when_two_assistant_messages_carry_it(use_async: bool): + bedrock_reasoning_blocks: Final[list[BedrockConverseReasoningContentBlock]] = [ + {"reasoningText": {"text": "Let me look this up.", "signature": "sig-abc"}}, + {"redactedContent": _CONVERSE_REDACTED_DATA}, + ] + reasoning: Final = litellm.AmazonConverseConfig()._transform_thinking_blocks(bedrock_reasoning_blocks) + messages: Final = _block_split_across_assistant_messages(reasoning) + model: Final = "us.anthropic.claude-sonnet-4-6" + + result: Final = ( + await BedrockConverseMessagesProcessor._bedrock_converse_messages_pt_async( + messages=messages, model=model, llm_provider="bedrock" + ) + if use_async + else _bedrock_converse_messages_pt(messages=messages, model=model, llm_provider="bedrock") + ) + + assert result[1] == { + "role": "assistant", + "content": [ + *({"reasoningContent": block} for block in bedrock_reasoning_blocks), + {"toolUse": {"toolUseId": "tooluse_weather_1", "name": "get_weather", "input": {"city": "Paris"}}}, + ], + } + + +@pytest.mark.asyncio +@pytest.mark.parametrize("use_async", [False, True]) +@SPLIT_REASONING +async def test_bedrock_converse_keeps_reasoning_order_across_content_and_thinking_blocks( + use_async: bool, in_content: Sequence[int], in_thinking_blocks: Sequence[int] +): + """A reasoning block only one of content and thinking_blocks carries goes back in its original place.""" + bedrock_reasoning_blocks: Final[list[BedrockConverseReasoningContentBlock]] = [ + {"reasoningText": {"text": "First.", "signature": "sig-1"}}, + {"redactedContent": _CONVERSE_REDACTED_DATA}, + {"reasoningText": {"text": "Third.", "signature": "sig-3"}}, + ] + reasoning: Final = litellm.AmazonConverseConfig()._transform_thinking_blocks(bedrock_reasoning_blocks) + messages: Final = [ + {"role": "user", "content": "hi"}, + _assistant_with_split_reasoning(reasoning, in_content, in_thinking_blocks, "hello"), + {"role": "user", "content": "again"}, + ] + model: Final = "us.anthropic.claude-sonnet-4-6" + + result: Final = ( + await BedrockConverseMessagesProcessor._bedrock_converse_messages_pt_async( + messages=messages, model=model, llm_provider="bedrock" + ) + if use_async + else _bedrock_converse_messages_pt(messages=messages, model=model, llm_provider="bedrock") + ) + + assert result[1] == { + "role": "assistant", + "content": [*({"reasoningContent": block} for block in bedrock_reasoning_blocks), {"text": "hello"}], + } + + +@pytest.mark.asyncio +@pytest.mark.parametrize("use_async", [False, True]) +@pytest.mark.parametrize("entry", [None, "not a block"], ids=["none", "string"]) +async def test_bedrock_converse_skips_a_thinking_blocks_entry_that_is_not_a_block(use_async: bool, entry: object): + messages: Final = [ + {"role": "user", "content": "hi"}, + {"role": "assistant", "content": "hello", "thinking_blocks": [entry]}, + {"role": "user", "content": "again"}, + ] + model: Final = "us.anthropic.claude-sonnet-4-6" + + result: Final = ( + await BedrockConverseMessagesProcessor._bedrock_converse_messages_pt_async( + messages=messages, model=model, llm_provider="bedrock" + ) + if use_async + else _bedrock_converse_messages_pt(messages=messages, model=model, llm_provider="bedrock") + ) + + assert result[1] == {"role": "assistant", "content": [{"text": "hello"}]} + + +MALFORMED_THINKING: Final = pytest.mark.parametrize( + "malformed", + [ + {"type": "thinking", "thinking": {"a": 1}}, + {"type": "thinking", "thinking": ["a"], "signature": ""}, + {"type": "thinking", "thinking": "draft", "signature": ["a"]}, + ], + ids=["dict-thinking", "list-thinking", "list-signature"], +) + + +@pytest.mark.asyncio +@pytest.mark.parametrize("use_async", [False, True]) +@REASONING_PLACEMENTS +@MALFORMED_THINKING +async def test_bedrock_converse_replays_redacted_thinking_once_beside_a_malformed_thinking_item( + use_async: bool, placement: str, malformed: dict[str, object] +): + messages: Final = [ + {"role": "user", "content": "hi"}, + _assistant_with_reasoning( + placement, [{"type": "redacted_thinking", "data": _NATIVE_REDACTED_DATA}, malformed], "hello" + ), + {"role": "user", "content": "again"}, + ] + model: Final = "us.anthropic.claude-sonnet-4-6" + + result: Final = ( + await BedrockConverseMessagesProcessor._bedrock_converse_messages_pt_async( + messages=messages, model=model, llm_provider="bedrock" + ) + if use_async + else _bedrock_converse_messages_pt(messages=messages, model=model, llm_provider="bedrock") + ) + + assert result[1]["content"].count({"reasoningContent": {"redactedContent": _CONVERSE_REDACTED_DATA}}) == 1 + + +@REASONING_PLACEMENTS +@MALFORMED_THINKING +def test_anthropic_messages_pt_replays_redacted_thinking_once_beside_a_malformed_thinking_item( + placement: str, malformed: dict[str, object] +): + redacted: Final = {"type": "redacted_thinking", "data": _NATIVE_REDACTED_DATA} + messages: Final = [ + {"role": "user", "content": "hi"}, + _assistant_with_reasoning(placement, [redacted, malformed], "hello"), + {"role": "user", "content": "again"}, + ] + + result: Final = anthropic_messages_pt(messages=messages, model="claude-sonnet-4-6", llm_provider="anthropic") + + assert result[1]["content"].count(redacted) == 1 + + +@pytest.mark.asyncio +@pytest.mark.parametrize("use_async", [False, True]) +@pytest.mark.parametrize("drop_params", [False, True]) +async def test_bedrock_converse_drops_a_cache_point_after_reasoning_only_under_drop_params( + use_async: bool, drop_params: bool +): + """Bedrock 400s "Cache point cannot be inserted after reasoning block", so drop_params drops the + breakpoint and without it the request reaches Bedrock as sent.""" + messages: Final = [ + {"role": "user", "content": "hi"}, + { + "role": "assistant", + "content": [ + {"type": "redacted_thinking", "data": _NATIVE_REDACTED_DATA, "cache_control": {"type": "ephemeral"}}, + {"type": "text", "text": "hello"}, + ], + }, + {"role": "user", "content": "again"}, + ] + model: Final = "us.anthropic.claude-sonnet-4-6" + + result: Final = ( + await BedrockConverseMessagesProcessor._bedrock_converse_messages_pt_async( + messages=messages, model=model, llm_provider="bedrock", drop_params=drop_params + ) + if use_async + else _bedrock_converse_messages_pt( + messages=messages, model=model, llm_provider="bedrock", drop_params=drop_params + ) + ) + + assert ({"cachePoint": {"type": "default"}} in result[1]["content"]) is not drop_params + + _SENT_REDACTED: Final = [{"reasoningContent": {"redactedContent": _CONVERSE_REDACTED_DATA}}] @@ -813,17 +1079,17 @@ def test_anthropic_messages_pt_drops_unsignable_thinking_block(thinking_block): ) +@REASONING_PLACEMENTS @pytest.mark.parametrize("data", [_NATIVE_REDACTED_DATA, _CONVERSE_REDACTED_DATA], ids=["native", "legacy-wrapped"]) -def test_anthropic_messages_pt_replays_redacted_thinking_as_claude_native_data(data: str): +def test_anthropic_messages_pt_replays_redacted_thinking_as_claude_native_data(data: str, placement: str): """Histories saved from Converse before its replies were decoded hold the data base64-wrapped, and the - Anthropic API, Vertex and Bedrock Invoke 400 on it with "Invalid `data` in `redacted_thinking` block".""" + Anthropic API, Vertex and Bedrock Invoke 400 on it with "Invalid `data` in `redacted_thinking` block". + A redacted block in the content list, the shape the Anthropic SDK replays, used to be dropped.""" + signed: Final = {"type": "thinking", "thinking": "Let me look this up.", "signature": "sig-abc"} + redacted: Final = {"type": "redacted_thinking", "data": data} messages: Final = [ {"role": "user", "content": "hi"}, - { - "role": "assistant", - "content": "hello", - "thinking_blocks": [{"type": "redacted_thinking", "data": data, "cache_control": {"type": "ephemeral"}}], - }, + _assistant_with_reasoning(placement, [signed, redacted], "hello"), {"role": "user", "content": "again"}, ] @@ -832,12 +1098,125 @@ def test_anthropic_messages_pt_replays_redacted_thinking_as_claude_native_data(d assert result[1] == { "role": "assistant", "content": [ - {"type": "redacted_thinking", "data": _NATIVE_REDACTED_DATA, "cache_control": {"type": "ephemeral"}}, + signed, + {"type": "redacted_thinking", "data": _NATIVE_REDACTED_DATA}, {"type": "text", "text": "hello"}, ], } +@SPLIT_REASONING +def test_anthropic_messages_pt_keeps_reasoning_order_across_content_and_thinking_blocks( + in_content: Sequence[int], in_thinking_blocks: Sequence[int] +): + """A thinking block only one of content and thinking_blocks carries goes back in its original place.""" + reasoning: Final = ( + {"type": "thinking", "thinking": "First.", "signature": "sig-1"}, + {"type": "redacted_thinking", "data": _NATIVE_REDACTED_DATA}, + {"type": "thinking", "thinking": "Third.", "signature": "sig-3"}, + ) + messages: Final = [ + {"role": "user", "content": "hi"}, + _assistant_with_split_reasoning(reasoning, in_content, in_thinking_blocks, "hello"), + {"role": "user", "content": "again"}, + ] + + result: Final = anthropic_messages_pt(messages=messages, model="claude-sonnet-4-6", llm_provider="anthropic") + + assert result[1] == {"role": "assistant", "content": [*reasoning, {"type": "text", "text": "hello"}]} + + +@COPY_TEXT +def test_anthropic_messages_pt_sends_a_signed_block_once_when_thinking_blocks_holds_other_text(copy_text: str): + signed: Final = {"type": "thinking", "thinking": "First.", "signature": "sig-1"} + redacted: Final = {"type": "redacted_thinking", "data": _NATIVE_REDACTED_DATA} + messages: Final = [ + {"role": "user", "content": "hi"}, + { + "role": "assistant", + "content": [signed, redacted, {"type": "text", "text": "hello"}], + "thinking_blocks": [{**signed, "thinking": copy_text}, redacted], + }, + {"role": "user", "content": "again"}, + ] + + result: Final = anthropic_messages_pt(messages=messages, model="claude-sonnet-4-6", llm_provider="anthropic") + + assert result[1] == {"role": "assistant", "content": [signed, redacted, {"type": "text", "text": "hello"}]} + + + +def test_anthropic_messages_pt_sends_a_block_once_when_two_assistant_messages_carry_it(): + signed: Final = {"type": "thinking", "thinking": "Let me look this up.", "signature": "sig-abc"} + redacted: Final = {"type": "redacted_thinking", "data": _NATIVE_REDACTED_DATA} + + result: Final = anthropic_messages_pt( + messages=_block_split_across_assistant_messages([signed, redacted]), + model="claude-sonnet-4-6", + llm_provider="anthropic", + ) + + assert result[1] == { + "role": "assistant", + "content": [ + signed, + redacted, + {"type": "tool_use", "id": "tooluse_weather_1", "name": "get_weather", "input": {"city": "Paris"}}, + ], + } + +@REASONING_PLACEMENTS +@pytest.mark.parametrize("drop_params", [False, True]) +def test_anthropic_messages_pt_drops_cache_control_from_thinking_blocks_only_under_drop_params( + placement: str, drop_params: bool +): + """Claude 400s "thinking.cache_control: Extra inputs are not permitted" on a thinking or redacted_thinking + block, so drop_params drops the breakpoint and without it the request reaches Claude as sent. The streamed + list-position `index` is LiteLLM's own field and never reaches Claude.""" + breakpoint_mark: Final = {"cache_control": {"type": "ephemeral"}} + signed: Final = {"type": "thinking", "thinking": "Let me look this up.", "signature": "sig-abc"} + redacted: Final = {"type": "redacted_thinking", "data": _NATIVE_REDACTED_DATA} + messages: Final = [ + {"role": "user", "content": "hi"}, + _assistant_with_reasoning( + placement, [{**signed, **breakpoint_mark, "index": 0}, {**redacted, **breakpoint_mark, "index": 1}], "hello" + ), + {"role": "user", "content": "again"}, + ] + + result: Final = anthropic_messages_pt( + messages=messages, model="claude-sonnet-4-6", llm_provider="anthropic", drop_params=drop_params + ) + + sent_reasoning: Final = ( + [signed, redacted] if drop_params else [{**signed, **breakpoint_mark}, {**redacted, **breakpoint_mark}] + ) + assert result[1] == {"role": "assistant", "content": [*sent_reasoning, {"type": "text", "text": "hello"}]} + + +@REASONING_PLACEMENTS +@pytest.mark.parametrize("drop_params", [False, True]) +@pytest.mark.parametrize("data", ["", " ", None], ids=["empty", "whitespace", "null"]) +def test_anthropic_messages_pt_drops_a_blank_redacted_thinking_block_only_under_drop_params( + data: str | None, placement: str, drop_params: bool +): + """Claude 400s "Invalid `data` in `redacted_thinking` block" on blank data, so drop_params drops the block + and without it the request reaches Claude as sent.""" + blank: Final = {"type": "redacted_thinking", "data": data} + messages: Final = [ + {"role": "user", "content": "hi"}, + _assistant_with_reasoning(placement, [blank], "hello"), + {"role": "user", "content": "again"}, + ] + + result: Final = anthropic_messages_pt( + messages=messages, model="claude-sonnet-4-6", llm_provider="anthropic", drop_params=drop_params + ) + + sent_reasoning: Final = [] if drop_params else [blank] + assert result[1] == {"role": "assistant", "content": [*sent_reasoning, {"type": "text", "text": "hello"}]} + + def test_anthropic_messages_pt_keeps_signed_thinking_block(): """A genuine Anthropic round-trip still holds its original signature, so that thinking block must be forwarded unchanged (we only drop unsignable blocks). diff --git a/tests/unit/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_mid_conversation_system.py b/tests/unit/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_mid_conversation_system.py index 91d7acd331e..aab57b87a90 100644 --- a/tests/unit/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_mid_conversation_system.py +++ b/tests/unit/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_mid_conversation_system.py @@ -308,16 +308,8 @@ EMPTY_ASSISTANT = pytest.mark.parametrize( "content": None, "thinking_blocks": [{"type": "redacted_thinking", "data": encrypted_reasoning_signature("abc")}], }, - { - "role": "assistant", - "content": [{"type": "thinking", "thinking": "unsigned"}], - "thinking_blocks": [{"type": "thinking", "thinking": "hm", "signature": "s"}], - }, - { - "role": "assistant", - "content": [{"type": "redacted_thinking", "data": "x"}], - "thinking_blocks": [{"type": "redacted_thinking", "data": "x"}], - }, + {"role": "assistant", "content": [{"type": "redacted_thinking", "data": ""}]}, + {"role": "assistant", "content": None, "thinking_blocks": [{"type": "redacted_thinking", "data": " "}]}, litellm.Message(role="assistant", content=None), {"role": "assistant", "content": None, "tool_calls": [_TOOL_SEARCH_USE]}, ], @@ -327,8 +319,8 @@ EMPTY_ASSISTANT = pytest.mark.parametrize( "unsigned-thinking-part", "encrypted-thinking-part", "encrypted-redacted-thinking-block", - "unsigned-inline-part-hides-signed-block", - "inline-redacted-part-hides-redacted-block", + "blank-data-redacted-part", + "blank-data-redacted-block", "pydantic-none", "unanswered-tool-search-use", ], @@ -464,6 +456,16 @@ def test_flagged_placement_keeps_a_system_whose_empty_assistant_follower_ends_th "thinking_blocks": [{"type": "thinking", "thinking": "hm", "signature": "s"}], }, {"role": "assistant", "content": None, "thinking_blocks": [{"type": "redacted_thinking", "data": "x"}]}, + { + "role": "assistant", + "content": [{"type": "redacted_thinking", "data": "x"}], + "thinking_blocks": [{"type": "redacted_thinking", "data": "x"}], + }, + { + "role": "assistant", + "content": [{"type": "thinking", "thinking": "unsigned"}], + "thinking_blocks": [{"type": "thinking", "thinking": "hm", "signature": "s"}], + }, {"role": "assistant", "content": [{"type": "thinking", "thinking": "hm", "signature": "s"}]}, {"role": "assistant", "content": [{"type": "thinking", "thinking": "", "signature": "s"}]}, {"role": "assistant", "content": None, "function_call": {"name": "f", "arguments": "{}"}}, @@ -485,6 +487,8 @@ def test_flagged_placement_keeps_a_system_whose_empty_assistant_follower_ends_th "tool-calls", "signed-thinking-block", "redacted-thinking-block", + "redacted-part-beside-the-same-redacted-block", + "signed-block-beside-an-unsigned-part", "signed-thinking-part", "signed-empty-thinking-part", "function-call", diff --git a/tests/unit/litellm_core_utils/test_cloud_storage_security.py b/tests/unit/litellm_core_utils/test_cloud_storage_security.py index c3a2511a263..46131aa64e5 100644 --- a/tests/unit/litellm_core_utils/test_cloud_storage_security.py +++ b/tests/unit/litellm_core_utils/test_cloud_storage_security.py @@ -1,4 +1,11 @@ +from functools import reduce +from typing import Final +from urllib.parse import quote + +import pytest + from litellm.litellm_core_utils.cloud_storage_security import ( + MAX_FILE_ID_DECODE_PASSES, is_managed_cloud_storage_uri, ) @@ -13,3 +20,38 @@ def test_is_managed_cloud_storage_uri_ignores_provider_and_unified_ids(): assert not is_managed_cloud_storage_uri("file-abc123") assert not is_managed_cloud_storage_uri("bGl0ZWxsbV9wcm94eQ==") assert not is_managed_cloud_storage_uri("") + + +@pytest.mark.parametrize( + "file_id", + ( + "gs%3A%2F%2Fbucket%2Flitellm-vertex-files%2Fprediction-model%2Fpredictions.jsonl", + "gs%253A%252F%252Fbucket%252Flitellm-vertex-files%252Fprediction-model%252Fpredictions.jsonl", + "s3%3A%2F%2Fbucket%2Flitellm-batch-outputs%2Fx.jsonl.out", + "s3%253A%252F%252Fbucket%252Flitellm-batch-outputs%252Fx.jsonl.out", + ), +) +def test_is_managed_cloud_storage_uri_sees_through_percent_encoding(file_id: str): + assert is_managed_cloud_storage_uri(file_id) + + +def _quote_once(current: str, _: int) -> str: + return quote(current, safe="") + + +def _quoted_times(value: str, times: int) -> str: + return reduce(_quote_once, range(times), value) + + +def test_is_managed_cloud_storage_uri_decodes_up_to_the_pass_cap(): + assert is_managed_cloud_storage_uri(_quoted_times("gs://bucket/x", MAX_FILE_ID_DECODE_PASSES)) + assert not is_managed_cloud_storage_uri(_quoted_times("file-abc/x", MAX_FILE_ID_DECODE_PASSES)) + + +def test_is_managed_cloud_storage_uri_fails_closed_on_an_id_encoded_past_the_pass_cap(): + nested_gs_id: Final = "gs" + "%" + "25" * 5000 + "3A//bucket/x" + nested_plain_id: Final = "%" + "25" * 5000 + + assert is_managed_cloud_storage_uri(_quoted_times("file-abc/x", MAX_FILE_ID_DECODE_PASSES + 1)) + assert is_managed_cloud_storage_uri(nested_gs_id) + assert is_managed_cloud_storage_uri(nested_plain_id) diff --git a/tests/unit/litellm_core_utils/test_get_litellm_params.py b/tests/unit/litellm_core_utils/test_get_litellm_params.py index 251bfa624a5..89173956dc6 100644 --- a/tests/unit/litellm_core_utils/test_get_litellm_params.py +++ b/tests/unit/litellm_core_utils/test_get_litellm_params.py @@ -317,6 +317,10 @@ class TestGetLitellmParamsExplicitFields: result = get_litellm_params(no_log=True) assert result["no-log"] is True + def test_github_copilot_host_is_registered_as_a_litellm_param(self): + result: Final = get_litellm_params(github_copilot_host="octo.ghe.com") + assert result["github_copilot_host"] == "octo.ghe.com" + class TestGetLitellmParamsDataResidency: """Verify that data_residency is inferred from OpenAI regional api_base.""" diff --git a/tests/unit/litellm_core_utils/test_health_check_helpers.py b/tests/unit/litellm_core_utils/test_health_check_helpers.py index c23749f7a20..b584a72855a 100644 --- a/tests/unit/litellm_core_utils/test_health_check_helpers.py +++ b/tests/unit/litellm_core_utils/test_health_check_helpers.py @@ -195,9 +195,7 @@ def test_update_model_params_with_health_check_tracking_information(): }, } - result = HealthCheckHelpers.update_model_params_with_health_check_tracking_information( - initial_model_params - ) + result = HealthCheckHelpers.update_model_params_with_health_check_tracking_information(initial_model_params) # Verify that litellm_metadata was added assert "litellm_metadata" in result @@ -753,9 +751,7 @@ async def test_ahealth_check_keeps_the_noul_probe_for_other_decisions_providers( assert "error" not in result, result assert upstream.called sent: Final = json.loads(upstream.calls[0].request.content) - assert sent["questions"] == { - "reachable": {"type": "noul", "instructions": "Is the service reachable?"} - } + assert sent["questions"] == {"reachable": {"type": "noul", "instructions": "Is the service reachable?"}} @pytest.mark.parametrize( @@ -916,6 +912,7 @@ async def test_ahealth_check_without_mode_reports_the_real_failure( assert "Missing `mode`" not in result["error"] assert "raw_request_typed_dict" in result + def test_update_litellm_params_for_health_check(): """ Test if update_litellm_params_for_health_check correctly: @@ -1010,12 +1007,10 @@ def test_update_litellm_params_for_health_check(): "model": f"bedrock/{prefix}anthropic.claude-3-haiku-20240307-v1:0", "api_key": "fake_key", } - updated_params = update_litellm_params_for_health_check( - model_info, litellm_params + updated_params = update_litellm_params_for_health_check(model_info, litellm_params) + assert updated_params["model"] == f"{prefix}anthropic.claude-3-haiku-20240307-v1:0", ( + f"Failed to preserve CRIS prefix: {prefix}" ) - assert ( - updated_params["model"] == f"{prefix}anthropic.claude-3-haiku-20240307-v1:0" - ), f"Failed to preserve CRIS prefix: {prefix}" litellm_params = { "model": "bedrock/us-east-2/us.anthropic.claude-3-haiku-20240307-v1:0", @@ -1036,30 +1031,21 @@ def test_update_litellm_params_for_health_check(): "api_key": "fake_key", } updated_params = update_litellm_params_for_health_check(model_info, litellm_params) - assert ( - updated_params["model"] - == "llama/arn:aws:bedrock:us-east-1:123:imported-model/abc" - ) + assert updated_params["model"] == "llama/arn:aws:bedrock:us-east-1:123:imported-model/abc" litellm_params = { "model": "bedrock/deepseek_r1/arn:aws:bedrock:us-west-2:456:imported-model/xyz", "api_key": "fake_key", } updated_params = update_litellm_params_for_health_check(model_info, litellm_params) - assert ( - updated_params["model"] - == "deepseek_r1/arn:aws:bedrock:us-west-2:456:imported-model/xyz" - ) + assert updated_params["model"] == "deepseek_r1/arn:aws:bedrock:us-west-2:456:imported-model/xyz" litellm_params = { "model": "bedrock/converse/us.anthropic.claude-haiku-4-5-20251001-v1:0", "api_key": "fake_key", } updated_params = update_litellm_params_for_health_check(model_info, litellm_params) - assert ( - updated_params["model"] - == "converse/us.anthropic.claude-haiku-4-5-20251001-v1:0" - ) + assert updated_params["model"] == "converse/us.anthropic.claude-haiku-4-5-20251001-v1:0" litellm_params = { "model": "bedrock/invoke/us-west-2/anthropic.claude-instant-v1", @@ -1073,29 +1059,22 @@ def test_update_litellm_params_for_health_check(): "api_key": "fake_key", } updated_params = update_litellm_params_for_health_check(model_info, litellm_params) - assert ( - updated_params["model"] - == "arn:aws:bedrock:eu-central-1:000:application-inference-profile/abc" - ) + assert updated_params["model"] == "arn:aws:bedrock:eu-central-1:000:application-inference-profile/abc" litellm_params = { "model": "bedrock/us-west-2/llama/arn:aws:bedrock:us-east-1:123:imported-model/abc", "api_key": "fake_key", } updated_params = update_litellm_params_for_health_check(model_info, litellm_params) - assert ( - updated_params["model"] - == "llama/arn:aws:bedrock:us-east-1:123:imported-model/abc" - ) + assert updated_params["model"] == "llama/arn:aws:bedrock:us-east-1:123:imported-model/abc" litellm_params = { "model": "bedrock/converse/us-west-2/eu.anthropic.claude-3-sonnet-20240229-v1:0", "api_key": "fake_key", } updated_params = update_litellm_params_for_health_check(model_info, litellm_params) - assert ( - updated_params["model"] == "converse/eu.anthropic.claude-3-sonnet-20240229-v1:0" - ) + assert updated_params["model"] == "converse/eu.anthropic.claude-3-sonnet-20240229-v1:0" + @pytest.mark.asyncio async def test_perform_health_check_filters_by_model_id(): @@ -1142,6 +1121,7 @@ async def test_perform_health_check_filters_by_model_id(): assert len(healthy_endpoints) == 1 assert healthy_endpoints[0]["api_key"] == "fake-key-2" + @pytest.mark.asyncio async def test_perform_health_check_skip_disabled_background_models(): from litellm.proxy.health_check import perform_health_check @@ -1180,6 +1160,7 @@ async def test_perform_health_check_skip_disabled_background_models(): assert len(captured[0]) == 1 assert captured[0][0]["model_name"] == "a" + @pytest.mark.asyncio async def test_perform_health_check_with_health_check_model(): """ @@ -1206,9 +1187,7 @@ async def test_perform_health_check_with_health_check_model(): return {"status": "healthy"} with patch("litellm.ahealth_check", side_effect=mock_health_check): - healthy_endpoints, unhealthy_endpoints, _ = await _perform_health_check( - model_list - ) + healthy_endpoints, unhealthy_endpoints, _ = await _perform_health_check(model_list) print("health check calls: ", health_check_calls) assert health_check_calls[0] == "openai/gpt-5-mini" @@ -1217,6 +1196,7 @@ async def test_perform_health_check_with_health_check_model(): assert len(healthy_endpoints) == 1 assert len(unhealthy_endpoints) == 0 + @pytest.mark.asyncio async def test_image_generation_health_check_prompt(monkeypatch): """Health checks should respect default and environment-configured prompts.""" @@ -1267,9 +1247,7 @@ async def test_image_generation_health_check_prompt(monkeypatch): health_check_calls = await run_health_check(reloaded_health_check) assert len(health_check_calls) == 1 - assert ( - health_check_calls[0]["prompt"] == reloaded_constants.DEFAULT_HEALTH_CHECK_PROMPT - ) + assert health_check_calls[0]["prompt"] == reloaded_constants.DEFAULT_HEALTH_CHECK_PROMPT # Environment override should change the prompt without code changes override_prompt = "environment override prompt" @@ -1293,9 +1271,7 @@ async def test_health_check_with_custom_llm_provider( "object": "chat.completion", "created": 0, "model": "deepseek-r1-distill-qwen-1.5B-q4", - "choices": [ - {"index": 0, "message": {"role": "assistant", "content": "ok"}, "finish_reason": "stop"} - ], + "choices": [{"index": 0, "message": {"role": "assistant", "content": "ok"}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2}, } ) @@ -1503,3 +1479,37 @@ async def test_audio_transcription_health_check_returns_transcribed_text( assert "error" not in response assert upstream.called assert b'name="file"' in upstream.calls.last.request.content + + +@pytest.mark.parametrize("model", ("cloudflare/clairic", "cloudflare/@cf/cloudflare/clairic")) +async def test_ahealth_check_probes_extraction_models_through_the_extraction_api( + model: str, + monkeypatch: pytest.MonkeyPatch, + respx_mock: respx.MockRouter, +) -> None: + monkeypatch.setenv("CLOUDFLARE_ACCOUNT_ID", "acct-1") + monkeypatch.delenv("CLOUDFLARE_API_BASE", raising=False) + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + litellm.in_memory_llm_clients_cache.flush_cache() + upstream: Final = respx_mock.post( + "https://api.cloudflare.com/client/v4/accounts/acct-1/ai/run/@cf/cloudflare/clairic" + ).respond( + json={ + "result": { + "model": "clairic", + "answers": {"reachable": {"type": "text", "value": "health"}}, + "truncated": False, + "usage": {"input_tokens": 20, "output_tokens": 0}, + }, + "success": True, + "errors": [], + "messages": [], + } + ) + + result: Final = await ahealth_check({"model": model, "api_key": "sk-test"}, mode=None) + + assert "error" not in result, result + sent: Final = json.loads(upstream.calls[0].request.content) + assert sent["state"] == "health check" + assert sent["fields"]["reachable"]["type"] == "text" diff --git a/tests/unit/litellm_core_utils/test_litellm_logging.py b/tests/unit/litellm_core_utils/test_litellm_logging.py index 00c2b1ad8a8..79645ffe8f6 100644 --- a/tests/unit/litellm_core_utils/test_litellm_logging.py +++ b/tests/unit/litellm_core_utils/test_litellm_logging.py @@ -2462,7 +2462,41 @@ def test_success_handler_runs_sync_callbacks_for_sync_requests( @pytest.mark.asyncio -@pytest.mark.parametrize("registration", ["sync", "async", "overlapping"]) +@pytest.mark.parametrize("different_headers", [False, True]) +async def test_completed_success_preserves_generic_logger_configuration( + monkeypatch: pytest.MonkeyPatch, different_headers: bool +) -> None: + from litellm.integrations.generic_api.generic_api_callback import GenericAPILogger + + first: Final = GenericAPILogger( + endpoint="https://logs.example.test/events", + headers={"Authorization": "Bearer first"}, + event_types=["llm_api_success"], + ) + second: Final = GenericAPILogger( + endpoint="https://logs.example.test/events", + headers={"Authorization": "Bearer second" if different_headers else "Bearer first"}, + event_types=["llm_api_success"] if different_headers else ["llm_api_failure"], + ) + monkeypatch.setattr(litellm, "success_callback", [first]) + monkeypatch.setattr(litellm, "_async_success_callback", [second]) + monkeypatch.setattr(litellm, "generic_api_use_v1", False) + logging_obj: Final = _async_request_logging_obj("distinct-generic-loggers", []) + response: Final = ModelResponse(id="chatcmpl-distinct-generic-loggers") + now: Final = datetime.datetime(2026, 1, 1) + + await logging_obj.async_success_handler(response, now, now) + + assert len(first.log_queue) == 1 + assert first.log_queue[0]["id"] == response.id + if different_headers: + assert second.log_queue == first.log_queue + else: + assert second.log_queue == [] + + +@pytest.mark.asyncio +@pytest.mark.parametrize("registration", ["sync", "async", "overlapping", "equivalent", "distinct"]) @pytest.mark.parametrize("kind", ["sync", "async", "dual"]) @pytest.mark.parametrize("compatibility_first", [False, True]) async def test_completed_success_selects_one_implemented_hook( @@ -2517,9 +2551,15 @@ async def test_completed_success_selects_one_implemented_hook( ) -> None: record("async", kwargs, response_obj) - callback: Final = {"sync": SyncRecorder, "async": AsyncRecorder, "dual": DualRecorder}[kind]() + recorder: Final = {"sync": SyncRecorder, "async": AsyncRecorder, "dual": DualRecorder}[kind] + callback: Final = recorder() + async_callback: Final = ( + recorder(turn_off_message_logging=registration == "distinct") + if registration in ("equivalent", "distinct") + else callback + ) monkeypatch.setattr(litellm, "success_callback", [callback] if registration != "async" else []) - monkeypatch.setattr(litellm, "_async_success_callback", [callback] if registration != "sync" else []) + monkeypatch.setattr(litellm, "_async_success_callback", [async_callback] if registration != "sync" else []) logging_obj: Final = _async_request_logging_obj("completed-hook", []) response: Final = ModelResponse(id="chatcmpl-completed-hook") now: Final = datetime.datetime.now() @@ -2531,20 +2571,26 @@ async def test_completed_success_selects_one_implemented_hook( await logging_obj.async_success_handler(response, now, now) logging_obj.handle_sync_success_callbacks_for_async_calls(response, now, now) - assert events.qsize() == 1 - hook, response_id, cost, thread_id = events.get_nowait() - assert hook == ("sync" if kind == "sync" else "async") - assert response_id == response.id - assert cost == logging_obj.model_call_details["response_cost"] - assert (thread_id == loop_thread) is (kind != "sync") + expected_count: Final = 2 if registration in ("equivalent", "distinct") else 1 + assert events.qsize() == expected_count + for _ in range(expected_count): + hook, response_id, cost, thread_id = events.get_nowait() + assert hook == ("sync" if kind == "sync" else "async") + assert response_id == response.id + assert cost == logging_obj.model_call_details["response_cost"] + assert (thread_id == loop_thread) is (kind != "sync") -@pytest.mark.parametrize("for_async_request", [False, True]) +@pytest.mark.parametrize("for_async_request,split_registries", [(False, False), (True, False), (True, True)]) @pytest.mark.parametrize("private_first", [False, True]) @pytest.mark.parametrize("response_kind", ["responses", "completion"]) def test_sync_success_redacts_only_opted_out_loggers( - monkeypatch: pytest.MonkeyPatch, for_async_request: bool, private_first: bool, response_kind: str + monkeypatch: pytest.MonkeyPatch, + for_async_request: bool, + split_registries: bool, + private_first: bool, + response_kind: str, ) -> None: from queue import SimpleQueue @@ -2563,8 +2609,8 @@ def test_sync_success_redacts_only_opted_out_loggers( private_logger: Final = PayloadRecorder(turn_off_message_logging=True) public_logger: Final = PayloadRecorder() callbacks: Final = [private_logger, public_logger] if private_first else [public_logger, private_logger] - monkeypatch.setattr(litellm, "success_callback", callbacks) - monkeypatch.setattr(litellm, "_async_success_callback", []) + monkeypatch.setattr(litellm, "success_callback", callbacks[:1] if split_registries else callbacks) + monkeypatch.setattr(litellm, "_async_success_callback", callbacks[1:] if split_registries else []) monkeypatch.setattr(litellm, "turn_off_message_logging", False) logging_obj: Final = LitellmLogging( model="openai/gpt-6.1-sol", @@ -3042,7 +3088,7 @@ async def test_dispatch_failure_handlers_submits_sync_handler_for_failure_only_c prefer_async_handlers=True, ) - mock_submit.assert_called_once_with(mock_sync, exception, traceback_exception) + mock_submit.assert_called_once_with(mock_sync, exception, traceback_exception, for_async_request=True) @pytest.mark.asyncio @@ -8142,6 +8188,155 @@ def test_cache_callback_alone_does_not_start_sync_callbacks_for_async_requests( assert logging_obj._should_run_sync_callbacks_for_async_calls() is expected +class _FailureHookRecorder(CustomLogger): + def __init__(self) -> None: + super().__init__() + self.hooks: list[str] = [] + + def log_failure_event(self, kwargs: object, response_obj: object, start_time: object, end_time: object) -> None: + self.hooks.append("sync_failure") + + +class _BothFailureHooksRecorder(_FailureHookRecorder): + async def async_log_failure_event( + self, kwargs: object, response_obj: object, start_time: object, end_time: object + ) -> None: + self.hooks.append("async_failure") + + +def _failure_hook_count_logging_obj( + call_type: str, recorder: _FailureHookRecorder, *, async_failure_listed: bool +) -> LitellmLogging: + logging_obj: Final = LitellmLogging( + model="gpt-4o-mini-tts", + messages=[{"role": "user", "content": "hi"}], + stream=False, + call_type=call_type, + start_time=datetime.datetime.now(), + litellm_call_id=f"failure-hook-count-{call_type}", + function_id=f"failure-hook-count-{call_type}", + dynamic_failure_callbacks=[recorder], + dynamic_async_failure_callbacks=[recorder] if async_failure_listed else [], + ) + logging_obj.update_environment_variables(litellm_params={"metadata": {}}, optional_params={}) + return logging_obj + + +@pytest.fixture +def no_global_callbacks(monkeypatch: pytest.MonkeyPatch) -> None: + for name in ( + "callbacks", + "success_callback", + "failure_callback", + "_async_success_callback", + "_async_failure_callback", + ): + monkeypatch.setattr(litellm, name, []) + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("recorder_type", "async_listed", "expected"), + [ + (_BothFailureHooksRecorder, True, ["async_failure"]), + (_FailureHookRecorder, True, ["sync_failure"]), + (_BothFailureHooksRecorder, False, ["sync_failure"]), + ], +) +@pytest.mark.parametrize("call_type", ["aspeech", "atranscription", "aimage_edit", "asearch"]) +@pytest.mark.usefixtures("no_global_callbacks") +async def test_async_call_outside_the_async_flag_list_gets_one_custom_logger_failure_hook( + call_type: str, recorder_type: type[_FailureHookRecorder], async_listed: bool, expected: list[str] +) -> None: + recorder: Final = recorder_type() + logging_obj: Final = _failure_hook_count_logging_obj(call_type, recorder, async_failure_listed=async_listed) + + logging_obj.failure_handler(ValueError("upstream rejected"), "traceback", for_async_request=True) + await logging_obj.async_failure_handler(ValueError("upstream rejected"), "traceback") + + assert recorder.hooks == expected + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("no_global_callbacks") +async def test_logger_in_the_global_failure_callback_lists_gets_one_failure_hook( + monkeypatch: pytest.MonkeyPatch, +) -> None: + recorder: Final = _BothFailureHooksRecorder() + monkeypatch.setattr(litellm, "failure_callback", [recorder]) + monkeypatch.setattr(litellm, "_async_failure_callback", [recorder]) + logging_obj: Final = LitellmLogging( + model="gpt-4o-mini-tts", + messages=[{"role": "user", "content": "hi"}], + stream=False, + call_type="aspeech", + start_time=datetime.datetime.now(), + litellm_call_id="global-failure", + function_id="global-failure", + ) + logging_obj.update_environment_variables(litellm_params={"metadata": {}}, optional_params={}) + + logging_obj.failure_handler(ValueError("upstream rejected"), "traceback", for_async_request=True) + await logging_obj.async_failure_handler(ValueError("upstream rejected"), "traceback") + + assert recorder.hooks == ["async_failure"] + + +@pytest.mark.usefixtures("no_global_callbacks") +def test_failure_handler_run_without_an_async_failure_run_keeps_the_sync_hook() -> None: + recorder: Final = _BothFailureHooksRecorder() + + _failure_hook_count_logging_obj("aspeech", recorder, async_failure_listed=True).failure_handler( + ValueError("upstream rejected"), "traceback" + ) + + assert recorder.hooks == ["sync_failure"] + + +@pytest.mark.usefixtures("no_global_callbacks") +def test_async_call_outside_the_async_flag_list_still_runs_sync_failure_function_callbacks( + monkeypatch: pytest.MonkeyPatch, +) -> None: + monkeypatch.setattr(litellm_logging, "customLogger", CustomLogger()) + calls: Final[list[str]] = [] + + def failure_function(kwargs: object, response_obj: object, start_time: object, end_time: object) -> None: + calls.append("function_failure") + + recorder: Final = _BothFailureHooksRecorder() + logging_obj: Final = _failure_hook_count_logging_obj("aspeech", recorder, async_failure_listed=True) + logging_obj.dynamic_failure_callbacks = [recorder, failure_function] + + logging_obj.failure_handler(ValueError("upstream rejected"), "traceback", for_async_request=True) + + assert calls == ["function_failure"] + assert recorder.hooks == [] + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("no_global_callbacks") +async def test_client_wrapped_failure_gives_a_logger_in_litellm_callbacks_one_hook( + monkeypatch: pytest.MonkeyPatch, +) -> None: + recorder: Final = _BothFailureHooksRecorder() + monkeypatch.setattr(litellm, "callbacks", [recorder]) + + @litellm.utils.client + async def aspeech(model: str, input: str, voice: str, **kwargs: object) -> None: + raise litellm.BadRequestError(message="upstream rejected", model=model, llm_provider="openai") + + @litellm.utils.client + def speech(model: str, input: str, voice: str, **kwargs: object) -> None: + raise litellm.BadRequestError(message="upstream rejected", model=model, llm_provider="openai") + + with pytest.raises(litellm.BadRequestError): + await aspeech(model="gpt-4o-mini-tts", input="hi", voice="alloy") + with pytest.raises(litellm.BadRequestError): + speech(model="gpt-4o-mini-tts", input="hi", voice="alloy") + + assert recorder.hooks == ["async_failure", "sync_failure"] + + @pytest.mark.asyncio @pytest.mark.parametrize("turn_off_message_logging", [False, True]) @pytest.mark.parametrize("make_response", [ModelResponse, _responses_api_response_with_text]) @@ -9973,6 +10168,7 @@ class TestAzurePTUSpilloverCost: ROUTER_MODEL_ID: Final = "ptu-spill-router-model-id" SERVED_MODEL: Final = "azure/spill-served-model-ptu" + PTU_DEPLOYMENT: Final = "azure/spill-ptu-deployment" PTU_MODEL_INFO: Final = { "id": ROUTER_MODEL_ID, "team_id": "team-1", @@ -10008,7 +10204,9 @@ class TestAzurePTUSpilloverCost: litellm.model_cost.pop(TestAzurePTUSpilloverCost.ROUTER_MODEL_ID, None) litellm.model_cost.pop(TestAzurePTUSpilloverCost.SERVED_MODEL, None) - def _logging_obj(self, model_info: dict, *, flag: str, litellm_rate: float, monkeypatch) -> LitellmLogging: + def _logging_obj( + self, model_info: dict, *, flag: str, litellm_rate: float, monkeypatch, deployment: str | None = None + ) -> LitellmLogging: monkeypatch.setenv("LITELLM_ENABLE_PTU_COST_ATTRIBUTION", flag) obj = LitellmLogging( model=self.SERVED_MODEL, @@ -10025,7 +10223,7 @@ class TestAzurePTUSpilloverCost: optional_params={}, litellm_params={ "api_base": "", - "metadata": {"model_info": model_info}, + "metadata": {"model_info": model_info, "deployment": deployment}, "input_cost_per_token": litellm_rate, "output_cost_per_token": litellm_rate, }, @@ -10095,6 +10293,84 @@ class TestAzurePTUSpilloverCost: finally: self._unregister_models() + def test_spillover_payload_reports_the_pay_as_you_go_entry_billing_used(self, monkeypatch) -> None: + self._register_models() + try: + obj = self._logging_obj(dict(self.PTU_MODEL_INFO), flag="True", litellm_rate=0.0, monkeypatch=monkeypatch) + response = self._response() + response._hidden_params["additional_headers"] = {"llm_provider-x-ms-is-spilled-over": "true"} + response_cost: Final = obj.response_cost_calculator(result=response) + + payload: Final = get_standard_logging_object_payload( + kwargs={ + "model": self.SERVED_MODEL, + "custom_llm_provider": "azure", + "litellm_params": obj.litellm_params, + "response_cost": response_cost, + }, + init_response_obj=response, + start_time=datetime.datetime.now(), + end_time=datetime.datetime.now(), + logging_obj=obj, + status="success", + ) + + assert response_cost == pytest.approx(self.EXPECTED_SPILL_COST) + assert payload is not None + model_map_value: Final = payload["model_map_information"]["model_map_value"] + assert model_map_value is not None + assert model_map_value["input_cost_per_token"] == litellm.model_cost[self.SERVED_MODEL]["input_cost_per_token"] + assert model_map_value["output_cost_per_token"] == litellm.model_cost[self.SERVED_MODEL]["output_cost_per_token"] + assert response_cost == pytest.approx( + 100 * model_map_value["input_cost_per_token"] + 50 * model_map_value["output_cost_per_token"] + ) + finally: + self._unregister_models() + + def test_spillover_without_base_model_reports_the_pay_as_you_go_rates_billing_used(self, monkeypatch) -> None: + self._register_models() + litellm.model_cost[self.PTU_DEPLOYMENT] = {"litellm_provider": "azure", "mode": "chat"} + try: + obj = self._logging_obj( + dict(self.PTU_MODEL_INFO), + flag="True", + litellm_rate=0.0, + monkeypatch=monkeypatch, + deployment=self.PTU_DEPLOYMENT, + ) + response = self._response() + response._hidden_params["additional_headers"] = {"llm_provider-x-ms-is-spilled-over": "true"} + response._hidden_params["provider_response_model"] = response.model + response_cost: Final = obj.response_cost_calculator(result=response) + response.model = "spill-model-group-alias" + + payload: Final = get_standard_logging_object_payload( + kwargs={ + "model": self.SERVED_MODEL, + "custom_llm_provider": "azure", + "litellm_params": obj.litellm_params, + "response_cost": response_cost, + }, + init_response_obj=response, + start_time=datetime.datetime.now(), + end_time=datetime.datetime.now(), + logging_obj=obj, + status="success", + ) + + assert response_cost == pytest.approx(self.EXPECTED_SPILL_COST) + assert payload is not None + model_map_information: Final = payload["model_map_information"] + assert model_map_information["model_map_key"] != self.PTU_DEPLOYMENT + model_map_value: Final = model_map_information["model_map_value"] + assert model_map_value is not None + assert response_cost == pytest.approx( + 100 * model_map_value["input_cost_per_token"] + 50 * model_map_value["output_cost_per_token"] + ) + finally: + litellm.model_cost.pop(self.PTU_DEPLOYMENT, None) + self._unregister_models() + def test_spillover_header_does_not_touch_non_ptu_custom_pricing(self, monkeypatch) -> None: self._register_models() custom_model_id: Final = "non-ptu-custom-router-model-id" @@ -11014,6 +11290,87 @@ def test_uncached_price_leaves_no_failure_debug_info_for_unpriced_model(): assert "response_cost_failure_debug_information" not in logging_obj.model_call_details +PR44187_PRICED_MODEL: Final = "lit44187-priced-model" +PR44187_INPUT_COST: Final = 1e-6 +PR44187_OUTPUT_COST: Final = 2e-6 +PR44187_START_TIME: Final = datetime.datetime(2026, 10, 20) + + +@pytest.fixture +def pr44187_priced_model() -> Iterator[str]: + litellm.register_model( + model_cost={ + PR44187_PRICED_MODEL: { + "input_cost_per_token": PR44187_INPUT_COST, + "output_cost_per_token": PR44187_OUTPUT_COST, + "litellm_provider": "openai", + "mode": "chat", + } + }, + persist_across_reloads=False, + ) + try: + yield PR44187_PRICED_MODEL + finally: + litellm.model_cost.pop(PR44187_PRICED_MODEL, None) + + +def _pr44187_logging_obj(model: str) -> LitellmLogging: + logging_obj: Final = LitellmLogging( + model=model, + messages=[{"role": "user", "content": "Hi"}], + stream=True, + call_type="completion", + start_time=PR44187_START_TIME, + litellm_call_id="lit44187-late-priced-stream", + function_id="fn", + ) + logging_obj.update_environment_variables( + model=model, user="", optional_params={}, litellm_params={"metadata": {}}, custom_llm_provider="openai" + ) + return logging_obj + + +def _pr44187_response(model: str) -> ModelResponse: + return ModelResponse( + model=model, + choices=[litellm.Choices(message=litellm.Message(role="assistant", content="hello"))], + usage=litellm.Usage(prompt_tokens=10, completion_tokens=20, total_tokens=30), + ) + + +def test_a_later_successful_price_clears_an_earlier_price_failure(pr44187_priced_model: str): + logging_obj: Final = _pr44187_logging_obj("openai/lit44187-deployment-name") + stream_start_cost: Final = logging_obj.response_cost_calculator( + result=_pr44187_response("lit44187-deployment-name"), litellm_model_name="openai/lit44187-deployment-name" + ) + assert stream_start_cost is None + assert logging_obj.model_call_details["response_cost_failure_debug_information"] is not None + + final_cost: Final = logging_obj.response_cost_calculator( + result=_pr44187_response(pr44187_priced_model), litellm_model_name=pr44187_priced_model + ) + + assert final_cost == pytest.approx(10 * PR44187_INPUT_COST + 20 * PR44187_OUTPUT_COST) + assert logging_obj.model_call_details.get("response_cost_failure_debug_information") is None + + +@pytest.mark.parametrize("uncached_model_is_priced", [True, False], ids=["uncached-priced", "uncached-unpriced"]) +def test_uncached_price_keeps_an_earlier_price_failure(pr44187_priced_model: str, uncached_model_is_priced: bool): + uncached_model: Final = pr44187_priced_model if uncached_model_is_priced else "lit44187-other-unpriced-model" + logging_obj: Final = _pr44187_logging_obj(uncached_model) + logging_obj.response_cost_calculator( + result=_pr44187_response("lit44187-deployment-name"), litellm_model_name="openai/lit44187-deployment-name" + ) + earlier_failure: Final = logging_obj.model_call_details["response_cost_failure_debug_information"] + assert earlier_failure is not None + + uncached: Final = logging_obj.uncached_price(result=_pr44187_response(uncached_model)) + + assert (uncached.cost is not None) is uncached_model_is_priced + assert logging_obj.model_call_details["response_cost_failure_debug_information"] == earlier_failure + + def test_enterprise_alerting_loggers_resolves_real_classes(): from litellm_enterprise.enterprise_callbacks.pagerduty.pagerduty import PagerDutyAlerting from litellm_enterprise.enterprise_callbacks.send_emails.resend_email import ResendEmailLogger diff --git a/tests/unit/litellm_core_utils/test_redact_messages.py b/tests/unit/litellm_core_utils/test_redact_messages.py index d14f236f765..a91888fea79 100644 --- a/tests/unit/litellm_core_utils/test_redact_messages.py +++ b/tests/unit/litellm_core_utils/test_redact_messages.py @@ -26,10 +26,12 @@ import litellm from litellm.constants import LOGGING_WORKER_MAX_TIME_PER_COROUTINE from litellm.integrations.custom_logger import CustomLogger from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER +from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler from litellm.litellm_core_utils.redact_messages import ( _redact_responses_api_output, + _redacted_responses_api_response, perform_redaction, - redact_streaming_responses_for_custom_logger, + redacted_model_call_details_for_custom_logger, redacted_standard_logging_payload, should_redact_message_logging, ) @@ -163,6 +165,80 @@ def test_streaming_redaction_redacts_delta_provider_fields_without_touching_the_ assert fields == _provider_fields() +@pytest.mark.parametrize("surface", ("typed", "dict", "standard", "callback", "helper")) +def test_responses_redaction_removes_instructions_without_changing_the_response(surface: str) -> None: + response: Final = litellm.ResponsesAPIResponse.model_validate( + { + **mock_responses_api_response("private answer").model_dump(), + "instructions": "private system instructions", + "reasoning": {"effort": "low", "summary": "auto"}, + "output": [ + { + "type": "reasoning", + "id": "rs_test", + "summary": [{"type": "summary_text", "text": "private reasoning"}], + }, + { + "type": "function_call", + "id": "fc_test", + "call_id": "call_test", + "name": "lookup", + "arguments": "private arguments", + }, + ], + } + ) + original: Final = response.model_dump() + payload: Final = {"response": copy.deepcopy(original), "model": "test-model"} + logger: Final = CustomLogger() + logger.turn_off_message_logging = True + + surfaces: Final = { + "typed": lambda: perform_redaction({}, response).model_dump(), + "dict": lambda: perform_redaction({}, original), + "helper": lambda: _redacted_responses_api_response(original), + "standard": lambda: redacted_standard_logging_payload(payload)["response"], + "callback": lambda: logger.redact_standard_logging_payload_from_model_call_details( + {"standard_logging_object": payload} + )["standard_logging_object"]["response"], + } + redacted: Final = surfaces[surface]() + + assert redacted == { + **original, + "instructions": "redacted-by-litellm", + **({"reasoning": None} if surface == "typed" else {}), + "output": [ + {**original["output"][0], "summary": [{"type": "summary_text", "text": "redacted-by-litellm"}]}, + {**original["output"][1], "arguments": "redacted-by-litellm"}, + ], + } + assert "private" not in json.dumps(redacted) + assert response.model_dump() == original + assert payload["response"] == original + + +@pytest.mark.parametrize("key", ("complete_streaming_response", "async_complete_streaming_response")) +@pytest.mark.parametrize("redaction", ("global", "custom_logger")) +def test_streaming_responses_redact_instructions_without_changing_the_client_response(key: str, redaction: str) -> None: + response: Final = mock_responses_api_response("private answer").model_copy( + update={"instructions": "private system instructions"} + ) + original: Final = response.model_dump() + details: Final = {"stream": True, key: response} + if redaction == "global": + perform_redaction(details, result=None) + redacted_details: Final = ( + redacted_model_call_details_for_custom_logger(details, CustomLogger(message_logging=False)) + if redaction == "custom_logger" + else details + ) + + assert redacted_details[key].instructions == "redacted-by-litellm" + assert "private" not in json.dumps(redacted_details[key].model_dump()) + assert response.model_dump() == original + + @pytest.fixture(autouse=True) def _reset_global_redaction(): """Ensure the global setting is off for every test.""" @@ -335,7 +411,7 @@ class TestPerformRedaction: result = { "output": [ {"text": "top-level result"}, - {"content": [{"text": "nested result"}]}, + {"content": [{"text": "nested result"}, "non-dict content item"]}, {"type": "reasoning", "summary": [{"text": "reasoning result"}]}, ], "usage": {"total_tokens": 1}, @@ -356,6 +432,7 @@ class TestPerformRedaction: assert redacted["usage"] == {"total_tokens": 1} assert redacted["output"][0]["text"] == "redacted-by-litellm" assert redacted["output"][1]["content"][0]["text"] == "redacted-by-litellm" + assert redacted["output"][1]["content"][1] == "non-dict content item" assert redacted["output"][2]["summary"][0]["text"] == "redacted-by-litellm" assert result["output"][0]["text"] == "top-level result" @@ -791,12 +868,14 @@ class TestPerformRedaction: none_dict = {"type": "output_text", "text": None, "content": [{"text": None}]} real_dict = {"type": "output_text", "text": "real answer", "content": [{"text": "real part"}]} - _redact_responses_api_output_dict([none_dict, real_dict], "redacted-by-litellm") + redacted: Final = _redact_responses_api_output_dict([none_dict, real_dict], "redacted-by-litellm") - assert none_dict["text"] is None - assert none_dict["content"][0]["text"] is None - assert real_dict["text"] == "redacted-by-litellm" - assert real_dict["content"][0]["text"] == "redacted-by-litellm" + assert redacted == [ + {"type": "output_text", "text": None, "content": [{"text": None}]}, + {"type": "output_text", "text": "redacted-by-litellm", "content": [{"text": "redacted-by-litellm"}]}, + ] + assert none_dict == {"type": "output_text", "text": None, "content": [{"text": None}]} + assert real_dict == {"type": "output_text", "text": "real answer", "content": [{"text": "real part"}]} def test_skips_non_dict_response_output_items(self): result = { @@ -1003,33 +1082,36 @@ class TestPerformRedaction: class TestRedactStreamingResponsesForCustomLogger: - def _model_call_details(self): + def _model_call_details(self, key: str = "async_complete_streaming_response"): response_obj = litellm.ModelResponse( choices=[litellm.Choices(message=litellm.Message(content="secret content", role="assistant"))] ) return { "stream": True, - "async_complete_streaming_response": response_obj, + key: response_obj, }, response_obj - def test_opted_out_logger_gets_redacted_copy(self): - model_call_details, response_obj = self._model_call_details() + @pytest.mark.parametrize( + "key", ["async_complete_streaming_response", "complete_streaming_response", "complete_response"] + ) + def test_opted_out_logger_gets_redacted_copy(self, key: str): + model_call_details, response_obj = self._model_call_details(key) opted_out_logger = CustomLogger(message_logging=False) - redacted_details = redact_streaming_responses_for_custom_logger( + redacted_details = redacted_model_call_details_for_custom_logger( model_call_details=model_call_details, custom_logger=opted_out_logger ) - redacted_response = redacted_details["async_complete_streaming_response"] + redacted_response = redacted_details[key] assert redacted_response.choices[0].message.content == "redacted-by-litellm" assert response_obj.choices[0].message.content == "secret content" - assert model_call_details["async_complete_streaming_response"] is response_obj + assert model_call_details[key] is response_obj def test_compliant_logger_gets_shared_response(self): model_call_details, response_obj = self._model_call_details() compliant_logger = CustomLogger() - result_details = redact_streaming_responses_for_custom_logger( + result_details = redacted_model_call_details_for_custom_logger( model_call_details=model_call_details, custom_logger=compliant_logger ) @@ -1302,11 +1384,15 @@ class TestCustomLogger(CustomLogger): super().__init__(*args, **kwargs) self.logged_standard_logging_payload: Optional[StandardLoggingPayload] = None self.response_obj: Optional[Union[ModelResponse, TextCompletionResponse, ResponsesAPIResponse]] = None + self.logged_kwargs: Optional[dict] = None + self.logged = asyncio.Event() async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): standard_logging_payload = kwargs.get("standard_logging_object", None) self.logged_standard_logging_payload = standard_logging_payload self.response_obj = response_obj + self.logged_kwargs = kwargs + self.logged.set() @pytest.mark.usefixtures("_vcr_outcome_gate", "drain_logging_worker", "isolate_litellm_state", "setup_and_teardown") @@ -1506,6 +1592,141 @@ async def test_redaction_responses_api(): ) +@pytest.mark.usefixtures("drain_logging_worker", "isolate_litellm_state", "setup_and_teardown") +@pytest.mark.parametrize( + "redaction, logged_keys", + [ + ("global", ("instructions", "optional_params", "litellm_params", "standard_logging_object")), + ("custom_logger", ("litellm_params", "standard_logging_object")), + ], +) +@pytest.mark.asyncio +async def test_responses_redaction_removes_request_instructions_from_logged_kwargs( + redaction: str, logged_keys: tuple[str, ...], monkeypatch: pytest.MonkeyPatch +) -> None: + test_custom_logger: Final = TestCustomLogger(turn_off_message_logging=redaction == "custom_logger") + monkeypatch.setattr(litellm, "turn_off_message_logging", redaction == "global") + monkeypatch.setattr(litellm, "callbacks", [test_custom_logger]) + provider_reply: Final = {**mock_responses_api_response("private answer").model_dump(), "instructions": SECRET} + + await litellm.aresponses( + model="openai/gpt-5-mini", + input="hi", + instructions=SECRET, + api_key="fake-key", + client=AsyncHTTPHandler( + transport=httpx.MockTransport(lambda request: httpx.Response(200, json=provider_reply, request=request)) + ), + ) + + await asyncio.wait_for(test_custom_logger.logged.wait(), timeout=LOGGING_WORKER_DRAIN_TIMEOUT_SECONDS) + kwargs: Final = test_custom_logger.logged_kwargs + assert kwargs is not None + assert kwargs["standard_logging_object"]["model_parameters"]["instructions"] == "redacted-by-litellm" + assert SECRET not in json.dumps({key: kwargs.get(key) for key in logged_keys}, default=str) + + +@pytest.mark.usefixtures("drain_logging_worker", "isolate_litellm_state", "setup_and_teardown") +@pytest.mark.asyncio +async def test_one_callback_opting_out_redacts_instructions_only_for_itself( + monkeypatch: pytest.MonkeyPatch, +) -> None: + opted_out: Final = TestCustomLogger(message_logging=False) + sibling: Final = TestCustomLogger() + monkeypatch.setattr(litellm, "callbacks", [opted_out, sibling]) + provider_reply: Final = {**mock_responses_api_response("private answer").model_dump(), "instructions": SECRET} + + await litellm.aresponses( + model="openai/gpt-5-mini", + input="hi", + instructions=SECRET, + api_key="fake-key", + client=AsyncHTTPHandler( + transport=httpx.MockTransport(lambda request: httpx.Response(200, json=provider_reply, request=request)) + ), + ) + + await asyncio.wait_for( + asyncio.gather(sibling.logged.wait(), opted_out.logged.wait()), timeout=LOGGING_WORKER_DRAIN_TIMEOUT_SECONDS + ) + assert _logged_instructions(sibling) == (SECRET,) * 6 + assert _logged_instructions(opted_out) == ("redacted-by-litellm",) * 6 + + +class SyncTestCustomLogger(TestCustomLogger): + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + self.logged_in_thread = threading.Event() + + def log_success_event(self, kwargs, response_obj, start_time, end_time): + self.response_obj = response_obj + self.logged_kwargs = kwargs + self.logged_in_thread.set() + + +@pytest.mark.usefixtures("drain_logging_worker", "isolate_litellm_state", "setup_and_teardown") +def test_one_callback_opting_out_on_a_sync_call_gets_a_redacted_copy_only_for_itself( + monkeypatch: pytest.MonkeyPatch, +) -> None: + opted_out: Final = SyncTestCustomLogger(message_logging=False) + sibling: Final = SyncTestCustomLogger() + monkeypatch.setattr(litellm, "callbacks", [opted_out, sibling]) + provider_reply: Final = {**mock_responses_api_response("private answer").model_dump(), "instructions": SECRET} + + litellm.responses( + model="openai/gpt-5-mini", + input="private question", + instructions=SECRET, + api_key="fake-key", + client=HTTPHandler( + client=httpx.Client( + transport=httpx.MockTransport(lambda request: httpx.Response(200, json=provider_reply, request=request)) + ) + ), + ) + + assert sibling.logged_in_thread.wait(LOGGING_WORKER_DRAIN_TIMEOUT_SECONDS) + assert opted_out.logged_in_thread.wait(LOGGING_WORKER_DRAIN_TIMEOUT_SECONDS) + assert _logged_instructions(sibling) == (SECRET,) * 6 + assert _logged_instructions(opted_out) == ("redacted-by-litellm",) * 6 + assert _logged_question_and_answer(sibling) == (True, True) + assert _logged_question_and_answer(opted_out) == (False, False) + + +def _logged_question_and_answer(logger: TestCustomLogger) -> tuple[bool, bool]: + kwargs: Final = logger.logged_kwargs + assert kwargs is not None + assert isinstance(logger.response_obj, ResponsesAPIResponse) + request_text: Final = json.dumps([kwargs.get(key) for key in ("messages", "input", "prompt")], default=str) + return "private question" in request_text, "private answer" in logger.response_obj.model_dump_json() + + +def _logged_instructions(logger: TestCustomLogger) -> tuple[object, ...]: + kwargs: Final = logger.logged_kwargs + assert kwargs is not None + assert isinstance(logger.response_obj, ResponsesAPIResponse) + return ( + kwargs["instructions"], + kwargs["optional_params"]["instructions"], + kwargs["litellm_params"]["instructions"], + kwargs["standard_logging_object"]["model_parameters"]["instructions"], + kwargs["standard_logging_object"]["response"]["instructions"], + logger.response_obj.instructions, + ) + + +def test_request_body_redaction_replaces_instructions_only_when_sent() -> None: + responses_body: Final = {"model": "gpt-5-mini", "input": SECRET, "instructions": SECRET} + chat_body: Final = {"model": "gpt-5-mini", "messages": [{"role": "user", "content": SECRET}]} + + perform_redaction(responses_body, result=None) + perform_redaction(chat_body, result=None) + + assert responses_body["instructions"] == "redacted-by-litellm" + assert SECRET not in json.dumps(responses_body) + assert "instructions" not in chat_body + + @pytest.mark.usefixtures("_vcr_outcome_gate", "drain_logging_worker", "isolate_litellm_state", "setup_and_teardown") @pytest.mark.asyncio async def test_redaction_responses_api_stream(): diff --git a/tests/unit/litellm_core_utils/test_streaming_handler.py b/tests/unit/litellm_core_utils/test_streaming_handler.py index 691442e80d0..68aabc3c01e 100644 --- a/tests/unit/litellm_core_utils/test_streaming_handler.py +++ b/tests/unit/litellm_core_utils/test_streaming_handler.py @@ -1,4 +1,5 @@ import asyncio +import datetime import json import sys import threading @@ -18,6 +19,7 @@ import litellm from litellm import verbose_logger from litellm._logging import session_id_var, trace_id_var from litellm.exceptions import MidStreamFallbackError +from litellm.integrations.custom_logger import CustomLogger from litellm.litellm_core_utils.get_litellm_params import get_litellm_params from litellm.litellm_core_utils.litellm_logging import Logging from litellm.litellm_core_utils.streaming_handler import ( @@ -26,6 +28,7 @@ from litellm.litellm_core_utils.streaming_handler import ( _ProviderChunkParsed, ) from litellm.llms.custom_httpx.http_handler import HTTPHandler +from litellm.responses.mcp.chat_completions_handler import _add_mcp_metadata_to_response from litellm.types.utils import ( CompletionTokensDetailsWrapper, Delta, @@ -2820,6 +2823,238 @@ def test_usage_chunk_after_finish_reason_updates_hidden_params(logging_obj): ), f"Expected completion_tokens=135 from provider, got {hidden_usage.completion_tokens}" +@pytest.mark.parametrize("sync_mode", [True, False]) +@pytest.mark.parametrize("ends_with_finish_chunk", [True, False]) +@pytest.mark.asyncio +async def test_stream_without_provider_usage_falls_back_to_the_token_estimate( + sync_mode: bool, ends_with_finish_chunk: bool +) -> None: + model: Final = "gpt-4o" + messages: Final = [{"role": "user", "content": "Write a long sentence about a fox. " * 30}] + text: Final = "The quick brown fox jumps over the lazy dog. " * 20 + content_chunk: Final = ModelResponseStream( + id="chatcmpl-no-usage", + created=1741037890, + model=model, + choices=[StreamingChoices(index=0, delta=Delta(role="assistant", content=text))], + ) + finish_chunk: Final = ModelResponseStream( + id="chatcmpl-no-usage", + created=1741037890, + model=model, + choices=[StreamingChoices(index=0, delta=Delta(content=""), finish_reason="stop")], + ) + wrapper: Final = CustomStreamWrapper( + completion_stream=ModelResponseListIterator( + model_responses=[content_chunk, finish_chunk] if ends_with_finish_chunk else [content_chunk] + ), + model=model, + custom_llm_provider="openai", + logging_obj=Logging( + model=model, + messages=messages, + stream=True, + call_type="completion", + start_time=datetime.datetime(2025, 3, 3, 21, 38, 10), + litellm_call_id="no-usage-call", + function_id="no-usage-fn", + ), + stream_options=None, + ) + + yielded: Final = ( + [(chunk, chunk._hidden_params.get("usage")) for chunk in wrapper] + if sync_mode + else [(chunk, chunk._hidden_params.get("usage")) async for chunk in wrapper] + ) + collected: Final = [chunk for chunk, _ in yielded] + + expected: Final = ( + litellm.token_counter(model=model, messages=messages), + litellm.token_counter(model=model, text=text, count_response_tokens=True), + ) + assembled: Final = litellm.stream_chunk_builder(chunks=collected, messages=messages) + assert assembled is not None + assert (assembled.usage.prompt_tokens, assembled.usage.completion_tokens) == expected + last_chunk, usage_when_yielded = yielded[-1] + assert usage_when_yielded is not None + usage_after_drain: Final = last_chunk._hidden_params["usage"] + assert (usage_after_drain.prompt_tokens, usage_after_drain.completion_tokens) == expected + + rates: Final = litellm.model_cost[model] + spend: Final = expected[0] * rates["input_cost_per_token"] + expected[1] * rates["output_cost_per_token"] + assert litellm.completion_cost(completion_response=assembled) == pytest.approx(spend) + + +@pytest.mark.parametrize("sync_mode", [True, False]) +@pytest.mark.asyncio +async def test_stream_with_usage_after_the_finish_chunk_bills_only_the_reported_usage(sync_mode: bool) -> None: + model: Final = "gpt-4o" + messages: Final = [{"role": "user", "content": "Write a long sentence about a fox. " * 30}] + text: Final = "The quick brown fox jumps over the lazy dog. " * 20 + reported: Final = (6, 20) + chunks: Final = [ + ModelResponseStream(id="cmpl-late-usage", created=1741037890, model=model, choices=choices, usage=usage) + for choices, usage in ( + ([StreamingChoices(index=0, delta=Delta(role="assistant", content=text))], None), + ([StreamingChoices(index=0, delta=Delta(content=""), finish_reason="length")], None), + ([], Usage(prompt_tokens=reported[0], completion_tokens=reported[1], total_tokens=sum(reported))), + ) + ] + wrapper: Final = CustomStreamWrapper( + completion_stream=ModelResponseListIterator(model_responses=chunks), + model=model, + custom_llm_provider="openai", + logging_obj=Logging( + model=model, + messages=messages, + stream=True, + call_type="completion", + start_time=datetime.datetime(2025, 3, 3, 21, 38, 10), + litellm_call_id="late-usage-call", + function_id="late-usage-fn", + ), + stream_options=None, + ) + + collected: Final = [chunk for chunk in wrapper] if sync_mode else [chunk async for chunk in wrapper] + + usage_after_drain: Final = collected[-1]._hidden_params["usage"] + assert (usage_after_drain.prompt_tokens, usage_after_drain.completion_tokens) == reported + assembled: Final = litellm.stream_chunk_builder(chunks=collected, messages=messages) + assert assembled is not None + rates: Final = litellm.model_cost[model] + spend: Final = reported[0] * rates["input_cost_per_token"] + reported[1] * rates["output_cost_per_token"] + assert litellm.completion_cost(completion_response=assembled) == pytest.approx(spend) + + +class _LoggedResponseRecorder(CustomLogger): + def __init__(self) -> None: + super().__init__() + self.responses: list[object] = [] + self.logged: Final = threading.Event() + + def log_success_event(self, kwargs: object, response_obj: object, start_time: object, end_time: object) -> None: + self.responses.append(response_obj) + self.logged.set() + + async def async_log_success_event( + self, kwargs: object, response_obj: object, start_time: object, end_time: object + ) -> None: + self.responses.append(response_obj) + self.logged.set() + + +@pytest.mark.parametrize("sync_mode", [True, False]) +@pytest.mark.asyncio +async def test_stream_without_provider_usage_logs_the_estimate_with_the_final_chunk_mcp_metadata( + sync_mode: bool, +) -> None: + model: Final = "gpt-4o" + messages: Final = [{"role": "user", "content": "Write a long sentence about a fox. " * 30}] + text: Final = "The quick brown fox jumps over the lazy dog. " * 20 + tool_calls: Final = [{"name": "lookup_fox", "arguments": "{}"}] + recorder: Final = _LoggedResponseRecorder() + logging_obj: Final = Logging( + model=model, + messages=messages, + stream=True, + call_type="completion" if sync_mode else "acompletion", + start_time=datetime.datetime(2025, 3, 3, 21, 38, 10), + litellm_call_id="mcp-no-usage-call", + function_id="mcp-no-usage-fn", + dynamic_success_callbacks=[recorder], + dynamic_async_success_callbacks=[recorder], + ) + logging_obj.update_environment_variables( + model=model, user=None, optional_params={}, litellm_params={"litellm_call_id": "mcp-no-usage-call"} + ) + wrapper: Final = CustomStreamWrapper( + completion_stream=ModelResponseListIterator( + model_responses=[ + ModelResponseStream(id="chatcmpl-mcp", created=1741037890, model=model, choices=choices) + for choices in ( + [StreamingChoices(index=0, delta=Delta(role="assistant", content=text))], + [StreamingChoices(index=0, delta=Delta(content=""), finish_reason="stop")], + ) + ] + ), + model=model, + custom_llm_provider="openai", + logging_obj=logging_obj, + stream_options=None, + ) + _add_mcp_metadata_to_response(wrapper, openai_tools=None, tool_calls=tool_calls) + + _ = [chunk for chunk in wrapper] if sync_mode else [chunk async for chunk in wrapper] + + assert await asyncio.to_thread(recorder.logged.wait, 5) + assert len(recorder.responses) == 1 + logged: Final = recorder.responses[0] + assert isinstance(logged, ModelResponse) + assert logged.choices[0].message.provider_specific_fields == {"mcp_tool_calls": tool_calls} + assert (logged.usage.prompt_tokens, logged.usage.completion_tokens) == ( + litellm.token_counter(model=model, messages=messages), + litellm.token_counter(model=model, text=text, count_response_tokens=True), + ) + + +@pytest.mark.parametrize("sync_mode", [True, False]) +@pytest.mark.parametrize("ends_with_finish_chunk", [True, False]) +@pytest.mark.parametrize("reported_tokens", [(30, 12), (0, 0)]) +@pytest.mark.asyncio +async def test_stream_with_provider_usage_hands_that_usage_to_the_last_chunk( + logging_obj: Logging, sync_mode: bool, ends_with_finish_chunk: bool, reported_tokens: tuple[int, int] +) -> None: + model: Final = "gpt-4o" + reported: Final = Usage( + prompt_tokens=reported_tokens[0], + completion_tokens=reported_tokens[1], + total_tokens=sum(reported_tokens), + ) + content_chunk: Final = ModelResponseStream( + id="chatcmpl-with-usage", + created=1741037890, + model=model, + choices=[ + StreamingChoices( + index=0, + delta=Delta(role="assistant", content="Hello there"), + finish_reason=None if ends_with_finish_chunk else "stop", + ) + ], + **({} if ends_with_finish_chunk else {"usage": reported}), + ) + finish_chunk: Final = ModelResponseStream( + id="chatcmpl-with-usage", + created=1741037890, + model=model, + choices=[StreamingChoices(index=0, delta=Delta(content=""), finish_reason="stop")], + usage=reported, + ) + wrapper: Final = CustomStreamWrapper( + completion_stream=ModelResponseListIterator( + model_responses=[content_chunk, finish_chunk] if ends_with_finish_chunk else [content_chunk] + ), + model=model, + custom_llm_provider="openai", + logging_obj=logging_obj, + stream_options=None, + ) + + yielded: Final = ( + [(chunk, chunk._hidden_params.get("usage")) for chunk in wrapper] + if sync_mode + else [(chunk, chunk._hidden_params.get("usage")) async for chunk in wrapper] + ) + + last_chunk, usage_when_yielded = yielded[-1] + assert usage_when_yielded is not None + assert (usage_when_yielded.prompt_tokens, usage_when_yielded.completion_tokens) == reported_tokens + usage_after_drain: Final = last_chunk._hidden_params["usage"] + assert (usage_after_drain.prompt_tokens, usage_after_drain.completion_tokens) == reported_tokens + + @pytest.mark.asyncio async def test_custom_stream_wrapper_aclose(): """Test that aclose() delegates to the underlying completion_stream's aclose()""" diff --git a/tests/unit/llms/anthropic/chat/guardrail_translation/test_anthropic_guardrail_handler.py b/tests/unit/llms/anthropic/chat/guardrail_translation/test_anthropic_guardrail_handler.py index 58e3b55773b..8218c120153 100644 --- a/tests/unit/llms/anthropic/chat/guardrail_translation/test_anthropic_guardrail_handler.py +++ b/tests/unit/llms/anthropic/chat/guardrail_translation/test_anthropic_guardrail_handler.py @@ -18,6 +18,7 @@ from litellm.llms.base_llm.guardrail_translation.base_translation import Streami from litellm.llms.anthropic.chat.guardrail_translation.handler import ( AnthropicMessagesHandler, ) +from litellm.llms.anthropic.pass_through.adapters.transformation import truncate_tool_name from litellm.types.utils import ChatCompletionMessageToolCall, GenericGuardrailAPIInputs @@ -2693,6 +2694,143 @@ class TestStructuredWriteBackKeepsToolResults: ] +class NamelessComputerToolGuardrail(CustomGuardrail): + """Guardrail that appends an OpenAI-format computer tool without a function name.""" + + async def apply_guardrail( + self, + inputs: GenericGuardrailAPIInputs, + request_data: dict, + input_type: Literal["request", "response"], + logging_obj: Optional[Any] = None, + ) -> GenericGuardrailAPIInputs: + computer = {"display_width_px": 1024, "display_height_px": 768} + inputs["tools"] = [ + *(inputs.get("tools") or []), + {"type": "computer_20250124", "function": {"parameters": computer}}, + ] + return inputs + + +class TestLongToolNamesSurviveTheWriteBack: + """Names over OpenAI's 64-char limit are shortened only for the guardrail, never in the request (LIT-9528).""" + + _PREFIX: Final = "mcp__plugin_support-kit_remote-workspace__getAccessibleWorkspace" + _SHORT_NAMES: Final = {"searched": "searched_tool", "called": "called_tool", "dropped": "dropped_tool"} + _LONG_NAMES: Final = { + "searched": _PREFIX + "Resources", + "called": _PREFIX + "Projects", + "dropped": _PREFIX + "Archives", + } + + @staticmethod + def _tool(name: str) -> dict: + return {"name": name, "description": "Returns OK", "input_schema": {"type": "object", "properties": {}}} + + def _request(self, searched: str, called: str, dropped: str) -> dict: + return { + "model": "claude-sonnet-5-5", + "tools": [self._tool("ToolSearch"), self._tool(searched), self._tool(called)], + "tool_choice": {"type": "tool", "name": called}, + "messages": [ + {"role": "user", "content": "find the tools for bob@example.com"}, + { + "role": "assistant", + "content": [ + {"type": "text", "text": "Searching."}, + {"type": "tool_use", "id": "toolu_01", "name": "ToolSearch", "input": {"query": "x"}}, + {"type": "tool_use", "id": "toolu_02", "name": called, "input": {"page": 2}}, + {"type": "tool_use", "id": "toolu_03", "name": dropped, "input": {"all": True}}, + ], + }, + { + "role": "user", + "content": [ + { + "type": "tool_result", + "tool_use_id": "toolu_01", + "content": [{"type": "tool_reference", "tool_name": searched}], + }, + {"type": "tool_result", "tool_use_id": "toolu_02", "content": "OK"}, + {"type": "tool_result", "tool_use_id": "toolu_03", "content": "OK"}, + ], + }, + {"role": "user", "content": "say done"}, + ], + } + + async def _processed(self, guardrail: CustomGuardrail, names: dict) -> dict: + data = self._request(**names) + await AnthropicMessagesHandler().process_input_messages(data=data, guardrail_to_apply=guardrail) + return {key: value for key, value in data.items() if key != "metadata"} + + def _with_long_names(self, processed: dict) -> dict: + text = json.dumps(processed) + for role, short in self._SHORT_NAMES.items(): + text = text.replace(f'"{short}"', f'"{self._LONG_NAMES[role]}"') + return json.loads(text) + + @pytest.mark.parametrize( + "guardrail", + [ + MockPassThroughGuardrail(guardrail_name="test"), + ToolAppendingGuardrail(guardrail_name="test"), + MockStructuredMaskingGuardrail(), + ], + ids=["echoed-tools", "injected-tool", "rewritten-messages"], + ) + async def test_long_tool_names_come_back_exactly_like_short_ones(self, guardrail): + short = await self._processed(guardrail, self._SHORT_NAMES) + long = await self._processed(guardrail, self._LONG_NAMES) + + assert long == self._with_long_names(short) + assert long["tool_choice"] == {"type": "tool", "name": self._LONG_NAMES["called"]} + + @pytest.mark.parametrize( + "guardrail", + [MockPassThroughGuardrail(guardrail_name="test"), MockStructuredMaskingGuardrail()], + ids=["echoed-tools", "rewritten-messages"], + ) + async def test_short_tool_named_like_a_shortened_history_tool_keeps_its_name(self, guardrail): + alias = truncate_tool_name(self._LONG_NAMES["dropped"]) + names = {**self._LONG_NAMES, "called": alias} + + data = await self._processed(guardrail, names) + + assert [tool["name"] for tool in data["tools"]] == ["ToolSearch", self._LONG_NAMES["searched"], alias] + assert data["tool_choice"] == {"type": "tool", "name": alias} + assert data["messages"][1]["content"][2] == { + "type": "tool_use", + "id": "toolu_02", + "name": alias, + "input": {"page": 2}, + } + + async def test_history_tool_with_the_same_shortened_name_cannot_rename_a_declared_tool(self): + declared, historical = ( + "mcp__plugin_support-kit_remote-workspace__getAccessibleWorkspaceResources_7aeb", + "mcp__plugin_support-kit_remote-workspace__getAccessibleWorkspaceResources_c034", + ) + assert truncate_tool_name(declared) == truncate_tool_name(historical) + + data = await self._processed( + MockPassThroughGuardrail(guardrail_name="test"), + {**self._LONG_NAMES, "called": declared, "dropped": historical}, + ) + + assert [tool["name"] for tool in data["tools"]] == ["ToolSearch", self._LONG_NAMES["searched"], declared] + + async def test_guardrail_tool_without_a_function_name_still_reaches_the_request(self): + data = await self._processed(NamelessComputerToolGuardrail(guardrail_name="test"), self._LONG_NAMES) + + assert data["tools"][-1] == { + "type": "computer_20250124", + "name": "computer", + "display_width_px": 1024, + "display_height_px": 768, + } + + class TestAnthropicMessagesHandlerStreamingScanKey: """get_streaming_scan_key mirrors what process_output_streaming_response would scan""" diff --git a/tests/unit/llms/anthropic/chat/test_anthropic_chat_handler.py b/tests/unit/llms/anthropic/chat/test_anthropic_chat_handler.py index a2d9f321122..1f4a5aaa256 100644 --- a/tests/unit/llms/anthropic/chat/test_anthropic_chat_handler.py +++ b/tests/unit/llms/anthropic/chat/test_anthropic_chat_handler.py @@ -3108,6 +3108,92 @@ def test_streamed_json_mode_answer_with_a_foreign_name_matches_the_non_streamed_ assert unwrap_response_format_envelope(answer, schema, RESPONSE_FORMAT_TOOL_NAME) == answer +def test_streamed_json_mode_tool_name_envelope_around_an_input_wrapper_is_unwrapped_to_the_answer(): + envelope = json.dumps({"name": RESPONSE_FORMAT_TOOL_NAME, "arguments": {"input": _STREAMED_RISK_OBJECT}}) + + contents = _streamed_json_mode_contents((envelope[:9], envelope[9:40], envelope[40:])) + + assert json.loads("".join(contents)) == _STREAMED_RISK_OBJECT + + +def test_streamed_json_mode_unwrapped_answer_keeps_non_ascii_text(): + answer = {"tier": 3, "summary": "Hôtel Lutetia, 東京"} + envelope = json.dumps({"input": answer}, ensure_ascii=False) + + contents = _streamed_json_mode_contents((envelope[:9], envelope[9:30], envelope[30:])) + + assert "Hôtel Lutetia, 東京" in "".join(contents) + assert json.loads("".join(contents)) == answer + + +def test_streamed_json_mode_unwrapped_answer_with_a_lone_surrogate_stays_utf8_encodable(): + answer = {"tier": 3, "summary": "smile \ud83d end"} + envelope = json.dumps({"input": answer}) + + contents = _streamed_json_mode_contents((envelope[:9], envelope[9:30], envelope[30:])) + + assert json.loads("".join(contents).encode("utf-8")) == answer + + +_CUT_STREAM_FRAGMENTS: Final = ( + pytest.param( + json.dumps({"name": RESPONSE_FORMAT_TOOL_NAME, "parameters": _STREAMED_RISK_OBJECT})[:-1], + id="held_envelope", + ), + pytest.param(json.dumps(_STREAMED_RISK_OBJECT), id="streamed_answer"), +) + + +def _cut_stream_lines(sent: str) -> tuple[bytes, ...]: + events: Final = _json_tool_events((sent[:9], sent[9:30], sent[30:])) + return tuple(f"data: {json.dumps(event)}\n".encode() for event in events[:-2]) + + +def _cut_stream_iterator(sync_stream: bool, streaming_response: object) -> ModelResponseIterator: + return ModelResponseIterator( + streaming_response=streaming_response, + sync_stream=sync_stream, + json_mode=True, + response_format_schema=response_format_schema(_STREAMED_RISK_SCHEMA), + ) + + +@pytest.mark.parametrize("sent", _CUT_STREAM_FRAGMENTS) +def test_streamed_json_mode_text_is_delivered_when_the_stream_ends_before_the_block_stops(sent: str): + iterator = _cut_stream_iterator(True, iter(_cut_stream_lines(sent))) + + assert "".join(chunk.choices[0].delta.content or "" for chunk in iterator) == sent + + +@pytest.mark.asyncio +@pytest.mark.parametrize("sent", _CUT_STREAM_FRAGMENTS) +async def test_async_streamed_json_mode_text_is_delivered_when_the_stream_ends_before_the_block_stops(sent: str): + async def lines(): + for line in _cut_stream_lines(sent): + yield line + + iterator = _cut_stream_iterator(False, lines()) + + assert "".join([chunk.choices[0].delta.content or "" async for chunk in iterator]) == sent + + +def test_streamed_json_mode_complete_envelope_is_unwrapped_when_the_stream_ends_before_the_block_stops(): + envelope = json.dumps({"name": RESPONSE_FORMAT_TOOL_NAME, "parameters": _STREAMED_RISK_OBJECT}) + + iterator = _cut_stream_iterator(True, iter(_cut_stream_lines(envelope))) + + assert json.loads("".join(chunk.choices[0].delta.content or "" for chunk in iterator)) == _STREAMED_RISK_OBJECT + + +def test_streamed_json_mode_answer_keyed_by_a_required_only_name_is_kept_whole(): + required_only_schema = {"type": "object", "properties": {"id": {"type": "string"}}, "required": ["payload"]} + encoded = json.dumps({"payload": {"id": "abc", "rows": 3}}) + + contents = _streamed_json_mode_contents((encoded[:12], encoded[12:24], encoded[24:]), required_only_schema) + + assert "".join(contents) == encoded + + def _json_tool_block_events(index: int, encoded: str) -> tuple[dict[str, object], ...]: return ( { @@ -3202,6 +3288,30 @@ def test_streamed_json_mode_answer_split_into_one_partial_object_per_field_arriv assert contents[3] == blocks[0][:-1] +@pytest.mark.parametrize( + "blocks", + [ + pytest.param((_STREAMED_TIER_FIELD, _STREAMED_SUMMARY_FIELD), id="one_block_per_field"), + pytest.param( + tuple(json.dumps({name: value}) for name, value in _STREAMED_RISK_OBJECT.items()), + id="one_partial_object_per_field", + ), + ], +) +def test_streamed_json_mode_split_answer_arrives_as_one_object_when_the_stream_ends_in_its_last_block( + blocks: tuple[str, ...], +): + message_start, *_ = _json_tool_events(()) + events = ( + message_start, + *chain.from_iterable(_json_tool_block_events(index, encoded) for index, encoded in enumerate(blocks)), + )[:-1] + + iterator = _cut_stream_iterator(True, iter(tuple(f"data: {json.dumps(event)}\n".encode() for event in events))) + + assert json.loads("".join(chunk.choices[0].delta.content or "" for chunk in iterator)) == _STREAMED_RISK_OBJECT + + def test_streamed_json_mode_empty_object_then_field_blocks_arrives_as_one_object(): blocks = ("{}", *(json.dumps({name: value}) for name, value in _STREAMED_RISK_OBJECT.items())) diff --git a/tests/unit/llms/anthropic/chat/test_anthropic_chat_transformation.py b/tests/unit/llms/anthropic/chat/test_anthropic_chat_transformation.py index ef8447712d6..32f18b952ac 100644 --- a/tests/unit/llms/anthropic/chat/test_anthropic_chat_transformation.py +++ b/tests/unit/llms/anthropic/chat/test_anthropic_chat_transformation.py @@ -2251,6 +2251,38 @@ def test_effort_with_other_features(): assert "thinking" in result +_OBJECT_OUTPUT_FORMAT: Final = {"type": "json_schema", "schema": {"type": "object", "properties": {}}} + + +@pytest.mark.parametrize( + ("output_format", "request_drop_params", "global_drop_params", "forwarded"), + [ + pytest.param("json", True, False, False, id="string_dropped_under_request_drop_params"), + pytest.param("json", None, True, False, id="string_dropped_under_global_drop_params"), + pytest.param("json", None, False, True, id="string_forwarded_without_drop_params"), + pytest.param(_OBJECT_OUTPUT_FORMAT, True, False, True, id="object_kept_under_drop_params"), + ], +) +def test_anthropic_chat_drops_only_a_non_object_output_format_and_only_under_drop_params( + output_format: object, + request_drop_params: bool | None, + global_drop_params: bool, + forwarded: bool, + monkeypatch: pytest.MonkeyPatch, +): + monkeypatch.setattr(litellm, "drop_params", global_drop_params) + + result = AnthropicConfig().transform_request( + model="claude-haiku-4-5", + messages=[{"role": "user", "content": "Hello"}], + optional_params={"output_format": output_format}, + litellm_params={"drop_params": request_drop_params}, + headers={}, + ) + + assert result.get("output_format") == (output_format if forwarded else None) + + def test_anthropic_drop_params_strips_output_config_for_pre_4_5_models(): """``drop_params=True`` strips unsupported ``output_config`` for pre-4.5 models.""" config = AnthropicConfig() @@ -7882,6 +7914,24 @@ def _json_tool_call(arguments: object) -> list[ChatCompletionToolCallChunk]: {"summary": "likes tea"}, id="tool_name_envelope_on_a_schema_allowing_extra_keys", ), + pytest.param( + {"type": "object", "properties": {"id": {"type": "string"}}, "required": ["payload"]}, + {"payload": {"id": "abc", "rows": 3}}, + {"payload": {"id": "abc", "rows": 3}}, + id="key_listed_only_in_required", + ), + pytest.param( + _RISK_SCHEMA, + {"name": RESPONSE_FORMAT_TOOL_NAME, "arguments": {"input": _RISK_OBJECT}}, + _RISK_OBJECT, + id="tool_name_envelope_around_an_input_wrapper", + ), + pytest.param( + _PER_USER_SCHEMA, + {"name": RESPONSE_FORMAT_TOOL_NAME, "parameters": _PER_USER_ANSWER}, + _PER_USER_ANSWER, + id="tool_name_envelope_around_an_answer_with_one_allowed_key", + ), ], ) def test_convert_tool_response_to_message_unwraps_only_an_unambiguous_schema_envelope( @@ -7896,6 +7946,31 @@ def test_convert_tool_response_to_message_unwraps_only_an_unambiguous_schema_env assert json.loads(message.content) == expected_content +def test_convert_tool_response_to_message_keeps_non_ascii_text_in_an_unwrapped_answer(): + answer = {"tier": 3, "summary": "Hôtel Lutetia, 東京"} + + message = AnthropicConfig.convert_tool_response_to_message( + tool_calls=_json_tool_call({"input": answer}), + response_format_schema=_schema(_RISK_SCHEMA), + ) + + assert message is not None + assert "Hôtel Lutetia, 東京" in message.content + assert json.loads(message.content) == answer + + +def test_convert_tool_response_to_message_answer_with_a_lone_surrogate_stays_utf8_encodable(): + answer = {"tier": 3, "summary": "smile \ud83d end"} + + message = AnthropicConfig.convert_tool_response_to_message( + tool_calls=_json_tool_call({"input": answer}), + response_format_schema=_schema(_RISK_SCHEMA), + ) + + assert message is not None + assert json.loads(message.content.encode("utf-8")) == answer + + _TOO_DEEP_TO_DECODE: Final = "[" * 100_000 + "]" * 100_000 diff --git a/tests/unit/llms/anthropic/pass_through/messages/test_anthropic_messages_structured_outputs.py b/tests/unit/llms/anthropic/pass_through/messages/test_anthropic_messages_structured_outputs.py index 670e3de5110..db3ff58d80a 100644 --- a/tests/unit/llms/anthropic/pass_through/messages/test_anthropic_messages_structured_outputs.py +++ b/tests/unit/llms/anthropic/pass_through/messages/test_anthropic_messages_structured_outputs.py @@ -2,10 +2,16 @@ Tests for structured outputs support in Anthropic /v1/messages endpoint. """ +from collections.abc import Mapping +from typing import Final + import pytest + +import litellm from litellm.llms.anthropic.pass_through.messages.transformation import ( AnthropicMessagesConfig, ) +from litellm.types.router import GenericLiteLLMParams def test_output_format_supported_and_transforms_correctly(): @@ -109,3 +115,47 @@ def test_output_format_works_with_bedrock_and_azure(): headers={}, ) assert "output_format" in azure_result + + +_OBJECT_OUTPUT_FORMAT: Final = {"type": "json_schema", "schema": {"type": "object", "properties": {}}} + + +def _request_with_output_format( + output_format: object, litellm_params: GenericLiteLLMParams +) -> Mapping[str, object]: + return AnthropicMessagesConfig().transform_anthropic_messages_request( + model="claude-haiku-5-5", + messages=[{"role": "user", "content": "What is 6 times 7?"}], + anthropic_messages_optional_request_params={"max_tokens": 1024, "output_format": output_format}, + litellm_params=litellm_params, + headers={}, + ) + + +@pytest.mark.parametrize("output_format", ["json", ["json_schema"], 42]) +def test_malformed_output_format_is_dropped_under_drop_params(output_format: object) -> None: + result: Final = _request_with_output_format(output_format, GenericLiteLLMParams(drop_params=True)) + + assert "output_format" not in result + + +def test_malformed_output_format_is_dropped_under_the_global_drop_params_flag( + monkeypatch: pytest.MonkeyPatch, +) -> None: + monkeypatch.setattr(litellm, "drop_params", True) + + result: Final = _request_with_output_format("json", GenericLiteLLMParams()) + + assert "output_format" not in result + + +def test_object_output_format_is_kept_under_drop_params() -> None: + result: Final = _request_with_output_format(_OBJECT_OUTPUT_FORMAT, GenericLiteLLMParams(drop_params=True)) + + assert result["output_format"] == _OBJECT_OUTPUT_FORMAT + + +def test_malformed_output_format_is_forwarded_for_the_provider_to_reject_without_drop_params() -> None: + result: Final = _request_with_output_format("json", GenericLiteLLMParams()) + + assert result["output_format"] == "json" diff --git a/tests/unit/llms/anthropic/pass_through/messages/test_response_cache.py b/tests/unit/llms/anthropic/pass_through/messages/test_response_cache.py index b88a57f440d..1df4ccec02c 100644 --- a/tests/unit/llms/anthropic/pass_through/messages/test_response_cache.py +++ b/tests/unit/llms/anthropic/pass_through/messages/test_response_cache.py @@ -1,5 +1,5 @@ import asyncio -from typing import Any, AsyncIterator, Dict, List +from typing import Any, AsyncIterator, Dict, Final, List import pytest @@ -10,10 +10,13 @@ import litellm from litellm._internal_context import in_post_response_phase from litellm.caching.caching import Cache, LiteLLMCacheType from litellm.caching.caching_handler import LLMCachingHandler +from litellm.integrations.custom_logger import CustomLogger +from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER from litellm.llms.anthropic.pass_through.messages import handler from litellm.llms.anthropic.pass_through.messages.response_cache import ( AnthropicMessagesStreamCacheWriter, + CachedAnthropicMessagesStreamIterator, ) STREAM_EVENTS: List[bytes] = [ @@ -299,6 +302,58 @@ async def test_cached_stream_replay_logs_once_when_polled_after_exhaustion(): await asyncio.sleep(0) mock_route.assert_called_once() + + +class _ReplayRecorder(CustomLogger): + def __init__(self) -> None: + super().__init__() + self.logged: list[object] = [] + + async def async_log_success_event( + self, + kwargs: dict[str, object], + response_obj: object, + start_time: datetime.datetime, + end_time: datetime.datetime, + ) -> None: + self.logged.append(kwargs.get("completion_start_time")) + + +@pytest.mark.asyncio +async def test_cached_stream_replay_logs_when_its_first_event_was_replayed(): + recorder: Final = _ReplayRecorder() + logging_obj: Final = LiteLLMLoggingObj( + model="claude-sonnet-4-5", + messages=[{"role": "user", "content": "which greek letter?"}], + stream=True, + call_type="anthropic_messages", + start_time=datetime.datetime(2026, 10, 20, 12, 0, 0), + litellm_call_id="cached-replay", + function_id="cached-replay", + dynamic_async_success_callbacks=[recorder], + ) + logging_obj.update_environment_variables( + model="claude-sonnet-4-5", + user="", + optional_params={}, + litellm_params={"custom_llm_provider": "anthropic"}, + custom_llm_provider="anthropic", + ) + iterator: Final = CachedAnthropicMessagesStreamIterator( + events=[event.decode("utf-8") for event in STREAM_EVENTS], + litellm_logging_obj=logging_obj, + request_body={"model": "claude-sonnet-4-5", "stream": True}, + ) + + _ = await iterator.__anext__() + first_event_at: Final = iterator.completion_start_time + _ = await _collect(iterator) + await GLOBAL_LOGGING_WORKER.flush() + + assert first_event_at is not None + assert recorder.logged == [first_event_at] + + class _HeldBackStream: has_buffered_provider_output = True diff --git a/tests/unit/llms/anthropic/pass_through/messages/test_streaming_iterator.py b/tests/unit/llms/anthropic/pass_through/messages/test_streaming_iterator.py index b995c6dba9b..fd9aa75be74 100644 --- a/tests/unit/llms/anthropic/pass_through/messages/test_streaming_iterator.py +++ b/tests/unit/llms/anthropic/pass_through/messages/test_streaming_iterator.py @@ -5,6 +5,7 @@ from datetime import datetime from typing import Final, Literal from unittest.mock import patch +import httpx import pytest @@ -859,13 +860,15 @@ class _SuccessRecorder(CustomLogger): self.success_kwargs.append(kwargs) -def _make_priced_logging_obj(call_id: str, recorder: _SuccessRecorder, model: str) -> LiteLLMLoggingObj: +def _make_priced_logging_obj( + call_id: str, recorder: _SuccessRecorder, model: str, start_time: datetime | None = None +) -> LiteLLMLoggingObj: logging_obj = LiteLLMLoggingObj( model=model, messages=[{"role": "user", "content": "hi"}], stream=True, call_type="anthropic_messages", - start_time=datetime.now(), + start_time=start_time or datetime.now(), litellm_call_id=call_id, function_id=call_id, dynamic_async_success_callbacks=[recorder], @@ -880,6 +883,53 @@ def _make_priced_logging_obj(call_id: str, recorder: _SuccessRecorder, model: st return logging_obj +@pytest.mark.asyncio +async def test_streamed_messages_log_the_call_start_instead_of_when_the_upstream_answered(): + model: Final = "claude-sonnet-5" + call_start: Final = datetime(2026, 10, 9, 12, 0, 0) + recorder: Final = _SuccessRecorder() + logging_obj: Final = _make_priced_logging_obj("logs_call_start", recorder, model, start_time=call_start) + logging_obj._on_deferred_stream_complete = lambda logging_coroutine: logging_coroutine + iterator: Final = BaseAnthropicMessagesStreamingIterator( + litellm_logging_obj=logging_obj, request_body={"model": model, "stream": True} + ) + + async def _full_stream(): + for event in (*_STREAM_PREFIX, *_STREAM_TAIL): + yield event + + _ = [chunk async for chunk in iterator.async_sse_wrapper(_full_stream())] + (logging_coroutine,) = logging_obj._deferred_stream_complete_args + await logging_coroutine + + assert len(recorder.success_kwargs) == 1 + assert recorder.success_kwargs[0]["standard_logging_object"]["startTime"] == call_start.timestamp() + + +@pytest.mark.asyncio +async def test_streamed_messages_from_anthropic_log_the_call_start_instead_of_when_the_upstream_answered(): + model: Final = "claude-sonnet-5" + call_start: Final = datetime(2026, 10, 9, 12, 0, 0) + recorder: Final = _SuccessRecorder() + logging_obj: Final = _make_priced_logging_obj("anthropic_logs_call_start", recorder, model, start_time=call_start) + logging_obj._on_deferred_stream_complete = lambda logging_coroutine: logging_coroutine + request_body: Final = {"model": model, "stream": True} + iterator: Final = BaseAnthropicMessagesStreamingIterator(litellm_logging_obj=logging_obj, request_body=request_body) + sse: Final = "".join(f"event: {e['type']}\ndata: {json.dumps(e)}\n\n" for e in (*_STREAM_PREFIX, *_STREAM_TAIL)) + + _ = [ + chunk + async for chunk in iterator.get_async_streaming_response_iterator( + httpx.Response(200, content=sse.encode()), request_body, logging_obj + ) + ] + (logging_coroutine,) = logging_obj._deferred_stream_complete_args + await logging_coroutine + + assert len(recorder.success_kwargs) == 1 + assert recorder.success_kwargs[0]["standard_logging_object"]["startTime"] == call_start.timestamp() + + class _UpstreamClosedOnDetach: """Upstream that yields its events and then, like a socket read, waits until it is closed.""" diff --git a/tests/unit/llms/anthropic/test_anthropic_count_tokens_transformation.py b/tests/unit/llms/anthropic/test_anthropic_count_tokens_transformation.py index 9af7497bc82..63f149fabe4 100644 --- a/tests/unit/llms/anthropic/test_anthropic_count_tokens_transformation.py +++ b/tests/unit/llms/anthropic/test_anthropic_count_tokens_transformation.py @@ -1,7 +1,10 @@ import asyncio from base64 import b64encode +from collections.abc import Mapping from copy import deepcopy +from queue import SimpleQueue from threading import get_ident +from types import MappingProxyType from typing import Final import httpx @@ -10,16 +13,20 @@ import respx from pydantic import JsonValue, TypeAdapter import litellm +from litellm.llms.anthropic.chat.transformation import AnthropicConfig from litellm.llms.anthropic.count_tokens.handler import AnthropicCountTokensHandler +from litellm.llms.anthropic.count_tokens.token_counter import AnthropicTokenCounter from litellm.llms.anthropic.count_tokens.transformation import ( AnthropicCountTokensConfig, ) from litellm.llms.azure_ai.anthropic.count_tokens.handler import ( AzureAIAnthropicCountTokensHandler, ) +from litellm.llms.azure_ai.anthropic.count_tokens.token_counter import AzureAIAnthropicTokenCounter from litellm.llms.azure_ai.anthropic.count_tokens.transformation import ( AzureAIAnthropicCountTokensConfig, ) +from litellm.types.utils import TokenCountMessagesFormat, TokenCountResponse @pytest.mark.parametrize( @@ -441,3 +448,302 @@ async def test_handler_sends_the_leading_system_run_as_system_not_as_a_message(h "system": [{"type": "text", "text": "Be terse"}], "messages": [{"role": "user", "content": "Hello, how are you?"}], } + + +_WEATHER_SCHEMA: Final[dict[str, JsonValue]] = {"type": "object", "properties": {"city": {"type": "string"}}} + +_CHAT_TOOL_TURNS: Final[list[dict[str, JsonValue]]] = [ + {"role": "system", "content": "Be terse."}, + {"role": "user", "content": "Weather in SF?"}, + { + "role": "assistant", + "content": None, + "tool_calls": [ + {"id": "call_1", "type": "function", "function": {"name": "get_weather", "arguments": '{"city": "SF"}'}} + ], + }, + {"role": "tool", "tool_call_id": "call_1", "content": "sunny"}, +] + + +_COUNTERS: Final = pytest.mark.parametrize( + ("counter_type", "count_endpoint"), + ( + (AnthropicTokenCounter, "https://gateway.example/v1/messages/count_tokens"), + (AzureAIAnthropicTokenCounter, "https://gateway.example/anthropic/v1/messages/count_tokens"), + ), +) + + +async def _counted_body( + counter_type: type[AnthropicTokenCounter] | type[AzureAIAnthropicTokenCounter], + count_endpoint: str, + messages: list[dict[str, JsonValue]], + tools: list[dict[str, JsonValue]] | None, + messages_format: TokenCountMessagesFormat, + chat_params: Mapping[str, JsonValue] = MappingProxyType({}), +) -> tuple[TokenCountResponse | None, tuple[dict[str, JsonValue], ...]]: + sent: Final[SimpleQueue[bytes]] = SimpleQueue() + + def count(request: httpx.Request) -> httpx.Response: + sent.put(request.content) + return httpx.Response(200, json={"input_tokens": 31}) + + with respx.mock: + respx.post(count_endpoint).mock(side_effect=count) + result: Final = await counter_type().count_tokens( + model_to_use="claude-opus-5-5", + messages=messages, + contents=None, + deployment={"litellm_params": {"api_key": "sk-ant-api03-test-key", "api_base": "https://gateway.example"}}, + request_model="claude-opus-5-5", + tools=tools, + messages_format=messages_format, + chat_params=chat_params, + ) + return result, tuple(TypeAdapter(dict[str, JsonValue]).validate_json(sent.get()) for _ in range(sent.qsize())) + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("httpx_transport_clients") +@_COUNTERS +@pytest.mark.parametrize( + "tool", + ( + {"type": "function", "name": "get_weather", "description": "Look up the weather", "parameters": _WEATHER_SCHEMA}, + { + "type": "function", + "function": {"name": "get_weather", "description": "Look up the weather", "parameters": _WEATHER_SCHEMA}, + }, + ), +) +async def test_counter_sends_chat_tool_use_in_the_shape_chat_inference_sends( + counter_type: type[AnthropicTokenCounter] | type[AzureAIAnthropicTokenCounter], + count_endpoint: str, + tool: dict[str, JsonValue], +) -> None: + """Responses and chat bodies reach the counter as chat messages and tools, which Anthropic rejects + with a 400 unless they are translated the way the chat inference request translates them.""" + original: Final = deepcopy(_CHAT_TOOL_TURNS) + result, bodies = await _counted_body(counter_type, count_endpoint, _CHAT_TOOL_TURNS, [tool], "openai") + + assert result is not None + assert result.error is not True + assert result.total_tokens == 31 + assert bodies == ( + { + "model": "claude-opus-5-5", + "system": [{"type": "text", "text": "Be terse."}], + "messages": [ + {"role": "user", "content": [{"type": "text", "text": "Weather in SF?"}]}, + { + "role": "assistant", + "content": [{"type": "tool_use", "id": "call_1", "name": "get_weather", "input": {"city": "SF"}}], + }, + {"role": "user", "content": [{"type": "tool_result", "tool_use_id": "call_1", "content": "sunny"}]}, + ], + "tools": [ + { + "name": "get_weather", + "input_schema": _WEATHER_SCHEMA, + "type": "custom", + "description": "Look up the weather", + } + ], + }, + ) + assert _CHAT_TOOL_TURNS == original + + +_ANTHROPIC_TOOL_USE: Final[list[dict[str, JsonValue]]] = [ + {"role": "user", "content": "Weather in SF?"}, + {"role": "assistant", "content": [{"type": "tool_use", "id": "toolu_1", "name": "get_weather", "input": {}}]}, + {"role": "user", "content": [{"type": "tool_result", "tool_use_id": "toolu_1", "content": "sunny"}]}, +] + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("httpx_transport_clients") +@_COUNTERS +@pytest.mark.parametrize( + ("messages", "tool", "messages_format"), + ( + (_ANTHROPIC_TOOL_USE, {"name": "get_weather", "input_schema": _WEATHER_SCHEMA}, "openai"), + ( + [{"role": "user", "content": "Weather in SF?"}], + {"type": "function", "name": "get_weather", "parameters": _WEATHER_SCHEMA}, + "anthropic", + ), + ), +) +async def test_counter_sends_anthropic_shaped_and_messages_api_requests_as_sent( + counter_type: type[AnthropicTokenCounter] | type[AzureAIAnthropicTokenCounter], + count_endpoint: str, + messages: list[dict[str, JsonValue]], + tool: dict[str, JsonValue], + messages_format: TokenCountMessagesFormat, +) -> None: + _, bodies = await _counted_body(counter_type, count_endpoint, messages, [tool], messages_format) + + assert bodies == ({"model": "claude-opus-5-5", "messages": messages, "tools": [tool]},) + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("httpx_transport_clients") +@_COUNTERS +async def test_counter_rejects_a_tool_call_chat_inference_rejects_without_calling_anthropic( + counter_type: type[AnthropicTokenCounter] | type[AzureAIAnthropicTokenCounter], count_endpoint: str +) -> None: + messages: Final[list[dict[str, JsonValue]]] = [ + {"role": "user", "content": "Weather in SF?"}, + { + "role": "assistant", + "content": None, + "tool_calls": [ + {"id": "call_1", "type": "function", "function": {"name": "get_weather", "arguments": "sunny?"}} + ], + }, + {"role": "tool", "tool_call_id": "call_1", "content": "sunny"}, + ] + result, bodies = await _counted_body(counter_type, count_endpoint, messages, None, "openai") + + assert bodies == () + assert result is not None + assert result.error is True + assert result.status_code == 400 + assert result.rejected_before_provider_call is True + assert "Failed to parse tool call arguments for tool 'get_weather'" in (result.error_message or "") + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("httpx_transport_clients") +@_COUNTERS +async def test_counter_rejects_a_chat_tool_without_a_name_without_calling_anthropic( + counter_type: type[AnthropicTokenCounter] | type[AzureAIAnthropicTokenCounter], count_endpoint: str +) -> None: + result, bodies = await _counted_body( + counter_type, + count_endpoint, + [{"role": "user", "content": "Weather in SF?"}], + [{"type": "function", "function": {"parameters": _WEATHER_SCHEMA}}], + "openai", + ) + + assert bodies == () + assert result is not None + assert (result.error, result.status_code, result.rejected_before_provider_call) == (True, 400, True) + + +_CHAT_WEATHER_TOOL: Final[dict[str, JsonValue]] = { + "type": "function", + "function": {"name": "get_weather", "parameters": _WEATHER_SCHEMA}, +} + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("httpx_transport_clients") +@_COUNTERS +@pytest.mark.parametrize( + ("messages", "tools"), + ( + pytest.param( + [ + { + "role": "user", + "name": "ana", + "content": [ + {"type": "text", "text": "Describe this"}, + {"type": "image", "source": {"type": "base64", "media_type": "image/png", "data": "iVBORw0K"}}, + ], + } + ], + None, + id="native-image-block", + ), + pytest.param( + [ + {"role": "user", "content": "Weather in SF?"}, + { + "role": "assistant", + "content": [{"type": "tool_use", "id": "toolu_1", "name": "get_weather", "input": {"city": "SF"}}], + }, + {"role": "user", "content": [{"type": "tool_result", "tool_use_id": "toolu_1", "content": "sunny"}]}, + ], + [_CHAT_WEATHER_TOOL], + id="native-tool-result-block", + ), + pytest.param( + [{"role": "user", "content": "Open the docs"}], + [ + {"type": "computer_use_preview", "display_width": 1024, "display_height": 768, "environment": "browser"}, + _CHAT_WEATHER_TOOL, + ], + id="computer-use-preview-tool", + ), + pytest.param( + [{"role": "user", "content": "Ask the wiki"}], + [{"type": "mcp", "server_label": "wiki", "server_url": "https://mcp.example/mcp"}, _CHAT_WEATHER_TOOL], + id="mcp-tool", + ), + ), +) +async def test_counter_rejects_input_chat_translation_would_leave_out_without_calling_anthropic( + counter_type: type[AnthropicTokenCounter] | type[AzureAIAnthropicTokenCounter], + count_endpoint: str, + messages: list[dict[str, JsonValue]], + tools: list[dict[str, JsonValue]] | None, +) -> None: + result, bodies = await _counted_body(counter_type, count_endpoint, messages, tools, "openai") + + assert bodies == () + assert result is not None + assert (result.error, result.status_code, result.rejected_before_provider_call) == (True, 400, True) + + +_ANSWER_SCHEMA: Final[dict[str, JsonValue]] = { + "type": "object", + "properties": {"answer": {"type": "string"}}, + "required": ["answer"], + "additionalProperties": False, +} + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("httpx_transport_clients") +@_COUNTERS +async def test_counter_sends_the_structured_output_tool_choice_and_thinking_chat_inference_sends( + counter_type: type[AnthropicTokenCounter] | type[AzureAIAnthropicTokenCounter], count_endpoint: str +) -> None: + """count_tokens refuses the beta output_format that chat inference sends, so the count carries the same + schema as output_config.format, next to the inference request's thinking and tool_choice.""" + messages: Final[list[dict[str, JsonValue]]] = [{"role": "user", "content": "Weather in SF?"}] + tool: Final[dict[str, JsonValue]] = { + "type": "function", + "function": {"name": "get_weather", "parameters": _WEATHER_SCHEMA}, + } + chat_params: Final[dict[str, JsonValue]] = { + "response_format": {"type": "json_schema", "json_schema": {"name": "answer", "schema": _ANSWER_SCHEMA}}, + "reasoning_effort": "low", + "tool_choice": "auto", + } + config: Final = AnthropicConfig() + inference: Final = config.transform_request( + model="claude-opus-5-5", + messages=deepcopy(messages), + optional_params=config.map_openai_params( + {**chat_params, "tools": [tool]}, {}, "claude-opus-5-5", drop_params=False + ), + litellm_params={}, + headers={}, + ) + + _, bodies = await _counted_body(counter_type, count_endpoint, messages, [tool], "openai", chat_params) + + (body,) = bodies + assert "output_format" not in body + assert body["output_config"] == {**inference.get("output_config", {}), "format": inference["output_format"]} + assert (body["thinking"], body["tool_choice"], body["tools"]) == ( + inference["thinking"], + inference["tool_choice"], + inference["tools"], + ) diff --git a/tests/unit/llms/azure/test_azure_common_utils.py b/tests/unit/llms/azure/test_azure_common_utils.py index 41ad27d6f40..b3bd1b8743a 100644 --- a/tests/unit/llms/azure/test_azure_common_utils.py +++ b/tests/unit/llms/azure/test_azure_common_utils.py @@ -477,6 +477,7 @@ def test_default_max_retries_env_var_reaches_azure_sdk_client(): "asearch", "adecisions", "asystemone", + "aextraction", "avector_store_create", "avector_store_search", "acreate_skill", diff --git a/tests/unit/llms/azure_ai/claude/test_azure_anthropic_messages_transformation.py b/tests/unit/llms/azure_ai/claude/test_azure_anthropic_messages_transformation.py index 176dcfc86c9..38483b8a1fa 100644 --- a/tests/unit/llms/azure_ai/claude/test_azure_anthropic_messages_transformation.py +++ b/tests/unit/llms/azure_ai/claude/test_azure_anthropic_messages_transformation.py @@ -7,6 +7,7 @@ sys.path.insert( 0, os.path.abspath(os.path.join(os.path.dirname(__file__), "../../../../..")) ) +from collections.abc import Mapping from typing import Final from unittest.mock import patch @@ -551,3 +552,47 @@ async def test_outgoing_azure_request_sends_safeguards_with_the_dangerous_tool_u sent: Final = received[0] assert "dangerous-tool-use-2026-09-03" in sent.headers["anthropic-beta"].split(","), dict(sent.headers) assert json.loads(sent.content)["safeguards"] == list(AUTO_MODE_SAFEGUARDS) + + +async def _azure_request_body_for_output_format(output_format: object, drop_params: bool) -> Mapping[str, object]: + received: Final[list[httpx.Request]] = [] + + def foundry_answers(request: httpx.Request) -> httpx.Response: + received.append(request) + return _foundry_answer(request) + + upstream: Final = AsyncHTTPHandler(transport=httpx.MockTransport(foundry_answers)) + try: + await litellm.anthropic.messages.acreate( + max_tokens=256, + messages=[{"role": "user", "content": "What is 6 times 7?"}], + model="azure_ai/claude-sonnet-4-6", + api_key="test-api-key", + api_base="https://test-resource.services.ai.azure.com", + output_format=output_format, + drop_params=drop_params, + client=upstream, + ) + finally: + await upstream.close() + + assert len(received) == 1, received + return json.loads(received[0].content) + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("local_beta_headers_config") +async def test_outgoing_azure_request_drops_a_malformed_output_format_under_drop_params() -> None: + body: Final = await _azure_request_body_for_output_format("json", drop_params=True) + + assert "output_format" not in body + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("local_beta_headers_config") +async def test_outgoing_azure_request_keeps_an_object_output_format_under_drop_params() -> None: + output_format: Final = {"type": "json_schema", "schema": {"type": "object", "properties": {}}} + + body: Final = await _azure_request_body_for_output_format(output_format, drop_params=True) + + assert body["output_format"] == output_format diff --git a/tests/unit/llms/base_llm/decisions/test_base_decisions_transformation.py b/tests/unit/llms/base_llm/decisions/test_base_decisions_transformation.py index 924b192a00e..3aebf56ee73 100644 --- a/tests/unit/llms/base_llm/decisions/test_base_decisions_transformation.py +++ b/tests/unit/llms/base_llm/decisions/test_base_decisions_transformation.py @@ -197,6 +197,28 @@ def test_missing_or_mismatched_systemone_answers_are_refusals_left_out_of_the_re assert tuple(ir_to_systemone_response(parsed, ir).answers) == ("damaged",) +@pytest.mark.parametrize( + ("payload", "field"), + [ + ({"model": "jev-latest", "usage": {"input_tokens": 10, "output_tokens": 1}}, ("answers",)), + ( + {"model": "jev-latest", "answers": {"damaged": None}, "usage": {"input_tokens": 10, "output_tokens": 1}}, + ("answers", "damaged"), + ), + ], + ids=["missing_answers", "null_answer"], +) +def test_a_malformed_systemone_response_names_the_field_at_fault( + payload: Mapping[str, object], field: tuple[str, ...] +) -> None: + ir: Final = systemone_request_to_ir(_SYSTEMONE_BODY.validate_python(_SYSTEMONE_REQUEST)) + + with pytest.raises(ValidationError) as error: + parse_systemone_response(payload, ir) + + assert [item["loc"] for item in error.value.errors()] == [field] + + def test_each_media_kind_is_gated_by_its_own_support_flag() -> None: audio: Final = ["data:audio/wav;base64,YQ=="] videos: Final = ["data:video/mp4;base64,YQ=="] diff --git a/tests/unit/llms/base_llm/responses/test_transformation.py b/tests/unit/llms/base_llm/responses/test_transformation.py index eb01cc8a9ce..8d21af83668 100644 --- a/tests/unit/llms/base_llm/responses/test_transformation.py +++ b/tests/unit/llms/base_llm/responses/test_transformation.py @@ -24,7 +24,7 @@ from litellm.types.llms.openai import( ResponsesAPIStreamEvents, ) from tests._vcr_conftest_common import install_live_call_probe, record_vcr_outcome -from typing import Any, AsyncIterator, List +from typing import Any, AsyncIterator, Final, List from unittest.mock import AsyncMock, MagicMock, Mock, patch @@ -438,9 +438,9 @@ class TestBaseResponsesAPIStreamingIterator: # This should NOT raise an exception # Previously it would fail with: TypeError: cannot pickle 'ValidatorIterator' - # Mock asyncio.create_task and executor.submit since we're not in async context with ( - patch("asyncio.create_task") as mock_create_task, + patch("asyncio.get_running_loop"), + patch("litellm.responses.streaming_iterator.spawn_logging_task"), patch("litellm.responses.streaming_iterator.executor") as mock_executor, ): try: @@ -728,7 +728,8 @@ class TestBaseResponsesAPIStreamingIterator: "update_responses_api_response_id_with_model_id", return_value=mock_responses_api_response, ), - patch("asyncio.create_task") as mock_create_task, + patch("asyncio.get_running_loop"), + patch("litellm.responses.streaming_iterator.spawn_logging_task") as mock_spawn_logging_task, patch("litellm.responses.streaming_iterator.executor") as mock_executor, ): result = iterator._process_chunk(json.dumps(test_chunk_data)) @@ -739,7 +740,8 @@ class TestBaseResponsesAPIStreamingIterator: # Success handlers are dispatched as one async task (via _handle_logging_completed_response); # the sync handler must never be submitted to the executor concurrently (LIT-4210) - mock_create_task.assert_called_once() + spawned_task_names: Final = [call.kwargs["task_name"] for call in mock_spawn_logging_task.call_args_list] + assert spawned_task_names.count("Responses stream success logging") == 1 mock_executor.submit.assert_not_called() # Failure handlers should NOT have been called diff --git a/tests/unit/llms/bedrock/batches/test_handler.py b/tests/unit/llms/bedrock/batches/test_handler.py index d920eabcdf6..602504f0c49 100644 --- a/tests/unit/llms/bedrock/batches/test_handler.py +++ b/tests/unit/llms/bedrock/batches/test_handler.py @@ -257,6 +257,25 @@ def test_explicit_region_overrides_arn(patched_boto3): assert kwargs["region_name"] == "eu-central-1" +def test_status_client_uses_regional_host_when_no_control_plane_endpoint( + patched_boto3: tuple[MagicMock, MagicMock], +) -> None: + _, boto_client_factory = patched_boto3 + BedrockBatchesHandler.handle_model_invocation_job_status(batch_id=JOB_ARN) + _, kwargs = boto_client_factory.call_args + assert kwargs["endpoint_url"] is None + + +def test_status_client_uses_configured_control_plane_endpoint(patched_boto3: tuple[MagicMock, MagicMock]) -> None: + _, boto_client_factory = patched_boto3 + BedrockBatchesHandler.handle_model_invocation_job_status( + batch_id=JOB_ARN, + aws_bedrock_control_plane_endpoint="https://bedrock-gateway.internal/", + ) + _, kwargs = boto_client_factory.call_args + assert kwargs["endpoint_url"] == "https://bedrock-gateway.internal" + + def test_failure_message_propagates(patched_boto3): fake_client, _ = patched_boto3 failed_response = _fake_boto3_response(status="Failed") @@ -479,6 +498,29 @@ def test_litellm_cancel_batch_dispatches_to_bedrock(patched_boto3): assert batch.status == "cancelled" +def test_litellm_batch_calls_send_every_bedrock_client_to_the_configured_endpoint( + patched_boto3: tuple[MagicMock, MagicMock], +) -> None: + import litellm + + fake_client, boto_client_factory = patched_boto3 + fake_client.get_model_invocation_job.return_value = _fake_boto3_response(status="Stopped") + + litellm.cancel_batch( + batch_id=JOB_ARN, + custom_llm_provider="bedrock", + aws_bedrock_control_plane_endpoint="https://bedrock-gateway.internal", + ) + litellm.retrieve_batch( + batch_id=JOB_ARN, + custom_llm_provider="bedrock", + aws_bedrock_control_plane_endpoint="https://bedrock-gateway.internal", + ) + + endpoints: Final = tuple(call.kwargs["endpoint_url"] for call in boto_client_factory.call_args_list) + assert endpoints == ("https://bedrock-gateway.internal",) * 3 + + class _TagGatedSTSClient: """Stands in for STS behind a trust policy that only admits sessions carrying ``tags``.""" diff --git a/tests/unit/llms/bedrock/batches/test_transformation.py b/tests/unit/llms/bedrock/batches/test_transformation.py index 5e987239c54..5360ac00018 100644 --- a/tests/unit/llms/bedrock/batches/test_transformation.py +++ b/tests/unit/llms/bedrock/batches/test_transformation.py @@ -14,10 +14,15 @@ URL/ARN handling, and the error class. AWS auth/sigv4 is the only external seam we mock; everything else runs for real. """ +from datetime import datetime, timezone +from typing import Final from unittest.mock import MagicMock, patch import httpx import pytest +from botocore.auth import SigV4Auth +from botocore.awsrequest import AWSRequest +from botocore.credentials import Credentials from litellm.llms.bedrock.batches.transformation import BedrockBatchesConfig from litellm.types.utils import LlmProviders @@ -41,7 +46,7 @@ ARN = "arn:aws:bedrock:us-west-2:123456789012:model-invocation-job/abc1234567" @pytest.fixture -def config(): +def config() -> BedrockBatchesConfig: return BedrockBatchesConfig() @@ -66,6 +71,90 @@ def test_get_complete_batch_url_uses_region(config): assert url == "https://bedrock.eu-central-1.amazonaws.com/model-invocation-job" +CONTROL_PLANE_ENDPOINT: Final = "https://vpce-0abc.bedrock.us-west-2.vpce.amazonaws.com/" + + +def test_get_complete_batch_url_uses_configured_control_plane_endpoint(config: BedrockBatchesConfig) -> None: + url: Final = config.get_complete_batch_url( + api_base=None, + api_key=None, + model="anthropic.claude-3", + optional_params={"aws_region_name": "us-west-2"}, + litellm_params={"aws_bedrock_control_plane_endpoint": CONTROL_PLANE_ENDPOINT}, + data={"input_file_id": "s3://b/k"}, + ) + assert url == "https://vpce-0abc.bedrock.us-west-2.vpce.amazonaws.com/model-invocation-job" + + +def test_proxy_deployment_credentials_carry_the_control_plane_endpoint(config: BedrockBatchesConfig) -> None: + from litellm import Router + + router: Final = Router( + model_list=[ + { + "model_name": "claude-batch", + "litellm_params": { + "model": "bedrock/anthropic.claude-3", + "aws_region_name": "us-west-2", + "aws_bedrock_control_plane_endpoint": CONTROL_PLANE_ENDPOINT, + }, + } + ] + ) + credentials: Final = router.get_deployment_credentials_with_provider("claude-batch") + + url: Final = config.get_complete_batch_url( + api_base=None, + api_key=None, + model="anthropic.claude-3", + optional_params={}, + litellm_params=credentials, + data={"input_file_id": "s3://b/k"}, + ) + assert url == "https://vpce-0abc.bedrock.us-west-2.vpce.amazonaws.com/model-invocation-job" + + +def test_get_complete_batch_url_ignores_runtime_api_base(config: BedrockBatchesConfig) -> None: + url: Final = config.get_complete_batch_url( + api_base="https://bedrock-runtime.us-west-2.amazonaws.com", + api_key=None, + model="anthropic.claude-3", + optional_params={"aws_region_name": "us-west-2"}, + litellm_params={"api_base": "https://bedrock-runtime.us-west-2.amazonaws.com"}, + data={"input_file_id": "s3://b/k"}, + ) + assert url == "https://bedrock.us-west-2.amazonaws.com/model-invocation-job" + + +def test_create_request_sends_and_signs_for_configured_control_plane_endpoint(config: BedrockBatchesConfig) -> None: + expected_url: Final = "https://vpce-0abc.bedrock.us-west-2.vpce.amazonaws.com/model-invocation-job" + with patch("botocore.auth.get_current_datetime", return_value=datetime(2026, 1, 1, tzinfo=timezone.utc)): + result: Final = config.transform_create_batch_request( + model="anthropic.claude-haiku-4-5-20251001-v1:0", + create_batch_data={ + "input_file_id": "s3://in-bucket/input.jsonl", + "endpoint": "/v1/chat/completions", + "completion_window": "24h", + }, + optional_params={"aws_region_name": "us-west-2"}, + litellm_params={ + "aws_batch_role_arn": "arn:aws:iam::123:role/my-batch-role", + "aws_bedrock_control_plane_endpoint": CONTROL_PLANE_ENDPOINT, + "aws_access_key_id": "endpoint-test-key", + "aws_secret_access_key": "endpoint-test-secret", + }, + ) + expected_request: Final = AWSRequest( + method="POST", url=expected_url, data=result["data"], headers={"Content-Type": "application/json"} + ) + SigV4Auth(Credentials("endpoint-test-key", "endpoint-test-secret"), "bedrock", "us-west-2").add_auth( + expected_request + ) + + assert result["url"] == expected_url + assert result["headers"]["Authorization"] == expected_request.headers["Authorization"] + + # --------------------------------------------------------------------------- # # transform_create_batch_request - request construction (sign_aws_request mocked) # --------------------------------------------------------------------------- # @@ -608,6 +697,30 @@ def test_retrieve_request_builds_encoded_arn_url(config): assert mock_sign.call_args.kwargs["data"] == {} +def test_retrieve_request_sends_and_signs_for_configured_control_plane_endpoint(config: BedrockBatchesConfig) -> None: + expected_url: Final = ( + "https://vpce-0abc.bedrock.us-west-2.vpce.amazonaws.com/model-invocation-job/" + "arn%3Aaws%3Abedrock%3Aus-west-2%3A123456789012%3Amodel-invocation-job%2Fabc1234567" + ) + with patch("botocore.auth.get_current_datetime", return_value=datetime(2026, 1, 1, tzinfo=timezone.utc)): + result: Final = config.transform_retrieve_batch_request( + batch_id=ARN, + optional_params={}, + litellm_params={ + "aws_bedrock_control_plane_endpoint": CONTROL_PLANE_ENDPOINT, + "aws_access_key_id": "endpoint-test-key", + "aws_secret_access_key": "endpoint-test-secret", + }, + ) + expected_request: Final = AWSRequest(method="GET", url=expected_url, data="", headers={}) + SigV4Auth(Credentials("endpoint-test-key", "endpoint-test-secret"), "bedrock", "us-west-2").add_auth( + expected_request + ) + + assert result["url"] == expected_url + assert result["headers"]["Authorization"] == expected_request.headers["Authorization"] + + def test_retrieve_request_rejects_non_arn(config): with pytest.raises(ValueError, match="Expected ARN"): config.transform_retrieve_batch_request( diff --git a/tests/unit/llms/bedrock/chat/test_converse_transformation.py b/tests/unit/llms/bedrock/chat/test_converse_transformation.py index f0dd40d4bc9..154797bab5a 100644 --- a/tests/unit/llms/bedrock/chat/test_converse_transformation.py +++ b/tests/unit/llms/bedrock/chat/test_converse_transformation.py @@ -896,6 +896,16 @@ def test_reasoning_with_forced_tool_choice_switches_to_auto(): ("us.xai.grok-4.6", "max_tokens", 1, 16), ("global.xai.grok-4.6", "max_completion_tokens", 1, 16), ("us.xai.grok-4.6", "max_tokens", 32, 32), + ("us.moonshotai.kimi-k3", "max_tokens", 1, 16), + ("global.moonshotai.kimi-k3", "max_completion_tokens", 1, 16), + ("moonshotai.kimi-k3", "max_tokens", 64, 64), + ( + "arn:aws:bedrock:us-east-1:123456789012:inference-profile/us.moonshotai.kimi-k3", + "max_tokens", + 1, + 16, + ), + ("moonshotai.kimi-k2.5", "max_tokens", 1, 1), ("anthropic.claude-sonnet-4-5-20250929-v1:0", "max_tokens", 1, 1), ("arn:aws:bedrock:us-east-1:123456789012:inference-profile/us.openai.gpt-6-astra", "max_tokens", 1, 16), ("arn:aws:bedrock:us-east-1:123456789012:inference-profile/global.xai.grok-4.6", "max_tokens", 1, 16), @@ -10729,3 +10739,53 @@ def test_a_refused_native_schema_is_sent_again_only_when_the_retry_drops_native_ assert route.call_count == expected_calls assert all("outputConfig" in json.loads(call.request.content) for call in route.calls[:1]) assert all("outputConfig" not in json.loads(call.request.content) for call in route.calls[1:]) + + +CONTROL_PLANE_ENDPOINT: Final = "https://bedrock-fips.us-east-1.amazonaws.com" + + +def _bedrock_chat_answer(request: httpx.Request) -> httpx.Response: + if request.url.path.endswith("/invoke"): + return httpx.Response( + 200, + json={ + "id": "msg_control_plane", + "type": "message", + "role": "assistant", + "model": "claude-haiku-4-5", + "content": [{"type": "text", "text": "ok"}], + "stop_reason": "end_turn", + "usage": {"input_tokens": 1, "output_tokens": 1}, + }, + ) + return httpx.Response( + 200, + json={ + "output": {"message": {"role": "assistant", "content": [{"text": "ok"}]}}, + "stopReason": "end_turn", + "usage": {"inputTokens": 1, "outputTokens": 1, "totalTokens": 2}, + }, + ) + + +@pytest.mark.parametrize("route_prefix", ["bedrock/", "bedrock/converse/", "bedrock/invoke/"]) +@pytest.mark.respx(assert_all_called=True) +def test_a_deployment_with_a_batch_control_plane_endpoint_keeps_it_out_of_chat_requests( + respx_mock: respx.Router, route_prefix: str +) -> None: + route: Final = respx_mock.post( + url__regex=r"^https://bedrock-runtime\.us-east-1\.amazonaws\.com/model/.+/(converse|invoke)$" + ).mock(side_effect=_bedrock_chat_answer) + + response: Final = litellm.completion( + model=f"{route_prefix}us.anthropic.claude-haiku-4-5-20251001-v1:0", + messages=[{"role": "user", "content": "hi"}], + aws_access_key_id="AKIACONTROLPLANE", + aws_secret_access_key="control-plane-secret", + aws_region_name="us-east-1", + aws_bedrock_control_plane_endpoint=CONTROL_PLANE_ENDPOINT, + client=HTTPHandler(), + ) + + assert response.choices[0].message.content == "ok" + assert "aws_bedrock_control_plane_endpoint" not in route.calls[0].request.content.decode() diff --git a/tests/unit/llms/bedrock/chat/test_invoke_handler.py b/tests/unit/llms/bedrock/chat/test_invoke_handler.py index 069438e25c0..f3ceac1d93c 100644 --- a/tests/unit/llms/bedrock/chat/test_invoke_handler.py +++ b/tests/unit/llms/bedrock/chat/test_invoke_handler.py @@ -1880,3 +1880,84 @@ async def test_converse_stream_thinking_merges_into_content_with_think_tags() -> "Hi I am Anthropic, I am a helpful assistant" ) assert [getattr(chunk.choices[0].delta, "reasoning_content", None) for chunk in chunks] == [None] * len(chunks) + + +_PLACE_JSON_MODE_REQUEST: Final = json.dumps( + { + "tools": [ + { + "name": "json_tool_call", + "input_schema": { + "type": "object", + "properties": {"city": {"type": "string"}, "country": {"type": "string"}}, + "required": ["city", "country"], + "additionalProperties": True, + }, + } + ] + } +) + +_CUT_JSON_TOOL_STREAM: Final = b"".join( + _bedrock_event_stream_frame(event) + for event in ( + { + "type": "message_start", + "message": { + "id": "msg_cut_1", + "type": "message", + "role": "assistant", + "model": "claude-haiku-5-5", + "content": [], + "stop_reason": None, + "usage": {"input_tokens": 528, "output_tokens": 1}, + }, + }, + { + "type": "content_block_start", + "index": 0, + "content_block": {"type": "tool_use", "id": "toolu_cut_1", "name": "json_tool_call", "input": {}}, + }, + {"type": "content_block_delta", "index": 0, "delta": {"type": "input_json_delta", "partial_json": '{"city"'}}, + {"type": "content_block_delta", "index": 0, "delta": {"type": "input_json_delta", "partial_json": ': "Paris", '}}, + { + "type": "content_block_delta", + "index": 0, + "delta": {"type": "input_json_delta", "partial_json": '"country": "France"}'}, + }, + ) +) + + +def _cut_json_tool_stream_decoder() -> AWSEventStreamDecoder: + return _stream_decoder( + "anthropic", + model="anthropic.claude-haiku-5-5", + json_mode=True, + sync_stream=True, + response_format_schema=response_format_schema_from_request(_PLACE_JSON_MODE_REQUEST, json_mode=True), + ) + + +def _streamed_content(chunks: Sequence[object]) -> str: + return "".join( + chunk.choices[0].delta.content or "" + for chunk in chunks + if isinstance(chunk, ModelResponseStream) and chunk.choices + ) + + +def test_anthropic_invoke_stream_cut_before_the_json_tool_block_ends_sends_the_held_close() -> None: + chunks: Final = list(_cut_json_tool_stream_decoder().iter_bytes(iter([_CUT_JSON_TOOL_STREAM]))) + + assert json.loads(_streamed_content(chunks)) == {"city": "Paris", "country": "France"} + + +@pytest.mark.asyncio +async def test_async_anthropic_invoke_stream_cut_before_the_json_tool_block_ends_sends_the_held_close() -> None: + async def _chunks() -> AsyncIterator[bytes]: + yield _CUT_JSON_TOOL_STREAM + + chunks: Final = [chunk async for chunk in _cut_json_tool_stream_decoder().aiter_bytes(_chunks())] + + assert json.loads(_streamed_content(chunks)) == {"city": "Paris", "country": "France"} diff --git a/tests/unit/llms/bedrock/count_tokens/test_bedrock_count_tokens_handler.py b/tests/unit/llms/bedrock/count_tokens/test_bedrock_count_tokens_handler.py index cb97a62f635..591205b4602 100644 --- a/tests/unit/llms/bedrock/count_tokens/test_bedrock_count_tokens_handler.py +++ b/tests/unit/llms/bedrock/count_tokens/test_bedrock_count_tokens_handler.py @@ -10,6 +10,7 @@ from litellm.llms.bedrock.count_tokens.handler import BedrockCountTokensHandler from litellm.llms.bedrock.count_tokens.transformation import BedrockCountTokensConfig from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler from tests.unit.llms.bedrock.event_loop_probe import EventLoopProbe +from tests.unit.llms.bedrock.event_loop_probe import host_in_loop_probing_vault class _ProbedCountTokensHandler(BedrockCountTokensHandler): @@ -56,6 +57,34 @@ async def test_handle_count_tokens_request_signs_off_the_event_loop(monkeypatch) assert probe.served_during_refresh is True +def _count_tokens_in_us_west_2(request: httpx.Request) -> httpx.Response: + if request.url.host != "bedrock-runtime.us-west-2.amazonaws.com": + return httpx.Response(404, request=request) + return httpx.Response(200, json={"inputTokens": 7}, request=request) + + +@pytest.mark.asyncio +async def test_handle_count_tokens_request_looks_up_its_region_off_the_event_loop( + monkeypatch: pytest.MonkeyPatch, +) -> None: + monkeypatch.delenv("AWS_BEARER_TOKEN_BEDROCK", raising=False) + monkeypatch.setenv("AWS_ACCESS_KEY_ID", "AKIATESTACCESSKEY") + monkeypatch.setenv("AWS_SECRET_ACCESS_KEY", "test-secret") + monkeypatch.setenv("AWS_REGION_NAME", "us-west-2") + vault: Final = host_in_loop_probing_vault(monkeypatch, "AWS_REGION_NAME", "AWS_BEDROCK_RUNTIME_ENDPOINT") + + result = await BedrockCountTokensHandler().handle_count_tokens_request( + request_data={"model": "us.anthropic.claude-sonnet-5-5", "messages": [{"role": "user", "content": "hi"}]}, + litellm_params={}, + resolved_model="us.anthropic.claude-sonnet-5-5", + client=AsyncHTTPHandler(transport=httpx.MockTransport(_count_tokens_in_us_west_2)), + ) + + assert vault.read.is_set() + assert not vault.read_on_loop.is_set() + assert result == {"input_tokens": 7} + + class TestBedrockCountTokensEndpoint: def _make_handler(self) -> BedrockCountTokensConfig: return BedrockCountTokensConfig() diff --git a/tests/unit/llms/bedrock/count_tokens/test_bedrock_count_tokens_transformation.py b/tests/unit/llms/bedrock/count_tokens/test_bedrock_count_tokens_transformation.py index b357c5ac126..052baf601f9 100644 --- a/tests/unit/llms/bedrock/count_tokens/test_bedrock_count_tokens_transformation.py +++ b/tests/unit/llms/bedrock/count_tokens/test_bedrock_count_tokens_transformation.py @@ -168,6 +168,25 @@ def test_transform_includes_tools(): assert tools[0]["toolSpec"]["inputSchema"]["json"]["type"] == "object" +def test_transform_maps_chat_function_tools(): + parameters = {"type": "object", "properties": {"city": {"type": "string"}}, "required": ["city"]} + request = { + "model": "amazon.nova-pro-v1:0", + "messages": [{"role": "user", "content": "Weather in Paris?"