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Update app.py
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app.py
CHANGED
@@ -5,8 +5,8 @@ from PIL import Image
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import requests
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from io import BytesIO
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import re
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import pandas as pd
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def fetch_api_endpoint(url):
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try:
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headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3'}
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@@ -15,7 +15,7 @@ def fetch_api_endpoint(url):
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# Use regular expressions to find the endpoint URL in the script content
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endpoint_match = re.search(r'root":"(https://[^"]+)', response.text)
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if
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endpoint_url = endpoint_match.group(1)
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return endpoint_url
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else:
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@@ -27,15 +27,19 @@ def fetch_api_endpoint(url):
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print("An unexpected error occurred:", e)
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return None
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url = "https://playgroundai-playground-v2-5.hf.space/"
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endpoint = fetch_api_endpoint(url)
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if endpoint is None:
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print("Failed to fetch the API endpoint.")
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exit(1)
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client_mistral = InferenceClient("mistralai/Mistral-7B-Instruct-v0.2")
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client_playground = Client(endpoint)
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def format_prompt(logo_request):
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@@ -102,20 +106,11 @@ css = """
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}
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"""
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results = []
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def process_request(logo_request, width, height, guidance_scale):
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improved_prompt = generate_improved_prompt(logo_request)
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image = generate_image(improved_prompt, width, height, guidance_scale)
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results.append({"Prompt": logo_request, "Guidance Scale": guidance_scale, "Size": f"{width}x{height}", "Image": image})
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display_results()
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return improved_prompt, image
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def display_results():
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df = pd.DataFrame(results)
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html = df.to_html(escape=False, formatters=dict(Image=lambda x: x._repr_html_()))
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display_html(html, raw=True)
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with gr.Blocks(css=css) as app:
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with gr.Row():
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with gr.Column(scale=2):
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@@ -124,9 +119,6 @@ with gr.Blocks(css=css) as app:
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width = gr.Slider(label="Width", minimum=256, maximum=1536, value=1024)
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height = gr.Slider(label="Height", minimum=256, maximum=1536, value=1024)
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guidance_scale = gr.Slider(label="Guidance Scale", minimum=0.1, maximum=20, value=3)
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example1 = gr.Button("Example 1: Abstract geometric shape")
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example2 = gr.Button("Example 2: Minimalist animal logo")
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example3 = gr.Button("Example 3: Futuristic tech icon")
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with gr.Column(scale=3):
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gr.HTML("<h1><center>Magical AI Logo Generator<h1><center>")
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generate_button = gr.Button("Generate")
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@@ -137,21 +129,6 @@ with gr.Blocks(css=css) as app:
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inputs=[logo_input, width, height, guidance_scale],
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outputs=[prompt_output, image_output]
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)
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example1.click(
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fn=lambda: ("Abstract geometric shape",),
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inputs=None,
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outputs=[logo_input]
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)
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example2.click(
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fn=lambda: ("Minimalist animal logo",),
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inputs=None,
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outputs=[logo_input]
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)
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example3.click(
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fn=lambda: ("Futuristic tech icon",),
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inputs=None,
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outputs=[logo_input]
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)
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gr.Markdown("""
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---
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import requests
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from io import BytesIO
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import re
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# Function to fetch the API endpoint from the URL using regular expressions
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def fetch_api_endpoint(url):
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try:
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headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3'}
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# Use regular expressions to find the endpoint URL in the script content
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endpoint_match = re.search(r'root":"(https://[^"]+)', response.text)
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if endpoint_match:
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endpoint_url = endpoint_match.group(1)
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return endpoint_url
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else:
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print("An unexpected error occurred:", e)
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return None
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# Define the URL to fetch the API endpoint from
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url = "https://playgroundai-playground-v2-5.hf.space/"
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# Fetch the API endpoint
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endpoint = fetch_api_endpoint(url)
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if endpoint is None:
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print("Failed to fetch the API endpoint.")
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exit(1)
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# Initialize the HuggingFace Inference Client with the specified model
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client_mistral = InferenceClient("mistralai/Mistral-7B-Instruct-v0.2")
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# Initialize the Playground AI client with the fetched endpoint
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client_playground = Client(endpoint)
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def format_prompt(logo_request):
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}
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"""
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def process_request(logo_request, width, height, guidance_scale):
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improved_prompt = generate_improved_prompt(logo_request)
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image = generate_image(improved_prompt, width, height, guidance_scale)
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return improved_prompt, image
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with gr.Blocks(css=css) as app:
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with gr.Row():
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with gr.Column(scale=2):
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width = gr.Slider(label="Width", minimum=256, maximum=1536, value=1024)
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height = gr.Slider(label="Height", minimum=256, maximum=1536, value=1024)
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guidance_scale = gr.Slider(label="Guidance Scale", minimum=0.1, maximum=20, value=3)
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with gr.Column(scale=3):
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gr.HTML("<h1><center>Magical AI Logo Generator<h1><center>")
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generate_button = gr.Button("Generate")
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inputs=[logo_input, width, height, guidance_scale],
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outputs=[prompt_output, image_output]
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)
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gr.Markdown("""
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---
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