# Clean WebSocket Implementation - Status Report

## Architecture Overview

### Clean KISS Design (Divide and Conquer)
```
Frontend WebSocket → Gateway (Token Verification Only) → Training Service WebSocket → RabbitMQ Events → Broadcast to All Clients
```

## ✅ COMPLETED Components

### 1. WebSocket Connection Manager (`services/training/app/websocket/manager.py`)
- **Status**: ✅ COMPLETE
- Simple connection manager for WebSocket clients
- Thread-safe connection tracking per job_id
- Broadcasting capability to all connected clients
- Auto-cleanup of failed connections

### 2. RabbitMQ Event Consumer (`services/training/app/websocket/events.py`)
- **Status**: ✅ COMPLETE
- Global consumer that listens to all training.* events
- Automatically broadcasts events to WebSocket clients
- Maps RabbitMQ event types to WebSocket message types
- Sets up on service startup

### 3. Clean Event Publishers (`services/training/app/services/training_events.py`)
- **Status**: ✅ COMPLETE
- **4 Main Events** as specified:
  1. `publish_training_started()` - 0% progress
  2. `publish_data_analysis()` - 20% progress
  3. `publish_product_training_completed()` - contributes to 20-80% progress
  4. `publish_training_completed()` - 100% progress
  5. `publish_training_failed()` - error handling

### 4. WebSocket Endpoint (`services/training/app/api/websocket_operations.py`)
- **Status**: ✅ COMPLETE
- Simple endpoint at `/api/v1/tenants/{tenant_id}/training/jobs/{job_id}/live`
- Token validation
- Connection management
- Ping/pong support
- Receives broadcasts from RabbitMQ consumer

### 5. Gateway WebSocket Proxy (`gateway/app/main.py`)
- **Status**: ✅ COMPLETE
- **KISS**: Token verification ONLY
- Simple bidirectional forwarding
- No business logic
- Clean error handling

### 6. Parallel Product Progress Tracker (`services/training/app/services/progress_tracker.py`)
- **Status**: ✅ COMPLETE
- Thread-safe tracking of parallel product training
- Automatic progress calculation (20-80% range)
- Each product completion = 60/N% progress
- Emits `publish_product_training_completed` events

### 7. Service Integration (services/training/app/main.py`)
- **Status**: ✅ COMPLETE
- Added WebSocket router to FastAPI app
- Setup WebSocket event consumer on startup
- Cleanup on shutdown

### 8. Removed Legacy Code
- **Status**: ✅ COMPLETE
- ❌ Deleted all WebSocket code from `training_operations.py`
- ❌ Removed ConnectionManager, message cache, backfill logic
- ❌ Removed per-job RabbitMQ consumers
- ❌ Simplified event imports

## 🚧 PENDING Components

### 1. Update Training Service to Use New Events
- **File**: `services/training/app/services/training_service.py`
- **Current**: Uses old `TrainingStatusPublisher` with many granular events
- **Needed**: Replace with 4 clean events:
  ```python
  # 1. Start (0%)
  await publish_training_started(job_id, tenant_id, total_products)

  # 2. Data Analysis (20%)
  await publish_data_analysis(job_id, tenant_id, "Analysis details...")

  # 3. Product Training (20-80%) - use ParallelProductProgressTracker
  tracker = ParallelProductProgressTracker(job_id, tenant_id, total_products)
  # In parallel training loop:
  await tracker.mark_product_completed(product_name)

  # 4. Completion (100%)
  await publish_training_completed(job_id, tenant_id, successful, failed, duration)
  ```

### 2. Update Training Orchestrator/Trainer
- **File**: `services/training/app/ml/trainer.py` (likely)
- **Needed**: Integrate `ParallelProductProgressTracker` in parallel training loop
- Must emit event for each product completion (order doesn't matter)

### 3. Remove Old Messaging Module
- **File**: `services/training/app/services/messaging.py`
- **Status**: Still exists with old complex event publishers
- **Action**: Can be removed once training_service.py is updated
- Keep only the new `training_events.py`

