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bakery-ia/services/training/app/api/websocket.py

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# services/training/app/api/websocket.py
"""
WebSocket endpoints for real-time training progress updates
"""
import json
import asyncio
from typing import Dict, Any
from fastapi import WebSocket, WebSocketDisconnect, Depends, HTTPException
from fastapi.routing import APIRouter
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import structlog
logger = structlog.get_logger(__name__)
from app.services.messaging import training_publisher
from shared.auth.decorators import (
get_current_user_dep,
get_current_tenant_id_dep
)
# Create WebSocket router
websocket_router = APIRouter()
class ConnectionManager:
"""Manage WebSocket connections for training progress"""
def __init__(self):
self.active_connections: Dict[str, Dict[str, WebSocket]] = {}
# Structure: {job_id: {connection_id: websocket}}
async def connect(self, websocket: WebSocket, job_id: str, connection_id: str):
"""Accept WebSocket connection and register it"""
await websocket.accept()
if job_id not in self.active_connections:
self.active_connections[job_id] = {}
self.active_connections[job_id][connection_id] = websocket
logger.info(f"WebSocket connected for job {job_id}, connection {connection_id}")
def disconnect(self, job_id: str, connection_id: str):
"""Remove WebSocket connection"""
if job_id in self.active_connections:
self.active_connections[job_id].pop(connection_id, None)
if not self.active_connections[job_id]:
del self.active_connections[job_id]
logger.info(f"WebSocket disconnected for job {job_id}, connection {connection_id}")
async def send_to_job(self, job_id: str, message: dict):
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"""Send message to all connections for a specific job with better error handling"""
if job_id not in self.active_connections:
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logger.debug(f"No active connections for job {job_id}")
return
# Send to all connections for this job
disconnected_connections = []
for connection_id, websocket in self.active_connections[job_id].items():
try:
await websocket.send_json(message)
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logger.debug(f"📤 Sent {message.get('type', 'unknown')} to connection {connection_id}")
except Exception as e:
logger.warning(f"Failed to send message to connection {connection_id}: {e}")
disconnected_connections.append(connection_id)
# Clean up disconnected connections
for connection_id in disconnected_connections:
self.disconnect(job_id, connection_id)
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# Log successful sends
active_count = len(self.active_connections.get(job_id, {}))
if active_count > 0:
logger.info(f"📡 Sent {message.get('type', 'unknown')} message to {active_count} connection(s) for job {job_id}")
# Global connection manager
connection_manager = ConnectionManager()
@websocket_router.websocket("/tenants/{tenant_id}/training/jobs/{job_id}/live")
async def training_progress_websocket(
websocket: WebSocket,
tenant_id: str,
job_id: str
):
"""
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FIXED WebSocket endpoint for real-time training progress updates
Prevents premature disconnection during training
"""
connection_id = f"{tenant_id}_{id(websocket)}"
# Accept connection
await connection_manager.connect(websocket, job_id, connection_id)
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logger.info(f"WebSocket connection established for job {job_id}")
# Set up RabbitMQ consumer for this job
consumer_task = None
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training_completed = False # Track training completion
try:
# Start RabbitMQ consumer
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logger.info(f"Setting up RabbitMQ consumer for job {job_id}")
consumer_task = asyncio.create_task(
setup_rabbitmq_consumer_for_job(job_id, tenant_id)
)
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# Give consumer time to set up
await asyncio.sleep(0.5)
# Send initial status if available
try:
initial_status = await get_current_job_status(job_id, tenant_id)
if initial_status:
await websocket.send_json({
"type": "initial_status",
"job_id": job_id,
"data": initial_status
})
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logger.info(f"Sent initial status for job {job_id}")
except Exception as e:
logger.warning(f"Failed to send initial status: {e}")
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# Keep connection alive - IMPROVED ERROR HANDLING
last_activity = asyncio.get_event_loop().time()
while not training_completed:
try:
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# Wait for client messages with timeout
try:
message = await asyncio.wait_for(websocket.receive_text(), timeout=30.0)
last_activity = asyncio.get_event_loop().time()
if message == "ping":
await websocket.send_text("pong")
logger.debug(f"Ping received from job {job_id}")
elif message == "get_status":
current_status = await get_current_job_status(job_id, tenant_id)
if current_status:
await websocket.send_json({
"type": "current_status",
"job_id": job_id,
"data": current_status
})
elif message == "close":
logger.info(f"Client requested connection close for job {job_id}")
break
except asyncio.TimeoutError:
# No message received in 30 seconds - send heartbeat
current_time = asyncio.get_event_loop().time()
if current_time - last_activity > 60: # 60 seconds of inactivity
logger.warning(f"Long inactivity period for job {job_id}, sending heartbeat")
try:
await websocket.send_json({
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"type": "heartbeat",
"job_id": job_id,
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"timestamp": datetime.utcnow().isoformat()
})
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except Exception as e:
logger.error(f"Failed to send heartbeat for job {job_id}: {e}")
break
except WebSocketDisconnect:
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logger.info(f"WebSocket client disconnected for job {job_id}")
break
except Exception as e:
logger.error(f"WebSocket error for job {job_id}: {e}")
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# Don't break immediately - try to recover
await asyncio.sleep(1)
logger.info(f"WebSocket loop ended for job {job_id}, training_completed: {training_completed}")
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except Exception as e:
logger.error(f"Critical WebSocket error for job {job_id}: {e}")
finally:
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# IMPROVED CLEANUP - Don't cancel consumer unless truly disconnecting
