Merge branch 'main' into litellm_v1.80.7_docs

docs/my-website/docs/providers/publicai.md

@@ -0,0 +1,209 @@
+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+
+# PublicAI
+
+## Overview
+
+| Property | Details |
+|-------|-------|
+| Description | PublicAI provides large language models including essential models like the swiss-ai apertus model. |
+| Provider Route on LiteLLM | `publicai/` |
+| Link to Provider Doc | [PublicAI ↗](https://platform.publicai.co/) |
+| Base URL | `https://platform.publicai.co/` |
+| Supported Operations | [`/chat/completions`](#sample-usage) |
+
+<br />
+<br />
+
+https://platform.publicai.co/
+
+**We support ALL PublicAI models, just set `publicai/` as a prefix when sending completion requests**
+
+## Required Variables
+
+```python showLineNumbers title="Environment Variables"
+os.environ["PUBLICAI_API_KEY"] = ""  # your PublicAI API key
+```
+
+You can overwrite the base url with:
+
+```
+os.environ["PUBLICAI_API_BASE"] = "https://platform.publicai.co/v1"
+```
+
+## Usage - LiteLLM Python SDK
+
+### Non-streaming
+
+```python showLineNumbers title="PublicAI Non-streaming Completion"
+import os
+import litellm
+from litellm import completion
+
+os.environ["PUBLICAI_API_KEY"] = ""  # your PublicAI API key
+
+messages = [{"content": "Hello, how are you?", "role": "user"}]
+
+# PublicAI call
+response = completion(
+    model="publicai/swiss-ai/apertus-8b-instruct", 
+    messages=messages
+)
+
+print(response)
+```
+
+### Streaming
+
+```python showLineNumbers title="PublicAI Streaming Completion"
+import os
+import litellm
+from litellm import completion
+
+os.environ["PUBLICAI_API_KEY"] = ""  # your PublicAI API key
+
+messages = [{"content": "Hello, how are you?", "role": "user"}]
+
+# PublicAI call with streaming
+response = completion(
+    model="publicai/swiss-ai/apertus-8b-instruct", 
+    messages=messages,
+    stream=True
+)
+
+for chunk in response:
+    print(chunk)
+```
+
+## Usage - LiteLLM Proxy
+
+Add the following to your LiteLLM Proxy configuration file:
+
+```yaml showLineNumbers title="config.yaml"
+model_list:
+  - model_name: swiss-ai-apertus-8b
+    litellm_params:
+      model: publicai/swiss-ai/apertus-8b-instruct
+      api_key: os.environ/PUBLICAI_API_KEY
+
+  - model_name: swiss-ai-apertus-70b
+    litellm_params:
+      model: publicai/swiss-ai/apertus-70b-instruct
+      api_key: os.environ/PUBLICAI_API_KEY
+```
+
+Start your LiteLLM Proxy server:
+
+```bash showLineNumbers title="Start LiteLLM Proxy"
+litellm --config config.yaml
+
+# RUNNING on http://0.0.0.0:4000
+```
+
+<Tabs>
+<TabItem value="openai-sdk" label="OpenAI SDK">
+
+```python showLineNumbers title="PublicAI via Proxy - Non-streaming"
+from openai import OpenAI
+
+# Initialize client with your proxy URL
+client = OpenAI(
+    base_url="http://localhost:4000",  # Your proxy URL
+    api_key="your-proxy-api-key"       # Your proxy API key
+)
+
+# Non-streaming response
+response = client.chat.completions.create(
+    model="swiss-ai-apertus-8b",
+    messages=[{"role": "user", "content": "hello from litellm"}]
+)
+
+print(response.choices[0].message.content)
+```
+
+```python showLineNumbers title="PublicAI via Proxy - Streaming"
+from openai import OpenAI
+
+# Initialize client with your proxy URL
+client = OpenAI(
+    base_url="http://localhost:4000",  # Your proxy URL
+    api_key="your-proxy-api-key"       # Your proxy API key
+)
+
+# Streaming response
+response = client.chat.completions.create(
+    model="swiss-ai-apertus-8b",
+    messages=[{"role": "user", "content": "hello from litellm"}],
+    stream=True
+)
+
+for chunk in response:
+    if chunk.choices[0].delta.content is not None:
+        print(chunk.choices[0].delta.content, end="")
+```
+
+</TabItem>
+
+<TabItem value="litellm-sdk" label="LiteLLM SDK">
+
+```python showLineNumbers title="PublicAI via Proxy - LiteLLM SDK"
+import litellm
+
+# Configure LiteLLM to use your proxy
+response = litellm.completion(
+    model="litellm_proxy/swiss-ai-apertus-8b",
+    messages=[{"role": "user", "content": "hello from litellm"}],
+    api_base="http://localhost:4000",
+    api_key="your-proxy-api-key"
+)
+
+print(response.choices[0].message.content)
+```
+
+```python showLineNumbers title="PublicAI via Proxy - LiteLLM SDK Streaming"
+import litellm
+
+# Configure LiteLLM to use your proxy with streaming
+response = litellm.completion(
+    model="litellm_proxy/swiss-ai-apertus-8b",
+    messages=[{"role": "user", "content": "hello from litellm"}],
+    api_base="http://localhost:4000",
+    api_key="your-proxy-api-key",
+    stream=True
+)
+
+for chunk in response:
+    if hasattr(chunk.choices[0], 'delta') and chunk.choices[0].delta.content is not None:
+        print(chunk.choices[0].delta.content, end="")
+```
+
+</TabItem>
+
+<TabItem value="curl" label="cURL">
+
+```bash showLineNumbers title="PublicAI via Proxy - cURL"
+curl http://localhost:4000/v1/chat/completions \
+  -H "Content-Type: application/json" \
+  -H "Authorization: Bearer your-proxy-api-key" \
+  -d '{
+    "model": "swiss-ai-apertus-8b",
+    "messages": [{"role": "user", "content": "hello from litellm"}]
+  }'
+```
+
+```bash showLineNumbers title="PublicAI via Proxy - cURL Streaming"
+curl http://localhost:4000/v1/chat/completions \
+  -H "Content-Type: application/json" \
+  -H "Authorization: Bearer your-proxy-api-key" \
+  -d '{
+    "model": "swiss-ai-apertus-8b",
+    "messages": [{"role": "user", "content": "hello from litellm"}],
+    "stream": true
+  }'
+```
+
+</TabItem>
+</Tabs>
+
+For more detailed information on using the LiteLLM Proxy, see the [LiteLLM Proxy documentation](../providers/litellm_proxy).

