This directory contains a Python script that implements a conversational retrieval system using LangChain and OpenAI's API. The script allows users to query a collection of documents and receive responses based on the retrieved information.

• Load documents from a specified directory.
• Create and persist a vector store index for efficient querying.
• Engage in conversational interactions, maintaining chat history.
• Easily exit the program.

• Python 3.7+
• Required packages:
  • openai
  • langchain
  • chromadb

You can install the required packages using pip:

pip install openai langchain chromadb

1. Clone the Repository:

   git clone https://github.com/king04aman/custom-gpt.git
   cd your_repository

2. Set the OpenAI API Key: Replace your_api_key_here in the script with your actual OpenAI API key. You can also set the environment variable directly in your terminal:

   export OPENAI_API_KEY="your_api_key_here"

3. Prepare Your Data: Place your documents in a folder named data/. The script will load all documents from this directory.

Run the script from the command line:

python main.py

You can provide an initial query as a command line argument:

python main.py "Your initial query here"

If no initial query is provided, the script will prompt you to enter queries interactively. Type your question and press Enter to get a response. Type quit, q, or exit to exit the program.

• Set the PERSIST variable to True in the script to enable saving the vector store index to disk for reuse in future sessions.
• The index will be saved in a directory named persist/.

Prompt (type 'quit' to exit): What is the significance of data persistence?
Response: [Your response here based on the documents]

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

Feel free to submit issues or pull requests. Contributions are welcome!