Working toward a shared understanding of the MVP for structured RAG.

This is an in-progress project aiming at a Pythonic translation of TypeAgent/ts/packages/knowPro and a few related packages to Python. (Pythonic because it uses Python conventions and types as appropriate.)

• Python class names correspond 1:1 to TS interface or type names.
• Field and method names are converted from camelCase to python_case.
• I-named interfaces become Protocol classes; other interfaces and structured types become dataclasses.
• Union types remain union types;
• but unions of string literals become Literal types.
• Not all of the TS class hierarchy is translated literally.

Tested only on Ubuntu 22 under WSL. Presumably works on most UNIXoids.

• Install Python 3.12 or higher (get it from (python.org)[python.org] or run sudo apt install python3.12)
• Set your environment to contain the necessary Azure or OpenAI keys.
• Run make all
• You should now have a wheel file under dist/
• TODO: Upload that wheel to PyPI
• To clean up, run make clean

• Set your environment to contain the necessary Azure or OpenAI keys.
• Run unit tests: make test; this also collects coverage data.
• Review coverage with coverage report etc.
• Interactively testing queries: make demo
• Comparing to a validated set of questions and expected answers:
  • Obtain or construct a JSON file of q/a pairs and install in testdata
  • Run make compare (takes about 5-10 seconds per q/a pair)

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.