Update app.py

app.py

@@ -1,58 +1,28 @@
 import gradio as gr
-#from transformers import pipeline
-
-"""
-pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
-
-def predict(image):
-    predictions = pipeline(image)
-    return {p["label"]: p["score"] for p in predictions}
-
-gr.Interface(
-    predict,
-    inputs=gr.inputs.Image(label="Upload hot dog candidate", type="filepath"),
-    outputs=gr.outputs.Label(num_top_classes=2),
-    title="Hot Dog? Or Not?",
-).launch()
-"""
-
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
 def chatbot_response(user_message):
-    # Load the pre-trained model and tokenizer
-    model_name = "gpt2"  # Replace with the name of the pre-trained model you want to use
+    model_name = "gpt2"  # You can change this to any other model from the list above
     tokenizer = AutoTokenizer.from_pretrained(model_name)
     model = AutoModelForCausalLM.from_pretrained(model_name)
 
-    # Tokenize the user's message and generate the response
     inputs = tokenizer.encode("User: " + user_message, return_tensors="pt")
     outputs = model.generate(inputs, max_length=100, num_return_sequences=1)
     response = tokenizer.decode(outputs[0], skip_special_tokens=True)
 
     return response
 
-user_input = input("You: ")
-
-gr.Interface(
-    chatbot_response,
-    inputs=user_input,
-    outputs=gr.outputs.Label(num_top_classes=2),
-    title="NLP Test",
-).launch()
-
-"""
-if __name__ == '__main__':
-    print("Chatbot: Hello! I'm your chatbot. Type 'exit' to end the conversation.")
-    
-    while True:
-        user_input = input("You: ")
-        
-        if user_input.lower() == 'exit':
-            break
-
-        response = chatbot_response(user_input)
-        print("Chatbot:", response)
-
-"""
-
-
+# Define the chatbot interface using Gradio
+iface = gr.Interface(
+    fn=chatbot_response,
+    inputs=gr.Textbox(prompt="You:"),
+    outputs=gr.Textbox(),
+    live=True,
+    capture_session=True,
+    title="Chatbot",
+    description="Type your message in the box above, and the chatbot will respond.",
+)
+
+# Launch the Gradio interface
+if __name__ == "__main__":
+    iface.launch()