Spaces:
Running
Running
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 | |
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 | |
} | |
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)) | |
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)) | |
async def root(): | |
logger.info("Serving index.html from root directory") | |
return FileResponse("index.html") | |
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) |