Start fixing forecast service API 3

services/forecasting/app/api/forecasts.py

@@ -47,7 +47,7 @@ async def create_single_forecast(
             )
         
         # Generate forecast
-        forecast = await forecasting_service.generate_forecast(request, db)
+        forecast = await forecasting_service.generate_forecast(tenant_id, request, db)
         
         # Convert to response model
         return ForecastResponse(

services/forecasting/app/schemas/forecasts.py

@@ -24,14 +24,7 @@ class ForecastRequest(BaseModel):
     """Request schema for generating forecasts"""
     tenant_id: str = Field(..., description="Tenant ID")
     product_name: str = Field(..., description="Product name")
-    location: str = Field(..., description="Location identifier")
     forecast_date: date = Field(..., description="Date for which to generate forecast")
-    business_type: BusinessType = Field(BusinessType.INDIVIDUAL, description="Business model type")
-    
-    # Optional context
-    include_weather: bool = Field(True, description="Include weather data in forecast")
-    include_traffic: bool = Field(True, description="Include traffic data in forecast")
-    confidence_level: float = Field(0.8, ge=0.5, le=0.95, description="Confidence level for intervals")
     
     @validator('forecast_date')
     def validate_forecast_date(cls, v):

services/forecasting/app/services/data_client.py

@@ -0,0 +1,64 @@
+# services/training/app/services/data_client.py
+"""
+Training Service Data Client
+Migrated to use shared service clients - much simpler now!
+"""
+
+import structlog
+from typing import Dict, Any, List, Optional
+from datetime import datetime
+
+# Import the shared clients
+from shared.clients import get_data_client, get_service_clients
+from app.core.config import settings
+
+logger = structlog.get_logger()
+
+class DataClient:
+    """
+    Data client for training service
+    Now uses the shared data service client under the hood
+    """
+    
+    def __init__(self):
+        # Get the shared data client configured for this service
+        self.data_client = get_data_client(settings, "forecasting")
+        
+        # Or alternatively, get all clients at once:
+        # self.clients = get_service_clients(settings, "training") 
+        # Then use: self.clients.data.get_sales_data(...)
+    
+    
+    async def fetch_weather_forecast(
+        self,
+        tenant_id: str,
+        days: str,
+        latitude: Optional[float] = None,
+        longitude: Optional[float] = None
+    ) -> List[Dict[str, Any]]:
+        """
+        Fetch weather data for forecats
+        All the error handling and retry logic is now in the base client!
+        """
+        try:
+            weather_data = await self.data_client.get_weather_forecast(
+                tenant_id=tenant_id,
+                days=days,
+                latitude=latitude,
+                longitude=longitude
+            )
+            
+            if weather_data:
+                logger.info(f"Fetched {len(weather_data)} weather records", 
+                           tenant_id=tenant_id)
+                return weather_data
+            else:
+                logger.warning("No weather data returned", tenant_id=tenant_id)
+                return []
+                
+        except Exception as e:
+            logger.error(f"Error fetching weather data: {e}", tenant_id=tenant_id)
+            return []
+
+# Global instance - same as before, but much simpler implementation
+data_client = DataClient()

services/forecasting/app/services/forecasting_service.py

@@ -21,6 +21,8 @@ from app.services.prediction_service import PredictionService
 from app.services.messaging import publish_forecast_completed, publish_alert_created
 from app.core.config import settings
 from shared.monitoring.metrics import MetricsCollector
+from app.services.model_client import ModelClient
+from app.services.data_client import DataClient
 
 logger = structlog.get_logger()
 metrics = MetricsCollector("forecasting-service")
@@ -33,6 +35,8 @@ class ForecastingService:
     
     def __init__(self):
         self.prediction_service = PredictionService()
+        self.model_client = ModelClient()
+        self.data_client = DataClient()
     
     async def generate_forecast(self, request: ForecastRequest, db: AsyncSession) -> Forecast:
         """Generate a single forecast for a product"""
@@ -48,7 +52,6 @@ class ForecastingService:
             model_info = await self._get_latest_model(
                 request.tenant_id, 
                 request.product_name,
-                request.location
             )
             
             if not model_info:
@@ -66,10 +69,9 @@ class ForecastingService:
             
             # Create forecast record
             forecast = Forecast(
-                tenant_id=uuid.UUID(request.tenant_id),
+                tenant_id=uuid.UUID(tenant_id),
-                product_name=request.product_name,
+                product_name=product_name,
-                location=request.location,
+                forecast_date=datetime.combine(forecast_date, datetime.min.time()),
-                forecast_date=datetime.combine(request.forecast_date, datetime.min.time()),
                 
                 # Prediction results
                 predicted_demand=prediction_result["demand"],
@@ -243,27 +245,12 @@ class ForecastingService:
             logger.error("Error retrieving forecasts", error=str(e))
             raise
     
-    async def _get_latest_model(self, tenant_id: str, product_name: str, location: str) -> Optional[Dict[str, Any]]:
+    async def _get_latest_model(self, tenant_id: str, product_name: str) -> Optional[Dict[str, Any]]:
         """Get the latest trained model for a tenant/product combination"""
         
         try:
-            # Call training service to get model information
+            model_data = await self.data_client.get_best_model_for_forecasting(tenant_id, product_name)
-            async with httpx.AsyncClient() as client:
+            return model_data
-                response = await client.get(
-                    f"{settings.TRAINING_SERVICE_URL}/tenants/{tenant_id}/models/{product_name}/active",
-                    params={},
-                    headers={"X-Service-Auth": settings.SERVICE_AUTH_TOKEN}
-                )
-                
-                if response.status_code == 200:
-                    return response.json()
-                elif response.status_code == 404:
-                    logger.warning("No model found", 
-                                 tenant_id=tenant_id, 
-                                 product=product_name)
-                    return None
-                else:
-                    response.raise_for_status()
                     
         except Exception as e:
             logger.error("Error getting latest model", error=str(e))
@@ -275,22 +262,15 @@ class ForecastingService:
         features = {
             "date": request.forecast_date.isoformat(),
             "day_of_week": request.forecast_date.weekday(),
-            "is_weekend": request.forecast_date.weekday() >= 5,
+            "is_weekend": request.forecast_date.weekday() >= 5
-            "business_type": request.business_type.value
         }
         
         # Add Spanish holidays
         features["is_holiday"] = await self._is_spanish_holiday(request.forecast_date)
         
-        # Add weather data if requested
-        if request.include_weather:
-            weather_data = await self._get_weather_forecast(request.forecast_date)
-            features.update(weather_data)
    
-        # Add traffic data if requested
+        weather_data = await self._get_weather_forecast(request.tenant_id, 1)
-        if request.include_traffic:
+        features.update(weather_data)
-            traffic_data = await self._get_traffic_forecast(request.forecast_date, request.location)
-            features.update(traffic_data)
         
         return features
     
@@ -315,61 +295,16 @@ class ForecastingService:
             logger.warning("Error checking holiday status", error=str(e))
             return False
     
-    async def _get_weather_forecast(self, forecast_date: date) -> Dict[str, Any]:
+    async def _get_weather_forecast(self, tenant_id: str, days: str) -> Dict[str, Any]:
         """Get weather forecast for the date"""
         
         try:
-            # Call data service for weather forecast
+            weather_data = await self.data_client.fetch_weather_forecast(tenant_id, days)
-            async with httpx.AsyncClient() as client:
+            return weather_data       
-                response = await client.get(
-                    f"{settings.DATA_SERVICE_URL}/api/v1/weather/forecast",
-                    params={"date": forecast_date.isoformat()},
-                    headers={"X-Service-Auth": settings.SERVICE_AUTH_TOKEN}
-                )
-                
-                if response.status_code == 200:
-                    weather = response.json()
-                    return {
-                        "temperature": weather.get("temperature"),
-                        "precipitation": weather.get("precipitation"),
-                        "humidity": weather.get("humidity"),
-                        "weather_description": weather.get("description")
-                    }
-                else:
-                    return {}
-                    
         except Exception as e:
             logger.warning("Error getting weather forecast", error=str(e))
             return {}
     
