bakery-ia/WEBSOCKET_CLEAN_IMPLEMENTATION_STATUS.md

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:

  # 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:

  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