test_saving_loading_round_trip() — langchain Function Reference

Architecture documentation for the test_saving_loading_round_trip() function in test_loading.py from the langchain codebase.

Function python CoreAbstractions Serialization

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CoreAbstractions→ Serialization→ test_saving_loading_round_trip() — langchain Function Reference

Dependency Diagram

graph TD
  d79c29fd_79ea_0cdb_7a5a_67643787c7b0["test_saving_loading_round_trip()"]
  eea05055_0cc3_c5ac_867f_b44ce74a7c7b["test_loading.py"]
  d79c29fd_79ea_0cdb_7a5a_67643787c7b0 -->|defined in| eea05055_0cc3_c5ac_867f_b44ce74a7c7b
  style d79c29fd_79ea_0cdb_7a5a_67643787c7b0 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/core/tests/unit_tests/prompts/test_loading.py lines 63–88

def test_saving_loading_round_trip(tmp_path: Path) -> None:
    """Test equality when saving and loading a prompt."""
    simple_prompt = PromptTemplate(
        input_variables=["adjective", "content"],
        template="Tell me a {adjective} joke about {content}.",
    )
    simple_prompt.save(file_path=tmp_path / "prompt.yaml")
    loaded_prompt = load_prompt(tmp_path / "prompt.yaml")
    assert loaded_prompt == simple_prompt

    few_shot_prompt = FewShotPromptTemplate(
        input_variables=["adjective"],
        prefix="Write antonyms for the following words.",
        example_prompt=PromptTemplate(
            input_variables=["input", "output"],
            template="Input: {input}\nOutput: {output}",
        ),
        examples=[
            {"input": "happy", "output": "sad"},
            {"input": "tall", "output": "short"},
        ],
        suffix="Input: {adjective}\nOutput:",
    )
    few_shot_prompt.save(file_path=tmp_path / "few_shot.yaml")
    loaded_prompt = load_prompt(tmp_path / "few_shot.yaml")
    assert loaded_prompt == few_shot_prompt