-    async def _get_traffic_forecast(self, forecast_date: date, location: str) -> Dict[str, Any]:
-        """Get traffic forecast for the date and location"""
-        
-        try:
-            # Call data service for traffic forecast
-            async with httpx.AsyncClient() as client:
-                response = await client.get(
-                    f"{settings.DATA_SERVICE_URL}/api/v1/traffic/forecast",
-                    params={
-                        "date": forecast_date.isoformat(),
-                        "location": location
-                    },
-                    headers={"X-Service-Auth": settings.SERVICE_AUTH_TOKEN}
-                )
-                
-                if response.status_code == 200:
-                    traffic = response.json()
-                    return {
-                        "traffic_volume": traffic.get("volume"),
-                        "pedestrian_count": traffic.get("pedestrian_count")
-                    }
-                else:
-                    return {}
-                    
-        except Exception as e:
-            logger.warning("Error getting traffic forecast", error=str(e))
-            return {}
-    
     async def _check_and_create_alerts(self, forecast: Forecast, db: AsyncSession):
         """Check forecast and create alerts if needed"""
         

services/forecasting/app/services/model_client.py

@@ -0,0 +1,183 @@
+# services/forecasting/app/services/model_client.py
+"""
+Forecast Service Model Client
+Demonstrates calling training service to get models
+"""
+
+import structlog
+from typing import Dict, Any, List, Optional
+
+# Import shared clients - no more code duplication!
+from shared.clients import get_service_clients, get_training_client, get_data_client
+from app.core.config import settings
+
+logger = structlog.get_logger()
+
+class ModelClient:
+    """
+    Client for managing models in forecasting service
+    Shows how to call multiple services cleanly
+    """
+    
+    def __init__(self):
+        # Option 1: Get all clients at once
+        self.clients = get_service_clients(settings, "forecasting")
+        
+        # Option 2: Get specific clients
+        # self.training_client = get_training_client(settings, "forecasting")
+        # self.data_client = get_data_client(settings, "forecasting")
+    
+    async def get_available_models(
+        self,
+        tenant_id: str,
+        model_type: Optional[str] = None
+    ) -> List[Dict[str, Any]]:
+        """
+        Get available trained models from training service
+        """
+        try:
+            models = await self.clients.training.list_models(
+                tenant_id=tenant_id,
+                status="deployed",  # Only get deployed models
+                model_type=model_type
+            )
+            
+            if models:
+                logger.info(f"Found {len(models)} available models", 
+                           tenant_id=tenant_id, model_type=model_type)
+                return models
+            else:
+                logger.warning("No available models found", tenant_id=tenant_id)
+                return []
+                
+        except Exception as e:
+            logger.error(f"Error fetching available models: {e}", tenant_id=tenant_id)
+            return []
+    
+    async def get_best_model_for_forecasting(
+        self,
+        tenant_id: str,
+        product_id: Optional[str] = None
+    ) -> Optional[Dict[str, Any]]:
+        """
+        Get the best model for forecasting based on performance metrics
+        """
+        try:
+            # Get latest model
+            latest_model = await self.clients.training.get_latest_model(
+                tenant_id=tenant_id,
+                model_type="forecasting"
+            )
+            
+            if not latest_model:
+                logger.warning("No trained models found", tenant_id=tenant_id)
+                return None
+            
+            # Get model metrics to validate quality
+            metrics = await self.clients.training.get_model_metrics(
+                tenant_id=tenant_id,
+                model_id=latest_model["id"]
+            )
+            
+            if metrics and metrics.get("accuracy", 0) > 0.7:  # 70% accuracy threshold
+                logger.info(f"Selected model {latest_model['id']} with accuracy {metrics.get('accuracy')}", 
+                           tenant_id=tenant_id)
+                return latest_model
+            else:
+                logger.warning(f"Model accuracy too low: {metrics.get('accuracy', 'unknown')}", 
+                              tenant_id=tenant_id)
+                return None
+                
+        except Exception as e:
+            logger.error(f"Error selecting best model: {e}", tenant_id=tenant_id)
+            return None
+    
+    async def validate_model_data_compatibility(
+        self,
+        tenant_id: str,
+        model_id: str,
+        forecast_start_date: str,
+        forecast_end_date: str
+    ) -> Dict[str, Any]:
+        """
+        Validate that we have sufficient data for the model to make forecasts
+        Demonstrates calling both training and data services
+        """
+        try:
+            # Get model details from training service
+            model = await self.clients.training.get_model(
+                tenant_id=tenant_id,
+                model_id=model_id
+            )
+            
+            if not model:
+                return {"is_valid": False, "error": "Model not found"}
+            
+            # Get data statistics from data service
+            data_stats = await self.clients.data.get_data_statistics(
+                tenant_id=tenant_id,
+                start_date=forecast_start_date,
+                end_date=forecast_end_date
+            )
+            
+            if not data_stats:
+                return {"is_valid": False, "error": "Could not retrieve data statistics"}
+            
+            # Check if we have minimum required data points
+            min_required = model.get("metadata", {}).get("min_data_points", 30)
+            available_points = data_stats.get("total_records", 0)
+            
+            is_valid = available_points >= min_required
+            
+            result = {
+                "is_valid": is_valid,
+                "model_id": model_id,
+                "required_points": min_required,
+                "available_points": available_points,
+                "data_coverage": data_stats.get("coverage_percentage", 0)
+            }
+            
+            if not is_valid:
+                result["error"] = f"Insufficient data: need {min_required}, have {available_points}"
+            
+            logger.info("Model data compatibility check completed", 
+                       tenant_id=tenant_id, model_id=model_id, is_valid=is_valid)
+            
+            return result
+            
+        except Exception as e:
+            logger.error(f"Error validating model compatibility: {e}", 
+                        tenant_id=tenant_id, model_id=model_id)
+            return {"is_valid": False, "error": str(e)}
+    
+    async def trigger_model_retraining(
+        self,
+        tenant_id: str,
+        include_weather: bool = True,
+        include_traffic: bool = False
+    ) -> Optional[Dict[str, Any]]:
+        """
+        Trigger a new training job if current model is outdated
+        """
+        try:
+            # Create training job through training service
+            job = await self.clients.training.create_training_job(
+                tenant_id=tenant_id,
+                include_weather=include_weather,
+                include_traffic=include_traffic,
+                min_data_points=50  # Higher threshold for forecasting
+            )
+            
+            if job:
+                logger.info(f"Training job created: {job['job_id']}", tenant_id=tenant_id)
+                return job
+            else:
+                logger.error("Failed to create training job", tenant_id=tenant_id)
+                return None
+                
+        except Exception as e:
+            logger.error(f"Error triggering model retraining: {e}", tenant_id=tenant_id)
+            return None
+
+# Global instance
+model_client = ModelClient()

services/training/app/core/service_auth.py

@@ -1,81 +0,0 @@
-import time
-import structlog
-from typing import Dict, Any
-from shared.auth.jwt_handler import JWTHandler
-from app.core.config import settings
-
-logger = structlog.get_logger()
-
-class ServiceAuthenticator:
-    """Handles service-to-service authentication via gateway"""
-    
-    def __init__(self):
-        self.jwt_handler = JWTHandler(settings.JWT_SECRET_KEY)
-        self._cached_token = None
-        self._token_expires_at = 0
-    
-    async def get_service_token(self) -> str:
-        """
-        Get a valid service token, using cache when possible
-        Creates JWT tokens that the gateway will accept
-        """
-        current_time = int(time.time())
-        
-        # Return cached token if still valid (with 5 min buffer)
-        if (self._cached_token and 
-            self._token_expires_at > current_time + 300):
-            return self._cached_token
-        
-        # Create new service token
-        token_expires_at = current_time + 3600  # 1 hour
-        
-        service_payload = {
-            # ✅ Required fields for gateway middleware
-            "sub": "training-service",
-            "user_id": "training-service",
-            "email": "training-service@internal",
-            "type": "access",  # ✅ Must be "access" for gateway
-            
-            # ✅ Expiration and timing
-            "exp": token_expires_at,
-            "iat": current_time,
-            "iss": "training-service",
-            
-            # ✅ Service identification
-            "service": "training",
-            "full_name": "Training Service",
-            "is_verified": True,
-            "is_active": True,
-            
-            # ✅ Optional tenant context (can be overridden per request)
-            "tenant_id": None
-        }
-        
-        try:
-            token = self.jwt_handler.create_access_token_from_payload(service_payload)
-            
-            # Cache the token
-            self._cached_token = token
-            self._token_expires_at = token_expires_at
-            
-            logger.debug("Created new service token", expires_at=token_expires_at)
-            return token
-            
-        except Exception as e:
-            logger.error(f"Failed to create service token: {e}")
-            raise ValueError(f"Service token creation failed: {e}")
-    
-    def get_request_headers(self, tenant_id: str = None) -> Dict[str, str]:
-        """Get standard headers for service requests"""
-        headers = {
-            "X-Service": "training-service",
-            "User-Agent": "training-service/1.0.0"
-        }
-        
-        if tenant_id:
-            headers["X-Tenant-ID"] = str(tenant_id)
-            
-        return headers
-
-# Global authenticator instance
-service_auth = ServiceAuthenticator()

services/training/app/services/data_client.py

@@ -1,140 +1,87 @@
-import httpx
+# services/training/app/services/data_client.py
+"""
+Training Service Data Client
+Migrated to use shared service clients - much simpler now!
+"""
+
 import structlog
-from typing import List, Dict, Any, Optional
+from typing import Dict, Any, List, Optional
+from datetime import datetime
+
+# Import the shared clients
+from shared.clients import get_data_client, get_service_clients
 from app.core.config import settings
-from app.core.service_auth import service_auth
 
 logger = structlog.get_logger()
 
-class DataServiceClient:
+class DataClient:
-    """Client for fetching data through the API Gateway"""
+    """
+    Data client for training service
+    Now uses the shared data service client under the hood
+    """
     
     def __init__(self):
-        self.base_url = settings.API_GATEWAY_URL
+        # Get the shared data client configured for this service
-        self.timeout = 2000.0
+        self.data_client = get_data_client(settings, "training")
         