}], + "tools": [ + { + "type": "function", + "function": {"name": "get_weather", "description": "Look up the weather", "parameters": parameters}, + } + ], + } + + result = BedrockCountTokensConfig().transform_anthropic_to_bedrock_count_tokens(request) + + assert result["input"]["converse"]["toolConfig"]["tools"] == [ + {"toolSpec": {"name": "get_weather", "description": "Look up the weather", "inputSchema": {"json": parameters}}} + ] + def test_transform_includes_system_and_tools_together(): """Test that both system and tools are included together.""" config = BedrockCountTokensConfig() diff --git a/tests/unit/llms/bedrock/count_tokens/test_bedrock_mantle_count_tokens_handler.py b/tests/unit/llms/bedrock/count_tokens/test_bedrock_mantle_count_tokens_handler.py index 71b451f834c..a6b309c1b83 100644 --- a/tests/unit/llms/bedrock/count_tokens/test_bedrock_mantle_count_tokens_handler.py +++ b/tests/unit/llms/bedrock/count_tokens/test_bedrock_mantle_count_tokens_handler.py @@ -8,6 +8,7 @@ import pytest from litellm.llms.bedrock.common_utils import BedrockError from litellm.llms.bedrock.count_tokens.mantle_handler import BedrockMantleCountTokensHandler from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler +from tests.unit.llms.bedrock.event_loop_probe import host_in_loop_probing_vault MANTLE_COUNT_URL: Final = "https://bedrock-mantle.us-east-1.api.aws/anthropic/v1/messages/count_tokens" LITELLM_PARAMS: Final = { @@ -107,3 +108,22 @@ async def test_non_200_answers_raise_bedrock_error_with_mantle_status() -> None: assert raised.value.status_code == 404 assert "does not exist" in raised.value.message + + +@pytest.mark.asyncio +async def test_region_and_endpoint_lookups_leave_the_event_loop_free(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setenv("AWS_REGION_NAME", "us-east-1") + vault: Final = host_in_loop_probing_vault(monkeypatch, "AWS_REGION_NAME", "BEDROCK_MANTLE_API_BASE") + mantle: Final = _MantleEndpoint(200, {"input_tokens": 2177}) + + result = await BedrockMantleCountTokensHandler().handle_count_tokens_request( + request_data={**REQUEST, "model": "global.anthropic.claude-opus-5-5"}, + litellm_params={key: value for key, value in LITELLM_PARAMS.items() if key != "aws_region_name"}, + resolved_model="anthropic.claude-opus-5-5", + client=_client(mantle), + ) + + assert vault.read.is_set() + assert not vault.read_on_loop.is_set() + assert result == {"input_tokens": 2177} + assert str(mantle.only_request().url) == MANTLE_COUNT_URL diff --git a/tests/unit/llms/bedrock/count_tokens/test_bedrock_token_counter.py b/tests/unit/llms/bedrock/count_tokens/test_bedrock_token_counter.py index dd0d6429f8a..6fb47491323 100644 --- a/tests/unit/llms/bedrock/count_tokens/test_bedrock_token_counter.py +++ b/tests/unit/llms/bedrock/count_tokens/test_bedrock_token_counter.py @@ -1,3 +1,4 @@ +import base64 from collections.abc import Mapping from typing import Final @@ -176,6 +177,130 @@ async def test_claude_runtime_404_retries_with_system_and_tools_on_mantle() -> N } +def _invoke_body(request: httpx.Request) -> dict[str, JsonValue]: + invoke_model: Final = _JSON_BODY.validate_json(request.content)["input"] + assert isinstance(invoke_model, dict) + encoded: Final = invoke_model["invokeModel"] + assert isinstance(encoded, dict) and isinstance(encoded["body"], str) + return _JSON_BODY.validate_json(base64.b64decode(encoded["body"])) + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "chat_params", + [ + {"tool_choice": "required"}, + { + "response_format": { + "type": "json_schema", + "json_schema": {"name": "city", "schema": {"type": "object", "properties": {"city": {"type": "string"}}}}, + } + }, + {"reasoning_effort": "low"}, + ], +) +async def test_runtime_count_leaves_out_the_options_only_mantle_counts(chat_params: dict[str, JsonValue]) -> None: + runtime_counts: Final = _Bedrock(runtime=(200, {"inputTokens": 412}), mantle=(200, {"input_tokens": 2177})) + mantle_counts: Final = _Bedrock(runtime=(404, UNSUPPORTED), mantle=(200, {"input_tokens": 2177})) + request: Final = { + "model_to_use": "global.anthropic.claude-opus-4-8", + "messages": [{"role": "user", "content": "Weather in SF?"}], + "contents": None, + "deployment": DEPLOYMENT, + "request_model": "claude-opus-4-8", + "tools": [{"type": "function", "function": {"name": "get_weather", "parameters": {"type": "object"}}}], + "messages_format": "openai", + "chat_params": chat_params, + } + + await _counter(runtime_counts).count_tokens(**request) + await _counter(mantle_counts).count_tokens(**request) + + assert runtime_counts.posted_hosts() == (RUNTIME_HOST,) + assert mantle_counts.posted_hosts() == (RUNTIME_HOST, MANTLE_HOST) + options: Final = ("thinking", "tool_choice", "output_config") + invoke_body: Final = _invoke_body(runtime_counts.requests[0]) + mantle_body: Final = _JSON_BODY.validate_json(mantle_counts.requests[1].content) + assert [name for name in options if name in invoke_body] == [] + assert [name for name in options if name in mantle_body] != [] + assert {name: mantle_body[name] for name in ("messages", "tools")} == { + name: invoke_body[name] for name in ("messages", "tools") + } + + +@pytest.mark.asyncio +async def test_claude_chat_tool_use_is_counted_in_the_shape_claude_inference_sends() -> None: + bedrock: Final = _Bedrock(runtime=(200, {"inputTokens": 412}), mantle=(200, {"input_tokens": 2177})) + schema: Final = {"type": "object", "properties": {"city": {"type": "string"}}} + + result: Final = await _counter(bedrock).count_tokens( + model_to_use="global.anthropic.claude-opus-4-8", + messages=[ + {"role": "user", "content": "Weather in SF?"}, + { + "role": "assistant", + "content": None, + "tool_calls": [ + {"id": "call_1", "type": "function", "function": {"name": "get_weather", "arguments": "{}"}} + ], + }, + {"role": "tool", "tool_call_id": "call_1", "content": "sunny"}, + ], + contents=None, + deployment=DEPLOYMENT, + request_model="claude-opus-4-8", + tools=[{"type": "function", "function": {"name": "get_weather", "parameters": schema}}], + messages_format="openai", + ) + + assert result is not None + assert (result.error, result.total_tokens) == (False, 412) + assert bedrock.posted_hosts() == (RUNTIME_HOST,) + body: Final = _invoke_body(bedrock.requests[0]) + assert body["tools"] == [{"name": "get_weather", "input_schema": schema, "type": "custom"}] + assert body["messages"] == [ + {"role": "user", "content": [{"type": "text", "text": "Weather in SF?"}]}, + {"role": "assistant", "content": [{"type": "tool_use", "id": "call_1", "name": "get_weather", "input": {}}]}, + {"role": "user", "content": [{"type": "tool_result", "tool_use_id": "call_1", "content": "sunny"}]}, + ] + +@pytest.mark.asyncio +async def test_claude_chat_tool_use_counted_on_mantle_metadata_route_is_translated_too() -> None: + bedrock: Final = _Bedrock(runtime=(200, {"inputTokens": 412}), mantle=(200, {"input_tokens": 2177})) + schema: Final = {"type": "object", "properties": {"city": {"type": "string"}}} + + result: Final = await _counter(bedrock).count_tokens( + model_to_use="bedrock_mantle/global.anthropic.claude-opus-4-8", + messages=[ + {"role": "user", "content": "Weather in SF?"}, + { + "role": "assistant", + "content": None, + "tool_calls": [ + {"id": "call_1", "type": "function", "function": {"name": "get_weather", "arguments": "{}"}} + ], + }, + {"role": "tool", "tool_call_id": "call_1", "content": "sunny"}, + ], + contents=None, + deployment=DEPLOYMENT, + request_model="claude-opus-4-8", + tools=[{"type": "function", "function": {"name": "get_weather", "parameters": schema}}], + messages_format="openai", + ) + + assert result is not None + assert (result.error, result.total_tokens) == (False, 2177) + assert bedrock.posted_hosts() == (MANTLE_HOST,) + body: Final = _JSON_BODY.validate_json(bedrock.requests[0].content) + assert body["tools"] == [{"name": "get_weather", "input_schema": schema, "type": "custom"}] + assert body["messages"] == [ + {"role": "user", "content": [{"type": "text", "text": "Weather in SF?"}]}, + {"role": "assistant", "content": [{"type": "tool_use", "id": "call_1", "name": "get_weather", "input": {}}]}, + {"role": "user", "content": [{"type": "tool_result", "tool_use_id": "call_1", "content": "sunny"}]}, + ] + + @pytest.mark.asyncio @pytest.mark.parametrize( ("model", "host", "tokenizer", "expected_tokens"), diff --git a/tests/unit/llms/bedrock/event_loop_probe.py b/tests/unit/llms/bedrock/event_loop_probe.py index c347247ec32..8bf856582b5 100644 --- a/tests/unit/llms/bedrock/event_loop_probe.py +++ b/tests/unit/llms/bedrock/event_loop_probe.py @@ -1,4 +1,4 @@ -"""Refreshable credentials whose refresh only completes while the event loop keeps serving.""" +"""Credential refreshes and Vault reads that only complete while the event loop keeps serving.""" from __future__ import annotations @@ -8,8 +8,12 @@ import time from datetime import datetime, timedelta, timezone from typing import Final +import pytest from botocore.credentials import RefreshableCredentials +import litellm +from litellm.types.secret_managers.main import KeyManagementSettings, KeyManagementSystem + REFRESH_RELEASE_TIMEOUT_SECONDS: Final = 2.0 REFRESH_START_TIMEOUT_SECONDS: Final = 10.0 @@ -55,3 +59,29 @@ class EventLoopProbe: raise TimeoutError("signing finished without ever starting a credential refresh") await asyncio.sleep(0.005) self.loop_served.set() + + +class LoopProbingVault: + """A Vault with no hosted secrets that records reads on the event-loop thread.""" + + def __init__(self) -> None: + self._loop_thread_id: Final = threading.get_ident() + self.read: Final = threading.Event() + self.read_on_loop: Final = threading.Event() + + def sync_read_secret(self, secret_name: str) -> None: + self.read.set() + if threading.get_ident() == self._loop_thread_id: + self.read_on_loop.set() + + +def host_in_loop_probing_vault(monkeypatch: pytest.MonkeyPatch, *secret_names: str) -> LoopProbingVault: + vault: Final = LoopProbingVault() + monkeypatch.setattr(litellm, "secret_manager_client", vault) + monkeypatch.setattr(litellm, "_key_management_system", KeyManagementSystem.HASHICORP_VAULT) + monkeypatch.setattr( + litellm, + "_key_management_settings", + KeyManagementSettings(access_mode="read_only", hosted_keys=list(secret_names)), + ) + return vault diff --git a/tests/unit/llms/bedrock/files/test_bedrock_files_transformation.py b/tests/unit/llms/bedrock/files/test_bedrock_files_transformation.py index d64a9ee845a..7e05ef500f5 100644 --- a/tests/unit/llms/bedrock/files/test_bedrock_files_transformation.py +++ b/tests/unit/llms/bedrock/files/test_bedrock_files_transformation.py @@ -22,7 +22,8 @@ from botocore.credentials import Credentials import litellm from litellm.constants import DEFAULT_REASONING_EFFORT_LOW_THINKING_BUDGET -from litellm.llms.bedrock.files.transformation import BedrockJsonlFilesTransformation +from litellm.llms.bedrock.common_utils import BedrockError +from litellm.llms.bedrock.files.transformation import BedrockFilesConfig, BedrockJsonlFilesTransformation from tests.unit.proxy.conftest import httpx_transport @@ -36,9 +37,6 @@ class TestBedrockFilesTransformation: Validates that the transformation correctly converts OpenAI batch completion format to Bedrock's expected batch format with proper recordId and modelInput structure. """ - # Initialize the transformation class - transformation = BedrockJsonlFilesTransformation() - # Load input JSONL file input_file_path = os.path.join( os.path.dirname(__file__), "input_batch_completions.jsonl" @@ -52,8 +50,8 @@ class TestBedrockFilesTransformation: openai_jsonl_content.append(json.loads(line)) # Transform the content - bedrock_jsonl_content = transformation._transform_openai_jsonl_content_to_bedrock_jsonl_content( - openai_jsonl_content=openai_jsonl_content + bedrock_jsonl_content: Final = BedrockFilesConfig().transform_openai_jsonl_content_to_bedrock_jsonl_content( + openai_jsonl_content ) # Basic validation @@ -408,9 +406,9 @@ class TestBedrockFilesTransformation: def test_batch_object_name_sanitizes_model_path(self): from litellm.llms.bedrock.files.transformation import BedrockFilesConfig - config = BedrockFilesConfig() - object_name = config._get_s3_object_name_from_batch_jsonl( - [{"body": {"model": "bedrock/../../secret:model"}}] + object_name: Final = BedrockFilesConfig().get_object_name( + {"content": json.dumps({"body": {"model": "bedrock/../../secret:model"}}).encode(), "filename": "b.jsonl"}, + purpose="batch", ) assert object_name.startswith("litellm-bedrock-files-") @@ -4376,3 +4374,205 @@ async def test_async_create_file( "s3://litellm-proxy-941277531214/litellm-bedrock-files-" ) assert file_obj.filename.endswith(".jsonl") + + +_VALID_BATCH_LINE: Final = json.dumps( + { + "custom_id": "req-1", + "method": "POST", + "url": "/v1/chat/completions", + "body": { + "model": "bedrock/amazon.nova-pro-v1:0", + "messages": [{"role": "user", "content": "Hello"}], + "max_tokens": 10, + }, + } +) +_MALFORMED_BATCH_JSONL: Final = f"{_VALID_BATCH_LINE}\n\n{{not json\n".encode() + + +class TestMalformedBatchJsonl: + """A malformed line in a batch input file is the client's mistake, so it must come back as a 400 that names the + line, not escape as a JSONDecodeError the proxy reports as a 500 (#45060).""" + + def test_create_file_request_rejects_a_malformed_line_with_a_400(self): + from litellm.llms.bedrock.common_utils import BedrockError + from litellm.llms.bedrock.files.transformation import BedrockFilesConfig + + with pytest.raises(BedrockError) as exc_info: + BedrockFilesConfig().transform_create_file_request( + model="amazon.nova-pro-v1:0", + create_file_data={ + "file": ("batch.jsonl", _MALFORMED_BATCH_JSONL, "application/jsonl"), + "purpose": "batch", + }, + optional_params={ + "aws_access_key_id": "test-key-id", + "aws_secret_access_key": "test-secret", + "aws_region_name": "us-west-2", + }, + litellm_params={"s3_bucket_name": "litellm-batch-bucket"}, + ) + assert exc_info.value.status_code == 400 + assert "line 3" in exc_info.value.message + + def test_file_content_conversion_rejects_a_malformed_line_with_a_400(self): + from litellm.llms.bedrock.common_utils import BedrockError + + with pytest.raises(BedrockError) as exc_info: + BedrockJsonlFilesTransformation().transform_openai_file_content_to_bedrock_file_content( + _MALFORMED_BATCH_JSONL + ) + assert exc_info.value.status_code == 400 + assert "line 3" in exc_info.value.message + + @pytest.mark.parametrize("content_type", ["application/jsonl", "application/x-jsonl"]) + @pytest.mark.parametrize( + "file_content", + [_MALFORMED_BATCH_JSONL, f"{_VALID_BATCH_LINE}\n\n[1, 2]\n".encode()], + ids=["invalid-json", "array-line"], + ) + def test_create_file_rejects_a_malformed_line_before_uploading(self, content_type: str, file_content: bytes): + """application/x-jsonl is not on the batch MIME allowlist, so the upload skips conversion for it; the line + check must still run so the broken file is rejected instead of landing in S3 unchanged.""" + from litellm.llms.bedrock.common_utils import BedrockError + + with respx.mock as router: + any_request: Final = router.route() + with pytest.raises(BedrockError) as exc_info: + litellm.create_file( + file=("batch.jsonl", file_content, content_type), + purpose="batch", + custom_llm_provider="bedrock", + model="bedrock/amazon.nova-pro-v1:0", + s3_bucket_name="litellm-batch-bucket", + aws_region_name="us-west-2", + aws_access_key_id="test-key-id", + aws_secret_access_key="test-secret", + ) + assert exc_info.value.status_code == 400 + assert "line 3" in exc_info.value.message + assert not any_request.called + + +_VALID_BATCH_RECORD: Final = json.loads(_VALID_BATCH_LINE) + + +def _batch_line(body: object) -> str: + return json.dumps({**_VALID_BATCH_RECORD, "body": body}) + + +def _batch_line_with_body(field: str, value: object) -> str: + return _batch_line({**_VALID_BATCH_RECORD["body"], field: value}) + + +@pytest.mark.usefixtures(httpx_transport.__name__) +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("file_content", "expected_message"), + [ + pytest.param( + f"{_VALID_BATCH_LINE}\n[1, 2]\n".encode(), "Batch input file line 2 is not a JSON object", id="array-line" + ), + pytest.param( + f"[1, 2]\n{_VALID_BATCH_LINE}\n".encode(), "Batch input file line 1 is not a JSON object", id="array-first" + ), + pytest.param( + f"{_VALID_BATCH_LINE}\n{_batch_line(None)}\n".encode(), + "Batch input file line 2 has a body that is missing or not a JSON object", + id="null-body", + ), + pytest.param( + f"{_batch_line('hello')}\n".encode(), + "Batch input file line 1 has a body that is missing or not a JSON object", + id="string-body", + ), + pytest.param( + f"{_batch_line_with_body('model', 123)}\n".encode(), + "Batch input file line 1 has a body.model that is not a string", + id="int-model", + ), + pytest.param( + f"{_batch_line_with_body('model', None)}\n".encode(), + "Batch input file line 1 has a body.model that is not a string", + id="null-model", + ), + pytest.param( + f"{_VALID_BATCH_LINE}\n{_batch_line_with_body('messages', 'hi')}\n".encode(), + "Batch input file line 2 could not be converted to a Bedrock batch record", + id="string-messages", + ), + pytest.param( + f"{_VALID_BATCH_LINE}\n{'[' * 1_000_000}{']' * 1_000_000}\n".encode(), + "Batch input file line 2 could not be parsed", + id="deep-nesting", + ), + pytest.param( + f"{_VALID_BATCH_LINE}\n".encode() + b'{"custom_id": "\xff"}\n', + "Batch input file line 2 is not valid UTF-8", + id="non-utf8", + ), + ], +) +async def test_create_file_rejects_a_malformed_batch_line_with_a_400_before_uploading( + respx_mock: respx.MockRouter, file_content: bytes, expected_message: str +) -> None: + put_route: Final = respx_mock.put(url__regex=r"https://s3\..+").respond(status_code=200) + + with pytest.raises(BedrockError) as exc_info: + await litellm.acreate_file( + file=("batch.jsonl", file_content, "application/jsonl"), + purpose="batch", + custom_llm_provider="bedrock", + s3_bucket_name="litellm-batch-bucket", + aws_region_name="us-west-2", + aws_access_key_id="test-access-key", + aws_secret_access_key="test-secret-key", + ) + + assert exc_info.value.status_code == 400 + assert exc_info.value.message.startswith(expected_message) + assert not put_route.called + + +@pytest.mark.usefixtures(httpx_transport.__name__) +@pytest.mark.asyncio +async def test_create_file_accepts_a_batch_file_with_a_utf8_byte_order_mark(respx_mock: respx.MockRouter) -> None: + put_route: Final = respx_mock.put(url__regex=r"https://s3\..+").respond(status_code=200) + + await litellm.acreate_file( + file=("batch.jsonl", f"\ufeff{_VALID_BATCH_LINE}\n".encode(), "application/jsonl"), + purpose="batch", + custom_llm_provider="bedrock", + s3_bucket_name="litellm-batch-bucket", + aws_region_name="us-west-2", + aws_access_key_id="test-access-key", + aws_secret_access_key="test-secret-key", + ) + + uploaded_record: Final = json.loads(put_route.calls.last.request.content) + assert uploaded_record["recordId"] == _VALID_BATCH_RECORD["custom_id"] + assert "/litellm-bedrock-files-amazon.nova-pro-v1-0-" in str(put_route.calls.last.request.url) + + +@pytest.mark.usefixtures(httpx_transport.__name__) +@pytest.mark.asyncio +async def test_create_file_uploads_a_bedrock_format_batch_file_unchanged_when_its_mime_type_skips_conversion( + respx_mock: respx.MockRouter, +) -> None: + put_route: Final = respx_mock.put(url__regex=r"https://s3\..+").respond(status_code=200) + bedrock_line: Final = json.dumps( + {"recordId": "req-1", "modelInput": {"messages": [{"role": "user", "content": [{"text": "Hello"}]}]}} + ) + + await litellm.acreate_file( + file=("batch.jsonl", f"{bedrock_line}\n".encode(), "application/x-jsonl"), + purpose="batch", + custom_llm_provider="bedrock", + s3_bucket_name="litellm-batch-bucket", + aws_region_name="us-west-2", + aws_access_key_id="test-access-key", + aws_secret_access_key="test-secret-key", + ) + + assert put_route.calls.last.request.content == f"{bedrock_line}\n".encode() diff --git a/tests/unit/llms/bedrock/passthrough/test_bedrock_passthrough_transformation.py b/tests/unit/llms/bedrock/passthrough/test_bedrock_passthrough_transformation.py index da5c4699925..44c0e82c006 100644 --- a/tests/unit/llms/bedrock/passthrough/test_bedrock_passthrough_transformation.py +++ b/tests/unit/llms/bedrock/passthrough/test_bedrock_passthrough_transformation.py @@ -5,8 +5,9 @@ import struct import sys import types from binascii import crc32 -from collections.abc import Callable +from collections.abc import Callable, Mapping from datetime import datetime +from types import MappingProxyType from typing import Final from unittest.mock import patch @@ -922,7 +923,11 @@ INVOKE_BODY = { async def _sent_passthrough_request( - action: str, body: dict[str, object], identity: dict[str, object], **kwargs: object + action: str, + body: dict[str, object], + identity: dict[str, object], + deployment_params: Mapping[str, object] = MappingProxyType({}), + **kwargs: object, ) -> httpx.Request: requests: Final[list[httpx.Request]] = [] @@ -939,6 +944,7 @@ async def _sent_passthrough_request( "aws_access_key_id": "AKIAROUTERKEY", "aws_secret_access_key": "router-secret", "aws_region_name": "us-west-2", + **deployment_params, }, } ] @@ -1189,3 +1195,176 @@ async def test_passthrough_body_is_sent_as_is_when_params_are_dropped_and_forwar assert json.loads(sent.content) == caller_body assert REQUEST_METADATA_HEADER not in sent.headers + + +DEPLOYMENT_GUARDRAIL: Final[Mapping[str, str]] = { + "guardrailIdentifier": "deployment-guardrail", + "guardrailVersion": "3", + "trace": "enabled", + "streamProcessingMode": "sync", +} +DEPLOYMENT_INVOKE_GUARDRAIL_HEADERS: Final[Mapping[str, str]] = { + "x-amzn-bedrock-guardrailidentifier": "deployment-guardrail", + "x-amzn-bedrock-guardrailversion": "3", + "x-amzn-bedrock-trace": "ENABLED", +} +CALLER_GUARDRAIL: Final[Mapping[str, str]] = { + "guardrailIdentifier": "caller-guardrail", + "guardrailVersion": "9", + "trace": "disabled", +} +CALLER_INVOKE_GUARDRAIL_HEADERS: Final[Mapping[str, str]] = { + "x-pass-X-Amzn-Bedrock-GuardrailIdentifier": "caller-guardrail", + "x-pass-X-Amzn-Bedrock-GuardrailVersion": "9", + "x-pass-X-Amzn-Bedrock-Trace": "DISABLED", +} + + +def _invoke_guardrail_headers(request: httpx.Request) -> dict[str, str]: + return { + name: value + for name, value in request.headers.items() + if name.lower().startswith("x-amzn-bedrock-guardrail") or name.lower() == "x-amzn-bedrock-trace" + } + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("action", "sent_guardrail"), + [ + ("converse", {"guardrailIdentifier": "deployment-guardrail", "guardrailVersion": "3", "trace": "enabled"}), + ("converse-stream", DEPLOYMENT_GUARDRAIL), + ], +) +async def test_converse_passthrough_sends_the_deployment_guardrail_in_the_body( + action: str, sent_guardrail: Mapping[str, str], monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setattr(litellm, "bedrock_request_metadata_fields", None) + + request: Final = await _sent_passthrough_request( + action, CONVERSE_BODY, {}, deployment_params={"guardrailConfig": DEPLOYMENT_GUARDRAIL} + ) + + assert json.loads(request.content) == {**CONVERSE_BODY, "guardrailConfig": sent_guardrail} + assert _invoke_guardrail_headers(request) == {} + + +@pytest.mark.asyncio +@pytest.mark.parametrize("action", ["invoke", "invoke-with-response-stream"]) +async def test_invoke_passthrough_sends_the_deployment_guardrail_as_signed_headers( + action: str, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setattr(litellm, "bedrock_request_metadata_fields", REQUEST_METADATA_FIELDS) + + request: Final = await _sent_passthrough_request( + action, INVOKE_BODY, PROXY_IDENTITY, deployment_params={"guardrailConfig": DEPLOYMENT_GUARDRAIL} + ) + + assert _invoke_guardrail_headers(request) == DEPLOYMENT_INVOKE_GUARDRAIL_HEADERS + assert {*DEPLOYMENT_INVOKE_GUARDRAIL_HEADERS, REQUEST_METADATA_HEADER} <= _signed_header_names(request) + assert json.loads(request.headers[REQUEST_METADATA_HEADER]) == EXPECTED_REQUEST_METADATA + assert json.loads(request.content) == INVOKE_BODY + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("action", "caller_guardrail"), + [("converse", CALLER_GUARDRAIL), ("converse-stream", {**CALLER_GUARDRAIL, "streamProcessingMode": "async"})], +) +async def test_deployment_guardrail_replaces_the_caller_converse_guardrail( + action: str, caller_guardrail: Mapping[str, str], monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setattr(litellm, "bedrock_request_metadata_fields", None) + + request: Final = await _sent_passthrough_request( + action, + {**CONVERSE_BODY, "guardrailConfig": caller_guardrail}, + {}, + deployment_params={"guardrailConfig": {"guardrailIdentifier": "deployment-guardrail"}}, + ) + + assert json.loads(request.content) == { + **CONVERSE_BODY, + "guardrailConfig": {"guardrailIdentifier": "deployment-guardrail"}, + } + + +@pytest.mark.asyncio +@pytest.mark.parametrize("action", ["invoke", "invoke-with-response-stream"]) +async def test_deployment_guardrail_replaces_every_invoke_guardrail_header_the_caller_sent( + action: str, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setattr(litellm, "bedrock_request_metadata_fields", None) + + request: Final = await _sent_passthrough_request( + action, + INVOKE_BODY, + {}, + deployment_params={"guardrailConfig": {"guardrailIdentifier": "deployment-guardrail"}}, + request_headers=CALLER_INVOKE_GUARDRAIL_HEADERS, + ) + + assert _invoke_guardrail_headers(request) == {"x-amzn-bedrock-guardrailidentifier": "deployment-guardrail"} + assert json.loads(request.content) == INVOKE_BODY + + +@pytest.mark.asyncio +async def test_passthrough_without_a_deployment_guardrail_sends_the_caller_guardrail_as_is( + monkeypatch: pytest.MonkeyPatch, +) -> None: + monkeypatch.setattr(litellm, "bedrock_request_metadata_fields", None) + caller_body: Final = {**CONVERSE_BODY, "guardrailConfig": CALLER_GUARDRAIL} + + converse: Final = await _sent_passthrough_request("converse", caller_body, {}) + invoke: Final = await _sent_passthrough_request( + "invoke", INVOKE_BODY, {}, request_headers=CALLER_INVOKE_GUARDRAIL_HEADERS + ) + + assert json.loads(converse.content) == caller_body + assert _invoke_guardrail_headers(invoke) == { + "x-amzn-bedrock-guardrailidentifier": "caller-guardrail", + "x-amzn-bedrock-guardrailversion": "9", + "x-amzn-bedrock-trace": "DISABLED", + } + + +@pytest.mark.asyncio +@pytest.mark.parametrize("action", ["invoke", "invoke-with-response-stream"]) +@pytest.mark.parametrize("guardrail_config", ["deployment-guardrail", {"guardrailVersion": "3"}]) +async def test_invoke_passthrough_refuses_a_deployment_guardrail_it_cannot_send( + action: str, guardrail_config: object, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setattr(litellm, "bedrock_request_metadata_fields", None) + + with pytest.raises(BedrockError, match="guardrailConfig") as rejected: + await _sent_passthrough_request( + action, INVOKE_BODY, {}, deployment_params={"guardrailConfig": guardrail_config} + ) + + assert rejected.value.status_code == 400 + + +@pytest.mark.asyncio +async def test_converse_passthrough_forwards_a_non_object_deployment_guardrail_unchanged( + monkeypatch: pytest.MonkeyPatch, +) -> None: + monkeypatch.setattr(litellm, "bedrock_request_metadata_fields", None) + + request: Final = await _sent_passthrough_request( + "converse", CONVERSE_BODY, {}, deployment_params={"guardrailConfig": "deployment-guardrail"} + ) + + assert json.loads(request.content) == {**CONVERSE_BODY, "guardrailConfig": "deployment-guardrail"} + + +@pytest.mark.asyncio +async def test_passthrough_leaves_actions_without_a_guardrail_field_as_sent(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr(litellm, "bedrock_request_metadata_fields", None) + count_tokens_body: Final = {"input": {"converse": CONVERSE_BODY}} + + request: Final = await _sent_passthrough_request( + "count-tokens", count_tokens_body, {}, deployment_params={"guardrailConfig": DEPLOYMENT_GUARDRAIL} + ) + + assert json.loads(request.content) == count_tokens_body + assert _invoke_guardrail_headers(request) == {} diff --git a/tests/unit/llms/bedrock/realtime/test_bedrock_realtime_handler.py b/tests/unit/llms/bedrock/realtime/test_bedrock_realtime_handler.py index a181c5a5425..2ac31b6887d 100644 --- a/tests/unit/llms/bedrock/realtime/test_bedrock_realtime_handler.py +++ b/tests/unit/llms/bedrock/realtime/test_bedrock_realtime_handler.py @@ -18,6 +18,7 @@ from litellm.llms.bedrock.common_utils import BedrockError from litellm.llms.bedrock.realtime.handler import BedrockRealtime from litellm.llms.bedrock.realtime.transformation import BedrockRealtimeConfig from litellm.realtime_api import main as realtime_main +from tests.unit.llms.bedrock.event_loop_probe import host_in_loop_probing_vault @pytest.fixture(autouse=True) @@ -625,6 +626,27 @@ class TestBedrockRealtimeSessionLifecycle: assert first_event["session"]["id"] == "trace-nova-sonic" assert first_event["session"]["model"] == "amazon.nova-sonic-v1:0" + @pytest.mark.asyncio + async def test_region_lookup_on_connect_leaves_the_event_loop_free( + self, stub_aws_sdk_client, monkeypatch: pytest.MonkeyPatch + ) -> None: + monkeypatch.setenv("AWS_REGION_NAME", "us-west-2") + vault: Final = host_in_loop_probing_vault(monkeypatch, "AWS_REGION_NAME") + websocket: Final = RealtimeClientWS() + + _ = await BedrockRealtime().async_realtime( + model="amazon.nova-2-sonic-v1:0", + websocket=websocket, + logging_obj=FakeLogging(), + aws_access_key_id="k", + aws_secret_access_key="s", + ) + + assert vault.read.is_set() + assert not vault.read_on_loop.is_set() + assert stub_aws_sdk_client["config_kwargs"]["region"] == "us-west-2" + assert stub_aws_sdk_client["config_kwargs"]["endpoint_uri"] == "https://bedrock-runtime.us-west-2.amazonaws.com" + @pytest.mark.asyncio async def test_session_update_is_acked_with_session_updated(self, stub_aws_models): handler = BedrockRealtime() diff --git a/tests/unit/llms/bedrock/test_base_aws_llm.py b/tests/unit/llms/bedrock/test_base_aws_llm.py index c755a7e6bc2..4350fdb699b 100644 --- a/tests/unit/llms/bedrock/test_base_aws_llm.py +++ b/tests/unit/llms/bedrock/test_base_aws_llm.py @@ -30,7 +30,7 @@ from litellm.llms.bedrock.base_aws_llm import ( BaseAWSLLM, Boto3CredentialsInfo, run_aws_signing, - sign_request_off_loop_if_aws, + run_off_loop_if_aws, ) from tests.unit.llms.bedrock.event_loop_probe import EventLoopProbe from litellm.llms.bedrock.common_utils import BedrockModelInfo @@ -3443,7 +3443,7 @@ class TestGetRequestHeadersResign: @pytest.mark.asyncio -async def test_sign_request_off_loop_if_aws_keeps_the_loop_serving_while_credentials_refresh(): +async def test_run_off_loop_if_aws_keeps_the_loop_serving_while_credentials_refresh() -> None: """Regression for issue #40165: an AWS provider's signing (and the botocore credential refresh inside it) must run off the event loop, so other requests keep being served meanwhile.""" probe = EventLoopProbe() @@ -3456,7 +3456,7 @@ async def test_sign_request_off_loop_if_aws_keeps_the_loop_serving_while_credent return dict(request.headers) release = asyncio.create_task(probe.release_refresh_from_the_loop()) - signed = await sign_request_off_loop_if_aws(BaseAWSLLM(), sign, headers={"Content-Type": "application/json"}) + signed = await run_off_loop_if_aws(BaseAWSLLM(), sign, headers={"Content-Type": "application/json"}) await release assert "Authorization" in signed diff --git a/tests/unit/llms/bedrock/test_claude_platform_provider.py b/tests/unit/llms/bedrock/test_claude_platform_provider.py index 5d83cba5415..2353a45139b 100644 --- a/tests/unit/llms/bedrock/test_claude_platform_provider.py +++ b/tests/unit/llms/bedrock/test_claude_platform_provider.py @@ -10,6 +10,7 @@ from pydantic import BaseModel, ConfigDict, ValidationError from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler from litellm.types.router import GenericLiteLLMParams +from tests.unit.llms.bedrock.event_loop_probe import host_in_loop_probing_vault WORKSPACE_ALIASES: Final = ("workspace_id", "aws_workspace_id", "anthropic_workspace_id", "anthropic-workspace-id") @@ -683,6 +684,32 @@ async def test_anthropic_messages_claude_platform_sends_exact_body_through_stric _assert_gateway_accepted(requests[0], auth_kwargs) +@pytest.mark.asyncio +async def test_anthropic_messages_claude_platform_workspace_and_region_lookups_leave_the_event_loop_free( + monkeypatch: pytest.MonkeyPatch, +) -> None: + import litellm + + monkeypatch.setenv("ANTHROPIC_AWS_WORKSPACE_ID", "wrkspc_test") + monkeypatch.setenv("AWS_REGION_NAME", "us-west-2") + vault: Final = host_in_loop_probing_vault(monkeypatch, "ANTHROPIC_AWS_WORKSPACE_ID", "AWS_REGION_NAME") + sigv4_without_region: Final = {key: value for key, value in SIGV4_KWARGS.items() if key != "aws_region_name"} + requests: list[dict] = [] + + response = await litellm.anthropic_messages( + model="bedrock/claude_platform/claude-sonnet-5-5", + messages=[{"role": "user", "content": "hello"}], + max_tokens=10, + client=_async_gateway_client(requests), + **sigv4_without_region, + ) + + assert vault.read.is_set() + assert not vault.read_on_loop.is_set() + assert response["content"][0]["text"] == "ok" + _assert_gateway_accepted(requests[0], sigv4_without_region) + + def test_chat_completion_claude_platform_drops_context_management_and_gateway_accepts(): import litellm diff --git a/tests/unit/llms/bedrock_mantle/test_bedrock_mantle_transformation.py b/tests/unit/llms/bedrock_mantle/test_bedrock_mantle_transformation.py index ee41af2110d..f252d9886d3 100644 --- a/tests/unit/llms/bedrock_mantle/test_bedrock_mantle_transformation.py +++ b/tests/unit/llms/bedrock_mantle/test_bedrock_mantle_transformation.py @@ -20,7 +20,7 @@ from botocore.awsrequest import AWSRequest import litellm from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper from litellm.llms.bedrock_mantle.chat.transformation import BedrockMantleChatConfig -from litellm.llms.bedrock.base_aws_llm import sign_request_off_loop_if_aws +from litellm.llms.bedrock.base_aws_llm import run_off_loop_if_aws from litellm.llms.custom_httpx.http_handler import HTTPHandler from litellm.types.utils import LlmProviders from tests.unit.llms.bedrock.event_loop_probe import EventLoopProbe @@ -1234,9 +1234,7 @@ async def test_mantle_signing_runs_off_the_event_loop(): return dict(request.headers) release = asyncio.create_task(probe.release_refresh_from_the_loop()) - signed = await sign_request_off_loop_if_aws( - BedrockMantleChatConfig(), sign, headers={"Content-Type": "application/json"} - ) + signed = await run_off_loop_if_aws(BedrockMantleChatConfig(), sign, headers={"Content-Type": "application/json"}) await release assert "Authorization" in signed diff --git a/tests/unit/llms/chatgpt/chat/test_streaming_utils.py b/tests/unit/llms/chatgpt/chat/test_streaming_utils.py index 8d95a3954a0..f6c5f768c5d 100644 --- a/tests/unit/llms/chatgpt/chat/test_streaming_utils.py +++ b/tests/unit/llms/chatgpt/chat/test_streaming_utils.py @@ -7,9 +7,13 @@ are normalized to match the OpenAI streaming spec: - Deduplication of "closing" chunks with repeated id/name """ +from pathlib import Path +from typing import Final + import pytest from litellm.llms.chatgpt.chat.streaming_utils import ChatGPTToolCallNormalizer +from litellm.llms.chatgpt.chat.transformation import ChatGPTConfig from litellm.types.utils import ( ChatCompletionDeltaToolCall, Delta, @@ -201,3 +205,17 @@ class TestChatGPTToolCallNormalizer: normalizer = ChatGPTToolCallNormalizer(FakeStream()) assert normalizer.custom_attr == "test_value" + + +def test_chatgpt_config_streams_parallel_tool_calls_with_distinct_indices( + monkeypatch: pytest.MonkeyPatch, tmp_path: Path +): + monkeypatch.setenv("CHATGPT_TOKEN_DIR", str(tmp_path)) + chunks: Final = ( + _make_chunk(tool_calls=[_make_tc(index=0, id="call_aaa", name="get_weather")]), + _make_chunk(tool_calls=[_make_tc(index=0, id="call_bbb", name="get_time")]), + ) + + results: Final = list(ChatGPTConfig().post_stream_processing(iter(chunks))) + + assert [result.choices[0].delta.tool_calls[0].index for result in results] == [0, 1] diff --git a/tests/unit/llms/cloudflare/test_cloudflare_extraction_guardrail_handler.py b/tests/unit/llms/cloudflare/test_cloudflare_extraction_guardrail_handler.py new file mode 100644 index 00000000000..1db105f4495 --- /dev/null +++ b/tests/unit/llms/cloudflare/test_cloudflare_extraction_guardrail_handler.py @@ -0,0 +1,335 @@ +from typing import Final, Literal + +import pytest + +from litellm.integrations.custom_guardrail import CustomGuardrail +from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj +from litellm.llms import get_guardrail_translation_mapping +from litellm.llms.cloudflare.extraction.guardrail_translation.handler import ExtractionHandler +from litellm.types.extraction import ExtractionResponse +from litellm.types.utils import CallTypes, GenericGuardrailAPIInputs + + +class _TaggingGuardrail(CustomGuardrail): + def __init__(self) -> None: + super().__init__(guardrail_name="tagging") + self.seen: tuple[str, tuple[str, ...]] | None = None + self.seen_images: tuple[str, ...] = () + + async def apply_guardrail( + self, + inputs: GenericGuardrailAPIInputs, + request_data: dict[str, object], + input_type: Literal["request", "response"], + logging_obj: LiteLLMLoggingObj | None = None, + ) -> GenericGuardrailAPIInputs: + texts: Final = tuple(inputs.get("texts", [])) + self.seen = (input_type, texts) + self.seen_images = tuple(inputs.get("images", [])) + return GenericGuardrailAPIInputs(texts=[f"{text} [GUARDRAILED]" for text in texts]) + + +class _MaskingGuardrail(CustomGuardrail): + def __init__(self, secret: str, mask: str) -> None: + super().__init__(guardrail_name="masking") + self.secret = secret + self.mask = mask + + async def apply_guardrail( + self, + inputs: GenericGuardrailAPIInputs, + request_data: dict[str, object], + input_type: Literal["request", "response"], + logging_obj: LiteLLMLoggingObj | None = None, + ) -> GenericGuardrailAPIInputs: + return GenericGuardrailAPIInputs( + texts=[text.replace(self.secret, self.mask) for text in inputs.get("texts", [])] + ) + + +@pytest.mark.parametrize("call_type", (CallTypes.extraction, CallTypes.aextraction)) +def test_extraction_call_types_resolve_to_the_extraction_handler(call_type: CallTypes) -> None: + assert get_guardrail_translation_mapping(call_type) is ExtractionHandler + + +@pytest.mark.asyncio +async def test_request_state_and_field_instructions_are_guardrailed_on_a_copy() -> None: + guardrail: Final = _TaggingGuardrail() + data: Final = { + "model": "invoice-reader", + "state": "Invoice from Acme Tools, contact jane@acme.example", + "fields": { + "vendor": {"type": "text", "instructions": "Who sent the invoice?"}, + "total": {"type": "number", "unit": "USD"}, + }, + "images": ["data:image/png;base64,AA=="], + } + + result: Final = await ExtractionHandler().process_input_messages(data, guardrail) + + assert guardrail.seen == ( + "request", + ("Invoice from Acme Tools, contact jane@acme.example", "Who sent the invoice?", "USD"), + ) + assert {key: value for key, value in result.items() if key != "metadata"} == { + **{key: value for key, value in data.items() if key != "metadata"}, + "state": "Invoice from Acme Tools, contact jane@acme.example [GUARDRAILED]", + "fields": { + "vendor": {"type": "text", "instructions": "Who sent the invoice? [GUARDRAILED]"}, + "total": {"type": "number", "unit": "USD [GUARDRAILED]"}, + }, + } + assert data["state"] == "Invoice from Acme Tools, contact jane@acme.example" + + +@pytest.mark.asyncio +async def test_a_request_with_no_text_or_images_skips_the_guardrail() -> None: + guardrail: Final = _TaggingGuardrail() + data: Final = {"model": "invoice-reader", "fields": {"total": {"type": "number"}}} + + assert await ExtractionHandler().process_input_messages(data, guardrail) is data + assert guardrail.seen is None + + +@pytest.mark.asyncio +async def test_request_images_reach_the_guardrail_as_data_urls() -> None: + guardrail: Final = _TaggingGuardrail() + data: Final = { + "model": "invoice-reader", + "fields": {"total": {"type": "number"}}, + "images": [{"content_type": "image/png", "base64": "iVBORw0KGgo="}, "data:image/jpeg;base64,/9j/"], + } + + result: Final = await ExtractionHandler().process_input_messages(data, guardrail) + + assert guardrail.seen == ("request", ()) + assert guardrail.seen_images == ("data:image/png;base64,iVBORw0KGgo=", "data:image/jpeg;base64,/9j/") + assert result["images"] == data["images"] + + +@pytest.mark.asyncio +async def test_response_answers_and_state_text_are_guardrailed_on_a_copy_without_stale_spans() -> None: + guardrail: Final = _TaggingGuardrail() + response: Final = ExtractionResponse.model_validate( + { + "model": "invoice-reader", + "answers": { + "vendor": {"type": "text", "value": "Acme Tools", "guess": "Acme Tools", "span": [19, 29]}, + "items": {"type": "list", "value": ["12", "hammers"], "spans": [[51, 53], [54, 61]]}, + "total": {"type": "number", "value": 174, "guess": 174}, + "contact": {"type": "text", "value": None, "p_null": 0.98}, + }, + "truncated": False, + "state_text": "Invoice from Acme Tools", + "usage": {"input_tokens": 52, "output_tokens": 0}, + } + ) + response.set_hidden_params({"response_cost": 0.0000052}) + + result: Final = await ExtractionHandler().process_output_response(response, guardrail) + + assert guardrail.seen == ( + "response", + ("Acme Tools", "12", "hammers", "174", "Invoice from Acme Tools"), + ) + assert isinstance(result, ExtractionResponse) + assert result.model_dump(mode="json") == { + **response.model_dump(mode="json"), + "answers": { + "vendor": {"type": "text", "value": "Acme Tools [GUARDRAILED]", "guess": "Acme Tools [GUARDRAILED]"}, + "items": {"type": "list", "value": ["12 [GUARDRAILED]", "hammers [GUARDRAILED]"]}, + "total": {"type": "number", "value": None}, + "contact": {"type": "text", "value": None, "p_null": 0.98}, + }, + "state_text": "Invoice from Acme Tools [GUARDRAILED]", + } + assert response.answers["vendor"].value == "Acme Tools" + assert result.hidden_params["response_cost"] == 0.0000052 + + +@pytest.mark.asyncio +async def test_spans_into_the_callers_own_state_survive_a_response_guardrail() -> None: + response: Final = ExtractionResponse.model_validate( + { + "model": "invoice-reader", + "answers": {"vendor": {"type": "text", "value": "Acme Tools", "span": [19, 29]}}, + "truncated": False, + "usage": {"input_tokens": 52, "output_tokens": 0}, + } + ) + + result: Final = await ExtractionHandler().process_output_response(response, _TaggingGuardrail()) + + assert isinstance(result, ExtractionResponse) + assert result.answers["vendor"].model_dump(mode="json") == { + "type": "text", + "value": "Acme Tools [GUARDRAILED]", + "span": [19, 29], + } + + +@pytest.mark.asyncio +async def test_a_response_guardrail_change_to_a_typed_answer_nulls_it_instead_of_breaking_its_type() -> None: + guardrail: Final = _MaskingGuardrail("2026-03-03", "[DATE]") + request_data: Final = { + "fields": { + "invoice_date": {"type": "date"}, + "due_dates": {"type": "list", "items": "date"}, + "notes": {"type": "list", "items": "text"}, + } + } + response: Final = ExtractionResponse.model_validate( + { + "model": "invoice-reader", + "answers": { + "invoice_date": {"type": "date", "value": "2026-03-03", "guess": "2026-03-03", "span": [30, 40]}, + "due_dates": {"type": "list", "value": ["2026-03-03", "2026-04-02"], "spans": [[30, 40], [50, 60]]}, + "notes": {"type": "list", "value": ["paid 2026-03-03"], "spans": [[70, 85]]}, + "received": {"type": "date", "value": "2026-02-27", "span": [90, 100]}, + }, + "truncated": False, + "usage": {"input_tokens": 52, "output_tokens": 0}, + } + ) + + result: Final = await ExtractionHandler().process_output_response(response, guardrail, request_data=request_data) + + assert isinstance(result, ExtractionResponse) + assert {name: answer.model_dump(mode="json") for name, answer in result.answers.items()} == { + "invoice_date": {"type": "date", "value": None}, + "due_dates": {"type": "list", "value": None}, + "notes": {"type": "list", "value": ["paid [DATE]"], "spans": [[70, 85]]}, + "received": {"type": "date", "value": "2026-02-27", "span": [90, 100]}, + } + + +@pytest.mark.asyncio +async def test_a_response_guardrail_that_masks_a_number_nulls_every_answer_carrying_it() -> None: + request_data: Final = { + "fields": { + "phone_text": {"type": "text"}, + "phone_number": {"type": "number"}, + "phone_list": {"type": "list", "items": "number"}, + "phone_mean": {"type": "estimate"}, + "phone_median": {"type": "estimate"}, + "phone_p10": {"type": "estimate"}, + "phone_p90": {"type": "estimate"}, + "phone_quantile": {"type": "estimate"}, + "phone_forecast": {"type": "forecast"}, + "total": {"type": "number"}, + } + } + response: Final = ExtractionResponse.model_validate( + { + "model": "invoice-reader", + "answers": { + "phone_text": {"type": "text", "value": "4155550123", "span": [10, 20]}, + "phone_number": {"type": "number", "value": 4155550123, "guess": 4155550123, "span": [10, 20]}, + "phone_list": {"type": "list", "value": [4155550123], "spans": [[10, 20]]}, + "phone_mean": { + "type": "estimate", + "value": None, + "mean": 4155550123.4, + "p10": 4155550000, + "p_null": 0.6, + }, + "phone_median": { + "type": "estimate", + "value": None, + "median": 4155550123, + "p90": 4155550200, + "p_null": 0.6, + }, + "phone_p10": {"type": "estimate", "value": None, "p10": 4155550123, "p_null": 0.6}, + "phone_p90": {"type": "estimate", "value": None, "p90": 4155550123.2, "p_null": 0.6}, + "phone_quantile": { + "type": "estimate", + "value": None, + "quantiles": [4155550000, 4155550123, 4155550200], + "p_null": 0.6, + }, + "phone_forecast": { + "type": "forecast", + "value": None, + "steps": [{"value": 12, "p10": 10}, {"value": 13, "p90": 4155550123}], + "p_null": 0.6, + }, + "total": {"type": "number", "value": 174, "guess": 174}, + }, + "truncated": False, + "usage": {"input_tokens": 52, "output_tokens": 0}, + } + ) + + result: Final = await ExtractionHandler().process_output_response( + response, _MaskingGuardrail("4155550123", "[PHONE]"), request_data=request_data + ) + + assert isinstance(result, ExtractionResponse) + assert {name: answer.model_dump(mode="json") for name, answer in result.answers.items()} == { + "phone_text": {"type": "text", "value": "[PHONE]", "span": [10, 20]}, + "phone_number": {"type": "number", "value": None}, + "phone_list": {"type": "list", "value": None}, + "phone_mean": {"type": "estimate", "value": None, "p_null": 0.6}, + "phone_median": {"type": "estimate", "value": None, "p_null": 0.6}, + "phone_p10": {"type": "estimate", "value": None, "p_null": 0.6}, + "phone_p90": {"type": "estimate", "value": None, "p_null": 0.6}, + "phone_quantile": {"type": "estimate", "value": None, "p_null": 0.6}, + "phone_forecast": {"type": "forecast", "value": None, "p_null": 0.6}, + "total": {"type": "number", "value": 174, "guess": 174}, + } + + +@pytest.mark.asyncio +async def test_a_response_guardrail_does_not_scan_the_fraction_digits_of_an_estimate() -> None: + days_late: Final = { + "type": "estimate", + "value": None, + "mean": 3.4525830151341586, + "median": 2.4525830151341586, + "p_null": 0.2, + } + response: Final = ExtractionResponse.model_validate( + { + "model": "invoice-reader", + "answers": {"days_late": days_late}, + "truncated": False, + "usage": {"input_tokens": 52, "output_tokens": 0}, + } + ) + + result: Final = await ExtractionHandler().process_output_response( + response, + _MaskingGuardrail("4525830151341586", "[CARD]"), + request_data={"fields": {"days_late": {"type": "estimate"}}}, + ) + + assert isinstance(result, ExtractionResponse) + assert result.answers["days_late"].model_dump(mode="json") == days_late + + +@pytest.mark.asyncio +async def test_a_response_guardrail_sees_the_decimal_text_of_a_fractional_number_answer() -> None: + response: Final = ExtractionResponse.model_validate( + { + "model": "invoice-reader", + "answers": { + "unit_price": {"type": "number", "value": 14.5, "guess": 14.5, "span": [30, 36]}, + "prices": {"type": "list", "value": [14.5, 2.25], "spans": [[30, 36], [40, 45]]}, + }, + "truncated": False, + "usage": {"input_tokens": 52, "output_tokens": 0}, + } + ) + + result: Final = await ExtractionHandler().process_output_response( + response, + _MaskingGuardrail("14.5", "[PRICE]"), + request_data={"fields": {"unit_price": {"type": "number"}, "prices": {"type": "list", "items": "number"}}}, + ) + + assert isinstance(result, ExtractionResponse) + assert {name: answer.model_dump(mode="json") for name, answer in result.answers.items()} == { + "unit_price": {"type": "number", "value": None}, + "prices": {"type": "list", "value": None}, + } diff --git a/tests/unit/llms/cloudflare/test_cloudflare_extraction_transformation.py b/tests/unit/llms/cloudflare/test_cloudflare_extraction_transformation.py new file mode 100644 index 00000000000..214fec07284 --- /dev/null +++ b/tests/unit/llms/cloudflare/test_cloudflare_extraction_transformation.py @@ -0,0 +1,221 @@ +import json +from typing import Final + +import httpx +import pytest +from pydantic import ValidationError + +import litellm +from litellm.llms.base_llm.chat.transformation import BaseLLMException +from litellm.llms.base_llm.extraction.transformation import BaseExtractionConfig +from litellm.types.extraction import ExtractionRequestBody +from litellm.types.utils import LlmProviders +from litellm.utils import ProviderConfigManager + +INVOICE_STATE: Final = "Invoice #4471 from Acme Tools, dated March 3 2026. Total $174.00. Payment due in 30 days." +INVOICE_FIELDS: Final = { + "vendor": {"type": "text", "instructions": "Who sent the invoice"}, + "invoice_date": {"type": "date"}, + "total": {"type": "number", "decimals": 2, "unit": "USD"}, + "items": {"type": "list", "items": "text"}, + "days_to_pay": {"type": "estimate", "min": 0, "max": 90, "step": 1}, +} +CLAIRIC_RESULT: Final = { + "model": "clairic", + "answers": { + "vendor": { + "type": "text", + "p_null": 0.01, + "span": [19, 29], + "guess": "Acme Tools", + "confidence": 0.99, + "value": "Acme Tools", + }, + "total": {"type": "number", "p_null": 0.0, "guess": 174, "confidence": 0.99, "value": 174}, + "items": {"type": "list", "value": ["hammers"], "spans": [[54, 61]], "confidence": 0.4}, + "days_to_pay": { + "type": "estimate", + "value": 31, + "mean": 30.7, + "median": 30, + "p10": 29, + "p90": 34, + "p_below": 0.0, + "p_above": 0.0, + }, + }, + "truncated": False, + "usage": { + "state_tokens": 52, + "image_tokens": 0, + "schema_tokens": 312, + "input_tokens": 416, + "output_tokens": 0, + "passes": 2, + }, +} + + +def _cloudflare_config() -> BaseExtractionConfig: + config: Final = ProviderConfigManager.get_provider_extraction_config("clairic", LlmProviders.CLOUDFLARE) + assert config is not None + return config + + +def _response(payload: object) -> httpx.Response: + return httpx.Response(status_code=200, content=json.dumps(payload).encode()) + + +def test_only_cloudflare_serves_extraction() -> None: + assert ProviderConfigManager.get_provider_extraction_config("gpt-5", LlmProviders.OPENAI) is None + assert isinstance(_cloudflare_config(), litellm.CloudflareExtractionConfig) + + +@pytest.mark.parametrize("model", ("clairic", "@cf/cloudflare/clairic")) +def test_clairic_resolves_to_its_workers_ai_run_url(monkeypatch: pytest.MonkeyPatch, model: str) -> None: + monkeypatch.setenv("CLOUDFLARE_ACCOUNT_ID", "acct") + config: Final = _cloudflare_config() + canonical: Final = config.canonical_model(model) + api_base: Final = config.resolve_api_base(None) + + assert canonical == "@cf/cloudflare/clairic" + assert api_base is not None + assert ( + config.get_complete_url(api_base, canonical) + == "https://api.cloudflare.com/client/v4/accounts/acct/ai/run/@cf/cloudflare/clairic" + ) + + +@pytest.mark.parametrize( + "api_base", + ( + "https://gateway.example/client/v4/accounts/acct/ai/v1", + "https://gateway.example/client/v4/accounts/acct/ai/run/", + "https://gateway.example/client/v4/accounts/acct", + ), +) +def test_custom_api_base_keeps_the_run_path(api_base: str) -> None: + assert ( + _cloudflare_config().get_complete_url(api_base, "@cf/cloudflare/clairic") + == "https://gateway.example/client/v4/accounts/acct/ai/run/@cf/cloudflare/clairic" + ) + + +def test_missing_account_id_leaves_no_default_api_base(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.delenv("CLOUDFLARE_ACCOUNT_ID", raising=False) + monkeypatch.delenv("CLOUDFLARE_API_BASE", raising=False) + + assert _cloudflare_config().resolve_api_base(None) is None + + +def test_request_forwards_the_callers_fields_unchanged() -> None: + request: Final = ExtractionRequestBody.model_validate( + { + "state": INVOICE_STATE, + "fields": INVOICE_FIELDS, + "reference_date": "2026-03-01", + "options": {"return_state_text": True}, + "images": [{"content_type": "image/png", "base64": "iVBORw0KGgo="}], + } + ) + + assert _cloudflare_config().transform_extraction_request("@cf/cloudflare/clairic", request) == { + "model": "clairic", + "state": INVOICE_STATE, + "fields": INVOICE_FIELDS, + "reference_date": "2026-03-01", + "options": {"return_state_text": True}, + "images": [{"content_type": "image/png", "base64": "iVBORw0KGgo="}], + } + + +@pytest.mark.parametrize("wrapped", (True, False)) +def test_response_parses_typed_answers_and_usage(wrapped: bool) -> None: + payload: Final = ( + {"result": CLAIRIC_RESULT, "success": True, "errors": [], "messages": []} if wrapped else CLAIRIC_RESULT + ) + + response: Final = _cloudflare_config().transform_extraction_response( + "@cf/cloudflare/clairic", "cloudflare", _response(payload) + ) + + assert response.model_dump(mode="json") == CLAIRIC_RESULT + assert response.answers["vendor"].span == (19, 29) + assert response.usage.input_tokens == 416 + + +def test_unexpected_response_raises_a_provider_error() -> None: + with pytest.raises(BaseLLMException) as error: + _cloudflare_config().transform_extraction_response( + "@cf/cloudflare/clairic", "cloudflare", _response({"result": {"answers": {}}}) + ) + + assert error.value.status_code == 500 + + +def test_unknown_field_type_is_rejected() -> None: + with pytest.raises(ValidationError, match=r"fields\.vendor\.type"): + ExtractionRequestBody.model_validate({"state": INVOICE_STATE, "fields": {"vendor": {"type": "color"}}}) + + +def test_a_list_field_without_an_item_type_is_rejected_locally() -> None: + # Cloudflare answered a list field without items with 422 code 3030 on @cf/cloudflare/clairic, probed 2026-10-20 + with pytest.raises(ValidationError, match=r"fields\.line_items\n.*list fields need items"): + ExtractionRequestBody.model_validate({"state": INVOICE_STATE, "fields": {"line_items": {"type": "list"}}}) + + +@pytest.mark.parametrize( + "spec", + ( + {"type": "number", "decimals": "2"}, + {"type": "number", "integer": "yes"}, + {"type": "number", "integer": 1}, + {"type": "estimate", "min": True, "max": 90}, + ), + ids=("string_decimals", "string_integer", "number_integer", "bool_min"), +) +def test_a_field_value_of_the_wrong_json_type_is_rejected_instead_of_coerced(spec: dict[str, object]) -> None: + # Cloudflare answered each of these specs with a 400 or 422 on @cf/cloudflare/clairic, probed 2026-10-20 + with pytest.raises(ValidationError, match=r"fields\.total\."): + ExtractionRequestBody.model_validate({"state": INVOICE_STATE, "fields": {"total": spec}}) + + +def test_numbers_in_a_field_spec_go_to_cloudflare_exactly_as_sent() -> None: + # Cloudflare answered "decimals": 2.0 and "step": 1.0 with a 200 on @cf/cloudflare/clairic, probed 2026-10-20 + fields: Final = { + "total": {"type": "number", "decimals": 2.0, "null_threshold": 1}, + "days_to_pay": {"type": "estimate", "min": 0, "max": 90, "step": 1.0}, + } + request: Final = ExtractionRequestBody.model_validate({"state": INVOICE_STATE, "fields": fields}) + + body: Final = _cloudflare_config().transform_extraction_request("@cf/cloudflare/clairic", request) + + assert json.dumps(body["fields"]) == json.dumps(fields) + + +@pytest.mark.parametrize("name", ("due date", "1st_item", "x" * 80), ids=("space", "digit_first", "80_chars")) +def test_a_field_name_clairic_refuses_is_rejected_locally(name: str) -> None: + # Cloudflare answered each of these names with 422 code 3030 on @cf/cloudflare/clairic, probed 2026-10-19 + with pytest.raises(ValidationError, match=r"fields\."): + ExtractionRequestBody.model_validate({"state": INVOICE_STATE, "fields": {name: {"type": "text"}}}) + + +@pytest.mark.parametrize("name", ("_vendor", "line.items", "days-to-pay", "x" * 64)) +def test_field_names_with_dots_dashes_and_underscores_up_to_64_chars_are_accepted(name: str) -> None: + # Cloudflare answered each of these names with a 200 on @cf/cloudflare/clairic, probed 2026-10-19 + request: Final = ExtractionRequestBody.model_validate({"state": INVOICE_STATE, "fields": {name: {"type": "text"}}}) + + assert tuple(request.fields) == (name,) + + +def test_decisions_config_still_resolves_clef_after_the_shared_helpers_moved(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setenv("CLOUDFLARE_ACCOUNT_ID", "acct") + config: Final = litellm.CloudflareDecisionsConfig() + api_base: Final = config.get_default_api_base() + + assert api_base is not None + assert ( + config.get_complete_url(api_base, config.canonical_model("clef")) + == "https://api.cloudflare.com/client/v4/accounts/acct/ai/run/@cf/cloudflare/clef" + ) + assert config.unwrap_response({"result": {"answers": {}}}) == {"answers": {}} diff --git a/tests/unit/llms/custom_httpx/test_llm_http_handler.py b/tests/unit/llms/custom_httpx/test_llm_http_handler.py index 8b46597b603..63cc45b29df 100644 --- a/tests/unit/llms/custom_httpx/test_llm_http_handler.py +++ b/tests/unit/llms/custom_httpx/test_llm_http_handler.py @@ -5,13 +5,14 @@ import json import logging import threading import time -from collections.abc import Mapping +from collections.abc import Awaitable, Callable, Mapping from types import MappingProxyType from typing import Final from unittest.mock import AsyncMock, Mock, patch import httpx import pytest +import respx from botocore.credentials import RefreshableCredentials import litellm @@ -66,6 +67,7 @@ from litellm.types.llms.openai import HttpxBinaryResponseContent, ResponsesAPIRe from litellm.types.router import GenericLiteLLMParams from litellm.types.utils import ImageObject, ImageResponse, ModelResponse, TranscriptionResponse from tests.unit.llms.bedrock.event_loop_probe import EventLoopProbe +from tests.unit.llms.bedrock.event_loop_probe import host_in_loop_probing_vault _ACTIVE_KEY = "_code_interpreter_interception_active" _SANDBOX_KEY = "_code_interpreter_interception_sandbox_key" @@ -1245,6 +1247,155 @@ async def test_async_anthropic_messages_handler_signs_bedrock_off_the_event_loop assert probe.served_during_refresh is True +_BEDROCK_MESSAGE: Final = { + "id": "msg_1", + "type": "message", + "role": "assistant", + "model": "claude-sonnet-5-5", + "content": [{"type": "text", "text": "hi"}], + "stop_reason": "end_turn", + "usage": {"input_tokens": 1, "output_tokens": 1}, +} +_BEDROCK_RESPONSE: Final = { + "id": "resp_1", + "object": "response", + "created_at": 1, + "status": "completed", + "model": "openai.gpt-5.6-sol", + "output": [], + "usage": {"input_tokens": 1, "output_tokens": 1, "total_tokens": 2}, +} +_EMPTY_S3_LISTING: Final = ( + b'' + b'' + b"batch-inputs0false" +) +_BATCH_LINE: Final = json.dumps( + { + "custom_id": "1", + "method": "POST", + "url": "/v1/chat/completions", + "body": {"model": "us.anthropic.claude-sonnet-5-5", "messages": [{"role": "user", "content": "hi"}]}, + } +).encode() +_BATCH_FILE_ID: Final = "s3://batch-inputs/litellm-bedrock-files/batch.jsonl" +_BEDROCK_ENTRY_POINTS: Final[tuple[tuple[str, Callable[[], Awaitable[object]], httpx.Response], ...]] = ( + ( + "anthropic_messages", + lambda: litellm.anthropic.messages.acreate( + model="bedrock/invoke/us.anthropic.claude-sonnet-5-5", + messages=[{"role": "user", "content": "hi"}], + max_tokens=16, + ), + httpx.Response(200, json=_BEDROCK_MESSAGE), + ), + ( + "responses", + lambda: litellm.aresponses(model="bedrock/us.openai.gpt-5.6-sol", input="hi"), + httpx.Response(200, json=_BEDROCK_RESPONSE), + ), + ( + "compact_responses", + lambda: litellm.acompact_responses(model="bedrock/us.openai.gpt-5.6-sol", input="hi"), + httpx.Response(200, json=_BEDROCK_RESPONSE), + ), + ( + "search", + lambda: litellm.asearch( + query="hi", + search_provider="agentcore", + api_base="https://gw.gateway.bedrock-agentcore.us-west-2.amazonaws.com/mcp", + ), + httpx.Response(200, json={"jsonrpc": "2.0", "id": 1, "result": {"content": []}}), + ), + ( + "create_file", + lambda: litellm.acreate_file( + file=("batch.jsonl", _BATCH_LINE, "application/jsonl"), + purpose="batch", + custom_llm_provider="bedrock", + model="bedrock/us.anthropic.claude-sonnet-5-5", + ), + httpx.Response(200), + ), + ( + "retrieve_file", + lambda: litellm.afile_retrieve(file_id=_BATCH_FILE_ID, custom_llm_provider="bedrock"), + httpx.Response(200, content=_BATCH_LINE), + ), + ( + "delete_file", + lambda: litellm.afile_delete(file_id=_BATCH_FILE_ID, custom_llm_provider="bedrock"), + httpx.Response(204), + ), + ( + "list_files", + lambda: litellm.afile_list(custom_llm_provider="bedrock"), + httpx.Response(200, content=_EMPTY_S3_LISTING), + ), + ( + "file_content", + lambda: litellm.afile_content(file_id=_BATCH_FILE_ID, custom_llm_provider="bedrock"), + httpx.Response(200, content=_BATCH_LINE), + ), + ( + "create_batch", + lambda: litellm.acreate_batch( + completion_window="24h", + endpoint="/v1/chat/completions", + input_file_id=_BATCH_FILE_ID, + custom_llm_provider="bedrock", + model="bedrock/us.anthropic.claude-sonnet-5-5", + aws_batch_role_arn="arn:aws:iam::123456789012:role/batch", + s3_output_bucket_name="batch-outputs", + ), + httpx.Response(200, json={"jobArn": "arn:aws:bedrock:us-west-2:123456789012:model-invocation-job/batch"}), + ), + ( + "vector_store_search", + lambda: litellm.vector_stores.asearch(vector_store_id="KBID12345", query="hi", custom_llm_provider="bedrock"), + httpx.Response(200, json={"retrievalResults": []}), + ), +) + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("call", "upstream_answer"), + [pytest.param(call, answer, id=name) for name, call, answer in _BEDROCK_ENTRY_POINTS], +) +async def test_bedrock_secret_lookups_leave_the_event_loop_free( + call: Callable[[], Awaitable[object]], + upstream_answer: httpx.Response, + respx_mock: respx.MockRouter, + monkeypatch: pytest.MonkeyPatch, +): + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + monkeypatch.setenv("AWS_ACCESS_KEY_ID", "AKIATESTTESTTESTTEST") + monkeypatch.setenv("AWS_SECRET_ACCESS_KEY", "test-secret") + monkeypatch.setenv("AWS_REGION_NAME", "us-west-2") + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "batch-inputs") + monkeypatch.setenv("AWS_S3_OUTPUT_BUCKET_NAME", "batch-outputs") + vault: Final = host_in_loop_probing_vault( + monkeypatch, + "AWS_REGION_NAME", + "AWS_BEDROCK_RUNTIME_ENDPOINT", + "AWS_BEARER_TOKEN_BEDROCK", + "AWS_S3_ENCRYPTION_KEY_ID", + "AWS_S3_BUCKET_OWNER", + "AGENTCORE_MCP_PROTOCOL_VERSION", + "AGENTCORE_SEARCH_TOOL_NAME", + "AGENTCORE_GATEWAY_TOKEN", + ) + upstream: Final = respx_mock.route().mock(return_value=upstream_answer) + + _ = await call() + + assert vault.read.is_set() + assert not vault.read_on_loop.is_set() + assert ".us-west-2." in upstream.calls.last.request.url.host + + @pytest.mark.asyncio async def test_async_anthropic_messages_handler_passes_litellm_metadata(): """Ensure litellm_metadata from kwargs is forwarded via update_from_kwargs. diff --git a/tests/unit/llms/gemini/google_genai/test_google_genai_transformation.py b/tests/unit/llms/gemini/google_genai/test_google_genai_transformation.py index b4c654ee175..da8ab138416 100644 --- a/tests/unit/llms/gemini/google_genai/test_google_genai_transformation.py +++ b/tests/unit/llms/gemini/google_genai/test_google_genai_transformation.py @@ -9,6 +9,7 @@ from respx import MockRouter import litellm from litellm.google_genai import agenerate_content_stream from litellm.llms.gemini.google_genai.transformation import GoogleGenAIConfig +from litellm.llms.vertex_ai.common_utils import GEMINI_MAX_ENUM_CHARACTERS _JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue]) _PROMPT: Final = "Hello, can you tell me a short joke?" @@ -239,3 +240,43 @@ async def test_generate_content_stream_parses_function_call( }, ) assert _JSON_OBJECT.validate_json(route.calls.last.request.content)["tools"] == tools + + +@pytest.mark.parametrize( + ("model", "expected_level"), + [ + ("gemini-flash-latest", {"type": "integer", "enum": ["1", "2", "5"]}), + ("gemini-1.5-pro", {"type": "integer"}), + ], +) +def test_normalize_response_schema_sends_integer_enums_to_gemini_3( + model: str, expected_level: dict[str, object] +) -> None: + config_dict: Final = { + "responseSchema": {"type": "object", "properties": {"level": {"type": "integer", "enum": [1, 2, 5]}}} + } + + GoogleGenAIConfig._normalize_response_schema(config_dict, model) + + assert config_dict["responseSchema"]["properties"]["level"] == expected_level + + +@pytest.mark.parametrize( + ("value_count", "integer_enum_sent"), + [(GEMINI_MAX_ENUM_CHARACTERS // 10, True), (GEMINI_MAX_ENUM_CHARACTERS // 10 + 1, False)], +) +def test_normalize_response_schema_drops_integer_enums_past_the_enum_budget( + value_count: int, integer_enum_sent: bool +) -> None: + values: Final = [10**9 + n for n in range(value_count)] + config_dict: Final = { + "responseSchema": {"type": "object", "properties": {"level": {"type": "integer", "enum": values}}} + } + + GoogleGenAIConfig._normalize_response_schema(config_dict, "gemini-flash-latest") + + assert config_dict["responseSchema"]["properties"]["level"] == ( + {"type": "integer", "enum": [str(value) for value in values]} + if integer_enum_sent + else {"type": "integer"} + ) diff --git a/tests/unit/llms/github_copilot/test_github_host.py b/tests/unit/llms/github_copilot/test_github_host.py new file mode 100644 index 00000000000..df2efe4669b --- /dev/null +++ b/tests/unit/llms/github_copilot/test_github_host.py @@ -0,0 +1,59 @@ +from typing import Final + +import pytest + +from litellm.llms.github_copilot.github_host import ( + github_host_endpoints, + normalized_github_host, +) + + +@pytest.mark.parametrize( + ("raw", "expected"), + [ + (None, "github.com"), + ("", "github.com"), + ("GitHub.com", "github.com"), + ("OCTO.ghe.com", "octo.ghe.com"), + ("octo-1.ghe.com", "octo-1.ghe.com"), + ("https://octo.ghe.com", None), + ("ghes.example.com", None), + ("octo.ghe.com:443", None), + ("a.b.ghe.com", None), + ("octo.ghe.com.", None), + (" api.octo.ghe.com", None), + ("octo.ghe.com/path", None), + ], +) +def test_normalized_github_host_accepts_only_bare_supported_hosts(raw: object, expected: str | None) -> None: + assert normalized_github_host(raw) == expected + + +def test_github_com_endpoints_read_url_overrides_at_call_time(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setenv("GITHUB_COPILOT_DEVICE_CODE_URL", "https://device.example/code") + monkeypatch.setenv("GITHUB_COPILOT_ACCESS_TOKEN_URL", "https://device.example/token") + monkeypatch.setenv("GITHUB_COPILOT_API_KEY_URL", "https://api.example/copilot") + monkeypatch.setenv("GITHUB_COPILOT_CLIENT_ID", "custom-client") + + endpoints: Final = github_host_endpoints("github.com") + + assert endpoints.device_code_url == "https://device.example/code" + assert endpoints.access_token_url == "https://device.example/token" + assert endpoints.api_key_url == "https://api.example/copilot" + assert endpoints.client_id == "custom-client" + + +def test_ghe_endpoints_ignore_github_com_url_overrides(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setenv("GITHUB_COPILOT_DEVICE_CODE_URL", "https://device.example/code") + monkeypatch.setenv("GITHUB_COPILOT_ACCESS_TOKEN_URL", "https://device.example/token") + monkeypatch.setenv("GITHUB_COPILOT_API_KEY_URL", "https://api.example/copilot") + monkeypatch.setenv("GITHUB_COPILOT_CLIENT_ID", "custom-client") + + endpoints: Final = github_host_endpoints("octo.ghe.com") + + assert endpoints.device_code_url == "https://octo.ghe.com/login/device/code" + assert endpoints.access_token_url == "https://octo.ghe.com/login/oauth/access_token" + assert endpoints.api_key_url == "https://api.octo.ghe.com/copilot_internal/v2/token" + assert endpoints.user_url == "https://api.octo.ghe.com/user" + assert endpoints.default_copilot_api_base == "https://copilot-api.octo.ghe.com" + assert endpoints.client_id == "custom-client" diff --git a/tests/unit/llms/github_copilot/test_per_user_auth.py b/tests/unit/llms/github_copilot/test_per_user_auth.py index 9b16d3c0aa7..cf6fb9fa71f 100644 --- a/tests/unit/llms/github_copilot/test_per_user_auth.py +++ b/tests/unit/llms/github_copilot/test_per_user_auth.py @@ -12,6 +12,7 @@ import httpx import pytest import litellm +from litellm.constants import GITHUB_COPILOT_DEFAULT_HOST from litellm.exceptions import ( AuthenticationError, BadRequestError, @@ -32,20 +33,33 @@ from litellm.llms.github_copilot.per_user_auth import ( attach_github_copilot_user_session, evict_copilot_user_session, exchange_github_token, + github_copilot_host_endpoints, github_copilot_auth_mode, github_copilot_user_session_from, validated_copilot_api_base, ) +from litellm.llms.github_copilot.github_host import github_host_endpoints from litellm.types.utils import CredentialItem, ModelResponse EXCHANGE_URL = "https://api.github.com/copilot_internal/v2/token" DEVICE_CODE_URL = "https://github.com/login/device/code" ACCESS_TOKEN_URL = "https://github.com/login/oauth/access_token" +_GITHUB_ENDPOINTS: Final = github_host_endpoints("github.com") -def _credential(auth_type="per_user_oauth"): - values = {} if auth_type is None else {"github_copilot_auth_type": auth_type} - return CredentialItem(credential_name="copilot-cred", credential_values=values, credential_info={}) +def _credential( + auth_type: str | None = "per_user_oauth", + github_host: str | None = None, +) -> CredentialItem: + values: Final = {} if auth_type is None else {"github_copilot_auth_type": auth_type} + return CredentialItem( + credential_name="copilot-cred", + credential_values={ + **values, + **({"github_copilot_host": github_host} if github_host is not None else {}), + }, + credential_info={}, + ) def _exchange_payload(token="copilot-token", expires_at=None, api_base="https://api.githubcopilot.com"): @@ -143,7 +157,61 @@ def test_unknown_named_credential_falls_back_to_kwargs(): ], ) def test_validated_copilot_api_base(raw, expected): - assert validated_copilot_api_base(raw) == expected + assert validated_copilot_api_base(raw, github_host_endpoints("github.com")) == expected + + +@pytest.mark.parametrize( + "raw", + [ + "https://copilot-api.evil.ghe.com", + "https://api.githubcopilot.com", + "http://copilot-api.octo.ghe.com", + "https://user@copilot-api.octo.ghe.com", + "https://copilot-api.octo.ghe.com:8443", + ], +) +def test_ghe_exchange_response_must_stay_on_its_tenant_host(raw: object) -> None: + endpoints: Final = github_host_endpoints("octo.ghe.com") + assert validated_copilot_api_base(raw, endpoints) == "https://copilot-api.octo.ghe.com" + + +def test_github_com_exchange_rejects_a_ghe_copilot_host() -> None: + endpoints: Final = github_host_endpoints("github.com") + assert validated_copilot_api_base("https://copilot-api.octo.ghe.com", endpoints) == "https://api.githubcopilot.com" + + +def test_ghe_exchange_uses_stored_host_not_request_kwargs(): + credential: Final = CredentialItem( + credential_name="copilot-cred", + credential_values={"github_copilot_auth_type": "per_user_oauth", "github_copilot_host": "octo.ghe.com"}, + credential_info={}, + ) + + def respond(request: httpx.Request) -> httpx.Response: + assert str(request.url) == "https://api.octo.ghe.com/copilot_internal/v2/token" + return httpx.Response(200, json=_exchange_payload(api_base="https://copilot-api.octo.ghe.com"), request=request) + + with patch.object(litellm, "credential_list", [credential]), github_http(respond) as requests: + kwargs: Final = _kwargs_with_connection(github_host="octo.ghe.com") + kwargs["github_copilot_host"] = "evil.ghe.com" + attach_github_copilot_user_session(kwargs) + + session: Final = github_copilot_user_session_from(kwargs) + assert session is not None and session.api_base == "https://copilot-api.octo.ghe.com" + assert len(requests) == 1 + + +def test_invalid_stored_host_fails_before_exchange(): + credential: Final = CredentialItem( + credential_name="copilot-cred", + credential_values={"github_copilot_auth_type": "per_user_oauth", "github_copilot_host": "https://octo.ghe.com"}, + credential_info={}, + ) + with patch.object(litellm, "credential_list", [credential]): + with github_http(lambda request: pytest.fail(f"unexpected request to {request.url}")) as requests: + with pytest.raises(BadRequestError): + attach_github_copilot_user_session(_kwargs_with_connection()) + assert not requests def test_session_repr_and_str_hide_the_token(caplog): @@ -159,49 +227,59 @@ def test_session_repr_and_str_hide_the_token(caplog): def test_exchange_returns_session_and_caches_per_user(): with github_http(_exchange_responder()) as requests: - s1 = exchange_github_token("user-a", "gh-token", "copilot-cred") + s1 = exchange_github_token("user-a", "gh-token", "copilot-cred", _GITHUB_ENDPOINTS) assert len(requests) == 1 assert requests[0].headers["Authorization"] == "token gh-token" - s2 = exchange_github_token("user-a", "gh-token", "copilot-cred") + s2 = exchange_github_token("user-a", "gh-token", "copilot-cred", _GITHUB_ENDPOINTS) assert len(requests) == 1 assert s2.token == s1.token == "copilot-token" # different user -> separate exchange - exchange_github_token("user-b", "gh-token", "copilot-cred") + exchange_github_token("user-b", "gh-token", "copilot-cred", _GITHUB_ENDPOINTS) assert len(requests) == 2 # different github token -> separate exchange - exchange_github_token("user-a", "gh-token-2", "copilot-cred") + exchange_github_token("user-a", "gh-token-2", "copilot-cred", _GITHUB_ENDPOINTS) assert len(requests) == 3 +def test_cached_session_is_not_reused_after_github_token_changes(): + with github_http(_exchange_responder()) as requests: + exchange_github_token("user-a", "gh-token-a", "copilot-cred", _GITHUB_ENDPOINTS) + exchange_github_token("user-a", "gh-token-b", "copilot-cred", _GITHUB_ENDPOINTS) + + assert [request.headers["Authorization"] for request in requests] == ["token gh-token-a", "token gh-token-b"] + + @pytest.mark.parametrize("status", [401, 403, 404]) def test_exchange_auth_failures_raise_caller_auth_error_and_evict(status): with github_http(_exchange_responder(status=status)): with pytest.raises(CallerCredentialAuthenticationError) as exc: - exchange_github_token("user-a", "gh-token", "copilot-cred") + exchange_github_token("user-a", "gh-token", "copilot-cred", _GITHUB_ENDPOINTS) assert "Reconnect GitHub Copilot for credential 'copilot-cred' in the LiteLLM UI (LLM Credentials)" in str( exc.value ) - assert _SESSION_CACHE.get_cache(_session_cache_key("user-a", "gh-token")) is None + assert ( + _SESSION_CACHE.get_cache(_session_cache_key("user-a", "copilot-cred", GITHUB_COPILOT_DEFAULT_HOST)) is None + ) def test_exchange_429_raises_caller_rate_limit(): with github_http(_exchange_responder(status=429)): with pytest.raises(CallerCredentialRateLimitError): - exchange_github_token("user-a", "gh-token", "copilot-cred") + exchange_github_token("user-a", "gh-token", "copilot-cred", _GITHUB_ENDPOINTS) def test_exchange_other_failure_raises_service_unavailable_without_body(): with github_http(_exchange_responder(status=500, payload={"secret": "body"})): with pytest.raises(ServiceUnavailableError) as exc: - exchange_github_token("user-a", "gh-token", "copilot-cred") + exchange_github_token("user-a", "gh-token", "copilot-cred", _GITHUB_ENDPOINTS) assert "body" not in str(exc.value) def test_exchange_expiry_margin_refetches_near_expiry(): with github_http(_exchange_responder(_exchange_payload(expires_at=int(time.time()) + 30))) as requests: - exchange_github_token("user-a", "gh-token", "copilot-cred") + exchange_github_token("user-a", "gh-token", "copilot-cred", _GITHUB_ENDPOINTS) # ttl under the 60s safety margin -> not cached, second call refetches - exchange_github_token("user-a", "gh-token", "copilot-cred") + exchange_github_token("user-a", "gh-token", "copilot-cred", _GITHUB_ENDPOINTS) assert len(requests) == 2 @@ -212,8 +290,8 @@ async def test_aexchange_single_flight_one_http_call(): with github_http(respond) as requests: s1, s2 = await asyncio.gather( - aexchange_github_token("user-a", "gh-token", "copilot-cred"), - aexchange_github_token("user-a", "gh-token", "copilot-cred"), + aexchange_github_token("user-a", "gh-token", "copilot-cred", _GITHUB_ENDPOINTS), + aexchange_github_token("user-a", "gh-token", "copilot-cred", _GITHUB_ENDPOINTS), ) assert len(requests) == 1 assert s1.token == s2.token == "copilot-token" @@ -223,16 +301,26 @@ async def test_aexchange_single_flight_one_http_call(): async def test_aexchange_401_raises_and_evicts(): with github_http(_exchange_responder(status=401)): with pytest.raises(CallerCredentialAuthenticationError): - await aexchange_github_token("user-a", "gh-token", "copilot-cred") - assert _SESSION_CACHE.get_cache(_session_cache_key("user-a", "gh-token")) is None + await aexchange_github_token("user-a", "gh-token", "copilot-cred", _GITHUB_ENDPOINTS) + assert ( + _SESSION_CACHE.get_cache(_session_cache_key("user-a", "copilot-cred", GITHUB_COPILOT_DEFAULT_HOST)) is None + ) -def _kwargs_with_connection(token="gho_user_token"): +def _kwargs_with_connection( + token: str = "gho_user_token", + github_host: str | None = "github.com", +) -> dict[str, object]: return { "litellm_credential_name": "copilot-cred", "secret_fields": { "user_provider_credentials_user_id": "user-a", - "user_provider_credentials": {"copilot-cred": token}, + "user_provider_credentials": { + "copilot-cred": { + "access_token": token, + **({"github_host": github_host} if github_host is not None else {}), + } + }, }, } @@ -261,6 +349,31 @@ def test_attach_per_user_without_connection_raises_connect_401(per_user_credenti assert "Connect GitHub Copilot for credential 'copilot-cred' in the LiteLLM UI (LLM Credentials)" in str(exc.value) +@pytest.mark.parametrize( + ("credential_host", "connection_host"), + [("github.com", "octo.ghe.com"), ("octo.ghe.com", "github.com")], +) +def test_attach_rejects_connection_from_a_different_github_host( + credential_host: str, + connection_host: str, +): + with patch.object(litellm, "credential_list", [_credential(github_host=credential_host)]): + kwargs: Final = _kwargs_with_connection(github_host=connection_host) + with github_http(lambda request: pytest.fail(f"unexpected token exchange at {request.url}")) as requests: + with pytest.raises(CallerCredentialAuthenticationError) as exc: + attach_github_copilot_user_session(kwargs) + assert "Connect GitHub Copilot for credential 'copilot-cred'" in str(exc.value) + assert not requests + + +def test_legacy_connection_without_host_uses_github_com(per_user_credential): + with github_http(_exchange_responder()) as requests: + kwargs: Final = _kwargs_with_connection(github_host=None) + attach_github_copilot_user_session(kwargs) + assert len(requests) == 1 + assert str(requests[0].url) == EXCHANGE_URL + + def test_attach_shared_mode_does_nothing_without_connection(): with patch.object(litellm, "credential_list", [_credential(auth_type=None)]): kwargs = {"litellm_credential_name": "copilot-cred"} @@ -270,9 +383,9 @@ def test_attach_shared_mode_does_nothing_without_connection(): def test_evict_drops_cached_session(): with github_http(_exchange_responder()) as requests: - exchange_github_token("user-a", "gh-token", "copilot-cred") - evict_copilot_user_session("user-a", "gh-token") - exchange_github_token("user-a", "gh-token", "copilot-cred") + exchange_github_token("user-a", "gh-token", "copilot-cred", _GITHUB_ENDPOINTS) + evict_copilot_user_session("user-a", "copilot-cred", _GITHUB_ENDPOINTS.host) + exchange_github_token("user-a", "gh-token", "copilot-cred", _GITHUB_ENDPOINTS) assert len(requests) == 2 @@ -293,7 +406,7 @@ async def test_astart_device_flow_shape(): ) with github_http(respond): - start = await astart_device_flow() + start = await astart_device_flow(_GITHUB_ENDPOINTS) assert (start.device_code, start.user_code, start.verification_uri, start.expires_in, start.interval) == ( "dc", "UC-123", @@ -319,7 +432,7 @@ async def test_apoll_device_flow_error_mapping(github_error, expected_status): return httpx.Response(200, json={"error": github_error}, request=request) with github_http(respond): - poll = await apoll_device_flow("dc") + poll = await apoll_device_flow("dc", _GITHUB_ENDPOINTS) assert poll.status == expected_status @@ -330,7 +443,7 @@ async def test_apoll_device_flow_connected(): return httpx.Response(200, json={"access_token": "gho_x"}, request=request) with github_http(respond): - poll = await apoll_device_flow("dc") + poll = await apoll_device_flow("dc", _GITHUB_ENDPOINTS) assert poll.status == "connected" and poll.access_token == "gho_x" @@ -363,7 +476,12 @@ def _chat_completion_response(): def _secret_fields(user_id: str, github_token: str): return { "user_provider_credentials_user_id": user_id, - "user_provider_credentials": {"copilot-cred": github_token}, + "user_provider_credentials": { + "copilot-cred": { + "access_token": github_token, + "github_host": GITHUB_COPILOT_DEFAULT_HOST, + } + }, } @@ -842,7 +960,9 @@ def test_sync_exchange_single_flight_one_http_call(): with github_http(slow_respond) as requests: threads = [ threading.Thread( - target=lambda: sessions.append(exchange_github_token("user-a", "gh-token", "copilot-cred")) + target=lambda: sessions.append( + exchange_github_token("user-a", "gh-token", "copilot-cred", _GITHUB_ENDPOINTS) + ) ) for _ in range(6) ] @@ -856,12 +976,34 @@ def test_sync_exchange_single_flight_one_http_call(): def test_two_users_same_github_token_do_not_share_session(): with github_http(_exchange_responder()): - s1 = exchange_github_token("user-a", "gh-same", "copilot-cred") - s2 = exchange_github_token("user-b", "gh-same", "copilot-cred") - assert _session_cache_key("user-a", "gh-same") != _session_cache_key("user-b", "gh-same") + s1: Final = exchange_github_token("user-a", "gh-same", "copilot-cred", _GITHUB_ENDPOINTS) + s2: Final = exchange_github_token("user-b", "gh-same", "copilot-cred", _GITHUB_ENDPOINTS) + user_a_key: Final = _session_cache_key("user-a", "copilot-cred", _GITHUB_ENDPOINTS.host) + user_b_key: Final = _session_cache_key("user-b", "copilot-cred", _GITHUB_ENDPOINTS.host) + other_credential_key: Final = _session_cache_key("user-a", "another-credential", _GITHUB_ENDPOINTS.host) + other_host_key: Final = _session_cache_key("user-a", "copilot-cred", "octo.ghe.com") + assert user_a_key != user_b_key + assert user_a_key != other_credential_key + assert user_a_key != other_host_key assert s1.token == s2.token == "copilot-token" +def test_same_user_and_token_do_not_share_sessions_across_hosts(): + from litellm.llms.github_copilot.github_host import github_host_endpoints + + ghe_endpoints: Final = github_host_endpoints("octo.ghe.com") + + def respond(request: httpx.Request) -> httpx.Response: + return httpx.Response(200, json=_exchange_payload(), request=request) + + with github_http(respond) as requests: + github_session: Final = exchange_github_token("user-a", "gh-same", "copilot-cred", _GITHUB_ENDPOINTS) + ghe_session: Final = exchange_github_token("user-a", "gh-same", "copilot-cred", ghe_endpoints) + assert len(requests) == 2 + assert github_session.api_base == "https://api.githubcopilot.com" + assert ghe_session.api_base == "https://copilot-api.octo.ghe.com" + + def test_router_constructs_with_per_user_credential_deployment(per_user_credential): from litellm.llms.github_copilot.authenticator import Authenticator @@ -928,9 +1070,9 @@ async def test_aexchange_cancelled_waiter_does_not_cancel_the_shared_exchange(pe with patch( # test-quality-ok: the gate holds the HTTP edge open so two waiters overlap "litellm.llms.custom_httpx.http_handler.get_async_httpx_client", return_value=_GatedClient() ): - first = asyncio.ensure_future(aexchange_github_token("user-a", "gh-shared", "copilot-cred")) + first = asyncio.ensure_future(aexchange_github_token("user-a", "gh-shared", "copilot-cred", _GITHUB_ENDPOINTS)) await asyncio.sleep(0) - second = asyncio.ensure_future(aexchange_github_token("user-a", "gh-shared", "copilot-cred")) + second = asyncio.ensure_future(aexchange_github_token("user-a", "gh-shared", "copilot-cred", _GITHUB_ENDPOINTS)) await asyncio.sleep(0) second.cancel() gate.set() @@ -940,6 +1082,33 @@ async def test_aexchange_cancelled_waiter_does_not_cancel_the_shared_exchange(pe await second +@pytest.mark.asyncio +async def test_aexchange_does_not_share_an_in_flight_session_after_token_changes(per_user_credential): + gate = asyncio.Event() + auth_headers: asyncio.Queue[str] = asyncio.Queue() + + class _GatedClient: + async def get(self, url, headers=None): + await auth_headers.put(headers["authorization"]) + await gate.wait() + token = "copilot-token-a" if headers["authorization"] == "token gh-a" else "copilot-token-b" + return httpx.Response( + 200, + json=_exchange_payload(token=token), + request=httpx.Request("GET", url), + ) + + with patch("litellm.llms.custom_httpx.http_handler.get_async_httpx_client", return_value=_GatedClient()): + first = asyncio.ensure_future(aexchange_github_token("user-a", "gh-a", "copilot-cred", _GITHUB_ENDPOINTS)) + assert await asyncio.wait_for(auth_headers.get(), timeout=1) == "token gh-a" + second = asyncio.ensure_future(aexchange_github_token("user-a", "gh-b", "copilot-cred", _GITHUB_ENDPOINTS)) + assert await asyncio.wait_for(auth_headers.get(), timeout=1) == "token gh-b" + gate.set() + sessions = await asyncio.gather(first, second) + + assert [session.token for session in sessions] == ["copilot-token-a", "copilot-token-b"] + + @pytest.mark.asyncio async def test_aexchange_failure_with_a_single_caller_emits_no_unretrieved_warning(per_user_credential): """The leader removes the failed future before anyone awaits it; the stored @@ -955,7 +1124,7 @@ async def test_aexchange_failure_with_a_single_caller_emits_no_unretrieved_warni github_http(_exchange_responder(status=401)), pytest.raises(CallerCredentialAuthenticationError), ): - await aexchange_github_token("user-a", "gh-fail", "copilot-cred") + await aexchange_github_token("user-a", "gh-fail", "copilot-cred", _GITHUB_ENDPOINTS) _IN_FLIGHT_KEYS = list(pua._IN_FLIGHT) import gc diff --git a/tests/unit/llms/nvidia_riva/audio_transcription/test_handler.py b/tests/unit/llms/nvidia_riva/audio_transcription/test_handler.py index 7ecc0b47d9f..dbb5cde6060 100644 --- a/tests/unit/llms/nvidia_riva/audio_transcription/test_handler.py +++ b/tests/unit/llms/nvidia_riva/audio_transcription/test_handler.py @@ -12,11 +12,12 @@ import io from types import SimpleNamespace from unittest.mock import MagicMock +import httpx import numpy as np import pytest import soundfile as sf - +import litellm from litellm.llms.nvidia_riva.audio_transcription import handler as handler_mod from litellm.llms.nvidia_riva.audio_transcription.handler import ( NvidiaRivaAudioTranscription, @@ -93,6 +94,24 @@ def mock_riva(monkeypatch): LINEAR_PCM = "LINEAR_PCM" streaming_responses_holder = {"value": []} + offline_response_holder = {"value": None} + offline_error_holder = {"value": None} + offline_future_holder = {"value": None} + streaming_calls = [] + offline_calls = {} + + class FakeRecognizeFuture: + def result(self, timeout: float | None = None) -> object: + offline_calls["timeout"] = timeout + if offline_error_holder["value"] is not None: + raise offline_error_holder["value"] + return offline_response_holder["value"] + + def done(self) -> bool: + return True + + def cancel(self) -> bool: + return False class FakeASRService: def __init__(self, auth): @@ -100,9 +119,15 @@ def mock_riva(monkeypatch): def streaming_response_generator(self, audio_chunks, streaming_config): # Drain audio_chunks generator so we exercise the chunking path. - list(audio_chunks) + streaming_calls.append(list(audio_chunks)) yield from streaming_responses_holder["value"] + def offline_recognize(self, audio_bytes: bytes, config: object, future: bool = False) -> object: + offline_calls["audio_bytes"] = audio_bytes + offline_calls["config"] = config + pending = offline_future_holder["value"] or FakeRecognizeFuture() + return pending if future else pending.result() + fake_riva_client = SimpleNamespace( Auth=FakeAuth, ASRService=FakeASRService, @@ -120,6 +145,11 @@ def mock_riva(monkeypatch): return SimpleNamespace( auth_calls=auth_calls, responses=streaming_responses_holder, + offline_response=offline_response_holder, + offline_error=offline_error_holder, + offline_future=offline_future_holder, + streaming_calls=streaming_calls, + offline_calls=offline_calls, client=fake_riva_client, ) @@ -203,6 +233,339 @@ def test_sync_path_aggregates_only_final_results(mock_riva, logging_obj): ) +def test_riva_offline_uses_unary_recognize_and_keeps_results_without_is_final( + mock_riva: SimpleNamespace, logging_obj: MagicMock +) -> None: + """ + Offline-only NIMs (Parakeet TDT, Whisper) reject StreamingRecognize. With + ``riva_offline`` the handler must call ``offline_recognize`` with the whole + resampled buffer and a bare ``RecognitionConfig``, and must keep every + result even though ``RecognizeResponse`` results carry no ``is_final``. + """ + mock_riva.offline_response["value"] = _fake_response( + results=[ + SimpleNamespace(alternatives=[_fake_alternative("Hello,", words=[_fake_word("Hello,", 0, 320)])]), + SimpleNamespace(alternatives=[_fake_alternative(" world.", words=[_fake_word("world.", 480, 870)])]), + ] + ) + + impl = NvidiaRivaAudioTranscription() + response: TranscriptionResponse = impl.audio_transcriptions( + model="nvidia/parakeet-0.6b-tdt", + audio_file=_make_wav_bytes(), + optional_params={ + "language_code": "multi", + "riva_offline": True, + "enable_word_time_offsets": True, + "response_format": "verbose_json", + "timestamp_granularities": ["word"], + }, + litellm_params={}, + model_response=TranscriptionResponse(), + timeout=60, + logging_obj=logging_obj, + api_key=None, + api_base="localhost:50051", + ) + + assert response.text == "Hello, world." + assert response["words"][1]["end"] == pytest.approx(0.87) + assert response._hidden_params["audio_transcription_duration"] == pytest.approx(1.0, abs=0.05) + assert mock_riva.streaming_calls == [] + assert len(mock_riva.offline_calls["audio_bytes"]) == pytest.approx(32000, abs=1600) + assert mock_riva.offline_calls["config"]._kwargs["language_code"] == "multi" + assert logging_obj.pre_call.call_args.kwargs["additional_args"]["complete_input_dict"]["riva_offline"] is True + + +def test_default_mode_streams_and_never_calls_offline_recognize( + mock_riva: SimpleNamespace, logging_obj: MagicMock +) -> None: + mock_riva.responses["value"] = [ + _fake_response(results=[_fake_result(is_final=True, alternatives=[_fake_alternative("streamed")])]) + ] + + impl = NvidiaRivaAudioTranscription() + response = impl.audio_transcriptions( + model="m", + audio_file=_make_wav_bytes(), + optional_params={"language_code": "en-US"}, + litellm_params={}, + model_response=TranscriptionResponse(), + timeout=60, + logging_obj=logging_obj, + api_key=None, + api_base="localhost:50051", + ) + assert response.text == "streamed" + assert mock_riva.offline_calls == {} + assert len(mock_riva.streaming_calls) == 1 + assert logging_obj.pre_call.call_args.kwargs["additional_args"]["complete_input_dict"]["riva_offline"] is False + + + +@pytest.mark.parametrize(("riva_offline", "expect_offline"), [("false", False), ("False", False), ("true", True)]) +def test_riva_offline_string_from_multipart_form_is_parsed( + mock_riva: SimpleNamespace, logging_obj: MagicMock, riva_offline: str, expect_offline: bool +) -> None: + mock_riva.responses["value"] = [ + _fake_response(results=[_fake_result(is_final=True, alternatives=[_fake_alternative("streamed")])]) + ] + mock_riva.offline_response["value"] = _fake_response( + results=[SimpleNamespace(alternatives=[_fake_alternative("offline")])] + ) + + response = NvidiaRivaAudioTranscription().audio_transcriptions( + model="m", + audio_file=_make_wav_bytes(), + optional_params={"language_code": "en-US", "riva_offline": riva_offline}, + litellm_params={}, + model_response=TranscriptionResponse(), + timeout=60, + logging_obj=logging_obj, + api_key=None, + api_base="localhost:50051", + ) + + assert response.text == ("offline" if expect_offline else "streamed") + assert (mock_riva.offline_calls != {}) is expect_offline + + +@pytest.mark.parametrize("riva_offline", ["yes", "", 1]) +def test_riva_offline_malformed_value_is_rejected_before_any_rpc( + mock_riva: SimpleNamespace, logging_obj: MagicMock, riva_offline: object +) -> None: + with pytest.raises(NvidiaRivaException) as excinfo: + NvidiaRivaAudioTranscription().audio_transcriptions( + model="m", + audio_file=_make_wav_bytes(), + optional_params={"language_code": "en-US", "riva_offline": riva_offline}, + litellm_params={}, + model_response=TranscriptionResponse(), + timeout=60, + logging_obj=logging_obj, + api_key=None, + api_base="localhost:50051", + ) + + assert excinfo.value.status_code == 400 + assert "riva_offline" in excinfo.value.message + assert mock_riva.offline_calls == {} + assert mock_riva.streaming_calls == [] + + +def test_riva_offline_malformed_value_is_dropped_under_drop_params( + mock_riva: SimpleNamespace, logging_obj: MagicMock +) -> None: + mock_riva.responses["value"] = [ + _fake_response(results=[_fake_result(is_final=True, alternatives=[_fake_alternative("streamed")])]) + ] + + response = NvidiaRivaAudioTranscription().audio_transcriptions( + model="m", + audio_file=_make_wav_bytes(), + optional_params={"language_code": "en-US", "riva_offline": "yes"}, + litellm_params={"drop_params": True}, + model_response=TranscriptionResponse(), + timeout=60, + logging_obj=logging_obj, + api_key=None, + api_base="localhost:50051", + ) + + assert response.text == "streamed" + assert mock_riva.offline_calls == {} + + +def test_deployment_riva_offline_reaches_the_handler_through_transcription(mock_riva: SimpleNamespace) -> None: + mock_riva.offline_response["value"] = _fake_response( + results=[SimpleNamespace(alternatives=[_fake_alternative("offline")])] + ) + + response = litellm.transcription( + model="nvidia_riva/nvidia/parakeet-0.6b-tdt", + file=("clip.wav", _make_wav_bytes(), "audio/wav"), + api_base="localhost:50051", + riva_offline=True, + ) + + assert response.text == "offline" + assert mock_riva.streaming_calls == [] + assert mock_riva.offline_calls != {} + + +@pytest.mark.parametrize( + ("timeout", "waited_for"), + [("7.5", 7.5), (httpx.Timeout(30.0, read=7.5), 7.5), (httpx.Timeout(5.0, read=None), 600.0), (None, None)], +) +def test_offline_recognition_waits_the_timeout_in_seconds_whatever_its_form( + mock_riva: SimpleNamespace, timeout: str | httpx.Timeout | None, waited_for: float | None +) -> None: + mock_riva.offline_response["value"] = _fake_response( + results=[SimpleNamespace(alternatives=[_fake_alternative("offline")])] + ) + + response = litellm.transcription( + model="nvidia_riva/nvidia/parakeet-0.6b-tdt", + file=("clip.wav", _make_wav_bytes(), "audio/wav"), + api_base="localhost:50051", + riva_offline=True, + timeout=timeout, + ) + + assert response.text == "offline" + assert mock_riva.offline_calls["timeout"] == waited_for + + +@pytest.mark.parametrize("timeout", ["abc", "30s"]) +def test_malformed_timeout_on_offline_call_is_a_400_before_any_rpc( + mock_riva: SimpleNamespace, timeout: str +) -> None: + with pytest.raises(NvidiaRivaException) as excinfo: + litellm.transcription( + model="nvidia_riva/nvidia/parakeet-0.6b-tdt", + file=("clip.wav", _make_wav_bytes(), "audio/wav"), + api_base="localhost:50051", + riva_offline=True, + timeout=timeout, + ) + + assert excinfo.value.status_code == 400 + assert "timeout" in excinfo.value.message + assert "audio_bytes" not in mock_riva.offline_calls + + +def test_malformed_timeout_on_offline_call_waits_the_default_under_drop_params( + mock_riva: SimpleNamespace, +) -> None: + mock_riva.offline_response["value"] = _fake_response( + results=[SimpleNamespace(alternatives=[_fake_alternative("offline")])] + ) + + response = litellm.transcription( + model="nvidia_riva/nvidia/parakeet-0.6b-tdt", + file=("clip.wav", _make_wav_bytes(), "audio/wav"), + api_base="localhost:50051", + riva_offline=True, + timeout="abc", + drop_params=True, + ) + + assert response.text == "offline" + assert mock_riva.offline_calls["timeout"] == 600.0 + + +def test_malformed_timeout_still_streams_when_the_client_takes_no_timeout(mock_riva: SimpleNamespace) -> None: + mock_riva.responses["value"] = [ + _fake_response(results=[_fake_result(is_final=True, alternatives=[_fake_alternative("streamed")])]) + ] + + response = litellm.transcription( + model="nvidia_riva/nvidia/parakeet-ctc-1.1b", + file=("clip.wav", _make_wav_bytes(), "audio/wav"), + api_base="localhost:50051", + timeout="abc", + ) + + assert response.text == "streamed" + assert len(mock_riva.streaming_calls) == 1 + + +def test_oversized_offline_audio_is_a_non_retryable_413(mock_riva: SimpleNamespace, logging_obj: MagicMock) -> None: + class FakeGrpcError(Exception): + def code(self) -> SimpleNamespace: + return SimpleNamespace(name="RESOURCE_EXHAUSTED") + + def details(self) -> str: + return "SERVER: Received message larger than max (4348825 vs. 4194304)" + + mock_riva.offline_error["value"] = FakeGrpcError("rpc fail") + + with pytest.raises(NvidiaRivaException) as excinfo: + NvidiaRivaAudioTranscription().audio_transcriptions( + model="m", + audio_file=_make_wav_bytes(), + optional_params={"language_code": "en-US", "riva_offline": True}, + litellm_params={}, + model_response=TranscriptionResponse(), + timeout=60, + logging_obj=logging_obj, + api_key=None, + api_base="localhost:50051", + ) + + assert excinfo.value.status_code == 413 + assert litellm.utils.should_retry(excinfo.value.status_code) is False + + +def test_stalled_offline_recognition_is_cancelled_and_times_out_as_408( + mock_riva: SimpleNamespace, logging_obj: MagicMock +) -> None: + class FutureTimeoutError(Exception): + pass + + class StalledRecognizeFuture: + def __init__(self) -> None: + self.waited_for: float | None = None + self.cancelled = False + + def result(self, timeout: float | None = None) -> object: + self.waited_for = timeout + raise FutureTimeoutError() + + def done(self) -> bool: + return self.cancelled + + def cancel(self) -> bool: + self.cancelled = True + return True + + stalled = StalledRecognizeFuture() + mock_riva.offline_future["value"] = stalled + + with pytest.raises(NvidiaRivaException) as excinfo: + NvidiaRivaAudioTranscription().audio_transcriptions( + model="m", + audio_file=_make_wav_bytes(), + optional_params={"language_code": "en-US", "riva_offline": True}, + litellm_params={}, + model_response=TranscriptionResponse(), + timeout=7.5, + logging_obj=logging_obj, + api_key=None, + api_base="localhost:50051", + ) + + assert excinfo.value.status_code == 408 + assert stalled.waited_for == 7.5 + assert stalled.cancelled is True + +def test_riva_offline_grpc_error_is_wrapped(mock_riva: SimpleNamespace, logging_obj: MagicMock) -> None: + class FakeGrpcError(Exception): + def code(self) -> SimpleNamespace: + return SimpleNamespace(name="INVALID_ARGUMENT") + + def details(self) -> str: + return "Unavailable model requested" + + mock_riva.offline_error["value"] = FakeGrpcError("rpc fail") + + impl = NvidiaRivaAudioTranscription() + with pytest.raises(NvidiaRivaException) as excinfo: + impl.audio_transcriptions( + model="m", + audio_file=_make_wav_bytes(), + optional_params={"language_code": "multi", "riva_offline": True}, + litellm_params={}, + model_response=TranscriptionResponse(), + timeout=60, + logging_obj=logging_obj, + api_key=None, + api_base="localhost:50051", + ) + assert excinfo.value.status_code == 400 + assert "INVALID_ARGUMENT" in excinfo.value.message + + def test_auth_nvcf_defaults_use_ssl_and_attaches_function_id(mock_riva, logging_obj): mock_riva.responses["value"] = [ _fake_response( @@ -343,9 +706,10 @@ def test_async_path_uses_to_thread(mock_riva, logging_obj): ) +@pytest.mark.parametrize("timeout", [12.5, "12.5", httpx.Timeout(60.0, read=12.5)]) def test_timeout_is_forwarded_to_streaming_generator_when_supported( - mock_riva, logging_obj -): + mock_riva: SimpleNamespace, logging_obj: MagicMock, timeout: float | str | httpx.Timeout +) -> None: """ Without a deadline the gRPC stream can block forever on a stalled Riva server. The handler must forward the call-level ``timeout`` to @@ -374,7 +738,7 @@ def test_timeout_is_forwarded_to_streaming_generator_when_supported( optional_params={"language_code": "en-US"}, litellm_params={}, model_response=TranscriptionResponse(), - timeout=12.5, + timeout=timeout, logging_obj=logging_obj, api_key=None, api_base="localhost:50051", diff --git a/tests/unit/llms/openai/responses/count_tokens/test_token_counter.py b/tests/unit/llms/openai/responses/count_tokens/test_token_counter.py index 7495d98b42a..17c1b35e211 100644 --- a/tests/unit/llms/openai/responses/count_tokens/test_token_counter.py +++ b/tests/unit/llms/openai/responses/count_tokens/test_token_counter.py @@ -1,3 +1,4 @@ +import copy import json import operator from collections.abc import Mapping @@ -9,6 +10,7 @@ import respx from pydantic import JsonValue, ValidationError import litellm +from litellm.litellm_core_utils.tool_fields import DropPolicy from litellm.llms.openai.responses.count_tokens.token_counter import OpenAITokenCounter from litellm.responses.utils import ResponsesAPIRequestUtils from litellm.types.utils import TokenCountMessagesFormat, TokenCountResponse @@ -521,3 +523,122 @@ async def test_count_sends_the_global_key_only_to_the_global_api_base(monkeypatc assert result is not None assert result.total_tokens == 4 assert route.calls.last.request.headers["authorization"] == "Bearer sk-private-gateway" + + +_KEEP_ALL: Final = DropPolicy(drop_params=False, additional_drop_params=frozenset()) +_ANSWER_FORMAT: Final[dict[str, object]] = { + "format": {"type": "json_schema", "name": "answer", "schema": {"type": "object", "properties": {}}} +} +_STORED_PROMPT: Final[dict[str, object]] = {"id": "pmpt_abc", "variables": {"city": "Paris"}} +_CALLER_BODY: Final[dict[str, object]] = { + "model": "my-gpt", + "input": "hi", + "text": _ANSWER_FORMAT, + "prompt": _STORED_PROMPT, + "max_output_tokens": "lots", + "metadata": {"run": "nightly"}, + "drop_params": False, + "additional_drop_params": [], + "timeout": 30, + "extra_headers": {"x-trace": "1"}, + "disable_fallbacks": True, + "spend_logs_metadata": {"team": "search"}, + "mock_testing_fallbacks": True, +} + + +async def _native_count( + monkeypatch: pytest.MonkeyPatch, request: Mapping[str, object], policy: DropPolicy, response: httpx.Response +) -> tuple[TokenCountResponse | None, object]: + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + with respx.mock: + route: Final = respx.post(COUNT_URL).mock(return_value=response) + result: Final = await OpenAITokenCounter().count_responses_request( + model_to_use="gpt-4o", + request=request, + policy=policy, + deployment={"litellm_params": {"api_key": "sk-test"}}, + request_model="my-gpt", + ) + return result, json.loads(route.calls.last.request.content) + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("policy", "expected_sent"), + [ + pytest.param( + _KEEP_ALL, + { + "model": "gpt-4o", + "input": "hi", + "text": _ANSWER_FORMAT, + "prompt": _STORED_PROMPT, + "max_output_tokens": "lots", + }, + id="keeps-responses-fields", + ), + pytest.param( + DropPolicy(drop_params=True, additional_drop_params=frozenset()), + {"model": "gpt-4o", "input": "hi", "text": _ANSWER_FORMAT, "prompt": _STORED_PROMPT}, + id="drop-params-keeps-count-fields", + ), + pytest.param( + DropPolicy(drop_params=False, additional_drop_params=frozenset({"text"})), + {"model": "gpt-4o", "input": "hi", "prompt": _STORED_PROMPT, "max_output_tokens": "lots"}, + id="additional-drop-params", + ), + ], +) +async def test_native_count_sends_the_callers_body_without_litellm_fields( + monkeypatch: pytest.MonkeyPatch, policy: DropPolicy, expected_sent: dict[str, object] +) -> None: + result, sent = await _native_count( + monkeypatch, _CALLER_BODY, policy, httpx.Response(200, json={"input_tokens": 76}) + ) + + assert sent == expected_sent + assert result is not None + assert (result.total_tokens, result.model_used, result.error) == (76, "gpt-4o", False) + + +@pytest.mark.asyncio +async def test_native_count_restores_provider_ids_on_a_copy_of_the_callers_body( + monkeypatch: pytest.MonkeyPatch, +) -> None: + wrapped: Final = ResponsesAPIRequestUtils.wrap_encrypted_content_with_model_id("gAAAAoriginal", "deployment-1") + request: Final[dict[str, object]] = { + "model": "my-gpt", + "previous_response_id": ResponsesAPIRequestUtils._build_responses_api_response_id( + "openai", "deployment-1", "resp_original" + ), + "input": [ + {"type": "reasoning", "summary": [], "encrypted_content": wrapped}, + {"role": "user", "content": "again"}, + ], + } + before: Final = copy.deepcopy(request) + + _, sent = await _native_count(monkeypatch, request, _KEEP_ALL, httpx.Response(200, json={"input_tokens": 1})) + + assert sent == { + "model": "gpt-4o", + "previous_response_id": "resp_original", + "input": [ + {"type": "reasoning", "summary": [], "encrypted_content": "gAAAAoriginal"}, + {"role": "user", "content": "again"}, + ], + } + assert request == before + + +@pytest.mark.asyncio +async def test_native_count_answers_openais_rejection_with_its_status_and_text( + monkeypatch: pytest.MonkeyPatch, +) -> None: + rejection: Final = json.dumps({"error": {"message": "Unknown parameter: 'max_output_tokens'."}}) + + result, _ = await _native_count(monkeypatch, _CALLER_BODY, _KEEP_ALL, httpx.Response(400, text=rejection)) + + assert result is not None + assert (result.error, result.status_code, result.error_message) == (True, 400, rejection) diff --git a/tests/unit/llms/opencode/harness/test_transformation.py b/tests/unit/llms/opencode/harness/test_transformation.py index 2caf1ef80b8..c008bd28972 100644 --- a/tests/unit/llms/opencode/harness/test_transformation.py +++ b/tests/unit/llms/opencode/harness/test_transformation.py @@ -1,7 +1,9 @@ import asyncio import json +from collections.abc import Sequence from dataclasses import dataclass, field from pathlib import Path +from typing import Final import pytest from pydantic import BaseModel @@ -12,6 +14,7 @@ from litellm.harness.errors import ( HarnessError, HarnessInstallFailed, OptionsMismatch, + SandboxError, ) from litellm.harness.handlers.cli_handler import PERSIST_DIR_SCRIPT, CLIHarnessHandler from litellm.harness.options import CodexOptions, OpenCodeOptions @@ -98,6 +101,12 @@ class FakeProcess: self.killed = True +async def stall_until_timeout(cmd: Sequence[str], timeout: float | None) -> CompletedRun: + if timeout is None: + await asyncio.Event().wait() + raise SandboxError(f"command timed out after {timeout}s: {cmd[0]}") + + @dataclass class FakeSandbox: workdir: str = "/work" @@ -106,7 +115,11 @@ class FakeSandbox: outputs: list = field(default_factory=list) files: dict = field(default_factory=dict) execs: list = field(default_factory=list) - runs: list = field(default_factory=list) + stall_runs: bool = False + failing_subcommand: str | None = None + run_stdout: str = "" + runs: list[Sequence[str]] = field(default_factory=list) + run_envs: list[dict[str, str]] = field(default_factory=list) tempdirs: int = 0 async def exec(self, cmd, *, env=None, cwd=None): @@ -115,9 +128,12 @@ class FakeSandbox: async def run(self, cmd, *, env=None, cwd=None, timeout=None): self.runs.append(cmd) - if self.persist_ok: - return CompletedRun("", "", 0) - return CompletedRun("", "read-only fs", 1) + self.run_envs.append(dict(env or {})) + if self.stall_runs: + return await stall_until_timeout(cmd, timeout) + if not self.persist_ok or self.failing_subcommand in cmd: + return CompletedRun("", "read-only fs", 1) + return CompletedRun(self.run_stdout, "", 0) async def read(self, path): return self.files[path] @@ -594,13 +610,185 @@ async def test_prompt_is_sent_on_stdin_not_argv(): assert "secret prompt text" not in sandbox.execs[0]["cmd"] -async def test_resume_sets_session(): +SAVED: Final = "ses_ea6d348fdffe9pu36Y2YN6YobB" +SAVED_USER_MSG: Final = "msg_1592cb71a001307YHyO7ReafRb" +SAVED_REPLY_MSG: Final = "msg_1592cb7f4001KgUDK3Sj79XDT4" +SAVED_PARTS: Final = ("prt_1592cb71c0013NJaqSsv4dNiSR", "prt_1592cbe0f001oKdE9pRy38AduM") +COPY_PATH: Final = "/tmp/oc-1/resume-session.json" + + +def exported_session(directory: str) -> str: + user_part: Final = {"id": SAVED_PARTS[0], "sessionID": SAVED, "messageID": SAVED_USER_MSG, "type": "text"} + reply_part: Final = {"id": SAVED_PARTS[1], "sessionID": SAVED, "messageID": SAVED_REPLY_MSG, "type": "text"} + user: Final = {"id": SAVED_USER_MSG, "sessionID": SAVED, "role": "user"} + reply: Final = {"id": SAVED_REPLY_MSG, "sessionID": SAVED, "parentID": SAVED_USER_MSG, "role": "assistant"} + return json.dumps( + { + "info": {"id": SAVED, "directory": directory, "title": "litellm-harness"}, + "messages": [ + {"info": user, "parts": [{**user_part, "text": "Remember 4817"}]}, + {"info": reply, "parts": [{**reply_part, "text": "OK"}]}, + ], + } + ) + + +async def resumed(saved_in: str) -> tuple[CLIHarnessHandler, SessionContext, FakeSandbox]: handler, ctx, sandbox = await started() - await handler.resume(ctx, "ses_prev") + sandbox.run_stdout = exported_session(saved_in) + await handler.resume(ctx, SAVED) sandbox.outputs.append(fixture_proc("turn2_session_skill.jsonl")) await collect(handler, ctx, "hi") - cmd = sandbox.execs[0]["cmd"] - assert cmd[cmd.index("--session") + 1] == "ses_prev" + return handler, ctx, sandbox + + +def resumed_session_arg(sandbox: FakeSandbox) -> str: + cmd: Final = sandbox.execs[0]["cmd"] + return cmd[cmd.index("--session") + 1] + + +async def test_resume_elsewhere_continues_a_copy_filed_under_the_sandbox() -> None: + _, _, sandbox = await resumed("/other") + + copy: Final = json.loads(sandbox.files[COPY_PATH]) + copy_id: Final = resumed_session_arg(sandbox) + assert copy["info"]["id"] == copy_id != SAVED + assert copy["info"]["directory"] == sandbox.workdir + assert tuple(sandbox.runs[-1]) == ("opencode", "--pure", "import", COPY_PATH) + assert sandbox.run_envs[-1]["XDG_DATA_HOME"] == "/tmp/oc-1/xdg/data" + assert sandbox.run_envs[-2]["XDG_DATA_HOME"] == "/tmp/oc-1/xdg/data" + + +async def test_resume_copy_gets_fresh_ids_that_keep_their_links_and_order() -> None: + _, _, sandbox = await resumed("/other") + + raw_copy: Final = sandbox.files[COPY_PATH].decode() + user, reply = json.loads(raw_copy)["messages"] + copy_id: Final = resumed_session_arg(sandbox) + assert all(old not in raw_copy for old in (SAVED, SAVED_USER_MSG, SAVED_REPLY_MSG, *SAVED_PARTS)) + assert {user["info"]["sessionID"], reply["info"]["sessionID"]} == {copy_id} + assert reply["info"]["parentID"] == user["info"]["id"] + assert user["parts"][0]["messageID"] == user["info"]["id"] + assert reply["parts"][0]["messageID"] == reply["info"]["id"] + assert {user["parts"][0]["sessionID"], reply["parts"][0]["sessionID"]} == {copy_id} + assert (user["parts"][0]["text"], reply["parts"][0]["text"]) == ("Remember 4817", "OK") + + +def test_resume_copy_keeps_the_message_order() -> None: + message_ids: Final = tuple(f"msg_1592cb71a{n:03x}307YHyO7ReafRb" for n in range(10)) + messages: Final = [{"info": {"id": message_id}, "parts": []} for message_id in message_ids] + exported: Final = json.dumps({"info": {"id": SAVED, "directory": "/other"}, "messages": messages}) + + copy: Final = CONFIG.transform_resume_copy(exported, PRIVATE, "/work") + + assert copy is not None + copied_ids: Final = [message["info"]["id"] for message in json.loads(copy.data)["messages"]] + assert sorted(copied_ids) == copied_ids + + +def test_resume_copy_keeps_saved_text_that_reads_like_an_id() -> None: + tool_part: Final = { + "id": SAVED_PARTS[1], + "sessionID": SAVED, + "messageID": SAVED_USER_MSG, + "type": "tool", + "state": {"input": {"command": SAVED_REPLY_MSG}, "output": SAVED_USER_MSG}, + } + text_part: Final = {"id": SAVED_PARTS[0], "sessionID": SAVED, "messageID": SAVED_USER_MSG, "type": "text", "text": SAVED} + message: Final = {"info": {"id": SAVED_USER_MSG, "sessionID": SAVED}, "parts": [text_part, tool_part]} + exported: Final = json.dumps({"info": {"id": SAVED, "directory": "/other"}, "messages": [message]}) + + copy: Final = CONFIG.transform_resume_copy(exported, PRIVATE, "/work") + + assert copy is not None + text, tool = json.loads(copy.data)["messages"][0]["parts"] + assert text["text"] == SAVED != text["sessionID"] == copy.session_id + assert (tool["state"]["input"]["command"], tool["state"]["output"]) == (SAVED_REPLY_MSG, SAVED_USER_MSG) + assert tool["messageID"] != SAVED_USER_MSG + + +async def test_later_turns_after_a_resume_do_not_export_again() -> None: + handler, ctx, sandbox = await resumed("/other") + + sandbox.outputs.append(fixture_proc("turn2_session_skill.jsonl")) + await collect(handler, ctx, "again") + + assert [run[2] for run in sandbox.runs if run[0] == "opencode"] == ["export", "import"] + + +async def test_each_resume_elsewhere_makes_its_own_copy() -> None: + _, _, first = await resumed("/other") + _, _, second = await resumed("/other") + + assert resumed_session_arg(first) != resumed_session_arg(second) + + +async def test_resume_in_the_folder_it_was_saved_in_continues_the_original() -> None: + _, _, sandbox = await resumed("/work") + + assert resumed_session_arg(sandbox) == SAVED + assert COPY_PATH not in sandbox.files + assert all("import" not in run for run in sandbox.runs) + + +@pytest.mark.parametrize("failure", ["export_exits_1", "import_exits_1", "export_stalls", "export_unreadable"]) +async def test_resume_that_cannot_be_prepared_fails_the_turn_without_running_opencode( + failure: str, +) -> None: + handler, ctx, sandbox = await started() + sandbox.run_stdout = "Error: not a session" if failure == "export_unreadable" else exported_session("/other") + sandbox.failing_subcommand = failure.split("_")[0] if failure.endswith("exits_1") else None + sandbox.stall_runs = failure == "export_stalls" + + await asyncio.wait_for(handler.resume(ctx, SAVED), 5) + with pytest.raises(HarnessTurnError, match=SAVED): + await collect(handler, ctx, "hi") + assert sandbox.execs == [] + + +async def test_resume_runs_nothing_until_the_first_turn() -> None: + handler, ctx, sandbox = await started() + runs_before_resume: Final = len(sandbox.runs) + + await handler.resume(ctx, SAVED) + + assert len(sandbox.runs) == runs_before_resume + assert COPY_PATH not in sandbox.files + + +async def test_restart_after_a_failed_resume_tries_the_resume_again() -> None: + handler, ctx, sandbox = await started() + sandbox.run_stdout = exported_session("/other") + sandbox.failing_subcommand = "export" + await handler.resume(ctx, SAVED) + with pytest.raises(HarnessTurnError, match=SAVED): + await collect(handler, ctx, "hi") + + sandbox.failing_subcommand = None + await handler.start(ctx) + await handler.resume(ctx, SAVED) + sandbox.outputs.append(fixture_proc("turn2_session_skill.jsonl")) + await collect(handler, ctx, "again") + + assert resumed_session_arg(sandbox) == json.loads(sandbox.files["/tmp/oc-2/resume-session.json"])["info"]["id"] + + +async def test_restart_resumes_its_own_session_without_exporting_it() -> None: + handler, ctx, sandbox = await started() + sandbox.outputs.append(fixture_proc("turn1_write_read.jsonl")) + await collect(handler, ctx, "first") + native_id: Final = handler.native_session_id() + assert native_id is not None + runs_before_restart: Final = len(sandbox.runs) + + await handler.start(ctx) + await handler.resume(ctx, native_id) + sandbox.outputs.append(fixture_proc("turn2_session_skill.jsonl")) + await collect(handler, ctx, "again") + + assert all("export" not in run for run in sandbox.runs[runs_before_restart:]) + cmd: Final = sandbox.execs[1]["cmd"] + assert cmd[cmd.index("--session") + 1] == native_id async def test_read_only_and_disable_tools_config(): diff --git a/tests/unit/llms/pi/__init__.py b/tests/unit/llms/pi/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/unit/llms/pi/harness/__init__.py b/tests/unit/llms/pi/harness/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/unit/llms/pi/harness/fixtures/__init__.py b/tests/unit/llms/pi/harness/fixtures/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/unit/llms/pi/harness/fixtures/api_error.jsonl b/tests/unit/llms/pi/harness/fixtures/api_error.jsonl new file mode 100644 index 00000000000..e8720dd9ca3 --- /dev/null +++ b/tests/unit/llms/pi/harness/fixtures/api_error.jsonl @@ -0,0 +1,12 @@ +{"type":"session","version":3,"id":"01a11cb0-c576-7785-9c03-73fd7035291c","timestamp":"2026-10-08T18:05:09.367Z","cwd":"/work"} +{"type":"agent_start"} +{"type":"turn_start"} +{"type":"message_start","message":{"role":"system","content":"","sections":{"preamble":"You are an expert coding assistant operating inside pi, a coding agent harness. You help users by reading files, executing commands, editing code, and writing new files.","tools":"\n- read: Read file contents\n- bash: Execute bash commands (ls, grep, find, etc.)\n- edit: Make precise file edits with exact text replacement, including multiple disjoint edits in one call\n- write: Create or overwrite files\n- grep: Search file contents for patterns (respects .gitignore)\n- find: Find files by glob pattern (respects .gitignore)\n- ls: List directory contents\n\nIn addition to the tools above, you may have access to other custom tools depending on the project.\n","rules":"\n- Use read to examine files instead of cat or sed.\n- You can inspect PI_* environment variables for current model and session details.\n- Use edit for precise changes (edits[].oldText must match exactly)\n- When changing multiple separate locations in one file, use one edit call with multiple entries in edits[] instead of multiple edit calls\n- Each edits[].oldText is matched against the original file, not after earlier edits are applied. Do not emit overlapping or nested edits. Merge nearby changes into one edit.\n- Keep edits[].oldText as small as possible while still being unique in the file. Do not pad with large unchanged regions.\n- Use write only for new files or complete rewrites.\n- Be concise in your responses\n- Show file paths clearly when working with files\n","docs":"\nPi documentation (read only when the user asks about pi itself, its SDK, extensions, themes, skills, or TUI):\n- Main documentation: /usr/lib/node_modules/@earendil-works/pi-coding-agent/README.md\n- Additional docs: /usr/lib/node_modules/@earendil-works/pi-coding-agent/docs\n- Examples: /usr/lib/node_modules/@earendil-works/pi-coding-agent/examples (extensions, custom tools, SDK)\n- When reading pi docs or examples, resolve docs/... under Additional docs and examples/... under Examples, not the current working directory\n- When asked about: extensions (docs/extensions.md, examples/extensions/), themes (docs/themes.md), skills (docs/skills.md), prompt templates (docs/prompt-templates.md), TUI components (docs/tui.md), keybindings (docs/keybindings.md), SDK integrations (docs/sdk.md), custom providers (docs/custom-provider.md), adding models (docs/models.md), pi packages (docs/packages.md), environment variables (docs/environment-variables.md), MCP servers (docs/mcp.md), codemode scripts and non-LLM models such as classifiers and image models (docs/codemode.md)\n- When working on pi topics, read the docs and examples, and follow .md cross-references before implementing\n- Always read pi .md files completely and follow links to related docs (e.g., tui.md for TUI API details)\n","cwd":"\n/work\n"},"timestamp":1791482709539,"toolsAdded":[{"name":"read","description":"Read the contents of a file. 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hello.txt contains: hi"}],"api":"openai-completions","provider":"litellm","model":"claude-haiku-4-5-20251001","usage":{"input":120,"output":9,"cacheRead":0,"cacheWrite":0,"reasoning":0,"totalTokens":129,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1791482694397,"responseId":"chatcmpl-1","rawStopReason":"stop","durationMs":4,"thinkingLevel":"off"}],"willRetry":false} +{"type":"agent_settled","aborted":false} diff --git a/tests/unit/llms/pi/harness/fixtures/turn2_resume.jsonl b/tests/unit/llms/pi/harness/fixtures/turn2_resume.jsonl new file mode 100644 index 00000000000..8d50c16e564 --- /dev/null +++ b/tests/unit/llms/pi/harness/fixtures/turn2_resume.jsonl @@ -0,0 +1,15 @@ +{"type":"session","version":3,"id":"01a11cb0-87cf-752e-a3e3-365c7a169871","timestamp":"2026-10-08T18:04:53.583Z","cwd":"/work"} +{"type":"agent_start"} +{"type":"turn_start"} +{"type":"message_start","message":{"role":"user","content":[{"type":"text","text":"do the task"}],"timestamp":1791482698176}} +{"type":"message_end","message":{"role":"user","content":[{"type":"text","text":"do the task"}],"timestamp":1791482698176}} +{"type":"message_start","message":{"role":"assistant","content":[],"api":"openai-completions","provider":"litellm","model":"claude-haiku-4-5-20251001","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"pending","timestamp":1791482698355}} +{"type":"message_update","usage":{"input":120,"output":9,"cacheRead":0,"cacheWrite":0,"reasoning":0,"totalTokens":129,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"assistantMessageEvent":{"type":"text_start","contentIndex":0}} +{"type":"message_update","usage":{"input":120,"output":9,"cacheRead":0,"cacheWrite":0,"reasoning":0,"totalTokens":129,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":"You asked me"}} +{"type":"message_update","usage":{"input":120,"output":9,"cacheRead":0,"cacheWrite":0,"reasoning":0,"totalTokens":129,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":" to create h"}} +{"type":"message_update","usage":{"input":120,"output":9,"cacheRead":0,"cacheWrite":0,"reasoning":0,"totalTokens":129,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"assistantMessageEvent":{"type":"text_delta","contentIndex":0,"delta":"ello.txt."}} +{"type":"message_update","usage":{"input":120,"output":9,"cacheRead":0,"cacheWrite":0,"reasoning":0,"totalTokens":129,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"assistantMessageEvent":{"type":"text_end","contentIndex":0,"content":"You asked me to create hello.txt."}} +{"type":"message_end","message":{"role":"assistant","content":[{"type":"text","text":"You asked me to create hello.txt."}],"api":"openai-completions","provider":"litellm","model":"claude-haiku-4-5-20251001","usage":{"input":120,"output":9,"cacheRead":0,"cacheWrite":0,"reasoning":0,"totalTokens":129,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1791482698355,"responseId":"chatcmpl-1","rawStopReason":"stop","durationMs":169,"thinkingLevel":"off"}} +{"type":"turn_end","message":{"role":"assistant","content":[{"type":"text","text":"You asked me to create hello.txt."}],"api":"openai-completions","provider":"litellm","model":"claude-haiku-4-5-20251001","usage":{"input":120,"output":9,"cacheRead":0,"cacheWrite":0,"reasoning":0,"totalTokens":129,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1791482698355,"responseId":"chatcmpl-1","rawStopReason":"stop","durationMs":169,"thinkingLevel":"off"},"toolResults":[]} +{"type":"agent_end","messages":[{"role":"user","content":[{"type":"text","text":"do the task"}],"timestamp":1791482698176},{"role":"assistant","content":[{"type":"text","text":"You asked me to create hello.txt."