Create app.py

app.py

@@ -0,0 +1,216 @@
+import logging
+import os
+import uvicorn
+from fastapi import FastAPI, HTTPException
+from fastapi.responses import FileResponse
+from pydantic import BaseModel
+from simple_salesforce import Salesforce
+from contextlib import asynccontextmanager
+import requests
+from typing import Optional
+
+# Set up logging early
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+logger.info("Starting application initialization")
+
+# Load environment variables
+SF_USERNAME = os.getenv('SF_USERNAME')
+SF_PASSWORD = os.getenv('SF_PASSWORD')
+SF_SECURITY_TOKEN = os.getenv('SF_SECURITY_TOKEN')
+
+# Validate environment variables
+required_vars = {
+    'SF_USERNAME': SF_USERNAME,
+    'SF_PASSWORD': SF_PASSWORD,
+    'SF_SECURITY_TOKEN': SF_SECURITY_TOKEN
+}
+missing_vars = [var for var, value in required_vars.items() if not value]
+if missing_vars:
+    logger.error(f"Missing required environment variables: {', '.join(missing_vars)}")
+    raise ValueError(f"Missing required environment variables: {', '.join(missing_vars)}")
+
+# Global Salesforce connection
+sf = None
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    """Manage application lifecycle."""
+    global sf
+    logger.info("Starting application lifecycle")
+    
+    # Initialize Salesforce connection
+    try:
+        sf = Salesforce(
+            username=SF_USERNAME,
+            password=SF_PASSWORD,
+            security_token=SF_SECURITY_TOKEN,
+            instance_url='https://aicoachforsitesupervisors-dev-ed.develop.my.salesforce.com',
+            version='63.0'
+        )
+        logger.info("Successfully connected to Salesforce")
+    except Exception as e:
+        logger.error(f"Failed to connect to Salesforce: {str(e)}")
+        sf = None
+    
+    logger.info("Application initialized successfully")
+    yield
+    logger.info("Shutting down application")
+
+# Initialize FastAPI app with lifespan
+app = FastAPI(lifespan=lifespan)
+
+# OpenWeatherMap API key (hardcoded as it works and doesn't cause issues)
+WEATHER_API_KEY = "60c00e1b8293d3c0482f8d6ca1a37003"
+
+# Pydantic model for request body
+class ProjectRequest(BaseModel):
+    projectId: str
+    projectName: str
+    milestones: Optional[str] = None
+    weatherLogs: Optional[str] = None
+    safetyLogs: Optional[str] = None
+    role: str
+
+def fetch_weather_data(location: str) -> str:
+    """Fetch weather data for a given location."""
+    try:
+        url = f"http://api.openweathermap.org/data/2.5/weather?q={location}&appid={WEATHER_API_KEY}&units=metric"
+        response = requests.get(url)
+        response.raise_for_status()
+        data = response.json()
+        weather = data['weather'][0]['description']
+        temp = data['main']['temp']
+        return f"{weather}, {temp}°C"
+    except Exception as e:
+        logger.error(f"Failed to fetch weather data: {str(e)}")
+        return "Weather data unavailable"
+
+def generate_coaching_data(project: dict, role: str) -> dict:
+    """Mock AI model to generate checklist, tips, and engagement score."""
+    logger.info(f"Generating coaching data for project {project.get('Name')}")
+    checklist = f"1. Review safety protocols for {project.get('Project_Name__c', 'project')}\n2. Check {role} tasks\n3. Update milestones"
+    tips = f"1. Prioritize safety due to {project.get('Weather_Logs__c', 'conditions')}\n2. Focus on {role} responsibilities\n3. Communicate progress"
+    engagement_score = 85.0  # Mock score; replace with real AI model
+    return {
+        "checklist": checklist,
+        "tips": tips,
+        "engagementScore": engagement_score
+    }
+
+@app.get("/api/latest-project")
+async def get_latest_project():
+    """Fetch the latest Project__c record based on CreatedDate."""
