diff --git a/litellm/completion_extras/litellm_responses_transformation/transformation.py b/litellm/completion_extras/litellm_responses_transformation/transformation.py index 1b976f5a48b..4024ce5360e 100644 --- a/litellm/completion_extras/litellm_responses_transformation/transformation.py +++ b/litellm/completion_extras/litellm_responses_transformation/transformation.py @@ -1115,7 +1115,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): responses_tools: Final[list[ALL_RESPONSES_API_TOOL_PARAMS]] = [] for tool in tools: # convert function tool from chat completion to responses API format - if tool.get("type") == "function": + if tool.get("type") == "function" and isinstance(tool.get("function"), dict): function_tool = cast(ChatCompletionToolParamFunctionChunk, tool.get("function")) responses_tools.append( FunctionToolParam( diff --git a/litellm/llms/azure_ai/common_utils.py b/litellm/llms/azure_ai/common_utils.py index d5a05cb8ea5..cffe9049de6 100644 --- a/litellm/llms/azure_ai/common_utils.py +++ b/litellm/llms/azure_ai/common_utils.py @@ -6,6 +6,7 @@ from urllib.parse import urlparse import litellm from litellm.llms.base_llm.base_utils import BaseLLMModelInfo, BaseTokenCounter +from litellm.llms.openai.chat.gpt_5_transformation import OpenAIGPT5Config from litellm.secret_managers.main import get_secret_str from litellm.types.llms.openai import AllMessageValues from litellm.types.router import GenericLiteLLMParams @@ -150,6 +151,14 @@ def azure_ai_supports_native_responses(model: str | None, api_base: str | None) return AzureFoundryModelInfo.get_azure_ai_route(model) == "default" +def foundry_chat_rejects_function_tools_while_reasoning( + model: str, reasoning_effort: str | Mapping[str, object] | None +) -> bool: + if reasoning_effort is None: + return OpenAIGPT5Config.is_model_gpt_6_plus_model(model) + return OpenAIGPT5Config.is_model_gpt_5_6_plus_model(model) + + class AzureFoundryModelInfo(BaseLLMModelInfo): """Model info for Azure AI / Azure Foundry models.""" diff --git a/litellm/llms/openai/chat/gpt_5_transformation.py b/litellm/llms/openai/chat/gpt_5_transformation.py index 1b93df95341..d0e5ff01e71 100644 --- a/litellm/llms/openai/chat/gpt_5_transformation.py +++ b/litellm/llms/openai/chat/gpt_5_transformation.py @@ -1,5 +1,6 @@ """Support for OpenAI gpt-5 model family.""" +import re from typing import Final import litellm @@ -11,6 +12,8 @@ from litellm.utils import ( from .gpt_transformation import OpenAIGPTConfig +_GPT_SERIES_VERSION: Final = re.compile(r"^gpt-(\d+)(?:\.(\d+))?(?=[.-]|$)") + def _catalogue_declares_default_effort() -> bool: """Whether the loaded cost map carries default_reasoning_effort for ANY entry. @@ -112,20 +115,28 @@ class OpenAIGPT5Config(OpenAIGPTConfig): model_name: Final = model.split("/")[-1] return model_name.startswith("gpt-5.4") + @staticmethod + def _gpt_series_version(model: str) -> tuple[int, int] | None: + match: Final = _GPT_SERIES_VERSION.match(model.split("/")[-1]) + if match is None: + return None + return int(match.group(1)), int(match.group(2) or 0) + @classmethod def is_model_gpt_5_4_plus_model(cls, model: str) -> bool: """Check if the model is gpt-5.4 or newer (5.4, 5.5, 5.6, etc., including pro).""" - model_name: Final = model.split("/")[-1] - if model_name.startswith("gpt-6"): - return True - if not model_name.startswith("gpt-5."): - return False - try: - version_str: Final = model_name.replace("gpt-5.", "").split("-")[0] - major: Final = version_str.split(".")