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https://github.com/pelikhan/action-genai-video-issue-analyzer

GitHub Action that analyzes attached videos and generate action bullet points.
https://github.com/pelikhan/action-genai-video-issue-analyzer

action automation genai genaiscript

Last synced: 6 months ago
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GitHub Action that analyzes attached videos and generate action bullet points.

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README 

          
# 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.



```yaml

    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)



```yaml

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)



```yaml

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)



```yaml

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](https://microsoft.github.io/genaiscript/reference/github-actions) 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:



```bash

npm run configure

```



To lint script files, run:



```bash

npm run lint

```



To typecheck the scripts, run:

```bash

npm run typecheck

```



To build the Docker image locally, run:

```bash

npm run docker:build

```



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

```bash

npm run docker:start

```



## Upgrade



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



```bash

npm run upgrade

```



## Release



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



```bash

npm run release

```