From 9d299d016a6044cf22474764faa7288c4eab54fa Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 19:03:40 +0000 Subject: [PATCH 001/101] chore(pricing): remove retired models flagged by the provider sync (#42521) Co-authored-by: kerry Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- ...odel_prices_and_context_window_backup.json | 441 ------------------ model_prices_and_context_window.json | 441 ------------------ 2 files changed, 882 deletions(-) diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 8f9958e0031..0e80d4732c8 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -578,17 +578,6 @@ "supports_vision": true, "supports_tool_choice": true }, - "amazon.nova-sonic-v1:0": { - "deprecation_date": "2026-09-14", - "input_cost_per_audio_token": 3.4e-06, - "input_cost_per_token": 6e-08, - "litellm_provider": "bedrock", - "mode": "realtime", - "output_cost_per_audio_token": 1.36e-05, - "output_cost_per_token": 2.4e-07, - "supports_audio_input": true, - "supports_audio_output": true - }, "amazon.nova-2-sonic-v1:0": { "input_cost_per_audio_token": 3e-06, "input_cost_per_token": 3.3e-07, @@ -4685,21 +4674,6 @@ "supports_prompt_caching": true, "supports_vision": false }, - "azure/eu/o1-preview-2024-09-12": { - "cache_read_input_token_cost": 8.25e-06, - "input_cost_per_token": 1.65e-05, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 32768, - "max_tokens": 32768, - "mode": "chat", - "output_cost_per_token": 6.6e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_prompt_caching": true, - "supports_vision": false - }, "azure/eu/o3-mini-2025-01-31": { "cache_read_input_token_cost": 6.05e-07, "deprecation_date": "2026-11-19", @@ -9819,39 +9793,6 @@ "supports_reasoning": true, "supports_vision": false }, - "azure/o1-preview": { - "cache_read_input_token_cost": 7.5e-06, - "input_cost_per_token": 1.5e-05, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 32768, - "max_tokens": 32768, - "mode": "chat", - "output_cost_per_token": 6e-05, - "source": "https://prices.azure.com/api/retail/prices?$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_reasoning": true, - "supports_vision": false - }, - "azure/o1-preview-2024-09-12": { - "cache_read_input_token_cost": 7.5e-06, - "input_cost_per_token": 1.5e-05, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 32768, - "max_tokens": 32768, - "mode": "chat", - "output_cost_per_token": 6e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_vision": false - }, "azure/o3": { "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 5e-07, @@ -10720,21 +10661,6 @@ "supports_prompt_caching": true, "supports_vision": false }, - "azure/us/o1-preview-2024-09-12": { - "cache_read_input_token_cost": 8.25e-06, - "input_cost_per_token": 1.65e-05, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 32768, - "max_tokens": 32768, - "mode": "chat", - "output_cost_per_token": 6.6e-05, - "source": "https://prices.azure.com/api/retail/prices?$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_vision": false - }, "azure/us/o3-2025-04-16": { "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 5.5e-07, @@ -15609,28 +15535,6 @@ "output_cost_per_token": 6e-07, "supports_tool_choice": true }, - "cohere.command-r-plus-v1:0": { - "deprecation_date": "2026-08-19", - "input_cost_per_token": 3e-06, - "litellm_provider": "bedrock", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.5e-05, - "supports_tool_choice": true - }, - "cohere.command-r-v1:0": { - "deprecation_date": "2026-08-19", - "input_cost_per_token": 5e-07, - "litellm_provider": "bedrock", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.5e-06, - "supports_tool_choice": true - }, "cohere.command-text-v14": { "input_cost_per_token": 1.5e-06, "litellm_provider": "bedrock", @@ -42975,32 +42879,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "openrouter/anthropic/claude-opus-4": { - "input_cost_per_image": 0.0048, - "cache_creation_input_token_cost": 1.875e-05, - "cache_creation_input_token_cost_above_1hr": 3e-05, - "cache_read_input_token_cost": 1.5e-06, - "input_cost_per_token": 1.5e-05, - "litellm_provider": "openrouter", - "max_input_tokens": 200000, - "max_output_tokens": 32000, - "max_tokens": 32000, - "mode": "chat", - "output_cost_per_token": 7.5e-05, - "supports_assistant_prefill": true, - "supports_computer_use": true, - "supports_function_calling": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_tool_choice": true, - "supports_vision": true, - "prompt_cache_min_tokens": 1024, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_pdf_input": true, - "supports_response_schema": false, - "supports_web_search": true - }, "openrouter/anthropic/claude-opus-4.1": { "input_cost_per_image": 0.0048, "cache_creation_input_token_cost": 1.875e-05, @@ -43928,27 +43806,6 @@ "supports_vision": true, "supports_web_search": false }, - "openrouter/mistralai/mistral-large-2512": { - "cache_read_input_token_cost": 5.5e-08, - "input_cost_per_image": 0, - "input_cost_per_token": 5.5e-07, - "litellm_provider": "openrouter", - "max_input_tokens": 262144, - "max_output_tokens": 209715, - "max_tokens": 209715, - "mode": "chat", - "output_cost_per_token": 1.65e-06, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": false, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": false - }, "openrouter/mistralai/mistral-7b-instruct": { "input_cost_per_token": 1.3e-07, "litellm_provider": "openrouter", @@ -48806,22 +48663,6 @@ "supports_response_schema": true, "supports_tool_choice": true }, - "us.amazon.nova-premier-v1:0": { - "deprecation_date": "2026-09-14", - "input_cost_per_token": 2.5e-06, - "litellm_provider": "bedrock_converse", - "max_input_tokens": 1000000, - "max_output_tokens": 10000, - "max_tokens": 10000, - "mode": "chat", - "output_cost_per_token": 1.25e-05, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_vision": true, - "cache_read_input_token_cost": 6.25e-07 - }, "us.amazon.nova-pro-v1:0": { "cache_read_input_token_cost": 2e-07, "input_cost_per_token": 8e-07, @@ -71275,15 +71116,6 @@ "output_cost_per_token": 1.6e-06, "source": "https://api.together.ai/v1/models" }, - "vertex_ai/gemini-2.5-flash-native-audio": { - "input_cost_per_audio_token": 3e-06, - "input_cost_per_token": 5e-07, - "litellm_provider": "vertex_ai", - "mode": "realtime", - "output_cost_per_audio_token": 1.2e-05, - "output_cost_per_token": 2e-06, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" - }, "vertex_ai/gemini-2.5-flash-preview-tts": { "input_cost_per_token": 5e-07, "input_cost_per_token_batches": 2.5e-07, @@ -71293,16 +71125,6 @@ "output_cost_per_token": 1e-05, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" }, - "vertex_ai/gemini-3.1-flash-live-preview": { - "input_cost_per_audio_token": 3e-06, - "input_cost_per_second": 8.33333333333e-05, - "input_cost_per_token": 7.5e-07, - "litellm_provider": "vertex_ai", - "mode": "realtime", - "output_cost_per_audio_token": 1.2e-05, - "output_cost_per_token": 4.5e-06, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" - }, "vertex_ai/gemini-3.1-flash-tts-preview": { "input_cost_per_token": 1e-06, "input_cost_per_token_batches": 5e-07, @@ -71335,16 +71157,6 @@ "output_cost_per_token": 9e-06, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" }, - "vertex_ai/gemini-robotics-er-2": { - "cache_read_input_token_cost": 1e-07, - "input_cost_per_token": 1e-06, - "input_cost_per_token_batches": 5e-07, - "litellm_provider": "vertex_ai", - "mode": "chat", - "output_cost_per_token": 5e-06, - "output_cost_per_token_batches": 2.5e-06, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" - }, "vertex_ai/gemma-4-26b-a4b-it": { "cache_read_input_token_cost": 1.5e-08, "input_cost_per_token": 1.5e-07, @@ -71754,14 +71566,6 @@ "output_cost_per_token_batches": 2.42e-06, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, - "azure/eu/o1-preview": { - "cache_read_input_token_cost": 8.25e-06, - "input_cost_per_token": 1.65e-05, - "litellm_provider": "azure", - "mode": "chat", - "output_cost_per_token": 6.6e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" - }, "azure/eu/o3-2025-04-16": { "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 5.5e-07, @@ -72103,14 +71907,6 @@ "output_cost_per_token_batches": 2.42e-06, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, - "azure/us/o1-preview": { - "cache_read_input_token_cost": 8.25e-06, - "input_cost_per_token": 1.65e-05, - "litellm_provider": "azure", - "mode": "chat", - "output_cost_per_token": 6.6e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" - }, "azure/us/o3-deep-research": { "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 2.75e-06, @@ -74456,85 +74252,6 @@ "supports_vision": false, "supports_web_search": false }, - "openrouter/deepseek/deepseek-v4-flash-0731:batch": { - "cache_read_input_token_cost": 3.5e-09, - "input_cost_per_token": 1.1e-07, - "litellm_provider": "openrouter", - "max_input_tokens": 1048576, - "max_output_tokens": 943718, - "max_tokens": 943718, - "mode": "chat", - "output_cost_per_token": 3.3e-07, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": false, - "supports_web_search": false - }, - "openrouter/deepseek/deepseek-v4-flash-0731:free": { - "input_cost_per_token": 0.0, - "litellm_provider": "openrouter", - "max_input_tokens": 1048576, - "max_output_tokens": 393216, - "max_tokens": 393216, - "mode": "chat", - "output_cost_per_token": 0.0, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": false, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": false, - "supports_web_search": false - }, - "openrouter/deepseek/deepseek-v4-flash-vision-exp:batch": { - "cache_read_input_token_cost": 3.5e-09, - "input_cost_per_token": 1.1e-07, - "litellm_provider": "openrouter", - "max_input_tokens": 1048576, - "max_output_tokens": 943718, - "max_tokens": 943718, - "mode": "chat", - "output_cost_per_token": 3.3e-07, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": false - }, - "openrouter/deepseek/deepseek-v4-pro-0813:batch": { - "cache_read_input_token_cost": 2.2e-08, - "input_cost_per_token": 6.6e-07, - "litellm_provider": "openrouter", - "max_input_tokens": 1048576, - "max_output_tokens": 943718, - "max_tokens": 943718, - "mode": "chat", - "output_cost_per_token": 1.98e-06, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": false, - "supports_web_search": false - }, "openrouter/dots-studio/dots-3-note-preview:free": { "deprecation_date": "2026-12-31", "input_cost_per_token": 0.0, @@ -75050,26 +74767,6 @@ "supports_vision": false, "supports_web_search": false }, - "openrouter/kwaipilot/kat-coder-pro-v2": { - "cache_read_input_token_cost": 6e-08, - "input_cost_per_token": 3e-07, - "litellm_provider": "openrouter", - "max_input_tokens": 262144, - "max_output_tokens": 144000, - "max_tokens": 144000, - "mode": "chat", - "output_cost_per_token": 1.2e-06, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": true, - "supports_reasoning": false, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": false, - "supports_web_search": false - }, "openrouter/kwaipilot/kat-coder-pro-v2.5": { "cache_read_input_token_cost": 1.5e-07, "input_cost_per_token": 7.4e-07, @@ -75149,26 +74846,6 @@ "supports_vision": true, "supports_web_search": false }, - "openrouter/meta/muse-glimmer-30b:batch": { - "cache_read_input_token_cost": 2e-08, - "input_cost_per_token": 1.75e-07, - "litellm_provider": "openrouter", - "max_input_tokens": 131072, - "max_output_tokens": 117964, - "max_tokens": 117964, - "mode": "chat", - "output_cost_per_token": 7.5e-07, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": false - }, "openrouter/meta/muse-spark-1.1": { "cache_read_input_token_cost": 1.5e-07, "input_cost_per_token": 1.25e-06, @@ -75307,26 +74984,6 @@ "supports_vision": false, "supports_web_search": false }, - "openrouter/minimax/minimax-m3:batch": { - "cache_read_input_token_cost": 6e-08, - "input_cost_per_token": 3e-07, - "litellm_provider": "openrouter", - "max_input_tokens": 524288, - "max_output_tokens": 471859, - "max_tokens": 471859, - "mode": "chat", - "output_cost_per_token": 1.2e-06, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": false - }, "openrouter/mistralai/codestral-2508:batch": { "cache_read_input_token_cost": 1.5e-08, "input_cost_per_token": 1.5e-07, @@ -76276,25 +75933,6 @@ "supports_vision": true, "supports_web_search": true }, - "openrouter/openai/gpt-oss-120b:batch": { - "input_cost_per_token": 1.5e-07, - "litellm_provider": "openrouter", - "max_input_tokens": 131072, - "max_output_tokens": 117964, - "max_tokens": 117964, - "mode": "chat", - "output_cost_per_token": 6e-07, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": false, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": false, - "supports_web_search": false - }, "openrouter/openai/o3-mini:batch": { "cache_read_input_token_cost": 2.75e-07, "input_cost_per_token": 5.5e-07, @@ -76469,45 +76107,6 @@ "supports_vision": true, "supports_web_search": true }, - "openrouter/qwen/qwen3.5-9b:batch": { - "input_cost_per_token": 1.7e-07, - "litellm_provider": "openrouter", - "max_input_tokens": 262144, - "max_output_tokens": 235929, - "max_tokens": 235929, - "mode": "chat", - "output_cost_per_token": 2.5e-07, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": false, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": false - }, - "openrouter/qwen/qwen3.8-2.4t-a95b:batch": { - "cache_read_input_token_cost": 2.5e-07, - "input_cost_per_token": 2e-06, - "litellm_provider": "openrouter", - "max_input_tokens": 1010000, - "max_output_tokens": 909000, - "max_tokens": 909000, - "mode": "chat", - "output_cost_per_token": 6e-06, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": false, - "supports_web_search": false - }, "openrouter/qwen/qwen3.8-27b:free": { "input_cost_per_token": 0.0, "litellm_provider": "openrouter", @@ -77040,26 +76639,6 @@ "supports_vision": true, "supports_web_search": false }, - "openrouter/thinkingmachines/inkling:batch": { - "cache_read_input_token_cost": 1.7e-07, - "input_cost_per_token": 1e-06, - "litellm_provider": "openrouter", - "max_input_tokens": 524288, - "max_output_tokens": 471859, - "max_tokens": 471859, - "mode": "chat", - "output_cost_per_token": 4.05e-06, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": true, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": false, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": false - }, "openrouter/thinkingmachines/inkling:free": { "input_cost_per_token": 0.0, "litellm_provider": "openrouter", @@ -77181,26 +76760,6 @@ "supports_vision": true, "supports_web_search": true }, - "openrouter/z-ai/glm-5.2:batch": { - "cache_read_input_token_cost": 7e-08, - "input_cost_per_token": 7e-07, - "litellm_provider": "openrouter", - "max_input_tokens": 1048576, - "max_output_tokens": 943718, - "max_tokens": 943718, - "mode": "chat", - "output_cost_per_token": 2.2e-06, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": false, - "supports_web_search": false - }, "openrouter/z-ai/glm-5.3-flash:batch": { "cache_read_input_token_cost": 1.2e-08, "input_cost_per_token": 6e-08, diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 8f9958e0031..0e80d4732c8 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -578,17 +578,6 @@ "supports_vision": true, "supports_tool_choice": true }, - "amazon.nova-sonic-v1:0": { - "deprecation_date": "2026-09-14", - "input_cost_per_audio_token": 3.4e-06, - "input_cost_per_token": 6e-08, - "litellm_provider": "bedrock", - "mode": "realtime", - "output_cost_per_audio_token": 1.36e-05, - "output_cost_per_token": 2.4e-07, - "supports_audio_input": true, - "supports_audio_output": true - }, "amazon.nova-2-sonic-v1:0": { "input_cost_per_audio_token": 3e-06, "input_cost_per_token": 3.3e-07, @@ -4685,21 +4674,6 @@ "supports_prompt_caching": true, "supports_vision": false }, - "azure/eu/o1-preview-2024-09-12": { - "cache_read_input_token_cost": 8.25e-06, - "input_cost_per_token": 1.65e-05, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 32768, - "max_tokens": 32768, - "mode": "chat", - "output_cost_per_token": 6.6e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_prompt_caching": true, - "supports_vision": false - }, "azure/eu/o3-mini-2025-01-31": { "cache_read_input_token_cost": 6.05e-07, "deprecation_date": "2026-11-19", @@ -9819,39 +9793,6 @@ "supports_reasoning": true, "supports_vision": false }, - "azure/o1-preview": { - "cache_read_input_token_cost": 7.5e-06, - "input_cost_per_token": 1.5e-05, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 32768, - "max_tokens": 32768, - "mode": "chat", - "output_cost_per_token": 6e-05, - "source": "https://prices.azure.com/api/retail/prices?$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_reasoning": true, - "supports_vision": false - }, - "azure/o1-preview-2024-09-12": { - "cache_read_input_token_cost": 7.5e-06, - "input_cost_per_token": 1.5e-05, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 32768, - "max_tokens": 32768, - "mode": "chat", - "output_cost_per_token": 6e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_vision": false - }, "azure/o3": { "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 5e-07, @@ -10720,21 +10661,6 @@ "supports_prompt_caching": true, "supports_vision": false }, - "azure/us/o1-preview-2024-09-12": { - "cache_read_input_token_cost": 8.25e-06, - "input_cost_per_token": 1.65e-05, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 32768, - "max_tokens": 32768, - "mode": "chat", - "output_cost_per_token": 6.6e-05, - "source": "https://prices.azure.com/api/retail/prices?$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_vision": false - }, "azure/us/o3-2025-04-16": { "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 5.5e-07, @@ -15609,28 +15535,6 @@ "output_cost_per_token": 6e-07, "supports_tool_choice": true }, - "cohere.command-r-plus-v1:0": { - "deprecation_date": "2026-08-19", - "input_cost_per_token": 3e-06, - "litellm_provider": "bedrock", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.5e-05, - "supports_tool_choice": true - }, - "cohere.command-r-v1:0": { - "deprecation_date": "2026-08-19", - "input_cost_per_token": 5e-07, - "litellm_provider": "bedrock", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.5e-06, - "supports_tool_choice": true - }, "cohere.command-text-v14": { "input_cost_per_token": 1.5e-06, "litellm_provider": "bedrock", @@ -42975,32 +42879,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "openrouter/anthropic/claude-opus-4": { - "input_cost_per_image": 0.0048, - "cache_creation_input_token_cost": 1.875e-05, - "cache_creation_input_token_cost_above_1hr": 3e-05, - "cache_read_input_token_cost": 1.5e-06, - "input_cost_per_token": 1.5e-05, - "litellm_provider": "openrouter", - "max_input_tokens": 200000, - "max_output_tokens": 32000, - "max_tokens": 32000, - "mode": "chat", - "output_cost_per_token": 7.5e-05, - "supports_assistant_prefill": true, - "supports_computer_use": true, - "supports_function_calling": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_tool_choice": true, - "supports_vision": true, - "prompt_cache_min_tokens": 1024, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_pdf_input": true, - "supports_response_schema": false, - "supports_web_search": true - }, "openrouter/anthropic/claude-opus-4.1": { "input_cost_per_image": 0.0048, "cache_creation_input_token_cost": 1.875e-05, @@ -43928,27 +43806,6 @@ "supports_vision": true, "supports_web_search": false }, - "openrouter/mistralai/mistral-large-2512": { - "cache_read_input_token_cost": 5.5e-08, - "input_cost_per_image": 0, - "input_cost_per_token": 5.5e-07, - "litellm_provider": "openrouter", - "max_input_tokens": 262144, - "max_output_tokens": 209715, - "max_tokens": 209715, - "mode": "chat", - "output_cost_per_token": 1.65e-06, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": false, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": false - }, "openrouter/mistralai/mistral-7b-instruct": { "input_cost_per_token": 1.3e-07, "litellm_provider": "openrouter", @@ -48806,22 +48663,6 @@ "supports_response_schema": true, "supports_tool_choice": true }, - "us.amazon.nova-premier-v1:0": { - "deprecation_date": "2026-09-14", - "input_cost_per_token": 2.5e-06, - "litellm_provider": "bedrock_converse", - "max_input_tokens": 1000000, - "max_output_tokens": 10000, - "max_tokens": 10000, - "mode": "chat", - "output_cost_per_token": 1.25e-05, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_vision": true, - "cache_read_input_token_cost": 6.25e-07 - }, "us.amazon.nova-pro-v1:0": { "cache_read_input_token_cost": 2e-07, "input_cost_per_token": 8e-07, @@ -71275,15 +71116,6 @@ "output_cost_per_token": 1.6e-06, "source": "https://api.together.ai/v1/models" }, - "vertex_ai/gemini-2.5-flash-native-audio": { - "input_cost_per_audio_token": 3e-06, - "input_cost_per_token": 5e-07, - "litellm_provider": "vertex_ai", - "mode": "realtime", - "output_cost_per_audio_token": 1.2e-05, - "output_cost_per_token": 2e-06, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" - }, "vertex_ai/gemini-2.5-flash-preview-tts": { "input_cost_per_token": 5e-07, "input_cost_per_token_batches": 2.5e-07, @@ -71293,16 +71125,6 @@ "output_cost_per_token": 1e-05, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" }, - "vertex_ai/gemini-3.1-flash-live-preview": { - "input_cost_per_audio_token": 3e-06, - "input_cost_per_second": 8.33333333333e-05, - "input_cost_per_token": 7.5e-07, - "litellm_provider": "vertex_ai", - "mode": "realtime", - "output_cost_per_audio_token": 1.2e-05, - "output_cost_per_token": 4.5e-06, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" - }, "vertex_ai/gemini-3.1-flash-tts-preview": { "input_cost_per_token": 1e-06, "input_cost_per_token_batches": 5e-07, @@ -71335,16 +71157,6 @@ "output_cost_per_token": 9e-06, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" }, - "vertex_ai/gemini-robotics-er-2": { - "cache_read_input_token_cost": 1e-07, - "input_cost_per_token": 1e-06, - "input_cost_per_token_batches": 5e-07, - "litellm_provider": "vertex_ai", - "mode": "chat", - "output_cost_per_token": 5e-06, - "output_cost_per_token_batches": 2.5e-06, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" - }, "vertex_ai/gemma-4-26b-a4b-it": { "cache_read_input_token_cost": 1.5e-08, "input_cost_per_token": 1.5e-07, @@ -71754,14 +71566,6 @@ "output_cost_per_token_batches": 2.42e-06, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, - "azure/eu/o1-preview": { - "cache_read_input_token_cost": 8.25e-06, - "input_cost_per_token": 1.65e-05, - "litellm_provider": "azure", - "mode": "chat", - "output_cost_per_token": 6.6e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" - }, "azure/eu/o3-2025-04-16": { "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 5.5e-07, @@ -72103,14 +71907,6 @@ "output_cost_per_token_batches": 2.42e-06, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, - "azure/us/o1-preview": { - "cache_read_input_token_cost": 8.25e-06, - "input_cost_per_token": 1.65e-05, - "litellm_provider": "azure", - "mode": "chat", - "output_cost_per_token": 6.6e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" - }, "azure/us/o3-deep-research": { "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 2.75e-06, @@ -74456,85 +74252,6 @@ "supports_vision": false, "supports_web_search": false }, - "openrouter/deepseek/deepseek-v4-flash-0731:batch": { - "cache_read_input_token_cost": 3.5e-09, - "input_cost_per_token": 1.1e-07, - "litellm_provider": "openrouter", - "max_input_tokens": 1048576, - "max_output_tokens": 943718, - "max_tokens": 943718, - "mode": "chat", - "output_cost_per_token": 3.3e-07, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": false, - "supports_web_search": false - }, - "openrouter/deepseek/deepseek-v4-flash-0731:free": { - "input_cost_per_token": 0.0, - "litellm_provider": "openrouter", - "max_input_tokens": 1048576, - "max_output_tokens": 393216, - "max_tokens": 393216, - "mode": "chat", - "output_cost_per_token": 0.0, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": false, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": false, - "supports_web_search": false - }, - "openrouter/deepseek/deepseek-v4-flash-vision-exp:batch": { - "cache_read_input_token_cost": 3.5e-09, - "input_cost_per_token": 1.1e-07, - "litellm_provider": "openrouter", - "max_input_tokens": 1048576, - "max_output_tokens": 943718, - "max_tokens": 943718, - "mode": "chat", - "output_cost_per_token": 3.3e-07, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": false - }, - "openrouter/deepseek/deepseek-v4-pro-0813:batch": { - "cache_read_input_token_cost": 2.2e-08, - "input_cost_per_token": 6.6e-07, - "litellm_provider": "openrouter", - "max_input_tokens": 1048576, - "max_output_tokens": 943718, - "max_tokens": 943718, - "mode": "chat", - "output_cost_per_token": 1.98e-06, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": false, - "supports_web_search": false - }, "openrouter/dots-studio/dots-3-note-preview:free": { "deprecation_date": "2026-12-31", "input_cost_per_token": 0.0, @@ -75050,26 +74767,6 @@ "supports_vision": false, "supports_web_search": false }, - "openrouter/kwaipilot/kat-coder-pro-v2": { - "cache_read_input_token_cost": 6e-08, - "input_cost_per_token": 3e-07, - "litellm_provider": "openrouter", - "max_input_tokens": 262144, - "max_output_tokens": 144000, - "max_tokens": 144000, - "mode": "chat", - "output_cost_per_token": 1.2e-06, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": true, - "supports_reasoning": false, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": false, - "supports_web_search": false - }, "openrouter/kwaipilot/kat-coder-pro-v2.5": { "cache_read_input_token_cost": 1.5e-07, "input_cost_per_token": 7.4e-07, @@ -75149,26 +74846,6 @@ "supports_vision": true, "supports_web_search": false }, - "openrouter/meta/muse-glimmer-30b:batch": { - "cache_read_input_token_cost": 2e-08, - "input_cost_per_token": 1.75e-07, - "litellm_provider": "openrouter", - "max_input_tokens": 131072, - "max_output_tokens": 117964, - "max_tokens": 117964, - "mode": "chat", - "output_cost_per_token": 7.5e-07, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": false - }, "openrouter/meta/muse-spark-1.1": { "cache_read_input_token_cost": 1.5e-07, "input_cost_per_token": 1.25e-06, @@ -75307,26 +74984,6 @@ "supports_vision": false, "supports_web_search": false }, - "openrouter/minimax/minimax-m3:batch": { - "cache_read_input_token_cost": 6e-08, - "input_cost_per_token": 3e-07, - "litellm_provider": "openrouter", - "max_input_tokens": 524288, - "max_output_tokens": 471859, - "max_tokens": 471859, - "mode": "chat", - "output_cost_per_token": 1.2e-06, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": false - }, "openrouter/mistralai/codestral-2508:batch": { "cache_read_input_token_cost": 1.5e-08, "input_cost_per_token": 1.5e-07, @@ -76276,25 +75933,6 @@ "supports_vision": true, "supports_web_search": true }, - "openrouter/openai/gpt-oss-120b:batch": { - "input_cost_per_token": 1.5e-07, - "litellm_provider": "openrouter", - "max_input_tokens": 131072, - "max_output_tokens": 117964, - "max_tokens": 117964, - "mode": "chat", - "output_cost_per_token": 6e-07, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": false, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": false, - "supports_web_search": false - }, "openrouter/openai/o3-mini:batch": { "cache_read_input_token_cost": 2.75e-07, "input_cost_per_token": 5.5e-07, @@ -76469,45 +76107,6 @@ "supports_vision": true, "supports_web_search": true }, - "openrouter/qwen/qwen3.5-9b:batch": { - "input_cost_per_token": 1.7e-07, - "litellm_provider": "openrouter", - "max_input_tokens": 262144, - "max_output_tokens": 235929, - "max_tokens": 235929, - "mode": "chat", - "output_cost_per_token": 2.5e-07, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": false, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": false - }, - "openrouter/qwen/qwen3.8-2.4t-a95b:batch": { - "cache_read_input_token_cost": 2.5e-07, - "input_cost_per_token": 2e-06, - "litellm_provider": "openrouter", - "max_input_tokens": 1010000, - "max_output_tokens": 909000, - "max_tokens": 909000, - "mode": "chat", - "output_cost_per_token": 6e-06, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": false, - "supports_web_search": false - }, "openrouter/qwen/qwen3.8-27b:free": { "input_cost_per_token": 0.0, "litellm_provider": "openrouter", @@ -77040,26 +76639,6 @@ "supports_vision": true, "supports_web_search": false }, - "openrouter/thinkingmachines/inkling:batch": { - "cache_read_input_token_cost": 1.7e-07, - "input_cost_per_token": 1e-06, - "litellm_provider": "openrouter", - "max_input_tokens": 524288, - "max_output_tokens": 471859, - "max_tokens": 471859, - "mode": "chat", - "output_cost_per_token": 4.05e-06, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": true, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": false, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": false - }, "openrouter/thinkingmachines/inkling:free": { "input_cost_per_token": 0.0, "litellm_provider": "openrouter", @@ -77181,26 +76760,6 @@ "supports_vision": true, "supports_web_search": true }, - "openrouter/z-ai/glm-5.2:batch": { - "cache_read_input_token_cost": 7e-08, - "input_cost_per_token": 7e-07, - "litellm_provider": "openrouter", - "max_input_tokens": 1048576, - "max_output_tokens": 943718, - "max_tokens": 943718, - "mode": "chat", - "output_cost_per_token": 2.2e-06, - "source": "https://openrouter.ai/api/v1/models", - "supports_audio_input": false, - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": false, - "supports_web_search": false - }, "openrouter/z-ai/glm-5.3-flash:batch": { "cache_read_input_token_cost": 1.2e-08, "input_cost_per_token": 6e-08, From 5035c458fbd25720118386dfb21bbfade4f8ff3c Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 12:05:23 -0700 Subject: [PATCH 002/101] feat(proxy): admin-only /debug/report sharing the bug report environment (#42440) * feat(proxy): add admin-only /debug/report sharing the bug report environment fields Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * feat(proxy): add verbose=true to /debug/report listing every config key with typed values Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): inject auth into /debug/report through Annotated to keep the B008 budget flat Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): bound the verbose config walk, drop nested-list recursion from the safe renderer, regenerate schema.d.ts Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): count pass-through and mcp header maps plus operator-named budget maps in verbose /debug/report, single-exit scalar renderers Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * chore(ui): regenerate schema.d.ts after dropping the verbose query from /debug/report Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: ryan Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- litellm/litellm_core_utils/bug_report.py | 53 +++++++----- litellm/proxy/bug_report_config.py | 29 +++++-- litellm/proxy/common_utils/debug_utils.py | 22 ++++- .../litellm_core_utils/test_bug_report.py | 26 ++++++ .../proxy/common_utils/test_debug_utils.py | 81 ++++++++++++++++++- .../proxy/test_bug_report_config.py | 14 +++- ui/litellm-dashboard/src/lib/http/schema.d.ts | 61 ++++++++++++++ 7 files changed, 255 insertions(+), 31 deletions(-) diff --git a/litellm/litellm_core_utils/bug_report.py b/litellm/litellm_core_utils/bug_report.py index 4a8f4bc65ad..25fddd6a10e 100644 --- a/litellm/litellm_core_utils/bug_report.py +++ b/litellm/litellm_core_utils/bug_report.py @@ -23,16 +23,22 @@ Surface = Literal["sdk", "proxy"] @dataclass(frozen=True, slots=True) -class BugReport: +class EnvironmentReport: surface: Surface - exception_type: str - litellm_frames: tuple[str, ...] litellm_version: str python_version: str + deployment: str | None + config_lines: tuple[str, ...] + + +@dataclass(frozen=True, slots=True) +class BugReport: + environment: EnvironmentReport + exception_type: str + litellm_frames: tuple[str, ...] call_type: str | None custom_llm_provider: str | None stream: bool | None - config_lines: tuple[str, ...] def bug_report_enabled() -> bool: @@ -69,6 +75,22 @@ def allowlisted(value: object, allowed: frozenset[str]) -> str | None: return value if isinstance(value, str) and value in allowed else None +def _deployment(surface: Surface) -> str | None: + if surface == "sdk": + return "pip / Python SDK" + return "Docker" if os.path.exists("/.dockerenv") else None + + +def build_environment_report(*, surface: Surface, config_lines: tuple[str, ...] = ()) -> EnvironmentReport: + return EnvironmentReport( + surface=surface, + litellm_version=litellm_version, + python_version=platform.python_version(), + deployment=_deployment(surface), + config_lines=config_lines, + ) + + def build_bug_report( exc: BaseException, *, @@ -79,20 +101,17 @@ def build_bug_report( config_lines: tuple[str, ...] = (), ) -> BugReport: return BugReport( - surface=surface, + environment=build_environment_report(surface=surface, config_lines=config_lines), exception_type=type(exc).__name__, litellm_frames=_get_litellm_frames(exc), - litellm_version=litellm_version, - python_version=platform.python_version(), call_type=call_type, custom_llm_provider=allowlisted(custom_llm_provider, KNOWN_PROVIDERS), stream=stream if isinstance(stream, bool) else None, - config_lines=config_lines, ) def _domain(report: BugReport) -> str: - if report.surface == "sdk": + if report.environment.surface == "sdk": return "Python SDK: the litellm package itself" if report.custom_llm_provider is not None: return "LLM translation: a specific provider's request or response" @@ -119,11 +138,11 @@ def _description(report: BugReport, frames: tuple[str, ...], config_lines: tuple "```\n\n```\n\n" f"Exception: `{report.exception_type}`\n\n" f"{frame_block}" - f"Surface: {report.surface}\n" + f"Surface: {report.environment.surface}\n" f"Endpoint / call: {report.call_type or 'unknown'}\n" f"Provider: {report.custom_llm_provider or 'unknown'}\n" - f"LiteLLM: {report.litellm_version}\n" - f"Python: {report.python_version}\n" + f"LiteLLM: {report.environment.litellm_version}\n" + f"Python: {report.environment.python_version}\n" f"{stream_line}" f"{config_block}" ) @@ -131,17 +150,13 @@ def _description(report: BugReport, frames: tuple[str, ...], config_lines: tuple def _issue_url(report: BugReport, frames: tuple[str, ...], config_lines: tuple[str, ...]) -> str: deployment: Final[tuple[tuple[str, str], ...]] = ( - (("deployment", "pip / Python SDK"),) - if report.surface == "sdk" - else (("deployment", "Docker"),) - if os.path.exists("/.dockerenv") - else () + () if report.environment.deployment is None else (("deployment", report.environment.deployment),) ) fields: Final = ( ("template", "bug_report.yml"), ("labels", "bug"), ("title", _title(report, frames)), - ("version", report.litellm_version), + ("version", report.environment.litellm_version), ("domain", _domain(report)), ("description", _description(report, frames, config_lines)), ) + deployment @@ -150,7 +165,7 @@ def _issue_url(report: BugReport, frames: tuple[str, ...], config_lines: tuple[s def bug_report_issue_url(report: BugReport) -> str: frames: Final = report.litellm_frames - config_lines: Final = report.config_lines + config_lines: Final = report.environment.config_lines candidates: Final = ( *((frames, config_lines[:count]) for count in range(len(config_lines), -1, -1)), *((frames[index:], ()) for index in range(1, len(frames) + 1)), diff --git a/litellm/proxy/bug_report_config.py b/litellm/proxy/bug_report_config.py index 527be65c9a7..d7b920de4d5 100644 --- a/litellm/proxy/bug_report_config.py +++ b/litellm/proxy/bug_report_config.py @@ -11,7 +11,14 @@ from typing import Final from pydantic import JsonValue, TypeAdapter, ValidationError import litellm -from litellm.litellm_core_utils.bug_report import KNOWN_PROVIDERS, BugReport, allowlisted, build_bug_report +from litellm.litellm_core_utils.bug_report import ( + KNOWN_PROVIDERS, + BugReport, + EnvironmentReport, + allowlisted, + build_bug_report, + build_environment_report, +) from litellm.proxy._types import ConfigGeneralSettings from litellm.router_utils.routing_groups import VALID_ROUTING_STRATEGIES from litellm.types.caching import LiteLLMCacheType @@ -191,6 +198,19 @@ def safe_config_lines(config: Mapping[str, object], general_settings: Mapping[st ) +def _proxy_config_lines() -> tuple[str, ...]: + from litellm.proxy import proxy_server + + return safe_config_lines( + proxy_server.proxy_config.config, + _object_map(proxy_server.general_settings), # pyright: ignore[reportUnknownMemberType, reportUnknownArgumentType] # bare dict global, validated by _object_map + ) + + +def build_proxy_environment_report() -> EnvironmentReport: + return build_environment_report(surface="proxy", config_lines=_proxy_config_lines()) + + def build_proxy_bug_report( exc: BaseException, *, @@ -198,16 +218,11 @@ def build_proxy_bug_report( custom_llm_provider: object = None, stream: object = None, ) -> BugReport: - from litellm.proxy import proxy_server - return build_bug_report( exc, surface="proxy", call_type=call_type, custom_llm_provider=custom_llm_provider, stream=stream, - config_lines=safe_config_lines( - proxy_server.proxy_config.config, - _object_map(proxy_server.general_settings), # pyright: ignore[reportUnknownMemberType, reportUnknownArgumentType] # bare dict global, validated by _object_map - ), + config_lines=_proxy_config_lines(), ) diff --git a/litellm/proxy/common_utils/debug_utils.py b/litellm/proxy/common_utils/debug_utils.py index dc329e55e31..2544321a1b6 100644 --- a/litellm/proxy/common_utils/debug_utils.py +++ b/litellm/proxy/common_utils/debug_utils.py @@ -8,7 +8,7 @@ import sys import tracemalloc from collections import Counter from collections.abc import Mapping, Sequence -from typing import Any, Final, NamedTuple, Protocol, TypedDict +from typing import Annotated, Any, Final, NamedTuple, Protocol, TypedDict from fastapi import APIRouter, Depends, HTTPException, Query from typing_extensions import ReadOnly @@ -16,8 +16,11 @@ from typing_extensions import ReadOnly from litellm import get_secret_str from litellm._logging import verbose_proxy_logger from litellm.constants import PYTHON_GC_THRESHOLD +from litellm.litellm_core_utils.bug_report import EnvironmentReport from litellm.proxy._types import UserAPIKeyAuth from litellm.proxy.auth.user_api_key_auth import user_api_key_auth +from litellm.proxy.bug_report_config import build_proxy_environment_report +from litellm.proxy.common_utils.resource_ownership import is_proxy_admin router: Final = APIRouter() @@ -783,6 +786,23 @@ async def configure_gc_thresholds_endpoint( } +@router.get("/debug/report", include_in_schema=False) +async def get_debug_report( + user_api_key_dict: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], +) -> EnvironmentReport: + """ + The same LiteLLM-owned environment facts the bug report link puts in a GitHub issue: + versions, deployment kind, and config flags whose keys and values LiteLLM defines. + Nothing from the operator's config values, request data, or errors + + Example usage: + curl http://localhost:4000/debug/report -H "Authorization: Bearer sk-1234" + """ + if not is_proxy_admin(user_api_key_dict): + raise HTTPException(status_code=403, detail="Only proxy admins can read /debug/report") + return build_proxy_environment_report() + + @router.get( "/otel-spans", dependencies=[Depends(user_api_key_auth)], diff --git a/tests/test_litellm/litellm_core_utils/test_bug_report.py b/tests/test_litellm/litellm_core_utils/test_bug_report.py index f47361dda2e..62d7090b960 100644 --- a/tests/test_litellm/litellm_core_utils/test_bug_report.py +++ b/tests/test_litellm/litellm_core_utils/test_bug_report.py @@ -21,6 +21,7 @@ from litellm.litellm_core_utils.bug_report import ( bug_report_issue_url, bug_report_notice, build_bug_report, + build_environment_report, should_report_bug, strip_bug_report_notice, ) @@ -202,3 +203,28 @@ def test_oversized_config_is_trimmed_from_the_end_before_any_frame(): assert all(frame in description for frame in report.litellm_frames) assert "general_settings.flag_0000 = true" in description assert "general_settings.flag_0399 = true" not in description + + +def test_issue_url_carries_exactly_the_environment_report_fields(): + report = build_bug_report( + RuntimeError("boom"), + surface="proxy", + config_lines=("litellm_settings.drop_params = true",), + ) + environment = report.environment + query = parse_qs(urlparse(bug_report_issue_url(report)).query) + description = query["description"][0] + + assert environment == build_environment_report( + surface="proxy", config_lines=("litellm_settings.drop_params = true",) + ) + assert query["version"] == [environment.litellm_version] + assert f"Surface: {environment.surface}\n" in description + assert f"LiteLLM: {environment.litellm_version}\n" in description + assert f"Python: {environment.python_version}\n" in description + assert "\nlitellm_settings.drop_params = true\n" in description + assert query.get("deployment") == (None if environment.deployment is None else [environment.deployment]) + + +def test_sdk_environment_reports_the_pip_deployment(): + assert build_environment_report(surface="sdk").deployment == "pip / Python SDK" diff --git a/tests/test_litellm/proxy/common_utils/test_debug_utils.py b/tests/test_litellm/proxy/common_utils/test_debug_utils.py index 163ea530be9..a64c94c2991 100644 --- a/tests/test_litellm/proxy/common_utils/test_debug_utils.py +++ b/tests/test_litellm/proxy/common_utils/test_debug_utils.py @@ -1,16 +1,25 @@ +import json import os import socket +from collections.abc import Iterator, Mapping +from dataclasses import asdict from pathlib import Path import pytest +from fastapi import FastAPI +from fastapi.testclient import TestClient -from litellm.proxy._types import UserAPIKeyAuth +from litellm.proxy import proxy_server +from litellm.proxy._types import LitellmUserRoles, UserAPIKeyAuth +from litellm.proxy.auth.user_api_key_auth import user_api_key_auth +from litellm.proxy.bug_report_config import build_proxy_bug_report from litellm.proxy.common_utils.debug_utils import ( PSUTIL_MISSING_ERROR, _ProcFilesystemProcess, _summary_process_memory, get_memory_summary, ) +from litellm.proxy.common_utils.debug_utils import router as debug_router PAGE_SIZE = 4096 STATM_SIZE_PAGES = 100_000 @@ -67,3 +76,73 @@ async def test_memory_summary_names_the_host_and_worker_that_answered() -> None: assert summary["hostname"] == socket.gethostname() assert summary["worker_pid"] == os.getpid() assert summary["memory"]["ram_usage_mb"] > 0 + + +HOSTILE_CONFIG: Mapping[str, object] = { + "model_list": [ + { + "model_name": "acme-prod-gpt4", + "litellm_params": { + "model": "azure/acme-gpt4o-deployment", + "api_base": "https://acme-eastus.openai.azure.com", + "api_key": "sk-live-secret-1", + }, + } + ], + "litellm_settings": {"drop_params": True, "callbacks": ["langfuse", "acme_hooks.audit_logger"]}, +} + +HOSTILE_GENERAL_SETTINGS: Mapping[str, object] = { + "master_key": "sk-live-secret-master", + "database_url": "postgres://user:hunter2@10.0.0.7/litellm", + "store_model_in_db": True, +} + +HOSTILE_STRINGS = ("acme", "sk-live-secret", "hunter2", "10.0.0.7", "azure.com") + + +@pytest.fixture +def hostile_proxy_config(monkeypatch: pytest.MonkeyPatch) -> Iterator[None]: + previous_config = proxy_server.proxy_config.get_config_state() + proxy_server.proxy_config.update_config_state(config=HOSTILE_CONFIG) + monkeypatch.setattr(proxy_server, "general_settings", dict(HOSTILE_GENERAL_SETTINGS)) + yield + proxy_server.proxy_config.update_config_state(config=previous_config) + + +def _debug_client(caller: UserAPIKeyAuth) -> TestClient: + app = FastAPI() + app.include_router(debug_router) + app.dependency_overrides[user_api_key_auth] = lambda: caller + return TestClient(app) + + +@pytest.mark.parametrize( + "caller", + [ + UserAPIKeyAuth(), + UserAPIKeyAuth(user_role=LitellmUserRoles.INTERNAL_USER), + UserAPIKeyAuth(user_role=LitellmUserRoles.PROXY_ADMIN_VIEW_ONLY), + ], +) +@pytest.mark.usefixtures("hostile_proxy_config") +def test_debug_report_refuses_everyone_but_proxy_admins(caller: UserAPIKeyAuth) -> None: + response = _debug_client(caller).get("/debug/report") + + assert response.status_code == 403, response.text + assert "litellm_version" not in response.text + + +@pytest.mark.usefixtures("hostile_proxy_config") +def test_debug_report_returns_what_the_bug_report_link_carries_and_nothing_from_the_operator() -> None: + response = _debug_client(UserAPIKeyAuth(user_role=LitellmUserRoles.PROXY_ADMIN)).get("/debug/report") + + assert response.status_code == 200, response.text + assert response.json() == json.loads(json.dumps(asdict(build_proxy_bug_report(RuntimeError("boom")).environment))) + assert response.json()["config_lines"] == [ + "general_settings.store_model_in_db = true", + "litellm_settings.drop_params = true", + "litellm_settings.callbacks = [langfuse]", + "model_list[*].provider = [azure]", + ] + assert not any(hostile in response.text for hostile in HOSTILE_STRINGS), response.text diff --git a/tests/test_litellm/proxy/test_bug_report_config.py b/tests/test_litellm/proxy/test_bug_report_config.py index 06bca8c66fb..6cffa55781e 100644 --- a/tests/test_litellm/proxy/test_bug_report_config.py +++ b/tests/test_litellm/proxy/test_bug_report_config.py @@ -5,7 +5,7 @@ from collections.abc import Iterator, Mapping import pytest from litellm.proxy import proxy_server -from litellm.proxy.bug_report_config import build_proxy_bug_report, safe_config_lines +from litellm.proxy.bug_report_config import build_proxy_bug_report, build_proxy_environment_report, safe_config_lines CUSTOMER_STRINGS = ( "acme", @@ -193,6 +193,14 @@ def loaded_proxy_config(monkeypatch: pytest.MonkeyPatch) -> Iterator[None]: def test_build_proxy_bug_report_reads_the_loaded_proxy_config(): report = build_proxy_bug_report(RuntimeError("boom"), stream=False) - assert report.surface == "proxy" + assert report.environment.surface == "proxy" assert report.stream is False - assert report.config_lines == safe_config_lines(CUSTOMER_CONFIG, CUSTOMER_GENERAL_SETTINGS) + assert report.environment.config_lines == safe_config_lines(CUSTOMER_CONFIG, CUSTOMER_GENERAL_SETTINGS) + + +@pytest.mark.usefixtures("loaded_proxy_config") +def test_proxy_environment_report_matches_the_bug_report_environment(): + environment = build_proxy_environment_report() + + assert environment == build_proxy_bug_report(RuntimeError("boom")).environment + assert environment.config_lines == safe_config_lines(CUSTOMER_CONFIG, CUSTOMER_GENERAL_SETTINGS) diff --git a/ui/litellm-dashboard/src/lib/http/schema.d.ts b/ui/litellm-dashboard/src/lib/http/schema.d.ts index 68d3ab364d6..a0fec542acf 100644 --- a/ui/litellm-dashboard/src/lib/http/schema.d.ts +++ b/ui/litellm-dashboard/src/lib/http/schema.d.ts @@ -4356,6 +4356,31 @@ export interface paths { patch?: never; trace?: never; }; + "/debug/report": { + parameters: { + query?: never; + header?: never; + path?: never; + cookie?: never; + }; + /** + * Get Debug Report + * @description The same LiteLLM-owned environment facts the bug report link puts in a GitHub issue: + * versions, deployment kind, and config flags whose keys and values LiteLLM defines. + * Nothing from the operator's config values, request data, or errors + * + * Example usage: + * curl http://localhost:4000/debug/report -H "Authorization: Bearer sk-1234" + */ + get: operations["get_debug_report_debug_report_get"]; + put?: never; + post?: never; + delete?: never; + options?: never; + head?: never; + patch?: never; + trace?: never; + }; "/delete/allowed_ip": { parameters: { query?: never; @@ -28779,6 +28804,22 @@ export interface components { /** Template Id */ template_id: string; }; + /** EnvironmentReport */ + EnvironmentReport: { + /** Config Lines */ + config_lines: string[]; + /** Deployment */ + deployment: string | null; + /** Litellm Version */ + litellm_version: string; + /** Python Version */ + python_version: string; + /** + * Surface + * @enum {string} + */ + surface: "sdk" | "proxy"; + }; /** ErrorResponse */ ErrorResponse: { /** @@ -48592,6 +48633,26 @@ export interface operations { }; }; }; + get_debug_report_debug_report_get: { + parameters: { + query?: never; + header?: never; + path?: never; + cookie?: never; + }; + requestBody?: never; + responses: { + /** @description Successful Response */ + 200: { + headers: { + [name: string]: unknown; + }; + content: { + "application/json": components["schemas"]["EnvironmentReport"]; + }; + }; + }; + }; delete_allowed_ip_delete_allowed_ip_post: { parameters: { query?: never; From 64456ce10311d52f32c88efa06e8bba65141d3a3 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 14:12:20 -0500 Subject: [PATCH 003/101] fix(aws_secret_manager_v2): restore secret scheduled for deletion instead of failing CreateSecret (#42454) * fix(aws_secret_manager_v2): restore secret scheduled for deletion instead of failing CreateSecret Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(aws_secret_manager_v2): reapply CreateSecret metadata and reschedule deletion when in-place restore fails Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: yassin Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- .../secret_managers/aws_secret_manager_v2.py | 131 ++++++++++--- .../test_aws_secret_manager_rotation.py | 178 +++++++++++++++++- 2 files changed, 286 insertions(+), 23 deletions(-) diff --git a/litellm/secret_managers/aws_secret_manager_v2.py b/litellm/secret_managers/aws_secret_manager_v2.py index 0fb59105b5f..3e9f4e259d5 100644 --- a/litellm/secret_managers/aws_secret_manager_v2.py +++ b/litellm/secret_managers/aws_secret_manager_v2.py @@ -16,6 +16,8 @@ Requires: import json import os +from collections.abc import Mapping +from types import MappingProxyType from typing import TYPE_CHECKING, Final import httpx @@ -294,32 +296,13 @@ class AWSSecretsManagerV2(BaseAWSLLM, BaseSecretManager): raise ValueError("Tags must be a dict or list of {Key, Value} pairs") data["Tags"] = tags_list - endpoint_url, headers, body = self._prepare_request( - action="CreateSecret", + create_response: Final = await self._async_create_or_restore_secret( secret_name=secret_name, - secret_value=secret_value, - optional_params=optional_params, request_data=data, + optional_params=optional_params, + timeout=timeout, ) - async_client: Final = get_async_httpx_client( - llm_provider=httpxSpecialProvider.SecretManager, - params={"timeout": timeout}, - ) - - try: - response: Final = await async_client.post( - url=endpoint_url, - headers=headers, - data=body.decode("utf-8"), - ) - response.raise_for_status() - create_response: Final = response.json() - except httpx.HTTPStatusError as err: - raise ValueError(f"HTTP error occurred: {err.response.text}") - except httpx.TimeoutException: - raise ValueError("Timeout error occurred") - if self.replica_regions: try: await self.async_replicate_secret( @@ -343,6 +326,110 @@ class AWSSecretsManagerV2(BaseAWSLLM, BaseSecretManager): return create_response + async def _async_create_or_restore_secret( + self, + secret_name: str, + request_data: Mapping[str, object], + optional_params: dict | None, + timeout: float | httpx.Timeout | None, + ) -> dict[str, object]: + try: + return await self._async_post_action( + action="CreateSecret", + secret_name=secret_name, + request_data=request_data, + optional_params=optional_params, + timeout=timeout, + ) + except ValueError: + if not await self._async_is_scheduled_for_deletion( + secret_name=secret_name, + optional_params=optional_params, + timeout=timeout, + ): + raise + + verbose_logger.info( + "Secret %s is scheduled for deletion, restoring and updating in place (RestoreSecret + UpdateSecret)", + secret_name, + ) + await self._async_post_action( + action="RestoreSecret", + secret_name=secret_name, + request_data=None, + optional_params=optional_params, + timeout=timeout, + ) + update_data: Final = MappingProxyType( + {("SecretId" if key == "Name" else key): value for key, value in request_data.items() if key != "Tags"} + ) + tags: Final = request_data.get("Tags") + try: + updated: Final = await self._async_post_action( + action="UpdateSecret", + secret_name=secret_name, + request_data=update_data, + optional_params=optional_params, + timeout=timeout, + ) + if tags is not None: + await self._async_post_action( + action="TagResource", + secret_name=secret_name, + request_data=MappingProxyType({"SecretId": secret_name, "Tags": tags}), + optional_params=optional_params, + timeout=timeout, + ) + except ValueError: + await self.async_delete_secret(secret_name=secret_name, optional_params=optional_params, timeout=timeout) + raise + return updated + + async def _async_is_scheduled_for_deletion( + self, + secret_name: str, + optional_params: dict | None, + timeout: float | httpx.Timeout | None, + ) -> bool: + try: + described: Final = await self._async_post_action( + action="DescribeSecret", + secret_name=secret_name, + request_data=None, + optional_params=optional_params, + timeout=timeout, + ) + except ValueError: + return False + return described.get("DeletedDate") is not None + + async def _async_post_action( + self, + action: str, + secret_name: str, + request_data: Mapping[str, object] | None, + optional_params: dict | None, + timeout: float | httpx.Timeout | None, + ) -> dict[str, object]: + endpoint_url, headers, body = self._prepare_request( + action=action, + secret_name=secret_name, + optional_params=optional_params, + request_data=dict(request_data) if request_data is not None else None, + ) + async_client: Final = get_async_httpx_client( + llm_provider=httpxSpecialProvider.SecretManager, + params={"timeout": timeout}, + ) + try: + response: Final = await async_client.post(url=endpoint_url, headers=headers, data=body.decode("utf-8")) + response.raise_for_status() + return response.json() + except httpx.HTTPStatusError as err: + raise ValueError(f"HTTP error occurred: {err.response.text}") + except httpx.TimeoutException: + raise ValueError("Timeout error occurred") + async def async_replicate_secret( self, secret_name: str, diff --git a/tests/test_litellm/secret_managers/test_aws_secret_manager_rotation.py b/tests/test_litellm/secret_managers/test_aws_secret_manager_rotation.py index 4a4cec6bf77..af1380f6fd1 100644 --- a/tests/test_litellm/secret_managers/test_aws_secret_manager_rotation.py +++ b/tests/test_litellm/secret_managers/test_aws_secret_manager_rotation.py @@ -1,11 +1,17 @@ -from collections.abc import Mapping +import json +from collections.abc import Iterator, Mapping +from contextlib import contextmanager from dataclasses import dataclass, replace from types import MappingProxyType from typing import Final, TypeAlias +import httpx import pytest +import litellm +from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler from litellm.secret_managers.aws_secret_manager_v2 import AWSSecretsManagerV2 +from litellm.types.llms.custom_http import httpxSpecialProvider OptionalParams: TypeAlias = Mapping[str, object] | None @@ -204,3 +210,173 @@ async def test_rotate_secret_different_names_persists_requested_value_and_delete assert manager.storage.values[new_name] == new_value assert current_name not in manager.storage.values assert manager.storage.values[unrelated_secret_name] == unrelated_value + + +@dataclass(frozen=True, slots=True) +class FakeSecretsManagerState: + live: Mapping[str, str] + scheduled_for_deletion: frozenset[str] = frozenset() + actions: tuple[str, ...] = () + descriptions: Mapping[str, str] = MappingProxyType({}) + failing_actions: frozenset[str] = frozenset() + + +class FakeSecretsManagerService: + def __init__(self, state: FakeSecretsManagerState) -> None: + self.state = state + + def handle(self, request: httpx.Request) -> httpx.Response: + action: Final = request.headers["X-Amz-Target"].removeprefix("secretsmanager.") + body: Final = json.loads(request.content) + name: Final = str(body.get("Name") or body.get("SecretId")) + self.state = replace(self.state, actions=(*self.state.actions, f"{action}:{name}")) + if action in self.state.failing_actions: + return self._error("InternalServiceError", f"injected failure for {action}") + match action: + case "CreateSecret": + if name in self.state.live: + return self._error("ResourceExistsException", f"The secret {name} already exists") + self.state = replace( + self.state, + live=MappingProxyType({**self.state.live, name: str(body["SecretString"])}), + descriptions=MappingProxyType({**self.state.descriptions, name: str(body.get("Description", ""))}), + ) + return httpx.Response(200, json={"ARN": f"arn:fake:{name}", "Name": name}) + case "UpdateSecret": + if name in self.state.scheduled_for_deletion: + return self._error( + "InvalidRequestException", + "You can't perform this operation on the secret because it was marked for deletion.", + ) + self.state = replace( + self.state, + live=MappingProxyType({**self.state.live, name: str(body["SecretString"])}), + descriptions=MappingProxyType({**self.state.descriptions, name: str(body.get("Description", ""))}), + ) + return httpx.Response(200, json={"ARN": f"arn:fake:{name}", "Name": name}) + case "DescribeSecret": + if name not in self.state.live: + return self._error("ResourceNotFoundException", "Secrets Manager can't find the specified secret.") + deleted: Final = "2026-01-01T00:00:00Z" if name in self.state.scheduled_for_deletion else None + return httpx.Response(200, json={"ARN": f"arn:fake:{name}", "Name": name, "DeletedDate": deleted}) + case "RestoreSecret": + self.state = replace(self.state, scheduled_for_deletion=self.state.scheduled_for_deletion - {name}) + return httpx.Response(200, json={"ARN": f"arn:fake:{name}", "Name": name}) + case "PutSecretValue": + if name in self.state.scheduled_for_deletion: + return self._error( + "InvalidRequestException", + "You can't perform this operation on the secret because it was marked for deletion.", + ) + self.state = replace( + self.state, live=MappingProxyType({**self.state.live, name: str(body["SecretString"])}) + ) + return httpx.Response(200, json={"ARN": f"arn:fake:{name}", "Name": name}) + case "GetSecretValue": + if name not in self.state.live or name in self.state.scheduled_for_deletion: + return self._error("ResourceNotFoundException", "Secrets Manager can't find the specified secret.") + return httpx.Response(200, json={"SecretString": self.state.live[name]}) + case "DeleteSecret": + self.state = replace(self.state, scheduled_for_deletion=self.state.scheduled_for_deletion | {name}) + return httpx.Response(200, json={"ARN": f"arn:fake:{name}", "Name": name}) + return self._error("UnsupportedAction", action) + + @staticmethod + def _error(error_type: str, message: str) -> httpx.Response: + return httpx.Response(400, json={"__type": error_type, "message": message}) + + +@contextmanager +def fake_secrets_manager(monkeypatch: pytest.MonkeyPatch) -> Iterator[FakeSecretsManagerService]: + monkeypatch.setenv("AWS_ACCESS_KEY_ID", "synthetic-access-key") + monkeypatch.setenv("AWS_SECRET_ACCESS_KEY", "synthetic-secret-key") + monkeypatch.setenv("AWS_REGION_NAME", "us-east-1") + service: Final = FakeSecretsManagerService(FakeSecretsManagerState(live=MappingProxyType({}))) + cache_key: Final = "async_httpx_clienttimeout_None" + httpxSpecialProvider.SecretManager + litellm.in_memory_llm_clients_cache.set_cache( + key=cache_key, + value=AsyncHTTPHandler(transport=httpx.MockTransport(service.handle)), + ) + try: + yield service + finally: + litellm.in_memory_llm_clients_cache.delete_cache( + litellm.in_memory_llm_clients_cache.update_cache_key_with_event_loop(cache_key) + ) + + +@pytest.mark.asyncio +async def test_rotate_secret_back_to_name_inside_recovery_window_restores_and_stores_new_value( + monkeypatch: pytest.MonkeyPatch, +) -> None: + alias_a: Final = "synthetic/alias-a" + alias_b: Final = "synthetic/alias-b" + with fake_secrets_manager(monkeypatch) as fake: + manager: Final = AWSSecretsManagerV2(aws_region_name="us-east-1") + await manager.async_write_secret(secret_name=alias_a, secret_value="value-1") + await manager.async_rotate_secret( + current_secret_name=alias_a, new_secret_name=alias_b, new_secret_value="value-2" + ) + assert alias_a in fake.state.scheduled_for_deletion + + await manager.async_rotate_secret( + current_secret_name=alias_b, new_secret_name=alias_a, new_secret_value="value-3" + ) + + assert await manager.async_read_secret(secret_name=alias_a) == "value-3" + assert await manager.async_read_secret(secret_name=alias_b) is None + assert fake.state.scheduled_for_deletion == frozenset({alias_b}) + assert fake.state.descriptions[alias_a] == f"Rotated from {alias_b}" + + +@pytest.mark.asyncio +async def test_write_secret_to_name_inside_recovery_window_reschedules_deletion_when_update_fails( + monkeypatch: pytest.MonkeyPatch, +) -> None: + alias: Final = "synthetic/deleted-alias" + with fake_secrets_manager(monkeypatch) as fake: + manager: Final = AWSSecretsManagerV2(aws_region_name="us-east-1") + await manager.async_write_secret(secret_name=alias, secret_value="value-1") + await manager.async_delete_secret(secret_name=alias, recovery_window_in_days=7) + fake.state = replace(fake.state, failing_actions=frozenset({"UpdateSecret"})) + + with pytest.raises(ValueError, match="injected failure for UpdateSecret"): + await manager.async_write_secret(secret_name=alias, secret_value="value-2") + + assert fake.state.scheduled_for_deletion == frozenset({alias}) + assert fake.state.live[alias] == "value-1" + + +@pytest.mark.asyncio +async def test_write_secret_to_name_inside_recovery_window_restores_and_stores_new_value( + monkeypatch: pytest.MonkeyPatch, +) -> None: + alias: Final = "synthetic/deleted-alias" + with fake_secrets_manager(monkeypatch) as fake: + manager: Final = AWSSecretsManagerV2(aws_region_name="us-east-1") + await manager.async_write_secret(secret_name=alias, secret_value="value-1") + await manager.async_delete_secret(secret_name=alias, recovery_window_in_days=7) + + assert await manager.async_write_secret(secret_name=alias, secret_value="value-2") == { + "ARN": f"arn:fake:{alias}", + "Name": alias, + } + + assert await manager.async_read_secret(secret_name=alias) == "value-2" + assert fake.state.scheduled_for_deletion == frozenset() + + +@pytest.mark.asyncio +async def test_write_secret_to_live_existing_name_still_fails_without_overwriting( + monkeypatch: pytest.MonkeyPatch, +) -> None: + alias: Final = "synthetic/live-alias" + with fake_secrets_manager(monkeypatch) as fake: + manager: Final = AWSSecretsManagerV2(aws_region_name="us-east-1") + await manager.async_write_secret(secret_name=alias, secret_value="value-1") + + with pytest.raises(ValueError, match="ResourceExistsException"): + await manager.async_write_secret(secret_name=alias, secret_value="value-2") + + assert await manager.async_read_secret(secret_name=alias) == "value-1" + assert f"RestoreSecret:{alias}" not in fake.state.actions From 05d7fb24bd1e9ced3a5877c82e2de00367744037 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 12:16:56 -0700 Subject: [PATCH 004/101] feat(rust): add python-compat crate for Python data formats (#42510) * feat(rust): add python-compat crate for Python data formats Add litellm-python-compat, a PyO3-free crate that reproduces the Python data formats LiteLLM persists, so Rust readers and writers can interoperate with state written by the Python proxy: - literal::literal_eval: a linear recursive-descent port of ast.literal_eval (prefixes, escapes, implicit concatenation, numeric underscores and radixes, single unary sign, real +/- complex with 3.14 mixed-mode rules, set(), Python-equality key dedup) - repr::{repr, to_str}: byte-exact repr()/str(), with a printable table generated from CPython's str.isprintable (Unicode 16.0.0) - json::{dumps, from_json, to_json}: json.dumps defaults and the json.loads mapping - pickle::{loads, dumps}: plain-data pickles via serde-pickle's serde interface, which keeps dict insertion order - truthy::truthy: bool() for plain data Tests replay fixtures generated by CPython 3.14 (values across every format and pickle protocol 0-5, plus 154 literal_eval source texts). Accepted divergences are pinned in a KNOWN table that fails once one starts matching. A criterion bench covers each format and literal_eval cost by nesting depth, guarding the linear parse: the py_literal grammar doubled per nested bracket (105 ms at 16 nested dicts; 19 us at 128 now). Co-Authored-By: Claude Opus 5 * refactor(rust): split python-compat modules and harden the pickle verifier - Disable class resolution in scripts/verify_rust_pickles.py, and truncate the export file once instead of removing and appending to it, so the verifier cannot be pointed at a pre-created file whose rows execute code through pickle.loads - Move Error to error.rs and Value to value.rs, leaving lib.rs as the crate overview, module list and MAX_DEPTH - Move the generator and verifier to scripts/, beside the Unicode table generator, leaving tests/ to the Rust tests - Group the bench by measured surface, give every case a Throughput so criterion reports bytes per second, and document baseline comparison Co-Authored-By: Claude Opus 5 --------- Co-authored-by: Yujong Lee Co-authored-by: Claude Opus 5 --- litellm-rust/Cargo.lock | 15 + litellm-rust/crates/python-compat/AGENTS.md | 23 + litellm-rust/crates/python-compat/Cargo.toml | 24 + .../crates/python-compat/benches/formats.rs | 111 + .../python-compat/generated/nonprintable.rs | 745 ++++++ .../python-compat/generated/values.json | 2164 +++++++++++++++++ .../scripts/generate_fixtures.py | 352 +++ .../scripts/generate_nonprintable.py | 35 + .../scripts/verify_rust_pickles.py | 43 + .../crates/python-compat/src/error.rs | 25 + litellm-rust/crates/python-compat/src/json.rs | 168 ++ litellm-rust/crates/python-compat/src/lib.rs | 39 + .../crates/python-compat/src/literal.rs | 745 ++++++ .../crates/python-compat/src/pickle.rs | 187 ++ litellm-rust/crates/python-compat/src/repr.rs | 237 ++ .../crates/python-compat/src/truthy.rs | 18 + .../crates/python-compat/src/value.rs | 53 + .../crates/python-compat/tests/fixtures.rs | 343 +++ .../crates/python-compat/tests/limits.rs | 122 + 19 files changed, 5449 insertions(+) create mode 100644 litellm-rust/crates/python-compat/AGENTS.md create mode 100644 litellm-rust/crates/python-compat/Cargo.toml create mode 100644 litellm-rust/crates/python-compat/benches/formats.rs create mode 100644 litellm-rust/crates/python-compat/generated/nonprintable.rs create mode 100644 litellm-rust/crates/python-compat/generated/values.json create mode 100644 litellm-rust/crates/python-compat/scripts/generate_fixtures.py create mode 100644 litellm-rust/crates/python-compat/scripts/generate_nonprintable.py create mode 100644 litellm-rust/crates/python-compat/scripts/verify_rust_pickles.py create mode 100644 litellm-rust/crates/python-compat/src/error.rs create mode 100644 litellm-rust/crates/python-compat/src/json.rs create mode 100644 litellm-rust/crates/python-compat/src/lib.rs create mode 100644 litellm-rust/crates/python-compat/src/literal.rs create mode 100644 litellm-rust/crates/python-compat/src/pickle.rs create mode 100644 litellm-rust/crates/python-compat/src/repr.rs create mode 100644 litellm-rust/crates/python-compat/src/truthy.rs create mode 100644 litellm-rust/crates/python-compat/src/value.rs create mode 100644 litellm-rust/crates/python-compat/tests/fixtures.rs create mode 100644 litellm-rust/crates/python-compat/tests/limits.rs diff --git a/litellm-rust/Cargo.lock b/litellm-rust/Cargo.lock index 76004c5d978..ea63746d56d 100644 --- a/litellm-rust/Cargo.lock +++ b/litellm-rust/Cargo.lock @@ -3072,6 +3072,21 @@ dependencies = [ "wiremock", ] +[[package]] +name = "litellm-python-compat" +version = "0.1.0" +dependencies = [ + "criterion", + "hex", + "num-bigint 0.4.8", + "num-traits", + "rstest", + "serde", + "serde-pickle", + "serde_json", + "thiserror 2.0.19", +] + [[package]] name = "litellm-secrets" version = "0.1.0" diff --git a/litellm-rust/crates/python-compat/AGENTS.md b/litellm-rust/crates/python-compat/AGENTS.md new file mode 100644 index 00000000000..0869568d33b --- /dev/null +++ b/litellm-rust/crates/python-compat/AGENTS.md @@ -0,0 +1,23 @@ +- Pure Python *data formats* in Rust, for state Python LiteLLM writes and Rust must read or write byte-compatibly + - No PyO3, no live objects: truthiness, `__str__`, descriptors of real Python objects belong to `python-bridge`'s coercion layer + - Format *choices* stay with callers: the `{timestamp, response}` envelope, diskcache modes, and the cache-key recipe live in the cache crates and only call into this crate +- Intended users + - `cache-response` codec: reading `str(dict)` values Python's sync Redis path writes (`literal_eval`) + - `cache-disk`: diskcache's pickled values (`pickle`), falsy-is-miss (`truthy`) + - Cache-key derivation: sha256 over `str(value)` must match Python byte for byte (`repr::to_str`) + - Byte-identical writes where Python compares raw values (`json::dumps`, `repr`) +- Relation to [`py_literal`](https://docs.rs/py_literal/latest/py_literal/): replaced, do not reintroduce + - Its pest grammar backtracks: parse time doubles per nested `[`/`{` (105 ms at depth 16); ours is linear (19 µs at depth 128) + - Its formatter is not `repr` (`2e-1`, always single quotes, escapes non-ASCII); it also lost `-0.0`, `(1+2j)`, `set()` + - `cache-response` and `cache-disk` still depend on it; migrate them here +- Relation to [`serde-pickle`](https://docs.rs/serde-pickle/latest/serde_pickle/): the pickle codec, used only through its serde interface + - Never `serde_pickle::Value`: its `BTreeMap` dicts reorder keys + - Accepted limits: ints beyond i64, `tuple`/`set`/`frozenset` decode as lists, class references (`GLOBAL`/`REDUCE`) fail; writes protocol 3 +- Every behavior is pinned by CPython output, not by reasoning; everything under `generated/` is script output, never hand-edited + - Regenerate `generated/values.json` with `scripts/generate_fixtures.py`; add a corpus row before changing behavior + - Divergences go in `KNOWN` in `tests/fixtures.rs` with a reason; an entry that starts matching fails until deleted + - Regenerate `generated/nonprintable.rs` with `scripts/generate_nonprintable.py` when the target Python's Unicode version changes + - `scripts/verify_rust_pickles.py` checks CPython reads Rust pickles, with class resolution disabled; CI does not run Python +- Decoders recurse, so they reject nesting beyond `MAX_DEPTH` for stack safety: deliberately stricter than CPython, whose parser takes ~200 levels and whose unpickler has no limit (pinned as `nested_150`) + - Formatters (`repr`, `json`) are unbounded; values from the decoders are already capped, a hand-built `Value` is the caller's responsibility + - `literal_eval` must stay linear in depth: `tests/limits.rs` times the deepest parse, `benches/formats.rs` measures the curve but is manual, since CI runs no Rust bench diff --git a/litellm-rust/crates/python-compat/Cargo.toml b/litellm-rust/crates/python-compat/Cargo.toml new file mode 100644 index 00000000000..2ab6fb29843 --- /dev/null +++ b/litellm-rust/crates/python-compat/Cargo.toml @@ -0,0 +1,24 @@ +[package] +name = "litellm-python-compat" +version = "0.1.0" +edition.workspace = true +license.workspace = true +repository.workspace = true +description = "Python data formats (repr, literal_eval, json.dumps, pickle) reproduced for interop with persisted LiteLLM state" + +[dependencies] +num-bigint = "0.4" +num-traits = "0.2" +serde.workspace = true +serde-pickle = "1.2" +serde_json = { workspace = true, features = ["preserve_order"] } +thiserror.workspace = true + +[dev-dependencies] +criterion.workspace = true +hex = "0.4" +rstest.workspace = true + +[[bench]] +name = "formats" +harness = false diff --git a/litellm-rust/crates/python-compat/benches/formats.rs b/litellm-rust/crates/python-compat/benches/formats.rs new file mode 100644 index 00000000000..f0b83cb1658 --- /dev/null +++ b/litellm-rust/crates/python-compat/benches/formats.rs @@ -0,0 +1,111 @@ +//! Throughput of each format on a cached chat completion, and `literal_eval` cost by nesting. +//! +//! Run one group with `cargo bench -p litellm-python-compat -- cached_completion`, and compare +//! against a stored run with `--save-baseline ` / `--baseline `. +//! +//! `literal_eval/nesting` guards against backtracking: the `py_literal` grammar this parser +//! replaced doubled its time per nested `[` or `{` (105 ms at depth 16), so cost must stay +//! linear in depth for every container shape. + +use std::{hint::black_box, time::Duration}; + +use criterion::{ + BatchSize, BenchmarkGroup, BenchmarkId, Criterion, Throughput, criterion_group, criterion_main, + measurement::WallTime, +}; +use litellm_python_compat::{Value, json, literal::literal_eval, pickle, repr::repr}; + +/// `str(entry)` for the `{timestamp, response}` envelope Python's sync Redis path writes. +fn cached_completion() -> String { + let choices: Vec = (0..4) + .map(|index| { + format!( + "{{'finish_reason': 'stop', 'index': {index}, 'message': {{'content': \ + 'Benchmarks compare the same workload under controlled conditions, so a \ + change in time reflects the code rather than the environment. café 日本 \ + {index}', 'role': 'assistant', 'tool_calls': None, 'function_call': None}}, \ + 'logprobs': None}}" + ) + }) + .collect(); + format!( + "{{'timestamp': 1726000000.123, 'response': {{'id': 'chatcmpl-9x1', 'created': \ + 1726000000, 'model': 'gpt-4o-2024-08-06', 'object': 'chat.completion', \ + 'system_fingerprint': 'fp_1', 'choices': [{}], 'usage': {{'completion_tokens': 120, \ + 'prompt_tokens': 42, 'total_tokens': 162, 'completion_tokens_details': None}}}}}}", + choices.join(", ") + ) +} + +/// Every text format, measured against the source bytes it reads or writes. +fn text_formats(group: &mut BenchmarkGroup<'_, WallTime>, text: &str, value: &Value) { + group.throughput(Throughput::Bytes(text.len() as u64)); + group.bench_function("literal_eval", |bencher| { + bencher.iter(|| literal_eval(black_box(text))) + }); + group.bench_function("repr", |bencher| bencher.iter(|| repr(black_box(value)))); + group.bench_function("json_dumps", |bencher| { + bencher.iter(|| json::dumps(black_box(value))) + }); + group.bench_function("to_json", |bencher| { + bencher.iter(|| json::to_json(black_box(value))) + }); +} + +/// Pickle, measured against its own encoding rather than the source text. +fn binary_formats(group: &mut BenchmarkGroup<'_, WallTime>, value: &Value, pickled: &[u8]) { + group.throughput(Throughput::Bytes(pickled.len() as u64)); + group.bench_function("pickle_dumps", |bencher| { + bencher.iter(|| pickle::dumps(black_box(value))) + }); + group.bench_function("pickle_loads", |bencher| { + bencher.iter(|| pickle::loads(black_box(pickled))) + }); +} + +fn formats(c: &mut Criterion) { + let text = cached_completion(); + let value = literal_eval(&text).expect("benchmark payload is a literal"); + let pickled = pickle::dumps(&value).expect("benchmark payload pickles"); + let dumped = json::dumps(&value).expect("benchmark payload is JSON serializable"); + + let mut group = c.benchmark_group("cached_completion"); + text_formats(&mut group, &text, &value); + binary_formats(&mut group, &value, &pickled); + // `from_json` consumes its input, so each iteration gets a freshly parsed one. + group.throughput(Throughput::Bytes(dumped.len() as u64)); + group.bench_function("from_json", |bencher| { + bencher.iter_batched( + || serde_json::from_str::(&dumped).expect("dumps output parses"), + json::from_json, + BatchSize::SmallInput, + ) + }); + group.finish(); +} + +/// One nesting level of each container shape, as `(name, open, close)`. +const SHAPES: [(&str, &str, &str); 3] = [ + ("list", "[", "]"), + ("dict", "{'a': ", "}"), + ("tuple", "(", ",)"), +]; + +fn literal_nesting(c: &mut Criterion) { + let mut group = c.benchmark_group("literal_eval/nesting"); + group.sample_size(10); + group.measurement_time(Duration::from_secs(3)); + for depth in [4, 16, 64, 128] { + for (shape, open, close) in SHAPES { + let text = format!("{}1{}", open.repeat(depth), close.repeat(depth)); + group.throughput(Throughput::Bytes(text.len() as u64)); + group.bench_with_input(BenchmarkId::new(shape, depth), &text, |bencher, text| { + bencher.iter(|| literal_eval(black_box(text))) + }); + } + } + group.finish(); +} + +criterion_group!(benches, formats, literal_nesting); +criterion_main!(benches); diff --git a/litellm-rust/crates/python-compat/generated/nonprintable.rs b/litellm-rust/crates/python-compat/generated/nonprintable.rs new file mode 100644 index 00000000000..a044210f07d --- /dev/null +++ b/litellm-rust/crates/python-compat/generated/nonprintable.rs @@ -0,0 +1,745 @@ +// Generated by scripts/generate_nonprintable.py from Python 3.14.7 +// (Unicode 16.0.0). Do not edit by hand. + +pub(crate) const UNICODE_VERSION: &str = "16.0.0"; + +/// Inclusive code point ranges for which Python's `str.isprintable()` is false. +pub(crate) const NONPRINTABLE: [(u32, u32); 737] = [ + (0x0000, 0x001F), + (0x007F, 0x00A0), + (0x00AD, 0x00AD), + (0x0378, 0x0379), + (0x0380, 0x0383), + (0x038B, 0x038B), + (0x038D, 0x038D), + (0x03A2, 0x03A2), + (0x0530, 0x0530), + (0x0557, 0x0558), + (0x058B, 0x058C), + (0x0590, 0x0590), + (0x05C8, 0x05CF), + (0x05EB, 0x05EE), + (0x05F5, 0x0605), + (0x061C, 0x061C), + (0x06DD, 0x06DD), + (0x070E, 0x070F), + (0x074B, 0x074C), + (0x07B2, 0x07BF), + (0x07FB, 0x07FC), + (0x082E, 0x082F), + (0x083F, 0x083F), + (0x085C, 0x085D), + (0x085F, 0x085F), + (0x086B, 0x086F), + (0x088F, 0x0896), + (0x08E2, 0x08E2), + (0x0984, 0x0984), + (0x098D, 0x098E), + (0x0991, 0x0992), + (0x09A9, 0x09A9), + (0x09B1, 0x09B1), + (0x09B3, 0x09B5), + (0x09BA, 0x09BB), + (0x09C5, 0x09C6), + (0x09C9, 0x09CA), + (0x09CF, 0x09D6), + (0x09D8, 0x09DB), + (0x09DE, 0x09DE), + (0x09E4, 0x09E5), + (0x09FF, 0x0A00), + (0x0A04, 0x0A04), + (0x0A0B, 0x0A0E), + (0x0A11, 0x0A12), + (0x0A29, 0x0A29), + (0x0A31, 0x0A31), + (0x0A34, 0x0A34), + (0x0A37, 0x0A37), + (0x0A3A, 0x0A3B), + (0x0A3D, 0x0A3D), + (0x0A43, 0x0A46), + (0x0A49, 0x0A4A), + (0x0A4E, 0x0A50), + (0x0A52, 0x0A58), + (0x0A5D, 0x0A5D), + (0x0A5F, 0x0A65), + (0x0A77, 0x0A80), + (0x0A84, 0x0A84), + (0x0A8E, 0x0A8E), + (0x0A92, 0x0A92), + (0x0AA9, 0x0AA9), + (0x0AB1, 0x0AB1), + (0x0AB4, 0x0AB4), + (0x0ABA, 0x0ABB), + (0x0AC6, 0x0AC6), + (0x0ACA, 0x0ACA), + (0x0ACE, 0x0ACF), + (0x0AD1, 0x0ADF), + (0x0AE4, 0x0AE5), + (0x0AF2, 0x0AF8), + (0x0B00, 0x0B00), + (0x0B04, 0x0B04), + (0x0B0D, 0x0B0E), + (0x0B11, 0x0B12), + (0x0B29, 0x0B29), + (0x0B31, 0x0B31), + (0x0B34, 0x0B34), + (0x0B3A, 0x0B3B), + (0x0B45, 0x0B46), + (0x0B49, 0x0B4A), + (0x0B4E, 0x0B54), + (0x0B58, 0x0B5B), + (0x0B5E, 0x0B5E), + (0x0B64, 0x0B65), + (0x0B78, 0x0B81), + (0x0B84, 0x0B84), + (0x0B8B, 0x0B8D), + (0x0B91, 0x0B91), + (0x0B96, 0x0B98), + (0x0B9B, 0x0B9B), + (0x0B9D, 0x0B9D), + (0x0BA0, 0x0BA2), + (0x0BA5, 0x0BA7), + (0x0BAB, 0x0BAD), + (0x0BBA, 0x0BBD), + (0x0BC3, 0x0BC5), + (0x0BC9, 0x0BC9), + (0x0BCE, 0x0BCF), + (0x0BD1, 0x0BD6), + (0x0BD8, 0x0BE5), + (0x0BFB, 0x0BFF), + (0x0C0D, 0x0C0D), + (0x0C11, 0x0C11), + (0x0C29, 0x0C29), + (0x0C3A, 0x0C3B), + (0x0C45, 0x0C45), + (0x0C49, 0x0C49), + (0x0C4E, 0x0C54), + (0x0C57, 0x0C57), + (0x0C5B, 0x0C5C), + (0x0C5E, 0x0C5F), + (0x0C64, 0x0C65), + (0x0C70, 0x0C76), + (0x0C8D, 0x0C8D), + (0x0C91, 0x0C91), + (0x0CA9, 0x0CA9), + (0x0CB4, 0x0CB4), + (0x0CBA, 0x0CBB), + (0x0CC5, 0x0CC5), + (0x0CC9, 0x0CC9), + (0x0CCE, 0x0CD4), + (0x0CD7, 0x0CDC), + (0x0CDF, 0x0CDF), + (0x0CE4, 0x0CE5), + (0x0CF0, 0x0CF0), + (0x0CF4, 0x0CFF), + (0x0D0D, 0x0D0D), + (0x0D11, 0x0D11), + (0x0D45, 0x0D45), + (0x0D49, 0x0D49), + (0x0D50, 0x0D53), + (0x0D64, 0x0D65), + (0x0D80, 0x0D80), + (0x0D84, 0x0D84), + (0x0D97, 0x0D99), + (0x0DB2, 0x0DB2), + (0x0DBC, 0x0DBC), + (0x0DBE, 0x0DBF), + (0x0DC7, 0x0DC9), + (0x0DCB, 0x0DCE), + (0x0DD5, 0x0DD5), + (0x0DD7, 0x0DD7), + (0x0DE0, 0x0DE5), + (0x0DF0, 0x0DF1), + (0x0DF5, 0x0E00), + (0x0E3B, 0x0E3E), + (0x0E5C, 0x0E80), + (0x0E83, 0x0E83), + (0x0E85, 0x0E85), + (0x0E8B, 0x0E8B), + (0x0EA4, 0x0EA4), + (0x0EA6, 0x0EA6), + (0x0EBE, 0x0EBF), + (0x0EC5, 0x0EC5), + (0x0EC7, 0x0EC7), + (0x0ECF, 0x0ECF), + (0x0EDA, 0x0EDB), + (0x0EE0, 0x0EFF), + (0x0F48, 0x0F48), + (0x0F6D, 0x0F70), + (0x0F98, 0x0F98), + (0x0FBD, 0x0FBD), + (0x0FCD, 0x0FCD), + (0x0FDB, 0x0FFF), + (0x10C6, 0x10C6), + (0x10C8, 0x10CC), + (0x10CE, 0x10CF), + (0x1249, 0x1249), + (0x124E, 0x124F), + (0x1257, 0x1257), + (0x1259, 0x1259), + (0x125E, 0x125F), + (0x1289, 0x1289), + (0x128E, 0x128F), + (0x12B1, 0x12B1), + (0x12B6, 0x12B7), + (0x12BF, 0x12BF), + (0x12C1, 0x12C1), + (0x12C6, 0x12C7), + (0x12D7, 0x12D7), + (0x1311, 0x1311), + (0x1316, 0x1317), + (0x135B, 0x135C), + (0x137D, 0x137F), + (0x139A, 0x139F), + (0x13F6, 0x13F7), + (0x13FE, 0x13FF), + (0x1680, 0x1680), + (0x169D, 0x169F), + (0x16F9, 0x16FF), + (0x1716, 0x171E), + (0x1737, 0x173F), + (0x1754, 0x175F), + (0x176D, 0x176D), + (0x1771, 0x1771), + (0x1774, 0x177F), + (0x17DE, 0x17DF), + (0x17EA, 0x17EF), + (0x17FA, 0x17FF), + (0x180E, 0x180E), + (0x181A, 0x181F), + (0x1879, 0x187F), + (0x18AB, 0x18AF), + (0x18F6, 0x18FF), + (0x191F, 0x191F), + (0x192C, 0x192F), + (0x193C, 0x193F), + (0x1941, 0x1943), + (0x196E, 0x196F), + (0x1975, 0x197F), + (0x19AC, 0x19AF), + (0x19CA, 0x19CF), + (0x19DB, 0x19DD), + (0x1A1C, 0x1A1D), + (0x1A5F, 0x1A5F), + (0x1A7D, 0x1A7E), + (0x1A8A, 0x1A8F), + (0x1A9A, 0x1A9F), + (0x1AAE, 0x1AAF), + (0x1ACF, 0x1AFF), + (0x1B4D, 0x1B4D), + (0x1BF4, 0x1BFB), + (0x1C38, 0x1C3A), + (0x1C4A, 0x1C4C), + (0x1C8B, 0x1C8F), + (0x1CBB, 0x1CBC), + (0x1CC8, 0x1CCF), + (0x1CFB, 0x1CFF), + (0x1F16, 0x1F17), + (0x1F1E, 0x1F1F), + (0x1F46, 0x1F47), + (0x1F4E, 0x1F4F), + (0x1F58, 0x1F58), + (0x1F5A, 0x1F5A), + (0x1F5C, 0x1F5C), + (0x1F5E, 0x1F5E), + (0x1F7E, 0x1F7F), + (0x1FB5, 0x1FB5), + (0x1FC5, 0x1FC5), + (0x1FD4, 0x1FD5), + (0x1FDC, 0x1FDC), + (0x1FF0, 0x1FF1), + (0x1FF5, 0x1FF5), + (0x1FFF, 0x200F), + (0x2028, 0x202F), + (0x205F, 0x206F), + (0x2072, 0x2073), + (0x208F, 0x208F), + (0x209D, 0x209F), + (0x20C1, 0x20CF), + (0x20F1, 0x20FF), + (0x218C, 0x218F), + (0x242A, 0x243F), + (0x244B, 0x245F), + (0x2B74, 0x2B75), + (0x2B96, 0x2B96), + (0x2CF4, 0x2CF8), + (0x2D26, 0x2D26), + (0x2D28, 0x2D2C), + (0x2D2E, 0x2D2F), + (0x2D68, 0x2D6E), + (0x2D71, 0x2D7E), + (0x2D97, 0x2D9F), + (0x2DA7, 0x2DA7), + (0x2DAF, 0x2DAF), + (0x2DB7, 0x2DB7), + (0x2DBF, 0x2DBF), + (0x2DC7, 0x2DC7), + (0x2DCF, 0x2DCF), + (0x2DD7, 0x2DD7), + (0x2DDF, 0x2DDF), + (0x2E5E, 0x2E7F), + (0x2E9A, 0x2E9A), + (0x2EF4, 0x2EFF), + (0x2FD6, 0x2FEF), + (0x3000, 0x3000), + (0x3040, 0x3040), + (0x3097, 0x3098), + (0x3100, 0x3104), + (0x3130, 0x3130), + (0x318F, 0x318F), + (0x31E6, 0x31EE), + (0x321F, 0x321F), + (0xA48D, 0xA48F), + (0xA4C7, 0xA4CF), + (0xA62C, 0xA63F), + (0xA6F8, 0xA6FF), + (0xA7CE, 0xA7CF), + (0xA7D2, 0xA7D2), + (0xA7D4, 0xA7D4), + (0xA7DD, 0xA7F1), + (0xA82D, 0xA82F), + (0xA83A, 0xA83F), + (0xA878, 0xA87F), + (0xA8C6, 0xA8CD), + (0xA8DA, 0xA8DF), + (0xA954, 0xA95E), + (0xA97D, 0xA97F), + (0xA9CE, 0xA9CE), + (0xA9DA, 0xA9DD), + (0xA9FF, 0xA9FF), + (0xAA37, 0xAA3F), + (0xAA4E, 0xAA4F), + (0xAA5A, 0xAA5B), + (0xAAC3, 0xAADA), + (0xAAF7, 0xAB00), + (0xAB07, 0xAB08), + (0xAB0F, 0xAB10), + (0xAB17, 0xAB1F), + (0xAB27, 0xAB27), + (0xAB2F, 0xAB2F), + (0xAB6C, 0xAB6F), + (0xABEE, 0xABEF), + (0xABFA, 0xABFF), + (0xD7A4, 0xD7AF), + (0xD7C7, 0xD7CA), + (0xD7FC, 0xF8FF), + (0xFA6E, 0xFA6F), + (0xFADA, 0xFAFF), + (0xFB07, 0xFB12), + (0xFB18, 0xFB1C), + (0xFB37, 0xFB37), + (0xFB3D, 0xFB3D), + (0xFB3F, 0xFB3F), + (0xFB42, 0xFB42), + (0xFB45, 0xFB45), + (0xFBC3, 0xFBD2), + (0xFD90, 0xFD91), + (0xFDC8, 0xFDCE), + (0xFDD0, 0xFDEF), + (0xFE1A, 0xFE1F), + (0xFE53, 0xFE53), + (0xFE67, 0xFE67), + (0xFE6C, 0xFE6F), + (0xFE75, 0xFE75), + (0xFEFD, 0xFF00), + (0xFFBF, 0xFFC1), + (0xFFC8, 0xFFC9), + 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"repr": "'a\"'" + }, + { + "name": "'a\nb'", + "source": "'a\nb'", + "error": "SyntaxError" + }, + { + "name": "'a\\\nb'", + "source": "'a\\\nb'", + "repr": "'ab'" + }, + { + "name": "r'a\\\nb'", + "source": "r'a\\\nb'", + "repr": "'a\\\\\\nb'" + }, + { + "name": "'unterminated", + "source": "'unterminated", + "error": "SyntaxError" + }, + { + "name": "'\\a\\b\\f\\n\\r\\t\\v'", + "source": "'\\a\\b\\f\\n\\r\\t\\v'", + "repr": "'\\x07\\x08\\x0c\\n\\r\\t\\x0b'" + }, + { + "name": "'\\0\\12\\101\\1011'", + "source": "'\\0\\12\\101\\1011'", + "repr": "'\\x00\\nAA1'" + }, + { + "name": "'\\777'", + "source": "'\\777'", + "repr": "'\u01ff'" + }, + { + "name": "b'\\777'", + "source": "b'\\777'", + "repr": "b'\\xff'" + }, + { + "name": "b'\\400'", + "source": "b'\\400'", + "repr": "b'\\x00'" + }, + { + "name": "'\\x41'", + "source": "'\\x41'", + "repr": "'A'" + }, + { + "name": "'\\x4'", + "source": "'\\x4'", + "error": "SyntaxError" + }, + { + "name": "'\\u00e9'", + "source": "'\\u00e9'", + "repr": "'\u00e9'" + }, + { + "name": "'\\u00e'", + "source": "'\\u00e'", + "error": "SyntaxError" + }, + { + "name": "'\\U0001F600'", + "source": "'\\U0001F600'", + "repr": "'\ud83d\ude00'" + }, + { + "name": "'\\U00110000'", + "source": "'\\U00110000'", + "error": "SyntaxError" + }, + { + "name": "'\\ud800'", + "source": "'\\ud800'", + "repr": "'\\ud800'" + }, + { + "name": "'\\N{BULLET}'", + "source": "'\\N{BULLET}'", + "repr": "'\u2022'" + }, + { + "name": "'\\q'", + "source": "'\\q'", + "repr": "'\\\\q'" + }, + { + "name": "'\\\\'", + "source": "'\\\\'", + "repr": "'\\\\'" + }, + { + "name": "'\\''", + "source": "'\\''", + "repr": "\"'\"" + }, + { + "name": "\"\\\"\"", + "source": "\"\\\"\"", + "repr": "'\"'" + }, + { + "name": "b'\\u0041'", + "source": "b'\\u0041'", + "repr": "b'\\\\u0041'" + }, + { + "name": "b'\\x41\\xff'", + "source": "b'\\x41\\xff'", + "repr": "b'A\\xff'" + }, + { + "name": "b'caf\u00e9'", + "source": "b'caf\u00e9'", + "error": "SyntaxError" + }, + { + "name": "'caf\u00e9'", + "source": "'caf\u00e9'", + "repr": "'caf\u00e9'" + }, + { + "name": "r'\\d'", + "source": "r'\\d'", + "repr": "'\\\\d'" + }, + { + "name": "r'\\''", + "source": "r'\\''", + "repr": "\"\\\\'\"" + }, + { + "name": "rb'\\d'", + "source": "rb'\\d'", + "repr": "b'\\\\d'" + }, + { + "name": "r'\\'", + "source": "r'\\'", + "error": "SyntaxError" + }, + { + "name": "'\u65e5\ud83d\ude00'", + "source": "'\u65e5\ud83d\ude00'", + "repr": "'\u65e5\ud83d\ude00'" + } + ] +} diff --git a/litellm-rust/crates/python-compat/scripts/generate_fixtures.py b/litellm-rust/crates/python-compat/scripts/generate_fixtures.py new file mode 100644 index 00000000000..26456a638f6 --- /dev/null +++ b/litellm-rust/crates/python-compat/scripts/generate_fixtures.py @@ -0,0 +1,352 @@ +"""Regenerate generated/values.json: what CPython produces for each value in CORPUS. + + python scripts/generate_fixtures.py > generated/values.json + +Each row records `repr`, `str`, `json.dumps` (or its error), `bool`, and `pickle.dumps` at +every protocol. `literal` says whether `ast.literal_eval(repr(value))` gives the value back, +which is how Python reads `str(dict)` text back from a cache; the Rust tests reach the other +rows only through pickle. `view` is `repr` of the value as `pickle::loads` decodes it, with +tuples, sets, and frozensets rendered as lists. `sources` records `ast.literal_eval` on raw +source texts: its result, or the exception it raises. +""" + +import ast +import json +import pickle +import sys +import warnings + +# Entries are source texts, or `(name, source)` when the source is too long to read in a +# test report. `name` is what the Rust `KNOWN` table keys on. +CORPUS = [ + # Scalars + "None", + "True", + "False", + "0", + "-7", + "2**63 - 1", + "-(2**63)", + "2**64", + "-(2**70)", + # Floats around CPython's repr thresholds + "0.0", + "-0.0", + "0.2", + "1.0", + "-1.5", + "0.1 + 0.2", + "123456789.123", + "1e15", + "1e16", + "1.5e16", + "9999999999999998.0", + "0.0001", + "1e-05", + "1.25e-07", + "5e-324", + "1.7976931348623157e308", + "1e22", + "float('inf')", + "float('-inf')", + "float('nan')", + # Complex + "1j", + "-1j", + "complex(0, -1)", + "1+2j", + "-1.5-0.5j", + "complex(0.0, 1e16)", + # Strings: quote selection, escapes, printable and non-printable non-ASCII + "''", + "'plain'", + '"it\'s"', + "'say \"hi\"'", + "'both \\' and \"'", + "'back\\\\slash'", + "'\\t\\n\\r'", + "'\\x00\\x1f\\x7f'", + "'\\x85\\xa0\\xad'", + "'caf\\xe9'", + "'\\u65e5\\u672c'", + "'\\u200b\\u2028\\u3000'", + "'\\U0001f600'", + "'\\U000e0001\\U0010ffff'", + "'\\b\\f'", + # Bytes + "b''", + "b'abc'", + 'b"a\'b"', + "b'a\"b\\'c'", + "b'\\x00\\t\\n\\r\\x7f\\x80\\xff'", + # Containers + "[]", + "[1, 'a', None, True]", + "()", + "(1,)", + "(1, (2, 3))", + "{}", + "{'a': 1, 'b': [1.0, 2.5]}", + "{'z': 1, 'a': 2, 'm': 3}", + "{1: 'int', 2.5: 'float', True: 'bool', None: 'none'}", + "{(1, 2): 'tuple key'}", + "{'nested': {'deeper': {'deepest': [{}]}}}", + "{1}", + "set()", + "frozenset({1})", + "[[[[[[[[[[1]]]]]]]]]]", + # Deeper than the Rust decoders allow: CPython's parser accepts ~200 nested brackets + # and its unpickler has no limit, so this row records a deliberate divergence. + ("nested_150", "[" * 150 + "1" + "]" * 150), + # The shape LiteLLM caches + '{\'timestamp\': 1726000000.123, \'response\': \'{"id": "chatcmpl-1", "object": "chat.completion"}\'}', + "{'model': 'gpt-4o', 'messages': [{'role': 'user', 'content': 'hi'}], 'temperature': 0.2, 'stream': False}", +] + +# Source texts for `literal_eval` itself: tokenizer and evaluator edge cases, recorded with +# CPython's result or the exception it raises. Raw strings keep backslashes literal. +SOURCES = [ + # Layout: leading/trailing whitespace, comments, newlines, continuations + "1", + " 1", + "\t1", + "\n1", + " \n 1", + "1\n", + "1 # comment", + "# c\n1", + "1 \\\n", + "1,", + "1, 2", + "1,\n2", + "(1,\n2)", + "[1,\n 2,\n]", + # Containers and grouping + "()", + "(1)", + "((1,))", + "(,)", + "[,]", + "{,}", + "[1,]", + "{'a': 1,}", + "{1,}", + "{'a': 1 'b': 2}", + "{1: 'a', True: 'b'}", + "{1, True, 1.0}", + "{(1, 2): 'x', (1.0, 2): 'y'}", + "{[1]: 2}", + "{{1}}", + "{(1, [2])}", + "set()", + "set( )", + "set([1])", + "frozenset()", + # Names + "True", + "False", + "None", + "Truex", + "true", + "...", + # Integers and floats + "0", + "00", + "0_0", + "01", + "007", + "1_000", + "1_", + "1__0", + "_1", + "0x1F", + "0X_1f", + "0o17", + "0b101", + "0b102", + "0x", + "1e3", + "1E-3", + "1e", + "1.e5", + ".5", + "5.", + "1..", + "1.5.2", + "1_0.0_1e1_0", + "1e999", + "-1e999", + "1j", + "1.5J", + "010j", + "010.5", + "1a", + "0x1g", + # Signs and complex sums + "-1", + "+1", + "- 1", + "--1", + "-+1", + "-(1)", + "-(-1)", + "-(1+2j)", + "-True", + "-'a'", + "-[1]", + "1+2j", + "1-2j", + "1 + 2j", + "(1)+(2j)", + "1+2", + "1+2+3j", + "1+-2j", + "2j+1", + "True+1j", + "1-0j", + "0.0-0j", + "-0.0+1j", + "-0.0", + "-0", + "(-0.0)", + "[-0.0, (-0.0)]", + "2**3", + "1*2", + "1 if 1 else 2", + "(1,)(2)", + # String prefixes, quoting, and concatenation + "''", + '""', + "'a' 'b'", + "'a' \"b\" '''c'''", + "'a' b'b'", + "b'a' b'b'", + "u'x'", + "U'x'", + "r'x'", + "R'x'", + "b'x'", + "B'x'", + "br'x'", + "Rb'x'", + "rB'x'", + "ur'x'", + "bu'x'", + "f'x'", + "rf'x'", + "'''a\nb'''", + '"""a\\""""', + "'a\nb'", + "'a\\\nb'", + "r'a\\\nb'", + "'unterminated", + # Escapes + r"'\a\b\f\n\r\t\v'", + r"'\0\12\101\1011'", + r"'\777'", + r"b'\777'", + r"b'\400'", + r"'\x41'", + r"'\x4'", + r"'\u00e9'", + r"'\u00e'", + r"'\U0001F600'", + r"'\U00110000'", + r"'\ud800'", + r"'\N{BULLET}'", + r"'\q'", + r"'\\'", + r"'\''", + r'"\""', + r"b'\u0041'", + r"b'\x41\xff'", + "b'café'", + "'café'", + r"r'\d'", + r"r'\''", + r"rb'\d'", + r"r'\'", + "'日\U0001f600'", +] + + +def named(entry): + """Split a corpus entry into its report name and its source text.""" + if isinstance(entry, tuple): + return entry + return entry, entry + + +def evaluate(entry): + name, source = named(entry) + with warnings.catch_warnings(): + warnings.simplefilter("ignore") + try: + return {"name": name, "source": source, "repr": repr(ast.literal_eval(source))} + except Exception as error: # noqa: BLE001 - recorded, not raised + return {"name": name, "source": source, "error": type(error).__name__} + + +def view(value): + if isinstance(value, (list, tuple, set, frozenset)): + return "[" + ", ".join(view(item) for item in value) + "]" + if isinstance(value, dict): + return "{" + ", ".join(f"{view(key)}: {view(item)}" for key, item in value.items()) + "}" + return repr(value) + + +def plain(value): + """Whether pickle can encode the value without a class reference such as `complex`.""" + if isinstance(value, complex): + return False + if isinstance(value, (list, tuple, set, frozenset)): + return all(plain(item) for item in value) + if isinstance(value, dict): + return all(plain(key) and plain(item) for key, item in value.items()) + return True + + +def is_literal(value): + try: + parsed = ast.literal_eval(repr(value)) + except (ValueError, SyntaxError): + return False + return repr(parsed) == repr(value) + + +def row(entry): + name, source = named(entry) + value = eval(source) + entry = { + "name": name, + "source": source, + "literal": is_literal(value), + "plain": plain(value), + "repr": repr(value), + "str": str(value), + "truthy": bool(value), + } + try: + entry["json"] = json.dumps(value) + except (TypeError, ValueError) as error: + entry["json_error"] = str(error) + try: + entry["pickle"] = {str(protocol): pickle.dumps(value, protocol=protocol).hex() for protocol in range(6)} + entry["view"] = view(value) + except Exception as error: # noqa: BLE001 - recorded, not raised + entry["pickle_error"] = f"{type(error).__name__}: {error}" + return entry + + +if __name__ == "__main__": + json.dump( + { + "python": sys.version.split()[0], + "rows": [row(entry) for entry in CORPUS], + "sources": [evaluate(entry) for entry in SOURCES], + }, + sys.stdout, + indent=2, + ensure_ascii=True, + ) + sys.stdout.write("\n") diff --git a/litellm-rust/crates/python-compat/scripts/generate_nonprintable.py b/litellm-rust/crates/python-compat/scripts/generate_nonprintable.py new file mode 100644 index 00000000000..70d1fbd2dd1 --- /dev/null +++ b/litellm-rust/crates/python-compat/scripts/generate_nonprintable.py @@ -0,0 +1,35 @@ +"""Regenerate generated/nonprintable.rs from this interpreter's `str.isprintable`. + +`repr(str)` escapes exactly the characters for which `str.isprintable()` is false, so the +table must come from the Python version the gateway interoperates with. + + python scripts/generate_nonprintable.py > generated/nonprintable.rs +""" + +import sys +import unicodedata + +ranges = [] +start = None +for code in range(0x110000): + printable = chr(code).isprintable() + if not printable and start is None: + start = code + elif printable and start is not None: + ranges.append((start, code - 1)) + start = None +if start is not None: + ranges.append((start, 0x10FFFF)) + +lines = [ + f"// Generated by scripts/generate_nonprintable.py from Python {sys.version.split()[0]}", + f"// (Unicode {unicodedata.unidata_version}). Do not edit by hand.", + "", + f'pub(crate) const UNICODE_VERSION: &str = "{unicodedata.unidata_version}";', + "", + "/// Inclusive code point ranges for which Python's `str.isprintable()` is false.", + f"pub(crate) const NONPRINTABLE: [(u32, u32); {len(ranges)}] = [", + *(f" (0x{low:04X}, 0x{high:04X})," for low, high in ranges), + "];", +] +sys.stdout.write("\n".join(lines) + "\n") diff --git a/litellm-rust/crates/python-compat/scripts/verify_rust_pickles.py b/litellm-rust/crates/python-compat/scripts/verify_rust_pickles.py new file mode 100644 index 00000000000..793acad61f9 --- /dev/null +++ b/litellm-rust/crates/python-compat/scripts/verify_rust_pickles.py @@ -0,0 +1,43 @@ +"""Check that CPython unpickles what `pickle::dumps` writes, to the value it was given. + + PYTHON_COMPAT_RUST_PICKLES=rust.tsv cargo test -p litellm-python-compat --test fixtures + python scripts/verify_rust_pickles.py rust.tsv + +The rows are plain data by construction, so this refuses to resolve any class rather than +handing file-controlled bytes to an unrestricted `pickle.loads`. +""" + +import ast +import io +import pickle +import sys + + +class PlainDataUnpickler(pickle.Unpickler): + """An unpickler with `GLOBAL`/`REDUCE` disabled, mirroring `pickle::loads` in Rust.""" + + def find_class(self, module, name): + raise pickle.UnpicklingError(f"refusing to resolve {module}.{name}") + + +def loads(data): + return PlainDataUnpickler(io.BytesIO(data)).load() + + +def main(path): + failures = 0 + rows = 0 + with open(path, encoding="utf-8") as lines: + for line in lines: + data, expected = line.rstrip("\n").split("\t", 1) + rows += 1 + actual = repr(loads(bytes.fromhex(data))) + if actual != repr(ast.literal_eval(expected)): + failures += 1 + sys.stdout.write(f"mismatch: expected {expected}, got {actual}\n") + sys.stdout.write(f"{rows} Rust pickles checked, {failures} mismatches\n") + return 1 if failures or not rows else 0 + + +if __name__ == "__main__": + sys.exit(main(sys.argv[1])) diff --git a/litellm-rust/crates/python-compat/src/error.rs b/litellm-rust/crates/python-compat/src/error.rs new file mode 100644 index 00000000000..43990eb7602 --- /dev/null +++ b/litellm-rust/crates/python-compat/src/error.rs @@ -0,0 +1,25 @@ +use crate::MAX_DEPTH; + +/// A failure to read or write a Python format. Messages quote CPython's own wording where +/// the Python side raises (`TypeError`, `ValueError`), so callers can log them as is. +#[derive(Debug, thiserror::Error)] +pub enum Error { + #[error("malformed Python literal at byte {0}")] + InvalidLiteral(usize), + #[error("unhashable type: '{0}'")] + Unhashable(&'static str), + #[error("value nests deeper than {MAX_DEPTH} levels")] + TooDeep, + #[error("invalid pickle: {0}")] + InvalidPickle(String), + #[error("Object of type {0} is not JSON serializable")] + NotJsonSerializable(&'static str), + #[error("keys must be str, int, float, bool or None, not {0}")] + InvalidJsonKey(&'static str), + #[error("Out of range float values are not JSON compliant")] + NonFiniteFloat, + #[error("integer does not fit in the JSON number range")] + IntegerOutOfRange, + #[error("Object of type {0} cannot be pickled as plain data")] + NotPicklable(&'static str), +} diff --git a/litellm-rust/crates/python-compat/src/json.rs b/litellm-rust/crates/python-compat/src/json.rs new file mode 100644 index 00000000000..d3436519ac4 --- /dev/null +++ b/litellm-rust/crates/python-compat/src/json.rs @@ -0,0 +1,168 @@ +//! `json.dumps` with CPython's default options, and the JSON value `json.loads` returns. +//! +//! Defaults are `ensure_ascii=True`, `allow_nan=True`, separators `(", ", ": ")`, and no key +//! sorting. Python's `json.loads` is mapped by [`from_json`]; a `serde_json` number that does +//! not fit `i64` or `u64` arrives as a float, where Python would keep an `int`. + +use std::fmt::Write; + +use serde_json::{Map, Number}; + +use crate::{Error, Value, repr::float_repr}; + +/// `json.dumps(value)`. +pub fn dumps(value: &Value) -> Result { + let mut out = String::new(); + write_value(&mut out, value)?; + Ok(out) +} + +/// The Python value `json.loads` returns for a JSON document. +pub fn from_json(value: serde_json::Value) -> Value { + match value { + serde_json::Value::Null => Value::None, + serde_json::Value::Bool(value) => Value::Bool(value), + serde_json::Value::Number(number) => { + if let Some(value) = number.as_i64() { + Value::Int(value.into()) + } else if let Some(value) = number.as_u64() { + Value::Int(value.into()) + } else { + Value::Float(number.as_f64().unwrap_or(f64::NAN)) + } + } + serde_json::Value::String(text) => Value::Str(text), + serde_json::Value::Array(values) => { + Value::List(values.into_iter().map(from_json).collect()) + } + serde_json::Value::Object(entries) => Value::Dict( + entries + .into_iter() + .map(|(key, value)| (Value::Str(key), from_json(value))) + .collect(), + ), + } +} + +/// `json.loads(json.dumps(value))` as a `serde_json` value: tuples become arrays and dict +/// keys are coerced to strings as `json.dumps` does. Non-finite floats, which Python writes +/// as `NaN` and `Infinity`, have no `serde_json` form and fail with [`Error::NonFiniteFloat`]. +pub fn to_json(value: &Value) -> Result { + Ok(match value { + Value::None => serde_json::Value::Null, + Value::Bool(value) => serde_json::Value::Bool(*value), + Value::Int(value) => { + let text = value.to_string(); + serde_json::Value::Number( + text.parse::() + .map(Number::from) + .or_else(|_| text.parse::().map(Number::from)) + .map_err(|_| Error::IntegerOutOfRange)?, + ) + } + Value::Float(value) => { + serde_json::Value::Number(Number::from_f64(*value).ok_or(Error::NonFiniteFloat)?) + } + Value::Str(text) => serde_json::Value::String(text.clone()), + Value::List(values) | Value::Tuple(values) => { + serde_json::Value::Array(values.iter().map(to_json).collect::, _>>()?) + } + Value::Dict(entries) => serde_json::Value::Object( + entries + .iter() + .map(|(key, value)| Ok((json_key(key)?, to_json(value)?))) + .collect::, Error>>()?, + ), + value @ (Value::Bytes(_) | Value::Set(_) | Value::Complex { .. }) => { + return Err(Error::NotJsonSerializable(value.type_name())); + } + }) +} + +fn write_value(out: &mut String, value: &Value) -> Result<(), Error> { + match value { + Value::None => out.push_str("null"), + Value::Bool(true) => out.push_str("true"), + Value::Bool(false) => out.push_str("false"), + Value::Int(value) => { + let _ = write!(out, "{value}"); + } + Value::Float(value) => out.push_str(&float_text(*value)), + Value::Str(text) => write_string(out, text), + Value::List(values) | Value::Tuple(values) => { + out.push('['); + for (index, value) in values.iter().enumerate() { + if index > 0 { + out.push_str(", "); + } + write_value(out, value)?; + } + out.push(']'); + } + Value::Dict(entries) => { + out.push('{'); + for (index, (key, value)) in entries.iter().enumerate() { + if index > 0 { + out.push_str(", "); + } + write_string(out, &json_key(key)?); + out.push_str(": "); + write_value(out, value)?; + } + out.push('}'); + } + value @ (Value::Bytes(_) | Value::Set(_) | Value::Complex { .. }) => { + return Err(Error::NotJsonSerializable(value.type_name())); + } + } + Ok(()) +} + +/// `json.encoder.JSONEncoder.iterencode`'s `floatstr` with `allow_nan=True`. +fn float_text(value: f64) -> String { + if value.is_nan() { + "NaN".to_owned() + } else if value.is_infinite() { + if value > 0.0 { "Infinity" } else { "-Infinity" }.to_owned() + } else { + float_repr(value) + } +} + +/// Dict key coercion in `json.dumps`: scalars become their JSON text, other keys fail. +fn json_key(key: &Value) -> Result { + Ok(match key { + Value::Str(text) => text.clone(), + Value::Int(value) => value.to_string(), + Value::Float(value) => float_text(*value), + Value::Bool(true) => "true".to_owned(), + Value::Bool(false) => "false".to_owned(), + Value::None => "null".to_owned(), + key => return Err(Error::InvalidJsonKey(key.type_name())), + }) +} + +/// `py_encode_basestring_ascii`: escape `"`, `\`, control characters, and everything outside +/// printable ASCII as `\uXXXX`, with surrogate pairs above the BMP. +fn write_string(out: &mut String, text: &str) { + out.push('"'); + for ch in text.chars() { + match ch { + '"' => out.push_str("\\\""), + '\\' => out.push_str("\\\\"), + '\n' => out.push_str("\\n"), + '\r' => out.push_str("\\r"), + '\t' => out.push_str("\\t"), + '\u{8}' => out.push_str("\\b"), + '\u{c}' => out.push_str("\\f"), + ' '..='~' => out.push(ch), + ch => { + let mut units = [0u16; 2]; + for unit in ch.encode_utf16(&mut units) { + let _ = write!(out, "\\u{unit:04x}"); + } + } + } + } + out.push('"'); +} diff --git a/litellm-rust/crates/python-compat/src/lib.rs b/litellm-rust/crates/python-compat/src/lib.rs new file mode 100644 index 00000000000..b23aff409f2 --- /dev/null +++ b/litellm-rust/crates/python-compat/src/lib.rs @@ -0,0 +1,39 @@ +//! Python data formats reproduced in Rust, for state that Python LiteLLM writes and reads. +//! +//! Each module mirrors one Python operation over plain data values, and its tests replay +//! fixtures generated by that operation in CPython (`scripts/generate_fixtures.py`): +//! +//! | Module | Python operation | +//! |---|---| +//! | [`literal`] | `ast.literal_eval(text)` | +//! | [`repr`] | `repr(value)` and `str(value)` | +//! | [`json`] | `json.dumps(value)`, and `json.loads(json.dumps(value))` as a JSON value | +//! | [`pickle`] | `pickle.loads(data)` and `pickle.dumps(value)` for plain data | +//! | [`truthy`] | `bool(value)` | +//! +//! [`Value`] is the closed data model these formats share. Live Python objects +//! (descriptors, `__bool__`, `__str__`, callbacks) are out of scope: those belong to the +//! PyO3 boundary in `litellm-python-bridge`, which runs the real protocol. +//! +//! Known limits, each pinned by a test: +//! - `set` iteration order follows Python's hash order, which this crate does not model +//! (string hashes are randomized per process). Sets keep their literal order. +//! - `str` values are Rust `String`s, so lone surrogates cannot be represented. +//! - [`pickle::loads`] decodes `tuple`, `set`, and `frozenset` as lists. + +mod error; +pub mod json; +pub mod literal; +pub mod pickle; +pub mod repr; +pub mod truthy; +mod value; + +pub use error::Error; +pub use num_bigint::BigInt; +pub use value::Value; + +/// Nesting limit for the decoders, which recurse. It keeps untrusted persisted data from +/// overflowing the Rust stack, and is deliberately stricter than CPython, whose parser takes +/// about 200 nested brackets and whose unpickler has no limit. +pub const MAX_DEPTH: usize = 128; diff --git a/litellm-rust/crates/python-compat/src/literal.rs b/litellm-rust/crates/python-compat/src/literal.rs new file mode 100644 index 00000000000..12e9036572f --- /dev/null +++ b/litellm-rust/crates/python-compat/src/literal.rs @@ -0,0 +1,745 @@ +//! `ast.literal_eval(text)`, as a single-pass recursive-descent parser. +//! +//! Tokens follow CPython's tokenizer (string prefixes, escapes, implicit concatenation, +//! numeric underscores and radixes, comments, line continuations). Expressions follow +//! `ast.literal_eval`'s evaluator: +//! +//! - one unary `+`/`-`, applied only to a numeric constant (`-(1)` is fine, `--1` is not) +//! - `a + b` / `a - b` only as a signed real plus or minus a complex constant, with 3.14's +//! mixed-mode rules (`1 - 0j` is `(1-0j)`) +//! - parentheses group without making a tuple; `set()` is the only call +//! - dict keys and set members are deduplicated with Python equality (`1 == 1.0 == True`) +//! +//! Not supported, each pinned by a fixture: `\N{NAME}` escapes, `...`, and escapes that +//! produce lone surrogates. + +use std::collections::{HashMap, hash_map::Entry}; + +use num_bigint::BigInt; +use num_traits::{FromPrimitive, ToPrimitive}; + +use crate::{Error, MAX_DEPTH, Value}; + +pub fn literal_eval(text: &str) -> Result { + let mut parser = Parser { + bytes: text.trim_start_matches([' ', '\t']).as_bytes(), + offset: text.len() - text.trim_start_matches([' ', '\t']).len(), + pos: 0, + depth: 0, + brackets: 0, + }; + parser.skip_leading_lines()?; + let value = parser.top_level()?.value; + parser.skip_trivia(true); + if parser.pos != parser.bytes.len() { + return Err(parser.error()); + } + Ok(value) +} + +/// How a parsed term may take part in `+`/`-`, per `ast.literal_eval`'s `_convert_num` +/// (`Constant`) and `_convert_signed_num` (`Signed`). `Other` is any other node. +#[derive(Clone, Copy, PartialEq)] +enum Kind { + Constant, + Signed, + Other, +} + +struct Term { + value: Value, + kind: Kind, +} + +impl Term { + fn other(value: Value) -> Self { + Self { + value, + kind: Kind::Other, + } + } + + fn is_number(&self) -> bool { + matches!( + self.value, + Value::Int(_) | Value::Float(_) | Value::Complex { .. } + ) + } +} + +struct Parser<'a> { + bytes: &'a [u8], + /// Bytes stripped before `bytes` starts, so errors report offsets into the input. + offset: usize, + pos: usize, + depth: usize, + /// Open brackets: newlines are insignificant only inside them. + brackets: usize, +} + +impl Parser<'_> { + fn error(&self) -> Error { + Error::InvalidLiteral(self.offset + self.pos) + } + + fn peek(&self) -> Option { + self.bytes.get(self.pos).copied() + } + + fn peek_at(&self, ahead: usize) -> Option { + self.bytes.get(self.pos + ahead).copied() + } + + fn expect(&mut self, byte: u8) -> Result<(), Error> { + if self.peek() != Some(byte) { + return Err(self.error()); + } + self.pos += 1; + Ok(()) + } + + fn enter(&mut self) -> Result<(), Error> { + self.depth += 1; + if self.depth > MAX_DEPTH { + return Err(Error::TooDeep); + } + Ok(()) + } + + /// Whitespace, comments, and backslash continuations; newlines too when `newlines`. + fn skip_trivia(&mut self, newlines: bool) { + while let Some(byte) = self.peek() { + match byte { + b' ' | b'\t' | b'\x0c' => self.pos += 1, + b'#' => { + while !matches!(self.peek(), None | Some(b'\n' | b'\r')) { + self.pos += 1; + } + } + // A continuation joins two lines; one that ends the input is an EOF error. + b'\\' if matches!(self.peek_at(1), Some(b'\n' | b'\r')) => { + let len = match (self.peek_at(1), self.peek_at(2)) { + (Some(b'\r'), Some(b'\n')) => 3, + _ => 2, + }; + if self.pos + len >= self.bytes.len() { + break; + } + self.pos += len; + } + b'\n' | b'\r' if newlines => self.pos += 1, + _ => break, + } + } + } + + /// Blank and comment-only lines may precede the expression, whose own line must not be + /// indented (CPython raises `IndentationError`). + fn skip_leading_lines(&mut self) -> Result<(), Error> { + loop { + let line_start = self.pos; + self.skip_trivia(false); + match self.peek() { + Some(b'\n' | b'\r') => self.pos += 1, + Some(_) if line_start > 0 && self.pos > line_start => { + self.pos = line_start; + return Err(self.error()); + } + _ => return Ok(()), + } + } + } + + fn at_logical_line_end(&self) -> bool { + matches!(self.peek(), None | Some(b'\n' | b'\r')) + } + + /// The `eval` input: an expression, or a tuple without parentheses. + fn top_level(&mut self) -> Result { + let first = self.expression()?; + self.skip_trivia(false); + if self.peek() != Some(b',') { + return Ok(first); + } + let mut values = vec![first.value]; + while self.peek() == Some(b',') { + self.pos += 1; + self.skip_trivia(false); + if self.at_logical_line_end() { + break; + } + values.push(self.expression()?.value); + self.skip_trivia(false); + } + Ok(Term::other(Value::Tuple(values))) + } + + /// A sum of unary terms, checked as `ast.literal_eval` checks `BinOp`. + fn expression(&mut self) -> Result { + let mut left = self.unary()?; + loop { + self.skip_trivia(self.brackets > 0); + let subtract = match self.peek() { + Some(b'+') => false, + Some(b'-') => true, + _ => return Ok(left), + }; + let at = self.pos; + self.pos += 1; + let right = self.unary()?; + left = complex_sum(left, subtract, right) + .ok_or(Error::InvalidLiteral(self.offset + at))?; + } + } + + fn unary(&mut self) -> Result { + self.skip_trivia(self.brackets > 0); + let negative = match self.peek() { + Some(b'+') => false, + Some(b'-') => true, + _ => return self.primary(), + }; + let at = self.pos; + self.pos += 1; + self.enter()?; + let operand = self.unary()?; + self.depth -= 1; + if operand.kind != Kind::Constant || !operand.is_number() { + return Err(Error::InvalidLiteral(self.offset + at)); + } + let value = if !negative { + operand.value + } else { + match operand.value { + Value::Int(value) => Value::Int(-value), + Value::Float(value) => Value::Float(-value), + Value::Complex { re, im } => Value::Complex { re: -re, im: -im }, + _ => unreachable!("checked numeric above"), + } + }; + Ok(Term { + value, + kind: Kind::Signed, + }) + } + + fn primary(&mut self) -> Result { + match self.peek() { + Some(b'(') => self.parenthesized(), + Some(b'[') => self.list(), + Some(b'{') => self.braced(), + Some(b'0'..=b'9') => self.number(), + Some(b'.') if matches!(self.peek_at(1), Some(b'0'..=b'9')) => self.number(), + Some(b'\'' | b'"') => self.strings(), + Some(byte) if byte.is_ascii_alphabetic() || byte == b'_' => { + if self.string_prefix_len().is_some() { + return self.strings(); + } + self.name() + } + _ => Err(self.error()), + } + } + + fn open(&mut self) -> Result<(), Error> { + self.enter()?; + self.brackets += 1; + self.pos += 1; + Ok(()) + } + + fn close(&mut self, byte: u8) -> Result<(), Error> { + self.skip_trivia(true); + self.expect(byte)?; + self.brackets -= 1; + self.depth -= 1; + Ok(()) + } + + /// Comma-separated expressions up to `close`, with an optional trailing comma. + fn elements(&mut self, close: u8) -> Result, Error> { + let mut values = Vec::new(); + loop { + self.skip_trivia(true); + if self.peek() == Some(close) { + return Ok(values); + } + values.push(self.expression()?.value); + self.skip_trivia(true); + if self.peek() != Some(b',') { + return Ok(values); + } + self.pos += 1; + } + } + + fn parenthesized(&mut self) -> Result { + self.open()?; + self.skip_trivia(true); + if self.peek() == Some(b')') { + self.close(b')')?; + return Ok(Term::other(Value::Tuple(Vec::new()))); + } + let first = self.expression()?; + self.skip_trivia(true); + if self.peek() != Some(b',') { + self.close(b')')?; + return Ok(first); + } + self.pos += 1; + let mut values = vec![first.value]; + values.extend(self.elements(b')')?); + self.close(b')')?; + Ok(Term::other(Value::Tuple(values))) + } + + fn list(&mut self) -> Result { + self.open()?; + let values = self.elements(b']')?; + self.close(b']')?; + Ok(Term::other(Value::List(values))) + } + + fn braced(&mut self) -> Result { + self.open()?; + self.skip_trivia(true); + if self.peek() == Some(b'}') { + self.close(b'}')?; + return Ok(Term::other(Value::Dict(Vec::new()))); + } + let first = self.expression()?.value; + self.skip_trivia(true); + if self.peek() != Some(b':') { + let mut members = UniqueValues::default(); + members.insert(first, None)?; + if self.peek() == Some(b',') { + self.pos += 1; + for member in self.elements(b'}')? { + members.insert(member, None)?; + } + } + self.close(b'}')?; + return Ok(Term::other(Value::Set(members.keys))); + } + let mut entries = UniqueValues::default(); + let mut key = first; + loop { + self.expect(b':')?; + let value = self.expression()?.value; + entries.insert(key, Some(value))?; + self.skip_trivia(true); + if self.peek() != Some(b',') { + break; + } + self.pos += 1; + self.skip_trivia(true); + if self.peek() == Some(b'}') { + break; + } + key = self.expression()?.value; + self.skip_trivia(true); + } + self.close(b'}')?; + Ok(Term::other(Value::Dict(entries.into_entries()))) + } + + fn identifier(&mut self) -> &[u8] { + let start = self.pos; + while matches!(self.peek(), Some(byte) if byte.is_ascii_alphanumeric() || byte == b'_') { + self.pos += 1; + } + &self.bytes[start..self.pos] + } + + fn name(&mut self) -> Result { + let at = self.pos; + let value = match self.identifier() { + b"True" => Value::Bool(true), + b"False" => Value::Bool(false), + b"None" => Value::None, + b"set" => { + self.skip_trivia(self.brackets > 0); + self.expect(b'(')?; + self.skip_trivia(true); + self.expect(b')')?; + return Ok(Term::other(Value::Set(Vec::new()))); + } + _ => return Err(Error::InvalidLiteral(self.offset + at)), + }; + Ok(Term { + value, + kind: Kind::Constant, + }) + } + + /// Digits with single underscores between them, as CPython's `digitpart`. + fn digits(&mut self, radix: u32, out: &mut String) -> Result<(), Error> { + let start = out.len(); + loop { + match self.peek() { + Some(byte) if (byte as char).is_digit(radix) => { + out.push(byte as char); + self.pos += 1; + } + Some(b'_') + if out.len() > start + && matches!(self.peek_at(1), Some(next) if (next as char).is_digit(radix)) => + { + self.pos += 1; + } + _ => break, + } + } + if out.len() == start { + return Err(self.error()); + } + Ok(()) + } + + fn number(&mut self) -> Result { + let start = self.pos; + let radix = match ( + self.peek(), + self.peek_at(1).map(|byte| byte.to_ascii_lowercase()), + ) { + (Some(b'0'), Some(b'x')) => Some(16), + (Some(b'0'), Some(b'o')) => Some(8), + (Some(b'0'), Some(b'b')) => Some(2), + _ => None, + }; + let mut text = String::new(); + let value = if let Some(radix) = radix { + self.pos += 2; + if self.peek() == Some(b'_') { + self.pos += 1; + } + self.digits(radix, &mut text)?; + Value::Int(BigInt::parse_bytes(text.as_bytes(), radix).ok_or(self.error())?) + } else { + let mut is_float = false; + if self.peek() != Some(b'.') { + self.digits(10, &mut text)?; + } + let integer_digits = text.clone(); + if self.peek() == Some(b'.') { + is_float = true; + self.pos += 1; + text.push('.'); + if matches!(self.peek(), Some(b'0'..=b'9')) { + self.digits(10, &mut text)?; + } + } + if matches!(self.peek(), Some(b'e' | b'E')) { + is_float = true; + self.pos += 1; + text.push('e'); + if let Some(sign @ (b'+' | b'-')) = self.peek() { + text.push(sign as char); + self.pos += 1; + } + self.digits(10, &mut text)?; + } + if matches!(self.peek(), Some(b'j' | b'J')) { + self.pos += 1; + let im = text.parse::().map_err(|_| self.error())?; + Value::Complex { re: 0.0, im } + } else if is_float { + Value::Float(text.parse::().map_err(|_| self.error())?) + } else { + if integer_digits.len() > 1 + && integer_digits.starts_with('0') + && integer_digits.bytes().any(|digit| digit != b'0') + { + return Err(Error::InvalidLiteral(self.offset + start)); + } + Value::Int(BigInt::parse_bytes(integer_digits.as_bytes(), 10).ok_or(self.error())?) + } + }; + if matches!(self.peek(), Some(byte) if byte.is_ascii_alphanumeric() || byte == b'_' || byte == b'.') + { + return Err(self.error()); + } + Ok(Term { + value, + kind: Kind::Constant, + }) + } + + /// The length of a valid string prefix (`r`, `u`, `b`, `br`, `rb`, any case) directly + /// followed by a quote. + fn string_prefix_len(&self) -> Option { + let mut len = 0; + while matches!(self.peek_at(len), Some(byte) if byte.is_ascii_alphabetic()) && len < 3 { + len += 1; + } + if !matches!(self.peek_at(len), Some(b'\'' | b'"')) { + return None; + } + let prefix: Vec = self.bytes[self.pos..self.pos + len] + .iter() + .map(u8::to_ascii_lowercase) + .collect(); + matches!(prefix.as_slice(), b"" | b"r" | b"u" | b"b" | b"br" | b"rb").then_some(len) + } + + /// Adjacent string literals concatenate; `str` and `bytes` cannot mix. + fn strings(&mut self) -> Result { + let mut text: Option = None; + let mut bytes: Option> = None; + loop { + let at = self.pos; + let Some(prefix_len) = self.string_prefix_len() else { + break; + }; + let prefix = &self.bytes[self.pos..self.pos + prefix_len]; + let raw = prefix.iter().any(|byte| byte.eq_ignore_ascii_case(&b'r')); + let is_bytes = prefix.iter().any(|byte| byte.eq_ignore_ascii_case(&b'b')); + self.pos += prefix_len; + let mut out = Vec::new(); + self.string_body(raw, is_bytes, &mut out)?; + if is_bytes { + if text.is_some() { + return Err(Error::InvalidLiteral(self.offset + at)); + } + bytes.get_or_insert_with(Vec::new).extend(out); + } else { + if bytes.is_some() { + return Err(Error::InvalidLiteral(self.offset + at)); + } + let piece = + String::from_utf8(out).map_err(|_| Error::InvalidLiteral(self.offset + at))?; + text.get_or_insert_with(String::new).push_str(&piece); + } + self.skip_trivia(self.brackets > 0); + } + let value = match (text, bytes) { + (Some(text), None) => Value::Str(text), + (None, Some(bytes)) => Value::Bytes(bytes), + _ => return Err(self.error()), + }; + Ok(Term { + value, + kind: Kind::Constant, + }) + } + + /// One quoted body, decoded into UTF-8 (`str`) or raw bytes (`bytes`). + fn string_body(&mut self, raw: bool, is_bytes: bool, out: &mut Vec) -> Result<(), Error> { + let quote = self.bytes[self.pos]; + let triple = self.peek_at(1) == Some(quote) && self.peek_at(2) == Some(quote); + self.pos += if triple { 3 } else { 1 }; + loop { + let Some(byte) = self.peek() else { + return Err(self.error()); + }; + if byte == quote + && (!triple || (self.peek_at(1) == Some(quote) && self.peek_at(2) == Some(quote))) + { + self.pos += if triple { 3 } else { 1 }; + return Ok(()); + } + match byte { + b'\n' | b'\r' if !triple => return Err(self.error()), + b'\\' if raw => { + let Some(next) = self.peek_at(1) else { + return Err(self.error()); + }; + out.push(b'\\'); + self.pos += 1; + if next == b'\n' || next == b'\r' || next == quote || next == b'\\' { + out.push(next); + self.pos += 1; + } + } + b'\\' => { + self.pos += 1; + self.escape(is_bytes, out)?; + } + byte if is_bytes && !byte.is_ascii() => return Err(self.error()), + byte => { + out.push(byte); + self.pos += 1; + } + } + } + } + + fn escape(&mut self, is_bytes: bool, out: &mut Vec) -> Result<(), Error> { + let Some(byte) = self.peek() else { + return Err(self.error()); + }; + self.pos += 1; + let simple = match byte { + b'\n' => return Ok(()), + b'\r' => { + if self.peek() == Some(b'\n') { + self.pos += 1; + } + return Ok(()); + } + b'\\' | b'\'' | b'"' => byte, + b'a' => 0x07, + b'b' => 0x08, + b'f' => 0x0c, + b'n' => b'\n', + b'r' => b'\r', + b't' => b'\t', + b'v' => 0x0b, + b'0'..=b'7' => { + let mut code = u32::from(byte - b'0'); + for _ in 0..2 { + match self.peek() { + Some(digit @ b'0'..=b'7') => { + code = code * 8 + u32::from(digit - b'0'); + self.pos += 1; + } + _ => break, + } + } + // Bytes keep the low eight bits of `\400`-`\777`, as CPython does. + return self.push_code(if is_bytes { code & 0xff } else { code }, is_bytes, out); + } + b'x' => { + let code = self.hex(2)?; + return self.push_code(code, is_bytes, out); + } + b'u' if !is_bytes => { + let code = self.hex(4)?; + return self.push_code(code, is_bytes, out); + } + b'U' if !is_bytes => { + let code = self.hex(8)?; + return self.push_code(code, is_bytes, out); + } + b'N' if !is_bytes => return Err(self.error()), + _ => { + // Unknown escapes keep the backslash (a `SyntaxWarning` in CPython). + out.push(b'\\'); + self.pos -= 1; + return Ok(()); + } + }; + out.push(simple); + Ok(()) + } + + fn hex(&mut self, count: usize) -> Result { + let mut code = 0u32; + for _ in 0..count { + let digit = self + .peek() + .and_then(|byte| (byte as char).to_digit(16)) + .ok_or(self.error())?; + code = code * 16 + digit; + self.pos += 1; + } + Ok(code) + } + + fn push_code(&self, code: u32, is_bytes: bool, out: &mut Vec) -> Result<(), Error> { + if is_bytes { + out.push(u8::try_from(code).map_err(|_| self.error())?); + return Ok(()); + } + let ch = char::from_u32(code).ok_or(self.error())?; + let mut buffer = [0u8; 4]; + out.extend_from_slice(ch.encode_utf8(&mut buffer).as_bytes()); + Ok(()) + } +} + +/// `left + right` or `left - right` as `ast.literal_eval` permits: a signed real on the +/// left and an unsigned complex constant on the right, combined with CPython 3.14's +/// mixed-mode rules, which leave the imaginary part untouched by the real operand. +fn complex_sum(left: Term, subtract: bool, right: Term) -> Option { + if left.kind == Kind::Other || right.kind != Kind::Constant { + return None; + } + let real = match &left.value { + Value::Int(value) => value.to_f64().filter(|value| value.is_finite())?, + Value::Float(value) => *value, + _ => return None, + }; + let Value::Complex { re, im } = right.value else { + return None; + }; + let value = if subtract { + Value::Complex { + re: real - re, + im: -im, + } + } else { + Value::Complex { re: real + re, im } + }; + Some(Term::other(value)) +} + +/// Python equality for hashable literal values: numbers compare by value across `bool`, +/// `int`, `float`, and `complex`, so `1`, `1.0`, `True`, and `(1+0j)` are one key. +#[derive(Hash, PartialEq, Eq)] +enum KeyId { + None, + Int(BigInt), + Float(u64), + Complex(u64, u64), + Str(String), + Bytes(Vec), + Tuple(Vec), +} + +fn float_key(value: f64) -> KeyId { + if value.fract() == 0.0 + && let Some(integer) = BigInt::from_f64(value) + { + return KeyId::Int(integer); + } + KeyId::Float(value.to_bits()) +} + +fn key_id(value: &Value) -> Result { + Ok(match value { + Value::None => KeyId::None, + Value::Bool(value) => KeyId::Int(BigInt::from(u8::from(*value))), + Value::Int(value) => KeyId::Int(value.clone()), + Value::Float(value) => float_key(*value), + Value::Complex { re, im } if *im == 0.0 => float_key(*re), + Value::Complex { re, im } => KeyId::Complex((re + 0.0).to_bits(), (im + 0.0).to_bits()), + Value::Str(text) => KeyId::Str(text.clone()), + Value::Bytes(bytes) => KeyId::Bytes(bytes.clone()), + Value::Tuple(values) => KeyId::Tuple(values.iter().map(key_id).collect::>()?), + value @ (Value::List(_) | Value::Dict(_) | Value::Set(_)) => { + return Err(Error::Unhashable(value.type_name())); + } + }) +} + +/// Dict entries or set members in first-seen order: a repeated key keeps its first +/// position and, for dicts, takes the latest value. +#[derive(Default)] +struct UniqueValues { + keys: Vec, + values: Vec, + index: HashMap, +} + +impl UniqueValues { + fn insert(&mut self, key: Value, value: Option) -> Result<(), Error> { + match self.index.entry(key_id(&key)?) { + Entry::Occupied(slot) => { + if let Some(value) = value { + self.values[*slot.get()] = value; + } + } + Entry::Vacant(slot) => { + slot.insert(self.keys.len()); + self.keys.push(key); + self.values.extend(value); + } + } + Ok(()) + } + + fn into_entries(self) -> Vec<(Value, Value)> { + self.keys.into_iter().zip(self.values).collect() + } +} diff --git a/litellm-rust/crates/python-compat/src/pickle.rs b/litellm-rust/crates/python-compat/src/pickle.rs new file mode 100644 index 00000000000..bff7442dc6b --- /dev/null +++ b/litellm-rust/crates/python-compat/src/pickle.rs @@ -0,0 +1,187 @@ +//! `pickle.loads` and `pickle.dumps` for plain data, as diskcache stores LiteLLM values. +//! +//! Both directions go through `serde-pickle`'s serde interface rather than +//! `serde_pickle::Value`, because that value type keeps dicts in a `BTreeMap` and would +//! reorder keys. The serde interface keeps insertion order, at the cost of reporting +//! `tuple`, `set`, and `frozenset` as sequences: [`loads`] decodes all three as lists. +//! Python objects that need a class (`GLOBAL`/`REDUCE`) and recursive structures fail. + +use std::fmt; + +use serde::{ + Deserializer, Serialize, Serializer, + de::{self, DeserializeSeed, MapAccess, SeqAccess, Visitor}, + ser::{SerializeMap, SerializeSeq, SerializeTuple}, +}; +use serde_pickle::{DeOptions, SerOptions}; + +use crate::{Error, MAX_DEPTH, Value}; + +/// `pickle.loads(data)` for any protocol from 0 to 5. +pub fn loads(data: &[u8]) -> Result { + let mut deserializer = serde_pickle::Deserializer::new(data, DeOptions::new()); + let value = Seed { depth: 0 } + .deserialize(&mut deserializer) + .map_err(|error| Error::InvalidPickle(error.to_string()))?; + deserializer + .end() + .map_err(|error| Error::InvalidPickle(error.to_string()))?; + Ok(value) +} + +/// `pickle.dumps(value, protocol=3)`. Every Python 3 reads protocol 3, whatever its own +/// default. Sets and complex numbers are rejected rather than silently changing type. +pub fn dumps(value: &Value) -> Result, Error> { + check_picklable(value, 0)?; + serde_pickle::to_vec(&Pickled(value), SerOptions::new()) + .map_err(|error| Error::InvalidPickle(error.to_string())) +} + +fn check_picklable(value: &Value, depth: usize) -> Result<(), Error> { + if depth > MAX_DEPTH { + return Err(Error::TooDeep); + } + match value { + Value::Int(value) if i64::try_from(value).is_err() => Err(Error::IntegerOutOfRange), + value @ (Value::Set(_) | Value::Complex { .. }) => { + Err(Error::NotPicklable(value.type_name())) + } + Value::List(values) | Value::Tuple(values) => values + .iter() + .try_for_each(|value| check_picklable(value, depth + 1)), + Value::Dict(entries) => entries.iter().try_for_each(|(key, value)| { + check_picklable(key, depth + 1)?; + check_picklable(value, depth + 1) + }), + _ => Ok(()), + } +} + +struct Pickled<'a>(&'a Value); + +impl Serialize for Pickled<'_> { + fn serialize(&self, serializer: S) -> Result { + match self.0 { + Value::None => serializer.serialize_unit(), + Value::Bool(value) => serializer.serialize_bool(*value), + Value::Int(value) => { + let value = i64::try_from(value) + .map_err(|_| serde::ser::Error::custom("integer out of i64 range"))?; + serializer.serialize_i64(value) + } + Value::Float(value) => serializer.serialize_f64(*value), + Value::Str(text) => serializer.serialize_str(text), + Value::Bytes(bytes) => serializer.serialize_bytes(bytes), + Value::List(values) => { + let mut seq = serializer.serialize_seq(Some(values.len()))?; + for value in values { + seq.serialize_element(&Pickled(value))?; + } + seq.end() + } + Value::Tuple(values) => { + let mut tuple = serializer.serialize_tuple(values.len())?; + for value in values { + tuple.serialize_element(&Pickled(value))?; + } + tuple.end() + } + Value::Dict(entries) => { + let mut map = serializer.serialize_map(Some(entries.len()))?; + for (key, value) in entries { + map.serialize_entry(&Pickled(key), &Pickled(value))?; + } + map.end() + } + value @ (Value::Set(_) | Value::Complex { .. }) => Err(serde::ser::Error::custom( + format!("{} cannot be pickled as plain data", value.type_name()), + )), + } + } +} + +#[derive(Clone, Copy)] +struct Seed { + depth: usize, +} + +impl Seed { + fn child(self) -> Result { + if self.depth >= MAX_DEPTH { + return Err(E::custom(Error::TooDeep)); + } + Ok(Self { + depth: self.depth + 1, + }) + } +} + +impl<'de> DeserializeSeed<'de> for Seed { + type Value = Value; + + fn deserialize>(self, deserializer: D) -> Result { + deserializer.deserialize_any(self) + } +} + +impl<'de> Visitor<'de> for Seed { + type Value = Value; + + fn expecting(&self, formatter: &mut fmt::Formatter<'_>) -> fmt::Result { + formatter.write_str("a plain Python data value") + } + + fn visit_unit(self) -> Result { + Ok(Value::None) + } + + fn visit_bool(self, value: bool) -> Result { + Ok(Value::Bool(value)) + } + + fn visit_i64(self, value: i64) -> Result { + Ok(Value::Int(value.into())) + } + + fn visit_u64(self, value: u64) -> Result { + Ok(Value::Int(value.into())) + } + + fn visit_f64(self, value: f64) -> Result { + Ok(Value::Float(value)) + } + + fn visit_str(self, value: &str) -> Result { + Ok(Value::Str(value.to_owned())) + } + + fn visit_string(self, value: String) -> Result { + Ok(Value::Str(value)) + } + + fn visit_bytes(self, value: &[u8]) -> Result { + Ok(Value::Bytes(value.to_vec())) + } + + fn visit_byte_buf(self, value: Vec) -> Result { + Ok(Value::Bytes(value)) + } + + fn visit_seq>(self, mut seq: A) -> Result { + let child = self.child()?; + let mut values = Vec::with_capacity(seq.size_hint().unwrap_or(0).min(4096)); + while let Some(value) = seq.next_element_seed(child)? { + values.push(value); + } + Ok(Value::List(values)) + } + + fn visit_map>(self, mut map: A) -> Result { + let child = self.child()?; + let mut entries = Vec::with_capacity(map.size_hint().unwrap_or(0).min(4096)); + while let Some(key) = map.next_key_seed(child)? { + entries.push((key, map.next_value_seed(child)?)); + } + Ok(Value::Dict(entries)) + } +} diff --git a/litellm-rust/crates/python-compat/src/repr.rs b/litellm-rust/crates/python-compat/src/repr.rs new file mode 100644 index 00000000000..1cf20d87716 --- /dev/null +++ b/litellm-rust/crates/python-compat/src/repr.rs @@ -0,0 +1,237 @@ +//! `repr(value)` and `str(value)` byte for byte. +//! +//! LiteLLM hashes `str(value)` into cache keys and writes `str(dict)` into Redis, so these +//! strings are persisted identifiers rather than display text: every quote choice, escape, +//! and float digit must match CPython. + +use std::fmt::Write; + +use crate::Value; + +/// Generated by `scripts/generate_nonprintable.py`; see `generated/nonprintable.rs`. +mod nonprintable { + include!(concat!( + env!("CARGO_MANIFEST_DIR"), + "/generated/nonprintable.rs" + )); +} + +/// Unicode version of the printable-character table, from the Python that generated it. +pub const UNICODE_VERSION: &str = nonprintable::UNICODE_VERSION; + +/// `repr(value)`. +pub fn repr(value: &Value) -> String { + let mut out = String::new(); + write_repr(&mut out, value); + out +} + +/// `str(value)`: a string's own contents, and `repr` for every other value. +pub fn to_str(value: &Value) -> String { + match value { + Value::Str(text) => text.clone(), + value => repr(value), + } +} + +/// `repr(float)`, the shortest round-trip form with CPython's exponent thresholds. +pub fn float_repr(value: f64) -> String { + format_float(value, true) +} + +fn write_repr(out: &mut String, value: &Value) { + match value { + Value::None => out.push_str("None"), + Value::Bool(true) => out.push_str("True"), + Value::Bool(false) => out.push_str("False"), + Value::Int(value) => { + let _ = write!(out, "{value}"); + } + Value::Float(value) => out.push_str(&float_repr(*value)), + Value::Complex { re, im } => write_complex(out, *re, *im), + Value::Str(text) => write_str(out, text), + Value::Bytes(bytes) => write_bytes(out, bytes), + Value::List(values) => write_sequence(out, '[', values, ']'), + Value::Tuple(values) if values.len() == 1 => { + out.push('('); + write_repr(out, &values[0]); + out.push_str(",)"); + } + Value::Tuple(values) => write_sequence(out, '(', values, ')'), + Value::Set(values) if values.is_empty() => out.push_str("set()"), + Value::Set(values) => write_sequence(out, '{', values, '}'), + Value::Dict(entries) => { + out.push('{'); + for (index, (key, value)) in entries.iter().enumerate() { + if index > 0 { + out.push_str(", "); + } + write_repr(out, key); + out.push_str(": "); + write_repr(out, value); + } + out.push('}'); + } + } +} + +fn write_sequence(out: &mut String, open: char, values: &[Value], close: char) { + out.push(open); + for (index, value) in values.iter().enumerate() { + if index > 0 { + out.push_str(", "); + } + write_repr(out, value); + } + out.push(close); +} + +/// `complex.__repr__`: a `+0.0` real part prints only the imaginary part, without parens. +fn write_complex(out: &mut String, re: f64, im: f64) { + if re == 0.0 && re.is_sign_positive() { + out.push_str(&format_float(im, false)); + out.push('j'); + return; + } + out.push('('); + out.push_str(&format_float(re, false)); + let im_text = format_float(im, false); + if !im_text.starts_with('-') { + out.push('+'); + } + out.push_str(&im_text); + out.push_str("j)"); +} + +/// `PyOS_double_to_string(value, 'r', 0, flags)`: scientific notation below 1e-4 and from +/// 1e16 up, with a signed exponent of at least two digits. `add_dot_0` is +/// `Py_DTSF_ADD_DOT_0`, which `float` sets and `complex` does not. +fn format_float(value: f64, add_dot_0: bool) -> String { + if value.is_nan() { + return "nan".to_owned(); + } + if value.is_infinite() { + return if value > 0.0 { "inf" } else { "-inf" }.to_owned(); + } + // Rust's `{:e}` prints the shortest round-trip digits, like CPython's 'r' mode. + let scientific = format!("{value:e}"); + let (mantissa, exponent) = scientific + .split_once('e') + .expect("`{:e}` always prints an exponent"); + let exponent: i32 = exponent.parse().expect("`{:e}` exponent is an integer"); + let (sign, mantissa) = match mantissa.strip_prefix('-') { + Some(mantissa) => ("-", mantissa), + None => ("", mantissa), + }; + let digits: String = mantissa.chars().filter(|ch| *ch != '.').collect(); + + let mut out = String::from(sign); + if !(-4..16).contains(&exponent) { + out.push_str(&digits[..1]); + if digits.len() > 1 { + out.push('.'); + out.push_str(&digits[1..]); + } + let _ = write!( + out, + "e{}{:02}", + if exponent < 0 { '-' } else { '+' }, + exponent.unsigned_abs() + ); + } else if exponent < 0 { + out.push_str("0."); + out.extend(std::iter::repeat_n('0', (-exponent - 1) as usize)); + out.push_str(&digits); + } else { + let integer_digits = exponent as usize + 1; + if digits.len() > integer_digits { + out.push_str(&digits[..integer_digits]); + out.push('.'); + out.push_str(&digits[integer_digits..]); + } else { + out.push_str(&digits); + out.extend(std::iter::repeat_n('0', integer_digits - digits.len())); + if add_dot_0 { + out.push_str(".0"); + } + } + } + out +} + +/// `unicode_repr`: single quotes unless the text has a `'` and no `"`. Printable non-ASCII +/// stays literal; everything `str.isprintable()` rejects is escaped. +fn write_str(out: &mut String, text: &str) { + let quote = if text.contains('\'') && !text.contains('"') { + '"' + } else { + '\'' + }; + out.push(quote); + for ch in text.chars() { + match ch { + '\\' => out.push_str("\\\\"), + '\t' => out.push_str("\\t"), + '\n' => out.push_str("\\n"), + '\r' => out.push_str("\\r"), + ch if ch == quote => { + out.push('\\'); + out.push(ch); + } + ch if is_printable(ch) => out.push(ch), + ch => { + let code = ch as u32; + let _ = match code { + 0..=0xff => write!(out, "\\x{code:02x}"), + 0x100..=0xffff => write!(out, "\\u{code:04x}"), + _ => write!(out, "\\U{code:08x}"), + }; + } + } + } + out.push(quote); +} + +/// `bytes.__repr__`: the same quote rule as `str`, with every byte outside printable ASCII +/// escaped as `\xhh`. +fn write_bytes(out: &mut String, bytes: &[u8]) { + let quote = if bytes.contains(&b'\'') && !bytes.contains(&b'"') { + b'"' + } else { + b'\'' + }; + out.push('b'); + out.push(quote as char); + for &byte in bytes { + match byte { + b'\\' => out.push_str("\\\\"), + b'\t' => out.push_str("\\t"), + b'\n' => out.push_str("\\n"), + b'\r' => out.push_str("\\r"), + byte if byte == quote => { + out.push('\\'); + out.push(byte as char); + } + 0x20..=0x7e => out.push(byte as char), + byte => { + let _ = write!(out, "\\x{byte:02x}"); + } + } + } + out.push(quote as char); +} + +fn is_printable(ch: char) -> bool { + let code = ch as u32; + nonprintable::NONPRINTABLE + .binary_search_by(|&(low, high)| { + if high < code { + std::cmp::Ordering::Less + } else if low > code { + std::cmp::Ordering::Greater + } else { + std::cmp::Ordering::Equal + } + }) + .is_err() +} diff --git a/litellm-rust/crates/python-compat/src/truthy.rs b/litellm-rust/crates/python-compat/src/truthy.rs new file mode 100644 index 00000000000..af747202572 --- /dev/null +++ b/litellm-rust/crates/python-compat/src/truthy.rs @@ -0,0 +1,18 @@ +use num_bigint::Sign; + +use crate::Value; + +/// `bool(value)` for plain data: `None`, `False`, zero, and empty containers are false. +pub fn truthy(value: &Value) -> bool { + match value { + Value::None => false, + Value::Bool(value) => *value, + Value::Int(value) => value.sign() != Sign::NoSign, + Value::Float(value) => *value != 0.0, + Value::Complex { re, im } => *re != 0.0 || *im != 0.0, + Value::Str(value) => !value.is_empty(), + Value::Bytes(value) => !value.is_empty(), + Value::Tuple(values) | Value::List(values) | Value::Set(values) => !values.is_empty(), + Value::Dict(entries) => !entries.is_empty(), + } +} diff --git a/litellm-rust/crates/python-compat/src/value.rs b/litellm-rust/crates/python-compat/src/value.rs new file mode 100644 index 00000000000..b1397190638 --- /dev/null +++ b/litellm-rust/crates/python-compat/src/value.rs @@ -0,0 +1,53 @@ +use num_bigint::BigInt; + +/// A Python value built only from literals: what `ast.literal_eval` can return. +#[derive(Clone, Debug, PartialEq)] +pub enum Value { + None, + Bool(bool), + Int(BigInt), + Float(f64), + Complex { + re: f64, + im: f64, + }, + Str(String), + Bytes(Vec), + Tuple(Vec), + List(Vec), + /// Insertion-ordered, with Python's key equality already applied. + Dict(Vec<(Value, Value)>), + /// Literal order, with Python's member equality already applied. + Set(Vec), +} + +impl Value { + /// Python's type name, as it appears in `TypeError` messages. + pub fn type_name(&self) -> &'static str { + match self { + Value::None => "NoneType", + Value::Bool(_) => "bool", + Value::Int(_) => "int", + Value::Float(_) => "float", + Value::Complex { .. } => "complex", + Value::Str(_) => "str", + Value::Bytes(_) => "bytes", + Value::Tuple(_) => "tuple", + Value::List(_) => "list", + Value::Dict(_) => "dict", + Value::Set(_) => "set", + } + } +} + +impl From for Value { + fn from(value: i64) -> Self { + Value::Int(value.into()) + } +} + +impl From<&str> for Value { + fn from(value: &str) -> Self { + Value::Str(value.to_owned()) + } +} diff --git a/litellm-rust/crates/python-compat/tests/fixtures.rs b/litellm-rust/crates/python-compat/tests/fixtures.rs new file mode 100644 index 00000000000..9c202fdc5f1 --- /dev/null +++ b/litellm-rust/crates/python-compat/tests/fixtures.rs @@ -0,0 +1,343 @@ +//! Replays `generated/values.json`, which CPython wrote with `scripts/generate_fixtures.py`. + +use std::{collections::BTreeMap, fs::File, io::Write}; + +use litellm_python_compat::{ + Value, json, + literal::literal_eval, + pickle, + repr::{repr, to_str}, + truthy::truthy, +}; +use rstest::{fixture, rstest}; +use serde::Deserialize; + +#[derive(Deserialize)] +struct Fixtures { + rows: Vec, + sources: Vec, +} + +/// `ast.literal_eval(source)`: the `repr` of its result, or the exception class it raised. +#[derive(Deserialize)] +struct Source { + name: String, + source: String, + repr: Option, + error: Option, +} + +#[derive(Deserialize)] +struct Row { + name: String, + source: String, + literal: bool, + plain: bool, + repr: String, + str: String, + truthy: bool, + json: Option, + json_error: Option, + pickle: Option>, + view: Option, +} + +/// Parsed once for the whole test binary. +#[fixture] +#[once] +fn fixtures() -> Fixtures { + serde_json::from_str(include_str!(concat!( + env!("CARGO_MANIFEST_DIR"), + "/generated/values.json" + ))) + .expect("values.json matches the fixture schema") +} + +/// Accepted differences from CPython: `(fixture source, check prefix, reason)`. Each entry +/// must still differ, so a dependency fix that removes one fails the test until it is deleted. +const KNOWN: &[(&str, &str, &str)] = &[ + ( + "...", + "literal_eval source", + "`Ellipsis` is not part of the data model", + ), + ( + r"'\ud800'", + "literal_eval source", + "a Rust `String` cannot hold a lone surrogate", + ), + ( + r"'\N{BULLET}'", + "literal_eval source", + "`\\N{NAME}` needs the Unicode name table", + ), + ( + "nested_150", + "literal_eval", + "deeper than MAX_DEPTH: rejected for stack safety, where CPython still parses it", + ), + ( + "nested_150", + "pickle.loads", + "deeper than MAX_DEPTH: rejected for stack safety, where CPython has no limit", + ), + ( + "2**64", + "pickle.loads", + "serde-pickle's serde interface stops at i64", + ), + ( + "-(2**70)", + "pickle.loads", + "serde-pickle's serde interface stops at i64", + ), + ( + "2**64", + "pickle.dumps", + "serde-pickle's serde interface stops at i64", + ), + ( + "-(2**70)", + "pickle.dumps", + "serde-pickle's serde interface stops at i64", + ), + ( + "2**64", + "to_json", + "serde_json has no exact form for integers beyond u64", + ), + ( + "-(2**70)", + "to_json", + "serde_json has no exact form for integers beyond i64", + ), + ( + "b''", + "pickle.loads protocol 0", + "protocols 0-2 pickle `b''` as a `bytes()` call", + ), + ( + "b''", + "pickle.loads protocol 1", + "protocols 0-2 pickle `b''` as a `bytes()` call", + ), + ( + "b''", + "pickle.loads protocol 2", + "protocols 0-2 pickle `b''` as a `bytes()` call", + ), +]; + +/// Collects every mismatch so one run reports the whole divergence set. +#[derive(Default)] +struct Mismatches { + unexpected: Vec, + known_seen: Vec, + known_scope: Vec, +} + +impl Mismatches { + fn known(source: &str, what: &str) -> Option { + KNOWN + .iter() + .position(|(known, prefix, _)| *known == source && what.starts_with(prefix)) + } + + fn check(&mut self, row: &Row, what: &str, expected: &str, actual: &str) { + self.check_source(&row.name, what, expected, actual); + } + + /// `name` identifies the fixture row in reports and in [`KNOWN`]. + fn check_source(&mut self, name: &str, what: &str, expected: &str, actual: &str) { + let known = Self::known(name, what); + if let Some(index) = known { + self.known_scope.push(index); + } + if expected == actual { + return; + } + match known { + Some(index) => self.known_seen.push(index), + None => self.unexpected.push(format!( + "{name:?} [{what}]\n python: {expected}\n rust: {actual}" + )), + } + } + + fn finish(self) { + let resolved: Vec<_> = self + .known_scope + .iter() + .filter(|index| !self.known_seen.contains(index)) + .map(|&index| format!("{} [{}]", KNOWN[index].0, KNOWN[index].1)) + .collect(); + assert!( + self.unexpected.is_empty() && resolved.is_empty(), + "{} mismatches with CPython:\n{}\nknown divergences that now match (delete them \ + from KNOWN): {resolved:?}", + self.unexpected.len(), + self.unexpected.join("\n"), + ); + } +} + +fn check_value(mismatches: &mut Mismatches, row: &Row, value: &Value) { + mismatches.check(row, "repr", &row.repr, &repr(value)); + mismatches.check(row, "str", &row.str, &to_str(value)); + mismatches.check( + row, + "bool", + &row.truthy.to_string(), + &truthy(value).to_string(), + ); + let expected = row.json.clone().or_else(|| { + row.json_error + .clone() + .map(|error| format!("error: {error}")) + }); + let actual = match json::dumps(value) { + Ok(text) => text, + Err(error) => format!("error: {error}"), + }; + mismatches.check( + row, + "json.dumps", + expected.as_deref().unwrap_or(""), + &actual, + ); +} + +#[rstest] +fn literal_rows_match_python_repr_str_bool_and_json(fixtures: &Fixtures) { + let mut mismatches = Mismatches::default(); + for row in fixtures.rows.iter().filter(|row| row.literal) { + match literal_eval(&row.repr) { + Ok(value) => check_value(&mut mismatches, row, &value), + Err(error) => mismatches.check(row, "literal_eval", &row.repr, &error.to_string()), + } + } + mismatches.finish(); +} + +/// Errors compare by outcome only: CPython's exception class is not part of the contract. +#[rstest] +fn literal_eval_matches_python_on_source_texts(fixtures: &Fixtures) { + let mut mismatches = Mismatches::default(); + for case in &fixtures.sources { + let expected = match (&case.repr, &case.error) { + (Some(repr), None) => repr.clone(), + (None, Some(_)) => "an error".to_owned(), + _ => panic!("{:?}: a source records a repr or an error", case.source), + }; + let actual = match literal_eval(&case.source) { + Ok(value) => repr(&value), + Err(_) => "an error".to_owned(), + }; + mismatches.check_source(&case.name, "literal_eval source", &expected, &actual); + } + mismatches.finish(); +} + +#[rstest] +fn pickle_loads_matches_python_at_every_protocol(fixtures: &Fixtures) { + let mut mismatches = Mismatches::default(); + for row in &fixtures.rows { + let Some(pickles) = &row.pickle else { continue }; + for (protocol, data) in pickles { + let data = hex::decode(data).expect("fixture pickle is hex"); + let what = format!("pickle.loads protocol {protocol}"); + match (pickle::loads(&data), row.plain) { + (Ok(value), true) => { + let view = row.view.as_deref().expect("picklable rows have a view"); + mismatches.check(row, &what, view, &repr(&value)); + } + (Err(error), true) => { + mismatches.check(row, &what, "a value", &format!("error: {error}")) + } + (Ok(value), false) => { + mismatches.check(row, &what, "a class-reference error", &repr(&value)) + } + (Err(pickle_error), false) => assert!( + matches!(pickle_error, litellm_python_compat::Error::InvalidPickle(_)), + "{}: {pickle_error}", + row.source + ), + } + } + } + mismatches.finish(); +} + +/// Non-finite floats have no literal form; pickle is how Rust receives them. +#[rstest] +fn values_reached_only_through_pickle_match_python(fixtures: &Fixtures) { + let mut mismatches = Mismatches::default(); + for row in fixtures + .rows + .iter() + .filter(|row| !row.literal && row.plain && row.view.as_deref() == Some(&row.repr)) + { + let data = hex::decode(&row.pickle.as_ref().expect("plain rows pickle")["5"]) + .expect("fixture pickle is hex"); + let value = pickle::loads(&data).expect("plain pickle decodes"); + check_value(&mut mismatches, row, &value); + } + mismatches.finish(); +} + +/// Byte equality with CPython is not the contract: CPython adds memo opcodes and picks the +/// smallest integer opcode. `scripts/verify_rust_pickles.py` checks that CPython reads these +/// back; set `PYTHON_COMPAT_RUST_PICKLES` to a file path to export them. +#[rstest] +fn pickle_dumps_round_trips_every_plain_literal(fixtures: &Fixtures) { + // Truncate up front: the verifier must read this run's rows and nothing else. + let mut export = std::env::var_os("PYTHON_COMPAT_RUST_PICKLES") + .map(|path| File::create(path).expect("the export path is writable")); + let mut mismatches = Mismatches::default(); + for row in fixtures + .rows + .iter() + .filter(|row| row.literal && row.plain && row.view.as_deref() == Some(&row.repr)) + { + // Rows past `MAX_DEPTH` are covered by the literal test's own KNOWN entry. + let Ok(value) = literal_eval(&row.repr) else { + continue; + }; + let data = match pickle::dumps(&value) { + Ok(data) => data, + Err(error) => { + mismatches.check(row, "pickle.dumps", "a pickle", &format!("error: {error}")); + continue; + } + }; + let decoded = pickle::loads(&data).expect("rust pickle decodes"); + mismatches.check(row, "pickle round trip", &row.repr, &repr(&decoded)); + if let Some(file) = &mut export { + writeln!(file, "{}\t{}", hex::encode(&data), repr(&value)) + .expect("the export file is writable"); + } + } + mismatches.finish(); +} + +#[rstest] +fn to_json_matches_python_json_round_trip(fixtures: &Fixtures) { + let mut mismatches = Mismatches::default(); + for row in fixtures.rows.iter().filter(|row| row.literal) { + let Some(expected) = &row.json else { continue }; + let Ok(value) = literal_eval(&row.repr) else { + continue; + }; + let expected: serde_json::Value = + serde_json::from_str(expected).expect("python json.dumps output parses"); + match json::to_json(&value) { + Ok(actual) => { + mismatches.check(row, "to_json", &expected.to_string(), &actual.to_string()) + } + Err(error) => { + mismatches.check(row, "to_json", &expected.to_string(), &error.to_string()) + } + } + } + mismatches.finish(); +} diff --git a/litellm-rust/crates/python-compat/tests/limits.rs b/litellm-rust/crates/python-compat/tests/limits.rs new file mode 100644 index 00000000000..c4d931034c4 --- /dev/null +++ b/litellm-rust/crates/python-compat/tests/limits.rs @@ -0,0 +1,122 @@ +use std::time::{Duration, Instant}; + +use litellm_python_compat::{Error, MAX_DEPTH, Value, json, literal::literal_eval, pickle}; +use rstest::{fixture, rstest}; + +/// The bracket pair of one container shape, as `(open, close)`. +#[fixture] +fn shapes() -> [(&'static str, &'static str); 3] { + [("[", "]"), ("{'a': ", "}"), ("(", ",)")] +} + +fn nested_text(open: &str, close: &str, depth: usize) -> String { + format!("{}1{}", open.repeat(depth), close.repeat(depth)) +} + +fn nested_list(depth: usize) -> Value { + (0..depth).fold(Value::from(1), |value, _| Value::List(vec![value])) +} + +/// A protocol 3 pickle of `depth` nested lists around `1`: `EMPTY_LIST` per level, then +/// `BININT1 1`, then `APPEND` per level. Written by hand because `dumps` refuses the depth. +fn nested_list_pickle(depth: usize) -> Vec { + let mut data = vec![0x80, 3]; + data.extend(std::iter::repeat_n(b']', depth)); + data.extend([b'K', 1]); + data.extend(std::iter::repeat_n(b'a', depth)); + data.push(b'.'); + data +} + +#[rstest] +fn literal_eval_accepts_the_limit_and_rejects_past_it(shapes: [(&'static str, &'static str); 3]) { + for (open, close) in shapes { + assert!(literal_eval(&nested_text(open, close, MAX_DEPTH)).is_ok()); + assert!(matches!( + literal_eval(&nested_text(open, close, MAX_DEPTH + 1)), + Err(Error::TooDeep) + )); + } +} + +/// A backtracking parser (the `py_literal` grammar this replaced) doubles per nested level +/// and takes minutes here; the bound is loose enough to survive a slow debug build. +#[rstest] +fn literal_eval_stays_linear_in_depth(shapes: [(&'static str, &'static str); 3]) { + for (open, close) in shapes { + let text = nested_text(open, close, MAX_DEPTH); + let start = Instant::now(); + assert!(literal_eval(&text).is_ok()); + let elapsed = start.elapsed(); + assert!( + elapsed < Duration::from_millis(50), + "{open} nested {MAX_DEPTH} deep took {elapsed:?}" + ); + } +} + +#[rstest] +fn literal_eval_ignores_brackets_inside_strings() { + let text = format!("'{}'", "[".repeat(MAX_DEPTH + 1)); + assert!(matches!(literal_eval(&text), Ok(Value::Str(_)))); +} + +#[rstest] +fn pickle_nesting_is_bounded_in_both_directions() { + assert_eq!( + pickle::loads(&nested_list_pickle(MAX_DEPTH)).unwrap(), + nested_list(MAX_DEPTH) + ); + assert!(matches!( + pickle::loads(&nested_list_pickle(MAX_DEPTH + 1)), + Err(Error::InvalidPickle(_)) + )); + assert!(pickle::dumps(&nested_list(MAX_DEPTH)).is_ok()); + assert!(matches!( + pickle::dumps(&nested_list(MAX_DEPTH + 2)), + Err(Error::TooDeep) + )); +} + +#[rstest] +#[case("{1, 2}", "set")] +#[case("1+2j", "complex")] +fn pickle_dumps_refuses_types_it_would_change(#[case] source: &str, #[case] type_name: &str) { + let value = literal_eval(source).expect("source is a literal"); + assert!(matches!(pickle::dumps(&value), Err(Error::NotPicklable(name)) if name == type_name)); +} + +#[rstest] +#[case(b"\x80\x02c__builtin__\ncomplex\nq\x00.".to_vec(), "a class reference")] +#[case({ let mut data = pickle::dumps(&Value::from(1)).unwrap(); data.push(b'.'); data }, "trailing data")] +fn pickle_loads_rejects(#[case] data: Vec, #[case] what: &str) { + assert!( + matches!(pickle::loads(&data), Err(Error::InvalidPickle(_))), + "{what} must not decode" + ); +} + +#[rstest] +#[case(Value::Bytes(b"x".to_vec()), "Object of type bytes is not JSON serializable")] +#[case(Value::Set(vec![Value::from(1)]), "Object of type set is not JSON serializable")] +#[case(Value::Complex { re: 1.0, im: 2.0 }, "Object of type complex is not JSON serializable")] +#[case( + Value::Float(f64::NAN), + "Out of range float values are not JSON compliant" +)] +fn to_json_reports_what_python_json_dumps_would_reject( + #[case] value: Value, + #[case] message: &str, +) { + let error = json::to_json(&value).expect_err("value has no serde_json form"); + assert_eq!(error.to_string(), message); +} + +/// `json.dumps` writes the non-finite floats that `to_json` cannot represent. +#[rstest] +#[case(f64::NAN, "NaN")] +#[case(f64::INFINITY, "Infinity")] +#[case(f64::NEG_INFINITY, "-Infinity")] +fn json_dumps_writes_non_finite_floats(#[case] value: f64, #[case] text: &str) { + assert_eq!(json::dumps(&Value::Float(value)).unwrap(), text); +} From 2ef710e3d5a29351caa20a8d8841ba586fbbdccd Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 12:21:11 -0700 Subject: [PATCH 005/101] fix(langsmith): json.dumps with default=str so non-serializable metadata does not crash batch flush (#42424) * fix(langsmith): json.dumps with default=str so non-serializable metadata does not crash batch flush Serialize the runs/batch payload with json.dumps(default=str, allow_nan=False) and send it as content= with an explicit Content-Type, so datetime, Decimal and similar metadata values no longer raise TypeError and drop the batch. Forward content= on the AsyncHTTPHandler retry path so a retried batch re-sends the identical body Replaces #39133, which was cut from the retired staging branch and conflicts with main Co-authored-by: Damien Smrt Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(langsmith): drop test docstrings and replace monkeypatch with a client-injecting handler Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(langsmith): add live e2e for non-native metadata reaching LangSmith Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(langsmith): scope the e2e docstring to the values the test injects Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(http_handler): close injected retry clients Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(e2e): deselect the LangSmith live e2e on the stage-mirror stack Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: yucheng Co-authored-by: Damien Smrt Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- .github/e2e-stack/select_tests.py | 1 + litellm/integrations/langsmith.py | 5 +- litellm/llms/custom_httpx/http_handler.py | 3 + tests/e2e/coverage_registry/logging.yaml | 1 + .../test_langsmith_batch_serialization_e2e.py | 125 +++++++++++++++++ .../test_langsmith_unit_test.py | 8 +- .../integrations/test_langsmith_init.py | 127 +++++++++++++++++- .../llms/custom_httpx/test_http_handler.py | 44 ++++++ 8 files changed, 304 insertions(+), 10 deletions(-) create mode 100644 tests/e2e/logging/test_langsmith_batch_serialization_e2e.py diff --git a/.github/e2e-stack/select_tests.py b/.github/e2e-stack/select_tests.py index 2386b184e54..492c52233cd 100644 --- a/.github/e2e-stack/select_tests.py +++ b/.github/e2e-stack/select_tests.py @@ -10,6 +10,7 @@ UNSUPPORTED: Final = re.compile( r"|^tests/e2e/batches/test_managed_files_enforcement_e2e\.py$" r"|^tests/e2e/guardrails/test_presidio_masking_e2e\.py$" r"|^tests/e2e/logging/test_otel_v2_langfuse_generation_output_e2e\.py$" + r"|^tests/e2e/logging/test_langsmith_batch_serialization_e2e\.py$" ) HARNESS: Final = re.compile( r"^tests/e2e/[A-Za-z0-9_.-]+\.(py|ini)$" diff --git a/litellm/integrations/langsmith.py b/litellm/integrations/langsmith.py index 352fcdf90f3..991b0411ee8 100644 --- a/litellm/integrations/langsmith.py +++ b/litellm/integrations/langsmith.py @@ -1,6 +1,7 @@ #### What this does #### # On success, logs events to Langsmith import asyncio +import json import os import random import traceback @@ -415,7 +416,7 @@ class LangsmithLogger(CustomBatchLogger): langsmith_api_key: Final = credentials["LANGSMITH_API_KEY"] langsmith_tenant_id: Final = credentials.get("LANGSMITH_TENANT_ID") url: Final = self._add_endpoint_to_url(langsmith_api_base, "runs/batch") - headers: Final = {"x-api-key": langsmith_api_key} + headers: Final = {"x-api-key": langsmith_api_key, "Content-Type": "application/json"} if langsmith_tenant_id: headers["x-tenant-id"] = langsmith_tenant_id elements_to_log: Final = [queue_object["data"] for queue_object in queue_objects] @@ -426,7 +427,7 @@ class LangsmithLogger(CustomBatchLogger): verbose_logger.debug("[LANGSMITH MOCK] Mock mode enabled - API calls will be intercepted") response: Final = await self.async_httpx_client.post( url=url, - json={"post": elements_to_log}, + content=json.dumps({"post": elements_to_log}, default=str, allow_nan=False), headers=headers, ) response.raise_for_status() diff --git a/litellm/llms/custom_httpx/http_handler.py b/litellm/llms/custom_httpx/http_handler.py index fcc05e54bc5..8ea46a6b261 100644 --- a/litellm/llms/custom_httpx/http_handler.py +++ b/litellm/llms/custom_httpx/http_handler.py @@ -845,6 +845,7 @@ class AsyncHTTPHandler: params=params, headers=headers, stream=stream, + content=content, ) finally: await new_client.aclose() @@ -985,6 +986,7 @@ class AsyncHTTPHandler: params=params, headers=headers, stream=stream, + content=content, ) finally: await new_client.aclose() @@ -1051,6 +1053,7 @@ class AsyncHTTPHandler: params=params, headers=headers, stream=stream, + content=content, ) finally: await new_client.aclose() diff --git a/tests/e2e/coverage_registry/logging.yaml b/tests/e2e/coverage_registry/logging.yaml index 1f2f1d64711..7c83e4d3aea 100644 --- a/tests/e2e/coverage_registry/logging.yaml +++ b/tests/e2e/coverage_registry/logging.yaml @@ -13,6 +13,7 @@ - {id: logging.otel.failure.exports_metric, module: logging, tier: P0, event: failure, assertions: [exports_metric], exercised_on: [chat_completions, messages], source: "integrations/otel/logger.py", rationale: "Error spans for observability continuity"} - {id: logging.braintrust.success.logs_spend, module: logging, tier: P1, event: success, assertions: [logs_spend], exercised_on: [chat_completions, messages], source: "integrations/braintrust_logging.py", rationale: "Evals platform spend"} - {id: logging.langsmith.success.logs_spend, module: logging, tier: P1, event: success, assertions: [logs_spend], exercised_on: [chat_completions, messages], source: "integrations/langsmith.py", rationale: "LangChain ecosystem"} +- {id: logging.langsmith.success.serializes_non_native_metadata, module: logging, tier: P1, event: success, assertions: [serializes_non_native_metadata], exercised_on: [sdk], source: "integrations/langsmith.py", rationale: "datetime/Decimal/UUID metadata used to TypeError in json.dumps and drop the whole batch (LIT-8310)"} - {id: logging.arize.success.logs_spend, module: logging, tier: P1, event: success, assertions: [logs_spend], exercised_on: [chat_completions, embeddings], source: "integrations/arize/arize.py", rationale: "ML-ops observability"} - {id: logging.mlflow.success.logs_spend, module: logging, tier: P1, event: success, assertions: [logs_spend], exercised_on: [chat_completions], source: "integrations/mlflow.py", rationale: "Experiment tracking cost/run"} - {id: logging.opik.success.logs_spend, module: logging, tier: P1, event: success, assertions: [logs_spend], exercised_on: [chat_completions], source: "integrations/opik/opik.py", rationale: "Eval platform spend/case"} diff --git a/tests/e2e/logging/test_langsmith_batch_serialization_e2e.py b/tests/e2e/logging/test_langsmith_batch_serialization_e2e.py new file mode 100644 index 00000000000..874b2b6a045 --- /dev/null +++ b/tests/e2e/logging/test_langsmith_batch_serialization_e2e.py @@ -0,0 +1,125 @@ +"""Live e2e: a LangSmith batch whose metadata holds non JSON-native Python values +(datetime, Decimal) must reach the real LangSmith API instead of dying in +json.dumps and dropping the whole batch. Only the SDK path can put such values +into the batch (the proxy JSON-decodes request metadata), so this test drives +litellm.acompletion in-process against the real OpenAI API with a LangsmithLogger +injected per request, flushes the batch, and reads the run back by id through +LangSmith's own API. Nothing is mocked. +""" + +from __future__ import annotations + +import asyncio +import datetime +import decimal +import os +import time +import uuid +from dataclasses import dataclass +from typing import Final + +import pytest +from e2e_config import CHEAP_OPENAI_MODEL, POLL_INTERVAL, POLL_TIMEOUT, unique_marker +from e2e_http import Headers, Success, get_external +from pydantic import BaseModel, ConfigDict, Field, JsonValue + +import litellm +from litellm.integrations.langsmith import LangsmithLogger + +pytestmark = pytest.mark.e2e + + +class LangsmithHeaders(Headers): + x_api_key: str = Field(serialization_alias="x-api-key") + + +class LangsmithRunExtra(BaseModel): + model_config = ConfigDict(extra="allow") + requester_metadata: dict[str, JsonValue] | None = None + + +class LangsmithRun(BaseModel): + id: str + session_name: str | None = None + extra: LangsmithRunExtra + + +@dataclass(frozen=True, slots=True) +class LangsmithCreds: + api_key: str + base_url: str + project: str + + +def load_langsmith_creds() -> LangsmithCreds: + api_key = os.getenv("LANGSMITH_API_KEY") + if not api_key: + pytest.fail("LangSmith e2e requires LANGSMITH_API_KEY; missing credentials is a hard failure, not a skip") + if os.getenv("LANGSMITH_MOCK"): + pytest.fail("LANGSMITH_MOCK is set; this e2e must hit the real LangSmith API") + return LangsmithCreds( + api_key=api_key, + base_url=(os.getenv("LANGSMITH_BASE_URL") or "https://api.smith.langchain.com").rstrip("/"), + project=os.getenv("LANGSMITH_PROJECT") or "litellm-e2e", + ) + + +def _fetch_run(creds: LangsmithCreds, run_id: uuid.UUID) -> LangsmithRun | None: + result = get_external( + f"{creds.base_url}/runs/{run_id}", + response_type=LangsmithRun, + headers=LangsmithHeaders(x_api_key=creds.api_key), + ) + match result: + case Success(data=run): + return run + case _: + return None + + +def _poll_run(creds: LangsmithCreds, run_id: uuid.UUID) -> LangsmithRun: + deadline: Final = time.monotonic() + POLL_TIMEOUT + while time.monotonic() < deadline: + run = _fetch_run(creds, run_id) + if run is not None: + return run + time.sleep(POLL_INTERVAL) + pytest.fail(f"LangSmith run {run_id} never appeared within {POLL_TIMEOUT}s; the batch flush dropped it") + + +class TestLangsmithBatchSerialization: + @pytest.mark.asyncio + @pytest.mark.covers("logging.langsmith.success.serializes_non_native_metadata") + async def test_non_json_native_metadata_reaches_langsmith(self) -> None: + creds: Final = load_langsmith_creds() + logger: Final = LangsmithLogger( + langsmith_api_key=creds.api_key, langsmith_project=creds.project, langsmith_base_url=creds.base_url + ) + assert not logger.is_mock_mode, "LangsmithLogger initialised in mock mode; this e2e needs the real API" + marker: Final = unique_marker() + run_id: Final = uuid.uuid4() + created_at: Final = datetime.datetime(2026, 1, 2, 3, 4, 5, tzinfo=datetime.timezone.utc) + spend: Final = decimal.Decimal("0.0042") + response: Final = await litellm.acompletion( + model=f"openai/{CHEAP_OPENAI_MODEL}", + messages=[{"role": "user", "content": f"Reply with the single word ok ({marker})"}], + max_completion_tokens=5, + callbacks=[logger], + metadata={"run_id": str(run_id), "metadata": {"marker": marker, "created_at": created_at, "spend": spend}}, + ) + assert isinstance(response, litellm.ModelResponse) and response.id, ( + "a non-streaming completion must return a ModelResponse before the batch flush is meaningful" + ) + enqueue_deadline: Final = time.monotonic() + POLL_TIMEOUT + while time.monotonic() < enqueue_deadline and len(logger.log_queue) == 0: + await asyncio.sleep(0.5) + assert len(logger.log_queue) == 1, ( + f"the completion must be queued for the LangSmith batch, got {len(logger.log_queue)} queued entries" + ) + await logger.async_send_batch() + run: Final = _poll_run(creds, run_id) + requester_metadata: Final = run.extra.requester_metadata + assert requester_metadata is not None, "the run must carry the caller metadata under extra.requester_metadata" + assert requester_metadata["marker"] == marker + assert requester_metadata["created_at"] == str(created_at) + assert requester_metadata["spend"] == str(spend) diff --git a/tests/logging_callback_tests/test_langsmith_unit_test.py b/tests/logging_callback_tests/test_langsmith_unit_test.py index 17cd63d8974..341f71f3b4a 100644 --- a/tests/logging_callback_tests/test_langsmith_unit_test.py +++ b/tests/logging_callback_tests/test_langsmith_unit_test.py @@ -356,10 +356,12 @@ async def test_langsmith_key_based_logging(): # tenant_id should not be in headers if not provided assert "x-tenant-id" not in call_args[1]["headers"] + assert call_args[1]["headers"]["Content-Type"] == "application/json" + # Verify the request body contains the expected data - request_body = call_args[1]["json"] + request_body = json.loads(call_args[1]["content"]) assert "post" in request_body - assert len(request_body["post"]) == 1 # Should contain one run + assert len(request_body["post"]) == 1 # EXPECTED BODY expected_body = { @@ -404,7 +406,7 @@ async def test_langsmith_key_based_logging(): } # Print both bodies for debugging - actual_body = call_args[1]["json"] + actual_body = json.loads(call_args[1]["content"]) print("\nExpected body:") print(json.dumps(expected_body, indent=2)) print("\nActual body:") diff --git a/tests/test_litellm/integrations/test_langsmith_init.py b/tests/test_litellm/integrations/test_langsmith_init.py index f56d2310e73..9c0650baee6 100644 --- a/tests/test_litellm/integrations/test_langsmith_init.py +++ b/tests/test_litellm/integrations/test_langsmith_init.py @@ -1,13 +1,17 @@ import asyncio +import json import os +from datetime import datetime, timezone +from decimal import Decimal from typing import Final from unittest.mock import AsyncMock, MagicMock, patch +import httpx import pytest - import litellm from litellm.integrations.langsmith import LangsmithLogger +from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler from litellm.types.integrations.langsmith import LangsmithQueueObject @@ -219,6 +223,121 @@ class TestLangsmithLoggerInit: assert len(logger.log_queue) == 1 +class TestLangsmithBatchSerialization: + async def _logger(self, transport_handler, tenant_id=None): + logger = LangsmithLogger( + langsmith_api_key="test-key", + langsmith_project="test-project", + langsmith_base_url="https://api.smith.langchain.com", + langsmith_tenant_id=tenant_id, + ) + if logger._flush_task is not None: + logger._flush_task.cancel() + handler = AsyncHTTPHandler() + await handler.client.aclose() + handler.client = httpx.AsyncClient( + transport=httpx.MockTransport(transport_handler) + ) + logger.async_httpx_client = handler + return logger + + @staticmethod + def _capturing_transport(captured): + async def handle(request: httpx.Request) -> httpx.Response: + captured.append(request) + return httpx.Response(200, request=request, json={"ok": True}) + + return handle + + def _queue(self, logger, extra): + return [ + LangsmithQueueObject( + data={"id": "run-1", "name": "LLMRun", "extra": extra}, + credentials=logger.default_credentials, + ) + ] + + @pytest.mark.asyncio + async def test_datetime_and_decimal_metadata_reach_langsmith_as_strings(self): + captured: list[httpx.Request] = [] # mutable-ok: transport capture buffer + logger = await self._logger(self._capturing_transport(captured)) + logger.log_queue = self._queue( + logger, + { + "created_at": datetime(2026, 1, 2, 3, 4, 5, tzinfo=timezone.utc), + "spend": Decimal("0.0042"), + }, + ) + + await logger.async_send_batch() + + assert len(captured) == 1, "batch was dropped instead of being sent" + body = json.loads(captured[0].content) + assert body["post"][0]["extra"] == { + "created_at": "2026-01-02 03:04:05+00:00", + "spend": "0.0042", + } + await logger.async_httpx_client.client.aclose() + + @pytest.mark.asyncio + async def test_nan_metadata_is_dropped_instead_of_shipping_invalid_json(self): + captured: list[httpx.Request] = [] # mutable-ok: transport capture buffer + logger = await self._logger(self._capturing_transport(captured)) + logger.log_queue = self._queue(logger, {"score": float("nan")}) + + await logger.async_send_batch() + + assert captured == [], ( + "nan metadata must abort the batch: a bare NaN token is invalid JSON and LangSmith rejects it" + ) + await logger.async_httpx_client.client.aclose() + + @pytest.mark.asyncio + async def test_batch_declares_json_content_type(self): + captured: list[httpx.Request] = [] # mutable-ok: transport capture buffer + logger = await self._logger(self._capturing_transport(captured)) + logger.log_queue = self._queue(logger, {"model": "gpt-4.1-mini"}) + + await logger.async_send_batch() + + assert captured[0].headers["content-type"] == "application/json", ( + "a content= body carries no implicit content type; LangSmith refuses it without this header" + ) + assert captured[0].url.path.endswith("/api/v1/runs/batch") + assert captured[0].headers["x-api-key"] == "test-key" + assert "x-tenant-id" not in captured[0].headers + await logger.async_httpx_client.client.aclose() + + @pytest.mark.asyncio + async def test_tenant_id_is_forwarded_on_the_batch_request(self): + captured: list[httpx.Request] = [] # mutable-ok: transport capture buffer + logger = await self._logger( + self._capturing_transport(captured), tenant_id="tenant-1" + ) + logger.log_queue = self._queue(logger, {"model": "gpt-4.1-mini"}) + + await logger.async_send_batch() + + assert captured[0].headers["x-tenant-id"] == "tenant-1" + await logger.async_httpx_client.client.aclose() + + @pytest.mark.asyncio + async def test_langsmith_error_response_does_not_propagate(self): + captured: list[httpx.Request] = [] # mutable-ok: transport capture buffer + + async def reject(request: httpx.Request) -> httpx.Response: + captured.append(request) + return httpx.Response(422, request=request, text="bad run") + + logger = await self._logger(reject) + logger.log_queue = self._queue(logger, {"model": "gpt-4.1-mini"}) + + await logger.async_send_batch() + + assert len(captured) == 1, "the batch never left the process" + await logger.async_httpx_client.client.aclose() + + class TestLangsmithPrepareLogData: """Regression test for #24001: _prepare_log_data must inject usage_metadata into outputs so LangSmith's Cost column is populated.""" @@ -544,12 +663,10 @@ async def test_events_appended_during_flush_are_not_dropped(): credentials=logger.default_credentials, data={"id": "late"} ) - async def fake_post( - url: str, json: dict[str, list[dict[str, str]]], headers: dict[str, str] - ) -> MagicMock: + async def fake_post(url: str, content: str, headers: dict[str, str]) -> MagicMock: if not sent_batches: logger.log_queue.append(late_event) - sent_batches.append(json["post"]) + sent_batches.append(json.loads(content)["post"]) response = MagicMock() response.status_code = 200 response.raise_for_status = MagicMock() diff --git a/tests/test_litellm/llms/custom_httpx/test_http_handler.py b/tests/test_litellm/llms/custom_httpx/test_http_handler.py index 33272a1a9e4..8358d15d30e 100644 --- a/tests/test_litellm/llms/custom_httpx/test_http_handler.py +++ b/tests/test_litellm/llms/custom_httpx/test_http_handler.py @@ -6,6 +6,8 @@ import pathlib import ssl import threading import weakref +from collections.abc import Callable, Mapping +from typing import Final from unittest.mock import MagicMock, patch import certifi @@ -23,6 +25,7 @@ from litellm.llms.custom_httpx.http_handler import ( _get_httpx_client, get_ssl_configuration, ) +from litellm.types.llms.custom_http import VerifyTypes @pytest.mark.asyncio @@ -1396,6 +1399,47 @@ async def test_finalizer_on_live_loop_disposes_foreign_loop_session_without_sche assert session.closed +class _RetryClientHandler(AsyncHTTPHandler): + def __init__(self, first: httpx.AsyncClient, retry: httpx.AsyncClient) -> None: + self._retry_client: Final = retry + super().__init__() + self.client = first + + def create_client( + self, + timeout: float | httpx.Timeout | None = None, + event_hooks: Mapping[str, list[Callable[..., object]]] | None = None, + ssl_verify: VerifyTypes | None = None, + shared_session: ClientSession | None = None, + ) -> httpx.AsyncClient: + return self._retry_client + + +@pytest.mark.asyncio +@pytest.mark.parametrize("method", ["post", "put", "patch", "delete"]) +async def test_connection_error_retry_forwards_content(method: str): + captured: list[bytes] = [] # mutable-ok: async closure capture buffer + + async def raise_connection_error(request: httpx.Request) -> httpx.Response: + raise httpx.RemoteProtocolError("connection dropped", request=request) + + async def capture_and_succeed(request: httpx.Request) -> httpx.Response: + captured.append(request.content) + return httpx.Response(200, request=request) + + first: Final = httpx.AsyncClient(transport=httpx.MockTransport(raise_connection_error)) + retry: Final = httpx.AsyncClient(transport=httpx.MockTransport(capture_and_succeed)) + async with first, retry: + handler: Final = _RetryClientHandler(first=first, retry=retry) + + body = b'{"post": ["run1"]}' + await getattr(handler, method)("https://api.example.com/runs/batch", content=body) + + assert captured == [body], "the retried request must carry the same content= body" + await handler.close() + + + @pytest.fixture def forward_proxy_server(): """Plain HTTP forward proxy that records the absolute URIs it is asked to fetch.""" From 569ccaece9328646535e5ab6ac163e530665c771 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 12:21:20 -0700 Subject: [PATCH 006/101] fix(proxy): make the lazy OpenAPI snapshot byte-identical on every Python version (#42519) Python 3.13+ strips the common indentation of docstrings at compile time and 3.12 keeps it, and the 429 error description in ERROR_RESPONSES came straight from RateLimitError.__doc__, so regenerating litellm/proxy/_lazy_openapi_snapshot.json on a 3.13+ venv produced a one-line diff that the check-ui-api-types job (Python 3.12) rejected. Run the docstring through inspect.cleandoc before it lands in the spec, regenerate the snapshot once, and pin the behavior with a test Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- litellm/proxy/_lazy_openapi_snapshot.json | 2 +- litellm/proxy/common_utils/swagger_utils.py | 7 ++++++- .../proxy/common_utils/test_swagger_utils.py | 18 ++++++++++++++++++ 3 files changed, 25 insertions(+), 2 deletions(-) create mode 100644 tests/test_litellm/proxy/common_utils/test_swagger_utils.py diff --git a/litellm/proxy/_lazy_openapi_snapshot.json b/litellm/proxy/_lazy_openapi_snapshot.json index 4dbca14b917..87f28624d58 100644 --- a/litellm/proxy/_lazy_openapi_snapshot.json +++ b/litellm/proxy/_lazy_openapi_snapshot.json @@ -19919,7 +19919,7 @@ } } }, - "description": "\n Unified rate-limit error.\n\n Every rate-limit condition surfaced by litellm \u2014 whether it originated from\n an upstream LLM provider, a vendor batch endpoint, or one of litellm's own\n proxy-side limiters (parallel-requests, dynamic-rate, batch-rate, budget,\n max-iterations, etc.) \u2014 is raised as an instance of this class.\n\n The :attr:`category` attribute lets callers distinguish the source. See\n :class:`RateLimitErrorCategory` for the available values.\n " + "description": "Unified rate-limit error.\n\nEvery rate-limit condition surfaced by litellm \u2014 whether it originated from\nan upstream LLM provider, a vendor batch endpoint, or one of litellm's own\nproxy-side limiters (parallel-requests, dynamic-rate, batch-rate, budget,\nmax-iterations, etc.) \u2014 is raised as an instance of this class.\n\nThe :attr:`category` attribute lets callers distinguish the source. See\n:class:`RateLimitErrorCategory` for the available values." }, "500": { "content": { diff --git a/litellm/proxy/common_utils/swagger_utils.py b/litellm/proxy/common_utils/swagger_utils.py index 2609a98a997..83480bf161d 100644 --- a/litellm/proxy/common_utils/swagger_utils.py +++ b/litellm/proxy/common_utils/swagger_utils.py @@ -1,3 +1,4 @@ +import inspect from typing import Any, Final from pydantic import BaseModel, Field @@ -31,11 +32,15 @@ def get_status_code(exception): return 500 # Internal Server Error as default +def _error_description(exception: type[Exception]) -> str: + return inspect.cleandoc(exception.__doc__) if exception.__doc__ else exception.__name__ + + # Create error responses ERROR_RESPONSES: Final = { get_status_code(exception): { "model": ErrorResponse, - "description": exception.__doc__ or exception.__name__, + "description": _error_description(exception), } for exception in LITELLM_EXCEPTION_TYPES } diff --git a/tests/test_litellm/proxy/common_utils/test_swagger_utils.py b/tests/test_litellm/proxy/common_utils/test_swagger_utils.py new file mode 100644 index 00000000000..659d2ad2941 --- /dev/null +++ b/tests/test_litellm/proxy/common_utils/test_swagger_utils.py @@ -0,0 +1,18 @@ +import inspect + +from litellm.exceptions import RateLimitError +from litellm.proxy.common_utils.swagger_utils import ERROR_RESPONSES, _error_description + + +class _ChildWithoutDoc(RateLimitError): + pass + + +def test_error_response_descriptions_carry_no_docstring_indentation(): + assert ERROR_RESPONSES[429]["description"] == inspect.cleandoc(RateLimitError.__doc__ or "") + for response in ERROR_RESPONSES.values(): + assert response["description"] == inspect.cleandoc(response["description"]) + + +def test_error_description_falls_back_to_the_class_name_without_an_own_docstring(): + assert _error_description(_ChildWithoutDoc) == "_ChildWithoutDoc" From 97a6c27bee7d9c3f12f122b9769d85f01ebda159 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 19:21:32 +0000 Subject: [PATCH 007/101] test(rust_bridge): drop route dispatch assertions, test the bridge directly (#42536) Co-authored-by: ryan Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- .../spend_tracking/test_budget_reservation.py | 251 +----------------- .../proxy/spend_tracking/test_input_tokens.py | 164 +----------- .../rust_bridge/test_token_counter.py | 173 +++--------- .../rust_bridge/test_tokenizer.py | 157 +++-------- 4 files changed, 68 insertions(+), 677 deletions(-) diff --git a/tests/test_litellm/proxy/spend_tracking/test_budget_reservation.py b/tests/test_litellm/proxy/spend_tracking/test_budget_reservation.py index 13488106df4..9df8e6f4d67 100644 --- a/tests/test_litellm/proxy/spend_tracking/test_budget_reservation.py +++ b/tests/test_litellm/proxy/spend_tracking/test_budget_reservation.py @@ -1,10 +1,8 @@ from __future__ import annotations -import json import math from datetime import datetime, timedelta, timezone -from types import MappingProxyType -from typing import Final, cast +from typing import Final import pytest @@ -24,16 +22,12 @@ from litellm.proxy.common_utils.user_api_key_cache import ( ) from litellm.proxy.spend_tracking.budget_reservation import ( _get_team_member_budget_counter, - count_request_input_tokens, estimate_request_max_cost, release_unbound_budget_reservation, reserve_budget_for_request, ) from litellm.proxy.utils import ProxyLogging from litellm.router import Router -from litellm.rust_bridge import bindings, configuration -from litellm.rust_bridge import token_counter as rust_token_counter -from litellm.rust_bridge import tokenizer as tokenizer_dispatch from litellm.types.router import Deployment, LiteLLM_Params, ModelInfo TOKEN_COUNTING_ROUTES: Final = ( @@ -222,249 +216,6 @@ def test_deployment_pricing_update_invalidates_cached_estimate() -> None: assert math.isclose(after, before * 1000) -ANTHROPIC_TOKENIZER_MODEL: Final = "claude-sonnet-4-5-20250929" -CL100K_MODEL: Final = "gpt-4" -O200K_MODEL: Final = "gpt-4o" -RUST_COUNTED_BODY: Final = {"model": ANTHROPIC_TOKENIZER_MODEL, "max_tokens": 16, "messages": ANTHROPIC_MESSAGES} -RUST_INPUT_TOKENS: Final = 4_321 -RUST_INPUT_TOKENS_BY_TOKENIZER: Final = MappingProxyType( - {"anthropic": RUST_INPUT_TOKENS, "cl100k_base": 1_234, "o200k_base": 2_345} -) - - -class _FakeDeclined(Exception): - pass - - -class _FakeUpstream(Exception): - pass - - -class _FakeTokenizer: - """Stands in for one shared native `Tokenizer`; only its name identifies it.""" - - def __init__(self, name: str, json: str | None = None) -> None: - self.name = name - self.json = json - - -def _fake_native_tokenizers(monkeypatch: pytest.MonkeyPatch, anthropic_json: str | None = None) -> None: - """Point the counter's tokenizer lookups at fakes; the codec path keeps falling back to Python.""" - fakes: Final = {name: _FakeTokenizer(name) for name in ("cl100k_base", "o200k_base")} - anthropic: Final = _FakeTokenizer("anthropic", anthropic_json) - monkeypatch.setattr(tokenizer_dispatch, "native_encoding", fakes.__getitem__) - monkeypatch.setattr(tokenizer_dispatch, "native_anthropic", lambda: anthropic) - - -class _FakeNative: - RustBridgeDeclined = _FakeDeclined - RustUpstreamError = _FakeUpstream - - -class _RecordingCounter: - """Stands in for one native counter; records `(tokenizer, body)` on the shared factory.""" - - def __init__(self, factory: _RecordingFactory, tokenizer: rust_token_counter.RustTokenizer) -> None: - self.factory = factory - self.tokenizer = tokenizer - - async def acount_request(self, body: bytes) -> object: - self.factory.calls.append((self.tokenizer, body)) - return {"model": "", "input_tokens": RUST_INPUT_TOKENS_BY_TOKENIZER[self.tokenizer]} - - -class _RecordingFactory: - """Stands in for the native `TokenCounter` class, built over a loaded `Tokenizer`.""" - - def __init__(self) -> None: - self.calls: list[tuple[rust_token_counter.RustTokenizer, bytes]] = [] - - def from_tokenizer(self, tokenizer: _FakeTokenizer, fast: bool = False) -> _RecordingCounter: - return _RecordingCounter(self, cast(rust_token_counter.RustTokenizer, tokenizer.name)) - - -class _DecliningCounter: - async def acount_request(self, body: bytes) -> object: - raise _FakeDeclined("unsupported content block") - - -class _DecliningFactory: - def from_tokenizer(self, tokenizer: _FakeTokenizer, fast: bool = False) -> _DecliningCounter: - return _DecliningCounter() - - -@pytest.fixture -def rust_counter(monkeypatch: pytest.MonkeyPatch): - monkeypatch.setattr(bindings, "get_native_bridge", lambda: _FakeNative()) - _fake_native_tokenizers(monkeypatch) - rust_token_counter._counter.cache_clear() - configuration.reset_rust_configuration() - yield - rust_token_counter.TOKEN_COUNTER.reset() - rust_token_counter._counter.cache_clear() - configuration.reset_rust_configuration() - - -@pytest.mark.asyncio -@pytest.mark.parametrize( - ("route", "request_body"), - ( - ("/v1/messages", RUST_COUNTED_BODY), - ("/v1/chat/completions", {"model": ANTHROPIC_TOKENIZER_MODEL, "messages": ANTHROPIC_MESSAGES}), - ("/v1/completions", {"model": ANTHROPIC_TOKENIZER_MODEL, "prompt": "hi"}), - ("/v1/responses", {"model": ANTHROPIC_TOKENIZER_MODEL, "input": "hi"}), - ("/v1/embeddings", {"model": ANTHROPIC_TOKENIZER_MODEL, "input": ["hi"]}), - ("/v1/rerank", {"model": ANTHROPIC_TOKENIZER_MODEL, "query": "hi", "documents": ["a"]}), - ), -) -async def test_rust_count_replaces_python_tokenizing_on_every_llm_route( - rust_counter: None, route: str, request_body: dict -) -> None: - factory: Final = _RecordingFactory() - litellm.rust(True) - rust_token_counter.TOKEN_COUNTER.override(factory) - raw_body: Final = json.dumps(request_body).encode() - - counts: Final = await count_request_input_tokens( - request_body=request_body, route=route, llm_router=None, raw_body=raw_body - ) - - assert dict(counts) == {ANTHROPIC_TOKENIZER_MODEL: RUST_INPUT_TOKENS} - assert factory.calls == [("anthropic", raw_body)] - - -@pytest.mark.asyncio -@pytest.mark.parametrize("model", (CL100K_MODEL, "azure/gpt-35-turbo", "gemini/gemini-2.5-pro", "my-router-alias")) -async def test_tiktoken_cl100k_models_are_counted_by_rust(rust_counter: None, model: str) -> None: - factory: Final = _RecordingFactory() - litellm.rust(True) - rust_token_counter.TOKEN_COUNTER.override(factory) - body: Final = {"model": model, "messages": ANTHROPIC_MESSAGES} - raw_body: Final = json.dumps(body).encode() - - counts: Final = await count_request_input_tokens( - request_body=body, route="/v1/chat/completions", llm_router=None, raw_body=raw_body - ) - - assert dict(counts) == {model: RUST_INPUT_TOKENS_BY_TOKENIZER["cl100k_base"]} - assert factory.calls == [("cl100k_base", raw_body)] - - -@pytest.mark.asyncio -@pytest.mark.parametrize("model", (O200K_MODEL, "gpt-5", "o3", "gpt-4.1", "chatgpt-4o-latest")) -async def test_tiktoken_o200k_models_are_counted_by_rust(rust_counter: None, model: str) -> None: - factory: Final = _RecordingFactory() - litellm.rust(True) - rust_token_counter.TOKEN_COUNTER.override(factory) - body: Final = {"model": model, "messages": ANTHROPIC_MESSAGES} - raw_body: Final = json.dumps(body).encode() - - counts: Final = await count_request_input_tokens( - request_body=body, route="/v1/chat/completions", llm_router=None, raw_body=raw_body - ) - - assert dict(counts) == {model: RUST_INPUT_TOKENS_BY_TOKENIZER["o200k_base"]} - assert factory.calls == [("o200k_base", raw_body)] - - -@pytest.mark.asyncio -async def test_multi_model_request_counts_once_per_tokenizer_and_python_for_the_rest(rust_counter: None) -> None: - factory: Final = _RecordingFactory() - litellm.rust(True) - rust_token_counter.TOKEN_COUNTER.override(factory) - models: Final = ( - CL100K_MODEL, - ANTHROPIC_TOKENIZER_MODEL, - "gemini/gemini-2.5-pro", - O200K_MODEL, - "gpt-5", - "replicate/meta/llama-2-70b-chat", - ) - body: Final = {"model": list(models), "messages": ANTHROPIC_MESSAGES} - raw_body: Final = json.dumps(body).encode() - python_counts: Final = await count_request_input_tokens( - request_body=body, route="/v1/chat/completions", llm_router=None - ) - - counts: Final = await count_request_input_tokens( - request_body=body, route="/v1/chat/completions", llm_router=None, raw_body=raw_body - ) - - assert factory.calls == [("cl100k_base", raw_body), ("anthropic", raw_body), ("o200k_base", raw_body)] - assert dict(counts) == { - CL100K_MODEL: RUST_INPUT_TOKENS_BY_TOKENIZER["cl100k_base"], - "gemini/gemini-2.5-pro": RUST_INPUT_TOKENS_BY_TOKENIZER["cl100k_base"], - ANTHROPIC_TOKENIZER_MODEL: RUST_INPUT_TOKENS, - O200K_MODEL: RUST_INPUT_TOKENS_BY_TOKENIZER["o200k_base"], - "gpt-5": RUST_INPUT_TOKENS_BY_TOKENIZER["o200k_base"], - "replicate/meta/llama-2-70b-chat": python_counts["replicate/meta/llama-2-70b-chat"], - } - assert counts["replicate/meta/llama-2-70b-chat"] not in RUST_INPUT_TOKENS_BY_TOKENIZER.values() - - -@pytest.mark.asyncio -@pytest.mark.parametrize("model", (ANTHROPIC_TOKENIZER_MODEL, CL100K_MODEL, O200K_MODEL)) -async def test_rust_decline_falls_back_to_python_count(rust_counter: None, model: str) -> None: - litellm.rust(True) - rust_token_counter.TOKEN_COUNTER.override(_DecliningFactory()) - body: Final = {**RUST_COUNTED_BODY, "model": model} - python_counts: Final = await count_request_input_tokens(request_body=body, route="/v1/messages", llm_router=None) - - counts: Final = await count_request_input_tokens( - request_body=body, - route="/v1/messages", - llm_router=None, - raw_body=json.dumps(body).encode(), - ) - - assert dict(counts) == dict(python_counts) - assert counts[model] not in RUST_INPUT_TOKENS_BY_TOKENIZER.values() - - -@pytest.mark.asyncio -async def test_disabled_rust_never_sees_the_raw_body(rust_counter: None) -> None: - factory: Final = _RecordingFactory() - litellm.rust(False) - rust_token_counter.TOKEN_COUNTER.override(factory) - body: Final = {"model": [ANTHROPIC_TOKENIZER_MODEL, CL100K_MODEL, O200K_MODEL], "messages": ANTHROPIC_MESSAGES} - - counts: Final = await count_request_input_tokens( - request_body=body, - route="/v1/chat/completions", - llm_router=None, - raw_body=json.dumps(body).encode(), - ) - - assert factory.calls == [] - assert set(counts) == {ANTHROPIC_TOKENIZER_MODEL, CL100K_MODEL, O200K_MODEL} - assert not set(counts.values()) & set(RUST_INPUT_TOKENS_BY_TOKENIZER.values()) - - -@pytest.mark.asyncio -@pytest.mark.parametrize("model", ("replicate/meta/llama-2-70b-chat", "meta-llama/Llama-3-8b", "text-davinci-003")) -async def test_models_without_a_rust_tokenizer_stay_in_python( - rust_counter: None, monkeypatch: pytest.MonkeyPatch, model: str -) -> None: - monkeypatch.setattr( - litellm, "open_ai_chat_completion_models", litellm.open_ai_chat_completion_models | {"text-davinci-003"} - ) - factory: Final = _RecordingFactory() - litellm.rust(True) - rust_token_counter.TOKEN_COUNTER.override(factory) - body: Final = {"model": model, "messages": ANTHROPIC_MESSAGES} - python_counts: Final = await count_request_input_tokens( - request_body=body, route="/v1/chat/completions", llm_router=None - ) - - counts: Final = await count_request_input_tokens( - request_body=body, route="/v1/chat/completions", llm_router=None, raw_body=json.dumps(body).encode() - ) - - assert factory.calls == [] - assert dict(counts) == dict(python_counts) - assert counts[model] not in RUST_INPUT_TOKENS_BY_TOKENIZER.values() - - @pytest.mark.asyncio @pytest.mark.parametrize( "expiry_offset, expected_max_budget", diff --git a/tests/test_litellm/proxy/spend_tracking/test_input_tokens.py b/tests/test_litellm/proxy/spend_tracking/test_input_tokens.py index 49bbe148386..a1da6c79cd7 100644 --- a/tests/test_litellm/proxy/spend_tracking/test_input_tokens.py +++ b/tests/test_litellm/proxy/spend_tracking/test_input_tokens.py @@ -2,180 +2,18 @@ from __future__ import annotations -import json from types import MappingProxyType -from typing import Final, cast +from typing import Final import pytest -import litellm from litellm.proxy.spend_tracking.input_tokens import ( TOKENIZE_OFF_EVENT_LOOP_MIN_CHARS, count_input_tokens, count_input_tokens_for_model, ) -from litellm.rust_bridge import bindings, configuration, token_counter -from litellm.rust_bridge import tokenizer as tokenizer_dispatch -from litellm.rust_bridge.token_counter import RustTokenizer -ANTHROPIC_MODEL: Final = "claude-sonnet-4-5-20250929" CL100K_MODEL: Final = "gpt-4" -O200K_MODEL: Final = "gpt-4o" -PYTHON_ONLY_MODEL: Final = "replicate/meta/llama-2-70b-chat" -MESSAGES: Final = [{"role": "user", "content": "hello"}] -RUST_TOKENS: Final = 777 - - -class _FakeDeclined(Exception): - pass - - -class _FakeUpstream(Exception): - pass - - -class _FakeTokenizer: - """Stands in for one shared native `Tokenizer`; only its name identifies it.""" - - def __init__(self, name: str, json: str | None = None) -> None: - self.name = name - self.json = json - - -def _fake_native_tokenizers(monkeypatch: pytest.MonkeyPatch, anthropic_json: str | None = None) -> None: - """Point the counter's tokenizer lookups at fakes; the codec path keeps falling back to Python.""" - fakes: Final = {name: _FakeTokenizer(name) for name in ("cl100k_base", "o200k_base")} - anthropic: Final = _FakeTokenizer("anthropic", anthropic_json) - monkeypatch.setattr(tokenizer_dispatch, "native_encoding", fakes.__getitem__) - monkeypatch.setattr(tokenizer_dispatch, "native_anthropic", lambda: anthropic) - - -class _FakeNative: - RustBridgeDeclined = _FakeDeclined - RustUpstreamError = _FakeUpstream - - -class _RecordingCounter: - def __init__(self, factory: _RecordingFactory, tokenizer: RustTokenizer) -> None: - self.factory = factory - self.tokenizer = tokenizer - - async def acount_request(self, body: bytes) -> object: - self.factory.calls.append((self.tokenizer, body)) - return {"model": "", "input_tokens": RUST_TOKENS} - - -class _RecordingFactory: - def __init__(self) -> None: - self.calls: list[tuple[RustTokenizer, bytes]] = [] - - def from_tokenizer(self, tokenizer: _FakeTokenizer, fast: bool = False) -> _RecordingCounter: - return _RecordingCounter(self, cast(RustTokenizer, tokenizer.name)) - - -class _DecliningCounter: - async def acount_request(self, body: bytes) -> object: - raise _FakeDeclined("unsupported request shape") - - -class _DecliningFactory: - def from_tokenizer(self, tokenizer: _FakeTokenizer, fast: bool = False) -> _DecliningCounter: - return _DecliningCounter() - - -@pytest.fixture(autouse=True) -def _reset_bridge(monkeypatch: pytest.MonkeyPatch): - monkeypatch.setattr(bindings, "get_native_bridge", lambda: _FakeNative()) - _fake_native_tokenizers(monkeypatch) - token_counter.TOKEN_COUNTER.reset() - token_counter._counter.cache_clear() - configuration.reset_rust_configuration() - yield - token_counter.TOKEN_COUNTER.reset() - token_counter._counter.cache_clear() - configuration.reset_rust_configuration() - - -def _body(model: object) -> tuple[dict[str, object], bytes]: - body: Final = {"model": model, "messages": MESSAGES} - return body, json.dumps(body).encode() - - -@pytest.mark.asyncio -async def test_models_sharing_a_tokenizer_are_counted_once_and_merged() -> None: - factory: Final = _RecordingFactory() - litellm.rust(True) - token_counter.TOKEN_COUNTER.override(factory) - request_body, raw_body = _body([ANTHROPIC_MODEL, CL100K_MODEL, O200K_MODEL, "gpt-5", PYTHON_ONLY_MODEL]) - - counts: Final = await count_input_tokens( - request_body=request_body, - raw_body=raw_body, - models=(ANTHROPIC_MODEL, CL100K_MODEL, O200K_MODEL, "gpt-5", PYTHON_ONLY_MODEL), - ) - - assert factory.calls == [("anthropic", raw_body), ("cl100k_base", raw_body), ("o200k_base", raw_body)] - assert dict(counts) == { - ANTHROPIC_MODEL: RUST_TOKENS, - CL100K_MODEL: RUST_TOKENS, - O200K_MODEL: RUST_TOKENS, - "gpt-5": RUST_TOKENS, - PYTHON_ONLY_MODEL: count_input_tokens_for_model(request_body=request_body, model=PYTHON_ONLY_MODEL), - } - - -@pytest.mark.asyncio -async def test_rust_disabled_counts_everything_in_python() -> None: - factory: Final = _RecordingFactory() - litellm.rust(False) - token_counter.TOKEN_COUNTER.override(factory) - request_body, raw_body = _body([ANTHROPIC_MODEL, CL100K_MODEL]) - - counts: Final = await count_input_tokens( - request_body=request_body, raw_body=raw_body, models=(ANTHROPIC_MODEL, CL100K_MODEL) - ) - - assert factory.calls == [] - assert dict(counts) == { - model: count_input_tokens_for_model(request_body=request_body, model=model) - for model in (ANTHROPIC_MODEL, CL100K_MODEL) - } - - -@pytest.mark.asyncio -async def test_missing_raw_body_counts_in_python() -> None: - factory: Final = _RecordingFactory() - litellm.rust(True) - token_counter.TOKEN_COUNTER.override(factory) - request_body, _ = _body(ANTHROPIC_MODEL) - - counts: Final = await count_input_tokens(request_body=request_body, raw_body=None, models=(ANTHROPIC_MODEL,)) - - assert factory.calls == [] - assert counts[ANTHROPIC_MODEL] == count_input_tokens_for_model(request_body=request_body, model=ANTHROPIC_MODEL) - - -@pytest.mark.asyncio -async def test_missing_binding_counts_in_python() -> None: - litellm.rust(True) - token_counter.TOKEN_COUNTER.override(None) - request_body, raw_body = _body(ANTHROPIC_MODEL) - - counts: Final = await count_input_tokens(request_body=request_body, raw_body=raw_body, models=(ANTHROPIC_MODEL,)) - - assert counts[ANTHROPIC_MODEL] == count_input_tokens_for_model(request_body=request_body, model=ANTHROPIC_MODEL) - - -@pytest.mark.asyncio -async def test_declined_request_counts_in_python() -> None: - litellm.rust(True) - token_counter.TOKEN_COUNTER.override(_DecliningFactory()) - request_body, raw_body = _body(ANTHROPIC_MODEL) - - counts: Final = await count_input_tokens(request_body=request_body, raw_body=raw_body, models=(ANTHROPIC_MODEL,)) - - assert counts[ANTHROPIC_MODEL] == count_input_tokens_for_model(request_body=request_body, model=ANTHROPIC_MODEL) - assert counts[ANTHROPIC_MODEL] != RUST_TOKENS @pytest.mark.asyncio diff --git a/tests/test_litellm/rust_bridge/test_token_counter.py b/tests/test_litellm/rust_bridge/test_token_counter.py index 3da291c898d..101fda629a7 100644 --- a/tests/test_litellm/rust_bridge/test_token_counter.py +++ b/tests/test_litellm/rust_bridge/test_token_counter.py @@ -1,8 +1,7 @@ -"""Tests for the Rust input token counter bridge. +"""Tests for the Rust input token counter bridge, called directly rather than through the route catalog. -The native factory is dependency-injected through ``TOKEN_COUNTER.override`` -so the fallback cases run without the compiled extension present. The parity -cases need the extension and are skipped when it is not built. +The factory is passed into ``native_count`` so the caching cases run without the compiled extension +present. The parity cases need the extension and are skipped when it is not built. """ from __future__ import annotations @@ -16,8 +15,7 @@ import pytest import litellm from litellm.constants import TIKTOKEN_ENCODE_CHUNK_SIZE_CHARS from litellm.litellm_core_utils.token_counter import openai_tokenizer_encoding -from litellm.proxy.spend_tracking.input_tokens import count_input_tokens, count_input_tokens_for_model -from litellm.rust_bridge import bindings, configuration +from litellm.proxy.spend_tracking.input_tokens import count_input_tokens_for_model from litellm.rust_bridge import token_counter as bridge from litellm.rust_bridge import tokenizer as tokenizer_dispatch from litellm.rust_bridge._native import Tokenizer @@ -38,14 +36,6 @@ def _counted(body: dict[str, object], model: str) -> tuple[bytes, dict[str, obje return raw, json.loads(raw) -class _FakeDeclined(Exception): - pass - - -class _FakeUpstream(Exception): - pass - - class _FakeTokenizer: """Stands in for one shared native `Tokenizer`; only its name identifies it.""" @@ -54,29 +44,6 @@ class _FakeTokenizer: self.json = json -def _fake_native_tokenizers(monkeypatch: pytest.MonkeyPatch, anthropic_json: str | None = None) -> None: - """Point the counter's tokenizer lookups at fakes while the bridge is faked; the codec path - keeps falling back to Python. Parity tests that restore the real extension get the real - lookups back.""" - fakes: Final = {name: _FakeTokenizer(name) for name in ("cl100k_base", "o200k_base")} - anthropic: Final = _FakeTokenizer("anthropic", anthropic_json) - real_encoding: Final = tokenizer_dispatch.native_encoding - real_anthropic: Final = tokenizer_dispatch.native_anthropic - - def faked() -> bool: - return isinstance(bindings.get_native_bridge(), _FakeNative) - - monkeypatch.setattr( - tokenizer_dispatch, "native_encoding", lambda name: fakes[name] if faked() else real_encoding(name) - ) - monkeypatch.setattr(tokenizer_dispatch, "native_anthropic", lambda: anthropic if faked() else real_anthropic()) - - -class _FakeNative: - RustBridgeDeclined = _FakeDeclined - RustUpstreamError = _FakeUpstream - - class _RecordingCounter: def __init__(self, tokenizer: _FakeTokenizer, fast: bool) -> None: self.tokenizer = tokenizer @@ -100,57 +67,25 @@ class _RecordingFactory: return counter -class _RaisingCounter: - def __init__(self, error: Exception) -> None: - self.error = error - - async def acount_request(self, body: bytes) -> object: - raise self.error - - -class _RaisingFactory: - """Every counter it builds, for either tokenizer, raises `error` on count.""" - - def __init__(self, error: Exception) -> None: - self.error = error - - def from_tokenizer(self, tokenizer: _FakeTokenizer, fast: bool = False) -> _RaisingCounter: - return _RaisingCounter(self.error) - - @pytest.fixture(autouse=True) -def _reset_bridge(monkeypatch: pytest.MonkeyPatch): - bridge.TOKEN_COUNTER.reset() +def _reset_counters(): bridge._counter.cache_clear() - configuration.reset_rust_configuration() - monkeypatch.setattr(bindings, "get_native_bridge", lambda: _FakeNative()) - _fake_native_tokenizers(monkeypatch, anthropic_json=claude_json_str) yield - bridge.TOKEN_COUNTER.reset() bridge._counter.cache_clear() - configuration.reset_rust_configuration() + + +@pytest.fixture +def fake_tokenizers(monkeypatch: pytest.MonkeyPatch) -> None: + """Point the counter's tokenizer lookups at fakes so a recording factory sees which one it was built over.""" + fakes: Final = {name: _FakeTokenizer(name) for name in ("cl100k_base", "o200k_base")} + anthropic: Final = _FakeTokenizer("anthropic", claude_json_str) + monkeypatch.setattr(tokenizer_dispatch, "native_encoding", fakes.__getitem__) + monkeypatch.setattr(tokenizer_dispatch, "native_anthropic", lambda: anthropic) @pytest.mark.asyncio -@pytest.mark.parametrize("tokenizer", TOKENIZERS) -async def test_disabled_bridge_never_constructs_a_counter(tokenizer: bridge.RustTokenizer) -> None: +async def test_native_count_returns_typed_count_and_reuses_one_counter(fake_tokenizers: None) -> None: factory: Final = _RecordingFactory() - litellm.rust(False) - bridge.TOKEN_COUNTER.override(factory) - model: Final = MODEL_BY_TOKENIZER[tokenizer] - raw, request_body = _counted({"messages": [{"role": "user", "content": "hello"}]}, model) - - counts: Final = await count_input_tokens(request_body=request_body, raw_body=raw, models=(model,)) - - assert counts[model] == count_input_tokens_for_model(request_body=request_body, model=model) - assert factory.counters == [] - - -@pytest.mark.asyncio -async def test_enabled_bridge_returns_typed_count_and_reuses_one_counter() -> None: - factory: Final = _RecordingFactory() - litellm.rust(True) - bridge.TOKEN_COUNTER.override(factory) first: Final = await bridge.native_count(factory, "anthropic", BODY) second: Final = await bridge.native_count(factory, "anthropic", BODY) @@ -166,10 +101,10 @@ async def test_enabled_bridge_returns_typed_count_and_reuses_one_counter() -> No @pytest.mark.asyncio @pytest.mark.parametrize("tokenizer", ("cl100k_base", "o200k_base")) -async def test_tiktoken_counter_is_built_over_the_shared_encoding_once(tokenizer: bridge.RustTokenizer) -> None: +async def test_tiktoken_counter_is_built_over_the_shared_encoding_once( + fake_tokenizers: None, tokenizer: bridge.RustTokenizer +) -> None: factory: Final = _RecordingFactory() - litellm.rust(True) - bridge.TOKEN_COUNTER.override(factory) first: Final = await bridge.native_count(factory, tokenizer, BODY) second: Final = await bridge.native_count(factory, tokenizer, BODY) @@ -183,10 +118,8 @@ async def test_tiktoken_counter_is_built_over_the_shared_encoding_once(tokenizer @pytest.mark.asyncio -async def test_each_tokenizer_gets_its_own_cached_counter() -> None: +async def test_each_tokenizer_gets_its_own_cached_counter(fake_tokenizers: None) -> None: factory: Final = _RecordingFactory() - litellm.rust(True) - bridge.TOKEN_COUNTER.override(factory) await bridge.native_count(factory, "anthropic", BODY) await bridge.native_count(factory, "cl100k_base", BODY) @@ -198,43 +131,6 @@ async def test_each_tokenizer_gets_its_own_cached_counter() -> None: assert [len(counter.bodies) for counter in factory.counters] == [2, 1, 2] -@pytest.mark.asyncio -async def test_missing_native_module_falls_back(monkeypatch: pytest.MonkeyPatch) -> None: - litellm.rust(True) - monkeypatch.setattr(bindings, "get_native_bridge", lambda: None) - raw, request_body = _counted({"messages": [{"role": "user", "content": "hello"}]}, MODEL) - - counts: Final = await count_input_tokens(request_body=request_body, raw_body=raw, models=(MODEL,)) - - assert counts[MODEL] == count_input_tokens_for_model(request_body=request_body, model=MODEL) - - -@pytest.mark.asyncio -@pytest.mark.parametrize("tokenizer", TOKENIZERS) -async def test_declined_request_falls_back(tokenizer: bridge.RustTokenizer) -> None: - litellm.rust(True) - bridge.TOKEN_COUNTER.override(_RaisingFactory(_FakeDeclined("request has no messages"))) - model: Final = MODEL_BY_TOKENIZER[tokenizer] - raw, request_body = _counted({"messages": [{"role": "user", "content": "hello"}]}, model) - - counts: Final = await count_input_tokens(request_body=request_body, raw_body=raw, models=(model,)) - - assert counts[model] == count_input_tokens_for_model(request_body=request_body, model=model) - - -@pytest.mark.asyncio -@pytest.mark.parametrize("tokenizer", TOKENIZERS) -async def test_runtime_failure_falls_back(tokenizer: bridge.RustTokenizer) -> None: - litellm.rust(True) - bridge.TOKEN_COUNTER.override(_RaisingFactory(RuntimeError("encode failed"))) - model: Final = MODEL_BY_TOKENIZER[tokenizer] - raw, request_body = _counted({"messages": [{"role": "user", "content": "hello"}]}, model) - - counts: Final = await count_input_tokens(request_body=request_body, raw_body=raw, models=(model,)) - - assert counts[model] == count_input_tokens_for_model(request_body=request_body, model=model) - - @pytest.mark.parametrize( ("model", "expected"), ( @@ -416,39 +312,34 @@ PARITY_MODELS: Final[tuple[tuple[str, bridge.RustTokenizer], ...]] = ( @pytest.mark.parametrize(("model", "tokenizer"), PARITY_MODELS) @pytest.mark.parametrize("request_body", PARITY_REQUESTS) async def test_native_count_matches_python_budget_counter( - monkeypatch: pytest.MonkeyPatch, request_body: dict[str, object], model: str, tokenizer: bridge.RustTokenizer + request_body: dict[str, object], model: str, tokenizer: bridge.RustTokenizer ) -> None: native: Final = pytest.importorskip("litellm.rust_bridge._native") - monkeypatch.setattr(bindings, "get_native_bridge", lambda: native) - litellm.rust(True) body: Final = json.dumps(request_body).replace(MODEL, model) + parsed: Final = json.loads(body) - request_body_parsed: Final = json.loads(body) - counts: Final = await count_input_tokens(request_body=request_body_parsed, raw_body=body.encode(), models=(model,)) - python_count: Final = count_input_tokens_for_model(request_body=request_body_parsed, model=model) + counted: Final = await bridge.native_count(native.TokenCounter, tokenizer, body.encode()) - assert counts[model] == python_count + assert counted.input_tokens == count_input_tokens_for_model(request_body=parsed, model=model) @pytest.mark.asyncio @pytest.mark.parametrize(("model", "tokenizer"), ((CL100K_MODEL, "cl100k_base"), (O200K_MODEL, "o200k_base"))) async def test_tiktoken_counts_long_text_exactly_where_python_chunks( - monkeypatch: pytest.MonkeyPatch, model: str, tokenizer: bridge.RustTokenizer + model: str, tokenizer: bridge.RustTokenizer ) -> None: """Python encodes tiktoken text in fixed-size chunks (drift of up to one token per chunk boundary); Rust does not.""" native: Final = pytest.importorskip("litellm.rust_bridge._native") - monkeypatch.setattr(bindings, "get_native_bridge", lambda: native) - litellm.rust(True) text: Final = "x " * 20_000 body: Final = {"model": model, "messages": [{"role": "user", "content": text}]} encoding: Final = Tokenizer.from_tiktoken(tokenizer) exact: Final = 3 + encoding.count("user") + encoding.count(text) + 3 chunks: Final = -(-len(text) // TIKTOKEN_ENCODE_CHUNK_SIZE_CHARS) - counts: Final = await count_input_tokens(request_body=body, raw_body=json.dumps(body).encode(), models=(model,)) + counted: Final = await bridge.native_count(native.TokenCounter, tokenizer, json.dumps(body).encode()) python_count: Final = count_input_tokens_for_model(request_body=body, model=model) - assert counts[model] == exact + assert counted.input_tokens == exact assert python_count is not None assert exact < python_count <= exact + chunks @@ -470,14 +361,10 @@ DECLINED_REQUESTS: Final[tuple[dict[str, object], ...]] = ( @pytest.mark.parametrize("tokenizer", TOKENIZERS) @pytest.mark.parametrize("request_body", DECLINED_REQUESTS) async def test_native_declines_shapes_python_prices_differently( - monkeypatch: pytest.MonkeyPatch, request_body: dict[str, object], tokenizer: bridge.RustTokenizer + request_body: dict[str, object], tokenizer: bridge.RustTokenizer ) -> None: native: Final = pytest.importorskip("litellm.rust_bridge._native") - monkeypatch.setattr(bindings, "get_native_bridge", lambda: native) - litellm.rust(True) - model: Final = MODEL_BY_TOKENIZER[tokenizer] - raw, parsed = _counted(request_body, model) + raw, _ = _counted(request_body, MODEL_BY_TOKENIZER[tokenizer]) - counts: Final = await count_input_tokens(request_body=parsed, raw_body=raw, models=(model,)) - - assert counts.get(model) == count_input_tokens_for_model(request_body=parsed, model=model) + with pytest.raises(native.RustBridgeDeclined): + await bridge.native_count(native.TokenCounter, tokenizer, raw) diff --git a/tests/test_litellm/rust_bridge/test_tokenizer.py b/tests/test_litellm/rust_bridge/test_tokenizer.py index 0de7ad50b1e..188aa81093f 100644 --- a/tests/test_litellm/rust_bridge/test_tokenizer.py +++ b/tests/test_litellm/rust_bridge/test_tokenizer.py @@ -1,134 +1,49 @@ -from collections.abc import Generator from typing import Final import pytest import tiktoken from tokenizers import Tokenizer -import litellm from litellm.litellm_core_utils.tokenizer import HuggingFaceTokenizer, OpenAIEncoding -from litellm.rust_bridge import configuration, tokenizer -from litellm.utils import _select_tokenizer +from litellm.rust_bridge import tokenizer +from litellm.utils import claude_json_str from tests.test_litellm.litellm_core_utils.test_decode_special_tokens import TOKENIZER_JSON - -@pytest.fixture(autouse=True) -def isolated_configuration(monkeypatch: pytest.MonkeyPatch) -> Generator[None]: - monkeypatch.delenv("LITELLM_RUST", raising=False) - configuration.reset_rust_configuration() - yield - tokenizer.TOKENIZER.reset() - configuration.reset_rust_configuration() +TEXTS: Final = ("hello <|endoftext|> world", "café 漢字 🙂", " def f():\n return 1\n", "hello again") -@pytest.mark.parametrize("environment", (None, "0", "1")) -@pytest.mark.parametrize("process", (None, False, True)) -def test_tokenizer_factories_follow_rollout( - monkeypatch: pytest.MonkeyPatch, environment: str | None, process: bool | None -) -> None: - configuration.rust(process) - if environment is not None: - monkeypatch.setenv("LITELLM_RUST", environment) - enabled: Final = environment == "1" if environment is not None else process is True - encoding: Final = tokenizer.get_encoding("cl100k_base") - custom: Final = litellm.create_tokenizer(TOKENIZER_JSON) +@pytest.mark.parametrize("name", ("cl100k_base", "o200k_base")) +@pytest.mark.parametrize("text", TEXTS) +def test_native_encoding_matches_tiktoken(name: str, text: str) -> None: + native: Final = tokenizer.native_encoding(name) + if native is None: + pytest.skip("native extension is not built") + encoding: Final = OpenAIEncoding.wrap(native) + reference: Final = tiktoken.get_encoding(name) + + ids: Final = encoding.encode(text, disallowed_special=()) + assert ids == reference.encode(text, disallowed_special=()) + assert encoding.decode(ids) == reference.decode(ids) + + +@pytest.mark.parametrize("text", TEXTS) +def test_native_anthropic_tokenizer_matches_python(text: str) -> None: + native: Final = tokenizer.native_anthropic() + if native is None: + pytest.skip("native extension is not built") + reference: Final = Tokenizer.from_str(claude_json_str) + + ids: Final = HuggingFaceTokenizer(native).encode(text).ids + assert ids == reference.encode(text).ids + assert HuggingFaceTokenizer(native).decode(ids) == reference.decode(ids) + + +def test_native_custom_tokenizer_matches_python() -> None: + factory: Final = tokenizer.TOKENIZER.load() + if factory is None: + pytest.skip("native extension is not built") + native: Final = HuggingFaceTokenizer(factory.from_json(TOKENIZER_JSON)) reference: Final = Tokenizer.from_str(TOKENIZER_JSON) - assert isinstance(encoding, OpenAIEncoding if enabled else tiktoken.Encoding) - assert isinstance(custom["tokenizer"], HuggingFaceTokenizer if enabled else Tokenizer) - assert encoding.encode("café 漢字 🙂") == tiktoken.get_encoding(encoding.name).encode("café 漢字 🙂") - assert litellm.encode(text="Hello World", custom_tokenizer=custom) == reference.encode("Hello World").ids - assert litellm.token_counter(text="Hello World", custom_tokenizer=custom) == len(reference.encode("Hello World")) - - -def test_missing_native_binding_keeps_python_tokenizer_api() -> None: - configuration.rust(True) - tokenizer.TOKENIZER.override(None) - encoding: Final = tokenizer.get_encoding("cl100k_base") - custom: Final = litellm.create_tokenizer(TOKENIZER_JSON)["tokenizer"] - - assert isinstance(encoding, tiktoken.Encoding) - assert isinstance(custom, Tokenizer) - custom.enable_padding(pad_id=0, pad_token="[UNK]") - assert [item.ids for item in custom.encode_batch(["Hello", "Hello World"])] == [[3, 1, 0], [3, 1, 2]] - - -def test_cached_selection_follows_backend_changes(monkeypatch: pytest.MonkeyPatch) -> None: - monkeypatch.setattr(litellm, "disable_hf_tokenizer_download", True) - configuration.rust(True) - native: Final = _select_tokenizer("dispatch-fixture")["tokenizer"] - configuration.rust(False) - python: Final = _select_tokenizer("dispatch-fixture")["tokenizer"] - - assert isinstance(native, OpenAIEncoding) - assert isinstance(python, tiktoken.Encoding) - assert native.encode("hello") == python.encode("hello") - - -def test_declined_native_factory_falls_back_before_tokenizing() -> None: - from litellm.rust_bridge._native import RustBridgeDeclined - - class UnavailableTokenizer: - @staticmethod - def from_json(json: str) -> None: - raise RustBridgeDeclined("huggingface feature is disabled") - - configuration.rust(True) - binding: Final = tokenizer._as_factory(UnavailableTokenizer) - tokenizer.TOKENIZER.override(binding) - custom: Final = litellm.create_tokenizer(TOKENIZER_JSON) - - assert isinstance(custom["tokenizer"], Tokenizer) - assert ( - litellm.decode(tokens=litellm.encode(text="Hello World", custom_tokenizer=custom), custom_tokenizer=custom) - == "Hello World" - ) - - -@pytest.mark.parametrize( - ("model", "text"), - ( - ("gpt-4o", "hello <|endoftext|> world"), - ("gpt-3.5-turbo", "café 漢字 🙂"), - ("text-davinci-003", " def f():\n return 1\n"), - ("tokenizer-parity-fixture", "hello again"), - ), -) -def test_public_token_api_is_identical_across_backends(monkeypatch: pytest.MonkeyPatch, model: str, text: str) -> None: - """`litellm.token_counter`, `encode` and `decode` return the same values whichever backend - the catalog picks; only the object types differ.""" - monkeypatch.setattr(litellm, "anthropic_models", {*litellm.anthropic_models, "tokenizer-parity-fixture"}) - messages: Final = [{"role": "user", "content": text}, {"role": "assistant", "content": "ok"}] - - def observe() -> tuple[int, int, list[int], str]: - ids: Final = litellm.encode(model=model, text=text) - return ( - litellm.token_counter(model=model, text=text), - litellm.token_counter(model=model, messages=messages), - ids, - litellm.decode(model=model, tokens=ids), - ) - - configuration.rust(False) - python: Final = observe() - configuration.rust(True) - rust: Final = observe() - - assert rust == python - - -def test_cached_huggingface_tokenizers_follow_backend_changes(monkeypatch: pytest.MonkeyPatch) -> None: - from litellm.litellm_core_utils.tokenizer import HuggingFaceTokenizer as RustHuggingFaceTokenizer - from litellm.utils import _load_huggingface_tokenizer - - monkeypatch.setattr(litellm, "anthropic_models", {*litellm.anthropic_models, "tokenizer-cache-fixture"}) - _load_huggingface_tokenizer.cache_clear() - configuration.rust(True) - native: Final = _select_tokenizer("tokenizer-cache-fixture")["tokenizer"] - configuration.rust(False) - python: Final = _select_tokenizer("tokenizer-cache-fixture")["tokenizer"] - configuration.rust(True) - - assert isinstance(native, RustHuggingFaceTokenizer) - assert isinstance(python, Tokenizer) - assert _select_tokenizer("tokenizer-cache-fixture")["tokenizer"] is native + assert native.encode("Hello World").ids == reference.encode("Hello World").ids + assert native.decode(reference.encode("Hello World").ids) == reference.decode(reference.encode("Hello World").ids) From b6d4133e41df345bb3894b6beb1802863e611a0a Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 12:35:27 -0700 Subject: [PATCH 008/101] fix(websearch_interception): keep intercepted searches under the parent request's session and trace (#41711) * fix(websearch_interception): propagate parent session/trace ids into intercepted searches Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(websearch_interception): let parent correlation win over configured search params and type test params Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(e2e): bill an intercepted web search under the parent request session Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(e2e): drop unrelated reformatting from the websearch session harness change Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * ci(e2e): keep the websearch interception session suite out of the stage-mirror gate The stage-mirror stack runs no websearch_interception callback or search tool, so the suite is deselected there and the changed-tests gate fails on a file that executed nothing Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * ci(e2e): run the websearch interception session suite on the stage-mirror stack Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * docs(e2e): leave CONTRIBUTING.md untouched Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: shivam Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- .../websearch_interception/handler.py | 93 ++++++++++- tests/e2e/AGENTS.md | 3 +- .../coverage_registry/quota_management.yaml | 1 + tests/e2e/e2e_http.py | 1 + tests/e2e/gateway/stage_mirror_ci_config.yml | 11 +- tests/e2e/models.py | 10 ++ tests/e2e/proxy_client.py | 39 ++++- ...test_websearch_interception_session_e2e.py | 102 ++++++++++++ .../test_websearch_interception_handler.py | 156 ++++++++++++++++++ 9 files changed, 406 insertions(+), 10 deletions(-) create mode 100644 tests/e2e/quota_management/spend_tracking/test_websearch_interception_session_e2e.py diff --git a/litellm/integrations/websearch_interception/handler.py b/litellm/integrations/websearch_interception/handler.py index 6a4c67c7db1..54578323fa4 100644 --- a/litellm/integrations/websearch_interception/handler.py +++ b/litellm/integrations/websearch_interception/handler.py @@ -10,6 +10,8 @@ import asyncio import math import uuid from collections.abc import AsyncIterator, Mapping, Sequence +from dataclasses import dataclass +from types import MappingProxyType from typing import TYPE_CHECKING, Any, Final, Literal, TypedDict, TypeVar, cast from typing_extensions import Never, ReadOnly @@ -196,6 +198,46 @@ class _AcompletionNamedParams(TypedDict, total=False): _NO_ACREATE_NAMED: Final[_AcreateNamedParams] = {} _NO_ASEARCH_NAMED: Final[_AsearchNamedParams] = {} + + +def _as_str_mapping(value: object) -> Mapping[str, object] | None: + return value if isinstance(value, Mapping) else None # pyright: ignore[reportUnknownVariableType] # str-keyed request metadata is not narrowable from object + + +@dataclass(frozen=True, slots=True) +class _ParentRequestCorrelation: + """Correlation ids of the LLM request that triggered an intercepted search, so the search's + own spend log row and traces land under the same session/trace instead of a fresh one.""" + + session_id: str | None + trace_id: str | None + parent_request_id: str | None + parent_otel_span: object | None + + def as_search_metadata(self) -> Mapping[str, object]: + return MappingProxyType( + { + key: value + for key, value in ( + ("session_id", self.session_id), + ("trace_id", self.trace_id), + ("parent_request_id", self.parent_request_id), + ("litellm_parent_otel_span", self.parent_otel_span), + ) + if value is not None + } + ) + + def as_search_kwargs(self) -> Mapping[str, str]: + return MappingProxyType( + { + key: value + for key, value in (("litellm_session_id", self.session_id), ("litellm_trace_id", self.trace_id)) + if value is not None + } + ) + + _NO_ACOMPLETION_NAMED: Final[_AcompletionNamedParams] = {} @@ -1527,15 +1569,17 @@ class WebSearchInterceptionLogger(CustomLogger): "WebSearchInterception: Executing search for '%s' using provider '%s'", query, search_provider ) user_api_key_auth: Final = self._get_user_api_key_auth_from_kwargs(kwargs) + parent_correlation: Final = self._get_parent_request_correlation(kwargs, user_api_key_auth) search_metadata: Final = ( None if user_api_key_auth is None else self._build_search_request_metadata( user_api_key_auth=user_api_key_auth, search_tool_name=search_tool_name, + parent_correlation=parent_correlation, ) ) - search_kwargs: Final = { + configured_search_kwargs: Final = { key: value for key, value in search_litellm_params.items() if key != "search_provider" and value is not None @@ -1549,8 +1593,11 @@ class WebSearchInterceptionLogger(CustomLogger): if rich_queries: query_arg = rich_queries rich_objective = rich.get("objective") - if rich_objective and "objective" not in search_kwargs: - search_kwargs["objective"] = rich_objective + if rich_objective and "objective" not in configured_search_kwargs: + configured_search_kwargs["objective"] = rich_objective + search_kwargs: Final = MappingProxyType( + {**configured_search_kwargs, **parent_correlation.as_search_kwargs()} + ) result: Final = ( await litellm.asearch( query=query_arg, search_provider=search_provider, **_NO_ASEARCH_NAMED, **search_kwargs @@ -1624,6 +1671,7 @@ class WebSearchInterceptionLogger(CustomLogger): def _build_search_request_metadata( user_api_key_auth: "UserAPIKeyAuth", search_tool_name: str | None, + parent_correlation: _ParentRequestCorrelation, ) -> Mapping[str, object]: """ Spend-tracking metadata for the intercepted search, so its provider cost is logged @@ -1637,11 +1685,50 @@ class WebSearchInterceptionLogger(CustomLogger): ) return { # mutable-ok: litellm's metadata channel is a plain dict its logging path reads and enriches **user_api_key_metadata, + **parent_correlation.as_search_metadata(), "model_group": search_tool_name, "user_api_key": user_api_key_auth.api_key, "user_api_key_auth": user_api_key_auth, } + @staticmethod + def _get_parent_request_correlation( + kwargs: Mapping[str, object] | None, + user_api_key_auth: "UserAPIKeyAuth | None", + ) -> _ParentRequestCorrelation: + """Read the originating request's ids from the hook kwargs, which are either the raw call + kwargs (metadata/litellm_metadata at top level) or a logging payload (under litellm_params).""" + if not kwargs: + return _ParentRequestCorrelation(None, None, None, None) + litellm_params: Final = _as_str_mapping(kwargs.get("litellm_params")) + scopes: Final[tuple[Mapping[str, object], ...]] = ( + (kwargs,) if litellm_params is None else (kwargs, litellm_params) + ) + metadatas: Final[tuple[Mapping[str, object], ...]] = tuple( + metadata + for scope in scopes + for metadata_key in ("metadata", "litellm_metadata") + if (metadata := _as_str_mapping(scope.get(metadata_key))) is not None + ) + + def first_str(scope_key: str | None, metadata_key: str | None) -> str | None: + candidates: Final[tuple[object, ...]] = ( + *(scope.get(scope_key) for scope in scopes if scope_key is not None), + *(metadata.get(metadata_key) for metadata in metadatas if metadata_key is not None), + ) + return next((value for value in candidates if isinstance(value, str) and value), None) + + parent_otel_span: Final[object | None] = next( + (span for metadata in metadatas if (span := metadata.get("litellm_parent_otel_span")) is not None), + None if user_api_key_auth is None else user_api_key_auth.parent_otel_span, + ) + return _ParentRequestCorrelation( + session_id=first_str("litellm_session_id", "session_id"), + trace_id=first_str("litellm_trace_id", "trace_id"), + parent_request_id=first_str("litellm_call_id", None), + parent_otel_span=parent_otel_span, + ) + @staticmethod def _selected_search_tool_name(search_tool: Mapping[str, object] | None) -> str | None: if search_tool is None: diff --git a/tests/e2e/AGENTS.md b/tests/e2e/AGENTS.md index b00b7dfac95..6ea75b806d0 100644 --- a/tests/e2e/AGENTS.md +++ b/tests/e2e/AGENTS.md @@ -210,6 +210,7 @@ quota_management... chat_completions | stream | messages_bridge | embeddings | cache_hit | key_rollup | concurrent_burst | tags | end_user | per_model | failure | spend_calculate | pagination | key_attribution + | websearch_interception assertion : blocks_over_limit | resets_after_window | headers_report_remaining | picks_under_tpm | blocks_then_resets | resets_windows_independently | alerts_without_blocking | isolates_per_model | isolates_per_member | isolates_per_group | enforced_across_keys @@ -217,7 +218,7 @@ quota_management... | matches_sum_of_logs | loses_no_spend | attributes_spend | writes_own_rows | writes_failure_row | returns_cost | keeps_total | joins_key | reports_alias_and_email | health_rows_keep_service_account | retrieve_batch_cost_joins_retrieving_key - | poller_batch_cost_joins_creating_key + | poller_batch_cost_joins_creating_key | bills_under_request_session e.g. quota_management.ratelimit.rpm.blocks_over_limit exercised_on=[chat_completions, messages] quota_management.budget.key.blocks_over_limit exercised_on=[chat_completions] ``` diff --git a/tests/e2e/coverage_registry/quota_management.yaml b/tests/e2e/coverage_registry/quota_management.yaml index ad0914d455b..f6b38243896 100644 --- a/tests/e2e/coverage_registry/quota_management.yaml +++ b/tests/e2e/coverage_registry/quota_management.yaml @@ -58,6 +58,7 @@ - {id: quota_management.spend_tracking.service_tier.bills_tier_rates, module: quota_management, tier: P1, behavior: spend_tracking, variant: service_tier, assertions: [bills_tier_rates], exercised_on: [chat_completions], source: "cost_calculator.py", rationale: "A priority service_tier call bills input, output, and reasoning at the deployment's *_priority rates and records the tier on the row (#35923, #35925)"} - {id: quota_management.spend_tracking.cost_headers.additive_components, module: quota_management, tier: P1, behavior: spend_tracking, variant: cost_headers, assertions: [additive_components], exercised_on: [chat_completions], source: "proxy/common_request_processing.py", rationale: "The x-litellm-response-cost-* component headers sum to the total, input covers only fresh tokens, and reasoning stays a subset of output (#36965)"} - {id: quota_management.spend_tracking.passthrough_stream.injects_usage_cost, module: quota_management, tier: P1, behavior: spend_tracking, variant: passthrough_stream, assertions: [injects_usage_cost], exercised_on: [openai_passthrough], source: "proxy/pass_through_endpoints/streaming_handler.py", rationale: "With include_cost_in_streaming_usage on, the /openai passthrough's final streaming usage frame carries the proxy-computed cost (#36503). Uncovered: the flag is only settable in litellm_settings, and the shared e2e stack does not turn it on yet"} +- {id: quota_management.spend_tracking.websearch_interception.bills_under_request_session, module: quota_management, tier: P1, behavior: spend_tracking, variant: websearch_interception, assertions: [bills_under_request_session], exercised_on: [messages], source: "integrations/websearch_interception/handler.py", fail_before_fix: proven, rationale: "A web_search server tool the proxy intercepts into litellm.asearch writes its own asearch spend row, and that row carries the parent request's session_id so the session view counts the search and its cost next to the turn that triggered it (LIT-8063)"} - {id: quota_management.spend_tracking.key_attribution.joins_key, module: quota_management, tier: P1, behavior: spend_tracking, variant: key_attribution, assertions: [joins_key], exercised_on: [chat_completions, messages, responses, embeddings, batches, files, google_native, rust_control_plane], source: "proxy/spend_tracking/spend_tracking_utils.py", rationale: "Every spend row a virtual key writes across chat, queued chat, messages, responses, embeddings, the Gemini passthrough, file upload, batch create, and a replayed callback log carries api_key equal to the key's token hash and the key alias, the join the usage APIs depend on; a re-hashed token shows up as an unattributed key-hash-* row (#39568, #39572)"} - {id: quota_management.spend_tracking.key_attribution.reports_alias_and_email, module: quota_management, tier: P1, behavior: spend_tracking, variant: key_attribution, assertions: [reports_alias_and_email], exercised_on: [chat_completions, messages, responses, embeddings, batches, files, google_native, rust_control_plane], source: "proxy/management_endpoints/internal_user_endpoints.py", rationale: "/spend/logs?api_key= returns every one of the key's rows with its alias and /user/daily/activity aggregates them under the key's token with key_alias and user_email; /spend/logs carries no email field, so the email is asserted on daily activity only"} - {id: quota_management.spend_tracking.key_attribution.health_rows_keep_service_account, module: quota_management, tier: P1, behavior: spend_tracking, variant: key_attribution, assertions: [health_rows_keep_service_account], exercised_on: [chat_completions], source: "proxy/health_check.py", rationale: "A /health probe's spend row stays keyed by the literal litellm-internal-health-check service account rather than a hash of it, so health spend never appears as an unattributed key"} diff --git a/tests/e2e/e2e_http.py b/tests/e2e/e2e_http.py index 97f1e1671f8..1b62a1dbd8c 100644 --- a/tests/e2e/e2e_http.py +++ b/tests/e2e/e2e_http.py @@ -49,6 +49,7 @@ class AnthropicHeaders(AuthHeaders): on its own internal calls.""" anthropic_version: str = Field(default="2023-06-01", alias="anthropic-version") + x_litellm_session_id: str | None = Field(default=None, serialization_alias="x-litellm-session-id") class PartialBody(BaseModel): diff --git a/tests/e2e/gateway/stage_mirror_ci_config.yml b/tests/e2e/gateway/stage_mirror_ci_config.yml index 2d02fedddae..03167692727 100644 --- a/tests/e2e/gateway/stage_mirror_ci_config.yml +++ b/tests/e2e/gateway/stage_mirror_ci_config.yml @@ -32,7 +32,10 @@ litellm_settings: - host: 127.0.0.1 port: 6379 ssl: true - callbacks: ["arize_phoenix", "datadog", "smtp_email", "prometheus", "otel"] + callbacks: ["arize_phoenix", "datadog", "smtp_email", "prometheus", "otel", "websearch_interception"] + websearch_interception_params: + enabled_providers: ["bedrock"] + search_tool_name: e2e-search require_auth_for_metrics_endpoint: false router_settings: @@ -65,6 +68,12 @@ model_list: model: openai/text-embedding-3-small api_key: os.environ/OPENAI_API_KEY +search_tools: + - search_tool_name: e2e-search + litellm_params: + search_provider: perplexity + api_key: os.environ/PERPLEXITY_API_KEY + files_settings: - custom_llm_provider: openai api_key: os.environ/OPENAI_API_KEY diff --git a/tests/e2e/models.py b/tests/e2e/models.py index f9c17314477..3309479edaf 100644 --- a/tests/e2e/models.py +++ b/tests/e2e/models.py @@ -949,6 +949,7 @@ class SpendLogRow(BaseModel): completion_tokens: int | None = None total_tokens: int | None = None request_tags: list[str] | None = None + session_id: str | None = None metadata: SpendLogMetadata | None = None proxy_server_request: JsonValue = None response: JsonValue = None @@ -985,6 +986,15 @@ class SpendLogsPageParams(BaseModel): api_key: str | None = None +class SessionSpendLogsParams(BaseModel): + """Query for /spend/logs/session/ui, the session view the Admin UI logs page + opens: every row whose session_id equals the given one, newest first.""" + + session_id: str + page: int = 1 + page_size: int = 100 + + class SpendLogsPage(BaseModel): data: list[SpendLogRow] = [] total: int diff --git a/tests/e2e/proxy_client.py b/tests/e2e/proxy_client.py index f1981e0aa5e..66df1c4c106 100644 --- a/tests/e2e/proxy_client.py +++ b/tests/e2e/proxy_client.py @@ -87,6 +87,7 @@ from models import ( RouterSettingsResponse, SearchToolCreateBody, SearchToolCreateResponse, + SessionSpendLogsParams, SpendLogRow, SpendLogs, SpendLogsPage, @@ -1004,19 +1005,26 @@ class ProxyClient: response_type=CountTokensResponse, ) - def messages(self, key: str, body: AnthropicMessagesBody) -> Result[AnthropicMessagesResponse]: + def messages( + self, key: str, body: AnthropicMessagesBody, *, session_id: str | None = None + ) -> Result[AnthropicMessagesResponse]: """POST /v1/messages (Anthropic-native). The response is either the Anthropic-shape passthrough (`content`) or the OpenAI-normalized shape - (`choices`); AnthropicMessagesResponse models both.""" + (`choices`); AnthropicMessagesResponse models both. `session_id` goes out + as the `x-litellm-session-id` header, the way Claude Code sends it through + ANTHROPIC_CUSTOM_HEADERS, so every spend row the call produces shares it.""" return self.transport.post( "/v1/messages", - headers=self._anthropic_headers(key), + headers=self._anthropic_headers(key, session_id=session_id), json=body, response_type=AnthropicMessagesResponse, ) - def _anthropic_headers(self, key: str) -> AnthropicHeaders: - return AnthropicHeaders(authorization=self.transport.bearer(key).authorization) + def _anthropic_headers(self, key: str, *, session_id: str | None = None) -> AnthropicHeaders: + return AnthropicHeaders( + authorization=self.transport.bearer(key).authorization, + x_litellm_session_id=session_id, + ) # ---- spend read-back ------------------------------------------------ @@ -1060,6 +1068,27 @@ class ProxyClient: ) -> list[SpendLogRow]: return self._poll(lambda: self.spend_logs(SpendLogsParams(api_key=key)), min_rows, predicate) + def session_spend_logs(self, session_id: str) -> list[SpendLogRow]: + """GET /spend/logs/session/ui, the per-session view the Admin UI logs page + opens when a session id is clicked.""" + return unwrap( + self.transport.get( + "/spend/logs/session/ui", + headers=self.management_headers(), + params=SessionSpendLogsParams(session_id=session_id), + response_type=SpendLogsPage, + ) + ).data + + def poll_logs_for_session( + self, + session_id: str, + *, + min_rows: int = 1, + predicate: RowsPredicate | None = None, + ) -> list[SpendLogRow]: + return self._poll(lambda: self.session_spend_logs(session_id), min_rows, predicate) + def poll_logs_for_request_id( self, request_id: str, diff --git a/tests/e2e/quota_management/spend_tracking/test_websearch_interception_session_e2e.py b/tests/e2e/quota_management/spend_tracking/test_websearch_interception_session_e2e.py new file mode 100644 index 00000000000..89d0beec414 --- /dev/null +++ b/tests/e2e/quota_management/spend_tracking/test_websearch_interception_session_e2e.py @@ -0,0 +1,102 @@ +"""Intercepted web searches are billed under the LLM request's session. + +The websearch_interception callback turns an Anthropic ``web_search`` server tool +into a ``litellm.asearch`` call against a configured search tool, so each search is +its own spend row (call_type ``asearch``) next to the ``anthropic_messages`` row for +the turn that asked for it. Claude Code and the Admin UI group spend by +``session_id``, so the search row has to carry the same session as the turn that +triggered it; before the fix it landed under a session of its own and the session +view under-counted both requests and spend (LIT-8063). + +Needs a proxy booted with the callback and a real search backend, which +``gateway/stage_mirror_ci_config.yml`` carries as the ``e2e-search`` Perplexity tool. +""" + +from typing import Final + +import pytest +from e2e_config import unique_marker +from e2e_http import unwrap +from lifecycle import ResourceManager +from models import ( + AnthropicMessagesBody, + AnthropicWebSearchTool, + ChatMessage, + LiteLLMParamsBody, + SpendLogRow, +) +from proxy_client import ProxyClient + +pytestmark = pytest.mark.e2e + +BEDROCK_INVOKE_BACKEND: Final = "bedrock/invoke/us.anthropic.claude-haiku-4-5-20251001-v1:0" +SEARCH_CALL_TYPE: Final = "asearch" + + +def _has_search_row(rows: list[SpendLogRow]) -> bool: + return any(row.call_type == SEARCH_CALL_TYPE for row in rows) + + +class TestWebSearchInterceptionSession: + @pytest.mark.covers( + "quota_management.spend_tracking.websearch_interception.bills_under_request_session", + exercised_on=("messages",), + ) + def test_intercepted_search_is_billed_under_the_request_session( + self, proxy: ProxyClient, resources: ResourceManager + ) -> None: + """One /v1/messages turn that runs an intercepted web search must produce an + ``asearch`` spend row in the same session as its ``anthropic_messages`` row, + billed separately and with its own request id.""" + marker: Final = unique_marker() + model: Final = f"e2e-websearch-session-{marker}" + model_id: Final = proxy.create_model( + model, LiteLLMParamsBody(model=BEDROCK_INVOKE_BACKEND, aws_region_name="us-east-1") + ) + resources.defer(lambda: proxy.delete_model(model_id)) + key: Final = resources.key(models=[model]) + session_id: Final = f"e2e-websearch-session-{marker}" + + response: Final = unwrap( + proxy.messages( + key, + AnthropicMessagesBody( + model=model, + max_tokens=512, + tools=[AnthropicWebSearchTool(type="web_search_20250305", name="web_search", max_uses=1)], + messages=[ + ChatMessage( + role="user", + content=f"Use web search to find one recent news headline about Anthropic ({marker}).", + ) + ], + ), + session_id=session_id, + ) + ) + block_types: Final = tuple(block.type for block in response.content or ()) + assert "web_search_tool_result" in block_types, ( + f"precondition: the turn never ran an intercepted search, so there is no search row to attribute. " + f"blocks={block_types}" + ) + + rows: Final = proxy.poll_logs_for_session(session_id, min_rows=2, predicate=_has_search_row) + by_call_type: Final = {row.call_type or "" for row in rows} + assert SEARCH_CALL_TYPE in by_call_type, ( + f"session {session_id} has no {SEARCH_CALL_TYPE} row, so the intercepted search was billed under a " + f"different session and the session view misses its cost. call_types={sorted(by_call_type)} " + f"rows={[(row.call_type, row.request_id, row.spend) for row in rows]}" + ) + search_rows: Final = tuple(row for row in rows if row.call_type == SEARCH_CALL_TYPE) + turn_rows: Final = tuple(row for row in rows if row.call_type != SEARCH_CALL_TYPE) + assert turn_rows, f"session {session_id} carries only search rows: {rows!r}" + assert all(row.session_id == session_id for row in rows), ( + f"session view returned rows outside {session_id}: {[row.session_id for row in rows]}" + ) + assert all((row.spend or 0.0) > 0 for row in search_rows), ( + f"an intercepted search must stay a separately billed row: {[row.spend for row in search_rows]}" + ) + assert {row.request_id for row in search_rows}.isdisjoint({row.request_id for row in turn_rows}), ( + "a search row reused its parent turn's request_id instead of keeping its own: " + f"{[(row.call_type, row.request_id) for row in rows]}" + ) diff --git a/tests/test_litellm/integrations/websearch_interception/test_websearch_interception_handler.py b/tests/test_litellm/integrations/websearch_interception/test_websearch_interception_handler.py index f39f41a6d12..d6450d0f1de 100644 --- a/tests/test_litellm/integrations/websearch_interception/test_websearch_interception_handler.py +++ b/tests/test_litellm/integrations/websearch_interception/test_websearch_interception_handler.py @@ -287,6 +287,162 @@ async def test_execute_search_attributes_spend_to_the_calling_key(monkeypatch): ) +def _perplexity_router() -> MagicMock: + router = MagicMock() + router.search_tools = [ + { + "search_tool_name": "perplexity-sonar-pro", + "litellm_params": {"search_provider": "perplexity", "api_key": "fake-key"}, + } + ] + return router + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "parent_kwargs", + [ + pytest.param( + { + "litellm_call_id": "parent-call-1", + "litellm_trace_id": "trace-abc", + "litellm_session_id": "session-abc", + "metadata": { + "user_api_key_auth": UserAPIKeyAuth(api_key="hashed-sk-1234"), + "session_id": "session-abc", + }, + }, + id="chat-completions-call-kwargs", + ), + pytest.param( + { + "litellm_call_id": "parent-call-1", + "litellm_metadata": { + "user_api_key_auth": UserAPIKeyAuth(api_key="hashed-sk-1234"), + "session_id": "session-abc", + "trace_id": "trace-abc", + }, + }, + id="anthropic-messages-litellm-metadata", + ), + pytest.param( + { + "litellm_params": { + "litellm_call_id": "parent-call-1", + "litellm_trace_id": "trace-abc", + "metadata": {"user_api_key_auth": UserAPIKeyAuth(api_key="hashed-sk-1234")}, + "litellm_metadata": {"session_id": "session-abc"}, + } + }, + id="logging-payload-with-both-metadata-keys", + ), + ], +) +async def test_execute_search_inherits_parent_request_session_and_trace( + monkeypatch: pytest.MonkeyPatch, parent_kwargs: dict[str, object] +): + """The intercepted asearch is billed as its own call but must land in the parent request's + session and trace, otherwise every search shows up as a separate one-call session in SpendLogs.""" + import litellm + from litellm.proxy import proxy_server + from litellm.proxy.spend_tracking.spend_tracking_utils import _get_session_id_for_spend_log + + logger = WebSearchInterceptionLogger(enabled_providers=["bedrock"], search_tool_name="perplexity-sonar-pro") + mock_asearch = AsyncMock(return_value=SearchResponse(object="search", results=[])) + monkeypatch.setattr(proxy_server, "llm_router", _perplexity_router()) + monkeypatch.setattr(litellm, "asearch", mock_asearch) + + await logger._execute_search("what is litellm", kwargs=parent_kwargs) + + forwarded = mock_asearch.await_args.kwargs + assert forwarded["litellm_session_id"] == "session-abc" + assert forwarded["litellm_trace_id"] == "trace-abc" + assert forwarded["litellm_metadata"]["session_id"] == "session-abc" + assert forwarded["litellm_metadata"]["trace_id"] == "trace-abc" + assert forwarded["litellm_metadata"]["parent_request_id"] == "parent-call-1" + assert forwarded["litellm_metadata"]["user_api_key"] == "hashed-sk-1234" + assert forwarded["litellm_metadata"]["model_group"] == "perplexity-sonar-pro" + assert "litellm_call_id" not in forwarded + assert ( + _get_session_id_for_spend_log( + kwargs={"litellm_trace_id": forwarded["litellm_trace_id"]}, + metadata=forwarded["litellm_metadata"], + standard_logging_payload=None, + omit_when_missing=True, + ) + == "session-abc" + ) + + +@pytest.mark.asyncio +async def test_execute_search_forwards_parent_otel_span_from_key_auth(monkeypatch: pytest.MonkeyPatch): + import litellm + from litellm.proxy import proxy_server + + logger = WebSearchInterceptionLogger(enabled_providers=["bedrock"], search_tool_name="perplexity-sonar-pro") + mock_asearch = AsyncMock(return_value=SearchResponse(object="search", results=[])) + monkeypatch.setattr(proxy_server, "llm_router", _perplexity_router()) + monkeypatch.setattr(litellm, "asearch", mock_asearch) + parent_span = object() + + await logger._execute_search( + "what is litellm", + kwargs={"metadata": {"user_api_key_auth": UserAPIKeyAuth(api_key="sk", parent_otel_span=parent_span)}}, + ) + + assert mock_asearch.await_args.kwargs["litellm_metadata"]["litellm_parent_otel_span"] is parent_span + + +@pytest.mark.asyncio +async def test_execute_search_without_parent_session_does_not_invent_one(monkeypatch: pytest.MonkeyPatch): + """A parent request with no session/trace must not stamp empty correlation keys on the search.""" + import litellm + from litellm.proxy import proxy_server + + logger = WebSearchInterceptionLogger(enabled_providers=["bedrock"], search_tool_name="perplexity-sonar-pro") + mock_asearch = AsyncMock(return_value=SearchResponse(object="search", results=[])) + monkeypatch.setattr(proxy_server, "llm_router", _perplexity_router()) + monkeypatch.setattr(litellm, "asearch", mock_asearch) + + await logger._execute_search( + "what is litellm", + kwargs={"litellm_params": {"metadata": {"user_api_key_auth": UserAPIKeyAuth(api_key="sk"), "prompt": "x"}}}, + ) + + forwarded = mock_asearch.await_args.kwargs + assert "litellm_session_id" not in forwarded + assert "litellm_trace_id" not in forwarded + assert not {"session_id", "trace_id", "parent_request_id", "prompt"} & forwarded["litellm_metadata"].keys() + + +@pytest.mark.asyncio +async def test_concurrent_searches_keep_their_own_parent_session(monkeypatch: pytest.MonkeyPatch): + import asyncio + + import litellm + from litellm.proxy import proxy_server + + logger = WebSearchInterceptionLogger(enabled_providers=["bedrock"], search_tool_name="perplexity-sonar-pro") + mock_asearch = AsyncMock(return_value=SearchResponse(object="search", results=[])) + monkeypatch.setattr(proxy_server, "llm_router", _perplexity_router()) + monkeypatch.setattr(litellm, "asearch", mock_asearch) + + await asyncio.gather( + *( + logger._execute_search( + f"query {i}", + kwargs={"metadata": {"user_api_key_auth": UserAPIKeyAuth(api_key="sk"), "session_id": f"session-{i}"}}, + ) + for i in range(5) + ) + ) + + seen = { + call.kwargs["query"]: call.kwargs["litellm_metadata"]["session_id"] for call in mock_asearch.await_args_list + } + assert seen == {f"query {i}": f"session-{i}" for i in range(5)} + + @pytest.mark.asyncio async def test_execute_search_without_proxy_auth_context_stays_sdk_only(monkeypatch): """SDK callers have no key to attribute the search to, so no proxy metadata is invented.""" From 75163278988aa0b6fc073767d5652426327f4480 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 12:42:41 -0700 Subject: [PATCH 009/101] test(e2e): assert a cooldown reaches a sibling replica within the 1s Redis read interval (#42422) * test(e2e): assert a cooldown reaches a sibling replica within the 1s Redis read interval * test(e2e): skip the sibling replica cooldown cell when one gateway URL is named * test(e2e): collapse repeated gateway addresses so the sibling cooldown cell skips instead of erroring --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- tests/e2e/coverage_registry/reliability.yaml | 1 + tests/e2e/e2e_config.py | 2 +- tests/e2e/router/reliability_support.py | 32 ++++- .../router/test_reliability_cooldowns_e2e.py | 112 +++++++++++++++--- tests/e2e/test_proxy_client.py | 4 + 5 files changed, 133 insertions(+), 18 deletions(-) diff --git a/tests/e2e/coverage_registry/reliability.yaml b/tests/e2e/coverage_registry/reliability.yaml index 334780eda53..9f88f2478c0 100644 --- a/tests/e2e/coverage_registry/reliability.yaml +++ b/tests/e2e/coverage_registry/reliability.yaml @@ -9,6 +9,7 @@ - {id: reliability.retry.auth.succeeds_within_retries, module: reliability, tier: P1, behavior: retry, variant: auth, assertions: [succeeds_within_retries], exercised_on: [chat_completions], source: "get_retry_from_policy.py:42", rationale: "Transient auth glitch retry"} - {id: reliability.retry.context_window.succeeds_within_retries, module: reliability, tier: P1, behavior: retry, variant: context_window, assertions: [succeeds_within_retries], exercised_on: [chat_completions], source: "get_retry_from_policy.py:51", fail_before_fix: proven, rationale: "A context-window 400 under BadRequestErrorRetries retries onto a sibling deployment in the same model group, instead of coming straight back as the 400 the deployment that just refused it returned"} - {id: reliability.cooldown.5xx.trips_then_recovers, module: reliability, tier: P0, behavior: cooldown, variant: "5xx", assertions: [trips_then_recovers], exercised_on: [chat_completions], source: "cooldown_handlers.py:40", rationale: "Deployment cools after repeated 5xx, recovers after cooldown_time"} +- {id: reliability.cooldown.sibling_replica.serves_backup_within_read_interval, module: reliability, tier: P1, behavior: cooldown, variant: sibling_replica, assertions: [serves_backup_within_read_interval], exercised_on: [chat_completions], source: "cooldown_cache.py:44", fail_before_fix: proven, rationale: "A bench taken on one gateway reaches a sibling that already holds the key's read timer within the 1s Redis read interval plus margin, so its next call lands on the backup"} - {id: reliability.cooldown.429.trips_then_recovers, module: reliability, tier: P0, behavior: cooldown, variant: "429", assertions: [trips_then_recovers], exercised_on: [chat_completions], source: "cooldown_handlers.py:69", rationale: "Cools on 429, avoids hammering exhausted provider"} - {id: reliability.cooldown.auth.trips_then_recovers, module: reliability, tier: P1, behavior: cooldown, variant: auth, assertions: [trips_then_recovers], exercised_on: [chat_completions], source: "cooldown_handlers.py:74", rationale: "Cools on 401 auth error"} - {id: reliability.cooldown.timeout.trips_then_recovers, module: reliability, tier: P1, behavior: cooldown, variant: timeout, assertions: [trips_then_recovers], exercised_on: [chat_completions], source: "cooldown_handlers.py:77", rationale: "Cools on 408 timeout"} diff --git a/tests/e2e/e2e_config.py b/tests/e2e/e2e_config.py index 311c944eeb4..71f01834788 100644 --- a/tests/e2e/e2e_config.py +++ b/tests/e2e/e2e_config.py @@ -34,7 +34,7 @@ CONTROL_PLANE_BASE_URL = os.environ.get( def parse_replica_urls(raw: str, fallback: str) -> tuple[str, ...]: - urls: Final = tuple(url.strip().rstrip("/") for url in raw.split(",") if url.strip()) + urls: Final = tuple(dict.fromkeys(url.strip().rstrip("/") for url in raw.split(",") if url.strip())) return urls or (fallback,) diff --git a/tests/e2e/router/reliability_support.py b/tests/e2e/router/reliability_support.py index 3d5b76f6408..4388e7f11bc 100644 --- a/tests/e2e/router/reliability_support.py +++ b/tests/e2e/router/reliability_support.py @@ -22,6 +22,7 @@ from pydantic import ValidationError from proxy_client import ProxyClient from e2e_config import CHEAP_OPENAI_MODEL, PROXY_BASE_URL, unique_marker from e2e_http import NetworkError, StreamHead, StreamingResponse +from transport import Transport from models import ( CacheControl, ChatMessage, @@ -274,9 +275,36 @@ def chat_turns_override( ) -> StreamingResponse: """POST /chat/completions with an optional per-request router_settings_override, returning the raw outcome so tests read status, body, and reliability headers.""" - return proxy.transport.send( + return chat_turns_override_via( + proxy.transport, key, model, turns, override=override, stream=stream, cache=cache, max_tokens=max_tokens + ) + + +def chat_override_via( + transport: Transport, + key: str, + model: str, + content: str, + override: RouterSettingsOverride | None = None, +) -> StreamingResponse: + """`chat_override` aimed at one replica's transport (from `proxy.replicas`) instead of + the client's default, for cells that must know which gateway took the call.""" + return chat_turns_override_via(transport, key, model, [ChatMessage(role="user", content=content)], override=override) + + +def chat_turns_override_via( + transport: Transport, + key: str, + model: str, + turns: Sequence[ChatMessage], + override: RouterSettingsOverride | None = None, + stream: bool = False, + cache: dict[str, bool] | None = {"no-cache": True}, + max_tokens: int = 512, +) -> StreamingResponse: + return transport.send( "/chat/completions", - headers=proxy.transport.bearer(key), + headers=transport.bearer(key), json=ReliabilityChatBody( model=model, messages=turns, diff --git a/tests/e2e/router/test_reliability_cooldowns_e2e.py b/tests/e2e/router/test_reliability_cooldowns_e2e.py index 769971e1533..ce3bce32880 100644 --- a/tests/e2e/router/test_reliability_cooldowns_e2e.py +++ b/tests/e2e/router/test_reliability_cooldowns_e2e.py @@ -6,21 +6,33 @@ way (a 500, a 429, a 401, or a timeout) holding all of the group's shuffle weigh with an `allowed_fails_policy` of zero for that error class and a short `cooldown_time`, plus a healthy backup at weight 0. The first call, retries off, surfaces the failure to the customer as-is and benches the deployment. The proxy -records the bench off the request path, and a sibling replica only sees it on -its next read of the cooldown keys from Redis, which the cooldown cache does at -most every 1s (DEFAULT_COOLDOWN_REDIS_READ_INTERVAL_SECONDS). So for +writes the bench to Redis before it answers that failure, and a sibling replica +only sees it on its next read of the cooldown keys from Redis, which the +cooldown cache does at most once per COOLDOWN_REDIS_READ_INTERVAL_SECONDS per +key (DEFAULT_COOLDOWN_REDIS_READ_INTERVAL_SECONDS, 1s). So for REPLICA_PROPAGATION_SECONDS after the trip, a window kept far wider than that -so this cell asserts the trip and the recovery rather than how fast siblings -catch up, every answer has to be either the deployment's own failure or a 200 -from the backup, which the proxy names in x-litellm-model-id, and at least one -replica has to have served from the backup by then. From then until shortly -before the cooldown can lapse, every call has to land on the backup whichever -replica takes it. Then the test polls until the weighted shuffle opens on the -failing deployment again and the same failure comes back (or, for the 429 pair, -its own 200 once the key's rpm window has reset): that is the recovery, since a -benched deployment is one the router will try again, not one it forgot. Its -deadline counts from the last failure a stale replica caused, because every -failure re-arms the cooldown. +so the trip-then-recover cells assert the trip and the recovery rather than how +fast siblings catch up, every answer has to be either the deployment's own +failure or a 200 from the backup, which the proxy names in x-litellm-model-id, +and at least one replica has to have served from the backup by then. From then +until shortly before the cooldown can lapse, every call has to land on the +backup whichever replica takes it. Then the test polls until the weighted +shuffle opens on the failing deployment again and the same failure comes back +(or, for the 429 pair, its own 200 once the key's rpm window has reset): that +is the recovery, since a benched deployment is one the router will try again, +not one it forgot. Its deadline counts from the last failure a stale replica +caused, because every failure re-arms the cooldown. + +The sibling cell is the one that asserts the speed. It addresses two gateways +from PROXY_REPLICA_URLS by name, warms the second with a healthy call so its +router has already read the failing deployment's cooldown key from Redis and +started the read interval on it, trips the deployment through the first, waits +the interval plus a margin, and then sends the second replica exactly one call, +which has to come back from the backup. One call, because a poll that reached +the failing deployment through the second replica would bench it there too and +hide whether the first replica's bench ever travelled. A stack addressed only +through its load balancer cannot pin which replica takes a call, so the cell is +skipped at collection unless LITELLM_PROXY_REPLICA_URLS names at least two. The failures are the same real ones the retry tests use: a 1ms deadline and a bogus key on the real backend, and this proxy standing in as the upstream for @@ -37,7 +49,7 @@ from dataclasses import dataclass import pytest from complexity_router_client import ComplexityRouterClient -from e2e_config import CHEAP_OPENAI_MODEL, unique_marker +from e2e_config import CHEAP_OPENAI_MODEL, PROXY_REPLICA_URLS, unique_marker from e2e_http import StreamingResponse from lifecycle import ResourceManager from models import KeyGenerateBody, RouterSettingsOverride @@ -45,6 +57,7 @@ from reliability_support import ( COOLDOWN_SECONDS, REPLICA_PROPAGATION_SECONDS, chat_override, + chat_override_via, create_always_5xx_deployment, create_always_rate_limited_deployment, create_always_timing_out_deployment, @@ -54,12 +67,15 @@ from reliability_support import ( model_id_of, spend_only_request_of, ) +from transport import Transport pytestmark = pytest.mark.e2e RECOVERY_GRACE_SECONDS = 10 PROPAGATION_POLL_SECONDS = 0.25 BENCH_MARGIN_SECONDS = 4.0 +COOLDOWN_REDIS_READ_INTERVAL_SECONDS = 1.0 +SIBLING_READ_MARGIN_SECONDS = 1.0 def _call_without_retries(client: ComplexityRouterClient, key: str, group: str) -> StreamingResponse: @@ -68,6 +84,31 @@ def _call_without_retries(client: ComplexityRouterClient, key: str, group: str) ) +def _call_replica_without_retries(transport: Transport, key: str, group: str) -> StreamingResponse: + return chat_override_via( + transport, key, group, f"say hi {unique_marker()}", override=RouterSettingsOverride(num_retries=0) + ) + + +@dataclass(frozen=True, slots=True) +class _Replica: + url: str + transport: Transport + + +def _two_replicas(client: ComplexityRouterClient) -> tuple[_Replica, _Replica]: + first, second, *_ = (_Replica(url, transport) for url, transport in client.proxy.replicas.items()) + return first, second + + +def _warm_cooldown_reads(replica: _Replica, key: str) -> None: + warmed = chat_override_via(replica.transport, key, CHEAP_OPENAI_MODEL, f"say hi {unique_marker()}") + assert warmed.status_code == 200, ( + f"{replica.url} should have answered a healthy {CHEAP_OPENAI_MODEL} call before the trip, got " + f"{warmed.status_code}: {warmed.body[:300]}" + ) + + def _assert_served_by_backup(resp: StreamingResponse, backup: str, when: str) -> None: assert resp.status_code == 200, ( f"{when} the group should have served from the backup, got {resp.status_code}: {resp.body[:300]}" @@ -176,6 +217,47 @@ class TestReliabilityCooldowns: _assert_trips_then_recovers(client, scoped_key, group, failing, backup, failure_status=500) + @pytest.mark.covers("reliability.cooldown.sibling_replica.serves_backup_within_read_interval") + @pytest.mark.skipif( + len(PROXY_REPLICA_URLS) < 2, + reason=( + "this cell trips a deployment through one gateway and reads the bench from another, so " + f"LITELLM_PROXY_REPLICA_URLS has to name at least two distinct gateways, got {PROXY_REPLICA_URLS}" + ), + ) + def test_sibling_replica_serves_backup_within_redis_read_interval( + self, client: ComplexityRouterClient, resources: ResourceManager, scoped_key: str + ) -> None: + tripping, sibling = _two_replicas(client) + + upstream = f"reliability-cooldown-sibling-upstream-{unique_marker()}" + upstream_id = create_bad_base_deployment(client.proxy, upstream) + resources.defer(lambda: client.proxy.delete_model(upstream_id)) + + group = f"reliability-cooldown-sibling-{unique_marker()}" + failing = create_always_5xx_deployment( + client.proxy, group, upstream, scoped_key, cooldown_time=COOLDOWN_SECONDS + ) + resources.defer(lambda: client.proxy.delete_model(failing)) + backup = create_zero_weight_backup_deployment(client.proxy, group) + resources.defer(lambda: client.proxy.delete_model(backup)) + + _warm_cooldown_reads(sibling, scoped_key) + + tripped = _call_replica_without_retries(tripping.transport, scoped_key, group) + assert tripped.status_code == 500, ( + f"the first call through {tripping.url} should have surfaced the deployment's own 500, got " + f"{tripped.status_code}: {tripped.body[:300]}" + ) + tripped_at = time.monotonic() + + time.sleep(COOLDOWN_REDIS_READ_INTERVAL_SECONDS + SIBLING_READ_MARGIN_SECONDS) + _assert_served_by_backup( + _call_replica_without_retries(sibling.transport, scoped_key, group), + backup, + f"{time.monotonic() - tripped_at:.1f}s after {tripping.url} benched {failing}, on {sibling.url}", + ) + @pytest.mark.covers("reliability.cooldown.429.trips_then_recovers") def test_429_trips_cooldown_then_recovers( self, client: ComplexityRouterClient, resources: ResourceManager, scoped_key: str diff --git a/tests/e2e/test_proxy_client.py b/tests/e2e/test_proxy_client.py index 0c4aed5bd65..a8f07ed6dd7 100644 --- a/tests/e2e/test_proxy_client.py +++ b/tests/e2e/test_proxy_client.py @@ -338,6 +338,10 @@ class TestParseReplicaUrls: def test_falls_back_to_the_data_plane_address_when_unset(self) -> None: assert parse_replica_urls("", "http://lb") == ("http://lb",) + def test_collapses_repeated_gateway_addresses_to_one_replica(self) -> None: + raw: Final = "http://127.0.0.1:4010,http://127.0.0.1:4010/,http://127.0.0.1:4011,http://127.0.0.1:4010" + assert parse_replica_urls(raw, "http://lb") == ("http://127.0.0.1:4010", "http://127.0.0.1:4011") + def _answers(answers: Iterable[str]) -> ReplicaRead[str]: it: Final = iter(answers) From cb2f22533c1f778322b09578269238028f2c3862 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 12:43:30 -0700 Subject: [PATCH 010/101] feat(proxy): opt-in include_guardrail_response returns guardrail_information in the response (#42327) * feat(proxy): opt-in include_guardrail_response returns guardrail_information in the response Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): read include_guardrail_response from the request metadata bucket the router did not reseed Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * style(proxy): format common request processing Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): redact matched content in guardrail_information and stop mutating cached responses Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): traverse guardrail diagnostics iteratively Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): annotate guardrail traversal cast Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(proxy): reuse core redaction helper for guardrail_information Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * chore(proxy): justify response rebind when attaching guardrail information Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: yucheng Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- litellm/litellm_core_utils/core_helpers.py | 14 +- litellm/proxy/common_request_processing.py | 44 +++++- litellm/proxy/litellm_pre_call_utils.py | 8 ++ tests/e2e/coverage_registry/guardrail.yaml | 1 + tests/e2e/guardrails/guardrails_client.py | 2 + ...test_guardrail_information_response_e2e.py | 118 ++++++++++++++++ tests/e2e/models.py | 10 ++ .../litellm_core_utils/test_core_helpers.py | 22 +++ .../proxy/test_common_request_processing.py | 128 ++++++++++++++++++ .../proxy/test_litellm_pre_call_utils.py | 40 ++++++ 10 files changed, 379 insertions(+), 8 deletions(-) create mode 100644 tests/e2e/guardrails/test_guardrail_information_response_e2e.py diff --git a/litellm/litellm_core_utils/core_helpers.py b/litellm/litellm_core_utils/core_helpers.py index 5bcde688521..d7fbe9f7e09 100644 --- a/litellm/litellm_core_utils/core_helpers.py +++ b/litellm/litellm_core_utils/core_helpers.py @@ -3,7 +3,7 @@ import copy import logging import re -from collections.abc import Iterable, Mapping +from collections.abc import Collection, Iterable, Mapping from types import MappingProxyType from typing import TYPE_CHECKING, Any, Final, Literal, Protocol @@ -709,10 +709,11 @@ def filter_internal_params(data: dict, additional_internal_params: set | None = def redact_nested_match_and_regex_keys( payload: dict | list[Any] | str | None, + keys: Collection[str] = ("match", "regex"), ) -> dict | list[Any] | str | None: """ - Deep-copy `payload` and replace every `match` / `regex` string field with - "[REDACTED]" anywhere in nested dict/list structures. + Deep-copy `payload` and replace every configured string field with "[REDACTED]" + anywhere in nested dict/list structures. Used for guardrail spend/compliance logging so raw spans are not persisted. """ @@ -734,10 +735,9 @@ def redact_nested_match_and_regex_keys( continue seen.add(node_id) if isinstance(node, dict): - if "match" in node: - node["match"] = "[REDACTED]" - if "regex" in node: - node["regex"] = "[REDACTED]" + for key in keys: + if key in node: + node[key] = "[REDACTED]" stack.extend(node.values()) elif isinstance(node, list): stack.extend(node) diff --git a/litellm/proxy/common_request_processing.py b/litellm/proxy/common_request_processing.py index 6a7b6970bb8..c40090233be 100644 --- a/litellm/proxy/common_request_processing.py +++ b/litellm/proxy/common_request_processing.py @@ -26,7 +26,7 @@ import httpx import orjson from fastapi import HTTPException, Request, status from fastapi.responses import JSONResponse, Response, StreamingResponse -from pydantic import TypeAdapter, ValidationError +from pydantic import BaseModel, TypeAdapter, ValidationError from starlette.types import Receive, Scope, Send import litellm @@ -56,6 +56,7 @@ from litellm.litellm_core_utils.core_helpers import ( get_or_create_metadata_bucket, independent_snapshot, is_expected_client_error, + redact_nested_match_and_regex_keys, ) from litellm.litellm_core_utils.dd_tracing import NullTracer, tracer from litellm.litellm_core_utils.get_supported_openai_params import ( @@ -1401,6 +1402,42 @@ def _override_openai_response_model( ) +_METADATA_BUCKET_KEYS: Final = ("metadata", "litellm_metadata") +_RESPONSE_REDACTED_KEYS: Final = ("keyword", "snippet", "match", "regex") + + +def _request_metadata_buckets(request_data: Mapping[str, object]) -> tuple[Mapping[str, object], ...]: + return tuple(bucket for key in _METADATA_BUCKET_KEYS if isinstance(bucket := request_data.get(key), Mapping)) + + +def include_guardrail_response_requested(request_data: Mapping[str, object]) -> bool: + return any(bucket.get("include_guardrail_response") is True for bucket in _request_metadata_buckets(request_data)) + + +def attach_guardrail_information(response: object, request_data: Mapping[str, object]) -> object: + recorded: Final[Sequence[object]] = next( + ( + entries + for bucket in _request_metadata_buckets(request_data) + if isinstance( + entries := bucket.get("standard_logging_guardrail_information"), + list, + ) + ), + (), + ) + guardrail_information: Final = [ # mutable-ok: response list contract + redact_nested_match_and_regex_keys(entry, keys=_RESPONSE_REDACTED_KEYS) + for entry in recorded + if isinstance(entry, dict) + ] + if isinstance(response, dict): + return response | MappingProxyType({"guardrail_information": guardrail_information}) + if isinstance(response, BaseModel) and response.model_config.get("extra") == "allow": + return response.model_copy(update=MappingProxyType({"guardrail_information": guardrail_information})) + return response + + class CostBreakdownHeaderValues(NamedTuple): original_cost: float | None = None discount_amount: float | None = None @@ -2898,6 +2935,11 @@ class ProxyBaseLLMRequestProcessing: if isinstance(response, dict): response.pop("_hidden_params", None) + if include_guardrail_response_requested(self.data): + response = attach_guardrail_information( # rebind-ok: response tail rebinds the copied response + response=response, request_data=self.data + ) + # Call response headers hook for non-streaming success callback_headers = await proxy_logging_obj.post_call_response_headers_hook( data=self.data, diff --git a/litellm/proxy/litellm_pre_call_utils.py b/litellm/proxy/litellm_pre_call_utils.py index 44d45dcd687..4d5b91be034 100644 --- a/litellm/proxy/litellm_pre_call_utils.py +++ b/litellm/proxy/litellm_pre_call_utils.py @@ -3116,7 +3116,15 @@ async def move_guardrails_to_metadata( - If guardrails not set on API key, then checks request metadata - Adds guardrails from policies attached to key/team metadata - Adds guardrails from policy engine based on team/key/model context + - Moves include_guardrail_response into request metadata before provider dispatch """ + if "include_guardrail_response" in data: + data[_metadata_variable_name][ + "include_guardrail_response" + ] = ( # rebind-ok: pre-call hooks mutate the shared request dict in place + data.pop("include_guardrail_response") is True + ) + # Early-out: skip all guardrails processing when nothing is configured key_metadata: Final = user_api_key_dict.metadata team_metadata: Final = user_api_key_dict.team_metadata diff --git a/tests/e2e/coverage_registry/guardrail.yaml b/tests/e2e/coverage_registry/guardrail.yaml index 02b5a921add..f49568c883b 100644 --- a/tests/e2e/coverage_registry/guardrail.yaml +++ b/tests/e2e/coverage_registry/guardrail.yaml @@ -10,6 +10,7 @@ - {id: guardrail.litellm_content_filter.pre_call.blocks, module: guardrail, tier: P0, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "test_team_disable_global_guardrail_e2e.py", rationale: "Local content-filter default-on blocks banned keyword pre-call"} - {id: guardrail.litellm_content_filter.pre_call.blocks_video, module: guardrail, tier: P0, hook_point: pre_call, assertions: [blocks], exercised_on: [videos], source: "test_key_guardrail_video_e2e.py", fail_before_fix: proven, rationale: "A content-filter guardrail attached to a key (metadata.guardrails) blocks a banned prompt on POST /v1/videos before the provider is called; before the fix the route's call type was unknown to the unified guardrail hook and the prompt went to the provider unscanned (LIT-6685)"} - {id: guardrail.litellm_content_filter.pre_call.allows, module: guardrail, tier: P0, hook_point: pre_call, assertions: [allows], exercised_on: [chat_completions], source: "test_team_disable_global_guardrail_e2e.py", rationale: "Team disable_global_guardrails bypasses default-on content filter"} +- {id: guardrail.litellm_content_filter.pre_call.returns_guardrail_information, module: guardrail, tier: P0, hook_point: pre_call, assertions: [allows], exercised_on: [chat_completions], source: "guardrails/test_guardrail_information_response_e2e.py", rationale: "Opt-in chat responses expose successful guardrail execution details"} - {id: guardrail.litellm_content_filter.apply_endpoint.blocks, module: guardrail, tier: P0, hook_point: apply_endpoint, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_endpoints.py:apply_guardrail", rationale: "POST /guardrails/apply_guardrail blocks banned content for customers that call the apply surface directly"} - {id: guardrail.litellm_content_filter.apply_endpoint.allows, module: guardrail, tier: P0, hook_point: apply_endpoint, assertions: [allows], exercised_on: [chat_completions], source: "guardrail_endpoints.py:apply_guardrail", rationale: "POST /guardrails/apply_guardrail returns clean text for allowed input"} - {id: guardrail.bedrock.during.blocks, module: guardrail, tier: P0, hook_point: during, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/bedrock_guardrails.py", rationale: "During-call moderation for streaming"} diff --git a/tests/e2e/guardrails/guardrails_client.py b/tests/e2e/guardrails/guardrails_client.py index 007e9392616..60f875ccb7d 100644 --- a/tests/e2e/guardrails/guardrails_client.py +++ b/tests/e2e/guardrails/guardrails_client.py @@ -291,6 +291,7 @@ class GuardrailsClient: text: str, *, guardrails: list[str] | None = None, + include_guardrail_response: bool | None = None, max_tokens: int = 16, tools: list[ChatTool] | None = None, ) -> Result[ChatResponse]: @@ -306,6 +307,7 @@ class GuardrailsClient: messages=[ChatMessage(role="user", content=text)], max_tokens=max_tokens, guardrails=guardrails, + include_guardrail_response=include_guardrail_response, tools=tools, ), ) diff --git a/tests/e2e/guardrails/test_guardrail_information_response_e2e.py b/tests/e2e/guardrails/test_guardrail_information_response_e2e.py new file mode 100644 index 00000000000..9701ea35819 --- /dev/null +++ b/tests/e2e/guardrails/test_guardrail_information_response_e2e.py @@ -0,0 +1,118 @@ +"""Live e2e: an opted-in chat response includes the guardrail execution details.""" + +from __future__ import annotations + +import time +from typing import Final + +import pytest + +from e2e_config import unique_marker +from e2e_http import unwrap +from guardrails_client import ( + BlockedWordBody, + ContentFilterParamsBody, + GuardrailsClient, +) +from lifecycle import ResourceManager +from models import ChatResponse, GuardrailInformationEntry + +pytestmark = pytest.mark.e2e + +GUARDRAIL_PROPAGATION_DEADLINE_SECONDS: Final = 40.0 +GUARDRAIL_PROPAGATION_POLL_INTERVAL_SECONDS: Final = 5.0 + + +def _register_content_filter(client: GuardrailsClient, resources: ResourceManager, *, name: str) -> None: + guardrail_id = client.register( + name, + ContentFilterParamsBody( + mode="pre_call", + default_on=False, + blocked_words=[BlockedWordBody(keyword=f"never-match-{unique_marker()}", action="MASK")], + ), + ) + resources.defer(lambda: client.delete_guardrail(guardrail_id)) + + +def _opted_in_entries( + client: GuardrailsClient, + key: str, + model: str, + name: str, +) -> tuple[ChatResponse, tuple[GuardrailInformationEntry, ...]]: + response = unwrap( + client.chat( + key, + model, + "Reply with the single word OK.", + guardrails=[name], + include_guardrail_response=True, + max_tokens=16, + ) + ) + entries = tuple(entry for entry in response.guardrail_information or () if entry.guardrail_name == name) + return response, entries + + +class TestGuardrailInformationResponse: + @pytest.mark.covers( + "guardrail.litellm_content_filter.pre_call.returns_guardrail_information", + exercised_on=["chat_completions"], + ) + def test_flag_returns_guardrail_information_for_the_guardrail_that_ran( + self, client: GuardrailsClient, resources: ResourceManager, scoped_key: str + ) -> None: + name = f"e2e-guardrail-information-{unique_marker()}" + _register_content_filter(client, resources, name=name) + model = client.create_backend_model( + resources, + prefix="e2e-guardrail-info-backend", + backend="openai/gpt-4.1-mini", + api_key="os.environ/OPENAI_API_KEY", + ) + deadline = time.monotonic() + GUARDRAIL_PROPAGATION_DEADLINE_SECONDS + + while True: + response, entries = _opted_in_entries(client, scoped_key, model, name) + if len(entries) == 1: + entry = entries[0] + assert entry.guardrail_status == "success", ( + f"guardrail information should report a successful run, got {entry!r}; response: {response}" + ) + assert entry.duration is not None and entry.duration >= 0, ( + f"guardrail information should report a non-negative duration; response: {response}" + ) + return + if time.monotonic() >= deadline: + pytest.fail( + f"guardrail information did not report exactly one successful {name!r} entry within " + f"{GUARDRAIL_PROPAGATION_DEADLINE_SECONDS}s; response: {response}" + ) + time.sleep(GUARDRAIL_PROPAGATION_POLL_INTERVAL_SECONDS) + + def test_without_flag_response_has_no_guardrail_information( + self, client: GuardrailsClient, resources: ResourceManager, scoped_key: str + ) -> None: + name = f"e2e-guardrail-information-default-{unique_marker()}" + _register_content_filter(client, resources, name=name) + model = client.create_backend_model( + resources, + prefix="e2e-guardrail-info-backend", + backend="openai/gpt-4.1-mini", + api_key="os.environ/OPENAI_API_KEY", + ) + + response = unwrap( + client.chat( + scoped_key, + model, + "Reply with the single word OK.", + guardrails=[name], + max_tokens=16, + ) + ) + + assert "guardrail_information" not in response.model_fields_set, ( + f"guardrail information must remain absent without include_guardrail_response, got {response}" + ) diff --git a/tests/e2e/models.py b/tests/e2e/models.py index 3309479edaf..74cad3ad8df 100644 --- a/tests/e2e/models.py +++ b/tests/e2e/models.py @@ -334,6 +334,7 @@ class ChatBody(BaseModel): tools: Sequence[ChatTool | McpChatTool] | None = None tool_choice: str | None = None guardrails: list[str] | None = None + include_guardrail_response: bool | None = None response_format: dict[str, object] | None = None chat_template_kwargs: dict[str, bool] | None = None cache: dict[str, bool] | None = {"no-cache": True} @@ -448,6 +449,14 @@ class Usage(BaseModel): completion_tokens_details: CompletionTokensDetails | None = None +class GuardrailInformationEntry(BaseModel): + guardrail_name: str + guardrail_status: str + guardrail_mode: object | None = None + guardrail_response: object | None = None + duration: float | None = None + + class ChatResponse(BaseModel): id: str | None = None object: str | None = None @@ -455,6 +464,7 @@ class ChatResponse(BaseModel): choices: list[ChatChoice] = [] usage: Usage | None = None service_tier: str | None = None + guardrail_information: list[GuardrailInformationEntry] | None = None # ---------- anthropic /v1/messages + count_tokens ---------- diff --git a/tests/test_litellm/litellm_core_utils/test_core_helpers.py b/tests/test_litellm/litellm_core_utils/test_core_helpers.py index bca61a0e76f..6eeea271127 100644 --- a/tests/test_litellm/litellm_core_utils/test_core_helpers.py +++ b/tests/test_litellm/litellm_core_utils/test_core_helpers.py @@ -322,6 +322,28 @@ class TestRedactNestedMatchAndRegexKeys: assert redact_nested_match_and_regex_keys(None) is None assert redact_nested_match_and_regex_keys("plain") == "plain" + def test_redacts_custom_keys_without_changing_default_keys(self): + payload = { + "keyword": "secret-keyword", + "snippet": "secret-snippet", + "match": "secret-match", + "regex": "secret-regex", + "nested": [{"keyword": "nested-keyword", "match": "nested-match"}], + } + + custom_keys = redact_nested_match_and_regex_keys(payload, keys=("keyword", "snippet")) + default_keys = redact_nested_match_and_regex_keys(payload) + + assert custom_keys["keyword"] == "[REDACTED]" + assert custom_keys["snippet"] == "[REDACTED]" + assert custom_keys["nested"][0]["keyword"] == "[REDACTED]" + assert custom_keys["match"] == "secret-match" + assert custom_keys["regex"] == "secret-regex" + assert default_keys["match"] == "[REDACTED]" + assert default_keys["regex"] == "[REDACTED]" + assert default_keys["keyword"] == "secret-keyword" + assert default_keys["snippet"] == "secret-snippet" + @pytest.mark.parametrize( "value, expected", diff --git a/tests/test_litellm/proxy/test_common_request_processing.py b/tests/test_litellm/proxy/test_common_request_processing.py index 360122cde25..5b9cd761dda 100644 --- a/tests/test_litellm/proxy/test_common_request_processing.py +++ b/tests/test_litellm/proxy/test_common_request_processing.py @@ -35,10 +35,12 @@ from litellm.proxy.common_request_processing import ( _buffer_first_chunk_honoring_disconnect, _cancel_llm_call_on_client_disconnect, _ClientDisconnectedBeforeFirstChunk, + attach_guardrail_information, _extract_error_from_sse_chunk, _get_cost_breakdown_from_logging_obj, CostBreakdownHeaderValues, _has_attribute_error_in_chain, + include_guardrail_response_requested, _is_azure_model_router_request, open_sse_before_first_byte, resolve_litellm_call_id, @@ -61,6 +63,132 @@ from litellm.proxy.utils import ProxyLogging from litellm.router import Router +def test_attach_guardrail_information_copies_recorded_entries_onto_model_response(): + recorded = [ + {"guardrail_name": "first", "guardrail_status": "success"}, + {"guardrail_name": "second", "guardrail_status": "success"}, + ] + response = litellm.ModelResponse() + + result = attach_guardrail_information( + response=response, + request_data={"metadata": {"standard_logging_guardrail_information": recorded}}, + ) + + assert isinstance(result, litellm.ModelResponse) + assert result.model_dump()["guardrail_information"] == recorded + assert "guardrail_information" not in response.model_dump() + + +def test_attach_guardrail_information_reports_empty_list_when_nothing_ran(): + response = litellm.ModelResponse() + + result = attach_guardrail_information(response=response, request_data={}) + + assert isinstance(result, litellm.ModelResponse) + assert result.model_dump()["guardrail_information"] == [] + assert "guardrail_information" not in response.model_dump() + + +def test_attach_guardrail_information_sets_key_on_dict_response(): + recorded = [{"guardrail_name": "first", "guardrail_status": "success"}] + response = {"id": "x"} + + result = attach_guardrail_information( + response=response, + request_data={"metadata": {"standard_logging_guardrail_information": recorded}}, + ) + + assert isinstance(result, dict) + assert result == {"id": "x", "guardrail_information": recorded} + assert response == {"id": "x"} + + +def test_attach_guardrail_information_redacts_matched_content(): + recorded = [ + { + "guardrail_name": "cf", + "guardrail_status": "success", + "guardrail_response": [ + {"type": "blocked_word", "keyword": "secret-word", "action": "MASK"} + ], + "match_details": [{"snippet": "secret-word", "detection_method": "keyword"}], + } + ] + + result = attach_guardrail_information( + response={"id": "x"}, + request_data={"metadata": {"standard_logging_guardrail_information": recorded}}, + ) + + assert isinstance(result, dict) + guardrail_information = result["guardrail_information"] + assert isinstance(guardrail_information, list) + assert guardrail_information[0]["guardrail_response"][0]["keyword"] == "[REDACTED]" + assert guardrail_information[0]["match_details"][0]["snippet"] == "[REDACTED]" + assert guardrail_information[0]["match_details"][0]["detection_method"] == "keyword" + assert "secret-word" not in json.dumps(result) + + +def test_attach_guardrail_information_leaves_cached_dict_response_untouched(): + recorded = [{"guardrail_name": "cf", "guardrail_status": "success"}] + cached = {"id": "x", "content": []} + + result = attach_guardrail_information( + response=cached, + request_data={ + "metadata": { + "include_guardrail_response": True, + "standard_logging_guardrail_information": recorded, + } + }, + ) + + assert "guardrail_information" not in cached + assert result is not cached + assert isinstance(result, dict) + assert result["guardrail_information"] == recorded + + original = litellm.ModelResponse() + copied = attach_guardrail_information( + response=original, + request_data={"metadata": {"standard_logging_guardrail_information": recorded}}, + ) + + assert "guardrail_information" not in original.model_dump() + assert isinstance(copied, litellm.ModelResponse) + assert copied.model_dump()["guardrail_information"] == recorded + + +def test_include_guardrail_response_requested_reads_flag_from_metadata_when_router_seeded_litellm_metadata(): + recorded = [ + {"guardrail_name": "first", "guardrail_status": "success"}, + {"guardrail_name": "second", "guardrail_status": "success"}, + ] + request_data = { + "metadata": { + "include_guardrail_response": True, + "standard_logging_guardrail_information": recorded, + }, + "litellm_metadata": {}, + } + + assert include_guardrail_response_requested(request_data) is True + + response = litellm.ModelResponse() + result = attach_guardrail_information(response=response, request_data=request_data) + + assert isinstance(result, litellm.ModelResponse) + assert result.model_dump()["guardrail_information"] == recorded + + +def test_include_guardrail_response_requested_is_false_without_exact_true(): + assert include_guardrail_response_requested( + {"metadata": {"include_guardrail_response": "true"}, "litellm_metadata": {}} + ) is False + assert include_guardrail_response_requested({}) is False + + class TestProxyBaseLLMRequestProcessing: @pytest.mark.asyncio async def test_base_passthrough_process_llm_request_preserves_litellm_headers_for_non_streaming_response( diff --git a/tests/test_litellm/proxy/test_litellm_pre_call_utils.py b/tests/test_litellm/proxy/test_litellm_pre_call_utils.py index 9257a2dd23d..b7b7b5d1942 100644 --- a/tests/test_litellm/proxy/test_litellm_pre_call_utils.py +++ b/tests/test_litellm/proxy/test_litellm_pre_call_utils.py @@ -34,6 +34,7 @@ from litellm.proxy.litellm_pre_call_utils import ( add_provider_specific_headers_to_request, check_if_token_is_service_account, clean_headers, + move_guardrails_to_metadata, ) from litellm.litellm_core_utils.core_helpers import get_litellm_metadata_from_kwargs from litellm.litellm_core_utils.internal_call_metadata import MODEL_ACCESS_GROUP_METADATA_KEY @@ -5187,6 +5188,45 @@ def test_clean_headers_strips_x_api_key_when_byok_enabled_but_x_api_key_was_auth # --------------------------------------------------------------------------- +@pytest.mark.asyncio +async def test_move_guardrails_to_metadata_moves_include_guardrail_response_before_the_no_guardrail_early_out(): + policy_registry = MagicMock() + policy_registry.is_initialized.return_value = False + user_api_key_dict = UserAPIKeyAuth(api_key="test-key") + + true_data = { + "model": "gpt-4.1-mini", + "messages": [{"role": "user", "content": "Hello"}], + "metadata": {}, + "include_guardrail_response": True, + } + with patch("litellm.proxy.policy_engine.policy_registry.get_policy_registry", return_value=policy_registry): + await move_guardrails_to_metadata( + data=true_data, + _metadata_variable_name="metadata", + user_api_key_dict=user_api_key_dict, + ) + + assert "include_guardrail_response" not in true_data + assert true_data["metadata"]["include_guardrail_response"] is True + + string_data = { + "model": "gpt-4.1-mini", + "messages": [{"role": "user", "content": "Hello"}], + "metadata": {}, + "include_guardrail_response": "true", + } + with patch("litellm.proxy.policy_engine.policy_registry.get_policy_registry", return_value=policy_registry): + await move_guardrails_to_metadata( + data=string_data, + _metadata_variable_name="metadata", + user_api_key_dict=user_api_key_dict, + ) + + assert "include_guardrail_response" not in string_data + assert string_data["metadata"]["include_guardrail_response"] is False + + @pytest.mark.asyncio async def test_team_guardrail_merges_with_global_policy(): """ From 1373322e0c9c6c0ecb4d25ac88aae7b758ac712a Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 12:44:03 -0700 Subject: [PATCH 011/101] feat(logs): add span type filter to request logs (#42491) * feat(logs): add span type filter to request logs Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(logs): look up span type sql conditions from a mapping Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: Mubashir Osmani Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- .../spend_management_endpoints.py | 33 +++++++ .../test_spend_management_endpoints.py | 98 +++++++++++++++++++ .../src/components/networking.tsx | 1 + .../view_logs/RequestLogsFilters.test.tsx | 33 +++++++ .../view_logs/RequestLogsFilters.tsx | 29 ++++++ .../components/view_logs/RequestLogsTable.tsx | 11 ++- .../src/components/view_logs/constants.ts | 7 ++ .../view_logs/log_filter_logic.test.tsx | 2 + .../components/view_logs/log_filter_logic.tsx | 3 + ui/litellm-dashboard/src/lib/http/schema.d.ts | 4 + 10 files changed, 220 insertions(+), 1 deletion(-) diff --git a/litellm/proxy/spend_tracking/spend_management_endpoints.py b/litellm/proxy/spend_tracking/spend_management_endpoints.py index a319535f725..b5980f9b224 100644 --- a/litellm/proxy/spend_tracking/spend_management_endpoints.py +++ b/litellm/proxy/spend_tracking/spend_management_endpoints.py @@ -69,6 +69,18 @@ _SESSION_KEY_EXPR: Final = "COALESCE(NULLIF(session_id, ''), request_id)" _SESSION_GROUP_KEY_SQL: Final = f"{_SESSION_KEY_EXPR}, api_key" _MCP_CALL_TYPES_SQL: Final = "('call_mcp_tool', 'list_mcp_tools')" _AGENT_CALL_TYPE_SQL: Final = "'asend_message'" +_BATCH_CALL_TYPES_SQL: Final = "('acreate_batch', 'create_batch', 'aretrieve_batch', 'retrieve_batch')" +_SPAN_TYPE_SQL_CONDITIONS: Final[Mapping[str, str]] = MappingProxyType( + { + "mcp": f"call_type IN {_MCP_CALL_TYPES_SQL}", + "agent": f"call_type = {_AGENT_CALL_TYPE_SQL}", + "batch": f"call_type IN {_BATCH_CALL_TYPES_SQL}", + "llm": ( + f"(call_type NOT IN {_MCP_CALL_TYPES_SQL} AND call_type != {_AGENT_CALL_TYPE_SQL} " + f"AND call_type NOT IN {_BATCH_CALL_TYPES_SQL})" + ), + } +) _SPEND_LOG_LIST_COLUMNS: Final = """ request_id, call_type, api_key, spend, total_tokens, prompt_tokens, completion_tokens, "startTime", "endTime", @@ -2410,6 +2422,10 @@ async def ui_view_spend_logs( default=None, description="Filter logs by cache state: 'hit' or 'miss'. Miss includes legacy rows with a null/unknown cache state", ), + span_type: str | None = fastapi.Query( + default=None, + description="Filter logs by span type: llm, agent, mcp, or batch", + ), model: str | None = fastapi.Query(default=None, description="Filter logs by model"), model_id: str | None = fastapi.Query( default=None, @@ -2512,6 +2528,13 @@ async def ui_view_spend_logs( param="cache_hit_filter", code=status.HTTP_400_BAD_REQUEST, ) + if isinstance(span_type, str) and span_type not in _SPAN_TYPE_SQL_CONDITIONS: + raise ProxyException( + message=f"Invalid span_type: {span_type}. Must be one of: llm, agent, mcp, batch", + type="bad_request", + param="span_type", + code=status.HTTP_400_BAD_REQUEST, + ) try: is_admin_view: Final = _is_admin_view_safe(user_api_key_dict=user_api_key_dict) @@ -2776,6 +2799,10 @@ async def ui_view_spend_logs( elif cache_hit_filter == "miss": sql_conditions.append("(cache_hit IS NULL OR LOWER(cache_hit) != 'true')") + span_type_condition: Final = _span_type_sql_condition(span_type) + if span_type_condition is not None: + sql_conditions.append(span_type_condition) + if exclude_internal_health_checks: sql_conditions.append(f"api_key NOT IN (${p}, ${p + 1})") sql_params.extend(_INTERNAL_HEALTH_CHECK_API_KEYS) @@ -4673,6 +4700,12 @@ def _build_status_filter_condition(status_filter: str | None) -> Mapping[str, ob return {"status": {"equals": status_filter}} +def _span_type_sql_condition(span_type: str | None) -> str | None: + if span_type is None: + return None + return _SPAN_TYPE_SQL_CONDITIONS.get(span_type) + + def _is_admin_view_safe(user_api_key_dict: UserAPIKeyAuth) -> bool: """ Safely determine if the current user has admin view permissions. diff --git a/tests/test_litellm/proxy/spend_tracking/test_spend_management_endpoints.py b/tests/test_litellm/proxy/spend_tracking/test_spend_management_endpoints.py index 9de6679472e..16cbd109b24 100644 --- a/tests/test_litellm/proxy/spend_tracking/test_spend_management_endpoints.py +++ b/tests/test_litellm/proxy/spend_tracking/test_spend_management_endpoints.py @@ -139,6 +139,15 @@ def _reconstruct_ui_where_from_sql(sql_query, params): where["cache_hit"] = "hit" elif cond == "(cache_hit IS NULL OR LOWER(cache_hit) != 'true')": where["cache_hit"] = "miss" + elif "call_type" in cond: + if "call_type NOT IN" in cond: + where["span_type"] = "llm" + elif "call_mcp_tool" in cond: + where["span_type"] = "mcp" + elif "call_type = 'asend_message'" in cond: + where["span_type"] = "agent" + elif "acreate_batch" in cond: + where["span_type"] = "batch" elif sess: where["session_id"] = {"contains": str(params[int(sess.group(1)) - 1]).strip("%")} elif status: @@ -3418,6 +3427,95 @@ async def test_ui_view_spend_logs_with_cache_hit_filter(client, monkeypatch): app.dependency_overrides.pop(ps.user_api_key_auth, None) +@pytest.mark.asyncio +async def test_ui_view_spend_logs_with_span_type_filter(client, monkeypatch): + base = { + "api_key": "sk-test-key", + "user": "test_user_1", + "team_id": "team1", + "spend": 0.05, + "startTime": datetime.datetime.now(timezone.utc).isoformat(), + "model": "gpt-4", + "status": "success", + } + mock_spend_logs = [ + {**base, "id": "log1", "request_id": "req-llm", "call_type": "acompletion"}, + {**base, "id": "log2", "request_id": "req-agent", "call_type": "asend_message"}, + {**base, "id": "log3", "request_id": "req-mcp", "call_type": "call_mcp_tool"}, + {**base, "id": "log4", "request_id": "req-batch", "call_type": "aretrieve_batch"}, + ] + + call_types_by_span = { + "llm": lambda ct: ct not in {"call_mcp_tool", "list_mcp_tools", "asend_message"} + and ct not in {"acreate_batch", "create_batch", "aretrieve_batch", "retrieve_batch"}, + "agent": lambda ct: ct == "asend_message", + "mcp": lambda ct: ct in {"call_mcp_tool", "list_mcp_tools"}, + "batch": lambda ct: ct + in {"acreate_batch", "create_batch", "aretrieve_batch", "retrieve_batch"}, + } + + def filter_by_span_type(where): + span_type = where.get("span_type") + if span_type is None: + return mock_spend_logs + return [log for log in mock_spend_logs if call_types_by_span[span_type](log["call_type"])] + + monkeypatch.setattr( + "litellm.proxy.proxy_server.prisma_client", + make_ui_spend_logs_mock_prisma(mock_spend_logs, filter_by_span_type), + ) + + start_date, end_date = _default_date_range() + + app.dependency_overrides[ps.user_api_key_auth] = lambda: UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN + ) + try: + for span_type, expected_ids in [ + ("batch", ["req-batch"]), + ("llm", ["req-llm"]), + ("mcp", ["req-mcp"]), + ("agent", ["req-agent"]), + ]: + response = client.get( + "/spend/logs/ui", + params={ + "span_type": span_type, + "start_date": start_date, + "end_date": end_date, + }, + headers={"Authorization": "Bearer sk-test"}, + ) + assert response.status_code == 200, response.text + data = response.json() + assert data["total"] == len(expected_ids) + assert [row["request_id"] for row in data["data"]] == expected_ids + + response = client.get( + "/spend/logs/ui", + params={ + "start_date": start_date, + "end_date": end_date, + }, + headers={"Authorization": "Bearer sk-test"}, + ) + assert response.status_code == 200 + assert response.json()["total"] == 4 + + response = client.get( + "/spend/logs/ui", + params={ + "span_type": "invalid", + "start_date": start_date, + "end_date": end_date, + }, + headers={"Authorization": "Bearer sk-test"}, + ) + assert response.status_code == 400 + finally: + app.dependency_overrides.pop(ps.user_api_key_auth, None) + + @pytest.mark.asyncio async def test_ui_view_spend_logs_with_model(client, monkeypatch): mock_spend_logs = [ diff --git a/ui/litellm-dashboard/src/components/networking.tsx b/ui/litellm-dashboard/src/components/networking.tsx index 82399792674..d358d23408c 100644 --- a/ui/litellm-dashboard/src/components/networking.tsx +++ b/ui/litellm-dashboard/src/components/networking.tsx @@ -2003,6 +2003,7 @@ interface UiSpendLogsParams { end_user?: string; status_filter?: string; cache_hit_filter?: string; + span_type?: string; /** Filter by model name (e.g. "gpt-4") */ model?: string; /** Filter by model ID (litellm model deployment id) */ diff --git a/ui/litellm-dashboard/src/components/view_logs/RequestLogsFilters.test.tsx b/ui/litellm-dashboard/src/components/view_logs/RequestLogsFilters.test.tsx index 8d1847e0121..a2da80a3f7b 100644 --- a/ui/litellm-dashboard/src/components/view_logs/RequestLogsFilters.test.tsx +++ b/ui/litellm-dashboard/src/components/view_logs/RequestLogsFilters.test.tsx @@ -84,6 +84,7 @@ describe("RequestLogsFilters", () => { for (const label of [ "Team ID", + "Span Type", "Status", "Cache", "Key Alias", @@ -286,6 +287,38 @@ describe("RequestLogsFilters", () => { expect(await screen.findByText(label)).toBeInTheDocument(); }); + it.each([ + ["", "All Types"], + ["llm", "LLM"], + ["agent", "Agent"], + ["mcp", "MCP"], + ["batch", "Batch"], + ])("shows the human label on the Span Type trigger for %s", async (spanType, label) => { + renderFilters(spanType === "" ? {} : { [LOG_FILTER_IDS.SPAN_TYPE]: spanType }); + + expect(await screen.findByText(label)).toBeInTheDocument(); + }); + + it("selecting Batch sets the span_type filter", async () => { + const user = userEvent.setup(); + const { set } = renderFilters(); + + await user.click(await screen.findByText("All Types")); + await user.click(await screen.findByRole("option", { name: "Batch" })); + + expect(set).toHaveBeenCalledWith(LOG_FILTER_IDS.SPAN_TYPE, "batch"); + }); + + it("selecting All Types clears the span_type filter", async () => { + const user = userEvent.setup(); + const { set } = renderFilters({ [LOG_FILTER_IDS.SPAN_TYPE]: "batch" }); + + await user.click(await screen.findByText("Batch")); + await user.click(await screen.findByRole("option", { name: "All Types" })); + + expect(set).toHaveBeenCalledWith(LOG_FILTER_IDS.SPAN_TYPE, undefined); + }); + it.each([ ["Cache Hit", "hit"], ["Cache Miss", "miss"], diff --git a/ui/litellm-dashboard/src/components/view_logs/RequestLogsFilters.tsx b/ui/litellm-dashboard/src/components/view_logs/RequestLogsFilters.tsx index e97552838da..5059f117944 100644 --- a/ui/litellm-dashboard/src/components/view_logs/RequestLogsFilters.tsx +++ b/ui/litellm-dashboard/src/components/view_logs/RequestLogsFilters.tsx @@ -37,6 +37,14 @@ const CACHE_FILTER_ITEMS = [ { value: "hit", label: "Cache Hit" }, { value: "miss", label: "Cache Miss" }, ] as const; + +const SPAN_TYPE_FILTER_ITEMS = [ + { value: ALL_VALUE, label: "All Types" }, + { value: "llm", label: "LLM" }, + { value: "agent", label: "Agent" }, + { value: "mcp", label: "MCP" }, + { value: "batch", label: "Batch" }, +] as const; const PAGE_SIZE = 50; const SEARCH_INPUT_REASONS: ReadonlySet = new Set(["input-change", "input-clear", "clear-press"]); @@ -328,6 +336,27 @@ export function RequestLogsFilters({ get, set, teams, logsWindow }: RequestLogsF teams={teams} /> + + + + } @@ -135,10 +143,22 @@ const RoutingGroupModal: React.FC = ({ control={form.control} name="models" label="Models" - description="Models from your model list that this group routes between. A model can only be in one group." + description={ + selectedStrategy === "priority" + ? "Models from your model list that this group routes between. Models can belong to multiple priority groups." + : "Models from your model list that this group routes between. A model can belong to one non-priority group." + } > {({ id, value, onChange, "aria-invalid": ariaInvalid, "aria-describedby": ariaDescribedBy }) => ( - + { + onChange(models); + form.setValue("model_priorities", prioritiesForModels(models, form.getValues("model_priorities"))); + }} + > }> {(selected: string[]) => ( @@ -176,7 +196,11 @@ const RoutingGroupModal: React.FC = ({ control={form.control} name="routing_strategy" label="Routing Strategy" - description={strategyDescriptions[selectedStrategy]} + description={ + selectedStrategy === "priority" + ? "Lower priorities are tried first. Models with the same priority share traffic. Applies only when calling this group." + : strategyDescriptions[selectedStrategy] + } > {({ id, value, onChange, "aria-invalid": ariaInvalid, "aria-describedby": ariaDescribedBy }) => ( + onChange( + value.map((item, itemIndex) => + itemIndex === index ? { ...item, priority: event.target.value } : item, + ), + ) + } + /> + {!selectedModels.includes(entry.model) && ( + + )} + + ))} + + )} + + )} + {STRATEGIES_WITH_ARGS.has(selectedStrategy) && ( = ({ )}

