From 42d4aab3e7046a2b6545c14dcd08e2b56953a289 Mon Sep 17 00:00:00 2001 From: Sameer Kankute Date: Mon, 5 Jan 2026 11:21:34 +0530 Subject: [PATCH 1/3] Add mapping for reasoning effort to summary of responses API --- .../transformation.py | 14 +++---- ...odel_prices_and_context_window_backup.json | 42 +++++++++++++++++++ ...responses_transformation_transformation.py | 40 ++++++++++++++++++ 3 files changed, 89 insertions(+), 7 deletions(-) diff --git a/litellm/completion_extras/litellm_responses_transformation/transformation.py b/litellm/completion_extras/litellm_responses_transformation/transformation.py index 55a8e665bb..9511537f72 100644 --- a/litellm/completion_extras/litellm_responses_transformation/transformation.py +++ b/litellm/completion_extras/litellm_responses_transformation/transformation.py @@ -691,19 +691,19 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): if isinstance(reasoning_effort, dict): return Reasoning(**reasoning_effort) # type: ignore[typeddict-item] - # If string is passed, map without summary (default) + # If string is passed, map with summary="concise" if reasoning_effort == "none": - return Reasoning(effort="none") # type: ignore + return Reasoning(effort="none", summary="concise") # type: ignore elif reasoning_effort == "high": - return Reasoning(effort="high") + return Reasoning(effort="high", summary="concise") elif reasoning_effort == "xhigh": - return Reasoning(effort="xhigh") # type: ignore[typeddict-item] + return Reasoning(effort="xhigh", summary="concise") # type: ignore[typeddict-item] elif reasoning_effort == "medium": - return Reasoning(effort="medium") + return Reasoning(effort="medium", summary="concise") elif reasoning_effort == "low": - return Reasoning(effort="low") + return Reasoning(effort="low", summary="concise") elif reasoning_effort == "minimal": - return Reasoning(effort="minimal") + return Reasoning(effort="minimal", summary="concise") return None def _transform_response_format_to_text_format( diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index d32adf54b5..81b4469f24 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -11640,6 +11640,7 @@ "supports_tool_choice": true }, "gemini-1.5-flash": { + "deprecation_date": "2025-09-29", "input_cost_per_audio_per_second": 2e-06, "input_cost_per_audio_per_second_above_128k_tokens": 4e-06, "input_cost_per_character": 1.875e-08, @@ -11744,6 +11745,7 @@ "supports_vision": true }, "gemini-1.5-flash-exp-0827": { + "deprecation_date": "2025-09-29", "input_cost_per_audio_per_second": 2e-06, "input_cost_per_audio_per_second_above_128k_tokens": 4e-06, "input_cost_per_character": 1.875e-08, @@ -11778,6 +11780,7 @@ "supports_vision": true }, "gemini-1.5-flash-preview-0514": { + "deprecation_date": "2025-09-29", "input_cost_per_audio_per_second": 2e-06, "input_cost_per_audio_per_second_above_128k_tokens": 4e-06, "input_cost_per_character": 1.875e-08, @@ -11811,6 +11814,7 @@ "supports_vision": true }, "gemini-1.5-pro": { + "deprecation_date": "2025-09-29", "input_cost_per_audio_per_second": 3.125e-05, "input_cost_per_audio_per_second_above_128k_tokens": 6.25e-05, "input_cost_per_character": 3.125e-07, @@ -11898,6 +11902,7 @@ "supports_vision": true }, "gemini-1.5-pro-preview-0215": { + "deprecation_date": "2025-09-29", "input_cost_per_audio_per_second": 3.125e-05, "input_cost_per_audio_per_second_above_128k_tokens": 6.25e-05, "input_cost_per_character": 3.125e-07, @@ -11925,6 +11930,7 @@ "supports_tool_choice": true }, "gemini-1.5-pro-preview-0409": { + "deprecation_date": "2025-09-29", "input_cost_per_audio_per_second": 