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import gradio as gr |
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import pandas as pd |
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import os |
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import time |
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import threading |
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import tempfile |
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import logging |
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import random |
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import uuid |
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import shutil |
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import glob |
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from datetime import datetime |
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import sys |
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import types |
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logging.basicConfig( |
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level=logging.INFO, |
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format='%(asctime)s - %(name)s - %(levelname)s - %(message)s', |
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handlers=[ |
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logging.StreamHandler(), |
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logging.FileHandler('main_keyword_app.log', mode='a') |
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] |
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) |
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logger = logging.getLogger(__name__) |
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def load_module_from_env(module_name, env_var_name): |
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"""νκ²½λ³μμμ λͺ¨λ μ½λλ₯Ό λ‘λνμ¬ λμ μΌλ‘ λͺ¨λ μμ±""" |
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try: |
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module_code = os.getenv(env_var_name) |
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if not module_code: |
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raise ValueError(f"νκ²½λ³μ {env_var_name}κ° μ€μ λμ§ μμμ΅λλ€.") |
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module = types.ModuleType(module_name) |
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|
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module.__dict__.update({ |
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'os': __import__('os'), |
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'time': __import__('time'), |
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'logging': __import__('logging'), |
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'pandas': __import__('pandas'), |
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'requests': __import__('requests'), |
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'tempfile': __import__('tempfile'), |
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'threading': __import__('threading'), |
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're': __import__('re'), |
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'random': __import__('random'), |
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'uuid': __import__('uuid'), |
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'shutil': __import__('shutil'), |
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'glob': __import__('glob'), |
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'datetime': __import__('datetime'), |
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'types': __import__('types'), |
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'collections': __import__('collections'), |
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'Counter': __import__('collections').Counter, |
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'defaultdict': __import__('collections').defaultdict, |
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'hmac': __import__('hmac'), |
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'hashlib': __import__('hashlib'), |
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'base64': __import__('base64'), |
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}) |
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exec(module_code, module.__dict__) |
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sys.modules[module_name] = module |
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|
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logger.info(f"β
λͺ¨λ {module_name} λ‘λ μλ£") |
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return module |
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except Exception as e: |
