GitHub Action Video Issue Analyzer

This GitHub Action runs all video assets in an issue body through a LLM model to analyze the content, or can analyze a direct video URL when triggered via workflow_dispatch. The default behavior is to summarize and extract task items but this can be customized through the instructions input.

The action outputs the analysis results to the GitHub Step Summary for easy viewing in the Actions tab.

Inputs

name	description	required	default
instructions	Custom prompting instructions for each video.	false	Analyze the video and provide a summary of its content. Extract list of followup subissues if any. The transcript is your primary source of text information, ignore text in images.
debug	Enable debug logging (https://microsoft.github.io/genaiscript/reference/scripts/logging/).	false
model_alias	A YAML-like list of model aliases and model id: translation: github:openai/gpt-4o	false
openai_api_key	OpenAI API key	false
openai_api_base	OpenAI API base URL	false
azure_openai_api_endpoint	Azure OpenAI endpoint. In the Azure Portal, open your Azure OpenAI resource, Keys and Endpoints, copy Endpoint.	false
azure_openai_api_key	Azure OpenAI API key. **You do NOT need this if you are using Microsoft Entra ID.	false
azure_openai_subscription_id	Azure OpenAI subscription ID to list available deployments (Microsoft Entra only).	false
azure_openai_api_version	Azure OpenAI API version.	false
azure_openai_api_credentials	Azure OpenAI API credentials type. Leave as 'default' unless you have a special Azure setup.	false
azure_ai_inference_api_key	Azure AI Inference key	false
azure_ai_inference_api_endpoint	Azure Serverless OpenAI endpoint	false
azure_ai_inference_api_version	Azure Serverless OpenAI API version	false
azure_ai_inference_api_credentials	Azure Serverless OpenAI API credentials type	false
github_token	GitHub token with models: read permission at least (https://microsoft.github.io/genaiscript/reference/github-actions/#github-models-permissions).	false
video_url	Direct video URL to analyze (alternative to extracting from issue body). Used when triggered via workflow_dispatch.	false

Outputs

name	description

| text | The generated text output. |

Note: The action also outputs the analysis results to the GitHub Step Summary ($GITHUB_STEP_SUMMARY) for easy viewing in the Actions tab.

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:

For Issue-based Analysis (automatic trigger)

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: actions/cache@v4
        with:
          path: .genaiscript/cache/**
          key: genaiscript-${{ github.run_id }}
          restore-keys: |
            genaiscript-
      - uses: pelikhan/action-genai-video-issue-analyzer@v0 # update to the major version you want to use
        with:
          github_token: ${{ secrets.GITHUB_TOKEN }}

For Direct Video URL Analysis (manual trigger)

name: genai video issue analyzer
on:
  workflow_dispatch:
    inputs:
      video_url:
        description: 'Direct video URL to analyze'
        required: true
        type: string
      instructions:
        description: 'Custom prompting instructions for the video'
        required: false
        default: 'Analyze the video and provide a summary of its content. Extract list of followup subissues if any. The transcript is your primary source of text information, ignore text in images.'
        type: string
permissions:
    contents: read
    models: read
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: actions/cache@v4
        with:
          path: .genaiscript/cache/**
          key: genaiscript-${{ github.run_id }}
          restore-keys: |
            genaiscript-
      - uses: pelikhan/action-genai-video-issue-analyzer@v0 # update to the major version you want to use
        with:
          github_token: ${{ secrets.GITHUB_TOKEN }}
          video_url: ${{ github.event.inputs.video_url }}
          instructions: ${{ github.event.inputs.instructions }}

Combined Workflow (both triggers)

name: genai video issue analyzer
on:
  issues:
    types: [opened, edited]
  workflow_dispatch:
    inputs:
      video_url:
        description: 'Direct video URL to analyze'
        required: true
        type: string
      instructions:
        description: 'Custom prompting instructions for the video'
        required: false
        default: 'Analyze the video and provide a summary of its content. Extract list of followup subissues if any. The transcript is your primary source of text information, ignore text in images.'
        type: string
permissions:
    contents: read
    issues: write
    models: read
concurrency:
    group: ${{ github.workflow }}-${{ github.ref }}
    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: actions/cache@v4
        with:
          path: .genaiscript/cache/**
          key: genaiscript-${{ github.run_id }}
          restore-keys: |
            genaiscript-
      - uses: pelikhan/action-genai-video-issue-analyzer@v0 # update to the major version you want to use
        with:
          github_token: ${{ secrets.GITHUB_TOKEN }}
          video_url: ${{ github.event.inputs.video_url }}
          instructions: ${{ github.event.inputs.instructions }}

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 description
• 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

Upgrade

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

npm run upgrade

Release

To release a new version of this action, run the release script on a clean working directory.

npm run release