Update app.py

app.py

@@ -1,4 +1,4 @@
-
+# Suppress TensorFlow warnings
 import os
 os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0'
 os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
@@ -475,16 +475,16 @@ def save_patient_data(name, age, sex, weight, height, complaint, medical_history
     global patient_data
     
     patient_data = {
-        'name': name,
-        'age': age,
-        'sex': sex,
-        'weight': weight,
-        'height': height,
-        'complaint': complaint,
-        'medical_history': medical_history,
-        'examination': examination,
-        'heartbeat_analysis': heartbeat_results,
-        'investigation_analysis': investigation_analysis,
+        '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',
         'timestamp': datetime.now().strftime('%Y-%m-%d %H:%M:%S')
     }
     
@@ -499,17 +499,16 @@ def process_complete_consultation(name, age, sex, weight, height, complaint,
     heartbeat_results = ""
     waveform_plot = None
     if audio_file is not None:
-        results, plot_path = analyze_heartbeat(audio_file)
-        heartbeat_results = results_text if results_text else "" 
+        heartbeat_analysis, plot_path = analyze_heartbeat(audio_file)
+        heartbeat_results = heartbeat_analysis if heartbeat_analysis 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)
-
-
+    
+    # Create patient data dictionary with proper handling
     patient_data_dict = {
         'name': name if name else 'Not provided',
         'age': age if age else 'Not provided',
@@ -523,14 +522,13 @@ def process_complete_consultation(name, age, sex, weight, height, complaint,
         'investigation_analysis': investigation_analysis if investigation_analysis else 'Not provided'
     }
     
-    
-    # Save patient data
+    # Save patient data to global variable
     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)
+    comprehensive_assessment = generate_comprehensive_assessment(patient_data_dict)
     
     return comprehensive_assessment, waveform_plot, heartbeat_results, investigation_analysis