-    async def fetch_sales_data(self, tenant_id: str) -> List[Dict[str, Any]]:
+        # Or alternatively, get all clients at once:
+        # self.clients = get_service_clients(settings, "training") 
+        # Then use: self.clients.data.get_sales_data(...)
+    
+    async def fetch_sales_data(
+        self,
+        tenant_id: str,
+        start_date: Optional[str] = None,
+        end_date: Optional[str] = None,
+        product_id: Optional[str] = None,
+        fetch_all: bool = True
+    ) -> List[Dict[str, Any]]:
         """
-        Fetch all sales data for training (no pagination limits)
+        Fetch sales data for training
-        FIXED: Retrieves ALL records instead of being limited to 1000
+        
+        Args:
+            tenant_id: Tenant identifier
+            start_date: Start date in ISO format
+            end_date: End date in ISO format  
+            product_id: Optional product filter
+            fetch_all: If True, fetches ALL records using pagination (original behavior)
+                      If False, fetches limited records (standard API response)
         """
         try:
-            # Get service token
+            if fetch_all:
-            token = await service_auth.get_service_token()
+                # Use paginated method to get ALL records (original behavior)
+                sales_data = await self.data_client.get_all_sales_data(
+                    tenant_id=tenant_id,
+                    start_date=start_date,
+                    end_date=end_date,
+                    product_id=product_id,
+                    aggregation="daily",
+                    page_size=5000,  # Match original page size
+                    max_pages=100    # Safety limit (500k records max)
+                )
+            else:
+                # Use standard method for limited results
+                sales_data = await self.data_client.get_sales_data(
+                    tenant_id=tenant_id,
+                    start_date=start_date,
+                    end_date=end_date,
+                    product_id=product_id,
+                    aggregation="daily"
+                )
+                sales_data = sales_data or []
             
-            # Prepare headers
+            if sales_data:
-            headers = service_auth.get_request_headers(tenant_id)
+                logger.info(f"Fetched {len(sales_data)} sales records", 
-            headers["Authorization"] = f"Bearer {token}"
+                           tenant_id=tenant_id, product_id=product_id, fetch_all=fetch_all)
-            
+                return sales_data
-            all_records = []
+            else:
-            page = 0
+                logger.warning("No sales data returned", tenant_id=tenant_id)
-            page_size = 5000  # Use maximum allowed by API
+                return []
-            
-            while True:
-                # Prepare query parameters for pagination
-                params = {
-                    "limit": page_size,
-                    "offset": page * page_size
-                }
-                
-                logger.info(f"Fetching sales data page {page + 1} (offset: {page * page_size})", 
-                        tenant_id=tenant_id)
-                
-                # Make GET request via gateway with pagination
-                async with httpx.AsyncClient(timeout=self.timeout) as client:
-                    response = await client.get(
-                        f"{self.base_url}/api/v1/tenants/{tenant_id}/sales",
-                        headers=headers,
-                        params=params
-                    )
-                    
-                    if response.status_code == 200:
-                        page_data = response.json()
-                        
-                        # Handle different response formats
-                        if isinstance(page_data, list):
-                            # Direct list response (no pagination metadata)
-                            records = page_data
-                            logger.info(f"Retrieved {len(records)} records from page {page + 1} (direct list)")
-                            
-                            # For direct list responses, we need to check if we got the max possible
-                            # If we got less than page_size, we're done
-                            if len(records) == 0:
-                                logger.info("No records in response, pagination complete")
-                                break
-                            elif len(records) < page_size:
-                                # Got fewer than requested, this is the last page
-                                all_records.extend(records)
-                                logger.info(f"Final page: retrieved {len(records)} records, total: {len(all_records)}")
-                                break
-                            else:
-                                # Got full page, there might be more
-                                all_records.extend(records)
-                                logger.info(f"Full page retrieved: {len(records)} records, continuing to next page")
-                                
-                        elif isinstance(page_data, dict):
-                            # Paginated response format
-                            records = page_data.get('records', page_data.get('data', []))
-                            total_available = page_data.get('total', 0)
-                            
-                            logger.info(f"Retrieved {len(records)} records from page {page + 1} (paginated response)")
-                            
-                            if not records:
-                                logger.info("No more records found in paginated response")
-                                break
-                                
-                            all_records.extend(records)
-                            
-                            # Check if we've got all available records
-                            if len(all_records) >= total_available:
-                                logger.info(f"Retrieved all available records: {len(all_records)}/{total_available}")
-                                break
-                                
-                        else:
-                            logger.warning(f"Unexpected response format: {type(page_data)}")
-                            records = []
-                            break
-                        
-                        page += 1
-                        
-                        # Safety break to prevent infinite loops
-                        if page > 100:  # Max 500,000 records (100 * 5000)
-                            logger.warning("Reached maximum page limit, stopping pagination")
-                            break
-                    
-                    elif response.status_code == 401:
-                        logger.error("Authentication failed with gateway", 
-                                    tenant_id=tenant_id,
-                                    response_text=response.text)
-                        return []
-                        
-                    elif response.status_code == 404:
-                        logger.warning("Sales data endpoint not found", 
-                                    tenant_id=tenant_id,
-                                    url=response.url)
-                        return []
-                        
-                    else:
-                        logger.error(f"Gateway request failed: HTTP {response.status_code}", 
-                                    tenant_id=tenant_id,
-                                    response_text=response.text)
-                        return []
-            
-            logger.info(f"Successfully fetched {len(all_records)} total sales records via gateway", 
-                    tenant_id=tenant_id)
-            return all_records
-                        
-        except httpx.TimeoutException:
-            logger.error("Timeout when fetching sales data via gateway", 
-                        tenant_id=tenant_id)
-            return []
                 
         except Exception as e:
-            logger.error(f"Error fetching sales data via gateway: {e}", 
+            logger.error(f"Error fetching sales data: {e}", tenant_id=tenant_id)
-                        tenant_id=tenant_id)
             return []
     
-
     async def fetch_weather_data(
         self,
         tenant_id: str,
@@ -144,72 +91,28 @@ class DataServiceClient:
         longitude: Optional[float] = None
     ) -> List[Dict[str, Any]]:
         """
-        Fetch historical weather data for training via API Gateway using POST
+        Fetch weather data for training
+        All the error handling and retry logic is now in the base client!
         """
         try:
-            # Get service token
+            weather_data = await self.data_client.get_weather_historical(
-            token = await service_auth.get_service_token()
+                tenant_id=tenant_id,
+                start_date=start_date,
+                end_date=end_date,
+                latitude=latitude,
+                longitude=longitude
+            )
             
-            # Prepare headers
+            if weather_data:
-            headers = service_auth.get_request_headers(tenant_id)
+                logger.info(f"Fetched {len(weather_data)} weather records", 
-            headers["Authorization"] = f"Bearer {token}"
+                           tenant_id=tenant_id)
-            headers["Content-Type"] = "application/json"
+                return weather_data
+            else:
+                logger.warning("No weather data returned", tenant_id=tenant_id)
+                return []
                 
-            # Prepare request payload with proper date handling
-            payload = {
-                "start_date": start_date,  # Already in ISO format from calling code
-                "end_date": end_date,      # Already in ISO format from calling code
-                "latitude": latitude or 40.4168,  # Default Madrid coordinates
-                "longitude": longitude or -3.7038
-            }
-            
-            logger.info(f"Weather request payload: {payload}", tenant_id=tenant_id)
-            
-            # Make POST request via gateway
-            async with httpx.AsyncClient(timeout=self.timeout) as client:
-                response = await client.post(
-                    f"{self.base_url}/api/v1/tenants/{tenant_id}/weather/historical",
-                    headers=headers,
-                    json=payload
-                )
-                
-                logger.info(f"Weather data request: {response.status_code}", 
-                        tenant_id=tenant_id, 
-                        url=response.url)
-                
-                if response.status_code == 200:
-                    data = response.json()
-                    logger.info(f"Successfully fetched {len(data)} weather records")
-                    return data
-                elif response.status_code == 400:
-                    error_details = response.text
-                    logger.error(f"Weather API validation error (400): {error_details}")
-                    
-                    # Try to parse the error and provide helpful info
-                    try:
-                        error_json = response.json()
-                        if 'detail' in error_json:
-                            detail = error_json['detail']
-                            if 'End date must be after start date' in str(detail):
-                                logger.error(f"Date range issue: start={start_date}, end={end_date}")
-                            elif 'Date range cannot exceed 90 days' in str(detail):
-                                logger.error(f"Date range too large: {start_date} to {end_date}")
-                    except:
-                        pass
-                    
-                    return []
-                elif response.status_code == 401:
-                    logger.error("Authentication failed for weather API")
-                    return []
-                else:
-                    logger.error(f"Failed to fetch weather data: {response.status_code} - {response.text}")
-                    return []
-                    
-        except httpx.TimeoutException:
-            logger.error("Timeout when fetching weather data")
-            return []
         except Exception as e:
-            logger.error(f"Error fetching weather data: {str(e)}")
+            logger.error(f"Error fetching weather data: {e}", tenant_id=tenant_id)
             return []
     
     async def fetch_traffic_data(
@@ -221,65 +124,57 @@ class DataServiceClient:
         longitude: Optional[float] = None
     ) -> List[Dict[str, Any]]:
         """
-        Fetch historical traffic data for training via API Gateway using POST
+        Fetch traffic data for training
         """
         try:
-            # Get service token
+            traffic_data = await self.data_client.get_traffic_data(
-            token = await service_auth.get_service_token()
+                tenant_id=tenant_id,
-            
+                start_date=start_date,
-            # Prepare headers
+                end_date=end_date,
-            headers = service_auth.get_request_headers(tenant_id)
+                latitude=latitude,
-            headers["Authorization"] = f"Bearer {token}"
+                longitude=longitude
-            headers["Content-Type"] = "application/json"
-            
-            # Prepare request payload
-            payload = {
-                "start_date": start_date,  # Already in ISO format from calling code
-                "end_date": end_date,      # Already in ISO format from calling code
-                "latitude": latitude or 40.4168,  # Default Madrid coordinates
-                "longitude": longitude or -3.7038
-            }
-            
-            logger.info(f"Traffic request payload: {payload}", tenant_id=tenant_id)
-            
-            # Madrid traffic data can take 5-10 minutes to download and process
-            timeout_config = httpx.Timeout(
-                connect=30.0,    # Connection timeout
-                read=600.0,      # Read timeout: 10 minutes (was 30s)
-                write=30.0,      # Write timeout
-                pool=30.0        # Pool timeout
             )
             
