Chatbot with RAG using LangChain and OpenAI

This is a basic console project for creating chatbots with RAG using LangChain and OpenAI's language model. You can save PDFs in a folder and have the chatbot respond with information extracted from them.

1. Prerequisites

Ensure you have the following installed:

• Python 3.12.5
• Git (optional) for cloning repositories and managing the code

2. Environment Setup

Clone the repository or extract the project

If you received the project as a ZIP file, extract it to a directory of your choice.

3. Installing Dependencies

With the virtual environment activated, install the required dependencies:

pip install -r requirements.txt

4. Project Configuration

Set up environment variables in the .env file as needed. This file should contain necessary variables such as API keys, directory paths, etc.

Get an API Key on OpenAI website https://platform.openai.com/docs/overview

5. Running the Project

To run the project, execute the main script:

python src/main.py

6. File & Folder Structure

chatbot_rag_langchain/
 ├── src/
 │   ├── chatbot.py          # Contains chatbot logic
 │   ├── main.py             # Main entry point of the project
 │   ├── rag_pipeline.py     # Handles the RAG (Retrieval-Augmented Generation) pipeline
 ├── config/
 │   ├── config.py           # Configuration settings for the project
 ├── data/
 │   ├── pdfs/               # Directory where PDFs are stored for analysis or retrieval
 ├── requirements.txt        # Dependencies required for the project
 ├── .env                    # Environment variables (API keys, paths, etc.)                 

Now you're ready to build, test, and enhance this chatbot.