3.125e-05, "input_cost_per_audio_per_second_above_128k_tokens": 6.25e-05, "input_cost_per_character": 3.125e-07, @@ -11951,6 +11957,7 @@ "supports_tool_choice": true }, "gemini-1.5-pro-preview-0514": { + "deprecation_date": "2025-09-29", "input_cost_per_audio_per_second": 3.125e-05, "input_cost_per_audio_per_second_above_128k_tokens": 6.25e-05, "input_cost_per_character": 3.125e-07, @@ -12222,6 +12229,7 @@ "tpm": 250000 }, "gemini-2.0-flash-preview-image-generation": { + "deprecation_date": "2025-11-14", "cache_read_input_token_cost": 2.5e-08, "input_cost_per_audio_token": 7e-07, "input_cost_per_token": 1e-07, @@ -12260,6 +12268,7 @@ "supports_web_search": true }, "gemini-2.0-flash-thinking-exp": { + "deprecation_date": "2025-12-02", "cache_read_input_token_cost": 0.0, "input_cost_per_audio_per_second": 0, "input_cost_per_audio_per_second_above_128k_tokens": 0, @@ -12308,6 +12317,7 @@ "supports_web_search": true }, "gemini-2.0-flash-thinking-exp-01-21": { + "deprecation_date": "2025-12-02", "cache_read_input_token_cost": 0.0, "input_cost_per_audio_per_second": 0, "input_cost_per_audio_per_second_above_128k_tokens": 0, @@ -12494,6 +12504,7 @@ "tpm": 8000000 }, "gemini-2.5-flash-image-preview": { + "deprecation_date": "2026-01-15", "cache_read_input_token_cost": 7.5e-08, "input_cost_per_audio_token": 1e-06, "input_cost_per_token": 3e-07, @@ -12804,6 +12815,7 @@ "tpm": 8000000 }, "gemini-2.5-flash-lite-preview-06-17": { + "deprecation_date": "2025-11-18", "cache_read_input_token_cost": 2.5e-08, "input_cost_per_audio_token": 5e-07, "input_cost_per_token": 1e-07, @@ -12893,6 +12905,7 @@ "supports_web_search": true }, "gemini-2.5-flash-preview-05-20": { + "deprecation_date": "2025-11-18", "cache_read_input_token_cost": 7.5e-08, "input_cost_per_audio_token": 1e-06, "input_cost_per_token": 3e-07, @@ -13164,6 +13177,7 @@ "supports_web_search": true }, "gemini-2.5-pro-preview-03-25": { + "deprecation_date": "2025-12-02", "cache_read_input_token_cost": 3.125e-07, "input_cost_per_audio_token": 1.25e-06, "input_cost_per_token": 1.25e-06, @@ -13209,6 +13223,7 @@ "supports_web_search": true }, "gemini-2.5-pro-preview-05-06": { + "deprecation_date": "2025-12-02", "cache_read_input_token_cost": 3.125e-07, "input_cost_per_audio_token": 1.25e-06, "input_cost_per_token": 1.25e-06, @@ -13424,6 +13439,7 @@ "tpm": 10000000 }, "gemini/gemini-1.5-flash": { + "deprecation_date": "2025-09-29", "input_cost_per_token": 7.5e-08, "input_cost_per_token_above_128k_tokens": 1.5e-07, "litellm_provider": "gemini", @@ -13507,6 +13523,7 @@ "tpm": 4000000 }, "gemini/gemini-1.5-flash-8b": { + "deprecation_date": "2025-09-29", "input_cost_per_token": 0, "input_cost_per_token_above_128k_tokens": 0, "litellm_provider": "gemini", @@ -13533,6 +13550,7 @@ "tpm": 4000000 }, "gemini/gemini-1.5-flash-8b-exp-0827": { + "deprecation_date": "2025-09-29", "input_cost_per_token": 0, "input_cost_per_token_above_128k_tokens": 0, "litellm_provider": "gemini", @@ -13558,6 +13576,7 @@ "tpm": 4000000 }, "gemini/gemini-1.5-flash-8b-exp-0924": { + "deprecation_date": "2025-09-29", "input_cost_per_token": 0, "input_cost_per_token_above_128k_tokens": 0, "litellm_provider": "gemini", @@ -13584,6 +13603,7 @@ "tpm": 4000000 }, "gemini/gemini-1.5-flash-exp-0827": { + "deprecation_date": "2025-09-29", "input_cost_per_token": 0, "input_cost_per_token_above_128k_tokens": 0, "litellm_provider": "gemini", @@ -13609,6 +13629,7 @@ "tpm": 4000000 }, "gemini/gemini-1.5-flash-latest": { + "deprecation_date": "2025-09-29", "input_cost_per_token": 