SimpleProject / README.md
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Final submission
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metadata
title: AnatomyBot - MBBS Anatomy Tutor
hackathon: https://huggingface.co/MCP-1st-Birthday
emoji: 🩺
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 6.0.0
app_file: app.py
pinned: false
license: mit
short_description: AnatomyBot - Interactive AI-powered MBBS anatomy tutor.
tags:
  - building-mcp-track-enterprise
  - building-mcp-track-customer
  - building-mcp-track-creative
  - mcp-in-action-track-creative
  - mcp-in-action-track-consumer

🩺 AnatomyBot – MBBS Anatomy Tutor

Welcome to our submission for the Hugging Face MCP 1st Birthday Hackathon!
This project showcases an intelligent multi-agent educational system powered by Gradio, designed to revolutionize how medical students learn anatomy through visuals, voice interaction, and active recall.

Link to demo: https://huggingface.co/spaces/gladguy/SimpleProject
YouTube Video: https://www.youtube.com/watch?v=5L5suQMTd5I


πŸ“ What I want to showcase

I want to showcase an intelligent, interactive educational platform designed specifically for MBBS (medical) students. The goal is to bridge the gap between static textbooks and active learning by providing:

  • Visual & Contextual Learning: Instantly fetching relevant anatomical diagrams alongside AI-generated educational summaries.
  • Active Recall & Simulation: A "VIVA Mode" that simulates an oral anatomy exam with a strict but fair AI professor, complete with voice interaction.
  • Resource Augmentation: A "Book Mode" that allows students to upload their own textbooks and get AI-powered analysis and quiz questions for specific pages.

πŸ› οΈ What I've built so far

I have built a fully functional Gradio web application that integrates multiple powerful AI services:

1. Smart Query Engine

  • Uses Hyperbolic AI (Llama 3.3 70B) to validate if questions are strictly anatomy-related.
  • Fetches high-quality diagrams using SERPAPI (Google Images), filtering out non-diagrammatic results.
  • Generates structured, emoji-rich educational content (Location, Features, Clinical Significance).

2. VIVA Training Mode

  • Simulates a real oral exam environment.
  • Generates progressive questions (from basic relations to clinical scenarios).
  • Voice Interaction: Uses ElevenLabs to vocalize questions, making the experience immersive.
  • AI Evaluation: Grades student answers (Distinction, Pass, Borderline, Fail) and provides detailed feedback with reference answers.

3. Book Learning Mode

  • Allows PDF textbook uploads.
  • Extracts and displays specific pages.
  • Analyzes page content to generate summaries, clinical points, and self-test questions.

πŸ’» Tech Stack

  • Frontend/UI: Gradio (Python)
  • LLM Intelligence: Hyperbolic AI API (Meta Llama 3.3 70B Instruct)
  • Image Search: SERPAPI (Google Images Engine)
  • Voice Synthesis: ElevenLabs API (Text-to-Speech)
  • Image/PDF Processing: Pillow, PyPDF2, pdf2image
  • Environment: Python, Hugging Face Spaces

πŸ”— Quick Links


πŸ› οΈ Installation & Setup

Prerequisites

  • Python 3.8 or higher
  • API Keys for SERPAPI, Hyperbolic, and ElevenLabs.

Steps

  1. Clone the repository:
    git clone https://huggingface.co/spaces/gladguy/SimpleProject
    cd SimpleProject
    
  2. Install dependencies:
    pip install -r requirements.txt
    
  3. Set up your .env file:
    SERPAPI_KEY=your_key
    HYPERBOLIC_API_KEY=your_key
    ELEVENLABS_API_KEY=your_key
    
  4. Run the app:
    python app.py or uv run app.py
    

πŸ§‘β€πŸ’» Authors


πŸ“ License

This project is licensed under the MIT License.