RAG Application

This is a Retrieval-Augmented Generation (RAG) application using Langchain, OpenAI, and Pinecone for movie history.

Features

• Chat
• Question Answering (QA)

Setup

1. Create a virtual environment:

   python -m venv venv

2. Activate the virtual environment:

   • On Windows:

     venv\Scripts\activate

   • On macOS and Linux:

     source venv/bin/activate

3. Install dependencies:

   pip install -r requirements.txt

4. Set up environment variables:

   Create a .env file in the root directory of your project and add the following variables:

   OPENAI_API_KEY=""
   PINECONE_API_KEY=""
   PINECONE_INDEX_NAME="movie-history"
   FEATURE_NAME="chat" # "qa"
   

   -> FEATURE_NAME will be chat|qa . diff is chat will preserve history

Load Data into Pinecone VectorDB

1. Load the data into Pinecone:

   python ./src/vector_store/load_data.py

Run the Project

1. start project with gradio ui

   python app.py

• 127.0.0.1:7860