focusflow / README.md
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metadata
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

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 installed and running
  • 8GB+ RAM recommended

Quick Start

# 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)