Create app.py

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+# Load the model and tokenizer
+model_name = "distilgpt2"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Function to generate response and maintain chat history
+def chat_function(user_input, history):
+    if history is None:
+        history = []
+    
+    # Create prompt with history
+    prompt = "\n".join([f"User: {h[0]}\nAI: {h[1]}" for h in history] + [f"User: {user_input}"])
+    
+    # Tokenize input
+    inputs = tokenizer(prompt, return_tensors="pt", padding=True)
+    
+    # Generate response
+    outputs = model.generate(
+        inputs["input_ids"],
+        max_length=100,
+        num_return_sequences=1,
+        temperature=0.7,
+        do_sample=True,
+        pad_token_id=tokenizer.eos_token_id
+    )
+    
+    # Decode response
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    response = response[len(prompt):].strip() or "Hmm, I'm not sure what to say!"
+    
+    # Update history
+    history.append((user_input, response))
+    return history, history
+
+# Create Gradio interface
+with gr.Blocks(title="Simple Chat App") as demo:
+    gr.Markdown("# Simple AI Chat App")
+    gr.Markdown("Chat with an AI powered by DistilGPT-2!")
+    
+    # Chatbot component for displaying conversation
+    chatbot = gr.Chatbot(label="Conversation")
+    
+    # Input box
+    user_input = gr.Textbox(label="Your message", placeholder="Type here...")
+    
+    # Hidden state to maintain chat history
+    history = gr.State(value=[])
+    
+    # Submit button
+    submit_btn = gr.Button("Send")
+    
+    # Clear button
+    clear_btn = gr.Button("Clear Chat")
+    
+    # Connect components
+    submit_btn.click(
+        fn=chat_function,
+        inputs=[user_input, history],
+        outputs=[chatbot, history]
+    )
+    
+    clear_btn.click(
+        fn=lambda: ([], []),
+        inputs=None,
+        outputs=[chatbot, history]
+    )
+
+# Launch the app
+demo.launch()