RAG Agent Monorepo

Enterprise-grade AI Agent application with Next.js frontend and FastAPI backend, deployed on Azure.

🚀 Quick Start

Prerequisites

• Node.js 20+
• Python 3.11+
• Azure CLI
• Google Gemini API Key

Local Development

# Install dependencies
npm run install-all

# Start dev servers (Frontend + Backend)
npm run dev

• Frontend: http://localhost:3000
• Backend: http://localhost:8000

Environment Setup

Backend (apps/api/.env):

GEMINI_API_KEY=your_key_here
AZURE_SEARCH_ENDPOINT=https://search-rag-agent-13674.search.windows.net
AZURE_SEARCH_KEY=your_key_here
AZURE_SEARCH_INDEX_NAME=rag-index

Frontend (apps/web/.env.local):

NEXT_PUBLIC_API_URL=http://localhost:8000

📦 Project Structure

my-rag-agent/
├── apps/
│   ├── api/          # FastAPI backend with Gemini integration
│   └── web/          # Next.js 14 frontend (App Router)
├── packages/
│   └── ui/           # Shared UI components
└── .github/
    └── workflows/    # CI/CD pipelines

🛠 Tech Stack

• Frontend: Next.js 14, TypeScript, Tailwind CSS, Framer Motion
• Backend: Python 3.11, FastAPI, Google Gemini 1.5 Flash
• Vector DB: Azure AI Search (Free Tier)
• Deployment: Azure App Service
• CI/CD: GitHub Actions

🚢 Deployment

Automatic (via GitHub Actions)

Push to main branch triggers automatic deployment to Azure.

Manual

# Deploy backend
bash azure-deploy.sh

# Deploy frontend (configure Vercel or Azure Static Web Apps)
cd apps/web && npm run build

🔧 Available Scripts

• npm run dev - Start development servers
• npm run build - Build all packages
• npm run lint - Lint code
• npm run format - Format code with Prettier

📚 Features

• ✅ RAG Pipeline: Upload PDFs and query with AI-powered search
• ✅ Hybrid Search: Text + Vector search in Azure AI Search
• ✅ Tool Calling: Gemini automatically retrieves context
• ✅ Neo-Noir UI: Dark, cyberpunk-themed interface
• ✅ Production Ready: Deployed on Azure with CI/CD

🔐 Security

• Secrets managed via GitHub Secrets
• Environment variables for sensitive data
• No hardcoded API keys

📊 Monitoring

• Azure Application Insights (configured)
• Health check endpoint: /health
• Logs: az webapp log tail --name app-rag-agent-16515 --resource-group rg-rag-agent-prod

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'feat: add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📝 License

MIT License - see LICENSE file for details

🙋‍♂️ Support

• Issues: https://github.com/tejaIG/first500days/issues
• Discussions: https://github.com/tejaIG/first500days/discussions

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Built with ❤️ using Azure AI + Google Gemini