Delete app-backup9.py

app-backup9.py

@@ -1,158 +0,0 @@
-import gradio as gr
-from huggingface_hub import InferenceClient, HfApi
-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
-import time
-import threading
-import json
-
-HF_TOKEN = os.getenv("HF_TOKEN")
-hf_client = InferenceClient("CohereForAI/c4ai-command-r-plus-08-2024", token=HF_TOKEN)
-hf_api = HfApi(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_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 summarize_code(app_content: str) -> str:
-    system_message = "당신은 Python 코드를 분석하고 요약하는 AI 조수입니다. 주어진 코드를 3줄 이내로 간결하게 요약해주세요."
-    user_message = f"다음 Python 코드를 3줄 이내로 요약해주세요:\n\n{app_content}"
-    
-    messages = [
-        {"role": "system", "content": system_message},
-        {"role": "user", "content": user_message}
-    ]
-    
-    try:
-        response = hf_client.chat_completion(messages, max_tokens=200, temperature=0.7)
-        return response.choices[0].message.content
-    except Exception as e:
-        return f"요약 생성 중 오류 발생: {str(e)}"
-
-def analyze_code(app_content: str) -> str:
-    system_message = """당신은 Python 코드를 분석하는 AI 조수입니다. 주어진 코드를 분석하여 다음 항목에 대해 설명해주세요:
-    A. 배경 및 필요성
-    B. 기능적 효용성 및 가치
-    C. 특장점
-    D. 적용 대상 및 타겟
-    E. 기대효과
-    기존 및 유사 프로젝트와 비교하여 분석해주세요."""
-    user_message = f"다음 Python 코드를 분석해주세요:\n\n{app_content}"
-    
-    messages = [
-        {"role": "system", "content": system_message},
-        {"role": "user", "content": user_message}
-    ]
-    
-    try:
-        response = hf_client.chat_completion(messages, max_tokens=1000, temperature=0.7)
-        return response.choices[0].message.content
-    except Exception as e:
-        return f"분석 생성 중 오류 발생: {str(e)}"
-
-def explain_usage(app_content: str) -> str:
-    system_message = "당신은 Python 코드를 분석하여 사용법을 설명하는 AI 조수입니다. 주어진 코드를 바탕으로 마치 화면을 보는 것처럼 사용법을 상세히 설명해주세요."
-    user_message = f"다음 Python 코드의 사용법을 설명해주세요:\n\n{app_content}"
-    
-    messages = [
-        {"role": "system", "content": system_message},
-        {"role": "user", "content": user_message}
-    ]
-    
-    try:
-        response = hf_client.chat_completion(messages, max_tokens=800, temperature=0.7)
-        return response.choices[0].message.content
-    except Exception as e:
-        return f"사용법 설명 생성 중 오류 발생: {str(e)}"
-
-def analyze_space(url: str):
-    try:
-        # URL에서 space_id 추출
-        space_id = url.split('spaces/')[-1]
-        
-        app_content = get_app_py_content(space_id)
-        summary = summarize_code(app_content)
-        analysis = analyze_code(app_content)
-        usage = explain_usage(app_content)
-        
-        return summary, analysis, usage, app_content
-    except Exception as e:
-        print(f"Error in analyze_space: {str(e)}")
-        print(traceback.format_exc())
-        return f"오류가 발생했습니다: {str(e)}", "", "", ""
-
-def create_ui():
-    try:
-        css = """
-        footer {visibility: hidden;}
-        .output-group {
-            border: 1px solid #ddd;
-            border-radius: 5px;
-            padding: 10px;
-            margin-bottom: 20px;
-        }
-        .scroll-lock {
-            overflow: auto !important;
-            max-height: 400px !important;
-        }
-        """
-
-        with gr.Blocks(css=css, theme="Nymbo/Nymbo_Theme") as demo:
-            gr.Markdown("# HuggingFace Space Analyzer")
-            
-            with gr.Row():
-                with gr.Column(scale=6):  # 왼쪽 60%
-                    url_input = gr.Textbox(label="HuggingFace Space URL")
-                    analyze_button = gr.Button("분석")
-                    
-                    with gr.Group(elem_classes="output-group scroll-lock"):
-                        summary_output = gr.Textbox(label="요약 (3줄 이내)", lines=3)
-                    
-                    with gr.Group(elem_classes="output-group scroll-lock"):
-                        analysis_output = gr.Textbox(label="분석", lines=15)
-                    
-                    with gr.Group(elem_classes="output-group scroll-lock"):
-                        usage_output = gr.Textbox(label="사용법", lines=10)
-                
-                with gr.Column(scale=4):  # 오른쪽 40%
-                    with gr.Group(elem_classes="output-group scroll-lock"):
-                        app_py_content = gr.Code(language="python", label="메인 소스코드", lines=30)
-
-            analyze_button.click(
-                analyze_space,
-                inputs=[url_input],
-                outputs=[summary_output, analysis_output, usage_output, app_py_content]
-            )
-
-        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())