-            # Make POST request via gateway
+            if traffic_data:
-            async with httpx.AsyncClient(timeout=timeout_config) as client:
+                logger.info(f"Fetched {len(traffic_data)} traffic records", 
-                response = await client.post(
+                           tenant_id=tenant_id)
-                    f"{self.base_url}/api/v1/tenants/{tenant_id}/traffic/historical",
+                return traffic_data
-                    headers=headers,
+            else:
-                    json=payload
+                logger.warning("No traffic data returned", tenant_id=tenant_id)
-                )
+                return []
                 
-                logger.info(f"Traffic data request: {response.status_code}", 
-                        tenant_id=tenant_id, 
-                        url=response.url)
-                
-                if response.status_code == 200:
-                    data = response.json()
-                    logger.info(f"Successfully fetched {len(data)} traffic records")
-                    return data
-                elif response.status_code == 400:
-                    error_details = response.text
-                    logger.error(f"Traffic API validation error (400): {error_details}")
-                    return []
-                elif response.status_code == 401:
-                    logger.error("Authentication failed for traffic API")
-                    return []
-                else:
-                    logger.error(f"Failed to fetch traffic data: {response.status_code} - {response.text}")
-                    return []
-                    
-        except httpx.TimeoutException:
-            logger.error("Timeout when fetching traffic data")
-            return []
         except Exception as e:
-            logger.error(f"Error fetching traffic data: {str(e)}")
+            logger.error(f"Error fetching traffic data: {e}", tenant_id=tenant_id)
             return []
+    
+    async def validate_data_quality(
+        self,
+        tenant_id: str,
+        start_date: str,
+        end_date: str
+    ) -> Dict[str, Any]:
+        """
+        Validate data quality before training
+        """
+        try:
+            validation_result = await self.data_client.validate_data_quality(
+                tenant_id=tenant_id,
+                start_date=start_date,
+                end_date=end_date
+            )
+            
+            if validation_result:
+                logger.info("Data validation completed", 
+                           tenant_id=tenant_id,
+                           is_valid=validation_result.get("is_valid", False))
+                return validation_result
+            else:
+                logger.warning("Data validation failed", tenant_id=tenant_id)
+                return {"is_valid": False, "errors": ["Validation service unavailable"]}
+                
+        except Exception as e:
+            logger.error(f"Error validating data: {e}", tenant_id=tenant_id)
+            return {"is_valid": False, "errors": [str(e)]}
+
+# Global instance - same as before, but much simpler implementation
+data_client = DataClient()

services/training/app/services/training_orchestrator.py

@@ -13,7 +13,7 @@ from concurrent.futures import ThreadPoolExecutor
 from datetime import timezone
 import pandas as pd
 
-from app.services.data_client import DataServiceClient
+from app.services.data_client import DataClient
 from app.services.date_alignment_service import DateAlignmentService, DateRange, DataSourceType, AlignedDateRange
 
 logger = logging.getLogger(__name__)
@@ -37,7 +37,7 @@ class TrainingDataOrchestrator:
                  madrid_client=None, 
                  weather_client=None,
                  date_alignment_service: DateAlignmentService = None):
-        self.data_client = DataServiceClient()
+        self.data_client = DataClient()
         self.date_alignment_service = date_alignment_service or DateAlignmentService()
         self.max_concurrent_requests = 3
         

shared/clients/__init__.py

@@ -0,0 +1,106 @@
+# shared/clients/__init__.py
+"""
+Service Client Factory and Convenient Imports
+Provides easy access to all service clients
+"""
+
+from .base_service_client import BaseServiceClient, ServiceAuthenticator
+from .training_client import TrainingServiceClient
+from .data_client import DataServiceClient
+from .forecast_client import ForecastServiceClient
+
+# Import config
+from shared.config.base import BaseServiceSettings
+
+# Cache clients to avoid recreating them
+_client_cache = {}
+
+def get_training_client(config: BaseServiceSettings = None, service_name: str = "unknown") -> TrainingServiceClient:
+    """Get or create a training service client"""
+    if config is None:
+        from app.core.config import settings as config
+    
+    cache_key = f"training_{service_name}"
+    if cache_key not in _client_cache:
+        _client_cache[cache_key] = TrainingServiceClient(config, service_name)
+    return _client_cache[cache_key]
+
+def get_data_client(config: BaseServiceSettings = None, service_name: str = "unknown") -> DataServiceClient:
+    """Get or create a data service client"""
+    if config is None:
+        from app.core.config import settings as config
+    
+    cache_key = f"data_{service_name}"
+    if cache_key not in _client_cache:
+        _client_cache[cache_key] = DataServiceClient(config, service_name)
+    return _client_cache[cache_key]
+
+def get_forecast_client(config: BaseServiceSettings = None, service_name: str = "unknown") -> ForecastServiceClient:
+    """Get or create a forecast service client"""
+    if config is None:
+        from app.core.config import settings as config
+    
+    cache_key = f"forecast_{service_name}"
+    if cache_key not in _client_cache:
+        _client_cache[cache_key] = ForecastServiceClient(config, service_name)
+    return _client_cache[cache_key]
+
+class ServiceClients:
+    """Convenient wrapper for all service clients"""
+    
+    def __init__(self, config: BaseServiceSettings = None, service_name: str = "unknown"):
+        self.service_name = service_name
+        self.config = config or self._get_default_config()
+        
+        # Initialize clients lazily
+        self._training_client = None
+        self._data_client = None
+        self._forecast_client = None
+    
+    def _get_default_config(self):
+        """Get default config from app settings"""
+        try:
+            from app.core.config import settings
+            return settings
+        except ImportError:
+            raise ImportError("Could not import app config. Please provide config explicitly.")
+    
+    @property
+    def training(self) -> TrainingServiceClient:
+        """Get training service client"""
+        if self._training_client is None:
+            self._training_client = get_training_client(self.config, self.service_name)
+        return self._training_client
+    
+    @property
+    def data(self) -> DataServiceClient:
+        """Get data service client"""
+        if self._data_client is None:
+            self._data_client = get_data_client(self.config, self.service_name)
+        return self._data_client
+    
+    @property
+    def forecast(self) -> ForecastServiceClient:
+        """Get forecast service client"""
+        if self._forecast_client is None:
+            self._forecast_client = get_forecast_client(self.config, self.service_name)
+        return self._forecast_client
+
+# Convenience function to get all clients
+def get_service_clients(config: BaseServiceSettings = None, service_name: str = "unknown") -> ServiceClients:
+    """Get a wrapper with all service clients"""
+    return ServiceClients(config, service_name)
+
+# Export all classes for direct import
+__all__ = [
+    'BaseServiceClient',
+    'ServiceAuthenticator', 
+    'TrainingServiceClient',
+    'DataServiceClient',
+    'ForecastServiceClient',
+    'ServiceClients',
+    'get_training_client',
+    'get_data_client', 
+    'get_forecast_client',
+    'get_service_clients'
+]

