Update model.py

model.py

@@ -5,6 +5,7 @@ import torch.nn as nn
 import numpy as np
 import pickle
 from sklearn.preprocessing import StandardScaler
+from datetime import datetime, timedelta
 
 # Configure logging
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
@@ -60,7 +61,8 @@ def get_weather_condition(score: int) -> str:
 def call_ai_model_for_insights(input_data: Dict, delay_risk: float) -> List[str]:
     """
     Generate detailed hardcoded insights based on input data and delay risk.
-    Returns 3-5 prioritized, phase/task-specific insights tailored to conditions, with enhanced weather focus.
+    Includes a 2-week risk alert if weather_forecast_date is within 14 days.
+    Returns 3-5 prioritized, phase/task-specific insights.
     """
     logger.info("Generating detailed hardcoded AI insights")
     phase = input_data.get("phase", "")
@@ -74,6 +76,7 @@ def call_ai_model_for_insights(input_data: Dict, delay_risk: float) -> List[str]
     weather_score = input_data.get("weather_impact_score", 0)
     weather_condition = input_data.get("weather_condition", get_weather_condition(weather_score))
     project_location = input_data.get("project_location", "Unknown")
+    weather_forecast_date = input_data.get("weather_forecast_date", "")
 
     # Initialize insights with scores for prioritization
     insights = []
@@ -82,6 +85,25 @@ def call_ai_model_for_insights(input_data: Dict, delay_risk: float) -> List[str]
     def add_insight(message: str, priority: float):
         insights.append((message, priority))
 
+    # 2-week risk alert
+    try:
+        forecast_date = datetime.strptime(weather_forecast_date, "%Y-%m-%d")
+        current_date = datetime(2025, 5, 26)  # Fixed date as per system
+        two_weeks_later = current_date + timedelta(days=14)
+        if current_date <= forecast_date <= two_weeks_later:
+            if delay_risk > 75 or weather_score > 75:
+                add_insight(
+                    f"⚠️ Critical 2-Week Risk Alert: High risk of delay for {phase}: {task} in {project_location} by {weather_forecast_date} due to {'severe weather' if weather_score > 75 else 'high delay probability'}. Implement contingency plans immediately.",
+                    1.2
+                )
+            elif delay_risk > 50 or weather_score > 50:
+                add_insight(
+                    f"⚠️ 2-Week Risk Alert: Moderate risk of delay for {phase}: {task} in {project_location} by {weather_forecast_date}. Monitor closely and prepare mitigation measures.",
+                    1.1
+                )
+    except ValueError:
+        logger.warning("Invalid weather_forecast_date format; skipping 2-week risk alert")
+
     # Delay risk-based insights
     if delay_risk > 75:
         add_insight(f"Urgent: High delay risk detected for {phase}: {task} in {project_location}. Take immediate action.", 1.0)