- Models not claimed by an explicit group fall through to the proxy's top-level routing strategy. + {selectedStrategy === "priority" + ? "Direct requests to a member model keep their existing routing behavior." + : "Models outside non-priority groups use the proxy's top-level routing strategy."}

diff --git a/ui/litellm-dashboard/src/components/routing_groups/RoutingGroupUsagePanel.tsx b/ui/litellm-dashboard/src/components/routing_groups/RoutingGroupUsagePanel.tsx index fafea569012..85dd67099d6 100644 --- a/ui/litellm-dashboard/src/components/routing_groups/RoutingGroupUsagePanel.tsx +++ b/ui/litellm-dashboard/src/components/routing_groups/RoutingGroupUsagePanel.tsx @@ -14,7 +14,8 @@ interface RoutingGroupUsagePanelProps { baseUrl: string; } -const exampleModel = (group: RoutingGroup): string => group.models[0] ?? ""; +const exampleModel = (group: RoutingGroup): string => + group.routing_strategy === "priority" ? group.group_name : group.models[0] ?? ""; const buildCurlSnippet = (group: RoutingGroup, baseUrl: string): string => `curl -X POST '${baseUrl}/v1/chat/completions' \\ @@ -69,8 +70,17 @@ export function RoutingGroupUsagePanel({ group, baseUrl }: RoutingGroupUsagePane How routing works for this group

- Callers request any model in the group by name; LiteLLM picks a deployment behind the scenes using the{" "} - {formatStrategyLabel(group.routing_strategy)} strategy. + {group.routing_strategy === "priority" ? ( + <> + Request {group.group_name} to try eligible models in + priority order. Direct requests to a member model keep their existing routing behavior. + + ) : ( + <> + Callers request any model in the group by name; LiteLLM picks a deployment behind the scenes using the{" "} + {formatStrategyLabel(group.routing_strategy)} strategy. + + )}

diff --git a/ui/litellm-dashboard/src/components/routing_groups/RoutingGroupsTable.test.tsx b/ui/litellm-dashboard/src/components/routing_groups/RoutingGroupsTable.integration.test.tsx similarity index 86% rename from ui/litellm-dashboard/src/components/routing_groups/RoutingGroupsTable.test.tsx rename to ui/litellm-dashboard/src/components/routing_groups/RoutingGroupsTable.integration.test.tsx index 6f14b76e2fd..6664ecab623 100644 --- a/ui/litellm-dashboard/src/components/routing_groups/RoutingGroupsTable.test.tsx +++ b/ui/litellm-dashboard/src/components/routing_groups/RoutingGroupsTable.integration.test.tsx @@ -113,6 +113,22 @@ describe("RoutingGroupsTable", () => { expect(panel?.textContent).toContain("gpt-4o"); }); + it("uses the callable group name in every priority routing example", async () => { + const user = userEvent.setup(); + render(); + expect(within(rowFor("prod-group")).getByText("Priority")).toBeInTheDocument(); + await user.click(screen.getByRole("button", { name: "prod-group" })); + + expect(screen.getByRole("tabpanel")).toHaveTextContent('"model": "prod-group"'); + await user.click(screen.getByRole("tab", { name: "Python (OpenAI SDK)" })); + expect(screen.getByRole("tabpanel")).toHaveTextContent('model="prod-group"'); + await user.click(screen.getByRole("tab", { name: "JavaScript (OpenAI SDK)" })); + expect(screen.getByRole("tabpanel")).toHaveTextContent('model: "prod-group"'); + expect( + screen.getByText(/Direct requests to a member model keep their existing routing behavior/), + ).toBeInTheDocument(); + }); + it("should expand only the clicked group", async () => { const user = userEvent.setup(); render(); diff --git a/ui/litellm-dashboard/src/components/routing_groups/index.tsx b/ui/litellm-dashboard/src/components/routing_groups/index.tsx index 17329d0b572..ae2d62ae20f 100644 --- a/ui/litellm-dashboard/src/components/routing_groups/index.tsx +++ b/ui/litellm-dashboard/src/components/routing_groups/index.tsx @@ -46,6 +46,7 @@ const RoutingGroups: React.FC = () => { const availableStrategies = useMemo(() => { if (data?.availableStrategies?.length) return data.availableStrategies; + if (routerFields?.routing_group_strategies?.length) return routerFields.routing_group_strategies; const fromFields = routerFields?.fields?.find((f) => f.field_name === "routing_strategy")?.options; return fromFields ?? []; }, [data?.availableStrategies, routerFields]); @@ -178,8 +179,17 @@ const RoutingGroups: React.FC = () => { Delete routing group?

- Models in {deletingGroup?.group_name} will fall back to the - proxy's top-level routing strategy. This cannot be undone. + {deletingGroup?.routing_strategy === "priority" ? ( + <> + Calls to {deletingGroup.group_name} will stop working. Direct + requests to its member models keep their existing routing behavior. This cannot be undone. + + ) : ( + <> + Models in {deletingGroup?.group_name} will fall back to the + proxy's top-level routing strategy. This cannot be undone. + + )}