shared/clients/base_service_client.py

@@ -0,0 +1,363 @@
+# shared/clients/base_service_client.py
+"""
+Base Service Client for Inter-Service Communication
+Provides a reusable foundation for all service-to-service API calls
+"""
+
+import time
+import asyncio
+import httpx
+import structlog
+from abc import ABC, abstractmethod
+from typing import Dict, Any, Optional, List, Union
+from urllib.parse import urljoin
+
+from shared.auth.jwt_handler import JWTHandler
+from shared.config.base import BaseServiceSettings
+
+logger = structlog.get_logger()
+
+class ServiceAuthenticator:
+    """Handles service-to-service authentication via gateway"""
+    
+    def __init__(self, service_name: str, config: BaseServiceSettings):
+        self.service_name = service_name
+        self.config = config
+        self.jwt_handler = JWTHandler(config.JWT_SECRET_KEY)
+        self._cached_token = None
+        self._token_expires_at = 0
+    
+    async def get_service_token(self) -> str:
+        """Get a valid service token, using cache when possible"""
+        current_time = int(time.time())
+        
+        # Return cached token if still valid (with 5 min buffer)
+        if (self._cached_token and 
+            self._token_expires_at > current_time + 300):
+            return self._cached_token
+        
+        # Create new service token
+        token_expires_at = current_time + 3600  # 1 hour
+        
+        service_payload = {
+            "sub": f"{self.service_name}-service",
+            "user_id": f"{self.service_name}-service", 
+            "email": f"{self.service_name}-service@internal",
+            "type": "access",
+            "exp": token_expires_at,
+            "iat": current_time,
+            "iss": f"{self.service_name}-service",
+            "service": self.service_name,
+            "full_name": f"{self.service_name.title()} Service",
+            "is_verified": True,
+            "is_active": True,
+            "tenant_id": None
+        }
+        
+        try:
+            token = self.jwt_handler.create_access_token_from_payload(service_payload)
+            self._cached_token = token
+            self._token_expires_at = token_expires_at
+            
+            logger.debug("Created new service token", service=self.service_name, expires_at=token_expires_at)
+            return token
+            
+        except Exception as e:
+            logger.error(f"Failed to create service token: {e}", service=self.service_name)
+            raise ValueError(f"Service token creation failed: {e}")
+    
+    def get_request_headers(self, tenant_id: Optional[str] = None) -> Dict[str, str]:
+        """Get standard headers for service requests"""
+        headers = {
+            "X-Service": f"{self.service_name}-service",
+            "User-Agent": f"{self.service_name}-service/1.0.0"
+        }
+        
+        if tenant_id:
+            headers["X-Tenant-ID"] = str(tenant_id)
+            
+        return headers
+
+
+class BaseServiceClient(ABC):
+    """
+    Base class for all inter-service communication clients
+    Provides common functionality for API calls through the gateway
+    """
+    
+    def __init__(self, service_name: str, config: BaseServiceSettings):
+        self.service_name = service_name
+        self.config = config
+        self.gateway_url = config.GATEWAY_URL
+        self.authenticator = ServiceAuthenticator(service_name, config)
+        
+        # HTTP client configuration
+        self.timeout = config.HTTP_TIMEOUT
+        self.retries = config.HTTP_RETRIES
+        self.retry_delay = config.HTTP_RETRY_DELAY
+    
+    @abstractmethod
+    def get_service_base_path(self) -> str:
+        """Return the base path for this service's APIs"""
+        pass
+    
+    async def _make_request(
+        self,
+        method: str,
+        endpoint: str,
+        tenant_id: Optional[str] = None,
+        data: Optional[Dict[str, Any]] = None,
+        params: Optional[Dict[str, Any]] = None,
+        headers: Optional[Dict[str, str]] = None,
+        timeout: Optional[Union[int, httpx.Timeout]] = None
+    ) -> Optional[Union[Dict[str, Any], List[Dict[str, Any]]]]:
+        """
+        Make an authenticated request to another service via gateway
+        
+        Args:
+            method: HTTP method (GET, POST, PUT, DELETE)
+            endpoint: API endpoint (will be prefixed with service base path)
+            tenant_id: Optional tenant ID for tenant-scoped requests
+            data: Request body data (for POST/PUT)
+            params: Query parameters
+            headers: Additional headers
+            timeout: Request timeout override
+            
+        Returns:
+            Response data or None if request failed
+        """
+        try:
+            # Get service token
+            token = await self.authenticator.get_service_token()
+            
+            # Build headers
+            request_headers = self.authenticator.get_request_headers(tenant_id)
+            request_headers["Authorization"] = f"Bearer {token}"
+            request_headers["Content-Type"] = "application/json"
+            
+            if headers:
+                request_headers.update(headers)
+            
+            # Build URL
+            base_path = self.get_service_base_path()
+            if tenant_id:
+                # For tenant-scoped endpoints
+                full_endpoint = f"{base_path}/tenants/{tenant_id}/{endpoint.lstrip('/')}"
+            else:
+                # For non-tenant endpoints
+                full_endpoint = f"{base_path}/{endpoint.lstrip('/')}"
+            
+            url = urljoin(self.gateway_url, full_endpoint)
+            
+            # Make request with retries
+            for attempt in range(self.retries + 1):
+                try:
+                    # Handle different timeout configurations
+                    if isinstance(timeout, httpx.Timeout):
+                        client_timeout = timeout
+                    else:
+                        client_timeout = timeout or self.timeout
+                    
+                    async with httpx.AsyncClient(timeout=client_timeout) as client:
+                        response = await client.request(
+                            method=method,
+                            url=url,
+                            json=data,
+                            params=params,
+                            headers=request_headers
+                        )
+                    
+                    if response.status_code == 200:
+                        return response.json()
+                    elif response.status_code == 201:
+                        return response.json()
+                    elif response.status_code == 204:
+                        return {}  # No content success
+                    elif response.status_code == 401:
+                        # Token might be expired, clear cache and retry once
+                        if attempt == 0:
+                            self.authenticator._cached_token = None
+                            logger.warning("Token expired, retrying with new token")
+                            continue
+                        else:
+                            logger.error("Authentication failed after retry")
+                            return None
+                    elif response.status_code == 404:
+                        logger.warning(f"Endpoint not found: {url}")
+                        return None
+                    else:
+                        error_detail = "Unknown error"
+                        try:
+                            error_json = response.json()
+                            error_detail = error_json.get('detail', f"HTTP {response.status_code}")
+                        except:
+                            error_detail = f"HTTP {response.status_code}: {response.text}"
+                        
+                        logger.error(f"Request failed: {error_detail}", 
+                                   url=url, status_code=response.status_code)
+                        return None
+                        
+                except httpx.TimeoutException:
+                    if attempt < self.retries:
+                        logger.warning(f"Request timeout, retrying ({attempt + 1}/{self.retries})")
+                        import asyncio
+                        await asyncio.sleep(self.retry_delay * (2 ** attempt))  # Exponential backoff
+                        continue
+                    else:
+                        logger.error(f"Request timeout after {self.retries} retries", url=url)
+                        return None
+                        
+                except Exception as e:
+                    if attempt < self.retries:
+                        logger.warning(f"Request failed, retrying ({attempt + 1}/{self.retries}): {e}")
+                        import asyncio
+                        await asyncio.sleep(self.retry_delay * (2 ** attempt))
+                        continue
+                    else:
+                        logger.error(f"Request failed after {self.retries} retries: {e}", url=url)
+                        return None
+            
+        except Exception as e:
+            logger.error(f"Unexpected error in _make_request: {e}")
+            return None
+    
+    async def _make_paginated_request(
+        self,
+        endpoint: str,
+        tenant_id: Optional[str] = None,
+        params: Optional[Dict[str, Any]] = None,
+        page_size: int = 5000,
+        max_pages: int = 100,
+        timeout: Optional[Union[int, httpx.Timeout]] = None
+    ) -> List[Dict[str, Any]]:
+        """
+        Make paginated GET requests to fetch all records
+        Handles both direct list and paginated object responses
+        
+        Args:
+            endpoint: API endpoint 
+            tenant_id: Optional tenant ID
+            params: Base query parameters
+            page_size: Records per page (default 5000)
+            max_pages: Maximum pages to fetch (safety limit)
+            timeout: Request timeout override
+            
+        Returns:
+            List of all records from all pages
+        """
+        all_records = []
+        page = 0
+        base_params = params or {}
+        
+        logger.info(f"Starting paginated request to {endpoint}", 
+                   tenant_id=tenant_id, page_size=page_size)
+        
+        while page < max_pages:
+            # Prepare pagination parameters
+            page_params = base_params.copy()
+            page_params.update({
+                "limit": page_size,
+                "offset": page * page_size
+            })
+            
+            logger.debug(f"Fetching page {page + 1} (offset: {page * page_size})", 
+                        tenant_id=tenant_id)
+            
+            # Make request for this page
+            result = await self._make_request(
+                "GET", 
+                endpoint, 
+                tenant_id=tenant_id, 
+                params=page_params,
+                timeout=timeout
+            )
+            
+            if result is None:
+                logger.error(f"Failed to fetch page {page + 1}", tenant_id=tenant_id)
+                break
+            
+            # Handle different response formats
+            if isinstance(result, list):
+                # Direct list response (no pagination metadata)
+                records = result
+                logger.debug(f"Retrieved {len(records)} records from page {page + 1} (direct list)")
+                
+                if len(records) == 0:
+                    logger.info("No records in response, pagination complete")
+                    break
+                elif len(records) < page_size:
+                    # Got fewer than requested, this is the last page
+                    all_records.extend(records)
+                    logger.info(f"Final page: retrieved {len(records)} records, total: {len(all_records)}")
+                    break
+                else:
+                    # Got full page, there might be more
+                    all_records.extend(records)
+                    logger.debug(f"Full page retrieved: {len(records)} records, continuing to next page")
+                    
+            elif isinstance(result, dict):
+                # Paginated response format
+                records = result.get('records', result.get('data', []))
+                total_available = result.get('total', 0)
+                
+                logger.debug(f"Retrieved {len(records)} records from page {page + 1} (paginated response)")
+                
+                if not records:
+                    logger.info("No more records found in paginated response")
+                    break
+                    
+                all_records.extend(records)
+                
+                # Check if we've got all available records
+                if len(all_records) >= total_available:
+                    logger.info(f"Retrieved all available records: {len(all_records)}/{total_available}")
+                    break
+                    
+            else:
+                logger.warning(f"Unexpected response format: {type(result)}")
+                break
+            
+            page += 1
+        
+        if page >= max_pages:
+            logger.warning(f"Reached maximum page limit ({max_pages}), stopping pagination")
+        
+        logger.info(f"Pagination complete: fetched {len(all_records)} total records", 
+                   tenant_id=tenant_id, pages_fetched=page)
+        
+        return all_records
+    
+    async def get(self, endpoint: str, tenant_id: Optional[str] = None, params: Optional[Dict[str, Any]] = None) -> Optional[Dict[str, Any]]:
+        """Make a GET request"""
+        return await self._make_request("GET", endpoint, tenant_id=tenant_id, params=params)
+    
+    async def get_paginated(
+        self, 
+        endpoint: str, 
+        tenant_id: Optional[str] = None, 
+        params: Optional[Dict[str, Any]] = None,
+        page_size: int = 5000,
+        max_pages: int = 100,
+        timeout: Optional[Union[int, httpx.Timeout]] = None
+    ) -> List[Dict[str, Any]]:
+        """Make a paginated GET request to fetch all records"""
+        return await self._make_paginated_request(
+            endpoint, 
+            tenant_id=tenant_id, 
+            params=params,
+            page_size=page_size,
+            max_pages=max_pages,
+            timeout=timeout
+        )
+    
+    async def post(self, endpoint: str, data: Dict[str, Any], tenant_id: Optional[str] = None) -> Optional[Dict[str, Any]]:
+        """Make a POST request"""
+        return await self._make_request("POST", endpoint, tenant_id=tenant_id, data=data)
+    
+    async def put(self, endpoint: str, data: Dict[str, Any], tenant_id: Optional[str] = None) -> Optional[Dict[str, Any]]:
+        """Make a PUT request"""
+        return await self._make_request("PUT", endpoint, tenant_id=tenant_id, data=data)
+    
+    async def delete(self, endpoint: str, tenant_id: Optional[str] = None) -> Optional[Dict[str, Any]]:
+        """Make a DELETE request"""
+        return await self._make_request("DELETE", endpoint, tenant_id=tenant_id)

