test_simplea() — langchain Function Reference

Architecture documentation for the test_simplea() function in test_conversation_retrieval.py from the langchain codebase.

Function python LangChainCore Runnables

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LangChainCore→ Runnables→ test_simplea() — langchain Function Reference

Dependency Diagram

graph TD
  57d5cf9d_b5d3_cb1d_6e72_a3a6d7aa69ec["test_simplea()"]
  995a7073_bf4f_3e52_1d5f_85841e01cccc["test_conversation_retrieval.py"]
  57d5cf9d_b5d3_cb1d_6e72_a3a6d7aa69ec -->|defined in| 995a7073_bf4f_3e52_1d5f_85841e01cccc
  style 57d5cf9d_b5d3_cb1d_6e72_a3a6d7aa69ec fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/langchain/tests/unit_tests/chains/test_conversation_retrieval.py lines 13–35

async def test_simplea() -> None:
    fixed_resp = "I don't know"
    answer = "I know the answer!"
    llm = FakeListLLM(responses=[answer])
    retriever = SequentialRetriever(sequential_responses=[[]])
    memory = ConversationBufferMemory(
        k=1,
        output_key="answer",
        memory_key="chat_history",
        return_messages=True,
    )
    qa_chain = ConversationalRetrievalChain.from_llm(
        llm=llm,
        memory=memory,
        retriever=retriever,
        return_source_documents=True,
        rephrase_question=False,
        response_if_no_docs_found=fixed_resp,
        verbose=True,
    )
    got = await qa_chain.acall("What is the answer?")
    assert got["chat_history"][1].content == fixed_resp
    assert got["answer"] == fixed_resp