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| import gradio as gr | |
| import os | |
| import json | |
| from data_service import DataAssessmentService | |
| from sheets_integration import SheetsLogger | |
| from datetime import datetime | |
| # Initialize services | |
| service = DataAssessmentService(api_key=os.environ.get("OPENAI_API_KEY")) | |
| sheets_logger = SheetsLogger() | |
| # Department mapping from abbreviations to full names | |
| DEPARTMENTS = { | |
| "Executive Management": "บริหาร ผอ รอง ผู้ช่วย", | |
| "Education Support": "สนับสนุนการศึกษา", | |
| "Medicine": "MED", | |
| "Cardiology": "Cardio", | |
| "Gastroenterology": "GI", | |
| "Medical Oncology": "Onco MED", | |
| "Hematology": "Hematology", | |
| "Operating Room": "OR", | |
| "Surgery": "Sx", | |
| "Orthopedics": "Ortho", | |
| "Obstetrics and Gynecology": "OBgyne", | |
| "Ophthalmology": "Oph", | |
| "Ear, Nose, and Throat": "ENT", | |
| "Anesthesiology": "Anes", | |
| "Emergency Medicine & EMS": "ER and EMS", | |
| "Pediatrics": "PED", | |
| "Family Medicine & Preventive Medicine": "GP Fammed preventive med", | |
| "Psychiatry": "Psych", | |
| "Physical Medicine & Rehabilitation": "PM&R Physiotherapy", | |
| "Pathology": "Patho", | |
| "Radiology": "Xray", | |
| "Radiation Oncology": "Onco radiology", | |
| "Cyclotron": "Cyclotron", | |
| "Inpatient Department": "IPD", | |
| "Outpatient Department": "OPD", | |
| "Pharmacy": "Pharmacy", | |
| "Dentistry": "dentistry", | |
| "Nutrition": "Nutrition", | |
| "Medical Records": "เวชระเบียน", | |
| "Finance": "การเงิน", | |
| "Other": "Other" | |
| } | |
| # Frequency options | |
| FREQUENCIES = ["One-time request", "Weekly", "Monthly"] | |
| # Urgency options | |
| URGENCY = ["Within a week", "Within a month", "Within a year"] | |
| # Example requests | |
| EXAMPLE_REQUESTS = """ | |
| ### Example 1: Clinical Data Request | |
| I need OPD patient statistics for the Cardiology department from January to June 2024, including daily patient volume, types of cardiac conditions (ICD-10 codes), average waiting times, and number of follow-up vs. new cases. This data will be used for department capacity planning and resource allocation. | |
| ### Example 2: Quality Improvement Request | |
| Requesting waiting time analysis for all OPD clinics for Q1 2024, including: | |
| - Registration to first nurse contact time | |
| - Nurse station to doctor examination time | |
| - Doctor examination duration | |
| - Time at pharmacy | |
| - Total visit duration | |
| Break down by day of week and time slots (morning/afternoon). This data will help identify service bottlenecks. | |
| ### Example 3: Department Performance Analysis | |
| Need Emergency Department performance data for March 2024: | |
| - Daily patient volume by triage level | |
| - Door-to-doctor times | |
| - Length of stay in ED | |
| - Admission rates | |
| - Transfer rates to other departments | |
| Purpose: Monthly performance review and staff allocation planning. | |
| """ | |
| def format_user_summary(analysis_result): | |
| """Format analysis result into user-friendly summary""" | |
| available = analysis_result.get("data_availability", {}).get("available_reports", []) | |
| data_lake = analysis_result.get("data_lake_requirements", {}).get("reports_needed", []) | |
| unavailable = analysis_result.get("unavailable_data", []) | |
| interpretation = analysis_result.get("request_analysis", {}).get("interpretation", "") | |
| summary = [ | |
| "### Summary of Your Request", | |
| f"**What you need**: {interpretation}\n", | |
| "\n**Data Availability Status:**\n" | |
| ] | |
| if available: | |
| summary.append("✅ **Available in Web Data System:**") | |
| for report in available: | |
| summary.append(f"- {report['name']}") | |
| summary.append(f"\nEstimated processing time: 3 working days\n") | |
