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metadata 
title: Edu MentorAI
emoji: 👁
colorFrom: pink
colorTo: green
sdk: docker
sdk_version: '1.0'
app_file: app.py
pinned: false

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

Edu MentorAI 👁

Edu MentorAI is a professional AI-powered study assistant web application that leverages cutting-edge Google Gemini Nano and Hugging Face Transformers models to provide intelligent, interactive learning support. This project offers a multi-page Flask web interface with chatbot capabilities, predefined Q&A, and seamless AI-driven responses to enhance educational experiences.

Edu MentorAI 👁

Edu MentorAI is a professional AI-powered study assistant web application that leverages cutting-edge Google Gemini Nano and Hugging Face Transformers models to provide intelligent, interactive learning support. This project offers a multi-page Flask web interface with chatbot capabilities, predefined Q&A, and seamless AI-driven responses to enhance educational experiences.

Features

  • AI-powered chatbot using Google Gemini Nano generative model
  • Predefined sample questions and answers for quick help
  • Multi-page Flask web application with routes for Home, AI, About, Contact, Services, and Library
  • Markdown support for rich text AI responses
  • Dockerized for easy deployment and environment consistency
  • Hugging Face cache management for efficient model loading

Technologies Used

  • Python 3.9
  • Flask web framework
  • Google Generative AI (Gemini Nano)
  • Hugging Face Transformers and Torch
  • Markdown for response formatting
  • Docker for containerized deployment
  • Additional libraries: flask-cors, requests, wikipedia, langchain, ollama, gunicorn

Installation

Prerequisites

  • Docker (optional, for containerized deployment)
  • Google API Key for Google Generative AI

Deployment with Docker

  1. Build the Docker image:
docker build -t edu-mentorai .
  1. Run the Docker container:
docker run -p 7860:7860 edu-mentorai
  1. Access the app at http://localhost:7860

Usage

  • Access the web interface with multiple pages: Home, AI, About, Contact, Services, Library
  • Use the chat endpoint to interact with the AI chatbot
  • Ask predefined questions or enter your own queries to get AI-generated responses
  • Responses support Markdown formatting for rich text display

Configuration

  • Hugging Face cache directory is set to /tmp/huggingface_cache by default
  • Google API key must be configured for the generative AI to work
  • Port 7860 is exposed by default; can be changed in app.py

Contributing

Contributions are welcome! Please fork the repository and submit pull requests for improvements, bug fixes, or new features.

License

This project is licensed under the MIT License.

Contact

For questions or support , please contact Selva Neyas U.

Made with ❤️ by Selva Neyas U 📬