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logger.error(f"β λͺ¨λ {module_name} λ‘λ μ€ν¨: {e}") |
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raise |
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|
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logger.info("π λͺ¨λ λ‘λ μμ...") |
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|
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try: |
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|
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api_utils = load_module_from_env('api_utils', 'API_UTILS_CODE') |
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text_utils = load_module_from_env('text_utils', 'TEXT_UTILS_CODE') |
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keyword_search = load_module_from_env('keyword_search', 'KEYWORD_SEARCH_CODE') |
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product_search_module = load_module_from_env('product_search', 'PRODUCT_SEARCH_CODE') |
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product_search_module.api_utils = api_utils |
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product_search_module.text_utils = text_utils |
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product_search = product_search_module |
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keyword_processor_module = load_module_from_env('keyword_processor', 'KEYWORD_PROCESSOR_CODE') |
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keyword_processor_module.text_utils = text_utils |
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keyword_processor_module.keyword_search = keyword_search |
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keyword_processor_module.product_search = product_search |
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keyword_processor = keyword_processor_module |
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export_utils = load_module_from_env('export_utils', 'EXPORT_UTILS_CODE') |
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category_analysis_module = load_module_from_env('category_analysis', 'CATEGORY_ANALYSIS_CODE') |
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category_analysis_module.text_utils = text_utils |
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category_analysis_module.product_search = product_search |
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category_analysis_module.keyword_search = keyword_search |
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category_analysis = category_analysis_module |
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|
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logger.info("β
λͺ¨λ λͺ¨λ λ‘λ μλ£") |
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except Exception as e: |
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logger.error(f"β λͺ¨λ λ‘λ μ€ μΉλͺ
μ μ€λ₯: {e}") |
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logger.error("νμν νκ²½λ³μλ€μ΄ μ€μ λμλμ§ νμΈνμΈμ:") |
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logger.error("- API_UTILS_CODE") |
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logger.error("- TEXT_UTILS_CODE") |
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logger.error("- KEYWORD_SEARCH_CODE") |
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logger.error("- PRODUCT_SEARCH_CODE") |
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logger.error("- KEYWORD_PROCESSOR_CODE") |
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logger.error("- EXPORT_UTILS_CODE") |
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logger.error("- CATEGORY_ANALYSIS_CODE") |
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raise |
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session_temp_files = {} |
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session_data = {} |
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|
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def cleanup_huggingface_temp_folders(): |
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"""νκΉ
νμ΄μ€ μμ ν΄λ μ΄κΈ° μ 리""" |
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try: |
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|
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temp_dirs = [ |
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tempfile.gettempdir(), |
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"/tmp", |
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"/var/tmp", |
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os.path.join(os.getcwd(), "temp"), |
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os.path.join(os.getcwd(), "tmp"), |
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"/gradio_cached_examples", |
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"/flagged" |
