RAG API 🤖

An API project for Retrieval-Augmented Generation (RAG) using OpenAI's models. This service enables document upload, storage, and intelligent querying using Large Language Models (LLMs).

🚀 Features

• Document upload and storage
• Text extraction and chunking
• Vector embeddings generation using OpenAI
• Semantic search capabilities
• Question answering with context
• Document management

🛠️ Tech Stack

• FastAPI: Modern, fast web framework for building APIs
• OpenAI: Embeddings and Language Models
• PostgreSQL + pgvector: Vector similarity search
• Python 3.10+: Modern Python features
• Docker: Containerization and deployment

🏃‍♂️ Quick Start

1. Clone the repository:

git clone https://github.com/rrequeena/rag-api.git
cd rag-api

2. Create a .env file with your configuration:

OPENAI_API_KEY=sk-this-is-your-super-api-key
POSTGRES_USERNAME=postgres
POSTGRES_PASSWORD=postgres
POSTGRES_HOST=postgres
POSTGRES_PORT=5432
DATABASE_NAME=rag_api_db

You will find a .env.example file at the project folder.

3. Start the services using Docker Compose:

docker-compose up --build

Or you can use Make commands:

make build
make compose

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

🔗 API Endpoints

GET /

Root endpoint that returns all the files stored in the DB.

curl -X 'GET' \
  'http://0.0.0.0:8080/' \
  -H 'accept: application/json'

POST /uploadfile/

Upload a document for processing.

curl -X 'POST' \
  'http://0.0.0.0:8080/uploadfile/' \
  -H 'accept: application/json' \
  -H 'Content-Type: multipart/form-data' \
  -F 'file=@your_file.pdf;type=application/pdf'

POST /ask/

Ask questions for a given document ID.

curl -X 'POST' \
  'http://0.0.0.0:8080/ask/' \
  -H 'accept: application/json' \
  -H 'Content-Type: application/json' \
  -d '{
  "document_id": 4,
  "question": "What is the document talking about?"
}'

POST /find-similar-chunks/{file_id}

Find similar chunks of text for a given document.

curl -X 'POST' \
  'http://0.0.0.0:8080/find-similar-chunks/4' \
  -H 'accept: application/json' \
  -H 'Content-Type: application/json' \
  -d '{
  "question": "Something you want to check"
}'

DELETE /delete-document/{file_id}

Delete a document and its associated data.

curl -X DELETE "http://localhost:8080/delete-document/1" \
     -H "accept: application/json"

📝 Documentation

Full API documentation is available at:

• Swagger UI: http://localhost:8080/docs