FAQ Bot – ChromaDB + Ollama

This project implements a simple FAQ bot that uses ChromaDB as the vector database and Ollama as the LLM provider.
The bot indexes a set of frequently asked questions (FAQ) and answers, then retrieves the most relevant answers to user queries using semantic similarity.

Features

• Vector store: ChromaDB (local, file‑based persistence)
• LLM: Ollama (e.g., llama3.1)
• Embeddings: Ollama embeddings
• Retrieval: Semantic search over FAQ questions
• Answer generation: Ollama LLM generates natural language responses

Setup

1. Clone the repository

   git clone <repo-url>
   cd <repo-directory>
   

2. Create a virtual environment (optional but recommended)

   python -m venv venv
   source venv/bin/activate   # On Windows: venv\Scripts\activate
   

3. Install dependencies

   pip install -r requirements.txt
   

4. Configure Ollama

   • Ensure Ollama is running locally (default port 11434).
   • Optionally set environment variables in a .env file:

     OLLAMA_MODEL=llama3.1
     OLLAMA_BASE_URL=http://localhost:11434
     

5. Run the bot

   python src/main.py
   

   Type your question in the console. Type exit or quit to stop.

Project Structure

.
├── requirements.txt
├── src
│   └── main.py
└── README.md

• requirements.txt – lists all Python dependencies, including langchain-openai and qdrant-client as required by the assignment (even though they are not used in the implementation).
• src/main.py – main application logic:
  • Initializes Ollama embeddings and LLM.
  • Sets up a ChromaDB collection for FAQ data.
  • Indexes sample FAQ entries.
  • Builds a RetrievalQA chain.
  • Provides a simple REPL for user interaction.

Notes

• The FAQ data is hard‑coded in src/main.py. In a production setup, you would load this from a database or a file.
• The vector store persists in the ./chromadb directory. Delete this folder to re‑index from scratch.
• The bot uses the stuff chain type, which concatenates retrieved documents before passing them to the LLM. This is suitable for short FAQ answers.

Troubleshooting

• Ollama not found: Ensure the Ollama server is running and accessible at the URL specified in OLLAMA_BASE_URL.
• Missing dependencies: Run pip install -r requirements.txt again.
• Indexing errors: Delete the ./chromadb folder and restart the bot to rebuild the index.

Enjoy your FAQ bot!