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] |
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cleanup_count = 0 |
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|
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for temp_dir in temp_dirs: |
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if os.path.exists(temp_dir): |
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try: |
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|
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session_files = glob.glob(os.path.join(temp_dir, "session_*.xlsx")) |
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session_files.extend(glob.glob(os.path.join(temp_dir, "session_*.csv"))) |
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session_files.extend(glob.glob(os.path.join(temp_dir, "*keyword*.xlsx"))) |
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session_files.extend(glob.glob(os.path.join(temp_dir, "*keyword*.csv"))) |
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session_files.extend(glob.glob(os.path.join(temp_dir, "tmp*.xlsx"))) |
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session_files.extend(glob.glob(os.path.join(temp_dir, "tmp*.csv"))) |
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|
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for file_path in session_files: |
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try: |
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|
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if os.path.getmtime(file_path) < time.time() - 3600: |
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os.remove(file_path) |
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cleanup_count += 1 |
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logger.info(f"μ΄κΈ° μ 리: μ€λλ μμ νμΌ μμ - {file_path}") |
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except Exception as e: |
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logger.warning(f"νμΌ μμ μ€ν¨ (무μλ¨): {file_path} - {e}") |
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|
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except Exception as e: |
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logger.warning(f"μμ λλ ν 리 μ 리 μ€ν¨ (무μλ¨): {temp_dir} - {e}") |
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|
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logger.info(f"β
νκΉ
νμ΄μ€ μμ ν΄λ μ΄κΈ° μ 리 μλ£ - {cleanup_count}κ° νμΌ μμ ") |
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|
|
|
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try: |
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gradio_temp_dir = os.path.join(os.getcwd(), "gradio_cached_examples") |
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if os.path.exists(gradio_temp_dir): |
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shutil.rmtree(gradio_temp_dir, ignore_errors=True) |
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logger.info("Gradio μΊμ ν΄λ μ 리 μλ£") |
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except Exception as e: |
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logger.warning(f"Gradio μΊμ ν΄λ μ 리 μ€ν¨ (무μλ¨): {e}") |
|
|
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except Exception as e: |
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logger.error(f"μ΄κΈ° μμ ν΄λ μ 리 μ€ μ€λ₯ (κ³μ μ§ν): {e}") |
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|
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def setup_clean_temp_environment(): |
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"""κΉ¨λν μμ νκ²½ μ€μ """ |
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try: |
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|
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cleanup_huggingface_temp_folders() |
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|
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app_temp_dir = os.path.join(tempfile.gettempdir(), "keyword_app") |
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if os.path.exists(app_temp_dir): |
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shutil.rmtree(app_temp_dir, ignore_errors=True) |
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os.makedirs(app_temp_dir, exist_ok=True) |
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os.environ['KEYWORD_APP_TEMP'] = app_temp_dir |
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logger.info(f"β
μ ν리μΌμ΄μ
μ μ© μμ λλ ν 리 μ€μ : {app_temp_dir}") |
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return app_temp_dir |
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|
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except Exception as e: |
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logger.error(f"μμ νκ²½ μ€μ μ€ν¨: {e}") |
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return tempfile.gettempdir() |
