Yusuf Ali
864958ee45
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51 lines
1.5 KiB
Markdown
51 lines
1.5 KiB
Markdown
# Issue Embedder Action
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Sends issue comment text to an embeddings API so issue discussions can be stored in a vector lake. Intended to run from an `issue_comment` workflow and pick up the latest comment text for embedding.
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## How it works
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- Reads issue comments via the GitHub API.
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- Builds a request payload using the first comment for `embed_text` and the latest comment for `store_text`.
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- POSTs the payload to the configured API URL with optional token auth.
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## Inputs
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- `api_url` (optional): API endpoint. Default: `http://agents-api.servc-agents:3000`
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- `api_token` (optional): API token for authentication.
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- `route` (optional): API route. Default: `agent-lake`
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- `method` (optional): API method. Default: `embeddings_insert`
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- `debug` (optional): Enable debug logging. Default: `false`
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## Example workflow
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```yaml
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name: Send Tasks to Agent
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on:
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issue_comment:
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types:
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- created
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- edited
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jobs:
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agent-embed-issue:
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if: contains(github.event.comment.body, 'solution:')
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runs-on: ubuntu-latest
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permissions:
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contents: read
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issues: read
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steps:
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- name: Send task to embedding agent
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uses: https://git.yusufali.ca/actions/embed-issues@main
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env:
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GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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with:
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api_token: ${{ secrets.AGENT_TOKEN }}
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api_url: ${{ secrets.AGENT_API_URL }}
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debug: false
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```
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## Notes
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- `GITHUB_TOKEN` is used to read issue comments.
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- `AGENT_API_URL` and `AGENT_TOKEN` are expected to be configured as repository secrets.
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