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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 = "๋น์ ์ Python ์ฝ๋๋ฅผ ๋ถ์ํ๊ณ ์์ฝํ๋ AI ์กฐ์์ ๋๋ค. ์ฃผ์ด์ง ์ฝ๋๋ฅผ 3์ค ์ด๋ด๋ก ๊ฐ๊ฒฐํ๊ฒ ์์ฝํด์ฃผ์ธ์." | |
user_message = f"๋ค์ Python ์ฝ๋๋ฅผ 3์ค ์ด๋ด๋ก ์์ฝํด์ฃผ์ธ์:\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"์์ฝ ์์ฑ ์ค ์ค๋ฅ ๋ฐ์: {str(e)}" | |
def analyze_code(app_content: str) -> str: | |
system_message = """๋น์ ์ Python ์ฝ๋๋ฅผ ๋ถ์ํ๋ AI ์กฐ์์ ๋๋ค. ์ฃผ์ด์ง ์ฝ๋๋ฅผ ๋ถ์ํ์ฌ ๋ค์ ํญ๋ชฉ์ ๋ํด ์ค๋ช ํด์ฃผ์ธ์: | |
A. ๋ฐฐ๊ฒฝ ๋ฐ ํ์์ฑ | |
B. ๊ธฐ๋ฅ์ ํจ์ฉ์ฑ ๋ฐ ๊ฐ์น | |
C. ํน์ฅ์ | |
D. ์ ์ฉ ๋์ ๋ฐ ํ๊ฒ | |
E. ๊ธฐ๋ํจ๊ณผ | |
๊ธฐ์กด ๋ฐ ์ ์ฌ ํ๋ก์ ํธ์ ๋น๊ตํ์ฌ ๋ถ์ํด์ฃผ์ธ์.""" | |
user_message = f"๋ค์ Python ์ฝ๋๋ฅผ ๋ถ์ํด์ฃผ์ธ์:\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"๋ถ์ ์์ฑ ์ค ์ค๋ฅ ๋ฐ์: {str(e)}" | |
def explain_usage(app_content: str) -> str: | |
system_message = "๋น์ ์ Python ์ฝ๋๋ฅผ ๋ถ์ํ์ฌ ์ฌ์ฉ๋ฒ์ ์ค๋ช ํ๋ AI ์กฐ์์ ๋๋ค. ์ฃผ์ด์ง ์ฝ๋๋ฅผ ๋ฐํ์ผ๋ก ๋ง์น ํ๋ฉด์ ๋ณด๋ ๊ฒ์ฒ๋ผ ์ฌ์ฉ๋ฒ์ ์์ธํ ์ค๋ช ํด์ฃผ์ธ์." | |
user_message = f"๋ค์ Python ์ฝ๋์ ์ฌ์ฉ๋ฒ์ ์ค๋ช ํด์ฃผ์ธ์:\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"์ฌ์ฉ๋ฒ ์ค๋ช ์์ฑ ์ค ์ค๋ฅ ๋ฐ์: {str(e)}" | |
def analyze_space(url: str): | |
try: | |
# URL์์ space_id ์ถ์ถ | |
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"์ค๋ฅ๊ฐ ๋ฐ์ํ์ต๋๋ค: {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): # ์ผ์ชฝ 60% | |
url_input = gr.Textbox(label="HuggingFace Space URL") | |
analyze_button = gr.Button("๋ถ์") | |
with gr.Group(elem_classes="output-group scroll-lock"): | |
summary_output = gr.Textbox(label="์์ฝ (3์ค ์ด๋ด)", lines=3) | |
with gr.Group(elem_classes="output-group scroll-lock"): | |
analysis_output = gr.Textbox(label="๋ถ์", lines=15) | |
with gr.Group(elem_classes="output-group scroll-lock"): | |
usage_output = gr.Textbox(label="์ฌ์ฉ๋ฒ", lines=10) | |
with gr.Column(scale=4): # ์ค๋ฅธ์ชฝ 40% | |
with gr.Group(elem_classes="output-group scroll-lock"): | |
app_py_content = gr.Code(language="python", label="๋ฉ์ธ ์์ค์ฝ๋", 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()) |