Update app.py

app.py

@@ -1,9 +1,34 @@
 import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
 
+# Load the model and tokenizer
+model_name = "CatGPT" # Replace with the exact model name if necessary
+model = AutoModelForCausalLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+# Define the chat function
 def chat(input_text):
- inputs = tokenizer.encode(input_text, return_tensors="pt")
- outputs = model.generate(inputs)
- response = tokenizer.decode(outputs[0])
- return response
+ try:
+ # Tokenize the input
+ inputs = tokenizer(input_text, return_tensors="pt")
+ 
+ # Generate a response from the model
+ outputs = model.generate(**inputs, max_length=150)
+ 
+ # Decode and return the response
+ response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+ return response
+
+ except Exception as e:
+ return f"An error occurred: {str(e)}"
+
+# Create the Gradio interface
+iface = gr.Interface(fn=chat, 
+ inputs=gr.inputs.Textbox(lines=7, label="Enter your message"),
+ outputs=gr.outputs.Textbox(label="Response"),
+ title="CatGPT - Chatbot",
+ description="Chat with CatGPT, a fun and intelligent chatbot!")
 
-gr.Interface(fn=chat, inputs="text", outputs="text").launch()
+# Launch the interface
+if __name__ == "__main__":
+ iface.launch()