RAG Chatbot with ChromaDB and LangChain

A Retrieval-Augmented Generation (RAG) chatbot that uses ChromaDB for vector storage and LangChain for LLM integration.

Project Structure

RAGChat/
│
├── app/                      
│   ├── __init__.py
│   ├── main.py              
│   ├── config.py             
│   │
│   ├── database/            
│   │   ├── __init__.py
│   │   ├── chroma_client.py
│   │   └── vector_store.py 
│   │
│   ├── retrieval/    
│   │   ├── __init__.py
│   │   └── retriever.py   
│   │
│   ├── llm/     
│   │   ├── __init__.py
│   │   ├── model.py     
│   │   └── prompt.py    
│   │
│   └── chat/         
│       ├── __init__.py
│       └── bot.py      
│
├── data/             
│   ├── raw/        
│   ├── processed/      
│   └── embeddings/        
│
│
├── tests/           
│   ├── __init__.py
│   ├── test_retrieval.py
│   └── test_chat.py       
│
├── requirements.txt         
├── .env
├── README.md        
└── .gitignore     

Adding Your Own Documents

Place your documents in the data/raw/ directory. The system supports:

• Text files (.txt)
• PDF files (.pdf)
• Markdown files (.md)
• HTML files (.html)

Running the Application

Setting Up a Virtual Environment

Create virtual environment.

python -m venv venv

Activate virtual environment.

source venv/bin/activate

Dependencies

pip install -r requirements.txt

Setup .env

OPENAI_API_KEY=your_openai_api_key

Vector Store Demo

To test the vector store functionality and see how documents are retrieved:

python -m app.main --demo

This will:

• Load sample documents from the data/raw/ directory
• Run test queries against the vector store
• Display the retrieved documents and their relevance scores

Interactive Chat

To start an interactive chat session with the RAG chatbot:

python -m app.main --chat

This will:

• Initialize the vector store with your documents
• Start an interactive command-line chat interface
• Retrieve relevant documents for each query
• Generate responses based on the retrieved context

Help

To see all available options:

python -m app.main --help