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DocQ.ai - RAG based Document Search (Q&A) Application

Table of Contents

• App Screenshots

• System Requirements

• Local Setup

  • Environment Variables

• Installation & Running

  • Frontend
  • Backend
  • RAG-Backend

• Testing

  • Frontend Testing
  • Backend Testing
  • RAG-Backend Testing

• Production Setup with ECS on EC2

• API Reference

  • Backend APIs
  • RAG-Backend APIs

System Requirements

Component	Requirement	Version
OS	macOS / Linux / Windows	Any modern
Node.js	JavaScript runtime	>= 20.x
npm	Node package manager	>= 9.x
Python	Python interpreter	>= 3.13
pip	Python package manager	>= 23.x
Docker	Container runtime	>= 20.x
AWS CLI	AWS command-line interface	>= 2.x
Git	Version control	>= 2.x

Local Setup

1. Clone this repository:

   git clone https://github.com/your-org/rag-app.git
   cd rag-app

2. Navigate into each subdirectory and set up environment variables.

Environment Variables

Copy the sample .env.example files and set your own values.

• Frontend (frontend/.env.local):

  NEXT_PUBLIC_API_URL=http://localhost:3001
  NEXT_PUBLIC_RAG_API_URL=http://localhost:8001

• Backend (backend/.env):

  PORT=3001
  DATABASE_URL=postgresql://user:password@localhost:5432/yourdb
  JWT_SECRET=your_jwt_secret

• RAG-Backend (rag-backend/.env):

  OPENAI_API_KEY=your_openai_api_key
  CHROMA_DB_URL=postgresql://chroma:chroma@localhost:5432/chromadb
  FASTAPI_PORT=8001

Installation & Running

Frontend

cd frontend
npm install
npm run dev
# Open http://localhost:3000

Backend

cd backend
npm install
npm run start:dev
# Open http://localhost:3001

RAG-Backend

cd rag-backend
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
uvicorn app.main:app --reload --port ${FASTAPI_PORT:-8001}
# chroma run --port 8001 # To run Chroma-DB (vector store DB) in foreground

Testing

Frontend Testing

cd frontend
npm run test

Backend Testing

cd backend
npm run test:cov

RAG-Backend Testing

Currently no automated tests are provided. You can add tests using pytest.

cd rag-backend
pip install pytest
pytest

Production Setup with ECS on EC2

1. Create ECR Repositories for each component or use GHCR:

   aws ecr create-repository --repository-name frontend
   aws ecr create-repository --repository-name backend
   aws ecr create-repository --repository-name rag-backend

2. Authenticate Docker to ECR:

   aws ecr get-login-password --region <region> | docker login --username AWS --password-stdin <aws_account_id>.dkr.ecr.<region>.amazonaws.com

3. Build and Push Docker Images:

   # Frontend
   docker build -t frontend:latest frontend/
   docker tag frontend:latest <ecr_uri>/frontend:latest
   docker push <ecr_uri>/frontend:latest
   
   # Backend
   docker build -t backend:latest backend/
   docker tag backend:latest <ecr_uri>/backend:latest
   docker push <ecr_uri>/backend:latest
   
   # RAG-Backend
   docker build -t rag-backend:latest rag-backend/
   docker tag rag-backend:latest <ecr_uri>/rag-backend:latest
   docker push <ecr_uri>/rag-backend:latest

4. Create an ECS Cluster (EC2 launch type, free-tier eligible):

   aws ecs create-cluster --cluster-name rag-app-cluster

5. Register Task Definitions for each service, specifying container images, port mappings, environment variables, and IAM roles.

6. Create Services associated with the task definitions, attach to an Application Load Balancer (ALB), and configure an Auto Scaling group of EC2 instances (e.g., t2.micro).

7. Configure Networking:

   • Security Groups to allow HTTP/HTTPS.
   • Load Balancer listeners on ports 80/443.
   • Set up Route 53 DNS if needed.

8. Deploy and verify each service is running:

   aws ecs update-service --cluster rag-app-cluster --service frontend-service --desired-count 2
   aws ecs update-service --cluster rag-app-cluster --service backend-service --desired-count 2
   aws ecs update-service --cluster rag-app-cluster --service rag-backend-service --desired-count 2

API Reference

Backend APIs

Endpoint	Method	Description
/auth/register	POST	Register a new user
/auth/login	POST	Authenticate and receive a JWT
/users	GET	List all users
/users/:id	GET	Get user by ID
/documents	GET	Retrieve all documents
/documents	POST	Upload/Create a new document
/documents/:id	GET	Get document by ID
/ingestion	POST	Trigger document ingestion

RAG-Backend APIs

Endpoint	Method	Description
/ingest	POST	Ingest documents into the vector store
/qa	POST	Query the vector store and get an answer
/health	GET	Health check endpoint
/docs	GET	Automatic API documentation (Swagger UI)

Note: Replace <ecr_uri>, <aws_account_id>, <region>, and other placeholders with your actual values as needed.