| if data_lake: | |
| summary.append("🔄 **Requires Additional Database Query:**") | |
| for report in data_lake: | |
| summary.append(f"- {report['report_type']}") | |
| summary.append(f"\nEstimated processing time: 2 weeks\n") | |
| if unavailable: | |
| summary.append("❌ **Data Not Currently Available:**") | |
| for item in unavailable: | |
| summary.append(f"- {item['report_type']}") | |
| summary.append("\nRecommendation: Schedule a meeting to discuss alternative data sources or solutions\n") | |
| return "\n".join(summary) | |
| def process_request(name, employee_id, email, department, other_dept, request_details, frequency, urgency): | |
| """Process the data request and return both user and technical responses""" | |
| # Debug prints | |
| print(f"Received inputs:") | |
| print(f"Name: {name}") | |
| print(f"Employee ID: {employee_id}") | |
| print(f"Email: {email}") | |
| print(f"Department: {department}") | |
| print(f"Other Dept: {other_dept}") | |
| print(f"Request Details: {request_details}") | |
| print(f"Frequency: {frequency}") | |
| print(f"Urgency: {urgency}") | |
| # Validate inputs | |
| if not all([name, employee_id, email, request_details, department, frequency, urgency]): | |
| print("Validation failed - missing required fields") | |
| return "Please fill in all required fields.", None | |
| # Combine department info | |
| final_department = other_dept if department == "Other" else department | |
| print(f"Final department: {final_department}") | |
| try: | |
| # Process the request through GPT | |
| print("Calling GPT service...") | |
| result = service.assess_request(request_details) | |
| print(f"GPT response: {result}") | |
| # Create user-friendly summary | |
| user_summary = format_user_summary(result) | |
| print(f"Generated summary: {user_summary}") | |
| # Prepare data for logging | |
| sheet_data = { | |
| "timestamp": datetime.now().strftime("%Y-%m-%d %H:%M:%S"), | |
| "name": name, | |
| "employee_id": employee_id, | |
| "email": email, | |
| "department": final_department, | |
| "request_details": request_details, | |
| "frequency": frequency, | |
| "urgency": urgency, | |
| "user_summary": user_summary, | |
| "system_analysis": json.dumps(result, ensure_ascii=False) | |
| } | |
| # Log to Google Sheets | |
| print("Logging to sheets...") | |
| success = sheets_logger.log_request(sheet_data) | |
| print(f"Sheet logging result: {success}") | |
| return user_summary, result | |
| except Exception as e: | |
| error_message = f"Error processing request: {str(e)}" | |
| print(f"Error occurred: {error_message}") | |
| print(f"Full exception: {traceback.format_exc()}") | |
| return error_message, None | |
| # Create Gradio interface | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# Hospital Data Request System") | |
| gr.Markdown("Please fill in the following information to request data access.") | |
| # Debug output for monitoring | |
| debug_output = gr.Markdown(visible=False) | |
| with gr.Row(): | |
| with gr.Column(): | |
| name = gr.Textbox( | |
| label="Full Name*", | |
| placeholder="Enter your full name", | |
| value="" # Ensure empty initial value | |
| ) | |
| employee_id = gr.Textbox( | |
| label="Employee ID*", | |
| placeholder="Enter your employee ID", | |
| value="" | |
| ) | |
| email = gr.Textbox( | |
| label="Email*", | |
| placeholder="Enter your email for contact", | |
| value="" | |
| ) | |
| with gr.Row(): | |
| with gr.Column(): | |
| department = gr.Dropdown( | |
| choices=list(DEPARTMENTS.keys()), | |
| label="Department*", | |
| info="Select your department", | |
| value=list(DEPARTMENTS.keys())[0] # Set default value | |
| ) | |
| other_dept = gr.Textbox( | |
| label="Other Department", | |
| placeholder="Specify your department if not in the list", | |
