📚 Study Agent

An AI-powered study assistant that helps students learn from their own study materials using Retrieval-Augmented Generation (RAG) and Agentic AI.

✨ Features

• 📄 Upload PDF lecture notes
• 🔍 Semantic search with ChromaDB
• 💬 Ask questions about uploaded documents
• 📝 AI-generated summaries
• 🧠 Flashcard generation
• ❓ Quiz generation
• 📅 Personalized study plans
• 📊 Progress tracking

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🏗️ Architecture

User
  │
FastAPI / Streamlit
  │
Orchestrator Agent
  ├── RAG Agent
  ├── Summary Agent
  ├── Quiz Agent
  ├── Flashcard Agent
  ├── Planner Agent
  └── Progress Agent

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🛠️ Tech Stack

• Python
• FastAPI
• PydanticAI
• ChromaDB
• Pydantic
• Streamlit / React
• Docker
• GitHub Actions

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📂 Project Structure

app/
 ├── agents/
 ├── rag/
 ├── memory/
 ├── tools/
 ├── prompts/
 ├── schemas/
 ├── models/
 └── main.py

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⚙️ Environment Variables

Create a .env file:

OPENAI_API_KEY=
EMBEDDING_MODEL=
CHROMA_PATH=

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▶️ Run

uv run python -m app.main

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🧪 Example Workflow

1. Upload a PDF.
2. The document is parsed and chunked.
3. Chunks are converted into embeddings.
4. ChromaDB indexes the embeddings.
5. Ask questions about the document.
6. Generate summaries, quizzes, and flashcards.

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📌 Roadmap

• PDF Upload
• RAG Pipeline
• Semantic Search
• Multi-Agent Workflow
• Study Planner
• Memory
• Tools
  • Web Search Integration
  • ...
• API
• UI
• Progress Tracking
• Voice Assistant

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📜 License

MIT License.