---
title: FocusFlow
emoji: 🎯
colorFrom: purple
colorTo: indigo
sdk: docker
app_file: app.py
pinned: false
---

# FocusFlow - AI Study Companion

An intelligent study assistant powered by AI that transforms your learning materials into personalized, adaptive study experiences.

[Try FocusFlow on Hugging Face Spaces](https://huggingface.co/spaces/noodledom/focusflow)

## Features

- **Multi-Subject Study Planning**: Upload PDFs and get automated multi-day study plans.
- **RAG-Powered Q&A**: Ask questions and get answers with source citations.
- **Adaptive Quizzes**: Context-based quizzes that adapt to your performance.
- **Progress Tracking**: Track mastery levels and quiz history.
- **Cloud Persistence**: Study plans and progress persist across sessions.
- **Multi-User Support**: Firebase Authentication enables secure, isolated data per user.

## Local Installation

### Prerequisites
- Python 3.10+
- [Ollama](https://ollama.ai/) installed and running
- 8GB+ RAM recommended

### Quick Start

```bash
# Clone the repository
git clone https://github.com/suwethadevakiruba3012-wq/Free.git
cd Free

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

# Install dependencies
pip install -r requirements.txt

# Pull required Ollama models
ollama pull llama3.2:1b
ollama pull nomic-embed-text

# Start the backend
uvicorn backend.main:app --reload &

# Start the frontend
streamlit run app.py
```

Visit `http://localhost:8501` to use the app.

## Tech Stack

- **Frontend**: Streamlit + Material Design
- **Backend**: FastAPI + LangChain
- **Vector DB**: ChromaDB
- **LLM**: Ollama (local) / HuggingFace (cloud)
- **Database**: Supabase PostgreSQL (cloud) / JSON files (local)