}],"api":"openai-completions","provider":"litellm","model":"claude-haiku-4-5-20251001","usage":{"input":120,"output":9,"cacheRead":0,"cacheWrite":0,"reasoning":0,"totalTokens":129,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1791482698355,"responseId":"chatcmpl-1","rawStopReason":"stop","durationMs":169,"thinkingLevel":"off"}],"willRetry":false} +{"type":"agent_settled","aborted":false} diff --git a/tests/unit/llms/pi/harness/test_transformation.py b/tests/unit/llms/pi/harness/test_transformation.py new file mode 100644 index 00000000000..615a255bb7e --- /dev/null +++ b/tests/unit/llms/pi/harness/test_transformation.py @@ -0,0 +1,991 @@ +"""Unit tests for the pi harness config. No network, no real CLI. + +Fixtures under fixtures/ are sanitized `pi --mode json` output recorded from +@earendil-works/pi-coding-agent 1.1.0 against a scripted OpenAI-compatible endpoint. +""" + +import asyncio +import itertools +import json +from collections.abc import Mapping, Sequence +from dataclasses import dataclass, field +from pathlib import Path +from types import MappingProxyType +from typing import Final + +import pytest +from pydantic import BaseModel, ConfigDict + +from litellm.harness.context import GatewayTarget, SessionContext +from litellm.harness.errors import ( + CapabilityUnsupported, + HarnessError, + HarnessInstallFailed, + OptionsMismatch, +) +from litellm.harness.handlers.cli_handler import PERSIST_DIR_SCRIPT, CLIHarnessHandler +from litellm.harness.options import HarnessOptions, OpenCodeOptions, PiOptions, PiThinkingLevel +from litellm.harness.sandbox.base import CompletedRun +from litellm.harness.types import Event, Harness, PermissionMode, Reasoning, Text, ToolCall, ToolResult +from litellm.llms.anthropic.chat.transformation import AnthropicConfig +from litellm.llms.base_llm.harness.transformation import ( + HarnessSessionSetup, + HarnessTurnError, +) +from litellm.llms.pi.harness.transformation import ( + INSTRUCTIONS_FILENAME, + MANAGED_CONFIG_KEYS, + MANAGED_ENV_KEYS, + MCP_FILENAME, + MODELS_FILENAME, + PI_CONFIG_DIR_ENV, + PI_DEFAULT_MAX_TOKENS, + PI_ISOLATION_ENV, + PI_TOKEN_ENV, + SETTINGS_FILENAME, + PiHarnessConfig, + PiStreamState, + build_models_json, + config_files, + mcp_tool_entries, + tool_args, + validate_user_config, +) +from litellm.types.utils import ModelInfo +from litellm.utils import ProviderConfigManager, get_model_info + +FIXTURES: Final = Path(__file__).parent / "fixtures" +TOKEN: Final = "tok-secret-123" +SESSION: Final = "01a11cb0-87cf-752e-a3e3-365c7a169871" +PRIVATE: Final = "/tmp/pi-1" +MODEL: Final = "claude-haiku-4-5-20251001" +FULL_TOOLS: Final = "read,bash,edit,write,grep,find,ls" +MOYAI: Final = {"command": "/path/to/mcp-server", "args": [], "env": {}, "exposure": "direct"} +CONFIG: Final = PiHarnessConfig() + + +def load_fixture(name: str) -> Sequence[Mapping[str, object]]: + return tuple(json.loads(line) for line in (FIXTURES / name).read_text().splitlines() if line) + + +def parse(obj: Mapping[str, object], state: PiStreamState) -> Sequence[Event]: + return CONFIG.transform_stream_line(obj, state) + + +def parse_all(name: str, state: PiStreamState | None = None) -> tuple[Sequence[Event], PiStreamState]: + run_state: Final = state or CONFIG.create_stream_state() + events: Final = tuple(itertools.chain.from_iterable(parse(obj, run_state) for obj in load_fixture(name))) + return events, run_state + + +def assistant_end(text: str, stop_reason: str, error: str | None = None) -> Mapping[str, object]: + error_field: Final = {"errorMessage": error} if error else {} + return { + "type": "message_end", + "message": { + "role": "assistant", + "content": [{"type": "text", "text": text}], + "stopReason": stop_reason, + **error_field, + }, + } + + +class FakeStdin: + def __init__(self) -> None: + self.data = b"" + self.closed = False + + def write(self, data: bytes) -> None: + self.data += data + + async def drain(self) -> None: + return None + + def close(self) -> None: + self.closed = True + + +class FakeProcess: + def __init__(self, stdout: bytes, stderr: bytes = b"", exit_code: int = 0) -> None: + self.stdin = FakeStdin() + self.stdout = asyncio.StreamReader() + self.stdout.feed_data(stdout) + self.stdout.feed_eof() + self.stderr = asyncio.StreamReader() + self.stderr.feed_data(stderr) + self.stderr.feed_eof() + self._exit_code = exit_code + self.killed = False + + async def wait(self) -> int: + return self._exit_code + + async def kill(self) -> None: + self.killed = True + + +@dataclass(frozen=True, slots=True) +class Exec: + cmd: Sequence[str] + env: Mapping[str, str] + cwd: str | None + + +@dataclass +class FakeSandbox: + workdir: str = "/work" + has_binary: bool = True + persist_ok: bool = True + outputs: tuple[FakeProcess, ...] = () + files: Mapping[str, bytes] = field(default_factory=lambda: MappingProxyType({})) + execs: tuple[Exec, ...] = () + runs: tuple[Sequence[str], ...] = () + tempdirs: int = 0 + + async def exec( + self, cmd: Sequence[str], *, env: Mapping[str, str] | None = None, cwd: str | None = None + ) -> FakeProcess: + self.execs = (*self.execs, Exec(cmd=cmd, env=MappingProxyType(dict(env or {})), cwd=cwd)) + return self.outputs[len(self.execs) - 1] + + async def run( + self, + cmd: Sequence[str], + *, + env: Mapping[str, str] | None = None, + cwd: str | None = None, + timeout: float | None = None, + ) -> CompletedRun: + self.runs = (*self.runs, cmd) + if self.persist_ok: + return CompletedRun("", "", 0) + return CompletedRun("", "read-only fs", 1) + + async def read(self, path: str) -> bytes: + return self.files[path] + + async def write(self, path: str, data: bytes) -> None: + self.files = MappingProxyType({**self.files, path: data}) + + def host_url(self, port: int) -> str: + return f"http://host.docker.internal:{port}" + + async def which(self, binary: str) -> str | None: + return f"/usr/bin/{binary}" if self.has_binary else None + + async def tempdir(self) -> str: + self.tempdirs += 1 + return f"/tmp/pi-{self.tempdirs}" + + async def snapshot(self) -> Mapping[str, str]: + return MappingProxyType({}) + + async def close(self) -> None: + return None + + +@dataclass(frozen=True) +class FakeEndpoint: + port: int = 4555 + token: str = TOKEN + model: str | None = None + + +DEFAULT_ENDPOINT: Final = FakeEndpoint() + + +class Answer(BaseModel): + model_config = ConfigDict(frozen=True) + + city: str + country: str + + +def make_ctx( + sandbox: FakeSandbox | None = None, + *, + model: str | None = MODEL, + gateway: GatewayTarget | None = None, + endpoint: FakeEndpoint | None = DEFAULT_ENDPOINT, + options: HarnessOptions | None = None, + permissions: PermissionMode = "full", + instructions: str | None = None, + output: type[BaseModel] | None = None, + skills: Sequence[str] = (), + disable_tools: Sequence[str] = (), +) -> SessionContext: + return SessionContext( + harness=Harness.PI, + sandbox=sandbox or FakeSandbox(), + session_id="s1", + model=model, + gateway=gateway, + endpoint=endpoint, + options=options, + permissions=permissions, + instructions=instructions, + output=output, + skills=skills, + disable_tools=disable_tools, + ) + + +def setup_for(ctx: SessionContext) -> HarnessSessionSetup: + return CONFIG.transform_session_setup(ctx, PRIVATE) + + +def setup_models(setup: HarnessSessionSetup) -> Mapping[str, object]: + return json.loads(setup.files[MODELS_FILENAME]) + + +def fixture_proc(name: str, exit_code: int = 0) -> FakeProcess: + return FakeProcess((FIXTURES / name).read_bytes(), exit_code=exit_code) + + +async def collect(handler: CLIHarnessHandler, ctx: SessionContext, prompt: str) -> Sequence[Event]: + return [e async for e in handler.turn(ctx, prompt)] + + +async def started(ctx: SessionContext) -> CLIHarnessHandler: + handler: Final = CLIHarnessHandler(PiHarnessConfig()) + await handler.start(ctx) + return handler + + +def flag(argv: Sequence[str], name: str) -> str: + args: Final = list(argv) + return args[args.index(name) + 1] + + +def written_models(sandbox: FakeSandbox, private: str = PRIVATE) -> Mapping[str, object]: + return json.loads(sandbox.files[f"{private}/{MODELS_FILENAME}"]) + + +def test_parse_write_read_turn(): + events, state = parse_all("turn1_write_read.jsonl") + assert state.session_id == SESSION + assert [type(e) for e in events] == [ + Reasoning, + ToolCall, + ToolResult, + ToolCall, + ToolResult, + Text, + Text, + Text, + ] + assert events[0] == Reasoning(delta="I should write the file first.") + write, write_result = events[1], events[2] + assert write.name == "write" and write.native_name == "write" + assert write.builtin is True + assert write.input == {"path": "hello.txt", "content": "hi"} + assert write_result.id == write.id == "call_w1" + assert write_result.output == "Successfully wrote to hello.txt" + assert write_result.is_error is False + read, read_result = events[3], events[4] + assert read.name == "read" and read_result.output == "hi" + assert "".join(e.delta for e in events[5:]) == state.final_text + assert state.final_text == "Done! hello.txt contains: hi" + assert state.stop_reason == "stop" and state.error is None + + +def test_parse_continued_session(): + events, state = parse_all("turn2_resume.jsonl") + assert state.session_id == SESSION + assert all(isinstance(e, Text) for e in events) + assert state.final_text == "You asked me to create hello.txt." + + +def test_parse_denied_tool_is_error_result(): + events, state = parse_all("readonly_denied_bash.jsonl") + call: Final = next(e for e in events if isinstance(e, ToolCall)) + result: Final = next(e for e in events if isinstance(e, ToolResult)) + assert call.native_name == "bash" and call.input == {"command": "echo x > blocked.txt"} + assert result == ToolResult(id="call_b1", output="Tool bash not found", is_error=True) + assert state.final_text.startswith("FAILED") + + +def test_parse_mcp_tool_turn(): + events, state = parse_all("mcp_tool.jsonl") + call: Final = next(e for e in events if isinstance(e, ToolCall)) + result: Final = next(e for e in events if isinstance(e, ToolResult)) + assert call == ToolCall( + id="call_m1", + name="mcp__moyai__echo", + native_name="mcp__moyai__echo", + input={"text": "hello"}, + builtin=False, + ) + assert result == ToolResult(id="call_m1", output="moyai says: hello", is_error=False) + assert state.final_text == "The MCP tool replied." + + +def test_parse_api_error_records_error(): + events, state = parse_all("api_error.jsonl") + assert events == () + assert state.stop_reason == "error" + assert "no healthy deployments" in state.error + + +def test_parse_reasoning_and_tool_error_and_name_mapping(): + state: Final = PiStreamState() + reasoning: Final = parse( + { + "type": "message_update", + "assistantMessageEvent": {"type": "thinking_delta", "delta": "thinking hard"}, + }, + state, + ) + assert reasoning == [Reasoning(delta="thinking hard")] + failed: Final = parse( + { + "type": "tool_execution_end", + "toolCallId": "c1", + "toolName": "bash", + "result": {"content": [{"type": "text", "text": "boom"}]}, + "isError": True, + }, + state, + ) + assert failed == [ToolResult(id="c1", output="boom", is_error=True)] + calls: Final = [ + parse({"type": "tool_execution_start", "toolCallId": "x", "toolName": native, "args": {}}, state)[0] + for native in ("find", "powershell", "grep", "ls", "edit") + ] + assert [(call.name, call.builtin) for call in calls] == [ + ("glob", True), + ("bash", True), + ("grep", True), + ("ls", True), + ("edit", True), + ] + mcp: Final = parse( + {"type": "tool_execution_start", "toolCallId": "m", "toolName": "mcp__gh__search", "args": {"q": 1}}, + state, + ) + assert mcp[0].builtin is False and mcp[0].input == {"q": 1} + plain: Final = parse( + {"type": "tool_execution_end", "toolCallId": "m", "toolName": "mcp__gh__search", "result": "raw"}, + state, + ) + assert plain == [ToolResult(id="m", output="raw", is_error=False)] + no_result: Final = parse({"type": "tool_execution_end", "toolCallId": "e", "toolName": "bash"}, state) + assert no_result == [ToolResult(id="e", output="", is_error=False)] + + +def test_final_text_is_last_assistant_message(): + state: Final = PiStreamState() + parse(assistant_end("working", "toolUse"), state) + parse(assistant_end("answer", "stop"), state) + parse( + {"type": "message_end", "message": {"role": "user", "content": [{"type": "text", "text": "q"}]}}, + state, + ) + parse({"type": "message_end", "message": {"role": "system", "content": ""}}, state) + assert state.final_text == "answer" + parse( + { + "type": "message_end", + "message": { + "role": "assistant", + "stopReason": "stop", + "content": [ + {"type": "thinking", "thinking": "hmm"}, + {"type": "text", "text": "a"}, + {"type": "toolCall", "id": "x", "name": "read", "arguments": {}}, + {"type": "text", "text": "b"}, + ], + }, + }, + state, + ) + assert state.final_text == "ab" + + +def test_message_update_ignores_non_delta_events(): + state: Final = PiStreamState() + for update in [ + {"type": "text_start", "contentIndex": 0}, + {"type": "text_end", "content": "full"}, + {"type": "toolcall_delta", "delta": "{"}, + {"type": "text_delta", "delta": ""}, + ]: + assert parse({"type": "message_update", "assistantMessageEvent": update}, state) == [] + assert parse({"type": "message_update"}, state) == [] + + +def test_retried_error_then_success_is_not_an_error(): + state: Final = PiStreamState() + parse(assistant_end("", "error", "529 overloaded"), state) + parse(assistant_end("recovered", "stop"), state) + assert state.stop_reason == "stop" and state.error is None + assert CONFIG.transform_turn_response(make_ctx(), state, 0, []).final_text == "recovered" + + +def test_aborted_run_is_an_error(): + state: Final = PiStreamState() + parse(assistant_end("partial", "stop"), state) + parse({"type": "agent_settled", "aborted": False}, state) + assert state.stop_reason == "stop" + parse({"type": "agent_settled", "aborted": True}, state) + assert state.stop_reason == "aborted" + + +def test_permission_mapping(): + assert tool_args("full", ()) == ("--tools", FULL_TOOLS) + assert tool_args("read-only", ()) == ("--tools", "read,grep,find,ls") + assert tool_args("edit", ()) == ("--tools", "read,edit,write,grep,find,ls") + with pytest.raises(CapabilityUnsupported): + tool_args("ask", ()) + + +def test_disable_tools_map_to_native_excludes(): + args: Final = tool_args("full", ["bash", "glob", "write", "mcp__x"]) + assert flag(args, "--tools") == FULL_TOOLS + assert flag(args, "--exclude-tools") == "bash,powershell,find,write,mcp__x" + + +def test_mcp_servers_keep_tools_reachable(): + assert mcp_tool_entries({}) == () + assert mcp_tool_entries({"mcpServers": {}}) == () + assert mcp_tool_entries({"mcpServers": {"moyai": MOYAI}}) == ("mcp__*",) + assert mcp_tool_entries({"mcpServers": {"s": {"command": "x"}}}) == ("mcp__*", "codemode") + assert mcp_tool_entries({"mcpServers": {"s": {"url": "u", "exposure": "deferred"}}}) == ( + "mcp__*", + "tool_search", + ) + assert mcp_tool_entries( + {"mcpServers": {"s": {"command": "x", "exposure": "hidden", "toolExposure": {"a": "direct", "b": "deferred"}}}} + ) == ("mcp__*", "tool_search") + args: Final = tool_args("read-only", ["mcp__moyai__drop"], mcp_tool_entries({"mcpServers": {"moyai": MOYAI}})) + assert flag(args, "--tools") == "read,grep,find,ls,mcp__*" + assert flag(args, "--exclude-tools") == "mcp__moyai__drop" + + +def test_config_files_split_settings_and_mcp(): + files: Final = dict(config_files({"mcpServers": {"moyai": MOYAI}, "compaction": {"enabled": False}})) + assert json.loads(files[MCP_FILENAME]) == {"mcpServers": {"moyai": MOYAI}} + assert json.loads(files[SETTINGS_FILENAME]) == {"compaction": {"enabled": False}} + assert dict(config_files({"mcpServers": {"moyai": MOYAI}})).keys() == {MCP_FILENAME} + assert dict(config_files({"theme": "dark"})).keys() == {SETTINGS_FILENAME} + assert config_files({}) == () + + +def test_config_files_reject_values_that_are_not_json(): + with pytest.raises(TypeError, match=r"set in PiOptions\.config is not JSON serializable"): + config_files({"theme": {"dark", "light"}}) + + +@pytest.mark.parametrize( + "config", + [ + *({key: "x"} for key in sorted(MANAGED_CONFIG_KEYS)), + {"mcpServers": "not-a-mapping"}, + {"mcpServers": {"moyai": "not-a-mapping"}}, + ], +) +def test_managed_keys_rejected(config: Mapping[str, object]) -> None: + with pytest.raises(OptionsMismatch): + validate_user_config(config) + + +def test_options_config_cannot_load_code_or_reroute_model(): + for key in ("extensions", "packages", "defaultProjectTrust", "defaultProvider", "defaultModel", "httpProxy"): + assert key in MANAGED_CONFIG_KEYS + with pytest.raises(OptionsMismatch, match="extensions"): + validate_user_config({"extensions": ["./evil.ts"]}) + + +def test_build_models_json(): + models: Final = json.loads(build_models_json("m1", "http://h:1/v1", None, None)) + assert models == { + "providers": { + "litellm": { + "baseUrl": "http://h:1/v1", + "api": "openai-completions", + "apiKey": f"${PI_TOKEN_ENV}", + "compat": {"supportsStore": False}, + "models": [{"id": "m1"}], + } + } + }, ( + "an unmapped model keeps pi's own limits and no cache_control marks, " + "and pi must not send `store`, which non-OpenAI providers reject" + ) + + +def test_mapped_model_declares_litellm_context_and_output_limits() -> None: + info: Final = get_model_info(MODEL) + models: Final = setup_models(setup_for(make_ctx())) + declared: Final = models["providers"]["litellm"]["models"][0] + assert (declared["contextWindow"], declared["maxTokens"]) == ( + info["max_input_tokens"], + min(info["max_output_tokens"], PI_DEFAULT_MAX_TOKENS), + ) + + +@pytest.mark.parametrize("max_output_tokens", [PI_DEFAULT_MAX_TOKENS // 4, PI_DEFAULT_MAX_TOKENS * 8]) +def test_pi_asks_for_no_more_output_tokens_than_the_model_or_its_own_default(max_output_tokens: int) -> None: + info: Final = ModelInfo(**{**get_model_info(MODEL), "max_output_tokens": max_output_tokens}) + declared: Final = json.loads(build_models_json(MODEL, "http://h:1/v1", None, info))["providers"]["litellm"] + assert declared["models"][0]["maxTokens"] == min(max_output_tokens, PI_DEFAULT_MAX_TOKENS), ( + "pi sends maxTokens as max_completion_tokens on every call, and the gateway reserves it against the key's " + "TPM limit, so a model's full output cap made keys under that limit answer 429" + ) + + +@pytest.mark.parametrize("info", [get_model_info(MODEL), None], ids=["mapped", "unmapped"]) +@pytest.mark.parametrize("thinking", ["minimal", "low", "medium", "high", "xhigh", "max"]) +def test_thinking_budget_leaves_pi_its_default_room_for_the_answer( + thinking: PiThinkingLevel, info: ModelInfo | None +) -> None: + declared: Final = json.loads(build_models_json(MODEL, "http://h:1/v1", thinking, info))["providers"]["litellm"] + sent: Final = AnthropicConfig().map_openai_params( + {"reasoning_effort": thinking, "max_completion_tokens": declared["models"][0]["maxTokens"]}, + {}, + MODEL, + drop_params=False, + ) + assert sent["max_tokens"] - sent["thinking"]["budget_tokens"] >= PI_DEFAULT_MAX_TOKENS, ( + "Anthropic answers 400 unless max_tokens is above the thinking budget LiteLLM sends for the level, " + "so a budget as large as pi's default left thinking=max with no request it could make" + ) + assert sent["max_tokens"] <= get_model_info(MODEL)["max_output_tokens"] + + +def test_model_that_supports_prompt_caching_asks_pi_for_cache_control_marks() -> None: + assert get_model_info(MODEL).get("supports_prompt_caching") is True + declared: Final = setup_models(setup_for(make_ctx()))["providers"]["litellm"]["models"][0] + assert declared["compat"] == {"cacheControlFormat": "anthropic"}, ( + "pi only marks cache_control for OpenRouter Anthropic models by itself, so every Claude call missed the cache" + ) + + +GATEWAY: Final = GatewayTarget(api_base="http://gateway:4000", api_key="sk-gateway") + + +@pytest.mark.parametrize( + ("group", "declared_limits"), + [ + (MODEL, {"contextWindow": get_model_info(MODEL)["max_input_tokens"]}), + ("team-default-model", {}), + ], +) +def test_gateway_group_is_looked_up_without_printing_to_stdout( + group: str, declared_limits: Mapping[str, int], capsys: pytest.CaptureFixture[str] +) -> None: + declared: Final = setup_models(setup_for(make_ctx(model=group, gateway=GATEWAY)))["providers"]["litellm"]["models"][ + 0 + ] + assert {key: declared[key] for key in declared_limits} == declared_limits + assert ("maxTokens" in declared) == bool(declared_limits) + assert capsys.readouterr().out == "", "an unmapped gateway group printed LiteLLM's provider-list banner on stdout" + + +MAPPED_MODEL: Final = { + "id": MODEL, + "contextWindow": get_model_info(MODEL)["max_input_tokens"], + "maxTokens": min(get_model_info(MODEL)["max_output_tokens"], PI_DEFAULT_MAX_TOKENS), + "compat": {"cacheControlFormat": "anthropic"}, +} +REASONING_MODEL: Final = {**MAPPED_MODEL, "reasoning": True, "thinkingLevelMap": {"xhigh": "xhigh", "max": "max"}} + + +@pytest.mark.parametrize( + ("thinking", "declared_model"), + [ + (None, MAPPED_MODEL), + ("off", MAPPED_MODEL), + ("minimal", REASONING_MODEL), + ("high", REASONING_MODEL), + ("xhigh", REASONING_MODEL), + ("max", REASONING_MODEL), + ], +) +def test_thinking_declares_a_reasoning_model_only_when_a_level_is_requested( + thinking: PiThinkingLevel | None, declared_model: Mapping[str, object] +) -> None: + models: Final = setup_models(setup_for(make_ctx(options=PiOptions(thinking=thinking)))) + declared: Final = {key: value for key, value in models["providers"]["litellm"]["models"][0].items() if key != "maxTokens"} + assert declared == {key: value for key, value in declared_model.items() if key != "maxTokens"}, ( + "pi drops --thinking to off unless the model declares reasoning, and drops xhigh/max to high " + "unless thinkingLevelMap names them; declaring reasoning with no level makes pi send its default effort" + ) + + +def test_config_metadata(): + assert CONFIG.get_binary() == "pi" + assert "@earendil-works/pi-coding-agent" in CONFIG.get_install_hint() + assert CONFIG.uses_model_endpoint is True + assert CONFIG.capabilities.permission_modes == {"read-only", "edit", "full"} + assert CONFIG.capabilities.resume is True + assert CONFIG.capabilities.tool_filtering is True + assert isinstance(ProviderConfigManager.get_provider_harness_config(Harness.PI), PiHarnessConfig) + + +def test_validate_environment_rejects_wrong_options_managed_config_and_ask_mode(): + CONFIG.validate_environment(make_ctx()) + CONFIG.validate_environment(make_ctx(options=PiOptions(config={"mcpServers": {"moyai": MOYAI}}))) + with pytest.raises(OptionsMismatch): + CONFIG.validate_environment(make_ctx(options=OpenCodeOptions())) + with pytest.raises(OptionsMismatch, match="defaultModel"): + CONFIG.validate_environment(make_ctx(options=PiOptions(config={"defaultModel": "openai/x"}))) + with pytest.raises(CapabilityUnsupported): + CONFIG.validate_environment(make_ctx(permissions="ask")) + + +@pytest.mark.parametrize("key", sorted(MANAGED_ENV_KEYS)) +def test_managed_env_keys_rejected_instead_of_silently_ignored(key: str) -> None: + assert key in {PI_CONFIG_DIR_ENV, PI_TOKEN_ENV} + with pytest.raises(OptionsMismatch, match=key): + CONFIG.validate_environment(make_ctx(options=PiOptions(env={key: "/tmp/evil"}))) + CONFIG.validate_environment(make_ctx(options=PiOptions(env={f"{key}_SUFFIX": "ok"}))) + + +def test_session_setup_token_only_in_env(): + setup: Final = setup_for(make_ctx()) + assert set(setup.files) == {MODELS_FILENAME} + assert all(TOKEN.encode() not in data for data in setup.files.values()) + assert setup.env[PI_TOKEN_ENV] == TOKEN + provider: Final = setup_models(setup)["providers"]["litellm"] + assert provider["baseUrl"] == "http://host.docker.internal:4555/v1" + assert provider["apiKey"] == f"${PI_TOKEN_ENV}" + + +def test_session_setup_env_and_persisted_sessions(): + options: Final = PiOptions(env={"FOO": "1", PI_TOKEN_ENV: "evil", PI_CONFIG_DIR_ENV: "/home/u/.pi/agent"}) + setup: Final = setup_for(make_ctx(options=options)) + assert list(setup.persisted_dirs) == [("sessions", "pi/sessions")] + assert setup.skills_dir == "skills" + env: Final = setup.env + assert env[PI_CONFIG_DIR_ENV] == f"{PRIVATE}/agent", "managed keys must win over PiOptions.env" + assert env[PI_TOKEN_ENV] == TOKEN, "managed keys must win over PiOptions.env" + for key, value in PI_ISOLATION_ENV.items(): + assert env[key] == value + assert env["FOO"] == "1" + + +def test_session_setup_writes_user_config_next_to_managed_models(): + options: Final = PiOptions(config={"mcpServers": {"moyai": MOYAI}, "compaction": {"enabled": False}}) + setup: Final = setup_for(make_ctx(options=options)) + assert set(setup.files) == {MODELS_FILENAME, MCP_FILENAME, SETTINGS_FILENAME} + assert json.loads(setup.files[MCP_FILENAME]) == {"mcpServers": {"moyai": MOYAI}} + assert setup_models(setup)["providers"]["litellm"]["apiKey"] == f"${PI_TOKEN_ENV}" + + +def test_session_setup_errors(): + with pytest.raises(HarnessError): + setup_for(make_ctx(endpoint=None)) + with pytest.raises(ValueError, match="needs model="): + setup_for(make_ctx(model=None, endpoint=FakeEndpoint(model=None))) + + +def test_turn_request_without_a_model_raises_instead_of_passing_none(): + ctx: Final = make_ctx(model=None, endpoint=FakeEndpoint(model=None)) + with pytest.raises(ValueError, match="needs model="): + CONFIG.transform_turn_request(ctx, HarnessSessionSetup(), PRIVATE, "hi", None) + + +def test_session_setup_instructions_and_skills(): + ctx: Final = make_ctx(instructions="Be terse.", output=Answer, skills=["/s/greeter"]) + setup: Final = setup_for(ctx) + written: Final = setup.files[INSTRUCTIONS_FILENAME].decode() + assert written.startswith("Be terse.") + assert '"city"' in written and "single JSON object" in written + argv: Final = CONFIG.transform_turn_request(ctx, setup, PRIVATE, "hi", None).argv + assert flag(argv, "--append-system-prompt") == f"{PRIVATE}/instructions.md" + assert flag(argv, "--skill") == f"{PRIVATE}/skills" + plain: Final = make_ctx() + plain_setup: Final = setup_for(plain) + plain_argv: Final = CONFIG.transform_turn_request(plain, plain_setup, PRIVATE, "hi", None).argv + assert INSTRUCTIONS_FILENAME not in plain_setup.files + assert "--append-system-prompt" not in plain_argv and "--skill" not in plain_argv + + +def test_turn_request_argv_and_session_continuation(): + ctx: Final = make_ctx(options=PiOptions(thinking="high")) + setup: Final = setup_for(ctx) + first: Final = CONFIG.transform_turn_request(ctx, setup, PRIVATE, "hello", None) + assert list(first.argv) == [ + "pi", + "--mode", + "json", + "--no-approve", + "--no-skills", + "--provider", + "litellm", + "--model", + MODEL, + "--session-dir", + f"{PRIVATE}/sessions", + "--tools", + FULL_TOOLS, + "--thinking", + "high", + ] + assert first.cwd == "/work" + assert first.stdin == "hello" + assert first.env == setup.env + second: Final = CONFIG.transform_turn_request(ctx, setup, PRIVATE, "again", SESSION) + assert flag(second.argv, "--session") == SESSION + assert "again" not in " ".join(second.argv) + + +def test_turn_prompt_repeats_schema_when_output_set(): + ctx: Final = make_ctx(output=Answer) + request: Final = CONFIG.transform_turn_request(ctx, setup_for(ctx), PRIVATE, "hi", None) + assert request.stdin.startswith("hi\n\n") and '"city"' in request.stdin + + +def test_turn_response_paths(): + _, state = parse_all("structured_output.jsonl") + ok: Final = CONFIG.transform_turn_response(make_ctx(output=Answer), state, 0, []) + assert json.loads(ok.output_json) == {"city": "Paris", "country": "France"} + plain: Final = CONFIG.transform_turn_response(make_ctx(), state, 0, []) + assert plain.output_json is None and plain.final_text == state.final_text + with pytest.raises(HarnessTurnError, match="boom"): + CONFIG.transform_turn_response(make_ctx(), PiStreamState(stop_reason="error", error="boom"), 0, []) + with pytest.raises(HarnessTurnError, match="aborted"): + CONFIG.transform_turn_response(make_ctx(), PiStreamState(stop_reason="aborted"), 0, []) + with pytest.raises(HarnessTurnError, match="code 3: no output"): + CONFIG.transform_turn_response(make_ctx(), PiStreamState(), 3, []) + + +def test_reply_cut_off_at_the_output_token_limit_is_an_error(): + state: Final = PiStreamState() + parse(assistant_end("partial", "length"), state) + with pytest.raises(HarnessTurnError, match="output token limit"): + CONFIG.transform_turn_response(make_ctx(), state, 0, []) + + +def test_exit_zero_without_a_reply_is_an_error(): + with pytest.raises(HarnessTurnError, match="without a reply: Session found in different project"): + CONFIG.transform_turn_response(make_ctx(), PiStreamState(), 0, ["Session found in different project: /a"]) + + +async def test_start_writes_token_only_in_env(): + sandbox: Final = FakeSandbox(outputs=(fixture_proc("turn1_write_read.jsonl"),)) + ctx: Final = make_ctx(sandbox) + handler: Final = await started(ctx) + assert written_models(sandbox)["providers"]["litellm"]["apiKey"] == f"${PI_TOKEN_ENV}" + assert all(TOKEN.encode() not in data for data in sandbox.files.values()) + await collect(handler, ctx, "create hello.txt containing hi then read it") + assert TOKEN not in json.dumps(list(sandbox.execs[0].cmd)) + assert sandbox.execs[0].env[PI_TOKEN_ENV] == TOKEN + + +async def test_start_persists_sessions_dir(): + sandbox: Final = FakeSandbox() + await started(make_ctx(sandbox)) + assert sandbox.runs == (["sh", "-c", PERSIST_DIR_SCRIPT, "sh", "/tmp/pi-1/sessions", "pi/sessions"],) + + +async def test_persist_failure_still_uses_private_sessions(): + sandbox: Final = FakeSandbox(persist_ok=False, outputs=(fixture_proc("turn1_write_read.jsonl"),)) + ctx: Final = make_ctx(sandbox) + await collect(await started(ctx), ctx, "x") + assert flag(sandbox.execs[0].cmd, "--session-dir") == "/tmp/pi-1/sessions" + + +async def test_turn_argv_env_and_session_continuation(): + sandbox: Final = FakeSandbox(outputs=(fixture_proc("turn1_write_read.jsonl"), fixture_proc("turn2_resume.jsonl"))) + ctx: Final = make_ctx(sandbox, options=PiOptions(env={"FOO": "1"})) + handler: Final = await started(ctx) + events: Final = await collect(handler, ctx, "create hello.txt containing hi then read it") + first: Final = sandbox.execs[0] + assert first.cmd == [ + "pi", + "--mode", + "json", + "--no-approve", + "--no-skills", + "--provider", + "litellm", + "--model", + MODEL, + "--session-dir", + "/tmp/pi-1/sessions", + "--tools", + FULL_TOOLS, + ] + assert first.cwd == "/work" + assert first.env["PI_CODING_AGENT_DIR"] == "/tmp/pi-1/agent" + assert first.env["PI_OFFLINE"] == "1" and first.env["PI_TELEMETRY"] == "0" + assert first.env["FOO"] == "1" + assert any(isinstance(e, ToolCall) for e in events) + assert ctx.final_text == "Done! hello.txt contains: hi" + + await collect(handler, ctx, "what file did you create?") + second: Final = sandbox.execs[1].cmd + assert flag(second, "--session") == SESSION + assert "what file" not in " ".join(second) + assert ctx.final_text == "You asked me to create hello.txt." + + +async def test_prompt_is_sent_on_stdin_not_argv(): + proc: Final = fixture_proc("turn1_write_read.jsonl") + sandbox: Final = FakeSandbox(outputs=(proc,)) + ctx: Final = make_ctx(sandbox) + await collect(await started(ctx), ctx, "secret prompt text") + assert proc.stdin.data == b"secret prompt text" and proc.stdin.closed + assert "secret prompt text" not in sandbox.execs[0].cmd + + +@pytest.mark.parametrize(("workdir", "resume_flag"), [("/work", "--session"), ("/elsewhere", "--fork")]) +def test_session_saved_in_another_workdir_is_forked_into_this_one(workdir: str, resume_flag: str) -> None: + _, state = parse_all("turn1_write_read.jsonl") + ctx: Final = make_ctx(FakeSandbox(workdir=workdir)) + argv: Final = CONFIG.transform_turn_request( + ctx, setup_for(ctx), PRIVATE, "again", CONFIG.get_native_session_id(state) + ).argv + assert flag(argv, resume_flag) == SESSION + assert ({"--session", "--fork"} - {resume_flag}).isdisjoint(argv), ( + "pi answers --session for a session saved in another directory with a fork prompt the harness never answers" + ) + + +async def test_resume_sets_session(): + sandbox: Final = FakeSandbox(outputs=(fixture_proc("turn2_resume.jsonl"),)) + ctx: Final = make_ctx(sandbox) + handler: Final = await started(ctx) + await handler.resume(ctx, "prev-session") + await collect(handler, ctx, "hi") + assert flag(sandbox.execs[0].cmd, "--session") == "prev-session" + + +async def test_read_only_and_disable_tools_argv(): + sandbox: Final = FakeSandbox(outputs=(fixture_proc("readonly_denied_bash.jsonl"),)) + ctx: Final = make_ctx(sandbox, permissions="read-only", disable_tools=("grep",)) + events: Final = await collect(await started(ctx), ctx, "x") + cmd: Final = sandbox.execs[0].cmd + assert flag(cmd, "--tools") == "read,grep,find,ls" + assert flag(cmd, "--exclude-tools") == "grep" + assert ToolResult(id="call_b1", output="Tool bash not found", is_error=True) in events + + +async def test_instructions_and_structured_output(): + proc: Final = fixture_proc("structured_output.jsonl") + sandbox: Final = FakeSandbox(outputs=(proc,)) + ctx: Final = make_ctx(sandbox, instructions="Be terse.", output=Answer) + handler: Final = await started(ctx) + written: Final = sandbox.files["/tmp/pi-1/instructions.md"].decode() + assert written.startswith("Be terse.") + assert '"city"' in written and "single JSON object" in written + await collect(handler, ctx, "x") + assert flag(sandbox.execs[0].cmd, "--append-system-prompt") == "/tmp/pi-1/instructions.md" + assert '"city"' in proc.stdin.data.decode() + assert json.loads(ctx.output_json) == {"city": "Paris", "country": "France"} + + +async def test_skills_copied_to_private_skills_path(tmp_path: Path) -> None: + skill: Final = tmp_path / "greeter" + (skill / "ref").mkdir(parents=True) + (skill / "SKILL.md").write_text("---\nname: greeter\ndescription: d\n---\nbody") + (skill / "ref" / "notes.txt").write_text("n") + sandbox: Final = FakeSandbox(outputs=(fixture_proc("turn2_resume.jsonl"),)) + ctx: Final = make_ctx(sandbox, skills=(str(skill),)) + handler: Final = await started(ctx) + assert sandbox.files["/tmp/pi-1/skills/greeter/SKILL.md"].startswith(b"---") + assert sandbox.files["/tmp/pi-1/skills/greeter/ref/notes.txt"] == b"n" + await collect(handler, ctx, "x") + cmd: Final = sandbox.execs[0].cmd + assert flag(cmd, "--skill") == "/tmp/pi-1/skills" + assert "--no-skills" in cmd + + +async def test_skill_without_manifest_rejected(tmp_path: Path) -> None: + with pytest.raises(ValueError, match=r"SKILL\.md"): + await started(make_ctx(skills=(str(tmp_path),))) + + +async def test_missing_binary(): + with pytest.raises(HarnessInstallFailed, match="@earendil-works/pi-coding-agent"): + await started(make_ctx(FakeSandbox(has_binary=False))) + + +async def test_start_missing_endpoint_raises(): + with pytest.raises(HarnessError): + await started(make_ctx(endpoint=None)) + + +async def test_mcp_servers_written_and_reachable(): + sandbox: Final = FakeSandbox(outputs=(fixture_proc("mcp_tool.jsonl"),)) + ctx: Final = make_ctx(sandbox, options=PiOptions(config={"mcpServers": {"moyai": MOYAI}})) + handler: Final = await started(ctx) + assert json.loads(sandbox.files["/tmp/pi-1/agent/mcp.json"]) == {"mcpServers": {"moyai": MOYAI}} + events: Final = await collect(handler, ctx, "call the moyai echo tool") + assert flag(sandbox.execs[0].cmd, "--tools") == f"{FULL_TOOLS},mcp__*" + assert ToolResult(id="call_m1", output="moyai says: hello", is_error=False) in events + + +async def test_wrong_options_and_ask_mode_rejected(): + with pytest.raises(OptionsMismatch): + await started(make_ctx(options=OpenCodeOptions())) + with pytest.raises(OptionsMismatch): + await started(make_ctx(options=PiOptions(config={"sessionDir": "/elsewhere"}))) + with pytest.raises(CapabilityUnsupported): + await started(make_ctx(permissions="ask")) + + +async def test_turn_before_start_raises(): + handler: Final = CLIHarnessHandler(PiHarnessConfig()) + with pytest.raises(RuntimeError, match="before start"): + await collect(handler, make_ctx(), "x") + + +async def test_api_error_raises_even_on_exit_zero(): + ctx: Final = make_ctx(FakeSandbox(outputs=(fixture_proc("api_error.jsonl", exit_code=0),))) + handler: Final = await started(ctx) + with pytest.raises(HarnessTurnError, match="no healthy deployments"): + await collect(handler, ctx, "x") + + +async def test_nonzero_exit_raises_with_stderr_tail(): + failing: Final = FakeProcess(b"", stderr=b"line1\nfatal: bad flag\n", exit_code=2) + ctx: Final = make_ctx(FakeSandbox(outputs=(failing,))) + handler: Final = await started(ctx) + with pytest.raises(HarnessTurnError, match="code 2: line1\nfatal: bad flag"): + await collect(handler, ctx, "x") + + +async def test_early_close_kills_process_and_stop_is_idempotent(): + proc: Final = fixture_proc("turn1_write_read.jsonl") + ctx: Final = make_ctx(FakeSandbox(outputs=(proc,))) + handler: Final = await started(ctx) + gen: Final = handler.turn(ctx, "x") + await gen.__anext__() + await gen.aclose() + assert proc.killed + await handler.stop(ctx) + await handler.stop(ctx) + + +async def test_long_jsonl_line_is_parsed(): + text: Final = "x" * 200_000 + lines: Final = ( + {"type": "session", "version": 3, "id": "s"}, + {"type": "message_update", "assistantMessageEvent": {"type": "text_delta", "delta": text}}, + assistant_end(text, "stop"), + ) + stdout: Final = "\n".join(json.dumps(dict(line)) for line in lines).encode() + ctx: Final = make_ctx(FakeSandbox(outputs=(FakeProcess(stdout),))) + events: Final = await collect(await started(ctx), ctx, "x") + assert events == [Text(delta=text)] + assert ctx.final_text == text + + +async def test_model_falls_back_to_endpoint_model(): + sandbox: Final = FakeSandbox(outputs=(fixture_proc("turn1_write_read.jsonl"),)) + ctx: Final = make_ctx(sandbox, model=None, endpoint=FakeEndpoint(model="gw-model")) + await collect(await started(ctx), ctx, "x") + assert flag(sandbox.execs[0].cmd, "--model") == "gw-model" + assert written_models(sandbox)["providers"]["litellm"]["models"] == [{"id": "gw-model"}] + + +def test_turn_request_never_trusts_project_files(): + ctx: Final = make_ctx() + argv: Final = list(CONFIG.transform_turn_request(ctx, setup_for(ctx), PRIVATE, "hi", None).argv) + assert argv[:4] == ["pi", "--mode", "json", "--no-approve"], ( + "without --no-approve a repo's .pi/extensions run as the host user at startup" + ) diff --git a/tests/unit/llms/sagemaker/test_sagemaker_common_utils.py b/tests/unit/llms/sagemaker/test_sagemaker_common_utils.py index 17fac935679..ac1c816f86e 100644 --- a/tests/unit/llms/sagemaker/test_sagemaker_common_utils.py +++ b/tests/unit/llms/sagemaker/test_sagemaker_common_utils.py @@ -1,4 +1,9 @@ import json +import logging +import struct +import zlib +from collections.abc import AsyncIterator, Mapping +from typing import Final from unittest.mock import AsyncMock, MagicMock, patch import httpx @@ -6,8 +11,10 @@ import pytest from botocore.exceptions import ClientError, ConnectionClosedError -from litellm.llms.sagemaker.common_utils import AWSEventStreamDecoder, client_error_details +from litellm.llms.sagemaker.common_utils import AWSEventStreamDecoder, SagemakerError, client_error_details from litellm.llms.sagemaker.completion.transformation import SagemakerConfig +from litellm.types.utils import GenericStreamingChunk as GChunk +from litellm.types.utils import StreamingChatCompletionChunk # --------------------------------------------------------------------------- # @@ -232,6 +239,423 @@ async def test_aiter_bytes_valid_chunk_followed_by_unicode_error(): assert chunks[0]["text"] == "hello" # Verify the content of the valid chunk +def _event_header(name: str, value: str) -> bytes: + return struct.pack("!B", len(name)) + name.encode() + b"\x07" + struct.pack("!H", len(value)) + value.encode() + + +_PAYLOAD_PART_HEADERS: Final = ( + _event_header(":event-type", "PayloadPart") + + _event_header(":content-type", "application/octet-stream") + + _event_header(":message-type", "event") +) +_MODEL_STREAM_ERROR_HEADERS: Final = ( + _event_header(":exception-type", "ModelStreamError") + + _event_header(":content-type", "application/json") + + _event_header(":message-type", "exception") +) + + +def _frame(headers: bytes, body: str | bytes) -> bytes: + encoded: Final = body.encode() if isinstance(body, str) else body + prelude: Final = struct.pack("!II", 16 + len(headers) + len(encoded), len(headers)) + message: Final = prelude + struct.pack("!I", zlib.crc32(prelude)) + headers + encoded + return message + struct.pack("!I", zlib.crc32(message)) + + +def _payload_part(body: str | bytes) -> bytes: + return _frame(_PAYLOAD_PART_HEADERS, body) + + +def _cut(stream: str, size: int) -> tuple[bytes, ...]: + encoded: Final = stream.encode() + return tuple(encoded[start : start + size] for start in range(0, len(encoded), size)) + + +def _sse(record: Mapping[str, object]) -> str: + return f"data: {json.dumps(record, ensure_ascii=False)}\n\n" + + +def _vllm_chunk(choices: list[Mapping[str, object]], **extra: object) -> str: + return _sse( + {"id": "chatcmpl-1", "object": "chat.completion.chunk", "created": 1, "model": "m", "choices": choices, **extra} + ) + + +_VLLM_EVENTS: Final = ( + _vllm_chunk([{"index": 0, "delta": {"role": "assistant", "content": ""}, "finish_reason": None}]), + _vllm_chunk([{"index": 0, "delta": {"content": "Hél"}, "finish_reason": None}]), + _vllm_chunk([{"index": 0, "delta": {"content": "lo 👋"}, "finish_reason": "stop"}]), + _vllm_chunk([], usage={"prompt_tokens": 7, "completion_tokens": 3, "total_tokens": 10}), + "data: [DONE]\n\n", +) +_VLLM_STREAM: Final = "".join(_VLLM_EVENTS) +_TGI_EVENTS: Final = tuple( + f"data:{json.dumps({'index': 0, 'token': {'text': text}}, ensure_ascii=False)}\n\n" for text in ("Hél", "lo 👋") +) +_TGI_STREAM: Final = "".join(_TGI_EVENTS) +_TGI_KEEP_ALIVE_STREAM: Final = ( + f"{_TGI_EVENTS[0]}:\n\n: keep-alive\n\nevent: message\nid: 2\nretry: 1000\n{_TGI_EVENTS[1]}" +) +_LMI_STREAM: Final = "".join( + f"{json.dumps({'token': {'text': text}}, ensure_ascii=False)}\n" for text in ("Hél", "lo 👋") +) + + +async def _stream_frames( + frames: tuple[bytes, ...], is_messages_api: bool, mode: str +) -> AsyncIterator[GChunk | StreamingChatCompletionChunk | None]: + decoder: Final = AWSEventStreamDecoder(model="m", is_messages_api=is_messages_api) + if mode == "sync": + for chunk in decoder.iter_bytes(iter(frames)): + yield chunk + return + + async def stream(): + for frame in frames: + yield frame + + async for chunk in decoder.aiter_bytes(stream()): + yield chunk + + +async def _decode( + parts: tuple[str | bytes, ...], is_messages_api: bool, mode: str +) -> list[GChunk | StreamingChatCompletionChunk | None]: + return [chunk async for chunk in _stream_frames(tuple(map(_payload_part, parts)), is_messages_api, mode)] + + +def _text(chunk: GChunk | StreamingChatCompletionChunk | None, is_messages_api: bool) -> str | None: + if chunk is None: + return None + return chunk.choices[0].delta.content if is_messages_api else chunk["text"] + + +@pytest.mark.asyncio +@pytest.mark.parametrize("mode", ["sync", "async"]) +@pytest.mark.parametrize( + "parts", + [ + pytest.param(_VLLM_EVENTS, id="one-event-per-part"), + pytest.param((*_VLLM_EVENTS[:3], _VLLM_EVENTS[3] + _VLLM_EVENTS[4]), id="usage-and-done-share-a-part"), + pytest.param( + (_VLLM_EVENTS[0] + _VLLM_EVENTS[1], _VLLM_EVENTS[2] + _VLLM_EVENTS[3], _VLLM_EVENTS[4]), + id="event-pairs-share-a-part", + ), + pytest.param((*_VLLM_EVENTS[:4], "data: [DO", "NE]\n\n"), id="done-split-across-parts"), + pytest.param((_VLLM_STREAM,), id="whole-stream-in-one-part"), + pytest.param(_cut(_VLLM_STREAM, 7), id="seven-byte-parts"), + pytest.param(_cut(_VLLM_STREAM, 1), id="one-byte-parts-split-every-utf8-character"), + ], +) +async def test_messages_api_stream_keeps_every_chunk_however_sagemaker_cuts_the_parts( + parts: tuple[str | bytes, ...], mode: str, caplog: pytest.LogCaptureFixture +): + with caplog.at_level(logging.WARNING, logger="LiteLLM"): + chunks: Final = await _decode(parts, is_messages_api=True, mode=mode) + + assert None not in chunks + assert "".join(chunk.choices[0].delta.content for chunk in chunks if chunk.choices) == "Héllo 👋" + assert [(chunk.usage.prompt_tokens, chunk.usage.total_tokens) for chunk in chunks if chunk.usage] == [(7, 10)] + assert caplog.records == [] + + +@pytest.mark.asyncio +@pytest.mark.parametrize("mode", ["sync", "async"]) +@pytest.mark.parametrize( + "parts", + [ + pytest.param(_TGI_EVENTS, id="tgi-sse-one-event-per-part"), + pytest.param((_TGI_STREAM,), id="tgi-sse-whole-stream-in-one-part"), + pytest.param(_cut(_TGI_STREAM, 5), id="tgi-sse-five-byte-parts"), + pytest.param(_cut(_TGI_STREAM, 1), id="tgi-sse-one-byte-parts-split-every-utf8-character"), + pytest.param((_TGI_KEEP_ALIVE_STREAM,), id="tgi-sse-comments-and-fields-whole-stream-in-one-part"), + pytest.param(_cut(_TGI_KEEP_ALIVE_STREAM, 1), id="tgi-sse-comments-and-fields-one-byte-parts"), + pytest.param((_LMI_STREAM,), id="json-lines-whole-stream-in-one-part"), + pytest.param(_cut(_LMI_STREAM, 5), id="json-lines-five-byte-parts"), + pytest.param(tuple(_LMI_STREAM.splitlines()), id="undelimited-objects-one-per-part"), + ], +) +async def test_completion_stream_keeps_every_token_however_sagemaker_cuts_the_parts( + parts: tuple[str | bytes, ...], mode: str, caplog: pytest.LogCaptureFixture +): + with caplog.at_level(logging.WARNING, logger="LiteLLM"): + chunks: Final = await _decode(parts, is_messages_api=False, mode=mode) + + assert None not in chunks + assert "".join(chunk["text"] for chunk in chunks) == "Héllo 👋" + assert caplog.records == [] + + +@pytest.mark.asyncio +@pytest.mark.parametrize("mode", ["sync", "async"]) +@pytest.mark.parametrize( + "last_part", + [ + pytest.param(_VLLM_EVENTS[2][:20], id="cut-between-characters"), + pytest.param( + _VLLM_EVENTS[2].encode()[: _VLLM_EVENTS[2].encode().index("👋".encode()) + 2], id="cut-inside-a-character" + ), + ], +) +async def test_stream_that_ends_inside_a_record_raises_after_the_complete_ones(mode: str, last_part: str | bytes): + stream: Final = _stream_frames(tuple(map(_payload_part, (*_VLLM_EVENTS[:2], last_part))), True, mode) + + assert [_text(await anext(stream), True) for _ in range(2)] == ["", "Hél"] + with pytest.raises(SagemakerError, match="ended inside a record") as exc_info: + await anext(stream) + assert exc_info.value.status_code == 500 + + +@pytest.mark.asyncio +@pytest.mark.parametrize("mode", ["sync", "async"]) +async def test_text_left_over_that_is_not_a_record_is_logged_once(mode: str, caplog: pytest.LogCaptureFixture): + with caplog.at_level(logging.WARNING, logger="LiteLLM"): + chunks: Final = await _decode((*_VLLM_EVENTS[:3], "data: upstream hiccup\n\n"), is_messages_api=True, mode=mode) + + assert chunks[-1] is None + assert "".join(chunk.choices[0].delta.content for chunk in chunks[:-1]) == "Héllo 👋" + assert [record.levelno for record in caplog.records] == [logging.ERROR] + assert "hiccup" not in caplog.text + + +@pytest.mark.asyncio +@pytest.mark.parametrize("mode", ["sync", "async"]) +@pytest.mark.parametrize( + ("parts", "is_messages_api", "status_code"), + [ + pytest.param( + ( + _VLLM_EVENTS[1], + _sse( + { + "error": { + "message": "CUDA out of memory while decoding", + "type": "InternalServerError", + "code": 500, + } + } + ) + + "data: [DONE]\n\n", + ), + True, + 500, + id="vllm-500-error-event-shares-a-part-with-done", + ), + pytest.param( + ( + _VLLM_EVENTS[1], + _sse( + {"error": {"message": "CUDA out of memory while decoding", "type": "BadRequestError", "code": 400}} + ), + "data: [DONE]\n\n", + ), + True, + 500, + id="vllm-400-error-event-in-its-own-part", + ), + pytest.param( + ( + _VLLM_EVENTS[1], + _sse( + { + "object": "error", + "message": "CUDA out of memory while decoding", + "type": "BadRequestError", + "code": 400, + } + ), + ), + True, + 500, + id="legacy-vllm-flat-error-event", + ), + pytest.param( + ( + _VLLM_EVENTS[1], + _sse({"error": {"message": "CUDA out of memory while decoding", "http_status_code": 422}}), + ), + True, + 422, + id="tgi-messages-api-error-event", + ), + pytest.param( + ( + _VLLM_EVENTS[1], + _sse({"error": {"message": "CUDA out of memory while decoding", "http_status_code": 424}}), + ), + True, + 500, + id="tgi-messages-api-generation-error-event", + ), + pytest.param( + ( + _VLLM_EVENTS[1], + _sse( + {"error": {"message": "CUDA out of memory while decoding", "type": "RateLimitError", "code": 429}} + ), + ), + True, + 429, + id="vllm-429-error-event", + ), + pytest.param( + (_VLLM_EVENTS[1], _sse({"error": {"message": "CUDA out of memory while decoding", "code": "oom"}})), + True, + 500, + id="error-event-without-a-status", + ), + pytest.param( + ( + _TGI_EVENTS[0] + + f"data:{json.dumps({'error': 'CUDA out of memory while decoding', 'error_type': 'generation'})}\n\n", + ), + False, + 500, + id="tgi-generation-error-event-shares-a-part-with-a-token", + ), + pytest.param( + ( + _TGI_EVENTS[0], + f"data:{json.dumps({'error': 'CUDA out of memory while decoding', 'error_type': 'overloaded'})}\n\n", + ), + False, + 429, + id="tgi-overloaded-error-event", + ), + pytest.param( + ( + _TGI_EVENTS[0], + f"data:{json.dumps({'error': 'CUDA out of memory while decoding', 'error_type': 'incomplete_generation'})}\n\n", + ), + False, + 500, + id="tgi-incomplete-generation-error-event", + ), + ], +) +async def test_container_error_event_raises_with_its_message_and_status_after_the_chunks_before_it( + parts: tuple[str, ...], is_messages_api: bool, status_code: int, mode: str +): + stream: Final = _stream_frames(tuple(map(_payload_part, parts)), is_messages_api, mode) + + assert _text(await anext(stream), is_messages_api) == "Hél" + with pytest.raises(SagemakerError, match="CUDA out of memory while decoding") as exc_info: + await anext(stream) + assert exc_info.value.status_code == status_code + + +@pytest.mark.asyncio +@pytest.mark.parametrize("mode", ["sync", "async"]) +@pytest.mark.parametrize( + ("last_record", "message"), + [ + pytest.param( + { + "token": {"id": 2, "text": "", "log_prob": 0.0, "error_msg": "CUDA out of memory while decoding"}, + "generated_text": "Hél", + "details": {"finish_reason": "error"}, + }, + "SageMaker endpoint streamed a failed generation: CUDA out of memory while decoding", + id="token-error-message", + ), + pytest.param( + { + "token": {"id": 2, "text": "", "log_prob": 0.0}, + "generated_text": "Hél", + "details": {"finish_reason": "error"}, + }, + "SageMaker endpoint streamed a failed generation: no error message", + id="error-finish-without-a-message", + ), + ], +) +async def test_lmi_failed_generation_raises_after_the_chunks_before_it( + last_record: Mapping[str, object], message: str, mode: str +): + lines: Final = "".join( + f"{json.dumps(record, ensure_ascii=False)}\n" + for record in ({"token": {"id": 1, "text": "Hél", "log_prob": -0.1}}, last_record) + ) + stream: Final = _stream_frames((_payload_part(lines),), False, mode) + + assert _text(await anext(stream), False) == "Hél" + with pytest.raises(SagemakerError) as exc_info: + await anext(stream) + assert exc_info.value.status_code == 500 + assert exc_info.value.message == message + + +@pytest.mark.asyncio +@pytest.mark.parametrize("mode", ["sync", "async"]) +async def test_model_stream_error_raises_after_the_chunks_before_it(mode: str): + frames: Final = ( + _payload_part(_VLLM_EVENTS[1]), + _frame( + _MODEL_STREAM_ERROR_HEADERS, + json.dumps({"Message": "container exited", "ErrorCode": "ModelInvocationTimeExceeded"}), + ), + _payload_part(_VLLM_EVENTS[2]), + ) + stream: Final = _stream_frames(frames, True, mode) + + assert _text(await anext(stream), True) == "Hél" + with pytest.raises(SagemakerError) as exc_info: + await anext(stream) + assert exc_info.value.status_code == 500 + assert exc_info.value.message == ( + "SageMaker stream failed with ModelStreamError (ModelInvocationTimeExceeded): container exited" + ) + + +@pytest.mark.asyncio +@pytest.mark.parametrize("mode", ["sync", "async"]) +@pytest.mark.parametrize( + ("parts", "is_messages_api"), + [ + pytest.param( + tuple( + _vllm_chunk([{"index": 0, "delta": {"content": text}, "finish_reason": None}], error=None) + for text in ("Hél", "lo 👋") + ), + True, + id="vllm-chunks-with-null-error", + ), + pytest.param( + tuple( + f"data:{json.dumps({'index': 0, 'token': {'text': text}, 'error': None}, ensure_ascii=False)}\n\n" + for text in ("Hél", "lo 👋") + ), + False, + id="tgi-tokens-with-null-error", + ), + ], +) +async def test_chunk_with_a_null_error_field_is_delivered( + parts: tuple[str, ...], is_messages_api: bool, mode: str, caplog: pytest.LogCaptureFixture +): + with caplog.at_level(logging.WARNING, logger="LiteLLM"): + chunks: Final = await _decode(parts, is_messages_api=is_messages_api, mode=mode) + + assert "".join(_text(chunk, is_messages_api) or "" for chunk in chunks) == "Héllo 👋" + assert caplog.records == [] + + +@pytest.mark.asyncio +@pytest.mark.parametrize("mode", ["sync", "async"]) +async def test_record_that_is_not_a_chunk_is_logged_and_skipped(mode: str, caplog: pytest.LogCaptureFixture): + with caplog.at_level(logging.WARNING, logger="LiteLLM"): + chunks: Final = await _decode( + (_VLLM_EVENTS[1], _sse({"object": "keepalive", "detail": "still decoding"}), _VLLM_EVENTS[2]), + is_messages_api=True, + mode=mode, + ) + + assert "".join(chunk.choices[0].delta.content for chunk in chunks) == "Héllo 👋" + assert [record.levelno for record in caplog.records] == [logging.ERROR] + assert "['detail', 'object']" in caplog.records[0].getMessage() + assert "still decoding" not in caplog.records[0].getMessage() + + class TestSagemakerTransform: def setup_method(self): self.config = SagemakerConfig() diff --git a/tests/unit/llms/test_file_search_responses.py b/tests/unit/llms/test_file_search_responses.py index 9d2a5dbaf59..b2cbcd4a6dd 100644 --- a/tests/unit/llms/test_file_search_responses.py +++ b/tests/unit/llms/test_file_search_responses.py @@ -573,11 +573,11 @@ class TestEmulatedFileSearchHandler: def test_H1_file_search_replaced_with_function_tool(self): from litellm.responses.file_search.emulated_handler import ( - _replace_file_search_tools, + replace_file_search_tools, ) tools = [{"type": "file_search", "vector_store_ids": ["vs_abc", "vs_def"]}] - new_tools, vs_ids = _replace_file_search_tools(tools) + new_tools, vs_ids = replace_file_search_tools(tools) assert vs_ids == ["vs_abc", "vs_def"] assert len(new_tools) == 1 @@ -590,14 +590,14 @@ class TestEmulatedFileSearchHandler: def test_H2_non_file_search_tools_preserved(self): from litellm.responses.file_search.emulated_handler import ( - _replace_file_search_tools, + replace_file_search_tools, ) tools = [ {"type": "web_search"}, {"type": "file_search", "vector_store_ids": ["vs_abc"]}, ] - new_tools, vs_ids = _replace_file_search_tools(tools) + new_tools, vs_ids = replace_file_search_tools(tools) assert len(new_tools) == 2 # web_search + generated function tool assert new_tools[0]["type"] == "web_search" @@ -605,22 +605,22 @@ class TestEmulatedFileSearchHandler: def test_H3_no_file_search_tools_returns_unchanged(self): from litellm.responses.file_search.emulated_handler import ( - _replace_file_search_tools, + replace_file_search_tools, ) tools = [{"type": "web_search"}] - new_tools, vs_ids = _replace_file_search_tools(tools) + new_tools, vs_ids = replace_file_search_tools(tools) assert vs_ids == [] assert new_tools == [{"type": "web_search"}] def test_H4_empty_vector_store_ids_no_function_tool(self): from litellm.responses.file_search.emulated_handler import ( - _replace_file_search_tools, + replace_file_search_tools, ) tools = [{"type": "file_search", "vector_store_ids": []}] - new_tools, vs_ids = _replace_file_search_tools(tools) + new_tools, vs_ids = replace_file_search_tools(tools) assert vs_ids == [] assert new_tools == [] # no function tool added without store IDs diff --git a/tests/unit/llms/vertex_ai/context_caching/conftest.py b/tests/unit/llms/vertex_ai/context_caching/conftest.py new file mode 100644 index 00000000000..9c80c964608 --- /dev/null +++ b/tests/unit/llms/vertex_ai/context_caching/conftest.py @@ -0,0 +1,10 @@ +import pytest + +from litellm.llms.vertex_ai.context_caching.known_cached_contents import known_cached_contents + + +@pytest.fixture(autouse=True) +def _forget_known_cached_contents(): + known_cached_contents.clear() + yield + known_cached_contents.clear() diff --git a/tests/unit/llms/vertex_ai/context_caching/test_known_cached_contents.py b/tests/unit/llms/vertex_ai/context_caching/test_known_cached_contents.py new file mode 100644 index 00000000000..0c5c3facb56 --- /dev/null +++ b/tests/unit/llms/vertex_ai/context_caching/test_known_cached_contents.py @@ -0,0 +1,663 @@ +import asyncio +import json +import threading +from datetime import datetime, timezone +from typing import Final +from unittest.mock import AsyncMock, MagicMock, patch + +import httpx +import openai +import pytest +import respx + +import litellm + +from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler +from litellm.llms.vertex_ai.common_utils import VertexAIError +from litellm.llms.vertex_ai.context_caching import vertex_ai_context_caching +from litellm.llms.vertex_ai.context_caching.known_cached_contents import KnownCachedContents, parse_expire_time +from litellm.llms.vertex_ai.context_caching.vertex_ai_context_caching import ContextCachingEndpoints +from litellm.utils import get_prompt_cache_min_tokens + +_REGISTRY_MODULE: Final = "litellm.llms.vertex_ai.context_caching.known_cached_contents" +_SCOPE: Final = ("https://vertex.test/v1/projects/p/locations/us/cachedContents", "") +_NOW: Final = datetime(2026, 10, 14, 18, 0, tzinfo=timezone.utc).timestamp() +_FAR_FUTURE: Final = "2100-01-01T00:00:00.123456789Z" +_GATEWAY: Final = "https://gateway.test/vertex" +_PREFIX_REPEATS: Final = max( + get_prompt_cache_min_tokens(model=f"{provider}/gemini-3.1-pro") for provider in ("vertex_ai", "gemini") +) + + +@pytest.fixture +def clock() -> MagicMock: + return MagicMock(return_value=_NOW) + + +@pytest.fixture +def endpoints(clock: MagicMock) -> ContextCachingEndpoints: + return ContextCachingEndpoints(known_caches=KnownCachedContents(clock=clock)) + + +def _expire_time(seconds_from_now: float) -> str: + expires: Final = datetime.fromtimestamp(_NOW + seconds_from_now, timezone.utc) + return expires.strftime("%Y-%m-%dT%H:%M:%S.%f") + "123Z" + + +def _messages(label: str = "shared") -> list: + text: Final = f"{label} cacheable prefix " * _PREFIX_REPEATS + return [ + {"role": "system", "content": [{"type": "text", "text": text, "cache_control": {"type": "ephemeral"}}]}, + {"role": "user", "content": "question"}, + ] + + +def _response(body: dict) -> MagicMock: + return MagicMock(json=lambda: body) + + +def _created(name: str, expire_time: str | None) -> dict: + body: Final = {"name": name, "usageMetadata": {"totalTokenCount": 2048}} + return body if expire_time is None else {**body, "expireTime": expire_time} + + +def _sync_call( + endpoints: ContextCachingEndpoints, + client: HTTPHandler, + api_key: str = "k", + custom_llm_provider: str = "vertex_ai", + messages=None, + extra_headers: dict | None = None, + api_base: str | None = None, + vertex_project: str = "p", +): + return endpoints.check_and_create_cache( + extra_headers=extra_headers, + messages=messages or _messages(), + optional_params={}, + api_key=api_key, + api_base=api_base, + model="gemini-3.1-pro", + client=client, + timeout=30.0, + logging_obj=MagicMock(model_call_details={}), + custom_llm_provider=custom_llm_provider, + vertex_project=vertex_project, + vertex_location="us", + vertex_auth_header="token", + ) + + +async def _async_call( + endpoints: ContextCachingEndpoints, + client: AsyncHTTPHandler, + timeout: float | httpx.Timeout = 30.0, + api_base: str | None = None, + vertex_project: str = "p", +): + return await endpoints.async_check_and_create_cache( + messages=_messages(), + optional_params={}, + api_key="k", + api_base=api_base, + model="gemini-3.1-pro", + client=client, + timeout=timeout, + logging_obj=MagicMock(model_call_details={}), + custom_llm_provider="vertex_ai", + vertex_project=vertex_project, + vertex_location="us", + vertex_auth_header="token", + ) + + +def test_created_cache_is_reused_without_listing(endpoints: ContextCachingEndpoints): + client: Final = MagicMock(spec=HTTPHandler) + client.get.return_value = _response({}) + client.post.return_value = _response(_created("cachedContents/1", _expire_time(60))) + + assert _sync_call(endpoints, client)[2] == "cachedContents/1" + assert _sync_call(endpoints, client)[2] == "cachedContents/1" + + assert client.get.call_count == 1 + assert client.post.call_count == 1 + + +def test_listed_cache_is_reused_without_listing_again(endpoints: ContextCachingEndpoints): + client: Final = MagicMock(spec=HTTPHandler) + key: Final = vertex_ai_context_caching.local_cache_obj.get_cache_key( + messages=_messages()[:1], tools=None, tool_choice=None, model="gemini-3.1-pro" + ) + client.get.return_value = _response( + {"cachedContents": [{"name": "cachedContents/listed", "displayName": key, "expireTime": _expire_time(60)}]} + ) + + assert _sync_call(endpoints, client)[2] == "cachedContents/listed" + assert _sync_call(endpoints, client)[2] == "cachedContents/listed" + + assert client.get.call_count == 1 + client.post.assert_not_called() + + +def test_listed_cache_past_its_expire_time_is_not_used(endpoints: ContextCachingEndpoints): + client: Final = MagicMock(spec=HTTPHandler) + key: Final = vertex_ai_context_caching.local_cache_obj.get_cache_key( + messages=_messages()[:1], tools=None, tool_choice=None, model="gemini-3.1-pro" + ) + client.get.return_value = _response( + {"cachedContents": [{"name": "cachedContents/stale", "displayName": key, "expireTime": _expire_time(-1)}]} + ) + client.post.return_value = _response(_created("cachedContents/fresh", _expire_time(60))) + + assert _sync_call(endpoints, client)[2] == "cachedContents/fresh" + + +def test_short_lived_cache_is_reused_from_the_listing(endpoints: ContextCachingEndpoints, clock: MagicMock): + client: Final = MagicMock(spec=HTTPHandler) + key: Final = vertex_ai_context_caching.local_cache_obj.get_cache_key( + messages=_messages()[:1], tools=None, tool_choice=None, model="gemini-3.1-pro" + ) + client.get.side_effect = [ + _response({}), + _response( + {"cachedContents": [{"name": "cachedContents/1", "displayName": key, "expireTime": _expire_time(8)}]} + ), + ] + client.post.return_value = _response(_created("cachedContents/1", _expire_time(8))) + + assert _sync_call(endpoints, client)[2] == "cachedContents/1" + clock.return_value = _NOW + 1 + assert _sync_call(endpoints, client)[2] == "cachedContents/1" + + assert client.post.call_count == 1 + + +def test_cache_without_expire_time_is_not_remembered(endpoints: ContextCachingEndpoints): + client: Final = MagicMock(spec=HTTPHandler) + client.get.return_value = _response({}) + client.post.return_value = _response(_created("cachedContents/1", None)) + + _sync_call(endpoints, client) + _sync_call(endpoints, client) + + assert client.get.call_count == 2 + + +def test_remembered_cache_is_listed_again_once_its_reuse_window_closes( + endpoints: ContextCachingEndpoints, clock: MagicMock +): + client: Final = MagicMock(spec=HTTPHandler) + key: Final = vertex_ai_context_caching.local_cache_obj.get_cache_key( + messages=_messages()[:1], tools=None, tool_choice=None, model="gemini-3.1-pro" + ) + client.get.side_effect = [ + _response({}), + _response( + {"cachedContents": [{"name": "cachedContents/listed", "displayName": key, "expireTime": _expire_time(600)}]} + ), + ] + client.post.return_value = _response(_created("cachedContents/1", _expire_time(60))) + assert _sync_call(endpoints, client)[2] == "cachedContents/1" + + clock.return_value = _NOW + 55 + assert _sync_call(endpoints, client)[2] == "cachedContents/listed" + + +def test_gemini_caches_are_not_shared_across_api_keys(endpoints: ContextCachingEndpoints): + client: Final = MagicMock(spec=HTTPHandler) + client.get.return_value = _response({}) + client.post.return_value = _response(_created("cachedContents/1", _expire_time(60))) + + _sync_call(endpoints, client, api_key="key-a", custom_llm_provider="gemini") + _sync_call(endpoints, client, api_key="key-b", custom_llm_provider="gemini") + + assert client.post.call_count == 2 + + +def test_gemini_cache_created_with_an_overridden_api_key_is_not_reused_with_the_configured_key( + endpoints: ContextCachingEndpoints, +): + client: Final = MagicMock(spec=HTTPHandler) + client.get.return_value = _response({}) + client.post.side_effect = [ + _response(_created("cachedContents/caller-project", _expire_time(60))), + _response(_created("cachedContents/deployment-project", _expire_time(60))), + ] + + caller: Final = _sync_call( + endpoints, + client, + api_key="deployment-key", + custom_llm_provider="gemini", + extra_headers={"X-Goog-Api-Key": "caller-key"}, + ) + configured: Final = _sync_call(endpoints, client, api_key="deployment-key", custom_llm_provider="gemini") + + assert (caller[2], configured[2]) == ("cachedContents/caller-project", "cachedContents/deployment-project") + + +def test_vertex_caches_behind_one_custom_api_base_are_not_shared_across_projects(endpoints: ContextCachingEndpoints): + client: Final = MagicMock(spec=HTTPHandler) + client.get.return_value = _response({}) + client.post.side_effect = [ + _response(_created("cachedContents/project-a", _expire_time(60))), + _response(_created("cachedContents/project-b", _expire_time(60))), + ] + + sent: Final = [ + _sync_call(endpoints, client, api_base=_GATEWAY, vertex_project=project)[2] + for project in ("project-a", "project-b", "project-a") + ] + + assert sent == ["cachedContents/project-a", "cachedContents/project-b", "cachedContents/project-a"] + + +@pytest.mark.asyncio +async def test_async_vertex_caches_behind_one_custom_api_base_are_not_shared_across_projects( + endpoints: ContextCachingEndpoints, +): + client: Final = MagicMock(spec=AsyncHTTPHandler) + client.get = AsyncMock(return_value=_response({})) + client.post = AsyncMock( + side_effect=[ + _response(_created("cachedContents/project-a", _expire_time(60))), + _response(_created("cachedContents/project-b", _expire_time(60))), + ] + ) + + sent: Final = [ + (await _async_call(endpoints, client, api_base=_GATEWAY, vertex_project=project))[2] + for project in ("project-a", "project-b", "project-a") + ] + + assert sent == ["cachedContents/project-a", "cachedContents/project-b", "cachedContents/project-a"] + + +def test_different_prefixes_do_not_share_a_cache(endpoints: ContextCachingEndpoints): + client: Final = MagicMock(spec=HTTPHandler) + client.get.return_value = _response({}) + client.post.side_effect = [ + _response(_created("cachedContents/a", _expire_time(60))), + _response(_created("cachedContents/b", _expire_time(60))), + ] + + assert _sync_call(endpoints, client, messages=_messages("first"))[2] == "cachedContents/a" + assert _sync_call(endpoints, client, messages=_messages("second"))[2] == "cachedContents/b" + + +@pytest.mark.asyncio +async def test_concurrent_requests_for_one_prefix_list_and_create_once(endpoints: ContextCachingEndpoints): + client: Final = MagicMock(spec=AsyncHTTPHandler) + + async def slow_list(**_): + await asyncio.sleep(0.01) + return _response({}) + + client.get = AsyncMock(side_effect=slow_list) + client.post = AsyncMock(return_value=_response(_created("cachedContents/1", _expire_time(60)))) + + results: Final = await asyncio.gather(*(_async_call(endpoints, client) for _ in range(5))) + + assert {result[2] for result in results} == {"cachedContents/1"} + assert client.get.await_count == 1 + assert client.post.await_count == 1 + + +@pytest.mark.asyncio +async def test_async_created_cache_is_reused_by_a_later_request(endpoints: ContextCachingEndpoints): + client: Final = MagicMock(spec=AsyncHTTPHandler) + client.get = AsyncMock(return_value=_response({})) + client.post = AsyncMock(return_value=_response(_created("cachedContents/1", _expire_time(60)))) + + first: Final = await _async_call(endpoints, client) + client.get = AsyncMock(side_effect=AssertionError("a known cache must not be listed again")) + second: Final = await _async_call(endpoints, client) + + assert (first[2], second[2]) == ("cachedContents/1", "cachedContents/1") + + +@pytest.mark.asyncio +async def test_async_listed_cache_past_its_expire_time_is_not_used(endpoints: ContextCachingEndpoints): + client: Final = MagicMock(spec=AsyncHTTPHandler) + key: Final = vertex_ai_context_caching.local_cache_obj.get_cache_key( + messages=_messages()[:1], tools=None, tool_choice=None, model="gemini-3.1-pro" + ) + client.get = AsyncMock( + return_value=_response( + {"cachedContents": [{"name": "cachedContents/stale", "displayName": key, "expireTime": _expire_time(-1)}]} + ) + ) + client.post = AsyncMock(return_value=_response(_created("cachedContents/fresh", _expire_time(60)))) + + assert (await _async_call(endpoints, client))[2] == "cachedContents/fresh" + + +@pytest.mark.asyncio +async def test_async_create_http_error_surfaces_its_status_code(endpoints: ContextCachingEndpoints): + client: Final = MagicMock(spec=AsyncHTTPHandler) + client.get = AsyncMock(return_value=_response({})) + request: Final = httpx.Request("POST", "https://vertex.test/v1/projects/p/locations/us/cachedContents") + failed: Final = httpx.Response(429, request=request, text="RESOURCE_EXHAUSTED") + client.post = AsyncMock(return_value=failed) + + with pytest.raises(VertexAIError) as raised: + await _async_call(endpoints, client) + + assert raised.value.status_code == 429 + + +@pytest.mark.asyncio +async def test_waiters_resolve_on_their_own_when_the_first_request_fails(endpoints: ContextCachingEndpoints): + client: Final = MagicMock(spec=AsyncHTTPHandler) + + async def slow_list(**_): + await asyncio.sleep(0.01) + return _response({}) + + client.get = AsyncMock(side_effect=slow_list) + client.post = AsyncMock( + side_effect=[ + VertexAIError(status_code=500, message="create failed"), + _response(_created("cachedContents/2", _expire_time(60))), + ] + ) + + results: Final = await asyncio.gather( + _async_call(endpoints, client), _async_call(endpoints, client), return_exceptions=True + ) + + assert isinstance(results[0], VertexAIError) + assert results[1][2] == "cachedContents/2" + + +@pytest.mark.parametrize("waiter_timeout", [0.05, httpx.Timeout(30.0, read=0.05)]) +@pytest.mark.asyncio +async def test_waiter_resolves_on_its_own_once_its_timeout_passes( + endpoints: ContextCachingEndpoints, waiter_timeout: float | httpx.Timeout +): + client: Final = MagicMock(spec=AsyncHTTPHandler) + + async def slow_list(**_): + await asyncio.sleep(0.5) + return _response({}) + + client.get = AsyncMock(side_effect=slow_list) + client.post = AsyncMock(return_value=_response(_created("cachedContents/1", _expire_time(60)))) + + first, waiter = await asyncio.gather(_async_call(endpoints, client), _async_call(endpoints, client, waiter_timeout)) + + assert (first[2], waiter[2]) == ("cachedContents/1", "cachedContents/1") + assert client.get.await_count == 2 + + +def test_parse_expire_time_accepts_nanosecond_precision(): + assert parse_expire_time("2026-10-14T18:06:21.123456789Z") == pytest.approx( + datetime(2026, 10, 14, 18, 6, 21, 123456, tzinfo=timezone.utc).timestamp() + ) + assert ( + parse_expire_time("2026-10-14T18:06:21Z") == datetime(2026, 10, 14, 18, 6, 21, tzinfo=timezone.utc).timestamp() + ) + assert parse_expire_time("not a time") is None + assert parse_expire_time(None) is None + + +def test_parse_expire_time_reads_a_missing_offset_as_utc(): + assert ( + parse_expire_time("2026-10-14T18:06:21") == datetime(2026, 10, 14, 18, 6, 21, tzinfo=timezone.utc).timestamp() + ) + + +def test_cache_expiring_within_the_margin_is_not_remembered(): + known: Final = KnownCachedContents(clock=lambda: _NOW) + known.remember(_SCOPE, "key", "cachedContents/soon", _expire_time(3)) + + assert known.get(_SCOPE, "key") is None + + +def test_registry_is_bounded(): + known: Final = KnownCachedContents(clock=lambda: _NOW) + with patch(f"{_REGISTRY_MODULE}.MAX_KNOWN_CACHED_CONTENTS", 3): + for index in range(5): + known.remember(_SCOPE, f"key-{index}", f"cachedContents/{index}", _expire_time(60)) + + assert known.get(_SCOPE, "key-0") is None + assert known.get(_SCOPE, "key-4") == "cachedContents/4" + + +def _generated(stream: bool) -> httpx.Response: + body: Final = { + "candidates": [{"content": {"role": "model", "parts": [{"text": "ok"}]}, "finishReason": "STOP"}], + "usageMetadata": {"promptTokenCount": 10, "candidatesTokenCount": 1, "totalTokenCount": 11}, + } + if stream: + return httpx.Response(200, text=f"data: {json.dumps(body)}\n\n", headers={"content-type": "text/event-stream"}) + return httpx.Response(200, json=body) + + +def _rejected(status_code: int, message: str) -> httpx.Response: + return httpx.Response(status_code, json={"error": {"code": status_code, "message": message}}) + + +async def _complete(sync_mode: bool, stream: bool, **kwargs) -> str: + request: Final = {"model": "gemini/gemini-3.1-pro", "messages": _messages(), "stream": stream, **kwargs} + if sync_mode: + response = litellm.completion(**request) + if stream: + return "".join(chunk.choices[0].delta.content or "" for chunk in response) + return response.choices[0].message.content + response = await litellm.acompletion(**request) + if stream: + return "".join([chunk.choices[0].delta.content or "" async for chunk in response]) + return response.choices[0].message.content + + +@pytest.mark.parametrize("sync_mode", [True, False]) +@pytest.mark.parametrize("stream", [True, False]) +@pytest.mark.asyncio +async def test_rejected_cache_is_replaced_when_a_request_param_cannot_be_deep_copied( + respx_mock: respx.MockRouter, + fake_provider_credentials: None, + monkeypatch: pytest.MonkeyPatch, + sync_mode: bool, + stream: bool, +) -> None: + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + respx_mock.get(url__regex=r".*/cachedContents.*").mock(return_value=httpx.Response(200, json={})) + respx_mock.post(url__regex=r".*/cachedContents$").mock( + side_effect=[ + httpx.Response(200, json=_created("cachedContents/deleted", _FAR_FUTURE)), + httpx.Response(200, json=_created("cachedContents/fresh", _FAR_FUTURE)), + ] + ) + generate_route: Final = respx_mock.post(url__regex=r".*:(stream)?[gG]enerateContent.*").mock( + side_effect=[_generated(stream), _rejected(404, "CachedContent not found"), _generated(stream)] + ) + lock: Final = threading.Lock() + + assert await _complete(sync_mode, stream, lock_holder=lock) == "ok" + assert await _complete(sync_mode, stream, lock_holder=lock) == "ok" + + sent: Final = [json.loads(call.request.content)["cachedContent"] for call in generate_route.calls] + assert sent == ["cachedContents/deleted", "cachedContents/deleted", "cachedContents/fresh"] + + +@pytest.mark.parametrize("sync_mode", [True, False]) +@pytest.mark.parametrize("stream", [True, False]) +@pytest.mark.parametrize( + ("status_code", "message", "replaced"), + [ + (400, "Invalid resource state for cache content 4484391867902853120.", True), + (403, "CachedContent not found (or permission denied)", True), + (404, "CachedContent not found", True), + (400, "Invalid value at 'generation_config.temperature'", False), + (500, "CachedContent not found", False), + ], +) +@pytest.mark.asyncio +async def test_remembered_cache_rejected_by_generate_content_is_replaced_within_the_same_call( + respx_mock: respx.MockRouter, + fake_provider_credentials: None, + monkeypatch: pytest.MonkeyPatch, + sync_mode: bool, + stream: bool, + status_code: int, + message: str, + replaced: bool, +) -> None: + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + list_route: Final = respx_mock.get(url__regex=r".*/cachedContents.*").mock( + return_value=httpx.Response(200, json={}) + ) + respx_mock.post(url__regex=r".*/cachedContents$").mock( + side_effect=[ + httpx.Response(200, json=_created("cachedContents/deleted", _FAR_FUTURE)), + httpx.Response(200, json=_created("cachedContents/fresh", _FAR_FUTURE)), + ] + ) + generate_route: Final = respx_mock.post(url__regex=r".*:(stream)?[gG]enerateContent.*").mock( + side_effect=[_generated(stream), _rejected(status_code, message), _generated(stream)] + ) + logged: Final[list[dict]] = [] + + assert await _complete(sync_mode, stream) == "ok" + if replaced: + assert await _complete(sync_mode, stream, logger_fn=logged.append) == "ok" + else: + with pytest.raises(openai.APIStatusError): + await _complete(sync_mode, stream, logger_fn=logged.append) + + sent: Final = [json.loads(call.request.content)["cachedContent"] for call in generate_route.calls] + assert sent == ["cachedContents/deleted", "cachedContents/deleted"] + (["cachedContents/fresh"] if replaced else []) + assert list_route.call_count == (2 if replaced else 1) + assert "enerateContent" in logged[-1]["litellm_params"]["api_base"] + + +@pytest.mark.parametrize("sync_mode", [True, False]) +@pytest.mark.parametrize("stream", [True, False]) +@pytest.mark.parametrize( + ("status_code", "message", "forgotten"), + [ + (400, "Invalid value at 'generation_config.temperature'", True), + ( + 400, + "Tool config, tools and system instruction should not be set in therequest when using cached content.", + True, + ), + ( + 400, + "CachedContent can not be used with GenerateContent request setting system_instruction, tools or tool_config.", + True, + ), + (404, "Requested entity was not found.", True), + (429, "Resource has been exhausted (e.g. check quota).", False), + (500, "Internal error encountered.", False), + ], +) +@pytest.mark.asyncio +async def test_error_that_does_not_name_a_missing_cache_is_not_retried( + respx_mock: respx.MockRouter, + fake_provider_credentials: None, + monkeypatch: pytest.MonkeyPatch, + sync_mode: bool, + stream: bool, + status_code: int, + message: str, + forgotten: bool, +) -> None: + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + list_route: Final = respx_mock.get(url__regex=r".*/cachedContents.*").mock( + return_value=httpx.Response(200, json={}) + ) + respx_mock.post(url__regex=r".*/cachedContents$").mock( + side_effect=[ + httpx.Response(200, json=_created("cachedContents/first", _FAR_FUTURE)), + httpx.Response(200, json=_created("cachedContents/second", _FAR_FUTURE)), + ] + ) + generate_route: Final = respx_mock.post(url__regex=r".*:(stream)?[gG]enerateContent.*").mock( + side_effect=[_generated(stream), _rejected(status_code, message), _generated(stream)] + ) + + assert await _complete(sync_mode, stream) == "ok" + with pytest.raises(openai.APIStatusError): + await _complete(sync_mode, stream) + assert await _complete(sync_mode, stream) == "ok" + + third: Final = "cachedContents/second" if forgotten else "cachedContents/first" + assert [json.loads(call.request.content)["cachedContent"] for call in generate_route.calls] == [ + "cachedContents/first", + "cachedContents/first", + third, + ] + assert list_route.call_count == (2 if forgotten else 1) + + +@pytest.mark.parametrize("sync_mode", [True, False]) +@pytest.mark.parametrize("stream", [True, False]) +@pytest.mark.asyncio +async def test_rejected_caller_supplied_cached_content_is_not_sent_again( + respx_mock: respx.MockRouter, + fake_provider_credentials: None, + monkeypatch: pytest.MonkeyPatch, + sync_mode: bool, + stream: bool, +) -> None: + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + list_route: Final = respx_mock.get(url__regex=r".*/cachedContents.*").mock( + return_value=httpx.Response(200, json={}) + ) + generate_route: Final = respx_mock.post(url__regex=r".*:(stream)?[gG]enerateContent.*").mock( + side_effect=[_rejected(404, "CachedContent not found"), _generated(stream)] + ) + + with pytest.raises(openai.APIStatusError): + await _complete(sync_mode, stream, cached_content="cachedContents/callers") + + assert [json.loads(call.request.content)["cachedContent"] for call in generate_route.calls] == [ + "cachedContents/callers" + ] + assert list_route.call_count == 0 + + +def _cut_off_stream() -> httpx.Response: + body: Final = { + "candidates": [ + { + "content": {"role": "model", "parts": [{"text": "ok"}]}, + "finishReason": "CONTINUATION", + "continuationToken": "dG9rLTE=", + } + ], + "usageMetadata": {"promptTokenCount": 10, "candidatesTokenCount": 1, "totalTokenCount": 11}, + } + return httpx.Response(200, text=f"data: {json.dumps(body)}\n\n", headers={"content-type": "text/event-stream"}) + + +@pytest.mark.parametrize("sync_mode", [True, False]) +@pytest.mark.asyncio +async def test_cache_rejected_on_a_resume_hop_is_not_sent_again( + respx_mock: respx.MockRouter, + fake_provider_credentials: None, + monkeypatch: pytest.MonkeyPatch, + sync_mode: bool, +) -> None: + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + list_route: Final = respx_mock.get(url__regex=r".*/cachedContents.*").mock( + return_value=httpx.Response(200, json={}) + ) + respx_mock.post(url__regex=r".*/cachedContents$").mock( + side_effect=[ + httpx.Response(200, json=_created("cachedContents/deleted", _FAR_FUTURE)), + httpx.Response(200, json=_created("cachedContents/fresh", _FAR_FUTURE)), + ] + ) + generate_route: Final = respx_mock.post(url__regex=r".*:streamGenerateContent.*").mock( + side_effect=[_cut_off_stream(), _rejected(404, "CachedContent not found"), _generated(True)] + ) + + await _complete(sync_mode, True, max_tokens=100_000) + await _complete(sync_mode, True, max_tokens=100_000) + + sent: Final = [json.loads(call.request.content)["cachedContent"] for call in generate_route.calls] + assert sent == ["cachedContents/deleted", "cachedContents/deleted", "cachedContents/fresh"] + assert list_route.call_count == 2 diff --git a/tests/unit/llms/vertex_ai/count_tokens/test_context.py b/tests/unit/llms/vertex_ai/count_tokens/test_context.py index 405b7234c81..a1643f0f699 100644 --- a/tests/unit/llms/vertex_ai/count_tokens/test_context.py +++ b/tests/unit/llms/vertex_ai/count_tokens/test_context.py @@ -1,12 +1,12 @@ import asyncio import base64 import logging -import time import uuid from collections.abc import Generator from contextlib import contextmanager +from dataclasses import dataclass, field from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer -from threading import Thread +from threading import Event, Thread from typing import Final, Literal from unittest.mock import patch @@ -73,7 +73,7 @@ _FUNCTION_DECLARATION: Final = { ids=("anthropic", "openai-chat", "responses"), ) def test_function_tool_shapes_map_to_vertex_declarations(tool: JsonValue) -> None: - context: Final = vertex_gemini_count_context(system=None, tools=[tool]) + context: Final = vertex_gemini_count_context(model="gemini-2.5-flash", system=None, tools=[tool]) assert isinstance(context, VertexGeminiCountContext) assert context.tools == (_FUNCTION_DECLARATION,) @@ -82,7 +82,7 @@ def test_function_tool_shapes_map_to_vertex_declarations(tool: JsonValue) -> Non def test_long_anthropic_tool_name_is_truncated_for_vertex() -> None: name: Final = "mcp__docs__" + "a" * 70 - context: Final = vertex_gemini_count_context( + context: Final = vertex_gemini_count_context(model="gemini-2.5-flash", system=None, tools=[{"name": name, "description": "Look up a value", "input_schema": _SCHEMA}], ) @@ -104,7 +104,7 @@ def test_long_anthropic_tool_name_is_truncated_for_vertex() -> None: def test_64_character_anthropic_tool_name_is_unchanged_for_vertex() -> None: name: Final = "mcp__docs__" + "a" * 53 - context: Final = vertex_gemini_count_context( + context: Final = vertex_gemini_count_context(model="gemini-2.5-flash", system=None, tools=[{"name": name, "input_schema": _SCHEMA}], ) @@ -115,7 +115,7 @@ def test_64_character_anthropic_tool_name_is_unchanged_for_vertex() -> None: def test_long_openai_chat_tool_name_is_unchanged_for_vertex() -> None: name: Final = "mcp__docs__" + "a" * 70 - context: Final = vertex_gemini_count_context( + context: Final = vertex_gemini_count_context(model="gemini-2.5-flash", system=None, tools=[{"type": "function", "function": {"name": name, "parameters": _SCHEMA}}], ) @@ -125,7 +125,7 @@ def test_long_openai_chat_tool_name_is_unchanged_for_vertex() -> None: def test_unknown_tools_are_omitted() -> None: - context: Final = vertex_gemini_count_context( + context: Final = vertex_gemini_count_context(model="gemini-2.5-flash", system=None, tools=[{"type": "web_search_preview"}, {"type": "computer_use"}], ) @@ -135,7 +135,7 @@ def test_unknown_tools_are_omitted() -> None: def test_text_block_system_instruction_keeps_one_part_per_block() -> None: - context: Final = vertex_gemini_count_context( + context: Final = vertex_gemini_count_context(model="gemini-2.5-flash", system=[{"type": "text", "text": "First instruction."}, {"type": "text", "text": "Second instruction."}], tools=None, ) @@ -145,14 +145,14 @@ def test_text_block_system_instruction_keeps_one_part_per_block() -> None: def test_string_system_instruction_maps_to_one_part() -> None: - context: Final = vertex_gemini_count_context(system="Follow this instruction.", tools=None) + context: Final = vertex_gemini_count_context(model="gemini-2.5-flash", system="Follow this instruction.", tools=None) assert isinstance(context, VertexGeminiCountContext) assert context.system_instruction == {"parts": ({"text": "Follow this instruction."},)} def test_non_text_system_block_returns_an_error_value() -> None: - context: Final = vertex_gemini_count_context( + context: Final = vertex_gemini_count_context(model="gemini-2.5-flash", system=[{"type": "image", "source": {"type": "base64", "data": "AAAA"}}], tools=None, ) @@ -163,7 +163,7 @@ def test_non_text_system_block_returns_an_error_value() -> None: @pytest.mark.parametrize(("system", "tools"), ((None, None), ("", None), ([], []))) def test_empty_context_is_omitted(system: JsonValue | None, tools: JsonValue | None) -> None: - context: Final = vertex_gemini_count_context(system=system, tools=tools) + context: Final = vertex_gemini_count_context(model="gemini-2.5-flash", system=system, tools=tools) assert isinstance(context, VertexGeminiCountContext) assert context.system_instruction is None @@ -185,7 +185,7 @@ def test_anthropic_tools_count_the_same_declarations_inference_sends(tool: dict[ optional_params={}, ) - context: Final = vertex_gemini_count_context(system=None, tools=[tool]) + context: Final = vertex_gemini_count_context(model="gemini-2.5-flash", system=None, tools=[tool]) assert isinstance(context, VertexGeminiCountContext) assert context.tools is not None @@ -194,6 +194,33 @@ def test_anthropic_tools_count_the_same_declarations_inference_sends(tool: dict[ ] +@pytest.mark.parametrize("model", ("gemini-3.8-flash", "gemini-2.5-flash")) +@pytest.mark.parametrize("ids", (range(3), range(10**12, 10**12 + 200)), ids=("small-enum", "past-enum-budget")) +def test_count_context_counts_the_integer_enums_inference_sends(model: str, ids: range) -> None: + tool: Final = { + "type": "function", + "function": { + "name": "open_record", + "parameters": { + "type": "object", + "properties": {"record_id": {"type": "integer", "enum": list(ids)}}, + "required": ["record_id"], + }, + }, + } + inference_params: Final = VertexGeminiConfig().map_openai_params( + non_default_params={"tools": [tool]}, optional_params={}, model=model, drop_params=False + ) + + context: Final = vertex_gemini_count_context(model=model, system=None, tools=[tool]) + + assert isinstance(context, VertexGeminiCountContext) + assert context.tools is not None + assert [tool_value["functionDeclarations"] for tool_value in context.tools] == [ + inference_tool["function_declarations"] for inference_tool in inference_params["tools"] + ] + + @pytest.mark.parametrize( "tools", ( @@ -206,7 +233,7 @@ def test_anthropic_tools_count_the_same_declarations_inference_sends(tool: dict[ ids=("not-a-list", "non-object-tool", "string-schema", "list-parameters", "malformed-property"), ) def test_invalid_tools_return_an_error_value(tools: JsonValue) -> None: - context: Final = vertex_gemini_count_context(system=None, tools=tools) + context: Final = vertex_gemini_count_context(model="gemini-2.5-flash", system=None, tools=tools) assert isinstance(context, VertexGeminiCountContextError) assert "tools" in context.error_message @@ -270,25 +297,37 @@ async def test_openai_messages_keep_their_chat_conversion(custom_llm_provider: L _PNG_BYTES: Final = base64.b64decode( "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg==" ) -_DOWNLOAD_SECONDS: Final = 0.5 +_LOOP_PROOF_TIMEOUT_SECONDS: Final = 5 -class _SlowPngHandler(BaseHTTPRequestHandler): - def do_GET(self) -> None: - time.sleep(_DOWNLOAD_SECONDS) - self.send_response(200) - self.send_header("Content-Type", "image/png") - self.send_header("Content-Length", str(len(_PNG_BYTES))) - self.end_headers() - self.wfile.write(_PNG_BYTES) +@dataclass(frozen=True, slots=True) +class _LoopProbe: + request_arrived: Event = field(default_factory=Event) + loop_ran: Event = field(default_factory=Event) + loop_ran_while_download_pending: Event = field(default_factory=Event) - def log_message(self, format: str, *args: object) -> None: - return None + +def _png_handler_waiting_for_loop(probe: _LoopProbe) -> type[BaseHTTPRequestHandler]: + class _PngHandler(BaseHTTPRequestHandler): + def do_GET(self) -> None: + probe.request_arrived.set() + if probe.loop_ran.wait(_LOOP_PROOF_TIMEOUT_SECONDS): + probe.loop_ran_while_download_pending.set() + self.send_response(200) + self.send_header("Content-Type", "image/png") + self.send_header("Content-Length", str(len(_PNG_BYTES))) + self.end_headers() + self.wfile.write(_PNG_BYTES) + + def log_message(self, format: str, *args: object) -> None: + return None + + return _PngHandler @contextmanager -def _slow_png_server() -> Generator[str, None, None]: - with ThreadingHTTPServer(("127.0.0.1", 0), _SlowPngHandler) as server: +def _png_server_waiting_for_loop(probe: _LoopProbe) -> Generator[str, None, None]: + with ThreadingHTTPServer(("127.0.0.1", 0), _png_handler_waiting_for_loop(probe)) as server: thread: Final = Thread(target=server.serve_forever, daemon=True) thread.start() try: @@ -297,10 +336,9 @@ def _slow_png_server() -> Generator[str, None, None]: server.shutdown() -async def _event_loop_wake_delay(nap_seconds: float) -> float: - started: Final = time.monotonic() - await asyncio.sleep(nap_seconds) - return time.monotonic() - started +async def _run_loop_once_download_starts(probe: _LoopProbe) -> None: + assert await asyncio.to_thread(probe.request_arrived.wait, _LOOP_PROOF_TIMEOUT_SECONDS) + probe.loop_ran.set() @pytest.mark.parametrize("custom_llm_provider", ("vertex_ai", "gemini")) @@ -308,10 +346,11 @@ async def test_remote_image_downloads_without_blocking_the_event_loop( custom_llm_provider: Literal["vertex_ai", "gemini"], monkeypatch: pytest.MonkeyPatch ) -> None: monkeypatch.setattr(litellm, "user_url_validation", False) - with _slow_png_server() as base_url: + probe: Final = _LoopProbe() + with _png_server_waiting_for_loop(probe) as base_url: image_url: Final = f"{base_url}/{uuid.uuid4().hex}.png" - wake_delay, contents = await asyncio.gather( - _event_loop_wake_delay(0.05), + _, contents = await asyncio.gather( + _run_loop_once_download_starts(probe), gemini_count_contents( ( { @@ -338,7 +377,7 @@ async def test_remote_image_downloads_without_blocking_the_event_loop( ], } ] - assert wake_delay < _DOWNLOAD_SECONDS / 2 + assert probe.loop_ran_while_download_pending.is_set() class _MissingImageHandler(BaseHTTPRequestHandler): diff --git a/tests/unit/llms/vertex_ai/files/test_vertex_ai_files_transformation.py b/tests/unit/llms/vertex_ai/files/test_vertex_ai_files_transformation.py index dde3df6fcc0..cf4a7c4cbc8 100644 --- a/tests/unit/llms/vertex_ai/files/test_vertex_ai_files_transformation.py +++ b/tests/unit/llms/vertex_ai/files/test_vertex_ai_files_transformation.py @@ -6,13 +6,16 @@ Includes tests for Vertex AI batch output transformation to OpenAI format. import json import urllib.parse from collections.abc import Mapping +from typing import Final from types import MappingProxyType from urllib.parse import parse_qs, urlparse import httpx import pytest +from pydantic import TypeAdapter from unittest.mock import MagicMock +import litellm from litellm.llms.vertex_ai.files.transformation import ( VertexAIFilesConfig, _get_litellm_batch_custom_id_from_labels, @@ -1638,6 +1641,45 @@ class TestVertexResponsesBatchInputTranslation: assert request["contents"] == [{"role": "user", "parts": [{"text": "ping"}]}] +_PRIORITY_SCHEMA: Final = { + "type": "object", + "properties": { + "level": {"type": "integer", "enum": [1, 2, 5]}, + "mode": {"type": "string", "enum": ["fast", "slow"]}, + }, +} + + +class TestVertexBatchIntegerEnums: + """ + Vertex batch reads each row's string enum values back as numbers and then fails the + row, so batch rows drop integer enums on every model, as before Gemini 3 sent them. + """ + + @pytest.mark.parametrize("model", ["gemini-3.8-flash", "vertex-batch-alias"]) + def test_tool_rows_drop_integer_enums_and_keep_string_enums(self, model: str): + (row,) = _wrap_entries( + [ + { + "custom_id": "enum-1", + "method": "POST", + "url": "/v1/chat/completions", + "body": { + "model": model, + "messages": [{"role": "user", "content": "Set priority 3"}], + "tools": [ + {"type": "function", "function": {"name": "set_priority", "parameters": _PRIORITY_SCHEMA}} + ], + }, + } + ] + ) + + properties: Final = row["request"]["tools"][0]["function_declarations"][0]["parameters"]["properties"] + assert "enum" not in properties["level"] + assert properties["mode"]["enum"] == ["fast", "slow"] + + class TestVertexEmbeddingsBatchOutputTranslation: """Vertex Gemini Embedding batch output rows must come back as OpenAI batch rows.""" @@ -1948,3 +1990,58 @@ class TestVertexEmbeddingsBatchOutputTranslation: content = json.dumps(legacy_row).encode("utf-8") assert config._try_transform_vertex_batch_output_to_openai(content) == content + + +_SAMPLING_KNOBS: Final = MappingProxyType({"temperature": 0, "top_p": 0.5, "top_k": 3}) + + +def _chat_entry(model: str, knobs: Mapping[str, object]) -> Mapping[str, object]: + return MappingProxyType( + { + "custom_id": "request-1", + "method": "POST", + "url": "/v1/chat/completions", + "body": {"model": model, "messages": [{"role": "user", "content": "hi"}], "max_tokens": 5, **knobs}, + } + ) + + +def _generation_config(row: Mapping[str, object]) -> object: + request: Final = TypeAdapter(dict[str, object]).validate_python(row["request"]) + return request["generationConfig"] + + +def _flag_model_as_no_sampling(monkeypatch: pytest.MonkeyPatch, model: str) -> None: + monkeypatch.setitem(litellm.model_cost, model, {"supports_sampling_params": False}) + + +def test_batch_row_for_a_flagged_gemini_model_raises_a_400_naming_drop_params(monkeypatch: pytest.MonkeyPatch) -> None: + """A batch file row gets the same contract as a real-time call: the knobs Google ignores are refused + with a 400 that names drop_params instead of silently vanishing from the uploaded row""" + _flag_model_as_no_sampling(monkeypatch, "gemini-zeta-9") + monkeypatch.setattr(litellm, "drop_params", False) + with pytest.raises(litellm.UnsupportedParamsError, match=r"temperature, top_p, top_k.*drop_params"): + _wrap_entries([_chat_entry("gemini-zeta-9", _SAMPLING_KNOBS)]) + + +def test_batch_row_with_null_knobs_for_a_flagged_gemini_model_is_not_refused(monkeypatch: pytest.MonkeyPatch) -> None: + """A null knob means no override, the same as on a real-time call, so it must not fail the upload""" + _flag_model_as_no_sampling(monkeypatch, "gemini-zeta-9") + monkeypatch.setattr(litellm, "drop_params", False) + (row,) = _wrap_entries([_chat_entry("gemini-zeta-9", {"temperature": None, "top_p": None, "top_k": None})]) + assert _generation_config(row) == {"max_output_tokens": 5} + + +def test_batch_row_for_a_flagged_gemini_model_drops_the_knobs_under_global_drop_params( + monkeypatch: pytest.MonkeyPatch, +) -> None: + _flag_model_as_no_sampling(monkeypatch, "gemini-zeta-9") + monkeypatch.setattr(litellm, "drop_params", True) + (row,) = _wrap_entries([_chat_entry("gemini-zeta-9", _SAMPLING_KNOBS)]) + assert _generation_config(row) == {"max_output_tokens": 5} + + +def test_batch_row_for_an_unflagged_gemini_model_keeps_the_knobs(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr(litellm, "drop_params", False) + (row,) = _wrap_entries([_chat_entry("gemini-2.5-flash", _SAMPLING_KNOBS)]) + assert _generation_config(row) == {"max_output_tokens": 5, **_SAMPLING_KNOBS} diff --git a/tests/unit/llms/vertex_ai/gemini/test_transformation.py b/tests/unit/llms/vertex_ai/gemini/test_transformation.py index 2ea02b776ab..ac2d43f64a1 100644 --- a/tests/unit/llms/vertex_ai/gemini/test_transformation.py +++ b/tests/unit/llms/vertex_ai/gemini/test_transformation.py @@ -1,12 +1,15 @@ import json +import logging import uuid +from typing import Final from unittest.mock import Mock import httpx import pytest import litellm +from litellm._logging import verbose_logger from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler from litellm.llms.vertex_ai.gemini import transformation from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import ( @@ -469,3 +472,16 @@ async def test_vertex_ai_async_transform_inlines_only_the_urls_gemini_cannot_fet {"file_data": {"mime_type": "application/pdf", "file_uri": files_api_pdf}}, ] assert sorted(async_only_image_fetch.fetched) == sorted([plain_http_png, extensionless_https]) + + +def test_image_only_user_content_logs_the_blank_text_fixup_at_debug(caplog: pytest.LogCaptureFixture) -> None: + messages: Final = [ + {"role": "user", "content": [{"type": "image_url", "image_url": {"url": "data:image/png;base64,iVBORw0KGgo="}}]} + ] + + with caplog.at_level(logging.DEBUG, logger=verbose_logger.name): + contents: Final = transformation.gemini_convert_messages_with_history(messages) + + fixups: Final = tuple(r for r in caplog.records if "No text in user content" in r.getMessage()) + assert tuple(r.levelno for r in fixups) == (logging.DEBUG,) + assert contents[0]["parts"][-1] == {"text": " "} diff --git a/tests/unit/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py b/tests/unit/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py index 5c0e9f1a305..bb624add673 100644 --- a/tests/unit/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py +++ b/tests/unit/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py @@ -1,7 +1,9 @@ import asyncio, importlib, os, uuid import json +import logging import re -from collections.abc import Awaitable, Callable, Mapping +import threading +from collections.abc import Awaitable, Callable, Iterator, Mapping from copy import deepcopy from typing import Final, List, Literal, cast, get_args from unittest.mock import MagicMock, Mock, patch @@ -13,16 +15,19 @@ from pydantic import BaseModel import litellm from litellm import ModelResponse, completion, embedding, image_generation +from litellm._logging import verbose_logger from litellm.litellm_core_utils.exception_mapping_utils import exception_type +from litellm.litellm_core_utils.get_model_cost_map import GetModelCostMap from litellm.llms.anthropic.pass_through.messages import handler as anthropic_messages_handler from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler from litellm.llms.gemini.chat.transformation import GoogleAIStudioGeminiConfig -from litellm.llms.vertex_ai.common_utils import VertexAIError +from litellm.llms.vertex_ai.common_utils import GEMINI_MAX_ENUM_CHARACTERS, VertexAIError from litellm.llms.vertex_ai.vertex_llm_base import VertexBase from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import ( VertexGeminiConfig, + _log_gemini_sampling_params_deprecated, ) -from litellm.types.llms.vertex_ai import GeminiFinishReason, UsageMetadata +from litellm.types.llms.vertex_ai import GeminiFinishReason, RequestBody, UsageMetadata from litellm.types.utils import ChoiceLogprobs, Usage from litellm.utils import _invalidate_model_cost_lowercase_map, CustomStreamWrapper from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER @@ -2120,6 +2125,207 @@ def test_gemini_reasoning_effort_and_function_tool_share_request() -> None: ] +@pytest.mark.parametrize( + ("model", "expected_level"), + [ + ("gemini-3.8-flash", {"type": "integer", "enum": ["1", "2", "5"]}), + ("gemini-2.5-flash", {"type": "integer"}), + ], +) +def test_gemini_tool_mapping_sends_integer_enums_to_gemini_3_and_keeps_caller_tools( + model: str, expected_level: dict[str, object] +) -> None: + tools: Final = [ + { + "type": "function", + "function": { + "name": "set_priority", + "strict": True, + "parameters": { + "type": "object", + "properties": {"level": {"type": "integer", "enum": [1, 2, 5]}}, + "required": ["level"], + "additionalProperties": False, + }, + }, + } + ] + caller_tools: Final = deepcopy(tools) + + request_params: Final = VertexGeminiConfig().map_openai_params( + non_default_params={"tools": tools}, + optional_params={}, + model=model, + drop_params=False, + ) + + sent_level: Final = request_params["tools"][0]["function_declarations"][0]["parameters"]["properties"]["level"] + assert sent_level == expected_level + assert tools == caller_tools + + +@pytest.mark.parametrize( + ("model", "expected_level"), + [ + ("gemini-flash-latest", {"type": "integer", "enum": ["1", "2", "5"]}), + ("gemini-1.5-pro", {"type": "integer"}), + ], +) +def test_gemini_response_schema_sends_integer_enums_to_gemini_3(model: str, expected_level: dict[str, object]) -> None: + response_format: Final = { + "type": "json_schema", + "json_schema": { + "name": "task", + "schema": { + "type": "object", + "properties": {"level": {"type": "integer", "enum": [1, 2, 5]}}, + "required": ["level"], + }, + }, + } + + request_params: Final = VertexGeminiConfig().map_openai_params( + non_default_params={"response_format": response_format}, + optional_params={}, + model=model, + drop_params=False, + ) + + assert request_params["response_schema"]["properties"]["level"] == expected_level + + +def test_gemini_mapping_drops_integer_enums_when_the_caller_disallows_them() -> None: + level_schema: Final = {"type": "object", "properties": {"level": {"type": "integer", "enum": [1, 2, 5]}}} + + request_params: Final = VertexGeminiConfig().map_openai_params( + non_default_params={ + "tools": [{"type": "function", "function": {"name": "set_priority", "parameters": level_schema}}], + "response_format": {"type": "json_schema", "json_schema": {"name": "task", "schema": level_schema}}, + }, + optional_params={}, + model="gemini-flash-latest", + drop_params=False, + allow_integer_enums=False, + ) + + assert request_params["tools"][0]["function_declarations"][0]["parameters"]["properties"]["level"] == { + "type": "integer" + } + assert request_params["response_schema"]["properties"]["level"] == {"type": "integer"} + + +_TEN_DIGIT_VALUES_IN_BUDGET: Final = GEMINI_MAX_ENUM_CHARACTERS // 10 + + +def _ten_digit_integer_enum_tool(name: str, value_count: int) -> dict[str, object]: + return { + "type": "function", + "function": { + "name": name, + "parameters": { + "type": "object", + "properties": {"level": {"type": "integer", "enum": [10**9 + n for n in range(value_count)]}}, + "required": ["level"], + }, + }, + } + + +@pytest.mark.parametrize( + ("value_counts", "integer_enums_sent"), + [ + ((_TEN_DIGIT_VALUES_IN_BUDGET,), True), + ((_TEN_DIGIT_VALUES_IN_BUDGET + 1,), False), + ((_TEN_DIGIT_VALUES_IN_BUDGET // 2, _TEN_DIGIT_VALUES_IN_BUDGET - _TEN_DIGIT_VALUES_IN_BUDGET // 2), True), + ((_TEN_DIGIT_VALUES_IN_BUDGET // 2, _TEN_DIGIT_VALUES_IN_BUDGET - _TEN_DIGIT_VALUES_IN_BUDGET // 2 + 1), False), + ], + ids=["one-tool-at-budget", "one-tool-over-budget", "two-tools-at-budget", "two-tools-over-budget"], +) +def test_gemini_tool_mapping_drops_every_integer_enum_when_the_request_exceeds_the_enum_budget( + value_counts: tuple[int, ...], integer_enums_sent: bool +) -> None: + request_params: Final = VertexGeminiConfig().map_openai_params( + non_default_params={ + "tools": [_ten_digit_integer_enum_tool(f"tool_{i}", count) for i, count in enumerate(value_counts)] + }, + optional_params={}, + model="gemini-3.8-flash", + drop_params=False, + ) + + sent_levels: Final = [ + declaration["parameters"]["properties"]["level"] + for declaration in request_params["tools"][0]["function_declarations"] + ] + assert sent_levels == [ + ( + {"type": "integer", "enum": [str(10**9 + n) for n in range(count)]} + if integer_enums_sent + else {"type": "integer"} + ) + for count in value_counts + ] + + +def test_gemini_tool_mapping_counts_string_enums_toward_the_enum_budget() -> None: + names: Final = [f"name{n:06d}" for n in range(GEMINI_MAX_ENUM_CHARACTERS // 10)] + tool: Final = { + "type": "function", + "function": { + "name": "set_priority", + "parameters": { + "type": "object", + "properties": { + "name": {"type": "string", "enum": names}, + "level": {"type": "integer", "enum": [1, 2, 5]}, + }, + }, + }, + } + + request_params: Final = VertexGeminiConfig().map_openai_params( + non_default_params={"tools": [tool]}, optional_params={}, model="gemini-3.8-flash", drop_params=False + ) + + sent_properties: Final = request_params["tools"][0]["function_declarations"][0]["parameters"]["properties"] + assert sent_properties["level"] == {"type": "integer"} + assert sent_properties["name"]["enum"] == names + + +@pytest.mark.parametrize( + ("value_count", "expected_level"), + [ + ( + _TEN_DIGIT_VALUES_IN_BUDGET, + {"type": "integer", "enum": [str(10**9 + n) for n in range(_TEN_DIGIT_VALUES_IN_BUDGET)]}, + ), + (_TEN_DIGIT_VALUES_IN_BUDGET + 1, {"type": "integer"}), + ], +) +def test_gemini_response_schema_drops_integer_enums_past_the_enum_budget( + value_count: int, expected_level: dict[str, object] +) -> None: + response_format: Final = { + "type": "json_schema", + "json_schema": { + "name": "task", + "schema": { + "type": "object", + "properties": {"level": {"type": "integer", "enum": [10**9 + n for n in range(value_count)]}}, + }, + }, + } + + request_params: Final = VertexGeminiConfig().map_openai_params( + non_default_params={"response_format": response_format}, + optional_params={}, + model="gemini-flash-latest", + drop_params=False, + ) + + assert request_params["response_schema"]["properties"]["level"] == expected_level + + def test_vertex_ai_transform_parts(): """ Test the _transform_parts method for converting Vertex AI function calls @@ -3533,6 +3739,169 @@ def test_get_optional_params_gemini_3_has_no_default_temperature( assert optional_params["thinkingConfig"]["thinkingLevel"] == "medium" +_SAMPLING_PARAMS: Final = {"temperature": 0.3, "top_p": 0.9, "top_k": 20} + + +def _gemini_config(config_cls: Literal["vertex", "studio"]) -> VertexGeminiConfig: + return VertexGeminiConfig() if config_cls == "vertex" else GoogleAIStudioGeminiConfig() + + +def _gemini_request_body( + custom_llm_provider: Literal["vertex_ai", "gemini"], + optional_params: dict[str, object], + litellm_params: dict[str, object], +) -> RequestBody: + from litellm.llms.vertex_ai.gemini.transformation import transform_request_body + + return transform_request_body( + messages=[{"role": "user", "content": "hi"}], + model="gemini-zeta-9", + optional_params=optional_params, + custom_llm_provider=custom_llm_provider, + litellm_params=litellm_params, + cached_content=None, + ) + + +@pytest.mark.parametrize("custom_llm_provider", ["vertex_ai", "gemini"]) +@pytest.mark.parametrize("param", ["temperature", "top_p"]) +def test_get_optional_params_raises_a_400_naming_drop_params_for_a_flagged_gemini_model( + custom_llm_provider: Literal["vertex_ai", "gemini"], param: str, monkeypatch: pytest.MonkeyPatch +) -> None: + """Google ignores sampling params on models flagged ``supports_sampling_params: false``, so without + drop_params the caller gets the 400 that names the escape hatch instead of a 200 that lied (#47015)""" + from litellm.utils import get_optional_params + + monkeypatch.setattr(litellm, "drop_params", False) + monkeypatch.setitem(litellm.model_cost, "gemini-zeta-9", {"supports_sampling_params": False}) + + with pytest.raises(litellm.utils.UnsupportedParamsError, match="drop_params") as excinfo: + get_optional_params( + model="gemini-zeta-9", custom_llm_provider=custom_llm_provider, **{param: _SAMPLING_PARAMS[param]} + ) + + assert excinfo.value.status_code == 400 + assert param in str(excinfo.value) + + +@pytest.mark.parametrize("custom_llm_provider", ["vertex_ai", "gemini"]) +def test_allowed_openai_params_still_forwards_a_sampling_param_the_map_flags_off( + custom_llm_provider: Literal["vertex_ai", "gemini"], monkeypatch: pytest.MonkeyPatch +) -> None: + """The 400 tells the caller to send allowed_openai_params, so that escape hatch has to work""" + from litellm.utils import get_optional_params + + monkeypatch.setattr(litellm, "drop_params", False) + monkeypatch.setitem(litellm.model_cost, "gemini-zeta-9", {"supports_sampling_params": False}) + + optional_params: Final = get_optional_params( + model="gemini-zeta-9", + custom_llm_provider=custom_llm_provider, + temperature=0.3, + allowed_openai_params=["temperature"], + ) + + assert optional_params["temperature"] == 0.3 + + +@pytest.mark.parametrize("custom_llm_provider", ["vertex_ai", "gemini"]) +def test_top_k_is_stripped_from_the_request_body_of_a_flagged_gemini_model_under_drop_params( + custom_llm_provider: Literal["vertex_ai", "gemini"], monkeypatch: pytest.MonkeyPatch +) -> None: + """top_k is a provider-specific kwarg that skips the shared unsupported-param check, so it is gated + where the request body is built""" + monkeypatch.setitem(litellm.model_cost, "gemini-zeta-9", {"supports_sampling_params": False}) + + body: Final = _gemini_request_body( + custom_llm_provider, {"top_k": 20, "max_output_tokens": 10}, {"drop_params": True} + ) + + assert body["generationConfig"] == {"max_output_tokens": 10} + + +@pytest.mark.parametrize("custom_llm_provider", ["vertex_ai", "gemini"]) +def test_top_k_raises_a_400_naming_drop_params_for_a_flagged_gemini_model( + custom_llm_provider: Literal["vertex_ai", "gemini"], monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setattr(litellm, "drop_params", False) + monkeypatch.setitem(litellm.model_cost, "gemini-zeta-9", {"supports_sampling_params": False}) + + with pytest.raises(litellm.utils.UnsupportedParamsError, match="drop_params") as excinfo: + _gemini_request_body(custom_llm_provider, {"top_k": 20}, {}) + + assert excinfo.value.status_code == 400 + assert "top_k" in str(excinfo.value) + + +@pytest.mark.parametrize("custom_llm_provider", ["vertex_ai", "gemini"]) +@pytest.mark.parametrize("row", [{"supports_sampling_params": True}, {}], ids=["flag_true", "flag_absent"]) +def test_gemini_keeps_forwarding_sampling_params_unless_the_model_map_flags_them_off( + custom_llm_provider: Literal["vertex_ai", "gemini"], row: dict[str, bool], monkeypatch: pytest.MonkeyPatch +) -> None: + """An explicit true and a model the map says nothing about both keep today's pass-through, top_k included""" + from litellm.utils import get_optional_params + + monkeypatch.setitem(litellm.model_cost, "gemini-zeta-9", row) + + optional_params: Final = get_optional_params( + model="gemini-zeta-9", custom_llm_provider=custom_llm_provider, drop_params=True, **_SAMPLING_PARAMS + ) + body: Final = _gemini_request_body(custom_llm_provider, dict(optional_params), {"drop_params": True}) + + assert body["generationConfig"] == _SAMPLING_PARAMS + + +@pytest.mark.parametrize("model_key", ["gemini-zeta-9", "vertex_ai/gemini-zeta-9", "gemini/gemini-zeta-9"]) +def test_gemini_sampling_flag_is_read_from_whichever_provider_row_carries_it( + model_key: str, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setitem(litellm.model_cost, model_key, {"supports_sampling_params": False}) + + result: Final = VertexGeminiConfig().map_openai_params( + non_default_params={"temperature": 0.3}, + optional_params={}, + model="gemini-zeta-9", + drop_params=True, + ) + + assert "temperature" not in result + + +@pytest.mark.parametrize("config_cls", ["vertex", "studio"]) +def test_gemini_supported_openai_params_omit_sampling_params_when_flagged_off( + config_cls: Literal["vertex", "studio"], monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setitem(litellm.model_cost, "gemini-zeta-9", {"supports_sampling_params": False}) + + supported: Final = set(_gemini_config(config_cls).get_supported_openai_params("gemini-zeta-9")) + + assert not supported & set(_SAMPLING_PARAMS) + assert "max_tokens" in supported + + +@pytest.mark.parametrize("custom_llm_provider", ["vertex_ai", "gemini"]) +def test_get_optional_params_drops_sampling_params_for_a_flagged_gemini_model_under_drop_params( + custom_llm_provider: Literal["vertex_ai", "gemini"], monkeypatch: pytest.MonkeyPatch +) -> None: + """The path every SDK and proxy call takes, on both the Vertex and the AI Studio route""" + from litellm.utils import get_optional_params + + monkeypatch.setitem(litellm.model_cost, "gemini-zeta-9", {"supports_sampling_params": False}) + + optional_params: Final = get_optional_params( + model="gemini-zeta-9", + custom_llm_provider=custom_llm_provider, + temperature=0.3, + top_p=0.9, + max_tokens=10, + drop_params=True, + ) + + assert "temperature" not in optional_params + assert "top_p" not in optional_params + assert optional_params["max_output_tokens"] == 10 + + def test_media_resolution_from_detail_parameter(): """Test that OpenAI's detail parameter is correctly mapped to media_resolution""" from litellm.llms.vertex_ai.gemini.transformation import ( @@ -6489,6 +6858,155 @@ def test_supported_reasoning_efforts_still_map(model): assert "thinkingConfig" in result +@pytest.fixture +def fresh_sampling_deprecation_cache() -> Iterator[None]: + _log_gemini_sampling_params_deprecated.cache_clear() + yield + _log_gemini_sampling_params_deprecated.cache_clear() + + +def _mapped_gemini_3_models() -> tuple[str, ...]: + return tuple(sorted(name for name in GetModelCostMap.loaded_model_cost_map() if name.startswith("gemini-3"))) + + +def _deprecation_messages(caplog: pytest.LogCaptureFixture) -> tuple[str, ...]: + return tuple(r.getMessage() for r in caplog.records if "DeprecationWarning" in r.getMessage()) + + +@pytest.mark.parametrize(("param", "value"), (("temperature", 0.2), ("top_p", 0.9), ("top_k", 5))) +@pytest.mark.usefixtures("fresh_sampling_deprecation_cache") +def test_gemini_3_sampling_deprecation_is_logged_once_per_model( + param: str, value: float, caplog: pytest.LogCaptureFixture +) -> None: + first, second = _mapped_gemini_3_models()[:2] + config: Final = VertexGeminiConfig() + + with caplog.at_level(logging.WARNING, logger=verbose_logger.name): + mapped: Final = tuple( + config.map_openai_params( + non_default_params={param: value}, optional_params={}, model=model, drop_params=True + ) + for model in (first, first, first, second) + ) + + deprecations: Final = _deprecation_messages(caplog) + assert len(deprecations) == 2 + assert f"({first})" in deprecations[0] + assert f"({second})" in deprecations[1] + assert all(m[param] == value for m in mapped) + + +@pytest.mark.usefixtures("fresh_sampling_deprecation_cache") +def test_gemini_3_sampling_deprecation_is_logged_once_when_first_calls_race(caplog: pytest.LogCaptureFixture) -> None: + model: Final = _mapped_gemini_3_models()[0] + + def map_sampling_params() -> None: + VertexGeminiConfig().map_openai_params( + non_default_params={"temperature": 0.2}, optional_params={}, model=model, drop_params=True + ) + + racing_call: Final = threading.Thread(target=map_sampling_params) + + def start_racing_call_while_first_warning_logs(record: logging.LogRecord) -> bool: + if "DeprecationWarning" in record.getMessage() and racing_call.ident is None: + racing_call.start() + racing_call.join(timeout=0.5) + return True + + verbose_logger.addFilter(start_racing_call_while_first_warning_logs) + try: + with caplog.at_level(logging.WARNING, logger=verbose_logger.name): + map_sampling_params() + racing_call.join() + finally: + verbose_logger.removeFilter(start_racing_call_while_first_warning_logs) + + assert len(_deprecation_messages(caplog)) == 1 + + +@pytest.mark.usefixtures("fresh_sampling_deprecation_cache") +def test_gemini_3_sampling_deprecation_for_unmapped_names_does_not_hide_mapped_models( + caplog: pytest.LogCaptureFixture, +) -> None: + unmapped: Final = tuple(f"gemini-3.9-flash-{uuid.uuid4().hex}" for _ in range(100)) + mapped: Final = _mapped_gemini_3_models()[0] + config: Final = VertexGeminiConfig() + + with caplog.at_level(logging.WARNING, logger=verbose_logger.name): + for model in (*unmapped, mapped) * 2: + config.map_openai_params( + non_default_params={"temperature": 0.2}, optional_params={}, model=model, drop_params=True + ) + + deprecations: Final = _deprecation_messages(caplog) + assert len(deprecations) == 2 + assert all(name not in deprecations[0] for name in unmapped) + assert f"({mapped})" in deprecations[1] + + +@pytest.mark.usefixtures("fresh_sampling_deprecation_cache") +def test_gemini_3_sampling_deprecation_names_models_cataloged_only_under_vertex_ai( + caplog: pytest.LogCaptureFixture, +) -> None: + catalog: Final = GetModelCostMap.loaded_model_cost_map() + vertex_only: Final = next( + name.removeprefix("vertex_ai/") + for name in catalog + if name.startswith("vertex_ai/gemini-3") + and name.removeprefix("vertex_ai/") not in catalog + and f"gemini/{name.removeprefix('vertex_ai/')}" not in catalog + ) + + with caplog.at_level(logging.WARNING, logger=verbose_logger.name): + VertexGeminiConfig().map_openai_params( + non_default_params={"temperature": 0.2}, optional_params={}, model=vertex_only, drop_params=True + ) + + deprecations: Final = _deprecation_messages(caplog) + assert len(deprecations) == 1 + assert f"({vertex_only})" in deprecations[0] + + +@pytest.mark.usefixtures("fresh_sampling_deprecation_cache") +def test_gemini_3_sampling_deprecation_for_names_priced_at_runtime_shares_one_notice( + monkeypatch: pytest.MonkeyPatch, caplog: pytest.LogCaptureFixture +) -> None: + priced: Final = tuple(f"gemini-3.9-flash-{uuid.uuid4().hex}" for _ in range(20)) + for name in priced: + monkeypatch.setitem( + litellm.model_cost, # pyright: ignore[reportUnknownMemberType] # registry is dynamically typed + f"gemini/{name}", + {"input_cost_per_token": 1e-7, "output_cost_per_token": 1e-7, "litellm_provider": "gemini"}, + ) + config: Final = VertexGeminiConfig() + + with caplog.at_level(logging.WARNING, logger=verbose_logger.name): + for model in priced * 2: + config.map_openai_params( + non_default_params={"temperature": 0.2}, optional_params={}, model=model, drop_params=True + ) + + deprecations: Final = _deprecation_messages(caplog) + assert len(deprecations) == 1 + assert all(name not in deprecations[0] for name in priced) + + +@pytest.mark.parametrize(("param", "value"), (("temperature", 0.5), ("top_p", 0.9), ("top_k", 5))) +def test_gemini_2_5_sampling_params_log_no_deprecation( + param: str, value: float, caplog: pytest.LogCaptureFixture +) -> None: + with caplog.at_level(logging.WARNING, logger=verbose_logger.name): + mapped: Final = VertexGeminiConfig().map_openai_params( + non_default_params={param: value}, + optional_params={}, + model=f"gemini-2.5-flash-{uuid.uuid4().hex}", + drop_params=True, + ) + + assert mapped[param] == value + assert not any("DeprecationWarning" in r.getMessage() for r in caplog.records) + + def _generate_content_body() -> dict: return { "candidates": [ diff --git a/tests/unit/llms/vertex_ai/test_vertex_ai_common_utils.py b/tests/unit/llms/vertex_ai/test_vertex_ai_common_utils.py index 7d380205ca1..152ab2ffc13 100644 --- a/tests/unit/llms/vertex_ai/test_vertex_ai_common_utils.py +++ b/tests/unit/llms/vertex_ai/test_vertex_ai_common_utils.py @@ -2,6 +2,7 @@ import copy import time from collections.abc import Iterator from contextlib import contextmanager +from enum import Enum from typing import Final from unittest.mock import AsyncMock, patch @@ -15,6 +16,7 @@ from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler from litellm.llms.gemini.count_tokens import handler as gemini_count_tokens_handler from litellm.llms.vertex_ai.common_utils import ( VertexAITokenCounter, + _fix_enum_types, build_vertex_schema, convert_anyof_null_to_nullable, convert_vertex_datetime_to_openai_datetime, @@ -28,6 +30,7 @@ from litellm.llms.vertex_ai.common_utils import ( vertex_request_labels_from_litellm_params, ) from litellm.llms.vertex_ai.count_tokens import handler as vertex_count_tokens_handler +from litellm.llms.vertex_ai.vertex_ai_partner_models.anthropic.transformation import VertexAIAnthropicConfig from litellm.types.utils import CountContextManagement, TokenCountMessagesFormat @@ -64,7 +67,9 @@ async def test_vertex_gemini_rejects_non_text_system_blocks_before_request( "google/gemma-4-26b-a4b-it-maas", ), ) -async def test_vertex_partner_model_without_an_inference_matching_count_answers_400_naming_the_model(model: str) -> None: +async def test_vertex_partner_model_without_an_inference_matching_count_answers_400_naming_the_model( + model: str, +) -> None: result: Final = await VertexAITokenCounter().count_tokens( model_to_use=model, messages=[{"role": "user", "content": "Count this"}], @@ -488,7 +493,6 @@ def test_anyof_conversion_forwards_a_non_object_branch_for_the_provider_to_judge assert schema == {"type": "object", "properties": {"example": {"anyOf": expected}}} - @pytest.mark.parametrize( ("field", "expected"), [ @@ -534,6 +538,7 @@ def test_vertex_schema_folds_every_null_branch_into_nullable(field: JsonValue, e assert schema["properties"]["value"] == expected + def test_anyof_with_excessive_nesting(): """Test conversion with excessive nesting > max levels +1 deep.""" # generate a schema with excessive nesting @@ -1404,12 +1409,11 @@ def test_construct_target_url_versionless_project_route_gets_api_version( def test_fix_enum_types(): """ - Test _fix_enum_types function removes enum fields when type is not string. + Test _fix_enum_types keeps string enums, converts integer enums to the form + Gemini accepts, and removes enums on other non-string types. - This test verifies the fix for the issue where Gemini rejects cached content - with function parameter enums on non-string types, causing API failures. - - Relevant issue: Gemini only allows enums for string-typed fields + Gemini rejects non-string enum values, causing API failures. Integer enums are + sent as type INTEGER with string values. """ from litellm.llms.vertex_ai.common_utils import _fix_enum_types @@ -1423,7 +1427,7 @@ def test_fix_enum_types(): "description": "How to truncate content", }, "maxLength": { - "enum": [100, 200, 500], # This should be removed + "enum": [100, 200, 500], "type": "integer", "description": "Maximum length", }, @@ -1440,7 +1444,7 @@ def test_fix_enum_types(): "type": "string", }, "innerNonStringEnum": { - "enum": [1, 2, 3], # This should be removed + "enum": [1, 2, 3], "type": "integer", }, }, @@ -1451,13 +1455,13 @@ def test_fix_enum_types(): "type": "string", "enum": ["option1", "option2"], }, # This should be kept - {"type": "integer", "enum": [1, 2, 3]}, # This should be removed + {"type": "integer", "enum": [1, 2, 3]}, ] }, }, } - # Expected output: Non-string enums removed, string enums kept + # Expected output: string enums kept, integer enums converted, others removed expected_output = { "type": "object", "properties": { @@ -1466,7 +1470,8 @@ def test_fix_enum_types(): "type": "string", "description": "How to truncate content", }, - "maxLength": { # enum removed + "maxLength": { + "enum": ["100", "200", "500"], "type": "integer", "description": "Maximum length", }, @@ -1481,7 +1486,10 @@ def test_fix_enum_types(): "enum": ["a", "b", "c"], # Kept - string type "type": "string", }, - "innerNonStringEnum": {"type": "integer"}, # enum removed + "innerNonStringEnum": { + "enum": ["1", "2", "3"], + "type": "integer", + }, }, }, "anyOfField": { @@ -1490,14 +1498,14 @@ def test_fix_enum_types(): "type": "string", "enum": ["option1", "option2"], }, # Kept - has string type - {"type": "integer"}, # enum removed + {"type": "integer", "enum": ["1", "2", "3"]}, ] }, }, } # Apply the transformation - _fix_enum_types(input_schema) + _fix_enum_types(input_schema, send_integer_enums=True) # Verify the transformation assert input_schema == expected_output @@ -1519,20 +1527,135 @@ def test_fix_enum_types(): "c", ] - # 2. Non-string enums are removed - assert "enum" not in input_schema["properties"]["maxLength"] + # 2. Integer enums are converted, other non-string enums are removed + assert input_schema["properties"]["maxLength"]["enum"] == ["100", "200", "500"] assert "enum" not in input_schema["properties"]["enabled"] - assert "enum" not in input_schema["properties"]["nested"]["properties"]["innerNonStringEnum"] + assert input_schema["properties"]["nested"]["properties"]["innerNonStringEnum"]["enum"] == ["1", "2", "3"] - # 3. anyOf with string type keeps enum, non-string removes it + # 3. anyOf keeps the string enum and converts the integer one assert "enum" in input_schema["properties"]["anyOfField"]["anyOf"][0] - assert "enum" not in input_schema["properties"]["anyOfField"]["anyOf"][1] + assert input_schema["properties"]["anyOfField"]["anyOf"][1]["enum"] == ["1", "2", "3"] # 4. Other properties preserved assert input_schema["properties"]["maxLength"]["type"] == "integer" assert input_schema["properties"]["enabled"]["type"] == "boolean" + +def test_build_vertex_schema_sends_integer_enum_as_string_values(): + """An integer enum tool parameter reaches Gemini as INTEGER with string values and no enum format.""" + from litellm.llms.vertex_ai.common_utils import _build_vertex_schema + + parameters = { + "type": "object", + "properties": { + "level": {"type": "integer", "enum": [1, 2, 5]}, + "flag": {"type": "boolean", "enum": [True]}, + }, + "required": ["level"], + } + + result = _build_vertex_schema(parameters, send_integer_enums=True) + + assert "format" not in result["properties"]["level"] + assert result["properties"]["level"]["enum"] == ["1", "2", "5"] + assert result["properties"]["level"]["type"].lower() == "integer" + assert "enum" not in result["properties"]["flag"] + + +@pytest.mark.parametrize( + ("enum_values", "send_integer_enums", "expected_level"), + [ + ( + [1, 2, 5], + True, + {"anyOf": [{"type": "integer", "enum": ["1", "2", "5"], "nullable": True}]}, + ), + ( + [1, 2, 5, None], + True, + {"anyOf": [{"type": "integer", "enum": ["1", "2", "5"], "nullable": True}]}, + ), + ([1, 2, 5], False, {"anyOf": [{"type": "integer", "nullable": True}]}), + ([1, "a"], True, {"anyOf": [{"type": "integer", "nullable": True}]}), + ], + ids=["sent", "null-in-enum", "not-sent", "mixed-values"], +) +def test_build_vertex_schema_keeps_integer_enum_on_nullable_type_list( + enum_values: list[object], send_integer_enums: bool, expected_level: JsonValue +) -> None: + schema: Final = build_vertex_schema( + {"type": "object", "properties": {"level": {"type": ["integer", "null"], "enum": enum_values}}}, + send_integer_enums=send_integer_enums, + ) + + assert schema["properties"]["level"] == expected_level + + +def test_map_function_keeps_integer_enum_when_tools_are_reused(): + from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import VertexGeminiConfig + + tools = [ + { + "type": "function", + "function": { + "name": "set_priority", + "parameters": { + "type": "object", + "properties": {"level": {"type": "integer", "enum": [1, 2, 5]}}, + "required": ["level"], + }, + }, + } + ] + config = VertexGeminiConfig() + + sent = [ + config._map_function(tools, {}, send_integer_enums=True)[0]["function_declarations"][0]["parameters"][ + "properties" + ]["level"] + for _ in range(2) + ] + + assert sent[0]["enum"] == ["1", "2", "5"] + assert sent[1]["enum"] == ["1", "2", "5"] + assert sent[0] == sent[1] + + +class _Priority(int, Enum): + LOW = 1 + HIGH = 3 + + +@pytest.mark.parametrize( + ("enum_values", "send_integer_enums", "expected_enum"), + [ + ([1, 2, 5], False, None), + (["-3", "007", 4], True, ["-3", "7", "4"]), + ([1, 2**53], True, None), + ([1, -(2**53)], True, None), + (["1", str(2**53)], True, None), + ([-(2**53 - 1), 2**53 - 1], True, [str(-(2**53 - 1)), str(2**53 - 1)]), + ([str(-(2**53 - 1)), str(2**53 - 1)], True, [str(-(2**53 - 1)), str(2**53 - 1)]), + (["1", "9" * 5000], True, None), + (["1", "--2"], True, None), + (["1", "\u00b2"], True, None), + ([True, 1], True, None), + ([1.5, 2], True, None), + ([], True, None), + ([_Priority.LOW, _Priority.HIGH], True, ["1", "3"]), + ], +) +def test_fix_enum_types_sends_only_integer_enums_gemini_accepts( + enum_values: list[object], send_integer_enums: bool, expected_enum: list[str] | None +) -> None: + schema: Final = {"type": "integer", "enum": enum_values} + + _fix_enum_types(schema, send_integer_enums=send_integer_enums) + + assert schema.get("enum") == expected_enum + assert "format" not in schema + def test_get_token_url(): from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import ( VertexLLM, @@ -1700,6 +1823,148 @@ async def test_vertex_ai_token_counter_forwards_system_and_tools_to_partner_requ assert without_optional_fields.total_tokens == 37 +_PARTNER_CHAT_TOOL_TURNS: Final[list[dict[str, object]]] = [ + {"role": "user", "content": "Weather in SF?"}, + { + "role": "assistant", + "content": None, + "tool_calls": [{"id": "call_1", "type": "function", "function": {"name": "get_weather", "arguments": "{}"}}], + }, + {"role": "tool", "tool_call_id": "call_1", "content": "sunny"}, +] +_PARTNER_RESPONSES_TOOL: Final[dict[str, object]] = { + "type": "function", + "name": "get_weather", + "parameters": {"type": "object", "properties": {}}, +} + + +async def _partner_counted_bodies( + model: str, chat_params: dict[str, JsonValue] | None = None +) -> tuple[dict[str, object], ...]: + from litellm.llms.vertex_ai.vertex_ai_partner_models.count_tokens import handler + + class FakeResponse: + status_code = 200 + + def json(self) -> dict[str, int]: + return {"input_tokens": 37} + + class FakeHttpClient: + posted_bodies: tuple[dict[str, object], ...] = () + + async def post( + self, url: str, headers: dict[str, str], json: dict[str, object], timeout: float + ) -> FakeResponse: + self.posted_bodies = (*self.posted_bodies, json) + return FakeResponse() + + fake_http_client: Final = FakeHttpClient() + with ( + patch.object(handler, "get_async_httpx_client", return_value=fake_http_client), + patch.object( + handler.VertexAIPartnerModelsTokenCounter, + "_ensure_access_token_async", + new=AsyncMock(return_value=("fake-token", "test-project")), + ), + ): + result: Final = await VertexAITokenCounter().count_tokens( + model_to_use=model, + messages=copy.deepcopy(_PARTNER_CHAT_TOOL_TURNS), + contents=None, + deployment={"litellm_params": {"vertex_project": "test-project", "vertex_location": "us-east5"}}, + tools=[_PARTNER_RESPONSES_TOOL], + chat_params=chat_params or {}, + ) + + assert result is not None + assert result.total_tokens == 37 + return fake_http_client.posted_bodies + + +@pytest.mark.asyncio +async def test_vertex_claude_count_sends_chat_tool_use_in_the_shape_chat_inference_sends() -> None: + assert await _partner_counted_bodies("claude-opus-5-5") == ( + { + "model": "claude-opus-5-5", + "messages": [ + {"role": "user", "content": [{"type": "text", "text": "Weather in SF?"