from_llm_and_tools() — langchain Function Reference

Architecture documentation for the from_llm_and_tools() function in agent.py from the langchain codebase.

Function python AgentOrchestration ActionLogic calls 4 called by 1

Entity Profile

AgentOrchestration→ ActionLogic→ from_llm_and_tools() — langchain Function Reference

Dependency Diagram

graph TD
  3a0359f9_7d00_0224_43fc_5340807a0410["from_llm_and_tools()"]
  37fcc3f3_2798_3648_915c_2bffdd19bff7["Agent"]
  3a0359f9_7d00_0224_43fc_5340807a0410 -->|defined in| 37fcc3f3_2798_3648_915c_2bffdd19bff7
  17edecaa_ea70_0ca0_a54a_689470a272cb["from_llm_and_tools()"]
  17edecaa_ea70_0ca0_a54a_689470a272cb -->|calls| 3a0359f9_7d00_0224_43fc_5340807a0410
  17edecaa_ea70_0ca0_a54a_689470a272cb["from_llm_and_tools()"]
  3a0359f9_7d00_0224_43fc_5340807a0410 -->|calls| 17edecaa_ea70_0ca0_a54a_689470a272cb
  435f2e16_bc7d_43f2_cc0b_360611c3dfdd["_validate_tools()"]
  3a0359f9_7d00_0224_43fc_5340807a0410 -->|calls| 435f2e16_bc7d_43f2_cc0b_360611c3dfdd
  34a00584_a217_acd8_c7a1_ffcb6682f776["create_prompt()"]
  3a0359f9_7d00_0224_43fc_5340807a0410 -->|calls| 34a00584_a217_acd8_c7a1_ffcb6682f776
  9b628998_af79_5d38_e7e8_9f8627958039["_get_default_output_parser()"]
  3a0359f9_7d00_0224_43fc_5340807a0410 -->|calls| 9b628998_af79_5d38_e7e8_9f8627958039
  style 3a0359f9_7d00_0224_43fc_5340807a0410 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/langchain/langchain_classic/agents/agent.py lines 885–918

    def from_llm_and_tools(
        cls,
        llm: BaseLanguageModel,
        tools: Sequence[BaseTool],
        callback_manager: BaseCallbackManager | None = None,
        output_parser: AgentOutputParser | None = None,
        **kwargs: Any,
    ) -> Agent:
        """Construct an agent from an LLM and tools.

        Args:
            llm: Language model to use.
            tools: Tools to use.
            callback_manager: Callback manager to use.
            output_parser: Output parser to use.
            kwargs: Additional arguments.

        Returns:
            Agent object.
        """
        cls._validate_tools(tools)
        llm_chain = LLMChain(
            llm=llm,
            prompt=cls.create_prompt(tools),
            callback_manager=callback_manager,
        )
        tool_names = [tool.name for tool in tools]
        _output_parser = output_parser or cls._get_default_output_parser()
        return cls(
            llm_chain=llm_chain,
            allowed_tools=tool_names,
            output_parser=_output_parser,
            **kwargs,
        )