Update run.py

run.py

@@ -1,12 +1,27 @@
 import time
 import gradio as gr
+import torch
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
 
-def slow_echo(message, history):
-    for i in range(len(message)):
-        time.sleep(0.05)
-        yield "You typed: " + message[: i+1]
+# Load pre-trained model and tokenizer
+tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
+model = GPT2LMHeadModel.from_pretrained("gpt2")
 
-demo = gr.ChatInterface(slow_echo).queue()
+def generate_response(user_input, max_length=50):
+    # Tokenize user input and convert to tensor
+    input_ids = tokenizer.encode(user_input, return_tensors="pt")
+
+    # Generate response using the model
+    output = model.generate(input_ids, max_length=max_length, num_return_sequences=1)
+
+    # Decode the generated response
+    response = tokenizer.decode(output[0], skip_special_tokens=True)
+    return response
+
+def resposeYielder(message, history):
+        yield generate_response(message)
+
+demo = gr.ChatInterface(resposeYielder).queue()
 
 if __name__ == "__main__":
     demo.launch()