[0] - return int(major) >= 4 - except (ValueError, IndexError): - return False + version: Final = cls._gpt_series_version(model) + return version is not None and version >= (5, 4) + + @classmethod + def is_model_gpt_5_6_plus_model(cls, model: str) -> bool: + version: Final = cls._gpt_series_version(model) + return version is not None and version >= (5, 6) + + @classmethod + def is_model_gpt_6_plus_model(cls, model: str) -> bool: + version: Final = cls._gpt_series_version(model) + return version is not None and version >= (6, 0) @classmethod def _model_map_lookup_name(cls, model: str) -> str: diff --git a/litellm/main.py b/litellm/main.py index b1aaf5c5dab..66466f01da4 100644 --- a/litellm/main.py +++ b/litellm/main.py @@ -100,6 +100,10 @@ from litellm.litellm_core_utils.prompt_templates.common_utils import ( from litellm.litellm_core_utils.request_timeout_resolver import ( get_configured_request_timeout, ) +from litellm.llms.azure_ai.common_utils import ( + azure_ai_supports_native_responses, + foundry_chat_rejects_function_tools_while_reasoning, +) from litellm.llms.base_llm import BaseConfig, BaseImageGenerationConfig from litellm.llms.base_llm.base_model_iterator import ( convert_model_response_to_streaming, @@ -1106,10 +1110,18 @@ def responses_api_bridge_check( # provider with a custom api_base and gpt-5.4+ model names serve tools without # reasoning fine and have no /responses route, so they keep pre-existing # behavior (bridge only on an explicit reasoning_effort). + # - Azure AI Foundry's OpenAI v1 hosts (azure_ai provider) enforce it later in the series: + # an explicit effort with function tools is rejected from gpt-5.6 on, and the unset + # effort only from gpt-6 on (gpt-5.6 serves tools with reasoning silently off), so the + # azure_ai gate keys on those measured boundaries instead of gpt-5.4+. # - Older GPT-5 names (e.g. ``gpt-5``, ``gpt-5.1``): bridge only when a reasoning # summary alias is present with ``reasoning_effort`` (tools alone stay on chat). has_function_tool: Final = any( - (tool.get("type") == "function" if isinstance(tool, dict) else getattr(tool, "type", None) == "function") + ( + tool.get("type") == "function" and (isinstance(tool.get("function"), dict) or "name" in tool) + if isinstance(tool, dict) + else getattr(tool, "type", None) == "function" + ) for tool in (tools or ()) ) if isinstance(reasoning_effort, dict): @@ -1118,28 +1130,35 @@ def responses_api_bridge_check( reasoning_active = reasoning_effort != "none" # The reasoning+tools constraint is enforced by the real OpenAI backend behind any api.openai.com # host (the default URL or a PrivateLink hostname such as .privatelink.api.openai.com) and - # by Azure OpenAI. Resolve the effective base arg>global>env>default exactly as the chat handler - # does, so a custom base set via litellm.api_base or OPENAI_BASE_URL/OPENAI_API_BASE isn't misread - # as the default and bridged to a /responses route it lacks. A whitespace-only base collapses to - # the default too. + # by Azure OpenAI through the azure provider. Resolve the effective OpenAI base arg>global>env>default + # exactly as the chat handler does, so a custom base set via litellm.api_base or + # OPENAI_BASE_URL/OPENAI_API_BASE isn't misread as the default and bridged to a /responses route it + # lacks. A whitespace-only base collapses to the default too. resolved_api_base: Final = _resolve_openai_api_base(api_base).strip() + on_foundry_openai_endpoint: Final = custom_llm_provider == "azure_ai" and azure_ai_supports_native_responses( + model, api_base + ) on_constraint_enforcing_endpoint: Final = ( custom_llm_provider == "azure" or resolved_api_base == "" or _is_openai_backed_api_base(resolved_api_base) ) - if ( - custom_llm_provider in ("openai", "azure") - and