Update app.py

app.py

@@ -1,19 +1,19 @@
 import gradio as gr
-from transformers import pipeline
+from transformers import BlenderbotTokenizer, BlenderbotForConditionalGeneration
 
-# Load the conversational pipeline with the "facebook/blenderbot-400M-distill" model
-pipe = pipeline("conversational", model="facebook/blenderbot-400M-distill")
+# Load the tokenizer and model
+tokenizer = BlenderbotTokenizer.from_pretrained("facebook/blenderbot-400M-distill")
+model = BlenderbotForConditionalGeneration.from_pretrained("facebook/blenderbot-400M-distill")
 
 def chat_with_model(input_text):
-    # Start a new conversation with the user's input
-    conversation = [{"role": "user", "content": input_text}]
-    
+    # Encode the user's input
+    input_ids = tokenizer.encode("You: " + input_text, return_tensors="pt", max_length=512, truncation=True)
+
     # Generate a response from the model
-    response = pipe(conversation)
-    
-    # Extract the assistant's reply
-    reply = response[0]['message']['content']
-    
+    response_ids = model.generate(input_ids, max_length=100, num_return_sequences=1, no_repeat_ngram_size=2)
+
+    # Decode and return the assistant's reply
+    reply = tokenizer.decode(response_ids[0], skip_special_tokens=True)
     return reply
 
 iface = gr.Interface(