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| import gradio as gr | |
| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
| import onnxruntime as ort | |
| # Load the Phi-3.5-mini-instruct model and tokenizer | |
| model_name = "microsoft/Phi-3.5-mini-instruct" | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| # Load the ONNX model | |
| session = ort.InferenceSession(f"{model_name}/model.onnx") | |
| # Simple HTML template for the website | |
| simple_website_template = """ | |
| <!DOCTYPE html> | |
| <html lang="en"> | |
| <head> | |
| <meta charset="UTF-8"> | |
| <meta name="viewport" content="width=device-width, initial-scale=1.0"> | |
| <title>Personalized Website</title> | |
| <style> | |
| body {{ | |
| font-family: Arial, sans-serif; | |
| background-color: #f4f4f4; | |
| color: #333; | |
| padding: 20px; | |
| }} | |
| h1 {{ | |
| color: {title_color}; | |
| }} | |
| p {{ | |
| font-size: {font_size}px; | |
| }} | |
| </style> | |
| </head> | |
| <body> | |
| <h1>{title}</h1> | |
| <p>{content}</p> | |
| </body> | |
| </html> | |
| """ | |
| # Function to generate personalized content using Phi-3.5-mini-instruct | |
| def personalize_website_llm(persona_text): | |
| # Create a prompt for the model | |
| prompt = f"Generate personalized website content for the following persona: {persona_text}. Provide a title and main content." | |
| # Tokenize the prompt | |
| inputs = tokenizer(prompt, return_tensors="np") | |
| # Run the ONNX model | |
| ort_inputs = {session.get_inputs()[0].name: inputs["input_ids"]} | |
| ort_outs = session.run(None, ort_inputs) | |
| # Decode the output | |
| generated_text = tokenizer.decode(ort_outs[0][0], skip_special_tokens=True) | |
| # Split the response into a title and content | |
| title, content = generated_text.split('\n', 1) | |
| # Set the title color and font size based on simple heuristics | |
| title_color = "#333" | |
| font_size = 16 | |
| if "young" in persona_text.lower(): | |
| title_color = "#ff5733" | |
| font_size = 18 | |
| if "professional" in persona_text.lower(): | |
| title_color = "#1c1c1c" | |
| font_size = 14 | |
| # Create the personalized website HTML | |
| personalized_website = simple_website_template.format( | |
| title_color=title_color, | |
| font_size=font_size, | |
| title=title.strip(), | |
| content=content.strip() | |
| ) | |
| return personalized_website | |
| # Create the Gradio interface | |
| with gr.Blocks() as demo: | |
| with gr.Row(): | |
| with gr.Column(): | |
| gr.HTML('<h3>Original Simple Website</h3>') | |
| gr.HTML(simple_website_template.format(title_color="#333", font_size=16, title="Welcome to Our Website!", content="We are glad to have you here.")) | |
| with gr.Column(): | |
| persona_input = gr.Textbox(label="Define Persona", placeholder="Describe the persona here...") | |
| generate_button = gr.Button("Generate Personalized Website") | |
| with gr.Column(): | |
| personalized_output = gr.HTML(label="Personalized Website Output") | |
| generate_button.click(personalize_website_llm, inputs=persona_input, outputs=personalized_output) | |
| # Launch the app | |
| demo.launch() | |