---
title: Enterprise AI Document Intelligence Platform
emoji: 🤖
colorFrom: blue
colorTo: indigo
sdk: gradio
sdk_version: 6.20.0
app_file: app.py
pinned: false
license: mit
---

# 🤖 Enterprise AI Document Intelligence Platform

An AI-powered Retrieval-Augmented Generation (RAG) application that enables users to upload PDF documents, perform semantic search, and interact with them using natural language. The application retrieves the most relevant document context using vector embeddings and generates grounded responses using Groq's Llama 3.3 model.

> 🚀 **Live Demo:** *(Add your Hugging Face Space URL after deployment)*

---

## ✨ Features

- 📄 **Upload & Analyze PDFs**
  - Upload enterprise documents, resumes, reports, manuals, or research papers.

- 🔍 **Semantic Search**
  - Retrieves the most relevant document sections using Sentence Transformers and FAISS vector search.

- 🤖 **AI-Powered Question Answering**
  - Generates context-aware answers using Groq Llama 3.3 with Retrieval-Augmented Generation (RAG).

- 💬 **Interactive Chat Interface**
  - Ask follow-up questions naturally through a clean Gradio interface.

- 🛡 **Grounded Responses**
  - Answers are generated only from the uploaded document context to reduce hallucinations.

---

## 🛠 Tech Stack

| Category | Technologies |
|----------|--------------|
| Frontend | Gradio |
| LLM | Groq Llama 3.3-70B Versatile |
| Embeddings | Sentence Transformers (all-MiniLM-L6-v2) |
| Vector Database | FAISS |
| PDF Processing | PyMuPDF |
| Language | Python |

---

## 🏗 Architecture

```text
PDF Upload
      │
      ▼
PyMuPDF
      │
      ▼
Text Chunking
      │
      ▼
Sentence Transformer Embeddings
      │
      ▼
FAISS Vector Index
      │
      ▼
Semantic Retrieval
      │
      ▼
Groq Llama 3.3
      │
      ▼
Grounded AI Response
```

---

## 🚀 Getting Started

### 1. Clone the repository

```bash
git clone <repository-url>
cd Enterprise-AI-HF-Space
```

### 2. Create a virtual environment

```bash
python -m venv .venv
```

Activate it:

**Windows**

```bash
.venv\Scripts\activate
```

**Linux / macOS**

```bash
source .venv/bin/activate
```

### 3. Install dependencies

```bash
pip install -r requirements.txt
```

### 4. Configure environment variables

Create a `.env` file:

```env
GROQ_API_KEY=your_groq_api_key
```

### 5. Run the application

```bash
python app.py
```

---

## 📌 Example Questions

- Summarize this document.
- What are the key technical skills?
- List the projects mentioned.
- What experience does this resume highlight?
- What are the major findings in this report?

---

## 🎯 Use Cases

- Resume Analysis
- Enterprise Knowledge Search
- Research Paper Exploration
- Policy & Compliance Documents
- Technical Documentation
- Business Reports

---

## 📄 License

This project is released under the MIT License.