Update app.py

app.py

@@ -1,40 +1,14 @@
 import gradio as gr
 import os
 import json
-import pandas as pd
 from data_service import DataAssessmentService
-from datetime import datetime
-import gspread
-from oauth2client.service_account import ServiceAccountCredentials
 from sheets_integration import SheetsLogger
+from datetime import datetime
 
 # Initialize services
 service = DataAssessmentService(api_key=os.environ.get("OPENAI_API_KEY"))
 sheets_logger = SheetsLogger()
 
-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.
-"""
-
 # Department mapping from abbreviations to full names
 DEPARTMENTS = {
     "Executive Management": "บริหาร ผอ รอง ผู้ช่วย",
@@ -76,34 +50,102 @@ FREQUENCIES = ["One-time request", "Weekly", "Monthly"]
 # Urgency options
 URGENCY = ["Within a week", "Within a month", "Within a year"]
 
-def save_to_sheet(data):
-    """Save request data to Google Sheet"""
-    # TODO: Implement Google Sheets integration
-    pass
+# Example requests for reference
+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"""
+    # Validate inputs
+    if not all([name, employee_id, email, request_details]):
+        return "Please fill in all required fields.", None
+        
     # Combine department info
     final_department = other_dept if department == "Other" else department
     
-    # Process the request through GPT
-    result = service.assess_request(request_details)
-    
-    # Prepare data for logging
-    request_data = {
-        "name": name,
-        "employee_id": employee_id,
-        "email": email,
-        "department": final_department,
-        "request_details": request_details,
-        "frequency": frequency,
-        "urgency": urgency,
-        "system_response": json.dumps(result, ensure_ascii=False)
-    }
-    
-    # Log to Google Sheets
-    sheets_logger.log_request(request_data)
-    
-    return result
+    try:
+        # Process the request through GPT
+        result = service.assess_request(request_details)
+        
+        # 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
+        sheets_logger.log_request(sheet_data)
+        
+        return user_summary, result
+        
+    except Exception as e:
+        error_message = f"Error processing request: {str(e)}"
+        return error_message, None
 
 # Create Gradio interface
 with gr.Blocks() as demo:
@@ -112,16 +154,29 @@ with gr.Blocks() as demo:
     
     with gr.Row():
         with gr.Column():
-            name = gr.Textbox(label="Full Name", placeholder="Enter your full name")
-            employee_id = gr.Textbox(label="Employee ID", placeholder="Enter your employee ID")
-            email = gr.Textbox(label="Email", placeholder="Enter your email for contact")
+            name = gr.Textbox(
+                label="Full Name",
+                placeholder="Enter your full name",
+                required=True
+            )
+            employee_id = gr.Textbox(
+                label="Employee ID",
+                placeholder="Enter your employee ID",
+                required=True
+            )
+            email = gr.Textbox(
+                label="Email",
+                placeholder="Enter your email for contact",
+                required=True
+            )
     
     with gr.Row():
         with gr.Column():
             department = gr.Dropdown(
-                choices=list(DEPARTMENTS.keys()) + ["Other"],
+                choices=list(DEPARTMENTS.keys()),
                 label="Department",
-                info="Select your department"
+                info="Select your department",
+                required=True
             )
             other_dept = gr.Textbox(
                 label="Other Department",
@@ -143,7 +198,8 @@ with gr.Blocks() as demo:
         request_details = gr.Textbox(
             label="Request Details",
             placeholder="Please describe in detail what data you need, including time period, specific parameters, etc.",
-            lines=5
+            lines=5,
+            required=True
         )
     
     with gr.Row():
@@ -151,22 +207,35 @@ with gr.Blocks() as demo:
             frequency = gr.Dropdown(
                 choices=FREQUENCIES,
                 label="Request Frequency",
-                info="How often do you need this data?"
+                info="How often do you need this data?",
+                required=True
             )
             urgency = gr.Dropdown(
                 choices=URGENCY,
                 label="Urgency Level",
-                info="How urgent is your request?"
+                info="How urgent is your request?",
+                required=True
             )
     
     submit_btn = gr.Button("Submit Request")
-    output = gr.JSON(label="Analysis Result")
+    
+    # Add user-friendly summary output
+    with gr.Row():
+        user_output = gr.Markdown(
+            label="Request Summary",
+            value="Your request summary will appear here...",
+            show_label=True
+        )
+    
+    # Technical analysis output (for data team)
+    with gr.Accordion("Technical Analysis (For Data Team)", open=False):
+        tech_output = gr.JSON(label="Detailed Analysis")
     
     submit_btn.click(
         fn=process_request,
         inputs=[name, employee_id, email, department, other_dept, 
                 request_details, frequency, urgency],
-        outputs=[output]
+        outputs=[user_output, tech_output]
     )
     
     gr.Markdown("""