🚀 Adaptive Learning Architect

Adaptive Learning Architect is a specialized AI Tutor designed to build personalized learning roadmaps. This project integrates a backend powered by Google AI ADK and Gemini 2.5 Flash with a modern frontend built using Vue 3.

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🌟 Key Features

• Syllabus Generation: Create a step-by-step roadmap for any topic. Each milestone includes clear explanations, core concepts, and realistic timeframes.
• Project Scoping: Design a "Starter Project" for every syllabus that is practical, achievable, and integrates the skills learned from the roadmap.
• Mentorship Matching: Identify professional roles relevant to the user's goals and recommend the types of mentors they should connect with from the database.
• Adaptive Logic: The AI adjusts content based on the user's background; skipping fundamentals they already know to jump straight into advanced topics.

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🛠️ Tech Stack

Backend (AI Agent)

• Engine: Google Generative AI ADK
• Model: gemini-2.5-flash (via Vertex AI)
• Framework: FastAPI / Uvicorn
• Package Manager: uv

Frontend (User Interface)

• Framework: Vue 3 + Vite
• Styling: Vanilla CSS (Premium Dark Mode & Glassmorphism)
• Animations: GSAP
• State Management: Vue Composition API

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📂 Folder Structure

.
├── AI/                         # Backend AI Folder
│   ├── roadmap/                # Core ADK Agent logic (Roadmap engine)
│   ├── scripts/                # Utility scripts (setup, database)
│   ├── .env                    # Environment Config (API Keys, Project ID)
│   ├── server.py               # Backend API Entry Point
│   └── tools.yaml              # Tool definitions for MCP Toolbox
├── frontend/                   # Frontend Web App Folder
│   ├── src/
│   │   ├── components/         # UI Components (Chat bubbles, Suggestions, etc.)
│   │   ├── services/           # API Integration (api.js)
│   │   └── composables/        # Chat & State Logic (useChat.js)
│   └── vite.config.js          # API Proxy Configuration
└── README.md                   # Project Documentation

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🚀 Getting Started

1. Backend Setup

Ensure you have uv installed and access to a Google Cloud Project.

cd AI
# 1. Environment Setup
# Create an .env file based on the provided template
# GOOGLE_CLOUD_PROJECT=your-project-id
# ADK_MODEL=gemini-2.5-flash

# 2. Run the Backend Server
uv run python server.py

The backend server will run at http://localhost:8080.

2. Frontend Setup

cd frontend
# 1. Install Dependencies
npm install

# 2. Start the Development Server
npm run dev

Open http://localhost:5173 in your browser.

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📝 AI Usage Guide

• Requesting a Roadmap: Type "Create a crash course on Learning Python for Data Science"
• Adjusting Difficulty: Type "I already understand JavaScript, please create a mid-level React roadmap"
• Final Project: The AI will automatically provide a project idea at the end of every syllabus generation.

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🤝 Contribution

This project was developed to make it easier for anyone to start learning something new in a structured way. Feel free to fork the repository and submit a Pull Request if you have any improvement ideas!

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Powered by Google ADK & Gemini 2.5 Flash