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fix(tool_choice): accept OpenAI allowed_tools on chat completions and flatten it for the Responses bridge (#49043)
* fix(tool_choice): accept OpenAI allowed_tools on chat completions and flatten it for the Responses bridge Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test: type the allowed_tools tool_choice fixtures Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test: raw regex for the allowed_tools provider gate match Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(tool_choice): move the allowed_tools provider gate out of completion() so pyright can still analyze it Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(tool_choice): keep the allowed_tools helpers typed so the basedpyright gate stays level Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(tool_choice): type the allowed_tools validation boundary with Any instead of casts Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(tool_choice): widen tool_choice to object at the allowed_tools helpers with a cast-ok reason Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(tool_choice): drop allowed_tools test docstrings, type the new tests, and revert unrelated reformatting Also reword the allowed_tools 400 so it no longer blames the flat Responses layout for every malformed choice --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
This commit is contained in:
ryan-crabbe-berri
GitHub
parent
20cb3ea439
commit
28c80048ed
10 changed files with 448 additions and 7 deletions
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@ -16,6 +16,7 @@ from openai.types.responses.response_input_param import (
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ResponseCustomToolCallOutputParam,
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ResponseCustomToolCallParam,
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)
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from openai.types.responses.tool_choice_allowed_param import ToolChoiceAllowedParam
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from openai.types.responses.tool_choice_custom_param import ToolChoiceCustomParam
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from openai.types.responses.tool_choice_function_param import ToolChoiceFunctionParam
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from openai.types.responses.tool_param import FunctionToolParam
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@ -34,6 +35,10 @@ from litellm.completion_extras.litellm_responses_transformation.history import (
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requested_phase,
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)
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from litellm.integrations.anthropic_cache_control_hook import supports_openai_prompt_cache_breakpoint
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from litellm.litellm_core_utils.allowed_tools_tool_choice import (
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parse_chat_allowed_tools_tool_choice,
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responses_allowed_tools_tool_choice,
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)
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from litellm.litellm_core_utils.core_helpers import drops_unsupported_params
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from litellm.litellm_core_utils.hidden_params import get_hidden_params, get_or_create_hidden_params
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from litellm.litellm_core_utils.prompt_templates.common_utils import (
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@ -783,13 +788,28 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
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def _normalize_tool_choice_for_responses_api(
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self, tool_choice: _ToolChoiceT
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) -> _ToolChoiceT | ToolChoiceFunctionParam | ToolChoiceCustomParam | Literal["auto", "none", "required"]:
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) -> (
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_ToolChoiceT
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| ToolChoiceFunctionParam
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| ToolChoiceCustomParam
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| ToolChoiceAllowedParam
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| Literal["auto", "none", "required"]
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):
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"""Chat tool_choice nests the name under function/custom; Responses API expects top-level name."""
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if not isinstance(tool_choice, dict):
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return tool_choice
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choice_type: Final = tool_choice.get("type")
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if isinstance(choice_type, str) and choice_type in ("auto", "none", "required"):
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return choice_type
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if choice_type == "allowed_tools":
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parsed: Final = parse_chat_allowed_tools_tool_choice(
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cast( # cast-ok: widening an untyped dict to object is always sound, the helper validates it with pydantic
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object, tool_choice
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)
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)
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flat: Final = responses_allowed_tools_tool_choice(parsed) if parsed is not None else None
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if flat is not None:
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return flat
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if choice_type not in ("function", "custom"):
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return tool_choice
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if isinstance(tool_choice.get("name"), str) and tool_choice.get("name"):
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111
litellm/litellm_core_utils/allowed_tools_tool_choice.py
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111
litellm/litellm_core_utils/allowed_tools_tool_choice.py
Normal file
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@ -0,0 +1,111 @@
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from collections.abc import Mapping
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from typing import Final, Literal
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from openai.types.responses.tool_choice_allowed_param import ToolChoiceAllowedParam
