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Issue Embedder Action
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.
How it works
- Reads issue comments via the GitHub API.
- Builds a request payload using the first comment for
embed_textand the latest comment forstore_text. - POSTs the payload to the configured API URL with optional token auth.
Inputs
api_url(optional): API endpoint. Default:http://agents-api.servc-agents:3000api_token(optional): API token for authentication.route(optional): API route. Default:agent-lakemethod(optional): API method. Default:embeddings_insertdebug(optional): Enable debug logging. Default:false
Example workflow
name: Send Tasks to Agent
on:
issue_comment:
types:
- created
- edited
jobs:
agent-embed-issue:
if: contains(github.event.comment.body, 'solution:')
runs-on: ubuntu-latest
permissions:
contents: read
issues: read
steps:
- name: Send task to embedding agent
uses: https://git.yusufali.ca/actions/embed-issues@main
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
with:
api_token: ${{ secrets.AGENT_TOKEN }}
api_url: ${{ secrets.AGENT_API_URL }}
debug: false
Notes
GITHUB_TOKENis used to read issue comments.AGENT_API_URLandAGENT_TOKENare expected to be configured as repository secrets.