Update app.py

app.py

@@ -1,33 +1,45 @@
-# Import Gradio and the Hugging Face Transformers pipeline
 import gradio as gr
 from transformers import pipeline
 
-# Load a text-generation pipeline with the DistilGPT-2 model.
-# DistilGPT-2 is a distilled (compressed) version of GPT-2, so it's faster and lightweight:contentReference[oaicite:3]{index=3}.
-generator = pipeline("text-generation", model="distilgpt2")  # This downloads the model weights if not already available
+# Load the DistilGPT-2 text-generation pipeline
+generator = pipeline("text-generation", model="distilgpt2")
 
-# Define a function that uses the generator to produce text based on the input prompt.
 def generate_text(prompt):
-    # Use the text-generation pipeline to continue the prompt.
-    # We set a max_length to limit the output length for practicality.
-    result = generator(prompt, max_length=100, num_return_sequences=1)[0]["generated_text"]
+    result = generator(prompt, max_length=120, num_return_sequences=1)[0]["generated_text"]
     return result
 
-# Set up the Gradio interface:
-# - Input: a textbox for the prompt (single-line or a short prompt, so we use lines=2).
-# - Output: a textbox for the generated text.
-# - We also add a title and description for user guidance.
-input_prompt = gr.Textbox(lines=2, label="Prompt", placeholder="Enter a text prompt...")
-output_text = gr.Textbox(label="Generated Text")
+# Two simple example prompts for students to try
+example_prompts = [
+    ["Once upon a time in a distant kingdom,"],
+    ["The future of artificial intelligence depends on"]
+]
 
-demo = gr.Interface(
-    fn=generate_text,
-    inputs=input_prompt,
-    outputs=output_text,
-    title="🤖 DistilGPT-2 Text Generator",
-    description="**Description:** Enter a prompt, and the DistilGPT-2 language model will continue the text. "
-                "This demonstrates basic text generation using a small pre-trained GPT-2 model."
-)
+with gr.Blocks(title="DistilGPT-2 Text Generator") as demo:
+    
+    gr.Markdown(
+        """### DistilGPT-2 Text Generator  
+Enter a short prompt and the model will continue it.  
+Below the input box you will find two example prompts you can try immediately."""
+    )
+    
+    prompt = gr.Textbox(
+        lines=2,
+        label="Prompt",
+        placeholder="Type a short prompt to begin…"
+    )
+    
+    output = gr.Textbox(
+        lines=12,         # Increased height for the output area
+        label="Generated Text"
+    )
+    
+    btn = gr.Button("Generate")
+    btn.click(generate_text, inputs=prompt, outputs=output)
+    
+    gr.Examples(
+        examples=example_prompts,
+        inputs=prompt,
+        label="Example Prompts"
+    )
 
-# Launch the app (in a Hugging Face Space, this will run automatically).
 demo.launch()