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INSTALL_GUIDE.md

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Devr.AI Installation Guide

Follow this guide to set up Devr.AI's development environment on your local machine. For Setup guide video tutorial go to Devr Setup Guide

Prerequisites

Quick Start

  1. Clone the repository
git clone https://github.com/AOSSIE-Org/Devr.AI.git
cd Devr.AI
  1. Install Poetry (Python package manager)
# Linux / MacOS / WSL
curl -sSL https://install.python-poetry.org | python3 -

# Windows (PowerShell)
(Invoke-WebRequest -Uri https://install.python-poetry.org -UseBasicParsing).Content | py -

# Verify installation
poetry --version  # Should show v2.0.0 or above
  1. Install Python dependencies
poetry env use python3.10
poetry lock 
poetry install --with dev
  1. Activate the virtual environment
# Linux / Mac / WSL
eval $(poetry env activate)

# Windows (PowerShell)
Invoke-Expression (poetry env activate)
  1. Set up environment variables
# Copy the example environment file
cp env.example .env

# Edit .env with your API keys and configuration
nano .env  # or use your preferred editor
  1. Set up Docker container
cd backend
docker-compose up -d # Start weaviate, falkordb, rabbitmq
  1. Start Docker containers
Go to docker dekstop and start the containers
  1. Start the backend server
cd backend
poetry run python main.py # Terminal 1
poetry run python start_github_mcp_server.py # Terminal 2 (Start MCP server)
flask --app api/index.py run --debug --port 5000 # Terminal 3 (Start graphDB)
  1. Start the frontend (in a new terminal)
cd frontend
npm install
npm run dev

Environment Variables

Create a .env file in the project root with the following variables:

Required Variables

# AI Services
GEMINI_API_KEY=your_gemini_api_key_here
TAVILY_API_KEY=your_tavily_api_key_here

# Platform Integrations
DISCORD_BOT_TOKEN=your_discord_bot_token_here
GITHUB_TOKEN=your_github_token_here

# Database
SUPABASE_URL=your_supabase_url_here
SUPABASE_KEY=your_supabase_anon_key_here

# Backend Configuration
BACKEND_URL=http://localhost:8000

Optional Variables

# LangSmith Tracing (for development)
LANGSMITH_TRACING=false
LANGSMITH_API_KEY=your_langsmith_api_key_here
LANGSMITH_PROJECT=DevR_AI

# RabbitMQ (uses default if not set)
RABBITMQ_URL=amqp://localhost:5672/

# Agent Configuration
DEVREL_AGENT_MODEL=gemini-2.5-flash
GITHUB_AGENT_MODEL=gemini-2.5-flash
CLASSIFICATION_AGENT_MODEL=gemini-2.0-flash
AGENT_TIMEOUT=30
MAX_RETRIES=3

API Key Setup

1. Google Gemini API

  1. Go to Google AI Studio
  2. Create a new API key
  3. Add it to your .env file as GEMINI_API_KEY

2. Tavily Search API

  1. Go to Tavily
  2. Sign up and get your API key
  3. Add it to your .env file as TAVILY_API_KEY

3. Discord Bot Token

  1. Go to Discord Developer Portal
  2. Create a new application
  3. Go to "Bot" section and create a bot
  4. Copy the token and add it to your .env file as DISCORD_BOT_TOKEN
  5. Enable required intents: Message Content Intent, Server Members Intent

4. GitHub Token

  1. Go to GitHub Settings > Developer settings > Personal access tokens
  2. Generate a new token with repo and user scopes
  3. Add it to your .env file as GITHUB_TOKEN

5. Supabase Setup

  1. Go to Supabase and create a new project
  2. Go to Settings > API
  3. Copy the URL and anon key
  4. Add them to your .env file as SUPABASE_URL and SUPABASE_KEY

Database Setup

Weaviate Vector Database

Weaviate is used for semantic search and embeddings storage. It runs in Docker:

cd backend
docker-compose up -d weaviate

The database will be available at http://localhost:8080

Supabase Database

Supabase provides the PostgreSQL database for user data and authentication. The connection is configured via environment variables.

Current Features

Discord Integration

  • Intelligent Message Processing: AI-powered responses to community questions
  • GitHub Account Verification: Link Discord accounts to GitHub profiles
  • Conversation Memory: Persistent context across sessions
  • Commands:
    • !verify_github - Link your GitHub account
    • !verification_status - Check account linking status
    • !reset - Clear conversation memory
    • !help_devrel - Show available commands

LangGraph Agent System

  • DevRel Agent: Primary conversational agent for community support
  • ReAct Workflow: Think → Act → Observe pattern for intelligent responses
  • Tool Integration: Web search, FAQ lookup, GitHub operations
  • Conversation Summarization: Automatic memory management

AI Services

  • Google Gemini: Primary LLM for reasoning and response generation
  • Tavily Search: Real-time web search for current information
  • Text Embeddings: Semantic search capabilities

Data Storage

  • Supabase: User profiles, authentication, conversation metadata
  • Weaviate: Vector embeddings and semantic search
  • Agent Memory: Persistent conversation context

Development

Running Tests

poetry run pytest

Code Formatting

poetry run black .
poetry run isort .

Linting

poetry run flake8

Frontend Development

cd frontend
npm run dev  # Start development server
npm run build  # Build for production
npm run lint  # Run ESLint

Troubleshooting

Common Issues

  1. Poetry environment not activated

    poetry shell

  2. Weaviate connection failed

    # Check if Docker is running
docker ps

# Restart Weaviate
docker-compose down
docker-compose up -d weaviate

  3. Missing environment variables

    • Ensure all required variables are set in .env
    • Check that the file is in the project root

  4. Port conflicts

    • Backend runs on port 8000
    • Frontend runs on port 5173 (Vite default)
    • Weaviate runs on port 8080

Logs

  • Backend logs are displayed in the terminal where you run python main.py
  • Check Docker logs for Weaviate: docker-compose logs weaviate

Project Structure

Devr.AI/
├── backend/                 # FastAPI backend
│   ├── app/
│   │   ├── agents/         # LangGraph agents
│   │   ├── api/           # API routes
│   │   ├── core/          # Configuration and core logic
│   │   ├── database/      # Database connections
│   │   ├── models/        # Data models
│   │   └── services/      # Business logic
│   ├── integrations/      # Platform integrations
│   │   ├── discord/       # Discord bot
│   │   ├── github/        # GitHub integration
│   │   └── slack/         # Slack integration (planned)
│   └── main.py           # Application entry point
├── frontend/              # React frontend
├── docs/                  # Documentation
└── tests/                 # Test files

Next Steps

  1. Set up your Discord server and invite the bot
  2. Configure GitHub OAuth for user verification
  3. Test the bot with basic commands
  4. Explore the codebase to understand the architecture
  5. Contribute by implementing new features or fixing bugs

For more information, refer to the main README.md file.