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Update app-backup4.py
Browse files- app-backup4.py +55 -50
app-backup4.py
CHANGED
@@ -3,13 +3,9 @@ from huggingface_hub import InferenceClient
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import os
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import requests
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from typing import List, Dict, Union
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import concurrent.futures
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import traceback
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# 환경 변수에서 토큰 가져오기
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HF_TOKEN = os.getenv("HF_TOKEN")
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# 추론 API 클라이언트 설정
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hf_client = InferenceClient("CohereForAI/c4ai-command-r-plus-08-2024", token=HF_TOKEN)
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def get_headers():
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@@ -17,7 +13,7 @@ def get_headers():
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raise ValueError("Hugging Face token not found in environment variables")
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return {"Authorization": f"Bearer {HF_TOKEN}"}
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def get_most_liked_spaces(limit: int =
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url = "https://huggingface.co/api/spaces"
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params = {
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"sort": "likes",
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@@ -29,12 +25,7 @@ def get_most_liked_spaces(limit: int = 100) -> Union[List[Dict], str]:
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try:
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response = requests.get(url, params=params, headers=get_headers())
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response.raise_for_status()
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if isinstance(data, list):
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return data
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else:
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return f"Unexpected API response format: {type(data)}"
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except requests.RequestException as e:
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return f"API request error: {str(e)}"
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except ValueError as e:
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@@ -56,15 +47,29 @@ def format_space(space: Dict) -> Dict:
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"name": space_name,
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"author": space_author,
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"likes": space_likes,
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"url": space_url
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}
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def format_spaces(spaces: Union[List[Dict], str]) -> List[Dict]:
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if isinstance(spaces, str):
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return [{"error": spaces}]
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def get_app_py_content(space_id: str) -> str:
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app_py_url = f"https://huggingface.co/spaces/{space_id}/raw/main/app.py"
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@@ -77,56 +82,56 @@ def get_app_py_content(space_id: str) -> str:
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except requests.RequestException:
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return f"Error fetching app.py content for space: {space_id}"
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def
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def create_ui():
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spaces_list = get_most_liked_spaces()
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formatted_spaces = format_spaces(spaces_list)
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print(f"Total spaces loaded: {len(formatted_spaces)}")
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with gr.Blocks() as demo:
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gr.Markdown("# Hugging Face Most Liked Spaces")
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with gr.Row():
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with gr.Column(scale=1):
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for space in formatted_spaces:
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with gr.Row():
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gr.
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with gr.Column(scale=1):
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info_output = gr.Textbox(label="Space 정보 및 요약", lines=
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app_py_content = gr.Code(language="python", label="app.py 내용")
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info += f"Likes: {space['likes']}\n"
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info += f"URL: {space['url']}\n\n"
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info += f"요약:\n{summary}"
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return info, app_content
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except Exception as e:
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print(f"Error in on_select: {str(e)}")
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print(traceback.format_exc())
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return f"오류가 발생했습니다: {str(e)}", ""
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for button, space in zip(space_buttons, formatted_spaces):
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button.click(on_select, inputs=[gr.State(space)], outputs=[info_output, app_py_content])
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return demo
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import os
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import requests
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from typing import List, Dict, Union
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import traceback
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HF_TOKEN = os.getenv("HF_TOKEN")
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hf_client = InferenceClient("CohereForAI/c4ai-command-r-plus-08-2024", token=HF_TOKEN)
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def get_headers():
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raise ValueError("Hugging Face token not found in environment variables")
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return {"Authorization": f"Bearer {HF_TOKEN}"}
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def get_most_liked_spaces(limit: int = 300) -> Union[List[Dict], str]:
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url = "https://huggingface.co/api/spaces"
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params = {
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"sort": "likes",
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try:
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response = requests.get(url, params=params, headers=get_headers())
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response.raise_for_status()
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return response.json()
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except requests.RequestException as e:
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return f"API request error: {str(e)}"
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except ValueError as e:
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"name": space_name,
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"author": space_author,
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"likes": space_likes,
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"url": space_url,
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}
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def format_spaces(spaces: Union[List[Dict], str]) -> List[Dict]:
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if isinstance(spaces, str):
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return [{"error": spaces}]
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return [format_space(space) for space in spaces if isinstance(space, dict)]
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def summarize_space(space: Dict) -> str:
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system_message = "당신은 Hugging Face Space의 내용을 요약하는 AI 조수입니다. 주어진 정보를 바탕으로 간결하고 명확한 요약을 제공해주세요."
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user_message = f"다음 Hugging Face Space를 요약해주세요: {space['name']} by {space['author']}. 좋아요 수: {space['likes']}. URL: {space['url']}"
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messages = [
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{"role": "system", "content": system_message},
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{"role": "user", "content": user_message}
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]
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try:
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response = hf_client.chat_completion(messages, max_tokens=400, temperature=0.7)
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return response.choices[0].message.content
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except Exception as e:
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return f"요약 생성 중 오류 발생: {str(e)}"
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def get_app_py_content(space_id: str) -> str:
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app_py_url = f"https://huggingface.co/spaces/{space_id}/raw/main/app.py"
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except requests.RequestException:
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return f"Error fetching app.py content for space: {space_id}"
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def on_select(space):
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try:
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summary = summarize_space(space)
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app_content = get_app_py_content(space['id'])
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info = f"선택된 Space: {space['name']} (ID: {space['id']})\n"
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info += f"Author: {space['author']}\n"
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info += f"Likes: {space['likes']}\n"
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info += f"URL: {space['url']}\n\n"
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info += f"요약:\n{summary}"
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return info, app_content
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except Exception as e:
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print(f"Error in on_select: {str(e)}")
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print(traceback.format_exc())
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return f"오류가 발생했습니다: {str(e)}", ""
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def create_ui():
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spaces_list = get_most_liked_spaces()
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print(f"Type of spaces_list: {type(spaces_list)}")
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formatted_spaces = format_spaces(spaces_list)
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print(f"Total spaces loaded: {len(formatted_spaces)}")
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css = """
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footer {visibility: hidden;}
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.minimal-button {min-width: 30px !important; height: 25px !important; line-height: 1 !important; font-size: 12px !important; padding: 2px 5px !important;}
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.space-row {margin-bottom: 5px !important;}
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"""
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with gr.Blocks(css=css, theme="Nymbo/Nymbo_Theme") as demo:
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gr.Markdown("# Hugging Face Most Liked Spaces")
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with gr.Row():
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with gr.Column(scale=1):
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space_rows = []
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for space in formatted_spaces:
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with gr.Row(elem_classes="space-row") as space_row:
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with gr.Column():
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gr.Markdown(f"{space['name']} by {space['author']} (Likes: {space['likes']})", elem_classes="space-info")
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button = gr.Button("클릭", elem_classes="minimal-button")
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space_rows.append((space_row, button, space))
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with gr.Column(scale=1):
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info_output = gr.Textbox(label="Space 정보 및 요약", lines=16)
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app_py_content = gr.Code(language="python", label="app.py 내용")
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for _, button, space in space_rows:
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button.click(
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lambda s=space: on_select(s),
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inputs=[],
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outputs=[info_output, app_py_content]
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)
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return demo
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