7.5e-08, "input_cost_per_token_above_128k_tokens": 1.5e-07, "litellm_provider": "gemini", @@ -13635,6 +13656,7 @@ "tpm": 4000000 }, "gemini/gemini-1.5-pro": { + "deprecation_date": "2025-09-29", "input_cost_per_token": 3.5e-06, "input_cost_per_token_above_128k_tokens": 7e-06, "litellm_provider": "gemini", @@ -13696,6 +13718,7 @@ "tpm": 4000000 }, "gemini/gemini-1.5-pro-exp-0801": { + "deprecation_date": "2025-09-29", "input_cost_per_token": 3.5e-06, "input_cost_per_token_above_128k_tokens": 7e-06, "litellm_provider": "gemini", @@ -13715,6 +13738,7 @@ "tpm": 4000000 }, "gemini/gemini-1.5-pro-exp-0827": { + "deprecation_date": "2025-09-29", "input_cost_per_token": 0, "input_cost_per_token_above_128k_tokens": 0, "litellm_provider": "gemini", @@ -13734,6 +13758,7 @@ "tpm": 4000000 }, "gemini/gemini-1.5-pro-latest": { + "deprecation_date": "2025-09-29", "input_cost_per_token": 3.5e-06, "input_cost_per_token_above_128k_tokens": 7e-06, "litellm_provider": "gemini", @@ -13916,6 +13941,7 @@ "tpm": 4000000 }, "gemini/gemini-2.0-flash-lite-preview-02-05": { + "deprecation_date": "2025-12-02", "cache_read_input_token_cost": 1.875e-08, "input_cost_per_audio_token": 7.5e-08, "input_cost_per_token": 7.5e-08, @@ -13953,6 +13979,7 @@ "tpm": 10000000 }, "gemini/gemini-2.0-flash-live-001": { + "deprecation_date": "2025-12-09", "cache_read_input_token_cost": 7.5e-08, "input_cost_per_audio_token": 2.1e-06, "input_cost_per_image": 2.1e-06, @@ -14001,6 +14028,7 @@ "tpm": 250000 }, "gemini/gemini-2.0-flash-preview-image-generation": { + "deprecation_date": "2025-11-14", "cache_read_input_token_cost": 2.5e-08, "input_cost_per_audio_token": 7e-07, "input_cost_per_token": 1e-07, @@ -14040,6 +14068,7 @@ "tpm": 10000000 }, "gemini/gemini-2.0-flash-thinking-exp": { + "deprecation_date": "2025-12-02", "cache_read_input_token_cost": 0.0, "input_cost_per_audio_per_second": 0, "input_cost_per_audio_per_second_above_128k_tokens": 0, @@ -14089,6 +14118,7 @@ "tpm": 4000000 }, "gemini/gemini-2.0-flash-thinking-exp-01-21": { + "deprecation_date": "2025-12-02", "cache_read_input_token_cost": 0.0, "input_cost_per_audio_per_second": 0, "input_cost_per_audio_per_second_above_128k_tokens": 0, @@ -14277,6 +14307,7 @@ "tpm": 8000000 }, "gemini/gemini-2.5-flash-image-preview": { + "deprecation_date": "2026-01-15", "cache_read_input_token_cost": 7.5e-08, "input_cost_per_audio_token": 1e-06, "input_cost_per_token": 3e-07, @@ -14597,6 +14628,7 @@ "tpm": 250000 }, "gemini/gemini-2.5-flash-lite-preview-06-17": { + "deprecation_date": "2025-11-18", "cache_read_input_token_cost": 2.5e-08, "input_cost_per_audio_token": 5e-07, "input_cost_per_token": 1e-07, @@ -14688,6 +14720,7 @@ "tpm": 250000 }, "gemini/gemini-2.5-flash-preview-05-20": { + "deprecation_date": "2025-11-18", "cache_read_input_token_cost": 7.5e-08, "input_cost_per_audio_token": 1e-06, "input_cost_per_token": 3e-07, @@ -15034,6 +15067,7 @@ "tpm": 250000 }, "gemini/gemini-2.5-pro-preview-03-25": { + "deprecation_date": "2025-12-02", "cache_read_input_token_cost": 3.125e-07, "input_cost_per_audio_token": 7e-07, "input_cost_per_token": 1.25e-06, @@ -15074,6 +15108,7 @@ "tpm": 10000000 }, "gemini/gemini-2.5-pro-preview-05-06": { + "deprecation_date": "2025-12-02", "cache_read_input_token_cost": 3.125e-07, "input_cost_per_audio_token": 7e-07, "input_cost_per_token": 1.25e-06, @@ -15349,6 +15384,7 @@ "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, @@ -15415,6 +15451,7 @@ ] }, "gemini/veo-3.0-fast-generate-preview": { + "deprecation_date": "2025-11-12", "litellm_provider": "gemini", "max_input_tokens": 