docs/my-website/docs/proxy/pass_through_guardrails.md

@@ -1,5 +1,7 @@
 # Guardrails on Pass-Through Endpoints
 
+import Image from '@theme/IdealImage';
+
 ## Overview
 
 | Property | Details |
@@ -10,7 +12,41 @@
 
 ## Quick Start
 
-### 1. Define guardrails and pass-through endpoint
+You can configure guardrails on pass-through endpoints either via the **UI** (recommended) or **config file**.
+
+### Using the UI
+
+#### 1. Navigate to Pass-Through Endpoints
+
+Go to **Models + Endpoints** → Click **+ Add Pass-Through Endpoint**
+
+<Image img={require('../../img/pt_guard1.png')} alt="Add guardrails to pass-through endpoint" />
+
+Scroll to the **Guardrails** section and select which guardrails to enforce.
+
+:::tip Default Behavior
+By default, you don't need to specify fields - LiteLLM will JSON dump the entire request/response payload and send it to the guardrail.
+:::
+
+#### 2. Target Specific Fields (Optional)
+
+<Image img={require('../../img/pt_guard2.png')} alt="Configure field-level targeting" />
+
+To check only specific fields instead of the entire payload:
+
+1. Select your guardrails
+2. In **Field Targeting (Optional)**, specify fields for each guardrail
+3. Use the quick-add buttons (`+ query`, `+ documents[*]`) or type custom JSONPath expressions
+4. **Request Fields (pre_call)**: Fields to check before sending to target API
+5. **Response Fields (post_call)**: Fields to check in the response from target API
+
+**Example**: In the screenshot above, we set `query` as a request field, so only the `query` field is sent to the guardrail instead of the entire request.
+
+---
+
+### Using Config File
+
+#### 1. Define guardrails and pass-through endpoint
 
 ```yaml showLineNumbers title="config.yaml"
 guardrails:
@@ -31,13 +67,13 @@ general_settings:
         pii-guard:
 ```
 
