Update app.py

app.py

@@ -26,7 +26,7 @@ dental_terms = {
     "occlusion": "Occlusion refers to the alignment and contact between teeth when the jaws close."
 }
 
-# Set up a gpt2-large pipeline 
+# Set up a gpt2-large pipeline
 generation_pipeline = pipeline(
     "text-generation",
     model="gpt2-large"
@@ -37,11 +37,8 @@ def chatbot_response(message, history):
     Hybrid response logic:
     1) Check if user input matches a known dental term (exactly or via fuzzy matching).
     2) If found or close match, return the definition from our dictionary.
-    3) Otherwise, use Flan-T5 to generate an open-ended response.
+    3) Otherwise, use GPT-2 to generate an open-ended response.
     """
-    print(f"User Input: {message}")
-    print(f"Chat History: {history}")
-
     # Normalize user input to lowercase for simpler matching
     user_input_lower = message.lower()
 
@@ -54,11 +51,13 @@ def chatbot_response(message, history):
     if score >= 80:
         return f"Did you mean '{closest_match}'? {dental_terms[closest_match]}"
 
-    # 3) If no match or fuzzy match is too low, use Flan-T5 for generation
-    # We'll prompt it directly with the user's message.
-    # Adjust parameters as desired for creativity, length, etc.
-    result = generation_pipeline(message, max_length=100, num_return_sequences=1)
-    generated_text = result[0]["generated_text"]
+    # 3) If no match or fuzzy match is too low, use GPT-2 for generation
+    try:
+        result = generation_pipeline(message, max_length=100, num_return_sequences=1)
+        generated_text = result[0]["generated_text"]
+    except Exception as e:
+        generated_text = f"Error generating response: {str(e)}"
+
     return generated_text
 
 # Gradio chat interface
@@ -67,7 +66,7 @@ demo = gr.ChatInterface(
     title="Hybrid Dental Terminology Chatbot",
     description=(
         "Enter a dental term to get its definition (20 known terms). "
-        "If the term isn't recognized, Flan-T5 will respond."
+        "If the term isn't recognized, GPT-2 will respond with a generated message."
     )
 )