1024, "max_tokens": 1024, @@ -15429,6 +15466,7 @@ ] }, "gemini/veo-3.0-generate-preview": { + "deprecation_date": "2025-11-12", "litellm_provider": "gemini", "max_input_tokens": 1024, "max_tokens": 1024, @@ -25126,6 +25164,7 @@ "source": "https://docs.mistral.ai/capabilities/code_generation/" }, "text-embedding-004": { + "deprecation_date": "2026-01-14", "input_cost_per_character": 2.5e-08, "input_cost_per_token": 1e-07, "litellm_provider": "vertex_ai-embedding-models", @@ -27896,6 +27935,7 @@ "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing" }, "vertex_ai/imagen-3.0-generate-002": { + "deprecation_date": "2025-11-10", "litellm_provider": "vertex_ai-image-models", "mode": "image_generation", "output_cost_per_image": 0.04, @@ -28406,6 +28446,7 @@ ] }, "vertex_ai/veo-3.0-fast-generate-preview": { + "deprecation_date": "2025-11-12", "litellm_provider": "vertex_ai-video-models", "max_input_tokens": 1024, "max_tokens": 1024, @@ -28420,6 +28461,7 @@ ] }, "vertex_ai/veo-3.0-generate-preview": { + "deprecation_date": "2025-11-12", "litellm_provider": "vertex_ai-video-models", "max_input_tokens": 1024, "max_tokens": 1024, diff --git a/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py b/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py index 4320c932f4..77ac074216 100644 --- a/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py +++ b/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py @@ -1007,3 +1007,43 @@ def test_multiple_tool_calls_in_single_choice(): assert tool_calls[2]["function"]["name"] == "get_horoscope" print("✓ Multiple tool calls are correctly grouped in a single choice") + + +def test_map_reasoning_effort_adds_summary_detailed(): + """ + Test that _map_reasoning_effort adds summary="detailed" when user provides reasoning_effort as a string. + + This ensures that when users pass reasoning_effort in the completions API for OpenAI responses/models, + the transformation automatically includes summary="detailed" in the reasoning parameter. + """ + from litellm.completion_extras.litellm_responses_transformation.transformation import ( + LiteLLMResponsesTransformationHandler, + ) + + handler = LiteLLMResponsesTransformationHandler() + + # Test all string effort levels + effort_levels = ["none", "low", "medium", "high", "xhigh", "minimal"] + + for effort in effort_levels: + result = handler._map_reasoning_effort(effort) + + assert result is not None, f"Result should not be None for effort={effort}" + assert result["effort"] == effort, f"Effort should be {effort}" + assert result["summary"] == "concise", f"Summary should be 'detailed' for effort={effort}" + + print(f"✓ reasoning_effort='{effort}' correctly maps to effort='{effort}', summary='detailed'") + + # Test that dict input is passed through as-is (no modification) + dict_input = {"effort": "high", "summary": "custom_summary"} + result_dict = handler._map_reasoning_effort(dict_input) + assert result_dict["effort"] == "high" + assert result_dict["summary"] == "custom_summary" + print("✓ Dict input is passed through without modification") + + # Test that None/unknown values return None + result_unknown = handler._map_reasoning_effort("unknown_value") + assert result_unknown is None + print("✓ Unknown reasoning_effort values return None") + + print("✓ All reasoning_effort string values correctly map to summary='detailed'") From 0f8e4364d609c5e7d11d08108de975e89ae0821f Mon Sep 17 00:00:00 2001 From: Sameer Kankute Date: Mon, 5 Jan 2026 11:24:35 +0530 