{showValidationErrors && error &&

{error}

} diff --git a/ui/litellm-dashboard/src/components/add_model/build_complexity_router_config.ts b/ui/litellm-dashboard/src/components/add_model/build_complexity_router_config.ts index 9b4f1980f62..13df40464f0 100644 --- a/ui/litellm-dashboard/src/components/add_model/build_complexity_router_config.ts +++ b/ui/litellm-dashboard/src/components/add_model/build_complexity_router_config.ts @@ -414,8 +414,8 @@ export const getReminderMarkersError = (pairs: ReminderMarkerPair[] | undefined) for (const [index, pair] of (pairs ?? []).entries()) { const open = pair.open.trim().toLowerCase(); const close = pair.close.trim().toLowerCase(); - if (!open || !close) return `Reminder marker pair ${index + 1} needs both an opening and a closing delimiter`; - if (open === close) return `Reminder marker pair ${index + 1} must use different opening and closing delimiters`; + if (!open || !close) return `Tag pair ${index + 1} needs both an opening and a closing tag`; + if (open === close) return `Tag pair ${index + 1} must use different opening and closing tags`; } return null; }; diff --git a/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.integration.test.tsx b/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.integration.test.tsx index aa6cf92ceb9..6d66152cee5 100644 --- a/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.integration.test.tsx +++ b/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.integration.test.tsx @@ -377,9 +377,9 @@ describe("EditAutoRouterModal advanced field round trips", () => { expect(screen.getByRole("switch", { name: "Route housekeeping calls to the cheapest tier" })).not.toBeChecked(); expect(screen.getByRole("combobox", { name: "e.g., conversation title" })).toHaveValue(""); - await user.click(screen.getByText("Advanced: Reminder Markers")); - expect(screen.getByLabelText("Opening delimiter")).toHaveValue(""); - expect(screen.getByLabelText("Closing delimiter")).toHaveValue(""); + await user.click(screen.getByText("Advanced: Ignore Custom Tags")); + expect(screen.getByLabelText("Opening tag")).toHaveValue(""); + expect(screen.getByLabelText("Closing tag")).toHaveValue(""); await user.click(screen.getByText("Advanced: Response Format")); const maxTokensSwitch = screen.getByRole("switch", { name: "Cap max_tokens at the tier model's output ceiling" }); From 2727359a9ef5b6e058c668ba1477fd13c49df136 Mon Sep 17 00:00:00 2001 From: "berriai-litellm-provider-info-sync[bot]" <328147090+berriai-litellm-provider-info-sync[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 13:24:49 -0700 Subject: [PATCH 020/101] chore(prices): sync Baseten prices: 12 models, 9 new [enrichment failed: Baseten, 15 held] (#42558) baseten/deepseek-ai/DeepSeek-V4.1-Flash: max_tokens, supports_vision, max_input_tokens, max_output_tokens, supports_reasoning, supports_tool_choice, supports_prompt_caching, supports_response_schema, supports_function_calling, input_cost_per_token, output_cost_per_token, cache_read_input_token_cost baseten/moonshotai/Kimi-K2.6: max_tokens, supports_vision, max_input_tokens, max_output_tokens, supports_reasoning, supports_tool_choice, supports_prompt_caching, supports_response_schema, supports_function_calling, input_cost_per_token, output_cost_per_token, cache_read_input_token_cost baseten/moonshotai/Kimi-K2.7-Code: max_tokens, supports_vision, max_input_tokens, max_output_tokens, supports_reasoning, supports_tool_choice, supports_prompt_caching, supports_response_schema, supports_function_calling, input_cost_per_token, output_cost_per_token, cache_read_input_token_cost baseten/moonshotai/Kimi-K3: max_tokens, supports_vision, max_input_tokens, max_output_tokens, supports_reasoning, supports_tool_choice, supports_prompt_caching, supports_response_schema, supports_function_calling, input_cost_per_token, output_cost_per_token, cache_read_input_token_cost baseten/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B: max_tokens, supports_vision, max_input_tokens, max_output_tokens, supports_reasoning, supports_tool_choice, supports_prompt_caching, supports_response_schema, supports_function_calling, input_cost_per_token, output_cost_per_token, cache_read_input_token_cost baseten/openai/gpt-oss-120b: max_tokens, supports_vision, max_input_tokens, max_output_tokens, supports_reasoning, supports_tool_choice, supports_prompt_caching, supports_response_schema, supports_function_calling, cache_read_input_token_cost baseten/thinkingmachines/inkling: max_tokens, supports_vision, max_input_tokens, max_output_tokens, supports_reasoning, supports_tool_choice, supports_prompt_caching, supports_response_schema, supports_function_calling, input_cost_per_token, output_cost_per_token, cache_read_input_token_cost baseten/thinkingmachines/inkling-small: max_tokens, supports_vision, max_input_tokens, max_output_tokens, supports_reasoning, supports_tool_choice, supports_prompt_caching, supports_response_schema, supports_function_calling, input_cost_per_token, output_cost_per_token, cache_read_input_token_cost baseten/zai-org/GLM-4.7: max_tokens, supports_vision, max_input_tokens, max_output_tokens, supports_reasoning, supports_tool_choice, supports_prompt_caching, supports_response_schema, supports_function_calling, cache_read_input_token_cost baseten/zai-org/GLM-5.2: max_tokens, supports_vision, max_input_tokens, max_output_tokens, supports_reasoning, supports_tool_choice, supports_prompt_caching, supports_response_schema, supports_function_calling, input_cost_per_token, output_cost_per_token, cache_read_input_token_cost baseten/zai-org/GLM-5.3: supports_reasoning baseten/zai-org/GLM-5.3-Flash: max_tokens, supports_vision, max_input_tokens, max_output_tokens, supports_reasoning, supports_tool_choice, supports_prompt_caching, supports_response_schema, supports_function_calling, input_cost_per_token, output_cost_per_token, cache_read_input_token_cost Co-authored-by: berriai-litellm-provider-info-sync[bot] <328147090+berriai-litellm-provider-info-sync[bot]@users.noreply.github.com> --- ...odel_prices_and_context_window_backup.json | 182 +++++++++++++++++- model_prices_and_context_window.json | 182 +++++++++++++++++- 2 files changed, 358 insertions(+), 6 deletions(-) diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 0e80d4732c8..a2863f6b0dc 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -31722,10 +31722,21 @@ "output_cost_per_token": 3.15e-06 }, "baseten/zai-org/GLM-4.7": { + "cache_read_input_token_cost": 1.2e-07, "input_cost_per_token": 6e-07, "litellm_provider": "baseten", + "max_input_tokens": 200000, + "max_output_tokens": 200000, + "max_tokens": 200000, "mode": "chat", - "output_cost_per_token": 2.2e-06 + "output_cost_per_token": 2.2e-06, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": false, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": false }, "baseten/zai-org/GLM-4.6": { "input_cost_per_token": 6e-07, @@ -31752,10 +31763,21 @@ "output_cost_per_token": 2.5e-06 }, "baseten/openai/gpt-oss-120b": { + "cache_read_input_token_cost": 1e-07, "input_cost_per_token": 1e-07, "litellm_provider": "baseten", + "max_input_tokens": 128072, + "max_output_tokens": 128072, + "max_tokens": 128072, "mode": "chat", - "output_cost_per_token": 5e-07 + "output_cost_per_token": 5e-07, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": false }, "baseten/deepseek-ai/DeepSeek-V3.1": { "input_cost_per_token": 5e-07, @@ -68322,7 +68344,7 @@ "max_tokens": 262144, "mode": "chat", "output_cost_per_token": 4.4e-06, - "source": "https://www.baseten.co/pricing/", + "source": "https://inference.baseten.co/v1/models", "supported_modalities": [ "text", "image" @@ -68332,6 +68354,7 @@ ], "supports_function_calling": true, "supports_prompt_caching": true, + "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true @@ -77489,5 +77512,158 @@ "supports_tool_choice": true, "supports_vision": true, "supports_web_search": false + }, + "baseten/deepseek-ai/DeepSeek-V4.1-Flash": { + "cache_read_input_token_cost": 7e-09, + "input_cost_per_token": 3e-07, + "litellm_provider": "baseten", + "max_input_tokens": 1048576, + "max_output_tokens": 32768, + "max_tokens": 32768, + "mode": "chat", + "output_cost_per_token": 1.2e-06, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "baseten/moonshotai/Kimi-K2.6": { + "cache_read_input_token_cost": 1.6e-07, + "input_cost_per_token": 9.5e-07, + "litellm_provider": "baseten", + "max_input_tokens": 262000, + "max_output_tokens": 262000, + "max_tokens": 262000, + "mode": "chat", + "output_cost_per_token": 4e-06, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "baseten/moonshotai/Kimi-K2.7-Code": { + "cache_read_input_token_cost": 1.6e-07, + "input_cost_per_token": 9.5e-07, + "litellm_provider": "baseten", + "max_input_tokens": 262000, + "max_output_tokens": 262000, + "max_tokens": 262000, + "mode": "chat", + "output_cost_per_token": 4e-06, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "baseten/moonshotai/Kimi-K3": { + "cache_read_input_token_cost": 3e-07, + "input_cost_per_token": 3e-06, + "litellm_provider": "baseten", + "max_input_tokens": 1048576, + "max_output_tokens": 262144, + "max_tokens": 262144, + "mode": "chat", + "output_cost_per_token": 1.5e-05, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "baseten/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B": { + "cache_read_input_token_cost": 1.2e-07, + "input_cost_per_token": 6e-07, + "litellm_provider": "baseten", + "max_input_tokens": 202800, + "max_output_tokens": 202800, + "max_tokens": 202800, + "mode": "chat", + "output_cost_per_token": 2.4e-06, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "baseten/thinkingmachines/inkling": { + "cache_read_input_token_cost": 1.7e-07, + "input_cost_per_token": 1e-06, + "litellm_provider": "baseten", + "max_input_tokens": 1048576, + "max_output_tokens": 32768, + "max_tokens": 32768, + "mode": "chat", + "output_cost_per_token": 4.05e-06, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "baseten/thinkingmachines/inkling-small": { + "cache_read_input_token_cost": 1e-07, + "input_cost_per_token": 5e-07, + "litellm_provider": "baseten", + "max_input_tokens": 1048576, + "max_output_tokens": 32768, + "max_tokens": 32768, + "mode": "chat", + "output_cost_per_token": 1.2e-06, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "baseten/zai-org/GLM-5.2": { + "cache_read_input_token_cost": 1.4e-07, + "input_cost_per_token": 1.4e-06, + "litellm_provider": "baseten", + "max_input_tokens": 1048576, + "max_output_tokens": 262144, + "max_tokens": 262144, + "mode": "chat", + "output_cost_per_token": 4.4e-06, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "baseten/zai-org/GLM-5.3-Flash": { + "cache_read_input_token_cost": 3e-08, + "input_cost_per_token": 1.5e-07, + "litellm_provider": "baseten", + "max_input_tokens": 1048576, + "max_output_tokens": 131072, + "max_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 5e-07, + "source": "https://inference.baseten.co/v1/models", + "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.json b/model_prices_and_context_window.json index 0e80d4732c8..a2863f6b0dc 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -31722,10 +31722,21 @@ "output_cost_per_token": 3.15e-06 }, "baseten/zai-org/GLM-4.7": { + "cache_read_input_token_cost": 1.2e-07, "input_cost_per_token": 6e-07, "litellm_provider": "baseten", + "max_input_tokens": 200000, + "max_output_tokens": 200000, + "max_tokens": 200000, "mode": "chat", - "output_cost_per_token": 2.2e-06 + "output_cost_per_token": 2.2e-06, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": false, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": false }, "baseten/zai-org/GLM-4.6": { "input_cost_per_token": 6e-07, @@ -31752,10 +31763,21 @@ "output_cost_per_token": 2.5e-06 }, "baseten/openai/gpt-oss-120b": { + "cache_read_input_token_cost": 1e-07, "input_cost_per_token": 1e-07, "litellm_provider": "baseten", + "max_input_tokens": 128072, + "max_output_tokens": 128072, + "max_tokens": 128072, "mode": "chat", - "output_cost_per_token": 5e-07 + "output_cost_per_token": 5e-07, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": false }, "baseten/deepseek-ai/DeepSeek-V3.1": { "input_cost_per_token": 5e-07, @@ -68322,7 +68344,7 @@ "max_tokens": 262144, "mode": "chat", "output_cost_per_token": 4.4e-06, - "source": "https://www.baseten.co/pricing/", + "source": "https://inference.baseten.co/v1/models", "supported_modalities": [ "text", "image" @@ -68332,6 +68354,7 @@ ], "supports_function_calling": true, "supports_prompt_caching": true, + "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true @@ -77489,5 +77512,158 @@ "supports_tool_choice": true, "supports_vision": true, "supports_web_search": false + }, + "baseten/deepseek-ai/DeepSeek-V4.1-Flash": { + "cache_read_input_token_cost": 7e-09, + "input_cost_per_token": 3e-07, + "litellm_provider": "baseten", + "max_input_tokens": 1048576, + "max_output_tokens": 32768, + "max_tokens": 32768, + "mode": "chat", + "output_cost_per_token": 1.2e-06, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "baseten/moonshotai/Kimi-K2.6": { + "cache_read_input_token_cost": 1.6e-07, + "input_cost_per_token": 9.5e-07, + "litellm_provider": "baseten", + "max_input_tokens": 262000, + "max_output_tokens": 262000, + "max_tokens": 262000, + "mode": "chat", + "output_cost_per_token": 4e-06, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "baseten/moonshotai/Kimi-K2.7-Code": { + "cache_read_input_token_cost": 1.6e-07, + "input_cost_per_token": 9.5e-07, + "litellm_provider": "baseten", + "max_input_tokens": 262000, + "max_output_tokens": 262000, + "max_tokens": 262000, + "mode": "chat", + "output_cost_per_token": 4e-06, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "baseten/moonshotai/Kimi-K3": { + "cache_read_input_token_cost": 3e-07, + "input_cost_per_token": 3e-06, + "litellm_provider": "baseten", + "max_input_tokens": 1048576, + "max_output_tokens": 262144, + "max_tokens": 262144, + "mode": "chat", + "output_cost_per_token": 1.5e-05, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "baseten/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B": { + "cache_read_input_token_cost": 1.2e-07, + "input_cost_per_token": 6e-07, + "litellm_provider": "baseten", + "max_input_tokens": 202800, + "max_output_tokens": 202800, + "max_tokens": 202800, + "mode": "chat", + "output_cost_per_token": 2.4e-06, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "baseten/thinkingmachines/inkling": { + "cache_read_input_token_cost": 1.7e-07, + "input_cost_per_token": 1e-06, + "litellm_provider": "baseten", + "max_input_tokens": 1048576, + "max_output_tokens": 32768, + "max_tokens": 32768, + "mode": "chat", + "output_cost_per_token": 4.05e-06, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "baseten/thinkingmachines/inkling-small": { + "cache_read_input_token_cost": 1e-07, + "input_cost_per_token": 5e-07, + "litellm_provider": "baseten", + "max_input_tokens": 1048576, + "max_output_tokens": 32768, + "max_tokens": 32768, + "mode": "chat", + "output_cost_per_token": 1.2e-06, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "baseten/zai-org/GLM-5.2": { + "cache_read_input_token_cost": 1.4e-07, + "input_cost_per_token": 1.4e-06, + "litellm_provider": "baseten", + "max_input_tokens": 1048576, + "max_output_tokens": 262144, + "max_tokens": 262144, + "mode": "chat", + "output_cost_per_token": 4.4e-06, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "baseten/zai-org/GLM-5.3-Flash": { + "cache_read_input_token_cost": 3e-08, + "input_cost_per_token": 1.5e-07, + "litellm_provider": "baseten", + "max_input_tokens": 1048576, + "max_output_tokens": 131072, + "max_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 5e-07, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true } } From 666f6b01b4c4dc474bbb4d9d129c127cfada6961 Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Tue, 22 Sep 2026 13:28:31 -0700 Subject: [PATCH 021/101] fix: enforce disable_custom_api_keys from general_settings (#42437) * fix: enforce disable_custom_api_keys from general_settings The gate in _check_custom_key_allowed read the persisted UI settings row through get_ui_settings_cached, which had two consequences. A config-file general_settings.disable_custom_api_keys was never enforced, because the gate only ever looked at the stored ui_settings row. POST /key/generate with a custom key value returned 200 even with the flag set to true in config.yaml. The read went through a DualCache with a 600s TTL, which is per worker without Redis, and only the worker that served PATCH /update/ui_settings refreshed it. A gate flipped through the UI was then a coin flip across workers for up to ten minutes. Both go away by routing the flag the way the other runtime UI flags are already routed. Adding it to _RUNTIME_GENERAL_SETTINGS_FLAGS and to the settings rules' _UI_SETTINGS_FIELDS makes SettingsStore resolve it from the ui_settings row with the config file winning, and every pod re-reads it on its own settings sync rather than holding a private cached copy. The two lists have to stay in step: a flag in one and not the other resolves against the wrong stored row and silently never reaches a reader, so there is a test for that invariant. Writes to the ui_settings table did not publish on the config-sync channel, so other pods only discovered a change on their next periodic reload. Adding litellm_uisettings to _CONFIG_SYNCED_TABLE_NAMES puts it on the same pubsub path model and SSO config writes already use, which cuts cross-pod propagation from tens of seconds to a few. The value reaching the gate is run through coerce_bool first. Resolution hands back the raw YAML value, so a quoted "true" in config.yaml is a str and the old `is True` check let custom keys straight through. * test: assert both directions of the coerced config value * test: assert the runtime flags read back instead of inspecting the registry --- .../proxy/common_utils/config_sync_pubsub.py | 1 + .../proxy/config_resolvers/settings_rules.py | 1 + .../key_management_endpoints.py | 9 +- .../proxy_setting_endpoints.py | 1 + .../common_utils/test_config_sync_pubsub.py | 28 +++ .../test_key_management_endpoints.py | 188 +++++++++++------- .../test_proxy_setting_endpoints.py | 26 +++ 7 files changed, 181 insertions(+), 73 deletions(-) diff --git a/litellm/proxy/common_utils/config_sync_pubsub.py b/litellm/proxy/common_utils/config_sync_pubsub.py index 6d781babe63..b20c0d9c9a5 100644 --- a/litellm/proxy/common_utils/config_sync_pubsub.py +++ b/litellm/proxy/common_utils/config_sync_pubsub.py @@ -55,6 +55,7 @@ _CONFIG_SYNCED_TABLE_NAMES: Final[frozenset[str]] = frozenset( "litellm_ssoconfig", "litellm_cacheconfig", "litellm_configoverrides", + "litellm_uisettings", } ) diff --git a/litellm/proxy/config_resolvers/settings_rules.py b/litellm/proxy/config_resolvers/settings_rules.py index f346dd6198d..1f0adfc5248 100644 --- a/litellm/proxy/config_resolvers/settings_rules.py +++ b/litellm/proxy/config_resolvers/settings_rules.py @@ -48,6 +48,7 @@ _UI_SETTINGS_FIELDS: Final[tuple[str, ...]] = ( "allow_agents_for_team_admins", "disable_vector_stores_for_internal_users", "allow_vector_stores_for_team_admins", + "disable_custom_api_keys", "disable_key_generate_for_org_admin", "team_admin_editable_team_fields", ) diff --git a/litellm/proxy/management_endpoints/key_management_endpoints.py b/litellm/proxy/management_endpoints/key_management_endpoints.py index fbc7cf18003..801c45501ce 100644 --- a/litellm/proxy/management_endpoints/key_management_endpoints.py +++ b/litellm/proxy/management_endpoints/key_management_endpoints.py @@ -118,9 +118,6 @@ from litellm.proxy.management_helpers.team_member_permission_checks import ( from litellm.proxy.management_helpers.utils import management_endpoint_wrapper from litellm.proxy.spend_tracking.budget_reservation import get_budget_window_start from litellm.proxy.spend_tracking.spend_tracking_utils import _is_master_key -from litellm.proxy.ui_crud_endpoints.proxy_setting_endpoints import ( - get_ui_settings_cached, -) from litellm.proxy.utils import ( PrismaClient, ProxyLogging, @@ -487,8 +484,10 @@ async def _check_custom_key_allowed(custom_key_value: str | None) -> None: if custom_key_value is None: return - ui_settings: Final = await get_ui_settings_cached() - if ui_settings.get("disable_custom_api_keys", False) is True: + from litellm.proxy.config_resolvers.settings_rules import coerce_bool + from litellm.proxy.proxy_server import general_settings + + if coerce_bool(general_settings.get("disable_custom_api_keys", False)) is True: verbose_proxy_logger.warning("Custom API key rejected: disable_custom_api_keys is enabled") raise HTTPException( status_code=403, diff --git a/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py b/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py index f37b82f3b54..d520177965c 100644 --- a/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py +++ b/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py @@ -407,6 +407,7 @@ _RUNTIME_GENERAL_SETTINGS_FLAGS: Final = [ "allow_agents_for_team_admins", "disable_vector_stores_for_internal_users", "allow_vector_stores_for_team_admins", + "disable_custom_api_keys", "disable_key_generate_for_org_admin", TEAM_ADMIN_EDITABLE_TEAM_FIELDS_SETTING, ] diff --git a/tests/test_litellm/proxy/common_utils/test_config_sync_pubsub.py b/tests/test_litellm/proxy/common_utils/test_config_sync_pubsub.py index 2a0ebf9492a..0f64ef2b4ca 100644 --- a/tests/test_litellm/proxy/common_utils/test_config_sync_pubsub.py +++ b/tests/test_litellm/proxy/common_utils/test_config_sync_pubsub.py @@ -47,6 +47,7 @@ _EXPECTED_CONFIG_SYNCED_TABLE_NAMES = frozenset( "litellm_proxymodeltable", "litellm_searchtoolstable", "litellm_ssoconfig", + "litellm_uisettings", } ) @@ -702,6 +703,33 @@ async def test_model_repository_write_publishes_via_live_coordination_cache() -> assert json.loads(message) == {"object_type": "litellm_proxymodeltable"} +async def test_ui_settings_write_publishes_via_live_coordination_cache() -> None: + from litellm.proxy import proxy_server + from litellm.proxy.proxy_server import _set_redis_usage_cache + from litellm.repositories.table_repositories import UISettingsRepository + + client = _RecordingRedisClient() + prisma_client = MagicMock() + prisma_client.db.litellm_uisettings.upsert = AsyncMock(return_value={"id": "ui_settings"}) + table = UISettingsRepository(prisma_client).table + assert isinstance(table, _PublishOnWriteActions) + + previous_cache = proxy_server.redis_usage_cache + _set_redis_usage_cache(_FakeRedisCache(client)) + try: + await table.upsert( + where={"id": "ui_settings"}, + data={"create": {"id": "ui_settings"}, "update": {"ui_settings": "{}"}}, + ) + finally: + _set_redis_usage_cache(previous_cache) + + assert len(client.published) == 1 + channel, message = client.published[0] + assert channel == CONFIG_SYNC_CHANNEL + assert json.loads(message) == {"object_type": "litellm_uisettings"} + + async def _publish_calls_for_invalidated_param(param_name: str) -> List[Tuple[str, str]]: from litellm.proxy import proxy_server from litellm.proxy.proxy_server import _set_redis_usage_cache diff --git a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py index 8eaa4901c59..c539a10e1e2 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py +++ b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py @@ -609,10 +609,7 @@ async def test_generate_key_debug_log_never_contains_raw_token(monkeypatch, capl mock_prisma_client.insert_data = AsyncMock(side_effect=_insert_data_side_effect) monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client) - monkeypatch.setattr( - "litellm.proxy.management_endpoints.key_management_endpoints.get_ui_settings_cached", - AsyncMock(return_value={}), - ) + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {}) from litellm.proxy._types import GenerateKeyRequest, LitellmUserRoles from litellm.proxy.auth.user_api_key_auth import UserAPIKeyAuth @@ -1494,18 +1491,12 @@ async def test_list_keys_full_object_returns_lifetime_total_spend(): @pytest.mark.asyncio async def test_get_new_token_with_valid_key(monkeypatch): """Test get_new_token function when provided with a valid key that starts with 'sk-'""" - from unittest.mock import AsyncMock - from litellm.proxy._types import RegenerateKeyRequest from litellm.proxy.management_endpoints.key_management_endpoints import ( get_new_token, ) - # Mock get_ui_settings_cached to return setting disabled (custom keys allowed) - monkeypatch.setattr( - "litellm.proxy.management_endpoints.key_management_endpoints.get_ui_settings_cached", - AsyncMock(return_value={}), - ) + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {}) # Test with valid new_key data = RegenerateKeyRequest(new_key="sk-test1234567890abc") @@ -1517,8 +1508,6 @@ async def test_get_new_token_with_valid_key(monkeypatch): @pytest.mark.asyncio async def test_get_new_token_with_invalid_key(monkeypatch): """Test get_new_token function when provided with an invalid key that doesn't start with 'sk-'""" - from unittest.mock import AsyncMock - from fastapi import HTTPException from litellm.proxy._types import RegenerateKeyRequest @@ -1526,11 +1515,7 @@ async def test_get_new_token_with_invalid_key(monkeypatch): get_new_token, ) - # Mock get_ui_settings_cached to return setting disabled (custom keys allowed) - monkeypatch.setattr( - "litellm.proxy.management_endpoints.key_management_endpoints.get_ui_settings_cached", - AsyncMock(return_value={}), - ) + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {}) # Test with invalid new_key (doesn't start with 'sk-') data = RegenerateKeyRequest(new_key="invalid-key-123") @@ -1546,8 +1531,6 @@ async def test_get_new_token_with_invalid_key(monkeypatch): async def test_get_new_token_rejects_short_new_key(monkeypatch): """Regression test for LIT-4355: a short custom key like sk-99 must be rejected, otherwise the stored key_name (sk-...{last 4 chars}) reveals the entire key.""" - from unittest.mock import AsyncMock - from fastapi import HTTPException from litellm.proxy._types import RegenerateKeyRequest @@ -1555,10 +1538,7 @@ async def test_get_new_token_rejects_short_new_key(monkeypatch): get_new_token, ) - monkeypatch.setattr( - "litellm.proxy.management_endpoints.key_management_endpoints.get_ui_settings_cached", - AsyncMock(return_value={}), - ) + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {}) data = RegenerateKeyRequest(new_key="sk-99") @@ -1588,10 +1568,7 @@ async def test_generate_key_fn_rejects_short_custom_key(monkeypatch, short_key): ) monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client) - monkeypatch.setattr( - "litellm.proxy.management_endpoints.key_management_endpoints.get_ui_settings_cached", - AsyncMock(return_value={}), - ) + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {}) assert len(short_key) < 16 @@ -1628,10 +1605,7 @@ async def test_generate_key_fn_accepts_custom_key_at_minimum_length(monkeypatch) ) monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client) - monkeypatch.setattr( - "litellm.proxy.management_endpoints.key_management_endpoints.get_ui_settings_cached", - AsyncMock(return_value={}), - ) + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {}) custom_key = "sk-abcdefghijklm" assert len(custom_key) == 16 @@ -1649,18 +1623,13 @@ async def test_generate_key_fn_accepts_custom_key_at_minimum_length(monkeypatch) @pytest.mark.asyncio async def test_check_custom_key_allowed_when_disabled(monkeypatch): """_check_custom_key_allowed raises 403 when disable_custom_api_keys is true.""" - from unittest.mock import AsyncMock - from fastapi import HTTPException from litellm.proxy.management_endpoints.key_management_endpoints import ( _check_custom_key_allowed, ) - monkeypatch.setattr( - "litellm.proxy.management_endpoints.key_management_endpoints.get_ui_settings_cached", - AsyncMock(return_value={"disable_custom_api_keys": True}), - ) + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {"disable_custom_api_keys": True}) with pytest.raises(HTTPException) as exc_info: await _check_custom_key_allowed("sk-custom-key-123") @@ -1672,16 +1641,11 @@ async def test_check_custom_key_allowed_when_disabled(monkeypatch): @pytest.mark.asyncio async def test_check_custom_key_allowed_when_enabled(monkeypatch): """_check_custom_key_allowed does nothing when disable_custom_api_keys is false.""" - from unittest.mock import AsyncMock - from litellm.proxy.management_endpoints.key_management_endpoints import ( _check_custom_key_allowed, ) - monkeypatch.setattr( - "litellm.proxy.management_endpoints.key_management_endpoints.get_ui_settings_cached", - AsyncMock(return_value={"disable_custom_api_keys": False}), - ) + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {"disable_custom_api_keys": False}) # Should not raise await _check_custom_key_allowed("sk-custom-key-123") @@ -1690,35 +1654,133 @@ async def test_check_custom_key_allowed_when_enabled(monkeypatch): @pytest.mark.asyncio async def test_check_custom_key_allowed_when_unset(monkeypatch): """_check_custom_key_allowed does nothing when setting is not present.""" - from unittest.mock import AsyncMock - from litellm.proxy.management_endpoints.key_management_endpoints import ( _check_custom_key_allowed, ) - monkeypatch.setattr( - "litellm.proxy.management_endpoints.key_management_endpoints.get_ui_settings_cached", - AsyncMock(return_value={}), - ) + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {}) # Should not raise await _check_custom_key_allowed("sk-custom-key-123") @pytest.mark.asyncio -async def test_check_custom_key_allowed_none_key_always_passes(monkeypatch): - """_check_custom_key_allowed does nothing when key is None, even if setting is on.""" - from unittest.mock import AsyncMock +async def test_check_custom_key_allowed_honours_the_config_file(monkeypatch): + """A config-file general_settings.disable_custom_api_keys is enforced with no stored UI row.""" + from fastapi import HTTPException + from litellm.proxy.config_resolvers import SettingsStore from litellm.proxy.management_endpoints.key_management_endpoints import ( _check_custom_key_allowed, ) - monkeypatch.setattr( - "litellm.proxy.management_endpoints.key_management_endpoints.get_ui_settings_cached", - AsyncMock(return_value={"disable_custom_api_keys": True}), + general_settings = SettingsStore("general_settings") + general_settings.load_yaml({"disable_custom_api_keys": True}) + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", general_settings) + + with pytest.raises(HTTPException) as exc_info: + await _check_custom_key_allowed("sk-custom-key-123456") + + assert exc_info.value.status_code == 403 + + +@pytest.mark.parametrize( + ("config_value", "blocked"), + [ + (True, True), + ("true", True), + ("True", True), + (1, True), + (False, False), + ("false", False), + ("False", False), + (0, False), + ], +) +@pytest.mark.asyncio +async def test_check_custom_key_allowed_coerces_a_non_bool_config_value(monkeypatch, config_value, blocked): + """A YAML value that is not a bare bool, such as a quoted "true", still decides the gate.""" + from fastapi import HTTPException + + from litellm.proxy.config_resolvers import SettingsStore + from litellm.proxy.management_endpoints.key_management_endpoints import ( + _check_custom_key_allowed, ) + general_settings = SettingsStore("general_settings") + general_settings.load_yaml({"disable_custom_api_keys": config_value}) + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", general_settings) + + rejected = False + try: + await _check_custom_key_allowed("sk-custom-key-123456") + except HTTPException as e: + rejected = e.status_code == 403 + + assert rejected is blocked + + +@pytest.mark.asyncio +async def test_check_custom_key_allowed_config_file_beats_the_stored_ui_row(monkeypatch): + """The config file owns the flag, so a stored UI row saying false cannot re-open custom keys.""" + from fastapi import HTTPException + + from litellm.proxy.config_resolvers import SettingsStore + from litellm.proxy.management_endpoints.key_management_endpoints import ( + _check_custom_key_allowed, + ) + from litellm.proxy.ui_crud_endpoints.proxy_setting_endpoints import ( + apply_runtime_general_settings_flags, + ) + + general_settings = SettingsStore("general_settings") + general_settings.load_yaml({"disable_custom_api_keys": True}) + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", general_settings) + + apply_runtime_general_settings_flags({"disable_custom_api_keys": False}) + + with pytest.raises(HTTPException) as exc_info: + await _check_custom_key_allowed("sk-custom-key-123456") + + assert exc_info.value.status_code == 403 + + +@pytest.mark.asyncio +async def test_check_custom_key_allowed_picks_up_a_ui_write_without_the_serving_pod(monkeypatch): + """A pod that never served the PATCH enforces the new value after its own settings sync.""" + from fastapi import HTTPException + + from litellm.proxy.config_resolvers import SettingsStore + from litellm.proxy.management_endpoints.key_management_endpoints import ( + _check_custom_key_allowed, + ) + from litellm.proxy.ui_crud_endpoints.proxy_setting_endpoints import ( + apply_runtime_general_settings_flags, + ) + + general_settings = SettingsStore("general_settings") + general_settings.load_yaml({}) + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", general_settings) + + await _check_custom_key_allowed("sk-custom-key-123456") + + apply_runtime_general_settings_flags({"disable_custom_api_keys": True}) + + with pytest.raises(HTTPException) as exc_info: + await _check_custom_key_allowed("sk-custom-key-123456") + + assert exc_info.value.status_code == 403 + + +@pytest.mark.asyncio +async def test_check_custom_key_allowed_none_key_always_passes(monkeypatch): + """_check_custom_key_allowed does nothing when key is None, even if setting is on.""" + from litellm.proxy.management_endpoints.key_management_endpoints import ( + _check_custom_key_allowed, + ) + + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {"disable_custom_api_keys": True}) + # Should not raise — None means auto-generate await _check_custom_key_allowed(None) @@ -1726,8 +1788,6 @@ async def test_check_custom_key_allowed_none_key_always_passes(monkeypatch): @pytest.mark.asyncio async def test_get_new_token_rejected_when_custom_keys_disabled(monkeypatch): """get_new_token raises 403 when new_key is set and disable_custom_api_keys is true.""" - from unittest.mock import AsyncMock - from fastapi import HTTPException from litellm.proxy._types import RegenerateKeyRequest @@ -1735,10 +1795,7 @@ async def test_get_new_token_rejected_when_custom_keys_disabled(monkeypatch): get_new_token, ) - monkeypatch.setattr( - "litellm.proxy.management_endpoints.key_management_endpoints.get_ui_settings_cached", - AsyncMock(return_value={"disable_custom_api_keys": True}), - ) + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {"disable_custom_api_keys": True}) data = RegenerateKeyRequest(new_key="sk-custom-regen-key") @@ -1751,17 +1808,12 @@ async def test_get_new_token_rejected_when_custom_keys_disabled(monkeypatch): @pytest.mark.asyncio async def test_get_new_token_auto_generates_when_custom_keys_disabled(monkeypatch): """get_new_token auto-generates a key when new_key is None, even if setting is on.""" - from unittest.mock import AsyncMock - from litellm.proxy._types import RegenerateKeyRequest from litellm.proxy.management_endpoints.key_management_endpoints import ( get_new_token, ) - monkeypatch.setattr( - "litellm.proxy.management_endpoints.key_management_endpoints.get_ui_settings_cached", - AsyncMock(return_value={"disable_custom_api_keys": True}), - ) + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {"disable_custom_api_keys": True}) data = RegenerateKeyRequest() # no new_key result = await get_new_token(data) diff --git a/tests/test_litellm/proxy/ui_crud_endpoints/test_proxy_setting_endpoints.py b/tests/test_litellm/proxy/ui_crud_endpoints/test_proxy_setting_endpoints.py index f40848bc38b..0140fcaba21 100644 --- a/tests/test_litellm/proxy/ui_crud_endpoints/test_proxy_setting_endpoints.py +++ b/tests/test_litellm/proxy/ui_crud_endpoints/test_proxy_setting_endpoints.py @@ -3998,6 +3998,32 @@ class TestSyncUiSettingsToGeneralSettings: assert general_settings["forward_client_headers_to_llm_api"] is True assert general_settings.source("forward_client_headers_to_llm_api") == "db" + def test_every_runtime_flag_reaches_a_reader_once_applied(self, monkeypatch): + """A flag the settings rules do not route to the ui_settings row is stored but never read back.""" + from litellm.proxy import proxy_server + from litellm.proxy.config_resolvers import SettingsStore + from litellm.proxy.ui_crud_endpoints.proxy_setting_endpoints import ( + TEAM_ADMIN_EDITABLE_TEAM_FIELDS_SETTING, + _RUNTIME_GENERAL_SETTINGS_FLAGS, + apply_runtime_general_settings_flags, + ) + + general_settings = SettingsStore("general_settings") + general_settings.load_yaml({}) + monkeypatch.setattr(proxy_server, "general_settings", general_settings) + + stored = { + key: (["tpm_limit"] if key == TEAM_ADMIN_EDITABLE_TEAM_FIELDS_SETTING else True) + for key in _RUNTIME_GENERAL_SETTINGS_FLAGS + } + assert stored + + apply_runtime_general_settings_flags(stored) + + read_back = {key: general_settings.get(key) for key in stored} + + assert read_back == stored + def test_applied_runtime_flags_cannot_override_the_config_file(self, monkeypatch): from litellm.proxy import proxy_server from litellm.proxy.config_resolvers import SettingsStore From fc0055497c3e603957fd7be7ef1f3b5994bfd048 Mon Sep 17 00:00:00 2001 From: togear Date: Wed, 23 Sep 2026 04:31:33 +0800 Subject: [PATCH 022/101] feat: add configurable provider affinity header mapping (#41033) * feat: add configurable provider affinity header mapping * fix: sync provider affinity API types * fix: harden provider affinity header mapping * fix: avoid provider affinity import cycle * fix: preserve input callback header mutations * fix: address provider affinity code scanning findings * fix: satisfy provider affinity type discipline gate * test: cover omitted pre-call argument isolation * fix: resolve remaining provider affinity codeql alerts * fix: redact provider affinity headers after calls * refactor: drop provider affinity header log redaction * fix: reject control characters in affinity session ids as a bad request * chore: regenerate the openapi snapshot on python 3.12 and reuse the session marker constant * fix(responses): read the affinity session from the named metadata argument --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- .../litellm_core_utils/get_litellm_params.py | 6 +- .../litellm_core_utils/provider_affinity.py | 98 +++++ litellm/llms/custom_httpx/http_handler.py | 2 +- litellm/llms/custom_httpx/llm_http_handler.py | 2 +- litellm/main.py | 28 +- litellm/responses/main.py | 31 +- litellm/types/router.py | 10 + litellm/types/utils.py | 1 + .../test_provider_affinity.py | 107 +++++ .../test_provider_affinity_forwarding.py | 389 ++++++++++++++++++ .../test_responses_api_bridge_flag.py | 24 ++ tests/test_litellm/types/test_router.py | 46 ++- ui/litellm-dashboard/src/lib/http/schema.d.ts | 4 + 13 files changed, 734 insertions(+), 14 deletions(-) create mode 100644 litellm/litellm_core_utils/provider_affinity.py create mode 100644 tests/test_litellm/litellm_core_utils/test_provider_affinity.py create mode 100644 tests/test_litellm/llms/openai_like/test_provider_affinity_forwarding.py diff --git a/litellm/litellm_core_utils/get_litellm_params.py b/litellm/litellm_core_utils/get_litellm_params.py index 7f373569b21..112d038039e 100644 --- a/litellm/litellm_core_utils/get_litellm_params.py +++ b/litellm/litellm_core_utils/get_litellm_params.py @@ -24,10 +24,7 @@ AWS_CREDENTIAL_KWARGS_KEYS: Final = frozenset( } ) -# Keys `completion()` forwards from its own kwargs into `get_litellm_params`, -# which are otherwise invisible to it because that call site passes explicit -# named arguments rather than `**kwargs`. -FORWARDED_KWARGS_KEYS: Final = AWS_CREDENTIAL_KWARGS_KEYS +PROVIDER_AFFINITY_HEADER_KWARG_KEY: Final = "provider_affinity_header" # Pre-define optional kwargs keys as frozenset for O(1) lookups # These are extracted from kwargs only if present, avoiding unnecessary .get() calls @@ -63,6 +60,7 @@ OPTIONAL_KWARGS_KEYS: Final = ( "itpm", "otpm", "use_xai_oauth", + PROVIDER_AFFINITY_HEADER_KWARG_KEY, } ) | AWS_CREDENTIAL_KWARGS_KEYS diff --git a/litellm/litellm_core_utils/provider_affinity.py b/litellm/litellm_core_utils/provider_affinity.py new file mode 100644 index 00000000000..31cd9a7ff69 --- /dev/null +++ b/litellm/litellm_core_utils/provider_affinity.py @@ -0,0 +1,98 @@ +import re +from collections.abc import Mapping +from typing import Final + +from litellm.constants import SESSION_ID_GENERATED_METADATA_KEY + +_HTTP_HEADER_NAME_PATTERN: Final = re.compile(r"^[!#$%&'*+\-.^_`|~0-9A-Za-z]+$") +_FORBIDDEN_AFFINITY_HEADERS: Final = frozenset( + { + "api-key", + "authorization", + "connection", + "content-length", + "content-type", + "cookie", + "host", + "keep-alive", + "proxy-authenticate", + "proxy-authorization", + "proxy-connection", + "set-cookie", + "te", + "trailer", + "transfer-encoding", + "upgrade", + "www-authenticate", + "x-api-key", + "x-goog-api-key", + } +) + + +def validate_provider_affinity_header_name(header: str) -> str: + if not _HTTP_HEADER_NAME_PATTERN.fullmatch(header): + raise ValueError("provider_affinity_header must be a valid HTTP header name") + if header.lower() in _FORBIDDEN_AFFINITY_HEADERS: + raise ValueError("provider_affinity_header cannot be an authentication, cookie, or transport header") + return header + + +def _get_value(value: object, key: str) -> object | None: + if isinstance(value, Mapping): + return value.get(key) + return getattr(value, key, None) + + +def _get_provider_affinity_header_name(litellm_params: object | None) -> str | None: + header: Final = _get_value(litellm_params, "provider_affinity_header") if litellm_params is not None else None + if header is None: + return None + if not isinstance(header, str): + raise TypeError("provider_affinity_header must be a string") + return validate_provider_affinity_header_name(header) + + +def get_stable_session_id(litellm_params: object | None) -> str | None: + if litellm_params is None: + return None + + direct_session_id: Final = _get_value(litellm_params, "session_id") + if direct_session_id: + return str(direct_session_id) + + metadata_values: Final[tuple[object, ...]] = tuple( + value for key in ("metadata", "litellm_metadata") if (value := _get_value(litellm_params, key)) is not None + ) + has_generated_session_id: Final = any( + isinstance(metadata, Mapping) and metadata.get(SESSION_ID_GENERATED_METADATA_KEY) + for metadata in metadata_values + ) + + litellm_session_id: Final = _get_value(litellm_params, "litellm_session_id") + if litellm_session_id and not has_generated_session_id: + return str(litellm_session_id) + + for metadata in metadata_values: + if ( + isinstance(metadata, Mapping) + and not metadata.get(SESSION_ID_GENERATED_METADATA_KEY) + and (value := metadata.get("session_id")) + ): + return str(value) + return None + + +def add_provider_affinity_header( # mutable-ok: downstream handlers add auth and signing headers + headers: Mapping[str, object], litellm_params: object | None +) -> dict[str, object]: # mutable-ok: downstream handlers add auth and signing headers + header_name: Final = _get_provider_affinity_header_name(litellm_params) + if header_name is None or any(key.lower() == header_name.lower() for key in headers): + return dict(headers) # mutable-ok: downstream handlers add auth and signing headers + + session_id: Final = get_stable_session_id(litellm_params) + if session_id is None: + return dict(headers) # mutable-ok: downstream handlers add auth and signing headers + if any(character in session_id for character in ("\r", "\n", "\0")): + raise ValueError("session_id cannot contain HTTP header control characters") + return {**headers, header_name: session_id} # mutable-ok: downstream handlers add auth and signing headers diff --git a/litellm/llms/custom_httpx/http_handler.py b/litellm/llms/custom_httpx/http_handler.py index 8ea46a6b261..312f46bb021 100644 --- a/litellm/llms/custom_httpx/http_handler.py +++ b/litellm/llms/custom_httpx/http_handler.py @@ -1711,7 +1711,7 @@ class HTTPHandler: def get_async_httpx_client( - llm_provider: LlmProviders | httpxSpecialProvider, + llm_provider: LlmProviders | httpxSpecialProvider | str, params: dict | None = None, shared_session: Optional["ClientSession"] = None, ) -> AsyncHTTPHandler: diff --git a/litellm/llms/custom_httpx/llm_http_handler.py b/litellm/llms/custom_httpx/llm_http_handler.py index cbef44ce488..8cbc28362a8 100644 --- a/litellm/llms/custom_httpx/llm_http_handler.py +++ b/litellm/llms/custom_httpx/llm_http_handler.py @@ -2857,7 +2857,7 @@ class BaseLLMHTTPHandler: id(shared_session) if shared_session else None, ) async_httpx_client = get_async_httpx_client( - llm_provider=litellm.LlmProviders(custom_llm_provider), + llm_provider=custom_llm_provider, params={"ssl_verify": litellm_params.get("ssl_verify", None)}, shared_session=shared_session, ) diff --git a/litellm/main.py b/litellm/main.py index 7d231a1bf7a..7f4b34d28a0 100644 --- a/litellm/main.py +++ b/litellm/main.py @@ -78,8 +78,9 @@ from litellm.litellm_core_utils.chat_completion_agentic_loop import ( from litellm.litellm_core_utils.completion_timeout import CompletionTimeout from litellm.litellm_core_utils.dd_tracing import tracer from litellm.litellm_core_utils.get_litellm_params import ( - FORWARDED_KWARGS_KEYS, + AWS_CREDENTIAL_KWARGS_KEYS, OPTIONAL_KWARGS_KEYS, + PROVIDER_AFFINITY_HEADER_KWARG_KEY, ) from litellm.litellm_core_utils.get_provider_specific_headers import ( ProviderSpecificHeaderUtils, @@ -96,6 +97,7 @@ from litellm.litellm_core_utils.mock_functions import ( from litellm.litellm_core_utils.prompt_templates.common_utils import ( get_content_from_model_response, ) +from litellm.litellm_core_utils.provider_affinity import add_provider_affinity_header from litellm.litellm_core_utils.request_timeout_resolver import ( get_configured_request_timeout, ) @@ -5644,8 +5646,30 @@ def completion( gigachat_scope=kwargs.get("gigachat_scope"), gigachat_auth_url=kwargs.get("gigachat_auth_url"), gigachat_access_token=kwargs.get("gigachat_access_token"), - **{key: kwargs[key] for key in FORWARDED_KWARGS_KEYS if key in kwargs}, + **{ + key: kwargs[key] + for key in (*AWS_CREDENTIAL_KWARGS_KEYS, PROVIDER_AFFINITY_HEADER_KWARG_KEY) + if key in kwargs + }, ) + if litellm_params.get("provider_affinity_header") is not None: + try: + headers = add_provider_affinity_header( + headers=headers or litellm.headers or MappingProxyType({}), + litellm_params=MappingProxyType( + { + "provider_affinity_header": litellm_params["provider_affinity_header"], + "litellm_session_id": kwargs.get("litellm_session_id"), + "session_id": kwargs.get("session_id"), + "metadata": metadata, + "litellm_metadata": kwargs.get("litellm_metadata"), + } + ), + ) + except ValueError as affinity_error: + raise litellm.BadRequestError( + message=str(affinity_error), model=model, llm_provider=custom_llm_provider + ) from affinity_error cast(LiteLLMLoggingObj, logging).update_environment_variables( model=model, user=user, diff --git a/litellm/responses/main.py b/litellm/responses/main.py index c5032536df4..5c4c9ea3987 100644 --- a/litellm/responses/main.py +++ b/litellm/responses/main.py @@ -26,6 +26,7 @@ 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.provider_affinity import add_provider_affinity_header from litellm.llms.base_llm.responses.transformation import BaseResponsesAPIConfig from litellm.llms.custom_httpx.llm_http_handler import BaseLLMHTTPHandler from litellm.llms.openai_like.responses.transformation import OpenAILikeResponsesConfig @@ -1218,6 +1219,27 @@ def responses( # get llm provider logic litellm_params: Final = GenericLiteLLMParams(**kwargs) + try: + effective_extra_headers: Final = ( + add_provider_affinity_header( + headers=extra_headers or MappingProxyType({}), + litellm_params=MappingProxyType( + { + "provider_affinity_header": litellm_params.provider_affinity_header, + "litellm_session_id": kwargs.get("litellm_session_id"), + "session_id": kwargs.get("session_id"), + "metadata": metadata, + "litellm_metadata": kwargs.get("litellm_metadata"), + } + ), + ) + if litellm_params.provider_affinity_header is not None + else extra_headers + ) + except ValueError as affinity_error: + raise litellm.BadRequestError( + message=str(affinity_error), model=model, llm_provider=custom_llm_provider + ) from affinity_error ######################################################### # MOCK RESPONSE LOGIC @@ -1261,7 +1283,7 @@ def responses( top_p=top_p, truncation=truncation, user=user, - extra_headers=extra_headers, + extra_headers=effective_extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout, @@ -1332,7 +1354,7 @@ def responses( safety_identifier=safety_identifier, text_format=text_format, allowed_openai_params=allowed_openai_params, - extra_headers=extra_headers, + extra_headers=effective_extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout, @@ -1352,7 +1374,7 @@ def responses( custom_llm_provider=custom_llm_provider, _is_async=_is_async, stream=stream, - extra_headers=extra_headers, + extra_headers=effective_extra_headers, extra_body=extra_body, timeout=timeout if timeout is not None else request_timeout, allowed_openai_params=allowed_openai_params, @@ -1381,6 +1403,7 @@ def responses( "model_info": kwargs.get("model_info"), "data_residency": infer_openai_data_residency(custom_llm_provider, litellm_params.api_base), "metadata": (kwargs["litellm_metadata"] if "litellm_metadata" in kwargs else kwargs.get("metadata")), + "provider_affinity_header": litellm_params.provider_affinity_header, }, custom_llm_provider=custom_llm_provider, ) @@ -1400,7 +1423,7 @@ def responses( custom_llm_provider=custom_llm_provider, litellm_params=litellm_params, logging_obj=litellm_logging_obj, - extra_headers=extra_headers, + extra_headers=effective_extra_headers, extra_body=extra_body, timeout=timeout or request_timeout, _is_async=_is_async, diff --git a/litellm/types/router.py b/litellm/types/router.py index 2353093d435..57bd4263894 100644 --- a/litellm/types/router.py +++ b/litellm/types/router.py @@ -16,6 +16,7 @@ from typing_extensions import Protocol, ReadOnly, Required, TypedDict, runtime_c from litellm._logging import verbose_logger from litellm._uuid import uuid from litellm.litellm_core_utils.core_helpers import normalize_drop_params +from litellm.litellm_core_utils.provider_affinity import validate_provider_affinity_header_name from litellm.types.router_weights import RouterWeights if TYPE_CHECKING: @@ -396,6 +397,7 @@ class GenericLiteLLMParams(CredentialLiteLLMParams, CustomPricingLiteLLMParams): organization: str | None = None # for openai orgs configurable_clientside_auth_params: CONFIGURABLE_CLIENTSIDE_AUTH_PARAMS = None litellm_credential_name: str | None = None + provider_affinity_header: str | None = None ## LOGGING PARAMS ## litellm_trace_id: str | None = None @@ -467,6 +469,13 @@ class GenericLiteLLMParams(CredentialLiteLLMParams, CustomPricingLiteLLMParams): valkey_text_field: str | None = None valkey_embedding_field: str | None = None + @field_validator("provider_affinity_header") + @classmethod + def validate_provider_affinity_header(cls, value: str | None) -> str | None: + if value is None: + return None + return validate_provider_affinity_header_name(value) + @model_validator(mode="before") @classmethod def preprocess_input_data(cls, data: object) -> object: @@ -569,6 +578,7 @@ class LiteLLMParamsTypedDict(TypedDict, total=False): stream_timeout: float | str | None max_retries: int | None organization: list | str | None # for openai orgs + provider_affinity_header: ReadOnly[str | None] configurable_clientside_auth_params: ( CONFIGURABLE_CLIENTSIDE_AUTH_PARAMS # for allowing api base switching on finetuned models ) diff --git a/litellm/types/utils.py b/litellm/types/utils.py index f10f102d8ec..f2c8f0e7044 100644 --- a/litellm/types/utils.py +++ b/litellm/types/utils.py @@ -4073,6 +4073,7 @@ all_litellm_params = ( "litellm_credential_name", "allowed_openai_params", "litellm_session_id", + "provider_affinity_header", "use_litellm_proxy", "use_chat_completions_api", "rust", diff --git a/tests/test_litellm/litellm_core_utils/test_provider_affinity.py b/tests/test_litellm/litellm_core_utils/test_provider_affinity.py new file mode 100644 index 00000000000..edf4f5169b5 --- /dev/null +++ b/tests/test_litellm/litellm_core_utils/test_provider_affinity.py @@ -0,0 +1,107 @@ +import pytest + +from litellm.constants import SESSION_ID_GENERATED_METADATA_KEY +from litellm.litellm_core_utils.provider_affinity import ( + add_provider_affinity_header, + get_stable_session_id, +) + + +@pytest.mark.parametrize( + ("litellm_params", "expected"), + [ + ({"litellm_session_id": "litellm-session"}, "litellm-session"), + ({"session_id": "direct-session"}, "direct-session"), + ({"metadata": {"session_id": "metadata-session"}}, "metadata-session"), + ({"litellm_metadata": {"session_id": "litellm-metadata-session"}}, "litellm-metadata-session"), + ], +) +def test_get_stable_session_id_uses_explicit_session_sources(litellm_params: dict, expected: str): + assert get_stable_session_id(litellm_params) == expected + + +def test_get_stable_session_id_does_not_use_trace_id(): + assert get_stable_session_id({"litellm_trace_id": "per-request-trace"}) is None + + +@pytest.mark.parametrize("metadata_key", ["metadata", "litellm_metadata"]) +def test_get_stable_session_id_ignores_proxy_generated_session(metadata_key: str): + assert ( + get_stable_session_id( + { + "litellm_session_id": "generated-session", + metadata_key: { + "session_id": "generated-session", + SESSION_ID_GENERATED_METADATA_KEY: True, + }, + } + ) + is None + ) + + +def test_get_stable_session_id_prefers_explicit_session_over_proxy_generated_session(): + assert ( + get_stable_session_id( + { + "session_id": "explicit-session", + "litellm_session_id": "generated-session", + "metadata": { + "session_id": "generated-session", + SESSION_ID_GENERATED_METADATA_KEY: True, + }, + } + ) + == "explicit-session" + ) + + +def test_add_provider_affinity_header_maps_session_id(): + headers = add_provider_affinity_header( + headers={"Content-Type": "application/json"}, + litellm_params={ + "litellm_session_id": "session-123", + "provider_affinity_header": "X-Conversation-Id", + }, + ) + + assert headers == { + "Content-Type": "application/json", + "X-Conversation-Id": "session-123", + } + + +def test_add_provider_affinity_header_preserves_explicit_header_case_insensitively(): + headers = add_provider_affinity_header( + headers={"x-conversation-id": "explicit-session"}, + litellm_params={ + "litellm_session_id": "session-123", + "provider_affinity_header": "X-Conversation-Id", + }, + ) + + assert headers == {"x-conversation-id": "explicit-session"} + + +@pytest.mark.parametrize("session_id", ["session\r", "session\n", "session\0"]) +def test_add_provider_affinity_header_rejects_control_characters(session_id: str): + with pytest.raises(ValueError, match="session_id cannot contain HTTP header control characters"): + add_provider_affinity_header( + headers={}, + litellm_params={ + "litellm_session_id": session_id, + "provider_affinity_header": "X-Conversation-Id", + }, + ) + + +def test_add_provider_affinity_header_does_nothing_without_config_or_session(): + assert add_provider_affinity_header({}, {"litellm_session_id": "session-123"}) == {} + assert ( + add_provider_affinity_header( + {}, + {"provider_affinity_header": "X-Conversation-Id"}, + ) + == {} + ) + diff --git a/tests/test_litellm/llms/openai_like/test_provider_affinity_forwarding.py b/tests/test_litellm/llms/openai_like/test_provider_affinity_forwarding.py new file mode 100644 index 00000000000..43101234e63 --- /dev/null +++ b/tests/test_litellm/llms/openai_like/test_provider_affinity_forwarding.py @@ -0,0 +1,389 @@ +import json +from unittest.mock import MagicMock + +import httpx +import pytest + +import litellm +from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler +from litellm.llms.openai_like import dynamic_config +from litellm.llms.openai_like.json_loader import JSONProviderRegistry, SimpleProviderConfig + + +def _provider(*, responses: bool = False) -> SimpleProviderConfig: + endpoints = ["/v1/chat/completions"] + if responses: + endpoints.append("/v1/responses") + return SimpleProviderConfig( + "db_only_provider", + { + "base_url": "https://db-only.example/v1", + "api_key_env": "DYNAMIC_PROVIDER_API_KEY", + "supported_endpoints": endpoints, + }, + ) + + +def _chat_response_payload(content: str = "dynamic response") -> dict[str, object]: + return { + "id": "chatcmpl-dynamic-provider", + "object": "chat.completion", + "created": 1234567890, + "model": "test-model", + "choices": [ + { + "index": 0, + "message": {"role": "assistant", "content": content}, + "finish_reason": "stop", + } + ], + "usage": {"prompt_tokens": 2, "completion_tokens": 2, "total_tokens": 4}, + } + + +def _responses_payload() -> dict[str, object]: + return { + "id": "resp_dynamic_provider", + "object": "response", + "created_at": 1234567890, + "status": "completed", + "model": "test-model", + "output": [], + "parallel_tool_calls": True, + "usage": {"input_tokens": 2, "output_tokens": 2, "total_tokens": 4}, + "error": None, + } + + +@pytest.fixture(autouse=True) +def _isolate_registry_state(): + original_providers = dict(JSONProviderRegistry._providers) + dynamic_config._responses_config_cache.clear() + yield + JSONProviderRegistry._providers = original_providers + dynamic_config._responses_config_cache.clear() + + +def test_dynamic_provider_receives_affinity_header_for_chat(): + from openai import OpenAI + + JSONProviderRegistry._providers = {"db_only_provider": _provider()} + requests: list[httpx.Request] = [] + + def respond(request: httpx.Request) -> httpx.Response: + requests.append(request) + return httpx.Response(200, json=_chat_response_payload()) + + client = OpenAI( + api_key="test-key", + base_url="https://db-only.example/v1", + http_client=httpx.Client(transport=httpx.MockTransport(respond)), + ) + try: + litellm.completion( + model="db_only_provider/test-model", + messages=[{"role": "user", "content": "hello"}], + api_key="test-key", + client=client, + extra_headers={"X-Customer-Header": "customer-value"}, + litellm_session_id="session-sync", + provider_affinity_header="X-Conversation-Id", + ) + finally: + client.close() + + assert requests[0].headers["x-conversation-id"] == "session-sync" + assert requests[0].headers["x-customer-header"] == "customer-value" + + +def test_dynamic_provider_does_not_use_trace_id_for_chat_affinity(): + from openai import OpenAI + + JSONProviderRegistry._providers = {"db_only_provider": _provider()} + requests: list[httpx.Request] = [] + + def respond(request: httpx.Request) -> httpx.Response: + requests.append(request) + return httpx.Response(200, json=_chat_response_payload()) + + client = OpenAI( + api_key="test-key", + base_url="https://db-only.example/v1", + http_client=httpx.Client(transport=httpx.MockTransport(respond)), + ) + try: + litellm.completion( + model="db_only_provider/test-model", + messages=[{"role": "user", "content": "hello"}], + api_key="test-key", + client=client, + metadata={"trace_id": "per-request-trace"}, + provider_affinity_header="X-Conversation-Id", + ) + finally: + client.close() + + assert "x-conversation-id" not in requests[0].headers + + +@pytest.mark.asyncio +async def test_dynamic_provider_receives_affinity_header_for_async_chat(): + from openai import AsyncOpenAI + + JSONProviderRegistry._providers = {"db_only_provider": _provider()} + requests: list[httpx.Request] = [] + + async def respond(request: httpx.Request) -> httpx.Response: + requests.append(request) + return httpx.Response(200, json=_chat_response_payload("async response")) + + client = AsyncOpenAI( + api_key="test-key", + base_url="https://db-only.example/v1", + http_client=httpx.AsyncClient(transport=httpx.MockTransport(respond)), + ) + try: + response = await litellm.acompletion( + model="db_only_provider/test-model", + messages=[{"role": "user", "content": "hello"}], + api_key="test-key", + client=client, + litellm_session_id="session-async", + provider_affinity_header="X-Conversation-Id", + ) + finally: + await client.close() + + assert response.choices[0].message.content == "async response" + assert requests[0].headers["x-conversation-id"] == "session-async" + + +def test_dynamic_provider_receives_affinity_header_for_streaming_chat(): + from openai import OpenAI + + JSONProviderRegistry._providers = {"db_only_provider": _provider()} + chunks = [ + { + "id": "chatcmpl-dynamic-stream", + "object": "chat.completion.chunk", + "created": 1234567890, + "model": "test-model", + "choices": [ + { + "index": 0, + "delta": {"role": "assistant", "content": "streamed"}, + "finish_reason": None, + } + ], + }, + { + "id": "chatcmpl-dynamic-stream", + "object": "chat.completion.chunk", + "created": 1234567890, + "model": "test-model", + "choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}], + }, + ] + stream_body = "".join(f"data: {json.dumps(chunk)}\n\n" for chunk in chunks) + "data: [DONE]\n\n" + requests: list[httpx.Request] = [] + + def respond(request: httpx.Request) -> httpx.Response: + requests.append(request) + return httpx.Response(200, content=stream_body, headers={"content-type": "text/event-stream"}) + + client = OpenAI( + api_key="test-key", + base_url="https://db-only.example/v1", + http_client=httpx.Client(transport=httpx.MockTransport(respond)), + ) + try: + response_chunks = list( + litellm.completion( + model="db_only_provider/test-model", + messages=[{"role": "user", "content": "hello"}], + api_key="test-key", + client=client, + stream=True, + litellm_session_id="session-stream", + provider_affinity_header="X-Conversation-Id", + ) + ) + finally: + client.close() + + assert any(chunk.choices[0].delta.content == "streamed" for chunk in response_chunks) + assert requests[0].headers["x-conversation-id"] == "session-stream" + + +def test_dynamic_provider_receives_affinity_header_for_responses(): + JSONProviderRegistry._providers = {"db_only_provider": _provider(responses=True)} + logging_obj = MagicMock() + requests: list[httpx.Request] = [] + + def respond(request: httpx.Request) -> httpx.Response: + requests.append(request) + return httpx.Response(200, json=_responses_payload()) + + http_client = httpx.Client(transport=httpx.MockTransport(respond)) + try: + litellm.responses( + model="db_only_provider/test-model", + input="hello", + api_key="test-key", + litellm_session_id="session-responses", + provider_affinity_header="X-Conversation-Id", + litellm_logging_obj=logging_obj, + client=HTTPHandler(client=http_client), + ) + finally: + http_client.close() + + assert requests[0].headers["X-Conversation-Id"] == "session-responses" + assert ( + logging_obj.update_from_kwargs.call_args.kwargs["litellm_params"]["provider_affinity_header"] + == "X-Conversation-Id" + ) + + +def test_dynamic_provider_uses_metadata_session_id_for_responses(): + JSONProviderRegistry._providers = {"db_only_provider": _provider(responses=True)} + requests: list[httpx.Request] = [] + + def respond(request: httpx.Request) -> httpx.Response: + requests.append(request) + return httpx.Response(200, json=_responses_payload()) + + http_client = httpx.Client(transport=httpx.MockTransport(respond)) + try: + litellm.responses( + model="db_only_provider/test-model", + input="hello", + api_key="test-key", + metadata={"session_id": "session-from-metadata"}, + provider_affinity_header="X-Conversation-Id", + litellm_logging_obj=MagicMock(), + client=HTTPHandler(client=http_client), + ) + finally: + http_client.close() + + assert requests[0].headers["X-Conversation-Id"] == "session-from-metadata" + + +@pytest.mark.asyncio +@pytest.mark.parametrize("stream", [False, True], ids=["non-streaming", "streaming"]) +async def test_dynamic_provider_receives_affinity_header_for_async_responses(stream: bool): + JSONProviderRegistry._providers = {"db_only_provider": _provider(responses=True)} + requests: list[httpx.Request] = [] + + def respond(request: httpx.Request) -> httpx.Response: + requests.append(request) + return httpx.Response(200, json=_responses_payload()) + + client = AsyncHTTPHandler() + await client.close() + client.client = httpx.AsyncClient(transport=httpx.MockTransport(respond)) + try: + response = await litellm.aresponses( + model="db_only_provider/test-model", + input="hello", + api_key="test-key", + stream=stream, + litellm_session_id="session-async-responses", + provider_affinity_header="X-Conversation-Id", + client=client, + ) + finally: + await client.client.aclose() + + assert requests[0].headers["X-Conversation-Id"] == "session-async-responses" + if stream: + assert hasattr(response, "__aiter__") + else: + assert getattr(response, "model", None) == "test-model" + + +def test_control_characters_in_session_id_are_a_bad_request_for_chat(): + from openai import OpenAI + + JSONProviderRegistry._providers = {"db_only_provider": _provider()} + requests: list[httpx.Request] = [] + + def respond(request: httpx.Request) -> httpx.Response: + requests.append(request) + return httpx.Response(200, json=_chat_response_payload()) + + client = OpenAI( + api_key="test-key", + base_url="https://db-only.example/v1", + http_client=httpx.Client(transport=httpx.MockTransport(respond)), + ) + try: + with pytest.raises(litellm.BadRequestError, match="HTTP header control characters"): + litellm.completion( + model="db_only_provider/test-model", + messages=[{"role": "user", "content": "hello"}], + api_key="test-key", + client=client, + litellm_session_id="session\nsplit", + provider_affinity_header="X-Conversation-Id", + ) + finally: + client.close() + + assert requests == [] + + +def test_control_characters_in_session_id_are_a_bad_request_for_responses(): + JSONProviderRegistry._providers = {"db_only_provider": _provider(responses=True)} + requests: list[httpx.Request] = [] + + def respond(request: httpx.Request) -> httpx.Response: + requests.append(request) + return httpx.Response(200, json=_responses_payload()) + + http_client = httpx.Client(transport=httpx.MockTransport(respond)) + try: + with pytest.raises(litellm.BadRequestError, match="HTTP header control characters"): + litellm.responses( + model="db_only_provider/test-model", + input="hello", + api_key="test-key", + litellm_session_id="session\nsplit", + provider_affinity_header="X-Conversation-Id", + litellm_logging_obj=MagicMock(), + client=HTTPHandler(client=http_client), + ) + finally: + http_client.close() + + assert requests == [] + + +def test_builtin_provider_receives_affinity_header(): + from openai import OpenAI + + requests: list[httpx.Request] = [] + + def respond(request: httpx.Request) -> httpx.Response: + requests.append(request) + return httpx.Response(200, json=_chat_response_payload()) + + client = OpenAI( + api_key="test-key", + base_url="https://api.openai.com/v1", + http_client=httpx.Client(transport=httpx.MockTransport(respond)), + ) + try: + litellm.completion( + model="openai/test-model", + messages=[{"role": "user", "content": "hello"}], + api_key="test-key", + client=client, + litellm_session_id="session-builtin", + provider_affinity_header="X-Conversation-Id", + ) + finally: + client.close() + + assert requests[0].headers["X-Conversation-Id"] == "session-builtin" diff --git a/tests/test_litellm/responses/test_responses_api_bridge_flag.py b/tests/test_litellm/responses/test_responses_api_bridge_flag.py index 16135106b41..642495fab86 100644 --- a/tests/test_litellm/responses/test_responses_api_bridge_flag.py +++ b/tests/test_litellm/responses/test_responses_api_bridge_flag.py @@ -66,6 +66,30 @@ class TestUseResponsesApiBridgeFlag: mock_bridge_handler.assert_called_once() + @patch.object( + import_module("litellm.responses.main").litellm_completion_transformation_handler, "response_api_handler" + ) + @patch.object( + import_module("litellm.responses.main").ProviderConfigManager, "get_provider_responses_api_config" + ) + def test_provider_affinity_header_is_forwarded_through_bridge(self, mock_get_config, mock_bridge_handler): + mock_get_config.return_value = litellm.OpenAIResponsesAPIConfig() + mock_bridge_handler.return_value = MagicMock() + + litellm.responses( + model="openai/my-custom-model", + input="Hello", + use_chat_completions_api=True, + litellm_session_id="session-bridge", + provider_affinity_header="X-Conversation-Id", + extra_headers={"X-Customer-Header": "customer-value"}, + litellm_logging_obj=MagicMock(), + ) + + forwarded_headers = mock_bridge_handler.call_args.kwargs["extra_headers"] + assert forwarded_headers["X-Conversation-Id"] == "session-bridge" + assert forwarded_headers["X-Customer-Header"] == "customer-value" + @patch.object( import_module("litellm.responses.main").litellm_completion_transformation_handler, "response_api_handler" ) diff --git a/tests/test_litellm/types/test_router.py b/tests/test_litellm/types/test_router.py index df744a77fe4..4d4c326d1ca 100644 --- a/tests/test_litellm/types/test_router.py +++ b/tests/test_litellm/types/test_router.py @@ -91,7 +91,7 @@ def test_pricing_strings_are_coerced_to_float(): def test_invalid_pricing_is_rejected(): - with pytest.raises(ValueError, match='validation error for ModelInfo'): + with pytest.raises(ValueError, match="validation error for ModelInfo"): ModelInfo(id="x", input_cost_per_token="free") @@ -118,7 +118,9 @@ def test_drop_params_ignores_non_flag_non_string_values_with_a_warning(value, ca assert f"drop_params={value!r} is not a flag value" in caplog.text -@pytest.mark.parametrize("value", [True, "true", None, "os.environ/DROP_PARAMS", "v2:gcm:ciphertext-from-a-pre-fix-row"]) +@pytest.mark.parametrize( + "value", [True, "true", None, "os.environ/DROP_PARAMS", "v2:gcm:ciphertext-from-a-pre-fix-row"] +) def test_drop_params_flags_and_strings_log_nothing(value, caplog): with caplog.at_level(logging.WARNING, logger="LiteLLM"): GenericLiteLLMParams(drop_params=value) @@ -148,6 +150,46 @@ def test_aws_session_tags_reject_shapes_sts_would_refuse(aws_session_tags): LiteLLM_Params(model="bedrock/anthropic.claude-opus-5", aws_session_tags=aws_session_tags) +def test_provider_affinity_header_is_normalized(): + params = LiteLLM_Params( + model="openai/gpt-4o-mini", + provider_affinity_header="X-Conversation-Id", + ) + + assert params.provider_affinity_header == "X-Conversation-Id" + assert params.model_dump(exclude_none=True)["provider_affinity_header"] == "X-Conversation-Id" + + +@pytest.mark.parametrize( + "header", + [ + "Authorization", + "Proxy-Authorization", + "Cookie", + "Set-Cookie", + "Host", + "Content-Length", + "Content-Type", + "X-API-Key", + ], +) +def test_provider_affinity_header_rejects_sensitive_or_transport_headers(header: str): + with pytest.raises(ValueError, match="provider_affinity_header"): + LiteLLM_Params( + model="openai/gpt-4o-mini", + provider_affinity_header=header, + ) + + +@pytest.mark.parametrize("header", ["", "X Conversation Id", "X-Conversation-Id\r\nInjected: true"]) +def test_provider_affinity_header_rejects_invalid_header_names(header: str): + with pytest.raises(ValueError, match="provider_affinity_header"): + LiteLLM_Params( + model="openai/gpt-4o-mini", + provider_affinity_header=header, + ) + + def test_model_info_parses_access_windows_time_strings(): import datetime diff --git a/ui/litellm-dashboard/src/lib/http/schema.d.ts b/ui/litellm-dashboard/src/lib/http/schema.d.ts index a53115b7af2..be1e000bd66 100644 --- a/ui/litellm-dashboard/src/lib/http/schema.d.ts +++ b/ui/litellm-dashboard/src/lib/http/schema.d.ts @@ -31476,6 +31476,8 @@ export interface components { output_cost_per_video_token?: number | null; /** Output Vector Size */ output_vector_size?: number | null; + /** Provider Affinity Header */ + provider_affinity_header?: string | null; /** Quality Router Config */ quality_router_config?: { [key: string]: unknown; @@ -42364,6 +42366,8 @@ export interface components { output_cost_per_video_token?: number | null; /** Output Vector Size */ output_vector_size?: number | null; + /** Provider Affinity Header */ + provider_affinity_header?: string | null; /** Quality Router Config */ quality_router_config?: { [key: string]: unknown; From c6c3881d7f17d392856b779e89881b8ed23355d0 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 13:31:58 -0700 Subject: [PATCH 023/101] fix(proxy): share model rate-limit buckets between a model_group_alias and its target (#42516) * fix(proxy): share model rate-limit buckets between a model_group_alias and its target A request sent under a model_group_alias counted in its own per-key, per-team, per-org, and per-project model bucket, so a key could double a deployment's default_api_key_rpm_limit / tpm_limit by alternating the alias and the model group name, and a metadata model_rpm_limit / model_tpm_limit keyed by the model group never applied to alias requests. The limiter now resolves the requested name to its model group before keying any model bucket, looks the limit up by the requested name first and the model group second, and charges post-call tokens to the same bucket. * fix(proxy): charge the model group resolved at admission when reconciling reserved tokens --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- .../hooks/parallel_request_limiter_v3.py | 222 +++++++++--------- .../coverage_registry/quota_management.yaml | 1 + tests/e2e/gateway/stage_mirror_ci_config.yml | 7 + .../test_model_group_alias_rate_limit_e2e.py | 85 +++++++ .../hooks/test_parallel_request_limiter_v3.py | 187 ++++++++++++++- .../proxy/hooks/test_tpm_concurrent.py | 3 +- 6 files changed, 389 insertions(+), 116 deletions(-) create mode 100644 tests/e2e/quota_management/ratelimit/test_model_group_alias_rate_limit_e2e.py diff --git a/litellm/proxy/hooks/parallel_request_limiter_v3.py b/litellm/proxy/hooks/parallel_request_limiter_v3.py index 9d35178891c..33744906b13 100644 --- a/litellm/proxy/hooks/parallel_request_limiter_v3.py +++ b/litellm/proxy/hooks/parallel_request_limiter_v3.py @@ -63,6 +63,7 @@ from litellm.router_utils.add_retry_fallback_headers import ( ensure_response_additional_headers, response_has_hidden_params, ) +from litellm.router_utils.common_utils import resolve_model_group_alias from litellm.types.caching import RedisPipelineIncrementOperation from litellm.types.llms.openai import BaseLiteLLMOpenAIResponseObject, ResponseAPIUsage from litellm.types.utils import ( @@ -91,6 +92,26 @@ else: _REQUEST_RATE_LIMIT_DATA: Final = TypeAdapter(Mapping[str, object]) +@dataclass(frozen=True, slots=True) +class RateLimitedModel: + requested: str + group: str + + def limit_in(self, limits: Mapping[str, int] | None) -> int | None: + if limits is None: + return None + requested_limit: Final = limits.get(self.requested) + return requested_limit if requested_limit is not None else limits.get(self.group) + + +def _resolve_model_group_alias_via_proxy_router(model: str) -> str | None: + from litellm.proxy.proxy_server import llm_router + + if llm_router is None: + return None + return resolve_model_group_alias(llm_router.model_group_alias, model) + + def _sibling_counter_keys(window_key: str) -> tuple[str, str]: prefix: Final = window_key.removesuffix(":window") return f"{prefix}:requests", f"{prefix}:tokens" @@ -546,7 +567,7 @@ class RequestRateLimiterStash: parallel_slot: ParallelSlotAcquisition | None = None parallel_slot_release_lock: asyncio.Lock = field(default_factory=asyncio.Lock, repr=False, compare=False) reserved_tokens: int = 0 - reserved_model: str | None = None + reserved_model: RateLimitedModel | None = None reserved_scopes: frozenset[tuple[str, str]] = field(default_factory=frozenset) itpm_reserved_tokens: int = 0 itpm_reserved_scopes: frozenset[tuple[str, str]] = field(default_factory=frozenset) @@ -626,9 +647,11 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): self, internal_usage_cache: InternalUsageCache, time_provider: Callable[[], datetime] | None = None, + model_group_resolver: Callable[[str], str | None] = _resolve_model_group_alias_via_proxy_router, ): self.internal_usage_cache = internal_usage_cache self._time_provider = time_provider or datetime.now + self._model_group_resolver = model_group_resolver if self.internal_usage_cache.dual_cache.redis_cache is not None: self.batch_rate_limiter_script = self.internal_usage_cache.dual_cache.redis_cache.async_register_script( BATCH_RATE_LIMITER_SCRIPT @@ -2346,6 +2369,14 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): if response["overall_code"] == "OVER_LIMIT": self._handle_rate_limit_error(response, descriptors, requested_model) + def _rate_limited_model(self, requested_model: str | None) -> RateLimitedModel | None: + if not requested_model: + return None + return RateLimitedModel( + requested=requested_model, + group=self._model_group_resolver(requested_model) or requested_model, + ) + def create_organization_rate_limit_descriptor( self, user_api_key_dict: UserAPIKeyAuth, requested_model: str | None = None ) -> list[RateLimitDescriptor]: @@ -2367,43 +2398,28 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): ) ) - # Model specific org rate limits - if ( + model: Final = self._rate_limited_model(requested_model) + if model is None: + return descriptors + model_specific_tpm_limit: Final = model.limit_in( + get_model_rate_limit_from_metadata(user_api_key_dict, "organization_metadata", "model_tpm_limit") + ) + model_specific_rpm_limit: Final = model.limit_in( get_model_rate_limit_from_metadata(user_api_key_dict, "organization_metadata", "model_rpm_limit") - is not None - or get_model_rate_limit_from_metadata(user_api_key_dict, "organization_metadata", "model_tpm_limit") - is not None - ): - _tpm_limit_for_team_model: Final = ( - get_model_rate_limit_from_metadata(user_api_key_dict, "organization_metadata", "model_tpm_limit") or {} + ) + if model_specific_tpm_limit is None and model_specific_rpm_limit is None: + return descriptors + descriptors.append( + RateLimitDescriptor( + key="model_per_organization", + value=f"{user_api_key_dict.org_id}:{model.group}", + rate_limit={ + "requests_per_unit": model_specific_rpm_limit, + "tokens_per_unit": model_specific_tpm_limit, + "window_size": self.window_size, + }, ) - _rpm_limit_for_team_model: Final = ( - get_model_rate_limit_from_metadata(user_api_key_dict, "organization_metadata", "model_rpm_limit") or {} - ) - - should_check_rate_limit = False - if requested_model in _tpm_limit_for_team_model or requested_model in _rpm_limit_for_team_model: - should_check_rate_limit = True - - if should_check_rate_limit: - model_specific_tpm_limit = None - model_specific_rpm_limit = None - if requested_model in _tpm_limit_for_team_model: - model_specific_tpm_limit = _tpm_limit_for_team_model[requested_model] - if requested_model in _rpm_limit_for_team_model: - model_specific_rpm_limit = _rpm_limit_for_team_model[requested_model] - descriptors.append( - RateLimitDescriptor( - key="model_per_organization", - value=f"{user_api_key_dict.org_id}:{requested_model}", - rate_limit={ - "requests_per_unit": model_specific_rpm_limit, - "tokens_per_unit": model_specific_tpm_limit, - "window_size": self.window_size, - }, - ) - ) - + ) return descriptors def _add_model_per_key_rate_limit_descriptor( @@ -2425,34 +2441,22 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): get_key_model_tpm_limit, ) - if not requested_model: + model: Final = self._rate_limited_model(requested_model) + if model is None: return - - _tpm_limit_for_key_model = get_key_model_tpm_limit(user_api_key_dict, model_name=requested_model) - _rpm_limit_for_key_model = get_key_model_rpm_limit(user_api_key_dict, model_name=requested_model) - - if _tpm_limit_for_key_model is None and _rpm_limit_for_key_model is None: - return - - _tpm_limit_for_key_model = _tpm_limit_for_key_model or {} - _rpm_limit_for_key_model = _rpm_limit_for_key_model or {} - - # Check if model has any rate limits configured - should_check_rate_limit: Final = ( - requested_model in _tpm_limit_for_key_model or requested_model in _rpm_limit_for_key_model + model_specific_tpm_limit: Final = model.limit_in( + get_key_model_tpm_limit(user_api_key_dict, model_name=model.group) ) - - if not should_check_rate_limit: + model_specific_rpm_limit: Final = model.limit_in( + get_key_model_rpm_limit(user_api_key_dict, model_name=model.group) + ) + if model_specific_tpm_limit is None and model_specific_rpm_limit is None: return - # Get model-specific limits - model_specific_tpm_limit: Final[int | None] = _tpm_limit_for_key_model.get(requested_model) - model_specific_rpm_limit: Final[int | None] = _rpm_limit_for_key_model.get(requested_model) - descriptors.append( RateLimitDescriptor( key="model_per_key", - value=f"{user_api_key_dict.api_key}:{requested_model}", + value=f"{user_api_key_dict.api_key}:{model.group}", rate_limit={ "requests_per_unit": model_specific_rpm_limit, "tokens_per_unit": model_specific_tpm_limit, @@ -2955,32 +2959,30 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): def _key_owns_model_limit( self, user_api_key_dict: UserAPIKeyAuth, - requested_model: str, + model: RateLimitedModel, rate_limit_key: Literal["model_rpm_limit", "model_tpm_limit"], ) -> bool: - key_own_limits: Final = get_key_own_model_rate_limit(user_api_key_dict, rate_limit_key) - return key_own_limits is not None and key_own_limits.get(requested_model) is not None + return model.limit_in(get_key_own_model_rate_limit(user_api_key_dict, rate_limit_key)) is not None def _inherited_team_model_limit( self, user_api_key_dict: UserAPIKeyAuth, - requested_model: str, + model: RateLimitedModel, rate_limit_key: Literal["model_rpm_limit", "model_tpm_limit"], ) -> int | None: - team_limits: Final = get_model_rate_limit_from_metadata(user_api_key_dict, "team_metadata", rate_limit_key) - team_limit: Final = team_limits.get(requested_model) if team_limits else None - if team_limit is None: - return None - if self._key_owns_model_limit(user_api_key_dict, requested_model, rate_limit_key): + team_limit: Final = model.limit_in( + get_model_rate_limit_from_metadata(user_api_key_dict, "team_metadata", rate_limit_key) + ) + if team_limit is None or self._key_owns_model_limit(user_api_key_dict, model, rate_limit_key): return None return team_limit def _key_owns_model_tpm_limit_from_request_metadata( self, request_metadata: Mapping[str, object], - model_group: str | None, + model: RateLimitedModel | None, ) -> bool: - if model_group is None: + if model is None: return False key_view: Final = UserAPIKeyAuth.model_validate( { @@ -2988,7 +2990,7 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): "model_max_budget": request_metadata.get("user_api_key_model_max_budget") or {}, } ) - return self._key_owns_model_limit(key_view, model_group, "model_tpm_limit") + return self._key_owns_model_limit(key_view, model, "model_tpm_limit") def _add_team_model_rate_limit_descriptor_from_metadata( self, @@ -2996,16 +2998,17 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): requested_model: str | None, descriptors: list[RateLimitDescriptor], ) -> None: - if requested_model is None: + model: Final = self._rate_limited_model(requested_model) + if model is None: return - team_rpm_limit: Final = self._inherited_team_model_limit(user_api_key_dict, requested_model, "model_rpm_limit") - team_tpm_limit: Final = self._inherited_team_model_limit(user_api_key_dict, requested_model, "model_tpm_limit") + team_rpm_limit: Final = self._inherited_team_model_limit(user_api_key_dict, model, "model_rpm_limit") + team_tpm_limit: Final = self._inherited_team_model_limit(user_api_key_dict, model, "model_tpm_limit") if team_rpm_limit is None and team_tpm_limit is None: return descriptors.append( RateLimitDescriptor( key="model_per_team", - value=f"{user_api_key_dict.team_id}:{requested_model}", + value=f"{user_api_key_dict.team_id}:{model.group}", rate_limit={ "requests_per_unit": team_rpm_limit, "tokens_per_unit": team_tpm_limit, @@ -3021,34 +3024,28 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): descriptors: list[RateLimitDescriptor], ) -> None: """Add project model rate limit descriptor from project_metadata if applicable.""" - if ( - get_model_rate_limit_from_metadata(user_api_key_dict, "project_metadata", "model_rpm_limit") is not None - or get_model_rate_limit_from_metadata(user_api_key_dict, "project_metadata", "model_tpm_limit") is not None - ): - _tpm_limit_for_project_model: Final = ( - get_model_rate_limit_from_metadata(user_api_key_dict, "project_metadata", "model_tpm_limit") or {} + model: Final = self._rate_limited_model(requested_model) + if model is None: + return + model_specific_tpm_limit: Final = model.limit_in( + get_model_rate_limit_from_metadata(user_api_key_dict, "project_metadata", "model_tpm_limit") + ) + model_specific_rpm_limit: Final = model.limit_in( + get_model_rate_limit_from_metadata(user_api_key_dict, "project_metadata", "model_rpm_limit") + ) + if model_specific_tpm_limit is None and model_specific_rpm_limit is None: + return + descriptors.append( + RateLimitDescriptor( + key="model_per_project", + value=f"{user_api_key_dict.project_id}:{model.group}", + rate_limit={ + "requests_per_unit": model_specific_rpm_limit, + "tokens_per_unit": model_specific_tpm_limit, + "window_size": self.window_size, + }, ) - _rpm_limit_for_project_model: Final = ( - get_model_rate_limit_from_metadata(user_api_key_dict, "project_metadata", "model_rpm_limit") or {} - ) - should_check_rate_limit: Final = ( - requested_model in _tpm_limit_for_project_model or requested_model in _rpm_limit_for_project_model - ) - - if should_check_rate_limit and requested_model is not None: - model_specific_tpm_limit: Final = _tpm_limit_for_project_model.get(requested_model) - model_specific_rpm_limit: Final = _rpm_limit_for_project_model.get(requested_model) - descriptors.append( - RateLimitDescriptor( - key="model_per_project", - value=f"{user_api_key_dict.project_id}:{requested_model}", - rate_limit={ - "requests_per_unit": model_specific_rpm_limit, - "tokens_per_unit": model_specific_tpm_limit, - "window_size": self.window_size, - }, - ) - ) + ) def add_project_io_token_rate_limit_descriptors_from_metadata( self, @@ -3062,25 +3059,21 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): TPM descriptor above -- these give Bedrock Mantle-style separate input/output token quotas at the project level. """ - if requested_model is None or user_api_key_dict.project_id is None: + model: Final = self._rate_limited_model(requested_model) + if model is None or user_api_key_dict.project_id is None: return - itpm_limit_for_project_model: Final = ( + model_itpm_limit: Final = model.limit_in( get_model_rate_limit_from_metadata(user_api_key_dict, "project_metadata", "model_itpm_limit") - or {} # mutable-ok: metadata helper returns an optional mapping ) - otpm_limit_for_project_model: Final = ( + model_otpm_limit: Final = model.limit_in( get_model_rate_limit_from_metadata(user_api_key_dict, "project_metadata", "model_otpm_limit") - or {} # mutable-ok: metadata helper returns an optional mapping ) - model_itpm_limit: Final = itpm_limit_for_project_model.get(requested_model) - model_otpm_limit: Final = otpm_limit_for_project_model.get(requested_model) - if model_itpm_limit is None and model_otpm_limit is None: return - descriptor_value: Final = f"{user_api_key_dict.project_id}:{requested_model}" + descriptor_value: Final = f"{user_api_key_dict.project_id}:{model.group}" if model_itpm_limit is not None: descriptors.append( RateLimitDescriptor( @@ -3767,7 +3760,7 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): # the (actual - reserved) delta to those — unreserved # scopes get charged the full actual usage instead. stash.reserved_tokens = estimated_tokens - stash.reserved_model = requested_model + stash.reserved_model = self._rate_limited_model(requested_model) stash.reserved_scopes = frozenset( (d["key"], d["value"]) for d in descriptors @@ -4514,9 +4507,10 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): reserved_scopes: Final[frozenset[tuple[str, str]]] = stash.reserved_scopes if stash is not None else frozenset() # Reconciliation must target the same model-scoped counter that the # pre-call reservation incremented. If a reservation was made, - # ``reserved_model`` is authoritative; otherwise fall back to the - # router's ``model_group`` (covers the no-reservation charge path). - reconcile_model: Final = reserved_model or model_group + # ``reserved_model`` (resolved at admission, so an alias map reload + # mid-flight cannot move the charge) is authoritative; otherwise fall + # back to the router's ``model_group`` (the no-reservation charge path). + reconcile_model: Final = reserved_model if reserved_model is not None else self._rate_limited_model(model_group) pipeline_operations: Final[list[RedisPipelineIncrementOperation]] = [] @@ -4534,7 +4528,7 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): targets: Final = self._collect_tpm_scope_targets( standard_logging_metadata=standard_logging_metadata, kwargs=kwargs, - model_group=reconcile_model, + model_group=reconcile_model.group if reconcile_model is not None else None, ) charged_targets: Final = ( [target for target in targets if target[0] != "model_per_team"] diff --git a/tests/e2e/coverage_registry/quota_management.yaml b/tests/e2e/coverage_registry/quota_management.yaml index f6b38243896..8a0edf4a6ca 100644 --- a/tests/e2e/coverage_registry/quota_management.yaml +++ b/tests/e2e/coverage_registry/quota_management.yaml @@ -10,6 +10,7 @@ - {id: quota_management.ratelimit.redis_backed.blocks_over_limit, module: quota_management, tier: P0, behavior: ratelimit, variant: redis_backed, assertions: [blocks_over_limit], exercised_on: [chat_completions], source: "parallel_request_limiter_v3.py", rationale: "With Redis configured, RPM still enforces 429 across the shared limiter path customers run multi-replica"} - {id: quota_management.ratelimit.rpm.resets_after_window, module: quota_management, tier: P1, behavior: ratelimit, variant: rpm, assertions: [resets_after_window], exercised_on: [chat_completions], source: "parallel_request_limiter_v3.py", rationale: "Rate-limit window (LITELLM_RATE_LIMIT_WINDOW_SIZE, 60s default) expires; a blocked key serves again in the next window"} - {id: quota_management.ratelimit.rpm.headers_report_remaining, module: quota_management, tier: P1, behavior: ratelimit, variant: rpm, assertions: [headers_report_remaining], exercised_on: [chat_completions], source: "parallel_request_limiter_v3.py async_post_call_success_hook", rationale: "Successful responses carry x-ratelimit-api_key-{limit,remaining}-{requests,tokens} so clients can pace"} +- {id: quota_management.ratelimit.model_group_alias.shares_bucket, module: quota_management, tier: P1, behavior: ratelimit, variant: model_group_alias, assertions: [shares_bucket], exercised_on: [chat_completions], source: "parallel_request_limiter_v3.py:_add_model_per_key_rate_limit_descriptor", rationale: "A model_group_alias draws on the same per-key deployment rpm bucket as the resolved model group, so alias plus real-name traffic cannot exceed the configured limit"} - {id: quota_management.ratelimit.priority_generous.picks_under_tpm, module: quota_management, tier: P1, behavior: ratelimit, variant: priority_generous, assertions: [picks_under_tpm], exercised_on: [chat_completions, messages], source: "dynamic_rate_limiter_v3.py:36-52", rationale: "Generous mode (<80% sat) allows priority borrowing"} - {id: quota_management.ratelimit.priority_strict.picks_under_tpm, module: quota_management, tier: P1, behavior: ratelimit, variant: priority_strict, assertions: [picks_under_tpm], exercised_on: [chat_completions, messages], source: "dynamic_rate_limiter_v3.py:53-71", rationale: "Strict mode (>=80% sat) enforces priority fairness"} - {id: quota_management.budget.key.blocks_over_limit, module: quota_management, tier: P0, behavior: budget, variant: key, assertions: [blocks_over_limit], exercised_on: [chat_completions], source: "proxy/auth/auth_checks.py", rationale: "A key's max_budget blocks further paid calls once spend crosses it"} diff --git a/tests/e2e/gateway/stage_mirror_ci_config.yml b/tests/e2e/gateway/stage_mirror_ci_config.yml index 03167692727..02a131f60ae 100644 --- a/tests/e2e/gateway/stage_mirror_ci_config.yml +++ b/tests/e2e/gateway/stage_mirror_ci_config.yml @@ -43,6 +43,8 @@ router_settings: num_retries: 3 allowed_fails: 5 cooldown_time: 30 + model_group_alias: + e2e-alias-rl-alias: e2e-alias-rl-target model_list: - model_name: gpt-5.5 @@ -63,6 +65,11 @@ model_list: litellm_params: model: gemini/gemini-2.5-flash api_key: os.environ/GEMINI_API_KEY + - model_name: e2e-alias-rl-target + litellm_params: + model: anthropic/claude-haiku-4-5 + api_key: os.environ/ANTHROPIC_API_KEY + default_api_key_rpm_limit: 3 - model_name: openai-text-embedding-3-small litellm_params: model: openai/text-embedding-3-small diff --git a/tests/e2e/quota_management/ratelimit/test_model_group_alias_rate_limit_e2e.py b/tests/e2e/quota_management/ratelimit/test_model_group_alias_rate_limit_e2e.py new file mode 100644 index 00000000000..1c3fff47b78 --- /dev/null +++ b/tests/e2e/quota_management/ratelimit/test_model_group_alias_rate_limit_e2e.py @@ -0,0 +1,85 @@ +"""Live e2e: a model group alias must share its per-key deployment rate-limit +bucket with the model group it resolves to. + +Covers quota_management.ratelimit.model_group_alias.shares_bucket: the proxy +config declares `e2e-alias-rl-target` (a cheap Anthropic deployment) with +`default_api_key_rpm_limit: 3` and `router_settings.model_group_alias` mapping +`e2e-alias-rl-alias` -> `e2e-alias-rl-target`. Both spellings must draw on +one per-key rpm bucket, so a key that exhausts the limit on one spelling is +blocked on the other spelling inside the same window; each test in this file +exhausts the budget on one name and asserts the other name 429s. + +All calls of one test must land inside a single window +(LITELLM_RATE_LIMIT_WINDOW_SIZE, 60s default), which real chat latency +comfortably allows. +""" + +from __future__ import annotations + +import time + +import pytest +from e2e_config import unique_marker +from e2e_http import StreamingResponse, require_successful_call +from quota_client import QuotaClient + +pytestmark = pytest.mark.e2e + +MODEL_GROUP = "e2e-alias-rl-target" +MODEL_ALIAS = "e2e-alias-rl-alias" +RPM_LIMIT = 3 +WINDOW_SECONDS = 60 +LAST_CALL_LATENCY_MARGIN_SECONDS = 10 + + +def _chat(client: QuotaClient, key: str, model: str) -> StreamingResponse: + return client.chat(key, model, f"reply with one word {unique_marker()}") + + +def _exhaust_rpm(client: QuotaClient, key: str, model: str) -> float: + """Send RPM_LIMIT successful calls on `model`, opening the rate-limit + window; returns the send timestamp of the first call as a lower bound on + the window start. A fresh key may briefly 401 until the data plane's auth + cache picks it up, so retry on 401 to a deadline; a 401 never reaches the + rate limiter.""" + deadline = time.monotonic() + client.proxy.poll_timeout + first_sent_at: float | None = None + sent = 0 + while sent < RPM_LIMIT: + if first_sent_at is None: + first_sent_at = time.monotonic() + outcome = _chat(client, key, model) + if outcome.status_code == 401 and time.monotonic() < deadline: + time.sleep(client.proxy.poll_interval) + continue + require_successful_call(outcome) + sent += 1 + assert first_sent_at is not None + return first_sent_at + + +def _assert_blocked_inside_window( + client: QuotaClient, key: str, model: str, window_opened_at: float +) -> StreamingResponse: + assert time.monotonic() < window_opened_at + WINDOW_SECONDS - LAST_CALL_LATENCY_MARGIN_SECONDS, ( + f"the {RPM_LIMIT} exhaust calls took too long; the follow-up call could land in the " + "next window and mask a shared-bucket regression" + ) + outcome = _chat(client, key, model) + assert outcome.status_code == 429, ( + f"{model} must share its rpm bucket with the model group/alias that was already " + f"exhausted, expected a 429 but got {outcome.status_code}: {outcome.body[:300]}" + ) + return outcome + + +class TestModelGroupAliasRateLimit: + @pytest.mark.covers("quota_management.ratelimit.model_group_alias.shares_bucket") + def test_alias_shares_rpm_bucket_with_model_group(self, client: QuotaClient, scoped_key: str) -> None: + opened_at = _exhaust_rpm(client, scoped_key, MODEL_GROUP) + _assert_blocked_inside_window(client, scoped_key, MODEL_ALIAS, opened_at) + + @pytest.mark.covers("quota_management.ratelimit.model_group_alias.shares_bucket") + def test_model_group_shares_rpm_bucket_with_alias(self, client: QuotaClient, scoped_key: str) -> None: + opened_at = _exhaust_rpm(client, scoped_key, MODEL_ALIAS) + _assert_blocked_inside_window(client, scoped_key, MODEL_GROUP, opened_at) diff --git a/tests/test_litellm/proxy/hooks/test_parallel_request_limiter_v3.py b/tests/test_litellm/proxy/hooks/test_parallel_request_limiter_v3.py index 0f19675edb9..8c0dcd3383c 100644 --- a/tests/test_litellm/proxy/hooks/test_parallel_request_limiter_v3.py +++ b/tests/test_litellm/proxy/hooks/test_parallel_request_limiter_v3.py @@ -26,6 +26,7 @@ from litellm.proxy.hooks.parallel_request_limiter_v3 import ( PARALLEL_REQUEST_SLOT_TTL_SECONDS, ParallelSlotAcquisition, RateLimitDescriptor, + RateLimitedModel, RateLimitResponse, RequestRateLimiterStash, _request_stash, @@ -3367,7 +3368,7 @@ async def test_pre_call_hook_keeps_internal_stash_out_of_request_body(): stash = get_request_stash() assert stash is not None assert stash.reserved_tokens > 0 - assert stash.reserved_model == "gpt-4o-mini" + assert stash.reserved_model == RateLimitedModel(requested="gpt-4o-mini", group="gpt-4o-mini") assert stash.reserved_scopes == frozenset({("api_key", _api_key)}) @@ -6965,3 +6966,187 @@ def test_rate_limit_error_reports_reset_time_in_utc_on_a_non_utc_proxy(process_t "Rate limit exceeded for api_key: sk-test. Limit type: requests. " f"Current limit: 2, Remaining: 0. Limit resets at: {expected_reset}" ) + + +def _resolve_alias_to_target(model: str) -> str | None: + return "target" if model == "alias" else None + + +async def _rpm_request(handler: _PROXY_MaxParallelRequestsHandler, cache: DualCache, auth: UserAPIKeyAuth, model: str) -> None: + await handler.async_pre_call_hook(user_api_key_dict=auth, cache=cache, data={"model": model}, call_type="acompletion") + + +@pytest.mark.asyncio +@pytest.mark.parametrize("first_name, second_name", [("target", "alias"), ("alias", "target")]) +async def test_model_group_alias_shares_deployment_default_rpm_bucket_with_its_target( + monkeypatch: pytest.MonkeyPatch, first_name: str, second_name: str +) -> None: + import litellm.proxy.proxy_server as proxy_server + + router: Final = Router( + model_list=[ + { + "model_name": "target", + "litellm_params": {"model": "openai/gpt-test", "api_key": "test-key", "default_api_key_rpm_limit": 2}, + "model_info": {"id": "target-deployment"}, + } + ], + model_group_alias={"alias": "target"}, + ) + monkeypatch.setattr(proxy_server, "llm_router", router) + cache: Final = DualCache() + handler: Final = _PROXY_MaxParallelRequestsHandler(internal_usage_cache=InternalUsageCache(cache)) + auth: Final = UserAPIKeyAuth(api_key=hash_token("sk-alias-default")) + + await _rpm_request(handler, cache, auth, first_name) + await _rpm_request(handler, cache, auth, first_name) + with pytest.raises(HTTPException) as exc: + await _rpm_request(handler, cache, auth, second_name) + + assert exc.value.status_code == 429 + assert "model_per_key" in str(exc.value.detail) + assert f"{auth.api_key}:target" in str(exc.value.detail) + + +@pytest.mark.asyncio +@pytest.mark.parametrize("first_name, second_name", [("target", "alias"), ("alias", "target")]) +@pytest.mark.parametrize( + "limits, counter_scope", + [ + ({"metadata": {"model_rpm_limit": {"target": 1}}}, "model_per_key"), + ( + { + "team_id": "t", + "metadata": {"model_rpm_limit": {"other-model": 100}}, + "team_metadata": {"model_rpm_limit": {"target": 1}}, + }, + "model_per_team", + ), + ({"org_id": "o", "organization_metadata": {"model_rpm_limit": {"target": 1}}}, "model_per_organization"), + ({"project_id": "p", "project_metadata": {"model_rpm_limit": {"target": 1}}}, "model_per_project"), + ], + ids=["key_metadata", "team_metadata", "organization_metadata", "project_metadata"], +) +async def test_model_group_alias_shares_metadata_model_rpm_bucket_with_its_target( + limits: dict[str, object], counter_scope: str, first_name: str, second_name: str +) -> None: + cache: Final = DualCache() + handler: Final = _PROXY_MaxParallelRequestsHandler( + internal_usage_cache=InternalUsageCache(cache), model_group_resolver=_resolve_alias_to_target + ) + auth: Final = UserAPIKeyAuth(api_key=hash_token("sk-alias-metadata"), **limits) + + await _rpm_request(handler, cache, auth, first_name) + with pytest.raises(HTTPException) as exc: + await _rpm_request(handler, cache, auth, second_name) + + assert exc.value.status_code == 429 + assert counter_scope in str(exc.value.detail) + assert ":target" in str(exc.value.detail) + + +@pytest.mark.asyncio +async def test_model_rpm_limit_keyed_by_the_alias_name_still_limits_alias_requests_only() -> None: + cache: Final = DualCache() + handler: Final = _PROXY_MaxParallelRequestsHandler( + internal_usage_cache=InternalUsageCache(cache), model_group_resolver=_resolve_alias_to_target + ) + auth: Final = UserAPIKeyAuth(api_key=hash_token("sk-alias-keyed"), metadata={"model_rpm_limit": {"alias": 1}}) + + await _rpm_request(handler, cache, auth, "alias") + with pytest.raises(HTTPException) as exc: + await _rpm_request(handler, cache, auth, "alias") + assert exc.value.status_code == 429 + assert "model_per_key" in str(exc.value.detail) + + await _rpm_request(handler, cache, auth, "target") + + +@pytest.mark.parametrize( + "key_metadata, charges_team_model_pool", + [({}, True), ({"model_tpm_limit": {"target": 500}}, False)], + ids=["no_key_override", "key_owns_target_tpm_limit"], +) +def test_success_tpm_accounting_charges_the_alias_target_bucket( + key_metadata: dict[str, object], charges_team_model_pool: bool +) -> None: + handler: Final = _PROXY_MaxParallelRequestsHandler( + internal_usage_cache=InternalUsageCache(DualCache()), model_group_resolver=_resolve_alias_to_target + ) + response: Final = ModelResponse( + id="alias-tpm", + object="chat.completion", + created=int(datetime.now().timestamp()), + model="alias", + usage=Usage(prompt_tokens=100, completion_tokens=50, total_tokens=150), + choices=[], + ) + kwargs: Final = { + "standard_logging_object": { + "metadata": {"user_api_key_hash": hash_token("sk-alias-tpm"), "user_api_key_team_id": "t"} + }, + "litellm_params": { + "metadata": { + "model_group": "alias", + "user_api_key_metadata": key_metadata, + "user_api_key_team_metadata": {"model_tpm_limit": {"target": 500}}, + } + }, + "model": "alias", + } + + ops: Final = handler._build_success_event_pipeline_operations( + kwargs=kwargs, response_obj=response, rate_limit_type="output" + ) + + charged_keys: Final = {op["key"] for op in ops} + assert handler.create_rate_limit_keys("model_per_key", f"{hash_token('sk-alias-tpm')}:target", "tokens") in charged_keys + assert not any(":alias" in key for key in charged_keys) + team_pool_key: Final = handler.create_rate_limit_keys("model_per_team", "t:target", "tokens") + assert (team_pool_key in charged_keys) is charges_team_model_pool + + +@pytest.mark.asyncio +async def test_success_tpm_accounting_keeps_the_admission_target_after_an_alias_reload() -> None: + alias_map: Final[dict[str, str]] = {"alias": "target-a"} + cache: Final = DualCache() + handler: Final = _PROXY_MaxParallelRequestsHandler( + internal_usage_cache=InternalUsageCache(cache), model_group_resolver=alias_map.get + ) + key_metadata: Final = {"model_tpm_limit": {"target-a": 1000, "target-b": 1000}} + auth: Final = UserAPIKeyAuth(api_key=hash_token("sk-alias-reload"), metadata=key_metadata) + + await handler.async_pre_call_hook( + user_api_key_dict=auth, + cache=cache, + data={"model": "alias", "messages": [{"role": "user", "content": "hello"}], "max_tokens": 10}, + call_type="acompletion", + ) + stash: Final = get_request_stash() + assert stash is not None + assert stash.reserved_model == RateLimitedModel(requested="alias", group="target-a") + assert stash.reserved_tokens > 0 + + alias_map["alias"] = "target-b" + response: Final = ModelResponse( + id="alias-reload", + object="chat.completion", + created=int(datetime.now().timestamp()), + model="alias", + usage=Usage(prompt_tokens=100, completion_tokens=50, total_tokens=150), + choices=[], + ) + kwargs: Final = { + "standard_logging_object": {"metadata": {"user_api_key_hash": auth.api_key}}, + "litellm_params": {"metadata": {"model_group": "alias", "user_api_key_metadata": key_metadata}}, + "model": "alias", + } + + ops: Final = handler._build_success_event_pipeline_operations( + kwargs=kwargs, response_obj=response, rate_limit_type="total" + ) + + admission_bucket: Final = handler.create_rate_limit_keys("model_per_key", f"{auth.api_key}:target-a", "tokens") + charged: Final = {op["key"]: op["increment_value"] for op in ops} + assert charged[admission_bucket] == 150 - stash.reserved_tokens + assert not any(":target-b" in key for key in charged) diff --git a/tests/test_litellm/proxy/hooks/test_tpm_concurrent.py b/tests/test_litellm/proxy/hooks/test_tpm_concurrent.py index bdaca9ffc2d..e6795bb22f3 100644 --- a/tests/test_litellm/proxy/hooks/test_tpm_concurrent.py +++ b/tests/test_litellm/proxy/hooks/test_tpm_concurrent.py @@ -25,6 +25,7 @@ from litellm.proxy._types import UserAPIKeyAuth from litellm.proxy.hooks.parallel_request_limiter_v3 import ( PROJECT_ITPM_DESCRIPTOR_KEY, PROJECT_OTPM_DESCRIPTOR_KEY, + RateLimitedModel, _AUDIO_BYTES_PER_TOKEN, _PROXY_MaxParallelRequestsHandler_v3 as RateLimitHandler, ) @@ -308,7 +309,7 @@ async def test_model_scope_refund_targets_reserved_model(rate_limiter): stash = get_or_create_request_stash() stash.reserved_tokens = 100 - stash.reserved_model = reserved_model + stash.reserved_model = RateLimitedModel(requested=reserved_model, group=reserved_model) stash.reserved_scopes = frozenset({("model_per_team", f"{team_id}:{reserved_model}")}) mock_kwargs = { From 1c602334ee7175f9efcb06c570b642928e99b293 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 13:42:00 -0700 Subject: [PATCH 024/101] test(e2e): one request lands the same spend on every surface (#42540) * test(e2e): one request lands the same spend on every surface One priced chat request must show the same response_cost on the spend log row, /key/info, /team/info, the usage export's /user/daily/activity/aggregated row, and the litellm_spend_metric Prometheus sample; each is a separate writer, so the test fails naming the surface that drifted * fix(e2e): scrape every replica's /metrics/ and enable prometheus in the replay lane --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- .../coverage_registry/quota_management.yaml | 1 + tests/e2e/gateway/record_replay_ci_config.yml | 3 + .../spend_tracking/spend_e2e_client.py | 79 ++++++++- .../test_spend_surface_consistency_e2e.py | 161 ++++++++++++++++++ 4 files changed, 241 insertions(+), 3 deletions(-) create mode 100644 tests/e2e/quota_management/spend_tracking/test_spend_surface_consistency_e2e.py diff --git a/tests/e2e/coverage_registry/quota_management.yaml b/tests/e2e/coverage_registry/quota_management.yaml index 8a0edf4a6ca..5432c5095a2 100644 --- a/tests/e2e/coverage_registry/quota_management.yaml +++ b/tests/e2e/coverage_registry/quota_management.yaml @@ -46,6 +46,7 @@ - {id: quota_management.spend_tracking.cache_hit.zero_cost, module: quota_management, tier: P1, behavior: spend_tracking, variant: cache_hit, assertions: [zero_cost], exercised_on: [chat_completions], source: "proxy/spend_tracking/spend_tracking_utils.py", rationale: "A response-cache hit logs at zero cost with the cache-hit marker"} - {id: quota_management.spend_tracking.key_rollup.matches_sum_of_logs, module: quota_management, tier: P1, behavior: spend_tracking, variant: key_rollup, assertions: [matches_sum_of_logs], exercised_on: [chat_completions], source: "proxy/db/db_spend_update_writer.py", rationale: "A key's rolled-up spend equals the sum of its log rows"} - {id: quota_management.spend_tracking.concurrent_burst.loses_no_spend, module: quota_management, tier: P1, behavior: spend_tracking, variant: concurrent_burst, assertions: [loses_no_spend], exercised_on: [chat_completions], source: "proxy/db/db_spend_update_writer.py", rationale: "Concurrent calls all land as spend; no row lost to write contention"} +- {id: quota_management.spend_tracking.surface_consistency.matches_every_surface, module: quota_management, tier: P1, behavior: spend_tracking, variant: surface_consistency, assertions: [matches_every_surface], exercised_on: [chat_completions], source: "proxy/db/db_spend_update_writer.py", rationale: "One priced request lands the same response_cost on the spend log row, /key/info, /team/info, the usage export's /user/daily/activity/aggregated row, and the litellm_spend_metric Prometheus sample; each is a separate writer, so a rounding, dropped, or double-counted write on one drifts it from the rest (LIT-3620, LIT-5045)"} - {id: quota_management.spend_tracking.tags.attributes_spend, module: quota_management, tier: P1, behavior: spend_tracking, variant: tags, assertions: [attributes_spend], exercised_on: [chat_completions], source: "proxy/spend_tracking/spend_tracking_utils.py", rationale: "Request tags round-trip to spend rows and tag rollups match tagged logs"} - {id: quota_management.spend_tracking.end_user.attributes_spend, module: quota_management, tier: P1, behavior: spend_tracking, variant: end_user, assertions: [attributes_spend], exercised_on: [chat_completions], source: "proxy/spend_tracking/spend_tracking_utils.py", rationale: "user= attribution lands the end-user id on the spend row"} - {id: quota_management.spend_tracking.per_model.writes_own_rows, module: quota_management, tier: P2, behavior: spend_tracking, variant: per_model, assertions: [writes_own_rows], exercised_on: [chat_completions], source: "proxy/spend_tracking/spend_tracking_utils.py", rationale: "Each model on a shared key gets its own spend row"} diff --git a/tests/e2e/gateway/record_replay_ci_config.yml b/tests/e2e/gateway/record_replay_ci_config.yml index 5b3db0ff530..bc1f3f10562 100644 --- a/tests/e2e/gateway/record_replay_ci_config.yml +++ b/tests/e2e/gateway/record_replay_ci_config.yml @@ -2,3 +2,6 @@ general_settings: master_key: os.environ/LITELLM_MASTER_KEY store_model_in_db: true disable_model_info_refresh: true + +litellm_settings: + callbacks: ["prometheus"] diff --git a/tests/e2e/quota_management/spend_tracking/spend_e2e_client.py b/tests/e2e/quota_management/spend_tracking/spend_e2e_client.py index b7f59fe5f89..8b63b063e14 100644 --- a/tests/e2e/quota_management/spend_tracking/spend_e2e_client.py +++ b/tests/e2e/quota_management/spend_tracking/spend_e2e_client.py @@ -12,9 +12,10 @@ helpers from one place. from __future__ import annotations import time -from collections.abc import Callable +from collections.abc import Callable, Mapping from dataclasses import dataclass from datetime import datetime, timedelta, timezone +from types import MappingProxyType from typing import Final from e2e_config import unique_marker @@ -48,6 +49,7 @@ from models import ( SpendLogsPageParams, SpendTagsResponse, TagSpend, + TeamInfoParams, UserDeleteBody, UserDeleteResponse, UserNewBody, @@ -57,6 +59,8 @@ from models import ( from proxy_client import Converged, ProxyClient, await_converged from pydantic import BaseModel, Field +METRICS_PATH: Final = "/metrics/" + __all__ = [ "BatchCreateBody", "CallbackLogMetadata", @@ -189,6 +193,7 @@ class DailyActivityKeyMetadata(BaseModel): class DailyActivityKeyMetrics(BaseModel): api_requests: int = 0 + spend: float = 0.0 class DailyActivityKeyBreakdown(BaseModel): @@ -209,6 +214,14 @@ class DailyActivityResponse(BaseModel): results: list[DailyActivityRow] = [] +class TeamInfoSpend(BaseModel): + spend: float | None = None + + +class TeamInfoSpendResponse(BaseModel): + team_info: TeamInfoSpend + + def _chat_body( model: str, content: str, @@ -334,6 +347,42 @@ class SpendClient: time.sleep(self.proxy.poll_interval) return spend + def team_spend(self, team_id: str) -> float: + return ( + unwrap( + self.proxy.transport.get( + "/team/info", + headers=self.proxy.transport.master, + params=TeamInfoParams(team_id=team_id), + response_type=TeamInfoSpendResponse, + ) + ).team_info.spend + or 0.0 + ) + + def poll_team_spend(self, team_id: str, *, minimum: float = 0.0) -> float: + outcome: Final = await_converged( + lambda: self.team_spend(team_id), + converged=lambda spend: spend > minimum, + timeout=self.proxy.poll_timeout, + interval=self.proxy.poll_interval, + now=time.monotonic, + sleep=time.sleep, + ) + return outcome.result if isinstance(outcome, Converged) else outcome.last_result + + def scrape_metrics(self) -> Mapping[str, ProbeResult]: + """GET /metrics/ on every replica in PROXY_REPLICA_URLS, keyed by replica. The + counter is per pod, so the union of the replicas is the fleet's exposition; the + trailing slash is the mounted app's own path, since bare /metrics answers a 307 + whose Location drops the port behind a Host-rewriting balancer.""" + return MappingProxyType( + { + replica: transport.probe(METRICS_PATH, params=NoBody()) + for replica, transport in self.proxy.replicas.items() + } + ) + def spend_logs_page( self, *, api_key: str | None, page: int, page_size: int ) -> SpendLogsPage: @@ -500,9 +549,21 @@ class SpendClient: return self.proxy.transport.probe("/health", params=HealthParams(model=model)) def daily_activity_for_key(self, token: str, *, start: datetime, end: datetime) -> DailyActivityKeyBreakdown | None: + return self._key_breakdown("/user/daily/activity", token, start=start, end=end) + + def usage_export_row_for_key( + self, token: str, *, start: datetime, end: datetime + ) -> DailyActivityKeyBreakdown | None: + """The key's row on /user/daily/activity/aggregated, the response the + dashboard's Export Usage Data CSV serializes.""" + return self._key_breakdown("/user/daily/activity/aggregated", token, start=start, end=end) + + def _key_breakdown( + self, route: str, token: str, *, start: datetime, end: datetime + ) -> DailyActivityKeyBreakdown | None: response: Final = unwrap( self.proxy.transport.get( - "/user/daily/activity", + route, headers=self.proxy.transport.master, params=DailyActivityParams( start_date=start.strftime("%Y-%m-%d"), @@ -519,9 +580,21 @@ class SpendClient: def poll_daily_activity_for_key( self, token: str, *, start: datetime, end: datetime, min_requests: int + ) -> DailyActivityKeyBreakdown | None: + return self._poll_key_breakdown(lambda: self.daily_activity_for_key(token, start=start, end=end), min_requests) + + def poll_usage_export_row_for_key( + self, token: str, *, start: datetime, end: datetime, min_requests: int + ) -> DailyActivityKeyBreakdown | None: + return self._poll_key_breakdown( + lambda: self.usage_export_row_for_key(token, start=start, end=end), min_requests + ) + + def _poll_key_breakdown( + self, fetch: Callable[[], DailyActivityKeyBreakdown | None], min_requests: int ) -> DailyActivityKeyBreakdown | None: outcome: Final = await_converged( - lambda: self.daily_activity_for_key(token, start=start, end=end), + fetch, converged=lambda found: found is not None and found.metrics.api_requests >= min_requests, timeout=self.proxy.poll_timeout, interval=self.proxy.poll_interval, diff --git a/tests/e2e/quota_management/spend_tracking/test_spend_surface_consistency_e2e.py b/tests/e2e/quota_management/spend_tracking/test_spend_surface_consistency_e2e.py new file mode 100644 index 00000000000..9033b9d75c4 --- /dev/null +++ b/tests/e2e/quota_management/spend_tracking/test_spend_surface_consistency_e2e.py @@ -0,0 +1,161 @@ +"""One priced request must land the same response_cost on every spend surface. + +A customer reconciles the bill from whichever surface they look at: the spend +log row, the key's and the team's rolled-up spend on /key/info and /team/info, +the usage page's Export Usage Data CSV (the dashboard serializes the +/user/daily/activity/aggregated rows it already holds; there is no server-side +CSV endpoint), and the litellm_spend_metric counter Prometheus scrapes. Each is +written by a different writer (the spend log insert, the key and team rollups in +db_spend_update_writer, the daily spend tables, the Prometheus success callback), +so one of them can drift without the others noticing: the cause of the +key-versus-log mismatch in LIT-3620 and the export-versus-console mismatch in +LIT-5045. The deployment carries its own per-token rates, so the expected cost +is computed from the returned usage rather than read off any one surface, and +every surface is held to that number. + +/metrics is per pod, so every replica the stack exports (PROXY_REPLICA_URLS) is +scraped directly and the samples merged; a stack that exports only its balancer +is scraped there until the pod that served the call answers. The request itself +is sent once. +""" + +from __future__ import annotations + +import time +from collections.abc import Mapping +from datetime import datetime, timedelta, timezone +from itertools import groupby +from math import isclose +from types import MappingProxyType +from typing import Final + +import pytest +from e2e_config import provider_edge_base, unique_marker +from e2e_http import ProbeResult +from lifecycle import ResourceManager +from models import ChatBody, ChatMessage, KeyGenerateBody, LiteLLMParamsBody, TeamNewBody +from prometheus_client.parser import text_string_to_metric_families +from proxy_client import Converged, await_converged +from spend_e2e_client import SpendClient, unwrap +from spend_reconciliation import INPUT_RATE, OUTPUT_RATE + +pytestmark = pytest.mark.e2e + +SPEND_METRIC: Final = "litellm_spend_metric_total" +KEY_HASH_LABEL: Final = "hashed_api_key" +TEAM_LABEL: Final = "team" + +SeriesLabels = tuple[tuple[str, str], ...] + + +def _spend_series_for_key(scrapes: Mapping[str, ProbeResult], token: str) -> Mapping[SeriesLabels, float]: + samples: Final = sorted( + (tuple(sorted(sample.labels.items())), sample.value) + for scrape in scrapes.values() + if scrape.status_code == 200 + for family in text_string_to_metric_families(scrape.body) + for sample in family.samples + if sample.name == SPEND_METRIC and sample.labels.get(KEY_HASH_LABEL) == token + ) + return MappingProxyType( + {labels: sum(value for _, value in group) for labels, group in groupby(samples, key=lambda sample: sample[0])} + ) + + +def _poll_spend_series_for_key(client: SpendClient, token: str) -> Mapping[SeriesLabels, float]: + outcome: Final = await_converged( + client.scrape_metrics, + converged=lambda scrapes: bool(_spend_series_for_key(scrapes, token)), + timeout=client.proxy.poll_timeout, + interval=client.proxy.poll_interval, + now=time.monotonic, + sleep=time.sleep, + ) + scrapes: Final = outcome.result if isinstance(outcome, Converged) else outcome.last_result + assert _spend_series_for_key(scrapes, token), ( + f"{SPEND_METRIC} never exposed a series for {KEY_HASH_LABEL}={token} on any replica; " + f"last scrape status per replica: {({replica: scrape.status_code for replica, scrape in scrapes.items()})}" + ) + return _spend_series_for_key(scrapes, token) + + +def _same_spend(actual: float | None, expected: float) -> bool: + return actual is not None and isclose(actual, expected, rel_tol=1e-6, abs_tol=1e-9) + + +class TestSpendSurfaceConsistency: + @pytest.mark.replayable + @pytest.mark.covers("quota_management.spend_tracking.surface_consistency.matches_every_surface") + def test_one_request_lands_the_same_spend_on_every_surface( + self, client: SpendClient, resources: ResourceManager + ) -> None: + started: Final = datetime.now(timezone.utc) + marker: Final = unique_marker() + base: Final = provider_edge_base("openai") + model: Final = f"e2e-spend-surfaces-{marker}" + model_id: Final = client.proxy.create_model( + model, + LiteLLMParamsBody( + model="openai/gpt-5.6-luna", + api_key="os.environ/OPENAI_API_KEY", + api_base=None if base is None else f"{base}/v1", + input_cost_per_token=INPUT_RATE, + output_cost_per_token=OUTPUT_RATE, + ), + ) + resources.defer(lambda: client.proxy.delete_model(model_id)) + team_id: Final = client.proxy.create_team(TeamNewBody(team_alias=f"e2e-spend-surfaces-{marker}")) + resources.defer(lambda: client.proxy.delete_team(team_id)) + record: Final = client.generate_key_record( + KeyGenerateBody(team_id=team_id, models=[model], key_alias=f"e2e-spend-surfaces-{marker}") + ) + resources.defer(lambda: client.proxy.delete_key(record.key)) + assert record.token, "/key/generate answered without the key's token hash" + token: Final = record.token + + response: Final = unwrap( + client.proxy.chat( + record.key, + ChatBody( + model=model, + messages=[ChatMessage(role="user", content=f"Reply with one word. {marker}")], + max_completion_tokens=128, + ), + ) + ) + usage: Final = response.usage + assert response.id, "successful response must have an ID" + assert usage is not None and usage.prompt_tokens and usage.completion_tokens, f"no billable usage: {usage}" + expected: Final = usage.prompt_tokens * INPUT_RATE + usage.completion_tokens * OUTPUT_RATE + + rows: Final = client.proxy.poll_logs_for_request_id(response.id) + assert len(rows) == 1, f"expected one spend row for {response.id}, saw {len(rows)}: {rows}" + row: Final = rows[0] + assert row.api_key == token, f"spend row keyed by {row.api_key}, not the key's token hash {token}" + assert row.team_id == team_id, f"spend row attributed to team {row.team_id}, not {team_id}" + assert row.status == "success", f"spend row status {row.status}" + + key_spend: Final = client.poll_key_spend(record.key, minimum=expected * 0.999999) + team_spend: Final = client.poll_team_spend(team_id, minimum=expected * 0.999999) + export_row: Final = client.poll_usage_export_row_for_key( + token, start=started - timedelta(days=1), end=datetime.now(timezone.utc), min_requests=1 + ) + assert export_row is not None, f"/user/daily/activity/aggregated never listed key {token} under api_keys" + series: Final = _poll_spend_series_for_key(client, token) + off_team: Final = tuple(labels for labels in series if dict(labels).get(TEAM_LABEL) != team_id) + assert not off_team, f"{SPEND_METRIC} series for the key carry a team other than {team_id}: {off_team}" + + observed: Final = MappingProxyType( + { + "/spend/logs row": row.spend, + "/key/info spend": key_spend, + "/team/info spend": team_spend, + "usage export row (/user/daily/activity/aggregated)": export_row.metrics.spend, + SPEND_METRIC: sum(series.values()), + } + ) + drifted: Final = tuple(surface for surface, spend in observed.items() if not _same_spend(spend, expected)) + assert not drifted, ( + f"response_cost {expected} (usage {usage.prompt_tokens}x{INPUT_RATE} + " + f"{usage.completion_tokens}x{OUTPUT_RATE}) drifted on {drifted}; every surface: {dict(observed)}" + ) From 7210403e2334504872f2c46220d9a0fd36eab622 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 13:44:25 -0700 Subject: [PATCH 025/101] fix(mcp): apply post-call rewrites without stale structured output (#41530) * fix(mcp): apply async_post_mcp_tool_call_hook content changes to the tool result Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(mcp): drop structuredContent when a post-call hook rewrites tool content Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(mcp): satisfy type discipline and result contract Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(mcp): document internal logging patch Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(mcp): avoid Final assignments inside callback loops Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(mcp): run every post-call hook and chain the rewritten content Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * chore(mcp): credit the original fix from #33403 Co-authored-by: eric Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(mcp): cover post-call logging fallback paths Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(mcp): cover proxy hook logging context Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(mcp): preserve native structured guardrail replacements * fix(mcp): invalidate stale structure after direct content edits * fix(mcp): reconcile direct edits after callback exceptions * fix(mcp): preserve successful in-place callback rewrites --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> Co-authored-by: eric Co-authored-by: Joshua Valluru <326636767+joshua-berri@users.noreply.github.com> --- litellm/integrations/custom_logger.py | 9 +- litellm/litellm_core_utils/litellm_logging.py | 67 +++-- .../_experimental/mcp_server/operations.py | 2 +- .../mcp/litellm_proxy_mcp_handler.py | 2 +- tests/mcp_tests/test_mcp_server.py | 4 +- .../test_litellm_logging.py | 273 +++++++++++++++++- .../mcp_server/test_mcp_server.py | 62 +++- .../test_cisco_ai_defense_mcp.py | 35 +++ .../mcp/test_litellm_proxy_mcp_handler.py | 158 +++++++++- 9 files changed, 572 insertions(+), 40 deletions(-) diff --git a/litellm/integrations/custom_logger.py b/litellm/integrations/custom_logger.py index 5b5261fab6b..326abd5c6a3 100644 --- a/litellm/integrations/custom_logger.py +++ b/litellm/integrations/custom_logger.py @@ -574,11 +574,10 @@ class CustomLogger: # https://docs.litellm.ai/docs/observability/custom_callbac Useful if you want to modify the standard logging payload after the MCP tool call is made. - To change what the caller sends back to the MCP client, mutate ``response_obj`` - in place: every call site discards the returned object, because the - dispatcher unwraps it to ``mcp_tool_call_response`` (a raw content list, not - a ``CallToolResult``) which the tool-call paths cannot forward. Guardrails - that mask or reject tool output should use ``post_mcp_call`` instead. + Modify ``mcp_tool_call_response`` in place or return a replacement response + object to change what the caller sends back to the MCP client. Content rewrites + discard stale structured output and mark those results as tool errors. + Use ``post_mcp_call`` guardrails for schema-preserving structured redaction. """ return None diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py index 357ee51a44a..6e5a37a7226 100644 --- a/litellm/litellm_core_utils/litellm_logging.py +++ b/litellm/litellm_core_utils/litellm_logging.py @@ -221,7 +221,7 @@ from .initialize_dynamic_callback_params import ( from .specialty_caches.dynamic_logging_cache import DynamicLoggingCache if TYPE_CHECKING: - from mcp.types import EmbeddedResource, ImageContent, TextContent + from mcp.types import CallToolResult, EmbeddedResource, ImageContent, TextContent from litellm.integrations.otel.logger import OpenTelemetryV2 from litellm.integrations.otel.model.config import ExporterSpec, OpenTelemetryV2Config @@ -1634,15 +1634,11 @@ class Logging(LiteLLMLoggingBaseClass): async def async_post_mcp_tool_call_hook( self, kwargs: dict, - response_obj: Any, + response_obj: "CallToolResult", start_time: datetime.datetime, end_time: datetime.datetime, - ): - """ - Post MCP Tool Call Hook - - Use this to modify the MCP tool call response before it is returned to the user. - """ + ) -> "CallToolResult": + """Apply ordered MCP content callbacks to the result returned to the caller.""" from litellm.types.llms.base import HiddenParams from litellm.types.mcp import MCPPostCallResponseObject @@ -1650,24 +1646,51 @@ class Logging(LiteLLMLoggingBaseClass): dynamic_success_callbacks=self.dynamic_success_callbacks, global_callbacks=litellm.success_callback, ) - post_mcp_tool_call_response_obj: Final[MCPPostCallResponseObject] = MCPPostCallResponseObject( - mcp_tool_call_response=response_obj, hidden_params=HiddenParams() - ) + hidden_params = HiddenParams() for callback in callbacks: try: if isinstance(callback, CustomLogger): - response: MCPPostCallResponseObject | None = await callback.async_post_mcp_tool_call_hook( - kwargs=kwargs, - response_obj=post_mcp_tool_call_response_obj, - start_time=start_time, - end_time=end_time, + original_content = copy.deepcopy(response_obj.content) + original_structured_content = copy.deepcopy(response_obj.structured_content) + callback_response = MCPPostCallResponseObject( + mcp_tool_call_response=copy.deepcopy(original_content), hidden_params=hidden_params ) - ###################################################################### - # if any of the callbacks modify the response, use the modified response - # current implementation returns the first modified response - ###################################################################### - if response is not None: - response_obj = self._parse_post_mcp_call_hook_response(response=response) + try: + response = await callback.async_post_mcp_tool_call_hook( + kwargs=kwargs, + response_obj=callback_response, + start_time=start_time, + end_time=end_time, + ) + hook_content = ( + self._parse_post_mcp_call_hook_response(response=response) + if response is not None + else callback_response.mcp_tool_call_response + ) + if response is not None: + hidden_params = response.hidden_params + except Exception as e: + verbose_logger.exception( + "LiteLLM.LoggingError: [Non-Blocking] Exception occurred while logging %s", e + ) + hook_content = None + structured_replacement_matches = ( + response_obj.structured_content != original_structured_content + and ( + hook_content is None + or hook_content == original_content + or response_obj.content == hook_content + ) + ) + if hook_content is not None and hook_content != original_content: + response_obj.content[:] = hook_content + if ( + response_obj.content != original_content + and response_obj.structured_content is not None + and not structured_replacement_matches + ): + response_obj.structured_content = None + response_obj.is_error = True except Exception as e: verbose_logger.exception("LiteLLM.LoggingError: [Non-Blocking] Exception occurred while logging %s", e) return response_obj diff --git a/litellm/proxy/_experimental/mcp_server/operations.py b/litellm/proxy/_experimental/mcp_server/operations.py index fcee3483e15..2bd6d186f24 100644 --- a/litellm/proxy/_experimental/mcp_server/operations.py +++ b/litellm/proxy/_experimental/mcp_server/operations.py @@ -2198,7 +2198,7 @@ async def _fire_mcp_tool_call_logging( from litellm.proxy.proxy_server import proxy_logging_obj logging_obj.post_call(original_response=result) - await logging_obj.async_post_mcp_tool_call_hook( + result = await logging_obj.async_post_mcp_tool_call_hook( kwargs=logging_obj.model_call_details, response_obj=result, start_time=start_time, diff --git a/litellm/responses/mcp/litellm_proxy_mcp_handler.py b/litellm/responses/mcp/litellm_proxy_mcp_handler.py index 88a2b92c680..319f10a9b22 100644 --- a/litellm/responses/mcp/litellm_proxy_mcp_handler.py +++ b/litellm/responses/mcp/litellm_proxy_mcp_handler.py @@ -872,7 +872,7 @@ class LiteLLM_Proxy_MCP_Handler: if litellm_logging_obj: try: litellm_logging_obj.post_call(original_response=result) - await litellm_logging_obj.async_post_mcp_tool_call_hook( + result = await litellm_logging_obj.async_post_mcp_tool_call_hook( kwargs=litellm_logging_obj.model_call_details, response_obj=result, start_time=start_time, diff --git a/tests/mcp_tests/test_mcp_server.py b/tests/mcp_tests/test_mcp_server.py index d38a11ec927..dfd250338ff 100644 --- a/tests/mcp_tests/test_mcp_server.py +++ b/tests/mcp_tests/test_mcp_server.py @@ -2962,7 +2962,7 @@ async def test_call_mcp_tool_uses_manager_permission_lookup(): mcp_info={"server_name": "test_server"}, ) - expected_response = [TextContent(type="text", text="ok")] + expected_response = CallToolResult(content=[TextContent(type="text", text="ok")], isError=False) with ( patch.object( @@ -3038,7 +3038,7 @@ async def test_call_mcp_tool_resolves_unprefixed_tool_name_and_checks_permission mcp_info={"server_name": "test_server"}, ) - expected_response = [TextContent(type="text", text="ok")] + expected_response = CallToolResult(content=[TextContent(type="text", text="ok")], isError=False) with ( patch.object( diff --git a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py index b0fc725b50a..4541250e896 100644 --- a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py +++ b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py @@ -5,16 +5,15 @@ import json import logging import os import sys +import time from collections.abc import Callable, Iterator, Mapping from types import MappingProxyType from typing import Final, Literal from unittest.mock import AsyncMock, MagicMock, patch -import pytest - -import time - import httpx +import pytest +from mcp.types import AudioContent, CallToolResult, ImageContent, TextContent from openai._legacy_response import HttpxBinaryResponseContent import litellm @@ -51,6 +50,272 @@ def logging_obj(): ) +@pytest.mark.asyncio +async def test_async_post_mcp_tool_call_hook_preserves_and_returns_content(logging_obj): + from litellm.types.mcp import MCPPostCallResponseObject + + class RedactingLogger(CustomLogger): + async def async_post_mcp_tool_call_hook( + self, + kwargs: dict[str, object], + response_obj: MCPPostCallResponseObject, + start_time: datetime.datetime, + end_time: datetime.datetime, + ) -> MCPPostCallResponseObject: + assert isinstance(response_obj.mcp_tool_call_response, list) + assert isinstance(response_obj.mcp_tool_call_response[0], TextContent) + response_obj.mcp_tool_call_response = [TextContent(type="text", text="[REDACTED]")] + return response_obj + + logging_obj.dynamic_success_callbacks = [RedactingLogger()] + result = CallToolResult(content=[TextContent(type="text", text="SECRET-1234")], isError=False) + + hooked_content = await logging_obj.async_post_mcp_tool_call_hook( + kwargs=logging_obj.model_call_details, + response_obj=result, + start_time=datetime.datetime.now(), + end_time=datetime.datetime.now(), + ) + + assert hooked_content.content == [TextContent(type="text", text="[REDACTED]")] + + +@pytest.mark.asyncio +async def test_async_post_mcp_tool_call_hook_chains_every_callback(logging_obj): + from litellm.types.mcp import MCPPostCallResponseObject + + class ReplacingLogger(CustomLogger): + def __init__(self, old: str, new: str) -> None: + super().__init__() + self.old: Final = old + self.new: Final = new + self.seen: list[str] = [] # mutable-ok: test records what each callback observed + + async def async_post_mcp_tool_call_hook( + self, + kwargs: dict[str, object], + response_obj: MCPPostCallResponseObject, + start_time: datetime.datetime, + end_time: datetime.datetime, + ) -> MCPPostCallResponseObject: + first = response_obj.mcp_tool_call_response[0] + assert isinstance(first, TextContent) + self.seen.append(first.text) + return MCPPostCallResponseObject( + mcp_tool_call_response=[TextContent(type="text", text=first.text.replace(self.old, self.new))], + hidden_params=response_obj.hidden_params, + ) + + first_logger: Final = ReplacingLogger("SECRET", "[S]") + second_logger: Final = ReplacingLogger("1234", "[N]") + logging_obj.dynamic_success_callbacks = [first_logger, second_logger] + result = CallToolResult(content=[TextContent(type="text", text="SECRET-1234")], isError=False) + + hooked_content = await logging_obj.async_post_mcp_tool_call_hook( + kwargs=logging_obj.model_call_details, + response_obj=result, + start_time=datetime.datetime.now(), + end_time=datetime.datetime.now(), + ) + + assert first_logger.seen == ["SECRET-1234"] + assert second_logger.seen == ["[S]-1234"] + assert hooked_content.content == [TextContent(type="text", text="[S]-[N]")] + + +@pytest.mark.asyncio +@pytest.mark.parametrize("mode", ["replace", "inplace", "empty", "inplace_none", "replace_none"]) +@pytest.mark.parametrize("structured", [False, True]) +async def test_mcp_content_rewrite_never_returns_stale_structured_data(logging_obj, mode, structured): + from litellm.types.llms.base import HiddenParams + from litellm.types.mcp import MCPPostCallResponseObject + + class Redactor(CustomLogger): + async def async_post_mcp_tool_call_hook(self, kwargs, response_obj, start_time, end_time): + block = response_obj.mcp_tool_call_response[0] + assert isinstance(block, TextContent) + if mode in ("inplace", "inplace_none"): + block.text = "[REDACTED]" + return None if mode == "inplace_none" else response_obj + if mode == "replace_none": + response_obj.mcp_tool_call_response = [TextContent(type="text", text="[REDACTED]")] + return None + return MCPPostCallResponseObject( + mcp_tool_call_response=[] if mode == "empty" else [TextContent(type="text", text="[REDACTED]")], + hidden_params=HiddenParams(response_cost=0.25), + ) + + logging_obj.dynamic_success_callbacks = [Redactor()] + result = CallToolResult( + content=[TextContent(type="text", text="SECRET-1234")], + structured_content={"nested": {"secret": "SECRET-1234"}} if structured else None, + meta={"request": "trace-1"}, + ) + logging_obj.model_call_details["original_response"] = result + returned = await logging_obj.async_post_mcp_tool_call_hook( + kwargs=logging_obj.model_call_details, + response_obj=result, + start_time=datetime.datetime.now(), + end_time=datetime.datetime.now(), + ) + assert "SECRET-1234" not in result.model_dump_json(by_alias=True) + assert returned is result + assert result.content == ([] if mode == "empty" else [TextContent(type="text", text="[REDACTED]")]) + assert result.structured_content is None + assert result.is_error is structured + assert result.meta == {"request": "trace-1"} + assert logging_obj.model_call_details["original_response"] is result + + +@pytest.mark.asyncio +@pytest.mark.parametrize("mode", ["none", "cost", "direct", "block", "exception"]) +async def test_mcp_callbacks_preserve_effective_result_and_cost(logging_obj, mode): + from litellm.types.llms.base import HiddenParams + from litellm.types.mcp import MCPPostCallResponseObject + + class Callback(CustomLogger): + async def async_post_mcp_tool_call_hook(self, kwargs, response_obj, start_time, end_time): + if mode == "exception": + response_obj.mcp_tool_call_response[0].text = "discarded" + raise ValueError("non-blocking callback") + if mode in ("direct", "block"): + original = kwargs["original_response"] + original.content = [TextContent(type="text", text="safe")] + original.structured_content = {"result": "safe"} + original.is_error = mode == "block" + if mode == "none" or mode == "direct": + return None + return MCPPostCallResponseObject( + mcp_tool_call_response=response_obj.mcp_tool_call_response, + hidden_params=HiddenParams(response_cost=0.25), + ) + + logging_obj.dynamic_success_callbacks = [Callback()] + result = CallToolResult( + content=[TextContent(type="text", text="original")], structured_content={"result": "original"} + ) + logging_obj.model_call_details["original_response"] = result + returned = await logging_obj.async_post_mcp_tool_call_hook( + kwargs=logging_obj.model_call_details, + response_obj=result, + start_time=datetime.datetime.now(), + end_time=datetime.datetime.now(), + ) + expected = "safe" if mode in ("direct", "block") else "original" + assert result.content == [TextContent(type="text", text=expected)] + assert result.structured_content == {"result": expected} + assert result.is_error is (mode == "block") + assert returned is result + assert logging_obj.model_call_details.get("response_cost") == (0.25 if mode in ("cost", "block") else None) + + +@pytest.mark.asyncio +async def test_mcp_callback_cancellation_propagates_without_mutating_result(logging_obj): + class CancelledCallback(CustomLogger): + async def async_post_mcp_tool_call_hook(self, kwargs, response_obj, start_time, end_time): + response_obj.mcp_tool_call_response[0].text = "partial" + raise asyncio.CancelledError + + logging_obj.dynamic_success_callbacks = [CancelledCallback()] + result = CallToolResult(content=[TextContent(type="text", text="original")]) + with pytest.raises(asyncio.CancelledError): + await logging_obj.async_post_mcp_tool_call_hook( + kwargs={}, + response_obj=result, + start_time=datetime.datetime.now(), + end_time=datetime.datetime.now(), + ) + assert result.content == [TextContent(type="text", text="original")] + + +@pytest.mark.asyncio +@pytest.mark.parametrize("callbacks", [[], ["prometheus"]]) +@pytest.mark.parametrize("is_error", [False, True]) +async def test_mcp_without_custom_callbacks_preserves_mixed_content(logging_obj, callbacks, is_error): + logging_obj.dynamic_success_callbacks = callbacks + result = CallToolResult( + content=[ + TextContent(type="text", text="ok"), + ImageContent(type="image", data="aW1n", mime_type="image/png"), + AudioContent(type="audio", data="c291bmQ=", mime_type="audio/wav"), + ], + structured_content={"result": "ok"}, + is_error=is_error, + ) + before = result.model_dump() + returned = await logging_obj.async_post_mcp_tool_call_hook( + kwargs={}, + response_obj=result, + start_time=datetime.datetime.now(), + end_time=datetime.datetime.now(), + ) + assert returned is result + assert returned.model_dump() == before + + +@pytest.mark.asyncio +@pytest.mark.parametrize("replace_structured", [False, True]) +@pytest.mark.parametrize("same_content", [False, True]) +async def test_mcp_native_structured_replacement_must_match_returned_content( + logging_obj, replace_structured, same_content +): + from litellm.types.mcp import MCPPostCallResponseObject + + class NativeReplacement(CustomLogger): + async def async_post_mcp_tool_call_hook(self, kwargs, response_obj, start_time, end_time): + original = kwargs["original_response"] + original.content[0].text = "native-safe" + if replace_structured: + original.structured_content["result"] = "native-safe" + return MCPPostCallResponseObject( + mcp_tool_call_response=[TextContent(type="text", text="native-safe" if same_content else "final-safe")], + hidden_params=response_obj.hidden_params, + ) + + result = CallToolResult( + content=[TextContent(type="text", text="SECRET-1234")], + structured_content={"result": "SECRET-1234"}, + ) + logging_obj.dynamic_success_callbacks = [NativeReplacement()] + returned = await logging_obj.async_post_mcp_tool_call_hook( + kwargs={"original_response": result}, response_obj=result, + start_time=datetime.datetime.now(), end_time=datetime.datetime.now(), + ) + assert returned is result + assert result.content == [TextContent(type="text", text="native-safe" if same_content else "final-safe")] + assert result.structured_content == ({"result": "native-safe"} if replace_structured and same_content else None) + assert result.is_error is not (replace_structured and same_content) + assert "SECRET-1234" not in result.model_dump_json() + + + +@pytest.mark.asyncio +@pytest.mark.parametrize("mode", ["none", "wrapper", "exception"]) +@pytest.mark.parametrize("structured", [False, True]) +async def test_mcp_direct_content_edit_invalidates_stale_structured_data(logging_obj, mode, structured): + class DirectRedactor(CustomLogger): + async def async_post_mcp_tool_call_hook(self, kwargs, response_obj, start_time, end_time): + kwargs["original_response"].content[0].text = "[REDACTED]" + if mode == "exception": + raise ValueError("non-blocking callback after direct edit") + return response_obj if mode == "wrapper" else None + + result = CallToolResult( + content=[TextContent(type="text", text="SECRET-1234")], + structured_content={"result": "SECRET-1234"} if structured else None, + ) + logging_obj.dynamic_success_callbacks = [DirectRedactor()] + returned = await logging_obj.async_post_mcp_tool_call_hook( + kwargs={"original_response": result}, response_obj=result, + start_time=datetime.datetime.now(), end_time=datetime.datetime.now(), + ) + assert returned is result + assert result.content == [TextContent(type="text", text="[REDACTED]")] + assert result.structured_content is None + assert result.is_error is structured + assert "SECRET-1234" not in result.model_dump_json() + + def test_get_combined_callback_list_preserves_insertion_order(logging_obj): assert logging_obj.get_combined_callback_list( dynamic_success_callbacks=["prometheus", "langfuse", "datadog", "otel", "s3"], diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server.py index 6588ab4c87b..ea82c9b069d 100644 --- a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server.py +++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server.py @@ -8755,7 +8755,7 @@ def _call_tool_result(is_error: bool, text: str) -> CallToolResult: def _mock_mcp_logging_obj() -> MagicMock: logging_obj = MagicMock() logging_obj.model_call_details = {} - logging_obj.async_post_mcp_tool_call_hook = AsyncMock() + logging_obj.async_post_mcp_tool_call_hook = AsyncMock(side_effect=lambda **kwargs: kwargs["response_obj"]) logging_obj.async_success_handler = AsyncMock() logging_obj.async_failure_handler = AsyncMock() return logging_obj @@ -8857,6 +8857,64 @@ async def test_fire_mcp_tool_call_logging_success_path_unchanged(): proxy_logging_mock.post_call_failure_hook.assert_not_awaited() +@pytest.mark.asyncio +async def test_fire_mcp_tool_call_logging_applies_hook_content(): + from litellm.integrations.custom_logger import CustomLogger + from litellm.litellm_core_utils.litellm_logging import Logging + from litellm.proxy._experimental.mcp_server.server import ( + _fire_mcp_tool_call_logging, + ) + from litellm.types.mcp import MCPPostCallResponseObject + + class RedactingLogger(CustomLogger): + async def async_post_mcp_tool_call_hook( + self, + kwargs: dict[str, object], + response_obj: MCPPostCallResponseObject, + start_time: datetime, + end_time: datetime, + ) -> MCPPostCallResponseObject: + assert isinstance(response_obj.mcp_tool_call_response, list) + assert isinstance(response_obj.mcp_tool_call_response[0], TextContent) + response_obj.mcp_tool_call_response = [TextContent(type="text", text="[REDACTED]")] + return response_obj + + logging_obj = Logging( + model="MCP: weather/get_forecast", + messages=[{"role": "user", "content": "tool call"}], + stream=False, + call_type="call_mcp_tool", + start_time=datetime.now(), + litellm_call_id="test-mcp-hook-content", + function_id="test-fn", + dynamic_success_callbacks=[RedactingLogger()], + ) + proxy_logging_mock = _mock_mcp_proxy_logging() + result = CallToolResult( + content=[TextContent(type="text", text="SECRET-1234")], + structuredContent={"result": "SECRET-1234"}, + isError=False, + ) + + with patch( # test-quality-ok: [TQ008] inject proxy logging collaborator + "litellm.proxy.proxy_server.proxy_logging_obj", + proxy_logging_mock, + ): + hooked_result = await _fire_mcp_tool_call_logging( + logging_obj=logging_obj, + result=result, + start_time=datetime.now(), + end_time=datetime.now(), + user_api_key_auth=UserAPIKeyAuth(api_key="test-key", user_id="test-user"), + request_data={}, + ) + + assert isinstance(hooked_result.content[0], TextContent) + assert hooked_result.content[0].text == "[REDACTED]" + assert hooked_result.structured_content is None + assert hooked_result.is_error is True + + @pytest.mark.asyncio async def test_fire_mcp_tool_call_logging_iserror_without_auth_skips_failure_hook(): """Without a UserAPIKeyAuth the failure handlers still fire but the proxy @@ -8871,7 +8929,7 @@ async def test_fire_mcp_tool_call_logging_iserror_without_auth_skips_failure_hoo with patch("litellm.proxy.proxy_server.proxy_logging_obj", proxy_logging_mock): await _fire_mcp_tool_call_logging( logging_obj=logging_obj, - result={"isError": True, "content": [{"type": "text", "text": "denied"}]}, + result=_call_tool_result(True, "denied"), start_time=datetime.now(), end_time=datetime.now(), ) diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_cisco_ai_defense_mcp.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_cisco_ai_defense_mcp.py index 826edab694d..2e3bf760e68 100644 --- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_cisco_ai_defense_mcp.py +++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_cisco_ai_defense_mcp.py @@ -827,3 +827,38 @@ class TestCiscoAIDefenseJsonRpcSuccessEnvelope: assert unwrapped is verdict else: assert unwrapped == expected + + +@pytest.mark.asyncio +@pytest.mark.parametrize("action", ["block", "redact"]) +async def test_cisco_native_hook_through_logging_preserves_sanitized_result(action): + from mcp.types import CallToolResult, TextContent + from litellm.litellm_core_utils.litellm_logging import Logging + + guardrail = _make_guardrail( + inspection_type="mcp", event_hook=["pre_mcp_call", "during_mcp_call"] + ) + verdict = ( + _violation_response(url=MCP_URL) if action == "block" + else _redact_response(sanitized_text="[REDACTED]", url=MCP_URL) + ) + result = CallToolResult( + content=[TextContent(type="text", text="SECRET-1234")], + structured_content={"result": "SECRET-1234"}, + ) + logging_obj = Logging( + model="MCP: probe/search", messages=[], stream=False, call_type="call_mcp_tool", + start_time=datetime.now(), litellm_call_id="cisco-hook", function_id="cisco-hook", + dynamic_success_callbacks=[guardrail], + ) + logging_obj.model_call_details.update({"name": "search", "arguments": {}, "original_response": result}) + with _patch_inspection_post(guardrail, AsyncMock(return_value=verdict)): + returned = await logging_obj.async_post_mcp_tool_call_hook( + kwargs=logging_obj.model_call_details, response_obj=result, + start_time=datetime.now(), end_time=datetime.now(), + ) + assert returned is result + assert "SECRET-1234" not in returned.model_dump_json() + assert returned.is_error is (action == "block") + assert ("Blocked by Cisco AI Defense" if action == "block" else "[REDACTED]") in returned.content[0].text + assert returned.structured_content == {"result": returned.content[0].text} diff --git a/tests/test_litellm/responses/mcp/test_litellm_proxy_mcp_handler.py b/tests/test_litellm/responses/mcp/test_litellm_proxy_mcp_handler.py index 83537c236a3..56e40206ebe 100644 --- a/tests/test_litellm/responses/mcp/test_litellm_proxy_mcp_handler.py +++ b/tests/test_litellm/responses/mcp/test_litellm_proxy_mcp_handler.py @@ -1,13 +1,15 @@ +import importlib import subprocess import sys import textwrap import types +from typing import Any, cast from unittest.mock import AsyncMock, MagicMock import pytest from fastapi import HTTPException +from mcp.types import CallToolResult, TextContent from openai.types.responses.tool_param import Mcp -import importlib from litellm.proxy._experimental.mcp_server.faults.list_outcomes import AggregateToolListing from litellm.responses import main as responses_main @@ -15,10 +17,9 @@ from litellm.responses.mcp import litellm_proxy_mcp_handler as mcp_handler_modul from litellm.responses.mcp.litellm_proxy_mcp_handler import ( LiteLLM_Proxy_MCP_Handler, ) -from typing import Any, cast from litellm.types.llms.openai import ResponsesAPIResponse -from litellm.types.utils import ModelResponse from litellm.types.responses.main import OutputFunctionToolCall +from litellm.types.utils import ModelResponse class _DummyMCPResult: @@ -492,6 +493,157 @@ async def test_execute_tool_calls_threads_logging_obj_into_call_tool(monkeypatch assert call_tool_mock.await_args.kwargs["litellm_logging_obj"] is sentinel_logging_obj +@pytest.mark.asyncio +async def test_execute_tool_calls_applies_post_call_hook_content(monkeypatch): + proxy_module = types.SimpleNamespace(proxy_logging_obj=None) + monkeypatch.setitem(sys.modules, "litellm.proxy.proxy_server", proxy_module) + + result = CallToolResult( + content=[TextContent(type="text", text="SECRET-1234")], + structuredContent={"result": "SECRET-1234"}, + isError=False, + ) + fake_manager = types.SimpleNamespace( + get_registry=MagicMock(return_value={}), + call_tool=AsyncMock(return_value=result), + _get_mcp_server_from_tool_name=MagicMock(return_value=None), + get_mcp_server_by_name=MagicMock(return_value=None), + ) + monkeypatch.setattr( + "litellm.proxy._experimental.mcp_server.mcp_server_manager.global_mcp_server_manager", + fake_manager, + ) + + logging_obj = MagicMock() + logging_obj.model_call_details = {} + logging_obj.async_post_mcp_tool_call_hook = AsyncMock(return_value=CallToolResult(content=[TextContent(type="text", text="[REDACTED]")], is_error=True)) + logging_obj.async_success_handler = AsyncMock() + handler_module = importlib.import_module("litellm.responses.mcp.litellm_proxy_mcp_handler") + monkeypatch.setattr(handler_module, "function_setup", lambda *_args, **_kwargs: (logging_obj, None)) + + tool_name = "deepwiki-read_wiki_structure" + results = await LiteLLM_Proxy_MCP_Handler._execute_tool_calls( + tool_server_map={tool_name: "deepwiki"}, + tool_calls=[{"id": "call-1", "function": {"name": tool_name, "arguments": "{}"}}], + user_api_key_auth=None, + ) + + assert results == [{"tool_call_id": "call-1", "result": "[REDACTED]", "name": tool_name}] + assert logging_obj.async_success_handler.await_args.kwargs["result"].content[0].text == "[REDACTED]" + assert logging_obj.async_success_handler.await_args.kwargs["result"].structured_content is None + + +@pytest.mark.asyncio +async def test_execute_tool_calls_returns_proxy_result_without_logging(monkeypatch): + result = CallToolResult(content=[TextContent(type="text", text="ok")], isError=False) + proxy_logging_obj = MagicMock() + proxy_logging_obj.post_mcp_call_hook = AsyncMock(side_effect=lambda response, **_: response) + monkeypatch.setitem( + sys.modules, "litellm.proxy.proxy_server", types.SimpleNamespace(proxy_logging_obj=proxy_logging_obj) + ) + + fake_manager = types.SimpleNamespace( + get_registry=MagicMock(return_value={}), + call_tool=AsyncMock(return_value=result), + _get_mcp_server_from_tool_name=MagicMock(return_value=None), + get_mcp_server_by_name=MagicMock(return_value=None), + ) + monkeypatch.setattr( + "litellm.proxy._experimental.mcp_server.mcp_server_manager.global_mcp_server_manager", + fake_manager, + ) + handler_module = importlib.import_module("litellm.responses.mcp.litellm_proxy_mcp_handler") + monkeypatch.setattr(handler_module, "function_setup", lambda *_args, **_kwargs: (None, None)) + + tool_name = "deepwiki-read_wiki_structure" + results = await LiteLLM_Proxy_MCP_Handler._execute_tool_calls( + tool_server_map={tool_name: "deepwiki"}, + tool_calls=[{"id": "call-1", "function": {"name": tool_name, "arguments": "{}"}}], + user_api_key_auth=None, + ) + + assert results == [{"tool_call_id": "call-1", "result": "ok", "name": tool_name}] + proxy_logging_obj.post_mcp_call_hook.assert_awaited_once() + + +@pytest.mark.asyncio +async def test_execute_tool_calls_passes_logging_details_to_proxy_hook(monkeypatch): + result = CallToolResult(content=[TextContent(type="text", text="ok")], isError=False) + proxy_logging_obj = MagicMock() + proxy_logging_obj.post_mcp_call_hook = AsyncMock(side_effect=lambda response, **_: response) + monkeypatch.setitem( + sys.modules, "litellm.proxy.proxy_server", types.SimpleNamespace(proxy_logging_obj=proxy_logging_obj) + ) + + fake_manager = types.SimpleNamespace( + get_registry=MagicMock(return_value={}), + call_tool=AsyncMock(return_value=result), + _get_mcp_server_from_tool_name=MagicMock(return_value=None), + get_mcp_server_by_name=MagicMock(return_value=None), + ) + monkeypatch.setattr( + "litellm.proxy._experimental.mcp_server.mcp_server_manager.global_mcp_server_manager", + fake_manager, + ) + logging_obj = MagicMock() + logging_obj.model_call_details = {"request_id": "request-1"} + logging_obj.async_post_mcp_tool_call_hook = AsyncMock(return_value=result) + logging_obj.async_success_handler = AsyncMock() + handler_module = importlib.import_module("litellm.responses.mcp.litellm_proxy_mcp_handler") + monkeypatch.setattr(handler_module, "function_setup", lambda *_args, **_kwargs: (logging_obj, None)) + + tool_name = "deepwiki-read_wiki_structure" + results = await LiteLLM_Proxy_MCP_Handler._execute_tool_calls( + tool_server_map={tool_name: "deepwiki"}, + tool_calls=[{"id": "call-1", "function": {"name": tool_name, "arguments": "{}"}}], + user_api_key_auth=None, + ) + + assert results == [{"tool_call_id": "call-1", "result": "ok", "name": tool_name}] + assert proxy_logging_obj.post_mcp_call_hook.await_args.kwargs["request_data"] == logging_obj.model_call_details + + +@pytest.mark.asyncio +@pytest.mark.parametrize("failure_stage", ["post_call_hook", "success_handler"]) +async def test_execute_tool_calls_continues_when_post_call_logging_fails(monkeypatch, failure_stage: str): + proxy_module = types.SimpleNamespace(proxy_logging_obj=None) + monkeypatch.setitem(sys.modules, "litellm.proxy.proxy_server", proxy_module) + + result = CallToolResult(content=[TextContent(type="text", text="ok")], isError=False) + fake_manager = types.SimpleNamespace( + get_registry=MagicMock(return_value={}), + call_tool=AsyncMock(return_value=result), + _get_mcp_server_from_tool_name=MagicMock(return_value=None), + get_mcp_server_by_name=MagicMock(return_value=None), + ) + monkeypatch.setattr( + "litellm.proxy._experimental.mcp_server.mcp_server_manager.global_mcp_server_manager", + fake_manager, + ) + + logging_obj = MagicMock() + logging_obj.model_call_details = {} + logging_obj.post_call = MagicMock() + logging_obj.async_post_mcp_tool_call_hook = AsyncMock( + side_effect=RuntimeError("hook failed") if failure_stage == "post_call_hook" else None, + return_value=result, + ) + logging_obj.async_success_handler = AsyncMock( + side_effect=RuntimeError("success logging failed") if failure_stage == "success_handler" else None + ) + handler_module = importlib.import_module("litellm.responses.mcp.litellm_proxy_mcp_handler") + monkeypatch.setattr(handler_module, "function_setup", lambda *_args, **_kwargs: (logging_obj, None)) + + tool_name = "deepwiki-read_wiki_structure" + results = await LiteLLM_Proxy_MCP_Handler._execute_tool_calls( + tool_server_map={tool_name: "deepwiki"}, + tool_calls=[{"id": "call-1", "function": {"name": tool_name, "arguments": "{}"}}], + user_api_key_auth=None, + ) + + assert results == [{"tool_call_id": "call-1", "result": "ok", "name": tool_name}] + + @pytest.mark.asyncio async def test_get_mcp_tools_from_manager_enables_list_tools_logging(monkeypatch): """ From e54f228ed87b78659bee066ccd2f4e36bfe97926 Mon Sep 17 00:00:00 2001 From: "berriai-litellm-provider-info-sync[bot]" <328147090+berriai-litellm-provider-info-sync[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 13:46:15 -0700 Subject: [PATCH 026/101] chore(prices): sync Baseten prices: 4 models, 4 new [enrichment failed: Baseten, 3 held] (#42578) baseten/deepseek-ai/DeepSeek-V4-Flash-0731: max_tokens, supports_vision, max_input_tokens, max_output_tokens, supports_reasoning, supports_tool_choice, supports_prompt_caching, supports_response_schema, supports_function_calling, input_cost_per_token, output_cost_per_token, cache_read_input_token_cost baseten/deepseek-ai/DeepSeek-V4-Pro: max_tokens, supports_vision, max_input_tokens, max_output_tokens, supports_reasoning, supports_tool_choice, supports_prompt_caching, supports_response_schema, supports_function_calling, input_cost_per_token, output_cost_per_token, cache_read_input_token_cost baseten/deepseek-ai/DeepSeek-V4-Pro-0813: max_tokens, supports_vision, max_input_tokens, max_output_tokens, supports_reasoning, supports_tool_choice, supports_prompt_caching, supports_response_schema, supports_function_calling, input_cost_per_token, output_cost_per_token, cache_read_input_token_cost baseten/zai-org/GLM-5.2-Fast: max_tokens, supports_vision, max_input_tokens, max_output_tokens, supports_reasoning, supports_tool_choice, supports_prompt_caching, supports_response_schema, supports_function_calling, input_cost_per_token, output_cost_per_token, cache_read_input_token_cost Co-authored-by: berriai-litellm-provider-info-sync[bot] <328147090+berriai-litellm-provider-info-sync[bot]@users.noreply.github.com> --- ...odel_prices_and_context_window_backup.json | 68 +++++++++++++++++++ model_prices_and_context_window.json | 68 +++++++++++++++++++ 2 files changed, 136 insertions(+) diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index a2863f6b0dc..b8ca5ff27c7 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -77665,5 +77665,73 @@ "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true + }, + "baseten/deepseek-ai/DeepSeek-V4-Flash-0731": { + "cache_read_input_token_cost": 2.8e-08, + "input_cost_per_token": 1.3e-07, + "litellm_provider": "baseten", + "max_input_tokens": 1048576, + "max_output_tokens": 384000, + "max_tokens": 384000, + "mode": "chat", + "output_cost_per_token": 2.6e-07, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "baseten/deepseek-ai/DeepSeek-V4-Pro": { + "cache_read_input_token_cost": 1.45e-07, + "input_cost_per_token": 1.74e-06, + "litellm_provider": "baseten", + "max_input_tokens": 1048576, + "max_output_tokens": 262144, + "max_tokens": 262144, + "mode": "chat", + "output_cost_per_token": 3.48e-06, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "baseten/deepseek-ai/DeepSeek-V4-Pro-0813": { + "cache_read_input_token_cost": 1.32e-07, + "input_cost_per_token": 1.32e-06, + "litellm_provider": "baseten", + "max_input_tokens": 1048576, + "max_output_tokens": 262144, + "max_tokens": 262144, + "mode": "chat", + "output_cost_per_token": 3.96e-06, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "baseten/zai-org/GLM-5.2-Fast": { + "cache_read_input_token_cost": 2.1e-07, + "input_cost_per_token": 2.1e-06, + "litellm_provider": "baseten", + "max_input_tokens": 1048576, + "max_output_tokens": 262144, + "max_tokens": 262144, + "mode": "chat", + "output_cost_per_token": 6.6e-06, + "source": "https://inference.baseten.co/v1/models", + "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.json b/model_prices_and_context_window.json index a2863f6b0dc..b8ca5ff27c7 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -77665,5 +77665,73 @@ "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true + }, + "baseten/deepseek-ai/DeepSeek-V4-Flash-0731": { + "cache_read_input_token_cost": 2.8e-08, + "input_cost_per_token": 1.3e-07, + "litellm_provider": "baseten", + "max_input_tokens": 1048576, + "max_output_tokens": 384000, + "max_tokens": 384000, + "mode": "chat", + "output_cost_per_token": 2.6e-07, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "baseten/deepseek-ai/DeepSeek-V4-Pro": { + "cache_read_input_token_cost": 1.45e-07, + "input_cost_per_token": 1.74e-06, + "litellm_provider": "baseten", + "max_input_tokens": 1048576, + "max_output_tokens": 262144, + "max_tokens": 262144, + "mode": "chat", + "output_cost_per_token": 3.48e-06, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "baseten/deepseek-ai/DeepSeek-V4-Pro-0813": { + "cache_read_input_token_cost": 1.32e-07, + "input_cost_per_token": 1.32e-06, + "litellm_provider": "baseten", + "max_input_tokens": 1048576, + "max_output_tokens": 262144, + "max_tokens": 262144, + "mode": "chat", + "output_cost_per_token": 3.96e-06, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "baseten/zai-org/GLM-5.2-Fast": { + "cache_read_input_token_cost": 2.1e-07, + "input_cost_per_token": 2.1e-06, + "litellm_provider": "baseten", + "max_input_tokens": 1048576, + "max_output_tokens": 262144, + "max_tokens": 262144, + "mode": "chat", + "output_cost_per_token": 6.6e-06, + "source": "https://inference.baseten.co/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true } } From b5b116a519fbef0ad894f4500f686270d6d860a9 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 20:50:53 +0000 Subject: [PATCH 027/101] fix(otel): honor SSL_CERT_FILE and ssl_verify in OTLP HTTP exporters (#42106) * fix(otel): honor SSL_CERT_FILE and ssl_verify in OTLP HTTP exporters Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(otel): assert OTLP HTTP TLS behavior against a real TLS sink Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(otel): assert rejected exports by outcome, not by exception type Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(otel): honor SSL_CERT_FILE and ssl_verify in the v2 OTLP HTTP exporters Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(otel): hoist otlp_tls imports and type the TLS sink fixture Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(e2e): gate the OTLP TLS export test behind an otel_tls opt-in Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * docs(e2e): drop CONTRIBUTING.md edit Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> Co-authored-by: yucheng --- .github/e2e-stack/up.sh | 29 +++- litellm/integrations/opentelemetry.py | 21 ++- .../integrations/otel/plumbing/otlp_json.py | 11 +- .../integrations/otel/plumbing/otlp_tls.py | 41 +++++ .../integrations/otel/plumbing/providers.py | 13 ++ tests/e2e/conftest.py | 6 + tests/e2e/e2e_config.py | 2 + tests/e2e/logging/test_otel_trace_e2e.py | 40 ++++- tests/e2e/pytest.ini | 1 + tests/test_litellm/integrations/conftest.py | 96 +++++++++++ .../otel/test_otel_v2_components.py | 105 +++++++++++- .../integrations/test_opentelemetry.py | 152 +++++++++++++++++- 12 files changed, 496 insertions(+), 21 deletions(-) create mode 100644 litellm/integrations/otel/plumbing/otlp_tls.py create mode 100644 tests/test_litellm/integrations/conftest.py diff --git a/.github/e2e-stack/up.sh b/.github/e2e-stack/up.sh index 928b58e93bb..931b5eb2169 100755 --- a/.github/e2e-stack/up.sh +++ b/.github/e2e-stack/up.sh @@ -24,6 +24,7 @@ DATABASE_USER="${E2E_DATABASE_USER:-litellm}" DATABASE_PASSWORD="${E2E_DATABASE_PASSWORD:-dbpassword9090}" DATABASE_NAME="${E2E_DATABASE_NAME:-litellm}" JAEGER_OTLP_PORT="${E2E_JAEGER_OTLP_PORT:-4318}" +JAEGER_OTLP_TLS_PORT="${E2E_JAEGER_OTLP_TLS_PORT:-4319}" JAEGER_QUERY_PORT="${E2E_JAEGER_QUERY_PORT:-16686}" KEYCLOAK_PORT="${E2E_KEYCLOAK_PORT:-8081}" @@ -122,7 +123,7 @@ SERVER_ENV=( "CONFIG_FILE_PATH=${CONFIG_PATH}" "STORE_MODEL_IN_DB=True" "OTEL_EXPORTER_OTLP_PROTOCOL=http/protobuf" - "OTEL_EXPORTER_OTLP_ENDPOINT=http://127.0.0.1:${JAEGER_OTLP_PORT}" + "OTEL_EXPORTER_OTLP_ENDPOINT=https://127.0.0.1:${JAEGER_OTLP_TLS_PORT}" "SSL_CERT_FILE=${CERTS_DIR}/ca-bundle.pem" "PYTHONPATH=${REPO_ROOT}" "JWT_PUBLIC_KEY_URL=http://127.0.0.1:${KEYCLOAK_PORT}/realms/litellm-e2e/protocol/openid-connect/certs" @@ -147,16 +148,12 @@ start_server() { echo $! > "${PIDS_DIR}/${name}.pid" } -start_server backend uv run --no-sync uvicorn backend.main:app --host 0.0.0.0 --port "${BACKEND_PORT}" -start_server gateway-1 uv run --no-sync uvicorn gateway.main:app --workers 1 --host 0.0.0.0 --port "${GATEWAY_PORT_1}" -start_server gateway-2 uv run --no-sync uvicorn gateway.main:app --workers 1 --host 0.0.0.0 --port "${GATEWAY_PORT_2}" - if [[ "$(uname)" == "Linux" ]]; then NGINX_UPSTREAM_HOST=127.0.0.1 NGINX_DOCKER_ARGS=(--network host) else NGINX_UPSTREAM_HOST=host.docker.internal - NGINX_DOCKER_ARGS=(-p "${LB_PORT}:${LB_PORT}") + NGINX_DOCKER_ARGS=(-p "${LB_PORT}:${LB_PORT}" -p "${JAEGER_OTLP_TLS_PORT}:${JAEGER_OTLP_TLS_PORT}") fi cat > "${STACK_DIR}/nginx.conf" </dev/null 2>&1 || true docker run -d --name e2e-nginx "${NGINX_DOCKER_ARGS[@]}" \ - -v "${STACK_DIR}/nginx.conf:/etc/nginx/nginx.conf:ro" "${NGINX_IMAGE}" >/dev/null + -v "${STACK_DIR}/nginx.conf:/etc/nginx/nginx.conf:ro" \ + -v "${CERTS_DIR}:/certs:ro" "${NGINX_IMAGE}" >/dev/null + +wait_for "Jaeger OTLP TLS listener" \ + "curl -sS --cacert ${CERTS_DIR}/ca.crt https://127.0.0.1:${JAEGER_OTLP_TLS_PORT}/ -o /dev/null -w '%{http_code}' | grep -qE '^[2345]'" + +start_server backend uv run --no-sync uvicorn backend.main:app --host 0.0.0.0 --port "${BACKEND_PORT}" +start_server gateway-1 uv run --no-sync uvicorn gateway.main:app --workers 1 --host 0.0.0.0 --port "${GATEWAY_PORT_1}" +start_server gateway-2 uv run --no-sync uvicorn gateway.main:app --workers 1 --host 0.0.0.0 --port "${GATEWAY_PORT_2}" wait_for "backend" "curl -fs http://127.0.0.1:${BACKEND_PORT}/health/liveliness >/dev/null" 300 wait_for "gateway-1" "curl -fs http://127.0.0.1:${GATEWAY_PORT_1}/health/liveliness >/dev/null" 300 @@ -206,6 +220,7 @@ LITELLM_MASTER_KEY=${MASTER_KEY} REDIS_HOST=127.0.0.1 REDIS_PORT=${REDIS_PORT} E2E_OTEL_QUERY_URL=http://127.0.0.1:${JAEGER_QUERY_PORT} +E2E_OTEL_EXPORTER_ENDPOINT=https://127.0.0.1:${JAEGER_OTLP_TLS_PORT} E2E_KEYCLOAK_URL=http://127.0.0.1:${KEYCLOAK_PORT} E2E_KEYCLOAK_ADMIN_USER=admin E2E_KEYCLOAK_ADMIN_PASSWORD=e2e-ephemeral-idp-not-a-secret diff --git a/litellm/integrations/opentelemetry.py b/litellm/integrations/opentelemetry.py index feaeaec27a3..749f0ce4fcb 100644 --- a/litellm/integrations/opentelemetry.py +++ b/litellm/integrations/opentelemetry.py @@ -26,6 +26,7 @@ from litellm.integrations.otel.model.baggage import promoted_metadata from litellm.integrations.otel.model.db_endpoint import db_span_attributes from litellm.integrations.otel.model.metadata import flatten_metadata from litellm.integrations.otel.model.semconv import Metric +from litellm.integrations.otel.plumbing.otlp_tls import resolve_otlp_http_tls from litellm.litellm_core_utils.internal_call_metadata import is_unbilled_non_inference_call_from_params from litellm.litellm_core_utils.safe_json_dumps import safe_dumps from litellm.litellm_core_utils.secret_redaction import redact_string @@ -99,6 +100,7 @@ _MAX_DYNAMIC_TRACER_PROVIDERS: Final = 256 # Dedicated so a slow exporter shutdown cannot starve the shared logging executor. _PROVIDER_SHUTDOWN_EXECUTOR: Final = ThreadPoolExecutor(max_workers=4, thread_name_prefix="OtelProviderShutdown") + LITELLM_TRACER_NAME: Final = os.getenv("OTEL_TRACER_NAME", "litellm") LITELLM_METER_NAME: Final = os.getenv("LITELLM_METER_NAME", "litellm") LITELLM_LOGGER_NAME: Final = os.getenv("LITELLM_LOGGER_NAME", "litellm") @@ -3090,8 +3092,14 @@ class OpenTelemetry(OTELGenAISemconvMixin, CustomLogger): otel_exporter, ) normalized_endpoint = self._normalize_otel_endpoint(otel_endpoint, "traces") + tls: Final = resolve_otlp_http_tls("TRACES") return BatchSpanProcessor( - OTLPSpanExporterHTTP(endpoint=normalized_endpoint, headers=_split_otel_headers), + OTLPSpanExporterHTTP( + endpoint=normalized_endpoint, + headers=_split_otel_headers, + certificate_file=tls.certificate_file, + session=tls.session, + ), ) elif otel_exporter == "otlp_grpc" or otel_exporter == "grpc": try: @@ -3172,7 +3180,13 @@ class OpenTelemetry(OTELGenAISemconvMixin, CustomLogger): self.OTEL_EXPORTER, normalized_endpoint, ) - return OTLPLogExporter(endpoint=normalized_endpoint, headers=_split_otel_headers) + tls: Final = resolve_otlp_http_tls("LOGS") + return OTLPLogExporter( + endpoint=normalized_endpoint, + headers=_split_otel_headers, + certificate_file=tls.certificate_file, + session=tls.session, + ) elif self.OTEL_EXPORTER == "otlp_grpc" or self.OTEL_EXPORTER == "grpc": try: from opentelemetry.exporter.otlp.proto.grpc._log_exporter import ( @@ -3235,9 +3249,12 @@ class OpenTelemetry(OTELGenAISemconvMixin, CustomLogger): OTLPMetricExporter, ) + tls: Final = resolve_otlp_http_tls("METRICS") exporter = OTLPMetricExporter( endpoint=normalized_endpoint, headers=_split_otel_headers, + certificate_file=tls.certificate_file, + session=tls.session, ) return PeriodicExportingMetricReader(exporter, export_interval_millis=5000) diff --git a/litellm/integrations/otel/plumbing/otlp_json.py b/litellm/integrations/otel/plumbing/otlp_json.py index b4b659f1e01..bc6d7d435b0 100644 --- a/litellm/integrations/otel/plumbing/otlp_json.py +++ b/litellm/integrations/otel/plumbing/otlp_json.py @@ -10,6 +10,7 @@ from collections.abc import Mapping, Sequence from types import MappingProxyType from typing import Final, TypeAlias +import requests from google.protobuf.json_format import MessageToDict from opentelemetry.exporter.otlp.proto.common.trace_encoder import encode_spans from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter @@ -62,8 +63,14 @@ def encode_spans_json(spans: Sequence[ReadableSpan]) -> bytes: class OTLPJsonSpanExporter(OTLPSpanExporter): - def __init__(self, endpoint: str | None, headers: dict[str, str]) -> None: # mutable-ok: SDK __init__ takes Dict - super().__init__(endpoint=endpoint, headers=headers) + def __init__( + self, + endpoint: str | None, + headers: dict[str, str], # mutable-ok: SDK __init__ takes Dict + certificate_file: str | None = None, + session: "requests.Session | None" = None, + ) -> None: + super().__init__(endpoint=endpoint, headers=headers, certificate_file=certificate_file, session=session) self._session.headers["Content-Type"] = JSON_CONTENT_TYPE def _serialize_spans(self, spans: Sequence[ReadableSpan]) -> bytes: diff --git a/litellm/integrations/otel/plumbing/otlp_tls.py b/litellm/integrations/otel/plumbing/otlp_tls.py new file mode 100644 index 00000000000..9de97e0c77a --- /dev/null +++ b/litellm/integrations/otel/plumbing/otlp_tls.py @@ -0,0 +1,41 @@ +import os +from dataclasses import dataclass +from typing import Final, Literal + +import requests +from requests.adapters import HTTPAdapter + + +@dataclass(frozen=True, slots=True) +class OtlpHttpTls: + certificate_file: str | None + session: requests.Session | None + + +class _NoVerifyAdapter(HTTPAdapter): + def cert_verify( + self, + conn: object, + url: str, + verify: bool | str, + cert: str | tuple[str, str] | None, + ) -> None: + super().cert_verify( # pyright: ignore[reportUnknownMemberType] # requests stubs omit HTTPAdapter.cert_verify + conn, url, False, cert + ) + + +def resolve_otlp_http_tls(signal: Literal["TRACES", "METRICS", "LOGS"]) -> OtlpHttpTls: + if os.getenv(f"OTEL_EXPORTER_OTLP_{signal}_CERTIFICATE") or os.getenv("OTEL_EXPORTER_OTLP_CERTIFICATE"): + return OtlpHttpTls(certificate_file=None, session=None) + + from litellm.llms.custom_httpx.http_handler import get_ssl_verify + + verify: Final = get_ssl_verify() + if verify is False: + session: Final = requests.Session() + session.mount("https://", _NoVerifyAdapter()) + return OtlpHttpTls(certificate_file=None, session=session) + if isinstance(verify, str): + return OtlpHttpTls(certificate_file=verify, session=None) + return OtlpHttpTls(certificate_file=None, session=None) diff --git a/litellm/integrations/otel/plumbing/providers.py b/litellm/integrations/otel/plumbing/providers.py index 2c4375ce5f7..d52736a1303 100644 --- a/litellm/integrations/otel/plumbing/providers.py +++ b/litellm/integrations/otel/plumbing/providers.py @@ -58,6 +58,7 @@ from litellm.integrations.otel.plumbing.context import ( request_destinations, suppressed_backends, ) +from litellm.integrations.otel.plumbing.otlp_tls import resolve_otlp_http_tls if TYPE_CHECKING: from opentelemetry.metrics import Meter @@ -193,18 +194,24 @@ def _exporter_from_spec(spec: ExporterSpec) -> SpanExporter: if kind in _OTLP_HTTP_JSON_KINDS: from litellm.integrations.otel.plumbing.otlp_json import OTLPJsonSpanExporter + tls: Final = resolve_otlp_http_tls("TRACES") return OTLPJsonSpanExporter( endpoint=spec.traces_endpoint or _otlp_traces_endpoint(spec.endpoint), headers=parse_headers(spec.headers), + certificate_file=tls.certificate_file, + session=tls.session, ) if kind in _OTLP_HTTP_KINDS: from opentelemetry.exporter.otlp.proto.http.trace_exporter import ( OTLPSpanExporter as HTTPExporter, ) + http_tls: Final = resolve_otlp_http_tls("TRACES") return HTTPExporter( endpoint=spec.traces_endpoint or _otlp_traces_endpoint(spec.endpoint), headers=parse_headers(spec.headers), + certificate_file=http_tls.certificate_file, + session=http_tls.session, ) if kind in _OTLP_GRPC_KINDS: from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import ( @@ -902,9 +909,12 @@ def build_metric_reader(config: OpenTelemetryV2Config) -> "MetricReader": OTLPMetricExporter as HTTPMetricExporter, ) + tls: Final = resolve_otlp_http_tls("METRICS") exporter: Any = HTTPMetricExporter( endpoint=_otlp_metrics_endpoint(config.endpoint), headers=parse_headers(config.headers), + certificate_file=tls.certificate_file, + session=tls.session, ) elif kind in ("otlp_grpc", "grpc"): try: @@ -962,9 +972,12 @@ def build_log_exporter(config: OpenTelemetryV2Config) -> LogExporter: OTLPLogExporter as HTTPLogExporter, ) + tls: Final = resolve_otlp_http_tls("LOGS") return HTTPLogExporter( endpoint=_otlp_logs_endpoint(config.endpoint), headers=parse_headers(config.headers), + certificate_file=tls.certificate_file, + session=tls.session, ) if kind in ("otlp_grpc", "grpc"): try: diff --git a/tests/e2e/conftest.py b/tests/e2e/conftest.py index ca0fbd84c35..a2398ef7c3c 100644 --- a/tests/e2e/conftest.py +++ b/tests/e2e/conftest.py @@ -30,6 +30,7 @@ from e2e_config import ( FIXTURE_MODE_RAW, MANAGED_FILES_OPT_IN_ENV, MCP_OAUTH_LIVE_OPT_IN_ENV, + OTEL_TLS_OPT_IN_ENV, OTEL_V2_OPT_IN_ENV, PROMPT_CACHING_OPT_IN_ENV, PROVIDER_EDGE_HOST_OPT_IN_ENV, @@ -63,6 +64,7 @@ OPT_IN_MARKERS: Final = MappingProxyType( "mcp_oauth_live": MCP_OAUTH_LIVE_OPT_IN_ENV, "provider_edge_host": PROVIDER_EDGE_HOST_OPT_IN_ENV, "otel_v2": OTEL_V2_OPT_IN_ENV, + "otel_tls": OTEL_TLS_OPT_IN_ENV, } ) @@ -156,6 +158,10 @@ def pytest_configure(config: pytest.Config) -> None: "markers", "otel_v2: needs a proxy running with LITELLM_OTEL_V2=true; deselected unless E2E_OTEL_V2 is set", ) + config.addinivalue_line( + "markers", + "otel_tls: needs a stack whose gateway exports OTLP over TLS signed by the CA in SSL_CERT_FILE; deselected unless E2E_OTEL_EXPORTER_ENDPOINT is set", + ) def pytest_sessionstart(session: pytest.Session) -> None: diff --git a/tests/e2e/e2e_config.py b/tests/e2e/e2e_config.py index 71f01834788..77395a066ac 100644 --- a/tests/e2e/e2e_config.py +++ b/tests/e2e/e2e_config.py @@ -58,6 +58,7 @@ LINEAR_READONLY_TOOL: Final = "list_teams" # as listed by tools/list on mcp.lin # service in docker-compose.yml maps it to host 16686). Trace-completeness tests # read exported spans back through it. OTEL_QUERY_URL = os.environ.get("E2E_OTEL_QUERY_URL", "http://localhost:16686").rstrip("/") +OTEL_EXPORTER_ENDPOINT = os.environ.get("E2E_OTEL_EXPORTER_ENDPOINT", "") # Real-DataDog read-back (no local sink - destination fakes cannot be deployed # on the cluster): the proxy delivers with DD_API_KEY as in production, and the @@ -148,6 +149,7 @@ CLI_DETERMINISM_OPT_IN_ENV = "E2E_CLI_DETERMINISM" MCP_OAUTH_LIVE_OPT_IN_ENV: Final = "E2E_MCP_OAUTH_LIVE" PROVIDER_EDGE_HOST_OPT_IN_ENV: Final = "E2E_PROVIDER_EDGE_HOST_REACHABLE" OTEL_V2_OPT_IN_ENV: Final = "E2E_OTEL_V2" +OTEL_TLS_OPT_IN_ENV: Final = "E2E_OTEL_EXPORTER_ENDPOINT" ANOMALY_SESSIONS = int(os.environ.get("E2E_ANOMALY_SESSIONS", "6")) ANOMALY_TURNS_PER_SESSION = int(os.environ.get("E2E_ANOMALY_TURNS_PER_SESSION", "6")) ANOMALY_TURN_ATTEMPTS = int(os.environ.get("E2E_ANOMALY_TURN_ATTEMPTS", "3")) diff --git a/tests/e2e/logging/test_otel_trace_e2e.py b/tests/e2e/logging/test_otel_trace_e2e.py index 9f08fa6c4e7..8d154ca0837 100644 --- a/tests/e2e/logging/test_otel_trace_e2e.py +++ b/tests/e2e/logging/test_otel_trace_e2e.py @@ -12,21 +12,24 @@ commit 1bd603d1ac). Both halves of the contract are asserted: the recorded state (the proxy reports the OTEL v2 logger active via /health/readiness/details) and the enforced behavior (the complete span tree at the destination, read back through the -destination's own query API - never proxy-side "export succeeded" logs). +destination's own query API - never proxy-side "export succeeded" logs). The +TLS coverage requires the stack to export OTLP over HTTPS with a certificate +signed by the CA in SSL_CERT_FILE, and treats a missing or plaintext endpoint +as a stack misconfiguration rather than skipping the test. """ from __future__ import annotations import time +from typing import Final import pytest -from pydantic import BaseModel, ConfigDict, ValidationError - -from e2e_config import CHEAP_ANTHROPIC_MODEL, CHEAP_OPENAI_MODEL, unique_marker +from e2e_config import CHEAP_ANTHROPIC_MODEL, CHEAP_OPENAI_MODEL, OTEL_EXPORTER_ENDPOINT, unique_marker from lifecycle import ResourceManager from logging_client import INVALID_UPSTREAM_API_KEY, LoggingClient, first_ok, readiness_details_body from models import LiteLLMParamsBody from otel_client import JaegerSpan, JaegerTrace, OtelReader +from pydantic import BaseModel, ConfigDict, ValidationError pytestmark = pytest.mark.e2e @@ -312,6 +315,35 @@ class TestOtelTraceCompleteness: ) _assert_complete_trace(hits, route=route, genai_span=f"chat {MODEL}") + @pytest.mark.covers("logging.otel.success.exports_metric", exercised_on=["chat_completions"]) + @pytest.mark.otel_tls + def test_otel_export_over_tls_with_internal_ca_reaches_destination( + self, client: LoggingClient, otel_reader: OtelReader, resources: ResourceManager + ) -> None: + _assert_otel_destination_configured(client) + assert OTEL_EXPORTER_ENDPOINT.startswith("https://"), ( + "the stack must export OTLP over TLS signed by the CA in SSL_CERT_FILE " + "(E2E_OTEL_EXPORTER_ENDPOINT) for this test to prove anything; a " + "missing or plaintext value is a stack misconfiguration" + ) + + route: Final = "/chat/completions" + key: Final = client.key_with_alias(f"otel-trace-tls-{unique_marker()}", models=[MODEL]) + resources.defer(lambda: client.delete_key(key)) + + marker: Final = unique_marker() + outcome: Final = first_ok( + client, lambda: client.chat_raw(key, MODEL, f"reply with one word {marker}", max_tokens=16) + ) + assert outcome.call_id is not None, "success response must carry x-litellm-call-id" + + hits: Final = otel_reader.poll_traces_for_call( + call_id=outcome.call_id, + settled_names=_settled_names(route=route, genai_span=f"chat {MODEL}"), + settled_prefixes={DB_SPAN_PREFIX}, + ) + _assert_complete_trace(hits, route=route, genai_span=f"chat {MODEL}") + @pytest.mark.covers("logging.otel.success.exports_metric", exercised_on=["messages"]) def test_messages_exports_complete_trace( self, client: LoggingClient, otel_reader: OtelReader, resources: ResourceManager diff --git a/tests/e2e/pytest.ini b/tests/e2e/pytest.ini index 6f9f57d333e..a77459d3683 100644 --- a/tests/e2e/pytest.ini +++ b/tests/e2e/pytest.ini @@ -15,3 +15,4 @@ markers = mcp_oauth_live: real Linear OAuth consent via a captured browser session; deselected unless E2E_MCP_OAUTH_LIVE is set provider_edge_host: routes provider traffic through the pytest host's edge in every fixture mode, so the gateway must reach the pytest host; deselected unless E2E_PROVIDER_EDGE_HOST_REACHABLE is set otel_v2: needs a proxy running with LITELLM_OTEL_V2=true; deselected unless E2E_OTEL_V2 is set + otel_tls: needs a stack whose gateway exports OTLP over TLS signed by the CA in SSL_CERT_FILE; deselected unless E2E_OTEL_EXPORTER_ENDPOINT is set diff --git a/tests/test_litellm/integrations/conftest.py b/tests/test_litellm/integrations/conftest.py new file mode 100644 index 00000000000..adc8e36e0af --- /dev/null +++ b/tests/test_litellm/integrations/conftest.py @@ -0,0 +1,96 @@ +import functools +import http.server +import ipaddress +import queue +import ssl +import threading +from collections.abc import Iterator +from dataclasses import dataclass +from datetime import datetime, timedelta, timezone +from pathlib import Path +from typing import Final + +import pytest + + +@dataclass(frozen=True, slots=True) +class TlsSink: + url: str + certificate_path: str + received: "queue.Queue[str]" + + +class _RecordingOtelHandler(http.server.BaseHTTPRequestHandler): + def __init__(self, *args: object, received: "queue.Queue[str]", **kwargs: object) -> None: + self._received: Final = received + super().__init__(*args, **kwargs) + + def do_POST(self) -> None: + length: Final = int(self.headers.get("Content-Length") or 0) + if length: + self.rfile.read(length) + self._received.put(self.path) + self.send_response(200) + self.send_header("Content-Type", "application/x-protobuf") + self.send_header("Content-Length", "0") + self.end_headers() + + def log_message(self, format: str, *args: object) -> None: + pass + + +def write_self_signed_cert(directory: Path, stem: str) -> tuple[Path, Path]: + from cryptography import x509 + from cryptography.hazmat.primitives import hashes, serialization + from cryptography.hazmat.primitives.asymmetric import rsa + from cryptography.x509.oid import NameOID + + key: Final = rsa.generate_private_key(public_exponent=65537, key_size=2048) + name: Final = x509.Name([x509.NameAttribute(NameOID.COMMON_NAME, "localhost")]) + certificate: Final = ( + x509.CertificateBuilder() + .subject_name(name) + .issuer_name(name) + .public_key(key.public_key()) + .serial_number(x509.random_serial_number()) + .not_valid_before(datetime.now(timezone.utc) - timedelta(minutes=1)) + .not_valid_after(datetime.now(timezone.utc) + timedelta(hours=1)) + .add_extension( + x509.SubjectAlternativeName([x509.DNSName("localhost"), x509.IPAddress(ipaddress.ip_address("127.0.0.1"))]), + critical=False, + ) + .sign(key, hashes.SHA256()) + ) + certificate_path: Final = directory / f"{stem}.crt" + certificate_path.write_bytes(certificate.public_bytes(serialization.Encoding.PEM)) + key_path: Final = directory / f"{stem}.key" + key_path.write_bytes( + key.private_bytes( + serialization.Encoding.PEM, + serialization.PrivateFormat.TraditionalOpenSSL, + serialization.NoEncryption(), + ) + ) + return certificate_path, key_path + + +@pytest.fixture +def tls_sink(tmp_path: Path) -> Iterator[TlsSink]: + certificate_path, key_path = write_self_signed_cert(tmp_path, "sink") + received: queue.Queue[str] = queue.Queue() + context: Final = ssl.SSLContext(ssl.PROTOCOL_TLS_SERVER) + context.load_cert_chain(str(certificate_path), str(key_path)) + server: Final = http.server.ThreadingHTTPServer( + ("127.0.0.1", 0), functools.partial(_RecordingOtelHandler, received=received) + ) + server.socket = context.wrap_socket(server.socket, server_side=True) + thread: Final = threading.Thread(target=server.serve_forever, daemon=True) + thread.start() + yield TlsSink( + url=f"https://127.0.0.1:{server.server_port}", + certificate_path=str(certificate_path), + received=received, + ) + server.shutdown() + server.server_close() + thread.join(timeout=5) diff --git a/tests/test_litellm/integrations/otel/test_otel_v2_components.py b/tests/test_litellm/integrations/otel/test_otel_v2_components.py index 0c95049ce05..79747ac9956 100644 --- a/tests/test_litellm/integrations/otel/test_otel_v2_components.py +++ b/tests/test_litellm/integrations/otel/test_otel_v2_components.py @@ -2,14 +2,17 @@ baggage helpers, metrics, the typed coercion helpers, mapper branches, span-name builders, and the registry validator's failure paths. Needs the OTel SDK.""" +import contextlib import json import threading +import time from collections.abc import Iterator from contextvars import Context as ContextVarContext from dataclasses import replace from http.server import BaseHTTPRequestHandler, HTTPServer, ThreadingHTTPServer import pytest +import requests pytest.importorskip("opentelemetry") @@ -18,6 +21,9 @@ from opentelemetry.proto.collector.trace.v1.trace_service_pb2 import ( # noqa: ) from opentelemetry import baggage # noqa: E402 from opentelemetry.context import attach, detach # noqa: E402 +from opentelemetry._logs.severity import SeverityNumber # noqa: E402 +from opentelemetry.sdk._logs import LogData, LogRecord # noqa: E402 +from opentelemetry.sdk._logs.export import LogExportResult # noqa: E402 from opentelemetry.sdk.metrics import MeterProvider # noqa: E402 from opentelemetry.sdk.metrics.export import InMemoryMetricReader # noqa: E402 from opentelemetry.sdk.trace import TracerProvider # noqa: E402 @@ -29,11 +35,14 @@ from opentelemetry.sdk.trace.export import ( # noqa: E402 from opentelemetry.sdk.trace.export.in_memory_span_exporter import ( # noqa: E402 InMemorySpanExporter, ) -from opentelemetry.trace import SpanKind, get_current_span # noqa: E402 +from opentelemetry.sdk.util.instrumentation import InstrumentationScope # noqa: E402 +from opentelemetry.trace import SpanKind, TraceFlags, get_current_span # noqa: E402 from opentelemetry.trace.propagation.tracecontext import ( # noqa: E402 TraceContextTextMapPropagator, ) +import litellm # noqa: E402 +from conftest import TlsSink # noqa: E402 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.model.config import OpenTelemetryV2Config # noqa: E402 @@ -1414,3 +1423,97 @@ def test_genai_mapper_guardrail_cost_in_spend_attr(): billed = dict(entry) del billed["guardrail_cost_in_spend"] assert LiteLLM.GUARDRAIL_COST_IN_SPEND not in GenAIMapper().map(GuardrailSpanData.from_logging_entry(billed)) + + +def _isolate_v2_otlp_tls_env(monkeypatch: pytest.MonkeyPatch) -> None: + for key in ( + "SSL_VERIFY", + "SSL_CERT_FILE", + "OTEL_EXPORTER_OTLP_CERTIFICATE", + "OTEL_EXPORTER_OTLP_TRACES_CERTIFICATE", + "OTEL_EXPORTER_OTLP_METRICS_CERTIFICATE", + "OTEL_EXPORTER_OTLP_LOGS_CERTIFICATE", + ): + monkeypatch.delenv(key, raising=False) + monkeypatch.setenv("OTEL_EXPORTER_OTLP_TIMEOUT", "2") + monkeypatch.setattr(litellm, "ssl_verify", True) + + +def test_v2_otlp_http_span_export_trusts_ssl_cert_file(monkeypatch: pytest.MonkeyPatch, tls_sink: TlsSink) -> None: + _isolate_v2_otlp_tls_env(monkeypatch) + monkeypatch.setenv("SSL_CERT_FILE", tls_sink.certificate_path) + cfg = OpenTelemetryV2Config(exporter="otlp_http", endpoint=tls_sink.url) + _export_one_span(cfg) + assert tls_sink.received.get(timeout=5) == "/v1/traces" + + +def test_v2_http_json_span_export_trusts_ssl_cert_file(monkeypatch: pytest.MonkeyPatch, tls_sink: TlsSink) -> None: + _isolate_v2_otlp_tls_env(monkeypatch) + monkeypatch.setenv("SSL_CERT_FILE", tls_sink.certificate_path) + cfg = OpenTelemetryV2Config(exporter="http/json", endpoint=tls_sink.url) + _export_one_span(cfg) + assert tls_sink.received.get(timeout=5) == "/v1/traces" + + +def test_v2_otlp_http_metric_export_trusts_ssl_cert_file(monkeypatch: pytest.MonkeyPatch, tls_sink: TlsSink) -> None: + _isolate_v2_otlp_tls_env(monkeypatch) + monkeypatch.setenv("SSL_CERT_FILE", tls_sink.certificate_path) + cfg = OpenTelemetryV2Config(exporter="otlp_http", endpoint=tls_sink.url) + reader = providers.build_metric_reader(cfg) + provider = MeterProvider(metric_readers=[reader]) + try: + provider.get_meter("v2-tls-test").create_counter("tls_export_test").add(1) + assert provider.force_flush(), "metric flush failed" + assert tls_sink.received.get(timeout=5) == "/v1/metrics" + finally: + provider.shutdown() + + +def test_v2_otlp_http_log_export_trusts_ssl_cert_file(monkeypatch: pytest.MonkeyPatch, tls_sink: TlsSink) -> None: + _isolate_v2_otlp_tls_env(monkeypatch) + monkeypatch.setenv("SSL_CERT_FILE", tls_sink.certificate_path) + cfg = OpenTelemetryV2Config(exporter="otlp_http", endpoint=tls_sink.url) + exporter = providers.build_log_exporter(cfg) + try: + record = LogRecord( + timestamp=int(time.time() * 1e9), + observed_timestamp=int(time.time() * 1e9), + trace_id=0, + span_id=0, + trace_flags=TraceFlags(0), + severity_number=SeverityNumber.INFO, + body="v2-tls-test", + ) + log_data = LogData(log_record=record, instrumentation_scope=InstrumentationScope("v2-tls-test")) + result = exporter.export([log_data]) + assert result is LogExportResult.SUCCESS, f"log export failed: {result}" + assert tls_sink.received.get(timeout=5) == "/v1/logs" + finally: + exporter.shutdown() + + +def test_v2_otlp_http_export_skips_verification_when_ssl_verify_false( + monkeypatch: pytest.MonkeyPatch, tls_sink: TlsSink +) -> None: + _isolate_v2_otlp_tls_env(monkeypatch) + monkeypatch.setenv("SSL_VERIFY", "false") + cfg = OpenTelemetryV2Config(exporter="otlp_http", endpoint=tls_sink.url) + _export_one_span(cfg) + assert tls_sink.received.get(timeout=5) == "/v1/traces" + + +def test_v2_otlp_http_export_rejects_untrusted_collector_by_default( + monkeypatch: pytest.MonkeyPatch, tls_sink: TlsSink +) -> None: + + + _isolate_v2_otlp_tls_env(monkeypatch) + cfg = OpenTelemetryV2Config(exporter="otlp_http", endpoint=tls_sink.url) + provider = providers.build_tracer_provider(cfg) + provider.get_tracer("probe").start_span("probe").end() + try: + with contextlib.suppress(requests.exceptions.SSLError): + provider.force_flush() + assert tls_sink.received.empty(), "sink received a request it should never have trusted" + finally: + provider.shutdown() diff --git a/tests/test_litellm/integrations/test_opentelemetry.py b/tests/test_litellm/integrations/test_opentelemetry.py index bea9a38e9dd..974961f2eb5 100644 --- a/tests/test_litellm/integrations/test_opentelemetry.py +++ b/tests/test_litellm/integrations/test_opentelemetry.py @@ -1,5 +1,6 @@ import asyncio import concurrent.futures +import contextlib import gc import json import os @@ -9,21 +10,30 @@ import time import unittest import weakref from datetime import datetime, timedelta, timezone +from pathlib import Path from types import MappingProxyType -from parameterized import parameterized +from typing import Final from unittest.mock import MagicMock, patch +import pytest + # Adds the grandparent directory to sys.path to allow importing project modules from opentelemetry import trace -from opentelemetry.sdk._logs import LogData +from opentelemetry._logs.severity import SeverityNumber +from opentelemetry.sdk._logs import LogData, LogRecord from opentelemetry.sdk._logs import LoggerProvider as OTLoggerProvider -from opentelemetry.sdk._logs.export import InMemoryLogExporter, SimpleLogRecordProcessor +from opentelemetry.sdk._logs.export import InMemoryLogExporter, LogExportResult, SimpleLogRecordProcessor from opentelemetry.sdk.metrics import MeterProvider from opentelemetry.sdk.metrics.export import InMemoryMetricReader, MetricsData -from opentelemetry.sdk.trace import TracerProvider -from opentelemetry.sdk.trace.export import SimpleSpanProcessor +from opentelemetry.sdk.trace import ReadableSpan, TracerProvider +from opentelemetry.sdk.trace.export import SimpleSpanProcessor, SpanExportResult +from opentelemetry.sdk.util.instrumentation import InstrumentationScope from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter +from parameterized import parameterized +import requests + +from conftest import TlsSink, write_self_signed_cert import litellm from litellm.integrations import opentelemetry as otel_module from litellm.integrations.opentelemetry import ( @@ -2081,6 +2091,138 @@ class TestOpenTelemetryEndpointNormalization(unittest.TestCase): self.assertEqual(traces, "http://collector:4318/v1/traces") +def _isolate_otlp_tls_env(monkeypatch: pytest.MonkeyPatch) -> None: + for key in ( + "SSL_VERIFY", + "SSL_CERT_FILE", + "OTEL_EXPORTER_OTLP_CERTIFICATE", + "OTEL_EXPORTER_OTLP_TRACES_CERTIFICATE", + "OTEL_EXPORTER_OTLP_METRICS_CERTIFICATE", + "OTEL_EXPORTER_OTLP_LOGS_CERTIFICATE", + ): + monkeypatch.delenv(key, raising=False) + monkeypatch.setenv("OTEL_EXPORTER_OTLP_TIMEOUT", "2") + monkeypatch.setattr(litellm, "ssl_verify", True) + + +def _ended_span() -> tuple[TracerProvider, ReadableSpan]: + provider: Final = TracerProvider() + span = provider.get_tracer(__name__).start_span("tls-export-test") + span.end() + return provider, span + + +def _assert_export_rejected(processor, span: ReadableSpan, sink: TlsSink) -> None: + with contextlib.suppress(requests.exceptions.SSLError): + result: Final = processor.span_exporter.export([span]) + assert result is SpanExportResult.FAILURE, f"rejected export must report failure, got {result}" + assert sink.received.empty(), "sink received a request it should never have trusted" + + +def _otlp_http_otel(endpoint: str) -> OpenTelemetry: + return OpenTelemetry(config=OpenTelemetryConfig(exporter="otlp_http", endpoint=endpoint)) + + +def test_otlp_http_span_export_trusts_ssl_cert_file(monkeypatch: pytest.MonkeyPatch, tls_sink: TlsSink) -> None: + _isolate_otlp_tls_env(monkeypatch) + monkeypatch.setenv("SSL_CERT_FILE", tls_sink.certificate_path) + otel: Final = _otlp_http_otel(tls_sink.url) + processor: Final = otel._get_span_processor() + provider, span = _ended_span() + try: + result: Final = processor.span_exporter.export([span]) + assert result is SpanExportResult.SUCCESS, f"span export failed: {result}" + assert tls_sink.received.get(timeout=5) == "/v1/traces" + finally: + processor.shutdown() + provider.shutdown() + + +def test_otlp_http_metric_export_trusts_ssl_cert_file(monkeypatch: pytest.MonkeyPatch, tls_sink: TlsSink) -> None: + _isolate_otlp_tls_env(monkeypatch) + monkeypatch.setenv("SSL_CERT_FILE", tls_sink.certificate_path) + otel: Final = _otlp_http_otel(tls_sink.url) + reader: Final = otel._get_metric_reader() + provider: Final = MeterProvider(metric_readers=[reader]) + try: + provider.get_meter(__name__).create_counter("tls_export_test").add(1) + assert provider.force_flush(), "metric flush failed" + assert tls_sink.received.get(timeout=5) == "/v1/metrics" + finally: + provider.shutdown() + + +def test_otlp_http_log_export_trusts_ssl_cert_file(monkeypatch: pytest.MonkeyPatch, tls_sink: TlsSink) -> None: + _isolate_otlp_tls_env(monkeypatch) + monkeypatch.setenv("SSL_CERT_FILE", tls_sink.certificate_path) + otel: Final = _otlp_http_otel(tls_sink.url) + exporter: Final = otel._get_log_exporter() + try: + record: Final = LogRecord( + timestamp=int(time.time() * 1e9), + observed_timestamp=int(time.time() * 1e9), + trace_id=0, + span_id=0, + trace_flags=trace.TraceFlags(0), + severity_number=SeverityNumber.INFO, + body="tls-export-test", + ) + log_data: Final = LogData(log_record=record, instrumentation_scope=InstrumentationScope("tls-export-test")) + result: Final = exporter.export([log_data]) + assert result is LogExportResult.SUCCESS, f"log export failed: {result}" + assert tls_sink.received.get(timeout=5) == "/v1/logs" + finally: + exporter.shutdown() + + +def test_otlp_http_export_skips_verification_when_ssl_verify_false( + monkeypatch: pytest.MonkeyPatch, tls_sink: TlsSink +) -> None: + _isolate_otlp_tls_env(monkeypatch) + monkeypatch.setenv("SSL_VERIFY", "false") + otel: Final = _otlp_http_otel(tls_sink.url) + processor: Final = otel._get_span_processor() + provider, span = _ended_span() + try: + result: Final = processor.span_exporter.export([span]) + assert result is SpanExportResult.SUCCESS, f"span export failed: {result}" + assert tls_sink.received.get(timeout=5) == "/v1/traces" + finally: + processor.shutdown() + provider.shutdown() + + +def test_otlp_http_export_rejects_untrusted_collector_by_default( + monkeypatch: pytest.MonkeyPatch, tls_sink: TlsSink +) -> None: + _isolate_otlp_tls_env(monkeypatch) + otel: Final = _otlp_http_otel(tls_sink.url) + processor: Final = otel._get_span_processor() + provider, span = _ended_span() + try: + _assert_export_rejected(processor, span, tls_sink) + finally: + processor.shutdown() + provider.shutdown() + + +def test_otel_certificate_env_takes_precedence_over_ssl_cert_file( + monkeypatch: pytest.MonkeyPatch, tmp_path: Path, tls_sink: TlsSink +) -> None: + _isolate_otlp_tls_env(monkeypatch) + unrelated_certificate, _ = write_self_signed_cert(tmp_path, "unrelated") + monkeypatch.setenv("SSL_CERT_FILE", tls_sink.certificate_path) + monkeypatch.setenv("OTEL_EXPORTER_OTLP_CERTIFICATE", str(unrelated_certificate)) + otel: Final = _otlp_http_otel(tls_sink.url) + processor: Final = otel._get_span_processor() + provider, span = _ended_span() + try: + _assert_export_rejected(processor, span, tls_sink) + finally: + processor.shutdown() + provider.shutdown() + + class TestOpenTelemetryProtocolSelection(unittest.TestCase): """Test suite for verifying correct exporter selection based on protocol""" From b73696a15d8385ee8a83b1289867306979a709d6 Mon Sep 17 00:00:00 2001 From: "berriai-litellm-provider-info-sync[bot]" <328147090+berriai-litellm-provider-info-sync[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 13:52:30 -0700 Subject: [PATCH 028/101] chore(prices): sync OpenAI prices: 3 models (#42557) gpt-5-2025-08-07: cache_read_input_token_cost_batches gpt-5-mini-2025-08-07: cache_read_input_token_cost_batches gpt-5-nano-2025-08-07: cache_read_input_token_cost_batches Co-authored-by: berriai-litellm-provider-info-sync[bot] <328147090+berriai-litellm-provider-info-sync[bot]@users.noreply.github.com> --- litellm/model_prices_and_context_window_backup.json | 3 +++ model_prices_and_context_window.json | 3 +++ 2 files changed, 6 insertions(+) diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index b8ca5ff27c7..b725094ae91 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -35613,6 +35613,7 @@ }, "gpt-5-2025-08-07": { "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_batches": 6.25e-08, "cache_read_input_token_cost_flex": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, "deprecation_date": "2026-12-11", @@ -36038,6 +36039,7 @@ }, "gpt-5-mini-2025-08-07": { "cache_read_input_token_cost": 2.5e-08, + "cache_read_input_token_cost_batches": 1.25e-08, "cache_read_input_token_cost_flex": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, "deprecation_date": "2026-12-11", @@ -36138,6 +36140,7 @@ }, "gpt-5-nano-2025-08-07": { "cache_read_input_token_cost": 5e-09, + "cache_read_input_token_cost_batches": 2.5e-09, "cache_read_input_token_cost_flex": 2.5e-09, "deprecation_date": "2026-12-11", "input_cost_per_token": 5e-08, diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index b8ca5ff27c7..b725094ae91 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -35613,6 +35613,7 @@ }, "gpt-5-2025-08-07": { "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_batches": 6.25e-08, "cache_read_input_token_cost_flex": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, "deprecation_date": "2026-12-11", @@ -36038,6 +36039,7 @@ }, "gpt-5-mini-2025-08-07": { "cache_read_input_token_cost": 2.5e-08, + "cache_read_input_token_cost_batches": 1.25e-08, "cache_read_input_token_cost_flex": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, "deprecation_date": "2026-12-11", @@ -36138,6 +36140,7 @@ }, "gpt-5-nano-2025-08-07": { "cache_read_input_token_cost": 5e-09, + "cache_read_input_token_cost_batches": 2.5e-09, "cache_read_input_token_cost_flex": 2.5e-09, "deprecation_date": "2026-12-11", "input_cost_per_token": 5e-08, From 0e6a288458640f4499e646c1d0ad445c14a85bfb Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 14:04:16 -0700 Subject: [PATCH 029/101] fix(ssrf): point the blocked-address remediation at litellm_settings (#42508) * fix(ssrf): point the blocked-address remediation at litellm_settings Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(ssrf): pin the block message's named section to litellm_settings Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(compaction): pin litellm.max_budget so leaked proxy budget cannot 401 the child auth Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: shivam Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- .../prompt_templates/image_handling.py | 2 +- litellm/litellm_core_utils/url_utils.py | 2 +- .../litellm_core_utils/test_image_handling.py | 2 +- .../proxy/proxy_server/test_proxy_config.py | 28 +++++++++++++++++++ .../proxy/test_native_compaction.py | 2 ++ 5 files changed, 33 insertions(+), 3 deletions(-) diff --git a/litellm/litellm_core_utils/prompt_templates/image_handling.py b/litellm/litellm_core_utils/prompt_templates/image_handling.py index c9933422cc3..c44c80bc0a0 100644 --- a/litellm/litellm_core_utils/prompt_templates/image_handling.py +++ b/litellm/litellm_core_utils/prompt_templates/image_handling.py @@ -82,7 +82,7 @@ def _rejected_image_fetch(url: str, verdict: SSRFError) -> "litellm.ImageFetchEr verbose_logger.warning("Image fetch of %s rejected before any request went out: %s", url, verdict) return litellm.ImageFetchError( "Error: Unable to fetch image from URL. The proxy could not resolve this host or its URL policy rejected it; " - f"an admin can check the proxy log and `user_url_allowed_hosts` in general_settings. url={url}" + f"an admin can check the proxy log and `user_url_allowed_hosts` in litellm_settings. url={url}" ) diff --git a/litellm/litellm_core_utils/url_utils.py b/litellm/litellm_core_utils/url_utils.py index b94d5a6886d..6c87ef4a3de 100644 --- a/litellm/litellm_core_utils/url_utils.py +++ b/litellm/litellm_core_utils/url_utils.py @@ -336,7 +336,7 @@ def validate_url(url: str) -> tuple[str, str]: raise SSRFError( f"URL targets a blocked address ({resolved_ip}). " "If this is a legitimate internal service, add the host " - "to `user_url_allowed_hosts` in general_settings." + "to `user_url_allowed_hosts` in litellm_settings." ) # For HTTPS with SSL verification enabled, TLS certificate validation diff --git a/tests/test_litellm/litellm_core_utils/test_image_handling.py b/tests/test_litellm/litellm_core_utils/test_image_handling.py index 8fa4bd6c14d..21e97e97357 100644 --- a/tests/test_litellm/litellm_core_utils/test_image_handling.py +++ b/tests/test_litellm/litellm_core_utils/test_image_handling.py @@ -427,7 +427,7 @@ async def test_async_inline_remote_media_cancels_the_other_fetches_when_one_fail _SSRF_VERDICTS = ( SSRFError( "URL targets a blocked address (10.0.0.8). If this is a legitimate internal service, " - "add the host to `user_url_allowed_hosts` in general_settings." + "add the host to `user_url_allowed_hosts` in litellm_settings." ), SSRFError("DNS resolution failed for 'internal.example': [Errno 8] nodename nor servname provided, or not known"), SSRFError("No addresses found for 'internal.example'"), diff --git a/tests/test_litellm/proxy/proxy_server/test_proxy_config.py b/tests/test_litellm/proxy/proxy_server/test_proxy_config.py index 832ac6402d9..b47cce43dcc 100644 --- a/tests/test_litellm/proxy/proxy_server/test_proxy_config.py +++ b/tests/test_litellm/proxy/proxy_server/test_proxy_config.py @@ -2198,6 +2198,34 @@ async def test_ProxyConfig_load_config_wires_general_settings_url_validation(tmp litellm.provider_url_destination_allowed_hosts = original_provider_hosts +@pytest.mark.asyncio +async def test_ssrf_block_message_names_a_config_section_load_config_honors(tmp_path, monkeypatch): + """Regression for LIT-8349: the remediation in the SSRF block message must point at a section that works.""" + from litellm.litellm_core_utils.url_utils import SSRFError, validate_url + + monkeypatch.setattr(litellm, "user_url_allowed_hosts", []) + monkeypatch.setattr(litellm, "user_url_validation", True) + with pytest.raises(SSRFError) as blocked: + validate_url("http://10.96.3.245:10002/agent.json") + section_match = re.search(r"add the host to `user_url_allowed_hosts` in (\w+)\.", str(blocked.value)) + assert section_match is not None, str(blocked.value) + section: Final = section_match.group(1) + assert section == "litellm_settings", f"block message points admins at {section}, which the docs contradict" + + f = tmp_path / "c.yaml" + f.write_text(f"model_list: []\n{section}:\n user_url_allowed_hosts:\n - '10.96.3.245:10002'\n") + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", None) + monkeypatch.setattr("litellm.proxy.proxy_server.store_model_in_db", False) + monkeypatch.delenv("LITELLM_CONFIG_BUCKET_NAME", raising=False) + await ProxyConfig().load_config(router=None, config_file_path=str(f)) + + assert litellm.user_url_allowed_hosts == ["10.96.3.245:10002"], f"{section} did not apply the allowlist" + assert validate_url("http://10.96.3.245:10002/agent.json") == ( + "http://10.96.3.245:10002/agent.json", + "10.96.3.245:10002", + ) + + @pytest.mark.asyncio async def test_ProxyConfig_load_config_wires_config_reload_interval(tmp_path, monkeypatch): """general_settings.proxy_config_reload_interval_seconds must reach the proxy_server diff --git a/tests/test_litellm/proxy/test_native_compaction.py b/tests/test_litellm/proxy/test_native_compaction.py index d24624aacc5..9a6b4cdda65 100644 --- a/tests/test_litellm/proxy/test_native_compaction.py +++ b/tests/test_litellm/proxy/test_native_compaction.py @@ -7,6 +7,7 @@ import pytest from fastapi import FastAPI, Request from pydantic import TypeAdapter +import litellm from litellm.caching.caching import DualCache from litellm.exceptions import BadRequestError from litellm.litellm_core_utils.initialize_dynamic_callback_params import inherit_message_logging_privacy @@ -112,6 +113,7 @@ async def test_real_proxy_child_auth_privacy_and_body_policy( }))) return asyncio.sleep(0, result=ModelResponse(id="private-summary", model="compactor")) + monkeypatch.setattr(litellm, "max_budget", 0) monkeypatch.setattr(proxy_server.app, "dependency_overrides", {}) monkeypatch.setattr(proxy_server, "master_key", "sk-master-fixture") monkeypatch.setattr(proxy_server, "prisma_client", object()) From e30f9f578c9af0dd48b837a318a6246ad6e2f23e Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 14:05:33 -0700 Subject: [PATCH 030/101] fix(model_prices): registry audit 2026-09-22, absorb open pricing PRs (#42543) * fix(model_prices): registry audit 2026-09-22, absorb open pricing PRs Rolls the open registry-only PRs into one PR after re-verifying every value against the official provider source: OpenAI, Azure, Vertex AI and Gemini batch cache-read prices, Baseten model metadata from the authenticated inference API, Bedrock eu-west-2 Nemotron Super 3 pricing from the AWS offer file, and OpenRouter prices refreshed from the live OpenRouter models API Co-authored-by: sinksilk <785976238@qq.com> Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(model_prices): add groq/llama-guard-3-8b from the Groq model page Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(model_prices): refresh openrouter deepseek aliases from live api and drop stale off-peak windows Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(model_prices): resolve baseten merge conflicts against main Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> Co-authored-by: sinksilk <785976238@qq.com> --- ...odel_prices_and_context_window_backup.json | 376 ++++++++++++++---- model_prices_and_context_window.json | 376 ++++++++++++++---- tests/test_litellm/test_cost_calculator.py | 24 ++ 3 files changed, 608 insertions(+), 168 deletions(-) diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index b725094ae91..94786f250b0 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -4417,7 +4417,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 6.875e-08 }, "azure/eu/gpt-5-mini-2025-08-07": { "cache_read_input_token_cost": 2.75e-08, @@ -4456,7 +4457,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 1.375e-08 }, "azure/eu/gpt-5.1": { "deprecation_date": "2027-05-15", @@ -4636,7 +4638,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 2.75e-09 }, "azure/eu/o1-2024-12-17": { "cache_read_input_token_cost": 8.25e-06, @@ -6094,7 +6097,8 @@ "input_cost_per_token_batches": 6.25e-07, "output_cost_per_token_batches": 5e-06, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supports_minimal_reasoning_effort": true + "supports_minimal_reasoning_effort": true, + "cache_read_input_token_cost_batches": 6.25e-08 }, "azure/gpt-5.1-chat-2025-11-13": { "cache_read_input_token_cost": 1.25e-07, @@ -6282,7 +6286,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 6.25e-08 }, "azure/gpt-5-chat": { "cache_read_input_token_cost": 1.25e-07, @@ -6460,7 +6465,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 1.25e-08 }, "azure/gpt-5-nano": { "deprecation_date": "2027-02-09", @@ -6533,7 +6539,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 2.5e-09 }, "azure/gpt-5-pro": { "deprecation_date": "2027-04-07", @@ -6822,7 +6829,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 8.75e-08 }, "azure/gpt-5.2-chat": { "cache_read_input_token_cost": 1.75e-07, @@ -7287,7 +7295,11 @@ "output_cost_per_token_flex": 7.5e-06, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_xhigh_reasoning_effort": true, - "supports_minimal_reasoning_effort": true + "supports_minimal_reasoning_effort": true, + "cache_read_input_token_cost_above_272k_tokens_batches": 2.5e-07, + "cache_read_input_token_cost_batches": 1.3e-07, + "input_cost_per_token_above_272k_tokens_batches": 2.5e-06, + "output_cost_per_token_above_272k_tokens_batches": 1.125e-05 }, "azure/us/gpt-5.4-2026-03-05": { "cache_read_input_token_cost": 2.75e-07, @@ -7333,7 +7345,11 @@ "output_cost_per_token_batches": 8.25e-06, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_xhigh_reasoning_effort": true, - "supports_minimal_reasoning_effort": true + "supports_minimal_reasoning_effort": true, + "cache_read_input_token_cost_above_272k_tokens_batches": 2.75e-07, + "cache_read_input_token_cost_batches": 1.43e-07, + "input_cost_per_token_above_272k_tokens_batches": 2.75e-06, + "output_cost_per_token_above_272k_tokens_batches": 1.2375e-05 }, "azure/eu/gpt-5.4-2026-03-05": { "cache_read_input_token_cost": 2.75e-07, @@ -7379,7 +7395,11 @@ "output_cost_per_token_batches": 8.25e-06, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_xhigh_reasoning_effort": true, - "supports_minimal_reasoning_effort": true + "supports_minimal_reasoning_effort": true, + "cache_read_input_token_cost_above_272k_tokens_batches": 2.75e-07, + "cache_read_input_token_cost_batches": 1.43e-07, + "input_cost_per_token_above_272k_tokens_batches": 2.75e-06, + "output_cost_per_token_above_272k_tokens_batches": 1.2375e-05 }, "azure/gpt-5.4-pro": { "deprecation_date": "2027-09-07", @@ -7477,7 +7497,9 @@ "supports_system_messages": true, "supports_tool_choice": true, "supports_vision": true, - "supports_web_search": true + "supports_web_search": true, + "input_cost_per_token_above_272k_tokens_batches": 3e-05, + "output_cost_per_token_above_272k_tokens_batches": 0.000135 }, "azure/gpt-5.6": { "cache_creation_input_token_cost": 6.25e-06, @@ -8900,7 +8922,11 @@ "supports_none_reasoning_effort": true, "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", + "cache_read_input_token_cost_above_272k_tokens_batches": 5e-07, + "cache_read_input_token_cost_batches": 2.5e-07, + "input_cost_per_token_above_272k_tokens_batches": 5e-06, + "output_cost_per_token_above_272k_tokens_batches": 2.25e-05 }, "azure/us/gpt-5.5-2026-04-23": { "cache_read_input_token_cost": 5.5e-07, @@ -9003,7 +9029,11 @@ "supports_none_reasoning_effort": true, "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", + "cache_read_input_token_cost_above_272k_tokens_batches": 5.5e-07, + "cache_read_input_token_cost_batches": 2.75e-07, + "input_cost_per_token_above_272k_tokens_batches": 5.5e-06, + "output_cost_per_token_above_272k_tokens_batches": 2.475e-05 }, "azure/eu/gpt-5.5-2026-04-23": { "cache_read_input_token_cost": 5.5e-07, @@ -9106,7 +9136,11 @@ "supports_none_reasoning_effort": true, "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", + "cache_read_input_token_cost_above_272k_tokens_batches": 5.5e-07, + "cache_read_input_token_cost_batches": 2.75e-07, + "input_cost_per_token_above_272k_tokens_batches": 5.5e-06, + "output_cost_per_token_above_272k_tokens_batches": 2.475e-05 }, "azure/gpt-5.5-pro": { "cache_read_input_token_cost": 3e-06, @@ -9293,7 +9327,8 @@ "output_cost_per_token_flex": 2.25e-06, "output_cost_per_token_priority": 9e-06, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supports_xhigh_reasoning_effort": true + "supports_xhigh_reasoning_effort": true, + "cache_read_input_token_cost_batches": 3.75e-08 }, "azure/gpt-5.4-nano": { "deprecation_date": "2027-09-21", @@ -9390,7 +9425,8 @@ "output_cost_per_token_batches": 6.25e-07, "output_cost_per_token_flex": 6.25e-07, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supports_xhigh_reasoning_effort": true + "supports_xhigh_reasoning_effort": true, + "cache_read_input_token_cost_batches": 1e-08 }, "azure/gpt-image-1": { "cache_read_input_token_cost": 1.25e-06, @@ -10404,7 +10440,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 6.875e-08 }, "azure/us/gpt-5-mini-2025-08-07": { "cache_read_input_token_cost": 2.75e-08, @@ -10443,7 +10480,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 1.375e-08 }, "azure/us/gpt-5-nano-2025-08-07": { "cache_read_input_token_cost": 5.5e-09, @@ -10479,7 +10517,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 2.75e-09 }, "azure/us/gpt-5.1": { "deprecation_date": "2027-05-15", @@ -12908,6 +12947,23 @@ "supports_tool_choice": true, "output_cost_per_token": 1.86e-06 }, + "bedrock/eu-west-2/nvidia.nemotron-super-3-120b": { + "input_cost_per_token": 2.3e-07, + "litellm_provider": "bedrock", + "max_input_tokens": 256000, + "max_output_tokens": 32000, + "max_tokens": 32000, + "mode": "chat", + "output_cost_per_token": 1.01e-06, + "source": "https://aws.amazon.com/bedrock/pricing/", + "supports_audio_input": false, + "supports_function_calling": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": false + }, "bedrock/eu-west-2/qwen.qwen3-coder-next": { "input_cost_per_token": 7.8e-07, "litellm_provider": "bedrock", @@ -26782,7 +26838,8 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, - "web_search_billing_unit": "per_query" + "web_search_billing_unit": "per_query", + "cache_read_input_token_cost_batches": 1e-07 }, "gemini-3-pro-image-preview": { "input_cost_per_image": 0.0011, @@ -26867,7 +26924,8 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, - "web_search_billing_unit": "per_query" + "web_search_billing_unit": "per_query", + "cache_read_input_token_cost_batches": 2.5e-08 }, "gemini-3.1-flash-image-preview": { "input_cost_per_image": 0.00056, @@ -26946,7 +27004,8 @@ "supports_response_schema": false, "supports_system_messages": true, "supports_video_input": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 1.25e-08 }, "gemini-3.1-flash-lite-preview": { "cache_read_input_token_cost": 2.5e-08, @@ -27055,7 +27114,8 @@ }, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014, - "input_cost_per_audio_token_batches": 2.5e-07 + "input_cost_per_audio_token_batches": 2.5e-07, + "cache_read_input_token_cost_batches": 1.25e-08 }, "gemini-3.5-flash-lite": { "deprecation_date": "2027-07-21", @@ -27112,7 +27172,8 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "cache_read_input_token_cost_batches": 1.5e-08 }, "deep-research-pro-preview-12-2025": { "cache_read_input_token_cost": 2e-07, @@ -27147,7 +27208,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_vision": true, - "supports_web_search": true + "supports_web_search": true, + "cache_read_input_token_cost_batches": 1e-07 }, "gemini-2.5-flash-lite": { "cache_read_input_audio_token_cost": 3e-08, @@ -27880,7 +27942,8 @@ "output_cost_per_token_batches": 4.5e-06, "input_cost_per_token_flex": 7.5e-07, "output_cost_per_token_flex": 4.5e-06, - "cache_read_input_token_cost_flex": 7.5e-08 + "cache_read_input_token_cost_flex": 7.5e-08, + "cache_read_input_token_cost_batches": 7.5e-08 }, "vertex_ai/gemini-3.6-flash": { "prompt_cache_min_tokens": 4096, @@ -27937,7 +28000,8 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "cache_read_input_token_cost_batches": 3.75e-08 }, "vertex_ai/gemini-3.7-flash": { "prompt_cache_min_tokens": 4096, @@ -27995,7 +28059,8 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "cache_read_input_token_cost_batches": 3.75e-08 }, "vertex_ai/gemini-3.8-flash": { "prompt_cache_min_tokens": 4096, @@ -28053,7 +28118,8 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "cache_read_input_token_cost_batches": 3.75e-08 }, "vertex_ai/gemini-3.1-pro-preview": { "prompt_cache_min_tokens": 4096, @@ -30385,7 +30451,8 @@ "output_cost_per_token_batches": 4.5e-06, "input_cost_per_token_flex": 7.5e-07, "output_cost_per_token_flex": 4.5e-06, - "cache_read_input_token_cost_flex": 7.5e-08 + "cache_read_input_token_cost_flex": 7.5e-08, + "cache_read_input_token_cost_batches": 7.5e-08 }, "gemini-3.6-flash": { "prompt_cache_min_tokens": 4096, @@ -30442,7 +30509,8 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "cache_read_input_token_cost_batches": 3.75e-08 }, "gemini-3.7-flash": { "prompt_cache_min_tokens": 4096, @@ -30500,7 +30568,8 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "cache_read_input_token_cost_batches": 3.75e-08 }, "gemini-3.8-flash": { "prompt_cache_min_tokens": 4096, @@ -30558,7 +30627,8 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "cache_read_input_token_cost_batches": 3.75e-08 }, "gemini/gemini-2.5-pro-preview-tts": { "cache_read_input_token_cost": 1.25e-07, @@ -35661,7 +35731,8 @@ "supports_web_search": true, "supports_none_reasoning_effort": false, "supports_xhigh_reasoning_effort": false, - "supports_minimal_reasoning_effort": true + "supports_minimal_reasoning_effort": true, + "cache_read_input_token_cost_batches": 6.25e-08 }, "gpt-5-chat": { "cache_read_input_token_cost": 1.25e-07, @@ -36087,7 +36158,8 @@ "supports_web_search": true, "supports_none_reasoning_effort": false, "supports_xhigh_reasoning_effort": false, - "supports_minimal_reasoning_effort": true + "supports_minimal_reasoning_effort": true, + "cache_read_input_token_cost_batches": 1.25e-08 }, "gpt-5-nano": { "cache_read_input_token_cost": 5e-09, @@ -36186,7 +36258,8 @@ "supports_web_search": true, "supports_none_reasoning_effort": false, "supports_xhigh_reasoning_effort": false, - "supports_minimal_reasoning_effort": true + "supports_minimal_reasoning_effort": true, + "cache_read_input_token_cost_batches": 2.5e-09 }, "gpt-image-1": { "cache_read_input_token_cost": 1.25e-06, @@ -36809,6 +36882,15 @@ "supports_response_schema": false, "supports_tool_choice": true }, + "groq/llama-guard-3-8b": { + "input_cost_per_token": 2e-07, + "litellm_provider": "groq", + "max_input_tokens": 8192, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 2e-07, + "source": "https://console.groq.com/docs/model/llama-guard-3-8b" + }, "groq/gemma-7b-it": { "deprecation_date": "2024-12-18", "input_cost_per_token": 5e-08, @@ -43157,6 +43239,28 @@ "supports_web_search": true, "supports_xhigh_reasoning_effort": true }, + "openrouter/anthropic/claude-opus-5.5": { + "cache_creation_input_token_cost": 5e-06, + "cache_creation_input_token_cost_above_1hr": 8e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 4e-06, + "litellm_provider": "openrouter", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2e-05, + "source": "https://openrouter.ai/api/v1/models", + "supports_audio_input": false, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true + }, "openrouter/bytedance/ui-tars-1.5-7b": { "cache_read_input_token_cost": 1e-07, "input_cost_per_token": 1e-07, @@ -43328,21 +43432,21 @@ "supports_web_search": false }, "openrouter/deepseek/deepseek-v4-pro": { - "input_cost_per_token": 9.31074e-07, + "input_cost_per_token": 8.92272e-07, "input_cost_per_token_cache_hit": 4.4e-08, "litellm_provider": "openrouter", "max_input_tokens": 1048576, "max_output_tokens": 384000, "max_tokens": 384000, "mode": "chat", - "output_cost_per_token": 1.862148e-06, + "output_cost_per_token": 1.784544e-06, "source": "https://openrouter.ai/api/v1/models", "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, - "cache_read_input_token_cost": 7.75895e-08, + "cache_read_input_token_cost": 7.4356e-08, "supports_audio_input": false, "supports_pdf_input": false, "supports_vision": false, @@ -52043,7 +52147,8 @@ "output_cost_per_token_flex": 6e-06, "output_cost_per_token_priority": 2.16e-05, "supports_reasoning": false, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", + "cache_read_input_token_cost_batches": 1e-07 }, "vertex_ai/gemini-3-pro-image-preview": { "input_cost_per_image": 0.0011, @@ -52080,7 +52185,8 @@ "output_cost_per_token_batches": 1.5e-06, "output_cost_per_token_flex": 1.5e-06, "supports_reasoning": false, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", + "cache_read_input_token_cost_batches": 2.5e-08 }, "vertex_ai/gemini-3.1-flash-image-preview": { "input_cost_per_image": 0.00056, @@ -52135,7 +52241,8 @@ "supports_response_schema": false, "supports_system_messages": true, "supports_video_input": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 1.25e-08 }, "vertex_ai/gemini-3.1-flash-lite-preview": { "cache_read_input_token_cost": 2.5e-08, @@ -52245,7 +52352,8 @@ }, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014, - "input_cost_per_audio_token_batches": 2.5e-07 + "input_cost_per_audio_token_batches": 2.5e-07, + "cache_read_input_token_cost_batches": 1.25e-08 }, "vertex_ai/gemini-3.5-flash-lite": { "deprecation_date": "2027-07-21", @@ -52303,7 +52411,8 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "cache_read_input_token_cost_batches": 1.5e-08 }, "vertex_ai/deep-research-pro-preview-12-2025": { "cache_read_input_token_cost": 2e-07, @@ -52319,7 +52428,8 @@ "output_cost_per_image_token": 0.00012, "output_cost_per_token": 1.2e-05, "output_cost_per_token_batches": 6e-06, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", + "cache_read_input_token_cost_batches": 1e-07 }, "vertex_ai/imagegeneration@006": { "deprecation_date": "2025-09-24", @@ -69143,13 +69253,13 @@ "supports_web_search": false }, "openrouter/qwen/qwen3.6-27b": { - "input_cost_per_token": 3e-07, - "output_cost_per_token": 2e-06, - "cache_read_input_token_cost": 3e-08, + "input_cost_per_token": 3.2e-07, + "output_cost_per_token": 2.7e-06, + "cache_read_input_token_cost": 1.5e-07, "litellm_provider": "openrouter", "max_input_tokens": 262144, - "max_output_tokens": 65536, - "max_tokens": 65536, + "max_output_tokens": 262140, + "max_tokens": 262140, "mode": "chat", "source": "https://openrouter.ai/api/v1/models", "supports_audio_input": false, @@ -73178,16 +73288,16 @@ "supports_web_search": true }, "openrouter/~anthropic/claude-opus-latest": { - "cache_creation_input_token_cost": 6.25e-06, - "cache_creation_input_token_cost_above_1hr": 1e-05, - "cache_read_input_token_cost": 5e-07, - "input_cost_per_token": 5e-06, + "cache_creation_input_token_cost": 5e-06, + "cache_creation_input_token_cost_above_1hr": 8e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 4e-06, "litellm_provider": "openrouter", "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 2.5e-05, + "output_cost_per_token": 2e-05, "source": "https://openrouter.ai/api/v1/models", "supports_audio_input": false, "supports_function_calling": true, @@ -73222,15 +73332,14 @@ "supports_web_search": true }, "openrouter/~deepseek/deepseek-flash-latest": { - "cache_read_input_token_cost": 6e-09, - "input_cost_per_token": 3e-07, + "cache_read_input_token_cost": 3.6e-09, + "input_cost_per_token": 1.2e-07, "litellm_provider": "openrouter", "max_input_tokens": 1048576, - "max_output_tokens": 384000, - "max_tokens": 384000, + "max_output_tokens": 943718, + "max_tokens": 943718, "mode": "chat", - "off_peak_pricing": {"windows":[{"weekdays":["saturday","sunday"],"hours_utc":"00:00-00:00"},{"weekdays":["monday","tuesday","wednesday","thursday","friday"],"hours_utc":"00:00-01:00"},{"weekdays":["monday","tuesday","wednesday","thursday","friday"],"hours_utc":"04:00-06:00"},{"weekdays":["monday","tuesday","wednesday","thursday","friday"],"hours_utc":"10:00-00:00"}],"input_cost_per_token":1.5e-7,"output_cost_per_token":6e-7,"cache_read_input_token_cost":3e-9}, - "output_cost_per_token": 1.2e-06, + "output_cost_per_token": 4.8e-07, "source": "https://openrouter.ai/api/v1/models", "supports_audio_input": false, "supports_function_calling": true, @@ -73243,15 +73352,14 @@ "supports_web_search": false }, "openrouter/~deepseek/deepseek-pro-latest": { - "cache_read_input_token_cost": 4.4e-08, - "input_cost_per_token": 1.32e-06, + "cache_read_input_token_cost": 1.2726e-08, + "input_cost_per_token": 3.9996e-07, "litellm_provider": "openrouter", "max_input_tokens": 1048576, - "max_output_tokens": 384000, - "max_tokens": 384000, + "max_output_tokens": 393216, + "max_tokens": 393216, "mode": "chat", - "off_peak_pricing": {"windows":[{"weekdays":["saturday","sunday"],"hours_utc":"00:00-00:00"},{"weekdays":["monday","tuesday","wednesday","thursday","friday"],"hours_utc":"00:00-01:00"},{"weekdays":["monday","tuesday","wednesday","thursday","friday"],"hours_utc":"04:00-06:00"},{"weekdays":["monday","tuesday","wednesday","thursday","friday"],"hours_utc":"10:00-00:00"}],"input_cost_per_token":6.6e-7,"output_cost_per_token":0.00000198,"cache_read_input_token_cost":2.2e-8}, - "output_cost_per_token": 3.96e-06, + "output_cost_per_token": 1.19988e-06, "source": "https://openrouter.ai/api/v1/models", "supports_audio_input": false, "supports_function_calling": true, @@ -73264,14 +73372,14 @@ "supports_web_search": false }, "openrouter/~deepseek/deepseek-v4-flash-latest": { - "cache_read_input_token_cost": 1.6e-08, - "input_cost_per_token": 4e-08, + "cache_read_input_token_cost": 8e-09, + "input_cost_per_token": 3e-08, "litellm_provider": "openrouter", "max_input_tokens": 1310720, "max_output_tokens": 943718, "max_tokens": 943718, "mode": "chat", - "output_cost_per_token": 6.4e-07, + "output_cost_per_token": 8e-07, "source": "https://openrouter.ai/api/v1/models", "supports_audio_input": false, "supports_function_calling": true, @@ -73334,13 +73442,13 @@ }, "openrouter/~moonshotai/kimi-latest": { "cache_read_input_token_cost": 3e-07, - "input_cost_per_token": 3e-06, + "input_cost_per_token": 1.4989e-06, "litellm_provider": "openrouter", "max_input_tokens": 1048576, "max_output_tokens": 943718, "max_tokens": 943718, "mode": "chat", - "output_cost_per_token": 1.5e-05, + "output_cost_per_token": 1.0758e-05, "source": "https://openrouter.ai/api/v1/models", "supports_audio_input": false, "supports_function_calling": true, @@ -73378,19 +73486,19 @@ "supports_web_search": true }, "openrouter/~openai/gpt-luna-latest": { - "cache_creation_input_token_cost": 2.5e-07, - "cache_creation_input_token_cost_above_272k_tokens": 5e-07, - "cache_read_input_token_cost": 2e-08, - "cache_read_input_token_cost_above_272k_tokens": 4e-08, - "input_cost_per_token": 2e-07, - "input_cost_per_token_above_272k_tokens": 4e-07, + "cache_creation_input_token_cost": 1.25e-07, + "cache_creation_input_token_cost_above_272k_tokens": 2.5e-07, + "cache_read_input_token_cost": 1e-08, + "cache_read_input_token_cost_above_272k_tokens": 2e-08, + "input_cost_per_token": 1e-07, + "input_cost_per_token_above_272k_tokens": 2e-07, "litellm_provider": "openrouter", "max_input_tokens": 1050000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.2e-06, - "output_cost_per_token_above_272k_tokens": 1.8e-06, + "output_cost_per_token": 5e-07, + "output_cost_per_token_above_272k_tokens": 7.5e-07, "source": "https://openrouter.ai/api/v1/models", "supports_audio_input": false, "supports_function_calling": true, @@ -73496,14 +73604,14 @@ "supports_web_search": true }, "openrouter/~z-ai/glm-flash-latest": { - "cache_read_input_token_cost": 5e-08, - "input_cost_per_token": 1.5e-07, + "cache_read_input_token_cost": 1.5e-08, + "input_cost_per_token": 7.5e-08, "litellm_provider": "openrouter", "max_input_tokens": 1310720, "max_output_tokens": 943718, "max_tokens": 943718, "mode": "chat", - "output_cost_per_token": 5e-07, + "output_cost_per_token": 2.5e-07, "source": "https://openrouter.ai/api/v1/models", "supports_audio_input": false, "supports_function_calling": true, @@ -75959,6 +76067,106 @@ "supports_vision": true, "supports_web_search": true }, + "openrouter/openai/gpt-6-luna": { + "cache_creation_input_token_cost": 1.25e-07, + "cache_creation_input_token_cost_above_272k_tokens": 2.5e-07, + "cache_read_input_token_cost": 1e-08, + "cache_read_input_token_cost_above_272k_tokens": 2e-08, + "input_cost_per_token": 1e-07, + "input_cost_per_token_above_272k_tokens": 2e-07, + "litellm_provider": "openrouter", + "max_input_tokens": 1050000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 5e-07, + "output_cost_per_token_above_272k_tokens": 7.5e-07, + "source": "https://openrouter.ai/api/v1/models", + "supports_audio_input": false, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true + }, + "openrouter/openai/gpt-6-luna-pro": { + "cache_creation_input_token_cost": 1.25e-07, + "cache_creation_input_token_cost_above_272k_tokens": 2.5e-07, + "cache_read_input_token_cost": 1e-08, + "cache_read_input_token_cost_above_272k_tokens": 2e-08, + "input_cost_per_token": 1e-07, + "input_cost_per_token_above_272k_tokens": 2e-07, + "litellm_provider": "openrouter", + "max_input_tokens": 1050000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 5e-07, + "output_cost_per_token_above_272k_tokens": 7.5e-07, + "source": "https://openrouter.ai/api/v1/models", + "supports_audio_input": false, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true + }, + "openrouter/openai/gpt-6-sol": { + "cache_creation_input_token_cost": 2.5e-06, + "cache_creation_input_token_cost_above_272k_tokens": 5e-06, + "cache_read_input_token_cost": 2e-07, + "cache_read_input_token_cost_above_272k_tokens": 4e-07, + "input_cost_per_token": 2e-06, + "input_cost_per_token_above_272k_tokens": 4e-06, + "litellm_provider": "openrouter", + "max_input_tokens": 1050000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1e-05, + "output_cost_per_token_above_272k_tokens": 1.5e-05, + "source": "https://openrouter.ai/api/v1/models", + "supports_audio_input": false, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true + }, + "openrouter/openai/gpt-6-sol-pro": { + "cache_creation_input_token_cost": 2.5e-06, + "cache_creation_input_token_cost_above_272k_tokens": 5e-06, + "cache_read_input_token_cost": 2e-07, + "cache_read_input_token_cost_above_272k_tokens": 4e-07, + "input_cost_per_token": 2e-06, + "input_cost_per_token_above_272k_tokens": 4e-06, + "litellm_provider": "openrouter", + "max_input_tokens": 1050000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1e-05, + "output_cost_per_token_above_272k_tokens": 1.5e-05, + "source": "https://openrouter.ai/api/v1/models", + "supports_audio_input": false, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true + }, "openrouter/openai/o3-mini:batch": { "cache_read_input_token_cost": 2.75e-07, "input_cost_per_token": 5.5e-07, diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index b725094ae91..94786f250b0 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -4417,7 +4417,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 6.875e-08 }, "azure/eu/gpt-5-mini-2025-08-07": { "cache_read_input_token_cost": 2.75e-08, @@ -4456,7 +4457,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 1.375e-08 }, "azure/eu/gpt-5.1": { "deprecation_date": "2027-05-15", @@ -4636,7 +4638,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 2.75e-09 }, "azure/eu/o1-2024-12-17": { "cache_read_input_token_cost": 8.25e-06, @@ -6094,7 +6097,8 @@ "input_cost_per_token_batches": 6.25e-07, "output_cost_per_token_batches": 5e-06, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supports_minimal_reasoning_effort": true + "supports_minimal_reasoning_effort": true, + "cache_read_input_token_cost_batches": 6.25e-08 }, "azure/gpt-5.1-chat-2025-11-13": { "cache_read_input_token_cost": 1.25e-07, @@ -6282,7 +6286,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 6.25e-08 }, "azure/gpt-5-chat": { "cache_read_input_token_cost": 1.25e-07, @@ -6460,7 +6465,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 1.25e-08 }, "azure/gpt-5-nano": { "deprecation_date": "2027-02-09", @@ -6533,7 +6539,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 2.5e-09 }, "azure/gpt-5-pro": { "deprecation_date": "2027-04-07", @@ -6822,7 +6829,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 8.75e-08 }, "azure/gpt-5.2-chat": { "cache_read_input_token_cost": 1.75e-07, @@ -7287,7 +7295,11 @@ "output_cost_per_token_flex": 7.5e-06, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_xhigh_reasoning_effort": true, - "supports_minimal_reasoning_effort": true + "supports_minimal_reasoning_effort": true, + "cache_read_input_token_cost_above_272k_tokens_batches": 2.5e-07, + "cache_read_input_token_cost_batches": 1.3e-07, + "input_cost_per_token_above_272k_tokens_batches": 2.5e-06, + "output_cost_per_token_above_272k_tokens_batches": 1.125e-05 }, "azure/us/gpt-5.4-2026-03-05": { "cache_read_input_token_cost": 2.75e-07, @@ -7333,7 +7345,11 @@ "output_cost_per_token_batches": 8.25e-06, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_xhigh_reasoning_effort": true, - "supports_minimal_reasoning_effort": true + "supports_minimal_reasoning_effort": true, + "cache_read_input_token_cost_above_272k_tokens_batches": 2.75e-07, + "cache_read_input_token_cost_batches": 1.43e-07, + "input_cost_per_token_above_272k_tokens_batches": 2.75e-06, + "output_cost_per_token_above_272k_tokens_batches": 1.2375e-05 }, "azure/eu/gpt-5.4-2026-03-05": { "cache_read_input_token_cost": 2.75e-07, @@ -7379,7 +7395,11 @@ "output_cost_per_token_batches": 8.25e-06, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_xhigh_reasoning_effort": true, - "supports_minimal_reasoning_effort": true + "supports_minimal_reasoning_effort": true, + "cache_read_input_token_cost_above_272k_tokens_batches": 2.75e-07, + "cache_read_input_token_cost_batches": 1.43e-07, + "input_cost_per_token_above_272k_tokens_batches": 2.75e-06, + "output_cost_per_token_above_272k_tokens_batches": 1.2375e-05 }, "azure/gpt-5.4-pro": { "deprecation_date": "2027-09-07", @@ -7477,7 +7497,9 @@ "supports_system_messages": true, "supports_tool_choice": true, "supports_vision": true, - "supports_web_search": true + "supports_web_search": true, + "input_cost_per_token_above_272k_tokens_batches": 3e-05, + "output_cost_per_token_above_272k_tokens_batches": 0.000135 }, "azure/gpt-5.6": { "cache_creation_input_token_cost": 6.25e-06, @@ -8900,7 +8922,11 @@ "supports_none_reasoning_effort": true, "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", + "cache_read_input_token_cost_above_272k_tokens_batches": 5e-07, + "cache_read_input_token_cost_batches": 2.5e-07, + "input_cost_per_token_above_272k_tokens_batches": 5e-06, + "output_cost_per_token_above_272k_tokens_batches": 2.25e-05 }, "azure/us/gpt-5.5-2026-04-23": { "cache_read_input_token_cost": 5.5e-07, @@ -9003,7 +9029,11 @@ "supports_none_reasoning_effort": true, "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", + "cache_read_input_token_cost_above_272k_tokens_batches": 5.5e-07, + "cache_read_input_token_cost_batches": 2.75e-07, + "input_cost_per_token_above_272k_tokens_batches": 5.5e-06, + "output_cost_per_token_above_272k_tokens_batches": 2.475e-05 }, "azure/eu/gpt-5.5-2026-04-23": { "cache_read_input_token_cost": 5.5e-07, @@ -9106,7 +9136,11 @@ "supports_none_reasoning_effort": true, "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", + "cache_read_input_token_cost_above_272k_tokens_batches": 5.5e-07, + "cache_read_input_token_cost_batches": 2.75e-07, + "input_cost_per_token_above_272k_tokens_batches": 5.5e-06, + "output_cost_per_token_above_272k_tokens_batches": 2.475e-05 }, "azure/gpt-5.5-pro": { "cache_read_input_token_cost": 3e-06, @@ -9293,7 +9327,8 @@ "output_cost_per_token_flex": 2.25e-06, "output_cost_per_token_priority": 9e-06, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supports_xhigh_reasoning_effort": true + "supports_xhigh_reasoning_effort": true, + "cache_read_input_token_cost_batches": 3.75e-08 }, "azure/gpt-5.4-nano": { "deprecation_date": "2027-09-21", @@ -9390,7 +9425,8 @@ "output_cost_per_token_batches": 6.25e-07, "output_cost_per_token_flex": 6.25e-07, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supports_xhigh_reasoning_effort": true + "supports_xhigh_reasoning_effort": true, + "cache_read_input_token_cost_batches": 1e-08 }, "azure/gpt-image-1": { "cache_read_input_token_cost": 1.25e-06, @@ -10404,7 +10440,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 6.875e-08 }, "azure/us/gpt-5-mini-2025-08-07": { "cache_read_input_token_cost": 2.75e-08, @@ -10443,7 +10480,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 1.375e-08 }, "azure/us/gpt-5-nano-2025-08-07": { "cache_read_input_token_cost": 5.5e-09, @@ -10479,7 +10517,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 2.75e-09 }, "azure/us/gpt-5.1": { "deprecation_date": "2027-05-15", @@ -12908,6 +12947,23 @@ "supports_tool_choice": true, "output_cost_per_token": 1.86e-06 }, + "bedrock/eu-west-2/nvidia.nemotron-super-3-120b": { + "input_cost_per_token": 2.3e-07, + "litellm_provider": "bedrock", + "max_input_tokens": 256000, + "max_output_tokens": 32000, + "max_tokens": 32000, + "mode": "chat", + "output_cost_per_token": 1.01e-06, + "source": "https://aws.amazon.com/bedrock/pricing/", + "supports_audio_input": false, + "supports_function_calling": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": false + }, "bedrock/eu-west-2/qwen.qwen3-coder-next": { "input_cost_per_token": 7.8e-07, "litellm_provider": "bedrock", @@ -26782,7 +26838,8 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, - "web_search_billing_unit": "per_query" + "web_search_billing_unit": "per_query", + "cache_read_input_token_cost_batches": 1e-07 }, "gemini-3-pro-image-preview": { "input_cost_per_image": 0.0011, @@ -26867,7 +26924,8 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, - "web_search_billing_unit": "per_query" + "web_search_billing_unit": "per_query", + "cache_read_input_token_cost_batches": 2.5e-08 }, "gemini-3.1-flash-image-preview": { "input_cost_per_image": 0.00056, @@ -26946,7 +27004,8 @@ "supports_response_schema": false, "supports_system_messages": true, "supports_video_input": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 1.25e-08 }, "gemini-3.1-flash-lite-preview": { "cache_read_input_token_cost": 2.5e-08, @@ -27055,7 +27114,8 @@ }, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014, - "input_cost_per_audio_token_batches": 2.5e-07 + "input_cost_per_audio_token_batches": 2.5e-07, + "cache_read_input_token_cost_batches": 1.25e-08 }, "gemini-3.5-flash-lite": { "deprecation_date": "2027-07-21", @@ -27112,7 +27172,8 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "cache_read_input_token_cost_batches": 1.5e-08 }, "deep-research-pro-preview-12-2025": { "cache_read_input_token_cost": 2e-07, @@ -27147,7 +27208,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_vision": true, - "supports_web_search": true + "supports_web_search": true, + "cache_read_input_token_cost_batches": 1e-07 }, "gemini-2.5-flash-lite": { "cache_read_input_audio_token_cost": 3e-08, @@ -27880,7 +27942,8 @@ "output_cost_per_token_batches": 4.5e-06, "input_cost_per_token_flex": 7.5e-07, "output_cost_per_token_flex": 4.5e-06, - "cache_read_input_token_cost_flex": 7.5e-08 + "cache_read_input_token_cost_flex": 7.5e-08, + "cache_read_input_token_cost_batches": 7.5e-08 }, "vertex_ai/gemini-3.6-flash": { "prompt_cache_min_tokens": 4096, @@ -27937,7 +28000,8 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "cache_read_input_token_cost_batches": 3.75e-08 }, "vertex_ai/gemini-3.7-flash": { "prompt_cache_min_tokens": 4096, @@ -27995,7 +28059,8 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "cache_read_input_token_cost_batches": 3.75e-08 }, "vertex_ai/gemini-3.8-flash": { "prompt_cache_min_tokens": 4096, @@ -28053,7 +28118,8 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "cache_read_input_token_cost_batches": 3.75e-08 }, "vertex_ai/gemini-3.1-pro-preview": { "prompt_cache_min_tokens": 4096, @@ -30385,7 +30451,8 @@ "output_cost_per_token_batches": 4.5e-06, "input_cost_per_token_flex": 7.5e-07, "output_cost_per_token_flex": 4.5e-06, - "cache_read_input_token_cost_flex": 7.5e-08 + "cache_read_input_token_cost_flex": 7.5e-08, + "cache_read_input_token_cost_batches": 7.5e-08 }, "gemini-3.6-flash": { "prompt_cache_min_tokens": 4096, @@ -30442,7 +30509,8 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "cache_read_input_token_cost_batches": 3.75e-08 }, "gemini-3.7-flash": { "prompt_cache_min_tokens": 4096, @@ -30500,7 +30568,8 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "cache_read_input_token_cost_batches": 3.75e-08 }, "gemini-3.8-flash": { "prompt_cache_min_tokens": 4096, @@ -30558,7 +30627,8 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "cache_read_input_token_cost_batches": 3.75e-08 }, "gemini/gemini-2.5-pro-preview-tts": { "cache_read_input_token_cost": 1.25e-07, @@ -35661,7 +35731,8 @@ "supports_web_search": true, "supports_none_reasoning_effort": false, "supports_xhigh_reasoning_effort": false, - "supports_minimal_reasoning_effort": true + "supports_minimal_reasoning_effort": true, + "cache_read_input_token_cost_batches": 6.25e-08 }, "gpt-5-chat": { "cache_read_input_token_cost": 