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| import gradio as gr | |
| from huggingface_hub import InferenceClient | |
| import base64 | |
| from io import BytesIO | |
| from PIL import Image | |
| import requests | |
| import random | |
| import bs4 | |
| import lxml | |
| # Define the list of models | |
| models = ["Qwen/Qwen2.5-Coder-32B-Instruct"] | |
| def format_prompt(message, mod, system): | |
| eos=f"<|im_end|>\n" | |
| bos=f"<|im_start|>\n" | |
| prompt="" | |
| prompt+=bos | |
| prompt+=system | |
| prompt+=eos | |
| prompt+=bos | |
| prompt += message | |
| prompt+=eos | |
| prompt+=bos | |
| return prompt | |
| def get_webpage_text(url): | |
| print("url ", url) | |
| source = requests.get(url) | |
| #isV('status: ', source.status_code) | |
| if source.status_code ==200: | |
| soup = bs4.BeautifulSoup(source.content,'lxml') | |
| rawp=f'RAW TEXT RETURNED: {soup.text}' | |
| return rawp | |
| else: | |
| return "ERROR couldn't find, "+url | |
| def generate_prompt(company_name, company_html, company_descp): | |
| client = InferenceClient(models[0]) | |
| output="" | |
| system_prompt=f"""You are a Master Generative Image Prompt Writer, you know just the perfect prompt secrets for every situation | |
| Today you will be generating Company Logo's | |
| You will be given a Company Name, Description, and HTML artifacts from their website, use this to generate a sufficiently long and detailed image generation prompt to satisfy the users request, make sure that the company name is the focal point of the image | |
| """ | |
| prompt=f"""Company Name: {company_name} | |
| Company Description: {company_descp} | |
| HTML from Company Website: {str(company_html)}""" | |
| formatted_prompt=format_prompt(prompt,0,system_prompt) | |
| generate_kwargs = dict( | |
| temperature=0.99, | |
| max_new_tokens=512, | |
| top_p=0.99, | |
| repetition_penalty=1.0, | |
| do_sample=True, | |
| seed=random.randint(1,100000000000000), | |
| ) | |
| stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=True) | |
| for response in stream: | |
| output += response.token.text | |
| return output | |
| def generate_image(comp_name, comp_desc="", comp_url=""): | |
| print(comp_name +"|"+comp_desc+"|"+comp_url) | |
| if comp_url != "": | |
| web_out=get_webpage_text(comp_url) | |
| else: | |
| web_out="No Web Data returned" | |
| print(web_out) | |
| prompt_out=generate_prompt(comp_name,web_out, comp_desc) | |
| client = InferenceClient("black-forest-labs/FLUX.1-dev") | |
| response = client.text_to_image(prompt_out) | |
| return response | |
| # Create Gradio Interface | |
| with gr.Blocks() as demo: | |
| gr.Markdown("## Smart Logo Maker") | |
| with gr.Row(): | |
| with gr.Column(): | |
| comp_name = gr.Textbox(label="Enter Company Name") | |
| comp_desc = gr.Textbox(label="Enter Company Description") | |
| comp_url = gr.Textbox(label="Enter Company URL") | |
| generate_button = gr.Button("Generate Image") | |
| with gr.Column(): | |
| output_image = gr.Image(label="Generated Image") | |
| generate_button.click(generate_image, [comp_name, comp_desc, comp_url], output_image) | |
| # Launch the interface | |
| demo.launch() |