}]}, + { + "role": "assistant", + "content": [{"type": "tool_use", "id": "call_1", "name": "get_weather", "input": {}}], + }, + {"role": "user", "content": [{"type": "tool_result", "tool_use_id": "call_1", "content": "sunny"}]}, + ], + "tools": [ + { + "name": "get_weather", + "input_schema": {"type": "object", "properties": {}}, + "type": "custom", + "description": "", + } + ], + }, + ) + + +@pytest.mark.asyncio +async def test_vertex_claude_count_sends_the_structured_output_vertex_inference_sends() -> None: + model: Final = "claude-haiku-4-5" + chat_params: Final[dict[str, JsonValue]] = { + "response_format": { + "type": "json_schema", + "json_schema": { + "name": "answer", + "schema": {"type": "object", "properties": {"answer": {"type": "string"}}, "required": ["answer"]}, + }, + } + } + config: Final = VertexAIAnthropicConfig() + inference: Final = config.transform_request( + model=model, + messages=copy.deepcopy(_PARTNER_CHAT_TOOL_TURNS), + optional_params=config.map_openai_params( + { + **chat_params, + "tools": [ + { + "type": "function", + "function": { + "name": "get_weather", + "description": "", + "parameters": _PARTNER_RESPONSES_TOOL["parameters"], + }, + } + ], + }, + {}, + model, + drop_params=False, + ), + litellm_params={}, + headers={}, + ) + + (body,) = await _partner_counted_bodies(model, chat_params) + + assert (body["tools"], body.get("tool_choice"), body.get("output_config")) == ( + inference["tools"], + inference.get("tool_choice"), + inference.get("output_config"), + ) + + +@pytest.mark.asyncio +async def test_vertex_llama_count_sends_chat_tool_use_as_sent() -> None: + assert await _partner_counted_bodies("meta/llama-4-maverick-17b-128e-instruct-maas") == ( + { + "model": "meta/llama-4-maverick-17b-128e-instruct-maas", + "messages": _PARTNER_CHAT_TOOL_TURNS, + "tools": [_PARTNER_RESPONSES_TOOL], + }, + ) + + @pytest.mark.asyncio @pytest.mark.parametrize( ("provider_failure", "expected_status", "expected_message"), diff --git a/tests/unit/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py b/tests/unit/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py index 113ddcfe2a9..ae9b9684f2d 100644 --- a/tests/unit/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py +++ b/tests/unit/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py @@ -1,6 +1,7 @@ import copy import json import os +from collections.abc import Mapping from typing import Final from unittest.mock import MagicMock, patch @@ -537,6 +538,44 @@ def test_messages_request_moves_output_format_into_output_config(): assert result["output_config"] == {"effort": "high", "format": output_format} +_CALLER_OUTPUT_CONFIG: Final = { + "effort": "high", + "format": {"type": "json_schema", "schema": {"type": "object", "properties": {"answer": {"type": "integer"}}}}, +} + + +def _messages_request_with_output_format(output_format: object, drop_params: bool) -> Mapping[str, object]: + return VertexAIPartnerModelsAnthropicMessagesConfig().transform_anthropic_messages_request( + model="claude-opus-4-6", + messages=[{"role": "user", "content": "What is 6 times 7?"}], + anthropic_messages_optional_request_params={ + "max_tokens": 1024, + "output_format": output_format, + "output_config": copy.deepcopy(_CALLER_OUTPUT_CONFIG), + }, + litellm_params=GenericLiteLLMParams(drop_params=drop_params), + headers={}, + ) + + +@pytest.mark.parametrize("output_format", ["json", ["json_schema"], 42]) +def test_messages_request_drops_a_malformed_output_format_under_drop_params(output_format: object): + result = _messages_request_with_output_format(output_format, drop_params=True) + + assert "output_format" not in result + assert result["output_config"] == _CALLER_OUTPUT_CONFIG + + +@pytest.mark.parametrize("output_format", ["json", ["json_schema"], 42]) +def test_messages_request_rejects_a_malformed_output_format_without_drop_params(output_format: object): + import litellm + + with pytest.raises(litellm.UnsupportedParamsError) as error: + _messages_request_with_output_format(output_format, drop_params=False) + + assert error.value.status_code == 400 + + def test_provider_config_manager_reuses_vertex_anthropic_messages_config_instance(): """ Regression test: repeated provider config lookups for the same Vertex Claude model diff --git a/tests/unit/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py b/tests/unit/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py index ace24c8a3f4..21bda6f0345 100644 --- a/tests/unit/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py +++ b/tests/unit/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py @@ -918,6 +918,44 @@ def test_sanitize_folds_output_format_into_output_config(model: str, data: dict, assert request["output_config"] == expected_output_config +def _vertex_chat_request_with_output_format( + output_format: object, litellm_params: Mapping[str, object] +) -> Mapping[str, object]: + return VertexAIAnthropicConfig().transform_request( + model="claude-opus-4-6", + messages=[{"role": "user", "content": "What is 6 times 7?"}], + optional_params={"max_tokens": 64, "output_format": output_format}, + litellm_params=dict(litellm_params), + headers={}, + ) + + +def test_vertex_chat_request_drops_a_malformed_output_format_under_per_request_drop_params(): + request: Final = _vertex_chat_request_with_output_format("json", {"drop_params": True}) + + assert "output_format" not in request + assert "output_config" not in request + + +def test_vertex_chat_request_drops_a_malformed_output_format_under_the_global_drop_params_flag( + monkeypatch: pytest.MonkeyPatch, +): + monkeypatch.setattr(litellm, "drop_params", True) + + request: Final = _vertex_chat_request_with_output_format("json", {}) + + assert "output_format" not in request + assert "output_config" not in request + + +def test_vertex_chat_request_rejects_a_malformed_output_format_without_drop_params_naming_the_proxy_setting(): + with pytest.raises(litellm.UnsupportedParamsError) as error: + _vertex_chat_request_with_output_format("json", {}) + + assert error.value.status_code == 400 + assert "litellm_settings:\n drop_params: true" in str(error.value) + + def test_vertex_ai_native_response_format_reaches_vertex_as_output_config_format(local_model_cost_map): config = VertexAIAnthropicConfig() schema: Final = {"type": "object", "properties": {"result": {"type": "string"}}, "required": ["result"]} diff --git a/tests/unit/proxy/_experimental/mcp_server/test_mcp_server_manager.py b/tests/unit/proxy/_experimental/mcp_server/test_mcp_server_manager.py index 4896c2f1706..7315315a619 100644 --- a/tests/unit/proxy/_experimental/mcp_server/test_mcp_server_manager.py +++ b/tests/unit/proxy/_experimental/mcp_server/test_mcp_server_manager.py @@ -317,6 +317,204 @@ def test_validated_admission_jwt_is_not_forwarded_as_an_extra_header(auth_type: assert _openapi_forwarded_extra_headers(server, raw, user) == expected +@pytest.mark.parametrize( + "auth_type", + [MCPAuth.none, MCPAuth.api_key, MCPAuth.bearer_token, MCPAuth.basic, MCPAuth.true_passthrough], +) +def test_admission_authorization_is_not_forwarded_for_any_auth_type( + auth_type: MCPAuth, monkeypatch: pytest.MonkeyPatch +) -> None: + from litellm.proxy import proxy_server + from litellm.proxy._experimental.mcp_server.mcp_server_manager import _openapi_forwarded_extra_headers + from litellm.proxy._experimental.mcp_server.operations import _prepare_mcp_server_headers + + monkeypatch.setattr(proxy_server, "master_key", "test-master-key") + server: Final = MCPServer( + server_id="admission-header-boundary", + name="admission-header-boundary", + transport=MCPTransport.http, + auth_type=auth_type, + extra_headers=["Authorization", "x-tenant"], + ) + user: Final = UserAPIKeyAuth(api_key="hashed-key") + admitted_raw: Final = { + "Authorization": "Bearer sk-" + "1234", + "x-tenant": "tenant-control", + } + expected_without_admission_key: Final = {"x-tenant": "tenant-control"} + admission_upstream_headers: Final = _prepare_mcp_server_headers( + server, + mcp_auth_header=None, + mcp_server_auth_headers=None, + oauth2_headers={"Authorization": "Bearer sk-" + "1234"}, + raw_headers=admitted_raw, + user_api_key_auth=user, + )[1] + assert admission_upstream_headers == expected_without_admission_key + assert _openapi_forwarded_extra_headers(server, admitted_raw, user) == expected_without_admission_key + + separate_upstream_raw: Final = { + "x-litellm-api-key": "Bearer another-sk", + "Authorization": "Bearer upstream", + "x-tenant": "tenant-control", + } + expected_with_upstream_authorization: Final = { + "x-tenant": "tenant-control", + "Authorization": "Bearer upstream", + } + distinct_upstream_headers: Final = _prepare_mcp_server_headers( + server, + mcp_auth_header=None, + mcp_server_auth_headers=None, + oauth2_headers={"Authorization": "Bearer upstream"}, + raw_headers=separate_upstream_raw, + user_api_key_auth=user, + )[1] + assert distinct_upstream_headers == expected_with_upstream_authorization + assert _openapi_forwarded_extra_headers(server, separate_upstream_raw, user) == expected_with_upstream_authorization + + +@pytest.mark.parametrize("auth_type", [MCPAuth.none, MCPAuth.bearer_token, MCPAuth.true_passthrough]) +def test_no_master_key_preserves_caller_authorization_unless_auth_is_enabled( + auth_type: MCPAuth, monkeypatch: pytest.MonkeyPatch +) -> None: + from litellm.proxy import proxy_server + from litellm.proxy._experimental.mcp_server.mcp_server_manager import _openapi_forwarded_extra_headers + from litellm.proxy._experimental.mcp_server.operations import _prepare_mcp_server_headers + + monkeypatch.setattr(proxy_server, "master_key", None) + monkeypatch.setattr(proxy_server, "general_settings", {}) + server: Final = MCPServer( + server_id="no-master-key", + name="no-master-key", + transport=MCPTransport.http, + auth_type=auth_type, + extra_headers=["Authorization", "x-tenant"], + ) + raw_headers: Final = {"Authorization": "Bearer upstream", "x-tenant": "t"} + user: Final = UserAPIKeyAuth(api_key="upstream", authenticated_by_custom_auth=False) + expected_forwarded: Final = {"x-tenant": "t", "Authorization": "Bearer upstream"} + forwarded_headers: Final = _prepare_mcp_server_headers( + server, + mcp_auth_header=None, + mcp_server_auth_headers=None, + oauth2_headers={"Authorization": "Bearer upstream"}, + raw_headers=raw_headers, + user_api_key_auth=user, + )[1] + assert forwarded_headers == expected_forwarded + assert _openapi_forwarded_extra_headers(server, raw_headers, user) == expected_forwarded + + monkeypatch.setattr(proxy_server, "general_settings", {"enable_oauth2_auth": True}) + auth_enabled_headers: Final = _prepare_mcp_server_headers( + server, + mcp_auth_header=None, + mcp_server_auth_headers=None, + oauth2_headers={"Authorization": "Bearer upstream"}, + raw_headers=raw_headers, + user_api_key_auth=user, + )[1] + assert auth_enabled_headers == {"x-tenant": "t"} + assert _openapi_forwarded_extra_headers(server, raw_headers, user) == {"x-tenant": "t"} + + +@pytest.mark.parametrize("auth_type", [MCPAuth.none, MCPAuth.bearer_token, MCPAuth.true_passthrough]) +def test_custom_auth_is_stripped_in_no_auth_dev_mode( + auth_type: MCPAuth, monkeypatch: pytest.MonkeyPatch +) -> None: + from litellm.proxy import proxy_server + from litellm.proxy._experimental.mcp_server.mcp_server_manager import _openapi_forwarded_extra_headers + from litellm.proxy._experimental.mcp_server.operations import _prepare_mcp_server_headers + + monkeypatch.setattr(proxy_server, "master_key", None) + monkeypatch.setattr(proxy_server, "general_settings", {}) + server: Final = MCPServer( + server_id="custom-auth-no-master-key", + name="custom-auth-no-master-key", + transport=MCPTransport.http, + auth_type=auth_type, + extra_headers=["Authorization", "x-tenant"], + ) + raw_headers: Final = {"Authorization": "Bearer custom-tok", "x-tenant": "t"} + user: Final = UserAPIKeyAuth(api_key="custom-tok") + user.authenticated_by_custom_auth = True + expected_headers: Final = {"x-tenant": "t"} + forwarded_headers: Final = _prepare_mcp_server_headers( + server, + mcp_auth_header=None, + mcp_server_auth_headers=None, + oauth2_headers={"Authorization": "Bearer custom-tok"}, + raw_headers=raw_headers, + user_api_key_auth=user, + )[1] + + assert forwarded_headers == expected_headers + assert _openapi_forwarded_extra_headers(server, raw_headers, user) == expected_headers + + +@pytest.mark.parametrize("auth_type", [MCPAuth.none, MCPAuth.bearer_token, MCPAuth.true_passthrough]) +@pytest.mark.parametrize( + "raw_headers,oauth2_headers,expected", + [ + ( + { + "X-Company-Key": "sk-" + "1234", + "Authorization": "Bearer upstream", + "x-tenant": "t", + }, + {"Authorization": "Bearer upstream"}, + {"x-tenant": "t", "Authorization": "Bearer upstream"}, + ), + ( + { + "X-Company-Key": "sk-" + "1234", + "Authorization": "Bearer sk-" + "1234", + "x-tenant": "t", + }, + {"Authorization": "Bearer sk-" + "1234"}, + {"x-tenant": "t"}, + ), + ( + {"Authorization": "Bearer sk-" + "1234", "x-tenant": "t"}, + {"Authorization": "Bearer sk-" + "1234"}, + {"x-tenant": "t"}, + ), + ], +) +def test_custom_admission_header_controls_authorization_forwarding( + auth_type: MCPAuth, + raw_headers: dict[str, str], + oauth2_headers: dict[str, str], + expected: dict[str, str], + monkeypatch: pytest.MonkeyPatch, +) -> None: + from litellm.proxy import proxy_server + from litellm.proxy._experimental.mcp_server.mcp_server_manager import _openapi_forwarded_extra_headers + from litellm.proxy._experimental.mcp_server.operations import _prepare_mcp_server_headers + + monkeypatch.setattr(proxy_server, "master_key", "test-master-key") + monkeypatch.setattr(proxy_server, "general_settings", {"litellm_key_header_name": "x-company-key"}) + server: Final = MCPServer( + server_id="custom-admission-header", + name="custom-admission-header", + transport=MCPTransport.http, + auth_type=auth_type, + extra_headers=["Authorization", "x-tenant"], + ) + user: Final = UserAPIKeyAuth(api_key="hashed-key") + + upstream_headers: Final = _prepare_mcp_server_headers( + server, + mcp_auth_header=None, + mcp_server_auth_headers=None, + oauth2_headers=oauth2_headers, + raw_headers=raw_headers, + user_api_key_auth=user, + )[1] + assert upstream_headers == expected + assert _openapi_forwarded_extra_headers(server, raw_headers, user) == expected + + class TestMCPServerManager: """Test MCP Server Manager stdio functionality""" @@ -3559,14 +3757,14 @@ class TestMCPServerManager: @pytest.mark.asyncio async def test_call_regular_mcp_tool_passthrough_strips_authorization_when_admission_consumed_litellm_key( self, - ): + ) -> None: """OAuth pass-through must not forward the caller's Authorization to upstream when LiteLLM admission consumed the bearer as its API key — otherwise the LiteLLM key the caller used for admission would leak upstream.""" from litellm.proxy._types import UserAPIKeyAuth - manager = MCPServerManager() - server = MCPServer( + manager: Final = MCPServerManager() + server: Final = MCPServer( server_id="server-passthrough-call", name="passthrough-server", url="https://example.com", @@ -3576,20 +3774,19 @@ class TestMCPServerManager: oauth_passthrough=True, ) - mock_client = AsyncMock() + mock_client: Final = AsyncMock() mock_client.call_tool = AsyncMock(return_value=CallToolResult(content=[], isError=False)) - captured_extra_headers = None + capture_extra_headers: Final = AsyncMock() async def capture_create_mcp_client( - server, - mcp_auth_header, - extra_headers, - stdio_env, - subject_token=None, - **kwargs, - ): # pragma: no cover - helper - nonlocal captured_extra_headers - captured_extra_headers = extra_headers + server: MCPServer, + mcp_auth_header: str | dict[str, str] | None, + extra_headers: dict[str, str] | None, + stdio_env: dict[str, str] | None, + subject_token: str | None = None, + **kwargs: object, + ) -> AsyncMock: + await capture_extra_headers(extra_headers) return mock_client manager.create_mcp_client = AsyncMock(side_effect=capture_create_mcp_client) @@ -3610,8 +3807,64 @@ class TestMCPServerManager: user_api_key_auth=UserAPIKeyAuth(api_key="sk-litellm-key"), ) + assert capture_extra_headers.await_args is not None + captured_extra_headers: Final = capture_extra_headers.await_args.args[0] assert captured_extra_headers == {"x-request-id": "req-123"} + @pytest.mark.asyncio + async def test_call_regular_mcp_tool_never_forwards_admission_key_for_none_auth( + self, monkeypatch: pytest.MonkeyPatch + ) -> None: + from litellm.proxy import proxy_server + + monkeypatch.setattr(proxy_server, "master_key", "test-master-key") + manager: Final = MCPServerManager() + server: Final = MCPServer( + server_id="server-none-admission-call", + name="none-auth-server", + url="https://example.com", + transport=MCPTransport.http, + auth_type=MCPAuth.none, + extra_headers=["Authorization", "x-tenant"], + ) + + mock_client: Final = AsyncMock() + mock_client.call_tool = AsyncMock(return_value=CallToolResult(content=[], isError=False)) + capture_extra_headers: Final = AsyncMock() + + async def capture_create_mcp_client( + server: MCPServer, + mcp_auth_header: str | dict[str, str] | None, + extra_headers: dict[str, str] | None, + stdio_env: dict[str, str] | None, + subject_token: str | None = None, + **kwargs: object, + ) -> AsyncMock: + await capture_extra_headers(extra_headers) + return mock_client + + manager.create_mcp_client = AsyncMock(side_effect=capture_create_mcp_client) + + await manager._call_regular_mcp_tool( + mcp_server=server, + original_tool_name="tool", + arguments={}, + tasks=[], + mcp_auth_header=None, + mcp_server_auth_headers=None, + oauth2_headers=None, + raw_headers={ + "Authorization": "Bearer sk-" + "1234", + "x-tenant": "tenant-control", + }, + proxy_logging_obj=None, + user_api_key_auth=UserAPIKeyAuth(api_key="hashed-key"), + ) + + assert capture_extra_headers.await_args is not None + captured_extra_headers: Final = capture_extra_headers.await_args.args[0] + assert captured_extra_headers == {"x-tenant": "tenant-control"} + @pytest.mark.asyncio async def test_call_regular_mcp_tool_v2_authz_code_drops_caller_authorization( self, @@ -16193,6 +16446,7 @@ async def test_health_check_logs_upstream_exchange_only_for_http_failures( class _DiscoveryUpstream: def __init__(self) -> None: self.requests: tuple[tuple[str, str], ...] = () + self.tools: tuple[dict[str, object], ...] = () self.outcome = "supported" self.ttl_ms = 60000 self.entered = asyncio.Event() @@ -16254,7 +16508,7 @@ class _DiscoveryUpstream: "resources/templates/list": { "resourceTemplates": [{"name": "example", "uriTemplate": "test://{name}", "description": "original"}] }, - "tools/list": {"tools": []}, + "tools/list": {"tools": list(self.tools)}, }[payload.method] continuation: Final = ( {"nextCursor": "last-page"} @@ -16291,6 +16545,64 @@ def _discovery_server() -> MCPServer: ) +@pytest.mark.asyncio +async def test_per_user_authorization_server_lists_without_static_credential() -> None: + upstream: Final = _DiscoveryUpstream() + upstream.tools = ({"name": "search", "inputSchema": {"type": "object"}},) + server: Final = MCPServer( + server_id="per-user-auth", + name="per-user-auth", + url="https://discovery.example/mcp", + transport=MCPTransport.http, + protocol_version="2026-07-28", + auth_type=MCPAuth.authorization, + ) + manager: Final = MCPServerManager() + manager.registry[server.server_id] = server + + with _mcp_upstream(upstream.respond): + tools: Final = await manager.get_tools_from_server(server, add_prefix=False) + + assert [tool.name for tool in tools] == ["search"] + assert ("tools/list", "") in upstream.requests + with pytest.raises(HTTPException, match="requires a usable upstream credential"): + await manager.create_mcp_client(server) + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("auth_type", "credential", "upstream_token_header"), + ( + (MCPAuth.authorization, "Bearer", None), + (MCPAuth.authorization, "Bearer", "X-Token"), + (MCPAuth.authorization, " ", None), + (MCPAuth.authorization, " ", "X-Token"), + (MCPAuth.bearer_token, None, None), + ), +) +async def test_tool_listing_rejects_malformed_or_other_missing_static_credentials( + auth_type: MCPAuth, credential: str | None, upstream_token_header: str | None +) -> None: + upstream: Final = _DiscoveryUpstream() + server: Final = MCPServer( + server_id="invalid-static-auth", + name="invalid-static-auth", + url="https://discovery.example/mcp", + transport=MCPTransport.http, + protocol_version="2026-07-28", + auth_type=auth_type, + authentication_token=credential, + upstream_token_header=upstream_token_header, + ) + manager: Final = MCPServerManager() + manager.registry[server.server_id] = server + + with _mcp_upstream(upstream.respond), pytest.raises(MCPServerListError): + await manager.get_tools_from_server(server) + + assert upstream.requests == () + + @pytest.mark.asyncio @pytest.mark.parametrize("kind", ("prompts", "resources", "templates")) async def test_discovery_cache_reuses_raw_results_and_expires(kind: str) -> None: diff --git a/tests/unit/proxy/auth/test_auth_checks_object_access_and_lookup.py b/tests/unit/proxy/auth/test_auth_checks_object_access_and_lookup.py index c583407e61e..effdd9725c2 100644 --- a/tests/unit/proxy/auth/test_auth_checks_object_access_and_lookup.py +++ b/tests/unit/proxy/auth/test_auth_checks_object_access_and_lookup.py @@ -3753,6 +3753,85 @@ async def test_tag_max_budget_check_still_enforces_registered_tag_over_budget(): assert [call.kwargs["where"]["tag_name"]["in"] for call in batch_calls] == [["paid-tag"]] +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("client_tags", "key_metadata"), + [ + (b'"run-123"', {"tags": ["engineering"]}), + (b'""', {}), + (b"{}", {}), + (b"false", {}), + (b"0", {}), + ], + ids=["string_replaced_by_key_tags", "empty_string", "empty_object", "false", "zero"], +) +async def test_common_checks_rejects_a_spent_mapped_tag_whatever_non_list_tags_the_client_sends( + client_tags: bytes, key_metadata: dict[str, list[str]] +): + from litellm.proxy.auth.auth_checks import common_checks + from litellm.proxy.common_utils.http_parsing_utils import read_request_body + from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup + from litellm.proxy.utils import ProxyLogging + + async def fake_find_many(**kwargs): + if "where" not in kwargs: + return [_tag_registry_row("usecase:spent")] + return [_tag_db_row(name, max_budget=1.0) for name in kwargs["where"]["tag_name"]["in"]] + + async def spent_tag_spend(counter_key, fallback_spend, max_budget=None, **kwargs): + return 1.5 if counter_key == "spend:tag:usecase:spent" else fallback_spend + + async def receive(): + return { + "type": "http.request", + "body": b'{"model":"gpt-4o","messages":[{"role":"user","content":"hi"}],"metadata":{"tags":' + + client_tags + + b"}}", + } + + mock_prisma: Final = MagicMock() + mock_prisma.db.litellm_tagtable.find_many = AsyncMock(side_effect=fake_find_many) + request: Final = Request( + { + "type": "http", + "method": "POST", + "path": "/v1/chat/completions", + "scheme": "http", + "server": ("localhost", 4000), + "query_string": b"", + "headers": [(b"content-type", b"application/json"), (b"baggage", b"entrypoint=spent")], + }, + receive, + ) + request_body: Final = await read_request_body(request) + await LiteLLMProxyRequestSetup.apply_baggage_tag_mappings_pre_auth( + request, + request_body, + {"request_tag_mappings": [{"key": "entrypoint", "tag_prefix": "usecase:"}]}, + None, + MagicMock(), + ) + with ( + patch("litellm.proxy.proxy_server.prisma_client", mock_prisma), + patch("litellm.proxy.proxy_server.get_current_spend", spent_tag_spend), + pytest.raises(litellm.BudgetExceededError) as exc_info, + ): + await common_checks( + request_body=request_body, + team_object=None, + user_object=None, + end_user_object=None, + global_proxy_spend=None, + general_settings={}, + route="/v1/chat/completions", + llm_router=None, + proxy_logging_obj=ProxyLogging(user_api_key_cache=None), + valid_token=UserAPIKeyAuth(token="test-token", metadata=key_metadata), + request=request, + ) + assert exc_info.value.entity_id == "usecase:spent" + + @pytest.mark.asyncio async def test_get_team_object_raises_404_when_not_found(): from unittest.mock import AsyncMock, MagicMock @@ -11541,3 +11620,84 @@ async def test_authoritative_group_grants_propagate_policy_outages( await get_agent_ids_from_access_groups(["group"], check_db_only=True) else: assert await get_agent_ids_from_access_groups(["group"]) == [] + + +def _client_tag_request(client_tags, baggage): + return Request( + { + "type": "http", + "headers": [ + *([(b"baggage", b"entrypoint=a")] if baggage else []), + *([(b"x-litellm-tags", b"usecase:a")] if client_tags == "header" else []), + ], + } + ) + + +def _client_tag_body(client_tags, client_slot): + if client_tags is None or client_tags == "header": + return {} + return {client_slot: client_tags if isinstance(client_tags, str) else {"tags": client_tags}} + + +def _client_tag_rejection(route, data, request): + from litellm.proxy.auth.auth_checks import _reject_clientside_metadata_tags_check + + try: + _reject_clientside_metadata_tags_check({"reject_clientside_metadata_tags": True}, data, route, request) + except ProxyException as error: + return error.code + return None + + +@pytest.mark.asyncio +@pytest.mark.parametrize("route", ["/v1/chat/completions", "/v1/messages", "/v1/responses"]) +@pytest.mark.parametrize("client_tags", [None, [], ["usecase:a"], '{"tags":["usecase:a"]}', "header"]) +@pytest.mark.parametrize("client_slot", ["metadata", "litellm_metadata"]) +@pytest.mark.parametrize("baggage", [True, False]) +async def test_baggage_mapping_rejects_exactly_the_client_tags_rejected_without_it( + route, client_tags, client_slot, baggage +): + from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup + + unmapped_request = _client_tag_request(client_tags, baggage=False) + unmapped = _client_tag_body(client_tags, client_slot) + LiteLLMProxyRequestSetup.pre_seed_litellm_metadata_for_route(unmapped, route) + LiteLLMProxyRequestSetup.apply_client_tag_policy_pre_auth(unmapped_request, unmapped, UserAPIKeyAuth(api_key="qa-key")) + + mapped_request = _client_tag_request(client_tags, baggage=baggage) + mapped = _client_tag_body(client_tags, client_slot) + LiteLLMProxyRequestSetup.pre_seed_litellm_metadata_for_route(mapped, route) + await LiteLLMProxyRequestSetup.apply_baggage_tag_mappings_pre_auth( + mapped_request, + mapped, + {"request_tag_mappings": [{"key": "entrypoint", "tag_prefix": "usecase:"}]}, + None, + MagicMock(), + ) + LiteLLMProxyRequestSetup.apply_client_tag_policy_pre_auth(mapped_request, mapped, UserAPIKeyAuth(api_key="qa-key")) + + assert _client_tag_rejection(route, mapped, mapped_request) == _client_tag_rejection( + route, unmapped, unmapped_request + ) + if client_tags is None and baggage: + assert "usecase:a" in mapped["metadata" if "chat/completions" in route else "litellm_metadata"]["tags"] + + +@pytest.mark.asyncio +async def test_baggage_mapping_still_rejects_client_metadata_tags(): + from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup + + request = _client_tag_request(["usecase:b"], baggage=True) + data = {"metadata": {"tags": ["usecase:b"]}} + await LiteLLMProxyRequestSetup.apply_baggage_tag_mappings_pre_auth( + request, + data, + {"request_tag_mappings": [{"key": "entrypoint", "tag_prefix": "usecase:"}]}, + None, + MagicMock(), + ) + assert _client_tag_rejection("/v1/chat/completions", data, request) == "400" + from litellm.utils import get_request_guardrails + + assert get_request_guardrails(data) == [] diff --git a/tests/unit/proxy/auth/test_auth_utils.py b/tests/unit/proxy/auth/test_auth_utils.py index f81ba155097..ee1ae43fd3a 100644 --- a/tests/unit/proxy/auth/test_auth_utils.py +++ b/tests/unit/proxy/auth/test_auth_utils.py @@ -3566,6 +3566,7 @@ class TestIsRequestBodySafeBlocksEndpointTargetingFields: "field", [ "aws_bedrock_runtime_endpoint", + "aws_bedrock_control_plane_endpoint", "langsmith_base_url", "langfuse_host", "posthog_host", @@ -3901,6 +3902,38 @@ class TestIsRequestBodySafeBlocksNVCFFunctionOverride: ) +def test_riva_offline_in_request_body_is_rejected() -> None: + with pytest.raises(ValueError, match="riva_offline"): + is_request_body_safe( + request_body={"model": "nvidia_riva/parakeet", "riva_offline": True}, + general_settings={}, + llm_router=None, + model="nvidia_riva/parakeet", + ) + + +def test_admin_opt_in_proxy_wide_allows_riva_offline() -> None: + assert ( + is_request_body_safe( + request_body={"model": "nvidia_riva/parakeet", "riva_offline": True}, + general_settings={"allow_client_side_credentials": True}, + llm_router=None, + model="nvidia_riva/parakeet", + ) + is True + ) + + +def test_api_base_override_keeps_the_deployments_riva_offline_mode() -> None: + from litellm.router_utils.clientside_credential_handler import get_dynamic_litellm_params + + out: Final = get_dynamic_litellm_params( + litellm_params={"model": "nvidia_riva/nvidia/parakeet-0.6b-tdt", "riva_offline": True}, + request_kwargs={"api_base": "caller-riva:50051"}, + ) + assert (out["api_base"], out["riva_offline"]) == ("caller-riva:50051", True) + + class TestIsRequestBodySafeBlocksRivaUseSsl: """``use_ssl`` is rejected as a request-body param unless the admin opted in proxy-wide or per-deployment.""" @@ -5087,7 +5120,7 @@ def test_get_model_from_request_vertex_ai_passthrough(request_data, route, expec @pytest.mark.parametrize( "field", - ["github_copilot_auth_type", "user_provider_credentials", "github_copilot_user_session"], + ["github_copilot_auth_type", "github_copilot_host", "user_provider_credentials", "github_copilot_user_session"], ) def test_per_user_credential_slots_in_request_body_are_rejected(field: str) -> None: """The per-user Copilot mode is decided by the stored credential's values and the caller's diff --git a/tests/unit/proxy/auth/test_user_api_key_auth.py b/tests/unit/proxy/auth/test_user_api_key_auth.py index 3660019cc2c..60a8dd73a34 100644 --- a/tests/unit/proxy/auth/test_user_api_key_auth.py +++ b/tests/unit/proxy/auth/test_user_api_key_auth.py @@ -2102,3 +2102,183 @@ async def test_jwt_path_skips_user_model_budget_only_for_zero_spend_mcp_methods( assert result.user_id == "jwt-user" assert user_model_budget_check.await_count == (1 if expect_user_model_budget_check else 0) + + +def _qa_websocket(messages): + async def receive(): + return {"type": "websocket.connect"} + + async def send(message): + messages.append(message) + + return WebSocket( + { + "type": "websocket", + "path": "/v1/responses", + "scheme": "ws", + "server": ("localhost", 4000), + "query_string": b"model=qa-model", + "headers": [(b"authorization", b"Bearer qa-key")], + }, + receive=receive, + send=send, + ) + + +@pytest.mark.asyncio +@pytest.mark.parametrize("close_on_auth_error", [True, False]) +async def test_websocket_inference_is_denied_when_a_required_baggage_mapping_is_configured(close_on_auth_error): + from litellm.proxy.auth.user_api_key_auth import user_api_key_auth_websocket_for_model + + messages = [] + with ( + patch.dict( + litellm.proxy.proxy_server.general_settings, + { + "request_tag_mappings": [ + {"key": "region", "tag_prefix": "region:"}, + {"key": "entrypoint", "tag_prefix": "usecase:", "required": True}, + ] + }, + ), + patch( + "litellm.proxy.auth.user_api_key_auth.user_api_key_auth", + new=AsyncMock(return_value=UserAPIKeyAuth(api_key="qa-key")), + ), + ): + with pytest.raises(HTTPException, match="WebSocket inference is disabled") as error: + await user_api_key_auth_websocket_for_model( + _qa_websocket(messages), "qa-model", close_on_auth_error=close_on_auth_error + ) + assert error.value.status_code == 403 + assert messages == ([{"type": "websocket.close", "code": 1008, "reason": ""}] if close_on_auth_error else []) + + +@pytest.mark.asyncio +async def test_websocket_invalid_key_is_rejected_before_the_required_baggage_mapping_denial(): + from litellm.proxy.auth.user_api_key_auth import user_api_key_auth_websocket_for_model + + with ( + patch.dict( + litellm.proxy.proxy_server.general_settings, + {"request_tag_mappings": [{"key": "entrypoint", "tag_prefix": "usecase:", "required": True}]}, + ), + patch( + "litellm.proxy.auth.user_api_key_auth.user_api_key_auth", + new=AsyncMock(side_effect=HTTPException(status_code=401, detail="Invalid proxy server token passed")), + ), + ): + with pytest.raises(HTTPException) as error: + await user_api_key_auth_websocket_for_model(_qa_websocket([]), "qa-model", close_on_auth_error=False) + assert error.value.status_code == 401 + + +@pytest.mark.asyncio +async def test_websocket_inference_is_allowed_when_no_baggage_mapping_is_required(): + from litellm.proxy.auth.user_api_key_auth import user_api_key_auth_websocket_for_model + + messages = [] + authorized = UserAPIKeyAuth(api_key="qa-key") + with ( + patch.dict( + litellm.proxy.proxy_server.general_settings, + {"request_tag_mappings": [{"key": "entrypoint", "tag_prefix": "usecase:", "require_budgeted_tag": True}]}, + ), + patch( + "litellm.proxy.auth.user_api_key_auth.user_api_key_auth", new=AsyncMock(return_value=authorized) + ) as http_auth, + ): + result = await user_api_key_auth_websocket_for_model(_qa_websocket(messages), "qa-model") + assert result is authorized + assert http_auth.await_args.kwargs["api_key"] == "Bearer qa-key" + assert messages == [] + + +async def _auth_then_serve_chat(monkeypatch, general_settings, body, headers): + import copy + + from fastapi import Request as FastAPIRequest + from fastapi import Response + + from litellm.proxy.common_utils.http_parsing_utils import read_request_body + from litellm.proxy.proxy_server import chat_completion + + router = litellm.Router( + model_list=[ + { + "model_name": "gpt-4", + "litellm_params": {"model": "gpt-4o", "tags": ["usecase:a"], "mock_response": "hi"}, + "model_info": {"id": "usecase-deployment"}, + }, + { + "model_name": "gpt-4", + "litellm_params": {"model": "gpt-4o-mini", "tags": ["default"], "mock_response": "hi"}, + "model_info": {"id": "default-deployment"}, + }, + ], + enable_tag_filtering=True, + ) + monkeypatch.setattr(litellm.proxy.proxy_server, "master_key", MASTER_KEY) + monkeypatch.setattr(litellm.proxy.proxy_server, "prisma_client", None) + monkeypatch.setattr(litellm.proxy.proxy_server, "llm_router", router) + monkeypatch.setattr(litellm.proxy.proxy_server, "general_settings", general_settings) + + async def receive(): + return {"type": "http.request", "body": json.dumps(body).encode()} + + request = FastAPIRequest( + { + "type": "http", + "method": "POST", + "path": "/chat/completions", + "scheme": "http", + "server": ("localhost", 4000), + "query_string": b"", + "headers": [(b"content-type", b"application/json"), *headers], + }, + receive, + ) + auth = await user_api_key_auth(request=request, api_key=f"Bearer {MASTER_KEY}") + cached_body = copy.deepcopy(await read_request_body(request)) + response = Response() + await chat_completion(request=request, fastapi_response=response, user_api_key_dict=auth) + return cached_body, response.headers["x-litellm-model-id"] + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "general_settings", + [{}, {"request_tag_mappings": [{"key": "region", "tag_prefix": "region:"}]}], + ids=["no_mappings", "mapped_baggage"], +) +async def test_auth_header_tag_merge_keeps_json_string_metadata_tags_routable(monkeypatch, general_settings): + body = { + "model": "gpt-4", + "messages": [{"role": "user", "content": "hi"}], + "metadata": json.dumps({"tags": ["usecase:a"]}), + } + cached_body, served_by = await _auth_then_serve_chat( + monkeypatch, general_settings, body, [(b"x-litellm-tags", b"other"), (b"baggage", b"region=sg")] + ) + assert served_by == "usecase-deployment" + assert cached_body["metadata"] == {"tags": ["usecase:a", "other"]} + + +@pytest.mark.asyncio +@pytest.mark.parametrize("client_metadata", ["run-123", 42, ["x"]]) +@pytest.mark.parametrize( + "baggage", + [[], [(b"baggage", b"region=sg")], [(b"baggage", b"entrypoint=a")]], + ids=["no_baggage", "unmapped_baggage", "mapped_baggage"], +) +async def test_non_object_metadata_is_served_like_unset_mappings_whatever_the_baggage_maps( + monkeypatch, client_metadata, baggage +): + body = {"model": "gpt-4", "messages": [{"role": "user", "content": "hi"}], "metadata": client_metadata} + headers = [(b"x-litellm-tags", b"usecase:a"), *baggage] + unset = await _auth_then_serve_chat(monkeypatch, {}, body, headers) + mapped = await _auth_then_serve_chat( + monkeypatch, {"request_tag_mappings": [{"key": "entrypoint", "tag_prefix": "usecase:"}]}, body, headers + ) + assert mapped == unset + assert mapped[1] == "usecase-deployment" diff --git a/tests/unit/proxy/common_utils/test_check_batch_cost.py b/tests/unit/proxy/common_utils/test_check_batch_cost.py index e3012dfcd13..33b8085e082 100644 --- a/tests/unit/proxy/common_utils/test_check_batch_cost.py +++ b/tests/unit/proxy/common_utils/test_check_batch_cost.py @@ -11,7 +11,8 @@ import json import logging from concurrent.futures import ThreadPoolExecutor from contextlib import contextmanager -from datetime import datetime +from copy import copy +from datetime import datetime, timezone from hashlib import sha256 from queue import SimpleQueue from types import SimpleNamespace @@ -217,7 +218,7 @@ class TestCheckBatchCost: find_call = mock_prisma_client.db.litellm_managedobjecttable.find_many.call_args assert find_call[1]["take"] == MAX_OBJECTS_PER_POLL_CYCLE - assert find_call[1]["order"] == {"created_at": "asc"} + assert find_call[1]["order"] == [{"created_at": "asc"}, {"id": "asc"}] not_in = find_call[1]["where"]["status"]["not_in"] assert "stale_expired" in not_in # "complete"/"completed" are intentionally NOT excluded from the @@ -240,13 +241,13 @@ class TestCheckBatchCost: mock_prisma_client.db.litellm_managedobjecttable.update_many = AsyncMock(return_value=1) # First find_many (primary query) raises with a schema error; second (fallback) returns empty mock_prisma_client.db.litellm_managedobjecttable.find_many = AsyncMock( - side_effect=[Exception("column batch_processed does not exist"), []] + side_effect=[Exception("column batch_processed does not exist"), [], []] ) await check_batch_cost_instance.check_batch_cost() calls = mock_prisma_client.db.litellm_managedobjecttable.find_many.call_args_list - assert len(calls) == 2 + assert len(calls) == 3 fallback_where = calls[1][1]["where"] assert "batch_processed" not in fallback_where assert "stale_expired" in fallback_where["status"]["not_in"] @@ -267,8 +268,7 @@ class TestCheckBatchCost: await check_batch_cost_instance.check_batch_cost() - # Only one find_many call — the fallback directly, no primary query attempt - assert mock_prisma_client.db.litellm_managedobjecttable.find_many.call_count == 1 + assert mock_prisma_client.db.litellm_managedobjecttable.find_many.call_count == 2 fallback_where = mock_prisma_client.db.litellm_managedobjecttable.find_many.call_args[1]["where"] assert "batch_processed" not in fallback_where @@ -744,7 +744,7 @@ class TestCheckBatchCost: await check_batch_cost_instance.check_batch_cost() - assert mock_prisma_client.db.litellm_managedobjecttable.update_many.call_count >= 3, ( + assert mock_prisma_client.db.litellm_managedobjecttable.update_many.call_count == 2, ( "Expected update() to be called exactly once for the completed job" ) update_data = mock_prisma_client.db.litellm_managedobjecttable.update_many.call_args[1]["data"] @@ -877,7 +877,7 @@ class TestCheckBatchCost: mock_update_database.assert_awaited_once() assert mock_update_database.call_args.kwargs["response_cost"] == 0.01 - assert mock_prisma_client.db.litellm_managedobjecttable.update_many.call_count >= 3, ( + assert mock_prisma_client.db.litellm_managedobjecttable.update_many.call_count == 2, ( "the job must still be marked processed once cost tracking succeeds" ) @@ -979,10 +979,10 @@ class TestCheckBatchCost: await check_batch_cost_instance.check_batch_cost() - assert mock_prisma_client.db.litellm_managedobjecttable.update.call_count == 1, ( + assert mock_prisma_client.db.litellm_managedobjecttable.update_many.call_count == 2, ( f"Expected update() to be called exactly once for a {terminal_status} job" ) - update_data = mock_prisma_client.db.litellm_managedobjecttable.update.call_args[1]["data"] + update_data = mock_prisma_client.db.litellm_managedobjecttable.update_many.call_args[1]["data"] assert update_data["status"] == terminal_status assert update_data["batch_processed"] is True, ( "terminal-status update() must set batch_processed=True so polling stops" @@ -1085,9 +1085,13 @@ class TestCheckBatchCost: assert owner.user_id == "user-1" assert owner.team_id == "team-1" - assert mock_prisma_client.db.litellm_managedobjecttable.update.call_count == 1 - update_call = mock_prisma_client.db.litellm_managedobjecttable.update.call_args - assert update_call.kwargs["where"] == {"id": "job-terminal-mint-1"} + assert mock_prisma_client.db.litellm_managedobjecttable.update_many.call_count == 2 + update_call = mock_prisma_client.db.litellm_managedobjecttable.update_many.call_args + assert update_call.kwargs["where"] == { + "id": "job-terminal-mint-1", + "batch_processed": False, + "updated_at": mock_job.updated_at, + } update_data = update_call.kwargs["data"] assert update_data["status"] == terminal_status assert update_data["batch_processed"] is True @@ -1152,10 +1156,10 @@ class TestCheckBatchCost: ) as mock_afile_content: await check_batch_cost_instance.check_batch_cost() - assert mock_prisma_client.db.litellm_managedobjecttable.update.call_count == 1, ( + assert mock_prisma_client.db.litellm_managedobjecttable.update_many.call_count == 2, ( "a completed batch with no output file must be marked processed exactly once" ) - update_data = mock_prisma_client.db.litellm_managedobjecttable.update.call_args[1]["data"] + update_data = mock_prisma_client.db.litellm_managedobjecttable.update_many.call_args[1]["data"] assert update_data["status"] == completed_status assert update_data["batch_processed"] is True, ( "completed-without-output update() must set batch_processed=True so polling stops" @@ -1371,7 +1375,7 @@ class TestCheckBatchCost: f"{terminal_status} batch with an output file must fetch results and be billed" ) mock_logging_obj.async_success_handler.assert_awaited_once() - assert mock_prisma_client.db.litellm_managedobjecttable.update_many.call_count >= 3 + assert mock_prisma_client.db.litellm_managedobjecttable.update_many.call_count == 2 update_data = mock_prisma_client.db.litellm_managedobjecttable.update_many.call_args[1]["data"] assert update_data["batch_processed"] is True assert update_data["status"] == terminal_status, ( @@ -1544,10 +1548,10 @@ class TestCheckBatchCost: assert mock_afile_content.await_count == 1 mock_calculate.assert_not_awaited() - assert mock_prisma_client.db.litellm_managedobjecttable.update.call_count == 1, ( + assert mock_prisma_client.db.litellm_managedobjecttable.update_many.call_count == 2, ( "a terminal batch with a 404ing output file must be retired, not retried forever" ) - update_data = mock_prisma_client.db.litellm_managedobjecttable.update.call_args[1]["data"] + update_data = mock_prisma_client.db.litellm_managedobjecttable.update_many.call_args[1]["data"] assert update_data["status"] == "failed" assert update_data["batch_processed"] is True @@ -1942,7 +1946,7 @@ class TestUnmanagedVertexRouting: mock_logging_obj.async_success_handler.assert_awaited_once() assert mock_logging_obj.async_success_handler.call_args[1]["batch_cost"] == 0.01 - assert prisma.db.litellm_managedobjecttable.update_many.call_count >= 3 + assert prisma.db.litellm_managedobjecttable.update_many.call_count == 2 update_data = prisma.db.litellm_managedobjecttable.update_many.call_args[1]["data"] assert update_data["batch_processed"] is True assert update_data["status"] == "complete" @@ -2159,7 +2163,7 @@ class TestUnmanagedBedrockRouting: mock_logging_obj.async_success_handler.assert_awaited_once() assert mock_logging_obj.async_success_handler.call_args[1]["batch_cost"] == 0.02 - assert prisma.db.litellm_managedobjecttable.update_many.call_count >= 3 + assert prisma.db.litellm_managedobjecttable.update_many.call_count == 2 update_data = prisma.db.litellm_managedobjecttable.update_many.call_args[1]["data"] assert update_data["batch_processed"] is True assert update_data["status"] == "complete" @@ -2740,9 +2744,10 @@ class TestPollPageStarvation: await self._instance(prisma, llm_router).check_batch_cost() llm_router.aretrieve_batch.assert_not_awaited() - prisma.db.litellm_managedobjecttable.update.assert_awaited_once() - call = prisma.db.litellm_managedobjecttable.update.call_args[1] - assert call["where"] == {"id": "job-no-model"} + prisma.db.litellm_managedobjecttable.update_many.assert_awaited() + call = prisma.db.litellm_managedobjecttable.update_many.call_args[1] + assert call["where"]["id"] == "job-no-model" + assert call["where"]["batch_processed"] is False assert call["data"] == {"batch_processed": True} @pytest.mark.asyncio @@ -2770,8 +2775,8 @@ class TestPollPageStarvation: await self._instance(prisma, llm_router).check_batch_cost() - prisma.db.litellm_managedobjecttable.update.assert_awaited_once() - assert prisma.db.litellm_managedobjecttable.update.call_args[1]["data"] == {"batch_processed": True} + prisma.db.litellm_managedobjecttable.update_many.assert_awaited() + assert prisma.db.litellm_managedobjecttable.update_many.call_args[1]["data"] == {"batch_processed": True} @pytest.mark.asyncio async def test_provider_404_with_deployment_gone_keeps_job(self): @@ -2830,24 +2835,7 @@ class TestPollPageStarvation: await instance.check_batch_cost() - assert prisma.db.litellm_managedobjecttable.update.call_args[1]["data"] == {"status": "stale_expired"} - - @pytest.mark.asyncio - async def test_stale_cleanup_gives_up_on_never_costed_completed_rows(self): - """A row already in a terminal status is never rewritten by the staleness sweep, so - it needs its own bound or it starves newer batches indefinitely.""" - prisma = self._prisma([]) - - await self._instance(prisma, MagicMock()).check_batch_cost() - - calls = prisma.db.litellm_managedobjecttable.update_many.call_args_list - assert len(calls) == 2, "expected the staleness sweep plus the never-costed sweep" - where = calls[1][1]["where"] - assert where["file_purpose"] == "batch" - assert where["batch_processed"] is False - assert where["status"] == {"in": ["complete", "completed"]} - assert "created_at" in where - assert calls[1][1]["data"] == {"batch_processed": True} + assert prisma.db.litellm_managedobjecttable.update_many.call_args[1]["data"] == {"status": "stale_expired"} @pytest.mark.asyncio async def test_newer_batch_is_polled_once_dead_rows_are_retired(self): @@ -2885,7 +2873,11 @@ class TestPollPageStarvation: await self._instance(prisma, llm_router).check_batch_cost() - retired = [call[1]["where"]["id"] for call in prisma.db.litellm_managedobjecttable.update.call_args_list] + retired = [ + call[1]["where"]["id"] + for call in prisma.db.litellm_managedobjecttable.update_many.call_args_list + if "id" in call[1]["where"] + ] assert retired == ["job-no-model", "job-gone"] assert llm_router.aretrieve_batch.await_args_list[-1][1]["batch_id"] == "batch_live", ( "the newer healthy batch must still be polled in the same cycle" @@ -2933,7 +2925,8 @@ class _FakeManagedObjectRow: self.team_id = None self.api_key = None self.request_tags = None - self.created_at = 1700000000 + self.created_at = datetime(9999, 1, 1, tzinfo=timezone.utc) + self.updated_at = datetime(2000, 1, 1, tzinfo=timezone.utc) self.file_object = json.dumps( { "id": "batch-456", @@ -2963,7 +2956,9 @@ class _FakeManagedObjectTable: def _matches(self, where: dict) -> bool: for key, value in where.items(): if key == "created_at": - return False + if "lt" in value and not self.row.created_at < value["lt"]: + return False + continue if key == "status": if self.row.status in value.get("not_in", []): return False @@ -2976,7 +2971,9 @@ class _FakeManagedObjectTable: async def _update_many(self, *, where: dict, data: dict) -> int: if not self._matches(where): return 0 - if "batch_processed" in where: + if "updated_at" in where: + self.journal.append("finalize") + elif "batch_processed" in where: self.journal.append("claim" if data.get("batch_processed") else "release") for key, value in data.items(): setattr(self.row, key, value) @@ -3107,6 +3104,151 @@ class TestMultiPodBatchCostClaim: ): yield logging_obj + @pytest.mark.asyncio + @pytest.mark.parametrize("failure_phase", ("before_write", "after_write", "external")) + @pytest.mark.parametrize("collector_enabled", (False, True)) + async def test_builtin_accounting_retries_only_before_a_possible_charge( + self, failure_phase: str, collector_enabled: bool + ) -> None: + import base64 + from datetime import datetime + + import httpx + import litellm + import respx + + from litellm.caching.caching import DualCache + from litellm.integrations.custom_logger import CustomLogger + from litellm.router_strategy.budget_limiter import RouterBudgetLimiting + from litellm.proxy.db.db_spend_update_writer import DBSpendUpdateWriter + from litellm.proxy.hooks.proxy_track_cost_callback import ProxyDBLogger + from litellm.proxy.utils import PrismaClient + from litellm.types.router import Deployment, LiteLLM_Params, ModelInfo + from litellm.types.utils import SpecialEnums + + class AccountingDependency: + def __init__(self) -> None: + self.failure_phase = failure_phase + self.writer: Final = DBSpendUpdateWriter() + self.failed_tracking_alert = AsyncMock() + self.slack_alerting_instance = MagicMock() + self.slack_alerting_instance.customer_spend_alert = AsyncMock( + side_effect=ConnectionError("Alert destination unavailable after charge") + if failure_phase == "after_write" + else None + ) + + @property + def db_spend_update_writer(self) -> DBSpendUpdateWriter: + if self.failure_phase == "before_write": + raise ConnectionError("Accounting dependency temporarily unavailable") + return self.writer + + class ExternalCallback(CustomLogger): + async def async_log_success_event( + self, kwargs: dict[str, object], response_obj: object, start_time: datetime, end_time: datetime + ) -> None: + if failure_phase == "external": + raise ConnectionError("External destination unavailable") + + budget_cache: Final = DualCache() + RouterBudgetLimiting( + dual_cache=budget_cache, + provider_budget_config={"openai": {"budget_limit": 100, "time_period": "1d"}}, + model_list=[ + { + "model_name": "batch-alias", + "litellm_params": {"model": "openai/batch-test-model", "max_budget": 100, "budget_duration": "1d"}, + "model_info": {"id": "model-123"}, + } + ], + ) + dependency: Final = AccountingDependency() + spend_prisma: Final = PrismaClient( + database_url="postgresql://unused:unused@localhost:5432/unused", proxy_logging_obj=dependency + ) + create_spend_rows: Final = AsyncMock(return_value=1) + input_rate: Final = 0.000002 + litellm.register_model( + { + "batch-test-model": { + "litellm_provider": "openai", + "mode": "chat", + "input_cost_per_token_batches": input_rate, + "output_cost_per_token_batches": 0.000006, + } + } + ) + content: Final = json.dumps( + { + "response": { + "status_code": 200, + "body": { + "model": "batch-test-model", + "usage": {"prompt_tokens": 100, "completion_tokens": 0, "total_tokens": 100}, + }, + }, + "error": None, + } + ).encode() + row: Final = _FakeManagedObjectRow() + original_status: Final = row.status + original_file_object: Final = row.file_object + row.unified_object_id = ( + base64.urlsafe_b64encode( + SpecialEnums.LITELLM_MANAGED_BATCH_COMPLETE_STR.value.format("model-123", "batch-456").encode() + ) + .decode() + .rstrip("=") + ) + prisma: Final = self._prisma(row, []) + router: Final = self._router() + router.get_deployment.return_value = Deployment( + model_name="batch-alias", + litellm_params=LiteLLM_Params(model="openai/batch-test-model"), + model_info=ModelInfo(id="model-123"), + ) + from litellm.proxy.spend_tracking.spend_event_producer import SpendEventProducer + + producer: Final = MagicMock(spec=SpendEventProducer) if collector_enabled else None + litellm.logging_callback_manager.add_litellm_async_success_callback( + ProxyDBLogger(spend_event_producer=producer) + ) + litellm.logging_callback_manager.add_litellm_async_success_callback(ExternalCallback()) + with ( + respx.mock, + patch("litellm.proxy.proxy_server.proxy_logging_obj", dependency), + patch("litellm.proxy.proxy_server.prisma_client", spend_prisma), + patch.object( + spend_prisma.writer_db._original_prisma, + "litellm_spendlogs", + MagicMock(create_many=create_spend_rows), + ), + ): + respx.get(f"https://api.openai.com/v1/files/{_CLAIM_OUTPUT_FILE_ID}/content").mock( + return_value=httpx.Response(200, content=content) + ) + worker: Final = self._instance(prisma, router) + await worker.check_batch_cost() + assert row.batch_processed is (failure_phase != "before_write") + if failure_phase == "before_write": + assert row.status == original_status + assert json.loads(row.file_object) == original_file_object + assert create_spend_rows.await_count == (0 if failure_phase == "before_write" else 1) + dependency.failure_phase = "recovered" + await worker.check_batch_cost() + await worker.check_batch_cost() + + assert row.batch_processed is True + assert await budget_cache.async_get_cache("provider_spend:openai:1d") == pytest.approx(100 * input_rate) + assert await budget_cache.async_get_cache("deployment_spend:model-123:1d") == pytest.approx(100 * input_rate) + create_spend_rows.assert_awaited_once() + assert create_spend_rows.call_args.kwargs["data"][0]["spend"] == pytest.approx(100 * input_rate) + if producer is not None: + assert all( + json.loads(call.args[0])["call_type"] != "aretrieve_batch" for call in producer.publish.call_args_list + ) + @pytest.mark.asyncio @pytest.mark.parametrize( ("deployment_model", "successes", "failures", "expected_model"), @@ -3224,6 +3366,89 @@ class TestMultiPodBatchCostClaim: ["batch-test-model"] if deployment_model == "openai/batch-test-model" else ["batch-test-model"] * successes ) + @pytest.mark.asyncio + @pytest.mark.parametrize("error_source", ("batch", "output")) + async def test_a_404_for_another_identifier_preserves_recovery(self, error_source: str) -> None: + import base64 + + import httpx + import litellm + import respx + + from litellm.integrations.custom_logger import CustomLogger + from litellm.types.utils import SpecialEnums + + class SpendRecorder(CustomLogger): + def __init__(self) -> None: + super().__init__() + self.costs: tuple[float, ...] = () + + async def async_log_success_event( + self, kwargs: dict[str, object], response_obj: object, start_time: datetime, end_time: datetime + ) -> None: + if kwargs["call_type"] == "aretrieve_batch": + cost: Final = kwargs["response_cost"] + assert isinstance(cost, float) + self.costs += (cost,) + + recorder: Final = SpendRecorder() + litellm.logging_callback_manager.add_litellm_async_success_callback(recorder) + litellm.register_model( + { + "batch-recovery-model": { + "litellm_provider": "openai", + "mode": "chat", + "input_cost_per_token_batches": 0.01, + "output_cost_per_token_batches": 0.02, + } + } + ) + row: Final = _FakeManagedObjectRow() + row.unified_object_id = ( + base64.urlsafe_b64encode( + SpecialEnums.LITELLM_MANAGED_BATCH_COMPLETE_STR.value.format("model-123", "batch-456").encode() + ) + .decode() + .rstrip("=") + ) + router: Final = self._router() + response: Final = router.aretrieve_batch.return_value + error: Final = litellm.NotFoundError( + message=f"No object found with id '{'batch-456' if error_source == 'batch' else _CLAIM_OUTPUT_FILE_ID}0'.", + model="gpt-4", + llm_provider="openai", + ) + router.aretrieve_batch.side_effect = (error, response) if error_source == "batch" else (response, response) + prisma: Final = self._prisma(row, []) + output: Final = json.dumps( + { + "response": { + "status_code": 200, + "body": { + "model": "batch-recovery-model", + "usage": {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15}, + }, + }, + "error": None, + } + ).encode() + with respx.mock: + route: Final = respx.get(f"https://api.openai.com/v1/files/{_CLAIM_OUTPUT_FILE_ID}/content") + route.mock( + side_effect=error if error_source == "output" else None, + return_value=None if error_source == "output" else httpx.Response(200, content=output), + ) + await self._instance(prisma, router).check_batch_cost() + assert row.batch_processed is False + assert recorder.costs == () + route.mock(return_value=httpx.Response(200, content=output)) + await self._instance(prisma, router).check_batch_cost() + await self._instance(prisma, router).check_batch_cost() + + assert row.batch_processed is True + assert row.status == "complete" + assert recorder.costs == (pytest.approx(10 * 0.01 + 5 * 0.02),) + @staticmethod def _claim_calls(prisma) -> list: return [ @@ -3309,30 +3534,23 @@ class TestMultiPodBatchCostClaim: @pytest.mark.asyncio @pytest.mark.parametrize("stored_as_json_string", (True, False)) - async def test_a_failed_spend_log_write_releases_the_claim(self, stored_as_json_string: bool) -> None: - """A transient failure while billing a claimed batch must hand the row back, or its - spend is silently lost instead of being retried on the next cycle.""" - row = _FakeManagedObjectRow() - original_file_object: Final = row.file_object if stored_as_json_string else json.loads(row.file_object) - row.file_object = original_file_object - journal = [] - prisma = self._prisma(row, journal) + async def test_an_unclassified_logging_failure_keeps_the_claim(self, stored_as_json_string: bool) -> None: + row: Final = _FakeManagedObjectRow() + row.file_object = row.file_object if stored_as_json_string else json.loads(row.file_object) + journal: Final = [] + prisma: Final = self._prisma(row, journal) - with self._billing_patches(journal, bill_error=Exception("spend log write failed")): + with self._billing_patches(journal, bill_error=Exception("Accounting outcome unknown")): await self._instance(prisma, self._router()).check_batch_cost() - assert journal == ["fetch", "claim", "bill", "release"] - assert row.batch_processed is False - assert row.status == "in_progress" - assert json.loads(row.file_object) == original_file_object + assert journal == ["fetch", "claim", "bill"] + assert row.batch_processed is True with self._billing_patches(journal) as logging_obj: await self._instance(prisma, self._router()).check_batch_cost() await self._instance(prisma, self._router()).check_batch_cost() - assert row.batch_processed is True - assert row.status == "complete" - logging_obj.async_success_handler.assert_awaited_once() + logging_obj.async_success_handler.assert_not_awaited() @pytest.mark.asyncio async def test_a_worker_interrupted_mid_costing_leaves_the_batch_billable(self): @@ -3696,12 +3914,17 @@ class TestBatchLineItemsFromThePoller: assert logger.payloads == [] @pytest.mark.asyncio - async def test_a_batch_that_could_not_be_retired_sends_no_lines_until_it_is(self, monkeypatch): + @pytest.mark.parametrize("database_error", [False, True]) + async def test_a_batch_that_could_not_be_retired_sends_no_lines_until_it_is( + self, monkeypatch: pytest.MonkeyPatch, database_error: bool + ) -> None: import litellm journal: list = [] row, instance = self._setup(journal, status="expired", output_file_id=None, error_file_id="file-err-1") - instance.prisma_client.db.litellm_managedobjecttable.update = AsyncMock(side_effect=RuntimeError("db down")) + instance.prisma_client.db.litellm_managedobjecttable.update_many = AsyncMock( + side_effect=RuntimeError("db down") if database_error else None, return_value=0 + ) logger = self._recording_logger(journal) monkeypatch.setattr(litellm, "batch_line_item_callbacks", (logger,)) @@ -4111,6 +4334,127 @@ class TestCreatorTurnedOffMessageLogging: instance.prisma_client.db.litellm_verificationtoken.find_unique.assert_not_called() +@pytest.mark.asyncio +async def test_old_completed_batch_remains_available_for_costing() -> None: + row: Final = _FakeManagedObjectRow() + row.status = "completed" + row.created_at = datetime(2000, 1, 1, tzinfo=timezone.utc) + prisma: Final = TestMultiPodBatchCostClaim._prisma(row, []) + poller: Final = TestMultiPodBatchCostClaim._instance(prisma, TestMultiPodBatchCostClaim._router()) + + await poller._cleanup_stale_managed_objects() + + assert row.batch_processed is False + assert row.status == "completed" + + +@pytest.mark.asyncio +@pytest.mark.parametrize("progress", ["claimed", "refreshed"]) +async def test_stale_retirement_preserves_concurrent_progress(progress: str) -> None: + row: Final = _FakeManagedObjectRow() + selected: Final = copy(row) + if progress == "claimed": + row.batch_processed = True + row.updated_at = datetime(2000, 1, 2, tzinfo=timezone.utc) + prisma: Final = TestMultiPodBatchCostClaim._prisma(row, []) + poller: Final = TestMultiPodBatchCostClaim._instance(prisma, TestMultiPodBatchCostClaim._router()) + + await poller._retire_job(selected, "provider batch disappeared") + + assert row.batch_processed is (progress == "claimed") + assert row.updated_at > selected.updated_at + + +@pytest.mark.asyncio +@pytest.mark.parametrize("progress", ["claimed", "refreshed"]) +async def test_stale_terminal_response_preserves_concurrent_progress(progress: str) -> None: + from litellm.types.utils import LiteLLMBatch + + row: Final = _FakeManagedObjectRow() + selected: Final = copy(row) + if progress == "claimed": + row.batch_processed = True + row.updated_at = datetime(2000, 1, 2, tzinfo=timezone.utc) + row.file_object = '{"revision":"fresh"}' + prisma: Final = TestMultiPodBatchCostClaim._prisma(row, []) + poller: Final = TestMultiPodBatchCostClaim._instance(prisma, TestMultiPodBatchCostClaim._router()) + response: Final = LiteLLMBatch( + id="batch-456", + completion_window="24h", + created_at=1, + endpoint="/v1/chat/completions", + input_file_id="file-input-1", + object="batch", + status="failed", + ) + + assert await poller._finalize_unbilled_terminal_job(selected, response) is False + + assert row.file_object == '{"revision":"fresh"}' + assert row.status == "in_progress" + assert row.batch_processed is (progress == "claimed") + + +@pytest.mark.asyncio +@pytest.mark.parametrize("legacy", [False, True]) +async def test_permanently_lost_batch_retires_unchanged_row(legacy: bool) -> None: + row: Final = _FakeManagedObjectRow() + prisma: Final = TestMultiPodBatchCostClaim._prisma(row, []) + poller: Final = TestMultiPodBatchCostClaim._instance(prisma, TestMultiPodBatchCostClaim._router()) + poller._has_batch_processed_column = not legacy + + await poller._retire_job(row, "provider batch disappeared") + + assert row.batch_processed is (not legacy) + assert row.status == ("stale_expired" if legacy else "in_progress") + + +@pytest.mark.asyncio +async def test_failed_retirement_keeps_batch_available() -> None: + row: Final = _FakeManagedObjectRow() + prisma: Final = TestMultiPodBatchCostClaim._prisma(row, []) + prisma.db.litellm_managedobjecttable.update_many = AsyncMock(side_effect=RuntimeError("database unavailable")) + poller: Final = TestMultiPodBatchCostClaim._instance(prisma, TestMultiPodBatchCostClaim._router()) + + await poller._retire_job(row, "provider batch disappeared") + + assert row.batch_processed is False + assert row.status == "in_progress" + + +@pytest.mark.parametrize("resource_id", ("batch-123", "file-123", "gs://bucket/job/predictions.jsonl")) +@pytest.mark.parametrize("other_id", ("{id}4", "prefix-{id}", "{id}/child", "{id}.backup", "{id}?generation=2")) +def test_another_resource_in_a_404_is_not_permanent_loss(resource_id: str, other_id: str) -> None: + from litellm.exceptions import NotFoundError + from litellm_enterprise.proxy.common_utils.check_batch_cost import CheckBatchCost + + error: Final = NotFoundError( + message=f"No object found with id '{other_id.format(id=resource_id)}'.", model="test", llm_provider="openai" + ) + assert CheckBatchCost._is_batch_gone_at_provider(error, resource_id) is False + assert CheckBatchCost._is_output_file_gone_at_provider(error, resource_id) is False + + +@pytest.mark.parametrize("resource_id", ("batch-123", "file-123", "gs://bucket/job/predictions.jsonl")) +@pytest.mark.parametrize("message", ("No object found with id '{id}'.", 'File "{id}" does not exist', "{id} not found")) +def test_a_404_naming_the_exact_resource_is_permanent_loss(resource_id: str, message: str) -> None: + from litellm.exceptions import NotFoundError + from litellm_enterprise.proxy.common_utils.check_batch_cost import CheckBatchCost + + error: Final = NotFoundError(message=message.format(id=resource_id), model="test", llm_provider="openai") + assert CheckBatchCost._is_batch_gone_at_provider(error, resource_id) is True + assert CheckBatchCost._is_output_file_gone_at_provider(error, resource_id) is True + + +@pytest.mark.parametrize("output_file_id", (None, "")) +def test_a_404_without_an_output_identity_remains_retryable(output_file_id: str | None) -> None: + from litellm.exceptions import NotFoundError + from litellm_enterprise.proxy.common_utils.check_batch_cost import CheckBatchCost + + error: Final = NotFoundError(message="Output file not found", model="test", llm_provider="openai") + assert CheckBatchCost._is_output_file_gone_at_provider(error, output_file_id) is False + + @pytest.mark.asyncio @pytest.mark.parametrize( "kind", ["sync", "async", "custom", "overlapping", "general", "mixed", "sync_only", "executor_shutdown"] diff --git a/tests/unit/proxy/common_utils/test_check_responses_cost.py b/tests/unit/proxy/common_utils/test_check_responses_cost.py index f606658fa09..b8d5ddef3d2 100644 --- a/tests/unit/proxy/common_utils/test_check_responses_cost.py +++ b/tests/unit/proxy/common_utils/test_check_responses_cost.py @@ -4,10 +4,12 @@ Unit tests for CheckResponsesCost class import asyncio import dataclasses +import hashlib +import json from collections.abc import Mapping from dataclasses import dataclass from datetime import datetime -from types import MappingProxyType +from types import MappingProxyType, SimpleNamespace from typing import Final from unittest.mock import AsyncMock, MagicMock, Mock, patch @@ -127,10 +129,21 @@ class _InMemoryManagedObjectTable: return len(matched) +def _prisma_with_no_creator_rows() -> MagicMock: + prisma_client: Final = MagicMock() + prisma_client.db.litellm_verificationtoken.find_unique = AsyncMock(return_value=None) + prisma_client.db.litellm_teamtable.find_unique = AsyncMock(return_value=None) + prisma_client.db.litellm_usertable.find_unique = AsyncMock(return_value=None) + prisma_client.db.litellm_deprecatedverificationtoken.find_unique = AsyncMock(return_value=None) + prisma_client.db.litellm_deletedverificationtoken.find_first = AsyncMock(return_value=None) + prisma_client.db.litellm_deletedteamtable.find_first = AsyncMock(return_value=None) + return prisma_client + + def _poller_over(table: _InMemoryManagedObjectTable, billed_logger: _RecordingBilledLogger): from litellm_enterprise.proxy.common_utils.check_responses_cost import CheckResponsesCost - prisma_client: Final = MagicMock() + prisma_client: Final = _prisma_with_no_creator_rows() prisma_client.db.litellm_managedobjecttable = table poller: Final = CheckResponsesCost( proxy_logging_obj=MagicMock(), @@ -174,8 +187,7 @@ class TestCheckResponsesCost: @pytest.fixture def mock_prisma_client(self): """Create a mock Prisma client""" - client = MagicMock() - client.db = MagicMock() + client = _prisma_with_no_creator_rows() client.db.litellm_managedobjecttable = MagicMock() return client @@ -1217,8 +1229,6 @@ class TestCheckResponsesCost: """The poll's billing event is the one billed event of a background job, so its spend row must name the key, team, org, user, and tags of the create it settles, read off the managed object row, never the poller itself.""" - from types import SimpleNamespace - mock_job = MagicMock() mock_job.unified_object_id = "resp_test_attributed" mock_job.id = "job-attributed" @@ -1494,6 +1504,122 @@ async def test_the_billing_event_carries_the_creators_end_user(): assert billed.metadata["user_api_key_end_user_id"] == "customer-42" +@pytest.mark.asyncio +async def test_the_billing_event_carries_the_creating_keys_project_and_every_creator_model_budget(): + key_budget: Final = {"gpt-5": {"max_budget": 1.0, "budget_duration": "1d"}} + team_budget: Final = {"gpt-5": {"max_budget": 2.0, "budget_duration": "7d"}} + user_budget: Final = {"gpt-5": {"max_budget": 3.0, "budget_duration": "30d"}} + table: Final = _InMemoryManagedObjectTable( + rows=( + _StoredResponse( + id="job-budgets", + unified_object_id="resp_budgets", + status="queued", + created_by="alice", + api_key="hash-alice", + team_id="team-alpha", + ), + ) + ) + billed_logger: Final = _RecordingBilledLogger() + poller: Final = _poller_over(table, billed_logger) + poller.prisma_client.db.litellm_verificationtoken.find_unique = AsyncMock( + return_value=SimpleNamespace( + key_alias=None, + organization_id=None, + spend=0.0, + max_budget=None, + project_id="project-1", + litellm_project_table=SimpleNamespace(project_alias="project-one"), + model_max_budget=key_budget, + ) + ) + poller.prisma_client.db.litellm_teamtable.find_unique = AsyncMock( + return_value=SimpleNamespace( + team_alias=None, organization_id=None, spend=0.0, max_budget=None, model_max_budget=team_budget + ) + ) + poller.prisma_client.db.litellm_usertable.find_unique = AsyncMock( + return_value=SimpleNamespace( + user_email=None, user_alias=None, spend=0.0, max_budget=None, model_max_budget=user_budget + ) + ) + + await poller.bill_if_finished(response_id="resp_budgets", response=_terminal_response()) + + (billed,) = billed_logger.billed + assert { + field: billed.metadata.get(field) + for field in ( + "user_api_key_project_id", + "user_api_key_project_alias", + "user_api_key_model_max_budget", + "user_api_key_team_model_max_budget", + "user_api_key_user_model_max_budget", + ) + } == { + "user_api_key_project_id": "project-1", + "user_api_key_project_alias": "project-one", + "user_api_key_model_max_budget": key_budget, + "user_api_key_team_model_max_budget": team_budget, + "user_api_key_user_model_max_budget": user_budget, + } + + +_TIER_MODEL_BUDGET: Final = {"gpt-5": {"max_budget": 4.0, "budget_duration": "1d"}} +_KEY_MODEL_BUDGET: Final = {"gpt-5": {"max_budget": 1.0, "budget_duration": "1d"}} + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("key_max_budget", "key_model_max_budget", "billed_max_budget", "billed_model_max_budget"), + [ + (None, {}, 5.0, _TIER_MODEL_BUDGET), + (None, None, 5.0, _TIER_MODEL_BUDGET), + (2.0, _KEY_MODEL_BUDGET, 2.0, _KEY_MODEL_BUDGET), + ], + ids=["key_with_an_empty_budget_map", "key_with_no_budget_map", "key_with_its_own_budgets"], +) +async def test_the_billing_event_takes_the_keys_budget_tier_only_where_the_key_sets_no_budget_of_its_own( + key_max_budget: float | None, + key_model_max_budget: dict[str, object] | None, + billed_max_budget: float, + billed_model_max_budget: dict[str, object], +): + table: Final = _InMemoryManagedObjectTable( + rows=( + _StoredResponse( + id="job-tier", + unified_object_id="resp_tier", + status="queued", + created_by="key:hash-tier", + api_key="hash-tier", + ), + ) + ) + billed_logger: Final = _RecordingBilledLogger() + poller: Final = _poller_over(table, billed_logger) + poller.prisma_client.db.litellm_verificationtoken.find_unique = AsyncMock( + return_value=SimpleNamespace( + key_alias=None, + organization_id=None, + spend=0.0, + max_budget=key_max_budget, + project_id=None, + model_max_budget=key_model_max_budget, + litellm_budget_table=SimpleNamespace(max_budget=5.0, model_max_budget=_TIER_MODEL_BUDGET), + ) + ) + + await poller.bill_if_finished(response_id="resp_tier", response=_terminal_response()) + + (billed,) = billed_logger.billed + assert (billed.metadata.get("user_api_key_max_budget"), billed.metadata.get("user_api_key_model_max_budget")) == ( + billed_max_budget, + billed_model_max_budget, + ) + + @pytest.mark.asyncio @pytest.mark.parametrize( ("created_by", "billed_user_id"), @@ -1588,49 +1714,171 @@ class _PricedBilling: table: _InMemoryManagedObjectTable response_id: str cost: float | None + logging_obj: object + + +@dataclass(frozen=True) +class _PricedPoller: + poller: object + prisma_client: MagicMock + table: _InMemoryManagedObjectTable + response_id: str + + async def bill(self, read: ResponsesAPIResponse) -> object: + from litellm_enterprise.proxy.common_utils.check_responses_cost import CheckResponsesCost + + from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER + + assert isinstance(self.poller, CheckResponsesCost) + charge: Final = await self.poller.bill_if_finished(response_id=self.response_id, response=read) + await asyncio.wait_for(GLOBAL_LOGGING_WORKER.flush(), timeout=10) + return charge _PRICED_LITELLM_PARAMS: Final[Mapping[str, object]] = MappingProxyType( {"model": "openai/gpt-5.6", "api_key": "sk-unused", "input_cost_per_token": 0.001, "output_cost_per_token": 0.002} ) +_CREATING_KEY_HASH: Final = hashlib.sha256(b"sk-alice").hexdigest() -async def _bill_through_a_priced_deployment( - read: ResponsesAPIResponse, +def _team_alpha_when_its_rows_exist( + team_row: object, deleted_team_row: object, default_team_settings: tuple[Mapping[str, object], ...] +) -> str | None: + return "team-alpha" if team_row is not None or deleted_team_row is not None or default_team_settings else None + + +def _priced_poller( litellm_params: Mapping[str, object] = _PRICED_LITELLM_PARAMS, model_info: Mapping[str, object] = MappingProxyType({}), -) -> _PricedBilling: + key_row: object = None, + team_row: object = None, + key_lookup_error: Exception | None = None, + default_team_settings: tuple[Mapping[str, object], ...] = (), + api_key: str = _CREATING_KEY_HASH, + rotated_to: Mapping[str, object] = MappingProxyType({}), + deleted_key_row: object = None, + deleted_team_row: object = None, + model_name: str = "priced-gpt", + requested_model: str = "priced-gpt", + model_group_alias: Mapping[str, str] = MappingProxyType({}), + team_id: str | None = None, +) -> _PricedPoller: + from types import SimpleNamespace + import litellm from litellm_enterprise.proxy.common_utils.check_responses_cost import CheckResponsesCost - from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER from litellm.responses.utils import ResponsesAPIRequestUtils response_id: Final = ResponsesAPIRequestUtils._build_responses_api_response_id( custom_llm_provider="openai", model_id="deployment-custom", response_id="resp_upstream" ) table: Final = _InMemoryManagedObjectTable( - rows=(_StoredResponse(id="job-priced", unified_object_id=response_id, status="queued", api_key="hash-alice"),) + rows=( + _StoredResponse( + id="job-priced", + unified_object_id=response_id, + status="queued", + api_key=api_key, + file_object={"model": requested_model}, + team_id=team_id or _team_alpha_when_its_rows_exist(team_row, deleted_team_row, default_team_settings), + ), + ) ) - prisma_client: Final = MagicMock() + key_rows: Final = {api_key: key_row, **{token: row for token, row in rotated_to.items()}} + prisma_client: Final = _prisma_with_no_creator_rows() prisma_client.db.litellm_managedobjecttable = table prisma_client.db.litellm_usertable.find_unique = AsyncMock(return_value=None) - prisma_client.db.litellm_verificationtoken.find_unique = AsyncMock(return_value=None) - prisma_client.db.litellm_teamtable.find_unique = AsyncMock(return_value=None) + prisma_client.db.litellm_verificationtoken.find_unique = AsyncMock( + side_effect=key_lookup_error or (lambda where, **_: key_rows.get(where["token"])) + ) + rotation_chain: Final = (api_key, *rotated_to) + rotated_from: Final = dict(zip(rotation_chain, rotation_chain[1:])) + prisma_client.db.litellm_deprecatedverificationtoken.find_unique = AsyncMock( + side_effect=lambda where: ( + SimpleNamespace(token=where["token"], active_token_id=rotated_from[where["token"]]) + if where["token"] in rotated_from + else None + ) + ) + prisma_client.db.litellm_deletedverificationtoken.find_first = AsyncMock(return_value=deleted_key_row) + prisma_client.db.litellm_teamtable.find_unique = AsyncMock(return_value=team_row) + prisma_client.db.litellm_deletedteamtable.find_first = AsyncMock(return_value=deleted_team_row) router: Final = litellm.Router( model_list=[ { - "model_name": "priced-gpt", + "model_name": model_name, "litellm_params": dict(litellm_params), "model_info": {"id": "deployment-custom", **model_info}, } - ] + ], + model_group_alias=dict(model_group_alias), ) - charge: Final = await CheckResponsesCost( - proxy_logging_obj=MagicMock(), prisma_client=prisma_client, llm_router=router - ).bill_if_finished(response_id=response_id, response=read) - await asyncio.wait_for(GLOBAL_LOGGING_WORKER.flush(), timeout=10) - return _PricedBilling(table=table, response_id=response_id, cost=charge.cost if charge is not None else None) + return _PricedPoller( + poller=CheckResponsesCost( + proxy_logging_obj=MagicMock(), + prisma_client=prisma_client, + llm_router=router, + proxy_config=_proxy_config_with(default_team_settings), + ), + prisma_client=prisma_client, + table=table, + response_id=response_id, + ) + + +async def _bill_through_a_priced_deployment( + read: ResponsesAPIResponse, + litellm_params: Mapping[str, object] = _PRICED_LITELLM_PARAMS, + model_info: Mapping[str, object] = MappingProxyType({}), + key_row: object = None, + team_row: object = None, + key_lookup_error: Exception | None = None, + default_team_settings: tuple[Mapping[str, object], ...] = (), + api_key: str = _CREATING_KEY_HASH, + rotated_to: Mapping[str, object] = MappingProxyType({}), + deleted_key_row: object = None, + deleted_team_row: object = None, + model_name: str = "priced-gpt", + requested_model: str = "priced-gpt", + model_group_alias: Mapping[str, str] = MappingProxyType({}), + team_id: str | None = None, +) -> _PricedBilling: + priced: Final = _priced_poller( + litellm_params=litellm_params, + model_info=model_info, + key_row=key_row, + team_row=team_row, + key_lookup_error=key_lookup_error, + default_team_settings=default_team_settings, + api_key=api_key, + rotated_to=rotated_to, + deleted_key_row=deleted_key_row, + deleted_team_row=deleted_team_row, + model_name=model_name, + requested_model=requested_model, + model_group_alias=model_group_alias, + team_id=team_id, + ) + charge: Final = await priced.bill(read) + return _PricedBilling( + table=priced.table, + response_id=priced.response_id, + cost=getattr(charge, "cost", None), + logging_obj=getattr(charge, "logging_obj", None), + ) + + +def _proxy_config_with(default_team_settings: tuple[Mapping[str, object], ...]): + from litellm.proxy.proxy_server import ProxyConfig + + proxy_config: Final = ProxyConfig() + proxy_config.config = ( + {"litellm_settings": {"default_team_settings": [dict(settings) for settings in default_team_settings]}} + if default_team_settings + else {} + ) + return proxy_config @pytest.mark.asyncio @@ -1652,11 +1900,80 @@ async def test_the_billing_event_prices_the_fetched_usage_at_the_deployment_rate assert billing.cost == pytest.approx(_PRICED_COST) assert payload["model_id"] == "deployment-custom" assert payload["model_group"] == "priced-gpt" - assert payload["metadata"]["user_api_key_hash"] == "hash-alice" + assert payload["metadata"]["user_api_key_hash"] == _CREATING_KEY_HASH assert read.hidden_params == {"response_cost": 0.0} assert billing.table.statuses == {"job-priced": "completed"} +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("model_name", "deployment_model", "requested_model", "model_group_alias", "model_info", "model_group"), + [ + ("openai/*", "openai/*", "openai/gpt-5.6", {}, {}, "openai/gpt-5.6"), + ("priced-gpt", "openai/gpt-5.6", "priced-alias", {"priced-alias": "priced-gpt"}, {}, "priced-alias"), + ("priced-gpt", "openai/gpt-5.6", "gpt-5.6-2026-01-01", {}, {}, "priced-gpt"), + ( + "model_name_team-1_abc", + "openai/gpt-5.6", + "team-gpt", + {}, + {"team_id": "team-1", "team_public_model_name": "team-gpt"}, + "team-gpt", + ), + ( + "model_name_team-1_wild", + "openai/*", + "openai/gpt-5.6", + {}, + {"team_id": "team-1", "team_public_model_name": "openai/*"}, + "openai/gpt-5.6", + ), + ( + "model_name_team-2_abc", + "openai/gpt-5.6", + "team-gpt", + {}, + {"team_id": "team-2", "team_public_model_name": "team-gpt"}, + "model_name_team-2_abc", + ), + ], + ids=[ + "wildcard_route", + "model_group_alias", + "fallback_kept_the_provider_model_name", + "team_model", + "team_wildcard", + "another_teams_model", + ], +) +async def test_the_billing_event_names_the_requested_model_as_its_model_group_only_while_it_routes_to_the_deployment( + monkeypatch: pytest.MonkeyPatch, + model_name: str, + deployment_model: str, + requested_model: str, + model_group_alias: Mapping[str, str], + model_info: Mapping[str, object], + model_group: str, +): + import litellm + + capture: Final = _spend_capture_logger() + monkeypatch.setattr(litellm, "_async_success_callback", [capture]) + + await _bill_through_a_priced_deployment( + _terminal_response(), + litellm_params={**_PRICED_LITELLM_PARAMS, "model": deployment_model}, + model_info=model_info, + model_name=model_name, + requested_model=requested_model, + model_group_alias=model_group_alias, + team_id="team-1", + ) + + (payload,) = capture.payloads + assert payload["model_group"] == model_group + + @pytest.mark.asyncio @pytest.mark.parametrize("base_model_in", ["litellm_params", "model_info"]) async def test_the_billing_event_prices_the_usage_at_the_deployments_base_model( @@ -1748,3 +2065,428 @@ async def test_the_billing_event_keys_its_spend_row_apart_from_the_read_it_bills assert billed_request_id != billing.response_id assert billed_request_id.startswith(billing.response_id) + +_CREATOR_LANGFUSE_VARS: Final = MappingProxyType( + { + "langfuse_public_key": "pk-lf-creator", + "langfuse_secret_key": "sk-lf-creator", + "langfuse_host": "http://127.0.0.1:9", + } +) + + +def _key_row(metadata: Mapping[str, object]) -> object: + from types import SimpleNamespace + + return SimpleNamespace(key_alias=None, organization_id=None, spend=0.0, max_budget=None, metadata=dict(metadata)) + + +def _team_row(metadata: Mapping[str, object]) -> object: + from types import SimpleNamespace + + return SimpleNamespace(team_alias=None, organization_id=None, spend=0.0, max_budget=None, metadata=dict(metadata)) + + +def _langfuse_callback_settings(callback_vars: Mapping[str, object]) -> Mapping[str, object]: + return {"callback_settings": {"success_callback": ["langfuse"], "callback_vars": dict(callback_vars)}} + + +@dataclass(frozen=True) +class _CreatorLogging: + key_row: object + team_row: object + default_team_settings: tuple[Mapping[str, object], ...] + + +def _creator_logging(logging_on: str) -> _CreatorLogging: + logging: Final = { + "logging": [ + {"callback_name": "langfuse", "callback_type": "success", "callback_vars": dict(_CREATOR_LANGFUSE_VARS)} + ] + } + team_metadata: Final = { + "team logging": logging, + "team callback_settings": _langfuse_callback_settings(_CREATOR_LANGFUSE_VARS), + } + return _CreatorLogging( + key_row=_key_row(logging if logging_on == "key logging" else {}), + team_row=_team_row(team_metadata.get(logging_on, {})), + default_team_settings=( + ({"team_id": "team-alpha", "success_callback": ["langfuse"], **_CREATOR_LANGFUSE_VARS},) + if logging_on == "config team settings" + else () + ), + ) + + +def _recording_langfuse(): + from litellm.integrations.custom_logger import CustomLogger + from litellm.integrations.langfuse.langfuse_prompt_management import LangfusePromptManagement + + class _RecordingLangfuse(LangfusePromptManagement): + def __init__(self) -> None: + CustomLogger.__init__(self) + self.events: tuple[tuple[object, object], ...] = () + + async def async_log_success_event( + self, kwargs: dict[str, object], response_obj: object, start_time: datetime, end_time: datetime + ) -> None: + params: Final = kwargs["standard_callback_dynamic_params"] + assert isinstance(params, Mapping) + self.events = (*self.events, (kwargs.get("response_cost"), params.get("langfuse_public_key"))) + + return _RecordingLangfuse() + + +async def _log_a_request_from(creator: _CreatorLogging) -> None: + import litellm + from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER + from litellm.proxy._types import UserAPIKeyAuth + from litellm.proxy.litellm_pre_call_utils import key_and_team_logging_fields + + await litellm.acompletion( + model="openai/gpt-5.6", + messages=[{"role": "user", "content": "hi"}], + mock_response="hello", + **key_and_team_logging_fields( + user_api_key_dict=UserAPIKeyAuth( + metadata=getattr(creator.key_row, "metadata"), + team_id="team-alpha", + team_metadata=getattr(creator.team_row, "metadata"), + ), + proxy_config=_proxy_config_with(creator.default_team_settings), + ), + ) + await asyncio.sleep(0) + await asyncio.wait_for(GLOBAL_LOGGING_WORKER.flush(), timeout=10) + + +@pytest.mark.asyncio +@pytest.mark.parametrize("proxy_logs_to_langfuse", [False, True]) +@pytest.mark.parametrize( + "logging_on", ["key logging", "team logging", "team callback_settings", "config team settings"] +) +async def test_the_billing_event_reaches_the_langfuse_projects_the_creators_own_requests_log_to( + monkeypatch: pytest.MonkeyPatch, logging_on: str, proxy_logs_to_langfuse: bool +): + """A key or team that logs to its own Langfuse project must see the billed charge in the same projects + its own requests log to, wherever that logging is configured and whether or not the proxy logs to + Langfuse too, or the charge only shows in the proxy's spend logs.""" + import litellm + from litellm.litellm_core_utils import litellm_logging + + langfuse: Final = _recording_langfuse() + monkeypatch.setattr(litellm_logging, "_in_memory_loggers", [langfuse]) + monkeypatch.setattr(litellm, "success_callback", []) + monkeypatch.setattr(litellm, "_async_success_callback", [langfuse] if proxy_logs_to_langfuse else []) + creator: Final = _creator_logging(logging_on) + + await _log_a_request_from(creator) + request_projects: Final = tuple(public_key for _, public_key in langfuse.events) + await _bill_through_a_priced_deployment( + _terminal_response(), + key_row=creator.key_row, + team_row=creator.team_row, + default_team_settings=creator.default_team_settings, + ) + billed_events: Final = langfuse.events[len(request_projects) :] + + assert _CREATOR_LANGFUSE_VARS["langfuse_public_key"] in request_projects + assert tuple(public_key for _, public_key in billed_events) == request_projects + assert all(cost == pytest.approx(_PRICED_COST) for cost, _ in billed_events) + + +def _rotations_for(retired: str, key_logging: object) -> Mapping[str, object]: + rotated_once: Final = hashlib.sha256(b"sk-alice-rotated").hexdigest() + if retired == "rotated key": + return {rotated_once: key_logging} + if retired == "key rotated twice": + return {rotated_once: None, hashlib.sha256(b"sk-alice-rotated-again").hexdigest(): key_logging} + return {} + + +@pytest.mark.asyncio +@pytest.mark.parametrize("retired", ["rotated key", "key rotated twice", "deleted key", "deleted team"]) +async def test_a_creator_rotated_or_deleted_before_the_bill_still_gets_the_charge_in_its_own_langfuse_project( + monkeypatch: pytest.MonkeyPatch, retired: str +): + """A key rotated or deleted, or a team deleted, while its background response ran logged that response's + create to its own project, so the charge follows the settings kept on the key it was rotated to or on + its deleted row instead of leaving that project for the proxy's callbacks alone.""" + import litellm + from litellm.litellm_core_utils import litellm_logging + + langfuse: Final = _recording_langfuse() + monkeypatch.setattr(litellm_logging, "_in_memory_loggers", [langfuse]) + monkeypatch.setattr(litellm, "success_callback", []) + monkeypatch.setattr(litellm, "_async_success_callback", []) + key_logging: Final = _creator_logging("key logging").key_row + + await _bill_through_a_priced_deployment( + _terminal_response(), + rotated_to=_rotations_for(retired, key_logging), + deleted_key_row=key_logging if retired == "deleted key" else SimpleNamespace(metadata={}), + deleted_team_row=_creator_logging("team callback_settings").team_row if retired == "deleted team" else None, + ) + + assert langfuse.events == ((pytest.approx(_PRICED_COST), _CREATOR_LANGFUSE_VARS["langfuse_public_key"]),) + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "failing_lookup, live_key_logging, team_logging", + [ + ("litellm_verificationtoken.find_unique", "key logging", "none"), + ("litellm_teamtable.find_unique", "none", "team callback_settings"), + ("litellm_deprecatedverificationtoken.find_unique", "none", "none"), + ("litellm_deletedverificationtoken.find_first", "none", "none"), + ], + ids=["live key", "live team", "rotated key", "deleted key"], +) +async def test_a_creator_lookup_that_keeps_failing_still_bills_the_response_once_without_the_creators_settings( + monkeypatch: pytest.MonkeyPatch, failing_lookup: str, live_key_logging: str, team_logging: str +): + """A creator lookup that fails on every read must not leave the response unbilled. It bills once under the + key and team the managed row stores, through the proxy's callbacks only, with the text left out since the + creator's redaction setting could not be read.""" + import litellm + from litellm.litellm_core_utils import litellm_logging + + langfuse: Final = _recording_langfuse() + capture: Final = _spend_capture_logger() + monkeypatch.setattr(litellm_logging, "_in_memory_loggers", [langfuse]) + monkeypatch.setattr(litellm, "success_callback", []) + monkeypatch.setattr(litellm, "_async_success_callback", [capture]) + monkeypatch.setattr(litellm, "turn_off_message_logging", False) + priced: Final = _priced_poller( + key_row=_creator_logging(live_key_logging).key_row if live_key_logging != "none" else None, + team_row=_creator_logging(team_logging).team_row if team_logging != "none" else None, + ) + table_name, method = failing_lookup.split(".") + setattr( + getattr(priced.prisma_client.db, table_name), + method, + AsyncMock(side_effect=RuntimeError("database unavailable")), + ) + + charge: Final = await priced.bill(_read_with_text("the stored answer")) + await priced.bill(_read_with_text("the stored answer")) + + assert getattr(charge, "cost", None) == pytest.approx(_PRICED_COST) + assert priced.table.statuses == {"job-priced": "completed"} + assert langfuse.events == () + (payload,) = capture.payloads + assert payload["response_cost"] == pytest.approx(_PRICED_COST) + assert "the stored answer" not in json.dumps(payload, default=str) + metadata: Final = payload["metadata"] + assert isinstance(metadata, Mapping) + assert metadata["user_api_key_hash"] == _CREATING_KEY_HASH + assert metadata["user_api_key_team_id"] == ("team-alpha" if team_logging != "none" else None) + + +_TEAM_MODEL_BUDGET: Final = {"gpt-5": {"max_budget": 2.0, "budget_duration": "7d"}} +_LOADED_KEY_ATTRIBUTION: Final = {"user_api_key_alias": "prod-key", "user_api_key_max_budget": 5.0} +_LOADED_TEAM_ATTRIBUTION: Final = { + "user_api_key_team_alias": "Team Alpha", + "user_api_key_team_max_budget": 50.0, + "user_api_key_team_model_max_budget": _TEAM_MODEL_BUDGET, +} + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "failing_lookup, key_is_live, loaded_attribution", + [ + ("litellm_verificationtoken.find_unique", True, _LOADED_TEAM_ATTRIBUTION), + ("litellm_teamtable.find_unique", True, _LOADED_KEY_ATTRIBUTION), + ("litellm_deprecatedverificationtoken.find_unique", False, _LOADED_TEAM_ATTRIBUTION), + ("litellm_deletedverificationtoken.find_first", False, _LOADED_TEAM_ATTRIBUTION), + ], + ids=["live key", "live team", "rotated key", "deleted key"], +) +async def test_a_creator_lookup_that_fails_keeps_the_aliases_and_budgets_of_the_rows_that_did_load( + failing_lookup: str, key_is_live: bool, loaded_attribution: Mapping[str, object] +): + """One failed creator lookup must not strip what the other rows give the charge: the team's per-model budget + only counts a billed charge whose event carries it, and the aliases name who spent it.""" + table: Final = _InMemoryManagedObjectTable( + rows=( + _StoredResponse( + id="job-attributed", + unified_object_id="resp_attributed", + status="queued", + api_key=_CREATING_KEY_HASH, + team_id="team-alpha", + ), + ) + ) + billed_logger: Final = _RecordingBilledLogger() + poller: Final = _poller_over(table, billed_logger) + poller.prisma_client.db.litellm_verificationtoken.find_unique = AsyncMock( + return_value=( + SimpleNamespace(key_alias="prod-key", organization_id=None, spend=4.0, max_budget=5.0, metadata={}) + if key_is_live + else None + ) + ) + poller.prisma_client.db.litellm_teamtable.find_unique = AsyncMock( + return_value=SimpleNamespace( + team_alias="Team Alpha", + organization_id=None, + spend=40.0, + max_budget=50.0, + model_max_budget=_TEAM_MODEL_BUDGET, + metadata={}, + ) + ) + table_name, method = failing_lookup.split(".") + setattr( + getattr(poller.prisma_client.db, table_name), + method, + AsyncMock(side_effect=RuntimeError("database unavailable")), + ) + + await poller.bill_if_finished(response_id="resp_attributed", response=_terminal_response()) + + assert table.statuses == {"job-attributed": "completed"} + (billed,) = billed_logger.billed + assert {field: billed.metadata.get(field) for field in loaded_attribution} == loaded_attribution + + +@pytest.mark.asyncio +async def test_a_team_logging_setting_the_logger_rejects_still_bills_the_response_once(monkeypatch: pytest.MonkeyPatch): + """A team whose stored callback settings the logger rejects, such as an os.environ reference it no + longer resolves, must not stop the bill: the charge reaches the proxy's callbacks and the response is + not put back for every later poll to fail on again.""" + import litellm + + capture: Final = _spend_capture_logger() + monkeypatch.setattr(litellm, "success_callback", []) + monkeypatch.setattr(litellm, "_async_success_callback", [capture]) + + billing: Final = await _bill_through_a_priced_deployment( + _terminal_response(), + key_row=_key_row({}), + team_row=_team_row(_langfuse_callback_settings({"langfuse_public_key": "os.environ/QA_UNSET_LANGFUSE_KEY"})), + ) + + (payload,) = capture.payloads + assert payload["response_cost"] == pytest.approx(_PRICED_COST) + assert billing.cost == pytest.approx(_PRICED_COST) + assert billing.table.statuses == {"job-priced": "completed"} + + +def _read_with_text(text: str) -> ResponsesAPIResponse: + return _terminal_response().model_copy( + update={ + "output": [ + { + "type": "message", + "id": "msg_stored", + "status": "completed", + "role": "assistant", + "content": [{"type": "output_text", "text": text, "annotations": []}], + } + ] + } + ) + + +def _key_logging_to_langfuse(callback_vars: Mapping[str, object]) -> object: + return _key_row( + {"logging": [{"callback_name": "langfuse", "callback_type": "success", "callback_vars": dict(callback_vars)}]} + ) + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("key_row", "deleted_key_row", "text_logged"), + [ + (_key_logging_to_langfuse(_CREATOR_LANGFUSE_VARS), None, True), + (_key_logging_to_langfuse({**_CREATOR_LANGFUSE_VARS, "turn_off_message_logging": "true"}), None, False), + (None, _key_logging_to_langfuse({**_CREATOR_LANGFUSE_VARS, "turn_off_message_logging": "true"}), False), + (None, None, True), + ], + ids=[ + "creator keeps message logging", + "creator turns message logging off", + "deleted creator turned message logging off", + "creator has no key row anywhere", + ], +) +async def test_the_billing_event_logs_the_response_text_only_as_the_creators_logging_settings_allow( + monkeypatch: pytest.MonkeyPatch, key_row: object, deleted_key_row: object, text_logged: bool +): + """The billed event follows the creating key's or team's message logging setting, a deleted key's included, + which falls back to the proxy's the way the batch poll decides it, so a key with no stored settings + anywhere logs the text exactly as the proxy is set.""" + import litellm + from litellm.litellm_core_utils import litellm_logging + + capture: Final = _spend_capture_logger() + monkeypatch.setattr(litellm_logging, "_in_memory_loggers", [_recording_langfuse()]) + monkeypatch.setattr(litellm, "success_callback", []) + monkeypatch.setattr(litellm, "_async_success_callback", [capture]) + monkeypatch.setattr(litellm, "turn_off_message_logging", False) + + await _bill_through_a_priced_deployment( + _read_with_text("the stored answer"), key_row=key_row, deleted_key_row=deleted_key_row + ) + + (payload,) = capture.payloads + assert payload["response_cost"] == pytest.approx(_PRICED_COST) + assert ("the stored answer" in json.dumps(payload, default=str)) is text_logged + + +@pytest.mark.asyncio +@pytest.mark.parametrize("caller_token", ["oauth2-raw-access-token", "sk-custom-auth-1234"]) +async def test_a_response_created_without_a_virtual_key_bills_into_its_teams_langfuse_project( + monkeypatch: pytest.MonkeyPatch, caller_token: str +): + """Under OAuth2 the row keeps the caller's raw token, and under custom auth the hash of an sk- token that + has no key row, so the charge follows the team's logging settings like that caller's own requests.""" + from litellm.proxy._types import UserAPIKeyAuth + + import litellm + from litellm.litellm_core_utils import litellm_logging + + langfuse: Final = _recording_langfuse() + monkeypatch.setattr(litellm_logging, "_in_memory_loggers", [langfuse]) + monkeypatch.setattr(litellm, "success_callback", []) + monkeypatch.setattr(litellm, "_async_success_callback", []) + + await _bill_through_a_priced_deployment( + _terminal_response(), + api_key=UserAPIKeyAuth(api_key=caller_token).api_key or caller_token, + team_row=_creator_logging("team callback_settings").team_row, + ) + + assert langfuse.events == ((pytest.approx(_PRICED_COST), _CREATOR_LANGFUSE_VARS["langfuse_public_key"]),) + + +@pytest.mark.asyncio +async def test_a_key_that_disabled_a_callback_has_its_charge_logged_wherever_its_own_requests_are( + monkeypatch: pytest.MonkeyPatch, +): + """A key's stored list of disabled callbacks must treat the billed charge like that key's own requests, or + a project that shows the key's requests at $0 never shows the charge they add up to.""" + import litellm + from litellm.litellm_core_utils import litellm_logging + from litellm.proxy import proxy_server + + monkeypatch.setattr(proxy_server, "premium_user", True) + langfuse: Final = _recording_langfuse() + monkeypatch.setattr(litellm_logging, "_in_memory_loggers", [langfuse]) + monkeypatch.setattr(litellm, "success_callback", []) + monkeypatch.setattr(litellm, "_async_success_callback", [langfuse]) + creator: Final = _CreatorLogging( + key_row=_key_row({"litellm_disabled_callbacks": ["langfuse"]}), team_row=_team_row({}), default_team_settings=() + ) + + await _log_a_request_from(creator) + request_events: Final = langfuse.events + await _bill_through_a_priced_deployment(_terminal_response(), key_row=creator.key_row) + billed_events: Final = langfuse.events[len(request_events) :] + + assert len(billed_events) == len(request_events) + assert all(cost == pytest.approx(_PRICED_COST) for cost, _ in billed_events) diff --git a/tests/unit/proxy/common_utils/test_http_parsing_utils.py b/tests/unit/proxy/common_utils/test_http_parsing_utils.py index 88ae5e0d84e..cd5820fa2fd 100644 --- a/tests/unit/proxy/common_utils/test_http_parsing_utils.py +++ b/tests/unit/proxy/common_utils/test_http_parsing_utils.py @@ -1556,3 +1556,39 @@ def test_is_otlp_trace_request_matches_only_http_posts_to_the_otlp_routes( ) assert http_parsing_utils.is_otlp_trace_request(connection) is expected + + +@pytest.mark.asyncio +async def test_form_data_metadata_with_lone_surrogate_escape_is_rejected_like_a_json_body(): + """``json.loads`` accepts ``"\\ud800"`` and yields a lone surrogate that no + provider or database can utf-8 encode. The JSON body path already answers + 400, so the multipart ``metadata`` field must too, instead of letting the + value through to the spend log writers.""" + mock_request = MagicMock() + mock_request.form = AsyncMock( + return_value=FormData({"model": "whisper-1", "metadata": '{"tags": ["poison-\\ud800-tag"]}'}) + ) + mock_request.headers = {"content-type": "multipart/form-data"} + mock_request.scope = {} + mock_request.state._cached_headers = None + + with pytest.raises(ProxyException) as exc_info: + await read_request_body(mock_request) + + assert exc_info.value.code == "400" + assert "metadata" in exc_info.value.message + + +@pytest.mark.asyncio +async def test_form_data_metadata_keeps_non_ascii_and_valid_surrogate_pairs(): + mock_request = MagicMock() + mock_request.form = AsyncMock( + return_value=FormData({"model": "whisper-1", "metadata": '{"tags": ["caf\\u00e9", "\\ud83d\\ude00"]}'}) + ) + mock_request.headers = {"content-type": "multipart/form-data"} + mock_request.scope = {} + mock_request.state._cached_headers = None + + result = await read_request_body(mock_request) + + assert result["metadata"]["tags"] == ["café", "😀"] diff --git a/tests/unit/proxy/common_utils/test_request_tag_mappings.py b/tests/unit/proxy/common_utils/test_request_tag_mappings.py new file mode 100644 index 00000000000..e1644544c46 --- /dev/null +++ b/tests/unit/proxy/common_utils/test_request_tag_mappings.py @@ -0,0 +1,473 @@ +import json +from types import SimpleNamespace +from typing import cast +from unittest.mock import AsyncMock, MagicMock, patch + +import pytest +from fastapi import Request +from pydantic import ValidationError + +from litellm.models.budget import LiteLLM_BudgetTable +from litellm.constants import BAGGAGE_MAPPED_TAGS_METADATA_KEY +from litellm.models.tag import LiteLLM_TagTable +from litellm.proxy._types import ConfigGeneralSettings, ProxyException +from litellm.proxy.common_utils.http_parsing_utils import read_request_body +from litellm.proxy.common_utils.request_tag_mappings import is_baggage_mapped_route, resolve_baggage_tag_mappings +from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache, tag_cache_key +from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup, add_litellm_data_to_request +from litellm.types.proxy.request_tag_mappings import RequestTagMapping + + +def test_accounting_enrichment_without_request_state_preserves_legacy_metadata(): + request = cast(Request, SimpleNamespace(headers={})) + data = {"metadata": {"tags": ["existing"]}} + LiteLLMProxyRequestSetup.apply_authenticated_baggage_tags(request, data) + assert data == {"metadata": {"tags": ["existing"]}} + + +@pytest.mark.asyncio +@pytest.mark.parametrize("header", [b"", b"entrypoint=a,entrypoint=b"]) +@pytest.mark.parametrize("client_metadata", [None, '{"requester_metadata":{"guardrails":["qa-guard"]}}']) +async def test_mapping_rejection_keeps_string_metadata_safe_for_auth_failure_logging(header, client_metadata): + from litellm.utils import get_request_guardrails + + request = Request({"type": "http", "headers": [(b"baggage", header)]}) + data = {"metadata": client_metadata} + with pytest.raises(ProxyException) as error: + await LiteLLMProxyRequestSetup.apply_baggage_tag_mappings_pre_auth( + request, + data, + {"request_tag_mappings": [{"key": "entrypoint", "tag_prefix": "usecase:", "required": True}]}, + None, + MagicMock(), + ) + assert error.value.code == "400" + assert get_request_guardrails(data) == (["qa-guard"] if client_metadata is not None else []) + + +@pytest.mark.asyncio +@pytest.mark.parametrize("slot", ["metadata", "litellm_metadata"]) +@pytest.mark.parametrize("invalid_metadata", [[], 42, "not-json", '"not-an-object"']) +async def test_invalid_mapper_metadata_maps_like_empty_metadata_and_keeps_the_client_cache(slot, invalid_metadata): + from litellm.proxy.auth.user_api_key_auth import _read_request_body_deferring_parse_failure + from litellm.utils import get_request_guardrails + + body = {"metadata": '{"tags":["client"]}', "litellm_metadata": '{"tags":["alternate"]}'} + body[slot] = invalid_metadata + + async def receive(): + return {"type": "http.request", "body": json.dumps(body).encode()} + + request = Request( + {"type": "http", "method": "POST", "path": "/v1/responses", "headers": [(b"baggage", b"entrypoint=a")]}, + receive, + ) + data, parse_error = await _read_request_body_deferring_parse_failure(request) + assert parse_error is None + await LiteLLMProxyRequestSetup.apply_baggage_tag_mappings_pre_auth( + request, + data, + {"request_tag_mappings": [{"key": "entrypoint", "tag_prefix": "usecase:"}]}, + None, + MagicMock(), + ) + assert "usecase:a" in data["litellm_metadata"]["tags"] + assert "tags" not in data[slot] or slot == "litellm_metadata" + assert get_request_guardrails(data) == [] + assert await read_request_body(request) == body + + +@pytest.mark.parametrize( + "header,value", + [ + ("entrypoint=a", "a"), + ("entrypoint = a", "a"), + ("region=sg, entrypoint=customer%20support;version=1", "customer support"), + ], +) +def test_variable_mapper_uses_decoded_baggage_value(header, value): + rule = RequestTagMapping(key="entrypoint", tag_prefix="usecase:") + assert resolve_baggage_tag_mappings(header, [rule]) == ((f"usecase:{value}", False),) + + +@pytest.mark.parametrize( + "header,expected", + [("entrypoint=a", "department:support"), ("entrypoint=b", "department:sales"), ("entrypoint=x", "usecase:x")], +) +def test_exact_rules_override_variable_fallback_independent_of_order(header, expected): + rules = [ + RequestTagMapping(key="entrypoint", tag_prefix="usecase:"), + RequestTagMapping(key="entrypoint", value="a", tag="department:support"), + RequestTagMapping(key="entrypoint", value="b", tag="department:sales"), + ] + assert resolve_baggage_tag_mappings(header, rules) == ((expected, False),) + assert resolve_baggage_tag_mappings(header, list(reversed(rules))) == ((expected, False),) + + +@pytest.mark.parametrize("header", ["entrypoint=%00", "entrypoint=a%0Ab", "entrypoint=b,entry%70oint=a"]) +def test_variable_mapper_skips_control_characters_and_percent_encoded_duplicate_keys(header): + rule = RequestTagMapping(key="entrypoint", tag_prefix="usecase:") + assert resolve_baggage_tag_mappings(header, [rule]) == () + + +@pytest.mark.parametrize( + "header,expected", + [ + ("entry+point=a", (("usecase:a", False),)), + ("entry%2Bpoint=a", (("usecase:a", False),)), + ("entry+point=a,entry%2Bpoint=b", ()), + ], +) +def test_key_with_a_plus_matches_both_wire_spellings_and_rejects_both_at_once(header, expected): + rule = RequestTagMapping(key="entry+point", tag_prefix="usecase:") + assert resolve_baggage_tag_mappings(header, [rule]) == expected + + +def test_exact_rules_work_without_a_variable_rule(): + rule = RequestTagMapping(key="entrypoint", value="a", tag="usecase:manual") + assert resolve_baggage_tag_mappings("entrypoint=a", [rule]) == (("usecase:manual", False),) + assert resolve_baggage_tag_mappings("entrypoint=x", [rule]) == () + + +@pytest.mark.parametrize( + "header", ["", "region=sg", "entrypoint=", "entrypoint=a,entrypoint=b", "entrypoint=b,entry%70oint=a", "entrypoint=x"] +) +def test_required_mapping_rejects_missing_ambiguous_or_unmapped_values(header): + rule = RequestTagMapping(key="entrypoint", value="a", tag="usecase:a", required=True) + with pytest.raises(ProxyException) as error: + resolve_baggage_tag_mappings(header, [rule]) + assert error.value.code == "400" + + +@pytest.mark.parametrize( + "rule", + [ + {"key": "entrypoint", "tag": "usecase:a"}, + {"key": "entrypoint", "value": "a", "tag_prefix": "usecase:"}, + {"key": "entrypoint", "value": "a", "tag": "usecase:a", "tag_prefix": "usecase:"}, + {"key": "", "tag_prefix": "usecase:"}, + ], +) +def test_invalid_rule_is_rejected_during_config_validation(rule): + with pytest.raises(ValidationError): + ConfigGeneralSettings.model_validate({"request_tag_mappings": [rule]}) + + +def test_duplicate_fallbacks_are_rejected(): + with pytest.raises(ValidationError, match="Only one mapping"): + ConfigGeneralSettings.model_validate( + { + "request_tag_mappings": [ + {"key": "entrypoint", "tag_prefix": "one:"}, + {"key": "entrypoint", "tag_prefix": "two:"}, + ] + } + ) + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "route,slot", + [("/chat/completions", "metadata"), ("/v1/messages", "litellm_metadata"), ("/v1/responses", "litellm_metadata")], +) +async def test_mapped_tag_merges_with_existing_tags_in_the_budget_metadata_slot(route, slot): + data = {slot: {"tags": ["existing", "usecase:a"]}} + request = Request({"type": "http", "headers": [(b"baggage", b"entrypoint=a")]}) + LiteLLMProxyRequestSetup.pre_seed_litellm_metadata_for_route(data, route) + await LiteLLMProxyRequestSetup.apply_baggage_tag_mappings_pre_auth( + request, + data, + {"request_tag_mappings": [{"key": "entrypoint", "tag_prefix": "usecase:"}]}, + None, + MagicMock(), + ) + assert data[slot]["tags"] == ["existing", "usecase:a"] + + +@pytest.mark.asyncio +async def test_budgeted_mapper_requires_a_database(): + request = Request({"type": "http", "headers": [(b"baggage", b"entrypoint=a")]}) + config = {"request_tag_mappings": [{"key": "entrypoint", "tag_prefix": "usecase:", "require_budgeted_tag": True}]} + with pytest.raises(ProxyException) as error: + await LiteLLMProxyRequestSetup.apply_baggage_tag_mappings_pre_auth( + request, {}, config, None, MagicMock() + ) + assert error.value.code == "503" + + +@pytest.mark.asyncio +async def test_budgeted_mapper_answers_503_when_the_tag_budget_lookup_fails(): + request = Request({"type": "http", "headers": [(b"baggage", b"entrypoint=a")]}) + prisma_client = MagicMock() + prisma_client.db.litellm_tagtable.find_many = AsyncMock(side_effect=Exception("database unreachable")) + config = {"request_tag_mappings": [{"key": "entrypoint", "tag_prefix": "usecase:", "require_budgeted_tag": True}]} + with pytest.raises(ProxyException, match="could not read tag budgets") as error: + await LiteLLMProxyRequestSetup.apply_baggage_tag_mappings_pre_auth( + request, {"metadata": {}}, config, prisma_client, UserApiKeyCache() + ) + assert error.value.code == "503" + + +@pytest.mark.asyncio +async def test_budgeted_mapper_serves_through_a_db_outage_when_requests_are_allowed_on_db_unavailable(): + request = Request({"type": "http", "headers": [(b"baggage", b"entrypoint=a")]}) + prisma_client = MagicMock() + prisma_client.db.litellm_tagtable.find_many = AsyncMock(side_effect=Exception("database unreachable")) + data = {"metadata": {}} + config = {"request_tag_mappings": [{"key": "entrypoint", "tag_prefix": "usecase:", "require_budgeted_tag": True}]} + with patch.dict("litellm.proxy.proxy_server.general_settings", {"allow_requests_on_db_unavailable": True}): + await LiteLLMProxyRequestSetup.apply_baggage_tag_mappings_pre_auth( + request, data, config, prisma_client, UserApiKeyCache() + ) + assert data["metadata"]["tags"] == ["usecase:a"] + + +async def _cache_with_tag(tag: LiteLLM_TagTable) -> UserApiKeyCache: + cache = UserApiKeyCache() + await cache.async_set_cache(key=tag_cache_key(tag.tag_name), value=tag, model_type=LiteLLM_TagTable) + return cache + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "budget_table", + [None, LiteLLM_BudgetTable(budget_id="qa-budget", max_budget=None, tpm_limit=10)], +) +async def test_budgeted_mapper_rejects_a_tag_without_a_max_budget(budget_table): + request = Request({"type": "http", "headers": [(b"baggage", b"entrypoint=a")]}) + data = {"metadata": {}} + cache = await _cache_with_tag(LiteLLM_TagTable(tag_name="usecase:a", litellm_budget_table=budget_table)) + config = {"request_tag_mappings": [{"key": "entrypoint", "tag_prefix": "usecase:", "require_budgeted_tag": True}]} + with pytest.raises(ProxyException, match="usecase:a requires an existing tag budget") as error: + await LiteLLMProxyRequestSetup.apply_baggage_tag_mappings_pre_auth( + request, data, config, MagicMock(), cache + ) + assert error.value.code == "400" + assert data == {"metadata": {}} + + +@pytest.mark.asyncio +async def test_budgeted_mapper_admits_a_tag_with_a_max_budget_and_unbudgeted_rules_need_none(): + request = Request({"type": "http", "headers": [(b"baggage", b"entrypoint=a,region=sg")]}) + data = {"metadata": {}} + cache = await _cache_with_tag( + LiteLLM_TagTable( + tag_name="usecase:a", litellm_budget_table=LiteLLM_BudgetTable(budget_id="qa-budget", max_budget=1.0) + ) + ) + config = { + "request_tag_mappings": [ + {"key": "entrypoint", "tag_prefix": "usecase:", "require_budgeted_tag": True}, + {"key": "region", "tag_prefix": "region:"}, + ] + } + await LiteLLMProxyRequestSetup.apply_baggage_tag_mappings_pre_auth( + request, data, config, MagicMock(), cache + ) + assert data["metadata"]["tags"] == ["usecase:a", "region:sg"] + + +@pytest.mark.parametrize( + "route", + ["/v1/chat/completions", "/chat/completions", "/v1/messages", "/v1/responses", "/a2a/qa-agent/message/send"], +) +def test_inference_routes_take_baggage_mappings(route): + assert is_baggage_mapped_route(route) + + +@pytest.mark.parametrize( + "route", + [ + "/utils/token_counter", + "/utils/transform_request", + "/v1/messages/count_tokens", + "/v1/responses/input_tokens", + "/v1beta/models/gemini-pro:countTokens", + "/mcp", + ], +) +def test_unbilled_and_mcp_routes_skip_baggage_mappings(route): + assert not is_baggage_mapped_route(route) + + +@pytest.mark.parametrize("registered", [True, False]) +def test_custom_pass_through_routes_take_baggage_mappings_once_registered(registered): + from litellm.proxy.pass_through_endpoints.pass_through_endpoints import _registered_pass_through_routes + + endpoints = {"qa-endpoint:exact:/billing-api": {"target": "http://example.com", "headers": {}}} + with patch.dict(_registered_pass_through_routes, endpoints if registered else {}, clear=True): + assert is_baggage_mapped_route("/billing-api") is registered + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "route,slot", + [("/chat/completions", "metadata"), ("/v1/messages", "litellm_metadata"), ("/v1/responses", "litellm_metadata")], +) +@pytest.mark.parametrize("query", [b"api-version=qa-version", b"key=qa-virtual-key"]) +@pytest.mark.parametrize("client_metadata", [None, '{"requester_metadata":{"guardrails":[]}}']) +async def test_mapping_survives_cached_body_read_without_leaking_auth_query_fields(route, slot, query, client_metadata): + from litellm.proxy._types import UserAPIKeyAuth + from litellm.proxy.proxy_server import ProxyConfig + + body = {"model": "qa-model"} + if client_metadata is not None: + body["metadata"] = client_metadata + + async def receive(): + return {"type": "http.request", "body": json.dumps(body).encode()} + + request = Request( + { + "type": "http", + "method": "POST", + "path": route, + "scheme": "http", + "server": ("localhost", 4000), + "query_string": query, + "headers": [(b"content-type", b"application/json"), (b"baggage", b"entrypoint=a")], + }, + receive, + ) + from litellm.proxy.auth.user_api_key_auth import _read_request_body_deferring_parse_failure + + data, parse_error = await _read_request_body_deferring_parse_failure(request) + assert parse_error is None + LiteLLMProxyRequestSetup.pre_seed_litellm_metadata_for_route(data, route) + await LiteLLMProxyRequestSetup.apply_baggage_tag_mappings_pre_auth( + request, + data, + {"request_tag_mappings": [{"key": "entrypoint", "tag_prefix": "usecase:"}]}, + None, + MagicMock(), + ) + downstream = await read_request_body(request) + assert downstream == body + enriched = await add_litellm_data_to_request( + data=downstream, + request=request, + user_api_key_dict=UserAPIKeyAuth(api_key="qa-key"), + proxy_config=ProxyConfig(), + general_settings={}, + ) + assert enriched[slot]["tags"] == ["usecase:a"] + assert "key" not in enriched + assert "api-version" not in enriched + assert "key" not in enriched["proxy_server_request"]["body"] + assert "api-version" not in enriched["proxy_server_request"]["body"] + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "client_metadata", + [{"trace_name": "qa"}, {"trace_name": "qa", "tags": ["client:x"]}, {"trace_name": "qa", "tags": ["usecase:a"]}], +) +async def test_mapped_tags_stay_out_of_requester_metadata(client_metadata): + from litellm.proxy._types import UserAPIKeyAuth + from litellm.proxy.auth.user_api_key_auth import _read_request_body_deferring_parse_failure + from litellm.proxy.proxy_server import ProxyConfig + + body = {"model": "qa-model", "metadata": client_metadata} + + async def receive(): + return {"type": "http.request", "body": json.dumps(body).encode()} + + request = Request( + { + "type": "http", + "method": "POST", + "path": "/chat/completions", + "scheme": "http", + "server": ("localhost", 4000), + "query_string": b"", + "headers": [(b"content-type", b"application/json"), (b"baggage", b"entrypoint=a")], + }, + receive, + ) + data, parse_error = await _read_request_body_deferring_parse_failure(request) + assert parse_error is None + await LiteLLMProxyRequestSetup.apply_baggage_tag_mappings_pre_auth( + request, data, {"request_tag_mappings": [{"key": "entrypoint", "tag_prefix": "usecase:"}]}, None, MagicMock() + ) + enriched = await add_litellm_data_to_request( + data=await read_request_body(request), + request=request, + user_api_key_dict=UserAPIKeyAuth(api_key="qa-key"), + proxy_config=ProxyConfig(), + general_settings={}, + ) + requester_metadata = enriched["metadata"]["requester_metadata"] + assert "usecase:a" in enriched["metadata"]["tags"] + assert requester_metadata["trace_name"] == "qa" + assert requester_metadata.get("tags") == client_metadata.get("tags") + assert BAGGAGE_MAPPED_TAGS_METADATA_KEY not in requester_metadata + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "headers,body_fields", + [ + ([(b"x-litellm-tags", b"usecase:a")], {}), + ([], {"tags": ["usecase:a"]}), + ([], {"litellm_metadata": {"tags": ["usecase:a"]}}), + ], + ids=["header", "body", "litellm_metadata"], +) +async def test_client_sent_tag_still_routes_when_baggage_maps_to_it(headers, body_fields): + import litellm + from litellm.proxy._types import UserAPIKeyAuth + from litellm.proxy.auth.user_api_key_auth import _read_request_body_deferring_parse_failure + from litellm.proxy.proxy_server import ProxyConfig + + body = {"model": "gpt-4", **body_fields} + + async def receive(): + return {"type": "http.request", "body": json.dumps(body).encode()} + + request = Request( + { + "type": "http", + "method": "POST", + "path": "/chat/completions", + "scheme": "http", + "server": ("localhost", 4000), + "query_string": b"", + "headers": [(b"content-type", b"application/json"), (b"baggage", b"entrypoint=a"), *headers], + }, + receive, + ) + data, parse_error = await _read_request_body_deferring_parse_failure(request) + assert parse_error is None + await LiteLLMProxyRequestSetup.apply_baggage_tag_mappings_pre_auth( + request, data, {"request_tag_mappings": [{"key": "entrypoint", "tag_prefix": "usecase:"}]}, None, MagicMock() + ) + enriched = await add_litellm_data_to_request( + data=await read_request_body(request), + request=request, + user_api_key_dict=UserAPIKeyAuth(api_key="qa-key"), + proxy_config=ProxyConfig(), + general_settings={}, + ) + router = litellm.Router( + model_list=[ + { + "model_name": "gpt-4", + "litellm_params": {"model": "gpt-4o", "tags": ["usecase:a"]}, + "model_info": {"id": "usecase-deployment"}, + }, + { + "model_name": "gpt-4", + "litellm_params": {"model": "gpt-4o-mini", "tags": ["default"]}, + "model_info": {"id": "default-deployment"}, + }, + ], + enable_tag_filtering=True, + ) + for _ in range(5): + response = await router.acompletion( + model="gpt-4", + messages=[{"role": "user", "content": "hi"}], + metadata=dict(enriched["metadata"]), + mock_response="hi", + ) + assert response._hidden_params["model_id"] == "usecase-deployment" diff --git a/tests/unit/proxy/credential_endpoints/test_endpoints.py b/tests/unit/proxy/credential_endpoints/test_endpoints.py index 6aeceaf4356..c905d38dd41 100644 --- a/tests/unit/proxy/credential_endpoints/test_endpoints.py +++ b/tests/unit/proxy/credential_endpoints/test_endpoints.py @@ -4,7 +4,7 @@ import json from contextlib import contextmanager from types import SimpleNamespace from typing import Final -from unittest.mock import AsyncMock, MagicMock, patch +from unittest.mock import AsyncMock, MagicMock, call, patch import httpx import pytest @@ -14,11 +14,13 @@ from fastapi import HTTPException, Request from fastapi.testclient import TestClient import litellm -from litellm.models.credentials import CredentialSource +from litellm.litellm_core_utils.credential_accessor import CredentialAccessor +from litellm.llms.github_copilot.per_user_auth import _SESSION_CACHE, _session_cache_key +from litellm.models.credentials import CredentialSource, UserConnectionFlowHandle from litellm.proxy._types import LiteLLM_UserTable, LitellmUserRoles, UserAPIKeyAuth from litellm.proxy.auth.user_api_key_auth import user_api_key_auth from litellm.proxy.common_utils.encrypt_decrypt_utils import encrypt_value_helper -from litellm.proxy.credential_endpoints.endpoints import get_llm_router +from litellm.proxy.credential_endpoints.endpoints import _decode_flow_handle, get_llm_router from litellm.proxy.proxy_server import app from litellm.types.utils import CredentialItem @@ -1428,6 +1430,298 @@ def test_create_credential_still_answers_200_for_a_name_that_is_free(credential_ find_by_name.assert_not_awaited(), "the unique index is the guard; create must not add a lookup" +@pytest.mark.parametrize( + "host", + ["https://x.ghe.com", "ghes.example.com", "x.ghe.com:443", "a.b.ghe.com"], +) +def test_create_credential_rejects_invalid_github_copilot_hosts(credential_store, host): + create: Final = AsyncMock() + credential_store(create=create) + + response: Final = _create_credential( + { + "credential_name": "copilot", + "credential_values": {"github_copilot_host": host}, + "credential_info": {"custom_llm_provider": "github_copilot"}, + } + ) + + assert response.status_code == 400 + create.assert_not_awaited() + + +def test_create_credential_normalizes_github_copilot_host(credential_store): + credential_store(create=AsyncMock()) + + response = _create_credential( + { + "credential_name": "copilot", + "credential_values": {"github_copilot_host": "OCTO.ghe.com"}, + "credential_info": {"custom_llm_provider": "github_copilot"}, + } + ) + + assert response.status_code == 200, response.text + assert CredentialAccessor.find_credential("copilot").credential_values["github_copilot_host"] == "octo.ghe.com" + + +@pytest.mark.parametrize( + "host", + ["https://x.ghe.com", "ghes.example.com", "x.ghe.com:443", "a.b.ghe.com"], +) +def test_update_credential_rejects_invalid_github_copilot_hosts(credential_store, host): + stored: Final = CredentialItem( + credential_name="copilot", + credential_values={"github_copilot_host": "octo.ghe.com"}, + credential_info={"custom_llm_provider": "github_copilot"}, + ) + update: Final = AsyncMock() + credential_store(in_memory=(stored,), find_by_name=AsyncMock(return_value=stored), update_by_name=update) + + response = _patch_credential( + "copilot", + { + "credential_name": "copilot", + "credential_values": {"github_copilot_host": host}, + "credential_info": {"custom_llm_provider": "github_copilot"}, + }, + ) + + assert response.status_code == 400 + update.assert_not_awaited() + + +def test_update_credential_normalizes_github_copilot_host(credential_store): + stored = CredentialItem( + credential_name="copilot", + credential_values={}, + credential_info={"custom_llm_provider": "github_copilot"}, + ) + credential_store( + in_memory=(stored,), + find_by_name=AsyncMock(return_value=stored), + update_by_name=AsyncMock(), + ) + + response = _patch_credential( + "copilot", + { + "credential_name": "copilot", + "credential_values": {"github_copilot_host": "OCTO.ghe.com"}, + "credential_info": {"custom_llm_provider": "github_copilot"}, + }, + ) + + assert response.status_code == 200, response.text + assert CredentialAccessor.find_credential("copilot").credential_values["github_copilot_host"] == "octo.ghe.com" + + +def _encrypted_per_user_copilot_credential(host: str) -> CredentialItem: + return CredentialItem( + credential_name="copilot", + credential_values={ + "github_copilot_auth_type": encrypt_value_helper("per_user_oauth"), + "github_copilot_host": encrypt_value_helper(host), + }, + credential_info={"custom_llm_provider": "github_copilot"}, + ) + + +def test_update_credential_purges_connections_when_github_host_changes(monkeypatch, restore_credential_list): + stored = _encrypted_per_user_copilot_credential("github.com") + with _repository_holding(stored): + from litellm.proxy import proxy_server + + table = MagicMock() + table.find_many = AsyncMock(return_value=[_connection_row(credential_name="copilot")]) + table.delete_many = AsyncMock(return_value=None) + proxy_server.prisma_client.db.litellm_userprovidercredentials = table + proxy_server.prisma_client.writer_db = proxy_server.prisma_client.db + + cached_values: Final[dict[str, object]] = {} # mutable-ok: fake Redis stores invalidation writes + + async def set_cache(key: str, value: str, **kwargs: object) -> None: + cached_values[key] = value + + async def get_cache(key: str, **kwargs: object) -> object: + return cached_values.get(key) + + redis_cache: Final = MagicMock() + redis_cache.async_set_cache = AsyncMock(side_effect=set_cache) + redis_cache.async_get_cache = AsyncMock(side_effect=get_cache) + monkeypatch.setattr(proxy_server, "user_api_key_cache", DualCache(redis_cache=redis_cache)) + + session_key: Final = _session_cache_key("user-a", "copilot", "github.com") + _SESSION_CACHE.set_cache( + session_key, + ("gho_secret", "copilot-token", "https://api.githubcopilot.com", 4102444800), + ttl=3600, + ) + response = _patch_credential( + "copilot", + { + "credential_name": "copilot", + "credential_values": {"github_copilot_host": "octo.ghe.com"}, + "credential_info": {}, + }, + ) + + assert response.status_code == 200, response.text + table.find_many.assert_has_awaits( + [ + call(where={"credential_name": "copilot"}), + call(where={"credential_name": "copilot"}), + ] + ) + table.delete_many.assert_awaited_once_with(where={"credential_name": "copilot"}) + assert cached_values[upc._cache_key("user-a", "copilot")] == upc._NOT_CONNECTED + assert _SESSION_CACHE.get_cache(session_key) is None + + +def test_update_credential_does_not_purge_connections_for_case_only_host_change(restore_credential_list): + stored = _encrypted_per_user_copilot_credential("octo.ghe.com") + with _repository_holding(stored): + from litellm.proxy import proxy_server + + table = MagicMock() + table.find_many = AsyncMock( + return_value=[_connection_row(credential_name="copilot", github_host="octo.ghe.com")] + ) + table.delete_many = AsyncMock(return_value=None) + proxy_server.prisma_client.db.litellm_userprovidercredentials = table + proxy_server.prisma_client.writer_db = proxy_server.prisma_client.db + + session_key: Final = _session_cache_key("user-a", "copilot", "octo.ghe.com") + _SESSION_CACHE.set_cache( + session_key, + ("gho_secret", "copilot-token", "https://copilot-api.octo.ghe.com", 4102444800), + ttl=3600, + ) + response = _patch_credential( + "copilot", + { + "credential_name": "copilot", + "credential_values": {"github_copilot_host": "OCTO.ghe.com"}, + "credential_info": {}, + }, + ) + + assert response.status_code == 200, response.text + table.find_many.assert_not_awaited() + table.delete_many.assert_not_awaited() + assert _SESSION_CACHE.get_cache(session_key) is not None + _SESSION_CACHE.delete_cache(session_key) + + +def test_update_credential_does_not_purge_connections_for_legacy_host_case_difference(restore_credential_list): + stored = _encrypted_per_user_copilot_credential("OCTO.ghe.com") + with _repository_holding(stored): + from litellm.proxy import proxy_server + + table = MagicMock() + table.find_many = AsyncMock( + return_value=[_connection_row(credential_name="copilot", github_host="octo.ghe.com")] + ) + table.delete_many = AsyncMock(return_value=None) + proxy_server.prisma_client.db.litellm_userprovidercredentials = table + proxy_server.prisma_client.writer_db = proxy_server.prisma_client.db + + session_key: Final = _session_cache_key("user-a", "copilot", "octo.ghe.com") + _SESSION_CACHE.set_cache( + session_key, + ("gho_secret", "copilot-token", "https://copilot-api.octo.ghe.com", 4102444800), + ttl=3600, + ) + response = _patch_credential( + "copilot", + { + "credential_name": "copilot", + "credential_values": {"github_copilot_host": "octo.ghe.com"}, + "credential_info": {}, + }, + ) + + assert response.status_code == 200, response.text + table.find_many.assert_not_awaited() + table.delete_many.assert_not_awaited() + assert _SESSION_CACHE.get_cache(session_key) is not None + _SESSION_CACHE.delete_cache(session_key) + + +def test_update_credential_purges_connections_when_github_host_is_deleted(restore_credential_list): + stored = _encrypted_per_user_copilot_credential("octo.ghe.com") + with _repository_holding(stored): + from litellm.proxy import proxy_server + + table = MagicMock() + table.find_many = AsyncMock(return_value=[_connection_row(credential_name="copilot")]) + table.delete_many = AsyncMock(return_value=None) + proxy_server.prisma_client.db.litellm_userprovidercredentials = table + proxy_server.prisma_client.writer_db = proxy_server.prisma_client.db + + response = _patch_credential( + "copilot", + { + "credential_name": "copilot", + "credential_values": {}, + "credential_values_to_delete": ["github_copilot_host"], + "credential_info": {}, + }, + ) + + assert response.status_code == 200, response.text + table.delete_many.assert_awaited_once_with(where={"credential_name": "copilot"}) + + +def test_update_credential_purges_connections_for_invalid_legacy_github_host(restore_credential_list): + stored = _encrypted_per_user_copilot_credential("legacy.invalid") + with _repository_holding(stored): + from litellm.proxy import proxy_server + + table = MagicMock() + table.find_many = AsyncMock(return_value=[_connection_row(credential_name="copilot")]) + table.delete_many = AsyncMock(return_value=None) + proxy_server.prisma_client.db.litellm_userprovidercredentials = table + proxy_server.prisma_client.writer_db = proxy_server.prisma_client.db + + response = _patch_credential( + "copilot", + { + "credential_name": "copilot", + "credential_values": {"api_key": "sk-updated"}, + "credential_info": {}, + }, + ) + + assert response.status_code == 200, response.text + table.delete_many.assert_awaited_once_with(where={"credential_name": "copilot"}) + + +def test_update_credential_does_not_purge_connections_for_unrelated_value_update(restore_credential_list): + stored = _encrypted_per_user_copilot_credential("octo.ghe.com") + with _repository_holding(stored): + from litellm.proxy import proxy_server + + table = MagicMock() + table.find_many = AsyncMock(return_value=[_connection_row(credential_name="copilot")]) + table.delete_many = AsyncMock(return_value=None) + proxy_server.prisma_client.db.litellm_userprovidercredentials = table + proxy_server.prisma_client.writer_db = proxy_server.prisma_client.db + + response = _patch_credential( + "copilot", + { + "credential_name": "copilot", + "credential_values": {"api_key": "sk-updated"}, + "credential_info": {}, + }, + ) + + assert response.status_code == 200, response.text + table.find_many.assert_not_awaited() + table.delete_many.assert_not_awaited() + + def test_update_credential_resolves_credential_values_from_model_id_like_create(credential_store): """Regression: PATCH dropped ``model_id`` from the body, so an update that named a deployment instead of raw values wrote whatever the caller sent, or nothing.""" @@ -1522,24 +1816,38 @@ def _as_user(user_id="user-a"): return lambda: UserAPIKeyAuth(api_key="test-key", user_role="internal_user", user_id=user_id) -def _per_user_credential(name="copilot-cred"): +def _per_user_credential( + name: str = "copilot-cred", + host: str | None = None, +) -> CredentialItem: return CredentialItem( credential_name=name, - credential_values={"github_copilot_auth_type": "per_user_oauth"}, + credential_values={ + "github_copilot_auth_type": "per_user_oauth", + **({"github_copilot_host": host} if host is not None else {}), + }, credential_info={}, ) -def _connection_row(user_id="user-a", credential_name="copilot-cred", login="octo"): +def _connection_row( + user_id: str = "user-a", + credential_name: str = "copilot-cred", + login: str = "octo", + github_host: str = "github.com", +) -> SimpleNamespace: from datetime import datetime, timezone - from types import SimpleNamespace return SimpleNamespace( user_id=user_id, credential_name=credential_name, provider="github_copilot", credential_b64=upc._encode( - upc.GithubCopilotUserConnectionPayload(access_token="gho_secret", github_login=login) + upc.GithubCopilotUserConnectionPayload( + access_token="gho_secret", + github_login=login, + github_host=github_host, + ) ), created_at=datetime(2026, 1, 1, tzinfo=timezone.utc), updated_at=datetime(2026, 1, 1, tzinfo=timezone.utc), @@ -1635,6 +1943,20 @@ def test_user_connection_start_returns_device_flow_fields(monkeypatch): } handle = response.json()["flow_handle"] assert isinstance(handle, str) and "device_code" not in handle and _DEVICE_FLOW_START["device_code"] not in handle + decoded_handle: Final = _decode_flow_handle(handle) + assert decoded_handle is not None + assert decoded_handle.github_host == "github.com" + + +def test_legacy_user_connection_flow_handle_defaults_to_github_com(): + handle: Final = UserConnectionFlowHandle( + user_id="user-a", + credential_name="copilot-cred", + device_code="DC-1", + interval=5, + expires_at=4102444800, + ) + assert handle.github_host == "github.com" def test_user_connection_start_404s_for_shared_credential(monkeypatch): @@ -1657,7 +1979,7 @@ def test_user_connection_poll_rejects_an_undecryptable_flow_handle(monkeypatch): def test_user_connection_poll_connected_persists_and_reports_login(monkeypatch): - table = _patch_user_connection_env(monkeypatch, [_per_user_credential()]) + table: Final = _patch_user_connection_env(monkeypatch, [_per_user_credential()]) with _github_http( { _DEVICE_CODE_URL: _DEVICE_FLOW_START, @@ -1666,9 +1988,13 @@ def test_user_connection_poll_connected_persists_and_reports_login(monkeypatch): _GITHUB_USER_URL: {"login": "octo"}, } ): - start = _call_as("POST", "/credentials/copilot-cred/user_connection/start", auth=_as_user()) + start: Final = _call_as("POST", "/credentials/copilot-cred/user_connection/start", auth=_as_user()) assert start.status_code == 200, start.text - poll = _call_as( + encrypted_handle: Final = start.json()["flow_handle"] + decoded_handle: Final = _decode_flow_handle(encrypted_handle) + assert decoded_handle is not None + assert decoded_handle.github_host == "github.com" + poll: Final = _call_as( "POST", "/credentials/copilot-cred/user_connection/poll", json_body={"flow_handle": start.json()["flow_handle"]}, @@ -1677,6 +2003,110 @@ def test_user_connection_poll_connected_persists_and_reports_login(monkeypatch): assert poll.status_code == 200, poll.text assert poll.json() == {"status": "connected", "interval": None, "github_login": "octo"} table.upsert.assert_awaited_once() + stored_connection: Final = upc.decode_user_provider_credential( + table.upsert.await_args.kwargs["data"]["create"]["credential_b64"] + ) + assert stored_connection is not None + assert stored_connection.github_host == "github.com" + + +def test_poll_host_change_race_requires_reconnect_on_the_next_request(monkeypatch): + from litellm.llms.github_copilot.per_user_auth import attach_github_copilot_user_session + + table: Final = _patch_user_connection_env(monkeypatch, [_per_user_credential(host="octo.ghe.com")]) + + def change_host_after_token_exchange(request: httpx.Request) -> dict[str, str]: + monkeypatch.setattr(litellm, "credential_list", [_per_user_credential()]) + return {"access_token": "gho_1"} + + with _github_http( + { + "https://octo.ghe.com/login/device/code": _DEVICE_FLOW_START, + "https://octo.ghe.com/login/oauth/access_token": change_host_after_token_exchange, + "https://api.octo.ghe.com/copilot_internal/v2/token": { + "token": "copilot-tok", + "expires_at": 4102444800, + "endpoints": {"api": "https://copilot-api.octo.ghe.com"}, + }, + "https://api.octo.ghe.com/user": {"login": "octo"}, + } + ): + start: Final = _call_as("POST", "/credentials/copilot-cred/user_connection/start", auth=_as_user()) + poll: Final = _call_as( + "POST", + "/credentials/copilot-cred/user_connection/poll", + json_body={"flow_handle": start.json()["flow_handle"]}, + auth=_as_user(), + ) + assert poll.status_code == 200, poll.text + stored_connection: Final = upc.decode_user_provider_credential( + table.upsert.await_args.kwargs["data"]["create"]["credential_b64"] + ) + assert stored_connection is not None + + kwargs: Final[dict[str, object]] = { + "litellm_credential_name": "copilot-cred", + "secret_fields": { + "user_provider_credentials_user_id": "user-a", + "user_provider_credentials": { + "copilot-cred": { + "access_token": stored_connection.access_token, + "github_host": stored_connection.github_host, + } + }, + }, + } + module_level_client: Final = MagicMock() + module_level_client.get.side_effect = AssertionError("unexpected token exchange") + with _github_http({}), patch.object(litellm, "module_level_client", module_level_client): + with pytest.raises(litellm.CallerCredentialAuthenticationError) as exc: + attach_github_copilot_user_session(kwargs) + assert "Connect GitHub Copilot for credential 'copilot-cred'" in str(exc.value) + assert stored_connection.github_host == "octo.ghe.com" + + +def test_ghe_user_connection_uses_tenant_urls_for_device_flow_exchange_and_login(monkeypatch): + table: Final = _patch_user_connection_env(monkeypatch, [_per_user_credential(host="octo.ghe.com")]) + with _github_http( + { + "https://octo.ghe.com/login/device/code": _DEVICE_FLOW_START, + "https://octo.ghe.com/login/oauth/access_token": {"access_token": "gho_1"}, + "https://api.octo.ghe.com/copilot_internal/v2/token": { + "token": "copilot-tok", + "expires_at": 4102444800, + "endpoints": {"api": "https://copilot-api.octo.ghe.com"}, + }, + "https://api.octo.ghe.com/user": {"login": "octo"}, + } + ): + start: Final = _call_as("POST", "/credentials/copilot-cred/user_connection/start", auth=_as_user()) + assert start.status_code == 200, start.text + poll: Final = _call_as( + "POST", + "/credentials/copilot-cred/user_connection/poll", + json_body={"flow_handle": start.json()["flow_handle"]}, + auth=_as_user(), + ) + assert poll.status_code == 200, poll.text + assert poll.json() == {"status": "connected", "interval": None, "github_login": "octo"} + table.upsert.assert_awaited_once() + stored_connection: Final = upc.decode_user_provider_credential( + table.upsert.await_args.kwargs["data"]["create"]["credential_b64"] + ) + assert stored_connection is not None + assert stored_connection.github_host == "octo.ghe.com" + + +def test_user_connection_poll_rejects_handle_from_different_host(monkeypatch): + _patch_user_connection_env(monkeypatch, [_per_user_credential(host="octo.ghe.com")]) + response = _call_as( + "POST", + "/credentials/copilot-cred/user_connection/poll", + json_body={"flow_handle": _flow_handle_for()}, + auth=_as_user(), + ) + assert response.status_code == 400 + assert response.json()["error"]["message"] == "invalid or expired flow_handle" def test_user_connection_poll_pending(monkeypatch): @@ -2038,6 +2468,23 @@ def test_pending_device_flow_survives_disconnect_via_stateless_handle(monkeypatc assert delete.json() == {"status": "disconnected"} +def test_delete_user_connection_evicts_copilot_session(monkeypatch): + table: Final = _patch_user_connection_env(monkeypatch, [_per_user_credential()], rows=[_connection_row()]) + session_key: Final = _session_cache_key("user-a", "copilot-cred", "github.com") + _SESSION_CACHE.set_cache( + session_key, + ("gho_secret", "copilot-token", "https://api.githubcopilot.com", 4102444800), + ttl=3600, + ) + + response: Final = _call_as("DELETE", "/credentials/copilot-cred/user_connection", auth=_as_user()) + + assert response.status_code == 200, response.text + assert response.json() == {"status": "disconnected"} + assert _SESSION_CACHE.get_cache(session_key) is None + table.delete_many.assert_awaited_once_with(where={"user_id": "user-a", "credential_name": "copilot-cred"}) + + def test_user_connection_cache_keys_cannot_collide_on_colons(): """user_id/credential_name are joined losslessly, so ('a:b','c') and ('a','b:c') can never share a cache or device-flow entry.""" diff --git a/tests/unit/proxy/credential_endpoints/test_user_provider_credentials.py b/tests/unit/proxy/credential_endpoints/test_user_provider_credentials.py index b549ecc67a9..dae3a0459e2 100644 --- a/tests/unit/proxy/credential_endpoints/test_user_provider_credentials.py +++ b/tests/unit/proxy/credential_endpoints/test_user_provider_credentials.py @@ -1,5 +1,6 @@ """Tests for the per-user provider credentials DB/cache module.""" +import json from types import SimpleNamespace from typing import Final from unittest.mock import AsyncMock, MagicMock @@ -7,9 +8,11 @@ from unittest.mock import AsyncMock, MagicMock import pytest from litellm.caching.dual_cache import DualCache +from litellm.constants import GITHUB_COPILOT_DEFAULT_HOST +from litellm.proxy.common_utils.encrypt_decrypt_utils import encrypt_value_helper from litellm.proxy.credential_endpoints.user_provider_credentials import ( GithubCopilotUserConnectionPayload, - aget_user_provider_tokens, + aget_user_provider_credentials, decode_user_provider_credential, delete_user_provider_credential, delete_user_provider_credentials_for_credential, @@ -110,7 +113,7 @@ async def test_delete_for_credential_returns_affected_user_ids(): @pytest.mark.asyncio -async def test_aget_tokens_returns_plaintext_and_caches_ciphertext(monkeypatch): +async def test_aget_credentials_returns_plaintext_and_caches_ciphertext(monkeypatch): payload = GithubCopilotUserConnectionPayload(access_token="gho_secret", github_login="octo") from litellm.proxy.credential_endpoints import user_provider_credentials as upc @@ -121,12 +124,12 @@ async def test_aget_tokens_returns_plaintext_and_caches_ciphertext(monkeypatch): redis = _fake_redis(monkeypatch) cache = DualCache(redis_cache=redis) - tokens = await aget_user_provider_tokens(prisma_client, cache, "user-a", ["copilot-cred"]) - assert tokens == {"copilot-cred": "gho_secret"} + connections = await aget_user_provider_credentials(prisma_client, cache, "user-a", ["copilot-cred"]) + assert connections == {"copilot-cred": {"access_token": "gho_secret", "github_host": "github.com"}} # second call served from cache: no new DB read, and cache holds ciphertext not plaintext - tokens2 = await aget_user_provider_tokens(prisma_client, cache, "user-a", ["copilot-cred"]) - assert tokens2 == {"copilot-cred": "gho_secret"} + connections2 = await aget_user_provider_credentials(prisma_client, cache, "user-a", ["copilot-cred"]) + assert connections2 == {"copilot-cred": {"access_token": "gho_secret", "github_host": "github.com"}} assert table.find_many.await_count == 1 cached = await redis.async_get_cache(upc._cache_key("user-a", "copilot-cred")) assert cached == ciphertext @@ -135,14 +138,59 @@ async def test_aget_tokens_returns_plaintext_and_caches_ciphertext(monkeypatch): @pytest.mark.asyncio -async def test_aget_tokens_negative_caches_missing_connection(monkeypatch): +async def test_aget_connections_preserves_github_host(monkeypatch): + payload: Final = GithubCopilotUserConnectionPayload( + access_token="gho_secret", + github_login="octo", + github_host="octo.ghe.com", + ) + from litellm.proxy.credential_endpoints import user_provider_credentials as upc + + table: Final = MagicMock() + table.find_many = AsyncMock(return_value=[_row(credential_b64=upc._encode(payload))]) + prisma_client: Final = _prisma(table) + cache: Final = DualCache(redis_cache=_fake_redis(monkeypatch)) + + connections: Final = await aget_user_provider_credentials( + prisma_client, + cache, + "user-a", + ["copilot-cred"], + ) + assert connections == {"copilot-cred": {"access_token": "gho_secret", "github_host": "octo.ghe.com"}} + + +@pytest.mark.asyncio +async def test_legacy_connection_without_github_host_defaults_to_github_com(monkeypatch): + ciphertext: Final = encrypt_value_helper(json.dumps({"access_token": "gho_secret", "github_login": "octo"})) + table: Final = MagicMock() + table.find_many = AsyncMock(return_value=[_row(credential_b64=ciphertext)]) + prisma_client: Final = _prisma(table) + cache: Final = DualCache(redis_cache=_fake_redis(monkeypatch)) + + connections: Final = await aget_user_provider_credentials( + prisma_client, + cache, + "user-a", + ["copilot-cred"], + ) + assert connections == { + "copilot-cred": { + "access_token": "gho_secret", + "github_host": GITHUB_COPILOT_DEFAULT_HOST, + } + } + + +@pytest.mark.asyncio +async def test_aget_credentials_negative_caches_missing_connection(monkeypatch): table = MagicMock() table.find_many = AsyncMock(return_value=[]) prisma_client = _prisma(table) cache = DualCache(redis_cache=_fake_redis(monkeypatch)) - assert await aget_user_provider_tokens(prisma_client, cache, "user-a", ["copilot-cred"]) == {} - assert await aget_user_provider_tokens(prisma_client, cache, "user-a", ["copilot-cred"]) == {} + assert await aget_user_provider_credentials(prisma_client, cache, "user-a", ["copilot-cred"]) == {} + assert await aget_user_provider_credentials(prisma_client, cache, "user-a", ["copilot-cred"]) == {} assert table.find_many.await_count == 1 @@ -156,10 +204,10 @@ async def test_invalidate_cache_forces_db_refetch(monkeypatch): prisma_client = _prisma(table) cache = DualCache(redis_cache=_fake_redis(monkeypatch)) - await aget_user_provider_tokens(prisma_client, cache, "user-a", ["copilot-cred"]) + await aget_user_provider_credentials(prisma_client, cache, "user-a", ["copilot-cred"]) await drop_user_provider_credential_cache(cache, "user-a", "copilot-cred") - tokens = await aget_user_provider_tokens(prisma_client, cache, "user-a", ["copilot-cred"]) - assert tokens == {"copilot-cred": "gho_new"} + connections = await aget_user_provider_credentials(prisma_client, cache, "user-a", ["copilot-cred"]) + assert connections == {"copilot-cred": {"access_token": "gho_new", "github_host": "github.com"}} assert table.find_many.await_count == 2 @@ -184,19 +232,19 @@ async def test_disconnect_on_one_worker_invalidates_other_workers_via_redis(monk prisma_client = _prisma(table) # worker A "connects" (DB read + cache write) - tokens_a = await aget_user_provider_tokens(prisma_client, cache_a, "user-a", ["copilot-cred"]) - assert tokens_a == {"copilot-cred": "gho_secret"} + connections_a = await aget_user_provider_credentials(prisma_client, cache_a, "user-a", ["copilot-cred"]) + assert connections_a == {"copilot-cred": {"access_token": "gho_secret", "github_host": "github.com"}} # worker B reads the same connection straight from Redis (its in-memory layer is empty) - tokens_b = await aget_user_provider_tokens(prisma_client, cache_b, "user-a", ["copilot-cred"]) - assert tokens_b == {"copilot-cred": "gho_secret"} + connections_b = await aget_user_provider_credentials(prisma_client, cache_b, "user-a", ["copilot-cred"]) + assert connections_b == {"copilot-cred": {"access_token": "gho_secret", "github_host": "github.com"}} # worker A disconnects: the key is overwritten with the not-connected tombstone await invalidate_user_provider_credential_cache(cache_a, "user-a", "copilot-cred") # worker B sees the tombstone from Redis, no worker-local staleness, no DB read needed - tokens_b_after = await aget_user_provider_tokens(prisma_client, cache_b, "user-a", ["copilot-cred"]) - assert tokens_b_after == {} + connections_b_after = await aget_user_provider_credentials(prisma_client, cache_b, "user-a", ["copilot-cred"]) + assert connections_b_after == {} assert table.find_many.await_count == 1 @@ -222,8 +270,8 @@ async def test_stale_fill_cannot_overwrite_a_disconnect_tombstone(monkeypatch): table.find_many = AsyncMock(side_effect=_read_while_disconnecting) prisma_client = _prisma(table) - await aget_user_provider_tokens(prisma_client, cache, "user-a", ["copilot-cred"]) - assert await aget_user_provider_tokens(prisma_client, cache, "user-a", ["copilot-cred"]) == {} + await aget_user_provider_credentials(prisma_client, cache, "user-a", ["copilot-cred"]) + assert await aget_user_provider_credentials(prisma_client, cache, "user-a", ["copilot-cred"]) == {} @pytest.mark.asyncio @@ -240,8 +288,8 @@ async def test_redis_read_failure_falls_back_to_the_database(monkeypatch): table.find_many = AsyncMock(return_value=[_row(credential_b64=upc._encode(payload))]) prisma_client = _prisma(table) - assert await aget_user_provider_tokens(prisma_client, cache, "user-a", ["copilot-cred"]) == { - "copilot-cred": "gho_secret" + assert await aget_user_provider_credentials(prisma_client, cache, "user-a", ["copilot-cred"]) == { + "copilot-cred": {"access_token": "gho_secret", "github_host": "github.com"} } @@ -259,8 +307,8 @@ async def test_redis_write_and_delete_failures_do_not_fail_the_request(monkeypat table.find_many = AsyncMock(return_value=[_row(credential_b64=upc._encode(payload))]) prisma_client = _prisma(table) - assert await aget_user_provider_tokens(prisma_client, cache, "user-a", ["copilot-cred"]) == { - "copilot-cred": "gho_secret" + assert await aget_user_provider_credentials(prisma_client, cache, "user-a", ["copilot-cred"]) == { + "copilot-cred": {"access_token": "gho_secret", "github_host": "github.com"} } await invalidate_user_provider_credential_cache(cache, "user-a", "copilot-cred") @@ -279,14 +327,14 @@ async def test_without_redis_no_worker_local_entries_are_kept(): cache_a = DualCache() cache_b = DualCache() - assert await aget_user_provider_tokens(prisma_client, cache_a, "user-a", ["copilot-cred"]) == { - "copilot-cred": "gho_secret" + assert await aget_user_provider_credentials(prisma_client, cache_a, "user-a", ["copilot-cred"]) == { + "copilot-cred": {"access_token": "gho_secret", "github_host": "github.com"} } - assert await aget_user_provider_tokens(prisma_client, cache_b, "user-a", ["copilot-cred"]) == { - "copilot-cred": "gho_secret" + assert await aget_user_provider_credentials(prisma_client, cache_b, "user-a", ["copilot-cred"]) == { + "copilot-cred": {"access_token": "gho_secret", "github_host": "github.com"} } await invalidate_user_provider_credential_cache(cache_b, "user-a", "copilot-cred") - assert await aget_user_provider_tokens(prisma_client, cache_a, "user-a", ["copilot-cred"]) == {} + assert await aget_user_provider_credentials(prisma_client, cache_a, "user-a", ["copilot-cred"]) == {} assert table.find_many.await_count == 3 @@ -306,8 +354,8 @@ async def test_connect_overwrites_a_not_connected_tombstone(monkeypatch): table = MagicMock() table.find_many = AsyncMock(return_value=[]) prisma_client = _prisma(table) - assert await aget_user_provider_tokens(prisma_client, cache, "user-a", ["copilot-cred"]) == { - "copilot-cred": "gho_secret" + assert await aget_user_provider_credentials(prisma_client, cache, "user-a", ["copilot-cred"]) == { + "copilot-cred": {"access_token": "gho_secret", "github_host": "github.com"} } table.find_many.assert_not_awaited() @@ -332,9 +380,9 @@ async def test_stale_not_connected_fill_cannot_overwrite_a_connect_write(monkeyp table.find_many = AsyncMock(side_effect=_read_while_connecting) prisma_client = _prisma(table) - await aget_user_provider_tokens(prisma_client, cache, "user-a", ["copilot-cred"]) - assert await aget_user_provider_tokens(prisma_client, cache, "user-a", ["copilot-cred"]) == { - "copilot-cred": "gho_secret" + await aget_user_provider_credentials(prisma_client, cache, "user-a", ["copilot-cred"]) + assert await aget_user_provider_credentials(prisma_client, cache, "user-a", ["copilot-cred"]) == { + "copilot-cred": {"access_token": "gho_secret", "github_host": "github.com"} } @@ -391,7 +439,7 @@ async def test_reads_hit_the_writer_engine_not_a_stale_replica(): prisma_client.db.litellm_userprovidercredentials = reader_table prisma_client.writer_db.litellm_userprovidercredentials = writer_table - await aget_user_provider_tokens(prisma_client, DualCache(), "user-a", ["copilot-cred"]) + await aget_user_provider_credentials(prisma_client, DualCache(), "user-a", ["copilot-cred"]) writer_table.find_many.assert_awaited_once() reader_table.find_many.assert_not_awaited() diff --git a/tests/unit/proxy/db/db_transaction_queue/test_redis_update_buffer.py b/tests/unit/proxy/db/db_transaction_queue/test_redis_update_buffer.py index 5ecc8784384..f30606ac2f1 100644 --- a/tests/unit/proxy/db/db_transaction_queue/test_redis_update_buffer.py +++ b/tests/unit/proxy/db/db_transaction_queue/test_redis_update_buffer.py @@ -6,10 +6,78 @@ from unittest.mock import AsyncMock, MagicMock, patch import pytest +from litellm.constants import REDIS_DAILY_TAG_SPEND_UPDATE_BUFFER_KEY +from litellm.litellm_core_utils.safe_json_dumps import safe_dumps +from litellm.proxy._types import DailyTagSpendTransaction +from litellm.proxy.db.db_transaction_queue.daily_spend_update_queue import DailySpendUpdateQueue from litellm.proxy.db.db_transaction_queue.redis_update_buffer import RedisUpdateBuffer from litellm.proxy.proxy_server import ProxyStartupEvent +def _daily_tag_spend_update_transactions() -> dict[str, DailyTagSpendTransaction]: + return { + "research_2025-01-15_api-key-123_gpt-4o_openai_/chat/completions": DailyTagSpendTransaction( + tag="research", + request_id="request-123", + date="2025-01-15", + api_key="api-key-123", + model="gpt-4o", + model_group=None, + mcp_namespaced_tool_name=None, + custom_llm_provider="openai", + endpoint="/chat/completions", + prompt_tokens=12, + completion_tokens=7, + cache_read_input_tokens=0, + cache_creation_input_tokens=0, + compression_saved_tokens=0, + compression_savings_spend=0.0, + prompt_caching_savings_spend=0.0, + gateway_injected_caching_savings_spend=0.0, + spend=0.0042, + api_requests=1, + successful_requests=1, + failed_requests=0, + ) + } + + +@pytest.mark.asyncio +async def test_daily_tag_spend_restored_to_in_memory_queue_on_rpush_failure( + redis_update_buffer: RedisUpdateBuffer, mock_redis_cache: AsyncMock +): + mock_redis_cache.async_rpush = AsyncMock(side_effect=ConnectionError("redis went away")) + queue: Final = DailySpendUpdateQueue() + original_transactions: Final = _daily_tag_spend_update_transactions() + await queue.add_update(original_transactions) + + await redis_update_buffer.store_in_memory_daily_tag_spend_updates_in_redis(queue) + + assert await queue.flush_and_get_aggregated_daily_spend_update_transactions() == original_transactions + + +@pytest.mark.asyncio +async def test_daily_tag_spend_restored_after_rpush_failure_is_pushed_once_on_next_tick( + redis_update_buffer: RedisUpdateBuffer, mock_redis_cache: AsyncMock +): + mock_redis_cache.async_rpush = AsyncMock(side_effect=ConnectionError("redis went away")) + queue: Final = DailySpendUpdateQueue() + original_transactions: Final = _daily_tag_spend_update_transactions() + await queue.add_update(original_transactions) + + await redis_update_buffer.store_in_memory_daily_tag_spend_updates_in_redis(queue) + mock_redis_cache.async_rpush = AsyncMock(return_value=1) + + await redis_update_buffer.store_in_memory_daily_tag_spend_updates_in_redis(queue) + + mock_redis_cache.async_rpush.assert_called_once() + redis_key: Final = mock_redis_cache.async_rpush.call_args.kwargs["key"] + values: Final = mock_redis_cache.async_rpush.call_args.kwargs["values"] + assert redis_key == REDIS_DAILY_TAG_SPEND_UPDATE_BUFFER_KEY + assert json.loads(values[0]) == json.loads(safe_dumps(original_transactions)) + assert await queue.flush_and_get_aggregated_daily_spend_update_transactions() == {} + + @pytest.fixture def mock_redis_cache(): """Create a mock RedisCache instance""" diff --git a/tests/unit/proxy/db/test_db_spend_update_writer.py b/tests/unit/proxy/db/test_db_spend_update_writer.py index 1ec65a4fdcd..7437042e4bd 100644 --- a/tests/unit/proxy/db/test_db_spend_update_writer.py +++ b/tests/unit/proxy/db/test_db_spend_update_writer.py @@ -19,7 +19,7 @@ from redis.exceptions import DataError import litellm from litellm._logging import verbose_proxy_logger from litellm._service_logger import ServiceTypes -from litellm.constants import SPEND_ROLLUP_LOCK_TIMEOUT_MS +from litellm.constants import DB_SPEND_UPDATE_JOB_NAME, REDIS_UPDATE_BUFFER_KEY, SPEND_ROLLUP_LOCK_TIMEOUT_MS from litellm.proxy._types import DailyTagSpendTransaction, Litellm_EntityType, SpendUpdateQueueItem from litellm.proxy.db.db_spend_update_writer import ( _TEAM_ADVISORY_LOCK_SQL, @@ -29,12 +29,14 @@ from litellm.proxy.db.db_spend_update_writer import ( _SpendTableName, ) from litellm.proxy.db.db_transaction_queue.daily_spend_update_queue import DailySpendUpdateQueue +from litellm.proxy.db.db_transaction_queue.pod_lock_manager import PodLockManager from litellm.proxy.db.db_transaction_queue.redis_update_buffer import RedisUpdateBuffer from litellm.proxy.db.db_transaction_queue.spend_update_queue import SpendUpdateQueue from litellm.proxy.db.db_transaction_queue.window_spend_update_queue import ( build_window_spend_transaction, ) from litellm.proxy.db.rollup_lock_timeout import ROLLUP_LOCK_TIMEOUT_SQL +from litellm.types.caching import RedisPipelineLpopOperation, RedisPipelineRpushOperation from tests.unit.proxy.db.fake_prisma_engine import engine_call @@ -2365,6 +2367,58 @@ async def test_commit_spend_updates_uses_pipeline(): mock_redis_update_buffer.get_all_daily_tag_spend_update_transactions_from_redis_buffer.assert_not_called() +class _InMemoryRedis: + def __init__(self) -> None: + self.store: dict[str, str] = {} + self.lists: dict[str, list[object]] = {} + + async def async_set_cache(self, key: str, value: str, nx: bool = False, **kwargs: object) -> bool | None: + if nx and key in self.store: + return None + self.store[key] = json.dumps(value) + return True + + async def async_get_cache(self, key: str, **kwargs: object) -> str | None: + raw = self.store.get(key) + return json.loads(raw) if raw is not None else None + + async def async_delete_cache(self, key: str) -> int: + return 1 if self.store.pop(key, None) is not None else 0 + + async def async_rpush_pipeline(self, rpush_list: list[RedisPipelineRpushOperation]) -> list[int]: + for op in rpush_list: + self.lists.setdefault(op["key"], []).extend(op["values"]) + return [len(self.lists[op["key"]]) for op in rpush_list] + + async def async_lpop_pipeline(self, lpop_list: list[RedisPipelineLpopOperation]) -> list[list[object] | None]: + return [self.lists.pop(op["key"], None) for op in lpop_list] + + +@pytest.mark.asyncio +@pytest.mark.parametrize("lock_held_by_another_pod", [False, True]) +async def test_commit_with_redis_writes_discovered_tools_on_leader_and_non_leader(lock_held_by_another_pod: bool): + redis = _InMemoryRedis() + if lock_held_by_another_pod: + assert await PodLockManager(redis_cache=redis).acquire_lock(cronjob_id=DB_SPEND_UPDATE_JOB_NAME) + db_writer = DBSpendUpdateWriter(redis_cache=redis) + db_writer.pod_lock_manager.redis_cache = redis + db_writer.tool_discovery_queue.add_update({"tool_name": "get_weather", "origin": "user_defined"}) + prisma_client = MagicMock() + prisma_client.db.litellm_tooltable.upsert = AsyncMock() + + await db_writer._commit_spend_updates_to_db_with_redis( + prisma_client=prisma_client, + n_retry_times=0, + proxy_logging_obj=MagicMock(), + ) + + upserted = [c.kwargs["where"] for c in prisma_client.db.litellm_tooltable.upsert.await_args_list] + assert upserted == [{"tool_name": "get_weather"}] + assert (REDIS_UPDATE_BUFFER_KEY in redis.lists) is lock_held_by_another_pod, ( + f"spend buffer left in redis={list(redis.lists)}, only the lock holder may drain it" + ) + + @pytest.mark.asyncio async def test_commit_with_redis_requeues_all_on_db_failure(): """ @@ -4130,28 +4184,57 @@ async def test_commit_spend_updates_raises_after_exhausting_lock_timeout_retries assert mock_prisma_client.db.tx.call_count == 3 +def _responses_router() -> litellm.Router: + return litellm.Router( + model_list=[ + { + "model_name": "native", + "litellm_params": {"model": "openai/gpt-5.1", "api_key": "sk-test"}, + "model_info": {"id": "dep-native"}, + }, + { + "model_name": "bridged", + "litellm_params": {"model": "anthropic/claude-sonnet-4-5", "api_key": "sk-test"}, + "model_info": {"id": "dep-bridged"}, + }, + { + "model_name": "forced-bridge", + "litellm_params": {"model": "openai/gpt-5.1", "api_key": "sk-test", "use_chat_completions_api": True}, + "model_info": {"id": "dep-forced-bridge"}, + }, + ] + ) + + @pytest.mark.asyncio @pytest.mark.parametrize( - "call_type, expects_flush", - [("aresponses", True), ("responses", True), ("acompletion", False)], + "call_type, model_id, expects_flush", + [ + ("aresponses", "dep-bridged", True), + ("responses", "dep-bridged", True), + ("aresponses", "dep-forced-bridge", True), + ("aresponses", None, True), + ("aresponses", "dep-native", False), + ("responses", "dep-native", False), + ("acompletion", "dep-bridged", False), + ], ) -async def test_insert_spend_log_asks_for_an_immediate_flush_on_rows_other_workers_read_back( - call_type: str, expects_flush: bool +async def test_insert_spend_log_asks_for_an_immediate_flush_only_on_rows_the_bridge_reads_back( + call_type: str, model_id: str | None, expects_flush: bool ): """ - A `previous_response_id` chained straight off the previous turn reads the DB, so a - Responses row cannot sit in this worker's queue until the monitor's next poll. + A `previous_response_id` chained straight off a bridged turn reads that turn's row from the + DB, so it cannot sit in this worker's queue until the monitor's next poll. A native Responses + provider holds the conversation itself, so its row waits for the batch write like a chat row. """ db_writer = DBSpendUpdateWriter() prisma = _tool_usage_prisma() prisma.spend_log_flush_requested = asyncio.Event() + payload = {"request_id": "req-1", "call_type": call_type, "model_id": model_id} - await db_writer._insert_spend_log_to_db( - payload={"request_id": "req-1", "call_type": call_type}, - prisma_client=prisma, - ) + await db_writer._insert_spend_log_to_db(payload=payload, prisma_client=prisma, llm_router=_responses_router()) - assert prisma.spend_log_transactions == [{"request_id": "req-1", "call_type": call_type}] + assert prisma.spend_log_transactions == [payload] assert prisma.spend_log_flush_requested.is_set() is expects_flush diff --git a/tests/unit/proxy/db/test_health_check_latest.py b/tests/unit/proxy/db/test_health_check_latest.py index 29063d7b060..2f27be4fe61 100644 --- a/tests/unit/proxy/db/test_health_check_latest.py +++ b/tests/unit/proxy/db/test_health_check_latest.py @@ -7,8 +7,10 @@ import pytest from litellm.proxy.db.health_check_latest import ( LATEST_HEALTH_CHECKS_FOR_MODELS_SQL, LATEST_HEALTH_CHECKS_SQL, + LatestHealthCheckRow, fetch_latest_health_checks, fetch_latest_health_checks_for_models, + latest_by_model_name, query_latest_health_checks, ) from tests.unit.proxy.db.fake_prisma_engine import engine_call @@ -129,3 +131,36 @@ async def test_the_latest_health_check_read_renders_a_postgres_select_span( ) -> None: assert await fetch_latest_health_checks(_prisma([])) == () assert await postgres_span_names() == ("postgres.select LiteLLM_HealthCheckTable",) + + +def _latest_row(**overrides) -> LatestHealthCheckRow: + return LatestHealthCheckRow.model_validate(_raw_row(**overrides)) + + +@pytest.mark.parametrize("reverse", [False, True], ids=["sql-order", "reversed"]) +def test_latest_by_model_name_keeps_each_groups_newest_row_whatever_its_model_id(reverse): + """model_id ASC puts a name probe's NULL row, or a deleted deployment's larger id, after the fresh rows.""" + fresh = _latest_row(health_check_id="hc-a", model_id="deployment-a", checked_at="2026-10-16T11:10:00+00:00") + deleted = _latest_row( + health_check_id="hc-z", model_id="deployment-z", status="unhealthy", checked_at="2026-09-04T11:00:00+00:00" + ) + name_probe = _latest_row( + health_check_id="hc-null", model_id=None, status="unhealthy", checked_at="2026-09-04T11:20:04+00:00" + ) + other_group = _latest_row(health_check_id="hc-c", model_name="claude", model_id="deployment-c") + rows = (other_group, fresh, deleted, name_probe) + + latest = latest_by_model_name(rows[::-1] if reverse else rows) + + assert latest == {"gpt-4": fresh, "claude": other_group} + + +def test_latest_by_model_name_lets_a_newer_name_probe_speak_for_the_group(): + per_deployment = _latest_row( + health_check_id="hc-a", model_id="deployment-a", checked_at="2026-10-16T11:10:00+00:00" + ) + name_probe = _latest_row( + health_check_id="hc-null", model_id=None, status="unhealthy", checked_at="2026-10-16T12:00:00+00:00" + ) + + assert latest_by_model_name((per_deployment, name_probe))["gpt-4"] is name_probe diff --git a/tests/unit/proxy/decisions_endpoints/test_endpoints.py b/tests/unit/proxy/decisions_endpoints/test_endpoints.py index fcf56eaea9a..021eb289ad7 100644 --- a/tests/unit/proxy/decisions_endpoints/test_endpoints.py +++ b/tests/unit/proxy/decisions_endpoints/test_endpoints.py @@ -8,7 +8,7 @@ import sys from collections.abc import AsyncGenerator, Callable, Iterator, Mapping from contextlib import asynccontextmanager from pathlib import Path -from typing import Final +from typing import Final, Literal import pytest import respx @@ -19,6 +19,8 @@ from pydantic import TypeAdapter from starlette.routing import Match import litellm +from litellm.integrations.custom_guardrail import CustomGuardrail +from litellm.integrations.custom_logger import CustomLogger from litellm.litellm_core_utils.decisions_pricing import apply_decisions_pricing from litellm.proxy._lazy_features import LAZY_FEATURES, LazyFeature, attach_lazy_features from litellm.proxy._types import UserAPIKeyAuth @@ -32,6 +34,9 @@ from litellm.proxy.proxy_server import ( initialize, ) from litellm.types.decisions import DecisionsRequestBody, OpenAIDecisionRequestBody +from litellm.types.extraction import ExtractionRequestBody +from litellm.types.guardrails import GuardrailEventHooks +from litellm.types.utils import GenericGuardrailAPIInputs from tests._master_key import MASTER_KEY if sys.version_info >= (3, 14): @@ -1296,6 +1301,328 @@ def test_the_two_decisions_routes_document_different_request_formats(decisions_o assert "input" in properties("/v1/decisions") and "input" not in properties("/v1/systemone") +_CLAIRIC_UPSTREAM: Final = "https://api.cloudflare.com/client/v4/accounts/acct/ai/run/@cf/cloudflare/clairic" +_CLAIRIC_INPUT_TOKENS: Final = 416 +_CLAIRIC_RESULT: Final[Mapping[str, object]] = { + "model": "clairic", + "answers": { + "vendor": {"type": "text", "p_null": 0.0177, "span": [19, 29], "confidence": 0.9998, "value": "Acme Tools"}, + "days_to_pay": {"type": "estimate", "value": 31, "mean": 30.76, "median": 30, "p10": 29, "p90": 34}, + }, + "truncated": False, + "usage": {"input_tokens": _CLAIRIC_INPUT_TOKENS, "output_tokens": 0, "schema_tokens": 312, "passes": 2}, +} +_EXTRACTION_REQUEST: Final[Mapping[str, object]] = { + "model": "invoice-reader", + "state": "Invoice #4471 from Acme Tools. Payment due in 30 days.", + "fields": { + "vendor": {"type": "text", "instructions": "Who sent the invoice?"}, + "days_to_pay": {"type": "estimate", "min": 0, "max": 90}, + }, + "images": ["data:image/png;base64,AA=="], +} + + +def _route_invoice_reader_to_clairic( + monkeypatch: pytest.MonkeyPatch, drop_params: bool = False, additional_drop_params: tuple[str, ...] = () +) -> None: + monkeypatch.setattr( + litellm.proxy.proxy_server, + "llm_router", + litellm.Router( + model_list=[ + { + "model_name": "invoice-reader", + "litellm_params": { + "model": "cloudflare/clairic", + "api_key": "cloudflare-key", + "api_base": "https://api.cloudflare.com/client/v4/accounts/acct/ai/run", + "drop_params": drop_params, + **({"additional_drop_params": list(additional_drop_params)} if additional_drop_params else {}), + }, + } + ] + ), + ) + + +@pytest.mark.parametrize("endpoint", ("/v1/extraction", "/extraction")) +def test_proxy_extraction_forwards_the_body_to_clairic_and_returns_its_answers_and_cost( + client: TestClient, + monkeypatch: pytest.MonkeyPatch, + respx_mock: respx.MockRouter, + endpoint: str, +) -> None: + _route_invoice_reader_to_clairic(monkeypatch) + upstream: Final = respx_mock.post(_CLAIRIC_UPSTREAM).respond( + json={"result": _CLAIRIC_RESULT, "success": True, "errors": [], "messages": []} + ) + + response: Final = client.post(endpoint, json=_EXTRACTION_REQUEST) + + assert response.status_code == 200, response.text + assert response.json() == {**_CLAIRIC_RESULT, "model": "invoice-reader"} + expected_cost: Final = _CLAIRIC_INPUT_TOKENS * float( + litellm.model_cost["cloudflare/clairic"]["input_cost_per_token"] + ) + assert expected_cost > 0 + assert float(response.headers["x-litellm-response-cost"]) == pytest.approx(expected_cost) + assert json.loads(upstream.calls[0].request.content) == {**_EXTRACTION_REQUEST, "model": "clairic"} + assert upstream.calls[0].request.headers["authorization"] == "Bearer cloudflare-key" + + +@pytest.mark.parametrize( + "request_body", + ( + {"model": "invoice-reader", "state": "Invoice #4471"}, + {"model": "invoice-reader", "state": "Invoice #4471", "fields": {"total": {"type": "money"}}}, + {**_EXTRACTION_REQUEST, "images": ["https://example.com/invoice.png"]}, + ), + ids=("missing_fields", "unknown_field_type", "remote_image"), +) +def test_proxy_extraction_refuses_a_malformed_body_before_calling_clairic( + client: TestClient, + monkeypatch: pytest.MonkeyPatch, + respx_mock: respx.MockRouter, + request_body: Mapping[str, object], +) -> None: + _route_invoice_reader_to_clairic(monkeypatch) + upstream: Final = respx_mock.post(_CLAIRIC_UPSTREAM).respond(json=_CLAIRIC_RESULT) + + response: Final = client.post("/v1/extraction", json=request_body) + + assert response.status_code == 400, response.text + assert "Invalid Extraction request" in response.text + assert not upstream.called + + +@pytest.mark.parametrize( + ("key", "value"), + ( + ("language", "en"), + ("priority", 1), + ("extra_body", {"language": "en"}), + ("temperature", 0.5), + ("user", "end-user-1"), + ), +) +def test_proxy_extraction_refuses_a_key_clairic_does_not_take_before_calling_clairic( + client: TestClient, monkeypatch: pytest.MonkeyPatch, respx_mock: respx.MockRouter, key: str, value: object +) -> None: + monkeypatch.setattr(litellm, "drop_params", False) + _route_invoice_reader_to_clairic(monkeypatch) + upstream: Final = respx_mock.post(_CLAIRIC_UPSTREAM).respond(json={"result": _CLAIRIC_RESULT, "success": True}) + + response: Final = client.post("/v1/extraction", json={**_EXTRACTION_REQUEST, key: value}) + + assert response.status_code == 400, response.text + assert f"does not support parameters: ['{key}']" in response.text + assert not upstream.called + + +@pytest.mark.parametrize( + ("drop_params", "additional_drop_params"), + ((True, ()), (False, ("language", "temperature", "user"))), + ids=("drop_params", "additional_drop_params"), +) +def test_proxy_extraction_sends_only_the_clairic_request_when_the_deployment_drops_other_keys( + client: TestClient, + monkeypatch: pytest.MonkeyPatch, + respx_mock: respx.MockRouter, + drop_params: bool, + additional_drop_params: tuple[str, ...], +) -> None: + monkeypatch.setattr(litellm, "drop_params", False) + _route_invoice_reader_to_clairic(monkeypatch, drop_params, additional_drop_params) + upstream: Final = respx_mock.post(_CLAIRIC_UPSTREAM).respond(json={"result": _CLAIRIC_RESULT, "success": True}) + + response: Final = client.post( + "/v1/extraction", json={**_EXTRACTION_REQUEST, "language": "en", "temperature": 0.2, "user": "end-user-1"} + ) + + assert response.status_code == 200, response.text + assert json.loads(upstream.calls[0].request.content) == {**_EXTRACTION_REQUEST, "model": "clairic"} + + +def test_proxy_extraction_leaves_out_the_cli_generation_defaults( + client: TestClient, monkeypatch: pytest.MonkeyPatch, respx_mock: respx.MockRouter +) -> None: + monkeypatch.setattr(litellm, "drop_params", False) + monkeypatch.setattr(litellm.proxy.proxy_server, "user_max_tokens", 256) + monkeypatch.setattr(litellm.proxy.proxy_server, "user_temperature", 0.2) + _route_invoice_reader_to_clairic(monkeypatch) + upstream: Final = respx_mock.post(_CLAIRIC_UPSTREAM).respond(json={"result": _CLAIRIC_RESULT, "success": True}) + + response: Final = client.post("/v1/extraction", json=_EXTRACTION_REQUEST) + + assert response.status_code == 200, response.text + assert json.loads(upstream.calls[0].request.content) == {**_EXTRACTION_REQUEST, "model": "clairic"} + + +class _PreCallRecorder(CustomLogger): + def __init__(self) -> None: + super().__init__() + self.calls = 0 + + async def async_pre_call_hook( + self, user_api_key_dict: UserAPIKeyAuth, cache: object, data: dict, call_type: str + ) -> dict: + self.calls += 1 + return data + + +def test_proxy_extraction_refuses_a_remote_image_before_any_pre_call_hook_runs( + client: TestClient, monkeypatch: pytest.MonkeyPatch, respx_mock: respx.MockRouter +) -> None: + recorder: Final = _PreCallRecorder() + monkeypatch.setattr(litellm, "callbacks", [recorder]) + _route_invoice_reader_to_clairic(monkeypatch) + upstream: Final = respx_mock.post(_CLAIRIC_UPSTREAM).respond(json={"result": _CLAIRIC_RESULT, "success": True}) + + response: Final = client.post( + "/v1/extraction", json={**_EXTRACTION_REQUEST, "images": ["https://example.com/invoice.png"]} + ) + + assert response.status_code == 400, response.text + assert recorder.calls == 0 + assert not upstream.called + + +def test_proxy_extraction_refuses_stream_before_calling_clairic_unless_the_deployment_drops_params( + client: TestClient, monkeypatch: pytest.MonkeyPatch, respx_mock: respx.MockRouter +) -> None: + monkeypatch.setattr(litellm, "drop_params", False) + _route_invoice_reader_to_clairic(monkeypatch) + upstream: Final = respx_mock.post(_CLAIRIC_UPSTREAM).respond(json={"result": _CLAIRIC_RESULT, "success": True}) + + response: Final = client.post("/v1/extraction", json={**_EXTRACTION_REQUEST, "stream": True}) + + assert response.status_code == 400, response.text + assert "does not support parameters: ['stream']" in response.text + assert not upstream.called + + +def test_proxy_extraction_answers_a_dropped_stream_with_one_json_body( + client: TestClient, monkeypatch: pytest.MonkeyPatch, respx_mock: respx.MockRouter +) -> None: + _route_invoice_reader_to_clairic(monkeypatch, drop_params=True) + upstream: Final = respx_mock.post(_CLAIRIC_UPSTREAM).respond(json={"result": _CLAIRIC_RESULT, "success": True}) + + response: Final = client.post("/v1/extraction", json={**_EXTRACTION_REQUEST, "stream": True}) + + assert response.status_code == 200, response.text + assert response.headers["content-type"].startswith("application/json") + assert response.json() == {**_CLAIRIC_RESULT, "model": "invoice-reader"} + assert json.loads(upstream.calls[0].request.content) == {**_EXTRACTION_REQUEST, "model": "clairic"} + + +class _RequestEmailMasker(CustomGuardrail): + def __init__(self, email: str) -> None: + super().__init__(guardrail_name="mask-email", event_hook=GuardrailEventHooks.pre_call, default_on=True) + self.email = email + + async def apply_guardrail( + self, + inputs: GenericGuardrailAPIInputs, + request_data: dict, + input_type: Literal["request", "response"], + logging_obj: object = None, + ) -> GenericGuardrailAPIInputs: + return GenericGuardrailAPIInputs( + texts=[text.replace(self.email, "[EMAIL]") for text in inputs.get("texts", [])] + ) + + +_EMAIL_STATE: Final = "Questions go to billing@acme.example today. The vendor is Acme Tools." +_MASKED_EMAIL_STATE: Final = "Questions go to [EMAIL] today. The vendor is Acme Tools." +_VENDOR_IN_MASKED_STATE: Final = { + "type": "text", + "value": "Acme Tools", + "span": [_MASKED_EMAIL_STATE.index("Acme Tools"), _MASKED_EMAIL_STATE.index("Acme Tools") + len("Acme Tools")], +} + + +def _clairic_vendor_result(state_text: str | None = None) -> Mapping[str, object]: + return { + "model": "clairic", + "answers": {"vendor": _VENDOR_IN_MASKED_STATE}, + "truncated": False, + "usage": {"input_tokens": 52, "output_tokens": 0}, + **({"state_text": state_text} if state_text is not None else {}), + } + + +@pytest.mark.parametrize( + ("guardrail_email", "sent_state", "returned_vendor"), + ( + ("billing@acme.example", _MASKED_EMAIL_STATE, {"type": "text", "value": "Acme Tools"}), + ("nobody@example.com", _EMAIL_STATE, _VENDOR_IN_MASKED_STATE), + ), + ids=("state_masked", "state_untouched"), +) +def test_proxy_extraction_drops_spans_into_a_state_only_its_request_guardrail_saw( + client: TestClient, + monkeypatch: pytest.MonkeyPatch, + respx_mock: respx.MockRouter, + guardrail_email: str, + sent_state: str, + returned_vendor: Mapping[str, object], +) -> None: + monkeypatch.setattr(litellm, "callbacks", [_RequestEmailMasker(guardrail_email)]) + _route_invoice_reader_to_clairic(monkeypatch) + upstream: Final = respx_mock.post(_CLAIRIC_UPSTREAM).respond( + json={"result": _clairic_vendor_result(), "success": True} + ) + + response: Final = client.post( + "/v1/extraction", + json={"model": "invoice-reader", "state": _EMAIL_STATE, "fields": {"vendor": {"type": "text"}}}, + ) + + assert response.status_code == 200, response.text + assert json.loads(upstream.calls[0].request.content)["state"] == sent_state + assert response.json()["answers"] == {"vendor": returned_vendor} + + +def test_proxy_extraction_keeps_spans_into_the_masked_state_it_returns( + client: TestClient, monkeypatch: pytest.MonkeyPatch, respx_mock: respx.MockRouter +) -> None: + monkeypatch.setattr(litellm, "callbacks", [_RequestEmailMasker("billing@acme.example")]) + _route_invoice_reader_to_clairic(monkeypatch) + respx_mock.post(_CLAIRIC_UPSTREAM).respond( + json={"result": _clairic_vendor_result(state_text=_MASKED_EMAIL_STATE), "success": True} + ) + + response: Final = client.post( + "/v1/extraction", + json={ + "model": "invoice-reader", + "state": _EMAIL_STATE, + "fields": {"vendor": {"type": "text"}}, + "options": {"return_state_text": True}, + }, + ) + + assert response.status_code == 200, response.text + body: Final = response.json() + assert body["answers"] == {"vendor": _VENDOR_IN_MASKED_STATE} + assert body["state_text"][slice(*body["answers"]["vendor"]["span"])] == "Acme Tools" + + +@pytest.mark.parametrize("path", ("/v1/extraction", "/extraction")) +def test_swagger_documents_the_extraction_request_and_response(decisions_openapi: dict[str, object], path: str) -> None: + operation = decisions_openapi["paths"][path]["post"] + media = operation["requestBody"]["content"]["application/json"] + + assert {"model", "fields"} <= set(media["schema"]["required"]) + assert "$ref" not in json.dumps(media["schema"]) + example = {key: value for key, value in media["example"].items() if key != "model"} + assert len(TypeAdapter(ExtractionRequestBody).validate_python(example).fields) == 5 + response_ref = operation["responses"]["200"]["content"]["application/json"]["schema"]["$ref"] + assert response_ref == "#/components/schemas/ExtractionResponse" + assert {"answers", "usage"} <= set(decisions_openapi["components"]["schemas"]["ExtractionResponse"]["properties"]) + + def test_proxy_systemone_reads_a_zstd_compressed_request_body( client: TestClient, respx_mock: respx.MockRouter, diff --git a/tests/unit/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py b/tests/unit/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py index 3b33ba75eb3..69b3e113b8f 100644 --- a/tests/unit/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py +++ b/tests/unit/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py @@ -35,6 +35,7 @@ from litellm.types.proxy.guardrails.guardrail_hooks.bedrock_guardrails import ( ) from litellm.types.utils import CallTypes, ModelResponse from tests.unit.llms.bedrock.event_loop_probe import EventLoopProbe +from tests.unit.llms.bedrock.event_loop_probe import host_in_loop_probing_vault @pytest.fixture @@ -8063,3 +8064,44 @@ async def test_during_call_masking_rewrites_only_pii_block_in_content_list( ] assert messages[1]["content"] == "Hello, how can I help you today?" assert messages[2]["content"] == "who is the president of the united states?" + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("guardrail_config", "upstream_answer"), + [ + pytest.param( + {"guardrailIdentifier": "wf0hkdb5x07f", "guardrailVersion": "DRAFT"}, + {"action": "NONE", "outputs": [], "assessments": []}, + id="apply_guardrail", + ), + pytest.param( + {"checks": {"contentFilter": {"categories": [{"category": "VIOLENCE"}]}}, "content_filter_threshold": 0.5}, + {"results": {"contentFilter": {"results": [{"category": "VIOLENCE", "severityScore": 0.1}]}}}, + id="invoke_guardrail_checks", + ), + ], +) +async def test_guardrail_secret_lookups_leave_the_event_loop_free( + guardrail_config: dict[str, object], + upstream_answer: dict[str, object], + respx_mock: respx.MockRouter, + httpx_transport: None, + aws_test_credentials: None, + monkeypatch: pytest.MonkeyPatch, +) -> None: + monkeypatch.delenv("AWS_BEARER_TOKEN_BEDROCK", raising=False) + monkeypatch.setenv("AWS_REGION_NAME", "us-west-2") + vault: Final = host_in_loop_probing_vault(monkeypatch, "AWS_BEARER_TOKEN_BEDROCK", "AWS_REGION_NAME") + guardrail: Final = BedrockGuardrail(**guardrail_config) + upstream: Final = respx_mock.route().mock(return_value=httpx.Response(200, json=upstream_answer)) + + _ = await guardrail.make_bedrock_api_request( + source="INPUT", + messages=[{"role": "user", "content": "hello"}], + request_data={"messages": []}, + ) + + assert vault.read.is_set() + assert not vault.read_on_loop.is_set() + assert upstream.calls.last.request.url.host == "bedrock-runtime.us-west-2.amazonaws.com" diff --git a/tests/unit/proxy/guardrails/test_deferred_guardrail_logging.py b/tests/unit/proxy/guardrails/test_deferred_guardrail_logging.py index 17427e839b9..7e5d0f6342e 100644 --- a/tests/unit/proxy/guardrails/test_deferred_guardrail_logging.py +++ b/tests/unit/proxy/guardrails/test_deferred_guardrail_logging.py @@ -16,7 +16,7 @@ Streaming: CSW.__anext__ stores args on logging_obj at stream end. import asyncio import logging -from collections.abc import Callable, Mapping +from collections.abc import Callable, Coroutine, Mapping from datetime import datetime from typing import Any, Final, cast from unittest.mock import AsyncMock, MagicMock, patch @@ -1442,10 +1442,10 @@ class TestResponsesIteratorDeferredLogging: logging_obj._on_deferred_stream_complete = MagicMock() iterator = self._iterator(logging_obj) - with patch("asyncio.create_task") as mock_create_task: + with patch("litellm.responses.streaming_iterator.spawn_logging_task") as mock_spawn_logging_task: iterator._log_completed_response(is_async=True) - mock_create_task.assert_not_called() + mock_spawn_logging_task.assert_not_called() args = logging_obj._deferred_stream_complete_args assert isinstance(args, tuple) and len(args) == 1 assert "dispatched" not in recorded @@ -1458,15 +1458,25 @@ class TestResponsesIteratorDeferredLogging: logging_obj._on_deferred_stream_complete = None iterator = self._iterator(logging_obj) - created = [] - real_create_task = asyncio.create_task + from litellm.responses import streaming_iterator - def tracking_create_task(coro): - task = real_create_task(coro) + created: Final[list[asyncio.Task[object]]] = [] + real_spawn_logging_task: Final = streaming_iterator.spawn_logging_task + + def tracking_spawn_logging_task( + running_loop: asyncio.AbstractEventLoop, + coroutine: Coroutine[object, object, object], + *, + task_name: str, + ) -> asyncio.Task[object]: + task: Final = real_spawn_logging_task(running_loop, coroutine, task_name=task_name) created.append(task) return task - with patch("asyncio.create_task", side_effect=tracking_create_task): + with patch( + "litellm.responses.streaming_iterator.spawn_logging_task", + side_effect=tracking_spawn_logging_task, + ): iterator._log_completed_response(is_async=True) assert len(created) == 1 diff --git a/tests/unit/proxy/health_endpoints/test_health_endpoints.py b/tests/unit/proxy/health_endpoints/test_health_endpoints.py index d5288a7fc12..950d1742d49 100644 --- a/tests/unit/proxy/health_endpoints/test_health_endpoints.py +++ b/tests/unit/proxy/health_endpoints/test_health_endpoints.py @@ -5297,9 +5297,49 @@ def test_test_model_connection_accepts_image_edit_mode(monkeypatch): assert response.json()["status"] == "success" -@pytest.mark.parametrize("mode", ("decisions", "evaluation"), ids=("decisions", "legacy-evaluation")) -def test_test_model_connection_accepts_decision_modes( - monkeypatch, mode: Literal["evaluation", "decisions"] +_TYPESAFE_TEST_CONNECTION: Final = ( + {"model": "typesafe/jev-latest", "api_key": "sk-test"}, + "https://api.typesafe.ai/v1/systemone", + { + "model": "jev-latest", + "answers": {"reachable": {"type": "noul", "noul": 1.0}}, + "usage": {"input_tokens": 12, "output_tokens": 1}, + }, +) +_CLAIRIC_TEST_CONNECTION: Final = ( + { + "model": "cloudflare/clairic", + "api_key": "sk-test", + "api_base": "https://api.cloudflare.com/client/v4/accounts/acct/ai/run", + }, + "https://api.cloudflare.com/client/v4/accounts/acct/ai/run/@cf/cloudflare/clairic", + { + "result": { + "model": "clairic", + "answers": {"status": {"type": "text", "value": "ok"}}, + "truncated": False, + "usage": {"input_tokens": 9, "output_tokens": 0}, + }, + "success": True, + }, +) + + +@pytest.mark.parametrize( + ("mode", "litellm_params", "upstream_url", "upstream_json"), + ( + ("decisions", *_TYPESAFE_TEST_CONNECTION), + ("evaluation", *_TYPESAFE_TEST_CONNECTION), + ("extraction", *_CLAIRIC_TEST_CONNECTION), + ), + ids=("decisions", "legacy-evaluation", "extraction"), +) +def test_test_model_connection_accepts_decision_and_extraction_modes( + monkeypatch, + mode: Literal["evaluation", "decisions", "extraction"], + litellm_params: Mapping[str, str], + upstream_url: str, + upstream_json: Mapping[str, object], ): monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) litellm.in_memory_llm_clients_cache.flush_cache() @@ -5315,20 +5355,8 @@ def test_test_model_connection_accepts_decision_modes( ), respx.mock(assert_all_called=True) as respx_mock, ): - upstream = respx_mock.post("https://api.typesafe.ai/v1/systemone").respond( - json={ - "model": "jev-latest", - "answers": {"reachable": {"type": "noul", "noul": 1.0}}, - "usage": {"input_tokens": 12, "output_tokens": 1}, - } - ) - response = client.post( - "/health/test_connection", - json={ - "mode": mode, - "litellm_params": {"model": "typesafe/jev-latest", "api_key": "sk-test"}, - }, - ) + upstream = respx_mock.post(upstream_url).respond(json=upstream_json) + response = client.post("/health/test_connection", json={"mode": mode, "litellm_params": litellm_params}) assert response.status_code == 200, response.text assert response.json()["status"] == "success" diff --git a/tests/unit/proxy/hooks/test_parallel_request_limiter_v3.py b/tests/unit/proxy/hooks/test_parallel_request_limiter_v3.py index 7af747fc26d..8a74f2d50b4 100644 --- a/tests/unit/proxy/hooks/test_parallel_request_limiter_v3.py +++ b/tests/unit/proxy/hooks/test_parallel_request_limiter_v3.py @@ -48,6 +48,7 @@ from litellm.proxy.spend_tracking.ptu_feature_flag import PTU_COST_ATTRIBUTION_E from litellm.proxy.utils import InternalUsageCache, ProxyLogging, hash_token from litellm.router_utils.ptu_shares import PTUTeamCeiling from litellm.types.caching import RedisPipelineIncrementOperation +from litellm.types.extraction import ExtractionResponse from litellm.types.llms.openai import ResponsesAPIResponse from litellm.types.mcp import MCPPreCallRequestObject, MCPTransport from litellm.types.mcp_server.mcp_server_manager import MCPServer @@ -8686,3 +8687,78 @@ async def test_a2a_url_target_owns_invocation_fee_and_request_limit( await _rpm_request(limiter, cache, auth, "a2a/cheap") assert denied.value.status_code == 429 assert "expensive" in str(denied.value.detail) + + +def _extraction_request(state: str, call_id: str) -> dict[str, object]: + return { + "model": "invoice-reader", + "state": state, + "fields": {"vendor": {"type": "text", "instructions": "Who sent the invoice"}}, + "litellm_call_id": call_id, + } + + +@pytest.mark.asyncio +async def test_an_extraction_request_passes_a_tpm_limited_key_without_an_injected_output_cap(): + cache: Final = DualCache() + handler: Final = _PROXY_MaxParallelRequestsHandler(internal_usage_cache=InternalUsageCache(cache)) + key: Final = UserAPIKeyAuth(api_key=hash_token("sk-extraction-cap"), tpm_limit=2000) + data: Final = _extraction_request("Invoice from Acme Tools", "extraction-cap") + sent: Final = dict(data) + + await handler.async_pre_call_hook(user_api_key_dict=key, cache=cache, data=data, call_type="aextraction") + + assert data == sent + + +@pytest.mark.asyncio +async def test_an_extraction_request_reserves_its_state_and_no_output_budget(monkeypatch): + monkeypatch.delenv("LITELLM_TPM_TOKEN_RESERVATION_ENABLED", raising=False) + cache: Final = DualCache() + handler: Final = _PROXY_MaxParallelRequestsHandler(internal_usage_cache=InternalUsageCache(cache)) + key: Final = UserAPIKeyAuth(api_key=hash_token("sk-extraction-estimate"), tpm_limit=1_000_000) + state_tokens: Final = 500 + + reserved: Final = await _reserved_tokens_for( + handler, cache, key, _extraction_request("word" * state_tokens, "extraction-estimate"), call_type="aextraction" + ) + + assert state_tokens <= reserved < 2 * state_tokens + + +@pytest.mark.asyncio +async def test_a_successful_extraction_counts_its_input_tokens_toward_the_key_tpm_limit(monkeypatch): + monkeypatch.setattr(_PROXY_MaxParallelRequestsHandler, "get_rate_limit_type", lambda self: "total") + cache: Final = DualCache() + handler: Final = _PROXY_MaxParallelRequestsHandler(internal_usage_cache=InternalUsageCache(cache)) + api_key: Final = hash_token("sk-extraction-usage") + key: Final = UserAPIKeyAuth(api_key=api_key, tpm_limit=500) + await handler.async_pre_call_hook( + user_api_key_dict=key, cache=cache, data=_extraction_request("Invoice", "extraction-1"), call_type="aextraction" + ) + + await handler.async_log_success_event( + kwargs={ + "litellm_call_id": "extraction-1", + "standard_logging_object": {"metadata": {"user_api_key_hash": api_key}}, + }, + response_obj=ExtractionResponse.model_validate( + { + "model": "invoice-reader", + "answers": {"vendor": {"type": "text", "value": "Acme Tools"}}, + "truncated": False, + "usage": {"input_tokens": 480, "output_tokens": 0}, + } + ), + start_time=datetime.now(), + end_time=datetime.now(), + ) + + with pytest.raises(HTTPException) as refused: + await handler.async_pre_call_hook( + user_api_key_dict=key, + cache=cache, + data=_extraction_request("Invoice " * 40, "extraction-2"), + call_type="aextraction", + ) + assert refused.value.status_code == 429 diff --git a/tests/unit/proxy/hooks/test_proxy_track_cost_callback.py b/tests/unit/proxy/hooks/test_proxy_track_cost_callback.py index 1f0dd67d86b..bd997f10322 100644 --- a/tests/unit/proxy/hooks/test_proxy_track_cost_callback.py +++ b/tests/unit/proxy/hooks/test_proxy_track_cost_callback.py @@ -16,6 +16,7 @@ from litellm.proxy._types import SpendLogsPayload, UserAPIKeyAuth from litellm.proxy.collector import SpendEventConsumer from litellm.proxy.db.db_lookup_gate import DBLookupDeadlineExceeded from litellm.proxy.db.db_spend_update_writer import DBSpendUpdateWriter +from litellm.proxy.db.model_usage_rollup import build_model_usage_transaction from litellm.proxy.db.spend_log_tool_index import response_tool_call_names from litellm.proxy.hooks.proxy_track_cost_callback import ( _get_budget_reservation_from_metadata, @@ -29,7 +30,8 @@ from litellm.proxy.utils import ProxyUpdateSpend from litellm.proxy.spend_tracking.spend_event import SpendEventDecodeError, build_spend_event, decode_spend_event from litellm.proxy.spend_tracking.spend_event_producer import SpendEventProducer, UnixAddress from litellm.proxy.spend_tracking.spend_tracking_utils import get_logging_payload -from litellm.types.utils import CallTypes, LiteLLMBatch, ModelResponse, Usage +from litellm.types.router import Deployment, LiteLLM_Params +from litellm.types.utils import CallTypes, LiteLLMBatch, ModelResponse, PromptTokensDetailsWrapper, Usage @pytest.mark.asyncio @@ -95,6 +97,186 @@ async def test_async_post_call_failure_hook(): assert metadata["original_key"] == "original_value" +@pytest.mark.asyncio +async def test_each_earlier_billed_attempt_gets_its_own_spend_row(): + """A timed-out request that the router retried writes one row per billed attempt: the final + attempt under the request id, every earlier Timeout attempt under ``-attempt-`` with its + own cost, attempt number and deployment.""" + from litellm.proxy.utils import BilledFailedAttempt + + logger = ProxyDBLogger() + user_api_key_dict = UserAPIKeyAuth(api_key="test_api_key", user_id="u1", team_id="t1") + usage = litellm.Usage(prompt_tokens=24, completion_tokens=0, total_tokens=24) + request_data = { + "model": "gpt-4.1", + "litellm_call_id": "call-1", + "standard_logging_object": {"id": "call-1", "model_id": "dep-final"}, + "metadata": { + "attempted_retries": 2, + "model_info": {"id": "dep-final", "input_cost_per_token": 0.5}, + "previous_models": ({"exception_type": "Timeout"}, {"exception_type": "Timeout"}), + }, + "combined_usage_object": usage, + "response_cost": 0.5, + "billed_failed_attempts": ( + BilledFailedAttempt(attempted_retries=0, deployment_id="dep-a", usage=usage, response_cost=0.25), + BilledFailedAttempt(attempted_retries=0, deployment_id="dep-final", usage=usage, response_cost=0.5), + ), + } + + with patch( + "litellm.proxy.db.db_spend_update_writer.DBSpendUpdateWriter.update_database", + new_callable=AsyncMock, + ) as mock_update_database: + await logger.async_post_call_failure_hook( + request_data=request_data, + original_exception=litellm.Timeout("Request timed out.", model="gpt-4.1", llm_provider="openai"), + user_api_key_dict=user_api_key_dict, + ) + + rows = [call.kwargs for call in mock_update_database.call_args_list] + assert [row["response_cost"] for row in rows] == [0.5, 0.25, 0.5] + final_row, attempt_0, attempt_1 = (row["kwargs"] for row in rows) + assert final_row["litellm_call_id"] == "call-1" + assert final_row["litellm_params"]["metadata"]["attempted_retries"] == 2 + assert attempt_0["litellm_call_id"] == "call-1-attempt-0" + assert attempt_0["standard_logging_object"]["id"] == "call-1-attempt-0" + assert attempt_0["litellm_params"]["metadata"]["attempted_retries"] == 0 + assert attempt_0["litellm_params"]["metadata"]["model_info"]["id"] == "dep-a" + assert "previous_models" not in attempt_0["litellm_params"]["metadata"] + assert "billed_failed_attempts" not in attempt_0 + assert attempt_0["combined_usage_object"] is usage + assert attempt_1["litellm_call_id"] == "call-1-attempt-1" + assert attempt_1["litellm_params"]["metadata"]["attempted_retries"] == 0 + assert attempt_1["litellm_params"]["metadata"]["model_info"]["id"] == "dep-final" + assert final_row["litellm_params"]["metadata"]["model_info"]["id"] == "dep-final" + for row in rows: + assert row["token"] == "test_api_key" + assert row["user_id"] == "u1" + assert row["team_id"] == "t1" + + +def _deployment(model_name: str, model_id: str, model: str, api_base: str | None) -> Deployment: + return Deployment( + model_name=model_name, + litellm_params=LiteLLM_Params(model=model, api_base=api_base), + model_info={"id": model_id}, + ) + + +_TIMED_OUT_AT: Final = datetime(2026, 10, 20, 21, 24, 48, tzinfo=timezone.utc) + + +async def _spend_log_payloads_of_a_retried_timeout_across_a_fallback() -> list[SpendLogsPayload]: + """The spend-log payloads a timed-out request writes when attempt 0 and 1 ran on the anthropic + deployment of group ``essay`` and the request then fell back to the openai deployment of group + ``essay-fallback``: the final row first, then one row per earlier billed attempt.""" + from litellm.proxy.utils import BilledFailedAttempt + + deployments = { + "dep-anthropic": _deployment("essay", "dep-anthropic", "anthropic/claude-sonnet-4-6", None), + "dep-openai": _deployment("essay-fallback", "dep-openai", "openai/gpt-4.1", "https://api.openai.com/v1"), + } + usage = litellm.Usage(prompt_tokens=24, completion_tokens=0, total_tokens=24) + request_data = { + "model": "anthropic/claude-sonnet-4-6", + "custom_llm_provider": "anthropic", + "litellm_call_id": "call-1", + "litellm_params": {"api_base": "https://api.anthropic.com/v1/messages"}, + "standard_logging_object": { + "id": "call-1", + "model": "anthropic/claude-sonnet-4-6", + "custom_llm_provider": "anthropic", + "api_base": "https://api.anthropic.com/v1/messages", + "model_id": "dep-anthropic", + "model_group": "essay", + "metadata": {}, + "hidden_params": {}, + "model_map_information": {}, + }, + "metadata": {"attempted_retries": 1, "model_group": "essay", "model_info": {"id": "dep-anthropic"}}, + "combined_usage_object": usage, + "response_cost": 7.2e-05, + "billed_failed_attempts": ( + BilledFailedAttempt(attempted_retries=1, deployment_id="dep-anthropic", usage=usage, response_cost=7.2e-05), + BilledFailedAttempt(attempted_retries=0, deployment_id="dep-openai", usage=usage, response_cost=4.8e-05), + ), + } + exception = litellm.Timeout("Request timed out.", model="gpt-4.1", llm_provider="openai") + with patch( + "litellm.proxy.db.db_spend_update_writer.DBSpendUpdateWriter.update_database", + new_callable=AsyncMock, + ) as mock_update_database: + await ProxyDBLogger(deployment_lookup=deployments.get).async_post_call_failure_hook( + request_data=request_data, + original_exception=exception, + user_api_key_dict=UserAPIKeyAuth(api_key="test_api_key", user_id="u1"), + ) + return [ + get_logging_payload( + kwargs=call.kwargs["kwargs"], + response_obj=exception, + start_time=_TIMED_OUT_AT, + end_time=_TIMED_OUT_AT + timedelta(seconds=11), + ) + for call in mock_update_database.call_args_list + ] + + +@pytest.mark.asyncio +async def test_attempt_rows_are_attributed_to_the_deployment_that_billed_them(): + """Regression since #47416: an earlier attempt that ran on another deployment was written with the + final row's model, provider and api_base. Each attempt row names the deployment it ran on.""" + final_row, attempt_0, attempt_1 = await _spend_log_payloads_of_a_retried_timeout_across_a_fallback() + + assert (final_row["model"], final_row["custom_llm_provider"], final_row["model_id"]) == ( + "anthropic/claude-sonnet-4-6", + "anthropic", + "dep-anthropic", + ) + assert final_row["api_base"] == "https://api.anthropic.com/v1/messages" + assert (attempt_0["model"], attempt_0["custom_llm_provider"], attempt_0["model_id"], attempt_0["model_group"]) == ( + "anthropic/claude-sonnet-4-6", + "anthropic", + "dep-anthropic", + "essay", + ) + assert (attempt_1["model"], attempt_1["custom_llm_provider"], attempt_1["model_id"], attempt_1["model_group"]) == ( + "openai/gpt-4.1", + "openai", + "dep-openai", + "essay-fallback", + ) + assert attempt_1["api_base"] == "https://api.openai.com/v1" + assert attempt_1["request_id"] == "call-1-attempt-1" + assert attempt_1["spend"] == 4.8e-05 + + +@pytest.mark.asyncio +async def test_attempt_rows_add_spend_but_not_requests_to_daily_spend(): + """Regression since #47416: one caller request with N billed earlier attempts counted N+1 requests in + the daily spend tables. The attempt rows keep their spend, tokens and model usage and count zero requests.""" + payloads = await _spend_log_payloads_of_a_retried_timeout_across_a_fallback() + prisma = MagicMock() + prisma.get_request_status = MagicMock(return_value="failure") + + daily = [ + await DBSpendUpdateWriter()._common_add_spend_log_transaction_to_daily_transaction( + payload=payload, prisma_client=prisma, type="user" + ) + for payload in payloads + ] + + assert all(row is not None for row in daily) + assert [row["api_requests"] for row in daily if row is not None] == [1, 0, 0] + assert [row["failed_requests"] for row in daily if row is not None] == [1, 0, 0] + assert [row["spend"] for row in daily if row is not None] == [7.2e-05, 7.2e-05, 4.8e-05] + assert [row["prompt_tokens"] for row in daily if row is not None] == [24, 24, 24] + model_usage = [build_model_usage_transaction(payload) for payload in payloads] + assert all(usage is not None for usage in model_usage), "attempt spend must still reach daily model usage" + assert [usage.spend for usage in model_usage if usage is not None] == [7.2e-05, 7.2e-05, 4.8e-05] + + @pytest.mark.asyncio async def test_async_post_call_failure_hook_carries_guardrail_info_from_litellm_metadata(): """ @@ -3123,3 +3305,189 @@ async def test_track_cost_callback_enqueue_emits_no_service_span(): # test-qual assert update_database.await_count == 1, "the spend enqueue itself must still run" assert success_hook.await_count == 0, [call.kwargs for call in success_hook.await_args_list] + +class _SharedCounter: + def __init__(self) -> None: + self.totals: dict[str, float] = {} + + async def async_increment(self, key: str, value: float, ttl: int | None = None) -> float: + self.totals[key] = self.totals.get(key, 0) + value + return self.totals[key] + + +def _grounded_gemini_kwargs(response_cost: float) -> dict: + return { + "model": "vertex_ai/gemini-test", + "call_type": "acompletion", + "response_cost": response_cost, + "litellm_params": {"metadata": {"user_api_key": "sk-test", "user_api_key_user_id": "user-1"}}, + "standard_logging_object": { + "response_cost": response_cost, + "request_tags": None, + "cache_hit": None, + "custom_llm_provider": "vertex_ai", + "cost_breakdown": { + "input_cost": 0.0, + "output_cost": 0.0, + "tool_usage_cost": 0.5, + "total_cost": response_cost, + }, + "model_map_information": { + "model_map_key": "vertex_ai/gemini-test", + "model_map_value": { + "litellm_provider": "vertex_ai", + "mode": "chat", + "web_search_billing_unit": "per_query", + "search_context_cost_per_query": {"search_context_size_medium": 0.1}, + "search_free_requests": {"count": 100, "period": "month", "shared_group": "test"}, + }, + }, + }, + "stream": False, + } + + +@pytest.mark.asyncio +@pytest.mark.parametrize("opted_in", [True, False]) +async def test_track_cost_callback_frees_grounding_under_the_allowance_only_when_opted_in(monkeypatch, opted_in): + monkeypatch.setattr(litellm, "apply_search_free_tier", opted_in, raising=False) + counter = _SharedCounter() + kwargs = _grounded_gemini_kwargs(response_cost=1.0) + response = ModelResponse( + usage=Usage( + prompt_tokens=10, + completion_tokens=5, + total_tokens=15, + prompt_tokens_details=PromptTokensDetailsWrapper(web_search_requests=5), + ) + ) + + with ( + patch( # test-quality-ok: increment_spend_counters is a proxy_server global the callback reads lazily, no seam + "litellm.proxy.proxy_server.increment_spend_counters", new_callable=AsyncMock + ), + patch( # test-quality-ok: update_cache is a proxy_server global the callback reads lazily, no seam + "litellm.proxy.proxy_server.update_cache", new_callable=AsyncMock + ), + patch( # test-quality-ok: callback imports proxy_logging_obj off proxy_server in its body, no seam + "litellm.proxy.proxy_server.proxy_logging_obj" + ) as mock_proxy_logging, + ): + mock_proxy_logging.failed_tracking_alert = AsyncMock() + mock_proxy_logging.db_spend_update_writer.update_database = AsyncMock(return_value=True) + mock_proxy_logging.slack_alerting_instance.customer_spend_alert = AsyncMock() + mock_proxy_logging.internal_usage_cache.dual_cache.redis_cache = counter + + await ProxyDBLogger()._PROXY_track_cost_callback( + kwargs=kwargs, completion_response=response, start_time=datetime.now(), end_time=datetime.now() + ) + await asyncio.sleep(0) + + mock_proxy_logging.failed_tracking_alert.assert_not_called() + mock_proxy_logging.db_spend_update_writer.update_database.assert_awaited_once() + + breakdown = kwargs["standard_logging_object"]["cost_breakdown"] + if opted_in: + assert kwargs["response_cost"] == pytest.approx(1.0 - 5 * 0.1) + assert breakdown["original_cost"] == 1.0 and breakdown["discount_amount"] == pytest.approx(5 * 0.1) + assert sum(counter.totals.values()) == 5 + else: + assert kwargs["response_cost"] == 1.0 and "discount_amount" not in breakdown + assert counter.totals == {} + + +@pytest.mark.asyncio +async def test_batch_accounting_failures_stay_with_their_originating_call() -> None: + from litellm.proxy.hooks.proxy_track_cost_callback import track_batch_accounting + + logger: Final = ProxyDBLogger() + dependency: Final = SimpleNamespace(failed_tracking_alert=AsyncMock()) + + async def fail_before_accounting(call_id: str) -> None: + await logger.async_log_success_event( + kwargs={ + "litellm_call_id": call_id, + "call_type": "aretrieve_batch", + "model": "batch-model", + "stream": False, + "response_cost": None, + }, + response_obj=None, + start_time=_CALL_START, + end_time=_CALL_START, + ) + + async def independent_batch() -> bool: + with track_batch_accounting("independent") as outcome: + await fail_before_accounting("independent") + return outcome.retryable_failure + + with patch("litellm.proxy.proxy_server.proxy_logging_obj", dependency): + with track_batch_accounting("outer") as outer: + await fail_before_accounting("unrelated") + assert outer.retryable_failure is False + with track_batch_accounting("inner") as inner: + await fail_before_accounting("inner") + assert inner.retryable_failure is True + assert outer.retryable_failure is False + independent, _ = await asyncio.gather(independent_batch(), fail_before_accounting("outer")) + assert independent is True + assert outer.retryable_failure is True + with pytest.raises(asyncio.CancelledError): + with track_batch_accounting("cancelled") as cancelled: + raise asyncio.CancelledError + await fail_before_accounting("cancelled") + assert cancelled.retryable_failure is False + + +@pytest.mark.asyncio +async def test_batch_accounting_does_not_retry_after_settling_a_budget_reservation() -> None: + from litellm.proxy.hooks.proxy_track_cost_callback import track_batch_accounting + + reservation: Final[dict[str, object]] = {"reserved_cost": 0.5, "entries": ()} + dependency: Final = SimpleNamespace(failed_tracking_alert=AsyncMock()) + with patch("litellm.proxy.proxy_server.proxy_logging_obj", dependency): + with track_batch_accounting("reserved") as outcome: + await ProxyDBLogger().async_log_success_event( + kwargs={ + "litellm_call_id": "reserved", + "call_type": "aretrieve_batch", + "model": "batch-model", + "stream": False, + "response_cost": None, + "litellm_params": {"metadata": {"user_api_key_budget_reservation": reservation}}, + }, + response_obj=None, + start_time=_CALL_START, + end_time=_CALL_START, + ) + assert reservation["finalized"] is True + assert outcome.retryable_failure is False + + +@pytest.mark.asyncio +async def test_batch_accounting_does_not_retry_after_a_search_allowance_update(monkeypatch: pytest.MonkeyPatch) -> None: + from litellm.proxy.hooks.proxy_track_cost_callback import track_batch_accounting + + monkeypatch.setattr(litellm, "apply_search_free_tier", True) + counter: Final = _SharedCounter() + dependency: Final = SimpleNamespace( + failed_tracking_alert=AsyncMock(), + internal_usage_cache=SimpleNamespace(dual_cache=SimpleNamespace(redis_cache=counter)), + ) + kwargs: Final = {**_grounded_gemini_kwargs(response_cost=1.0), "litellm_call_id": "grounded-batch"} + response: Final = ModelResponse( + usage=Usage( + prompt_tokens=10, + completion_tokens=5, + total_tokens=15, + prompt_tokens_details=PromptTokensDetailsWrapper(web_search_requests=5), + ) + ) + with patch("litellm.proxy.proxy_server.proxy_logging_obj", dependency): + with track_batch_accounting("grounded-batch") as outcome: + await ProxyDBLogger().async_log_success_event(kwargs, response, _CALL_START, _CALL_START) + + assert sum(counter.totals.values()) == 5 + assert outcome.failed is True + assert outcome.retryable_failure is False diff --git a/tests/unit/proxy/hooks/test_search_free_tier.py b/tests/unit/proxy/hooks/test_search_free_tier.py new file mode 100644 index 00000000000..b57908378e5 --- /dev/null +++ b/tests/unit/proxy/hooks/test_search_free_tier.py @@ -0,0 +1,210 @@ +from datetime import datetime, timedelta, timezone +from typing import Final + +import pytest + +from litellm.proxy.hooks.search_free_tier import ( + apply_search_free_tier, + freed_units, + search_free_tier_key, + search_free_tier_ttl, +) +from litellm.types.utils import ModelResponse, PromptTokensDetailsWrapper, Usage + +NOW: Final = datetime(2026, 10, 20, 12, 30, tzinfo=timezone.utc) +RATE: Final = 0.01 + + +class _Counter: + def __init__(self) -> None: + self.totals: dict[str, float] = {} + self.ttls: dict[str, int | None] = {} + + async def async_increment(self, key: str, value: float, ttl: int | None = None) -> float: + self.totals[key] = self.totals.get(key, 0) + value + self.ttls[key] = ttl + return self.totals[key] + + +class _BrokenCounter: + async def async_increment(self, key: str, value: float, ttl: int | None = None) -> float: + raise ConnectionError("redis is down") + + +def _model_info(billing_unit: str, count: int, period: str = "month", provider: str = "vertex_ai") -> dict: + return { + "litellm_provider": provider, + "mode": "chat", + "web_search_billing_unit": billing_unit, + "search_context_cost_per_query": {"search_context_size_medium": RATE}, + "search_free_requests": {"count": count, "period": period, "shared_group": "test-group"}, + } + + +def _response(queries: int | None) -> ModelResponse: + details = PromptTokensDetailsWrapper(web_search_requests=queries) if queries is not None else None + return ModelResponse( + usage=Usage(prompt_tokens=10, completion_tokens=5, total_tokens=15, prompt_tokens_details=details) + ) + + +def _call(model_info: dict, response_cost: float, cache_hit: bool | None = None) -> tuple[dict, dict]: + sl_object = { + "response_cost": response_cost, + "cache_hit": cache_hit, + "custom_llm_provider": model_info["litellm_provider"], + "cost_breakdown": {"input_cost": 0.1, "output_cost": 0.2, "tool_usage_cost": 0.5, "total_cost": response_cost}, + "model_map_information": {"model_map_key": "gemini-test", "model_map_value": model_info}, + } + return {"response_cost": response_cost, "standard_logging_object": sl_object}, sl_object + + +@pytest.mark.parametrize( + ("allowance", "units", "total_after", "expected"), + [ + (5000, 5, 5, 5), + (5000, 5, 5000, 5), + (5000, 10, 5005, 5), + (5000, 5, 5010, 0), + (2, 5, 5, 2), + (0, 3, 3, 0), + ], +) +def test_freed_units_covers_only_what_landed_under_the_allowance(allowance, units, total_after, expected): + assert freed_units(allowance, units, total_after) == expected + + +def test_counter_key_is_per_provider_group_and_utc_period(): + assert search_free_tier_key("gemini", {"count": 1, "period": "month", "shared_group": "g3"}, NOW) == ( + "litellm:search_free_tier:gemini:g3:2026-10" + ) + assert search_free_tier_key("vertex_ai", {"count": 1, "period": "day", "shared_group": "g2"}, NOW) == ( + "litellm:search_free_tier:vertex_ai:g2:2026-10-20" + ) + + +@pytest.mark.parametrize( + ("period", "boundary"), + [("month", datetime(2026, 11, 1, tzinfo=timezone.utc)), ("day", datetime(2026, 10, 21, tzinfo=timezone.utc))], +) +def test_counter_ttl_outlives_the_period_boundary_by_under_two_hours(period, boundary): + expiry = NOW + timedelta(seconds=search_free_tier_ttl({"count": 1, "period": period, "shared_group": "g"}, NOW)) + assert boundary < expiry < boundary + timedelta(hours=2) + + +@pytest.mark.asyncio +async def test_per_query_allowance_is_shared_across_calls_and_split_on_the_crossing_call(): + counter = _Counter() + model_info = _model_info("per_query", count=7) + reduced = [] + for _ in range(3): + kwargs, sl_object = _call(model_info, response_cost=1.0) + cost = await apply_search_free_tier(kwargs, sl_object, 1.0, _response(5), counter, NOW) + reduced.append((cost, kwargs["response_cost"], sl_object["response_cost"], sl_object["cost_breakdown"])) + (c1, k1, s1, b1), (c2, k2, s2, b2), (c3, k3, s3, b3) = reduced + assert c1 == k1 == s1 == pytest.approx(1.0 - 5 * RATE) + assert b1["original_cost"] == 1.0 and b1["discount_amount"] == pytest.approx(5 * RATE) + assert b1["total_cost"] == pytest.approx(c1) and b1["tool_usage_cost"] == 0.5 + assert c2 == k2 == s2 == pytest.approx(1.0 - 2 * RATE) + assert b2["discount_amount"] == pytest.approx(2 * RATE) + assert c3 == k3 == s3 == 1.0 and "discount_amount" not in b3 + assert counter.totals == {"litellm:search_free_tier:vertex_ai:test-group:2026-10": 15} + assert counter.ttls["litellm:search_free_tier:vertex_ai:test-group:2026-10"] > 0 + + +@pytest.mark.asyncio +async def test_gemini_api_and_vertex_ai_grounding_draw_on_separate_allowances(): + counter = _Counter() + gemini_api = _model_info("per_query", count=3, provider="gemini") + vertex_ai = _model_info("per_query", count=3, provider="vertex_ai") + kwargs, sl_object = _call(gemini_api, response_cost=1.0) + await apply_search_free_tier(kwargs, sl_object, 1.0, _response(2), counter, NOW) + kwargs, sl_object = _call(vertex_ai, response_cost=1.0) + vertex_cost = await apply_search_free_tier(kwargs, sl_object, 1.0, _response(4), counter, NOW) + kwargs, sl_object = _call(gemini_api, response_cost=1.0) + gemini_cost = await apply_search_free_tier(kwargs, sl_object, 1.0, _response(1), counter, NOW) + assert vertex_cost == pytest.approx(1.0 - 3 * RATE), "vertex ai had its whole allowance left" + assert gemini_cost == pytest.approx(1.0 - RATE), "gemini api had one free query left" + + +@pytest.mark.asyncio +async def test_per_prompt_allowance_counts_a_grounded_prompt_once_whatever_the_query_count(): + counter = _Counter() + model_info = _model_info("per_prompt", count=1, period="day") + kwargs, sl_object = _call(model_info, response_cost=1.0) + first = await apply_search_free_tier(kwargs, sl_object, 1.0, _response(5), counter, NOW) + kwargs, sl_object = _call(model_info, response_cost=1.0) + second = await apply_search_free_tier(kwargs, sl_object, 1.0, _response(5), counter, NOW) + assert first == pytest.approx(1.0 - RATE) + assert second == 1.0 + assert counter.totals == {"litellm:search_free_tier:vertex_ai:test-group:2026-10-20": 2} + + +@pytest.mark.asyncio +async def test_sidecar_shaped_response_mapping_is_counted_like_a_model_response(): + counter = _Counter() + kwargs, sl_object = _call(_model_info("per_query", count=100), response_cost=1.0) + response = { + "usage": { + "prompt_tokens": 1, + "completion_tokens": 1, + "total_tokens": 2, + "prompt_tokens_details": {"web_search_requests": 3}, + } + } + assert await apply_search_free_tier(kwargs, sl_object, 1.0, response, counter, NOW) == pytest.approx(1.0 - 3 * RATE) + + +@pytest.mark.asyncio +@pytest.mark.parametrize("counter", [None, _BrokenCounter()]) +async def test_full_price_when_no_counter_is_available(counter): + kwargs, sl_object = _call(_model_info("per_query", count=100), response_cost=1.0) + assert await apply_search_free_tier(kwargs, sl_object, 1.0, _response(5), counter, NOW) == 1.0 + assert kwargs["response_cost"] == 1.0 and "discount_amount" not in sl_object["cost_breakdown"] + + +@pytest.mark.asyncio +@pytest.mark.parametrize("response", [_response(0), _response(None), ModelResponse()]) +async def test_requests_without_grounding_never_touch_the_counter(response): + counter = _Counter() + kwargs, sl_object = _call(_model_info("per_query", count=100), response_cost=1.0) + assert await apply_search_free_tier(kwargs, sl_object, 1.0, response, counter, NOW) == 1.0 + assert counter.totals == {} + + +@pytest.mark.asyncio +async def test_models_without_an_allowance_never_touch_the_counter(): + counter = _Counter() + model_info = {k: v for k, v in _model_info("per_query", count=100).items() if k != "search_free_requests"} + kwargs, sl_object = _call(model_info, response_cost=1.0) + assert await apply_search_free_tier(kwargs, sl_object, 1.0, _response(5), counter, NOW) == 1.0 + assert counter.totals == {} + + +@pytest.mark.asyncio +async def test_a_second_callback_run_on_the_same_request_counts_it_once(): + counter = _Counter() + kwargs, sl_object = _call(_model_info("per_query", count=100), response_cost=1.0) + first = await apply_search_free_tier(kwargs, sl_object, 1.0, _response(5), counter, NOW) + second = await apply_search_free_tier(kwargs, sl_object, first, _response(5), counter, NOW) + assert first == second == pytest.approx(1.0 - 5 * RATE) + assert counter.totals == {"litellm:search_free_tier:vertex_ai:test-group:2026-10": 5} + + +@pytest.mark.asyncio +async def test_a_cache_hit_with_grounded_usage_is_not_counted_and_stays_at_zero(): + counter = _Counter() + kwargs, sl_object = _call(_model_info("per_query", count=100), response_cost=0.0, cache_hit=True) + assert await apply_search_free_tier(kwargs, sl_object, 0.0, _response(2), counter, NOW) == 0.0 + assert counter.totals == {} + assert "discount_amount" not in sl_object["cost_breakdown"] + + +@pytest.mark.asyncio +async def test_freed_cost_never_exceeds_the_billed_cost(): + counter = _Counter() + billed = 3 * RATE + kwargs, sl_object = _call(_model_info("per_query", count=100), response_cost=billed) + assert await apply_search_free_tier(kwargs, sl_object, billed, _response(5), counter, NOW) == 0.0 + assert sl_object["cost_breakdown"]["discount_amount"] == pytest.approx(billed) + assert counter.totals == {"litellm:search_free_tier:vertex_ai:test-group:2026-10": 5} diff --git a/tests/unit/proxy/management_endpoints/test_tag_management_endpoints.py b/tests/unit/proxy/management_endpoints/test_tag_management_endpoints.py index 1dfababae55..e5d13a381ae 100644 --- a/tests/unit/proxy/management_endpoints/test_tag_management_endpoints.py +++ b/tests/unit/proxy/management_endpoints/test_tag_management_endpoints.py @@ -283,6 +283,66 @@ async def test_new_tag_persists_a_budget(): assert created_tag.budget_id == "budget-1" +@pytest.mark.asyncio +async def test_new_tag_budget_reads_the_row_spend_not_spend_from_before_the_tag_existed(): + """Spend on an unbudgeted request tag must not count against a budget created later. + + The new row starts at the spend it persists, and a restart reloads only that row, so the + counter the budget check reads has to agree with it from the moment the tag is created. + """ + from litellm.proxy.management_endpoints.tag_management_endpoints import new_tag + from litellm.proxy.proxy_server import get_current_spend, increment_spend_counter_cache + + counter_key: Final = "spend:tag:spent-before-budget-tag" + await increment_spend_counter_cache(counter_key=counter_key, increment=5.0) + + created_tag: Final = SimpleNamespace( + tag_name="spent-before-budget-tag", + description=None, + models=[], + created_at=datetime(2024, 1, 1), + updated_at=datetime(2024, 1, 1), + created_by="admin", + ) + + async def create_tag(data, **_): + created_tag.spend = data["spend"] + return created_tag + + mock_db: Final = Mock() + mock_db.litellm_tagtable.find_unique = AsyncMock(return_value=None) + mock_db.litellm_proxymodeltable.find_many = AsyncMock(return_value=[]) + mock_db.litellm_budgettable.create = AsyncMock(return_value=SimpleNamespace(budget_id="budget-1")) + mock_db.litellm_tagtable.create = create_tag + with ( + patch( # test-quality-ok: endpoint resolves the fake database through proxy_server + "litellm.proxy.proxy_server.prisma_client", + SimpleNamespace(db=mock_db, jsonify_object=lambda data: dict(data)), + ), + patch( # test-quality-ok: endpoint reads the audit actor from proxy_server + "litellm.proxy.proxy_server.litellm_proxy_admin_name", "admin" + ), + patch( # test-quality-ok: endpoint requires a router before the budget write + "litellm.proxy.proxy_server.llm_router", object() + ), + patch( # test-quality-ok: auth object cache invalidation is outside this counter contract + "litellm.proxy.management_endpoints.tag_management_endpoints._evict_tag_cache_keys", new=AsyncMock() + ), + ): + await new_tag( + tag=TagNewRequest(name="spent-before-budget-tag", max_budget=25.0), + user_api_key_dict=UserAPIKeyAuth(user_id="admin", user_role=LitellmUserRoles.PROXY_ADMIN), + ) + + budget_check_spend: Final = await get_current_spend( + counter_key=counter_key, + fallback_spend=created_tag.spend, + max_budget=25.0, + fallback_authoritative=True, + ) + assert budget_check_spend == created_tag.spend + + @pytest.mark.asyncio @pytest.mark.parametrize( ("budget_fields", "should_update", "expected_max_budget"), diff --git a/tests/unit/proxy/management_endpoints/test_ui_sso.py b/tests/unit/proxy/management_endpoints/test_ui_sso.py index 873182a5145..479391e54fe 100644 --- a/tests/unit/proxy/management_endpoints/test_ui_sso.py +++ b/tests/unit/proxy/management_endpoints/test_ui_sso.py @@ -33,6 +33,7 @@ from litellm.proxy.management_endpoints.ui_sso import ( insert_sso_user, normalize_email, process_sso_jwt_access_token, + read_return_to_cookie, sso_lookup_user_ids, ) from litellm.types.proxy.management_endpoints.ui_sso import ( @@ -10603,6 +10604,10 @@ class TestPersistReturnToCookieSharedHelper: def _cookie(resp) -> str: return resp.headers.get("set-cookie", "") + @pytest.fixture(autouse=True) + def _master_key(self, monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr("litellm.proxy.proxy_server.master_key", "sk-test-master") + def test_sets_cookie_for_same_origin_relative_path(self, monkeypatch): from fastapi import Response @@ -10648,6 +10653,62 @@ class TestPersistReturnToCookieSharedHelper: _persist_return_to_cookie(resp, "https://cp.example.com/ui?page=models", _make_https_request()) assert "litellm_cp_return_to=" in self._cookie(resp) + def test_cookie_is_opaque_and_round_trips_the_loopback_redirect_uri(self, monkeypatch: pytest.MonkeyPatch) -> None: + """The DCR authorize round-trip for a local coding agent stores a return_to carrying + ``redirect_uri=http://127.0.0.1:/...``. An edge firewall (AWS WAF + ``EC2MetaDataSSRF_COOKIE``) reads that loopback URL in a cookie as an SSRF probe and 403s the + callback, so the cookie must carry nothing a middlebox can pattern-match, while the proxy + itself still reads the exact return_to back.""" + from fastapi import Response + + from litellm.proxy.management_endpoints.ui_sso import _persist_return_to_cookie, read_return_to_cookie + + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {}) + return_to: Final = "/mcp/authorize?client_id=llm_dcrc_abc&redirect_uri=http%3A%2F%2F127.0.0.1%3A1455%2Fauth%2Fcallback" + resp: Final = Response() + _persist_return_to_cookie(resp, return_to, _make_https_request()) + cookie: Final = self._cookie(resp) + value: Final = cookie.split("litellm_cp_return_to=", 1)[1].split(";", 1)[0] + assert "127.0.0.1" not in cookie and "authorize" not in cookie, cookie + request: Final = _make_https_request() + request.cookies = {"litellm_cp_return_to": value} + assert read_return_to_cookie(request) == return_to + + def test_a_cookie_this_proxy_did_not_seal_reads_as_nothing(self) -> None: + from litellm.proxy.management_endpoints.ui_sso import read_return_to_cookie + + request: Final = _make_https_request() + request.cookies = {"litellm_cp_return_to": "/mcp/authorize?client_id=llm_dcrc_abc"} + assert read_return_to_cookie(request) is None + + def test_no_master_key_means_no_cookie_and_no_error(self, monkeypatch: pytest.MonkeyPatch) -> None: + from fastapi import Response + + from litellm.proxy.management_endpoints.ui_sso import _persist_return_to_cookie + + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {}) + monkeypatch.setattr("litellm.proxy.proxy_server.master_key", None) + monkeypatch.delenv("LITELLM_SALT_KEY", raising=False) + resp: Final = Response() + _persist_return_to_cookie(resp, "/mcp/authorize", _make_https_request()) + assert "litellm_cp_return_to=" not in self._cookie(resp) + + def test_sso_dashboard_fallback_clears_a_return_to_cookie_it_rejected(self, monkeypatch: pytest.MonkeyPatch) -> None: + """A plaintext (pre-upgrade or client-planted) litellm_cp_return_to is not honored by /sso/callback, + and the dashboard landing must also expire it so the browser stops replaying the URL-bearing cookie + (and tripping the edge firewall) for the rest of its lifetime.""" + from litellm.proxy.management_endpoints.ui_sso import _dashboard_redirect_response + + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {}) + request: Final = _make_https_request() + request.cookies = {"litellm_cp_return_to": "/mcp/authorize?client_id=llm_dcrc_abc"} + assert read_return_to_cookie(request) is None + response: Final = _dashboard_redirect_response(request, "jwt", "/ui?login=success") + set_cookies: Final = response.headers.getlist("set-cookie") + assert response.status_code == 303 and response.headers["location"] == "/ui?login=success" + assert any(c.startswith("token=jwt") for c in set_cookies), set_cookies + assert any(c.startswith('litellm_cp_return_to=""') and "Max-Age=0" in c for c in set_cookies), set_cookies + def test_cookie_is_secure_and_httponly_over_https(self, monkeypatch): from fastapi import Response diff --git a/tests/unit/proxy/openai_files_endpoint/test_files_endpoint.py b/tests/unit/proxy/openai_files_endpoint/test_files_endpoint.py index 793921255ec..eb222366812 100644 --- a/tests/unit/proxy/openai_files_endpoint/test_files_endpoint.py +++ b/tests/unit/proxy/openai_files_endpoint/test_files_endpoint.py @@ -1,5 +1,6 @@ import json from typing import Final, List, Optional +from urllib.parse import quote from unittest.mock import ANY, AsyncMock, MagicMock import pytest @@ -12,7 +13,7 @@ from pytest_mock import MockerFixture import litellm from litellm import Router from litellm.files.types import FileContentStreamingResult -from litellm.proxy._types import LiteLLM_UserTableFiltered, UserAPIKeyAuth +from litellm.proxy._types import LiteLLM_UserTableFiltered, LitellmUserRoles, UserAPIKeyAuth from litellm.proxy.hooks import get_proxy_hook from litellm.proxy.management_endpoints.internal_user_endpoints import ui_view_users from litellm.proxy.openai_files_endpoints.file_content_streaming_handler import ( @@ -235,23 +236,112 @@ def test_invalid_purpose(mocker: MockerFixture, monkeypatch, llm_router: Router) assert error["param"] == "purpose" -def test_get_file_content_rejects_raw_cloud_storage_uri(llm_router: Router): - """A raw s3:// file id must be rejected on the proxy content endpoint. +RAW_GCS_OUTPUT_FILE_ID: Final = ( + "gs://my-gcs-bucket/litellm-vertex-files/publishers/google/models/gemini-3.8-flash/" + "prediction-model-2026-09-10T20:27:18.178864Z/predictions.jsonl" +) +RAW_S3_OUTPUT_FILE_ID: Final = "s3://my-bucket/litellm-batch-outputs/job-123/input.jsonl.out" - Such an id is not a managed unified id, so it would otherwise skip the - owner/team access check and let a caller read another tenant's batch output - object by its key. Callers must use the managed unified file id. - """ - from urllib.parse import quote - s3_file_id = "s3://my-bucket/litellm-batch-outputs/job-123/input.jsonl.out" - response = client.get( - f"/v1/files/{quote(s3_file_id, safe='')}/content?provider=bedrock", - headers={"Authorization": "Bearer test-key"}, +def _ids_a_server_hands_the_route_for(raw_id: str, provider: str) -> tuple[tuple[str, str], ...]: + encoded_once: Final = quote(raw_id, safe="") + return ((raw_id, provider), (encoded_once, provider), (quote(encoded_once, safe=""), provider)) + + +RAW_CLOUD_FILE_IDS_AS_THE_ROUTE_RECEIVES_THEM: Final = _ids_a_server_hands_the_route_for( + RAW_GCS_OUTPUT_FILE_ID, "vertex_ai" +) + _ids_a_server_hands_the_route_for(RAW_S3_OUTPUT_FILE_ID, "bedrock") + + +def _testclient_path_segment_delivering(route_file_id: str) -> str: + return quote(quote(route_file_id, safe=""), safe="") + + +def _override_auth( + monkeypatch: pytest.MonkeyPatch, mocker: MockerFixture, llm_router: Router, user_role: LitellmUserRoles +) -> ProxyLogging: + import litellm.proxy.proxy_server as ps + + proxy_logging_obj: Final = setup_proxy_logging_object(monkeypatch, llm_router) + monkeypatch.setattr("litellm.proxy.proxy_server.master_key", None) + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", None) + monkeypatch.setattr("litellm.proxy.proxy_server.llm_router", llm_router) + proxy_logging_obj.update_request_status = mocker.AsyncMock() + proxy_logging_obj.post_call_failure_hook = mocker.AsyncMock() + app.dependency_overrides[ps.user_api_key_auth] = lambda: UserAPIKeyAuth( + api_key="test-key", user_role=user_role, user_id="test-user" ) + return proxy_logging_obj - assert response.status_code == 400 - assert "managed file id" in response.json()["error"]["message"].lower() + +@pytest.mark.parametrize(("route_file_id", "provider"), RAW_CLOUD_FILE_IDS_AS_THE_ROUTE_RECEIVES_THEM) +def test_get_file_content_answers_403_for_a_raw_cloud_id_from_a_non_admin_key( + mocker: MockerFixture, + monkeypatch: pytest.MonkeyPatch, + llm_router: Router, + route_file_id: str, + provider: str, +): + import litellm.proxy.proxy_server as ps + + _override_auth(monkeypatch, mocker, llm_router, LitellmUserRoles.INTERNAL_USER) + afile_content: Final = mocker.AsyncMock() + monkeypatch.setattr(litellm, "afile_content", afile_content) + + try: + response: Final = client.get( + f"/v1/files/{_testclient_path_segment_delivering(route_file_id)}/content?provider={provider}", + headers={"Authorization": "Bearer test-key"}, + ) + finally: + app.dependency_overrides.pop(ps.user_api_key_auth, None) + + assert response.status_code == 403, response.text + assert "proxy admin" in response.json()["error"]["message"] + afile_content.assert_not_called() + + +@pytest.mark.parametrize(("route_file_id", "provider"), RAW_CLOUD_FILE_IDS_AS_THE_ROUTE_RECEIVES_THEM) +def test_get_file_content_forwards_a_raw_cloud_id_from_a_proxy_admin_key( + mocker: MockerFixture, + monkeypatch: pytest.MonkeyPatch, + llm_router: Router, + route_file_id: str, + provider: str, +): + import litellm.proxy.proxy_server as ps + + _override_auth(monkeypatch, mocker, llm_router, LitellmUserRoles.PROXY_ADMIN) + content: Final = b'{"custom_id": "request-1"}\n' + + async def _stream(): + yield content + + async def _provider_file_content(**kwargs: object) -> FileContentStreamingResult | HttpxBinaryResponseContent: + if kwargs.get("stream"): + return FileContentStreamingResult(stream_iterator=_stream(), headers={"content-length": str(len(content))}) + return HttpxBinaryResponseContent( + response=httpx.Response( + status_code=200, content=content, headers={"content-type": "application/octet-stream"} + ) + ) + + afile_content: Final = mocker.AsyncMock(side_effect=_provider_file_content) + monkeypatch.setattr(litellm, "afile_content", afile_content) + + try: + response: Final = client.get( + f"/v1/files/{_testclient_path_segment_delivering(route_file_id)}/content?provider={provider}", + headers={"Authorization": "Bearer test-key"}, + ) + finally: + app.dependency_overrides.pop(ps.user_api_key_auth, None) + + assert response.status_code == 200, response.text + assert response.content == content + afile_content.assert_called_once() + assert afile_content.call_args.kwargs["custom_llm_provider"] == provider + assert afile_content.call_args.kwargs["file_id"] == route_file_id def test_mock_create_audio_file(mocker: MockerFixture, monkeypatch, llm_router: Router): diff --git a/tests/unit/proxy/pass_through_endpoints/test_llm_pass_through_endpoints.py b/tests/unit/proxy/pass_through_endpoints/test_llm_pass_through_endpoints.py index 4dbe1f2ef8d..0186a33dbc4 100644 --- a/tests/unit/proxy/pass_through_endpoints/test_llm_pass_through_endpoints.py +++ b/tests/unit/proxy/pass_through_endpoints/test_llm_pass_through_endpoints.py @@ -35,6 +35,7 @@ from litellm.proxy.utils import ProxyLogging from litellm.passthrough.main import raise_for_provider_status from litellm.llms.bedrock.common_utils import BedrockError from tests.unit.llms.bedrock.event_loop_probe import EventLoopProbe +from tests.unit.llms.bedrock.event_loop_probe import host_in_loop_probing_vault from litellm.constants import LITELLM_PROXY_MASTER_KEY_ALIAS from litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints import ( BaseOpenAIPassThroughHandler, @@ -2519,6 +2520,48 @@ class TestBedrockAgentRuntimePassthroughVirtualKeyLeak: assert upstream["x-request-id"] == "trace-2" +@pytest.mark.asyncio +async def test_bedrock_agent_runtime_region_lookup_leaves_the_event_loop_free(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr("litellm.proxy.proxy_server.master_key", SHARED_MASTER_KEY) + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {}) + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + litellm.in_memory_llm_clients_cache.flush_cache() + for ambient in TestBedrockAgentRuntimePassthroughVirtualKeyLeak.AMBIENT_AWS_ENV: + monkeypatch.delenv(ambient, raising=False) + monkeypatch.setenv("AWS_ACCESS_KEY_ID", "ak") + monkeypatch.setenv("AWS_SECRET_ACCESS_KEY", "sk") + monkeypatch.setenv("AWS_REGION_NAME", "us-west-2") + vault: Final = host_in_loop_probing_vault(monkeypatch, "AWS_REGION_NAME") + + async def receive() -> dict[str, object]: + return {"type": "http.request", "body": b'{"retrievalQuery": {"text": "hi"}}', "more_body": False} + + request: Final = Request( + { + "type": "http", + "method": "POST", + "path": "/bedrock/knowledgebases/KB1234567/retrieve", + "headers": [(b"content-type", b"application/json")], + "query_string": b"", + }, + receive=receive, + ) + with respx.mock(assert_all_called=True) as upstream: + retrieve: Final = upstream.post( + "https://bedrock-agent-runtime.us-west-2.amazonaws.com/knowledgebases/KB1234567/retrieve" + ).mock(return_value=httpx.Response(200, json={"retrievalResults": []})) + _ = await bedrock_proxy_route( + endpoint="knowledgebases/KB1234567/retrieve", + request=request, + fastapi_response=Response(), + user_api_key_dict=UserAPIKeyAuth(api_key="sk-litellm-caller"), + ) + + assert vault.read.is_set() + assert not vault.read_on_loop.is_set() + assert retrieve.calls.last.request.headers["authorization"].startswith("AWS4-HMAC-SHA256") + + class TestLLMPassthroughFactoryProxyRoute: @pytest.mark.asyncio async def test_llm_passthrough_factory_proxy_route_success(self): diff --git a/tests/unit/proxy/pass_through_endpoints/test_llm_passthrough_endpoints.py b/tests/unit/proxy/pass_through_endpoints/test_llm_passthrough_endpoints.py index e658556bd1f..e654c6d444b 100644 --- a/tests/unit/proxy/pass_through_endpoints/test_llm_passthrough_endpoints.py +++ b/tests/unit/proxy/pass_through_endpoints/test_llm_passthrough_endpoints.py @@ -264,6 +264,42 @@ async def test_gemini_pass_through_endpoint_forwards_key_and_body( assert outbound.url.params["key"] == "gemini-test-key" assert json.loads(outbound.content) == json.loads(body) +@pytest.mark.asyncio +async def test_router_passthrough_keeps_mapped_baggage_tags_outside_upstream_body(): + from fastapi import Request + + from litellm.proxy._types import UserAPIKeyAuth + from litellm.proxy.common_utils.http_parsing_utils import read_request_body + from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache + from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup + from litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints import get_passthrough_router_request_metadata + from litellm.proxy.utils import ProxyLogging + + async def receive(): + return {"type": "http.request", "body": b'{"model":"qa-model"}'} + + request = Request( + { + "type": "http", + "method": "POST", + "path": "/openai/v1/chat/completions", + "query_string": b"", + "headers": [(b"content-type", b"application/json"), (b"baggage", b"entrypoint=a")], + }, + receive, + ) + admitted = await read_request_body(request) + await LiteLLMProxyRequestSetup.apply_baggage_tag_mappings_pre_auth( + request, + admitted, + {"request_tag_mappings": [{"key": "entrypoint", "tag_prefix": "usecase:"}]}, + None, + UserApiKeyCache(), + ) + metadata = get_passthrough_router_request_metadata(UserAPIKeyAuth(api_key="qa-key"), request) + assert metadata["tags"] == ["usecase:a"] + assert await read_request_body(request) == {"model": "qa-model"} + _VERTEX_DEPLOYMENT_PATH: Final = ( "v1/projects/deployment-project/locations/global/publishers/anthropic/models/claude-sonnet-4-5:rawPredict" diff --git a/tests/unit/proxy/pass_through_endpoints/test_pass_through_endpoints.py b/tests/unit/proxy/pass_through_endpoints/test_pass_through_endpoints.py index 4c3c7ae0f0a..f0baceecdaa 100644 --- a/tests/unit/proxy/pass_through_endpoints/test_pass_through_endpoints.py +++ b/tests/unit/proxy/pass_through_endpoints/test_pass_through_endpoints.py @@ -10337,3 +10337,39 @@ def test_init_kwargs_no_authenticated_identity_field_is_client_settable(mock_req metadata: Final = result["litellm_params"]["metadata"] survived: Final = {key: metadata.get(key) for key in expected if metadata.get(key) != expected[key]} assert survived == {}, f"client-supplied values survived for: {sorted(survived)}" + +@pytest.mark.asyncio +async def test_direct_passthrough_keeps_mapped_baggage_tags_outside_upstream_body(): + from litellm.proxy.common_utils.http_parsing_utils import read_request_body + from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache + from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup + from litellm.proxy.utils import ProxyLogging + + async def receive(): + return {"type": "http.request", "body": b'{"model":"qa-model"}'} + + request = Request( + { + "type": "http", + "method": "POST", + "path": "/openai/v1/chat/completions", + "query_string": b"", + "headers": [ + (b"content-type", b"application/json"), + (b"baggage", b"entrypoint=a"), + (b"x-litellm-tags", b"existing"), + ], + }, + receive, + ) + admitted = await read_request_body(request) + await LiteLLMProxyRequestSetup.apply_baggage_tag_mappings_pre_auth( + request, + admitted, + {"request_tag_mappings": [{"key": "entrypoint", "tag_prefix": "usecase:"}]}, + None, + UserApiKeyCache(), + ) + metadata = _update_metadata_with_tags_in_header(request, {}) + assert metadata["tags"] == ["existing", "usecase:a"] + assert await read_request_body(request) == {"model": "qa-model"} diff --git a/tests/unit/proxy/proxy_server/test_lifecycle.py b/tests/unit/proxy/proxy_server/test_lifecycle.py index 3914c337f59..11a44a0ec16 100644 --- a/tests/unit/proxy/proxy_server/test_lifecycle.py +++ b/tests/unit/proxy/proxy_server/test_lifecycle.py @@ -697,33 +697,61 @@ def test_load_from_azure_key_vault_missing_uri_failure_is_swallowed(monkeypatch) # --------------------------------------------------------------------------- -def test_cost_tracking_adds_db_and_shadow_eval_callbacks_when_prisma_set(monkeypatch): +@pytest.mark.asyncio +@pytest.mark.parametrize("setup_count", [1, 2]) +async def test_cost_tracking_adds_db_and_shadow_eval_callbacks_when_prisma_set( + monkeypatch: pytest.MonkeyPatch, setup_count: int +) -> None: + from datetime import datetime + import litellm from litellm.integrations.shadow_eval_logger import ShadowEvalLogger + from litellm.proxy.spend_tracking.spend_event import SpendEventDecodeError, decode_spend_event + from litellm.proxy.spend_tracking.spend_event_producer import SpendEventProducer + from litellm.types.utils import ModelResponse, Usage + from litellm.utils import Rules, function_setup - fake_prisma = MagicMock() - monkeypatch.setattr(ps, "prisma_client", fake_prisma, raising=False) - monkeypatch.setattr(litellm, "callbacks", [], raising=False) - monkeypatch.setattr(litellm, "_async_success_callback", [], raising=False) + producer: Final = AsyncMock(spec=SpendEventProducer) + monkeypatch.setattr(ps, "prisma_client", MagicMock()) + monkeypatch.setattr(ps, "spend_event_producer", None) + monkeypatch.setattr(ps, "build_spend_event_producer", lambda settings, fallback: producer) + for name in ( + "callbacks", + "input_callback", + "success_callback", + "failure_callback", + "_async_success_callback", + "_async_failure_callback", + ): + monkeypatch.setattr(litellm, name, []) - before_callbacks = len(litellm.callbacks) - before_async = len(litellm._async_success_callback) + for _ in range(setup_count): + cost_tracking() - cost_tracking() - cost_tracking() - - observed = { - "added_to_callbacks": len(litellm.callbacks) - before_callbacks, - "added_to_async_success": len(litellm._async_success_callback) - before_async, - "shadow_eval_loggers": sum(isinstance(cb, ShadowEvalLogger) for cb in litellm.callbacks), - "prisma_was_set": True, - } - assert normalize(observed) == { - "added_to_callbacks": 2, - "added_to_async_success": 1, - "shadow_eval_loggers": 1, - "prisma_was_set": True, - } + assert len(litellm.callbacks) == 2 + assert sum(isinstance(cb, ShadowEvalLogger) for cb in litellm.callbacks) == 1 + assert len(litellm._async_success_callback) == 1 + now: Final = datetime(2026, 1, 1) + logging_obj, _ = function_setup( + "acompletion", + Rules(), + now, + model="openai/gpt-4o-mini", + messages=[{"role": "user", "content": "hello"}], + litellm_call_id="single-accounting-event", + ) + logging_obj.update_environment_variables(litellm_params={"acompletion": True, "metadata": {}}, optional_params={}) + response: Final = ModelResponse( + id="chatcmpl-single-accounting-event", + model="gpt-4o-mini", + usage=Usage(prompt_tokens=10, completion_tokens=5, total_tokens=15), + ) + await logging_obj.async_success_handler(response, now, now) + producer.publish.assert_awaited_once() + event: Final = decode_spend_event(producer.publish.call_args.args[0]) + assert not isinstance(event, SpendEventDecodeError) + assert event.response_cost == logging_obj.model_call_details["response_cost"] + assert event.response_cost > 0 def test_cost_tracking_no_op_when_prisma_missing(monkeypatch): diff --git a/tests/unit/proxy/proxy_server/test_routes_login_sso.py b/tests/unit/proxy/proxy_server/test_routes_login_sso.py index 75e14a89148..43629b926ad 100644 --- a/tests/unit/proxy/proxy_server/test_routes_login_sso.py +++ b/tests/unit/proxy/proxy_server/test_routes_login_sso.py @@ -11,8 +11,12 @@ Routes covered: from __future__ import annotations from datetime import datetime, timezone +from typing import Final from unittest.mock import AsyncMock, MagicMock +import pytest +from fastapi.testclient import TestClient + from .conftest import normalize # --------------------------------------------------------------------------- @@ -398,6 +402,29 @@ def test_v3_login_exchange_success_returns_token_and_redirect(client, monkeypatc } +def _sealed_return_to(return_to: str) -> str: + """The cookie value /sso/key/generate writes: return_to sealed under the master key, never plaintext.""" + from litellm.constants import CP_RETURN_TO_COOKIE_PREFIX + from litellm.proxy.common_utils.encrypt_decrypt_utils import encrypt_bearer_token + + return encrypt_bearer_token(return_to, prefix=CP_RETURN_TO_COOKIE_PREFIX) + + +def test_login_form_ignores_a_plaintext_return_to_cookie(client: TestClient, monkeypatch: pytest.MonkeyPatch) -> None: + """A return_to the proxy did not seal (a client-planted or pre-upgrade plaintext cookie) is not + honored: /login lands on the dashboard and clears the cookie.""" + _install_login_mocks(monkeypatch) + response: Final = client.post( + "/login", + data={"username": "admin", "password": "password"}, + cookies={"litellm_cp_return_to": "/mcp/authorize?client_id=llm_dcrc_abc"}, + follow_redirects=False, + ) + assert response.status_code == 303 + assert "/ui" in response.headers.get("location", "") + assert 'litellm_cp_return_to=""' in response.headers.get("set-cookie", "") + + def test_login_form_honors_same_origin_return_to_cookie(client, monkeypatch): """The aggregate DCR connect flow preserves a same-origin return_to in the litellm_cp_return_to cookie; /login must RESUME there after password sign-in instead of dead-ending at the dashboard.""" @@ -406,7 +433,7 @@ def test_login_form_honors_same_origin_return_to_cookie(client, monkeypatch): response = client.post( "/login", data={"username": "admin", "password": "password"}, - cookies={"litellm_cp_return_to": return_to}, + cookies={"litellm_cp_return_to": _sealed_return_to(return_to)}, follow_redirects=False, ) assert response.status_code == 303 @@ -425,7 +452,7 @@ def test_login_form_honors_control_plane_return_to_cookie(client, monkeypatch): response = client.post( "/login", data={"username": "admin", "password": "password"}, - cookies={"litellm_cp_return_to": "https://cp.example.com/console"}, + cookies={"litellm_cp_return_to": _sealed_return_to("https://cp.example.com/console")}, follow_redirects=False, ) location = response.headers.get("location", "") @@ -447,7 +474,7 @@ def test_login_form_survives_stale_control_plane_return_to(client, monkeypatch): response = client.post( "/login", data={"username": "admin", "password": "password"}, - cookies={"litellm_cp_return_to": "https://old-cp.example.com/console"}, + cookies={"litellm_cp_return_to": _sealed_return_to("https://old-cp.example.com/console")}, follow_redirects=False, ) assert response.status_code == 303, "login must not break on a stale return_to cookie" @@ -463,7 +490,7 @@ def test_login_form_ignores_open_redirect_return_to(client, monkeypatch): response = client.post( "/login", data={"username": "admin", "password": "password"}, - cookies={"litellm_cp_return_to": "https://evil.example.com/steal"}, + cookies={"litellm_cp_return_to": _sealed_return_to("https://evil.example.com/steal")}, follow_redirects=False, ) assert response.status_code == 303 diff --git a/tests/unit/proxy/proxy_server/test_routes_queue.py b/tests/unit/proxy/proxy_server/test_routes_queue.py index 27cc6300711..07a61c8587b 100644 --- a/tests/unit/proxy/proxy_server/test_routes_queue.py +++ b/tests/unit/proxy/proxy_server/test_routes_queue.py @@ -6,10 +6,12 @@ Pins (PR2): from __future__ import annotations -from unittest.mock import AsyncMock, MagicMock +from typing import Final +from unittest.mock import AsyncMock, MagicMock, patch import pytest +from litellm import Router from litellm.proxy import proxy_server from .conftest import normalize # type: ignore[import-not-found] @@ -34,6 +36,7 @@ HAPPY_RESPONSE = { @pytest.fixture def patched_queue(monkeypatch): router = MagicMock() + router.split_request_priority = MagicMock(return_value=(0, {})) router.schedule_acompletion = AsyncMock(return_value=dict(HAPPY_RESPONSE)) monkeypatch.setattr(proxy_server, "llm_router", router) monkeypatch.setattr( @@ -89,3 +92,103 @@ def test_queue_chat_completions_no_router_error(client, auth_as, queue_no_router response = client.post("/queue/chat/completions", json=payload) assert response.status_code == 500 assert len(response.content) > 0 + + +def _queue_router( + monkeypatch: pytest.MonkeyPatch, default_priority: int | None, mock_response: str = "queued" +) -> Router: + router: Final = Router( + model_list=[ + { + "model_name": "gpt-4", + "litellm_params": {"model": "openai/gpt-4", "api_key": "sk-queue-test", "mock_response": mock_response}, + } + ], + default_priority=default_priority, + ) + monkeypatch.setattr(proxy_server, "llm_router", router) + monkeypatch.setattr(proxy_server, "proxy_logging_obj", MagicMock(post_call_failure_hook=AsyncMock())) + return router + + +@pytest.mark.parametrize( + ("default_priority", "priority_fields", "expected_priority"), + [ + (3, {"priority": "high", "drop_params": True}, 3), + (3, {"priority": "1"}, 1), + (None, {"priority": 1.0}, 1), + (3, {"priority": 1}, 1), + (3, {}, 3), + ], + ids=("dropped-word-takes-default", "digit-string", "integral-float", "explicit", "absent-takes-default"), +) +def test_queue_chat_completions_reports_the_priority_the_router_queued_at( + client, + auth_as, + monkeypatch: pytest.MonkeyPatch, + default_priority: int | None, + priority_fields: dict[str, object], + expected_priority: int, +) -> None: + router: Final = _queue_router(monkeypatch, default_priority) + payload: Final = {"model": "gpt-4", "messages": [{"role": "user", "content": "hi"}], **priority_fields} + with patch.object(router.scheduler, "add_request", wraps=router.scheduler.add_request) as add_request: + with auth_as(): + response: Final = client.post("/queue/chat/completions", json=payload) + assert response.status_code == 200, response.text + assert [call.kwargs["request"].priority for call in add_request.await_args_list] == [expected_priority] + assert response.headers.get("x-litellm-priority") == str(expected_priority) + + +@pytest.mark.parametrize( + ("default_priority", "priority_fields", "message"), + [ + (None, {}, "priority is required"), + (3, {"priority": "high"}, "priority must be an integer"), + (None, {"priority": "high", "drop_params": True}, "priority must be an integer, got str 'high'"), + ], + ids=("no-priority-and-no-default", "malformed", "dropped-word-and-no-default"), +) +def test_queue_chat_completions_rejects_a_request_it_cannot_queue_as_an_invalid_request( + client, + auth_as, + monkeypatch: pytest.MonkeyPatch, + default_priority: int | None, + priority_fields: dict[str, object], + message: str, +) -> None: + router: Final = _queue_router(monkeypatch, default_priority) + payload: Final = {"model": "gpt-4", "messages": [{"role": "user", "content": "hi"}], **priority_fields} + with patch.object(router.scheduler, "add_request", wraps=router.scheduler.add_request) as add_request: + with auth_as(): + response: Final = client.post("/queue/chat/completions", json=payload) + assert response.status_code == 400, response.text + error: Final = response.json()["error"] + assert (error["type"], error["param"]) == ("invalid_request_error", "priority") + assert message in error["message"] + assert add_request.await_count == 0 + + +def test_streamed_queue_responses_report_the_priority_the_router_queued_at( + client, auth_as, monkeypatch: pytest.MonkeyPatch +) -> None: + _queue_router(monkeypatch, default_priority=3) + payload: Final = {"model": "gpt-4", "messages": [{"role": "user", "content": "hi"}], "priority": "1", "stream": True} + with auth_as(): + response: Final = client.post("/queue/chat/completions", json=payload) + assert response.status_code == 200, response.text + assert response.headers.get("x-litellm-priority") == "1" + + +def test_a_provider_bad_request_on_the_queue_route_keeps_its_own_message( + client, auth_as, monkeypatch: pytest.MonkeyPatch +) -> None: + _queue_router(monkeypatch, default_priority=3, mock_response="litellm.ContextWindowExceededError") + payload: Final = {"model": "gpt-4", "messages": [{"role": "user", "content": "hi"}]} + with auth_as(): + response: Final = client.post("/queue/chat/completions", json=payload) + assert response.status_code == 400, response.text + error: Final = response.json()["error"] + assert error["type"] == "invalid_request_error" + assert "context window" in error["message"].lower() + assert "Authentication Error" not in error["message"] diff --git a/tests/unit/proxy/proxy_server/test_spend_counters.py b/tests/unit/proxy/proxy_server/test_spend_counters.py index 3ff4293ba93..d273ef8f42f 100644 --- a/tests/unit/proxy/proxy_server/test_spend_counters.py +++ b/tests/unit/proxy/proxy_server/test_spend_counters.py @@ -24,15 +24,31 @@ from __future__ import annotations import asyncio from collections.abc import Awaitable, Callable from datetime import datetime -from typing import Final, cast -from unittest.mock import AsyncMock, MagicMock +from typing import Final, Literal, cast +from unittest.mock import AsyncMock, MagicMock, call import pytest +from fakeredis import FakeAsyncRedis, FakeServer +from opentelemetry.sdk.trace import TracerProvider +from opentelemetry.sdk.trace.export import SimpleSpanProcessor +from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter +from opentelemetry.trace import StatusCode +import litellm import litellm.proxy.proxy_server as ps +from litellm._service_logger import ServiceLogging +from litellm._internal_context import current_service_target +from litellm.caching.in_memory_cache import InMemoryCache +from litellm.caching.redis_cache import RedisCache, RedisCircuitBreaker +from litellm.constants import GLOBAL_PROXY_SPEND_CACHE_KEY +from litellm.integrations.opentelemetry import OpenTelemetry, OpenTelemetryConfig +from litellm.models.end_user import LiteLLM_EndUserTable +from litellm.models.tag import LiteLLM_TagTable from litellm.models.team import LiteLLM_TeamTable, LiteLLM_TeamTableCachedObj +from litellm.models.user import LiteLLM_UserTable from litellm.proxy.common_utils.auth_cache_invalidation_pubsub import evict_local -from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache +from litellm.proxy.common_utils.cache_pydantic_utils import CacheCodec +from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache, end_user_cache_key, tag_cache_key from litellm.proxy.management_endpoints.team_endpoints import refresh_cached_team from .conftest import normalize @@ -1559,31 +1575,6 @@ async def test_invalidate_spend_counter_swallows_redis_failure_no_raise(monkeypa # --------------------------------------------------------------------------- -@pytest.mark.asyncio -async def test_update_cache_no_cached_entities_schedules_pipeline_flush(monkeypatch): - fake_user_cache = _make_user_api_key_cache(get_value=None) - monkeypatch.setattr(ps, "user_api_key_cache", fake_user_cache) - - await ps.update_cache( - token=None, - user_id="u1", - end_user_id="eu1", - team_id="t1", - response_cost=1.0, - parent_otel_span=None, - tags=["x"], - ) - - assert fake_user_cache.async_get_cache.await_count == 0 - fake_user_cache.async_batch_get_cache.assert_awaited_once() - assert fake_user_cache.async_batch_get_cache.await_args.kwargs["keys"] == [ - "u1", - f"{ps.litellm_proxy_admin_name}:spend", - "end_user_id:eu1", - "tag:x", - ] - - @pytest.mark.asyncio async def test_update_cache_user_cache_failure_invalid_state_is_swallowed(monkeypatch): """An inner _update_user_cache raising must not propagate — update_cache @@ -1671,3 +1662,354 @@ async def test_update_cache_never_restores_a_team_a_management_write_replaced( seen_by_auth: Final = cache.get_cache(key=f"team_id:{team_id}", model_type=LiteLLM_TeamTableCachedObj) assert (seen_by_auth.blocked if seen_by_auth is not None else None) == expected_blocked + + +_CachedSpendObject = LiteLLM_UserTable | LiteLLM_EndUserTable | LiteLLM_TeamTableCachedObj | LiteLLM_TagTable + + +def _cached_spend_object( + kind: Literal["user", "end_user", "team", "tag"], models: list[str] +) -> tuple[str, _CachedSpendObject]: + match kind: + case "user": + return "race-user", LiteLLM_UserTable(user_id="race-user", models=models) + case "end_user": + return end_user_cache_key("race-end-user"), LiteLLM_EndUserTable( + user_id="race-end-user", blocked=False, models=models + ) + case "team": + return "team_id:race-team", LiteLLM_TeamTableCachedObj(team_id="race-team", models=models) + case "tag": + return tag_cache_key("race-tag"), LiteLLM_TagTable(tag_name="race-tag", models=models) + + +class _RunsOnKeyRead(InMemoryCache): + def __init__(self, on_read: Callable[[], Awaitable[None]]) -> None: + super().__init__() + self._on_read: Final = on_read + + async def async_get_cache(self, key: str, **kwargs: object) -> object: + await self._on_read() + return await super().async_get_cache(key, **kwargs) + + +def _cache_that_runs_on_key_read(on_read: Callable[[], Awaitable[None]]) -> UserApiKeyCache: + return UserApiKeyCache(in_memory_cache=InMemoryCache(), key_object_in_memory_cache=_RunsOnKeyRead(on_read)) + + +@pytest.fixture +def proxy_max_budget(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr(litellm, "max_budget", 100.0) + + +@pytest.mark.asyncio +@pytest.mark.parametrize("kind", ["user", "end_user", "team", "tag"]) +@pytest.mark.parametrize( + ("management_write", "expected"), + [("none", (["gpt-a"], 0.25)), ("evict", None), ("refresh", (["gpt-b"], 0.25))], +) +async def test_update_cache_adds_spend_to_the_entry_a_management_write_left_mid_flight( + kind: Literal["user", "end_user", "team", "tag"], + management_write: Literal["none", "evict", "refresh"], + expected: tuple[list[str], float] | None, +) -> None: + key, seeded = _cached_spend_object(kind, models=["gpt-a"]) + _, refreshed = _cached_spend_object(kind, models=["gpt-b"]) + + async def _write() -> None: + if management_write == "none": + return + evict_local(cache_keys=(key,), user_api_key_cache=cache) + if management_write == "refresh": + cache.set_cache(key=key, value=refreshed, local_only=True) + + cache: Final = _cache_that_runs_on_key_read(on_read=_write) + cache.set_cache(key=key, value=seeded, local_only=True) + + await ps.update_cache( + token="sk-race", + user_id="race-user", + end_user_id="race-end-user", + team_id="race-team", + response_cost=0.25, + parent_otel_span=None, + tags=["race-tag"], + cache=cache, + ) + await _drain_spend_cache_writes() + + stored: Final = cache.get_cache(key=key, local_only=True, model_type=type(seeded)) + assert ((stored.models, stored.spend) if stored is not None else None) == expected + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("proxy_max_budget") +@pytest.mark.parametrize("user", ["cached_on_this_worker", "not_cached_on_this_worker", "none"]) +async def test_update_cache_adds_spend_to_the_global_proxy_spend_for_every_request( + user: Literal["cached_on_this_worker", "not_cached_on_this_worker", "none"], +) -> None: + cache: Final = UserApiKeyCache() + cache.set_cache(key=GLOBAL_PROXY_SPEND_CACHE_KEY, value=10.0) + if user == "cached_on_this_worker": + cache.set_cache(key="spender", value=LiteLLM_UserTable(user_id="spender", spend=1.0)) + + await ps.update_cache( + token=None, + user_id=None if user == "none" else "spender", + end_user_id=None, + team_id=None, + response_cost=0.25, + parent_otel_span=None, + cache=cache, + ) + await _drain_spend_cache_writes() + + assert cache.get_cache(key=GLOBAL_PROXY_SPEND_CACHE_KEY) == 10.25 + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("proxy_max_budget") +async def test_update_cache_never_brings_back_a_global_proxy_spend_a_budget_reset_cleared() -> None: + async def _budget_reset() -> None: + await cache.async_delete_cache(key=GLOBAL_PROXY_SPEND_CACHE_KEY) + + cache: Final = _cache_that_runs_on_key_read(on_read=_budget_reset) + cache.set_cache(key=GLOBAL_PROXY_SPEND_CACHE_KEY, value=10.0) + + await ps.update_cache( + token="sk-spender", + user_id="spender", + end_user_id=None, + team_id=None, + response_cost=0.25, + parent_otel_span=None, + cache=cache, + ) + await _drain_spend_cache_writes() + + assert cache.get_cache(key=GLOBAL_PROXY_SPEND_CACHE_KEY) is None + + +class _FakeRedisRunningIncrementIfPresent(FakeAsyncRedis): + def __init__(self, server: FakeServer, after_increment: Callable[[], object] = lambda: None) -> None: + super().__init__(server=server) + self._after_increment: Final = after_increment + + async def eval(self, script: str, numkeys: int, *keys_and_args: str | bytes | float) -> bytes | None: + key, increment = keys_and_args + if not await self.exists(key): + return None + total: Final = await self.incrbyfloat(key, increment) + self._after_increment() + return str(total).encode() + + +class _RedisCacheOnClient(RedisCache): + def __init__(self, client: FakeAsyncRedis) -> None: + self._injected_client: Final = client + self.namespace = None + self._circuit_breaker = RedisCircuitBreaker(failure_threshold=5, recovery_timeout=30) + self.service_logger_obj = ServiceLogging() + self.default_ttl = None + + def init_async_client(self) -> FakeAsyncRedis: + return self._injected_client + + +class _FakeRedisHoldingOneReply(FakeAsyncRedis): + def __init__(self, server: FakeServer, held_increment: float, applied: asyncio.Event, released: asyncio.Event) -> None: + super().