1.25e-07, @@ -36087,7 +36158,8 @@ "supports_web_search": true, "supports_none_reasoning_effort": false, "supports_xhigh_reasoning_effort": false, - "supports_minimal_reasoning_effort": true + "supports_minimal_reasoning_effort": true, + "cache_read_input_token_cost_batches": 1.25e-08 }, "gpt-5-nano": { "cache_read_input_token_cost": 5e-09, @@ -36186,7 +36258,8 @@ "supports_web_search": true, "supports_none_reasoning_effort": false, "supports_xhigh_reasoning_effort": false, - "supports_minimal_reasoning_effort": true + "supports_minimal_reasoning_effort": true, + "cache_read_input_token_cost_batches": 2.5e-09 }, "gpt-image-1": { "cache_read_input_token_cost": 1.25e-06, @@ -36809,6 +36882,15 @@ "supports_response_schema": false, "supports_tool_choice": true }, + "groq/llama-guard-3-8b": { + "input_cost_per_token": 2e-07, + "litellm_provider": "groq", + "max_input_tokens": 8192, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 2e-07, + "source": "https://console.groq.com/docs/model/llama-guard-3-8b" + }, "groq/gemma-7b-it": { "deprecation_date": "2024-12-18", "input_cost_per_token": 5e-08, @@ -43157,6 +43239,28 @@ "supports_web_search": true, "supports_xhigh_reasoning_effort": true }, + "openrouter/anthropic/claude-opus-5.5": { + "cache_creation_input_token_cost": 5e-06, + "cache_creation_input_token_cost_above_1hr": 8e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 4e-06, + "litellm_provider": "openrouter", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2e-05, + "source": "https://openrouter.ai/api/v1/models", + "supports_audio_input": false, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true + }, "openrouter/bytedance/ui-tars-1.5-7b": { "cache_read_input_token_cost": 1e-07, "input_cost_per_token": 1e-07, @@ -43328,21 +43432,21 @@ "supports_web_search": false }, "openrouter/deepseek/deepseek-v4-pro": { - "input_cost_per_token": 9.31074e-07, + "input_cost_per_token": 8.92272e-07, "input_cost_per_token_cache_hit": 4.4e-08, "litellm_provider": "openrouter", "max_input_tokens": 1048576, "max_output_tokens": 384000, "max_tokens": 384000, "mode": "chat", - "output_cost_per_token": 1.862148e-06, + "output_cost_per_token": 1.784544e-06, "source": "https://openrouter.ai/api/v1/models", "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, - "cache_read_input_token_cost": 7.75895e-08, + "cache_read_input_token_cost": 7.4356e-08, "supports_audio_input": false, "supports_pdf_input": false, "supports_vision": false, @@ -52043,7 +52147,8 @@ "output_cost_per_token_flex": 6e-06, "output_cost_per_token_priority": 2.16e-05, "supports_reasoning": false, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", + "cache_read_input_token_cost_batches": 1e-07 }, "vertex_ai/gemini-3-pro-image-preview": { "input_cost_per_image": 0.0011, @@ -52080,7 +52185,8 @@ "output_cost_per_token_batches": 1.5e-06, "output_cost_per_token_flex": 1.5e-06, "supports_reasoning": false, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", + "cache_read_input_token_cost_batches": 2.5e-08 }, "vertex_ai/gemini-3.1-flash-image-preview": { "input_cost_per_image": 0.00056, @@ -52135,7 +52241,8 @@ "supports_response_schema": false, "supports_system_messages": true, "supports_video_input": true, - "supports_vision": true + "supports_vision": true, + "cache_read_input_token_cost_batches": 1.25e-08 }, "vertex_ai/gemini-3.1-flash-lite-preview": { "cache_read_input_token_cost": 2.5e-08, @@ -52245,7 +52352,8 @@ }, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014, - "input_cost_per_audio_token_batches": 2.5e-07 + "input_cost_per_audio_token_batches": 2.5e-07, + "cache_read_input_token_cost_batches": 1.25e-08 }, "vertex_ai/gemini-3.5-flash-lite": { "deprecation_date": "2027-07-21", @@ -52303,7 +52411,8 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "cache_read_input_token_cost_batches": 1.5e-08 }, "vertex_ai/deep-research-pro-preview-12-2025": { "cache_read_input_token_cost": 2e-07, @@ -52319,7 +52428,8 @@ "output_cost_per_image_token": 0.00012, "output_cost_per_token": 1.2e-05, "output_cost_per_token_batches": 6e-06, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", + "cache_read_input_token_cost_batches": 1e-07 }, "vertex_ai/imagegeneration@006": { "deprecation_date": "2025-09-24", @@ -69143,13 +69253,13 @@ "supports_web_search": false }, "openrouter/qwen/qwen3.6-27b": { - "input_cost_per_token": 3e-07, - "output_cost_per_token": 2e-06, - "cache_read_input_token_cost": 3e-08, + "input_cost_per_token": 3.2e-07, + "output_cost_per_token": 2.7e-06, + "cache_read_input_token_cost": 1.5e-07, "litellm_provider": "openrouter", "max_input_tokens": 262144, - "max_output_tokens": 65536, - "max_tokens": 65536, + "max_output_tokens": 262140, + "max_tokens": 262140, "mode": "chat", "source": "https://openrouter.ai/api/v1/models", "supports_audio_input": false, @@ -73178,16 +73288,16 @@ "supports_web_search": true }, "openrouter/~anthropic/claude-opus-latest": { - "cache_creation_input_token_cost": 6.25e-06, - "cache_creation_input_token_cost_above_1hr": 1e-05, - "cache_read_input_token_cost": 5e-07, - "input_cost_per_token": 5e-06, + "cache_creation_input_token_cost": 5e-06, + "cache_creation_input_token_cost_above_1hr": 8e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 4e-06, "litellm_provider": "openrouter", "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 2.5e-05, + "output_cost_per_token": 2e-05, "source": "https://openrouter.ai/api/v1/models", "supports_audio_input": false, "supports_function_calling": true, @@ -73222,15 +73332,14 @@ "supports_web_search": true }, "openrouter/~deepseek/deepseek-flash-latest": { - "cache_read_input_token_cost": 6e-09, - "input_cost_per_token": 3e-07, + "cache_read_input_token_cost": 3.6e-09, + "input_cost_per_token": 1.2e-07, "litellm_provider": "openrouter", "max_input_tokens": 1048576, - "max_output_tokens": 384000, - "max_tokens": 384000, + "max_output_tokens": 943718, + "max_tokens": 943718, "mode": "chat", - "off_peak_pricing": {"windows":[{"weekdays":["saturday","sunday"],"hours_utc":"00:00-00:00"},{"weekdays":["monday","tuesday","wednesday","thursday","friday"],"hours_utc":"00:00-01:00"},{"weekdays":["monday","tuesday","wednesday","thursday","friday"],"hours_utc":"04:00-06:00"},{"weekdays":["monday","tuesday","wednesday","thursday","friday"],"hours_utc":"10:00-00:00"}],"input_cost_per_token":1.5e-7,"output_cost_per_token":6e-7,"cache_read_input_token_cost":3e-9}, - "output_cost_per_token": 1.2e-06, + "output_cost_per_token": 4.8e-07, "source": "https://openrouter.ai/api/v1/models", "supports_audio_input": false, "supports_function_calling": true, @@ -73243,15 +73352,14 @@ "supports_web_search": false }, "openrouter/~deepseek/deepseek-pro-latest": { - "cache_read_input_token_cost": 4.4e-08, - "input_cost_per_token": 1.32e-06, + "cache_read_input_token_cost": 1.2726e-08, + "input_cost_per_token": 3.9996e-07, "litellm_provider": "openrouter", "max_input_tokens": 1048576, - "max_output_tokens": 384000, - "max_tokens": 384000, + "max_output_tokens": 393216, + "max_tokens": 393216, "mode": "chat", - "off_peak_pricing": {"windows":[{"weekdays":["saturday","sunday"],"hours_utc":"00:00-00:00"},{"weekdays":["monday","tuesday","wednesday","thursday","friday"],"hours_utc":"00:00-01:00"},{"weekdays":["monday","tuesday","wednesday","thursday","friday"],"hours_utc":"04:00-06:00"},{"weekdays":["monday","tuesday","wednesday","thursday","friday"],"hours_utc":"10:00-00:00"}],"input_cost_per_token":6.6e-7,"output_cost_per_token":0.00000198,"cache_read_input_token_cost":2.2e-8}, - "output_cost_per_token": 3.96e-06, + "output_cost_per_token": 1.19988e-06, "source": "https://openrouter.ai/api/v1/models", "supports_audio_input": false, "supports_function_calling": true, @@ -73264,14 +73372,14 @@ "supports_web_search": false }, "openrouter/~deepseek/deepseek-v4-flash-latest": { - "cache_read_input_token_cost": 1.6e-08, - "input_cost_per_token": 4e-08, + "cache_read_input_token_cost": 8e-09, + "input_cost_per_token": 3e-08, "litellm_provider": "openrouter", "max_input_tokens": 1310720, "max_output_tokens": 943718, "max_tokens": 943718, "mode": "chat", - "output_cost_per_token": 6.4e-07, + "output_cost_per_token": 8e-07, "source": "https://openrouter.ai/api/v1/models", "supports_audio_input": false, "supports_function_calling": true, @@ -73334,13 +73442,13 @@ }, "openrouter/~moonshotai/kimi-latest": { "cache_read_input_token_cost": 3e-07, - "input_cost_per_token": 3e-06, + "input_cost_per_token": 1.4989e-06, "litellm_provider": "openrouter", "max_input_tokens": 1048576, "max_output_tokens": 943718, "max_tokens": 943718, "mode": "chat", - "output_cost_per_token": 1.5e-05, + "output_cost_per_token": 1.0758e-05, "source": "https://openrouter.ai/api/v1/models", "supports_audio_input": false, "supports_function_calling": true, @@ -73378,19 +73486,19 @@ "supports_web_search": true }, "openrouter/~openai/gpt-luna-latest": { - "cache_creation_input_token_cost": 2.5e-07, - "cache_creation_input_token_cost_above_272k_tokens": 5e-07, - "cache_read_input_token_cost": 2e-08, - "cache_read_input_token_cost_above_272k_tokens": 4e-08, - "input_cost_per_token": 2e-07, - "input_cost_per_token_above_272k_tokens": 4e-07, + "cache_creation_input_token_cost": 1.25e-07, + "cache_creation_input_token_cost_above_272k_tokens": 2.5e-07, + "cache_read_input_token_cost": 1e-08, + "cache_read_input_token_cost_above_272k_tokens": 2e-08, + "input_cost_per_token": 1e-07, + "input_cost_per_token_above_272k_tokens": 2e-07, "litellm_provider": "openrouter", "max_input_tokens": 1050000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.2e-06, - "output_cost_per_token_above_272k_tokens": 1.8e-06, + "output_cost_per_token": 5e-07, + "output_cost_per_token_above_272k_tokens": 7.5e-07, "source": "https://openrouter.ai/api/v1/models", "supports_audio_input": false, "supports_function_calling": true, @@ -73496,14 +73604,14 @@ "supports_web_search": true }, "openrouter/~z-ai/glm-flash-latest": { - "cache_read_input_token_cost": 5e-08, - "input_cost_per_token": 1.5e-07, + "cache_read_input_token_cost": 1.5e-08, + "input_cost_per_token": 7.5e-08, "litellm_provider": "openrouter", "max_input_tokens": 1310720, "max_output_tokens": 943718, "max_tokens": 943718, "mode": "chat", - "output_cost_per_token": 5e-07, + "output_cost_per_token": 2.5e-07, "source": "https://openrouter.ai/api/v1/models", "supports_audio_input": false, "supports_function_calling": true, @@ -75959,6 +76067,106 @@ "supports_vision": true, "supports_web_search": true }, + "openrouter/openai/gpt-6-luna": { + "cache_creation_input_token_cost": 1.25e-07, + "cache_creation_input_token_cost_above_272k_tokens": 2.5e-07, + "cache_read_input_token_cost": 1e-08, + "cache_read_input_token_cost_above_272k_tokens": 2e-08, + "input_cost_per_token": 1e-07, + "input_cost_per_token_above_272k_tokens": 2e-07, + "litellm_provider": "openrouter", + "max_input_tokens": 1050000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 5e-07, + "output_cost_per_token_above_272k_tokens": 7.5e-07, + "source": "https://openrouter.ai/api/v1/models", + "supports_audio_input": false, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true + }, + "openrouter/openai/gpt-6-luna-pro": { + "cache_creation_input_token_cost": 1.25e-07, + "cache_creation_input_token_cost_above_272k_tokens": 2.5e-07, + "cache_read_input_token_cost": 1e-08, + "cache_read_input_token_cost_above_272k_tokens": 2e-08, + "input_cost_per_token": 1e-07, + "input_cost_per_token_above_272k_tokens": 2e-07, + "litellm_provider": "openrouter", + "max_input_tokens": 1050000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 5e-07, + "output_cost_per_token_above_272k_tokens": 7.5e-07, + "source": "https://openrouter.ai/api/v1/models", + "supports_audio_input": false, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true + }, + "openrouter/openai/gpt-6-sol": { + "cache_creation_input_token_cost": 2.5e-06, + "cache_creation_input_token_cost_above_272k_tokens": 5e-06, + "cache_read_input_token_cost": 2e-07, + "cache_read_input_token_cost_above_272k_tokens": 4e-07, + "input_cost_per_token": 2e-06, + "input_cost_per_token_above_272k_tokens": 4e-06, + "litellm_provider": "openrouter", + "max_input_tokens": 1050000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1e-05, + "output_cost_per_token_above_272k_tokens": 1.5e-05, + "source": "https://openrouter.ai/api/v1/models", + "supports_audio_input": false, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true + }, + "openrouter/openai/gpt-6-sol-pro": { + "cache_creation_input_token_cost": 2.5e-06, + "cache_creation_input_token_cost_above_272k_tokens": 5e-06, + "cache_read_input_token_cost": 2e-07, + "cache_read_input_token_cost_above_272k_tokens": 4e-07, + "input_cost_per_token": 2e-06, + "input_cost_per_token_above_272k_tokens": 4e-06, + "litellm_provider": "openrouter", + "max_input_tokens": 1050000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1e-05, + "output_cost_per_token_above_272k_tokens": 1.5e-05, + "source": "https://openrouter.ai/api/v1/models", + "supports_audio_input": false, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true + }, "openrouter/openai/o3-mini:batch": { "cache_read_input_token_cost": 2.75e-07, "input_cost_per_token": 5.5e-07, diff --git a/tests/test_litellm/test_cost_calculator.py b/tests/test_litellm/test_cost_calculator.py index 7d2a04c500f..ecc01857f8c 100644 --- a/tests/test_litellm/test_cost_calculator.py +++ b/tests/test_litellm/test_cost_calculator.py @@ -4847,3 +4847,27 @@ def test_cost_per_token_bedrock_qwen3_next_uses_regional_entry_not_us_rate( assert prompt_usd == pytest.approx(prompt_tokens * regional["input_cost_per_token"]) assert completion_usd == pytest.approx(completion_tokens * regional["output_cost_per_token"]) + + +def test_cost_per_token_bedrock_nemotron_super_3_uses_eu_west_2_entry_not_us_rate( + monkeypatch: pytest.MonkeyPatch, +) -> None: + monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") + monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url="")) + + regional_key: Final = "bedrock/eu-west-2/nvidia.nemotron-super-3-120b" + regional: Final = litellm.model_cost[regional_key] + us: Final = litellm.model_cost["nvidia.nemotron-super-3-120b"] + assert regional["input_cost_per_token"] != us["input_cost_per_token"] + assert regional["output_cost_per_token"] != us["output_cost_per_token"] + + prompt_tokens, completion_tokens = 1000, 500 + prompt_usd, completion_usd = cost_per_token( + model=regional_key, + prompt_tokens=prompt_tokens, + completion_tokens=completion_tokens, + custom_llm_provider="bedrock", + ) + + assert prompt_usd == pytest.approx(prompt_tokens * regional["input_cost_per_token"]) + assert completion_usd == pytest.approx(completion_tokens * regional["output_cost_per_token"]) From bbc702cd8be9025c405e4789f37aa24ec45c7159 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 14:09:40 -0700 Subject: [PATCH 031/101] fix(gateway): expose /api/event_logging/batch on the gateway allowlist (#42572) * fix(gateway): expose /api/event_logging/batch on the gateway allowlist Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(gateway): route /api/event_logging to gateway pods in helm and terraform Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(proxy): stop max_budget leaking between proxy_server and native_compaction tests Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: kerry Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- gateway/routes/allowlist.py | 1 + helm/litellm/templates/ingress.yaml | 2 +- terraform/litellm/aws/locals.tf | 2 +- terraform/litellm/gcp/locals.tf | 2 +- tests/test_litellm/proxy/test_native_compaction.py | 1 + tests/test_litellm/proxy/test_proxy_server.py | 12 ++++++------ 6 files changed, 11 insertions(+), 9 deletions(-) diff --git a/gateway/routes/allowlist.py b/gateway/routes/allowlist.py index fe58e2dd58c..c4a3d3f7473 100644 --- a/gateway/routes/allowlist.py +++ b/gateway/routes/allowlist.py @@ -131,6 +131,7 @@ GATEWAY_EXACT_PATHS: frozenset[str] = frozenset( "/redoc", "/test", "/debug/memory/summary", + "/api/event_logging/batch", } ) diff --git a/helm/litellm/templates/ingress.yaml b/helm/litellm/templates/ingress.yaml index e6717821a57..e9f7ed4ec3f 100644 --- a/helm/litellm/templates/ingress.yaml +++ b/helm/litellm/templates/ingress.yaml @@ -61,7 +61,7 @@ "/v1/fine-tuning" "/fine-tuning" "/v1/responses" "/responses" "/v1/threads" "/threads" "/v1/assistants" "/assistants" "/v1/vector_stores" "/vector_stores" "/v1/indexes" "/v1/models" "/models" "/openai" "/engines" - "/v1/messages" "/messages" "/v1/skills" "/v1/a2a" "/a2a" + "/v1/messages" "/messages" "/v1/skills" "/v1/a2a" "/a2a" "/api/event_logging" "/v1/rerank" "/v2/rerank" "/rerank" "/v1/ocr" "/ocr" "/v1/rag" "/rag" "/v1/video" "/v1/videos" "/video" "/videos" "/v1/search" "/search" "/v1/containers" "/containers" "/v1/evals" "/v1/memory" "/queue/chat" diff --git a/terraform/litellm/aws/locals.tf b/terraform/litellm/aws/locals.tf index 778d31642c1..b89bd486d02 100644 --- a/terraform/litellm/aws/locals.tf +++ b/terraform/litellm/aws/locals.tf @@ -74,7 +74,7 @@ locals { "/v1/models*", "/models*", "/openai/*", "/engines/*", "/v1/messages*", "/messages*", - "/v1/skills/*", "/v1/a2a/*", + "/v1/skills/*", "/v1/a2a/*", "/api/event_logging*", "/v1/rerank*", "/v2/rerank*", "/rerank*", "/v1/ocr*", "/ocr*", "/v1/rag/*", "/rag/*", diff --git a/terraform/litellm/gcp/locals.tf b/terraform/litellm/gcp/locals.tf index d263c781449..e82892b27cb 100644 --- a/terraform/litellm/gcp/locals.tf +++ b/terraform/litellm/gcp/locals.tf @@ -43,7 +43,7 @@ locals { "/v1/models*", "/models*", "/openai/*", "/engines/*", "/v1/messages*", "/messages*", - "/v1/skills/*", "/v1/a2a/*", + "/v1/skills/*", "/v1/a2a/*", "/api/event_logging*", "/v1/rerank*", "/v2/rerank*", "/rerank*", "/v1/ocr*", "/ocr*", "/v1/rag/*", "/rag/*", diff --git a/tests/test_litellm/proxy/test_native_compaction.py b/tests/test_litellm/proxy/test_native_compaction.py index 9a6b4cdda65..778c1715530 100644 --- a/tests/test_litellm/proxy/test_native_compaction.py +++ b/tests/test_litellm/proxy/test_native_compaction.py @@ -116,6 +116,7 @@ async def test_real_proxy_child_auth_privacy_and_body_policy( monkeypatch.setattr(litellm, "max_budget", 0) monkeypatch.setattr(proxy_server.app, "dependency_overrides", {}) monkeypatch.setattr(proxy_server, "master_key", "sk-master-fixture") + monkeypatch.setattr(litellm, "max_budget", 0.0) monkeypatch.setattr(proxy_server, "prisma_client", object()) monkeypatch.setattr(proxy_server, "user_api_key_cache", cache) monkeypatch.setattr(proxy_server, "llm_router", None) diff --git a/tests/test_litellm/proxy/test_proxy_server.py b/tests/test_litellm/proxy/test_proxy_server.py index 26bfd5c52bd..32b89885ac2 100644 --- a/tests/test_litellm/proxy/test_proxy_server.py +++ b/tests/test_litellm/proxy/test_proxy_server.py @@ -3200,7 +3200,7 @@ def test_normalize_datetime_for_sorting(): @pytest.mark.asyncio -async def test_add_proxy_budget_to_db_only_creates_user_no_keys(): +async def test_add_proxy_budget_to_db_only_creates_user_no_keys(monkeypatch: pytest.MonkeyPatch): """ Test that _add_proxy_budget_to_db only creates a user and no keys are added. @@ -3218,8 +3218,8 @@ async def test_add_proxy_budget_to_db_only_creates_user_no_keys(): from litellm.proxy.proxy_server import ProxyStartupEvent # Set up required litellm settings - litellm.budget_duration = "30d" - litellm.max_budget = 100.0 + monkeypatch.setattr(litellm, "budget_duration", "30d") + monkeypatch.setattr(litellm, "max_budget", 100.0) litellm_proxy_budget_name = "litellm-proxy-budget" @@ -3258,7 +3258,7 @@ async def test_add_proxy_budget_to_db_only_creates_user_no_keys(): @pytest.mark.asyncio -async def test_add_proxy_budget_to_db_backfills_budget_reset_at(): +async def test_add_proxy_budget_to_db_backfills_budget_reset_at(monkeypatch: pytest.MonkeyPatch): """ Test that _upsert_proxy_budget_with_reset_at_backfill issues a conditional update_many with `WHERE budget_reset_at IS NULL` to backfill the column on @@ -3276,8 +3276,8 @@ async def test_add_proxy_budget_to_db_backfills_budget_reset_at(): import litellm from litellm.proxy.proxy_server import ProxyStartupEvent - litellm.budget_duration = "30d" - litellm.max_budget = 100.0 + monkeypatch.setattr(litellm, "budget_duration", "30d") + monkeypatch.setattr(litellm, "max_budget", 100.0) litellm_proxy_budget_name = "litellm-proxy-budget" mock_prisma = MagicMock() From 12dffbafd6dce04a0ea81c93b35ff83f871027d6 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 16:10:49 -0500 Subject: [PATCH 032/101] fix(proxy): honor DATABASE_DISABLE_PREPARED_STATEMENTS in the litellm CLI (#42556) * fix(proxy): honor DATABASE_DISABLE_PREPARED_STATEMENTS in the litellm CLI Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(proxy): pooled pgbouncer url keeps a single pgbouncer=true when the upstream already carries it Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): reject a malformed DATABASE_DISABLE_PREPARED_STATEMENTS even when the config already enables it Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: yassin Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- litellm/proxy/proxy_cli.py | 7 +- tests/test_litellm/proxy/db/test_pgbouncer.py | 7 + tests/test_litellm/proxy/test_proxy_cli.py | 166 ++++++++++++++++++ 3 files changed, 179 insertions(+), 1 deletion(-) diff --git a/litellm/proxy/proxy_cli.py b/litellm/proxy/proxy_cli.py index 78885461724..40140974198 100644 --- a/litellm/proxy/proxy_cli.py +++ b/litellm/proxy/proxy_cli.py @@ -1283,6 +1283,7 @@ def run_server( if os.getenv("DATABASE_URL", None) is not None or os.getenv("DIRECT_URL", None) is not None: from litellm.proxy.db.db_url_settings import ( + DISABLE_PREPARED_STATEMENTS_ENV_VAR, add_missing_query_params, idle_lifetime_params, reader_shareable_params, @@ -1305,12 +1306,16 @@ def run_server( sys.exit(1) from litellm.secret_managers.main import get_secret + env_disable_prepared_statements: Final = token_auth_flag_enabled( + os.getenv(DISABLE_PREPARED_STATEMENTS_ENV_VAR), env_var=DISABLE_PREPARED_STATEMENTS_ENV_VAR + ) + disable_prepared_statements: Final = db_disable_prepared_statements or env_disable_prepared_statements connection_url_params: Final = _build_db_connection_url_params( connection_limit=db_connection_pool_limit, pool_timeout=db_connection_timeout, connect_timeout=db_connect_timeout, socket_timeout=db_socket_timeout, - disable_prepared_statements=db_disable_prepared_statements, + disable_prepared_statements=disable_prepared_statements, extra_params=db_extra_connection_params, ) lifetime_params: Final = idle_lifetime_params(general_settings.get("database_max_idle_connection_lifetime")) diff --git a/tests/test_litellm/proxy/db/test_pgbouncer.py b/tests/test_litellm/proxy/db/test_pgbouncer.py index bf7df3077ea..c69c8d015a3 100644 --- a/tests/test_litellm/proxy/db/test_pgbouncer.py +++ b/tests/test_litellm/proxy/db/test_pgbouncer.py @@ -122,6 +122,13 @@ class TestPlanPgBouncer: "pgbouncer": "true", } + def test_an_upstream_that_already_disables_prepared_statements_gets_a_single_pgbouncer_flag(self): + pooled: Final = _plan("postgresql://app:pw@db/litellm?connection_limit=5&pgbouncer=true").pooled_url + assert urllib.parse.parse_qsl(urllib.parse.urlsplit(pooled).query) == [ + ("connection_limit", "5"), + ("pgbouncer", "true"), + ] + @pytest.mark.parametrize("hop_param", ["channel_binding=require", "gssencmode=require"]) def test_transport_params_for_the_postgres_hop_stay_off_the_plain_tcp_loopback_url(self, hop_param: str): pooled: Final = _plan(f"postgresql://app:pw@db/litellm?connection_limit=5&{hop_param}").pooled_url diff --git a/tests/test_litellm/proxy/test_proxy_cli.py b/tests/test_litellm/proxy/test_proxy_cli.py index a38470d1fdf..d2d71d6df05 100644 --- a/tests/test_litellm/proxy/test_proxy_cli.py +++ b/tests/test_litellm/proxy/test_proxy_cli.py @@ -1174,6 +1174,172 @@ class TestProxyInitializationHelpers: else: assert "pgbouncer" not in appended_params + @pytest.mark.parametrize( + "env_value, config_value, expect_pgbouncer", + [ + ("true", None, True), + ("1", None, True), + ("false", None, False), + (None, None, False), + ("true", False, True), + ("false", True, True), + ], + ) + @patch("subprocess.run") + @patch("atexit.register") + @patch("litellm.proxy.db.prisma_client.PrismaManager.setup_database") + @patch( + "litellm.proxy.db.prisma_client.should_update_prisma_schema", return_value=False + ) + def test_disable_prepared_statements_env_var_forwarded_to_url( + self, + mock_should_update, + mock_setup_db, + mock_atexit_register, + mock_subprocess_run, + env_value, + config_value, + expect_pgbouncer, + ): + from click.testing import CliRunner + + from litellm.proxy.proxy_cli import run_server + + runner = CliRunner() + mock_subprocess_run.return_value = MagicMock(returncode=0) + + general_settings = {"database_url": "postgresql://test:test@localhost:5432/test"} + if config_value is not None: + general_settings["database_disable_prepared_statements"] = config_value + mock_proxy_module = MagicMock( + app=MagicMock(), + ProxyConfig=MagicMock(), + KeyManagementSettings=MagicMock(), + save_worker_config=MagicMock(), + ) + mock_proxy_module.ProxyConfig.return_value.get_config = AsyncMock( + return_value={"general_settings": general_settings} + ) + + clean_env = { + k: v + for k, v in os.environ.items() + if k not in ("DATABASE_URL", "DIRECT_URL", "DATABASE_DISABLE_PREPARED_STATEMENTS") + } + if env_value is not None: + clean_env["DATABASE_DISABLE_PREPARED_STATEMENTS"] = env_value + + with ( + patch.dict(os.environ, clean_env, clear=True), + patch.dict( + "sys.modules", + { + "proxy_server": mock_proxy_module, + "litellm.proxy.proxy_server": mock_proxy_module, + }, + ), + patch( + "litellm.proxy.proxy_cli.ProxyInitializationHelpers._get_default_unvicorn_init_args" + ) as mock_get_args, + patch( + "litellm.proxy.proxy_cli.append_query_params", + side_effect=lambda url, params: str(url), + ) as mock_append_query_params, + ): + mock_get_args.return_value = { + "app": "litellm.proxy.proxy_server:app", + "host": "localhost", + "port": 8000, + } + + result = runner.invoke( + run_server, + ["--local", "--config", "test-config.yaml", "--skip_server_startup"], + ) + + assert ( + result.exit_code == 0 + ), f"exit_code={result.exit_code}, output={result.output}" + appended_params = mock_append_query_params.call_args.args[1] + if expect_pgbouncer: + assert appended_params["pgbouncer"] == "true", appended_params + else: + assert "pgbouncer" not in appended_params, appended_params + + @patch("subprocess.run") + @patch("atexit.register") + @patch("litellm.proxy.db.prisma_client.PrismaManager.setup_database") + @patch( + "litellm.proxy.db.prisma_client.should_update_prisma_schema", return_value=False + ) + def test_malformed_disable_prepared_statements_env_var_is_rejected_even_when_config_enables_it( + self, + mock_should_update, + mock_setup_db, + mock_atexit_register, + mock_subprocess_run, + ): + from click.testing import CliRunner + + from litellm.proxy.proxy_cli import run_server + + runner = CliRunner() + mock_subprocess_run.return_value = MagicMock(returncode=0) + + mock_proxy_module = MagicMock( + app=MagicMock(), + ProxyConfig=MagicMock(), + KeyManagementSettings=MagicMock(), + save_worker_config=MagicMock(), + ) + mock_proxy_module.ProxyConfig.return_value.get_config = AsyncMock( + return_value={ + "general_settings": { + "database_url": "postgresql://test:test@localhost:5432/test", + "database_disable_prepared_statements": True, + } + } + ) + + clean_env = { + k: v + for k, v in os.environ.items() + if k not in ("DATABASE_URL", "DIRECT_URL", "DATABASE_DISABLE_PREPARED_STATEMENTS") + } + clean_env["DATABASE_DISABLE_PREPARED_STATEMENTS"] = "enabled" + + with ( + patch.dict(os.environ, clean_env, clear=True), + patch.dict( + "sys.modules", + { + "proxy_server": mock_proxy_module, + "litellm.proxy.proxy_server": mock_proxy_module, + }, + ), + patch( + "litellm.proxy.proxy_cli.ProxyInitializationHelpers._get_default_unvicorn_init_args" + ) as mock_get_args, + patch( + "litellm.proxy.proxy_cli.append_query_params", + side_effect=lambda url, params: str(url), + ) as mock_append_query_params, + ): + mock_get_args.return_value = { + "app": "litellm.proxy.proxy_server:app", + "host": "localhost", + "port": 8000, + } + + result = runner.invoke( + run_server, + ["--local", "--config", "test-config.yaml", "--skip_server_startup"], + ) + + assert isinstance(result.exception, ValueError), f"exit_code={result.exit_code}, output={result.output}" + assert "DATABASE_DISABLE_PREPARED_STATEMENTS" in str(result.exception), result.exception + mock_append_query_params.assert_not_called() + @patch("uvicorn.run") @patch("atexit.register") @patch("litellm.proxy.db.prisma_client.PrismaManager.setup_database") From cd69342eef5a317c8f54d39bfaddf06884f3e0c5 Mon Sep 17 00:00:00 2001 From: "berriai-litellm-provider-info-sync[bot]" <328147090+berriai-litellm-provider-info-sync[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 14:11:31 -0700 Subject: [PATCH 033/101] chore(prices): sync Vertex AI prices: 20 models (#42577) deep-research-pro-preview-12-2025: cache_read_input_token_cost_batches vertex_ai/deep-research-pro-preview-12-2025: cache_read_input_token_cost_batches gemini-3-pro-image: cache_read_input_token_cost_batches vertex_ai/gemini-3-pro-image: cache_read_input_token_cost_batches gemini-3.1-flash-image: cache_read_input_token_cost_batches vertex_ai/gemini-3.1-flash-image: cache_read_input_token_cost_batches gemini-3.1-flash-lite: cache_read_input_token_cost_batches vertex_ai/gemini-3.1-flash-lite: cache_read_input_token_cost_batches gemini-3.1-flash-lite-image: cache_read_input_token_cost_batches vertex_ai/gemini-3.1-flash-lite-image: cache_read_input_token_cost_batches gemini-3.5-flash: cache_read_input_token_cost_batches vertex_ai/gemini-3.5-flash: cache_read_input_token_cost_batches gemini-3.5-flash-lite: cache_read_input_token_cost_batches vertex_ai/gemini-3.5-flash-lite: cache_read_input_token_cost_batches gemini-3.6-flash: cache_read_input_token_cost_batches vertex_ai/gemini-3.6-flash: cache_read_input_token_cost_batches gemini-3.7-flash: cache_read_input_token_cost_batches vertex_ai/gemini-3.7-flash: cache_read_input_token_cost_batches gemini-3.8-flash: cache_read_input_token_cost_batches vertex_ai/gemini-3.8-flash: cache_read_input_token_cost_batches Co-authored-by: berriai-litellm-provider-info-sync[bot] <328147090+berriai-litellm-provider-info-sync[bot]@users.noreply.github.com> --- ...odel_prices_and_context_window_backup.json | 20 +++++++++++++++++++ model_prices_and_context_window.json | 20 +++++++++++++++++++ 2 files changed, 40 insertions(+) diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 94786f250b0..431e965524e 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -26790,6 +26790,7 @@ "cache_read_input_token_cost": 2e-07, "cache_read_input_token_cost_above_200k_tokens": 4e-07, "cache_read_input_token_cost_above_200k_tokens_priority": 7.2e-07, + "cache_read_input_token_cost_batches": 1e-07, "cache_read_input_token_cost_flex": 1e-07, "cache_read_input_token_cost_priority": 3.6e-07, "deprecation_date": "2027-05-28", @@ -26883,6 +26884,7 @@ }, "gemini-3.1-flash-image": { "cache_read_input_token_cost": 5e-08, + "cache_read_input_token_cost_batches": 2.5e-08, "cache_read_input_token_cost_flex": 2.5e-08, "deprecation_date": "2027-05-28", "input_cost_per_image": 0.00056, @@ -26967,6 +26969,7 @@ }, "gemini-3.1-flash-lite-image": { "cache_read_input_token_cost": 2.5e-08, + "cache_read_input_token_cost_batches": 1.25e-08, "cache_read_input_token_cost_flex": 1.25e-08, "input_cost_per_image": 0.00028, "input_cost_per_token": 2.5e-07, @@ -27060,6 +27063,7 @@ "cache_read_input_audio_token_cost": 5e-08, "deprecation_date": "2027-05-07", "cache_read_input_token_cost": 2.5e-08, + "cache_read_input_token_cost_batches": 1.25e-08, "cache_read_input_token_cost_flex": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, "input_cost_per_audio_token": 5e-07, @@ -27120,6 +27124,7 @@ "gemini-3.5-flash-lite": { "deprecation_date": "2027-07-21", "cache_read_input_token_cost": 3e-08, + "cache_read_input_token_cost_batches": 1.5e-08, "cache_read_input_token_cost_flex": 1.5e-08, "cache_read_input_token_cost_priority": 5.4e-08, "input_cost_per_token": 3e-07, @@ -27177,6 +27182,7 @@ }, "deep-research-pro-preview-12-2025": { "cache_read_input_token_cost": 2e-07, + "cache_read_input_token_cost_batches": 1e-07, "input_cost_per_image": 0.0011, "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, @@ -27888,6 +27894,7 @@ "prompt_cache_min_tokens": 4096, "deprecation_date": "2027-05-19", "cache_read_input_token_cost": 1.5e-07, + "cache_read_input_token_cost_batches": 7.5e-08, "input_cost_per_token": 1.5e-06, "input_cost_per_audio_token": 1.5e-06, "litellm_provider": "vertex_ai", @@ -27948,6 +27955,7 @@ "vertex_ai/gemini-3.6-flash": { "prompt_cache_min_tokens": 4096, "cache_read_input_token_cost": 7.5e-08, + "cache_read_input_token_cost_batches": 3.75e-08, "cache_read_input_token_cost_flex": 3.75e-08, "input_cost_per_token": 7.5e-07, "input_cost_per_token_batches": 3.75e-07, @@ -28006,6 +28014,7 @@ "vertex_ai/gemini-3.7-flash": { "prompt_cache_min_tokens": 4096, "cache_read_input_token_cost": 7.5e-08, + "cache_read_input_token_cost_batches": 3.75e-08, "cache_read_input_token_cost_flex": 3.75e-08, "input_cost_per_token": 7.5e-07, "input_cost_per_token_batches": 3.75e-07, @@ -28065,6 +28074,7 @@ "vertex_ai/gemini-3.8-flash": { "prompt_cache_min_tokens": 4096, "cache_read_input_token_cost": 7.5e-08, + "cache_read_input_token_cost_batches": 3.75e-08, "cache_read_input_token_cost_flex": 3.75e-08, "input_cost_per_token": 7.5e-07, "input_cost_per_token_batches": 3.75e-07, @@ -30397,6 +30407,7 @@ "prompt_cache_min_tokens": 4096, "deprecation_date": "2027-05-19", "cache_read_input_token_cost": 1.5e-07, + "cache_read_input_token_cost_batches": 7.5e-08, "input_cost_per_audio_token": 1.5e-06, "input_cost_per_token": 1.5e-06, "litellm_provider": "vertex_ai-language-models", @@ -30457,6 +30468,7 @@ "gemini-3.6-flash": { "prompt_cache_min_tokens": 4096, "cache_read_input_token_cost": 7.5e-08, + "cache_read_input_token_cost_batches": 3.75e-08, "cache_read_input_token_cost_flex": 3.75e-08, "input_cost_per_token": 7.5e-07, "input_cost_per_token_batches": 3.75e-07, @@ -30515,6 +30527,7 @@ "gemini-3.7-flash": { "prompt_cache_min_tokens": 4096, "cache_read_input_token_cost": 7.5e-08, + "cache_read_input_token_cost_batches": 3.75e-08, "cache_read_input_token_cost_flex": 3.75e-08, "input_cost_per_token": 7.5e-07, "input_cost_per_token_batches": 3.75e-07, @@ -30574,6 +30587,7 @@ "gemini-3.8-flash": { "prompt_cache_min_tokens": 4096, "cache_read_input_token_cost": 7.5e-08, + "cache_read_input_token_cost_batches": 3.75e-08, "cache_read_input_token_cost_flex": 3.75e-08, "input_cost_per_token": 7.5e-07, "input_cost_per_token_batches": 3.75e-07, @@ -52123,6 +52137,7 @@ "cache_read_input_token_cost": 2e-07, "cache_read_input_token_cost_above_200k_tokens": 4e-07, "cache_read_input_token_cost_above_200k_tokens_priority": 7.2e-07, + "cache_read_input_token_cost_batches": 1e-07, "cache_read_input_token_cost_flex": 1e-07, "cache_read_input_token_cost_priority": 3.6e-07, "deprecation_date": "2027-05-28", @@ -52168,6 +52183,7 @@ }, "vertex_ai/gemini-3.1-flash-image": { "cache_read_input_token_cost": 5e-08, + "cache_read_input_token_cost_batches": 2.5e-08, "cache_read_input_token_cost_flex": 2.5e-08, "deprecation_date": "2027-05-28", "input_cost_per_image": 0.00056, @@ -52204,6 +52220,7 @@ }, "vertex_ai/gemini-3.1-flash-lite-image": { "cache_read_input_token_cost": 2.5e-08, + "cache_read_input_token_cost_batches": 1.25e-08, "cache_read_input_token_cost_flex": 1.25e-08, "input_cost_per_image": 0.00028, "input_cost_per_token": 2.5e-07, @@ -52297,6 +52314,7 @@ "cache_read_input_audio_token_cost": 5e-08, "deprecation_date": "2027-05-07", "cache_read_input_token_cost": 2.5e-08, + "cache_read_input_token_cost_batches": 1.25e-08, "cache_read_input_token_cost_flex": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, "input_cost_per_audio_token": 5e-07, @@ -52358,6 +52376,7 @@ "vertex_ai/gemini-3.5-flash-lite": { "deprecation_date": "2027-07-21", "cache_read_input_token_cost": 3e-08, + "cache_read_input_token_cost_batches": 1.5e-08, "cache_read_input_token_cost_flex": 1.5e-08, "cache_read_input_token_cost_priority": 5.4e-08, "input_cost_per_token": 3e-07, @@ -52416,6 +52435,7 @@ }, "vertex_ai/deep-research-pro-preview-12-2025": { "cache_read_input_token_cost": 2e-07, + "cache_read_input_token_cost_batches": 1e-07, "input_cost_per_image": 0.0011, "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 94786f250b0..431e965524e 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -26790,6 +26790,7 @@ "cache_read_input_token_cost": 2e-07, "cache_read_input_token_cost_above_200k_tokens": 4e-07, "cache_read_input_token_cost_above_200k_tokens_priority": 7.2e-07, + "cache_read_input_token_cost_batches": 1e-07, "cache_read_input_token_cost_flex": 1e-07, "cache_read_input_token_cost_priority": 3.6e-07, "deprecation_date": "2027-05-28", @@ -26883,6 +26884,7 @@ }, "gemini-3.1-flash-image": { "cache_read_input_token_cost": 5e-08, + "cache_read_input_token_cost_batches": 2.5e-08, "cache_read_input_token_cost_flex": 2.5e-08, "deprecation_date": "2027-05-28", "input_cost_per_image": 0.00056, @@ -26967,6 +26969,7 @@ }, "gemini-3.1-flash-lite-image": { "cache_read_input_token_cost": 2.5e-08, + "cache_read_input_token_cost_batches": 1.25e-08, "cache_read_input_token_cost_flex": 1.25e-08, "input_cost_per_image": 0.00028, "input_cost_per_token": 2.5e-07, @@ -27060,6 +27063,7 @@ "cache_read_input_audio_token_cost": 5e-08, "deprecation_date": "2027-05-07", "cache_read_input_token_cost": 2.5e-08, + "cache_read_input_token_cost_batches": 1.25e-08, "cache_read_input_token_cost_flex": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, "input_cost_per_audio_token": 5e-07, @@ -27120,6 +27124,7 @@ "gemini-3.5-flash-lite": { "deprecation_date": "2027-07-21", "cache_read_input_token_cost": 3e-08, + "cache_read_input_token_cost_batches": 1.5e-08, "cache_read_input_token_cost_flex": 1.5e-08, "cache_read_input_token_cost_priority": 5.4e-08, "input_cost_per_token": 3e-07, @@ -27177,6 +27182,7 @@ }, "deep-research-pro-preview-12-2025": { "cache_read_input_token_cost": 2e-07, + "cache_read_input_token_cost_batches": 1e-07, "input_cost_per_image": 0.0011, "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, @@ -27888,6 +27894,7 @@ "prompt_cache_min_tokens": 4096, "deprecation_date": "2027-05-19", "cache_read_input_token_cost": 1.5e-07, + "cache_read_input_token_cost_batches": 7.5e-08, "input_cost_per_token": 1.5e-06, "input_cost_per_audio_token": 1.5e-06, "litellm_provider": "vertex_ai", @@ -27948,6 +27955,7 @@ "vertex_ai/gemini-3.6-flash": { "prompt_cache_min_tokens": 4096, "cache_read_input_token_cost": 7.5e-08, + "cache_read_input_token_cost_batches": 3.75e-08, "cache_read_input_token_cost_flex": 3.75e-08, "input_cost_per_token": 7.5e-07, "input_cost_per_token_batches": 3.75e-07, @@ -28006,6 +28014,7 @@ "vertex_ai/gemini-3.7-flash": { "prompt_cache_min_tokens": 4096, "cache_read_input_token_cost": 7.5e-08, + "cache_read_input_token_cost_batches": 3.75e-08, "cache_read_input_token_cost_flex": 3.75e-08, "input_cost_per_token": 7.5e-07, "input_cost_per_token_batches": 3.75e-07, @@ -28065,6 +28074,7 @@ "vertex_ai/gemini-3.8-flash": { "prompt_cache_min_tokens": 4096, "cache_read_input_token_cost": 7.5e-08, + "cache_read_input_token_cost_batches": 3.75e-08, "cache_read_input_token_cost_flex": 3.75e-08, "input_cost_per_token": 7.5e-07, "input_cost_per_token_batches": 3.75e-07, @@ -30397,6 +30407,7 @@ "prompt_cache_min_tokens": 4096, "deprecation_date": "2027-05-19", "cache_read_input_token_cost": 1.5e-07, + "cache_read_input_token_cost_batches": 7.5e-08, "input_cost_per_audio_token": 1.5e-06, "input_cost_per_token": 1.5e-06, "litellm_provider": "vertex_ai-language-models", @@ -30457,6 +30468,7 @@ "gemini-3.6-flash": { "prompt_cache_min_tokens": 4096, "cache_read_input_token_cost": 7.5e-08, + "cache_read_input_token_cost_batches": 3.75e-08, "cache_read_input_token_cost_flex": 3.75e-08, "input_cost_per_token": 7.5e-07, "input_cost_per_token_batches": 3.75e-07, @@ -30515,6 +30527,7 @@ "gemini-3.7-flash": { "prompt_cache_min_tokens": 4096, "cache_read_input_token_cost": 7.5e-08, + "cache_read_input_token_cost_batches": 3.75e-08, "cache_read_input_token_cost_flex": 3.75e-08, "input_cost_per_token": 7.5e-07, "input_cost_per_token_batches": 3.75e-07, @@ -30574,6 +30587,7 @@ "gemini-3.8-flash": { "prompt_cache_min_tokens": 4096, "cache_read_input_token_cost": 7.5e-08, + "cache_read_input_token_cost_batches": 3.75e-08, "cache_read_input_token_cost_flex": 3.75e-08, "input_cost_per_token": 7.5e-07, "input_cost_per_token_batches": 3.75e-07, @@ -52123,6 +52137,7 @@ "cache_read_input_token_cost": 2e-07, "cache_read_input_token_cost_above_200k_tokens": 4e-07, "cache_read_input_token_cost_above_200k_tokens_priority": 7.2e-07, + "cache_read_input_token_cost_batches": 1e-07, "cache_read_input_token_cost_flex": 1e-07, "cache_read_input_token_cost_priority": 3.6e-07, "deprecation_date": "2027-05-28", @@ -52168,6 +52183,7 @@ }, "vertex_ai/gemini-3.1-flash-image": { "cache_read_input_token_cost": 5e-08, + "cache_read_input_token_cost_batches": 2.5e-08, "cache_read_input_token_cost_flex": 2.5e-08, "deprecation_date": "2027-05-28", "input_cost_per_image": 0.00056, @@ -52204,6 +52220,7 @@ }, "vertex_ai/gemini-3.1-flash-lite-image": { "cache_read_input_token_cost": 2.5e-08, + "cache_read_input_token_cost_batches": 1.25e-08, "cache_read_input_token_cost_flex": 1.25e-08, "input_cost_per_image": 0.00028, "input_cost_per_token": 2.5e-07, @@ -52297,6 +52314,7 @@ "cache_read_input_audio_token_cost": 5e-08, "deprecation_date": "2027-05-07", "cache_read_input_token_cost": 2.5e-08, + "cache_read_input_token_cost_batches": 1.25e-08, "cache_read_input_token_cost_flex": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, "input_cost_per_audio_token": 5e-07, @@ -52358,6 +52376,7 @@ "vertex_ai/gemini-3.5-flash-lite": { "deprecation_date": "2027-07-21", "cache_read_input_token_cost": 3e-08, + "cache_read_input_token_cost_batches": 1.5e-08, "cache_read_input_token_cost_flex": 1.5e-08, "cache_read_input_token_cost_priority": 5.4e-08, "input_cost_per_token": 3e-07, @@ -52416,6 +52435,7 @@ }, "vertex_ai/deep-research-pro-preview-12-2025": { "cache_read_input_token_cost": 2e-07, + "cache_read_input_token_cost_batches": 1e-07, "input_cost_per_image": 0.0011, "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, From 989d7b87b2d30982a6300dde227ec45d8f60f4ce Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 14:14:13 -0700 Subject: [PATCH 034/101] fix(proxy): attribute provider and model_info on pre_call_hook rejections (#41077) * fix(proxy): attribute provider and model info on pre-call rejected requests Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): keep pre-call rejections out of deployment cooldown and prometheus deployment state Stamp model_info only into the logging metadata so the router's failure callbacks do not count a key-level 429 or guardrail 403 against the deployment, treat a resolved plus an unresolved deployment as ambiguous provider attribution, and stop the prometheus deployment counters and deployment_state from treating a proxy-side reject as a selected deployment Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): skip deployment attribution when the rejected body's model is not a string Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(prometheus): bucket non-string request models as other instead of raising in failure hook Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): resolve team deployments and treat guardrail rejects as proxy-side in failure attribution Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(prometheus): flag pre-routing rejects instead of matching exception names Post-call GuardrailRaisedException failures kept their deployment labels on main but lost them on this branch because every GuardrailRaisedException was treated as a pre-routing reject. The proxy failure path now flags litellm_params with proxy_rejected_before_routing only when it adds deployment attribution itself, and the Prometheus logger keys deployment selection off that flag Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): key pre-routing reject flag off provider handoff, not caller metadata Caller-supplied metadata.model_info (kept for keys allowed to override pricing) no longer suppresses proxy_rejected_before_routing. The hook now checks the logging object's first_api_call_start_time, which only the provider handoff sets, so Prometheus never records a deployment failure for a request that was rejected before routing. Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(e2e): poll for both served and rejected spend rows before asserting attribution Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> Co-authored-by: yucheng --- litellm/constants.py | 3 + litellm/integrations/prometheus.py | 19 +- litellm/proxy/utils.py | 101 ++++ tests/e2e/AGENTS.md | 2 +- .../coverage_registry/quota_management.yaml | 1 + tests/e2e/models.py | 1 + .../spend_tracking/test_spend_tracking_e2e.py | 46 +- ...ometheus_deployment_state_proxy_rejects.py | 101 ++++ ..._prometheus_requested_model_cardinality.py | 16 + .../test_post_call_failure_hook.py | 456 +++++++++++++++++- 10 files changed, 734 insertions(+), 12 deletions(-) create mode 100644 tests/test_litellm/integrations/test_prometheus_deployment_state_proxy_rejects.py diff --git a/litellm/constants.py b/litellm/constants.py index 1012ca831f2..e5b662bd515 100644 --- a/litellm/constants.py +++ b/litellm/constants.py @@ -238,6 +238,9 @@ LOGS_GUARDRAIL_INFORMATION_MARKER: Final = "_litellm_logs_guardrail_information" # llm_provider stamped on proxy-side rate limit errors when the model resolves to no deployment PROXY_LLM_PROVIDER_FALLBACK: Final = "litellm_proxy" +# litellm_params flag on failure logs for requests the proxy rejected before routing to a deployment +PROXY_REJECTED_BEFORE_ROUTING_KEY: Final = "proxy_rejected_before_routing" + # Generic fallback for unknown models DEFAULT_REASONING_EFFORT_MINIMAL_THINKING_BUDGET: Final = int( os.getenv("DEFAULT_REASONING_EFFORT_MINIMAL_THINKING_BUDGET", 128) diff --git a/litellm/integrations/prometheus.py b/litellm/integrations/prometheus.py index 28ac9f5cdae..d62a6c3427a 100644 --- a/litellm/integrations/prometheus.py +++ b/litellm/integrations/prometheus.py @@ -18,7 +18,7 @@ from typing_extensions import ReadOnly, TypedDict import litellm from litellm._logging import print_verbose, verbose_logger -from litellm.constants import PROXY_LLM_PROVIDER_FALLBACK +from litellm.constants import PROXY_LLM_PROVIDER_FALLBACK, PROXY_REJECTED_BEFORE_ROUTING_KEY from litellm.exceptions import ( validate_rate_limit_category, validate_rate_limit_type, @@ -214,17 +214,22 @@ def _get_proxy_llm_router() -> Router | None: return llm_router -def _bounded_requested_model_label(requested_model: str | None, router_originated: bool = False) -> str | None: +def _bounded_requested_model_label(requested_model: object, router_originated: bool = False) -> str | None: """ Bound ``requested_model`` label cardinality: names the router recognizes (model names, deployment ids, aliases, routing groups, team public model names) or matches via a global or team wildcard/pattern route keep their own label value; any other client-supplied string collapses into the - single ``other`` bucket. With no proxy router to vouch for the string, - client-supplied values collapse to ``other`` while ``router_originated`` - values (emitted by an SDK ``Router``'s own deployment failure and - fallback events, where the proxy router never exists) pass through. + single ``other`` bucket, as does any non-string request ``model`` value. + With no proxy router to vouch for the string, client-supplied values + collapse to ``other`` while ``router_originated`` values (emitted by an + SDK ``Router``'s own deployment failure and fallback events, where the + proxy router never exists) pass through. """ + if requested_model is None: + return None + if not isinstance(requested_model, str): + return UNRECOGNIZED_REQUESTED_MODEL_LABEL if not requested_model: return requested_model llm_router: Final = _get_proxy_llm_router() @@ -2832,7 +2837,7 @@ class PrometheusLogger(CustomLogger): # On LiteLLM-side rejects (no deployment picked), route request_kwargs["model"] # into requested_model and leave deployment-scoped labels empty. - deployment_selected: Final = bool(model_id) + deployment_selected: Final = bool(model_id) and not _litellm_params.get(PROXY_REJECTED_BEFORE_ROUTING_KEY) if deployment_selected: label_litellm_model_name = litellm_model_name label_model_id = model_id diff --git a/litellm/proxy/utils.py b/litellm/proxy/utils.py index ea3ecb7f637..c7ce9d081d6 100644 --- a/litellm/proxy/utils.py +++ b/litellm/proxy/utils.py @@ -52,6 +52,7 @@ from litellm.constants import ( DEFAULT_MODEL_CREATED_AT_TIME, LITELLM_LOGGING_NO_UPSTREAM_LLM_CALL, MAX_TEAM_LIST_LIMIT, + PROXY_REJECTED_BEFORE_ROUTING_KEY, REDIS_SPEND_LOGS_BUFFER_DEQUEUE_COUNT, SPEND_LOG_QUEUE_MAX_BYTES, SPEND_LOG_WRITE_BATCH_MAX_BYTES, @@ -979,6 +980,92 @@ def _failure_usage_to_lift( _EMPTY_LIFT: Final = MappingProxyType({}) +def _stamp_deployment_attribution( + litellm_params: dict[str, object], model_group: str | None, team_id: str | None, dispatched: bool +) -> Mapping[str, object]: + """Stamp provider and logging-metadata attribution onto ``litellm_params`` and return it. + ``litellm_params["model_info"]`` stays unset: the router's cooldown and per-deployment rpm + callbacks key off it and must not count a proxy-side reject against the deployment. A failure + after the provider handoff keeps the metadata the router stamped; a request that never reached a + provider is flagged ``PROXY_REJECTED_BEFORE_ROUTING_KEY`` (deployment metrics key off it) whatever + its metadata says, since ``metadata.model_info`` can be caller supplied.""" + attribution: Final = _deployment_attribution_for_model_group(model_group, team_id) + if "custom_llm_provider" in attribution: + litellm_params["custom_llm_provider"] = attribution["custom_llm_provider"] + if dispatched: + return attribution + litellm_params[PROXY_REJECTED_BEFORE_ROUTING_KEY] = True + if "model_info" not in attribution: + return attribution + if litellm_params.get("metadata") is None: + litellm_params["metadata"] = {} # mutable-ok: legacy logging payload is populated in place + metadata: Final = litellm_params["metadata"] + if not isinstance(metadata, dict): + return attribution + metadata.setdefault("model_info", attribution["model_info"]) + metadata.setdefault("deployment", attribution["deployment"]) + return attribution + + +def _deployment_attribution_for_model_group(model_group: object, team_id: str | None) -> Mapping[str, object]: + """Provider fields the router would have stamped had it reached a deployment: + ``custom_llm_provider`` when every deployment in the group resolves to the same + provider, plus ``model_info`` and ``deployment`` when the group has exactly one. + ``team_id`` picks the key's team deployments over a global group of the same public name.""" + if not isinstance(model_group, str): + return _EMPTY_LIFT + + from litellm.proxy.proxy_server import llm_router + + if llm_router is None: + return _EMPTY_LIFT + deployments: Final = llm_router.get_model_list(model_name=model_group, team_id=team_id) + if not deployments: + return _EMPTY_LIFT + + def _provider_for_deployment(deployment: Mapping[str, object]) -> str | None: + litellm_params: Final = cast( # cast-ok: router deployment parameters are mapping-shaped + Mapping[str, object], deployment["litellm_params"] + ) + try: + provider: Final = litellm.get_llm_provider( + model=cast(str, litellm_params["model"]), # cast-ok: router deployment model is a string + custom_llm_provider=cast( # cast-ok: router deployment provider is optional + str | None, litellm_params.get("custom_llm_provider") + ), + )[1] + return cast(str | None, provider) # cast-ok: provider resolver returns an optional provider string + except Exception: # noqa: BLE001 # get_llm_provider raises for unmapped models + return None + + providers: Final = frozenset(_provider_for_deployment(deployment) for deployment in deployments) + shared_provider: Final = next(iter(providers)) if len(providers) == 1 else None + single_deployment: Final = deployments[0] if len(deployments) == 1 else None + single_deployment_params: Final = ( + cast( # cast-ok: router deployment parameters are mapping-shaped + Mapping[str, object], single_deployment["litellm_params"] + ) + if single_deployment is not None + else None + ) + return MappingProxyType( + { + # mutable-ok: frozen immediately by the outer MappingProxyType + **({"custom_llm_provider": shared_provider} if shared_provider is not None else {}), + **( + { # mutable-ok: frozen immediately by the outer MappingProxyType + "model_info": dict( # mutable-ok: preserve the router's mutable model-info payload + single_deployment.get("model_info") or {} + ), + "deployment": single_deployment_params["model"], + } + if single_deployment is not None and single_deployment_params is not None + else {} # mutable-ok: frozen immediately by the outer MappingProxyType + ), + } + ) + + def _call_type_for_route(route: str | None) -> str | None: """The route's call type when it maps to a single operation (its async and sync variants); None for routes shared by several operations, since the method is not known here.""" @@ -3227,11 +3314,25 @@ class ProxyLogging: elif k not in ("model", "user", "litellm_logging_obj"): _optional_params[k] = v + attribution: Final = _stamp_deployment_attribution( + _litellm_params, + request_data.get("model"), + user_api_key_dict.team_id, + dispatched=litellm_logging_obj.model_call_details.get("first_api_call_start_time") is not None, + ) + litellm_logging_obj.update_environment_variables( model=request_data.get("model", ""), user=request_data.get("user", ""), optional_params=_optional_params, litellm_params=_litellm_params, + **( + { # mutable-ok: frozen immediately by keyword expansion + "custom_llm_provider": attribution["custom_llm_provider"] + } + if "custom_llm_provider" in attribution + else {} # mutable-ok: frozen immediately by keyword expansion + ), ) input: list | str | dict = "" diff --git a/tests/e2e/AGENTS.md b/tests/e2e/AGENTS.md index 6ea75b806d0..ad1e0322787 100644 --- a/tests/e2e/AGENTS.md +++ b/tests/e2e/AGENTS.md @@ -216,7 +216,7 @@ quota_management... | isolates_per_model | isolates_per_member | isolates_per_group | enforced_across_keys | routes_to_fallback | reseed_matches_db | reports_spend | logs_cost | zero_cost | matches_sum_of_logs | loses_no_spend | attributes_spend | writes_own_rows - | writes_failure_row | returns_cost | keeps_total | joins_key | reports_alias_and_email + | writes_failure_row | attributes_provider | returns_cost | keeps_total | joins_key | reports_alias_and_email | health_rows_keep_service_account | retrieve_batch_cost_joins_retrieving_key | poller_batch_cost_joins_creating_key | bills_under_request_session e.g. quota_management.ratelimit.rpm.blocks_over_limit exercised_on=[chat_completions, messages] diff --git a/tests/e2e/coverage_registry/quota_management.yaml b/tests/e2e/coverage_registry/quota_management.yaml index 5432c5095a2..5ea48fdcd9d 100644 --- a/tests/e2e/coverage_registry/quota_management.yaml +++ b/tests/e2e/coverage_registry/quota_management.yaml @@ -51,6 +51,7 @@ - {id: quota_management.spend_tracking.end_user.attributes_spend, module: quota_management, tier: P1, behavior: spend_tracking, variant: end_user, assertions: [attributes_spend], exercised_on: [chat_completions], source: "proxy/spend_tracking/spend_tracking_utils.py", rationale: "user= attribution lands the end-user id on the spend row"} - {id: quota_management.spend_tracking.per_model.writes_own_rows, module: quota_management, tier: P2, behavior: spend_tracking, variant: per_model, assertions: [writes_own_rows], exercised_on: [chat_completions], source: "proxy/spend_tracking/spend_tracking_utils.py", rationale: "Each model on a shared key gets its own spend row"} - {id: quota_management.spend_tracking.failure.writes_failure_row, module: quota_management, tier: P1, behavior: spend_tracking, variant: failure, assertions: [writes_failure_row], exercised_on: [chat_completions], source: "proxy/spend_tracking/spend_log_error_logger.py", rationale: "A failed call writes a failure-status spend row"} +- {id: quota_management.spend_tracking.failure.attributes_provider, module: quota_management, tier: P1, behavior: spend_tracking, variant: failure, assertions: [attributes_provider], exercised_on: [chat_completions], source: "proxy/utils.py", rationale: "A request rejected in pre_call_hook (rate limit, guardrail) still lands its single deployment's provider and model_id on the failure spend row"} - {id: quota_management.spend_tracking.spend_calculate.returns_cost, module: quota_management, tier: P2, behavior: spend_tracking, variant: spend_calculate, assertions: [returns_cost], exercised_on: [spend_calculate], source: "proxy/spend_tracking/spend_management_endpoints.py", rationale: "/spend/calculate prices a hypothetical request at nonzero cost"} - {id: quota_management.spend_tracking.pagination.keeps_total, module: quota_management, tier: P2, behavior: spend_tracking, variant: pagination, assertions: [keeps_total], exercised_on: [chat_completions], source: "proxy/spend_tracking/spend_management_endpoints.py", rationale: "Spend-logs v2 pagination caps page size without losing the total"} - {id: quota_management.spend_tracking.cache_write.bills_cache_creation_rate, module: quota_management, tier: P1, behavior: spend_tracking, variant: cache_write, assertions: [bills_cache_creation_rate], exercised_on: [chat_completions], source: "litellm_core_utils/llm_cost_calc/utils.py", rationale: "OpenAI cache-write tokens land on the spend row as cache-creation tokens billed at the cache-creation rate, not silently at the input rate (#34046)"} diff --git a/tests/e2e/models.py b/tests/e2e/models.py index 74cad3ad8df..bc81d1015ba 100644 --- a/tests/e2e/models.py +++ b/tests/e2e/models.py @@ -952,6 +952,7 @@ class SpendLogRow(BaseModel): cache_hit: str | None = None call_type: str | None = None custom_llm_provider: str | None = None + model_id: str | None = None team_id: str | None = None user: str | None = None end_user: str | None = None diff --git a/tests/e2e/quota_management/spend_tracking/test_spend_tracking_e2e.py b/tests/e2e/quota_management/spend_tracking/test_spend_tracking_e2e.py index 8a91e53e7d7..6ca6f8cee55 100644 --- a/tests/e2e/quota_management/spend_tracking/test_spend_tracking_e2e.py +++ b/tests/e2e/quota_management/spend_tracking/test_spend_tracking_e2e.py @@ -21,9 +21,9 @@ from math import isclose from typing import Final import pytest -from e2e_http import Success +from e2e_http import RateLimitedError, Success from lifecycle import ResourceManager -from models import LiteLLMParamsBody, SpendLogs, SpendLogsParams +from models import KeyGenerateBody, LiteLLMParamsBody, SpendLogs, SpendLogsParams from spend_e2e_client import SpendClient, SpendLogRow, is_ok, unique_marker, unwrap pytestmark = pytest.mark.e2e @@ -43,6 +43,7 @@ def _summarize(rows: list[SpendLogRow]) -> list[dict[str, object]]: "cache_hit", "call_type", "custom_llm_provider", + "model_id", "prompt_tokens", "completion_tokens", "total_tokens", @@ -498,6 +499,47 @@ def test_failure_call_writes_failure_status_row( assert (failure_row.spend or 0) == 0.0, "failed call must not be charged" +@pytest.mark.covers("quota_management.spend_tracking.failure.attributes_provider") +def test_pre_call_rejection_row_attributes_provider_and_model_id( + client: SpendClient, resources: ResourceManager +) -> None: + """A request the proxy rejects before the router picks a deployment (here the + key's rpm limit, a pre_call_hook 429) never reaches the code that stamps the + deployment onto the log. The failure row must still carry the provider and + model_id of the model group's only deployment, so per-provider failure reports + can count it.""" + model = f"e2e-spend-precall-{unique_marker()}" + model_id = client.proxy.create_model( + model, LiteLLMParamsBody(model="openai/gpt-5.5", api_key="os.environ/OPENAI_API_KEY") + ) + resources.defer(lambda: client.proxy.delete_model(model_id)) + key = client.proxy.generate_key(KeyGenerateBody(models=[model], rpm_limit=1)) + resources.defer(lambda: client.proxy.delete_key(key)) + + unwrap(client.chat(key, model, f"reply with one word {unique_marker()}", max_tokens=8)) + rejected = client.chat(key, model, f"over the rpm limit {unique_marker()}", max_tokens=8) + assert isinstance(rejected, RateLimitedError), ( + f"the second call on an rpm_limit=1 key must be rejected with 429 before routing, got {rejected}" + ) + + rows = client.poll_logs_for_key( + key, + min_rows=2, + predicate=lambda rs: {r.status for r in rs} >= {"success", "failure"}, + ) + success_row = _require_row(rows, lambda r: r.status == "success", "for the served call") + failure_row = _require_row(rows, lambda r: r.status == "failure", "for the rate-limited call") + + assert failure_row.custom_llm_provider == success_row.custom_llm_provider, ( + f"rejected call lost its provider: failure row {failure_row.custom_llm_provider!r} vs " + f"served row {success_row.custom_llm_provider!r}; {_summarize(rows)}" + ) + assert failure_row.model_id == model_id, ( + f"rejected call lost its deployment: failure row model_id {failure_row.model_id!r} vs " + f"registered {model_id!r}; {_summarize(rows)}" + ) + + @pytest.mark.covers("quota_management.spend_tracking.spend_calculate.returns_cost") def test_spend_calculate_returns_nonzero_cost(client: SpendClient) -> None: cost = client.calculate_spend( diff --git a/tests/test_litellm/integrations/test_prometheus_deployment_state_proxy_rejects.py b/tests/test_litellm/integrations/test_prometheus_deployment_state_proxy_rejects.py new file mode 100644 index 00000000000..fedfc2b0848 --- /dev/null +++ b/tests/test_litellm/integrations/test_prometheus_deployment_state_proxy_rejects.py @@ -0,0 +1,101 @@ +""" +LIT-7701 attributes a pre_call_hook rejection's failure log to the model +group's single deployment (``model_id`` and ``custom_llm_provider``) and flags +it with ``PROXY_REJECTED_BEFORE_ROUTING_KEY``. The deployment health metrics +must keep treating such rejects as "no deployment picked": a key rate limit or +guardrail block never reached the deployment, so it must not flip +``litellm_deployment_state`` to partial outage or count as a deployment failure +response. A failure raised after the router picked a deployment (a post-call +guardrail block, a provider error) carries no flag and keeps its deployment labels. +""" + +import pytest +from fastapi import HTTPException +from prometheus_client import REGISTRY + +from litellm.constants import PROXY_REJECTED_BEFORE_ROUTING_KEY +from litellm.exceptions import GuardrailRaisedException +from litellm.integrations.prometheus import PrometheusLogger +from litellm.proxy._types import ProxyException +from litellm.proxy.common_utils.proxy_rate_limit_error import ProxyRateLimitError + + +@pytest.fixture(autouse=True) +def cleanup_prometheus_registry(): + for collector in list(REGISTRY._collector_to_names.keys()): + try: + REGISTRY.unregister(collector) + except Exception: + pass + + yield + + for collector in list(REGISTRY._collector_to_names.keys()): + try: + REGISTRY.unregister(collector) + except Exception: + pass + + +def _attributed_failure_kwargs(exception: Exception, rejected_before_routing: bool) -> dict: + return { + "model": "openai/gpt-4.1", + "litellm_params": { + "custom_llm_provider": "openai", + "metadata": {"model_info": {"id": "dep-1"}, "model_group": "internal-model"}, + **({PROXY_REJECTED_BEFORE_ROUTING_KEY: True} if rejected_before_routing else {}), + }, + "standard_logging_object": { + "model_id": "dep-1", + "model_group": "internal-model", + "api_base": "https://api.openai.com", + "metadata": {}, + }, + "exception": exception, + } + + +def _model_id_values(metric) -> set[str]: + index = metric._labelnames.index("model_id") + return {sample_key[index] for sample_key in metric._metrics} + + +class _ProviderError(Exception): + status_code = 500 + + +@pytest.mark.parametrize( + "rejection", + [ + HTTPException(status_code=403, detail="guardrail blocked"), + ProxyException(message="budget exceeded", type="budget_exceeded", param=None, code=400), + ProxyRateLimitError(detail={"error": "key rpm limit"}), + GuardrailRaisedException(guardrail_name="pii", message="blocked", status_code=403), + ], + ids=["http_exception", "proxy_exception", "proxy_rate_limit", "guardrail_raised"], +) +def test_attributed_proxy_reject_leaves_deployment_healthy(rejection: Exception): + logger = PrometheusLogger() + + logger.set_llm_deployment_failure_metrics(_attributed_failure_kwargs(rejection, rejected_before_routing=True)) + + assert logger.litellm_deployment_state._metrics == {} + assert _model_id_values(logger.litellm_deployment_failure_responses) == {""} + assert _model_id_values(logger.litellm_deployment_total_requests) == {""} + + +@pytest.mark.parametrize( + "failure", + [ + _ProviderError("upstream 500"), + GuardrailRaisedException(guardrail_name="pii", message="response blocked", status_code=400), + ], + ids=["provider_error", "post_call_guardrail"], +) +def test_failure_after_routing_still_marks_deployment_partial_outage(failure: Exception): + logger = PrometheusLogger() + + logger.set_llm_deployment_failure_metrics(_attributed_failure_kwargs(failure, rejected_before_routing=False)) + + assert _model_id_values(logger.litellm_deployment_state) == {"dep-1"} + assert _model_id_values(logger.litellm_deployment_failure_responses) == {"dep-1"} diff --git a/tests/test_litellm/integrations/test_prometheus_requested_model_cardinality.py b/tests/test_litellm/integrations/test_prometheus_requested_model_cardinality.py index 519a13751f1..f86f4460b28 100644 --- a/tests/test_litellm/integrations/test_prometheus_requested_model_cardinality.py +++ b/tests/test_litellm/integrations/test_prometheus_requested_model_cardinality.py @@ -116,6 +116,22 @@ async def test_unknown_models_collapse_to_one_series_on_proxy_request_metrics(ro assert _total_value(metric) == 25 +@pytest.mark.asyncio +@pytest.mark.parametrize("model", [["gpt-4o-mini"], {"name": "gpt-4o-mini"}, 123]) +async def test_non_string_models_collapse_to_other_on_proxy_request_metrics(router, model: object): + logger = PrometheusLogger() + + with patch("litellm.proxy.proxy_server.llm_router", router, create=True): # test-quality-ok: production reads proxy_server.llm_router lazily, no injection seam + await logger.async_post_call_failure_hook( + request_data={"model": model, "metadata": {}, "proxy_server_request": {}}, + original_exception=_ClientSideError("'model' must be a string."), + user_api_key_dict=UserAPIKeyAuth(api_key="hashed-key-1"), + ) + + assert _requested_model_values(logger.litellm_proxy_failed_requests_metric) == {UNRECOGNIZED_REQUESTED_MODEL_LABEL} + assert _total_value(logger.litellm_proxy_failed_requests_metric) == 1 + + @pytest.mark.asyncio async def test_known_alias_and_wildcard_models_keep_their_own_labels(router): logger = PrometheusLogger() diff --git a/tests/test_litellm/proxy/utils/proxy_logging/test_post_call_failure_hook.py b/tests/test_litellm/proxy/utils/proxy_logging/test_post_call_failure_hook.py index a4bb7d63548..d7c52c528eb 100644 --- a/tests/test_litellm/proxy/utils/proxy_logging/test_post_call_failure_hook.py +++ b/tests/test_litellm/proxy/utils/proxy_logging/test_post_call_failure_hook.py @@ -5,16 +5,18 @@ from __future__ import annotations import asyncio from datetime import datetime -from typing import Any, Final +from types import MappingProxyType +from typing import Final from unittest.mock import AsyncMock, MagicMock import pytest from fastapi import HTTPException import litellm +from litellm.constants import PROXY_REJECTED_BEFORE_ROUTING_KEY from litellm.exceptions import GuardrailRaisedException from litellm.integrations.custom_logger import CustomLogger -from litellm.proxy._types import AlertType, ProxyErrorTypes, UserAPIKeyAuth +from litellm.proxy._types import ProxyErrorTypes, UserAPIKeyAuth from litellm.proxy.utils import ProxyLogging @@ -99,6 +101,456 @@ async def test_post_call_failure_hook_no_callbacks_returns_none( } +@pytest.mark.asyncio +async def test_post_call_failure_hook_attributes_single_router_deployment( + proxy_logging, make_user_api_key_auth, monkeypatch +): + from litellm.proxy import proxy_server + + recorded: list[dict] = [] + + class _RecordingLogger(CustomLogger): + async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time): + recorded.append(kwargs) + + monkeypatch.setattr( + proxy_server, + "llm_router", + litellm.Router( + model_list=[ + { + "model_name": "internal-model", + "litellm_params": {"model": "openai/gpt-4.1", "api_key": "sk-test"}, + "model_info": {"provider": "acme"}, + } + ] + ), + ) + monkeypatch.setattr(litellm, "callbacks", [_RecordingLogger()]) + proxy_logging.alert_types = [] + + await proxy_logging.post_call_failure_hook( + request_data={"model": "internal-model", "messages": [{"role": "user", "content": "hi"}]}, + original_exception=HTTPException(status_code=403, detail="blocked"), + user_api_key_dict=make_user_api_key_auth(request_route="/chat/completions"), + route="/chat/completions", + ) + + assert len(recorded) == 1 + kwargs = recorded[0] + assert kwargs["custom_llm_provider"] == "openai" + assert kwargs["litellm_params"]["custom_llm_provider"] == "openai" + assert kwargs["litellm_params"]["metadata"]["model_info"]["provider"] == "acme" + assert kwargs["litellm_params"]["metadata"]["deployment"] == "openai/gpt-4.1" + assert kwargs["litellm_params"][PROXY_REJECTED_BEFORE_ROUTING_KEY] is True + assert kwargs["standard_logging_object"]["custom_llm_provider"] == "openai" + assert ( + kwargs["standard_logging_object"]["model_id"] == proxy_server.llm_router.get_model_list()[0]["model_info"]["id"] + ) + + +@pytest.mark.asyncio +async def test_post_call_failure_hook_keeps_router_stamped_metadata_for_post_call_failures( + proxy_logging, make_user_api_key_auth, monkeypatch +): + """A post-call guardrail block arrives after the provider handoff with the router's own + ``model_info`` in the request metadata. The pre-routing flag must stay off so deployment + metrics keep attributing the failure to the deployment that actually served the call.""" + from litellm.proxy import proxy_server + + recorded: list[dict] = [] + + class _RecordingLogger(CustomLogger): + async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time): + recorded.append(kwargs) + + monkeypatch.setattr( + proxy_server, + "llm_router", + litellm.Router( + model_list=[ + { + "model_name": "internal-model", + "litellm_params": {"model": "openai/gpt-4.1", "api_key": "sk-test"}, + "model_info": {"id": "routed-deployment"}, + } + ] + ), + ) + monkeypatch.setattr(litellm, "callbacks", [_RecordingLogger()]) + proxy_logging.alert_types = [] + + request_data = { + "litellm_call_id": "post-call-guardrail", + "model": "internal-model", + "messages": [{"role": "user", "content": "hi"}], + "metadata": {"model_info": {"id": "routed-deployment", "served": True}}, + } + logging_obj, request_data = litellm.utils.function_setup( + original_function="acompletion", rules_obj=litellm.utils.Rules(), start_time=datetime.now(), **request_data + ) + logging_obj.model_call_details["first_api_call_start_time"] = datetime.now() + request_data["litellm_logging_obj"] = logging_obj + + await proxy_logging.post_call_failure_hook( + request_data=request_data, + original_exception=GuardrailRaisedException(guardrail_name="g", message="response blocked"), + user_api_key_dict=make_user_api_key_auth(request_route="/chat/completions"), + route="/chat/completions", + ) + + assert len(recorded) == 1 + kwargs = recorded[0] + assert kwargs["litellm_params"]["metadata"]["model_info"] == {"id": "routed-deployment", "served": True} + assert PROXY_REJECTED_BEFORE_ROUTING_KEY not in kwargs["litellm_params"] + assert kwargs["standard_logging_object"]["model_id"] == "routed-deployment" + + +@pytest.mark.asyncio +async def test_post_call_failure_hook_flags_pre_routing_reject_despite_caller_model_info( + proxy_logging, make_user_api_key_auth, monkeypatch +): + """A key allowed to override pricing keeps caller-supplied ``metadata.model_info``. A reject + before any provider handoff must still carry the pre-routing flag so deployment metrics do + not record an outage for a deployment the request never reached.""" + from litellm.proxy import proxy_server + + recorded: list[dict] = [] + + class _RecordingLogger(CustomLogger): + async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time): + recorded.append(kwargs) + + monkeypatch.setattr( + proxy_server, + "llm_router", + litellm.Router( + model_list=[ + { + "model_name": "internal-model", + "litellm_params": {"model": "openai/gpt-4.1", "api_key": "sk-test"}, + "model_info": {"id": "real-deployment"}, + } + ] + ), + ) + monkeypatch.setattr(litellm, "callbacks", [_RecordingLogger()]) + proxy_logging.alert_types = [] + + await proxy_logging.post_call_failure_hook( + request_data={ + "model": "internal-model", + "messages": [{"role": "user", "content": "hi"}], + "metadata": {"model_info": {"id": "spoofed-deployment"}}, + }, + original_exception=HTTPException(status_code=429, detail="key over limit"), + user_api_key_dict=make_user_api_key_auth(request_route="/chat/completions"), + route="/chat/completions", + ) + + assert len(recorded) == 1 + kwargs = recorded[0] + assert kwargs["litellm_params"][PROXY_REJECTED_BEFORE_ROUTING_KEY] is True + assert kwargs["litellm_params"]["custom_llm_provider"] == "openai" + + +@pytest.mark.asyncio +async def test_post_call_failure_hook_attribution_does_not_count_against_the_deployment( + proxy_logging, make_user_api_key_auth, monkeypatch +): + """The router's failure callbacks run on this path too. A proxy-side reject must not + bump the deployment's failure or rpm counters, or a key hitting its own limit + could cool down the only deployment for everyone.""" + from litellm.proxy import proxy_server + + router = litellm.Router( + model_list=[ + { + "model_name": "internal-model", + "litellm_params": {"model": "openai/gpt-4.1", "api_key": "sk-test", "rpm": 100}, + } + ] + ) + monkeypatch.setattr(proxy_server, "llm_router", router) + proxy_logging.alert_types = [] + deployment_id = router.get_model_list()[0]["model_info"]["id"] + + for status in (403, 429): + await proxy_logging.post_call_failure_hook( + request_data={"model": "internal-model", "messages": [{"role": "user", "content": "hi"}]}, + original_exception=HTTPException(status_code=status, detail="blocked"), + user_api_key_dict=make_user_api_key_auth(request_route="/chat/completions"), + route="/chat/completions", + ) + pending = asyncio.all_tasks() - {asyncio.current_task()} + await asyncio.gather(*pending, return_exceptions=True) + + deployment_keys = [key for key in router.cache.in_memory_cache.cache_dict if deployment_id in key] + assert deployment_keys == [], f"proxy reject was counted against the deployment: {deployment_keys}" + + +@pytest.mark.asyncio +async def test_post_call_failure_hook_attributes_the_keys_team_deployment_over_the_global_group( + proxy_logging, make_user_api_key_auth, monkeypatch +): + """A team key requesting its team public model name must be attributed to the team's + deployment, not to a global group that happens to share the public name.""" + from litellm.proxy import proxy_server + + recorded: list[dict] = [] + + class _RecordingLogger(CustomLogger): + async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time): + recorded.append(kwargs) + + monkeypatch.setattr( + proxy_server, + "llm_router", + litellm.Router( + model_list=[ + { + "model_name": "shared-name", + "litellm_params": {"model": "openai/gpt-4.1", "api_key": "sk-test"}, + "model_info": {"id": "global-deployment"}, + }, + { + "model_name": "shared-name_test-team_deadbeef", + "litellm_params": {"model": "anthropic/claude-sonnet-4-5", "api_key": "sk-test"}, + "model_info": { + "id": "team-deployment", + "team_id": "test-team", + "team_public_model_name": "shared-name", + }, + }, + ] + ), + ) + monkeypatch.setattr(litellm, "callbacks", [_RecordingLogger()]) + proxy_logging.alert_types = [] + + await proxy_logging.post_call_failure_hook( + request_data={"model": "shared-name", "messages": [{"role": "user", "content": "hi"}]}, + original_exception=HTTPException(status_code=429, detail="rate limited"), + user_api_key_dict=make_user_api_key_auth(team_id="test-team", request_route="/chat/completions"), + route="/chat/completions", + ) + + assert len(recorded) == 1 + kwargs = recorded[0] + assert kwargs["custom_llm_provider"] == "anthropic" + assert kwargs["litellm_params"]["metadata"]["deployment"] == "anthropic/claude-sonnet-4-5" + assert kwargs["standard_logging_object"]["model_id"] == "team-deployment" + + +@pytest.mark.asyncio +async def test_post_call_failure_hook_omits_provider_for_mixed_router_deployments( + proxy_logging, make_user_api_key_auth, monkeypatch +): + from litellm.proxy import proxy_server + + recorded: list[dict] = [] + + class _RecordingLogger(CustomLogger): + async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time): + recorded.append(kwargs) + + monkeypatch.setattr( + proxy_server, + "llm_router", + litellm.Router( + model_list=[ + { + "model_name": "internal-model", + "litellm_params": {"model": "openai/gpt-4.1", "api_key": "sk-test"}, + }, + { + "model_name": "internal-model", + "litellm_params": {"model": "anthropic/claude-sonnet-4-5", "api_key": "sk-test"}, + }, + ] + ), + ) + monkeypatch.setattr(litellm, "callbacks", [_RecordingLogger()]) + proxy_logging.alert_types = [] + + await proxy_logging.post_call_failure_hook( + request_data={"model": "internal-model", "messages": [{"role": "user", "content": "hi"}]}, + original_exception=HTTPException(status_code=403, detail="blocked"), + user_api_key_dict=make_user_api_key_auth(request_route="/chat/completions"), + route="/chat/completions", + ) + + assert len(recorded) == 1 + kwargs = recorded[0] + assert kwargs.get("custom_llm_provider") is None + assert "model_info" not in (kwargs["litellm_params"].get("metadata") or {}) + + +@pytest.mark.asyncio +async def test_post_call_failure_hook_omits_provider_when_a_deployment_does_not_resolve( + proxy_logging, make_user_api_key_auth, monkeypatch +): + """One deployment resolves to openai and its sibling resolves to nothing: the group + is not known to be single-provider, so no provider is stamped on the failure.""" + from litellm.proxy import proxy_server + + recorded: list[dict] = [] + + class _RecordingLogger(CustomLogger): + async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time): + recorded.append(kwargs) + + router = MagicMock() + router.get_model_list.return_value = [ + {"model_name": "internal-model", "litellm_params": {"model": "openai/gpt-4.1"}}, + {"model_name": "internal-model", "litellm_params": {"model": "unmapped-model-with-no-provider"}}, + ] + monkeypatch.setattr(proxy_server, "llm_router", router) + monkeypatch.setattr(litellm, "callbacks", [_RecordingLogger()]) + proxy_logging.alert_types = [] + + await proxy_logging.post_call_failure_hook( + request_data={"model": "internal-model", "messages": [{"role": "user", "content": "hi"}]}, + original_exception=HTTPException(status_code=403, detail="blocked"), + user_api_key_dict=make_user_api_key_auth(request_route="/chat/completions"), + route="/chat/completions", + ) + + assert len(recorded) == 1 + kwargs = recorded[0] + assert kwargs.get("custom_llm_provider") is None + assert kwargs["litellm_params"].get("custom_llm_provider") is None + + +@pytest.mark.asyncio +async def test_handle_logging_proxy_only_path_attributes_with_read_only_metadata( + proxy_logging, make_user_api_key_auth, monkeypatch +): + """With a logging object already on the request, its metadata is taken as given; + a read-only mapping there must not crash the stamp, and the failure handler + still receives the provider attribution.""" + from litellm.proxy import proxy_server + + monkeypatch.setattr( + proxy_server, + "llm_router", + litellm.Router( + model_list=[ + { + "model_name": "internal-model", + "litellm_params": {"model": "openai/gpt-4.1", "api_key": "sk-test"}, + "model_info": {"provider": "acme"}, + } + ] + ), + ) + logging_obj = MagicMock() + logging_obj.call_type = "acompletion" + logging_obj.model_call_details = {} + logging_obj.async_failure_handler = AsyncMock() + + await proxy_logging._handle_logging_proxy_only_error( + request_data={ + "litellm_logging_obj": logging_obj, + "model": "internal-model", + "messages": [{"role": "user", "content": "hi"}], + "metadata": MappingProxyType({"user_api_key_alias": "frozen"}), + }, + user_api_key_dict=make_user_api_key_auth(request_route="/chat/completions"), + route="/chat/completions", + original_exception=HTTPException(status_code=403, detail="blocked"), + ) + + assert logging_obj.async_failure_handler.called + update_kwargs = logging_obj.update_environment_variables.call_args.kwargs + assert update_kwargs["custom_llm_provider"] == "openai" + assert update_kwargs["litellm_params"]["custom_llm_provider"] == "openai" + assert update_kwargs["litellm_params"]["metadata"] == {"user_api_key_alias": "frozen"} + + +@pytest.mark.asyncio +async def test_post_call_failure_hook_fires_without_router_attribution( + proxy_logging, make_user_api_key_auth, monkeypatch +): + from litellm.proxy import proxy_server + + recorded: list[dict] = [] + + class _RecordingLogger(CustomLogger): + async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time): + recorded.append(kwargs) + + monkeypatch.setattr( + proxy_server, + "llm_router", + litellm.Router( + model_list=[ + { + "model_name": "different-model", + "litellm_params": {"model": "openai/gpt-4.1", "api_key": "sk-test"}, + } + ] + ), + ) + monkeypatch.setattr(litellm, "callbacks", [_RecordingLogger()]) + proxy_logging.alert_types = [] + + await proxy_logging.post_call_failure_hook( + request_data={"model": "internal-model", "messages": [{"role": "user", "content": "hi"}]}, + original_exception=HTTPException(status_code=403, detail="blocked"), + user_api_key_dict=make_user_api_key_auth(request_route="/chat/completions"), + route="/chat/completions", + ) + + assert len(recorded) == 1 + kwargs = recorded[0] + assert kwargs.get("custom_llm_provider") is None + assert "model_info" not in (kwargs["litellm_params"].get("metadata") or {}) + + +@pytest.mark.asyncio +@pytest.mark.parametrize("model", [123, ["internal-model"], {"name": "internal-model"}, None]) +async def test_post_call_failure_hook_fires_for_non_string_model( + proxy_logging, make_user_api_key_auth, monkeypatch, model: object +): + """A body whose ``model`` is not a string is rejected by the proxy before routing; its + failure callback must still fire, unattributed, instead of a TypeError escaping the hook.""" + from litellm.proxy import proxy_server + + recorded: list[dict] = [] + + class _RecordingLogger(CustomLogger): + async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time): + recorded.append(kwargs) + + monkeypatch.setattr( + proxy_server, + "llm_router", + litellm.Router( + model_list=[ + { + "model_name": "internal-model", + "litellm_params": {"model": "openai/gpt-4.1", "api_key": "sk-test"}, + } + ] + ), + ) + monkeypatch.setattr(litellm, "callbacks", [_RecordingLogger()]) + proxy_logging.alert_types = [] + + await proxy_logging.post_call_failure_hook( + request_data={"model": model, "messages": [{"role": "user", "content": "hi"}]}, + original_exception=HTTPException(status_code=400, detail="'model' must be a string."), + user_api_key_dict=make_user_api_key_auth(request_route="/chat/completions"), + route="/chat/completions", + ) + + assert len(recorded) == 1 + kwargs = recorded[0] + assert kwargs.get("custom_llm_provider") is None + assert "model_info" not in (kwargs["litellm_params"].get("metadata") or {}) + + @pytest.mark.asyncio async def test_post_call_failure_hook_callback_returns_http_exception( proxy_logging, make_user_api_key_auth, monkeypatch From 075536eca1a247bbab78d7992275a176875b96ae Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 21:19:26 +0000 Subject: [PATCH 035/101] chore(cost-map): remove models past their deprecation date (#42435) * chore(cost-map): remove models past their deprecation date Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(cost-calc): drop the empty parametrize left behind by the gemini web search removal Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(cost-map): drop merge base block left by conflict resolution Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(cost-calc): drop gemini image cost tests pinned on removed model Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: kerry Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- ...odel_prices_and_context_window_backup.json | 6095 +---------------- model_prices_and_context_window.json | 6095 +---------------- .../test_anthropic_cache_control_hook.py | 2 +- .../llm_cost_calc/test_llm_cost_calc_utils.py | 151 - .../test_tool_call_cost_tracking.py | 123 - .../test_fallback_generalizations.py | 4 - .../test_get_model_cost_map.py | 1 - .../test_litellm_logging.py | 15 - ...streaming_chunk_builder_server_tool_use.py | 26 - .../litellm_core_utils/test_token_counter.py | 3 - .../chat/test_converse_transformation.py | 37 - .../test_databricks_cost_calculator.py | 8 - .../llms/gemini/test_cost_calculator.py | 195 - .../test_github_copilot_transformation.py | 54 - .../llms/openai/test_gpt5_transformation.py | 16 - ...test_vertex_and_google_ai_studio_gemini.py | 4 +- ...test_vertex_passthrough_logging_handler.py | 28 - .../wandb/test_wandb_chat_transformation.py | 4 - .../llms/xai/test_xai_cost_calculator.py | 73 - .../xai/test_xai_redirected_slug_pricing.py | 102 - .../proxy/auth/test_auth_checks.py | 1 - ...t_anthropic_passthrough_logging_handler.py | 73 - .../test_vertex_ai_batch_passthrough.py | 232 - .../proxy/spend_tracking/test_savings.py | 19 - .../test_spend_management_endpoints.py | 172 - .../responses/test_metadata_codex_callback.py | 66 - .../rust_bridge/test_token_counter.py | 1 - tests/test_litellm/test_cost_calculator.py | 374 - .../test_count_tokens_public_api.py | 18 - .../test_gpt_image_cost_calculator.py | 21 - tests/test_litellm/test_router.py | 30 - .../test_together_ai_model_metadata.py | 9 - tests/test_litellm/test_utils.py | 6 - .../test_xai_responses_auto_routing.py | 77 - .../chat/test_azure_ai_transformation.py | 21 - .../test_fireworks_ai_chat_transformation.py | 15 - .../test_moonshot_chat_transformation.py | 2 +- 37 files changed, 18 insertions(+), 14155 deletions(-) delete mode 100644 tests/test_litellm/llms/xai/test_xai_redirected_slug_pricing.py diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 431e965524e..b48bdd6322c 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -53,13 +53,6 @@ "mode": "image_generation", "output_cost_per_image": 0.04 }, - "1024-x-1024/dall-e-2": { - "deprecation_date": "2026-05-12", - "input_cost_per_pixel": 1.9e-08, - "litellm_provider": "openai", - "mode": "image_generation", - "output_cost_per_pixel": 0.0 - }, "1024-x-1024/max-steps/stability.stable-diffusion-xl-v1": { "litellm_provider": "bedrock", "max_input_tokens": 77, @@ -67,13 +60,6 @@ "mode": "image_generation", "output_cost_per_image": 0.08 }, - "256-x-256/dall-e-2": { - "deprecation_date": "2026-05-12", - "input_cost_per_pixel": 2.4414e-07, - "litellm_provider": "openai", - "mode": "image_generation", - "output_cost_per_pixel": 0.0 - }, "512-x-512/50-steps/stability.stable-diffusion-xl-v0": { "litellm_provider": "bedrock", "max_input_tokens": 77, @@ -81,13 +67,6 @@ "mode": "image_generation", "output_cost_per_image": 0.018 }, - "512-x-512/dall-e-2": { - "deprecation_date": "2026-05-12", - "input_cost_per_pixel": 6.86e-08, - "litellm_provider": "openai", - "mode": "image_generation", - "output_cost_per_pixel": 0.0 - }, "512-x-512/max-steps/stability.stable-diffusion-xl-v0": { "litellm_provider": "bedrock", "max_input_tokens": 77, @@ -961,23 +940,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "anthropic.claude-3-haiku-20240307-v1:0": { - "deprecation_date": "2026-09-10", - "input_cost_per_token": 2.5e-07, - "litellm_provider": "bedrock", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.25e-06, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "cache_read_input_token_cost": 2.5e-08, - "cache_creation_input_token_cost": 3.125e-07 - }, "anthropic.claude-3-opus-20240229-v1:0": { "input_cost_per_token": 1.5e-05, "litellm_provider": "bedrock", @@ -993,23 +955,6 @@ "cache_read_input_token_cost": 1.5e-06, "cache_creation_input_token_cost": 1.875e-05 }, - "anthropic.claude-3-sonnet-20240229-v1:0": { - "deprecation_date": "2026-07-30", - "input_cost_per_token": 3e-06, - "litellm_provider": "bedrock", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.5e-05, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "cache_read_input_token_cost": 3e-07, - "cache_creation_input_token_cost": 3.75e-06 - }, "anthropic.claude-instant-v1": { "input_cost_per_token": 8e-07, "litellm_provider": "bedrock", @@ -2971,60 +2916,6 @@ "supports_vision": true, "supports_tool_choice": true }, - "apac.anthropic.claude-3-5-sonnet-20240620-v1:0": { - "deprecation_date": "2026-07-30", - "input_cost_per_token": 3e-06, - "litellm_provider": "bedrock", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.5e-05, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "cache_read_input_token_cost": 3e-07, - "cache_creation_input_token_cost": 3.75e-06 - }, - "apac.anthropic.claude-3-5-sonnet-20241022-v2:0": { - "cache_creation_input_token_cost": 3.75e-06, - "cache_read_input_token_cost": 3e-07, - "deprecation_date": "2026-07-30", - "input_cost_per_token": 3e-06, - "litellm_provider": "bedrock", - "max_input_tokens": 200000, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 1.5e-05, - "supports_assistant_prefill": true, - "supports_computer_use": true, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "apac.anthropic.claude-3-haiku-20240307-v1:0": { - "deprecation_date": "2026-09-10", - "input_cost_per_token": 2.5e-07, - "litellm_provider": "bedrock", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.25e-06, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "cache_read_input_token_cost": 2.5e-08, - "cache_creation_input_token_cost": 3.125e-07 - }, "apac.anthropic.claude-haiku-4-5-20251001-v1:0": { "cache_creation_input_token_cost": 1.375e-06, "cache_read_input_token_cost": 1.1e-07, @@ -3052,23 +2943,6 @@ "input_cost_per_token_batches": 5.5e-07, "output_cost_per_token_batches": 2.75e-06 }, - "apac.anthropic.claude-3-sonnet-20240229-v1:0": { - "deprecation_date": "2026-07-30", - "input_cost_per_token": 3e-06, - "litellm_provider": "bedrock", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.5e-05, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "cache_read_input_token_cost": 3e-07, - "cache_creation_input_token_cost": 3.75e-06 - }, "apac.anthropic.claude-sonnet-4-20250514-v1:0": { "cache_creation_input_token_cost": 3.75e-06, "cache_read_input_token_cost": 3e-07, @@ -3446,29 +3320,6 @@ "supports_max_reasoning_effort": true, "prompt_cache_min_tokens": 1024 }, - "azure_ai/claude-opus-4-1": { - "deprecation_date": "2026-08-05", - "cache_creation_input_token_cost": 1.875e-05, - "cache_creation_input_token_cost_above_1hr": 3e-05, - "cache_read_input_token_cost": 1.5e-06, - "input_cost_per_token": 1.5e-05, - "litellm_provider": "azure_ai", - "max_input_tokens": 200000, - "max_output_tokens": 32000, - "max_tokens": 32000, - "mode": "chat", - "output_cost_per_token": 7.5e-05, - "supports_assistant_prefill": true, - "supports_computer_use": true, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "prompt_cache_min_tokens": 1024 - }, "azure_ai/claude-sonnet-4-5": { "deprecation_date": "2026-10-19", "cache_creation_input_token_cost": 3.75e-06, @@ -4503,43 +4354,6 @@ "output_cost_per_token_priority": 2.2e-05, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, - "azure/eu/gpt-5.1-chat": { - "cache_read_input_token_cost": 1.375e-07, - "deprecation_date": "2026-06-29", - "input_cost_per_token": 1.375e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 1.1e-05, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/batch", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text", - "image" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_none_reasoning_effort": true, - "default_reasoning_effort": "none", - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" - }, "azure/eu/gpt-5.1-codex": { "deprecation_date": "2027-05-15", "cache_read_input_token_cost": 1.375e-07, @@ -4832,43 +4646,6 @@ "output_cost_per_token_priority": 2e-05, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, - "azure/global/gpt-5.1-chat": { - "cache_read_input_token_cost": 1.25e-07, - "deprecation_date": "2026-06-29", - "input_cost_per_token": 1.25e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 1e-05, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/batch", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text", - "image" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_none_reasoning_effort": true, - "default_reasoning_effort": "none", - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" - }, "azure/global/gpt-5.1-codex": { "deprecation_date": "2027-05-15", "cache_read_input_token_cost": 1.25e-07, @@ -4944,19 +4721,6 @@ "supports_function_calling": true, "supports_tool_choice": true }, - "azure/gpt-3.5-turbo-0125": { - "deprecation_date": "2025-03-31", - "input_cost_per_token": 5e-07, - "litellm_provider": "azure", - "max_input_tokens": 16384, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.5e-06, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_tool_choice": true - }, "azure/gpt-3.5-turbo-instruct-0914": { "input_cost_per_token": 1.5e-06, "litellm_provider": "azure_text", @@ -4976,32 +4740,6 @@ "supports_function_calling": true, "supports_tool_choice": true }, - "azure/gpt-35-turbo-0125": { - "deprecation_date": "2025-05-31", - "input_cost_per_token": 5e-07, - "litellm_provider": "azure", - "max_input_tokens": 16384, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.5e-06, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_tool_choice": true - }, - "azure/gpt-35-turbo-1106": { - "deprecation_date": "2025-03-31", - "input_cost_per_token": 1e-06, - "litellm_provider": "azure", - "max_input_tokens": 16384, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 2e-06, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_tool_choice": true - }, "azure/gpt-35-turbo-16k": { "input_cost_per_token": 3e-06, "litellm_provider": "azure", @@ -5769,40 +5507,6 @@ "supports_system_messages": true, "supports_tool_choice": true }, - "azure/gpt-realtime-2": { - "cache_read_input_audio_token_cost": 4e-07, - "cache_read_input_token_cost": 4e-07, - "deprecation_date": "2026-08-31", - "input_cost_per_audio_token": 3.2e-05, - "input_cost_per_image_token": 5e-06, - "input_cost_per_token": 4e-06, - "litellm_provider": "azure", - "max_input_tokens": 32000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "realtime", - "output_cost_per_audio_token": 6.4e-05, - "output_cost_per_token": 2.4e-05, - "source": "https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure", - "supported_endpoints": [ - "/v1/realtime" - ], - "supported_modalities": [ - "text", - "image", - "audio" - ], - "supported_output_modalities": [ - "text", - "audio" - ], - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, "azure/gpt-realtime-2.1": { "cache_creation_input_audio_token_cost": 4e-07, "cache_read_input_audio_token_cost": 4e-07, @@ -6100,45 +5804,6 @@ "supports_minimal_reasoning_effort": true, "cache_read_input_token_cost_batches": 6.25e-08 }, - "azure/gpt-5.1-chat-2025-11-13": { - "cache_read_input_token_cost": 1.25e-07, - "cache_read_input_token_cost_priority": 2.5e-07, - "deprecation_date": "2026-06-29", - "input_cost_per_token": 1.25e-06, - "input_cost_per_token_priority": 2.5e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 1e-05, - "output_cost_per_token_priority": 2e-05, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text", - "image" - ], - "supports_function_calling": false, - "supports_native_streaming": true, - "supports_parallel_function_calling": false, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": false, - "supports_vision": true, - "supports_none_reasoning_effort": true, - "default_reasoning_effort": "none", - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" - }, "azure/gpt-5.1-codex-2025-11-13": { "cache_read_input_token_cost": 1.25e-07, "cache_read_input_token_cost_priority": 2.5e-07, @@ -6289,73 +5954,6 @@ "supports_vision": true, "cache_read_input_token_cost_batches": 6.25e-08 }, - "azure/gpt-5-chat": { - "cache_read_input_token_cost": 1.25e-07, - "deprecation_date": "2026-06-29", - "input_cost_per_token": 1.25e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 1e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/batch", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "azure/gpt-5-chat-latest": { - "cache_read_input_token_cost": 1.25e-07, - "deprecation_date": "2026-06-29", - "input_cost_per_token": 1.25e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 1e-05, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/batch", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, "azure/gpt-5-codex": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2027-03-17", @@ -6617,43 +6215,6 @@ "output_cost_per_token_priority": 2e-05, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, - "azure/gpt-5.1-chat": { - "cache_read_input_token_cost": 1.25e-07, - "deprecation_date": "2026-06-29", - "input_cost_per_token": 1.25e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 1e-05, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/batch", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text", - "image" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_none_reasoning_effort": true, - "default_reasoning_effort": "none", - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" - }, "azure/gpt-5.1-codex": { "deprecation_date": "2027-05-15", "cache_read_input_token_cost": 1.25e-07, @@ -6832,78 +6393,6 @@ "supports_vision": true, "cache_read_input_token_cost_batches": 8.75e-08 }, - "azure/gpt-5.2-chat": { - "cache_read_input_token_cost": 1.75e-07, - "cache_read_input_token_cost_priority": 3.5e-07, - "deprecation_date": "2026-06-29", - "input_cost_per_token": 1.75e-06, - "input_cost_per_token_priority": 3.5e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 1.4e-05, - "output_cost_per_token_priority": 2.8e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "azure/gpt-5.2-chat-2025-12-11": { - "cache_read_input_token_cost": 1.75e-07, - "cache_read_input_token_cost_priority": 3.5e-07, - "deprecation_date": "2026-05-13", - "input_cost_per_token": 1.75e-06, - "input_cost_per_token_priority": 3.5e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 1.4e-05, - "output_cost_per_token_priority": 2.8e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, "azure/gpt-5.2-codex": { "cache_read_input_token_cost": 1.75e-07, "deprecation_date": "2027-07-13", @@ -6936,42 +6425,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "azure/gpt-5.3-chat": { - "cache_read_input_token_cost": 1.75e-07, - "cache_read_input_token_cost_priority": 3.5e-07, - "deprecation_date": "2026-06-29", - "input_cost_per_token": 1.75e-06, - "input_cost_per_token_priority": 3.5e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 1.4e-05, - "output_cost_per_token_priority": 2.8e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - 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"azure_ai/Phi-3-medium-128k-instruct": { "input_cost_per_token": 1.7e-07, "litellm_provider": "azure_ai", @@ -11518,16 +10870,6 @@ "supports_tool_choice": true, "supports_reasoning": true }, - "azure_ai/mistral-document-ai-2505": { - "deprecation_date": "2026-07-20", - "litellm_provider": "azure_ai", - "ocr_cost_per_page": 0.003, - "mode": "ocr", - "supported_endpoints": [ - "/v1/ocr" - ], - "source": "https://devblogs.microsoft.com/foundry/whats-new-in-azure-ai-foundry-august-2025/#mistral-document-ai-(ocr)-%E2%80%94-serverless-in-foundry" - }, "azure_ai/mistral-document-ai-2512": { "litellm_provider": "azure_ai", "ocr_cost_per_page": 0.003, @@ -11628,17 +10970,6 @@ "mode": "rerank", "output_cost_per_token": 0.0 }, - "azure_ai/cohere-rerank-v3.5": { - "deprecation_date": "2026-05-14", - "input_cost_per_query": 0.002, - "input_cost_per_token": 0.0, - "litellm_provider": "azure_ai", - "max_input_tokens": 4096, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "rerank", - 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"https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supports_function_calling": true, - "supports_response_schema": false, - "supports_tool_choice": true, - "supports_web_search": true - }, - "azure_ai/grok-3-mini": { - "deprecation_date": "2026-05-01", - "input_cost_per_token": 2.5e-07, - "litellm_provider": "azure_ai", - "max_input_tokens": 131072, - "max_output_tokens": 131072, - "max_tokens": 131072, - "mode": "chat", - "output_cost_per_token": 1.27e-06, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supports_function_calling": true, - "supports_reasoning": true, - "supports_response_schema": false, - "supports_tool_choice": true, - "supports_web_search": true - }, "azure_ai/grok-4": { "input_cost_per_token": 3e-06, "litellm_provider": "azure_ai", @@ -11963,36 +11192,6 @@ "supports_vision": true, "supports_web_search": true }, - "azure_ai/grok-4-fast-non-reasoning": { - "deprecation_date": "2026-05-01", - "input_cost_per_token": 2e-07, - "output_cost_per_token": 5e-07, - "litellm_provider": "azure_ai", - "max_input_tokens": 131072, - "max_output_tokens": 131072, - "max_tokens": 131072, - "mode": "chat", - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_web_search": true - }, - "azure_ai/grok-4-fast-reasoning": { - "deprecation_date": "2026-05-01", - "input_cost_per_token": 2e-07, - "output_cost_per_token": 5e-07, - "litellm_provider": "azure_ai", - "max_input_tokens": 131072, - "max_output_tokens": 131072, - "max_tokens": 131072, - "mode": "chat", - "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_response_schema": true, - "supports_tool_choice": true, - "supports_web_search": true - }, "azure_ai/grok-4-1-fast-non-reasoning": { "input_cost_per_token": 2e-07, "output_cost_per_token": 5e-07, @@ -13516,40 +12715,6 @@ "mode": "chat", "output_cost_per_token": 1.5e-06 }, - "bedrock/us-gov-east-1/anthropic.claude-3-5-sonnet-20240620-v1:0": { - "deprecation_date": "2026-07-30", - "input_cost_per_token": 3.6e-06, - "litellm_provider": "bedrock", - "max_input_tokens": 200000, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 1.8e-05, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "cache_read_input_token_cost": 3.6e-07, - "cache_creation_input_token_cost": 4.5e-06 - }, - "bedrock/us-gov-east-1/anthropic.claude-3-haiku-20240307-v1:0": { - "deprecation_date": "2026-09-10", - "input_cost_per_token": 3e-07, - "litellm_provider": "bedrock", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.5e-06, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "cache_read_input_token_cost": 3e-08, - "cache_creation_input_token_cost": 3.75e-07 - }, "bedrock/us-gov-east-1/anthropic.claude-sonnet-4-5-20250929-v1:0": { "cache_creation_input_token_cost": 4.5e-06, "cache_creation_input_token_cost_above_1hr": 7.2e-06, @@ -13727,61 +12892,6 @@ "mode": "chat", "output_cost_per_token": 1.5e-06 }, - "bedrock/us-gov-west-1/anthropic.claude-3-7-sonnet-20250219-v1:0": { - "cache_creation_input_token_cost": 4.5e-06, - "cache_read_input_token_cost": 3.6e-07, - "deprecation_date": "2026-07-30", - "input_cost_per_token": 3.6e-06, - "litellm_provider": "bedrock", - "max_input_tokens": 200000, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 1.8e-05, - "supports_assistant_prefill": true, - "supports_computer_use": true, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "bedrock/us-gov-west-1/anthropic.claude-3-5-sonnet-20240620-v1:0": { - "deprecation_date": "2026-07-30", - "input_cost_per_token": 3.6e-06, - "litellm_provider": "bedrock", - "max_input_tokens": 200000, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 1.8e-05, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "cache_read_input_token_cost": 3.6e-07, - "cache_creation_input_token_cost": 4.5e-06 - }, - "bedrock/us-gov-west-1/anthropic.claude-3-haiku-20240307-v1:0": { - "deprecation_date": "2026-09-10", - "input_cost_per_token": 3e-07, - "litellm_provider": "bedrock", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.5e-06, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "cache_read_input_token_cost": 3e-08, - "cache_creation_input_token_cost": 3.75e-07 - }, "bedrock/us-gov-west-1/anthropic.claude-sonnet-4-5-20250929-v1:0": { "cache_creation_input_token_cost": 4.5e-06, "cache_creation_input_token_cost_above_1hr": 7.2e-06, @@ -14219,34 +13329,6 @@ "supports_reasoning": true, "supports_tool_choice": true }, - "cerebras/zai-glm-4.6": { - "deprecation_date": "2026-01-20", - "input_cost_per_token": 2.25e-06, - "litellm_provider": "cerebras", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 2.75e-06, - "source": "https://www.cerebras.ai/pricing", - "supports_function_calling": true, - "supports_reasoning": true, - "supports_tool_choice": true - }, - "cerebras/zai-glm-4.7": { - "deprecation_date": "2026-08-17", - "input_cost_per_token": 2.25e-06, - "litellm_provider": "cerebras", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 2.75e-06, - "source": "https://www.cerebras.ai/pricing", - "supports_function_calling": true, - "supports_reasoning": true, - "supports_tool_choice": true - }, "cerebras/qwen-3.8-27b": { "input_cost_per_token": 9.9e-07, "litellm_provider": "cerebras", @@ -14272,23 +13354,6 @@ "mode": "chat", "output_cost_per_token": 5e-07 }, - "chatgpt-4o-latest": { - "deprecation_date": "2026-02-17", - "input_cost_per_token": 5e-06, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.5e-05, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, "gpt-4o-transcribe-diarize": { "input_cost_per_audio_token": 2.5e-06, "input_cost_per_token": 2.5e-06, @@ -14351,131 +13416,6 @@ "prompt_cache_min_tokens": 4096, "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, - "claude-3-7-sonnet-20250219": { - "cache_creation_input_token_cost": 3.75e-06, - "cache_creation_input_token_cost_above_1hr": 6e-06, - "cache_read_input_token_cost": 3e-07, - "deprecation_date": "2026-02-19", - "input_cost_per_token": 3e-06, - "litellm_provider": "anthropic", - "max_input_tokens": 200000, - "max_output_tokens": 64000, - "max_tokens": 64000, - "mode": "chat", - "output_cost_per_token": 1.5e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supports_assistant_prefill": true, - "supports_computer_use": true, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": true - }, - "claude-3-haiku-20240307": { - "cache_creation_input_token_cost": 3e-07, - "cache_creation_input_token_cost_above_1hr": 5e-07, - "cache_read_input_token_cost": 3e-08, - "deprecation_date": "2026-04-20", - "input_cost_per_token": 2.5e-07, - "litellm_provider": "anthropic", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.25e-06, - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "claude-3-opus-20240229": { - "cache_creation_input_token_cost": 1.875e-05, - "cache_creation_input_token_cost_above_1hr": 3e-05, - "cache_read_input_token_cost": 1.5e-06, - "deprecation_date": "2026-01-05", - "input_cost_per_token": 1.5e-05, - "litellm_provider": "anthropic", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 7.5e-05, - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "claude-4-opus-20250514": { - "cache_creation_input_token_cost": 1.875e-05, - "cache_read_input_token_cost": 1.5e-06, - "deprecation_date": "2026-06-15", - "input_cost_per_token": 1.5e-05, - "litellm_provider": "anthropic", - "max_input_tokens": 200000, - "max_output_tokens": 32000, - "max_tokens": 32000, - "mode": "chat", - "output_cost_per_token": 7.5e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supports_assistant_prefill": true, - "supports_computer_use": true, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "prompt_cache_min_tokens": 1024 - }, - "claude-4-sonnet-20250514": { - "cache_creation_input_token_cost": 3.75e-06, - "cache_creation_input_token_cost_above_200k_tokens": 7.5e-06, - "cache_read_input_token_cost": 3e-07, - "cache_read_input_token_cost_above_200k_tokens": 6e-07, - "deprecation_date": "2026-06-15", - "input_cost_per_token": 3e-06, - "input_cost_per_token_above_200k_tokens": 6e-06, - "litellm_provider": "anthropic", - "max_input_tokens": 1000000, - "max_output_tokens": 64000, - "max_tokens": 64000, - "mode": "chat", - "output_cost_per_token": 1.5e-05, - "output_cost_per_token_above_200k_tokens": 2.25e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supports_assistant_prefill": true, - "supports_computer_use": true, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": true, - "prompt_cache_min_tokens": 1024 - }, "claude-sonnet-4-5": { "cache_creation_input_token_cost": 3.75e-06, "cache_creation_input_token_cost_above_1hr": 6e-06, @@ -14654,92 +13594,6 @@ "input_cost_per_token_batches": 1.5e-06, "output_cost_per_token_batches": 7.5e-06 }, - "claude-opus-4-1": { - "cache_creation_input_token_cost": 1.875e-05, - "cache_creation_input_token_cost_above_1hr": 3e-05, - "cache_read_input_token_cost": 1.5e-06, - "input_cost_per_token": 1.5e-05, - "litellm_provider": "anthropic", - "max_input_tokens": 200000, - "max_output_tokens": 32000, - "max_tokens": 32000, - "mode": "chat", - "output_cost_per_token": 7.5e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supports_assistant_prefill": true, - "supports_computer_use": true, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_native_structured_output": true, - "supports_tool_choice": true, - "supports_vision": true, - "prompt_cache_min_tokens": 1024, - "deprecation_date": "2026-08-05" - }, - "claude-opus-4-1-20250805": { - "cache_creation_input_token_cost": 1.875e-05, - "cache_creation_input_token_cost_above_1hr": 3e-05, - "cache_read_input_token_cost": 1.5e-06, - "input_cost_per_token": 1.5e-05, - "deprecation_date": "2026-08-05", - "litellm_provider": "anthropic", - "max_input_tokens": 200000, - "max_output_tokens": 32000, - "max_tokens": 32000, - "mode": "chat", - "output_cost_per_token": 7.5e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supports_assistant_prefill": true, - "supports_computer_use": true, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_native_structured_output": true, - "supports_tool_choice": true, - "supports_vision": true, - "prompt_cache_min_tokens": 1024 - }, - "claude-opus-4-20250514": { - "cache_creation_input_token_cost": 1.875e-05, - "cache_creation_input_token_cost_above_1hr": 3e-05, - "cache_read_input_token_cost": 1.5e-06, - "input_cost_per_token": 1.5e-05, - "deprecation_date": "2026-06-15", - "litellm_provider": "anthropic", - "max_input_tokens": 200000, - "max_output_tokens": 32000, - "max_tokens": 32000, - "mode": "chat", - "output_cost_per_token": 7.5e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supports_assistant_prefill": true, - "supports_computer_use": true, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "prompt_cache_min_tokens": 1024 - }, "claude-opus-4-5-20251101": { "cache_creation_input_token_cost": 6.25e-06, "cache_creation_input_token_cost_above_1hr": 1e-05, @@ -15167,38 +14021,6 @@ "prompt_cache_min_tokens": 1024, "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, - "claude-sonnet-4-20250514": { - "deprecation_date": "2026-06-15", - "cache_creation_input_token_cost": 3.75e-06, - "cache_creation_input_token_cost_above_1hr": 6e-06, - "cache_read_input_token_cost": 3e-07, - "input_cost_per_token": 3e-06, - "input_cost_per_token_above_200k_tokens": 6e-06, - "output_cost_per_token_above_200k_tokens": 2.25e-05, - "cache_creation_input_token_cost_above_200k_tokens": 7.5e-06, - "cache_read_input_token_cost_above_200k_tokens": 6e-07, - "litellm_provider": "anthropic", - "max_input_tokens": 1000000, - "max_output_tokens": 64000, - "max_tokens": 64000, - "mode": "chat", - "output_cost_per_token": 1.5e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supports_assistant_prefill": true, - "supports_computer_use": true, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "prompt_cache_min_tokens": 1024 - }, "cloudflare/@cf/meta/llama-2-7b-chat-fp16": { "input_cost_per_token": 1.923e-06, "litellm_provider": "cloudflare", @@ -15551,36 +14373,6 @@ "supports_assistant_prefill": true, "supports_tool_choice": true }, - "codex-mini-latest": { - "cache_read_input_token_cost": 3.75e-07, - "deprecation_date": "2026-02-12", - "input_cost_per_token": 1.5e-06, - "litellm_provider": "openai", - "max_input_tokens": 200000, - "max_output_tokens": 100000, - "max_tokens": 100000, - "mode": "responses", - "output_cost_per_token": 6e-06, - "supported_endpoints": [ - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, "cohere.command-light-text-v14": { "input_cost_per_token": 3e-07, "litellm_provider": "bedrock", @@ -15680,16 +14472,6 @@ "mode": "rerank", "output_cost_per_token": 0.0 }, - "command": { - "input_cost_per_token": 1e-06, - "litellm_provider": "cohere", - "max_input_tokens": 4096, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "completion", - "output_cost_per_token": 2e-06, - "deprecation_date": "2025-09-15" - }, "command-a-03-2025": { "input_cost_per_token": 2.5e-06, "litellm_provider": "cohere_chat", @@ -15716,17 +14498,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "command-light": { - "input_cost_per_token": 3e-07, - "litellm_provider": "cohere_chat", - "max_input_tokens": 4096, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 6e-07, - "supports_tool_choice": true, - "deprecation_date": "2025-09-15" - }, "command-nightly": { "input_cost_per_token": 1e-06, "litellm_provider": "cohere", @@ -15736,18 +14507,6 @@ "mode": "completion", "output_cost_per_token": 2e-06 }, - "command-r": { - "input_cost_per_token": 1.5e-07, - "litellm_provider": "cohere_chat", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 6e-07, - "supports_function_calling": true, - "supports_tool_choice": true, - "deprecation_date": "2025-09-15" - }, "command-r-08-2024": { "input_cost_per_token": 1.5e-07, "litellm_provider": "cohere_chat", @@ -15759,18 +14518,6 @@ "supports_function_calling": true, "supports_tool_choice": true }, - "command-r-plus": { - "input_cost_per_token": 2.5e-06, - "litellm_provider": "cohere_chat", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1e-05, - "supports_function_calling": true, - "supports_tool_choice": true, - "deprecation_date": "2025-09-15" - }, "command-r-plus-08-2024": { "input_cost_per_token": 2.5e-06, "litellm_provider": "cohere_chat", @@ -15823,26 +14570,6 @@ "supports_vision": true, "source": "https://platform.openai.com/docs/models/computer-use-preview" }, - "dall-e-2": { - "deprecation_date": "2026-05-12", - "input_cost_per_image": 0.02, - "litellm_provider": "openai", - "mode": "image_generation", - "supported_endpoints": [ - "/v1/images/generations", - "/v1/images/edits", - "/v1/images/variations" - ] - }, - "dall-e-3": { - "deprecation_date": "2026-05-12", - "input_cost_per_image": 0.04, - "litellm_provider": "openai", - "mode": "image_generation", - "supported_endpoints": [ - "/v1/images/generations" - ] - }, "deepseek-chat": { "cache_read_input_token_cost": 2.8e-08, "input_cost_per_token": 2.8e-07, @@ -18839,30 +17566,6 @@ "output_vector_size": 1024, "source": "https://www.databricks.com/product/pricing/foundation-model-serving" }, - "databricks/databricks-claude-3-7-sonnet": { - "cache_creation_input_token_cost": 3.74997e-06, - "cache_read_input_token_cost": 3.0002e-07, - "deprecation_date": "2026-04-12", - "input_cost_per_token": 2.9999900000000002e-06, - "input_dbu_cost_per_token": 4.2857e-05, - "litellm_provider": "databricks", - "max_input_tokens": 200000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 1.5000020000000002e-05, - "output_dbu_cost_per_token": 0.000214286, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_anthropic_thinking_payload": true, - "supports_tool_choice": true - }, "databricks/databricks-claude-fable-5": { "cache_creation_input_token_cost": 1.250004e-05, "cache_read_input_token_cost": 1.00002e-06, @@ -19825,44 +18528,6 @@ "supports_prompt_caching": true, "supports_tool_choice": true }, - "databricks/databricks-gpt-5-1-codex-max": { - "cache_creation_input_token_cost": 1.24999e-06, - "cache_read_input_token_cost": 1.2502e-07, - "deprecation_date": "2026-07-16", - "input_cost_per_token": 1.24999e-06, - "input_dbu_cost_per_token": 1.7857e-05, - "litellm_provider": "databricks", - "max_input_tokens": 272000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 9.999990000000002e-06, - "output_dbu_cost_per_token": 0.000142857, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supports_prompt_caching": true - }, - "databricks/databricks-gpt-5-1-codex-mini": { - "cache_creation_input_token_cost": 2.4997e-07, - "cache_read_input_token_cost": 2.499e-08, - "deprecation_date": "2026-07-16", - "input_cost_per_token": 2.4997e-07, - "input_dbu_cost_per_token": 3.571e-06, - "litellm_provider": "databricks", - "max_input_tokens": 272000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 1.99997e-06, - "output_dbu_cost_per_token": 2.8571e-05, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supports_prompt_caching": true - }, "databricks/databricks-gpt-5-2": { "cache_creation_input_token_cost": 1.75e-06, "cache_read_input_token_cost": 1.75e-07, @@ -19883,25 +18548,6 @@ "supports_prompt_caching": true, "supports_tool_choice": true }, - "databricks/databricks-gpt-5-2-codex": { - "cache_creation_input_token_cost": 1.75e-06, - "cache_read_input_token_cost": 1.75e-07, - "deprecation_date": "2026-07-16", - "input_cost_per_token": 1.75e-06, - "input_dbu_cost_per_token": 2.5e-05, - "litellm_provider": "databricks", - "max_input_tokens": 272000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 1.4e-05, - "output_dbu_cost_per_token": 0.0002, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supports_prompt_caching": true - }, "databricks/databricks-gpt-5-3-codex": { "cache_creation_input_token_cost": 1.75e-06, "cache_read_input_token_cost": 1.75e-07, @@ -20328,25 +18974,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "databricks/databricks-llama-2-70b-chat": { - "cache_creation_input_token_cost": 5.0001e-07, - "cache_read_input_token_cost": 5.0001e-07, - "deprecation_date": "2024-10-30", - "input_cost_per_token": 5.0001e-07, - "input_dbu_cost_per_token": 7.143e-06, - "litellm_provider": "databricks", - "max_input_tokens": 4096, - "max_output_tokens": 4096, - "max_tokens": 4096, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 1.5000300000000002e-06, - "output_dbu_cost_per_token": 2.1429e-05, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving", - "supports_tool_choice": true - }, "databricks/databricks-llama-4-maverick": { "cache_creation_input_token_cost": 5.0001e-07, "cache_read_input_token_cost": 5.0001e-07, @@ -20365,25 +18992,6 @@ "source": "https://www.databricks.com/product/pricing/foundation-model-serving", "supports_tool_choice": true }, - "databricks/databricks-meta-llama-3-1-405b-instruct": { - "cache_creation_input_token_cost": 5.00003e-06, - "cache_read_input_token_cost": 5.00003e-06, - "deprecation_date": "2026-02-15", - "input_cost_per_token": 5.00003e-06, - "input_dbu_cost_per_token": 7.1429e-05, - "litellm_provider": "databricks", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 1.5000020000000002e-05, - "output_dbu_cost_per_token": 0.000214286, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving", - "supports_tool_choice": true - }, "databricks/databricks-meta-llama-3-1-8b-instruct": { "cache_creation_input_token_cost": 1.5001e-07, "cache_read_input_token_cost": 1.5001e-07, @@ -20419,82 +19027,6 @@ "source": "https://www.databricks.com/product/pricing/foundation-model-serving", "supports_tool_choice": true }, - "databricks/databricks-meta-llama-3-70b-instruct": { - "cache_creation_input_token_cost": 1.00002e-06, - "cache_read_input_token_cost": 1.00002e-06, - "deprecation_date": "2024-07-23", - "input_cost_per_token": 1.00002e-06, - "input_dbu_cost_per_token": 1.4286e-05, - "litellm_provider": "databricks", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 2.9999900000000002e-06, - "output_dbu_cost_per_token": 4.2857e-05, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving", - "supports_tool_choice": true - }, - "databricks/databricks-mixtral-8x7b-instruct": { - "cache_creation_input_token_cost": 5.0001e-07, - "cache_read_input_token_cost": 5.0001e-07, - "deprecation_date": "2025-04-30", - "input_cost_per_token": 5.0001e-07, - "input_dbu_cost_per_token": 7.143e-06, - "litellm_provider": "databricks", - "max_input_tokens": 4096, - "max_output_tokens": 4096, - "max_tokens": 4096, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 1.00002e-06, - "output_dbu_cost_per_token": 1.4286e-05, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving", - "supports_tool_choice": true - }, - "databricks/databricks-mpt-30b-instruct": { - "cache_creation_input_token_cost": 1.00002e-06, - "cache_read_input_token_cost": 1.00002e-06, - "deprecation_date": "2024-08-30", - "input_cost_per_token": 1.00002e-06, - "input_dbu_cost_per_token": 1.4286e-05, - "litellm_provider": "databricks", - "max_input_tokens": 8192, - "max_output_tokens": 8192, - "max_tokens": 8192, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 1.00002e-06, - "output_dbu_cost_per_token": 1.4286e-05, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving", - "supports_tool_choice": true - }, - "databricks/databricks-mpt-7b-instruct": { - "cache_creation_input_token_cost": 5.0001e-07, - "cache_read_input_token_cost": 5.0001e-07, - "deprecation_date": "2024-08-30", - "input_cost_per_token": 5.0001e-07, - "input_dbu_cost_per_token": 7.143e-06, - "litellm_provider": "databricks", - "max_input_tokens": 8192, - "max_output_tokens": 8192, - "max_tokens": 8192, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 0.0, - "output_dbu_cost_per_token": 0.0, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving", - "supports_tool_choice": true - }, "databricks/databricks-qwen35-122b-a10b": { "cache_creation_input_token_cost": 2.2001e-07, "cache_read_input_token_cost": 2.2001e-07, @@ -21559,18 +20091,6 @@ "supports_tool_choice": true, "supports_function_calling": true }, - "deepinfra/google/gemini-2.0-flash-001": { - "deprecation_date": "2026-06-01", - "max_tokens": 1000000, - "max_input_tokens": 1000000, - "max_output_tokens": 1000000, - "input_cost_per_token": 1e-07, - "output_cost_per_token": 4e-07, - "litellm_provider": "deepinfra", - "mode": "chat", - "supports_tool_choice": true, - "supports_function_calling": true - }, "deepinfra/google/gemini-2.5-flash": { "max_tokens": 1000000, "max_input_tokens": 1000000, @@ -22429,15 +20949,6 @@ "/v1/audio/speech" ] }, - "embed-english-light-v2.0": { - "deprecation_date": "2026-04-04", - "input_cost_per_token": 1e-07, - "litellm_provider": "cohere", - "max_input_tokens": 1024, - "max_tokens": 1024, - "mode": "embedding", - "output_cost_per_token": 0.0 - }, "embed-english-light-v3.0": { "input_cost_per_token": 1e-07, "litellm_provider": "cohere", @@ -22446,15 +20957,6 @@ "mode": "embedding", "output_cost_per_token": 0.0 }, - "embed-english-v2.0": { - "deprecation_date": "2026-04-04", - "input_cost_per_token": 1e-07, - "litellm_provider": "cohere", - "max_input_tokens": 4096, - "max_tokens": 4096, - "mode": "embedding", - "output_cost_per_token": 0.0 - }, "embed-english-v3.0": { "input_cost_per_image": 0.0001, "input_cost_per_token": 1e-07, @@ -22469,15 +20971,6 @@ "supports_embedding_image_input": true, "supports_image_input": true }, - "embed-multilingual-v2.0": { - "deprecation_date": "2026-04-04", - "input_cost_per_token": 1e-07, - "litellm_provider": "cohere", - "max_input_tokens": 768, - "max_tokens": 768, - "mode": "embedding", - "output_cost_per_token": 0.0 - }, "embed-multilingual-v3.0": { "input_cost_per_token": 1e-07, "litellm_provider": "cohere", @@ -22645,23 +21138,6 @@ "cache_read_input_token_cost": 3e-07, "cache_creation_input_token_cost": 3.75e-06 }, - "eu.anthropic.claude-3-haiku-20240307-v1:0": { - "deprecation_date": "2026-09-10", - "input_cost_per_token": 2.5e-07, - "litellm_provider": "bedrock", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.25e-06, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "cache_read_input_token_cost": 2.5e-08, - "cache_creation_input_token_cost": 3.125e-07 - }, "eu.anthropic.claude-3-opus-20240229-v1:0": { "input_cost_per_token": 1.5e-05, "litellm_provider": "bedrock", @@ -22677,23 +21153,6 @@ "cache_read_input_token_cost": 1.5e-06, "cache_creation_input_token_cost": 1.875e-05 }, - "eu.anthropic.claude-3-sonnet-20240229-v1:0": { - "deprecation_date": "2026-07-30", - "input_cost_per_token": 3e-06, - "litellm_provider": "bedrock", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.5e-05, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "cache_read_input_token_cost": 3e-07, - "cache_creation_input_token_cost": 3.75e-06 - }, "eu.anthropic.claude-opus-4-1-20250805-v1:0": { "cache_creation_input_token_cost": 1.875e-05, "cache_read_input_token_cost": 1.5e-06, @@ -25265,26 +23724,6 @@ "supports_tool_choice": true, "supports_vision": false }, - "fireworks_ai/accounts/fireworks/models/deepseek-v4-pro": { - "cache_read_input_token_cost": 6e-07, - "cache_read_input_token_cost_priority": 6e-07, - "deprecation_date": "2026-08-27", - "input_cost_per_token": 1.2e-06, - "input_cost_per_token_priority": 1.2e-06, - "litellm_provider": "fireworks_ai", - "max_input_tokens": 1048576, - "max_output_tokens": 384000, - "max_tokens": 384000, - "mode": "chat", - "output_cost_per_token": 1.2e-06, - "output_cost_per_token_priority": 1.2e-06, - "source": "https://api.fireworks.ai/v1/serverless/models", - "supports_function_calling": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": false - }, "fireworks_ai/accounts/fireworks/models/deepseek-v4-pro-0813": { "cache_read_input_token_cost": 4.4e-08, "cache_read_input_token_cost_priority": 5.5e-08, @@ -25672,26 +24111,6 @@ "supports_response_schema": true, "supports_tool_choice": true }, - "fireworks_ai/accounts/fireworks/models/minimax-m2p7": { - "cache_read_input_token_cost": 6e-08, - "cache_read_input_token_cost_priority": 6e-07, - "deprecation_date": "2026-08-27", - "input_cost_per_token": 3e-07, - "input_cost_per_token_priority": 1.2e-06, - "litellm_provider": "fireworks_ai", - "max_input_tokens": 196608, - "max_output_tokens": 196608, - "max_tokens": 196608, - "mode": "chat", - "output_cost_per_token": 1.2e-06, - "output_cost_per_token_priority": 1.2e-06, - "source": "https://api.fireworks.ai/v1/serverless/models", - "supports_function_calling": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": false - }, "fireworks_ai/accounts/fireworks/models/minimax-m3": { "cache_read_input_token_cost": 6e-08, "cache_read_input_token_cost_priority": 9e-08, @@ -25779,26 +24198,6 @@ "supports_tool_choice": true, "supports_vision": false }, - "fireworks_ai/deepseek-v4-pro": { - "cache_read_input_token_cost": 6e-07, - "cache_read_input_token_cost_priority": 6e-07, - "deprecation_date": "2026-08-27", - "input_cost_per_token": 1.2e-06, - "input_cost_per_token_priority": 1.2e-06, - "litellm_provider": "fireworks_ai", - "max_input_tokens": 1048576, - "max_output_tokens": 384000, - "max_tokens": 384000, - "mode": "chat", - "output_cost_per_token": 1.2e-06, - "output_cost_per_token_priority": 1.2e-06, - "source": "https://api.fireworks.ai/v1/serverless/models", - "supports_function_calling": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": false - }, "fireworks_ai/glm-4p7": { "cache_read_input_token_cost": 3e-07, "input_cost_per_token": 6e-07, @@ -25998,26 +24397,6 @@ "supports_response_schema": true, "supports_tool_choice": true }, - "fireworks_ai/minimax-m2p7": { - "cache_read_input_token_cost": 6e-08, - "cache_read_input_token_cost_priority": 6e-07, - "deprecation_date": "2026-08-27", - "input_cost_per_token": 3e-07, - "input_cost_per_token_priority": 1.2e-06, - "litellm_provider": "fireworks_ai", - "max_input_tokens": 196608, - "max_output_tokens": 196608, - "max_tokens": 196608, - "mode": "chat", - "output_cost_per_token": 1.2e-06, - "output_cost_per_token_priority": 1.2e-06, - "source": "https://api.fireworks.ai/v1/serverless/models", - "supports_function_calling": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": false - }, "fireworks_ai/minimax-m3": { "cache_read_input_token_cost": 6e-08, "cache_read_input_token_cost_priority": 9e-08, @@ -26195,31 +24574,6 @@ "comment": "Open flagship GLM for long-horizon coding agents and million-token context work", "source": "https://api.friendli.ai/serverless/v1/models" }, - "friendliai/LGAI-EXAONE/K-EXAONE-2.0-750B-A37B": { - "litellm_provider": "friendliai", - "max_input_tokens": 262144, - "max_output_tokens": 262144, - "max_tokens": 262144, - "input_cost_per_token": 6e-07, - "output_cost_per_token": 2.4e-06, - "cache_read_input_token_cost": 1.2e-07, - "supports_prompt_caching": true, - "supports_reasoning": true, - "reasoning_effort_levels": [], - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_response_schema": true, - "supports_native_structured_output": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": false, - "supports_image_input": false, - "supports_video_input": false, - "mode": "chat", - "comment": "Frontier-scale multilingual language model developed by LG AI Research", - "deprecation_date": "2026-09-06", - "source": "https://api.friendli.ai/serverless/v1/models" - }, "friendliai/deepseek-ai/DeepSeek-V3.2": { "litellm_provider": "friendliai", "max_input_tokens": 163840, @@ -26525,160 +24879,6 @@ "supports_response_schema": true, "supports_tool_choice": true }, - "gemini-2.0-flash": { - "cache_read_input_token_cost": 2.5e-08, - "deprecation_date": "2026-06-01", - "input_cost_per_audio_token": 1e-06, - "input_cost_per_audio_token_batches": 5e-07, - "input_cost_per_character": 3.75e-08, - "input_cost_per_token": 1.5e-07, - "input_cost_per_token_batches": 7.5e-08, - "litellm_provider": "vertex_ai-language-models", - "max_input_tokens": 1048576, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 6e-07, - "output_cost_per_token_batches": 3e-07, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", - "supported_modalities": [ - "text", - "image", - "audio", - "video" - ], - "supported_output_modalities": [ - "text", - "image" - ], - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_url_context": true, - "supports_vision": true, - "supports_web_search": true, - "search_context_cost_per_query": { - "search_context_size_low": 0.035, - "search_context_size_medium": 0.035, - "search_context_size_high": 0.035 - } - }, - "gemini-2.0-flash-001": { - "cache_read_input_token_cost": 3.75e-08, - "deprecation_date": "2026-06-01", - "input_cost_per_audio_token": 1e-06, - "input_cost_per_token": 1.5e-07, - "litellm_provider": "vertex_ai-language-models", - "max_input_tokens": 1048576, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 6e-07, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", - "supported_modalities": [ - "text", - "image", - "audio", - "video" - ], - "supported_output_modalities": [ - "text", - "image" - ], - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": true, - "search_context_cost_per_query": { - "search_context_size_low": 0.035, - "search_context_size_medium": 0.035, - "search_context_size_high": 0.035 - } - }, - "gemini-2.0-flash-lite": { - "cache_read_input_token_cost": 1.875e-08, - "deprecation_date": "2026-06-01", - "input_cost_per_audio_token": 7.5e-08, - "input_cost_per_audio_token_batches": 3.75e-08, - "input_cost_per_character": 1.875e-08, - "input_cost_per_token": 7.5e-08, - "input_cost_per_token_batches": 3.75e-08, - "litellm_provider": "vertex_ai-language-models", - "max_input_tokens": 1048576, - "max_output_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 3e-07, - "output_cost_per_token_batches": 1.5e-07, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", - "supported_modalities": [ - "text", - "image", - "audio", - "video" - ], - "supported_output_modalities": [ - "text" - ], - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": true, - "search_context_cost_per_query": { - "search_context_size_low": 0.035, - "search_context_size_medium": 0.035, - "search_context_size_high": 0.035 - } - }, - "gemini-2.0-flash-lite-001": { - "cache_read_input_token_cost": 1.875e-08, - "deprecation_date": "2026-06-01", - "input_cost_per_audio_token": 7.5e-08, - "input_cost_per_token": 7.5e-08, - "litellm_provider": "vertex_ai-language-models", - "max_input_tokens": 1048576, - "max_output_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 3e-07, - "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#gemini-2.0-flash", - "supported_modalities": [ - "text", - "image", - "audio", - "video" - ], - "supported_output_modalities": [ - "text" - ], - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": true, - "search_context_cost_per_query": { - "search_context_size_low": 0.035, - "search_context_size_medium": 0.035, - "search_context_size_high": 0.035 - } - }, "gemini-2.5-flash": { "cache_read_input_audio_token_cost": 1e-07, "deprecation_date": "2026-10-20", @@ -27503,53 +25703,6 @@ }, "gemini_native_audio": true }, - "gemini-2.5-flash-lite-preview-06-17": { - "deprecation_date": "2025-11-18", - "cache_read_input_token_cost": 1e-08, - "input_cost_per_audio_token": 5e-07, - "input_cost_per_token": 1e-07, - "litellm_provider": "vertex_ai-language-models", - "max_input_tokens": 1048576, - "max_output_tokens": 65535, - "max_tokens": 65535, - "mode": "chat", - "output_cost_per_reasoning_token": 4e-07, - "output_cost_per_token": 4e-07, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/completions", - "/v1/batch" - ], - "supported_modalities": [ - "text", - "image", - "audio", - "video" - ], - "supported_output_modalities": [ - "text" - ], - "supports_audio_output": false, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - 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"supports_url_context": true, - "supports_video_input": true, - "supports_vision": true, - "supports_web_search": true, - "supports_native_streaming": true, - "tpm": 250000, - "search_context_cost_per_query": { - "search_context_size_low": 0.014, - "search_context_size_medium": 0.014, - "search_context_size_high": 0.014 - }, - "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 - }, "gemini/gemini-3.1-flash-lite": { "cache_read_input_audio_token_cost": 5e-08, "cache_read_input_token_cost": 2.5e-08, @@ -30826,34 +28339,6 @@ "output_cost_per_image": 0.04, "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing" }, - "gemini/imagen-3.0-generate-002": { - "deprecation_date": "2025-11-10", - "litellm_provider": "gemini", - "mode": "image_generation", - "output_cost_per_image": 0.04, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing" - }, - "gemini/imagen-4.0-fast-generate-001": { - "deprecation_date": "2026-08-17", - "litellm_provider": "gemini", - "mode": "image_generation", - "output_cost_per_image": 0.02, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing" - }, - "gemini/imagen-4.0-generate-001": { - "deprecation_date": "2026-08-17", - "litellm_provider": "gemini", - "mode": "image_generation", - "output_cost_per_image": 0.04, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing" - }, - "gemini/imagen-4.0-ultra-generate-001": { - "deprecation_date": "2026-08-17", - "litellm_provider": "gemini", - "mode": "image_generation", - "output_cost_per_image": 0.06, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing" - }, "gemini/learnlm-1.5-pro-experimental": { "input_cost_per_audio_per_second": 0, "input_cost_per_audio_per_second_above_128k_tokens": 0, @@ -30932,21 +28417,6 @@ "supports_web_search": false, "output_cost_per_image": 0.08 }, - "gemini/veo-2.0-generate-001": { - "deprecation_date": "2026-06-30", - "litellm_provider": "gemini", - "max_input_tokens": 1024, - "max_tokens": 1024, - "mode": "video_generation", - "output_cost_per_second": 0.35, - "source": "https://ai.google.dev/gemini-api/docs/video", - "supported_modalities": [ - "text" - ], - "supported_output_modalities": [ - "video" - ] - }, "gemini/veo-3.1-fast-generate-preview": { "litellm_provider": "gemini", "max_input_tokens": 1024, @@ -32156,33 +29626,6 @@ "supports_system_messages": true, "supports_tool_choice": true }, - "gpt-4-0125-preview": { - "deprecation_date": "2026-03-26", - "input_cost_per_token": 1e-05, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 3e-05, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_prompt_caching": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, - "gpt-4-0314": { - "deprecation_date": "2026-03-26", - "input_cost_per_token": 3e-05, - "litellm_provider": "openai", - "max_input_tokens": 8192, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 6e-05, - "supports_system_messages": true, - "supports_tool_choice": true - }, "gpt-4-0613": { "deprecation_date": "2026-10-23", "input_cost_per_token": 3e-05, @@ -32252,22 +29695,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "gpt-4-turbo-preview": { - "deprecation_date": "2026-03-26", - "input_cost_per_token": 1e-05, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 3e-05, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, "gpt-4.1": { "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_priority": 8.75e-07, @@ -32610,24 +30037,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "gpt-4o-audio-preview": { - "deprecation_date": "2026-05-07", - "input_cost_per_audio_token": 4e-05, - "input_cost_per_token": 2.5e-06, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_audio_token": 8e-05, - "output_cost_per_token": 1e-05, - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, "gpt-4o-audio-preview-2024-12-17": { "deprecation_date": "2027-01-20", "input_cost_per_audio_token": 4e-05, @@ -32812,44 +30221,6 @@ "supports_tool_choice": true, "supports_vision": false }, - "gpt-audio-mini-2025-10-06": { - "deprecation_date": "2026-07-23", - "input_cost_per_audio_token": 1e-05, - "input_cost_per_token": 6e-07, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_audio_token": 2e-05, - "output_cost_per_token": 2.4e-06, - "source": "https://developers.openai.com/api/docs/pricing", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/responses", - "/v1/realtime", - "/v1/batch" - ], - "supported_modalities": [ - "text", - "audio" - ], - "supported_output_modalities": [ - "text", - "audio" - ], - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_prompt_caching": false, - "supports_reasoning": false, - "supports_response_schema": false, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": false - }, "gpt-audio-mini-2025-12-15": { "input_cost_per_audio_token": 1e-05, "input_cost_per_token": 6e-07, @@ -32946,24 +30317,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "gpt-4o-mini-audio-preview": { - "deprecation_date": "2026-05-07", - "input_cost_per_audio_token": 1e-05, - "input_cost_per_token": 1.5e-07, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_audio_token": 2e-05, - "output_cost_per_token": 6e-07, - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, "gpt-4o-mini-audio-preview-2024-12-17": { "deprecation_date": "2027-01-20", "input_cost_per_audio_token": 1e-05, @@ -32982,26 +30335,6 @@ "supports_system_messages": true, "supports_tool_choice": true }, - "gpt-4o-mini-realtime-preview": { - "cache_creation_input_audio_token_cost": 3e-07, - "cache_read_input_token_cost": 3e-07, - "deprecation_date": "2026-05-07", - "input_cost_per_audio_token": 1e-05, - "input_cost_per_token": 6e-07, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "realtime", - "output_cost_per_audio_token": 2e-05, - "output_cost_per_token": 2.4e-06, - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, "gpt-4o-mini-realtime-preview-2024-12-17": { "cache_creation_input_audio_token_cost": 3e-07, "cache_read_input_token_cost": 3e-07, @@ -33048,32 +30381,6 @@ "supports_vision": true, "supports_web_search": true }, - "gpt-4o-mini-search-preview-2025-03-11": { - "cache_read_input_token_cost": 7.5e-08, - "deprecation_date": "2026-07-23", - "input_cost_per_token": 1.5e-07, - "input_cost_per_token_batches": 7.5e-08, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 6e-07, - "output_cost_per_token_batches": 3e-07, - "search_context_cost_per_query": { - "search_context_size_high": 0.025, - "search_context_size_low": 0.025, - "search_context_size_medium": 0.025 - }, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, "gpt-4o-mini-transcribe": { "input_cost_per_audio_token": 1.25e-06, "input_cost_per_token": 1.25e-06, @@ -33108,63 +30415,6 @@ "audio" ] }, - "gpt-4o-realtime-preview": { - "cache_read_input_token_cost": 2.5e-06, - "deprecation_date": "2026-05-07", - "input_cost_per_audio_token": 4e-05, - "input_cost_per_token": 5e-06, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "realtime", - "output_cost_per_audio_token": 8e-05, - "output_cost_per_token": 2e-05, - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, - "gpt-4o-realtime-preview-2024-12-17": { - "cache_read_input_token_cost": 2.5e-06, - "deprecation_date": "2026-05-07", - "input_cost_per_audio_token": 4e-05, - "input_cost_per_token": 5e-06, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "realtime", - "output_cost_per_audio_token": 8e-05, - "output_cost_per_token": 2e-05, - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, - "gpt-4o-realtime-preview-2025-06-03": { - "cache_read_input_token_cost": 2.5e-06, - "deprecation_date": "2026-05-07", - "input_cost_per_audio_token": 4e-05, - "input_cost_per_token": 5e-06, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "realtime", - "output_cost_per_audio_token": 8e-05, - "output_cost_per_token": 2e-05, - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, "gpt-4o-search-preview": { "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 2.5e-06, @@ -33191,32 +30441,6 @@ "supports_vision": true, "supports_web_search": true }, - "gpt-4o-search-preview-2025-03-11": { - "cache_read_input_token_cost": 1.25e-06, - "deprecation_date": "2026-07-23", - "input_cost_per_token": 2.5e-06, - "input_cost_per_token_batches": 1.25e-06, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 1e-05, - "output_cost_per_token_batches": 5e-06, - "search_context_cost_per_query": { - "search_context_size_high": 0.025, - "search_context_size_low": 0.025, - "search_context_size_medium": 0.025 - }, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, "gpt-4o-transcribe": { "input_cost_per_audio_token": 2.5e-06, "input_cost_per_token": 2.5e-06, @@ -33879,52 +31103,6 @@ "supports_xhigh_reasoning_effort": false, "supports_minimal_reasoning_effort": false }, - "gpt-5.1-chat-latest": { - "cache_read_input_token_cost": 1.25e-07, - "cache_read_input_token_cost_priority": 2.5e-07, - "deprecation_date": "2026-07-23", - "input_cost_per_token": 1.25e-06, - "input_cost_per_token_priority": 2.5e-06, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 1e-05, - "output_cost_per_token_priority": 2e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text", - "image" - ], - "supports_function_calling": false, - "supports_native_streaming": true, - "supports_parallel_function_calling": false, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": false, - "supports_vision": true, - "supports_web_search": true, - "supports_none_reasoning_effort": true, - "default_reasoning_effort": "none", - "supports_xhigh_reasoning_effort": false, - "supports_minimal_reasoning_effort": true - }, "gpt-5.2": { "cache_read_input_token_cost": 1.75e-07, "cache_read_input_token_cost_batches": 8.75e-08, @@ -34031,94 +31209,6 @@ "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false }, - "gpt-5.2-chat-latest": { - "cache_read_input_token_cost": 1.75e-07, - "cache_read_input_token_cost_priority": 3.5e-07, - "deprecation_date": "2026-08-10", - "input_cost_per_token": 1.75e-06, - "input_cost_per_token_priority": 3.5e-06, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 1.4e-05, - "output_cost_per_token_priority": 2.8e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": true, - "supports_none_reasoning_effort": false, - "supports_xhigh_reasoning_effort": false, - "supports_minimal_reasoning_effort": true - }, - "gpt-5.3-chat-latest": { - "cache_read_input_token_cost": 1.75e-07, - "cache_read_input_token_cost_priority": 3.5e-07, - "deprecation_date": "2026-08-10", - "input_cost_per_token": 1.75e-06, - "input_cost_per_token_priority": 3.5e-06, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 1.4e-05, - "output_cost_per_token_priority": 2.8e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": true, - "supports_none_reasoning_effort": false, - "supports_xhigh_reasoning_effort": false, - "supports_minimal_reasoning_effort": true - }, "gpt-5.2-pro": { "input_cost_per_token": 2.1e-05, "input_cost_per_token_batches": 1.05e-05, @@ -35783,251 +32873,6 @@ "supports_xhigh_reasoning_effort": false, "supports_minimal_reasoning_effort": true }, - "gpt-5-chat-latest": { - "cache_read_input_token_cost": 1.25e-07, - "deprecation_date": "2026-07-23", - "input_cost_per_token": 1.25e-06, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - 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"max_tokens": 131072, - "mode": "chat", - "output_cost_per_token": 8e-08, - "supports_function_calling": true, - "supports_response_schema": false, - "supports_tool_choice": true - }, - "groq/llama-3.3-70b-versatile": { - "deprecation_date": "2026-08-16", - "input_cost_per_token": 5.9e-07, - "litellm_provider": "groq", - "max_input_tokens": 131072, - "max_output_tokens": 32768, - "max_tokens": 32768, - "mode": "chat", - "output_cost_per_token": 7.9e-07, - "supports_function_calling": true, - "supports_response_schema": false, - "supports_tool_choice": true - }, "groq/llama-guard-3-8b": { "input_cost_per_token": 2e-07, "litellm_provider": "groq", @@ -36905,19 +33724,6 @@ "output_cost_per_token": 2e-07, "source": "https://console.groq.com/docs/model/llama-guard-3-8b" }, - "groq/gemma-7b-it": { - "deprecation_date": "2024-12-18", - "input_cost_per_token": 5e-08, - "litellm_provider": "groq", - "max_input_tokens": 8192, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - 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"supports_tool_choice": true, - "supports_vision": true - }, - "groq/meta-llama/llama-4-scout-17b-16e-instruct": { - "deprecation_date": "2026-07-17", - "input_cost_per_token": 1.1e-07, - "litellm_provider": "groq", - "max_input_tokens": 131072, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 3.4e-07, - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "groq/moonshotai/kimi-k2-instruct-0905": { - "deprecation_date": "2026-04-15", - "input_cost_per_token": 1e-06, - "output_cost_per_token": 3e-06, - "cache_read_input_token_cost": 5e-07, - "litellm_provider": "groq", - "max_input_tokens": 262144, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, "groq/openai/gpt-oss-120b": { "cache_read_input_token_cost": 7.5e-08, "input_cost_per_token": 1.5e-07, @@ -37070,45 +33824,6 @@ "mode": "audio_speech", "source": "https://console.groq.com/docs/models" }, - "groq/playai-tts": { - "deprecation_date": "2025-12-31", - "input_cost_per_character": 5e-05, - "litellm_provider": "groq", - "max_input_tokens": 10000, - "max_output_tokens": 10000, - "max_tokens": 10000, - "mode": "audio_speech" - }, - "groq/qwen/qwen3.6-27b": { - "input_cost_per_token": 6e-07, - "litellm_provider": "groq", - "max_input_tokens": 131072, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 3e-06, - "source": "https://console.groq.com/docs/model/qwen/qwen3.6-27b", - "deprecation_date": "2026-09-14", - "supports_function_calling": true, - "supports_reasoning": true, - "supports_response_schema": false, - "supports_tool_choice": true, - "supports_vision": true - }, - "groq/qwen/qwen3-32b": { - "deprecation_date": "2026-07-17", - "input_cost_per_token": 2.9e-07, - "litellm_provider": "groq", - "max_input_tokens": 131000, - "max_output_tokens": 131000, - "max_tokens": 131000, - "mode": "chat", - "output_cost_per_token": 5.9e-07, - "supports_function_calling": true, - "supports_reasoning": true, - "supports_response_schema": false, - "supports_tool_choice": true - }, "groq/whisper-large-v3": { "input_cost_per_second": 3.083e-05, "litellm_provider": "groq", @@ -37121,27 +33836,6 @@ "mode": "audio_transcription", "output_cost_per_second": 0.0 }, - "hd/1024-x-1024/dall-e-3": { - "deprecation_date": "2026-05-12", - "input_cost_per_pixel": 7.629e-08, - "litellm_provider": "openai", - "mode": "image_generation", - "output_cost_per_pixel": 0.0 - }, - "hd/1024-x-1792/dall-e-3": { - "deprecation_date": "2026-05-12", - "input_cost_per_pixel": 6.539e-08, - "litellm_provider": "openai", - "mode": "image_generation", - "output_cost_per_pixel": 0.0 - }, - "hd/1792-x-1024/dall-e-3": { - "deprecation_date": "2026-05-12", - "input_cost_per_pixel": 6.539e-08, - "litellm_provider": "openai", - "mode": "image_generation", - "output_cost_per_pixel": 0.0 - }, "heroku/claude-3-5-haiku": { "litellm_provider": "heroku", "max_tokens": 8192, @@ -38968,19 +35662,6 @@ "supports_system_messages": true, "supports_native_structured_output": true }, - "mistral/codestral-2405": { - "deprecation_date": "2025-06-16", - "input_cost_per_token": 1e-06, - "litellm_provider": "mistral", - "max_input_tokens": 32000, - "max_output_tokens": 8191, - "max_tokens": 8191, - "mode": "chat", - "output_cost_per_token": 3e-06, - "supports_assistant_prefill": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, "mistral/codestral-2508": { "cache_read_input_token_cost": 3e-08, "input_cost_per_token": 3e-07, @@ -39024,51 +35705,6 @@ "supports_assistant_prefill": true, "supports_tool_choice": true }, - "mistral/devstral-medium-2507": { - "deprecation_date": "2026-05-31", - "input_cost_per_token": 4e-07, - "litellm_provider": "mistral", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 2e-06, - "source": "https://mistral.ai/news/devstral", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, - "mistral/devstral-small-2505": { - "deprecation_date": "2025-11-30", - "input_cost_per_token": 1e-07, - "litellm_provider": "mistral", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 3e-07, - "source": "https://mistral.ai/news/devstral", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, - "mistral/devstral-small-2507": { - "deprecation_date": "2026-05-31", - "input_cost_per_token": 1e-07, - "litellm_provider": "mistral", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 3e-07, - "source": "https://mistral.ai/news/devstral", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, "mistral/devstral-small-latest": { "cache_read_input_token_cost": 1e-08, "input_cost_per_token": 1e-07, @@ -39084,21 +35720,6 @@ "supports_response_schema": true, "supports_tool_choice": true }, - "mistral/labs-devstral-small-2512": { - "deprecation_date": "2026-03-31", - "input_cost_per_token": 1e-07, - "litellm_provider": "mistral", - "max_input_tokens": 256000, - "max_output_tokens": 256000, - "max_tokens": 256000, - "mode": "chat", - "output_cost_per_token": 3e-07, - "source": "https://docs.mistral.ai/models/devstral-small-2-25-12", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, "mistral/devstral-latest": { "cache_read_input_token_cost": 4e-08, "input_cost_per_token": 4e-07, @@ -39129,21 +35750,6 @@ "supports_response_schema": true, "supports_tool_choice": true }, - "mistral/devstral-2512": { - "deprecation_date": "2026-07-31", - "input_cost_per_token": 4e-07, - "litellm_provider": "mistral", - "max_input_tokens": 256000, - "max_output_tokens": 256000, - "max_tokens": 256000, - "mode": "chat", - "output_cost_per_token": 2e-06, - "source": "https://mistral.ai/news/devstral-2-vibe-cli", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, "mistral/ministral-14b-2512": { "input_cost_per_token": 2e-07, "litellm_provider": "mistral", @@ -39419,54 +36025,6 @@ "supports_response_schema": true, "supports_tool_choice": true }, - "mistral/magistral-medium-2506": { - "deprecation_date": "2025-11-30", - "input_cost_per_token": 2e-06, - "litellm_provider": "mistral", - "max_input_tokens": 40000, - "max_output_tokens": 40000, - "max_tokens": 40000, - "mode": "chat", - "output_cost_per_token": 5e-06, - "source": "https://mistral.ai/news/magistral", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, - "mistral/magistral-medium-2509": { - "deprecation_date": "2026-07-31", - "input_cost_per_token": 2e-06, - "litellm_provider": "mistral", - "max_input_tokens": 40000, - "max_output_tokens": 40000, - "max_tokens": 40000, - "mode": "chat", - "output_cost_per_token": 5e-06, - "source": "https://mistral.ai/news/magistral", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, - "mistral/magistral-medium-1-2-2509": { - "deprecation_date": "2026-07-31", - "input_cost_per_token": 2e-06, - "litellm_provider": "mistral", - "max_input_tokens": 40000, - "max_output_tokens": 40000, - "max_tokens": 40000, - "mode": "chat", - "output_cost_per_token": 5e-06, - "source": "https://mistral.ai/news/magistral", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, "mistral/mistral-ocr-latest": { "litellm_provider": "mistral", "ocr_cost_per_page": 0.004, @@ -39506,20 +36064,6 @@ "/v1/batch" ] }, - "mistral/mistral-ocr-2505-completion": { - "deprecation_date": "2026-05-31", - "litellm_provider": "mistral", - "ocr_cost_per_page": 0.001, - "ocr_cost_per_page_batches": 0.0005, - "annotation_cost_per_page": 0.003, - "annotation_cost_per_page_batches": 0.0015, - "mode": "ocr", - "supported_endpoints": [ - "/v1/ocr", - "/v1/batch" - ], - "source": "https://mistral.ai/pricing#api-pricing" - }, "mistral/mistral-ocr-2512": { "litellm_provider": "mistral", "ocr_cost_per_page": 0.002, @@ -39550,22 +36094,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "mistral/magistral-small-2506": { - "deprecation_date": "2025-11-30", - "input_cost_per_token": 5e-07, - "litellm_provider": "mistral", - "max_input_tokens": 40000, - "max_output_tokens": 40000, - "max_tokens": 40000, - "mode": "chat", - "output_cost_per_token": 1.5e-06, - "source": "https://mistral.ai/pricing#api-pricing", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, "mistral/magistral-small-latest": { "cache_read_input_token_cost": 1.5e-08, "input_cost_per_token": 1.5e-07, @@ -39583,22 +36111,6 @@ "supports_tool_choice": true, "supports_vision": true }, - 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"supports_response_schema": true, - "supports_tool_choice": true - }, - "mistral/mistral-large-2407": { - "deprecation_date": "2025-03-30", - "input_cost_per_token": 3e-06, - "litellm_provider": "mistral", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 9e-06, - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, - "mistral/mistral-large-2411": { - "deprecation_date": "2026-05-31", - "input_cost_per_token": 2e-06, - "litellm_provider": "mistral", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 6e-06, - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, "mistral/mistral-large-latest": { "cache_read_input_token_cost": 5e-08, "input_cost_per_token": 5e-07, @@ -39733,49 +36203,6 @@ "supports_tool_choice": true, "supports_vision": true }, - 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"supports_web_search": true - }, "moonshot/moonshot-v1-128k": { "input_cost_per_token": 2e-06, "litellm_provider": "moonshot", @@ -40396,19 +36543,6 @@ "supports_response_schema": true, "supports_tool_choice": true }, - "moonshot/moonshot-v1-128k-0430": { - "deprecation_date": "2024-04-30", - "input_cost_per_token": 2e-06, - "litellm_provider": "moonshot", - "max_input_tokens": 131072, - "max_output_tokens": 131072, - "max_tokens": 131072, - "mode": "chat", - "output_cost_per_token": 5e-06, - "source": "https://platform.moonshot.ai/docs/pricing", - "supports_function_calling": true, - "supports_tool_choice": true - }, "moonshot/moonshot-v1-128k-vision-preview": { "input_cost_per_token": 2e-06, "litellm_provider": "moonshot", @@ -40436,19 +36570,6 @@ "supports_response_schema": true, "supports_tool_choice": true }, - "moonshot/moonshot-v1-32k-0430": { - "deprecation_date": "2024-04-30", - "input_cost_per_token": 1e-06, - "litellm_provider": "moonshot", - "max_input_tokens": 32768, - "max_output_tokens": 32768, - "max_tokens": 32768, - "mode": "chat", - "output_cost_per_token": 3e-06, - "source": "https://platform.moonshot.ai/docs/pricing", - "supports_function_calling": true, - "supports_tool_choice": true - }, "moonshot/moonshot-v1-32k-vision-preview": { "input_cost_per_token": 1e-06, "litellm_provider": "moonshot", @@ -40476,19 +36597,6 @@ "supports_response_schema": true, "supports_tool_choice": true }, - "moonshot/moonshot-v1-8k-0430": { - "deprecation_date": "2024-04-30", - "input_cost_per_token": 2e-07, - "litellm_provider": "moonshot", - "max_input_tokens": 8192, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 2e-06, - "source": "https://platform.moonshot.ai/docs/pricing", - "supports_function_calling": true, - "supports_tool_choice": true - }, "moonshot/moonshot-v1-8k-vision-preview": { "input_cost_per_token": 2e-07, "litellm_provider": "moonshot", @@ -41679,88 +37787,6 @@ "supports_vision": true, "supports_web_search": true }, - "o3-deep-research": { - 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"supports_vision": true, - "supports_web_search": true - }, - "o3-deep-research-2025-06-26": { - "cache_read_input_token_cost": 2.5e-06, - "deprecation_date": "2026-07-23", - "input_cost_per_token": 1e-05, - "input_cost_per_token_batches": 5e-06, - "litellm_provider": "openai", - "max_input_tokens": 200000, - "max_output_tokens": 100000, - "max_tokens": 100000, - "mode": "responses", - "output_cost_per_token": 4e-05, - "output_cost_per_token_batches": 2e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/batch", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": true - }, "o3-mini": { "cache_read_input_token_cost": 5.5e-07, "deprecation_date": "2026-10-23", @@ -41946,88 +37972,6 @@ "supports_vision": true, "supports_web_search": true }, - "o4-mini-deep-research": { - "cache_read_input_token_cost": 5e-07, - "deprecation_date": "2026-07-23", - "input_cost_per_token": 2e-06, - "input_cost_per_token_batches": 1e-06, - "litellm_provider": "openai", - "max_input_tokens": 200000, - "max_output_tokens": 100000, - "max_tokens": 100000, - "mode": "responses", - "output_cost_per_token": 8e-06, - "output_cost_per_token_batches": 4e-06, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/batch", - "/v1/responses" - ], - "supported_modalities": [ - "text", - 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}, "cerebras/gemma-4-31b": { "input_cost_per_token": 9.9e-07, "litellm_provider": "cerebras", @@ -71240,37 +65298,14 @@ "output_cost_per_token": 1.5e-07, "source": "https://api.together.ai/v1/models" }, - "together_ai/deepseek-ai/deepseek-coder-33b-instruct": { - "deprecation_date": "2024-08-22", - "input_cost_per_token": 8e-07, - "litellm_provider": "together_ai", - "mode": "chat", - "output_cost_per_token": 8e-07, - "source": "https://api.together.ai/v1/models" - }, - "together_ai/deepseek-ai/DeepSeek-R1-Distill-Llama-70B": { - "deprecation_date": "2025-12-23", - "input_cost_per_token": 2e-06, - "litellm_provider": "together_ai", - "mode": "chat", + "vertex_ai/gemini-2.5-flash-native-audio": { + "input_cost_per_audio_token": 3e-06, + "input_cost_per_token": 5e-07, + "litellm_provider": "vertex_ai", + "mode": "realtime", + "output_cost_per_audio_token": 1.2e-05, "output_cost_per_token": 2e-06, - "source": "https://api.together.ai/v1/models" - }, - "together_ai/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B": { - "deprecation_date": "2025-08-28", - "input_cost_per_token": 1.8e-07, - "litellm_provider": "together_ai", - "mode": "chat", - "output_cost_per_token": 1.8e-07, - "source": "https://api.together.ai/v1/models" - }, - "together_ai/deepseek-ai/DeepSeek-R1-Distill-Qwen-14B": { - "deprecation_date": "2025-11-13", - "input_cost_per_token": 1.6e-06, - "litellm_provider": "together_ai", - "mode": "chat", - "output_cost_per_token": 1.6e-06, - "source": "https://api.together.ai/v1/models" + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" }, "vertex_ai/gemini-2.5-flash-preview-tts": { "input_cost_per_token": 5e-07, @@ -71321,14 +65356,6 @@ "output_cost_per_token": 6e-07, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" }, - "together_ai/google/gemma-2-27b-it": { - "deprecation_date": "2025-08-28", - "input_cost_per_token": 8e-07, - "litellm_provider": "together_ai", - "mode": "chat", - "output_cost_per_token": 8e-07, - "source": "https://api.together.ai/v1/models" - }, "gpt-5.5-cyber": { "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 1.25e-05, @@ -71346,14 +65373,6 @@ "output_cost_per_token": 2.5e-05, "source": "https://developers.openai.com/api/docs/pricing" }, - "together_ai/meta-llama/Llama-3-8b-chat-hf": { - "deprecation_date": "2025-08-28", - "input_cost_per_token": 2e-07, - "litellm_provider": "together_ai", - "mode": "chat", - "output_cost_per_token": 2e-07, - "source": "https://api.together.ai/v1/models" - }, "together_ai/meta-llama/Llama-3.1-405B-Instruct": { "input_cost_per_token": 3.5e-06, "litellm_provider": "together_ai", @@ -71375,38 +65394,6 @@ "output_cost_per_token": 6e-08, "source": "https://api.together.ai/v1/models" }, - "together_ai/meta-llama/Meta-Llama-3-70B-Instruct-Turbo": { - "deprecation_date": "2025-12-23", - "input_cost_per_token": 8.8e-07, - "litellm_provider": "together_ai", - "mode": "chat", - "output_cost_per_token": 8.8e-07, - "source": "https://api.together.ai/v1/models" - }, - "together_ai/meta-llama/Meta-Llama-3-8B-Instruct": { - "deprecation_date": "2025-08-28", - "input_cost_per_token": 2e-07, - "litellm_provider": "together_ai", - "mode": "chat", - "output_cost_per_token": 2e-07, - "source": "https://api.together.ai/v1/models" - }, - "together_ai/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO": { - "deprecation_date": "2025-08-28", - "input_cost_per_token": 6e-07, - "litellm_provider": "together_ai", - "mode": "chat", - "output_cost_per_token": 6e-07, - "source": "https://api.together.ai/v1/models" - }, - "together_ai/nvidia/Llama-3.1-Nemotron-70B-Instruct-HF": { - "deprecation_date": "2025-08-28", - "input_cost_per_token": 8.8e-07, - "litellm_provider": "together_ai", - "mode": "chat", - "output_cost_per_token": 8.8e-07, - "source": "https://api.together.ai/v1/models" - }, "together_ai/Qwen/Qwen2-1.5B-Instruct": { "input_cost_per_token": 2e-08, "litellm_provider": "together_ai", @@ -71414,22 +65401,6 @@ "output_cost_per_token": 2e-08, "source": "https://api.together.ai/v1/models" }, - "together_ai/Qwen/Qwen2-72B-Instruct": { - "deprecation_date": "2025-08-28", - "input_cost_per_token": 9e-07, - "litellm_provider": "together_ai", - "mode": "chat", - "output_cost_per_token": 9e-07, - "source": "https://api.together.ai/v1/models" - }, - "together_ai/Qwen/Qwen2-VL-72B-Instruct": { - "deprecation_date": "2025-08-28", - "input_cost_per_token": 1.2e-06, - "litellm_provider": "together_ai", - "mode": "chat", - "output_cost_per_token": 1.2e-06, - "source": "https://api.together.ai/v1/models" - }, "together_ai/Qwen/Qwen2.5-14B-Instruct": { "input_cost_per_token": 8e-07, "litellm_provider": "together_ai", @@ -71444,22 +65415,6 @@ "output_cost_per_token": 1.2e-06, "source": "https://api.together.ai/v1/models" }, - "together_ai/Qwen/Qwen2.5-Coder-32B-Instruct": { - "deprecation_date": "2025-11-13", - "input_cost_per_token": 8e-07, - "litellm_provider": "together_ai", - "mode": "chat", - "output_cost_per_token": 8e-07, - "source": "https://api.together.ai/v1/models" - }, - "together_ai/Qwen/Qwen2.5-VL-72B-Instruct": { - "deprecation_date": "2026-01-05", - "input_cost_per_token": 1.95e-06, - "litellm_provider": "together_ai", - "mode": "chat", - "output_cost_per_token": 8e-06, - "source": "https://api.together.ai/v1/models" - }, "azure/eu/codex-mini": { "deprecation_date": "2026-11-15", "cache_read_input_token_cost": 4.13e-07, @@ -71610,15 +65565,6 @@ "output_cost_per_token_priority": 3.08e-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/gpt-5.2-chat": { - "deprecation_date": "2026-06-29", - "cache_read_input_token_cost": 1.925e-07, - "input_cost_per_token": 1.925e-06, - "litellm_provider": "azure", - "mode": "chat", - "output_cost_per_token": 1.54e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" - }, "azure/eu/gpt-5.2-codex": { "deprecation_date": "2027-07-13", "cache_read_input_token_cost": 1.925e-07, @@ -71637,15 +65583,6 @@ "output_cost_per_token_batches": 9.24e-05, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, - "azure/eu/gpt-5.3-chat": { - "deprecation_date": "2026-06-29", - "cache_read_input_token_cost": 1.925e-07, - "input_cost_per_token": 1.925e-06, - "litellm_provider": "azure", - "mode": "chat", - "output_cost_per_token": 1.54e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" - }, "azure/eu/gpt-5.3-codex": { "deprecation_date": "2027-08-24", "cache_read_input_token_cost": 1.925e-07, @@ -71964,15 +65901,6 @@ "output_cost_per_token_priority": 3.08e-05, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, - "azure/us/gpt-5.2-chat": { - "deprecation_date": "2026-06-29", - "cache_read_input_token_cost": 1.925e-07, - "input_cost_per_token": 1.925e-06, - "litellm_provider": "azure", - "mode": "chat", - "output_cost_per_token": 1.54e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" - }, "azure/us/gpt-5.2-codex": { "deprecation_date": "2027-07-13", "cache_read_input_token_cost": 1.925e-07, @@ -71991,15 +65919,6 @@ "output_cost_per_token_batches": 9.24e-05, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, - "azure/us/gpt-5.3-chat": { - "deprecation_date": "2026-06-29", - "cache_read_input_token_cost": 1.925e-07, - "input_cost_per_token": 1.925e-06, - "litellm_provider": "azure", - "mode": "chat", - "output_cost_per_token": 1.54e-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/us/gpt-5.3-codex": { "deprecation_date": "2027-08-24", "cache_read_input_token_cost": 1.925e-07, diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 431e965524e..b48bdd6322c 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -53,13 +53,6 @@ "mode": "image_generation", "output_cost_per_image": 0.04 }, - "1024-x-1024/dall-e-2": { - "deprecation_date": "2026-05-12", - "input_cost_per_pixel": 1.9e-08, - "litellm_provider": "openai", - "mode": "image_generation", - "output_cost_per_pixel": 0.0 - }, "1024-x-1024/max-steps/stability.stable-diffusion-xl-v1": { "litellm_provider": "bedrock", "max_input_tokens": 77, @@ -67,13 +60,6 @@ "mode": "image_generation", "output_cost_per_image": 0.08 }, - "256-x-256/dall-e-2": { - "deprecation_date": "2026-05-12", - "input_cost_per_pixel": 2.4414e-07, - "litellm_provider": "openai", - "mode": "image_generation", - "output_cost_per_pixel": 0.0 - }, "512-x-512/50-steps/stability.stable-diffusion-xl-v0": { "litellm_provider": "bedrock", "max_input_tokens": 77, @@ -81,13 +67,6 @@ "mode": "image_generation", "output_cost_per_image": 0.018 }, - "512-x-512/dall-e-2": { - "deprecation_date": "2026-05-12", - "input_cost_per_pixel": 6.86e-08, - "litellm_provider": "openai", - "mode": "image_generation", - "output_cost_per_pixel": 0.0 - }, "512-x-512/max-steps/stability.stable-diffusion-xl-v0": { "litellm_provider": "bedrock", "max_input_tokens": 77, @@ -961,23 +940,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "anthropic.claude-3-haiku-20240307-v1:0": { - "deprecation_date": "2026-09-10", - "input_cost_per_token": 2.5e-07, - "litellm_provider": "bedrock", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.25e-06, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "cache_read_input_token_cost": 2.5e-08, - "cache_creation_input_token_cost": 3.125e-07 - }, "anthropic.claude-3-opus-20240229-v1:0": { "input_cost_per_token": 1.5e-05, "litellm_provider": "bedrock", @@ -993,23 +955,6 @@ "cache_read_input_token_cost": 1.5e-06, "cache_creation_input_token_cost": 1.875e-05 }, - "anthropic.claude-3-sonnet-20240229-v1:0": { - "deprecation_date": "2026-07-30", - "input_cost_per_token": 3e-06, - "litellm_provider": "bedrock", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.5e-05, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "cache_read_input_token_cost": 3e-07, - "cache_creation_input_token_cost": 3.75e-06 - }, "anthropic.claude-instant-v1": { "input_cost_per_token": 8e-07, "litellm_provider": "bedrock", @@ -2971,60 +2916,6 @@ "supports_vision": true, "supports_tool_choice": true }, - "apac.anthropic.claude-3-5-sonnet-20240620-v1:0": { - "deprecation_date": "2026-07-30", - "input_cost_per_token": 3e-06, - "litellm_provider": "bedrock", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.5e-05, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "cache_read_input_token_cost": 3e-07, - "cache_creation_input_token_cost": 3.75e-06 - }, - "apac.anthropic.claude-3-5-sonnet-20241022-v2:0": { - "cache_creation_input_token_cost": 3.75e-06, - "cache_read_input_token_cost": 3e-07, - "deprecation_date": "2026-07-30", - "input_cost_per_token": 3e-06, - "litellm_provider": "bedrock", - "max_input_tokens": 200000, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 1.5e-05, - "supports_assistant_prefill": true, - "supports_computer_use": true, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "apac.anthropic.claude-3-haiku-20240307-v1:0": { - "deprecation_date": "2026-09-10", - "input_cost_per_token": 2.5e-07, - "litellm_provider": "bedrock", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.25e-06, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "cache_read_input_token_cost": 2.5e-08, - "cache_creation_input_token_cost": 3.125e-07 - }, "apac.anthropic.claude-haiku-4-5-20251001-v1:0": { "cache_creation_input_token_cost": 1.375e-06, "cache_read_input_token_cost": 1.1e-07, @@ -3052,23 +2943,6 @@ "input_cost_per_token_batches": 5.5e-07, "output_cost_per_token_batches": 2.75e-06 }, - "apac.anthropic.claude-3-sonnet-20240229-v1:0": { - "deprecation_date": "2026-07-30", - "input_cost_per_token": 3e-06, - "litellm_provider": "bedrock", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.5e-05, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "cache_read_input_token_cost": 3e-07, - "cache_creation_input_token_cost": 3.75e-06 - }, "apac.anthropic.claude-sonnet-4-20250514-v1:0": { "cache_creation_input_token_cost": 3.75e-06, "cache_read_input_token_cost": 3e-07, @@ -3446,29 +3320,6 @@ "supports_max_reasoning_effort": true, "prompt_cache_min_tokens": 1024 }, - "azure_ai/claude-opus-4-1": { - "deprecation_date": "2026-08-05", - "cache_creation_input_token_cost": 1.875e-05, - "cache_creation_input_token_cost_above_1hr": 3e-05, - "cache_read_input_token_cost": 1.5e-06, - "input_cost_per_token": 1.5e-05, - "litellm_provider": "azure_ai", - "max_input_tokens": 200000, - "max_output_tokens": 32000, - "max_tokens": 32000, - "mode": "chat", - "output_cost_per_token": 7.5e-05, - "supports_assistant_prefill": true, - "supports_computer_use": true, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "prompt_cache_min_tokens": 1024 - }, "azure_ai/claude-sonnet-4-5": { "deprecation_date": "2026-10-19", "cache_creation_input_token_cost": 3.75e-06, @@ -4503,43 +4354,6 @@ "output_cost_per_token_priority": 2.2e-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/gpt-5.1-chat": { - "cache_read_input_token_cost": 1.375e-07, - "deprecation_date": "2026-06-29", - "input_cost_per_token": 1.375e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 1.1e-05, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/batch", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text", - "image" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_none_reasoning_effort": true, - "default_reasoning_effort": "none", - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" - }, "azure/eu/gpt-5.1-codex": { "deprecation_date": "2027-05-15", "cache_read_input_token_cost": 1.375e-07, @@ -4832,43 +4646,6 @@ "output_cost_per_token_priority": 2e-05, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, - "azure/global/gpt-5.1-chat": { - "cache_read_input_token_cost": 1.25e-07, - "deprecation_date": "2026-06-29", - "input_cost_per_token": 1.25e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 1e-05, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/batch", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text", - "image" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_none_reasoning_effort": true, - "default_reasoning_effort": "none", - "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/global/gpt-5.1-codex": { "deprecation_date": "2027-05-15", "cache_read_input_token_cost": 1.25e-07, @@ -4944,19 +4721,6 @@ "supports_function_calling": true, "supports_tool_choice": true }, - "azure/gpt-3.5-turbo-0125": { - "deprecation_date": "2025-03-31", - "input_cost_per_token": 5e-07, - "litellm_provider": "azure", - "max_input_tokens": 16384, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.5e-06, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_tool_choice": true - }, "azure/gpt-3.5-turbo-instruct-0914": { "input_cost_per_token": 1.5e-06, "litellm_provider": "azure_text", @@ -4976,32 +4740,6 @@ "supports_function_calling": true, "supports_tool_choice": true }, - "azure/gpt-35-turbo-0125": { - "deprecation_date": "2025-05-31", - "input_cost_per_token": 5e-07, - "litellm_provider": "azure", - "max_input_tokens": 16384, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.5e-06, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_tool_choice": true - }, - "azure/gpt-35-turbo-1106": { - "deprecation_date": "2025-03-31", - "input_cost_per_token": 1e-06, - "litellm_provider": "azure", - "max_input_tokens": 16384, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 2e-06, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_tool_choice": true - }, "azure/gpt-35-turbo-16k": { "input_cost_per_token": 3e-06, "litellm_provider": "azure", @@ -5769,40 +5507,6 @@ "supports_system_messages": true, "supports_tool_choice": true }, - "azure/gpt-realtime-2": { - "cache_read_input_audio_token_cost": 4e-07, - "cache_read_input_token_cost": 4e-07, - "deprecation_date": "2026-08-31", - "input_cost_per_audio_token": 3.2e-05, - "input_cost_per_image_token": 5e-06, - "input_cost_per_token": 4e-06, - "litellm_provider": "azure", - "max_input_tokens": 32000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "realtime", - "output_cost_per_audio_token": 6.4e-05, - "output_cost_per_token": 2.4e-05, - "source": "https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure", - "supported_endpoints": [ - "/v1/realtime" - ], - "supported_modalities": [ - "text", - "image", - "audio" - ], - "supported_output_modalities": [ - "text", - "audio" - ], - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, "azure/gpt-realtime-2.1": { "cache_creation_input_audio_token_cost": 4e-07, "cache_read_input_audio_token_cost": 4e-07, @@ -6100,45 +5804,6 @@ "supports_minimal_reasoning_effort": true, "cache_read_input_token_cost_batches": 6.25e-08 }, - "azure/gpt-5.1-chat-2025-11-13": { - "cache_read_input_token_cost": 1.25e-07, - "cache_read_input_token_cost_priority": 2.5e-07, - "deprecation_date": "2026-06-29", - "input_cost_per_token": 1.25e-06, - "input_cost_per_token_priority": 2.5e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 1e-05, - "output_cost_per_token_priority": 2e-05, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text", - "image" - ], - "supports_function_calling": false, - "supports_native_streaming": true, - "supports_parallel_function_calling": false, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": false, - "supports_vision": true, - "supports_none_reasoning_effort": true, - "default_reasoning_effort": "none", - "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/gpt-5.1-codex-2025-11-13": { "cache_read_input_token_cost": 1.25e-07, "cache_read_input_token_cost_priority": 2.5e-07, @@ -6289,73 +5954,6 @@ "supports_vision": true, "cache_read_input_token_cost_batches": 6.25e-08 }, - "azure/gpt-5-chat": { - "cache_read_input_token_cost": 1.25e-07, - "deprecation_date": "2026-06-29", - "input_cost_per_token": 1.25e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 1e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/batch", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "azure/gpt-5-chat-latest": { - "cache_read_input_token_cost": 1.25e-07, - "deprecation_date": "2026-06-29", - "input_cost_per_token": 1.25e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 1e-05, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/batch", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, "azure/gpt-5-codex": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2027-03-17", @@ -6617,43 +6215,6 @@ "output_cost_per_token_priority": 2e-05, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, - "azure/gpt-5.1-chat": { - "cache_read_input_token_cost": 1.25e-07, - "deprecation_date": "2026-06-29", - "input_cost_per_token": 1.25e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 1e-05, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/batch", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text", - "image" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_none_reasoning_effort": true, - "default_reasoning_effort": "none", - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" - }, "azure/gpt-5.1-codex": { "deprecation_date": "2027-05-15", "cache_read_input_token_cost": 1.25e-07, @@ -6832,78 +6393,6 @@ "supports_vision": true, "cache_read_input_token_cost_batches": 8.75e-08 }, - "azure/gpt-5.2-chat": { - "cache_read_input_token_cost": 1.75e-07, - "cache_read_input_token_cost_priority": 3.5e-07, - "deprecation_date": "2026-06-29", - "input_cost_per_token": 1.75e-06, - "input_cost_per_token_priority": 3.5e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 1.4e-05, - "output_cost_per_token_priority": 2.8e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "azure/gpt-5.2-chat-2025-12-11": { - "cache_read_input_token_cost": 1.75e-07, - "cache_read_input_token_cost_priority": 3.5e-07, - "deprecation_date": "2026-05-13", - "input_cost_per_token": 1.75e-06, - "input_cost_per_token_priority": 3.5e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 1.4e-05, - "output_cost_per_token_priority": 2.8e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, "azure/gpt-5.2-codex": { "cache_read_input_token_cost": 1.75e-07, "deprecation_date": "2027-07-13", @@ -6936,42 +6425,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "azure/gpt-5.3-chat": { - "cache_read_input_token_cost": 1.75e-07, - "cache_read_input_token_cost_priority": 3.5e-07, - "deprecation_date": "2026-06-29", - "input_cost_per_token": 1.75e-06, - "input_cost_per_token_priority": 3.5e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 1.4e-05, - "output_cost_per_token_priority": 2.8e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, "azure/gpt-5.3-codex": { "cache_read_input_token_cost": 1.75e-07, "cache_read_input_token_cost_priority": 3.5e-07, @@ -10563,43 +10016,6 @@ "output_cost_per_token_priority": 2.2e-05, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, - "azure/us/gpt-5.1-chat": { - "cache_read_input_token_cost": 1.375e-07, - "deprecation_date": "2026-06-29", - "input_cost_per_token": 1.375e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 1.1e-05, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/batch", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text", - "image" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_none_reasoning_effort": true, - "default_reasoning_effort": "none", - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" - }, "azure/us/gpt-5.1-codex": { "deprecation_date": "2027-05-15", "cache_read_input_token_cost": 1.375e-07, @@ -11201,18 +10617,6 @@ "/v1/images/edits" ] }, - "azure_ai/MAI-Image-2e": { - "deprecation_date": "2026-08-15", - "input_cost_per_token": 5e-06, - "litellm_provider": "azure_ai", - "mode": "image_generation", - "output_cost_per_image": 0.02, - "output_cost_per_image_token": 1.95e-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'", - "supported_endpoints": [ - "/v1/images/generations" - ] - }, "azure_ai/MAI-Thinking-1": { "cache_read_input_token_cost": 2e-07, "input_cost_per_token": 2e-06, @@ -11237,34 +10641,6 @@ "supports_reasoning": true, "supports_tool_choice": true }, - "azure_ai/Llama-3.2-11B-Vision-Instruct": { - "deprecation_date": "2026-06-13", - "input_cost_per_token": 3.7e-07, - "litellm_provider": "azure_ai", - "max_input_tokens": 128000, - "max_output_tokens": 2048, - "max_tokens": 2048, - "mode": "chat", - "output_cost_per_token": 3.7e-07, - "source": "https://marketplace.microsoft.com/en/marketplace/apps/metagenai.meta-llama-3-2-11b-vision-instruct-offer?tab=Overview", - "supports_function_calling": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "azure_ai/Llama-3.2-90B-Vision-Instruct": { - "deprecation_date": "2026-06-13", - "input_cost_per_token": 2.04e-06, - "litellm_provider": "azure_ai", - "max_input_tokens": 128000, - "max_output_tokens": 2048, - "max_tokens": 2048, - "mode": "chat", - "output_cost_per_token": 2.04e-06, - "source": "https://marketplace.microsoft.com/en/marketplace/apps/metagenai.meta-llama-3-2-90b-vision-instruct-offer?tab=Overview", - "supports_function_calling": true, - "supports_tool_choice": true, - "supports_vision": true - }, "azure_ai/Llama-3.3-70B-Instruct": { "input_cost_per_token": 7.1e-07, "litellm_provider": "azure_ai", @@ -11313,18 +10689,6 @@ "output_cost_per_token": 3.7e-07, "supports_tool_choice": true }, - "azure_ai/Meta-Llama-3.1-405B-Instruct": { - "deprecation_date": "2026-06-13", - "input_cost_per_token": 5.33e-06, - "litellm_provider": "azure_ai", - "max_input_tokens": 128000, - "max_output_tokens": 2048, - "max_tokens": 2048, - "mode": "chat", - "output_cost_per_token": 1.6e-05, - "source": "https://marketplace.microsoft.com/en-us/marketplace/apps/metagenai.meta-llama-3-1-405b-instruct-offer?tab=PlansAndPrice", - "supports_tool_choice": true - }, "azure_ai/Meta-Llama-3.1-70B-Instruct": { "input_cost_per_token": 2.68e-06, "litellm_provider": "azure_ai", @@ -11336,18 +10700,6 @@ "source": "https://marketplace.microsoft.com/en-us/marketplace/apps/metagenai.meta-llama-3-1-70b-instruct-offer?tab=PlansAndPrice", "supports_tool_choice": true }, - "azure_ai/Meta-Llama-3.1-8B-Instruct": { - "deprecation_date": "2026-06-13", - "input_cost_per_token": 3e-07, - "litellm_provider": "azure_ai", - "max_input_tokens": 128000, - "max_output_tokens": 2048, - "max_tokens": 2048, - "mode": "chat", - "output_cost_per_token": 6.1e-07, - "source": "https://marketplace.microsoft.com/en-us/marketplace/apps/metagenai.meta-llama-3-1-8b-instruct-offer?tab=PlansAndPrice", - "supports_tool_choice": true - }, "azure_ai/Phi-3-medium-128k-instruct": { "input_cost_per_token": 1.7e-07, "litellm_provider": "azure_ai", @@ -11518,16 +10870,6 @@ "supports_tool_choice": true, "supports_reasoning": true }, - "azure_ai/mistral-document-ai-2505": { - "deprecation_date": "2026-07-20", - "litellm_provider": "azure_ai", - "ocr_cost_per_page": 0.003, - "mode": "ocr", - "supported_endpoints": [ - "/v1/ocr" - ], - "source": "https://devblogs.microsoft.com/foundry/whats-new-in-azure-ai-foundry-august-2025/#mistral-document-ai-(ocr)-%E2%80%94-serverless-in-foundry" - }, "azure_ai/mistral-document-ai-2512": { "litellm_provider": "azure_ai", "ocr_cost_per_page": 0.003, @@ -11628,17 +10970,6 @@ "mode": "rerank", "output_cost_per_token": 0.0 }, - "azure_ai/cohere-rerank-v3.5": { - "deprecation_date": "2026-05-14", - "input_cost_per_query": 0.002, - "input_cost_per_token": 0.0, - "litellm_provider": "azure_ai", - "max_input_tokens": 4096, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "rerank", - "output_cost_per_token": 0.0 - }, "azure_ai/cohere-rerank-v4.0-pro": { "input_cost_per_query": 0.0025, "input_cost_per_token": 0.0, @@ -11691,19 +11022,6 @@ "supports_reasoning": true, "supports_tool_choice": true }, - "azure_ai/deepseek-r1": { - "deprecation_date": "2026-08-13", - "input_cost_per_token": 1.35e-06, - "litellm_provider": "azure_ai", - "max_input_tokens": 128000, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 5.4e-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'", - "supports_reasoning": true, - "supports_tool_choice": true - }, "azure_ai/deepseek-v3": { "input_cost_per_token": 1.14e-06, "litellm_provider": "azure_ai", @@ -11715,33 +11033,6 @@ "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_tool_choice": true }, - 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}, - "azure_ai/grok-3-mini": { - "deprecation_date": "2026-05-01", - "input_cost_per_token": 2.5e-07, - "litellm_provider": "azure_ai", - "max_input_tokens": 131072, - "max_output_tokens": 131072, - "max_tokens": 131072, - "mode": "chat", - "output_cost_per_token": 1.27e-06, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supports_function_calling": true, - "supports_reasoning": true, - "supports_response_schema": false, - "supports_tool_choice": true, - "supports_web_search": true - }, "azure_ai/grok-4": { "input_cost_per_token": 3e-06, "litellm_provider": "azure_ai", @@ -11963,36 +11192,6 @@ "supports_vision": true, "supports_web_search": true }, - "azure_ai/grok-4-fast-non-reasoning": { - "deprecation_date": "2026-05-01", - "input_cost_per_token": 2e-07, - "output_cost_per_token": 5e-07, - "litellm_provider": "azure_ai", - "max_input_tokens": 131072, - "max_output_tokens": 131072, - "max_tokens": 131072, - "mode": "chat", - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_web_search": true - }, - "azure_ai/grok-4-fast-reasoning": { - "deprecation_date": "2026-05-01", - "input_cost_per_token": 2e-07, - "output_cost_per_token": 5e-07, - "litellm_provider": "azure_ai", - "max_input_tokens": 131072, - "max_output_tokens": 131072, - "max_tokens": 131072, - "mode": "chat", - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_web_search": true - }, "azure_ai/grok-4-1-fast-non-reasoning": { "input_cost_per_token": 2e-07, "output_cost_per_token": 5e-07, @@ -13516,40 +12715,6 @@ "mode": "chat", "output_cost_per_token": 1.5e-06 }, - 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"max_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 2.75e-06, - "source": "https://www.cerebras.ai/pricing", - "supports_function_calling": true, - "supports_reasoning": true, - "supports_tool_choice": true - }, "cerebras/qwen-3.8-27b": { "input_cost_per_token": 9.9e-07, "litellm_provider": "cerebras", @@ -14272,23 +13354,6 @@ "mode": "chat", "output_cost_per_token": 5e-07 }, - "chatgpt-4o-latest": { - "deprecation_date": "2026-02-17", - "input_cost_per_token": 5e-06, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.5e-05, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, "gpt-4o-transcribe-diarize": { "input_cost_per_audio_token": 2.5e-06, "input_cost_per_token": 2.5e-06, @@ -14351,131 +13416,6 @@ "prompt_cache_min_tokens": 4096, "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, - "claude-3-7-sonnet-20250219": { - "cache_creation_input_token_cost": 3.75e-06, - "cache_creation_input_token_cost_above_1hr": 6e-06, - "cache_read_input_token_cost": 3e-07, - "deprecation_date": "2026-02-19", - "input_cost_per_token": 3e-06, - "litellm_provider": "anthropic", - "max_input_tokens": 200000, - "max_output_tokens": 64000, - "max_tokens": 64000, - "mode": "chat", - "output_cost_per_token": 1.5e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supports_assistant_prefill": true, - "supports_computer_use": true, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": true - }, - "claude-3-haiku-20240307": { - "cache_creation_input_token_cost": 3e-07, - "cache_creation_input_token_cost_above_1hr": 5e-07, - "cache_read_input_token_cost": 3e-08, - "deprecation_date": "2026-04-20", - "input_cost_per_token": 2.5e-07, - "litellm_provider": "anthropic", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.25e-06, - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "claude-3-opus-20240229": { - "cache_creation_input_token_cost": 1.875e-05, - "cache_creation_input_token_cost_above_1hr": 3e-05, - "cache_read_input_token_cost": 1.5e-06, - "deprecation_date": "2026-01-05", - "input_cost_per_token": 1.5e-05, - "litellm_provider": "anthropic", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 7.5e-05, - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_prompt_caching": true, - 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"cache_creation_input_token_cost_above_200k_tokens": 7.5e-06, - "cache_read_input_token_cost": 3e-07, - "cache_read_input_token_cost_above_200k_tokens": 6e-07, - "deprecation_date": "2026-06-15", - "input_cost_per_token": 3e-06, - "input_cost_per_token_above_200k_tokens": 6e-06, - "litellm_provider": "anthropic", - "max_input_tokens": 1000000, - "max_output_tokens": 64000, - "max_tokens": 64000, - "mode": "chat", - "output_cost_per_token": 1.5e-05, - "output_cost_per_token_above_200k_tokens": 2.25e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supports_assistant_prefill": true, - "supports_computer_use": true, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": true, - "prompt_cache_min_tokens": 1024 - }, "claude-sonnet-4-5": { "cache_creation_input_token_cost": 3.75e-06, "cache_creation_input_token_cost_above_1hr": 6e-06, @@ -14654,92 +13594,6 @@ "input_cost_per_token_batches": 1.5e-06, "output_cost_per_token_batches": 7.5e-06 }, - "claude-opus-4-1": { - "cache_creation_input_token_cost": 1.875e-05, - "cache_creation_input_token_cost_above_1hr": 3e-05, - "cache_read_input_token_cost": 1.5e-06, - "input_cost_per_token": 1.5e-05, - "litellm_provider": "anthropic", - "max_input_tokens": 200000, - "max_output_tokens": 32000, - "max_tokens": 32000, - "mode": "chat", - "output_cost_per_token": 7.5e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supports_assistant_prefill": true, - "supports_computer_use": true, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_native_structured_output": true, - "supports_tool_choice": true, - "supports_vision": true, - "prompt_cache_min_tokens": 1024, - "deprecation_date": "2026-08-05" - }, - "claude-opus-4-1-20250805": { - "cache_creation_input_token_cost": 1.875e-05, - "cache_creation_input_token_cost_above_1hr": 3e-05, - "cache_read_input_token_cost": 1.5e-06, - "input_cost_per_token": 1.5e-05, - "deprecation_date": "2026-08-05", - "litellm_provider": "anthropic", - "max_input_tokens": 200000, - "max_output_tokens": 32000, - "max_tokens": 32000, - "mode": "chat", - "output_cost_per_token": 7.5e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supports_assistant_prefill": true, - "supports_computer_use": true, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_native_structured_output": true, - "supports_tool_choice": true, - "supports_vision": true, - "prompt_cache_min_tokens": 1024 - }, - "claude-opus-4-20250514": { - "cache_creation_input_token_cost": 1.875e-05, - "cache_creation_input_token_cost_above_1hr": 3e-05, - "cache_read_input_token_cost": 1.5e-06, - "input_cost_per_token": 1.5e-05, - "deprecation_date": "2026-06-15", - "litellm_provider": "anthropic", - "max_input_tokens": 200000, - "max_output_tokens": 32000, - "max_tokens": 32000, - "mode": "chat", - "output_cost_per_token": 7.5e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supports_assistant_prefill": true, - "supports_computer_use": true, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "prompt_cache_min_tokens": 1024 - }, "claude-opus-4-5-20251101": { "cache_creation_input_token_cost": 6.25e-06, "cache_creation_input_token_cost_above_1hr": 1e-05, @@ -15167,38 +14021,6 @@ "prompt_cache_min_tokens": 1024, "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, - "claude-sonnet-4-20250514": { - "deprecation_date": "2026-06-15", - "cache_creation_input_token_cost": 3.75e-06, - "cache_creation_input_token_cost_above_1hr": 6e-06, - "cache_read_input_token_cost": 3e-07, - "input_cost_per_token": 3e-06, - "input_cost_per_token_above_200k_tokens": 6e-06, - "output_cost_per_token_above_200k_tokens": 2.25e-05, - "cache_creation_input_token_cost_above_200k_tokens": 7.5e-06, - "cache_read_input_token_cost_above_200k_tokens": 6e-07, - "litellm_provider": "anthropic", - "max_input_tokens": 1000000, - "max_output_tokens": 64000, - "max_tokens": 64000, - "mode": "chat", - "output_cost_per_token": 1.5e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supports_assistant_prefill": true, - "supports_computer_use": true, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "prompt_cache_min_tokens": 1024 - }, "cloudflare/@cf/meta/llama-2-7b-chat-fp16": { "input_cost_per_token": 1.923e-06, "litellm_provider": "cloudflare", @@ -15551,36 +14373,6 @@ "supports_assistant_prefill": true, "supports_tool_choice": true }, - "codex-mini-latest": { - "cache_read_input_token_cost": 3.75e-07, - "deprecation_date": "2026-02-12", - "input_cost_per_token": 1.5e-06, - "litellm_provider": "openai", - "max_input_tokens": 200000, - "max_output_tokens": 100000, - "max_tokens": 100000, - "mode": "responses", - "output_cost_per_token": 6e-06, - "supported_endpoints": [ - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, "cohere.command-light-text-v14": { "input_cost_per_token": 3e-07, "litellm_provider": "bedrock", @@ -15680,16 +14472,6 @@ "mode": "rerank", "output_cost_per_token": 0.0 }, - "command": { - "input_cost_per_token": 1e-06, - "litellm_provider": "cohere", - "max_input_tokens": 4096, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "completion", - "output_cost_per_token": 2e-06, - "deprecation_date": "2025-09-15" - }, "command-a-03-2025": { "input_cost_per_token": 2.5e-06, "litellm_provider": "cohere_chat", @@ -15716,17 +14498,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "command-light": { - "input_cost_per_token": 3e-07, - "litellm_provider": "cohere_chat", - "max_input_tokens": 4096, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 6e-07, - "supports_tool_choice": true, - "deprecation_date": "2025-09-15" - }, "command-nightly": { "input_cost_per_token": 1e-06, "litellm_provider": "cohere", @@ -15736,18 +14507,6 @@ "mode": "completion", "output_cost_per_token": 2e-06 }, - "command-r": { - "input_cost_per_token": 1.5e-07, - "litellm_provider": "cohere_chat", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 6e-07, - "supports_function_calling": true, - "supports_tool_choice": true, - "deprecation_date": "2025-09-15" - }, "command-r-08-2024": { "input_cost_per_token": 1.5e-07, "litellm_provider": "cohere_chat", @@ -15759,18 +14518,6 @@ "supports_function_calling": true, "supports_tool_choice": true }, - "command-r-plus": { - "input_cost_per_token": 2.5e-06, - "litellm_provider": "cohere_chat", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1e-05, - "supports_function_calling": true, - "supports_tool_choice": true, - "deprecation_date": "2025-09-15" - }, "command-r-plus-08-2024": { "input_cost_per_token": 2.5e-06, "litellm_provider": "cohere_chat", @@ -15823,26 +14570,6 @@ "supports_vision": true, "source": "https://platform.openai.com/docs/models/computer-use-preview" }, - "dall-e-2": { - "deprecation_date": "2026-05-12", - "input_cost_per_image": 0.02, - "litellm_provider": "openai", - "mode": "image_generation", - "supported_endpoints": [ - "/v1/images/generations", - "/v1/images/edits", - "/v1/images/variations" - ] - }, - "dall-e-3": { - "deprecation_date": "2026-05-12", - "input_cost_per_image": 0.04, - "litellm_provider": "openai", - "mode": "image_generation", - "supported_endpoints": [ - "/v1/images/generations" - ] - }, "deepseek-chat": { "cache_read_input_token_cost": 2.8e-08, "input_cost_per_token": 2.8e-07, @@ -18839,30 +17566,6 @@ "output_vector_size": 1024, "source": "https://www.databricks.com/product/pricing/foundation-model-serving" }, - "databricks/databricks-claude-3-7-sonnet": { - "cache_creation_input_token_cost": 3.74997e-06, - "cache_read_input_token_cost": 3.0002e-07, - "deprecation_date": "2026-04-12", - "input_cost_per_token": 2.9999900000000002e-06, - "input_dbu_cost_per_token": 4.2857e-05, - "litellm_provider": "databricks", - "max_input_tokens": 200000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 1.5000020000000002e-05, - "output_dbu_cost_per_token": 0.000214286, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_anthropic_thinking_payload": true, - "supports_tool_choice": true - }, "databricks/databricks-claude-fable-5": { "cache_creation_input_token_cost": 1.250004e-05, "cache_read_input_token_cost": 1.00002e-06, @@ -19825,44 +18528,6 @@ "supports_prompt_caching": true, "supports_tool_choice": true }, - "databricks/databricks-gpt-5-1-codex-max": { - "cache_creation_input_token_cost": 1.24999e-06, - "cache_read_input_token_cost": 1.2502e-07, - "deprecation_date": "2026-07-16", - "input_cost_per_token": 1.24999e-06, - "input_dbu_cost_per_token": 1.7857e-05, - "litellm_provider": "databricks", - "max_input_tokens": 272000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 9.999990000000002e-06, - "output_dbu_cost_per_token": 0.000142857, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supports_prompt_caching": true - }, - "databricks/databricks-gpt-5-1-codex-mini": { - "cache_creation_input_token_cost": 2.4997e-07, - "cache_read_input_token_cost": 2.499e-08, - "deprecation_date": "2026-07-16", - "input_cost_per_token": 2.4997e-07, - "input_dbu_cost_per_token": 3.571e-06, - "litellm_provider": "databricks", - "max_input_tokens": 272000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 1.99997e-06, - "output_dbu_cost_per_token": 2.8571e-05, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supports_prompt_caching": true - }, "databricks/databricks-gpt-5-2": { "cache_creation_input_token_cost": 1.75e-06, "cache_read_input_token_cost": 1.75e-07, @@ -19883,25 +18548,6 @@ "supports_prompt_caching": true, "supports_tool_choice": true }, - "databricks/databricks-gpt-5-2-codex": { - "cache_creation_input_token_cost": 1.75e-06, - "cache_read_input_token_cost": 1.75e-07, - "deprecation_date": "2026-07-16", - "input_cost_per_token": 1.75e-06, - "input_dbu_cost_per_token": 2.5e-05, - "litellm_provider": "databricks", - "max_input_tokens": 272000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 1.4e-05, - "output_dbu_cost_per_token": 0.0002, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supports_prompt_caching": true - }, "databricks/databricks-gpt-5-3-codex": { "cache_creation_input_token_cost": 1.75e-06, "cache_read_input_token_cost": 1.75e-07, @@ -20328,25 +18974,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "databricks/databricks-llama-2-70b-chat": { - "cache_creation_input_token_cost": 5.0001e-07, - "cache_read_input_token_cost": 5.0001e-07, - "deprecation_date": "2024-10-30", - "input_cost_per_token": 5.0001e-07, - "input_dbu_cost_per_token": 7.143e-06, - "litellm_provider": "databricks", - "max_input_tokens": 4096, - "max_output_tokens": 4096, - "max_tokens": 4096, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 1.5000300000000002e-06, - "output_dbu_cost_per_token": 2.1429e-05, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving", - "supports_tool_choice": true - }, "databricks/databricks-llama-4-maverick": { "cache_creation_input_token_cost": 5.0001e-07, "cache_read_input_token_cost": 5.0001e-07, @@ -20365,25 +18992,6 @@ "source": "https://www.databricks.com/product/pricing/foundation-model-serving", "supports_tool_choice": true }, - "databricks/databricks-meta-llama-3-1-405b-instruct": { - "cache_creation_input_token_cost": 5.00003e-06, - "cache_read_input_token_cost": 5.00003e-06, - "deprecation_date": "2026-02-15", - "input_cost_per_token": 5.00003e-06, - "input_dbu_cost_per_token": 7.1429e-05, - "litellm_provider": "databricks", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 1.5000020000000002e-05, - "output_dbu_cost_per_token": 0.000214286, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving", - "supports_tool_choice": true - }, "databricks/databricks-meta-llama-3-1-8b-instruct": { "cache_creation_input_token_cost": 1.5001e-07, "cache_read_input_token_cost": 1.5001e-07, @@ -20419,82 +19027,6 @@ "source": "https://www.databricks.com/product/pricing/foundation-model-serving", "supports_tool_choice": true }, - "databricks/databricks-meta-llama-3-70b-instruct": { - "cache_creation_input_token_cost": 1.00002e-06, - "cache_read_input_token_cost": 1.00002e-06, - "deprecation_date": "2024-07-23", - "input_cost_per_token": 1.00002e-06, - "input_dbu_cost_per_token": 1.4286e-05, - "litellm_provider": "databricks", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 2.9999900000000002e-06, - "output_dbu_cost_per_token": 4.2857e-05, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving", - "supports_tool_choice": true - }, - "databricks/databricks-mixtral-8x7b-instruct": { - "cache_creation_input_token_cost": 5.0001e-07, - "cache_read_input_token_cost": 5.0001e-07, - "deprecation_date": "2025-04-30", - "input_cost_per_token": 5.0001e-07, - "input_dbu_cost_per_token": 7.143e-06, - "litellm_provider": "databricks", - "max_input_tokens": 4096, - "max_output_tokens": 4096, - "max_tokens": 4096, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 1.00002e-06, - "output_dbu_cost_per_token": 1.4286e-05, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving", - "supports_tool_choice": true - }, - "databricks/databricks-mpt-30b-instruct": { - "cache_creation_input_token_cost": 1.00002e-06, - "cache_read_input_token_cost": 1.00002e-06, - "deprecation_date": "2024-08-30", - "input_cost_per_token": 1.00002e-06, - "input_dbu_cost_per_token": 1.4286e-05, - "litellm_provider": "databricks", - "max_input_tokens": 8192, - "max_output_tokens": 8192, - "max_tokens": 8192, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 1.00002e-06, - "output_dbu_cost_per_token": 1.4286e-05, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving", - "supports_tool_choice": true - }, - "databricks/databricks-mpt-7b-instruct": { - "cache_creation_input_token_cost": 5.0001e-07, - "cache_read_input_token_cost": 5.0001e-07, - "deprecation_date": "2024-08-30", - "input_cost_per_token": 5.0001e-07, - "input_dbu_cost_per_token": 7.143e-06, - "litellm_provider": "databricks", - "max_input_tokens": 8192, - "max_output_tokens": 8192, - "max_tokens": 8192, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 0.0, - "output_dbu_cost_per_token": 0.0, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving", - "supports_tool_choice": true - }, "databricks/databricks-qwen35-122b-a10b": { "cache_creation_input_token_cost": 2.2001e-07, "cache_read_input_token_cost": 2.2001e-07, @@ -21559,18 +20091,6 @@ "supports_tool_choice": true, "supports_function_calling": true }, - "deepinfra/google/gemini-2.0-flash-001": { - "deprecation_date": "2026-06-01", - "max_tokens": 1000000, - "max_input_tokens": 1000000, - "max_output_tokens": 1000000, - "input_cost_per_token": 1e-07, - "output_cost_per_token": 4e-07, - "litellm_provider": "deepinfra", - "mode": "chat", - "supports_tool_choice": true, - "supports_function_calling": true - }, "deepinfra/google/gemini-2.5-flash": { "max_tokens": 1000000, "max_input_tokens": 1000000, @@ -22429,15 +20949,6 @@ "/v1/audio/speech" ] }, - "embed-english-light-v2.0": { - "deprecation_date": "2026-04-04", - "input_cost_per_token": 1e-07, - "litellm_provider": "cohere", - "max_input_tokens": 1024, - "max_tokens": 1024, - "mode": "embedding", - "output_cost_per_token": 0.0 - }, "embed-english-light-v3.0": { "input_cost_per_token": 1e-07, "litellm_provider": "cohere", @@ -22446,15 +20957,6 @@ "mode": "embedding", "output_cost_per_token": 0.0 }, - "embed-english-v2.0": { - "deprecation_date": "2026-04-04", - "input_cost_per_token": 1e-07, - "litellm_provider": "cohere", - "max_input_tokens": 4096, - "max_tokens": 4096, - "mode": "embedding", - "output_cost_per_token": 0.0 - }, "embed-english-v3.0": { "input_cost_per_image": 0.0001, "input_cost_per_token": 1e-07, @@ -22469,15 +20971,6 @@ "supports_embedding_image_input": true, "supports_image_input": true }, - "embed-multilingual-v2.0": { - "deprecation_date": "2026-04-04", - "input_cost_per_token": 1e-07, - "litellm_provider": "cohere", - "max_input_tokens": 768, - "max_tokens": 768, - "mode": "embedding", - "output_cost_per_token": 0.0 - }, "embed-multilingual-v3.0": { "input_cost_per_token": 1e-07, "litellm_provider": "cohere", @@ -22645,23 +21138,6 @@ "cache_read_input_token_cost": 3e-07, "cache_creation_input_token_cost": 3.75e-06 }, - "eu.anthropic.claude-3-haiku-20240307-v1:0": { - "deprecation_date": "2026-09-10", - "input_cost_per_token": 2.5e-07, - "litellm_provider": "bedrock", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.25e-06, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "cache_read_input_token_cost": 2.5e-08, - "cache_creation_input_token_cost": 3.125e-07 - }, "eu.anthropic.claude-3-opus-20240229-v1:0": { "input_cost_per_token": 1.5e-05, "litellm_provider": "bedrock", @@ -22677,23 +21153,6 @@ "cache_read_input_token_cost": 1.5e-06, "cache_creation_input_token_cost": 1.875e-05 }, - "eu.anthropic.claude-3-sonnet-20240229-v1:0": { - "deprecation_date": "2026-07-30", - "input_cost_per_token": 3e-06, - "litellm_provider": "bedrock", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.5e-05, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true, - "cache_read_input_token_cost": 3e-07, - "cache_creation_input_token_cost": 3.75e-06 - }, "eu.anthropic.claude-opus-4-1-20250805-v1:0": { "cache_creation_input_token_cost": 1.875e-05, "cache_read_input_token_cost": 1.5e-06, @@ -25265,26 +23724,6 @@ "supports_tool_choice": true, "supports_vision": false }, - "fireworks_ai/accounts/fireworks/models/deepseek-v4-pro": { - "cache_read_input_token_cost": 6e-07, - "cache_read_input_token_cost_priority": 6e-07, - "deprecation_date": "2026-08-27", - "input_cost_per_token": 1.2e-06, - "input_cost_per_token_priority": 1.2e-06, - 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"output_cost_per_token_batches": 3e-07, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", - "supported_modalities": [ - "text", - "image", - "audio", - "video" - ], - "supported_output_modalities": [ - "text", - "image" - ], - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_url_context": true, - "supports_vision": true, - "supports_web_search": true, - "search_context_cost_per_query": { - "search_context_size_low": 0.035, - "search_context_size_medium": 0.035, - "search_context_size_high": 0.035 - } - }, - "gemini-2.0-flash-001": { - "cache_read_input_token_cost": 3.75e-08, - "deprecation_date": "2026-06-01", - "input_cost_per_audio_token": 1e-06, - "input_cost_per_token": 1.5e-07, - "litellm_provider": "vertex_ai-language-models", - 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} - }, - "gemini-2.0-flash-lite-001": { - "cache_read_input_token_cost": 1.875e-08, - "deprecation_date": "2026-06-01", - "input_cost_per_audio_token": 7.5e-08, - "input_cost_per_token": 7.5e-08, - "litellm_provider": "vertex_ai-language-models", - "max_input_tokens": 1048576, - "max_output_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 3e-07, - "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#gemini-2.0-flash", - "supported_modalities": [ - "text", - "image", - "audio", - "video" - ], - "supported_output_modalities": [ - "text" - ], - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": true, - "search_context_cost_per_query": { - "search_context_size_low": 0.035, - "search_context_size_medium": 0.035, - "search_context_size_high": 0.035 - } - }, "gemini-2.5-flash": { "cache_read_input_audio_token_cost": 1e-07, "deprecation_date": "2026-10-20", @@ -27503,53 +25703,6 @@ }, "gemini_native_audio": true }, - "gemini-2.5-flash-lite-preview-06-17": { - "deprecation_date": "2025-11-18", - "cache_read_input_token_cost": 1e-08, - "input_cost_per_audio_token": 5e-07, - "input_cost_per_token": 1e-07, - "litellm_provider": "vertex_ai-language-models", - "max_input_tokens": 1048576, - "max_output_tokens": 65535, - "max_tokens": 65535, - "mode": "chat", - "output_cost_per_reasoning_token": 4e-07, - "output_cost_per_token": 4e-07, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/completions", - "/v1/batch" - ], - "supported_modalities": [ - "text", - "image", - "audio", - "video" - ], - "supported_output_modalities": [ - "text" - ], - "supports_audio_output": false, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_url_context": true, - "supports_vision": true, - "supports_web_search": true, - "search_context_cost_per_query": { - "search_context_size_low": 0.035, - "search_context_size_medium": 0.035, - "search_context_size_high": 0.035 - }, - "google_maps_grounding_cost_per_query": 0.025, - "supports_image_size": false - }, "gemini-2.5-pro": { "deprecation_date": "2026-10-20", "cache_read_input_token_cost": 1.25e-07, @@ -27608,62 +25761,6 @@ "output_cost_per_token_flex": 5e-06, "output_cost_per_token_priority": 1.8e-05 }, - "gemini-3-pro-preview": { - "deprecation_date": "2026-03-26", - "cache_read_input_token_cost": 2e-07, - "cache_read_input_token_cost_above_200k_tokens": 4e-07, - "cache_creation_input_token_cost_above_200k_tokens": 2.5e-07, - "input_cost_per_token": 2e-06, - "input_cost_per_token_above_200k_tokens": 4e-06, - 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"gemini/gemini-robotics-er-1.6-preview": { - "deprecation_date": "2026-08-31", - "input_cost_per_audio_token": 2e-06, - "input_cost_per_token": 1e-06, - "litellm_provider": "gemini", - "max_input_tokens": 131072, - "max_output_tokens": 65536, - "max_tokens": 65536, - "mode": "chat", - "output_cost_per_reasoning_token": 5e-06, - "output_cost_per_token": 5e-06, - "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://ai.google.dev/gemini-api/docs/pricing#gemini-robotics-er", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/completions", - "/v1/batch" - ], - "supported_modalities": [ - "text", - "image", - "audio", - "video" - ], - "supported_output_modalities": [ - "text" - ], - "supports_audio_input": true, - "supports_audio_output": false, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_url_context": true, - "supports_video_input": true, - "supports_vision": true, - "supports_web_search": true, - "web_search_billing_unit": "per_query" - }, "gemini-2.5-computer-use-preview-10-2025": { "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, @@ -28600,27 +26605,6 @@ "source": "https://ai.google.dev/gemini-api/docs/embeddings#model-versions", "tpm": 10000000 }, - "gemini/gemini-embedding-2-preview": { - "deprecation_date": "2026-08-10", - "input_cost_per_audio_token": 6.5e-06, - "input_cost_per_audio_token_batches": 3.25e-06, - "input_cost_per_image_token": 4.5e-07, - "input_cost_per_image_token_batches": 2.25e-07, - "input_cost_per_token": 2e-07, - "input_cost_per_token_batches": 1e-07, - "input_cost_per_video_token": 1.2e-05, - "input_cost_per_video_token_batches": 6e-06, - "litellm_provider": "gemini", - 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"/v1/batch" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text", - "image" - ], - "supports_function_calling": false, - "supports_prompt_caching": true, - "supports_reasoning": false, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_vision": true, - "supports_web_search": true, - "search_context_cost_per_query": { - "search_context_size_low": 0.014, - "search_context_size_medium": 0.014, - "search_context_size_high": 0.014 - }, - "web_search_billing_unit": "per_query" - }, "gemini/gemini-3.1-flash-lite-image": { "input_cost_per_image": 0.00028, "input_cost_per_token": 2.5e-07, @@ -29244,104 +27012,6 @@ "supports_audio_input": true, "supports_image_size": false }, - "gemini/gemini-2.5-flash-lite-preview-09-2025": { - "cache_read_input_token_cost": 1e-08, - "deprecation_date": "2026-03-31", - "input_cost_per_audio_token": 3e-07, - "input_cost_per_token": 1e-07, - "litellm_provider": "gemini", - "max_input_tokens": 1048576, - 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"search_context_size_medium": 0.035, - "search_context_size_high": 0.035 - }, - "google_maps_grounding_cost_per_query": 0.025, - "supports_image_size": false - }, - "gemini/gemini-2.5-flash-preview-09-2025": { - "cache_read_input_token_cost": 3e-08, - "deprecation_date": "2026-02-17", - "input_cost_per_audio_token": 1e-06, - "input_cost_per_token": 3e-07, - "litellm_provider": "gemini", - "max_input_tokens": 1048576, - "max_output_tokens": 65535, - "max_tokens": 65535, - "mode": "chat", - "output_cost_per_reasoning_token": 2.5e-06, - "output_cost_per_token": 2.5e-06, - "rpm": 15, - "source": "https://ai.google.dev/gemini-api/docs/pricing", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/completions", - "/v1/batch" - ], - "supported_modalities": [ - "text", - "image", - "audio", - "video" - ], - "supported_output_modalities": [ - "text" - ], - "supports_audio_output": false, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_url_context": true, - "supports_vision": true, - "supports_web_search": true, - "tpm": 250000, - "search_context_cost_per_query": { - "search_context_size_low": 0.035, - "search_context_size_medium": 0.035, - "search_context_size_high": 0.035 - }, - "google_maps_grounding_cost_per_query": 0.025, - "supports_image_size": false - }, "gemini/gemini-flash-latest": { "cache_read_input_token_cost": 7.5e-08, "input_cost_per_token": 7.5e-07, @@ -29459,55 +27129,6 @@ "supports_video_input": true, "web_search_billing_unit": "per_query" }, - "gemini/gemini-2.5-flash-lite-preview-06-17": { - "deprecation_date": "2025-11-18", - "cache_read_input_token_cost": 1e-08, - "input_cost_per_audio_token": 5e-07, - "input_cost_per_token": 1e-07, - "litellm_provider": "gemini", - "max_input_tokens": 1048576, - "max_output_tokens": 65535, - "max_tokens": 65535, - "mode": "chat", - "output_cost_per_reasoning_token": 4e-07, - "output_cost_per_token": 4e-07, - "rpm": 15, - "source": "https://ai.google.dev/gemini-api/docs/pricing", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/completions", - "/v1/batch" - ], - "supported_modalities": [ - "text", - "image", - "audio", - "video" - ], - "supported_output_modalities": [ - "text" - ], - "supports_audio_output": false, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_url_context": true, - "supports_vision": true, - "supports_web_search": true, - "tpm": 250000, - "search_context_cost_per_query": { - "search_context_size_low": 0.035, - "search_context_size_medium": 0.035, - "search_context_size_high": 0.035 - }, - "google_maps_grounding_cost_per_query": 0.025, - "supports_image_size": false - }, "gemini/gemini-2.5-flash-preview-tts": { "input_cost_per_token": 5e-07, "input_cost_per_token_batches": 2.5e-07, @@ -29618,114 +27239,6 @@ "supports_vision": true, "tpm": 800000 }, - "gemini/gemini-3-pro-preview": { - "deprecation_date": "2026-03-09", - "cache_read_input_token_cost": 2e-07, - "cache_read_input_token_cost_above_200k_tokens": 4e-07, - "input_cost_per_token": 2e-06, - "input_cost_per_token_above_200k_tokens": 4e-06, - "input_cost_per_token_batches": 1e-06, - "litellm_provider": "gemini", - "max_input_tokens": 1048576, - "max_output_tokens": 65535, - "max_tokens": 65535, - "mode": "chat", - "output_cost_per_token": 1.2e-05, - "output_cost_per_token_above_200k_tokens": 1.8e-05, - "output_cost_per_token_batches": 6e-06, - "rpm": 2000, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/completions", - "/v1/batch" - ], - "supported_modalities": [ - "text", - "image", - "audio", - "video" - ], - "supported_output_modalities": [ - "text" - ], - "supports_audio_input": true, - "supports_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_video_input": true, - "supports_vision": true, - "supports_web_search": true, - "tpm": 800000, - "input_cost_per_token_priority": 3.6e-06, - "input_cost_per_token_above_200k_tokens_priority": 7.2e-06, - "output_cost_per_token_priority": 2.16e-05, - "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, - "cache_read_input_token_cost_priority": 3.6e-07, - "cache_read_input_token_cost_above_200k_tokens_priority": 7.2e-07, - "search_context_cost_per_query": { - "search_context_size_low": 0.014, - "search_context_size_medium": 0.014, - "search_context_size_high": 0.014 - }, - "web_search_billing_unit": "per_query" - }, - "gemini/gemini-3.1-flash-lite-preview": { - "cache_read_input_token_cost": 2.5e-08, - "deprecation_date": "2026-05-25", - "input_cost_per_audio_token": 5e-07, - "input_cost_per_token": 2.5e-07, - "litellm_provider": "gemini", - "max_input_tokens": 1048576, - "max_output_tokens": 65536, - "max_tokens": 65536, - "mode": "chat", - "output_cost_per_reasoning_token": 1.5e-06, - "output_cost_per_token": 1.5e-06, - "rpm": 15, - "source": "https://ai.google.dev/gemini-api/docs/models", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/completions", - "/v1/batch" - ], - "supported_modalities": [ - "text", - "image", - "audio", - "video" - ], - "supported_output_modalities": [ - "text" - ], - "supports_audio_input": true, - "supports_audio_output": false, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_url_context": true, - "supports_video_input": true, - "supports_vision": true, - "supports_web_search": true, - "supports_native_streaming": true, - "tpm": 250000, - "search_context_cost_per_query": { - "search_context_size_low": 0.014, - "search_context_size_medium": 0.014, - "search_context_size_high": 0.014 - }, - "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 - }, "gemini/gemini-3.1-flash-lite": { "cache_read_input_audio_token_cost": 5e-08, "cache_read_input_token_cost": 2.5e-08, @@ -30826,34 +28339,6 @@ "output_cost_per_image": 0.04, "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing" }, - "gemini/imagen-3.0-generate-002": { - "deprecation_date": "2025-11-10", - "litellm_provider": "gemini", - "mode": "image_generation", - "output_cost_per_image": 0.04, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing" - }, - "gemini/imagen-4.0-fast-generate-001": { - "deprecation_date": "2026-08-17", - "litellm_provider": "gemini", - "mode": "image_generation", - "output_cost_per_image": 0.02, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing" - }, - "gemini/imagen-4.0-generate-001": { - "deprecation_date": "2026-08-17", - "litellm_provider": "gemini", - "mode": "image_generation", - "output_cost_per_image": 0.04, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing" - }, - "gemini/imagen-4.0-ultra-generate-001": { - "deprecation_date": "2026-08-17", - "litellm_provider": "gemini", - "mode": "image_generation", - "output_cost_per_image": 0.06, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing" - }, "gemini/learnlm-1.5-pro-experimental": { "input_cost_per_audio_per_second": 0, "input_cost_per_audio_per_second_above_128k_tokens": 0, @@ -30932,21 +28417,6 @@ "supports_web_search": false, "output_cost_per_image": 0.08 }, - "gemini/veo-2.0-generate-001": { - "deprecation_date": "2026-06-30", - "litellm_provider": "gemini", - "max_input_tokens": 1024, - "max_tokens": 1024, - "mode": "video_generation", - "output_cost_per_second": 0.35, - "source": "https://ai.google.dev/gemini-api/docs/video", - "supported_modalities": [ - "text" - ], - "supported_output_modalities": [ - "video" - ] - }, "gemini/veo-3.1-fast-generate-preview": { "litellm_provider": "gemini", "max_input_tokens": 1024, @@ -32156,33 +29626,6 @@ "supports_system_messages": true, "supports_tool_choice": true }, - "gpt-4-0125-preview": { - "deprecation_date": "2026-03-26", - "input_cost_per_token": 1e-05, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 3e-05, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_prompt_caching": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, - "gpt-4-0314": { - "deprecation_date": "2026-03-26", - "input_cost_per_token": 3e-05, - "litellm_provider": "openai", - "max_input_tokens": 8192, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 6e-05, - "supports_system_messages": true, - "supports_tool_choice": true - }, "gpt-4-0613": { "deprecation_date": "2026-10-23", "input_cost_per_token": 3e-05, @@ -32252,22 +29695,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "gpt-4-turbo-preview": { - "deprecation_date": "2026-03-26", - "input_cost_per_token": 1e-05, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 3e-05, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, "gpt-4.1": { "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_priority": 8.75e-07, @@ -32610,24 +30037,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "gpt-4o-audio-preview": { - "deprecation_date": "2026-05-07", - "input_cost_per_audio_token": 4e-05, - "input_cost_per_token": 2.5e-06, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_audio_token": 8e-05, - "output_cost_per_token": 1e-05, - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, "gpt-4o-audio-preview-2024-12-17": { "deprecation_date": "2027-01-20", "input_cost_per_audio_token": 4e-05, @@ -32812,44 +30221,6 @@ "supports_tool_choice": true, "supports_vision": false }, - "gpt-audio-mini-2025-10-06": { - "deprecation_date": "2026-07-23", - "input_cost_per_audio_token": 1e-05, - "input_cost_per_token": 6e-07, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_audio_token": 2e-05, - "output_cost_per_token": 2.4e-06, - "source": "https://developers.openai.com/api/docs/pricing", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/responses", - "/v1/realtime", - "/v1/batch" - ], - "supported_modalities": [ - "text", - "audio" - ], - "supported_output_modalities": [ - "text", - "audio" - ], - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_prompt_caching": false, - "supports_reasoning": false, - "supports_response_schema": false, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": false - }, "gpt-audio-mini-2025-12-15": { "input_cost_per_audio_token": 1e-05, "input_cost_per_token": 6e-07, @@ -32946,24 +30317,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "gpt-4o-mini-audio-preview": { - "deprecation_date": "2026-05-07", - "input_cost_per_audio_token": 1e-05, - "input_cost_per_token": 1.5e-07, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_audio_token": 2e-05, - "output_cost_per_token": 6e-07, - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, "gpt-4o-mini-audio-preview-2024-12-17": { "deprecation_date": "2027-01-20", "input_cost_per_audio_token": 1e-05, @@ -32982,26 +30335,6 @@ "supports_system_messages": true, "supports_tool_choice": true }, - "gpt-4o-mini-realtime-preview": { - "cache_creation_input_audio_token_cost": 3e-07, - "cache_read_input_token_cost": 3e-07, - "deprecation_date": "2026-05-07", - "input_cost_per_audio_token": 1e-05, - "input_cost_per_token": 6e-07, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "realtime", - "output_cost_per_audio_token": 2e-05, - "output_cost_per_token": 2.4e-06, - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, "gpt-4o-mini-realtime-preview-2024-12-17": { "cache_creation_input_audio_token_cost": 3e-07, "cache_read_input_token_cost": 3e-07, @@ -33048,32 +30381,6 @@ "supports_vision": true, "supports_web_search": true }, - "gpt-4o-mini-search-preview-2025-03-11": { - "cache_read_input_token_cost": 7.5e-08, - "deprecation_date": "2026-07-23", - "input_cost_per_token": 1.5e-07, - "input_cost_per_token_batches": 7.5e-08, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 6e-07, - "output_cost_per_token_batches": 3e-07, - "search_context_cost_per_query": { - "search_context_size_high": 0.025, - "search_context_size_low": 0.025, - "search_context_size_medium": 0.025 - }, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, "gpt-4o-mini-transcribe": { "input_cost_per_audio_token": 1.25e-06, "input_cost_per_token": 1.25e-06, @@ -33108,63 +30415,6 @@ "audio" ] }, - "gpt-4o-realtime-preview": { - "cache_read_input_token_cost": 2.5e-06, - "deprecation_date": "2026-05-07", - "input_cost_per_audio_token": 4e-05, - "input_cost_per_token": 5e-06, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "realtime", - "output_cost_per_audio_token": 8e-05, - "output_cost_per_token": 2e-05, - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, - "gpt-4o-realtime-preview-2024-12-17": { - "cache_read_input_token_cost": 2.5e-06, - "deprecation_date": "2026-05-07", - "input_cost_per_audio_token": 4e-05, - "input_cost_per_token": 5e-06, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "realtime", - "output_cost_per_audio_token": 8e-05, - "output_cost_per_token": 2e-05, - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, - "gpt-4o-realtime-preview-2025-06-03": { - "cache_read_input_token_cost": 2.5e-06, - "deprecation_date": "2026-05-07", - "input_cost_per_audio_token": 4e-05, - "input_cost_per_token": 5e-06, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "realtime", - "output_cost_per_audio_token": 8e-05, - "output_cost_per_token": 2e-05, - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, "gpt-4o-search-preview": { "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 2.5e-06, @@ -33191,32 +30441,6 @@ "supports_vision": true, "supports_web_search": true }, - "gpt-4o-search-preview-2025-03-11": { - "cache_read_input_token_cost": 1.25e-06, - "deprecation_date": "2026-07-23", - "input_cost_per_token": 2.5e-06, - "input_cost_per_token_batches": 1.25e-06, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 1e-05, - "output_cost_per_token_batches": 5e-06, - "search_context_cost_per_query": { - "search_context_size_high": 0.025, - "search_context_size_low": 0.025, - "search_context_size_medium": 0.025 - }, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, "gpt-4o-transcribe": { "input_cost_per_audio_token": 2.5e-06, "input_cost_per_token": 2.5e-06, @@ -33879,52 +31103,6 @@ "supports_xhigh_reasoning_effort": false, "supports_minimal_reasoning_effort": false }, - "gpt-5.1-chat-latest": { - "cache_read_input_token_cost": 1.25e-07, - "cache_read_input_token_cost_priority": 2.5e-07, - "deprecation_date": "2026-07-23", - "input_cost_per_token": 1.25e-06, - "input_cost_per_token_priority": 2.5e-06, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 1e-05, - "output_cost_per_token_priority": 2e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text", - "image" - ], - "supports_function_calling": false, - "supports_native_streaming": true, - "supports_parallel_function_calling": false, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": false, - "supports_vision": true, - "supports_web_search": true, - "supports_none_reasoning_effort": true, - "default_reasoning_effort": "none", - "supports_xhigh_reasoning_effort": false, - "supports_minimal_reasoning_effort": true - }, "gpt-5.2": { "cache_read_input_token_cost": 1.75e-07, "cache_read_input_token_cost_batches": 8.75e-08, @@ -34031,94 +31209,6 @@ "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false }, - "gpt-5.2-chat-latest": { - "cache_read_input_token_cost": 1.75e-07, - "cache_read_input_token_cost_priority": 3.5e-07, - "deprecation_date": "2026-08-10", - "input_cost_per_token": 1.75e-06, - "input_cost_per_token_priority": 3.5e-06, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 1.4e-05, - "output_cost_per_token_priority": 2.8e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": true, - "supports_none_reasoning_effort": false, - "supports_xhigh_reasoning_effort": false, - "supports_minimal_reasoning_effort": true - }, - "gpt-5.3-chat-latest": { - "cache_read_input_token_cost": 1.75e-07, - "cache_read_input_token_cost_priority": 3.5e-07, - "deprecation_date": "2026-08-10", - "input_cost_per_token": 1.75e-06, - "input_cost_per_token_priority": 3.5e-06, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 1.4e-05, - "output_cost_per_token_priority": 2.8e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": true, - "supports_none_reasoning_effort": false, - "supports_xhigh_reasoning_effort": false, - "supports_minimal_reasoning_effort": true - }, "gpt-5.2-pro": { "input_cost_per_token": 2.1e-05, "input_cost_per_token_batches": 1.05e-05, @@ -35783,251 +32873,6 @@ "supports_xhigh_reasoning_effort": false, "supports_minimal_reasoning_effort": true }, - "gpt-5-chat-latest": { - "cache_read_input_token_cost": 1.25e-07, - "deprecation_date": "2026-07-23", - "input_cost_per_token": 1.25e-06, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 1e-05, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/batch", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": false, - "supports_native_streaming": true, - "supports_parallel_function_calling": false, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": false, - "supports_vision": true, - "supports_none_reasoning_effort": false, - "supports_xhigh_reasoning_effort": false, - "supports_minimal_reasoning_effort": true - }, - "gpt-5-codex": { - "cache_read_input_token_cost": 1.25e-07, - "deprecation_date": "2026-07-23", - "input_cost_per_token": 1.25e-06, - "litellm_provider": "openai", - "max_input_tokens": 272000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "responses", - "output_cost_per_token": 1e-05, - 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"input_cost_per_token_priority": 2.5e-06, - "litellm_provider": "openai", - "max_input_tokens": 272000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "responses", - "output_cost_per_token": 1e-05, - "output_cost_per_token_priority": 2e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supported_endpoints": [ - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": false, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": true, - "supports_none_reasoning_effort": false, - "supports_xhigh_reasoning_effort": false, - "supports_minimal_reasoning_effort": true - }, - "gpt-5.1-codex-max": { - "cache_read_input_token_cost": 1.25e-07, - "deprecation_date": "2026-07-23", - "input_cost_per_token": 1.25e-06, - "litellm_provider": "openai", - "max_input_tokens": 272000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "responses", - "output_cost_per_token": 1e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supported_endpoints": [ - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": false, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": true, - "supports_none_reasoning_effort": false, - "supports_xhigh_reasoning_effort": true, - "supports_minimal_reasoning_effort": true - }, - "gpt-5.1-codex-mini": { - "cache_read_input_token_cost": 2.5e-08, - "cache_read_input_token_cost_priority": 4.5e-08, - "deprecation_date": "2026-07-23", - "input_cost_per_token": 2.5e-07, - "input_cost_per_token_priority": 4.5e-07, - "litellm_provider": "openai", - "max_input_tokens": 272000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "responses", - "output_cost_per_token": 2e-06, - "output_cost_per_token_priority": 3.6e-06, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supported_endpoints": [ - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": false, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": true, - "supports_none_reasoning_effort": false, - "supports_xhigh_reasoning_effort": false, - "supports_minimal_reasoning_effort": true - }, - "gpt-5.2-codex": { - "cache_read_input_token_cost": 1.75e-07, - "cache_read_input_token_cost_priority": 3.5e-07, - "deprecation_date": "2026-07-23", - "input_cost_per_token": 1.75e-06, - "input_cost_per_token_priority": 3.5e-06, - "litellm_provider": "openai", - "max_input_tokens": 272000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "responses", - "output_cost_per_token": 1.4e-05, - "output_cost_per_token_priority": 2.8e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supported_endpoints": [ - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": false, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": true, - "supports_none_reasoning_effort": false, - "supports_xhigh_reasoning_effort": true, - "supports_minimal_reasoning_effort": true - }, "gpt-5.3-codex": { "cache_read_input_token_cost": 1.75e-07, "cache_read_input_token_cost_priority": 3.5e-07, @@ -36870,32 +33715,6 @@ "supports_response_schema": true, "supports_vision": true }, - "groq/llama-3.1-8b-instant": { - "deprecation_date": "2026-08-16", - "input_cost_per_token": 5e-08, - "litellm_provider": "groq", - "max_input_tokens": 131072, - "max_output_tokens": 131072, - "max_tokens": 131072, - "mode": "chat", - "output_cost_per_token": 8e-08, - "supports_function_calling": true, - "supports_response_schema": false, - "supports_tool_choice": true - }, - "groq/llama-3.3-70b-versatile": { - "deprecation_date": "2026-08-16", - "input_cost_per_token": 5.9e-07, - "litellm_provider": "groq", - "max_input_tokens": 131072, - "max_output_tokens": 32768, - "max_tokens": 32768, - "mode": "chat", - "output_cost_per_token": 7.9e-07, - "supports_function_calling": true, - "supports_response_schema": false, - "supports_tool_choice": true - }, "groq/llama-guard-3-8b": { "input_cost_per_token": 2e-07, "litellm_provider": "groq", @@ -36905,19 +33724,6 @@ "output_cost_per_token": 2e-07, "source": "https://console.groq.com/docs/model/llama-guard-3-8b" }, - "groq/gemma-7b-it": { - "deprecation_date": "2024-12-18", - "input_cost_per_token": 5e-08, - "litellm_provider": "groq", - "max_input_tokens": 8192, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 8e-08, - "supports_function_calling": true, - "supports_response_schema": false, - "supports_tool_choice": true - }, "groq/meta-llama/llama-prompt-guard-2-22m": { "input_cost_per_token": 3e-08, "litellm_provider": "groq", @@ -36938,58 +33744,6 @@ "output_cost_per_token": 4e-08, "source": "https://console.groq.com/docs/model/meta-llama/llama-prompt-guard-2-86m" }, - "groq/meta-llama/llama-guard-4-12b": { - "deprecation_date": "2026-03-05", - "input_cost_per_token": 2e-07, - "litellm_provider": "groq", - "max_input_tokens": 8192, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 2e-07 - }, - "groq/meta-llama/llama-4-maverick-17b-128e-instruct": { - "deprecation_date": "2026-03-09", - "input_cost_per_token": 2e-07, - "litellm_provider": "groq", - "max_input_tokens": 131072, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 6e-07, - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "groq/meta-llama/llama-4-scout-17b-16e-instruct": { - "deprecation_date": "2026-07-17", - "input_cost_per_token": 1.1e-07, - "litellm_provider": "groq", - "max_input_tokens": 131072, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 3.4e-07, - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "groq/moonshotai/kimi-k2-instruct-0905": { - "deprecation_date": "2026-04-15", - "input_cost_per_token": 1e-06, - "output_cost_per_token": 3e-06, - "cache_read_input_token_cost": 5e-07, - "litellm_provider": "groq", - "max_input_tokens": 262144, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, "groq/openai/gpt-oss-120b": { "cache_read_input_token_cost": 7.5e-08, "input_cost_per_token": 1.5e-07, @@ -37070,45 +33824,6 @@ "mode": "audio_speech", "source": "https://console.groq.com/docs/models" }, - "groq/playai-tts": { - "deprecation_date": "2025-12-31", - "input_cost_per_character": 5e-05, - "litellm_provider": "groq", - "max_input_tokens": 10000, - "max_output_tokens": 10000, - "max_tokens": 10000, - "mode": "audio_speech" - }, - "groq/qwen/qwen3.6-27b": { - "input_cost_per_token": 6e-07, - "litellm_provider": "groq", - "max_input_tokens": 131072, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 3e-06, - "source": "https://console.groq.com/docs/model/qwen/qwen3.6-27b", - "deprecation_date": "2026-09-14", - "supports_function_calling": true, - "supports_reasoning": true, - "supports_response_schema": false, - "supports_tool_choice": true, - "supports_vision": true - }, - "groq/qwen/qwen3-32b": { - "deprecation_date": "2026-07-17", - "input_cost_per_token": 2.9e-07, - "litellm_provider": "groq", - "max_input_tokens": 131000, - "max_output_tokens": 131000, - "max_tokens": 131000, - "mode": "chat", - "output_cost_per_token": 5.9e-07, - "supports_function_calling": true, - "supports_reasoning": true, - "supports_response_schema": false, - "supports_tool_choice": true - }, "groq/whisper-large-v3": { "input_cost_per_second": 3.083e-05, "litellm_provider": "groq", @@ -37121,27 +33836,6 @@ "mode": "audio_transcription", "output_cost_per_second": 0.0 }, - "hd/1024-x-1024/dall-e-3": { - "deprecation_date": "2026-05-12", - "input_cost_per_pixel": 7.629e-08, - "litellm_provider": "openai", - "mode": "image_generation", - "output_cost_per_pixel": 0.0 - }, - "hd/1024-x-1792/dall-e-3": { - "deprecation_date": "2026-05-12", - "input_cost_per_pixel": 6.539e-08, - "litellm_provider": "openai", - "mode": "image_generation", - "output_cost_per_pixel": 0.0 - }, - "hd/1792-x-1024/dall-e-3": { - "deprecation_date": "2026-05-12", - "input_cost_per_pixel": 6.539e-08, - "litellm_provider": "openai", - "mode": "image_generation", - "output_cost_per_pixel": 0.0 - }, "heroku/claude-3-5-haiku": { "litellm_provider": "heroku", "max_tokens": 8192, @@ -38968,19 +35662,6 @@ "supports_system_messages": true, "supports_native_structured_output": true }, - "mistral/codestral-2405": { - "deprecation_date": "2025-06-16", - "input_cost_per_token": 1e-06, - "litellm_provider": "mistral", - "max_input_tokens": 32000, - "max_output_tokens": 8191, - "max_tokens": 8191, - "mode": "chat", - "output_cost_per_token": 3e-06, - "supports_assistant_prefill": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, "mistral/codestral-2508": { "cache_read_input_token_cost": 3e-08, "input_cost_per_token": 3e-07, @@ -39024,51 +35705,6 @@ "supports_assistant_prefill": true, "supports_tool_choice": true }, - "mistral/devstral-medium-2507": { - "deprecation_date": "2026-05-31", - "input_cost_per_token": 4e-07, - "litellm_provider": "mistral", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 2e-06, - "source": "https://mistral.ai/news/devstral", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, - "mistral/devstral-small-2505": { - "deprecation_date": "2025-11-30", - "input_cost_per_token": 1e-07, - "litellm_provider": "mistral", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 3e-07, - "source": "https://mistral.ai/news/devstral", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, - "mistral/devstral-small-2507": { - "deprecation_date": "2026-05-31", - "input_cost_per_token": 1e-07, - "litellm_provider": "mistral", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 3e-07, - "source": "https://mistral.ai/news/devstral", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, "mistral/devstral-small-latest": { "cache_read_input_token_cost": 1e-08, "input_cost_per_token": 1e-07, @@ -39084,21 +35720,6 @@ "supports_response_schema": true, "supports_tool_choice": true }, - "mistral/labs-devstral-small-2512": { - "deprecation_date": "2026-03-31", - "input_cost_per_token": 1e-07, - "litellm_provider": "mistral", - "max_input_tokens": 256000, - "max_output_tokens": 256000, - "max_tokens": 256000, - "mode": "chat", - "output_cost_per_token": 3e-07, - "source": "https://docs.mistral.ai/models/devstral-small-2-25-12", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, "mistral/devstral-latest": { "cache_read_input_token_cost": 4e-08, "input_cost_per_token": 4e-07, @@ -39129,21 +35750,6 @@ "supports_response_schema": true, "supports_tool_choice": true }, - "mistral/devstral-2512": { - "deprecation_date": "2026-07-31", - "input_cost_per_token": 4e-07, - "litellm_provider": "mistral", - "max_input_tokens": 256000, - "max_output_tokens": 256000, - "max_tokens": 256000, - "mode": "chat", - "output_cost_per_token": 2e-06, - "source": "https://mistral.ai/news/devstral-2-vibe-cli", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, "mistral/ministral-14b-2512": { "input_cost_per_token": 2e-07, "litellm_provider": "mistral", @@ -39419,54 +36025,6 @@ "supports_response_schema": true, "supports_tool_choice": true }, - "mistral/magistral-medium-2506": { - "deprecation_date": "2025-11-30", - "input_cost_per_token": 2e-06, - "litellm_provider": "mistral", - "max_input_tokens": 40000, - "max_output_tokens": 40000, - "max_tokens": 40000, - "mode": "chat", - "output_cost_per_token": 5e-06, - "source": "https://mistral.ai/news/magistral", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, - "mistral/magistral-medium-2509": { - "deprecation_date": "2026-07-31", - "input_cost_per_token": 2e-06, - "litellm_provider": "mistral", - "max_input_tokens": 40000, - "max_output_tokens": 40000, - 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"litellm_provider": "mistral", - "ocr_cost_per_page": 0.001, - "ocr_cost_per_page_batches": 0.0005, - "annotation_cost_per_page": 0.003, - "annotation_cost_per_page_batches": 0.0015, - "mode": "ocr", - "supported_endpoints": [ - "/v1/ocr", - "/v1/batch" - ], - "source": "https://mistral.ai/pricing#api-pricing" - }, "mistral/mistral-ocr-2512": { "litellm_provider": "mistral", "ocr_cost_per_page": 0.002, @@ -39550,22 +36094,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "mistral/magistral-small-2506": { - "deprecation_date": "2025-11-30", - "input_cost_per_token": 5e-07, - "litellm_provider": "mistral", - "max_input_tokens": 40000, - "max_output_tokens": 40000, - "max_tokens": 40000, - "mode": "chat", - "output_cost_per_token": 1.5e-06, - "source": "https://mistral.ai/pricing#api-pricing", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, "mistral/magistral-small-latest": { "cache_read_input_token_cost": 1.5e-08, "input_cost_per_token": 1.5e-07, @@ -39583,22 +36111,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "mistral/magistral-small-1-2-2509": { - "deprecation_date": "2026-07-31", - "input_cost_per_token": 5e-07, - "litellm_provider": "mistral", - "max_input_tokens": 40000, - "max_output_tokens": 40000, - "max_tokens": 40000, - "mode": "chat", - "output_cost_per_token": 1.5e-06, - "source": "https://mistral.ai/pricing#api-pricing", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, "mistral/mistral-embed": { "input_cost_per_token": 1e-07, "litellm_provider": "mistral", @@ -39622,48 +36134,6 @@ "max_tokens": 8192, "mode": "embedding" }, - "mistral/mistral-large-2402": { - "deprecation_date": "2025-06-16", - "input_cost_per_token": 4e-06, - "litellm_provider": "mistral", - "max_input_tokens": 32000, - "max_output_tokens": 8191, - "max_tokens": 8191, - "mode": "chat", - "output_cost_per_token": 1.2e-05, - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, - "mistral/mistral-large-2407": { - "deprecation_date": "2025-03-30", - "input_cost_per_token": 3e-06, - "litellm_provider": "mistral", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 9e-06, - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, - "mistral/mistral-large-2411": { - "deprecation_date": "2026-05-31", - "input_cost_per_token": 2e-06, - "litellm_provider": "mistral", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 6e-06, - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, "mistral/mistral-large-latest": { "cache_read_input_token_cost": 5e-08, "input_cost_per_token": 5e-07, @@ -39733,49 +36203,6 @@ "supports_tool_choice": true, "supports_vision": true }, - 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"mode": "chat", - "output_cost_per_token": 