🍕 Pizza Restaurant QA Bot

An interactive question-answering bot for a pizza restaurant, built using LangChain, Ollama's LLMs, and ChromaDB. The bot answers user questions by leveraging realistic customer reviews stored in a local vector database.

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✨ Features

• Uses LangChain and Ollama LLM (llama3) to generate accurate, context-aware responses.
• Embeds customer reviews using the mxbai-embed-large model for efficient semantic search.
• Stores embedded reviews in ChromaDB, a local vector database.
• Retrieves the top 5 most relevant reviews per query to provide informed answers.

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📦 Requirements

To run this project, you need the following Python packages:

• langchain
• langchain-ollama
• langchain-chroma
• pandas

Install all dependencies using the provided requirements.txt:

pip install -r requirements.txt

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🧠 Local LLM Setup (Ollama)

1. Install Ollama from the official website:
   👉 https://ollama.com/download

2. Pull the required models:

ollama pull llama3
ollama pull mxbai-embed-large

3. Ensure the Ollama service is running in the background before executing any scripts.

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📁 File Structure

├── main.py                            # Main QA bot loop
├── vector.py                          # Embeds reviews into ChromaDB
├── realistic_restaurant_reviews.csv  # Customer review dataset
├── requirements.txt                   # Project dependencies
└── README.md                          # Project documentation

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▶️ How to Run

1. Clone the repository:

git clone https://github.com/kawish918/CritiqueChain.git
cd CritiqueChain

2. Install dependencies:

pip install -r requirements.txt

3. Create the vector database (only needed once):

python vector.py

4. Start the QA chatbot:

python main.py

✅ Ask questions about the restaurant!
💬 Type q to quit.

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💡 Notes

• Ensure Ollama is running before starting any script.
• This project runs entirely locally with no cloud dependencies.

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