Testing and Validation

Testing and Validation

In the source

self_test(results) checks deterministic outputs for the offline examples: greeting, factorial, normal/conditional edges, TypedDict routing, Pydantic errors, input/output/private schemas, reducers, message updates, and HR/IT subgraphs.

python .\langgraph_example_multi_agents.py --self-test

The expected summary is SELF-TEST PASSED: 16 offline examples, if the dependencies are installed and all tests pass. Optional OpenAI calls are not part of the self-test.

Verification performed for the downloadable package

• Original archive inspected and all five files accounted for.
• Python module syntax, notebook JSON structure, and all notebook code-cell syntax checked.
• Internal Wiki link references and Mermaid source blocks validated structurally.
• ZIP archives checked for corruption and accidental source omission.

Not performed: Full LangGraph runtime execution, model calls or notebook Run All in an environment containing all declared dependencies. These require installing dependencies; please run --self-test locally.

Recommended additional engineering tests

Add unit tests for every example_* result, CLI return codes, optional LLM credential errors, and integration tests for both subgraph mapping patterns. Pin tested dependencies for reproducibility when publishing a release.