Update app.py

app.py

@@ -500,23 +500,34 @@ def process_complete_consultation(name, age, sex, weight, height, complaint,
     waveform_plot = None
     if audio_file is not None:
         results, plot_path = analyze_heartbeat(audio_file)
-        if results:
-            heartbeat_results = f"""
-            Heartbeat Analysis Results:
-            - Normal: {results.get('normal', 0)*100:.1f}%
-            - Murmur: {results.get('murmur', 0)*100:.1f}%
-            - Artifact: {results.get('artifact', 0)*100:.1f}%
-            """
-            waveform_plot = plot_path
+        heartbeat_results = results_text if results_text else "" 
+        waveform_plot = plot_path
+    
     
     # Analyze investigation image if provided
     investigation_analysis = ""
     if investigation_image is not None:
         investigation_analysis = analyze_medical_image(investigation_image)
+
+
+    patient_data_dict = {
+        'name': name if name else 'Not provided',
+        'age': age if age else 'Not provided',
+        'sex': sex if sex else 'Not provided',
+        'weight': weight if weight else 'Not provided',
+        'height': height if height else 'Not provided',
+        'complaint': complaint if complaint else 'Not provided',
+        'medical_history': medical_history if medical_history else 'Not provided',
+        'examination': examination if examination else 'Not provided',
+        'heartbeat_analysis': heartbeat_results if heartbeat_results else 'Not performed',
+        'investigation_analysis': investigation_analysis if investigation_analysis else 'Not provided'
+    }
+    
     
     # Save patient data
-    save_patient_data(name, age, sex, weight, height, complaint, medical_history,
-                     examination, heartbeat_results, investigation_analysis)
+    global patient_data
+    patient_data = patient_data_dict.copy()
+    patient_data['timestamp'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
     
     # Generate comprehensive assessment
     comprehensive_assessment = generate_comprehensive_assessment(patient_data)