RAG-Backend

This project is a Retrieval-Augmented Generation (RAG) backend implemented in Go. It provides an API to upload documents, retrieve relevant content based on user queries, and generate responses using OpenAI's GPT model.

Features

• File Upload: Upload text files to be stored in memory.
• Context Retrieval: Extract relevant content from uploaded documents based on a user query.
• AI Response Generation: Use OpenAI's GPT model to generate responses based on retrieved context.
• CORS Support: Configured to allow frontend access.

Project Structure

rag-backend/
│── rag/
│   ├── generator.go   # Handles OpenAI API interactions
│   ├── retriever.go   # Retrieves relevant context from uploaded documents
│── server/
│   ├── handlers.go    # Defines API handlers
│   ├── router.go      # Configures API routes
│   ├── server.go      # Initializes and starts the HTTP server
│── storage/
│   ├── memory.go      # Manages in-memory file storage
│── utils/
│   ├── parser.go      # Text processing utilities
│── .env               # Stores environment variables (not included in version control)
│── .gitignore         # Git ignore rules
│── go.mod             # Go module dependencies
│── go.sum             # Dependency checksums
│── main.go            # Entry point of the application

Dependencies

This project uses the following Go packages:

• gorilla/mux - HTTP router for request handling
• gorilla/handlers - Middleware for CORS support
• joho/godotenv - Loads environment variables from .env
• sashabaranov/go-openai - OpenAI API client

Setup

Prerequisites

• Install Go (1.24 or higher)
• Get an OpenAI API key from OpenAI

Installation

1. Clone the repository:

   git clone https://github.com/starmanv4/rag-backend.git
   cd rag-backend

2. Install dependencies:

   go mod tidy

3. Create a .env file and add your OpenAI API key:

   OPENAI_API_KEY=your_openai_api_key_here
   

Running the Server

Start the server with:

go run main.go

The server will start on http://localhost:8080.

API Endpoints

1. Upload File

• Endpoint: /upload
• Method: POST
• Content-Type: multipart/form-data
• Description: Uploads a text file for processing.

Example Request (cURL)

curl -X POST -F "[email protected]" http://localhost:8080/upload

Example Response

{
	"message": "File uploaded successfully",
	"filename": "sample.txt"
}

2. Query Document

• Endpoint: /query
• Method: POST
• Content-Type: application/json
• Description: Submits a query and receives a response based on uploaded documents.

Example Request (cURL)

curl -X POST http://localhost:8080/query \
     -H "Content-Type: application/json" \
     -d '{"query": "What is the main topic of the document?"}'

Example Response

{
	"response": "The document discusses artificial intelligence and its applications."
}

Environment Variables

Variable	Description
OPENAI_API_KEY	OpenAI API key (required for response generation)

Future Improvements

• Persistent Storage: Store uploaded files in a database instead of memory.
• Authentication: Implement API key-based authentication.
• More Retrieval Methods: Enhance document retrieval with embeddings.

License

This project is licensed under the MIT License.

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Author: starmanv4
GitHub: github.com/starmanv4/rag-backend