projectApp / app.py
Swathi6's picture
Create app.py
5cd0c37 verified
raw
history blame
19.8 kB
from fastapi import FastAPI, HTTPException, Header
from pydantic import BaseModel
from reportlab.lib.pagesizes import letter
from reportlab.pdfgen import canvas
import base64
import os
import logging
from datetime import datetime
from fastapi.responses import HTMLResponse
from simple_salesforce import Salesforce
import json
# Set up logging to capture errors and debug information
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
app = FastAPI()
# Salesforce credentials
SF_USERNAME = os.getenv("SF_USERNAME", "[email protected]")
SF_PASSWORD = os.getenv("SF_PASSWORD", "Internal@1")
SF_SECURITY_TOKEN = os.getenv("SF_SECURITY_TOKEN", "NbUKcTx45azba5HEdntE9YAh")
SF_DOMAIN = os.getenv("SF_DOMAIN", "login")
# Verify API key is set
API_KEY = os.getenv("HUGGINGFACE_API_KEY")
if not API_KEY:
logger.error("HUGGINGFACE_API_KEY environment variable not set")
raise ValueError("HUGGINGFACE_API_KEY environment variable not set")
# Connect to Salesforce
try:
sf = Salesforce(
username=SF_USERNAME,
password=SF_PASSWORD,
security_token=SF_SECURITY_TOKEN,
domain=SF_DOMAIN
)
logger.info("Successfully connected to Salesforce")
except Exception as e:
logger.error(f"Failed to connect to Salesforce: {str(e)}")
raise
# VendorLog model to match Salesforce data
class VendorLog(BaseModel):
vendorLogId: str
vendorId: str
vendorRecordId: str
workDetails: str
qualityReport: str
incidentLog: str
workCompletionDate: str
actualCompletionDate: str
vendorLogName: str
delayDays: int
project: str
# Store vendor logs for display
vendor_logs = []
def fetch_vendor_logs_from_salesforce():
try:
query = """
SELECT Id, Name, Vendor__c, Work_Completion_Percentage__c, Quality_Percentage__c, Incident_Severity__c,
Work_Completion_Date__c, Actual_Completion_Date__c, Delay_Days__c,Project__c
FROM Vendor_Log__c
"""
result = sf.query_all(query)
logs = []
for record in result['records']:
if not record['Vendor__c']:
logger.warning(f"Skipping Vendor_Log__c record with ID {record['Id']} due to missing Vendor__c")
continue
log = VendorLog(
vendorLogId=record['Id'] or "Unknown",
vendorId=record['Name'] or "Unknown",
vendorRecordId=record['Vendor__c'] or "Unknown",
workDetails=str(record['Work_Completion_Percentage__c'] or "0.0"),
qualityReport=str(record['Quality_Percentage__c'] or "0.0"),
incidentLog=record['Incident_Severity__c'] or "None",
workCompletionDate=record['Work_Completion_Date__c'] or "N/A",
actualCompletionDate=record['Actual_Completion_Date__c'] or "N/A",
vendorLogName=record['Name'] or "Unknown",
delayDays=int(record['Delay_Days__c'] or 0),
project=record['Project__c'] or "Unknown"
)
logs.append(log)
return logs
except Exception as e:
logger.error(f"Error fetching vendor logs from Salesforce: {str(e)}")
raise
def calculate_scores(log: VendorLog):
try:
work_completion_percentage = float(log.workDetails)
quality_percentage = float(log.qualityReport)
# Quality Score: Directly use the quality percentage
quality_score = quality_percentage
# Timeliness Score: Based on delay days
timeliness_score = 100.0 if log.delayDays <= 0 else 80.0 if log.delayDays <= 3 else 60.0 if log.delayDays <= 7 else 40.0
# Safety Score: Based on incident severity
severity_map = {'None': 100.0, 'Low': 80.0, 'Minor': 80.0, 'Medium': 50.0, 'High': 20.0}
safety_score = severity_map.get(log.incidentLog, 100.0)
# Communication Score: Weighted average of other scores
communication_score = (quality_score * 0.33 + timeliness_score * 0.33 + safety_score * 0.33)
# Removed finalScore calculation since Final_Score__c is a Formula field
return {
'qualityScore': round(quality_score, 2),
'timelinessScore': round(timeliness_score, 2),