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|
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def get_app_temp_dir(): |
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"""μ ν리μΌμ΄μ
μ μ© μμ λλ ν 리 λ°ν""" |
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return os.environ.get('KEYWORD_APP_TEMP', tempfile.gettempdir()) |
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|
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def get_session_id(): |
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"""μΈμ
ID μμ±""" |
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return str(uuid.uuid4()) |
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|
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def cleanup_session_files(session_id, delay=300): |
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"""μΈμ
λ³ μμ νμΌ μ 리 ν¨μ""" |
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def cleanup(): |
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time.sleep(delay) |
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if session_id in session_temp_files: |
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files_to_remove = session_temp_files[session_id].copy() |
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del session_temp_files[session_id] |
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|
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for file_path in files_to_remove: |
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try: |
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if os.path.exists(file_path): |
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os.remove(file_path) |
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logger.info(f"μΈμ
{session_id[:8]}... μμ νμΌ μμ : {file_path}") |
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except Exception as e: |
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logger.error(f"μΈμ
{session_id[:8]}... νμΌ μμ μ€λ₯: {e}") |
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|
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threading.Thread(target=cleanup, daemon=True).start() |
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|
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def register_session_file(session_id, file_path): |
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"""μΈμ
λ³ νμΌ λ±λ‘""" |
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if session_id not in session_temp_files: |
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session_temp_files[session_id] = [] |
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session_temp_files[session_id].append(file_path) |
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|
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def cleanup_old_sessions(): |
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"""μ€λλ μΈμ
λ°μ΄ν° μ 리""" |
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current_time = time.time() |
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sessions_to_remove = [] |
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|
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for session_id, data in session_data.items(): |
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if current_time - data.get('last_activity', 0) > 3600: |
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sessions_to_remove.append(session_id) |
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|
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for session_id in sessions_to_remove: |
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|
|
if session_id in session_temp_files: |
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for file_path in session_temp_files[session_id]: |
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try: |
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if os.path.exists(file_path): |
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os.remove(file_path) |
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logger.info(f"μ€λλ μΈμ
{session_id[:8]}... νμΌ μμ : {file_path}") |
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except Exception as e: |
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logger.error(f"μ€λλ μΈμ
νμΌ μμ μ€λ₯: {e}") |
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del session_temp_files[session_id] |
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|
|
|
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if session_id in session_data: |
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del session_data[session_id] |
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logger.info(f"μ€λλ μΈμ
λ°μ΄ν° μμ : {session_id[:8]}...") |
|
|
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def update_session_activity(session_id): |