-### 2. Start proxy
+#### 2. Start proxy
 
 ```bash
 litellm --config config.yaml
 ```
 
-### 3. Test request
+#### 3. Test request
 
 ```bash
 curl -X POST "http://localhost:4000/v1/rerank" \

docs/my-website/sidebars.js

@@ -622,6 +622,7 @@ const sidebars = {
         "providers/ovhcloud",
         "providers/perplexity",
         "providers/petals",
+        "providers/publicai",
         "providers/predibase",
         "providers/recraft",
         "providers/replicate",

litellm/__init__.py

@@ -555,6 +555,7 @@ deepgram_models: Set = set()
 elevenlabs_models: Set = set()
 dashscope_models: Set = set()
 moonshot_models: Set = set()
+publicai_models: Set = set()
 v0_models: Set = set()
 morph_models: Set = set()
 lambda_ai_models: Set = set()
@@ -781,6 +782,8 @@ def add_known_models():
             dashscope_models.add(key)
         elif value.get("litellm_provider") == "moonshot":
             moonshot_models.add(key)
+        elif value.get("litellm_provider") == "publicai":
+            publicai_models.add(key)
         elif value.get("litellm_provider") == "v0":
             v0_models.add(key)
         elif value.get("litellm_provider") == "morph":
@@ -899,6 +902,7 @@ model_list = list(
     | elevenlabs_models
     | dashscope_models
     | moonshot_models
+    | publicai_models
     | v0_models
     | morph_models
     | lambda_ai_models
@@ -992,6 +996,7 @@ models_by_provider: dict = {
     "heroku": heroku_models,
     "dashscope": dashscope_models,
     "moonshot": moonshot_models,
+    "publicai": publicai_models,
     "v0": v0_models,
     "morph": morph_models,
     "lambda_ai": lambda_ai_models,
@@ -1370,6 +1375,7 @@ from .llms.nebius.chat.transformation import NebiusConfig
 from .llms.wandb.chat.transformation import WandbConfig
 from .llms.dashscope.chat.transformation import DashScopeChatConfig
 from .llms.moonshot.chat.transformation import MoonshotChatConfig
+from .llms.publicai.chat.transformation import PublicAIChatConfig
 from .llms.docker_model_runner.chat.transformation import DockerModelRunnerChatConfig
 from .llms.v0.chat.transformation import V0ChatConfig
 from .llms.oci.chat.transformation import OCIChatConfig

litellm/constants.py

@@ -384,6 +384,7 @@ LITELLM_CHAT_PROVIDERS = [
     "nebius",
     "dashscope",
     "moonshot",
+    "publicai",
     "v0",
     "heroku",
     "oci",
@@ -526,6 +527,7 @@ openai_compatible_endpoints: List = [
     "api.studio.nebius.ai/v1",
     "https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
     "https://api.moonshot.ai/v1",
+    "https://platform.publicai.co/v1",
     "https://api.v0.dev/v1",
     "https://api.morphllm.com/v1",
     "https://api.lambda.ai/v1",
@@ -571,6 +573,7 @@ openai_compatible_providers: List = [
     "nebius",
     "dashscope",
     "moonshot",
+    "publicai",
     "v0",
     "morph",
     "lambda_ai",
@@ -593,6 +596,7 @@ openai_text_completion_compatible_providers: List = (
         "nebius",
         "dashscope",
         "moonshot",
+        "publicai",
         "v0",
         "lambda_ai",
         "hyperbolic",

litellm/litellm_core_utils/get_llm_provider_logic.py

@@ -258,6 +258,9 @@ def get_llm_provider(  # noqa: PLR0915
                     elif endpoint == "api.moonshot.ai/v1":
                         custom_llm_provider = "moonshot"
                         dynamic_api_key = get_secret_str("MOONSHOT_API_KEY")
+                    elif endpoint == "platform.publicai.co/v1":
+                        custom_llm_provider = "publicai"
+                        dynamic_api_key = get_secret_str("PUBLICAI_API_KEY")
                     elif endpoint == "https://api.v0.dev/v1":
                         custom_llm_provider = "v0"
                         dynamic_api_key = get_secret_str("V0_API_KEY")
@@ -759,6 +762,13 @@ def _get_openai_compatible_provider_info(  # noqa: PLR0915
         ) = litellm.MoonshotChatConfig()._get_openai_compatible_provider_info(
             api_base, api_key
         )
+    elif custom_llm_provider == "publicai":
+        (
+            api_base,
+            dynamic_api_key,
+        ) = litellm.PublicAIChatConfig()._get_openai_compatible_provider_info(
+            api_base, api_key
