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Runtime error
Runtime error
Update app.py
Browse files
app.py
CHANGED
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@@ -26,11 +26,24 @@ def generate_gradio_app(image):
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img_str = base64.b64encode(buffered.getvalue()).decode()
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# Prepare the prompt
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prompt = """You are
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# Make the API call
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stream = client.chat.completions.create(
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model="meta-llama/Llama-Vision-
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messages=[
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{
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"role": "user",
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@@ -45,7 +58,7 @@ def generate_gradio_app(image):
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],
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}
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],
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max_tokens=
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temperature=0.7,
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top_p=0.7,
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top_k=50,
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@@ -55,16 +68,16 @@ def generate_gradio_app(image):
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)
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# Collect the streamed response
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for chunk in stream:
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if chunk.choices[0].delta.content is not None:
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yield f"Generating... (Current length: {len(
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if not
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return "Error: No
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return
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except Exception as e:
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error_message = str(e)
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@@ -72,21 +85,21 @@ def generate_gradio_app(image):
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return f"An error occurred: {error_message}\n\nStack trace:\n{stack_trace}\n\nPlease try again or check your API key and connection."
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with gr.Blocks() as demo:
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gr.Markdown("#
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gr.Markdown("Upload an image of your UI design
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with gr.Row():
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with gr.Column(scale=1):
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image_input = gr.Image(label="Upload a screenshot", elem_id="image_upload")
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generate_button = gr.Button("
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with gr.Column(scale=2):
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generate_button.click(
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fn=generate_gradio_app,
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inputs=[image_input],
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outputs=[
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)
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if __name__ == "__main__":
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img_str = base64.b64encode(buffered.getvalue()).decode()
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# Prepare the prompt
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prompt = """You are an AI assistant specialized in UI/UX design and Gradio app development. Analyze the attached screenshot or UI mockup and generate a complete Gradio code that recreates this design. Follow these steps:
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1. Describe the main elements of the UI, including layout, colors, and components.
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2. Generate a complete Gradio Python code that recreates this UI as closely as possible.
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3. Use appropriate Gradio components for each element in the UI.
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4. Include all necessary imports at the beginning of the code.
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5. Implement placeholder functions for any interactive elements (buttons, inputs, etc.).
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6. Use gr.Blocks() to create a layout that matches the screenshot.
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7. Add appropriate labels and descriptions for all components.
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8. Include the gr.Blocks().launch() call at the end of the code.
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9. Provide a complete, runnable Gradio application that can be executed as-is.
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10. Add comments explaining the purpose of each major section or component.
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Please generate the entire Gradio code based on the provided image."""
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# Make the API call
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stream = client.chat.completions.create(
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model="meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo",
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messages=[
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{
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"role": "user",
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],
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}
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],
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max_tokens=4096,
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temperature=0.7,
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top_p=0.7,
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top_k=50,
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)
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# Collect the streamed response
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generated_code = ""
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for chunk in stream:
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if chunk.choices[0].delta.content is not None:
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generated_code += chunk.choices[0].delta.content
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yield f"Generating Gradio code... (Current length: {len(generated_code)} characters)\n\n{generated_code}"
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if not generated_code:
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return "Error: No code generated from the model. Please try again."
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return generated_code
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except Exception as e:
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error_message = str(e)
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return f"An error occurred: {error_message}\n\nStack trace:\n{stack_trace}\n\nPlease try again or check your API key and connection."
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with gr.Blocks() as demo:
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gr.Markdown("# Generate Gradio App from Wireframe")
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gr.Markdown("Upload an image of your UI design, and we'll generate Gradio code to recreate it.")
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with gr.Row():
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with gr.Column(scale=1):
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image_input = gr.Image(label="Upload a screenshot", elem_id="image_upload")
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generate_button = gr.Button("Generate Gradio Code", variant="primary")
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with gr.Column(scale=2):
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code_output = gr.Code(language="python", label="Generated Gradio Code", lines=30)
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generate_button.click(
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fn=generate_gradio_app,
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inputs=[image_input],
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outputs=[code_output]
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)
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if __name__ == "__main__":
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