### 4. Update Frontend WebSocket Client
- **File**: `frontend/src/api/hooks/training.ts`
- **Current**: Already well-implemented but expects certain message types
- **Needed**: Update to handle new message types:
  - `started` - 0%
  - `progress` - for data_analysis (20%)
  - `product_completed` - for each product (calculate 20 + (completed/total * 60))
  - `completed` - 100%
  - `failed` - error

### 5. Frontend Progress Calculation
- **Location**: Frontend WebSocket message handler
- **Logic Needed**:
  ```typescript
  case 'product_completed':
    const { products_completed, total_products } = message.data;
    const progress = 20 + Math.floor((products_completed / total_products) * 60);
    // Update UI with progress
    break;
  ```

## Event Flow Diagram

```
Training Start
    ↓
[Event 1: training.started] → 0% progress
    ↓
Data Analysis
    ↓
[Event 2: training.progress] → 20% progress (data_analysis step)
    ↓
Product Training (Parallel)
    ↓
[Event 3a: training.product.completed] → Product 1 done
[Event 3b: training.product.completed] → Product 2 done
[Event 3c: training.product.completed] → Product 3 done
... (progress calculated as: 20 + (completed/total * 60))
    ↓
[Event 3n: training.product.completed] → Product N done → 80% progress
    ↓
Training Complete
    ↓
[Event 4: training.completed] → 100% progress
```

## Key Design Principles

1. **KISS (Keep It Simple, Stupid)**
   - No complex caching or backfilling
   - No per-job consumers
   - One global consumer broadcasts to all clients
   - Simple, stateless WebSocket connections

2. **Divide and Conquer**
   - Gateway: Token verification only
   - Training Service: WebSocket connections + RabbitMQ consumer
   - Progress Tracker: Parallel training progress
   - Event Publishers: 4 simple event types

3. **No Backward Compatibility**
   - Deleted all legacy WebSocket code
   - Clean slate implementation
   - No TODOs (implement everything)

## Next Steps

1. Update `training_service.py` to use new event publishers
2. Update trainer to integrate `ParallelProductProgressTracker`
3. Remove old `messaging.py` module
4. Update frontend WebSocket client message handlers
5. Test end-to-end flow
6. Monitor WebSocket connections in production

## Testing Checklist

- [ ] WebSocket connection established through gateway
- [ ] Token verification works (valid and invalid tokens)
- [ ] Event 1 (started) received with 0% progress
- [ ] Event 2 (data_analysis) received with 20% progress
- [ ] Event 3 (product_completed) received for each product
- [ ] Progress correctly calculated (20 + completed/total * 60)
- [ ] Event 4 (completed) received with 100% progress
- [ ] Error events handled correctly
- [ ] Multiple concurrent clients receive same events
- [ ] Connection survives network hiccups
- [ ] Clean disconnection when training completes

## Files Modified

### Created:
- `services/training/app/websocket/manager.py`
- `services/training/app/websocket/events.py`
- `services/training/app/websocket/__init__.py`
- `services/training/app/api/websocket_operations.py`
- `services/training/app/services/training_events.py`
- `services/training/app/services/progress_tracker.py`

### Modified:
- `services/training/app/main.py` - Added WebSocket router and event consumer setup
- `services/training/app/api/training_operations.py` - Removed all WebSocket code
- `gateway/app/main.py` - Simplified WebSocket proxy

### To Remove:
- `services/training/app/services/messaging.py` - Replace with `training_events.py`

## Notes

- RabbitMQ exchange: `training.events`
- Routing keys: `training.*` (wildcard for all events)
- WebSocket URL: `ws://gateway/api/v1/tenants/{tenant_id}/training/jobs/{job_id}/live?token={token}`
- Progress range: 0% → 20% → 20-80% (products) → 100%
- Each product contributes: 60/N% where N = total products