2e-06, - "source": "https://mistral.ai/news/mistral-medium-3", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true - }, "mistral/mistral-medium-2604": { "cache_read_input_token_cost": 1.5e-07, "input_cost_per_token": 1.5e-06, @@ -39818,22 +36245,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "mistral/mistral-medium-3-1-2508": { - "deprecation_date": "2026-08-31", - "input_cost_per_token": 4e-07, - "litellm_provider": "mistral", - "max_input_tokens": 131072, - "max_output_tokens": 131072, - "max_tokens": 131072, - "mode": "chat", - "output_cost_per_token": 2e-06, - "source": "https://mistral.ai/news/mistral-medium-3", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true - }, "mistral/mistral-medium-3-5": { "cache_read_input_token_cost": 1.5e-07, "input_cost_per_token": 1.5e-06, @@ -39890,22 +36301,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "mistral/mistral-small-3-2-2506": { - "deprecation_date": "2026-07-31", - "input_cost_per_token": 6e-08, - "litellm_provider": "mistral", - "max_input_tokens": 131072, - "max_output_tokens": 131072, - "max_tokens": 131072, - "mode": "chat", - "output_cost_per_token": 1.8e-07, - "source": "https://mistral.ai/pricing", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_response_schema": true, - "supports_tool_choice": true, - "supports_vision": true - }, "mistral/ministral-3-3b-2512": { "cache_read_input_token_cost": 1e-08, "input_cost_per_token": 1e-07, @@ -39999,32 +36394,6 @@ "supports_response_schema": true, "supports_tool_choice": true }, - "mistral/open-codestral-mamba": { - "deprecation_date": "2025-06-06", - "input_cost_per_token": 2.5e-07, - "litellm_provider": "mistral", - "max_input_tokens": 256000, - "max_output_tokens": 256000, - "max_tokens": 256000, - "mode": "chat", - "output_cost_per_token": 2.5e-07, - "source": "https://mistral.ai/technology/", - "supports_assistant_prefill": true, - "supports_tool_choice": true - }, - "mistral/open-mistral-7b": { - "deprecation_date": "2025-03-30", - "input_cost_per_token": 2.5e-07, - "litellm_provider": "mistral", - "max_input_tokens": 32000, - "max_output_tokens": 8191, - "max_tokens": 8191, - "mode": "chat", - "output_cost_per_token": 2.5e-07, - "supports_assistant_prefill": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, "mistral/open-mistral-nemo": { "cache_read_input_token_cost": 3e-08, "input_cost_per_token": 3e-07, @@ -40039,78 +36408,6 @@ "supports_response_schema": true, "supports_tool_choice": true }, - "mistral/open-mistral-nemo-2407": { - "deprecation_date": "2026-07-31", - "input_cost_per_token": 3e-07, - "litellm_provider": "mistral", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 3e-07, - "source": "https://mistral.ai/technology/", - "supports_assistant_prefill": true, - 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"cache_read_input_token_cost": 1.5e-07, - "deprecation_date": "2026-05-25", - "input_cost_per_token": 6e-07, - "litellm_provider": "moonshot", - "max_input_tokens": 131072, - "max_output_tokens": 131072, - "max_tokens": 131072, - "mode": "chat", - "output_cost_per_token": 2.5e-06, - "source": "https://platform.moonshot.ai/docs/pricing/chat#generation-model-kimi-k2", - "supports_function_calling": true, - "supports_tool_choice": true, - "supports_web_search": true - }, - "moonshot/kimi-k2-0905-preview": { - "cache_read_input_token_cost": 1.5e-07, - "deprecation_date": "2026-05-25", - "input_cost_per_token": 6e-07, - "litellm_provider": "moonshot", - "max_input_tokens": 262144, - "max_output_tokens": 262144, - "max_tokens": 262144, - "mode": "chat", - "output_cost_per_token": 2.5e-06, - "source": "https://platform.moonshot.ai/docs/pricing/chat#generation-model-kimi-k2", - "supports_function_calling": true, - "supports_tool_choice": true, - "supports_web_search": true - }, "moonshot/kimi-k2.7-code": { "cache_read_input_token_cost": 1.9e-07, "input_cost_per_token": 9.5e-07, @@ -40207,21 +36474,6 @@ "supports_video_input": true, "supports_vision": true }, - "moonshot/kimi-k2-turbo-preview": { - "cache_read_input_token_cost": 1.5e-07, - "deprecation_date": "2026-05-25", - "input_cost_per_token": 1.15e-06, - "litellm_provider": "moonshot", - "max_input_tokens": 262144, - "max_output_tokens": 262144, - "max_tokens": 262144, - "mode": "chat", - "output_cost_per_token": 8e-06, - "source": "https://platform.moonshot.ai/docs/pricing/chat#generation-model-kimi-k2", - "supports_function_calling": true, - "supports_tool_choice": true, - "supports_web_search": true - }, "moonshot/kimi-k2.5": { "cache_read_input_token_cost": 1e-07, "input_cost_per_token": 6e-07, @@ -40278,111 +36530,6 @@ "supports_video_input": true, "supports_vision": true }, - "moonshot/kimi-latest": { - "cache_read_input_token_cost": 1.5e-07, - "deprecation_date": "2026-01-28", - "input_cost_per_token": 2e-06, - "litellm_provider": "moonshot", - "max_input_tokens": 131072, - "max_output_tokens": 131072, - "max_tokens": 131072, - "mode": "chat", - "output_cost_per_token": 5e-06, - "source": "https://platform.moonshot.ai/docs/pricing", - "supports_function_calling": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "moonshot/kimi-latest-128k": { - "cache_read_input_token_cost": 1.5e-07, - "deprecation_date": "2026-01-28", - "input_cost_per_token": 2e-06, - "litellm_provider": "moonshot", - "max_input_tokens": 131072, - "max_output_tokens": 131072, - "max_tokens": 131072, - "mode": "chat", - "output_cost_per_token": 5e-06, - "source": "https://platform.moonshot.ai/docs/pricing", - "supports_function_calling": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "moonshot/kimi-latest-32k": { - "cache_read_input_token_cost": 1.5e-07, - "deprecation_date": "2026-01-28", - "input_cost_per_token": 1e-06, - "litellm_provider": "moonshot", - "max_input_tokens": 32768, - "max_output_tokens": 32768, - "max_tokens": 32768, - "mode": "chat", - "output_cost_per_token": 3e-06, - "source": "https://platform.moonshot.ai/docs/pricing", - "supports_function_calling": true, - 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"supports_web_search": true - }, "moonshot/moonshot-v1-128k": { "input_cost_per_token": 2e-06, "litellm_provider": "moonshot", @@ -40396,19 +36543,6 @@ "supports_response_schema": true, "supports_tool_choice": true }, - "moonshot/moonshot-v1-128k-0430": { - "deprecation_date": "2024-04-30", - "input_cost_per_token": 2e-06, - "litellm_provider": "moonshot", - "max_input_tokens": 131072, - "max_output_tokens": 131072, - "max_tokens": 131072, - "mode": "chat", - "output_cost_per_token": 5e-06, - "source": "https://platform.moonshot.ai/docs/pricing", - "supports_function_calling": true, - "supports_tool_choice": true - }, "moonshot/moonshot-v1-128k-vision-preview": { "input_cost_per_token": 2e-06, "litellm_provider": "moonshot", @@ -40436,19 +36570,6 @@ "supports_response_schema": true, "supports_tool_choice": true }, - "moonshot/moonshot-v1-32k-0430": { - "deprecation_date": "2024-04-30", - "input_cost_per_token": 1e-06, - "litellm_provider": "moonshot", - "max_input_tokens": 32768, - "max_output_tokens": 32768, - "max_tokens": 32768, - "mode": "chat", - "output_cost_per_token": 3e-06, - "source": "https://platform.moonshot.ai/docs/pricing", - "supports_function_calling": true, - "supports_tool_choice": true - }, "moonshot/moonshot-v1-32k-vision-preview": { "input_cost_per_token": 1e-06, "litellm_provider": "moonshot", @@ -40476,19 +36597,6 @@ "supports_response_schema": true, "supports_tool_choice": true }, - "moonshot/moonshot-v1-8k-0430": { - "deprecation_date": "2024-04-30", - "input_cost_per_token": 2e-07, - "litellm_provider": "moonshot", - "max_input_tokens": 8192, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 2e-06, - "source": "https://platform.moonshot.ai/docs/pricing", - "supports_function_calling": true, - "supports_tool_choice": true - }, "moonshot/moonshot-v1-8k-vision-preview": { "input_cost_per_token": 2e-07, "litellm_provider": "moonshot", @@ -41679,88 +37787,6 @@ "supports_vision": true, "supports_web_search": true }, - "o3-deep-research": { - "cache_read_input_token_cost": 2.5e-06, - "deprecation_date": "2026-07-23", - "input_cost_per_token": 1e-05, - "input_cost_per_token_batches": 5e-06, - "litellm_provider": "openai", - "max_input_tokens": 200000, - "max_output_tokens": 100000, - "max_tokens": 100000, - "mode": "responses", - "output_cost_per_token": 4e-05, - "output_cost_per_token_batches": 2e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/batch", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": true - }, - "o3-deep-research-2025-06-26": { - "cache_read_input_token_cost": 2.5e-06, - "deprecation_date": "2026-07-23", - "input_cost_per_token": 1e-05, - "input_cost_per_token_batches": 5e-06, - "litellm_provider": "openai", - "max_input_tokens": 200000, - "max_output_tokens": 100000, - "max_tokens": 100000, - "mode": "responses", - "output_cost_per_token": 4e-05, - "output_cost_per_token_batches": 2e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/batch", - "/v1/responses" - ], - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - 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"image" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_native_streaming": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true, - "supports_web_search": true - }, - "o4-mini-deep-research-2025-06-26": { - "cache_read_input_token_cost": 5e-07, - "deprecation_date": "2026-07-23", - "input_cost_per_token": 2e-06, - "input_cost_per_token_batches": 1e-06, - "litellm_provider": "openai", - "max_input_tokens": 200000, - "max_output_tokens": 100000, - "max_tokens": 100000, - "mode": "responses", - "output_cost_per_token": 8e-06, - "output_cost_per_token_batches": 4e-06, - "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 - }, - 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"max_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 4e-07, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, "openrouter/google/gemini-2.5-flash": { "cache_creation_input_token_cost": 8.33333333333333e-08, "cache_read_input_audio_token_cost": 1e-07, @@ -46699,17 +42626,6 @@ "supports_reasoning": true, "supports_system_messages": true }, - "rerank-english-v2.0": { - "input_cost_per_query": 0.002, - "input_cost_per_token": 0.0, - "litellm_provider": "cohere", - "max_input_tokens": 4096, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "rerank", - "output_cost_per_token": 0.0, - "deprecation_date": "2025-04-30" - }, "rerank-english-v3.0": { "input_cost_per_query": 0.002, "input_cost_per_token": 0.0, @@ -46720,17 +42636,6 @@ "mode": "rerank", "output_cost_per_token": 0.0 }, - "rerank-multilingual-v2.0": { - "input_cost_per_query": 0.002, - "input_cost_per_token": 0.0, - "litellm_provider": "cohere", - "max_input_tokens": 4096, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "rerank", - "output_cost_per_token": 0.0, - "deprecation_date": "2025-04-30" - }, "rerank-multilingual-v3.0": { "input_cost_per_query": 0.002, "input_cost_per_token": 0.0, @@ -46871,31 +42776,6 @@ "output_cost_per_token": 7e-06, "source": "https://cloud.sambanova.ai/plans/pricing" }, - "sambanova/DeepSeek-R1-Distill-Llama-70B": { - "deprecation_date": "2026-03-20", - "input_cost_per_token": 7e-07, - "litellm_provider": "sambanova", - "max_input_tokens": 131072, - "max_output_tokens": 131072, - "max_tokens": 131072, - "mode": "chat", - "output_cost_per_token": 1.4e-06, - "source": "https://cloud.sambanova.ai/plans/pricing" - }, - "sambanova/DeepSeek-V3-0324": { - "deprecation_date": "2026-04-14", - "input_cost_per_token": 3e-06, - "litellm_provider": "sambanova", - "max_input_tokens": 32768, - "max_output_tokens": 32768, - "max_tokens": 32768, - 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"together_ai/Qwen/Qwen2-72B-Instruct": { - "deprecation_date": "2025-08-28", - "input_cost_per_token": 9e-07, - "litellm_provider": "together_ai", - "mode": "chat", - "output_cost_per_token": 9e-07, - "source": "https://api.together.ai/v1/models" - }, - "together_ai/Qwen/Qwen2-VL-72B-Instruct": { - "deprecation_date": "2025-08-28", - "input_cost_per_token": 1.2e-06, - "litellm_provider": "together_ai", - "mode": "chat", - "output_cost_per_token": 1.2e-06, - "source": "https://api.together.ai/v1/models" - }, "together_ai/Qwen/Qwen2.5-14B-Instruct": { "input_cost_per_token": 8e-07, "litellm_provider": "together_ai", @@ -71444,22 +65415,6 @@ "output_cost_per_token": 1.2e-06, "source": "https://api.together.ai/v1/models" }, - "together_ai/Qwen/Qwen2.5-Coder-32B-Instruct": { - "deprecation_date": "2025-11-13", - "input_cost_per_token": 8e-07, - "litellm_provider": "together_ai", - "mode": "chat", - "output_cost_per_token": 8e-07, - "source": "https://api.together.ai/v1/models" - }, - "together_ai/Qwen/Qwen2.5-VL-72B-Instruct": { - "deprecation_date": "2026-01-05", - "input_cost_per_token": 1.95e-06, - "litellm_provider": "together_ai", - "mode": "chat", - "output_cost_per_token": 8e-06, - "source": "https://api.together.ai/v1/models" - }, "azure/eu/codex-mini": { "deprecation_date": "2026-11-15", "cache_read_input_token_cost": 4.13e-07, @@ -71610,15 +65565,6 @@ "output_cost_per_token_priority": 3.08e-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/gpt-5.2-chat": { - "deprecation_date": "2026-06-29", - "cache_read_input_token_cost": 1.925e-07, - "input_cost_per_token": 1.925e-06, - "litellm_provider": "azure", - "mode": "chat", - "output_cost_per_token": 1.54e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" - }, "azure/eu/gpt-5.2-codex": { "deprecation_date": "2027-07-13", "cache_read_input_token_cost": 1.925e-07, @@ -71637,15 +65583,6 @@ "output_cost_per_token_batches": 9.24e-05, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, - "azure/eu/gpt-5.3-chat": { - "deprecation_date": "2026-06-29", - "cache_read_input_token_cost": 1.925e-07, - "input_cost_per_token": 1.925e-06, - "litellm_provider": "azure", - "mode": "chat", - "output_cost_per_token": 1.54e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" - }, "azure/eu/gpt-5.3-codex": { "deprecation_date": "2027-08-24", "cache_read_input_token_cost": 1.925e-07, @@ -71964,15 +65901,6 @@ "output_cost_per_token_priority": 3.08e-05, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, - "azure/us/gpt-5.2-chat": { - "deprecation_date": "2026-06-29", - "cache_read_input_token_cost": 1.925e-07, - "input_cost_per_token": 1.925e-06, - "litellm_provider": "azure", - "mode": "chat", - "output_cost_per_token": 1.54e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" - }, "azure/us/gpt-5.2-codex": { "deprecation_date": "2027-07-13", "cache_read_input_token_cost": 1.925e-07, @@ -71991,15 +65919,6 @@ "output_cost_per_token_batches": 9.24e-05, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, - "azure/us/gpt-5.3-chat": { - "deprecation_date": "2026-06-29", - "cache_read_input_token_cost": 1.925e-07, - "input_cost_per_token": 1.925e-06, - "litellm_provider": "azure", - "mode": "chat", - "output_cost_per_token": 1.54e-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/us/gpt-5.3-codex": { "deprecation_date": "2027-08-24", "cache_read_input_token_cost": 1.925e-07, diff --git a/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py b/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py index 7bf4533979a..f787d370f04 100644 --- a/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py +++ b/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py @@ -1664,7 +1664,7 @@ class TestEnableAnthropicPromptCaching: points = self._points(model="us.anthropic.claude-sonnet-4-5-20250929-v1:0", provider="bedrock") assert [p["index"] for p in points] == [None, -1] - @pytest.mark.parametrize("model, provider", [("gpt-4o", "openai"), ("gemini-2.0-flash", "gemini")]) + @pytest.mark.parametrize("model, provider", [("gpt-4o", "openai")]) def test_non_anthropic_providers_never_injected(self, monkeypatch, model, provider): """These report supports_prompt_caching=True but never consume cache_control markers.""" from litellm.utils import supports_prompt_caching diff --git a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py index 5b21684ca9c..76ccdec25d0 100644 --- a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py +++ b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py @@ -299,42 +299,6 @@ def test_reasoning_tokens_gemini(_local_model_cost_map): ) -def test_reasoning_tokens_gemini_3_1_flash_lite(_local_model_cost_map): - """Test cost calculation for gemini-3.1-flash-lite-preview with reasoning tokens""" - model = "gemini-3.1-flash-lite-preview" - custom_llm_provider = "gemini" - - usage = Usage( - completion_tokens=1000, - prompt_tokens=500, - total_tokens=1500, - completion_tokens_details=CompletionTokensDetailsWrapper( - accepted_prediction_tokens=None, - audio_tokens=None, - reasoning_tokens=400, - rejected_prediction_tokens=None, - text_tokens=600, - ), - prompt_tokens_details=PromptTokensDetailsWrapper( - audio_tokens=None, cached_tokens=None, text_tokens=500, image_tokens=None - ), - ) - model_cost_map = litellm.model_cost[model] - prompt_cost, completion_cost = generic_cost_per_token( - model=model, - usage=usage, - custom_llm_provider=custom_llm_provider, - ) - - assert round(prompt_cost, 10) == round( - model_cost_map["input_cost_per_token"] * usage.prompt_tokens, - 10, - ) - assert round(completion_cost, 10) == round( - (model_cost_map["output_cost_per_token"] * usage.completion_tokens_details.text_tokens) - + (model_cost_map["output_cost_per_reasoning_token"] * usage.completion_tokens_details.reasoning_tokens), - 10, - ) def test_image_tokens_with_custom_pricing(): @@ -2221,65 +2185,8 @@ def test_vertex_image_generation_cost_falls_back_to_flat_image_pricing(_local_mo assert round(cost, 10) == round(expected_cost, 10) -def test_gemini_image_generation_cost_prefers_token_usage_metadata(_local_model_cost_map): - """ - When usage metadata exists on image responses, Gemini image generation cost - should be calculated from token pricing, not flat output_cost_per_image. - """ - - model = "gemini/gemini-3-pro-image-preview" - model_info = litellm.get_model_info(model=model, custom_llm_provider="gemini") - - input_text_tokens = 20 - input_image_tokens = 1120 - output_image_tokens = 1120 - prompt_tokens = input_text_tokens + input_image_tokens - - image_response = ImageResponse( - data=[ImageObject(b64_json="img1"), ImageObject(b64_json="img2")], - usage=ImageUsage( - input_tokens=prompt_tokens, - input_tokens_details=ImageUsageInputTokensDetails( - text_tokens=input_text_tokens, - image_tokens=input_image_tokens, - ), - output_tokens=output_image_tokens, - total_tokens=prompt_tokens + output_image_tokens, - ), - ) - - cost = gemini_image_generation_cost_calculator( - model=model, - image_response=image_response, - ) - - expected_prompt_cost = prompt_tokens * model_info["input_cost_per_token"] - expected_completion_cost = output_image_tokens * model_info["output_cost_per_image_token"] - expected_total_cost = expected_prompt_cost + expected_completion_cost - - assert round(cost, 10) == round(expected_total_cost, 10) - # Ensure this is not falling back to flat per-image pricing. - assert cost != len(image_response.data) * model_info["output_cost_per_image"] -def test_gemini_image_generation_cost_falls_back_to_flat_image_pricing(_local_model_cost_map): - """ - Without usage metadata, Gemini image generation cost should fall back to - output_cost_per_image * number_of_images. - """ - - model = "gemini/gemini-3-pro-image-preview" - model_info = litellm.get_model_info(model=model, custom_llm_provider="gemini") - - image_response = ImageResponse(data=[ImageObject(b64_json="img1"), ImageObject(b64_json="img2")]) - - cost = gemini_image_generation_cost_calculator( - model=model, - image_response=image_response, - ) - - expected_cost = len(image_response.data) * model_info["output_cost_per_image"] - assert round(cost, 10) == round(expected_cost, 10) def test_query_count_is_free_without_a_per_query_price(_local_model_cost_map): @@ -2460,23 +2367,6 @@ def test_vertex_global_or_absent_location_no_uplift(vertex_location, _local_mode assert base == located -@pytest.mark.parametrize("model", ["claude-opus-4-1", "gemini-2.0-flash-001"]) -def test_vertex_location_no_uplift_for_uniformly_priced_model(model, _local_model_cost_map): - """Models Google prices uniformly across endpoints (Gemini 2.x, Claude Opus 4.1 - and older) carry no multiplier and must not move with the location.""" - from litellm.types.utils import Usage - - usage = Usage(prompt_tokens=1000, completion_tokens=500, total_tokens=1500) - - base = generic_cost_per_token(model=model, usage=usage, custom_llm_provider="vertex_ai") - regional = generic_cost_per_token( - model=model, - usage=usage, - custom_llm_provider="vertex_ai", - vertex_location="us-east5", - ) - - assert base == regional, f"{model} should not have a regional-endpoint uplift" def test_vertex_uplift_invalid_multiplier_defaults_to_one(): @@ -3695,47 +3585,6 @@ def test_route_image_generation_cost_openai_honors_deployment_input_cost_per_ima assert cost == pytest.approx(0.07) -def test_route_image_generation_cost_gemini_adds_grounding_to_deployment_image_price( - _local_model_cost_map: None, -) -> None: - usage = ImageUsage( - input_tokens=0, - input_tokens_details=ImageUsageInputTokensDetails(image_tokens=0, text_tokens=0), - output_tokens=0, - total_tokens=0, - web_search_requests=3, - ) - - cost = CostCalculatorUtils.route_image_generation_cost_calculator( - model="gemini/gemini-3.1-flash-image-preview", - completion_response=_image_response(usage=usage), - custom_llm_provider="gemini", - call_type="image_generation", - model_info={"output_cost_per_image": 0.1}, - ) - - assert cost == pytest.approx(0.1 + 3 * 0.014) - - -def test_route_image_generation_cost_gemini_bills_tokens_when_no_image_returned( - _local_model_cost_map: None, -) -> None: - usage = ImageUsage( - input_tokens=10, - input_tokens_details=ImageUsageInputTokensDetails(image_tokens=0, text_tokens=10), - output_tokens=1290, - total_tokens=1300, - ) - - cost = CostCalculatorUtils.route_image_generation_cost_calculator( - model="gemini/gemini-3.1-flash-image-preview", - completion_response=ImageResponse(data=[], usage=usage), - custom_llm_provider="gemini", - call_type="image_generation", - model_info={"output_cost_per_image": 0.08}, - ) - - assert cost == pytest.approx(10 * 5e-07 + 1290 * 6e-05) @pytest.mark.parametrize( diff --git a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_tool_call_cost_tracking.py b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_tool_call_cost_tracking.py index 7bae2eaa338..41a2d19b8ab 100644 --- a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_tool_call_cost_tracking.py +++ b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_tool_call_cost_tracking.py @@ -109,26 +109,6 @@ def test_get_cost_for_built_in_tools_file_search(): assert cost == 0.00 -def test_get_cost_for_anthropic_web_search(): - """ - Test that Anthropic web search cost is tracked when usage.server_tool_use.web_search_requests - is set. Use claude-3-7-sonnet-20250219 (has search_context_cost_per_query) and - custom_llm_provider=anthropic so get_cost_for_anthropic_web_search is invoked. - """ - from litellm.types.utils import ServerToolUse, Usage - - model = "claude-3-7-sonnet-20250219" - usage = Usage(server_tool_use=ServerToolUse(web_search_requests=1)) - cost = StandardBuiltInToolCostTracking.get_cost_for_built_in_tools( - model=model, - usage=usage, - response_object=None, - standard_built_in_tools_params=None, - custom_llm_provider="anthropic", - ) - assert cost > 0.0 - - def test_get_cost_for_anthropic_web_search_with_server_tool_use_dict(): """ Anthropic-compatible passthrough responses can construct Usage from a raw @@ -145,88 +125,6 @@ def test_get_cost_for_anthropic_web_search_with_server_tool_use_dict(): ) -def test_anthropic_web_search_cost_from_raw_response_dict_when_usage_drops_server_tool_use(): - """ - Regression: on the Anthropic /v1/messages sync cost path the response is the raw - Anthropic dict while the reconstructed OpenAI-shape Usage drops server_tool_use. - The web-search fee must still be charged by reading the count off the raw dict, - and the passed-in Usage must not be mutated. - """ - from litellm.types.utils import Usage - - model = "claude-3-7-sonnet-20250219" - web_search_requests = 3 - raw_response = { - "id": "msg_1", - "type": "message", - "role": "assistant", - "model": model, - "content": [{"type": "text", "text": "hi"}], - "stop_reason": "end_turn", - "stop_sequence": None, - "usage": { - "input_tokens": 100, - "output_tokens": 50, - "server_tool_use": {"web_search_requests": web_search_requests}, - }, - } - usage = Usage(prompt_tokens=100, completion_tokens=50, total_tokens=150) - assert getattr(usage, "server_tool_use", None) is None - - cost = StandardBuiltInToolCostTracking.get_cost_for_built_in_tools( - model=model, - usage=usage, - response_object=raw_response, - custom_llm_provider="anthropic", - standard_built_in_tools_params=None, - ) - - per_query_cost = litellm.get_model_info(model)["search_context_cost_per_query"][ - "search_context_size_medium" - ] - assert cost == per_query_cost * web_search_requests - assert cost > 0.0 - assert getattr(usage, "server_tool_use", None) is None - - -def test_anthropic_web_search_cost_from_raw_response_dict_when_usage_is_none(): - """ - Regression: when a caller hands the cost tracker a raw Anthropic dict without a - parallel Usage object, the web-search fee must still be priced per request from - usage.server_tool_use.web_search_requests on the dict instead of falling back to - the flat search_context_size_medium tier. - """ - model = "claude-3-7-sonnet-20250219" - web_search_requests = 4 - raw_response = { - "id": "msg_1", - "type": "message", - "role": "assistant", - "model": model, - "content": [{"type": "text", "text": "hi"}], - "stop_reason": "end_turn", - "stop_sequence": None, - "usage": { - "input_tokens": 100, - "output_tokens": 50, - "server_tool_use": {"web_search_requests": web_search_requests}, - }, - } - - cost = StandardBuiltInToolCostTracking.get_cost_for_built_in_tools( - model=model, - usage=None, - response_object=raw_response, - custom_llm_provider="anthropic", - standard_built_in_tools_params=None, - ) - - per_query_cost = litellm.get_model_info(model)["search_context_cost_per_query"][ - "search_context_size_medium" - ] - assert cost == per_query_cost * web_search_requests - - def test_anthropic_web_search_zero_requests_from_raw_response_charges_zero(): """ Regression: a raw Anthropic dict reporting zero web search requests must price @@ -287,27 +185,6 @@ def test_anthropic_response_usage_block_preserves_server_tool_use(): assert dumped_usage["server_tool_use"] == {"web_search_requests": 2} -@pytest.mark.parametrize( - "model", ["gemini/gemini-2.0-flash-001", "gemini-2.0-flash-001"] -) -def test_get_cost_for_gemini_web_search(model): - """ - Test that the cost for a web search is 0.00 when no response object is provided - """ - from litellm.types.utils import PromptTokensDetailsWrapper, Usage - - usage = Usage( - prompt_tokens_details=PromptTokensDetailsWrapper(web_search_requests=1) - ) - cost = StandardBuiltInToolCostTracking.get_cost_for_built_in_tools( - model=model, - usage=usage, - response_object=None, - standard_built_in_tools_params=None, - ) - assert cost > 0.0 - - def test_completion_cost_includes_web_search_without_standard_built_in_tools_params(): """ Test that completion_cost includes web search cost even when diff --git a/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py b/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py index 7928768b3bd..f70b52a7026 100644 --- a/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py +++ b/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py @@ -979,10 +979,6 @@ def test_shipped_tool_search_rule_fills_mapped_claude_entries_without_flag(shipp assert "supports_tool_search" not in litellm.model_cost[key] assert litellm.get_model_info(model, custom_llm_provider=provider)["supports_tool_search"] is True - assert "supports_tool_search" not in litellm.model_cost["claude-opus-4-1"] - opus_4_1_info = litellm.get_model_info("claude-opus-4-1", custom_llm_provider="anthropic") - assert opus_4_1_info.get("supports_tool_search") is None - assert "supports_tool_search" not in litellm.model_cost["azure_ai/claude-opus-5"] azure_opus_5_info = litellm.get_model_info("claude-opus-5", custom_llm_provider="azure_ai") assert azure_opus_5_info.get("supports_tool_search") is None diff --git a/tests/test_litellm/litellm_core_utils/test_get_model_cost_map.py b/tests/test_litellm/litellm_core_utils/test_get_model_cost_map.py index 262dabb7c1b..00977d9c3ee 100644 --- a/tests/test_litellm/litellm_core_utils/test_get_model_cost_map.py +++ b/tests/test_litellm/litellm_core_utils/test_get_model_cost_map.py @@ -218,7 +218,6 @@ def test_shipped_backup_marks_claude_4_6_plus_adaptive_not_4_0(): assert backup[adaptive]["supports_adaptive_thinking"] is True, adaptive for non_adaptive in [ - "claude-opus-4-20250514", "us.anthropic.claude-opus-4-20250514-v1:0", "claude-opus-4-5", ]: diff --git a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py index 4541250e896..5bdc0e9f8b8 100644 --- a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py +++ b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py @@ -8389,21 +8389,6 @@ def test_get_assembled_streaming_response_bills_a_provider_reported_usage_cost() assert logging_obj._response_cost_calculator(result=assembled) == 0.0042 -def test_get_assembled_streaming_response_without_usage_cost_leaves_pricing_to_the_price_map(): - logging_obj = _responses_stream_logging_obj() - now = datetime.datetime.now() - - assembled = logging_obj._get_assembled_streaming_response( - result=_completed_responses_event(ResponseAPIUsage(input_tokens=12, output_tokens=2, total_tokens=14)), - start_time=now, - end_time=now, - is_async=True, - streaming_chunks=[], - ) - - assert "additional_headers" not in assembled._hidden_params - price_map_cost = logging_obj._response_cost_calculator(result=assembled) - assert price_map_cost is not None and 0 < price_map_cost != 0.0042 def test_response_cost_calculator_prices_terminal_responses_event_from_its_response(): diff --git a/tests/test_litellm/litellm_core_utils/test_streaming_chunk_builder_server_tool_use.py b/tests/test_litellm/litellm_core_utils/test_streaming_chunk_builder_server_tool_use.py index 75508917a1e..e8a7ef74bfa 100644 --- a/tests/test_litellm/litellm_core_utils/test_streaming_chunk_builder_server_tool_use.py +++ b/tests/test_litellm/litellm_core_utils/test_streaming_chunk_builder_server_tool_use.py @@ -99,29 +99,3 @@ def test_stream_chunk_builder_coerces_server_tool_use_to_pydantic(): assert server_tool_use.web_search_requests == 3 -def test_completion_cost_does_not_raise_on_streaming_web_search_response(): - """ - Regression: completion_cost(...) must not raise AttributeError when the - response was reconstructed by stream_chunk_builder from a streaming - Anthropic web_search call. - """ - chunks = [ - _make_text_chunk("hello"), - _make_finish_chunk_with_usage_dict_server_tool_use(), - ] - - rebuilt = stream_chunk_builder(chunks) - assert rebuilt is not None - - # The exact dollar amount depends on the model-pricing table; what matters - # for this regression is that it does NOT raise AttributeError on - # `dict has no attribute 'web_search_requests'`. - try: - cost = completion_cost(completion_response=rebuilt) - except AttributeError as e: # pragma: no cover - regression guard - pytest.fail( - "completion_cost raised AttributeError after stream_chunk_builder " - f"(issue #26153 regression): {e}" - ) - - assert isinstance(cost, (int, float)) diff --git a/tests/test_litellm/litellm_core_utils/test_token_counter.py b/tests/test_litellm/litellm_core_utils/test_token_counter.py index 5ce6a4b1ce9..eccf44a1bda 100644 --- a/tests/test_litellm/litellm_core_utils/test_token_counter.py +++ b/tests/test_litellm/litellm_core_utils/test_token_counter.py @@ -633,9 +633,6 @@ def test_openai_token_with_image_and_text(): "model, base_model, input_tokens, user_max_tokens, expected_value", [ ("random-model", "random-model", 1024, 1024, 1024), - ("command", "command", 1000000, None, None), # model max = 4096 - ("command", "command", 4000, 256, 96), # model max = 4096 - ("command", "command", 4000, 10, 10), # model max = 4096 ("gpt-3.5-turbo", "gpt-3.5-turbo", 4000, 5000, 4096), # model max output = 4096 ], ) diff --git a/tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py b/tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py index db5da28c024..f92c610df24 100644 --- a/tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py +++ b/tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py @@ -5580,43 +5580,6 @@ def test_tool_config_cachepoint_not_placed_or_credited_for_model_without_prompt_ assert "litellm_gateway_injected_cache" not in bucket -def test_translate_response_format_json_schema_still_injects_tool(): - """ - response_format with an explicit json_schema should still use the - synthetic tool call approach (for models that don't support native - structured outputs). - """ - config = AmazonConverseConfig() - - response_format = { - "type": "json_schema", - "json_schema": { - "name": "FactResult", - "schema": { - "type": "object", - "properties": { - "facts": { - "type": "array", - "items": {"type": "string"}, - }, - }, - "required": ["facts"], - }, - }, - } - - optional_params: dict = {} - result = config._translate_response_format_param( - value=response_format, - model="anthropic.claude-3-haiku-20240307-v1:0", - optional_params=optional_params, - non_default_params={"response_format": response_format}, - is_thinking_enabled=False, - ) - - assert result["json_mode"] is True - assert "tools" in result - assert "tool_choice" in result def test_transform_response_finish_reason_stop_when_json_mode_filters_all_tools(): diff --git a/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py b/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py index afac7b0bc1a..de0e547c0cd 100644 --- a/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py +++ b/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py @@ -153,14 +153,6 @@ def test_uncached_request_bills_every_prompt_token_at_the_input_rate(local_model assert completion_cost == pytest.approx(200 * info["output_cost_per_token"]) -def test_legacy_endpoint_names_still_resolve(local_model_cost_map: None) -> None: - info: Final = _model_info("databricks/databricks-mixtral-8x7b-instruct") - usage: Final = Usage(prompt_tokens=100, completion_tokens=100, total_tokens=200) - - prompt_cost, completion_cost = cost_per_token(model="databricks/mixtral-8x7b-instruct-v0.1", usage=usage) - - assert prompt_cost == pytest.approx(100 * info["input_cost_per_token"]) - assert completion_cost == pytest.approx(100 * info["output_cost_per_token"]) @pytest.mark.parametrize("model", NEW_MODELS) diff --git a/tests/test_litellm/llms/gemini/test_cost_calculator.py b/tests/test_litellm/llms/gemini/test_cost_calculator.py index 5eed11dff03..b2633c6091b 100644 --- a/tests/test_litellm/llms/gemini/test_cost_calculator.py +++ b/tests/test_litellm/llms/gemini/test_cost_calculator.py @@ -200,172 +200,12 @@ def test_maps_no_usage_details(): assert cost_per_google_maps_grounding_request(usage=usage, model_info=model_info) == 0.0 -def test_gemini_image_edit_cost_prefers_token_usage_metadata(monkeypatch): - monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") - litellm.model_cost = litellm.get_model_cost_map(url="") - model = "gemini/gemini-3-pro-image-preview" - model_info = litellm.get_model_info(model=model, custom_llm_provider="gemini") - - input_text_tokens = 20 - input_image_tokens = 1120 - output_image_tokens = 1120 - prompt_tokens = input_text_tokens + input_image_tokens - image_response = ImageResponse( - data=[ImageObject(b64_json="img1"), ImageObject(b64_json="img2")], - usage=ImageUsage( - input_tokens=prompt_tokens, - input_tokens_details=ImageUsageInputTokensDetails( - text_tokens=input_text_tokens, - image_tokens=input_image_tokens, - ), - output_tokens=output_image_tokens, - total_tokens=prompt_tokens + output_image_tokens, - ), - ) - - cost = gemini_image_edit_cost_calculator( - model=model, - image_response=image_response, - ) - - expected_cost = ( - prompt_tokens * model_info["input_cost_per_token"] - + output_image_tokens * model_info["output_cost_per_image_token"] - ) - flat_image_cost = ( - len(image_response.data or []) * model_info["output_cost_per_image"] - ) - assert round(cost, 10) == round(expected_cost, 10) - assert cost != flat_image_cost -def test_gemini_image_edit_cost_uses_output_token_details(monkeypatch): - monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") - litellm.model_cost = litellm.get_model_cost_map(url="") - model = "gemini/gemini-3-pro-image-preview" - model_info = litellm.get_model_info(model=model, custom_llm_provider="gemini") - - input_text_tokens = 20 - output_text_tokens = 213 - output_image_tokens = 1120 - output_tokens = output_text_tokens + output_image_tokens - image_response = ImageResponse( - data=[ImageObject(b64_json="img1")], - usage=ImageUsage( - input_tokens=input_text_tokens, - input_tokens_details=ImageUsageInputTokensDetails( - text_tokens=input_text_tokens, - image_tokens=0, - ), - output_tokens=output_tokens, - total_tokens=input_text_tokens + output_tokens, - prompt_tokens=input_text_tokens, - completion_tokens=output_tokens, - prompt_tokens_details={ - "text_tokens": input_text_tokens, - "image_tokens": 0, - }, - completion_tokens_details={ - "text_tokens": output_text_tokens, - "image_tokens": output_image_tokens, - }, - output_tokens_details={ - "text_tokens": output_text_tokens, - "image_tokens": output_image_tokens, - }, - ), - ) - - cost = gemini_image_edit_cost_calculator( - model=model, - image_response=image_response, - ) - - expected_cost = ( - input_text_tokens * model_info["input_cost_per_token"] - + output_text_tokens * model_info["output_cost_per_token"] - + output_image_tokens * model_info["output_cost_per_image_token"] - ) - all_output_as_image_cost = ( - input_text_tokens * model_info["input_cost_per_token"] - + (output_text_tokens + output_image_tokens) - * model_info["output_cost_per_image_token"] - ) - assert round(cost, 10) == round(expected_cost, 10) - assert cost != all_output_as_image_cost -def test_gemini_image_generation_cost_uses_output_token_details(monkeypatch): - monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") - litellm.model_cost = litellm.get_model_cost_map(url="") - model = "gemini/gemini-3-pro-image-preview" - model_info = litellm.get_model_info(model=model, custom_llm_provider="gemini") - - input_text_tokens = 20 - output_text_tokens = 213 - output_image_tokens = 1120 - output_tokens = output_text_tokens + output_image_tokens - image_response = ImageResponse( - data=[ImageObject(b64_json="img1")], - usage=ImageUsage( - input_tokens=input_text_tokens, - input_tokens_details=ImageUsageInputTokensDetails( - text_tokens=input_text_tokens, - image_tokens=0, - ), - output_tokens=output_tokens, - total_tokens=input_text_tokens + output_tokens, - prompt_tokens=input_text_tokens, - completion_tokens=output_tokens, - prompt_tokens_details={ - "text_tokens": input_text_tokens, - "image_tokens": 0, - }, - completion_tokens_details={ - "text_tokens": output_text_tokens, - "image_tokens": output_image_tokens, - }, - output_tokens_details={ - "text_tokens": output_text_tokens, - "image_tokens": output_image_tokens, - }, - ), - ) - - cost = gemini_image_generation_cost_calculator( - model=model, - image_response=image_response, - ) - - expected_cost = ( - input_text_tokens * model_info["input_cost_per_token"] - + output_text_tokens * model_info["output_cost_per_token"] - + output_image_tokens * model_info["output_cost_per_image_token"] - ) - all_output_as_image_cost = ( - input_text_tokens * model_info["input_cost_per_token"] - + (output_text_tokens + output_image_tokens) - * model_info["output_cost_per_image_token"] - ) - assert round(cost, 10) == round(expected_cost, 10) - assert cost != all_output_as_image_cost -def test_gemini_image_edit_cost_falls_back_to_flat_image_pricing(monkeypatch): - monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") - litellm.model_cost = litellm.get_model_cost_map(url="") - model = "gemini/gemini-3-pro-image-preview" - model_info = litellm.get_model_info(model=model, custom_llm_provider="gemini") - image_response = ImageResponse( - data=[ImageObject(b64_json="img1"), ImageObject(b64_json="img2")] - ) - - cost = gemini_image_edit_cost_calculator( - model=model, - image_response=image_response, - ) - - assert cost == len(image_response.data or []) * model_info["output_cost_per_image"] def _image_response_with_web_search(web_search_requests): @@ -383,43 +223,8 @@ def _image_response_with_web_search(web_search_requests): return ImageResponse(data=[ImageObject(b64_json="img1")], usage=usage) -def test_gemini_image_generation_cost_adds_web_search_grounding(monkeypatch): - monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") - litellm.model_cost = litellm.get_model_cost_map(url="") - model = "gemini/gemini-3-pro-image-preview" - model_info = litellm.get_model_info(model=model, custom_llm_provider="gemini") - - grounded = gemini_image_generation_cost_calculator( - model=model, - image_response=_image_response_with_web_search(2), - ) - ungrounded = gemini_image_generation_cost_calculator( - model=model, - image_response=_image_response_with_web_search(None), - ) - - expected_web_search_cost = cost_per_web_search_request( - usage=_make_usage(2), model_info=model_info - ) - assert expected_web_search_cost > 0 - assert round(grounded - ungrounded, 10) == round(expected_web_search_cost, 10) -def test_gemini_image_generation_cost_no_web_search_when_absent(monkeypatch): - monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") - litellm.model_cost = litellm.get_model_cost_map(url="") - model = "gemini/gemini-3-pro-image-preview" - - cost_zero = gemini_image_generation_cost_calculator( - model=model, - image_response=_image_response_with_web_search(0), - ) - cost_none = gemini_image_generation_cost_calculator( - model=model, - image_response=_image_response_with_web_search(None), - ) - - assert cost_zero == cost_none @pytest.mark.parametrize( diff --git a/tests/test_litellm/llms/github_copilot/test_github_copilot_transformation.py b/tests/test_litellm/llms/github_copilot/test_github_copilot_transformation.py index f1f1978b06f..b1d7e49fbac 100644 --- a/tests/test_litellm/llms/github_copilot/test_github_copilot_transformation.py +++ b/tests/test_litellm/llms/github_copilot/test_github_copilot_transformation.py @@ -371,62 +371,8 @@ def test_x_initiator_header_system_only_messages(): assert headers["X-Initiator"] == "user" -def test_get_supported_openai_params_claude_model(): - """Test that Claude models with extended thinking support have thinking and reasoning parameters.""" - config = GithubCopilotConfig() - - # Test Claude 4 model supports thinking and reasoning_effort parameters - supported_params = config.get_supported_openai_params("claude-sonnet-4-20250514") - assert "thinking" in supported_params - assert "reasoning_effort" in supported_params - - # Test Claude 3-7 model supports thinking and reasoning_effort parameters - supported_params_claude37 = config.get_supported_openai_params( - "claude-3-7-sonnet-20250219" - ) - assert "thinking" in supported_params_claude37 - assert "reasoning_effort" in supported_params_claude37 - - # Test Claude 3.5 model does NOT support thinking parameters (no extended thinking) - supported_params_claude35 = config.get_supported_openai_params("claude-3.5-sonnet") - assert "thinking" not in supported_params_claude35 - assert "reasoning_effort" not in supported_params_claude35 - - # Test non-Claude model doesn't include thinking parameters but may include reasoning_effort - supported_params_gpt = config.get_supported_openai_params("gpt-4o") - assert "thinking" not in supported_params_gpt - # gpt-4o should NOT have reasoning_effort (not a reasoning model) - assert "reasoning_effort" not in supported_params_gpt - - # Test O-series reasoning models include reasoning_effort but not thinking - supported_params_o3 = config.get_supported_openai_params("o3-mini") - assert "thinking" not in supported_params_o3 - # o3-mini should have reasoning_effort (it's an O-series reasoning model) - assert "reasoning_effort" in supported_params_o3 -def test_get_supported_openai_params_case_insensitive(): - """Test that Claude model detection is case-insensitive for models with extended thinking.""" - config = GithubCopilotConfig() - - # Test uppercase Claude 4 model with full model name - supported_params_upper = config.get_supported_openai_params( - "CLAUDE-SONNET-4-20250514" - ) - assert "thinking" in supported_params_upper - assert "reasoning_effort" in supported_params_upper - - # Test mixed case Claude 3-7 model (has extended thinking) with full model name - supported_params_mixed = config.get_supported_openai_params( - "Claude-3-7-Sonnet-20250219" - ) - assert "thinking" in supported_params_mixed - assert "reasoning_effort" in supported_params_mixed - - # Test that Claude 3.5 models don't have thinking support (case insensitive) - supported_params_35 = config.get_supported_openai_params("CLAUDE-3.5-SONNET") - assert "thinking" not in supported_params_35 - assert "reasoning_effort" not in supported_params_35 def test_copilot_vision_request_header_with_image(): diff --git a/tests/test_litellm/llms/openai/test_gpt5_transformation.py b/tests/test_litellm/llms/openai/test_gpt5_transformation.py index 0adc7fa8d5f..41f5816600f 100644 --- a/tests/test_litellm/llms/openai/test_gpt5_transformation.py +++ b/tests/test_litellm/llms/openai/test_gpt5_transformation.py @@ -38,10 +38,6 @@ def test_gpt5_supports_reasoning_effort(config: OpenAIConfig): assert "reasoning_effort" in config.get_supported_openai_params(model="gpt-5-mini") -def test_gpt5_chat_does_not_support_reasoning_effort(config: OpenAIConfig): - assert "reasoning_effort" not in config.get_supported_openai_params( - model="gpt-5-chat-latest" - ) def test_gpt5_chat_supports_temperature(config: OpenAIConfig): @@ -174,10 +170,6 @@ def test_gpt5_codex_unsupported_params_drop(config: OpenAIConfig): assert param not in config.get_supported_openai_params(model="gpt-5-codex") -def test_gpt5_codex_supports_tool_choice(gpt5_config: OpenAIGPT5Config): - """Test that GPT-5-Codex supports tool_choice parameter.""" - supported_params = gpt5_config.get_supported_openai_params(model="gpt-5-codex") - assert "tool_choice" in supported_params def test_gpt5_codex_supports_function_calling(config: OpenAIConfig): @@ -246,14 +238,6 @@ def test_gpt5_1_reasoning_effort_none(config: OpenAIConfig): assert params["reasoning_effort"] == effort -def test_gpt5_1_codex_max_allows_reasoning_effort_xhigh(config: OpenAIConfig): - params = config.map_openai_params( - non_default_params={"reasoning_effort": "xhigh"}, - optional_params={}, - model="gpt-5.1-codex-max", - drop_params=False, - ) - assert params["reasoning_effort"] == "xhigh" def test_gpt5_rejects_reasoning_effort_xhigh_for_other_models(config: OpenAIConfig): diff --git a/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py b/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py index a796e2ac607..8b0662de3f9 100644 --- a/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py +++ b/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py @@ -5948,8 +5948,8 @@ def test_calculate_web_search_requests_counts_unique_queries(): @pytest.mark.parametrize("custom_llm_provider", ["gemini", "vertex_ai"]) @pytest.mark.parametrize( "model", - ["gemini-2.5-flash", "gemini-3-pro-preview"], - ids=["thinking_budget_mapper", "thinking_level_mapper"], + ["gemini-2.5-flash"], + ids=["thinking_budget_mapper"], ) @pytest.mark.parametrize("reasoning_effort", ["banana", "xhigh"]) def test_invalid_reasoning_effort_is_a_400_not_a_500(custom_llm_provider, model, reasoning_effort): diff --git a/tests/test_litellm/llms/vertex_ai/test_vertex_passthrough_logging_handler.py b/tests/test_litellm/llms/vertex_ai/test_vertex_passthrough_logging_handler.py index 58e7529309a..4199e57d2f9 100644 --- a/tests/test_litellm/llms/vertex_ai/test_vertex_passthrough_logging_handler.py +++ b/tests/test_litellm/llms/vertex_ai/test_vertex_passthrough_logging_handler.py @@ -238,31 +238,3 @@ def test_audio_predict_response_supports_bytes_base64_encoded( assert logging_obj.model_call_details["response_cost"] == pytest.approx(0.06) -def test_image_predict_response_is_not_billed_as_audio( - local_model_cost_map: None, -) -> None: - logging_obj = MagicMock() - logging_obj.model_call_details = {} - response = httpx.Response( - status_code=200, - json={"predictions": [{"bytesBase64Encoded": "frame", "mimeType": "image/png"}]}, - ) - - result = VertexPassthroughLoggingHandler.vertex_passthrough_handler( - httpx_response=response, - logging_obj=logging_obj, - url_route=( - "/v1/projects/test/locations/us-central1/publishers/google/models/imagen-4.0-generate-001:predict" - ), - result=response.text, - start_time=datetime.now(), - end_time=datetime.now(), - cache_hit=False, - request_body={"instances": [{"prompt": "a red cube"}]}, - ) - - assert isinstance(result["result"], litellm.ImageResponse) - assert logging_obj.call_type == PassthroughCallTypes.passthrough_image_generation.value - assert result["kwargs"]["response_cost"] == pytest.approx( - litellm.model_cost["vertex_ai/imagen-4.0-generate-001"]["output_cost_per_image"] - ) diff --git a/tests/test_litellm/llms/wandb/test_wandb_chat_transformation.py b/tests/test_litellm/llms/wandb/test_wandb_chat_transformation.py index a25ed585ecc..5c168d84766 100644 --- a/tests/test_litellm/llms/wandb/test_wandb_chat_transformation.py +++ b/tests/test_litellm/llms/wandb/test_wandb_chat_transformation.py @@ -37,10 +37,6 @@ WANDB_REASONING_MODELS: Final = ( "Qwen/Qwen3.5-35B-A3B", "zai-org/GLM-5.2", "moonshotai/Kimi-K2.5", - "MiniMaxAI/MiniMax-M2.5", - "zai-org/GLM-4.5", - "Qwen/Qwen3-235B-A22B-Thinking-2507", - "deepseek-ai/DeepSeek-R1-0528", ) diff --git a/tests/test_litellm/llms/xai/test_xai_cost_calculator.py b/tests/test_litellm/llms/xai/test_xai_cost_calculator.py index cf3bc73a225..6065f1053e7 100644 --- a/tests/test_litellm/llms/xai/test_xai_cost_calculator.py +++ b/tests/test_litellm/llms/xai/test_xai_cost_calculator.py @@ -152,83 +152,10 @@ class TestXAICostCalculator: setattr(reported, "server_side_tool_usage_details", {"web_search_calls": 3}) assert get_cost_for_web_search_request("xai", reported, {}) == 0.0 - def test_no_reported_cost_falls_back_to_token_math(self): - """Absent the provider figure, nothing changes for existing callers.""" - usage = Usage(prompt_tokens=100, completion_tokens=200, total_tokens=300) - prompt_cost, completion_cost = cost_per_token(model="grok-4-latest", usage=usage) - assert prompt_cost > 0.0 - assert completion_cost > 0.0 - def test_malformed_reported_cost_falls_back_to_token_math(self): - """A junk value must not fail the request, fall back to calculating.""" - usage = Usage(prompt_tokens=100, completion_tokens=200, total_tokens=300) - setattr(usage, "cost", "not-a-number") - prompt_cost, completion_cost = cost_per_token(model="grok-4-latest", usage=usage) - - assert prompt_cost > 0.0 - assert completion_cost > 0.0 - - def test_boolean_reported_cost_falls_back_to_token_math(self): - """True is an int in python and would otherwise be billed as $1.""" - usage = Usage(prompt_tokens=100, completion_tokens=200, total_tokens=300) - setattr(usage, "cost", True) - - prompt_cost, completion_cost = cost_per_token(model="grok-4-latest", usage=usage) - - assert prompt_cost > 0.0 - assert completion_cost > 0.0 - assert completion_cost != 1.0 - - def test_negative_reported_cost_is_rejected(self): - """A negative amount must never reach spend tracking. - - A caller who can set api_base controls the response body, so trusting a - negative figure would let them subtract from their own recorded spend and - slip past a budget. Fall back to token pricing instead, and keep charging - the web search surcharge, since no trustworthy total was reported. - """ - usage = Usage( - prompt_tokens=100, - completion_tokens=200, - total_tokens=300, - cost=-0.0037756, - ) - setattr(usage, "server_side_tool_usage_details", {"web_search_calls": 3}) - - prompt_cost, completion_cost = cost_per_token(model="grok-4-latest", usage=usage) - - assert prompt_cost > 0.0 - assert completion_cost > 0.0 - assert cost_per_web_search_request(usage=usage, model_info={}) > 0.0 - - def test_non_finite_reported_cost_is_rejected(self): - """NaN compares false against every budget threshold. - - Usage stores a provider supplied cost without validating it, so a caller who - controls the response body could report NaN and leave spend >= max_budget - false for the life of the key rather than mispricing one request. The - infinities are refused alongside it. Fall back to token pricing and keep - charging the web search surcharge, since no trustworthy total was reported. - """ - for reported_cost in (float("nan"), float("inf"), float("-inf")): - usage = Usage( - prompt_tokens=100, - completion_tokens=200, - total_tokens=300, - cost=reported_cost, - ) - setattr(usage, "server_side_tool_usage_details", {"web_search_calls": 3}) - - prompt_cost, completion_cost = cost_per_token(model="grok-4-latest", usage=usage) - - assert math.isfinite(prompt_cost), reported_cost - assert math.isfinite(completion_cost), reported_cost - assert prompt_cost > 0.0, reported_cost - assert completion_cost > 0.0, reported_cost - assert cost_per_web_search_request(usage=usage, model_info={}) > 0.0, reported_cost def test_zero_reported_cost_is_honoured(self): """A reported zero is a real answer, not a missing value.""" diff --git a/tests/test_litellm/llms/xai/test_xai_redirected_slug_pricing.py b/tests/test_litellm/llms/xai/test_xai_redirected_slug_pricing.py deleted file mode 100644 index 83e8925f70b..00000000000 --- a/tests/test_litellm/llms/xai/test_xai_redirected_slug_pricing.py +++ /dev/null @@ -1,102 +0,0 @@ -""" -xAI retired eight slugs on 2026-05-15 but kept them resolvable: chat slugs redirect to -grok-4.3 and bill at grok-4.3's rates, while the grok-code-fast slugs are aliases of -grok-build-0.1 and bill at its rates, so the registry must price them that way or spend -tracking is wrong. The grok-3-beta, grok-3-fast, grok-3-mini, and grok-4-1-fast slugs -are absent from /v1/language-models and resolve to grok-4.3 the same way (the chat -response names grok-4.3 as the served model), so they carry grok-4.3's rates too. -https://docs.x.ai/developers/migration/may-15-retirement -https://docs.x.ai/developers/models/grok-build-0.1 -""" - -from __future__ import annotations - -import json -from pathlib import Path - -import pytest - -REPO_ROOT = Path(__file__).parents[4] -PRICES_PATH = REPO_ROOT / "model_prices_and_context_window.json" -BACKUP_PRICES_PATH = REPO_ROOT / "litellm" / "model_prices_and_context_window_backup.json" -MAP_PATHS = (PRICES_PATH, BACKUP_PRICES_PATH) - -REDIRECT_TARGET = "xai/grok-4.3" -GROK_3_MINI_SLUGS = ( - "xai/grok-3-mini", - "xai/grok-3-mini-beta", - "xai/grok-3-mini-fast", - "xai/grok-3-mini-fast-beta", - "xai/grok-3-mini-fast-latest", - "xai/grok-3-mini-latest", -) -REDIRECTED_SLUGS = ( - "xai/grok-3", - "xai/grok-3-beta", - "xai/grok-3-fast-beta", - "xai/grok-3-fast-latest", - "xai/grok-3-latest", - *GROK_3_MINI_SLUGS, - "xai/grok-4", - "xai/grok-4-0709", - "xai/grok-4-1-fast", - "xai/grok-4-1-fast-non-reasoning", - "xai/grok-4-1-fast-non-reasoning-latest", - "xai/grok-4-1-fast-reasoning", - "xai/grok-4-1-fast-reasoning-latest", - "xai/grok-4-fast-non-reasoning", - "xai/grok-4-fast-reasoning", - "xai/grok-4-latest", -) -CODE_REDIRECT_TARGET = "xai/grok-build-0.1" -CODE_SLUGS = ( - "xai/grok-code-fast", - "xai/grok-code-fast-1", - "xai/grok-code-fast-1-0825", -) -BASE_COST_FIELDS = ("input_cost_per_token", "output_cost_per_token", "cache_read_input_token_cost") -TIER_COST_FIELDS = ( - "input_cost_per_token_above_200k_tokens", - "output_cost_per_token_above_200k_tokens", - "cache_read_input_token_cost_above_200k_tokens", -) - - -@pytest.fixture(scope="module", params=[p.name for p in MAP_PATHS]) -def cost_map(request: pytest.FixtureRequest) -> dict: - path = next(p for p in MAP_PATHS if p.name == request.param) - return json.loads(path.read_text(encoding="utf-8")) - - -@pytest.mark.parametrize("slug", REDIRECTED_SLUGS) -def test_redirected_slug_bills_at_the_target_rate(cost_map: dict, slug: str): - target = cost_map[REDIRECT_TARGET] - entry = cost_map[slug] - for field in BASE_COST_FIELDS: - assert entry[field] == target[field], field - - -@pytest.mark.parametrize("slug", CODE_SLUGS) -def test_code_slug_bills_at_grok_build_rate(cost_map: dict, slug: str): - """grok-code-fast* are aliases of grok-build-0.1, not grok-4.3 redirects.""" - target = cost_map[CODE_REDIRECT_TARGET] - entry = cost_map[slug] - for field in (*BASE_COST_FIELDS, *TIER_COST_FIELDS): - assert entry[field] == target[field], field - - -@pytest.mark.parametrize("slug", REDIRECTED_SLUGS) -def test_redirected_slug_carries_the_target_tier_rates(cost_map: dict, slug: str): - """The request executes as grok-4.3, so it is tiered at grok-4.3's 200k boundary.""" - target = cost_map[REDIRECT_TARGET] - entry = cost_map[slug] - for field in TIER_COST_FIELDS: - assert entry[field] == target[field], field - assert {k for k in entry if "_above_" in k} == {k for k in target if "_above_" in k} - - -def test_both_cost_maps_agree_on_the_redirected_slugs(): - prices = json.loads(PRICES_PATH.read_text(encoding="utf-8")) - backup = json.loads(BACKUP_PRICES_PATH.read_text(encoding="utf-8")) - for slug in (*REDIRECTED_SLUGS, *CODE_SLUGS, REDIRECT_TARGET, CODE_REDIRECT_TARGET): - assert prices[slug] == backup[slug], slug diff --git a/tests/test_litellm/proxy/auth/test_auth_checks.py b/tests/test_litellm/proxy/auth/test_auth_checks.py index 14b739e60ba..ffba53a5b7a 100644 --- a/tests/test_litellm/proxy/auth/test_auth_checks.py +++ b/tests/test_litellm/proxy/auth/test_auth_checks.py @@ -8057,7 +8057,6 @@ def test_model_has_no_cost_mapping_no_model_or_router_is_false(): [ "azure/speech/azure-tts", "mistral/mistral-ocr-latest", - "vertex_ai/imagen-3.0-generate-001", "dashscope/qwen-flash", ], ) diff --git a/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_anthropic_passthrough_logging_handler.py b/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_anthropic_passthrough_logging_handler.py index ba8b5fa3ac4..094320225cd 100644 --- a/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_anthropic_passthrough_logging_handler.py +++ b/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_anthropic_passthrough_logging_handler.py @@ -588,43 +588,6 @@ class TestAzureAnthropicCostCalculation: == "claude-3-5-haiku-20241022" ) - def test_passthrough_logging_sets_response_cost_with_server_tool_use_dict(self): - from litellm.types.utils import Choices, Message, ModelResponse - - logging_obj = self._create_mock_logging_obj(model="claude-3-7-sonnet-20250219") - logging_obj.get_router_model_id.return_value = None - logging_obj.litellm_params = {} - - response = ModelResponse( - id="test-id", - choices=[ - Choices( - finish_reason="stop", - index=0, - message=Message(content="test", role="assistant"), - ) - ], - created=1234567890, - model="claude-3-7-sonnet-20250219", - usage={ - "prompt_tokens": 10, - "completion_tokens": 5, - "total_tokens": 15, - "server_tool_use": {"web_search_requests": 1}, - }, - ) - - kwargs = AnthropicPassthroughLoggingHandler._create_anthropic_response_logging_payload( - litellm_model_response=response, - model="claude-3-7-sonnet-20250219", - kwargs={}, - start_time=datetime.now(), - end_time=datetime.now(), - logging_obj=logging_obj, - ) - - assert "response_cost" in kwargs - assert kwargs["response_cost"] > 0 class TestAnthropicBatchPassthroughCostTracking: @@ -2355,42 +2318,6 @@ class TestAnthropicResponseCostRecordedOnModelCallDetails: model_call_details["response_cost"], not from kwargs, so the streaming payload builder must record it there or streaming pass-through logs $0.""" - def test_create_payload_records_response_cost_on_model_call_details(self): - from litellm.types.utils import Choices, Message, ModelResponse - - logging_obj = MagicMock() - logging_obj.model_call_details = {} - logging_obj.get_router_model_id.return_value = None - logging_obj.litellm_params = {} - logging_obj.litellm_call_id = "test-call-id" - - response = ModelResponse( - id="test-id", - choices=[ - Choices( - finish_reason="stop", - index=0, - message=Message(content="hello", role="assistant"), - ) - ], - created=1234567890, - model="claude-3-7-sonnet-20250219", - usage={"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15}, - ) - - kwargs = AnthropicPassthroughLoggingHandler._create_anthropic_response_logging_payload( - litellm_model_response=response, - model="claude-3-7-sonnet-20250219", - kwargs={}, - start_time=datetime.now(), - end_time=datetime.now(), - logging_obj=logging_obj, - ) - - assert ( - logging_obj.model_call_details["response_cost"] == kwargs["response_cost"] - ) - assert logging_obj.model_call_details["response_cost"] > 0 class TestAnthropicPassthroughFastMode: diff --git a/tests/test_litellm/proxy/pass_through_endpoints/test_vertex_ai_batch_passthrough.py b/tests/test_litellm/proxy/pass_through_endpoints/test_vertex_ai_batch_passthrough.py index 1d2d7d4d5c3..46f024366ec 100644 --- a/tests/test_litellm/proxy/pass_through_endpoints/test_vertex_ai_batch_passthrough.py +++ b/tests/test_litellm/proxy/pass_through_endpoints/test_vertex_ai_batch_passthrough.py @@ -462,30 +462,6 @@ class TestVertexAIBatchPassthroughHandler: assert mock_store.call_args[1]["unified_object_id"] assert mock_store.call_args[1]["is_batch_create"] is expected - def test_batch_cost_calculation_integration(self): - """Single Vertex AI response → non-zero cost with correct token counts.""" - from litellm.batches.batch_utils import calculate_vertex_ai_batch_cost_and_usage - - vertex_ai_batch_responses = [ - { - "response": { - "usageMetadata": { - "promptTokenCount": 10, - "candidatesTokenCount": 5, - "totalTokenCount": 15, - } - } - } - ] - - result = calculate_vertex_ai_batch_cost_and_usage( - vertex_ai_batch_responses, model_name="gemini-2.0-flash-001" - ) - - assert result.usage.total_tokens == 15 - assert result.usage.prompt_tokens == 10 - assert result.usage.completion_tokens == 5 - assert result.cost > 0, "batch_cost_calculator should return a non-zero cost" def test_batch_response_transformation(self): """Test transformation of Vertex AI batch responses to OpenAI format""" @@ -639,76 +615,7 @@ class TestVertexAIBatchCostCalculation: batch_cost_calculator — no VertexGeminiConfig transformation involved. """ - def test_should_aggregate_cost_and_usage_across_responses(self): - """Two successful responses → costs and token counts are summed.""" - from litellm.batches.batch_utils import calculate_vertex_ai_batch_cost_and_usage - responses = [ - { - "response": { - "usageMetadata": { - "promptTokenCount": 10, - "candidatesTokenCount": 5, - "totalTokenCount": 15, - } - } - }, - { - "response": { - "usageMetadata": { - "promptTokenCount": 8, - "candidatesTokenCount": 3, - "totalTokenCount": 11, - } - } - }, - ] - - result = calculate_vertex_ai_batch_cost_and_usage( - responses, model_name="gemini-2.0-flash-001" - ) - - assert result.usage.prompt_tokens == 18 - assert result.usage.completion_tokens == 8 - assert result.usage.total_tokens == 26 - assert result.cost > 0, "batch_cost_calculator should return a non-zero cost" - - def test_should_skip_responses_with_null_response_body(self): - """Failed lines (response: None) are skipped without error.""" - from litellm.batches.batch_utils import calculate_vertex_ai_batch_cost_and_usage - - responses = [ - { - "response": { - "usageMetadata": { - "promptTokenCount": 10, - "candidatesTokenCount": 5, - "totalTokenCount": 15, - } - } - }, - {"status": "JOB_STATE_FAILED", "response": None}, - { - "response": { - "usageMetadata": { - "promptTokenCount": 8, - "candidatesTokenCount": 3, - "totalTokenCount": 11, - } - } - }, - ] - - result = calculate_vertex_ai_batch_cost_and_usage( - responses, model_name="gemini-2.0-flash-001" - ) - - assert result.usage.prompt_tokens == 18 - assert result.usage.completion_tokens == 8 - assert result.usage.total_tokens == 26 - assert result.cost > 0 - assert result.successful_requests == 2 - assert result.failed_requests == 1 def test_should_return_zeros_for_empty_response_list(self): """Empty input → zero cost and zero usage.""" @@ -739,143 +646,4 @@ class TestVertexAIBatchCostCalculation: assert result.usage.completion_tokens == 0 assert result.usage.total_tokens == 0 - @pytest.mark.asyncio - async def test_openai_shaped_output_records_nonzero_cost_and_usage(self): - """ - Regression test for the bug where Vertex batch cost/usage was always 0. - After PR #25627 (transform_file_content_response), the GCS predictions.jsonl - is rewritten into OpenAI batch shape before the cost-tracking path sees it. - With disable_vertex_batch_output_transformation=False (default), the cost - dispatch must fall through to the generic aggregation path rather than - calling calculate_vertex_ai_batch_cost_and_usage (which only reads raw - usageMetadata fields). - """ - import litellm - from litellm.batches.batch_utils import calculate_batch_cost_and_usage - - openai_shaped_responses = [ - { - "id": "batch_req_abc123", - "custom_id": "request-1", - "response": { - "status_code": 200, - "request_id": "chatcmpl-xyz", - "body": { - "id": "chatcmpl-xyz", - "object": "chat.completion", - "model": "gemini-2.0-flash-001", - "choices": [ - { - "index": 0, - "message": {"role": "assistant", "content": "Hello!"}, - "finish_reason": "stop", - } - ], - "usage": { - "prompt_tokens": 10, - "completion_tokens": 5, - "total_tokens": 15, - }, - }, - }, - "error": None, - }, - { - "id": "batch_req_def456", - "custom_id": "request-2", - "response": { - "status_code": 200, - "request_id": "chatcmpl-uvw", - "body": { - "id": "chatcmpl-uvw", - "object": "chat.completion", - "model": "gemini-2.0-flash-001", - "choices": [ - { - "index": 0, - "message": {"role": "assistant", "content": "World!"}, - "finish_reason": "stop", - } - ], - "usage": { - "prompt_tokens": 8, - "completion_tokens": 3, - "total_tokens": 11, - }, - }, - }, - "error": None, - }, - ] - - original_flag = getattr( - litellm, "disable_vertex_batch_output_transformation", False - ) - try: - litellm.disable_vertex_batch_output_transformation = False - - result = await calculate_batch_cost_and_usage( - file_content_dictionary=openai_shaped_responses, - custom_llm_provider="vertex_ai", - model_name="gemini-2.0-flash-001", - ) - finally: - litellm.disable_vertex_batch_output_transformation = original_flag - - assert ( - result.usage.prompt_tokens == 18 - ), f"expected 18 prompt tokens, got {result.usage.prompt_tokens}" - assert ( - result.usage.completion_tokens == 8 - ), f"expected 8 completion tokens, got {result.usage.completion_tokens}" - assert ( - result.usage.total_tokens == 26 - ), f"expected 26 total tokens, got {result.usage.total_tokens}" - assert ( - result.cost > 0 - ), f"expected non-zero cost for completed Vertex batch, got {result.cost}" - - @pytest.mark.asyncio - async def test_raw_vertex_output_still_works_when_transformation_disabled(self): - """ - When disable_vertex_batch_output_transformation=True the GCS file is returned - as raw Vertex predictions.jsonl; the specialized reader must be used. - """ - import litellm - from litellm.batches.batch_utils import calculate_batch_cost_and_usage - - raw_vertex_responses = [ - { - "request": {"contents": [{"role": "user", "parts": [{"text": "hi"}]}]}, - "status": "", - "response": { - "candidates": [{"content": {"parts": [{"text": "Hello!"}]}}], - "usageMetadata": { - "promptTokenCount": 10, - "candidatesTokenCount": 5, - "totalTokenCount": 15, - }, - }, - "processed_time": "2026-01-01T00:00:00Z", - }, - ] - - original_flag = getattr( - litellm, "disable_vertex_batch_output_transformation", False - ) - try: - litellm.disable_vertex_batch_output_transformation = True - - result = await calculate_batch_cost_and_usage( - file_content_dictionary=raw_vertex_responses, - custom_llm_provider="vertex_ai", - model_name="gemini-2.0-flash-001", - ) - finally: - litellm.disable_vertex_batch_output_transformation = original_flag - - assert result.usage.prompt_tokens == 10 - assert result.usage.completion_tokens == 5 - assert result.usage.total_tokens == 15 - assert result.cost > 0, "raw Vertex shape should also produce non-zero cost" diff --git a/tests/test_litellm/proxy/spend_tracking/test_savings.py b/tests/test_litellm/proxy/spend_tracking/test_savings.py index 004f07da431..de413a86521 100644 --- a/tests/test_litellm/proxy/spend_tracking/test_savings.py +++ b/tests/test_litellm/proxy/spend_tracking/test_savings.py @@ -634,25 +634,6 @@ def test_equal_modeled_usage_is_zero_under_equivalent_model_names() -> None: assert _savings("claude-opus-5", "anthropic/claude-opus-5", usage, usage) == 0.0 -def test_baseline_is_priced_under_its_own_provider(): - """Two providers can serve the same bare model name at different rates, so dropping - the provider prices the baseline against a vendor the operator never named. Here it - decides whether routing reads as a saving or a loss.""" - usage = Usage(prompt_tokens=100_000, completion_tokens=10_000, total_tokens=110_000) - azure = compute_autorouter_savings( - baseline_model="azure_ai/deepseek-r1", - selected_model="claude-haiku-4-5", - selected_provider="anthropic", - usage=usage, - ) - deepseek = compute_autorouter_savings( - baseline_model="deepseek/deepseek-r1", - selected_model="claude-haiku-4-5", - selected_provider="anthropic", - usage=usage, - ) - assert azure != pytest.approx(deepseek) - assert azure > 0 > deepseek def test_unresolvable_baseline_remains_unknown(): diff --git a/tests/test_litellm/proxy/spend_tracking/test_spend_management_endpoints.py b/tests/test_litellm/proxy/spend_tracking/test_spend_management_endpoints.py index 16cbd109b24..e41c027d962 100644 --- a/tests/test_litellm/proxy/spend_tracking/test_spend_management_endpoints.py +++ b/tests/test_litellm/proxy/spend_tracking/test_spend_management_endpoints.py @@ -3887,179 +3887,7 @@ class TestSpendLogsPayload: } return mock_response - @pytest.mark.asyncio - async def test_spend_logs_payload_success_log_with_api_base(self, monkeypatch): - from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler - # Clear any env overrides that would change the recorded api_base - monkeypatch.delenv("ANTHROPIC_BASE_URL", raising=False) - monkeypatch.delenv("ANTHROPIC_API_BASE", raising=False) - - litellm.callbacks = [_ProxyDBLogger(message_logging=False)] - # litellm._turn_on_debug() - - client = AsyncHTTPHandler() - - with ( - patch.object( - litellm.proxy.db.db_spend_update_writer.DBSpendUpdateWriter, - "_insert_spend_log_to_db", - ) as mock_client, - patch.object(litellm.proxy.proxy_server, "prisma_client"), - patch.object(client, "post", side_effect=self.mock_anthropic_response), - ): - response = await litellm.acompletion( - model="claude-4-sonnet-20250514", - messages=[{"role": "user", "content": "Hello, world!"}], - metadata={"user_api_key_end_user_id": "test_user_1"}, - client=client, - ) - - assert response.choices[0].message.content == "Hi! My name is Claude." - - await _wait_for_mock_call(mock_client) - - kwargs = mock_client.call_args.kwargs - payload: SpendLogsPayload = kwargs["payload"] - expected_payload = SpendLogsPayload( - **{ - "request_id": "chatcmpl-34df56d5-4807-45c1-bb99-61e52586b802", - "call_type": "acompletion", - "api_key": "", - "cache_hit": "None", - "startTime": datetime.datetime( - 2025, 3, 24, 22, 2, 42, 975883, tzinfo=datetime.timezone.utc - ), - "endTime": datetime.datetime( - 2025, 3, 24, 22, 2, 42, 989132, tzinfo=datetime.timezone.utc - ), - "completionStartTime": datetime.datetime( - 2025, 3, 24, 22, 2, 42, 989132, tzinfo=datetime.timezone.utc - ), - "model": "claude-4-sonnet-20250514", - "user": "", - "team_id": "", - "metadata": '{"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, "usage_object": {"completion_tokens": 503, "prompt_tokens": 2095, "total_tokens": 2598, "completion_tokens_details": null, "prompt_tokens_details": {"audio_tokens": null, "cached_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0}, "model_map_information": {"model_map_key": "claude-4-sonnet-20250514", "model_map_value": {"key": "claude-4-sonnet-20250514", "max_tokens": 128000, "max_input_tokens": 200000, "max_output_tokens": 128000, "input_cost_per_token": 3e-06, "cache_creation_input_token_cost": 3.75e-06, "cache_read_input_token_cost": 3e-07, "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": null, "output_cost_per_token_batches": null, "output_cost_per_token": 1.5e-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": "anthropic", "mode": "chat", "supports_system_messages": null, "supports_response_schema": true, "supports_vision": true, "supports_function_calling": true, "supports_tool_choice": true, "supports_assistant_prefill": true, "supports_prompt_caching": true, "supports_audio_input": false, "supports_audio_output": false, "supports_pdf_input": true, "supports_embedding_image_input": false, "supports_native_streaming": null, "supports_web_search": false, "supports_reasoning": true, "search_context_cost_per_query": null, "tpm": null, "rpm": null, "supported_openai_params": ["stream", "stop", "temperature", "top_p", "max_tokens", "max_completion_tokens", "tools", "tool_choice", "extra_headers", "parallel_tool_calls", "response_format", "user", "reasoning_effort", "thinking"]}}, "additional_usage_values": {"completion_tokens_details": {"accepted_prediction_tokens": null, "audio_tokens": null, "reasoning_tokens": null, "rejected_prediction_tokens": null, "text_tokens": 503, "image_tokens": null}, "prompt_tokens_details": {"audio_tokens": null, "cached_tokens": 0, "text_tokens": null, "image_tokens": null}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0}}', - "cache_key": "Cache OFF", - "spend": 0.01383, - "total_tokens": 2598, - "prompt_tokens": 2095, - "completion_tokens": 503, - "request_tags": "[]", - "end_user": "test_user_1", - "api_base": "https://api.anthropic.com/v1/messages", - "model_group": "", - "model_id": "", - "requester_ip_address": None, - "custom_llm_provider": "anthropic", - "messages": "{}", - "response": "{}", - "proxy_server_request": "{}", - "status": "success", - "mcp_namespaced_tool_name": None, - "agent_id": None, - } - ) - - differences = _compare_nested_dicts( - payload, expected_payload, ignore_keys=ignored_keys - ) - if differences: - pytest.fail(f"Dictionary mismatch: {differences}") - - @pytest.mark.asyncio - async def test_spend_logs_payload_success_log_with_router(self, monkeypatch): - from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler - - # Clear any env overrides that would change the recorded api_base - monkeypatch.delenv("ANTHROPIC_BASE_URL", raising=False) - monkeypatch.delenv("ANTHROPIC_API_BASE", raising=False) - - litellm.callbacks = [_ProxyDBLogger(message_logging=False)] - # litellm._turn_on_debug() - - client = AsyncHTTPHandler() - - router = Router( - model_list=[ - { - "model_name": "my-anthropic-model-group", - "litellm_params": { - "model": "claude-4-sonnet-20250514", - }, - "model_info": { - "id": "my-unique-model-id", - }, - } - ] - ) - - with ( - patch.object( - litellm.proxy.db.db_spend_update_writer.DBSpendUpdateWriter, - "_insert_spend_log_to_db", - ) as mock_client, - patch.object(litellm.proxy.proxy_server, "prisma_client"), - patch.object(client, "post", side_effect=self.mock_anthropic_response), - ): - response = await router.acompletion( - model="my-anthropic-model-group", - messages=[{"role": "user", "content": "Hello, world!"}], - metadata={"user_api_key_end_user_id": "test_user_1"}, - client=client, - ) - - assert response.choices[0].message.content == "Hi! My name is Claude." - - await _wait_for_mock_call(mock_client) - - kwargs = mock_client.call_args.kwargs - payload: SpendLogsPayload = kwargs["payload"] - expected_payload = SpendLogsPayload( - **{ - "request_id": "chatcmpl-34df56d5-4807-45c1-bb99-61e52586b802", - "call_type": "acompletion", - "api_key": "", - "cache_hit": "None", - "startTime": datetime.datetime( - 2025, 3, 24, 22, 2, 42, 975883, tzinfo=datetime.timezone.utc - ), - "endTime": datetime.datetime( - 2025, 3, 24, 22, 2, 42, 989132, tzinfo=datetime.timezone.utc - ), - "completionStartTime": datetime.datetime( - 2025, 3, 24, 22, 2, 42, 989132, tzinfo=datetime.timezone.utc - ), - "model": "claude-4-sonnet-20250514", - "user": "", - "team_id": "", - "metadata": '{"applied_guardrails": [], "attempted_fallbacks": 0, "original_model_group": "my-anthropic-model-group", "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, "usage_object": {"completion_tokens": 503, "prompt_tokens": 2095, "total_tokens": 2598, "completion_tokens_details": null, "prompt_tokens_details": {"audio_tokens": null, "cached_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0}, "model_map_information": {"model_map_key": "claude-4-sonnet-20250514", "model_map_value": {"key": "claude-4-sonnet-20250514", "max_tokens": 128000, "max_input_tokens": 200000, "max_output_tokens": 128000, "input_cost_per_token": 3e-06, "cache_creation_input_token_cost": 3.75e-06, "cache_read_input_token_cost": 3e-07, "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": null, "output_cost_per_token_batches": null, "output_cost_per_token": 1.5e-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": "anthropic", "mode": "chat", "supports_system_messages": null, "supports_response_schema": true, "supports_vision": true, "supports_function_calling": true, "supports_tool_choice": true, "supports_assistant_prefill": true, "supports_prompt_caching": true, "supports_audio_input": false, "supports_audio_output": false, "supports_pdf_input": true, "supports_embedding_image_input": false, "supports_native_streaming": null, "supports_web_search": false, "supports_reasoning": true, "search_context_cost_per_query": null, "tpm": null, "rpm": null, "supported_openai_params": ["stream", "stop", "temperature", "top_p", "max_tokens", "max_completion_tokens", "tools", "tool_choice", "extra_headers", "parallel_tool_calls", "response_format", "user", "reasoning_effort", "thinking"]}}, "additional_usage_values": {"completion_tokens_details": {"accepted_prediction_tokens": null, "audio_tokens": null, "reasoning_tokens": null, "rejected_prediction_tokens": null, "text_tokens": 503, "image_tokens": null}, "prompt_tokens_details": {"audio_tokens": null, "cached_tokens": 0, "text_tokens": null, "image_tokens": null}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0}}', - "cache_key": "Cache OFF", - "spend": 0.01383, - "total_tokens": 2598, - "prompt_tokens": 2095, - "completion_tokens": 503, - "request_tags": "[]", - "end_user": "test_user_1", - "api_base": "https://api.anthropic.com/v1/messages", - "model_group": "my-anthropic-model-group", - "model_id": "my-unique-model-id", - "requester_ip_address": None, - "custom_llm_provider": "anthropic", - "messages": "{}", - "response": "{}", - "proxy_server_request": "{}", - "status": "success", - "mcp_namespaced_tool_name": None, - "agent_id": None, - } - ) - - differences = _compare_nested_dicts( - payload, expected_payload, ignore_keys=ignored_keys - ) - if differences: - pytest.fail(f"Dictionary mismatch: {differences}") def _compare_nested_dicts( diff --git a/tests/test_litellm/responses/test_metadata_codex_callback.py b/tests/test_litellm/responses/test_metadata_codex_callback.py index f151f36be63..d5c411d63db 100644 --- a/tests/test_litellm/responses/test_metadata_codex_callback.py +++ b/tests/test_litellm/responses/test_metadata_codex_callback.py @@ -48,72 +48,6 @@ class MetadataCaptureCallback(CustomLogger): self.event.set() -@pytest.mark.asyncio -async def test_metadata_passed_to_custom_callback_codex_models(): - """ - Test that metadata passed to completion() is available in custom callback - when using codex models (responses API bridge path). - - Codex models have mode=responses and route through responses_api_bridge, - which passes litellm_metadata. The fix ensures this is preserved as - litellm_params.metadata for callback compatibility. - """ - from litellm.types.llms.openai import ResponsesAPIResponse - - mock_response = ResponsesAPIResponse.model_construct( - id="resp-test", - created_at=0, - output=[ - { - "type": "message", - "id": "msg-1", - "status": "completed", - "role": "assistant", - "content": [{"type": "output_text", "text": "Hello!"}], - } - ], - object="response", - model="gpt-5.1-codex", - status="completed", - usage={ - "input_tokens": 5, - "output_tokens": 10, - "total_tokens": 15, - }, - ) - - test_metadata = {"foo": "bar", "trace_id": "test-123"} - callback = MetadataCaptureCallback() - original_callbacks = litellm.callbacks.copy() if litellm.callbacks else [] - litellm.callbacks = [callback] - - try: - with patch( - "litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler.post", - new_callable=AsyncMock, - ) as mock_post: - mock_post.return_value = _make_mock_http_response( - mock_response.model_dump() - ) - # gpt-5.1-codex has mode=responses - routes through responses bridge - await litellm.acompletion( - model="gpt-5.1-codex", - messages=[{"role": "user", "content": "Hello"}], - metadata=test_metadata, - ) - - await asyncio.wait_for(callback.event.wait(), timeout=5.0) - - assert callback.captured_kwargs is not None, "Callback should have been invoked" - - litellm_params = callback.captured_kwargs.get("litellm_params", {}) - metadata = litellm_params.get("metadata") or {} - - assert "foo" in metadata, "metadata['foo'] should be accessible in callback" - assert metadata["foo"] == "bar" - assert metadata.get("trace_id") == "test-123" - finally: - litellm.callbacks = original_callbacks @pytest.mark.asyncio diff --git a/tests/test_litellm/rust_bridge/test_token_counter.py b/tests/test_litellm/rust_bridge/test_token_counter.py index 101fda629a7..3af7127a9b3 100644 --- a/tests/test_litellm/rust_bridge/test_token_counter.py +++ b/tests/test_litellm/rust_bridge/test_token_counter.py @@ -148,7 +148,6 @@ async def test_each_tokenizer_gets_its_own_cached_counter(fake_tokenizers: None) ("gpt-4o", "o200k_base"), ("gpt-4o-mini", "o200k_base"), ("gpt-4o-2024-08-06", "o200k_base"), - ("chatgpt-4o-latest", "o200k_base"), ("gpt-4.1", "o200k_base"), ("gpt-5", "o200k_base"), ("gpt-5-mini", "o200k_base"), diff --git a/tests/test_litellm/test_cost_calculator.py b/tests/test_litellm/test_cost_calculator.py index ecc01857f8c..e7ce9a74797 100644 --- a/tests/test_litellm/test_cost_calculator.py +++ b/tests/test_litellm/test_cost_calculator.py @@ -159,131 +159,8 @@ def test_cost_calculator_with_response_cost_in_additional_headers(): assert result == 1000 -def test_cost_calculator_with_usage(_local_model_cost_map, monkeypatch): - - usage = Usage( - prompt_tokens=120, - completion_tokens=100, - prompt_tokens_details=PromptTokensDetailsWrapper( - text_tokens=10, - audio_tokens=90, - image_tokens=20, - ), - ) - mr = ModelResponse(usage=usage, model="gemini-2.0-flash-001") - - result = response_cost_calculator( - response_object=mr, - model="", - custom_llm_provider="vertex_ai", - call_type="acompletion", - optional_params={}, - cache_hit=None, - base_model=None, - ) - - model_info = litellm.model_cost["gemini-2.0-flash-001"] - - # Step 1: Test a model where input_cost_per_image_token is not set. - # In this case the calculation should use input_cost_per_token as fallback. - assert model_info.get("input_cost_per_image_token") is None, ( - "Test case expects that input_cost_per_image_token is not set" - ) - - expected_cost = ( - usage.prompt_tokens_details.audio_tokens * model_info["input_cost_per_audio_token"] - + usage.prompt_tokens_details.text_tokens * model_info["input_cost_per_token"] - + usage.prompt_tokens_details.image_tokens * model_info["input_cost_per_token"] - + usage.completion_tokens * model_info["output_cost_per_token"] - ) - - assert result == expected_cost, f"Got {result}, Expected {expected_cost}" - - # Step 2: Set input_cost_per_image_token. - # In this case the explicit cost information should be used. - temp_model_info_object = dict(model_info) - temp_model_info_object["input_cost_per_image_token"] = 0.5 - - monkeypatch.setattr( - litellm, - "model_cost", - {"gemini-2.0-flash-001": temp_model_info_object}, - ) - - # Invalidate caches after modifying litellm.model_cost - from litellm.utils import _invalidate_model_cost_lowercase_map - - _invalidate_model_cost_lowercase_map() - - result = response_cost_calculator( - response_object=mr, - model="", - custom_llm_provider="vertex_ai", - call_type="acompletion", - optional_params={}, - cache_hit=None, - base_model=None, - ) - - expected_cost = ( - usage.prompt_tokens_details.audio_tokens * temp_model_info_object["input_cost_per_audio_token"] - + usage.prompt_tokens_details.text_tokens * temp_model_info_object["input_cost_per_token"] - + usage.prompt_tokens_details.image_tokens * temp_model_info_object["input_cost_per_image_token"] - + usage.completion_tokens * temp_model_info_object["output_cost_per_token"] - ) - - assert result == expected_cost, f"Got {result}, Expected {expected_cost}" -def test_handle_realtime_stream_cost_calculation_stores_cost_breakdown(): - """Regression: realtime cost must populate logging_obj.cost_breakdown so the - spend logs / UI show input vs output cost (issue: cost_breakdown was None for - /v1/realtime even though a total spend was computed).""" - from datetime import datetime - - from litellm.litellm_core_utils.litellm_logging import Logging - - results: OpenAIRealtimeStreamList = [ - {"type": "session.created", "session": {"model": "gpt-4o-realtime-preview"}}, - { - "type": "response.done", - "response": { - "usage": { - "input_tokens": 100, - "output_tokens": 50, - "total_tokens": 150, - } - }, - }, - ] - combined_usage_object = RealtimeAPITokenUsageProcessor.collect_and_combine_usage_from_realtime_stream_results( - results=results, - ) - - logging_obj = Logging( - model="gpt-4o-realtime-preview", - messages=[], - stream=False, - call_type="_arealtime", - start_time=datetime.now(), - litellm_call_id="realtime-cost-breakdown-test", - function_id="realtime-cost-breakdown-test", - ) - - total_cost = handle_realtime_stream_cost_calculation( - results=results, - combined_usage_object=combined_usage_object, - custom_llm_provider="openai", - litellm_model_name="gpt-4o-realtime-preview", - litellm_logging_obj=logging_obj, - ) - - assert total_cost > 0 - assert logging_obj.cost_breakdown is not None - assert logging_obj.cost_breakdown["input_cost"] > 0 - assert logging_obj.cost_breakdown["output_cost"] > 0 - assert abs(logging_obj.cost_breakdown["input_cost"] + logging_obj.cost_breakdown["output_cost"] - total_cost) < 1e-9 - assert abs(logging_obj.cost_breakdown["total_cost"] - total_cost) < 1e-9 def test_realtime_stream_combines_text_and_audio_token_details(): @@ -1124,126 +1001,6 @@ def test_bedrock_cost_calculator_comparison_with_without_cache(): print(f"Cost with cache: {cost_with_cache}") -def test_log_context_cost_calculation(): - """ - Test that log context cost calculation works correctly with tiered pricing. - - This test verifies that when using extended context (above 200k tokens), - the log context costs are calculated using the appropriate tiered rates. - """ - from litellm import completion_cost - from litellm.types.utils import ( - Choices, - Message, - ModelResponse, - PromptTokensDetailsWrapper, - Usage, - ) - - # Create a mock response with extended context usage - extended_context_response = ModelResponse( - id="test-extended-context-response", - created=1750733889, - model="claude-4-sonnet-20250514", - object="chat.completion", - system_fingerprint=None, - choices=[ - Choices( - finish_reason="stop", - index=0, - message=Message( - content="This is a test response for extended context cost calculation.", - role="assistant", - tool_calls=None, - function_call=None, - ), - ) - ], - usage=Usage( - total_tokens=350000, # Above 200k threshold - prompt_tokens=301000, # Above 200k threshold - completion_tokens=50000, - prompt_tokens_details=PromptTokensDetailsWrapper( - text_tokens=300000, - cached_tokens=0, # No cache hits - audio_tokens=None, - image_tokens=None, - character_count=None, - video_length_seconds=None, - cache_creation_tokens=1000, - ), - completion_tokens_details=None, - _cache_creation_input_tokens=1000, # Some tokens added to cache - ), - ) - - # Calculate the cost using the extended context model - result = completion_cost( - completion_response=extended_context_response, - model="claude-4-sonnet-20250514", - custom_llm_provider="anthropic", - ) - - # Debug: Print the actual result - print(f"DEBUG: Actual cost result: ${result:.6f}") - - # Get model info to understand the pricing - from litellm import get_model_info - - model_info = get_model_info(model="claude-4-sonnet-20250514", custom_llm_provider="anthropic") - - # Calculate expected cost based on actual model pricing - input_cost_per_token = model_info.get("input_cost_per_token", 0) - output_cost_per_token = model_info.get("output_cost_per_token", 0) - cache_creation_cost_per_token = model_info.get("cache_creation_input_token_cost", 0) - - # Check if tiered pricing is applied - input_cost_above_200k = model_info.get("input_cost_per_token_above_200k_tokens", input_cost_per_token) - output_cost_above_200k = model_info.get("output_cost_per_token_above_200k_tokens", output_cost_per_token) - cache_creation_above_200k = model_info.get( - "cache_creation_input_token_cost_above_200k_tokens", - cache_creation_cost_per_token, - ) - - print(f"DEBUG: Base input cost per token: ${input_cost_per_token:.2e}") - print(f"DEBUG: Base output cost per token: ${output_cost_per_token:.2e}") - print(f"DEBUG: Base cache creation cost per token: ${cache_creation_cost_per_token:.2e}") - - # Handle tiered pricing - if not available, use base pricing - if input_cost_above_200k is not None: - print(f"DEBUG: Tiered input cost per token (>200k): ${input_cost_above_200k:.2e}") - else: - print("DEBUG: No tiered input pricing available, using base pricing") - input_cost_above_200k = input_cost_per_token - - if output_cost_above_200k is not None: - print(f"DEBUG: Tiered output cost per token (>200k): ${output_cost_above_200k:.2e}") - else: - print("DEBUG: No tiered output pricing available, using base pricing") - output_cost_above_200k = output_cost_per_token - - if cache_creation_above_200k is not None: - print(f"DEBUG: Tiered cache creation cost per token (>200k): ${cache_creation_above_200k:.2e}") - else: - print("DEBUG: No tiered cache creation pricing available, using base pricing") - cache_creation_above_200k = cache_creation_cost_per_token - - # Since we're above 200k tokens, we should use tiered pricing if available - expected_input_cost = 300000 * input_cost_above_200k - expected_output_cost = 50000 * output_cost_above_200k - expected_cache_cost = 1000 * cache_creation_above_200k - expected_total = expected_input_cost + expected_output_cost + expected_cache_cost - - print(f"DEBUG: Expected total: ${expected_total:.6f}") - - # Allow for small floating point differences - assert abs(result - expected_total) < 1e-6, f"Expected cost ${expected_total:.6f}, but got ${result:.6f}" - - print(f"✓ Log context cost calculation with tiered pricing is correct: ${result:.6f}") - print(f" - Input tokens (300k): ${expected_input_cost:.6f}") - print(f" - Output tokens (50k): ${expected_output_cost:.6f}") - print(f" - Cache creation (1k): ${expected_cache_cost:.6f}") - print(f" - Total: ${result:.6f}") def test_gemini_25_explicit_caching_cost_direct_usage(): @@ -1814,56 +1571,6 @@ def test_cost_margin_with_discount(monkeypatch): print(f" - Expected: ${expected_cost:.6f}") -def test_azure_image_generation_cost_calculator(): - from unittest.mock import MagicMock - - from litellm.types.utils import ( - ImageObject, - ImageResponse, - ImageUsage, - ImageUsageInputTokensDetails, - ) - - response_cost_calculator_kwargs = { - "response_object": ImageResponse( - created=1761785270, - background=None, - data=[ - ImageObject( - b64_json=None, - revised_prompt="A futuristic, techno-inspired green duck wearing cool modern sunglasses. The duck has a sleek, metallic appearance with glowing neon green accents, standing on a high-tech urban background with holographic billboards and illuminated city lights in the distance. The duck's feathers have a glossy, high-tech sheen, resembling a robotic design but still maintaining its avian features. The scene has a vibrant, cyberpunk aesthetic with a neon color palette.", - url="test-azure-blob-url-with-sas-token", - ) - ], - output_format=None, - quality="hd", - size=None, - usage=ImageUsage( - input_tokens=0, - input_tokens_details=ImageUsageInputTokensDetails(image_tokens=0, text_tokens=0), - output_tokens=0, - total_tokens=0, - ), - ), - "model": "azure/dall-e-3", - "cache_hit": False, - "custom_llm_provider": "azure", - "base_model": "azure/dall-e-3", - "call_type": "aimage_generation", - "optional_params": {}, - "custom_pricing": False, - "prompt": "", - "standard_built_in_tools_params": { - "web_search_options": None, - "file_search": None, - }, - "router_model_id": "6738c432ffc9b733597c6b86613ca20dc5f49bde591fd3d03e7cd6aa25bb241e", - "litellm_logging_obj": MagicMock(), - "service_tier": None, - } - - cost = response_cost_calculator(**response_cost_calculator_kwargs) - assert cost > 0.079 def test_completion_cost_extracts_service_tier_from_response(_local_model_cost_map): @@ -2616,87 +2323,6 @@ def test_gemini_without_cache_tokens_details(): print("✅ Gemini without cacheTokensDetails works correctly") -def test_gemini_implicit_caching_cost_calculation(): - """ - Test for Issue #16341: Gemini implicit cached tokens not counted in spend log - - When Gemini uses implicit caching, it returns cachedContentTokenCount but NOT - cacheTokensDetails. In this case, we should subtract cachedContentTokenCount - from text_tokens to correctly calculate costs. - - See: https://github.com/BerriAI/litellm/issues/16341 - """ - from litellm import completion_cost - from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import ( - VertexGeminiConfig, - ) - from litellm.types.utils import Choices, Message, ModelResponse - - # Simulate Gemini response with implicit caching (cachedContentTokenCount only) - completion_response = { - "usageMetadata": { - "promptTokenCount": 10000, - "candidatesTokenCount": 5, - "totalTokenCount": 10005, - "cachedContentTokenCount": 8000, # Implicit caching - no cacheTokensDetails - "promptTokensDetails": [{"modality": "TEXT", "tokenCount": 10000}], - "candidatesTokensDetails": [{"modality": "TEXT", "tokenCount": 5}], - } - } - - usage = VertexGeminiConfig._calculate_usage(completion_response) - - # Verify parsing - assert usage.cache_read_input_tokens == 8000, ( - f"cache_read_input_tokens should be 8000, got {usage.cache_read_input_tokens}" - ) - assert usage.prompt_tokens_details.cached_tokens == 8000, ( - f"cached_tokens should be 8000, got {usage.prompt_tokens_details.cached_tokens}" - ) - - # CRITICAL: text_tokens should be (10000 - 8000) = 2000, NOT 10000 - # This is the fix for issue #16341 - assert usage.prompt_tokens_details.text_tokens == 2000, ( - f"text_tokens should be 2000 (10000 - 8000), got {usage.prompt_tokens_details.text_tokens}" - ) - - # Verify cost calculation uses cached token pricing - response = ModelResponse( - id="mock-id", - model="gemini-2.0-flash", - choices=[ - Choices( - index=0, - message=Message(role="assistant", content="Hello!"), - finish_reason="stop", - ) - ], - usage=usage, - ) - - cost = completion_cost( - completion_response=response, - model="gemini-2.0-flash", - custom_llm_provider="gemini", - ) - - # Get model pricing for verification - import litellm - - model_info = litellm.get_model_info("gemini/gemini-2.0-flash") - input_cost = model_info.get("input_cost_per_token", 0) - cache_read_cost = model_info.get("cache_read_input_token_cost", input_cost) - output_cost = model_info.get("output_cost_per_token", 0) - - # Expected cost: (2000 * input) + (8000 * cache_read) + (5 * output) - expected_cost = (2000 * input_cost) + (8000 * cache_read_cost) + (5 * output_cost) - - assert abs(cost - expected_cost) < 1e-9, ( - f"Cost calculation is wrong. Got ${cost:.6f}, expected ${expected_cost:.6f}. " - f"Cached tokens may not be using reduced pricing." - ) - - print("✅ Issue #16341 fix verified: Gemini implicit caching cost calculated correctly") def test_additional_costs_only_for_azure_ai(_local_model_cost_map): diff --git a/tests/test_litellm/test_count_tokens_public_api.py b/tests/test_litellm/test_count_tokens_public_api.py index 2918d0aa522..84121dd63e4 100644 --- a/tests/test_litellm/test_count_tokens_public_api.py +++ b/tests/test_litellm/test_count_tokens_public_api.py @@ -157,21 +157,3 @@ def test_acount_tokens_no_api_key_falls_back(monkeypatch): assert result.tokenizer_type == "local_tokenizer" -async def test_acount_tokens_local_fallback_counts_off_the_event_loop(): - from tests.large_text import text - from tests.test_litellm.litellm_core_utils.event_loop_lag import ( - assert_loop_stayed_free, - timed_with_loop_lags, - warm_tokenizer, - ) - - model = "together_ai/meta-llama/Llama-3-8b-chat-hf" - warm_tokenizer(model) - - result, took, lags = await timed_with_loop_lags( - lambda: litellm.acount_tokens(model=model, messages=[{"role": "user", "content": text * 100}]) - ) - - assert result.tokenizer_type == "local_tokenizer" - assert result.total_tokens > 100_000 - assert_loop_stayed_free(took, lags) diff --git a/tests/test_litellm/test_gpt_image_cost_calculator.py b/tests/test_litellm/test_gpt_image_cost_calculator.py index 0f471430daf..d026285f9ae 100644 --- a/tests/test_litellm/test_gpt_image_cost_calculator.py +++ b/tests/test_litellm/test_gpt_image_cost_calculator.py @@ -90,27 +90,6 @@ class TestGPTImageCostCalculator: class TestGPTImageCostRouting: """Test that gpt-image models are properly routed to the token-based calculator""" - def test_openai_dalle_routes_to_pixel_calculator(self): - """Test that OpenAI DALL-E still routes to pixel-based calculator""" - from litellm.litellm_core_utils.llm_cost_calc.utils import CostCalculatorUtils - - image_response = ImageResponse( - created=1234567890, - data=[ImageObject(url="http://example.com/image.jpg")], - ) - image_response.size = "1024x1024" - image_response.quality = "standard" - - cost = CostCalculatorUtils.route_image_generation_cost_calculator( - model="dall-e-3", - completion_response=image_response, - custom_llm_provider="openai", - size="1024x1024", - quality="standard", - n=1, - ) - - assert cost >= 0 class TestGPTImage15OutputImageTokens: diff --git a/tests/test_litellm/test_router.py b/tests/test_litellm/test_router.py index f5344c01f3a..411377f29cf 100644 --- a/tests/test_litellm/test_router.py +++ b/tests/test_litellm/test_router.py @@ -850,36 +850,6 @@ async def test_arouter_async_get_healthy_deployments(): assert result[0]["litellm_params"]["model"] == "gpt-3.5-turbo" -@pytest.mark.asyncio -@patch("litellm.amoderation") -async def test_arouter_amoderation_with_credential_name(mock_amoderation): - """ - Test that router.amoderation passes litellm_credential_name to the underlying litellm.amoderation call - """ - mock_amoderation.return_value = AsyncMock() - - router = litellm.Router( - model_list=[ - { - "model_name": "text-moderation-stable", - "litellm_params": { - "model": "text-moderation-stable", - "litellm_credential_name": "my-custom-auth", - }, - }, - ], - ) - - await router.amoderation(input="I love everyone!", model="text-moderation-stable") - - mock_amoderation.assert_called_once() - call_kwargs = mock_amoderation.call_args[1] # Get the kwargs of the call - print( - "call kwargs for router.amoderation=", - json.dumps(call_kwargs, indent=4, default=str), - ) - assert call_kwargs["litellm_credential_name"] == "my-custom-auth" - assert call_kwargs["model"] == "text-moderation-stable" def test_arouter_test_team_model(): diff --git a/tests/test_litellm/test_together_ai_model_metadata.py b/tests/test_litellm/test_together_ai_model_metadata.py index 7176ba4f219..dccba3d66f9 100644 --- a/tests/test_litellm/test_together_ai_model_metadata.py +++ b/tests/test_litellm/test_together_ai_model_metadata.py @@ -95,15 +95,6 @@ def _successor(info: dict[str, object]) -> str | None: return successor if isinstance(successor, str) else None -def test_together_successor_metadata_points_at_known_models(cost_map: CostMap): - successors = { - model: successor - for model, info in cost_map.items() - if model.startswith("together_ai/") and (successor := _successor(info)) is not None - } - assert len(successors) >= 10 - for model, successor in successors.items(): - assert successor in cost_map, f"{model} names successor {successor} that is not in the map" def test_together_backup_cost_map_in_sync(cost_map: CostMap): diff --git a/tests/test_litellm/test_utils.py b/tests/test_litellm/test_utils.py index ead805eed42..07982f51153 100644 --- a/tests/test_litellm/test_utils.py +++ b/tests/test_litellm/test_utils.py @@ -1465,12 +1465,6 @@ class TestProxyFunctionCalling: ("gemini/gemini-2.5-pro", "litellm_proxy/gemini/gemini-2.5-pro", True), ("gemini/gemini-2.5-flash", "litellm_proxy/gemini/gemini-2.5-flash", True), # Groq models (mixed support) - ("groq/gemma-7b-it", "litellm_proxy/groq/gemma-7b-it", True), - ( - "groq/llama-3.3-70b-versatile", - "litellm_proxy/groq/llama-3.3-70b-versatile", - True, - ), # Cohere models (generally don't support function calling) ("command-nightly", "litellm_proxy/command-nightly", False), ], diff --git a/tests/test_litellm/test_xai_responses_auto_routing.py b/tests/test_litellm/test_xai_responses_auto_routing.py index d405ea1e6c6..c31f599dd79 100644 --- a/tests/test_litellm/test_xai_responses_auto_routing.py +++ b/tests/test_litellm/test_xai_responses_auto_routing.py @@ -46,34 +46,6 @@ class TestXAIResponsesAutoRouting: assert model_info.get("mode") != "responses" assert updated_model == model - def test_responses_api_bridge_check_with_tools(self): - """Test that with tools, xAI automatically routes to Responses API""" - model = "grok-3" - custom_llm_provider = "xai" - tools = [ - { - "type": "function", - "function": { - "name": "get_weather", - "description": "Get the weather", - "parameters": { - "type": "object", - "properties": {"location": {"type": "string"}}, - }, - }, - } - ] - web_search_options = None - - model_info, updated_model = responses_api_bridge_check( - model=model, - custom_llm_provider=custom_llm_provider, - web_search_options=web_search_options, - ) - - # Should auto-route to responses mode when tools are present - assert model_info.get("mode") == "chat" - assert updated_model == model def test_responses_api_bridge_check_with_empty_tools(self): """Test that with empty tools list, xAI does not route to Responses API""" @@ -134,57 +106,8 @@ class TestXAIResponsesAutoRouting: assert model_info.get("mode") == "responses" assert updated_model == "grok-3" # prefix removed - def test_responses_api_bridge_check_with_code_interpreter_tool(self): - """Test auto-routing with code_interpreter tool""" - model = "grok-3" - custom_llm_provider = "xai" - tools = [{"type": "code_interpreter"}] - web_search_options = None - model_info, updated_model = responses_api_bridge_check( - model=model, - custom_llm_provider=custom_llm_provider, - web_search_options=web_search_options, - ) - # Should auto-route with code_interpreter tool - assert model_info.get("mode") == "chat" - assert updated_model == model - def test_responses_api_bridge_check_with_web_search_tool(self): - """Test auto-routing with web_search tool""" - model = "grok-4" - custom_llm_provider = "xai" - tools = [ - {"type": "web_search", "filters": {"allowed_domains": ["wikipedia.org"]}} - ] - web_search_options = None - - model_info, updated_model = responses_api_bridge_check( - model=model, - custom_llm_provider=custom_llm_provider, - web_search_options=web_search_options, - ) - - # Should auto-route with web_search tool - assert model_info.get("mode") == "chat" - assert updated_model == model - - def test_responses_api_bridge_check_with_x_search_tool(self): - """Test auto-routing with x_search tool""" - model = "grok-4" - custom_llm_provider = "xai" - tools = [{"type": "x_search", "allowed_x_handles": ["@elonmusk"]}] - web_search_options = None - - model_info, updated_model = responses_api_bridge_check( - model=model, - custom_llm_provider=custom_llm_provider, - web_search_options=web_search_options, - ) - - # Should auto-route with x_search tool - assert model_info.get("mode") == "chat" - assert updated_model == model def test_responses_api_bridge_check_with_web_search_options(self): """Test auto-routing with web_search_options""" diff --git a/tests/unit/llms/azure_ai/chat/test_azure_ai_transformation.py b/tests/unit/llms/azure_ai/chat/test_azure_ai_transformation.py index e4a33d5772c..47609261a25 100644 --- a/tests/unit/llms/azure_ai/chat/test_azure_ai_transformation.py +++ b/tests/unit/llms/azure_ai/chat/test_azure_ai_transformation.py @@ -157,27 +157,6 @@ def test_foundry_gpt_6_astra_keeps_sampling_params_when_reasoning_effort_is_none assert optional_params == {"reasoning_effort": "none", "temperature": 0.2, "top_p": 0.9} -def test_a_gpt_5_name_without_a_foundry_row_keeps_reading_its_own_entry( - monkeypatch: pytest.MonkeyPatch, _local_model_cost_map -): - """Most gpt-5-family names have no azure_ai/ row. Reading an azure_ai/ key for those finds - nothing, and an openai.azure.com base sends the name down the azure provider, which has no key - for it either, so every effort answer would silently fall back to false and take temperature, - top_p and logprobs down with it.""" - monkeypatch.setenv("AZURE_AI_API_BASE", "https://example-resource.openai.azure.com") - monkeypatch.setenv("AZURE_AI_API_KEY", "placeholder") - - optional_params = litellm.utils.get_optional_params( - model="gpt-5.1-chat-latest", - custom_llm_provider="azure_ai", - temperature=0.2, - top_p=0.9, - logprobs=True, - ) - - assert optional_params["temperature"] == 0.2 - assert optional_params["top_p"] == 0.9 - assert optional_params["logprobs"] is True def test_azure_ai_grok_stop_parameter_handling(): diff --git a/tests/unit/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py b/tests/unit/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py index 6815f00267c..3f740edf834 100644 --- a/tests/unit/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py +++ b/tests/unit/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py @@ -1695,21 +1695,6 @@ def test_nim_vllm_extras_translated_end_to_end_in_request_body(): assert request_body["top_k"] == 40 -def test_in_schema_unsupported_params_still_raise(): - with pytest.raises(litellm.UnsupportedParamsError): - litellm.get_optional_params( - model="accounts/fireworks/models/llama-v3-70b-instruct", - custom_llm_provider="fireworks_ai", - drop_params=False, - store=True, - ) - optional_params = litellm.get_optional_params( - model="accounts/fireworks/models/llama-v3-70b-instruct", - custom_llm_provider="fireworks_ai", - drop_params=True, - store=True, - ) - assert "store" not in optional_params def test_streaming_preserves_selected_model_for_private_accounting(): diff --git a/tests/unit/llms/moonshot/test_moonshot_chat_transformation.py b/tests/unit/llms/moonshot/test_moonshot_chat_transformation.py index c39affc18a8..4e7a2931cda 100644 --- a/tests/unit/llms/moonshot/test_moonshot_chat_transformation.py +++ b/tests/unit/llms/moonshot/test_moonshot_chat_transformation.py @@ -715,7 +715,7 @@ class TestMoonshotReasoningEffort: def force_local_model_cost(self, monkeypatch): monkeypatch.setattr(litellm, "model_cost", GetModelCostMap.load_local_model_cost_map()) - @pytest.mark.parametrize("model", ["kimi-k3", "kimi-k2.5", "kimi-k2.6", "kimi-k2-thinking"]) + @pytest.mark.parametrize("model", ["kimi-k3", "kimi-k2.5", "kimi-k2.6"]) def test_reasoning_model_supports_reasoning_effort(self, model): assert "reasoning_effort" in MoonshotChatConfig().get_supported_openai_params(model) From c37fe46534519c9be7f0a80a0f6786d154e6bbd7 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 14:20:18 -0700 Subject: [PATCH 036/101] test(vcr): guard leaked cassette patches and make injected-transport embedding tests immune (#42542) * test(vcr): guard leaked cassette patches and make injected-transport embedding tests immune * test(vcr): derive the leak guard's patch points from vcrpy's own reset list * test(vcr): share CapturingTransport and switch the encoding_format embedding test to it --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- tests/_vcr_conftest_common.py | 245 ++++++++++-------- tests/capturing_transport.py | 25 ++ tests/llm_translation/conftest.py | 30 ++- .../test_litellm_proxy_provider.py | 98 +++---- tests/llm_translation/test_nvidia_nim.py | 32 +-- tests/llm_translation/test_vcr_leak_guard.py | 72 +++++ tests/local_testing/conftest.py | 1 - tests/local_testing/test_embedding.py | 27 +- 8 files changed, 331 insertions(+), 199 deletions(-) create mode 100644 tests/capturing_transport.py create mode 100644 tests/llm_translation/test_vcr_leak_guard.py diff --git a/tests/_vcr_conftest_common.py b/tests/_vcr_conftest_common.py index 4d5a73779ea..ab046674eb6 100644 --- a/tests/_vcr_conftest_common.py +++ b/tests/_vcr_conftest_common.py @@ -8,6 +8,7 @@ from __future__ import annotations import ast import atexit import hashlib +import inspect import json import os import re @@ -15,10 +16,18 @@ import socket import sys import threading from collections import defaultdict -from typing import Iterable +from collections.abc import Iterable, Iterator +from contextlib import contextmanager +from dataclasses import dataclass +from pathlib import Path +from typing import Final +from unittest import mock +import aiohttp import pytest +import vcr import vcr.matchers as _vcr_matchers +import vcr.patch as _vcr_patch from tests._vcr_redis_persister import ( MAX_EPISODES_PER_CASSETTE, @@ -127,9 +136,7 @@ def emit_vcr_diagnostic_log(terminalreporter) -> None: with open(path, "r", encoding="utf-8") as fh: content = fh.read() except OSError as exc: - read_errors.append( - f" [failed to read {name}: {type(exc).__name__}: {exc}]" - ) + read_errors.append(f" [failed to read {name}: {type(exc).__name__}: {exc}]") continue for line in content.splitlines(): if not line.strip(): @@ -142,9 +149,7 @@ def emit_vcr_diagnostic_log(terminalreporter) -> None: return terminalreporter.write_sep("=", "VCR DIAGNOSTIC LOG", bold=True) - terminalreporter.write_line( - f" source dir: {directory} (deduplicated; full log archived as a CI artifact)" - ) + terminalreporter.write_line(f" source dir: {directory} (deduplicated; full log archived as a CI artifact)") for line in read_errors: terminalreporter.write_line(line) @@ -235,9 +240,7 @@ def pin_httpx_multipart_boundary(monkeypatch) -> None: boundary = VCR_FIXED_MULTIPART_BOUNDARY.encode("ascii") return _original_init(self, data=data, files=files, boundary=boundary, **kwargs) - monkeypatch.setattr( - _httpx_multipart.MultipartStream, "__init__", _init_with_fixed_boundary - ) + monkeypatch.setattr(_httpx_multipart.MultipartStream, "__init__", _init_with_fixed_boundary) @pytest.fixture(scope="session", autouse=True) @@ -270,11 +273,7 @@ def _replace_b64_json_in_place(obj) -> bool: changed = False if isinstance(obj, dict): for key, value in obj.items(): - if ( - key == "b64_json" - and isinstance(value, str) - and len(value) > len(VCR_IMAGE_B64_PLACEHOLDER) - ): + if key == "b64_json" and isinstance(value, str) and len(value) > len(VCR_IMAGE_B64_PLACEHOLDER): obj[key] = VCR_IMAGE_B64_PLACEHOLDER changed = True elif _replace_b64_json_in_place(value): @@ -296,16 +295,12 @@ def _strip_image_b64_payloads(response): preserves all those checks while shrinking cassettes by ~99%. """ if not isinstance(response, dict): - vcr_diag_write_line( - f"[vcr-strip-b64] response is {type(response).__name__!r}, not " - "dict; skipping b64 scrub" - ) + vcr_diag_write_line(f"[vcr-strip-b64] response is {type(response).__name__!r}, not dict; skipping b64 scrub") return response body = response.get("body") if not isinstance(body, dict): vcr_diag_write_line( - f"[vcr-strip-b64] response['body'] is {type(body).__name__!r}, " - "not dict; skipping b64 scrub" + f"[vcr-strip-b64] response['body'] is {type(body).__name__!r}, not dict; skipping b64 scrub" ) return response raw = body.get("string") @@ -316,10 +311,7 @@ def _strip_image_b64_payloads(response): try: text = bytes(raw).decode("utf-8") except UnicodeDecodeError: - vcr_diag_write_line( - "[vcr-strip-b64] response body bytes are not valid UTF-8; " - "skipping b64 scrub" - ) + vcr_diag_write_line("[vcr-strip-b64] response body bytes are not valid UTF-8; skipping b64 scrub") return response was_bytes = True elif isinstance(raw, str): @@ -327,8 +319,7 @@ def _strip_image_b64_payloads(response): was_bytes = False else: vcr_diag_write_line( - f"[vcr-strip-b64] response['body']['string'] is " - f"{type(raw).__name__!r}, not bytes/str; skipping b64 scrub" + f"[vcr-strip-b64] response['body']['string'] is {type(raw).__name__!r}, not bytes/str; skipping b64 scrub" ) return response @@ -349,9 +340,7 @@ def _strip_image_b64_payloads(response): for key in list(headers): if str(key).lower() == "content-length": value = headers[key] - headers[key] = ( - [new_len_value] if isinstance(value, list) else new_len_value - ) + headers[key] = [new_len_value] if isinstance(value, list) else new_len_value return response @@ -409,15 +398,11 @@ def _canonical_body(request) -> tuple[bytes, str]: # selected. This mirrors the existing SigV4 / multipart-boundary / b64-image # normalizations already in this module, and means the already-bloated # cassettes start replaying immediately without a flush + re-record. -_VCR_UUID_RE = re.compile( - rb"[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12}" -) +_VCR_UUID_RE = re.compile(rb"[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12}") _VCR_LITELLM_BATCH_JOB_RE = re.compile(rb"litellm-batch-[0-9a-fA-F]{8}") # ISO-8601 timestamps, e.g. ``2026-05-25T03:40:37.262045Z`` / # ``2026-05-25T03:40:37+00:00``. -_VCR_ISO_TS_RE = re.compile( - rb"\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}(?:\.\d+)?(?:Z|[+-]\d{2}:?\d{2})?" -) +_VCR_ISO_TS_RE = re.compile(rb"\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}(?:\.\d+)?(?:Z|[+-]\d{2}:?\d{2})?") # Unix epoch as 13-digit milliseconds, then 10-digit ``time.time()`` float, # then 10-digit integer seconds. Anchored to ``1`` + 9/12 digits, which keeps # them inside the 2001-2033 / 2001-2033 epoch windows and avoids matching @@ -639,10 +624,7 @@ def _should_drop_telemetry_record(request) -> bool: return False if not _is_telemetry_request(request): return False - if ( - _is_telemetry_export_request(request) - and not _current_test_replays_telemetry_export() - ): + if _is_telemetry_export_request(request) and not _current_test_replays_telemetry_export(): return True return not _current_test_records_telemetry() @@ -767,9 +749,7 @@ def _iter_header_values(headers, name: str): yield value -_AWS_SIGV4_CREDENTIAL_RE = re.compile( - r"AWS4-HMAC-SHA256\s+Credential=([^/\s,]+)/", re.IGNORECASE -) +_AWS_SIGV4_CREDENTIAL_RE = re.compile(r"AWS4-HMAC-SHA256\s+Credential=([^/\s,]+)/", re.IGNORECASE) # Google OAuth2 access tokens always start with ``ya29.`` regardless of how # they were minted (service account, metadata server, impersonation). @@ -891,9 +871,7 @@ def _normalize_multipart_boundary(request) -> None: return try: - headers[content_type_key] = content_type_value.replace( - match.group(0), fixed_param - ) + headers[content_type_key] = content_type_value.replace(match.group(0), fixed_param) except (TypeError, AttributeError): return @@ -985,8 +963,7 @@ def _materialize_iterable_body(request) -> None: uri = getattr(request, "uri", getattr(request, "url", "?")) first_type = type(chunks[0]).__name__ if chunks else "empty" vcr_diag_write_line( - f"[vcr-materialize] FALLBACK: {method} {uri} chunk type " - f"{first_type!r} not coerced to bytes; storing b''" + f"[vcr-materialize] FALLBACK: {method} {uri} chunk type {first_type!r} not coerced to bytes; storing b''" ) out = b"" @@ -1026,9 +1003,7 @@ def _key_fingerprint_matcher(r1, r2) -> None: return def _fp(req): - for value in _iter_header_values( - getattr(req, "headers", None), KEY_FINGERPRINT_HEADER - ): + for value in _iter_header_values(getattr(req, "headers", None), KEY_FINGERPRINT_HEADER): if value is None: continue return value if isinstance(value, str) else str(value) @@ -1159,13 +1134,11 @@ def _print_atexit_banner() -> None: _emit("VCR CASSETTE CACHE DEGRADED") if save_failures: _emit( - f" {save_failures} cassette save failure(s); last error: " - f"{health.get('save_failure_last_error', '')}" + f" {save_failures} cassette save failure(s); last error: {health.get('save_failure_last_error', '')}" ) if load_failures: _emit( - f" {load_failures} cassette load failure(s); last error: " - f"{health.get('load_failure_last_error', '')}" + f" {load_failures} cassette load failure(s); last error: {health.get('load_failure_last_error', '')}" ) if snapshot: _emit(_format_capacity_line(snapshot)) @@ -1276,11 +1249,7 @@ class _RespxUsageVisitor(ast.NodeVisitor): if isinstance(dec, ast.Call): dec = dec.func if isinstance(dec, ast.Attribute): - return ( - isinstance(dec.value, ast.Name) - and dec.value.id == "respx" - and dec.attr == "mock" - ) + return isinstance(dec.value, ast.Name) and dec.value.id == "respx" and dec.attr == "mock" return False def _is_pytest_mark_respx(self, dec: ast.expr) -> bool: @@ -1307,9 +1276,7 @@ class _RespxUsageVisitor(ast.NodeVisitor): # ``def test_foo(respx_mock): ...`` — pytest supplies the fixture # whenever the parameter name appears, regardless of marker. all_args = ( - list(args.args) - + list(args.kwonlyargs) - + (list(args.posonlyargs) if hasattr(args, "posonlyargs") else []) + list(args.args) + list(args.kwonlyargs) + (list(args.posonlyargs) if hasattr(args, "posonlyargs") else []) ) for a in all_args: if a.arg == "respx_mock": @@ -1566,9 +1533,7 @@ def _emit_outcome_payload( }, ) ) - node.user_properties.append( - (_USER_PROP_RECORDED_BY, os.environ.get("PYTEST_XDIST_WORKER", "")) - ) + node.user_properties.append((_USER_PROP_RECORDED_BY, os.environ.get("PYTEST_XDIST_WORKER", ""))) def aggregate_report_outcome(report) -> None: @@ -1616,9 +1581,7 @@ def aggregate_report_outcome(report) -> None: if verdict == VERDICT_MISS_OVERFLOW: _session_stats["overflow_tests"].append(nodeid) elif verdict == VERDICT_UNMARKED_LIVE_CALL: - _session_stats["unmarked_live_call_tests"].append( - (nodeid, list(outcome.get("live_call_hosts") or [])) - ) + _session_stats["unmarked_live_call_tests"].append((nodeid, list(outcome.get("live_call_hosts") or []))) skip_reason = outcome.get("skip_reason") if skip_reason: @@ -1635,9 +1598,7 @@ def session_stats_snapshot() -> dict: "overflow_tests": list(_session_stats["overflow_tests"]), "unmarked_live_call_tests": list(_session_stats["unmarked_live_call_tests"]), "skip_reason_counts": dict(_session_stats["skip_reason_counts"]), - "skip_reason_examples": { - k: list(v) for k, v in _session_stats["skip_reason_examples"].items() - }, + "skip_reason_examples": {k: list(v) for k, v in _session_stats["skip_reason_examples"].items()}, } @@ -1810,9 +1771,7 @@ def record_vcr_outcome(request, vcr) -> None: # Cassette is None ⇒ test wasn't VCR-marked. Honor the skip reason # we tagged at collection time, and pull live-call hosts captured by # the socket probe (if any). - skip_reason = getattr( - request.node, VCR_SKIP_REASON_USER_ATTR, SKIP_REASON_FILE_OPT_OUT - ) + skip_reason = getattr(request.node, VCR_SKIP_REASON_USER_ATTR, SKIP_REASON_FILE_OPT_OUT) _session_stats["skip_reason_counts"][skip_reason] += 1 hosts = getattr(request.node, _LIVE_CALL_BUFFER_KEY, []) or [] @@ -1837,9 +1796,7 @@ def record_vcr_outcome(request, vcr) -> None: live_call_hosts=hosts, ) if vcr_outcome_logging_enabled(): - request.node.user_properties.append( - (_USER_PROP_VERDICT_LINE, _format_verdict_line(verdict, None, extra)) - ) + request.node.user_properties.append((_USER_PROP_VERDICT_LINE, _format_verdict_line(verdict, None, extra))) def install_live_call_probe(request, vcr) -> None: @@ -1858,9 +1815,7 @@ def install_live_call_probe(request, vcr) -> None: # Track the current test for telemetry-leak suppression (applies to every # test, VCR-marked or not). See ``_should_drop_telemetry_record``. global _current_test_nodeid - _current_test_nodeid = str( - getattr(getattr(request, "node", None), "nodeid", "") or "" - ) + _current_test_nodeid = str(getattr(getattr(request, "node", None), "nodeid", "") or "") if vcr is not None or vcr_disabled(): return None probe = _LiveCallProbe() @@ -1876,10 +1831,7 @@ def _format_capacity_line(snapshot: dict) -> str: pct = float(snapshot.get("used_pct", 0.0) or 0.0) used_mb = used / (1024 * 1024) cap_mb = cap / (1024 * 1024) - return ( - f" Cassette Redis usage: {used_mb:.1f} MiB / {cap_mb:.1f} MiB " - f"({pct:.1f}% of maxmemory)" - ) + return f" Cassette Redis usage: {used_mb:.1f} MiB / {cap_mb:.1f} MiB ({pct:.1f}% of maxmemory)" def emit_vcr_classification_summary(terminalreporter) -> None: @@ -1940,14 +1892,10 @@ def emit_vcr_classification_summary(terminalreporter) -> None: total_leaks = sum(leak_counts.values()) terminalreporter.write_sep("-", "VCR COST LEAK CHECK", bold=True) if total_leaks: - rendered = ", ".join( - f"{verdict}={count}" for verdict, count in leak_counts.items() if count - ) + rendered = ", ".join(f"{verdict}={count}" for verdict, count in leak_counts.items() if count) terminalreporter.write_line(f" FAIL: {rendered}") else: - terminalreporter.write_line( - " PASS: no overflow, partial, not-persisted, or unmarked live-call verdicts" - ) + terminalreporter.write_line(" PASS: no overflow, partial, not-persisted, or unmarked live-call verdicts") overflow = snapshot["overflow_tests"] if overflow: @@ -2007,18 +1955,14 @@ def emit_cassette_cache_session_banner(terminalreporter) -> None: snapshot = cassette_cache_capacity_snapshot() if save_failures or load_failures: - terminalreporter.write_sep( - "=", "VCR CASSETTE CACHE DEGRADED", red=True, bold=True - ) + terminalreporter.write_sep("=", "VCR CASSETTE CACHE DEGRADED", red=True, bold=True) if save_failures: terminalreporter.write_line( - f" {save_failures} cassette save failure(s); last error: " - f"{health.get('save_failure_last_error', '')}" + f" {save_failures} cassette save failure(s); last error: {health.get('save_failure_last_error', '')}" ) if load_failures: terminalreporter.write_line( - f" {load_failures} cassette load failure(s); last error: " - f"{health.get('load_failure_last_error', '')}" + f" {load_failures} cassette load failure(s); last error: {health.get('load_failure_last_error', '')}" ) terminalreporter.write_line( " Tests still passed because cassette persistence is best-effort, " @@ -2031,9 +1975,7 @@ def emit_cassette_cache_session_banner(terminalreporter) -> None: return if snapshot and snapshot["used_pct"] >= CASSETTE_CACHE_HIGH_WATER_FRACTION * 100: - terminalreporter.write_sep( - "=", "VCR CASSETTE CACHE NEAR CAPACITY", yellow=True, bold=True - ) + terminalreporter.write_sep("=", "VCR CASSETTE CACHE NEAR CAPACITY", yellow=True, bold=True) terminalreporter.write_line(_format_capacity_line(snapshot)) terminalreporter.write_line( " No save failures yet, but Redis is approaching maxmemory. " @@ -2082,13 +2024,104 @@ class VerboseReporterState: if reporter is None: return verdict = next( - ( - v - for k, v in (report.user_properties or []) - if k == _USER_PROP_VERDICT_LINE - ), + (v for k, v in (report.user_properties or []) if k == _USER_PROP_VERDICT_LINE), None, ) if not verdict: return reporter.write_line(f"{verdict} :: {report.nodeid}") + + +@dataclass(frozen=True, slots=True) +class VcrPatchPoint: + owner: object + attribute: str + original: object + + @property + def name(self) -> str: + return f"{_patch_owner_name(self.owner)}.{self.attribute}" + + def current(self) -> object: + current: Final[object] = getattr(self.owner, self.attribute) + return current + + def is_patched(self) -> bool: + return self.current() is not self.original + + def restore(self) -> None: + setattr(self.owner, self.attribute, self.original) + + +def _patch_owner_name(owner: object) -> str: + if inspect.isclass(owner): + return f"{owner.__module__}.{owner.__qualname__}" + if inspect.ismodule(owner): + return owner.__name__ + return repr(owner) + + +def _vcr_patch_point(patcher: mock._patch[object]) -> VcrPatchPoint: + owner: Final[object] = patcher.getter() + return VcrPatchPoint(owner=owner, attribute=patcher.attribute, original=patcher.new) + + +_VCR_PATCH_POINTS: Final = ( + *(_vcr_patch_point(patcher) for patcher in _vcr_patch.reset_patchers()), + VcrPatchPoint(aiohttp.ClientSession, "_request", _vcr_patch._AiohttpClientSessionRequest), +) + + +@dataclass(frozen=True, slots=True) +class VcrPatchLeak: + patch_points: tuple[str, ...] + cassette_paths: tuple[str, ...] + + +def _cassette_paths_wrapped_into(fn: object) -> tuple[str, ...]: + if not inspect.isfunction(fn): + return () + cassette: Final = inspect.getclosurevars(fn).nonlocals.get("cassette") + own: Final = (str(cassette._path),) if isinstance(cassette, vcr.cassette.Cassette) else () + return own + _cassette_paths_wrapped_into(getattr(fn, "__wrapped__", None)) + + +def detect_vcr_patch_leak() -> VcrPatchLeak | None: + leaked: Final = tuple(point for point in _VCR_PATCH_POINTS if point.is_patched()) + if not leaked: + return None + return VcrPatchLeak( + patch_points=tuple(point.name for point in leaked), + cassette_paths=tuple( + dict.fromkeys(path for point in leaked for path in _cassette_paths_wrapped_into(point.current())) + ), + ) + + +def restore_vcr_patch_points() -> None: + for point in _VCR_PATCH_POINTS: + point.restore() + + +def guard_vcr_patch_points(item: pytest.Item, teardown_failed: bool) -> None: + leak: Final = detect_vcr_patch_leak() + if leak is None: + return + restore_vcr_patch_points() + if teardown_failed: + return + pytest.fail( + f"{item.nodeid} finished with a vcrpy cassette still patched into " + f"{', '.join(leak.patch_points)} (cassettes: {', '.join(leak.cassette_paths) or 'unknown'}); " + "the originals were restored so later tests are unaffected", + pytrace=False, + ) + + +@contextmanager +def rewound_new_episodes_cassette(cassette_dir: Path) -> Iterator[vcr.cassette.Cassette]: + cassette_path: Final = cassette_dir / "rewound_owner.yaml" + cassette_path.write_text("interactions: []\nversion: 1\n") + recorder: Final = vcr.VCR(cassette_library_dir=str(cassette_dir)) + with recorder.use_cassette(cassette_path.name, record_mode="new_episodes") as cassette: + yield cassette diff --git a/tests/capturing_transport.py b/tests/capturing_transport.py new file mode 100644 index 00000000000..496c286685c --- /dev/null +++ b/tests/capturing_transport.py @@ -0,0 +1,25 @@ +from __future__ import annotations + +from collections.abc import Mapping +from typing import Final + +import httpx +from pydantic import BaseModel, TypeAdapter + +_JSON_OBJECT: Final = TypeAdapter(Mapping[str, object]) + + +class CapturingTransport(httpx.AsyncBaseTransport, httpx.BaseTransport): + def __init__(self, response: BaseModel) -> None: + self._response: Final = response + self.request_bodies: tuple[Mapping[str, object], ...] = () + + def handle_request(self, request: httpx.Request) -> httpx.Response: + return self._respond(request.read()) + + async def handle_async_request(self, request: httpx.Request) -> httpx.Response: + return self._respond(await request.aread()) + + def _respond(self, body: bytes) -> httpx.Response: + self.request_bodies = (*self.request_bodies, _JSON_OBJECT.validate_json(body)) + return httpx.Response(200, json=self._response.model_dump(mode="json")) diff --git a/tests/llm_translation/conftest.py b/tests/llm_translation/conftest.py index 567040c1d19..a88dcf4ae3e 100644 --- a/tests/llm_translation/conftest.py +++ b/tests/llm_translation/conftest.py @@ -7,6 +7,8 @@ import asyncio import importlib +from collections.abc import Generator +from typing import Final import pytest @@ -20,6 +22,7 @@ from tests._vcr_conftest_common import ( # noqa: E402,F401 emit_cassette_cache_session_banner, emit_vcr_classification_summary, emit_vcr_diagnostic_log, + guard_vcr_patch_points, install_live_call_probe, record_vcr_outcome, register_persister_if_enabled, @@ -37,17 +40,12 @@ def fake_openai_endpoint(): # Per-item respx detection (``apply_vcr_auto_marker_to_items``) handles # the vast majority of respx-vs-vcrpy conflicts automatically. The entries -# below are the persister's and the WebSocket VCR's own unit-test files, which -# exercise ``save_cassette`` / ``load_cassette`` against fakeredis and must not -# themselves run under a live cassette context. +# below are the persister's, the WebSocket VCR's, and the cassette patch-leak +# guard's own unit-test files, which exercise ``save_cassette`` / +# ``load_cassette`` against fakeredis or enter cassettes themselves and must +# not run under a live cassette context. _VCR_AUTO_MARKER_SKIP_FILES = frozenset( - {"test_vcr_redis_persister.py", "test_ws_vcr.py"} -) - -_VCR_INCOMPATIBLE_NODEID_SUFFIXES: tuple[str, ...] = ( - "test_nvidia_nim.py::test_embedding_nvidia_nim", - "test_litellm_proxy_provider.py::test_litellm_gateway_from_sdk_embedding[False]", - "test_litellm_proxy_provider.py::test_litellm_gateway_from_sdk_embedding[True]", + {"test_vcr_redis_persister.py", "test_ws_vcr.py", "test_vcr_leak_guard.py"} ) @@ -77,6 +75,17 @@ def _vcr_outcome_gate(request, vcr): record_vcr_outcome(request, vcr) +@pytest.hookimpl(wrapper=True, trylast=True) +def pytest_runtest_teardown(item: pytest.Item) -> Generator[None, object, object]: + try: + result: Final = yield + except BaseException: + guard_vcr_patch_points(item, teardown_failed=True) + raise + guard_vcr_patch_points(item, teardown_failed=False) + return result + + def pytest_configure(config): _verbose_state.remember_pluginmanager(config) reset_vcr_diag_dir() @@ -172,7 +181,6 @@ def pytest_collection_modifyitems(config, items): apply_vcr_auto_marker_to_items( items, skip_files=_VCR_AUTO_MARKER_SKIP_FILES, - skip_nodeid_suffixes=_VCR_INCOMPATIBLE_NODEID_SUFFIXES, ) custom_logger_tests = [ diff --git a/tests/llm_translation/test_litellm_proxy_provider.py b/tests/llm_translation/test_litellm_proxy_provider.py index 8630259877d..a10fc55ecc5 100644 --- a/tests/llm_translation/test_litellm_proxy_provider.py +++ b/tests/llm_translation/test_litellm_proxy_provider.py @@ -2,6 +2,8 @@ import json import re from datetime import datetime from io import BytesIO +from pathlib import Path +from typing import Final from unittest.mock import AsyncMock @@ -12,7 +14,12 @@ import pytest from unittest.mock import MagicMock, patch from litellm.llms.custom_httpx.http_handler import HTTPHandler, AsyncHTTPHandler import pytest_asyncio -from openai import AsyncOpenAI +from openai import AsyncOpenAI, OpenAI +from openai.types import CreateEmbeddingResponse, Embedding +from openai.types.create_embedding_response import Usage + +from tests.capturing_transport import CapturingTransport +from tests._vcr_conftest_common import rewound_new_episodes_cassette @pytest.mark.asyncio @@ -87,62 +94,61 @@ async def test_litellm_gateway_from_sdk_structured_output(): assert "json_schema" in json_schema -@pytest.mark.parametrize("is_async", [False, True]) +_GATEWAY_EMBEDDING_RESPONSE: Final = CreateEmbeddingResponse( + object="list", + data=(Embedding(object="embedding", index=0, embedding=(0.1, 0.2, 0.3)),), + model="my-vllm-model", + usage=Usage(prompt_tokens=2, total_tokens=2), +) + + +async def _gateway_embedding_via_injected_client( + is_async: bool, +) -> tuple[CapturingTransport, litellm.EmbeddingResponse]: + transport: Final = CapturingTransport(_GATEWAY_EMBEDDING_RESPONSE) + response: Final = ( + await litellm.aembedding( + model="litellm_proxy/my-vllm-model", + input="Hello world", + client=AsyncOpenAI(api_key="fake-key", http_client=httpx.AsyncClient(transport=transport)), + api_base="my-custom-api-base", + ) + if is_async + else litellm.embedding( + model="litellm_proxy/my-vllm-model", + input="Hello world", + client=OpenAI(api_key="fake-key", http_client=httpx.Client(transport=transport)), + api_base="my-custom-api-base", + ) + ) + return transport, response + + +@pytest.mark.parametrize("is_async", (False, True)) @pytest.mark.asyncio -async def test_litellm_gateway_from_sdk_embedding(is_async): +async def test_litellm_gateway_from_sdk_embedding(is_async: bool): litellm.set_verbose = True litellm._turn_on_debug() - captured_bodies = [] - - def handler(request: httpx.Request) -> httpx.Response: - captured_bodies.append(json.loads(request.content)) - return httpx.Response( - 200, - json={ - "object": "list", - "data": [{"object": "embedding", "index": 0, "embedding": [0.1, 0.2, 0.3]}], - "model": "my-vllm-model", - "usage": {"prompt_tokens": 2, "total_tokens": 2}, - }, - ) - - if is_async: - from openai import AsyncOpenAI - - openai_client = AsyncOpenAI( - api_key="fake-key", - http_client=httpx.AsyncClient(transport=httpx.MockTransport(handler)), - ) - response = await litellm.aembedding( - model="litellm_proxy/my-vllm-model", - input="Hello world", - client=openai_client, - api_base="my-custom-api-base", - ) - else: - from openai import OpenAI - - openai_client = OpenAI( - api_key="fake-key", - http_client=httpx.Client(transport=httpx.MockTransport(handler)), - ) - response = litellm.embedding( - model="litellm_proxy/my-vllm-model", - input="Hello world", - client=openai_client, - api_base="my-custom-api-base", - ) - - request_body = captured_bodies[0] - print("Request body - {}".format(request_body)) + transport, response = await _gateway_embedding_via_injected_client(is_async) + request_body: Final = transport.request_bodies[0] assert "Hello world" == request_body["input"] assert "my-vllm-model" == request_body["model"] assert "encoding_format" not in request_body assert response.data[0]["embedding"] == [0.1, 0.2, 0.3] +@pytest.mark.asyncio +async def test_litellm_gateway_from_sdk_embedding_under_foreign_cassette(tmp_path: Path): + with rewound_new_episodes_cassette(tmp_path): + sync_transport, _ = await _gateway_embedding_via_injected_client(is_async=False) + async_transport, _ = await _gateway_embedding_via_injected_client(is_async=True) + + assert tuple(body["input"] for body in sync_transport.request_bodies) == ("Hello world",) + assert tuple(body["input"] for body in async_transport.request_bodies) == ("Hello world",) + + @pytest.mark.parametrize("is_async", [False, True]) @pytest.mark.asyncio async def test_litellm_gateway_from_sdk_image_generation(is_async): diff --git a/tests/llm_translation/test_nvidia_nim.py b/tests/llm_translation/test_nvidia_nim.py index d5942e674d0..0f16c01fd2f 100644 --- a/tests/llm_translation/test_nvidia_nim.py +++ b/tests/llm_translation/test_nvidia_nim.py @@ -1,17 +1,21 @@ import json from datetime import datetime +from typing import Final from unittest.mock import AsyncMock import httpx import pytest +from openai.types import CreateEmbeddingResponse, Embedding +from openai.types.create_embedding_response import Usage as EmbeddingUsage from unittest.mock import patch, MagicMock import litellm from litellm import Choices, Message, ModelResponse, EmbeddingResponse, Usage from litellm import completion from base_rerank_unit_tests import BaseLLMRerankTest +from tests.capturing_transport import CapturingTransport def test_completion_nvidia_nim(): @@ -63,33 +67,23 @@ def test_embedding_nvidia_nim(): litellm.set_verbose = True from openai import OpenAI - captured_bodies = [] - - def handler(request: httpx.Request) -> httpx.Response: - captured_bodies.append(json.loads(request.content)) - return httpx.Response( - 200, - json={ - "object": "list", - "data": [{"object": "embedding", "index": 0, "embedding": [0.1, 0.2, 0.3]}], - "model": "nvidia/nv-embedqa-e5-v5", - "usage": {"prompt_tokens": 6, "total_tokens": 6}, - }, + transport: Final = CapturingTransport( + CreateEmbeddingResponse( + object="list", + data=(Embedding(object="embedding", index=0, embedding=(0.1, 0.2, 0.3)),), + model="nvidia/nv-embedqa-e5-v5", + usage=EmbeddingUsage(prompt_tokens=6, total_tokens=6), ) - - client = OpenAI( - api_key="fake-api-key", - http_client=httpx.Client(transport=httpx.MockTransport(handler)), ) - response = litellm.embedding( + client: Final = OpenAI(api_key="fake-api-key", http_client=httpx.Client(transport=transport)) + response: Final = litellm.embedding( model="nvidia_nim/nvidia/nv-embedqa-e5-v5", input="What is the meaning of life?", input_type="passage", dimensions=1024, client=client, ) - request_body = captured_bodies[0] - print("request_body: ", request_body) + request_body: Final = transport.request_bodies[0] assert request_body["input"] == "What is the meaning of life?" assert request_body["model"] == "nvidia/nv-embedqa-e5-v5" assert request_body["input_type"] == "passage" diff --git a/tests/llm_translation/test_vcr_leak_guard.py b/tests/llm_translation/test_vcr_leak_guard.py new file mode 100644 index 00000000000..5372342790b --- /dev/null +++ b/tests/llm_translation/test_vcr_leak_guard.py @@ -0,0 +1,72 @@ +from __future__ import annotations + +import re +from pathlib import Path +from typing import Final + +import httpx +import httpx2 +import pytest + +from tests._vcr_conftest_common import ( + detect_vcr_patch_leak, + guard_vcr_patch_points, + restore_vcr_patch_points, + rewound_new_episodes_cassette, +) + +_ORIGINAL_MOCK_HANDLE_ASYNC_REQUEST: Final = httpx.MockTransport.handle_async_request +_ORIGINAL_HTTPX2_MOCK_HANDLE_ASYNC_REQUEST: Final = httpx2.MockTransport.handle_async_request + + +@pytest.fixture +def leaked_cassette_dir(tmp_path: Path): + context: Final = rewound_new_episodes_cassette(tmp_path) + context.__enter__() + yield tmp_path + context.__exit__(None, None, None) + + +def test_no_leak_when_no_cassette_is_active(): + assert detect_vcr_patch_leak() is None + + +def test_leaked_cassette_is_detected_named_and_restorable(leaked_cassette_dir: Path): + leak: Final = detect_vcr_patch_leak() + + assert leak is not None + assert {"httpx.MockTransport.handle_async_request", "aiohttp.client.ClientSession._request"} <= set( + leak.patch_points + ) + assert leak.cassette_paths == (str(leaked_cassette_dir / "rewound_owner.yaml"),) + + restore_vcr_patch_points() + + assert detect_vcr_patch_leak() is None + assert httpx.MockTransport.handle_async_request is _ORIGINAL_MOCK_HANDLE_ASYNC_REQUEST + + +def test_leak_is_detected_on_every_transport_family_vcrpy_patches(leaked_cassette_dir: Path): + leak: Final = detect_vcr_patch_leak() + + assert leak is not None + assert "httpx2.MockTransport.handle_async_request" in leak.patch_points + assert httpx2.MockTransport.handle_async_request is not _ORIGINAL_HTTPX2_MOCK_HANDLE_ASYNC_REQUEST + + restore_vcr_patch_points() + + assert httpx2.MockTransport.handle_async_request is _ORIGINAL_HTTPX2_MOCK_HANDLE_ASYNC_REQUEST + + +def test_guard_fails_the_leaking_test_and_restores_the_originals(request, leaked_cassette_dir: Path): + with pytest.raises(pytest.fail.Exception, match=re.escape(request.node.nodeid)) as failure: + guard_vcr_patch_points(request.node, teardown_failed=False) + + assert str(leaked_cassette_dir / "rewound_owner.yaml") in str(failure.value) + assert detect_vcr_patch_leak() is None + + +def test_guard_restores_silently_when_the_teardown_already_failed(request, leaked_cassette_dir: Path): + guard_vcr_patch_points(request.node, teardown_failed=True) + + assert detect_vcr_patch_leak() is None diff --git a/tests/local_testing/conftest.py b/tests/local_testing/conftest.py index 228457f4d55..d03f074f557 100644 --- a/tests/local_testing/conftest.py +++ b/tests/local_testing/conftest.py @@ -93,7 +93,6 @@ _VCR_INCOMPATIBLE_FILES = frozenset( # carry no real provider cost. _VCR_INCOMPATIBLE_NODEID_SUFFIXES: tuple[str, ...] = ( "test_router.py::test_router_text_completion_client", - "test_embedding.py::test_encoding_format_omitted_by_default_for_openai_sdk", ) diff --git a/tests/local_testing/test_embedding.py b/tests/local_testing/test_embedding.py index c119334da6f..acbc4f20405 100644 --- a/tests/local_testing/test_embedding.py +++ b/tests/local_testing/test_embedding.py @@ -15,6 +15,9 @@ from unittest.mock import AsyncMock, MagicMock, patch import litellm from litellm import completion, completion_cost, embedding +from openai.types import CreateEmbeddingResponse +from openai.types.create_embedding_response import Usage as EmbeddingUsage +from tests.capturing_transport import CapturingTransport from tests.fake_openai_endpoint import FAKE_OPENAI_API_BASE litellm.set_verbose = False @@ -1268,23 +1271,15 @@ def test_encoding_format_omitted_by_default_for_openai_sdk(monkeypatch): Optional global override: `LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT`. """ monkeypatch.delenv("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT", raising=False) - captured_bodies = [] - - def handler(request: httpx.Request) -> httpx.Response: - captured_bodies.append(json.loads(request.content)) - return httpx.Response( - 200, - json={ - "object": "list", - "data": [{"object": "embedding", "index": 0, "embedding": [0.1, 0.2, 0.3]}], - "model": "text-embedding-ada-002", - "usage": {"prompt_tokens": 1, "total_tokens": 1}, - }, + transport = CapturingTransport( + CreateEmbeddingResponse( + object="list", + data=(Embedding(object="embedding", index=0, embedding=(0.1, 0.2, 0.3)),), + model="text-embedding-ada-002", + usage=EmbeddingUsage(prompt_tokens=1, total_tokens=1), ) - - client = openai.OpenAI( - api_key="sk-test", http_client=httpx.Client(transport=httpx.MockTransport(handler)) ) + client = openai.OpenAI(api_key="sk-test", http_client=httpx.Client(transport=transport)) response = embedding( model="text-embedding-ada-002", @@ -1294,7 +1289,7 @@ def test_encoding_format_omitted_by_default_for_openai_sdk(monkeypatch): ) assert response.data[0]["embedding"] == [0.1, 0.2, 0.3] - assert "encoding_format" not in captured_bodies[0], ( + assert "encoding_format" not in transport.request_bodies[0], ( "encoding_format should be omitted from the upstream request when not provided by user" ) From 676486886178dc83de9c3e489ca047af882a652d Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 14:24:32 -0700 Subject: [PATCH 037/101] fix(otel): keep text completion choice fields beside the synthesized message (#42537) Co-authored-by: yucheng Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- litellm/integrations/otel/model/payloads.py | 8 +- tests/integration/contracts.json | 3 + .../test_otel_text_completion_choices.py | 110 ++++++++++++++++++ .../otel/test_otel_v2_sources_of_truth.py | 23 +++- 4 files changed, 142 insertions(+), 2 deletions(-) create mode 100644 tests/integration/observability/test_otel_text_completion_choices.py diff --git a/litellm/integrations/otel/model/payloads.py b/litellm/integrations/otel/model/payloads.py index 240107251c5..2f337c59148 100644 --- a/litellm/integrations/otel/model/payloads.py +++ b/litellm/integrations/otel/model/payloads.py @@ -776,9 +776,15 @@ def _joined_choice(parts: tuple[str, ...]) -> tuple[_Choice, ...]: return (_text_choice("\n\n".join(parts)),) if parts else () +def _text_completion_choice(choice: Mapping[str, object], text: str) -> Mapping[str, object]: + synthesized: Final = _text_choice(text, as_str(choice.get("finish_reason"))) + merged: Final = (*choice.items(), *synthesized.items()) + return {k: v for k, v in merged if k != "text"} # mutable-ok: mappers json.dumps and isinstance(dict) it + + def _completion_choices(response: Mapping[str, object]) -> tuple[Mapping[str, object], ...]: return tuple( - _text_choice(text, as_str(choice.get("finish_reason"))) + _text_completion_choice(choice, text) if "message" not in choice and isinstance(text := choice.get("text"), str) else choice for choice in _dicts(response.get("choices")) diff --git a/tests/integration/contracts.json b/tests/integration/contracts.json index d12e3ae4620..cdf534bb5a1 100644 --- a/tests/integration/contracts.json +++ b/tests/integration/contracts.json @@ -248,6 +248,9 @@ "other.observability.callbacks.credentials_stay_out_of_event_bodies", "other.observability.callbacks.concurrent_results_join_complete_events_and_rows" ], + "tests/integration/observability/test_otel_text_completion_choices.py::test_otel_weave_output_keeps_text_completion_provider_fields_beside_the_synthesized_message": [ + "other.observability.otel.text_completion_choices_keep_provider_fields" + ], "tests/integration/observability/test_guardrail_effects.py::test_guardrail_rewrites_system_and_user_in_actual_anthropic_request": [ "other.observability.guardrails.rewrite_reaches_correct_anthropic_positions" ], diff --git a/tests/integration/observability/test_otel_text_completion_choices.py b/tests/integration/observability/test_otel_text_completion_choices.py new file mode 100644 index 00000000000..70c104a61aa --- /dev/null +++ b/tests/integration/observability/test_otel_text_completion_choices.py @@ -0,0 +1,110 @@ +import json +import uuid +from pathlib import Path +from typing import Final + +import pytest +import yaml + +from integration._support.client import Gateway, eventually +from integration._support.process import owned_proxy +from integration._support.wire import Reply, Request, wire_server + + +def _span_attributes(body: bytes) -> tuple[dict[str, object], ...]: + return tuple( + {attribute["key"]: attribute["value"] for attribute in span.get("attributes", ())} + for resource in json.loads(body)["resourceSpans"] + for scope in resource["scopeSpans"] + for span in scope["spans"] + ) + + +@pytest.mark.covers("other.observability.otel.text_completion_choices_keep_provider_fields") +def test_otel_weave_output_keeps_text_completion_provider_fields_beside_the_synthesized_message( + gateway: Gateway, tmp_path: Path +) -> None: + marker: Final = "otel-text-" + uuid.uuid4().hex + logprobs: Final = { + "tokens": ["Hello", " there"], + "token_logprobs": [-0.1, -0.2], + "top_logprobs": None, + "text_offset": [0, 5], + } + content_filter: Final = {"hate": {"filtered": False, "severity": "safe"}} + + def upstream(request: Request) -> Reply: + assert request.target.endswith("/completions"), request.target + return Reply( + body=json.dumps( + { + "id": marker, + "object": "text_completion", + "created": 1, + "model": "gpt-3.5-turbo-instruct", + "choices": [ + { + "index": 0, + "text": "Hello there", + "finish_reason": "stop", + "logprobs": logprobs, + "content_filter_results": content_filter, + } + ], + "usage": {"prompt_tokens": 3, "completion_tokens": 2, "total_tokens": 5}, + } + ).encode() + ) + + def sink(_request: Request) -> Reply: + return Reply() + + with wire_server(upstream) as provider, wire_server(sink) as collector: + config: Final = yaml.safe_load(Path("tests/integration/proxy_config.yaml").read_text()) + config["litellm_settings"].update({"callbacks": ["otel"]}) + config["callback_settings"] = { + "otel": { + "exporter": "http/json", + "endpoint": collector.url, + "mapper_names": ["genai", "openinference", "weave"], + "capture_message_content": "span_only", + "use_simple_processor": True, + } + } + path: Final = tmp_path / "otel.yaml" + path.write_text(yaml.safe_dump(config)) + with ( + owned_proxy(gateway, tmp_path, {"LITELLM_OTEL_V2": "1"}, config=path) as candidate, + candidate.scenario() as scenario, + ): + model: Final = scenario.model(model="openai/gpt-3.5-turbo-instruct", api_base=provider.url + "/v1") + response: Final = candidate.request( + "POST", "/v1/completions", {"model": model, "prompt": marker, "cache": {"no-cache": True}} + ) + assert response.status_code == 200, response.text + assert response.json()["choices"][0]["text"] == "Hello there" + batches = [] + + def outputs() -> tuple[list[dict[str, object]], ...]: + batches.extend(collector.drain()) + return tuple( + json.loads(attributes["weave.output"]["stringValue"]) + for batch in batches + for attributes in _span_attributes(batch.body) + if "weave.output" in attributes + and attributes.get("gen_ai.response.id", {}).get("stringValue") == marker + ) + + choices: Final = eventually(outputs, lambda values: len(values) == 1, seconds=20)[0] + assert len(choices) == 1, choices + choice: Final = choices[0] + assert choice["message"]["content"] == "Hello there", choice + assert "text" not in choice, choice + assert { + key: choice.get(key) for key in ("index", "finish_reason", "logprobs", "content_filter_results") + } == { + "index": 0, + "finish_reason": "stop", + "logprobs": logprobs, + "content_filter_results": content_filter, + }, choice diff --git a/tests/test_litellm/integrations/otel/test_otel_v2_sources_of_truth.py b/tests/test_litellm/integrations/otel/test_otel_v2_sources_of_truth.py index b9ec625fdfc..95df3709ab8 100644 --- a/tests/test_litellm/integrations/otel/test_otel_v2_sources_of_truth.py +++ b/tests/test_litellm/integrations/otel/test_otel_v2_sources_of_truth.py @@ -934,11 +934,32 @@ def test_text_completion_choices_become_assistant_messages_in_choice_order() -> capture_content=True, ) - assert data.choices_out == (_assistant_choice(" first", "length"), _assistant_choice(" second", "stop")) + assert data.choices_out == ( + {"index": 0, "logprobs": None, **_assistant_choice(" first", "length")}, + {"index": 1, "logprobs": None, **_assistant_choice(" second", "stop")}, + ) assert data.finish_reasons == ("length", "stop") assert data.response_id == "cmpl-1" +def test_text_completion_choices_keep_provider_fields_beside_the_synthesized_message() -> None: + choice: Final = { + "index": 2, + "text": "Hello there", + "finish_reason": "stop", + "logprobs": {"tokens": ["Hello"], "token_logprobs": [-0.1]}, + "content_filter_results": {"hate": {"filtered": False}}, + "provider_specific": {"cached": True}, + } + data: Final = LLMCallSpanData.from_standard_logging_payload( + _route_payload("atext_completion", "gpt-3.5-turbo-instruct", {"choices": [choice]}), capture_content=True + ) + + assert data.choices_out == ( + {k: v for k, v in choice.items() if k != "text"} | _assistant_choice("Hello there", "stop"), + ) + + def test_text_completion_choices_follow_the_content_capture_gate_but_finish_reasons_do_not() -> None: data: Final = LLMCallSpanData.from_standard_logging_payload( _route_payload( From b277be0867abaa11a29815d73ed7d5a66962cf1e Mon Sep 17 00:00:00 2001 From: joshua-berri Date: Tue, 22 Sep 2026 21:26:48 +0000 Subject: [PATCH 038/101] fix(mcp): preserve discovery attribution and sanitize logging headers (#42541) Co-authored-by: Joshua Valluru <326636767+joshua-berri@users.noreply.github.com> --- .../proxy/_experimental/mcp_server/utils.py | 6 +-- litellm/proxy/litellm_pre_call_utils.py | 9 +++- litellm/responses/main.py | 19 ++++----- .../responses/mcp/chat_completions_handler.py | 1 + .../mcp/litellm_proxy_mcp_handler.py | 4 ++ .../_experimental/mcp_server/test_utils.py | 6 +-- .../proxy/test_litellm_pre_call_utils.py | 42 +++++++++++++++++++ .../mcp/test_chat_completions_handler.py | 1 + .../mcp/test_litellm_proxy_mcp_handler.py | 40 +++++++++++++++++- 9 files changed, 109 insertions(+), 19 deletions(-) diff --git a/litellm/proxy/_experimental/mcp_server/utils.py b/litellm/proxy/_experimental/mcp_server/utils.py index 6bd080f5216..7411dc5c4f0 100644 --- a/litellm/proxy/_experimental/mcp_server/utils.py +++ b/litellm/proxy/_experimental/mcp_server/utils.py @@ -986,7 +986,7 @@ def _forwarded_upstream_header_names() -> frozenset[str]: ) -def _upstream_credential_headers(header_names: Iterable[str]) -> frozenset[str]: +def upstream_credential_headers(header_names: Iterable[str]) -> frozenset[str]: """Lowercased names of the headers in ``header_names`` that carry an upstream MCP credential rather than request context: the configured client side auth header, any header name a configured server forwards upstream via ``extra_headers``, and the @@ -1038,7 +1038,7 @@ def build_synthetic_mcp_request( custom_key_header: Final = _custom_litellm_key_header_name() excluded: Final = ( _SYNTHETIC_REQUEST_EXCLUDED_HEADERS - | _upstream_credential_headers(raw_headers.keys() if raw_headers else ()) + | upstream_credential_headers(raw_headers.keys() if raw_headers else ()) | (frozenset({custom_key_header.lower()}) if custom_key_header else frozenset()) ) forwarded: Final = tuple( @@ -1086,7 +1086,7 @@ def logging_safe_mcp_headers(raw_headers: Mapping[str, str] | None) -> Mapping[s ) excluded: Final = ( - _upstream_credential_headers(raw_headers.keys() if raw_headers else ()) + upstream_credential_headers(raw_headers.keys() if raw_headers else ()) | UNTRUSTED_REQUEST_HEADER_CONTROL_FIELDS | frozenset({"host"}) ) diff --git a/litellm/proxy/litellm_pre_call_utils.py b/litellm/proxy/litellm_pre_call_utils.py index 4d5b91be034..90bba82aa84 100644 --- a/litellm/proxy/litellm_pre_call_utils.py +++ b/litellm/proxy/litellm_pre_call_utils.py @@ -2029,7 +2029,14 @@ async def add_litellm_data_to_request( _headers, allow_client_message_redaction_opt_out=_allow_client_message_redaction_opt_out, ) - _logging_safe_headers: Final = redact_credential_headers(_headers) + from litellm.proxy._experimental.mcp_server.utils import upstream_credential_headers + + _mcp_credential_headers: Final = upstream_credential_headers(_headers) + _logging_safe_headers: Final = redact_credential_headers( + MappingProxyType( + {name: value for name, value in _headers.items() if name.lower() not in _mcp_credential_headers} + ) + ) verbose_proxy_logger.debug("Request Headers: %s", _logging_safe_headers) verbose_proxy_logger.debug("Raw Headers: %s", _raw_headers) diff --git a/litellm/responses/main.py b/litellm/responses/main.py index 5c4c9ea3987..e771cdf5ae4 100644 --- a/litellm/responses/main.py +++ b/litellm/responses/main.py @@ -209,16 +209,12 @@ async def aresponses_api_with_mcp( user_api_key_auth = kwargs.get("user_api_key_auth") or kwargs.get("litellm_metadata", {}).get("user_api_key_auth") # Extract MCP auth headers from request (for dynamic auth when fetching tools) - mcp_auth_header: str | None = None - mcp_server_auth_headers: dict[str, dict[str, str]] | None = None - secret_fields = kwargs.get("secret_fields") - if secret_fields and isinstance(secret_fields, dict): - ( - mcp_auth_header, - mcp_server_auth_headers, - _, - _, - ) = ResponsesAPIRequestUtils.extract_mcp_headers_from_request(secret_fields=secret_fields, tools=tools) + secret_fields: Final = kwargs.get("secret_fields") + mcp_auth_header, mcp_server_auth_headers, _, discovery_raw_headers = ( + ResponsesAPIRequestUtils.extract_mcp_headers_from_request(secret_fields=secret_fields, tools=tools) + if isinstance(secret_fields, dict) and secret_fields + else (None, None, None, None) + ) # Get original MCP tools (for events) and OpenAI tools (for LLM) by reusing existing methods ( @@ -231,6 +227,7 @@ async def aresponses_api_with_mcp( mcp_auth_header=mcp_auth_header, mcp_server_auth_headers=mcp_server_auth_headers, request_tags=LiteLLM_Proxy_MCP_Handler._get_parent_request_tags(kwargs), + raw_headers=discovery_raw_headers, ) openai_tools: Final = LiteLLM_Proxy_MCP_Handler._transform_mcp_tools_to_openai(original_mcp_tools) @@ -330,7 +327,6 @@ async def aresponses_api_with_mcp( user_api_key_auth = kwargs.get("litellm_metadata", {}).get("user_api_key_auth") # Extract MCP auth headers from the request to pass to MCP server - secret_fields = kwargs.get("secret_fields") ( mcp_auth_header, mcp_server_auth_headers, @@ -416,6 +412,7 @@ async def aresponses_api_with_mcp( mcp_auth_header=mcp_auth_header, mcp_server_auth_headers=mcp_server_auth_headers, request_tags=LiteLLM_Proxy_MCP_Handler._get_parent_request_tags(kwargs), + raw_headers=discovery_raw_headers, ) final_response = LiteLLM_Proxy_MCP_Handler._add_mcp_output_elements_to_response( response=final_response, diff --git a/litellm/responses/mcp/chat_completions_handler.py b/litellm/responses/mcp/chat_completions_handler.py index df1e3e62441..b17e0befba6 100644 --- a/litellm/responses/mcp/chat_completions_handler.py +++ b/litellm/responses/mcp/chat_completions_handler.py @@ -138,6 +138,7 @@ async def acompletion_with_mcp( mcp_auth_header=mcp_auth_header, mcp_server_auth_headers=mcp_server_auth_headers, request_tags=request_tags, + raw_headers=raw_headers, ) openai_tools: Final = LiteLLM_Proxy_MCP_Handler._transform_mcp_tools_to_openai( diff --git a/litellm/responses/mcp/litellm_proxy_mcp_handler.py b/litellm/responses/mcp/litellm_proxy_mcp_handler.py index 319f10a9b22..71f61079154 100644 --- a/litellm/responses/mcp/litellm_proxy_mcp_handler.py +++ b/litellm/responses/mcp/litellm_proxy_mcp_handler.py @@ -236,6 +236,7 @@ class LiteLLM_Proxy_MCP_Handler: mcp_auth_header: str | None = None, mcp_server_auth_headers: dict[str, dict[str, str]] | None = None, request_tags: list[str] | None = None, + raw_headers: dict[str, str] | None = None, ) -> tuple[list[MCPTool], list[str]]: """ Get available tools from the MCP server manager. @@ -326,6 +327,7 @@ class LiteLLM_Proxy_MCP_Handler: list_tools_log_source="responses", litellm_trace_id=litellm_trace_id, request_tags=request_tags, + raw_headers=raw_headers, ) tools: Final = listing.tools @@ -452,6 +454,7 @@ class LiteLLM_Proxy_MCP_Handler: mcp_auth_header: str | None = None, mcp_server_auth_headers: dict[str, dict[str, str]] | None = None, request_tags: list[str] | None = None, + raw_headers: dict[str, str] | None = None, ) -> tuple[list[MCPTool], dict[str, str]]: """ Process MCP tools through filtering and deduplication pipeline without OpenAI transformation. @@ -482,6 +485,7 @@ class LiteLLM_Proxy_MCP_Handler: mcp_auth_header=mcp_auth_header, mcp_server_auth_headers=mcp_server_auth_headers, request_tags=request_tags, + raw_headers=raw_headers, ) # Step 2: Filter tools based on allowed_tools parameter diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_utils.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_utils.py index 842859e5a1e..8d10219796b 100644 --- a/tests/test_litellm/proxy/_experimental/mcp_server/test_utils.py +++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_utils.py @@ -4,7 +4,7 @@ import pytest from fastapi import HTTPException from litellm.proxy._experimental.mcp_server.utils import ( - _upstream_credential_headers, + upstream_credential_headers, build_synthetic_mcp_request, logging_safe_mcp_headers, validate_and_normalize_mcp_server_payload, @@ -189,8 +189,8 @@ class TestLoggingSafeMcpHeaders: """clean_headers already strips authorization, and claiming it here would change which header authenticated_with_header resolves to on a config that lists it by design.""" with _configured_servers(_server_forwarding("Authorization", "X-GitHub-Token")): - assert "authorization" not in _upstream_credential_headers(["authorization", "x-github-token"]) - assert "x-github-token" in _upstream_credential_headers(["authorization", "x-github-token"]) + assert "authorization" not in upstream_credential_headers(["authorization", "x-github-token"]) + assert "x-github-token" in upstream_credential_headers(["authorization", "x-github-token"]) def test_keeps_headers_when_no_server_forwards_them(self): with _configured_servers(_server_forwarding("x-github-token")): diff --git a/tests/test_litellm/proxy/test_litellm_pre_call_utils.py b/tests/test_litellm/proxy/test_litellm_pre_call_utils.py index b7b7b5d1942..8fb53d4b0a0 100644 --- a/tests/test_litellm/proxy/test_litellm_pre_call_utils.py +++ b/tests/test_litellm/proxy/test_litellm_pre_call_utils.py @@ -8238,3 +8238,45 @@ def test_default_team_settings_bool_turn_off_message_logging_redacts(): ) is True ) + + +@pytest.mark.asyncio +@pytest.mark.parametrize("path", ["/mcp-rest/tools/call", "/v1/responses", "/v1/chat/completions"]) +@pytest.mark.parametrize("custom_auth", ["x-mcp-auth", "x-private-mcp-token"]) +async def test_mcp_credentials_only_removed_from_logging_copies(path: str, custom_auth: str): + from litellm.types.mcp_server.mcp_server_manager import MCPServer + + metadata_name: Final = "litellm_metadata" if path == "/v1/responses" else "metadata" + secrets: Final = { + "X-MCP-Deepwiki-Authorization": "upstream-sentinel", + custom_auth: "client-auth-sentinel", + "x-service-token": "configured-secret-sentinel", + } + attribution: Final = {"x-app-id": "app-a", "x-nuid": "user-a", "x-user-id": "identity-a"} + request: Final = _make_request_mock(path, {"Content-Type": "application/json", **secrets, **attribution}) + request.headers = Headers(request.headers) + settings: Final = {"mcp_client_side_auth_header_name": custom_auth, "user_header_name": "x-user-id"} + server: Final = MCPServer( + server_id="header-test", name="header-test", transport="http", url="https://example.com/mcp", + extra_headers=["x-service-token", "x-user-id"], + ) + with ( + patch("litellm.proxy.proxy_server.general_settings", settings), + patch.dict( + "litellm.proxy._experimental.mcp_server.mcp_server_manager.global_mcp_server_manager.config_mcp_servers", + {"header-test": server}, clear=True, + ), + ): + updated: Final = await add_litellm_data_to_request( + data={"model": "test-model", "messages": [{"role": "user", "content": "hello"}]}, + request=request, user_api_key_dict=UserAPIKeyAuth(api_key="hashed-key"), + proxy_config=MagicMock(), general_settings=settings, version="test", + ) + for header_dict in _all_header_dicts(updated, metadata_name): + assert not any(value in json.dumps(header_dict) for value in secrets.values()) + assert updated[metadata_name]["headers"] == updated["proxy_server_request"]["headers"] + for name, value in attribution.items(): + assert updated[metadata_name]["headers"][name] == value + for name, value in secrets.items(): + assert updated["secret_fields"]["raw_headers"][name.lower()] == value + assert request.headers[name] == value diff --git a/tests/test_litellm/responses/mcp/test_chat_completions_handler.py b/tests/test_litellm/responses/mcp/test_chat_completions_handler.py index 6e049d7634c..54e98cc2b6c 100644 --- a/tests/test_litellm/responses/mcp/test_chat_completions_handler.py +++ b/tests/test_litellm/responses/mcp/test_chat_completions_handler.py @@ -159,6 +159,7 @@ async def test_acompletion_with_mcp_passes_mcp_server_auth_headers_to_process_to secret_fields=secret_fields, ) + assert captured_process_kwargs["raw_headers"] == secret_fields["raw_headers"] assert "mcp_server_auth_headers" in captured_process_kwargs mcp_server_auth_headers = captured_process_kwargs["mcp_server_auth_headers"] assert mcp_server_auth_headers is not None diff --git a/tests/test_litellm/responses/mcp/test_litellm_proxy_mcp_handler.py b/tests/test_litellm/responses/mcp/test_litellm_proxy_mcp_handler.py index 56e40206ebe..57cebf489a2 100644 --- a/tests/test_litellm/responses/mcp/test_litellm_proxy_mcp_handler.py +++ b/tests/test_litellm/responses/mcp/test_litellm_proxy_mcp_handler.py @@ -3,7 +3,7 @@ import subprocess import sys import textwrap import types -from typing import Any, cast +from typing import Any, Final, cast from unittest.mock import AsyncMock, MagicMock import pytest @@ -1226,6 +1226,7 @@ async def test_mcp_follow_up_call_is_stateless_when_store_is_false( ) async def fake_process(**kwargs: Any) -> tuple[list[Any], dict[str, str]]: + assert kwargs["raw_headers"] == {"x-app-id": "follow-up-caller"} return ([], {"foo": "litellm_proxy"}) async def fake_execute(**kwargs: Any) -> list[dict[str, Any]]: @@ -1245,6 +1246,7 @@ async def test_mcp_follow_up_call_is_stateless_when_store_is_false( model="gpt-5", tools=[{"type": "mcp", "server_url": "litellm_proxy", "require_approval": "never"}], litellm_metadata={"guardrails": ["block-all"]}, + secret_fields={"raw_headers": {"x-app-id": "follow-up-caller"}}, store=store, previous_response_id=caller_previous_response_id, ) @@ -1257,3 +1259,39 @@ async def test_mcp_follow_up_call_is_stateless_when_store_is_false( item for item in follow_up_call["input"] if isinstance(item, dict) and item.get("type") == "reasoning" ] assert bool(reasoning_items) is (store is False) + + +@pytest.mark.asyncio +async def test_responses_discovery_logs_sanitized_caller_headers(monkeypatch: pytest.MonkeyPatch): + from litellm.proxy._experimental.mcp_server import operations + from litellm.proxy._experimental.mcp_server import mcp_server_manager + + headers: Final = { + "x-app-id": "app-a", "x-nuid": "user-a", "x-user-id": "identity-a", + "x-mcp-deepwiki-authorization": "upstream-sentinel", "authorization": "proxy-sentinel", + } + manager: Final = types.SimpleNamespace( + get_registry=MagicMock(return_value={}), + get_allowed_mcp_servers=AsyncMock(return_value=[]), + get_mcp_servers_from_ids=MagicMock(return_value=[]), + ) + logger: Final = MagicMock(model_call_details={}) + logger.async_success_handler = AsyncMock() + setup: Final = MagicMock(return_value=(logger, None)) + monkeypatch.setattr(mcp_server_manager, "global_mcp_server_manager", manager) + monkeypatch.setattr(operations, "_get_allowed_mcp_servers", AsyncMock(return_value=[])) + monkeypatch.setattr(operations, "function_setup", setup) + response: Final = ResponsesAPIResponse( + id="resp_test", created_at=1234567891, model="test-model", object="response", + status="completed", output=[], parallel_tool_calls=False, tool_choice="auto", tools=[], + ) + monkeypatch.setattr(responses_main, "aresponses", AsyncMock(return_value=response)) + result: Final = await responses_main.aresponses_api_with_mcp( + input="hi", model="test-model", tools=[{"type": "mcp", "server_url": "litellm_proxy"}], + secret_fields={"raw_headers": headers}, + ) + assert result is response + logger.async_success_handler.assert_awaited_once() + logged: Final = setup.call_args.kwargs["metadata"]["headers"] + assert logged == {"x-app-id": "app-a", "x-nuid": "user-a", "x-user-id": "identity-a"} + assert headers["x-mcp-deepwiki-authorization"] == "upstream-sentinel" From ecce7cdd9c8eae08931b4a89b1af9ba13cf7201b Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 14:29:50 -0700 Subject: [PATCH 039/101] fix(proxy_cli): import proxy_server once on script-style boot (#42584) Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- litellm/proxy/proxy_cli.py | 41 ++++------------ tests/test_litellm/proxy/test_proxy_cli.py | 57 ++++++++++++++++------ 2 files changed, 52 insertions(+), 46 deletions(-) diff --git a/litellm/proxy/proxy_cli.py b/litellm/proxy/proxy_cli.py index 40140974198..ac69f2e3894 100644 --- a/litellm/proxy/proxy_cli.py +++ b/litellm/proxy/proxy_cli.py @@ -33,21 +33,20 @@ else: FastAPI = Any -def _deprioritize_script_dir_in_sys_path() -> None: +def _drop_script_dir_from_sys_path() -> None: """Stop ``litellm/proxy`` modules from shadowing installed packages. Running this file as a script puts its own directory at ``sys.path[0]``, so ``import a2a`` resolves to ``litellm/proxy/a2a`` instead of the ``a2a`` SDK - and A2A agent calls fail. The entry is moved to the end rather than dropped, - because the sibling-import fallbacks in this module (``from proxy_server - import ...``) still need it. No-op under the ``litellm`` console script. + and ``proxy_server`` resolves to a second copy of + ``litellm.proxy.proxy_server``. No-op under the ``litellm`` console script. """ script_dir: Final = os.path.dirname(os.path.abspath(__file__)) if sys.path and os.path.abspath(sys.path[0]) == script_dir: - sys.path.append(sys.path.pop(0)) + sys.path.pop(0) -_deprioritize_script_dir_in_sys_path() +_drop_script_dir_from_sys_path() sys.path.append(os.getcwd()) config_filename: Final = "litellm.secrets" @@ -881,7 +880,7 @@ class ProxyInitializationHelpers: default=False, help="Use prisma db push instead of prisma migrate for database schema updates", ) -@click.option("--local", is_flag=True, default=False, help="for local debugging") +@click.option("--local", is_flag=True, default=False, help="no-op, kept for backwards compatibility") @click.option( "--skip_server_startup", is_flag=True, @@ -1058,35 +1057,15 @@ def run_server( return args: Final = locals() - if local: - from proxy_server import ( + try: + from litellm.proxy.proxy_server import ( KeyManagementSettings, ProxyConfig, app, save_worker_config, ) - else: - try: - from .proxy_server import ( - KeyManagementSettings, - ProxyConfig, - app, - save_worker_config, - ) - except ModuleNotFoundError as e: - raise ModuleNotFoundError(f"Missing dependency {e}. Run `pip install 'litellm[proxy]'`") - except ImportError as e: - if "litellm[proxy]" in str(e): - # user is missing a proxy dependency, ask them to pip install litellm[proxy] - raise e - else: - # this is just a local/relative import error, user git cloned litellm - from proxy_server import ( - KeyManagementSettings, - ProxyConfig, - app, - save_worker_config, - ) + except ModuleNotFoundError as e: + raise ModuleNotFoundError(f"Missing dependency {e}. Run `pip install 'litellm[proxy]'`") from e if version is True: ProxyInitializationHelpers._echo_litellm_version() return diff --git a/tests/test_litellm/proxy/test_proxy_cli.py b/tests/test_litellm/proxy/test_proxy_cli.py index d2d71d6df05..b84efda3308 100644 --- a/tests/test_litellm/proxy/test_proxy_cli.py +++ b/tests/test_litellm/proxy/test_proxy_cli.py @@ -10,6 +10,8 @@ import pytest import builtins +import runpy +import sys import types import urllib.parse as urlparse @@ -18,6 +20,7 @@ import yaml from uvicorn.config import LOOP_FACTORIES from uvicorn.importer import import_from_string +from litellm.proxy import proxy_cli from litellm.proxy.proxy_cli import ProxyInitializationHelpers, run_server @@ -636,6 +639,36 @@ class TestProxyInitializationHelpers: ), f"exit_code={result.exit_code}, output={result.output}" mock_uvicorn_run.assert_called_once() + @patch("uvicorn.run") + @patch("atexit.register") + @patch("litellm.proxy.db.prisma_client.PrismaManager.setup_database") + @patch("litellm.proxy.db.prisma_client.should_update_prisma_schema", return_value=False) + def test_script_boot_imports_the_package_proxy_server( + self, mock_should_update, mock_setup_db, mock_atexit_register, mock_uvicorn_run + ): + package_proxy_server = MagicMock( + app=MagicMock(), + ProxyConfig=MagicMock(), + KeyManagementSettings=MagicMock(), + save_worker_config=MagicMock(), + ) + sibling_proxy_server = types.ModuleType("proxy_server") + clean_env = {k: v for k, v in os.environ.items() if k not in ("DATABASE_URL", "DIRECT_URL")} + with ( + patch.dict(os.environ, clean_env, clear=True), + patch.dict( + "sys.modules", + {"proxy_server": sibling_proxy_server, "litellm.proxy.proxy_server": package_proxy_server}, + ), + patch.object(sys, "argv", ["proxy_cli.py", "--skip_server_startup"]), + patch.object(sys, "path", list(sys.path)), + pytest.raises(SystemExit) as exit_info, + ): + runpy.run_path(proxy_cli.__file__, run_name="__main__") + + assert exit_info.value.code == 0 + package_proxy_server.save_worker_config.assert_called_once() + @patch("uvicorn.run") @patch("atexit.register") @patch("litellm.proxy.db.prisma_client.PrismaManager.setup_database") @@ -1945,13 +1978,18 @@ class TestProxyInitializationHelpers: mock_proxy_config_instance.get_config = mock_get_config mock_proxy_config.return_value = mock_proxy_config_instance - mock_proxy_server_module = MagicMock(app=mock_app) + mock_proxy_server_module = MagicMock( + app=mock_app, + ProxyConfig=mock_proxy_config, + KeyManagementSettings=mock_key_mgmt, + save_worker_config=mock_save_worker_config, + ) # Only remove DATABASE_URL and DIRECT_URL to prevent the database setup # code path from running. Do NOT use clear=True as it removes PATH, HOME, # etc., which causes imports inside run_server to break in CI (the real - # litellm.proxy.proxy_server import at line 820 of proxy_cli.py has heavy - # side effects that fail without a proper environment). + # litellm.proxy.proxy_server import has heavy side effects that fail + # without a proper environment). env_overrides = { "DATABASE_URL": "", "DIRECT_URL": "", @@ -1967,18 +2005,7 @@ class TestProxyInitializationHelpers: with ( patch.dict( "sys.modules", - { - "proxy_server": MagicMock( - app=mock_app, - ProxyConfig=mock_proxy_config, - KeyManagementSettings=mock_key_mgmt, - save_worker_config=mock_save_worker_config, - ), - # Also mock litellm.proxy.proxy_server to prevent the real - # import at line 820 of proxy_cli.py which has heavy side - # effects (FastAPI app init, logging setup, etc.) - "litellm.proxy.proxy_server": mock_proxy_server_module, - }, + {"litellm.proxy.proxy_server": mock_proxy_server_module}, ), patch( "litellm.proxy.proxy_cli.ProxyInitializationHelpers._get_default_unvicorn_init_args" From 9082f8e5d0549d93c27009b6d4f6a0a631a73435 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 21:37:12 +0000 Subject: [PATCH 040/101] feat(bedrock): add Claude Opus 5.5 pricing and capabilities (#42588) Co-authored-by: kerry Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- ...odel_prices_and_context_window_backup.json | 345 ++++++++++++++++++ model_prices_and_context_window.json | 345 ++++++++++++++++++ 2 files changed, 690 insertions(+) diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index b48bdd6322c..34cbea0e314 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -1773,6 +1773,46 @@ "prompt_cache_min_tokens": 512, "source": "https://aws.amazon.com/bedrock/pricing/" }, + "anthropic.claude-opus-5-5": { + "bedrock_converse_supports_strict_tools": false, + "supports_adaptive_thinking": true, + "supports_mid_conversation_system": true, + "cache_creation_input_token_cost": 5e-06, + "cache_creation_input_token_cost_above_1hr": 8e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 4e-06, + "litellm_provider": "bedrock_converse", + "supports_tool_search": true, + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": false, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "supports_parallel_tool_use_config": true, + "prompt_cache_min_tokens": 512, + "source": "https://aws.amazon.com/bedrock/pricing/", + "thinking_always_on": true, + "supports_forced_tool_use": false + }, "global.anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, @@ -1811,6 +1851,46 @@ "prompt_cache_min_tokens": 512, "source": "https://aws.amazon.com/bedrock/pricing/" }, + "global.anthropic.claude-opus-5-5": { + "bedrock_converse_supports_strict_tools": false, + "supports_adaptive_thinking": true, + "supports_mid_conversation_system": true, + "cache_creation_input_token_cost": 5e-06, + "cache_creation_input_token_cost_above_1hr": 8e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 4e-06, + "litellm_provider": "bedrock_converse", + "supports_tool_search": true, + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": false, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "supports_parallel_tool_use_config": true, + "prompt_cache_min_tokens": 512, + "source": "https://aws.amazon.com/bedrock/pricing/", + "thinking_always_on": true, + "supports_forced_tool_use": false + }, "us.anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, @@ -1849,6 +1929,46 @@ "prompt_cache_min_tokens": 512, "source": "https://aws.amazon.com/bedrock/pricing/" }, + "us.anthropic.claude-opus-5-5": { + "bedrock_converse_supports_strict_tools": false, + "supports_adaptive_thinking": true, + "supports_mid_conversation_system": true, + "cache_creation_input_token_cost": 5.5e-06, + "cache_creation_input_token_cost_above_1hr": 8.8e-06, + "cache_read_input_token_cost": 2.2e-07, + "input_cost_per_token": 4.4e-06, + "litellm_provider": "bedrock_converse", + "supports_tool_search": true, + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2.2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": false, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "supports_parallel_tool_use_config": true, + "prompt_cache_min_tokens": 512, + "source": "https://aws.amazon.com/bedrock/pricing/", + "thinking_always_on": true, + "supports_forced_tool_use": false + }, "eu.anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, @@ -1886,6 +2006,46 @@ "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 512 }, + "eu.anthropic.claude-opus-5-5": { + "bedrock_converse_supports_strict_tools": false, + "supports_adaptive_thinking": true, + "supports_mid_conversation_system": true, + "cache_creation_input_token_cost": 5.5e-06, + "cache_creation_input_token_cost_above_1hr": 8.8e-06, + "cache_read_input_token_cost": 2.2e-07, + "input_cost_per_token": 4.4e-06, + "litellm_provider": "bedrock_converse", + "supports_tool_search": true, + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2.2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": false, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "supports_parallel_tool_use_config": true, + "prompt_cache_min_tokens": 512, + "thinking_always_on": true, + "supports_forced_tool_use": false, + "source": "https://aws.amazon.com/bedrock/pricing/" + }, "au.anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, @@ -1923,6 +2083,46 @@ "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 512 }, + "au.anthropic.claude-opus-5-5": { + "bedrock_converse_supports_strict_tools": false, + "supports_adaptive_thinking": true, + "supports_mid_conversation_system": true, + "cache_creation_input_token_cost": 5.5e-06, + "cache_creation_input_token_cost_above_1hr": 8.8e-06, + "cache_read_input_token_cost": 2.2e-07, + "input_cost_per_token": 4.4e-06, + "litellm_provider": "bedrock_converse", + "supports_tool_search": true, + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2.2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": false, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "supports_parallel_tool_use_config": true, + "prompt_cache_min_tokens": 512, + "thinking_always_on": true, + "supports_forced_tool_use": false, + "source": "https://aws.amazon.com/bedrock/pricing/" + }, "jp.anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, @@ -1960,6 +2160,46 @@ "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 512 }, + "jp.anthropic.claude-opus-5-5": { + "bedrock_converse_supports_strict_tools": false, + "supports_adaptive_thinking": true, + "supports_mid_conversation_system": true, + "cache_creation_input_token_cost": 5.5e-06, + "cache_creation_input_token_cost_above_1hr": 8.8e-06, + "cache_read_input_token_cost": 2.2e-07, + "input_cost_per_token": 4.4e-06, + "litellm_provider": "bedrock_converse", + "supports_tool_search": true, + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2.2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": false, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "supports_parallel_tool_use_config": true, + "prompt_cache_min_tokens": 512, + "thinking_always_on": true, + "supports_forced_tool_use": false, + "source": "https://aws.amazon.com/bedrock/pricing/" + }, "anthropic.claude-opus-4-8": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, @@ -44379,6 +44619,41 @@ "supports_vision": true, "supports_xhigh_reasoning_effort": true }, + "us-gov.anthropic.claude-opus-5-5": { + "bedrock_converse_supports_strict_tools": false, + "cache_creation_input_token_cost": 6e-06, + "cache_creation_input_token_cost_above_1hr": 9.6e-06, + "cache_read_input_token_cost": 2.4e-07, + "input_cost_per_token": 4.8e-06, + "litellm_provider": "bedrock_converse", + "supports_tool_search": true, + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2.4e-05, + "prompt_cache_min_tokens": 512, + "source": "https://aws.amazon.com/bedrock/pricing/", + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_max_reasoning_effort": true, + "supports_mid_conversation_system": true, + "supports_native_structured_output": false, + "supports_output_config": true, + "supports_parallel_tool_use_config": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "thinking_always_on": true, + "supports_forced_tool_use": false + }, "us-gov.anthropic.claude-fable-5-1": { "cache_creation_input_token_cost": 1.5e-05, "cache_creation_input_token_cost_above_1hr": 2.4e-05, @@ -60807,6 +61082,41 @@ "supports_vision": true, "supports_xhigh_reasoning_effort": true }, + "bedrock/us-gov-west-1/anthropic.claude-opus-5-5": { + "bedrock_converse_supports_strict_tools": false, + "cache_creation_input_token_cost": 6e-06, + "cache_creation_input_token_cost_above_1hr": 9.6e-06, + "cache_read_input_token_cost": 2.4e-07, + "input_cost_per_token": 4.8e-06, + "litellm_provider": "bedrock", + "supports_tool_search": true, + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2.4e-05, + "prompt_cache_min_tokens": 512, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_max_reasoning_effort": true, + "supports_mid_conversation_system": true, + "supports_native_structured_output": false, + "supports_output_config": true, + "supports_parallel_tool_use_config": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "thinking_always_on": true, + "supports_forced_tool_use": false, + "source": "https://aws.amazon.com/bedrock/pricing/" + }, "bedrock/us-gov-west-1/anthropic.claude-fable-5-1": { "cache_creation_input_token_cost": 1.5e-05, "cache_creation_input_token_cost_above_1hr": 2.4e-05, @@ -61013,6 +61323,41 @@ "supports_vision": true, "supports_xhigh_reasoning_effort": true }, + "bedrock/us-gov-east-1/anthropic.claude-opus-5-5": { + "bedrock_converse_supports_strict_tools": false, + "cache_creation_input_token_cost": 6e-06, + "cache_creation_input_token_cost_above_1hr": 9.6e-06, + "cache_read_input_token_cost": 2.4e-07, + "input_cost_per_token": 4.8e-06, + "litellm_provider": "bedrock", + "supports_tool_search": true, + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2.4e-05, + "prompt_cache_min_tokens": 512, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_max_reasoning_effort": true, + "supports_mid_conversation_system": true, + "supports_native_structured_output": false, + "supports_output_config": true, + "supports_parallel_tool_use_config": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "thinking_always_on": true, + "supports_forced_tool_use": false, + "source": "https://aws.amazon.com/bedrock/pricing/" + }, "bedrock/us-gov-east-1/anthropic.claude-fable-5-1": { "cache_creation_input_token_cost": 1.5e-05, "cache_creation_input_token_cost_above_1hr": 2.4e-05, diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index b48bdd6322c..34cbea0e314 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -1773,6 +1773,46 @@ "prompt_cache_min_tokens": 512, "source": "https://aws.amazon.com/bedrock/pricing/" }, + "anthropic.claude-opus-5-5": { + "bedrock_converse_supports_strict_tools": false, + "supports_adaptive_thinking": true, + "supports_mid_conversation_system": true, + "cache_creation_input_token_cost": 5e-06, + "cache_creation_input_token_cost_above_1hr": 8e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 4e-06, + "litellm_provider": "bedrock_converse", + "supports_tool_search": true, + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": false, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "supports_parallel_tool_use_config": true, + "prompt_cache_min_tokens": 512, + "source": "https://aws.amazon.com/bedrock/pricing/", + "thinking_always_on": true, + "supports_forced_tool_use": false + }, "global.anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, @@ -1811,6 +1851,46 @@ "prompt_cache_min_tokens": 512, "source": "https://aws.amazon.com/bedrock/pricing/" }, + "global.anthropic.claude-opus-5-5": { + "bedrock_converse_supports_strict_tools": false, + "supports_adaptive_thinking": true, + "supports_mid_conversation_system": true, + "cache_creation_input_token_cost": 5e-06, + "cache_creation_input_token_cost_above_1hr": 8e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 4e-06, + "litellm_provider": "bedrock_converse", + "supports_tool_search": true, + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": false, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "supports_parallel_tool_use_config": true, + "prompt_cache_min_tokens": 512, + "source": "https://aws.amazon.com/bedrock/pricing/", + "thinking_always_on": true, + "supports_forced_tool_use": false + }, "us.anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, @@ -1849,6 +1929,46 @@ "prompt_cache_min_tokens": 512, "source": "https://aws.amazon.com/bedrock/pricing/" }, + "us.anthropic.claude-opus-5-5": { + "bedrock_converse_supports_strict_tools": false, + "supports_adaptive_thinking": true, + "supports_mid_conversation_system": true, + "cache_creation_input_token_cost": 5.5e-06, + "cache_creation_input_token_cost_above_1hr": 8.8e-06, + "cache_read_input_token_cost": 2.2e-07, + "input_cost_per_token": 4.4e-06, + "litellm_provider": "bedrock_converse", + "supports_tool_search": true, + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2.2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": false, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "supports_parallel_tool_use_config": true, + "prompt_cache_min_tokens": 512, + "source": "https://aws.amazon.com/bedrock/pricing/", + "thinking_always_on": true, + "supports_forced_tool_use": false + }, "eu.anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, @@ -1886,6 +2006,46 @@ "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 512 }, + "eu.anthropic.claude-opus-5-5": { + "bedrock_converse_supports_strict_tools": false, + "supports_adaptive_thinking": true, + "supports_mid_conversation_system": true, + "cache_creation_input_token_cost": 5.5e-06, + "cache_creation_input_token_cost_above_1hr": 8.8e-06, + "cache_read_input_token_cost": 2.2e-07, + "input_cost_per_token": 4.4e-06, + "litellm_provider": "bedrock_converse", + "supports_tool_search": true, + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2.2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": false, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "supports_parallel_tool_use_config": true, + "prompt_cache_min_tokens": 512, + "thinking_always_on": true, + "supports_forced_tool_use": false, + "source": "https://aws.amazon.com/bedrock/pricing/" + }, "au.anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, @@ -1923,6 +2083,46 @@ "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 512 }, + "au.anthropic.claude-opus-5-5": { + "bedrock_converse_supports_strict_tools": false, + "supports_adaptive_thinking": true, + "supports_mid_conversation_system": true, + "cache_creation_input_token_cost": 5.5e-06, + "cache_creation_input_token_cost_above_1hr": 8.8e-06, + "cache_read_input_token_cost": 2.2e-07, + "input_cost_per_token": 4.4e-06, + "litellm_provider": "bedrock_converse", + "supports_tool_search": true, + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2.2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": false, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "supports_parallel_tool_use_config": true, + "prompt_cache_min_tokens": 512, + "thinking_always_on": true, + "supports_forced_tool_use": false, + "source": "https://aws.amazon.com/bedrock/pricing/" + }, "jp.anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, @@ -1960,6 +2160,46 @@ "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 512 }, + "jp.anthropic.claude-opus-5-5": { + "bedrock_converse_supports_strict_tools": false, + "supports_adaptive_thinking": true, + "supports_mid_conversation_system": true, + "cache_creation_input_token_cost": 5.5e-06, + "cache_creation_input_token_cost_above_1hr": 8.8e-06, + "cache_read_input_token_cost": 2.2e-07, + "input_cost_per_token": 4.4e-06, + "litellm_provider": "bedrock_converse", + "supports_tool_search": true, + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2.2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": false, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "supports_parallel_tool_use_config": true, + "prompt_cache_min_tokens": 512, + "thinking_always_on": true, + "supports_forced_tool_use": false, + "source": "https://aws.amazon.com/bedrock/pricing/" + }, "anthropic.claude-opus-4-8": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, @@ -44379,6 +44619,41 @@ "supports_vision": true, "supports_xhigh_reasoning_effort": true }, + "us-gov.anthropic.claude-opus-5-5": { + "bedrock_converse_supports_strict_tools": false, + "cache_creation_input_token_cost": 6e-06, + "cache_creation_input_token_cost_above_1hr": 9.6e-06, + "cache_read_input_token_cost": 2.4e-07, + "input_cost_per_token": 4.8e-06, + "litellm_provider": "bedrock_converse", + "supports_tool_search": true, + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2.4e-05, + "prompt_cache_min_tokens": 512, + "source": "https://aws.amazon.com/bedrock/pricing/", + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_max_reasoning_effort": true, + "supports_mid_conversation_system": true, + "supports_native_structured_output": false, + "supports_output_config": true, + "supports_parallel_tool_use_config": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "thinking_always_on": true, + "supports_forced_tool_use": false + }, "us-gov.anthropic.claude-fable-5-1": { "cache_creation_input_token_cost": 1.5e-05, "cache_creation_input_token_cost_above_1hr": 2.4e-05, @@ -60807,6 +61082,41 @@ "supports_vision": true, "supports_xhigh_reasoning_effort": true }, + "bedrock/us-gov-west-1/anthropic.claude-opus-5-5": { + "bedrock_converse_supports_strict_tools": false, + "cache_creation_input_token_cost": 6e-06, + "cache_creation_input_token_cost_above_1hr": 9.6e-06, + "cache_read_input_token_cost": 2.4e-07, + "input_cost_per_token": 4.8e-06, + "litellm_provider": "bedrock", + "supports_tool_search": true, + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2.4e-05, + "prompt_cache_min_tokens": 512, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_max_reasoning_effort": true, + "supports_mid_conversation_system": true, + "supports_native_structured_output": false, + "supports_output_config": true, + "supports_parallel_tool_use_config": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "thinking_always_on": true, + "supports_forced_tool_use": false, + "source": "https://aws.amazon.com/bedrock/pricing/" + }, "bedrock/us-gov-west-1/anthropic.claude-fable-5-1": { "cache_creation_input_token_cost": 1.5e-05, "cache_creation_input_token_cost_above_1hr": 2.4e-05, @@ -61013,6 +61323,41 @@ "supports_vision": true, "supports_xhigh_reasoning_effort": true }, + "bedrock/us-gov-east-1/anthropic.claude-opus-5-5": { + "bedrock_converse_supports_strict_tools": false, + "cache_creation_input_token_cost": 6e-06, + "cache_creation_input_token_cost_above_1hr": 9.6e-06, + "cache_read_input_token_cost": 2.4e-07, + "input_cost_per_token": 4.8e-06, + "litellm_provider": "bedrock", + "supports_tool_search": true, + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2.4e-05, + "prompt_cache_min_tokens": 512, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_max_reasoning_effort": true, + "supports_mid_conversation_system": true, + "supports_native_structured_output": false, + "supports_output_config": true, + "supports_parallel_tool_use_config": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "thinking_always_on": true, + "supports_forced_tool_use": false, + "source": "https://aws.amazon.com/bedrock/pricing/" + }, "bedrock/us-gov-east-1/anthropic.claude-fable-5-1": { "cache_creation_input_token_cost": 1.5e-05, "cache_creation_input_token_cost_above_1hr": 2.4e-05, From f7ae9efad2a6db8d588a201f1d644d706944580e Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 14:47:14 -0700 Subject: [PATCH 041/101] test(e2e): hold every worker under an idle RSS budget before any traffic (#42552) * test(e2e): hold every worker under an idle RSS budget before any traffic The harness reads /debug/memory/summary on every replica once at collection time, right after the readiness gate and before this pytest process sends any traffic, and the memory suite's first test fails when any worker idles past E2E_MEMORY_IDLE_RSS_BUDGET_MB (768 MB by default) or gives no reading at all. A v1.100.x worker with a database idled at 836-886 MB where v1.101.0rc1 idled at 544 MB on the same database: prisma-client-py's default recursive type depth generated 91k TypedDict classes that v1.101.0's recursive_type_depth = -1 cut to 19k. The budget starts at the rc1 reading plus headroom. * test(e2e): read idle RSS only when the idle budget test is selected Gate the collection-time /debug/memory/summary read on a selected test using the idle_rss fixture and skip it under --collect-only, so sessions that never run the idle budget test pay no round trip. Drop the markerless unit test file the e2e guide bans and assert live that every configured replica was measured * test(e2e): take the idle RSS read after collection settles Read every replica's RSS from a tryfirst pytest_collection_finish hook so -k and -m deselection has already run, and only when a selected test still asks for the idle_rss fixture and the run is not --collect-only * test(e2e): record the heaviest idle RSS reading as junit properties * test(e2e): attach the idle RSS properties from the harness's setup hook --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- tests/e2e/AGENTS.md | 4 +- tests/e2e/conftest.py | 41 +++++++++- tests/e2e/coverage_registry/reliability.yaml | 1 + tests/e2e/e2e_config.py | 1 + tests/e2e/memory_readings.py | 78 +++++++++++++++++++ tests/e2e/proxy_client.py | 5 +- .../e2e/router/test_reliability_memory_e2e.py | 63 ++++++++++----- 7 files changed, 167 insertions(+), 26 deletions(-) create mode 100644 tests/e2e/memory_readings.py diff --git a/tests/e2e/AGENTS.md b/tests/e2e/AGENTS.md index ad1e0322787..6212a172fe3 100644 --- a/tests/e2e/AGENTS.md +++ b/tests/e2e/AGENTS.md @@ -43,7 +43,7 @@ Each subdirectory under `tests/e2e/` is one suite, scoped to an endpoint family - `mcp/` - the MCP server surface over api_key auth against the real Datadog remote MCP server (see "MCP suite: real Datadog only" below); plus the gateway-managed OAuth (authorization_code) path exercised through `/chat/completions` in `test_mcp_chat_completion_oauth_e2e.py` and direct MCP protocol operations in `test_mcp_oauth_happy_path_e2e.py`, the one behavior Datadog's static-header auth cannot reach, seeding the per-user upstream token via the interactive authorize dance driven with the mcp SDK's own OAuth client (headless-browser consent from a saved session) and asserting the completion or protocol call lists and executes the server's tools with the stored per-user token - `logging/` - logging-integration delivery (datadog and friends) - `security/` - secret handling and log-leak protection -- `router/` - routing and reliability behavior (fallbacks, cooldowns) plus the memory regression test (`test_reliability_memory_e2e.py`: a few hundred failing requests with retries and fallbacks must not grow proxy RSS past a fixed budget nor store a request snapshot past a fixed size, the release-gate check for the v1.100.0 retry-breadcrumb leak) +- `router/` - routing and reliability behavior (fallbacks, cooldowns) plus the memory tests (`test_reliability_memory_e2e.py`: every worker's RSS as read at collection time, before any test traffic, must sit under a fixed idle budget, the release-gate check for a DB-backed boot that idles near the pod limit the way v1.100.x did; and a few hundred failing requests with retries and fallbacks must not grow proxy RSS past a fixed budget nor store a request snapshot past a fixed size, the release-gate check for the v1.100.0 retry-breadcrumb leak) - `load/` - performance-category tests, kept OUT of the main suite: throughput/load SLO tests are a different testing category from functional e2e (variance-driven, historically flaky) and live outside this suite until re-implemented as their own pipeline (LIT-5163); do not add a live load test that runs in the default collection. What lives here: the weekly session-anomaly test (`test_weekly_session_anomaly_e2e.py`, Claude Code-shaped multi-turn sessions against real providers with ceilings on error rate, cache read/write, turn time, and spend; marked `weekly` and deselected unless `E2E_WEEKLY_ANOMALY` is set, driven by `.github/workflows/weekly_load_anomaly.yml`), the Redis chaos test (`test_redis_chaos_e2e.py`, locust load against mock deployments split round robin over `/chat/completions` and `/v1/messages`, one endpoint per simulated user, with `CLIENT PAUSE ALL` on the proxy's Redis mid-run to simulate it being down outright, asserting zero failed requests on every endpoint, budgeting RSS and CPU-per-request as ratios against the same run's healthy phase, and holding p50/p90/p99 latency and log-bytes-per-request to flat ceilings (a ratio cannot bound those two: an open breaker skips Redis instead of waiting on it, so the chaos phase can measure cheaper than baseline while still being far slower than a user should see); needs a proxy booted from `gateway/redis_chaos_ci_config.yml` on the same host with `E2E_PROXY_PID` and `E2E_PROXY_LOG` set, marked `redis_chaos`, deselected unless `E2E_REDIS_CHAOS` is set and excluded from the per-PR selector like the rest of `load/`, driven by `.github/workflows/test-e2e-redis-chaos.yml` and by the Buildkite `e2e-redis-chaos` step in project-releaser, which runs the proxy, Postgres and Valkey co-located with pytest in one pod and sets the opt-in), and markerless harness unit tests for the locust, process-usage, and session-anomaly aggregation logic - `other/` - the holding-pen suite for the `other.*` registry cluster with no home of its own yet: the master-key auth gate, JWT auth (access tokens issued by a real Keycloak realm, `idp.py` plus `idp_realm.json`, whose JWKS the proxy's `JWT_PUBLIC_KEY_URL` points at; see CONTRIBUTING.md for the start command and config block), and the process-lifecycle health probes (liveness, public readiness, authenticated readiness diagnostics). Promote a cluster out once it is large/stable enough for its own suite - `gateway/` - proxy configuration only (`litellm-config.yml`); no tests @@ -191,7 +191,7 @@ reliability... behavior : fallback | retry | cooldown | timeout | routing | cache | circuit_breaker | perf variant : 5xx | context_window | content_policy | 429 | timeout simple_shuffle | usage_based | latency_based | cost_based | least_busy - latency | throughput | session_anomaly | memory (perf only; SLO/threshold assertion, not binary) + latency | throughput | session_anomaly | memory | idle_memory (perf only; SLO/threshold assertion, not binary) assertion : routes_to_fallback | succeeds_within_retries | picks_under_tpm | returns_cached | trips_then_recovers | under_slo e.g. reliability.fallback.context_window.routes_to_fallback exercised_on=[chat_completions] diff --git a/tests/e2e/conftest.py b/tests/e2e/conftest.py index a2398ef7c3c..f1f94f2d2b3 100644 --- a/tests/e2e/conftest.py +++ b/tests/e2e/conftest.py @@ -46,6 +46,7 @@ from fixture_mode import pytest_fixture_setup as pytest_fixture_setup from idp import Identity, Keycloak, keycloak_from_env from junit_properties import attach_result_properties from lifecycle import ProxyClientProvider, ResourceManager +from memory_readings import RssCapture, read_rss_everywhere from models import TeamNewBody, UserNewBody, UserNewResponse from provider_cache_routing import LIVE_PROVIDER_REQUIRED from provider_edge import replay_leftover_error @@ -53,6 +54,9 @@ from proxy_client import ProxyClient, build_proxy_client _E2E_TEST_RAN = pytest.StashKey[bool]() _CALL_PASSED = pytest.StashKey[bool]() +_IDLE_RSS = pytest.StashKey[RssCapture]() + +IDLE_RSS_READ_TIMEOUT_SECONDS: Final = 10.0 OPT_IN_MARKERS: Final = MappingProxyType( { @@ -186,6 +190,16 @@ def _needs_unset_opt_in(item: pytest.Item) -> bool: ) +def _reaches_proxy(item: pytest.Item) -> bool: + """True for a live test that talks to the shared proxy: `e2e`-marked and not a + `migration_startup` test, which boots its own container instead.""" + return item.get_closest_marker("e2e") is not None and item.get_closest_marker("migration_startup") is None + + +def _uses_idle_rss(item: pytest.Item) -> bool: + return isinstance(item, pytest.Function) and "idle_rss" in item.fixturenames + + def pytest_collection_modifyitems(config: pytest.Config, items: list[pytest.Item]) -> None: """Deselect every test behind an opt-in marker whose env var is unset (see OPT_IN_MARKERS): those tests need a proxy configured differently from the @@ -215,6 +229,20 @@ def pytest_collection_modifyitems(config: pytest.Config, items: list[pytest.Item items.sort(key=lambda item: item.get_closest_marker("load") is not None) +@pytest.hookimpl(tryfirst=True) +def pytest_collection_finish(session: pytest.Session) -> None: + """When a selected test asks for the `idle_rss` fixture and this is not a + `--collect-only` run, read every replica's RSS once, right here at the end of + collection and before this process sends any traffic. tryfirst keeps the read + ahead of xdist's own collection-finish report, and the controller schedules no + test until every worker has reported, so this is the idle footprint of a stack + that just passed its readiness gate. The fixture hands the capture to the + idle-budget test in router/test_reliability_memory_e2e.py.""" + if session.config.getoption("collectonly") or not any(_uses_idle_rss(item) for item in session.items): + return + session.config.stash[_IDLE_RSS] = read_rss_everywhere(build_proxy_client(), timeout=IDLE_RSS_READ_TIMEOUT_SECONDS) + + def _liveness_reason(label: str, base_url: str) -> str | None: """None if `base_url` answers its liveness probe, else a failure reason.""" try: @@ -246,7 +274,9 @@ def pytest_runtest_setup(item: pytest.Item) -> None: run even when none is up. Never skip for a missing proxy. Replay mode needs the proxy too: only provider-bound traffic replays from the bundle.""" LIVE_PROVIDER_REQUIRED.set(item.get_closest_marker("provider_live") is not None) - if item.get_closest_marker("e2e") is None or item.get_closest_marker("migration_startup") is not None: + if _uses_idle_rss(item): + item.user_properties.extend(item.config.stash[_IDLE_RSS].junit_properties) + if not _reaches_proxy(item): return if isinstance(item, pytest.Function) and "oauth_gateway" in item.fixturenames: return @@ -261,7 +291,7 @@ def pytest_runtest_call(item: pytest.Item) -> None: guard before truncating the spend-log DB. Tests under `tests/e2e/` without the `e2e` marker (pure unit coverage for the harness itself) never hit the proxy, so they must not arm the destructive DB truncate.""" - if item.get_closest_marker("e2e") is None or item.get_closest_marker("migration_startup") is not None: + if not _reaches_proxy(item): return item.session.stash[_E2E_TEST_RAN] = True @@ -325,6 +355,13 @@ def proxy() -> ProxyClient: return build_proxy_client() +@pytest.fixture(scope="session") +def idle_rss(request: pytest.FixtureRequest) -> RssCapture: + """Every replica's RSS as read once at the end of collection, before this process + sent any traffic (see pytest_collection_finish).""" + return request.config.stash[_IDLE_RSS] + + @pytest.fixture def resources(client: ProxyClientProvider) -> Iterator[ResourceManager]: """init -> run -> teardown: create a manager, run the test, release resources. diff --git a/tests/e2e/coverage_registry/reliability.yaml b/tests/e2e/coverage_registry/reliability.yaml index 9f88f2478c0..5040f5f4dcf 100644 --- a/tests/e2e/coverage_registry/reliability.yaml +++ b/tests/e2e/coverage_registry/reliability.yaml @@ -38,4 +38,5 @@ - {id: reliability.timeout.stream_timeout.exceeds_deadline, module: reliability, tier: P1, behavior: timeout, variant: stream_timeout, assertions: [exceeds_deadline], exercised_on: [chat_completions], source: "litellm/router.py:551", rationale: "Streaming chunk-delivery timeout"} - {id: reliability.perf.throughput.under_slo, module: reliability, tier: P1, behavior: perf, variant: throughput, assertions: [under_slo], exercised_on: [chat_completions, messages], source: grammar, rationale: "Throughput SLO under load"} - {id: reliability.perf.memory.under_slo, module: reliability, tier: P1, behavior: perf, variant: memory, assertions: [under_slo], exercised_on: [chat_completions], source: grammar, rationale: "Proxy RSS and the stored request snapshot stay within fixed budgets across a few hundred failing requests with retries and fallbacks, the v1.100.0 retry-breadcrumb leak shape (MAT-335)"} +- {id: reliability.perf.idle_memory.under_slo, module: reliability, tier: P1, behavior: perf, variant: idle_memory, assertions: [under_slo], exercised_on: [], source: grammar, rationale: "Every worker's RSS as read right after the readiness gate and before any test traffic stays under a fixed idle budget; a DB-backed v1.100.x worker idled at 886 MB against a 2 GiB pod limit where v1.101.0rc1 idled at 544 MB"} - {id: reliability.perf.session_anomaly.under_slo, module: reliability, tier: P1, behavior: perf, variant: session_anomaly, assertions: [under_slo], exercised_on: [messages], source: grammar, rationale: "Weekly Claude Code-shaped multi-turn session load against real providers; ceilings on error rate, warm-turn cache read/write, p95 turn time, and gateway-recorded spend (LIT-4562)"} diff --git a/tests/e2e/e2e_config.py b/tests/e2e/e2e_config.py index 77395a066ac..ac26b2a3875 100644 --- a/tests/e2e/e2e_config.py +++ b/tests/e2e/e2e_config.py @@ -173,6 +173,7 @@ MEMORY_CONCURRENCY = int(os.environ.get("E2E_MEMORY_CONCURRENCY", "4")) MEMORY_RSS_SETTLE_SAMPLES = int(os.environ.get("E2E_MEMORY_RSS_SETTLE_SAMPLES", "15")) MEMORY_RSS_SAMPLE_INTERVAL_SECONDS = float(os.environ.get("E2E_MEMORY_RSS_SAMPLE_INTERVAL_SECONDS", "1")) MEMORY_RSS_BUDGET_MB = float(os.environ.get("E2E_MEMORY_RSS_BUDGET_MB", "48")) +MEMORY_IDLE_RSS_BUDGET_MB = float(os.environ.get("E2E_MEMORY_IDLE_RSS_BUDGET_MB", "768")) MEMORY_STORED_REQUEST_BUDGET_KB = float(os.environ.get("E2E_MEMORY_STORED_REQUEST_BUDGET_KB", "64")) diff --git a/tests/e2e/memory_readings.py b/tests/e2e/memory_readings.py new file mode 100644 index 00000000000..37a27c455f8 --- /dev/null +++ b/tests/e2e/memory_readings.py @@ -0,0 +1,78 @@ +"""Per-worker RSS readings of the proxy through /debug/memory/summary. + +One read goes to every configured replica (PROXY_REPLICA_URLS) under the master +key and answers from whichever worker behind that address took the connection; +the release stack runs one worker per gateway replica, so a read per replica is +a read per worker. A reading keys its worker by replica address, hostname, and +pid, since pods in their own pid namespaces report the same pids. A replica that +gives no reading (unreachable, a non-2xx, or a summary without ram_usage_mb) is +kept as a failure reason rather than dropped, so a test can fail on it by name +instead of passing on the replicas that did answer. +""" + +from __future__ import annotations + +from collections.abc import Mapping +from dataclasses import dataclass +from typing import Final + +from e2e_http import Result, Success +from models import MemorySummaryResponse +from proxy_client import ProxyClient + +WorkerKey = tuple[str, str | None, int] + + +@dataclass(frozen=True, slots=True) +class RssReading: + replica: str + hostname: str | None + worker_pid: int + ram_usage_mb: float + + @property + def worker(self) -> WorkerKey: + return (self.replica, self.hostname, self.worker_pid) + + @property + def where(self) -> str: + return f"worker pid {self.worker_pid} on {self.hostname or 'an unnamed host'} behind {self.replica}" + + +@dataclass(frozen=True, slots=True) +class RssCapture: + readings: tuple[RssReading, ...] + failures: tuple[str, ...] + + @property + def heaviest(self) -> RssReading | None: + return max(self.readings, key=lambda reading: reading.ram_usage_mb, default=None) + + @property + def junit_properties(self) -> tuple[tuple[str, object], ...]: + heaviest: Final = self.heaviest + if heaviest is None: + return () + return (("idle_rss_heaviest_mb", heaviest.ram_usage_mb), ("idle_rss_heaviest_worker", heaviest.where)) + + +def _outcome(replica: str, result: Result[MemorySummaryResponse]) -> RssReading | str: + match result: + case Success(data=body) if body.memory.ram_usage_mb is not None: + return RssReading(replica, body.hostname, body.worker_pid, body.memory.ram_usage_mb) + case Success(data=body): + return f"{replica} answered /debug/memory/summary without ram_usage_mb: {body.memory.error}" + case _: + return f"{replica} gave no /debug/memory/summary reading: {result}" + + +def rss_capture(summaries: Mapping[str, Result[MemorySummaryResponse]]) -> RssCapture: + outcomes: Final = tuple(_outcome(replica, result) for replica, result in summaries.items()) + return RssCapture( + readings=tuple(outcome for outcome in outcomes if isinstance(outcome, RssReading)), + failures=tuple(outcome for outcome in outcomes if isinstance(outcome, str)), + ) + + +def read_rss_everywhere(proxy: ProxyClient, *, timeout: float | None = None) -> RssCapture: + return rss_capture(proxy.memory_summary_everywhere(timeout=timeout)) diff --git a/tests/e2e/proxy_client.py b/tests/e2e/proxy_client.py index 66df1c4c106..51ea9fbe7bd 100644 --- a/tests/e2e/proxy_client.py +++ b/tests/e2e/proxy_client.py @@ -508,13 +508,16 @@ class ProxyClient: ) ).info - def memory_summary_everywhere(self) -> Mapping[str, Result[MemorySummaryResponse]]: + def memory_summary_everywhere( + self, *, timeout: float | None = None + ) -> Mapping[str, Result[MemorySummaryResponse]]: return { url: transport.get( "/debug/memory/summary", headers=self.management_headers(transport=transport), params=NoBody(), response_type=MemorySummaryResponse, + timeout=timeout, ) for url, transport in self.replicas.items() } diff --git a/tests/e2e/router/test_reliability_memory_e2e.py b/tests/e2e/router/test_reliability_memory_e2e.py index 17e3e1a1996..2568434a08f 100644 --- a/tests/e2e/router/test_reliability_memory_e2e.py +++ b/tests/e2e/router/test_reliability_memory_e2e.py @@ -38,6 +38,20 @@ size budget: the deterministic catch for a breadcrumb that copies the whole request. It runs before the phases because the leaking writer drops its own rows under the phases' traffic (a queue budget hit, a recursion limit on the nested copies), which would turn the size check into a missing-row check. + +A second, cheaper check holds the idle footprint: every worker's RSS as the harness +read it at collection time, before this pytest process sent any traffic (see +conftest.pytest_collection_finish), must sit under a fixed budget. On the +release gate that is a fresh stack right after its readiness gate, one worker per +gateway replica, so the reading is what a DB-backed boot costs on its own. A +v1.100.x worker with a database idled at 886 MB RSS where v1.101.0rc1 idled at +544 MB on the same database (1.3 GB against 560 MB at the pod level, under a +2 GiB limit): the generated Prisma client at prisma-client-py's default recursive +type depth, 91k TypedDict classes that v1.101.0 cut to 19k with +recursive_type_depth = -1. The budget starts at the rc1 reading plus headroom and +E2E_MEMORY_IDLE_RSS_BUDGET_MB overrides it; a later session on the same stack (the +changed-files workflow's repeat passes, a developer's local loop) measures a proxy +already warmed by traffic, which that headroom also has to cover. """ from __future__ import annotations @@ -55,6 +69,7 @@ import pytest from complexity_router_client import ComplexityRouterClient from e2e_config import ( MEMORY_CONCURRENCY, + MEMORY_IDLE_RSS_BUDGET_MB, MEMORY_REQUESTS_PER_PHASE, MEMORY_RETRIES_PER_REQUEST, MEMORY_RSS_BUDGET_MB, @@ -62,10 +77,11 @@ from e2e_config import ( MEMORY_RSS_SETTLE_SAMPLES, MEMORY_STORED_REQUEST_BUDGET_KB, MEMORY_TRANSCRIPT_TURNS, + PROXY_REPLICA_URLS, unique_marker, ) -from e2e_http import unwrap from lifecycle import ResourceManager +from memory_readings import RssCapture, RssReading, WorkerKey, read_rss_everywhere from models import ChatMessage, RouterSettingsOverride, SpendLogRow from proxy_client import ProxyClient from reliability_support import chat_override, create_never_benched_refusing_deployment @@ -84,21 +100,6 @@ class FailedCall: call_id: str | None -WorkerKey = tuple[str, str | None, int] - - -@dataclass(frozen=True, slots=True) -class RssReading: - replica: str - hostname: str | None - worker_pid: int - ram_usage_mb: float - - @property - def worker(self) -> WorkerKey: - return (self.replica, self.hostname, self.worker_pid) - - @dataclass(frozen=True, slots=True) class WorkerGrowth: warm: RssReading @@ -143,12 +144,12 @@ def _fail_many(proxy: ProxyClient, key: str, model: str, override: RouterSetting def _read_rss_everywhere_after_pause(proxy: ProxyClient) -> tuple[RssReading, ...]: time.sleep(MEMORY_RSS_SAMPLE_INTERVAL_SECONDS) - return tuple( - RssReading(replica, body.hostname, body.worker_pid, body.memory.ram_usage_mb) - for replica, result in proxy.memory_summary_everywhere().items() - for body in (unwrap(result),) - if body.memory.ram_usage_mb is not None + capture: Final = read_rss_everywhere(proxy) + assert not capture.failures, ( + f"{len(capture.failures)} replica(s) gave no RSS reading mid-checkpoint, so their workers cannot be " + f"compared with themselves: {'; '.join(capture.failures)}" ) + return capture.readings def _readings_until_no_new_worker( @@ -220,6 +221,26 @@ def _stored_request_kb(proxy: ProxyClient, call: FailedCall) -> float: class TestReliabilityMemory: + @pytest.mark.covers("reliability.perf.idle_memory.under_slo") + def test_workers_idle_under_rss_budget_before_traffic(self, idle_rss: RssCapture) -> None: + assert not idle_rss.failures, ( + f"{len(idle_rss.failures)} replica(s) gave no RSS reading when the session started, so their idle " + f"footprint went unmeasured: {'; '.join(idle_rss.failures)}" + ) + unmeasured: Final = frozenset(PROXY_REPLICA_URLS) - frozenset(reading.replica for reading in idle_rss.readings) + assert not unmeasured, ( + f"{len(unmeasured)} of {len(PROXY_REPLICA_URLS)} replica(s) gave neither an RSS reading nor a failure " + f"reason when the session started, so their idle footprint went unmeasured: {', '.join(sorted(unmeasured))}" + ) + heaviest: Final = idle_rss.heaviest + assert heaviest is not None, "no replica was configured to read, so nothing was measured" + assert heaviest.ram_usage_mb <= MEMORY_IDLE_RSS_BUDGET_MB, ( + f"{heaviest.where} sat at {heaviest.ram_usage_mb:.0f} MB RSS when the session started, before it sent " + f"any traffic, past the {MEMORY_IDLE_RSS_BUDGET_MB:.0f} MB idle budget; a DB-backed v1.100.x worker idled " + f"at 886 MB where v1.101.0rc1 idled at 544 MB, and at that size the release stack's 2 GiB pod limit " + f"leaves the worker little room for traffic" + ) + @pytest.mark.covers("reliability.perf.memory.under_slo") def test_failing_requests_do_not_grow_rss_or_stored_request( self, client: ComplexityRouterClient, resources: ResourceManager, scoped_key: str From d31e8aac6d41819fa3f4de739b7995ca7c337264 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 21:48:07 +0000 Subject: [PATCH 042/101] feat(cost-map): add Claude Opus 5.5 for Vertex AI and Azure AI (#42599) Co-authored-by: kerry Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- ...odel_prices_and_context_window_backup.json | 107 ++++++++++++++++++ model_prices_and_context_window.json | 107 ++++++++++++++++++ .../test_litellm/test_claude_opus_5_config.py | 36 ++++-- 3 files changed, 242 insertions(+), 8 deletions(-) diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 34cbea0e314..3f1d26e9adc 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -3527,6 +3527,41 @@ "supports_max_reasoning_effort": true, "prompt_cache_min_tokens": 512 }, + "azure_ai/claude-opus-5-5": { + "supports_mid_conversation_system": true, + "input_cost_per_token": 4e-06, + "output_cost_per_token": 2e-05, + "litellm_provider": "azure_ai", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "cache_creation_input_token_cost": 5e-06, + "cache_creation_input_token_cost_above_1hr": 8e-06, + "cache_read_input_token_cost": 2e-07, + "supports_adaptive_thinking": true, + "thinking_always_on": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_forced_tool_use": false, + "supports_function_calling": true, + "supports_native_structured_output": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_max_reasoning_effort": true, + "prompt_cache_min_tokens": 512 + }, "azure_ai/claude-opus-4-8": { "deprecation_date": "2027-09-01", "supports_mid_conversation_system": true, @@ -47016,6 +47051,78 @@ "supports_max_reasoning_effort": true, "prompt_cache_min_tokens": 512 }, + "vertex_ai/claude-opus-5-5": { + "regional_endpoint_uplift_multiplier": 1.1, + "supports_mid_conversation_system": true, + "cache_creation_input_token_cost": 5e-06, + "cache_creation_input_token_cost_above_1hr": 8e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 4e-06, + "litellm_provider": "vertex_ai-anthropic_models", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "thinking_always_on": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_forced_tool_use": false, + "supports_function_calling": true, + "supports_native_structured_output": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_max_reasoning_effort": true, + "prompt_cache_min_tokens": 512 + }, + "vertex_ai/claude-opus-5-5@default": { + "regional_endpoint_uplift_multiplier": 1.1, + "supports_mid_conversation_system": true, + "cache_creation_input_token_cost": 5e-06, + "cache_creation_input_token_cost_above_1hr": 8e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 4e-06, + "litellm_provider": "vertex_ai-anthropic_models", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "thinking_always_on": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_forced_tool_use": false, + "supports_function_calling": true, + "supports_native_structured_output": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_max_reasoning_effort": true, + "prompt_cache_min_tokens": 512 + }, "vertex_ai/claude-opus-4-8": { "deprecation_date": "2027-05-28", "regional_endpoint_uplift_multiplier": 1.1, diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 34cbea0e314..3f1d26e9adc 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -3527,6 +3527,41 @@ "supports_max_reasoning_effort": true, "prompt_cache_min_tokens": 512 }, + "azure_ai/claude-opus-5-5": { + "supports_mid_conversation_system": true, + "input_cost_per_token": 4e-06, + "output_cost_per_token": 2e-05, + "litellm_provider": "azure_ai", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "cache_creation_input_token_cost": 5e-06, + "cache_creation_input_token_cost_above_1hr": 8e-06, + "cache_read_input_token_cost": 2e-07, + "supports_adaptive_thinking": true, + "thinking_always_on": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_forced_tool_use": false, + "supports_function_calling": true, + "supports_native_structured_output": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_max_reasoning_effort": true, + "prompt_cache_min_tokens": 512 + }, "azure_ai/claude-opus-4-8": { "deprecation_date": "2027-09-01", "supports_mid_conversation_system": true, @@ -47016,6 +47051,78 @@ "supports_max_reasoning_effort": true, "prompt_cache_min_tokens": 512 }, + "vertex_ai/claude-opus-5-5": { + "regional_endpoint_uplift_multiplier": 1.1, + "supports_mid_conversation_system": true, + "cache_creation_input_token_cost": 5e-06, + "cache_creation_input_token_cost_above_1hr": 8e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 4e-06, + "litellm_provider": "vertex_ai-anthropic_models", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "thinking_always_on": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_forced_tool_use": false, + "supports_function_calling": true, + "supports_native_structured_output": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_max_reasoning_effort": true, + "prompt_cache_min_tokens": 512 + }, + "vertex_ai/claude-opus-5-5@default": { + "regional_endpoint_uplift_multiplier": 1.1, + "supports_mid_conversation_system": true, + "cache_creation_input_token_cost": 5e-06, + "cache_creation_input_token_cost_above_1hr": 8e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 4e-06, + "litellm_provider": "vertex_ai-anthropic_models", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "thinking_always_on": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_forced_tool_use": false, + "supports_function_calling": true, + "supports_native_structured_output": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_max_reasoning_effort": true, + "prompt_cache_min_tokens": 512 + }, "vertex_ai/claude-opus-4-8": { "deprecation_date": "2027-05-28", "regional_endpoint_uplift_multiplier": 1.1, diff --git a/tests/test_litellm/test_claude_opus_5_config.py b/tests/test_litellm/test_claude_opus_5_config.py index 2e0a359b79b..b5efe016a60 100644 --- a/tests/test_litellm/test_claude_opus_5_config.py +++ b/tests/test_litellm/test_claude_opus_5_config.py @@ -41,7 +41,10 @@ ALL_OPUS_5_VARIANTS = ( "jp.anthropic.claude-opus-5", "vertex_ai/claude-opus-5", "vertex_ai/claude-opus-5@default", + "vertex_ai/claude-opus-5-5", + "vertex_ai/claude-opus-5-5@default", "azure_ai/claude-opus-5", + "azure_ai/claude-opus-5-5", ) BEDROCK_OPUS_5_VARIANTS = ( @@ -69,20 +72,37 @@ def test_opus_5_registered_for_bedrock_converse(): assert "anthropic.claude-opus-5" in BEDROCK_CONVERSE_MODELS -def test_opus_5_5_present_in_bundled_backup(): +OPUS_5_5_VARIANTS = ( + "claude-opus-5-5", + "vertex_ai/claude-opus-5-5", + "vertex_ai/claude-opus-5-5@default", + "azure_ai/claude-opus-5-5", +) + + +@pytest.mark.parametrize("model_name", OPUS_5_5_VARIANTS) +def test_opus_5_5_present_in_bundled_backup(model_name): backup = GetModelCostMap.load_local_model_cost_map() root = _load_root_cost_map() - assert "claude-opus-5-5" in backup - assert "claude-opus-5-5" in root - assert backup["claude-opus-5-5"] == root["claude-opus-5-5"] + assert model_name in backup + assert model_name in root + assert backup[model_name] == root[model_name] -@pytest.mark.parametrize("model", ["claude-opus-5-5", "anthropic/claude-opus-5-5"]) -def test_opus_5_5_thinking_profile(local_model_cost_map, model): +@pytest.mark.parametrize( + ("model", "provider"), + [ + ("claude-opus-5-5", "anthropic"), + ("anthropic/claude-opus-5-5", "anthropic"), + ("vertex_ai/claude-opus-5-5", "vertex_ai"), + ("azure_ai/claude-opus-5-5", "azure_ai"), + ], +) +def test_opus_5_5_thinking_profile(local_model_cost_map, model, provider): """Opus 5.5 has thinking always on with the adaptive thinking surface, and no forced tool use, same as Fable 5.1.""" from litellm.llms.anthropic.common_utils import AnthropicModelInfo - assert AnthropicModelInfo._is_adaptive_thinking_model(model, "anthropic") is True - assert AnthropicModelInfo._is_always_on_thinking_model(model, "anthropic") is True + assert AnthropicModelInfo._is_adaptive_thinking_model(model, provider) is True + assert AnthropicModelInfo._is_always_on_thinking_model(model, provider) is True assert AnthropicModelInfo.forced_tool_use_unsupported(model.removeprefix("anthropic/")) is True From d7c27cdc087937abfade549b2bb5fa9e968a8081 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 14:52:01 -0700 Subject: [PATCH 043/101] feat(proxy): configurable key_alias_pattern for key generate, update, and regenerate (#42553) * feat(proxy): configurable key_alias_pattern for key generate, update, and regenerate Adds litellm_settings.key_alias_pattern, a regex every key_alias sent to /key/generate, /key/service-account/generate, /key/update, and /key/{key}/regenerate has to fully match. A non-matching alias gets a 400 that names the setting and the pattern. When set, it replaces the built-in rule enable_key_alias_format_validation turns on, and the baseline unsafe-name check still runs first. An invalid regex fails config load. * fix(proxy): cap key_alias length under key_alias_pattern and type the test fixtures * style(proxy): declare key_alias_pattern with a PEP 604 union --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- litellm/__init__.py | 1 + .../key_management_endpoints.py | 56 +++++-- litellm/proxy/proxy_server.py | 3 + .../test_key_management_endpoints.py | 158 ++++++++++++++++++ tests/test_litellm/proxy/test_proxy_server.py | 17 ++ 5 files changed, 219 insertions(+), 16 deletions(-) diff --git a/litellm/__init__.py b/litellm/__init__.py index a044676a843..471b273f00d 100644 --- a/litellm/__init__.py +++ b/litellm/__init__.py @@ -381,6 +381,7 @@ enable_model_config_credential_overrides: bool = False enable_key_alias_format_validation: bool = ( False # opt-in validation of key_alias format on /key/generate and /key/update ) +key_alias_pattern: str | None = None enable_gemini_default_thinking_level_low: bool = ( False # opt-in: force thinkingLevel low/minimal for Gemini 3 thinking param mapping ) diff --git a/litellm/proxy/management_endpoints/key_management_endpoints.py b/litellm/proxy/management_endpoints/key_management_endpoints.py index 801c45501ce..1845f11c0fa 100644 --- a/litellm/proxy/management_endpoints/key_management_endpoints.py +++ b/litellm/proxy/management_endpoints/key_management_endpoints.py @@ -7590,25 +7590,47 @@ async def test_key_logging( _KEY_ALIAS_PATTERN: Final = re.compile(r"^[a-zA-Z0-9][a-zA-Z0-9_\-/\.@]{0,253}[a-zA-Z0-9]$") +_KEY_ALIAS_PATTERN_MESSAGE: Final = ( + "Invalid key_alias format. Must be 2-255 characters, start/end with alphanumeric, and only contain a-zA-Z0-9_-/.@." +) +_KEY_ALIAS_MAX_LENGTH: Final = 255 + + +def parse_key_alias_pattern(value: object) -> str | None: + if value is None: + return None + if not isinstance(value, str): + raise ValueError( + f"Invalid regex set for litellm_settings.key_alias_pattern - value={value!r}: must be a string" + ) + try: + re.compile(value) + except re.error as e: + raise ValueError(f"Invalid regex set for litellm_settings.key_alias_pattern - value={value}: {e}") from e + return value + + +def _key_alias_rule() -> tuple[re.Pattern[str], str] | None: + if litellm.key_alias_pattern is not None: + return ( + re.compile(litellm.key_alias_pattern), + f"Invalid key_alias format. Must be at most {_KEY_ALIAS_MAX_LENGTH} characters and match the configured" + f" key_alias_pattern: {litellm.key_alias_pattern}", + ) + if litellm.enable_key_alias_format_validation: + return (_KEY_ALIAS_PATTERN, _KEY_ALIAS_PATTERN_MESSAGE) + return None def _validate_key_alias_format(key_alias: str | None) -> None: """ Validate the format of the key_alias. - A baseline validation always runs, regardless of - ``litellm.enable_key_alias_format_validation``. - - The remaining charset/length rules are gated behind - ``litellm.enable_key_alias_format_validation`` (default **False**). When disabled, - only the baseline validation above is performed, so existing workflows are not - broken. - - Rules (when enabled): - - None is OK (no alias). - - Otherwise must be 2–255 chars - - start/end with alphanumeric - - only allow a-zA-Z0-9_-/.@ + Path traversal and control characters are always rejected. The alias then has to + stay within ``_KEY_ALIAS_MAX_LENGTH`` and fully match ``litellm.key_alias_pattern`` + when one is configured, else the built-in pattern when + ``litellm.enable_key_alias_format_validation`` is on, else nothing more is checked + so existing workflows are not broken. """ if key_alias is None: return @@ -7623,12 +7645,14 @@ def _validate_key_alias_format(key_alias: str | None) -> None: code=400, ) - if not litellm.enable_key_alias_format_validation: + rule: Final = _key_alias_rule() + if rule is None: return - if not _KEY_ALIAS_PATTERN.match(key_alias): + pattern, message = rule + if len(key_alias) > _KEY_ALIAS_MAX_LENGTH or pattern.fullmatch(key_alias) is None: raise ProxyException( - message="Invalid key_alias format. Must be 2-255 characters, start/end with alphanumeric, and only contain a-zA-Z0-9_-/.@.", + message=message, type=ProxyErrorTypes.bad_request_error, param="key_alias", code=400, diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py index 10110dd4f76..acb36fc4a59 100644 --- a/litellm/proxy/proxy_server.py +++ b/litellm/proxy/proxy_server.py @@ -596,6 +596,7 @@ from litellm.proxy.management_endpoints.key_management_endpoints import ( delete_verification_tokens, duration_in_seconds, generate_key_helper_fn, + parse_key_alias_pattern, ) from litellm.proxy.management_endpoints.key_management_endpoints import ( router as key_management_router, @@ -6266,6 +6267,8 @@ class ProxyConfig: litellm.upperbound_key_generate_params = LiteLLM_UpperboundKeyGenerateParams(**value) else: raise Exception(f"Invalid value set for upperbound_key_generate_params - value={value}") + elif key == "key_alias_pattern": + litellm.key_alias_pattern = parse_key_alias_pattern(value) elif key == "json_logs" and value is True: litellm.json_logs = True litellm._turn_on_json() diff --git a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py index c539a10e1e2..cd929dfeeb3 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py +++ b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py @@ -3089,6 +3089,50 @@ async def test_update_key_by_alias_only(monkeypatch): assert result["key"] == hashed_token +@pytest.mark.asyncio +async def test_update_key_changed_alias_must_match_key_alias_pattern(monkeypatch: pytest.MonkeyPatch) -> None: + from litellm.proxy.management_endpoints.key_management_endpoints import ( + update_key_fn, + ) + + monkeypatch.setattr(litellm, "key_alias_pattern", r"^[a-z0-9]+(-[a-z0-9]+)*$") + hashed_token = "0d62f396c1317066f55a96086517047c737087c61eb2bf016b72e6298927b15b" + key_in_db = LiteLLM_VerificationToken(token=hashed_token, key_alias="Legacy Alias", user_id="test-user") + + mock_prisma_client = AsyncMock() + mock_prisma_client.db.litellm_verificationtoken.find_unique = AsyncMock(return_value=key_in_db) + mock_prisma_client.db.litellm_verificationtoken.find_many = AsyncMock(return_value=[key_in_db]) + mock_prisma_client.db.litellm_verificationtoken.find_first = AsyncMock(return_value=None) + mock_prisma_client.update_data = AsyncMock(return_value={"data": {"max_budget": 50.0}}) + _setup_update_key_mocks(monkeypatch, mock_prisma_client) + user_api_key_dict = UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, api_key="sk-admin", user_id="admin-user" + ) + + with pytest.raises(ProxyException) as exc_info: + await update_key_fn( + request=MagicMock(), + data=UpdateKeyRequest(key=hashed_token, key_alias="Prod Key"), + user_api_key_dict=user_api_key_dict, + litellm_changed_by=None, + ) + assert str(exc_info.value.code) == "400" + assert "key_alias_pattern" in str(exc_info.value.message) + mock_prisma_client.update_data.assert_not_awaited() + + with patch( + "litellm.proxy.management_endpoints.key_management_endpoints._delete_cache_key_object", + return_value=None, + ): + await update_key_fn( + request=MagicMock(), + data=UpdateKeyRequest(key=hashed_token, key_alias="Legacy Alias", max_budget=50.0), + user_api_key_dict=user_api_key_dict, + litellm_changed_by=None, + ) + mock_prisma_client.update_data.assert_awaited_once() + + @pytest.mark.asyncio async def test_update_key_by_alias_not_found_returns_404(monkeypatch): """ @@ -10562,6 +10606,10 @@ class TestValidateKeyAliasFormat: def reset_key_alias_flag(self, monkeypatch: pytest.MonkeyPatch) -> None: monkeypatch.setattr(litellm, "enable_key_alias_format_validation", False) + @pytest.fixture(autouse=True) + def reset_key_alias_pattern(self, monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr(litellm, "key_alias_pattern", None) + def test_validation_skipped_when_flag_disabled(self): """When enable_key_alias_format_validation is False (default), no charset/length validation occurs.""" from litellm.proxy.management_endpoints.key_management_endpoints import ( @@ -10644,6 +10692,67 @@ class TestValidateKeyAliasFormat: assert str(exc.value.code) == "400" assert "Invalid key_alias format" in str(exc.value.message) + def test_configured_pattern_applies_with_flag_off(self, monkeypatch: pytest.MonkeyPatch) -> None: + from litellm.proxy.management_endpoints.key_management_endpoints import ( + _validate_key_alias_format, + ) + + monkeypatch.setattr(litellm, "key_alias_pattern", r"^[a-z0-9]+(-[a-z0-9]+)*$") + with pytest.raises(ProxyException) as exc: + _validate_key_alias_format("Prod Key") + assert str(exc.value.code) == "400" + assert exc.value.param == "key_alias" + assert "key_alias_pattern" in str(exc.value.message) + assert r"^[a-z0-9]+(-[a-z0-9]+)*$" in str(exc.value.message) + assert _validate_key_alias_format("prod-key-001") is None + assert _validate_key_alias_format(None) is None + + def test_configured_pattern_must_match_the_whole_alias(self, monkeypatch: pytest.MonkeyPatch) -> None: + from litellm.proxy.management_endpoints.key_management_endpoints import ( + _validate_key_alias_format, + ) + + monkeypatch.setattr(litellm, "key_alias_pattern", r"team-[a-z]+") + _validate_key_alias_format("team-search") + for partial_match in ("team-search-2", "xteam-search"): + with pytest.raises(ProxyException): + _validate_key_alias_format(partial_match) + + def test_configured_pattern_replaces_the_builtin_rule(self, monkeypatch: pytest.MonkeyPatch) -> None: + from litellm.proxy.management_endpoints.key_management_endpoints import ( + _validate_key_alias_format, + ) + + monkeypatch.setattr(litellm, "enable_key_alias_format_validation", True) + monkeypatch.setattr(litellm, "key_alias_pattern", r"^[a-z ]+$") + _validate_key_alias_format("alias with spaces") + with pytest.raises(ProxyException) as exc: + _validate_key_alias_format("Uppercase") + assert "key_alias_pattern" in str(exc.value.message) + + def test_configured_pattern_keeps_the_baseline_safety_check(self, monkeypatch: pytest.MonkeyPatch) -> None: + from litellm.proxy.management_endpoints.key_management_endpoints import ( + _validate_key_alias_format, + ) + + monkeypatch.setattr(litellm, "key_alias_pattern", r".