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from pydantic import BaseModel, ConfigDict, Field, TypeAdapter, ValidationError
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from litellm.exceptions import BadRequestError
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ALLOWED_TOOLS_TOOL_CHOICE_PROVIDERS: Final = frozenset({"openai", "azure", "litellm_proxy"})
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CHAT_ALLOWED_TOOLS_LAYOUT: Final = (
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'{"type": "allowed_tools", "allowed_tools": {"mode": "auto" | "required", "tools": [<at least one tool>]}}'
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)
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class ChatAllowedTools(BaseModel):
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model_config = ConfigDict(frozen=True, extra="forbid")
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mode: Literal["auto", "required"]
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tools: tuple[Mapping[str, object], ...] = Field(min_length=1)
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class ChatAllowedToolsToolChoice(BaseModel):
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model_config = ConfigDict(frozen=True, extra="forbid")
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type: Literal["allowed_tools"]
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allowed_tools: ChatAllowedTools
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_CHAT_ALLOWED_TOOLS_TOOL_CHOICE: Final = TypeAdapter(ChatAllowedToolsToolChoice)
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_SELECTOR: Final = TypeAdapter(dict[str, object])
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class _ToolChoiceType(BaseModel):
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model_config = ConfigDict(frozen=True)
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type: str
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_TOOL_CHOICE_TYPE: Final = TypeAdapter(_ToolChoiceType)
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def is_allowed_tools_tool_choice(tool_choice: object) -> bool:
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try:
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return _TOOL_CHOICE_TYPE.validate_python(tool_choice).type == "allowed_tools"
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except ValidationError:
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return False
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def raise_if_allowed_tools_tool_choice_unsupported(
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tool_choice: object,
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custom_llm_provider: str,
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model: str,
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) -> None:
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"""Providers outside the set would silently send the request with no tool restriction at all, so the call stops
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here with a 400. ``drop_params`` is deliberately not consulted: dropping a restriction widens what the model may call."""
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if not is_allowed_tools_tool_choice(tool_choice) or custom_llm_provider in ALLOWED_TOOLS_TOOL_CHOICE_PROVIDERS:
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return
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raise BadRequestError(
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message=(
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"tool_choice type 'allowed_tools' is only supported for "
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f"{', '.join(sorted(ALLOWED_TOOLS_TOOL_CHOICE_PROVIDERS))}, got custom_llm_provider={custom_llm_provider}. "
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"drop_params does not drop it, since that would let the model call tools the request excluded. "
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"Send only the allowed tools in `tools` with tool_choice='auto' or 'required' instead."
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),
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model=model,
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llm_provider=custom_llm_provider,
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)
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def parse_chat_allowed_tools_tool_choice(tool_choice: object) -> ChatAllowedToolsToolChoice | None:
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try:
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return _CHAT_ALLOWED_TOOLS_TOOL_CHOICE.validate_python(tool_choice)
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except ValidationError:
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return None
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def _has_name(selector: Mapping[str, object]) -> bool:
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name: Final = selector.get("name")
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return isinstance(name, str) and name != ""
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def _responses_allowed_tool(tool: Mapping[str, object]) -> Mapping[str, object] | None:
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tool_type: Final = tool.get("type")
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if tool_type not in ("function", "custom"):
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return tool
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if tool_type not in tool:
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return tool if _has_name(tool) else None
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try:
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nested: Final = _SELECTOR.validate_python(tool[tool_type])
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except ValidationError:
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return None
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outer: Final = {key: value for key, value in tool.items() if key != tool_type}
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if not _has_name(nested) or outer.keys() & nested.keys():
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return None
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return {**outer, **nested}
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def responses_allowed_tools_tool_choice(choice: ChatAllowedToolsToolChoice) -> ToolChoiceAllowedParam | None:
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"""The flat Responses API layout of a chat ``allowed_tools`` choice, or ``None`` when an entry is malformed or
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carries conflicting keys, so the caller sends the original rather than a rewrite that could mean something looser."""
