Create app.py

app.py

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+import torch
+import gradio as gr
+from transformers import pipeline
+
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+code_writer = pipeline("text-generation", model="Qwen/Qwen2.5-Coder-32B-Instruct",torch_dtype=torch.bfloat16 )
+
+# Define the code generation function
+def generate_code(prompt, max_length):
+    # Generate code based on the input prompt and maximum length
+    output = code_writer(prompt, max_length=max_length, num_return_sequences=1, do_sample=True)
+    return output[0]['generated_text']
+
+# Close any existing Gradio instances
+gr.close_all()
+
+# Set up the Gradio interface
+Demo = gr.Interface(
+    fn=generate_code,
+    inputs=[
+        gr.Textbox(label="Code Prompt", lines=10, placeholder="Enter a description or snippet for code generation."),
+        gr.Slider(
+            label="Code Length (Tokens Approx.)", 
+            minimum=10, maximum=130000, step=1000, value=150
+        )
+    ],
+    outputs=[gr.Textbox(label="Generated Code", lines=20)],
+    title="Code_Generator_App",
+    description="This application generates code based on your input prompt."
+)
+
+# Launch the app with a public link
+Demo.launch(share=True)
+