Update app.py

app.py

@@ -194,22 +194,22 @@ def summarize(
     
     if not text.strip():
         return "Please enter some text to summarize."
-    
-    messages = [
-        {"role": "system", "content": prompt.strip()},
-        {"role": "user", "content": text.strip()},
-    ]
-
-    text = tokenizer.apply_chat_template(
-        messages,
-        tokenize=False,
-        add_generation_prompt=True,
-        enable_thinking=False, # only relevant for qwen
-    )
 
-    if text == default_value:
+    if text == default_value: 
         response = ['{"life_style": "N/A", "family_history": "N/A", "social_history": "N/A", "medical_surgical_history": "N/A", "signs_symptoms": "Fever; Chest pain; Cough; Progressive dyspnea; Tachypnea; Tachycardia; Decreased breath sounds in both lung bases; Crackles on the left", "comorbidities": "N/A", "diagnostic_techniques_procedures": "Chest X-ray; Echocardiography; Thoracentesis; Laboratory tests; Pleural fluid analysis; Urinary pneumococcal antigen test; Pleural fluid culture", "diagnosis": "Pneumonia; Pericardial effusion; S. pneumoniae infection", "laboratory_values": "White blood cell count: 11.78 \\u00d7 10^9 cells/L (84.3% neutrophils, 4.3% lymphocytes, 9.1% monocytes); Platelet count: 512 \\u00d7 10^9/L; Serum C-reactive protein: 31.27 mg/dL; Serum creatinine: 0.94 mg/dL; Serum sodium: 133 mEq/L; Serum potassium: 3.72 mEq/L; Pleural fluid pH: 7.16; Pleural fluid glucose: 4.5 mg/dL; Pleural fluid proteins: 49.1 g/L; Pleural fluid LDH: 1,385 U/L", "pathology": "N/A", "pharmacological_therapy": "Amoxicillin-clavulanate (2.2 g/8 h, i.v.); Levofloxacin (500 mg twice a day); Ibuprofen (800 mg/day)", "interventional_therapy": "Pericardiocentesis; Thoracentesis", "patient_outcome_assessment": "Nearly complete resolution of alterations on chest X-ray and CT scan", "age": "57 year", "gender": "Male"}']
     else:
+        messages = [
+            {"role": "system", "content": prompt.strip()},
+            {"role": "user", "content": text.strip()},
+        ]
+
+        text = tokenizer.apply_chat_template(
+            messages,
+            tokenize=False,
+            add_generation_prompt=True,
+            enable_thinking=False, # only relevant for qwen
+        )
+    
         model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
         generated_ids = model.generate(
             input_ids=model_inputs["input_ids"],