model_info.get("mode") != "responses" - and OpenAIGPT5Config.is_model_gpt_5_model(model) - and not OpenAIGPT5Config.is_model_gpt_5_search_model(model) + chat_rejects_function_tools: Final = ( + has_function_tool + and reasoning_active and ( - (reasoning_effort is not None and reasoning_summary is not None) - or ( + foundry_chat_rejects_function_tools_while_reasoning(model, reasoning_effort) + if on_foundry_openai_endpoint + else ( OpenAIGPT5Config.is_model_gpt_5_4_plus_model(model) - and has_function_tool - and reasoning_active and (reasoning_effort is not None or on_constraint_enforcing_endpoint) ) ) + ) + if ( + (custom_llm_provider in ("openai", "azure") or on_foundry_openai_endpoint) + and model_info.get("mode") != "responses" + and OpenAIGPT5Config.is_model_gpt_5_model(model) + and not OpenAIGPT5Config.is_model_gpt_5_search_model(model) + and ((reasoning_effort is not None and reasoning_summary is not None) or chat_rejects_function_tools) ): model_info["mode"] = "responses" model = model.replace("responses/", "") 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 c326ad4a0f7..7e03a8886fb 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 @@ -830,6 +830,24 @@ def test_convert_tools_to_responses_format(): assert result[0]["name"] == "test" +def test_convert_tools_to_responses_format_passes_flat_function_tool_through(): + from litellm.completion_extras.litellm_responses_transformation.transformation import ( + LiteLLMResponsesTransformationHandler, + ) + + handler = LiteLLMResponsesTransformationHandler() + flat_tool = { + "type": "function", + "name": "shell", + "description": "Run a shell command", + "parameters": {"type": "object", "properties": {"cmd": {"type": "string"}}, "required": ["cmd"]}, + } + + converted = handler._convert_tools_to_responses_format([flat_tool]) + + assert converted == [flat_tool] + + def test_extract_extra_body_params_reasoning_effort_override(): """Test that reasoning_effort from extra_body overrides top-level reasoning_effort""" from litellm.completion_extras.litellm_responses_transformation.transformation import ( diff --git a/tests/test_litellm/llms/openai/test_is_model_gpt_5_model.py b/tests/test_litellm/llms/openai/test_is_model_gpt_5_model.py index 107a1afb2c6..0bb8425d95e 100644 --- a/tests/test_litellm/llms/openai/test_is_model_gpt_5_model.py +++ b/tests/test_litellm/llms/openai/test_is_model_gpt_5_model.py @@ -159,6 +159,58 @@ class TestOpenAIGPT5ConfigIsModelGpt54PlusModel: ), f"Expected '{model}' NOT to be classified as gpt-5.4-or-newer" +GPT5_6_PLUS_MODELS = [ + "gpt-6-astra", + "openai/gpt-6-astra", + "gpt-5.6", + "gpt-5.6-sol", + "gpt-5.6-terra", + "gpt-5.10-preview", +] + +GPT5_PRE_5_6_MODELS = [ + "gpt-5", + "gpt-5.4", + "gpt-5.4-mini", + "gpt-5.5", + "gpt-5.5-pro", + "gpt-4o", +] + +GPT6_PLUS_MODELS = [ + "gpt-6-astra", + "openai/gpt-6-astra", + "gpt-6", + "gpt-6.1-preview", +] + +GPT_PRE_6_MODELS = [ + "gpt-5.6-sol", + "gpt-5.5", + "gpt-5", + "gpt-4o", +] + + +class TestOpenAIGPT5ConfigSeriesBoundaries: + + @pytest.mark.parametrize("model", GPT5_6_PLUS_MODELS) + def test_gpt5_6_plus_models_are_classified_as_5_6_plus(self, model: str): + assert OpenAIGPT5Config.is_model_gpt_5_6_plus_model(model) + + @pytest.mark.parametrize("model", GPT5_PRE_5_6_MODELS) + def test_pre_5_6_models_are_not_classified_as_5_6_plus(self, model: str): + assert not OpenAIGPT5Config.is_model_gpt_5_6_plus_model(model) + + @pytest.mark.parametrize("model", GPT6_PLUS_MODELS) + def test_gpt6_plus_models_are_classified_as_6_plus(self, model: str): + assert OpenAIGPT5Config.is_model_gpt_6_plus_model(model) + + @pytest.mark.parametrize("model", GPT_PRE_6_MODELS) + def