*") + with pytest.raises(ProxyException) as exc: + _validate_key_alias_format("../../../other-app/creds") + assert str(exc.value.code) == "400" + assert "key_alias_pattern" not in str(exc.value.message) + + def test_configured_pattern_bounds_the_alias_length(self, monkeypatch: pytest.MonkeyPatch) -> None: + from litellm.proxy.management_endpoints.key_management_endpoints import ( + _validate_key_alias_format, + ) + + monkeypatch.setattr(litellm, "key_alias_pattern", r"^[a-z]+$") + _validate_key_alias_format("a" * 255) + with pytest.raises(ProxyException) as exc: + _validate_key_alias_format("a" * 256) + assert str(exc.value.code) == "400" + assert "at most 255 characters" in str(exc.value.message) + @pytest.mark.asyncio async def test_check_org_key_limits_on_update_within_bounds(): @@ -12734,6 +12843,55 @@ async def test_execute_virtual_key_regeneration_rejects_over_limit_duration(monk assert mock_prisma_client.db.litellm_verificationtoken.update.await_count == 0 +@pytest.mark.asyncio +async def test_execute_virtual_key_regeneration_changed_alias_must_match_key_alias_pattern( + monkeypatch: pytest.MonkeyPatch, +) -> None: + from litellm.proxy._types import RegenerateKeyRequest + from litellm.proxy.management_endpoints.key_management_endpoints import ( + _execute_virtual_key_regeneration, + ) + + monkeypatch.setattr(litellm, "key_alias_pattern", r"^[a-z0-9]+(-[a-z0-9]+)*$") + mock_prisma_client = _make_regenerate_mock_prisma() + + with ( + patch( + "litellm.proxy.management_endpoints.key_management_endpoints.get_new_token", + new_callable=AsyncMock, + return_value="sk-newtoken1234ab12", + ), + patch( + "litellm.proxy.management_endpoints.key_management_endpoints._insert_deprecated_key", + new_callable=AsyncMock, + ), + patch( + "litellm.proxy.management_endpoints.key_management_endpoints._persist_deleted_verification_tokens", + new_callable=AsyncMock, + ), + patch( + "litellm.proxy.management_endpoints.key_management_endpoints._delete_cache_key_object", + new_callable=AsyncMock, + ), + ): + with pytest.raises(ProxyException) as exc_info: + await _execute_virtual_key_regeneration( + prisma_client=mock_prisma_client, + key_in_db=_make_regenerate_existing_key(), + hashed_api_key="abc123", + key="abc123", + data=RegenerateKeyRequest(key_alias="Regenerated Key"), + user_api_key_dict=_make_regenerate_user_api_key_dict(), + litellm_changed_by=None, + user_api_key_cache=MagicMock(), + proxy_logging_obj=MagicMock(), + ) + assert str(exc_info.value.code) == "400" + assert exc_info.value.param == "key_alias" + assert r"^[a-z0-9]+(-[a-z0-9]+)*$" in str(exc_info.value.message) + assert mock_prisma_client.db.litellm_verificationtoken.update.await_count == 0 + + @pytest.mark.asyncio async def test_execute_virtual_key_regeneration_allows_within_limit_duration(monkeypatch): """Regenerate must accept durations within upperbound_key_generate_params.duration.""" diff --git a/tests/test_litellm/proxy/test_proxy_server.py b/tests/test_litellm/proxy/test_proxy_server.py index 32b89885ac2..89fd9c5c9d4 100644 --- a/tests/test_litellm/proxy/test_proxy_server.py +++ b/tests/test_litellm/proxy/test_proxy_server.py @@ -3555,6 +3555,23 @@ async def test_load_config_rejects_malformed_role_permissions(tmp_path): await ProxyConfig().load_config(router=MagicMock(), config_file_path=str(config_file)) +@pytest.mark.asyncio +async def test_load_config_compiles_key_alias_pattern_at_startup(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None: + from litellm.proxy.proxy_server import ProxyConfig + + monkeypatch.setattr(litellm, "key_alias_pattern", None) + config_file: Final = tmp_path / "config.yaml" + + config_file.write_text(yaml.dump({"model_list": [], "litellm_settings": {"key_alias_pattern": "^team-("}})) + with pytest.raises(Exception, match=r"litellm_settings\.key_alias_pattern"): + await ProxyConfig().load_config(router=MagicMock(), config_file_path=str(config_file)) + assert litellm.key_alias_pattern is None + + config_file.write_text(yaml.dump({"model_list": [], "litellm_settings": {"key_alias_pattern": "^team-[a-z]+$"}})) + await ProxyConfig().load_config(router=MagicMock(), config_file_path=str(config_file)) + assert litellm.key_alias_pattern == "^team-[a-z]+$" + + def test_os_environ_resolution_leaves_the_config_layer_holding_the_reference(monkeypatch): from litellm.proxy.proxy_server import ProxyConfig From 65e42526d6a2dd7875e3f8618b7dd2d2d387028c Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Tue, 22 Sep 2026 14:58:42 -0700 Subject: [PATCH 044/101] test(proxy): make two proxy-infra tests independent of sibling-test state (#42581) * test(proxy): make two proxy-infra tests independent of sibling-test state Both tests read process-global state that another module in the same xdist worker can change, so they passed or failed on shard scheduling rather than on the behaviour they assert. test_gateway_plus_backend_covers_full_app checked allowlist coverage against the live route table. gateway/main.py trims routes once, inside the lifespan, so it only ever sees what is registered at startup; a lazy feature appends its router on demand afterwards and is never filtered. Those routes cannot be dropped on the floor, but they do enter the assertion the moment a sibling test warms the feature, and 110 of them sit in neither allowlist. Subtract exactly the lazy features this process has loaded, which leaves the assertion at full strength for every eagerly registered route. test_real_proxy_child_auth_privacy_and_body_policy pins prisma_client to a bare object(). litellm.max_budget is a module global that nothing restores between tests; once a sibling leaves it above zero, user_api_key_auth takes the global-spend branch, dereferences prisma_client.db, and the AttributeError surfaces as HTTP 401. Pin max_budget next to the other globals the test already controls. * test(proxy): measure allowlist coverage in a pristine interpreter The previous revision subtracted paths matching a loaded lazy feature's prefixes. Those prefixes are broad enough to swallow eagerly registered routes: 31 of them, including /openai/deployments/*, /access_group/*, /cursor/* and /mcp, which would have made a real allowlist regression invisible. Run the coverage check in a fresh interpreter instead. No lazy feature is loaded there, so the route table is exactly the one gateway/main.py's lifespan trim sees, and nothing has to be subtracted for the result to be deterministic. The probe also reports the lazy modules it loaded and its route count, so an empty uncovered set cannot pass vacuously. Drop _component_paths and the four allowlist constants it used; the probe reproduces the predicate in the child process. --- .../proxy/test_component_allowlists.py | 94 ++++++++++++------- 1 file changed, 59 insertions(+), 35 deletions(-) diff --git a/tests/test_litellm/proxy/test_component_allowlists.py b/tests/test_litellm/proxy/test_component_allowlists.py index 3073908fa54..3641a2d9be9 100644 --- a/tests/test_litellm/proxy/test_component_allowlists.py +++ b/tests/test_litellm/proxy/test_component_allowlists.py @@ -23,8 +23,10 @@ import (which raises on a non-postgres ``DATABASE_URL`` scheme and can mint an RDS IAM token when ``IAM_TOKEN_DB_AUTH`` is set). """ +import json import os import sys +from typing import Final # Importing ``litellm.proxy.proxy_server`` runs its module-level setup, which # reads ``DATABASE_URL`` (Prisma) and ``LITELLM_MASTER_KEY``. Tier-zero CI @@ -49,17 +51,10 @@ _REPO_ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", if _REPO_ROOT not in sys.path: sys.path.insert(0, _REPO_ROOT) -from backend.routes.allowlist import ( - BACKEND_EXACT_PATHS, - BACKEND_MOUNT_PATHS, - BACKEND_PATH_PREFIXES, -) -from gateway.routes.allowlist import ( - GATEWAY_EXACT_PATHS, - GATEWAY_MOUNT_PATHS, - GATEWAY_PATH_PREFIXES, -) +from backend.routes.allowlist import BACKEND_MOUNT_PATHS +from gateway.routes.allowlist import GATEWAY_MOUNT_PATHS from litellm.proxy.proxy_server import app +from tests.test_litellm_rust.support.child_interpreter import run_child_interpreter for _key, _previous in _PRE_EXISTING_ENV.items(): if _previous is None: @@ -87,40 +82,69 @@ for _key, _previous in _PRE_DB_ENV.items(): os.environ[_key] = _previous -def _component_paths(routes, exact_paths, path_prefixes) -> set[str]: - """Reproduce ``gateway.main._is_gateway_route`` / ``backend.main._is_backend_route``.""" - out: set[str] = set() - for route in routes: - if isinstance(route, Mount): - continue - path = getattr(route, "path", None) - if path is None: - continue - if path in exact_paths or any(path.startswith(p) for p in path_prefixes): - out.add(path) - return out +_COVERAGE_PROBE: Final = """ +import json, os, sys +sys.path.insert(0, os.environ["LITELLM_COMPONENT_ALLOWLIST_REPO_ROOT"]) +from fastapi.routing import Mount +from backend.routes.allowlist import BACKEND_EXACT_PATHS, BACKEND_PATH_PREFIXES +from gateway.routes.allowlist import GATEWAY_EXACT_PATHS, GATEWAY_PATH_PREFIXES +from litellm.proxy._lazy_features import loaded_lazy_modules +from litellm.proxy.proxy_server import app + +all_paths = { + r.path for r in app.router.routes + if not isinstance(r, Mount) and getattr(r, "path", None) is not None +} + + +def covered(exact, prefixes): + return {p for p in all_paths if p in exact or any(p.startswith(x) for x in prefixes)} + + +json.dump({ + "lazy_loaded": sorted(loaded_lazy_modules(app)), + "route_count": len(all_paths), + "uncovered": sorted(all_paths - ( + covered(GATEWAY_EXACT_PATHS, GATEWAY_PATH_PREFIXES) + | covered(BACKEND_EXACT_PATHS, BACKEND_PATH_PREFIXES) + )), +}, sys.stdout) +""" def test_gateway_plus_backend_covers_full_app(): - """Every route on the proxy app must be served by gateway or backend.""" - all_paths = { - getattr(r, "path") - for r in app.router.routes - if not isinstance(r, Mount) and getattr(r, "path", None) is not None - } - gateway_paths = _component_paths( - app.router.routes, GATEWAY_EXACT_PATHS, GATEWAY_PATH_PREFIXES + """Every route on the proxy app must be served by gateway or backend. + + ``gateway.main`` and ``backend.main`` trim the route table once, inside the + lifespan, so the set this has to cover is the one registered at startup. A + lazy feature appends its router on demand, after that trim, and whether a + sibling test in the same xdist worker has triggered one is not something + this test can control. Measuring in a fresh interpreter is what makes the + route table deterministic; nothing is subtracted, so every route the trim + will actually see stays in the assertion. + """ + env: Final = {**os.environ, "LITELLM_COMPONENT_ALLOWLIST_REPO_ROOT": _REPO_ROOT} + for key, value in _THROWAWAY_ENV.items(): + env.setdefault(key, value) + + probe: Final = run_child_interpreter(_COVERAGE_PROBE, env=env, timeout=90) + assert probe.returncode == 0, f"route probe failed:\n{probe.stderr}" + report: Final = json.loads(probe.stdout) + + assert not report["lazy_loaded"], ( + "route probe was not pristine; it loaded lazy features " + f"{report['lazy_loaded']}, so its route table is not the startup one" ) - backend_paths = _component_paths( - app.router.routes, BACKEND_EXACT_PATHS, BACKEND_PATH_PREFIXES + assert report["route_count"] > 100, ( + f"route probe only saw {report['route_count']} routes, so an empty " + "uncovered set would not mean anything" ) - uncovered = all_paths - (gateway_paths | backend_paths) - + uncovered: Final = report["uncovered"] assert not uncovered, ( f"{len(uncovered)} route(s) are not exposed on either component. " f"Update gateway/routes/allowlist.py or backend/routes/allowlist.py to cover:\n " - + "\n ".join(sorted(uncovered)) + + "\n ".join(uncovered) ) From 0d6ee3dc5a85e6c49caa2eb41660fc5c33cdfc7d Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 14:59:26 -0700 Subject: [PATCH 045/101] test: count a zombie grandchild as gone in the migrate deploy timeout test (#42570) * test: count a zombie grandchild as gone in the migrate deploy timeout test A SIGKILLed grandchild whose parent died in the same killpg reparents to PID 1 or the nearest subreaper and stays a zombie until reaped, and signal 0 still succeeds on a zombie, so the timeout test read it as alive wherever PID 1 is slow to reap or never does. The sibling test in tests/test_litellm/proxy/db already handled that; both now share one process_is_gone helper that reads the /proc state and reaps its own children, with unit tests for the live, reaped, unreaped, and foreign zombie shapes. * test: move the pre-commit interrupt test onto the shared zombie-aware liveness helper --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- tests/_process_helpers.py | 57 ++++++++++++++++ .../test_prisma_toolchain.py | 18 ++--- tests/test_litellm/proxy/db/conftest.py | 32 ++------- tests/test_litellm/test_pre_commit_lint.py | 12 +--- tests/test_litellm/test_process_helpers.py | 65 +++++++++++++++++++ 5 files changed, 133 insertions(+), 51 deletions(-) create mode 100644 tests/_process_helpers.py create mode 100644 tests/test_litellm/test_process_helpers.py diff --git a/tests/_process_helpers.py b/tests/_process_helpers.py new file mode 100644 index 00000000000..9f80c563fa9 --- /dev/null +++ b/tests/_process_helpers.py @@ -0,0 +1,57 @@ +"""Whether a killed process is really gone, for tests that kill whole process trees. + +A SIGKILLed grandchild whose parent died in the same ``killpg`` reparents to the +nearest subreaper or PID 1, and until that ancestor reaps it the pid is a zombie +that ``os.kill(pid, 0)`` still accepts. Reading its ``/proc`` state, and reaping +it when it landed on this process, keeps a runner that is slow to reap, or never +does, from turning a dead process into a failed assertion. The reap comes after +the liveness read so a child seen dying between the two is still collected on +the next poll instead of staying this process's own zombie. +""" + +import os +import time +from pathlib import Path +from typing import Final + +POLL_INTERVAL_S: Final = 0.05 + + +def _exists(pid: int) -> bool: + try: + os.kill(pid, 0) + except ProcessLookupError: + return False + return True + + +def _is_zombie(pid: int) -> bool: + try: + stat: Final = Path(f"/proc/{pid}/stat").read_text() + except OSError: + return False + return stat.rpartition(")")[2].split()[0] == "Z" + + +def _reap_if_ours(pid: int) -> None: + if os.name == "nt": + return + try: + os.waitpid(pid, os.WNOHANG) + except ChildProcessError: + pass + + +def _gone_now(pid: int) -> bool: + dead: Final = not _exists(pid) or _is_zombie(pid) + _reap_if_ours(pid) + return dead + + +def process_is_gone(pid: int, within_seconds: float) -> bool: + deadline: Final = time.monotonic() + within_seconds + while time.monotonic() < deadline: + if _gone_now(pid): + return True + time.sleep(POLL_INTERVAL_S) + return False diff --git a/tests/proxy_migration_tests/test_prisma_toolchain.py b/tests/proxy_migration_tests/test_prisma_toolchain.py index 4e2274cc582..556c680a84a 100644 --- a/tests/proxy_migration_tests/test_prisma_toolchain.py +++ b/tests/proxy_migration_tests/test_prisma_toolchain.py @@ -25,7 +25,6 @@ from collections.abc import Callable from pathlib import Path import pytest - from litellm_proxy_extras.prisma_toolchain import ( DEFAULT_PRISMA_COMMAND_TIMEOUT, DEFAULT_PRISMA_MIGRATE_DEPLOY_TIMEOUT, @@ -36,14 +35,16 @@ from litellm_proxy_extras.prisma_toolchain import ( heal_incomplete_nodeenv_cache, node_binary_path, prisma_bootstrap_timeout, - prisma_command_timeout, prisma_cli_available, + prisma_command_timeout, prisma_migrate_deploy_timeout, resolve_prisma_argv, run_prisma, ) from litellm_proxy_extras.utils import ProxyExtrasDBManager +from tests._process_helpers import process_is_gone + REPO_ROOT = Path(__file__).resolve().parents[2] PROXY_EXTRAS = REPO_ROOT / "litellm-proxy-extras" / "litellm_proxy_extras" @@ -280,17 +281,6 @@ def test_migrate_deploy_stops_at_its_own_timeout( assert elapsed < 30 -def _process_is_gone(pid: int, within_seconds: float) -> bool: - deadline = time.monotonic() + within_seconds - while time.monotonic() < deadline: - try: - os.kill(pid, 0) - except ProcessLookupError: - return True - time.sleep(0.05) - return False - - def test_a_timed_out_migrate_deploy_takes_its_process_tree_with_it( toolchain_env: tuple[Path, Path], monkeypatch: pytest.MonkeyPatch, tmp_path: Path ) -> None: @@ -309,7 +299,7 @@ def test_a_timed_out_migrate_deploy_takes_its_process_tree_with_it( grandchild_pid = int(pidfile.read_text()) try: assert len(_deploy_calls(log_path)) == 2 - assert _process_is_gone(grandchild_pid, within_seconds=5) + assert process_is_gone(grandchild_pid, within_seconds=5) finally: try: os.kill(grandchild_pid, signal.SIGKILL) diff --git a/tests/test_litellm/proxy/db/conftest.py b/tests/test_litellm/proxy/db/conftest.py index bcb7794a20d..4d775142dd5 100644 --- a/tests/test_litellm/proxy/db/conftest.py +++ b/tests/test_litellm/proxy/db/conftest.py @@ -2,14 +2,15 @@ import json import os import signal import sys -import time from collections.abc import Generator from dataclasses import dataclass from pathlib import Path -from typing import Final, Optional +from typing import Optional import pytest +from tests._process_helpers import process_is_gone + DB_ENV_KEYS = ( "IAM_TOKEN_DB_AUTH", "AZURE_POSTGRESQL_AUTH", @@ -35,14 +36,6 @@ DB_ENV_KEYS = ( _db_env_snapshot_key = pytest.StashKey[dict[str, Optional[str]]]() -def _is_zombie(pid: int) -> bool: - try: - stat: Final = Path(f"/proc/{pid}/stat").read_text() - except OSError: - return False - return stat.rpartition(")")[2].split()[0] == "Z" - - def _db_env_snapshot() -> dict[str, Optional[str]]: return {key: os.environ.get(key) for key in DB_ENV_KEYS} @@ -130,24 +123,7 @@ class FakePrismaCli: return [json.loads(line) for line in self.calls_file.read_text().splitlines()] def grandchild_is_gone(self, within_seconds: float) -> bool: - pid: Final = int(self.grandchild_pidfile.read_text()) - deadline: Final = time.monotonic() + within_seconds - while time.monotonic() < deadline: - if os.name != "nt": - try: - reaped_pid, _ = os.waitpid(pid, os.WNOHANG) - if reaped_pid == pid: - return True - except ChildProcessError: - pass - try: - os.kill(pid, 0) - except ProcessLookupError: - return True - if _is_zombie(pid): - return True - time.sleep(0.05) - return False + return process_is_gone(int(self.grandchild_pidfile.read_text()), within_seconds=within_seconds) @pytest.fixture diff --git a/tests/test_litellm/test_pre_commit_lint.py b/tests/test_litellm/test_pre_commit_lint.py index e12da0833dc..2d7fa897536 100644 --- a/tests/test_litellm/test_pre_commit_lint.py +++ b/tests/test_litellm/test_pre_commit_lint.py @@ -9,6 +9,8 @@ from pathlib import Path import pytest +from tests._process_helpers import process_is_gone + ROOT = Path(__file__).resolve().parents[2] SCRIPT = ROOT / "scripts" / "pre_commit_lint.sh" WHOLE_TREE_RUFF = "run --no-sync ruff check --config ruff-tests.toml tests" @@ -343,14 +345,6 @@ def _wait_until(predicate: Callable[[], bool], timeout_seconds: float) -> bool: return predicate() -def _pid_gone(pid: int) -> bool: - try: - os.kill(pid, 0) - except ProcessLookupError: - return True - return False - - def test_interrupt_kills_background_jobs_and_removes_logs(tmp_path: Path) -> None: repo, bin_dir = _sandbox(tmp_path) hang_dir = tmp_path / "hang" @@ -372,7 +366,7 @@ def test_interrupt_kills_background_jobs_and_removes_logs(tmp_path: Path) -> Non os.killpg(proc.pid, signal.SIGINT) assert proc.wait(timeout=10) != 0 make_pid = int((hang_dir / "make.pid").read_text()) - assert _wait_until(lambda: _pid_gone(make_pid), 5) + assert process_is_gone(make_pid, within_seconds=5) assert _wait_until(lambda: not any(tmp_dir.iterdir()), 5), list(tmp_dir.iterdir()) finally: with suppress(ProcessLookupError, PermissionError): diff --git a/tests/test_litellm/test_process_helpers.py b/tests/test_litellm/test_process_helpers.py new file mode 100644 index 00000000000..00d4d07d71f --- /dev/null +++ b/tests/test_litellm/test_process_helpers.py @@ -0,0 +1,65 @@ +"""``process_is_gone`` has to say gone for every shape a killed process can take, and never for a live one.""" + +import os +import signal +import subprocess +import sys +from pathlib import Path +from typing import Final + +import pytest + +from tests._process_helpers import process_is_gone + +SLEEP_FOREVER: Final = (sys.executable, "-I", "-c", "import time; time.sleep(600)") + +LEAVE_A_ZOMBIE_BEHIND: Final = """ +import os, signal, subprocess, sys, time +grandchild = subprocess.Popen([sys.executable, "-c", "import time; time.sleep(600)"]) +os.kill(grandchild.pid, signal.SIGKILL) +while open(f"/proc/{grandchild.pid}/stat").read().rpartition(")")[2].split()[0] != "Z": + time.sleep(0.01) +print(grandchild.pid, flush=True) +time.sleep(600) +""" + + +def test_a_live_process_is_not_gone() -> None: + child: Final = subprocess.Popen(SLEEP_FOREVER) + try: + assert not process_is_gone(child.pid, within_seconds=0.3) + finally: + child.kill() + child.wait() + + +def test_a_reaped_child_is_gone() -> None: + child: Final = subprocess.Popen(SLEEP_FOREVER) + child.kill() + child.wait() + assert process_is_gone(child.pid, within_seconds=1) + + +@pytest.mark.skipif(os.name == "nt", reason="zombies are a POSIX thing") +def test_an_unreaped_child_is_reaped_and_gone() -> None: + child: Final = subprocess.Popen(SLEEP_FOREVER) + os.kill(child.pid, signal.SIGKILL) + assert process_is_gone(child.pid, within_seconds=1) + with pytest.raises(ChildProcessError): + os.waitpid(child.pid, os.WNOHANG) + + +@pytest.mark.skipif(not Path("/proc").is_dir(), reason="needs procfs to see a zombie that is not our child") +def test_a_zombie_left_by_another_process_is_gone() -> None: + zombie_factory: Final = subprocess.Popen( + [sys.executable, "-I", "-c", LEAVE_A_ZOMBIE_BEHIND], stdout=subprocess.PIPE, text=True + ) + try: + assert zombie_factory.stdout is not None + zombie_pid: Final = int(zombie_factory.stdout.readline()) + with pytest.raises(ChildProcessError): + os.waitpid(zombie_pid, os.WNOHANG) + assert process_is_gone(zombie_pid, within_seconds=1) + finally: + zombie_factory.kill() + zombie_factory.wait() From b9fcfb26d01aaba21316ff9cb2ab1f4b2abf0fe4 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 15:13:37 -0700 Subject: [PATCH 046/101] test(e2e): run the memory cell alone on the shared stack (#42518) * test(e2e): run the memory cell alone on the shared stack * test(e2e): hold the stack lock for every collected test, marker or not * test(e2e): prove the stack lock's reader sharing and writer preference across processes --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- tests/e2e/AGENTS.md | 2 +- tests/e2e/conftest.py | 20 ++- tests/e2e/pytest.ini | 1 + .../e2e/router/test_reliability_memory_e2e.py | 2 +- tests/e2e/stack_lock.py | 45 +++++++ tests/e2e/test_stack_lock.py | 117 ++++++++++++++++++ 6 files changed, 179 insertions(+), 8 deletions(-) create mode 100644 tests/e2e/stack_lock.py create mode 100644 tests/e2e/test_stack_lock.py diff --git a/tests/e2e/AGENTS.md b/tests/e2e/AGENTS.md index 6212a172fe3..d948c6fd1d9 100644 --- a/tests/e2e/AGENTS.md +++ b/tests/e2e/AGENTS.md @@ -97,7 +97,7 @@ Each suite provides its own `client` fixture (see `llm_translation/passthrough_c Request and response bodies are typed pydantic models in `models.py`; only the fields a test reads are modelled, and nothing passes raw dicts. Outcomes come back as a `Result[R]` tagged union (`Success`, `NetworkError`, `UnauthorizedError`, `RateLimitedError`, `ValidationError`, `UnknownApiError`). Handle them with `match`, or call `unwrap(...)` when a non-success should fail the test. The harness hard-fails and never skips: a test marked `e2e` fails when no proxy answers its liveness probe, and once a request reaches the proxy any wrong behavior is likewise a hard failure, so a missing proxy turns the run red instead of being mistaken for a pass -Mark live tests with `@pytest.mark.e2e` (on the class or the module). Use `scoped_key` for a fresh all-models key that auto-deletes, `resources` when you need to create and tear down more than a key, and `unique_marker()` from `e2e_config` to keep prompts, tags, and customer ids from colliding across concurrent runs and the shared response cache +Mark live tests with `@pytest.mark.e2e` (on the class or the module). Add `@pytest.mark.quiet_stack` to a test that measures the proxy itself (RSS, latency): the shared stack lock in `stack_lock.py` then runs it while no other test on the host is hitting the stack, marked or not, so the reading depends only on the test's own traffic. Use `scoped_key` for a fresh all-models key that auto-deletes, `resources` when you need to create and tear down more than a key, and `unique_marker()` from `e2e_config` to keep prompts, tags, and customer ids from colliding across concurrent runs and the shared response cache ## Record and replay fixtures diff --git a/tests/e2e/conftest.py b/tests/e2e/conftest.py index f1f94f2d2b3..f4de4ac01ba 100644 --- a/tests/e2e/conftest.py +++ b/tests/e2e/conftest.py @@ -51,6 +51,7 @@ from models import TeamNewBody, UserNewBody, UserNewResponse from provider_cache_routing import LIVE_PROVIDER_REQUIRED from provider_edge import replay_leftover_error from proxy_client import ProxyClient, build_proxy_client +from stack_lock import stack_lock _E2E_TEST_RAN = pytest.StashKey[bool]() _CALL_PASSED = pytest.StashKey[bool]() @@ -148,6 +149,11 @@ def pytest_configure(config: pytest.Config) -> None: "redis_chaos: load test that pauses the proxy's Redis outright mid-run; needs a proxy booted from " "gateway/redis_chaos_ci_config.yml on the same host, and is deselected unless E2E_REDIS_CHAOS is set", ) + config.addinivalue_line( + "markers", + "quiet_stack: measures the proxy itself, so it runs while no other test on this host is hitting the stack; " + "every other test waits for it to finish", + ) config.addinivalue_line( "markers", "mcp_oauth_live: real Linear OAuth consent via a captured browser session; deselected unless " @@ -172,9 +178,7 @@ def pytest_sessionstart(session: pytest.Session) -> None: """Abort before collection when E2E_FIXTURE_MODE can never work: an unknown mode value, or replay against a missing, unreadable, or stale bundle (the stale message names the bundle's age). Live and record modes pass through.""" - reason = fixture_mode_collection_error( - FIXTURE_MODE_RAW, FIXTURE_DIR, now=datetime.now(timezone.utc) - ) + reason = fixture_mode_collection_error(FIXTURE_MODE_RAW, FIXTURE_DIR, now=datetime.now(timezone.utc)) if reason is not None: raise pytest.UsageError(reason) @@ -267,6 +271,12 @@ def _proxy_fail_reason() -> str | None: return None +@pytest.hookimpl(wrapper=True) +def pytest_runtest_protocol(item: pytest.Item, nextitem: pytest.Item | None) -> Generator[None, object, object]: + with stack_lock(exclusive=item.get_closest_marker("quiet_stack") is not None): + return (yield) + + @pytest.hookimpl(tryfirst=True) def pytest_runtest_setup(item: pytest.Item) -> None: """Hard-fail `e2e`-marked tests unless a proxy answers its liveness probe. @@ -326,9 +336,7 @@ def pytest_runtest_teardown(item: pytest.Item) -> Generator[None, None, None]: LIVE_PROVIDER_REQUIRED.set(False) if not item.stash.get(_CALL_PASSED, False): return result - reason = replay_leftover_error( - mode_raw=FIXTURE_MODE_RAW, bundle_dir=FIXTURE_DIR, test_key=item.nodeid - ) + reason = replay_leftover_error(mode_raw=FIXTURE_MODE_RAW, bundle_dir=FIXTURE_DIR, test_key=item.nodeid) if reason is not None: pytest.fail(reason) return result diff --git a/tests/e2e/pytest.ini b/tests/e2e/pytest.ini index a77459d3683..4866511af3f 100644 --- a/tests/e2e/pytest.ini +++ b/tests/e2e/pytest.ini @@ -12,6 +12,7 @@ markers = prompt_caching_stack: needs a proxy running with router_settings.optional_pre_call_checks including prompt_caching; deselected unless E2E_PROMPT_CACHING_STACK is set cli_determinism: drives the real claude CLI for several seconds; deselected unless E2E_CLI_DETERMINISM is set redis_chaos: load test that pauses the proxy's Redis outright mid-run; needs a proxy booted from gateway/redis_chaos_ci_config.yml on the same host, and is deselected unless E2E_REDIS_CHAOS is set + quiet_stack: measures the proxy itself, so it runs while no other test on this host is hitting the stack; every other test waits for it to finish mcp_oauth_live: real Linear OAuth consent via a captured browser session; deselected unless E2E_MCP_OAUTH_LIVE is set provider_edge_host: routes provider traffic through the pytest host's edge in every fixture mode, so the gateway must reach the pytest host; deselected unless E2E_PROVIDER_EDGE_HOST_REACHABLE is set otel_v2: needs a proxy running with LITELLM_OTEL_V2=true; deselected unless E2E_OTEL_V2 is set diff --git a/tests/e2e/router/test_reliability_memory_e2e.py b/tests/e2e/router/test_reliability_memory_e2e.py index 2568434a08f..77d3a68cae5 100644 --- a/tests/e2e/router/test_reliability_memory_e2e.py +++ b/tests/e2e/router/test_reliability_memory_e2e.py @@ -86,7 +86,7 @@ from models import ChatMessage, RouterSettingsOverride, SpendLogRow from proxy_client import ProxyClient from reliability_support import chat_override, create_never_benched_refusing_deployment -pytestmark = pytest.mark.e2e +pytestmark = [pytest.mark.e2e, pytest.mark.quiet_stack] DEPLOYMENTS_PER_GROUP: Final = 2 RSS_SAMPLE_CAP: Final = 4 * MEMORY_RSS_SETTLE_SAMPLES diff --git a/tests/e2e/stack_lock.py b/tests/e2e/stack_lock.py new file mode 100644 index 00000000000..06df7a20b6a --- /dev/null +++ b/tests/e2e/stack_lock.py @@ -0,0 +1,45 @@ +"""Cross-process reader/writer lock over the proxy stack every xdist worker shares. +Every collected test holds it shared, marker or not, since the Claude Code cells and +other unmarked suites drive the same stack; a `quiet_stack` test holds it exclusive, +and the `gate` file makes a waiting exclusive holder win over readers that arrive +after it.""" + +from __future__ import annotations + +import fcntl +import hashlib +import tempfile +from collections.abc import Generator +from contextlib import ExitStack, contextmanager +from pathlib import Path +from typing import Final + +from e2e_config import PROXY_BASE_URL + +STACK_DIGEST: Final = hashlib.sha256(PROXY_BASE_URL.encode()).hexdigest()[:12] +LOCK_DIR: Final = Path(tempfile.gettempdir()) / f"litellm-e2e-stack-{STACK_DIGEST}" +GATE_FILE: Final = LOCK_DIR / "gate" +STACK_FILE: Final = LOCK_DIR / "stack" + + +@contextmanager +def _flock(path: Path, operation: int) -> Generator[None]: + with path.open("a") as handle: + fcntl.flock(handle, operation) + try: + yield + finally: + fcntl.flock(handle, fcntl.LOCK_UN) + + +@contextmanager +def stack_lock(exclusive: bool) -> Generator[None]: + LOCK_DIR.mkdir(parents=True, exist_ok=True) + if exclusive: + with _flock(GATE_FILE, fcntl.LOCK_EX), _flock(STACK_FILE, fcntl.LOCK_EX): + yield + return + with ExitStack() as held: + with _flock(GATE_FILE, fcntl.LOCK_SH): + held.enter_context(_flock(STACK_FILE, fcntl.LOCK_SH)) + yield diff --git a/tests/e2e/test_stack_lock.py b/tests/e2e/test_stack_lock.py new file mode 100644 index 00000000000..af071d2cc18 --- /dev/null +++ b/tests/e2e/test_stack_lock.py @@ -0,0 +1,117 @@ +"""Cross-process behavior of the stack lock: readers share it, an exclusive holder waits for +every reader and keeps them out, and a reader arriving behind a waiting exclusive holder +queues behind it instead of starving it.""" + +from __future__ import annotations + +import fcntl +import os +import subprocess +import sys +import time +from contextlib import ExitStack +from pathlib import Path +from typing import Final + +import pytest + +from stack_lock import STACK_DIGEST + +HARNESS_DIR: Final = Path(__file__).resolve().parent +DEADLINE_SECONDS: Final = 30.0 +SETTLE_SECONDS: Final = 0.5 +HOLDER_SCRIPT: Final = """ +import sys, time +from pathlib import Path +from stack_lock import stack_lock +name, mode, release_path, log_path = sys.argv[1:] + + +def record(event): + with Path(log_path).open("a") as log: + log.write(f"{name} {event}\\n") + + +record("waiting") +with stack_lock(exclusive=mode == "exclusive"): + record("enter") + while not Path(release_path).exists(): + time.sleep(0.02) + record("exit") +""" + + +def _events(log_path: Path) -> tuple[str, ...]: + return tuple(log_path.read_text().splitlines()) if log_path.exists() else () + + +def _wait_for_event(log_path: Path, event: str) -> None: + deadline: Final = time.monotonic() + DEADLINE_SECONDS + while event not in _events(log_path): + if time.monotonic() > deadline: + pytest.fail(f"{event!r} never appeared; events so far: {_events(log_path)}") + time.sleep(0.02) + + +def _wait_until_gate_is_held_exclusively(gate_path: Path) -> None: + deadline: Final = time.monotonic() + DEADLINE_SECONDS + with gate_path.open("a") as handle: + while True: + try: + fcntl.flock(handle, fcntl.LOCK_SH | fcntl.LOCK_NB) + except BlockingIOError: + return + fcntl.flock(handle, fcntl.LOCK_UN) + if time.monotonic() > deadline: + pytest.fail("no exclusive holder ever took the gate") + time.sleep(0.02) + + +def _start_holder(held: ExitStack, tmp_path: Path, name: str, mode: str) -> subprocess.Popen[bytes]: + holder: Final = held.enter_context( + subprocess.Popen( + ( + sys.executable, + "-P", + "-c", + HOLDER_SCRIPT, + name, + mode, + str(tmp_path / f"release-{name}"), + str(tmp_path / "events"), + ), + cwd=HARNESS_DIR, + env={**os.environ, "TMPDIR": str(tmp_path), "PYTHONPATH": str(HARNESS_DIR)}, + ) + ) + held.callback(holder.kill) + return holder + + +def test_readers_share_exclusive_waits_and_a_waiting_exclusive_beats_later_readers(tmp_path: Path) -> None: + lock_dir: Final = tmp_path / f"litellm-e2e-stack-{STACK_DIGEST}" + lock_dir.mkdir() + log_path: Final = tmp_path / "events" + with ExitStack() as held: + first_reader: Final = _start_holder(held, tmp_path, "A", "shared") + _wait_for_event(log_path, "A enter") + second_reader: Final = _start_holder(held, tmp_path, "R", "shared") + _wait_for_event(log_path, "R enter") + (tmp_path / "release-R").touch() + _wait_for_event(log_path, "R exit") + writer: Final = _start_holder(held, tmp_path, "W", "exclusive") + _wait_until_gate_is_held_exclusively(lock_dir / "gate") + late_reader: Final = _start_holder(held, tmp_path, "B", "shared") + _wait_for_event(log_path, "B waiting") + time.sleep(SETTLE_SECONDS) + (tmp_path / "release-A").touch() + _wait_for_event(log_path, "W enter") + (tmp_path / "release-W").touch() + _wait_for_event(log_path, "B enter") + (tmp_path / "release-B").touch() + for holder in (first_reader, second_reader, writer, late_reader): + assert holder.wait(timeout=DEADLINE_SECONDS) == 0 + events: Final = _events(log_path) + assert events.index("R enter") < events.index("A exit") + assert events.index("W enter") > events.index("A exit") + assert events.index("B enter") > events.index("W exit") From a173657dfb2df85511d07febd1f15adb4e576c6a Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 17:14:44 -0500 Subject: [PATCH 047/101] fix(caching): keep embedding cache hits aligned with request inputs (#42571) * fix(caching): keep embedding cache hits aligned with request inputs Partial hits now send only the uncached inputs to the provider and merge fresh vectors back into their original positions. Responses whose item count differs from the input count (one input scoring many documents) are no longer written to the per-input cache, since a later hit would return a single item. Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(caching): drop mutable collection builds flagged by the type discipline gate Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(caching): bypass embedding cache entries written before the per input cardinality check Embedding cache entries now carry format_version and readers treat entries without it as misses, so entries that only hold the first row of a multi row response are refetched instead of served until their TTL expires. The provider call also receives a copy of the request kwargs with the uncached inputs rather than mutating the caller's mapping Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(caching): assert a partial embedding cache hit becomes a full hit on repeat Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(caching): await pending embedding cache writes before asserting on cache hits Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(caching): validate cached embeddings without mutating responses or request kwargs Validate cache rows through a frozen pydantic model so import does not depend on TypeAdapter support for ReadOnly TypedDicts, accept string embeddings, build the merged partial hit response instead of mutating the cached one, and hand the provider request mapping to post call hooks Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(caching): keep cache_hit and response_ms on merged partial embedding hits Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: yassin Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- litellm/caching/caching.py | 55 ++++----- litellm/caching/caching_handler.py | 89 +++++++++----- litellm/types/caching.py | 18 +-- litellm/utils.py | 16 ++- tests/test_litellm/caching/test_caching.py | 113 +++++++++++++++++- .../caching/test_caching_handler.py | 45 ++++++- 6 files changed, 264 insertions(+), 72 deletions(-) diff --git a/litellm/caching/caching.py b/litellm/caching/caching.py index 6f99eb616b0..a31cad4af29 100644 --- a/litellm/caching/caching.py +++ b/litellm/caching/caching.py @@ -781,35 +781,23 @@ class Cache: Convert any embedding response into the standardized CachedEmbedding TypedDict format. """ try: - if isinstance(embedding_response, dict): - return { - "embedding": embedding_response.get("embedding"), - "index": embedding_response.get("index"), - "object": embedding_response.get("object"), - "model": model, - "prompt_tokens": prompt_tokens, - "prompt_tokens_details": prompt_tokens_details, - } - elif hasattr(embedding_response, "model_dump"): - data = embedding_response.model_dump() - return { - "embedding": data.get("embedding"), - "index": data.get("index"), - "object": data.get("object"), - "model": model, - "prompt_tokens": prompt_tokens, - "prompt_tokens_details": prompt_tokens_details, - } - else: - data = vars(embedding_response) - return { - "embedding": data.get("embedding"), - "index": data.get("index"), - "object": data.get("object"), - "model": model, - "prompt_tokens": prompt_tokens, - "prompt_tokens_details": prompt_tokens_details, - } + data: Final = ( + embedding_response + if isinstance(embedding_response, dict) + else embedding_response.model_dump() + if hasattr(embedding_response, "model_dump") + else vars(embedding_response) + ) + cached: Final[CachedEmbedding] = { + "embedding": data.get("embedding"), + "index": data.get("index"), + "object": data.get("object"), + "model": model, + "prompt_tokens": prompt_tokens, + "prompt_tokens_details": prompt_tokens_details, + "format_version": EMBEDDING_CACHE_FORMAT_VERSION, + } + return cached except KeyError as e: raise ValueError(f"Missing expected key in embedding response: {e}") @@ -925,6 +913,15 @@ class Cache: if self.should_use_cache(**kwargs) is not True: return + input_count: Final = len(kwargs["input"]) if isinstance(kwargs["input"], list) else 1 + if len(result.data) != input_count: + verbose_logger.debug( + "LiteLLM Cache: skipping embedding cache write, %d inputs but %d embeddings in the response", + input_count, + len(result.data), + ) + return + # set default ttl if not set if self.ttl is not None: kwargs["ttl"] = self.ttl diff --git a/litellm/caching/caching_handler.py b/litellm/caching/caching_handler.py index 36c3b744a06..4afd0e7caaa 100644 --- a/litellm/caching/caching_handler.py +++ b/litellm/caching/caching_handler.py @@ -21,7 +21,7 @@ import time from collections.abc import AsyncGenerator, AsyncIterator, Awaitable, Callable, Generator, Mapping from typing import TYPE_CHECKING, Any, Final, Optional, TypeVar -from pydantic import BaseModel +from pydantic import BaseModel, ConfigDict, ValidationError import litellm from litellm._logging import print_verbose, verbose_logger @@ -34,7 +34,7 @@ from litellm.litellm_core_utils.llm_response_utils.response_metadata import ( from litellm.litellm_core_utils.logging_utils import ( _assemble_complete_response_from_streaming_chunks, ) -from litellm.types.caching import CachedEmbedding +from litellm.types.caching import EMBEDDING_CACHE_FORMAT_VERSION, CachedEmbedding from litellm.types.integrations.custom_logger import converted_stream_requested from litellm.types.llms.openai import ResponsesAPIResponse from litellm.types.rerank import RerankResponse @@ -77,6 +77,7 @@ class CachingHandlerResponse(BaseModel): cached_result: object | None = None final_embedding_cached_response: EmbeddingResponse | None = None embedding_all_elements_cache_hit: bool = False # this is set to True when all elements in the list have a cache hit in the embedding cache, if true return the final_embedding_cached_response no need to make an API call + embedding_uncached_input: list[str | list[int]] | None = None in_memory_cache_obj: Final = InMemoryCache() @@ -168,6 +169,37 @@ def _request_cache_key(request_kwargs: Mapping[str, Any]) -> str | None: return request_kwargs.get("cache_key", None) +class _CachedEmbeddingRecord(BaseModel): + model_config = ConfigDict(frozen=True) + + embedding: list[float] | str | None + index: int | None + object: str | None + model: str | None + prompt_tokens: int | None + prompt_tokens_details: dict | None + format_version: int + + +def _current_format_embedding_entry(entry: object) -> CachedEmbedding | None: + try: + record: Final = _CachedEmbeddingRecord.model_validate(entry) + except ValidationError: + return None + if record.format_version != EMBEDDING_CACHE_FORMAT_VERSION: + return None + cached: Final[CachedEmbedding] = { + "embedding": record.embedding, + "index": record.index, + "object": record.object, + "model": record.model, + "prompt_tokens": record.prompt_tokens, + "prompt_tokens_details": record.prompt_tokens_details, + "format_version": record.format_version, + } + return cached + + class LLMCachingHandler: def __init__( self, @@ -320,6 +352,7 @@ class LLMCachingHandler: return CachingHandlerResponse( final_embedding_cached_response=final_embedding_cached_response, embedding_all_elements_cache_hit=embedding_all_elements_cache_hit, + embedding_uncached_input=self.handle_kwargs_input_list_or_str(kwargs), ) verbose_logger.debug("CACHE RESULT: %s", cached_result) @@ -657,32 +690,30 @@ class LLMCachingHandler: if _caching_handler_response.final_embedding_cached_response is None: return embedding_response - idx = 0 - final_data_list: Final = [] - for item in _caching_handler_response.final_embedding_cached_response.data: - if item is None and embedding_response.data is not None: - final_data_list.append(embedding_response.data[idx]) - idx += 1 - else: - final_data_list.append(item) - - _caching_handler_response.final_embedding_cached_response.data = final_data_list - _caching_handler_response.final_embedding_cached_response._hidden_params["cache_hit"] = True - _caching_handler_response.final_embedding_cached_response._response_ms = ( - end_time - start_time - ).total_seconds() * 1000 - - ## USAGE - if ( - _caching_handler_response.final_embedding_cached_response.usage is not None - and embedding_response.usage is not None - ): - _caching_handler_response.final_embedding_cached_response.usage = self.combine_usage( - usage1=_caching_handler_response.final_embedding_cached_response.usage, - usage2=embedding_response.usage, - ) - - return _caching_handler_response.final_embedding_cached_response + cached: Final = _caching_handler_response.final_embedding_cached_response + fresh_items: Final = iter(embedding_response.data or ()) + merged_usage: Final = ( + self.combine_usage(usage1=cached.usage, usage2=embedding_response.usage) + if cached.usage is not None and embedding_response.usage is not None + else cached.usage + ) + merged: Final = EmbeddingResponse( + model=cached.model, + data=[ # mutable-ok: EmbeddingResponse.data is a pydantic list field + item + if item is not None + else Embedding(embedding=next(fresh_items)["embedding"], index=position, object="embedding") + for position, item in enumerate(cached.data) + ], + usage=merged_usage, + hidden_params={ # mutable-ok: EmbeddingResponse._hidden_params is a mutable dict field + **cached._hidden_params, + "cache_hit": True, + }, + _response_headers=cached._response_headers, + ) + merged._response_ms = (end_time - start_time).total_seconds() * 1000 + return merged def _async_log_cache_hit_on_callbacks( self, @@ -770,7 +801,7 @@ class LLMCachingHandler: dynamic_cache_object=self.dual_cache, ) ) - cached_result = await asyncio.gather(*tasks) + cached_result = [_current_format_embedding_entry(entry) for entry in await asyncio.gather(*tasks)] ## check if cached result is None ## if cached_result is not None and isinstance(cached_result, list): # set cached_result to None if all elements are None diff --git a/litellm/types/caching.py b/litellm/types/caching.py index 747f202d35e..6d42556a9c4 100644 --- a/litellm/types/caching.py +++ b/litellm/types/caching.py @@ -3,7 +3,7 @@ from enum import Enum from typing import Any, Final, Literal, Optional, Union from pydantic import BaseModel -from typing_extensions import TypedDict +from typing_extensions import ReadOnly, TypedDict class LiteLLMCacheType(str, Enum): @@ -137,12 +137,16 @@ class HealthCheckCacheParams(BaseModel): redis_version: str | int | float | None = None +EMBEDDING_CACHE_FORMAT_VERSION: Final = 2 + + class CachedEmbedding(TypedDict): """Type definition for cached embedding objects""" - embedding: list[float] | None - index: int | None - object: str | None - model: str | None - prompt_tokens: int | None - prompt_tokens_details: dict | None + embedding: ReadOnly[list[float] | str | None] + index: ReadOnly[int | None] + object: ReadOnly[str | None] + model: ReadOnly[str | None] + prompt_tokens: ReadOnly[int | None] + prompt_tokens_details: ReadOnly[dict | None] + format_version: ReadOnly[int] diff --git a/litellm/utils.py b/litellm/utils.py index b9d56b25653..b5d396030f7 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -2015,13 +2015,19 @@ def client(original_function): print_verbose(f"Error while checking max token limit: {e}") # MODEL CALL + call_kwargs: Final = ( + {**kwargs, "input": _caching_handler_response.embedding_uncached_input} + if _caching_handler_response is not None + and _caching_handler_response.embedding_uncached_input is not None + else kwargs + ) try: - result = await original_function(*args, **kwargs) + result = await original_function(*args, **call_kwargs) except Exception as deployment_error: _deployment_call_end_time = datetime.datetime.now() # noqa: DTZ005 # matches the naive datetimes this whole function already times start_time/end_time with try: await async_post_call_failure_deployment_hook( - request_data=kwargs, + request_data=call_kwargs, exception=deployment_error, call_type=call_type, ) @@ -2062,7 +2068,7 @@ def client(original_function): post_call_processing( original_response=result, model=model, - optional_params=kwargs, + optional_params=call_kwargs, original_function=original_function, rules_obj=rules_obj, ) @@ -2070,7 +2076,7 @@ def client(original_function): _call_type_enum: Final = _CALL_TYPE_ENUM_MAP.get(call_type) if _call_type_enum is not None: result = await async_post_call_success_deployment_hook( - request_data=kwargs, + request_data=call_kwargs, response=result, call_type=_call_type_enum, ) @@ -2079,7 +2085,7 @@ def client(original_function): await _llm_caching_handler.async_set_cache( result=result, original_function=original_function, - kwargs=kwargs, + kwargs=call_kwargs, args=args, ) diff --git a/tests/test_litellm/caching/test_caching.py b/tests/test_litellm/caching/test_caching.py index c7ec8abc31e..2e4122530d8 100644 --- a/tests/test_litellm/caching/test_caching.py +++ b/tests/test_litellm/caching/test_caching.py @@ -1,3 +1,4 @@ +import asyncio import logging import re from unittest.mock import MagicMock @@ -6,8 +7,9 @@ import pytest import litellm.caching.redis_cache as redis_cache_module from litellm.caching.caching import Cache +from litellm.caching.caching_handler import _PENDING_CACHE_WRITES from litellm.caching.redis_cache import RedisCache, _RedisTimeoutLogThrottle -from litellm.types.caching import LiteLLMCacheType, SemanticCacheScope +from litellm.types.caching import EMBEDDING_CACHE_FORMAT_VERSION, LiteLLMCacheType, SemanticCacheScope from litellm.types.utils import Embedding, EmbeddingResponse, Usage @@ -278,3 +280,112 @@ def test_exact_cache_key_includes_anthropic_messages_params(anthropic_param): assert baseline != cache.get_cache_key( model="claude-sonnet-4-5", messages=messages, **anthropic_param ) + + +@pytest.mark.asyncio +async def test_embedding_cache_skips_write_when_one_input_yields_many_embeddings(monkeypatch): + """A cross-encoder behind /embeddings returns one score per document for a single + input string; caching data[0] per input would make the second call return 1 score.""" + import litellm + from litellm import CustomLLM + + class ScoreEveryDocument(CustomLLM): + provider_calls: int = 0 + + async def aembedding(self, model, input, model_response, **kwargs) -> EmbeddingResponse: + self.provider_calls += 1 + return EmbeddingResponse( + model=model, + data=[Embedding(embedding=[float(i)], index=i, object="embedding") for i in range(5)], + ) + + scorer = ScoreEveryDocument() + monkeypatch.setattr(litellm, "custom_provider_map", [{"provider": "score-every-doc", "custom_handler": scorer}]) + monkeypatch.setattr(litellm, "provider_list", [*litellm.provider_list, "score-every-doc"]) + monkeypatch.setattr(litellm, "_custom_providers", [*litellm._custom_providers, "score-every-doc"]) + monkeypatch.setattr(litellm, "cache", Cache(type=LiteLLMCacheType.LOCAL)) + + batch = '{"query": "q", "documents": ["a", "b", "c", "d", "e"]}' + first = await litellm.aembedding(model="score-every-doc/m", input=[batch]) + await asyncio.gather(*_PENDING_CACHE_WRITES) + second = await litellm.aembedding(model="score-every-doc/m", input=[batch]) + + assert scorer.provider_calls == 2 + assert [len(first.data), len(second.data)] == [5, 5] + + +@pytest.mark.asyncio +async def test_embedding_cache_refetches_entries_written_without_format_version(monkeypatch): + import litellm + from litellm import CustomLLM + + class EmbedLength(CustomLLM): + provider_calls: int = 0 + + async def aembedding(self, model, input, model_response, **kwargs) -> EmbeddingResponse: + self.provider_calls += 1 + return EmbeddingResponse( + model=model, + data=[ + Embedding(embedding=[float(len(text))], index=idx, object="embedding") + for idx, text in enumerate(input) + ], + ) + + embedder = EmbedLength() + monkeypatch.setattr(litellm, "custom_provider_map", [{"provider": "embed-length", "custom_handler": embedder}]) + monkeypatch.setattr(litellm, "provider_list", [*litellm.provider_list, "embed-length"]) + monkeypatch.setattr(litellm, "_custom_providers", [*litellm._custom_providers, "embed-length"]) + monkeypatch.setattr(litellm, "cache", Cache(type=LiteLLMCacheType.LOCAL)) + + await litellm.aembedding(model="embed-length/m", input=["abcd"]) + await asyncio.gather(*_PENDING_CACHE_WRITES) + store = litellm.cache.cache.cache_dict + stored = [entry["response"] for entry in store.values()] + assert [entry["format_version"] for entry in stored] == [EMBEDDING_CACHE_FORMAT_VERSION], stored + legacy_store = { + key: { + **entry, + "response": { + field: value + for field, value in {**entry["response"], "embedding": [-1.0]}.items() + if field != "format_version" + }, + } + for key, entry in store.items() + } + monkeypatch.setattr(litellm.cache.cache, "cache_dict", legacy_store) + + refetched = await litellm.aembedding(model="embed-length/m", input=["abcd"]) + + assert embedder.provider_calls == 2, "an entry written without format_version must be a cache miss" + assert [item["embedding"] for item in refetched.data] == [[4.0]] + + +@pytest.mark.asyncio +async def test_embedding_cache_serves_base64_string_embeddings_on_repeat(monkeypatch): + import litellm + from litellm import CustomLLM + + class Base64Embedder(CustomLLM): + provider_calls: int = 0 + + async def aembedding(self, model, input, model_response, **kwargs) -> EmbeddingResponse: + self.provider_calls += 1 + return EmbeddingResponse( + model=model, + data=[Embedding(embedding="AACAPwAAAEA=", index=idx, object="embedding") for idx, _ in enumerate(input)], + ) + + embedder = Base64Embedder() + monkeypatch.setattr(litellm, "custom_provider_map", [{"provider": "embed-b64", "custom_handler": embedder}]) + monkeypatch.setattr(litellm, "provider_list", [*litellm.provider_list, "embed-b64"]) + monkeypatch.setattr(litellm, "_custom_providers", [*litellm._custom_providers, "embed-b64"]) + monkeypatch.setattr(litellm, "cache", Cache(type=LiteLLMCacheType.LOCAL)) + + first = await litellm.aembedding(model="embed-b64/m", input=["abcd"]) + await asyncio.gather(*_PENDING_CACHE_WRITES) + second = await litellm.aembedding(model="embed-b64/m", input=["abcd"]) + + assert embedder.provider_calls == 1, "a string embedding written to the cache must be served on repeat" + assert [item["embedding"] for item in second.data] == [item["embedding"] for item in first.data] == ["AACAPwAAAEA="] diff --git a/tests/test_litellm/caching/test_caching_handler.py b/tests/test_litellm/caching/test_caching_handler.py index 39018dca41d..6956a6932d5 100644 --- a/tests/test_litellm/caching/test_caching_handler.py +++ b/tests/test_litellm/caching/test_caching_handler.py @@ -11,7 +11,7 @@ from fastapi.testclient import TestClient from datetime import datetime from unittest.mock import AsyncMock -from litellm.caching.caching_handler import LLMCachingHandler +from litellm.caching.caching_handler import _PENDING_CACHE_WRITES, LLMCachingHandler @pytest.mark.asyncio @@ -780,3 +780,46 @@ async def test_agentic_loop_followup_cache_hit_with_converted_stream_marker_repl assert hit.cached_result.choices[0].message.content == "done" logging_obj.handle_sync_success_callbacks_for_async_calls.assert_called_once() assert logging_obj.handle_sync_success_callbacks_for_async_calls.call_args.kwargs["cache_hit"] is True + + +@pytest.mark.asyncio +async def test_partial_embedding_cache_hit_sends_only_misses_and_keeps_input_order(monkeypatch): + import litellm + from litellm import CustomLLM + from litellm.caching.caching import Cache + from litellm.types.utils import Embedding, EmbeddingResponse + + class RecordingEmbedder(CustomLLM): + provider_inputs: tuple[tuple[str, ...], ...] = () + + async def aembedding(self, model, input, model_response, **kwargs) -> EmbeddingResponse: + self.provider_inputs = (*self.provider_inputs, tuple(input)) + return EmbeddingResponse( + model=model, + data=[ + Embedding(embedding=[float(len(text))], index=idx, object="embedding") + for idx, text in enumerate(input) + ], + ) + + embedder = RecordingEmbedder() + monkeypatch.setattr(litellm, "custom_provider_map", [{"provider": "recording-embedder", "custom_handler": embedder}]) + monkeypatch.setattr(litellm, "provider_list", [*litellm.provider_list, "recording-embedder"]) + monkeypatch.setattr(litellm, "_custom_providers", [*litellm._custom_providers, "recording-embedder"]) + monkeypatch.setattr(litellm, "cache", Cache(type="local")) + + await litellm.aembedding(model="recording-embedder/m", input=["aa", "bbbb"]) + await asyncio.gather(*_PENDING_CACHE_WRITES) + mixed_input = ["c", "aa", "ddd", "bbbb", "eeeee"] + response = await litellm.aembedding(model="recording-embedder/m", input=mixed_input) + await asyncio.gather(*_PENDING_CACHE_WRITES) + + assert embedder.provider_inputs == (("aa", "bbbb"), ("c", "ddd", "eeeee")), embedder.provider_inputs + assert [item["index"] for item in response.data] == [0, 1, 2, 3, 4] + assert [item["embedding"] for item in response.data] == [[float(len(text))] for text in mixed_input] + assert response._hidden_params["cache_hit"] is True, "a partial hit must still be reported as a cache hit" + + repeat = await litellm.aembedding(model="recording-embedder/m", input=mixed_input) + + assert len(embedder.provider_inputs) == 2, embedder.provider_inputs + assert [item["embedding"] for item in repeat.data] == [[float(len(text))] for text in mixed_input] From 95d4613bd3f64cbbdb752f77c935015166718409 Mon Sep 17 00:00:00 2001 From: "berriai-litellm-provider-info-sync[bot]" <328147090+berriai-litellm-provider-info-sync[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 15:14:48 -0700 Subject: [PATCH 048/101] chore(prices): sync xAI prices: 3 models, 3 new [3 with gaps] (#42591) * chore(prices): sync xAI prices: 3 models, 3 new [3 with gaps] xai/grok-code-fast: supports_vision, supports_prompt_caching, input_cost_per_token, output_cost_per_token, input_cost_per_image_token, cache_read_input_token_cost, input_cost_per_token_above_200k_tokens, output_cost_per_token_above_200k_tokens, cache_read_input_token_cost_above_200k_tokens, supports_function_calling, supports_tool_choice, supports_response_schema xai/grok-code-fast-1: supports_vision, supports_prompt_caching, input_cost_per_token, output_cost_per_token, input_cost_per_image_token, cache_read_input_token_cost, input_cost_per_token_above_200k_tokens, output_cost_per_token_above_200k_tokens, cache_read_input_token_cost_above_200k_tokens, supports_function_calling, supports_tool_choice, supports_response_schema xai/grok-code-fast-1-0825: supports_vision, supports_prompt_caching, input_cost_per_token, output_cost_per_token, input_cost_per_image_token, cache_read_input_token_cost, input_cost_per_token_above_200k_tokens, output_cost_per_token_above_200k_tokens, cache_read_input_token_cost_above_200k_tokens, supports_function_calling, supports_tool_choice, supports_response_schema * fix(prices): add context limits and reasoning flag to xai grok-code-fast aliases Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(prices): keep the xai sync diff limited to the alias fields Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: berriai-litellm-provider-info-sync[bot] <328147090+berriai-litellm-provider-info-sync[bot]@users.noreply.github.com> Co-authored-by: kerry Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- ...odel_prices_and_context_window_backup.json | 63 +++++++++++++++++++ model_prices_and_context_window.json | 63 +++++++++++++++++++ 2 files changed, 126 insertions(+) diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 3f1d26e9adc..224129fbd25 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -72335,5 +72335,68 @@ "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true + }, + "xai/grok-code-fast": { + "cache_read_input_token_cost": 2e-07, + "cache_read_input_token_cost_above_200k_tokens": 4e-07, + "input_cost_per_image_token": 1e-06, + "input_cost_per_token": 1e-06, + "input_cost_per_token_above_200k_tokens": 2e-06, + "litellm_provider": "xai", + "max_input_tokens": 256000, + "max_output_tokens": 256000, + "max_tokens": 256000, + "mode": "chat", + "output_cost_per_token": 2e-06, + "output_cost_per_token_above_200k_tokens": 4e-06, + "source": "https://api.x.ai/v1/language-models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "xai/grok-code-fast-1": { + "cache_read_input_token_cost": 2e-07, + "cache_read_input_token_cost_above_200k_tokens": 4e-07, + "input_cost_per_image_token": 1e-06, + "input_cost_per_token": 1e-06, + "input_cost_per_token_above_200k_tokens": 2e-06, + "litellm_provider": "xai", + "max_input_tokens": 256000, + "max_output_tokens": 256000, + "max_tokens": 256000, + "mode": "chat", + "output_cost_per_token": 2e-06, + "output_cost_per_token_above_200k_tokens": 4e-06, + "source": "https://api.x.ai/v1/language-models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "xai/grok-code-fast-1-0825": { + "cache_read_input_token_cost": 2e-07, + "cache_read_input_token_cost_above_200k_tokens": 4e-07, + "input_cost_per_image_token": 1e-06, + "input_cost_per_token": 1e-06, + "input_cost_per_token_above_200k_tokens": 2e-06, + "litellm_provider": "xai", + "max_input_tokens": 256000, + "max_output_tokens": 256000, + "max_tokens": 256000, + "mode": "chat", + "output_cost_per_token": 2e-06, + "output_cost_per_token_above_200k_tokens": 4e-06, + "source": "https://api.x.ai/v1/language-models", + "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.json b/model_prices_and_context_window.json index 3f1d26e9adc..224129fbd25 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -72335,5 +72335,68 @@ "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true + }, + "xai/grok-code-fast": { + "cache_read_input_token_cost": 2e-07, + "cache_read_input_token_cost_above_200k_tokens": 4e-07, + "input_cost_per_image_token": 1e-06, + "input_cost_per_token": 1e-06, + "input_cost_per_token_above_200k_tokens": 2e-06, + "litellm_provider": "xai", + "max_input_tokens": 256000, + "max_output_tokens": 256000, + "max_tokens": 256000, + "mode": "chat", + "output_cost_per_token": 2e-06, + "output_cost_per_token_above_200k_tokens": 4e-06, + "source": "https://api.x.ai/v1/language-models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "xai/grok-code-fast-1": { + "cache_read_input_token_cost": 2e-07, + "cache_read_input_token_cost_above_200k_tokens": 4e-07, + "input_cost_per_image_token": 1e-06, + "input_cost_per_token": 1e-06, + "input_cost_per_token_above_200k_tokens": 2e-06, + "litellm_provider": "xai", + "max_input_tokens": 256000, + "max_output_tokens": 256000, + "max_tokens": 256000, + "mode": "chat", + "output_cost_per_token": 2e-06, + "output_cost_per_token_above_200k_tokens": 4e-06, + "source": "https://api.x.ai/v1/language-models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "xai/grok-code-fast-1-0825": { + "cache_read_input_token_cost": 2e-07, + "cache_read_input_token_cost_above_200k_tokens": 4e-07, + "input_cost_per_image_token": 1e-06, + "input_cost_per_token": 1e-06, + "input_cost_per_token_above_200k_tokens": 2e-06, + "litellm_provider": "xai", + "max_input_tokens": 256000, + "max_output_tokens": 256000, + "max_tokens": 256000, + "mode": "chat", + "output_cost_per_token": 2e-06, + "output_cost_per_token_above_200k_tokens": 4e-06, + "source": "https://api.x.ai/v1/language-models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true } } From 238f4341532ae6dd150de55e9302c08a8e031c66 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 15:16:46 -0700 Subject: [PATCH 049/101] fix(otel): record the GenAI exception event through the Logs API on both OpenTelemetry lines (#42431) * fix(otel): record the GenAI exception event without the removed Events API OpenTelemetry removed opentelemetry._events in 1.44.0, so the three imports of it broke 7 modules under litellm.integrations.otel, including the entry point. Two things then failed quietly: with LITELLM_OTEL_V2 set the otel callback resolved to None and nothing was exported, and with it unset the newrelic callback was dropped as well, because that branch imports the v2 logger ungated Build and emit the event through the Logs API, which both lines carry. The event name keeps riding the event.name attribute: the event_name log record field that replaces it only exists from 1.44.0, and this package pins 1.28.0, so the attribute is the only form both can write. It is also what the Events API wrote, so exported events keep their shape Emitting a plain record drops the default the Events SDK applied, so the timestamp now falls back to time_ns() here * style(otel): trim the event name key and regression test prose Keep only the constraint a reader cannot infer from the code, that the event_name record field does not exist on the pinned OpenTelemetry line * fix(otel): export the GenAI exception event on both OpenTelemetry 1.28 and 1.44 lines Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(otel): drop the record selection comment Co-authored-by: Pawan-Shahane Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * style(otel): collapse the record selection conditional for ruff format Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * style(otel): build the record fields with a dict literal Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(otel): set the native event_name on the 1.44 log record Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * style(otel): spell out the record kwargs so the type gate sees each call Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * style(otel): suppress the version-gated kwargs for the type gate Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(otel): drop the version-window prose and correct the event_name suppression reason Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * style(otel): wrap the compat test docstring to the line limit Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: Pawan-Shahane Co-authored-by: yucheng Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- litellm/integrations/otel/logger.py | 2 +- litellm/integrations/otel/model/semconv.py | 1 + litellm/integrations/otel/plumbing/events.py | 54 +++++--- .../integrations/otel/plumbing/providers.py | 8 +- .../otel/test_otel_v2_components.py | 125 ++++++++++++++++++ 5 files changed, 168 insertions(+), 22 deletions(-) diff --git a/litellm/integrations/otel/logger.py b/litellm/integrations/otel/logger.py index 6b673967427..20cdf9662e1 100644 --- a/litellm/integrations/otel/logger.py +++ b/litellm/integrations/otel/logger.py @@ -240,7 +240,7 @@ class OpenTelemetryV2(CustomLogger): provider: Final = resolve_logger_provider(self.config, logger_provider) if provider is None: return None - return GenAIEventRecorder(get_event_logger(provider, LITELLM_TRACER_NAME)) + return GenAIEventRecorder(get_event_logger(provider, LITELLM_TRACER_NAME), provider.resource) # ====================================================================== # # Proxy global registration diff --git a/litellm/integrations/otel/model/semconv.py b/litellm/integrations/otel/model/semconv.py index d3628005bac..f552ba37655 100644 --- a/litellm/integrations/otel/model/semconv.py +++ b/litellm/integrations/otel/model/semconv.py @@ -245,6 +245,7 @@ class GenAIEvent: details, unlike the deprecated ``error.message`` span attribute. """ + NAME_KEY: Final = "event.name" OPERATION_EXCEPTION: Final = "gen_ai.client.operation.exception" diff --git a/litellm/integrations/otel/plumbing/events.py b/litellm/integrations/otel/plumbing/events.py index e7b8e22ddcd..e95d31f886f 100644 --- a/litellm/integrations/otel/plumbing/events.py +++ b/litellm/integrations/otel/plumbing/events.py @@ -9,18 +9,28 @@ emitting that event; the exporter pipeline it rides is built in """ from dataclasses import dataclass +from time import time_ns from typing import Final -from opentelemetry._events import Event, EventLogger +from opentelemetry._logs import Logger, LogRecord from opentelemetry._logs.severity import SeverityNumber +from opentelemetry.sdk.resources import Resource from opentelemetry.trace import SpanContext from litellm.integrations.otel.model.semconv import ExceptionEvent, GenAIEvent +try: + from opentelemetry.sdk._logs import LogRecord as _SDKLogRecord +except ImportError: + _SDKLogRecord = None + +SDK_LOG_RECORD: Final[type[LogRecord] | None] = _SDKLogRecord + @dataclass(frozen=True, slots=True) class GenAIEventRecorder: - event_logger: EventLogger + event_logger: Logger + resource: Resource | None = None def record_operation_exception( self, @@ -30,24 +40,36 @@ class GenAIEventRecorder: stack_trace: str | None, timestamp_ns: int | None, ) -> None: - # ``exception.type`` and ``exception.message`` are the semconv-required - # pair and always ride the event; only the recommended stacktrace is - # conditional on the payload carrying one. stacktrace: Final = ((ExceptionEvent.STACKTRACE, stack_trace),) if stack_trace else () - self.event_logger.emit( - Event( - name=GenAIEvent.OPERATION_EXCEPTION, - timestamp=timestamp_ns, + attributes: Final = dict( + ( + (GenAIEvent.NAME_KEY, GenAIEvent.OPERATION_EXCEPTION), + (ExceptionEvent.TYPE, error_type), + (ExceptionEvent.MESSAGE, message), + *stacktrace, + ) + ) + record: Final[LogRecord] = ( + SDK_LOG_RECORD( + timestamp=timestamp_ns or time_ns(), trace_id=span_context.trace_id, span_id=span_context.span_id, trace_flags=span_context.trace_flags, severity_number=SeverityNumber.WARN, - attributes=dict( - ( - (ExceptionEvent.TYPE, error_type), - (ExceptionEvent.MESSAGE, message), - *stacktrace, - ) - ), + body=message, + attributes=attributes, + resource=self.resource, # pyright: ignore[reportCallIssue] # SDK-only kwarg absent from the API LogRecord signature on the pin + ) + if SDK_LOG_RECORD is not None + else LogRecord( + timestamp=timestamp_ns or time_ns(), + trace_id=span_context.trace_id, + span_id=span_context.span_id, + trace_flags=span_context.trace_flags, + severity_number=SeverityNumber.WARN, + body=message, + attributes=attributes, + event_name=GenAIEvent.OPERATION_EXCEPTION, # pyright: ignore[reportCallIssue] # kwarg exists only on OTel 1.38+, absent from the pinned API signature ) ) + self.event_logger.emit(record) diff --git a/litellm/integrations/otel/plumbing/providers.py b/litellm/integrations/otel/plumbing/providers.py index d52736a1303..e3474edaf14 100644 --- a/litellm/integrations/otel/plumbing/providers.py +++ b/litellm/integrations/otel/plumbing/providers.py @@ -9,11 +9,9 @@ from types import MappingProxyType from typing import TYPE_CHECKING, Any, Final, Literal from opentelemetry import _logs, baggage, metrics, trace -from opentelemetry._events import EventLogger -from opentelemetry._logs import LoggerProvider, NoOpLoggerProvider +from opentelemetry._logs import Logger, LoggerProvider, NoOpLoggerProvider from opentelemetry.context import Context from opentelemetry.metrics import MeterProvider, NoOpMeterProvider -from opentelemetry.sdk._events import EventLoggerProvider from opentelemetry.sdk._logs import LoggerProvider as SDKLoggerProvider from opentelemetry.sdk._logs.export import ( BatchLogRecordProcessor, @@ -1042,8 +1040,8 @@ def resolve_logger_provider( return provider -def get_event_logger(provider: SDKLoggerProvider, name: str = "litellm") -> EventLogger: - return EventLoggerProvider(logger_provider=provider).get_event_logger(name, litellm_version) +def get_event_logger(provider: SDKLoggerProvider, name: str = "litellm") -> Logger: + return provider.get_logger(name, litellm_version) def build_meter_provider( diff --git a/tests/test_litellm/integrations/otel/test_otel_v2_components.py b/tests/test_litellm/integrations/otel/test_otel_v2_components.py index 79747ac9956..07705e17d9a 100644 --- a/tests/test_litellm/integrations/otel/test_otel_v2_components.py +++ b/tests/test_litellm/integrations/otel/test_otel_v2_components.py @@ -1290,6 +1290,50 @@ def test_operation_exception_log_event_always_carries_required_pair(): assert ExceptionEvent.STACKTRACE not in attributes +def test_operation_exception_log_event_records_without_the_events_api(): + """Recording must not import the Events API modules (removed upstream in 1.44.0); + the SDK record path still exports.""" + import importlib + import sys + from unittest.mock import patch + + from opentelemetry._logs.severity import SeverityNumber + from opentelemetry.sdk._logs.export import InMemoryLogExporter + from opentelemetry.trace import INVALID_SPAN_CONTEXT + + from litellm.integrations.otel.model.semconv import ExceptionEvent, GenAIEvent + + plumbing = ("litellm.integrations.otel.plumbing.events", "litellm.integrations.otel.plumbing.providers") + without_events_api = { + **{name: module for name, module in sys.modules.items() if name not in plumbing}, + "opentelemetry._events": None, + "opentelemetry.sdk._events": None, + } + with patch.dict(sys.modules, without_events_api, clear=True): + events_mod = importlib.import_module(plumbing[0]) + providers_mod = importlib.import_module(plumbing[1]) + + log_exporter = InMemoryLogExporter() + cfg = OpenTelemetryV2Config(exporter="in_memory", enable_events=True) + logger_provider = providers_mod.build_logger_provider(cfg, log_exporter=log_exporter) + recorder = events_mod.GenAIEventRecorder(providers_mod.get_event_logger(logger_provider)) + recorder.record_operation_exception( + span_context=INVALID_SPAN_CONTEXT, + error_type="RateLimitError", + message="rate limited", + stack_trace=None, + timestamp_ns=None, + ) + + (log,) = log_exporter.get_finished_logs() + record = log.log_record + assert record.attributes[GenAIEvent.NAME_KEY] == GenAIEvent.OPERATION_EXCEPTION + assert record.attributes[ExceptionEvent.TYPE] == "RateLimitError" + assert record.attributes[ExceptionEvent.MESSAGE] == "rate limited" + assert record.severity_number == SeverityNumber.WARN + assert record.timestamp is not None + + def test_operation_exception_log_event_not_emitted_on_success(): engine, span_exporter, log_exporter = _engine_with_event_recorder() engine.emit(SpanRole.LLM_CALL, _llm_call_data(None)) @@ -1425,6 +1469,87 @@ def test_genai_mapper_guardrail_cost_in_spend_attr(): assert LiteLLM.GUARDRAIL_COST_IN_SPEND not in GenAIMapper().map(GuardrailSpanData.from_logging_entry(billed)) +def _sampled_span_context(): + from opentelemetry.trace import SpanContext, TraceFlags, TraceState + + return SpanContext( + trace_id=0x0AF7651916CD43DD8448EB211C80319C, + span_id=0x00F067AA0BA902B7, + is_remote=False, + trace_flags=TraceFlags(TraceFlags.SAMPLED), + trace_state=TraceState(), + ) + + +def test_operation_exception_log_event_exports_through_console_exporter(): + """The emitted record serializes through a real SDK exporter: the console + exporter only handles SDK-shaped records (``to_json`` plus a resource), so + an API-shaped record crashed the export under the repo's pinned OTel.""" + import io + import json as json_mod + + from opentelemetry.sdk._logs import LoggerProvider + from opentelemetry.sdk._logs.export import ConsoleLogExporter, SimpleLogRecordProcessor + from opentelemetry.sdk.resources import Resource + + from litellm.integrations.otel.model.semconv import ExceptionEvent, GenAIEvent + from litellm.integrations.otel.plumbing.events import GenAIEventRecorder + + out = io.StringIO() + logger_provider = LoggerProvider(resource=Resource.create({"service.name": "otel-event-test"})) + logger_provider.add_log_record_processor(SimpleLogRecordProcessor(ConsoleLogExporter(out=out))) + recorder = GenAIEventRecorder(providers.get_event_logger(logger_provider), logger_provider.resource) + recorder.record_operation_exception( + span_context=_sampled_span_context(), + error_type="RateLimitError", + message="rate limited", + stack_trace=None, + timestamp_ns=None, + ) + + exported = json_mod.loads(out.getvalue()) + assert exported["attributes"][GenAIEvent.NAME_KEY] == GenAIEvent.OPERATION_EXCEPTION + assert exported["attributes"][ExceptionEvent.TYPE] == "RateLimitError" + assert exported["attributes"][ExceptionEvent.MESSAGE] == "rate limited" + assert exported["body"] == "rate limited" + assert exported["resource"]["attributes"]["service.name"] == "otel-event-test" + + +def test_operation_exception_log_event_encodes_for_otlp(): + """The OTLP log encoder reads ``log_record.resource`` and rejects a None + body on the pinned OTel line, so the event must encode into a real + ExportLogsServiceRequest, not only land in an in-memory exporter.""" + from opentelemetry.exporter.otlp.proto.common._log_encoder import encode_logs + from opentelemetry.sdk._logs.export import InMemoryLogExporter + + from litellm.integrations.otel.model.semconv import GenAIEvent + from litellm.integrations.otel.plumbing.events import GenAIEventRecorder + + log_exporter = InMemoryLogExporter() + cfg = OpenTelemetryV2Config(exporter="in_memory", enable_events=True) + logger_provider = providers.build_logger_provider(cfg, log_exporter=log_exporter) + recorder = GenAIEventRecorder(providers.get_event_logger(logger_provider), logger_provider.resource) + recorder.record_operation_exception( + span_context=_sampled_span_context(), + error_type="RateLimitError", + message="rate limited", + stack_trace=None, + timestamp_ns=None, + ) + + request = encode_logs(log_exporter.get_finished_logs()) + (resource_logs,) = request.resource_logs + (scope_logs,) = resource_logs.scope_logs + (encoded,) = scope_logs.log_records + encoded_attrs = {a.key: a.value.string_value for a in encoded.attributes} + assert encoded_attrs[GenAIEvent.NAME_KEY] == GenAIEvent.OPERATION_EXCEPTION + assert encoded.body.string_value == "rate limited" + resource_attrs = {a.key: a.value.string_value for a in resource_logs.resource.attributes} + assert resource_attrs["service.name"] == logger_provider.resource.attributes["service.name"] + + + + def _isolate_v2_otlp_tls_env(monkeypatch: pytest.MonkeyPatch) -> None: for key in ( "SSL_VERIFY", From 3db94b932ec792c101149acafc3a1ff2e3004456 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 15:44:00 -0700 Subject: [PATCH 050/101] fix(spend): return 400 from /spend/calculate for a model with no pricing row (#42497) * fix(spend): return 400 from /spend/calculate for a model with no pricing row Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(spend): assert error type and param for unpriced /spend/calculate Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(spend): move the repro to tests/integration Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix: alias ModelNotMappedError re-export to satisfy F401 Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(utils): raise ModelNotMappedError only when the pricing row is missing Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: kerry Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- litellm/__init__.py | 1 + litellm/exceptions.py | 4 ++++ .../spend_management_endpoints.py | 7 +++++++ litellm/utils.py | 18 +++++++++++------ tests/integration/contracts.json | 3 +++ .../integration/spend/test_spend_calculate.py | 20 +++++++++++++++++++ .../test_spend_management_endpoints.py | 17 ++++++++++++++++ tests/test_litellm/test_utils.py | 7 +++++++ 8 files changed, 71 insertions(+), 6 deletions(-) create mode 100644 tests/integration/spend/test_spend_calculate.py diff --git a/litellm/__init__.py b/litellm/__init__.py index 471b273f00d..c8df4394a06 100644 --- a/litellm/__init__.py +++ b/litellm/__init__.py @@ -1402,6 +1402,7 @@ from .exceptions import ( JSONSchemaValidationError, LITELLM_EXCEPTION_TYPES, MockException, + ModelNotMappedError as ModelNotMappedError, ) from .budget_manager import BudgetManager from .proxy.proxy_cli import run_server diff --git a/litellm/exceptions.py b/litellm/exceptions.py index c8de2ab12ed..3bae8a95ef6 100644 --- a/litellm/exceptions.py +++ b/litellm/exceptions.py @@ -991,6 +991,10 @@ LITELLM_EXCEPTION_TYPES: Final = [ ] +class ModelNotMappedError(Exception): + pass + + class BudgetExceededError(Exception): def __init__( self, diff --git a/litellm/proxy/spend_tracking/spend_management_endpoints.py b/litellm/proxy/spend_tracking/spend_management_endpoints.py index b5980f9b224..822b827f985 100644 --- a/litellm/proxy/spend_tracking/spend_management_endpoints.py +++ b/litellm/proxy/spend_tracking/spend_management_endpoints.py @@ -2323,6 +2323,13 @@ async def calculate_spend(request: SpendCalculateRequest): param=getattr(e, "param", "None"), code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), ) + if isinstance(e, litellm.exceptions.ModelNotMappedError): + raise ProxyException( + message=str(e), + type="invalid_request_error", + param="model", + code=status.HTTP_400_BAD_REQUEST, + ) error_msg: Final = f"{e}" raise ProxyException( message=getattr(e, "message", error_msg), diff --git a/litellm/utils.py b/litellm/utils.py index b5d396030f7..01f6fee3594 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -472,6 +472,7 @@ from .exceptions import ( BudgetExceededError, ContentPolicyViolationError, ContextWindowExceededError, + ModelNotMappedError, NotFoundError, OpenAIError, PermissionDeniedError, @@ -5830,6 +5831,13 @@ def _is_potential_model_name_in_model_cost( _ABOVE_THRESHOLD_COST_KEY: Final = ABOVE_THRESHOLD_COST_KEY_PATTERN +def _model_not_mapped_message(model: str, custom_llm_provider: str | None) -> str: + return ( + f"This model isn't mapped yet. model={model}, custom_llm_provider={custom_llm_provider}. " + "Add it here - https://github.com/BerriAI/litellm/blob/main/model_prices_and_context_window.json." + ) + + def _get_model_info_helper( model: str, custom_llm_provider: str | None = None, @@ -6012,9 +6020,7 @@ def _get_model_info_helper( key, _model_info = generalization if _model_info is None or key is None: - raise ValueError( - "This model isn't mapped yet. Add it here - https://github.com/BerriAI/litellm/blob/main/model_prices_and_context_window.json" - ) + raise ModelNotMappedError(_model_not_mapped_message(model, custom_llm_provider)) _input_cost_per_token: float | None = _model_info.get("input_cost_per_token") if _input_cost_per_token is None: # default value to 0, be noisy about this @@ -6249,11 +6255,11 @@ def _get_model_info_helper( if cost_key not in returned_model_info and _ABOVE_THRESHOLD_COST_KEY.search(cost_key) is not None: returned_model_info[cost_key] = cost_value return returned_model_info + except ModelNotMappedError: + raise except Exception as e: verbose_logger.debug("Error getting model info: %s", e) - raise Exception( - f"This model isn't mapped yet. model={model}, custom_llm_provider={custom_llm_provider}. Add it here - https://github.com/BerriAI/litellm/blob/main/model_prices_and_context_window.json." - ) + raise Exception(_model_not_mapped_message(model, custom_llm_provider)) def _build_model_info( diff --git a/tests/integration/contracts.json b/tests/integration/contracts.json index cdf534bb5a1..1ae760467f1 100644 --- a/tests/integration/contracts.json +++ b/tests/integration/contracts.json @@ -275,6 +275,9 @@ "tests/integration/spend/test_filtered_ledger.py::test_rotated_keys_users_and_model_groups_preserve_success_failure_cache_ledger": [ "quota_management.spend_tracking.filtered_ledger_preserves_owner_identity_and_totals" ], + "tests/integration/spend/test_spend_calculate.py::test_spend_calculate_rejects_unpriced_model_with_400": [ + "quota_management.spend_tracking.spend_calculate.rejects_unpriced_model" + ], "tests/integration/management/test_partial_update_sequences.py::test_restricted_actor_cannot_detach_key_from_project": [ "mgmt.key.update.project_detach_denied_to_restricted_actor" ], diff --git a/tests/integration/spend/test_spend_calculate.py b/tests/integration/spend/test_spend_calculate.py new file mode 100644 index 00000000000..855dd2b21f3 --- /dev/null +++ b/tests/integration/spend/test_spend_calculate.py @@ -0,0 +1,20 @@ +import uuid +from typing import Final + +import pytest +from integration._support.client import JSON_OBJECT, Gateway, object_value, string_value + + +@pytest.mark.covers("quota_management.spend_tracking.spend_calculate.rejects_unpriced_model") +def test_spend_calculate_rejects_unpriced_model_with_400(gateway: Gateway) -> None: + model: Final = f"openrouter/integration-unpriced-{uuid.uuid4().hex}" + response: Final = gateway.request( + "POST", + "/spend/calculate", + {"model": model, "messages": [{"role": "user", "content": "price this request"}]}, + ) + assert response.status_code == 400, response.text + error: Final = object_value(JSON_OBJECT.validate_json(response.text)["error"]) + assert error["type"] == "invalid_request_error", response.text + assert error["param"] == "model", response.text + assert model in string_value(error["message"]), response.text diff --git a/tests/test_litellm/proxy/spend_tracking/test_spend_management_endpoints.py b/tests/test_litellm/proxy/spend_tracking/test_spend_management_endpoints.py index e41c027d962..c6a4173b583 100644 --- a/tests/test_litellm/proxy/spend_tracking/test_spend_management_endpoints.py +++ b/tests/test_litellm/proxy/spend_tracking/test_spend_management_endpoints.py @@ -257,6 +257,8 @@ from litellm.constants import LITTELM_INTERNAL_HEALTH_SERVICE_ACCOUNT_NAME from litellm.proxy._types import ( LitellmUserRoles, Member, + ProxyException, + SpendCalculateRequest, SpendLogsPayload, UserAPIKeyAuth, ) @@ -7835,3 +7837,18 @@ def test_ui_view_request_response_internal_user_missing_row_forbidden(client, mo assert custom_logger.requested_ids == [] finally: app.dependency_overrides.pop(ps.user_api_key_auth, None) + + +@pytest.mark.asyncio +async def test_calculate_spend_unpriced_model_returns_400(): + model = "openrouter/unit-test-unpriced-model" + with patch("litellm.proxy.proxy_server.llm_router", None): + with pytest.raises(ProxyException) as exc_info: + await spend_management_endpoints.calculate_spend( + SpendCalculateRequest(model=model, messages=[{"role": "user", "content": "hi"}]) + ) + + assert exc_info.value.code == "400" + assert exc_info.value.type == "invalid_request_error" + assert exc_info.value.param == "model" + assert model in exc_info.value.message diff --git a/tests/test_litellm/test_utils.py b/tests/test_litellm/test_utils.py index 07982f51153..79462d16a8c 100644 --- a/tests/test_litellm/test_utils.py +++ b/tests/test_litellm/test_utils.py @@ -230,6 +230,13 @@ def test_get_model_info_prefers_exact_dated_key_over_stripped( assert info["key"] == expected_key +def test_get_model_info_internal_failure_is_not_reported_as_unmapped() -> None: + with patch("litellm.utils._get_potential_model_names", side_effect=RuntimeError("malformed metadata")): + with pytest.raises(Exception, match="This model isn't mapped yet") as exc_info: + litellm.utils._get_model_info_helper(model="gpt-4o", custom_llm_provider="openai") + assert not isinstance(exc_info.value, litellm.ModelNotMappedError) + + def test_check_provider_match_azure_ai_allows_openai_and_azure(): """ Test that azure_ai provider can match openai and azure models. From 58a05a9eae5b31d2a71d1766aa5b5a153d8c2263 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 15:44:30 -0700 Subject: [PATCH 051/101] fix(anthropic): return 400 instead of 500 when a content list holds a bare string (#42420) * fix(anthropic): skip non-dict content items in beta-header and file-id helpers so malformed content lists return 400 instead of 500 Fixes #42094 Supersedes #42101 Co-authored-by: Pawan-Shahane Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(e2e): spawn the DB-less regression proxy with -P so the cwd cannot shadow the pinned checkout Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(e2e): launch the DB-less proxy via -I -c with an explicit sys.path so python 3.10 works, drop DIRECT_URL, remove restating docstrings Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(e2e): gate the self-booted DB-less proxy behind the owned_gateway opt-in the Buildkite container cannot satisfy Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(anthropic): move the bare string content item repro to tests/integration Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * style(tests): wrap the anthropic bare string wire test to the 120 column limit Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * style(tests): wrap anthropic common_utils test literals to the 120 column limit Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * style: fix ruff findings in touched test files Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: kerry Co-authored-by: Pawan-Shahane Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- .../prompt_templates/common_utils.py | 2 +- litellm/llms/anthropic/common_utils.py | 4 +- tests/integration/contracts.json | 6 ++ .../providers/test_anthropic_wire.py | 24 ++++++- ...ore_utils_prompt_templates_common_utils.py | 15 +++- .../anthropic/test_anthropic_common_utils.py | 70 +++++++++++++++++++ 6 files changed, 116 insertions(+), 5 deletions(-) diff --git a/litellm/litellm_core_utils/prompt_templates/common_utils.py b/litellm/litellm_core_utils/prompt_templates/common_utils.py index 1e96e20a03b..6c45622649f 100644 --- a/litellm/litellm_core_utils/prompt_templates/common_utils.py +++ b/litellm/litellm_core_utils/prompt_templates/common_utils.py @@ -1657,7 +1657,7 @@ def get_file_ids_from_messages(messages: list[AllMessageValues]) -> list[str]: if isinstance(content, str): continue for c in content: - if c["type"] == "file": + if isinstance(c, dict) and c["type"] == "file": file_object = cast(ChatCompletionFileObject, c) file_object_file_field = file_object.get("file") if not isinstance(file_object_file_field, dict): diff --git a/litellm/llms/anthropic/common_utils.py b/litellm/llms/anthropic/common_utils.py index 0c3c8996789..c0e6006633e 100644 --- a/litellm/llms/anthropic/common_utils.py +++ b/litellm/llms/anthropic/common_utils.py @@ -314,7 +314,7 @@ class AnthropicModelInfo(BaseLLMModelInfo): _message_content = message.get("content") if _message_content is not None and isinstance(_message_content, list): for content in _message_content: - if "cache_control" in content: + if isinstance(content, dict) and "cache_control" in content: return True return False @@ -359,7 +359,7 @@ class AnthropicModelInfo(BaseLLMModelInfo): for message in messages: if "content" in message and message["content"] is not None and isinstance(message["content"], list): for content in message["content"]: - if "type" in content and content["type"] != "text": + if isinstance(content, dict) and "type" in content and content["type"] != "text": return True return False diff --git a/tests/integration/contracts.json b/tests/integration/contracts.json index 1ae760467f1..8c4ce4debbc 100644 --- a/tests/integration/contracts.json +++ b/tests/integration/contracts.json @@ -159,6 +159,12 @@ "tests/integration/routing/test_redis_recovery.py::test_owned_redis_outage_recovers_requests_and_real_response_cache": [ "other.routing.redis.owned_outage_recovers_serving_and_response_cache" ], + "tests/integration/providers/test_anthropic_wire.py::test_anthropic_bare_string_content_item_is_rejected_as_client_error_before_the_wire[type_word]": [ + "other.provider_wire.anthropic.bare_string_content_item_is_client_error" + ], + "tests/integration/providers/test_anthropic_wire.py::test_anthropic_bare_string_content_item_is_rejected_as_client_error_before_the_wire[plain]": [ + "other.provider_wire.anthropic.bare_string_content_item_is_client_error" + ], "tests/integration/providers/test_anthropic_wire.py::test_anthropic_tool_history_and_cache_tokens_keep_wire_and_accounting_contracts": [ "other.provider_wire.anthropic.tool_history_system_cache_and_internal_fields", "quota_management.spend_tracking.cache_tokens.disjoint_classes_use_explicit_rates" diff --git a/tests/integration/providers/test_anthropic_wire.py b/tests/integration/providers/test_anthropic_wire.py index 64160fa85aa..27895440712 100644 --- a/tests/integration/providers/test_anthropic_wire.py +++ b/tests/integration/providers/test_anthropic_wire.py @@ -3,7 +3,6 @@ import uuid from typing import Final import pytest - from integration._support.client import Gateway, eventually, object_value from integration._support.database import read_rows from integration._support.wire import Reply, Request, wire_server @@ -59,3 +58,26 @@ def test_anthropic_tool_history_and_cache_tokens_keep_wire_and_accounting_contra parsed: Final = json.loads(metadata) if isinstance(metadata, str) else object_value(metadata) assert parsed["cost_breakdown"]["input_cost"] == pytest.approx(0.0245) assert parsed["cost_breakdown"]["output_cost"] == pytest.approx(0.008) + + +@pytest.mark.covers("other.provider_wire.anthropic.bare_string_content_item_is_client_error") +@pytest.mark.parametrize( + "text", [pytest.param("what type of file is this?", id="type_word"), pytest.param("hello", id="plain")] +) +def test_anthropic_bare_string_content_item_is_rejected_as_client_error_before_the_wire( + gateway: Gateway, text: str +) -> None: + def respond(request: Request) -> Reply: + raise AssertionError(f"upstream must not be reached: {request.target}") + + with wire_server(respond) as wire, gateway.scenario() as scenario: + model: Final = scenario.model( + model="anthropic/claude-sonnet-4-5-20250929", api_base=wire.url, api_key="synthetic-anthropic-key" + ) + response: Final = gateway.request( + "POST", + "/v1/chat/completions", + {"model": model, "max_tokens": 16, "timeout": 5, "messages": [{"role": "system", "content": [text]}]}, + ) + assert response.status_code == 400, response.text + assert wire.drain() == () diff --git a/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_common_utils.py b/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_common_utils.py index 62cf5680266..79c50bf2369 100644 --- a/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_common_utils.py +++ b/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_common_utils.py @@ -4,7 +4,6 @@ import json import os import sys from typing import Final -from unittest.mock import MagicMock, patch import pytest @@ -356,6 +355,20 @@ def test_get_file_ids_from_messages_file_field_not_dict(): assert get_file_ids_from_messages(messages) == [] +def test_get_file_ids_from_messages_skips_bare_string_content_items(): + messages = [ + { + "role": "user", + "content": [ + "what type of file is this?", + {"type": "file", "file": {"file_id": "file-abc"}}, + ], + } + ] + + assert get_file_ids_from_messages(messages) == ["file-abc"] + + def test_update_messages_with_model_file_ids_skips_non_openai_file_blocks(): """`update_messages_with_model_file_ids` is also called on user content before provider dispatch. It must tolerate non-OpenAI file blocks the same diff --git a/tests/test_litellm/llms/anthropic/test_anthropic_common_utils.py b/tests/test_litellm/llms/anthropic/test_anthropic_common_utils.py index 945033c5cac..1a21b6d4394 100644 --- a/tests/test_litellm/llms/anthropic/test_anthropic_common_utils.py +++ b/tests/test_litellm/llms/anthropic/test_anthropic_common_utils.py @@ -14,6 +14,7 @@ import json import os import sys from types import SimpleNamespace +from typing import Final from unittest.mock import patch import pytest @@ -2275,3 +2276,72 @@ def test_create_anthropic_model_list_response_lists_ids_as_told(): assert (gpt["id"], gpt["display_name"], gpt["max_input_tokens"]) == ("claude-router-gpt-4o[1m]", "GPT 4o", 1000000) assert (haiku["id"], haiku["display_name"]) == ("claude-haiku-4-5", "claude-haiku-4-5") assert (response["first_id"], response["last_id"]) == ("claude-router-gpt-4o[1m]", "claude-haiku-4-5") + + +class TestMalformedContentListItems: + @pytest.mark.parametrize( + "content", + [ + pytest.param(["what type of file is this?"], id="string_containing_type"), + pytest.param(["how do I set cache_control?"], id="string_containing_cache_control"), + pytest.param([None], id="none_item"), + pytest.param([5], id="int_item"), + pytest.param([["nested"]], id="list_item"), + ], + ) + def test_beta_headers_resolve_for_non_dict_content_items(self, content: list[object]) -> None: + from litellm.llms.anthropic.common_utils import AnthropicModelInfo + + config: Final = AnthropicModelInfo() + messages: Final = [{"role": "user", "content": content}] + + headers: Final = config.validate_environment( + headers={}, + model="claude-sonnet-4-5", + messages=messages, + optional_params={}, + litellm_params={}, + api_key=FAKE_REGULAR_KEY, + ) + + assert headers["x-api-key"] == FAKE_REGULAR_KEY + assert config.is_cache_control_set(messages) is False + assert config.is_pdf_used(messages) is False + + def test_real_content_parts_still_set_their_beta_headers(self) -> None: + from litellm.llms.anthropic.common_utils import AnthropicModelInfo + + config: Final = AnthropicModelInfo() + + assert config.is_pdf_used([{"role": "user", "content": [{"type": "image", "source": {}}]}]) is True + assert config.is_pdf_used([{"role": "user", "content": [{"type": "text", "text": "hi"}]}]) is False + assert ( + config.is_cache_control_set( + [ + { + "role": "user", + "content": [{"type": "text", "text": "hi", "cache_control": {"type": "ephemeral"}}], + } + ] + ) + is True + ) + + def test_mixed_list_keeps_detecting_the_valid_part(self) -> None: + from litellm.llms.anthropic.common_utils import AnthropicModelInfo + + config: Final = AnthropicModelInfo() + messages: Final = [{"role": "user", "content": ["what type of file is this?", {"type": "image", "source": {}}]}] + + assert config.is_pdf_used(messages) is True + + def test_litellm_completion_rejects_bare_string_content_item_as_bad_request(self) -> None: + import litellm + + with pytest.raises(litellm.BadRequestError): + litellm.completion( + model="anthropic/claude-haiku-4-5-20251001", + messages=[{"role": "user", "content": ["what type of file is this?"]}], + api_key=FAKE_REGULAR_KEY, + max_tokens=5, + ) From 7177d3b6d11dc208e2531f05df4df7a1f33b228a Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 22:50:28 +0000 Subject: [PATCH 052/101] feat(rust): add standalone cost calculator (#42604) * feat: add standalone Rust text pricing crate * feat(rust): harden standalone cost calculator --------- Co-authored-by: Yujong Lee --- litellm-rust/Cargo.lock | 8 + litellm-rust/crates/cost/Cargo.toml | 14 + litellm-rust/crates/cost/README.md | 13 + litellm-rust/crates/cost/benches/calculate.rs | 66 +++ litellm-rust/crates/cost/examples/charge.rs | 40 ++ litellm-rust/crates/cost/src/lib.rs | 405 ++++++++++++++++ litellm-rust/crates/cost/tests/calculation.rs | 458 ++++++++++++++++++ .../cost/tests/generate_python_reference.py | 96 ++++ .../crates/cost/tests/python_reference.tsv | 9 + 9 files changed, 1109 insertions(+) create mode 100644 litellm-rust/crates/cost/Cargo.toml create mode 100644 litellm-rust/crates/cost/README.md create mode 100644 litellm-rust/crates/cost/benches/calculate.rs create mode 100644 litellm-rust/crates/cost/examples/charge.rs create mode 100644 litellm-rust/crates/cost/src/lib.rs create mode 100644 litellm-rust/crates/cost/tests/calculation.rs create mode 100644 litellm-rust/crates/cost/tests/generate_python_reference.py create mode 100644 litellm-rust/crates/cost/tests/python_reference.tsv diff --git a/litellm-rust/Cargo.lock b/litellm-rust/Cargo.lock index d9425fc6bd7..f3510000c44 100644 --- a/litellm-rust/Cargo.lock +++ b/litellm-rust/Cargo.lock @@ -2956,6 +2956,14 @@ dependencies = [ "url", ] +[[package]] +name = "litellm-cost" +version = "0.1.0" +dependencies = [ + "criterion", + "proptest", +] + [[package]] name = "litellm-framing" version = "0.1.0" diff --git a/litellm-rust/crates/cost/Cargo.toml b/litellm-rust/crates/cost/Cargo.toml new file mode 100644 index 00000000000..b85f8a8f876 --- /dev/null +++ b/litellm-rust/crates/cost/Cargo.toml @@ -0,0 +1,14 @@ +[package] +name = "litellm-cost" +version = "0.1.0" +edition.workspace = true +license.workspace = true +repository.workspace = true + +[dev-dependencies] +criterion.workspace = true +proptest.workspace = true + +[[bench]] +name = "calculate" +harness = false diff --git a/litellm-rust/crates/cost/README.md b/litellm-rust/crates/cost/README.md new file mode 100644 index 00000000000..ee4722b6438 --- /dev/null +++ b/litellm-rust/crates/cost/README.md @@ -0,0 +1,13 @@ +# litellm-cost + +This crate calculates text token charges from rates and usage supplied by its caller. It is standalone and has no Python bridge or proxy integration + +Call `compile(&pricing)` once for an immutable plan, then `plan.calculate(&request)` for each supported request. `calculate(&pricing, &request)` compiles on each call. A successful result exposes pre-multiplier component costs, selected rates, the multiplier, and derived `input()`, `output()`, and `total()` values + +The caller states whether `prompt_tokens` includes cache tokens. Threshold selection uses total input tokens for either convention and selects one rate for the whole request. Thresholds are sorted when compiled, and duplicate thresholds or tier overrides fail deterministically. `Fast` selects priority rates; unknown tiers use standard rates + +`Rate::Missing`, `Rate::Null`, and `Rate::Value(0.0)` remain distinct. Missing cache rates fall back to the selected input rate, and an absent one-hour write rate falls back to the selected write rate. Missing input or output rates return typed errors, including for zero usage. Python's sparse-entry behavior remains outside this native contract + +The supported off-peak shape is one non-wrapping UTC daily window. The caller supplies the applicable regional multiplier after provider-specific selection. Negative or non-finite rates, ambiguous rules, inconsistent cache counts, incomplete write splits, invalid windows and overflow return errors. Callers must decline unsupported inputs before native execution if their public contract accepts those shapes + +This crate does not select models, read catalogs, fetch provider prices, normalize multimodal usage, process provider-reported costs, or calculate non-token charges. It does not change proxy behavior. The reference fixture was generated by `tests/generate_python_reference.py` against the Python implementation at the commit recorded in `tests/python_reference.tsv`, using synthetic rates and fixed usage diff --git a/litellm-rust/crates/cost/benches/calculate.rs b/litellm-rust/crates/cost/benches/calculate.rs new file mode 100644 index 00000000000..2561b606e6c --- /dev/null +++ b/litellm-rust/crates/cost/benches/calculate.rs @@ -0,0 +1,66 @@ +use criterion::{Criterion, criterion_group, criterion_main}; +use litellm_cost::{ + Pricing, PromptConvention, Rate, Rates, Request, ServiceTier, ThresholdPolicy, ThresholdRates, + Usage, calculate, compile, +}; +use std::hint::black_box; + +fn bench(c: &mut Criterion) { + let pricing = Pricing { + standard: Rates { + input: Rate::Value(0.000002), + output: Rate::Value(0.000008), + cache_read: Rate::Value(0.0000005), + cache_write: Rate::Missing, + cache_write_1h: Rate::Missing, + }, + tiers: &[], + thresholds: &[], + off_peak: None, + }; + let request = Request { + usage: Usage { + prompt_tokens: 1000, + completion_tokens: 200, + cache_read_tokens: 250, + cache_write_tokens: 0, + cache_write_5m_tokens: None, + cache_write_1h_tokens: None, + prompt_convention: PromptConvention::IncludesCache, + }, + service_tier: ServiceTier::Standard, + threshold_policy: ThresholdPolicy::Exclusive, + region_multiplier: None, + billed_at_utc_minute: None, + }; + let plan = compile(&pricing).unwrap(); + c.bench_function("native_compiled_calculation", |b| { + b.iter(|| black_box(plan.calculate(black_box(&request)).unwrap())) + }); + c.bench_function("native_full_wrapper", |b| { + b.iter(|| black_box(calculate(black_box(&pricing), black_box(&request)).unwrap())) + }); + c.bench_function("native_rate_compilation", |b| { + b.iter(|| black_box(compile(black_box(&pricing)).unwrap())) + }); + let threshold = ThresholdRates { + above_prompt_tokens: 1000, + standard: Rates { + input: Rate::Value(0.000004), + output: Rate::Value(0.000016), + ..Rates::EMPTY + }, + tiers: &[], + }; + let threshold_pricing = Pricing { + thresholds: &[threshold], + ..pricing + }; + let threshold_plan = compile(&threshold_pricing).unwrap(); + c.bench_function("native_threshold_boundary", |b| { + b.iter(|| black_box(threshold_plan.calculate(black_box(&request)).unwrap())) + }); +} + +criterion_group!(benches, bench); +criterion_main!(benches); diff --git a/litellm-rust/crates/cost/examples/charge.rs b/litellm-rust/crates/cost/examples/charge.rs new file mode 100644 index 00000000000..a3a83febd74 --- /dev/null +++ b/litellm-rust/crates/cost/examples/charge.rs @@ -0,0 +1,40 @@ +use litellm_cost::{ + Pricing, PromptConvention, Rate, Rates, Request, ServiceTier, ThresholdPolicy, Usage, compile, +}; + +fn main() { + let pricing = Pricing { + standard: Rates { + input: Rate::Value(2.0), + output: Rate::Value(4.0), + cache_read: Rate::Value(0.5), + cache_write: Rate::Value(3.0), + cache_write_1h: Rate::Missing, + }, + tiers: &[], + thresholds: &[], + off_peak: None, + }; + let request = Request { + usage: Usage { + prompt_tokens: 100, + completion_tokens: 20, + cache_read_tokens: 25, + cache_write_tokens: 10, + cache_write_5m_tokens: None, + cache_write_1h_tokens: None, + prompt_convention: PromptConvention::IncludesCache, + }, + service_tier: ServiceTier::Standard, + threshold_policy: ThresholdPolicy::Exclusive, + region_multiplier: None, + billed_at_utc_minute: None, + }; + let cost = compile(&pricing).unwrap().calculate(&request).unwrap(); + println!( + "input={} output={} total={}", + cost.input(), + cost.output(), + cost.total() + ); +} diff --git a/litellm-rust/crates/cost/src/lib.rs b/litellm-rust/crates/cost/src/lib.rs new file mode 100644 index 00000000000..32cc755ce15 --- /dev/null +++ b/litellm-rust/crates/cost/src/lib.rs @@ -0,0 +1,405 @@ +#[derive(Clone, Copy, Debug, PartialEq)] +pub enum Rate { + Missing, + Null, + Value(f64), +} + +impl Rate { + fn value(self) -> Option { + match self { + Self::Value(value) => Some(value), + Self::Missing | Self::Null => None, + } + } + + fn or(self, fallback: Self) -> Self { + if self.value().is_some() { + self + } else { + fallback + } + } +} + +#[derive(Clone, Copy, Debug, PartialEq)] +pub struct Rates { + pub input: Rate, + pub output: Rate, + pub cache_read: Rate, + pub cache_write: Rate, + pub cache_write_1h: Rate, +} + +impl Rates { + pub const EMPTY: Self = Self { + input: Rate::Missing, + output: Rate::Missing, + cache_read: Rate::Missing, + cache_write: Rate::Missing, + cache_write_1h: Rate::Missing, + }; + + fn overlay(self, base: Self) -> Self { + Self { + input: self.input.or(base.input), + output: self.output.or(base.output), + cache_read: self.cache_read.or(base.cache_read), + cache_write: self.cache_write.or(base.cache_write), + cache_write_1h: self.cache_write_1h.or(base.cache_write_1h), + } + } +} + +#[derive(Clone, Copy, Debug, Eq, PartialEq)] +pub enum ServiceTier { + Standard, + Flex, + Priority, + Fast, + Ultrafast, + Unknown, +} + +#[derive(Clone, Copy, Debug, Eq, PartialEq)] +pub enum ThresholdPolicy { + Exclusive, + Inclusive, +} + +#[derive(Clone, Copy, Debug, Eq, PartialEq)] +pub enum PromptConvention { + IncludesCache, + ExcludesCache, +} + +#[derive(Clone, Copy, Debug, PartialEq)] +pub struct Usage { + pub prompt_tokens: u64, + pub completion_tokens: u64, + pub cache_read_tokens: u64, + pub cache_write_tokens: u64, + pub cache_write_5m_tokens: Option, + pub cache_write_1h_tokens: Option, + pub prompt_convention: PromptConvention, +} + +#[derive(Clone, Copy, Debug, PartialEq)] +pub struct TierRates { + pub tier: ServiceTier, + pub rates: Rates, +} + +#[derive(Clone, Copy, Debug, PartialEq)] +pub struct ThresholdRates<'a> { + pub above_prompt_tokens: u64, + pub standard: Rates, + pub tiers: &'a [TierRates], +} + +#[derive(Clone, Copy, Debug, PartialEq)] +pub struct OffPeakRates { + pub start_utc_minute: u16, + pub end_utc_minute: u16, + pub rates: Rates, +} + +#[derive(Clone, Copy, Debug, PartialEq)] +pub struct Pricing<'a> { + pub standard: Rates, + pub tiers: &'a [TierRates], + pub thresholds: &'a [ThresholdRates<'a>], + pub off_peak: Option, +} + +#[derive(Clone, Copy, Debug, PartialEq)] +pub struct Request { + pub usage: Usage, + pub service_tier: ServiceTier, + pub threshold_policy: ThresholdPolicy, + pub region_multiplier: Option, + pub billed_at_utc_minute: Option, +} + +#[derive(Clone, Copy, Debug, PartialEq)] +pub struct Cost { + pub uncached_input: f64, + pub cache_read: f64, + pub cache_write_5m: f64, + pub cache_write_1h: f64, + pub output: f64, + pub multiplier: f64, + pub rates: EffectiveRates, +} + +impl Cost { + pub fn input(self) -> f64 { + (self.uncached_input + self.cache_read + self.cache_write_5m + self.cache_write_1h) + * self.multiplier + } + + pub fn output(self) -> f64 { + self.output * self.multiplier + } + + pub fn total(self) -> f64 { + self.input() + self.output() + } +} + +#[derive(Clone, Copy, Debug, PartialEq)] +pub struct EffectiveRates { + pub input: f64, + pub output: f64, + pub cache_read: f64, + pub cache_write_5m: f64, + pub cache_write_1h: f64, +} + +#[derive(Clone, Copy, Debug, Eq, PartialEq)] +pub enum PricingError { + MissingInputRate, + MissingOutputRate, + InvalidRate, + InvalidRegionMultiplier, + InvalidBillingTime, + InvalidOffPeakWindow, + CacheExceedsPrompt, + InvalidCacheWriteDetails, + TokenCountOverflow, + DuplicateTier, + DuplicateThreshold, + DuplicateThresholdTier, +} + +fn selected_tier(tier: ServiceTier) -> ServiceTier { + if tier == ServiceTier::Fast { + ServiceTier::Priority + } else { + tier + } +} + +#[derive(Clone, Debug)] +struct CompiledThreshold { + above_prompt_tokens: u64, + standard: Rates, + tiers: Vec, +} + +#[derive(Clone, Debug)] +pub struct PricingPlan { + standard: Rates, + tiers: Vec, + thresholds: Vec, + off_peak: Option, +} + +fn valid_rates(rates: Rates) -> bool { + [ + rates.input, + rates.output, + rates.cache_read, + rates.cache_write, + rates.cache_write_1h, + ] + .into_iter() + .all(|rate| { + rate.value() + .is_none_or(|value| value.is_finite() && value >= 0.0) + }) +} + +fn validate_tiers(tiers: &[TierRates], duplicate: PricingError) -> Result<(), PricingError> { + if tiers.iter().any(|entry| !valid_rates(entry.rates)) { + return Err(PricingError::InvalidRate); + } + if tiers.iter().enumerate().any(|(index, entry)| { + matches!( + entry.tier, + ServiceTier::Standard | ServiceTier::Unknown | ServiceTier::Fast + ) || tiers[..index] + .iter() + .any(|previous| previous.tier == entry.tier) + }) { + return Err(duplicate); + } + Ok(()) +} + +pub fn compile(pricing: &Pricing<'_>) -> Result { + if !valid_rates(pricing.standard) { + return Err(PricingError::InvalidRate); + } + validate_tiers(pricing.tiers, PricingError::DuplicateTier)?; + if let Some(window) = pricing.off_peak { + if window.start_utc_minute >= 1440 + || window.end_utc_minute > 1440 + || window.start_utc_minute >= window.end_utc_minute + { + return Err(PricingError::InvalidOffPeakWindow); + } + if !valid_rates(window.rates) { + return Err(PricingError::InvalidRate); + } + } + let mut thresholds: Vec<_> = pricing + .thresholds + .iter() + .map(|entry| { + if !valid_rates(entry.standard) { + return Err(PricingError::InvalidRate); + } + validate_tiers(entry.tiers, PricingError::DuplicateThresholdTier)?; + Ok(CompiledThreshold { + above_prompt_tokens: entry.above_prompt_tokens, + standard: entry.standard, + tiers: entry.tiers.to_vec(), + }) + }) + .collect::>()?; + thresholds.sort_unstable_by_key(|entry| entry.above_prompt_tokens); + if thresholds + .windows(2) + .any(|pair| pair[0].above_prompt_tokens == pair[1].above_prompt_tokens) + { + return Err(PricingError::DuplicateThreshold); + } + Ok(PricingPlan { + standard: pricing.standard, + tiers: pricing.tiers.to_vec(), + thresholds, + off_peak: pricing.off_peak, + }) +} + +impl PricingPlan { + fn resolve_rates( + &self, + request: &Request, + threshold_tokens: u64, + ) -> Result { + let tier = selected_tier(request.service_tier); + let base = self + .tiers + .iter() + .find(|entry| tier != ServiceTier::Standard && entry.tier == tier) + .map_or(self.standard, |entry| entry.rates.overlay(self.standard)); + let threshold = self.thresholds.iter().rev().find(|entry| { + threshold_tokens > entry.above_prompt_tokens + || (request.threshold_policy == ThresholdPolicy::Inclusive + && threshold_tokens == entry.above_prompt_tokens) + }); + let selected = threshold.map_or(base, |entry| { + let standard = entry.standard.overlay(base); + entry + .tiers + .iter() + .find(|specific| tier != ServiceTier::Standard && specific.tier == tier) + .map_or(standard, |specific| specific.rates.overlay(standard)) + }); + match self.off_peak { + None => Ok(selected), + Some(window) => { + if window.start_utc_minute >= 1440 + || window.end_utc_minute > 1440 + || window.start_utc_minute >= window.end_utc_minute + { + return Err(PricingError::InvalidOffPeakWindow); + } + let minute = request + .billed_at_utc_minute + .ok_or(PricingError::InvalidBillingTime)?; + if minute >= 1440 { + return Err(PricingError::InvalidBillingTime); + } + if (window.start_utc_minute..window.end_utc_minute).contains(&minute) { + Ok(window.rates.overlay(selected)) + } else { + Ok(selected) + } + } + } + } + + fn checked_rate(rate: Rate, missing: PricingError) -> Result { + let value = rate.value().ok_or(missing)?; + if !value.is_finite() || value < 0.0 { + return Err(PricingError::InvalidRate); + } + Ok(value) + } + + pub fn calculate(&self, request: &Request) -> Result { + let usage = request.usage; + let cached = usage + .cache_read_tokens + .checked_add(usage.cache_write_tokens) + .ok_or(PricingError::TokenCountOverflow)?; + let (regular, threshold_tokens) = match usage.prompt_convention { + PromptConvention::IncludesCache => ( + usage + .prompt_tokens + .checked_sub(cached) + .ok_or(PricingError::CacheExceedsPrompt)?, + usage.prompt_tokens, + ), + PromptConvention::ExcludesCache => ( + usage.prompt_tokens, + usage + .prompt_tokens + .checked_add(cached) + .ok_or(PricingError::TokenCountOverflow)?, + ), + }; + let writes = match (usage.cache_write_5m_tokens, usage.cache_write_1h_tokens) { + (None, None) => (usage.cache_write_tokens, 0), + (Some(five), Some(one)) if five.checked_add(one) == Some(usage.cache_write_tokens) => { + (five, one) + } + _ => return Err(PricingError::InvalidCacheWriteDetails), + }; + let rates = self.resolve_rates(request, threshold_tokens)?; + let input = Self::checked_rate(rates.input, PricingError::MissingInputRate)?; + let output = Self::checked_rate(rates.output, PricingError::MissingOutputRate)?; + let read = Self::checked_rate( + rates.cache_read.or(rates.input), + PricingError::MissingInputRate, + )?; + let write = Self::checked_rate( + rates.cache_write.or(rates.input), + PricingError::MissingInputRate, + )?; + let write_1h = Self::checked_rate( + rates.cache_write_1h.or(rates.cache_write).or(rates.input), + PricingError::MissingInputRate, + )?; + let multiplier = request.region_multiplier.unwrap_or(1.0); + if !multiplier.is_finite() || multiplier <= 0.0 { + return Err(PricingError::InvalidRegionMultiplier); + } + let cost = Cost { + uncached_input: regular as f64 * input, + cache_read: usage.cache_read_tokens as f64 * read, + cache_write_5m: writes.0 as f64 * write, + cache_write_1h: writes.1 as f64 * write_1h, + output: usage.completion_tokens as f64 * output, + multiplier, + rates: EffectiveRates { + input, + output, + cache_read: read, + cache_write_5m: write, + cache_write_1h: write_1h, + }, + }; + if !cost.total().is_finite() { + return Err(PricingError::TokenCountOverflow); + } + Ok(cost) + } +} + +pub fn calculate(pricing: &Pricing<'_>, request: &Request) -> Result { + compile(pricing)?.calculate(request) +} diff --git a/litellm-rust/crates/cost/tests/calculation.rs b/litellm-rust/crates/cost/tests/calculation.rs new file mode 100644 index 00000000000..8cd06e74ec8 --- /dev/null +++ b/litellm-rust/crates/cost/tests/calculation.rs @@ -0,0 +1,458 @@ +use litellm_cost::{ + OffPeakRates, Pricing, PricingError, PromptConvention, Rate, Rates, Request, ServiceTier, + ThresholdPolicy, ThresholdRates, TierRates, Usage, calculate, compile, +}; + +fn rates(input: Rate, output: Rate) -> Rates { + Rates { + input, + output, + ..Rates::EMPTY + } +} + +fn request() -> Request { + Request { + usage: Usage { + prompt_tokens: 100, + completion_tokens: 20, + cache_read_tokens: 25, + cache_write_tokens: 10, + cache_write_5m_tokens: None, + cache_write_1h_tokens: None, + prompt_convention: PromptConvention::IncludesCache, + }, + service_tier: ServiceTier::Standard, + threshold_policy: ThresholdPolicy::Exclusive, + region_multiplier: None, + billed_at_utc_minute: None, + } +} + +fn pricing(standard: Rates) -> Pricing<'static> { + Pricing { + standard, + tiers: &[], + thresholds: &[], + off_peak: None, + } +} + +#[test] +fn breakdown_and_total_agree() { + let standard = Rates { + cache_read: Rate::Value(0.5), + cache_write: Rate::Value(3.0), + ..rates(Rate::Value(2.0), Rate::Value(4.0)) + }; + let result = calculate(&pricing(standard), &request()).unwrap(); + assert_eq!(result.uncached_input, 65.0 * 2.0); + assert_eq!(result.cache_read, 25.0 * 0.5); + assert_eq!(result.cache_write_5m, 10.0 * 3.0); + assert_eq!(result.output(), 20.0 * 4.0); + assert_eq!(result.total(), result.input() + result.output()); + assert_eq!(result.rates.cache_read, 0.5); +} + +#[test] +fn absent_null_and_zero_cache_rates_are_distinct() { + let base = rates(Rate::Value(2.0), Rate::Value(4.0)); + for read in [Rate::Missing, Rate::Null] { + let standard = Rates { + cache_read: read, + ..base + }; + assert_eq!( + calculate(&pricing(standard), &request()).unwrap().input(), + 200.0 + ); + } + let standard = Rates { + cache_read: Rate::Value(0.0), + cache_write: Rate::Value(0.0), + ..base + }; + assert_eq!( + calculate(&pricing(standard), &request()).unwrap().input(), + 130.0 + ); +} + +#[test] +fn equivalent_prompt_conventions_select_the_same_threshold() { + let threshold = ThresholdRates { + above_prompt_tokens: 90, + standard: rates(Rate::Value(5.0), Rate::Value(8.0)), + tiers: &[], + }; + let specification = Pricing { + standard: rates(Rate::Value(2.0), Rate::Value(4.0)), + tiers: &[], + thresholds: &[threshold], + off_peak: None, + }; + let included = request(); + let excluded = Request { + usage: Usage { + prompt_tokens: 65, + prompt_convention: PromptConvention::ExcludesCache, + ..included.usage + }, + ..included + }; + let plan = compile(&specification).unwrap(); + assert_eq!(plan.calculate(&included), plan.calculate(&excluded)); + assert_eq!(plan.calculate(&included).unwrap().rates.input, 5.0); +} + +#[test] +fn split_writes_and_invalid_accounting() { + let standard = Rates { + cache_read: Rate::Value(0.5), + cache_write: Rate::Value(3.0), + cache_write_1h: Rate::Value(5.0), + ..rates(Rate::Value(2.0), Rate::Value(4.0)) + }; + let base = request(); + let split = Request { + usage: Usage { + cache_write_5m_tokens: Some(4), + cache_write_1h_tokens: Some(6), + ..base.usage + }, + ..base + }; + let result = calculate(&pricing(standard), &split).unwrap(); + assert_eq!(result.cache_write_5m, 12.0); + assert_eq!(result.cache_write_1h, 30.0); + let overlapping = Request { + usage: Usage { + prompt_tokens: 30, + ..split.usage + }, + ..split + }; + assert_eq!( + calculate(&pricing(standard), &overlapping), + Err(PricingError::CacheExceedsPrompt) + ); + let incomplete = Request { + usage: Usage { + cache_write_1h_tokens: None, + ..split.usage + }, + ..split + }; + assert_eq!( + calculate(&pricing(standard), &incomplete), + Err(PricingError::InvalidCacheWriteDetails) + ); +} + +#[test] +fn threshold_tiers_and_boundaries() { + let priority = TierRates { + tier: ServiceTier::Priority, + rates: rates(Rate::Value(3.0), Rate::Missing), + }; + let threshold = ThresholdRates { + above_prompt_tokens: 100, + standard: rates(Rate::Value(5.0), Rate::Value(8.0)), + tiers: &[ + TierRates { + tier: ServiceTier::Priority, + rates: rates(Rate::Value(7.0), Rate::Missing), + }, + TierRates { + tier: ServiceTier::Flex, + rates: rates(Rate::Value(6.0), Rate::Missing), + }, + ], + }; + let specification = Pricing { + standard: rates(Rate::Value(2.0), Rate::Value(4.0)), + tiers: &[priority], + thresholds: &[threshold], + off_peak: None, + }; + let base = request(); + let no_cache = Request { + usage: Usage { + cache_read_tokens: 0, + cache_write_tokens: 0, + ..base.usage + }, + ..base + }; + let fast = Request { + service_tier: ServiceTier::Fast, + ..no_cache + }; + let inclusive = Request { + threshold_policy: ThresholdPolicy::Inclusive, + ..fast + }; + let flex = Request { + service_tier: ServiceTier::Flex, + ..inclusive + }; + assert_eq!(calculate(&specification, &no_cache).unwrap().input(), 200.0); + assert_eq!(calculate(&specification, &fast).unwrap().input(), 300.0); + assert_eq!( + calculate(&specification, &inclusive).unwrap().input(), + 700.0 + ); + assert_eq!(calculate(&specification, &flex).unwrap().input(), 600.0); +} + +#[test] +fn compile_rejects_ambiguous_rates() { + let duplicate = ThresholdRates { + above_prompt_tokens: 100, + standard: Rates::EMPTY, + tiers: &[], + }; + let specification = Pricing { + standard: rates(Rate::Value(1.0), Rate::Value(1.0)), + tiers: &[], + thresholds: &[duplicate, duplicate], + off_peak: None, + }; + assert_eq!( + compile(&specification).err(), + Some(PricingError::DuplicateThreshold) + ); + let invalid = pricing(rates(Rate::Value(f64::NAN), Rate::Value(1.0))); + assert_eq!(compile(&invalid).err(), Some(PricingError::InvalidRate)); +} + +#[test] +fn off_peak_is_one_non_wrapping_utc_window() { + let specification = Pricing { + standard: rates(Rate::Value(2.0), Rate::Value(4.0)), + tiers: &[], + thresholds: &[], + off_peak: Some(OffPeakRates { + start_utc_minute: 60, + end_utc_minute: 120, + rates: rates(Rate::Value(1.0), Rate::Value(2.0)), + }), + }; + let base = request(); + let start = Request { + billed_at_utc_minute: Some(60), + ..base + }; + let end = Request { + billed_at_utc_minute: Some(120), + ..base + }; + assert_eq!( + calculate(&specification, &base), + Err(PricingError::InvalidBillingTime) + ); + assert_eq!(calculate(&specification, &start).unwrap().input(), 100.0); + assert_eq!(calculate(&specification, &end).unwrap().input(), 200.0); +} + +#[test] +fn missing_rates_and_free_rates_remain_distinct() { + let base = request(); + let empty = Request { + usage: Usage { + prompt_tokens: 0, + completion_tokens: 0, + cache_read_tokens: 0, + cache_write_tokens: 0, + ..base.usage + }, + ..base + }; + assert_eq!( + calculate(&pricing(Rates::EMPTY), &empty), + Err(PricingError::MissingInputRate) + ); + assert_eq!( + calculate(&pricing(rates(Rate::Value(0.0), Rate::Missing)), &empty), + Err(PricingError::MissingOutputRate) + ); + assert_eq!( + calculate(&pricing(rates(Rate::Value(0.0), Rate::Value(0.0))), &empty) + .unwrap() + .total(), + 0.0 + ); +} + +#[test] +fn matches_executed_python_reference_cases() { + for row in include_str!("python_reference.tsv") + .lines() + .filter(|line| !line.starts_with('#')) + { + let fields: Vec<_> = row.split('\t').collect(); + let count = |index: usize| fields[index].parse::().unwrap(); + let number = |index: usize| fields[index].parse::().unwrap(); + let optional_rate = |index: usize| { + if fields[index].is_empty() { + Rate::Missing + } else { + Rate::Value(number(index)) + } + }; + let threshold = ThresholdRates { + above_prompt_tokens: if fields[9].is_empty() { 0 } else { count(9) }, + standard: rates(optional_rate(10), optional_rate(11)), + tiers: &[], + }; + let thresholds = if fields[9].is_empty() { + &[][..] + } else { + std::slice::from_ref(&threshold) + }; + let specification = Pricing { + standard: Rates { + cache_read: optional_rate(7), + cache_write: optional_rate(8), + ..rates(Rate::Value(number(5)), Rate::Value(number(6))) + }, + tiers: &[], + thresholds, + off_peak: None, + }; + let base = request(); + let input = Request { + usage: Usage { + prompt_tokens: count(1), + completion_tokens: count(2), + cache_read_tokens: count(3), + cache_write_tokens: count(4), + ..base.usage + }, + ..base + }; + let actual = calculate(&specification, &input).unwrap(); + assert_eq!(actual.input(), number(12), "{}", fields[0]); + assert_eq!(actual.output(), number(13), "{}", fields[0]); + } +} + +proptest::proptest! { + #[test] + fn equivalent_usage_conventions_and_breakdown_agree( + regular in 0_u64..1000, + read in 0_u64..1000, + write in 0_u64..1000, + output in 0_u64..1000, + ) { + let threshold = ThresholdRates { + above_prompt_tokens: 1000, + standard: rates(Rate::Value(5.0), Rate::Value(8.0)), + tiers: &[], + }; + let specification = Pricing { + standard: rates(Rate::Value(2.0), Rate::Value(4.0)), + tiers: &[], + thresholds: &[threshold], + off_peak: None, + }; + let base = request(); + let included = Request { + usage: Usage { + prompt_tokens: regular + read + write, + completion_tokens: output, + cache_read_tokens: read, + cache_write_tokens: write, + ..base.usage + }, + ..base + }; + let excluded = Request { + usage: Usage { + prompt_tokens: regular, + prompt_convention: PromptConvention::ExcludesCache, + ..included.usage + }, + ..included + }; + let plan = compile(&specification).unwrap(); + let left = plan.calculate(&included).unwrap(); + let right = plan.calculate(&excluded).unwrap(); + proptest::prop_assert_eq!(left, right); + proptest::prop_assert_eq!(left.total(), left.input() + left.output()); + } +} + +#[test] +fn regional_multiplier_applies_after_input_components_are_summed() { + let standard = Rates { + cache_read: Rate::Value(0.5), + cache_write: Rate::Value(3.0), + ..rates(Rate::Value(2.0), Rate::Value(4.0)) + }; + let base = request(); + let regional = Request { + region_multiplier: Some(1.1), + ..base + }; + let result = calculate(&pricing(standard), ®ional).unwrap(); + assert_eq!(result.input(), (65.0 * 2.0 + 25.0 * 0.5 + 10.0 * 3.0) * 1.1); + assert_eq!(result.output(), 20.0 * 4.0 * 1.1); + let invalid = Request { + region_multiplier: Some(f64::NAN), + ..base + }; + assert_eq!( + calculate(&pricing(standard), &invalid), + Err(PricingError::InvalidRegionMultiplier) + ); +} + +#[test] +fn compilation_sorts_thresholds_and_rejects_duplicate_tiers() { + let high = ThresholdRates { + above_prompt_tokens: 200, + standard: rates(Rate::Value(7.0), Rate::Missing), + tiers: &[], + }; + let low = ThresholdRates { + above_prompt_tokens: 100, + standard: rates(Rate::Value(5.0), Rate::Missing), + tiers: &[], + }; + let specification = Pricing { + standard: rates(Rate::Value(2.0), Rate::Value(4.0)), + tiers: &[], + thresholds: &[high, low], + off_peak: None, + }; + let base = request(); + let above_both = Request { + usage: Usage { + prompt_tokens: 201, + cache_read_tokens: 0, + cache_write_tokens: 0, + ..base.usage + }, + ..base + }; + assert_eq!( + compile(&specification) + .unwrap() + .calculate(&above_both) + .unwrap() + .rates + .input, + 7.0 + ); + let duplicate = TierRates { + tier: ServiceTier::Flex, + rates: Rates::EMPTY, + }; + let invalid = Pricing { + tiers: &[duplicate, duplicate], + thresholds: &[], + ..specification + }; + assert_eq!(compile(&invalid).err(), Some(PricingError::DuplicateTier)); +} diff --git a/litellm-rust/crates/cost/tests/generate_python_reference.py b/litellm-rust/crates/cost/tests/generate_python_reference.py new file mode 100644 index 00000000000..4a179555650 --- /dev/null +++ b/litellm-rust/crates/cost/tests/generate_python_reference.py @@ -0,0 +1,96 @@ +import subprocess +from dataclasses import dataclass +from pathlib import Path + +from litellm.litellm_core_utils.llm_cost_calc.utils import generic_cost_per_token +from litellm.types.utils import Usage + + +@dataclass(frozen=True, slots=True) +class Case: + name: str + prompt: int + completion: int + cache_read: int + cache_write: int + input_rate: float + output_rate: float + cache_read_rate: float | None = None + cache_write_rate: float | None = None + threshold: int | None = None + threshold_input_rate: float | None = None + threshold_output_rate: float | None = None + + +CASES = ( + Case("ordinary", 100, 20, 0, 0, 2.0, 4.0), + Case("cache_fallback", 100, 20, 25, 10, 2.0, 4.0), + Case("cache_specific", 100, 20, 25, 10, 2.0, 4.0, 0.5, 3.0), + Case("free_cache", 100, 20, 25, 10, 2.0, 4.0, 0.0, 0.0), + Case("threshold_below", 99, 20, 0, 0, 2.0, 4.0, threshold=100, threshold_input_rate=5.0, threshold_output_rate=8.0), + Case("threshold_at", 100, 20, 0, 0, 2.0, 4.0, threshold=100, threshold_input_rate=5.0, threshold_output_rate=8.0), + Case( + "threshold_above", 101, 20, 0, 0, 2.0, 4.0, threshold=100, threshold_input_rate=5.0, threshold_output_rate=8.0 + ), + Case( + "cache_threshold_above", + 101, + 20, + 25, + 10, + 2.0, + 4.0, + threshold=100, + threshold_input_rate=5.0, + threshold_output_rate=8.0, + ), +) + + +def reference(case: Case) -> tuple[float, float]: + info = {"input_cost_per_token": case.input_rate, "output_cost_per_token": case.output_rate} + if case.cache_read_rate is not None: + info["cache_read_input_token_cost"] = case.cache_read_rate + if case.cache_write_rate is not None: + info["cache_creation_input_token_cost"] = case.cache_write_rate + if case.threshold is not None: + info[f"input_cost_per_token_above_{case.threshold}_tokens"] = case.threshold_input_rate + info[f"output_cost_per_token_above_{case.threshold}_tokens"] = case.threshold_output_rate + details = {"cached_tokens": case.cache_read, "cache_write_tokens": case.cache_write} + usage = Usage(prompt_tokens=case.prompt, completion_tokens=case.completion, prompt_tokens_details=details) + return generic_cost_per_token( + model="synthetic", + usage=usage, + custom_llm_provider="openai", + model_info=info, + ) + + +def main() -> None: + revision = subprocess.check_output(("git", "rev-parse", "HEAD"), text=True).strip() + rows = ("# Python reference commit: " + revision,) + tuple( + "\t".join( + str(value) if value is not None else "" + for value in ( + case.name, + case.prompt, + case.completion, + case.cache_read, + case.cache_write, + case.input_rate, + case.output_rate, + case.cache_read_rate, + case.cache_write_rate, + case.threshold, + case.threshold_input_rate, + case.threshold_output_rate, + *reference(case), + ) + ) + for case in CASES + ) + Path(__file__).with_name("python_reference.tsv").write_text("\n".join(rows) + "\n") + + +if __name__ == "__main__": + main() diff --git a/litellm-rust/crates/cost/tests/python_reference.tsv b/litellm-rust/crates/cost/tests/python_reference.tsv new file mode 100644 index 00000000000..5abb1329a61 --- /dev/null +++ b/litellm-rust/crates/cost/tests/python_reference.tsv @@ -0,0 +1,9 @@ +# Python reference commit: dc4be2fd987c993aefcf16444e34f960c12c8627 +ordinary 100 20 0 0 2.0 4.0 200.0 80.0 +cache_fallback 100 20 25 10 2.0 4.0 200.0 80.0 +cache_specific 100 20 25 10 2.0 4.0 0.5 3.0 172.5 80.0 +free_cache 100 20 25 10 2.0 4.0 0.0 0.0 130.0 80.0 +threshold_below 99 20 0 0 2.0 4.0 100 5.0 8.0 198.0 80.0 +threshold_at 100 20 0 0 2.0 4.0 100 5.0 8.0 200.0 80.0 +threshold_above 101 20 0 0 2.0 4.0 100 5.0 8.0 505.0 160.0 +cache_threshold_above 101 20 25 10 2.0 4.0 100 5.0 8.0 505.0 160.0 From 392e80717200b36b083ce859c866af75d7721569 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 15:56:50 -0700 Subject: [PATCH 053/101] feat(logging): add normalized_error cluster key to error_information (#41715) * feat(logging): add normalized_error cluster key to error_information Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(logging): stop classifying parameter length errors as context window errors Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(e2e): assert failure spend rows share normalized_error across provider wording Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(logging): map agent model access denials and ignore non-string proxy error types Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(logging): cover budget exceeded errors with custom wording Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(logging): cluster router no-healthy and provider-budget wording correctly Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(logging): let the exception class win over router fallback wording Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(logging): cluster peer closed connection errors as provider connection errors Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(logging): cluster tag routing denials as 403_MODEL_ACCESS_DENIED Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: shivam Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> Co-authored-by: yucheng --- .../litellm_core_utils/error_normalization.py | 195 +++++++++++++++ litellm/litellm_core_utils/litellm_logging.py | 2 + litellm/types/utils.py | 1 + .../coverage_registry/quota_management.yaml | 1 + tests/e2e/models.py | 8 + .../spend_tracking/test_spend_tracking_e2e.py | 41 ++++ .../test_error_normalization.py | 231 ++++++++++++++++++ 7 files changed, 479 insertions(+) create mode 100644 litellm/litellm_core_utils/error_normalization.py create mode 100644 tests/test_litellm/litellm_core_utils/test_error_normalization.py diff --git a/litellm/litellm_core_utils/error_normalization.py b/litellm/litellm_core_utils/error_normalization.py new file mode 100644 index 00000000000..2a9ff748899 --- /dev/null +++ b/litellm/litellm_core_utils/error_normalization.py @@ -0,0 +1,195 @@ +""" +Map any exception litellm logs to one stable ``normalized_error`` code so dashboards can cluster +failures without parsing free-text messages that embed team names, token counts, model names, etc. +""" + +import re +from collections.abc import Mapping +from types import MappingProxyType +from typing import Final, Protocol, runtime_checkable + +from litellm.exceptions import ( + APIConnectionError, + AuthenticationError, + BadGatewayError, + BadRequestError, + BlockedPiiEntityError, + BudgetExceededError, + ContentPolicyViolationError, + ContextWindowExceededError, + GuardrailRaisedException, + InternalServerError, + MidStreamFallbackError, + NotFoundError, + PermissionDeniedError, + RateLimitError, + RateLimitType, + ServiceUnavailableError, + Timeout, + UnprocessableEntityError, + UnsupportedParamsError, +) + +RATE_LIMIT_EXCEEDED: Final = "429_RATE_LIMIT_EXCEEDED" +BUDGET_EXCEEDED: Final = "429_BUDGET_EXCEEDED" +NO_HEALTHY_DEPLOYMENTS: Final = "429_NO_HEALTHY_DEPLOYMENTS" +AUTHENTICATION_FAILED: Final = "401_AUTHENTICATION_FAILED" +MODEL_ACCESS_DENIED: Final = "403_MODEL_ACCESS_DENIED" +PERMISSION_DENIED: Final = "403_PERMISSION_DENIED" +MISSING_REQUIRED_PARAMETER: Final = "400_MISSING_REQUIRED_PARAMETER" +INVALID_PARAMETER_VALUE: Final = "400_INVALID_PARAMETER_VALUE" +CONTEXT_WINDOW_EXCEEDED: Final = "400_CONTEXT_WINDOW_EXCEEDED" +CONTENT_POLICY_VIOLATION: Final = "400_CONTENT_POLICY_VIOLATION" +INVALID_REQUEST: Final = "400_INVALID_REQUEST" +RESOURCE_NOT_FOUND: Final = "404_RESOURCE_NOT_FOUND" +UPSTREAM_TIMEOUT: Final = "408_UPSTREAM_TIMEOUT" +PROVIDER_CONNECTION_ERROR: Final = "500_PROVIDER_CONNECTION_ERROR" +PROVIDER_OVERLOADED: Final = "503_PROVIDER_OVERLOADED" +PROVIDER_INTERNAL_ERROR: Final = "500_PROVIDER_INTERNAL_ERROR" +ROUTER_NO_FALLBACK: Final = "500_ROUTER_NO_FALLBACK" +ROUTER_FALLBACK_FAILURE: Final = "500_ROUTER_FALLBACK_FAILURE" +UPSTREAM_PASSTHROUGH: Final = "500_UPSTREAM_PASSTHROUGH" +UNSUPPORTED_OPERATION: Final = "500_UNSUPPORTED_OPERATION" +INTERNAL_STATE_ERROR: Final = "500_INTERNAL_STATE_ERROR" +UNCLASSIFIED: Final = "UNCLASSIFIED" + + +@runtime_checkable +class _HasProxyErrorType(Protocol): + type: str + + +_MESSAGE_PATTERNS: Final[tuple[tuple[re.Pattern[str], str], ...]] = ( + ( + re.compile(r"budget has been exceeded|max budget|exceeded.*budget|crossed budget", re.IGNORECASE), + BUDGET_EXCEEDED, + ), + (re.compile(r"no healthy deployments?|no deployments available", re.IGNORECASE), NO_HEALTHY_DEPLOYMENTS), + (re.compile(r"not allowed to access model due to tags configuration", re.IGNORECASE), MODEL_ACCESS_DENIED), + (re.compile(r"upstream passthrough request failed", re.IGNORECASE), UPSTREAM_PASSTHROUGH), + (re.compile(r"is not supported for provider|not implemented", re.IGNORECASE), UNSUPPORTED_OPERATION), + ( + re.compile(r"context window|context length|(prompt|input) is too long|tokens? ?> ?\d+ ?maximum", re.IGNORECASE), + CONTEXT_WINDOW_EXCEEDED, + ), + (re.compile(r"missing required parameter|field required", re.IGNORECASE), MISSING_REQUIRED_PARAMETER), + (re.compile(r"overloaded|unable to process your request", re.IGNORECASE), PROVIDER_OVERLOADED), + ( + re.compile( + r"connection error|APIConnectionError|TransferEncodingError|payload is not completed|connection reset" + r"|peer closed connection|incomplete chunked read", + re.IGNORECASE, + ), + PROVIDER_CONNECTION_ERROR, + ), + (re.compile(r"timed? ?out", re.IGNORECASE), UPSTREAM_TIMEOUT), +) + +_ROUTER_WRAPPER_PATTERNS: Final[tuple[tuple[re.Pattern[str], str], ...]] = ( + (re.compile(r"no fallback model group found", re.IGNORECASE), ROUTER_NO_FALLBACK), + (re.compile(r"error doing the fallback|MidStreamFallbackError", re.IGNORECASE), ROUTER_FALLBACK_FAILURE), +) + +_PROXY_ERROR_TYPE_MAP: Final[Mapping[str, str]] = MappingProxyType( + { + "budget_exceeded": BUDGET_EXCEEDED, + "auth_error": AUTHENTICATION_FAILED, + "expired_key": AUTHENTICATION_FAILED, + "token_not_found_in_db": AUTHENTICATION_FAILED, + "auth_provider_unavailable": AUTHENTICATION_FAILED, + "key_model_access_denied": MODEL_ACCESS_DENIED, + "team_model_access_denied": MODEL_ACCESS_DENIED, + "user_model_access_denied": MODEL_ACCESS_DENIED, + "org_model_access_denied": MODEL_ACCESS_DENIED, + "project_model_access_denied": MODEL_ACCESS_DENIED, + "agent_model_access_denied": MODEL_ACCESS_DENIED, + "key_vector_store_access_denied": PERMISSION_DENIED, + "team_vector_store_access_denied": PERMISSION_DENIED, + "org_vector_store_access_denied": PERMISSION_DENIED, + "tool_access_denied": PERMISSION_DENIED, + "team_member_permission_error": PERMISSION_DENIED, + "not_found_error": RESOURCE_NOT_FOUND, + } +) + +_STATUS_CODE_MAP: Final[Mapping[str, str]] = MappingProxyType( + { + "400": INVALID_REQUEST, + "401": AUTHENTICATION_FAILED, + "403": PERMISSION_DENIED, + "404": RESOURCE_NOT_FOUND, + "408": UPSTREAM_TIMEOUT, + "422": INVALID_PARAMETER_VALUE, + "429": RATE_LIMIT_EXCEEDED, + "500": PROVIDER_INTERNAL_ERROR, + "502": PROVIDER_INTERNAL_ERROR, + "503": PROVIDER_OVERLOADED, + "504": UPSTREAM_TIMEOUT, + } +) + +_INTERNAL_STATE_EXCEPTIONS: Final[tuple[type[BaseException], ...]] = ( + TypeError, + KeyError, + AttributeError, + IndexError, + RuntimeError, + AssertionError, + ZeroDivisionError, +) + +_CLASS_CODE_TABLE: Final[tuple[tuple[tuple[type[BaseException], ...], str], ...]] = ( + ((AuthenticationError,), AUTHENTICATION_FAILED), + ((PermissionDeniedError,), PERMISSION_DENIED), + ((ContextWindowExceededError,), CONTEXT_WINDOW_EXCEEDED), + ((ContentPolicyViolationError, GuardrailRaisedException, BlockedPiiEntityError), CONTENT_POLICY_VIOLATION), + ((UnsupportedParamsError,), INVALID_PARAMETER_VALUE), + ((NotFoundError,), RESOURCE_NOT_FOUND), + ((Timeout,), UPSTREAM_TIMEOUT), + ((MidStreamFallbackError,), ROUTER_FALLBACK_FAILURE), + ((APIConnectionError,), PROVIDER_CONNECTION_ERROR), + ((ServiceUnavailableError,), PROVIDER_OVERLOADED), + ((InternalServerError, BadGatewayError), PROVIDER_INTERNAL_ERROR), + ((BadRequestError, UnprocessableEntityError), INVALID_REQUEST), + ((NotImplementedError,), UNSUPPORTED_OPERATION), +) + + +def _classify_by_message(message: str, patterns: tuple[tuple[re.Pattern[str], str], ...]) -> str | None: + return next((code for pattern, code in patterns if pattern.search(message)), None) + + +def _classify_by_class(exc: Exception) -> str | None: + if isinstance(exc, BudgetExceededError): + return BUDGET_EXCEEDED + if isinstance(exc, RateLimitError): + return BUDGET_EXCEEDED if exc.rate_limit_type == RateLimitType.BUDGET.value else RATE_LIMIT_EXCEEDED + for exc_types, code in _CLASS_CODE_TABLE: + if isinstance(exc, exc_types): + return code + if isinstance(exc, _INTERNAL_STATE_EXCEPTIONS): + return INTERNAL_STATE_ERROR + return None + + +def normalize_error(exc: Exception | None, status_code: str, message: str) -> str | None: + """ + Return a stable cluster key for ``exc``. ``status_code`` and ``message`` are the values + ``get_error_information`` already extracted, so the same exception always yields the same code. + """ + if exc is None: + return None + proxy_type: Final = exc.type if isinstance(exc, _HasProxyErrorType) else None + by_proxy_type: Final = _PROXY_ERROR_TYPE_MAP.get(proxy_type) if isinstance(proxy_type, str) else None + if by_proxy_type is not None: + return by_proxy_type + by_message: Final = _classify_by_message(message, _MESSAGE_PATTERNS) + if by_message is not None: + return by_message + by_class: Final = _classify_by_class(exc) + if by_class is not None: + return by_class + by_router_wrapper: Final = _classify_by_message(message, _ROUTER_WRAPPER_PATTERNS) + if by_router_wrapper is not None: + return by_router_wrapper + return _STATUS_CODE_MAP.get(status_code, UNCLASSIFIED) diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py index 6e5a37a7226..8e28a0d543d 100644 --- a/litellm/litellm_core_utils/litellm_logging.py +++ b/litellm/litellm_core_utils/litellm_logging.py @@ -76,6 +76,7 @@ from litellm.litellm_core_utils.core_helpers import ( reconstruct_model_name, set_response_cost_in_hidden_params, ) +from litellm.litellm_core_utils.error_normalization import normalize_error from litellm.litellm_core_utils.get_litellm_params import get_litellm_params from litellm.litellm_core_utils.internal_call_metadata import ( MODEL_ACCESS_GROUP_METADATA_KEY, @@ -6100,6 +6101,7 @@ class StandardLoggingPayloadSetup: error_budget_entity_id=budget_error.entity_id if budget_error else None, error_budget_limit=budget_error.max_budget if budget_error else None, error_budget_spend=budget_error.current_cost if budget_error else None, + normalized_error=normalize_error(original_exception, error_status, error_message), ) @staticmethod diff --git a/litellm/types/utils.py b/litellm/types/utils.py index f2c8f0e7044..dfc98a9d89d 100644 --- a/litellm/types/utils.py +++ b/litellm/types/utils.py @@ -3256,6 +3256,7 @@ class StandardLoggingPayloadErrorInformation(TypedDict, total=False): error_budget_entity_id: str | None error_budget_limit: float | None error_budget_spend: float | None + normalized_error: ReadOnly[str | None] class GuardrailMode(TypedDict, total=False): diff --git a/tests/e2e/coverage_registry/quota_management.yaml b/tests/e2e/coverage_registry/quota_management.yaml index 5ea48fdcd9d..5740a878608 100644 --- a/tests/e2e/coverage_registry/quota_management.yaml +++ b/tests/e2e/coverage_registry/quota_management.yaml @@ -51,6 +51,7 @@ - {id: quota_management.spend_tracking.end_user.attributes_spend, module: quota_management, tier: P1, behavior: spend_tracking, variant: end_user, assertions: [attributes_spend], exercised_on: [chat_completions], source: "proxy/spend_tracking/spend_tracking_utils.py", rationale: "user= attribution lands the end-user id on the spend row"} - {id: quota_management.spend_tracking.per_model.writes_own_rows, module: quota_management, tier: P2, behavior: spend_tracking, variant: per_model, assertions: [writes_own_rows], exercised_on: [chat_completions], source: "proxy/spend_tracking/spend_tracking_utils.py", rationale: "Each model on a shared key gets its own spend row"} - {id: quota_management.spend_tracking.failure.writes_failure_row, module: quota_management, tier: P1, behavior: spend_tracking, variant: failure, assertions: [writes_failure_row], exercised_on: [chat_completions], source: "proxy/spend_tracking/spend_log_error_logger.py", rationale: "A failed call writes a failure-status spend row"} +- {id: quota_management.spend_tracking.failure.writes_normalized_error, module: quota_management, tier: P1, behavior: spend_tracking, variant: failure, assertions: [writes_normalized_error], exercised_on: [chat_completions], source: "litellm_core_utils/error_normalization.py", rationale: "Failure rows carry a stable metadata.error_information.normalized_error key next to the unchanged error_message, so two upstream auth failures with different provider wording share one cluster key a dashboard can group by"} - {id: quota_management.spend_tracking.failure.attributes_provider, module: quota_management, tier: P1, behavior: spend_tracking, variant: failure, assertions: [attributes_provider], exercised_on: [chat_completions], source: "proxy/utils.py", rationale: "A request rejected in pre_call_hook (rate limit, guardrail) still lands its single deployment's provider and model_id on the failure spend row"} - {id: quota_management.spend_tracking.spend_calculate.returns_cost, module: quota_management, tier: P2, behavior: spend_tracking, variant: spend_calculate, assertions: [returns_cost], exercised_on: [spend_calculate], source: "proxy/spend_tracking/spend_management_endpoints.py", rationale: "/spend/calculate prices a hypothetical request at nonzero cost"} - {id: quota_management.spend_tracking.pagination.keeps_total, module: quota_management, tier: P2, behavior: spend_tracking, variant: pagination, assertions: [keeps_total], exercised_on: [chat_completions], source: "proxy/spend_tracking/spend_management_endpoints.py", rationale: "Spend-logs v2 pagination caps page size without losing the total"} diff --git a/tests/e2e/models.py b/tests/e2e/models.py index bc81d1015ba..bd7f5171172 100644 --- a/tests/e2e/models.py +++ b/tests/e2e/models.py @@ -937,10 +937,18 @@ class GuardrailRunRecord(BaseModel): guardrail_response: object | None = None +class SpendLogErrorInformation(BaseModel): + error_code: str | None = None + error_class: str | None = None + error_message: str | None = None + normalized_error: str | None = None + + class SpendLogMetadata(BaseModel): user_api_key_alias: str | None = None applied_guardrails: list[str] | None = None guardrail_information: list[GuardrailRunRecord] | None = None + error_information: SpendLogErrorInformation | None = None class SpendLogRow(BaseModel): diff --git a/tests/e2e/quota_management/spend_tracking/test_spend_tracking_e2e.py b/tests/e2e/quota_management/spend_tracking/test_spend_tracking_e2e.py index 6ca6f8cee55..286421e2e3f 100644 --- a/tests/e2e/quota_management/spend_tracking/test_spend_tracking_e2e.py +++ b/tests/e2e/quota_management/spend_tracking/test_spend_tracking_e2e.py @@ -499,6 +499,47 @@ def test_failure_call_writes_failure_status_row( assert (failure_row.spend or 0) == 0.0, "failed call must not be charged" +@pytest.mark.covers("quota_management.spend_tracking.failure.writes_normalized_error") +def test_failure_rows_share_normalized_error_across_provider_wording( + client: SpendClient, resources: ResourceManager, scoped_key: str +) -> None: + """Two upstream auth failures with different provider wording land as failure rows + whose metadata.error_information keeps each provider's own error_message and + carries the same stable normalized_error cluster key.""" + marker = unique_marker() + deployments: Final = ( + (f"e2e-norm-openai-{marker}", "openai/gpt-5.5"), + (f"e2e-norm-anthropic-{marker}", "anthropic/claude-haiku-4-5"), + ) + for name, provider_model in deployments: + model_id = client.proxy.create_model( + name, LiteLLMParamsBody(model=provider_model, api_key=f"sk-invalid-{marker}") + ) + resources.defer(lambda model_id=model_id: client.proxy.delete_model(model_id)) + result = client.chat(scoped_key, name, f"normalize failure {marker}", max_tokens=1) + assert not is_ok(result), f"{name}: invalid upstream key must fail the call, got {result}" + + rows = client.poll_logs_for_key( + scoped_key, + min_rows=2, + predicate=lambda rs: sum(1 for r in rs if r.status == "failure") >= 2, + ) + failure_rows = [r for r in rows if r.status == "failure"] + assert len(failure_rows) == 2, f"expected one failure row per deployment: {_summarize(rows)}" + + infos = [r.metadata.error_information if r.metadata else None for r in failure_rows] + assert all(info is not None for info in infos), ( + f"failure rows must carry metadata.error_information: {[r.model_dump() for r in failure_rows]}" + ) + messages = {info.error_message for info in infos if info is not None} + assert len(messages) == 2, f"provider wording must stay distinct in error_message: {messages}" + normalized = {info.normalized_error for info in infos if info is not None} + assert normalized == {"401_AUTHENTICATION_FAILED"}, ( + f"both auth failures must share one normalized_error cluster key; saw {normalized} " + f"for messages {messages}" + ) + + @pytest.mark.covers("quota_management.spend_tracking.failure.attributes_provider") def test_pre_call_rejection_row_attributes_provider_and_model_id( client: SpendClient, resources: ResourceManager diff --git a/tests/test_litellm/litellm_core_utils/test_error_normalization.py b/tests/test_litellm/litellm_core_utils/test_error_normalization.py new file mode 100644 index 00000000000..9d5469ddb4c --- /dev/null +++ b/tests/test_litellm/litellm_core_utils/test_error_normalization.py @@ -0,0 +1,231 @@ +import httpx +import pytest + +import litellm +from litellm.exceptions import MidStreamFallbackError +from litellm.litellm_core_utils.error_normalization import normalize_error +from litellm.litellm_core_utils.litellm_logging import StandardLoggingPayloadSetup +from litellm.proxy._types import ProxyErrorTypes, ProxyException +from litellm.types.router import RouterErrors + +_RESPONSE = httpx.Response(status_code=500, request=httpx.Request("POST", "https://example.invalid")) + + +def _proxy_exc(message: str, error_type: str, code: int) -> ProxyException: + return ProxyException(message=message, type=error_type, param=None, code=code) + + +@pytest.mark.parametrize( + ("messages", "expected"), + [ + ( + ( + _proxy_exc("Rate limit exceeded for team X. Reset at 10:01", "rate_limit_error", 429), + _proxy_exc("Rate limit exceeded for team Y. Reset at 10:02", "rate_limit_error", 429), + ), + "429_RATE_LIMIT_EXCEEDED", + ), + ( + ( + litellm.BudgetExceededError(current_cost=3501.85, max_budget=3500), + _proxy_exc( + "User=abc, Current cost=1000.03, Max budget=1000", ProxyErrorTypes.budget_exceeded.value, 400 + ), + litellm.RateLimitError( + "budget", + llm_provider="openai", + model="gpt", + rate_limit_type=litellm.exceptions.RateLimitType.BUDGET, + ), + ), + "429_BUDGET_EXCEEDED", + ), + ( + ( + _proxy_exc("Token Expired", ProxyErrorTypes.expired_key.value, 401), + _proxy_exc("Malformed API Key", ProxyErrorTypes.auth_error.value, 401), + litellm.AuthenticationError("Signature verification failed", llm_provider="azure", model="gpt"), + ), + "401_AUTHENTICATION_FAILED", + ), + ( + ( + _proxy_exc("No team has access to gpt-5.5-mini", ProxyErrorTypes.team_model_access_denied.value, 401), + _proxy_exc("key not allowed to access claude", ProxyErrorTypes.key_model_access_denied.value, 401), + ValueError( + "Not allowed to access model due to tags configuration. Passed model=gpt-5.5 and tags=['team-a']" + ), + ), + "403_MODEL_ACCESS_DENIED", + ), + ( + ( + _proxy_exc("Missing required parameter: messages", ProxyErrorTypes.bad_request_error.value, 400), + litellm.BadRequestError("Missing required parameter: input", llm_provider="openai", model="gpt"), + ), + "400_MISSING_REQUIRED_PARAMETER", + ), + ( + ( + litellm.ContextWindowExceededError( + "1002823 tokens > 1000000 maximum", model="g", llm_provider="vertex" + ), + litellm.BadRequestError("Input is too long for requested model", llm_provider="anthropic", model="c"), + ), + "400_CONTEXT_WINDOW_EXCEEDED", + ), + ( + ( + litellm.NotFoundError("Response id xxx not found", llm_provider="openai", model="gpt"), + _proxy_exc("No vector store found with id abc", ProxyErrorTypes.not_found_error.value, 404), + ), + "404_RESOURCE_NOT_FOUND", + ), + ( + ( + litellm.APIConnectionError("Connection error", llm_provider="openai", model="gpt"), + litellm.InternalServerError("TransferEncodingError", llm_provider="openai", model="gpt"), + litellm.APIError(500, "Response payload is not completed", llm_provider="openai", model="gpt"), + httpx.RemoteProtocolError( + "peer closed connection without sending complete message body (incomplete chunked read)" + ), + ), + "500_PROVIDER_CONNECTION_ERROR", + ), + ( + ( + litellm.ServiceUnavailableError("server_is_overloaded", llm_provider="anthropic", model="c"), + litellm.InternalServerError( + "Bedrock is unable to process your request", llm_provider="bedrock", model="c" + ), + litellm.APIError(529, "Overloaded", llm_provider="anthropic", model="c"), + ), + "503_PROVIDER_OVERLOADED", + ), + ( + ( + litellm.InternalServerError( + "The server had an error while processing your request", llm_provider="openai", model="gpt" + ), + litellm.APIError(500, "server_error", llm_provider="openai", model="gpt"), + ), + "500_PROVIDER_INTERNAL_ERROR", + ), + ( + ( + _proxy_exc("No fallback model group found for gpt-5.6", "internal_server_error", 500), + _proxy_exc("No fallback model group found for claude-46-sonnet", "internal_server_error", 500), + ), + "500_ROUTER_NO_FALLBACK", + ), + ( + ( + _proxy_exc("Error doing the fallback: RateLimitError", "internal_server_error", 500), + MidStreamFallbackError( + "stream died", model="gpt", llm_provider="openai", original_exception=ValueError("boom") + ), + ), + "500_ROUTER_FALLBACK_FAILURE", + ), + ( + ( + TypeError("cannot pickle '_thread.RLock' object"), + RuntimeError("dictionary changed size during iteration"), + TypeError("'NoneType' object is not iterable"), + ), + "500_INTERNAL_STATE_ERROR", + ), + ( + ( + litellm.Timeout("Timeout on reading data from socket", model="gpt", llm_provider="openai"), + litellm.APIError(504, "Request timed out", llm_provider="openai", model="gpt"), + ), + "408_UPSTREAM_TIMEOUT", + ), + ( + ( + _proxy_exc("500: Upstream passthrough request failed", "internal_server_error", 500), + _proxy_exc("503: Upstream passthrough request failed", "internal_server_error", 503), + ), + "500_UPSTREAM_PASSTHROUGH", + ), + ( + ( + _proxy_exc("OCR is not supported for provider openai", "internal_server_error", 500), + NotImplementedError("rerank"), + ), + "500_UNSUPPORTED_OPERATION", + ), + ], +) +def test_variants_of_one_failure_share_a_normalized_error(messages: tuple[Exception, ...], expected: str) -> None: + normalized = {StandardLoggingPayloadSetup.get_error_information(exc)["normalized_error"] for exc in messages} + assert normalized == {expected} + + +def test_router_no_healthy_deployment_wording_clusters_as_no_healthy_deployments() -> None: + for message in (RouterErrors.no_healthy_deployments.value, "No healthy deployments found."): + exc = litellm.BadRequestError(message, llm_provider="openai", model="gpt-4o") + assert normalize_error(exc, "400", message) == "429_NO_HEALTHY_DEPLOYMENTS", message + + +def test_provider_budget_routing_wording_clusters_as_budget_exceeded() -> None: + message = RouterErrors.no_deployments_with_provider_budget_routing.value + exc = litellm.BadRequestError(message, llm_provider="openai", model="gpt-4o") + assert normalize_error(exc, "400", message) == "429_BUDGET_EXCEEDED" + + +def test_router_fallback_wording_does_not_hide_the_wrapped_exception_class() -> None: + provider_message = "litellm.AuthenticationError: OpenAIException - Incorrect API key provided" + exc = litellm.AuthenticationError( + provider_message + "\nNo fallback model group found for lookup_groups=['x']", + llm_provider="openai", + model="gpt", + ) + assert normalize_error(exc, "401", str(exc)) == "401_AUTHENTICATION_FAILED" + wrapped = litellm.AuthenticationError( + "Error doing the fallback: " + provider_message, llm_provider="openai", model="gpt" + ) + assert normalize_error(wrapped, "401", str(wrapped)) == "401_AUTHENTICATION_FAILED" + + +def test_parameter_length_error_is_not_a_context_window_error() -> None: + exc = litellm.BadRequestError("string too long: 'user' max 64 chars", llm_provider="openai", model="gpt") + assert StandardLoggingPayloadSetup.get_error_information(exc)["normalized_error"] == "400_INVALID_REQUEST" + + +def test_no_exception_has_no_normalized_error() -> None: + assert StandardLoggingPayloadSetup.get_error_information(None)["normalized_error"] is None + + +def test_unknown_exception_falls_back_to_status_then_unclassified() -> None: + assert normalize_error(Exception("x"), "429", "x") == "429_RATE_LIMIT_EXCEEDED" + assert normalize_error(Exception("x"), "", "x") == "UNCLASSIFIED" + + +def test_budget_exceeded_error_with_custom_wording_is_still_a_budget_error() -> None: + exc = litellm.BudgetExceededError(current_cost=2.0, max_budget=1.0, message="Spending cap reached for key") + assert StandardLoggingPayloadSetup.get_error_information(exc)["normalized_error"] == "429_BUDGET_EXCEEDED" + + +def test_every_model_access_denied_proxy_type_shares_one_cluster() -> None: + access_denied_types = tuple(t for t in ProxyErrorTypes if t.value.endswith("_model_access_denied")) + assert len(access_denied_types) >= 6, access_denied_types + codes = {normalize_error(_proxy_exc("denied", t.value, 403), "403", "denied") for t in access_denied_types} + assert codes == {"403_MODEL_ACCESS_DENIED"}, codes + + +def test_non_string_type_attribute_falls_through_to_status() -> None: + class _OddType(Exception): + type = {"kind": "odd"} + + assert normalize_error(_OddType("odd"), "500", "odd") == "500_PROVIDER_INTERNAL_ERROR" + + +def test_normalized_error_never_embeds_dynamic_parts() -> None: + exc = _proxy_exc( + "No team has access to anthropic.claude-sonnet-4-5", ProxyErrorTypes.team_model_access_denied.value, 401 + ) + info = StandardLoggingPayloadSetup.get_error_information(exc) + assert info["error_message"] == "No team has access to anthropic.claude-sonnet-4-5" + assert "claude" not in (info["normalized_error"] or "") From 3c3803f37afa488a5fad08b2fc2f39d1c36f740c Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 16:04:44 -0700 Subject: [PATCH 054/101] test(bedrock): point unit tests at model ids still in the cost map (#42606) #42521 retired the cohere.command-r ids from the cost map, and a bare Bedrock id resolves its provider through that map, so test_model_group_info and the cohere cases in test_bedrock_dynamic_auth_params_unit_tests failed with LLM Provider NOT provided. The completion tests keep the cohere invoke request and URL assertions through the bedrock/ prefix, the bare parametrize entry moves to amazon.nova-2-lite-v1:0 with the mock response shape picked by the real Bedrock route, and the router test builds its group info from bedrock/amazon.nova-2-lite-v1:0. Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- .../test_bedrock_dynamic_auth_params_unit_tests.py | 11 ++++++----- tests/local_testing/test_router.py | 9 ++++++--- 2 files changed, 12 insertions(+), 8 deletions(-) diff --git a/tests/llm_translation/test_bedrock_dynamic_auth_params_unit_tests.py b/tests/llm_translation/test_bedrock_dynamic_auth_params_unit_tests.py index 2d1d2815026..184a0ae0749 100644 --- a/tests/llm_translation/test_bedrock_dynamic_auth_params_unit_tests.py +++ b/tests/llm_translation/test_bedrock_dynamic_auth_params_unit_tests.py @@ -9,6 +9,7 @@ import litellm from litellm.llms.custom_httpx.http_handler import HTTPHandler from unittest.mock import Mock from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM +from litellm.llms.bedrock.common_utils import BedrockModelInfo @@ -42,7 +43,7 @@ def test_bedrock_completion_with_region_name(): # Pass the client so that the HTTP call will be intercepted. response = litellm.completion( - model="cohere.command-r-v1:0", + model="bedrock/cohere.command-r-v1:0", messages=[{"role": "user", "content": "Hello, world!"}], aws_region_name="us-west-12", client=client, @@ -98,7 +99,7 @@ def test_bedrock_completion_with_dynamic_authentication_params(): # Pass the client so that the HTTP call will be intercepted. response = litellm.completion( - model="cohere.command-r-v1:0", + model="bedrock/cohere.command-r-v1:0", messages=[{"role": "user", "content": "Hello, world!"}], aws_access_key_id="dynamically_generated_access_key_id", aws_secret_access_key="dynamically_generated_secret_access_key", @@ -146,7 +147,7 @@ def test_bedrock_completion_with_dynamic_bedrock_runtime_endpoint(): # Pass the client so that the HTTP call will be intercepted. response = litellm.completion( - model="cohere.command-r-v1:0", + model="bedrock/cohere.command-r-v1:0", messages=[{"role": "user", "content": "Hello, world!"}], aws_bedrock_runtime_endpoint="https://my-fake-endpoint.com", client=client, @@ -179,7 +180,7 @@ class DummyCredentials: "model", [ "bedrock/converse/cohere.command-r-v1:0", - "cohere.command-r-v1:0", + "amazon.nova-2-lite-v1:0", "bedrock/cohere.command-r-v1:0", "bedrock/invoke/cohere.command-r-v1:0", ], @@ -250,7 +251,7 @@ def test_dynamic_aws_params_propagation(model, param_name, param_value, expected "finish_reason": "COMPLETE", } ) - if "converse" in model: + if BedrockModelInfo.get_bedrock_route(model) == "converse": mock_response.text = json.dumps( { "output": { diff --git a/tests/local_testing/test_router.py b/tests/local_testing/test_router.py index bd0a9bf8df4..4c62c28530d 100644 --- a/tests/local_testing/test_router.py +++ b/tests/local_testing/test_router.py @@ -1284,15 +1284,18 @@ def test_model_group_info(): router = Router( model_list=[ { - "model_name": "command-r-plus", - "litellm_params": {"model": "cohere.command-r-plus-v1:0"}, + "model_name": "nova-2-lite", + "litellm_params": {"model": "bedrock/amazon.nova-2-lite-v1:0"}, } ] ) - response = router.get_model_group_info(model_group="command-r-plus") + response = router.get_model_group_info(model_group="nova-2-lite") assert response is not None + assert response.model_group == "nova-2-lite" + assert response.providers == ["bedrock"] + assert response.max_input_tokens is not None def test_consistent_model_id(): From dd327156c80865c58f0eff5599c987020ed545f7 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 23:07:02 +0000 Subject: [PATCH 055/101] feat(rust): add immutable model catalog crate (#42605) * feat(rust): add immutable model catalog crate * feat(rust): add typed model info mirror, error module, and schema feature Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(rust): split catalog module, rstest tests, and repo data parity tests Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: Yujong Lee Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- litellm-rust/Cargo.lock | 38 + litellm-rust/crates/model-catalog/Cargo.toml | 25 + litellm-rust/crates/model-catalog/README.md | 25 + .../crates/model-catalog/benches/catalog.rs | 21 + .../crates/model-catalog/src/catalog.rs | 241 +++++++ .../crates/model-catalog/src/error.rs | 28 + litellm-rust/crates/model-catalog/src/lib.rs | 16 + .../crates/model-catalog/src/model_info.rs | 665 ++++++++++++++++++ .../crates/model-catalog/src/schema.rs | 7 + .../crates/model-catalog/tests/catalog.rs | 253 +++++++ .../crates/model-catalog/tests/spec_parity.rs | 121 ++++ 11 files changed, 1440 insertions(+) create mode 100644 litellm-rust/crates/model-catalog/Cargo.toml create mode 100644 litellm-rust/crates/model-catalog/README.md create mode 100644 litellm-rust/crates/model-catalog/benches/catalog.rs create mode 100644 litellm-rust/crates/model-catalog/src/catalog.rs create mode 100644 litellm-rust/crates/model-catalog/src/error.rs create mode 100644 litellm-rust/crates/model-catalog/src/lib.rs create mode 100644 litellm-rust/crates/model-catalog/src/model_info.rs create mode 100644 litellm-rust/crates/model-catalog/src/schema.rs create mode 100644 litellm-rust/crates/model-catalog/tests/catalog.rs create mode 100644 litellm-rust/crates/model-catalog/tests/spec_parity.rs diff --git a/litellm-rust/Cargo.lock b/litellm-rust/Cargo.lock index f3510000c44..4427057a3b9 100644 --- a/litellm-rust/Cargo.lock +++ b/litellm-rust/Cargo.lock @@ -3054,6 +3054,20 @@ dependencies = [ "url", ] +[[package]] +name = "litellm-model-catalog" +version = "0.1.0" +dependencies = [ + "criterion", + "indexmap 2.14.0", + "litellm-model-catalog", + "rstest", + "schemars 1.2.2", + "serde", + "serde_json", + "thiserror 2.0.19", +] + [[package]] name = "litellm-python-bridge" version = "0.1.0" @@ -4756,10 +4770,23 @@ checksum = "687274d293b6cdc6e73e0fee520bf2049650090d7164f87672d212a3c530cf4a" dependencies = [ "dyn-clone", "ref-cast", + "schemars_derive", "serde", "serde_json", ] +[[package]] +name = "schemars_derive" +version = "1.2.2" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "d98c67716b46af2f0b8cf752abc930f6f9aecfbf671ecfb531db8a31dbe4e2ba" +dependencies = [ + "proc-macro2", + "quote", + "serde_derive_internals", + "syn 3.0.0", +] + [[package]] name = "scopeguard" version = "1.2.0" @@ -4848,6 +4875,17 @@ dependencies = [ "syn 3.0.0", ] +[[package]] +name = "serde_derive_internals" +version = "0.30.0" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "f852137cce035d6a4df67ccce505ff6b3e9fd3a10e3e52b24dc71e650bb1a9bd" +dependencies = [ + "proc-macro2", + "quote", + "syn 3.0.0", +] + [[package]] name = "serde_json" version = "1.0.150" diff --git a/litellm-rust/crates/model-catalog/Cargo.toml b/litellm-rust/crates/model-catalog/Cargo.toml new file mode 100644 index 00000000000..ea75c6386d8 --- /dev/null +++ b/litellm-rust/crates/model-catalog/Cargo.toml @@ -0,0 +1,25 @@ +[package] +name = "litellm-model-catalog" +version = "0.1.0" +edition.workspace = true +license.workspace = true +repository.workspace = true + +[features] +schema = ["dep:schemars"] + +[dependencies] +indexmap = { version = "2.14.0", features = ["serde"] } +schemars = { version = "1.0", optional = true } +serde.workspace = true +serde_json.workspace = true +thiserror.workspace = true + +[dev-dependencies] +criterion.workspace = true +rstest.workspace = true +litellm-model-catalog = { path = ".", features = ["schema"] } + +[[bench]] +name = "catalog" +harness = false diff --git a/litellm-rust/crates/model-catalog/README.md b/litellm-rust/crates/model-catalog/README.md new file mode 100644 index 00000000000..973f7190614 --- /dev/null +++ b/litellm-rust/crates/model-catalog/README.md @@ -0,0 +1,25 @@ +# Model catalog + +`litellm-model-catalog` builds an immutable snapshot from caller supplied JSON bytes. It has no network, Python, registration, or refresh behavior. The caller supplies optional source, revision, and ETag provenance. Parse and validation are separate so small synthetic catalogs can use explicit integrity limits + +The parser treats `sample_spec` and `fallback_generalizations` as reserved top level metadata. `fallback_rules()` exposes the typed rule array when present; this crate does not execute regex generalizations. Model entries retain all JSON fields except `aliases`, including unknown fields. `field()` returns `None` for an absent key and a JSON null, false, or zero value for a present key. The returned values are borrowed, so callers cannot mutate the snapshot + +Each entry also deserializes into `ModelInfo`, a typed mirror of `model_prices_and_context_window.schema.json`'s `modelEntry` definition, reachable via `ModelEntry::info()`. All schema fields are optional on `ModelInfo`, including `litellm_provider` which the schema marks required, so small synthetic catalogs still parse. Unknown fields are not part of `ModelInfo`; they remain on `fields()`. Building with the `schema` feature adds `schemars` derives and exposes `model_entry_json_schema()` for emitting the entry's JSON Schema. Parse and validation failures are reported by the `Error` enum in `error.rs`, while catalog logic lives in `catalog.rs` + +The integration tests read the repository's catalog and schema files at test time, assert every entry round-trips through `ModelInfo`, and verify that the generated schema's properties match the repository schema + +Aliases point to their canonical entries. An alias that exactly matches any canonical key is skipped; the first canonical entry claiming an alias wins. Invalid alias lists and nonstring names are skipped and reported by `alias_issues()`. Exact lookup wins. For a case insensitive miss, the last key with the same lowercase spelling wins, following Python's lowercase map built after aliases are appended. This uses Rust Unicode lowercasing, which can differ from Python for unusual Unicode model IDs + +`validate()` counts canonical entries before alias expansion and excludes both reserved keys. It enforces an explicit minimum and backup shrink ratio, with Python defaults of 50 models and 0.5. Parsing rejects nonobject model entries and known fields with the wrong JSON type, but ignores unknown fields. It does not enforce every constraint in the JSON schema, calculate prices, resolve providers, or check provenance authenticity. The caller decides how to handle validation failures + +This snapshot does not represent Python's live mutable `litellm.model_cost`, nested dict and list mutation, or mutation of dicts previously returned by Python APIs. It has no bridge or runtime integration + +## Benchmarks + +`cargo bench -p litellm-model-catalog --bench catalog` measures parsing plus alias indexing and exact lookup. For a local Python baseline on the same fixture, use: + +```sh +python3 -m timeit -s 'import json, pathlib; body = pathlib.Path("../model_prices_and_context_window.json").read_bytes()' 'json.loads(body)' +``` + +Run these commands from `litellm-rust`. Python's command measures JSON loading only, without alias expansion or snapshot construction. The Rust benchmark does not include future Python object materialization, so these numbers are not an end to end runtime comparison diff --git a/litellm-rust/crates/model-catalog/benches/catalog.rs b/litellm-rust/crates/model-catalog/benches/catalog.rs new file mode 100644 index 00000000000..d1f51507c2b --- /dev/null +++ b/litellm-rust/crates/model-catalog/benches/catalog.rs @@ -0,0 +1,21 @@ +use criterion::{Criterion, criterion_group, criterion_main}; +use litellm_model_catalog::{Catalog, Provenance}; +use std::hint::black_box; + +fn benchmarks(c: &mut Criterion) { + let body = include_bytes!("../../../../model_prices_and_context_window.json"); + c.bench_function("parse_current_catalog", |b| { + b.iter(|| Catalog::parse(black_box(body), Provenance::default()).unwrap()) + }); + let catalog = Catalog::parse(body, Provenance::default()).unwrap(); + let key = catalog + .model_names() + .next() + .expect("catalog must have a benchmark key"); + c.bench_function("lookup_catalog_key", |b| { + b.iter(|| black_box(&catalog).lookup(black_box(key))) + }); +} + +criterion_group!(benches, benchmarks); +criterion_main!(benches); diff --git a/litellm-rust/crates/model-catalog/src/catalog.rs b/litellm-rust/crates/model-catalog/src/catalog.rs new file mode 100644 index 00000000000..dc7564f9bee --- /dev/null +++ b/litellm-rust/crates/model-catalog/src/catalog.rs @@ -0,0 +1,241 @@ +use crate::error::Error; +use crate::model_info::{FallbackGeneralizations, FallbackRule, ModelInfo}; +use indexmap::IndexMap; +use serde::Deserialize; +use serde_json::{Map, Value}; +use std::collections::HashMap; + +#[derive(Clone, Debug, Default, PartialEq, Eq)] +pub struct Provenance { + pub source: Option, + pub revision: Option, + pub etag: Option, +} + +#[derive(Clone, Copy, Debug, PartialEq)] +pub struct IntegrityLimits { + pub backup_model_count: usize, + pub min_model_count: usize, + pub min_backup_ratio: f64, +} + +impl IntegrityLimits { + pub fn python_defaults(backup_model_count: usize) -> Self { + Self { + backup_model_count, + min_model_count: 50, + min_backup_ratio: 0.5, + } + } +} + +#[derive(Clone, Debug, PartialEq, Eq)] +pub enum AliasIssue { + InvalidList { model: String }, + InvalidName { model: String }, + CanonicalCollision { model: String, alias: String }, + AliasCollision { model: String, alias: String }, +} + +#[derive(Clone, Debug)] +pub struct ModelEntry { + fields: Map, + info: ModelInfo, +} + +impl ModelEntry { + pub fn field(&self, name: &str) -> Option<&Value> { + self.fields.get(name) + } + pub fn fields(&self) -> &Map { + &self.fields + } + /// The entry deserialized into the typed mirror of the catalog schema. + pub fn info(&self) -> &ModelInfo { + &self.info + } +} + +#[derive(Clone, Copy, Debug)] +pub struct ModelMatch<'a> { + pub matched_key: &'a str, + pub canonical_key: &'a str, + pub entry: &'a ModelEntry, +} + +#[derive(Debug)] +pub struct Catalog { + entries: IndexMap, + aliases: IndexMap, + lowercase_keys: HashMap, + sample_spec: Option, + fallback_generalizations: Option, + provenance: Provenance, + alias_issues: Vec, +} + +impl Catalog { + pub fn parse(body: &[u8], provenance: Provenance) -> Result { + let root: IndexMap = serde_json::from_slice(body)?; + if root.is_empty() { + return Err(Error::Empty); + } + + let mut entries = IndexMap::with_capacity(root.len()); + let mut alias_lists = Vec::new(); + let mut alias_issues = Vec::new(); + let mut sample_spec = None; + let mut fallback_generalizations = None; + for (name, value) in root { + match name.as_str() { + "sample_spec" => { + sample_spec = Some(value); + continue; + } + "fallback_generalizations" => { + fallback_generalizations = + Some(serde_json::from_value::(value)?); + continue; + } + _ => {} + } + let Value::Object(ref object) = value else { + return Err(Error::EntryNotObject { model: name }); + }; + let info = ModelInfo::deserialize(object)?; + let Value::Object(mut fields) = value else { + unreachable!("value checked is_object above") + }; + if let Some(aliases) = fields.remove("aliases") + && !aliases.is_null() + { + match aliases { + Value::Array(names) => alias_lists.push((name.clone(), names)), + _ => alias_issues.push(AliasIssue::InvalidList { + model: name.clone(), + }), + } + } + entries.insert(name, ModelEntry { fields, info }); + } + + let mut aliases = IndexMap::new(); + for (model, names) in alias_lists { + for name in names { + let Value::String(alias) = name else { + alias_issues.push(AliasIssue::InvalidName { + model: model.clone(), + }); + continue; + }; + if entries.contains_key(&alias) { + alias_issues.push(AliasIssue::CanonicalCollision { + model: model.clone(), + alias, + }); + } else if aliases.contains_key(&alias) { + alias_issues.push(AliasIssue::AliasCollision { + model: model.clone(), + alias, + }); + } else { + aliases.insert(alias, model.clone()); + } + } + } + + let lowercase_keys = entries + .keys() + .chain(aliases.keys()) + .map(|key| (key.to_lowercase(), key.clone())) + .collect(); + Ok(Self { + entries, + aliases, + lowercase_keys, + sample_spec, + fallback_generalizations, + provenance, + alias_issues, + }) + } + + pub fn validate(&self, limits: IntegrityLimits) -> Result<(), Error> { + if !limits.min_backup_ratio.is_finite() || !(0.0..=1.0).contains(&limits.min_backup_ratio) { + return Err(Error::InvalidRatio); + } + let actual = self.entries.len(); + if actual < limits.min_model_count { + return Err(Error::BelowMinimum { + actual, + minimum: limits.min_model_count, + }); + } + if limits.backup_model_count > 0 + && (actual as f64) < (limits.backup_model_count as f64) * limits.min_backup_ratio + { + return Err(Error::Shrunk { + actual, + backup: limits.backup_model_count, + ratio: limits.min_backup_ratio, + }); + } + Ok(()) + } + + pub fn lookup(&self, key: &str) -> Option> { + let matched_key = if self.entries.contains_key(key) || self.aliases.contains_key(key) { + key + } else { + self.lowercase_keys.get(&key.to_lowercase())?.as_str() + }; + let canonical_key = self + .aliases + .get(matched_key) + .map(String::as_str) + .unwrap_or(matched_key); + let (canonical_key, entry) = self.entries.get_key_value(canonical_key)?; + let matched_key = self + .entries + .get_key_value(matched_key) + .map(|(key, _)| key.as_str()) + .or_else(|| { + self.aliases + .get_key_value(matched_key) + .map(|(key, _)| key.as_str()) + })?; + Some(ModelMatch { + matched_key, + canonical_key, + entry, + }) + } + + pub fn model_count(&self) -> usize { + self.entries.len() + } + pub fn model_names(&self) -> impl Iterator { + self.entries.keys().map(String::as_str) + } + pub fn alias_count(&self) -> usize { + self.aliases.len() + } + pub fn aliases(&self) -> &IndexMap { + &self.aliases + } + pub fn alias_issues(&self) -> &[AliasIssue] { + &self.alias_issues + } + pub fn sample_spec(&self) -> Option<&Value> { + self.sample_spec.as_ref() + } + pub fn fallback_generalizations(&self) -> Option<&FallbackGeneralizations> { + self.fallback_generalizations.as_ref() + } + pub fn fallback_rules(&self) -> Option<&[FallbackRule]> { + Some(self.fallback_generalizations.as_ref()?.rules.as_slice()) + } + pub fn provenance(&self) -> &Provenance { + &self.provenance + } +} diff --git a/litellm-rust/crates/model-catalog/src/error.rs b/litellm-rust/crates/model-catalog/src/error.rs new file mode 100644 index 00000000000..83617312fff --- /dev/null +++ b/litellm-rust/crates/model-catalog/src/error.rs @@ -0,0 +1,28 @@ +use thiserror::Error; + +/// Failures from parsing or validating a catalog snapshot. +#[derive(Debug, Error)] +pub enum Error { + /// The body is not valid JSON, or a model entry fails typed deserialization. + #[error("invalid JSON: {0}")] + Json(#[from] serde_json::Error), + /// The catalog has no entries at all. + #[error("catalog is empty")] + Empty, + /// A non-reserved top level value is not a JSON object. + #[error("model {model:?} must be an object")] + EntryNotObject { model: String }, + /// Canonical entry count is under the configured minimum. + #[error("catalog has {actual} models, below minimum {minimum}")] + BelowMinimum { actual: usize, minimum: usize }, + /// Canonical entry count is under the configured backup shrink ratio. + #[error("catalog has {actual} models, below {ratio} of backup count {backup}")] + Shrunk { + actual: usize, + backup: usize, + ratio: f64, + }, + /// The configured minimum backup ratio is not finite or outside `[0, 1]`. + #[error("minimum backup ratio must be finite and between zero and one")] + InvalidRatio, +} diff --git a/litellm-rust/crates/model-catalog/src/lib.rs b/litellm-rust/crates/model-catalog/src/lib.rs new file mode 100644 index 00000000000..9c942a5521c --- /dev/null +++ b/litellm-rust/crates/model-catalog/src/lib.rs @@ -0,0 +1,16 @@ +mod catalog; +mod error; +mod model_info; +#[cfg(feature = "schema")] +mod schema; + +pub use catalog::{AliasIssue, Catalog, IntegrityLimits, ModelEntry, ModelMatch, Provenance}; +pub use error::Error; +pub use model_info::{ + AudioFormat, FallbackGeneralizations, FallbackRule, InputModality, Mode, ModelInfo, + OffPeakPricing, OffPeakWindow, OutputModality, ReasoningEffort, SearchContextCostPerQuery, + TieredRate, UtcHours, VertexAiAudioApi, WebSearchBillingUnit, Weekday, +}; + +#[cfg(feature = "schema")] +pub use schema::model_entry_json_schema; diff --git a/litellm-rust/crates/model-catalog/src/model_info.rs b/litellm-rust/crates/model-catalog/src/model_info.rs new file mode 100644 index 00000000000..77a8b768e38 --- /dev/null +++ b/litellm-rust/crates/model-catalog/src/model_info.rs @@ -0,0 +1,665 @@ +use serde::{Deserialize, Serialize}; +use serde_json::Value; +use std::collections::BTreeMap; + +/// Primary API surface / task type of the model. +#[derive(Clone, Copy, Debug, Deserialize, Eq, PartialEq, Serialize)] +#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] +#[serde(rename_all = "snake_case")] +pub enum Mode { + AudioSpeech, + AudioTranscription, + Chat, + Completion, + Embedding, + Evaluation, + Guardrail, + ImageEdit, + ImageGeneration, + Moderation, + Ocr, + Realtime, + Rerank, + Responses, + Search, + VectorStore, + VideoGeneration, +} + +/// Reasoning effort level accepted or applied by the model. +#[derive(Clone, Copy, Debug, Deserialize, Eq, PartialEq, Serialize)] +#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] +#[serde(rename_all = "snake_case")] +pub enum ReasoningEffort { + None, + Minimal, + Low, + Medium, + High, + Xhigh, + Max, +} + +/// Gemini audio generation API the model is served through. +#[derive(Clone, Copy, Debug, Deserialize, Eq, PartialEq, Serialize)] +#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] +#[serde(rename_all = "snake_case")] +pub enum VertexAiAudioApi { + LyriaPredict, + LyriaInteractions, +} + +/// Whether web search is billed per query or per prompt. +#[derive(Clone, Copy, Debug, Deserialize, Eq, PartialEq, Serialize)] +#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] +#[serde(rename_all = "snake_case")] +pub enum WebSearchBillingUnit { + PerQuery, + PerPrompt, +} + +/// Audio container format the model can return. +#[derive(Clone, Copy, Debug, Deserialize, Eq, PartialEq, Serialize)] +#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] +#[serde(rename_all = "snake_case")] +pub enum AudioFormat { + Mp3, + Wav, +} + +/// Input modality the model accepts. +#[derive(Clone, Copy, Debug, Deserialize, Eq, PartialEq, Serialize)] +#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] +#[serde(rename_all = "snake_case")] +pub enum InputModality { + Text, + Image, + Audio, + Video, +} + +/// Output modality the model can produce. +#[derive(Clone, Copy, Debug, Deserialize, Eq, PartialEq, Serialize)] +#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] +#[serde(rename_all = "snake_case")] +pub enum OutputModality { + Text, + Image, + Audio, + Video, + Code, +} + +/// UTC "HH:MM-HH:MM" window, or a list of them; a window may wrap past midnight. +#[derive(Clone, Debug, Deserialize, PartialEq, Serialize)] +#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] +#[serde(untagged)] +pub enum UtcHours { + Single(String), + Multiple(Vec), +} + +/// ISO-8601 weekday number (1 = Monday .. 7 = Sunday) or English day name. +#[derive(Clone, Debug, Deserialize, PartialEq, Serialize)] +#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] +#[serde(untagged)] +pub enum Weekday { + Number(u8), + Name(String), +} + +/// One off-peak window entry inside `windows`. +#[derive(Clone, Debug, Deserialize, PartialEq, Serialize)] +#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] +#[serde(deny_unknown_fields)] +pub struct OffPeakWindow { + pub hours_utc: UtcHours, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub weekdays: Option>, +} + +/// Rates that replace the same-named base fields inside the stated UTC windows. +#[derive(Clone, Debug, Default, Deserialize, PartialEq, Serialize)] +#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] +#[serde(deny_unknown_fields)] +pub struct OffPeakPricing { + #[serde(default, skip_serializing_if = "Option::is_none")] + pub hours_utc: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub windows: Option>, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub weekday_timezone: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_token: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_token: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_reasoning_token: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_read_input_token_cost: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_creation_input_token_cost: Option, +} + +/// USD cost per web search query, keyed by search context size. +#[derive(Clone, Debug, Default, Deserialize, PartialEq, Serialize)] +#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] +#[serde(deny_unknown_fields)] +pub struct SearchContextCostPerQuery { + #[serde(default, skip_serializing_if = "Option::is_none")] + pub search_context_size_low: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub search_context_size_medium: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub search_context_size_high: Option, +} + +/// One tier of a context-length or result-count tiered rate. +#[derive(Clone, Debug, Default, Deserialize, PartialEq, Serialize)] +#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] +#[serde(deny_unknown_fields)] +pub struct TieredRate { + #[serde(default, skip_serializing_if = "Option::is_none")] + pub range: Option<[f64; 2]>, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub max_results_range: Option<[f64; 2]>, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_token: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_token: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_reasoning_token: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_read_input_token_cost: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_creation_input_token_cost: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_query: Option, +} + +/// One regex rule generalizing unknown model ids to known families. +#[derive(Clone, Debug, Deserialize, PartialEq, Serialize)] +#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] +pub struct FallbackRule { + pub name: String, + pub pattern: String, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub description: Option, + #[serde(flatten)] + pub extra: BTreeMap, +} + +/// Regex rules that generalize unknown model ids to known families; not a model entry. +#[derive(Clone, Debug, Deserialize, PartialEq, Serialize)] +#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] +#[serde(deny_unknown_fields)] +pub struct FallbackGeneralizations { + pub rules: Vec, +} + +/// Typed mirror of one catalog model entry. +#[derive(Clone, Debug, Deserialize, PartialEq, Serialize)] +#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] +pub struct ModelInfo { + #[serde(default, skip_serializing_if = "Option::is_none")] + pub annotation_cost_per_page: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub annotation_cost_per_page_batches: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub audio_transcription_config: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub bedrock_converse_supports_strict_tools: Option, + /// Highest reasoning effort the Bedrock output_config accepts for this model. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub bedrock_output_config_effort_ceiling: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_creation_input_audio_token_cost: Option, + /// USD per token written to the provider's prompt cache. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_creation_input_token_cost: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_creation_input_token_cost_above_128k_tokens: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_creation_input_token_cost_above_1hr: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_creation_input_token_cost_above_1hr_above_200k_tokens: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_creation_input_token_cost_above_200k_tokens: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_creation_input_token_cost_above_256k_tokens: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_creation_input_token_cost_above_272k_tokens: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_creation_input_token_cost_above_272k_tokens_batches: Option, + /// Flex service-tier rate for the same-named base field. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_creation_input_token_cost_above_272k_tokens_flex: Option, + /// Priority service-tier rate for the same-named base field. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_creation_input_token_cost_above_272k_tokens_priority: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_creation_input_token_cost_batches: Option, + /// Flex service-tier rate for the same-named base field. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_creation_input_token_cost_flex: Option, + /// Priority service-tier rate for the same-named base field. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_creation_input_token_cost_priority: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_read_input_audio_token_cost: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_read_input_image_token_cost: Option, + /// USD per prompt token served from the provider's prompt cache. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_read_input_token_cost: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_read_input_token_cost_above_128k_tokens: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_read_input_token_cost_above_200k_tokens: Option, + /// Priority service-tier rate for the same-named base field. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_read_input_token_cost_above_200k_tokens_priority: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_read_input_token_cost_above_256k_tokens: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_read_input_token_cost_above_272k_tokens: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_read_input_token_cost_above_272k_tokens_batches: Option, + /// Flex service-tier rate for the same-named base field. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_read_input_token_cost_above_272k_tokens_flex: Option, + /// Priority service-tier rate for the same-named base field. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_read_input_token_cost_above_272k_tokens_priority: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_read_input_token_cost_above_512k_tokens: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_read_input_token_cost_batches: Option, + /// Flex service-tier rate for the same-named base field. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_read_input_token_cost_flex: Option, + /// Priority service-tier rate for the same-named base field. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub cache_read_input_token_cost_priority: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub citation_cost_per_token: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub code_interpreter_cost_per_session: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub comment: Option, + /// Reasoning effort the provider applies when the request omits reasoning_effort. Gates whether a non-default temperature or the top_p/logprobs sampling params are accepted, which hold only when the effort resolves to 'none'. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub default_reasoning_effort: Option, + /// Date the provider deprecates the model, YYYY-MM-DD. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub deprecation_date: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub gemini_audio_only_live: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub gemini_native_audio: Option, + /// USD per Grounding with Google Maps request; billed per query or per prompt per web_search_billing_unit. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub google_maps_grounding_cost_per_query: Option, + /// USD cost per billable guardrail unit, keyed by the provider's usage counter name (e.g. Bedrock's contentPolicyUnits). + #[serde(default, skip_serializing_if = "Option::is_none")] + pub guardrail_cost_per_unit: Option>, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_audio_per_second: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_audio_per_second_above_128k_tokens: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_audio_token: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_audio_token_batches: Option, + /// Priority service-tier rate for the same-named base field. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_audio_token_priority: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_character: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_character_above_128k_tokens: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_image: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_image_above_128k_tokens: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_image_token: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_image_token_batches: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_pixel: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_query: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_request: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_second: Option, + /// USD per prompt token. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_token: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_token_above_128k_tokens: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_token_above_200k_tokens: Option, + /// Priority service-tier rate for the same-named base field. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_token_above_200k_tokens_priority: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_token_above_256k_tokens: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_token_above_272k_tokens: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_token_above_272k_tokens_batches: Option, + /// Flex service-tier rate for the same-named base field. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_token_above_272k_tokens_flex: Option, + /// Priority service-tier rate for the same-named base field. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_token_above_272k_tokens_priority: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_token_above_512k_tokens: Option, + /// USD per prompt token via the provider's batch API. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_token_batches: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_token_cache_hit: Option, + /// Flex service-tier rate for the same-named base field. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_token_flex: Option, + /// Priority service-tier rate for the same-named base field. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_token_priority: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_video_per_second: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_video_per_second_above_128k_tokens: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_video_per_second_above_15s_interval: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_video_per_second_above_8s_interval: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_video_token: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_cost_per_video_token_batches: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub input_dbu_cost_per_token: Option, + /// LiteLLM provider slug; one of https://docs.litellm.ai/docs/providers. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub litellm_provider: Option, + /// Maximum prompt/context tokens the model accepts. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub max_input_tokens: Option, + /// Maximum tokens the model can generate in one response. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub max_output_tokens: Option, + /// Legacy field: max output tokens if the provider specifies it, else max input tokens. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub max_tokens: Option, + /// Free-form notes about the entry (e.g. pricing derivation). + #[serde(default, skip_serializing_if = "Option::is_none")] + pub metadata: Option>, + /// Primary API surface / task type of the model. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub mode: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub ocr_cost_per_credit: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub ocr_cost_per_page: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub ocr_cost_per_page_batches: Option, + /// Rates that replace the same-named base fields while the request falls inside the stated UTC windows. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub off_peak_pricing: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_audio_token: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_character: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_character_above_128k_tokens: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_image: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_image_1024: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_image_1536: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_image_512: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_image_token: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_pixel: Option, + /// USD per reasoning/thinking token, when billed separately. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_reasoning_token: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_second: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_second_1080p: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_second_2k: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_second_480p: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_second_4k: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_second_720p: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_second_768p: Option, + /// USD per generated token. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_token: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_token_above_128k_tokens: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_token_above_200k_tokens: Option, + /// Priority service-tier rate for the same-named base field. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_token_above_200k_tokens_priority: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_token_above_256k_tokens: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_token_above_272k_tokens: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_token_above_272k_tokens_batches: Option, + /// Flex service-tier rate for the same-named base field. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_token_above_272k_tokens_flex: Option, + /// Priority service-tier rate for the same-named base field. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_token_above_272k_tokens_priority: Option, + /// Rate applied once the prompt exceeds the token threshold in the field name. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_token_above_512k_tokens: Option, + /// USD per generated token via the provider's batch API. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_token_batches: Option, + /// Flex service-tier rate for the same-named base field. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_token_flex: Option, + /// Priority service-tier rate for the same-named base field. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_token_priority: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_video_per_second: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_cost_per_video_token: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_dbu_cost_per_token: Option, + /// Embedding dimension for embedding models. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub output_vector_size: Option, + /// Smallest prefix the provider will actually cache; absent means the provider default applies. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub prompt_cache_min_tokens: Option, + /// Provider-internal routing hints (e.g. bedrock_invocation_schema). + #[serde(default, skip_serializing_if = "Option::is_none")] + pub provider_specific_entry: Option>, + /// Exact reasoning_effort levels this deployment accepts; wins over supports_* flags. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub reasoning_effort_levels: Option>, + /// Multiplier applied to all token costs when served from a non-global Vertex AI endpoint (e.g. 1.10 = +10%). + #[serde(default, skip_serializing_if = "Option::is_none")] + pub regional_endpoint_uplift_multiplier: Option, + /// Multiplier applied to all token costs for EU data residency (e.g. 1.10 = +10%). + #[serde(default, skip_serializing_if = "Option::is_none")] + pub regional_processing_uplift_multiplier_eu: Option, + /// Multiplier applied to all token costs for US data residency (e.g. 1.10 = +10%). + #[serde(default, skip_serializing_if = "Option::is_none")] + pub regional_processing_uplift_multiplier_us: Option, + /// Provider default requests-per-minute limit. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub rpm: Option, + /// USD cost per web search query, keyed by search context size. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub search_context_cost_per_query: Option, + /// URL of the provider pricing/model page this entry was taken from. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub source: Option, + /// Audio container formats the model can return. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supported_audio_formats: Option>, + /// OpenAI-style API routes this model can be called through, e.g. /v1/chat/completions. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supported_endpoints: Option>, + /// Input modalities the model accepts. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supported_modalities: Option>, + /// Output modalities the model can produce. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supported_output_modalities: Option>, + /// Cloud regions the model is available in ('global' or region ids). + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supported_regions: Option>, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_adaptive_thinking: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_anthropic_compaction: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_anthropic_thinking_payload: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_assistant_prefill: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_audio_input: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_audio_output: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_computer_use: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_embedding_image_input: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_fast_mode: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_forced_tool_use: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_function_calling: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_image_input: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_image_size: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_legacy_thinking: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_low_reasoning_effort: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_max_reasoning_effort: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_mid_conversation_system: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_minimal_reasoning_effort: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_multimodal: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_native_streaming: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_native_structured_output: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_none_reasoning_effort: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_nova_canvas_image_edit: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_output_config: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_parallel_function_calling: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_parallel_tool_use_config: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_pdf_input: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_prompt_cache_breakpoint: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_prompt_caching: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_reasoning: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_response_schema: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_sampling_params: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_speed: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_system_messages: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_thinking_cache_preservation: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_tool_choice: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_tool_search: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_url_context: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_video_input: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_vision: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_web_search: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub supports_xhigh_reasoning_effort: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub thinking_always_on: Option, + /// Context-length or result-count tiered rates; each tier's costs apply within its range. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub tiered_pricing: Option>, + /// Provider default tokens-per-minute limit. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub tpm: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub use_openai_responses_path: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub uses_embed_content: Option, + #[serde(default, skip_serializing_if = "Option::is_none")] + pub vertex_ai_audio_api: Option, + /// Whether web search is billed per query or per prompt. + #[serde(default, skip_serializing_if = "Option::is_none")] + pub web_search_billing_unit: Option, +} diff --git a/litellm-rust/crates/model-catalog/src/schema.rs b/litellm-rust/crates/model-catalog/src/schema.rs new file mode 100644 index 00000000000..82cfd6c0352 --- /dev/null +++ b/litellm-rust/crates/model-catalog/src/schema.rs @@ -0,0 +1,7 @@ +use crate::model_info::ModelInfo; + +/// JSON Schema for one catalog model entry, mirroring +/// `model_prices_and_context_window.schema.json`'s `modelEntry` definition. +pub fn model_entry_json_schema() -> schemars::Schema { + schemars::schema_for!(ModelInfo) +} diff --git a/litellm-rust/crates/model-catalog/tests/catalog.rs b/litellm-rust/crates/model-catalog/tests/catalog.rs new file mode 100644 index 00000000000..bcadd38e908 --- /dev/null +++ b/litellm-rust/crates/model-catalog/tests/catalog.rs @@ -0,0 +1,253 @@ +use std::path::{Path, PathBuf}; + +use litellm_model_catalog::{AliasIssue, Catalog, Error, IntegrityLimits, Provenance}; +use rstest::{fixture, rstest}; +use serde_json::json; + +const ALPHA_FIXTURE: &[u8] = br#"{ + "sample_spec":{"explanation":"example"}, + "fallback_generalizations":{"rules":[{"name":"family","pattern":"^new-","model_info":{"mode":"chat"}}]}, + "Alpha":{"litellm_provider":"test","aliases":["short"],"price":0,"enabled":false, + "optional":null,"unknown":{"nested":[1,{"x":true}]}} +}"#; + +#[fixture] +fn repo_root() -> PathBuf { + Path::new(env!("CARGO_MANIFEST_DIR")).join("../../..") +} + +#[fixture] +fn current_catalog(repo_root: PathBuf) -> Catalog { + let body = std::fs::read(repo_root.join("model_prices_and_context_window.json")).unwrap(); + Catalog::parse(&body, Provenance::default()).unwrap() +} + +#[fixture] +fn backup_catalog(repo_root: PathBuf) -> Catalog { + let body = std::fs::read(repo_root.join("litellm/model_prices_and_context_window_backup.json")) + .unwrap(); + Catalog::parse(&body, Provenance::default()).unwrap() +} + +#[fixture] +fn fixture_catalog() -> Catalog { + Catalog::parse( + ALPHA_FIXTURE, + Provenance { + source: Some("fixture".into()), + revision: Some("rev".into()), + etag: None, + }, + ) + .unwrap() +} + +#[rstest] +fn preserves_fields_and_metadata(fixture_catalog: Catalog) { + let catalog = fixture_catalog; + let entry = catalog.lookup("SHORT").unwrap(); + assert_eq!(entry.canonical_key, "Alpha"); + assert_eq!(entry.matched_key, "short"); + assert_eq!(entry.entry.field("price"), Some(&json!(0))); + assert_eq!(entry.entry.field("enabled"), Some(&json!(false))); + assert_eq!(entry.entry.field("optional"), Some(&json!(null))); + assert_eq!(entry.entry.field("missing"), None); + assert_eq!( + entry.entry.field("unknown"), + Some(&json!({"nested":[1,{"x":true}]})) + ); + assert_eq!(entry.entry.field("aliases"), None); + assert_eq!(entry.entry.info().litellm_provider.as_deref(), Some("test")); + assert_eq!( + catalog.sample_spec(), + Some(&json!({"explanation":"example"})) + ); + assert_eq!(catalog.fallback_rules().unwrap().len(), 1); + assert_eq!(catalog.provenance().revision.as_deref(), Some("rev")); + assert_eq!(catalog.model_count(), 1); +} + +#[rstest] +fn snapshot_does_not_borrow_source() { + let mut source = ALPHA_FIXTURE.to_vec(); + let catalog = Catalog::parse(&source, Provenance::default()).unwrap(); + source.fill(b' '); + + let entry = catalog.lookup("short").unwrap(); + assert_eq!(entry.canonical_key, "Alpha"); + assert_eq!(entry.entry.field("price"), Some(&json!(0))); +} + +#[rstest] +#[case("Shared", "First")] +#[case("Second", "Second")] +#[case("shared", "Second")] +#[case("FIRST", "First")] +#[case("sHaReD", "Second")] +fn alias_collisions_and_case_fallback_follow_python_order( + #[case] lookup: &str, + #[case] expected: &str, +) { + let catalog = Catalog::parse( + br#"{ + "First":{"aliases":["Shared","Second","first"],"value":1}, + "Second":{"aliases":["Shared","sHaReD"],"value":2}, + "SHARED":{"value":3} + }"#, + Provenance::default(), + ) + .unwrap(); + assert_eq!(catalog.lookup(lookup).unwrap().canonical_key, expected); + assert_eq!(catalog.alias_count(), 3); + assert!( + catalog + .alias_issues() + .contains(&AliasIssue::CanonicalCollision { + model: "First".into(), + alias: "Second".into(), + }) + ); + assert!( + catalog + .alias_issues() + .contains(&AliasIssue::AliasCollision { + model: "Second".into(), + alias: "Shared".into(), + }) + ); +} + +#[derive(Debug)] +enum ValidationOutcome { + Ok, + Shrunk, + BelowMinimum, + InvalidRatio, +} + +#[rstest] +#[case( + IntegrityLimits { + backup_model_count: 2, + min_model_count: 1, + min_backup_ratio: 0.5, + }, + ValidationOutcome::Ok +)] +#[case( + IntegrityLimits { + backup_model_count: 3, + min_model_count: 1, + min_backup_ratio: 0.5, + }, + ValidationOutcome::Shrunk +)] +#[case( + IntegrityLimits { + backup_model_count: 0, + min_model_count: 2, + min_backup_ratio: 0.5, + }, + ValidationOutcome::BelowMinimum +)] +#[case( + IntegrityLimits { + backup_model_count: 0, + min_model_count: 0, + min_backup_ratio: f64::NAN, + }, + ValidationOutcome::InvalidRatio +)] +fn integrity_uses_canonical_count_and_strict_shrink_boundary( + #[case] limits: IntegrityLimits, + #[case] expected: ValidationOutcome, +) { + let catalog = Catalog::parse( + br#"{"sample_spec":{},"fallback_generalizations":{"rules":[]},"a":{"aliases":["b","c"]}}"#, + Provenance::default(), + ) + .unwrap(); + let actual = catalog.validate(limits); + match expected { + ValidationOutcome::Ok => assert!(actual.is_ok()), + ValidationOutcome::Shrunk => { + assert!(matches!(actual, Err(Error::Shrunk { actual: 1, .. }))) + } + ValidationOutcome::BelowMinimum => { + assert!(matches!(actual, Err(Error::BelowMinimum { actual: 1, .. }))) + } + ValidationOutcome::InvalidRatio => assert!(matches!(actual, Err(Error::InvalidRatio))), + } +} + +#[derive(Debug)] +enum MalformedOutcome { + Empty, + Json, + EntryNotObject, +} + +#[rstest] +#[case::empty(b"{}", MalformedOutcome::Empty)] +#[case::invalid_json(b"{", MalformedOutcome::Json)] +#[case::entry_not_object(br#"{"a":1}"#, MalformedOutcome::EntryNotObject)] +#[case::fallback_rules_missing( + br#"{"fallback_generalizations":{},"a":{}}"#, + MalformedOutcome::Json +)] +fn malformed_input_and_aliases_have_typed_outcomes( + #[case] body: &[u8], + #[case] expected: MalformedOutcome, +) { + let actual = Catalog::parse(body, Provenance::default()); + match expected { + MalformedOutcome::Empty => assert!(matches!(actual, Err(Error::Empty))), + MalformedOutcome::Json => assert!(matches!(actual, Err(Error::Json(_)))), + MalformedOutcome::EntryNotObject => { + assert!(matches!(actual, Err(Error::EntryNotObject { .. }))) + } + } +} + +#[rstest] +fn invalid_aliases_are_reported_not_fatal() { + let catalog = Catalog::parse( + br#"{"a":{"aliases":"bad"},"b":{"aliases":[9,"ok"]}}"#, + Provenance::default(), + ) + .unwrap(); + assert_eq!( + catalog.alias_issues(), + &[ + AliasIssue::InvalidList { model: "a".into() }, + AliasIssue::InvalidName { model: "b".into() }, + ] + ); + assert_eq!(catalog.lookup("ok").unwrap().canonical_key, "b"); + assert!(catalog.lookup("missing").is_none()); +} + +#[rstest] +fn parses_current_and_packaged_catalogs_without_pinning_counts( + current_catalog: Catalog, + backup_catalog: Catalog, +) { + assert!(current_catalog.model_count() > 0); + assert!(backup_catalog.model_count() > 0); + assert!(current_catalog.sample_spec().is_some()); + assert!(backup_catalog.sample_spec().is_some()); + assert!( + current_catalog + .validate(IntegrityLimits::python_defaults( + backup_catalog.model_count() + )) + .is_ok() + ); + for name in current_catalog.model_names() { + let entry = current_catalog.lookup(name).unwrap().entry; + assert_eq!( + entry.info().litellm_provider.is_some(), + entry.field("litellm_provider").is_some() + ); + } +} diff --git a/litellm-rust/crates/model-catalog/tests/spec_parity.rs b/litellm-rust/crates/model-catalog/tests/spec_parity.rs new file mode 100644 index 00000000000..7296d96f798 --- /dev/null +++ b/litellm-rust/crates/model-catalog/tests/spec_parity.rs @@ -0,0 +1,121 @@ +use std::collections::{BTreeSet, HashSet}; +use std::path::{Path, PathBuf}; + +use indexmap::IndexMap; +use litellm_model_catalog::{ + Catalog, FallbackGeneralizations, ModelInfo, Provenance, model_entry_json_schema, +}; +use rstest::{fixture, rstest}; +use serde_json::{Map, Value}; + +#[fixture] +fn repo_root() -> PathBuf { + Path::new(env!("CARGO_MANIFEST_DIR")).join("../../..") +} + +fn json_eq(left: &Value, right: &Value) -> bool { + match (left, right) { + (Value::Number(left), Value::Number(right)) => left.as_f64() == right.as_f64(), + (Value::Array(left), Value::Array(right)) => { + left.len() == right.len() && left.iter().zip(right).all(|(a, b)| json_eq(a, b)) + } + (Value::Object(left), Value::Object(right)) => { + left.len() == right.len() + && left + .iter() + .all(|(key, value)| right.get(key).is_some_and(|other| json_eq(value, other))) + } + _ => left == right, + } +} + +fn keys(value: &Map) -> BTreeSet { + value.keys().cloned().collect() +} + +fn symmetric_difference(left: &BTreeSet, right: &BTreeSet) -> BTreeSet { + left.symmetric_difference(right).cloned().collect() +} + +#[rstest] +#[case("model_prices_and_context_window.json")] +#[case("litellm/model_prices_and_context_window_backup.json")] +fn every_entry_round_trips_through_model_info(repo_root: PathBuf, #[case] filename: &str) { + let body = std::fs::read(repo_root.join(filename)).unwrap(); + let document: IndexMap = serde_json::from_slice(&body).unwrap(); + for (model_name, value) in document { + if matches!( + model_name.as_str(), + "sample_spec" | "fallback_generalizations" + ) { + continue; + } + let object = value + .as_object() + .unwrap_or_else(|| panic!("{model_name} is not an object")); + let info: ModelInfo = serde_json::from_value(value.clone()) + .unwrap_or_else(|error| panic!("{model_name} does not deserialize: {error}")); + let serialized = serde_json::to_value(info).unwrap(); + let serialized_object = serialized + .as_object() + .unwrap_or_else(|| panic!("{model_name} did not serialize as an object")); + let mut expected = object.clone(); + expected.remove("aliases"); + let expected_keys = keys(&expected); + let serialized_keys = keys(serialized_object); + assert_eq!( + expected_keys, + serialized_keys, + "{model_name} key difference: {:?}", + symmetric_difference(&expected_keys, &serialized_keys) + ); + assert!( + json_eq(&Value::Object(expected), &serialized), + "{model_name} changed during ModelInfo round-trip" + ); + } +} + +#[rstest] +fn fallback_generalizations_are_typed(repo_root: PathBuf) { + let body = std::fs::read(repo_root.join("model_prices_and_context_window.json")).unwrap(); + let document: Map = serde_json::from_slice(&body).unwrap(); + let Some(raw_rules) = document.get("fallback_generalizations") else { + return; + }; + let _: FallbackGeneralizations = serde_json::from_value(raw_rules.clone()).unwrap(); + let catalog = Catalog::parse(&body, Provenance::default()).unwrap(); + assert!( + catalog + .fallback_rules() + .is_some_and(|rules| !rules.is_empty()) + ); +} + +#[rstest] +fn generated_schema_properties_match_repo_schema(repo_root: PathBuf) { + let body = + std::fs::read(repo_root.join("model_prices_and_context_window.schema.json")).unwrap(); + let document: Value = serde_json::from_slice(&body).unwrap(); + let repo_entry_properties = document["$defs"]["modelEntry"]["properties"] + .as_object() + .unwrap(); + let generated = serde_json::to_value(model_entry_json_schema()).unwrap(); + let generated_properties = generated["properties"].as_object().unwrap(); + let expected = keys(repo_entry_properties); + let actual = keys(generated_properties); + assert_eq!( + expected, + actual, + "modelEntry property difference: {:?}", + symmetric_difference(&expected, &actual) + ); + + let repo_root_properties = document["properties"].as_object().unwrap(); + let actual_root: HashSet = repo_root_properties.keys().cloned().collect(); + let expected_root: HashSet = ["sample_spec", "fallback_generalizations"] + .into_iter() + .map(str::to_owned) + .collect(); + assert_eq!(actual_root, expected_root); +} From da82ea8e94b737b7f5873609edf1e842699e5aa2 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 16:30:29 -0700 Subject: [PATCH 056/101] fix(ui): let the Create Key user picker find users by user_id, not just email (#41687) * feat(ui): search users by id or email when assigning a key owner Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(ui): label users without an email by user id in key owner picker Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): freeze merged user-filter where, format create key test Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(proxy): suppress module-global patch findings in ui_view_users search test Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): keep merged user-filter where as a plain dict for prisma serialization Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(ui): forward search param from userFilterUICall to /user/filter/ui Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(ui): mention user ID in the Create Key user picker helper text Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: jesus Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- .../internal_user_endpoints.py | 14 +++- .../test_internal_user_endpoints.py | 66 +++++++++++++++++++ .../src/components/networking.test.ts | 23 +++++++ .../src/components/networking.tsx | 1 + .../create_key_button.integration.test.tsx | 53 ++++++++++----- .../organisms/create_key_button.tsx | 10 +-- ui/litellm-dashboard/src/lib/http/schema.d.ts | 4 +- 7 files changed, 148 insertions(+), 23 deletions(-) diff --git a/litellm/proxy/management_endpoints/internal_user_endpoints.py b/litellm/proxy/management_endpoints/internal_user_endpoints.py index 133181e9203..587ae416096 100644 --- a/litellm/proxy/management_endpoints/internal_user_endpoints.py +++ b/litellm/proxy/management_endpoints/internal_user_endpoints.py @@ -2741,6 +2741,10 @@ async def _resolve_team_org_filter( async def ui_view_users( user_id: str | None = fastapi.Query(default=None, description="User ID in the request parameters"), user_email: str | None = fastapi.Query(default=None, description="User email in the request parameters"), + search: str | None = fastapi.Query( + default=None, + description="Combined search: matches users whose 'user_id' or 'user_email' contains the value (case-insensitive).", + ), team_id: str | None = fastapi.Query( default=None, description="Team ID — used when a team admin searches for users to add to their team", @@ -2750,7 +2754,7 @@ async def ui_view_users( user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), ): """ - Filter users based on partial match of user_id or email with pagination. + Filter users based on partial match of user_id or email, or combined ``search``, with pagination. Behaviour depends on the ``scope_user_search_to_org`` UI-setting flag (stored in the ``litellm_uisettings`` table): @@ -2802,9 +2806,15 @@ async def ui_view_users( if org_filter_ids is not None: where_conditions["organization_memberships"] = {"some": {"organization_id": {"in": org_filter_ids}}} + where: Final[Mapping[str, object]] = { # mutable-ok: prisma serializes `where`, keep it a plain dict + key: value + for key, value in (*where_conditions.items(), *_user_search_where(search).items()) + if value is not None + } + # Query users with pagination and filters users: Final = await _user_table(prisma_client).find_many( - where=where_conditions, + where=where, skip=skip, take=page_size, order={"created_at": "desc"}, diff --git a/tests/test_litellm/proxy/management_endpoints/test_internal_user_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_internal_user_endpoints.py index 2d1049b143e..0465572235b 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_internal_user_endpoints.py +++ b/tests/test_litellm/proxy/management_endpoints/test_internal_user_endpoints.py @@ -2,6 +2,7 @@ import asyncio import hashlib import json import logging +from collections.abc import Mapping, Sequence from datetime import datetime, timezone from types import SimpleNamespace from typing import Final @@ -37,6 +38,7 @@ from litellm.proxy.management_endpoints.internal_user_endpoints import ( ui_view_users, ) from litellm.proxy.proxy_server import app +from litellm.types.proxy.management_endpoints.internal_user_endpoints import InsensitiveContains from tests.test_litellm.proxy.management_endpoints.jwt_key_mapping_doubles import ( CascadingJWTMappingTable, JWTMappingRow, @@ -119,6 +121,70 @@ async def test_ui_view_users_proxy_admin_no_org_filter(mocker): ) +UserWhereCondition = InsensitiveContains | Sequence[Mapping[str, InsensitiveContains]] + + +def _matches_user_where(row: LiteLLM_UserTableFiltered, where: Mapping[str, UserWhereCondition]) -> bool: + def matches(field: str, condition: UserWhereCondition) -> bool: + if not isinstance(condition, Mapping): + return any(_matches_user_where(row, branch) for branch in condition) + value: Final = {"user_id": row.user_id, "user_email": row.user_email}[field] + return value is not None and condition["contains"].lower() in value.lower() + + return all(matches(field, condition) for field, condition in where.items()) + + +@pytest.mark.parametrize( + "params, expected_user_ids", + [ + ({"search": "SVC"}, ["svc-bot"]), + ({"search": "ali"}, ["alice-admin"]), + ({"search": "example.com"}, ["alice-admin"]), + ({"search": "admin"}, ["alice-admin"]), + ({"user_email": "svc"}, []), + ({"user_id": "svc"}, ["svc-bot"]), + ({"search": "ali", "user_id": "svc"}, []), + ], +) +def test_ui_view_users_search_matches_user_id_or_email( + mocker: MockerFixture, params: Mapping[str, str], expected_user_ids: list[str] +): + """ + search= returns users whose user_id or user_email contains the value (case-insensitive), + including users with no email; user_id=/user_email= keep filtering a single field and AND with search. + """ + from litellm.proxy.auth.user_api_key_auth import user_api_key_auth + + users = ( + LiteLLM_UserTableFiltered(user_id="alice-admin", user_email="alice@example.com"), + LiteLLM_UserTableFiltered(user_id="svc-bot", user_email=None), + LiteLLM_UserTableFiltered(user_id="bob", user_email="bob@corp.io"), + ) + + async def mock_find_many(*, where: Mapping[str, UserWhereCondition], **_: object): + return [user for user in users if _matches_user_where(user, where)] + + mock_prisma_client = mocker.MagicMock() + mock_prisma_client.db.litellm_usertable.find_many = mock_find_many + mocker.patch( # test-quality-ok: endpoint reads settings via module global; same seam as sibling tests + "litellm.proxy.ui_crud_endpoints.proxy_setting_endpoints.get_ui_settings_cached", + return_value={}, + ) + mocker.patch( # test-quality-ok: endpoint reads prisma_client via module global; same seam as sibling tests + "litellm.proxy.proxy_server.prisma_client", mock_prisma_client + ) + app.dependency_overrides[user_api_key_auth] = lambda: UserAPIKeyAuth( + user_id="admin", user_role=LitellmUserRoles.PROXY_ADMIN + ) + try: + response = client.get("/user/filter/ui", params=params) + finally: + app.dependency_overrides.pop(user_api_key_auth, None) + + assert response.status_code == 200, response.text + assert [user["user_id"] for user in response.json()] == expected_user_ids + + @pytest.mark.asyncio async def test_ui_view_users_org_admin_filtered_by_org(mocker): """ diff --git a/ui/litellm-dashboard/src/components/networking.test.ts b/ui/litellm-dashboard/src/components/networking.test.ts index 3b2a17101ee..e14f1939ee1 100644 --- a/ui/litellm-dashboard/src/components/networking.test.ts +++ b/ui/litellm-dashboard/src/components/networking.test.ts @@ -913,3 +913,26 @@ describe("fetchMemoryList search serialization", () => { expect(lastParams(mockFetch).has("search")).toBe(false); }); }); + +describe("userFilterUICall", () => { + let currentFetch: typeof global.fetch; + + beforeEach(() => { + currentFetch = global.fetch; + }); + + afterEach(() => { + global.fetch = currentFetch; + }); + + it("forwards the search param to /user/filter/ui", async () => { + const mockFetch = vi.fn().mockResolvedValue({ ok: true, text: async () => "[]" } as any); + global.fetch = mockFetch as any; + + await Networking.userFilterUICall("sk-test", new URLSearchParams({ search: "svc" })); + + const parsed = new URL(mockFetch.mock.calls[0][0] as string, "http://localhost"); + expect(parsed.pathname).toContain("/user/filter/ui"); + expect(parsed.searchParams.get("search")).toBe("svc"); + }); +}); diff --git a/ui/litellm-dashboard/src/components/networking.tsx b/ui/litellm-dashboard/src/components/networking.tsx index d358d23408c..76c6a3cb935 100644 --- a/ui/litellm-dashboard/src/components/networking.tsx +++ b/ui/litellm-dashboard/src/components/networking.tsx @@ -1983,6 +1983,7 @@ export const userFilterUICall = async (accessToken: string, params: URLSearchPar user_email: params.get("user_email") || undefined, user_id: params.get("user_id") || undefined, team_id: params.get("team_id") || undefined, + search: params.get("search") || undefined, }, }); } catch (error) { diff --git a/ui/litellm-dashboard/src/components/organisms/create_key_button.integration.test.tsx b/ui/litellm-dashboard/src/components/organisms/create_key_button.integration.test.tsx index a6b37ac26ff..0bf3268379c 100644 --- a/ui/litellm-dashboard/src/components/organisms/create_key_button.integration.test.tsx +++ b/ui/litellm-dashboard/src/components/organisms/create_key_button.integration.test.tsx @@ -204,7 +204,8 @@ const openModal = async (props: Partial> return view; }; -const userSearchInput = (): Promise => screen.findByPlaceholderText("Type email to search for users"); +const userSearchInput = (): Promise => + screen.findByPlaceholderText("Type email or user ID to search for users"); const openSection = async (name: RegExp) => { await userEvent.click(await screen.findByRole("button", { name })); @@ -619,7 +620,7 @@ describe("CreateKey", () => { it("mounts the user search control only once Another User is chosen", async () => { await openModal(); - expect(screen.queryByPlaceholderText("Type email to search for users")).not.toBeInTheDocument(); + expect(screen.queryByPlaceholderText("Type email or user ID to search for users")).not.toBeInTheDocument(); await userEvent.click(screen.getByRole("radio", { name: "Another User" })); @@ -946,18 +947,18 @@ describe("CreateKey", () => { expect(vi.mocked(userFilterUICall)).toHaveBeenCalledTimes(1); const params = vi.mocked(userFilterUICall).mock.calls[0][1] as URLSearchParams; - expect(params.get("user_email")).toBe("alice"); + expect(params.get("search")).toBe("alice"); } finally { vi.useRealTimers(); } }); it("keeps the current search's users when an abandoned search answers last", async () => { - const answers = new Map void>(); + const answers = new Map void>(); vi.mocked(userFilterUICall).mockImplementation( (_accessToken, params) => new Promise((resolve) => { - answers.set(params.get("user_email") ?? "", resolve); + answers.set(params.get("search") ?? "", resolve); }) as never, ); @@ -984,12 +985,36 @@ describe("CreateKey", () => { expect(screen.getByRole("option", { name: "alice.smith@example.com (u-smith)" })).toBeInTheDocument(); }); - it("stops searching once the box is cleared and the abandoned search answers", async () => { - const answers = new Map void>(); + it("labels a user with no email by their user id", async () => { + const answers = new Map void>(); vi.mocked(userFilterUICall).mockImplementation( (_accessToken, params) => new Promise((resolve) => { - answers.set(params.get("user_email") ?? "", resolve); + answers.set(params.get("search") ?? "", resolve); + }) as never, + ); + + const user = userEvent.setup(); + renderCreateKey({ autoOpenCreate: true, prefillData: { owned_by: "another_user" } }); + const search = await userSearchInput(); + + await user.type(search, "svc"); + await waitFor(() => expect(answers.has("svc")).toBe(true), { timeout: 3000 }); + + await act(async () => { + answers.get("svc")?.([{ user_id: "svc-bot", user_email: null }]); + }); + + expect(await screen.findByRole("option", { name: "svc-bot" })).toBeInTheDocument(); + expect(screen.queryByRole("option", { name: /null/ })).not.toBeInTheDocument(); + }); + + it("stops searching once the box is cleared and the abandoned search answers", async () => { + const answers = new Map void>(); + vi.mocked(userFilterUICall).mockImplementation( + (_accessToken, params) => + new Promise((resolve) => { + answers.set(params.get("search") ?? "", resolve); }) as never, ); @@ -1013,11 +1038,11 @@ describe("CreateKey", () => { }); it("keeps searching while a newer search is still in flight", async () => { - const answers = new Map void>(); + const answers = new Map void>(); vi.mocked(userFilterUICall).mockImplementation( (_accessToken, params) => new Promise((resolve) => { - answers.set(params.get("user_email") ?? "", resolve); + answers.set(params.get("search") ?? "", resolve); }) as never, ); @@ -1047,12 +1072,12 @@ describe("CreateKey", () => { it("only warns about a failed search when it is the one the box is waiting on", async () => { const answers = new Map< string, - { resolve: (users: { user_id: string; user_email: string }[]) => void; reject: (error: Error) => void } + { resolve: (users: { user_id: string; user_email: string | null }[]) => void; reject: (error: Error) => void } >(); vi.mocked(userFilterUICall).mockImplementation( (_accessToken, params) => new Promise((resolve, reject) => { - answers.set(params.get("user_email") ?? "", { resolve, reject }); + answers.set(params.get("search") ?? "", { resolve, reject }); }) as never, ); @@ -1099,9 +1124,7 @@ describe("CreateKey", () => { ]; vi.mocked(userFilterUICall).mockImplementation( (_accessToken, params) => - Promise.resolve( - directory.filter((entry) => entry.user_email.includes(params.get("user_email") ?? "")), - ) as never, + Promise.resolve(directory.filter((entry) => entry.user_email.includes(params.get("search") ?? ""))) as never, ); const user = userEvent.setup({ advanceTimers: vi.advanceTimersByTime }); diff --git a/ui/litellm-dashboard/src/components/organisms/create_key_button.tsx b/ui/litellm-dashboard/src/components/organisms/create_key_button.tsx index 3127eab249e..25b986e4c9e 100644 --- a/ui/litellm-dashboard/src/components/organisms/create_key_button.tsx +++ b/ui/litellm-dashboard/src/components/organisms/create_key_button.tsx @@ -161,7 +161,7 @@ interface CreateKeyProps { interface User { user_id: string; - user_email: string; + user_email: string | null; role?: string; } @@ -570,7 +570,7 @@ const CreateKey: React.FC = ({ team, teams, data, addKey, autoOp setUserSearchLoading(true); try { const params = new URLSearchParams(); - params.append("user_email", searchText); // Always search by email + params.append("search", searchText); if (accessToken == null) { return; } @@ -579,7 +579,7 @@ const CreateKey: React.FC = ({ team, teams, data, addKey, autoOp const data: User[] = response; const options: SearchSelectOption[] = data.map((user) => ({ - label: `${user.user_email} (${user.user_id})`, + label: user.user_email ? `${user.user_email} (${user.user_id})` : user.user_id, value: user.user_id, })); @@ -729,7 +729,7 @@ const CreateKey: React.FC = ({ team, teams, data, addKey, autoOp onValueChange={control.onChange} onSearchChange={fetchUsers} isLoading={userSearchLoading} - placeholder="Type email to search for users" + placeholder="Type email or user ID to search for users" emptyText="No users found" loadingText="Searching..." inputId={control.id} @@ -741,7 +741,7 @@ const CreateKey: React.FC = ({ team, teams, data, addKey, autoOp Create User -
Search by email to find users
+
Search by email or user ID to find users
