README.md

metadata

license: mit
title: DocuMind
sdk: docker
colorFrom: red
colorTo: indigo
short_description: Enterprise RAG Chatbot
emoji: 📃

🧠 DocuMind: Enterprise RAG Chatbot

DocuMind is a production-ready, highly accurate Enterprise Retrieval-Augmented Generation (RAG) system. It allows organizations to ingest .pdf, .docx, and .txt documents and interact with them securely using a ChatGPT-style interface, completely circumventing LLM hallucinations by enforcing strict source-grounding.

🌟 Key Features

• Multi-Format Document Ingestion: Seamlessly upload APIs and TXTs locally or through the UI drag-and-drop.
• High-Accuracy RAG Pipeline: Combines dense retrieval via ChromaDB (all-MiniLM-L6-v2) with precision reranking via a CrossEncoder (ms-marco-MiniLM-L-6-v2) to pull only the 3 most strictly relevant context chunks.
• Citation-Backed UI: The Streamlit interface displays the exact ReRanker context chunks drawn from the documents, allowing users to verify LLM claims instantly.
• Conversation Memory: Maintains multi-turn context awareness seamlessly using LangChain's conversational buffer memory.
• Enterprise-Ready Middleware: API endpoints are secured with slowapi rate limiting.
• Instant Deployment: Fully dockerized with multi-container docker-compose routing, alongside a unified Dockerfile for HuggingFace Space hosting.

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🛠️ Tech Stack

• Backend Framework: FastAPI, Uvicorn
• Frontend UI: Streamlit
• RAG Orchestrator: LangChain
• Embeddings & ReRanker: HuggingFace sentence-transformers
• Vector Database: ChromaDB (Local SQLite Persistence)
• Generation LLM: LLaMA-3.1-8B (via Groq API)

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🚀 Getting Started Locally

1. Requirements

Ensure you have Docker installed. Clone this repository and execute:

git clone https://your-repo-link/DocuMind.git
cd DocuMind

2. Configure Environment Variables

Create a .env file in the root directory and add your Groq inference key:

GROQ_API_KEY=gsk_YOUR_GROQ_API_KEY_HERE

3. Spin up the Containers

Boot the unified backend, vector store, and frontend seamlessly using Docker Compose:

docker-compose up --build -d

Access the application by navigating to http://localhost:8501 in your browser.

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🌐 Deploying to Hugging Face Spaces

This project contains a unified Dockerfile and run.sh script precisely tuned to bypass HF networking permissions and boot the application perfectly.

1. Create a New Space on Hugging Face using the Docker SDK (Blank Template).
2. Clone your Space, copy the contents of this repository into it, and git push.
3. Go to the Settings > Variables and secrets tab of the Space.
4. Create a new Secret named GROQ_API_KEY and provide your token.
5. Hugging Face will automatically execute the build and render the Streamlit app!

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🔒 Security & Model Boundaries

Please review MODEL_CARD.md for detailed descriptions on token chunking logic, LLM fallback behaviors limiting false generation, and privacy constraints.