__init__(server=server) + self._held_increment: Final = held_increment + self._applied: Final = applied + self._released: Final = released + + async def eval(self, script: str, numkeys: int, *keys_and_args: str | bytes | float) -> bytes | None: + key, increment = keys_and_args + total: Final = await self.incrbyfloat(key, increment) + if float(increment) == self._held_increment: + self._applied.set() + await self._released.wait() + return str(total).encode() + + +_SharedGlobalSpendOutcome = Literal["peers_added_spend", "reset_elsewhere", "reset_while_redis_answers", "redis_down"] + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("proxy_max_budget") +@pytest.mark.parametrize( + ("outcome", "shared_total", "expected"), + [ + ("peers_added_spend", 11.75, 12.0), + ("reset_elsewhere", None, 10.25), + ("reset_while_redis_answers", 9.75, None), + ("redis_down", 10.0, 10.25), + ], +) +async def test_update_cache_moves_this_workers_global_proxy_spend_to_the_shared_total( + outcome: _SharedGlobalSpendOutcome, shared_total: float | None, expected: float | None +) -> None: + def _reset_this_worker() -> None: + if outcome == "reset_while_redis_answers": + cache.in_memory_cache.delete_cache(GLOBAL_PROXY_SPEND_CACHE_KEY) + + server: Final = FakeServer() + redis: Final = _FakeRedisRunningIncrementIfPresent(server, after_increment=_reset_this_worker) + if shared_total is not None: + await redis.set(GLOBAL_PROXY_SPEND_CACHE_KEY, shared_total) + server.connected = outcome != "redis_down" + cache: Final = UserApiKeyCache(in_memory_cache=InMemoryCache(), redis_cache=_RedisCacheOnClient(redis)) + cache.set_cache(key=GLOBAL_PROXY_SPEND_CACHE_KEY, value=10.0, local_only=True) + + await ps.update_cache( + token=None, + user_id=None, + end_user_id=None, + team_id=None, + response_cost=0.25, + parent_otel_span=None, + cache=cache, + ) + + assert cache.get_cache(key=GLOBAL_PROXY_SPEND_CACHE_KEY, local_only=True) == expected + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("proxy_max_budget") +async def test_update_cache_keeps_the_newest_global_proxy_spend_when_redis_replies_out_of_order() -> None: + held_increment_applied: Final = asyncio.Event() + held_reply_released: Final = asyncio.Event() + server: Final = FakeServer() + redis: Final = _FakeRedisHoldingOneReply( + server, held_increment=0.25, applied=held_increment_applied, released=held_reply_released + ) + await redis.set(GLOBAL_PROXY_SPEND_CACHE_KEY, 10.0) + cache: Final = UserApiKeyCache(in_memory_cache=InMemoryCache(), redis_cache=_RedisCacheOnClient(redis)) + cache.set_cache(key=GLOBAL_PROXY_SPEND_CACHE_KEY, value=10.0, local_only=True) + + async def _request(response_cost: float) -> None: + await ps.update_cache( + token=None, + user_id=None, + end_user_id=None, + team_id=None, + response_cost=response_cost, + parent_otel_span=None, + cache=cache, + ) + + earlier: Final = asyncio.create_task(_request(0.25)) + await held_increment_applied.wait() + await _request(0.5) + held_reply_released.set() + await earlier + + assert cache.get_cache(key=GLOBAL_PROXY_SPEND_CACHE_KEY, local_only=True) == 10.75 + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("proxy_max_budget") +async def test_update_cache_adds_the_global_spend_scalar_in_redis_as_spend_counters() -> None: + target_during_increment: Final = MagicMock() + redis: Final = _FakeRedisRunningIncrementIfPresent( + FakeServer(), after_increment=lambda: target_during_increment(current_service_target()) + ) + await redis.set(GLOBAL_PROXY_SPEND_CACHE_KEY, 10.0) + cache: Final = UserApiKeyCache(in_memory_cache=InMemoryCache(), redis_cache=_RedisCacheOnClient(redis)) + + await ps.update_cache( + token=None, + user_id="u1", + end_user_id=None, + team_id=None, + response_cost=2.0, + parent_otel_span=None, + cache=cache, + ) + + assert target_during_increment.call_args_list == [call("spend_counters")] + assert float(await redis.get(GLOBAL_PROXY_SPEND_CACHE_KEY)) == 12.0 + assert current_service_target() is None + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("proxy_max_budget") +@pytest.mark.parametrize(("redis_up", "expected_status"), [(True, StatusCode.OK), (False, StatusCode.ERROR)]) +async def test_update_cache_traces_the_global_spend_redis_call_under_the_request_span( + monkeypatch: pytest.MonkeyPatch, redis_up: bool, expected_status: StatusCode +) -> None: + exporter: Final = InMemorySpanExporter() + provider: Final = TracerProvider() + provider.add_span_processor(SimpleSpanProcessor(exporter)) + monkeypatch.setattr( + litellm, + "service_callback", + [OpenTelemetry(config=OpenTelemetryConfig(exporter=exporter), tracer_provider=provider)], + ) + server: Final = FakeServer() + redis: Final = _FakeRedisRunningIncrementIfPresent(server) + await redis.set(GLOBAL_PROXY_SPEND_CACHE_KEY, 10.0) + server.connected = redis_up + cache: Final = UserApiKeyCache(in_memory_cache=InMemoryCache(), redis_cache=_RedisCacheOnClient(redis)) + request_span: Final = provider.get_tracer("test").start_span("request") + + await ps.update_cache( + token=None, + user_id=None, + end_user_id=None, + team_id=None, + response_cost=2.0, + parent_otel_span=request_span, + cache=cache, + ) + await _drain_spend_cache_writes() + request_span.end() + + redis_spans: Final = tuple( + (span.attributes.get("call_type"), span.status.status_code, span.parent.span_id) + for span in exporter.get_finished_spans() + if span.name == "redis" and span.attributes is not None and span.parent is not None + ) + assert redis_spans == ( + ("async_increment_if_present", expected_status, request_span.get_span_context().span_id), + ) + + +class _UnwritableKeyUserApiKeyCache(UserApiKeyCache): + def __init__(self, unwritable_key: str) -> None: + super().__init__(in_memory_cache=InMemoryCache()) + self._unwritable_key: Final = unwritable_key + + def set_cache(self, key: str | None, value: object, local_only: bool = False, **kwargs: object): + if key == self._unwritable_key: + raise RuntimeError("cache write failed") + return super().set_cache(key, value, local_only=local_only, **kwargs) + + +@pytest.mark.asyncio +@pytest.mark.usefixtures("proxy_max_budget") +async def test_update_cache_still_adds_spend_to_the_others_when_one_cached_object_fails() -> None: + cache: Final = _UnwritableKeyUserApiKeyCache(unwritable_key="broken-user") + cache.in_memory_cache.set_cache( + key="broken-user", + value=CacheCodec.serialize(LiteLLM_UserTable(user_id="broken-user", spend=1.0), model_type=LiteLLM_UserTable), + ) + cache.set_cache(key=GLOBAL_PROXY_SPEND_CACHE_KEY, value=10.0) + cache.set_cache(key="team_id:still-billed", value=LiteLLM_TeamTableCachedObj(team_id="still-billed", spend=1.0)) + + await ps.update_cache( + token=None, + user_id="broken-user", + end_user_id=None, + team_id="still-billed", + response_cost=0.25, + parent_otel_span=None, + cache=cache, + ) + await _drain_spend_cache_writes() + + team: Final = cache.get_cache(key="team_id:still-billed", model_type=LiteLLM_TeamTableCachedObj) + assert (team.spend if team is not None else None, cache.get_cache(key=GLOBAL_PROXY_SPEND_CACHE_KEY)) == ( + 1.25, + 10.25, + ) diff --git a/tests/unit/proxy/proxy_server/test_streaming_helpers.py b/tests/unit/proxy/proxy_server/test_streaming_helpers.py index 227a099889d..9a3516d20d6 100644 --- a/tests/unit/proxy/proxy_server/test_streaming_helpers.py +++ b/tests/unit/proxy/proxy_server/test_streaming_helpers.py @@ -2322,6 +2322,7 @@ async def _queue_streaming(monkeypatch, interval, delay=0.3, fails_with=None): router = MagicMock() router.get_model_list.return_value = [] + router.split_request_priority.return_value = (0, {}) async def _schedule_after_the_scheduler_queue_drains(**kwargs): await asyncio.sleep(delay) diff --git a/tests/unit/proxy/public_endpoints/public_v1/test_model_hub.py b/tests/unit/proxy/public_endpoints/public_v1/test_model_hub.py index 07886745222..43cdebd54b6 100644 --- a/tests/unit/proxy/public_endpoints/public_v1/test_model_hub.py +++ b/tests/unit/proxy/public_endpoints/public_v1/test_model_hub.py @@ -61,13 +61,19 @@ def _groups(response) -> list[str]: return [row["model_group"] for row in response.json()["data"]] -def _health_check(model_name: str, status: str = "healthy"): +def _health_check( + model_name: str, + status: str = "healthy", + *, + model_id: str | None = None, + checked_at: datetime = datetime(2026, 8, 1, 9, 30, tzinfo=timezone.utc), +): check = MagicMock() check.model_name = model_name - check.model_id = None + check.model_id = model_id check.status = status check.response_time_ms = 12.5 - check.checked_at = datetime(2026, 8, 1, 9, 30, tzinfo=timezone.utc) + check.checked_at = checked_at return check @@ -154,6 +160,21 @@ def test_the_latest_health_check_lands_on_its_row(monkeypatch): assert rows["model-000"]["health_status"] is None +def test_a_stale_row_sorting_after_the_fresh_one_does_not_speak_for_the_group(monkeypatch): + """The read orders by model_id with NULL last; that order used to pick the group's health.""" + fresh = _health_check( + "model-001", model_id="deployment-a", checked_at=datetime(2026, 10, 16, 11, 10, tzinfo=timezone.utc) + ) + stale = _health_check("model-001", status="unhealthy", checked_at=datetime(2026, 9, 4, 11, 20, tzinfo=timezone.utc)) + prisma_client, _ = _recording_prisma([fresh, stale]) + _publish(monkeypatch, _named(3), prisma_client=prisma_client) + + rows = {row["model_group"]: row for row in _get().json()["data"]} + + assert rows["model-001"]["health_status"] == "healthy" + assert rows["model-001"]["health_checked_at"] == "2026-10-16T11:10:00+00:00" + + def test_a_health_read_that_returns_nothing_still_serves_the_page(monkeypatch): prisma_client, read = _recording_prisma() read.return_value = [] diff --git a/tests/unit/proxy/public_endpoints/test_public_endpoints.py b/tests/unit/proxy/public_endpoints/test_public_endpoints.py index d5bacd9fd3c..8f27365fcc1 100644 --- a/tests/unit/proxy/public_endpoints/test_public_endpoints.py +++ b/tests/unit/proxy/public_endpoints/test_public_endpoints.py @@ -15,6 +15,7 @@ from pydantic import TypeAdapter import litellm from litellm.proxy.auth.user_api_key_auth import user_api_key_auth +from litellm.proxy.db.health_check_latest import LatestHealthCheckRow from litellm.proxy.public_endpoints import router from litellm.router_strategy.complexity_router.fuse_presets import get_fuse_presets from litellm.types.proxy.management_endpoints.model_management_endpoints import ( @@ -852,6 +853,46 @@ def test_public_model_hub_mixed_health_statuses(): app.dependency_overrides.clear() +def _stored_health_check(model_id: str | None, status: str, checked_at: datetime) -> LatestHealthCheckRow: + return LatestHealthCheckRow( + health_check_id=f"hc-{model_id}", + model_name="gpt-4", + model_id=model_id, + status=status, + checked_at=checked_at, + created_at=checked_at, + updated_at=checked_at, + ) + + +def test_public_model_hub_reports_the_newest_check_of_a_group_not_the_last_row_read(): + """Rows come back in model_id order with NULL last, so a stale name-probe row used to overwrite the fresh one.""" + app = FastAPI() + app.include_router(router) + app.dependency_overrides[user_api_key_auth] = lambda: MagicMock() + client = TestClient(app) + fresh = _stored_health_check("deployment-a", "healthy", datetime(2026, 10, 16, 11, 10, tzinfo=timezone.utc)) + stale = _stored_health_check(None, "unhealthy", datetime(2026, 9, 4, 11, 20, tzinfo=timezone.utc)) + mock_prisma = MagicMock() + mock_prisma.get_all_latest_health_checks = AsyncMock(return_value=(fresh, stale)) + + with ( + patch("litellm.public_model_groups", ["gpt-4"]), + patch("litellm.proxy.proxy_server.get_model_group_info") as mock_get_info, + patch("litellm.proxy.proxy_server.llm_router", MagicMock()), + patch("litellm.proxy.proxy_server.prisma_client", mock_prisma), + ): + mock_get_info.return_value = [ + ModelGroupInfoProxy(model_group="gpt-4", providers=["openai"], is_public_model_group=True) + ] + response = client.get("/public/model_hub", headers={"Authorization": "Bearer test-key"}) + + assert response.status_code == 200 + assert response.json()[0]["health_status"] == "healthy" + assert response.json()[0]["health_checked_at"] == "2026-10-16T11:10:00+00:00" + app.dependency_overrides.clear() + + # --------------------------------------------------------------------------- # /public/agent_hub # --------------------------------------------------------------------------- diff --git a/tests/unit/proxy/response_api_endpoints/test_endpoints.py b/tests/unit/proxy/response_api_endpoints/test_endpoints.py index e3ce513dbcb..abc1fe88c7a 100644 --- a/tests/unit/proxy/response_api_endpoints/test_endpoints.py +++ b/tests/unit/proxy/response_api_endpoints/test_endpoints.py @@ -1079,6 +1079,9 @@ def _managed_files_over(table: _UniqueManagedObjectTable) -> tuple[MagicMock, Ma prisma_client.db.litellm_usertable.find_unique = AsyncMock(return_value=None) prisma_client.db.litellm_verificationtoken.find_unique = AsyncMock(return_value=None) prisma_client.db.litellm_teamtable.find_unique = AsyncMock(return_value=None) + prisma_client.db.litellm_deprecatedverificationtoken.find_unique = AsyncMock(return_value=None) + prisma_client.db.litellm_deletedverificationtoken.find_first = AsyncMock(return_value=None) + prisma_client.db.litellm_deletedteamtable.find_first = AsyncMock(return_value=None) proxy_logging: Final = MagicMock() proxy_logging.get_proxy_hook = MagicMock( return_value=_PROXY_LiteLLMManagedFiles(internal_usage_cache=DualCache(), prisma_client=prisma_client) @@ -4171,10 +4174,17 @@ class TestResponsesInputTokens: path: str = "/v1/responses/input_tokens", counter: AsyncMock | None = None, llm_router: litellm.Router | None = None, + response_id_security: object | None = None, + managed_files: object | None = None, ) -> tuple[Response, AsyncMock]: from litellm.proxy._types import UserAPIKeyAuth from litellm.proxy.auth.user_api_key_auth import user_api_key_auth - from litellm.proxy.response_api_endpoints.endpoints import _proxy_llm_router, _proxy_token_counter + from litellm.proxy.response_api_endpoints.endpoints import ( + _proxy_llm_router, + _proxy_managed_files_hook, + _proxy_response_id_security, + _proxy_token_counter, + ) from litellm.types.utils import TokenCountResponse token_counter_mock = ( @@ -4192,6 +4202,10 @@ class TestResponsesInputTokens: app.dependency_overrides[user_api_key_auth] = lambda: UserAPIKeyAuth(api_key="sk-test", request_route=path) app.dependency_overrides[_proxy_token_counter] = lambda: token_counter_mock app.dependency_overrides[_proxy_llm_router] = lambda: llm_router + if response_id_security is not None: + app.dependency_overrides[_proxy_response_id_security] = lambda: response_id_security + if managed_files is not None: + app.dependency_overrides[_proxy_managed_files_hook] = lambda: managed_files try: client = TestClient(app) response = client.post(path, json=body, headers={"Authorization": "Bearer sk-9876"}) @@ -4200,6 +4214,8 @@ class TestResponsesInputTokens: app.dependency_overrides.pop(user_api_key_auth, None) app.dependency_overrides.pop(_proxy_token_counter, None) app.dependency_overrides.pop(_proxy_llm_router, None) + app.dependency_overrides.pop(_proxy_response_id_security, None) + app.dependency_overrides.pop(_proxy_managed_files_hook, None) def test_string_input_returns_openai_input_tokens_shape(self): response, counter = self._post_input_tokens({"model": "gpt-4o", "input": "Hello, how are you?"}) @@ -4324,6 +4340,139 @@ class TestResponsesInputTokens: assert response.status_code == 200, response.text assert counter.await_args.kwargs["request"].tools == [{"type": "web_search"}] + assert counter.await_args.kwargs["responses_request"]["tools"] == [{"type": "web_search"}] + + @pytest.mark.parametrize( + ("tools", "expected"), + [ + ([5], {}), + ( + [5, {"type": "web_search"}], + {"tools": [{"type": "web_search"}], "tool_choice": "required", "parallel_tool_calls": False}, + ), + ], + ) + def test_tool_choice_leaves_the_count_with_the_tools_drop_params_drops( + self, tools: list[object], expected: dict[str, object] + ) -> None: + response, counter = self._post_input_tokens( + { + "model": "gpt-4o", + "input": "hi", + "tools": tools, + "tool_choice": "required", + "parallel_tool_calls": False, + "drop_params": True, + } + ) + + assert response.status_code == 200, response.text + sent = counter.await_args.kwargs["responses_request"] + assert {name: sent[name] for name in ("tools", "tool_choice", "parallel_tool_calls") if name in sent} == expected + + def test_previous_response_id_reaches_the_counter_authorized_next_to_the_id_the_client_held(self) -> None: + from litellm.types.utils import ADDRESSED_RESPONSE_ID_FIELD + + class DecodingSecurity: + def authorize_response_id(self, response_id: str, user_api_key_dict: object) -> str: + return {"resp_client_form": "resp_raw"}[response_id] + + response, counter = self._post_input_tokens( + {"model": "gpt-4o", "input": "hi", "previous_response_id": "resp_client_form"}, + response_id_security=DecodingSecurity(), + ) + + assert response.status_code == 200, response.text + responses_request: Final = counter.await_args.kwargs["responses_request"] + assert (responses_request["previous_response_id"], responses_request[ADDRESSED_RESPONSE_ID_FIELD]) == ( + "resp_raw", + "resp_client_form", + ) + + def test_managed_file_ids_reach_the_counter_with_the_mapping_inference_uses(self) -> None: + from litellm.integrations.custom_logger import CustomLogger + + mapping: Final = {"litellm-managed-file": {"deployment-a": "file-on-a"}} + + class ManagedFiles(CustomLogger): + async def async_pre_call_hook(self, user_api_key_dict, cache, data, call_type): + if call_type == "aresponses": + data["model_file_id_mapping"] = mapping + return None + + response, counter = self._post_input_tokens( + { + "model": "gpt-4o", + "input": [{"role": "user", "content": [{"type": "input_file", "file_id": "litellm-managed-file"}]}], + }, + managed_files=ManagedFiles(), + ) + + assert response.status_code == 200, response.text + assert counter.await_args.kwargs["responses_request"]["model_file_id_mapping"] == mapping + + @pytest.mark.parametrize("caller_mapping", [5, "lots", [1], {"file-x": {"deployment-a": 7}}]) + def test_a_caller_sent_model_file_id_mapping_does_not_break_the_count( + self, monkeypatch: pytest.MonkeyPatch, caller_mapping: object + ) -> None: + from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler + from litellm.llms.openai.responses.count_tokens import handler as openai_count_tokens_http + from litellm.proxy.proxy_server import count_request_tokens + + router: Final = litellm.Router( + model_list=[ + { + "model_name": "gpt-files", + "litellm_params": { + "model": "openai/gpt-4o-mini", + "api_key": "test-key", + "api_base": "https://count.test/v1", + }, + "model_info": {"id": "deployment-a"}, + } + ] + ) + monkeypatch.setattr(litellm.proxy.proxy_server, "llm_router", router) + sent: Final[list[object]] = [] # mutable-ok: collects what the mock peer receives + + def count_peer(request: httpx.Request) -> httpx.Response: + sent.append(json.loads(request.content)) + return httpx.Response(200, json={"object": "response.input_tokens", "input_tokens": 7}, request=request) + + with patch.object( + openai_count_tokens_http, + "get_async_httpx_client", + return_value=AsyncHTTPHandler(transport=httpx.MockTransport(count_peer)), + ): + response, _ = self._post_input_tokens( + {"model": "gpt-files", "input": "hi", "model_file_id_mapping": caller_mapping}, + counter=AsyncMock(side_effect=count_request_tokens), + llm_router=router, + ) + + assert (response.status_code, response.json().get("input_tokens")) == (200, 7), response.text + assert sent == [{"model": "gpt-4o-mini", "input": "hi"}] + + def test_a_managed_file_the_key_cannot_read_answers_403_without_a_count(self) -> None: + from litellm.integrations.custom_logger import CustomLogger + + denied: Final = "User u1 does not have access to the file litellm-managed-file" + + class ManagedFiles(CustomLogger): + async def async_pre_call_hook(self, user_api_key_dict, cache, data, call_type): + raise HTTPException(status_code=403, detail=denied) + + response, counter = self._post_input_tokens( + { + "model": "gpt-4o", + "input": [{"role": "user", "content": [{"type": "input_file", "file_id": "litellm-managed-file"}]}], + }, + managed_files=ManagedFiles(), + ) + + assert response.status_code == 403, response.text + assert response.json()["error"]["message"] == denied + counter.assert_not_awaited() def test_malformed_tools_follow_the_counted_deployment_even_when_fallbacks_are_configured(self) -> None: router: Final = litellm.Router( @@ -4345,6 +4494,7 @@ class TestResponsesInputTokens: assert response.status_code == 200, response.text assert counter.await_args.kwargs["request"].tools is None + assert "tools" not in counter.await_args.kwargs["responses_request"] def test_malformed_tools_for_a_model_outside_the_router_get_a_clean_400(self) -> None: router: Final = litellm.Router( diff --git a/tests/unit/proxy/spend_tracking/test_spend_counter_batch.py b/tests/unit/proxy/spend_tracking/test_spend_counter_batch.py index 1fddfaaa766..8ba79a45ff3 100644 --- a/tests/unit/proxy/spend_tracking/test_spend_counter_batch.py +++ b/tests/unit/proxy/spend_tracking/test_spend_counter_batch.py @@ -737,22 +737,3 @@ async def test_a_resized_reservation_is_carried_at_its_resized_cost_to_the_count assert reservation["reserved_cost"] == pytest.approx(0.1) assert redis.store["spend:key:hashed"] == pytest.approx(9.9) assert redis.store["spend:team:team"] == pytest.approx(2.1) - - -@pytest.mark.asyncio -async def test_update_cache_reads_an_object_redis_gained_right_after_a_batch_read_missed_it(monkeypatch): - """DualCache throttles repeated batch reads of a key that just missed; the per-object GET update_cache used to - issue never did, so its batched read must not either.""" - from litellm.caching.dual_cache import DualCache - - redis = CountingRedis() - cache = DualCache(redis_cache=redis) - monkeypatch.setattr(ps, "user_api_key_cache", cache) - assert await cache.async_batch_get_cache(keys=["team_id:team"]) == [None] - redis.store["team_id:team"] = {"spend": 1.0} - assert await cache.async_batch_get_cache(keys=["team_id:team"]) == [None] - - assert await ps._read_update_cache_values(keys=["team_id:team"], parent_otel_span=None) == { - "team_id:team": {"spend": 1.0} - } - assert redis.commands.count("MGET team_id:team") == 2 diff --git a/tests/unit/proxy/spend_tracking/test_spend_management_endpoints.py b/tests/unit/proxy/spend_tracking/test_spend_management_endpoints.py index ed8ae2db8b1..23bbe521670 100644 --- a/tests/unit/proxy/spend_tracking/test_spend_management_endpoints.py +++ b/tests/unit/proxy/spend_tracking/test_spend_management_endpoints.py @@ -3725,7 +3725,7 @@ class TestSpendLogsPayload: "model": "gpt-4o", "user": "", "team_id": "", - "metadata": '{"user_api_key_user_email": null, "actor_agent_id": null, "target_agent_id": null, "billing_agent_id": null, "agent_execution_mode": null, "verified_human_user_id": null, "applied_guardrails": [], "attempted_fallbacks": null, "original_model_group": null, "batch_models": null, "batch_successful_requests": null, "batch_failed_requests": null, "mcp_tool_call_metadata": null, "vector_store_request_metadata": null, "routing_decision": null, "internal_call_origin": null, "guardrail_information": null, "compression_savings": null, "litellm_gateway_injected_cache": null, "router_metadata": null, "autorouter_savings_estimate": null, "autorouter_baseline_observation": null, "azure_spillover": null, "used_client_oauth_token": null, "litellm_roi_estimator": false, "usage_object": {"completion_tokens": 20, "prompt_tokens": 10, "total_tokens": 30, "completion_tokens_details": null, "prompt_tokens_details": null}, "model_map_information": {"model_map_key": "gpt-4o", "model_map_value": {"key": "gpt-4o", "max_tokens": 16384, "max_input_tokens": 128000, "max_output_tokens": 16384, "input_cost_per_token": 2.5e-06, "cache_creation_input_token_cost": null, "cache_read_input_token_cost": 1.25e-06, "input_cost_per_character": null, "input_cost_per_token_above_128k_tokens": null, "input_cost_per_token_above_200k_tokens": null, "input_cost_per_query": null, "input_cost_per_second": null, "input_cost_per_audio_token": null, "input_cost_per_token_batches": 1.25e-06, "output_cost_per_token_batches": 5e-06, "output_cost_per_token": 1e-05, "output_cost_per_audio_token": null, "output_cost_per_character": null, "output_cost_per_token_above_128k_tokens": null, "output_cost_per_character_above_128k_tokens": null, "output_cost_per_token_above_200k_tokens": null, "output_cost_per_second": null, "output_cost_per_reasoning_token": null, "output_cost_per_image": null, "output_vector_size": null, "litellm_provider": "openai", "mode": "chat", "supports_system_messages": true, "supports_response_schema": true, "supports_vision": true, "supports_function_calling": true, "supports_tool_choice": true, "supports_assistant_prefill": false, "supports_prompt_caching": true, "supports_audio_input": false, "supports_audio_output": false, "supports_pdf_input": false, "supports_embedding_image_input": false, "supports_native_streaming": null, "supports_web_search": true, "supports_reasoning": false, "search_context_cost_per_query": {"search_context_size_low": 0.03, "search_context_size_medium": 0.035, "search_context_size_high": 0.05}, "tpm": null, "rpm": null, "supported_openai_params": ["frequency_penalty", "logit_bias", "logprobs", "top_logprobs", "max_tokens", "max_completion_tokens", "modalities", "prediction", "n", "presence_penalty", "seed", "stop", "stream", "stream_options", "temperature", "top_p", "tools", "tool_choice", "function_call", "functions", "max_retries", "extra_headers", "parallel_tool_calls", "audio", "response_format", "user"]}}, "additional_usage_values": {"completion_tokens_details": null, "prompt_tokens_details": null}}', + "metadata": '{"user_api_key_user_email": null, "actor_agent_id": null, "target_agent_id": null, "billing_agent_id": null, "agent_execution_mode": null, "verified_human_user_id": null, "applied_guardrails": [], "attempted_fallbacks": null, "original_model_group": null, "batch_models": null, "batch_successful_requests": null, "batch_failed_requests": null, "mcp_tool_call_metadata": null, "vector_store_request_metadata": null, "routing_decision": null, "internal_call_origin": null, "guardrail_information": null, "compression_savings": null, "litellm_gateway_injected_cache": null, "router_metadata": null, "autorouter_savings_estimate": null, "autorouter_baseline_observation": null, "azure_spillover": null, "used_client_oauth_token": null, "litellm_roi_estimator": false, "billed_retry_attempt": false, "usage_object": {"completion_tokens": 20, "prompt_tokens": 10, "total_tokens": 30, "completion_tokens_details": null, "prompt_tokens_details": null}, "model_map_information": {"model_map_key": "gpt-4o", "model_map_value": {"key": "gpt-4o", "max_tokens": 16384, "max_input_tokens": 128000, "max_output_tokens": 16384, "input_cost_per_token": 2.5e-06, "cache_creation_input_token_cost": null, "cache_read_input_token_cost": 1.25e-06, "input_cost_per_character": null, "input_cost_per_token_above_128k_tokens": null, "input_cost_per_token_above_200k_tokens": null, "input_cost_per_query": null, "input_cost_per_second": null, "input_cost_per_audio_token": null, "input_cost_per_token_batches": 1.25e-06, "output_cost_per_token_batches": 5e-06, "output_cost_per_token": 1e-05, "output_cost_per_audio_token": null, "output_cost_per_character": null, "output_cost_per_token_above_128k_tokens": null, "output_cost_per_character_above_128k_tokens": null, "output_cost_per_token_above_200k_tokens": null, "output_cost_per_second": null, "output_cost_per_reasoning_token": null, "output_cost_per_image": null, "output_vector_size": null, "litellm_provider": "openai", "mode": "chat", "supports_system_messages": true, "supports_response_schema": true, "supports_vision": true, "supports_function_calling": true, "supports_tool_choice": true, "supports_assistant_prefill": false, "supports_prompt_caching": true, "supports_audio_input": false, "supports_audio_output": false, "supports_pdf_input": false, "supports_embedding_image_input": false, "supports_native_streaming": null, "supports_web_search": true, "supports_reasoning": false, "search_context_cost_per_query": {"search_context_size_low": 0.03, "search_context_size_medium": 0.035, "search_context_size_high": 0.05}, "tpm": null, "rpm": null, "supported_openai_params": ["frequency_penalty", "logit_bias", "logprobs", "top_logprobs", "max_tokens", "max_completion_tokens", "modalities", "prediction", "n", "presence_penalty", "seed", "stop", "stream", "stream_options", "temperature", "top_p", "tools", "tool_choice", "function_call", "functions", "max_retries", "extra_headers", "parallel_tool_calls", "audio", "response_format", "user"]}}, "additional_usage_values": {"completion_tokens_details": null, "prompt_tokens_details": null}}', "cache_key": "Cache OFF", "spend": 0.00022500000000000002, "total_tokens": 30, diff --git a/tests/unit/proxy/test_common_request_processing.py b/tests/unit/proxy/test_common_request_processing.py index 679e1bfd85a..d742956bb59 100644 --- a/tests/unit/proxy/test_common_request_processing.py +++ b/tests/unit/proxy/test_common_request_processing.py @@ -25,7 +25,7 @@ from litellm.litellm_core_utils.bug_report import ( build_bug_report, ) from litellm.types.router import RouterRateLimitError, RouterRateLimitErrorBasic -from litellm.types.utils import CachingDetails +from litellm.types.utils import CachingDetails, Delta, ModelResponseStream, StreamingChoices from litellm.constants import ( CLIENT_REQUESTED_MODEL_SCOPE_KEY, MAX_LITELLM_CALL_ID_LENGTH, @@ -76,6 +76,8 @@ from litellm.proxy.hooks.model_max_budget_limiter import ( ) from litellm.proxy.utils import ProxyLogging from litellm.router import Router +from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper +from litellm.utils import ModelResponseListIterator from litellm.router_utils.add_retry_fallback_headers import prepare_response_for_header_attachment @@ -3549,6 +3551,30 @@ class TestOverrideOpenAIResponseModel: assert response_obj.model == "downstream-model" + def test_frozen_response_comes_back_as_a_copy_carrying_the_requested_model(self): + from litellm.types.extraction import ExtractionResponse + + response_obj = ExtractionResponse.model_validate( + { + "model": "cloudflare/@cf/cloudflare/clairic", + "answers": {"vendor": {"type": "text", "value": "Acme Tools"}}, + "truncated": False, + "usage": {"input_tokens": 52, "output_tokens": 0}, + } + ) + response_obj.set_hidden_params({"response_cost": 0.0000052}) + + stamped = _override_openai_response_model( + response_obj=response_obj, + requested_model="invoice-reader", + log_context="test_context", + ) + + assert isinstance(stamped, ExtractionResponse) + assert stamped.model == "invoice-reader" + assert stamped.answers == response_obj.answers + assert stamped.hidden_params["response_cost"] == 0.0000052 + class TestIsAzureModelRouterRequest: """Tests for _is_azure_model_router_request helper""" @@ -8480,9 +8506,11 @@ class _RecordingSuccessLogger(CustomLogger): def __init__(self): super().__init__() self.success_events = [] + self.logged: Final = asyncio.Event() async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): self.success_events.append({"kwargs": kwargs, "response_obj": response_obj}) + self.logged.set() class TestStreamingClientDisconnectBilling: @@ -8593,6 +8621,60 @@ class TestStreamingClientDisconnectBilling: assert getattr(partial_response, "service_tier") == "priority" assert partial_response.usage.total_tokens > 0 + @pytest.mark.asyncio + async def test_disconnect_after_finish_chunk_bills_the_estimate_when_the_provider_sent_no_usage(self): + model: Final = "gpt-4o" + messages: Final = [{"role": "user", "content": "Write a long sentence about a fox. " * 30}] + text: Final = "The quick brown fox jumps over the lazy dog. " * 20 + recorder: Final = _RecordingSuccessLogger() + logging_obj: Final = LiteLLMLoggingObj( + model=model, + messages=messages, + stream=True, + call_type="acompletion", + start_time=datetime.datetime(2025, 3, 3, 21, 38, 10), + litellm_call_id="no-usage-disconnect-call", + function_id="no-usage-disconnect-fn", + dynamic_async_success_callbacks=[recorder], + ) + logging_obj.update_environment_variables( + model=model, user=None, optional_params={}, litellm_params={"litellm_call_id": "no-usage-disconnect-call"} + ) + response: Final = CustomStreamWrapper( + completion_stream=ModelResponseListIterator( + model_responses=[ + ModelResponseStream(id="chatcmpl-no-usage", created=1741037890, model=model, choices=choices) + for choices in ( + [StreamingChoices(index=0, delta=Delta(role="assistant", content=text))], + [StreamingChoices(index=0, delta=Delta(content=""), finish_reason="stop")], + ) + ] + ), + model=model, + custom_llm_provider="openai", + logging_obj=logging_obj, + stream_options=None, + ) + stream_iter: Final = response.__aiter__() + first_chunk: Final = await stream_iter.__anext__() + finish_chunk: Final = await stream_iter.__anext__() + assert first_chunk.choices[0].finish_reason is None + assert finish_chunk.choices[0].finish_reason == "stop" + + billed: Final = await _bill_partial_streamed_spend_on_disconnect( + {"litellm_logging_obj": logging_obj}, + response, + ) + await asyncio.wait_for(recorder.logged.wait(), timeout=5) + + assert billed is True + assert len(recorder.success_events) == 1 + usage: Final = recorder.success_events[0]["response_obj"].usage + assert (usage.prompt_tokens, usage.completion_tokens) == ( + litellm.token_counter(model=model, messages=messages), + litellm.token_counter(model=model, text=text, count_response_tokens=True), + ) + @pytest.mark.asyncio async def test_completed_stream_does_not_double_bill_on_late_disconnect(self): recorder = _RecordingSuccessLogger() @@ -8953,6 +9035,118 @@ def _apply_stream_usage_tracking( ) + async def _start_partial_responses_stream(self, recorder: _RecordingSuccessLogger, *, relay_text: bool = True): + from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig + from litellm.responses.streaming_iterator import ResponsesAPIStreamingIterator + + mocked: Final = await litellm.aresponses( + model="gpt-4o-mini", + input="tell me a story", + mock_response="The codename is AZURE-FALCON-42 and the story is long.", + stream=True, + api_key="test-key", + ) + logging_obj: Final = mocked.logging_obj + logging_obj.dynamic_async_success_callbacks = [recorder] + stream: Final = ResponsesAPIStreamingIterator( + response=httpx.Response(200), + model="gpt-4o-mini", + responses_api_provider_config=OpenAIResponsesAPIConfig(), + logging_obj=logging_obj, + request_data={"model": "gpt-4o-mini", "input": "tell me a story"}, + custom_llm_provider="openai", + ) + created: Final = { + "type": "response.created", + "sequence_number": 0, + "response": { + "id": "resp_partial", + "object": "response", + "created_at": 1700000000.0, + "model": "gpt-4o-mini", + "status": "in_progress", + "output": [], + "parallel_tool_calls": True, + "tool_choice": "auto", + "tools": [], + "service_tier": "priority", + }, + } + delta: Final = { + "type": "response.output_text.delta", + "sequence_number": 1, + "item_id": "msg_partial", + "output_index": 0, + "content_index": 0, + "delta": "The codename is AZURE-FALCON-42", + } + for event in (created, delta) if relay_text else (created,): + stream._process_chunk(json.dumps(event)) + return stream + + async def _bill_and_wait(self, recorder: _RecordingSuccessLogger, streamed: object, logging_obj: object) -> bool: + billed: Final = await _bill_partial_streamed_spend_on_disconnect({"litellm_logging_obj": logging_obj}, streamed) + for _ in range(50): + if recorder.success_events: + break + await asyncio.sleep(0.1) + await asyncio.sleep(0.5) + return billed + + @pytest.mark.asyncio + async def test_disconnect_bills_partial_native_responses_stream_with_counted_usage(self): + from litellm.types.llms.openai import ResponsesAPIResponse + + recorder: Final = _RecordingSuccessLogger() + stream: Final = await self._start_partial_responses_stream(recorder) + billed: Final = await self._bill_and_wait(recorder, stream, stream.logging_obj) + + assert billed is True + assert len(recorder.success_events) == 1 + partial_response: Final = recorder.success_events[0]["response_obj"] + assert isinstance(partial_response, ResponsesAPIResponse) + assert partial_response.status == "incomplete" + assert getattr(partial_response, "service_tier") == "priority" + assert partial_response.usage.output_tokens == litellm.token_counter( + model="gpt-4o-mini", text="The codename is AZURE-FALCON-42" + ) + assert partial_response.usage.input_tokens > 0 + + @pytest.mark.asyncio + async def test_disconnect_bills_partial_default_route_messages_stream_through_the_responses_adapter(self): + from litellm.llms.anthropic.pass_through.responses_adapters.streaming_iterator import ( + AnthropicResponsesStreamWrapper, + ) + from litellm.router import FallbackAwareAnthropicMessagesStream + from litellm.types.llms.openai import ResponsesAPIResponse + + async def _sse_frames() -> AsyncGenerator[bytes, None]: + yield b"event: message_start\n\n" + + recorder: Final = _RecordingSuccessLogger() + stream: Final = await self._start_partial_responses_stream(recorder) + wrapper: Final = AnthropicResponsesStreamWrapper(responses_stream=stream, model="gpt-4o-mini") + streamed: Final = FallbackAwareAnthropicMessagesStream(_sse_frames(), wrapper.async_anthropic_sse_wrapper()) + billed: Final = await self._bill_and_wait(recorder, streamed, stream.logging_obj) + + assert billed is True + assert len(recorder.success_events) == 1 + partial_response: Final = recorder.success_events[0]["response_obj"] + assert isinstance(partial_response, ResponsesAPIResponse) + assert partial_response.usage.output_tokens == litellm.token_counter( + model="gpt-4o-mini", text="The codename is AZURE-FALCON-42" + ) + + @pytest.mark.asyncio + async def test_disconnect_before_any_responses_output_bills_nothing(self): + recorder: Final = _RecordingSuccessLogger() + stream: Final = await self._start_partial_responses_stream(recorder, relay_text=False) + billed: Final = await self._bill_and_wait(recorder, stream, stream.logging_obj) + + assert billed is False + assert recorder.success_events == [] + + class TestApplyStreamUsageTracking: @pytest.mark.parametrize( ("general_settings", "requested_stream_options", "expected_stream_options"), diff --git a/tests/unit/proxy/test_litellm_pre_call_utils.py b/tests/unit/proxy/test_litellm_pre_call_utils.py index 4647952312a..c2a5b01fe4e 100644 --- a/tests/unit/proxy/test_litellm_pre_call_utils.py +++ b/tests/unit/proxy/test_litellm_pre_call_utils.py @@ -3330,9 +3330,7 @@ def test_x_litellm_trace_id_keeps_the_body_session_beside_it_whatever_the_log_se assert data["litellm_trace_id"] == "req-trace-1" -@pytest.mark.parametrize( - "session_header", ["x-litellm-session-id", "x-claude-code-session-id", "x-session-id"] -) +@pytest.mark.parametrize("session_header", ["x-litellm-session-id", "x-claude-code-session-id", "x-session-id"]) @pytest.mark.parametrize("with_trace_header", [False, True], ids=["session-header-only", "beside-trace-header"]) def test_session_headers_still_beat_the_body_session_with_correlation_logging( monkeypatch: pytest.MonkeyPatch, session_header: str, with_trace_header: bool @@ -4756,6 +4754,43 @@ async def test_add_guardrails_from_policy_engine(): attachment_registry._initialized = False +@pytest.mark.asyncio +@pytest.mark.parametrize( + "caller_tags,inherited_tags,expected_guardrails", + [((), (), []), (("usecase:a",), (), ["usecase_guard"]), ((), ("usecase:a",), ["usecase_guard"])], +) +async def test_baggage_mapped_tags_match_tag_policies_only_when_the_caller_or_key_asked_for_them( + caller_tags, inherited_tags, expected_guardrails +): + from typing import cast + + from litellm.proxy.policy_engine.attachment_registry import get_attachment_registry + from litellm.proxy.policy_engine.policy_registry import get_policy_registry + from litellm.types.proxy.policy_engine import Policy, PolicyAttachment, PolicyGuardrails + + request = cast(Request, SimpleNamespace(state=SimpleNamespace(litellm_baggage_mapped_tags=("usecase:a",)))) + data = {"model": "gpt-4", "metadata": {"tags": [], "inherited_tags": inherited_tags}} + LiteLLMProxyRequestSetup.apply_authenticated_baggage_tags(request, data) + data["metadata"]["caller_tags"] = caller_tags + policy_registry = get_policy_registry() + attachment_registry = get_attachment_registry() + policy_registry._policies = {"usecase": Policy(guardrails=PolicyGuardrails(add=["usecase_guard"]))} + policy_registry._initialized = True + attachment_registry._attachments = [PolicyAttachment(policy="usecase", tags=["usecase:a"])] + attachment_registry._initialized = True + try: + await add_guardrails_from_policy_engine( + data=data, metadata_variable_name="metadata", user_api_key_dict=UserAPIKeyAuth(api_key="test-key") + ) + finally: + policy_registry._policies = {} + policy_registry._initialized = False + attachment_registry._attachments = [] + attachment_registry._initialized = False + assert "usecase:a" in data["metadata"]["tags"] + assert data["metadata"].get("guardrails", []) == expected_guardrails + + def test_match_and_track_policies_preserves_attachment_and_request_body_order(): from litellm.proxy.policy_engine.attachment_registry import AttachmentRegistry from litellm.types.proxy.policy_engine import Policy, PolicyMatchContext @@ -8245,6 +8280,7 @@ _PLANTED_STAMPS = { "attempted_fallbacks": 99, "original_model_group": "spoofed-group", "request_retry_count": -100, + "previous_models": [{"exception_type": "Timeout", "deployment_id": "spoofed", "attempted_retries": 101}], "_client_output_ceiling": {"api_base": "https://attacker.example"}, ROUTER_USAGE_COUNTED_TOKENS_METADATA_KEY: 10**9, "client_key": "client_value", @@ -8279,6 +8315,7 @@ async def test_add_litellm_data_to_request_strips_router_reserved_stamps_from_bo assert "original_model_group" not in updated["metadata"] assert "_client_output_ceiling" not in updated["metadata"] assert "request_retry_count" not in updated["metadata"] + assert "previous_models" not in updated["metadata"] assert ROUTER_USAGE_COUNTED_TOKENS_METADATA_KEY not in updated["metadata"] assert updated["metadata"]["client_key"] == "client_value" @@ -9310,7 +9347,9 @@ class TestResolveUserProviderCredentials: llm_router=self._router(), ) - assert data["secret_fields"]["user_provider_credentials"] == {"copilot-cred": "gho_secret"} + assert data["secret_fields"]["user_provider_credentials"] == { + "copilot-cred": {"access_token": "gho_secret", "github_host": "github.com"} + } assert data["secret_fields"]["user_provider_credentials_user_id"] == "user-a" # the shared fallback credential is never looked up call_where = table.find_many.await_args.kwargs["where"] @@ -9767,7 +9806,9 @@ class TestResolveUserProviderCredentials: team_id=None, llm_router=router, ) - assert data["secret_fields"]["user_provider_credentials"] == {"copilot-cred": "gho_secret"} + assert data["secret_fields"]["user_provider_credentials"] == { + "copilot-cred": {"access_token": "gho_secret", "github_host": "github.com"} + } call_where: Final = table.find_many.await_args.kwargs["where"] assert call_where == {"AND": ({"user_id": "user-a"}, {"credential_name": {"in": ["copilot-cred"]}})} @@ -10253,7 +10294,8 @@ async def test_secret_fields_user_provider_credentials_repr_hides_tokens(monkeyp assert isinstance(credentials, RedactedDict) assert "gho_secret" not in str(data) assert "gho_secret" not in repr(credentials) - assert credentials["copilot-cred"] == "gho_secret", "provider reads still get the token" + assert credentials["copilot-cred"]["access_token"] == "gho_secret", "provider reads still get the token" + assert credentials["copilot-cred"]["github_host"] == "github.com" @pytest.mark.asyncio @@ -10267,8 +10309,10 @@ async def test_header_mapped_user_id_cannot_load_another_users_connection(monkey from litellm.proxy.litellm_pre_call_utils import add_litellm_data_to_request _per_user_env(monkeypatch) - load = AsyncMock(return_value={"copilot-cred": "gho_user_a_token"}) - monkeypatch.setattr(upc, "aget_user_provider_tokens", load) + load = AsyncMock( + return_value={"copilot-cred": {"access_token": "gho_user_a_token", "github_host": "github.com"}} + ) + monkeypatch.setattr(upc, "aget_user_provider_credentials", load) router = Router( model_list=[ { @@ -10307,7 +10351,8 @@ async def test_header_mapped_user_id_cannot_load_another_users_connection(monkey called_user_ids = [call.kwargs["user_id"] for call in load.await_args_list] assert called_user_ids == ["user-a"], f"header-mapped user-b must never reach the token loader: {called_user_ids}" credentials = updated["secret_fields"]["user_provider_credentials"] - assert credentials["copilot-cred"] == "gho_user_a_token" + assert credentials["copilot-cred"]["access_token"] == "gho_user_a_token" + assert credentials["copilot-cred"]["github_host"] == "github.com" assert updated["secret_fields"]["user_provider_credentials_user_id"] == "user-a" @@ -10320,8 +10365,10 @@ async def test_per_user_token_resolution_uses_key_identity_without_header_mappin from litellm.proxy.litellm_pre_call_utils import add_litellm_data_to_request _per_user_env(monkeypatch) - load = AsyncMock(return_value={"copilot-cred": "gho_user_a_token"}) - monkeypatch.setattr(upc, "aget_user_provider_tokens", load) + load = AsyncMock( + return_value={"copilot-cred": {"access_token": "gho_user_a_token", "github_host": "github.com"}} + ) + monkeypatch.setattr(upc, "aget_user_provider_credentials", load) router = Router( model_list=[ { @@ -10357,4 +10404,114 @@ async def test_per_user_token_resolution_uses_key_identity_without_header_mappin called_user_ids = [call.kwargs["user_id"] for call in load.await_args_list] assert called_user_ids == ["user-a"] - assert updated["secret_fields"]["user_provider_credentials"]["copilot-cred"] == "gho_user_a_token" + assert updated["secret_fields"]["user_provider_credentials"]["copilot-cred"]["access_token"] == "gho_user_a_token" + assert updated["secret_fields"]["user_provider_credentials"]["copilot-cred"]["github_host"] == "github.com" + + +@pytest.mark.asyncio +@pytest.mark.parametrize("route", ["/v1/images/generations", "/v1/rerank"]) +async def test_raw_body_inference_keeps_authenticated_baggage_tags_for_spend(route): + from litellm.proxy.common_utils.http_parsing_utils import read_request_body + from litellm.proxy.proxy_server import ProxyConfig + + async def receive(): + return {"type": "http.request", "body": b'{"model":"qa-model","metadata":{"tags":["existing"]}}'} + + request = Request( + { + "type": "http", + "method": "POST", + "path": route, + "scheme": "http", + "server": ("localhost", 4000), + "query_string": b"", + "headers": [(b"content-type", b"application/json"), (b"baggage", b"entrypoint=a")], + }, + receive, + ) + admitted = await read_request_body(request) + await LiteLLMProxyRequestSetup.apply_baggage_tag_mappings_pre_auth( + request, + admitted, + {"request_tag_mappings": [{"key": "entrypoint", "tag_prefix": "usecase:"}]}, + None, + MagicMock(), + ) + reparsed = json.loads(await request.body()) + enriched = await add_litellm_data_to_request( + data=reparsed, + request=request, + user_api_key_dict=UserAPIKeyAuth(api_key="qa-key"), + proxy_config=ProxyConfig(), + general_settings={}, + ) + assert "usecase:a" in enriched["metadata"]["tags"] + assert "existing" in enriched["metadata"]["tags"] + assert "usecase:a" not in enriched["metadata"]["inherited_tags"] + assert enriched["metadata"]["tags"].count("usecase:a") == 1 + + +async def _string_tags_outcome(baggage_headers: tuple[tuple[bytes, bytes], ...]) -> str: + from litellm.proxy.common_utils.http_parsing_utils import read_request_body + from litellm.proxy.proxy_server import ProxyConfig + + async def receive(): + return {"type": "http.request", "body": b'{"model":"qa-model","metadata":{"tags":"client-tag"}}'} + + request: Final = Request( + { + "type": "http", + "method": "POST", + "path": "/v1/chat/completions", + "scheme": "http", + "server": ("localhost", 4000), + "query_string": b"", + "headers": [(b"content-type", b"application/json"), *baggage_headers], + }, + receive, + ) + admitted: Final = await read_request_body(request) + await LiteLLMProxyRequestSetup.apply_baggage_tag_mappings_pre_auth( + request, + admitted, + {"request_tag_mappings": [{"key": "tenant", "tag_prefix": "tenant:"}]}, + None, + MagicMock(), + ) + try: + enriched: Final = await add_litellm_data_to_request( + data=json.loads(await request.body()), + request=request, + user_api_key_dict=UserAPIKeyAuth(api_key="qa-key"), + proxy_config=ProxyConfig(), + general_settings={}, + ) + except Exception as error: + return type(error).__name__ + return repr(enriched["metadata"].get("tags")) + + +@pytest.mark.asyncio +async def test_string_metadata_tags_get_the_same_outcome_with_or_without_mapped_baggage(): + without_baggage: Final = await _string_tags_outcome(()) + with_baggage: Final = await _string_tags_outcome(((b"baggage", b"tenant=a"),)) + assert with_baggage == without_baggage + + +def test_applying_mapped_baggage_tags_again_leaves_the_metadata_unchanged(): + request: Final = Request({"type": "http", "headers": []}) + request.state.litellm_baggage_mapped_tags = ("tenant:a",) + once: Final[dict[str, object]] = {"metadata": {"tags": ["client-tag"]}} + twice: Final[dict[str, object]] = copy.deepcopy(once) + LiteLLMProxyRequestSetup.apply_authenticated_baggage_tags(request, once) + LiteLLMProxyRequestSetup.apply_authenticated_baggage_tags(request, twice) + LiteLLMProxyRequestSetup.apply_authenticated_baggage_tags(request, twice) + assert twice == once + + +def test_mapped_baggage_tags_keep_non_string_client_tags_as_sent(): + request: Final = Request({"type": "http", "headers": []}) + request.state.litellm_baggage_mapped_tags = ("tenant:a",) + data: Final[dict[str, object]] = {"metadata": {"tags": [1, {"team": "x"}, "client-tag", "client-tag"]}} + LiteLLMProxyRequestSetup.apply_authenticated_baggage_tags(request, data) + assert data["metadata"]["tags"] == [1, {"team": "x"}, "client-tag", "client-tag", "tenant:a"] diff --git a/tests/unit/proxy/test_moyai_endpoints.py b/tests/unit/proxy/test_moyai_endpoints.py index 92a1261d952..aecda75c661 100644 --- a/tests/unit/proxy/test_moyai_endpoints.py +++ b/tests/unit/proxy/test_moyai_endpoints.py @@ -186,11 +186,13 @@ async def test_exchange_without_database_fails_before_nonce(monkeypatch: pytest. @pytest.mark.asyncio async def test_exchange_rejects_tampered_signature(monkeypatch: pytest.MonkeyPatch) -> None: from fastapi import HTTPException - from litellm.proxy.moyai_endpoints import _sign_connect_code + from litellm.proxy.moyai_endpoints import _b64url, _b64url_decode, _sign_connect_code await _exchange_env(monkeypatch) code = _sign_connect_code("sk-master", "https://moyai.example.com", "admin-user") - tampered = code[:-2] + ("aa" if not code.endswith("aa") else "bb") + payload_b64, signature_b64 = code.split(".", 1) + signature = _b64url_decode(signature_b64) + tampered = f"{payload_b64}.{_b64url(bytes((signature[0] ^ 1,)) + signature[1:])}" with pytest.raises(HTTPException) as exc: await _exchange_call(tampered, "https://moyai.example.com") diff --git a/tests/unit/proxy/test_pricing_field_strip.py b/tests/unit/proxy/test_pricing_field_strip.py index 395fdc3a16e..3e9bee9217d 100644 --- a/tests/unit/proxy/test_pricing_field_strip.py +++ b/tests/unit/proxy/test_pricing_field_strip.py @@ -57,7 +57,7 @@ class TestStripClientPricingOverrides: # The strip set is built from the model so additions are picked up # automatically — this test guards against the model and the strip # set drifting apart if someone replaces the auto-derivation later. - assert _CLIENT_PRICING_CONTROL_FIELDS == frozenset(CustomPricingLiteLLMParams.model_fields.keys()) + assert _CLIENT_PRICING_CONTROL_FIELDS >= frozenset(CustomPricingLiteLLMParams.model_fields.keys()) # Sanity: the obvious top-level pricing fields are in the set. for field in ( "input_cost_per_token", @@ -82,6 +82,22 @@ class TestStripClientPricingOverrides: "messages": [{"role": "user", "content": "hi"}], } + def test_root_base_model_dropped(self): + # ``base_model`` picks the cost-map entry a spend row is priced with + # (success rows via the standard logging payload, billed failure rows + # via the failure lift), so a caller naming a cheaper model lowers + # their own recorded spend. + data = { + "model": "gpt-4o", + "messages": [{"role": "user", "content": "hi"}], + "base_model": "gpt-4o-mini", + } + _strip_client_pricing_overrides(data) + assert data == { + "model": "gpt-4o", + "messages": [{"role": "user", "content": "hi"}], + } + def test_metadata_model_info_dropped(self): data = { "model": "gpt-4", @@ -280,6 +296,7 @@ async def test_add_litellm_data_to_request_skips_strip_with_key_opt_in(): "model": "gpt-4", "messages": [{"role": "user", "content": "hi"}], "input_cost_per_token": 0.0001, + "base_model": "gpt-4o-mini", "metadata": {"model_info": {"output_cost_per_token": 0.0002}}, } @@ -295,6 +312,7 @@ async def test_add_litellm_data_to_request_skips_strip_with_key_opt_in(): assert updated["input_cost_per_token"] == 0.0001 assert updated["metadata"]["model_info"] == {"output_cost_per_token": 0.0002} + assert updated["base_model"] == "gpt-4o-mini" @pytest.mark.asyncio diff --git a/tests/unit/proxy/test_proxy_reject_logging.py b/tests/unit/proxy/test_proxy_reject_logging.py index 6e8545a58b3..b300d48808f 100644 --- a/tests/unit/proxy/test_proxy_reject_logging.py +++ b/tests/unit/proxy/test_proxy_reject_logging.py @@ -209,4 +209,4 @@ async def test_chat_completion_request_with_redaction(route, body, router, monke assert _test_logger.reaches_async_failure_event is True - assert _test_logger.reaches_sync_failure_event is True + assert _test_logger.reaches_sync_failure_event is False diff --git a/tests/unit/proxy/test_proxy_server_endpoints_and_startup.py b/tests/unit/proxy/test_proxy_server_endpoints_and_startup.py index 1de51fa71eb..bcd010e3eed 100644 --- a/tests/unit/proxy/test_proxy_server_endpoints_and_startup.py +++ b/tests/unit/proxy/test_proxy_server_endpoints_and_startup.py @@ -6192,53 +6192,24 @@ async def test_tag_cache_update_called(): """ Test that update_cache updates tag cache when tags are provided. """ - from litellm.caching.caching import DualCache - from litellm.proxy.proxy_server import user_api_key_cache + from litellm.caching.in_memory_cache import InMemoryCache + from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache - cache = DualCache() + cache = UserApiKeyCache(in_memory_cache=InMemoryCache()) + cache.in_memory_cache.set_cache("tag:test-tag", {"tag_name": "test-tag", "spend": 10.0}) - setattr( - litellm.proxy.proxy_server, - "user_api_key_cache", - cache, + await litellm.proxy.proxy_server.update_cache( + token=None, + user_id=None, + end_user_id=None, + team_id=None, + response_cost=5.0, + parent_otel_span=None, + tags=["test-tag"], + cache=cache, ) - mock_tag_obj = { - "tag_name": "test-tag", - "spend": 10.0, - } - - set_cache_called: Final = asyncio.Event() - - async def _record_set_cache(*args: object, **kwargs: object) -> None: - set_cache_called.set() - - with patch.object(cache, "async_batch_get_cache", new=AsyncMock(return_value=[mock_tag_obj])) as mock_get_cache: - with patch.object( - cache, "async_set_cache_pipeline", new=AsyncMock(side_effect=_record_set_cache) - ) as mock_set_cache: - await litellm.proxy.proxy_server.update_cache( - token=None, - user_id=None, - end_user_id=None, - team_id=None, - response_cost=5.0, - parent_otel_span=None, - tags=["test-tag"], - ) - - assert await asyncio.wait_for(set_cache_called.wait(), timeout=5) - - mock_get_cache.assert_awaited_once_with(keys=["tag:test-tag"], parent_otel_span=None, throttle_redis=False) - mock_set_cache.assert_awaited_once() - - call_args = mock_set_cache.call_args - cache_list = call_args.kwargs["cache_list"] - - assert len(cache_list) == 1 - cache_key, cache_value = cache_list[0] - assert cache_key == "tag:test-tag" - assert cache_value["spend"] == 15.0 + assert cache.in_memory_cache.get_cache("tag:test-tag")["spend"] == 15.0 @pytest.mark.asyncio @@ -6246,59 +6217,26 @@ async def test_tag_cache_update_multiple_tags(): """ Test that multiple tags are updated in cache. """ - from litellm.caching.caching import DualCache - from litellm.proxy.proxy_server import user_api_key_cache + from litellm.caching.in_memory_cache import InMemoryCache + from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache - cache = DualCache() + cache = UserApiKeyCache(in_memory_cache=InMemoryCache()) + cache.in_memory_cache.set_cache("tag:tag1", {"tag_name": "tag1", "spend": 10.0}) + cache.in_memory_cache.set_cache("tag:tag2", {"tag_name": "tag2", "spend": 20.0}) - setattr( - litellm.proxy.proxy_server, - "user_api_key_cache", - cache, + await litellm.proxy.proxy_server.update_cache( + token=None, + user_id=None, + end_user_id=None, + team_id=None, + response_cost=5.0, + parent_otel_span=None, + tags=["tag1", "tag2"], + cache=cache, ) - mock_tag1_obj = {"tag_name": "tag1", "spend": 10.0} - mock_tag2_obj = {"tag_name": "tag2", "spend": 20.0} - - async def mock_get_cache_side_effect(keys, **kwargs): - return [{"tag:tag1": mock_tag1_obj, "tag:tag2": mock_tag2_obj}.get(key) for key in keys] - - set_cache_called: Final = asyncio.Event() - - async def _record_set_cache(*args: object, **kwargs: object) -> None: - set_cache_called.set() - - with patch.object( - cache, "async_batch_get_cache", new=AsyncMock(side_effect=mock_get_cache_side_effect) - ) as mock_get_cache: - with patch.object( - cache, "async_set_cache_pipeline", new=AsyncMock(side_effect=_record_set_cache) - ) as mock_set_cache: - await litellm.proxy.proxy_server.update_cache( - token=None, - user_id=None, - end_user_id=None, - team_id=None, - response_cost=5.0, - parent_otel_span=None, - tags=["tag1", "tag2"], - ) - - assert await asyncio.wait_for(set_cache_called.wait(), timeout=5) - - mock_get_cache.assert_awaited_once_with(keys=["tag:tag1", "tag:tag2"], parent_otel_span=None, throttle_redis=False) - mock_set_cache.assert_awaited_once() - - call_args = mock_set_cache.call_args - cache_list = call_args.kwargs["cache_list"] - - assert len(cache_list) == 2 - - tag_updates = {cache_key: cache_value for cache_key, cache_value in cache_list} - assert "tag:tag1" in tag_updates - assert "tag:tag2" in tag_updates - assert tag_updates["tag:tag1"]["spend"] == 15.0 - assert tag_updates["tag:tag2"]["spend"] == 25.0 + assert cache.in_memory_cache.get_cache("tag:tag1")["spend"] == 15.0 + assert cache.in_memory_cache.get_cache("tag:tag2")["spend"] == 25.0 @pytest.mark.asyncio @@ -6309,41 +6247,25 @@ async def test_update_cache_pipeline_honors_user_api_key_cache_ttl(): a hardcoded 60s, otherwise every priced request resets an active key's cache entry back to 60s and the configured TTL is never observed. """ - from litellm.caching.caching import DualCache + from litellm.caching.in_memory_cache import InMemoryCache + from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache - original_cache = litellm.proxy.proxy_server.user_api_key_cache - cache = DualCache(default_in_memory_ttl=300) - setattr(litellm.proxy.proxy_server, "user_api_key_cache", cache) - set_cache_called: Final = asyncio.Event() + cache = UserApiKeyCache(in_memory_cache=InMemoryCache(clock=lambda: 1000.0), default_in_memory_ttl=300) + cache.in_memory_cache.cache_dict["tag:active-tag"] = {"tag_name": "active-tag", "spend": 1.0} - async def _record_set_cache(*args: object, **kwargs: object) -> None: - set_cache_called.set() + await litellm.proxy.proxy_server.update_cache( + token=None, + user_id=None, + end_user_id=None, + team_id=None, + response_cost=5.0, + parent_otel_span=None, + tags=["active-tag"], + cache=cache, + ) - try: - with patch.object( - cache, - "async_batch_get_cache", - new=AsyncMock(return_value=[{"tag_name": "active-tag", "spend": 1.0}]), - ): - with patch.object( - cache, "async_set_cache_pipeline", new=AsyncMock(side_effect=_record_set_cache) - ) as mock_set_cache: - await litellm.proxy.proxy_server.update_cache( - token=None, - user_id=None, - end_user_id=None, - team_id=None, - response_cost=5.0, - parent_otel_span=None, - tags=["active-tag"], - ) - - assert await asyncio.wait_for(set_cache_called.wait(), timeout=5) - - mock_set_cache.assert_awaited_once() - assert mock_set_cache.call_args.kwargs["ttl"] == 300 - finally: - setattr(litellm.proxy.proxy_server, "user_api_key_cache", original_cache) + assert cache.in_memory_cache.ttl_dict["tag:active-tag"] == 1300.0 + assert cache.in_memory_cache.get_cache("tag:active-tag")["spend"] == 6.0 @pytest.mark.asyncio @@ -6396,63 +6318,6 @@ async def test_spend_tracking_never_writes_the_auth_object_back(): setattr(litellm.proxy.proxy_server, "user_api_key_cache", original_cache) -@pytest.mark.asyncio -async def test_update_cache_global_proxy_spend_scalar_stays_shared(): - """ - The proxy-wide spend estimate must keep flowing to Redis when the spend - writeback goes per-pod: the global max_budget check reads the - ``{litellm_proxy_admin_name}:spend`` cache entry between authoritative DB - reloads, so keeping it pod-local would let traffic spread across replicas - exceed the proxy budget by roughly a factor of the replica count within a - cache TTL. Sharing this scalar is safe because it carries no limits or - permissions, so it cannot resurrect an invalidated auth blob. - """ - from litellm.caching.caching import DualCache - - admin_name = litellm.proxy.proxy_server.litellm_proxy_admin_name - global_key = "{}:spend".format(admin_name) - - def fake_get(key): - if key == "user-lit": - return {"user_id": "user-lit", "spend": 1.0} - if key == global_key: - return 10.0 - return None - - async def fake_batch_get(keys, **kwargs): - return [fake_get(key) for key in keys] - - original_cache = litellm.proxy.proxy_server.user_api_key_cache - cache = DualCache(default_in_memory_ttl=300) - setattr(litellm.proxy.proxy_server, "user_api_key_cache", cache) - try: - with patch.object(cache, "async_batch_get_cache", new=AsyncMock(side_effect=fake_batch_get)): - with patch.object(cache, "async_set_cache_pipeline", new=AsyncMock()) as mock_set_cache: - await litellm.proxy.proxy_server.update_cache( - token=None, - user_id="user-lit", - end_user_id=None, - team_id=None, - response_cost=5.0, - parent_otel_span=None, - ) - - pending = [t for t in asyncio.all_tasks() if t is not asyncio.current_task()] - if pending: - await asyncio.wait(pending, timeout=5) - - calls = mock_set_cache.await_args_list - local_keys = [k for c in calls if c.kwargs.get("local_only") is True for k, _ in c.kwargs["cache_list"]] - shared_keys = [ - k for c in calls if c.kwargs.get("local_only") is not True for k, _ in c.kwargs["cache_list"] - ] - assert "user-lit" in local_keys - assert global_key not in local_keys - assert shared_keys == [global_key] - finally: - setattr(litellm.proxy.proxy_server, "user_api_key_cache", original_cache) - - @pytest.mark.asyncio async def test_init_sso_settings_in_db(): """ @@ -8314,6 +8179,37 @@ async def test_update_general_settings_ignores_an_invalid_user_api_key_cache_max assert cache.get_cache(key="key-0", local_only=True) == {"token": "key-0"} +@pytest.mark.asyncio +async def test_update_general_settings_serves_an_invalid_db_request_tag_mappings_like_unset_until_fixed(monkeypatch): + from fastapi import Request + + from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup + from litellm.proxy.proxy_server import ProxyConfig + + proxy_config = ProxyConfig() + monkeypatch.setattr(proxy_server_module, "general_settings", proxy_config.settings) + + async def mapped_tags() -> list[str]: + data: Final[dict[str, object]] = {} + await LiteLLMProxyRequestSetup.apply_baggage_tag_mappings_pre_auth( + Request({"type": "http", "headers": [(b"baggage", b"tenant=a")]}), + data, + proxy_server_module.general_settings, + None, + MagicMock(), + ) + metadata: Final = data.get("metadata") + return list(metadata.get("tags", [])) if isinstance(metadata, dict) else [] + + await proxy_config._update_general_settings(db_general_settings={"request_tag_mappings": [{"key": "tenant"}]}) + assert await mapped_tags() == [] + + await proxy_config._update_general_settings( + db_general_settings={"request_tag_mappings": [{"key": "tenant", "tag_prefix": "tenant:", "required": True}]} + ) + assert await mapped_tags() == ["tenant:a"] + + @pytest.mark.asyncio async def test_update_general_settings_user_api_key_cache_max_size_yaml_wins(monkeypatch): """A DB value must not silently override an explicit YAML capacity on reload.""" @@ -15692,50 +15588,6 @@ async def test_spend_capture_rate_check_job_clears_the_gauge_once_the_setting_is ] -@pytest.mark.asyncio -async def test_update_cache_reads_and_writes_declare_the_auth_objects_key_family(): - """The post-call spend write-back reads and rewrites the cached auth objects, so its - Redis spans must read ``redis.mget auth_objects`` / ``redis.set auth_objects`` (the key - family the auth phase declares) and the global spend scalar ``redis.set spend_counters``, - never a bare ``redis.mget`` with no owner.""" - from litellm.caching.caching import DualCache - - original_cache = litellm.proxy.proxy_server.user_api_key_cache - cache = DualCache() - setattr(litellm.proxy.proxy_server, "user_api_key_cache", cache) - seen: list[tuple[str, str | None]] = [] - - async def _mget(keys, **_kwargs): - seen.append(("mget", current_service_target())) - return [{"user_id": "u1", "spend": 1.0} for _ in keys] - - async def _set_pipeline(**_kwargs): - seen.append(("set", current_service_target())) - - try: - with ( - patch.object(cache, "async_batch_get_cache", new=AsyncMock(side_effect=_mget)), - patch.object(cache, "async_set_cache_pipeline", new=AsyncMock(side_effect=_set_pipeline)), - ): - await litellm.proxy.proxy_server.update_cache( - token=None, - user_id="u1", - end_user_id=None, - team_id=None, - response_cost=2.0, - parent_otel_span=None, - ) - pending = [t for t in asyncio.all_tasks() if t is not asyncio.current_task()] - if pending: - await asyncio.wait(pending, timeout=5) - finally: - setattr(litellm.proxy.proxy_server, "user_api_key_cache", original_cache) - - assert seen, "update_cache must touch the cache for a priced user request" - assert {target for _, target in seen} == {"auth_objects"} - assert current_service_target() is None - - def test_feedback_box_is_one_json_record_in_json_mode(monkeypatch, capfd): """The feedback box is a dozen terminal lines; with JSON logs on it has to land as one parseable record, not a plaintext line per row.""" diff --git a/tests/unit/proxy/test_proxy_token_counter.py b/tests/unit/proxy/test_proxy_token_counter.py index 714d8bb77d7..fa0c9eda02d 100644 --- a/tests/unit/proxy/test_proxy_token_counter.py +++ b/tests/unit/proxy/test_proxy_token_counter.py @@ -9,7 +9,6 @@ import itertools import json import logging import threading -import time import traceback from collections.abc import Callable, Coroutine, Mapping from functools import partial @@ -57,8 +56,10 @@ from litellm.llms.bedrock.count_tokens.kimi_k3 import ( ) from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler from litellm.llms.gemini.count_tokens import handler as gemini_count_tokens_handler +from litellm.llms.openai.responses.count_tokens import handler as openai_count_tokens_http from litellm.llms.vertex_ai.vertex_ai_partner_models.count_tokens.handler import VertexAIPartnerModelsTokenCounter from litellm.proxy._types import ProxyException, TokenCountRequest, UserAPIKeyAuth +from litellm.responses.litellm_completion_transformation.session_handler import ResponsesSessionHandler from litellm.proxy.anthropic_endpoints.endpoints import ( count_tokens as anthropic_count_tokens, ) @@ -77,9 +78,16 @@ from litellm.proxy.proxy_server import ( count_request_tokens, token_counter, ) +from litellm.responses.utils import ResponsesAPIRequestUtils from litellm.rust_bridge.fork_guard import ForkedAfterNativeRuntimeStarted from litellm.types.secret_managers.main import KeyManagementSettings, KeyManagementSystem -from litellm.types.utils import SelectTokenizerResponse, TokenCountMessagesFormat, TokenCountResponse +from litellm.types.utils import ( + ADDRESSED_RESPONSE_ID_FIELD, + SelectTokenizerResponse, + SpecialEnums, + TokenCountMessagesFormat, + TokenCountResponse, +) def _hugging_face_offline() -> NoReturn: @@ -270,6 +278,50 @@ async def test_token_counter_reads_an_oidc_api_key_only_when_it_calls_the_provid assert str(tmp_path) not in excinfo.value.message +@pytest.mark.asyncio +async def test_native_openai_responses_count_sends_the_token_an_oidc_api_key_points_to( + tmp_path: Path, monkeypatch: pytest.MonkeyPatch +): + monkeypatch.setenv("LITELLM_OIDC_ALLOWED_CREDENTIAL_DIRS", str(tmp_path)) + token_file: Final = tmp_path / "token" + token_file.write_text("sa-token-from-file") + monkeypatch.setattr( + litellm.proxy.proxy_server, + "llm_router", + Router( + model_list=[ + { + "model_name": "gpt-oidc", + "litellm_params": { + "model": "openai/gpt-4o-mini", + "api_key": f"oidc/file/{token_file}", + "api_base": "https://count.test/v1", + }, + } + ] + ), + ) + authorizations: Final[list[str | None]] = [] # mutable-ok: collects what the mock peer receives + + def count_peer(request: httpx.Request) -> httpx.Response: + authorizations.append(request.headers.get("authorization")) + return httpx.Response(200, json={"object": "response.input_tokens", "input_tokens": 9}, request=request) + + with patch.object( + openai_count_tokens_http, + "get_async_httpx_client", + return_value=AsyncHTTPHandler(transport=httpx.MockTransport(count_peer)), + ): + result: Final = await count_request_tokens( + request=TokenCountRequest(model="gpt-oidc", messages=[{"role": "user", "content": "hello"}]), + call_endpoint=True, + responses_request={"model": "gpt-oidc", "input": "hello"}, + ) + + assert (result.error, result.total_tokens) == (False, 9) + assert authorizations == ["Bearer sa-token-from-file"] + + @pytest.mark.asyncio async def test_anthropic_messages_count_tokens_endpoint(): """ @@ -1567,6 +1619,7 @@ class _ScriptedCounter(BaseTokenCounter): messages_format: TokenCountMessagesFormat = "openai", output_format: JsonValue = None, context_management: object = None, + chat_params: object = None, ) -> TokenCountResponse | None: self.calls.append((model_to_use, messages, tools, system)) self.regions.append(None if deployment is None else deployment["litellm_params"].get("aws_region_name")) @@ -2676,7 +2729,7 @@ async def test_slow_cost_map_lookup_does_not_stall_other_requests_on_the_worker( request=TokenCountRequest(model="slow-lookup-model", messages=[{"role": "user", "content": "hi"}]) ) ) - await asyncio.to_thread(lookup_started.wait, 5) + assert await asyncio.to_thread(lookup_started.wait, 5) other_request_ran.set() await counting @@ -2800,17 +2853,24 @@ async def test_shipped_token_count_model_keeps_the_prompt_in_the_deployment_geog assert (counter.calls[0][0], counter.regions[0]) == ("bedrock_mantle/anthropic.claude-opus-5-5", counted_in) -class _SlowVault: +_LOOP_PROGRESS_TIMEOUT_SECONDS: Final = 5 + + +class _VaultWaitingForLoopProgress: + def __init__( + self, + lookup_started: threading.Event, + loop_progressed: threading.Event, + loop_progressed_during_lookup: threading.Event, + ) -> None: + self._lookup_started = lookup_started + self._loop_progressed = loop_progressed + self._loop_progressed_during_lookup = loop_progressed_during_lookup + def sync_read_secret(self, secret_name: str) -> None: - time.sleep(0.5) - - -async def _longest_stall(done: asyncio.Event) -> float: - if done.is_set(): - return 0.0 - started: Final = time.monotonic() - await asyncio.sleep(0.01) - return max(time.monotonic() - started, await _longest_stall(done)) + self._lookup_started.set() + if self._loop_progressed.wait(_LOOP_PROGRESS_TIMEOUT_SECONDS): + self._loop_progressed_during_lookup.set() @pytest.mark.asyncio @@ -2830,25 +2890,30 @@ async def test_region_lookup_for_a_shipped_count_model_leaves_the_event_loop_fre ), ) monkeypatch.setattr(proxy_server, "_get_provider_token_counter", bedrock_counter) - monkeypatch.setattr(litellm, "secret_manager_client", _SlowVault()) + lookup_started: Final = threading.Event() + loop_progressed: Final = threading.Event() + loop_progressed_during_lookup: Final = threading.Event() + monkeypatch.setattr( + litellm, + "secret_manager_client", + _VaultWaitingForLoopProgress(lookup_started, loop_progressed, loop_progressed_during_lookup), + ) monkeypatch.setattr(litellm, "_key_management_system", KeyManagementSystem.HASHICORP_VAULT) monkeypatch.setattr(litellm, "_key_management_settings", KeyManagementSettings(access_mode="read_only")) - done: Final = asyncio.Event() async def count() -> TokenCountResponse: - try: - return await token_counter( - request=TokenCountRequest(model="sonnet", messages=[{"role": "user", "content": "hi"}]), - call_endpoint=True, - ) - finally: - done.set() + return await token_counter( + request=TokenCountRequest(model="sonnet", messages=[{"role": "user", "content": "hi"}]), + call_endpoint=True, + ) - started: Final = time.monotonic() - stall, response = await asyncio.gather(_longest_stall(done), count()) + async def prove_loop_progress() -> None: + assert await asyncio.to_thread(lookup_started.wait, _LOOP_PROGRESS_TIMEOUT_SECONDS) + loop_progressed.set() - assert time.monotonic() - started >= 1.0 - assert stall < 0.4 + response, _ = await asyncio.gather(count(), prove_loop_progress()) + + assert loop_progressed_during_lookup.is_set() assert response.total_tokens == 447 @@ -3505,3 +3570,325 @@ async def test_call_endpoint_prompt_keeps_the_local_count_on_a_counter_that_need local.total_tokens, local.tokenizer_type, ) + + +_PINNED_COUNTS: Final = MappingProxyType({"deployment-a.test": 11, "deployment-b.test": 22}) + + +def _pinned_count_peer(request: httpx.Request) -> httpx.Response: + if json.loads(request.content).get("previous_response_id") != "resp_original": + return httpx.Response(400, json={"error": {"message": "previous_response_id was not decoded"}}, request=request) + return httpx.Response(200, json={"input_tokens": _PINNED_COUNTS[request.url.host]}, request=request) + + +@pytest.mark.asyncio +@pytest.mark.parametrize("pinned", ["deployment-a", "deployment-b"]) +async def test_responses_count_goes_to_the_deployment_that_served_the_previous_response( + monkeypatch: pytest.MonkeyPatch, pinned: str +) -> None: + router: Final = Router( + model_list=[ + { + "model_name": "gpt-group", + "litellm_params": { + "model": "openai/gpt-4o-mini", + "api_key": "test-key", + "api_base": f"https://{identity}.test/v1", + }, + "model_info": {"id": identity}, + } + for identity in ("deployment-a", "deployment-b") + ], + optional_pre_call_checks=["responses_api_deployment_check"], + ) + monkeypatch.setattr(litellm.proxy.proxy_server, "llm_router", router) + client: Final = AsyncHTTPHandler(transport=httpx.MockTransport(_pinned_count_peer)) + previous_response_id: Final = ResponsesAPIRequestUtils._build_responses_api_response_id( + "openai", pinned, "resp_original" + ) + + with patch.object(openai_count_tokens_http, "get_async_httpx_client", return_value=client): + counts: Final = [ + ( + await count_request_tokens( + request=TokenCountRequest(model="gpt-group", messages=[{"role": "user", "content": "again"}]), + call_endpoint=True, + responses_request={ + "model": "gpt-group", + "input": "again", + "previous_response_id": previous_response_id, + }, + ) + ).total_tokens + for _ in range(8) + ] + + assert counts == [_PINNED_COUNTS[f"{pinned}.test"]] * 8 + + +def _managed_file_id(provider_file_id: str, model_id: str) -> str: + unified: Final = SpecialEnums.LITELLM_MANAGED_FILE_COMPLETE_STR.value.format( + "application/pdf", "3f0c9a", "gpt-files", provider_file_id, model_id + ) + return base64.urlsafe_b64encode(unified.encode()).decode().rstrip("=") + + +@pytest.mark.asyncio +@pytest.mark.parametrize(("with_mapping", "expected_file_id"), [(False, "file-uploaded"), (True, "file-on-a")]) +async def test_responses_count_sends_openai_the_provider_file_id_inference_sends( + monkeypatch: pytest.MonkeyPatch, with_mapping: bool, expected_file_id: str +) -> None: + router: Final = Router( + model_list=[ + { + "model_name": "gpt-files", + "litellm_params": {"model": "openai/gpt-4o-mini", "api_key": "test-key", "api_base": "https://count.test/v1"}, + "model_info": {"id": "deployment-a"}, + } + ] + ) + monkeypatch.setattr(litellm.proxy.proxy_server, "llm_router", router) + managed_id: Final = _managed_file_id("file-uploaded", "deployment-a") + bodies: Final[list[dict[str, JsonValue]]] = [] # mutable-ok: collects what the mock peer receives + + def count_peer(request: httpx.Request) -> httpx.Response: + bodies.append(json.loads(request.content)) + return httpx.Response(200, json={"object": "response.input_tokens", "input_tokens": 49}, request=request) + + with patch.object( + openai_count_tokens_http, + "get_async_httpx_client", + return_value=AsyncHTTPHandler(transport=httpx.MockTransport(count_peer)), + ): + result: Final = await count_request_tokens( + request=TokenCountRequest(model="gpt-files", messages=[{"role": "user", "content": "Summarize"}]), + call_endpoint=True, + responses_request={ + "model": "gpt-files", + "input": [{"role": "user", "content": [{"type": "input_file", "file_id": managed_id}]}], + **({"model_file_id_mapping": {managed_id: {"deployment-a": "file-on-a"}}} if with_mapping else {}), + }, + ) + + assert (result.error, result.total_tokens) == (False, 49) + (body,) = bodies + assert body["input"] == [{"role": "user", "content": [{"type": "input_file", "file_id": expected_file_id}]}] + assert "model_file_id_mapping" not in body + + +_ANSWER_SCHEMA: Final[dict[str, JsonValue]] = { + "type": "object", + "properties": {"answer": {"type": "string"}}, + "required": ["answer"], + "additionalProperties": False, +} + + +@pytest.mark.asyncio +async def test_responses_count_on_claude_counts_the_chat_request_responses_inference_sends( + monkeypatch: pytest.MonkeyPatch, +) -> None: + router: Final = Router( + model_list=[ + { + "model_name": "claude-counted", + "litellm_params": { + "model": "anthropic/claude-opus-5-5", + "api_key": "test-key", + "api_base": "https://count-tokens.test", + }, + } + ] + ) + monkeypatch.setattr(litellm.proxy.proxy_server, "llm_router", router) + bodies: Final[list[dict[str, JsonValue]]] = [] # mutable-ok: collects what the mock peer receives + + def count_peer(request: httpx.Request) -> httpx.Response: + bodies.append(json.loads(request.content)) + return httpx.Response(200, json={"input_tokens": 77}, request=request) + + responses_tools: Final[list[dict[str, JsonValue]]] = [ + {"type": "function", "name": "get_weather", "parameters": {"type": "object", "properties": {}}}, + {"type": "web_search"}, + {"type": "file_search", "vector_store_ids": ["vs_docs"]}, + ] + with patch.object( + anthropic_count_tokens_handler, + "get_async_httpx_client", + return_value=AsyncHTTPHandler(transport=httpx.MockTransport(count_peer)), + ): + result: Final = await count_request_tokens( + request=TokenCountRequest( + model="claude-counted", messages=[{"role": "user", "content": "Weather?"}], tools=responses_tools + ), + call_endpoint=True, + responses_request={ + "model": "claude-counted", + "input": "Weather?", + "tools": responses_tools, + "tool_choice": "auto", + "text": {"format": {"type": "json_schema", "name": "answer", "schema": _ANSWER_SCHEMA}}, + "reasoning": {"effort": "low"}, + }, + ) + + assert (result.error, result.total_tokens) == (False, 77) + (body,) = bodies + tools: Final = body["tools"] + assert isinstance(tools, list) + tool_names: Final = [tool["name"] for tool in tools if isinstance(tool, dict)] + assert sorted(tool_names) == ["get_weather", "litellm_file_search", "web_search"] + assert any(isinstance(tool, dict) and str(tool.get("type")).startswith("web_search") for tool in tools) + assert body["tool_choice"] == {"type": "auto"} + output_config: Final = body["output_config"] + assert isinstance(output_config, dict) + assert output_config["format"] == {"type": "json_schema", "schema": _ANSWER_SCHEMA} + assert "thinking" in body + + +_WEATHER_TOOL: Final[dict[str, JsonValue]] = { + "type": "function", + "name": "get_weather", + "parameters": {"type": "object", "properties": {}}, +} + + +async def _claude_count( + monkeypatch: pytest.MonkeyPatch, + deployment_params: Mapping[str, JsonValue], + responses_request: Mapping[str, object], +) -> tuple[TokenCountResponse, list[dict[str, JsonValue]]]: + router: Final = Router( + model_list=[ + { + "model_name": "claude-counted", + "litellm_params": { + "model": "anthropic/claude-zeta-9", + "api_key": "test-key", + "api_base": "https://count-tokens.test", + **deployment_params, + }, + } + ] + ) + monkeypatch.setattr(litellm.proxy.proxy_server, "llm_router", router) + bodies: Final[list[dict[str, JsonValue]]] = [] # mutable-ok: collects what the mock peer receives + + def count_peer(request: httpx.Request) -> httpx.Response: + bodies.append(json.loads(request.content)) + return httpx.Response(200, json={"input_tokens": 77}, request=request) + + with patch.object( + anthropic_count_tokens_handler, + "get_async_httpx_client", + return_value=AsyncHTTPHandler(transport=httpx.MockTransport(count_peer)), + ): + result: Final = await count_request_tokens( + request=TokenCountRequest(model="claude-counted", messages=[{"role": "user", "content": "Weather?"}]), + call_endpoint=True, + responses_request={"model": "claude-counted", **responses_request}, + ) + return result, bodies + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("deployment_params", "request_params"), + [({"drop_params": True}, {}), ({}, {"drop_params": True})], + ids=["deployment", "request"], +) +async def test_responses_count_on_claude_downgrades_forced_tool_choice_under_drop_params( + monkeypatch: pytest.MonkeyPatch, + deployment_params: Mapping[str, JsonValue], + request_params: Mapping[str, JsonValue], +) -> None: + monkeypatch.setitem(litellm.model_cost, "claude-zeta-9", {"supports_forced_tool_use": False}) + + result, bodies = await _claude_count( + monkeypatch, + deployment_params, + {"input": "Weather?", "tools": [_WEATHER_TOOL], "tool_choice": "required", **request_params}, + ) + + assert (result.error, result.total_tokens) == (False, 77) + (body,) = bodies + assert body["tool_choice"] == {"type": "auto"} + + +@pytest.mark.asyncio +async def test_responses_count_on_claude_rejects_forced_tool_choice_without_drop_params( + monkeypatch: pytest.MonkeyPatch, +) -> None: + monkeypatch.setitem(litellm.model_cost, "claude-zeta-9", {"supports_forced_tool_use": False}) + + with pytest.raises(ProxyException) as rejected: + await _claude_count( + monkeypatch, {}, {"input": "Weather?", "tools": [_WEATHER_TOOL], "tool_choice": "required"} + ) + + assert (rejected.value.code, "forced tool use" in rejected.value.message) == ("400", True) + + +def _texts(message: JsonValue) -> list[str]: + assert isinstance(message, dict) + content: Final = message["content"] + if isinstance(content, str): + return [content] + assert isinstance(content, list) + return [str(block["text"]) for block in content if isinstance(block, dict) and "text" in block] + + +@pytest.mark.asyncio +async def test_responses_count_on_claude_counts_the_turns_previous_response_id_replays( + monkeypatch: pytest.MonkeyPatch, +) -> None: + stored_turn: Final = { + "request_id": "chatcmpl-stored", + "call_type": "aresponses", + "session_id": "session-1", + "proxy_server_request": {"input": "Who won in 1998?", "model": "claude-counted"}, + "response": { + "id": "chatcmpl-stored", + "object": "chat.completion", + "choices": [ + { + "index": 0, + "message": { + "role": "assistant", + "content": "The Bulls.", + "reasoning_content": "Chicago beat Utah in six games.", + }, + "finish_reason": "stop", + } + ], + }, + "status": "success", + } + + with patch.object( + ResponsesSessionHandler, + "get_all_spend_logs_for_previous_response_id", + new_callable=AsyncMock, + return_value=[stored_turn], + ) as spend_logs: + result, bodies = await _claude_count( + monkeypatch, + {}, + { + "input": "And in 1999?", + "previous_response_id": "chatcmpl-stored", + ADDRESSED_RESPONSE_ID_FIELD: "resp_client_form", + }, + ) + + assert (result.error, result.total_tokens) == (False, 77) + (body,) = bodies + messages: Final = body["messages"] + assert isinstance(messages, list) + assert list(itertools.chain.from_iterable(map(_texts, messages))) == [ + "Who won in 1998?", + "The Bulls.", + "And in 1999?", + ] + assert [sorted(message) for message in messages if isinstance(message, dict)] == [["content", "role"]] * 3 + spend_logs.assert_awaited_once_with("chatcmpl-stored", ("chatcmpl-stored", "resp_client_form")) diff --git a/tests/unit/proxy/test_proxy_utils.py b/tests/unit/proxy/test_proxy_utils.py index 2fc1b72c932..02f31bf07c6 100644 --- a/tests/unit/proxy/test_proxy_utils.py +++ b/tests/unit/proxy/test_proxy_utils.py @@ -2652,6 +2652,58 @@ async def test_post_call_failure_hook_auth_error_llm_api_route(): mock_handle_logging.assert_called_once() +class _InlineThread: + def __init__(self, target, args=(), kwargs=None, daemon=None) -> None: + self._run = lambda: target(*args, **(kwargs or {})) + + def start(self) -> None: + self._run() + + +@pytest.mark.asyncio +async def test_proxy_only_failure_gives_a_logger_with_both_failure_hooks_only_the_async_one( + monkeypatch: pytest.MonkeyPatch, +) -> None: + import types + + import litellm.proxy.utils as proxy_utils + from litellm.integrations.custom_logger import CustomLogger + from litellm.litellm_core_utils.litellm_logging import Logging + + hooks: Final[list[str]] = [] + + class Recorder(CustomLogger): + def log_failure_event(self, kwargs, response_obj, start_time, end_time) -> None: + hooks.append("sync_failure") + + async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time) -> None: + hooks.append("async_failure") + + for name in ("failure_callback", "_async_failure_callback"): + monkeypatch.setattr(litellm, name, []) + monkeypatch.setattr(proxy_utils, "threading", types.SimpleNamespace(Thread=_InlineThread)) + recorder: Final = Recorder() + logging_obj: Final = Logging( + model="gpt-4o-mini-tts", + messages=[{"role": "user", "content": "hi"}], + stream=False, + call_type="aspeech", + start_time=datetime.now(), + litellm_call_id="proxy-only-failure", + function_id="proxy-only-failure", + dynamic_failure_callbacks=[recorder], + dynamic_async_failure_callbacks=[recorder], + ) + logging_obj.update_environment_variables(litellm_params={"metadata": {}}, optional_params={}) + + await proxy_utils.ProxyLogging._dispatch_proxy_only_failure_handlers( + litellm_logging_obj=logging_obj, + original_exception=HTTPException(status_code=401, detail="Authentication Error: invalid user key"), + ) + + assert hooks == ["async_failure"] + + @pytest.mark.asyncio @pytest.mark.parametrize( "request_data, route, expected_call_type", diff --git a/tests/unit/proxy/test_proxy_utils_model_creation_and_error_logging.py b/tests/unit/proxy/test_proxy_utils_model_creation_and_error_logging.py index 77d17741a18..7b18cb3350c 100644 --- a/tests/unit/proxy/test_proxy_utils_model_creation_and_error_logging.py +++ b/tests/unit/proxy/test_proxy_utils_model_creation_and_error_logging.py @@ -828,6 +828,125 @@ class TestPostCallFailureHookEstimatesDispatchedInputTokens: assert expected_input_cost > 0 assert request_data["response_cost"] == pytest.approx(expected_input_cost) + @pytest.mark.asyncio + async def test_upstream_499_error_is_a_plain_failure_not_a_priced_disconnect(self): + """A provider answering HTTP 499 surfaces as litellm.APIError with status_code 499. Only the + proxy's own disconnect HTTPException means the caller hung up mid-generation, so the upstream + error keeps the estimated usage at zero cost like any other post-dispatch provider error.""" + from datetime import datetime + + from litellm.constants import LITELLM_HTTP_STATUS_CLIENT_DISCONNECTED + from litellm.types.utils import Usage + + request_data = { + "litellm_logging_obj": self._logging_obj( + { + "first_api_call_start_time": datetime(2026, 1, 1, 12, 0, 0), + "model": "gpt-3.5-turbo", + "messages": [{"role": "user", "content": "count these input tokens please"}], + "call_type": "acompletion", + } + ), + "metadata": {}, + } + await self._run( + request_data, + original_exception=litellm.APIError( + status_code=LITELLM_HTTP_STATUS_CLIENT_DISCONNECTED, + message="client closed request", + llm_provider="openai", + model="gpt-3.5-turbo", + ), + ) + + estimated = request_data["combined_usage_object"] + assert isinstance(estimated, Usage) + assert estimated.prompt_tokens > 0 + assert request_data["response_cost"] == 0.0 + + @pytest.mark.asyncio + async def test_client_disconnect_after_the_call_already_completed_is_not_priced_again(self): + """The LLM task finished and claimed its success log (which carries the real usage and cost) + while a during_call guardrail task was still pending, then the caller hung up. The 499 raised + for that disconnect must not price the prompt a second time.""" + from datetime import datetime + + from fastapi import HTTPException + + from litellm.constants import LITELLM_HTTP_STATUS_CLIENT_DISCONNECTED + from litellm.litellm_core_utils.litellm_logging import Logging + + logging_obj = Logging( + model="gpt-3.5-turbo", + messages=[{"role": "user", "content": "count these input tokens please"}], + stream=False, + call_type="acompletion", + start_time=datetime(2026, 1, 1, 12, 0, 0), + litellm_call_id="completed-before-disconnect", + function_id="fn", + ) + logging_obj.model_call_details.update( + { + "first_api_call_start_time": datetime(2026, 1, 1, 12, 0, 1), + "model": "gpt-3.5-turbo", + "messages": [{"role": "user", "content": "count these input tokens please"}], + "call_type": "acompletion", + } + ) + assert logging_obj.claim_async_success_log() + logging_obj.mark_async_success_log_enqueued() + request_data = {"litellm_logging_obj": logging_obj, "metadata": {}} + await self._run( + request_data, + original_exception=HTTPException( + status_code=LITELLM_HTTP_STATUS_CLIENT_DISCONNECTED, detail="Client disconnected the request" + ), + ) + + assert request_data.get("response_cost", 0.0) == 0.0 + + @pytest.mark.asyncio + async def test_client_disconnect_with_a_claimed_but_deferred_success_log_is_still_priced(self): + """With a post_call guardrail registered the success log is claimed but parked in the deferred slot, + and a 499 raised before the flush means it never runs. Nothing else bills that request, so the + failure row keeps the estimated input cost.""" + from datetime import datetime + + from fastapi import HTTPException + + from litellm.constants import LITELLM_HTTP_STATUS_CLIENT_DISCONNECTED + from litellm.litellm_core_utils.litellm_logging import Logging + + logging_obj = Logging( + model="gpt-3.5-turbo", + messages=[{"role": "user", "content": "count these input tokens please"}], + stream=False, + call_type="acompletion", + start_time=datetime(2026, 1, 1, 12, 0, 0), + litellm_call_id="deferred-success-never-flushed", + function_id="fn", + ) + logging_obj.model_call_details.update( + { + "first_api_call_start_time": datetime(2026, 1, 1, 12, 0, 1), + "model": "gpt-3.5-turbo", + "messages": [{"role": "user", "content": "count these input tokens please"}], + "call_type": "acompletion", + } + ) + logging_obj.defer_async_logging = True + assert logging_obj.claim_async_success_log() + logging_obj.enqueue_deferred_logging = lambda: None + request_data = {"litellm_logging_obj": logging_obj, "metadata": {}} + await self._run( + request_data, + original_exception=HTTPException( + status_code=LITELLM_HTTP_STATUS_CLIENT_DISCONNECTED, detail="Client disconnected the request" + ), + ) + + assert request_data["response_cost"] > 0.0 + @pytest.mark.asyncio async def test_client_disconnect_before_provider_handoff_is_not_priced(self): """A caller that hung up while the request was still in pre-call hooks never reached the @@ -1174,7 +1293,7 @@ from typing import cast import litellm from litellm.proxy.utils import create_model_info_response from litellm.types.router import DeploymentModelListingInfo -from litellm.types.utils import ModelInfo +from litellm.types.utils import ModelInfo, ModelResponse, Usage def _fake_model_info(**fields: object) -> ModelInfo: @@ -2084,6 +2203,31 @@ def test_usage_the_stream_already_recovered_beats_an_estimate(): assert lifted == (recovered, 0.25) +def test_a_failed_request_counts_its_instructions_even_after_logging_redacted_them(): + from litellm.constants import REDACTED_BY_LITELLM + from litellm.proxy.utils import _failure_usage_to_lift + + instructions: Final = "Review every changed line and explain each risk you find. " * 40 + call: Final[dict[str, object]] = { + "call_type": "aresponses", + "model": FAILURE_USAGE_MODEL, + "messages": ONE_USER_MESSAGE, + } + + def estimated_prompt_tokens(dispatched_instructions: str) -> int: + lifted: Final = _failure_usage_to_lift( + model_call_details={**call, "optional_params": {"instructions": dispatched_instructions}}, + request_body={"instructions": instructions}, + dispatched=True, + ) + assert lifted is not None + usage: Final = lifted[0] + assert isinstance(usage, Usage) + return usage.prompt_tokens + + assert estimated_prompt_tokens(REDACTED_BY_LITELLM) == estimated_prompt_tokens(instructions) + + def test_a_timed_out_request_on_an_unmapped_model_keeps_its_row_at_zero_cost(): from litellm.proxy.utils import _failure_usage_to_lift @@ -2135,6 +2279,240 @@ def test_a_timed_out_request_is_priced_at_the_rate_the_router_registered_for_the assert response_cost == pytest.approx(usage.prompt_tokens * 0.25) +@pytest.mark.parametrize(("prompt_tokens", "expected_rate"), [(1_000, 1e-7), (250_000, 5e-7)]) +def test_a_timed_out_request_is_priced_at_the_deployments_long_context_tier(monkeypatch, prompt_tokens, expected_rate): + """A deployment that declares ``input_cost_per_token_above_200k_tokens`` next to its standard rate + bills a 250k-token prompt at the tier on the success path; the failure row must not flatten it to + the standard rate.""" + from litellm.proxy.utils import _estimated_input_cost + + monkeypatch.setitem( + litellm.model_cost, + "dep-lit-f9-tiered", + { + "litellm_provider": "openai", + "mode": "chat", + "input_cost_per_token": 1e-7, + "input_cost_per_token_above_200k_tokens": 5e-7, + "output_cost_per_token": 4e-7, + }, + ) + + response_cost = _estimated_input_cost( + model_call_details={"model": FAILURE_USAGE_MODEL, "custom_llm_provider": "openai"}, + prompt_tokens=prompt_tokens, + deployment_id="dep-lit-f9-tiered", + base_model=None, + ) + + assert response_cost == pytest.approx(prompt_tokens * expected_rate) + + +def test_every_earlier_timed_out_attempt_is_billed_at_its_own_deployment_rate(monkeypatch): + """The router leaves one RetryAttemptRecord per failed attempt in metadata.previous_models, the + final attempt included; the earlier Timeout ones are billed (each at the deployment that served + it), a 429 attempt is not, and the final attempt is left to the failure row itself.""" + from litellm.proxy.utils import _billed_earlier_attempts + + monkeypatch.setitem( + litellm.model_cost, + "dep-lit145-b", + {"litellm_provider": "openai", "mode": "chat", "input_cost_per_token": 0.25, "output_cost_per_token": 1.0}, + ) + usage = litellm.Usage(prompt_tokens=24, completion_tokens=0, total_tokens=24) + public_rate, _ = litellm.cost_per_token(model=FAILURE_USAGE_MODEL, prompt_tokens=24) + + attempts = _billed_earlier_attempts( + model_call_details={"model": FAILURE_USAGE_MODEL, "custom_llm_provider": "openai"}, + litellm_params={ + "metadata": { + "attempted_retries": 3, + "previous_models": ( + {"deployment_id": "dep-lit145-a", "exception_type": "Timeout", "attempted_retries": 0}, + {"deployment_id": "dep-lit145-b", "exception_type": "RateLimitError", "attempted_retries": 1}, + {"deployment_id": "dep-lit145-b", "exception_type": "Timeout", "attempted_retries": 2}, + {"deployment_id": "dep-lit145-a", "exception_type": "Timeout", "attempted_retries": 3}, + ), + } + }, + estimated_usage=usage, + base_model=None, + deployment_id="dep-lit145-a", + ) + + assert [(a.attempted_retries, a.deployment_id) for a in attempts] == [(0, "dep-lit145-a"), (2, "dep-lit145-b")] + assert attempts[0].response_cost == pytest.approx(public_rate) + assert attempts[0].response_cost > 0 + assert attempts[1].response_cost == pytest.approx(24 * 0.25) + assert all(a.usage is usage for a in attempts) + + +def test_an_earlier_attempt_on_another_model_is_priced_at_that_models_rate_not_the_final_models(monkeypatch): + """After a fallback hop the final attempt runs on another model group, so the records of the group + that timed out first name their own deployment model (and its ``base_model`` when the deployment + name is not in the cost map). Each is billed at that model's input rate, not at the final model's.""" + from litellm.proxy.utils import _billed_earlier_attempts + + for pricing_model, provider, input_rate in ( + ("lit145-final-model", "openai", 0.5), + ("lit145-first-model", "openai", 0.02), + ("azure/lit145-first-model", "azure", 0.02), + ): + monkeypatch.setitem( + litellm.model_cost, + pricing_model, + {"litellm_provider": provider, "mode": "chat", "input_cost_per_token": input_rate, "output_cost_per_token": 1.0}, + ) + usage = litellm.Usage(prompt_tokens=24, completion_tokens=0, total_tokens=24) + + attempts = _billed_earlier_attempts( + model_call_details={"model": "openai/lit145-final-model", "custom_llm_provider": "openai"}, + litellm_params={ + "metadata": { + "attempted_retries": 1, + "model_info": {"id": "dep-lit145-final"}, + "previous_models": ( + { + "deployment_id": "dep-lit145-first", + "model": "openai/lit145-first-model", + "base_model": None, + "exception_type": "Timeout", + "attempted_retries": 0, + }, + { + "deployment_id": "dep-lit145-first-azure", + "model": "azure/lit145-first-deployment", + "base_model": "azure/lit145-first-model", + "exception_type": "Timeout", + "attempted_retries": 1, + }, + { + "deployment_id": "dep-lit145-final", + "model": "openai/lit145-final-model", + "base_model": None, + "exception_type": "Timeout", + "attempted_retries": 0, + }, + { + "deployment_id": "dep-lit145-final", + "model": "openai/lit145-final-model", + "base_model": None, + "exception_type": "Timeout", + "attempted_retries": 1, + }, + ), + } + }, + estimated_usage=usage, + base_model=None, + deployment_id="dep-lit145-final", + ) + + assert [(a.attempted_retries, a.deployment_id, a.response_cost) for a in attempts] == [ + (0, "dep-lit145-first", pytest.approx(24 * 0.02)), + (1, "dep-lit145-first-azure", pytest.approx(24 * 0.02)), + (0, "dep-lit145-final", pytest.approx(24 * 0.5)), + ] + + +def test_earlier_attempts_are_priced_from_the_prompt_estimate_not_the_final_streams_recovered_usage(): + """A final attempt whose stream broke mid-flight lifts its recovered usage (prompt plus the chunks + delivered); the earlier timed-out attempts never produced output, so they are priced from the + input-only estimate and not from that recovered usage.""" + from litellm.litellm_core_utils.get_litellm_params import get_litellm_params + from litellm.proxy.utils import _estimated_prompt_usage, _failure_fields_to_lift + + logging_obj = _dispatched_failure_logging_obj( + FAILURE_USAGE_MODEL, + get_litellm_params( + metadata={ + "attempted_retries": 1, + "model_info": {"id": "dep-lit145-final"}, + "previous_models": ( + {"deployment_id": "dep-lit145-final", "exception_type": "Timeout", "attempted_retries": 0}, + ), + } + ), + ) + recovered = litellm.Usage(prompt_tokens=500, completion_tokens=40, total_tokens=540) + logging_obj.model_call_details["combined_usage_object"] = recovered + logging_obj.model_call_details["response_cost"] = 0.01 + + lifted = _failure_fields_to_lift({"litellm_logging_obj": logging_obj}, provider_billed=True) + + estimate = _estimated_prompt_usage(logging_obj.model_call_details, {}) + assert lifted["combined_usage_object"] is recovered + assert [(a.usage.prompt_tokens, a.usage.completion_tokens) for a in lifted["billed_failed_attempts"]] == [ + (estimate.prompt_tokens, 0) + ] + assert estimate.prompt_tokens < recovered.prompt_tokens + + +def test_attempts_already_summed_into_the_final_row_are_not_lifted_again(): + """``Logging.carry_failed_attempt_usage`` moves a cut stream's usage into ``failed_attempts_usage`` + and the final row already bills every entry of it, so no earlier attempt gets a row of its own.""" + from litellm.litellm_core_utils.get_litellm_params import get_litellm_params + from litellm.proxy.utils import _failure_fields_to_lift + + logging_obj = _dispatched_failure_logging_obj( + FAILURE_USAGE_MODEL, + get_litellm_params( + metadata={ + "attempted_retries": 1, + "model_info": {"id": "dep-lit145-final"}, + "previous_models": ( + {"deployment_id": "dep-lit145-final", "exception_type": "Timeout", "attempted_retries": 0}, + ), + } + ), + ) + logging_obj.model_call_details["failed_attempts_usage"] = ( + (litellm.Usage(prompt_tokens=24, completion_tokens=3, total_tokens=27), 0.001), + ) + + lifted = _failure_fields_to_lift({"litellm_logging_obj": logging_obj}, provider_billed=True) + + assert lifted["combined_usage_object"].prompt_tokens == 24 + assert "billed_failed_attempts" not in lifted + + +def test_a_timed_out_attempt_from_the_group_a_fallback_left_is_still_billed(): + """After a fallback hop the router restarts ``attempted_retries`` at 0 for the new model group and + re-logs the attempt that exhausted the previous group, so the final attempt (dep-b, retry 1) must be + told from the previous group's attempt with the same count (dep-a, retry 1), and the re-logged + record must bill once.""" + from litellm.proxy.utils import _billed_earlier_attempts + + usage = litellm.Usage(prompt_tokens=24, completion_tokens=0, total_tokens=24) + + attempts = _billed_earlier_attempts( + model_call_details={"model": FAILURE_USAGE_MODEL, "custom_llm_provider": "openai"}, + litellm_params={ + "metadata": { + "attempted_retries": 1, + "model_info": {"id": "dep-lit145-b"}, + "previous_models": ( + {"deployment_id": "dep-lit145-a", "exception_type": "Timeout", "attempted_retries": 0}, + {"deployment_id": "dep-lit145-a", "exception_type": "Timeout", "attempted_retries": 1}, + {"deployment_id": "dep-lit145-a", "exception_type": "Timeout", "attempted_retries": 1}, + {"deployment_id": "dep-lit145-b", "exception_type": "Timeout", "attempted_retries": 0}, + {"deployment_id": "dep-lit145-b", "exception_type": "Timeout", "attempted_retries": 1}, + ), + } + }, + estimated_usage=usage, + base_model=None, + deployment_id="dep-lit145-b", + ) + + assert [(a.attempted_retries, a.deployment_id) for a in attempts] == [ + (0, "dep-lit145-a"), + (1, "dep-lit145-a"), + (0, "dep-lit145-b"), + ] + assert all(a.response_cost > 0 for a in attempts) + + def _dispatched_failure_logging_obj(model: str, litellm_params: dict) -> object: """A Logging object as the failure hook sees it: litellm_params in the real get_litellm_params() shape (every key present, ``litellm_metadata`` None on chat completions) and a first-handoff @@ -2200,6 +2578,34 @@ def test_an_azure_deployment_is_priced_at_its_base_model_like_the_success_path() assert lifted["response_cost"] == pytest.approx(expected_cost) +def test_an_unmapped_base_model_falls_back_to_the_deployment_model_like_the_success_path(): + """``completion_cost`` tries ``base_model`` first and then the deployment model, so a + ``model_info.base_model`` the cost map does not know still prices a success row at the + deployment model's rate. The failure row must land on the same number instead of $0.""" + from litellm.litellm_core_utils.get_litellm_params import get_litellm_params + from litellm.proxy.utils import _failure_fields_to_lift + + logging_obj = _dispatched_failure_logging_obj( + FAILURE_USAGE_MODEL, + get_litellm_params(metadata={"model_info": {"base_model": "not-in-the-cost-map"}}), + ) + logging_obj.model_call_details["custom_llm_provider"] = "openai" + + lifted = _failure_fields_to_lift({"litellm_logging_obj": logging_obj}, provider_billed=True) + + prompt_tokens = lifted["combined_usage_object"].prompt_tokens + success_cost = litellm.completion_cost( + completion_response=ModelResponse( + model=FAILURE_USAGE_MODEL, usage=Usage(prompt_tokens=prompt_tokens, completion_tokens=0) + ), + model=FAILURE_USAGE_MODEL, + custom_llm_provider="openai", + base_model="not-in-the-cost-map", + ) + assert success_cost > 0 + assert lifted["response_cost"] == pytest.approx(success_cost) + + def test_a_litellm_params_key_in_the_request_body_cannot_zero_the_timeout_price(): """``model_call_details`` is flattened with the request's optional_params, so a body key named ``litellm_params`` can land there; the deployment rate must come from the logging diff --git a/tests/unit/proxy/test_route_llm_request.py b/tests/unit/proxy/test_route_llm_request.py index 4e4e2f23950..8928b79bcd4 100644 --- a/tests/unit/proxy/test_route_llm_request.py +++ b/tests/unit/proxy/test_route_llm_request.py @@ -1,4 +1,6 @@ +import contextlib import httpx +import json import litellm import pytest import respx @@ -10,7 +12,8 @@ from unittest.mock import MagicMock from fastapi import HTTPException -from litellm.proxy.route_llm_request import ProxyModelNotFoundError, route_request +from litellm.proxy.route_llm_request import JSON_OBJECT_ADAPTER, ProxyModelNotFoundError, route_request +from litellm.types.router import RouterGeneralSettings @pytest.mark.parametrize( @@ -390,7 +393,6 @@ async def test_route_request_with_router_settings_override(): "timeout": 30, "model_group_retry_policy": {"gpt-3.5-turbo": {"RateLimitErrorRetries": 3}}, "routing_strategy": "least-busy", - # This setting should be ignored (not in per_request_settings list) "model_group_alias": {"alias": "real_model"}, }, } @@ -437,12 +439,12 @@ async def test_route_request_with_router_settings_override_no_router(): litellm.acompletion = mock_completion try: - response = await route_request(data, None, None, "acompletion") + response = await route_request(data, None, "gpt-3.5-turbo", "acompletion") assert response == "success" # Verify litellm.acompletion was called with merged settings call_kwargs = mock_completion.call_args[1] - assert call_kwargs["fallbacks"] == [{"gpt-3.5-turbo": ["gpt-4"]}] + assert "fallbacks" not in call_kwargs assert call_kwargs["num_retries"] == 3 finally: litellm.acompletion = original_acompletion @@ -1039,6 +1041,408 @@ async def test_route_request_override_enable_tag_filtering_beats_body_value(): assert call_kwargs["enable_tag_filtering"] is True +_PROXY_DEPLOYMENT_BASE: Final = "https://proxy-deployment.example/v1" +_HELLO_MESSAGES: Final = ({"role": "user", "content": "Hello"},) + + +def _chat_completion_response(model: str) -> httpx.Response: + return httpx.Response( + 200, + json={ + "id": "chatcmpl-1", + "object": "chat.completion", + "created": 1, + "model": model, + "choices": [{"index": 0, "message": {"role": "assistant", "content": "hi"}, "finish_reason": "stop"}], + "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2}, + }, + ) + + +def _proxy_router_with_two_model_groups() -> litellm.Router: + return litellm.Router( + model_list=[ + { + "model_name": model, + "litellm_params": { + "model": f"openai/{model}", + "api_key": "sk-proxy", + "api_base": _PROXY_DEPLOYMENT_BASE, + }, + } + for model in ("gpt-3.5-turbo", "gpt-4") + ], + num_retries=0, + ) + + +@pytest.mark.parametrize( + "extra_body, upstream_base", + [ + pytest.param({"api_key": "sk-from-pre-call-hook"}, _PROXY_DEPLOYMENT_BASE, id="clientside-api-key"), + pytest.param( + {"api_base": "https://clientside.example/v1"}, "https://clientside.example/v1", id="clientside-api-base" + ), + pytest.param({"model": "gpt-3.5-turbo,gpt-4"}, _PROXY_DEPLOYMENT_BASE, id="comma-separated-batch"), + pytest.param({"drop_params": True}, _PROXY_DEPLOYMENT_BASE, id="drop-params"), + pytest.param( + { + "user_config": { + "model_list": [ + { + "model_name": "gpt-3.5-turbo", + "litellm_params": { + "model": "openai/gpt-3.5-turbo", + "api_key": "sk-user-config", + "api_base": "https://user-config.example/v1", + }, + } + ], + } + }, + "https://user-config.example/v1", + id="user-config", + ), + ], +) +@pytest.mark.asyncio +async def test_route_request_never_forwards_router_settings_override( + monkeypatch: pytest.MonkeyPatch, extra_body: dict[str, object], upstream_base: str +) -> None: + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + data: Final = { + "model": "gpt-3.5-turbo", + "messages": list(_HELLO_MESSAGES), + "router_settings_override": {"num_retries": 2, "timeout": None}, + **extra_body, + } + + with respx.mock(assert_all_called=False) as respx_mock: + primary: Final = respx_mock.post(f"{upstream_base}/chat/completions", json__model="gpt-3.5-turbo").mock( + side_effect=[ + httpx.Response(500, json={"error": {"message": "boom"}}), + _chat_completion_response("gpt-3.5-turbo"), + ] + ) + respx_mock.post(f"{upstream_base}/chat/completions", json__model="gpt-4").mock( + return_value=_chat_completion_response("gpt-4") + ) + response: Final = await (await route_request(data, _proxy_router_with_two_model_groups(), None, "acompletion")) + + primary_response: Final = response[0] if isinstance(response, list) else response + sent_bodies: Final = [json.loads(call.request.content) for call in primary.calls] + assert not [body for body in sent_bodies if "router_settings_override" in body], sent_bodies + assert primary_response._hidden_params["additional_headers"]["x-litellm-max-retries"] == 2, ( + primary_response._hidden_params + ) + + +@pytest.mark.parametrize("extra_body", [{}, {"api_key": "sk-from-pre-call-hook"}], ids=["router", "clientside-api-key"]) +@pytest.mark.asyncio +async def test_route_request_treats_null_router_settings_override_as_absent( + monkeypatch: pytest.MonkeyPatch, extra_body: dict[str, str] +) -> None: + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + data: Final = { + "model": "gpt-3.5-turbo", + "messages": list(_HELLO_MESSAGES), + "router_settings_override": None, + **extra_body, + } + + with respx.mock(assert_all_called=False) as respx_mock: + upstream: Final = respx_mock.post(f"{_PROXY_DEPLOYMENT_BASE}/chat/completions").mock( + return_value=_chat_completion_response("gpt-3.5-turbo") + ) + response: Final = await (await route_request(data, _proxy_router_with_two_model_groups(), None, "acompletion")) + + assert response.choices[0].message.content == "hi", response + assert "router_settings_override" not in json.loads(upstream.calls.last.request.content) + + +@pytest.mark.parametrize( + "global_drop_params, extra_body", + [ + pytest.param(False, {}, id="drop-params-off"), + pytest.param(False, {"drop_params": False}, id="request-drop-params-false"), + ], +) +@pytest.mark.parametrize("override", ["fallbacks", ["num_retries"], 3]) +@pytest.mark.asyncio +async def test_route_request_rejects_non_object_router_settings_override( + monkeypatch: pytest.MonkeyPatch, global_drop_params: bool, extra_body: dict[str, bool | str], override: object +) -> None: + from litellm.proxy._types import ProxyException + + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + monkeypatch.setattr(litellm, "drop_params", global_drop_params) + data: Final = { + "model": "gpt-3.5-turbo", + "messages": list(_HELLO_MESSAGES), + "router_settings_override": override, + **extra_body, + } + + with respx.mock(assert_all_called=False) as respx_mock: + upstream: Final = respx_mock.post(f"{_PROXY_DEPLOYMENT_BASE}/chat/completions").mock( + return_value=_chat_completion_response("gpt-3.5-turbo") + ) + with pytest.raises(ProxyException) as exc_info: + await route_request(data, _proxy_router_with_two_model_groups(), None, "acompletion") + + assert exc_info.value.code == "400" + assert exc_info.value.param == "router_settings_override" + assert upstream.call_count == 0 + + +@pytest.mark.parametrize( + "global_drop_params, extra_body", + [ + pytest.param(False, {"drop_params": True}, id="request-drop-params"), + pytest.param(True, {}, id="global-drop-params"), + pytest.param(True, {"drop_params": False}, id="global-drop-params-with-request-false"), + pytest.param(False, {"drop_params": "true"}, id="request-drop-params-string"), + ], +) +@pytest.mark.parametrize("override", ["fallbacks", ["num_retries"], 3]) +@pytest.mark.asyncio +async def test_route_request_drops_non_object_router_settings_override_under_drop_params( + monkeypatch: pytest.MonkeyPatch, global_drop_params: bool, extra_body: dict[str, bool | str], override: object +) -> None: + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + monkeypatch.setattr(litellm, "drop_params", global_drop_params) + data: Final = { + "model": "gpt-3.5-turbo", + "messages": list(_HELLO_MESSAGES), + "router_settings_override": override, + **extra_body, + } + + with respx.mock(assert_all_called=False) as respx_mock: + upstream: Final = respx_mock.post(f"{_PROXY_DEPLOYMENT_BASE}/chat/completions").mock( + return_value=_chat_completion_response("gpt-3.5-turbo") + ) + response: Final = await (await route_request(data, _proxy_router_with_two_model_groups(), None, "acompletion")) + + assert response.choices[0].message.content == "hi", response + assert upstream.call_count == 1 + assert "router_settings_override" not in json.loads(upstream.calls.last.request.content) + + +@pytest.mark.parametrize( + "user_config_settings, expected_upstream_calls", + [ + pytest.param({}, 2, id="key-setting-fills-unset-user-config-setting"), + pytest.param({"num_retries": 0}, 1, id="user-config-setting-beats-key-setting"), + ], +) +@pytest.mark.asyncio +async def test_route_request_user_config_router_settings_beat_key_settings( + monkeypatch: pytest.MonkeyPatch, user_config_settings: dict[str, int], expected_upstream_calls: int +) -> None: + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + user_config_base: Final = "https://user-config.example/v1" + data: Final = { + "model": "gpt-3.5-turbo", + "messages": list(_HELLO_MESSAGES), + "router_settings_override": {"num_retries": 1}, + "user_config": { + **user_config_settings, + "model_list": [ + { + "model_name": "gpt-3.5-turbo", + "litellm_params": { + "model": "openai/gpt-3.5-turbo", + "api_key": "sk-user-config", + "api_base": user_config_base, + }, + } + ], + }, + } + + with respx.mock(assert_all_called=False) as respx_mock: + upstream: Final = respx_mock.post(f"{user_config_base}/chat/completions").mock( + side_effect=[ + httpx.Response(500, json={"error": {"message": "boom"}}), + _chat_completion_response("gpt-3.5-turbo"), + ] + ) + with contextlib.suppress(litellm.InternalServerError): + await (await route_request(data, _proxy_router_with_two_model_groups(), None, "acompletion")) + + assert upstream.call_count == expected_upstream_calls + + +@pytest.mark.parametrize( + "extra_body", + [ + pytest.param({}, id="no-key-settings"), + pytest.param({"router_settings_override": {"num_retries": 2}}, id="key-settings"), + ], +) +@pytest.mark.asyncio +async def test_route_request_refuses_blocked_model_whether_or_not_key_has_router_settings( + extra_body: dict[str, dict[str, int]], +) -> None: + router: Final = litellm.Router( + model_list=[ + { + "model_name": "gpt-3.5-turbo", + "litellm_params": {"model": "openai/gpt-3.5-turbo", "api_key": "sk-proxy"}, + "model_info": {"blocked": True}, + } + ], + ) + data: Final = {"model": "gpt-3.5-turbo", "messages": list(_HELLO_MESSAGES), **extra_body} + + with pytest.raises(litellm.PermissionDeniedError): + await route_request(data, router, None, "acompletion") + + +@pytest.mark.parametrize( + "credential", + [ + pytest.param({"api_key": "sk-from-pre-call-hook"}, id="clientside-api-key"), + pytest.param({"api_base": _PROXY_DEPLOYMENT_BASE}, id="clientside-api-base"), + ], +) +@pytest.mark.parametrize( + "fallback_field, upstream_error", + [ + pytest.param("fallbacks", httpx.Response(500, json={"error": {"message": "boom"}}), id="fallbacks"), + pytest.param( + "context_window_fallbacks", + httpx.Response( + 400, + json={ + "error": { + "message": "This model's maximum context length is 16385 tokens", + "code": "context_length_exceeded", + } + }, + ), + id="context-window-fallbacks", + ), + pytest.param( + "content_policy_fallbacks", + httpx.Response( + 400, + json={ + "error": { + "message": "Your request was rejected by the content filter", + "type": "invalid_request_error", + "code": "content_policy_violation", + } + }, + ), + id="content-policy-fallbacks", + ), + ], +) +@pytest.mark.asyncio +async def test_route_request_applies_override_fallbacks_when_request_carries_credentials( + monkeypatch: pytest.MonkeyPatch, + credential: dict[str, str], + fallback_field: str, + upstream_error: httpx.Response, +) -> None: + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + data: Final = { + "model": "gpt-3.5-turbo", + "messages": list(_HELLO_MESSAGES), + "router_settings_override": {fallback_field: [{"gpt-3.5-turbo": ["gpt-4"]}]}, + **credential, + } + + with respx.mock(assert_all_called=False) as respx_mock: + respx_mock.post(f"{_PROXY_DEPLOYMENT_BASE}/chat/completions", json__model="gpt-3.5-turbo").mock( + return_value=upstream_error + ) + fallback: Final = respx_mock.post(f"{_PROXY_DEPLOYMENT_BASE}/chat/completions", json__model="gpt-4").mock( + return_value=_chat_completion_response("gpt-4") + ) + response: Final = await (await route_request(data, _proxy_router_with_two_model_groups(), None, "acompletion")) + + assert fallback.call_count == 1, [str(call.request.url) for call in respx_mock.calls] + assert "router_settings_override" not in json.loads(fallback.calls.last.request.content) + assert response.choices[0].message.content == "hi", response + + +@pytest.mark.parametrize( + "router_only_setting", + [ + pytest.param({"model_group_retry_policy": {"gpt-4": {"TimeoutErrorRetries": 1}}}, id="model-group-retry-policy"), + pytest.param({"context_window_fallbacks": [{"gpt-4": ["gpt-3.5-turbo"]}]}, id="context-window-fallbacks"), + pytest.param({"content_policy_fallbacks": [{"gpt-4": ["gpt-3.5-turbo"]}]}, id="content-policy-fallbacks"), + ], +) +@pytest.mark.asyncio +async def test_route_request_keeps_router_only_override_settings_out_of_pass_through_provider_body( + monkeypatch: pytest.MonkeyPatch, router_only_setting: dict[str, object] +) -> None: + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + monkeypatch.setenv("OPENAI_API_KEY", "sk-pass-through") + monkeypatch.delenv("OPENAI_BASE_URL", raising=False) + monkeypatch.delenv("OPENAI_API_BASE", raising=False) + router: Final = litellm.Router( + model_list=[ + { + "model_name": "gpt-4", + "litellm_params": {"model": "openai/gpt-4", "api_key": "sk-proxy", "api_base": _PROXY_DEPLOYMENT_BASE}, + } + ], + router_general_settings=RouterGeneralSettings(pass_through_all_models=True), + ) + data: Final = { + "model": "openai/gpt-pass-through", + "messages": list(_HELLO_MESSAGES), + "router_settings_override": router_only_setting, + } + + with respx.mock(assert_all_called=True) as respx_mock: + upstream: Final = respx_mock.post("https://api.openai.com/v1/chat/completions").mock( + return_value=_chat_completion_response("gpt-pass-through") + ) + await (await route_request(data, router, None, "acompletion")) + + assert set(router_only_setting).isdisjoint(JSON_OBJECT_ADAPTER.validate_json(upstream.calls.last.request.content)) + + +@pytest.mark.asyncio +async def test_route_request_keeps_key_fallbacks_out_of_pass_through_provider_body( + monkeypatch: pytest.MonkeyPatch, +) -> None: + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + monkeypatch.setenv("OPENAI_API_KEY", "sk-pass-through") + monkeypatch.delenv("OPENAI_BASE_URL", raising=False) + monkeypatch.delenv("OPENAI_API_BASE", raising=False) + router: Final = litellm.Router( + model_list=[ + { + "model_name": "gpt-4", + "litellm_params": {"model": "openai/gpt-4", "api_key": "sk-proxy", "api_base": _PROXY_DEPLOYMENT_BASE}, + } + ], + router_general_settings=RouterGeneralSettings(pass_through_all_models=True), + ) + data: Final = { + "model": "openai/gpt-pass-through", + "messages": list(_HELLO_MESSAGES), + "router_settings_override": {"fallbacks": [{"gpt-4": ["gpt-4"]}], "num_retries": 0}, + } + + with respx.mock(assert_all_called=True) as respx_mock: + upstream: Final = respx_mock.post("https://api.openai.com/v1/chat/completions").mock( + return_value=httpx.Response(500, json={"error": {"message": "upstream down"}}) + ) + with pytest.raises(litellm.InternalServerError): + await (await route_request(data, router, None, "acompletion")) + + provider_bodies: Final = tuple(JSON_OBJECT_ADAPTER.validate_json(call.request.content) for call in upstream.calls) + assert provider_bodies and all("gpt-4" not in body for body in provider_bodies), provider_bodies + + @pytest.mark.parametrize( "route_type, param, route", [ @@ -1524,6 +1928,54 @@ async def test_route_request_read_through_recovers_model_created_on_sibling_repl assert table.find_many_wheres[0] == {"model_name": model_name} +def _tagged_db_model_row(model_name: str, tag: str, order: int) -> SimpleNamespace: + return SimpleNamespace( + model_id=f"{model_name}-{tag}-id", + model_name=model_name, + litellm_params={ + "model": "openai/gpt-4o", + "api_key": "fake", + "mock_response": f"{tag}-deployment", + "tags": [tag], + "order": order, + }, + model_info={}, + blocked=False, + ) + + +@pytest.mark.asyncio +async def test_route_request_read_through_retry_keeps_key_tag_filtering(monkeypatch: pytest.MonkeyPatch) -> None: + import litellm.proxy.proxy_server as proxy_server + + model_name: Final = "sibling-replica-model-for-key-with-tag-filtering" + router: Final = litellm.Router( + model_list=[{"model_name": "some-other-model", "litellm_params": {"model": "openai/gpt-4o", "api_key": "fake"}}] + ) + fake_prisma, _ = _fake_prisma_client_with_models( + [_tagged_db_model_row(model_name, "free", order=1), _tagged_db_model_row(model_name, "paid", order=2)] + ) + monkeypatch.setattr(proxy_server, "prisma_client", fake_prisma) + monkeypatch.setattr(proxy_server, "store_model_in_db", True) + monkeypatch.setattr(proxy_server, "llm_router", router) + + response: Final = await ( + await route_request( + { + "model": model_name, + "messages": [{"role": "user", "content": "hi"}], + "metadata": {"tags": ["paid"]}, + "router_settings_override": {"enable_tag_filtering": True}, + }, + router, + None, + "acompletion", + ) + ) + + assert response.choices[0].message.content == "paid-deployment" + + @pytest.mark.asyncio async def test_route_request_unknown_model_raises_and_hits_db_once_within_ttl(monkeypatch): import litellm diff --git a/tests/unit/proxy/test_spend_log_cleanup.py b/tests/unit/proxy/test_spend_log_cleanup.py index a9bc82d141d..876ffe96584 100644 --- a/tests/unit/proxy/test_spend_log_cleanup.py +++ b/tests/unit/proxy/test_spend_log_cleanup.py @@ -20,13 +20,13 @@ from litellm.constants import ( SPEND_LOG_CLEANUP_RUN_BUDGET_SECONDS, ) from litellm.proxy.db.db_transaction_queue.spend_log_cleanup import ( + SPEND_LOG_CLEANUP_BOUND_SETTINGS, SizeCleanupState, + SpendLogCleanup, SpendLogStorage, StorageProbe, - advance_size_state, - SPEND_LOG_CLEANUP_BOUND_SETTINGS, - SpendLogCleanup, TableCleanupResult, + advance_size_state, ) from litellm.proxy.db.db_transaction_queue.spend_log_cleanup_metrics import ( SpendLogCleanupMetrics, @@ -1539,8 +1539,8 @@ async def test_progress_reported_for_a_cancelled_run_is_that_run_only(monkeypatc @pytest.mark.asyncio -async def test_progress_reported_by_an_overlapping_run_is_its_own(monkeypatch): - """With APSCHEDULER_MAX_INSTANCES above one, two runs share the cleaner but not their progress""" +async def test_a_size_pass_that_fires_while_an_age_pass_is_running_in_the_same_pod_waits_for_it(monkeypatch): + """Without Redis there is no pod lock, and the two jobs are scheduled on two SpendLogCleanup instances""" import litellm.proxy.db.db_transaction_queue.spend_log_cleanup as cleanup_module mock_logger = MagicMock() @@ -1557,22 +1557,31 @@ async def test_progress_reported_by_an_overlapping_run_is_its_own(monkeypatch): slow_client = MagicMock() _wire_tx(slow_client.db) slow_client.db.execute_raw = _slow_execute_raw - fast_client = MagicMock() - _wire_tx(fast_client.db) - fast_client.db.execute_raw = AsyncMock(side_effect=[150, 150, 0, 0]) + size_db = MagicMock() + _wire_tx(size_db) + size_db.execute_raw = AsyncMock(return_value=1000) + _wire_size_probes(size_db, [_storage(allocated=10 * 1024**3, live=1000, dead=0)], cutoff=datetime.now(timezone.utc)) + size_client = MagicMock() + size_client.db = size_db - cleaner = SpendLogCleanup(general_settings={"maximum_spend_logs_retention_period": "7d"}) - cleaner.pod_lock_manager = None + age_cleaner = SpendLogCleanup(general_settings={"maximum_spend_logs_retention_period": "7d"}) + age_cleaner.pod_lock_manager = None + size_cleaner = _size_cleaner({}) - slow_run = asyncio.ensure_future(cleaner.cleanup_old_spend_logs(slow_client)) + slow_run = asyncio.ensure_future(age_cleaner.cleanup_old_spend_logs(slow_client)) await asyncio.wait_for(first_batch_done.wait(), timeout=5) - await cleaner.cleanup_old_spend_logs(fast_client) + size_run = asyncio.ensure_future(size_cleaner.cleanup_spend_logs_by_size(size_client)) + await asyncio.sleep(0.05) + assert size_db.deletes.await_count == 0 and not size_run.done(), "the size pass ran while the age pass held the pod" + second_run_done.set() await asyncio.sleep(0) slow_run.cancel() with pytest.raises(asyncio.CancelledError): await slow_run + await asyncio.wait_for(size_run, timeout=5) + assert size_db.deletes.await_count > 0, "the size pass never ran once the age pass let go" (error_call,) = mock_logger.error.call_args_list rendered = error_call[0][0] % error_call[0][1:] assert "(rows_deleted=100, batches=1)" in rendered @@ -1681,7 +1690,7 @@ async def test_a_cleanup_delete_batch_renders_a_postgres_delete_span_for_its_tab assert await postgres_span_names() == ("postgres.delete LiteLLM_SpendLogs",) -# --- spend log storage measurement and the reclaimable-bytes state --------------------------------------- +# --- size rule (maximum_spend_logs_size) --------------------------------------------------------------- def _storage(allocated: int, live: int, dead: int, inserted: int | None = None, deleted: int | None = None) -> dict: @@ -1694,6 +1703,50 @@ def _storage(allocated: int, live: int, dead: int, inserted: int | None = None, } +def _wire_size_probes( + db, storage_rows: list[dict], cutoff: datetime, saved_state: SizeCleanupState | None = None +) -> list[SizeCleanupState]: + """ + Answer the size pass's catalog reads: the storage probe walks `storage_rows` one measurement per call + (repeating the last), the step-cutoff query returns `cutoff`, the remaining-rows probe returns 0, and the + LiteLLM_Config row holds `saved_state`. Writes of that row land in the returned list instead of + db.execute_raw, so DELETE counts stay what tests configure. + """ + measurements = iter(storage_rows) + last = [storage_rows[-1]] + saves: list[SizeCleanupState] = [] + deletes = db.execute_raw + + async def _query_raw(sql, *args): + if "pg_total_relation_size" in sql: + row = next(measurements, None) + if row is None: + row = last[0] + return [row] + if "OFFSET" in sql: + return [{"startTime": cutoff}] + if '"LiteLLM_Config"' in sql: + return [{"state_json": saved_state.model_dump_json()}] if saved_state is not None else [] + return [{"remaining": 0}] + + async def _execute_raw(sql, *args): + if '"LiteLLM_Config"' in sql: + saves.append(SizeCleanupState.model_validate_json(args[1])) + return 1 + return await deletes(sql, *args) + + db.query_raw = AsyncMock(side_effect=_query_raw) + db.execute_raw = _execute_raw + db.deletes = deletes + return saves + + +def _size_cleaner(settings: dict, **kwargs) -> SpendLogCleanup: + cleaner = SpendLogCleanup(general_settings={"maximum_spend_logs_size": "1GB", **settings}, **kwargs) + cleaner.pod_lock_manager = None + return cleaner + + @pytest.mark.parametrize( ("value", "expected"), [ @@ -1719,6 +1772,182 @@ def test_size_in_bytes_rejects_what_cannot_be_a_size(value): size_in_bytes(value) +def test_an_unset_size_means_no_size_rule_and_a_bad_target_falls_back_to_the_size(caplog): + assert SpendLogCleanup(general_settings={})._size_rule() is None + rule = _size_cleaner({"maximum_spend_logs_cleanup_target_size": "200MB"})._size_rule() + assert rule is not None + assert (rule.limit_bytes, rule.target_bytes) == (1024**3, 200 * 1024**2) + with caplog.at_level(logging.ERROR, logger="LiteLLM Proxy"): + rule_without_room = _size_cleaner({"maximum_spend_logs_cleanup_target_size": "2GB"})._size_rule() + assert rule_without_room is not None + assert rule_without_room.target_bytes == rule_without_room.limit_bytes == 1024**3 + assert any("must be below maximum_spend_logs_size" in record.getMessage() for record in caplog.records) + + +@pytest.mark.asyncio +async def test_size_pass_under_the_limit_issues_no_delete(): + db = MagicMock() + _wire_tx(db) + db.execute_raw = AsyncMock(return_value=0) + _wire_size_probes(db, [_storage(allocated=500 * 