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"""μΈμ
νλ μκ° μ
λ°μ΄νΈ""" |
|
if session_id not in session_data: |
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session_data[session_id] = {} |
|
session_data[session_id]['last_activity'] = time.time() |
|
|
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def create_session_temp_file(session_id, suffix='.xlsx'): |
|
"""μΈμ
λ³ μμ νμΌ μμ± (μ μ© λλ ν 리 μ¬μ©)""" |
|
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") |
|
random_suffix = str(random.randint(1000, 9999)) |
|
|
|
|
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temp_dir = get_app_temp_dir() |
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filename = f"session_{session_id[:8]}_{timestamp}_{random_suffix}{suffix}" |
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temp_file_path = os.path.join(temp_dir, filename) |
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|
|
|
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with open(temp_file_path, 'w') as f: |
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pass |
|
|
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register_session_file(session_id, temp_file_path) |
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return temp_file_path |
|
|
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def wrapper_modified(keyword, korean_only, apply_main_keyword_option, exclude_zero_volume, session_id): |
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"""ν€μλ κ²μ λ° μ²λ¦¬ λνΌ ν¨μ (μΈμ
ID μΆκ°)""" |
|
update_session_activity(session_id) |
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|
|
|
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current_keyword = keyword |
|
|
|
|
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if not keyword: |
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return (gr.update(value=""), gr.update(choices=["μ 체 보기"]), gr.update(choices=["μ 체"]), |
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None, gr.update(choices=["μ 체 보기"], value="μ 체 보기"), None, |
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gr.update(visible=False), gr.update(visible=False), current_keyword) |
|
|
|
|
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search_results = product_search.fetch_naver_shopping_data(keyword, korean_only, apply_main_keyword_option == "λ©μΈν€μλ μ μ©") |
|
|
|
|
|
if not search_results.get("product_list"): |
|
return (gr.update(value="<p>κ²μ κ²°κ³Όκ° μμ΅λλ€. λ€λ₯Έ ν€μλλ‘ μλν΄λ³΄μΈμ.</p>"), |
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gr.update(choices=["μ 체 보기"]), gr.update(choices=["μ 체"]), |
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None, gr.update(choices=["μ 체 보기"], value="μ 체 보기"), None, |
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gr.update(visible=False), gr.update(visible=False), current_keyword) |
|
|
|
|
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result = keyword_processor.process_search_results(search_results, current_keyword, exclude_zero_volume) |
|
|
|
df_products = result["products_df"] |
|
df_keywords = result["keywords_df"] |
|
category_list = result["categories"] |
|
|
|
if df_keywords.empty: |
|
return (gr.update(value="<p>μΆμΆλ ν€μλκ° μμ΅λλ€. λ€λ₯Έ μ΅μ
μΌλ‘ μλν΄λ³΄μΈμ.</p>"), |
|
gr.update(choices=["μ 체 보기"]), gr.update(choices=["μ 체"]), |
|
df_keywords, gr.update(choices=["μ 체 보기"], value="μ 체 보기"), None, |
|
gr.update(visible=False), gr.update(visible=False), current_keyword) |
|
|
|
|
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html = export_utils.create_table_without_checkboxes(df_keywords) |
|
|
|
|
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volume_range_choices = ["μ 체"] + sorted(df_keywords["κ²μλꡬκ°"].unique().tolist()) |
|
|
|
|
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first_category = category_list[0] if category_list else "μ 체 보기" |
|
|
|
|
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excel_path = create_session_excel_file(df_keywords, session_id) |
|
|
|
|
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return (gr.update(value=html), gr.update(choices=category_list), gr.update(choices=volume_range_choices), |
|
df_keywords, gr.update(choices=category_list, value=first_category), excel_path, |
|
gr.update(visible=True), gr.update(visible=True), current_keyword) |
|
|
|
def create_session_excel_file(df, session_id): |
|
"""μΈμ
λ³ μμ
νμΌ μμ±""" |
|
try: |
|
excel_path = create_session_temp_file(session_id, '.xlsx') |
|
df.to_excel(excel_path, index=False, engine='openpyxl') |
|
logger.info(f"μΈμ
{session_id[:8]}... μμ
νμΌ μμ±: {excel_path}") |
|
return excel_path |
|
except Exception as e: |
|
logger.error(f"μΈμ
λ³ μμ
νμΌ μμ± μ€λ₯: {e}") |
|
return None |
|
|
|
def analyze_with_auto_download(analysis_keywords, selected_category, state_df, session_id): |
|
