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Production-Ready AI Q&A Chatbot (RAG + OpenAI + ChromaDB)

structured-rag-chatbot

Build a scalable, production-ready Q&A chatbot using OpenAI APIs, Retrieval-Augmented Generation (RAG), ChromaDB vector database, and Streamlit UI. This project demonstrates structured JSON outputs using Pydantic, semantic search with embeddings, and a clean modular Python architecture suitable for real-world AI systems.

📌 Features

  • Structured JSON output (Pydantic)
  • RAG pipeline (retrieval + generation)
  • ChromaDB vector search
  • Streamlit UI

Folder Stracture

qa-chatbot/ │── app.py │── main.py │── rag/ │ ├── ingest.py │ ├── retrieve.py │ ├── prompt.py │── models/ │ ├── schema.py │── utils/ │ ├── openai_client.py │── data/ │── chroma_db/ │── requirements.txt │── .env │── README.md

⚙️ Setup

git clone <repo>
cd qa-chatbot
python -m venv venv
venv\\Scripts\\activate
pip install -r requirements.txt

## 🚀 Run Project

```bash
streamlit run app.py

About

Build a scalable, production-ready Q&A chatbot using OpenAI APIs, Retrieval-Augmented Generation (RAG), ChromaDB vector database, and Streamlit UI. This project demonstrates structured JSON outputs using Pydantic, semantic search with embeddings, and a clean modular Python architecture suitable for real-world AI systems.

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