Create app.py

app.py

@@ -0,0 +1,98 @@
+from fastapi import FastAPI, HTTPException
+from pydantic import BaseModel
+import simple_salesforce
+import requests
+from typing import Optional
+import os
+
+app = FastAPI()
+
+# Salesforce credentials (replace with environment variables in production)
+SF_USERNAME = "your_salesforce_username"  # Replace with your username
+SF_PASSWORD = "your_salesforce_password"  # Replace with your password
+SF_SECURITY_TOKEN = "BNgBGeH986OPZk0fWxPlIR3Is"
+SF_INSTANCE_URL = "https://aicoachforsitesupervisors-dev-ed.develop.my.salesforce.com"
+
+# OpenWeatherMap API key
+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
+
+# Initialize Salesforce connection
+sf = simple_salesforce.Salesforce(
+    username=SF_USERNAME,
+    password=SF_PASSWORD,
+    security_token=SF_SECURITY_TOKEN,
+    instance_url=SF_INSTANCE_URL
+)
+
+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:
+        return "Weather data unavailable"
+
+def generate_coaching_data(project: dict, role: str) -> dict:
+    """Mock AI model to generate checklist, tips, and engagement score."""
+    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.post("/api/generate")
+async def generate_coaching(request: ProjectRequest):
+    try:
+        # Query Project__c by Supervisor_ID__c (lookup via role or projectId)
+        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"
+        result = sf.query(query)
+        
+        if result['totalSize'] == 0:
+            raise HTTPException(status_code=404, detail="Project not found")
+        
+        project = result['records'][0]
+        
+        # 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']
+        }
+        
+        return response
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+@app.get("/")
+async def root():
+    return {"message": "Welcome to AI Coach API. Use POST /api/generate"}