update app16

app.py

@@ -2,14 +2,17 @@ import gradio as gr
 from transformers import GPT2LMHeadModel, GPT2Tokenizer
 import torch
 
+
 # Load model and tokenizer (using smaller GPT-2 for free tier)
 model_name = "gpt2"  # You can also use "gpt2-medium" if it fits in memory
 tokenizer = GPT2Tokenizer.from_pretrained(model_name)
 model = GPT2LMHeadModel.from_pretrained(model_name)
 
+
 # Set pad token
 tokenizer.pad_token = tokenizer.eos_token
 
+
 def generate_text(prompt, max_length=100, temperature=0.7, top_p=0.9, top_k=50):
     """Generate text using GPT-2"""
     try:
@@ -38,6 +41,7 @@ def generate_text(prompt, max_length=100, temperature=0.7, top_p=0.9, top_k=50):
     except Exception as e:
         return f"Error generating text: {str(e)}"
 
+
 # Create Gradio interface
 with gr.Blocks(title="GPT-2 Text Generator") as demo:
     gr.Markdown("# GPT-2 Text Generation Server")
@@ -103,13 +107,15 @@ with gr.Blocks(title="GPT-2 Text Generator") as demo:
         inputs=prompt_input
     )
     
-    # Connect the function
+    # Connect the function with explicit API endpoint name
     generate_btn.click(
         fn=generate_text,
         inputs=[prompt_input, max_length, temperature, top_p, top_k],
-        outputs=output_text
+        outputs=output_text,
+        api_name="/predict"  # Explicit API endpoint for external calls
     )
 
+
 # Launch the app
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()