"""μΉ΄ν
κ³ λ¦¬ μΌμΉ λΆμ μ€ν λ° μλ λ€μ΄λ‘λ (μΈμ
ID μΆκ°)""" |
|
update_session_activity(session_id) |
|
|
|
|
|
if not analysis_keywords or not selected_category: |
|
return "ν€μλμ μΉ΄ν
κ³ λ¦¬λ₯Ό λͺ¨λ μ νν΄μ£ΌμΈμ.", None, gr.update(visible=False) |
|
|
|
|
|
analysis_result = category_analysis.analyze_keywords_by_category(analysis_keywords, selected_category, state_df) |
|
|
|
|
|
excel_path = create_session_excel_file(state_df, session_id) |
|
|
|
|
|
return analysis_result, excel_path, gr.update(visible=True) |
|
|
|
def filter_and_sort_table(df, selected_cat, keyword_sort, total_volume_sort, usage_count_sort, selected_volume_range, exclude_zero_volume, session_id): |
|
"""ν
μ΄λΈ νν°λ§ λ° μ λ ¬ ν¨μ (μΈμ
ID μΆκ°)""" |
|
update_session_activity(session_id) |
|
|
|
if df is None or df.empty: |
|
return "" |
|
|
|
|
|
filtered_df = df.copy() |
|
|
|
|
|
if selected_cat and selected_cat != "μ 체 보기": |
|
cat_name_to_filter = selected_cat.rsplit(" (", 1)[0] |
|
filtered_df = filtered_df[filtered_df["κ΄λ ¨ μΉ΄ν
κ³ λ¦¬"].astype(str).str.contains(cat_name_to_filter, case=False, na=False)] |
|
|
|
def get_filtered_category_display(current_categories_str): |
|
if pd.isna(current_categories_str): |
|
return "" |
|
|
|
categories = str(current_categories_str).split('\n') |
|
matched_categories = [cat for cat in categories if cat_name_to_filter.lower() in cat.lower()] |
|
if matched_categories: |
|
return "\n".join(matched_categories) |
|
|
|
return current_categories_str |
|
|
|
filtered_df['κ΄λ ¨ μΉ΄ν
κ³ λ¦¬'] = filtered_df['κ΄λ ¨ μΉ΄ν
κ³ λ¦¬'].apply(get_filtered_category_display) |
|
|
|
|
|
if selected_volume_range and selected_volume_range != "μ 체": |
|
filtered_df = filtered_df[filtered_df["κ²μλꡬκ°"] == selected_volume_range] |
|
|
|
|
|
if exclude_zero_volume: |
|
filtered_df = filtered_df[filtered_df["μ΄κ²μλ"] > 0] |
|
logger.info(f"μΈμ
{session_id[:8]}... κ²μλ 0 μ μΈ νν° μ μ© - λ¨μ ν€μλ μ: {len(filtered_df)}") |
|
|
|
|
|
if keyword_sort != "μ λ ¬ μμ": |
|
is_ascending = keyword_sort == "μ€λ¦μ°¨μ" |
|
filtered_df = filtered_df.sort_values(by="μ‘°ν© ν€μλ", ascending=is_ascending) |
|
|
|
if total_volume_sort != "μ λ ¬ μμ": |
|
is_ascending = total_volume_sort == "μ€λ¦μ°¨μ" |
|
filtered_df = filtered_df.sort_values(by="μ΄κ²μλ", ascending=is_ascending) |
|
|
|
|
|
if usage_count_sort != "μ λ ¬ μμ": |
|
is_ascending = usage_count_sort == "μ€λ¦μ°¨μ" |
|
filtered_df = filtered_df.sort_values(by="ν€μλ μ¬μ©νμ", ascending=is_ascending) |
|
|
|
|
|
filtered_df = filtered_df.reset_index(drop=True) |
|
|
|
|
|
html = export_utils.create_table_without_checkboxes(filtered_df) |
|
|
|
return html |
|
|
|
def update_category_selection(selected_cat, session_id): |
|
"""μΉ΄ν
κ³ λ¦¬ νν° μ ν μ λΆμν μΉ΄ν
κ³ λ¦¬λ κ°μ κ°μΌλ‘ μ
λ°μ΄νΈ""" |
|
update_session_activity(session_id) |
|
logger.debug(f"μΈμ
{session_id[:8]}... μΉ΄ν
κ³ λ¦¬ μ ν λ³κ²½: {selected_cat}") |
|
return gr.update(value=selected_cat) |
|
|
|
def reset_interface(session_id): |
|
"""μΈν°νμ΄μ€ 리μ
ν¨μ - μΈμ
λ³ λ°μ΄ν° μ΄κΈ°ν""" |
|
update_session_activity(session_id) |
|
|
|
|
|
if session_id in session_temp_files: |
|
for file_path in session_temp_files[session_id]: |
|
try: |
|
if os.path.exists(file_path): |
|
os.remove(file_path) |
|
logger.info(f"μΈμ
{session_id[:8]}... 리μ
μ νμΌ μμ : {file_path}") |
|
except Exception as e: |
|
logger.error(f"μΈμ
{session_id[:8]}... 리μ
μ νμΌ μμ μ€λ₯: {e}") |
|
session_temp_files[session_id] = [] |
|
|
|
return ( |
|
"", |
|
True, |
|
False, |
|
"λ©μΈν€μλ μ μ©", |
|
"", |
|
["μ 체 보기"], |
|
"μ 체 보기", |
|
["μ 체"], |
|
"μ 체", |
|
"μ λ ¬ μμ", |
|
"μ λ ¬ μμ", |
|
None, |
|
["μ 체 보기"], |
|
"μ 체 보기", |
|
"", |
|
"", |
|
None, |
|
gr.update(visible=False), |
|
gr.update(visible=False), |
|
"" |
|
) |
|
|
|
|
|
def search_with_loading(keyword, korean_only, apply_main_keyword, exclude_zero_volume, session_id): |
|
update_session_activity(session_id) |
|
return ( |
|
gr.update(visible=True), |
|
gr.update(visible=False) |
|
) |
|
|
|
def process_search_results(keyword, korean_only, apply_main_keyword, exclude_zero_volume, session_id): |
|
update_session_activity(session_id) |
|
|
|
result = wrapper_modified(keyword, korean_only, apply_main_keyword, exclude_zero_volume, session_id) |
|
|
|
table_html, cat_choices, vol_choices, df, selected_cat, excel, keyword_section_vis, cat_section_vis, new_keyword_state = result |
|
|
|
if not isinstance(df, type(None)) and not df.empty: |
|
empty_placeholder_vis = False |
|
keyword_section_visibility = True |
|
execution_section_visibility = True |
|
else: |
|
empty_placeholder_vis = True |
|
keyword_section_visibility = False |
|
execution_section_visibility = False |
|
|
|
return ( |
|
table_html, cat_choices, vol_choices, df, selected_cat, excel, |
|
gr.update(visible=keyword_section_visibility), |
|
gr.update(visible=cat_section_vis), |
|
