Update app.py

app.py

@@ -3,42 +3,54 @@ from huggingface_hub import InferenceClient
 import base64
 from io import BytesIO
 from PIL import Image
-
+import bs4
+import lxml
 # Define the list of models
 models = [
-    "black-forest-labs/FLUX.1-dev",
-    "CompVis/stable-diffusion-v1-4",
-    "runwayml/stable-diffusion-v1-5",
-    "stabilityai/stable-diffusion-2-1-base",
-    "stabilityai/stable-diffusion-2-1",
-    "CompVis/ldm-text2im-large-256",
-    "lambdalabs/sd-text2img-base-2-0",
-    "ZB-Tech/Text-to-Image",
-    "cloudqi/cqi_text_to_image_pt_v0",
-    "kothariyashhh/GenAi-Texttoimage",
-    "sairajg/Text_To_Image"
+    "Qwen/Qwen2.5-Coder-32B-Instruct",
 ]
-
-def generate_image(prompt, model_name):
-    client = InferenceClient(model_name)
+def get_webpage_text(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_image(prompt):
+    client = InferenceClient("black-forest-labs/FLUX.1-dev")
     response = client.text_to_image(prompt)
-    #image_data = response[0]['image']
-    #image = Image.open(BytesIO(base64.b64decode(response)))
     return response
-    if isinstance(response, list):
-        image_data = response[0]['image']
-        image = Image.open(BytesIO(base64.b64decode(response)))
-        return image
-    else:
-        return "Failed to generate image."
+
+
+def generate_prompt(company_name, company_url=""):
+    
+    client = InferenceClient(model_name)
+    company_html = get_webpage_text(company_url)
+
+    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, 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
+    Company Name: {company_name}
+    HTML from Company Website: {company_html}"""
+    prompt_in=[
+        {'role':'system','content':system_prompt},
+        {'role':'user','content':prompt},
+    ]
+    stream = client.text_generation(prompt_in, **self.generate_kwargs, stream=True, details=True, return_full_text=True)
+    for response in stream:
+        output += response.token.text
+    return output
 
 # Create Gradio Interface
 with gr.Blocks() as demo:
-    gr.Markdown("## Text-to-Image Generation with Hugging Face Models")
+    gr.Markdown("## Smart Logo Maker")
     with gr.Row():
         with gr.Column():
             model_dropdown = gr.Dropdown(models, label="Select Model")
-            prompt_input = gr.Textbox(label="Enter Text Prompt")
+            prompt_input = gr.Textbox(label="Enter Company Name")
+            prompt_input = gr.Textbox(label="Enter Company Name")
             generate_button = gr.Button("Generate Image")
         with gr.Column():
             output_image = gr.Image(label="Generated Image")