Update app.py

app.py

@@ -1,23 +1,20 @@
-import gradio as gr
 from transformers import pipeline
 import torch
 
-# Load GPT-2 with optimized parameters
+# Load GPT-2 with float32 (remove torch_dtype=torch.float16)
 model = pipeline(
     "text-generation",
     model="gpt2",
     max_length=200,
     temperature=0.7,
     early_stopping=True,
-    torch_dtype=torch.float16  # Use half-precision for speed
+    torch_dtype=torch.float32  # << Use float32 instead of float16
 )
 
 def generate_test_cases(requirement):
-    # Simplified prompt with clear instructions and example
     prompt = f"""
     Generate test cases for '{requirement}' in JSON format. Output only the array.
-    
-    Example format:
+    Example:
     [
         {{
             "id": 1,
@@ -33,30 +30,20 @@ def generate_test_cases(requirement):
         }}
     ]
     """
-    
     try:
-        # Generate text with a timeout (avoids long inference)
         with torch.no_grad():
             result = model(prompt, max_time=10)[0]["generated_text"]
         return result.strip()
     except Exception as e:
         return f"Error: {str(e)}"
 
-# Create Gradio interface with proper flagging_mode
 demo = gr.Interface(
     fn=generate_test_cases,
     inputs="text",
     outputs="text",
     title="Test Case Generator",
     description="Enter a requirement to generate test cases.",
-    flagging_mode="never"  # Valid value
+    flagging_mode="never"
 )
 
-# Launch with proper settings
-if __name__ == "__main__":
-    demo.launch(
-        server_name="0.0.0.0",
-        server_port=7860,
-        debug=True,
-        prevent_thread_lock=True
-    )
+demo.launch(server_name="0.0.0.0", server_port=7860)