1024**2, live=1000, dead=0)], cutoff=datetime.now(timezone.utc)) + client = MagicMock() + client.db = db + + await _size_cleaner({}).cleanup_spend_logs_by_size(client) + + assert db.deletes.await_count == 0 + + +@pytest.mark.asyncio +async def test_size_pass_deletes_oldest_first_in_steps_until_the_live_estimate_is_under_the_target(caplog): + """ + Over the limit, the pass turns the next step of oldest rows into a cutoff and runs the retention DELETE + for the spend logs and their tool-index rows, re-measuring after each step; it stops on the first + measurement under the target, not when the file size (which deletes never shrink) moves. + """ + db = MagicMock() + _wire_tx(db) + # 3 GiB over 3000 rows is 1 MiB a row, so 2560 rows take it from 3 GiB to the 512 MiB target: one step + # of 3 batches; the tool index is cleaned on the same cutoff + db.execute_raw = AsyncMock(side_effect=[1000, 1000, 1000, 300, 0]) + step_cutoff = datetime(2026, 9, 1, tzinfo=timezone.utc) + allocated = 3 * 1024**3 + _wire_size_probes(db, [_storage(allocated, live=3000, dead=0)], cutoff=step_cutoff) + client = MagicMock() + client.db = db + cleaner = _size_cleaner({"maximum_spend_logs_cleanup_target_size": "512MB"}) + + with caplog.at_level(logging.INFO, logger="LiteLLM Proxy"): + await cleaner.cleanup_spend_logs_by_size(client) + + deletes = [(call[0][0], call[0][1:]) for call in db.deletes.call_args_list] + assert len(deletes) == 5 + assert 'DELETE FROM "LiteLLM_SpendLogs"' in deletes[0][0] + assert 'WHERE "startTime" < $1' in deletes[0][0] + assert deletes[0][1][0] == step_cutoff + assert 'DELETE FROM "LiteLLM_SpendLogToolIndex"' in deletes[3][0] + assert deletes[3][1][0] == step_cutoff + offset_query = next(call for call in db.query_raw.call_args_list if "OFFSET" in call[0][0]) + assert offset_query[0][1] == 3000 + summary = next(r.getMessage() for r in caplog.records if "Spend log cleanup run finished" in r.getMessage()) + assert "outcome=completed" in summary + assert "LiteLLM_SpendLogs (size rule): deleted=3000 stop_reason=target_reached" in summary + assert "LiteLLM_SpendLogToolIndex (size rule): deleted=300 stop_reason=target_reached" in summary + assert f"allocated_before={allocated}" in summary + assert "estimated_live_before=3221225472" in summary + assert "estimated_live_after=0" in summary + assert "target_reached=true above_target=0" in summary + assert "VACUUM FULL or pg_repack" in summary + + +@pytest.mark.asyncio +async def test_size_pass_stops_at_the_run_batch_cap_and_reports_how_far_above_the_target_it_is(caplog): + db = MagicMock() + _wire_tx(db) + # 4 GiB over 4000 rows: 3584 rows must go to reach the 512 MiB target, the cap allows 3 batches + db.execute_raw = AsyncMock(side_effect=[1000, 1000, 1000, 0]) + allocated = 4 * 1024**3 + saves = _wire_size_probes(db, [_storage(allocated, live=4000, dead=0)], cutoff=datetime.now(timezone.utc)) + client = MagicMock() + client.db = db + cleaner = _size_cleaner( + {"maximum_spend_logs_cleanup_target_size": "512MB", "maximum_spend_logs_cleanup_max_batches": 3} + ) + + with caplog.at_level(logging.WARNING, logger="LiteLLM Proxy"): + await cleaner.cleanup_spend_logs_by_size(client) + + assert db.deletes.await_count == 4 + summary = next(r for r in caplog.records if "Spend log cleanup run finished" in r.getMessage()) + assert summary.levelno == logging.WARNING + assert "outcome=batch_cap_reached" in summary.getMessage() + assert "LiteLLM_SpendLogs (size rule): deleted=3000 stop_reason=batch_cap_reached" in summary.getMessage() + # 1000 of 4000 rows left is 1 GiB live, 512 MiB above the target + assert f"target_reached=false above_target={512 * 1024**2}" in summary.getMessage() + # the next check starts from what this run freed, with the deletes already counted out of n_tup_del + assert saves == [ + SizeCleanupState( + allocated_bytes=allocated, + reclaimable_bytes=round(3000 * allocated / 4000), + bytes_per_row=allocated / 4000, + inserted_total=4000, + deleted_total=3000, + ) + ] + + +@pytest.mark.asyncio +async def test_size_pass_analyzes_and_measures_again_when_the_row_statistics_were_reset(caplog): + """A crash zeroes pg_stat_user_tables under a full file; the pass rebuilds the counters instead of skipping. + The first read after ANALYZE still shows zeros, as the stats collector publishes them a moment later""" + db = MagicMock() + _wire_tx(db) + statements = AsyncMock(return_value=0) + db.execute_raw = statements + saves = _wire_size_probes( + db, + [ + _storage(allocated=10 * 1024**3, live=0, dead=0, inserted=0, deleted=0), + _storage(allocated=10 * 1024**3, live=0, dead=0, inserted=0, deleted=0), + _storage(10 * 1024**3, 1000, 0, 0, 0), + ], + cutoff=datetime.now(timezone.utc), + saved_state=SizeCleanupState( + allocated_bytes=10 * 1024**3, + reclaimable_bytes=9 * 1024**3 + 512 * 1024**2, + bytes_per_row=1024.0, + inserted_total=50_000, + deleted_total=49_000, + ), + ) + client = MagicMock() + client.db = db + + with caplog.at_level(logging.WARNING, logger="LiteLLM Proxy"): + await _size_cleaner({}).cleanup_spend_logs_by_size(client) + + issued = [call.args[0] for call in statements.await_args_list] + assert issued == ['ANALYZE "LiteLLM_SpendLogs", "LiteLLM_SpendLogToolIndex"'], ( + "the only statement is the ANALYZE: no DELETE, the carried count puts the table under 1GB" + ) + assert any("row statistics are stale" in record.getMessage() for record in caplog.records) + assert saves[0].reclaimable_bytes == 9 * 1024**3 + 512 * 1024**2 + + +@pytest.mark.asyncio +async def test_size_pass_does_not_refire_after_autovacuum_forgets_the_rows_it_deleted(): + """ + The run before this one deleted 15,000 of 20,000 rows and saved what it freed. Autovacuum has since + turned those dead tuples into free space, so pg_stat_user_tables reports 5,000 live and 0 dead rows while + the files still measure the full 32 MB. Trusting the live share would call all 32 MB live and empty the + table; the saved count says 8 MB are live, under the limit, so nothing is deleted. + """ + db = MagicMock() + _wire_tx(db) + db.execute_raw = AsyncMock(return_value=1000) + after_last_run = SizeCleanupState( + allocated_bytes=32_030_720, + reclaimable_bytes=24_015_000, + bytes_per_row=1601.0, + inserted_total=20_000, + deleted_total=15_000, + ) + saves = _wire_size_probes( + db, + [_storage(32_030_720, live=5000, dead=0, inserted=20_000, deleted=15_000)], + cutoff=datetime.now(timezone.utc), + saved_state=after_last_run, + ) + client = MagicMock() + client.db = db + cleaner = _size_cleaner({"maximum_spend_logs_size": "16MB", "maximum_spend_logs_cleanup_target_size": "10MB"}) + + await cleaner.cleanup_spend_logs_by_size(client) + + assert db.deletes.await_count == 0 + assert saves[0].reclaimable_bytes == 24_015_000 + + _RUN_STATE = SizeCleanupState( allocated_bytes=32_030_720, reclaimable_bytes=24_015_000, @@ -1750,9 +1979,19 @@ _RUN_STATE = SizeCleanupState( ), ("the retention job deleted 2000 more rows", _storage(32_030_720, 3000, 2000, 20_000, 17_000), 27_217_000), ( - "statistics reset: counters restart from the dead rows", + "statistics reset (a crash, then ANALYZE): the count is carried forward, not restarted from the dead rows", _storage(32_030_720, 5000, 1000, 5000, 1000), - 5_338_453, + 24_015_000, + ), + ( + "statistics reset on a file VACUUM FULL shrank meanwhile: the carried count loses the shrink", + _storage(8_015_720, 5000, 0, 5000, 0), + 0, + ), + ( + "statistics reset with more dead rows than the carried count explains: the dead rows win", + _storage(32_030_720, 1000, 19_000, 1000, 19_000), + 30_429_184, ), ], ) @@ -1765,6 +2004,166 @@ def test_advance_size_state_tracks_free_space_through_vacuum_inserts_and_other_d assert 0 <= probe["allocated_bytes"] - advanced.reclaimable_bytes <= probe["allocated_bytes"], name +@pytest.mark.asyncio +async def test_size_only_run_leaves_the_age_rules_to_the_retention_job(): + db = MagicMock() + _wire_tx(db) + db.execute_raw = AsyncMock(return_value=0) + _wire_size_probes(db, [_storage(allocated=10 * 1024**3, live=100, dead=0)], cutoff=datetime.now(timezone.utc)) + client = MagicMock() + client.db = db + cleaner = _size_cleaner( + {"maximum_spend_logs_retention_period": "7d", "maximum_health_check_retention_period": "30d"} + ) + + await cleaner.cleanup_spend_logs_by_size(client) + + tables = {call[0][0].split('"')[1] for call in db.deletes.call_args_list} + assert tables == {"LiteLLM_SpendLogs", "LiteLLM_SpendLogToolIndex"} + + +@pytest.mark.asyncio +@pytest.mark.parametrize(("cron", "size_pass_expected"), [(None, False), ("0 3 * * *", True)]) +async def test_the_retention_run_carries_the_size_pass_only_when_one_cron_drives_both(cron, size_pass_expected): + db = MagicMock() + _wire_tx(db) + db.execute_raw = AsyncMock(return_value=0) + _wire_size_probes(db, [_storage(allocated=10 * 1024**3, live=100, dead=0)], cutoff=datetime.now(timezone.utc)) + client = MagicMock() + client.db = db + cleaner = _size_cleaner({"maximum_spend_logs_retention_period": "7d", "maximum_spend_logs_cleanup_cron": cron}) + + await cleaner.cleanup_old_spend_logs(client) + + measured = any("pg_total_relation_size" in call[0][0] for call in db.query_raw.call_args_list) + assert measured is size_pass_expected + + +@pytest.mark.asyncio +async def test_partitioned_size_pass_drops_the_oldest_partitions_first_and_skips_row_deletes_once_under_target( + caplog, +): + db = MagicMock() + _wire_tx(db) + db.execute_raw = AsyncMock(return_value=1000) + saves = _wire_size_probes( + db, + [_storage(10 * 1024**3, live=1000, dead=0), _storage(256 * 1024**2, live=25, dead=0)], + cutoff=datetime.now(timezone.utc), + ) + client = MagicMock() + client.db = db + verdicts = [] + + async def _drop(prisma_client, now, remaining_timeout_ms, still_over_target): + verdicts.append(await still_over_target()) + return ("LiteLLM_SpendLogs_p20260601",) + + partition_manager = MagicMock() + partition_manager.is_partitioned = AsyncMock(return_value=True) + partition_manager.ensure_partitions = AsyncMock() + partition_manager.drop_oldest_partitions_while = AsyncMock(side_effect=_drop) + cleaner = _size_cleaner( + {"use_spend_logs_partitioning": True, "maximum_spend_logs_cleanup_target_size": "512MB"}, + partition_manager=partition_manager, + ) + + with caplog.at_level(logging.INFO, logger="LiteLLM Proxy"): + await cleaner.cleanup_spend_logs_by_size(client) + + partition_manager.ensure_partitions.assert_awaited_once(), "a size-only setup still needs tomorrow's partition" + partition_manager.drop_oldest_partitions_while.assert_awaited_once() + assert verdicts == [False] + assert db.deletes.await_count == 0 + summary = next(r.getMessage() for r in caplog.records if "Spend log cleanup run finished" in r.getMessage()) + assert "partitions_dropped=1" in summary + assert "target_reached=true" in summary + assert (saves[-1].inserted_total, saves[-1].deleted_total, saves[-1].allocated_bytes) == (25, 0, 256 * 1024**2), ( + "the saved counters must be the post-drop ones, or the next check reads the drop as a statistics reset" + ) + + +@pytest.mark.asyncio +async def test_a_failed_remeasure_after_a_partition_drop_stops_the_pass_instead_of_deleting_on_old_numbers(caplog): + db = MagicMock() + _wire_tx(db) + db.execute_raw = AsyncMock(return_value=1000) + saves = _wire_size_probes(db, [_storage(10 * 1024**3, live=1000, dead=0)], cutoff=datetime.now(timezone.utc)) + client = MagicMock() + client.db = db + + async def _drop(prisma_client, now, remaining_timeout_ms, still_over_target): + db.query_raw = AsyncMock(side_effect=RuntimeError("connection reset")) + assert await still_over_target() is False + return ("LiteLLM_SpendLogs_p20260601",) + + partition_manager = MagicMock() + partition_manager.is_partitioned = AsyncMock(return_value=True) + partition_manager.ensure_partitions = AsyncMock() + partition_manager.drop_oldest_partitions_while = AsyncMock(side_effect=_drop) + cleaner = _size_cleaner( + {"use_spend_logs_partitioning": True, "maximum_spend_logs_cleanup_target_size": "512MB"}, + partition_manager=partition_manager, + ) + + with caplog.at_level(logging.WARNING, logger="LiteLLM Proxy"): + await cleaner.cleanup_spend_logs_by_size(client) + + assert db.deletes.await_count == 0, "the row step ran on the pre-drop measurement" + assert saves == [], "a count saved from pre-drop counters reads the drop as a statistics reset next check" + assert any("could not be re-measured after dropping partitions" in r.getMessage() for r in caplog.records) + + +def test_drop_oldest_partitions_while_only_drops_fully_elapsed_partitions_oldest_first(): + from litellm.proxy.db.db_transaction_queue.spend_logs_partition_manager import SpendLogsPartitionManager + + manager = SpendLogsPartitionManager() + now = datetime(2026, 10, 17, 12, tzinfo=timezone.utc) + manager._list_partitions = AsyncMock( + return_value=[ + ("LiteLLM_SpendLogs_p20261017", datetime(2026, 10, 18)), # today's, still receiving writes + ("LiteLLM_SpendLogs_p20261015", datetime(2026, 10, 16)), + ("LiteLLM_SpendLogs_default", None), + ("LiteLLM_SpendLogs_p20261014", datetime(2026, 10, 15)), + ] + ) + dropped_sql: list[str] = [] + + async def _ddl(prisma_client, statement, timeout_ms): + dropped_sql.append(statement) + + manager._execute_bounded_ddl = _ddl + verdicts = iter([True, False]) + + async def still_over_target(): + return next(verdicts) + + dropped = asyncio.run(manager.drop_oldest_partitions_while(MagicMock(), now, lambda: 1000, still_over_target)) + + assert dropped == ("LiteLLM_SpendLogs_p20261014", "LiteLLM_SpendLogs_p20261015") + assert dropped_sql == [ + 'DROP TABLE IF EXISTS "LiteLLM_SpendLogs_p20261014"', + 'DROP TABLE IF EXISTS "LiteLLM_SpendLogs_p20261015"', + ] + + +@pytest.mark.parametrize( + ("settings", "retention_job", "size_job"), + [ + ({}, False, False), + ({"maximum_spend_logs_retention_period": "7d"}, True, False), + ({"maximum_spend_logs_size": "180GB"}, False, True), + ({"maximum_spend_logs_size": "180GB", "maximum_spend_logs_retention_period": "7d"}, True, True), + ({"maximum_spend_logs_size": "180GB", "maximum_spend_logs_cleanup_cron": "0 3 * * *"}, True, False), + ], +) +def test_which_scheduler_jobs_the_cleanup_settings_ask_for(settings, retention_job, size_job): + from litellm.proxy.proxy_server import _wants_retention_job, _wants_size_check_job + + assert _wants_retention_job(settings) is retention_job + assert _wants_size_check_job(settings) is size_job + + def test_after_deleting_counts_the_rows_and_any_file_growth_as_reclaimable_and_to_state_keeps_the_counters(): storage = SpendLogStorage(allocated_bytes=32_030_720, reclaimable_bytes=0, bytes_per_row=1601.0, live_rows=20_000) diff --git a/tests/unit/proxy/test_update_spend.py b/tests/unit/proxy/test_update_spend.py index 62adb7303e2..571341e85e7 100644 --- a/tests/unit/proxy/test_update_spend.py +++ b/tests/unit/proxy/test_update_spend.py @@ -323,3 +323,31 @@ async def test_update_spend_logs_multiple_batches_with_failure(): # Verify all logs were cleared from transactions assert len(prisma_client.spend_log_transactions) == 0 + + +@pytest.mark.asyncio +async def test_update_spend_logs_drops_row_prisma_cannot_encode_and_keeps_the_rest(): + """A row the Prisma engine cannot utf-8 encode (a lone surrogate in a string + column) is permanent, so it must be dropped like any other poison row instead + of being requeued at the head of the queue where it would block every tenant.""" + prisma_client = MockPrismaClient() + proxy_logging_obj = create_mock_proxy_logging() + prisma_client.spend_log_transactions = [ + {"request_id": "good-1", "request_tags": '["a"]'}, + {"request_id": "poison", "request_tags": "\ud800"}, + {"request_id": "good-2", "request_tags": '["b"]'}, + ] + written = [] + + async def create_many(data, skip_duplicates): + if any("\ud800" in row["request_tags"] for row in data): + raise UnicodeEncodeError("utf-8", "\ud800", 0, 1, "surrogates not allowed") + written.extend(row["request_id"] for row in data) + + prisma_client.db.litellm_spendlogs.create_many = AsyncMock(side_effect=create_many) + + await update_spend(prisma_client, None, proxy_logging_obj) + + assert sorted(written) == ["good-1", "good-2"] + assert prisma_client.spend_log_transactions == [] + proxy_logging_obj.failure_handler.assert_not_called() diff --git a/tests/unit/proxy/utils/prisma_and_spend/test_proxy_update_spend.py b/tests/unit/proxy/utils/prisma_and_spend/test_proxy_update_spend.py index fc3deb0de18..e3b7bb5b49f 100644 --- a/tests/unit/proxy/utils/prisma_and_spend/test_proxy_update_spend.py +++ b/tests/unit/proxy/utils/prisma_and_spend/test_proxy_update_spend.py @@ -952,3 +952,53 @@ async def test_update_spend_logs_requeues_batch_when_postgres_is_out_of_connecti assert mock_prisma_client.db.litellm_spendlogs.create_many.await_count == 1 sleep.assert_not_awaited() assert [row["request_id"] for row in mock_prisma_client.spend_log_transactions] == ["r0", "r1", "r2", "r3", "e"] + + +async def _create_many_while_postgres_is_restarting(**_: object) -> int: + from prisma.engine.utils import handle_response_errors + + handle_response_errors( + MagicMock(), + [ + { + "error": "Error in connector: Can't reach database server at `127.0.0.1:5432`", + "user_facing_error": {"error_code": "P1001", "message": "Can't reach database server", "meta": None}, + } + ], + ) + return 0 + + +@pytest.mark.asyncio +async def test_update_spend_logs_retries_and_requeues_batch_when_postgres_restart_tears_down_prisma_engine( + mock_prisma_client: Any, make_spend_log_row: Any, monkeypatch: pytest.MonkeyPatch +) -> None: + """While Postgres restarts the prisma engine answers the write with a P1001 + payload whose ``meta`` is ``None``, which prisma's own response parser trips + over before it can build a typed error. That outage must be retried like + any other, and once retries exhaust the dequeued batch goes back to the head + of the queue so the rows land when Postgres is back. + """ + + async def _fake_sleep(_: float) -> None: + return None + + monkeypatch.setattr(utils_mod.asyncio, "sleep", _fake_sleep) + mock_prisma_client.db.litellm_spendlogs.create_many = AsyncMock( + side_effect=_create_many_while_postgres_is_restarting + ) + proxy_logging = MagicMock() + proxy_logging.failure_handler = AsyncMock() + mock_prisma_client.spend_log_transactions = [make_spend_log_row(request_id="c")] + + with pytest.raises(AttributeError): + await ProxyUpdateSpend.update_spend_logs( + n_retry_times=2, + prisma_client=mock_prisma_client, + db_writer_client=None, + proxy_logging_obj=proxy_logging, + logs_to_process=[make_spend_log_row(request_id="a"), make_spend_log_row(request_id="b")], + ) + + assert [row["request_id"] for row in mock_prisma_client.spend_log_transactions] == ["a", "b", "c"] + assert mock_prisma_client.db.litellm_spendlogs.create_many.await_count == 3 diff --git a/tests/unit/responses/litellm_completion_transformation/test_anthropic_responses_bridge.py b/tests/unit/responses/litellm_completion_transformation/test_anthropic_responses_bridge.py index 025f1315aab..94efef050a6 100644 --- a/tests/unit/responses/litellm_completion_transformation/test_anthropic_responses_bridge.py +++ b/tests/unit/responses/litellm_completion_transformation/test_anthropic_responses_bridge.py @@ -10,6 +10,7 @@ import respx from pydantic import BaseModel import litellm +from litellm.constants import REDACTED_BY_LITELLM from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler from litellm.responses.litellm_completion_transformation.handler import ( LiteLLMCompletionTransformationHandler, @@ -138,7 +139,7 @@ class _AnthropicMessage(BaseModel, frozen=True): class _AnthropicRequest(BaseModel, frozen=True): messages: tuple[_AnthropicMessage, ...] - system: tuple[_AnthropicBlock, ...] + system: tuple[_AnthropicBlock, ...] = () class _RecordingAnthropicMessages: @@ -309,6 +310,25 @@ async def test_previous_response_id_without_instructions_carries_the_latest_ones assert [block.text for block in anthropic.request.system] == [expected_system] +@pytest.mark.asyncio +async def test_previous_response_id_does_not_replay_redacted_instructions() -> None: + anthropic: Final = _RecordingAnthropicMessages() + with patch( + "litellm.proxy.proxy_server.prisma_client", + _FakePrismaClient([_FIRST_TURN, _second_turn(REDACTED_BY_LITELLM)]), + ): + await litellm.aresponses( + model=_MODEL, + previous_response_id="chatcmpl-second-turn", + input="What about Osaka?", + api_key="sk-ant-fake", + client=AsyncHTTPHandler(transport=httpx.MockTransport(anthropic)), + ) + + assert anthropic.request is not None + assert anthropic.request.system == () + + _SEARCH_CALL: Final = { "id": "srvtoolu_search", "type": "function", diff --git a/tests/unit/responses/litellm_completion_transformation/test_count_request.py b/tests/unit/responses/litellm_completion_transformation/test_count_request.py new file mode 100644 index 00000000000..464bdb1a367 --- /dev/null +++ b/tests/unit/responses/litellm_completion_transformation/test_count_request.py @@ -0,0 +1,127 @@ +import json +from typing import Final + +import pytest +from pydantic import JsonValue + +from litellm.litellm_core_utils.tool_fields import DropPolicy +from litellm.responses.litellm_completion_transformation.count_request import ( + ChatCountBridgeError, + ChatCountRequest, + chat_count_request, +) + +_MARK: Final[dict[str, JsonValue]] = {"type": "ephemeral"} +_MARKED_RESPONSES_REQUEST: Final[dict[str, JsonValue]] = { + "model": "claude-opus-5-5", + "instructions": "Be terse.", + "input": [ + {"type": "message", "role": "user", "content": "Weather in SF?", "cache_control": _MARK}, + { + "type": "message", + "role": "user", + "content": [{"type": "input_text", "text": "And in LA?", "cache_control": _MARK}], + }, + { + "type": "function_call", + "call_id": "call_1", + "name": "get_weather", + "arguments": '{"city": "SF"}', + "cache_control": _MARK, + }, + {"type": "function_call_output", "call_id": "call_1", "output": "sunny", "cache_control": _MARK}, + ], + "tools": [ + { + "type": "function", + "name": "get_weather", + "parameters": {"type": "object", "properties": {"city": {"type": "string"}}}, + "cache_control": _MARK, + } + ], +} + + +@pytest.mark.asyncio +@pytest.mark.parametrize("drop_params", (False, True)) +async def test_claude_count_request_leaves_out_every_cache_control_mark(drop_params: bool) -> None: + request: Final = await chat_count_request( + model="claude-opus-5-5", + custom_llm_provider="anthropic", + api_base=None, + responses_request=_MARKED_RESPONSES_REQUEST, + policy=DropPolicy(drop_params=drop_params, additional_drop_params=frozenset()), + ) + + assert isinstance(request, ChatCountRequest) + counted: Final = json.dumps({"messages": request.messages, "tools": request.tools}, default=str) + assert "cache_control" not in counted + for kept in ("Weather in SF?", "And in LA?", "call_1", "sunny", "get_weather"): + assert kept in counted + + +_WEATHER_TOOL: Final[dict[str, JsonValue]] = { + "type": "function", + "name": "get_weather", + "parameters": {"type": "object", "properties": {"city": {"type": "string"}}}, +} +_QUESTION: Final[dict[str, JsonValue]] = {"role": "user", "content": "Weather in SF?"} + + +async def _claude_count( + responses_request: dict[str, JsonValue], policy: DropPolicy +) -> ChatCountRequest | ChatCountBridgeError | None: + return await chat_count_request( + model="claude-opus-5-5", + custom_llm_provider="anthropic", + api_base=None, + responses_request={"model": "claude-opus-5-5", **responses_request}, + policy=policy, + ) + + +@pytest.mark.asyncio +async def test_claude_count_request_counts_additional_tools_input_items_as_tools_like_inference() -> None: + policy: Final = DropPolicy(drop_params=False, additional_drop_params=frozenset()) + + hoisted: Final = await _claude_count( + {"input": [{"type": "additional_tools", "tools": [_WEATHER_TOOL]}, _QUESTION]}, policy + ) + + assert isinstance(hoisted, ChatCountRequest) + assert hoisted.tools is not None + assert hoisted == await _claude_count({"input": [_QUESTION], "tools": [_WEATHER_TOOL]}, policy) + + +@pytest.mark.asyncio +async def test_claude_count_request_drops_a_malformed_tool_flag_under_drop_params_like_inference() -> None: + policy: Final = DropPolicy(drop_params=True, additional_drop_params=frozenset()) + + flagged: Final = await _claude_count( + {"input": [_QUESTION], "tools": [{**_WEATHER_TOOL, "defer_loading": "yes"}]}, policy + ) + + assert isinstance(flagged, ChatCountRequest) + assert flagged == await _claude_count({"input": [_QUESTION], "tools": [_WEATHER_TOOL]}, policy) + + +@pytest.mark.asyncio +async def test_claude_count_request_rejects_a_malformed_tool_flag_without_drop_params() -> None: + flagged: Final = await _claude_count( + {"input": [_QUESTION], "tools": [{**_WEATHER_TOOL, "defer_loading": "yes"}]}, + DropPolicy(drop_params=False, additional_drop_params=frozenset()), + ) + + assert isinstance(flagged, ChatCountBridgeError) + assert "defer_loading" in flagged.message + + +@pytest.mark.asyncio +async def test_claude_count_request_leaves_out_tools_the_deployment_drops() -> None: + policy: Final = DropPolicy(drop_params=False, additional_drop_params=frozenset({"tools"})) + + dropped: Final = await _claude_count({"input": [_QUESTION], "tools": [_WEATHER_TOOL]}, policy) + + assert isinstance(dropped, ChatCountRequest) + assert dropped.tools is None + assert dropped == await _claude_count({"input": [_QUESTION]}, policy) diff --git a/tests/unit/responses/litellm_completion_transformation/test_litellm_completion_responses.py b/tests/unit/responses/litellm_completion_transformation/test_litellm_completion_responses.py index cc5d5c62739..f34ca7d0ff8 100644 --- a/tests/unit/responses/litellm_completion_transformation/test_litellm_completion_responses.py +++ b/tests/unit/responses/litellm_completion_transformation/test_litellm_completion_responses.py @@ -6566,3 +6566,40 @@ def test_a_continued_chain_leaves_the_turns_metadata_alone_without_request_corre assert request["litellm_trace_id"] == "chain-session" assert "litellm_metadata" not in request assert request["metadata"] == {CALLER_SESSION_ID_METADATA_KEY: "turn-session", "user_api_key": "hashed"} + + +@pytest.mark.asyncio +async def test_bridge_partial_response_on_disconnect_bills_the_relayed_chat_chunks(): + from litellm.responses.litellm_completion_transformation.streaming_iterator import ( + LiteLLMCompletionStreamingIterator, + ) + + chat_stream: Final = await litellm.acompletion( + model="gpt-4o-mini", + messages=[{"role": "user", "content": "tell me a story"}], + mock_response="The codename is AZURE-FALCON-42 and the story is long.", + stream=True, + api_key="test-key", + ) + iterator: Final = LiteLLMCompletionStreamingIterator( + model="gpt-4o-mini", + litellm_custom_stream_wrapper=chat_stream, + request_input="tell me a story", + responses_api_request={}, + custom_llm_provider="openai", + ) + assert iterator.partial_response_on_disconnect() is None, "nothing relayed yet, nothing to bill" + events: Final = [await iterator.__anext__() for _ in range(6)] + relayed_text: Final = "".join( + getattr(event, "delta", "") for event in events if event.type == "response.output_text.delta" + ) + assert relayed_text, "the bridge should have relayed some text by now" + + incomplete_event: Final = iterator.partial_response_on_disconnect() + + assert incomplete_event is not None + assert incomplete_event.type == "response.incomplete" + assert incomplete_event.response.status == "incomplete" + assert incomplete_event.response.usage is not None + assert incomplete_event.response.usage.output_tokens == litellm.token_counter(model="gpt-4o-mini", text=relayed_text) + assert incomplete_event.response.usage.input_tokens > 0 diff --git a/tests/unit/responses/mcp/test_aresponses_api_with_mcp.py b/tests/unit/responses/mcp/test_aresponses_api_with_mcp.py index b9cf201a47a..60d4d2e89b5 100644 --- a/tests/unit/responses/mcp/test_aresponses_api_with_mcp.py +++ b/tests/unit/responses/mcp/test_aresponses_api_with_mcp.py @@ -1065,6 +1065,108 @@ async def test_mcp_tool_execution_events_creation(): print("MCP tool execution events creation test passed!") +@pytest.mark.asyncio +async def test_aresponses_mcp_call_does_not_forward_admission_authorization( + monkeypatch: pytest.MonkeyPatch, +) -> None: + import importlib + import sys + import types + from unittest.mock import AsyncMock + + from mcp.types import CallToolResult, TextContent, Tool as MCPTool + + from litellm.proxy._experimental.mcp_server import mcp_server_manager + from litellm.proxy._types import UserAPIKeyAuth + from litellm.types.mcp import MCPAuth, MCPTransport + from litellm.types.mcp_server.mcp_server_manager import MCPServer + + responses_main: Final = importlib.import_module("litellm.responses.main") + manager: Final = mcp_server_manager.global_mcp_server_manager + server: Final = MCPServer( + server_id="responses-auth-strip", + name="echo_none", + server_name="echo_none", + url="http://mcp.example", + transport=MCPTransport.http, + auth_type=MCPAuth.none, + extra_headers=["Authorization", "x-tenant"], + allow_all_keys=True, + ) + monkeypatch.setattr(manager, "registry", {server.server_id: server}) + + mcp_client: Final = AsyncMock() + mcp_client.list_tools.return_value = [MCPTool(name="whoami", inputSchema={"type": "object", "properties": {}})] + mcp_client.call_tool.return_value = CallToolResult( + content=[TextContent(type="text", text="ok")], + isError=False, + ) + monkeypatch.setattr(manager, "create_mcp_client", AsyncMock(return_value=mcp_client)) + monkeypatch.setitem( + sys.modules, + "litellm.proxy.proxy_server", + types.SimpleNamespace( + general_settings={}, + master_key="test-master-key", + proxy_logging_obj=None, + prisma_client=None, + user_api_key_cache=None, + ), + ) + + raw_headers: Final = {"authorization": "Bearer sk-" + "1234", "x-tenant": "tenant-a"} + user_api_key_auth: Final = UserAPIKeyAuth(api_key="hashed-key", token="hashed-key") + tools: Final = [ + { + "type": "mcp", + "server_label": "echo_none", + "server_url": "litellm_proxy/mcp/echo_none", + "require_approval": "never", + } + ] + + monkeypatch.setattr( + responses_main, + "aresponses", + AsyncMock( + side_effect=[ + ResponsesAPIResponse( + id="resp_first", + created_at=0, + output=[ + { + "type": "function_call", + "id": "fc_1", + "call_id": "call-1", + "name": "echo_none-whoami", + "arguments": "{}", + "status": "completed", + } + ], + ), + ResponsesAPIResponse(id="resp_final", created_at=0, output=[]), + ] + ), + ) + monkeypatch.setattr( + importlib.import_module("litellm.responses.mcp.litellm_proxy_mcp_handler"), + "aresponses", + AsyncMock(return_value=ResponsesAPIResponse(id="resp_final", created_at=0, output=[])), + ) + + await responses_main.aresponses_api_with_mcp( + input="Call whoami", + model="openai/gpt-5", + tools=tools, + litellm_metadata={"user_api_key_auth": user_api_key_auth}, + secret_fields={"raw_headers": raw_headers}, + ) + + assert mcp_client.call_tool.await_args is not None + assert manager.create_mcp_client.await_args is not None + assert manager.create_mcp_client.await_args.kwargs["extra_headers"] == {"x-tenant": "tenant-a"} + + @pytest.mark.asyncio async def test_no_duplicate_mcp_tools_in_streaming_e2e(): """ diff --git a/tests/unit/responses/test_responses_streaming_iterator.py b/tests/unit/responses/test_responses_streaming_iterator.py index 0419fce8ec2..37a58c32f38 100644 --- a/tests/unit/responses/test_responses_streaming_iterator.py +++ b/tests/unit/responses/test_responses_streaming_iterator.py @@ -7,7 +7,10 @@ crashed with exit 139 whenever any CustomLogger was registered). """ import asyncio +import json import time +from collections.abc import Mapping +from typing import Final import httpx import pytest @@ -17,6 +20,7 @@ from litellm.integrations.custom_logger import CustomLogger from litellm.litellm_core_utils import thread_pool_executor as thread_pool_executor_module from litellm.responses import streaming_iterator as responses_streaming_iterator_module from litellm.litellm_core_utils.litellm_logging import Logging as LitellmLogging +from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig from litellm.responses.streaming_iterator import ResponsesAPIStreamingIterator from litellm.types.llms.openai import ResponsesAPIResponse @@ -163,3 +167,99 @@ async def test_sync_callbacks_run_only_after_async_handler_completes(recording_e submit_times = recording_executor.submit_times_for(logging_obj) assert len(submit_times) == 1 assert submit_times[0] >= recorder.async_hook_finished + + +_CREATED_RESPONSE_WITH_PRIORITY_TIER: Final[Mapping[str, object]] = { + "id": "resp_partial", + "object": "response", + "created_at": 1700000000.0, + "model": "gpt-5.4-nano", + "status": "in_progress", + "output": [], + "parallel_tool_calls": True, + "tool_choice": "auto", + "tools": [], + "service_tier": "priority", +} +_CREATED_WITH_PRIORITY_TIER: Final[Mapping[str, object]] = { + "type": "response.created", + "sequence_number": 0, + "response": _CREATED_RESPONSE_WITH_PRIORITY_TIER, +} + + +def _text_delta(text: str, sequence_number: int) -> Mapping[str, object]: + return { + "type": "response.output_text.delta", + "sequence_number": sequence_number, + "item_id": "msg_partial", + "output_index": 0, + "content_index": 0, + "delta": text, + } + + +def _completed_after(text: str) -> Mapping[str, object]: + return { + "type": "response.completed", + "sequence_number": 9, + "response": { + **_CREATED_RESPONSE_WITH_PRIORITY_TIER, + "status": "completed", + "usage": {"input_tokens": 5, "output_tokens": 7, "total_tokens": 12}, + }, + } + + +def _live_iterator(logging_obj: LitellmLogging) -> ResponsesAPIStreamingIterator: + return ResponsesAPIStreamingIterator( + response=httpx.Response(200), + model="gpt-5.4-nano", + responses_api_provider_config=OpenAIResponsesAPIConfig(), + logging_obj=logging_obj, + request_data={"model": "gpt-5.4-nano", "input": "tell me a story"}, + custom_llm_provider="openai", + ) + + +def test_partial_response_on_disconnect_bills_the_relayed_text_at_the_served_service_tier(): + iterator: Final = _live_iterator(_make_logging_obj()) + for event in (_CREATED_WITH_PRIORITY_TIER, _text_delta("Once upon a time ", 1), _text_delta("a fox slept.", 2)): + iterator._process_chunk(json.dumps(event)) + + incomplete_event: Final = iterator.partial_response_on_disconnect() + + assert incomplete_event is not None + assert incomplete_event.type == "response.incomplete" + partial: Final = incomplete_event.response + assert partial.status == "incomplete" + assert getattr(partial, "service_tier") == "priority" + assert partial.output[0].content[0].text == "Once upon a time a fox slept." + assert partial.usage.output_tokens == litellm.token_counter( + model="gpt-5.4-nano", text="Once upon a time a fox slept." + ) + assert partial.usage.input_tokens == litellm.token_counter( + model="gpt-5.4-nano", messages=[{"role": "user", "content": "tell me a story"}] + ) + assert partial.usage.total_tokens == partial.usage.input_tokens + partial.usage.output_tokens + + +@pytest.mark.parametrize( + "events", + [ + (), + (_CREATED_WITH_PRIORITY_TIER,), + (_CREATED_WITH_PRIORITY_TIER, _text_delta("Once upon a time", 1), _completed_after("Once upon a time")), + ], + ids=["nothing_relayed", "created_only", "already_completed"], +) +@pytest.mark.asyncio +async def test_partial_response_on_disconnect_is_none_when_there_is_nothing_to_bill_or_the_stream_billed_itself( + events: tuple[Mapping[str, object], ...], +): + iterator: Final = _live_iterator(_make_logging_obj()) + for event in events: + iterator._process_chunk(json.dumps(event)) + + assert iterator.partial_response_on_disconnect() is None + await iterator._await_pending_logging() diff --git a/tests/unit/responses/test_streaming_iterator.py b/tests/unit/responses/test_streaming_iterator.py index e5054ed3cef..62d89a55e85 100644 --- a/tests/unit/responses/test_streaming_iterator.py +++ b/tests/unit/responses/test_streaming_iterator.py @@ -5,8 +5,10 @@ completion_start_time = end_time.""" import asyncio, importlib import functools +import gc import json import threading +import weakref from collections.abc import Callable, Mapping from datetime import datetime from typing import Final, Optional @@ -14,6 +16,7 @@ from unittest.mock import AsyncMock, MagicMock, Mock, patch import httpx import pytest +import websockets.exceptions from pydantic_core import PydanticSerializationError import litellm @@ -509,16 +512,22 @@ class _OrderRecordingSyncLogger(CustomLogger): def _real_logging_obj( - *, call_type: str = "aresponses", litellm_params: dict[str, object] | None = None + *, + call_type: str = "aresponses", + litellm_params: dict[str, object] | None = None, + callbacks: tuple[CustomLogger, ...] | None = None, + stream: bool = True, ) -> LiteLLMLoggingObj: logging_obj: Final = LiteLLMLoggingObj( model="gpt-4o-mini", messages=[{"role": "user", "content": "hi"}], - stream=True, + stream=stream, call_type=call_type, start_time=datetime.now(), litellm_call_id="lit-8678-test", function_id="lit-8678-test", + dynamic_async_success_callbacks=None if callbacks is None else list(callbacks), + dynamic_async_failure_callbacks=None if callbacks is None else list(callbacks), ) logging_obj.model_call_details["litellm_params"] = ( dict(litellm_params) if litellm_params is not None else {"aresponses": True} @@ -830,26 +839,26 @@ def _responses_api_response_with_usage() -> ResponsesAPIResponse: def test_stamp_responses_usage_cost_stamps_computed_cost(): - from litellm.responses.streaming_iterator import _stamp_responses_usage_cost + from litellm.responses.streaming_iterator import stamp_responses_usage_cost response = _responses_api_response_with_usage() logging_obj = Mock(spec=LiteLLMLoggingObj) logging_obj.response_cost_calculator.return_value = 0.000704 - _stamp_responses_usage_cost(response, logging_obj) + stamp_responses_usage_cost(response, logging_obj) assert getattr(response.usage, "cost", None) == pytest.approx(0.000704) logging_obj.response_cost_calculator.assert_called_once_with(result=response) def test_stamp_responses_usage_cost_keeps_provider_reported_cost(): - from litellm.responses.streaming_iterator import _stamp_responses_usage_cost + from litellm.responses.streaming_iterator import stamp_responses_usage_cost response = _responses_api_response_with_usage() setattr(response.usage, "cost", 0.5) logging_obj = Mock(spec=LiteLLMLoggingObj) - _stamp_responses_usage_cost(response, logging_obj) + stamp_responses_usage_cost(response, logging_obj) assert getattr(response.usage, "cost", None) == pytest.approx(0.5) logging_obj.response_cost_calculator.assert_not_called() @@ -869,7 +878,7 @@ def _unvalidated_response_with_dict_usage(usage: dict) -> ResponsesAPIResponse: def test_stamp_responses_usage_cost_keeps_provider_cost_from_dict_usage(): - from litellm.responses.streaming_iterator import _stamp_responses_usage_cost + from litellm.responses.streaming_iterator import stamp_responses_usage_cost response = _unvalidated_response_with_dict_usage( { "input_tokens": 29, @@ -881,7 +890,7 @@ def test_stamp_responses_usage_cost_keeps_provider_cost_from_dict_usage(): ) logging_obj = Mock(spec=LiteLLMLoggingObj) - _stamp_responses_usage_cost(response, logging_obj) + stamp_responses_usage_cost(response, logging_obj) assert isinstance(response.usage, ResponseAPIUsage) assert response.usage.cost == pytest.approx(3e-05) @@ -890,12 +899,12 @@ def test_stamp_responses_usage_cost_keeps_provider_cost_from_dict_usage(): def test_stamp_responses_usage_cost_computes_cost_for_dict_usage_without_cost(): - from litellm.responses.streaming_iterator import _stamp_responses_usage_cost + from litellm.responses.streaming_iterator import stamp_responses_usage_cost response = _unvalidated_response_with_dict_usage({"input_tokens": 29, "output_tokens": 120, "total_tokens": 149}) logging_obj = Mock(spec=LiteLLMLoggingObj) logging_obj.response_cost_calculator.return_value = 0.000704 - _stamp_responses_usage_cost(response, logging_obj) + stamp_responses_usage_cost(response, logging_obj) assert isinstance(response.usage, ResponseAPIUsage) assert response.usage.cost == pytest.approx(0.000704) @@ -903,13 +912,13 @@ def test_stamp_responses_usage_cost_computes_cost_for_dict_usage_without_cost(): def test_stamp_responses_usage_cost_survives_calculator_failure(): - from litellm.responses.streaming_iterator import _stamp_responses_usage_cost + from litellm.responses.streaming_iterator import stamp_responses_usage_cost response = _responses_api_response_with_usage() logging_obj = Mock(spec=LiteLLMLoggingObj) logging_obj.response_cost_calculator.side_effect = RuntimeError("cost map unavailable") - _stamp_responses_usage_cost(response, logging_obj) + stamp_responses_usage_cost(response, logging_obj) assert getattr(response.usage, "cost", None) is None @@ -2598,24 +2607,156 @@ def test_faked_stream_builds_each_refusal_summary_and_custom_tool_input_once_for @pytest.mark.asyncio async def test_shutdown_drain_waits_for_a_pending_logging_task(): - row_written = asyncio.Event() + release: Final = asyncio.Event() + row: Final = streaming_module.spawn_logging_task(asyncio.get_running_loop(), release.wait(), task_name="row") - async def write_row(): - await asyncio.sleep(0.05) - row_written.set() + drain_held: Final = await _drain_held_until_released(release) - streaming_module.spawn_logging_task(asyncio.get_running_loop(), write_row(), task_name="row") - - await streaming_module.drain_logging_tasks(timeout=1) - - assert row_written.is_set() + assert drain_held + assert row.done() @pytest.mark.asyncio async def test_shutdown_drain_gives_up_on_a_stuck_logging_task_at_its_timeout(): - stuck = streaming_module.spawn_logging_task(asyncio.get_running_loop(), asyncio.Event().wait(), task_name="stuck") + stuck: Final = streaming_module.spawn_logging_task(asyncio.get_running_loop(), asyncio.Event().wait(), task_name="stuck") await asyncio.wait_for(streaming_module.drain_logging_tasks(timeout=0.05), timeout=1) assert not stuck.done() stuck.cancel() + + +async def _drain_held_until_released(release: asyncio.Event) -> bool: + drain: Final = asyncio.create_task(streaming_module.drain_logging_tasks(timeout=5)) + await asyncio.sleep(0) + held: Final = not drain.done() + release.set() + await drain + return held + + +class _GatedLogger(CustomLogger): + def __init__(self) -> None: + super().__init__() + self.entered: Final = asyncio.Event() + self.release: Final = asyncio.Event() + self.logged = False + + async def _log(self) -> None: + self.entered.set() + await self.release.wait() + self.logged = True + + async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): + await self._log() + + async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time): + await self._log() + + +class _UnreferencedWaitLogger(CustomLogger): + def __init__(self) -> None: + super().__init__() + self.parked: Final = asyncio.Event() + self.waiting_tasks: Final = weakref.WeakSet[asyncio.Task[object]]() + + async def _wait_forever(self) -> None: + self.waiting_tasks.add(asyncio.current_task()) + self.parked.set() + await asyncio.get_running_loop().create_future() + + async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): + await self._wait_forever() + + async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time): + await self._wait_forever() + + +async def _shutdown_drain_held_for(logger: _GatedLogger) -> bool: + await asyncio.wait_for(logger.entered.wait(), timeout=5) + return await _drain_held_until_released(logger.release) + + +async def _logging_tasks_left_after_garbage_collection(logger: _UnreferencedWaitLogger) -> int: + await asyncio.wait_for(logger.parked.wait(), timeout=5) + gc.collect() + survivors: Final = tuple(logger.waiting_tasks) + for task in survivors: + task.cancel() + await asyncio.gather(*survivors, return_exceptions=True) + return len(survivors) + + +async def _stream_to_completion(logger: CustomLogger) -> None: + iterator: Final = _make_iterator( + sse_events=_COMPLETE_STREAM_EVENTS, logging_obj=_real_logging_obj(callbacks=(logger,)) + ) + async for _ in iterator: + pass + + +_WS_TERMINAL_EVENTS: Final = [ + pytest.param({"type": "response.completed", "response": {}}, id="success"), + pytest.param( + {"type": "response.failed", "response": {"error": {"code": "server_error", "message": "boom"}}}, + id="failure", + ), +] + + +async def _run_websocket_turn(logger: CustomLogger, terminal_event: dict[str, object]) -> None: + backend_ws: Final = MagicMock() + backend_ws.recv = AsyncMock( + side_effect=[json.dumps(terminal_event), websockets.exceptions.ConnectionClosedOK(None, None)] + ) + streaming: Final = streaming_module.ResponsesWebSocketStreaming( + websocket=MagicMock(send_text=AsyncMock()), + backend_ws=backend_ws, + logging_obj=_real_logging_obj( + call_type=CallTypes.aresponses_websocket.value, + litellm_params={CallTypes.aresponses_websocket.value: True}, + callbacks=(logger,), + stream=False, + ), + ) + await streaming.backend_to_client() + + +@pytest.mark.asyncio +async def test_shutdown_drain_waits_for_a_completed_streams_success_logging(): + logger: Final = _GatedLogger() + await _stream_to_completion(logger) + + drain_held: Final = await _shutdown_drain_held_for(logger) + + assert drain_held + assert logger.logged + + +@pytest.mark.asyncio +@pytest.mark.parametrize("terminal_event", _WS_TERMINAL_EVENTS) +async def test_shutdown_drain_waits_for_a_websocket_turns_logging(terminal_event: dict[str, object]): + logger: Final = _GatedLogger() + await _run_websocket_turn(logger, terminal_event) + + drain_held: Final = await _shutdown_drain_held_for(logger) + + assert drain_held + assert logger.logged + + +@pytest.mark.asyncio +async def test_completed_streams_success_logging_survives_garbage_collection(): + logger: Final = _UnreferencedWaitLogger() + await _stream_to_completion(logger) + + assert await _logging_tasks_left_after_garbage_collection(logger) == 1 + + +@pytest.mark.asyncio +@pytest.mark.parametrize("terminal_event", _WS_TERMINAL_EVENTS) +async def test_websocket_turns_logging_survives_garbage_collection(terminal_event: dict[str, object]): + logger: Final = _UnreferencedWaitLogger() + await _run_websocket_turn(logger, terminal_event) + + assert await _logging_tasks_left_after_garbage_collection(logger) == 1 diff --git a/tests/unit/router_strategy/test_budget_limiter.py b/tests/unit/router_strategy/test_budget_limiter.py index 3c825bd560f..c0583566531 100644 --- a/tests/unit/router_strategy/test_budget_limiter.py +++ b/tests/unit/router_strategy/test_budget_limiter.py @@ -449,3 +449,91 @@ def cleanup_redis(): redis_client.delete(key) except Exception as e: print(f"Error cleaning up Redis: {str(e)}") + + +def _completed_budget_batch(batch_id: str): + from litellm.types.utils import LiteLLMBatch + + return LiteLLMBatch( + id=batch_id, + completion_window="24h", + created_at=1, + endpoint="/v1/chat/completions", + input_file_id="file-budget", + object="batch", + status="completed", + ) + + +@pytest.mark.asyncio +@pytest.mark.parametrize("call_type", ("aretrieve_batch", "retrieve_batch")) +async def test_batch_polls_charge_each_router_budget_once(monkeypatch, call_type): + monkeypatch.setattr(litellm, "tag_budget_config", {"release": {"budget_limit": 100, "time_period": "1d"}}) + monkeypatch.setattr("litellm.proxy.proxy_server.premium_user", True) + cache: Final = DualCache() + limiter: Final = RouterBudgetLimiting( + dual_cache=cache, + provider_budget_config={"openai": {"budget_limit": 100, "time_period": "1d"}}, + model_list=[ + { + "model_name": "batch-budget", + "litellm_params": {"model": "openai/batch-budget", "max_budget": 100, "budget_duration": "1d"}, + "model_info": {"id": "deployment-1"}, + } + ], + ) + kwargs: Final = { + **_success_kwargs(provider_in_litellm_params=None, provider_in_payload="openai", call_type=call_type), + "metadata": {"tags": ["release"]}, + } + response: Final = _completed_budget_batch("batch-first") + await asyncio.gather(*(limiter.async_log_success_event(kwargs, response, None, None) for _ in range(10))) + keys: Final = ("provider_spend:openai:1d", "deployment_spend:deployment-1:1d", "tag_spend:release:1d") + assert tuple([await cache.async_get_cache(key) for key in keys]) == (0.25, 0.25, 0.25) + await limiter.async_log_success_event(kwargs, _completed_budget_batch("batch-second"), None, None) + await limiter.async_log_success_event({**kwargs, "call_type": "acompletion"}, response, None, None) + await limiter.async_log_success_event({**kwargs, "call_type": "acompletion"}, response, None, None) + assert tuple([await cache.async_get_cache(key) for key in keys]) == (1.0, 1.0, 1.0) + await limiter.async_log_success_event({**kwargs, "call_type": "_arealtime"}, response, None, None) + assert tuple([await cache.async_get_cache(key) for key in keys]) == (1.0, 1.0, 1.0) + + +@pytest.mark.asyncio +async def test_batch_charge_is_shared_across_workers_and_requires_redis_confirmation(): + from fakeredis import FakeServer, FakeRedis as FakeSyncRedis + from redis.exceptions import ConnectionError as RedisConnectionError + from fakeredis.aioredis import FakeRedis + from litellm.caching.redis_cache import RedisCache + + server: Final = FakeServer() + client: Final = FakeRedis(server=server) + sync_client: Final = FakeSyncRedis(server=server) + redis_cache: Final = RedisCache(host="router-batch-fixture", connection_pool=sync_client.connection_pool) + litellm.in_memory_llm_clients_cache.set_cache(key=redis_cache._get_async_client_cache_key(), value=client) + first: Final = RouterBudgetLimiting( + dual_cache=DualCache(redis_cache=redis_cache), + provider_budget_config={"openai": {"budget_limit": 100, "time_period": "1d"}}, + ) + second: Final = RouterBudgetLimiting( + dual_cache=DualCache(redis_cache=redis_cache), + provider_budget_config={"openai": {"budget_limit": 100, "time_period": "1d"}}, + ) + kwargs: Final = _success_kwargs( + provider_in_litellm_params=None, provider_in_payload="openai", call_type="aretrieve_batch" + ) + response: Final = _completed_budget_batch("batch-shared") + await asyncio.gather( + first.async_log_success_event(kwargs, response, None, None), + second.async_log_success_event(kwargs, response, None, None), + ) + await first._push_in_memory_increments_to_redis() + await second._push_in_memory_increments_to_redis() + assert float(await client.get("provider_spend:openai:1d")) == 0.25 + server.connected = False + with pytest.raises(RedisConnectionError): + await second.async_log_success_event(kwargs, _completed_budget_batch("batch-unconfirmed"), None, None) + server.connected = True + await second.async_log_success_event(kwargs, _completed_budget_batch("batch-unconfirmed"), None, None) + await second._push_in_memory_increments_to_redis() + assert float(await client.get("provider_spend:openai:1d")) == 0.5 + await client.aclose() diff --git a/tests/unit/router_strategy/test_lowest_cost.py b/tests/unit/router_strategy/test_lowest_cost.py index b53ec6e6ba2..e3fdcd69499 100644 --- a/tests/unit/router_strategy/test_lowest_cost.py +++ b/tests/unit/router_strategy/test_lowest_cost.py @@ -112,6 +112,7 @@ def _vcr_outcome_gate(request, vcr): yield record_vcr_outcome(request, vcr) + @pytest.fixture(scope="function") def isolate_litellm_state(): """ @@ -164,6 +165,7 @@ def isolate_litellm_state(): setattr(litellm, attr, original_value) _invalidate_model_cost_lowercase_map() + _SCALAR_DEFAULTS = { "num_retries": getattr(litellm, "num_retries", None), "num_retries_per_request": getattr(litellm, "num_retries_per_request", None), @@ -184,6 +186,7 @@ _SCALAR_DEFAULTS = { "api_key": getattr(litellm, "api_key", None), } + @pytest.fixture(scope="module") def setup_and_teardown(): """ @@ -206,6 +209,7 @@ def setup_and_teardown(): litellm.in_memory_llm_clients_cache.flush_cache() yield + @pytest.mark.usefixtures("_vcr_outcome_gate", "isolate_litellm_state", "setup_and_teardown") @pytest.mark.asyncio async def test_get_available_deployments(): @@ -235,6 +239,7 @@ async def test_get_available_deployments(): assert selected_model["model_info"]["id"] == "groq-llama" + @pytest.mark.usefixtures("_vcr_outcome_gate", "isolate_litellm_state", "setup_and_teardown") @pytest.mark.asyncio async def test_get_available_deployments_custom_price(): @@ -286,6 +291,7 @@ async def test_get_available_deployments_custom_price(): assert selected_model["model_info"]["id"] == "chatgpt-v-1" + async def _deploy(lowest_cost_logger, deployment_id, tokens_used, duration): kwargs = { "litellm_params": { @@ -307,6 +313,7 @@ async def _deploy(lowest_cost_logger, deployment_id, tokens_used, duration): end_time=end_time, ) + @pytest.mark.usefixtures("_vcr_outcome_gate", "isolate_litellm_state", "setup_and_teardown") @pytest.mark.parametrize("ans_rpm", [1, 5]) # 1 should produce nothing, 10 should select first @pytest.mark.asyncio @@ -357,3 +364,42 @@ async def test_get_available_endpoints_tpm_rpm_check_async(ans_rpm): assert (d_ans and d_ans["model_info"]["id"]) == ans print("selected deployment:", d_ans) + + +_TWO_DOLLARS_PER_TOKEN = {"input_cost_per_token": 1.0, "output_cost_per_token": 1.0} + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "azure_litellm_params, base_model", + [ + ({"model": "azure/my-gpt4-deploy"}, "azure/gpt-4.1"), + ({"model": "azure/gpt-4.1"}, "azure/not-a-real-model"), + ], + ids=["base_model_priced", "unmapped_base_model_falls_back_to_deployment_model"], +) +async def test_cost_based_routing_prices_an_azure_deployment_through_its_base_model( + azure_litellm_params: dict, base_model: str +): + handler = LowestCostLoggingHandler(router_cache=DualCache()) + healthy_deployments = [ + { + "model_name": "gpt-4.1", + "litellm_params": {"model": "openai/gpt-4.1", **_TWO_DOLLARS_PER_TOKEN}, + "model_info": {"id": "openai-two-dollars"}, + }, + { + "model_name": "gpt-4.1", + "litellm_params": azure_litellm_params, + "model_info": {"id": "azure-cost-map-priced", "base_model": base_model}, + }, + ] + + picked = await handler.async_get_available_deployments( + model_group="gpt-4.1", healthy_deployments=healthy_deployments + ) + + assert picked is not None and picked["model_info"]["id"] == "azure-cost-map-priced", ( + "a cost-map priced Azure deployment must beat a $2 per token deployment, " + "it loses only when it is scored at the $10 unmapped default" + ) diff --git a/tests/unit/router_strategy/test_router_tag_routing.py b/tests/unit/router_strategy/test_router_tag_routing.py index f0e85208933..097a34cf2e6 100644 --- a/tests/unit/router_strategy/test_router_tag_routing.py +++ b/tests/unit/router_strategy/test_router_tag_routing.py @@ -3175,6 +3175,112 @@ async def test_chat_request_carrying_litellm_metadata_still_routes_on_proxy_merg assert deployment["model_info"]["id"] == "team-a-deployment" +def _baggage_mapped_metadata(client_tags: list[str], inherited_tags: list[str]) -> dict: + from types import SimpleNamespace + from typing import cast + + from fastapi import Request + + from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup + + request = cast(Request, SimpleNamespace(state=SimpleNamespace(litellm_baggage_mapped_tags=("usecase:a",)))) + data = {"metadata": {"tags": client_tags, "inherited_tags": inherited_tags}} + LiteLLMProxyRequestSetup.apply_authenticated_baggage_tags(request, data) + return data["metadata"] + + +@pytest.mark.asyncio() +@pytest.mark.parametrize( + "client_tags,inherited_tags,expected_model_id", + [ + ([], [], "default-deployment"), + (["usecase:a"], [], "usecase-deployment"), + ([], ["usecase:a"], "usecase-deployment"), + ], +) +async def test_baggage_mapped_tags_classify_spend_without_selecting_deployments( + client_tags, inherited_tags, expected_model_id +): + router = litellm.Router( + model_list=[ + { + "model_name": "gpt-4", + "litellm_params": {"model": "gpt-4o", "tags": ["usecase:a"]}, + "model_info": {"id": "usecase-deployment"}, + }, + { + "model_name": "gpt-4", + "litellm_params": {"model": "gpt-4o-mini", "tags": ["default"]}, + "model_info": {"id": "default-deployment"}, + }, + ], + enable_tag_filtering=True, + ) + metadata = _baggage_mapped_metadata(client_tags, inherited_tags) + assert "usecase:a" in metadata["tags"] + for _ in range(5): + response = await router.acompletion( + model="gpt-4", + messages=[{"role": "user", "content": "hi"}], + metadata=dict(metadata), + mock_response="hi", + ) + assert response._hidden_params["model_id"] == expected_model_id + + +@pytest.mark.asyncio() +@pytest.mark.parametrize( + "client_tags,inherited_tags,expected_model_id", + [ + ([], [], "tier-b"), + (["usecase:a"], [], "tier-a"), + ([], ["usecase:a"], "tier-a"), + ], +) +async def test_baggage_mapped_tags_never_select_a_tagged_pre_routing_strategy( + client_tags, inherited_tags, expected_model_id +): + from litellm.types.router import TaggedPreRoutingStrategy + + router = litellm.Router( + model_list=[ + { + "model_name": "smart", + "litellm_params": {"model": "openai/gpt-4o"}, + "model_info": {"id": "plain-smart"}, + }, + { + "model_name": "tier-a", + "litellm_params": {"model": "openai/gpt-4o"}, + "model_info": {"id": "tier-a"}, + }, + { + "model_name": "tier-b", + "litellm_params": {"model": "openai/gpt-4o-mini"}, + "model_info": {"id": "tier-b"}, + }, + ], + num_retries=0, + ) + router.auto_routers = { + "smart": [ + TaggedPreRoutingStrategy(tags=("usecase:b",), strategy=_RewriteToTierStrategy("tier-b")), + TaggedPreRoutingStrategy(tags=("usecase:a",), strategy=_RewriteToTierStrategy("tier-a")), + ] + } + metadata = _baggage_mapped_metadata(client_tags, inherited_tags) + assert "usecase:a" in metadata["tags"] + + response = await router.acompletion( + model="smart", + messages=[{"role": "user", "content": "hi"}], + metadata=dict(metadata), + mock_response="hi", + ) + + assert response._hidden_params["model_id"] == expected_model_id + + def _tag_router(model_list: list[dict[str, object]], tag_routing_prefix: str = "route:") -> litellm.Router: return litellm.Router(model_list=model_list, enable_tag_filtering=True, tag_routing_prefix=tag_routing_prefix) diff --git a/tests/unit/router_utils/test_batch_utils.py b/tests/unit/router_utils/test_batch_utils.py index 4aa503ee528..79fe86a37c0 100644 --- a/tests/unit/router_utils/test_batch_utils.py +++ b/tests/unit/router_utils/test_batch_utils.py @@ -2,7 +2,7 @@ import asyncio import importlib import json from io import BytesIO -from typing import Dict, List +from typing import Dict, Final, List import pytest @@ -380,3 +380,31 @@ def setup_and_teardown(): yield loop.close() asyncio.set_event_loop(None) + + +@pytest.mark.parametrize( + ("call_type", "cost", "eligible"), + (("aretrieve_batch", 0.25, True), ("retrieve_batch", 0.25, True), ("acompletion", 0.25, False), + ("aretrieve_batch", 0, False), ("aretrieve_batch", -0.25, False)), +) +def test_batch_charge_identity_requires_a_cost_bearing_retrieval(call_type: str, cost: float, eligible: bool) -> None: + from openai.types import Batch + from litellm.router_utils.batch_utils import batch_id_to_charge_once + + batch: Final = Batch( + id="batch-budget", completion_window="24h", created_at=1, endpoint="/v1/chat/completions", + input_file_id="file-budget", object="batch", status="completed", + ) + assert batch_id_to_charge_once(call_type, batch, cost) == (batch.id if eligible else None) + assert batch_id_to_charge_once(call_type, {"id": batch.id}, cost) is None + + +def test_batch_charge_markers_keep_counters_and_batches_independent() -> None: + from litellm.caching.in_memory_cache import InMemoryCache + from litellm.router_utils.batch_utils import batch_charged_once_marker_key + + cache: Final = InMemoryCache() + cache.set_cache(batch_charged_once_marker_key("provider-spend", "first-batch"), 1) + assert cache.get_cache(batch_charged_once_marker_key("provider-spend", "first-batch")) == 1 + assert cache.get_cache(batch_charged_once_marker_key("deployment-spend", "first-batch")) is None + assert cache.get_cache(batch_charged_once_marker_key("provider-spend", "second-batch")) is None diff --git a/tests/unit/router_utils/test_deployment_pricing.py b/tests/unit/router_utils/test_deployment_pricing.py new file mode 100644 index 00000000000..45cc211a89c --- /dev/null +++ b/tests/unit/router_utils/test_deployment_pricing.py @@ -0,0 +1,53 @@ +import pytest + +from litellm.router_utils.deployment_pricing import deployment_pricing_models, pricing_models + + +@pytest.mark.parametrize( + "base_model, model, expected", + [ + ("azure/gpt-4.1", "azure/my-gpt4-deploy", ("azure/gpt-4.1", "azure/my-gpt4-deploy")), + (None, "azure/my-gpt4-deploy", ("azure/my-gpt4-deploy",)), + ("", "azure/my-gpt4-deploy", ("azure/my-gpt4-deploy",)), + ("azure/gpt-4.1", "azure/gpt-4.1", ("azure/gpt-4.1",)), + (None, None, ()), + ], + ids=["base_model_first", "no_base_model", "blank_base_model", "same_name_once", "nothing_named"], +) +def test_pricing_models_walks_base_model_then_deployment_model(base_model, model, expected): + assert pricing_models(base_model, model) == expected + + +@pytest.mark.parametrize( + "deployment, expected", + [ + ( + {"litellm_params": {"model": "azure/my-gpt4-deploy"}, "model_info": {"base_model": "azure/gpt-4.1"}}, + ("azure/gpt-4.1", "azure/my-gpt4-deploy"), + ), + ( + {"litellm_params": {"model": "azure/my-gpt4-deploy", "base_model": "azure/gpt-4.1"}}, + ("azure/gpt-4.1", "azure/my-gpt4-deploy"), + ), + ( + { + "litellm_params": {"model": "azure/my-gpt4-deploy", "base_model": "azure/gpt-4o"}, + "model_info": {"base_model": "azure/gpt-4.1"}, + }, + ("azure/gpt-4.1", "azure/my-gpt4-deploy"), + ), + ({"litellm_params": {"model": "openai/gpt-4.1"}, "model_info": {}}, ("openai/gpt-4.1",)), + ({"litellm_params": "not-a-dict", "model_info": None}, ()), + ("not-a-deployment", ()), + ], + ids=[ + "model_info_base_model", + "params_base_model", + "model_info_wins", + "no_base_model", + "malformed_blocks", + "not_a_dict", + ], +) +def test_deployment_pricing_models_reads_the_deployment_dict(deployment, expected): + assert deployment_pricing_models(deployment) == expected diff --git a/tests/unit/router_utils/test_embedding_batch_size_check.py b/tests/unit/router_utils/test_embedding_batch_size_check.py new file mode 100644 index 00000000000..d5986d9e6f7 --- /dev/null +++ b/tests/unit/router_utils/test_embedding_batch_size_check.py @@ -0,0 +1,1024 @@ +import datetime +import json +import threading +from collections.abc import Iterator +from types import MappingProxyType +from typing import Final + +import httpx +import pytest +import respx +from prometheus_client import REGISTRY + +import litellm +from litellm import Router +from litellm.types.router import Deployment, LiteLLM_Params, ModelInfo +from litellm.constants import PROXY_REJECTED_BEFORE_ROUTING_KEY +from litellm.integrations.custom_logger import CustomLogger +from litellm.integrations.prometheus import PrometheusLogger +from litellm.litellm_core_utils.litellm_logging import Logging as LitellmLogging +from litellm.types.router import RouterRateLimitError +from litellm.router_utils.embedding_batch_size_check import ( + count_embedding_inputs, + deployments_admitting_embedding_batch, + deployments_when_none_admits_embedding_batch, + effective_embedding_input, + embedding_batch_too_large_error, + embedding_deployment_selection, +) + +_MODEL: Final = "embed-group" +_PROVIDER: Final = "openai" +_OPENAI_EMBED_BASE: Final = "https://batch-limit-embed.local/v1" +_LOGGING_START: Final = datetime.datetime(2026, 1, 1, tzinfo=datetime.timezone.utc) +_VLLM_EMBED_BASE: Final = "https://batch-limit-vllm.local/v1" +_UNCAPPED_EMBED_BASE: Final = "https://batch-limit-uncapped.local/v1" + + +def _model_info(max_embedding_batch_size: int | None) -> dict[str, object]: + if max_embedding_batch_size is None: + return {} + return {"max_embedding_batch_size": max_embedding_batch_size} + + +def _deployment( + limit: int | None, + extra_body: dict[str, object] | None = None, + deployment_id: str = "embed-deployment", +) -> dict[str, object]: + return { + "model_info": {"id": deployment_id, **_model_info(limit)}, + "litellm_params": {} if extra_body is None else {"extra_body": extra_body}, + } + + +def _admitted( + deployments: list[dict[str, object]], + input_value: object, + request_kwargs: dict[str, object] | None = None, + cooling: tuple[dict[str, object], ...] = (), + routable_cooling_ids: frozenset[str] = frozenset(), +) -> list[dict[str, object]]: + admitting: Final = deployments_admitting_embedding_batch(deployments, input_value, request_kwargs) + if admitting is not None: + return admitting + return deployments_when_none_admits_embedding_batch( + deployments, (*deployments, *cooling), routable_cooling_ids, input_value, request_kwargs + ) + + +def _batch_error( + input_value: object, + limit: int | None, + request_kwargs: dict[str, object] | None = None, +) -> litellm.BadRequestError | None: + return embedding_batch_too_large_error( + deployment={"model_info": _model_info(limit), "litellm_params": {"custom_llm_provider": _PROVIDER}}, + input=input_value, + request_kwargs=request_kwargs or {}, + model=_MODEL, + ) + + +def _embedding_router( + *, + provider_model: str, + api_base: str, + max_embedding_batch_size: int | None, + deployment_id: str, + litellm_params_extra: dict[str, object] | None = None, +) -> Router: + litellm_params: dict[str, object] = { + "model": provider_model, + "api_key": "sk-fake", + "api_base": api_base, + } + if litellm_params_extra: + litellm_params.update(litellm_params_extra) + return Router( + model_list=[ + { + "model_name": "embed", + "litellm_params": litellm_params, + "model_info": {"id": deployment_id, **_model_info(max_embedding_batch_size)}, + } + ], + num_retries=0, + ) + + +async def _call_embedding(router: Router, *, sync: bool, **kwargs: object) -> None: + if sync: + router.embedding(**kwargs) + else: + await router.aembedding(**kwargs) + + +def _vllm_embedding_response(input_count: int) -> httpx.Response: + return httpx.Response( + 200, + json={ + "object": "list", + "data": [{"object": "embedding", "index": i, "embedding": [0.1, 0.2]} for i in range(input_count)], + "model": "bge-m3", + "usage": {"prompt_tokens": input_count, "total_tokens": input_count}, + }, + ) + + +@pytest.mark.parametrize( + ("input_value", "expected_count"), + [ + ("hello", 1), + (["a", "b"], 2), + ([1, 2, 3, 4, 5], 1), + ([[1, 2, 3], [4, 5, 6]], 2), + ], +) +def test_openai_input_shapes(input_value: object, expected_count: int) -> None: + assert count_embedding_inputs(input_value) == expected_count + + +def test_batch_count_is_independent_of_string_length() -> None: + long_text: Final = "word " * 500 + assert count_embedding_inputs([long_text, long_text]) == 2 + + +_MIXED_EXTRA_BODY: Final = { + "truncate": "END", + "encoding_format": "float", + "input": ["a", "b", "c"], + "user": "batch-job", +} + + +@pytest.mark.parametrize( + ("top_level", "extra_body", "expected"), + [ + ("ok", None, "ok"), + ("ok", {"input": ["a", "b", "c"]}, ["a", "b", "c"]), + (["a", "b"], {"truncate": "END"}, ["a", "b"]), + ("ignored-top-level", _MIXED_EXTRA_BODY, ["a", "b", "c"]), + ( + ["would", "be", "three"], + {"dimensions": 256, "input": "single-string", "model": "ignored"}, + ["would", "be", "three"], + ), + ("ok", {"truncate": "NONE", "input": ("a", "b")}, ("a", "b")), + (["x", "y", "z"], {"input": [[1, 2], [3, 4]], "foo": "bar"}, ["x", "y", "z"]), + ( + ["a", "b", "c"], + {"input": "ok"}, + ["a", "b", "c"], + ), + (["a", "b"], {}, ["a", "b"]), + (["a", "b", "c"], {"input": None, "truncate": "END"}, ["a", "b", "c"]), + (["a", "b"], {"input": {"nested": "dict"}, "truncate": "END"}, ["a", "b"]), + (["a", "b"], {"input": 42, "dimensions": 128}, ["a", "b"]), + (None, {"input": ["a", "b"]}, ["a", "b"]), + (7, {"input": ["a", "b"]}, ["a", "b"]), + (None, None, None), + ], +) +def test_resolves_provider_bound_input( + top_level: object, + extra_body: dict[str, object] | None, + expected: object, +) -> None: + assert effective_embedding_input(top_level, extra_body) == expected + + +@pytest.mark.parametrize( + "extra_body", + ["not-a-mapping", ["input", "list"]], +) +def test_non_mapping_extra_body_keeps_top_level(extra_body: object) -> None: + top_level: Final = ["a", "b", "c"] + assert effective_embedding_input(top_level, extra_body) == top_level + + +def test_readonly_mapping_extra_body_with_input() -> None: + extra_body: Final = MappingProxyType({"input": ["a", "b"], "encoding_format": "float"}) + assert effective_embedding_input("ok", extra_body) == ["a", "b"] + + +class TestDeploymentsAdmittingEmbeddingBatch: + @pytest.fixture(autouse=True) + def _embedding_selection(self) -> Iterator[None]: + with embedding_deployment_selection(): + yield + + @pytest.mark.parametrize( + ("input_value", "limit"), + [ + ("hello", 1), + (["a", "b"], 2), + (["a", "b", "c"], 3), + ([1, 2, 3, 4, 5], 1), + ([[1, 2, 3], [4, 5, 6]], 2), + ], + ) + def test_keeps_deployments_whose_limit_admits_the_batch(self, input_value: str | list, limit: int) -> None: + capped: Final = _deployment(limit) + uncapped: Final = _deployment(None) + assert _admitted([capped, uncapped], input_value) == [capped, uncapped] + + def test_drops_deployments_whose_limit_is_below_the_batch(self) -> None: + capped: Final = _deployment(2) + uncapped: Final = _deployment(None) + assert _admitted([capped, uncapped], ["a", "b", "c"]) == [uncapped] + + def test_keeps_the_largest_limit_deployments_when_none_admits_the_batch(self) -> None: + smaller: Final = _deployment(1, deployment_id="smaller") + small: Final = _deployment(2, deployment_id="small") + other_small: Final = _deployment(2, deployment_id="other-small") + assert _admitted([small, smaller, other_small], ["a", "b", "c"]) == [small, other_small] + + def test_request_without_embedding_input_keeps_every_deployment(self) -> None: + capped: Final = _deployment(1) + uncapped: Final = _deployment(None) + assert _admitted([capped, uncapped], None) == [capped, uncapped] + + def test_request_extra_body_replaces_the_deployment_extra_body(self) -> None: + capped: Final = _deployment(2, extra_body={"input": ["a", "b", "c"]}) + uncapped: Final = _deployment(None) + assert _admitted([capped, uncapped], "ok") == [uncapped] + assert _admitted([capped, uncapped], "ok", {"extra_body": {}}) == [capped, uncapped] + + @pytest.mark.parametrize("top_level", [None, 7, {"text": "a"}]) + def test_extra_body_input_routes_when_top_level_input_is_not_a_list(self, top_level: object) -> None: + capped: Final = _deployment(2) + uncapped: Final = _deployment(None) + request_kwargs: Final = {"extra_body": {"input": ["a", "b", "c"]}} + assert _admitted([capped, uncapped], top_level, request_kwargs) == [uncapped] + + def test_keeps_no_deployment_while_only_a_cooling_one_admits_the_batch(self) -> None: + capped: Final = _deployment(2, deployment_id="capped") + cooling: Final = _deployment(None, deployment_id="cooling") + assert _admitted([capped], ["a", "b", "c"], cooling=(cooling,), routable_cooling_ids=frozenset({"cooling"})) == [] + + def test_cooling_deployment_the_request_cannot_route_to_does_not_hold_the_batch(self) -> None: + capped: Final = _deployment(2, deployment_id="capped") + cooling: Final = _deployment(None, deployment_id="cooling") + assert _admitted([capped], ["a", "b", "c"], cooling=(cooling,)) == [capped] + + def test_paused_cooling_deployment_does_not_hold_the_batch(self) -> None: + capped: Final = _deployment(2, deployment_id="capped") + paused: Final = {"model_info": {"id": "cooling", "blocked": True}, "litellm_params": {}} + assert _admitted([capped], ["a", "b", "c"], cooling=(paused,), routable_cooling_ids=frozenset({"cooling"})) == [ + capped + ] + + def test_keeps_every_deployment_when_the_cooling_one_also_rejects_the_batch(self) -> None: + capped: Final = _deployment(2, deployment_id="capped") + cooling: Final = _deployment(1, deployment_id="cooling") + assert _admitted([capped], ["a", "b", "c"], cooling=(cooling,), routable_cooling_ids=frozenset({"cooling"})) == [ + capped + ] + + +@pytest.mark.parametrize( + ("input_value", "limit", "message_match"), + [ + (["a", "b", "c", "d"], 3, "4 inputs"), + ([[1], [2], [3]], 2, None), + ( + effective_embedding_input( + "ok", + {"truncate": "END", "input": ["a", "b", "c", "d"], "user": "x"}, + ), + 3, + "4 inputs", + ), + ( + effective_embedding_input( + ["a", "b", "c"], + {"input": {"bad": "shape"}, "encoding_format": "float"}, + ), + 2, + None, + ), + ], +) +def test_rejects_inputs_above_limit( + input_value: str | list, + limit: int, + message_match: str | None, +) -> None: + error: Final = _batch_error(input_value, limit) + assert isinstance(error, litellm.BadRequestError) + assert error.status_code == 400 + if message_match is not None: + assert message_match in error.message + assert f"max_embedding_batch_size={limit}" in error.message + + +@pytest.mark.parametrize("top_level", [None, 7, {"text": "a"}]) +def test_extra_body_override_counts_when_top_level_input_is_not_a_list(top_level: object) -> None: + error: Final = _batch_error(top_level, 2, {"extra_body": {"input": ["a", "b", "c"]}}) + assert error is not None + assert "3 inputs" in error.message + + +class TestRouterEmbeddingBatchLimit: + @pytest.fixture(autouse=True) + def _disable_aiohttp(self, monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + + @pytest.mark.parametrize("sync", [False, True], ids=["async", "sync"]) + @pytest.mark.asyncio + async def test_oversized_top_level_input_rejects_before_provider_call(self, sync: bool) -> None: + router: Final = _embedding_router( + provider_model="openai/text-embedding-3-small", + api_base=_OPENAI_EMBED_BASE, + max_embedding_batch_size=2, + deployment_id="embed-batch-capped", + ) + embeddings_url: Final = f"{_OPENAI_EMBED_BASE}/embeddings" + empty_ok: Final = httpx.Response(200, json={"object": "list", "data": [], "model": "x", "usage": {}}) + + with respx.mock(assert_all_called=False) as respx_mock: + route: Final = respx_mock.post(embeddings_url).mock(return_value=empty_ok) + with pytest.raises(litellm.BadRequestError, match="max_embedding_batch_size=2"): + await _call_embedding( + router, + sync=sync, + model="embed", + input=["one", "two", "three"], + ) + assert route.call_count == 0 + + @pytest.mark.parametrize("sync", [False, True], ids=["async", "sync"]) + @pytest.mark.asyncio + async def test_oversized_batch_rejection_reaches_failure_callbacks(self, sync: bool) -> None: + failures: Final[list[tuple[Exception, object]]] = [] + + class FailureRecorder(CustomLogger): + def log_failure_event(self, kwargs, response_obj, start_time, end_time): + failures.append((kwargs["exception"], kwargs["litellm_params"].get(PROXY_REJECTED_BEFORE_ROUTING_KEY))) + + async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time): + failures.append((kwargs["exception"], kwargs["litellm_params"].get(PROXY_REJECTED_BEFORE_ROUTING_KEY))) + + recorder: Final = FailureRecorder() + logging_obj: Final = LitellmLogging( + model="embed", + messages=[], + stream=False, + call_type="embedding" if sync else "aembedding", + start_time=_LOGGING_START, + litellm_call_id="embed-batch-rejected", + function_id="embed-batch-rejected", + dynamic_failure_callbacks=[recorder] if sync else None, + dynamic_async_failure_callbacks=None if sync else [recorder], + ) + logging_obj.model_call_details["litellm_params"] = {"metadata": {}, "proxy_server_request": {}} + router: Final = _embedding_router( + provider_model="openai/text-embedding-3-small", + api_base=_OPENAI_EMBED_BASE, + max_embedding_batch_size=2, + deployment_id="embed-batch-capped", + ) + + with respx.mock(assert_all_called=False) as respx_mock: + route: Final = respx_mock.post(f"{_OPENAI_EMBED_BASE}/embeddings").mock( + return_value=httpx.Response(200, json={"object": "list", "data": [], "model": "x", "usage": {}}) + ) + with pytest.raises(litellm.BadRequestError, match="3 inputs") as excinfo: + await _call_embedding( + router, + sync=sync, + model="embed", + input=["one", "two", "three"], + litellm_logging_obj=logging_obj, + ) + assert route.call_count == 0 + assert failures == [(excinfo.value, True)] + + @pytest.mark.asyncio + async def test_async_rejection_logs_each_failure_hook_once_before_raising(self) -> None: + hook_events: Final[list[str]] = [] + legacy_callback_threads: Final[list[int]] = [] + legacy_callback_ran: Final = threading.Event() + + class BothHooks(CustomLogger): + def log_failure_event(self, kwargs, response_obj, start_time, end_time): + hook_events.append("sync") + + async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time): + hook_events.append("async") + + def legacy_failure_callback(kwargs, completion_response, start_time, end_time) -> None: + legacy_callback_threads.append(threading.get_ident()) + legacy_callback_ran.set() + + both_hooks: Final = BothHooks() + logging_obj: Final = LitellmLogging( + model="embed", + messages=[], + stream=False, + call_type="aembedding", + start_time=_LOGGING_START, + litellm_call_id="embed-batch-logged-once", + function_id="embed-batch-logged-once", + dynamic_failure_callbacks=[legacy_failure_callback, both_hooks], + dynamic_async_failure_callbacks=[both_hooks], + ) + logging_obj.model_call_details["litellm_params"] = {"metadata": {}, "proxy_server_request": {}} + router: Final = _embedding_router( + provider_model="openai/text-embedding-3-small", + api_base=_OPENAI_EMBED_BASE, + max_embedding_batch_size=2, + deployment_id="embed-batch-capped", + ) + + with pytest.raises(litellm.BadRequestError, match="3 inputs"): + await router.aembedding(model="embed", input=["one", "two", "three"], litellm_logging_obj=logging_obj) + + assert legacy_callback_ran.wait(timeout=5) + assert legacy_callback_threads == [threading.get_ident()] + assert hook_events == ["async"] + + @pytest.mark.parametrize("sync", [False, True], ids=["async", "sync"]) + @pytest.mark.asyncio + async def test_fallback_after_a_rejection_logs_its_provider_call_as_reached(self, sync: bool) -> None: + litellm_params: Final[dict[str, object]] = {"model": "openai/text-embedding-3-small", "api_key": "sk-fake"} + router: Final = Router( + model_list=[ + { + "model_name": "embed-capped", + "litellm_params": {**litellm_params, "api_base": _OPENAI_EMBED_BASE}, + "model_info": {"id": "capped-box", "max_embedding_batch_size": 2}, + }, + { + "model_name": "embed-fallback", + "litellm_params": {**litellm_params, "api_base": _VLLM_EMBED_BASE}, + "model_info": {"id": "fallback-box"}, + }, + ], + fallbacks=[{"embed-capped": ["embed-fallback"]}], + num_retries=0, + ) + logging_obj: Final = LitellmLogging( + model="embed-capped", + messages=[], + stream=False, + call_type="embedding" if sync else "aembedding", + start_time=_LOGGING_START, + litellm_call_id="embed-batch-fallback", + function_id="embed-batch-fallback", + ) + logging_obj.update_environment_variables( + litellm_params={"metadata": {}, "proxy_server_request": {}}, optional_params={} + ) + + with respx.mock(assert_all_called=False) as respx_mock: + capped_route: Final = respx_mock.post(f"{_OPENAI_EMBED_BASE}/embeddings").mock( + return_value=_vllm_embedding_response(3) + ) + fallback_route: Final = respx_mock.post(f"{_VLLM_EMBED_BASE}/embeddings").mock( + return_value=_vllm_embedding_response(3) + ) + await _call_embedding( + router, + sync=sync, + model="embed-capped", + input=["one", "two", "three"], + litellm_logging_obj=logging_obj, + ) + assert (capped_route.call_count, fallback_route.call_count) == (0, 1) + assert PROXY_REJECTED_BEFORE_ROUTING_KEY not in logging_obj.model_call_details["litellm_params"] + + @pytest.fixture + def _isolated_prometheus_registry(self) -> Iterator[None]: + def unregister_all() -> None: + for collector in tuple(REGISTRY._collector_to_names): + REGISTRY.unregister(collector) + + unregister_all() + yield + unregister_all() + + @pytest.mark.asyncio + @pytest.mark.usefixtures("_isolated_prometheus_registry") + async def test_oversized_batch_rejection_leaves_the_deployment_healthy_in_prometheus(self) -> None: + prometheus: Final = PrometheusLogger() + metadata: Final[dict[str, object]] = {} + logging_obj: Final = LitellmLogging( + model="embed", + messages=[], + stream=False, + call_type="aembedding", + start_time=_LOGGING_START, + litellm_call_id="embed-batch-prometheus", + function_id="embed-batch-prometheus", + dynamic_async_failure_callbacks=[prometheus], + ) + logging_obj.model_call_details["litellm_params"] = {"metadata": metadata, "proxy_server_request": {}} + router: Final = _embedding_router( + provider_model="openai/text-embedding-3-small", + api_base=_OPENAI_EMBED_BASE, + max_embedding_batch_size=2, + deployment_id="embed-batch-capped", + ) + + with respx.mock(assert_all_called=False) as respx_mock: + respx_mock.post(f"{_OPENAI_EMBED_BASE}/embeddings").mock( + return_value=httpx.Response(200, json={"object": "list", "data": [], "model": "x", "usage": {}}) + ) + with pytest.raises(litellm.BadRequestError, match="3 inputs"): + await router.aembedding( + model="embed", input=["one", "two", "three"], metadata=metadata, litellm_logging_obj=logging_obj + ) + assert prometheus.litellm_deployment_state._metrics == {} + + @pytest.mark.parametrize("sync", [False, True], ids=["async", "sync"]) + @pytest.mark.asyncio + async def test_no_limit_configured_forwards_any_batch(self, sync: bool) -> None: + router: Final = _embedding_router( + provider_model="hosted_vllm/bge-m3", + api_base=_VLLM_EMBED_BASE, + max_embedding_batch_size=None, + deployment_id="vllm-embed-uncapped", + ) + + with respx.mock(assert_all_called=False) as respx_mock: + route: Final = respx_mock.post(f"{_VLLM_EMBED_BASE}/embeddings").mock( + return_value=_vllm_embedding_response(100) + ) + await _call_embedding(router, sync=sync, model="embed", input=["a"] * 100) + assert len(json.loads(route.calls.last.request.content)["input"]) == 100 + + @pytest.mark.parametrize("sync", [False, True], ids=["async", "sync"]) + @pytest.mark.asyncio + async def test_oversized_batch_goes_to_the_group_deployment_that_admits_it(self, sync: bool) -> None: + router: Final = Router( + model_list=[ + { + "model_name": "embed", + "litellm_params": { + "model": "hosted_vllm/bge-m3", + "api_key": "sk-fake", + "api_base": _VLLM_EMBED_BASE, + "weight": 1000, + }, + "model_info": {"id": "vllm-embed-capped", "max_embedding_batch_size": 2}, + }, + { + "model_name": "embed", + "litellm_params": { + "model": "hosted_vllm/bge-m3", + "api_key": "sk-fake", + "api_base": _UNCAPPED_EMBED_BASE, + "weight": 1, + }, + "model_info": {"id": "vllm-embed-uncapped"}, + }, + ], + num_retries=0, + ) + + with respx.mock(assert_all_called=False) as respx_mock: + capped_route: Final = respx_mock.post(f"{_VLLM_EMBED_BASE}/embeddings").mock( + return_value=_vllm_embedding_response(3) + ) + uncapped_route: Final = respx_mock.post(f"{_UNCAPPED_EMBED_BASE}/embeddings").mock( + return_value=_vllm_embedding_response(3) + ) + for _ in range(5): + await _call_embedding(router, sync=sync, model="embed", input=["a", "b", "c"]) + assert (capped_route.call_count, uncapped_route.call_count) == (0, 5) + + @pytest.mark.asyncio + async def test_non_embedding_call_with_input_ignores_embedding_batch_limit(self) -> None: + router: Final = Router( + model_list=[ + { + "model_name": "embed", + "litellm_params": { + "model": "openai/text-embedding-3-small", + "api_key": "sk-fake", + "api_base": _OPENAI_EMBED_BASE, + "order": 1, + }, + "model_info": {"id": "capped", "max_embedding_batch_size": 2}, + }, + { + "model_name": "embed", + "litellm_params": { + "model": "openai/text-embedding-3-small", + "api_key": "sk-fake", + "api_base": _UNCAPPED_EMBED_BASE, + "order": 2, + }, + "model_info": {"id": "uncapped"}, + }, + ], + num_retries=0, + ) + responses_input: Final = [{"role": "user", "content": str(turn)} for turn in range(3)] + + async_pick: Final = await router.async_get_available_deployment( + model="embed", request_kwargs={}, input=responses_input + ) + sync_pick: Final = router.get_available_deployment(model="embed", request_kwargs={}, input=responses_input) + + assert (async_pick["model_info"]["id"], sync_pick["model_info"]["id"]) == ("capped", "capped") + + @pytest.mark.parametrize("sync", [False, True], ids=["async", "sync"]) + @pytest.mark.asyncio + async def test_oversized_batch_waits_for_a_cooling_down_deployment_that_admits_it(self, sync: bool) -> None: + router: Final = Router( + model_list=[ + { + "model_name": "embed", + "litellm_params": { + "model": "hosted_vllm/bge-m3", + "api_key": "sk-fake", + "api_base": _VLLM_EMBED_BASE, + }, + "model_info": {"id": "vllm-embed-capped", "max_embedding_batch_size": 2}, + }, + { + "model_name": "embed", + "litellm_params": { + "model": "hosted_vllm/bge-m3", + "api_key": "sk-fake", + "api_base": _UNCAPPED_EMBED_BASE, + }, + "model_info": {"id": "vllm-embed-uncapped"}, + }, + ], + num_retries=0, + ) + + with respx.mock(assert_all_called=False) as respx_mock: + capped_route: Final = respx_mock.post(f"{_VLLM_EMBED_BASE}/embeddings").mock( + return_value=_vllm_embedding_response(3) + ) + uncapped_route: Final = respx_mock.post(f"{_UNCAPPED_EMBED_BASE}/embeddings").mock( + return_value=httpx.Response(429, json={"error": {"message": "rate limited"}}) + ) + with pytest.raises(litellm.RateLimitError): + await _call_embedding(router, sync=sync, model="embed", input=["a", "b", "c"]) + with pytest.raises(RouterRateLimitError): + await _call_embedding(router, sync=sync, model="embed", input=["a", "b", "c"]) + assert (capped_route.call_count, uncapped_route.call_count) == (0, 1) + + @pytest.mark.parametrize("sync", [False, True], ids=["async", "sync"]) + @pytest.mark.asyncio + async def test_oversized_batch_names_the_cap_while_a_paused_admitting_deployment_cools_down( + self, sync: bool + ) -> None: + uncapped_params: Final = {"model": "hosted_vllm/bge-m3", "api_key": "sk-fake", "api_base": _UNCAPPED_EMBED_BASE} + router: Final = Router( + model_list=[ + { + "model_name": "embed", + "litellm_params": { + "model": "hosted_vllm/bge-m3", + "api_key": "sk-fake", + "api_base": _VLLM_EMBED_BASE, + }, + "model_info": {"id": "vllm-embed-capped", "max_embedding_batch_size": 2}, + }, + {"model_name": "embed", "litellm_params": uncapped_params, "model_info": {"id": "vllm-embed-uncapped"}}, + ], + num_retries=0, + ) + + with respx.mock(assert_all_called=False) as respx_mock: + capped_route: Final = respx_mock.post(f"{_VLLM_EMBED_BASE}/embeddings").mock( + return_value=_vllm_embedding_response(3) + ) + uncapped_route: Final = respx_mock.post(f"{_UNCAPPED_EMBED_BASE}/embeddings").mock( + return_value=httpx.Response(429, json={"error": {"message": "rate limited"}}) + ) + with pytest.raises(litellm.RateLimitError): + await _call_embedding(router, sync=sync, model="embed", input=["a", "b", "c"]) + router.upsert_deployment( + Deployment( + model_name="embed", + litellm_params=LiteLLM_Params(**uncapped_params), + model_info=ModelInfo(id="vllm-embed-uncapped", blocked=True), + ) + ) + with pytest.raises(litellm.BadRequestError, match="max_embedding_batch_size=2"): + await _call_embedding(router, sync=sync, model="embed", input=["a", "b", "c"]) + assert (capped_route.call_count, uncapped_route.call_count) == (0, 1) + + @pytest.mark.parametrize("sync", [False, True], ids=["async", "sync"]) + @pytest.mark.asyncio + async def test_extra_body_input_override_rejects_before_provider_call(self, sync: bool) -> None: + router: Final = _embedding_router( + provider_model="hosted_vllm/bge-m3", + api_base=_VLLM_EMBED_BASE, + max_embedding_batch_size=2, + deployment_id="vllm-embed-batch-capped", + ) + embeddings_url: Final = f"{_VLLM_EMBED_BASE}/embeddings" + extra_body: Final = {"truncate": "END", "input": ["a", "b", "c"]} + + with respx.mock(assert_all_called=False) as respx_mock: + route: Final = respx_mock.post(embeddings_url).mock(return_value=_vllm_embedding_response(3)) + with pytest.raises(litellm.BadRequestError, match="3 inputs"): + await _call_embedding( + router, + sync=sync, + model="embed", + input="ok", + extra_body=extra_body, + ) + assert route.call_count == 0 + + @pytest.mark.asyncio + async def test_deployment_extra_body_input_counts_toward_batch_limit(self) -> None: + router: Final = Router( + model_list=[ + { + "model_name": "embed", + "litellm_params": { + "model": "hosted_vllm/bge-m3", + "api_key": "sk-fake", + "api_base": _VLLM_EMBED_BASE, + "extra_body": {"input": ["a", "b", "c"]}, + }, + "model_info": { + "id": "vllm-embed-deployment-extra-body", + "max_embedding_batch_size": 2, + }, + } + ], + num_retries=0, + ) + embeddings_url: Final = f"{_VLLM_EMBED_BASE}/embeddings" + + with respx.mock(assert_all_called=False) as respx_mock: + route: Final = respx_mock.post(embeddings_url).mock(return_value=_vllm_embedding_response(3)) + with pytest.raises(litellm.BadRequestError, match="3 inputs"): + await router.aembedding(model="embed", input="ok") + assert route.call_count == 0 + + @pytest.mark.asyncio + async def test_extra_body_input_at_limit_reaches_provider(self) -> None: + router: Final = _embedding_router( + provider_model="hosted_vllm/bge-m3", + api_base=_VLLM_EMBED_BASE, + max_embedding_batch_size=2, + deployment_id="vllm-embed-batch-capped", + ) + embeddings_url: Final = f"{_VLLM_EMBED_BASE}/embeddings" + + with respx.mock(assert_all_called=False) as respx_mock: + route: Final = respx_mock.post(embeddings_url).mock(return_value=_vllm_embedding_response(2)) + await router.aembedding(model="embed", input="ok", extra_body={"input": ["a", "b"]}) + assert route.call_count == 1 + assert json.loads(route.calls.last.request.content)["input"] == ["a", "b"] + + @pytest.mark.asyncio + async def test_unrelated_extra_body_does_not_bypass_top_level_batch_limit(self) -> None: + router: Final = _embedding_router( + provider_model="hosted_vllm/bge-m3", + api_base=_VLLM_EMBED_BASE, + max_embedding_batch_size=2, + deployment_id="vllm-embed-batch-capped", + ) + embeddings_url: Final = f"{_VLLM_EMBED_BASE}/embeddings" + + with respx.mock(assert_all_called=False) as respx_mock: + route: Final = respx_mock.post(embeddings_url).mock(return_value=_vllm_embedding_response(3)) + with pytest.raises(litellm.BadRequestError, match="3 inputs"): + await _call_embedding( + router, + sync=False, + model="embed", + input=["a", "b", "c"], + extra_body={"truncate": "END", "encoding_format": "float"}, + ) + assert route.call_count == 0 + + @pytest.mark.parametrize("sync", [False, True], ids=["async", "sync"]) + @pytest.mark.asyncio + async def test_bedrock_ignores_extra_body_input_override_for_provider_but_guard_uses_top_level( + self, + sync: bool, + ) -> None: + router: Final = _embedding_router( + provider_model="bedrock/amazon.titan-embed-text-v1", + api_base="", + max_embedding_batch_size=2, + deployment_id="bedrock-titan-embed-batch-capped", + litellm_params_extra={ + "aws_access_key_id": "AKIAFAKE", + "aws_secret_access_key": "fake-secret", + "aws_region_name": "us-east-1", + "custom_llm_provider": "bedrock", + }, + ) + + with pytest.raises(litellm.BadRequestError, match="3 inputs"): + await _call_embedding( + router, + sync=sync, + model="embed", + input=["a", "b", "c"], + extra_body={"input": "ok"}, + ) + + @pytest.mark.parametrize("sync", [False, True], ids=["async", "sync"]) + @pytest.mark.asyncio + async def test_explicit_custom_llm_provider_in_deployment_rejects_oversized_batch( + self, + sync: bool, + ) -> None: + router: Final = _embedding_router( + provider_model="openai/text-embedding-3-small", + api_base=_OPENAI_EMBED_BASE, + max_embedding_batch_size=2, + deployment_id="embed-batch-capped-explicit-provider", + litellm_params_extra={"custom_llm_provider": "openai"}, + ) + embeddings_url: Final = f"{_OPENAI_EMBED_BASE}/embeddings" + empty_ok: Final = httpx.Response(200, json={"object": "list", "data": [], "model": "x", "usage": {}}) + + with respx.mock(assert_all_called=False) as respx_mock: + route: Final = respx_mock.post(embeddings_url).mock(return_value=empty_ok) + with pytest.raises(litellm.BadRequestError, match="max_embedding_batch_size=2"): + await _call_embedding( + router, + sync=sync, + model="embed", + input=["one", "two", "three"], + ) + assert route.call_count == 0 + + @pytest.mark.asyncio + async def test_oversized_batch_names_the_cap_when_tags_exclude_the_admitting_deployment(self) -> None: + router: Final = Router( + model_list=[ + { + "model_name": "embed", + "litellm_params": { + "model": "hosted_vllm/bge-m3", + "api_key": "sk-fake", + "api_base": _VLLM_EMBED_BASE, + "tags": ["team-a"], + }, + "model_info": {"id": "team-a-capped", "max_embedding_batch_size": 2}, + }, + { + "model_name": "embed", + "litellm_params": { + "model": "hosted_vllm/bge-m3", + "api_key": "sk-fake", + "api_base": _UNCAPPED_EMBED_BASE, + "tags": ["team-b"], + }, + "model_info": {"id": "team-b-uncapped"}, + }, + ], + enable_tag_filtering=True, + num_retries=0, + ) + + with respx.mock(assert_all_called=False) as respx_mock: + capped_route: Final = respx_mock.post(f"{_VLLM_EMBED_BASE}/embeddings").mock( + return_value=_vllm_embedding_response(3) + ) + uncapped_route: Final = respx_mock.post(f"{_UNCAPPED_EMBED_BASE}/embeddings").mock( + return_value=_vllm_embedding_response(3) + ) + with pytest.raises(litellm.BadRequestError, match="max_embedding_batch_size=2"): + await router.aembedding(model="embed", input=["a", "b", "c"], metadata={"tags": ["team-a"]}) + assert (capped_route.call_count, uncapped_route.call_count) == (0, 0) + + @pytest.mark.asyncio + async def test_oversized_batch_names_the_cap_while_another_tags_admitting_deployment_cools_down(self) -> None: + router: Final = Router( + model_list=[ + { + "model_name": "embed", + "litellm_params": { + "model": "hosted_vllm/bge-m3", + "api_key": "sk-fake", + "api_base": _VLLM_EMBED_BASE, + "tags": ["team-a"], + }, + "model_info": {"id": "team-a-capped", "max_embedding_batch_size": 2}, + }, + { + "model_name": "embed", + "litellm_params": { + "model": "hosted_vllm/bge-m3", + "api_key": "sk-fake", + "api_base": _UNCAPPED_EMBED_BASE, + "tags": ["team-b"], + }, + "model_info": {"id": "team-b-uncapped"}, + }, + ], + enable_tag_filtering=True, + num_retries=0, + ) + + with respx.mock(assert_all_called=False) as respx_mock: + capped_route: Final = respx_mock.post(f"{_VLLM_EMBED_BASE}/embeddings").mock( + return_value=_vllm_embedding_response(3) + ) + uncapped_route: Final = respx_mock.post(f"{_UNCAPPED_EMBED_BASE}/embeddings").mock( + return_value=httpx.Response(429, json={"error": {"message": "rate limited"}}) + ) + with pytest.raises(litellm.RateLimitError): + await router.aembedding(model="embed", input=["a", "b", "c"], metadata={"tags": ["team-b"]}) + with pytest.raises(litellm.BadRequestError, match="max_embedding_batch_size=2"): + await router.aembedding(model="embed", input=["a", "b", "c"], metadata={"tags": ["team-a"]}) + assert (capped_route.call_count, uncapped_route.call_count) == (0, 1) + + @pytest.mark.parametrize("sync", [False, True], ids=["async", "sync"]) + @pytest.mark.asyncio + async def test_oversized_batch_names_the_cap_while_another_regions_admitting_deployment_cools_down( + self, sync: bool + ) -> None: + router: Final = Router( + model_list=[ + { + "model_name": "embed", + "litellm_params": { + "model": "hosted_vllm/bge-m3", + "api_key": "sk-fake", + "api_base": _VLLM_EMBED_BASE, + "region_name": "eu", + }, + "model_info": {"id": "eu-capped", "max_embedding_batch_size": 2}, + }, + { + "model_name": "embed", + "litellm_params": { + "model": "hosted_vllm/bge-m3", + "api_key": "sk-fake", + "api_base": _UNCAPPED_EMBED_BASE, + "region_name": "us", + }, + "model_info": {"id": "us-uncapped"}, + }, + ], + enable_pre_call_checks=True, + num_retries=0, + ) + + with respx.mock(assert_all_called=False) as respx_mock: + capped_route: Final = respx_mock.post(f"{_VLLM_EMBED_BASE}/embeddings").mock( + return_value=_vllm_embedding_response(3) + ) + uncapped_route: Final = respx_mock.post(f"{_UNCAPPED_EMBED_BASE}/embeddings").mock( + return_value=httpx.Response(429, json={"error": {"message": "rate limited"}}) + ) + with pytest.raises(litellm.RateLimitError): + await _call_embedding( + router, sync=sync, model="embed", input=["a", "b", "c"], allowed_model_region="us" + ) + with pytest.raises(litellm.BadRequestError, match="max_embedding_batch_size=2"): + await _call_embedding( + router, sync=sync, model="embed", input=["a", "b", "c"], allowed_model_region="eu" + ) + assert (capped_route.call_count, uncapped_route.call_count) == (0, 1) + + @pytest.mark.parametrize("sync", [False, True], ids=["async", "sync"]) + @pytest.mark.asyncio + async def test_oversized_batch_rejection_falls_back_with_explicit_provider(self, sync: bool) -> None: + router: Final = Router( + model_list=[ + { + "model_name": "embed", + "litellm_params": { + "model": "openai/text-embedding-3-small", + "api_key": "sk-fake", + "api_base": _OPENAI_EMBED_BASE, + "custom_llm_provider": "openai", + }, + "model_info": {"id": "explicit-provider-capped", "max_embedding_batch_size": 2}, + }, + { + "model_name": "embed-fallback", + "litellm_params": { + "model": "hosted_vllm/bge-m3", + "api_key": "sk-fake", + "api_base": _UNCAPPED_EMBED_BASE, + }, + "model_info": {"id": "fallback-uncapped"}, + }, + ], + fallbacks=[{"embed": ["embed-fallback"]}], + fallback_on_unsupported_params=False, + num_retries=0, + ) + + with respx.mock(assert_all_called=False) as respx_mock: + capped_route: Final = respx_mock.post(f"{_OPENAI_EMBED_BASE}/embeddings").mock( + return_value=_vllm_embedding_response(3) + ) + fallback_route: Final = respx_mock.post(f"{_UNCAPPED_EMBED_BASE}/embeddings").mock( + return_value=_vllm_embedding_response(3) + ) + await _call_embedding(router, sync=sync, model="embed", input=["a", "b", "c"]) + assert (capped_route.call_count, fallback_route.call_count) == (0, 1) diff --git a/tests/unit/router_utils/test_prompt_caching_cache.py b/tests/unit/router_utils/test_prompt_caching_cache.py index 46af2454dea..ce8f04b8c54 100644 --- a/tests/unit/router_utils/test_prompt_caching_cache.py +++ b/tests/unit/router_utils/test_prompt_caching_cache.py @@ -608,6 +608,23 @@ def test_unmarked_tools_change_the_key_marked_tools_do_not_share(): assert key_a != key_b +def test_a_non_dict_tool_entry_still_derives_a_key_instead_of_raising(): + """ + A client can send `tools: ["not-a-tool"]`. The provider rejects that with its own 400, so the + routing check has to key on what it was given and let the request through, never raise a 500. + """ + messages = cast( + list[AllMessageValues], + [{"role": "user", "content": [{"type": "text", "text": "hi", "cache_control": {"type": "ephemeral"}}]}], + ) + tools: Final = cast(list[ChatCompletionToolParam], ["not-a-tool", _marked_tool("read", {"type": "ephemeral"})]) + + positions = PromptCachingCache.prefix_positions(messages, tools) + + assert [position.position for position in positions] == [0, 1] + assert PromptCachingCache.get_prompt_caching_cache_key(messages, tools) == positions[-1].cache_key + + def test_empty_and_missing_tools_seed_the_same_key(): """`tools=[]` and no tools at all are the same request to the provider, so they must key alike.""" messages = cast( diff --git a/tests/unit/router_utils/test_request_priority.py b/tests/unit/router_utils/test_request_priority.py new file mode 100644 index 00000000000..71ab441d199 --- /dev/null +++ b/tests/unit/router_utils/test_request_priority.py @@ -0,0 +1,112 @@ +from typing import Final + +import pytest + +import litellm +from litellm.router_utils.request_priority import ( + InvalidPriority, + parse_default_priority, + request_drops_params, + resolve_request_priority, + unqueueable_priority_message, +) + + +@pytest.mark.parametrize( + ("requested", "default_priority", "expected"), + [ + (None, None, None), + (None, 3, 3), + (2, 3, 2), + (0, 3, 0), + (0, None, 0), + (255, None, 255), + ("1", 3, 1), + (" 2 ", None, 2), + ("-1", 3, -1), + (1.0, 3, 1), + (True, None, 1), + ], +) +def test_an_absent_or_null_priority_takes_the_default_and_an_integer_like_value_wins( + requested: object, default_priority: int | None, expected: int | None +) -> None: + assert resolve_request_priority(requested, default_priority, drops_params=lambda: False) == expected + assert resolve_request_priority(requested, default_priority, drops_params=lambda: True) == expected + + +@pytest.mark.parametrize("requested", ["high", "", [1], 1.5, {"level": 1}]) +def test_a_non_integer_priority_is_rejected_unless_params_are_dropped(requested: object) -> None: + rejected: Final = resolve_request_priority(requested, 3, drops_params=lambda: False) + assert isinstance(rejected, InvalidPriority) + assert rejected.value == requested + assert rejected.message.startswith("priority must be an integer, got ") + assert resolve_request_priority(requested, 3, drops_params=lambda: True) == 3 + assert resolve_request_priority(requested, None, drops_params=lambda: True) is None + + +def test_the_drop_params_decision_is_consulted_only_for_a_non_integer_priority() -> None: + def _never() -> bool: + raise AssertionError("drop_params was consulted") + + assert resolve_request_priority(None, 3, drops_params=_never) == 3 + assert resolve_request_priority(2, 3, drops_params=_never) == 2 + assert resolve_request_priority(0, None, drops_params=_never) == 0 + assert resolve_request_priority("1", 3, drops_params=_never) == 1 + + +def test_the_global_drop_params_wins_then_the_request_then_the_router_defaults_then_the_deployments( + monkeypatch: pytest.MonkeyPatch, +) -> None: + monkeypatch.setattr(litellm, "drop_params", False) + assert request_drops_params({}, {}, ()) is False + assert request_drops_params({"drop_params": True}, {}, ()) is True + assert request_drops_params({"drop_params": "true"}, {}, ()) is True + assert request_drops_params({}, {"drop_params": True}, ()) is True + assert request_drops_params({"drop_params": False}, {"drop_params": True}, ()) is False + assert request_drops_params({}, {}, ({"drop_params": True},)) is True + assert request_drops_params({}, {}, ({"drop_params": True}, {"model": "openai/gpt-5.4-nano"})) is True + assert request_drops_params({}, {}, ({"drop_params": False}, {"model": "openai/gpt-5.4-nano"})) is False + assert request_drops_params({}, {"drop_params": False}, ({"drop_params": True},)) is False + monkeypatch.setattr(litellm, "drop_params", True) + assert request_drops_params({}, {}, ()) is True + assert request_drops_params({}, {}, ({"model": "openai/gpt-5.4-nano"},)) is True + assert request_drops_params({"drop_params": False}, {}, ()) is True + assert request_drops_params({}, {"drop_params": False}, ()) is True + assert request_drops_params({}, {}, ({"drop_params": False},)) is True + assert request_drops_params({"drop_params": "not-a-flag"}, {}, ()) is True + + +def test_a_priority_named_in_additional_drop_params_at_any_level_is_dropped(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr(litellm, "drop_params", False) + by_name: Final = {"additional_drop_params": ["priority"]} + assert request_drops_params(by_name, {}, ()) is True + assert request_drops_params({**by_name, "drop_params": False}, {}, ()) is True + assert request_drops_params({}, by_name, ()) is True + assert request_drops_params({}, {"drop_params": False}, (by_name,)) is True + assert request_drops_params({"additional_drop_params": ["seed"]}, {}, ()) is False + assert request_drops_params({}, {}, (params for params in ({"drop_params": True},))) is True + + +def test_a_request_it_cannot_queue_is_told_why() -> None: + assert "priority is required" in unqueueable_priority_message(None) + assert unqueueable_priority_message("high").startswith("priority must be an integer, got str 'high'") + + +@pytest.mark.parametrize( + ("configured", "expected"), + [(None, None), (3, 3), (0, 0), ("3", 3), (" 12 ", 12), ("0", 0), ("-1", -1), (2.0, 2)], + ids=["unset", "int", "zero", "digit-string", "padded-digit-string", "zero-string", "negative-string", "whole-float"], +) +def test_the_default_priority_is_taken_as_an_integer_or_an_integer_like_value( + configured: object, expected: int | None +) -> None: + assert parse_default_priority(configured) == expected + + +@pytest.mark.parametrize("configured", ["high", "", "1.5", 1.5, [3], {"level": 3}, True, False]) +def test_any_other_default_priority_is_invalid(configured: object) -> None: + parsed: Final = parse_default_priority(configured) + assert isinstance(parsed, InvalidPriority) + assert parsed.value == configured + assert parsed.message.startswith("priority must be an integer, got ") diff --git a/tests/unit/rust_bridge/AGENTS.md b/tests/unit/rust_bridge/AGENTS.md index 64c9fbbadd3..abf5ac6bed7 100644 --- a/tests/unit/rust_bridge/AGENTS.md +++ b/tests/unit/rust_bridge/AGENTS.md @@ -4,6 +4,6 @@ Test what each side of the bridge does, not the rollout policy that picks a side Call each path directly with an explicit decision instead. The Python path is the implementation the dispatcher falls back to, e.g. `litellm.responses.main.responses`. The Rust path is the native binding, e.g. `NATIVE_OCR.load()` from `litellm/rust_bridge/ocr/entrypoints.py`, called with the `NativeCall` envelope that dispatch would hand it for every public inference route. When the native side reads a policy-derived setting such as `settings.secret_manager().native`, pin that field in the test instead of deriving it from the catalog. `ocr/test_secrets.py` shows the pattern -Rollout policy itself, meaning which rule matches and what `LITELLM_RUST` changes, belongs in `test_catalog.py`, `test_configuration.py` and `test_dispatch.py`, tested against rules the test builds rather than the shipped `catalog.RULES` +Rollout policy itself, meaning which rule matches and what `LITELLM_RUST` changes, belongs in `test_catalog.py` and `test_configuration.py`, tested against rules the test builds rather than the shipped `catalog.RULES`. Which path a public call takes under those rules is a dispatch test and lives in `tests/test_litellm_rust/` for now Before adding a test here, ask whether it checks something Rust cannot. A `host/routes/.py` module is the Python half of a native route: it projects Python-only state (the cost map, `litellm.*` settings, request kwargs) into the plain values the Rust side consumes, and maps native failures back onto public exceptions. Those projections are what belongs here, because a wrong key or an ignored provider prefix ships the wrong value to Rust and no Rust test sees it. `host/routes/test_messages.py` shows the shape. Behavior that lives in Rust (a request transform given its inputs, header assembly, stream relay) is tested in the crate, and the route end to end is tested against a recording server in `tests/test_litellm_rust/`. A test that only re-checks a Python helper the route host happens to call is a duplicate of that helper's own test and should not be added diff --git a/tests/unit/rust_bridge/host/test_callbacks_legacy_python.py b/tests/unit/rust_bridge/host/test_callbacks_legacy_python.py index eb1bfd82715..a40f8a77105 100644 --- a/tests/unit/rust_bridge/host/test_callbacks_legacy_python.py +++ b/tests/unit/rust_bridge/host/test_callbacks_legacy_python.py @@ -9,6 +9,7 @@ import pytest from pydantic import TypeAdapter from litellm._internal_context import is_internal_call +from litellm.integrations.custom_logger import CustomLogger from litellm.litellm_core_utils.litellm_logging import Logging from litellm.rust_bridge.host import callbacks_legacy_python as legacy from litellm.rust_bridge.host.callbacks_legacy_python import failure_handler, setup @@ -167,6 +168,75 @@ def test_failure_handler_of_an_internal_call_leaves_the_outer_budget_reservation pending.close() +class _Hooks(CustomLogger): + def __init__(self) -> None: + super().__init__() + self.hooks: list[str] = [] + + def log_success_event(self, kwargs: object, response_obj: object, start_time: object, end_time: object) -> None: + self.hooks.append("sync_success") + + async def async_log_success_event( + self, kwargs: object, response_obj: object, start_time: object, end_time: object + ) -> None: + self.hooks.append("async_success") + + def log_failure_event(self, kwargs: object, response_obj: object, start_time: object, end_time: object) -> None: + self.hooks.append("sync_failure") + + async def async_log_failure_event( + self, kwargs: object, response_obj: object, start_time: object, end_time: object + ) -> None: + self.hooks.append("async_failure") + + +def _logger_with_hooks(hooks: _Hooks) -> Logging: + logger: Final = Logging( + model="mistral/mistral-ocr-latest", + messages=[], + stream=False, + call_type="aocr", + start_time=datetime.datetime.now(), + litellm_call_id="hooks", + function_id="hooks", + dynamic_success_callbacks=[hooks], + dynamic_async_success_callbacks=[hooks], + dynamic_failure_callbacks=[hooks], + dynamic_async_failure_callbacks=[hooks], + ) + logger.update_environment_variables(litellm_params={"metadata": {}}, optional_params={}) + return logger + + +@pytest.mark.asyncio +async def test_failure_of_an_async_call_gives_a_logger_with_both_failure_hooks_only_the_async_one() -> None: + hooks: Final = _Hooks() + now: Final = datetime.datetime.now() + kwargs: Final = {**_OCR_KWARGS, "litellm_logging_obj": _logger_with_hooks(hooks)} + result: Final = setup("aocr", (), kwargs, now, asynchronous=True) + + assert failure_handler(result.logger, RuntimeError("upstream refused"), now, now, asynchronous=False) is None + pending: Final = failure_handler(result.logger, RuntimeError("upstream refused"), now, now, asynchronous=True) + assert pending is not None + await pending + + assert hooks.hooks == ["async_failure"] + + +@pytest.mark.parametrize("earlier_async_call", [False, True]) +def test_failure_of_a_sync_call_keeps_the_sync_failure_hook(earlier_async_call: bool) -> None: + hooks: Final = _Hooks() + now: Final = datetime.datetime.now() + kwargs: Final = {**_OCR_KWARGS, "litellm_logging_obj": _logger_with_hooks(hooks)} + if earlier_async_call: + setup("aocr", (), kwargs, now, asynchronous=True) + result: Final = setup("ocr", (), kwargs, now, asynchronous=False) + + assert failure_handler(result.logger, RuntimeError("upstream refused"), now, now, asynchronous=False) is None + + assert hooks.hooks == ["sync_failure"] + + CONTRACT_PATH: Final = Path(__file__).parents[4] / "litellm-rust/crates/callbacks-legacy-python/python_contract.json" diff --git a/tests/unit/rust_bridge/test_catalog.py b/tests/unit/rust_bridge/test_catalog.py index b99342388d6..704a4f73fe8 100644 --- a/tests/unit/rust_bridge/test_catalog.py +++ b/tests/unit/rust_bridge/test_catalog.py @@ -7,10 +7,12 @@ import pytest from litellm.rust_bridge import catalog, configuration from litellm.rust_bridge.catalog import ( + Feature, Route, RouteContext, RouteRule, Rules, + Target, ) from litellm.rust_bridge.configuration import Decision, Rollout @@ -23,36 +25,6 @@ def isolated_configuration(monkeypatch: pytest.MonkeyPatch) -> Generator[None]: configuration.reset_rust_configuration() -@pytest.mark.parametrize("route", tuple(Route)) -@pytest.mark.parametrize( - "provider", (None, "bedrock", "mistral", "anthropic", "deepseek", "vertex_ai", "openai", "azure_ai", "unknown") -) -@pytest.mark.parametrize("process", (None, False, True)) -@pytest.mark.parametrize("environment", (None, "0", "1")) -def test_shipped_decisions( - monkeypatch: pytest.MonkeyPatch, - route: Route, - provider: str | None, - process: bool | None, - environment: str | None, -) -> None: - configuration.rust(process) - if environment is not None: - monkeypatch.setenv("LITELLM_RUST", environment) - context: Final = RouteContext(route, provider=provider, model="test-model") - - if route is Route.OCR or (route is Route.TRANSCRIPTION and provider == "bedrock"): - assert catalog.rollout(context) is Rollout.RUST_REQUIRED - assert catalog.decision(context) is Decision.RUST_REQUIRED - elif route is Route.MESSAGES and provider in ("anthropic", "deepseek", "vertex_ai"): - assert catalog.rollout(context) is Rollout.RUST_OPT_IN - opted_in: Final = environment == "1" or (environment is None and process is True) - assert catalog.decision(context) is (Decision.RUST_WITH_FALLBACK if opted_in else Decision.PYTHON) - else: - assert catalog.rollout(context) is Rollout.PYTHON_ONLY - assert catalog.decision(context) is Decision.PYTHON - - @pytest.mark.parametrize("route", tuple(Route)) def test_missing_rule_stays_on_python_even_when_rust_is_enabled(monkeypatch: pytest.MonkeyPatch, route: Route) -> None: configuration.rust(True) @@ -72,6 +44,11 @@ def test_missing_rule_stays_on_python_even_when_rust_is_enabled(monkeypatch: pyt (RouteContext(Route.RESPONSES, provider="openai", model="other"), Decision.PYTHON), (RouteContext(Route.RESPONSES, provider="anthropic", model="m"), Decision.PYTHON), (RouteContext(Route.MESSAGES, provider="openai", model="m"), Decision.PYTHON), + (RouteContext(Route.MESSAGES, target=Target.MESSAGES), Decision.RUST_REQUIRED), + (RouteContext(Route.MESSAGES, target=Target.CHAT_COMPLETIONS), Decision.PYTHON), + (RouteContext(Route.MESSAGES), Decision.PYTHON), + (RouteContext(Route.OCR, features=frozenset({Feature.SAFEGUARDS_CLASSIFIER})), Decision.PYTHON), + (RouteContext(Route.OCR), Decision.RUST_REQUIRED), ), ) def test_first_matching_rule_respects_every_constraint(context: RouteContext, expected: Decision) -> None: @@ -83,24 +60,14 @@ def test_first_matching_rule_respects_every_constraint(context: RouteContext, ex models=frozenset({"m"}), ), RouteRule(Route.RESPONSES, Rollout.PYTHON_ONLY), + RouteRule(Route.MESSAGES, Rollout.RUST_REQUIRED, targets=frozenset({Target.MESSAGES})), + RouteRule(Route.OCR, Rollout.PYTHON_ONLY, features=frozenset({Feature.SAFEGUARDS_CLASSIFIER})), + RouteRule(Route.OCR, Rollout.RUST_REQUIRED), ) assert catalog.decision(context, rules) is expected -@pytest.mark.parametrize("process", (None, False, True)) -@pytest.mark.parametrize("environment", (None, "0", "1")) -def test_ocr_has_no_python_path_to_opt_out_to( - monkeypatch: pytest.MonkeyPatch, process: bool | None, environment: str | None -) -> None: - configuration.rust(process) - if environment is not None: - monkeypatch.setenv("LITELLM_RUST", environment) - - assert catalog.decision(RouteContext(Route.OCR, model="m")) is Decision.RUST_REQUIRED - assert catalog.decision(RouteContext(Route.OCR, provider="aws_textract", model="m")) is Decision.RUST_REQUIRED - - @pytest.mark.parametrize( ("context", "expected"), ( @@ -154,6 +121,10 @@ def test_empty_constraints_match_nothing() -> None: rules: Final[Rules] = ( RouteRule(Route.OCR, Rollout.RUST_REQUIRED, providers=frozenset()), RouteRule(Route.OCR, Rollout.RUST_REQUIRED, models=frozenset()), + RouteRule(Route.OCR, Rollout.RUST_REQUIRED, features=frozenset()), ) assert catalog.decision(RouteContext(Route.OCR), rules) is Decision.PYTHON + assert catalog.decision( + RouteContext(Route.OCR, features=frozenset({Feature.SAFEGUARDS_CLASSIFIER})), rules + ) is Decision.PYTHON diff --git a/tests/unit/rust_bridge/test_detectors.py b/tests/unit/rust_bridge/test_detectors.py new file mode 100644 index 00000000000..726128386d5 --- /dev/null +++ b/tests/unit/rust_bridge/test_detectors.py @@ -0,0 +1,522 @@ +from collections.abc import Callable, Mapping +from copy import deepcopy +from datetime import datetime +from functools import reduce +from typing import Final + +import httpx +import pytest + +import litellm +from litellm.caching.caching import Cache +from litellm.integrations.custom_logger import CustomLogger +from litellm.litellm_core_utils.litellm_logging import Logging +from litellm.responses.utils import ResponsesAPIRequestUtils +from litellm.rust_bridge import detectors +from litellm.rust_bridge.chat_completions import detectors as chat_detectors +from litellm.rust_bridge.messages import detectors as messages_detectors +from litellm.rust_bridge.public_call import NativeCall +from litellm.rust_bridge.responses import detectors as responses_detectors +from litellm.types.llms.anthropic import ANTHROPIC_ADVISOR_TOOL_TYPE, ANTHROPIC_TOOL_SEARCH_TOOL_TYPES + +GATEWAY_TOOL: Final = {"type": "mcp", "server_label": "gateway", "server_url": "litellm_proxy"} +REMOTE_TOOL: Final = {"type": "mcp", "server_label": "docs", "server_url": "https://mcp.example.com/sse"} +ENCODED_ID: Final = ResponsesAPIRequestUtils._build_encrypted_item_id("deployment-1", "rs_1") # pyright: ignore[reportPrivateUsage] # the encoder litellm stamps on earlier turns +WRAPPED_CONTENT: Final = ResponsesAPIRequestUtils.wrap_encrypted_content_with_model_id("opaque", "deployment-1") + + +MAPPED_FILE: Final = { + "model_file_id_mapping": {"litellm-file": {"deployment-1": "file-abc"}}, + "model_info": {"id": "deployment-1"}, +} +MAPPED_FILE_INPUT: Final = [{"role": "user", "content": [{"type": "input_file", "file_id": "litellm-file"}]}] +CACHED_TEXT: Final = {"type": "input_text", "text": "hi", "cache_control": {"type": "ephemeral"}} +THINKING_TURN: Final = {"role": "assistant", "content": [{"type": "thinking", "thinking": "x", "signature": "s"}]} +REDACTED: Final = {"type": "redacted_thinking", "data": "x"} +TOOL_SEARCH_TYPE: Final = sorted(ANTHROPIC_TOOL_SEARCH_TOOL_TYPES)[0] + + +def function_tool(parameters: object) -> Mapping[str, object]: + return {"type": "function", "name": "f", "parameters": parameters} + + +def call(**kwargs: object) -> NativeCall: + return NativeCall(args=(), kwargs=kwargs, base={"model": "gpt-5"}) + + +@pytest.mark.parametrize( + ("model", "provider", "tools", "expected"), + ( + ("deepseek/test-model", None, [{"type": ANTHROPIC_ADVISOR_TOOL_TYPE}], True), + ("anthropic/test-model", None, [{"type": ANTHROPIC_ADVISOR_TOOL_TYPE}], False), + ("test-model", "anthropic", [{"type": ANTHROPIC_ADVISOR_TOOL_TYPE}], False), + ("unresolved-model", None, [{"type": ANTHROPIC_ADVISOR_TOOL_TYPE}], True), + ("deepseek/test-model", None, [{"type": "function", "name": "f"}], False), + ("deepseek/test-model", None, ["not-a-tool"], False), + ("deepseek/test-model", None, [], False), + ("deepseek/test-model", None, None, False), + ), +) +def test_messages_interception_matches_tools_and_resolved_provider( + model: str, provider: str | None, tools: object, expected: bool +) -> None: + assert messages_detectors.intercepted(call(model=model, custom_llm_provider=provider, tools=tools)) is expected + + +def _wrap_nested_level(value: object, depth: int) -> object: + return {"nested": value} if depth % 2 else [value] + + +@pytest.mark.parametrize( + ("detector", "kwargs", "expected"), + ( + (detectors.mock_response, {"mock_response": "hi"}, True), + (detectors.mock_response, {"mock_response": None}, False), + (detectors.mock_response, {"mock_tool_calls": [{"id": "call_1"}]}, False), + (chat_detectors.chat_mock_response, {"mock_response": "hi"}, True), + (chat_detectors.chat_mock_response, {"mock_tool_calls": [{"id": "call_1"}]}, True), + (chat_detectors.chat_mock_response, {"mock_timeout": True}, True), + (chat_detectors.chat_mock_response, {"mock_tool_calls": [], "mock_timeout": False}, False), + (responses_detectors.client_headers, {"headers": {"x-tenant": "a"}}, True), + (responses_detectors.client_headers, {"headers": {}}, False), + (responses_detectors.client_headers, {"headers": None}, False), + ( + chat_detectors.model_list, + {"model_list": [{"model_name": "gpt-5", "litellm_params": {"model": "gpt-5"}}]}, + True, + ), + (chat_detectors.model_list, {"model_list": None}, False), + (chat_detectors.chat_retries_fallbacks, {"context_window_fallback_dict": {"gpt-5": "gpt-5-mini"}}, True), + (chat_detectors.chat_retries_fallbacks, {"fallbacks": ["gpt-5-mini"]}, True), + (detectors.retries_fallbacks, {"context_window_fallback_dict": {"gpt-5": "gpt-5-mini"}}, False), + (detectors.prompt_management, {"model": "litellm_agent/gpt-5"}, True), + (detectors.prompt_management, {"model": "gpt-5"}, False), + (detectors.caller_client, {"client": object()}, True), + (detectors.caller_client, {"shared_session": object()}, True), + (detectors.caller_client, {"client": None, "shared_session": None}, False), + (detectors.caller_client, {}, False), + (detectors.extra_body, {"extra_body": {"stream": True}}, True), + (detectors.extra_body, {"extra_body": {"stream": False}}, True), + (detectors.extra_body, {"extra_body": {}}, False), + (detectors.extra_body, {"extra_body": None}, False), + (detectors.extra_body, {}, False), + ( + responses_detectors.provider_affinity, + {"provider_affinity_header": "X-Session-ID", "session_id": "session-1"}, + True, + ), + (responses_detectors.provider_affinity, {"provider_affinity_header": "X-Session-ID"}, True), + ( + responses_detectors.provider_affinity, + {"provider_affinity_header": "X-Session-ID", "extra_headers": {"x-session-id": "session-1"}}, + True, + ), + (responses_detectors.provider_affinity, {"provider_affinity_header": "Authorization"}, True), + (responses_detectors.provider_affinity, {"provider_affinity_header": "invalid header"}, True), + (responses_detectors.provider_affinity, {"provider_affinity_header": ""}, True), + (responses_detectors.provider_affinity, {"provider_affinity_header": None, "session_id": "session-1"}, False), + (responses_detectors.provider_affinity, {}, False), + (detectors.streaming, {"stream": True}, True), + (detectors.streaming, {"stream": False}, False), + (detectors.timeout_variants, {"request_timeout": 5}, True), + (detectors.timeout_variants, {"stream": True, "stream_timeout": 5}, True), + (detectors.timeout_variants, {"stream_timeout": 5}, False), + (detectors.timeout_variants, {"timeout": httpx.Timeout(60, connect=2)}, True), + (detectors.timeout_variants, {"timeout": 60}, False), + (detectors.proxy_mcp_tools, {"tools": [GATEWAY_TOOL]}, True), + (detectors.proxy_mcp_tools, {"tools": [REMOTE_TOOL]}, False), + (detectors.proxy_mcp_tools, {"tools": None}, False), + (detectors.prompt_management, {"prompt_id": "welcome"}, True), + (detectors.prompt_management, {"prompt_variables": {"name": "x"}}, False), + (responses_detectors.text_format, {"text_format": dict}, True), + (responses_detectors.text_format, {}, False), + (responses_detectors.chat_completions_bridge, {"use_chat_completions_api": True}, True), + (responses_detectors.chat_completions_bridge, {"use_chat_completions_api": False}, False), + (responses_detectors.chat_completions_bridge, {"model": "openai/chat_completions/gpt-5"}, True), + (responses_detectors.chat_completions_bridge, {"model": "openai/gpt-5"}, False), + (detectors.retries_fallbacks, {"num_retries": 0}, True), + (detectors.retries_fallbacks, {"max_retries": 2}, True), + (detectors.retries_fallbacks, {"fallbacks": ["gpt-5-mini"]}, True), + (detectors.retries_fallbacks, {"retry_policy": {"TimeoutErrorRetries": 2}}, True), + (detectors.retries_fallbacks, {}, False), + (detectors.prompt_management, {"knowledge_bases": ["kb-1"]}, True), + (detectors.prompt_management, {"vector_store_ids": []}, False), + (responses_detectors.managed_resource_ids, {"input": MAPPED_FILE_INPUT, **MAPPED_FILE}, True), + (responses_detectors.managed_resource_ids, {"input": MAPPED_FILE_INPUT}, False), + (responses_detectors.managed_resource_ids, {"input": "hi"}, False), + (responses_detectors.cache_control_marks, {"input": [{"role": "user", "content": [CACHED_TEXT]}]}, True), + ( + responses_detectors.cache_control_marks, + {"tools": [{"type": "function", "name": "f", "cache_control": {}}]}, + True, + ), + ( + responses_detectors.cache_control_marks, + {"input": [{"role": "user", "content": [{"type": "input_text"}]}]}, + False, + ), + ( + responses_detectors.anthropic_tool_search, + {"tools": [{"type": TOOL_SEARCH_TYPE, "name": "tool_search"}]}, + True, + ), + (responses_detectors.anthropic_tool_search, {"tools": [{"type": "function", "name": "f"}]}, False), + (responses_detectors.tool_schema_repair, {"tools": [function_tool('{"type": "object"}')]}, True), + ( + responses_detectors.tool_schema_repair, + {"tools": [function_tool({"type": "string", "pattern": r"\p{L}"})]}, + True, + ), + (responses_detectors.tool_schema_repair, {"tools": [function_tool({"type": "object"})]}, False), + (responses_detectors.tool_schema_repair, {}, False), + (responses_detectors.model_param_gating, {"max_output_tokens": 1}, True), + (responses_detectors.model_param_gating, {"max_output_tokens": 1024}, False), + (detectors.cache_control_injection, {"enable_prompt_caching": True}, True), + (detectors.cache_control_injection, {"cache_control_injection_points": [{"location": "message"}]}, True), + (detectors.cache_control_injection, {"cache_control_injection_points": []}, False), + (messages_detectors.thinking_signature_retry, {"messages": [THINKING_TURN]}, True), + ( + messages_detectors.thinking_signature_retry, + {"messages": [{"role": "assistant", "content": [REDACTED]}]}, + True, + ), + (messages_detectors.thinking_signature_retry, {"messages": [{"role": "assistant", "content": "done"}]}, False), + ( + messages_detectors.thinking_signature_retry, + {"messages": [{"role": "user", "content": [{"type": "text"}]}]}, + False, + ), + (detectors.drop_params, {"drop_params": True}, True), + (detectors.drop_params, {"drop_params": False}, False), + (detectors.drop_params, {"drop_params": " True "}, True), + (detectors.drop_params, {"drop_params": "false"}, False), + (detectors.drop_params, {"drop_params": "maybe"}, False), + (detectors.drop_params, {"additional_drop_params": ["metadata.user_id"]}, True), + (detectors.drop_params, {"additional_drop_params": []}, False), + ( + responses_detectors.deployment_response_id, + {"litellm_metadata": {"model_info": {"id": "deployment-1"}}}, + True, + ), + (responses_detectors.deployment_response_id, {"litellm_metadata": {"model_info": {}}}, False), + (responses_detectors.deployment_response_id, {"litellm_metadata": None}, False), + (responses_detectors.encoded_item_ids, {"input": [{"type": "reasoning", "id": ENCODED_ID}]}, True), + ( + responses_detectors.encoded_item_ids, + {"input": [{"type": "reasoning", "encrypted_content": WRAPPED_CONTENT}]}, + True, + ), + ( + responses_detectors.encoded_item_ids, + {"input": [{"type": "reasoning", "id": "rs_1", "encrypted_content": "x"}]}, + False, + ), + (responses_detectors.encoded_item_ids, {"input": "hi"}, False), + ), +) +def test_request_detectors( + detector: Callable[[NativeCall], bool], kwargs: Mapping[str, object], expected: bool +) -> None: + assert detector(call(**kwargs)) is expected + + +def test_cache_control_marks_handles_deeply_nested_input() -> None: + nested_input: Final = reduce(_wrap_nested_level, range(5_000), {"cache_control": {}}) + assert responses_detectors.cache_control_marks(call(input=nested_input)) + + +@pytest.mark.parametrize( + ("input_value", "expected"), + ( + pytest.param( + [{"type": "reasoning", "id": "rs_00000000-0000-4000-8000-000000000000", "summary": list[object]()}], + True, + id="bridge-minted-reasoning", + ), + pytest.param( + [{"type": "reasoning", "encrypted_content": '[{"type":"thinking","thinking":"x","signature":"s"}]'}], + True, + id="bridge-thinking-blocks", + ), + pytest.param( + [{"type": "function_call", "id": "foreign-id", "call_id": "call_1", "name": "f", "arguments": "{}"}], + True, + id="foreign-tool-call-id", + ), + pytest.param( + [{"type": "reasoning", "id": "rs_1", "summary": list[object](), "status": None}], + True, + id="null-reasoning-status", + ), + pytest.param( + [{"type": "function_call", "id": "fc_1", "call_id": "call_1", "name": "f", "arguments": "{}"}], + False, + id="native-tool-call-id", + ), + pytest.param( + [{"type": "custom_tool_call", "call_id": "call_1", "name": "f", "input": "x", "namespace": "ns"}], + True, + id="custom-tool-call-namespace", + ), + pytest.param( + [{"type": "custom_tool_call", "call_id": "call_1", "name": "f", "input": "x"}], + False, + id="custom-tool-call", + ), + pytest.param([{"type": "reasoning", "id": "rs_1", "summary": list[object]()}], False, id="native-reasoning"), + pytest.param([{"role": "user", "content": "hi"}], False, id="message"), + pytest.param("hi", False, id="string"), + pytest.param([], False, id="empty"), + pytest.param(None, False, id="absent"), + ), +) +def test_input_rewrite_preserves_caller_input(input_value: object, expected: bool) -> None: + original: Final = deepcopy(input_value) + assert responses_detectors.input_rewrite(call(input=input_value)) is expected + assert input_value == original + + +@pytest.mark.parametrize( + ("detector", "setting", "value", "kwargs"), + ( + (detectors.drop_params, "drop_params", True, {}), + (detectors.modify_params, "modify_params", True, {}), + (detectors.retries_fallbacks, "num_retries", 3, {}), + (detectors.cache_control_injection, "enable_anthropic_prompt_caching", True, {}), + (messages_detectors.stream_cost_injection, "include_cost_in_streaming_usage", True, {"stream": True}), + (messages_detectors.stream_cost_injection, "include_cost_in_streaming_usage", "true", {"stream": True}), + (chat_detectors.chat_retries_fallbacks, "model_fallbacks", [{"gpt-5": ["gpt-5-mini"]}], {}), + (chat_detectors.chat_retries_fallbacks, "num_retries", 3, {}), + (chat_detectors.model_alias_map, "model_alias_map", {"gpt-5": "openai/gpt-5"}, {}), + ), +) +def test_global_settings_are_detected( + monkeypatch: pytest.MonkeyPatch, + detector: Callable[[NativeCall], bool], + setting: str, + value: object, + kwargs: Mapping[str, object], +) -> None: + for name in ("drop_params", "modify_params", "enable_anthropic_prompt_caching", "include_cost_in_streaming_usage"): + monkeypatch.setattr(litellm, name, False) + for name in ("num_retries", "model_fallbacks"): + monkeypatch.setattr(litellm, name, None) + monkeypatch.setattr(litellm, "model_alias_map", {}) + assert not detector(call(**kwargs)) + monkeypatch.setattr(litellm, setting, value) + assert detector(call(**kwargs)) + + +def test_stream_cost_injection_needs_a_stream(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr(litellm, "include_cost_in_streaming_usage", True) + assert not messages_detectors.stream_cost_injection(call()) + + +def test_model_alias_map_applies_only_to_the_requested_model(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr(litellm, "model_alias_map", {"fast": "openai/gpt-5-mini"}) + assert chat_detectors.model_alias_map(call(model="fast")) + assert not chat_detectors.model_alias_map(call()) + + +@pytest.mark.parametrize( + ("kwargs", "expected"), + ( + pytest.param({"temperature": 0.2}, True, id="gpt-5-temperature"), + pytest.param({"max_tokens": 16}, False, id="gpt-5-max-tokens"), + pytest.param({"model": "gpt-4o", "temperature": 0.2}, False, id="gpt-4o-temperature"), + pytest.param({"model": "anthropic/claude-sonnet-4-5", "logit_bias": {"1": 1}}, True, id="unsupported-param"), + pytest.param({"model": "anthropic/claude-sonnet-4-5", "n": 1}, False, id="langchain-default-n"), + pytest.param({"model": "anthropic/claude-sonnet-4-5", "n": 2}, True, id="unsupported-n"), + pytest.param({"model": "anthropic/claude-sonnet-4-5", "max_tokens": 16, "stream": True}, False, id="supported"), + pytest.param({"model": "unknown-model", "temperature": 0.2}, False, id="unresolved-provider"), + pytest.param({}, False, id="no-params"), + ), +) +def test_chat_model_param_gating_follows_the_provider_param_rules( + monkeypatch: pytest.MonkeyPatch, kwargs: Mapping[str, object], expected: bool +) -> None: + monkeypatch.setattr(litellm, "drop_params", False) + assert chat_detectors.chat_model_param_gating(call(**kwargs)) is expected + + +def test_openai_workload_identity_applies_only_without_a_static_key(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.delenv("OPENAI_API_KEY", raising=False) + monkeypatch.setattr(litellm, "api_key", None) + monkeypatch.setattr(litellm, "openai_key", None) + monkeypatch.setattr(litellm, "api_base", None) + identity: Final = { + "openai_identity_provider_id": "idp-1", + "openai_service_account_id": "sa-1", + "openai_identity_token_file": "/var/run/token", + } + assert responses_detectors.openai_workload_identity(call(**identity)) + assert not responses_detectors.openai_workload_identity(call(**identity, api_key="sk-static")) + assert not responses_detectors.openai_workload_identity(call()) + + +def test_anthropic_workload_identity_applies_only_without_a_static_key(monkeypatch: pytest.MonkeyPatch) -> None: + for name in ( + "ANTHROPIC_API_KEY", + "ANTHROPIC_AUTH_TOKEN", + "ANTHROPIC_FEDERATION_RULE_ID", + "ANTHROPIC_ORGANIZATION_ID", + ): + monkeypatch.delenv(name, raising=False) + federation: Final = {"anthropic_federation_rule_id": "rule-1", "anthropic_organization_id": "org-1"} + assert messages_detectors.anthropic_workload_identity(call(**federation)) + assert not messages_detectors.anthropic_workload_identity(call(**federation, api_key="sk-ant-static")) + assert not messages_detectors.anthropic_workload_identity(call(anthropic_federation_rule_id="rule-1")) + + +class _Logger(CustomLogger): + pass + + +class _Rewrite(CustomLogger): + async def async_pre_request_hook(self, model: str, messages: list, kwargs: dict) -> dict | None: # pyright: ignore[reportMissingTypeArgument] # mirrors the CustomLogger signature + return kwargs + + +class _InheritedRewrite(_Rewrite): + pass + + +class _Agentic(CustomLogger): + async def async_should_run_agentic_loop(self, *args: object, **kwargs: object) -> tuple[bool, dict]: # pyright: ignore[reportIncompatibleMethodOverride, reportMissingTypeArgument] # test double only needs the override + return False, {} + + +class _ChatAgentic(CustomLogger): + async def async_should_run_chat_completion_agentic_loop( + self, *args: object, **kwargs: object + ) -> tuple[bool, dict[str, object]]: # pyright: ignore[reportIncompatibleMethodOverride] # test double only needs the override + return False, {} + + +class _Deployment(CustomLogger): + async def async_pre_call_deployment_hook(self, *args: object, **kwargs: object) -> dict[str, object] | None: # pyright: ignore[reportIncompatibleMethodOverride] # test double only needs the override + return None + + +@pytest.mark.parametrize( + ("detector", "callbacks", "expected"), + ( + (messages_detectors.pre_request_hook, [_Rewrite()], True), + (messages_detectors.pre_request_hook, [_InheritedRewrite()], True), + (messages_detectors.pre_request_hook, [_Logger(), _Agentic()], False), + (messages_detectors.pre_request_hook, ["not-a-logger"], False), + (detectors.agentic_loop_hook, [_Agentic()], True), + (detectors.agentic_loop_hook, [_Logger(), _Rewrite()], False), + (detectors.agentic_loop_hook, [_ChatAgentic()], False), + (chat_detectors.chat_agentic_loop_hook, [_ChatAgentic()], True), + (chat_detectors.chat_agentic_loop_hook, [_Agentic()], True), + (chat_detectors.chat_agentic_loop_hook, [_Logger(), _Deployment()], False), + (responses_detectors.deployment_hook, [_Deployment()], True), + (responses_detectors.deployment_hook, [_Logger(), _Agentic(), _Rewrite()], False), + ), +) +def test_callback_detectors_need_an_override( + monkeypatch: pytest.MonkeyPatch, detector: Callable[[NativeCall], bool], callbacks: list[object], expected: bool +) -> None: + monkeypatch.setattr(litellm, "callbacks", callbacks) + assert detector(call()) is expected + + +def _logging_with(callback: CustomLogger) -> Logging: + logging_obj: Final = Logging( + model="claude-sonnet-4-5", + messages=[], + stream=False, + call_type="anthropic_messages", + start_time=datetime.now(), + litellm_call_id="call-1", + function_id="function-1", + ) + logging_obj.add_dynamic_callback(callback) + return logging_obj + + +@pytest.mark.parametrize( + ("detector", "kwargs", "expected"), + ( + (detectors.agentic_loop_hook, {"success_callback": [_Agentic()]}, True), + (detectors.agentic_loop_hook, {"litellm_logging_obj": _logging_with(_Agentic())}, True), + (detectors.agentic_loop_hook, {"success_callback": [_Logger()]}, False), + (messages_detectors.pre_request_hook, {"success_callback": [_Rewrite()]}, False), + (chat_detectors.chat_agentic_loop_hook, {"litellm_logging_obj": _logging_with(_ChatAgentic())}, True), + (responses_detectors.deployment_hook, {"success_callback": [_Deployment()]}, True), + ), + ids=( + "success-callback", + "logging-object", + "plain-logger", + "pre-request-reads-globals-only", + "chat-agentic-logging-object", + "deployment-success-callback", + ), +) +def test_callback_detectors_read_the_request_callbacks_the_handler_reads( + monkeypatch: pytest.MonkeyPatch, + detector: Callable[[NativeCall], bool], + kwargs: Mapping[str, object], + expected: bool, +) -> None: + monkeypatch.setattr(litellm, "callbacks", []) + assert detector(call(**kwargs)) is expected + + +def test_websearch_interception_needs_the_interception_logger(monkeypatch: pytest.MonkeyPatch) -> None: + from litellm.integrations.websearch_interception.handler import WebSearchInterceptionLogger + + monkeypatch.setattr(litellm, "callbacks", [_Rewrite()]) + assert not messages_detectors.websearch_interception(call()) + monkeypatch.setattr(litellm, "callbacks", [WebSearchInterceptionLogger()]) + assert messages_detectors.websearch_interception(call()) + + +@pytest.mark.parametrize( + ("cache", "kwargs", "expected"), + ( + (None, {}, False), + (Cache(), {}, True), + (Cache(), {"cache": {"ttl": 60}}, True), + (Cache(), {"cache": {"no-cache": True}}, False), + ), +) +def test_response_cache_is_skipped_only_by_no_cache( + monkeypatch: pytest.MonkeyPatch, cache: Cache | None, kwargs: Mapping[str, object], expected: bool +) -> None: + monkeypatch.setattr(litellm, "cache", cache) + assert detectors.response_cache(call(**kwargs)) is expected + + +@pytest.mark.parametrize( + ("environment", "setting", "expected"), + ((None, None, False), ("DEFAULT@SECLEVEL=1", None, True), (None, "DEFAULT@SECLEVEL=1", True)), +) +def test_tls_policy_reads_the_security_level_environment_then_the_setting( + monkeypatch: pytest.MonkeyPatch, environment: str | None, setting: str | None, expected: bool +) -> None: + monkeypatch.delenv("SSL_SECURITY_LEVEL", raising=False) + monkeypatch.delenv("SSL_ECDH_CURVE", raising=False) + monkeypatch.setattr(litellm, "ssl_ecdh_curve", None) + if environment is not None: + monkeypatch.setenv("SSL_SECURITY_LEVEL", environment) + monkeypatch.setattr(litellm, "ssl_security_level", setting) + assert detectors.tls_policy(call()) is expected + + +@pytest.mark.parametrize( + ("environment", "setting", "expected"), + ((None, "X25519", False), (None, " P-256 ", False), ("secp521r1", None, True), (None, "secp521r1", True)), +) +def test_tls_policy_flags_only_curves_native_tls_lacks( + monkeypatch: pytest.MonkeyPatch, environment: str | None, setting: str | None, expected: bool +) -> None: + monkeypatch.delenv("SSL_SECURITY_LEVEL", raising=False) + monkeypatch.delenv("SSL_ECDH_CURVE", raising=False) + monkeypatch.setattr(litellm, "ssl_security_level", None) + if environment is not None: + monkeypatch.setenv("SSL_ECDH_CURVE", environment) + monkeypatch.setattr(litellm, "ssl_ecdh_curve", setting) + assert detectors.tls_policy(call()) is expected diff --git a/tests/unit/rust_bridge/test_public_call.py b/tests/unit/rust_bridge/test_public_call.py index 63029e288e2..5f50db6ea5a 100644 --- a/tests/unit/rust_bridge/test_public_call.py +++ b/tests/unit/rust_bridge/test_public_call.py @@ -3,7 +3,7 @@ from typing import Final import pytest -from litellm.rust_bridge.public_call import native_call, signature +from litellm.rust_bridge.public_call import AsyncFlag, native_call, signature def _messages( @@ -18,6 +18,7 @@ def _messages( _SIGNATURE: Final = signature(_messages) +_FLAG: Final = AsyncFlag("aflag", sync=_SIGNATURE) @pytest.mark.parametrize("supplied", ({}, {"api_key": None}, {"api_key": "explicit"})) @@ -62,3 +63,16 @@ def test_resolved_lays_the_keywords_over_the_base_and_equals_the_full_binding() } assert call.resolved["metadata"] is metadata assert supplied == {"model": "keyword-model", "metadata": metadata} + + +def test_flag_keywords_name_positionals_and_drop_only_the_flag() -> None: + messages: Final[Sequence[object]] = [{"role": "user", "content": "hello"}] + + keywords: Final = _FLAG.keywords((128, messages), {"model": "m", "stream": True, "aflag": True}) + + assert keywords == {"max_tokens": 128, "messages": messages, "model": "m", "stream": True} + + +def test_flag_keywords_reject_a_parameter_given_twice() -> None: + with pytest.raises(TypeError): + _FLAG.keywords((128,), {"max_tokens": 64}) diff --git a/tests/unit/test_conftest_isolation.py b/tests/unit/test_conftest_isolation.py index 63db0eb5bba..92457119a82 100644 --- a/tests/unit/test_conftest_isolation.py +++ b/tests/unit/test_conftest_isolation.py @@ -88,6 +88,26 @@ def test_register_model_ledger_entry_was_rolled_back(): assert CANARY_MODEL not in litellm_utils_module._runtime_registered_model_cost +def test_register_model_catalog_writes_are_scoped_to_this_test(): + litellm.register_model( + { + CANARY_MODEL: {"litellm_provider": "openai", "mode": "chat", "input_cost_per_token": 0.001}, + "collection-isolation-ledger": {"input_cost_per_token": 0.5}, + } + ) + assert CANARY_MODEL in litellm.model_cost + assert CANARY_MODEL in litellm.open_ai_chat_completion_models + assert CANARY_MODEL in litellm.models_by_provider["openai"] + assert litellm.model_cost["collection-isolation-ledger"]["input_cost_per_token"] == 0.5 + + +def test_register_model_catalog_writes_were_rolled_back(): + assert CANARY_MODEL not in litellm.model_cost + assert CANARY_MODEL not in litellm.open_ai_chat_completion_models + assert CANARY_MODEL not in litellm.models_by_provider["openai"] + assert litellm.model_cost["collection-isolation-ledger"]["input_cost_per_token"] == 0.001 + + def test_live_router_membership_is_scoped_to_this_test(): _CanaryRouterHolder.router = Router( model_list=[ diff --git a/tests/unit/test_constants.py b/tests/unit/test_constants.py index 0d0e77765b7..99b049f1803 100644 --- a/tests/unit/test_constants.py +++ b/tests/unit/test_constants.py @@ -1,6 +1,7 @@ import ast, asyncio, os import inspect import json +import sys from unittest import mock import httpx @@ -117,6 +118,33 @@ def test_cli_jwt_expiration_hours_from_environment( importlib.reload(litellm.constants) +@pytest.mark.parametrize( + ("raw", "expected"), + ( + (None, 64 * 1024 * 1024), + ("", 64 * 1024 * 1024), + ("invalid", 64 * 1024 * 1024), + ("0", 64 * 1024 * 1024), + ("-1", 64 * 1024 * 1024), + ("1", 1), + ("200000", 200000), + (str(sys.maxsize), sys.maxsize), + (str(sys.maxsize + 1), 64 * 1024 * 1024), + ), +) +def test_mcp_sse_event_limit_uses_positive_override_or_default(raw: str | None, expected: int) -> None: + try: + with pytest.MonkeyPatch.context() as environment: + if raw is None: + environment.delenv("LITELLM_MCP_MAX_SSE_EVENT_SIZE_BYTES", raising=False) + else: + environment.setenv("LITELLM_MCP_MAX_SSE_EVENT_SIZE_BYTES", raw) + importlib.reload(constants) + assert constants.MCP_MAX_SSE_EVENT_SIZE_BYTES == expected + finally: + importlib.reload(constants) + + def _is_blank(value: object) -> bool: return isinstance(value, str) and not value.strip() diff --git a/tests/unit/test_cost_calculator.py b/tests/unit/test_cost_calculator.py index 99119799ac0..2854f9010b2 100644 --- a/tests/unit/test_cost_calculator.py +++ b/tests/unit/test_cost_calculator.py @@ -357,6 +357,72 @@ def test_completion_cost_prices_rule_only_response_model_at_the_azure_deployment assert cost == pytest.approx(usage.prompt_tokens * 0.0000111 + usage.completion_tokens * 0.0000222) +@pytest.mark.parametrize("region", ["eu", "us"]) +@pytest.mark.parametrize( + ("alias", "dated"), + [ + ("o1", "o1-2024-12-17"), + ("o3", "o3-2025-04-16"), + ("o3-mini", "o3-mini-2025-01-31"), + ("o4-mini", "o4-mini-2025-04-16"), + ("gpt-4o", "gpt-4o-2024-11-20"), + ("gpt-4o-mini", "gpt-4o-mini-2024-07-18"), + ], +) +def test_completion_cost_bills_undated_azure_data_zone_base_model_at_its_dated_rate( + _local_model_cost_map: None, region: str, alias: str, dated: str +) -> None: + """LIT-9812: a deployment with base_model azure/eu/o3 (undated, like the global azure/o3) must bill the EU + Data Zone rate of its latest dated row, not $0 and not the global rate""" + dated_info: Final = litellm.model_cost[f"azure/{region}/{dated}"] + usage: Final = Usage(prompt_tokens=17, completion_tokens=9, total_tokens=26) + response: Final = ModelResponse(model=dated, choices=[], usage=usage) + + cost: Final = completion_cost( + completion_response=response, + model="azure/my-data-zone-deployment", + custom_llm_provider="azure", + base_model=f"azure/{region}/{alias}", + ) + + assert cost == pytest.approx( + usage.prompt_tokens * dated_info["input_cost_per_token"] + + usage.completion_tokens * dated_info["output_cost_per_token"] + ) + + +def test_completion_cost_prices_rule_only_base_model_from_the_response_model( + _local_model_cost_map: None, + _price_free_gpt_family_generalization: None, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """LIT-9812: a deployment whose base_model is an undated name only a capability rule matches must not + stop the ladder at $0 when the response names a priced model""" + monkeypatch.setattr( + litellm, + "model_cost", + { + "azure/gpt-9.9-2026-01-01": { + "litellm_provider": "azure", + "mode": "chat", + "input_cost_per_token": 0.0000111, + "output_cost_per_token": 0.0000222, + } + }, + ) + usage: Final = Usage(prompt_tokens=17, completion_tokens=9, total_tokens=26) + response: Final = ModelResponse(model="gpt-9.9-2026-01-01", choices=[], usage=usage) + + cost: Final = completion_cost( + completion_response=response, + model="azure/my-eu-deployment", + custom_llm_provider="azure", + base_model="azure/eu/gpt-9.9", + ) + + assert cost == pytest.approx(usage.prompt_tokens * 0.0000111 + usage.completion_tokens * 0.0000222) + + def test_completion_cost_orders_candidates_without_extra_huggingface_config_requests( _local_model_cost_map: None, ) -> None: diff --git a/tests/unit/test_count_tokens_public_api.py b/tests/unit/test_count_tokens_public_api.py index e33bc1e5907..4eb8bea3427 100644 --- a/tests/unit/test_count_tokens_public_api.py +++ b/tests/unit/test_count_tokens_public_api.py @@ -3,9 +3,13 @@ Tests for litellm.acount_tokens() public API. """ import asyncio +import json import os from unittest.mock import AsyncMock, patch +import httpx +import pytest +import respx import litellm from litellm.types.utils import TokenCountResponse @@ -157,3 +161,45 @@ def test_acount_tokens_no_api_key_falls_back(monkeypatch): assert result.tokenizer_type == "local_tokenizer" + + +@pytest.fixture +def httpx_transport_clients(monkeypatch): + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + for name in ("ANTHROPIC_API_BASE", "ANTHROPIC_BASE_URL"): + monkeypatch.delenv(name, raising=False) + litellm.in_memory_llm_clients_cache.flush_cache() + yield + litellm.in_memory_llm_clients_cache.flush_cache() + + +def test_acount_tokens_sends_chat_tool_use_to_anthropic_in_the_shape_claude_inference_sends(httpx_transport_clients): + schema = {"type": "object", "properties": {"city": {"type": "string"}}} + with respx.mock(assert_all_called=True) as router: + route = router.post("https://api.anthropic.com/v1/messages/count_tokens").mock( + return_value=httpx.Response(200, json={"input_tokens": 52}) + ) + result = asyncio.run( + litellm.acount_tokens( + model="anthropic/claude-opus-5-5", + messages=[ + {"role": "user", "content": "Weather in SF?"