logger.info(f"Cleaning up WebSocket connection for job {job_id}")
connection_manager.disconnect(job_id, connection_id)
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# Only cancel consumer if we're truly done (not just a temporary error)
if consumer_task and not consumer_task.done():
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if training_completed:
logger.info(f"Training completed, cancelling consumer for job {job_id}")
consumer_task.cancel()
else:
logger.warning(f"WebSocket disconnected but training not completed for job {job_id}")
# Let the consumer continue running for other potential connections
# Don't cancel it unless we're sure the job is done
try:
await consumer_task
except asyncio.CancelledError:
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logger.info(f"Consumer task cancelled for job {job_id}")
except Exception as e:
logger.error(f"Consumer task error for job {job_id}: {e}")
async def setup_rabbitmq_consumer_for_job(job_id: str, tenant_id: str):
"""Set up RabbitMQ consumer to listen for training events for a specific job"""
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logger.info(f"🚀 Setting up RabbitMQ consumer for job {job_id}")
try:
# Create a unique queue for this WebSocket connection
queue_name = f"websocket_training_{job_id}_{tenant_id}"
async def handle_training_message(message):
"""Handle incoming RabbitMQ messages and forward to WebSocket"""
try:
# Parse the message
body = message.body.decode()
data = json.loads(body)
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logger.debug(f"🔍 Received message for job {job_id}: {data.get('event_type', 'unknown')}")
# Extract event data
event_type = data.get("event_type", "unknown")
event_data = data.get("data", {})
# Only process messages for this specific job
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message_job_id = event_data.get("job_id") if event_data else None
if message_job_id != job_id:
logger.debug(f"⏭️ Ignoring message for different job: {message_job_id}")
await message.ack()
return
# Transform RabbitMQ message to WebSocket message format
websocket_message = {
"type": map_event_type_to_websocket_type(event_type),
"job_id": job_id,
"timestamp": data.get("timestamp"),
"data": event_data
}
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logger.info(f"📤 Forwarding {event_type} message to WebSocket clients for job {job_id}")
# Send to all WebSocket connections for this job
await connection_manager.send_to_job(job_id, websocket_message)
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# Check if this is a completion message
if event_type in ["training.completed", "training.failed"]:
logger.info(f"🎯 Training completion detected for job {job_id}: {event_type}")
# Mark training as completed (you might want to store this in a global state)
# For now, we'll let the WebSocket handle this through the message
# Acknowledge the message
await message.ack()
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logger.debug(f"✅ Successfully processed {event_type} for job {job_id}")
except Exception as e:
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logger.error(f"❌ Error handling training message for job {job_id}: {e}")
import traceback
logger.error(f"💥 Traceback: {traceback.format_exc()}")
await message.nack(requeue=False)
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# Check if training_publisher is connected
if not training_publisher.connected:
logger.warning(f"⚠️ Training publisher not connected for job {job_id}, attempting to connect...")
success = await training_publisher.connect()
if not success:
logger.error(f"❌ Failed to connect training_publisher for job {job_id}")
return
# Subscribe to training events
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logger.info(f"🔗 Subscribing to training events for job {job_id}")
success = await training_publisher.consume_events(
exchange_name="training.events",
queue_name=queue_name,
routing_key="training.*", # Listen to all training events
callback=handle_training_message
)
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if success:
logger.info(f"✅ Successfully set up RabbitMQ consumer for job {job_id} (queue: {queue_name})")
# Keep the consumer running indefinitely until cancelled
try:
while True:
await asyncio.sleep(10) # Keep consumer alive
logger.debug(f"🔄 Consumer heartbeat for job {job_id}")
except asyncio.CancelledError:
logger.info(f"🛑 Consumer cancelled for job {job_id}")
raise
except Exception as e:
logger.error(f"💥 Consumer error for job {job_id}: {e}")
raise
else:
logger.error(f"❌ Failed to set up RabbitMQ consumer for job {job_id}")
except Exception as e:
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logger.error(f"💥 Exception in setup_rabbitmq_consumer_for_job for job {job_id}: {e}")
import traceback
logger.error(f"🔥 Traceback: {traceback.format_exc()}")
def map_event_type_to_websocket_type(rabbitmq_event_type: str) -> str:
"""Map RabbitMQ event types to WebSocket message types"""
mapping = {
"training.started": "started",
"training.progress": "progress",
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"training.completed": "completed", # This is the key completion event
"training.failed": "failed", # This is also a completion event
"training.cancelled": "cancelled",
"training.step.completed": "step_completed",
"training.product.started": "product_started",
"training.product.completed": "product_completed",
"training.product.failed": "product_failed",
"training.model.trained": "model_trained",
"training.data.validation.started": "validation_started",
"training.data.validation.completed": "validation_completed"
}
return mapping.get(rabbitmq_event_type, "unknown")
async def get_current_job_status(job_id: str, tenant_id: str) -> Dict[str, Any]:
"""Get current job status from database or cache"""
try:
# This should query your database for current job status
# For now, return a placeholder - implement based on your database schema
from app.core.database import get_db_session
from app.models.training import ModelTrainingLog # Assuming you have this model
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# async with get_background_db_session() as db:
# Query your training job status
# This is a placeholder - adjust based on your actual database models
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# pass
# Placeholder return - replace with actual database query
return {
"job_id": job_id,
"status": "running", # or "completed", "failed", etc.
"progress": 0,
"current_step": "Starting...",
"started_at": "2025-07-30T19:00:00Z"
}
except Exception as e:
logger.error(f"Failed to get current job status: {e}")
return None