FakeToolCallingModel Class — langchain Architecture

Architecture documentation for the FakeToolCallingModel class in test_prompt_caching.py from the langchain codebase.

Class python

Entity Profile

Dependency Diagram

graph TD
  84cca705_1eaa_cf41_ae6b_9059440df4c8["FakeToolCallingModel"]
  48aa29b8_65e7_522f_a445_a441eeb6baff["BaseChatModel"]
  84cca705_1eaa_cf41_ae6b_9059440df4c8 -->|extends| 48aa29b8_65e7_522f_a445_a441eeb6baff
  80b9bbd1_b825_9778_a36c_351fbf1d2478["test_prompt_caching.py"]
  84cca705_1eaa_cf41_ae6b_9059440df4c8 -->|defined in| 80b9bbd1_b825_9778_a36c_351fbf1d2478
  bba57080_8949_db45_736a_e8f9fb0fa832["_generate()"]
  84cca705_1eaa_cf41_ae6b_9059440df4c8 -->|method| bba57080_8949_db45_736a_e8f9fb0fa832
  7011d587_acb4_b0cd_06ad_04d2c3714e13["_agenerate()"]
  84cca705_1eaa_cf41_ae6b_9059440df4c8 -->|method| 7011d587_acb4_b0cd_06ad_04d2c3714e13
  4a242aa4_a02d_3f88_7091_9149ee9f4c9a["_llm_type()"]
  84cca705_1eaa_cf41_ae6b_9059440df4c8 -->|method| 4a242aa4_a02d_3f88_7091_9149ee9f4c9a

Relationship Graph

Source Code

libs/partners/anthropic/tests/unit_tests/middleware/test_prompt_caching.py lines 26–55

class FakeToolCallingModel(BaseChatModel):
    """Fake model for testing middleware."""

    def _generate(
        self,
        messages: list[BaseMessage],
        stop: list[str] | None = None,
        run_manager: CallbackManagerForLLMRun | None = None,
        **kwargs: Any,
    ) -> ChatResult:
        """Top Level call"""
        messages_string = "-".join([str(m.content) for m in messages])
        message = AIMessage(content=messages_string, id="0")
        return ChatResult(generations=[ChatGeneration(message=message)])

    async def _agenerate(
        self,
        messages: list[BaseMessage],
        stop: list[str] | None = None,
        run_manager: AsyncCallbackManagerForLLMRun | None = None,
        **kwargs: Any,
    ) -> ChatResult:
        """Async top level call"""
        messages_string = "-".join([str(m.content) for m in messages])
        message = AIMessage(content=messages_string, id="0")
        return ChatResult(generations=[ChatGeneration(message=message)])

    @property
    def _llm_type(self) -> str:
        return "fake-tool-call-model"