# 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 body and comments via the GitHub API.
- Builds a request payload using the issue body for `embed_text` and the latest comment for `store_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:3000`
- `api_token` (optional): API token for authentication.
- `route` (optional): API route. Default: `agent-lake`
- `method` (optional): API method. Default: `embeddings_insert`
- `debug` (optional): Enable debug logging. Default: `false`

## Example workflow

```yaml
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_TOKEN` is used to read issue comments.
- `AGENT_API_URL` and `AGENT_TOKEN` are expected to be configured as repository secrets.