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CONTRIBUTING.md

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Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Developer setup

You can open this repo in GitHub Codespace/Docker to get the build environment needed.

Manual setup

yarn install --frozen-lockfile --prefer-offline
  • Start the Run - sample Debugger to launch the sample project in debugging mode

Dependencies

  • run yarn install to refresh the lock file
  • run yarn gen:licenses to refresh the 3rd party licenses

Docs

Run docs to launch the documentation site.

yarn docs

GitHub Pages are automatically updated on new release; or thourh manual trigger at https://github.com/microsoft/genaiscript/actions/workflows/docs.yml .

Slides

All files slides/*slides.md will be compiled and deployed on build.

  • run slides to launch the slide show (add the file name or it will default to slides.md)
yarn slides [slides file name]

Learn more about Slidev on documentations. For diagrams, leverage mermaid or use draw.io, tldraw.

Packaging

To compile and package the Visual Studio Code extension, run the package script.

yarn package

You will find the built package files, genaiscript.vsix and genaiscript.insiders.vsix, in the packages/vscode folder.

Release

Run the release script.

yarn release

Documentation basics

Start local server

yarn docs

Local AI

If you are lacking a OpenAI API token, you can use LocalAI to simulate OpenAI access.

  • Create a new Codespace and make sure to create a larger image,
  • launch localai to download and start the localai docker image.
yarn run localai

# OPENAI_API_KEY=... not needed
OPENAI_API_BASE=http://localhost:8080/v1
  • start the debugger and voila!