managarten/apps-archived/wisekeep/CLAUDE.md

CLAUDE.md - Wisekeep

This file provides guidance to Claude Code when working with the Wisekeep project.

Project Overview

Wisekeep is an AI-powered wisdom extraction application that captures insights from video content:

• YouTube video download via yt-dlp
• Ultra-fast audio transcription using Groq Whisper API (~300x realtime)
• Fallback to local Whisper for offline use
• Playlist management for batch processing
• Real-time progress updates via WebSocket
• Multi-platform support (Web, Mobile, Landing)

Architecture

apps/wisekeep/
├── apps/
│   ├── backend/       # NestJS API server (port 3006)
│   ├── web/           # SvelteKit web application
│   ├── landing/       # Astro landing/content site
│   └── mobile/        # Expo React Native app
├── packages/
│   └── shared-types/  # Shared TypeScript types
├── data/              # Transcripts & playlists (gitignored)
├── legacy/            # Original Python code (reference)
├── package.json       # Root orchestrator
└── CLAUDE.md          # This file

Quick Start

Prerequisites

• Node.js 20+
• pnpm 9.15.0+
• yt-dlp installed (brew install yt-dlp on macOS)
• For local Whisper: Python 3 with openai-whisper package

Development

# From monorepo root
pnpm install

# Start all wisekeep apps
pnpm wisekeep:dev

# Start individual apps
pnpm dev:wisekeep:backend   # NestJS backend (port 3006)
pnpm dev:wisekeep:web       # SvelteKit web (port 5173)
pnpm dev:wisekeep:landing   # Astro landing (port 4321)
pnpm dev:wisekeep:mobile    # Expo mobile

# Start web + backend together
pnpm dev:wisekeep:app

Environment Variables

Create apps/wisekeep/apps/backend/.env:

PORT=3006
WHISPER_PROVIDER=groq         # groq or local
WHISPER_MODEL=whisper-large-v3-turbo  # whisper-large-v3-turbo, whisper-large-v3 (groq) | tiny, base, small, medium, large (local)
GROQ_API_KEY=gsk_...          # Required for Groq provider
TEMP_AUDIO_DIR=./temp_audio
TRANSCRIPTS_DIR=./data/transcripts
PLAYLISTS_DIR=./data/playlists

API Endpoints

Transcription

Method	Endpoint	Description
POST	/transcription	Start new transcription job
GET	/transcription	List all jobs
GET	/transcription/:id	Get job status
DELETE	/transcription/:id	Cancel job
GET	/transcription/stats	Get statistics

Playlists

Method	Endpoint	Description
GET	/playlist	List all playlists
GET	/playlist/:category/:name	Get specific playlist
POST	/playlist	Create playlist
DELETE	/playlist/:category/:name	Delete playlist

Whisper

Method	Endpoint	Description
GET	/whisper/models	Get available models

Health

Method	Endpoint	Description
GET	/health	Health check
GET	/health/ready	Readiness check
GET	/health/live	Liveness check

WebSocket

Connect to /progress namespace for real-time updates:

const socket = io('http://localhost:3006/progress');

socket.on('job_update', (data) => {
	// { type, jobId, status, progress, videoInfo }
});

socket.on('job_complete', (data) => {
	// { type, jobId, status, transcriptPath }
});

socket.on('job_error', (data) => {
	// { type, jobId, error }
});

Whisper Configuration

Groq Whisper API (Recommended)

• Ultra-fast, cloud-based (~300x realtime speed)
• Cost: ~$0.04/hour (whisper-large-v3-turbo) or ~$0.111/hour (whisper-large-v3)
• No GPU required
• Models: whisper-large-v3-turbo (fast) or whisper-large-v3 (accurate)
• Set WHISPER_PROVIDER=groq and GROQ_API_KEY

Local Whisper

• Free, runs locally
• Requires Python + openai-whisper
• GPU recommended for larger models
• Models: tiny, base, small, medium, large
• Set WHISPER_PROVIDER=local and WHISPER_MODEL

Technology Stack

Component	Technology
Backend	NestJS 10, TypeScript
Web	SvelteKit 2, Svelte 5, Tailwind
Landing	Astro 4, Tailwind
Mobile	Expo 52, React Native, NativeWind
YouTube	yt-dlp (via child_process)
Transcription	Groq Whisper API / local Whisper
Real-time	Socket.io
State (Mobile)	Zustand

Code Patterns

Backend Services

@Injectable()
export class TranscriptionService {
	async createJob(dto: TranscribeRequestDto): Promise<TranscriptionJob> {
		// Background processing with WebSocket updates
	}
}

Web (Svelte 5 Runes)

// Correct - Svelte 5
let jobs = $state<Job[]>([]);
let activeJobs = $derived(jobs.filter((j) => j.status === 'active'));

// Wrong - Old Svelte syntax
let jobs = [];
$: activeJobs = jobs.filter((j) => j.status === 'active');

Mobile (Zustand)

export const useJobStore = create<JobStore>((set) => ({
	jobs: [],
	addJob: (job) => set((state) => ({ jobs: [...state.jobs, job] })),
}));

Legacy Python Code

The original Python implementation is preserved in legacy/ for reference:

• transcriber_v4_parallel.py - Main transcription logic
• api_server.py - FastAPI server (replaced by NestJS)
• requirements.txt - Python dependencies

Troubleshooting

yt-dlp not found

# macOS
brew install yt-dlp

# Linux
pip install yt-dlp

Local Whisper not working

# Install Whisper
pip install openai-whisper

# Test
python3 -c "import whisper; print(whisper.available_models())"

Backend can't start

# Check port 3006
lsof -i :3006 && kill -9 $(lsof -t -i:3006)

# Check environment
cat apps/backend/.env