FlexiRAG Development Project by Aayush PaigwarFlexiRAG Development Project by Aayush Paigwar

FlexiRAG Development Project

Aayush Paigwar

Completed work

AI Chatbot Developer

AI Developer

Web Developer

FastAPI

React

Supabase

Computer Software

FlexiRAG - Flexible Retrieval Augmented Generation

FlexiRAG - Flexible Retrieval Augmented Generation

FlexiRAG is a powerful document RAG (Retrieval Augmented Generation) platform that allows you to upload, deploy, and query documents through an intuitive interface and API.

🚀 Features

Document Management: Upload and manage various document types

RAG Deployments: Deploy documents as queryable API endpoints

Chat Interface: Interact with your documents through a conversational UI

API Access: Programmatically access your deployed documents

Gemini Integration: Leverage Google's Gemini AI for document understanding

🛠️ Tech Stack

This project is built with modern web technologies:

Frontend:

React with TypeScript

Vite for fast development and building

Tailwind CSS for styling

shadcn/ui for UI components

React Router for navigation

Backend:

FastAPI (Python)

Supabase for authentication and storage

Google Gemini AI for document processing

📋 Prerequisites

Node.js & npm (or bun)

Python 3.8+ (for backend development)

Gemini API key (for document deployments)

🚦 Getting Started

Frontend Setup

Clone the repository:

git clone <YOUR_REPOSITORY_URL>
cd flexi-rag-nest

Install dependencies:

npm install

Start the development server:

npm run dev

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

Backend Setup

Install Python dependencies:

pip install -r requirements.txt

Set up environment variables in .env:

GEMINI_API_KEY=your_key
SUPABASE_URL=your_url
SUPABASE_KEY=your_key

Run the API:

uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload

📚 Documentation

The API documentation is available at:

Swagger UI: /docs

ReDoc: /redoc

🔄 Workflow

Create an account or sign in

Upload documents to your library

Deploy documents as API endpoints

Query documents through the chat interface or API

Manage deployments and API keys in the settings

🔑 API Usage

Once you've deployed a document, you can query it using the provided endpoint:

POST https://flexirag-cqdrbdcvc0gfhxbg.canadacentral-01.azurewebsites.net//api/v1/deployed/{document_id}
Content-Type: application/json

{
  "query": "Your question about the document",
  "api_key": "your_gemini_api_key" // Optional, if configured in settings
}

🧩 Project Structure

flexi-rag-nest/
├── src/
│   ├── components/     # UI components
│   ├── pages/          # Application pages
│   ├── services/       # API services
│   ├── hooks/          # Custom React hooks
│   ├── lib/            # Utility functions
│   └── App.tsx         # Main application component
├── public/             # Static assets
└── ...                 # Configuration files

🤝 Contributing

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

📄 License

This project is licensed under the MIT License.

🔗 Links

Deployed Link

Built with ❤️ using modern web technologies

Like this project

Completed work

Posted Sep 12, 2025

Developed FlexiRAG, a document RAG platform with API and chat interface.

Likes

Views