Subject: [PATCH 2/3] Replace summary param as detailed --- .../transformation.py | 12 ++++++------ ...itellm_responses_transformation_transformation.py | 2 +- 2 files changed, 7 insertions(+), 7 deletions(-) diff --git a/litellm/completion_extras/litellm_responses_transformation/transformation.py b/litellm/completion_extras/litellm_responses_transformation/transformation.py index 9511537f72..3fb69f97fd 100644 --- a/litellm/completion_extras/litellm_responses_transformation/transformation.py +++ b/litellm/completion_extras/litellm_responses_transformation/transformation.py @@ -693,17 +693,17 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): # If string is passed, map with summary="concise" if reasoning_effort == "none": - return Reasoning(effort="none", summary="concise") # type: ignore + return Reasoning(effort="none", summary="detailed") # type: ignore elif reasoning_effort == "high": - return Reasoning(effort="high", summary="concise") + return Reasoning(effort="high", summary="detailed") elif reasoning_effort == "xhigh": - return Reasoning(effort="xhigh", summary="concise") # type: ignore[typeddict-item] + return Reasoning(effort="xhigh", summary="detailed") # type: ignore[typeddict-item] elif reasoning_effort == "medium": - return Reasoning(effort="medium", summary="concise") + return Reasoning(effort="medium", summary="detailed") elif reasoning_effort == "low": - return Reasoning(effort="low", summary="concise") + return Reasoning(effort="low", summary="detailed") elif reasoning_effort == "minimal": - return Reasoning(effort="minimal", summary="concise") + return Reasoning(effort="minimal", summary="detailed") return None def _transform_response_format_to_text_format( diff --git a/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py b/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py index 77ac074216..6490352c39 100644 --- a/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py +++ b/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py @@ -1030,7 +1030,7 @@ def test_map_reasoning_effort_adds_summary_detailed(): assert result is not None, f"Result should not be None for effort={effort}" assert result["effort"] == effort, f"Effort should be {effort}" - assert result["summary"] == "concise", f"Summary should be 'detailed' for effort={effort}" + assert result["summary"] == "detailed", f"Summary should be 'detailed' for effort={effort}" print(f"✓ reasoning_effort='{effort}' correctly maps to effort='{effort}', summary='detailed'") From 02a41a5c13bfbe89d8d0672e27c0e768e57b7727 Mon Sep 17 00:00:00 2001 From: Sameer Kankute Date: Mon, 5 Jan 2026 11:40:40 +0530 Subject: [PATCH 3/3] fix the comment --- .../litellm_responses_transformation/transformation.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/litellm/completion_extras/litellm_responses_transformation/transformation.py b/litellm/completion_extras/litellm_responses_transformation/transformation.py index 3fb69f97fd..5b206317b2 100644 --- a/litellm/completion_extras/litellm_responses_transformation/transformation.py +++ b/litellm/completion_extras/litellm_responses_transformation/transformation.py @@ -691,7 +691,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): if isinstance(reasoning_effort, dict): return Reasoning(**reasoning_effort) # type: ignore[typeddict-item] - # If string is passed, map with summary="concise" + # If string is passed, map with summary="detailed" if reasoning_effort == "none": return Reasoning(effort="none", summary="detailed") # type: ignore elif reasoning_effort == "high":