from_llm() — langchain Function Reference

Architecture documentation for the from_llm() function in base.py from the langchain codebase.

Function python AgentOrchestration ClassicChains

Entity Profile

AgentOrchestration→ ClassicChains→ from_llm() — langchain Function Reference

Dependency Diagram

graph TD
  062c7fde_383f_ddbc_fa3b_affdcf00ca07["from_llm()"]
  1cb458d9_f8c6_d78d_c1e3_79a8b3106c08["BaseRetrievalQA"]
  062c7fde_383f_ddbc_fa3b_affdcf00ca07 -->|defined in| 1cb458d9_f8c6_d78d_c1e3_79a8b3106c08
  style 062c7fde_383f_ddbc_fa3b_affdcf00ca07 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/langchain/langchain_classic/chains/retrieval_qa/base.py lines 70–101

    def from_llm(
        cls,
        llm: BaseLanguageModel,
        prompt: PromptTemplate | None = None,
        callbacks: Callbacks = None,
        llm_chain_kwargs: dict | None = None,
        **kwargs: Any,
    ) -> BaseRetrievalQA:
        """Initialize from LLM."""
        _prompt = prompt or PROMPT_SELECTOR.get_prompt(llm)
        llm_chain = LLMChain(
            llm=llm,
            prompt=_prompt,
            callbacks=callbacks,
            **(llm_chain_kwargs or {}),
        )
        document_prompt = PromptTemplate(
            input_variables=["page_content"],
            template="Context:\n{page_content}",
        )
        combine_documents_chain = StuffDocumentsChain(
            llm_chain=llm_chain,
            document_variable_name="context",
            document_prompt=document_prompt,
            callbacks=callbacks,
        )

        return cls(
            combine_documents_chain=combine_documents_chain,
            callbacks=callbacks,
            **kwargs,
        )