+    if sf is None:
+        logger.error("Salesforce connection not initialized")
+        raise HTTPException(status_code=500, detail="Salesforce connection not initialized")
+    
+    try:
+        query = """
+            SELECT Id, Name, Project_Name__c, Milestones__c, Weather_Logs__c, Safety_Logs__c, Location__c, Supervisor_ID__c
+            FROM Project__c
+            ORDER BY CreatedDate DESC
+            LIMIT 1
+        """
+        logger.info(f"Executing SOQL query for latest project: {query}")
+        result = sf.query(query)
+        
+        if result['totalSize'] == 0:
+            logger.warning("No Project__c records found")
+            raise HTTPException(status_code=404, detail="No projects found")
+        
+        project = result['records'][0]
+        logger.info(f"Fetched latest project: {project['Name']}")
+        
+        # Prepare response with extracted fields
+        response = {
+            "projectId": project['Name'],
+            "projectName": project['Project_Name__c'],
+            "milestones": project.get('Milestones__c', ''),
+            "weatherLogs": project.get('Weather_Logs__c', ''),
+            "safetyLogs": project.get('Safety_Logs__c', ''),
+            "role": "Site Manager"  # Default role; can be updated based on Supervisor_ID__c if needed
+        }
+        
+        return response
+    except Exception as e:
+        logger.error(f"Error fetching latest project: {str(e)}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+@app.post("/api/generate")
+async def generate_coaching(request: ProjectRequest):
+    if sf is None:
+        logger.error("Salesforce connection not initialized")
+        raise HTTPException(status_code=500, detail="Salesforce connection not initialized")
+    
+    try:
+        # Query Project__c by projectId to get the full record
+        query = f"SELECT Id, Name, Project_Name__c, Milestones__c, Weather_Logs__c, Safety_Logs__c, Location__c, Supervisor_ID__c FROM Project__c WHERE Name = '{request.projectId}' LIMIT 1"
+        logger.info(f"Executing SOQL query: {query}")
+        result = sf.query(query)
+        
+        if result['totalSize'] == 0:
+            logger.warning(f"Project {request.projectId} not found")
+            raise HTTPException(status_code=404, detail="Project not found")
+        
+        project = result['records'][0]
+        logger.info(f"Retrieved project: {project['Name']}")
+        
+        # Update weather logs if location available
+        if project.get('Location__c'):
+            project['Weather_Logs__c'] = fetch_weather_data(project['Location__c'])
+        
+        # Generate coaching data
+        coaching_data = generate_coaching_data(project, request.role)
+        
+        # Prepare response with extracted fields and generated results
+        response = {
+            "projectId": project['Name'],
+            "projectName": project['Project_Name__c'],
+            "milestones": project.get('Milestones__c', ''),
+            "weatherLogs": project.get('Weather_Logs__c', ''),
+            "safetyLogs": project.get('Safety_Logs__c', ''),
+            "role": request.role,
+            "checklist": coaching_data['checklist'],
+            "tips": coaching_data['tips'],
+            "engagementScore": coaching_data['engagementScore']
+        }
+        
+        # Insert into Supervisor_AI_Coaching__c
+        try:
+            coaching_record = {
+                'Project_ID__c': project['Id'],  # Updated to correct API name for Lookup field
+                'Checklist__c': coaching_data['checklist'],
+                'Tips__c': coaching_data['tips'],
+                'Engagement_Score__c': coaching_data['engagementScore'],
+                'Role__c': request.role,
+                'Project_Name__c': project['Project_Name__c'],
+                'Milestones__c': project.get('Milestones__c', ''),
+                'Weather_Logs__c': project.get('Weather_Logs__c', ''),
+                'Safety_Logs__c': project.get('Safety_Logs__c', '')
+            }
+            sf.Supervisor_AI_Coaching__c.create(coaching_record)
+            logger.info(f"Inserted coaching data into Supervisor_AI_Coaching__c for project {project['Name']}")
+        except Exception as e:
+            logger.error(f"Failed to insert into Supervisor_AI_Coaching__c: {str(e)}")
+            raise HTTPException(status_code=500, detail=f"Failed to save coaching data: {str(e)}")
+        
+        logger.info(f"Generated coaching response: {response}")
+        return response
+    except Exception as e:
+        logger.error(f"Error generating coaching data: {str(e)}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+@app.get("/")
+async def root():
+    logger.info("Serving index.html from root directory")
+    return FileResponse("index.html")
+
+@app.get("/styles.css")
+async def serve_styles():
+    logger.info("Serving styles.css from root directory")
+    return FileResponse("styles.css", media_type="text/css")
+
+# Start Uvicorn server for Hugging Face Spaces
+logger.info("Starting Uvicorn server for Hugging Face Spaces")
+uvicorn.run(app, host="0.0.0.0", port=7860)