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import gradio as gr
from huggingface_hub import InferenceClient
import os
import requests
from typing import List, Dict, Union
import traceback
from selenium import webdriver
from selenium.common.exceptions import WebDriverException
from PIL import Image
from io import BytesIO
HF_TOKEN = os.getenv("HF_TOKEN")
hf_client = InferenceClient("CohereForAI/c4ai-command-r-plus-08-2024", token=HF_TOKEN)
def get_headers():
if not HF_TOKEN:
raise ValueError("Hugging Face token not found in environment variables")
return {"Authorization": f"Bearer {HF_TOKEN}"}
def get_most_liked_spaces(limit: int = 300) -> Union[List[Dict], str]:
url = "https://huggingface.co/api/spaces"
params = {
"sort": "likes",
"direction": -1,
"limit": limit,
"full": "true"
}
try:
response = requests.get(url, params=params, headers=get_headers())
response.raise_for_status()
return response.json()
except requests.RequestException as e:
return f"API request error: {str(e)}"
except ValueError as e:
return f"JSON decoding error: {str(e)}"
def format_space(space: Dict) -> Dict:
space_id = space.get('id', 'Unknown')
space_name = space_id.split('/')[-1] if '/' in space_id else space_id
space_author = space.get('author', 'Unknown')
if isinstance(space_author, dict):
space_author = space_author.get('user', space_author.get('name', 'Unknown'))
space_likes = space.get('likes', 'N/A')
space_url = f"https://huggingface.co/spaces/{space_id}"
return {
"id": space_id,
"name": space_name,
"author": space_author,
"likes": space_likes,
"url": space_url,
}
def format_spaces(spaces: Union[List[Dict], str]) -> List[Dict]:
if isinstance(spaces, str):
return [{"error": spaces}]
return [format_space(space) for space in spaces if isinstance(space, dict)]
def summarize_space(space: Dict) -> str:
system_message = "๋น์ ์ Hugging Face Space์ ๋ด์ฉ์ ์์ฝํ๋ AI ์กฐ์์
๋๋ค. ์ฃผ์ด์ง ์ ๋ณด๋ฅผ ๋ฐํ์ผ๋ก ๊ฐ๊ฒฐํ๊ณ ๋ช
ํํ ์์ฝ์ ์ ๊ณตํด์ฃผ์ธ์."
user_message = f"๋ค์ Hugging Face Space๋ฅผ ์์ฝํด์ฃผ์ธ์: {space['name']} by {space['author']}. ์ข์์ ์: {space['likes']}. URL: {space['url']}"
messages = [
{"role": "system", "content": system_message},
{"role": "user", "content": user_message}
]
try:
response = hf_client.chat_completion(messages, max_tokens=400, temperature=0.7)
return response.choices[0].message.content
except Exception as e:
return f"์์ฝ ์์ฑ ์ค ์ค๋ฅ ๋ฐ์: {str(e)}"
def get_app_py_content(space_id: str) -> str:
app_py_url = f"https://huggingface.co/spaces/{space_id}/raw/main/app.py"
try:
response = requests.get(app_py_url, headers=get_headers())
if response.status_code == 200:
return response.text
else:
return f"app.py file not found or inaccessible for space: {space_id}"
except requests.RequestException:
return f"Error fetching app.py content for space: {space_id}"
def on_select(space):
try:
summary = summarize_space(space)
app_content = get_app_py_content(space['id'])
screenshot = take_screenshot(space['url'])
info = f"์ ํ๋ Space: {space['name']} (ID: {space['id']})\n"
info += f"Author: {space['author']}\n"
info += f"Likes: {space['likes']}\n"
info += f"URL: {space['url']}\n\n"
info += f"์์ฝ:\n{summary}"
return info, app_content, screenshot
except Exception as e:
print(f"Error in on_select: {str(e)}")
print(traceback.format_exc())
return f"์ค๋ฅ๊ฐ ๋ฐ์ํ์ต๋๋ค: {str(e)}", "", Image.new('RGB', (1, 1))
def take_screenshot(url):
options = webdriver.ChromeOptions()
options.add_argument('--headless')
options.add_argument('--no-sandbox')
options.add_argument('--disable-dev-shm-usage')
try:
wd = webdriver.Chrome(options=options)
wd.set_window_size(1080, 720)
wd.get(url)
wd.implicitly_wait(10)
screenshot = wd.get_screenshot_as_png()
except WebDriverException as e:
return Image.new('RGB', (1, 1))
finally:
if wd:
wd.quit()
return Image.open(BytesIO(screenshot))
def create_ui():
spaces_list = get_most_liked_spaces()
print(f"Type of spaces_list: {type(spaces_list)}")
formatted_spaces = format_spaces(spaces_list)
print(f"Total spaces loaded: {len(formatted_spaces)}")
css = """
footer {visibility: hidden;}
.minimal-button {min-width: 30px !important; height: 25px !important; line-height: 1 !important; font-size: 12px !important; padding: 2px 5px !important;}
.space-row {margin-bottom: 5px !important;}
"""
with gr.Blocks(css=css, theme="Nymbo/Nymbo_Theme") as demo:
gr.Markdown("# Hugging Face Most Liked Spaces")
with gr.Row():
with gr.Column(scale=1):
space_rows = []
for space in formatted_spaces:
with gr.Row(elem_classes="space-row") as space_row:
with gr.Column():
gr.Markdown(f"{space['name']} by {space['author']} (Likes: {space['likes']})", elem_classes="space-info")
button = gr.Button("ํด๋ฆญ", elem_classes="minimal-button")
space_rows.append((space_row, button, space))
with gr.Column(scale=1):
info_output = gr.Textbox(label="Space ์ ๋ณด ๋ฐ ์์ฝ", lines=16)
app_py_content = gr.Code(language="python", label="app.py ๋ด์ฉ")
for _, button, space in space_rows:
button.click(
lambda s=space: on_select(s),
inputs=[],
outputs=[info_output, app_py_content]
)
with gr.Column(scale=1):
info_output = gr.Textbox(label="Space ์ ๋ณด ๋ฐ ์์ฝ", lines=16)
app_py_content = gr.Code(language="python", label="app.py ๋ด์ฉ")
screenshot_output = gr.Image(type="pil", label="Live ํ๋ฉด", height=360, width=540)
for _, button, space in space_rows:
button.click(
lambda s=space: on_select(s),
inputs=[],
outputs=[info_output, app_py_content, screenshot_output]
)
return demo
if __name__ == "__main__":
demo = create_ui()
demo.launch() |