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flattened: Final = tuple(_responses_allowed_tool(tool) for tool in choice.allowed_tools.tools)
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if any(tool is None for tool in flattened):
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return None
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return ToolChoiceAllowedParam(
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type="allowed_tools",
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mode=choice.allowed_tools.mode,
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tools=[dict(tool) for tool in flattened if tool is not None],
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)
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@ -1,11 +1,17 @@
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from collections.abc import Mapping, Sequence
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from types import MappingProxyType
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from typing import TYPE_CHECKING, Any, Final
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from typing import (
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TYPE_CHECKING,
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Any,
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Final,
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cast, # noqa: TID251 # non_default_params reaches the mapper as an untyped dict
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)
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from httpx._models import Headers, Response
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import litellm
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from litellm.integrations.anthropic_cache_control_hook import deployment_prompt_cache_breakpoint_support
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from litellm.litellm_core_utils.allowed_tools_tool_choice import is_allowed_tools_tool_choice
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from litellm.litellm_core_utils.core_helpers import drops_unsupported_params
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from litellm.litellm_core_utils.prompt_templates.common_utils import (
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chat_completion_prompt_cache_breakpoints_for_wire,
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@ -245,12 +251,12 @@ class AzureOpenAIConfig(BaseConfig):
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or (api_version_year == "2023" and api_version_month < "12")
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or (api_version_year == "2023" and api_version_month == "12" and api_version_day < "01")
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):
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if litellm.drop_params is True or (drop_params is not None and drop_params is True):
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pass
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else:
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if is_allowed_tools_tool_choice(
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cast(object, value) # cast-ok: widening an untyped dict value to object is always sound
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) or not (litellm.drop_params is True or (drop_params is not None and drop_params is True)):
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raise UnsupportedParamsError(
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status_code=400,
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message=f"""Azure does not support 'tool_choice', for api_version={api_version}. Bump your API version to '2023-12-01-preview' or later. This parameter requires 'api_version="2023-12-01-preview"' or later. Azure API Reference: https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#chat-completions""",
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message=f"""Azure does not support 'tool_choice', for api_version={api_version}. Bump your API version to '2023-12-01-preview' or later. This parameter requires 'api_version="2023-12-01-preview"' or later. drop_params never drops an allowed_tools tool_choice, since that would let the model call tools the request excluded. Azure API Reference: https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#chat-completions""",
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)
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elif value == "required" and (
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api_version_year == "2024" and api_version_month <= "05"
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@ -70,6 +70,9 @@ from litellm.constants import (
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)
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from litellm.exceptions import LiteLLMUnknownProvider
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from litellm.integrations.custom_logger import CustomLogger
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from litellm.litellm_core_utils.allowed_tools_tool_choice import (
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raise_if_allowed_tools_tool_choice_unsupported,
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)
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from litellm.litellm_core_utils.asyncify import asyncify, run_async_function
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from litellm.litellm_core_utils.audio_utils.utils import (
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calculate_request_duration,
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@ -5956,6 +5959,14 @@ def completion(
