Create app.py

app.py

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+from transformers import AutoModelForCausalLM, AutoTokenizer
+import gradio as gr
+import torch
+
+# ✅ Load the fastest model for code review
+model_name = "EleutherAI/pythia-70m"  # Smallest & fastest alternative
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16).to("cuda")
+
+# ✅ Function to analyze Python code
+def review_code(code_snippet):
+    inputs = tokenizer(code_snippet, return_tensors="pt").to("cuda")  # Move input to GPU
+    outputs = model.generate(**inputs, max_length=80, do_sample=False, num_beams=3)  # Fast inference
+    reviewed_code = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return reviewed_code
+
+# ✅ Function to handle user input & return reviewed code
+def check_code(input_code):
+    reviewed_code = review_code(input_code)
+    return input_code, reviewed_code, reviewed_code  # Return for UI display & download
+
+# ✅ Gradio UI with Side-by-Side Comparison & Download Option
+interface = gr.Interface(
+    fn=check_code,
+    inputs=gr.Textbox(label="Enter Python Code"),
+    outputs=[
+        gr.Textbox(label="Original Code", interactive=False),  # Left side
+        gr.Textbox(label="Reviewed Code", interactive=False),  # Right side
+        gr.File(label="Download Reviewed Code")  # Download button
+    ],
+    title="🚀 AI Code Reviewer",
+    description="Enter Python code and get a reviewed version. Download the reviewed code as a file.",
+    allow_flagging="never"
+)
+
+# ✅ Launch the app on Hugging Face Spaces with timeout settings
+interface.launch(share=True, server_timeout=40)