ParagonAI is an open-source project designed to make interacting with large bodies of information simple and efficient. By leveraging Retrieval-Augmented Generation (RAG), ParagonAI allows users to build a custom knowledge base by providing URLs, from which it extracts, stores, and indexes relevant content. Users can then ask natural language questions about the information, receiving precise, contextually relevant answers.

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1. Getting Started 🚀

1.1. Front-End

To install all packages and start the front-end app run these commands

cd frontend
npm install
npm run dev

1.2. Back-end

Prerequisites

Make sure you have the following installed:

• Python 3.9+
• Pip (package installer for Python)

Installation

1. Create a virtual environment and activate it:

   cd backend
   python3 -m venv env
   source env/bin/activate  # On Windows use `env\Scripts\activate`

2. Install the dependencies:

   pip install -r requirements.txt

Running the App

1. Create .env file and add the following values (field values are examples):

   DB_DIR_NAME="chroma_db"
   DB_COLLECTION_NAME="langchain"
   OPENAI_API_KEY= # Optional - you can use this env variable or set_openai_api_key/ endpoint to set value

2. Run the development server using Uvicorn:

   fastapi dev src/api.py

3. The app will be available at http://127.0.0.1:8000.

Testing the API

To explore and test the API, you can use the automatically generated OpenAPI docs provided by FastAPI:

• OpenAPI docs: http://127.0.0.1:8000/docs
• ReDoc: http://127.0.0.1:8000/redoc