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if not is_claude_tool_target(custom_llm_provider=custom_llm_provider, model=model):
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tools = _drop_anthropic_only_tool_keys(tools=tools)
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raise_if_allowed_tools_tool_choice_unsupported(
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tool_choice=cast( # cast-ok: widening an untyped dict to object is always sound, the helper validates it with pydantic
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object, tool_choice
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),
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custom_llm_provider=custom_llm_provider,
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model=model,
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)
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if provider_specific_header is not None:
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headers.update(
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ProviderSpecificHeaderUtils.get_provider_specific_headers(
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@ -83,6 +83,10 @@ from litellm.constants import (
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PROVIDERS_THAT_AUTHENTICATE_ON_PROVIDER_INFO,
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TOOL_CHOICE_OBJECT_TOKEN_COUNT,
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)
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from litellm.litellm_core_utils.allowed_tools_tool_choice import (
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CHAT_ALLOWED_TOOLS_LAYOUT,
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parse_chat_allowed_tools_tool_choice,
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)
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from litellm.litellm_core_utils.core_helpers import (
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bind_budget_reservation_to_callbacks,
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normalize_drop_params,
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@ -9470,9 +9474,28 @@ def validate_chat_completion_tool_choice(
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tool_choice_type = tool_choice.get("type")
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if tool_choice_type in ("auto", "none", "required") and "function" not in tool_choice:
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return tool_choice_type
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if (
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tool_choice_type == "allowed_tools"
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and (
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parse_chat_allowed_tools_tool_choice(
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cast( # cast-ok: widening an untyped dict to object is always sound, the helper validates it with pydantic
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object, tool_choice
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)
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)
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is None
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)
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):
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raise BadRequestError(
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message=(
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f"Invalid tool choice, tool_choice={tool_choice}. On chat completions an allowed_tools "
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f"tool_choice must be {CHAT_ALLOWED_TOOLS_LAYOUT}"
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),
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model=model,
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llm_provider="",
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)
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# Standard OpenAI format: {"type": "function", "function": {...}}
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if tool_choice.get("type") is None or tool_choice.get("function") is None:
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if tool_choice_type != "allowed_tools" and (tool_choice_type is None or tool_choice.get("function") is None):
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raise BadRequestError(
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message=f"Invalid tool choice, tool_choice={tool_choice}. Please ensure tool_choice follows the OpenAI spec",
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model=model,
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@ -3064,6 +3064,38 @@ def test_map_optional_params_tool_choice_chat_nested_to_responses_api():
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{"type": "custom", "name": "ApplyPatch"},
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),
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({"type": "custom"}, {"type": "custom"}),
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(
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{
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"type": "allowed_tools",
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"allowed_tools": {
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"mode": "required",
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"tools": [
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{"type": "function", "function": {"name": "get_time"}},
