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Fix function_calling_llm support for custom models
- Add supports_function_calling() method to BaseLLM class with default True - Add supports_function_calling parameter to LLM class to allow override of litellm check - Add tests for both BaseLLM default and LLM override functionality - Fixes #3708: Custom models not in litellm's list can now use function calling Co-Authored-By: João <joao@crewai.com>
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@@ -299,6 +299,7 @@ class LLM(BaseLLM):
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callbacks: list[Any] | None = None,
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reasoning_effort: Literal["none", "low", "medium", "high"] | None = None,
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stream: bool = False,
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supports_function_calling: bool | None = None,
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**kwargs,
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):
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self.model = model
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@@ -325,6 +326,7 @@ class LLM(BaseLLM):
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self.additional_params = kwargs
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self.is_anthropic = self._is_anthropic_model(model)
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self.stream = stream
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self._supports_function_calling_override = supports_function_calling
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litellm.drop_params = True
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@@ -1197,6 +1199,9 @@ class LLM(BaseLLM):
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)
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def supports_function_calling(self) -> bool:
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if self._supports_function_calling_override is not None:
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return self._supports_function_calling_override
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try:
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provider = self._get_custom_llm_provider()
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return litellm.utils.supports_function_calling(
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@@ -9,6 +9,7 @@ from typing import Any, Final
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DEFAULT_CONTEXT_WINDOW_SIZE: Final[int] = 4096
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DEFAULT_SUPPORTS_STOP_WORDS: Final[bool] = True
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DEFAULT_SUPPORTS_FUNCTION_CALLING: Final[bool] = True
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class BaseLLM(ABC):
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@@ -82,6 +83,14 @@ class BaseLLM(ABC):
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RuntimeError: If the LLM request fails for other reasons.
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"""
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def supports_function_calling(self) -> bool:
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"""Check if the LLM supports function calling.
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Returns:
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True if the LLM supports function calling, False otherwise.
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"""
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return DEFAULT_SUPPORTS_FUNCTION_CALLING
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def supports_stop_words(self) -> bool:
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"""Check if the LLM supports stop words.
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@@ -358,3 +358,25 @@ def test_timeout_handling_llm():
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with pytest.raises(TimeoutError, match="LLM request failed after 2 attempts"):
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llm.call("Test message")
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assert len(llm.calls) == 2 # Initial call + failed retry attempt
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class MinimalCustomLLM(BaseLLM):
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"""Minimal custom LLM implementation that doesn't override supports_function_calling."""
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def __init__(self):
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super().__init__(model="minimal-model")
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def call(
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self,
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messages: Union[str, List[Dict[str, str]]],
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tools: Optional[List[dict]] = None,
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callbacks: Optional[List[Any]] = None,
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available_functions: Optional[Dict[str, Any]] = None,
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) -> Union[str, Any]:
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return "Minimal response"
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def test_base_llm_supports_function_calling_default():
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"""Test that BaseLLM supports function calling by default."""
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llm = MinimalCustomLLM()
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assert llm.supports_function_calling() is True
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@@ -711,3 +711,18 @@ def test_ollama_does_not_modify_when_last_is_user(ollama_llm):
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formatted = ollama_llm._format_messages_for_provider(original_messages)
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assert formatted == original_messages
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def test_supports_function_calling_with_override_true():
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llm = LLM(model="custom-model/my-model", supports_function_calling=True)
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assert llm.supports_function_calling() is True
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def test_supports_function_calling_with_override_false():
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llm = LLM(model="gpt-4o-mini", supports_function_calling=False)
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assert llm.supports_function_calling() is False
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def test_supports_function_calling_without_override():
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llm = LLM(model="gpt-4o-mini")
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assert llm.supports_function_calling() is True
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