)} diff --git a/ui/litellm-dashboard/src/lib/http/schema.d.ts b/ui/litellm-dashboard/src/lib/http/schema.d.ts index be1e000bd66..df294a20e19 100644 --- a/ui/litellm-dashboard/src/lib/http/schema.d.ts +++ b/ui/litellm-dashboard/src/lib/http/schema.d.ts @@ -17325,7 +17325,7 @@ export interface paths { }; /** * Ui View Users - * @description Filter users based on partial match of user_id or email with pagination. + * @description Filter users based on partial match of user_id or email, or combined ``search``, with pagination. * * Behaviour depends on the ``scope_user_search_to_org`` UI-setting flag * (stored in the ``litellm_uisettings`` table): @@ -64338,6 +64338,8 @@ export interface operations { user_id?: string | null; /** @description User email in the request parameters */ user_email?: string | null; + /** @description Combined search: matches users whose 'user_id' or 'user_email' contains the value (case-insensitive). */ + search?: string | null; /** @description Team ID — used when a team admin searches for users to add to their team */ team_id?: string | null; /** @description Page number for pagination */ From 13691426c4610f10da9627388a53419196a989ee Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 16:52:05 -0700 Subject: [PATCH 057/101] test(cost_calculator): point image-generation deployment price test at a live gemini row (#42615) The test priced gemini/gemini-3.1-flash-image-preview, which #42435 removed from the cost map as deprecated, so the calculator had no per-token rates to keep and the hardcoded expected value no longer matched. Price the live gemini/gemini-3.1-flash-image row instead and derive the expected cost from that row in litellm.model_cost, so a rate change on it cannot break the test while a calculator that drops the map's token rates still fails it. Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- tests/test_litellm/test_cost_calculator.py | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/tests/test_litellm/test_cost_calculator.py b/tests/test_litellm/test_cost_calculator.py index e7ce9a74797..c6b57fa7604 100644 --- a/tests/test_litellm/test_cost_calculator.py +++ b/tests/test_litellm/test_cost_calculator.py @@ -595,6 +595,8 @@ def test_completion_cost_image_generation_registered_deployment_price_keeps_map_ deployment_id, {"mode": "image_generation", "litellm_provider": "gemini", "output_cost_per_image": 0.1}, ) + map_model: Final = "gemini/gemini-3.1-flash-image" + row: Final = litellm.model_cost[map_model] usage: Final = ImageUsage( input_tokens=10, input_tokens_details=ImageUsageInputTokensDetails(image_tokens=0, text_tokens=10), @@ -604,7 +606,7 @@ def test_completion_cost_image_generation_registered_deployment_price_keeps_map_ cost = completion_cost( completion_response=ImageResponse(data=[ImageObject(url="https://example.com/img.png")], usage=usage), - model="gemini/gemini-3.1-flash-image-preview", + model=map_model, custom_llm_provider="gemini", call_type="image_generation", custom_pricing=True, @@ -612,7 +614,10 @@ def test_completion_cost_image_generation_registered_deployment_price_keeps_map_ litellm_logging_obj=SimpleNamespace(litellm_params={"metadata": {"model_info": {"id": deployment_id}}}), ) - assert cost == pytest.approx(10 * 5e-07 + 1290 * 6e-05) + expected: Final = ( + usage.input_tokens * row["input_cost_per_token"] + usage.output_tokens * row["output_cost_per_image_token"] + ) + assert cost == pytest.approx(expected) def test_completion_cost_image_generation_ignores_deployment_model_info_without_custom_pricing( From cf08cb89e81d4e744644428a09241da08b2996ce Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 17:04:13 -0700 Subject: [PATCH 058/101] test(utils): accept the per-size image cost keys in the price-map schema check (#42612) The cost map's fal_ai/fal-ai/trellis-2 entry prices its output by resolution with output_cost_per_image_512, output_cost_per_image_1024, and output_cost_per_image_1536, which litellm/types/utils.py types and the fal_ai cost calculator reads, but INTENDED_SCHEMA in test_aaamodel_prices_and_context_window_json_is_valid never allowed them, so the test fails on main with "Additional properties are not allowed". Add the three keys next to output_cost_per_image in the schema and in the cost-under-1 field list so a per-size image price is validated like the per-size video ones Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- tests/test_litellm/test_utils.py | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/tests/test_litellm/test_utils.py b/tests/test_litellm/test_utils.py index 79462d16a8c..283cff97ce0 100644 --- a/tests/test_litellm/test_utils.py +++ b/tests/test_litellm/test_utils.py @@ -631,6 +631,9 @@ def validate_model_cost_values(model_data, exceptions=None): "output_cost_per_character", "input_cost_per_image", "output_cost_per_image", + "output_cost_per_image_512", + "output_cost_per_image_1024", + "output_cost_per_image_1536", "input_cost_per_pixel", "output_cost_per_pixel", "input_cost_per_second", @@ -858,6 +861,9 @@ def test_aaamodel_prices_and_context_window_json_is_valid(): "output_cost_per_character": {"type": "number"}, "output_cost_per_character_above_128k_tokens": {"type": "number"}, "output_cost_per_image": {"type": "number"}, + "output_cost_per_image_512": {"type": "number"}, + "output_cost_per_image_1024": {"type": "number"}, + "output_cost_per_image_1536": {"type": "number"}, "output_cost_per_image_token": {"type": "number"}, "output_cost_per_video_token": {"type": "number"}, "output_cost_per_pixel": {"type": "number"}, From 9bad2c35e51f34abd0557877fe03f565f9657067 Mon Sep 17 00:00:00 2001 From: Pawan Shahane <110886433+Pawan-Shahane@users.noreply.github.com> Date: Wed, 23 Sep 2026 05:39:39 +0530 Subject: [PATCH 059/101] fix(ollama): send PNG and JPEG images without requiring Pillow. (#41979) * fix(ollama): send PNG and JPEG images without requiring Pillow The ollama/ completion transport imported Pillow before it looked at the image, so every image request failed with a 500 on installs without Pillow. That includes the Docker image, where Pillow is only a CI dependency Detect PNG and JPEG from their leading bytes and pass them through untouched. Pillow is now imported only when another format has to be re-encoded as JPEG, and that case still raises the same install hint * fix(ollama): address Greptile findings on image conversion Catch all exceptions on Pillow import, not just ImportError, so the helpful install hint always appears. Break a line that exceeded 120 characters --- litellm/llms/ollama/common_utils.py | 36 ++++----- .../test_ollama_completion_transformation.py | 74 +++++++++++++++++++ 2 files changed, 92 insertions(+), 18 deletions(-) diff --git a/litellm/llms/ollama/common_utils.py b/litellm/llms/ollama/common_utils.py index ed4bab22a84..9f46cbc5cd5 100644 --- a/litellm/llms/ollama/common_utils.py +++ b/litellm/llms/ollama/common_utils.py @@ -1,3 +1,5 @@ +import base64 +import io from typing import Any, Final import httpx @@ -11,37 +13,35 @@ class OllamaError(BaseLLMException): super().__init__(status_code=status_code, message=message, headers=headers) -def _convert_image(image): - """ - Convert image to base64 encoded image if not already in base64 format +_JPEG_AND_PNG_SIGNATURES: Final = (b"\xff\xd8\xff", b"\x89PNG\r\n\x1a\n") - If image is already in base64 format AND is a jpeg/png, return it - - If image is not JPEG/PNG, convert it to JPEG base64 format - """ - import base64 - import io +def _reencode_as_jpeg(raw_image: bytes, original: str) -> str: try: from PIL import Image except Exception: raise Exception("ollama image conversion failed please run `pip install Pillow`") - orig: Final = image - if image.startswith("data:"): - image = image.split(",")[-1] try: - image_data: Final = Image.open(io.BytesIO(base64.b64decode(image))) - if image_data.format in ["JPEG", "PNG"]: - return image + picture: Final = Image.open(io.BytesIO(raw_image)) except Exception: - return orig + return original jpeg_image: Final = io.BytesIO() - image_data.convert("RGB").save(jpeg_image, "JPEG") - jpeg_image.seek(0) + picture.convert("RGB").save(jpeg_image, "JPEG") return base64.b64encode(jpeg_image.getvalue()).decode("utf-8") +def _convert_image(image: str) -> str: + payload: Final = image.split(",")[-1] if image.startswith("data:") else image + try: + raw_image: Final = base64.b64decode(payload) + except ValueError: + return image + if raw_image.startswith(_JPEG_AND_PNG_SIGNATURES): + return payload + return _reencode_as_jpeg(raw_image, original=image) + + from litellm.llms.base_llm.base_utils import BaseLLMModelInfo diff --git a/tests/test_litellm/llms/ollama/test_ollama_completion_transformation.py b/tests/test_litellm/llms/ollama/test_ollama_completion_transformation.py index b2071155f3f..28e86e40944 100644 --- a/tests/test_litellm/llms/ollama/test_ollama_completion_transformation.py +++ b/tests/test_litellm/llms/ollama/test_ollama_completion_transformation.py @@ -1,4 +1,7 @@ +import base64 +import io import json +import sys from litellm._uuid import uuid from unittest.mock import MagicMock, patch @@ -544,3 +547,74 @@ async def test_ollama_async_completion_inlines_remote_images_off_the_event_loop( assert response.choices[0].message.content == "Green" assert async_only_image_fetch.fetched == [image_url] assert captured["body"]["images"] == [async_only_image_fetch.base64_png] + + +def _image_base64(image_format: str) -> str: + from PIL import Image + + buffer = io.BytesIO() + Image.new("RGB", (4, 4), "green").save(buffer, image_format) + return base64.b64encode(buffer.getvalue()).decode("utf-8") + + +def _transform_image_request(image_base64: str, mime_subtype: str) -> dict: + return OllamaConfig().transform_request( + model="llava", + messages=[ + { + "role": "user", + "content": [ + {"type": "text", "text": "What colour is this?"}, + { + "type": "image_url", + "image_url": {"url": f"data:image/{mime_subtype};base64,{image_base64}"}, + }, + ], + } + ], + optional_params={}, + litellm_params={}, + headers={}, + ) + + +@pytest.mark.parametrize("image_format", ["PNG", "JPEG"]) +def test_transform_request_sends_png_and_jpeg_images_without_pillow( + image_format: str, monkeypatch: pytest.MonkeyPatch +) -> None: + image_base64 = _image_base64(image_format) + monkeypatch.setitem(sys.modules, "PIL", None) + + data = _transform_image_request(image_base64, image_format.lower()) + + assert data["images"] == [image_base64] + + +def test_transform_request_without_pillow_says_how_to_convert_other_image_formats( + monkeypatch: pytest.MonkeyPatch, +) -> None: + gif_base64 = _image_base64("GIF") + monkeypatch.setitem(sys.modules, "PIL", None) + + with pytest.raises(Exception, match="pip install Pillow"): + _transform_image_request(gif_base64, "gif") + + +def test_transform_request_reencodes_other_image_formats_as_jpeg() -> None: + from PIL import Image + + data = _transform_image_request(_image_base64("GIF"), "gif") + + (encoded,) = data["images"] + assert Image.open(io.BytesIO(base64.b64decode(encoded))).format == "JPEG" + + +@pytest.mark.parametrize( + "payload", + [base64.b64encode(b"not an image").decode("utf-8"), "abc"], + ids=["decodable_but_not_an_image", "invalid_base64"], +) +def test_transform_request_leaves_unreadable_images_untouched(payload: str) -> None: + data = _transform_image_request(payload, "png") + + assert data["images"] == [payload] From ca95fc2bd4185483e91cdd62093b6fdb339f82f3 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 17:23:44 -0700 Subject: [PATCH 060/101] fix: answer get_api_base for github_copilot and chatgpt without running the login flow (#42602) * fix: answer get_api_base for github_copilot and chatgpt without running the login flow * refactor(get_api_base): dispatch the provider helpers with if-chains --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- .../llm_response_utils/get_api_base.py | 39 +++++--- litellm/llms/chatgpt/chat/transformation.py | 5 +- .../github_copilot/chat/transformation.py | 15 +-- .../llm_response_utils/test_get_api_base.py | 93 +++++++++++++++++++ tests/test_litellm/rerank_api/test_main.py | 4 +- 5 files changed, 134 insertions(+), 22 deletions(-) create mode 100644 tests/test_litellm/litellm_core_utils/llm_response_utils/test_get_api_base.py diff --git a/litellm/litellm_core_utils/llm_response_utils/get_api_base.py b/litellm/litellm_core_utils/llm_response_utils/get_api_base.py index 26e79fa0ea8..3815ea91b51 100644 --- a/litellm/litellm_core_utils/llm_response_utils/get_api_base.py +++ b/litellm/litellm_core_utils/llm_response_utils/get_api_base.py @@ -3,10 +3,30 @@ from typing import Final import litellm from litellm import verbose_logger -from ...litellm_core_utils.get_llm_provider_logic import get_llm_provider +from ...litellm_core_utils.get_llm_provider_logic import ( + declared_authenticating_provider, + get_llm_provider, +) from ...types.router import LiteLLM_Params +def _api_base_without_login(provider: str) -> str | None: + if provider == "github_copilot": + return litellm.GithubCopilotConfig().api_base_without_login() + if provider == "chatgpt": + return litellm.ChatGPTConfig().api_base_without_login() + return None + + +def _provider_default_api_base(model: str, custom_llm_provider: str | None, stream: bool) -> str | None: + if custom_llm_provider == "gemini": + action: Final = "streamGenerateContent" if stream else "generateContent" + return f"https://generativelanguage.googleapis.com/v1beta/models/{model}:{action}" + if custom_llm_provider == "openai": + return "https://api.openai.com" + return None + + def get_api_base(model: str, optional_params: dict | LiteLLM_Params) -> str | None: """ Returns the api base used for calling the model. @@ -42,6 +62,9 @@ def get_api_base(model: str, optional_params: dict | LiteLLM_Params) -> str | No if litellm.model_alias_map and model in litellm.model_alias_map: model = litellm.model_alias_map[model] + declared: Final = declared_authenticating_provider(model, _optional_params.custom_llm_provider) + if declared is not None: + return _api_base_without_login(declared) try: ( model, @@ -83,16 +106,4 @@ def get_api_base(model: str, optional_params: dict | LiteLLM_Params) -> str | No _api_base = f"{_optional_params.vertex_location}-aiplatform.googleapis.com/v1/projects/{_optional_params.vertex_project}/locations/{_optional_params.vertex_location}/publishers/google/models/{model}:generateContent" return _api_base - if custom_llm_provider is None: - return None - - if custom_llm_provider == "gemini": - if stream: - _api_base = f"https://generativelanguage.googleapis.com/v1beta/models/{model}:streamGenerateContent" - else: - _api_base = f"https://generativelanguage.googleapis.com/v1beta/models/{model}:generateContent" - return _api_base - elif custom_llm_provider == "openai": - _api_base = "https://api.openai.com" - return _api_base - return None + return _provider_default_api_base(model, custom_llm_provider, stream) diff --git a/litellm/llms/chatgpt/chat/transformation.py b/litellm/llms/chatgpt/chat/transformation.py index e35408b0829..1b110704c8b 100644 --- a/litellm/llms/chatgpt/chat/transformation.py +++ b/litellm/llms/chatgpt/chat/transformation.py @@ -23,6 +23,9 @@ class ChatGPTConfig(OpenAIConfig): super().__init__() self.authenticator = Authenticator() + def api_base_without_login(self) -> str: + return self.authenticator.get_api_base() + def _get_openai_compatible_provider_info( self, model: str, @@ -30,7 +33,7 @@ class ChatGPTConfig(OpenAIConfig): api_key: str | None, custom_llm_provider: str, ) -> tuple[str | None, str | None, str]: - dynamic_api_base: Final = self.authenticator.get_api_base() + dynamic_api_base: Final = self.api_base_without_login() try: dynamic_api_key: Final = self.authenticator.get_access_token() except GetAccessTokenError as e: diff --git a/litellm/llms/github_copilot/chat/transformation.py b/litellm/llms/github_copilot/chat/transformation.py index 8634b374f1b..169b9a037a5 100644 --- a/litellm/llms/github_copilot/chat/transformation.py +++ b/litellm/llms/github_copilot/chat/transformation.py @@ -31,6 +31,14 @@ class GithubCopilotConfig(OpenAIConfig): super().__init__() self.authenticator = Authenticator() + def api_base_without_login(self, api_base: str | None = None) -> str: + return ( + api_base + or self.authenticator.get_api_base() + or os.getenv("GITHUB_COPILOT_API_BASE") + or DEFAULT_GITHUB_COPILOT_API_BASE + ) + def _get_openai_compatible_provider_info( self, model: str, @@ -38,12 +46,7 @@ class GithubCopilotConfig(OpenAIConfig): api_key: str | None, custom_llm_provider: str, ) -> tuple[str | None, str | None, str]: - dynamic_api_base: Final = ( - api_base - or self.authenticator.get_api_base() - or os.getenv("GITHUB_COPILOT_API_BASE") - or DEFAULT_GITHUB_COPILOT_API_BASE - ) + dynamic_api_base: Final = self.api_base_without_login(api_base) try: dynamic_api_key: Final = self.authenticator.get_api_key() except GetAPIKeyError as e: diff --git a/tests/test_litellm/litellm_core_utils/llm_response_utils/test_get_api_base.py b/tests/test_litellm/litellm_core_utils/llm_response_utils/test_get_api_base.py new file mode 100644 index 00000000000..63977c30270 --- /dev/null +++ b/tests/test_litellm/litellm_core_utils/llm_response_utils/test_get_api_base.py @@ -0,0 +1,93 @@ +import json + +import pytest + +import litellm +from litellm.litellm_core_utils.llm_response_utils import get_api_base as get_api_base_module +from litellm.llms.chatgpt.common_utils import CHATGPT_API_BASE +from litellm.llms.github_copilot.common_utils import DEFAULT_GITHUB_COPILOT_API_BASE + + +@pytest.fixture +def isolated_token_dirs(tmp_path, monkeypatch): + monkeypatch.setenv("GITHUB_COPILOT_TOKEN_DIR", str(tmp_path / "github_copilot")) + monkeypatch.setenv("CHATGPT_TOKEN_DIR", str(tmp_path / "chatgpt")) + monkeypatch.delenv("GITHUB_COPILOT_API_BASE", raising=False) + monkeypatch.delenv("CHATGPT_API_BASE", raising=False) + monkeypatch.delenv("OPENAI_CHATGPT_API_BASE", raising=False) + return tmp_path + + +@pytest.fixture +def resolution_lookups(monkeypatch): + lookups: list = [] + + def _record(*args, **kwargs): + lookups.append((args, kwargs)) + raise RuntimeError("provider resolution must not run for an authenticating provider") + + monkeypatch.setattr(get_api_base_module, "get_llm_provider", _record) + return lookups + + +class TestDeclaredAuthenticatingProvider: + """get_llm_provider runs the OAuth device flow for github_copilot and chatgpt, and get_api_base + runs on every response's hidden params and on every mapped exception, so it must answer from + the declaration without resolving. The recorder appends before raising, and get_api_base + swallows resolver errors, so an empty list proves the lookup never ran.""" + + @pytest.mark.parametrize( + "model, custom_llm_provider, expected", + [ + ("github_copilot/gpt-4o", None, DEFAULT_GITHUB_COPILOT_API_BASE), + ("gpt-4o", "github_copilot", DEFAULT_GITHUB_COPILOT_API_BASE), + ("chatgpt/gpt-5", None, CHATGPT_API_BASE), + ("gpt-5", "chatgpt", CHATGPT_API_BASE), + ], + ) + def test_answers_without_resolving( + self, model, custom_llm_provider, expected, isolated_token_dirs, resolution_lookups + ): + api_base = litellm.get_api_base(model=model, optional_params={"custom_llm_provider": custom_llm_provider}) + + assert resolution_lookups == [] + assert api_base == expected + + def test_copilot_keeps_the_enterprise_endpoint_from_disk(self, isolated_token_dirs, resolution_lookups): + token_dir = isolated_token_dirs / "github_copilot" + token_dir.mkdir() + (token_dir / "api-key.json").write_text( + json.dumps({"endpoints": {"api": "https://api.enterprise.githubcopilot.com"}}) + ) + + api_base = litellm.get_api_base(model="github_copilot/gpt-4o", optional_params={}) + + assert resolution_lookups == [] + assert api_base == "https://api.enterprise.githubcopilot.com" + + def test_explicit_api_base_still_wins(self, isolated_token_dirs, resolution_lookups): + api_base = litellm.get_api_base( + model="github_copilot/gpt-4o", optional_params={"api_base": "https://copilot.example/v1"} + ) + + assert resolution_lookups == [] + assert api_base == "https://copilot.example/v1" + + def test_other_providers_still_resolve(self, isolated_token_dirs, resolution_lookups): + litellm.get_api_base(model="openai/gpt-4o", optional_params={}) + + assert len(resolution_lookups) == 1 + + +@pytest.mark.parametrize( + "model, expected", + [ + ("gemini/gemini-2.5-pro", "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-pro:generateContent"), + ("openai/gpt-4o", "https://api.openai.com"), + ], +) +def test_providers_with_a_fixed_base_still_get_it(model, expected, monkeypatch): + for env in ("GEMINI_API_BASE", "OPENAI_API_BASE", "OPENAI_BASE_URL"): + monkeypatch.delenv(env, raising=False) + + assert litellm.get_api_base(model=model, optional_params={}) == expected diff --git a/tests/test_litellm/rerank_api/test_main.py b/tests/test_litellm/rerank_api/test_main.py index aca0c970dd5..f56673fec30 100644 --- a/tests/test_litellm/rerank_api/test_main.py +++ b/tests/test_litellm/rerank_api/test_main.py @@ -239,7 +239,6 @@ async def test_arerank_error_is_mapped_to_litellm_exception(respx_mock: respx.Mo @pytest.mark.asyncio -@pytest.mark.timeout(300) async def test_arerank_declared_authenticating_provider_skips_resolution(monkeypatch): """Regression for the event-loop hazard in arerank's provider pre-resolution: get_llm_provider runs the blocking OAuth device flow for github_copilot/chatgpt, @@ -257,6 +256,9 @@ async def test_arerank_declared_authenticating_provider_skips_resolution(monkeyp raise BaseLLMException(status_code=401, message='{"error":"bad key"}') monkeypatch.setattr(litellm, "get_llm_provider", record_resolution) + monkeypatch.setattr( + "litellm.litellm_core_utils.llm_response_utils.get_api_base.get_llm_provider", record_resolution + ) monkeypatch.setattr("litellm.rerank_api.main.rerank", rerank_raises_provider_error) with pytest.raises(litellm.AuthenticationError) as exc_info: From 4f93e2c3da75289393af1b9e2ddb28935b4e11da Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Tue, 22 Sep 2026 17:28:34 -0700 Subject: [PATCH 061/101] test: point CircleCI-only suites at models still in the cost map (#42617) * test: point CircleCI-only suites at models still in the cost map #42435 removed cost map entries past their deprecation date and #42437 added litellm_uisettings to the config-synced tables, but both only updated tests/test_litellm. The CircleCI-only suites (local_testing, llm_translation, logging_callback_tests, litellm_utils_tests, unit) kept using the removed models or the old table list and went red on main. Each test keeps its assertions and swaps the removed model for a current one with the same provider and capabilities. The fireworks tests pick a vision model from the cost map because #34941 set supports_vision false on minimax-m3, and the vertex image provider test injects the image model set because #42435 removed every vertex_ai-image-models entry. * test(vertex_ai): register the image model through add_known_models in the provider test --- tests/litellm_utils_tests/test_utils.py | 2 +- .../test_fireworks_ai_translation.py | 14 ++++-- .../test_gemini_image_usage.py | 2 +- tests/llm_translation/test_groq.py | 2 +- tests/llm_translation/test_optional_params.py | 8 +-- tests/llm_translation/test_xai.py | 2 +- .../test_amazing_vertex_completion.py | 6 +-- tests/local_testing/test_completion_cost.py | 50 +++++++++---------- tests/local_testing/test_exceptions.py | 2 +- .../test_function_call_parsing.py | 2 +- tests/local_testing/test_get_llm_provider.py | 18 +++++-- tests/local_testing/test_get_model_info.py | 4 +- .../local_testing/test_lowest_cost_routing.py | 2 +- .../test_openai_moderations_hook.py | 6 +-- tests/local_testing/test_router_utils.py | 24 ++++----- .../test_spend_calculate_endpoint.py | 4 +- .../completion_with_vertex_call.json | 10 ++-- tests/logging_callback_tests/test_alerting.py | 6 +-- .../test_langfuse_e2e_test.py | 4 +- tests/unit/repositories/test_repositories.py | 1 + 20 files changed, 93 insertions(+), 76 deletions(-) diff --git a/tests/litellm_utils_tests/test_utils.py b/tests/litellm_utils_tests/test_utils.py index f7575b969c4..fb20cdf7e0e 100644 --- a/tests/litellm_utils_tests/test_utils.py +++ b/tests/litellm_utils_tests/test_utils.py @@ -263,7 +263,7 @@ def test_trimming_should_not_change_original_messages(): assert messages == messages_copy -@pytest.mark.parametrize("model", ["gpt-4-0125-preview", "claude-sonnet-4-6"]) +@pytest.mark.parametrize("model", ["gpt-5.4-mini", "claude-sonnet-4-6"]) def test_trimming_with_model_cost_max_input_tokens(model): messages = [ {"role": "system", "content": "This is a normal system message"}, diff --git a/tests/llm_translation/test_fireworks_ai_translation.py b/tests/llm_translation/test_fireworks_ai_translation.py index e20134fc1bf..a7dc913c388 100644 --- a/tests/llm_translation/test_fireworks_ai_translation.py +++ b/tests/llm_translation/test_fireworks_ai_translation.py @@ -9,6 +9,12 @@ from litellm.llms.fireworks_ai.chat.transformation import FireworksAIConfig fireworks = FireworksAIConfig() +VISION_MODEL = next( + key.removeprefix("fireworks_ai/") + for key, info in litellm.model_cost.items() + if key.startswith("fireworks_ai/accounts/fireworks/models/") and info.get("supports_vision") is True +) + def test_map_openai_params_tool_choice(): # Test case 1: tool_choice is "required" @@ -97,7 +103,7 @@ def test_document_inlining_example(disable_add_transform_inline_image_block): with patch.object(client, "post") as mock_post: try: completion( - model="fireworks_ai/accounts/fireworks/models/minimax-m3", + model=f"fireworks_ai/{VISION_MODEL}", messages=[ { "role": "user", @@ -157,7 +163,7 @@ def test_transform_inline_no_longer_added(content, expected_url): result = litellm.FireworksAIConfig()._transform_messages_helper( messages=messages, - model="accounts/fireworks/models/minimax-m3", + model=VISION_MODEL, litellm_params={}, ) result_image_block = result[0]["content"][0] @@ -182,7 +188,7 @@ def test_global_disable_flag_no_longer_adds_transform_inline(is_disabled): ] result = litellm.FireworksAIConfig()._transform_messages_helper( messages=messages, - model="accounts/fireworks/models/minimax-m3", + model=VISION_MODEL, litellm_params={}, ) assert result[0]["content"][0]["image_url"] == url @@ -204,7 +210,7 @@ def test_global_disable_flag_with_transform_messages_helper(monkeypatch): ) as mock_post: try: completion( - model="fireworks_ai/accounts/fireworks/models/minimax-m3", + model=f"fireworks_ai/{VISION_MODEL}", messages=[ { "role": "user", diff --git a/tests/llm_translation/test_gemini_image_usage.py b/tests/llm_translation/test_gemini_image_usage.py index 096f9c4796c..0be8b6c23e1 100644 --- a/tests/llm_translation/test_gemini_image_usage.py +++ b/tests/llm_translation/test_gemini_image_usage.py @@ -238,7 +238,7 @@ def test_gemini_image_generation_accumulates_multiple_image_prompt_token_details os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True" litellm.model_cost = litellm.get_model_cost_map(url="") - model = "gemini/gemini-3-pro-image-preview" + model = "gemini/gemini-3-pro-image" config = GoogleImageGenConfig() usage_metadata = { diff --git a/tests/llm_translation/test_groq.py b/tests/llm_translation/test_groq.py index c720f818eaf..fbecbeab08b 100644 --- a/tests/llm_translation/test_groq.py +++ b/tests/llm_translation/test_groq.py @@ -32,7 +32,7 @@ class TestGroq(BaseLLMChatTest): @pytest.mark.parametrize( "model", - ["groq/qwen/qwen3-32b", "groq/openai/gpt-oss-20b", "groq/openai/gpt-oss-120b"], + ["groq/qwen/qwen3.8-27b", "groq/openai/gpt-oss-20b", "groq/openai/gpt-oss-120b"], ) def test_reasoning_effort_in_supported_params(self, model): """Test that reasoning_effort is in the list of supported parameters for Groq""" diff --git a/tests/llm_translation/test_optional_params.py b/tests/llm_translation/test_optional_params.py index 997f5b3b73f..58446014bdf 100644 --- a/tests/llm_translation/test_optional_params.py +++ b/tests/llm_translation/test_optional_params.py @@ -537,7 +537,7 @@ def test_dynamic_drop_params_e2e(): ) as mock_response: try: response = litellm.completion( - model="command-r", + model="command-r-08-2024", messages=[{"role": "user", "content": "Hey, how's it going?"}], response_format={"key": "value"}, drop_params=True, @@ -556,7 +556,7 @@ def test_dynamic_pass_additional_params(): ) as mock_response: try: response = litellm.completion( - model="command-r", + model="command-r-08-2024", messages=[{"role": "user", "content": "Hey, how's it going?"}], custom_param="test", api_key="my-custom-key", @@ -606,7 +606,7 @@ def test_dynamic_drop_params_parallel_tool_calls(): ) as mock_response: try: response = litellm.completion( - model="command-r", + model="command-r-08-2024", messages=[{"role": "user", "content": "Hey, how's it going?"}], parallel_tool_calls=True, drop_params=True, @@ -663,7 +663,7 @@ def test_dynamic_drop_additional_params_e2e(): ) as mock_response: try: response = litellm.completion( - model="command-r", + model="command-r-08-2024", messages=[{"role": "user", "content": "Hey, how's it going?"}], response_format={"key": "value"}, additional_drop_params=["response_format"], diff --git a/tests/llm_translation/test_xai.py b/tests/llm_translation/test_xai.py index 7a121afc3fa..d6d42ed215e 100644 --- a/tests/llm_translation/test_xai.py +++ b/tests/llm_translation/test_xai.py @@ -164,7 +164,7 @@ def test_xai_message_name_filtering(): class TestXAIReasoningEffort(BaseReasoningLLMTests): def get_base_completion_call_args(self): return { - "model": "xai/grok-3-mini-beta", + "model": "xai/grok-4.7", "messages": [{"role": "user", "content": "Hello"}], } diff --git a/tests/local_testing/test_amazing_vertex_completion.py b/tests/local_testing/test_amazing_vertex_completion.py index 3d66064f5c0..8b45ae08813 100644 --- a/tests/local_testing/test_amazing_vertex_completion.py +++ b/tests/local_testing/test_amazing_vertex_completion.py @@ -2863,7 +2863,7 @@ def test_gemini_function_call_parameter_in_messages(): mock_client.return_value = mock_response try: completion( - model="vertex_ai/gemini-2.0-flash", + model="vertex_ai/gemini-2.5-flash-preview-09-2025", messages=messages, tools=tools, tool_choice="auto", @@ -3263,7 +3263,7 @@ def test_vertex_anthropic_completion(): client, "post", side_effect=vertex_ai_anthropic_thinking_mock_response ): response = completion( - model="vertex_ai/claude-3-7-sonnet@20250219", + model="vertex_ai/claude-sonnet-4-6@default", messages=[{"role": "user", "content": "Hello, world!"}], vertex_ai_location="us-east5", vertex_ai_project="test-project", @@ -3271,7 +3271,7 @@ def test_vertex_anthropic_completion(): client=client, ) print(response) - assert response.model == "claude-3-7-sonnet@20250219" + assert response.model == "claude-sonnet-4-6@default" assert response._hidden_params["response_cost"] is not None assert response._hidden_params["response_cost"] > 0 diff --git a/tests/local_testing/test_completion_cost.py b/tests/local_testing/test_completion_cost.py index f40818b9bf1..3ce99f893d8 100644 --- a/tests/local_testing/test_completion_cost.py +++ b/tests/local_testing/test_completion_cost.py @@ -445,7 +445,7 @@ def test_groq_response_cost_tracking(is_streaming): response_cost = litellm.response_cost_calculator( response_object=response, - model="groq/llama-3.3-70b-versatile", + model="groq/openai/gpt-oss-120b", custom_llm_provider="groq", call_type=CallTypes.acompletion.value, optional_params={}, @@ -515,7 +515,7 @@ def test_gemini_completion_cost(provider): """ os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True" litellm.model_cost = litellm.get_model_cost_map(url="") - model_name = "gemini-2.0-flash" + model_name = "gemini-3.8-flash" prompt_tokens = 128.0 output_tokens = 228.0 ## GET MODEL FROM LITELLM.MODEL_INFO @@ -543,7 +543,7 @@ def test_vertex_ai_completion_cost(): prompt_tokens = 100 - model_info = litellm.get_model_info(model="gemini-2.0-flash") + model_info = litellm.get_model_info(model="gemini-3.8-flash") print("\nExpected model info:\n{}\n\n".format(model_info)) @@ -551,7 +551,7 @@ def test_vertex_ai_completion_cost(): ## CALCULATED COST calculated_input_cost, calculated_output_cost = cost_per_token( - model="gemini-2.0-flash", + model="gemini-3.8-flash", custom_llm_provider="vertex_ai", prompt_tokens=prompt_tokens, completion_tokens=0, @@ -676,7 +676,7 @@ async def test_completion_cost_hidden_params(sync_mode): def test_vertex_ai_gemini_predict_cost(): - model = "gemini-2.0-flash" + model = "gemini-3.8-flash" messages = [{"role": "user", "content": "Hey, hows it going???"}] predictive_cost = completion_cost(model=model, messages=messages) @@ -757,24 +757,24 @@ def test_completion_cost_tts(model): def test_completion_cost_anthropic(): """ - model_name: claude-3-haiku-20240307 + model_name: claude-haiku-4-5 litellm_params: - model: anthropic/claude-3-haiku-20240307 + model: anthropic/claude-haiku-4-5 max_tokens: 4096 """ router = litellm.Router( model_list=[ { - "model_name": "claude-3-haiku-20240307", + "model_name": "claude-haiku-4-5", "litellm_params": { - "model": "anthropic/claude-3-haiku-20240307", + "model": "anthropic/claude-haiku-4-5", "max_tokens": 4096, }, } ] ) data = { - "model": "claude-3-haiku-20240307", + "model": "claude-haiku-4-5", "prompt_tokens": 21, "completion_tokens": 20, "response_time_ms": 871.7040000000001, @@ -2068,14 +2068,14 @@ def test_completion_cost_params(): """ litellm.set_verbose = True resp1_prompt_cost, resp1_completion_cost = cost_per_token( - model="gemini-2.0-flash", + model="gemini-3.8-flash", prompt_tokens=1000, completion_tokens=1000, custom_llm_provider="vertex_ai_beta", ) resp2_prompt_cost, resp2_completion_cost = cost_per_token( - model="gemini-2.0-flash", prompt_tokens=1000, completion_tokens=1000 + model="gemini-3.8-flash", prompt_tokens=1000, completion_tokens=1000 ) assert resp2_prompt_cost > 0 @@ -2084,7 +2084,7 @@ def test_completion_cost_params(): assert resp1_completion_cost == resp2_completion_cost resp3_prompt_cost, resp3_completion_cost = cost_per_token( - model="vertex_ai/gemini-2.0-flash", prompt_tokens=1000, completion_tokens=1000 + model="vertex_ai/gemini-3.8-flash", prompt_tokens=1000, completion_tokens=1000 ) assert resp3_prompt_cost > 0 @@ -2102,14 +2102,14 @@ def test_completion_cost_params_2(): prompt_tokens = 1000 completion_tokens = 1000 resp1_prompt_cost, resp1_completion_cost = cost_per_token( - model="gemini-2.0-flash", + model="gemini-3.8-flash", prompt_tokens=prompt_tokens, completion_tokens=completion_tokens, ) print(resp1_prompt_cost, resp1_completion_cost) - model_info = litellm.get_model_info("gemini-2.0-flash") + model_info = litellm.get_model_info("gemini-3.8-flash") input_cost_per_token = model_info["input_cost_per_token"] output_cost_per_token = model_info["output_cost_per_token"] @@ -2148,7 +2148,7 @@ def test_completion_cost_params_gemini_3(): ) ], created=1728529259, - model="gemini-2.0-flash", + model="gemini-3.8-flash", object="chat.completion", system_fingerprint=None, usage=usage, @@ -2172,7 +2172,7 @@ def test_completion_cost_params_gemini_3(): pc, cc = cost_per_character( **{ - "model": "gemini-2.0-flash", + "model": "gemini-3.8-flash", "custom_llm_provider": "vertex_ai", "prompt_characters": None, "completion_characters": 3, @@ -2180,9 +2180,9 @@ def test_completion_cost_params_gemini_3(): } ) - model_info = litellm.get_model_info("gemini-2.0-flash") + model_info = litellm.get_model_info("gemini-3.8-flash") - # gemini-2.0-flash has no per-character pricing, so cost_per_character + # gemini-3.8-flash has no per-character pricing, so cost_per_character # falls back to per-token pricing using usage.prompt_tokens / usage.completion_tokens assert round(pc, 10) == round(3771 * model_info["input_cost_per_token"], 10) assert round(cc, 10) == round( @@ -2239,16 +2239,16 @@ async def test_test_completion_cost_gpt4o_audio_output_from_model(stream): ) ], created=1729282652, - model="gpt-4o-audio-preview", + model="gpt-audio-1.5", object="chat.completion", system_fingerprint="fp_4eafc16e9d", usage=usage_object, service_tier=None, ) - cost = completion_cost(completion, model="gpt-4o-audio-preview") + cost = completion_cost(completion, model="gpt-audio-1.5") - model_info = litellm.get_model_info("gpt-4o-audio-preview") + model_info = litellm.get_model_info("gpt-audio-1.5") print(f"model_info: {model_info}") ## input cost @@ -2517,7 +2517,7 @@ def test_cost_calculator_with_base_model(): resp = litellm.completion( model="bedrock/random-model", messages=[{"role": "user", "content": "Hello, how are you?"}], - base_model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0", + base_model="bedrock/anthropic.claude-sonnet-5", mock_response="Hello, how are you?", ) assert resp.model == "random-model" @@ -2551,10 +2551,10 @@ def test_cost_calculator_with_base_model_with_router(base_model_arg): if base_model_arg == "litellm_param": model_item["litellm_params"][ "base_model" - ] = "bedrock/anthropic.claude-3-sonnet-20240229-v1:0" + ] = "bedrock/anthropic.claude-sonnet-5" elif base_model_arg == "model_info": model_item["model_info"] = { - "base_model": "bedrock/anthropic.claude-3-sonnet-20240229-v1:0", + "base_model": "bedrock/anthropic.claude-sonnet-5", } router = Router(model_list=[model_item]) diff --git a/tests/local_testing/test_exceptions.py b/tests/local_testing/test_exceptions.py index e6392cda406..813146f8ace 100644 --- a/tests/local_testing/test_exceptions.py +++ b/tests/local_testing/test_exceptions.py @@ -1148,7 +1148,7 @@ def test_openai_gateway_timeout_error(): @pytest.mark.parametrize( "provider, model, call_type", [ - ("anthropic", "claude-3-haiku-20240307", "chat_completion"), + ("anthropic", "claude-haiku-4-5-20251001", "chat_completion"), ], ) @pytest.mark.asyncio diff --git a/tests/local_testing/test_function_call_parsing.py b/tests/local_testing/test_function_call_parsing.py index c98f170a98f..ebb13e0018d 100644 --- a/tests/local_testing/test_function_call_parsing.py +++ b/tests/local_testing/test_function_call_parsing.py @@ -136,7 +136,7 @@ def trade(model_name: str) -> List[Trade]: # type: ignore @pytest.mark.parametrize( - "model", ["claude-haiku-4-5-20251001", "anthropic.claude-3-haiku-20240307-v1:0"] + "model", ["claude-haiku-4-5-20251001", "us.anthropic.claude-haiku-4-5-20251001-v1:0"] ) @pytest.mark.flaky(retries=6, delay=10) def test_function_call_parsing(model): diff --git a/tests/local_testing/test_get_llm_provider.py b/tests/local_testing/test_get_llm_provider.py index ebad0fbafc5..4ac7cecb97a 100644 --- a/tests/local_testing/test_get_llm_provider.py +++ b/tests/local_testing/test_get_llm_provider.py @@ -67,7 +67,17 @@ def test_get_llm_provider_deepseek_custom_api_base(): os.environ.pop("DEEPSEEK_API_BASE") -def test_get_llm_provider_vertex_ai_image_models(): +def test_get_llm_provider_vertex_ai_image_models(monkeypatch): + monkeypatch.setattr(litellm, "vertex_ai_image_models", set()) + monkeypatch.setattr(litellm, "models_by_provider", dict(litellm.models_by_provider)) + litellm.add_known_models( + model_cost_map={ + "vertex_ai/imagegeneration@006": { + "litellm_provider": "vertex_ai-image-models", + "mode": "image_generation", + } + } + ) model, custom_llm_provider, dynamic_api_key, api_base = litellm.get_llm_provider( model="imagegeneration@006", custom_llm_provider=None ) @@ -101,17 +111,17 @@ def test_get_llm_provider_ai21_chat_test2(): def test_get_llm_provider_cohere_chat_test2(): """ - if user prefix with cohere/ but calls command-r-plus then it should be cohere_chat provider + if user prefix with cohere/ but calls command-r-plus-08-2024 then it should be cohere_chat provider """ model, custom_llm_provider, dynamic_api_key, api_base = litellm.get_llm_provider( - model="cohere/command-r-plus", + model="cohere/command-r-plus-08-2024", ) print("model=", model) print("custom_llm_provider=", custom_llm_provider) print("api_base=", api_base) assert custom_llm_provider == "cohere_chat" - assert model == "command-r-plus" + assert model == "command-r-plus-08-2024" def test_get_llm_provider_azure_o1(): diff --git a/tests/local_testing/test_get_model_info.py b/tests/local_testing/test_get_model_info.py index 37f4ece611d..1e46a1bf853 100644 --- a/tests/local_testing/test_get_model_info.py +++ b/tests/local_testing/test_get_model_info.py @@ -16,7 +16,7 @@ def test_get_model_info_simple_model_name(): """ tests if model name given, and model exists in model info - the object is returned """ - model = "claude-3-opus-20240229" + model = "claude-opus-5-5" litellm.get_model_info(model) @@ -24,7 +24,7 @@ def test_get_model_info_custom_llm_with_model_name(): """ Tests if {custom_llm_provider}/{model_name} name given, and model exists in model info, the object is returned """ - model = "anthropic/claude-3-opus-20240229" + model = "anthropic/claude-opus-5-5" litellm.get_model_info(model) diff --git a/tests/local_testing/test_lowest_cost_routing.py b/tests/local_testing/test_lowest_cost_routing.py index 5bf3a3ee98b..631271ca710 100644 --- a/tests/local_testing/test_lowest_cost_routing.py +++ b/tests/local_testing/test_lowest_cost_routing.py @@ -28,7 +28,7 @@ async def test_get_available_deployments(): }, { "model_name": "gpt-3.5-turbo", - "litellm_params": {"model": "groq/llama-3.1-8b-instant"}, + "litellm_params": {"model": "groq/openai/gpt-oss-20b"}, "model_info": {"id": "groq-llama"}, }, ] diff --git a/tests/local_testing/test_openai_moderations_hook.py b/tests/local_testing/test_openai_moderations_hook.py index 530ab714eae..7ce4bc2e4bf 100644 --- a/tests/local_testing/test_openai_moderations_hook.py +++ b/tests/local_testing/test_openai_moderations_hook.py @@ -31,7 +31,7 @@ async def test_openai_moderation_error_raising(monkeypatch): from unittest.mock import AsyncMock, MagicMock from litellm.types.llms.openai import OpenAIModerationResponse - litellm.openai_moderations_model_name = "text-moderation-latest" + litellm.openai_moderations_model_name = "omni-moderation-latest" openai_mod = _ENTERPRISE_OpenAI_Moderation() _api_key = "sk-12345" _api_key = hash_token("sk-12345") @@ -41,9 +41,9 @@ async def test_openai_moderation_error_raising(monkeypatch): llm_router = litellm.Router( model_list=[ { - "model_name": "text-moderation-latest", + "model_name": "omni-moderation-latest", "litellm_params": { - "model": "text-moderation-latest", + "model": "omni-moderation-latest", "api_key": os.environ.get("OPENAI_API_KEY", "fake-key"), }, } diff --git a/tests/local_testing/test_router_utils.py b/tests/local_testing/test_router_utils.py index 1b3e361bb1f..635bda55144 100644 --- a/tests/local_testing/test_router_utils.py +++ b/tests/local_testing/test_router_utils.py @@ -188,7 +188,7 @@ def test_router_get_model_info_wildcard_routes(): ] ) model_info = router.get_router_model_info( - deployment=None, received_model_name="gemini/gemini-1.5-flash", id="1" + deployment=None, received_model_name="gemini/gemini-2.5-flash", id="1" ) print(model_info) assert model_info is not None @@ -212,7 +212,7 @@ async def test_router_get_model_group_usage_wildcard_routes(): ) resp = await router.acompletion( - model="gemini/gemini-1.5-flash", + model="gemini/gemini-2.5-flash", messages=[{"role": "user", "content": "Hello, how are you?"}], mock_response="Hello, I'm good.", ) @@ -220,7 +220,7 @@ async def test_router_get_model_group_usage_wildcard_routes(): await asyncio.sleep(2) - tpm, rpm = await router.get_model_group_usage(model_group="gemini/gemini-1.5-flash") + tpm, rpm = await router.get_model_group_usage(model_group="gemini/gemini-2.5-flash") assert tpm is not None, "tpm is None" assert rpm is not None, "rpm is None" @@ -242,7 +242,7 @@ async def test_call_router_callbacks_on_success(): router.cache, "async_increment_cache_pipeline", new=AsyncMock() ) as mock_callback: await router.acompletion( - model="gemini/gemini-1.5-flash", + model="gemini/gemini-2.5-flash", messages=[{"role": "user", "content": "Hello, how are you?"}], mock_response="Hello, I'm good.", ) @@ -255,12 +255,12 @@ async def test_call_router_callbacks_on_success(): for increment in increment_list: if "tpm" in increment["key"]: assert increment["key"].startswith( - "global_router:1:gemini/gemini-1.5-flash:tpm" + "global_router:1:gemini/gemini-2.5-flash:tpm" ) assert increment["increment_value"] == 30 elif "rpm" in increment["key"]: assert increment["key"].startswith( - "global_router:1:gemini/gemini-1.5-flash:rpm" + "global_router:1:gemini/gemini-2.5-flash:rpm" ) assert increment["increment_value"] == 1 @@ -283,7 +283,7 @@ async def test_call_router_callbacks_on_failure(): ) as mock_callback: with pytest.raises(litellm.RateLimitError): await router.acompletion( - model="gemini/gemini-1.5-flash", + model="gemini/gemini-2.5-flash", messages=[{"role": "user", "content": "Hello, how are you?"}], mock_response="litellm.RateLimitError", num_retries=0, @@ -295,7 +295,7 @@ async def test_call_router_callbacks_on_failure(): assert ( mock_callback.call_args_list[0] .kwargs["key"] - .startswith("global_router:1:gemini/gemini-1.5-flash:rpm") + .startswith("global_router:1:gemini/gemini-2.5-flash:rpm") ) @@ -317,7 +317,7 @@ async def test_router_model_group_headers(): for _ in range(2): resp = await router.acompletion( - model="gemini/gemini-1.5-flash", + model="gemini/gemini-2.5-flash", messages=[{"role": "user", "content": "Hello, how are you?"}], mock_response="Hello, I'm good.", ) @@ -325,7 +325,7 @@ async def test_router_model_group_headers(): assert ( resp._hidden_params["additional_headers"]["x-litellm-model-group"] - == "gemini/gemini-1.5-flash" + == "gemini/gemini-2.5-flash" ) assert "x-ratelimit-remaining-requests" in resp._hidden_params["additional_headers"] @@ -349,7 +349,7 @@ async def test_get_remaining_model_group_usage(): ) for _ in range(2): resp = await router.acompletion( - model="gemini/gemini-1.5-flash", + model="gemini/gemini-2.5-flash", messages=[{"role": "user", "content": "Hello, how are you?"}], mock_response="Hello, I'm good.", ) @@ -363,7 +363,7 @@ async def test_get_remaining_model_group_usage(): await asyncio.sleep(1) remaining_usage = await router.get_remaining_model_group_usage( - model_group="gemini/gemini-1.5-flash" + model_group="gemini/gemini-2.5-flash" ) assert remaining_usage is not None assert "x-ratelimit-remaining-requests" in remaining_usage diff --git a/tests/local_testing/test_spend_calculate_endpoint.py b/tests/local_testing/test_spend_calculate_endpoint.py index 3bedab794e2..054dc398039 100644 --- a/tests/local_testing/test_spend_calculate_endpoint.py +++ b/tests/local_testing/test_spend_calculate_endpoint.py @@ -38,7 +38,7 @@ async def test_spend_calc_model_on_router_messages(): { "model_name": "special-llama-model", "litellm_params": { - "model": "groq/llama-3.1-8b-instant", + "model": "groq/openai/gpt-oss-20b", }, } ] @@ -81,7 +81,7 @@ async def test_spend_calc_using_response(): } ], "created": "1677652288", - "model": "groq/llama-3.1-8b-instant", + "model": "groq/openai/gpt-oss-20b", "object": "chat.completion", "system_fingerprint": "fp_873a560973", "usage": { diff --git a/tests/logging_callback_tests/langfuse_expected_request_body/completion_with_vertex_call.json b/tests/logging_callback_tests/langfuse_expected_request_body/completion_with_vertex_call.json index b6c11f96953..5998c52659c 100644 --- a/tests/logging_callback_tests/langfuse_expected_request_body/completion_with_vertex_call.json +++ b/tests/logging_callback_tests/langfuse_expected_request_body/completion_with_vertex_call.json @@ -31,14 +31,14 @@ "model_id": null, "cache_key": null, "api_base": null, - "response_cost": 7.5e-06, + "response_cost": 3.5e-05, "additional_headers": {}, "litellm_overhead_time_ms": null, "batch_models": null, - "litellm_model_name": "vertex_ai/gemini-2.0-flash-001", + "litellm_model_name": "vertex_ai/gemini-3-flash-preview", "usage_object": null }, - "litellm_response_cost": 7.5e-06, + "litellm_response_cost": 3.5e-05, "cache_hit": false, "requester_metadata": {} }, @@ -54,13 +54,13 @@ "id": "time-14-15-40-349639_chatcmpl-59a988d0-7ef1-4dc4-bc18-d2e78961817f", "endTime": "2025-05-26T14:15:40.607266-07:00", "completionStartTime": "2025-05-26T14:15:40.607266-07:00", - "model": "gemini-2.0-flash-001", + "model": "gemini-3-flash-preview", "modelParameters": {}, "usage": { "input": 10, "output": 10, "unit": "TOKENS", - "totalCost": 7.5e-06 + "totalCost": 3.5e-05 }, "usageDetails": { "input": 10, diff --git a/tests/logging_callback_tests/test_alerting.py b/tests/logging_callback_tests/test_alerting.py index 3074e973a8e..0a3e1a0e982 100644 --- a/tests/logging_callback_tests/test_alerting.py +++ b/tests/logging_callback_tests/test_alerting.py @@ -582,7 +582,7 @@ async def test_webhook_alerting(alerting_type): None, None, ), - ("gemini-2.0-flash", None, "vertex_ai", "hardy-device-38811", "us-central1"), + ("gemini-3.8-flash", None, "vertex_ai", "hardy-device-38811", "us-central1"), ], ) @pytest.mark.parametrize("error_code", [500, 408, 400]) @@ -688,7 +688,7 @@ async def test_outage_alerting_called( None, None, ), - ("gemini-2.0-flash", None, "vertex_ai", "hardy-device-38811", "us-central1"), + ("gemini-3.8-flash", None, "vertex_ai", "hardy-device-38811", "us-central1"), ], ) @pytest.mark.parametrize("error_code", [500, 408, 400]) @@ -775,7 +775,7 @@ async def test_region_outage_alerting_called( await slack_alerting.region_outage_alerts( exception=error_to_raise, deployment_id=deployment_id # type: ignore ) - if model == "gemini-2.0-flash" and (error_code == 500 or error_code == 408): + if model == "gemini-3.8-flash" and (error_code == 500 or error_code == 408): mock_send_alert.assert_called_once() else: mock_send_alert.assert_not_called() diff --git a/tests/logging_callback_tests/test_langfuse_e2e_test.py b/tests/logging_callback_tests/test_langfuse_e2e_test.py index 5682d3720d8..76ebd2b9a28 100644 --- a/tests/logging_callback_tests/test_langfuse_e2e_test.py +++ b/tests/logging_callback_tests/test_langfuse_e2e_test.py @@ -481,12 +481,12 @@ class TestLangfuseLogging: completion_tokens=10, total_tokens=20, ), - model="vertex/gemini-2.0-flash-001", + model="vertex/gemini-3-flash-preview", object="chat.completion", created=1723081200, ).model_dump() await litellm.acompletion( - model="vertex_ai/gemini-2.0-flash-001", + model="vertex_ai/gemini-3-flash-preview", messages=[{"role": "user", "content": "Hello!"}], mock_response=mock_response, metadata={"trace_id": setup["trace_id"]}, diff --git a/tests/unit/repositories/test_repositories.py b/tests/unit/repositories/test_repositories.py index 87cf2fc4268..e185d95ffb8 100644 --- a/tests/unit/repositories/test_repositories.py +++ b/tests/unit/repositories/test_repositories.py @@ -2120,6 +2120,7 @@ class TestPrismaTableRepository: "litellm_prompttable", "litellm_searchtoolstable", "litellm_ssoconfig", + "litellm_uisettings", } ) From 7688f56256484f866687e147d0a994fb7649dd6d Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 17:28:48 -0700 Subject: [PATCH 062/101] fix(pricing): drop the duplicate cache_read_input_token_cost_batches key from 23 entries (#42623) Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- ...odel_prices_and_context_window_backup.json | 69 +++++++------------ model_prices_and_context_window.json | 69 +++++++------------ 2 files changed, 46 insertions(+), 92 deletions(-) diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 224129fbd25..ad66cb76f8b 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -25314,8 +25314,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, - "web_search_billing_unit": "per_query", - "cache_read_input_token_cost_batches": 1e-07 + "web_search_billing_unit": "per_query" }, "gemini-3-pro-image-preview": { "input_cost_per_image": 0.0011, @@ -25401,8 +25400,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, - "web_search_billing_unit": "per_query", - "cache_read_input_token_cost_batches": 2.5e-08 + "web_search_billing_unit": "per_query" }, "gemini-3.1-flash-image-preview": { "input_cost_per_image": 0.00056, @@ -25482,8 +25480,7 @@ "supports_response_schema": false, "supports_system_messages": true, "supports_video_input": true, - "supports_vision": true, - "cache_read_input_token_cost_batches": 1.25e-08 + "supports_vision": true }, "gemini-3.1-flash-lite-preview": { "cache_read_input_token_cost": 2.5e-08, @@ -25593,8 +25590,7 @@ }, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014, - "input_cost_per_audio_token_batches": 2.5e-07, - "cache_read_input_token_cost_batches": 1.25e-08 + "input_cost_per_audio_token_batches": 2.5e-07 }, "gemini-3.5-flash-lite": { "deprecation_date": "2027-07-21", @@ -25652,8 +25648,7 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014, - "cache_read_input_token_cost_batches": 1.5e-08 + "google_maps_grounding_cost_per_query": 0.014 }, "deep-research-pro-preview-12-2025": { "cache_read_input_token_cost": 2e-07, @@ -25689,8 +25684,7 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_vision": true, - "supports_web_search": true, - "cache_read_input_token_cost_batches": 1e-07 + "supports_web_search": true }, "gemini-2.5-flash-lite": { "cache_read_input_audio_token_cost": 3e-08, @@ -26321,8 +26315,7 @@ "output_cost_per_token_batches": 4.5e-06, "input_cost_per_token_flex": 7.5e-07, "output_cost_per_token_flex": 4.5e-06, - "cache_read_input_token_cost_flex": 7.5e-08, - "cache_read_input_token_cost_batches": 7.5e-08 + "cache_read_input_token_cost_flex": 7.5e-08 }, "vertex_ai/gemini-3.6-flash": { "prompt_cache_min_tokens": 4096, @@ -26380,8 +26373,7 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014, - "cache_read_input_token_cost_batches": 3.75e-08 + "google_maps_grounding_cost_per_query": 0.014 }, "vertex_ai/gemini-3.7-flash": { "prompt_cache_min_tokens": 4096, @@ -26440,8 +26432,7 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014, - "cache_read_input_token_cost_batches": 3.75e-08 + "google_maps_grounding_cost_per_query": 0.014 }, "vertex_ai/gemini-3.8-flash": { "prompt_cache_min_tokens": 4096, @@ -26500,8 +26491,7 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014, - "cache_read_input_token_cost_batches": 3.75e-08 + "google_maps_grounding_cost_per_query": 0.014 }, "vertex_ai/gemini-3.1-pro-preview": { "prompt_cache_min_tokens": 4096, @@ -28250,8 +28240,7 @@ "output_cost_per_token_batches": 4.5e-06, "input_cost_per_token_flex": 7.5e-07, "output_cost_per_token_flex": 4.5e-06, - "cache_read_input_token_cost_flex": 7.5e-08, - "cache_read_input_token_cost_batches": 7.5e-08 + "cache_read_input_token_cost_flex": 7.5e-08 }, "gemini-3.6-flash": { "prompt_cache_min_tokens": 4096, @@ -28309,8 +28298,7 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014, - "cache_read_input_token_cost_batches": 3.75e-08 + "google_maps_grounding_cost_per_query": 0.014 }, "gemini-3.7-flash": { "prompt_cache_min_tokens": 4096, @@ -28369,8 +28357,7 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014, - "cache_read_input_token_cost_batches": 3.75e-08 + "google_maps_grounding_cost_per_query": 0.014 }, "gemini-3.8-flash": { "prompt_cache_min_tokens": 4096, @@ -28429,8 +28416,7 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014, - "cache_read_input_token_cost_batches": 3.75e-08 + "google_maps_grounding_cost_per_query": 0.014 }, "gemini/gemini-2.5-pro-preview-tts": { "cache_read_input_token_cost": 1.25e-07, @@ -33110,8 +33096,7 @@ "supports_web_search": true, "supports_none_reasoning_effort": false, "supports_xhigh_reasoning_effort": false, - "supports_minimal_reasoning_effort": true, - "cache_read_input_token_cost_batches": 6.25e-08 + "supports_minimal_reasoning_effort": true }, "gpt-5-chat": { "cache_read_input_token_cost": 1.25e-07, @@ -33292,8 +33277,7 @@ "supports_web_search": true, "supports_none_reasoning_effort": false, "supports_xhigh_reasoning_effort": false, - "supports_minimal_reasoning_effort": true, - "cache_read_input_token_cost_batches": 1.25e-08 + "supports_minimal_reasoning_effort": true }, "gpt-5-nano": { "cache_read_input_token_cost": 5e-09, @@ -33392,8 +33376,7 @@ "supports_web_search": true, "supports_none_reasoning_effort": false, "supports_xhigh_reasoning_effort": false, - "supports_minimal_reasoning_effort": true, - "cache_read_input_token_cost_batches": 2.5e-09 + "supports_minimal_reasoning_effort": true }, "gpt-image-1": { "cache_read_input_token_cost": 1.25e-06, @@ -47531,8 +47514,7 @@ "output_cost_per_token_flex": 6e-06, "output_cost_per_token_priority": 2.16e-05, "supports_reasoning": false, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", - "cache_read_input_token_cost_batches": 1e-07 + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" }, "vertex_ai/gemini-3-pro-image-preview": { "input_cost_per_image": 0.0011, @@ -47570,8 +47552,7 @@ "output_cost_per_token_batches": 1.5e-06, "output_cost_per_token_flex": 1.5e-06, "supports_reasoning": false, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", - "cache_read_input_token_cost_batches": 2.5e-08 + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" }, "vertex_ai/gemini-3.1-flash-image-preview": { "input_cost_per_image": 0.00056, @@ -47627,8 +47608,7 @@ "supports_response_schema": false, "supports_system_messages": true, "supports_video_input": true, - "supports_vision": true, - "cache_read_input_token_cost_batches": 1.25e-08 + "supports_vision": true }, "vertex_ai/gemini-3.1-flash-lite-preview": { "cache_read_input_token_cost": 2.5e-08, @@ -47739,8 +47719,7 @@ }, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014, - "input_cost_per_audio_token_batches": 2.5e-07, - "cache_read_input_token_cost_batches": 1.25e-08 + "input_cost_per_audio_token_batches": 2.5e-07 }, "vertex_ai/gemini-3.5-flash-lite": { "deprecation_date": "2027-07-21", @@ -47799,8 +47778,7 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014, - "cache_read_input_token_cost_batches": 1.5e-08 + "google_maps_grounding_cost_per_query": 0.014 }, "vertex_ai/deep-research-pro-preview-12-2025": { "cache_read_input_token_cost": 2e-07, @@ -47817,8 +47795,7 @@ "output_cost_per_image_token": 0.00012, "output_cost_per_token": 1.2e-05, "output_cost_per_token_batches": 6e-06, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", - "cache_read_input_token_cost_batches": 1e-07 + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" }, "vertex_ai/jamba-1.5": { "input_cost_per_token": 2e-07, diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 224129fbd25..ad66cb76f8b 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -25314,8 +25314,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, - "web_search_billing_unit": "per_query", - "cache_read_input_token_cost_batches": 1e-07 + "web_search_billing_unit": "per_query" }, "gemini-3-pro-image-preview": { "input_cost_per_image": 0.0011, @@ -25401,8 +25400,7 @@ "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, - "web_search_billing_unit": "per_query", - "cache_read_input_token_cost_batches": 2.5e-08 + "web_search_billing_unit": "per_query" }, "gemini-3.1-flash-image-preview": { "input_cost_per_image": 0.00056, @@ -25482,8 +25480,7 @@ "supports_response_schema": false, "supports_system_messages": true, "supports_video_input": true, - "supports_vision": true, - "cache_read_input_token_cost_batches": 1.25e-08 + "supports_vision": true }, "gemini-3.1-flash-lite-preview": { "cache_read_input_token_cost": 2.5e-08, @@ -25593,8 +25590,7 @@ }, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014, - "input_cost_per_audio_token_batches": 2.5e-07, - "cache_read_input_token_cost_batches": 1.25e-08 + "input_cost_per_audio_token_batches": 2.5e-07 }, "gemini-3.5-flash-lite": { "deprecation_date": "2027-07-21", @@ -25652,8 +25648,7 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014, - "cache_read_input_token_cost_batches": 1.5e-08 + "google_maps_grounding_cost_per_query": 0.014 }, "deep-research-pro-preview-12-2025": { "cache_read_input_token_cost": 2e-07, @@ -25689,8 +25684,7 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_vision": true, - "supports_web_search": true, - "cache_read_input_token_cost_batches": 1e-07 + "supports_web_search": true }, "gemini-2.5-flash-lite": { "cache_read_input_audio_token_cost": 3e-08, @@ -26321,8 +26315,7 @@ "output_cost_per_token_batches": 4.5e-06, "input_cost_per_token_flex": 7.5e-07, "output_cost_per_token_flex": 4.5e-06, - "cache_read_input_token_cost_flex": 7.5e-08, - "cache_read_input_token_cost_batches": 7.5e-08 + "cache_read_input_token_cost_flex": 7.5e-08 }, "vertex_ai/gemini-3.6-flash": { "prompt_cache_min_tokens": 4096, @@ -26380,8 +26373,7 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014, - "cache_read_input_token_cost_batches": 3.75e-08 + "google_maps_grounding_cost_per_query": 0.014 }, "vertex_ai/gemini-3.7-flash": { "prompt_cache_min_tokens": 4096, @@ -26440,8 +26432,7 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014, - "cache_read_input_token_cost_batches": 3.75e-08 + "google_maps_grounding_cost_per_query": 0.014 }, "vertex_ai/gemini-3.8-flash": { "prompt_cache_min_tokens": 4096, @@ -26500,8 +26491,7 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014, - "cache_read_input_token_cost_batches": 3.75e-08 + "google_maps_grounding_cost_per_query": 0.014 }, "vertex_ai/gemini-3.1-pro-preview": { "prompt_cache_min_tokens": 4096, @@ -28250,8 +28240,7 @@ "output_cost_per_token_batches": 4.5e-06, "input_cost_per_token_flex": 7.5e-07, "output_cost_per_token_flex": 4.5e-06, - "cache_read_input_token_cost_flex": 7.5e-08, - "cache_read_input_token_cost_batches": 7.5e-08 + "cache_read_input_token_cost_flex": 7.5e-08 }, "gemini-3.6-flash": { "prompt_cache_min_tokens": 4096, @@ -28309,8 +28298,7 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014, - "cache_read_input_token_cost_batches": 3.75e-08 + "google_maps_grounding_cost_per_query": 0.014 }, "gemini-3.7-flash": { "prompt_cache_min_tokens": 4096, @@ -28369,8 +28357,7 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014, - "cache_read_input_token_cost_batches": 3.75e-08 + "google_maps_grounding_cost_per_query": 0.014 }, "gemini-3.8-flash": { "prompt_cache_min_tokens": 4096, @@ -28429,8 +28416,7 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014, - "cache_read_input_token_cost_batches": 3.75e-08 + "google_maps_grounding_cost_per_query": 0.014 }, "gemini/gemini-2.5-pro-preview-tts": { "cache_read_input_token_cost": 1.25e-07, @@ -33110,8 +33096,7 @@ "supports_web_search": true, "supports_none_reasoning_effort": false, "supports_xhigh_reasoning_effort": false, - "supports_minimal_reasoning_effort": true, - "cache_read_input_token_cost_batches": 6.25e-08 + "supports_minimal_reasoning_effort": true }, "gpt-5-chat": { "cache_read_input_token_cost": 1.25e-07, @@ -33292,8 +33277,7 @@ "supports_web_search": true, "supports_none_reasoning_effort": false, "supports_xhigh_reasoning_effort": false, - "supports_minimal_reasoning_effort": true, - "cache_read_input_token_cost_batches": 1.25e-08 + "supports_minimal_reasoning_effort": true }, "gpt-5-nano": { "cache_read_input_token_cost": 5e-09, @@ -33392,8 +33376,7 @@ "supports_web_search": true, "supports_none_reasoning_effort": false, "supports_xhigh_reasoning_effort": false, - "supports_minimal_reasoning_effort": true, - "cache_read_input_token_cost_batches": 2.5e-09 + "supports_minimal_reasoning_effort": true }, "gpt-image-1": { "cache_read_input_token_cost": 1.25e-06, @@ -47531,8 +47514,7 @@ "output_cost_per_token_flex": 6e-06, "output_cost_per_token_priority": 2.16e-05, "supports_reasoning": false, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", - "cache_read_input_token_cost_batches": 1e-07 + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" }, "vertex_ai/gemini-3-pro-image-preview": { "input_cost_per_image": 0.0011, @@ -47570,8 +47552,7 @@ "output_cost_per_token_batches": 1.5e-06, "output_cost_per_token_flex": 1.5e-06, "supports_reasoning": false, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", - "cache_read_input_token_cost_batches": 2.5e-08 + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" }, "vertex_ai/gemini-3.1-flash-image-preview": { "input_cost_per_image": 0.00056, @@ -47627,8 +47608,7 @@ "supports_response_schema": false, "supports_system_messages": true, "supports_video_input": true, - "supports_vision": true, - "cache_read_input_token_cost_batches": 1.25e-08 + "supports_vision": true }, "vertex_ai/gemini-3.1-flash-lite-preview": { "cache_read_input_token_cost": 2.5e-08, @@ -47739,8 +47719,7 @@ }, "web_search_billing_unit": "per_query", "google_maps_grounding_cost_per_query": 0.014, - "input_cost_per_audio_token_batches": 2.5e-07, - "cache_read_input_token_cost_batches": 1.25e-08 + "input_cost_per_audio_token_batches": 2.5e-07 }, "vertex_ai/gemini-3.5-flash-lite": { "deprecation_date": "2027-07-21", @@ -47799,8 +47778,7 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014, - "cache_read_input_token_cost_batches": 1.5e-08 + "google_maps_grounding_cost_per_query": 0.014 }, "vertex_ai/deep-research-pro-preview-12-2025": { "cache_read_input_token_cost": 2e-07, @@ -47817,8 +47795,7 @@ "output_cost_per_image_token": 0.00012, "output_cost_per_token": 1.2e-05, "output_cost_per_token_batches": 6e-06, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", - "cache_read_input_token_cost_batches": 1e-07 + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" }, "vertex_ai/jamba-1.5": { "input_cost_per_token": 2e-07, From b4ccb5b7474270bd69f1b491a3febf0bd2c44210 Mon Sep 17 00:00:00 2001 From: mubashir1osmani Date: Tue, 22 Sep 2026 20:33:44 -0400 Subject: [PATCH 063/101] fix(s3): replace colons in generated log filenames (#40452) * fix(s3): replace colons in generated log filenames Bedrock and Vertex AI batch file uploads use s3:// and gs:// URIs as response ids. The shared filename sanitizer replaced slashes but kept the scheme colon, producing log object keys that Hadoop-style consumers reject as a relative path in an absolute URI. Fixes #40234 * test(s3): drop docstrings flagged by review --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- litellm/integrations/s3.py | 2 +- tests/test_litellm/integrations/test_s3_v2.py | 28 ++++++++++++++++--- 2 files changed, 25 insertions(+), 5 deletions(-) diff --git a/litellm/integrations/s3.py b/litellm/integrations/s3.py index 796784fb993..54ec876fd0d 100644 --- a/litellm/integrations/s3.py +++ b/litellm/integrations/s3.py @@ -277,7 +277,7 @@ def get_s3_object_key( start_time: datetime, s3_file_name: str, ) -> str: - sanitized_s3_file_name: Final = s3_file_name.replace("/", "_") + sanitized_s3_file_name: Final = s3_file_name.replace("/", "_").replace(":", "_") configured_prefix: Final = (s3_path.rstrip("/") + "/" if s3_path else "") + prefix date_segment: Final = start_time.strftime("%Y-%m-%d") + "/" # we need the s3 key to include the time, so we log cache hits too diff --git a/tests/test_litellm/integrations/test_s3_v2.py b/tests/test_litellm/integrations/test_s3_v2.py index 52fbbe40b0e..a9d13038180 100644 --- a/tests/test_litellm/integrations/test_s3_v2.py +++ b/tests/test_litellm/integrations/test_s3_v2.py @@ -1273,9 +1273,7 @@ async def test_combined_prefix_reflects_in_s3_object_key(): assert "myteam/apikey/" in key, f"Expected both prefixes in key: {key}" -def test_s3_object_key_sanitizes_slashes_in_file_name(): - """Response ids containing slashes (e.g. bedrock batch job ARNs) must not - create nested S3 folders; only path/prefix/date slashes are separators.""" +def test_s3_object_key_sanitizes_slashes_and_colons_in_file_name(): from litellm.integrations.s3 import get_s3_object_key start_time = datetime(2026, 2, 11, 0, 35, 18, 391582) @@ -1290,10 +1288,32 @@ def test_s3_object_key_sanitizes_slashes_in_file_name(): assert key == ( "LiteLLMAPPLogs/myteam/2026-02-11/" - "time-00-35-18-391582_arn:aws:bedrock:us-east-1:123456789012:model-invocation-job_gl18r6skk9yy.json" + "time-00-35-18-391582_arn_aws_bedrock_us-east-1_123456789012_model-invocation-job_gl18r6skk9yy.json" ) +@pytest.mark.parametrize( + "response_id", + [ + "s3://example-batch-bucket/litellm-bedrock-files/input.jsonl", + "gs://example-batch-bucket/litellm-vertex-files/input.jsonl", + ], +) +def test_s3_object_key_has_no_colon_for_cloud_uri_file_ids(response_id: str): + from litellm.integrations.s3 import get_s3_object_key + + key = get_s3_object_key( + s3_path="", + prefix="", + start_time=datetime(2026, 9, 7, 4, 51, 6, 685889), + s3_file_name=f"time-04-51-06-685889_{response_id}", + ) + + filename = key.rsplit("/", 1)[-1] + assert ":" not in filename + assert filename.endswith("_input.jsonl.json") + + def test_create_s3_batch_logging_element_flat_key_for_arn_response_id(): """End-to-end through the s3_v2 element builder: an ARN response id must yield a flat file directly under the date segment.""" From 38f0eb876bf2f05b4850adb8e80bcb48885e557e Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 17:42:12 -0700 Subject: [PATCH 064/101] test(realtime): drop legacy InvalidStatusCode tests and pin websockets imports (#42624) The two redaction tests raised the deprecated InvalidStatusCode, which the websockets 15 asyncio client never raises, and asserted the raw 403 close code that the handshake refusal path replaced with 1008. The refusal path builds its close reason from the status code alone, so there is no secret to redact there, and the handshake refusal tests already cover the error event and the 1008 close. Those refusal tests only passed when run after a sibling test had imported websockets.asyncio.client, since websockets lazy-loads its exceptions submodule. Importing InvalidStatus, Response, and Headers from their own submodules makes them pass in any order. Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- .../llms/azure/realtime/test_handler.py | 8 +-- .../realtime/test_openai_realtime_handler.py | 8 +-- .../test_redact_string_in_error_paths.py | 56 +------------------ 3 files changed, 9 insertions(+), 63 deletions(-) diff --git a/tests/test_litellm/llms/azure/realtime/test_handler.py b/tests/test_litellm/llms/azure/realtime/test_handler.py index edf1b8b290f..e9d24b459d8 100644 --- a/tests/test_litellm/llms/azure/realtime/test_handler.py +++ b/tests/test_litellm/llms/azure/realtime/test_handler.py @@ -21,7 +21,9 @@ class _RecordingClientWebSocket: @pytest.mark.asyncio async def test_async_realtime_upstream_handshake_refusal_sends_error_event_then_policy_close(): - import websockets + from websockets.datastructures import Headers + from websockets.exceptions import InvalidStatus + from websockets.http11 import Response from litellm.llms.azure.realtime.handler import AzureOpenAIRealtime from litellm.types.realtime import RealtimeErrorEvent @@ -32,9 +34,7 @@ async def test_async_realtime_upstream_handshake_refusal_sends_error_event_then_ dummy_websocket = _RecordingClientWebSocket() dummy_logging_obj = MagicMock() - refused = websockets.exceptions.InvalidStatus( - websockets.http11.Response(401, "Unauthorized", websockets.datastructures.Headers()) - ) + refused = InvalidStatus(Response(401, "Unauthorized", Headers())) with patch("websockets.connect", side_effect=refused): await handler.async_realtime( # pyright: ignore[reportUnknownMemberType] # handler's websocket param is a Protocol here but the mock connect type is incomplete diff --git a/tests/test_litellm/llms/openai/realtime/test_openai_realtime_handler.py b/tests/test_litellm/llms/openai/realtime/test_openai_realtime_handler.py index 7cd2b9e259c..f7a88b5ba63 100644 --- a/tests/test_litellm/llms/openai/realtime/test_openai_realtime_handler.py +++ b/tests/test_litellm/llms/openai/realtime/test_openai_realtime_handler.py @@ -422,7 +422,9 @@ async def test_async_realtime_ws_url_has_no_ssl(): async def test_async_realtime_upstream_handshake_refusal_sends_error_event_then_policy_close(): from typing import cast - import websockets + from websockets.datastructures import Headers + from websockets.exceptions import InvalidStatus + from websockets.http11 import Response from litellm.llms.openai.realtime.handler import OpenAIRealtime from litellm.types.realtime import RealtimeErrorEvent @@ -445,9 +447,7 @@ async def test_async_realtime_upstream_handshake_refusal_sends_error_event_then_ dummy_websocket = RecordingClientWebSocket() dummy_logging_obj = MagicMock() - refused = websockets.exceptions.InvalidStatus( - websockets.http11.Response(401, "Unauthorized", websockets.datastructures.Headers()) - ) + refused = InvalidStatus(Response(401, "Unauthorized", Headers())) with patch("websockets.connect", side_effect=refused): await handler.async_realtime( # pyright: ignore[reportUnknownMemberType] # handler's websocket param is Any diff --git a/tests/test_litellm/test_redact_string_in_error_paths.py b/tests/test_litellm/test_redact_string_in_error_paths.py index 07d1ec5f523..a5128a87b0d 100644 --- a/tests/test_litellm/test_redact_string_in_error_paths.py +++ b/tests/test_litellm/test_redact_string_in_error_paths.py @@ -2,7 +2,7 @@ Tests for _redact_string usage in error/logging paths. Covers actual execution of redaction in: -- WebSocket close reasons in realtime handlers (openai, azure, bedrock) +- WebSocket close reasons in realtime handlers (openai, bedrock) - Gemini RAG ingestion x-goog-api-key header usage - Traceback redaction pattern used in proxy streaming - Router fallback-failure traceback redaction @@ -72,25 +72,6 @@ class TestOpenAIRealtimeRedaction: api_key="test-key", ) - @pytest.mark.asyncio - async def test_invalid_status_code_redacts_reason(self): - import websockets.exceptions - - from litellm.llms.openai.realtime.handler import OpenAIRealtime - - handler = OpenAIRealtime() - exc = websockets.exceptions.InvalidStatusCode(403, None) - exc.status_code = 403 - - kwargs = self._call_kwargs() - mock_ws = kwargs["websocket"] - p1, p2, p3 = self._make_patches(handler) - with p1, p2, p3, patch("websockets.connect", side_effect=exc): - await handler.async_realtime(**kwargs) - - mock_ws.close.assert_called_once() - assert mock_ws.close.call_args[1]["code"] == 403 - @pytest.mark.asyncio async def test_generic_exception_redacts_reason(self): from litellm.llms.openai.realtime.handler import OpenAIRealtime @@ -111,41 +92,6 @@ class TestOpenAIRealtimeRedaction: assert "sk-1234567890abcdefghij" not in mock_ws.close.call_args[1]["reason"] -class TestAzureRealtimeRedaction: - """Test that Azure realtime handler redacts secrets in websocket close reasons.""" - - @pytest.mark.asyncio - async def test_invalid_status_code_redacts_reason(self): - import websockets.exceptions - - from litellm.llms.azure.realtime.handler import AzureOpenAIRealtime - - handler = AzureOpenAIRealtime() - mock_ws = AsyncMock() - exc = websockets.exceptions.InvalidStatusCode(403, None) - exc.status_code = 403 - - with ( - patch.object( - handler, - "_construct_url", - return_value="wss://test.openai.azure.com/openai/realtime", - ), - patch("websockets.connect", side_effect=exc), - ): - await handler.async_realtime( - model="gpt-4", - websocket=mock_ws, - logging_obj=MagicMock(), - api_base="https://test.openai.azure.com/", - api_key="test-key", - api_version="2024-10-01-preview", - ) - - mock_ws.close.assert_called_once() - assert mock_ws.close.call_args[1]["code"] == 403 - - class TestBedrockRealtimeRedaction: """Test that _redact_string produces safe close reasons for Bedrock-style errors.""" From 8ee6bab52931798d9aec00003797c25d0190e144 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 17:55:22 -0700 Subject: [PATCH 065/101] fix(bedrock): treat blank AWS_S3_* env vars as unset for batch jobs (#42528) * test(e2e): pin bedrock batch create with blank S3 env vars Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(bedrock): treat blank S3 env vars as unset for batch jobs Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(e2e): trim blank S3 env gateway config Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(e2e): register blank_s3_env capability and clean gateway tempdir Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(e2e): move blank S3 env batch test to its own module Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: yucheng Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- litellm/llms/bedrock/common_utils.py | 2 +- tests/e2e/batches/COVERAGE.md | 1 + tests/e2e/batches/bedrock_env_gateway.py | 145 ++++++++++++++++++ .../batches/test_bedrock_blank_s3_env_e2e.py | 109 +++++++++++++ .../llm_nonconversational.yaml | 1 + tests/e2e/coverage_registry/schema.py | 1 + .../bedrock/batches/test_transformation.py | 41 ++++- 7 files changed, 297 insertions(+), 3 deletions(-) create mode 100644 tests/e2e/batches/bedrock_env_gateway.py create mode 100644 tests/e2e/batches/test_bedrock_blank_s3_env_e2e.py diff --git a/litellm/llms/bedrock/common_utils.py b/litellm/llms/bedrock/common_utils.py index d9fc813a594..2e20aafffcb 100644 --- a/litellm/llms/bedrock/common_utils.py +++ b/litellm/llms/bedrock/common_utils.py @@ -1593,7 +1593,7 @@ def _resolve_s3_setting( source.get(param_name) for source in (litellm_params, optional_params) if source is not None ) explicit: Final = next((value for value in candidates if isinstance(value, str) and value), None) - return explicit or get_secret_str(env_var) + return explicit or get_secret_str(env_var) or None class CommonBatchFilesUtils: diff --git a/tests/e2e/batches/COVERAGE.md b/tests/e2e/batches/COVERAGE.md index 1731b4c620d..862eef5c0f4 100644 --- a/tests/e2e/batches/COVERAGE.md +++ b/tests/e2e/batches/COVERAGE.md @@ -22,6 +22,7 @@ failures are hard test failures (see `tests/e2e/AGENTS.md`). | Bedrock | yes (unified only) | yes | yes | yes (unfiltered managed list) | yes (provider-transformed) | S3 (`s3_bucket_name` + `aws_*` + `AWS_BATCH_ROLE_ARN` on model) | | Bedrock GovCloud (`us-gov-west-1`) | yes (unified only) | yes | no | no | yes (provider-transformed) | S3 (`s3_bucket_name` + `aws_*` on model, resolved from `AWS_GOVCLOUD_ACCESS_KEY_ID` / `AWS_GOVCLOUD_SECRET_ACCESS_KEY` / `AWS_GOVCLOUD_BATCH_S3_BUCKET` / `AWS_GOVCLOUD_BATCH_ROLE_ARN`) | | Bedrock split S3 identity | no | no | no | no | yes (file upload, content, delete) | S3 signed with `s3_access_key_id` / `s3_secret_access_key` (`AWS_S3_ONLY_ACCESS_KEY_ID` / `AWS_S3_ONLY_SECRET_ACCESS_KEY`, object rights on `AWS_BATCH_S3_BUCKET` only) while `aws_*` is `AWS_BEDROCK_ONLY_ACCESS_KEY_ID` / `AWS_BEDROCK_ONLY_SECRET_ACCESS_KEY`, an identity with no S3 rights on that bucket | +| Bedrock blank S3 env | yes (unified only, on an owned gateway exporting `AWS_S3_ENCRYPTION_KEY_ID` / `AWS_S3_BUCKET_OWNER` as empty strings) | no | no | no | no | S3 (`s3_bucket_name` + `aws_*` + `AWS_BATCH_ROLE_ARN` in the gateway config); blank env vars must be treated as unset, not serialized | Bedrock cancel maps to `StopModelInvocationJob` and comes back `cancelling`; the lifecycle asserts it the same way it does for OpenAI (`_CANCEL_ASSERTED_PROVIDERS`). diff --git a/tests/e2e/batches/bedrock_env_gateway.py b/tests/e2e/batches/bedrock_env_gateway.py new file mode 100644 index 00000000000..fb3ec60c87c --- /dev/null +++ b/tests/e2e/batches/bedrock_env_gateway.py @@ -0,0 +1,145 @@ +"""An owned, source-built proxy whose process env exports AWS_S3_* vars blank. + +The shared fixture proxy inherits the harness env, which cannot reproduce a user +shell that exports AWS_S3_ENCRYPTION_KEY_ID / AWS_S3_BUCKET_OWNER as empty +strings. This gateway boots a second proxy with both vars present but blank, so +a batch create through it proves blank means unset, not an empty string. +""" + +from __future__ import annotations + +import os +import shutil +import socket +import subprocess +import sys +import tempfile +import time +from collections.abc import Mapping +from dataclasses import dataclass, field +from pathlib import Path +from typing import Final + +from e2e_config import unique_marker +from e2e_http import NoBody +from idp import stop_process_group +from proxy_client import ProxyClient, build_proxy_client +from pydantic import TypeAdapter + +STARTUP_TIMEOUT_SECONDS: Final = 240 +LOG_TAIL_BYTES: Final = 4000 +REPO_ROOT: Final = Path(__file__).resolve().parents[3] + +_CONFIG_YAML: Final = """model_list: + - model_name: bedrock-blank-s3-batch + litellm_params: + model: bedrock/us.anthropic.claude-haiku-4-5-20251001-v1:0 + 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 + s3_region_name: os.environ/AWS_REGION + s3_bucket_name: os.environ/AWS_BATCH_S3_BUCKET + s3_access_key_id: os.environ/AWS_ACCESS_KEY_ID + s3_secret_access_key: os.environ/AWS_SECRET_ACCESS_KEY + aws_batch_role_arn: os.environ/AWS_BATCH_ROLE_ARN + +general_settings: + master_key: os.environ/LITELLM_MASTER_KEY + database_url: os.environ/DATABASE_URL +""" + + +def available_port() -> int: + with socket.socket() as listener: + listener.bind(("127.0.0.1", 0)) + return TypeAdapter(tuple[str, int]).validate_python(listener.getsockname())[1] + + +@dataclass(slots=True) +class BedrockEnvGateway: + base_url: str + master_key: str + proxy: ProxyClient + _environment: Mapping[str, str] = field(repr=False) + _command: tuple[str, ...] = field(repr=False) + _log_path: Path + _child: subprocess.Popen[bytes] | None = field(default=None, init=False, repr=False) + + @classmethod + def start(cls) -> BedrockEnvGateway: + assert os.environ.get("DATABASE_URL"), "DATABASE_URL is required for the blank-S3-env gateway" + port: Final = available_port() + base_url: Final = f"http://127.0.0.1:{port}" + master_key: Final = f"sk-e2e-blank-s3-{unique_marker()}" + directory: Final = Path(tempfile.mkdtemp(prefix="litellm-e2e-blank-s3-")) + config: Final = directory / "blank-s3-gateway.yaml" + config.write_text(_CONFIG_YAML) + environment: Final = { + **{key: value for key, value in os.environ.items() if not key.startswith("REDIS_")}, + "DATABASE_URL": os.environ["DATABASE_URL"], + "LITELLM_MASTER_KEY": master_key, + "STORE_MODEL_IN_DB": "False", + "PYTHONPATH": str(REPO_ROOT), + "AWS_S3_ENCRYPTION_KEY_ID": "", + "AWS_S3_BUCKET_OWNER": "", + } + gateway: Final = cls( + base_url=base_url, + master_key=master_key, + proxy=build_proxy_client( + base_url=base_url, + control_plane_base_url=base_url, + replica_urls=(base_url,), + master_key=master_key, + ), + _environment=environment, + _command=( + sys.executable, + "-m", + "litellm.proxy.proxy_cli", + "--config", + str(config), + "--port", + str(port), + "--host", + "127.0.0.1", + ), + _log_path=directory / "blank-s3-gateway.log", + ) + with gateway._log_path.open("ab") as log: + gateway._child = subprocess.Popen( + gateway._command, + env=dict(gateway._environment), + stdout=log, + stderr=log, + start_new_session=True, + cwd=REPO_ROOT, + ) + deadline: Final = time.monotonic() + STARTUP_TIMEOUT_SECONDS + while time.monotonic() < deadline: + assert gateway._child.poll() is None, ( + f"blank-S3-env gateway exited early; log tail:\n{gateway.log_tail()}" + ) + result = gateway.proxy.transport.probe("/health/liveliness", params=NoBody()) + if result.status_code == 200: + return gateway + time.sleep(0.5) + tail: Final = gateway.log_tail() + gateway.stop() + raise AssertionError( + f"blank-S3-env gateway did not become ready in {STARTUP_TIMEOUT_SECONDS}s; log tail:\n{tail}" + ) + + def log_tail(self) -> str: + if not self._log_path.exists(): + return "" + with self._log_path.open("rb") as log: + log.seek(0, 2) + size: Final = log.tell() + log.seek(max(0, size - LOG_TAIL_BYTES)) + return log.read().decode("utf-8", errors="replace") + + def stop(self) -> None: + if self._child is not None: + stop_process_group(self._child) + shutil.rmtree(self._log_path.parent, ignore_errors=True) diff --git a/tests/e2e/batches/test_bedrock_blank_s3_env_e2e.py b/tests/e2e/batches/test_bedrock_blank_s3_env_e2e.py new file mode 100644 index 00000000000..77eb8427e59 --- /dev/null +++ b/tests/e2e/batches/test_bedrock_blank_s3_env_e2e.py @@ -0,0 +1,109 @@ +"""Live e2e pin for Bedrock batch create with blank AWS_S3_* env vars. + +Owns its own file (not test_batches_e2e.py) so the PR changed-file e2e gate +stays a single tiny file: this class boots its own gateway with +AWS_S3_ENCRYPTION_KEY_ID and AWS_S3_BUCKET_OWNER exported empty, then runs the +unified target_model_names upload + batch create lifecycle against real Bedrock. +""" + +from __future__ import annotations + +import json +from typing import Final + +import pytest +from batch_cleanup import cleanup_batch, cleanup_file +from batch_client import BatchClient, BatchCreateBody, BatchObject, FileObject +from bedrock_env_gateway import BedrockEnvGateway +from capabilities import is_managed_id +from e2e_http import FileUploadForm, require_successful_call, unwrap +from lifecycle import ResourceManager +from models import KeyGenerateBody + +pytestmark = pytest.mark.e2e + +CREATED_BATCH_STATUSES = {"validating", "in_progress", "finalizing"} +BLANK_S3_RAW_MODEL: Final = "bedrock/us.anthropic.claude-haiku-4-5-20251001-v1:0" + + +def render_jsonl(model: str) -> bytes: + line = { + "custom_id": "req-1", + "method": "POST", + "url": "/v1/chat/completions", + "body": { + "model": model, + "messages": [{"role": "user", "content": "ping"}], + "max_tokens": 8, + }, + } + return (json.dumps(line) + "\n").encode() + + +def assert_file_object(file: FileObject, *, provider: str) -> None: + assert file.object == "file", f"file.object={file.object!r}" + assert file.purpose == "batch", f"file.purpose={file.purpose!r}" + assert file.bytes is not None, f"file.bytes={file.bytes!r}" + if provider != "bedrock": + assert file.bytes > 0, f"file.bytes={file.bytes!r}" + assert file.status, "file.status missing" + assert file.created_at is not None and file.created_at > 0, "file.created_at missing" + + +def assert_batch_object(batch: BatchObject) -> None: + assert batch.object == "batch", f"batch.object={batch.object!r}" + if batch.endpoint: + assert batch.endpoint == "/v1/chat/completions", f"batch.endpoint={batch.endpoint!r}" + assert batch.completion_window == "24h", f"window={batch.completion_window!r}" + assert batch.input_file_id, "batch.input_file_id missing" + assert batch.created_at is not None and batch.created_at > 0, "batch.created_at missing" + + +class TestBedrockBatchBlankS3EnvVars: + """Bedrock batch create with AWS_S3_* env vars exported but blank. + + Regression: a blank AWS_S3_ENCRYPTION_KEY_ID or AWS_S3_BUCKET_OWNER env var + resolved to "" and was serialized into the create-job request, which Bedrock + rejects. The owned gateway exports both vars empty, so the unified lifecycle + only passes when blank is treated as unset. + """ + + @pytest.mark.covers( + "llm.batches.bedrock.blank_s3_env.nonstream.works", + "llm.files.bedrock.upload.nonstream.works", + exercised_on=["batches", "files"], + ) + def test_unified_batch_create_ignores_blank_s3_env_vars(self, resources: ResourceManager) -> None: + gateway: Final = BedrockEnvGateway.start() + resources.defer(gateway.stop) + client: Final = BatchClient(proxy=gateway.proxy) + + key: Final = client.proxy.generate_key(KeyGenerateBody(models=[], user_id="e2e-test-user")) + resources.defer(lambda: client.proxy.delete_key(key)) + + file: Final = unwrap( + client.upload_file( + content=render_jsonl(BLANK_S3_RAW_MODEL), + form=FileUploadForm(purpose="batch", target_model_names="bedrock-blank-s3-batch"), + key=key, + ) + ) + resources.defer(lambda: cleanup_file(client, file.id, key=key)) + assert_file_object(file, provider="bedrock") + + created: Final = client.create_batch(body=BatchCreateBody(input_file_id=file.id), key=key) + assert created.status_code < 400, ( + f"blank AWS_S3_ENCRYPTION_KEY_ID / AWS_S3_BUCKET_OWNER must be treated as " + f"unset; Bedrock rejected the job: {created.body[:400]}" + ) + require_successful_call(created) + batch: Final = BatchObject.model_validate_json(created.body) + resources.defer(lambda: cleanup_batch(client, batch.id, key=key)) + + assert is_managed_id(batch.id), ( + f"blank-S3-env create via target_model_names must return a managed batch id, got {batch.id!r}" + ) + assert batch.status in CREATED_BATCH_STATUSES, ( + f"blank-S3-env batch has non-transitional status {batch.status!r}" + ) + assert_batch_object(batch) diff --git a/tests/e2e/coverage_registry/llm_nonconversational.yaml b/tests/e2e/coverage_registry/llm_nonconversational.yaml index c58c8af44ff..3e389acc2a9 100644 --- a/tests/e2e/coverage_registry/llm_nonconversational.yaml +++ b/tests/e2e/coverage_registry/llm_nonconversational.yaml @@ -24,6 +24,7 @@ - {id: llm.batches.bedrock.basic.nonstream.works, module: llm, tier: P0, subject_endpoint: batches, route: bedrock_converse, capability: basic, streaming: nonstream, assertions: [works], source: "batches/capabilities.py:98", rationale: "Bedrock batches (encoded/unified only)"} - {id: llm.batches.bedrock.assume_role.nonstream.works, module: llm, tier: P0, subject_endpoint: batches, route: bedrock_converse, capability: assume_role, streaming: nonstream, assertions: [works], source: "test_batches_e2e.py", rationale: "Bedrock batch create under STS assume-role credentials"} - {id: llm.batches.bedrock.govcloud_partition.nonstream.works, module: llm, tier: P0, subject_endpoint: batches, route: bedrock_converse, capability: govcloud_partition, streaming: nonstream, assertions: [works], source: "test_batches_e2e.py", rationale: "Bedrock batch create in the us-gov-west-1 partition"} +- {id: llm.batches.bedrock.blank_s3_env.nonstream.works, module: llm, tier: P0, subject_endpoint: batches, route: bedrock_converse, capability: blank_s3_env, streaming: nonstream, assertions: [works], source: "test_bedrock_blank_s3_env_e2e.py", rationale: "Bedrock batch create treats blank AWS_S3_ENCRYPTION_KEY_ID / AWS_S3_BUCKET_OWNER env vars as unset instead of serializing empty strings"} - {id: llm.batches.bedrock.cancel.nonstream.works, module: llm, tier: P0, subject_endpoint: batches, route: bedrock_converse, capability: basic, streaming: nonstream, assertions: [works], source: "test_batches_e2e.py", rationale: "Bedrock batch cancel (StopModelInvocationJob) returns the same id with a cancelling/cancelled status"} - {id: llm.batches.bedrock.list.nonstream.works, module: llm, tier: P0, subject_endpoint: batches, route: bedrock_converse, capability: basic, streaming: nonstream, assertions: [works], source: "test_batches_e2e.py", rationale: "A Bedrock managed batch is present in the GET /v1/batches list envelope"} - {id: llm.batches.hosted_vllm.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: batches, route: hosted_vllm, capability: basic, streaming: nonstream, assertions: [works], source: "test_batches_e2e.py", rationale: "hosted_vllm OpenAI-compatible batch create"} diff --git a/tests/e2e/coverage_registry/schema.py b/tests/e2e/coverage_registry/schema.py index f3ac1ef8a83..e009b02b69c 100644 --- a/tests/e2e/coverage_registry/schema.py +++ b/tests/e2e/coverage_registry/schema.py @@ -65,6 +65,7 @@ LlmCapability = Literal[ "assume_role", "basic", "batch_deployment", + "blank_s3_env", "count_tokens", "govcloud_partition", "split_s3_credentials", diff --git a/tests/test_litellm/llms/bedrock/batches/test_transformation.py b/tests/test_litellm/llms/bedrock/batches/test_transformation.py index eb08c19cbdf..347c459a369 100644 --- a/tests/test_litellm/llms/bedrock/batches/test_transformation.py +++ b/tests/test_litellm/llms/bedrock/batches/test_transformation.py @@ -19,9 +19,8 @@ from unittest.mock import MagicMock, patch import httpx import pytest - from litellm.llms.bedrock.batches.transformation import BedrockBatchesConfig -from litellm.types.utils import LiteLLMBatch, LlmProviders +from litellm.types.utils import LlmProviders # AWS JobStatus -> OpenAI BatchJobStatus, exactly as encoded in transformation.py # (both transform_create_batch_response and transform_retrieve_batch_response). @@ -270,6 +269,44 @@ def test_create_request_keeps_kms_key_alongside_s3_bucket_owner(config, monkeypa } +def test_create_request_omits_kms_key_when_env_var_is_blank(config, monkeypatch): + monkeypatch.setenv("AWS_S3_ENCRYPTION_KEY_ID", "") + monkeypatch.delenv("AWS_S3_BUCKET_OWNER", raising=False) + + bedrock_request = _signed_batch_request(config, {}, {}) + + assert bedrock_request["outputDataConfig"] == { + "s3OutputDataConfig": {"s3Uri": "s3://in-bucket/litellm-batch-outputs/litellm-batch-1/"} + } + + +def test_create_request_omits_s3_bucket_owner_when_env_var_is_blank(config, monkeypatch): + monkeypatch.setenv("AWS_S3_BUCKET_OWNER", "") + monkeypatch.delenv("AWS_S3_ENCRYPTION_KEY_ID", raising=False) + + bedrock_request = _signed_batch_request(config, {}, {}) + + assert bedrock_request["inputDataConfig"] == {"s3InputDataConfig": {"s3Uri": "s3://in-bucket/in.jsonl"}} + assert bedrock_request["outputDataConfig"] == { + "s3OutputDataConfig": {"s3Uri": "s3://in-bucket/litellm-batch-outputs/litellm-batch-1/"} + } + + +def test_create_request_emits_real_values_alongside_blank_sibling_env_var(config, monkeypatch): + monkeypatch.setenv("AWS_S3_ENCRYPTION_KEY_ID", "kms-key-123") + monkeypatch.setenv("AWS_S3_BUCKET_OWNER", "") + + bedrock_request = _signed_batch_request(config, {}, {}) + + assert bedrock_request["inputDataConfig"] == {"s3InputDataConfig": {"s3Uri": "s3://in-bucket/in.jsonl"}} + assert bedrock_request["outputDataConfig"] == { + "s3OutputDataConfig": { + "s3Uri": "s3://in-bucket/litellm-batch-outputs/litellm-batch-1/", + "s3EncryptionKeyId": "kms-key-123", + } + } + + def test_create_request_missing_input_file_id_raises(config): with pytest.raises(ValueError, match="input_file_id is required"): config.transform_create_batch_request( From 21a2d828dffd70b0c868d2dba487d3c372239475 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Wed, 23 Sep 2026 00:56:32 +0000 Subject: [PATCH 066/101] ci(test-unit): drop dead misc shard paths and skip missing paths with a warning (#42603) Eight directories the misc shard named moved to tests/unit on 2026-09-20, and one missing path makes pytest-xdist collect [0 items] for the whole shard, which the exit-5 tolerance turned into a green required check running nothing. The shared Run tests step now drops a path that does not exist with a ::warning:: and runs pytest over the rest, keeping option tokens verbatim. Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- .github/workflows/_test-unit-base.yml | 32 +++++--- .github/workflows/test-unit.yml | 8 -- .../test_unit_shard_missing_paths.py | 74 +++++++++++++++++++ 3 files changed, 97 insertions(+), 17 deletions(-) create mode 100644 tests/test_litellm/test_unit_shard_missing_paths.py diff --git a/.github/workflows/_test-unit-base.yml b/.github/workflows/_test-unit-base.yml index f4d4fb54ba6..8faddd11df8 100644 --- a/.github/workflows/_test-unit-base.yml +++ b/.github/workflows/_test-unit-base.yml @@ -4,7 +4,13 @@ on: workflow_call: inputs: test-path: - description: "Pytest path(s) to run" + description: >- + Space-separated pytest paths to run. A path that no longer exists is + dropped with a warning instead of being passed to pytest, because one + missing path makes pytest-xdist collect nothing and report exit 5, which + the step treats as a drained shard. Options are passed through as + written, so use the `--flag=value` form: a bare `--ignore path` would + have its path existence-checked like any other token. required: true type: string workers: @@ -165,14 +171,22 @@ jobs: DIST: ${{ inputs.dist }} COVERAGE_CORE: sysmon run: | - found_path=false - for path in ${TEST_PATH}; do - if [ -e "${path%%::*}" ]; then - found_path=true - break - fi + pytest_args=() + existing_paths=0 + for token in ${TEST_PATH:?}; do + case "${token}" in + -*) pytest_args+=("${token}") ;; + *) + if [ -e "${token%%::*}" ]; then + pytest_args+=("${token}") + existing_paths=$((existing_paths + 1)) + else + echo "::warning::${token} does not exist; drop it from this shard's test-path" + fi + ;; + esac done - if [ "$found_path" = false ]; then + if [ "${existing_paths}" -eq 0 ]; then echo "No path in TEST_PATH exists (${TEST_PATH}); nothing to run" exit 0 fi @@ -181,7 +195,7 @@ jobs: xdist_args=(-n "${WORKERS}" --dist="${DIST}") fi set +e - uv run --no-sync pytest ${TEST_PATH:?} \ + uv run --no-sync pytest "${pytest_args[@]}" \ --tb=short -vv \ --maxfail="${MAX_FAILURES}" \ "${xdist_args[@]}" \ diff --git a/.github/workflows/test-unit.yml b/.github/workflows/test-unit.yml index 49e6d7040d4..ac60a9b5f05 100644 --- a/.github/workflows/test-unit.yml +++ b/.github/workflows/test-unit.yml @@ -107,26 +107,18 @@ jobs: tests/test_litellm/batches tests/test_litellm/secret_managers tests/test_litellm/a2a_protocol - tests/test_litellm/anthropic_interface tests/test_litellm/chat_completions tests/test_litellm/completion_extras - tests/test_litellm/compression tests/test_litellm/containers tests/test_litellm/endpoints - tests/test_litellm/models - tests/test_litellm/repositories tests/test_litellm/images tests/test_litellm/interactions tests/test_litellm/messages tests/test_litellm/ocr tests/test_litellm/passthrough tests/test_litellm/rag - tests/test_litellm/realtime_api tests/test_litellm/rerank_api tests/test_litellm/rust_bridge - tests/test_litellm/sandbox - tests/test_litellm/skills - tests/test_litellm/test_router tests/test_litellm/vector_stores tests/test_litellm/videos tests/test_litellm/test_*.py diff --git a/tests/test_litellm/test_unit_shard_missing_paths.py b/tests/test_litellm/test_unit_shard_missing_paths.py new file mode 100644 index 00000000000..b91c2cff764 --- /dev/null +++ b/tests/test_litellm/test_unit_shard_missing_paths.py @@ -0,0 +1,74 @@ +import os +import subprocess +import sys +from pathlib import Path +from types import MappingProxyType +from typing import Final + +import pytest +import yaml + +_REPO_ROOT: Final = Path(__file__).resolve().parents[2] +_BASE_WORKFLOW: Final = _REPO_ROOT / ".github" / "workflows" / "_test-unit-base.yml" +_SHARD_ENV: Final = MappingProxyType( + {"MAX_FAILURES": "10", "RERUNS": "0", "DIST": "loadscope", "TEST_TIMEOUT_SECONDS": "60", "COVERAGE_CORE": "sysmon"} +) +_UV_SHIM: Final = f'#!/usr/bin/env bash\nshift 2\nexec "{sys.executable}" -m "$@"\n' +_PASSING_TEST: Final = "def test_passes():\n assert True\n" +_FAILING_TEST: Final = "def test_fails():\n assert False\n" + + +def _run_tests_script() -> str: + workflow: Final = yaml.safe_load(_BASE_WORKFLOW.read_text()) + return next(step["run"] for step in workflow["jobs"]["run"]["steps"] if step.get("name") == "Run tests") + + +def _run_shard(tmp_path: Path, test_path: str, workers: str) -> subprocess.CompletedProcess[str]: + shim_dir: Final = tmp_path / "bin" + shim_dir.mkdir() + (shim_dir / "uv").write_text(_UV_SHIM) + (shim_dir / "uv").chmod(0o755) + (tmp_path / "pyproject.toml").write_text("[tool.pytest.ini_options]\naddopts = '-p no:cacheprovider'\n") + return subprocess.run( + ("bash", "--noprofile", "--norc", "-eo", "pipefail", "-c", _run_tests_script()), + cwd=tmp_path, + env={ + **os.environ, + **_SHARD_ENV, + "PATH": f"{shim_dir}{os.pathsep}{os.environ['PATH']}", + "TEST_PATH": test_path, + "WORKERS": workers, + }, + capture_output=True, + text=True, + timeout=120, + check=False, + ) + + +def _write_passing_test(tmp_path: Path) -> Path: + present: Final = tmp_path / "tests" / "present" + present.mkdir(parents=True) + (present / "test_present.py").write_text(_PASSING_TEST) + return present + + +@pytest.mark.parametrize("workers", ("0", "2"), ids=("serial", "xdist")) +def test_a_missing_path_is_dropped_and_the_existing_paths_still_run(tmp_path: Path, workers: str) -> None: + _write_passing_test(tmp_path) + + result: Final = _run_shard(tmp_path, "tests/gone tests/present", workers) + + assert result.returncode == 0, result.stdout + result.stderr + assert "1 passed" in result.stdout, result.stdout + assert "::warning::tests/gone does not exist" in result.stdout + + +def test_ignore_flags_survive_the_path_filter(tmp_path: Path) -> None: + present: Final = _write_passing_test(tmp_path) + (present / "test_ignored.py").write_text(_FAILING_TEST) + + result: Final = _run_shard(tmp_path, "tests/present --ignore=tests/present/test_ignored.py", "0") + + assert result.returncode == 0, result.stdout + result.stderr + assert "1 passed" in result.stdout, result.stdout From a80379baf8910f5aa72990cd1bdbd8088d5e6b2c Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 17:58:08 -0700 Subject: [PATCH 067/101] fix(proxy): keep the in-flight daily spend batch when shutdown cancels the flush (#42593) * fix(proxy): keep the in-flight daily spend batch when shutdown cancels the flush A daily spend batch drained from the in-memory queue was dropped for good when the scheduler tick was cancelled by shutdown, because asyncio.CancelledError bypasses the except Exception requeue. The flush now requeues the drained rows on cancellation and re-raises, and each daily batch upsert runs in an interactive transaction so a statement that already reached Postgres is rolled back with the cancel instead of committing behind the requeue Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): requeue the cancelled daily spend batch before its rollback returns Behind a lock the rollback of the cancelled interactive transaction only returns once the blocked statement does, which is after the shutdown flush has already run. The commit now runs as a shielded task so the cancelled tick requeues the batch at once and lets the rollback finish in the background. The final flush then finds the rows and writes them exactly once Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(proxy): give the recording db a transaction seam for the bulk upsert tests Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(proxy): route the mocked daily tag spend upsert through the transaction seam Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(proxy): restore the drained Redis tag batch when shutdown cancels its commit Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: yucheng Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- litellm/proxy/db/db_spend_update_writer.py | 25 +- tests/integration/_support/process.py | 37 ++- tests/integration/contracts.json | 6 + .../integration/spend/test_shutdown_flush.py | 189 ++++++++++++ .../test_update_daily_tag_spend.py | 1 + .../proxy/db/test_daily_spend_bulk_upsert.py | 9 + .../proxy/db/test_db_spend_update_writer.py | 270 +++++++++++++++++- 7 files changed, 520 insertions(+), 17 deletions(-) create mode 100644 tests/integration/spend/test_shutdown_flush.py diff --git a/litellm/proxy/db/db_spend_update_writer.py b/litellm/proxy/db/db_spend_update_writer.py index d9c8b271646..e38214c98a6 100644 --- a/litellm/proxy/db/db_spend_update_writer.py +++ b/litellm/proxy/db/db_spend_update_writer.py @@ -1606,13 +1606,21 @@ class DBSpendUpdateWriter: proxy_logging_obj: ProxyLogging, ) -> None: transactions: Final = await queue.flush_and_get_aggregated_daily_spend_update_transactions() - try: - await commit( + commit_task: Final = asyncio.ensure_future( + commit( n_retry_times=n_retry_times, prisma_client=prisma_client, proxy_logging_obj=proxy_logging_obj, daily_spend_transactions=cast(dict[str, _DailySpendTransactionT], transactions), ) + ) + try: + await asyncio.shield(commit_task) + except asyncio.CancelledError: + commit_task.cancel() + if transactions: + await queue.add_update(transactions) + raise except Exception as e: # noqa: BLE001 # whatever failed here, the other tables must still flush if not transactions: return @@ -1839,14 +1847,18 @@ class DBSpendUpdateWriter: if not daily_tag_spend_update_transactions: return - try: - await DBSpendUpdateWriter.update_daily_tag_spend( + commit_task: Final = asyncio.ensure_future( + DBSpendUpdateWriter.update_daily_tag_spend( n_retry_times=n_retry_times, prisma_client=prisma_client, proxy_logging_obj=proxy_logging_obj, daily_spend_transactions=daily_tag_spend_update_transactions, ) - except Exception: + ) + try: + await asyncio.shield(commit_task) + except BaseException: # noqa: BLE001 # a cancel must restore the drained rows before its rollback returns + commit_task.cancel() await self.redis_update_buffer.restore_transactions_to_redis( daily_tag_spend_update_transactions=daily_tag_spend_update_transactions, ) @@ -2368,7 +2380,8 @@ class DBSpendUpdateWriter: table=table, transactions=tuple(transactions_to_process.values()) ) sql, params = build_bulk_upsert(table=table, batch=merged_batch) - await prisma_client.db.execute_raw(sql, *params) + async with _spend_update_tx(prisma_client) as transaction: + await transaction.execute_raw(sql, *params) except Exception as batch_error: if _spend_commit_failure_is_requeue_safe(batch_error): spend_log_error( diff --git a/tests/integration/_support/process.py b/tests/integration/_support/process.py index e0923c9d055..0798927c6d1 100644 --- a/tests/integration/_support/process.py +++ b/tests/integration/_support/process.py @@ -7,6 +7,7 @@ import time import uuid from collections.abc import Iterator, Mapping from contextlib import contextmanager +from dataclasses import dataclass from pathlib import Path from typing import Final @@ -45,8 +46,37 @@ def stop_root_process(process: subprocess.Popen[bytes]) -> bool: return True +@dataclass(frozen=True, slots=True) +class OwnedProxy: + gateway: Gateway + process: subprocess.Popen[bytes] + log: Path + + @contextmanager -def owned_proxy(gateway: Gateway, directory: Path, overrides: Mapping[str, str], *, config: Path | None = None, remove_environment: tuple[str, ...] = ()) -> Iterator[Gateway]: +def owned_proxy( + gateway: Gateway, + directory: Path, + overrides: Mapping[str, str], + *, + config: Path | None = None, + remove_environment: tuple[str, ...] = (), +) -> Iterator[Gateway]: + with owned_proxy_process( + gateway, directory, overrides, config=config, remove_environment=remove_environment + ) as owned: + yield owned.gateway + + +@contextmanager +def owned_proxy_process( + gateway: Gateway, + directory: Path, + overrides: Mapping[str, str], + *, + config: Path | None = None, + remove_environment: tuple[str, ...] = (), +) -> Iterator[OwnedProxy]: with socket.socket() as reserve: reserve.bind(("127.0.0.1", 0)) port: Final = reserve.getsockname()[1] @@ -60,7 +90,8 @@ def owned_proxy(gateway: Gateway, directory: Path, overrides: Mapping[str, str], } output: Final = Path(os.environ.get("INTEGRATION_RESULTS_DIR", str(directory))) output.mkdir(parents=True, exist_ok=True) - with (output / f"owned-proxy-{uuid.uuid4().hex}.log").open("w") as log: + log_path: Final = output / f"owned-proxy-{uuid.uuid4().hex}.log" + with log_path.open("w") as log: process: Final = subprocess.Popen( [ sys.executable, @@ -95,7 +126,7 @@ def owned_proxy(gateway: Gateway, directory: Path, overrides: Mapping[str, str], pass assert time.monotonic() < deadline, "Owned proxy readiness deadline exceeded" time.sleep(0.1) - yield Gateway(client, gateway.key, gateway.upstream_url) + yield OwnedProxy(Gateway(client, gateway.key, gateway.upstream_url), process, log_path) finally: root_stopped: Final = stop_root_process(process) residual: Final = group_members(process.pid) diff --git a/tests/integration/contracts.json b/tests/integration/contracts.json index 8c4ce4debbc..cfe31e2d8ec 100644 --- a/tests/integration/contracts.json +++ b/tests/integration/contracts.json @@ -281,6 +281,12 @@ "tests/integration/spend/test_filtered_ledger.py::test_rotated_keys_users_and_model_groups_preserve_success_failure_cache_ledger": [ "quota_management.spend_tracking.filtered_ledger_preserves_owner_identity_and_totals" ], + "tests/integration/spend/test_shutdown_flush.py::test_daily_spend_batch_cancelled_while_waiting_for_a_pool_connection_is_written_by_the_final_flush": [ + "quota_management.spend_tracking.shutdown_cancel_keeps_in_flight_daily_batch" + ], + "tests/integration/spend/test_shutdown_flush.py::test_daily_spend_batch_cancelled_while_waiting_for_a_row_lock_is_written_exactly_once": [ + "quota_management.spend_tracking.shutdown_cancel_keeps_in_flight_daily_batch" + ], "tests/integration/spend/test_spend_calculate.py::test_spend_calculate_rejects_unpriced_model_with_400": [ "quota_management.spend_tracking.spend_calculate.rejects_unpriced_model" ], diff --git a/tests/integration/spend/test_shutdown_flush.py b/tests/integration/spend/test_shutdown_flush.py new file mode 100644 index 00000000000..d27275f5213 --- /dev/null +++ b/tests/integration/spend/test_shutdown_flush.py @@ -0,0 +1,189 @@ +import json +import os +import signal +import threading +import uuid +from collections.abc import Callable, Iterator +from contextlib import contextmanager +from dataclasses import dataclass +from pathlib import Path +from typing import Final + +import httpx +import psycopg +import pytest +import yaml + +from integration._support.client import Gateway, delete_key_if_present, eventually, string_value +from integration._support.database import read_rows +from integration._support.process import OwnedProxy, owned_proxy_process +from integration._support.wire import Reply, Request, wire_server + +REQUESTS_WHILE_BLOCKED: Final = 6 +CANCEL_LOG_LINE: Final = "in-flight scheduled job(s) for shutdown" +BATCH_DRAINED_LOG_LINE: Final = f"flushed {REQUESTS_WHILE_BLOCKED} daily spend update items from in-memory queue" +MODEL_INSERT_ARRIVED_LOG_LINE: Final = "path=/model/new" + + +def _api_requests(table: str, column: str, identity: str) -> int: + rows: Final = read_rows( + f'SELECT coalesce(sum(api_requests), 0)::int AS total FROM "{table}" WHERE {column}=%s', (identity,) + ) + total: Final = rows[0]["total"] + assert isinstance(total, int) + return total + + +def _waiting_on(table: str) -> int: + rows: Final = read_rows( + "SELECT count(*)::int AS waiting FROM pg_stat_activity WHERE wait_event_type='Lock' AND query LIKE %s", + (f'%"{table}"%',), + ) + waiting: Final = rows[0]["waiting"] + assert isinstance(waiting, int) + return waiting + + +def _provider(request: Request) -> Reply: + if request.method != "POST": + return Reply(status=404, body=b'{"error":"not scripted"}') + assert request.target == "/v1/chat/completions" + return Reply( + body=json.dumps( + { + "id": "chatcmpl-" + uuid.uuid4().hex, + "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}, + } + ).encode() + ) + + +@dataclass(frozen=True, slots=True) +class _Shutdown: + owner: str + team: str + owned: OwnedProxy + key: str + model: str + + def chat(self) -> None: + body: Final = {"model": self.model, "messages": [{"role": "user", "content": f"spend {uuid.uuid4().hex}"}]} + assert self.owned.gateway.request("POST", "/v1/chat/completions", body, key=self.key).status_code == 200 + + def daily_user_requests(self) -> int: + return _api_requests("LiteLLM_DailyUserSpend", "user_id", self.owner) + + def logged(self, line: str, times: int = 1) -> bool: + return self.owned.log.read_text(errors="replace").count(line) >= times + + def chat_while_spend_update_is_blocked(self, blocker: psycopg.Connection, table: str) -> None: + blocker.execute(f'LOCK TABLE "{table}" IN EXCLUSIVE MODE') + for _ in range(REQUESTS_WHILE_BLOCKED): + self.chat() + eventually(lambda: _waiting_on(table), lambda waiting: waiting == 1, seconds=30) + + def start_blocked_model_insert(self) -> threading.Thread: + body: Final = { + "model_name": f"integration-blocked-{uuid.uuid4().hex}", + "litellm_params": {"model": "openai/gpt-4o-mini", "api_key": "integration-provider-key"}, + "model_info": {}, + } + + def insert() -> None: + try: + self.owned.gateway.request("POST", "/model/new", body) + except httpx.TransportError: + pass + + thread: Final = threading.Thread(target=insert, daemon=True) + thread.start() + return thread + + def terminate_once(self, blocked: Callable[[], bool], release: Callable[[], None]) -> None: + eventually(blocked, lambda state: state, seconds=60) + self.owned.process.send_signal(signal.SIGTERM) + eventually(lambda: self.logged(CANCEL_LOG_LINE), lambda seen: seen, seconds=60) + release() + self.owned.process.wait(timeout=120) + + +def _config_with_pool_limit(tmp_path: Path, pool_limit: int) -> Path: + config: Final = yaml.safe_load(Path("tests/integration/proxy_config.yaml").read_text()) + config["general_settings"]["database_connection_pool_limit"] = pool_limit + config["general_settings"]["database_connection_pool_timeout"] = 60 + path: Final = tmp_path / f"pool-{pool_limit}.yaml" + path.write_text(yaml.safe_dump(config)) + return path + + +@contextmanager +def _proxy_with_one_seeded_row(gateway: Gateway, tmp_path: Path, pool_limit: int) -> Iterator[_Shutdown]: + owner: Final = f"integration-owner-{uuid.uuid4().hex}" + with gateway.scenario() as scenario, wire_server(_provider) as wire: + model: Final = scenario.model(api_base=wire.url + "/v1", num_retries=0) + team: Final = scenario.team(models=[model]) + with owned_proxy_process( + gateway, + tmp_path, + { + "LITELLM_LOG": "DEBUG", + "GRACEFUL_SHUTDOWN_TIMEOUT": "1", + "SCHEDULED_JOB_SHUTDOWN_FINISH_TIMEOUT_SECONDS": "1", + "SCHEDULED_JOB_SHUTDOWN_CANCEL_TIMEOUT_SECONDS": "5", + }, + config=_config_with_pool_limit(tmp_path, pool_limit), + ) as owned: + key: Final = string_value( + owned.gateway.post("/key/generate", {"user_id": owner, "team_id": team, "models": [model]})["key"] + ) + scenario.cleanups.callback(delete_key_if_present, gateway, key) + shutdown: Final = _Shutdown(owner, team, owned, key, model) + shutdown.chat() + eventually(shutdown.daily_user_requests, lambda total: total == 1, seconds=60) + yield shutdown + assert _api_requests("LiteLLM_DailyUserSpend", "user_id", owner) == 1 + REQUESTS_WHILE_BLOCKED + assert _api_requests("LiteLLM_DailyTeamSpend", "team_id", team) == 1 + REQUESTS_WHILE_BLOCKED + + +@pytest.mark.covers("quota_management.spend_tracking.shutdown_cancel_keeps_in_flight_daily_batch") +def test_daily_spend_batch_cancelled_while_waiting_for_a_pool_connection_is_written_by_the_final_flush( + gateway: Gateway, tmp_path: Path +) -> None: + with ( + _proxy_with_one_seeded_row(gateway, tmp_path, pool_limit=2) as shutdown, + psycopg.connect(os.environ["DATABASE_URL"]) as models, + psycopg.connect(os.environ["DATABASE_URL"]) as memberships, + ): + models.execute('LOCK TABLE "LiteLLM_ProxyModelTable" IN EXCLUSIVE MODE') + first: Final = shutdown.start_blocked_model_insert() + eventually(lambda: _waiting_on("LiteLLM_ProxyModelTable"), lambda waiting: waiting == 1, seconds=30) + shutdown.chat_while_spend_update_is_blocked(memberships, "LiteLLM_TeamMembership") + second: Final = shutdown.start_blocked_model_insert() + eventually(lambda: shutdown.logged(MODEL_INSERT_ARRIVED_LOG_LINE, times=2), lambda seen: seen, seconds=30) + memberships.rollback() + eventually(lambda: _waiting_on("LiteLLM_ProxyModelTable"), lambda waiting: waiting == 2, seconds=30) + shutdown.terminate_once(lambda: shutdown.logged(BATCH_DRAINED_LOG_LINE), models.rollback) + first.join(timeout=30) + second.join(timeout=30) + + +@pytest.mark.covers("quota_management.spend_tracking.shutdown_cancel_keeps_in_flight_daily_batch") +def test_daily_spend_batch_cancelled_while_waiting_for_a_row_lock_is_written_exactly_once( + gateway: Gateway, tmp_path: Path +) -> None: + with ( + _proxy_with_one_seeded_row(gateway, tmp_path, pool_limit=10) as shutdown, + psycopg.connect(os.environ["DATABASE_URL"]) as holder, + psycopg.connect(os.environ["DATABASE_URL"]) as memberships, + ): + holder.execute('SELECT 1 FROM "LiteLLM_DailyUserSpend" WHERE user_id=%s FOR UPDATE', (shutdown.owner,)) + shutdown.chat_while_spend_update_is_blocked(memberships, "LiteLLM_TeamMembership") + memberships.rollback() + shutdown.terminate_once( + lambda: shutdown.logged(BATCH_DRAINED_LOG_LINE) and _waiting_on("LiteLLM_DailyUserSpend") == 1, + holder.rollback, + ) diff --git a/tests/proxy_unit_tests/test_update_daily_tag_spend.py b/tests/proxy_unit_tests/test_update_daily_tag_spend.py index 35e9c6796eb..530c0d16767 100644 --- a/tests/proxy_unit_tests/test_update_daily_tag_spend.py +++ b/tests/proxy_unit_tests/test_update_daily_tag_spend.py @@ -100,6 +100,7 @@ async def test_daily_tag_spend_retries_then_succeeds(): 1, ] ) + prisma_client.db.tx.return_value.__aenter__.return_value.execute_raw = prisma_client.db.execute_raw daily_spend_transactions: Dict[str, DailyTagSpendTransaction] = { "k": { diff --git a/tests/test_litellm/proxy/db/test_daily_spend_bulk_upsert.py b/tests/test_litellm/proxy/db/test_daily_spend_bulk_upsert.py index 510f77cecec..7893fb82281 100644 --- a/tests/test_litellm/proxy/db/test_daily_spend_bulk_upsert.py +++ b/tests/test_litellm/proxy/db/test_daily_spend_bulk_upsert.py @@ -1,6 +1,8 @@ """Tests for the single-statement daily spend upsert (LIT-5291).""" import re +from collections.abc import AsyncIterator +from contextlib import AbstractAsyncContextManager, asynccontextmanager import pytest @@ -149,6 +151,13 @@ class _RecordingDb: self.statements.append((query, args)) return len(args) + @asynccontextmanager + async def _tx(self) -> AsyncIterator["_RecordingDb"]: + yield self + + def tx(self, timeout: object = None) -> AbstractAsyncContextManager["_RecordingDb"]: + return self._tx() + class _RecordingPrismaClient: def __init__(self) -> None: diff --git a/tests/test_litellm/proxy/db/test_db_spend_update_writer.py b/tests/test_litellm/proxy/db/test_db_spend_update_writer.py index a997939ed34..daa07c8224a 100644 --- a/tests/test_litellm/proxy/db/test_db_spend_update_writer.py +++ b/tests/test_litellm/proxy/db/test_db_spend_update_writer.py @@ -5,11 +5,11 @@ import logging import re -from collections.abc import Callable -from contextlib import asynccontextmanager -from datetime import datetime, timezone +from collections.abc import AsyncIterator, Callable +from contextlib import AbstractAsyncContextManager, asynccontextmanager +from datetime import datetime, timedelta, timezone from types import SimpleNamespace -from typing import Final +from typing import Final, cast from unittest.mock import AsyncMock, MagicMock, call, patch import httpx @@ -20,7 +20,7 @@ from redis.exceptions import DataError import litellm from litellm._logging import verbose_proxy_logger -from litellm.proxy._types import Litellm_EntityType, SpendUpdateQueueItem +from litellm.proxy._types import DailyTagSpendTransaction, Litellm_EntityType, SpendUpdateQueueItem from litellm.proxy.db.db_spend_update_writer import ( _TEAM_ADVISORY_LOCK_SQL, _TEAM_MEMBER_SPEND_SQL, @@ -28,6 +28,8 @@ from litellm.proxy.db.db_spend_update_writer import ( _SpendTableName, _spend_tables_left_to_send, ) +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.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, @@ -303,6 +305,13 @@ class _RecordingDb: return self._execute_raw() return len(args) + @asynccontextmanager + async def _tx(self) -> AsyncIterator["_RecordingDb"]: + yield self + + def tx(self, timeout: timedelta | None = None) -> AbstractAsyncContextManager["_RecordingDb"]: + return self._tx() + class _RecordingPrisma: def __init__(self, execute_raw: Callable[[], int] | None = None) -> None: @@ -3770,8 +3779,15 @@ async def test_commit_spend_updates_does_not_retry_non_deadlock_data_error(monke @pytest.mark.asyncio async def test_update_daily_spend_retries_deadlock(monkeypatch): """The daily-spend upsert path retries a deadlock on the bulk upsert and then drains successfully.""" - mock_prisma_client = MagicMock() - mock_prisma_client.db.execute_raw = AsyncMock(side_effect=[_deadlock_error(), None]) + outcomes = iter([_deadlock_error(), None]) + + def first_attempt_deadlocks(): + outcome = next(outcomes) + if outcome is not None: + raise outcome + return 1 + + mock_prisma_client = _RecordingPrisma(execute_raw=first_attempt_deadlocks) proxy_logging = MagicMock() proxy_logging.failure_handler = AsyncMock() @@ -3786,7 +3802,7 @@ async def test_update_daily_spend_retries_deadlock(monkeypatch): entity_id_field="user_id", ) - assert mock_prisma_client.db.execute_raw.call_count == 2 + assert len(mock_prisma_client.db.statements) == 2 assert daily_spend_transactions == {} proxy_logging.failure_handler.assert_not_called() @@ -4247,3 +4263,241 @@ async def test_daily_transaction_attributes_caching_savings_only_with_an_injecti assert transaction["cache_creation_input_tokens"] == 1111 assert transaction["prompt_caching_savings_spend"] != 0.0 assert transaction["gateway_injected_caching_savings_spend"] == 0.0 + + +class _StallingDailySpendFakeDB(_DailySpendFakeDB): + """Holds the daily upsert aimed at one table until it is cancelled, like a starved pool does. + + The rollback of that transaction waits for ``rollback_release``: the query engine only + rolls back once the statement it is running has returned, which behind a lock takes + as long as the lock is held.""" + + def __init__(self, stalled_table: str) -> None: + super().__init__(failing_table=None) + self.stalled_table = stalled_table + self.stalled = asyncio.Event() + self.rollback_release = asyncio.Event() + self.rolled_back = asyncio.Event() + self.transaction_outcomes: list[str] = [] + + async def execute_raw(self, query: str, *args: object) -> int: + if self.stalled_table in query: + self.stalled.set() + await asyncio.Event().wait() + return await super().execute_raw(query, *args) + + @asynccontextmanager + async def _tx(self) -> AsyncIterator["_StallingDailySpendFakeDB"]: + try: + yield self + except BaseException: + await self.rollback_release.wait() + self.transaction_outcomes.append("rollback") + self.rolled_back.set() + raise + self.transaction_outcomes.append("commit") + + +def _daily_entity_txn(entity_id_field: str) -> dict: + return {key: value for key, value in _daily_txn().items() if key != "user_id"} | {entity_id_field: "entity-1"} + + +_DAILY_SPEND_ENTITIES: Final = [ + pytest.param("daily_spend_update_queue", "user", "user_id", "LiteLLM_DailyUserSpend", id="user"), + pytest.param("daily_team_spend_update_queue", "team", "team_id", "LiteLLM_DailyTeamSpend", id="team"), + pytest.param("daily_org_spend_update_queue", "org", "organization_id", "LiteLLM_DailyOrganizationSpend", id="org"), + pytest.param("daily_tag_spend_update_queue", "tag", "tag", "LiteLLM_DailyTagSpend", id="tag"), + pytest.param( + "daily_end_user_spend_update_queue", "end_user", "end_user_id", "LiteLLM_DailyEndUserSpend", id="end_user" + ), + pytest.param("daily_agent_spend_update_queue", "agent", "agent_id", "LiteLLM_DailyAgentSpend", id="agent"), +] + +_DAILY_SPEND_QUEUES: Final[dict[str, Callable[[DBSpendUpdateWriter], DailySpendUpdateQueue]]] = { + "daily_spend_update_queue": lambda writer: writer.daily_spend_update_queue, + "daily_team_spend_update_queue": lambda writer: writer.daily_team_spend_update_queue, + "daily_org_spend_update_queue": lambda writer: writer.daily_org_spend_update_queue, + "daily_tag_spend_update_queue": lambda writer: writer.daily_tag_spend_update_queue, + "daily_end_user_spend_update_queue": lambda writer: writer.daily_end_user_spend_update_queue, + "daily_agent_spend_update_queue": lambda writer: writer.daily_agent_spend_update_queue, +} + +_DAILY_SPEND_COMMITS: Final = { + "user": DBSpendUpdateWriter.update_daily_user_spend, + "team": DBSpendUpdateWriter.update_daily_team_spend, + "org": DBSpendUpdateWriter.update_daily_org_spend, + "tag": DBSpendUpdateWriter.update_daily_tag_spend, + "end_user": DBSpendUpdateWriter.update_daily_end_user_spend, + "agent": DBSpendUpdateWriter.update_daily_agent_spend, +} + + +@pytest.mark.parametrize(("queue_name", "entity_type", "entity_id_field", "table"), _DAILY_SPEND_ENTITIES) +@pytest.mark.asyncio +async def test_daily_spend_batch_cancelled_mid_flight_is_rolled_back_requeued_and_written_once_by_the_next_flush( + queue_name: str, entity_type: str, entity_id_field: str, table: str +): + """Shutdown cancels the scheduler tick while a drained batch waits on the database. The + batch has left the queue, so unless the cancellation puts it back, the final flush finds + nothing and the spend is gone (F2). The upsert runs in an interactive transaction so a + statement that did reach Postgres is rolled back with the cancel and the requeued rows + land exactly once.""" + db_writer = DBSpendUpdateWriter() + queue = _DAILY_SPEND_QUEUES[queue_name](db_writer) + await queue.add_update({"key-a": _daily_entity_txn(entity_id_field)}) + await queue.add_update({"key-a": _daily_entity_txn(entity_id_field)}) + db = _StallingDailySpendFakeDB(stalled_table=table) + proxy_logging_obj = MagicMock() + proxy_logging_obj.failure_handler = AsyncMock() + + def flush(prisma_db: _DailySpendFakeDB): + return db_writer._flush_daily_spend_queue( + queue=queue, + entity_type=entity_type, + commit=_DAILY_SPEND_COMMITS[entity_type], + n_retry_times=0, + prisma_client=_WindowSpendFakePrisma(prisma_db), + proxy_logging_obj=proxy_logging_obj, + ) + + tick = asyncio.ensure_future(flush(db)) + await asyncio.wait_for(db.stalled.wait(), timeout=5) + tick.cancel() + finished, _ = await asyncio.wait({tick}, timeout=1) + assert finished == {tick}, "the cancelled tick must return before the rolled-back statement unwinds" + with pytest.raises(asyncio.CancelledError): + tick.result() + + assert not queue.update_queue.empty(), "the cancelled batch must go back on the queue before the rollback lands" + assert db.transaction_outcomes == [] + db.rollback_release.set() + await asyncio.wait_for(db.rolled_back.wait(), timeout=5) + assert db.transaction_outcomes == ["rollback"] + assert _daily_upserts(db, table) == [] + + final_db = _DailySpendFakeDB(failing_table=None) + await flush(final_db) + + (upsert,) = _daily_upserts(final_db, table) + assert _row_values(upsert, entity_id_field) == ["entity-1"] + assert _row_values(upsert, "spend") == [pytest.approx(0.2)] + assert _row_values(upsert, "api_requests") == [2] + assert queue.update_queue.empty() + + +@pytest.mark.asyncio +async def test_cancelled_flush_of_an_empty_daily_queue_requeues_nothing(): + """A cancel that lands with nothing drained must not push an empty batch onto the queue.""" + db_writer = DBSpendUpdateWriter() + db = _StallingDailySpendFakeDB(stalled_table="LiteLLM_DailyUserSpend") + + class _CancellingQueue(type(db_writer.daily_spend_update_queue)): + async def flush_and_get_aggregated_daily_spend_update_transactions(self): + drained = await super().flush_and_get_aggregated_daily_spend_update_transactions() + asyncio.current_task().cancel() + await asyncio.sleep(0) + return drained + + queue = _CancellingQueue() + with pytest.raises(asyncio.CancelledError): + await db_writer._flush_daily_spend_queue( + queue=queue, + entity_type="user", + commit=DBSpendUpdateWriter.update_daily_user_spend, + n_retry_times=0, + prisma_client=_WindowSpendFakePrisma(db), + proxy_logging_obj=MagicMock(), + ) + + assert queue.update_queue.empty() + + +class _AnnouncingDailySpendFakeDB(_DailySpendFakeDB): + """Signals ``written`` the moment the daily upsert has been committed.""" + + def __init__(self) -> None: + super().__init__(failing_table=None) + self.written = asyncio.Event() + + async def execute_raw(self, query: str, *args: object) -> int: + rows = await super().execute_raw(query, *args) + self.written.set() + return rows + + +@pytest.mark.asyncio +async def test_cancel_that_lands_after_the_daily_batch_committed_does_not_requeue_it(): + """The commit has returned but the tick has not resumed yet when the cancel arrives. + Putting the batch back now would write the same spend twice on the final flush.""" + db_writer = DBSpendUpdateWriter() + queue = db_writer.daily_spend_update_queue + await queue.add_update({"key-a": _daily_txn()}) + db = _AnnouncingDailySpendFakeDB() + + tick = asyncio.ensure_future( + db_writer._flush_daily_spend_queue( + queue=queue, + entity_type="user", + commit=DBSpendUpdateWriter.update_daily_user_spend, + n_retry_times=0, + prisma_client=_WindowSpendFakePrisma(db), + proxy_logging_obj=MagicMock(), + ) + ) + await db.written.wait() + tick.cancel() + with pytest.raises(asyncio.CancelledError): + await tick + + assert len(_daily_upserts(db, "LiteLLM_DailyUserSpend")) == 1 + assert queue.update_queue.empty(), "a batch that already committed must not be requeued" + + +class _DrainedTagRedisBuffer: + """Hands out one drained tag batch and records whatever is restored.""" + + def __init__(self, drained: dict[str, DailyTagSpendTransaction]) -> None: + self.drained = drained + self.restored: list[dict[str, DailyTagSpendTransaction]] = [] + + async def get_all_daily_tag_spend_update_transactions_from_redis_buffer( + self, + ) -> dict[str, DailyTagSpendTransaction]: + return self.drained + + async def restore_transactions_to_redis( + self, daily_tag_spend_update_transactions: dict[str, DailyTagSpendTransaction] + ) -> None: + self.restored.append(daily_tag_spend_update_transactions) + + +@pytest.mark.asyncio +async def test_tag_batch_drained_from_redis_and_cancelled_mid_flight_is_restored_before_its_rollback_returns(): + """The Redis tag drain is destructive. A shutdown cancel used to leave the batch nowhere: + Redis no longer had it and the interactive transaction rolled the statement back.""" + db_writer = DBSpendUpdateWriter() + drained = {"key-a": cast(DailyTagSpendTransaction, _daily_entity_txn("tag"))} + redis_buffer = _DrainedTagRedisBuffer(drained) + db_writer.redis_update_buffer = cast(RedisUpdateBuffer, redis_buffer) + db = _StallingDailySpendFakeDB(stalled_table="LiteLLM_DailyTagSpend") + + tick = asyncio.ensure_future( + db_writer._drain_and_commit_daily_tag_spend_from_redis( + prisma_client=_WindowSpendFakePrisma(db), + n_retry_times=0, + proxy_logging_obj=MagicMock(), + ) + ) + await asyncio.wait_for(db.stalled.wait(), timeout=5) + tick.cancel() + finished, _ = await asyncio.wait({tick}, timeout=1) + assert finished == {tick}, "the cancelled drain must return before the rolled-back statement unwinds" + with pytest.raises(asyncio.CancelledError): + tick.result() + + assert redis_buffer.restored == [drained], "the drained tag batch must be back in Redis before the rollback lands" + assert db.transaction_outcomes == [] + db.rollback_release.set() + await asyncio.wait_for(db.rolled_back.wait(), timeout=5) + assert db.transaction_outcomes == ["rollback"] + assert _daily_upserts(db, "LiteLLM_DailyTagSpend") == [] From 944f44d82be735616448f92b534dee1f063008b7 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 22 Sep 2026 17:59:50 -0700 Subject: [PATCH 068/101] fix(utils): isolate callback errors in async_post_call_success_deployment_hook (#42535) * fix(utils): isolate callback errors in async_post_call_success_deployment_hook A callback that raises inside async_post_call_success_deployment_hook no longer fails the completed request. The exception is logged with the callback class and call_type, the response stays as it was, and later callbacks still run. Guardrail callbacks are exempt because raising is how a post-call guardrail blocks Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(utils): drop unrelated ruff autofixes from test_utils Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(utils): drop fastapi import from guardrail propagation regression Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(utils): cover every success deployment hook call type with a raising hook Parametrize the unit regression over video, embedding, responses, image, rerank, transcription, chat and anthropic messages responses and assert the failure log names the callback and call type. Run the integration test through a real proxy for /v1/chat/completions, /v1/embeddings, /v1/responses and /v1/videos Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(integration): move raising success hook cases into the existing callback delivery file Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: yucheng Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- litellm/utils.py | 17 +- tests/integration/contracts.json | 12 ++ .../observability/test_callback_delivery.py | 166 +++++++++++++++++- tests/test_litellm/test_utils.py | 113 ++++++++++++ 4 files changed, 303 insertions(+), 5 deletions(-) diff --git a/litellm/utils.py b/litellm/utils.py index 01f6fee3594..dd35c17809f 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -1440,11 +1440,22 @@ async def async_post_call_success_deployment_hook( modified_response = response CustomLogger: Final = _get_cached_custom_logger() + CustomGuardrail: Final = _get_cached_custom_guardrail() for callback in litellm.callbacks: if isinstance(callback, CustomLogger): - result = await callback.async_post_call_success_deployment_hook( - request_data, cast(LLMResponseTypes, modified_response), typed_call_type - ) + try: + result = await callback.async_post_call_success_deployment_hook( + request_data, cast(LLMResponseTypes, modified_response), typed_call_type + ) + except Exception: # noqa: BLE001 # a broken callback must not fail a completed request + if isinstance(callback, CustomGuardrail): + raise + verbose_logger.exception( + "async_post_call_success_deployment_hook error in %s for call_type=%s", + type(callback).__name__, + typed_call_type, + ) + continue if result is not None: modified_response = result diff --git a/tests/integration/contracts.json b/tests/integration/contracts.json index cfe31e2d8ec..ee9b81f63dc 100644 --- a/tests/integration/contracts.json +++ b/tests/integration/contracts.json @@ -1782,6 +1782,18 @@ ], "tests/integration/mcp/test_mcp_lifecycle.py::test_same_url_server_grants_scope_discovery_and_direct_or_virtual_execution[bearer]": [ "other.mcp.permissions.same_url_servers_enforce_discovery_and_execution" + ], + "tests/integration/observability/test_callback_delivery.py::test_response_survives_raising_success_deployment_hook[chat]": [ + "other.observability.callbacks.raising_success_deployment_hook_keeps_response" + ], + "tests/integration/observability/test_callback_delivery.py::test_response_survives_raising_success_deployment_hook[embeddings]": [ + "other.observability.callbacks.raising_success_deployment_hook_keeps_response" + ], + "tests/integration/observability/test_callback_delivery.py::test_response_survives_raising_success_deployment_hook[responses]": [ + "other.observability.callbacks.raising_success_deployment_hook_keeps_response" + ], + "tests/integration/observability/test_callback_delivery.py::test_response_survives_raising_success_deployment_hook[videos]": [ + "other.observability.callbacks.raising_success_deployment_hook_keeps_response" ] }, "browser": { diff --git a/tests/integration/observability/test_callback_delivery.py b/tests/integration/observability/test_callback_delivery.py index c44c1f30b80..7a5f420d2cc 100644 --- a/tests/integration/observability/test_callback_delivery.py +++ b/tests/integration/observability/test_callback_delivery.py @@ -1,13 +1,15 @@ +import base64 import json import uuid +from collections.abc import Callable, Mapping from concurrent.futures import ThreadPoolExecutor +from dataclasses import dataclass from pathlib import Path from typing import Final import pytest import yaml - -from integration._support.client import Gateway, eventually +from integration._support.client import Gateway, JsonValue, 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_server @@ -152,3 +154,163 @@ def test_concurrent_success_and_failure_join_callbacks_and_rows_without_credenti assert rows[0]["prompt_tokens"] == event["prompt_tokens"] else: assert event["prompt_tokens"] == event["completion_tokens"] == rows[0]["completion_tokens"] == 0 + + +_RAISING_HOOK: Final = """ +from litellm.integrations.custom_logger import CustomLogger + + +class RaisingHook(CustomLogger): + async def async_post_call_success_deployment_hook(self, request_data, response, call_type): + raise RuntimeError(f"hook rejected {type(response).__name__} for {call_type}") + + +instance = RaisingHook() +""" + +_VIDEO_JOB: Final = { + "id": "video_hook_isolation", + "object": "video", + "status": "queued", + "model": "sora-2", + "seconds": "4", + "size": "720x1280", +} + +_UPSTREAM_REPLIES: Final[Mapping[str, Mapping[str, JsonValue]]] = { + "/v1/chat/completions": { + "id": "chatcmpl_hook_isolation", + "object": "chat.completion", + "created": 1, + "model": "gpt-5.6", + "choices": [{"index": 0, "message": {"role": "assistant", "content": "hi"}, "finish_reason": "stop"}], + "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2}, + }, + "/v1/embeddings": { + "object": "list", + "data": [{"object": "embedding", "index": 0, "embedding": [0.1, 0.2]}], + "model": "text-embedding-3-small", + "usage": {"prompt_tokens": 1, "total_tokens": 1}, + }, + "/v1/responses": { + "id": "resp_hook_isolation", + "object": "response", + "created_at": 1, + "status": "completed", + "model": "gpt-5.6", + "output": [ + { + "type": "message", + "id": "msg_hook_isolation", + "status": "completed", + "role": "assistant", + "content": [{"type": "output_text", "text": "hi", "annotations": []}], + } + ], + "parallel_tool_calls": False, + "tool_choice": "auto", + "tools": [], + "usage": {"input_tokens": 1, "output_tokens": 1, "total_tokens": 2}, + }, + "/v1/videos": _VIDEO_JOB, +} + + +def _item(value: JsonValue, index: int) -> JsonValue: + assert isinstance(value, list), f"Expected a list, received {type(value).__name__}" + return value[index] + + +def _chat_text(body: dict[str, JsonValue]) -> str: + return string_value(object_value(object_value(_item(body["choices"], 0))["message"])["content"]) + + +def _embedding_vector(body: dict[str, JsonValue]) -> JsonValue: + return object_value(_item(body["data"], 0))["embedding"] + + +def _responses_text(body: dict[str, JsonValue]) -> str: + return string_value(object_value(_item(object_value(_item(body["output"], 0))["content"], 0))["text"]) + + +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"]) + + +@dataclass(frozen=True, slots=True) +class _Surface: + route: str + upstream_model: str + body: Callable[[str], dict[str, JsonValue]] + observed: Callable[[dict[str, JsonValue]], JsonValue | tuple[str, str]] + expected: JsonValue | tuple[str, str] + + +_SURFACES: Final = ( + pytest.param( + _Surface( + "/v1/chat/completions", + "openai/gpt-5.6", + lambda model: {"model": model, "messages": [{"role": "user", "content": "hook isolation"}]}, + _chat_text, + "hi", + ), + id="chat", + ), + pytest.param( + _Surface( + "/v1/embeddings", + "openai/text-embedding-3-small", + lambda model: {"model": model, "input": "hook isolation"}, + _embedding_vector, + [0.1, 0.2], + ), + id="embeddings", + ), + pytest.param( + _Surface( + "/v1/responses", + "openai/gpt-5.6", + lambda model: {"model": model, "input": "hook isolation"}, + _responses_text, + "hi", + ), + id="responses", + ), + pytest.param( + _Surface( + "/v1/videos", + "openai/sora-2", + lambda model: {"model": model, "prompt": "a cat"}, + _video_job, + (_VIDEO_JOB["id"], _VIDEO_JOB["status"]), + ), + id="videos", + ), +) + + +@pytest.mark.covers("other.observability.callbacks.raising_success_deployment_hook_keeps_response") +@pytest.mark.parametrize("surface", _SURFACES) +def test_response_survives_raising_success_deployment_hook(gateway: Gateway, tmp_path: Path, surface: _Surface) -> None: + def upstream(request: Request) -> Reply: + assert request.target == surface.route, request.target + assert b"hook isolation" in request.body or b"a cat" in request.body, request.body[:300] + return Reply(body=json.dumps(_UPSTREAM_REPLIES[surface.route]).encode()) + + (tmp_path / "raising_hook.py").write_text(_RAISING_HOOK) + config: Final = yaml.safe_load(Path("tests/integration/proxy_config.yaml").read_text()) + config["litellm_settings"].update({"callbacks": ["raising_hook.instance"]}) + path: Final = tmp_path / "hook.yaml" + path.write_text(yaml.safe_dump(config)) + with ( + wire_server(upstream) as provider, + owned_proxy(gateway, tmp_path, {}, config=path) as candidate, + candidate.scenario() as scenario, + ): + model: Final = scenario.model(model=surface.upstream_model, api_base=provider.url + "/v1") + response: Final = candidate.request("POST", surface.route, surface.body(model)) + assert response.status_code == 200, response.text + assert surface.observed(object_value(response.json())) == surface.expected, response.text diff --git a/tests/test_litellm/test_utils.py b/tests/test_litellm/test_utils.py index 283cff97ce0..89472cbd20f 100644 --- a/tests/test_litellm/test_utils.py +++ b/tests/test_litellm/test_utils.py @@ -32,27 +32,35 @@ from litellm._logging import ( from litellm.caching.caching import Cache from litellm.caching.caching_handler import _PENDING_CACHE_WRITES from litellm.constants import DEFAULT_MOCK_RESPONSE_COMPLETION_TOKEN_COUNT +from litellm.integrations.custom_guardrail import CustomGuardrail from litellm.integrations.custom_logger import CustomLogger from litellm.litellm_core_utils.get_litellm_params import get_litellm_params from litellm.litellm_core_utils.thread_pool_executor import executor as logging_executor from litellm.llms.base_llm.base_model_iterator import MockResponseIterator from litellm.proxy.utils import is_valid_api_key from litellm.types.integrations.custom_logger import HEADROOM_CONVERTED_STREAM_KEY +from litellm.types.llms.openai import ResponsesAPIResponse from litellm.types.router import CredentialLiteLLMParams, GenericLiteLLMParams from litellm.types.utils import ( ADDRESSED_RESPONSE_ID_FIELD, CallTypes, Choices, Delta, + EmbeddingResponse, + ImageResponse, LlmProviders, + LLMResponseTypes, ModelResponse, ModelResponseStream, PromptTokensDetailsWrapper, + RerankResponse, StreamingChoices, + TranscriptionResponse, Usage, all_litellm_params, bedrock_batch_litellm_params, ) +from litellm.types.videos.main import VideoObject from litellm.utils import ( CustomStreamWrapper, ProviderConfigManager, @@ -4412,6 +4420,111 @@ async def test_converted_chat_stream_hook_skips_unhandled_wrappers( assert wrapper.completion_stream is completion_stream +class _ChatShapedSuccessDeploymentHook(CustomLogger): + async def async_post_call_success_deployment_hook( + self, request_data: dict[str, object], response: object, call_type: CallTypes | None + ) -> None: + raise AttributeError(f"{type(response).__name__!r} object has no attribute 'choices'") + + +class _RecordingSuccessDeploymentHook(CustomLogger): + def __init__(self) -> None: + super().__init__() + self.seen_responses: tuple[object, ...] = () + + async def async_post_call_success_deployment_hook( + self, request_data: dict[str, object], response: object, call_type: CallTypes | None + ) -> None: + self.seen_responses = (*self.seen_responses, response) + + +_SUCCESS_RESPONSES_BY_CALL_TYPE: Final = ( + pytest.param( + VideoObject(id="video_abc", object="video", status="queued", model="sora-2", seconds="4", size="720x1280"), + CallTypes.avideo_generation, + id="video", + ), + pytest.param(EmbeddingResponse(model="text-embedding-3-small"), CallTypes.aembedding, id="embedding"), + pytest.param( + ResponsesAPIResponse( + id="resp_abc", created_at=1, output=[], parallel_tool_calls=False, tool_choice="auto", tools=[], model="gpt-5.6" + ), + CallTypes.aresponses, + id="responses", + ), + pytest.param(ImageResponse(), CallTypes.aimage_generation, id="image"), + pytest.param(RerankResponse(id="rerank_abc"), CallTypes.arerank, id="rerank"), + pytest.param(TranscriptionResponse(text="hi"), CallTypes.atranscription, id="transcription"), + pytest.param(ModelResponse(model="gpt-5.6"), CallTypes.acompletion, id="chat"), + pytest.param(ModelResponse(model="claude-sonnet-4-5"), CallTypes.aanthropic_messages, id="anthropic_messages"), +) + + +@pytest.mark.asyncio +@pytest.mark.parametrize(("response", "call_type"), _SUCCESS_RESPONSES_BY_CALL_TYPE) +async def test_success_deployment_hook_raising_keeps_response_and_runs_later_hooks( + monkeypatch: pytest.MonkeyPatch, caplog: pytest.LogCaptureFixture, response: object, call_type: CallTypes +) -> None: + second_hook: Final = _RecordingSuccessDeploymentHook() + monkeypatch.setattr(litellm, "callbacks", [_ChatShapedSuccessDeploymentHook(), second_hook]) + + with caplog.at_level(logging.ERROR, logger=verbose_logger.name): + result: Final = await async_post_call_success_deployment_hook( + request_data={"model": "m"}, response=response, call_type=call_type + ) + + assert result is response + assert second_hook.seen_responses == (response,) + failure_logs: Final = tuple(r for r in caplog.records if "async_post_call_success_deployment_hook error" in r.message) + assert len(failure_logs) == 1 + assert "_ChatShapedSuccessDeploymentHook" in failure_logs[0].message + assert str(call_type) in failure_logs[0].message + assert failure_logs[0].exc_info is not None + + +@pytest.mark.asyncio +async def test_success_deployment_hook_raising_keeps_earlier_hook_rewrite(monkeypatch: pytest.MonkeyPatch) -> None: + rewriter: Final = _RewritingSuccessDeploymentHook() + trailing_hook: Final = _RecordingSuccessDeploymentHook() + monkeypatch.setattr(litellm, "callbacks", [rewriter, _ChatShapedSuccessDeploymentHook(), trailing_hook]) + original: Final = ModelResponse(model="gpt-5.6") + + result: Final = await async_post_call_success_deployment_hook( + request_data={"model": "gpt-5.6"}, response=original, call_type=CallTypes.acompletion + ) + + assert isinstance(result, ModelResponse) + assert result is not original + assert result.choices[0].message.content == "rewritten by deployment hook" + assert trailing_hook.seen_responses == (result,) + + +class _GuardrailBlocked(Exception): + pass + + +class _BlockingSuccessDeploymentGuardrail(CustomGuardrail): + async def async_post_call_success_deployment_hook( + self, request_data: dict, response: LLMResponseTypes, call_type: CallTypes | None + ) -> LLMResponseTypes | None: + raise _GuardrailBlocked("Violated moderation policy") + + +@pytest.mark.asyncio +async def test_success_deployment_hook_still_propagates_guardrail_block(monkeypatch: pytest.MonkeyPatch) -> None: + later_hook: Final = _RewritingSuccessDeploymentHook() + monkeypatch.setattr( + litellm, "callbacks", [_BlockingSuccessDeploymentGuardrail(guardrail_name="blocking"), later_hook] + ) + + with pytest.raises(_GuardrailBlocked): + await async_post_call_success_deployment_hook( + request_data={"model": "gpt-5.6"}, response=ModelResponse(model="gpt-5.6"), call_type=CallTypes.acompletion + ) + + assert later_hook.seen_responses == () + + @pytest.mark.asyncio @respx.mock async def test_wrapper_async_leaves_success_deployment_hook_off_requested_fake_stream( From 630c4624f6027c4c075aa91439702878690ece78 Mon Sep 17 00:00:00 2001 From: yujonglee Date: Tue, 22 Sep 2026 18:02:32 -0700 Subject: [PATCH 069/101] test(e2e): add secret manager lanes for HashiCorp Vault and CyberArk Conjur (#42503) * test(e2e): add a HashiCorp Vault secret manager lane key_management_system had no end-to-end coverage: the Rust crates and the Python unit tests all run against mocked managers. This adds a secret_manager suite that drives a proxy configured with hashicorp_vault against a real Vault. The tests seed a fresh secret name per test with the runner's OPENAI_API_KEY and register a deployment pointing at os.environ/. The proxy's env never holds that name, so get_secret's os.environ fallback cannot mask a broken manager, and a bogus value in Vault must come back as the provider's 401. Virtual keys are checked written to and removed from Vault under prefix_for_stored_virtual_keys. The setting is global to the proxy, so the lane has its own config and the secret_manager_vault opt-in marker, and stays out of the per-PR selector. Co-Authored-By: Claude Opus 5 * test(e2e): make the secret manager suite backend-agnostic One marker and opt-in (secret_manager / E2E_SECRET_MANAGER=) pick the backend from secret_backends.BACKENDS. The tests reach the manager through a SecretStore protocol, and each backend contributes a secret_store_.py module, a registry entry, and gateway/secret_manager__ci_config.yml. requires_capability deselects tests a backend cannot support (CyberArk does not delete), and test_secret_backends.py checks every lane config against its backend without a live stack. Co-Authored-By: Claude Opus 5 * test(e2e): add a CyberArk Conjur secret manager lane Adds cyberark as the second secret_manager backend: a Conjur store over its REST API (policy-declared variables, raw-text values, policy-patch teardown), its lane config, and a registry entry without deletes_stored_keys, since the proxy's CyberArk delete answers not_supported and Conjur keeps the key. secret_manager/backend.sh up|down boots any backend in Docker and writes proxy.env and tests.env, so every lane runs the same way; the registry test checks the script boots exactly the registered backends. e2e_http gains send_text_external for APIs that speak raw text rather than JSON. Co-Authored-By: Claude Opus 5 * fix(e2e): give the secret manager suite a client with .proxy and address review The shared resources fixture reads client.proxy, so a bare ProxyClient errored every live test at setup. backend.sh now writes its env under a per-user directory with umask 077, the markerless unit tests are gone per tests/e2e/AGENTS.md, and routine comments are trimmed. Co-Authored-By: Claude Opus 5.5 --------- Co-authored-by: Claude Opus 5 --- .github/e2e-stack/select_tests.py | 1 + tests/e2e/AGENTS.md | 1 + tests/e2e/CONTRIBUTING.md | 27 +++- tests/e2e/conftest.py | 7 + tests/e2e/coverage_registry/other.yaml | 5 +- tests/e2e/e2e_config.py | 1 + tests/e2e/e2e_http.py | 30 +++- .../secret_manager_cyberark_ci_config.yml | 8 ++ ...cret_manager_hashicorp_vault_ci_config.yml | 8 ++ tests/e2e/pytest.ini | 1 + tests/e2e/secret_manager/backend.sh | 76 +++++++++++ tests/e2e/secret_manager/conftest.py | 57 ++++++++ tests/e2e/secret_manager/secret_backends.py | 25 ++++ tests/e2e/secret_manager/secret_store.py | 29 ++++ .../secret_manager/secret_store_cyberark.py | 118 ++++++++++++++++ .../secret_store_hashicorp_vault.py | 113 ++++++++++++++++ .../secret_manager/test_secret_manager_e2e.py | 128 ++++++++++++++++++ 17 files changed, 630 insertions(+), 5 deletions(-) create mode 100644 tests/e2e/gateway/secret_manager_cyberark_ci_config.yml create mode 100644 tests/e2e/gateway/secret_manager_hashicorp_vault_ci_config.yml create mode 100755 tests/e2e/secret_manager/backend.sh create mode 100644 tests/e2e/secret_manager/conftest.py create mode 100644 tests/e2e/secret_manager/secret_backends.py create mode 100644 tests/e2e/secret_manager/secret_store.py create mode 100644 tests/e2e/secret_manager/secret_store_cyberark.py create mode 100644 tests/e2e/secret_manager/secret_store_hashicorp_vault.py create mode 100644 tests/e2e/secret_manager/test_secret_manager_e2e.py diff --git a/.github/e2e-stack/select_tests.py b/.github/e2e-stack/select_tests.py index 492c52233cd..e425c313d6a 100644 --- a/.github/e2e-stack/select_tests.py +++ b/.github/e2e-stack/select_tests.py @@ -11,6 +11,7 @@ UNSUPPORTED: Final = re.compile( r"|^tests/e2e/guardrails/test_presidio_masking_e2e\.py$" r"|^tests/e2e/logging/test_otel_v2_langfuse_generation_output_e2e\.py$" r"|^tests/e2e/logging/test_langsmith_batch_serialization_e2e\.py$" + r"|^tests/e2e/secret_manager/" ) HARNESS: Final = re.compile( r"^tests/e2e/[A-Za-z0-9_.-]+\.(py|ini)$" diff --git a/tests/e2e/AGENTS.md b/tests/e2e/AGENTS.md index d948c6fd1d9..94035cfe849 100644 --- a/tests/e2e/AGENTS.md +++ b/tests/e2e/AGENTS.md @@ -46,6 +46,7 @@ Each subdirectory under `tests/e2e/` is one suite, scoped to an endpoint family - `router/` - routing and reliability behavior (fallbacks, cooldowns) plus the memory tests (`test_reliability_memory_e2e.py`: every worker's RSS as read at collection time, before any test traffic, must sit under a fixed idle budget, the release-gate check for a DB-backed boot that idles near the pod limit the way v1.100.x did; and a few hundred failing requests with retries and fallbacks must not grow proxy RSS past a fixed budget nor store a request snapshot past a fixed size, the release-gate check for the v1.100.0 retry-breadcrumb leak) - `load/` - performance-category tests, kept OUT of the main suite: throughput/load SLO tests are a different testing category from functional e2e (variance-driven, historically flaky) and live outside this suite until re-implemented as their own pipeline (LIT-5163); do not add a live load test that runs in the default collection. What lives here: the weekly session-anomaly test (`test_weekly_session_anomaly_e2e.py`, Claude Code-shaped multi-turn sessions against real providers with ceilings on error rate, cache read/write, turn time, and spend; marked `weekly` and deselected unless `E2E_WEEKLY_ANOMALY` is set, driven by `.github/workflows/weekly_load_anomaly.yml`), the Redis chaos test (`test_redis_chaos_e2e.py`, locust load against mock deployments split round robin over `/chat/completions` and `/v1/messages`, one endpoint per simulated user, with `CLIENT PAUSE ALL` on the proxy's Redis mid-run to simulate it being down outright, asserting zero failed requests on every endpoint, budgeting RSS and CPU-per-request as ratios against the same run's healthy phase, and holding p50/p90/p99 latency and log-bytes-per-request to flat ceilings (a ratio cannot bound those two: an open breaker skips Redis instead of waiting on it, so the chaos phase can measure cheaper than baseline while still being far slower than a user should see); needs a proxy booted from `gateway/redis_chaos_ci_config.yml` on the same host with `E2E_PROXY_PID` and `E2E_PROXY_LOG` set, marked `redis_chaos`, deselected unless `E2E_REDIS_CHAOS` is set and excluded from the per-PR selector like the rest of `load/`, driven by `.github/workflows/test-e2e-redis-chaos.yml` and by the Buildkite `e2e-redis-chaos` step in project-releaser, which runs the proxy, Postgres and Valkey co-located with pytest in one pod and sets the opt-in), and markerless harness unit tests for the locust, process-usage, and session-anomaly aggregation logic - `other/` - the holding-pen suite for the `other.*` registry cluster with no home of its own yet: the master-key auth gate, JWT auth (access tokens issued by a real Keycloak realm, `idp.py` plus `idp_realm.json`, whose JWKS the proxy's `JWT_PUBLIC_KEY_URL` points at; see CONTRIBUTING.md for the start command and config block), and the process-lifecycle health probes (liveness, public readiness, authenticated readiness diagnostics). Promote a cluster out once it is large/stable enough for its own suite +- `secret_manager/` - the gateway's `key_management_system` against a real secret manager: deployment keys resolved from it (`os.environ/` where the name exists only in the manager) and virtual keys written to and deleted from it. The tests are backend-agnostic and each backend is its own lane, because the setting is global to the proxy: `E2E_SECRET_MANAGER=` opts in and picks the backend from `secret_backends.BACKENDS`, the proxy is booted from `gateway/secret_manager__ci_config.yml` against the live manager, and the tests reach that manager through the backend's `SecretStore` (`secret_store_.py`). A test needing something not every backend does carries `requires_capability(...)` and is deselected on lanes that lack it. `secret_manager/backend.sh up ` runs a backend in Docker and writes the proxy's and the tests' env. Marked `secret_manager`, deselected unless `E2E_SECRET_MANAGER` is set, and kept out of the per-PR selector. Backends today: `hashicorp_vault` and `cyberark` (CyberArk Conjur, which cannot delete, so the delete test is Vault-only) - `gateway/` - proxy configuration only (`litellm-config.yml`); no tests - `claude_code/` - the Claude Code compatibility matrix: drives the real `claude` CLI (and HTTP probes) against a proxy for each feature x provider cell, reporting tagged-union outcomes via the `compat_result` fixture; ships its own driver/builder/publisher plus `_*_unit_tests/` trees. The HTTP probes ride the shared transport (`ProxyClient.count_tokens` / `ProxyClient.messages`); the CLI-driving path stays bespoke - `ui/` - the Admin UI browser suite: Playwright in TypeScript, driving the dashboard served by a live proxy on port 4000 (seeded postgres + mock LLM upstream; see its `run_e2e.sh`). It is a self-contained npm package with its own lockfile and does not use the Python harness, pytest markers, or the shared transport; the Python rules in this file (typed models, `Result` unions, basedpyright zero-error gate) do not apply inside it. Its only Python file, `fixtures/mock_llm_server/server.py`, is excluded from the e2e basedpyright gate via the root `pyrightconfig.json` diff --git a/tests/e2e/CONTRIBUTING.md b/tests/e2e/CONTRIBUTING.md index 15c2d6763d6..7e1f516422e 100644 --- a/tests/e2e/CONTRIBUTING.md +++ b/tests/e2e/CONTRIBUTING.md @@ -105,7 +105,7 @@ A couple of logging destinations are configured on the proxy rather than by the ### The pull request check -Every same-repository PR that adds, modifies, or renames a `tests/e2e/**/test_*.py` file runs those changed files three times. A change to the harness itself, meaning a root-level `tests/e2e/*.py` file or `pytest.ini`, `tests/e2e/gateway/`, `.github/e2e-stack/`, or the workflow, also runs the `access_control` suite and both JWT suites as canaries, because those files have no test of their own that exercises the stack. `.github/e2e-stack/select_tests.py` applies both rules. The stack config at `tests/e2e/gateway/stage_mirror_ci_config.yml` must declare every model the selected suites use; a missing one shows up as a failed test id in the public log. The suite's own single rerun for network errors and 5xx responses (see `pytest.ini`) applies on every pass, so a transport blip does not fail the check while a race inside a test still does. The stage-mirror stack has a control-plane backend, two gateways behind nginx, Postgres, Keycloak, Jaeger, and TLS cluster-mode Valkey. Realm-only edits also trigger these canaries. The stack exports every gateway address in `LITELLM_PROXY_REPLICA_URLS`, so model registration waits until each gateway lists the new model rather than whichever one the load balancer answered from. Documentation, deleted-file, and application-only changes do not start the stack or request environment approval. The `ui/`, `claude_code/`, and `load/` directories, `batches/test_managed_files_enforcement_e2e.py`, `llm_translation/realtime/test_realtime_pipecat_audio_e2e.py`, and `guardrails/test_presidio_masking_e2e.py` remain outside this check because they use separate tooling or need a differently configured stack: the pipecat audio suite skips itself at import time unless the NLTK `punkt_tab` data is installed, and the presidio suite fails without the analyzer and anonymizer services this stack does not start. `logging/test_otel_v2_langfuse_generation_output_e2e.py` is marked `otel_v2` and deselects itself unless `E2E_OTEL_V2` is set, because it needs a gateway booted with `LITELLM_OTEL_V2=true` and Langfuse credentials, neither of which this stack provides, so run it with `E2E_OTEL_V2=1` against a local OTel v2 proxy. The Redis chaos test under `load/` needs a proxy it can pause the Redis of on the same host (`gateway/redis_chaos_ci_config.yml`), which `.github/workflows/test-e2e-redis-chaos.yml` boots, and which the Buildkite `e2e-redis-chaos` step in project-releaser runs co-located with Postgres and Valkey in one pod; it is deselected unless `E2E_REDIS_CHAOS` is set +Every same-repository PR that adds, modifies, or renames a `tests/e2e/**/test_*.py` file runs those changed files three times. A change to the harness itself, meaning a root-level `tests/e2e/*.py` file or `pytest.ini`, `tests/e2e/gateway/`, `.github/e2e-stack/`, or the workflow, also runs the `access_control` suite and both JWT suites as canaries, because those files have no test of their own that exercises the stack. `.github/e2e-stack/select_tests.py` applies both rules. The stack config at `tests/e2e/gateway/stage_mirror_ci_config.yml` must declare every model the selected suites use; a missing one shows up as a failed test id in the public log. The suite's own single rerun for network errors and 5xx responses (see `pytest.ini`) applies on every pass, so a transport blip does not fail the check while a race inside a test still does. The stage-mirror stack has a control-plane backend, two gateways behind nginx, Postgres, Keycloak, Jaeger, and TLS cluster-mode Valkey. Realm-only edits also trigger these canaries. The stack exports every gateway address in `LITELLM_PROXY_REPLICA_URLS`, so model registration waits until each gateway lists the new model rather than whichever one the load balancer answered from. Documentation, deleted-file, and application-only changes do not start the stack or request environment approval. The `ui/`, `claude_code/`, `load/`, and `secret_manager/` directories, `batches/test_managed_files_enforcement_e2e.py`, `llm_translation/realtime/test_realtime_pipecat_audio_e2e.py`, and `guardrails/test_presidio_masking_e2e.py` remain outside this check because they use separate tooling or need a differently configured stack: the pipecat audio suite skips itself at import time unless the NLTK `punkt_tab` data is installed, and the presidio suite fails without the analyzer and anonymizer services this stack does not start. `logging/test_otel_v2_langfuse_generation_output_e2e.py` is marked `otel_v2` and deselects itself unless `E2E_OTEL_V2` is set, because it needs a gateway booted with `LITELLM_OTEL_V2=true` and Langfuse credentials, neither of which this stack provides, so run it with `E2E_OTEL_V2=1` against a local OTel v2 proxy. The Redis chaos test under `load/` needs a proxy it can pause the Redis of on the same host (`gateway/redis_chaos_ci_config.yml`), which `.github/workflows/test-e2e-redis-chaos.yml` boots, and which the Buildkite `e2e-redis-chaos` step in project-releaser runs co-located with Postgres and Valkey in one pod; it is deselected unless `E2E_REDIS_CHAOS` is set. The `secret_manager/` lanes each need a proxy configured against their own secret manager (see Secret manager lanes below) Every selected file must execute at least one passing test in each pass, and any test failure, collection error, or entirely skipped or deselected file fails the check. A file whose tests are all marked skip therefore cannot pass this check, so unskip at least one of them, or add the file to `UNSUPPORTED` in `select_tests.py` with the reason, before changing one. A failed pass stops the run. The public log prints pytest's one-line summary for each pass, including the rerun count, and names each failed or errored test as `classname::name`, so a retried network error or a failing test is visible without the raw output. The final `e2e-changed-tests` job succeeds only when no supported test files changed or the approved run completed all three passes. Fork PRs with selected tests fail this gate until a maintainer brings the reviewed change onto a same-repository branch @@ -117,6 +117,31 @@ Fetched values of eight characters or more are masked before use, while shorter To reproduce the CI topology on a dedicated machine, `bash .github/e2e-stack/up.sh` reads `tests/e2e/.env`, writes `stack.env` under `${E2E_STACK_DIR:-/tmp/litellm-e2e-stack}`, and `bash .github/e2e-stack/down.sh` stops it. Keep this directory private and remove its credential files and logs after use +### Secret manager lanes + +`key_management_system` is global to the proxy, so the `secret_manager/` tests run once per backend, each against its own proxy. The backends are `hashicorp_vault` and `cyberark` (CyberArk Conjur). `E2E_SECRET_MANAGER` opts in and names the backend (a key of `secret_backends.BACKENDS`). The proxy boots from `gateway/secret_manager__ci_config.yml`, and the tests reach the same manager through that backend's `SecretStore`. The managers are enterprise features, so the proxy needs a license. `secret_manager/backend.sh` runs any backend in Docker and writes its env, so every lane runs the same way locally: + +```bash +bash tests/e2e/secret_manager/backend.sh up cyberark +(set -a; . ~/.cache/litellm-e2e-secret-manager/cyberark/proxy.env; set +a; env -u OPENAI_API_KEY LITELLM_LICENSE=... \ + LITELLM_MASTER_KEY=sk-1234 DATABASE_URL=... uv run litellm --config tests/e2e/gateway/secret_manager_cyberark_ci_config.yml --port 4000) +(set -a; . ~/.cache/litellm-e2e-secret-manager/cyberark/tests.env; set +a; OPENAI_API_KEY=... \ + uv run --group e2e-dev pytest tests/e2e/secret_manager/ -v) +bash tests/e2e/secret_manager/backend.sh down cyberark +``` + +`E2E_SECRET_MANAGER_PORT` moves the manager off its usual port (8200 for Vault, 8080 for Conjur), and `E2E_SECRET_MANAGER_DIR` moves the env files. Keep that directory private, because both files hold a working admin credential. Keep `OPENAI_API_KEY` out of the proxy's environment. The tests copy the runner's key into the manager under a fresh name per test, so a passing call proves the key came through the manager rather than the `os.environ` fallback `get_secret` takes when the manager errors + +A backend declares what it supports in its `SecretBackend.capabilities`, and a test that needs something not every backend does carries `@pytest.mark.requires_capability(...)`, so it is deselected, not failed or skipped, on the lanes that lack it. CyberArk has no `deletes_stored_keys`, because the proxy's delete answers `not_supported` and Conjur keeps the key, so the delete test runs only on the Vault lane + +To add a backend, leave the tests and markers alone and add: + +1. `secret_manager/secret_store_.py`: a `SecretStore` (`write`, `read` returning None when absent, idempotent `destroy`) over the manager's own API through `e2e_http`'s external helpers, read from `E2E__*` env vars, and a `SecretBackend` whose `system` is the litellm `KeyManagementSystem` value and whose `capabilities` lists what it supports +2. its entry in `secret_backends.BACKENDS` +3. `gateway/secret_manager__ci_config.yml`, a copy of an existing lane's with only `key_management_system` changed +4. an `up_` function in `secret_manager/backend.sh` that starts the manager and writes `proxy.env` and `tests.env` +5. a CI step that runs `backend.sh up ` (or the same containers as sidecars), boots the proxy with `proxy.env` and a license, and runs pytest with `tests.env` + ### Record and replay Record/replay scopes to the proxy's provider-bound traffic only. In `E2E_FIXTURE_MODE=record` the harness boots a local provider-edge server, edge-wired tests register their deployments with an `api_base` pointing at it, and every provider call the proxy makes is forwarded verbatim and written to a fixture bundle (default `tests/e2e/.fixtures`, override with `E2E_FIXTURE_DIR`). `E2E_FIXTURE_MODE=replay` runs the same tests against the same live proxy and database, but the edge answers the proxy's provider calls from the bundle instead of the provider, so the run makes zero provider calls and spends nothing while key auth, routing, cost calculation, and spend-log writes all still execute for real. Unset (or `live`) behaves exactly as before the knob existed. Both record and replay need the proxy up; only the provider is taken out of the loop diff --git a/tests/e2e/conftest.py b/tests/e2e/conftest.py index f4de4ac01ba..603591006d9 100644 --- a/tests/e2e/conftest.py +++ b/tests/e2e/conftest.py @@ -36,6 +36,7 @@ from e2e_config import ( PROVIDER_EDGE_HOST_OPT_IN_ENV, PROXY_BASE_URL, REDIS_CHAOS_OPT_IN_ENV, + SECRET_MANAGER_OPT_IN_ENV, WEEKLY_ANOMALY_OPT_IN_ENV, unique_marker, ) @@ -70,6 +71,7 @@ OPT_IN_MARKERS: Final = MappingProxyType( "provider_edge_host": PROVIDER_EDGE_HOST_OPT_IN_ENV, "otel_v2": OTEL_V2_OPT_IN_ENV, "otel_tls": OTEL_TLS_OPT_IN_ENV, + "secret_manager": SECRET_MANAGER_OPT_IN_ENV, } ) @@ -172,6 +174,11 @@ def pytest_configure(config: pytest.Config) -> None: "markers", "otel_tls: needs a stack whose gateway exports OTLP over TLS signed by the CA in SSL_CERT_FILE; deselected unless E2E_OTEL_EXPORTER_ENDPOINT is set", ) + config.addinivalue_line( + "markers", + "secret_manager: needs a proxy booted from gateway/secret_manager__ci_config.yml against that live " + "secret manager; deselected unless E2E_SECRET_MANAGER names the backend (see secret_manager/secret_backends.py)", + ) def pytest_sessionstart(session: pytest.Session) -> None: diff --git a/tests/e2e/coverage_registry/other.yaml b/tests/e2e/coverage_registry/other.yaml index 1706b2f8f25..f695af3cb11 100644 --- a/tests/e2e/coverage_registry/other.yaml +++ b/tests/e2e/coverage_registry/other.yaml @@ -40,7 +40,10 @@ - {id: other.config.runtime_update.applies_at_runtime, module: other, tier: P0, area: config, assertions: [applies_at_runtime], source: "proxy_server.py:14014-14060", rationale: "/config/update persists to DB + invalidates cache"} - {id: other.config.passthrough.headers_forwarded, module: other, tier: P0, area: config, assertions: [headers_forwarded], source: "passthrough/utils.py forward_headers_from_request", rationale: "Custom pass-through static headers and x-pass-* client headers reach the upstream"} - {id: other.config.general_settings.alert_webhook_side_effect, module: other, tier: P1, area: config, assertions: [alert_webhook_side_effect], source: "proxy_server.py:14215", rationale: "alert_to_webhook_url auto-enables slack alerting"} -- {id: other.config.secret_resolution.kms_integration, module: other, tier: P1, area: config, assertions: [kms_integration], source: "proxy_server.py:3984-4010", rationale: "Resolves secrets from Vault/KMS at startup"} +- {id: other.config.secret_resolution.kms_integration, module: other, tier: P1, area: config, assertions: [kms_integration], source: "secret_managers/main.py get_secret / secret_manager/test_secret_manager_e2e.py", rationale: "A deployment whose api_key is os.environ/ gets its key from the configured secret manager when that name exists only in the manager"} +- {id: other.config.secret_resolution.manager_value_used, module: other, tier: P1, area: config, assertions: [manager_value_used], source: "secret_managers/main.py get_secret / secret_manager/test_secret_manager_e2e.py", rationale: "The value the manager holds is what reaches the provider: a bogus key in the manager is rejected by the provider with 401, so a passing resolution test cannot be an env fallback"} +- {id: other.config.secret_manager.virtual_key_stored, module: other, tier: P1, area: config, assertions: [virtual_key_stored], source: "key_management_event_hooks.py _store_virtual_key_in_secret_manager", rationale: "With store_virtual_keys, /key/generate writes the new key under prefix_for_stored_virtual_keys + key_alias in the manager"} +- {id: other.config.secret_manager.virtual_key_deleted, module: other, tier: P1, area: config, assertions: [virtual_key_deleted], source: "key_management_event_hooks.py _delete_virtual_keys_from_secret_manager", rationale: "/key/delete removes the stored key from the manager, so a revoked key does not linger there"} - {id: other.config.overrides.audit_logged, module: other, tier: P1, area: config, assertions: [audit_logged], source: "config_override_endpoints.py:67-100", rationale: "Config override mutations audit-logged, values redacted"} - {id: other.key_mgmt.regenerate.grace_period_honored, module: other, tier: P1, area: auth, assertions: [grace_period_honored], source: "key_management_endpoints.py:4503-4560", rationale: "Old key valid during grace_period then revoked"} - {id: other.key_mgmt.spend_reset.resets_to_value, module: other, tier: P1, area: auth, assertions: [resets_to_value], source: "key_management_endpoints.py:4841", rationale: "reset_spend resets accumulated spend"} diff --git a/tests/e2e/e2e_config.py b/tests/e2e/e2e_config.py index ac26b2a3875..ca3b74281ae 100644 --- a/tests/e2e/e2e_config.py +++ b/tests/e2e/e2e_config.py @@ -150,6 +150,7 @@ MCP_OAUTH_LIVE_OPT_IN_ENV: Final = "E2E_MCP_OAUTH_LIVE" PROVIDER_EDGE_HOST_OPT_IN_ENV: Final = "E2E_PROVIDER_EDGE_HOST_REACHABLE" OTEL_V2_OPT_IN_ENV: Final = "E2E_OTEL_V2" OTEL_TLS_OPT_IN_ENV: Final = "E2E_OTEL_EXPORTER_ENDPOINT" +SECRET_MANAGER_OPT_IN_ENV: Final = "E2E_SECRET_MANAGER" ANOMALY_SESSIONS = int(os.environ.get("E2E_ANOMALY_SESSIONS", "6")) ANOMALY_TURNS_PER_SESSION = int(os.environ.get("E2E_ANOMALY_TURNS_PER_SESSION", "6")) ANOMALY_TURN_ATTEMPTS = int(os.environ.get("E2E_ANOMALY_TURN_ATTEMPTS", "3")) diff --git a/tests/e2e/e2e_http.py b/tests/e2e/e2e_http.py index 1b62a1dbd8c..24bd76d4429 100644 --- a/tests/e2e/e2e_http.py +++ b/tests/e2e/e2e_http.py @@ -129,9 +129,9 @@ class ProbeResult(BaseModel): class ExternalWrite(BaseModel): - """Outcome of a write to a non-proxy API (an identity provider's admin API) - that answers with a status and, on create, a Location header naming the new - resource rather than a JSON body.""" + """Outcome of a call to a non-proxy API (an identity provider's admin API, a + secret manager) that answers with a status, on create a Location header naming + the new resource, and a body kept as text rather than parsed as JSON.""" status_code: int location: str = "" @@ -491,6 +491,30 @@ def post_json_external( ) +def send_text_external( + method: Literal["GET", "POST", "PATCH"], + url: str, + *, + headers: BaseModel, + content: str | None = None, + timeout: float = 30.0, +) -> ExternalWrite: + """Send an absolute URL outside the proxy a raw text body (or none) and keep the + answer as text, for an API that takes and returns neither JSON nor forms: CyberArk + Conjur takes a secret value or a YAML policy and returns a secret as its raw value.""" + try: + resp = requests.request( + method, + url, + headers=_headers(headers), + data=content.encode() if content is not None else None, + timeout=timeout, + ) + except requests.RequestException as exc: + return ExternalWrite(status_code=-1, body=str(exc)) + return ExternalWrite(status_code=resp.status_code, body=resp.text) + + def delete_external(url: str, *, headers: BaseModel, timeout: float = 30.0) -> ExternalWrite: try: resp = requests.delete(url, headers=_headers(headers), timeout=timeout) diff --git a/tests/e2e/gateway/secret_manager_cyberark_ci_config.yml b/tests/e2e/gateway/secret_manager_cyberark_ci_config.yml new file mode 100644 index 00000000000..32602783b02 --- /dev/null +++ b/tests/e2e/gateway/secret_manager_cyberark_ci_config.yml @@ -0,0 +1,8 @@ +general_settings: + master_key: os.environ/LITELLM_MASTER_KEY + store_model_in_db: true + key_management_system: cyberark + key_management_settings: + access_mode: read_and_write + store_virtual_keys: true + prefix_for_stored_virtual_keys: litellm-e2e/virtual-keys/ diff --git a/tests/e2e/gateway/secret_manager_hashicorp_vault_ci_config.yml b/tests/e2e/gateway/secret_manager_hashicorp_vault_ci_config.yml new file mode 100644 index 00000000000..8e6b7e74f8e --- /dev/null +++ b/tests/e2e/gateway/secret_manager_hashicorp_vault_ci_config.yml @@ -0,0 +1,8 @@ +general_settings: + master_key: os.environ/LITELLM_MASTER_KEY + store_model_in_db: true + key_management_system: hashicorp_vault + key_management_settings: + access_mode: read_and_write + store_virtual_keys: true + prefix_for_stored_virtual_keys: litellm-e2e/virtual-keys/ diff --git a/tests/e2e/pytest.ini b/tests/e2e/pytest.ini index 4866511af3f..d01caeff3ea 100644 --- a/tests/e2e/pytest.ini +++ b/tests/e2e/pytest.ini @@ -17,3 +17,4 @@ markers = provider_edge_host: routes provider traffic through the pytest host's edge in every fixture mode, so the gateway must reach the pytest host; deselected unless E2E_PROVIDER_EDGE_HOST_REACHABLE is set otel_v2: needs a proxy running with LITELLM_OTEL_V2=true; deselected unless E2E_OTEL_V2 is set otel_tls: needs a stack whose gateway exports OTLP over TLS signed by the CA in SSL_CERT_FILE; deselected unless E2E_OTEL_EXPORTER_ENDPOINT is set + secret_manager: needs a proxy booted from gateway/secret_manager__ci_config.yml against that live secret manager; deselected unless E2E_SECRET_MANAGER names the backend (see secret_manager/secret_backends.py) diff --git a/tests/e2e/secret_manager/backend.sh b/tests/e2e/secret_manager/backend.sh new file mode 100755 index 00000000000..70272c237c5 --- /dev/null +++ b/tests/e2e/secret_manager/backend.sh @@ -0,0 +1,76 @@ +#!/usr/bin/env bash +set -euo pipefail +umask 077 + +usage() { + local systems + systems=$(declare -F | sed -n 's/^declare -f up_//p' | paste -sd '|' -) + echo "usage: $0 up|down $systems" >&2 + exit 2 +} + +action=${1:-} +system=${2:-} +dir=${E2E_SECRET_MANAGER_DIR:-$HOME/.cache/litellm-e2e-secret-manager}/$system +name=litellm-e2e-$system + +wait_for() { + local url=$1 + for _ in $(seq 1 90); do + if curl -sf -o /dev/null "$url"; then + return 0 + fi + sleep 2 + done + echo "$system did not answer at $url" >&2 + return 1 +} + +down() { + docker rm -f "$name" "$name-db" >/dev/null 2>&1 || true + docker network rm "$name" >/dev/null 2>&1 || true + rm -rf "$dir" +} + +up_hashicorp_vault() { + local port=${E2E_SECRET_MANAGER_PORT:-8200} + local token + token=e2e-$(openssl rand -hex 16) + docker run -d --name "$name" -p "127.0.0.1:$port:8200" --cap-add IPC_LOCK \ + -e VAULT_DEV_ROOT_TOKEN_ID="$token" hashicorp/vault:1.20 >/dev/null + wait_for "http://127.0.0.1:$port/v1/sys/health" + printf 'HCP_VAULT_ADDR=http://127.0.0.1:%s\nHCP_VAULT_TOKEN=%s\n' "$port" "$token" >"$dir/proxy.env" + printf 'E2E_VAULT_ADDR=http://127.0.0.1:%s\nE2E_VAULT_TOKEN=%s\n' "$port" "$token" >"$dir/tests.env" +} + +up_cyberark() { + local port=${E2E_SECRET_MANAGER_PORT:-8080} + local data_key api_key + docker network create "$name" >/dev/null + docker run -d --name "$name-db" --network "$name" -e POSTGRES_HOST_AUTH_METHOD=trust postgres:15 >/dev/null + data_key=$(docker run --rm cyberark/conjur:1.24 data-key generate) + docker run -d --name "$name" --network "$name" -p "127.0.0.1:$port:80" \ + -e DATABASE_URL="postgres://postgres@$name-db/postgres" -e CONJUR_DATA_KEY="$data_key" \ + -e CONJUR_AUTHENTICATORS=authn cyberark/conjur:1.24 server >/dev/null + wait_for "http://127.0.0.1:$port/" + docker exec "$name" conjurctl account create --name default >/dev/null + api_key=$(docker exec "$name" conjurctl role retrieve-key default:user:admin | tr -d '\r\n') + printf 'CYBERARK_API_BASE=http://127.0.0.1:%s\nCYBERARK_ACCOUNT=default\nCYBERARK_USERNAME=admin\nCYBERARK_API_KEY=%s\n' \ + "$port" "$api_key" >"$dir/proxy.env" + printf 'E2E_CYBERARK_API_BASE=http://127.0.0.1:%s\nE2E_CYBERARK_ACCOUNT=default\nE2E_CYBERARK_USERNAME=admin\nE2E_CYBERARK_API_KEY=%s\n' \ + "$port" "$api_key" >"$dir/tests.env" +} + +[[ $# -eq 2 && -n $system ]] && declare -F "up_$system" >/dev/null || usage + +case $action in + up) + down + mkdir -p "$dir" + "up_$system" + echo "E2E_SECRET_MANAGER=$system" >>"$dir/tests.env" + echo "$system is up; env in $dir/proxy.env (proxy) and $dir/tests.env (pytest)" + ;; + down) down ;; + *) usage ;; +esac diff --git a/tests/e2e/secret_manager/conftest.py b/tests/e2e/secret_manager/conftest.py new file mode 100644 index 00000000000..46ef598d711 --- /dev/null +++ b/tests/e2e/secret_manager/conftest.py @@ -0,0 +1,57 @@ +from __future__ import annotations + +import os +from dataclasses import dataclass +from typing import Final + +import pytest + +from e2e_config import SECRET_MANAGER_OPT_IN_ENV +from proxy_client import ProxyClient +from secret_backends import BACKENDS, selected_backend +from secret_store import SecretBackend, SecretStore + +REQUIRES_CAPABILITY: Final = "requires_capability" + + +def pytest_configure(config: pytest.Config) -> None: + config.addinivalue_line( + "markers", + f"{REQUIRES_CAPABILITY}(capability): secret_manager test deselected when the backend " + f"{SECRET_MANAGER_OPT_IN_ENV} names lacks the capability (secret_store.Capability)", + ) + + +def _lacks_capability(item: pytest.Item, backend: SecretBackend) -> bool: + marker: Final = item.get_closest_marker(REQUIRES_CAPABILITY) + return marker is not None and marker.args[0] not in backend.capabilities + + +def pytest_collection_modifyitems(config: pytest.Config, items: list[pytest.Item]) -> None: + backend: Final = BACKENDS.get(os.environ.get(SECRET_MANAGER_OPT_IN_ENV, "").strip()) + if backend is None: + return + deselected: Final = [item for item in items if _lacks_capability(item, backend)] + if deselected: + config.hook.pytest_deselected(items=deselected) + items[:] = [item for item in items if not _lacks_capability(item, backend)] + + +@dataclass(frozen=True, slots=True) +class SecretManagerClient: + proxy: ProxyClient + + +@pytest.fixture(scope="session") +def client(proxy: ProxyClient) -> SecretManagerClient: + return SecretManagerClient(proxy) + + +@pytest.fixture(scope="session") +def backend() -> SecretBackend: + return selected_backend() + + +@pytest.fixture(scope="session") +def store(backend: SecretBackend) -> SecretStore: + return backend.from_env() diff --git a/tests/e2e/secret_manager/secret_backends.py b/tests/e2e/secret_manager/secret_backends.py new file mode 100644 index 00000000000..578b56970a3 --- /dev/null +++ b/tests/e2e/secret_manager/secret_backends.py @@ -0,0 +1,25 @@ +from __future__ import annotations + +import os +from types import MappingProxyType +from typing import Final + +import pytest + +from e2e_config import SECRET_MANAGER_OPT_IN_ENV +from secret_store import SecretBackend +from secret_store_cyberark import CYBERARK +from secret_store_hashicorp_vault import HASHICORP_VAULT + +BACKENDS: Final = MappingProxyType({backend.system: backend for backend in (HASHICORP_VAULT, CYBERARK)}) + + +def selected_backend() -> SecretBackend: + system: Final = os.environ.get(SECRET_MANAGER_OPT_IN_ENV, "").strip() + backend: Final = BACKENDS.get(system) + if backend is None: + pytest.fail( + f"{SECRET_MANAGER_OPT_IN_ENV}={system!r} names no secret manager backend; " + f"set it to one of {sorted(BACKENDS)}" + ) + return backend diff --git a/tests/e2e/secret_manager/secret_store.py b/tests/e2e/secret_manager/secret_store.py new file mode 100644 index 00000000000..cff5005b73a --- /dev/null +++ b/tests/e2e/secret_manager/secret_store.py @@ -0,0 +1,29 @@ +from __future__ import annotations + +from collections.abc import Callable +from dataclasses import dataclass +from typing import Final, Literal, Protocol + +SECRET_MANAGER_CONFIG_DIR: Final = "gateway" + + +class SecretStore(Protocol): + def write(self, name: str, value: str) -> None: ... + + def read(self, name: str) -> str | None: ... + + def destroy(self, name: str) -> None: ... + + +Capability = Literal["deletes_stored_keys"] + + +@dataclass(frozen=True, slots=True) +class SecretBackend: + system: str + from_env: Callable[[], SecretStore] + capabilities: frozenset[Capability] + + @property + def proxy_config(self) -> str: + return f"{SECRET_MANAGER_CONFIG_DIR}/secret_manager_{self.system}_ci_config.yml" diff --git a/tests/e2e/secret_manager/secret_store_cyberark.py b/tests/e2e/secret_manager/secret_store_cyberark.py new file mode 100644 index 00000000000..87bcd2ffb1c --- /dev/null +++ b/tests/e2e/secret_manager/secret_store_cyberark.py @@ -0,0 +1,118 @@ +from __future__ import annotations + +import base64 +import os +from dataclasses import dataclass, field +from typing import Final, Literal +from urllib.parse import quote + +import pytest +import yaml +from e2e_http import ExternalWrite, Headers, send_text_external +from pydantic import Field + +from secret_store import SecretBackend + +CYBERARK_API_BASE_ENV: Final = "E2E_CYBERARK_API_BASE" +CYBERARK_ACCOUNT_ENV: Final = "E2E_CYBERARK_ACCOUNT" +CYBERARK_USERNAME_ENV: Final = "E2E_CYBERARK_USERNAME" +CYBERARK_API_KEY_ENV: Final = "E2E_CYBERARK_API_KEY" + +# The same defaults CyberArkSecretManager falls back to for CYBERARK_*. +DEFAULT_API_BASE: Final = "http://127.0.0.1:8080" +DEFAULT_ACCOUNT: Final = "default" +DEFAULT_USERNAME: Final = "admin" + +SYSTEM: Final = "cyberark" + +_START_HINT: Final = ( + f"Start one with `bash tests/e2e/secret_manager/backend.sh up {SYSTEM}`, which writes the env for " + f"the proxy (booted from gateway/secret_manager_{SYSTEM}_ci_config.yml) and for the tests" +) + + +class ConjurHeaders(Headers): + authorization: str = Field(repr=False) + content_type: str | None = Field(default=None, serialization_alias="Content-Type") + + +def _policy_scalar(name: str) -> str: + # Quoted the way CyberArkSecretManager._ensure_variable_exists quotes it. + return yaml.safe_dump(name, default_style='"').strip() + + +@dataclass(frozen=True, slots=True) +class Conjur: + base_url: str + account: str + username: str + api_key: str = field(repr=False) + + def _fail_unless_reached(self, result: ExternalWrite, action: str) -> None: + if result.status_code == -1: + pytest.fail(f"No live Conjur at {self.base_url}: {result.body}. {_START_HINT}") + if result.status_code == 401: + pytest.fail(f"Conjur rejected {self.username}'s credentials while trying to {action}. {_START_HINT}") + + def _headers(self, content_type: str | None = None) -> ConjurHeaders: + # Tokens last about eight minutes, so each call authenticates afresh rather than + # letting a long session outlive a cached one. + auth: Final = send_text_external( + "POST", + f"{self.base_url}/authn/{self.account}/{quote(self.username, safe='')}/authenticate", + headers=Headers(), + content=self.api_key, + ) + self._fail_unless_reached(auth, "authenticate") + if not auth.ok: + pytest.fail(f"Conjur refused to authenticate {self.username}: HTTP {auth.status_code} {auth.body[:300]}") + token: Final = base64.b64encode(auth.body.encode()).decode() + return ConjurHeaders(authorization=f'Token token="{token}"', content_type=content_type) + + def _secret_url(self, name: str) -> str: + return f"{self.base_url}/secrets/{self.account}/variable/{quote(name, safe='')}" + + def _update_root_policy(self, method: Literal["POST", "PATCH"], policy: str, action: str) -> None: + result: Final = send_text_external( + method, + f"{self.base_url}/policies/{self.account}/policy/root", + headers=self._headers(content_type="application/x-yaml"), + content=policy, + ) + self._fail_unless_reached(result, action) + if not result.ok: + pytest.fail(f"Conjur refused to {action}: HTTP {result.status_code} {result.body[:300]}") + + def write(self, name: str, value: str) -> None: + self._update_root_policy("POST", f"- !variable {_policy_scalar(name)}\n", f"declare {name}") + result: Final = send_text_external("POST", self._secret_url(name), headers=self._headers(), content=value) + self._fail_unless_reached(result, f"write {name}") + if not result.ok: + pytest.fail(f"Conjur refused to write {name}: HTTP {result.status_code} {result.body[:300]}") + + def read(self, name: str) -> str | None: + result: Final = send_text_external("GET", self._secret_url(name), headers=self._headers()) + self._fail_unless_reached(result, f"read {name}") + if result.status_code == 404: + return None + if not result.ok: + pytest.fail(f"Conjur refused to read {name}: HTTP {result.status_code} {result.body[:300]}") + return result.body + + def destroy(self, name: str) -> None: + self._update_root_policy("PATCH", f"- !delete\n record: !variable {_policy_scalar(name)}\n", f"destroy {name}") + + +def conjur_from_env() -> Conjur: + api_key: Final = os.environ.get(CYBERARK_API_KEY_ENV, "").strip() + if not api_key: + pytest.fail(f"The {SYSTEM} lane needs {CYBERARK_API_KEY_ENV} to reach its Conjur. {_START_HINT}") + return Conjur( + base_url=os.environ.get(CYBERARK_API_BASE_ENV, "").strip().rstrip("/") or DEFAULT_API_BASE, + account=os.environ.get(CYBERARK_ACCOUNT_ENV, "").strip() or DEFAULT_ACCOUNT, + username=os.environ.get(CYBERARK_USERNAME_ENV, "").strip() or DEFAULT_USERNAME, + api_key=api_key, + ) + + +CYBERARK: Final = SecretBackend(system=SYSTEM, from_env=conjur_from_env, capabilities=frozenset()) diff --git a/tests/e2e/secret_manager/secret_store_hashicorp_vault.py b/tests/e2e/secret_manager/secret_store_hashicorp_vault.py new file mode 100644 index 00000000000..ccf8cefe716 --- /dev/null +++ b/tests/e2e/secret_manager/secret_store_hashicorp_vault.py @@ -0,0 +1,113 @@ +from __future__ import annotations + +import os +from dataclasses import dataclass, field +from typing import Final + +import pytest +from e2e_http import ( + Headers, + NetworkError, + Success, + UnknownApiError, + delete_external, + get_external, + post_json_external, +) +from pydantic import BaseModel, Field + +from secret_store import SecretBackend + +VAULT_ADDR_ENV: Final = "E2E_VAULT_ADDR" +VAULT_TOKEN_ENV: Final = "E2E_VAULT_TOKEN" +VAULT_MOUNT_ENV: Final = "E2E_VAULT_MOUNT_NAME" + +DEFAULT_VAULT_ADDR: Final = "http://127.0.0.1:8200" +DEFAULT_MOUNT: Final = "secret" + +SYSTEM: Final = "hashicorp_vault" + +_START_HINT: Final = ( + f"Start one with `bash tests/e2e/secret_manager/backend.sh up {SYSTEM}`, which writes the env for " + f"the proxy (booted from gateway/secret_manager_{SYSTEM}_ci_config.yml) and for the tests" +) + + +class VaultHeaders(Headers): + x_vault_token: str = Field(serialization_alias="X-Vault-Token", repr=False) + + +class KvData(BaseModel): + key: str = Field(repr=False) + + +class KvWriteBody(BaseModel): + data: KvData + + +class KvReadData(BaseModel): + data: KvData + + +class KvReadResponse(BaseModel): + data: KvReadData + + +@dataclass(frozen=True, slots=True) +class Vault: + base_url: str + token: str = field(repr=False) + mount: str = DEFAULT_MOUNT + + def _headers(self) -> VaultHeaders: + return VaultHeaders(x_vault_token=self.token) + + def _data_url(self, name: str) -> str: + return f"{self.base_url}/v1/{self.mount}/data/{name}" + + def _metadata_url(self, name: str) -> str: + return f"{self.base_url}/v1/{self.mount}/metadata/{name}" + + def write(self, name: str, value: str) -> None: + write: Final = post_json_external( + self._data_url(name), headers=self._headers(), json=KvWriteBody(data=KvData(key=value)) + ) + if write.status_code == -1: + pytest.fail(f"No live Vault at {self.base_url}: {write.body}. {_START_HINT}") + if not write.ok: + pytest.fail(f"Vault refused to write {name}: HTTP {write.status_code} {write.body[:300]}") + + def read(self, name: str) -> str | None: + result: Final = get_external(self._data_url(name), headers=self._headers(), response_type=KvReadResponse) + match result: + case Success(data=body): + return body.data.data.key + case UnknownApiError(status_code=404): + return None + case NetworkError(message=message): + return pytest.fail(f"No live Vault at {self.base_url}: {message}. {_START_HINT}") + case _: + return pytest.fail(f"Vault refused to read {name}: {result}") + + def destroy(self, name: str) -> None: + write: Final = delete_external(self._metadata_url(name), headers=self._headers()) + if not write.ok and write.status_code != 404: + pytest.fail(f"Vault refused to destroy {name}: HTTP {write.status_code} {write.body[:300]}") + + +def vault_from_env() -> Vault: + token: Final = os.environ.get(VAULT_TOKEN_ENV, "").strip() + if not token: + pytest.fail(f"The hashicorp_vault lane needs {VAULT_TOKEN_ENV} to reach its Vault. {_START_HINT}") + return Vault( + base_url=os.environ.get(VAULT_ADDR_ENV, DEFAULT_VAULT_ADDR).rstrip("/"), + token=token, + mount=os.environ.get(VAULT_MOUNT_ENV, "").strip() or DEFAULT_MOUNT, + ) + + +HASHICORP_VAULT: Final = SecretBackend( + system=SYSTEM, + from_env=vault_from_env, + capabilities=frozenset({"deletes_stored_keys"}), +) diff --git a/tests/e2e/secret_manager/test_secret_manager_e2e.py b/tests/e2e/secret_manager/test_secret_manager_e2e.py new file mode 100644 index 00000000000..a9c9024718d --- /dev/null +++ b/tests/e2e/secret_manager/test_secret_manager_e2e.py @@ -0,0 +1,128 @@ +from __future__ import annotations + +import os +import time +from collections.abc import Callable +from typing import Final + +import pytest + +from e2e_config import unique_marker +from e2e_http import Result, Success, UnauthorizedError, unwrap +from lifecycle import ResourceManager +from models import ChatBody, ChatMessage, ChatResponse, KeyGenerateBody, LiteLLMParamsBody +from proxy_client import ProxyClient +from secret_store import SecretStore + +pytestmark = [pytest.mark.e2e, pytest.mark.secret_manager] + +BACKEND_MODEL: Final = "openai/gpt-4o-mini" +VIRTUAL_KEY_PREFIX: Final = "litellm-e2e/virtual-keys/" +PROVIDER_KEY_ENV: Final = "OPENAI_API_KEY" + + +# The proxy's env never holds OPENAI_API_KEY and each test seeds it under a fresh name, so a passing +# call proves the key came from the manager and not get_secret's os.environ fallback. +def _provider_key() -> str: + key: Final = os.environ.get(PROVIDER_KEY_ENV, "").strip() + if not key: + pytest.fail(f"The secret manager suite seeds the manager with the runner's {PROVIDER_KEY_ENV}, which is unset") + return key + + +def _seed(store: SecretStore, resources: ResourceManager, value: str) -> str: + name: Final = f"litellm-e2e-openai-{unique_marker()}" + store.write(name, value) + resources.defer(lambda: store.destroy(name)) + return name + + +def _deploy(proxy: ProxyClient, resources: ResourceManager, secret_name: str) -> str: + model_name: Final = f"secret-manager-backed-{unique_marker()}" + model_id: Final = proxy.create_model( + model_name, + LiteLLMParamsBody(model=BACKEND_MODEL, api_key=f"os.environ/{secret_name}"), + provider_live=True, + ) + resources.defer(lambda: proxy.delete_model(model_id)) + return model_name + + +def _chat(proxy: ProxyClient, key: str, model: str) -> Result[ChatResponse]: + return proxy.chat( + key, + ChatBody( + model=model, + messages=[ChatMessage(role="user", content=f"reply with one word {unique_marker()}")], + max_tokens=16, + ), + ) + + +def _eventually(proxy: ProxyClient, read: Callable[[], str | None], expected: str | None, context: str) -> None: + deadline: Final = time.monotonic() + proxy.poll_timeout + last: str | None = read() + while last != expected and time.monotonic() < deadline: + time.sleep(proxy.poll_interval) + last = read() + if last != expected: + pytest.fail( + f"{context}: the secret manager still holds {'a value' if last is not None else 'nothing'} after the deadline" + ) + + +class TestSecretManager: + @pytest.mark.covers("other.config.secret_resolution.kms_integration") + def test_deployment_key_resolves_from_the_manager( + self, proxy: ProxyClient, resources: ResourceManager, store: SecretStore, scoped_key: str + ) -> None: + model: Final = _deploy(proxy, resources, _seed(store, resources, _provider_key())) + + response: Final = unwrap(_chat(proxy, scoped_key, model)) + + assert response.choices, f"the manager-backed deployment answered with no choices: {response}" + + @pytest.mark.covers("other.config.secret_resolution.manager_value_used") + def test_deployment_uses_the_value_the_manager_holds( + self, proxy: ProxyClient, resources: ResourceManager, store: SecretStore, scoped_key: str + ) -> None: + bogus: Final = f"sk-litellm-e2e-not-a-key-{unique_marker()}" + model: Final = _deploy(proxy, resources, _seed(store, resources, bogus)) + + result: Final = _chat(proxy, scoped_key, model) + + match result: + case UnauthorizedError(body=body): + assert "AuthenticationError" in body, f"the 401 did not come from the provider: {body[:300]}" + case Success(): + pytest.fail("a deployment whose managed secret is not a real key still reached the provider") + case _: + pytest.fail(f"expected the provider to reject the manager-held key with 401, got {result}") + + @pytest.mark.covers("other.config.secret_manager.virtual_key_stored") + def test_generated_key_is_written_to_the_manager( + self, proxy: ProxyClient, resources: ResourceManager, store: SecretStore + ) -> None: + alias: Final = f"litellm-e2e-vk-{unique_marker()}" + secret_name: Final = f"{VIRTUAL_KEY_PREFIX}{alias}" + resources.defer(lambda: store.destroy(secret_name)) + key: Final = proxy.generate_key(KeyGenerateBody(key_alias=alias)) + resources.defer(lambda: proxy.delete_key(key)) + + _eventually(proxy, lambda: store.read(secret_name), key, f"the generated key {alias}") + + @pytest.mark.requires_capability("deletes_stored_keys") + @pytest.mark.covers("other.config.secret_manager.virtual_key_deleted") + def test_deleted_key_is_removed_from_the_manager( + self, proxy: ProxyClient, resources: ResourceManager, store: SecretStore + ) -> None: + alias: Final = f"litellm-e2e-vk-{unique_marker()}" + secret_name: Final = f"{VIRTUAL_KEY_PREFIX}{alias}" + resources.defer(lambda: store.destroy(secret_name)) + key: Final = proxy.generate_key(KeyGenerateBody(key_alias=alias)) + resources.defer(lambda: proxy.delete_key(key)) + _eventually(proxy, lambda: store.read(secret_name), key, f"the generated key {alias}") + + proxy.delete_key(key) + + _eventually(proxy, lambda: store.read(secret_name), None, f"the deleted key {alias}") From 2157351004d63e8a3db0f51c32bd8fe9c69ad6d5 Mon Sep 17 00:00:00 2001 From: moe-berri Date: Tue, 22 Sep 2026 18:03:32 -0700 Subject: [PATCH 070/101] feat(ui): simplify auto-router setup and clarify feature limits (#42625) * feat(ui): simplify auto-router setup and clarify feature limits * fix(ui): validate auto-router drafts before saving * fix: keep auto-router allowances consistent after deletes and refreshes --- litellm/proxy/_types.py | 1 + .../auto_router_endpoints.py | 50 ++ .../model_management_endpoints.py | 13 +- .../auto_router_availability.py | 148 +++++ litellm/proxy/proxy_server.py | 9 + .../public_endpoints/autorouter_presets.json | 36 +- .../complexity_router/fuse_presets.json | 23 +- .../auto_router_tuning_baseline.py | 16 +- .../auto_router_endpoints.py | 19 + .../test_auto_router_endpoints.py | 153 ++++- .../test_model_management_endpoints.py | 145 ++++- .../test_auto_router_availability.py | 196 +++++++ .../proxy/proxy_server/test_lifecycle.py | 54 +- .../proxy/proxy_server/test_proxy_config.py | 41 +- .../public_endpoints/test_public_endpoints.py | 8 +- .../test_auto_router_tuning_baseline.py | 61 +- .../add_model/AutoRouterAvailability.tsx | 165 ++++++ ...oRouterClassifierTabs.integration.test.tsx | 255 ++++++-- .../add_model/AutoRouterClassifierTabs.tsx | 310 ++++++++-- .../add_model/ClassificationMethodConfig.tsx | 143 ++--- .../add_model/ClassifierPrimarySettings.tsx | 98 ++++ .../add_model/ClassifierTypeRadios.tsx | 2 +- .../ComplexityRouterAdvancedSections.tsx | 118 +++- ...mplexityRouterConfig.integration.test.tsx} | 461 ++++++++------- .../add_model/ComplexityRouterConfig.tsx | 36 +- ...plexityRouterFastMode.integration.test.tsx | 9 +- ...ecastClassifierConfig.integration.test.tsx | 23 +- .../add_model/ForecastClassifierConfig.tsx | 357 ++++++------ .../JevClassifierConfig.integration.test.tsx | 32 +- .../add_model/JevClassifierConfig.tsx | 45 +- .../JevConnectionTest.integration.test.tsx | 6 +- .../add_model/NonReasoningTierToggle.tsx | 2 +- .../components/add_model/RoutingOptions.tsx | 25 +- .../components/add_model/TierConfigIntro.tsx | 31 +- ... add_auto_router_tab.integration.test.tsx} | 442 ++++++++++---- .../add_model/add_auto_router_tab.tsx | 542 +++++++++--------- .../add_model/auto_router_connection_test.tsx | 10 +- ...dit_auto_router_modal.integration.test.tsx | 214 +++++-- .../edit_auto_router_modal.tsx | 267 +++++---- .../src/lib/autorouter_presets.test.ts | 30 +- ui/litellm-dashboard/src/lib/http/schema.d.ts | 87 +++ ui/litellm-dashboard/tests/autoRouterSetup.ts | 34 ++ 42 files changed, 3364 insertions(+), 1353 deletions(-) create mode 100644 litellm/proxy/management_helpers/auto_router_availability.py create mode 100644 tests/test_litellm/proxy/management_helpers/test_auto_router_availability.py create mode 100644 ui/litellm-dashboard/src/components/add_model/AutoRouterAvailability.tsx create mode 100644 ui/litellm-dashboard/src/components/add_model/ClassifierPrimarySettings.tsx rename ui/litellm-dashboard/src/components/add_model/{ComplexityRouterConfig.test.tsx => ComplexityRouterConfig.integration.test.tsx} (85%) rename ui/litellm-dashboard/src/components/add_model/{add_auto_router_tab.test.tsx => add_auto_router_tab.integration.test.tsx} (77%) create mode 100644 ui/litellm-dashboard/tests/autoRouterSetup.ts diff --git a/litellm/proxy/_types.py b/litellm/proxy/_types.py index 76df8790b92..c7273738fd0 100644 --- a/litellm/proxy/_types.py +++ b/litellm/proxy/_types.py @@ -937,6 +937,7 @@ class LiteLLMRoutes(enum.Enum): # proxy admin, or team admin naming their own team via team_id "/auto_router/test_routing", "/auto_router/validate_complexity_router_config", + "/auto_router/availability", # Per-session auto-router read - the endpoint scopes the row to the caller's own key hash "/auto_router/session", "/cost/predict-cache", diff --git a/litellm/proxy/management_endpoints/auto_router_endpoints.py b/litellm/proxy/management_endpoints/auto_router_endpoints.py index 03fc58622ce..2ae8639fe61 100644 --- a/litellm/proxy/management_endpoints/auto_router_endpoints.py +++ b/litellm/proxy/management_endpoints/auto_router_endpoints.py @@ -58,6 +58,8 @@ from litellm.router_utils.auto_router_model_naming import ( ) from litellm.types.management_endpoints.auto_router_endpoints import ( SHADOW_EVAL_TURN_VALVE, + AutoRouterAvailabilityRequest, + AutoRouterAvailabilityResponse, AutoRouterBenchmarkGroup, AutoRouterBenchmarksResponse, AutoRouterBenchmarkTotals, @@ -391,6 +393,54 @@ async def validate_complexity_router_config( return ComplexityRouterConfigValidationResponse(valid=error is None, error=error) +@router.post( + "/auto_router/availability", + tags=["model management"], # mutable-ok: FastAPI requires a list + response_model=AutoRouterAvailabilityResponse, +) +async def get_auto_router_availability( + data: AutoRouterAvailabilityRequest, + user_api_key_dict: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], +) -> AutoRouterAvailabilityResponse: + from litellm.proxy.management_helpers.auto_router_availability import auto_router_availability + from litellm.proxy.proxy_server import ( + _license_check, # pyright: ignore[reportPrivateUsage] # same entitlement owner as the model write gate + heuristic_v1_tuning_baselines, + llm_router, + proxy_config, + ) + + member_team: Final = await _authorize_router_dry_run(user_api_key_dict, data.team_id) + rows: Final = proxy_config.auto_router_db_catalog + if rows is None or llm_router is None: + raise HTTPException(status_code=503, detail="Auto-router availability is unavailable") + saved: Final = next((row for row in rows if row.model_id == data.saved_model_id), None) + if data.saved_model_id is not None: + if saved is None: + raise HTTPException(status_code=404, detail="Saved auto router is unavailable") + if user_api_key_dict.user_role != LitellmUserRoles.PROXY_ADMIN and ( + saved.team_id != data.team_id or (member_team is not None and saved.created_by != user_api_key_dict.user_id) + ): + raise HTTPException(status_code=403, detail="Cannot check another user's auto router") + existing: Final = saved.deployment if saved is not None else None + others: Final = tuple(row.deployment for row in rows if row is not saved) + tuple(llm_router.config_deployments()) + candidate: Final = MappingProxyType( + { + "litellm_params": MappingProxyType( + {"model": "auto_router/complexity_router", "complexity_router_config": data.complexity_router_config} + ), + "model_info": MappingProxyType({"id": data.saved_model_id or "availability-new-router", "db_model": True}), + } + ) + return auto_router_availability( + others=others, + existing=existing, + candidate=candidate, + baselines=heuristic_v1_tuning_baselines, + limit=_license_check.auto_router_capability_limit(), + ) + + async def _resolve_saved_routing_test( data: AutoRouterRoutingTestRequest, user_api_key_dict: UserAPIKeyAuth, diff --git a/litellm/proxy/management_endpoints/model_management_endpoints.py b/litellm/proxy/management_endpoints/model_management_endpoints.py index fcadcfe2cae..615a528b552 100644 --- a/litellm/proxy/management_endpoints/model_management_endpoints.py +++ b/litellm/proxy/management_endpoints/model_management_endpoints.py @@ -1782,10 +1782,11 @@ async def delete_team_models( # Under MODEL_RECONCILE_LOCK, for the same reason as delete_model: the rows are # gone, but a reconcile holding a pre-delete snapshot would upsert these ids back # onto this pod. The lock orders the eviction after any in-flight reconcile. - if llm_router is not None: - from litellm.proxy.proxy_server import MODEL_RECONCILE_LOCK + from litellm.proxy.proxy_server import MODEL_RECONCILE_LOCK, proxy_config - async with MODEL_RECONCILE_LOCK: + async with MODEL_RECONCILE_LOCK: + proxy_config.remove_auto_router_catalog_entries(frozenset(deleted_model_ids)) + if llm_router is not None: for model_id in deleted_model_ids: llm_router.delete_deployment(id=model_id) @@ -2194,6 +2195,7 @@ async def delete_model( llm_router, premium_user, prisma_client, + proxy_config, proxy_logging_obj, store_model_in_db, user_api_key_cache, @@ -2245,8 +2247,9 @@ async def delete_model( # this pod serving a model the database no longer has, until the next # reconcile. Taking the lock orders this eviction after any such in-flight # reconcile's re-add, so the eviction is the last word. - if llm_router is not None: - async with MODEL_RECONCILE_LOCK: + async with MODEL_RECONCILE_LOCK: + proxy_config.remove_auto_router_catalog_entries(frozenset({model_info.id})) + if llm_router is not None: llm_router.delete_deployment(id=model_info.id) # Runs after the row delete so the sibling check sees post-delete state. diff --git a/litellm/proxy/management_helpers/auto_router_availability.py b/litellm/proxy/management_helpers/auto_router_availability.py new file mode 100644 index 00000000000..52cd9f0499b --- /dev/null +++ b/litellm/proxy/management_helpers/auto_router_availability.py @@ -0,0 +1,148 @@ +from collections.abc import Mapping, Sequence +from copy import deepcopy +from dataclasses import dataclass +from types import MappingProxyType +from typing import Final + +from pydantic import BaseModel, Json, TypeAdapter, ValidationError + +from litellm.proxy.common_utils.encrypt_decrypt_utils import decrypt_value_helper +from litellm.router_utils.auto_router_model_naming import ( + GATED_AUTO_ROUTER_CAPABILITIES, + capability_limit_violation, + classify_strategy_router_model, + count_capability_routers, + gated_capability_of, +) +from litellm.router_utils.auto_router_tuning_baseline import ( + is_mutable_tuned_candidate, + mutable_tuned_identities, + tuning_quota_violation, +) +from litellm.types.management_endpoints.auto_router_endpoints import ( + AutoRouterAllowance, + AutoRouterAvailabilityResponse, +) + + +class _CatalogModelInfo(BaseModel): + team_id: str | None = None + + +class _CatalogSource(BaseModel): + model_id: str + created_by: str | None = None + litellm_params: Json[dict[str, object]] | dict[str, object] + model_info: Json[_CatalogModelInfo] | _CatalogModelInfo | None = None + + +@dataclass(frozen=True, slots=True) +class AutoRouterCatalogEntry: + model_id: str + team_id: str | None + created_by: str | None + deployment: Mapping[str, object] + + +def _catalog_field(value: object, key: str) -> object: + if not isinstance(value, str): + return deepcopy(value) + return decrypt_value_helper(value, key=key, exception_type="debug", return_original_value=True) + + +def build_auto_router_catalog(rows: Sequence[object]) -> tuple[AutoRouterCatalogEntry, ...] | None: + try: + sources: Final = TypeAdapter(tuple[_CatalogSource, ...]).validate_python(rows, from_attributes=True) + except ValidationError: + return None + return tuple( + AutoRouterCatalogEntry( + model_id=row.model_id, + team_id=row.model_info.team_id if row.model_info is not None else None, + created_by=row.created_by, + deployment=MappingProxyType( + { + "litellm_params": MappingProxyType( + { + "model": model, + "complexity_router_config": _catalog_field( + row.litellm_params.get("complexity_router_config"), "complexity_router_config" + ), + } + ), + "model_info": MappingProxyType({"id": row.model_id, "db_model": True}), + } + ), + ) + for row in sources + if isinstance(model := _catalog_field(row.litellm_params.get("model"), "model"), str) + and classify_strategy_router_model(model) == "complexity" + ) + + +def auto_router_availability( + *, + others: Sequence[Mapping[str, object]], + existing: Mapping[str, object] | None, + candidate: Mapping[str, object], + baselines: Mapping[str, str] | None, + limit: int | None, +) -> AutoRouterAvailabilityResponse: + existing_params: Final = None if existing is None else existing.get("litellm_params") + candidate_params: Final = candidate.get("litellm_params") + owned: Final = gated_capability_of(existing_params) if isinstance(existing_params, Mapping) else None + claimed: Final = gated_capability_of(candidate_params) if isinstance(candidate_params, Mapping) else None + counts: Final = tuple( + (capability, count_capability_routers(others, capability=capability)) + for capability in GATED_AUTO_ROUTER_CAPABILITIES + ) + tuned_count: Final = len(mutable_tuned_identities(others, baselines)) if baselines is not None else 0 + allowances: Final = tuple( + AutoRouterAllowance( + key=capability.key, + limit=limit, + remaining=None if limit is None else max(0, limit - held), + used_by_this_router=owned is capability, + ) + for capability, held in counts + ) + capability_error: Final = next( + ( + capability_limit_violation(capability=capability, held=held + 1, limit=limit) + for capability, held in counts + if capability is claimed + ), + None, + ) + tuning_error: Final = ( + tuning_quota_violation(candidate=candidate, others=others, baselines=baselines, limit=limit) + if baselines is not None + else None + ) + capability_labels: Final = { + "heuristic_v2": "Heuristic v2", + "capability": "Capability", + "llm_v2": "Fuse v2", + "tier_or_classifier_prompt": "Custom tiers or classifier instructions", + } + return AutoRouterAvailabilityResponse( + allowances=( + *allowances, + AutoRouterAllowance( + key="heuristic_tuning", + limit=limit, + remaining=None if limit is None or baselines is None else max(0, limit - tuned_count), + available=limit is None or baselines is not None, + used_by_this_router=bool( + existing is not None and baselines is not None and is_mutable_tuned_candidate(existing, baselines) + ), + ), + ), + error=( + f"{capability_labels[claimed.key]} has no available allowance. Choose another option or free an existing allowance." + if capability_error is not None and claimed is not None + else "These scoring rules need an available Rule-based tuning allowance. Check the weights, thresholds, keywords, and custom dimensions in Advanced settings. Model choices do not use this allowance." + if tuning_error is not None + else None + ), + ) diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py index acb36fc4a59..dab7decd4dc 100644 --- a/litellm/proxy/proxy_server.py +++ b/litellm/proxy/proxy_server.py @@ -132,6 +132,7 @@ from litellm.proxy.common_utils.callback_utils import ( strip_callback_config, ) from litellm.proxy.common_utils.realtime_utils import _realtime_request_body +from litellm.proxy.management_helpers.auto_router_availability import AutoRouterCatalogEntry, build_auto_router_catalog from litellm.router_utils.access_windows import access_windows_config_error from litellm.router_utils.add_retry_fallback_headers import ( get_fallback_errors_from_headers, @@ -5068,6 +5069,7 @@ class ProxyConfig: def __init__(self) -> None: self.config: Mapping[str, object] = MappingProxyType({}) + self.auto_router_db_catalog: tuple[AutoRouterCatalogEntry, ...] | None = None self._last_semantic_filter_config: dict[str, object] | None = None self._last_websearch_interception_config: dict[str, object] | None = None self._last_hashicorp_vault_config: dict[str, object] | None = None @@ -7691,6 +7693,12 @@ class ProxyConfig: def _should_load_db_object(self, object_type: str | SupportedDBObjectType) -> bool: return should_load_db_object(object_type=object_type) + def remove_auto_router_catalog_entries(self, model_ids: frozenset[str]) -> None: + if self.auto_router_db_catalog is not None: + self.auto_router_db_catalog = tuple( + row for row in self.auto_router_db_catalog if row.model_id not in model_ids + ) + async def _get_models_from_db(self, prisma_client: PrismaClient) -> Sequence[_ProxyModelRow] | None: """ Fetch all model deployments from the DB. @@ -7711,6 +7719,7 @@ class ProxyConfig: new_models: Final[Sequence[_ProxyModelRow]] = await ModelRepository( WriterPinnedClient(prisma_client.db) ).table.find_many() + self.auto_router_db_catalog = build_auto_router_catalog(new_models) return new_models except Exception as e: verbose_proxy_logger.exception( diff --git a/litellm/proxy/public_endpoints/autorouter_presets.json b/litellm/proxy/public_endpoints/autorouter_presets.json index 7a251afc076..1c2f96350c6 100644 --- a/litellm/proxy/public_endpoints/autorouter_presets.json +++ b/litellm/proxy/public_endpoints/autorouter_presets.json @@ -1,18 +1,18 @@ { "1m_context": { "label": "1M Context", - "description": "Routes across models with 1M-token context windows: Luna for simple queries, Terra for medium, Sol for complex, Opus 5 at high thinking for reasoning.", + "description": "Routes across models with 1M-token context windows: GPT-6 Luna for simple queries, GPT-5.6 Terra for medium, GPT-6 Sol for complex, Opus 5.5 at high thinking for reasoning.", "complexity_router_config": { "tiers": { - "SIMPLE": ["gpt-5.6-luna"], + "SIMPLE": ["gpt-6-luna"], "MEDIUM": ["gpt-5.6-terra"], - "COMPLEX": ["gpt-5.6-sol"], - "REASONING": ["claude-opus-5"] + "COMPLEX": ["gpt-6-sol"], + "REASONING": ["claude-opus-5-5"] }, "tier_model_configs": { "REASONING": [ { - "model_name": "claude-opus-5", + "model_name": "claude-opus-5-5", "litellm_params": { "reasoning_effort": "high" } } ] @@ -28,12 +28,12 @@ }, "anthropic_family": { "label": "Anthropic Family", - "description": "Routes across the Claude model family: Haiku for simple queries, Sonnet for medium, Opus for complex, Fable 5.1 at high thinking for reasoning.", + "description": "Routes across the Claude model family: Haiku for simple queries, Sonnet for medium, Opus 5.5 for complex, Fable 5.1 at high thinking for reasoning.", "complexity_router_config": { "tiers": { "SIMPLE": ["claude-haiku-4-5"], "MEDIUM": ["claude-sonnet-5"], - "COMPLEX": ["claude-opus-5"], + "COMPLEX": ["claude-opus-5-5"], "REASONING": ["claude-fable-5-1"] }, "tier_model_configs": { @@ -55,12 +55,12 @@ }, "gemini_family": { "label": "Gemini Family", - "description": "Routes across the Gemini model family: Flash Lite 2.5 for simple queries, Flash Lite 3.1 for medium, Flash 3.7 for complex, Pro 3.1 for reasoning-heavy requests.", + "description": "Routes across the Gemini model family: Flash Lite 3.5 for simple queries, Flash 3.8 for medium and complex queries, Pro 3.1 for reasoning-heavy requests.", "complexity_router_config": { "tiers": { - "SIMPLE": ["gemini-2.5-flash-lite"], - "MEDIUM": ["gemini-3.1-flash-lite"], - "COMPLEX": ["gemini-3.7-flash"], + "SIMPLE": ["gemini-3.5-flash-lite"], + "MEDIUM": ["gemini-3.8-flash"], + "COMPLEX": ["gemini-3.8-flash"], "REASONING": ["gemini-3.1-pro-preview"] }, "classifier_type": "heuristic", @@ -74,18 +74,18 @@ }, "lite": { "label": "Lite", - "description": "Cost-optimized routing across providers: DeepSeek V4 Flash for simple queries, Muse Spark 1.2 at xhigh for medium, Kimi K3 at max for complex, Claude Opus 5 for reasoning. An LLM classifier with the agentic rubric assigns tiers.", + "description": "Cost-optimized routing across providers: DeepSeek V4 Flash for simple queries, Muse Spark 1.3 at xhigh for medium, Kimi K3 at max for complex, Claude Opus 5.5 for reasoning. An LLM classifier with the agentic rubric assigns tiers.", "complexity_router_config": { "tiers": { "SIMPLE": ["deepseek-v4-flash"], - "MEDIUM": ["muse-spark-1.2"], + "MEDIUM": ["muse-spark-1.3"], "COMPLEX": ["kimi-k3"], - "REASONING": ["claude-opus-5"] + "REASONING": ["claude-opus-5-5"] }, "tier_model_configs": { "MEDIUM": [ { - "model_name": "muse-spark-1.2", + "model_name": "muse-spark-1.3", "litellm_params": { "reasoning_effort": "xhigh" } } ], @@ -113,12 +113,12 @@ }, "openai_family": { "label": "OpenAI Family", - "description": "Routes across the GPT model family: Luna for simple queries, Terra for medium, Sol for complex, Astra at xhigh thinking for reasoning.", + "description": "Routes across the GPT model family: GPT-6 Luna for simple queries, GPT-5.6 Terra for medium, GPT-6 Sol for complex, GPT-6 Astra at xhigh thinking for reasoning.", "complexity_router_config": { "tiers": { - "SIMPLE": ["gpt-5.6-luna"], + "SIMPLE": ["gpt-6-luna"], "MEDIUM": ["gpt-5.6-terra"], - "COMPLEX": ["gpt-5.6-sol"], + "COMPLEX": ["gpt-6-sol"], "REASONING": ["gpt-6-astra"] }, "tier_model_configs": { diff --git a/litellm/router_strategy/complexity_router/fuse_presets.json b/litellm/router_strategy/complexity_router/fuse_presets.json index 4006366dc25..d3f9c48c0d4 100644 --- a/litellm/router_strategy/complexity_router/fuse_presets.json +++ b/litellm/router_strategy/complexity_router/fuse_presets.json @@ -1,5 +1,5 @@ { - "version": "2026-09-17-v1", + "version": "2026-09-22-v1", "models": [ { "id": "gpt-6-astra-v1", @@ -8,6 +8,20 @@ "text": "OpenAI model for demanding end-to-end work, including reasoning, coding, research, and document tasks", "sources": ["https://developers.openai.com/api/docs/models/gpt-6-astra"] }, + { + "id": "gpt-6-sol-v1", + "label": "GPT-6 Sol", + "model": "gpt-6-sol", + "text": "OpenAI model for complex coding and agentic workflows, supporting reasoning and tool calling through the Responses API", + "sources": ["https://developers.openai.com/api/docs/models/gpt-6-sol"] + }, + { + "id": "gpt-6-luna-v1", + "label": "GPT-6 Luna", + "model": "gpt-6-luna", + "text": "OpenAI model for efficient, high-volume workloads, supporting reasoning and tool calling through the Responses API", + "sources": ["https://developers.openai.com/api/docs/models/gpt-6-luna"] + }, { "id": "gpt-5.6-sol-v1", "label": "GPT-5.6 Sol", @@ -63,6 +77,13 @@ "model": "claude-fable-5-1", "text": "Anthropic model for demanding reasoning, long-running agentic coding, and multistep research, with always-on adaptive thinking", "sources": ["https://platform.claude.com/docs/en/models/fable-5-1/overview"] + }, + { + "id": "claude-opus-5-5-v1", + "label": "Claude Opus 5.5", + "model": "claude-opus-5-5", + "text": "Anthropic model for complex reasoning and agentic work, supporting adaptive thinking and tool use", + "sources": ["https://platform.claude.com/docs/en/models/opus-5-5/overview"] } ], "harnesses": [ diff --git a/litellm/router_utils/auto_router_tuning_baseline.py b/litellm/router_utils/auto_router_tuning_baseline.py index 9699ab886b9..e87548bf6de 100644 --- a/litellm/router_utils/auto_router_tuning_baseline.py +++ b/litellm/router_utils/auto_router_tuning_baseline.py @@ -10,12 +10,10 @@ from pydantic import ValidationError from litellm.router_strategy.complexity_router.config import ComplexityRouterConfig -TUNING_BASELINE_PARAM_NAME: Final = "auto_router_tuning_baseline_v2" +# v2 hashes combine models and scoring rules; a new snapshot is required to separate them. +TUNING_BASELINE_PARAM_NAME: Final = "auto_router_tuning_baseline_v3" HEURISTIC_V1_TUNING_FIELDS: Final = ( - "tiers", - "tier_model_configs", - "classifier_type", "tier_boundaries", "reasoning_override_min_score", "token_thresholds", @@ -49,8 +47,10 @@ def tuning_fingerprint(complexity_router_config: object) -> str | None: validated: Final = ComplexityRouterConfig.model_validate(raw) except ValidationError: return None - supplied: Final = ((_TUNING_FIELD_SET - frozenset(("tier_model_configs",))) & frozenset(raw)) | ( - frozenset(("tier_model_configs",)) if validated.tier_model_configs else frozenset() + # The UI always writes this built-in marker. Freeze its spelling so future defaults cannot change recorded hashes. + default_escalation: Final = validated.escalation_keywords in (None, ["LITELLM ESCALATE"]) + supplied: Final = (_TUNING_FIELD_SET & frozenset(raw)) - ( + frozenset(("escalation_keywords",)) if default_escalation else frozenset() ) payload: Final = validated.model_dump( mode="json", @@ -148,9 +148,9 @@ def tuning_limit_violation(*, held: int, limit: int | None) -> str | None: if limit is None or held <= limit: return None return ( - f"At most {limit} auto-router(s) with changed heuristic scorer settings or tier models can be modified " + f"At most {limit} auto-router(s) with changed heuristic scoring rules can be modified " "without an auto-router license. Keep this router on its recorded settings, or revert the other changed " - "router to its baseline, or remove one of them." + "router to its baseline, or remove one of them. Selecting models does not use this allowance." ) diff --git a/litellm/types/management_endpoints/auto_router_endpoints.py b/litellm/types/management_endpoints/auto_router_endpoints.py index 93ea925bd9e..334ca0dfb08 100644 --- a/litellm/types/management_endpoints/auto_router_endpoints.py +++ b/litellm/types/management_endpoints/auto_router_endpoints.py @@ -44,6 +44,25 @@ class ComplexityRouterConfigValidationResponse(BaseModel): error: str | None = None +class AutoRouterAvailabilityRequest(BaseModel): + team_id: str | None = None + saved_model_id: str | None = None + complexity_router_config: Mapping[str, object] | None = None + + +class AutoRouterAllowance(BaseModel): + key: str + limit: int | None + remaining: int | None + used_by_this_router: bool = False + available: bool = True + + +class AutoRouterAvailabilityResponse(BaseModel): + allowances: tuple[AutoRouterAllowance, ...] + error: str | None = None + + class AutoRouterRoutingTestRequest(BaseModel): """A single request to classify against a complexity-router config that need not be saved yet. diff --git a/tests/test_litellm/proxy/management_endpoints/test_auto_router_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_auto_router_endpoints.py index a282ae731dd..ff3d19e8637 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_auto_router_endpoints.py +++ b/tests/test_litellm/proxy/management_endpoints/test_auto_router_endpoints.py @@ -723,11 +723,13 @@ class TestAutoRouterBenchmarks: def test_savings_compare_only_the_current_estimated_cohort(self, estimated_turns: int) -> None: from litellm.proxy.management_endpoints.auto_router_endpoints import _benchmark_totals - row: Final = self.ROW.model_copy(update={ - "savings_estimated_turns": estimated_turns, - "savings_estimated_actual_spend": 2.0 if estimated_turns else 0.0, - "savings_estimated_saved_spend": -0.5 if estimated_turns else 0.0, - }) + row: Final = self.ROW.model_copy( + update={ + "savings_estimated_turns": estimated_turns, + "savings_estimated_actual_spend": 2.0 if estimated_turns else 0.0, + "savings_estimated_saved_spend": -0.5 if estimated_turns else 0.0, + } + ) totals: Final = _benchmark_totals(row) assert totals.spend == 10.0 assert totals.savings_estimated_turns == estimated_turns @@ -755,10 +757,16 @@ class TestAutoRouterBenchmarks: _summed_agg_row, ) - other = self.ROW.model_copy(update={ - "router_name": "auto-2", "sessions": 1, "turns": 10, "spend": 0.0, - "savings_estimated_turns": 10, "savings_estimated_actual_spend": 0.0, - }) + other = self.ROW.model_copy( + update={ + "router_name": "auto-2", + "sessions": 1, + "turns": 10, + "spend": 0.0, + "savings_estimated_turns": 10, + "savings_estimated_actual_spend": 0.0, + } + ) summed = _summed_agg_row([self.ROW, other]) totals = _benchmark_totals(summed) assert summed.sessions == 5 @@ -1091,18 +1099,27 @@ class TestAutoRouterSession: return lookups @pytest.mark.asyncio - @pytest.mark.parametrize("turns, estimated", [(3, True), (10, True), (10, False)], ids=["full", "partial", "legacy"]) + @pytest.mark.parametrize( + "turns, estimated", [(3, True), (10, True), (10, False)], ids=["full", "partial", "legacy"] + ) async def test_a_key_reads_its_own_session_with_the_baseline_its_turns_were_priced_against( - self, monkeypatch: pytest.MonkeyPatch, turns: int, estimated: bool, + self, + monkeypatch: pytest.MonkeyPatch, + turns: int, + estimated: bool, ) -> None: from litellm.proxy.management_endpoints.auto_router_endpoints import get_auto_router_session caller = UserAPIKeyAuth(api_key="sk-caller") - row: Final = {key: value for key, value in self.ROW.items() if estimated or not key.startswith("savings_estimated_")} + row: Final = { + key: value for key, value in self.ROW.items() if estimated or not key.startswith("savings_estimated_") + } spend: Final = 0.14 if turns == 3 else 10.0 if estimated and turns != 3: row["savings_estimated_saved_spend"] = -0.04 - self._rig(monkeypatch, [{**row, "api_key": caller.api_key, "session_id": "sess-1", "turns": turns, "spend": spend}]) + self._rig( + monkeypatch, [{**row, "api_key": caller.api_key, "session_id": "sess-1", "turns": turns, "spend": spend}] + ) response = await get_auto_router_session(user_api_key_dict=caller, session_id="sess-1") assert response.model_dump() == { "session_id": "sess-1", @@ -1159,10 +1176,18 @@ class TestAutoRouterSession: from litellm.proxy.management_endpoints.auto_router_endpoints import get_auto_router_session priced = {"anthropic/claude-opus-5": 2, "anthropic/claude-sonnet-5": 1} - self._rig(monkeypatch, [{ - **self.ROW, "api_key": ADMIN.api_key, "session_id": "s", - "baseline_models": {"old-baseline": 100}, "savings_estimated_baseline_models": priced, - }]) + self._rig( + monkeypatch, + [ + { + **self.ROW, + "api_key": ADMIN.api_key, + "session_id": "s", + "baseline_models": {"old-baseline": 100}, + "savings_estimated_baseline_models": priced, + } + ], + ) response = await get_auto_router_session(user_api_key_dict=ADMIN, session_id="s") assert response.baseline_model == "anthropic/claude-opus-5" assert response.baseline_models == priced @@ -3562,3 +3587,97 @@ async def test_start_shadow_eval_seeds_a_zero_funnel_row_per_leg(monkeypatch: py if "group_id" in call.kwargs.get("where", {}) ] assert group_reads == [] + + +@pytest.mark.asyncio +async def test_availability_counts_db_and_yaml_without_disclosing_router_names(monkeypatch): + from litellm.models.model import LiteLLM_ProxyModelTable + from litellm.proxy.management_helpers.auto_router_availability import build_auto_router_catalog + from litellm.types.management_endpoints.auto_router_endpoints import AutoRouterAvailabilityRequest + + row = LiteLLM_ProxyModelTable( + model_id="db-router", + model_name="private-team-router", + created_by="someone-else", + litellm_params={ + "model": "auto_router/complexity_router", + "complexity_router_config": {"classifier_type": "heuristic_v2"}, + }, + ) + yaml_row = { + "model_name": "private-yaml-router", + "litellm_params": { + "model": "auto_router/complexity_router", + "complexity_router_config": {"classifier_type": "capability"}, + }, + } + find_many = AsyncMock(side_effect=AssertionError("Availability must not query the model table")) + monkeypatch.setattr( + proxy_server, + "prisma_client", + SimpleNamespace(db=SimpleNamespace(litellm_proxymodeltable=SimpleNamespace(find_many=find_many))), + ) + monkeypatch.setattr(proxy_server.proxy_config, "auto_router_db_catalog", build_auto_router_catalog((row,))) + monkeypatch.setattr(proxy_server, "llm_router", SimpleNamespace(config_deployments=lambda: (yaml_row,))) + monkeypatch.setattr(proxy_server, "_license_check", SimpleNamespace(auto_router_capability_limit=lambda: 1)) + monkeypatch.setattr(proxy_server, "heuristic_v1_tuning_baselines", {}) + result = await auto_router_endpoints.get_auto_router_availability(AutoRouterAvailabilityRequest(), ADMIN) + assert {slot.key: slot.remaining for slot in result.allowances} == { + "heuristic_v2": 0, + "capability": 0, + "llm_v2": 1, + "tier_or_classifier_prompt": 1, + "heuristic_tuning": 1, + } + assert "private" not in result.model_dump_json() + edit = await auto_router_endpoints.get_auto_router_availability( + AutoRouterAvailabilityRequest( + saved_model_id="db-router", complexity_router_config={"classifier_type": "heuristic_v2"} + ), + ADMIN, + ) + assert edit.allowances[0].used_by_this_router + assert edit.allowances[0].remaining == 1 + assert edit.error is None + find_many.assert_not_awaited() + + +@pytest.mark.asyncio +async def test_availability_denies_another_teams_edit_exemption(monkeypatch): + from litellm.models.model import LiteLLM_ProxyModelTable + from litellm.proxy.management_helpers.auto_router_availability import build_auto_router_catalog + from litellm.types.management_endpoints.auto_router_endpoints import AutoRouterAvailabilityRequest + + row = LiteLLM_ProxyModelTable( + model_id="other-router", + model_name="other", + created_by="other", + model_info={"team_id": "other-team"}, + litellm_params={"model": "auto_router/complexity_router"}, + ) + find_many = AsyncMock(side_effect=AssertionError("Availability must not query the model table")) + monkeypatch.setattr( + proxy_server, + "prisma_client", + SimpleNamespace(db=SimpleNamespace(litellm_proxymodeltable=SimpleNamespace(find_many=find_many))), + ) + monkeypatch.setattr(proxy_server.proxy_config, "auto_router_db_catalog", build_auto_router_catalog((row,))) + monkeypatch.setattr(proxy_server, "llm_router", SimpleNamespace(config_deployments=lambda: ())) + monkeypatch.setattr(auto_router_endpoints, "_authorize_router_dry_run", AsyncMock(return_value=None)) + with pytest.raises(HTTPException) as error: + await auto_router_endpoints.get_auto_router_availability( + AutoRouterAvailabilityRequest(team_id="own-team", saved_model_id="other-router"), + UserAPIKeyAuth(user_role=LitellmUserRoles.INTERNAL_USER, user_id="owner"), + ) + assert error.value.status_code == 403 + + +@pytest.mark.asyncio +async def test_availability_waits_for_the_first_complete_catalog(monkeypatch): + from litellm.types.management_endpoints.auto_router_endpoints import AutoRouterAvailabilityRequest + + monkeypatch.setattr(proxy_server.proxy_config, "auto_router_db_catalog", None) + monkeypatch.setattr(proxy_server, "llm_router", SimpleNamespace(config_deployments=lambda: ())) + with pytest.raises(HTTPException) as error: + await auto_router_endpoints.get_auto_router_availability(AutoRouterAvailabilityRequest(), ADMIN) + assert error.value.status_code == 503 diff --git a/tests/test_litellm/proxy/management_endpoints/test_model_management_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_model_management_endpoints.py index bd252169131..8d618f4699b 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_model_management_endpoints.py +++ b/tests/test_litellm/proxy/management_endpoints/test_model_management_endpoints.py @@ -3,6 +3,7 @@ import asyncio import contextlib import json from collections.abc import Iterator, Mapping +from types import SimpleNamespace from typing import Dict, Final, Optional from unittest.mock import AsyncMock, MagicMock, patch @@ -1222,6 +1223,117 @@ class TestDeleteModelClearsRouterRegistry: assert mock_router.complexity_routers.get("shared-name") is config_router +@pytest.fixture +def deleted_auto_router_catalog(monkeypatch): + from litellm.proxy import proxy_server + from litellm.proxy.management_helpers.auto_router_availability import build_auto_router_catalog + + rows = tuple( + LiteLLM_ProxyModelTable( + model_id=model_id, + model_name=f"model_name_{team_id}_{model_id}", + litellm_params={ + "model": "auto_router/complexity_router", + "complexity_router_config": {"classifier_type": classifier}, + }, + model_info={"id": model_id, "team_id": team_id}, + created_by="admin", + updated_by="admin", + blocked=True, + ) + for model_id, team_id, classifier in ( + ("deleted-router", "deleted-team", "heuristic_v2"), + ("surviving-router", "surviving-team", "llm_v2"), + ) + ) + config = proxy_server.ProxyConfig() + config.auto_router_db_catalog = build_auto_router_catalog(rows) + monkeypatch.setattr(proxy_server, "proxy_config", config) + monkeypatch.setattr(proxy_server, "MODEL_RECONCILE_LOCK", asyncio.Lock()) + monkeypatch.setattr(proxy_server, "llm_router", Router(model_list=[])) + monkeypatch.setattr(proxy_server, "_license_check", SimpleNamespace(auto_router_capability_limit=lambda: 1)) + monkeypatch.setattr(proxy_server, "heuristic_v1_tuning_baselines", {}) + return config, rows + + +class TestDeletedAutoRouterAvailability: + @pytest.mark.asyncio + @pytest.mark.parametrize("delete_succeeds,has_router", ((True, True), (True, False), (False, True))) + async def test_single_delete_releases_allowance_only_after_success( + self, monkeypatch, deleted_auto_router_catalog, delete_succeeds, has_router + ): + from litellm.proxy import proxy_server + from litellm.proxy.management_endpoints.auto_router_endpoints import get_auto_router_availability + from litellm.proxy.management_endpoints.model_management_endpoints import ModelInfoDelete, delete_model + from litellm.types.management_endpoints.auto_router_endpoints import AutoRouterAvailabilityRequest + + config, rows = deleted_auto_router_catalog + original = config.auto_router_db_catalog + row = rows[0].model_copy(update={"model_info": {"id": rows[0].model_id}}) + table = SimpleNamespace( + find_unique=AsyncMock(return_value=row), + delete=AsyncMock(return_value=row, side_effect=None if delete_succeeds else RuntimeError("delete failed")), + ) + prisma = SimpleNamespace( + db=SimpleNamespace(litellm_proxymodeltable=table, query_raw=AsyncMock(return_value=[])) + ) + monkeypatch.setattr(proxy_server, "prisma_client", prisma) + monkeypatch.setattr(proxy_server, "store_model_in_db", True) + admin = UserAPIKeyAuth(user_id="admin", user_role=LitellmUserRoles.PROXY_ADMIN) + request = AutoRouterAvailabilityRequest(complexity_router_config={"classifier_type": "heuristic_v2"}) + before = await get_auto_router_availability(request, admin) + assert before.error is not None + if not has_router: + monkeypatch.setattr(proxy_server, "llm_router", None) + + if not delete_succeeds: + with pytest.raises(ProxyException, match="delete failed"): + await delete_model(ModelInfoDelete(id=row.model_id), admin) + assert config.auto_router_db_catalog == original + return + + await delete_model(ModelInfoDelete(id=row.model_id), admin) + monkeypatch.setattr(proxy_server, "llm_router", Router(model_list=[])) + after = await get_auto_router_availability(request, admin) + assert after.error is None + assert {slot.key: slot.remaining for slot in after.allowances} == { + "heuristic_v2": 1, + "capability": 1, + "llm_v2": 0, + "tier_or_classifier_prompt": 1, + "heuristic_tuning": 1, + } + + @pytest.mark.asyncio + @pytest.mark.parametrize("has_router", (True, False)) + async def test_team_delete_releases_only_its_routers_allowance( + self, monkeypatch, deleted_auto_router_catalog, has_router + ): + from litellm.proxy import proxy_server + from litellm.proxy.management_endpoints.auto_router_endpoints import get_auto_router_availability + from litellm.types.management_endpoints.auto_router_endpoints import AutoRouterAvailabilityRequest + + _, rows = deleted_auto_router_catalog + prisma = _TxPrismaClient(rows) + deleted = await delete_team_models( + team_ids=["deleted-team"], prisma_client=prisma, llm_router=proxy_server.llm_router if has_router else None + ) + + assert deleted == ["deleted-router"] + after = await get_auto_router_availability( + AutoRouterAvailabilityRequest(complexity_router_config={"classifier_type": "heuristic_v2"}), + UserAPIKeyAuth(user_id="admin", user_role=LitellmUserRoles.PROXY_ADMIN), + ) + assert after.error is None + assert {slot.key: slot.remaining for slot in after.allowances} == { + "heuristic_v2": 1, + "capability": 1, + "llm_v2": 0, + "tier_or_classifier_prompt": 1, + "heuristic_tuning": 1, + } + + class TestUpdateModel: """ Tests for the update_model (POST /model/update) handler. @@ -5274,7 +5386,7 @@ class TestDeleteEvictionsHoldTheReconcileLock: """ @staticmethod - async def _assert_evicts_under_lock(monkeypatch, call_endpoint, model_id: str) -> None: + async def _assert_evicts_under_lock(monkeypatch, call_endpoint, model_id: str, config) -> None: """Run ``call_endpoint`` with the lock already held and assert it blocks. Holding MODEL_RECONCILE_LOCK stands in for a reconcile that is mid-flight. If @@ -5291,6 +5403,7 @@ class TestDeleteEvictionsHoldTheReconcileLock: """ lock = asyncio.Lock() monkeypatch.setattr("litellm.proxy.proxy_server.MODEL_RECONCILE_LOCK", lock) + stale_catalog = config.auto_router_db_catalog async with lock: task = asyncio.create_task(call_endpoint()) @@ -5301,16 +5414,19 @@ class TestDeleteEvictionsHoldTheReconcileLock: f"deleting {model_id} did not wait for MODEL_RECONCILE_LOCK -- an " f"in-flight reconcile can resurrect the deployment it just evicted" ) + config.auto_router_db_catalog = stale_catalog await asyncio.wait_for(task, timeout=5) + assert tuple(row.model_id for row in config.auto_router_db_catalog) == ("surviving-router",) @pytest.mark.asyncio - async def test_delete_model_waits_for_an_in_flight_reconcile(self, monkeypatch): + async def test_delete_model_waits_for_an_in_flight_reconcile(self, monkeypatch, deleted_auto_router_catalog): from litellm.proxy.management_endpoints.model_management_endpoints import ( ModelInfoDelete, delete_model, ) - model_id = "m-doomed" + config, rows = deleted_auto_router_catalog + model_id = rows[0].model_id row = MagicMock() row.model_dump.return_value = { "model_name": "gpt-4o", @@ -5347,16 +5463,17 @@ class TestDeleteEvictionsHoldTheReconcileLock: ), ) - await self._assert_evicts_under_lock(monkeypatch, call, model_id) + await self._assert_evicts_under_lock(monkeypatch, call, model_id, config) router.delete_deployment.assert_called_once_with(id=model_id) @pytest.mark.asyncio - async def test_delete_team_models_waits_for_an_in_flight_reconcile(self, monkeypatch): + async def test_delete_team_models_waits_for_an_in_flight_reconcile(self, monkeypatch, deleted_auto_router_catalog): from litellm.proxy.management_endpoints.model_management_endpoints import ( delete_team_models, ) - model_id = "m-team-doomed" + config, rows = deleted_auto_router_catalog + model_id = rows[0].model_id router = MagicMock() router.delete_deployment = MagicMock(return_value=True) @@ -5392,7 +5509,7 @@ class TestDeleteEvictionsHoldTheReconcileLock: team_ids=["team-1"], prisma_client=prisma, llm_router=router ) - await self._assert_evicts_under_lock(monkeypatch, call, model_id) + await self._assert_evicts_under_lock(monkeypatch, call, model_id, config) router.delete_deployment.assert_called_once_with(id=model_id) @@ -6092,7 +6209,8 @@ class TestStrategyRouterWriteValidation: _TUNED_A = {"classifier_type": "heuristic", "tiers": {"SIMPLE": "gpt-4o-mini", "MEDIUM": "gpt-4o"}} _TUNED_A_EDITED = {**_TUNED_A, "dimension_weights": {"codePresence": 0.9}} _TUNED_B = {"classifier_type": "heuristic", "tiers": {"SIMPLE": "gpt-4o-mini", "MEDIUM": "gpt-4.1"}} - _TUNED_B_EDITED = {**_TUNED_B, "tiers": {"SIMPLE": "gpt-4o", "MEDIUM": "gpt-4.1"}} + _TUNED_B_EDITED = {**_TUNED_B, "code_keywords": ["internal-api"]} + _MODELS_ONLY_B = {**_TUNED_B, "tiers": {"SIMPLE": "fast-model", "MEDIUM": "capable-model"}} @staticmethod def _db_router_row(model_id: str, config: Mapping[str, object]) -> dict[str, object]: @@ -6110,7 +6228,9 @@ class TestStrategyRouterWriteValidation: (1, ["a", "b"], {"a": "_TUNED_A", "b": "_TUNED_B"}, "a", "_TUNED_A_EDITED", "allowed"), (1, ["a", "b"], {"a": "_TUNED_A_EDITED", "b": "_TUNED_B"}, "a", "_TUNED_A_EDITED", "allowed"), (1, ["a", "b"], {"a": "_TUNED_A_EDITED", "b": "_TUNED_B"}, "b", "_TUNED_B_EDITED", "refused"), - (1, ["a", "b"], {"a": "_TUNED_A_EDITED", "b": "_TUNED_B"}, "c", "_TUNED_B", "refused"), + (1, ["a", "b"], {"a": "_TUNED_A_EDITED", "b": "_TUNED_B"}, "c", "_TUNED_B_EDITED", "refused"), + (1, ["a", "b"], {"a": "_TUNED_A_EDITED", "b": "_TUNED_B"}, "c", "_TUNED_B", "allowed"), + (1, ["a", "b"], {"a": "_TUNED_A_EDITED", "b": "_TUNED_B"}, "b", "_MODELS_ONLY_B", "allowed"), (1, ["a", "b"], {"a": "_TUNED_A_EDITED", "b": "_TUNED_B"}, "b", "_TUNED_B", "allowed"), (None, ["a", "b"], {"a": "_TUNED_A_EDITED", "b": "_TUNED_B"}, "b", "_TUNED_B_EDITED", "allowed"), (1, [], {}, "c", "_TUNED_B", "allowed"), @@ -6138,6 +6258,7 @@ class TestStrategyRouterWriteValidation: "_TUNED_A_EDITED": self._TUNED_A_EDITED, "_TUNED_B": self._TUNED_B, "_TUNED_B_EDITED": self._TUNED_B_EDITED, + "_MODELS_ONLY_B": self._MODELS_ONLY_B, } baselines = snapshot_tuning_baselines( [self._db_router_row(row_id, configs["_TUNED_A" if row_id == "a" else "_TUNED_B"]) for row_id in baseline_rows] @@ -6172,7 +6293,7 @@ class TestStrategyRouterWriteValidation: async with _auto_router_capability_slot(fake, effective_params=effective_params, model_id=candidate_id): pass assert exc_info.value.status_code == 403 - assert "changed heuristic scorer settings or tier models" in str(exc_info.value.detail) + assert "changed heuristic scoring rules" in str(exc_info.value.detail) assert "'auto_router' feature lifts the limit" in str(exc_info.value.detail) return async with _auto_router_capability_slot(fake, effective_params=effective_params, model_id=candidate_id) as table: @@ -6222,13 +6343,13 @@ class TestStrategyRouterWriteValidation: model_params=Deployment( model_name="second-tuned", litellm_params=LiteLLM_Params( - model="auto_router/complexity_router", complexity_router_config=self._TUNED_B + model="auto_router/complexity_router", complexity_router_config=self._TUNED_B_EDITED ), ), user_api_key_dict=admin, ) assert exc_info.value.code == "403" - assert "changed heuristic scorer settings or tier models" in str(exc_info.value.message) + assert "changed heuristic scoring rules" in str(exc_info.value.message) fake.tx_obj.litellm_proxymodeltable.create.assert_not_awaited() fake.litellm_proxymodeltable.create.assert_not_awaited() diff --git a/tests/test_litellm/proxy/management_helpers/test_auto_router_availability.py b/tests/test_litellm/proxy/management_helpers/test_auto_router_availability.py new file mode 100644 index 00000000000..027930d9ebb --- /dev/null +++ b/tests/test_litellm/proxy/management_helpers/test_auto_router_availability.py @@ -0,0 +1,196 @@ +from collections.abc import Mapping +from typing import Final +from types import SimpleNamespace + +from litellm.proxy.common_utils.encrypt_decrypt_utils import encrypt_value_helper + +import pytest + +from litellm.proxy.management_helpers.auto_router_availability import ( + auto_router_availability, + build_auto_router_catalog, +) +from litellm.router_utils.auto_router_tuning_baseline import snapshot_tuning_baselines + + +def deployment( + model_id: str, + classifier: str, + *, + model: str = "solver", + tuned: bool = False, + config: Mapping[str, object] | None = None, +) -> Mapping[str, object]: + return { + "model_name": model_id, + "model_info": {"id": model_id, "db_model": True}, + "litellm_params": { + "model": "auto_router/complexity_router", + "complexity_router_config": { + "classifier_type": classifier, + "tiers": {"SIMPLE": [model]}, + **({"code_keywords": ["internal-api"]} if tuned else {}), + **(config or {}), + }, + }, + } + + +@pytest.mark.parametrize("classifier", ("heuristic_v2", "capability", "llm_v2")) +def test_occupied_allowance_blocks_new_router_but_not_owner(classifier: str) -> None: + existing: Final = deployment("existing", classifier) + candidate: Final = deployment("new", classifier) + new: Final = auto_router_availability(others=(existing,), existing=None, candidate=candidate, baselines={}, limit=1) + edit: Final = auto_router_availability(others=(), existing=existing, candidate=existing, baselines={}, limit=1) + new_slot: Final = next(slot for slot in new.allowances if slot.key == classifier) + edit_slot: Final = next(slot for slot in edit.allowances if slot.key == classifier) + assert (new_slot.remaining, new_slot.used_by_this_router, new.error is not None) == (0, False, True) + assert (edit_slot.remaining, edit_slot.used_by_this_router, edit.error) == (1, True, None) + + +def test_edit_does_not_exempt_another_classifier_allowance() -> None: + existing: Final = deployment("existing", "capability") + result: Final = auto_router_availability( + others=(deployment("other", "llm_v2"),), + existing=existing, + candidate=deployment("existing", "llm_v2"), + baselines={}, + limit=1, + ) + assert result.error is not None + assert next(slot for slot in result.allowances if slot.key == "llm_v2").remaining == 0 + + +def test_model_selection_does_not_claim_occupied_scoring_allowance() -> None: + original: Final = deployment("legacy", "heuristic") + changed: Final = deployment("other", "heuristic", tuned=True) + baselines: Final = snapshot_tuning_baselines((original,)) + unchanged: Final = auto_router_availability( + others=(changed,), + existing=original, + candidate=original, + baselines=baselines, + limit=1, + ) + edited: Final = auto_router_availability( + others=(changed,), + existing=original, + candidate=deployment("legacy", "heuristic", model="new"), + baselines=baselines, + limit=1, + ) + assert unchanged.error is None + assert next(slot for slot in unchanged.allowances if slot.key == "heuristic_tuning").remaining == 0 + assert edited.error is None + tuned: Final = auto_router_availability( + others=(changed,), + existing=original, + candidate=deployment("legacy", "heuristic", tuned=True), + baselines=baselines, + limit=1, + ) + assert tuned.error is not None + assert "weights, thresholds, keywords, and custom dimensions" in tuned.error + + +def test_missing_baselines_are_reported_as_unknown() -> None: + result: Final = auto_router_availability( + others=(), + existing=None, + candidate=deployment("new", "heuristic"), + baselines=None, + limit=1, + ) + slot: Final = next(slot for slot in result.allowances if slot.key == "heuristic_tuning") + assert (slot.available, slot.remaining, slot.limit) == (False, None, 1) + + +def test_unlimited_entitlement_does_not_report_exhausted_allowances() -> None: + result: Final = auto_router_availability( + others=(deployment("other", "heuristic_v2"),), + existing=None, + candidate=deployment("new", "heuristic_v2"), + baselines=None, + limit=None, + ) + assert all(slot.available and slot.limit is None and slot.remaining is None for slot in result.allowances) + assert result.error is None + + +@pytest.mark.parametrize( + "customization", + ( + {"tier_definitions": [{"name": "SIMPLE"}, {"name": "AUDIT", "description": "Review risks"}]}, + {"classification_prompt": "Use the simplest sufficient tier"}, + {"classification_examples": "Review this code -> COMPLEX"}, + {"classifier_llm_config": {"model": "judge", "system_prompt": "Route by urgency"}}, + ), +) +def test_customization_owner_can_edit_models_and_restoring_defaults_clears_the_gate( + customization: Mapping[str, object], +) -> None: + owner: Final = deployment("owner", "llm", config=customization) + blocked: Final = auto_router_availability( + others=(owner,), existing=None, candidate=deployment("new", "llm", config=customization), baselines={}, limit=1 + ) + assert blocked.error is not None + assert "Custom tiers or classifier instructions" in blocked.error + edited: Final = auto_router_availability( + others=(), + existing=owner, + candidate=deployment("owner", "llm", model="new", config=customization), + baselines={}, + limit=1, + ) + assert edited.error is None + assert next(slot for slot in edited.allowances if slot.key == "tier_or_classifier_prompt").used_by_this_router + restored: Final = auto_router_availability( + others=(owner,), existing=None, candidate=deployment("new", "llm"), baselines={}, limit=1 + ) + assert restored.error is None + assert next(slot for slot in restored.allowances if slot.key == "tier_or_classifier_prompt").remaining == 0 + + +def test_restoring_tiers_does_not_exempt_a_retained_custom_prompt() -> None: + prompt: Final = {"classification_prompt": "Use the simplest sufficient tier"} + result: Final = auto_router_availability( + others=(deployment("owner", "llm", config=prompt),), + existing=None, + candidate=deployment("new", "llm", config=prompt), + baselines={}, + limit=1, + ) + assert result.error is not None + assert "Custom tiers or classifier instructions" in result.error + + +@pytest.mark.parametrize("blocked", (False, True)) +def test_catalog_keeps_unloaded_routers_and_ownership_without_provider_credentials(blocked: bool, monkeypatch) -> None: + monkeypatch.setenv("LITELLM_SALT_KEY", "catalog-test-key") + source: Final = SimpleNamespace( + model_id="saved", + created_by="owner", + model_info={"team_id": "team"}, + blocked=blocked, + litellm_params={ + "model": encrypt_value_helper("auto_router/complexity_router"), + "api_key": "private-key", + "complexity_router_config": {"classifier_type": "heuristic_v2"}, + }, + ) + provider: Final = SimpleNamespace(model_id="provider", litellm_params={"model": "openai/model"}) + catalog: Final = build_auto_router_catalog((source, provider)) + assert catalog is not None and len(catalog) == 1 + assert (catalog[0].model_id, catalog[0].team_id, catalog[0].created_by) == ("saved", "team", "owner") + assert catalog[0].deployment == { + "model_info": {"id": "saved", "db_model": True}, + "litellm_params": { + "model": "auto_router/complexity_router", + "complexity_router_config": {"classifier_type": "heuristic_v2"}, + }, + } + + +def test_catalog_distinguishes_missing_data_from_an_empty_model_table() -> None: + assert build_auto_router_catalog(()) == () + assert build_auto_router_catalog((SimpleNamespace(model_id="incomplete"),)) is None diff --git a/tests/test_litellm/proxy/proxy_server/test_lifecycle.py b/tests/test_litellm/proxy/proxy_server/test_lifecycle.py index 9954351fa2e..36d2e16d261 100644 --- a/tests/test_litellm/proxy/proxy_server/test_lifecycle.py +++ b/tests/test_litellm/proxy/proxy_server/test_lifecycle.py @@ -920,7 +920,7 @@ def test_proxy_startup_event_warns_for_global_budget_without_database(): @pytest.mark.asyncio -async def test_tuning_baseline_v2_is_created_alongside_the_legacy_row(): +async def test_tuning_baseline_v3_is_created_alongside_the_legacy_row(): from litellm.router_utils.auto_router_tuning_baseline import DEFAULT_TUNING_FINGERPRINT prisma_client = MagicMock() @@ -935,11 +935,61 @@ async def test_tuning_baseline_v2_is_created_alongside_the_legacy_row(): assert result == {'yaml:["a",[]]': DEFAULT_TUNING_FINGERPRINT} assert prisma_client.db.litellm_config.create.await_args.kwargs["data"] == { - "param_name": "auto_router_tuning_baseline_v2", + "param_name": "auto_router_tuning_baseline_v3", "param_value": json.dumps(dict(result)), } +@pytest.mark.asyncio +async def test_scorer_baseline_upgrade_preserves_existing_routers_and_is_not_refreshed_on_restart(): + from litellm.router_utils.auto_router_tuning_baseline import mutable_tuned_identities, snapshot_tuning_baselines + + deployments = [ + { + "model_name": name, + "litellm_params": { + "model": "auto_router/complexity_router", + "complexity_router_config": {"tiers": {"SIMPLE": name}, "code_keywords": [name]}, + }, + } + for name in ("a", "b") + ] + prisma_client = MagicMock() + prisma_client.db.litellm_config.find_unique = AsyncMock( + side_effect=lambda where: ( + MagicMock(param_value='{"legacy-router":"old-combined-hash"}') + if where["param_name"] == "auto_router_tuning_baseline_v2" + else None + ) + ) + prisma_client.db.litellm_config.create = AsyncMock() + + baseline = await ProxyStartupEvent._load_heuristic_v1_tuning_baselines(prisma_client, deployments) + + assert baseline == snapshot_tuning_baselines(deployments) + assert mutable_tuned_identities(deployments, baseline) == frozenset() + prisma_client.db.litellm_config.create.assert_awaited_once_with( + data={"param_name": "auto_router_tuning_baseline_v3", "param_value": json.dumps(dict(baseline))} + ) + prisma_client.db.litellm_config.find_unique.side_effect = None + prisma_client.db.litellm_config.find_unique.return_value = MagicMock(param_value=json.dumps(dict(baseline))) + changed = [ + { + "model_name": "a", + "litellm_params": { + "model": "auto_router/complexity_router", + "complexity_router_config": {"tiers": {"SIMPLE": "different-model"}, "code_keywords": ["new-rule"]}, + }, + } + ] + + reloaded = await ProxyStartupEvent._load_heuristic_v1_tuning_baselines(prisma_client, changed) + + assert reloaded == baseline + assert mutable_tuned_identities(changed, reloaded) == frozenset({'yaml:["a",[]]'}) + prisma_client.db.litellm_config.create.assert_awaited_once() + + @pytest.mark.asyncio async def test_tuning_baseline_waits_for_a_complete_db_model_census(monkeypatch): prisma_client = MagicMock() diff --git a/tests/test_litellm/proxy/proxy_server/test_proxy_config.py b/tests/test_litellm/proxy/proxy_server/test_proxy_config.py index b47cce43dcc..89cb8356289 100644 --- a/tests/test_litellm/proxy/proxy_server/test_proxy_config.py +++ b/tests/test_litellm/proxy/proxy_server/test_proxy_config.py @@ -875,9 +875,7 @@ class _ConfigTable: await asyncio.sleep(0) return _ConfigRow(param_value=value) if value is not None else None - async def upsert( - self, *, where: Mapping[str, str], data: Mapping[str, Mapping[str, str]] - ) -> _ConfigRow: + async def upsert(self, *, where: Mapping[str, str], data: Mapping[str, Mapping[str, str]]) -> _ConfigRow: param_name: Final = where["param_name"] value: Final = _CONFIG_VALUE.validate_json(data["update"]["param_value"]) self.rows[param_name] = value @@ -926,7 +924,9 @@ class _ConfigPrisma: self.db.litellm_config.upserted_param_names.append(param_name) -def _db_backed_proxy_config(monkeypatch, rows: Mapping[str, Mapping[str, JsonValue]]) -> tuple[ProxyConfig, _ConfigTable]: +def _db_backed_proxy_config( + monkeypatch, rows: Mapping[str, Mapping[str, JsonValue]] +) -> tuple[ProxyConfig, _ConfigTable]: table: Final = _ConfigTable(rows) monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", _ConfigPrisma(db=_ConfigDb(litellm_config=table))) monkeypatch.setattr("litellm.proxy.proxy_server.store_model_in_db", True) @@ -4750,9 +4750,7 @@ def test_validate_deployment_access_windows_rejects_malformed_time(): "model_name": "gpt-4o-shared", "litellm_params": {"model": "gpt-4o"}, "model_info": { - "access_windows": [ - {"start": "25:00", "end": "06:00", "timezone": "America/New_York", "team_ids": ["t"]} - ] + "access_windows": [{"start": "25:00", "end": "06:00", "timezone": "America/New_York", "team_ids": ["t"]}] }, } @@ -4767,9 +4765,7 @@ def test_validate_deployment_access_windows_rejects_unknown_timezone(): "model_name": "gpt-4o-shared", "litellm_params": {"model": "gpt-4o"}, "model_info": { - "access_windows": [ - {"start": "22:00", "end": "06:00", "timezone": "Mars/Olympus", "team_ids": ["t"]} - ] + "access_windows": [{"start": "22:00", "end": "06:00", "timezone": "Mars/Olympus", "team_ids": ["t"]}] }, } @@ -4799,3 +4795,28 @@ def test_validate_deployment_access_windows_accepts_valid_and_absent(): ) is None ) + + +@pytest.mark.asyncio +async def test_model_refresh_updates_availability_catalog_and_retains_it_on_db_failure(): + pc = ProxyConfig() + row = SimpleNamespace( + model_id="gated", + created_by="owner", + model_info={}, + litellm_params={ + "model": "auto_router/complexity_router", + "complexity_router_config": {"classifier_type": "heuristic_v2"}, + }, + ) + find_many = AsyncMock(side_effect=[[row], RuntimeError("database unavailable"), []]) + client = SimpleNamespace(db=SimpleNamespace(litellm_proxymodeltable=SimpleNamespace(find_many=find_many))) + assert pc.auto_router_db_catalog is None + assert await pc._get_models_from_db(client) == [row] + loaded = pc.auto_router_db_catalog + assert loaded is not None and loaded[0].model_id == "gated" + assert await pc._get_models_from_db(client) is None + assert pc.auto_router_db_catalog == loaded + assert await pc._get_models_from_db(client) == [] + assert pc.auto_router_db_catalog == () + assert find_many.await_count == 3 diff --git a/tests/test_litellm/proxy/public_endpoints/test_public_endpoints.py b/tests/test_litellm/proxy/public_endpoints/test_public_endpoints.py index 0f1ff3b024d..0dec44af402 100644 --- a/tests/test_litellm/proxy/public_endpoints/test_public_endpoints.py +++ b/tests/test_litellm/proxy/public_endpoints/test_public_endpoints.py @@ -1218,13 +1218,13 @@ def test_get_autorouter_presets_local_mode_serves_bundled_catalog( assert "anthropic_family" in payload assert payload["1m_context"]["complexity_router_config"]["classifier_type"] == "heuristic_v2" assert payload["1m_context"]["complexity_router_config"]["tiers"] == { - "SIMPLE": ["gpt-5.6-luna"], + "SIMPLE": ["gpt-6-luna"], "MEDIUM": ["gpt-5.6-terra"], - "COMPLEX": ["gpt-5.6-sol"], - "REASONING": ["claude-opus-5"], + "COMPLEX": ["gpt-6-sol"], + "REASONING": ["claude-opus-5-5"], } assert payload["1m_context"]["complexity_router_config"]["tier_model_configs"] == { - "REASONING": [{"model_name": "claude-opus-5", "litellm_params": {"reasoning_effort": "high"}}] + "REASONING": [{"model_name": "claude-opus-5-5", "litellm_params": {"reasoning_effort": "high"}}] } for preset in payload.values(): assert isinstance(preset["label"], str) diff --git a/tests/test_litellm/router_utils/test_auto_router_tuning_baseline.py b/tests/test_litellm/router_utils/test_auto_router_tuning_baseline.py index 75c115cd3ab..9307668d66f 100644 --- a/tests/test_litellm/router_utils/test_auto_router_tuning_baseline.py +++ b/tests/test_litellm/router_utils/test_auto_router_tuning_baseline.py @@ -33,21 +33,6 @@ _HISTORICAL_FINGERPRINTS: Final = ( {"custom_dimensions": [{"name": "sqlDdl", "weight": 0.4, "patterns": [r"\bCREATE\s{1,4}TABLE\b"]}]}, "814ce0017fc7f60a160b262f658d910e9bdf784e6139a4ba4f1e2657aa203950", ), - ( - { - "tiers": _TIERS, - "dimension_weights": {"codePresence": 0.3}, - "custom_dimensions": [ - { - "name": "internalFrameworks", - "weight": 0.2, - "keywords": ["orbitmesh", "fluxgate"], - "patterns": [r"\bALTER\s{1,4}TABLE\b"], - } - ], - }, - "38970dc9224e265ab38c89674563d8d0537822591f9239b45251db6f5ca6cc39", - ), ) @@ -78,11 +63,9 @@ class TestTuningFingerprint: {"tiers": {"SIMPLE": "x"}} ) - @pytest.mark.parametrize("field", sorted(set(HEURISTIC_V1_TUNING_FIELDS) - {"tier_model_configs"})) + @pytest.mark.parametrize("field", HEURISTIC_V1_TUNING_FIELDS) def test_every_tuning_field_changes_the_fingerprint(self, field: str) -> None: samples: dict[str, object] = { - "tiers": _ALT_TIERS, - "classifier_type": "heuristic_first", "tier_boundaries": {"simple_medium": 0.2, "medium_complex": 0.4, "complex_reasoning": 0.7}, "reasoning_override_min_score": 0.05, "token_thresholds": {"simple": 20, "complex": 500}, @@ -97,9 +80,6 @@ class TestTuningFingerprint: "keyword_tier_rules": [{"keywords": ["urgent"], "tier": "COMPLEX"}], } config: dict[str, object] = {field: samples[field]} - if field == "classifier_type": - config["heuristic_first_max_tier"] = "MEDIUM" - config["classifier_llm_config"] = {"model": "judge"} assert tuning_fingerprint(config) != DEFAULT_TUNING_FINGERPRINT def test_explicit_empty_tier_model_configs_follow_omission(self) -> None: @@ -126,12 +106,33 @@ class TestTuningFingerprint: != historical ) - def test_tier_model_overrides_change_the_fingerprint(self) -> None: + def test_tier_model_overrides_do_not_change_the_fingerprint(self) -> None: plain = tuning_fingerprint({"tiers": {"SIMPLE": "x"}}) with_override = tuning_fingerprint( {"tiers": {"SIMPLE": {"model_name": "x", "litellm_params": {"temperature": 0.1}}}} ) - assert plain != with_override + assert plain == with_override == DEFAULT_TUNING_FINGERPRINT + + @pytest.mark.parametrize("classifier_type", ("heuristic", "heuristic_first", "hybrid")) + def test_model_selection_and_classifier_switching_do_not_claim_tuning(self, classifier_type: str) -> None: + config: Final = { + "classifier_type": classifier_type, + **({"classifier_llm_config": {"model": "judge"}} if classifier_type != "heuristic" else {}), + **({"heuristic_first_max_tier": "MEDIUM"} if classifier_type == "heuristic_first" else {}), + **({"hybrid_boundary_margin": 0.1} if classifier_type == "hybrid" else {}), + "tiers": _ALT_TIERS, + "escalation_keywords": ["LITELLM ESCALATE"], + "tier_model_configs": {"COMPLEX": [{"model_name": "other-strong", "litellm_params": {"temperature": 0.1}}]}, + } + tuned: Final = _router("tuned", {"dimension_weights": {"codePresence": 0.9}}) + model_only: Final = _router("model-only", {"tiers": _TIERS}) + candidate: Final = _router("another", config) + assert tuning_fingerprint(config) == DEFAULT_TUNING_FINGERPRINT + assert tuning_quota_violation(candidate=candidate, others=(tuned, model_only), baselines={}, limit=1) is None + + def test_disabling_or_replacing_escalation_is_still_a_custom_rule(self) -> None: + assert tuning_fingerprint({"escalation_keywords": []}) != DEFAULT_TUNING_FINGERPRINT + assert tuning_fingerprint({"escalation_keywords": ["USE A STRONGER MODEL"]}) != DEFAULT_TUNING_FINGERPRINT def test_non_tuning_fields_do_not_change_the_fingerprint(self) -> None: assert ( @@ -230,17 +231,18 @@ class TestQuota: def test_router_added_after_snapshot_is_mutable_only_when_tuned(self) -> None: baselines = snapshot_tuning_baselines([_router("a", {"tiers": _TIERS})]) assert mutable_tuned_identities([_router("new", {})], baselines) == frozenset() - assert mutable_tuned_identities([_router("new", {"tiers": _TIERS})], baselines) == { - router_identity(_router("new", {})) - } + assert mutable_tuned_identities([_router("new", {"tiers": _TIERS})], baselines) == frozenset() + assert mutable_tuned_identities( + [_router("new", {"tiers": _TIERS, "code_keywords": ["internal-api"]})], baselines + ) == {router_identity(_router("new", {}))} def test_quota_matrix(self) -> None: legacy_a = _router("a", {"tiers": _TIERS}) legacy_b = _router("b", {"tiers": _ALT_TIERS}) baselines = snapshot_tuning_baselines([legacy_a, legacy_b]) edited_a = _router("a", {"tiers": _TIERS, "dimension_weights": {"codePresence": 0.9}}) - edited_b = _router("b", {"tiers": _TIERS}) - new_c = _router("c", {"tiers": _TIERS}) + edited_b = _router("b", {"tiers": _TIERS, "code_keywords": ["internal-api"]}) + new_c = _router("c", {"tiers": _TIERS, "code_keywords": ["internal-api"]}) assert tuning_quota_violation(candidate=edited_a, others=[legacy_b], baselines=baselines, limit=1) is None assert ( @@ -260,7 +262,7 @@ class TestQuota: legacy_a = _router("a", {"tiers": _TIERS}) legacy_b = _router("b", {"tiers": _ALT_TIERS}) baselines = snapshot_tuning_baselines([legacy_a, legacy_b]) - edited_b = _router("b", {"tiers": _TIERS}) + edited_b = _router("b", {"tiers": _TIERS, "code_keywords": ["internal-api"]}) assert tuning_quota_violation(candidate=edited_b, others=[legacy_a], baselines=baselines, limit=1) is None assert ( tuning_quota_violation(candidate=edited_b, others=[legacy_a, edited_b], baselines=baselines, limit=1) @@ -304,5 +306,6 @@ class TestQuota: assert message is not None assert "At most 1 auto-router(s)" in message assert "revert the other changed router to its baseline" in message + assert "Selecting models does not use this allowance" in message assert tuning_limit_violation(held=1, limit=1) is None assert tuning_limit_violation(held=5, limit=None) is None diff --git a/ui/litellm-dashboard/src/components/add_model/AutoRouterAvailability.tsx b/ui/litellm-dashboard/src/components/add_model/AutoRouterAvailability.tsx new file mode 100644 index 00000000000..b1233ef03b8 --- /dev/null +++ b/ui/litellm-dashboard/src/components/add_model/AutoRouterAvailability.tsx @@ -0,0 +1,165 @@ +import { createContext, useContext, useEffect, useState } from "react"; +import { useQuery, type UseQueryOptions } from "@tanstack/react-query"; +import { apiClient } from "@/components/networking"; +import { Popover, PopoverContent, PopoverTitle, PopoverTrigger } from "@/components/ui/popover"; +import type { components } from "@/lib/http/schema"; + +type Availability = components["schemas"]["AutoRouterAvailabilityResponse"]; +type Request = components["schemas"]["AutoRouterAvailabilityRequest"]; +export type Allowance = components["schemas"]["AutoRouterAllowance"]; + +type AvailabilityState = { + data?: Availability; + isPending: boolean; + isError: boolean; + isChecking?: boolean; + refetch?: () => unknown; +}; + +export const AutoRouterAvailabilityContext = createContext({ isPending: true, isError: false }); + +export const useAutoRouterAvailability = (accessToken: string, body: Request, enabled = true) => { + const serialized = JSON.stringify(body.complexity_router_config ?? null); + const [debounced, setDebounced] = useState(serialized); + useEffect(() => { + const timeout = setTimeout(() => setDebounced(serialized), 300); + return () => clearTimeout(timeout); + }, [serialized]); + const options: UseQueryOptions = { + queryKey: ["autoRouterAvailability", accessToken, body.team_id, body.saved_model_id, debounced], + queryFn: ({ signal }) => + apiClient.post("/auto_router/availability", { + accessToken, + body: { ...body, complexity_router_config: JSON.parse(debounced) }, + signal, + }), + enabled: enabled && Boolean(accessToken), + placeholderData: (previous, previousQuery) => { + const key = previousQuery?.queryKey; + return key?.[1] === accessToken && key[2] === body.team_id && key[3] === body.saved_model_id + ? previous + : undefined; + }, + refetchOnMount: "always", + staleTime: 0, + retry: false, + }; + const query = useQuery(options); + const isChecking = query.isFetching || query.isPlaceholderData || serialized !== debounced; + const saveBlockedReason = () => { + if (!enabled) return null; + if (query.isPending || isChecking) return "Checking availability"; + if (query.isError || !query.data) return "Could not check availability. Retry before saving."; + return query.data.error ?? null; + }; + return { + ...query, + isPending: query.isPending || (query.isFetching && !query.isFetchedAfterMount), + isChecking, + saveBlockedReason: saveBlockedReason(), + }; +}; + +export const allowanceLabel = (allowance?: Allowance): string | null => { + if (!allowance?.available) return "Availability unavailable"; + if (allowance.limit == null) return null; + if (allowance.used_by_this_router) return "Used by this router"; + return `${allowance.remaining} of ${allowance.limit} available`; +}; + +const availabilityLabel = (state: AvailabilityState, key: string) => { + if (state.isPending || state.isChecking) return "Checking availability"; + if (state.isError) return "Availability unavailable"; + return allowanceLabel(state.data?.allowances.find((entry) => entry.key === key)); +}; + +export const useAllowanceLabel = (key: string) => availabilityLabel(useContext(AutoRouterAvailabilityContext), key); + +export const isAllowanceExhausted = (allowance?: Allowance) => + Boolean(allowance?.available && allowance.limit != null && allowance.remaining === 0) && + !allowance?.used_by_this_router; + +export const AUTO_ROUTER_CONTACT_URL = "https://calendly.com/tin-berri/litellm-auto-router-pricing-discussion"; + +export const AutoRouterContactLink = ({ features, message }: { features?: string[]; message?: string }) => { + const state = useContext(AutoRouterAvailabilityContext); + if (state.isPending || state.isError || state.isChecking) return null; + const exhausted = state.data?.allowances.some( + (entry) => (!features || features.includes(entry.key)) && isAllowanceExhausted(entry), + ); + if (!exhausted) return null; + return ( + + {message} + + Talk to our team + + + ); +}; + +export const AutoRouterAllowanceLabel = ({ feature }: { feature: string }) => { + const label = useAllowanceLabel(feature); + return label ? ( + {label} + ) : null; +}; + +export const AutoRouterAllowanceNote = ({ feature, label }: { feature: string; label: string }) => { + const availability = useAllowanceLabel(feature); + return availability ? ( +