shared/clients/data_client.py

@@ -0,0 +1,399 @@
+# shared/clients/data_client.py
+"""
+Data Service Client
+Handles all API calls to the data service
+"""
+
+import httpx
+import structlog
+from typing import Dict, Any, Optional, List, Union
+from .base_service_client import BaseServiceClient
+from shared.config.base import BaseServiceSettings
+
+logger = structlog.get_logger()
+
+
+class DataServiceClient(BaseServiceClient):
+    """Client for communicating with the data service"""
+    
+    def __init__(self, config: BaseServiceSettings, calling_service_name: str = "unknown"):
+        super().__init__(calling_service_name, config)
+    
+    def get_service_base_path(self) -> str:
+        return "/api/v1"
+    
+    # ================================================================
+    # SALES DATA (with advanced pagination support)
+    # ================================================================
+    
+    async def get_sales_data(
+        self,
+        tenant_id: str,
+        start_date: Optional[str] = None,
+        end_date: Optional[str] = None,
+        product_id: Optional[str] = None,
+        aggregation: str = "daily"
+    ) -> Optional[List[Dict[str, Any]]]:
+        """Get sales data for a date range"""
+        params = {"aggregation": aggregation}
+        if start_date:
+            params["start_date"] = start_date
+        if end_date:
+            params["end_date"] = end_date
+        if product_id:
+            params["product_id"] = product_id
+        
+        result = await self.get("sales", tenant_id=tenant_id, params=params)
+        return result.get("sales", []) if result else None
+    
+    async def get_all_sales_data(
+        self,
+        tenant_id: str,
+        start_date: Optional[str] = None,
+        end_date: Optional[str] = None,
+        product_id: Optional[str] = None,
+        aggregation: str = "daily",
+        page_size: int = 5000,
+        max_pages: int = 100
+    ) -> List[Dict[str, Any]]:
+        """
+        Get ALL sales data using pagination (equivalent to original fetch_sales_data)
+        Retrieves all records without pagination limits
+        """
+        params = {"aggregation": aggregation}
+        if start_date:
+            params["start_date"] = start_date
+        if end_date:
+            params["end_date"] = end_date
+        if product_id:
+            params["product_id"] = product_id
+        
+        # Use the inherited paginated request method
+        try:
+            all_records = await self.get_paginated(
+                "sales",
+                tenant_id=tenant_id,
+                params=params,
+                page_size=page_size,
+                max_pages=max_pages,
+                timeout=2000.0  # Match original timeout
+            )
+            
+            logger.info(f"Successfully fetched {len(all_records)} total sales records via gateway", 
+                       tenant_id=tenant_id)
+            return all_records
+            
+        except AttributeError as e:
+            # Fallback: implement pagination directly if inheritance isn't working
+            logger.warning(f"Using fallback pagination due to: {e}")
+            return await self._fallback_paginated_sales(tenant_id, params, page_size, max_pages)
+    
+    async def _fallback_paginated_sales(
+        self,
+        tenant_id: str,
+        base_params: Dict[str, Any],
+        page_size: int = 5000,
+        max_pages: int = 100
+    ) -> List[Dict[str, Any]]:
+        """
+        Fallback pagination implementation for sales data
+        This replicates your original pagination logic directly
+        """
+        all_records = []
+        page = 0
+        
+        logger.info(f"Starting fallback paginated request for sales data", 
+                   tenant_id=tenant_id, page_size=page_size)
+        
+        while page < max_pages:
+            # Prepare pagination parameters
+            params = base_params.copy()
+            params.update({
+                "limit": page_size,
+                "offset": page * page_size
+            })
+            
+            logger.info(f"Fetching sales data page {page + 1} (offset: {page * page_size})", 
+                       tenant_id=tenant_id)
+            
+            # Make request using the base client's _make_request method
+            result = await self._make_request(
+                "GET",
+                "sales",
+                tenant_id=tenant_id,
+                params=params,
+                timeout=2000.0
+            )
+            
+            if result is None:
+                logger.error(f"Failed to fetch page {page + 1}", tenant_id=tenant_id)
+                break
+            
+            # Handle different response formats (from your original code)
+            if isinstance(result, list):
+                # Direct list response (no pagination metadata)
+                records = result
+                logger.info(f"Retrieved {len(records)} records from page {page + 1} (direct list)")
+                
+                if len(records) == 0:
+                    logger.info("No records in response, pagination complete")
+                    break
+                elif len(records) < page_size:
+                    # Got fewer than requested, this is the last page
+                    all_records.extend(records)
+                    logger.info(f"Final page: retrieved {len(records)} records, total: {len(all_records)}")
+                    break
+                else:
+                    # Got full page, there might be more
+                    all_records.extend(records)
+                    logger.info(f"Full page retrieved: {len(records)} records, continuing to next page")
+                    
+            elif isinstance(result, dict):
+                # Paginated response format
+                records = result.get('records', result.get('data', []))
+                total_available = result.get('total', 0)
+                
+                logger.info(f"Retrieved {len(records)} records from page {page + 1} (paginated response)")
+                
+                if not records:
+                    logger.info("No more records found in paginated response")
+                    break
+                    
+                all_records.extend(records)
+                
+                # Check if we've got all available records
+                if len(all_records) >= total_available:
+                    logger.info(f"Retrieved all available records: {len(all_records)}/{total_available}")
+                    break
+                    
+            else:
+                logger.warning(f"Unexpected response format: {type(result)}")
+                break
+            
+            page += 1
+        
+        logger.info(f"Fallback pagination complete: fetched {len(all_records)} total records", 
+                   tenant_id=tenant_id, pages_fetched=page)
+        
+        return all_records
+    
+    async def upload_sales_data(
+        self,
+        tenant_id: str,
+        sales_data: List[Dict[str, Any]]
+    ) -> Optional[Dict[str, Any]]:
+        """Upload sales data"""
+        data = {"sales": sales_data}
+        return await self.post("sales", data=data, tenant_id=tenant_id)
+    
+    # ================================================================
+    # WEATHER DATA
+    # ================================================================
+    
+    async def get_weather_historical(
+        self,
+        tenant_id: str,
+        start_date: str,
+        end_date: str,
+        latitude: Optional[float] = None,
+        longitude: Optional[float] = None
+    ) -> Optional[List[Dict[str, Any]]]:
+        """
+        Get weather data for a date range and location
+        Uses POST request as per original implementation
+        """
+        # Prepare request payload with proper date handling
+        payload = {
+            "start_date": start_date,  # Already in ISO format from calling code
+            "end_date": end_date,      # Already in ISO format from calling code
+            "latitude": latitude or 40.4168,  # Default Madrid coordinates
+            "longitude": longitude or -3.7038
+        }
+        
+        logger.info(f"Weather request payload: {payload}", tenant_id=tenant_id)
+        
+        # Use POST request with extended timeout
+        result = await self._make_request(
+            "POST",
+            "weather/historical",
+            tenant_id=tenant_id,
+            data=payload,
+            timeout=2000.0  # Match original timeout
+        )
+        
+        if result:
+            logger.info(f"Successfully fetched {len(result)} weather records")
+            return result
+        else:
+            logger.error("Failed to fetch weather data")
+            return []
+        
+    async def get_weather_forecast(
+        self,
+        tenant_id: str,
+        days: str,
+        latitude: Optional[float] = None,
+        longitude: Optional[float] = None
+    ) -> Optional[List[Dict[str, Any]]]:
+        """
+        Get weather data for a date range and location
+        Uses POST request as per original implementation
+        """
+        # Prepare request payload with proper date handling
+        payload = {
+            "days": days,  # Already in ISO format from calling code
+            "latitude": latitude or 40.4168,  # Default Madrid coordinates
+            "longitude": longitude or -3.7038
+        }
+        
+        logger.info(f"Weather request payload: {payload}", tenant_id=tenant_id)
+        
+        # Use POST request with extended timeout
+        result = await self._make_request(
+            "POST",
+            "weather/historical",
+            tenant_id=tenant_id,
+            data=payload,
+            timeout=2000.0  # Match original timeout
+        )
+        
+        if result:
+            logger.info(f"Successfully fetched {len(result)} weather forecast for {days}")
+            return result
+        else:
+            logger.error("Failed to fetch weather data")
+            return []
+    
+    # ================================================================
+    # TRAFFIC DATA  
+    # ================================================================
+    
+    async def get_traffic_data(
+        self,
+        tenant_id: str,
+        start_date: str,
+        end_date: str,
+        latitude: Optional[float] = None,
+        longitude: Optional[float] = None
+    ) -> Optional[List[Dict[str, Any]]]:
+        """
+        Get traffic data for a date range and location
+        Uses POST request with extended timeout for Madrid traffic data processing
+        """
+        # Prepare request payload
+        payload = {
+            "start_date": start_date,  # Already in ISO format from calling code
+            "end_date": end_date,      # Already in ISO format from calling code
+            "latitude": latitude or 40.4168,  # Default Madrid coordinates
+            "longitude": longitude or -3.7038
+        }
+        
+        logger.info(f"Traffic request payload: {payload}", tenant_id=tenant_id)
+        
+        # Madrid traffic data can take 5-10 minutes to download and process
+        traffic_timeout = httpx.Timeout(
+            connect=30.0,    # Connection timeout
+            read=600.0,      # Read timeout: 10 minutes (was 30s)
+            write=30.0,      # Write timeout
+            pool=30.0        # Pool timeout
+        )
+        
+        # Use POST request with extended timeout
+        result = await self._make_request(
+            "POST",
+            "traffic/historical", 
+            tenant_id=tenant_id,
+            data=payload,
+            timeout=traffic_timeout
+        )
+        
+        if result:
+            logger.info(f"Successfully fetched {len(result)} traffic records")
+            return result
+        else:
+            logger.error("Failed to fetch traffic data")
+            return []
+    
+    # ================================================================
+    # PRODUCTS
+    # ================================================================
+    
+    async def get_products(self, tenant_id: str) -> Optional[List[Dict[str, Any]]]:
+        """Get all products for a tenant"""
+        result = await self.get("products", tenant_id=tenant_id)
+        return result.get("products", []) if result else None
+    
+    async def get_product(self, tenant_id: str, product_id: str) -> Optional[Dict[str, Any]]:
+        """Get a specific product"""
+        return await self.get(f"products/{product_id}", tenant_id=tenant_id)
+    
+    async def create_product(
+        self,
+        tenant_id: str,
+        name: str,
+        category: str,
+        price: float,
+        **kwargs
+    ) -> Optional[Dict[str, Any]]:
+        """Create a new product"""
+        data = {
+            "name": name,
+            "category": category,
+            "price": price,
+            **kwargs
+        }
+        return await self.post("products", data=data, tenant_id=tenant_id)
+    
+    async def update_product(
+        self,
+        tenant_id: str,
+        product_id: str,
+        **updates
+    ) -> Optional[Dict[str, Any]]:
+        """Update a product"""
+        return await self.put(f"products/{product_id}", data=updates, tenant_id=tenant_id)
+    
+    # ================================================================
+    # STORES & LOCATIONS
+    # ================================================================
+    
+    async def get_stores(self, tenant_id: str) -> Optional[List[Dict[str, Any]]]:
+        """Get all stores for a tenant"""
+        result = await self.get("stores", tenant_id=tenant_id)
+        return result.get("stores", []) if result else None
+    
+    async def get_store(self, tenant_id: str, store_id: str) -> Optional[Dict[str, Any]]:
+        """Get a specific store"""
+        return await self.get(f"stores/{store_id}", tenant_id=tenant_id)
+    
+    # ================================================================
+    # DATA VALIDATION & HEALTH
+    # ================================================================
+    
+    async def validate_data_quality(
+        self,
+        tenant_id: str,
+        start_date: str,
+        end_date: str
+    ) -> Optional[Dict[str, Any]]:
+        """Validate data quality for a date range"""
+        params = {
+            "start_date": start_date,
+            "end_date": end_date
+        }
+        return await self.get("validation", tenant_id=tenant_id, params=params)
+    
+    async def get_data_statistics(
+        self,
+        tenant_id: str,
+        start_date: Optional[str] = None,
+        end_date: Optional[str] = None
+    ) -> Optional[Dict[str, Any]]:
+        """Get data statistics for a tenant"""
+        params = {}
+        if start_date:
+            params["start_date"] = start_date
+        if end_date:
+            params["end_date"] = end_date
+        
+        return await self.get("statistics", tenant_id=tenant_id, params=params)