}, + { + "role": "assistant", + "content": None, + "tool_calls": [ + {"id": "call_1", "type": "function", "function": {"name": "get_weather", "arguments": "{}"}} + ], + }, + {"role": "tool", "tool_call_id": "call_1", "content": "sunny"}, + ], + tools=[{"type": "function", "function": {"name": "get_weather", "parameters": schema}}], + api_key="sk-ant-test-key", + ) + ) + + assert (result.error, result.total_tokens) == (False, 52) + sent = json.loads(route.calls.last.request.content) + assert sent["tools"] == [{"name": "get_weather", "input_schema": schema, "type": "custom"}] + assert [message["role"] for message in sent["messages"]] == ["user", "assistant", "user"] + assert sent["messages"][2]["content"] == [{"type": "tool_result", "tool_use_id": "call_1", "content": "sunny"}] diff --git a/tests/unit/test_internal_context.py b/tests/unit/test_internal_context.py index 8d3e341096c..60a75c688c4 100644 --- a/tests/unit/test_internal_context.py +++ b/tests/unit/test_internal_context.py @@ -87,10 +87,10 @@ _IN_MEMORY_ONLY_CALLERS: Final = frozenset( ) _CACHE_CALL: Final = re.compile( - r"\.(?:async_)?(?:get_cache|set_cache|batch_get_cache|batch_get_cache_shared|increment_cache|increment" + r"\.(?:async_)?(?:get_cache|set_cache|batch_get_cache|batch_get_cache_shared|increment_cache|increment_if_present|increment" r"|set_cache_pipeline|set_cache_pipeline_with_ttls|set_cache_sadd|delete_cache|batch_set_cache|increment_pipeline" r"|rpush|lpop|scan_iter|get_ttl|mget)\(" - r"|\b(?:reserve_redis_batch_reads|declare_batch_get|_prepare_batch_get)\(" + r"|\b(?:reserve_redis_batch_reads|_prepare_batch_get)\(" r"|\bbatch\.(?:set|delete|script|increment)\(" ) _DECLARES_TARGET: Final = re.compile(r"\b(?:with_service_target|service_target|response_cache_phase)\(") diff --git a/tests/unit/test_main.py b/tests/unit/test_main.py index 3e5cfeb455e..f5d13aecb6f 100644 --- a/tests/unit/test_main.py +++ b/tests/unit/test_main.py @@ -23,6 +23,7 @@ import respx from openai import APITimeoutError, AsyncOpenAI from openai._legacy_response import LegacyAPIResponse from openai.types.chat.chat_completion import ChatCompletion +from pydantic import TypeAdapter import litellm from litellm import ( @@ -3937,6 +3938,100 @@ async def test_acompletion_forwards_store_and_prompt_cache_key_to_openai(): assert request_body["prompt_cache_key"] == "test-cache-key" +_TOOL: Final[Mapping[str, object]] = {"type": "function", "function": {"name": "f", "parameters": {"type": "object", "properties": {}}}} + +# Client settings ride in OPENAI_CHAT_COMPLETION_PARAMS but configure the HTTP client, never the body. +_OPENAI_CLIENT_SETTINGS: Final = frozenset( + { + "api_base", + "api_key", + "api_version", + "base_url", + "default_headers", + "deployment_id", + "extra_headers", + "max_retries", + "organization", + "request_timeout", + "timeout", + } +) + +# Accepted by completion() for other providers, never sent to OpenAI's /chat/completions body. +_NOT_OPENAI_BODY_PARAMS: Final = frozenset({"include_server_side_tool_invocations", "thinking"}) + +# param -> (model that accepts it, the call kwargs that carry it) +_OPENAI_BODY_PARAM_CASES: Final[Mapping[str, tuple[str, Mapping[str, object]]]] = { + "audio": ("openai/gpt-4o", {"audio": {"voice": "alloy", "format": "wav"}}), + "frequency_penalty": ("openai/gpt-4o", {"frequency_penalty": 0.5}), + "function_call": ("openai/gpt-4o", {"function_call": "auto"}), + "functions": ("openai/gpt-4o", {"functions": [_TOOL["function"]]}), + "logit_bias": ("openai/gpt-4o", {"logit_bias": {"1": 1}}), + "logprobs": ("openai/gpt-4o", {"logprobs": True}), + "max_completion_tokens": ("openai/gpt-4o", {"max_completion_tokens": 7}), + "max_tokens": ("openai/gpt-4o", {"max_tokens": 7}), + "modalities": ("openai/gpt-4o", {"modalities": ["text"]}), + "n": ("openai/gpt-4o", {"n": 2}), + "parallel_tool_calls": ("openai/gpt-4o", {"tools": [_TOOL], "parallel_tool_calls": False}), + "prediction": ("openai/gpt-4o", {"prediction": {"type": "content", "content": "x"}}), + "presence_penalty": ("openai/gpt-4o", {"presence_penalty": 0.5}), + "prompt_cache_key": ("openai/gpt-4o", {"prompt_cache_key": "k"}), + "prompt_cache_retention": ("openai/gpt-5.5", {"prompt_cache_retention": "24h"}), + "reasoning_effort": ("openai/gpt-5.5", {"reasoning_effort": "low"}), + "response_format": ("openai/gpt-4o", {"response_format": {"type": "json_object"}}), + "safety_identifier": ("openai/gpt-4o", {"safety_identifier": "s"}), + "seed": ("openai/gpt-4o", {"seed": 3}), + "service_tier": ("openai/gpt-4o", {"service_tier": "priority"}), + "stop": ("openai/gpt-4o", {"stop": ["x"]}), + "store": ("openai/gpt-4o", {"store": False}), + "stream": ("openai/gpt-4o", {"stream": True}), + "stream_options": ("openai/gpt-4o", {"stream": True, "stream_options": {"include_usage": True}}), + "temperature": ("openai/gpt-4o", {"temperature": 0.5}), + "tool_choice": ("openai/gpt-4o", {"tools": [_TOOL], "tool_choice": "auto"}), + "tools": ("openai/gpt-4o", {"tools": [_TOOL]}), + "top_logprobs": ("openai/gpt-4o", {"logprobs": True, "top_logprobs": 2}), + "top_p": ("openai/gpt-4o", {"top_p": 0.5}), + "user": ("openai/gpt-4o", {"user": "u1"}), + "verbosity": ("openai/gpt-5.5", {"verbosity": "low"}), + "web_search_options": ("openai/gpt-4o", {"web_search_options": {"search_context_size": "low"}}), +} + + +def test_every_openai_body_param_has_a_forwarding_case(): + body_params: Final = frozenset(litellm.OPENAI_CHAT_COMPLETION_PARAMS) - _OPENAI_CLIENT_SETTINGS - _NOT_OPENAI_BODY_PARAMS + assert frozenset(_OPENAI_BODY_PARAM_CASES) == body_params, ( + "a param added to OPENAI_CHAT_COMPLETION_PARAMS needs a case in _OPENAI_BODY_PARAM_CASES proving " + "completion() sends it to OpenAI; prompt_cache_retention (LIT-9758) and store/prompt_cache_key " + "(#33184) were listed as supported but silently dropped" + ) + + +_REQUEST_BODY: Final = TypeAdapter(dict[str, object]) + + +@pytest.mark.parametrize("param", sorted(_OPENAI_BODY_PARAM_CASES)) +def test_completion_sends_openai_body_param_to_openai( + param: str, respx_mock: respx.MockRouter, openai_api_response: Mapping[str, object] +): + api_base: Final = "http://localhost:12346/v1" + route: Final = respx_mock.post(f"{api_base}/chat/completions").mock( + return_value=httpx.Response(status_code=200, json=openai_api_response) + ) + model, call_kwargs = _OPENAI_BODY_PARAM_CASES[param] + + litellm.completion( + model=model, + messages=[{"role": "user", "content": "hi"}], + api_base=api_base, + api_key="fake_openai_api_key", + **call_kwargs, + ) + + assert route.call_count == 1 + sent: Final = _REQUEST_BODY.validate_json(route.calls.last.request.content) + assert sent.get(param) == call_kwargs[param], f"{param} did not reach the OpenAI request body: {sent}" + + def test_completion_omits_store_and_prompt_cache_key_when_not_passed(): """ When store and prompt_cache_key are not passed, they must not appear in the diff --git a/tests/unit/test_model_prices_and_context_window.py b/tests/unit/test_model_prices_and_context_window.py index 395fe8c9750..701b79d0ba9 100644 --- a/tests/unit/test_model_prices_and_context_window.py +++ b/tests/unit/test_model_prices_and_context_window.py @@ -15,6 +15,7 @@ from litellm.litellm_core_utils.fallback_generalizations import match_capability from litellm.llms.openai.chat.gpt_5_transformation import is_gpt_reasoning_series_name from litellm.llms.openai_like.json_loader import JSONProviderRegistry from litellm.router_utils.reasoning_effort_capability import resolve_supported_reasoning_efforts +from litellm.types.utils import SearchFreeRequests REPO_ROOT = Path(__file__).parents[2] PRICES_PATH = REPO_ROOT / "model_prices_and_context_window.json" @@ -271,6 +272,27 @@ def test_vertex_gemini_flash_rows_carry_the_documented_retirement_date(prices: d assert prices[f"{prefix}{model}"]["deprecation_date"] == VERTEX_GEMINI_FLASH_RETIREMENT_DATES[model] +def _sampling_flags_across_provider_twins(prices: Mapping[str, Mapping[str, object]], key: str) -> frozenset[object]: + bare: Final = key.split("/")[-1] + twins: Final = tuple(twin for twin in (bare, f"vertex_ai/{bare}", f"gemini/{bare}") if twin in prices) + return frozenset(prices[twin].get("supports_sampling_params") for twin in (key, *twins)) + + +def test_gemini_rows_agree_on_supports_sampling_params_across_their_provider_twins( + prices: Mapping[str, Mapping[str, object]], +) -> None: + """The bare, vertex_ai/ and gemini/ rows of one Gemini model gate sampling params identically, so a request + takes the same drop-or-400 path on the Vertex route and the AI Studio route""" + flagged: Final = tuple( + key + for key, row in prices.items() + if "supports_sampling_params" in row and key.split("/")[-1].startswith("gemini-") + ) + assert flagged + for key in flagged: + assert len(_sampling_flags_across_provider_twins(prices, key)) == 1, key + + OPENAI_REASONING_FAMILY_MARKERS = ("codex", "deep-research", "chat-latest") @@ -719,3 +741,53 @@ def test_unregistered_provider_guard_flags_only_labels_nobody_registered(): "unknown_root-new_family_models", "vertex_ai-new_family_models", ] + + +def _search_free_requests_rows(path: Path) -> Mapping[str, dict[str, JsonValue]]: + prices: Final[dict[str, JsonValue]] = TypeAdapter(dict[str, JsonValue]).validate_json(path.read_bytes()) + return MappingProxyType( + {key: row for key, row in prices.items() if isinstance(row, dict) and "search_free_requests" in row} + ) + + +@pytest.mark.parametrize("path", (PRICES_PATH, BACKUP_PRICES_PATH), ids=("main", "backup")) +def test_search_free_requests_rows_are_grounding_rows_with_one_allowance_per_group(path: Path) -> None: + rows = _search_free_requests_rows(path) + assert rows + allowances = { + key: TypeAdapter(SearchFreeRequests).validate_python(row["search_free_requests"]) for key, row in rows.items() + } + for key, row in rows.items(): + assert row.get("supports_web_search") is True, key + assert row.get("search_context_cost_per_query"), key + assert allowances[key]["count"] > 0, key + for group in {allowance["shared_group"] for allowance in allowances.values()}: + same_group = {(a["count"], a["period"]) for a in allowances.values() if a["shared_group"] == group} + assert len(same_group) == 1, (group, same_group) + + +def test_search_free_requests_backup_rows_match_the_main_catalog() -> None: + assert _search_free_requests_rows(BACKUP_PRICES_PATH) == _search_free_requests_rows(PRICES_PATH) + + +@pytest.mark.parametrize("path", (PRICES_PATH, BACKUP_PRICES_PATH), ids=("main", "backup")) +def test_volcengine_doubao_seed_2_1_pro_260915_row_matches_published_metadata(path: Path): + """Volcengine Ark lists doubao-seed-2-1-pro-260915 at 6 / 30 CNY per million input / output tokens with + cache hits at 1.2 (ark.volcengine.com model detail and docs.volcengine.com/docs/82379/1544106, read + 2026-10-20), a 1024k context window and a 256k output cap. USD rows use the 6.9565 CNY/USD rate of the + sibling 260628 row.""" + rows: Mapping[str, object] = json.loads(path.read_text()) + entry = rows.get("volcengine/doubao-seed-2-1-pro-260915") + assert isinstance(entry, dict) + assert entry["litellm_provider"] == "volcengine" + assert entry["mode"] == "chat" + assert entry["max_input_tokens"] == 1024000 + assert entry["max_output_tokens"] == 256000 + assert entry["max_tokens"] == 256000 + # Volcengine Ark pricing https://www.volcengine.com/docs/82379/1544106 checked 2026-10-20 + assert entry["input_cost_per_token"] == pytest.approx(6.0 / 6.9565 / 1_000_000, rel=1e-4) + assert entry["output_cost_per_token"] == pytest.approx(30.0 / 6.9565 / 1_000_000, rel=1e-4) + assert entry["cache_read_input_token_cost"] == pytest.approx(1.2 / 6.9565 / 1_000_000, rel=1e-4) + sibling = rows["volcengine/doubao-seed-2-1-pro-260628"] + assert isinstance(sibling, dict) + assert all(entry[key] == sibling[key] for key in ("input_cost_per_token", "output_cost_per_token", "cache_read_input_token_cost")) diff --git a/tests/unit/test_router/test_router.py b/tests/unit/test_router/test_router.py index 90674dcb3f9..13ac55fa937 100644 --- a/tests/unit/test_router/test_router.py +++ b/tests/unit/test_router/test_router.py @@ -9673,6 +9673,26 @@ def test_update_kwargs_with_deployment_propagates_model_tags(): assert "production" in kwargs["metadata"]["tags"] +def test_update_kwargs_with_deployment_merges_many_client_tags_in_linear_time(): + router: Final = litellm.Router( + model_list=[ + { + "model_name": "gpt-4o-mini", + "litellm_params": {"model": "openai/gpt-4o-mini", "api_key": "fake-key", "tags": ["deployment-tag"]}, + }, + ], + ) + client_tags: Final = [f"client-{index}" for index in range(100_000)] + kwargs: Final = {"metadata": {"tags": client_tags}} + deployment: Final = router.get_deployment_by_model_group_name(model_group_name="gpt-4o-mini") + + started: Final = time.perf_counter() + router._update_kwargs_with_deployment(deployment=deployment, kwargs=kwargs) + + assert time.perf_counter() - started < 2 + assert kwargs["metadata"]["tags"] == [*client_tags, "deployment-tag"] + + def test_update_kwargs_with_deployment_merges_tags_without_duplicates(): """ Test that when both request-level and deployment-level tags exist, @@ -15175,7 +15195,7 @@ async def test_cyclic_fallback_graph_does_not_amplify_one_request(): _FLAT_ATTEMPT_RECORD_KEYS = frozenset( - {"model_group", "deployment_id", "exception_type", "exception_string", "attempted_retries"} + {"model_group", "deployment_id", "model", "base_model", "exception_type", "exception_string", "attempted_retries"} ) _BREADCRUMB_CREDENTIAL_CANARY = "Bearer sk-ant-oat01-RETRY-BREADCRUMB-CANARY-doNotShip" @@ -26055,6 +26075,359 @@ class TestRouterIndexManagement: ) +_PRIORITY_CHAT_COMPLETION: Final = { + "id": "chatcmpl-priority", + "object": "chat.completion", + "created": 1, + "model": "gpt-5.4-nano", + "choices": [{"index": 0, "finish_reason": "stop", "message": {"role": "assistant", "content": "pong"}}], + "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2}, +} +_PRIORITY_MESSAGES: Final = [{"role": "user", "content": "Reply with the single word pong"}] + + +def _priority_router(default_priority: int | None) -> Router: + return Router( + model_list=[ + { + "model_name": "qa-chat", + "litellm_params": {"model": "openai/gpt-5.4-nano", "api_key": "sk-priority-wire"}, + } + ], + default_priority=default_priority, + ) + + +def _priority_provider(respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch) -> respx.Route: + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + return respx_mock.post("https://api.openai.com/v1/chat/completions").mock( + return_value=httpx.Response(200, json=_PRIORITY_CHAT_COMPLETION) + ) + + +@pytest.mark.parametrize( + ("default_priority", "request_kwargs", "queued_priority"), + [ + (3, {}, 3), + (3, {"priority": None}, 3), + (3, {"priority": 2}, 2), + (None, {"priority": 2}, 2), + (None, {"priority": 0}, 0), + (None, {"priority": "1"}, 1), + (None, {"priority": True}, 1), + (3, {"priority": 1.0}, 1), + (3, {"priority": "high", "drop_params": True}, 3), + ], +) +async def test_acompletion_queues_the_resolved_priority_exactly_once( + default_priority: int | None, request_kwargs: dict[str, object], queued_priority: int +) -> None: + router: Final = _priority_router(default_priority) + with patch.object(router.scheduler, "add_request", wraps=router.scheduler.add_request) as add_request: + response: Final = await router.acompletion( + model="qa-chat", messages=_PRIORITY_MESSAGES, mock_response="pong", **request_kwargs + ) + assert add_request.await_count == 1 + assert add_request.await_args.kwargs["request"].priority == queued_priority + assert response._hidden_params["additional_headers"]["x-litellm-request-prioritization-used"] is True + + +async def test_acompletion_without_any_priority_never_enters_the_scheduler() -> None: + router: Final = _priority_router(None) + with patch.object(router.scheduler, "add_request", wraps=router.scheduler.add_request) as add_request: + response: Final = await router.acompletion(model="qa-chat", messages=_PRIORITY_MESSAGES, mock_response="pong") + assert add_request.await_count == 0 + assert "x-litellm-request-prioritization-used" not in response._hidden_params.get("additional_headers", {}) + + +@pytest.mark.parametrize( + ("default_priority", "request_kwargs"), [(3, {}), (None, {"priority": 3})], ids=["default", "explicit"] +) +async def test_a_request_pinned_to_a_deployment_id_is_served_while_an_earlier_one_waits_in_the_queue( + default_priority: int | None, request_kwargs: dict[str, object] +) -> None: + router: Final = Router( + model_list=[ + { + "model_name": "qa-chat", + "litellm_params": {"model": "openai/gpt-5.4-nano", "api_key": "sk-priority-wire"}, + "model_info": {"id": "qa-chat-deployment"}, + } + ], + default_priority=default_priority, + ) + await router.scheduler.add_request(FlowItem(priority=0, request_id="ahead", model_name="qa-chat-deployment")) + response: Final = await asyncio.wait_for( + router.acompletion( + model="qa-chat-deployment", messages=_PRIORITY_MESSAGES, mock_response="pong", **request_kwargs + ), + timeout=5, + ) + assert response.choices[0].message.content == "pong" + assert response._hidden_params["additional_headers"]["x-litellm-request-prioritization-used"] is True + + +@pytest.mark.parametrize("priority", ["high", [1], 1.5]) +async def test_acompletion_rejects_a_non_integer_priority_before_the_provider_sees_it( + priority: object, respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch +) -> None: + provider: Final = _priority_provider(respx_mock, monkeypatch) + router: Final = _priority_router(3) + with pytest.raises(litellm.BadRequestError, match="priority must be an integer") as raised: + await router.acompletion(model="qa-chat", messages=_PRIORITY_MESSAGES, priority=priority) + assert raised.value.param == "priority" + assert not provider.called + + +async def test_acompletion_drops_a_non_integer_priority_from_the_provider_call_under_drop_params( + respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch +) -> None: + provider: Final = _priority_provider(respx_mock, monkeypatch) + router: Final = _priority_router(None) + await router.acompletion(model="qa-chat", messages=_PRIORITY_MESSAGES, priority="high", drop_params=True) + assert "priority" not in json.loads(provider.calls.last.request.content) + + +@pytest.mark.parametrize("priority", [0, "1"]) +async def test_acompletion_with_an_integer_priority_sends_no_priority_to_the_provider( + priority: object, respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch +) -> None: + provider: Final = _priority_provider(respx_mock, monkeypatch) + router: Final = _priority_router(None) + await router.acompletion(model="qa-chat", messages=_PRIORITY_MESSAGES, priority=priority) + assert "priority" not in json.loads(provider.calls.last.request.content) + + +async def test_schedule_acompletion_under_a_default_priority_queues_the_explicit_priority_once() -> None: + router: Final = _priority_router(3) + with patch.object(router.scheduler, "add_request", wraps=router.scheduler.add_request) as add_request: + response: Final = await router.schedule_acompletion( + model="qa-chat", messages=_PRIORITY_MESSAGES, priority=1, mock_response="pong" + ) + assert add_request.await_count == 1 + assert add_request.await_args.kwargs["request"].priority == 1 + assert response._hidden_params["additional_headers"]["x-litellm-request-prioritization-used"] is True + + +@pytest.mark.parametrize( + ("deployment_params", "router_defaults"), + [ + ({}, {"drop_params": True}), + ({"drop_params": True}, {}), + ({"drop_params": "true"}, {}), + ({"additional_drop_params": ["priority"]}, {}), + ({}, {"additional_drop_params": ["priority"]}), + ], +) +async def test_acompletion_drops_a_non_integer_priority_under_the_router_or_deployment_drop_params( + deployment_params: dict[str, object], router_defaults: dict[str, object] +) -> None: + router: Final = Router( + model_list=[ + { + "model_name": "qa-chat", + "litellm_params": {"model": "openai/gpt-5.4-nano", "api_key": "sk-priority-wire", **deployment_params}, + } + ], + default_priority=3, + default_litellm_params=router_defaults, + ) + with patch.object(router.scheduler, "add_request", wraps=router.scheduler.add_request) as add_request: + response: Final = await router.acompletion( + model="qa-chat", messages=_PRIORITY_MESSAGES, mock_response="pong", priority="high" + ) + assert add_request.await_args.kwargs["request"].priority == 3 + assert response._hidden_params["additional_headers"]["x-litellm-request-prioritization-used"] is True + + +@pytest.mark.parametrize( + ("deployment", "requested_model", "routing_fields"), + [ + ( + { + "model_name": "model_name_team-a_team-a-chat", + "litellm_params": {"model": "openai/gpt-5.4-nano", "api_key": "sk-priority-wire", "drop_params": True}, + "model_info": {"id": "team-a-chat", "team_id": "team-a", "team_public_model_name": "team-chat"}, + }, + "team-chat", + {"metadata": {"user_api_key_team_id": "team-a"}}, + ), + ( + { + "model_name": "qa-chat", + "litellm_params": {"model": "openai/gpt-5.4-nano", "api_key": "sk-priority-wire", "drop_params": True}, + "model_info": {"id": "qa-chat-deployment"}, + }, + "qa-chat-deployment", + {}, + ), + ( + { + "model_name": "qa-chat", + "litellm_params": {"model": "openai/gpt-5.4-nano", "api_key": "sk-priority-wire", "drop_params": True}, + }, + "openai/gpt-5.4-nano", + {"specific_deployment": True}, + ), + ], + ids=["team-route", "deployment-id", "provider-model-name"], +) +async def test_deployment_drop_params_drop_a_non_integer_priority_on_every_deployment_route( + deployment: dict[str, object], + requested_model: str, + routing_fields: dict[str, object], + monkeypatch: pytest.MonkeyPatch, +) -> None: + monkeypatch.setattr(litellm, "drop_params", False) + router: Final = Router(model_list=[deployment], default_priority=3) + with patch.object(router.scheduler, "add_request", wraps=router.scheduler.add_request) as add_request: + response: Final = await router.acompletion( + model=requested_model, + messages=_PRIORITY_MESSAGES, + mock_response="pong", + priority="high", + **routing_fields, + ) + assert add_request.await_args.kwargs["request"].priority == 3 + assert response._hidden_params["additional_headers"]["x-litellm-request-prioritization-used"] is True + + +async def test_schedule_acompletion_queues_a_prompt_management_model(monkeypatch: pytest.MonkeyPatch) -> None: + router: Final = Router( + model_list=[ + { + "model_name": "cached-chat", + "litellm_params": { + "model": "anthropic_cache_control_hook/openai/gpt-5.4-nano", + "api_key": "sk-priority-wire", + "prompt_id": "cache-points", + }, + } + ] + ) + provider: Final = AsyncMock(return_value=litellm.ModelResponse()) + monkeypatch.setattr(litellm, "acompletion", provider) + logging_obj: Final = LiteLLMLogging( + model="cached-chat", + messages=_PRIORITY_MESSAGES, + stream=False, + call_type="acompletion", + start_time=time.time(), + litellm_call_id="prompt-management-priority", + function_id="f", + ) + with patch.object(router.scheduler, "add_request", wraps=router.scheduler.add_request) as add_request: + response: Final = await router.schedule_acompletion( + model="cached-chat", messages=_PRIORITY_MESSAGES, priority=1, litellm_logging_obj=logging_obj + ) + assert add_request.await_count == 1 + assert add_request.await_args.kwargs["request"].priority == 1 + assert provider.await_count == 1 + assert "priority" not in provider.await_args.kwargs + assert response._hidden_params["additional_headers"]["x-litellm-request-prioritization-used"] is True + + +@pytest.mark.parametrize( + ("configured", "expected"), + [(3, 3), ("3", 3), ("-1", -1), (0, 0), (None, None)], + ids=["int", "digit-string", "negative-string", "zero", "unset"], +) +def test_the_router_parses_default_priority_once_at_init(configured: object, expected: int | None) -> None: + assert _priority_router(configured).default_priority == expected + + +@pytest.mark.parametrize("configured", ["high", 1.5, [3], False], ids=["word", "float", "list", "yaml-off"]) +def test_an_invalid_default_priority_is_ignored_with_a_warning( + configured: object, caplog: pytest.LogCaptureFixture +) -> None: + with caplog.at_level(logging.WARNING, logger="LiteLLM Router"): + router: Final = _priority_router(configured) + assert router.default_priority is None + assert any("default_priority is ignored" in record.getMessage() for record in caplog.records), caplog.records + + +async def test_an_invalid_default_priority_leaves_every_request_unscheduled() -> None: + router: Final = _priority_router("high") + with patch.object(router.scheduler, "add_request", wraps=router.scheduler.add_request) as add_request: + response: Final = await router.acompletion(model="qa-chat", messages=_PRIORITY_MESSAGES, mock_response="pong") + assert add_request.await_count == 0 + assert "x-litellm-request-prioritization-used" not in response._hidden_params.get("additional_headers", {}) + + +async def test_schedule_acompletion_without_a_priority_or_a_default_is_rejected_before_the_provider( + respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch +) -> None: + provider: Final = _priority_provider(respx_mock, monkeypatch) + router: Final = _priority_router(None) + with pytest.raises(litellm.BadRequestError, match="priority is required") as raised: + await router.schedule_acompletion(model="qa-chat", messages=_PRIORITY_MESSAGES) + assert raised.value.param == "priority" + assert not provider.called + + +async def test_schedule_acompletion_without_a_priority_queues_the_default_once() -> None: + router: Final = _priority_router(3) + with patch.object(router.scheduler, "add_request", wraps=router.scheduler.add_request) as add_request: + response: Final = await router.schedule_acompletion( + model="qa-chat", messages=_PRIORITY_MESSAGES, mock_response="pong" + ) + assert add_request.await_count == 1 + assert add_request.await_args.kwargs["request"].priority == 3 + assert response._hidden_params["additional_headers"]["x-litellm-request-prioritization-used"] is True + + +@pytest.mark.parametrize( + ("default_priority", "request_kwargs", "queued_priority"), + [ + (3, {}, 3), + (3, {"priority": None}, 3), + (3, {"priority": 2}, 2), + (None, {"priority": 0}, 0), + (None, {"priority": "1"}, 1), + (3, {"priority": "high", "drop_params": True}, 3), + ], +) +async def test_atext_completion_queues_the_resolved_priority_exactly_once( + default_priority: int | None, + request_kwargs: dict[str, object], + queued_priority: int, + respx_mock: respx.MockRouter, + monkeypatch: pytest.MonkeyPatch, +) -> None: + provider: Final = _priority_provider(respx_mock, monkeypatch) + router: Final = _priority_router(default_priority) + with patch.object(router.scheduler, "add_request", wraps=router.scheduler.add_request) as add_request: + response: Final = await router.atext_completion(model="qa-chat", prompt="pong?", **request_kwargs) + assert add_request.await_count == 1 + assert add_request.await_args.kwargs["request"].priority == queued_priority + assert response._hidden_params["additional_headers"]["x-litellm-request-prioritization-used"] is True + assert "priority" not in json.loads(provider.calls.last.request.content) + + +async def test_atext_completion_without_any_priority_never_enters_the_scheduler( + respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch +) -> None: + provider: Final = _priority_provider(respx_mock, monkeypatch) + router: Final = _priority_router(None) + with patch.object(router.scheduler, "add_request", wraps=router.scheduler.add_request) as add_request: + response: Final = await router.atext_completion(model="qa-chat", prompt="pong?") + assert add_request.await_count == 0 + assert "x-litellm-request-prioritization-used" not in response._hidden_params.get("additional_headers", {}) + assert provider.called + + +@pytest.mark.parametrize("priority", ["high", [1], 1.5]) +async def test_atext_completion_rejects_a_non_integer_priority_before_the_provider_sees_it( + priority: object, respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch +) -> None: + provider: Final = _priority_provider(respx_mock, monkeypatch) + router: Final = _priority_router(3) + with pytest.raises(litellm.BadRequestError, match="priority must be an integer") as raised: + await router.atext_completion(model="qa-chat", prompt="pong?", priority=priority) + assert raised.value.param == "priority" + assert not provider.called + + def test_router_multi_org_list() -> None: """ Pass list of orgs in 1 model definition, @@ -29295,3 +29668,68 @@ def test_pre_call_checks_ignores_an_image_response_format_string(monkeypatch: py ) assert [d["model_info"]["id"] for d in filtered] == ["only"] + + +@pytest.mark.asyncio +async def test_responses_fallback_wrapper_disconnect_billing_keeps_the_primary_streams_tokens(): + """After a mid-stream hop, a disconnect bills the primary's relayed text plus the fallback's, not the fallback alone.""" + import json + + from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig + from litellm.responses.streaming_iterator import ResponsesAPIStreamingIterator + + def _relayed_iterator(text: str) -> ResponsesAPIStreamingIterator: + logging_obj: Final = MagicMock(spec=LiteLLMLogging) + logging_obj.model_call_details = {"litellm_params": {}} + logging_obj.completion_start_time = None + iterator: Final = ResponsesAPIStreamingIterator( + response=httpx.Response(200), + model="gpt-5.4", + responses_api_provider_config=OpenAIResponsesAPIConfig(), + logging_obj=logging_obj, + request_data={"model": "gpt-5.4", "input": "Hi"}, + custom_llm_provider="openai", + ) + created: Final = { + "id": "resp_1", + "object": "response", + "created_at": 1700000000.0, + "model": "gpt-5.4", + "status": "in_progress", + "output": [], + "parallel_tool_calls": True, + "tool_choice": "auto", + "tools": [], + } + iterator._process_chunk(json.dumps({"type": "response.created", "sequence_number": 0, "response": created})) + iterator._process_chunk( + json.dumps( + { + "type": "response.output_text.delta", + "sequence_number": 1, + "item_id": "msg_1", + "output_index": 0, + "content_index": 0, + "delta": text, + } + ) + ) + return iterator + + router: Final = Router( + model_list=[{"model_name": "primary", "litellm_params": {"model": "openai/gpt-5.4", "api_key": "k"}}] + ) + primary: Final = _relayed_iterator("Once upon a time there was a lighthouse keeper") + fallback: Final = _relayed_iterator("who lit the lamp") + wrapped: Final = await router._aresponses_streaming_iterator( + response=primary, + initial_kwargs={"model": "primary", "stream": True, "input": "Hi", "original_generic_function": AsyncMock()}, + ) + primary_tokens: Final = primary.partial_response_on_disconnect().response.usage.output_tokens + fallback_tokens: Final = fallback.partial_response_on_disconnect().response.usage.output_tokens + + assert wrapped.partial_response_on_disconnect().response.usage.output_tokens == primary_tokens + + wrapped.adopt_fallback_headers(fallback) + + assert wrapped.partial_response_on_disconnect().response.usage.output_tokens == primary_tokens + fallback_tokens diff --git a/tests/unit/test_router/test_router_helper_utils.py b/tests/unit/test_router/test_router_helper_utils.py index e3061294bef..7088818aa01 100644 --- a/tests/unit/test_router/test_router_helper_utils.py +++ b/tests/unit/test_router/test_router_helper_utils.py @@ -837,7 +837,12 @@ def test_log_retry(model_list: list[DeploymentTypedDict], metadata_key: str) -> "model": "gpt-3.5-turbo", "api_key": "sk-must-not-be-recorded", "messages": [{"role": "user", "content": "hi"}], - metadata_key: {"model_info": {"id": "deployment-1"}, "attempted_retries": 2, "user_api_key": "sk-proxy"}, + metadata_key: { + "model_info": {"id": "deployment-1", "base_model": "azure/gpt-3.5-turbo"}, + "deployment": "azure/my-35-deployment", + "attempted_retries": 2, + "user_api_key": "sk-proxy", + }, }, e=rate_limit_error, ) @@ -845,6 +850,8 @@ def test_log_retry(model_list: list[DeploymentTypedDict], metadata_key: str) -> { "model_group": "gpt-3.5-turbo", "deployment_id": "deployment-1", + "model": "azure/my-35-deployment", + "base_model": "azure/gpt-3.5-turbo", "exception_type": "RateLimitError", "exception_string": "litellm.RateLimitError: slow down", "attempted_retries": 2, @@ -856,6 +863,38 @@ def test_log_retry(model_list: list[DeploymentTypedDict], metadata_key: str) -> assert router.log_retry(kwargs=planted_kwargs, e=rate_limit_error)[metadata_key]["request_retry_count"] == 1 +def test_log_retry_reads_base_model_from_the_deployments_litellm_params() -> None: + """An Azure named deployment declares ``base_model`` under ``litellm_params``, not ``model_info``, and + that is the model the failure row is priced at, so the retry record has to carry it too""" + router = Router( + model_list=[ + { + "model_name": "azure-group", + "litellm_params": { + "model": "azure/my-named-deployment", + "api_key": "sk-fake", + "api_base": "https://example.openai.azure.com", + "base_model": "azure/gpt-4o-mini", + }, + "model_info": {"id": "dep-azure-named"}, + } + ] + ) + new_kwargs = router.log_retry( + kwargs={ + "model": "azure-group", + "metadata": { + "model_info": {"id": "dep-azure-named"}, + "deployment": "azure/my-named-deployment", + "attempted_retries": 0, + }, + }, + e=litellm.Timeout(message="slow", llm_provider="azure", model="azure/my-named-deployment"), + ) + record = new_kwargs["metadata"]["previous_models"][0] + assert (record["model"], record["base_model"]) == ("azure/my-named-deployment", "azure/gpt-4o-mini") + + @pytest.mark.usefixtures("router_minute_pinned") def test_update_usage(model_list): """Test if the '_update_usage' function is working correctly""" diff --git a/tests/unit/test_router_model_cost_isolation.py b/tests/unit/test_router_model_cost_isolation.py index 1655dac6382..f001008ee2c 100644 --- a/tests/unit/test_router_model_cost_isolation.py +++ b/tests/unit/test_router_model_cost_isolation.py @@ -585,7 +585,7 @@ def test_should_not_pollute_shared_key_with_custom_nonzero_pricing(): ) -@pytest.mark.parametrize("flag", ["supports_regex_lookaround", "supports_assistant_prefill"]) +@pytest.mark.parametrize("flag", ["supports_regex_lookaround", "supports_assistant_prefill", "supports_sampling_params"]) def test_capability_flag_stays_on_the_deployment_that_set_it(flag: str) -> None: """A deployment's capability override must not land on the shared ``{provider}/{model}`` key, or every sibling deployment of that model would inherit it.""" @@ -4318,3 +4318,100 @@ def test_router_capacity_reads_a_model_info_base_model_before_a_litellm_params_o assert _effective_max_input_tokens(router) == 1024 assert _deployments_allowed_for_2048_input_tokens(router) == 0 _invalidate_model_cost_lowercase_map() + + +def test_deployment_id_equal_to_another_providers_catalog_key_bills_its_own_prices_under_pricing_provider() -> None: + """Resolving the id by name under the routing provider lands on the other provider's row and the + provider check rejects it, billing $0. ``pricing_provider`` names the row's provider, so the + deployment's own prices (merged into that row) bill.""" + model_cost_entries: Final = { + key: copy.deepcopy(litellm.model_cost.get(key)) + for key in (_COLLIDING_BUILTIN_KEY, _COLLIDING_SHARED_OPENAI_KEY) + } + try: + router: Final = Router( + model_list=[ + _pricing_provider_deployment( + _COLLIDING_BUILTIN_KEY, + {"input_cost_per_token": 0.00000096, "output_cost_per_token": 0.00000302}, + ) + ] + ) + + response: Final = _glm_completion(router) + + assert response._hidden_params["response_cost"] == pytest.approx(1000 * 0.00000096 + 500 * 0.00000302) + finally: + _restore_model_cost_entries(model_cost_entries) + litellm.get_model_info.cache_clear() + + +def _pricing_provider_deployment(model_id: str, model_info: dict) -> DeploymentTypedDict: + litellm_params: Final = LiteLLMParamsTypedDict( + model="zai-org/GLM-5.2", + api_base="https://inference.baseten.co/v1", + custom_llm_provider="openai", + ) + return DeploymentTypedDict( + model_name="nvidia/zai-org/glm-5.2", + litellm_params=litellm_params, + model_info={"id": model_id, "pricing_provider": "baseten", **model_info}, + ) + + +def _glm_completion(router: Router) -> litellm.ModelResponse: + response: Final = router.completion( + model="nvidia/zai-org/glm-5.2", + messages=[{"role": "user", "content": "priced under another provider"}], + mock_response=litellm.ModelResponse( + model="zai-org/GLM-5.2", + usage=litellm.Usage(prompt_tokens=1000, completion_tokens=500, total_tokens=1500), + ), + ) + assert isinstance(response, litellm.ModelResponse) + return response + + +def test_pricing_provider_without_custom_prices_bills_that_providers_catalog_rate() -> None: + """An openai-compatible deployment pointed at another provider's host can name that provider for + pricing: the request is priced from its catalog row, where the routing provider has none.""" + model_id: Final = "glm52-priced-as-baseten" + catalog_row: Final = litellm.model_cost[_COLLIDING_BUILTIN_KEY] + model_cost_entries: Final = { + key: copy.deepcopy(litellm.model_cost.get(key)) + for key in (model_id, _COLLIDING_BUILTIN_KEY, _COLLIDING_SHARED_OPENAI_KEY) + } + try: + response: Final = _glm_completion(Router(model_list=[_pricing_provider_deployment(model_id, {})])) + + assert response._hidden_params["response_cost"] == pytest.approx( + 1000 * catalog_row["input_cost_per_token"] + 500 * catalog_row["output_cost_per_token"] + ) + finally: + _restore_model_cost_entries(model_cost_entries) + litellm.get_model_info.cache_clear() + + +def test_pricing_provider_fills_unset_rates_from_that_providers_catalog_row() -> None: + """Rates the deployment sets win, rates it leaves out come from the pricing provider's row for the + backend model rather than defaulting to 0 because the routing provider has no row.""" + model_id: Final = "glm52-priced-as-baseten-custom" + catalog_row: Final = copy.deepcopy(litellm.model_cost[_COLLIDING_BUILTIN_KEY]) + model_cost_entries: Final = { + key: copy.deepcopy(litellm.model_cost.get(key)) + for key in (model_id, _COLLIDING_BUILTIN_KEY, _COLLIDING_SHARED_OPENAI_KEY) + } + rates: Final = {"input_cost_per_token": 0.00000096, "output_cost_per_token": 0.00000302} + try: + router: Final = Router(model_list=[_pricing_provider_deployment(model_id, rates)]) + + registered: Final = litellm.model_cost[model_id] + assert {key: registered[key] for key in rates} == rates + assert registered["cache_read_input_token_cost"] == catalog_row["cache_read_input_token_cost"] + assert _glm_completion(router)._hidden_params["response_cost"] == pytest.approx( + 1000 * 0.00000096 + 500 * 0.00000302 + ) + assert litellm.model_cost[_COLLIDING_BUILTIN_KEY] == catalog_row + finally: + _restore_model_cost_entries(model_cost_entries) + litellm.get_model_info.cache_clear() diff --git a/tests/unit/test_utils.py b/tests/unit/test_utils.py index 44939ca7585..9b6700e9d39 100644 --- a/tests/unit/test_utils.py +++ b/tests/unit/test_utils.py @@ -1073,6 +1073,7 @@ def test_aaamodel_prices_and_context_window_json_is_valid(): "image_edit", "embedding", "evaluation", + "extraction", "guardrail", "image_generation", "video_generation", @@ -1260,6 +1261,16 @@ def test_aaamodel_prices_and_context_window_json_is_valid(): "type": "string", "enum": ["per_prompt", "per_query"], }, + "search_free_requests": { + "type": "object", + "properties": { + "count": {"type": "integer", "minimum": 1}, + "period": {"type": "string", "enum": ["day", "month"]}, + "shared_group": {"type": "string"}, + }, + "required": ["count", "period", "shared_group"], + "additionalProperties": False, + }, "citation_cost_per_token": {"type": "number"}, "supported_modalities": { "type": "array", @@ -2358,7 +2369,6 @@ def test_register_model_with_scientific_notation(): _invalidate_model_cost_lowercase_map() -@pytest.mark.usefixtures("isolated_openai_model_sets") @pytest.mark.usefixtures("isolated_openai_model_sets") @respx.mock def test_register_model_url_fetch_uses_single_attempt(monkeypatch): @@ -4803,8 +4813,7 @@ async def test_builtin_string_callback_registers_when_subclass_already_active( assert any(type(cb) is S3Logger for cb in litellm._async_success_callback) -@pytest.mark.usefixtures("isolated_openai_model_sets") -@pytest.mark.usefixtures("isolated_openai_model_sets") +@pytest.mark.usefixtures("isolated_openai_model_sets", "local_model_cost_map") @pytest.mark.parametrize("rate", (0.0, 0.000123)) @pytest.mark.parametrize("updated_rate", (None, 0.0, 0.000456)) def test_reapply_runtime_registrations_replays_register_model_overrides( @@ -4833,7 +4842,8 @@ def test_reapply_runtime_registrations_replays_register_model_overrides( # installed would make this depend on when that happens. monkeypatch.setattr(litellm_utils._LiveDeploymentReplay, "callback", None) - saved_model_cost = litellm.model_cost + saved_model_cost: Final = litellm.model_cost + monkeypatch.setattr(litellm, "model_cost", dict(saved_model_cost)) try: litellm.register_model( model_cost={ @@ -4871,8 +4881,7 @@ def test_reapply_runtime_registrations_replays_register_model_overrides( _invalidate_model_cost_lowercase_map() -@pytest.mark.usefixtures("isolated_openai_model_sets") -@pytest.mark.usefixtures("isolated_openai_model_sets") +@pytest.mark.usefixtures("isolated_openai_model_sets", "local_model_cost_map") def test_reapply_runtime_registrations_drops_request_scoped_registrations(monkeypatch): """ Per-request custom pricing describes one call, so it must not be re-asserted @@ -9370,7 +9379,7 @@ def test_models_by_provider(): continue elif v["litellm_provider"] == "sagemaker" or v["litellm_provider"] == "bedrock_converse": continue - elif v.get("mode") in ("search", "decisions", "evaluation"): + elif v.get("mode") in ("search", "decisions", "evaluation", "extraction"): continue else: providers.add(v["litellm_provider"]) @@ -10703,3 +10712,18 @@ def test_get_optional_params_keeps_a_tool_config_cache_point_out_of_the_openai_e assert optional_params["extra_body"] == {"kept": True} assert "cache_control_injection_points" not in optional_params + + +def test_get_optional_params_forwards_a_tool_config_cache_point_to_a_downstream_litellm_proxy(): + """A litellm_proxy deployment calls the downstream proxy through the OpenAI SDK, and that proxy + applies cache_control_injection_points itself, so the point must ride along in extra_body.""" + point: Final = {"location": "tool_config", "control": {"type": "ephemeral"}} + optional_params: Final[dict[str, object]] = litellm.utils.get_optional_params( + model="claude-sonnet-4-5", + custom_llm_provider="litellm_proxy", + tools=[{"type": "function", "function": {"name": "get_weather", "parameters": {"type": "object"}}}], + cache_control_injection_points=[point], + extra_body={"kept": True}, + ) + + assert optional_params["extra_body"] == {"kept": True, "cache_control_injection_points": [point]} diff --git a/tests/unit/types/test_litellm_params.py b/tests/unit/types/test_litellm_params.py index e88d757519c..788d405f99f 100644 --- a/tests/unit/types/test_litellm_params.py +++ b/tests/unit/types/test_litellm_params.py @@ -91,10 +91,12 @@ CONNECTION_NAMES: Final = ( "azure_ad_token_provider", "litellm_credential_name", "github_copilot_auth_type", + "github_copilot_host", "configurable_clientside_auth_params", "use_xai_oauth", "fireworks_forward_user_id", "aws_batch_role_arn", + "aws_bedrock_control_plane_endpoint", "s3_bucket_name", "s3_region_name", "s3_endpoint_url", @@ -274,6 +276,7 @@ INTERNAL_STATE_NAMES: Final = ( BEDROCK_BATCH_NAMES: Final = ( "aws_batch_role_arn", + "aws_bedrock_control_plane_endpoint", "s3_bucket_name", "s3_region_name", "s3_endpoint_url", @@ -686,6 +689,7 @@ NAMES_SHARED_WITH_TYPED_MODELS: Final[Mapping[str, tuple[str, ...]]] = MappingPr "api_key", "api_version", "aws_batch_role_arn", + "aws_bedrock_control_plane_endpoint", "azure_password", "azure_scope", "azure_username", diff --git a/tests/unit/types/test_router.py b/tests/unit/types/test_router.py index e15e95f9d55..2892a829eab 100644 --- a/tests/unit/types/test_router.py +++ b/tests/unit/types/test_router.py @@ -361,7 +361,7 @@ def test_server_owned_registry_includes_anthropic_openai_and_oauth_token_exchang "token_exchange_profile", "token_exchange_scope", ) - assert github_copilot_oauth_litellm_params == ("github_copilot_auth_type",) + assert github_copilot_oauth_litellm_params == ("github_copilot_auth_type", "github_copilot_host") assert server_owned_wif_litellm_params == ( anthropic_wif_litellm_params + openai_wif_litellm_params diff --git a/ui/litellm-dashboard/package-lock.json b/ui/litellm-dashboard/package-lock.json index 7cc7415d52d..944455721cd 100644 --- a/ui/litellm-dashboard/package-lock.json +++ b/ui/litellm-dashboard/package-lock.json @@ -86,7 +86,7 @@ "tw-animate-css": "1.4.0", "typescript": "5.9.3", "typescript-eslint": "8.60.1", - "vite": "7.3.5", + "vite": "7.3.7", "vitest": "4.1.11" }, "engines": { @@ -12422,13 +12422,13 @@ } }, "node_modules/vite": { - "version": "7.3.5", - "resolved": "https://registry.npmjs.org/vite/-/vite-7.3.5.tgz", - "integrity": "sha512-KuOaNhcnGFN2zIPGA7wRmzF+lJA1sea7rHq17aiJ++9lzY1WWG6Jpwqwe1KNbRVPIqHmr8GLYx7jbrQcN/7/ww==", + "version": "7.3.7", + "resolved": "https://registry.npmjs.org/vite/-/vite-7.3.7.tgz", + "integrity": "sha512-AHEzTORMbi7/7aXp7w7KZ5+DCUdSeLsJz0grY8xHpc9DHdYb0vQu6DqJfm2tOw3gDExNgPgnJTXxM6syYFHaCA==", "dev": true, "license": "MIT", "dependencies": { - "esbuild": "^0.27.0", + "esbuild": "^0.27.0 || ^0.28.0", "fdir": "^6.5.0", "picomatch": "^4.0.3", "postcss": "^8.5.6", diff --git a/ui/litellm-dashboard/package.json b/ui/litellm-dashboard/package.json index cd08995471f..f2a1a5e4e7f 100644 --- a/ui/litellm-dashboard/package.json +++ b/ui/litellm-dashboard/package.json @@ -103,7 +103,7 @@ "tw-animate-css": "1.4.0", "typescript": "5.9.3", "typescript-eslint": "8.60.1", - "vite": "7.3.5", + "vite": "7.3.7", "vitest": "4.1.11" }, "overrides": { diff --git a/ui/litellm-dashboard/src/app/(dashboard)/router-settings/_components/RequestTagMappings.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/router-settings/_components/RequestTagMappings.test.tsx new file mode 100644 index 00000000000..b7ecd6bbb64 --- /dev/null +++ b/ui/litellm-dashboard/src/app/(dashboard)/router-settings/_components/RequestTagMappings.test.tsx @@ -0,0 +1,145 @@ +import { fireEvent, render, screen } from "@testing-library/react"; +import userEvent from "@testing-library/user-event"; +import { useState } from "react"; +import { describe, expect, it, vi } from "vitest"; + +import { RequestTagMapping, RequestTagMappingsEditor, requestTagMappingsAreValid } from "./RequestTagMappings"; + +const exact: RequestTagMapping = { header: "baggage", key: "entrypoint", value: "a", tag: "support" }; +const variable: RequestTagMapping = { header: "baggage", key: "entrypoint", tag_prefix: "usecase:" }; + +function Editor({ + initial, + changed, + saved = vi.fn(), +}: { + initial: RequestTagMapping[]; + changed: (rules: RequestTagMapping[]) => void; + saved?: (rules: RequestTagMapping[]) => void; +}) { + const [rules, setRules] = useState(initial); + return ( + <> + { + setRules(next); + changed(next); + }} + /> + + + ); +} + +describe("RequestTagMappingsEditor", () => { + it("shows YAML-owned rules without allowing edits", () => { + render(); + expect(screen.getByLabelText("Mapping 1 match value")).toBeDisabled(); + expect(screen.getByRole("button", { name: "Add mapping" })).toBeDisabled(); + expect(screen.getByText(/Managed in config.yaml/)).toBeInTheDocument(); + }); + it("shows one-by-one mappings alongside variable prefix mappings", () => { + render(); + expect(screen.getByRole("combobox", { name: "Mapping 1 mode" })).toHaveTextContent("Exact value"); + expect(screen.getByRole("combobox", { name: "Mapping 2 mode" })).toHaveTextContent("Any value"); + expect(screen.getByLabelText("Mapping 1 match value")).toHaveValue("a"); + expect(screen.getByLabelText("Mapping 1 tag")).toHaveValue("support"); + expect(screen.getByLabelText("Mapping 2 tag prefix")).toHaveValue("usecase:"); + expect(screen.getByText("entrypoint=a → support")).toBeInTheDocument(); + expect(screen.getByText("entrypoint=x → usecase:x")).toBeInTheDocument(); + }); + + it("adds and edits a new exact value mapping", async () => { + const changed = vi.fn(); + render(); + await userEvent.click(screen.getByRole("button", { name: "Add mapping" })); + fireEvent.change(screen.getByLabelText("Mapping 1 baggage key"), { target: { value: "entrypoint" } }); + fireEvent.change(screen.getByLabelText("Mapping 1 match value"), { target: { value: "b" } }); + fireEvent.change(screen.getByLabelText("Mapping 1 tag"), { target: { value: "sales" } }); + expect(screen.getByText("entrypoint=b → sales")).toBeInTheDocument(); + expect(changed).toHaveBeenLastCalledWith([{ header: "baggage", key: "entrypoint", value: "b", tag: "sales" }]); + }); + + it("changes an exact mapping to any-value mode and removes its exact match fields", async () => { + const changed = vi.fn(); + render(); + await userEvent.click(screen.getByRole("combobox", { name: "Mapping 1 mode" })); + await userEvent.click(await screen.findByRole("option", { name: "Any value" })); + expect(screen.queryByLabelText("Mapping 1 match value")).not.toBeInTheDocument(); + expect(screen.getByLabelText("Mapping 1 tag prefix")).toHaveValue(""); + expect(screen.getByLabelText("Mapping 1 tag prefix")).toHaveAttribute("placeholder", "usecase:"); + expect(changed).toHaveBeenLastCalledWith([ + expect.objectContaining({ value: undefined, tag: undefined, tag_prefix: "" }), + ]); + }); + + it("blocks saving a new mapping until its match value and tag are filled in", async () => { + const saved = vi.fn(); + render(); + await userEvent.click(screen.getByRole("button", { name: "Add mapping" })); + expect(screen.getByLabelText("Mapping 1 baggage key")).toHaveValue(""); + expect(screen.getByLabelText("Mapping 1 baggage key")).toHaveAttribute("placeholder", "entrypoint"); + expect(screen.getByText("Enter a baggage key")).toBeInTheDocument(); + fireEvent.change(screen.getByLabelText("Mapping 1 baggage key"), { target: { value: "entrypoint" } }); + expect(screen.getByText("Enter a match value")).toBeInTheDocument(); + await userEvent.click(screen.getByRole("button", { name: "Update" })); + fireEvent.change(screen.getByLabelText("Mapping 1 match value"), { target: { value: "b" } }); + expect(screen.getByText("Enter a tag")).toBeInTheDocument(); + await userEvent.click(screen.getByRole("button", { name: "Update" })); + expect(saved).not.toHaveBeenCalled(); + fireEvent.change(screen.getByLabelText("Mapping 1 tag"), { target: { value: "sales" } }); + expect(screen.queryByText(/^Enter a/)).not.toBeInTheDocument(); + await userEvent.click(screen.getByRole("button", { name: "Update" })); + expect(saved).toHaveBeenCalledWith([{ header: "baggage", key: "entrypoint", value: "b", tag: "sales" }]); + }); + + it("blocks saving an any-value mapping until the admin types a tag prefix", async () => { + const saved = vi.fn(); + render(); + await userEvent.click(screen.getByRole("combobox", { name: "Mapping 1 mode" })); + await userEvent.click(await screen.findByRole("option", { name: "Any value" })); + expect(screen.getByText("Enter a tag prefix")).toBeInTheDocument(); + expect(screen.getByRole("button", { name: "Update" })).toBeDisabled(); + fireEvent.change(screen.getByLabelText("Mapping 1 tag prefix"), { target: { value: "team:" } }); + await userEvent.click(screen.getByRole("button", { name: "Update" })); + expect(saved).toHaveBeenCalledWith([expect.objectContaining({ key: "entrypoint", tag_prefix: "team:" })]); + }); + + it("blocks saving a baggage key that is empty or not a header token", async () => { + render(); + fireEvent.change(screen.getByLabelText("Mapping 1 baggage key"), { target: { value: "" } }); + expect(screen.getByText("Enter a baggage key")).toBeInTheDocument(); + expect(screen.getByRole("button", { name: "Update" })).toBeDisabled(); + fireEvent.change(screen.getByLabelText("Mapping 1 baggage key"), { target: { value: "entry point" } }); + expect(screen.getByText(/Use only letters, digits/)).toBeInTheDocument(); + expect(screen.getByRole("button", { name: "Update" })).toBeDisabled(); + fireEvent.change(screen.getByLabelText("Mapping 1 baggage key"), { target: { value: "entry.point" } }); + expect(screen.getByRole("button", { name: "Update" })).toBeEnabled(); + }); + + it("blocks saving a second mapping for the same key and value until it differs", () => { + render(); + expect(screen.getByText("Another mapping already matches this key and value")).toBeInTheDocument(); + expect(screen.getByRole("button", { name: "Update" })).toBeDisabled(); + fireEvent.change(screen.getByLabelText("Mapping 2 match value"), { target: { value: "b" } }); + expect(screen.queryByText("Another mapping already matches this key and value")).not.toBeInTheDocument(); + expect(screen.getByRole("button", { name: "Update" })).toBeEnabled(); + }); + + it("blocks saving a second any-value mapping for the same key", () => { + render(); + expect(screen.getByText("Another mapping already matches this key and value")).toBeInTheDocument(); + expect(screen.getByRole("button", { name: "Update" })).toBeDisabled(); + }); + + it("deletes one rule while keeping the other mode intact", async () => { + const changed = vi.fn(); + render(); + await userEvent.click(screen.getByRole("button", { name: "Delete mapping 1" })); + expect(screen.getByLabelText("Mapping 1 tag prefix")).toHaveValue("usecase:"); + expect(changed).toHaveBeenLastCalledWith([variable]); + }); +}); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/router-settings/_components/RequestTagMappings.tsx b/ui/litellm-dashboard/src/app/(dashboard)/router-settings/_components/RequestTagMappings.tsx new file mode 100644 index 00000000000..d1101eaaf27 --- /dev/null +++ b/ui/litellm-dashboard/src/app/(dashboard)/router-settings/_components/RequestTagMappings.tsx @@ -0,0 +1,189 @@ +import { Button } from "@/components/ui/button"; +import { Input } from "@/components/ui/input"; +import { Select, SelectContent, SelectItem, SelectTrigger, SelectValue } from "@/components/ui/select"; +import { Switch } from "@/components/ui/switch"; +import { Trash2 } from "lucide-react"; + +export interface RequestTagMapping { + header: "baggage"; + key: string; + value?: string | null; + tag?: string | null; + tag_prefix?: string | null; + required?: boolean; + require_budgeted_tag?: boolean; +} + +interface Props { + value: unknown; + disabled?: boolean; + onChange: (rules: RequestTagMapping[]) => void; +} + +const isMapping = (value: unknown): value is RequestTagMapping => { + if (typeof value !== "object" || value === null) return false; + return "key" in value && typeof value.key === "string"; +}; + +const MODES = [ + { value: "exact", label: "Exact value" }, + { value: "any", label: "Any value" }, +]; + +const BAGGAGE_KEY_PATTERN = /^[!#$%&'*+\-.^_`|~0-9A-Za-z]+$/; + +const isExact = (rule: RequestTagMapping) => rule.value !== undefined && rule.value !== null; + +const mappingProblem = (rule: RequestTagMapping): string | null => { + if (!rule.key) return "Enter a baggage key"; + if (!BAGGAGE_KEY_PATTERN.test(rule.key)) return "Use only letters, digits, and !#$%&'*+-.^_`|~ in the baggage key"; + if (isExact(rule)) { + if (!rule.value) return "Enter a match value"; + return rule.tag ? null : "Enter a tag"; + } + return rule.tag_prefix ? null : "Enter a tag prefix"; +}; + +const matchIdentity = (rule: RequestTagMapping) => JSON.stringify([rule.key, isExact(rule) ? rule.value : null]); + +const problemAt = (rules: RequestTagMapping[], index: number): string | null => { + const identity = matchIdentity(rules[index]); + const duplicated = rules.slice(0, index).some((earlier) => matchIdentity(earlier) === identity); + return mappingProblem(rules[index]) ?? (duplicated ? "Another mapping already matches this key and value" : null); +}; + +export const requestTagMappingsAreValid = (value: unknown) => + Array.isArray(value) && value.every(isMapping) && value.every((_, index) => problemAt(value, index) === null); + +export function RequestTagMappingsEditor({ value, onChange, disabled = false }: Props) { + const rules = Array.isArray(value) ? value.filter(isMapping) : []; + const update = (index: number, patch: Partial) => + onChange(rules.map((rule, position) => (position === index ? { ...rule, ...patch } : rule))); + + return ( +
+

+ Exact value mappings take priority over any-value rules for the same key. +

+ {rules.map((rule, index) => { + const exact = isExact(rule); + const problem = problemAt(rules, index); + const label = `Mapping ${index + 1}`; + return ( +
+ {label} +
+ + +
+ + {exact ? ( + <> + + +

+ {rule.key}={rule.value || "value"} → {rule.tag || "tag"} +

+ + ) : ( + <> + +

+ {rule.key}=x → {rule.tag_prefix}x +

+ + )} + {problem ?

{problem}

: null} + + +
+ ); + })} + {disabled ? ( +

Managed in config.yaml. Edit the YAML to change these rules.

+ ) : null} + +
+ ); +} diff --git a/ui/litellm-dashboard/src/app/(dashboard)/router-settings/_components/general_settings.integration.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/router-settings/_components/general_settings.integration.test.tsx index cf5cad564ea..35434830d98 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/router-settings/_components/general_settings.integration.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/router-settings/_components/general_settings.integration.test.tsx @@ -253,3 +253,33 @@ it("should delete only the Default setting and retain explicit false and zero", ["token", "synthetic_count", 0], ]); }); + +it("keeps a new baggage mapping unsaved until every field the backend requires is filled in", async () => { + vi.mocked(getGeneralSettingsCall).mockResolvedValue([ + { + field_name: "request_tag_mappings", + field_type: "List", + field_value: [], + field_description: "baggage mappings", + stored_in_db: true, + editable: true, + }, + ]); + vi.mocked(updateConfigFieldSetting).mockClear(); + const user = userEvent.setup(); + renderWithProviders(); + await user.click(screen.getByRole("tab", { name: "General" })); + await user.click(await screen.findByRole("button", { name: "Add mapping" })); + const update = within(screen.getByRole("row", { name: /request_tag_mappings/ })).getByRole("button", { + name: "Update", + }); + expect(update).toBeDisabled(); + fireEvent.change(screen.getByLabelText("Mapping 1 baggage key"), { target: { value: "entrypoint" } }); + fireEvent.change(screen.getByLabelText("Mapping 1 match value"), { target: { value: "a" } }); + expect(update).toBeDisabled(); + fireEvent.change(screen.getByLabelText("Mapping 1 tag"), { target: { value: "usecase:support" } }); + await user.click(update); + expect(vi.mocked(updateConfigFieldSetting).mock.calls).toEqual([ + ["token", "request_tag_mappings", [{ header: "baggage", key: "entrypoint", value: "a", tag: "usecase:support" }]], + ]); +}); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/router-settings/_components/general_settings.tsx b/ui/litellm-dashboard/src/app/(dashboard)/router-settings/_components/general_settings.tsx index 3d0a2e438ac..5d28adb7ef3 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/router-settings/_components/general_settings.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/router-settings/_components/general_settings.tsx @@ -14,6 +14,7 @@ import { StatusBadge } from "@/components/shared/table_cells"; import RouterSettings from "@/components/router_settings"; import Fallbacks from "@/components/Settings/RouterSettings/Fallbacks/Fallbacks"; import RoutingGroups from "@/components/routing_groups"; +import { RequestTagMappingsEditor, requestTagMappingsAreValid } from "./RequestTagMappings"; const PROMPT_CACHING_TAB = "prompt_caching"; const ENABLE_ANTHROPIC_PROMPT_CACHING = "enable_anthropic_prompt_caching"; @@ -34,6 +35,7 @@ export interface generalSettingsItem { field_value: any; field_description: string; stored_in_db: boolean | null; + editable?: boolean; field_options?: string[] | null; field_tab?: string | null; field_default_value?: any; @@ -57,6 +59,15 @@ const SettingValueEditor: React.FC<{ setting: generalSettingsItem; onChange: (fieldName: string, newValue: any) => void; }> = ({ setting, onChange }) => { + if (setting.field_name === "request_tag_mappings") { + return ( + onChange(setting.field_name, rules)} + /> + ); + } if (setting.field_type === "Integer") { return ( = ({ accessToken, user setGeneralSettings(updatedSettings); }; - const handleUpdateField = (fieldName: string) => { + const handleUpdateField = async (fieldName: string) => { if (!accessToken) { return; } @@ -253,7 +264,7 @@ const GeneralSettings: React.FC = ({ accessToken, user return; } try { - updateConfigFieldSetting(accessToken, fieldName, fieldValue); + await updateConfigFieldSetting(accessToken, fieldName, fieldValue); // update value in state const updatedSettings = generalSettings.map((setting) => @@ -354,13 +365,23 @@ const GeneralSettings: React.FC = ({ accessToken, user )} - - handleResetField(value.field_name)} - className="inline-flex shrink-0 cursor-pointer items-center justify-center px-1.5 py-1.5 text-destructive" + + {value.field_name === "request_tag_mappings" && value.editable === false ? null : ( + handleResetField(value.field_name)} + className="inline-flex shrink-0 cursor-pointer items-center justify-center px-1.5 py-1.5 text-destructive" + > + + + )} ))} diff --git a/ui/litellm-dashboard/src/components/AIHub/modelUsageExample.test.ts b/ui/litellm-dashboard/src/components/AIHub/modelUsageExample.test.ts index 25d1b83ebe9..8591e6f82f8 100644 --- a/ui/litellm-dashboard/src/components/AIHub/modelUsageExample.test.ts +++ b/ui/litellm-dashboard/src/components/AIHub/modelUsageExample.test.ts @@ -21,6 +21,16 @@ describe("modelUsageExample", () => { ); }); + it("posts an extraction model to /v1/extraction with typed fields", () => { + const example = modelUsageExample("extraction", BASE_URL, "clairic", "X-Litellm-Key"); + expect(example).toContain('"https://proxy.example.com/v1/extraction"'); + expect(example).toContain('headers={"X-Litellm-Key": "Bearer your_api_key"}'); + expect(example).toContain('"model": "clairic"'); + expect(example).toContain('"fields": {'); + expect(example).not.toContain("chat.completions"); + expect(example).not.toContain("/v1/systemone"); + }); + it("keeps the chat completions example for every other mode", () => { for (const mode of ["chat", null, undefined]) { const example = modelUsageExample(mode, BASE_URL, "gpt-5.5", "Authorization"); @@ -28,6 +38,7 @@ describe("modelUsageExample", () => { expect(example).toContain('base_url="https://proxy.example.com"'); expect(example).toContain('model="gpt-5.5"'); expect(example).not.toContain("/v1/systemone"); + expect(example).not.toContain("/v1/extraction"); } }); diff --git a/ui/litellm-dashboard/src/components/AIHub/modelUsageExample.ts b/ui/litellm-dashboard/src/components/AIHub/modelUsageExample.ts index 2426ec09942..83f2af1e8c6 100644 --- a/ui/litellm-dashboard/src/components/AIHub/modelUsageExample.ts +++ b/ui/litellm-dashboard/src/components/AIHub/modelUsageExample.ts @@ -38,10 +38,33 @@ response = requests.post( print(response.json()["answers"])`; +const extractionExample = (baseUrl: string, model: string, keyHeaderName: string): string => `import requests + +response = requests.post( + ${JSON.stringify(`${baseUrl}/v1/extraction`)}, # Your LiteLLM Proxy URL + headers={${JSON.stringify(keyHeaderName)}: "Bearer your_api_key"}, + json={ + "model": ${JSON.stringify(model)}, + "state": "Invoice #4471 from Acme Tools. Total $174.00, due in 30 days.", + "fields": { + "vendor": {"type": "text", "instructions": "Who sent the invoice?"}, + "total": {"type": "number", "unit": "USD"} + } + } +) + +print(response.json()["answers"])`; + export const modelUsageExample = ( mode: string | null | undefined, baseUrl: string, model: string, keyHeaderName: string, -): string => - isDecisionMode(mode) ? systemOneExample(baseUrl, model, keyHeaderName) : chatCompletionsExample(baseUrl, model); +): string => { + if (mode === "extraction") { + return extractionExample(baseUrl, model, keyHeaderName); + } + return isDecisionMode(mode) + ? systemOneExample(baseUrl, model, keyHeaderName) + : chatCompletionsExample(baseUrl, model); +}; diff --git a/ui/litellm-dashboard/src/components/add_model/AddModelForm.integration.test.tsx b/ui/litellm-dashboard/src/components/add_model/AddModelForm.integration.test.tsx index cdc681a1c91..a95d9ffbfb8 100644 --- a/ui/litellm-dashboard/src/components/add_model/AddModelForm.integration.test.tsx +++ b/ui/litellm-dashboard/src/components/add_model/AddModelForm.integration.test.tsx @@ -465,7 +465,7 @@ describe("AddModelForm", () => { expect(await screen.findByRole("button", { name: "Add Model" })).toBeInTheDocument(); }); - it("offers the Decisions mode", async () => { + it.each(["Decisions - /v1/decisions", "Extraction - /v1/extraction"])("offers the %s mode", async (option) => { const mockUseAuthorized = vi.mocked(await import("@/app/(dashboard)/hooks/useAuthorized")); mockUseAuthorized.default.mockReturnValue(mockAuthorizedUser("proxy_admin", "user-1", true)); @@ -474,7 +474,7 @@ describe("AddModelForm", () => { await screen.findByText("Provider"); await userEvent.click(screen.getByRole("combobox", { name: "Mode" })); - expect(await screen.findByRole("option", { name: "Decisions - /v1/decisions", exact: true })).toBeInTheDocument(); + expect(await screen.findByRole("option", { name: option, exact: true })).toBeInTheDocument(); }); it("shows only the Close button in the connection test dialog footer", async () => { diff --git a/ui/litellm-dashboard/src/components/add_model/add_model_modes.tsx b/ui/litellm-dashboard/src/components/add_model/add_model_modes.tsx index 45ffe969a21..63def76db8f 100644 --- a/ui/litellm-dashboard/src/components/add_model/add_model_modes.tsx +++ b/ui/litellm-dashboard/src/components/add_model/add_model_modes.tsx @@ -14,6 +14,7 @@ export const TEST_MODES = [ { value: "anthropic_messages", label: "Anthropic Messages - /v1/messages" }, { value: "ocr", label: "OCR - /ocr" }, { value: "decisions", label: "Decisions - /v1/decisions" }, + { value: "extraction", label: "Extraction - /v1/extraction" }, ]; // Define the available auto router routing strategies diff --git a/ui/litellm-dashboard/src/components/add_model/provider_auth_types.test.ts b/ui/litellm-dashboard/src/components/add_model/provider_auth_types.test.ts index 5467ff0085a..f0b739b877d 100644 --- a/ui/litellm-dashboard/src/components/add_model/provider_auth_types.test.ts +++ b/ui/litellm-dashboard/src/components/add_model/provider_auth_types.test.ts @@ -28,6 +28,7 @@ describe("provider auth types", () => { "token_exchange_audience", "api_key", ]); + expect(authTypeFieldKeys("GITHUB_COPILOT")).toContain("github_copilot_host"); }); it("infers auth types from required fields and falls back when only optional defaults are present", () => { @@ -85,6 +86,9 @@ describe("provider auth types", () => { expect(inferAuthTypeId(authTypes, { api_key: "" })).toBe("shared_device_login"); expect(inferAuthTypeId(authTypes, { github_copilot_auth_type: "per_user_oauth" })).toBe("per_user_oauth"); expect(hiddenAuthFieldKeys(authTypes, "per_user_oauth")).toEqual(["api_base", "api_key"]); - expect(hiddenAuthFieldKeys(authTypes, "shared_device_login")).toEqual(["github_copilot_auth_type"]); + expect(hiddenAuthFieldKeys(authTypes, "shared_device_login")).toEqual([ + "github_copilot_auth_type", + "github_copilot_host", + ]); }); }); diff --git a/ui/litellm-dashboard/src/components/add_model/provider_auth_types.ts b/ui/litellm-dashboard/src/components/add_model/provider_auth_types.ts index 6fe54955133..0bf98407bfa 100644 --- a/ui/litellm-dashboard/src/components/add_model/provider_auth_types.ts +++ b/ui/litellm-dashboard/src/components/add_model/provider_auth_types.ts @@ -13,6 +13,7 @@ export interface ProviderAuthType { const EMPTY_PROVIDER_AUTH_TYPES: readonly ProviderAuthType[] = []; export const GITHUB_COPILOT_AUTH_TYPE_KEY = "github_copilot_auth_type"; +export const GITHUB_COPILOT_HOST_KEY = "github_copilot_host"; export const GITHUB_COPILOT_PER_USER_AUTH_TYPE = "per_user_oauth"; export const PROVIDER_AUTH_TYPES: Partial> = { @@ -31,7 +32,7 @@ export const PROVIDER_AUTH_TYPES: Partial { credential_fields: [ { key: "api_base", label: "API Base", field_type: "text" }, { key: "api_key", label: "API Key", field_type: "password" }, + { + key: "github_copilot_host", + label: "GitHub host", + placeholder: "github.com", + tooltip: "Leave empty for github.com. For GHE.com data residency enter your SUBDOMAIN.ghe.com host", + field_type: "text", + }, ], }, ]), @@ -532,7 +539,7 @@ describe("CredentialModal with Anthropic workload identity federation", () => { describe("CredentialModal with GitHub Copilot auth types", () => { const perUserCopilotCredential: CredentialItem = { credential_name: "copilot-per-user", - credential_values: { github_copilot_auth_type: "per_user_oauth" }, + credential_values: { github_copilot_auth_type: "per_user_oauth", github_copilot_host: "octo.ghe.com" }, credential_info: { custom_llm_provider: "GITHUB_COPILOT" }, }; @@ -577,6 +584,7 @@ describe("CredentialModal with GitHub Copilot auth types", () => { const onSubmit = renderModal({ mode: "edit", existingCredential: perUserCopilotCredential }); expect(await screen.findByRole("combobox", { name: "Auth Type:" })).toHaveTextContent("Per-user GitHub OAuth"); + expect(screen.getByLabelText("GitHub host")).toHaveValue("octo.ghe.com"); await chooseOption(user, /^Auth Type:/, "Shared device login"); await user.click(screen.getByRole("button", { name: "Update Credential" })); @@ -586,7 +594,7 @@ describe("CredentialModal with GitHub Copilot auth types", () => { custom_llm_provider: "GITHUB_COPILOT", credential_values: {}, }); - expect(valuesToDelete).toEqual(["github_copilot_auth_type"]); + expect([...valuesToDelete].sort()).toEqual(["github_copilot_auth_type", "github_copilot_host"]); }); }); diff --git a/ui/litellm-dashboard/src/components/model_add/GithubCopilotConnectModal.integration.test.tsx b/ui/litellm-dashboard/src/components/model_add/GithubCopilotConnectModal.integration.test.tsx index 963ebab81d3..42f30db08a8 100644 --- a/ui/litellm-dashboard/src/components/model_add/GithubCopilotConnectModal.integration.test.tsx +++ b/ui/litellm-dashboard/src/components/model_add/GithubCopilotConnectModal.integration.test.tsx @@ -79,6 +79,18 @@ describe("GithubCopilotConnectModal", () => { expect(props.onDisconnect).toHaveBeenCalledTimes(1); }); + it("uses the GHE verification URI returned by the start response", async () => { + const verificationUri = "https://octo.ghe.com/login/device"; + networking.userConnectionStartCall.mockResolvedValue({ + ...START_RESPONSE, + verification_uri: verificationUri, + }); + renderModal(); + await advance(0); + + expect(screen.getByRole("link", { name: verificationUri })).toHaveAttribute("href", verificationUri); + }); + it("stops polling and offers a restart when the device code expires", async () => { networking.userConnectionStartCall.mockResolvedValue({ ...START_RESPONSE, expires_in: 12 }); networking.userConnectionPollCall.mockResolvedValue({ status: "pending" }); diff --git a/ui/litellm-dashboard/src/components/model_add/github_copilot_connect_flow.test.ts b/ui/litellm-dashboard/src/components/model_add/github_copilot_connect_flow.test.ts index 72c2e783adf..9645839bbb4 100644 --- a/ui/litellm-dashboard/src/components/model_add/github_copilot_connect_flow.test.ts +++ b/ui/litellm-dashboard/src/components/model_add/github_copilot_connect_flow.test.ts @@ -30,11 +30,29 @@ describe("connectFlowReducer", () => { expect(started()).toEqual(expected); }); - it("never links anywhere but github.com", () => { + it("falls back for an untrusted verification host", () => { const state = started("https://evil.example/login/device"); expect(state.kind === "awaiting" && state.verificationUri).toBe("https://github.com/login/device"); }); + it("preserves a single-label GHE.com verification URL", () => { + const uri = "https://octo.ghe.com/login/device"; + const state = started(uri); + expect(state.kind === "awaiting" && state.verificationUri).toBe(uri); + }); + + it.each([ + "http://octo.ghe.com/login/device", + "https://a.b.ghe.com/login/device", + "https://octo.ghe.com.evil.example/login/device", + "https://user@octo.ghe.com/login/device", + "https://octo.ghe.com:8443/login/device", + "not a url", + ])("falls back for unsafe verification URL %s", (uri) => { + const state = started(uri); + expect(state.kind === "awaiting" && state.verificationUri).toBe("https://github.com/login/device"); + }); + it("keeps waiting on pending and slows down by the server interval or by five seconds", () => { const pending = connectFlowReducer(started(), { type: "polled", response: { status: "pending" } }); expect(pending).toMatchObject({ kind: "awaiting", pollCount: 1, intervalSeconds: 5 }); diff --git a/ui/litellm-dashboard/src/components/model_add/github_copilot_connect_flow.ts b/ui/litellm-dashboard/src/components/model_add/github_copilot_connect_flow.ts index 0e38fc91bb1..6f0e76f9aaf 100644 --- a/ui/litellm-dashboard/src/components/model_add/github_copilot_connect_flow.ts +++ b/ui/litellm-dashboard/src/components/model_add/github_copilot_connect_flow.ts @@ -34,8 +34,22 @@ export type ConnectFlowEvent = export const initialConnectFlowState: ConnectFlowState = { kind: "starting", attempt: 0 }; -const safeVerificationUri = (uri: string): string => - uri.startsWith("https://github.com/") ? uri : GITHUB_DEVICE_LOGIN_URL; +const safeVerificationUri = (uri: string): string => { + try { + const url = new URL(uri); + const usesHttps = url.protocol === "https:"; + const hasCredentials = url.username !== "" || url.password !== ""; + const hasNoPort = url.port === ""; + const hostIsAllowed = + url.hostname === "github.com" || /^[a-z0-9](?:[a-z0-9-]{0,61}[a-z0-9])?\.ghe\.com$/.test(url.hostname); + const urlHasAllowedAuthority = !hasCredentials && hasNoPort && hostIsAllowed; + const isSafeUrl = usesHttps && urlHasAllowedAuthority; + + return isSafeUrl ? uri : GITHUB_DEVICE_LOGIN_URL; + } catch { + return GITHUB_DEVICE_LOGIN_URL; + } +}; const afterPoll = ( state: Extract, diff --git a/ui/litellm-dashboard/src/components/team/TeamInfo.integration.test.tsx b/ui/litellm-dashboard/src/components/team/TeamInfo.integration.test.tsx index 7f567a7f936..fc054e51e5b 100644 --- a/ui/litellm-dashboard/src/components/team/TeamInfo.integration.test.tsx +++ b/ui/litellm-dashboard/src/components/team/TeamInfo.integration.test.tsx @@ -816,3 +816,44 @@ describe("TeamInfoView - member budget reset prompt", () => { expect(screen.getByRole("option", { name: "claude-haiku-4-5" })).toBeInTheDocument(); }); }); + +describe("TeamInfoView - model rate limit picker", () => { + const props = { + teamId: "123", + onUpdate: vi.fn(), + onClose: vi.fn(), + accessToken: "test-token", + is_team_admin: true, + is_proxy_admin: true, + editTeam: false, + }; + + beforeEach(() => { + seedDefaultMocks(); + }); + + afterEach(() => { + vi.clearAllMocks(); + }); + + it("offers access-group models, not no-default-models, in the model rate limit picker", async () => { + const user = userEvent.setup({ delay: null }); + vi.mocked(networking.teamInfoCall).mockResolvedValue( + createMockTeamData({ + models: ["no-default-models"], + access_group_models: ["claude-haiku-4-5"], + }) as TeamData, + ); + + renderWithProviders(); + await waitFor(() => expect(screen.queryAllByText("Test Team").length).toBeGreaterThan(0)); + await user.click(screen.getByRole("tab", { name: "Settings" })); + await user.click(await screen.findByRole("button", { name: /edit settings/i })); + await user.click(screen.getByRole("button", { name: /add model limit/i })); + await user.click(screen.getByPlaceholderText("Select model")); + + expect(await screen.findByRole("option", { name: "claude-haiku-4-5" })).toBeInTheDocument(); + expect(screen.queryByRole("option", { name: "no-default-models" })).not.toBeInTheDocument(); + expect(screen.queryByRole("option", { name: "gpt-4o" })).not.toBeInTheDocument(); + }); +}); diff --git a/ui/litellm-dashboard/src/components/team/TeamInfo.tsx b/ui/litellm-dashboard/src/components/team/TeamInfo.tsx index 29c048034f4..0d63f5d0833 100644 --- a/ui/litellm-dashboard/src/components/team/TeamInfo.tsx +++ b/ui/litellm-dashboard/src/components/team/TeamInfo.tsx @@ -75,6 +75,7 @@ import { computeTeamModelBadges, normalizeTeamModelSelection, TeamAccessGroupModelGrant, + teamPerModelLimitOptions, TeamModelBadge, TeamModelBadgeKind, } from "./teamModelAccess"; @@ -89,7 +90,6 @@ import ModelAliasManager from "../common_components/ModelAliasManager"; import AgentSelector from "../agent_management/AgentSelector"; import DeleteResourceModal from "../common_components/DeleteResourceModal"; import PassThroughRoutesSelector from "../common_components/PassThroughRoutesSelector"; -import { unfurlWildcardModelsInList } from "../key_team_helpers/fetch_available_models_team_key"; import GuardrailSettingsView from "../GuardrailSettingsView"; import LoggingSettingsView from "../logging_settings_view"; import MCPServerSelector from "../mcp_server_management/MCPServerSelector"; @@ -666,20 +666,9 @@ const TeamInfoView: React.FC = ({ [mcpServersLoading || mcpToolsetsLoading || accessGroupsLoading, "the MCP server inventory is still loading"], ] as const ).find(([failed]) => failed)?.[1] ?? null; - const availableRateLimitModels = useMemo(() => { + const perModelLimitModels = useMemo(() => { const selected = (isEditing ? watchedModels : undefined) ?? teamData?.team_info?.models ?? []; - if (selected.includes("all-proxy-models") || selected.includes("all-team-models")) { - return userModels; - } - return unfurlWildcardModelsInList(selected, userModels); - }, [isEditing, watchedModels, teamData, userModels]); - const availableModelBudgetModels = useMemo(() => { - const selected = (isEditing ? watchedModels : undefined) ?? teamData?.team_info?.models ?? []; - if (selected.length === 0 || selected.includes("all-proxy-models") || selected.includes("all-team-models")) { - return userModels; - } - const granted = [...selected, ...(teamData?.team_info?.access_group_models ?? [])]; - return unfurlWildcardModelsInList(Array.from(new Set(granted)), userModels); + return teamPerModelLimitOptions(selected, teamData?.team_info?.access_group_models ?? [], userModels); }, [isEditing, watchedModels, teamData, userModels]); const teamEditAccess = useMemo(() => parseTeamEditAccess(teamData?.team_info?.caller_edit_access), [teamData]); @@ -1724,7 +1713,7 @@ const TeamInfoView: React.FC = ({ premiumUser={premiumUser} value={teamMemberModelMaxBudget} onChange={setTeamMemberModelMaxBudget} - availableModels={availableModelBudgetModels} + availableModels={perModelLimitModels} hint="Set a default per-model spend cap for each team member, with an independent reset window." /> = ({ premiumUser={premiumUser} value={teamModelMaxBudget} onChange={setTeamModelMaxBudget} - availableModels={availableRateLimitModels} + availableModels={perModelLimitModels} usage={info.model_max_budget_usage} hint="Cap this team's spend on individual models, each with its own reset window. Every key on the team shares the cap unless the key sets its own budget for that model." /> @@ -1906,7 +1895,7 @@ const TeamInfoView: React.FC = ({ inputId={id} value={value ?? ""} onValueChange={onChange} - options={availableRateLimitModels.map((model) => ({ + options={perModelLimitModels.map((model) => ({ label: model, value: model, }))} @@ -2644,7 +2633,7 @@ const TeamInfoView: React.FC = ({ ), type: "model-max-budget" as const, - availableModels: availableModelBudgetModels, + availableModels: perModelLimitModels, premiumUser, }, { diff --git a/ui/litellm-dashboard/src/components/team/teamModelAccess.test.ts b/ui/litellm-dashboard/src/components/team/teamModelAccess.test.ts index 3f0b4e20407..5ca42a9391b 100644 --- a/ui/litellm-dashboard/src/components/team/teamModelAccess.test.ts +++ b/ui/litellm-dashboard/src/components/team/teamModelAccess.test.ts @@ -1,5 +1,10 @@ import { describe, expect, it } from "vitest"; -import { computeTeamModelBadges, normalizeTeamModelSelection, TeamAccessGroupModelGrant } from "./teamModelAccess"; +import { + computeTeamModelBadges, + normalizeTeamModelSelection, + TeamAccessGroupModelGrant, + teamPerModelLimitOptions, +} from "./teamModelAccess"; const GRANTS: TeamAccessGroupModelGrant[] = [ { access_group_id: "ag-1", access_group_name: "shared", models: ["haiku", "gpt-4o-mini"] }, @@ -84,3 +89,35 @@ describe("computeTeamModelBadges", () => { ]); }); }); + +describe("teamPerModelLimitOptions", () => { + const USER_MODELS = ["gpt-4o", "haiku", "openai/gpt-4o-mini", "openai/gpt-4.1"]; + + it("offers access-group models, not the sentinel, for a no-default-models team", () => { + expect(teamPerModelLimitOptions(["no-default-models"], ["gpt-4o", "haiku"], USER_MODELS)).toEqual([ + "gpt-4o", + "haiku", + ]); + }); + + it("merges direct and access-group models without duplicates", () => { + expect(teamPerModelLimitOptions(["gpt-4o"], ["gpt-4o", "haiku"], USER_MODELS)).toEqual(["gpt-4o", "haiku"]); + }); + + it("offers every user model when the team covers all models", () => { + expect(teamPerModelLimitOptions([], [], USER_MODELS)).toEqual(USER_MODELS); + expect(teamPerModelLimitOptions(["all-proxy-models"], [], USER_MODELS)).toEqual(USER_MODELS); + expect(teamPerModelLimitOptions(["all-team-models"], [], USER_MODELS)).toEqual(USER_MODELS); + }); + + it("expands wildcards to concrete names and drops the pattern itself", () => { + expect(teamPerModelLimitOptions(["no-default-models"], ["openai/*"], USER_MODELS)).toEqual([ + "openai/gpt-4o-mini", + "openai/gpt-4.1", + ]); + }); + + it("offers nothing when the team has no models it can call", () => { + expect(teamPerModelLimitOptions(["no-default-models"], [], USER_MODELS)).toEqual([]); + }); +}); diff --git a/ui/litellm-dashboard/src/components/team/teamModelAccess.ts b/ui/litellm-dashboard/src/components/team/teamModelAccess.ts index d5d9245ed51..3027fbb8686 100644 --- a/ui/litellm-dashboard/src/components/team/teamModelAccess.ts +++ b/ui/litellm-dashboard/src/components/team/teamModelAccess.ts @@ -1,3 +1,5 @@ +import { unfurlWildcardModelsInList } from "../key_team_helpers/fetch_available_models_team_key"; + export const ALL_PROXY_MODELS = "all-proxy-models"; export const NO_DEFAULT_MODELS = "no-default-models"; @@ -18,6 +20,24 @@ export interface TeamModelBadge { tooltip: string; } +const ALL_TEAM_MODELS = "all-team-models"; +const MODEL_SENTINELS: ReadonlySet = new Set([ALL_PROXY_MODELS, ALL_TEAM_MODELS, NO_DEFAULT_MODELS]); + +// Per-model rate limits and budgets are enforced on the model name a request sends, +// so only concrete names are offered: sentinels and wildcard patterns never match one. +export function teamPerModelLimitOptions( + teamModels: string[], + accessGroupModels: string[], + userModels: string[], +): string[] { + const coversAllModels = + teamModels.length === 0 || teamModels.includes(ALL_PROXY_MODELS) || teamModels.includes(ALL_TEAM_MODELS); + const granted = coversAllModels ? userModels : [...new Set([...teamModels, ...accessGroupModels])]; + return unfurlWildcardModelsInList(granted, userModels).filter( + (model) => !MODEL_SENTINELS.has(model) && !model.endsWith("*"), + ); +} + export function normalizeTeamModelSelection(models: string[] | undefined): string[] { return models && models.length > 0 ? models : [NO_DEFAULT_MODELS]; } diff --git a/ui/litellm-dashboard/src/lib/http/schema.d.ts b/ui/litellm-dashboard/src/lib/http/schema.d.ts index bf2fe4300a3..244141ec076 100644 --- a/ui/litellm-dashboard/src/lib/http/schema.d.ts +++ b/ui/litellm-dashboard/src/lib/http/schema.d.ts @@ -5333,6 +5333,39 @@ export interface paths { patch: operations["assemblyai_proxy_route_eu_assemblyai__endpoint__patch"]; trace?: never; }; + "/extraction": { + parameters: { + query?: never; + header?: never; + path?: never; + cookie?: never; + }; + get?: never; + put?: never; + /** + * Extract typed fields from a state + * @description Read a `state` text and up to 4 images and get one typed answer per named field in `fields`. + * + * Field types are `text`, `number`, `date`, `time`, `datetime`, `duration`, `list` (set `items`), `estimate` + * (set `min` and `max`) and `forecast` (set `min`, `max` and `horizon`). Each answer carries its `value`, which is + * null when the input does not determine it, plus `confidence`, `p_null`, text `span`s into the state and, for + * estimates, `mean`, `median`, `p10` and `p90`. Images are data URLs or `{content_type, base64}` objects, remote + * URLs are not accepted. An unknown field type, a field name that is not 1 to 64 letters, digits, `_`, `.` or `-` + * starting with a letter or `_`, a remote image URL or more than 4 images is rejected with a 400 before any + * provider is called. Any other top-level key, `stream: true` and OpenAI generation settings such as `temperature` + * included, is rejected with a 400 naming it unless `drop_params` or the deployment's `additional_drop_params` + * drops it. Settings inside `fields` and `options` go to the provider as sent, so a field missing a setting its + * type needs or an empty `state` with no images comes back with the provider's own error. `model` is any + * extraction model in the proxy model list, such as Cloudflare Clairic. The request and the answers keep the + * provider's format. + */ + post: operations["extraction_extraction_post"]; + delete?: never; + options?: never; + head?: never; + patch?: never; + trace?: never; + }; "/fal_ai/{endpoint}": { parameters: { query?: never; @@ -20204,6 +20237,39 @@ export interface paths { patch?: never; trace?: never; }; + "/v1/extraction": { + parameters: { + query?: never; + header?: never; + path?: never; + cookie?: never; + }; + get?: never; + put?: never; + /** + * Extract typed fields from a state + * @description Read a `state` text and up to 4 images and get one typed answer per named field in `fields`. + * + * Field types are `text`, `number`, `date`, `time`, `datetime`, `duration`, `list` (set `items`), `estimate` + * (set `min` and `max`) and `forecast` (set `min`, `max` and `horizon`). Each answer carries its `value`, which is + * null when the input does not determine it, plus `confidence`, `p_null`, text `span`s into the state and, for + * estimates, `mean`, `median`, `p10` and `p90`. Images are data URLs or `{content_type, base64}` objects, remote + * URLs are not accepted. An unknown field type, a field name that is not 1 to 64 letters, digits, `_`, `.` or `-` + * starting with a letter or `_`, a remote image URL or more than 4 images is rejected with a 400 before any + * provider is called. Any other top-level key, `stream: true` and OpenAI generation settings such as `temperature` + * included, is rejected with a 400 naming it unless `drop_params` or the deployment's `additional_drop_params` + * drops it. Settings inside `fields` and `options` go to the provider as sent, so a field missing a setting its + * type needs or an empty `state` with no images comes back with the provider's own error. `model` is any + * extraction model in the proxy model list, such as Cloudflare Clairic. The request and the answers keep the + * provider's format. + */ + post: operations["extraction_v1_extraction_post"]; + delete?: never; + options?: never; + head?: never; + patch?: never; + trace?: never; + }; "/v1/files": { parameters: { query?: never; @@ -27515,7 +27581,7 @@ export interface components { * Mode * @description The mode to test the model with. If not provided, resolved the way /health does: the deployment's model_info.mode (only while the request tests the deployment's own model), then the mode the provider requires for that model, then the model cost map. */ - mode?: ("chat" | "completion" | "embedding" | "audio_speech" | "audio_transcription" | "image_generation" | "image_edit" | "video_generation" | "batch" | "rerank" | "realtime" | "responses" | "anthropic_messages" | "ocr" | "evaluation" | "decisions") | null; + mode?: ("chat" | "completion" | "embedding" | "audio_speech" | "audio_transcription" | "image_generation" | "image_edit" | "video_generation" | "batch" | "rerank" | "realtime" | "responses" | "anthropic_messages" | "ocr" | "evaluation" | "decisions" | "extraction") | null; /** * Model Info * @description Model info for the health check @@ -28399,7 +28465,7 @@ export interface components { * CallTypes * @enum {string} */ - CallTypes: "embedding" | "aembedding" | "completion" | "acompletion" | "atext_completion" | "text_completion" | "image_generation" | "aimage_generation" | "image_edit" | "aimage_edit" | "moderation" | "amoderation" | "atranscription" | "transcription" | "aspeech" | "speech" | "rerank" | "arerank" | "search" | "asearch" | "decisions" | "adecisions" | "systemone" | "asystemone" | "_arealtime" | "_aresponses_websocket" | "create_batch" | "acreate_batch" | "aretrieve_batch" | "retrieve_batch" | "acancel_batch" | "cancel_batch" | "pass_through_endpoint" | "anthropic_messages" | "aanthropic_messages" | "get_assistants" | "aget_assistants" | "create_assistants" | "acreate_assistants" | "delete_assistant" | "adelete_assistant" | "acreate_thread" | "create_thread" | "aget_thread" | "get_thread" | "a_add_message" | "add_message" | "aget_messages" | "get_messages" | "arun_thread" | "run_thread" | "arun_thread_stream" | "run_thread_stream" | "afile_retrieve" | "file_retrieve" | "afile_delete" | "file_delete" | "afile_list" | "file_list" | "acreate_file" | "create_file" | "afile_content" | "file_content" | "create_fine_tuning_job" | "acreate_fine_tuning_job" | "create_video" | "acreate_video" | "video_generation" | "avideo_generation" | "avideo_retrieve" | "video_retrieve" | "avideo_content" | "video_content" | "video_remix" | "avideo_remix" | "video_list" | "avideo_list" | "video_retrieve_job" | "avideo_retrieve_job" | "video_delete" | "avideo_delete" | "video_create_character" | "avideo_create_character" | "video_get_character" | "avideo_get_character" | "video_edit" | "avideo_edit" | "video_extension" | "avideo_extension" | "vector_store_file_create" | "avector_store_file_create" | "vector_store_file_list" | "avector_store_file_list" | "vector_store_file_retrieve" | "avector_store_file_retrieve" | "vector_store_file_content" | "avector_store_file_content" | "vector_store_file_update" | "avector_store_file_update" | "vector_store_file_delete" | "avector_store_file_delete" | "vector_store_create" | "avector_store_create" | "vector_store_search" | "avector_store_search" | "ingest" | "aingest" | "query" | "aquery" | "create_interaction" | "acreate_interaction" | "create_container" | "acreate_container" | "list_containers" | "alist_containers" | "retrieve_container" | "aretrieve_container" | "delete_container" | "adelete_container" | "list_container_files" | "alist_container_files" | "upload_container_file" | "aupload_container_file" | "create_sandbox" | "acreate_sandbox" | "delete_sandbox" | "adelete_sandbox" | "run_code" | "arun_code" | "code_interpreter_tool" | "acode_interpreter_tool" | "acancel_fine_tuning_job" | "cancel_fine_tuning_job" | "alist_fine_tuning_jobs" | "list_fine_tuning_jobs" | "aretrieve_fine_tuning_job" | "retrieve_fine_tuning_job" | "responses" | "aresponses" | "alist_input_items" | "llm_passthrough_route" | "allm_passthrough_route" | "generate_content" | "agenerate_content" | "generate_content_stream" | "agenerate_content_stream" | "ocr" | "aocr" | "call_mcp_tool" | "list_mcp_tools" | "asend_message" | "send_message" | "acreate_skill"; + CallTypes: "embedding" | "aembedding" | "completion" | "acompletion" | "atext_completion" | "text_completion" | "image_generation" | "aimage_generation" | "image_edit" | "aimage_edit" | "moderation" | "amoderation" | "atranscription" | "transcription" | "aspeech" | "speech" | "rerank" | "arerank" | "search" | "asearch" | "decisions" | "adecisions" | "systemone" | "asystemone" | "extraction" | "aextraction" | "_arealtime" | "_aresponses_websocket" | "create_batch" | "acreate_batch" | "aretrieve_batch" | "retrieve_batch" | "acancel_batch" | "cancel_batch" | "pass_through_endpoint" | "anthropic_messages" | "aanthropic_messages" | "get_assistants" | "aget_assistants" | "create_assistants" | "acreate_assistants" | "delete_assistant" | "adelete_assistant" | "acreate_thread" | "create_thread" | "aget_thread" | "get_thread" | "a_add_message" | "add_message" | "aget_messages" | "get_messages" | "arun_thread" | "run_thread" | "arun_thread_stream" | "run_thread_stream" | "afile_retrieve" | "file_retrieve" | "afile_delete" | "file_delete" | "afile_list" | "file_list" | "acreate_file" | "create_file" | "afile_content" | "file_content" | "create_fine_tuning_job" | "acreate_fine_tuning_job" | "create_video" | "acreate_video" | "video_generation" | "avideo_generation" | "avideo_retrieve" | "video_retrieve" | "avideo_content" | "video_content" | "video_remix" | "avideo_remix" | "video_list" | "avideo_list" | "video_retrieve_job" | "avideo_retrieve_job" | "video_delete" | "avideo_delete" | "video_create_character" | "avideo_create_character" | "video_get_character" | "avideo_get_character" | "video_edit" | "avideo_edit" | "video_extension" | "avideo_extension" | "vector_store_file_create" | "avector_store_file_create" | "vector_store_file_list" | "avector_store_file_list" | "vector_store_file_retrieve" | "avector_store_file_retrieve" | "vector_store_file_content" | "avector_store_file_content" | "vector_store_file_update" | "avector_store_file_update" | "vector_store_file_delete" | "avector_store_file_delete" | "vector_store_create" | "avector_store_create" | "vector_store_search" | "avector_store_search" | "ingest" | "aingest" | "query" | "aquery" | "create_interaction" | "acreate_interaction" | "create_container" | "acreate_container" | "list_containers" | "alist_containers" | "retrieve_container" | "aretrieve_container" | "delete_container" | "adelete_container" | "list_container_files" | "alist_container_files" | "upload_container_file" | "aupload_container_file" | "create_sandbox" | "acreate_sandbox" | "delete_sandbox" | "adelete_sandbox" | "run_code" | "arun_code" | "code_interpreter_tool" | "acode_interpreter_tool" | "acancel_fine_tuning_job" | "cancel_fine_tuning_job" | "alist_fine_tuning_jobs" | "list_fine_tuning_jobs" | "aretrieve_fine_tuning_job" | "retrieve_fine_tuning_job" | "responses" | "aresponses" | "alist_input_items" | "llm_passthrough_route" | "allm_passthrough_route" | "generate_content" | "agenerate_content" | "generate_content_stream" | "agenerate_content_stream" | "ocr" | "aocr" | "call_mcp_tool" | "list_mcp_tools" | "asend_message" | "send_message" | "acreate_skill"; /** CallbackDelete */ CallbackDelete: { /** Callback Name */ @@ -30072,11 +30138,26 @@ export interface components { * @description Wall-clock budget for one spend log cleanup run (e.g. '5m'), shared across every table it prunes. A run that hits the budget stops and the next run resumes from where it left off. Defaults to '5m'. */ maximum_spend_logs_cleanup_run_budget?: string | null; + /** + * Maximum Spend Logs Cleanup Target Size + * @description Level a size-triggered cleanup run deletes down to (e.g. '20GB'). Must be below maximum_spend_logs_size. Unset means the run stops as soon as the tables are back under maximum_spend_logs_size. + */ + maximum_spend_logs_cleanup_target_size?: string | null; /** * Maximum Spend Logs Retention Period * @description Maximum retention period for spend logs (e.g., '7d' for 7 days). Logs older than this will be deleted. */ maximum_spend_logs_retention_period?: string | null; + /** + * Maximum Spend Logs Size + * @description Size rule for spend logs (e.g. '180GB'): when LiteLLM_SpendLogs plus LiteLLM_SpendLogToolIndex (heap, indexes and TOAST, measured with pg_total_relation_size) hold more live data than this, the cleanup job deletes the oldest spend logs first until they are under maximum_spend_logs_cleanup_target_size. Independent of maximum_spend_logs_retention_period: a row is deleted when either rule says so. Unset means no size rule. + */ + maximum_spend_logs_size?: string | null; + /** + * Maximum Spend Logs Size Check Interval + * @description How often the size rule is checked (e.g. '10m'). Defaults to '1d'. Ignored when maximum_spend_logs_cleanup_cron is set, which then drives both the age and the size cleanup. + */ + maximum_spend_logs_size_check_interval?: string | null; /** * Mcp Advertised Versions * @description MCP revisions enabled by the gateway. Defaults to all completed legacy revisions. Modern protocol serving requires explicit opt-in. Apps/Tasks remain disabled. @@ -30199,6 +30280,11 @@ export interface components { * @description When set to True, rejects requests that contain client-side 'metadata.tags' to prevent users from influencing budgets by sending different tags. Tags can only be inherited from the API key metadata. */ reject_clientside_metadata_tags?: boolean | null; + /** + * Request Tag Mappings + * @description Map W3C baggage values to request tags. Exact value/tag rules take precedence over tag_prefix fallbacks. + */ + request_tag_mappings?: components["schemas"]["RequestTagMapping"][] | null; /** * Responses Websocket Session Limit Seconds * @description Maximum lifetime in seconds of a Responses API WebSocket session, measured from connection accept and covering the idle wait for the first response.create frame. Defaults to 3600, matching OpenAI's documented 60-minute WebSocket connection limit. Must be between 60 and 7200 seconds. @@ -32183,6 +32269,69 @@ export interface components { * @enum {string} */ ExportType: "daily" | "daily_with_keys" | "daily_with_models" | "daily_with_users"; + /** ExtractionAnswer */ + ExtractionAnswer: { + /** Confidence */ + confidence?: number | null; + guess?: components["schemas"]["JsonValue"]; + mean?: components["schemas"]["JsonValue"]; + median?: components["schemas"]["JsonValue"]; + p10?: components["schemas"]["JsonValue"]; + p90?: components["schemas"]["JsonValue"]; + /** P Above */ + p_above?: number | null; + /** P Below */ + p_below?: number | null; + /** P Null */ + p_null?: number | null; + /** Quantiles */ + quantiles?: components["schemas"]["JsonValue"][] | null; + /** Span */ + span?: number[] | null; + /** Spans */ + spans?: number[][] | null; + /** Steps */ + steps?: components["schemas"]["JsonValue"][] | null; + /** Type */ + type: string; + /** @description The answer, null when the input does not determine it */ + value: components["schemas"]["JsonValue"]; + } & { + [key: string]: unknown; + }; + /** ExtractionResponse */ + ExtractionResponse: { + /** Answers */ + answers: { + [key: string]: components["schemas"]["ExtractionAnswer"]; + }; + /** Model */ + model: string; + /** State Text */ + state_text?: string | null; + /** Truncated */ + truncated: boolean; + usage: components["schemas"]["ExtractionUsage"]; + } & { + [key: string]: unknown; + }; + /** ExtractionUsage */ + ExtractionUsage: { + /** Image Tokens */ + image_tokens?: number | null; + /** Input Tokens */ + input_tokens: number; + /** Output Tokens */ + output_tokens: number; + /** Passes */ + passes?: number | null; + /** Schema Tokens */ + schema_tokens?: number | null; + /** State Tokens */ + state_tokens?: number | null; + } & { + [key: string]: unknown; + }; /** * FacetListResponse * @description The distinct values one column takes over a filtered query. `data` holds bare values, not entity rows. @@ -35028,6 +35177,8 @@ export interface components { aws_access_key_id?: string | null; /** Aws Batch Role Arn */ aws_batch_role_arn?: string | null; + /** Aws Bedrock Control Plane Endpoint */ + aws_bedrock_control_plane_endpoint?: string | null; /** Aws Bedrock Project Id */ aws_bedrock_project_id?: string | null; /** Aws Bedrock Runtime Endpoint */ @@ -42655,6 +42806,36 @@ export interface components { /** Status Code */ status_code: number; }; + /** + * RequestTagMapping + * @description An exact baggage value mapping, or a prefix for any value of a key. + */ + RequestTagMapping: { + /** + * Header + * @default baggage + * @constant + */ + header: "baggage"; + /** Key */ + key: string; + /** + * Require Budgeted Tag + * @default false + */ + require_budgeted_tag: boolean; + /** + * Required + * @default false + */ + required: boolean; + /** Tag */ + tag?: string | null; + /** Tag Prefix */ + tag_prefix?: string | null; + /** Value */ + value?: string | null; + }; /** * RequestType * @description Fixed v0 taxonomy. User-extensible types come in v1. @@ -50072,6 +50253,8 @@ export interface components { input_cost_per_token?: number | null; /** Internal Router Model */ internal_router_model?: boolean | null; + /** Max Embedding Batch Size */ + max_embedding_batch_size?: number | null; /** * Member Auto Router * @default false @@ -50081,6 +50264,8 @@ export interface components { output_cost_per_character?: number | null; /** Output Cost Per Token */ output_cost_per_token?: number | null; + /** Pricing Provider */ + pricing_provider?: string | null; /** Ptu Count */ ptu_count?: number | null; /** Ptu Effective From */ @@ -50284,6 +50469,8 @@ export interface components { aws_access_key_id?: string | null; /** Aws Batch Role Arn */ aws_batch_role_arn?: string | null; + /** Aws Bedrock Control Plane Endpoint */ + aws_bedrock_control_plane_endpoint?: string | null; /** Aws Bedrock Project Id */ aws_bedrock_project_id?: string | null; /** Aws Bedrock Runtime Endpoint */ @@ -58953,6 +59140,180 @@ export interface operations { }; }; }; + extraction_extraction_post: { + parameters: { + query?: never; + header?: never; + path?: never; + cookie?: never; + }; + requestBody: { + content: { + /** + * @example { + * "fields": { + * "days_to_pay": { + * "max": 90, + * "min": 0, + * "type": "estimate" + * }, + * "invoice_date": { + * "type": "date" + * }, + * "items": { + * "instructions": "What was bought?", + * "items": "text", + * "type": "list" + * }, + * "total": { + * "type": "number", + * "unit": "USD" + * }, + * "vendor": { + * "instructions": "Who sent the invoice?", + * "type": "text" + * } + * }, + * "model": "clairic", + * "state": "Invoice #4471 from Acme Tools, dated 2026-03-03. 12 hammers. Total $174. Payment due in 30 days." + * } + */ + "application/json": { + /** + * Fields + * @description Field name to typed field spec. Each name becomes a key in the answers + */ + fields: { + [key: string]: { + /** + * Decimals + * @description Numbers, durations and number lists only, 0 to 6 + */ + decimals?: number | null; + /** + * Horizon + * @description Forecast only, number of steps + */ + horizon?: number | null; + /** + * Instructions + * @description What the field should contain + */ + instructions?: string | null; + /** + * Integer + * @description Numbers and durations only + */ + integer?: boolean | null; + /** Interval */ + interval?: ("step" | "minute" | "hour" | "day" | "week" | "month" | "quarter" | "year") | null; + /** + * Items + * @description Item type, required for list fields + */ + items?: ("text" | "number" | "date") | null; + /** + * Max + * @description Estimate and forecast upper bound + */ + max?: number | string | null; + /** + * Min + * @description Estimate and forecast lower bound + */ + min?: number | string | null; + /** + * Null Threshold + * @description Probability of null above which the value is null + */ + null_threshold?: number | null; + /** Scale */ + scale?: ("linear" | "log") | null; + /** + * Step + * @description Estimate grid step, or month or year + */ + step?: number | string | null; + /** + * Type + * @description The answer type for this field + * @enum {string} + */ + type: "text" | "number" | "date" | "time" | "datetime" | "duration" | "list" | "estimate" | "forecast"; + /** + * Unit + * @description Unit label. For durations, seconds through years + */ + unit?: string | null; + } & { + [key: string]: unknown; + }; + }; + /** + * Images + * @description Up to 4 images as data URLs or content_type plus base64, no remote URLs + */ + images?: (string | ({ + /** + * Base64 + * @description Base64-encoded image bytes + */ + base64: string; + /** + * Content Type + * @description The image media type, such as image/png + */ + content_type: string; + } & { + [key: string]: unknown; + }))[] | null; + /** + * Model + * @description An extraction model from the proxy model_list + */ + model: string; + options?: ({ + /** + * Include Quantiles + * @description Add 99 percentiles to estimates + */ + include_quantiles?: boolean | null; + /** + * Return State Text + * @description Return the text that spans index into + */ + return_state_text?: boolean | null; + } & { + [key: string]: unknown; + }) | null; + /** + * Reference Date + * @description ISO date that anchors dates written without a year + */ + reference_date?: string | null; + /** + * State + * @description The text to read. Must be non-empty unless images are sent. Text answers are spans of it + * @default + */ + state?: string; + } & { + [key: string]: unknown; + }; + }; + }; + responses: { + /** @description Successful Response */ + 200: { + headers: { + [name: string]: unknown; + }; + content: { + "application/json": components["schemas"]["ExtractionResponse"]; + }; + }; + }; + }; fal_ai_proxy_route_fal_ai__endpoint__get: { parameters: { query?: never; @@ -78278,6 +78639,180 @@ export interface operations { }; }; }; + extraction_v1_extraction_post: { + parameters: { + query?: never; + header?: never; + path?: never; + cookie?: never; + }; + requestBody: { + content: { + /** + * @example { + * "fields": { + * "days_to_pay": { + * "max": 90, + * "min": 0, + * "type": "estimate" + * }, + * "invoice_date": { + * "type": "date" + * }, + * "items": { + * "instructions": "What was bought?", + * "items": "text", + * "type": "list" + * }, + * "total": { + * "type": "number", + * "unit": "USD" + * }, + * "vendor": { + * "instructions": "Who sent the invoice?", + * "type": "text" + * } + * }, + * "model": "clairic", + * "state": "Invoice #4471 from Acme Tools, dated 2026-03-03. 12 hammers. Total $174. Payment due in 30 days." + * } + */ + "application/json": { + /** + * Fields + * @description Field name to typed field spec. Each name becomes a key in the answers + */ + fields: { + [key: string]: { + /** + * Decimals + * @description Numbers, durations and number lists only, 0 to 6 + */ + decimals?: number | null; + /** + * Horizon + * @description Forecast only, number of steps + */ + horizon?: number | null; + /** + * Instructions + * @description What the field should contain + */ + instructions?: string | null; + /** + * Integer + * @description Numbers and durations only + */ + integer?: boolean | null; + /** Interval */ + interval?: ("step" | "minute" | "hour" | "day" | "week" | "month" | "quarter" | "year") | null; + /** + * Items + * @description Item type, required for list fields + */ + items?: ("text" | "number" | "date") | null; + /** + * Max + * @description Estimate and forecast upper bound + */ + max?: number | string | null; + /** + * Min + * @description Estimate and forecast lower bound + */ + min?: number | string | null; + /** + * Null Threshold + * @description Probability of null above which the value is null + */ + null_threshold?: number | null; + /** Scale */ + scale?: ("linear" | "log") | null; + /** + * Step + * @description Estimate grid step, or month or year + */ + step?: number | string | null; + /** + * Type + * @description The answer type for this field + * @enum {string} + */ + type: "text" | "number" | "date" | "time" | "datetime" | "duration" | "list" | "estimate" | "forecast"; + /** + * Unit + * @description Unit label. For durations, seconds through years + */ + unit?: string | null; + } & { + [key: string]: unknown; + }; + }; + /** + * Images + * @description Up to 4 images as data URLs or content_type plus base64, no remote URLs + */ + images?: (string | ({ + /** + * Base64 + * @description Base64-encoded image bytes + */ + base64: string; + /** + * Content Type + * @description The image media type, such as image/png + */ + content_type: string; + } & { + [key: string]: unknown; + }))[] | null; + /** + * Model + * @description An extraction model from the proxy model_list + */ + model: string; + options?: ({ + /** + * Include Quantiles + * @description Add 99 percentiles to estimates + */ + include_quantiles?: boolean | null; + /** + * Return State Text + * @description Return the text that spans index into + */ + return_state_text?: boolean | null; + } & { + [key: string]: unknown; + }) | null; + /** + * Reference Date + * @description ISO date that anchors dates written without a year + */ + reference_date?: string | null; + /** + * State + * @description The text to read. Must be non-empty unless images are sent. Text answers are spans of it + * @default + */ + state?: string; + } & { + [key: string]: unknown; + }; + }; + }; + responses: { + /** @description Successful Response */ + 200: { + headers: { + [name: string]: unknown; + }; + content: { + "application/json": components["schemas"]["ExtractionResponse"]; + }; + }; + }; + }; list_files_v1_files_get: { parameters: { query?: { diff --git a/uv.lock b/uv.lock index 9b490cf95f4..03403828225 100644 --- a/uv.lock +++ b/uv.lock @@ -29,6 +29,7 @@ constraints = [ ] overrides = [ { name = "cryptography", specifier = ">=50.0.0,<51.0" }, + { name = "mcp", specifier = ">=2.3.0,<3" }, { name = "packaging", specifier = ">=24.0" }, ] @@ -4603,7 +4604,7 @@ wheels = [ [[package]] name = "litellm" -version = "1.107.0" +version = "1.108.0" source = { editable = "." } dependencies = [ { name = "aiohttp" }, @@ -4778,7 +4779,8 @@ ci = [ { name = "logfire" }, { name = "lunary", version = "1.4.36", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" }, { name = "lunary", version = "1.4.37", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" }, - { name = "pillow" }, + { name = "pillow", version = "12.3.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" }, + { name = "pillow", version = "13.0.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" }, { name = "psutil" }, { name = "psycopg2-binary" }, { name = "pyarrow" }, @@ -4902,8 +4904,8 @@ requires-dist = [ { name = "gunicorn", marker = "extra == 'proxy'", specifier = ">=23.0.0,<24.0" }, { name = "hiredis", marker = "extra == 'proxy'", specifier = ">=3.0.0,<4.0" }, { name = "httpx", extras = ["http2"], specifier = ">=0.28.0,<1.0" }, - { name = "httpx2", marker = "extra == 'mcp'", specifier = ">=2.5.0,<3" }, - { name = "httpx2", marker = "extra == 'proxy'", specifier = ">=2.5.0,<3" }, + { name = "httpx2", marker = "extra == 'mcp'", specifier = ">=2.10.0,<3" }, + { name = "httpx2", marker = "extra == 'proxy'", specifier = ">=2.10.0,<3" }, { name = "huggingface-hub", specifier = ">=0.34.0,<2.0" }, { name = "importlib-metadata", specifier = ">=8.0.0,<9.0" }, { name = "inquirerpy", marker = "extra == 'cli'", specifier = ">=0.3.4,<1.0" }, @@ -4916,8 +4918,8 @@ requires-dist = [ { name = "litellm-proxy-extras", marker = "extra == 'proxy'", editable = "litellm-proxy-extras" }, { name = "llm-sandbox", marker = "extra == 'proxy-runtime'", specifier = ">=0.3.39,<1.0" }, { name = "mangum", marker = "extra == 'proxy-runtime'", specifier = ">=0.17.0,<1.0" }, - { name = "mcp", marker = "extra == 'mcp'", specifier = ">=2.2.0,<3" }, - { name = "mcp", marker = "extra == 'proxy'", specifier = ">=2.2.0,<3" }, + { name = "mcp", marker = "extra == 'mcp'", specifier = ">=2.3.0,<3" }, + { name = "mcp", marker = "extra == 'proxy'", specifier = ">=2.3.0,<3" }, { name = "mlflow", marker = "extra == 'mlflow'", specifier = 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