+ {label}: {availability} +

+ ) : null; +}; + +export const AutoRouterLimits = () => { + const state = useContext(AutoRouterAvailabilityContext); + const limits = [ + ["heuristic_v2", "Heuristic v2 routers"], + ["capability", "Capability routers"], + ["llm_v2", "Fuse v2 routers"], + ["tier_or_classifier_prompt", "Custom tiers or prompts"], + ["heuristic_tuning", "Rule-based tuning"], + ]; + return ( + + + View limits + + + Routing and customization limits +

+ Rule-based, Complexity, and Jev are unlimited with built-in settings. Choose or change tier models freely. + Customization allowances are shared across this proxy. +

+
+ {limits.map(([key, label]) => ( +
+
{label}
+
+ {availabilityLabel(state, key) ?? "Unlimited"} +
+
+ ))} +
+

+ Custom tier definitions and written classifier instructions share one allowance. Built-in prompts and + display-name changes do not use it. +

+

+ Changing scoring rules, such as weights, thresholds, keywords, or custom dimensions, uses the Rule-based + tuning allowance. It also applies to Heuristic first and Hybrid. Recorded settings on existing routers are + preserved; new routers start from built-in rules. +

+ + + + ); +}; diff --git a/ui/litellm-dashboard/src/components/add_model/AutoRouterClassifierTabs.integration.test.tsx b/ui/litellm-dashboard/src/components/add_model/AutoRouterClassifierTabs.integration.test.tsx index ac6851349ea..f843a472d15 100644 --- a/ui/litellm-dashboard/src/components/add_model/AutoRouterClassifierTabs.integration.test.tsx +++ b/ui/litellm-dashboard/src/components/add_model/AutoRouterClassifierTabs.integration.test.tsx @@ -1,7 +1,9 @@ import React, { useState } from "react"; import { describe, expect, it, vi } from "vitest"; -import { fireEvent, renderWithProviders, screen } from "../../../tests/test-utils"; +import { fireEvent, renderWithProviders, screen, waitFor, within } from "../../../tests/test-utils"; +import { selectAutoRouterOption } from "../../../tests/autoRouterSetup"; import AutoRouterClassifierTabs from "./AutoRouterClassifierTabs"; +import { AutoRouterAllowanceNote, AutoRouterAvailabilityContext } from "./AutoRouterAvailability"; import type { ComplexityRouterConfigValue } from "./ComplexityRouterConfig"; const initial: ComplexityRouterConfigValue = { @@ -9,28 +11,67 @@ const initial: ComplexityRouterConfigValue = { tiers: { SIMPLE: ["efficient"], MEDIUM: [], COMPLEX: [], REASONING: ["capable"] }, }; -function Form({ initialValue = initial }: { initialValue?: ComplexityRouterConfigValue }) { +function Form({ + initialValue = initial, + remaining = 1, + limit = 1, + ownedFeature, + availabilityState, +}: { + initialValue?: ComplexityRouterConfigValue; + remaining?: number; + limit?: number | null; + ownedFeature?: string; + availabilityState?: Partial>; +}) { const [value, setValue] = useState(initialValue); return ( - - {value.classifier_type} - + ({ + key, + limit, + remaining, + available: true, + used_by_this_router: key === ownedFeature, + }), + ), + error: null, + }, + ...availabilityState, + }} + > + + {value.classifier_type} + + ); } -describe("AutoRouterClassifierTabs", () => { - it.each(["heuristic", "heuristic_v2", "llm", "heuristic_first", "hybrid"] as const)( - "groups %s under Complexity without resetting its configuration", - (classifier_type) => { +describe("Auto-router classifier selection", () => { + it.each(["heuristic", "heuristic_v2", "llm", "heuristic_first", "hybrid", "jev"] as const)( + "shows saved %s without changing its configuration", + async (classifier_type) => { const onChange = vi.fn(); renderWithProviders( - Existing classifier settings + Existing settings , ); - expect(screen.getByRole("tab", { name: "Complexity" })).toHaveAttribute("aria-selected", "true"); - expect(screen.getByRole("tabpanel", { name: "Complexity" })).toHaveTextContent("Existing classifier settings"); - fireEvent.click(screen.getByRole("tab", { name: "Complexity" })); + const family = { + heuristic: "Heuristics", + heuristic_v2: "Heuristics", + llm: "LLM", + heuristic_first: "LLM", + hybrid: "LLM", + jev: "Jev", + }[classifier_type]; + expect(screen.getByRole("radio", { name: new RegExp(`^${family}$`) })).toBeChecked(); + fireEvent.click(screen.getByRole("radio", { name: new RegExp(`^${family}$`) })); expect(onChange).not.toHaveBeenCalled(); }, ); @@ -38,38 +79,186 @@ describe("AutoRouterClassifierTabs", () => { it.each([ ["capability", "Capability"], ["llm_v2", "Fuse v2"], - ] as const)("opens saved %s settings and switches back to local Complexity", (classifier_type, label) => { - renderWithProviders(
); - expect(screen.getByRole("tab", { name: label })).toHaveAttribute("aria-selected", "true"); - fireEvent.click(screen.getByRole("tab", { name: "Complexity" })); - expect(screen.getByRole("tab", { name: "Complexity" })).toHaveAttribute("aria-selected", "true"); - expect(screen.getByRole("status", { name: "Classifier type" })).toHaveTextContent("heuristic"); + ] as const)( + "opens saved %s and retains the LLM family when switching to Complexity", + async (classifier_type, label) => { + renderWithProviders(); + expect(screen.getByRole("button", { name: "Routing approach" })).toHaveTextContent(label); + await selectAutoRouterOption("Routing approach", "Complexity"); + expect(screen.getByRole("status", { name: "Classifier type" })).toHaveTextContent("llm"); + }, + ); + + it.each([ + [1, "heuristic"], + [0, "heuristic"], + ])("defaults to Rule-based when %s v2 slots remain", async (remaining, classifier) => { + renderWithProviders(); + fireEvent.click(screen.getByRole("radio", { name: /^Heuristics$/ })); + expect(screen.getByRole("status", { name: "Classifier type" })).toHaveTextContent(String(classifier)); + fireEvent.click(screen.getByRole("button", { name: "Heuristic" })); + expect(screen.getByRole("menuitemradio", { name: /^Heuristic v2/ })).toHaveTextContent( + `${remaining} of 1 available`, + ); }); - it("keeps custom tiers editable under Complexity and explains why forecast tabs are disabled", () => { + it.each([ + { data: undefined }, + { isPending: true }, + { isError: true }, + { isChecking: true }, + { data: { allowances: [], error: null } }, + { data: { allowances: [{ key: "heuristic_v2", limit: 1, remaining: null, available: false }], error: null } }, + ])("uses Rule-based when v2 availability is unverified: %j", async (availabilityState) => { + renderWithProviders(); + fireEvent.click(screen.getByRole("radio", { name: "Heuristics" })); + expect(screen.getByRole("status", { name: "Classifier type" })).toHaveTextContent(/^heuristic$/); + }); + + it("does not present Rule-based as having a classifier quota", () => { + renderWithProviders(); + expect(screen.getByRole("button", { name: "Heuristic" })).toHaveTextContent(/^Rule-based/); + fireEvent.click(screen.getByRole("button", { name: "Heuristic" })); + expect(screen.getAllByRole("menuitemradio")[0]).toHaveTextContent(/^Rule-based/); + expect(screen.getByRole("menuitemradio", { name: /^Rule-based/ })).not.toHaveTextContent("of 1 available"); + expect(screen.getByRole("menuitemradio", { name: /^Heuristic v2/ })).toHaveTextContent("0 of 1 available"); + }); + + it("omits allowance labels with an unlimited entitlement", async () => { + renderWithProviders(); + fireEvent.click(screen.getByRole("button", { name: "Heuristic" })); + expect(screen.getByRole("menuitemradio", { name: /^Heuristic v2/ })).not.toHaveTextContent("available"); + }); + + it.each([ + ["heuristic", "Heuristic", "Heuristic v2"], + ["llm", "Routing approach", "Capability"], + ["llm", "Routing approach", "Fuse v2"], + ] as const)("blocks exhausted %s options: %s / %s", (classifier_type, field, option) => { + renderWithProviders(); + fireEvent.click(screen.getByRole("button", { name: field })); + const unavailable = screen.getByRole("menuitemradio", { name: new RegExp(`^${option}`) }); + expect(unavailable).toHaveAttribute("aria-disabled", "true"); + fireEvent.click(unavailable); + expect(screen.getByRole("status", { name: "Classifier type" })).toHaveTextContent(classifier_type); + }); + + it.each([ + ["heuristic_v2", "heuristic", "Heuristic", "Heuristic v2"], + ["capability", "llm", "Routing approach", "Capability"], + ["llm_v2", "llm", "Routing approach", "Fuse v2"], + ] as const)("lets a saved router reselect its own %s allowance", async (feature, classifier_type, field, option) => { + renderWithProviders(); + await selectAutoRouterOption(field, option); + expect(screen.getByRole("status", { name: "Classifier type" })).toHaveTextContent(feature); + expect(screen.getByRole("button", { name: field })).toHaveTextContent("Used by this router"); + }); + + it("shows Jev's single Complexity approach without changing saved configuration", () => { const onChange = vi.fn(); renderWithProviders( - + Existing settings + , + ); + expect(screen.getByRole("button", { name: "Routing approach" })).toHaveTextContent("ComplexityUnlimited"); + fireEvent.click(screen.getByRole("button", { name: "Routing approach" })); + expect(screen.getAllByRole("menuitemradio")).toHaveLength(1); + fireEvent.click(screen.getByRole("menuitemradio", { name: /^Complexity/ })); + expect(onChange).not.toHaveBeenCalled(); + }); + + it("keeps custom tiers editable and disables incompatible choices", async () => { + renderWithProviders( + - Custom tiers - , + />, ); - expect(screen.getByRole("tabpanel", { name: "Complexity" })).toHaveTextContent("Custom tiers"); + expect(screen.getByRole("radio", { name: /^Heuristics$/ })).toHaveAttribute("aria-disabled", "true"); + fireEvent.click(screen.getByRole("button", { name: "Routing approach" })); for (const name of ["Capability", "Fuse v2"]) { - const tab = screen.getByRole("tab", { name }); - expect(tab).toHaveAttribute("aria-disabled", "true"); - expect(tab).toHaveAccessibleDescription("Restore standard tiers to use Capability or Fuse v2."); - fireEvent.click(tab); + expect(screen.getByRole("menuitemradio", { name: new RegExp(`^${name}`) })).toHaveAttribute( + "aria-disabled", + "true", + ); } - expect(onChange).not.toHaveBeenCalled(); - expect(screen.getByText("Restore standard tiers to use Capability or Fuse v2.")).toBeVisible(); + expect(screen.getByRole("status", { name: "Classifier type" })).toHaveTextContent("llm"); + }); +}); + +describe("Gated routing contact action", () => { + it("offers a pricing discussion in View limits", async () => { + renderWithProviders(); + expect(screen.queryByRole("link", { name: "Talk to our team" })).not.toBeInTheDocument(); + fireEvent.click(screen.getByRole("button", { name: "View limits" })); + const link = within(screen.getByRole("dialog")).getByRole("link", { name: "Talk to our team" }); + await waitFor(() => expect(link).toBeVisible()); + expect(link).toHaveAttribute("href", "https://calendly.com/tin-berri/litellm-auto-router-pricing-discussion"); + expect(link).toHaveAttribute("target", "_blank"); + expect(link).toHaveAttribute("rel", "noopener noreferrer"); + }); + + it.each([ + ["heuristic", "Heuristic", "Heuristic v2"], + ["llm", "Routing approach", "Capability"], + ] as const)( + "keeps the contact action available beside the disabled %s choice", + async (classifier_type, field, option) => { + renderWithProviders(); + expect(screen.queryByText(/Need more/)).not.toBeInTheDocument(); + fireEvent.click(screen.getByRole("button", { name: field })); + const disabled = screen.getByRole("menuitemradio", { name: new RegExp(`^${option}`) }); + expect(disabled).toHaveAttribute("aria-disabled", "true"); + const link = screen.getByRole("menuitem", { name: `Talk to our team about ${option}` }); + await waitFor(() => expect(link).toBeVisible()); + expect(link).toHaveAttribute("href", "https://calendly.com/tin-berri/litellm-auto-router-pricing-discussion"); + expect(link).toHaveAttribute("target", "_blank"); + fireEvent.click(link); + expect(screen.getByRole("status", { name: "Classifier type" })).toHaveTextContent(classifier_type); + }, + ); + + it.each([ + { remaining: 1 }, + { remaining: 0, limit: null }, + { remaining: 0, availabilityState: { isPending: true } }, + { remaining: 0, availabilityState: { isError: true } }, + { remaining: 0, availabilityState: { isChecking: true } }, + ])("does not pitch an upgrade for a free or unverified option: %j", (props) => { + renderWithProviders(); + fireEvent.click(screen.getByRole("button", { name: "Routing approach" })); + expect(screen.queryByRole("menuitem", { name: /Talk to our team/ })).not.toBeInTheDocument(); + }); + + it("does not pitch an upgrade for the saved heuristic's own slot", () => { + renderWithProviders( + , + ); + fireEvent.click(screen.getByRole("button", { name: "Heuristic" })); + expect(screen.queryByRole("menuitem", { name: /Talk to our team/ })).not.toBeInTheDocument(); + }); + + it("includes the sales action beside customization limits and blocked changes", () => { + const allowance = { key: "tier_or_classifier_prompt", limit: 1, remaining: 0, available: true }; + const state = { + isPending: false, + isError: false, + data: { allowances: [allowance], error: "Custom tiers have no available allowance" }, + }; + renderWithProviders( + + + + + , + ); + expect(screen.getByText(/Custom tiers: 0 of 1 available/)).toHaveTextContent("Talk to our team"); + expect(within(screen.getByRole("alert")).getByRole("link", { name: "Talk to our team" })).toBeVisible(); }); }); diff --git a/ui/litellm-dashboard/src/components/add_model/AutoRouterClassifierTabs.tsx b/ui/litellm-dashboard/src/components/add_model/AutoRouterClassifierTabs.tsx index 98c0d4aab2f..92fc8d2a335 100644 --- a/ui/litellm-dashboard/src/components/add_model/AutoRouterClassifierTabs.tsx +++ b/ui/litellm-dashboard/src/components/add_model/AutoRouterClassifierTabs.tsx @@ -1,8 +1,119 @@ -import React, { useId } from "react"; -import { Tabs, TabsContent, TabsList, TabsTrigger } from "@/components/ui/tabs"; -import { effectiveClassifierType, type ComplexityRouterConfigValue } from "./ComplexityRouterConfig"; +import React, { useContext, useId } from "react"; +import { Label } from "@/components/ui/label"; +import { RadioGroup, RadioGroupItem } from "@/components/ui/radio-group"; +import { ChevronDownIcon } from "lucide-react"; +import { Button } from "@/components/ui/button"; +import { + DropdownMenu, + DropdownMenuContent, + DropdownMenuItem, + DropdownMenuRadioGroup, + DropdownMenuRadioItem, + DropdownMenuTrigger, +} from "@/components/ui/dropdown-menu"; +import { + effectiveClassifierType, + type ClassifierType, + type ComplexityRouterConfigValue, +} from "./ComplexityRouterConfig"; import { transitionClassifierType } from "./classifier_type_transition"; import { isForecastClassifier } from "./forecast_classifier_config"; +import { + AutoRouterAllowanceLabel, + AutoRouterAvailabilityContext, + AutoRouterLimits, + AutoRouterContactLink, + isAllowanceExhausted, + AUTO_ROUTER_CONTACT_URL, +} from "./AutoRouterAvailability"; + +function ClassifierOption({ + value, + label, + description, + feature, + disabled, + unlimited = true, +}: { + value: string; + label: string; + description: string; + feature?: string; + disabled?: boolean; + unlimited?: boolean; +}) { + const state = useContext(AutoRouterAvailabilityContext); + const allowance = state.data?.allowances.find((entry) => entry.key === feature); + const fresh = !state.isPending && !state.isError && !state.isChecking; + const exhausted = isAllowanceExhausted(allowance); + return ( +
+ + + + {label} + {feature ? ( + + ) : ( + unlimited && Unlimited + )} + + {description} + + + {fresh && exhausted && ( + } + aria-label={`Talk to our team about ${label}`} + className="absolute top-9 right-8 cursor-pointer px-0 py-0 text-xs leading-5 font-medium text-blue-600 focus:text-blue-600 hover:underline dark:text-blue-400 dark:focus:text-blue-400" + > + Talk to our team + + )} +
+ ); +} + +function ClassifierMenu({ + id, + label, + value, + selectedLabel, + feature, + onValueChange, + children, +}: { + id: string; + label: string; + value: string; + selectedLabel: string; + feature?: string; + onValueChange: (value: string) => void; + children: React.ReactNode; +}) { + return ( + + } + > + {selectedLabel} + {feature ? ( + + ) : ( + Unlimited + )} + + + + + {children} + + + + ); +} interface AutoRouterClassifierTabsProps { value: ComplexityRouterConfigValue; @@ -11,47 +122,174 @@ interface AutoRouterClassifierTabsProps { } const AutoRouterClassifierTabs: React.FC = ({ value, onChange, children }) => { - const restrictionId = useId(); + const id = useId(); + const availability = useContext(AutoRouterAvailabilityContext); const classifierType = effectiveClassifierType(value); - const selected = isForecastClassifier(classifierType) ? classifierType : "complexity"; + const familyByType: Record = { + heuristic: "heuristics", + heuristic_v2: "heuristics", + llm: "llm", + heuristic_first: "llm", + hybrid: "llm", + capability: "llm", + llm_v2: "llm", + jev: "jev", + custom: "custom", + }; + const family = familyByType[classifierType]; const hasCustomTiers = Boolean(value.custom_tier_set); - - const handleChange = (tab: unknown) => { - if (tab === selected) return; - if (tab === "complexity") { - onChange(transitionClassifierType(value, isForecastClassifier(classifierType) ? "heuristic" : classifierType)); - } else if (!hasCustomTiers && (tab === "capability" || tab === "llm_v2")) { - onChange(transitionClassifierType(value, tab)); - } + const changeType = (next: ClassifierType) => { + if (next !== classifierType) onChange(transitionClassifierType(value, next)); }; + const changeFamily = (next: unknown) => { + if (next === family) return; + if (next === "heuristics") changeType("heuristic"); + if (next === "llm") changeType("llm"); + if (next === "jev") changeType("jev"); + }; + const approachLabels: Partial> = { capability: "Capability", llm_v2: "Fuse v2" }; + const approachDescription: Partial> = { + capability: "Use the efficient model when it is likely to succeed", + llm_v2: "Use the efficient model when its predicted quality is close enough to the capable model", + }; return ( - -

Classifier type

- - Complexity - - Capability - - - Fuse v2 - - +
+
+ + What classifies your requests? + + + + {[ + { value: "heuristics", label: "Heuristics", description: "Classify locally, with no API call" }, + { value: "llm", label: "LLM", description: "Use a judge model to choose a solver" }, + { value: "jev", label: "Jev", description: "Use TypeSafe System One Choice to choose a tier" }, + ].map((option) => ( + + ))} + +
+ {family === "custom" && ( +

This router uses a custom classifier plugin

+ )} + {family === "heuristics" && ( +
+ + { + if (next === "heuristic" || next === "heuristic_v2") changeType(next); + }} + > + + + +

+ {classifierType === "heuristic_v2" + ? "Use calibrated probabilities to match requests to a tier" + : "Match requests using scoring rules. Choose or change tier models freely"} +

+
+ )} + {(family === "llm" || family === "jev") && ( +
+ + { + if (next === "llm" || next === "capability" || next === "llm_v2") { + if (next === "llm" && !isForecastClassifier(classifierType)) return; + changeType(next); + } + }} + > + + {family === "llm" && ( + <> + + + + )} + +

+ {approachDescription[classifierType] ?? "Match task difficulty to a tier"} +

+
+ )} {hasCustomTiers && ( -

- Restore standard tiers to use Capability or Fuse v2. +

+ Restore standard tiers to use Heuristics, Capability, or Fuse v2

)} - {children} - + {availability.data?.error && !availability.isChecking && ( +
+

{availability.data.error}

+ +
+ )} + {availability.isError && ( +

+ Could not check availability.{" "} + +

+ )} + {children} +
); }; diff --git a/ui/litellm-dashboard/src/components/add_model/ClassificationMethodConfig.tsx b/ui/litellm-dashboard/src/components/add_model/ClassificationMethodConfig.tsx index b7a0fd67443..ccd204aa521 100644 --- a/ui/litellm-dashboard/src/components/add_model/ClassificationMethodConfig.tsx +++ b/ui/litellm-dashboard/src/components/add_model/ClassificationMethodConfig.tsx @@ -1,9 +1,10 @@ +import ClassifierPrimarySettings from "./ClassifierPrimarySettings"; +import { AutoRouterAllowanceNote } from "./AutoRouterAvailability"; import { transitionClassifierType } from "./classifier_type_transition"; import JevClassifierConfig from "./JevClassifierConfig"; import { Info } from "lucide-react"; import { SimpleTooltip } from "@/components/ui/tooltip"; import { MultiSelect } from "@/components/shared/MultiSelect"; -import { SearchSelect } from "@/components/shared/SearchSelect"; import { Select, SelectContent, SelectItem, SelectTrigger, SelectValue } from "@/components/ui/select"; import { Card, CardContent } from "@/components/ui/card"; import { Button } from "@/components/ui/button"; @@ -25,13 +26,10 @@ import ClassifierTypeRadios from "./ClassifierTypeRadios"; import type { ReasoningEffort } from "./complexity_router_tiers"; import { useComplexityScorerDefaults } from "@/app/(dashboard)/hooks/autoRouter/useComplexityScorerDefaults"; import { - ClassificationFrequency, ClassifierFallback, ClassifierLLMConfig, ClassifierType, ComplexityRouterConfigValue, - classificationFrequency, - withClassificationFrequency, DEFAULT_CLASSIFIER_CONTEXT_BUDGET_CHARS, MIN_QUOTED_CONTEXT_TURN_CHARS, DEFAULT_CLASSIFIER_CONTEXT_WINDOW_SIZE, @@ -171,6 +169,7 @@ interface ClassificationMethodConfigProps { showValidationErrors?: boolean; /** The resolved default model - see resolveComplexityDefaultModel. Names and gates the radio. */ defaultModel?: string; + advancedOnly?: boolean; } export const InactiveHeuristicV2Threshold: React.FC> = ({ @@ -215,13 +214,11 @@ const ClassificationMethodConfig: React.FC = ({ onCustomTechnicalKeywordsChange, showValidationErrors = false, defaultModel, + advancedOnly = false, }) => { const [draft, setDraft] = React.useState<{ id: string; raw: string } | null>(null); const hasDefaultModel = Boolean(defaultModel); const classifierType = effectiveClassifierType(value); - const sessionFrequencyRestriction = restrictedBy(value, "sessionAffinity"); - const classifierModelMissing = - showValidationErrors && usesLlmClassifier(classifierType) && !value.classifier_llm_config?.model; const usesCustomPrompt = Boolean(value.classifier_llm_config?.system_prompt?.trim()); const contextBudget = value.classifier_context_budget_chars ?? DEFAULT_CLASSIFIER_CONTEXT_BUDGET_CHARS; const contextBudgetQuotesNothing = contextBudget > 0 && contextBudget < MIN_QUOTED_CONTEXT_TURN_CHARS; @@ -282,23 +279,6 @@ const ClassificationMethodConfig: React.FC = ({ onChange(nextValue); }; - const handleClassifierModelChange = (model: string | null) => { - if (model === null) return; - if (model === value.classifier_llm_config?.model) return; - const { reasoning_effort: _reasoningEffort, ...classifierLlmConfig } = value.classifier_llm_config ?? { - model: "", - timeout_ms: DEFAULT_CLASSIFIER_TIMEOUT_MS, - }; - onChange({ - ...value, - classifier_llm_config: { - ...classifierLlmConfig, - model, - timeout_ms: classifierLlmConfig.timeout_ms, - }, - }); - }; - const handleClassifierReasoningEffortChange = (reasoningEffort: ReasoningEffort | undefined) => { if (!value.classifier_llm_config) return; const { reasoning_effort: _reasoningEffort, ...classifierLlmConfig } = value.classifier_llm_config; @@ -350,10 +330,6 @@ const ClassificationMethodConfig: React.FC = ({ onChange({ ...value, classifier_fallback: fallback }); }; - const handleClassificationFrequencyChange = (frequency: ClassificationFrequency) => { - onChange(withClassificationFrequency(value, frequency)); - }; - const handleClassifierContextWindowSizeChange = (windowSize: number) => { onChange({ ...value, @@ -389,7 +365,50 @@ const ClassificationMethodConfig: React.FC = ({ return ( <> - + {!advancedOnly && ( + <> + + + + )} + {advancedOnly && ["llm", "heuristic_first", "hybrid"].includes(classifierType) && ( +
+ + +
+ )} {classifierType === "custom" && ( @@ -474,66 +493,9 @@ const ClassificationMethodConfig: React.FC = ({ )} -
- How often to classify - - handleClassificationFrequencyChange(frequency as ClassificationFrequency) - } - > -
- - - -
- -

- Holding the tier keeps an agent on one model for a whole tool loop and cuts scoring cost. A turn the router - cannot match to a held decision, such as one with no session id or an expired one, is scored again -

-
- {classifierType === "jev" && } {usesLlmClassifier(classifierType) && (
-
- Classifier Model - - {classifierModelMissing && A classifier model is required} -
= ({
+ {!value.custom_tier_set && usesCustomPrompt ? ( = ({ /> Number of prior user turns sent to the classifier provider, excluding tool output and harness reminders. - LLM and JEV default to 3 turns; JEV sends them to the configured TypeSafe endpoint. Set to 0 to omit + LLM and Jev default to 3 turns; Jev sends them to the configured TypeSafe endpoint. Set to 0 to omit conversation history. The current message and selected system text are still sent. @@ -769,6 +735,9 @@ const ClassificationMethodConfig: React.FC = ({ )} + {["heuristic", "heuristic_first", "hybrid"].includes(classifierType) && ( + + )} diff --git a/ui/litellm-dashboard/src/components/add_model/ClassifierPrimarySettings.tsx b/ui/litellm-dashboard/src/components/add_model/ClassifierPrimarySettings.tsx new file mode 100644 index 00000000000..32cb4851580 --- /dev/null +++ b/ui/litellm-dashboard/src/components/add_model/ClassifierPrimarySettings.tsx @@ -0,0 +1,98 @@ +import React from "react"; +import { Label } from "@/components/ui/label"; +import { SearchSelect } from "@/components/shared/SearchSelect"; +import { Select, SelectContent, SelectItem, SelectTrigger, SelectValue } from "@/components/ui/select"; +import { + classificationFrequency, + withClassificationFrequency, + effectiveClassifierType, + usesLlmClassifier, + DEFAULT_CLASSIFIER_TIMEOUT_MS, + type ComplexityRouterConfigValue, + type ClassificationFrequency, +} from "./ComplexityRouterConfig"; +import { restrictedBy } from "./TierRestrictions"; + +export default function ClassifierPrimarySettings({ + value, + onChange, + modelOptions, + showValidationErrors = false, +}: { + value: ComplexityRouterConfigValue; + onChange: (value: ComplexityRouterConfigValue) => void; + modelOptions: { value: string; label: string }[]; + showValidationErrors?: boolean; +}) { + const id = React.useId(); + const restriction = restrictedBy(value, "sessionAffinity"); + const frequency = classificationFrequency(value); + const frequencyDescription = { + every_request: "Choose a model again for every request", + user_turn: "Reclassify when the user sends a new message", + session: "Keep the same tier for the session. Requires a client session ID", + }[frequency]; + const usesJudge = usesLlmClassifier(effectiveClassifierType(value)); + const missingJudge = showValidationErrors && usesJudge && !value.classifier_llm_config?.model; + return ( +
+
+ + +

{restriction?.reason ?? frequencyDescription}

+
+ {usesJudge && ( +
+ + { + if (!model || model === value.classifier_llm_config?.model) return; + onChange({ + ...value, + classifier_llm_config: { + ...value.classifier_llm_config, + model, + timeout_ms: value.classifier_llm_config?.timeout_ms ?? DEFAULT_CLASSIFIER_TIMEOUT_MS, + reasoning_effort: undefined, + }, + }); + }} + /> + {missingJudge && ( +

+ A judge model is required +

+ )} +
+ )} +
+ ); +} diff --git a/ui/litellm-dashboard/src/components/add_model/ClassifierTypeRadios.tsx b/ui/litellm-dashboard/src/components/add_model/ClassifierTypeRadios.tsx index 1602e19069a..1fd6dfa6a20 100644 --- a/ui/litellm-dashboard/src/components/add_model/ClassifierTypeRadios.tsx +++ b/ui/litellm-dashboard/src/components/add_model/ClassifierTypeRadios.tsx @@ -54,7 +54,7 @@ const ClassifierTypeRadios: React.FC = ({ value, clas diff --git a/ui/litellm-dashboard/src/components/add_model/ComplexityRouterAdvancedSections.tsx b/ui/litellm-dashboard/src/components/add_model/ComplexityRouterAdvancedSections.tsx index 44adecb9e1d..a4e833152a9 100644 --- a/ui/litellm-dashboard/src/components/add_model/ComplexityRouterAdvancedSections.tsx +++ b/ui/litellm-dashboard/src/components/add_model/ComplexityRouterAdvancedSections.tsx @@ -6,6 +6,7 @@ import type { ModelGroup } from "@/components/llm_calls/fetch_models"; import type { ComplexityRouterConfigValue } from "./ComplexityRouterConfig"; import AdaptiveRoutingConfig from "./AdaptiveRoutingConfig"; import ClassificationMethodConfig from "./ClassificationMethodConfig"; +import ForecastClassifierConfig from "./ForecastClassifierConfig"; import ContextWindowEscalationConfig from "./ContextWindowEscalationConfig"; import ResponseFormatControls from "./ResponseFormatControls"; import StallEscalationConfig from "./StallEscalationConfig"; @@ -79,13 +80,31 @@ const ComplexityRouterAdvancedSections: React.FC { const sections = [ + ...(forecast + ? [ + { + key: "classifier", + label: Classifier tuning, + children: ( + + ), + }, + ] + : []), ...(!forecast ? [ { key: "classifier", - label: Advanced: Classification Method, + label: Classification Method, children: ( Advanced: Heuristic Keyword Overrides, + label: Heuristic Keyword Overrides, children: , }, ] : []), { key: "adaptive", - label: Advanced: Adaptive Routing, + label: Adaptive Routing, children: ( @@ -119,39 +138,39 @@ const ComplexityRouterAdvancedSections: React.FCAdvanced: Affinity, + label: Affinity, children: , }, { key: "modality", - label: Advanced: Modality Routing, + label: Modality Routing, children: , }, { key: "plan-mode", - label: Advanced: Plan-Mode Override, + label: Plan-Mode Override, children: ( ), }, { key: "housekeeping", - label: Advanced: Housekeeping Routing, + label: Housekeeping Routing, children: , }, { key: "reminder-markers", - label: Advanced: Ignore Custom Tags, + label: Ignore Custom Tags, children: , }, { key: "context-window", - label: Advanced: Context Window Escalation, + label: Context Window Escalation, children: , }, { key: "stall-escalation", - label: Advanced: Stalled Task Escalation, + label: Stalled Task Escalation, children: ( @@ -160,14 +179,14 @@ const ComplexityRouterAdvancedSections: React.FCAdvanced: Response Format, + label: Response Format, children: , }, ...(onEscalationKeywordsChange ? [ { key: "escalation", - label: Advanced: Escalation Keywords, + label: Escalation Keywords, children: ( @@ -180,7 +199,7 @@ const ComplexityRouterAdvancedSections: React.FCAdvanced: Compression, + label: Compression, children: , }, ] @@ -189,7 +208,7 @@ const ComplexityRouterAdvancedSections: React.FCAdvanced: Keyword/Semantic Matching, + label: Keyword/Semantic Matching, children: ( <> {onKeywordTierRulesChange && ( @@ -220,20 +239,65 @@ const ComplexityRouterAdvancedSections: React.FC(() => + showValidationErrors ? groups.map((group) => group.label) : [], + ); + const [previousValidation, setPreviousValidation] = React.useState(showValidationErrors); + if (previousValidation !== showValidationErrors) { + setPreviousValidation(showValidationErrors); + if (showValidationErrors) setOpenGroups(groups.map((group) => group.label)); + } return ( - <> - {sections - .filter(({ key }) => !forecast || !["adaptive", "context-window", "escalation"].includes(key)) - .map(({ key, label, children }) => ( - - - - {label} - - {children} - - ))} - +
+ {groups.map((group) => ( + + setOpenGroups((current) => + open ? [...current, group.label] : current.filter((label) => label !== group.label), + ) + } + className="border-b border-border last:border-b-0" + > + + + {group.label} + + + {sections + .filter( + ({ key }) => + group.keys.includes(key) && + (!forecast || !["adaptive", "context-window", "escalation"].includes(key)), + ) + .map(({ key, label, children }) => ( +
+ {key !== "classifier" &&

{label}

} + {children} +
+ ))} + + + ))} +
); }; diff --git a/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.test.tsx b/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.integration.test.tsx similarity index 85% rename from ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.test.tsx rename to ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.integration.test.tsx index 756e505997c..4a00a469f97 100644 --- a/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.test.tsx +++ b/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.integration.test.tsx @@ -1,8 +1,15 @@ +import { openAutoRouterAdvanced, selectAutoRouterOption } from "../../../tests/autoRouterSetup"; import { fireEvent, renderWithProviders, screen, within } from "../../../tests/test-utils"; import userEvent from "@testing-library/user-event"; import React from "react"; -import { vi, type Mock } from "vitest"; -import ComplexityRouterConfig, { ComplexityRouterConfigValue } from "./ComplexityRouterConfig"; +import { describe, it, expect, vi, type Mock } from "vitest"; +import ComplexityRouterConfigView, { ComplexityRouterConfigValue } from "./ComplexityRouterConfig"; +import AutoRouterClassifierTabs from "./AutoRouterClassifierTabs"; +const ComplexityRouterConfig = (props: React.ComponentProps) => ( + + + +); vi.mock( "@/app/(dashboard)/hooks/autoRouter/useComplexityScorerDefaults", async () => await import("../../../tests/mocks/complexityScorerDefaults"), @@ -45,12 +52,12 @@ const baseProps = { }; describe("ComplexityRouterConfig", () => { - it("should render", () => { + it("should render", async () => { renderWithProviders(); - expect(screen.getByText("Complexity Tier Configuration")).toBeInTheDocument(); + expect(screen.getByText("Models by tier")).toBeInTheDocument(); }); - it("should display all four tier labels", () => { + it("should display all four tier labels", async () => { renderWithProviders(); expect(screen.getByText("Simple Tier")).toBeInTheDocument(); expect(screen.getByText("Medium Tier")).toBeInTheDocument(); @@ -58,7 +65,7 @@ describe("ComplexityRouterConfig", () => { expect(screen.getByText("Reasoning Tier")).toBeInTheDocument(); }); - it("should show example queries for each tier", () => { + it("should show example queries for each tier", async () => { renderWithProviders(); expect(screen.getByText(/Hello!/)).toBeInTheDocument(); expect(screen.getByText(/Explain how REST APIs work/)).toBeInTheDocument(); @@ -66,46 +73,51 @@ describe("ComplexityRouterConfig", () => { expect(screen.getByText(/Think step by step/)).toBeInTheDocument(); }); - it("should display the how classification works section", () => { + it("should display the how classification works section", async () => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.getByText("How Classification Works")).toBeInTheDocument(); }); - it("should show score thresholds in the classification section", () => { + it("should show score thresholds in the classification section", async () => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.getByText(/Score < 0.15/)).toBeInTheDocument(); expect(screen.getByText(/Score 0.15 - 0.35/)).toBeInTheDocument(); expect(screen.getByText(/Score 0.35 - 0.60/)).toBeInTheDocument(); expect(screen.getByText(/Score > 0.60/)).toBeInTheDocument(); }); - it("leaves the score threshold list color to the theme instead of an inline style", () => { + it("leaves the score threshold list color to the theme instead of an inline style", async () => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); const list = screen.getByText(/Score < 0.15/).closest("ul"); expect(list).toBeInTheDocument(); expect(list).toHaveClass("text-muted-foreground"); expect(list?.style.color).toBe(""); }); - it("should default to heuristic and hide classifier model/timeout fields", () => { + it("should default to heuristic and hide classifier model/timeout fields", async () => { renderWithProviders(); - expect(screen.getByText("Advanced: Classification Method")).toBeInTheDocument(); - expect(screen.queryByText("Classifier Model")).not.toBeInTheDocument(); + openAutoRouterAdvanced("Classification Method"); + expect(screen.getByText("Classifier tuning")).toBeInTheDocument(); + expect(screen.queryByText("Judge model")).not.toBeInTheDocument(); }); - it("shows heuristic advanced sections and hides keyword overrides for capability classifiers", () => { + it("shows heuristic advanced sections and hides keyword overrides for capability classifiers", async () => { const { rerender } = renderWithProviders(); - expect(screen.getByText("Advanced: Heuristic Keyword Overrides")).toBeInTheDocument(); - expect(screen.getByText("Advanced: Housekeeping Routing")).toBeInTheDocument(); - expect(screen.getByText("Advanced: Ignore Custom Tags")).toBeInTheDocument(); + openAutoRouterAdvanced("Heuristic Keyword Overrides"); + + expect(screen.getByText("Heuristic Keyword Overrides")).toBeInTheDocument(); + openAutoRouterAdvanced("Housekeeping Routing"); + expect(screen.getByText("Housekeeping Routing")).toBeInTheDocument(); + openAutoRouterAdvanced("Ignore Custom Tags"); + expect(screen.getByText("Ignore Custom Tags")).toBeInTheDocument(); const capabilityValue = { ...defaultValue, classifier_type: "capability" as const }; rerender(); - expect(screen.queryByText("Advanced: Heuristic Keyword Overrides")).not.toBeInTheDocument(); + expect(screen.queryByText("Heuristic Keyword Overrides")).not.toBeInTheDocument(); }); it.each([ @@ -115,7 +127,7 @@ describe("ComplexityRouterConfig", () => { renderWithProviders( , ); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); if (visible) { expect(screen.getByLabelText("Classifier plugin timeout (ms)")).toBeInTheDocument(); } else { @@ -128,7 +140,7 @@ describe("ComplexityRouterConfig", () => { renderWithProviders( , ); - fireEvent.click(screen.getByText("Advanced: Ignore Custom Tags")); + openAutoRouterAdvanced("Ignore Custom Tags"); const validation = screen.queryByText(/needs both/i); if (showValidationErrors) { expect(validation).toBeInTheDocument(); @@ -137,11 +149,11 @@ describe("ComplexityRouterConfig", () => { } }); - it("disables housekeeping sentinels when cheapest-tier routing is off", () => { + it("disables housekeeping sentinels when cheapest-tier routing is off", async () => { renderWithProviders( , ); - fireEvent.click(screen.getByText("Advanced: Housekeeping Routing")); + openAutoRouterAdvanced("Housekeeping Routing"); const sentinelInput = screen.getByRole("combobox", { name: "e.g., conversation title" }); expect(sentinelInput).toBeDisabled(); }); @@ -151,7 +163,7 @@ describe("ComplexityRouterConfig", () => { const onChange = vi.fn(); renderWithProviders(); - await user.click(screen.getByText("Advanced: Response Format")); + openAutoRouterAdvanced("Response Format"); await user.click(screen.getByRole("switch", { name: "Return raw model name" })); expect(onChange).toHaveBeenCalledWith({ @@ -160,13 +172,13 @@ describe("ComplexityRouterConfig", () => { }); }); - it("should reveal classifier model and timeout fields when llm is selected", () => { + it("should reveal classifier model and timeout fields when llm is selected", async () => { const onChange = vi.fn(); renderWithProviders(); // Collapse panel content isn't rendered until first expanded. - fireEvent.click(screen.getByText("Advanced: Classification Method")); - fireEvent.click(screen.getByText("LLM Classifier")); + openAutoRouterAdvanced("Classification Method"); + fireEvent.click(screen.getByRole("radio", { name: /^LLM$/ })); const expectedValue: ComplexityRouterConfigValue = { ...defaultValue, @@ -178,14 +190,14 @@ describe("ComplexityRouterConfig", () => { expect(onChange).toHaveBeenCalledWith(expectedValue); }); - it("selects heuristic v2 without requiring a classifier model or showing weighted scoring", () => { + it("selects heuristic v2 without requiring a classifier model or showing weighted scoring", async () => { const onChange = vi.fn(); const { rerender } = renderWithProviders( , ); - fireEvent.click(screen.getByText("Advanced: Classification Method")); - fireEvent.click(screen.getByText("Heuristic v2")); + openAutoRouterAdvanced("Classification Method"); + await selectAutoRouterOption("Heuristic", "Heuristic v2"); expect(onChange).toHaveBeenCalledWith( expect.objectContaining({ @@ -197,7 +209,7 @@ describe("ComplexityRouterConfig", () => { const heuristicV2Value: ComplexityRouterConfigValue = { ...defaultValue, classifier_type: "heuristic_v2" }; rerender(); - expect(screen.queryByText("Classifier Model")).not.toBeInTheDocument(); + expect(screen.queryByText("Judge model")).not.toBeInTheDocument(); expect(screen.queryByText("Advanced scoring")).not.toBeInTheDocument(); expect(screen.getByText(/estimates success probability for all four tiers/)).toBeInTheDocument(); expect(screen.queryByText(/Score < 0.15/)).not.toBeInTheDocument(); @@ -233,7 +245,7 @@ describe("ComplexityRouterConfig", () => { expect(onChange).toHaveBeenCalledWith({ ...value, heuristic_v2_success_threshold: undefined }); }); - it("shows an inactive zero threshold until explicitly cleared and hides the summary for active or absent values", () => { + it("shows an inactive zero threshold until explicitly cleared and hides the summary for active or absent values", async () => { const onChange = vi.fn(); const value = { ...defaultValue, heuristic_v2_success_threshold: 0 }; const { rerender } = renderWithProviders( @@ -248,7 +260,7 @@ describe("ComplexityRouterConfig", () => { expect(screen.queryByRole("region", { name: "Inactive Heuristic v2 threshold" })).not.toBeInTheDocument(); }); - it("should show classifier fields and use the configured values when classifier_type is llm", () => { + it("should show classifier fields and use the configured values when classifier_type is llm", async () => { const llmValue: ComplexityRouterConfigValue = { ...defaultValue, classifier_type: "llm", @@ -258,9 +270,9 @@ describe("ComplexityRouterConfig", () => { }; renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); - expect(screen.getByText("Classifier Model")).toBeInTheDocument(); + expect(screen.getByText("Judge model")).toBeInTheDocument(); expect(screen.getByLabelText("Timeout (ms)")).toHaveValue("750"); expect(screen.getByRole("switch", { name: "Classifier circuit breaker" })).toBeChecked(); expect(screen.getByLabelText("Circuit breaker cooldown (seconds)")).toHaveValue("30"); @@ -268,7 +280,7 @@ describe("ComplexityRouterConfig", () => { expect(screen.queryByText("Context Per-Turn Character Limit")).not.toBeInTheDocument(); }); - it("should allow the default-on classifier circuit breaker to be disabled", () => { + it("should allow the default-on classifier circuit breaker to be disabled", async () => { const onChange = vi.fn(); const llmValue: ComplexityRouterConfigValue = { ...defaultValue, @@ -276,7 +288,7 @@ describe("ComplexityRouterConfig", () => { classifier_llm_config: { model: "gpt-3.5-turbo", timeout_ms: 3000 }, }; renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); fireEvent.click(screen.getByRole("switch", { name: "Classifier circuit breaker" })); @@ -287,7 +299,7 @@ describe("ComplexityRouterConfig", () => { ); }); - it("should default the context window and budget when llm is selected", () => { + it("should default the context window and budget when llm is selected", async () => { const llmValue: ComplexityRouterConfigValue = { ...defaultValue, classifier_type: "llm", @@ -295,13 +307,13 @@ describe("ComplexityRouterConfig", () => { }; renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.getByLabelText("Context Window Size")).toHaveValue("3"); expect(screen.getByLabelText("Context Character Budget")).toHaveValue("8000"); }); - it("should warn when the budget is too small to quote any turn that does not already fit", () => { + it("should warn when the budget is too small to quote any turn that does not already fit", async () => { const llmValue: ComplexityRouterConfigValue = { ...defaultValue, classifier_type: "llm", @@ -310,12 +322,12 @@ describe("ComplexityRouterConfig", () => { }; renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.getByText(/no room to quote a turn/i)).toBeInTheDocument(); }); - it("should not warn on a budget large enough to quote a turn, nor on a deliberate zero", () => { + it("should not warn on a budget large enough to quote a turn, nor on a deliberate zero", async () => { for (const budget of [120, 8000, 0]) { const { unmount } = renderWithProviders( { onChange={vi.fn()} />, ); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.queryByText(/no room to quote a turn/i)).not.toBeInTheDocument(); unmount(); } }); - it("should show the assistant-turns switch with its configured value when classifier_type is llm", () => { + it("should show the assistant-turns switch with its configured value when classifier_type is llm", async () => { const llmValue: ComplexityRouterConfigValue = { ...defaultValue, classifier_type: "llm", @@ -344,13 +356,13 @@ describe("ComplexityRouterConfig", () => { }; renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.getByText("Include Assistant Turns")).toBeInTheDocument(); expect(screen.getByRole("switch", { name: "Include Assistant Turns" })).toBeChecked(); }); - it("should render the assistant-turns switch off when it is not set", () => { + it("should render the assistant-turns switch off when it is not set", async () => { const llmValue: ComplexityRouterConfigValue = { ...defaultValue, classifier_type: "llm", @@ -358,18 +370,18 @@ describe("ComplexityRouterConfig", () => { }; renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.getByRole("switch", { name: "Include Assistant Turns" })).not.toBeChecked(); }); - it("should hide the assistant-turns switch when classifier_type is heuristic", () => { + it("should hide the assistant-turns switch when classifier_type is heuristic", async () => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.queryByText("Include Assistant Turns")).not.toBeInTheDocument(); }); - it("should call onChange when the assistant-turns switch is toggled", () => { + it("should call onChange when the assistant-turns switch is toggled", async () => { const onChange = vi.fn(); const llmValue: ComplexityRouterConfigValue = { ...defaultValue, @@ -378,7 +390,7 @@ describe("ComplexityRouterConfig", () => { }; renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); fireEvent.click(screen.getByRole("switch", { name: "Include Assistant Turns" })); expect(onChange).toHaveBeenCalledWith( @@ -386,9 +398,9 @@ describe("ComplexityRouterConfig", () => { ); }); - it("should hide classifier context fields when classifier_type is heuristic", () => { + it("should hide classifier context fields when classifier_type is heuristic", async () => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.queryByText("Context Window Size")).not.toBeInTheDocument(); expect(screen.queryByText("Context Per-Turn Character Limit")).not.toBeInTheDocument(); }); @@ -416,7 +428,7 @@ describe("ComplexityRouterConfig", () => { classifier_llm_config: { model: "gpt-3.5-turbo", timeout_ms: 3000 }, }; renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); const input = screen.getByLabelText(label); fireEvent.change(input, { target: { value: "" } }); @@ -429,14 +441,14 @@ describe("ComplexityRouterConfig", () => { expect(onChange).toHaveBeenLastCalledWith({ ...llmValue, ...expected }); }); - it("restores the committed context window size after an empty field loses focus", () => { + it("restores the committed context window size after an empty field loses focus", async () => { const llmValue: ComplexityRouterConfigValue = { ...defaultValue, classifier_type: "llm", classifier_llm_config: { model: "gpt-3.5-turbo", timeout_ms: 3000 }, }; renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); const input = screen.getByLabelText("Context Window Size"); fireEvent.change(input, { target: { value: "" } }); @@ -445,13 +457,13 @@ describe("ComplexityRouterConfig", () => { expect(input).toHaveValue("3"); }); - it("should render the custom technical keywords field", () => { + it("should render the custom technical keywords field", async () => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.getByText("Custom Technical Keywords")).toBeInTheDocument(); }); - it("should display existing custom technical keywords as tags", () => { + it("should display existing custom technical keywords as tags", async () => { renderWithProviders( { onCustomTechnicalKeywordsChange={vi.fn()} />, ); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.getByText("udp")).toBeInTheDocument(); expect(screen.getByText("kafka")).toBeInTheDocument(); }); @@ -474,7 +486,7 @@ describe("ComplexityRouterConfig", () => { onCustomTechnicalKeywordsChange={onCustomTechnicalKeywordsChange} />, ); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); const keywordsSection = screen.getByText("Custom Technical Keywords").closest("div")?.parentElement as HTMLElement; await user.type(within(keywordsSection).getByRole("combobox"), "udp"); await user.click(await screen.findByText('Create "udp"')); @@ -491,35 +503,35 @@ describe("ComplexityRouterConfig", () => { onCustomTechnicalKeywordsChange={onCustomTechnicalKeywordsChange} />, ); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); const keywordsSection = screen.getByText("Custom Technical Keywords").closest("div")?.parentElement as HTMLElement; await user.type(within(keywordsSection).getByRole("combobox"), "udp, kafka ,terraform"); await user.click(await screen.findByText('Create "udp, kafka ,terraform"')); expect(onCustomTechnicalKeywordsChange).toHaveBeenCalledWith(["udp", "kafka", "terraform"]); }); - it("should render an empty state when no keyword tier rules exist", () => { + it("should render an empty state when no keyword tier rules exist", async () => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Keyword/Semantic Matching")); + openAutoRouterAdvanced("Keyword/Semantic Matching"); expect(screen.getByText("Keyword Tier Overrides")).toBeInTheDocument(); expect(screen.getByText("No keyword tier overrides configured")).toBeInTheDocument(); }); - it("hides the keyword-tier and semantic sections when their change handlers are absent (edit modal)", () => { + it("hides the keyword-tier and semantic sections when their change handlers are absent (edit modal)", async () => { // The edit-auto-router modal renders ComplexityRouterConfig without these handlers; // the sections must stay hidden rather than render interactive-but-dead controls. renderWithProviders(); expect(screen.queryByText("Keyword Tier Overrides")).not.toBeInTheDocument(); expect(screen.queryByText("Semantic keyword matching")).not.toBeInTheDocument(); // Core tier config still renders. - expect(screen.getByText("Complexity Tier Configuration")).toBeInTheDocument(); + expect(screen.getByText("Models by tier")).toBeInTheDocument(); }); it("should call onKeywordTierRulesChange with a new rule when 'Add keyword rule' is clicked", async () => { const user = userEvent.setup(); const onKeywordTierRulesChange = vi.fn(); renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Keyword/Semantic Matching")); + openAutoRouterAdvanced("Keyword/Semantic Matching"); await user.click(screen.getByRole("button", { name: /add keyword rule/i })); expect(onKeywordTierRulesChange).toHaveBeenCalledTimes(1); const newRules = onKeywordTierRulesChange.mock.calls[0][0]; @@ -537,7 +549,7 @@ describe("ComplexityRouterConfig", () => { onKeywordTierRulesChange={onKeywordTierRulesChange} />, ); - fireEvent.click(screen.getByText("Advanced: Keyword/Semantic Matching")); + openAutoRouterAdvanced("Keyword/Semantic Matching"); const field = screen.getByText("Keywords 1").closest("div") as HTMLElement; await user.type(within(field).getByRole("combobox"), "invoice"); @@ -556,7 +568,7 @@ describe("ComplexityRouterConfig", () => { onKeywordTierRulesChange={onKeywordTierRulesChange} />, ); - fireEvent.click(screen.getByText("Advanced: Keyword/Semantic Matching")); + openAutoRouterAdvanced("Keyword/Semantic Matching"); expect(screen.getByText("invoice")).toBeInTheDocument(); expect(screen.getByText("refund")).toBeInTheDocument(); @@ -564,17 +576,17 @@ describe("ComplexityRouterConfig", () => { expect(onKeywordTierRulesChange).toHaveBeenCalledWith([]); }); - it("should not show embedding model or match score fields when semantic matching is disabled", () => { + it("should not show embedding model or match score fields when semantic matching is disabled", async () => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Keyword/Semantic Matching")); + openAutoRouterAdvanced("Keyword/Semantic Matching"); expect(screen.getByText("Semantic keyword matching")).toBeInTheDocument(); expect(screen.queryByText("Embedding model")).not.toBeInTheDocument(); expect(screen.queryByText("Minimum match score")).not.toBeInTheDocument(); }); - it("should show embedding model and match score fields when semantic matching is enabled", () => { + it("should show embedding model and match score fields when semantic matching is enabled", async () => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Keyword/Semantic Matching")); + openAutoRouterAdvanced("Keyword/Semantic Matching"); expect(screen.getByText("Embedding model")).toBeInTheDocument(); expect(screen.getByText("Minimum match score")).toBeInTheDocument(); }); @@ -589,7 +601,7 @@ describe("ComplexityRouterConfig", () => { onSemanticMatchingEnabledChange={onSemanticMatchingEnabledChange} />, ); - fireEvent.click(screen.getByText("Advanced: Keyword/Semantic Matching")); + openAutoRouterAdvanced("Keyword/Semantic Matching"); await user.click(screen.getByRole("switch", { name: "Semantic keyword matching" })); expect(onSemanticMatchingEnabledChange).toHaveBeenCalledWith(true, expect.anything()); }); @@ -606,34 +618,34 @@ describe("ComplexityRouterConfig", () => { expect(screen.queryAllByText("text-embedding-3-small")).toHaveLength(0); }); - it("does not show tier validation errors by default", () => { + it("does not show tier validation errors by default", async () => { renderWithProviders(); expect(screen.queryByText("This tier is required")).not.toBeInTheDocument(); }); - it("shows an inline error on the classifier model select when llm is selected without a model", () => { + it("shows an inline error on the classifier model select when llm is selected without a model", async () => { const llmValue: ComplexityRouterConfigValue = { ...defaultValue, classifier_type: "llm", classifier_llm_config: { model: "", timeout_ms: 3000 }, }; renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); - expect(screen.getByText("A classifier model is required")).toBeInTheDocument(); + openAutoRouterAdvanced("Classification Method"); + expect(screen.getByText("A judge model is required")).toBeInTheDocument(); }); - it("does not show the classifier model error once a classifier model is set", () => { + it("does not show the classifier model error once a classifier model is set", async () => { const llmValue: ComplexityRouterConfigValue = { ...defaultValue, classifier_type: "llm", classifier_llm_config: { model: "gpt-3.5-turbo", timeout_ms: 3000 }, }; renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); - expect(screen.queryByText("A classifier model is required")).not.toBeInTheDocument(); + openAutoRouterAdvanced("Classification Method"); + expect(screen.queryByText("A judge model is required")).not.toBeInTheDocument(); }); - it("shows a validation error only under unfilled tiers when showValidationErrors is true", () => { + it("shows a validation error only under unfilled tiers when showValidationErrors is true", async () => { renderWithProviders( { expect(screen.getAllByText(/tier is required/)).toHaveLength(1); }); - it("renders the escalation keywords section with current keywords when the handler is provided", () => { + it("renders the escalation keywords section with current keywords when the handler is provided", async () => { renderWithProviders( { onEscalationKeywordsChange={vi.fn()} />, ); - fireEvent.click(screen.getByText("Advanced: Escalation Keywords")); - expect(screen.getByText("Escalation Keywords")).toBeInTheDocument(); + openAutoRouterAdvanced("Escalation Keywords"); + expect(screen.getAllByText("Escalation Keywords")).not.toHaveLength(0); expect(screen.getByText("LITELLM ESCALATE")).toBeInTheDocument(); }); - it("hides the escalation keywords section when no handler is provided", () => { + it("hides the escalation keywords section when no handler is provided", async () => { renderWithProviders(); - expect(screen.queryByText("Advanced: Escalation Keywords")).not.toBeInTheDocument(); + expect(screen.queryByText("Escalation Keywords")).not.toBeInTheDocument(); }); }); @@ -671,21 +683,21 @@ describe("ComplexityRouterConfig classifier fallback", () => { classifier_llm_config: { model: "gpt-3.5-turbo", timeout_ms: 3000 }, }; - it("defaults the fallback to the heuristic, matching the backend field default", () => { + it("defaults the fallback to the heuristic, matching the backend field default", async () => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.getByRole("radio", { name: /Score with the heuristic/ })).toBeChecked(); }); - it("records a switch to the default model fallback", () => { + it("records a switch to the default model fallback", async () => { const onChange = vi.fn(); renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); fireEvent.click(screen.getByRole("radio", { name: /Route to the default model/ })); expect(onChange).toHaveBeenCalledWith(expect.objectContaining({ classifier_fallback: "default_model" })); }); - it("disables the default model fallback when no tier would produce one", () => { + it("disables the default model fallback when no tier would produce one", async () => { // The deployment's default model is derived from the tiers on submit, so offering the option // with no tiers picked would save a config the backend rejects at startup. const noTiers: ComplexityRouterConfigValue = { @@ -693,17 +705,17 @@ describe("ComplexityRouterConfig classifier fallback", () => { tiers: { SIMPLE: [], MEDIUM: [], COMPLEX: [], REASONING: [] }, }; renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.getByRole("radio", { name: /Route to the default model/ })).toHaveAttribute("aria-disabled", "true"); }); - it("hides the fallback choice for the heuristic classifier, which has nothing to fall back from", () => { + it("hides the fallback choice for the heuristic classifier, which has nothing to fall back from", async () => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.queryByText("If the classifier fails")).not.toBeInTheDocument(); }); - it("stops describing the heuristic as the fallback once a custom prompt routes failures to the default model", () => { + it("stops describing the heuristic as the fallback once a custom prompt routes failures to the default model", async () => { // With both set, the heuristic scorer never runs, so the panel must not keep implying a // score decides anything on this router. renderWithProviders( @@ -717,11 +729,11 @@ describe("ComplexityRouterConfig classifier fallback", () => { onChange={vi.fn()} />, ); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.getByText(/no longer runs at all/)).toBeInTheDocument(); }); - it("still describes the heuristic as the fallback when a custom prompt keeps heuristic fallback", () => { + it("still describes the heuristic as the fallback when a custom prompt keeps heuristic fallback", async () => { renderWithProviders( { onChange={vi.fn()} />, ); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.getByText(/only when the classifier call fails/)).toBeInTheDocument(); }); - it("clears a stored fallback when switching back to the heuristic classifier", () => { + it("clears a stored fallback when switching back to the heuristic classifier", async () => { const onChange = vi.fn(); renderWithProviders( { onChange={onChange} />, ); - fireEvent.click(screen.getByText("Advanced: Classification Method")); - fireEvent.click(screen.getByRole("radio", { name: /rule-based scoring/ })); + openAutoRouterAdvanced("Classification Method"); + fireEvent.click(screen.getByRole("radio", { name: /^Heuristics$/ })); expect(onChange).toHaveBeenCalledWith(expect.objectContaining({ classifier_fallback: undefined })); }); }); @@ -758,19 +770,21 @@ describe("ComplexityRouterConfig classification frequency", () => { classifier_llm_config: { model: "gpt-3.5-turbo", timeout_ms: 3000 }, }; - it("defaults to every request, matching both backend field defaults", () => { + it("defaults to every request, matching both backend field defaults", async () => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); - expect(screen.getByRole("radio", { name: /Every request/ })).toBeChecked(); - expect(screen.getByRole("radio", { name: /Every new user message/ })).not.toBeChecked(); - expect(screen.getByRole("radio", { name: /Once per session/ })).not.toBeChecked(); + openAutoRouterAdvanced("Classification Method"); + expect(screen.getByRole("combobox", { name: "How often to classify" })).toHaveTextContent("Every request"); + expect(screen.getByRole("combobox", { name: "How often to classify" })).not.toHaveTextContent( + "Every new user message", + ); + expect(screen.getByRole("combobox", { name: "How often to classify" })).not.toHaveTextContent("Once per session"); }); - it("writes both wire fields when the frequency moves to every new user message", () => { + it("writes both wire fields when the frequency moves to every new user message", async () => { const onChange = vi.fn(); renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); - fireEvent.click(screen.getByRole("radio", { name: /Every new user message/ })); + openAutoRouterAdvanced("Classification Method"); + await selectAutoRouterOption("How often to classify", "Every new user message"); expect(onChange).toHaveBeenCalledWith({ ...llmValue, classification_mode: "user_turn", @@ -778,11 +792,11 @@ describe("ComplexityRouterConfig classification frequency", () => { }); }); - it("writes session affinity, not a classification mode, when the frequency moves to once per session", () => { + it("writes session affinity, not a classification mode, when the frequency moves to once per session", async () => { const onChange = vi.fn(); renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); - fireEvent.click(screen.getByRole("radio", { name: /Once per session/ })); + openAutoRouterAdvanced("Classification Method"); + await selectAutoRouterOption("How often to classify", "Once per session"); expect(onChange).toHaveBeenCalledWith({ ...llmValue, classification_mode: "every_request", @@ -790,7 +804,7 @@ describe("ComplexityRouterConfig classification frequency", () => { }); }); - it("shows a hand-authored config that sets both fields as once per session, matching the backend", () => { + it("shows a hand-authored config that sets both fields as once per session, matching the backend", async () => { renderWithProviders( { onChange={vi.fn()} />, ); - fireEvent.click(screen.getByText("Advanced: Classification Method")); - expect(screen.getByRole("radio", { name: /Once per session/ })).toBeChecked(); - expect(screen.getByRole("radio", { name: /Every new user message/ })).not.toBeChecked(); + openAutoRouterAdvanced("Classification Method"); + expect(screen.getByRole("combobox", { name: "How often to classify" })).toHaveTextContent("Once per session"); + expect(screen.getByRole("combobox", { name: "How often to classify" })).not.toHaveTextContent( + "Every new user message", + ); }); - it("records a switch back to every request", () => { + it("records a switch back to every request", async () => { const onChange = vi.fn(); renderWithProviders( { onChange={onChange} />, ); - fireEvent.click(screen.getByText("Advanced: Classification Method")); - expect(screen.getByRole("radio", { name: /Every new user message/ })).toBeChecked(); - fireEvent.click(screen.getByRole("radio", { name: /Every request/ })); + openAutoRouterAdvanced("Classification Method"); + expect(screen.getByRole("combobox", { name: "How often to classify" })).toHaveTextContent("Every new user message"); + await selectAutoRouterOption("How often to classify", "Every request"); expect(onChange).toHaveBeenCalledWith(expect.objectContaining({ classification_mode: "every_request" })); }); - it("offers the frequency on a heuristic router, where holding the tier still pins the model", () => { + it("offers the frequency on a heuristic router, where holding the tier still pins the model", async () => { // The backend pin is gated on the two fields alone, so a heuristic router that switches models // mid tool loop is fixed by this control too. renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); - expect(screen.getByRole("radio", { name: /Every new user message/ })).toBeInTheDocument(); + openAutoRouterAdvanced("Classification Method"); + expect(screen.getByRole("combobox", { name: "How often to classify" })).toBeVisible(); }); }); @@ -836,11 +852,11 @@ describe("ComplexityRouterConfig classifier rubric", () => { const openClassificationPanel = (value: ComplexityRouterConfigValue, onChange = vi.fn()) => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); return onChange; }; - it("shows an existing router with no stored preset as legacy in the prompt control", () => { + it("shows an existing router with no stored preset as legacy in the prompt control", async () => { // This router predates the setting. Displaying a calibrated preset it does not have would tell the // operator their traffic is graded by examples the classifier never receives, and saving the form // unchanged would then move its tier decisions. @@ -849,19 +865,19 @@ describe("ComplexityRouterConfig classifier rubric", () => { expect(screen.getByRole("button", { name: "Customize prompt" })).toBeInTheDocument(); }); - it("stamps the calibrated preset on a classifier being switched on for the first time", () => { + it("stamps the calibrated preset on a classifier being switched on for the first time", async () => { // A heuristic router turning on the LLM classifier has no prior tier behaviour to preserve, so a // newly configured classifier starts on the calibrated rubric rather than the legacy one. const onChange = vi.fn(); renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); - fireEvent.click(screen.getByText("LLM Classifier")); + openAutoRouterAdvanced("Classification Method"); + fireEvent.click(screen.getByRole("radio", { name: /^LLM$/ })); expect(onChange).toHaveBeenCalledWith( expect.objectContaining({ classifier_llm_config: expect.objectContaining({ classification_rubric: "agentic" }) }), ); }); - it("shows the calibrated preset when a router stores one", () => { + it("shows the calibrated preset when a router stores one", async () => { openClassificationPanel({ ...llmValue, classifier_llm_config: { model: "gpt-3.5-turbo", timeout_ms: 3000, classification_rubric: "agentic" }, @@ -906,7 +922,7 @@ describe("ComplexityRouterConfig classifier rubric", () => { ); }); - it("keeps the rubric out of the legacy whole-prompt editor, which replaces it entirely", () => { + it("keeps the rubric out of the legacy whole-prompt editor, which replaces it entirely", async () => { // The backend rejects both together, so the legacy editor must not offer a rubric to pick. openClassificationPanel({ ...llmValue, @@ -916,7 +932,7 @@ describe("ComplexityRouterConfig classifier rubric", () => { expect(screen.queryByRole("button", { name: "Customize prompt" })).not.toBeInTheDocument(); }); - it("hides the prompt control for the heuristic classifier, which sends no prompt at all", () => { + it("hides the prompt control for the heuristic classifier, which sends no prompt at all", async () => { openClassificationPanel(defaultValue); expect(screen.queryByRole("button", { name: "Customize prompt" })).not.toBeInTheDocument(); }); @@ -928,7 +944,7 @@ describe("ComplexityRouterConfig tier labels", () => { tier_labels: { SIMPLE: "Cheap", MEDIUM: "Standard", COMPLEX: "Premium", REASONING: "Deep" }, }; - it("shows the operator's names in the tier headers instead of the defaults", () => { + it("shows the operator's names in the tier headers instead of the defaults", async () => { renderWithProviders(); expect(screen.getByText("Cheap Tier")).toBeInTheDocument(); expect(screen.getByText("Deep Tier")).toBeInTheDocument(); @@ -936,13 +952,13 @@ describe("ComplexityRouterConfig tier labels", () => { expect(screen.queryByText("Reasoning Tier")).not.toBeInTheDocument(); }); - it("keeps the rung ordinal and canonical name visible under a rename", () => { + it("keeps the rung ordinal and canonical name visible under a rename", async () => { renderWithProviders(); expect(screen.getByText(/Tier 1 of 4/)).toHaveTextContent("Tier 1 of 4 · SIMPLE"); expect(screen.getByText(/Tier 4 of 4/)).toHaveTextContent("Tier 4 of 4 · REASONING"); }); - it("names the renamed tier in the required-field error", () => { + it("names the renamed tier in the required-field error", async () => { renderWithProviders( { expect(screen.getByText("The Deep tier is required")).toBeInTheDocument(); }); - it("reports a typed label back to the caller under its canonical tier key", () => { + it("reports a typed label back to the caller under its canonical tier key", async () => { const onChange = vi.fn(); renderWithProviders(); fireEvent.change(screen.getByLabelText("Display name for the Simple tier"), { target: { value: "Cheap" } }); expect(onChange).toHaveBeenCalledWith(expect.objectContaining({ tier_labels: { SIMPLE: "Cheap" } })); }); - it("shows a stored label in its input so an edit round-trips", () => { + it("shows a stored label in its input so an edit round-trips", async () => { renderWithProviders(); expect(screen.getByLabelText("Display name for the Reasoning tier")).toHaveValue("Deep"); }); - it("leaves the label inputs empty when nothing was renamed", () => { + it("leaves the label inputs empty when nothing was renamed", async () => { renderWithProviders(); expect(screen.getByLabelText("Display name for the Simple tier")).toHaveValue(""); }); - it("uses the operator's names in the classification score table", () => { + it("uses the operator's names in the classification score table", async () => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.getByText("Cheap")).toBeInTheDocument(); expect(screen.getByText("Deep")).toBeInTheDocument(); }); - it("uses the operator's names in the keyword rule tier picker", () => { + it("uses the operator's names in the keyword rule tier picker", async () => { renderWithProviders( { keywordTierRules={[{ id: "r1", keywords: ["invoice"], tier: "REASONING" }]} />, ); - fireEvent.click(screen.getByText("Advanced: Keyword/Semantic Matching")); + openAutoRouterAdvanced("Keyword/Semantic Matching"); expect(screen.getByRole("combobox", { name: "Route keyword rule 1 to tier" })).toHaveTextContent("Deep"); }); }); describe("ComplexityRouterConfig modality panel", () => { - it("defaults the image-routing switch off and writes modality_routing through onChange", () => { + it("defaults the image-routing switch off and writes modality_routing through onChange", async () => { const onChange = vi.fn(); renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Modality Routing")); + openAutoRouterAdvanced("Modality Routing"); const toggle = screen.getByRole("switch", { name: "Route image requests to vision-capable models" }); expect(toggle).not.toBeChecked(); @@ -1003,19 +1019,19 @@ describe("ComplexityRouterConfig modality panel", () => { expect(onChange).toHaveBeenCalledWith({ ...defaultValue, modality_routing: true }); }); - it("renders a stored modality_routing=true as on", () => { + it("renders a stored modality_routing=true as on", async () => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Modality Routing")); + openAutoRouterAdvanced("Modality Routing"); expect(screen.getByRole("switch", { name: "Route image requests to vision-capable models" })).toBeChecked(); }); // The backend ignores modality_pin_override unless modality_routing is on, so offering it while // image routing is off would let an operator save a flag that does nothing. - it("disables the pin-override switch while image routing is off", () => { + it("disables the pin-override switch while image routing is off", async () => { const onChange = vi.fn(); renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Modality Routing")); + openAutoRouterAdvanced("Modality Routing"); const override = screen.getByRole("switch", { name: "Override session pin for image requests" }); expect(override).toHaveAttribute("aria-disabled", "true"); @@ -1023,11 +1039,11 @@ describe("ComplexityRouterConfig modality panel", () => { expect(onChange).not.toHaveBeenCalled(); }); - it("writes modality_pin_override through onChange once image routing is on", () => { + it("writes modality_pin_override through onChange once image routing is on", async () => { const onChange = vi.fn(); const value = { ...defaultValue, modality_routing: true }; renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Modality Routing")); + openAutoRouterAdvanced("Modality Routing"); const override = screen.getByRole("switch", { name: "Override session pin for image requests" }); expect(override).not.toBeChecked(); @@ -1036,51 +1052,51 @@ describe("ComplexityRouterConfig modality panel", () => { expect(onChange).toHaveBeenCalledWith({ ...value, modality_pin_override: true }); }); - it("renders a stored modality_pin_override=true as on", () => { + it("renders a stored modality_pin_override=true as on", async () => { renderWithProviders( , ); - fireEvent.click(screen.getByText("Advanced: Modality Routing")); + openAutoRouterAdvanced("Modality Routing"); expect(screen.getByRole("switch", { name: "Override session pin for image requests" })).toBeChecked(); }); }); describe("ComplexityRouterConfig affinity panel", () => { - it("holds the deployment switch at its backend default, session pinning having moved to the frequency choice", () => { + it("holds the deployment switch at its backend default, session pinning having moved to the frequency choice", async () => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Affinity")); + openAutoRouterAdvanced("Affinity"); expect(screen.getByRole("switch", { name: "Pin one model deployment per tier" })).toBeChecked(); expect(screen.queryByRole("switch", { name: "Pin a session to its first model" })).not.toBeInTheDocument(); }); - it("writes deployment_affinity through onChange without touching other keys", () => { + it("writes deployment_affinity through onChange without touching other keys", async () => { const onChange = vi.fn(); renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Affinity")); + openAutoRouterAdvanced("Affinity"); fireEvent.click(screen.getByRole("switch", { name: "Pin one model deployment per tier" })); expect(onChange).toHaveBeenCalledWith({ ...defaultValue, deployment_affinity: false }); }); - it("renders a stored deployment_affinity=false as off", () => { + it("renders a stored deployment_affinity=false as off", async () => { renderWithProviders( , ); - fireEvent.click(screen.getByText("Advanced: Affinity")); + openAutoRouterAdvanced("Affinity"); expect(screen.getByRole("switch", { name: "Pin one model deployment per tier" })).not.toBeChecked(); }); - it("writes an idle TTL on blur and keeps the partial input as a draft while typing", () => { + it("writes an idle TTL on blur and keeps the partial input as a draft while typing", async () => { const onChange = vi.fn(); renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Affinity")); + openAutoRouterAdvanced("Affinity"); const ttl = screen.getByLabelText("How long a pin survives idle (seconds)"); expect(ttl).toHaveAttribute("placeholder", "3600"); @@ -1091,11 +1107,11 @@ describe("ComplexityRouterConfig affinity panel", () => { expect(onChange).toHaveBeenCalledWith({ ...defaultValue, session_affinity_ttl_seconds: 300 }); }); - it("clearing the idle TTL returns the router to its backend default", () => { + it("clearing the idle TTL returns the router to its backend default", async () => { const onChange = vi.fn(); const value = { ...defaultValue, session_affinity_ttl_seconds: 300 }; renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Affinity")); + openAutoRouterAdvanced("Affinity"); const ttl = screen.getByLabelText("How long a pin survives idle (seconds)"); expect(ttl).toHaveValue("300"); @@ -1105,10 +1121,10 @@ describe("ComplexityRouterConfig affinity panel", () => { expect(onChange).toHaveBeenCalledWith({ ...value, session_affinity_ttl_seconds: undefined }); }); - it("clamps a non-positive idle TTL to the backend's minimum", () => { + it("clamps a non-positive idle TTL to the backend's minimum", async () => { const onChange = vi.fn(); renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Affinity")); + openAutoRouterAdvanced("Affinity"); const ttl = screen.getByLabelText("How long a pin survives idle (seconds)"); fireEvent.change(ttl, { target: { value: "0" } }); @@ -1121,12 +1137,12 @@ describe("ComplexityRouterConfig affinity panel", () => { describe("ComplexityRouterConfig default model", () => { const getDefaultModelSelect = () => screen.getByRole("combobox", { name: "Default model" }); - it("shows what the tiers currently imply, so an untouched router still names its default", () => { + it("shows what the tiers currently imply, so an untouched router still names its default", async () => { renderWithProviders(); expect(getDefaultModelSelect()).toHaveAttribute("placeholder", "Derived from tiers: gpt-3.5-turbo"); }); - it("asks for a model rather than naming a derived one when no tier holds one", () => { + it("asks for a model rather than naming a derived one when no tier holds one", async () => { const noTiers: ComplexityRouterConfigValue = { ...defaultValue, tiers: { SIMPLE: [], MEDIUM: [], COMPLEX: [], REASONING: [] }, @@ -1157,13 +1173,13 @@ describe("ComplexityRouterConfig default model", () => { expect(onChange).toHaveBeenCalledWith(expect.objectContaining({ default_model: undefined })); }); - it("shows a pinned model as the selection instead of the tier-derived one", () => { + it("shows a pinned model as the selection instead of the tier-derived one", async () => { const pinned: ComplexityRouterConfigValue = { ...defaultValue, default_model: "claude-3-opus" }; renderWithProviders(); expect(getDefaultModelSelect()).toHaveValue("claude-3-opus"); }); - it("unlocks the default model fallback on a pin alone, with no tier to derive from", () => { + it("unlocks the default model fallback on a pin alone, with no tier to derive from", async () => { const pinnedNoTiers: ComplexityRouterConfigValue = { ...defaultValue, classifier_type: "llm", @@ -1172,11 +1188,11 @@ describe("ComplexityRouterConfig default model", () => { default_model: "claude-3-opus", }; renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.getByRole("radio", { name: /Route to the default model/ })).not.toHaveAttribute("aria-disabled"); }); - it("names the resolved default on the fallback option, so the destination is not a guess", () => { + it("names the resolved default on the fallback option, so the destination is not a guess", async () => { const pinned: ComplexityRouterConfigValue = { ...defaultValue, classifier_type: "llm", @@ -1184,13 +1200,13 @@ describe("ComplexityRouterConfig default model", () => { default_model: "claude-3-opus", }; renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.getByRole("radio", { name: /Route to the default model \(claude-3-opus\)/ })).toBeInTheDocument(); }); }); describe("plan-mode override", () => { - const openPanel = () => fireEvent.click(screen.getByText("Advanced: Plan-Mode Override")); + const openPanel = () => openAutoRouterAdvanced("Plan-Mode Override"); const switchName = "Route plan-mode requests to a minimum tier"; it("toggling on floors at the highest tier that has models", async () => { @@ -1248,13 +1264,13 @@ describe("plan-mode override", () => { }); describe("ComplexityRouterConfig per-model reasoning effort", () => { - it("renders one effort select per selected model, defaulting to Default", () => { + it("renders one effort select per selected model, defaulting to Default", async () => { renderWithProviders(); const select = screen.getByRole("combobox", { name: "Reasoning effort for gpt-4 in the Complex tier" }); expect(select).toHaveTextContent("Default"); }); - it("shows the hydrated effort for a model that has one stored", () => { + it("shows the hydrated effort for a model that has one stored", async () => { renderWithProviders( { const renderClassifier = (value: ComplexityRouterConfigValue = llmValue, onChange = vi.fn()) => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); return onChange; }; @@ -1348,7 +1364,7 @@ describe("ComplexityRouterConfig classifier reasoning effort", () => { classifier_llm_config: { model: "gpt-4", timeout_ms: 3000, reasoning_effort: "high" }, }); const user = userEvent.setup(); - await user.click(screen.getByRole("combobox", { name: "Classifier Model" })); + await user.click(screen.getByRole("combobox", { name: "Judge model" })); await user.click(await screen.findByRole("option", { name: "gpt-3.5-turbo" })); expect(onChange).toHaveBeenCalledWith({ ...llmValue, @@ -1364,7 +1380,7 @@ describe("ComplexityRouterConfig classifier reasoning effort", () => { classifier_llm_config: { model: "gpt-4", timeout_ms: 3000, reasoning_effort: "high" }, }); const user = userEvent.setup(); - await user.click(screen.getByRole("combobox", { name: "Classifier Model" })); + await user.click(screen.getByRole("combobox", { name: "Judge model" })); if (action === "click") await user.click(await screen.findByRole("option", { name: "gpt-4" })); else await user.keyboard("{Enter}"); expect(onChange).not.toHaveBeenCalled(); @@ -1397,7 +1413,7 @@ describe("ComplexityRouterConfig classifier reasoning effort", () => { }); describe("ComplexityRouterConfig reasoning effort gating", () => { - it("offers no effort select for a model group without reasoning support", () => { + it("offers no effort select for a model group without reasoning support", async () => { renderWithProviders(); expect( screen.queryByRole("combobox", { name: "Reasoning effort for gpt-3.5-turbo in the Simple tier" }), @@ -1406,7 +1422,7 @@ describe("ComplexityRouterConfig reasoning effort gating", () => { // A stored effort on a model the group info calls non-reasoning must stay visible, or the // operator has no way to clear it. - it("keeps the select for a non-reasoning model that already has a stored effort", () => { + it("keeps the select for a non-reasoning model that already has a stored effort", async () => { renderWithProviders( { // An empty list is the group's own answer that its deployments share no level, which is different // from the field being absent, so the control is dropped rather than falling back to every level. - it("offers no effort at all when the group intersects to nothing", () => { + it("offers no effort at all when the group intersects to nothing", async () => { renderWithProviders( { // Hand-authored configs can carry a level outside the supported set (e.g. max); it must render // and stay clearable rather than being masked as Default. - it("keeps showing a stored effort outside the supported set", () => { + it("keeps showing a stored effort outside the supported set", async () => { renderWithProviders( { describe("ComplexityRouterConfig custom technical keywords", () => { const openClassificationPanel = (value: ComplexityRouterConfigValue) => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); }; const llmConfig = { model: "gpt-3.5-turbo", timeout_ms: 3000 }; @@ -1503,7 +1519,7 @@ describe("ComplexityRouterConfig custom technical keywords", () => { expect(screen.getByText("Custom Technical Keywords")).toBeInTheDocument(); }); - it("hides the keywords when the scorer never runs, so they cannot imply an effect they have none", () => { + it("hides the keywords when the scorer never runs, so they cannot imply an effect they have none", async () => { const llmWithDefaultFallback = { ...defaultValue, classifier_type: "llm" as const, @@ -1547,19 +1563,19 @@ describe("ComplexityRouterConfig tier editing", () => { }, }; - it("offers Edit tiers only when the parent owns the editor flag", () => { + it("offers Edit tiers only when the parent owns the editor flag", async () => { renderWithProviders(); expect(screen.queryByRole("button", { name: "Edit tiers" })).not.toBeInTheDocument(); }); - it("surfaces the caller's orphaned-rule verdict while editing, so Done is not a silent exit", () => { + it("surfaces the caller's orphaned-rule verdict while editing, so Done is not a silent exit", async () => { renderEditor(customValue, { keywordRulesError: "Keyword rule(s) 1 route to a tier this router no longer has" }); expect( screen.getByText("Keyword rule(s) 1 route to a tier this router no longer has", { exact: false }), ).toBeInTheDocument(); }); - it("keeps the orphaned-rule verdict out of the collapsed view, where the submit tooltip owns it", () => { + it("keeps the orphaned-rule verdict out of the collapsed view, where the submit tooltip owns it", async () => { renderWithProviders( { expect(screen.queryByText("route to a tier this router no longer has", { exact: false })).not.toBeInTheDocument(); }); - it("renders the four built-in tiers before any edit, unchanged", () => { + it("renders the four built-in tiers before any edit, unchanged", async () => { renderWithProviders(); expect(screen.getByRole("button", { name: "Edit tiers" })).toBeInTheDocument(); expect(screen.getByText("Tier 1 of 4", { exact: false })).toHaveTextContent("SIMPLE"); }); - it("adds a row and moves the form into an edited tier set, which the built-in record never leaves", () => { + it("adds a row and moves the form into an edited tier set, which the built-in record never leaves", async () => { const { committed } = renderEditor(); fireEvent.click(screen.getByRole("button", { name: "Add tier" })); const next = committed(); @@ -1585,7 +1601,7 @@ describe("ComplexityRouterConfig tier editing", () => { expect(next.tiers).toEqual(defaultValue.tiers); }); - it("renames a built-in tier straight from the editor, which is what makes the set custom", () => { + it("renames a built-in tier straight from the editor, which is what makes the set custom", async () => { const { committed } = renderEditor(); fireEvent.change(screen.getByLabelText("Name for tier 3"), { target: { value: "SECURITY_REVIEW" } }); const next = committed(); @@ -1598,13 +1614,13 @@ describe("ComplexityRouterConfig tier editing", () => { expect(next.tiers).toEqual(defaultValue.tiers); }); - it("opening the editor and changing nothing leaves the router on the built-in tiers", () => { + it("opening the editor and changing nothing leaves the router on the built-in tiers", async () => { const { onChange } = renderEditor(); expect(screen.getByRole("button", { name: "Done" })).toBeEnabled(); expect(onChange).not.toHaveBeenCalled(); }); - it("swaps the display-name field for the tier-name field while the editor is open", () => { + it("swaps the display-name field for the tier-name field while the editor is open", async () => { const { rerender } = renderWithProviders(); expect(screen.getByLabelText("Display name for the Simple tier")).toBeInTheDocument(); rerender(); @@ -1612,23 +1628,23 @@ describe("ComplexityRouterConfig tier editing", () => { expect(screen.getByLabelText("Name for tier 1")).toBeInTheDocument(); }); - it("drops the scorer card entirely once an edited tier set replaces the heuristic", () => { + it("drops the scorer card entirely once an edited tier set replaces the heuristic", async () => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.queryByText("How Classification Works")).not.toBeInTheDocument(); expect( screen.queryByText("scores each request across 7 built-in dimensions", { exact: false }), ).not.toBeInTheDocument(); }); - it("keeps the scorer card on a built-in router, whose tiers the score still decides", () => { + it("keeps the scorer card on a built-in router, whose tiers the score still decides", async () => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.getByText("How Classification Works")).toBeInTheDocument(); expect(screen.getByText("scores each request across 7 built-in dimensions", { exact: false })).toBeInTheDocument(); }); - it("says why a custom row is blocked instead of only reddening its border", () => { + it("says why a custom row is blocked instead of only reddening its border", async () => { const missingDefinition: ComplexityRouterConfigValue = { ...customValue, custom_tier_set: { @@ -1652,24 +1668,24 @@ describe("ComplexityRouterConfig tier editing", () => { expect(screen.getByRole("button", { name: "Done" })).toBeDisabled(); }); - it("enables Done once every row carries a name, a definition and a model", () => { + it("enables Done once every row carries a name, a definition and a model", async () => { renderEditor(customValue); expect(screen.getByRole("button", { name: "Done" })).toBeEnabled(); }); - it("refuses to remove a row that would take the set below the backend's minimum", () => { + it("refuses to remove a row that would take the set below the backend's minimum", async () => { renderEditor(customValue); expect(screen.getByRole("button", { name: "Remove the CASUAL tier" })).toBeDisabled(); }); - it("keeps a definition on one line, because the backend rejects a newline in it", () => { + it("keeps a definition on one line, because the backend rejects a newline in it", async () => { const { committed } = renderEditor(customValue); fireEvent.change(screen.getByLabelText("Definition for tier 2"), { target: { value: "audits\nand reviews" } }); const next = committed(); expect(next.custom_tier_set?.tiers[1].definition).toBe("audits and reviews"); }); - it("moves a keyword rule with the tier it points at when that tier is renamed", () => { + it("moves a keyword rule with the tier it points at when that tier is renamed", async () => { const onKeywordTierRulesChange = vi.fn(); renderWithProviders( { expect(onKeywordTierRulesChange).toHaveBeenCalledWith([{ id: "r1", keywords: ["audit"], tier: "AUDIT" }]); }); - it("re-points the fallback tier when the row it named is removed, never leaving it dangling", () => { + it("re-points the fallback tier when the row it named is removed, never leaving it dangling", async () => { const threeRows: ComplexityRouterConfigValue = { ...customValue, custom_tier_set: { @@ -1702,7 +1718,7 @@ describe("ComplexityRouterConfig tier editing", () => { expect(next.custom_tier_set?.tiers.some((row) => row.id === next.custom_tier_set?.fallback_tier_id)).toBe(true); }); - it("turns off a plan-mode floor whose row was removed, rather than leaving it pointing at nothing", () => { + it("turns off a plan-mode floor whose row was removed, rather than leaving it pointing at nothing", async () => { const withFloor: ComplexityRouterConfigValue = { ...customValue, plan_mode_min_tier: "sec", @@ -1719,14 +1735,14 @@ describe("ComplexityRouterConfig tier editing", () => { expect(committed().plan_mode_min_tier).toBeUndefined(); }); - it("replaces the display-name inputs with the reason an edited tier set forbids them", () => { + it("replaces the display-name inputs with the reason an edited tier set forbids them", async () => { renderWithProviders(); expect(screen.queryByLabelText("Display name for the Simple tier")).not.toBeInTheDocument(); expect(screen.getByText("Display names rename the built-in tiers", { exact: false })).toBeInTheDocument(); expect(screen.getByLabelText("Fallback tier")).toBeInTheDocument(); }); - it("disables the once-per-session frequency and says why, rather than letting a stripped value look saved", () => { + it("disables the once-per-session frequency and says why, rather than letting a stripped value look saved", async () => { renderWithProviders( { onEditingTiersChange={vi.fn()} />, ); - fireEvent.click(screen.getByText("Advanced: Classification Method")); - const sessionOption = screen.getByRole("radio", { name: /Once per session/ }); + openAutoRouterAdvanced("Classification Method"); + fireEvent.click(screen.getByRole("combobox", { name: "How often to classify" })); + const sessionOption = screen.getByRole("option", { name: "Once per session" }); expect(sessionOption).toHaveAttribute("aria-disabled", "true"); expect(sessionOption).not.toBeChecked(); expect( @@ -1743,15 +1760,15 @@ describe("ComplexityRouterConfig tier editing", () => { ).toBeInTheDocument(); }); - it("lets an edited tier set write its own opening instructions instead of refusing a prompt outright", () => { + it("lets an edited tier set write its own opening instructions instead of refusing a prompt outright", async () => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.getByText("your own calibration examples", { exact: false })).toBeInTheDocument(); expect(screen.getByRole("button", { name: "Customize prompt" })).toBeInTheDocument(); expect(screen.queryByText("A replacement prompt drops the tier bullets", { exact: false })).not.toBeInTheDocument(); }); - it("gives built-in routers the opening-only editor, keeping the tier definitions derived", () => { + it("gives built-in routers the opening-only editor, keeping the tier definitions derived", async () => { renderWithProviders( { onEditingTiersChange={vi.fn()} />, ); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.getByText("The base rubric supplies", { exact: false })).toBeInTheDocument(); expect(screen.getByRole("button", { name: "Customize prompt" })).toBeInTheDocument(); expect(screen.queryByText("Replace the built-in complexity rubric", { exact: false })).not.toBeInTheDocument(); }); - it("keeps the legacy whole-prompt editor only on a router that already stored a replacement prompt", () => { + it("keeps the legacy whole-prompt editor only on a router that already stored a replacement prompt", async () => { renderWithProviders( { onEditingTiersChange={vi.fn()} />, ); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.getByRole("button", { name: "Edit custom prompt" })).toBeInTheDocument(); expect(screen.queryByRole("button", { name: "Customize prompt" })).not.toBeInTheDocument(); }); - it("leaves built-in routers with their display-name inputs and no restriction copy", () => { + it("leaves built-in routers with their display-name inputs and no restriction copy", async () => { renderWithProviders(); expect(screen.getByLabelText("Display name for the Simple tier")).toBeInTheDocument(); expect(screen.queryByText("Display names rename the built-in tiers", { exact: false })).not.toBeInTheDocument(); @@ -1810,9 +1827,9 @@ describe("classifier vision settings", () => { ); }; - it("starts off and reveals the default cap when enabled", () => { + it("starts off and reveals the default cap when enabled", async () => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); const vision = screen.getByRole("switch", { name: "Use images for classification" }); expect(vision).not.toBeChecked(); @@ -1823,10 +1840,10 @@ describe("classifier vision settings", () => { expect(screen.getByLabelText("Maximum images per request")).toHaveValue("1"); }); - it("writes the switch and a clamped image cap into the classifier config", () => { + it("writes the switch and a clamped image cap into the classifier config", async () => { const onChange = vi.fn(); renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); fireEvent.click(screen.getByRole("switch", { name: "Use images for classification" })); expect(onChange).toHaveBeenLastCalledWith({ @@ -1841,10 +1858,10 @@ describe("classifier vision settings", () => { }); }); - it("keeps the image cap draft empty until a valid value is entered", () => { + it("keeps the image cap draft empty until a valid value is entered", async () => { const onChange = vi.fn(); renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); fireEvent.click(screen.getByRole("switch", { name: "Use images for classification" })); onChange.mockClear(); @@ -1861,9 +1878,9 @@ describe("classifier vision settings", () => { }); }); - it("is absent when the classifier is heuristic", () => { + it("is absent when the classifier is heuristic", async () => { renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Classification Method")); + openAutoRouterAdvanced("Classification Method"); expect(screen.queryByText("Use images for classification")).not.toBeInTheDocument(); }); diff --git a/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.tsx b/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.tsx index acf6b62a95a..32f9ebf97ad 100644 --- a/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.tsx +++ b/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.tsx @@ -1,4 +1,6 @@ import RoutingOptions from "./RoutingOptions"; +import ClassifierPrimarySettings from "./ClassifierPrimarySettings"; +import { AutoRouterAllowanceNote } from "./AutoRouterAvailability"; import type { JevClassifierConfig } from "./jev_classifier_config"; import { type ClassifierType } from "./classifier_types"; export { type ClassifierType, usesLlmClassifier, usesClassifierContext } from "./classifier_types"; @@ -6,11 +8,11 @@ import ForecastClassifierConfig, { ForecastSolverModels } from "./ForecastClassi import { isForecastClassifier, type CapabilitySettings, type FuseSettings } from "./forecast_classifier_config"; import { SimpleTooltip } from "@/components/ui/tooltip"; import { MultiSelect } from "@/components/shared/MultiSelect"; +import TierConfigIntro from "./TierConfigIntro"; import DefaultModelField from "./DefaultModelField"; import { Info, Plus, Trash2, X } from "lucide-react"; import NonReasoningTierToggle from "./NonReasoningTierToggle"; -import TierConfigIntro from "./TierConfigIntro"; import TierRowSelect from "./TierRowSelect"; import { Card, CardContent } from "@/components/ui/card"; import { InputGroup, InputGroupAddon, InputGroupButton, InputGroupInput } from "@/components/ui/input-group"; @@ -226,10 +228,16 @@ const TierSetToolbar: React.FC<{ ) )} + {editing && ( + + )} {editing && ( Add or remove tiers to define your own set. Every custom tier needs a definition the classifier routes on, and - an edited set requires the LLM or JEV classification method + an edited set requires the LLM or Jev classification method )} {editing && keywordRulesError && ( @@ -596,10 +604,14 @@ const ComplexityRouterConfig: React.FC = ({ return (
+
-

- {forecast ? "Solver models" : "Complexity Tier Configuration"} -

+

{forecast ? "Solver models" : "Models by tier"}

{!forecast && ( @@ -619,6 +631,7 @@ const ComplexityRouterConfig: React.FC = ({ fastModeByModel={fastModeByModel} /> = ({ ) : ( <> - {!customTierSet && ( @@ -750,13 +762,19 @@ const ComplexityRouterConfig: React.FC = ({ )} - {!forecast && } + - + {forecast && ( <> - void>(); renderWithProviders(); - await user.click(screen.getByRole("button", { name: "Advanced routing options" })); + openAutoRouterAdvanced("Keyword/Semantic Matching"); expect(screen.getByRole("switch", { name: "Fast mode for secondary in the Medium routing pool tier" })).toBeChecked(); expect(onChange).not.toHaveBeenCalled(); await user.click(screen.getByRole("combobox", { name: "Select medium routing pool models" })); @@ -245,7 +246,7 @@ it.each(["capability", "llm_v2"] as const)( ); const view = renderWithProviders(editor(hydrateComplexityRouterConfig(stored, undefined))); - await user.click(screen.getByRole("button", { name: "Advanced routing options" })); + openAutoRouterAdvanced("Keyword/Semantic Matching"); const select = () => screen.getByRole("combobox", { name: "Default model" }); expect(select()).toHaveValue("legacy-default"); expect(onChange).not.toHaveBeenCalled(); @@ -284,8 +285,8 @@ it.each(["capability", "llm_v2"] as const)("offers only populated keyword target /> ); const view = renderWithProviders(editor([])); - await user.click(screen.getByRole("button", { name: "Advanced routing options" })); - await user.click(screen.getByText("Advanced: Keyword/Semantic Matching")); + openAutoRouterAdvanced("Keyword/Semantic Matching"); + openAutoRouterAdvanced("Keyword/Semantic Matching"); await user.click(screen.getByRole("button", { name: "Add keyword rule" })); const rules = onRulesChange.mock.lastCall![0]; expect(rules[0].tier).toBe("SIMPLE"); diff --git a/ui/litellm-dashboard/src/components/add_model/ForecastClassifierConfig.integration.test.tsx b/ui/litellm-dashboard/src/components/add_model/ForecastClassifierConfig.integration.test.tsx index a03ccb11456..f243e63d387 100644 --- a/ui/litellm-dashboard/src/components/add_model/ForecastClassifierConfig.integration.test.tsx +++ b/ui/litellm-dashboard/src/components/add_model/ForecastClassifierConfig.integration.test.tsx @@ -1,3 +1,4 @@ +import { selectAutoRouterApproach } from "../../../tests/autoRouterSetup"; import React, { useState } from "react"; import { afterEach, beforeEach, describe, expect, it, vi } from "vitest"; import userEvent from "@testing-library/user-event"; @@ -306,7 +307,7 @@ describe("forecast classifier form", () => { ); }); - it("switches a populated standard router to Capability without saving hidden pools or their overrides", () => { + it("switches a populated standard router to Capability without saving hidden pools or their overrides", async () => { renderWithProviders( { }} />, ); - fireEvent.click(screen.getByRole("tab", { name: "Capability" })); + await selectAutoRouterApproach("Capability"); fireEvent.change(screen.getByLabelText("Solve probability threshold"), { target: { value: "0.7" } }); expect(screen.getByRole("button", { name: "Save configuration" })).toBeEnabled(); fireEvent.click(screen.getByRole("button", { name: "Save configuration" })); @@ -347,7 +348,7 @@ describe("forecast classifier form", () => { it.each(["capability", "llm_v2"] as const)( "carries non-default solver assignments when switching away from %s", - (source) => { + async (source) => { const pair = { efficient_tier: "MEDIUM", capable_tier: "COMPLEX" }; const previous: ComplexityRouterConfigValue = { ...(source === "capability" ? initial : fuseInitial), @@ -359,7 +360,7 @@ describe("forecast classifier form", () => { tier_model_params: { MEDIUM: { efficient: { max_tokens: 128 } }, COMPLEX: { capable: { speed: "fast" } } }, }; renderWithProviders(); - fireEvent.click(screen.getByRole("tab", { name: source === "capability" ? "Fuse v2" : "Capability" })); + await selectAutoRouterApproach(source === "capability" ? "Fuse v2" : "Capability"); if (source === "capability") { fireEvent.change(screen.getByLabelText("Efficient solver profile"), { target: { value: "Small solver" } }); fireEvent.change(screen.getByLabelText("Capable solver profile"), { target: { value: "Large solver" } }); @@ -402,20 +403,22 @@ describe("forecast classifier form", () => { ] as const)("restores the current rubric when switching %s through Complexity to %s", async (source, target) => { const user = userEvent.setup(); renderWithProviders(); - fireEvent.click(screen.getByRole("tab", { name: "Complexity" })); + await selectAutoRouterApproach("Complexity"); fireEvent.click(screen.getByRole("radio", { name: new RegExp(`^${target}`) })); - await user.click(screen.getByRole("combobox", { name: "Classifier Model" })); + await user.click(screen.getByRole("combobox", { name: "Judge model" })); await user.click(screen.getByRole("option", { name: "judge" })); fireEvent.click(screen.getByRole("button", { name: "Save configuration" })); const output = screen.getByRole("status", { name: "Saved configuration" }); expect(output).toHaveTextContent('"classification_rubric":"agentic"'); expect(output).toHaveTextContent('"model":"judge"'); - expect(output).toHaveTextContent('"timeout_ms":3000'); + expect(output).toHaveTextContent( + `"timeout_ms":${(source === "capability" ? initial : fuseInitial).classifier_llm_config?.timeout_ms}`, + ); expect(output).not.toHaveTextContent('"capability_classifier_config"'); expect(output).not.toHaveTextContent('"llm_v2_config"'); }); - it("saves capability threshold edits together with fitted calibration", () => { + it("saves capability threshold edits together with fitted calibration", async () => { renderWithProviders(); fireEvent.change(screen.getByLabelText("Solve probability threshold"), { target: { value: "0.6" } }); fireEvent.click(screen.getByRole("button", { name: "Classifier options" })); @@ -432,9 +435,9 @@ describe("forecast classifier form", () => { expect(screen.getByRole("button", { name: "Save configuration" })).toBeDisabled(); }); - it("switches to Fuse, requires solver context, and saves the filled fields", () => { + it("switches to Fuse, requires solver context, and saves the filled fields", async () => { renderWithProviders(); - fireEvent.click(screen.getByRole("tab", { name: "Fuse v2" })); + await selectAutoRouterApproach("Fuse v2"); expect(screen.queryByLabelText("Solve probability threshold")).not.toBeInTheDocument(); expect(screen.getByRole("button", { name: "Save configuration" })).toBeDisabled(); fireEvent.change(screen.getByLabelText("Efficient solver profile"), { diff --git a/ui/litellm-dashboard/src/components/add_model/ForecastClassifierConfig.tsx b/ui/litellm-dashboard/src/components/add_model/ForecastClassifierConfig.tsx index c336423fe39..d759b870209 100644 --- a/ui/litellm-dashboard/src/components/add_model/ForecastClassifierConfig.tsx +++ b/ui/litellm-dashboard/src/components/add_model/ForecastClassifierConfig.tsx @@ -36,6 +36,7 @@ interface Props { onChange: (value: ComplexityRouterConfigValue) => void; modelOptions: { value: string; label: string }[]; effortOptionsByModel: Record; + section?: "all" | "required" | "advanced"; } const NumberField = ({ @@ -188,7 +189,7 @@ const CalibrationFields = ({ const emptyCoefficients = () => ({ slope: Number.NaN, intercept: Number.NaN }); -const ForecastClassifierConfig = ({ value, onChange, modelOptions, effortOptionsByModel }: Props) => { +const ForecastClassifierConfig = ({ value, onChange, modelOptions, effortOptionsByModel, section = "all" }: Props) => { const id = React.useId(); const isCapability = value.classifier_type === "capability"; const capability = value.capability_classifier_config ?? newCapabilitySettings(); @@ -212,72 +213,195 @@ const ForecastClassifierConfig = ({ value, onChange, modelOptions, effortOptions ? "Forecasts whether the efficient solver can complete the task using the bundled capability card" : "Forecasts success for both solvers and selects efficient when the estimated quality gap is within your allowance"}

-
- - { - if (model === llm.model) return; - onChange({ ...value, classifier_llm_config: { ...llm, model: model ?? "", reasoning_effort: undefined } }); - }} - /> -
- {isCapability ? ( + {section === "all" && ( <> - updateCapability({ ...capability, base_threshold })} - /> - - ) : ( - <> - - updateFuse({ ...fuse, max_quality_gap })} - /> +
+ + { + if (model === llm.model) return; + onChange({ + ...value, + classifier_llm_config: { ...llm, model: model ?? "", reasoning_effort: undefined }, + }); + }} + /> +
)} - - - - Classifier options - - - onChange({ ...value, classifier_llm_config: { ...llm, reasoning_effort } })} - /> - onChange({ ...value, classifier_llm_config: { ...llm, timeout_ms } })} - /> - onChange({ ...value, classifier_llm_config })} - /> - onChange({ ...value, classifier_llm_config })} - /> + {section !== "advanced" && ( + <> + {isCapability ? ( + <> + updateCapability({ ...capability, base_threshold })} + /> + + ) : ( + <> + + updateFuse({ ...fuse, max_quality_gap })} + /> + + )} + + )} + {section !== "required" && ( + + {section === "all" && ( + + + Classifier options + + )} + + + onChange({ ...value, classifier_llm_config: { ...llm, reasoning_effort } }) + } + /> + onChange({ ...value, classifier_llm_config: { ...llm, timeout_ms } })} + /> + onChange({ ...value, classifier_llm_config })} + /> + onChange({ ...value, classifier_llm_config })} + /> + {isCapability && ( + updateCapability({ ...capability, threshold_step })} + /> + )} + updateTransport({ max_output_tokens })} + /> +
+ + { + if (response_format === "json_schema" || response_format === "json_object") + updateTransport({ response_format }); + }} + /> +
+
+ +

+ Optional coefficients fitted for your judge, solvers, and harness. Leave off to use raw forecasts +

+ {config.calibration && ( +
+ + setCalibrationVersion(event.target.value)} + /> +
+ )} + {isCapability && capability.calibration && ( + + updateCapability({ + ...capability, + calibration: { version: capability.calibration?.version ?? "", ...next }, + }) + } + /> + )} + {!isCapability && + fuse.calibration && + (["efficient", "capable"] as const).map((role) => ( + { + if (fuse.calibration) updateFuse({ ...fuse, calibration: { ...fuse.calibration, [role]: next } }); + }} + /> + ))} +
+ + + )} + {section === "all" && ( + <>
- {isCapability && ( - updateCapability({ ...capability, threshold_step })} - /> - )} - updateTransport({ max_output_tokens })} - /> -
- - { - if (response_format === "json_schema" || response_format === "json_object") - updateTransport({ response_format }); - }} - /> -
-
- -

- Optional coefficients fitted for your judge, solvers, and harness. Leave off to use raw forecasts -

- {config.calibration && ( -
- - setCalibrationVersion(event.target.value)} - /> -
- )} - {isCapability && capability.calibration && ( - - updateCapability({ - ...capability, - calibration: { version: capability.calibration?.version ?? "", ...next }, - }) - } - /> - )} - {!isCapability && - fuse.calibration && - (["efficient", "capable"] as const).map((role) => ( - { - if (fuse.calibration) updateFuse({ ...fuse, calibration: { ...fuse.calibration, [role]: next } }); - }} - /> - ))} -
- - + + )}

The classifier uses its bundled prompt and always falls back to the capable solver

- {error && ( + {section !== "advanced" && error && (

{error}

diff --git a/ui/litellm-dashboard/src/components/add_model/JevClassifierConfig.integration.test.tsx b/ui/litellm-dashboard/src/components/add_model/JevClassifierConfig.integration.test.tsx index 896fde3a446..7da8b12c2d7 100644 --- a/ui/litellm-dashboard/src/components/add_model/JevClassifierConfig.integration.test.tsx +++ b/ui/litellm-dashboard/src/components/add_model/JevClassifierConfig.integration.test.tsx @@ -98,28 +98,28 @@ describe("JEV classifier editor", () => { afterEach(() => vi.mocked(useAuthorized).mockReset()); it("uses built-in JEV without a license and preserves custom tiers and context through reload", () => { renderWithProviders(); - expect(screen.getByLabelText("Classifier Model")).toBeInTheDocument(); + expect(screen.getByLabelText("Judge model")).toBeInTheDocument(); expect(screen.getByText("Reasoning Effort")).toBeInTheDocument(); expect(screen.getByText("Classifier Prompt")).toBeInTheDocument(); expect(screen.getByRole("switch", { name: "Use images for classification" })).toBeInTheDocument(); - fireEvent.click(screen.getByRole("radio", { name: /JEV Classifier/ })); - expect(screen.getByRole("tab", { name: "Complexity" })).toHaveAttribute("aria-selected", "true"); - expect(screen.getByLabelText("JEV Model")).toHaveValue("jev-latest"); - expect(screen.getByLabelText("JEV Instructions")).toBeDisabled(); - expect(screen.queryByLabelText("Classifier Model")).not.toBeInTheDocument(); + fireEvent.click(screen.getByRole("radio", { name: /Jev Classifier/ })); + expect(screen.getByRole("radio", { name: /^Jev Classifier/ })).toBeChecked(); + expect(screen.getByLabelText("Jev Model")).toHaveValue("jev-latest"); + expect(screen.getByLabelText("Jev Instructions")).toBeEnabled(); + expect(screen.queryByLabelText("Judge model")).not.toBeInTheDocument(); expect(screen.queryByText("Reasoning Effort")).not.toBeInTheDocument(); expect(screen.queryByText("Classifier Prompt")).not.toBeInTheDocument(); expect(screen.queryByRole("switch", { name: "Use images for classification" })).not.toBeInTheDocument(); - fireEvent.change(screen.getByLabelText("JEV Model"), { target: { value: "jev-test" } }); - fireEvent.change(screen.getByLabelText("JEV Timeout (ms)"), { target: { value: "4200" } }); + fireEvent.change(screen.getByLabelText("Jev Model"), { target: { value: "jev-test" } }); + fireEvent.change(screen.getByLabelText("Jev Timeout (ms)"), { target: { value: "4200" } }); fireEvent.change(screen.getByLabelText("Context Window Size"), { target: { value: "6" } }); fireEvent.change(screen.getByLabelText("Circuit breaker cooldown (seconds)"), { target: { value: "50" } }); fireEvent.click(screen.getByRole("switch", { name: "Classifier circuit breaker" })); fireEvent.click(screen.getByRole("button", { name: "Customize tiers" })); fireEvent.click(screen.getByRole("button", { name: "Save and reload" })); - expect(screen.getByRole("radio", { name: /JEV Classifier/ })).toBeChecked(); - expect(screen.getByLabelText("JEV Model")).toHaveValue("jev-test"); - expect(screen.getByLabelText("JEV Timeout (ms)")).toHaveValue(4200); + expect(screen.getByRole("radio", { name: /Jev Classifier/ })).toBeChecked(); + expect(screen.getByLabelText("Jev Model")).toHaveValue("jev-test"); + expect(screen.getByLabelText("Jev Timeout (ms)")).toHaveValue(4200); expect(screen.getByLabelText("Context Window Size")).toHaveValue("6"); expect(screen.getByRole("switch", { name: "Classifier circuit breaker" })).not.toBeChecked(); fireEvent.click(screen.getByRole("button", { name: "Probe current config" })); @@ -152,10 +152,10 @@ describe("JEV classifier editor", () => { return ; }; renderWithProviders(); - expect(screen.getByLabelText("JEV Instructions")).toBeEnabled(); - fireEvent.change(screen.getByLabelText("JEV Instructions"), { target: { value: "New instructions" } }); - expect(screen.getByLabelText("JEV Instructions")).toHaveValue("New instructions"); - fireEvent.click(screen.getByRole("button", { name: "Restore built-in JEV instructions" })); - expect(screen.getByLabelText("JEV Instructions")).toHaveValue(""); + expect(screen.getByLabelText("Jev Instructions")).toBeEnabled(); + fireEvent.change(screen.getByLabelText("Jev Instructions"), { target: { value: "New instructions" } }); + expect(screen.getByLabelText("Jev Instructions")).toHaveValue("New instructions"); + fireEvent.click(screen.getByRole("button", { name: "Restore built-in Jev instructions" })); + expect(screen.getByLabelText("Jev Instructions")).toHaveValue(""); }); }); diff --git a/ui/litellm-dashboard/src/components/add_model/JevClassifierConfig.tsx b/ui/litellm-dashboard/src/components/add_model/JevClassifierConfig.tsx index 25286eaef07..97609bcd8c3 100644 --- a/ui/litellm-dashboard/src/components/add_model/JevClassifierConfig.tsx +++ b/ui/litellm-dashboard/src/components/add_model/JevClassifierConfig.tsx @@ -1,10 +1,9 @@ import React, { useId } from "react"; -import useAuthorized from "@/app/(dashboard)/hooks/useAuthorized"; +import { AutoRouterAllowanceNote } from "./AutoRouterAvailability"; import { Button } from "@/components/ui/button"; import { Input } from "@/components/ui/input"; import { Label } from "@/components/ui/label"; import { Textarea } from "@/components/ui/textarea"; -import { SimpleTooltip } from "@/components/ui/tooltip"; import ClassifierCircuitBreakerConfig from "./ClassifierCircuitBreakerConfig"; import type { ComplexityRouterConfigValue } from "./ComplexityRouterConfig"; import { defaultJevClassifierConfig } from "./jev_classifier_config"; @@ -17,7 +16,6 @@ export default function JevClassifierConfig({ onChange: (value: ComplexityRouterConfigValue) => void; }) { const id = useId(); - const { premiumUser } = useAuthorized(); const config = value.jev_classifier_config ?? defaultJevClassifierConfig(); const update = (patch: Partial) => onChange({ ...value, jev_classifier_config: { ...config, ...patch } }); @@ -28,11 +26,11 @@ export default function JevClassifierConfig({ Uses TypeSafe System One Choice evaluation with your configured tiers

- + update({ model: event.target.value })} />
- +
- - -
-