Upload app.py

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# Load model and tokenizer
+MODEL_NAME = "Qwen/Qwen-7B-Chat"
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, trust_remote_code=True)
+
+# Define the refactor function
+def refactor_code(message, code):
+    input_text = f"{message}\n\nCode:\n{code}"
+    inputs = tokenizer(input_text, return_tensors="pt", max_length=1024, truncation=True)
+    outputs = model.generate(inputs["input_ids"], max_new_tokens=200)
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+# Gradio Interface
+interface = gr.Interface(
+    fn=refactor_code,
+    inputs=[
+        gr.Textbox(label="Message (Instruction)"),
+        gr.Textbox(label="Code", lines=15),
+    ],
+    outputs="text",
+    title="Code Refactor with Qwen Model",
+    description="Provide an instruction and code to refactor. The model will return the updated code."
+)
+
+# Launch the app
+interface.launch()