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{"type": "custom", "custom": {"name": "apply_patch"}},
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{"type": "mcp", "server_label": "docs"},
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{"type": "function", "name": "already_flat"},
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],
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},
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},
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{
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"type": "allowed_tools",
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"mode": "required",
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"tools": [
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{"type": "function", "name": "get_time"},
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{"type": "custom", "name": "apply_patch"},
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{"type": "mcp", "server_label": "docs"},
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{"type": "function", "name": "already_flat"},
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],
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},
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),
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(
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{"type": "allowed_tools", "allowed_tools": {"mode": "auto", "tools": [{"type": "function"}]}},
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{"type": "allowed_tools", "allowed_tools": {"mode": "auto", "tools": [{"type": "function"}]}},
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),
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(
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{"type": "allowed_tools", "mode": "auto", "tools": [{"type": "function", "name": "get_time"}]},
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{"type": "allowed_tools", "mode": "auto", "tools": [{"type": "function", "name": "get_time"}]},
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),
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],
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)
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def test_normalize_tool_choice_for_responses_api(tool_choice, expected):
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@ -4105,6 +4137,16 @@ def test_output_item_done_with_stream_map_keeps_empty_delta():
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({"type": "required"}, "required"),
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("auto", "auto"),
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({"type": "function", "function": {"name": "get_weather"}}, {"type": "function", "name": "get_weather"}),
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(
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{
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"type": "allowed_tools",
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"allowed_tools": {
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"mode": "required",
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"tools": [{"type": "function", "function": {"name": "get_weather"}}],
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},
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},
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{"type": "allowed_tools", "mode": "required", "tools": [{"type": "function", "name": "get_weather"}]},
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),
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],
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)
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async def test_acompletion_bridge_normalizes_tool_choice_on_the_wire(
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@ -4177,6 +4219,7 @@ async def test_acompletion_bridge_normalizes_tool_choice_on_the_wire(
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post_kwargs = mock_post.call_args.kwargs
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request_body = post_kwargs["json"] if "json" in post_kwargs else json.loads(post_kwargs["data"])
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assert request_body["tool_choice"] == expected_wire_tool_choice
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assert [tool["name"] for tool in request_body["tools"]] == ["get_weather"]
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def _make_incomplete_responses_api_response(
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|
|
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100
tests/unit/litellm_core_utils/test_allowed_tools_tool_choice.py
Normal file
100
tests/unit/litellm_core_utils/test_allowed_tools_tool_choice.py
Normal file
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@ -0,0 +1,100 @@
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import copy
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from collections.abc import Mapping
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from typing import Final
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import pytest
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from litellm.litellm_core_utils.allowed_tools_tool_choice import (
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ChatAllowedToolsToolChoice,
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is_allowed_tools_tool_choice,
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parse_chat_allowed_tools_tool_choice,
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responses_allowed_tools_tool_choice,
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)
