README.md

metadata

title: ScratchLM
emoji: 🎓
colorFrom: purple
colorTo: blue
sdk: docker
app_port: 7860
pinned: false

ScratchLM

Zero-DB AI Study Assistant - Upload PDFs, extract content, and get AI-powered cheatsheets and interactive tutoring.

✨ Key Features

📄 Local PDF Processing

• Drag & Drop Upload: Upload multiple PDFs directly in your browser
• Local Extraction: Text extraction happens entirely on the server
• Multi-Document Support: Process multiple PDFs simultaneously with clear demarcation

📚 AI-Powered Cheatsheet Generator

• 4-Zone Structure: Automatically generates comprehensive study guides:
  • Zone A: Concept Deep-Dive
  • Zone B: Real-World Analogies
  • Zone C: Worked Problems
  • Zone D: Exam Traps & Strategy
• Markdown Export: Download cheatsheets as .md files for Obsidian, Notion, or any笔记 app

💬 RAG Chat with Full Context

• Document-Aware: Chat remembers everything from your uploaded PDFs
• Conversation History: Multi-turn dialogues with context retention
• Step-by-Step Teaching: AI tutor explains concepts rather than just answering

🔒 Privacy First

• Zero Database: No user data stored anywhere
• Session Isolation: Each browser tab is isolated
• One-Click Wipe: Refresh the page to clear all data

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🎓 AI Architecture

Model: Gemma 4 31B IT

The app uses Gemma 4 31B Instruction-Tuned model via Google AI Studio API for:

• Complex reasoning and explanation generation
• Multi-step problem solving
• Conceptual teaching with analogies

PDF Processing: pypdf

• Pure Python PDF text extraction
• No external services or cloud dependencies
• Preserves document structure and page breaks

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🛠️ Technical Stack

Component	Technology
Web Framework	FastAPI
Frontend	Vanilla HTML/CSS/JS
AI Model	Gemma 4 31B IT
PDF Parsing	pypdf
Markdown Rendering	marked.js

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🚀 Getting Started

Prerequisites

• A Google AI Studio API key (free tier available)
• Docker (for local development)

Local Setup

1. Clone the repository:

   git clone https://huggingface.co/spaces/mingnatthakitt/ScratchLM
   

2. Set up environment variable:

   export GEMINI_API_KEY="your_api_key_here"
   

3. Run with Docker:

   docker build -t scratchlm .
   docker run -p 7860:7860 -e GEMINI_API_KEY=$GEMINI_API_KEY scratchlm
   

   Or run without Docker:

   pip install -r requirements.txt
   python app.py
   

4. Open in browser: Navigate to http://localhost:7860

Hugging Face Spaces

1. Fork the Space: Clone it to your account
2. Add Secrets: Go to Space Settings → Repository secrets → Add GEMINI_API_KEY
3. Done: The Space will automatically build and run

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📖 How to Use

Step 1: Upload PDFs

Drag and drop PDF files onto the upload area, or click to browse.

Step 2: Extract Text

Click ⚡ Extract to process your documents. The extracted text will appear in the preview panel.

Step 3: Generate Cheatsheet

Click ✨ Generate to create a comprehensive 4-zone study guide from your documents.

Step 4: Download or Chat

• 📥 Download .md: Save the cheatsheet as a Markdown file
• 💬 Chat: Ask questions about your documents with full context awareness

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⚖️ License

GNU Affero General Public License v3.0 (AGPL-3.0)

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License along with this program. If not, see https://www.gnu.org/licenses/agpl-3.0.en.html.

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🙏 Acknowledgments

• Google AI for providing Gemma models via AI Studio
• Hugging Face for the Spaces infrastructure
• FastAPI for the excellent web framework