# CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

## Project Overview

Reflector is an AI-powered audio transcription and meeting analysis platform with real-time processing capabilities. The system consists of:

- **Frontend**: Next.js 14 React application (`www/`) with Chakra UI, real-time WebSocket integration
- **Backend**: Python FastAPI server (`server/`) with async database operations and background processing
- **Processing**: GPU-accelerated ML pipeline for transcription, diarization, summarization via Modal.com
- **Infrastructure**: Redis, PostgreSQL/SQLite, Celery workers, WebRTC streaming

## Development Commands

### Backend (Python) - `cd server/`

**Setup and Dependencies:**
```bash
# Install dependencies
uv sync

# Database migrations (first run or schema changes)
uv run alembic upgrade head

# Start services
docker compose up -d redis
```

**Development:**
```bash
# Start FastAPI server
uv run -m reflector.app --reload

# Start Celery worker for background tasks
uv run celery -A reflector.worker.app worker --loglevel=info

# Start Celery beat scheduler (optional, for cron jobs)
uv run celery -A reflector.worker.app beat
```

**Testing:**
```bash
# Run all tests with coverage
uv run pytest

# Run specific test file
uv run pytest tests/test_transcripts.py

# Run tests with verbose output
uv run pytest -v
```

**Process Audio Files:**
```bash
# Process local audio file manually
uv run python -m reflector.tools.process path/to/audio.wav
```

### Frontend (Next.js) - `cd www/`

**Setup:**
```bash
# Install dependencies
yarn install

# Copy configuration templates
cp .env_template .env
cp config-template.ts config.ts
```

**Development:**
```bash
# Start development server
yarn dev

# Generate TypeScript API client from OpenAPI spec
yarn openapi

# Lint code
yarn lint

# Format code
yarn format

# Build for production
yarn build
```

### Docker Compose (Full Stack)

```bash
# Start all services
docker compose up -d

# Start specific services
docker compose up -d redis server worker
```

## Architecture Overview

### Backend Processing Pipeline

The audio processing follows a modular pipeline architecture:

1. **Audio Input**: WebRTC streaming, file upload, or cloud recording ingestion
2. **Chunking**: Audio split into processable segments (`AudioChunkerProcessor`)
3. **Transcription**: Whisper or Modal.com GPU processing (`AudioTranscriptAutoProcessor`)
4. **Diarization**: Speaker identification (`AudioDiarizationAutoProcessor`)
5. **Text Processing**: Formatting, translation, topic detection
6. **Summarization**: AI-powered summaries and title generation
7. **Storage**: Database persistence with optional S3 backend

### Database Models

Core entities:
- `transcript`: Main table with processing results, summaries, topics, participants
- `meeting`: Live meeting sessions with consent management
- `room`: Virtual meeting spaces with configuration
- `recording`: Audio/video file metadata and processing status

### API Structure

All endpoints prefixed `/v1/`:
- `transcripts/` - CRUD operations for transcripts
- `transcripts_audio/` - Audio streaming and download
- `transcripts_webrtc/` - Real-time WebRTC endpoints
- `transcripts_websocket/` - WebSocket for live updates
- `meetings/` - Meeting lifecycle management
- `rooms/` - Virtual room management

### Frontend Architecture

- **App Router**: Next.js 14 with route groups for organization
- **State**: React Context pattern, no Redux
- **Real-time**: WebSocket integration for live transcription updates
- **Auth**: NextAuth.js with Authentik OAuth/OIDC provider
- **UI**: Chakra UI components with Tailwind CSS utilities

## Key Configuration

### Environment Variables

**Backend** (`server/.env`):
- `DATABASE_URL` - Database connection string
- `REDIS_URL` - Redis broker for Celery
- `MODAL_TOKEN_ID`, `MODAL_TOKEN_SECRET` - Modal.com GPU processing
- `WHEREBY_API_KEY` - Video platform integration
- `REFLECTOR_AUTH_BACKEND` - Authentication method (none, jwt)

**Frontend** (`www/.env`):
- `NEXTAUTH_URL`, `NEXTAUTH_SECRET` - Authentication configuration
- `NEXT_PUBLIC_REFLECTOR_API_URL` - Backend API endpoint
- `REFLECTOR_DOMAIN_CONFIG` - Feature flags and domain settings

## Testing Strategy

- **Backend**: pytest with async support, HTTP client mocking, audio processing tests
- **Frontend**: No current test suite - opportunities for Jest/React Testing Library
- **Coverage**: Backend maintains test coverage reports in `htmlcov/`

## GPU Processing

Modal.com integration for scalable ML processing:
- Deploy changes: `modal run server/gpu/path/to/model.py`
- Requires Modal account with `REFLECTOR_GPU_APIKEY` secret
- Fallback to local processing when Modal unavailable

## Common Issues

- **Permissions**: Browser microphone access required in System Preferences
- **Audio Routing**: Use BlackHole (Mac) for merging multiple audio sources
- **WebRTC**: Ensure proper CORS configuration for cross-origin streaming
- **Database**: Run `uv run alembic upgrade head` after pulling schema changes