A powerful AI-powered DevOps assistant that helps with infrastructure automation, CI/CD pipelines, containerization, and cloud deployments.

• 🤖 AI-Powered Assistant: Leverages multiple LLMs (Google Gemini, Azure OpenAI, OpenAI, Anthropic) for intelligent DevOps guidance
• 🛠️ Tool Integration: Extensible tool system for executing system commands
• 💬 Interactive Chat Interface: Command-line chat interface with conversation history
• 🎨 Rich Terminal Output: Beautiful markdown rendering with ANSI colors and formatting
• 🔧 DevOps Expertise: Specialized in infrastructure automation and deployment strategies
• 📝 TypeScript: Fully typed codebase for better development experience
• 🎯 Modular Architecture: Clean separation of concerns with pluggable providers and tools

• Node.js 24+ (ES2024 support required)
• At least one AI provider:
  • Google Gemini API key, or
  • Azure OpenAI service endpoint and API key, or
  • OpenAI API key, or
  • Anthropic API key
• TypeScript knowledge (for development)

1. Clone the repository:

   git clone <repository-url>
   cd devops-agent

2. Install dependencies:

   npm install

   This will install all required dependencies including:

   • AI provider SDKs (Google Gemini, OpenAI, Azure OpenAI, Anthropic)
   • Markdown rendering libraries (marked, marked-terminal)
   • TypeScript and development tools

3. Configure the application:

   cp config.yaml.example config.yaml

   Edit config.yaml and configure your preferred AI provider.

Run the application in development mode with auto-reload:

npm run dev

Build and run the application:

npm run build
npm start

Once the application is running, you can use the following commands:

• help - Show available commands
• ask <question> - Ask the AI agent a specific question
• tools - List available tools
• clear - Clear conversation history
• exit - Exit the application

> ask How do I create a Dockerfile for a Node.js application?
> What are the best practices for Kubernetes deployments?
> tools
> clear
> exit

The DevOps AI Agent features rich terminal output with markdown rendering:

• Headings: Color-coded headings with different levels (H1-H6)
• Code Blocks: Syntax-highlighted code blocks with background colors
• Inline Code: Highlighted inline code with cyan background
• Lists: Properly formatted bullet points and numbered lists
• Links: Clickable links with underlines and URLs
• Emphasis: Bold text and italic text formatting
• Tables: Beautiful table formatting with borders

The markdown renderer uses the marked-terminal library to convert AI responses into visually appealing terminal output with ANSI escape codes for colors and formatting.

Before using the DevOps AI Agent, you'll need to obtain API keys from your chosen provider(s):

1. Visit the Google AI Studio
2. Sign in with your Google account
3. Click "Create API Key"
4. Copy your API key

1. Visit OpenAI's API platform
2. Sign in or create an account
3. Navigate to API Keys
4. Click "Create new secret key"
5. Copy your API key

1. Create an Azure OpenAI resource in the Azure Portal
2. Deploy a model (e.g., GPT-4)
3. Get your endpoint URL and API key from the resource overview
4. Note your deployment name

1. Visit Anthropic Console
2. Sign in or create an account
3. Navigate to API Keys
4. Click "Create Key"
5. Copy your API key

The application uses a YAML configuration file (config.yaml) with the following structure:

default_provider: "gemini"  # Your preferred provider

providers:
  gemini:
    enabled: true
    api_key: "your-api-key-here"
    model: "your-model"
    temperature: 0.7  # Optional, controls randomness (0.0 to 1.0)
    max_tokens: 4096  # Optional, maximum tokens in response

  azure_openai:
    enabled: false
    api_key: "your-azure-api-key"
    endpoint: "https://your-resource.openai.azure.com"
    deployment_name: "your-deployment"
    api_version: "2024-02-15-preview"
    temperature: 0.7  # Optional, controls randomness (0.0 to 2.0)
    max_tokens: 4096  # Optional, maximum tokens in response

  openai:
    enabled: false
    api_key: "your-openai-api-key"
    model: "gpt-4o"
    organization: "your-org-id"  # Optional
    base_url: "https://api.openai.com/v1"  # Optional, for custom endpoints
    temperature: 0.7  # Optional, controls randomness (0.0 to 2.0)
    max_tokens: 4096  # Optional, maximum tokens in response

  anthropic:
    enabled: false
    api_key: "your-anthropic-api-key"
    model: "claude-3-5-sonnet-20241022"
    base_url: "https://api.anthropic.com"  # Optional, for custom endpoints
    temperature: 0.7  # Optional, controls randomness (0.0 to 1.0)
    max_tokens: 4096  # Optional, maximum tokens in response

You can enable multiple providers and specify which one to use as the default.

See the documentation on providers for more information.

• temperature: Controls the randomness of responses
  • Gemini/Anthropic: 0.0 (deterministic) to 1.0 (creative)
  • OpenAI/Azure OpenAI: 0.0 (deterministic) to 2.0 (very creative)
• max_tokens: Maximum number of tokens in the response (default: 4096)

• npm run typecheck - Type checking without compilation
• npm run build - Compile TypeScript to JavaScript
• npm run dev - Development mode with auto-reload
• npm run start - Run the compiled application
• npm run check - Run Biome linter and formatter checks
• npm run check:fix - Auto-fix linting and formatting issues
• npm run format - Format code with Biome
• npm run format:write - Format and write changes
• npm run lint - Run Biome linter

• API Keys: Store API keys securely in config.yaml (excluded from version control)
• Command Execution: The execute command tool runs with the same permissions as the Node.js process
• Input Validation: All tool parameters are validated according to their schemas

This project is licensed under the AGPL-3.0-only License. See the LICENSE file for details.

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Run tests and linting: npm run check
5. Submit a pull request

"Provider configuration is missing"

• Ensure config.yaml exists and contains valid provider configuration
• Check that your API key is correct and has proper permissions

"API key is required"

• Verify your API key in config.yaml
• Make sure the API key has access to the provider

Tool execution failures

• Check that the system has the necessary permissions for command execution
• Verify that required system tools are installed

Markdown rendering issues

• If terminal output appears garbled, ensure your terminal supports ANSI escape codes
• For best results, use a modern terminal emulator (VS Code integrated terminal, iTerm2, Windows Terminal)
• Some older terminals may not support all formatting features