shared/clients/forecast_client.py

@@ -0,0 +1,175 @@
+# shared/clients/forecast_client.py
+"""
+Forecast Service Client
+Handles all API calls to the forecasting service
+"""
+
+from typing import Dict, Any, Optional, List
+from .base_service_client import BaseServiceClient
+from shared.config.base import BaseServiceSettings
+
+
+class ForecastServiceClient(BaseServiceClient):
+    """Client for communicating with the forecasting service"""
+    
+    def __init__(self, config: BaseServiceSettings, calling_service_name: str = "unknown"):
+        super().__init__(calling_service_name, config)
+    
+    def get_service_base_path(self) -> str:
+        return "/api/v1"
+    
+    # ================================================================
+    # FORECASTS
+    # ================================================================
+    
+    async def create_forecast(
+        self,
+        tenant_id: str,
+        model_id: str,
+        start_date: str,
+        end_date: str,
+        product_ids: Optional[List[str]] = None,
+        include_confidence_intervals: bool = True,
+        **kwargs
+    ) -> Optional[Dict[str, Any]]:
+        """Create a new forecast"""
+        data = {
+            "model_id": model_id,
+            "start_date": start_date,
+            "end_date": end_date,
+            "include_confidence_intervals": include_confidence_intervals,
+            **kwargs
+        }
+        if product_ids:
+            data["product_ids"] = product_ids
+        
+        return await self.post("forecasts", data=data, tenant_id=tenant_id)
+    
+    async def get_forecast(self, tenant_id: str, forecast_id: str) -> Optional[Dict[str, Any]]:
+        """Get forecast details"""
+        return await self.get(f"forecasts/{forecast_id}", tenant_id=tenant_id)
+    
+    async def list_forecasts(
+        self,
+        tenant_id: str,
+        status: Optional[str] = None,
+        model_id: Optional[str] = None,
+        limit: int = 50
+    ) -> Optional[List[Dict[str, Any]]]:
+        """List forecasts for a tenant"""
+        params = {"limit": limit}
+        if status:
+            params["status"] = status
+        if model_id:
+            params["model_id"] = model_id
+        
+        result = await self.get("forecasts", tenant_id=tenant_id, params=params)
+        return result.get("forecasts", []) if result else None
+    
+    async def delete_forecast(self, tenant_id: str, forecast_id: str) -> Optional[Dict[str, Any]]:
+        """Delete a forecast"""
+        return await self.delete(f"forecasts/{forecast_id}", tenant_id=tenant_id)
+    
+    # ================================================================
+    # PREDICTIONS
+    # ================================================================
+    
+    async def get_predictions(
+        self,
+        tenant_id: str,
+        forecast_id: str,
+        start_date: Optional[str] = None,
+        end_date: Optional[str] = None,
+        product_id: Optional[str] = None
+    ) -> Optional[List[Dict[str, Any]]]:
+        """Get predictions from a forecast"""
+        params = {}
+        if start_date:
+            params["start_date"] = start_date
+        if end_date:
+            params["end_date"] = end_date
+        if product_id:
+            params["product_id"] = product_id
+        
+        result = await self.get(f"forecasts/{forecast_id}/predictions", tenant_id=tenant_id, params=params)
+        return result.get("predictions", []) if result else None
+    
+    async def create_realtime_prediction(
+        self,
+        tenant_id: str,
+        model_id: str,
+        target_date: str,
+        features: Dict[str, Any],
+        **kwargs
+    ) -> Optional[Dict[str, Any]]:
+        """Create a real-time prediction"""
+        data = {
+            "model_id": model_id,
+            "target_date": target_date,
+            "features": features,
+            **kwargs
+        }
+        return await self.post("predictions", data=data, tenant_id=tenant_id)
+    
+    # ================================================================
+    # FORECAST VALIDATION & METRICS
+    # ================================================================
+    
+    async def get_forecast_accuracy(
+        self,
+        tenant_id: str,
+        forecast_id: str,
+        start_date: Optional[str] = None,
+        end_date: Optional[str] = None
+    ) -> Optional[Dict[str, Any]]:
+        """Get forecast accuracy metrics"""
+        params = {}
+        if start_date:
+            params["start_date"] = start_date
+        if end_date:
+            params["end_date"] = end_date
+        
+        return await self.get(f"forecasts/{forecast_id}/accuracy", tenant_id=tenant_id, params=params)
+    
+    async def compare_forecasts(
+        self,
+        tenant_id: str,
+        forecast_ids: List[str],
+        metric: str = "mape"
+    ) -> Optional[Dict[str, Any]]:
+        """Compare multiple forecasts"""
+        data = {
+            "forecast_ids": forecast_ids,
+            "metric": metric
+        }
+        return await self.post("forecasts/compare", data=data, tenant_id=tenant_id)
+    
+    # ================================================================
+    # FORECAST SCENARIOS
+    # ================================================================
+    
+    async def create_scenario_forecast(
+        self,
+        tenant_id: str,
+        model_id: str,
+        scenario_name: str,
+        scenario_data: Dict[str, Any],
+        start_date: str,
+        end_date: str,
+        **kwargs
+    ) -> Optional[Dict[str, Any]]:
+        """Create a scenario-based forecast"""
+        data = {
+            "model_id": model_id,
+            "scenario_name": scenario_name,
+            "scenario_data": scenario_data,
+            "start_date": start_date,
+            "end_date": end_date,
+            **kwargs
+        }
+        return await self.post("scenarios", data=data, tenant_id=tenant_id)
+    
+    async def list_scenarios(self, tenant_id: str) -> Optional[List[Dict[str, Any]]]:
+        """List forecast scenarios for a tenant"""
+        result = await self.get("scenarios", tenant_id=tenant_id)
+        return result.get("scenarios", []) if result else None

