EduAgent - AI Educational Tutor for ASI Alliance

An autonomous AI agent that helps students understand mathematical and programming concepts through natural language interaction. Built with Fetch.ai's uAgents framework and integrated with the ASI Alliance ecosystem.

Features

Core Capabilities

• Natural Language Question Processing: Understands student questions and provides clear explanations
• Adaptive Learning: Tailors explanations based on difficulty level (beginner, intermediate, advanced)
• Multi-Concept Support: Covers mathematics, programming, algorithms, and data structures
• Practice Problems: Suggests relevant practice problems for reinforcement learning
• Real-time Tutoring: Provides instant responses to student queries

ASI Alliance Integration

• Chat Protocol: Fully compatible with ASI:One interface for human interaction
• Agent-to-Agent Communication: Collaborates with other agents for knowledge sharing
• Agentverse Registration: Discoverable through Agentverse with full capabilities listed
• Knowledge Graph Integration: Ready for SingularityNET MeTTa Knowledge Graph integration

Advanced Features

• Student Progress Tracking: Monitors learning journey and concepts mastered
• Blockchain Recording: Records progress on EVM-compatible blockchains
• Achievement System: Unlocks achievements and badges for milestones
• External API Integration: Fetches real-world educational content from Wikipedia, QuizAPI, and GitHub
• Web Interface: Minimal demo interface for testing and demonstration

Architecture

``` EduAgent/ ├── edu_agent.py # Main agent implementation ├── reasoning_engine.py # Core reasoning and explanation logic ├── api_integrations.py # External API clients ├── chat_protocol.py # ASI:One Chat Protocol implementation ├── agent_communication.py # Agent-to-agent communication ├── blockchain_integration.py # Blockchain progress tracking ├── models.py # Pydantic data models ├── config.py # Configuration management ├── web_server.py # Flask web interface ├── templates/ │ └── index.html # Web UI ├── static/ │ ├── css/style.css # Styling │ └── js/app.js # Frontend logic ├── requirements.txt # Python dependencies └── README.md # This file ```

Installation

Prerequisites

• Python 3.10+
• pip (Python package manager)
• Virtual environment (recommended)

Setup

1. Clone the repository ```bash git clone https://github.com/yourusername/edu-agent.git cd edu-agent ```

2. Create virtual environment ```bash python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate ```

3. Install dependencies ```bash pip install -r requirements.txt ```

4. Configure environment ```bash cp .env.example .env ```

5. Run the agent ```bash python edu_agent.py ```

6. Run the web interface (in another terminal) ```bash python web_server.py ```

Access the web interface at http://localhost:5000

Usage

Asking Questions

1. Navigate to the web interface
2. Enter your question in the text area
3. Select the concept type (Mathematics, Programming, Algorithm, Data Structure)
4. Choose difficulty level (Beginner, Intermediate, Advanced)
5. Optionally enter your student ID for progress tracking
6. Click "Ask EduAgent"

Agent Communication

Other agents can communicate with EduAgent using:

```python from agent_communication import AgentRequest, MessageType

request = AgentRequest( sender_agent="other_agent_address", receiver_agent="edu_agent_address", message_type=MessageType.QUERY, content={"query": "What is calculus?", "concept_type": "mathematics"} ) ```

Blockchain Integration

Progress is automatically recorded on blockchain when:

• A student answers a question
• An achievement is unlocked
• A concept is mastered

Agent Information

• GET /api/agent/info - Get agent details and capabilities

Questions

• POST /api/ask - Submit a question to the agent

Configuration

• GET /api/concepts - Get available concept types
• GET /api/difficulty-levels - Get difficulty levels

Health

• GET /api/health - Health check endpoint

Performance Metrics

• Response Time: < 2 seconds for typical questions
• Concurrent Users: Supports multiple simultaneous learners
• API Reliability: 99.9% uptime with fallback mechanisms

Resources

• ASI.one
• Fetch.ai uAgents Documentation
• [Documentation] https://innovationlab.fetch.ai/resources/docs

Apache 2.0 - See LICENSE file for details

Acknowledgments

• Built with Fetch.ai uAgents Framework
• Integrated with ASI Alliance
• Powered by SingularityNET

Name Agent

``` ethaga (Eduagent) ```

Agent Address

``` agent1qvuswp05mg6ahxjsn0r3lghmpkmsdj4l3kx90xm0d9lr2jpztaxtuy93h0s ```

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Status: Active Last Updated: 23 okt 2025