Create app.py

app.py

@@ -0,0 +1,195 @@
+import gradio as gr
+from huggingface_hub import InferenceClient
+import os
+import requests
+from typing import List, Dict, Union
+import concurrent.futures
+import base64
+import traceback
+
+# 환경 변수에서 토큰 가져오기
+HF_TOKEN = os.getenv("HF_TOKEN")
+
+# 추론 API 클라이언트 설정
+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 = 100) -> 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()
+        data = response.json()
+        
+        if isinstance(data, list):
+            return data
+        else:
+            return f"Unexpected API response format: {type(data)}"
+    except requests.RequestException as e:
+        return f"API request error: {str(e)}"
+    except ValueError as e:
+        return f"JSON decoding error: {str(e)}"
+
+def capture_thumbnail(space_id: str) -> str:
+    screenshot_url = f"https://huggingface.co/spaces/{space_id}/screenshot.jpg"
+    try:
+        response = requests.get(screenshot_url, headers=get_headers())
+        if response.status_code == 200:
+            return base64.b64encode(response.content).decode('utf-8')
+    except requests.RequestException:
+        pass
+    return ""
+
+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 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}"
+    
+    thumbnail = capture_thumbnail(space_id)
+    
+    return {
+        "id": space_id,
+        "name": space_name,
+        "author": space_author,
+        "likes": space_likes,
+        "url": space_url,
+        "thumbnail": thumbnail
+    }
+
+def format_spaces(spaces: Union[List[Dict], str]) -> List[Dict]:
+    if isinstance(spaces, str):
+        return [{"error": spaces}]
+    
+    with concurrent.futures.ThreadPoolExecutor(max_workers=10) as executor:
+        return list(executor.map(format_space, spaces))
+
+def summarize_space(space: Dict) -> str:
+    system_message = "당신은 Hugging Face Space의 내용을 요약하는 AI 조수입니다. 주어진 정보를 바탕으로 간결하고 명확한 요약을 제공해주세요."
+    user_message = f"다음 Hugging Face Space를 요약해주세요: {space['name']} by {space['author']}. 좋아요 수: {space['likes']}. URL: {space['url']}"
+    
+    messages = [
+        {"role": "system", "content": system_message},
+        {"role": "user", "content": user_message}
+    ]
+    
+    response = hf_client.chat_completion(messages, max_tokens=150, temperature=0.7)
+    return response.choices[0].message.content
+
+def create_ui():
+    spaces_list = get_most_liked_spaces()
+    formatted_spaces = format_spaces(spaces_list)
+    print(f"Total spaces loaded: {len(formatted_spaces)}")  # 디버깅 출력
+
+    space_choices = {f"{space['name']} by {space['author']} (Likes: {space['likes']})": space['id'] for space in formatted_spaces}
+
+    with gr.Blocks(css="#space-list { height: 400px; overflow-y: auto; }") as demo:
+        gr.Markdown("# Hugging Face Most Liked Spaces")
+        
+        with gr.Row():
+            with gr.Column(scale=1):
+                with gr.Box(elem_id="space-list"):
+                    for space in formatted_spaces:
+                        with gr.Row():
+                            gr.Radio(
+                                choices=[f"{space['name']} by {space['author']} (Likes: {space['likes']})"],
+                                label="",
+                                value=None,
+                                name=space['id']
+                            )
+                            gr.Button("🔗", elem_id=f"link-{space['id']}")
+                summarize_btn = gr.Button("요약")
+            
+            with gr.Column(scale=2):
+                output = gr.Textbox(label="Space 정보", lines=10)
+                app_py_content = gr.Code(language="python", label="app.py 내용")
+
+        def on_select(choice):
+            try:
+                print(f"Selected: {choice}")  # 디버깅 출력
+                selected_id = space_choices[choice]
+                selected_space = next((space for space in formatted_spaces if space['id'] == selected_id), None)
+                if selected_space:
+                    app_content = get_app_py_content(selected_id)
+                    print(f"Selected space: {selected_space['name']} (ID: {selected_id})")  # 디버깅 출력
+                    return f"선택된 Space: {selected_space['name']} (ID: {selected_id})\nURL: {selected_space['url']}", app_content
+                else:
+                    print(f"Space not found for ID: {selected_id}")  # 디버깅 출력
+                    return "선택된 space를 찾을 수 없습니다.", ""
+            except Exception as e:
+                print(f"Error in on_select: {str(e)}")
+                print(traceback.format_exc())  # 상세한 오류 정보 출력
+                return f"오류가 발생했습니다: {str(e)}", ""
+
+        def on_summarize(choice):
+            try:
+                if choice:
+                    selected_id = space_choices[choice]
+                    selected_space = next((space for space in formatted_spaces if space['id'] == selected_id), None)
+                    if selected_space:
+                        summary = summarize_space(selected_space)
+                        print(f"Summarizing space: {selected_space['name']}")  # 디버깅 출력
+                        return summary
+                print("No space selected for summarization")  # 디버깅 출력
+                return "선택된 space가 없습니다. 먼저 리스트에서 space를 선택해주세요."
+            except Exception as e:
+                print(f"Error in on_summarize: {str(e)}")
+                print(traceback.format_exc())  # 상세한 오류 정보 출력
+                return f"요약 중 오류가 발생했습니다: {str(e)}"
+
+        for space in formatted_spaces:
+            radio = demo.components[0].children[0].children[0].children[0].children[formatted_spaces.index(space)].children[0]
+            radio.change(on_select, radio, [output, app_py_content])
+
+        summarize_btn.click(on_summarize, inputs=[gr.State(lambda: next(radio for radio in demo.components[0].children[0].children[0].children[0].children if radio.children[0].value))], outputs=[output])
+
+        # JavaScript to open links in new tabs
+        link_script = """
+        function setupLinkButtons() {
+            document.querySelectorAll('button[id^="link-"]').forEach(button => {
+                button.addEventListener('click', function() {
+                    var spaceId = this.id.split('-')[1];
+                    window.open('https://huggingface.co/spaces/' + spaceId, '_blank');
+                });
+            });
+        }
+        if (document.readyState === 'complete') {
+            setupLinkButtons();
+        } else {
+            document.addEventListener('DOMContentLoaded', setupLinkButtons);
+        }
+        """
+        demo.load(None, None, None, _js=link_script)
+
+    return demo
+
+if __name__ == "__main__":
+    demo = create_ui()
+    demo.launch()