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_CHAT_LAYOUT: Final[dict[str, object]] = {
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"type": "allowed_tools",
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"allowed_tools": {
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"mode": "auto",
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"tools": [
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{"type": "function", "function": {"name": "get_time"}},
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{"type": "custom", "custom": {"name": "apply_patch", "x-vendor": 1}, "x-trace": "a"},
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{"type": "mcp", "server_label": "docs", "server_url": "https://docs.example"},
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{"type": "function", "name": "already_flat"},
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],
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},
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}
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def _parsed(tool_choice: Mapping[str, object]) -> ChatAllowedToolsToolChoice:
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parsed: Final = parse_chat_allowed_tools_tool_choice(tool_choice)
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assert parsed is not None
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return parsed
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def test_responses_layout_lifts_mode_and_tools_and_flattens_names_in_order():
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assert responses_allowed_tools_tool_choice(_parsed(_CHAT_LAYOUT)) == {
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"type": "allowed_tools",
|
||||
"mode": "auto",
|
||||
"tools": [
|
||||
{"type": "function", "name": "get_time"},
|
||||
{"type": "custom", "name": "apply_patch", "x-vendor": 1, "x-trace": "a"},
|
||||
{"type": "mcp", "server_label": "docs", "server_url": "https://docs.example"},
|
||||
{"type": "function", "name": "already_flat"},
|
||||
],
|
||||
}
|
||||
|
||||
|
||||
def test_responses_layout_leaves_the_caller_dict_untouched():
|
||||
original: Final = copy.deepcopy(_CHAT_LAYOUT)
|
||||
flat: Final = responses_allowed_tools_tool_choice(_parsed(_CHAT_LAYOUT))
|
||||
assert flat is not None
|
||||
next(iter(flat["tools"]))["name"] = "mutated"
|
||||
assert _CHAT_LAYOUT == original
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"tool",
|
||||
[
|
||||
{"type": "function"},
|
||||
{"type": "function", "name": ""},
|
||||
{"type": "function", "function": {}},
|
||||
{"type": "function", "function": "get_time"},
|
||||
{"type": "custom", "custom": {"name": ""}},
|
||||
{"type": "function", "name": "get_time", "function": {"name": "get_weather"}},
|
||||
{"type": "function", "function": {"name": "get_time", "type": "custom"}},
|
||||
],
|
||||
)
|
||||
def test_responses_layout_refuses_to_rewrite_a_malformed_or_conflicting_entry(tool: dict[str, object]):
|
||||
tool_choice: Final[dict[str, object]] = {
|
||||
"type": "allowed_tools",
|
||||
"allowed_tools": {"mode": "required", "tools": [tool]},
|
||||
}
|
||||
assert responses_allowed_tools_tool_choice(_parsed(tool_choice)) is None
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"tool_choice",
|
||||
[
|
||||
{"type": "allowed_tools", "mode": "auto", "tools": [{"type": "function", "name": "get_time"}]},
|
||||
{"type": "allowed_tools", "allowed_tools": {"mode": "auto", "tools": []}},
|
||||
{"type": "allowed_tools", "allowed_tools": {"mode": "any", "tools": [{"type": "function"}]}},
|
||||
{"type": "allowed_tools", "allowed_tools": {"mode": "auto", "tools": [{"type": "function"}]}, "extra": 1},
|
||||
{"type": "function", "function": {"name": "get_time"}},
|
||||
],
|
||||
)
|
||||
def test_parse_rejects_anything_but_the_chat_layout(tool_choice: dict[str, object]):
|
||||
assert parse_chat_allowed_tools_tool_choice(tool_choice) is None
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
("tool_choice", "expected"),
|
||||
[
|
||||
(_CHAT_LAYOUT, True),
|
||||
({"type": "allowed_tools"}, True),
|
||||
({"type": "function"}, False),
|
||||
("auto", False),
|
||||
(None, False),
|
||||
],
|
||||
)
|
||||
def test_is_allowed_tools_tool_choice(tool_choice: Mapping[str, object] | str | None, expected: bool):
|
||||
assert is_allowed_tools_tool_choice(tool_choice) is expected
|
||||
|
|
@ -75,6 +75,42 @@ def test_map_openai_params_with_preview_api_version():
|
|||
)
|
||||
|
||||
|
||||
def _map_tool_choice_on_pre_tool_choice_api_version(tool_choice: dict[str, object]) -> dict[str, object]:
|
||||
return AzureOpenAIConfig().map_openai_params(
|
||||
{"tool_choice": tool_choice, "tools": [{"type": "function", "function": {"name": "get_time"}}]},
|
||||
{},
|
||||
"gpt-4o",
|
||||
drop_params=True,
|
||||
api_version="2023-07-01-preview",
|
||||
)
|
||||
|
||||
|
||||
def test_map_openai_params_drop_params_still_drops_a_named_tool_choice_on_old_api_version():
|
||||
mapped: Final = _map_tool_choice_on_pre_tool_choice_api_version(
|
||||
{"type": "function", "function": {"name": "get_time"}}
|
||||
)
|
||||
assert "tool_choice" not in mapped
|
||||
|
||||
|
||||
def test_map_openai_params_drop_params_never_drops_allowed_tools_on_old_api_version():
|
||||
with pytest.raises(litellm.UnsupportedParamsError, match="allowed_tools") as exc:
|
||||
_map_tool_choice_on_pre_tool_choice_api_version(
|
||||
{"type": "allowed_tools", "allowed_tools": {"mode": "auto", "tools": [{"type": "function"}]}}
|
||||
)
|
||||
assert exc.value.status_code == 400
|
||||
|
||||
|
||||
def test_map_openai_params_forwards_allowed_tools_on_current_api_version():
