GitHub Action Video Issue Analyzer

This GitHub Action runs all video assets in an issue body through a LLM model to analyze the content. The default behavior is to summarize and extract task items but this can be customized through the prompt input.

Inputs

github_token: GitHub token with models: read permission at least. (required)
instructions: Custom prompt to use for the LLM model. If not provided, a default prompt will be used.
github_issue: The issue number to analyze. Typically this variable is inferred from the event context.
debug: Enable debug logging.

Usage

Add the following to your step in your workflow file. It will launch a whisper service in a container that can be used by genaiscript.

    runs-on: ubuntu-latest
    services:
      whisper:
        image: onerahmet/openai-whisper-asr-webservice:latest
        env:
          ASR_MODEL: base
          ASR_ENGINE: openai_whisper
        ports:
          - 9000:9000
        options: >-
          --health-cmd "curl -f http://localhost:9000/docs || exit 1"
          --health-interval 10s
          --health-timeout 5s
          --health-retries 5
          --health-start-period 20s
    steps:
      - uses: actions/checkout@v4
      - uses: pelikhan/action-genai-video-issue-analyzer@v0
        with:
          github_token: ${{ secrets.GITHUB_TOKEN }}

Example

Save the following in .github/workflows/genai-video-issue-analyzer.yml file:

name: genai video issue analyzer
on:
  issues:
    types: [opened, edited]
permissions:
    contents: read
    issues: write
    models: read
concurrency:
    group: ${{ github.workflow }}-${{ github.event.issue.number }}
    cancel-in-progress: true
jobs:
  genai-video-analyze:
    runs-on: ubuntu-latest
    services:
      whisper:
        image: onerahmet/openai-whisper-asr-webservice:latest
        env:
          ASR_MODEL: base
          ASR_ENGINE: openai_whisper
        ports:
          - 9000:9000
        options: >-
          --health-cmd "curl -f http://localhost:9000/docs || exit 1"
          --health-interval 10s
          --health-timeout 5s
          --health-retries 5
          --health-start-period 20s
    steps:
      - uses: actions/checkout@v4
      - uses: pelikhan/action-genai-video-issue-analyzer@v0
        with:
          github_token: ${{ secrets.GITHUB_TOKEN }}

Development

This action was automatically generated by GenAIScript from the script metadata. We recommend updating the script metadata instead of editing the action files directly.

the action inputs are inferred from the script parameters
the action outputs are inferred from the script output schema
the action description is the script title
the readme description is the script description
the action branding is the script branding

To regenerate the action files (action.yml), run:

npm run configure

To lint script files, run:

npm run lint

To typecheck the scripts, run:

npm run typecheck

To build the Docker image locally, run:

npm run docker:build

To run the action locally in Docker (build it first), use:

npm run docker:start

To run the action using act, first install the act CLI:

npm run act:install

Then, you can run the action with:

npm run act

Upgrade

The GenAIScript version is pinned in the package.json file. To upgrade it, run: