test_configurable_fields_example() — langchain Function Reference

Architecture documentation for the test_configurable_fields_example() function in test_runnable.py from the langchain codebase.

Function python LangChainCore Runnables calls 1

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LangChainCore→ Runnables→ test_configurable_fields_example() — langchain Function Reference

Dependency Diagram

graph TD
  2f48bb67_be06_63b0_47d4_f590a7b778f8["test_configurable_fields_example()"]
  26df6ad8_0189_51d0_c3c1_6c3248893ff5["test_runnable.py"]
  2f48bb67_be06_63b0_47d4_f590a7b778f8 -->|defined in| 26df6ad8_0189_51d0_c3c1_6c3248893ff5
  fb618d44_c03b_ea8b_385b_2278dfb173d4["invoke()"]
  2f48bb67_be06_63b0_47d4_f590a7b778f8 -->|calls| fb618d44_c03b_ea8b_385b_2278dfb173d4
  style 2f48bb67_be06_63b0_47d4_f590a7b778f8 fill:#6366f1,stroke:#818cf8,color:#fff

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Source Code

libs/core/tests/unit_tests/runnables/test_runnable.py lines 937–1000

def test_configurable_fields_example(snapshot: SnapshotAssertion) -> None:
    fake_chat = FakeListChatModel(responses=["b"]).configurable_fields(
        responses=ConfigurableFieldMultiOption(
            id="chat_responses",
            name="Chat Responses",
            options={
                "hello": "A good morning to you!",
                "bye": "See you later!",
                "helpful": "How can I help you?",
            },
            default=["hello", "bye"],
        )
    )
    fake_llm = (
        FakeListLLM(responses=["a"])
        .configurable_fields(
            responses=ConfigurableField(
                id="llm_responses",
                name="LLM Responses",
                description="A list of fake responses for this LLM",
            )
        )
        .configurable_alternatives(
            ConfigurableField(id="llm", name="LLM"),
            chat=fake_chat | StrOutputParser(),
        )
    )

    prompt = PromptTemplate.from_template("Hello, {name}!").configurable_fields(
        template=ConfigurableFieldSingleOption(
            id="prompt_template",
            name="Prompt Template",
            description="The prompt template for this chain",
            options={
                "hello": "Hello, {name}!",
                "good_morning": "A very good morning to you, {name}!",
            },
            default="hello",
        )
    )

    # deduplication of configurable fields
    chain_configurable = prompt | fake_llm | (lambda x: {"name": x}) | prompt | fake_llm

    assert chain_configurable.invoke({"name": "John"}) == "a"

    if PYDANTIC_VERSION_AT_LEAST_29:
        assert _normalize_schema(
            chain_configurable.get_config_jsonschema()
        ) == snapshot(name="schema7")

    assert (
        chain_configurable.with_config(configurable={"llm": "chat"}).invoke(
            {"name": "John"}
        )
        == "A good morning to you!"
    )

    assert (
        chain_configurable.with_config(
            configurable={"llm": "chat", "chat_responses": ["helpful"]}
        ).invoke({"name": "John"})
        == "How can I help you?"
    )