'safetyScore': round(safety_score, 2),
'communicationScore': round(communication_score, 2)
}
except Exception as e:
logger.error(f"Error calculating scores: {str(e)}")
raise
def get_feedback(score: float, metric: str) -> str:
try:
if score >= 90:
return "Excellent: Maintain this standard"
elif score >= 70:
return "Good: Keep up the good work"
elif score >= 50:
if metric == 'Timeliness':
return "Needs Improvement: Maintain schedules to complete tasks on time"
elif metric == 'Safety':
return "Needs Improvement: Implement stricter safety protocols"
elif metric == 'Quality':
return "Needs Improvement: Focus on improving work quality"
else:
return "Needs Improvement: Enhance coordination with project teams"
else:
if metric == 'Timeliness':
return "Poor: Significant delays detected"
elif metric == 'Safety':
return "Poor: Critical safety issues identified"
elif metric == 'Quality':
return "Poor: Quality standards not met"
else:
return "Poor: Communication issues detected"
except Exception as e:
logger.error(f"Error generating feedback: {str(e)}")
raise
def generate_pdf(vendor_id: str, vendor_log_name: str, scores: dict):
try:
filename = f'report_{vendor_id}.pdf'
c = canvas.Canvas(filename, pagesize=letter)
c.setFont('Helvetica', 12)
c.drawString(100, 750, 'Subcontractor Performance Report')
c.drawString(100, 730, f'Vendor ID: {vendor_id}')
c.drawString(100, 710, f'Vendor Log Name: {vendor_log_name}')
c.drawString(100, 690, f'Quality Score: {scores["qualityScore"]}% ({get_feedback(scores["qualityScore"], "Quality")})')
c.drawString(100, 670, f'Timeliness Score: {scores["timelinessScore"]}% ({get_feedback(scores["timelinessScore"], "Timeliness")})')
c.drawString(100, 650, f'Safety Score: {scores["safetyScore"]}% ({get_feedback(scores["safetyScore"], "Safety")})')
c.drawString(100, 630, f'Communication Score: {scores["communicationScore"]}% ({get_feedback(scores["communicationScore"], "Communication")})')
# Removed Final Score from PDF since it's a Formula field
c.save()
with open(filename, 'rb') as f:
pdf_content = f.read()
os.remove(filename)
return pdf_content
except Exception as e:
logger.error(f"Error generating PDF: {str(e)}")
raise
def determine_alert_flag(scores: dict, all_logs: list):
try:
if not all_logs:
return False
# Since finalScore is a Formula field, we'll need to fetch it from Salesforce or adjust logic
# For now, we'll base the alert on the average of other scores
avg_score = (scores['qualityScore'] + scores['timelinessScore'] + scores['safetyScore'] + scores['communicationScore']) / 4
if avg_score < 50:
return True
lowest_avg = min([(log['scores']['qualityScore'] + log['scores']['timelinessScore'] + log['scores']['safetyScore'] + log['scores']['communicationScore']) / 4 for log in all_logs])
return avg_score == lowest_avg
except Exception as e:
logger.error(f"Error determining alert flag: {str(e)}")
raise
def store_scores_in_salesforce(log: VendorLog, scores: dict, pdf_content: bytes, alert_flag: bool):
try:
# Step 1: Create the Subcontractor_Performance_Score__c record without Final_Score__c
score_record = sf.Subcontractor_Performance_Score__c.create({
'Vendor_Log__c': log.vendorLogId,
'Vendor__c': log.vendorRecordId,
'Quality_Score__c': scores['qualityScore'],
'Timeliness_Score__c': scores['timelinessScore'],
'Safety_Score__c': scores['safetyScore'],
'Communication_Score__c': scores['communicationScore'],
'Alert_Flag__c': alert_flag
# Removed Final_Score__c since it's a Formula field
})
score_record_id = score_record['id']
logger.info(f"Successfully created Subcontractor_Performance_Score__c record with ID: {score_record_id}")
# Step 2: Upload the PDF as a ContentVersion
pdf_base64 = base64.b64encode(pdf_content).decode('utf-8')
