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| 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", "scores@app.com") | |
| 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 | |
| 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)}") | |
| 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)}") | |
| 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) |