test_pre_6_models_are_not_classified_as_6_plus(self, model: str): + assert not OpenAIGPT5Config.is_model_gpt_6_plus_model(model) + + # --------------------------------------------------------------------------- # AzureOpenAIGPT5Config # --------------------------------------------------------------------------- diff --git a/tests/test_litellm/test_main.py b/tests/test_litellm/test_main.py index 2a8a4cce526..af754e069da 100644 --- a/tests/test_litellm/test_main.py +++ b/tests/test_litellm/test_main.py @@ -1049,6 +1049,35 @@ def test_responses_api_bridge_check_gpt_5_4_flat_function_tool_routes_to_respons assert model_info.get("mode") == "responses" +@pytest.mark.parametrize( + "custom_llm_provider, model_name, api_base", + [ + pytest.param("openai", "gpt-5.6", None, id="openai"), + pytest.param("azure_ai", "gpt-6-astra", "https://myproject.services.ai.azure.com", id="azure-ai-foundry"), + ], +) +def test_responses_api_bridge_check_function_tool_without_body_stays_chat( + monkeypatch, custom_llm_provider, model_name, api_base +): + import litellm + from litellm.main import responses_api_bridge_check + + monkeypatch.delenv("OPENAI_BASE_URL", raising=False) + monkeypatch.delenv("OPENAI_API_BASE", raising=False) + monkeypatch.setattr(litellm, "api_base", None) + + model_info, model = responses_api_bridge_check( + model=model_name, + custom_llm_provider=custom_llm_provider, + tools=[{"type": "function"}], + reasoning_effort=None, + api_base=api_base, + ) + + assert model == model_name + assert model_info.get("mode") != "responses" + + def test_responses_api_bridge_check_dict_effort_none_stays_chat(): """The escape hatch must honor litellm's dict form: {"effort": "none"} means reasoning off.""" from litellm.main import responses_api_bridge_check @@ -1308,6 +1337,68 @@ def test_responses_api_bridge_check_azure_with_api_base_and_unset_effort_routes( assert model_info.get("mode") == "responses" +_FOUNDRY_API_BASE: Final = "https://myproject.services.ai.azure.com" +_FOUNDRY_FUNCTION_TOOL: Final = ({"type": "function", "function": {"name": "get_weather"}},) + + +@pytest.mark.parametrize( + "model_name, api_base, reasoning_effort", + [ + pytest.param("gpt-6-astra", _FOUNDRY_API_BASE, None, id="gpt-6-unset-effort"), + pytest.param("gpt-6-astra", _FOUNDRY_API_BASE, "low", id="gpt-6-explicit-effort"), + pytest.param("gpt-6-astra", "https://myresource.openai.azure.com", None, id="gpt-6-azure-openai-host"), + pytest.param("gpt-5.6-sol", _FOUNDRY_API_BASE, "low", id="gpt-5.6-explicit-effort"), + pytest.param("gpt-5.6-sol", _FOUNDRY_API_BASE, {"effort": "high"}, id="gpt-5.6-explicit-effort-dict"), + ], +) +def test_responses_api_bridge_check_azure_ai_foundry_rejected_tools_route_to_responses( + model_name, api_base, reasoning_effort +): + from litellm.main import responses_api_bridge_check + + model_info, model = responses_api_bridge_check( + model=model_name, + custom_llm_provider="azure_ai", + tools=_FOUNDRY_FUNCTION_TOOL, + reasoning_effort=reasoning_effort, + api_base=api_base, + ) + + assert model == model_name + assert model_info.get("mode") == "responses" + + +@pytest.mark.parametrize( + "model_name, api_base, reasoning_effort", + [ + pytest.param("gpt-6-astra", _FOUNDRY_API_BASE, "none", id="explicit-none-stays-chat"), + pytest.param("gpt-5.6-sol", _FOUNDRY_API_BASE, None, id="gpt-5.6-unset-effort-stays-chat"), + pytest.param("gpt-5.6-sol", _FOUNDRY_API_BASE, "none", id="gpt-5.6-explicit-none-stays-chat"), + pytest.param("gpt-5.5", _FOUNDRY_API_BASE, "high", id="gpt-5.5-explicit-effort-stays-chat"), + pytest.param("gpt-5.4-mini", _FOUNDRY_API_BASE, None, id="gpt-5.4-mini-unset-effort-stays-chat"), + pytest.param("gpt-5.4-mini", _FOUNDRY_API_BASE, "low", id="gpt-5.4-mini-explicit-effort-stays-chat"), + pytest.param("gpt-6-astra", "https://myproject.models.ai.azure.com", None, id="serverless-host-stays-chat"), + pytest.param("Mistral-large-2411", _FOUNDRY_API_BASE, None, id="non-gpt-5-model-stays-chat"), + pytest.param("claude-opus-4-1", _FOUNDRY_API_BASE, None, id="claude-on-foundry-stays-chat"), + ], +) +def test_responses_api_bridge_check_azure_ai_without_foundry_responses_route_stays_chat( + model_name, api_base, reasoning_effort +): + from litellm.main import responses_api_bridge_check + + model_info, model = responses_api_bridge_check( + model=model_name, + custom_llm_provider="azure_ai", + tools=_FOUNDRY_FUNCTION_TOOL, + reasoning_effort=reasoning_effort, + api_base=api_base, + ) + + assert model == model_name + assert model_info.get("mode") != "responses" + + def test_responses_api_bridge_check_older_gpt_5_tools_without_reasoning_stays_chat(): """Pre-5.4 GPT-5 names keep the old boundary: tools alone never bridge.""" from litellm.main import responses_api_bridge_check @@ -1488,6 +1579,81 @@ def test_responses_bridge_preserves_reasoning_effort_with_drop_params( assert request_body["reasoning"] == {"effort": "high"} +_FOUNDRY_RESPONSES_FUNCTION_CALL_BODY: Final = { + "id": "resp_foundry", + "object": "response", + "created_at": 1789852145, + "status": "completed", + "model": "gpt-6-astra", + "output": [ + { + "id": "fc_1", + "type": "function_call", + "status": "completed", + "arguments": '{"city":"Paris"}', + "call_id": "call_1", + "name": "get_weather", + } + ], + "parallel_tool_calls": True, + "usage": { + "input_tokens": 53, + "output_tokens": 18, + "total_tokens": 71, + "output_tokens_details": {"reasoning_tokens": 0}, + }, + "error": None, + "incomplete_details": None, + "instructions": None, + "metadata": {}, + "temperature": 1.0, + "tool_choice": "auto", + "tools": [], + "top_p": 1.0, + "max_output_tokens": 200, + "previous_response_id": None, + "reasoning": {"effort": "medium", "summary": None}, + "truncation": "disabled", + "user": None, +} + + +def test_completion_bridges_azure_ai_foundry_gpt_5_4_plus_function_tools_to_responses( + respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch +): + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + responses_route: Final = respx_mock.post(f"{_FOUNDRY_API_BASE}/openai/v1/responses").respond( + json=_FOUNDRY_RESPONSES_FUNCTION_CALL_BODY + ) + + response: Final = litellm.completion( + model="azure_ai/gpt-6-astra", + messages=[{"role": "user", "content": "What is the weather in Paris? Use the tool."}], + tools=[ + { + "type": "function", + "function": { + "name": "get_weather", + "description": "Get weather for a city", + "parameters": {"type": "object", "properties": {"city": {"type": "string"}}, "required": ["city"]}, + }, + } + ], + max_tokens=200, + api_base=_FOUNDRY_API_BASE, + api_key="fake-foundry-key", + ) + + assert [str(call.request.url) for call in respx_mock.calls] == [f"{_FOUNDRY_API_BASE}/openai/v1/responses"] + request: Final = responses_route.calls[0].request + request_body: Final = json.loads(request.content) + assert request_body["tools"][0]["type"] == "function" + assert request_body["tools"][0]["name"] == "get_weather" + assert request.headers["api-key"] == "fake-foundry-key" + assert response.choices[0].finish_reason == "tool_calls" + assert response.choices[0].message.tool_calls[0].function.name == "get_weather" + + @pytest.mark.parametrize( "model, model_info, expected_model_param, expected_base_model_param", [