Update app.py

app.py

@@ -10,8 +10,9 @@ class Classifier:
       # Specify the desired model and additional options
       response = openai.Completion.create(
           engine="text-davinci-003",
-          prompt=f"""Your are Mental healthcare Assistant. Classify the following text if the text related to Mental healtcare isse return 'True', Else not related return 'False':
-                    Text to classify: {text}""",
+          prompt = f"""Your are Mental healthcare Assistant. Classify the following text if the text related to Mental healtcare isse return 'True', Else not related return 'False':
+                    Text to classify: {text}
+                    """ ,
           temperature=0,
           max_tokens=1,  # We only need a single token as the classification result
           n=1,
@@ -20,10 +21,11 @@ class Classifier:
 
       # Extract and return the generated classification result
       generated_text = response.choices[0].text.strip()
-      print(generated_text)
       return generated_text
+        
     def clear_func(self):
       return " "," "
+        
     def gradio_interface(self):
       with gr.Blocks(css="style.css",theme=gr.themes.Soft()) as demo:
         gr.HTML("""<center><h1>Mental healthcare</h1></center>""")