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Contributor Guide: Repository Guidelines
- User Guide - Comprehensive guide for end users
- Quick Start - Get up and running in 5 minutes
- Installation Guide - Detailed installation instructions
- Developer Tutorial - Complete development guide
- API Documentation - Comprehensive API reference
- Component Documentation - React component reference
- Architecture Overview - System design and architecture
- Backend Guide - FastAPI backend details
- Frontend Guide - React frontend architecture
- Electron Guide - Desktop app implementation
- Performance Guide - Monitoring and optimization
- Security Guide - Security best practices
- Testing Guide - Testing strategies and CI/CD
- Operations Guide - Deployment and maintenance
- Documentation Standards - Writing and maintenance guidelines
- Contributing Guidelines - How to contribute to the project
- App dev (first time):
cd notebook-mlx-app && pnpm installcd backend && pip install -r requirements.txt && cd ..
- Frontend only:
cd notebook-mlx-app/frontend && pnpm start - Backend only:
cd notebook-mlx-app/backend && uvicorn main:app --reload - Electron (all-in-one):
cd notebook-mlx-app && pnpm start - Docker (backend):
docker compose up --build(serves on:8000)
I ported NotebookLlama and implemented it with MLX 🔥
It uses mlx-community/Qwen2.5-1.5B-Instruct-4bit for pre-processing the PDF, mlx-community/Qwen2.5-14B-Instruct-4bit for creating transcripts, mlx-community/Qwen2.5-7B-Instruct-4bit for rewrites, and lucasnewman/f5-tts-mlx for Text-to-Speech ⚡
Citing the NotebookLlama outline.
Step 1: Pre-process PDF: Use mlx-community/Qwen2.5-1.5B-Instruct-4bit to pre-process the PDF and save it in a .txt file.
Step 2: Transcript Writer: Use mlx-community/Qwen2.5-14B-Instruct-4bit to write a podcast transcript from the text.
Step 3: Dramatic Re-Writer: Use the mlx-community/Qwen2.5-7B-Instruct-4bit model to make the transcript more dramatic.
Step 4: Text-To-Speech Workflow: Use lucasnewman/f5-tts-mlx to generate a conversational podcast.