content_version = sf.ContentVersion.create({
'Title': f'Performance_Report_{log.vendorId}',
'PathOnClient': f'report_{log.vendorId}.pdf',
'VersionData': pdf_base64,
'FirstPublishLocationId': score_record_id
})
logger.info(f"Successfully uploaded PDF as ContentVersion for Vendor Log ID: {log.vendorLogId}")
# Step 3: Get the ContentDocumentId and construct a URL to the file
content_version_id = content_version['id']
content_version_record = sf.query(f"SELECT ContentDocumentId FROM ContentVersion WHERE Id = '{content_version_id}'")
content_document_id = content_version_record['records'][0]['ContentDocumentId']
# Construct the URL to the file
pdf_url = f"https://{sf.sf_instance}/sfc/servlet.shepherd/document/download/{content_document_id}"
# Step 4: Update the Subcontractor_Performance_Score__c record with the PDF URL
sf.Subcontractor_Performance_Score__c.update(score_record_id, {
'PDF_Link__c': pdf_url
})
logger.info(f"Successfully updated Subcontractor_Performance_Score__c record with PDF URL: {pdf_url}")
except Exception as e:
logger.error(f"Error storing scores in Salesforce: {str(e)}")
raise
@app.post('/score')
async def score_vendor(log: VendorLog, authorization: str = Header(...)):
try:
logger.info(f"Received Vendor Log: {log}")
if authorization != f'Bearer {API_KEY}':
raise HTTPException(status_code=401, detail='Invalid API key')
scores = calculate_scores(log)
pdf_content = generate_pdf(log.vendorId, log.vendorLogName, scores)
pdf_base64 = base64.b64encode(pdf_content).decode('utf-8')
alert_flag = determine_alert_flag(scores, vendor_logs)
store_scores_in_salesforce(log, scores, pdf_content, alert_flag)
vendor_logs.append({
'vendorLogId': log.vendorLogId,
'vendorId': log.vendorId,
'vendorLogName': log.vendorLogName,
'workDetails': log.workDetails,
'qualityReport': log.qualityReport,
'incidentLog': log.incidentLog,
'workCompletionDate': log.workCompletionDate,
'actualCompletionDate': log.actualCompletionDate,
'delayDays': log.delayDays,
'project': log.project,
'scores': scores,
'extracted': True
})
return {
'vendorLogId': log.vendorLogId,
'vendorId': log.vendorId,
'vendorLogName': log.vendorLogName,
'qualityScore': scores['qualityScore'],
'timelinessScore': scores['timelinessScore'],
'safetyScore': scores['safetyScore'],
'communicationScore': scores['communicationScore'],
'pdfContent': pdf_base64,
'alert': alert_flag
}
except Exception as e:
logger.error(f"Error in /score endpoint: {str(e)}")
raise HTTPException(status_code=500, detail=f"Error processing vendor log: {str(e)}")
@app.get('/', response_class=HTMLResponse)
async def get_dashboard():
try:
global vendor_logs
fetched_logs = fetch_vendor_logs_from_salesforce()
for log in fetched_logs:
if not any(existing_log['vendorLogId'] == log.vendorLogId for existing_log in vendor_logs):
scores = calculate_scores(log)
pdf_content = generate_pdf(log.vendorId, log.vendorLogName, scores)
pdf_base64 = base64.b64encode(pdf_content).decode('utf-8')
alert_flag = determine_alert_flag(scores, vendor_logs)
store_scores_in_salesforce(log, scores, pdf_content, alert_flag)
vendor_logs.append({
'vendorLogId': log.vendorLogId,
'vendorId': log.vendorId,
'vendorLogName': log.vendorLogName,
'workDetails': log.workDetails,
'qualityReport': log.qualityReport,
'incidentLog': log.incidentLog,
'workCompletionDate': log.workCompletionDate,
'actualCompletionDate': log.actualCompletionDate,
'delayDays': log.delayDays,
'project': log.project,
'scores': scores,
'extracted': True
})
html_content = """
<html>
<head>
<title>Subcontractor Performance Score App</title>
<style>
body { font-family: Arial, sans-serif; margin: 20px; }
table { width: 100%; border-collapse: collapse; margin-top: 20px; }
th, td { border: 1px solid #ddd; padding: 8px; text-align: left; }
th { background-color: #f2f2f2; }
h1, h2 { text-align: center; }
.generate-btn {
display: block;
margin: 20px auto;
padding: 10px 20px;
background-color: #4CAF50;
color: white;
border: none;
border-radius: 5px;
cursor: pointer;
font-size: 16px;
}
.generate-btn:hover { background-color: #45a049; }
</style>
<script>
async function generateScores() {
const response = await fetch('/generate', { method: 'POST' });
if (response.ok) {
window.location.reload();
} else {
alert('Error generating scores');
}
}
</script>
</head>
<body>
<h1>SUBCONTRACTOR PERFORMANCE SCORE APP GENERATOR</h1>
<h2>VENDOR LOGS SUBMISSION</h2>
<table>
<tr>
<th>Vendor ID</th>
<th>Vendor Log Name</th>
<th>Project</th>
<th>Work Completion Percentage</th>
<th>Quality Percentage</th>
<th>Incident Severity</th>
<th>Work Completion Date</th>
<th>Actual Completion Date</th>
<th>Delay Days</th>
</tr>
"""
if not vendor_logs:
html_content += """
<tr>
<td colspan="9" style="text-align: center;">No vendor logs available</td>
</tr>
"""
else:
for log in vendor_logs:
html_content += f"""
<tr>
<td>{log['vendorId']}</td>
<td>{log['vendorLogName']}</td>
<td>{log['project']}</td>
<td>{log['workDetails']}</td>
<td>{log['qualityReport']}</td>
<td>{log['incidentLog']}</td>
<td>{log['workCompletionDate']}</td>
<td>{log['actualCompletionDate']}</td>
<td>{log['delayDays']}</td>
</tr>
"""
html_content += """
</table>
<button class="generate-btn" onclick="generateScores()">Generate</button>
<h2>SUBCONTRACTOR PERFORMANCE SCORES</h2>
<table>
<tr>
<th>Vendor ID</th>
<th>Vendor Log Name</th>
<th>Project</th>
<th>Quality Score</th>
<th>Timeliness Score</th>
<th>Safety Score</th>
<th>Communication Score</th>
<th>Alert Flag</th>
</tr>
"""
if not vendor_logs:
html_content += """
<tr>
<td colspan="8" style="text-align: center;">No scores available</td>
</tr>
"""
else:
for log in vendor_logs:
scores = log['scores']
alert_flag = determine_alert_flag(scores, vendor_logs)
html_content += f"""
<tr>
<td>{log['vendorId']}</td>
<td>{log['vendorLogName']}</td>
<td>{log['project']}</td>
<td>{scores['qualityScore']}%</td>
<td>{scores['timelinessScore']}%</td>
<td>{scores['safetyScore']}%</td>
<td>{scores['communicationScore']}%</td>
<td>{'Checked' if alert_flag else 'Unchecked'}</td>
</tr>
"""
html_content += """
</table>
</body>
</html>
"""
return HTMLResponse(content=html_content)
except Exception as e:
logger.error(f"Error in / endpoint: {str(e)}")
raise HTTPException(status_code=500, detail=f"Error generating dashboard: {str(e)}")
@app.post('/generate')
async def generate_scores():
try:
global vendor_logs
fetched_logs = fetch_vendor_logs_from_salesforce()
vendor_logs = []
for log in fetched_logs:
scores = calculate_scores(log)
pdf_content = generate_pdf(log.vendorId, log.vendorLogName, scores)
pdf_base64 = base64.b64encode(pdf_content).decode('utf-8')
alert_flag = determine_alert_flag(scores, vendor_logs)
store_scores_in_salesforce(log, scores, pdf_content, alert_flag)
vendor_logs.append({
'vendorLogId': log.vendorLogId,
'vendorId': log.vendorId,
'vendorLogName': log.vendorLogName,
'workDetails': log.workDetails,
'qualityReport': log.qualityReport,
'incidentLog': log.incidentLog,
'workCompletionDate': log.workCompletionDate,
'actualCompletionDate': log.actualCompletionDate,
'delayDays': log.delayDays,
'project': log.project,
'scores': scores,
'extracted': True
})
return {"status": "success"}
except Exception as e:
logger.error(f"Error in /generate endpoint: {str(e)}")
raise HTTPException(status_code=500, detail=f"Error generating scores: {str(e)}")
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=7860)