|
||||
tool_choice: Final[dict[str, object]] = {
|
||||
"type": "allowed_tools",
|
||||
"allowed_tools": {"mode": "required", "tools": [{"type": "function", "function": {"name": "get_time"}}]},
|
||||
}
|
||||
mapped: Final = AzureOpenAIConfig().map_openai_params(
|
||||
{"tool_choice": tool_choice}, {}, "gpt-4o", drop_params=True, api_version="2025-04-01-preview"
|
||||
)
|
||||
assert mapped["tool_choice"] == tool_choice
|
||||
|
||||
|
||||
def test_transform_request_hoists_tool_message_image():
|
||||
"""Azure builds its request via convert_to_azure_openai_messages without the
|
||||
OpenAIGPTConfig._transform_messages pipeline, so transform_request must hoist
|
||||
|
|
|
|||
|
|
@ -553,6 +553,63 @@ def test_completion_strips_eager_input_streaming_before_openai(respx_mock: respx
|
|||
assert sent_tool["function"]["name"] == "write_file"
|
||||
|
||||
|
||||
_ALLOWED_TOOLS_TOOL_CHOICE: Final = {
|
||||
"type": "allowed_tools",
|
||||
"allowed_tools": {"mode": "required", "tools": [{"type": "function", "function": {"name": "get_time"}}]},
|
||||
}
|
||||
_TWO_TOOLS: Final = [
|
||||
{"type": "function", "function": {"name": "get_time", "parameters": {"type": "object", "properties": {}}}},
|
||||
{"type": "function", "function": {"name": "get_weather", "parameters": {"type": "object", "properties": {}}}},
|
||||
]
|
||||
|
||||
|
||||
@pytest.mark.parametrize("model", ["openai/gpt-5.5", "azure/my-gpt-deployment"])
|
||||
def test_completion_forwards_allowed_tools_tool_choice_to_openai_compatible_chat(
|
||||
respx_mock: respx.MockRouter, openai_api_response: dict[str, object], model: str
|
||||
):
|
||||
mock_route: Final = respx_mock.post(url__regex=r"http://localhost:12346/.*chat/completions.*").mock(
|
||||
return_value=httpx.Response(status_code=200, json=openai_api_response)
|
||||
)
|
||||
|
||||
litellm.completion(
|
||||
model=model,
|
||||
messages=[{"role": "user", "content": "What time is it?"}],
|
||||
tools=_TWO_TOOLS,
|
||||
tool_choice=_ALLOWED_TOOLS_TOOL_CHOICE,
|
||||
api_base="http://localhost:12346/v1",
|
||||
api_key="fake_api_key",
|
||||
api_version="2025-04-01-preview",
|
||||
)
|
||||
|
||||
assert mock_route.called
|
||||
sent: Final = json.loads(respx_mock.calls[0].request.content)
|
||||
assert sent["tool_choice"] == _ALLOWED_TOOLS_TOOL_CHOICE
|
||||
assert [tool["function"]["name"] for tool in sent["tools"]] == ["get_time", "get_weather"]
|
||||
|
||||
|
||||
@pytest.mark.parametrize("drop_params", [False, True])
|
||||
@pytest.mark.parametrize("model", ["anthropic/claude-sonnet-4-5", "gemini/gemini-2.5-flash", "bedrock/converse/x"])
|
||||
def test_completion_allowed_tools_tool_choice_is_a_400_where_the_provider_cannot_enforce_it(
|
||||
respx_mock: respx.MockRouter, model: str, drop_params: bool
|
||||
):
|
||||
with pytest.raises(
|
||||
litellm.BadRequestError, match=r"allowed_tools.*only supported for azure, litellm_proxy, openai"
|
||||
) as exc:
|
||||
litellm.completion(
|
||||
model=model,
|
||||
messages=[{"role": "user", "content": "What time is it?"}],
|
||||
tools=_TWO_TOOLS,
|
||||
tool_choice=_ALLOWED_TOOLS_TOOL_CHOICE,
|
||||
drop_params=drop_params,
|
||||
api_key="fake_api_key",
|
||||
aws_access_key_id="fake",
|
||||
aws_secret_access_key="fake",
|
||||
aws_region_name="us-east-1",
|
||||
)
|
||||
assert exc.value.status_code == 400
|
||||
assert not respx_mock.calls
|
||||
|
||||
|
||||
_CLAUDE_TOOL_SEARCH_CALL: Final = {
|
||||
"id": "srvtoolu_01search",
|
||||
"type": "function",
|
||||
|
|
|
|||
|
|
@ -8651,6 +8651,40 @@ def test_validate_tool_choice_invalid_dict_is_a_400(tool_choice):
|
|||
assert exc_info.value.model == MODEL
|
||||
|
||||
|
||||
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
||||
@pytest.mark.parametrize("mode", ["auto", "required"])
|
||||
def test_validate_tool_choice_allowed_tools_chat_layout_passes_through(mode: str):
|
||||
tool_choice: Final = {
|
||||
"type": "allowed_tools",
|
||||
"allowed_tools": {
|
||||
"mode": mode,
|
||||
"tools": [{"type": "function", "function": {"name": "get_time"}}, {"type": "mcp", "server_label": "docs"}],
|
||||
},
|
||||
}
|
||||
assert validate_chat_completion_tool_choice(tool_choice, model=MODEL) is tool_choice
|
||||
|
||||
|
||||
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
||||
@pytest.mark.parametrize(
|
||||
"tool_choice",
|
||||
[
|
||||
{"type": "allowed_tools", "mode": "required", "tools": [{"type": "function", "name": "get_time"}]},
|
||||
{"type": "allowed_tools"},
|
||||
{"type": "allowed_tools", "allowed_tools": {"mode": "required"}},
|
||||
{"type": "allowed_tools", "allowed_tools": {"mode": "required", "tools": []}},
|
||||
{"type": "allowed_tools", "allowed_tools": {"mode": "none", "tools": [{"type": "function"}]}},
|
||||
{"type": "allowed_tools", "allowed_tools": {"tools": [{"type": "function", "function": {"name": "a"}}]}},
|
||||
{"type": "allowed_tools", "allowed_tools": {"mode": "auto", "tools": "get_time"}},
|
||||
],
|
||||
)
|
||||
def test_validate_tool_choice_allowed_tools_malformed_is_a_400(tool_choice: dict[str, object]):
|
||||
with pytest.raises(litellm.BadRequestError, match="allowed_tools") as exc_info:
|
||||
validate_chat_completion_tool_choice(tool_choice, model=MODEL)
|
||||
assert exc_info.value.status_code == 400
|
||||
assert exc_info.value.model == MODEL
|
||||
assert '"mode": "auto" | "required"' in str(exc_info.value)
|
||||
|
||||
|
||||
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
||||
@pytest.mark.parametrize("tool_choice", [123, []])
|
||||
def test_validate_tool_choice_invalid_type_is_a_400(tool_choice):
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue