title	emoji	colorFrom	colorTo	sdk	sdk_version	app_file	pinned	license	short_description
NVIDIA NIM Demo	🔥	purple	yellow	streamlit	1.42.2	app.py	false	apache-2.0	AI-powered document retrieval and question-answering system

NVIDIA DeepSeek AI Document Search

Overview 🧠📄

This project is an AI-powered document retrieval and question-answering system utilizing NVIDIA DeepSeek AI and FAISS vector stores. It allows users to embed, retrieve, and query research papers using advanced NVIDIA AI models for accurate and contextual responses.

Features ✨

• FAISS-based Vector Storage: Efficiently stores and retrieves document embeddings.
• NVIDIA DeepSeek AI Integration: Uses deepseek-ai/deepseek-r1 for high-quality AI inference.
• PDF Processing: Extracts and processes research papers for retrieval-based QA.
• Streamlit UI: Interactive user interface for querying and document similarity search.

Deployment 🚀

The application is deployed on Hugging Face Spaces. You can access it using the following link:

👉 Deployment Link

Installation & Setup 🛠️

1️⃣ Clone the Repository

git clone https://github.com/Rohit-Madhesiya/NVIDIA-NIM-Demo.git
cd NVIDIA-NIM-Demo

2️⃣ Create a Virtual Environment (Optional but Recommended)

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

3️⃣ Install Dependencies

pip install -r requirements.txt

4️⃣ Set Up API Key

• Create a .env file in the root directory.
• Add the following line:

NVIDIA_API_KEY=<your_nvidia_api_key>

Usage 📌

Run the Streamlit application:

streamlit run main.py

Once the app is running:

1. Enter your NVIDIA API Key.
2. Click Document Embedding to process research papers.
3. Type a question and get AI-generated responses based on the document content.
4. Expand Document Similarity Search to view retrieved document chunks.

Dependencies 📋

The project requires the following Python libraries:

• streamlit
• langchain_nvidia_ai_endpoints
• langchain_community
• faiss-cpu
• pypdf
• python-dotenv
• openai

Project Structure 📂

├── main.py              # Main application file
├── requirements.txt     # List of dependencies
├── .env                 # API key configuration (not included in repo)
└── README.md            # Project documentation

Contributing 🤝

Feel free to fork the repository, submit pull requests, or report any issues.

Author 👨‍💻

Developed by [Rohit Gupta].