Project Overview

The goal of developing this repository is to create a scalable project based on RAG operations of a vector database (Postgres with pgvector), and to expose a question-answering system developed with LangChain and FastAPI on a Next.js frontend.

The entire system will be deployed in a serverless manner, both on the backend (a Terraform submodule for setting up a cloud run with CloudSQL and Redis) and on the frontend (deployment via Vercel).

Additionally, a layer will be added to limit the app's usage through a subscription plan via Stripe

Setting Up the Infrastructure

Import Terraform Submodule

Refer to the following guide for adding and managing submodules: Adding a Submodule and Committing Changes: Git, Terraform, FastAPI

Steps to Initialize Terraform:

Navigate to the Terraform directory and initialize the configuration:

cd terraform
terraform init
terraform apply

Configuring the Application

Set Environment Variables

Duplicate the .env.example file and set the required variables:

cp .env.example .env

Backend Setup

• Navigate to the backend directory:

cd backend

• Install dependencies using Poetry:

poetry install
poetry shell

Database Connection

Connect to the database using the Cloud SQL Proxy. Instructions are available in the Terraform README.

./cloud-sql-proxy ...

Initialize Database

Run the initialization script to set up the database. This script adds the pgvector extension and creates a superuser:

python app/init_db.py

Data Ingestion

Place your PDF files in data/raw and run the following script to populate the database:

python app/ingestion/run.py

Accessing the Application

API Documentation

Access live-generated API documentation at:

https://cloudrun-service-upr23soxia-uc.a.run.app/api/v1/docs

Obtaining an Access Token

Generate an access token using the /api/v1/login/access-token endpoint with credentials specified in your .env file.

Connecting the Frontend

Generate an Access Token

Obtain an access token using the login endpoint:

const token = "your_generated_access_token_here"; // Replace with actual token

Example Frontend Integration

Utilize the access token in your Next.js application as follows:

const headers = new Headers({
  Authorization: "Bearer " + token,
  "Content-Type": "application/json",
});

async function chatAnswer() {
  const res = await fetch(
    `${process.env.NEXT_PUBLIC_API_BASE_URL}/api/v1/qa/chat`,
    {
      method: "POST",
      headers: headers,
      body: JSON.stringify({ message: "Your query here" }),
    }
  );
  return res.json();
}

Subscription Management

Integrate Stripe to manage subscriptions and limit usage based on the chosen plan. Follow Stripe's official documentation to set up the billing and subscription logic.

Contributing

Contributions are welcome! For major changes, please open an issue first to discuss what you would like to change.

License

This project is licensed under the MIT License - see the LICENSE file for details.