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| import gradio as gr | |
| import os | |
| from together import Together | |
| import base64 | |
| from io import BytesIO | |
| from PIL import Image | |
| import numpy as np | |
| import traceback | |
| # Initialize the Together client | |
| api_key = os.environ.get('TOGETHER_API_KEY') | |
| client = Together(api_key=api_key) | |
| def generate_gradio_app(image): | |
| if not api_key: | |
| return "Error: TOGETHER_API_KEY not set. Please check your API key." | |
| try: | |
| # Convert numpy array to PIL Image | |
| if isinstance(image, np.ndarray): | |
| image = Image.fromarray(image.astype('uint8'), 'RGB') | |
| # Convert the image to base64 | |
| buffered = BytesIO() | |
| image.save(buffered, format="PNG") | |
| img_str = base64.b64encode(buffered.getvalue()).decode() | |
| # Prepare the prompt | |
| 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: | |
| 1. Describe the main elements of the UI, including layout, colors, and components. | |
| 2. Generate a complete Gradio Python code that recreates this UI as closely as possible. | |
| 3. Use appropriate Gradio components for each element in the UI. | |
| 4. Include all necessary imports at the beginning of the code. | |
| 5. Implement placeholder functions for any interactive elements (buttons, inputs, etc.). | |
| 6. Use gr.Blocks() to create a layout that matches the screenshot. | |
| 7. Add appropriate labels and descriptions for all components. | |
| 8. Include the gr.Blocks().launch() call at the end of the code. | |
| 9. Provide a complete, runnable Gradio application that can be executed as-is. | |
| 10. Add comments explaining the purpose of each major section or component. | |
| Please generate the entire Gradio code based on the provided image.""" | |
| # Make the API call | |
| stream = client.chat.completions.create( | |
| model="meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo", | |
| messages=[ | |
| { | |
| "role": "user", | |
| "content": [ | |
| {"type": "text", "text": prompt}, | |
| { | |
| "type": "image_url", | |
| "image_url": { | |
| "url": f"data:image/png;base64,{img_str}", | |
| }, | |
| }, | |
| ], | |
| } | |
| ], | |
| max_tokens=4096, | |
| temperature=0.7, | |
| top_p=0.7, | |
| top_k=50, | |
| repetition_penalty=1, | |
| stop=["<|eot_id|>", "<|eom_id|>"], | |
| stream=True | |
| ) | |
| # Collect the streamed response | |
| generated_code = "" | |
| for chunk in stream: | |
| if chunk.choices[0].delta.content is not None: | |
| generated_code += chunk.choices[0].delta.content | |
| yield f"Generating Gradio code... (Current length: {len(generated_code)} characters)\n\n{generated_code}" | |
| if not generated_code: | |
| return "Error: No code generated from the model. Please try again." | |
| return generated_code | |
| except Exception as e: | |
| error_message = str(e) | |
| stack_trace = traceback.format_exc() | |
| return f"An error occurred: {error_message}\n\nStack trace:\n{stack_trace}\n\nPlease try again or check your API key and connection." | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# Generate Gradio App from Wireframe") | |
| gr.Markdown("Upload an image of your UI design, and we'll generate Gradio code to recreate it.") | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| image_input = gr.Image(label="Upload a screenshot", elem_id="image_upload") | |
| generate_button = gr.Button("Generate Gradio Code", variant="primary") | |
| with gr.Column(scale=2): | |
| code_output = gr.Code(language="python", label="Generated Gradio Code", lines=30) | |
| generate_button.click( | |
| fn=generate_gradio_app, | |
| inputs=[image_input], | |
| outputs=[code_output] | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch(debug=True) |