💡 Abstract (for the publication overview / search preview)

Ready Tensor RAG Assistant is an AI-powered tool that enables intelligent, context-aware querying of Ready Tensor publications.
Built with FastAPI, LangChain, and Streamlit, it combines retrieval and generation to deliver accurate, research-driven insights in real time.
     
# 🧠 Ready Tensor RAG Assistant

A **Retrieval-Augmented Generation (RAG)** AI Assistant built using **FastAPI**, **LangChain**, **ChromaDB**, and **Streamlit**.  
This assistant allows users to query Ready Tensor publications and receive **intelligent, context-aware answers** in real time.

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## 🚀 Features

- 🔗 **RAG Pipeline** – Combines document retrieval and generation for accurate contextual answers  
- ⚡ **FastAPI Backend** – Lightweight, high-performance API server  
- 🧩 **LangChain Integration** – Uses OpenAI embeddings and models for semantic understanding  
- 🗃️ **Chroma Vectorstore** – Efficient storage and semantic search for publication data  
- 💬 **Streamlit Frontend** – Interactive and user-friendly chat-style UI  
- ☁️ **Render Deployment** – Fully Dockerized and deployable on any cloud platform  

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## 🧰 Tech Stack

| Layer | Technology |
|--------|-------------|
| Frontend | Streamlit |
| Backend | FastAPI |
| AI Framework | LangChain |
| Database | ChromaDB |
| Embeddings | OpenAI |
| Deployment | Render (Docker) |

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## ⚙️ Setup Instructions

### 1️⃣ Clone the Repository
```bash
git clone https://github.com/strdst7/readytensor-rag-assistant.git
cd readytensor-rag-assistant

2️⃣ Create and Activate Virtual Environment

python3 -m venv venv
source venv/bin/activate  # macOS/Linux
pip install -r requirements.txt

3️⃣ Run Locally

bash run_all.sh

Then open your browser and visit 👉 http://localhost:8502

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🌐 Live Demo

🟢 Deployed on Render:
🔗 https://readytensor-rag-assistant.onrender.com

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🖼️ Screenshots

| API Docs |

| Streamlit App

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📄 License

MIT License © 2025

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👩‍💻 About the Developer

Developed by Nur Amirah Mohd Kamil as part of the Ready Tensor RAG Assistant program.
Passionate about combining AI, data science, and cloud deployment to create intelligent, production-ready tools.