+        )
     elif custom_llm_provider == "docker_model_runner":
         (
             api_base,

litellm/llms/publicai/chat/transformation.py

@@ -0,0 +1,114 @@
+"""
+Translates from OpenAI's `/v1/chat/completions` to PublicAI's `/v1/chat/completions`
+"""
+
+from typing import Any, Coroutine, List, Literal, Optional, Tuple, Union, overload
+
+from litellm.litellm_core_utils.prompt_templates.common_utils import (
+    handle_messages_with_content_list_to_str_conversion,
+)
+from litellm.secret_managers.main import get_secret_str
+from litellm.types.llms.openai import AllMessageValues
+
+from ...openai.chat.gpt_transformation import OpenAIGPTConfig
+
+
+class PublicAIChatConfig(OpenAIGPTConfig):
+    @overload
+    def _transform_messages(
+        self, messages: List[AllMessageValues], model: str, is_async: Literal[True]
+    ) -> Coroutine[Any, Any, List[AllMessageValues]]:
+        ...
+
+    @overload
+    def _transform_messages(
+        self,
+        messages: List[AllMessageValues],
+        model: str,
+        is_async: Literal[False] = False,
+    ) -> List[AllMessageValues]:
+        ...
+
+    def _transform_messages(
+        self, messages: List[AllMessageValues], model: str, is_async: bool = False
+    ) -> Union[List[AllMessageValues], Coroutine[Any, Any, List[AllMessageValues]]]:
+        """
+        PublicAI does not support content in list format.
+        """
+        messages = handle_messages_with_content_list_to_str_conversion(messages)
+        if is_async:
+            return super()._transform_messages(
+                messages=messages, model=model, is_async=True
+            )
+        else:
+            return super()._transform_messages(
+                messages=messages, model=model, is_async=False
+            )
+
+    def _get_openai_compatible_provider_info(
+        self, api_base: Optional[str], api_key: Optional[str]
+    ) -> Tuple[Optional[str], Optional[str]]:
+        api_base = (
+            api_base
+            or get_secret_str("PUBLICAI_API_BASE")
+            or "https://platform.publicai.co/v1"
+        )  # type: ignore
+        dynamic_api_key = api_key or get_secret_str("PUBLICAI_API_KEY")
+        return api_base, dynamic_api_key
+
+    def get_complete_url(
+        self,
+        api_base: Optional[str],
+        api_key: Optional[str],
+        model: str,
+        optional_params: dict,
+        litellm_params: dict,
+        stream: Optional[bool] = None,
+    ) -> str:
+        """
+        If api_base is not provided, use the default PublicAI /chat/completions endpoint.
+        """
+        if not api_base:
+            api_base = "https://platform.publicai.co/v1"
+
+        if not api_base.endswith("/chat/completions"):
+            api_base = f"{api_base}/chat/completions"
+
+        return api_base
+
+    def get_supported_openai_params(self, model: str) -> list:
+        """
+        Get the supported OpenAI params for PublicAI models
+        
+        PublicAI limitations:
+        - functions parameter is not supported (use tools instead)
+        """
+        excluded_params: List[str] = ["functions"]
+        
+        base_openai_params = super().get_supported_openai_params(model=model)
+        final_params: List[str] = []
+        for param in base_openai_params:
+            if param not in excluded_params:
+                final_params.append(param)
+        
+        return final_params
+
+    def map_openai_params(
+        self,
+        non_default_params: dict,
+        optional_params: dict,
+        model: str,
+        drop_params: bool,
+    ) -> dict:
+        """
+        Map OpenAI parameters to PublicAI parameters
+        """
+        supported_openai_params = self.get_supported_openai_params(model)
+        for param, value in non_default_params.items():
+            if param == "max_completion_tokens":
+                optional_params["max_tokens"] = value
+            elif param in supported_openai_params:
+                optional_params[param] = value
+
+        return optional_params
+

litellm/model_prices_and_context_window_backup.json

@@ -21570,6 +21570,116 @@
         "mode": "chat",
         "output_cost_per_token": 2.8e-07