shared/clients/training_client.py

@@ -0,0 +1,134 @@
+# shared/clients/training_client.py
+"""
+Training Service Client
+Handles all API calls to the training service
+"""
+
+from typing import Dict, Any, Optional, List
+from .base_service_client import BaseServiceClient
+from shared.config.base import BaseServiceSettings
+
+
+class TrainingServiceClient(BaseServiceClient):
+    """Client for communicating with the training service"""
+    
+    def __init__(self, config: BaseServiceSettings, calling_service_name: str = "unknown"):
+        super().__init__(calling_service_name, config)
+    
+    def get_service_base_path(self) -> str:
+        return "/api/v1"
+    
+    # ================================================================
+    # TRAINING JOBS
+    # ================================================================
+    
+    async def create_training_job(
+        self,
+        tenant_id: str,
+        include_weather: bool = True,
+        include_traffic: bool = False,
+        min_data_points: int = 30,
+        **kwargs
+    ) -> Optional[Dict[str, Any]]:
+        """Create a new training job"""
+        data = {
+            "include_weather": include_weather,
+            "include_traffic": include_traffic,
+            "min_data_points": min_data_points,
+            **kwargs
+        }
+        return await self.post("jobs", data=data, tenant_id=tenant_id)
+    
+    async def get_training_job(self, tenant_id: str, job_id: str) -> Optional[Dict[str, Any]]:
+        """Get training job details"""
+        return await self.get(f"jobs/{job_id}", tenant_id=tenant_id)
+    
+    async def list_training_jobs(
+        self,
+        tenant_id: str,
+        status: Optional[str] = None,
+        limit: int = 50
+    ) -> Optional[List[Dict[str, Any]]]:
+        """List training jobs for a tenant"""
+        params = {"limit": limit}
+        if status:
+            params["status"] = status
+        
+        result = await self.get("jobs", tenant_id=tenant_id, params=params)
+        return result.get("jobs", []) if result else None
+    
+    async def cancel_training_job(self, tenant_id: str, job_id: str) -> Optional[Dict[str, Any]]:
+        """Cancel a training job"""
+        return await self.delete(f"jobs/{job_id}", tenant_id=tenant_id)
+    
+    # ================================================================
+    # MODELS
+    # ================================================================
+    
+    async def get_model(self, tenant_id: str, model_id: str) -> Optional[Dict[str, Any]]:
+        """Get model details"""
+        return await self.get(f"models/{model_id}", tenant_id=tenant_id)
+    
+    async def list_models(
+        self,
+        tenant_id: str,
+        status: Optional[str] = None,
+        model_type: Optional[str] = None,
+        limit: int = 50
+    ) -> Optional[List[Dict[str, Any]]]:
+        """List models for a tenant"""
+        params = {"limit": limit}
+        if status:
+            params["status"] = status
+        if model_type:
+            params["model_type"] = model_type
+        
+        result = await self.get("models", tenant_id=tenant_id, params=params)
+        return result.get("models", []) if result else None
+    
+    async def get_latest_model(
+        self,
+        tenant_id: str,
+        model_type: Optional[str] = None
+    ) -> Optional[Dict[str, Any]]:
+        """Get the latest trained model for a tenant"""
+        params = {"latest": "true"}
+        if model_type:
+            params["model_type"] = model_type
+        
+        result = await self.get("models", tenant_id=tenant_id, params=params)
+        models = result.get("models", []) if result else []
+        return models[0] if models else None
+    
+    async def deploy_model(self, tenant_id: str, model_id: str) -> Optional[Dict[str, Any]]:
+        """Deploy a trained model"""
+        return await self.post(f"models/{model_id}/deploy", data={}, tenant_id=tenant_id)
+    
+    async def delete_model(self, tenant_id: str, model_id: str) -> Optional[Dict[str, Any]]:
+        """Delete a model"""
+        return await self.delete(f"models/{model_id}", tenant_id=tenant_id)
+    
+    # ================================================================
+    # MODEL METRICS & PERFORMANCE
+    # ================================================================
+    
+    async def get_model_metrics(self, tenant_id: str, model_id: str) -> Optional[Dict[str, Any]]:
+        """Get model performance metrics"""
+        return await self.get(f"models/{model_id}/metrics", tenant_id=tenant_id)
+    
+    async def get_model_predictions(
+        self,
+        tenant_id: str,
+        model_id: str,
+        start_date: Optional[str] = None,
+        end_date: Optional[str] = None
+    ) -> Optional[List[Dict[str, Any]]]:
+        """Get model predictions for evaluation"""
+        params = {}
+        if start_date:
+            params["start_date"] = start_date
+        if end_date:
+            params["end_date"] = end_date
+        
+        result = await self.get(f"models/{model_id}/predictions", tenant_id=tenant_id, params=params)
+        return result.get("predictions", []) if result else None

tests/test_onboarding_flow.sh

@@ -569,28 +569,22 @@ echo ""
 
 log_step "5.1. Testing basic dashboard functionality"
 
-# Test basic forecasting capability (if training completed)
+# Use a real product name from our CSV for forecasting
-if [ -n "$TRAINING_TASK_ID" ]; then
+FIRST_PRODUCT=$(echo "$REAL_PRODUCTS" | sed 's/"//g' | cut -d',' -f1)
-    # Use a real product name from our CSV for forecasting
-    FIRST_PRODUCT=$(echo "$REAL_PRODUCTS" | sed 's/"//g' | cut -d',' -f1)
     
-    FORECAST_RESPONSE=$(curl -s -X POST "$API_BASE/api/v1/forecasting/predict" \
+FORECAST_RESPONSE=$(curl -s -X POST "$API_BASE/api/v1/tenants/$TENANT_ID/forecast/single" \
-        -H "Content-Type: application/json" \
+    -H "Content-Type: application/json" \
-        -H "Authorization: Bearer $ACCESS_TOKEN" \
+    -H "Authorization: Bearer $ACCESS_TOKEN" \
-        -H "X-Tenant-ID: $TENANT_ID" \
+    -d "{
-        -d "{
+        \"products\": [\"$FIRST_PRODUCT\"],
-            \"products\": [\"$FIRST_PRODUCT\"],
+        \"forecast_days\": 7,
-            \"forecast_days\": 7,
+        \"date\": \"2025-09-15\"
-            \"date\": \"2024-01-15\"
         }")
     
-    if echo "$FORECAST_RESPONSE" | grep -q '"predictions"\|"forecast"'; then
+if echo "$FORECAST_RESPONSE" | grep -q '"predictions"\|"forecast"'; then
-        log_success "Forecasting service is accessible"
+    log_success "Forecasting service is accessible"
-    else
-        log_warning "Forecasting may not be ready yet (model training required)"
-    fi
 else
-    log_warning "Skipping forecast test - no training task ID available"
+    log_warning "Forecasting may not be ready yet (model training required)"
 fi
 
 echo ""