The process you've described for automating the addition of new sources using GitHub Actions and an AI-driven script is quite innovative. Here's a summary of what you accomplished:
-
Setup: You created a Python script that uses an AI model (likely through OpenRouter) to scrape, validate, and generate YAML files for new sources.
-
GitHub Actions Workflow:
- A scheduled workflow runs on the first day of each month.
- It checks out the repository, creates a new branch, sets up Python, and runs your script.
- The script generates new YAML files if there are any new sources to add.
- Any new YAML files are committed and a pull request is opened.
-
Validation:
- Once the PR lands, another workflow validates the new YAML files.
- If validation passes, the new sources are posted to your API, making them available in the live dashboard.
-
Results: The process now takes less than a minute of human time each month and has successfully added new sources with correct URLs and descriptions.
Next Steps: Claims and Proofs
For claims and proofs, you'll face more complex challenges:
- Data Complexity:
- Claims and
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