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Runtime error
Runtime error
VictorSanh
commited on
Commit
•
b537793
1
Parent(s):
2096b5f
update
Browse files
app.py
CHANGED
@@ -1,22 +1,31 @@
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from typing import List, Optional, Tuple
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from PIL import Image
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from playwright.sync_api import sync_playwright
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import os
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import gradio as gr
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from gradio_client.client import DEFAULT_TEMP_DIR
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from transformers import AutoProcessor, AutoModelForCausalLM
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API_TOKEN = os.getenv("HF_AUTH_TOKEN")
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# PROCESSOR = AutoProcessor.from_pretrained(
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# "HuggingFaceM4/img2html",
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# token=API_TOKEN,
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# )
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IMAGE_GALLERY_PATHS = [
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f"example_images/{ex_image}"
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for ex_image in os.listdir(f"example_images")
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]
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import subprocess
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def install_playwright():
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try:
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@@ -25,19 +34,11 @@ def install_playwright():
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except subprocess.CalledProcessError as e:
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print(f"Error during Playwright installation: {e}")
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# Call the function to install Playwright
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install_playwright()
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def add_file_gallery(selected_state: gr.SelectData, gallery_list: List[str]):
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# return (
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# f"example_images/{gallery_list.root[selected_state.index].image.orig_name}",
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# "",
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# )
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return f"example_images/{gallery_list.root[selected_state.index].image.orig_name}"
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def expand_layout():
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return gr.Column(scale=2), gr.Textbox()
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def render_webpage(
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html_css_code,
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):
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@@ -188,23 +189,18 @@ def model_inference(
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rendered_page = render_webpage(CAR_COMPNAY)
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return CAR_COMPNAY, rendered_page
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# textbox = gr.Textbox(
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# placeholder="Upload an image and ask the AI to create a meme!",
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# show_label=False,
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# value="Write a meme about this image.",
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# visible=True,
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# container=False,
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# label="Text input",
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# scale=8,
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# max_lines=5,
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# )
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generated_html = gr.
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label="
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elem_id="generated_html",
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)
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rendered_html = gr.Image(
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)
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css = """
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.gradio-container{max-width: 1000px!important}
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@@ -212,12 +208,15 @@ h1{display: flex;align-items: center;justify-content: center;gap: .25em}
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*{transition: width 0.5s ease, flex-grow 0.5s ease}
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"""
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with gr.Blocks(title="Img2html", theme=gr.themes.Base(), css=css) as demo:
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with gr.Row(equal_height=True):
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# scale=2 when expanded
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with gr.Column(scale=4, min_width=250) as upload_area:
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imagebox = gr.Image(
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type="filepath",
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)
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with gr.Group():
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with gr.Row():
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regenerate_btn = gr.Button(
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value="🔄 Regenerate", visible=True, min_width=120
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)
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with gr.Column(scale=
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rendered_html.render()
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with gr.Row():
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generated_html.render()
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template_gallery = gr.Gallery(
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value=IMAGE_GALLERY_PATHS,
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label="Templates Gallery",
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regenerate_btn.click,
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],
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fn=model_inference,
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inputs=[
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imagebox,
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],
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outputs=[generated_html, rendered_html],
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queue=False,
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)
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outputs=[imagebox],
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queue=False,
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)
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demo.load(
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# inputs=[gallery_type_choice],
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# outputs=[template_gallery],
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queue=False,
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)
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demo.queue(max_size=40, api_open=False)
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demo.launch(max_threads=400)
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import os
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import subprocess
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from playwright.sync_api import sync_playwright
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from typing import List
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from PIL import Image
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import gradio as gr
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from gradio_client.client import DEFAULT_TEMP_DIR
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from transformers import AutoProcessor, AutoModelForCausalLM
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API_TOKEN = os.getenv("HF_AUTH_TOKEN")
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# PROCESSOR = AutoProcessor.from_pretrained(
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# "HuggingFaceM4/img2html",
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# token=API_TOKEN,
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# )
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# MODEL = AutoModelForCausalLM.from_pretrained(
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# "HuggingFaceM4/img2html",
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# token=API_TOKEN,
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# )
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IMAGE_GALLERY_PATHS = [
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f"example_images/{ex_image}"
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for ex_image in os.listdir(f"example_images")
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]
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def install_playwright():
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try:
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except subprocess.CalledProcessError as e:
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print(f"Error during Playwright installation: {e}")
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install_playwright()
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def add_file_gallery(selected_state: gr.SelectData, gallery_list: List[str]):
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return f"example_images/{gallery_list.root[selected_state.index].image.orig_name}"
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def render_webpage(
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html_css_code,
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):
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rendered_page = render_webpage(CAR_COMPNAY)
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return CAR_COMPNAY, rendered_page
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generated_html = gr.Code(
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label="Extracted HTML",
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elem_id="generated_html",
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)
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rendered_html = gr.Image(
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label="Rendered HTML"
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)
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# rendered_html = gr.HTML(
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# label="Rendered HTML"
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# )
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css = """
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.gradio-container{max-width: 1000px!important}
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*{transition: width 0.5s ease, flex-grow 0.5s ease}
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"""
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with gr.Blocks(title="Img2html", theme=gr.themes.Base(), css=css) as demo:
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with gr.Row(equal_height=True):
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with gr.Column(scale=4, min_width=250) as upload_area:
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imagebox = gr.Image(
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type="filepath",
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label="Screenshot to extract",
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visible=True,
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sources=["upload", "clipboard"],
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)
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with gr.Group():
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with gr.Row():
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regenerate_btn = gr.Button(
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value="🔄 Regenerate", visible=True, min_width=120
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)
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with gr.Column(scale=4) as result_area:
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rendered_html.render()
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with gr.Row():
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generated_html.render()
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with gr.Row():
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template_gallery = gr.Gallery(
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value=IMAGE_GALLERY_PATHS,
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label="Templates Gallery",
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regenerate_btn.click,
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],
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fn=model_inference,
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inputs=[imagebox],
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outputs=[generated_html, rendered_html],
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queue=False,
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)
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outputs=[imagebox],
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queue=False,
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)
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demo.load(queue=False)
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demo.queue(max_size=40, api_open=False)
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demo.launch(max_threads=400)
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