| visible=False, | |
| value="" | |
| ) | |
| # Handle department change | |
| def update_other_dept_visibility(dept): | |
| return gr.update(visible=(dept == "Other")) | |
| department.change( | |
| fn=update_other_dept_visibility, | |
| inputs=department, | |
| outputs=other_dept | |
| ) | |
| # Example requests section | |
| with gr.Accordion("📝 Click here to see example requests", open=False): | |
| gr.Markdown(EXAMPLE_REQUESTS) | |
| with gr.Row(): | |
| request_details = gr.Textbox( | |
| label="Request Details*", | |
| placeholder="Please describe in detail what data you need, including time period, specific parameters, etc.", | |
| lines=5, | |
| value="" | |
| ) | |
| with gr.Row(): | |
| with gr.Column(): | |
| frequency = gr.Dropdown( | |
| choices=FREQUENCIES, | |
| label="Request Frequency*", | |
| value=FREQUENCIES[0] # Set default value | |
| ) | |
| urgency = gr.Dropdown( | |
| choices=URGENCY, | |
| label="Urgency Level*", | |
| value=URGENCY[0] # Set default value | |
| ) | |
| # Submit button and processing | |
| submit_btn = gr.Button("Submit Request", variant="primary") | |
| # Output sections | |
| with gr.Row(): | |
| user_output = gr.Markdown( | |
| label="Request Summary", | |
| value="" | |
| ) | |
| with gr.Accordion("Technical Analysis (For Data Team)", open=False): | |
| tech_output = gr.JSON() | |
| def process_request(name, employee_id, email, department, other_dept, request_details, frequency, urgency): | |
| print(f"Processing request with inputs:") | |
| print(f"Name: {name}") | |
| print(f"Employee ID: {employee_id}") | |
| print(f"Email: {email}") | |
| print(f"Department: {department}") | |
| print(f"Other Dept: {other_dept}") | |
| print(f"Request Details: {request_details}") | |
| print(f"Frequency: {frequency}") | |
| print(f"Urgency: {urgency}") | |
| # Validate inputs | |
| if not all([name, employee_id, email, request_details, department, frequency, urgency]): | |
| print("Validation failed - missing required fields") | |
| return "Please fill in all required fields.", None | |
| # Combine department info | |
| final_department = other_dept if department == "Other" else department | |
| try: | |
| # Process the request through GPT | |
| print("Calling GPT service...") | |
| result = service.assess_request(request_details) | |
| print(f"GPT response received: {result}") | |
| # Create user-friendly summary | |
| user_summary = format_user_summary(result) | |
| # Prepare data for logging | |
| sheet_data = { | |
| "timestamp": datetime.now().strftime("%Y-%m-%d %H:%M:%S"), | |
| "name": name, | |
| "employee_id": employee_id, | |
| "email": email, | |
| "department": final_department, | |
| "request_details": request_details, | |
| "frequency": frequency, | |
| "urgency": urgency, | |
| "user_summary": user_summary, | |
| "system_analysis": json.dumps(result, ensure_ascii=False) | |
| } | |
| # Log to Google Sheets | |
| print("Logging to sheets...") | |
| sheets_logger.log_request(sheet_data) | |
| return user_summary, result | |
| except Exception as e: | |
| error_msg = f"Error processing request: {str(e)}" | |
| print(error_msg) | |
| return error_msg, None | |
| # Connect the submit button to the process function | |
| submit_btn.click( | |
| fn=process_request, | |
| inputs=[ | |
| name, employee_id, email, department, other_dept, | |
| request_details, frequency, urgency | |
| ], | |
| outputs=[user_output, tech_output] | |
| ) | |
| gr.Markdown(""" | |
| ### Notes: | |
| - Fields marked with * are required | |
| - Please provide detailed information about the data you need | |
| - Include specific time periods and parameters | |
| - Clearly state the purpose of your request | |
| - All communications will be sent to the provided email | |
| """) | |
| if __name__ == "__main__": | |
| demo.launch() |