     },
+    "publicai/swiss-ai/apertus-8b-instruct": {
+        "input_cost_per_token": 0.0,
+        "litellm_provider": "publicai",
+        "max_input_tokens": 8192,
+        "max_output_tokens": 4096,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 0.0,
+        "source": "https://platform.publicai.co/docs",
+        "supports_function_calling": true,
+        "supports_tool_choice": true
+    },
+    "publicai/swiss-ai/apertus-70b-instruct": {
+        "input_cost_per_token": 0.0,
+        "litellm_provider": "publicai",
+        "max_input_tokens": 8192,
+        "max_output_tokens": 4096,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 0.0,
+        "source": "https://platform.publicai.co/docs",
+        "supports_function_calling": true,
+        "supports_tool_choice": true
+    },
+    "publicai/aisingapore/Gemma-SEA-LION-v4-27B-IT": {
+        "input_cost_per_token": 0.0,
+        "litellm_provider": "publicai",
+        "max_input_tokens": 8192,
+        "max_output_tokens": 4096,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 0.0,
+        "source": "https://platform.publicai.co/docs",
+        "supports_function_calling": true,
+        "supports_tool_choice": true
+    },
+    "publicai/BSC-LT/salamandra-7b-instruct-tools-16k": {
+        "input_cost_per_token": 0.0,
+        "litellm_provider": "publicai",
+        "max_input_tokens": 16384,
+        "max_output_tokens": 4096,
+        "max_tokens": 16384,
+        "mode": "chat",
+        "output_cost_per_token": 0.0,
+        "source": "https://platform.publicai.co/docs",
+        "supports_function_calling": true,
+        "supports_tool_choice": true
+    },
+    "publicai/BSC-LT/ALIA-40b-instruct_Q8_0": {
+        "input_cost_per_token": 0.0,
+        "litellm_provider": "publicai",
+        "max_input_tokens": 8192,
+        "max_output_tokens": 4096,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 0.0,
+        "source": "https://platform.publicai.co/docs",
+        "supports_function_calling": true,
+        "supports_tool_choice": true
+    },
+    "publicai/allenai/Olmo-3-7B-Instruct": {
+        "input_cost_per_token": 0.0,
+        "litellm_provider": "publicai",
+        "max_input_tokens": 32768,
+        "max_output_tokens": 4096,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "output_cost_per_token": 0.0,
+        "source": "https://platform.publicai.co/docs",
+        "supports_function_calling": true,
+        "supports_tool_choice": true
+    },
+    "publicai/aisingapore/Qwen-SEA-LION-v4-32B-IT": {
+        "input_cost_per_token": 0.0,
+        "litellm_provider": "publicai",
+        "max_input_tokens": 32768,
+        "max_output_tokens": 4096,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "output_cost_per_token": 0.0,
+        "source": "https://platform.publicai.co/docs",
+        "supports_function_calling": true,
+        "supports_tool_choice": true
+    },
+    "publicai/allenai/Olmo-3-7B-Think": {
+        "input_cost_per_token": 0.0,
+        "litellm_provider": "publicai",
+        "max_input_tokens": 32768,
+        "max_output_tokens": 4096,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "output_cost_per_token": 0.0,
+        "source": "https://platform.publicai.co/docs",
+        "supports_function_calling": true,
+        "supports_tool_choice": true,
+        "supports_reasoning": true
+    },
+    "publicai/allenai/Olmo-3-32B-Think": {
+        "input_cost_per_token": 0.0,
+        "litellm_provider": "publicai",
+        "max_input_tokens": 32768,
+        "max_output_tokens": 4096,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "output_cost_per_token": 0.0,
+        "source": "https://platform.publicai.co/docs",
+        "supports_function_calling": true,
+        "supports_tool_choice": true,
+        "supports_reasoning": true
+    },
     "qwen.qwen3-coder-480b-a35b-v1:0": {
         "input_cost_per_token": 2.2e-07,
         "litellm_provider": "bedrock_converse",

litellm/proxy/_experimental/out/_next/static/chunks/app/(dashboard)/experimental/caching/page-0a286b7e7489b565.js

@@ -1 +1 @@
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