LLM-action

LLM Action

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A GitHub Action to interact with OpenAI Compatible LLM services. This action allows you to connect to any OpenAI-compatible API endpoint (including local or self-hosted services) and get responses that can be used in your workflow.

Features

• 🔌 Connect to any OpenAI-compatible API endpoint
• 🔐 Support for custom API keys
• 🔧 Configurable base URL for self-hosted services
• 🚫 Optional SSL certificate verification skip
• 🎯 System prompt support for context setting
• 📝 Output response available for subsequent actions
• 🎛️ Configurable temperature and max tokens
• 🐛 Debug mode with secure API key masking

Inputs

Outputs

Usage Examples

Basic Example

name: LLM Workflow
on: [push]

jobs:
  llm-task:
    runs-on: ubuntu-latest
    steps:
      - name: Call LLM
        id: llm
        uses: appleboy/LLM-action@v1
        with:
          api_key: ${{ secrets.OPENAI_API_KEY }}
          input_prompt: 'What is GitHub Actions?'

      - name: Use LLM Response
        run: |
          echo "LLM Response:"
          echo "${{ steps.llm.outputs.response }}"

With System Prompt

- name: Code Review with LLM
  id: review
  uses: appleboy/LLM-action@v1
  with:
    api_key: ${{ secrets.OPENAI_API_KEY }}
    model: 'gpt-4'
    system_prompt: 'You are a code reviewer. Provide constructive feedback on code quality, best practices, and potential issues.'
    input_prompt: |
      Review this code:
      ```python
      def add(a, b):
          return a + b
      ```
    temperature: '0.3'
    max_tokens: '2000'

- name: Post Review Comment
  run: |
    echo "${{ steps.review.outputs.response }}"

With Multiline System Prompt

- name: Advanced Code Review
  id: review
  uses: appleboy/LLM-action@v1
  with:
    api_key: ${{ secrets.OPENAI_API_KEY }}
    model: 'gpt-4'
    system_prompt: |
      You are an expert code reviewer with deep knowledge of software engineering best practices.

      Your responsibilities:
      - Identify potential bugs and security vulnerabilities
      - Suggest improvements for code quality and maintainability
      - Check for adherence to coding standards
      - Evaluate performance implications

      Provide constructive, actionable feedback in a professional tone.
    input_prompt: |
      Review the following pull request changes:
      ${{ github.event.pull_request.body }}
    temperature: '0.3'
    max_tokens: '2000'

Self-Hosted / Local LLM

- name: Call Local LLM
  id: local_llm
  uses: appleboy/LLM-action@v1
  with:
    base_url: 'http://localhost:8080/v1'
    api_key: 'your-local-api-key'
    model: 'llama2'
    skip_ssl_verify: 'true'
    input_prompt: 'Explain quantum computing in simple terms'

Using with Ollama

- name: Call Ollama
  id: ollama
  uses: appleboy/LLM-action@v1
  with:
    base_url: 'http://localhost:11434/v1'
    api_key: 'ollama'
    model: 'llama3'
    system_prompt: 'You are a helpful assistant'
    input_prompt: 'Write a haiku about programming'

Chain Multiple LLM Calls

- name: Generate Story
  id: generate
  uses: appleboy/LLM-action@v1
  with:
    api_key: ${{ secrets.OPENAI_API_KEY }}
    input_prompt: 'Write a short story about a robot'
    max_tokens: '500'

- name: Translate Story
  id: translate
  uses: appleboy/LLM-action@v1
  with:
    api_key: ${{ secrets.OPENAI_API_KEY }}
    system_prompt: 'You are a translator'
    input_prompt: |
      Translate the following text to Spanish:
      ${{ steps.generate.outputs.response }}

- name: Display Results
  run: |
    echo "Original Story:"
    echo "${{ steps.generate.outputs.response }}"
    echo ""
    echo "Translated Story:"
    echo "${{ steps.translate.outputs.response }}"

Debug Mode

Enable debug mode to troubleshoot issues and inspect all parameters:

- name: Call LLM with Debug
  id: llm_debug
  uses: appleboy/LLM-action@v1
  with:
    api_key: ${{ secrets.OPENAI_API_KEY }}
    model: 'gpt-4'
    system_prompt: 'You are a helpful assistant'
    input_prompt: 'Explain how GitHub Actions work'
    temperature: '0.8'
    max_tokens: '1500'
    debug: true  # Enable debug mode

Debug Output Example:

=== Debug Mode: All Parameters ===
main.Config{
    BaseURL: "https://api.openai.com/v1",
    APIKey: "sk-ab****xyz9",  // Masked for security
    Model: "gpt-4",
    SkipSSLVerify: false,
    SystemPrompt: "You are a helpful assistant",
    InputPrompt: "Explain how GitHub Actions work",
    Temperature: 0.8,
    MaxTokens: 1500,
    Debug: true
}
===================================
=== Debug Mode: Messages ===
[... message details ...]
============================

Security Note: When debug mode is enabled, the API key is automatically masked (only showing first 4 and last 4 characters) to prevent accidental exposure in logs.

Supported Services

This action works with any OpenAI-compatible API, including:

• OpenAI - https://api.openai.com/v1
• Azure OpenAI - https://{your-resource}.openai.azure.com/openai/deployments/{deployment-id}
• Ollama - http://localhost:11434/v1
• LocalAI - http://localhost:8080/v1
• LM Studio - http://localhost:1234/v1
• Jan - http://localhost:1337/v1
• vLLM - Your vLLM server endpoint
• Text Generation WebUI - Your WebUI endpoint
• Any other OpenAI-compatible service

Security Considerations

• Always use GitHub Secrets for API keys: ${{ secrets.YOUR_API_KEY }}
• Only use skip_ssl_verify: 'true' for trusted local/internal services
• Be careful with sensitive data in prompts, as they will be sent to the LLM service

License

MIT License - see LICENSE file for details

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.