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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 PIL import Image
from io import BytesIO
import asyncio
from gradio_client import Client
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:
content = response.text
if len(content) > 500: # ๋ด์ฉ์ 500์๋ก ์ ํํฉ๋๋ค
content = content[:497] + "..."
return content
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', (1080, 720), color='lightgray')
def take_screenshot(url):
try:
client = Client("ginipick/selenium-screenshot-gradio")
result = client.predict(url=url, api_name="/predict")
return Image.open(result)
except Exception as e:
print(f"Screenshot error: {str(e)}")
return Image.new('RGB', (1080, 720), color='lightgray')
def create_ui():
try:
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("# 300: HuggingFace 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=20)
screenshot_output = gr.Image(type="pil", label="Space ์คํฌ๋ฆฐ์ท", height=360, width=600)
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, screenshot_output]
)
return demo
except Exception as e:
print(f"Error in create_ui: {str(e)}")
print(traceback.format_exc())
raise
if __name__ == "__main__":
try:
demo = create_ui()
demo.launch()
except Exception as e:
print(f"Error in main: {str(e)}")
print(traceback.format_exc()) |