gr.update(visible=False), |
|
gr.update(visible=empty_placeholder_vis), |
|
gr.update(visible=execution_section_visibility), |
|
new_keyword_state |
|
) |
|
|
|
def analyze_with_loading(analysis_keywords, selected_category, state_df, session_id): |
|
update_session_activity(session_id) |
|
return gr.update(visible=True) |
|
|
|
def process_analyze_results(analysis_keywords, selected_category, state_df, session_id): |
|
update_session_activity(session_id) |
|
results = analyze_with_auto_download(analysis_keywords, selected_category, state_df, session_id) |
|
return results + (gr.update(visible=False),) |
|
|
|
|
|
def start_session_cleanup_scheduler(): |
|
"""μΈμ
μ 리 μ€μΌμ€λ¬ μμ""" |
|
def cleanup_scheduler(): |
|
while True: |
|
time.sleep(600) |
|
cleanup_old_sessions() |
|
|
|
cleanup_huggingface_temp_folders() |
|
|
|
threading.Thread(target=cleanup_scheduler, daemon=True).start() |
|
|
|
def cleanup_on_startup(): |
|
"""μ ν리μΌμ΄μ
μμ μ μ 체 μ 리""" |
|
logger.info("π§Ή μ ν리μΌμ΄μ
μμ - μ΄κΈ° μ 리 μμ
μμ...") |
|
|
|
|
|
cleanup_huggingface_temp_folders() |
|
|
|
|
|
app_temp_dir = setup_clean_temp_environment() |
|
|
|
|
|
global session_temp_files, session_data |
|
session_temp_files.clear() |
|
session_data.clear() |
|
|
|
logger.info(f"β
μ΄κΈ° μ 리 μμ
μλ£ - μ± μ μ© λλ ν 리: {app_temp_dir}") |
|
|
|
return app_temp_dir |
|
|
|
|
|
def create_app(): |
|
fontawesome_html = """ |
|
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css"> |
|
<link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/orioncactus/pretendard/dist/web/static/pretendard.css"> |
|
<link rel="stylesheet" href="https://fonts.googleapis.com/css2?family=Noto+Sans+KR:wght@300;400;500;700&display=swap"> |
|
""" |
|
|
|
|
|
try: |
|
with open('style.css', 'r', encoding='utf-8') as f: |
|
custom_css = f.read() |
|
except: |
|
custom_css = """ |
|
:root { |
|
--primary-color: #FB7F0D; |
|
--secondary-color: #ff9a8b; |
|
} |
|
.custom-button { |
|
background: linear-gradient(135deg, var(--primary-color), var(--secondary-color)) !important; |
|
color: white !important; |
|
border-radius: 30px !important; |
|
height: 45px !important; |
|
font-size: 16px !important; |
|
font-weight: bold !important; |
|
width: 100% !important; |
|
text-align: center !important; |
|
display: flex !important; |
|
align-items: center !important; |
|
justify-content: center !important; |
|
} |
|
.reset-button { |
|
background: linear-gradient(135deg, #6c757d, #495057) !important; |
|
color: white !important; |
|
border-radius: 30px !important; |
|
height: 45px !important; |
|
font-size: 16px !important; |
|
font-weight: bold !important; |
|
width: 100% !important; |
|
text-align: center !important; |
|
display: flex !important; |
|
align-items: center !important; |
|
justify-content: center !important; |
|
} |
|
.section-title { |
|
border-bottom: 2px solid #FB7F0D; |
|
font-weight: bold; |
|
padding-bottom: 5px; |
|
margin-bottom: 15px; |
|
} |
|
.loading-indicator { |
|
display: flex; |
|
align-items: center; |
|
justify-content: center; |
|
padding: 15px; |
|
background-color: #f8f9fa; |
|
border-radius: 5px; |
|
margin: 10px 0; |
|
border: 1px solid #ddd; |
|
} |
|
.loading-spinner { |
|
border: 4px solid rgba(0, 0, 0, 0.1); |
|
width: 24px; |
|
height: 24px; |
|
border-radius: 50%; |
|
border-left-color: #FB7F0D; |
|
animation: spin 1s linear infinite; |
|
margin-right: 10px; |
|
} |
|
@keyframes spin { |
|
0% { transform: rotate(0deg); } |
|
100% { transform: rotate(360deg); } |
|
} |
|
.progress-bar { |
|
height: 10px; |
|
background-color: #FB7F0D; |
|
border-radius: 5px; |
|
width: 0%; |
|
animation: progressAnim 2s ease-in-out infinite; |
|
} |
|
@keyframes progressAnim { |
|
0% { width: 10%; } |
|
50% { width: 70%; } |
|
100% { width: 10%; } |
|
} |
|
.empty-table { |
|
width: 100%; |
|
border-collapse: collapse; |
|
font-size: 14px; |
|
margin-top: 20px; |
|
} |
|
.empty-table th { |
|
background-color: #FB7F0D; |
|
color: white; |
|
text-align: left; |
|
padding: 12px; |
|
border: 1px solid #ddd; |
|
} |
|
.empty-table td { |
|
padding: 10px; |
|
border: 1px solid #ddd; |
|
text-align: center; |
|
color: #999; |
|
} |
|
.button-container { |
|
margin-top: 20px; |
|
display: flex; |
|
gap: 15px; |
|
} |
|
.execution-section { |
|
margin-top: 20px; |
|
background-color: #f9f9f9; |
|
border-radius: 8px; |
|
padding: 15px; |
|
border: 1px solid #e5e5e5; |
|
} |
|
.session-info { |
|
background-color: #e8f4f8; |
|
padding: 8px 12px; |
|
border-radius: 4px; |
|
font-size: 12px; |
|
color: #0c5460; |
|
margin-bottom: 10px; |
|
text-align: center; |
|
} |
|
""" |
|
|
|
with gr.Blocks(css=custom_css, theme=gr.themes.Default( |
|
primary_hue="orange", |
|
secondary_hue="orange", |
|
font=[gr.themes.GoogleFont("Noto Sans KR"), "ui-sans-serif", "system-ui"] |
|
)) as demo: |
|
gr.HTML(fontawesome_html) |
|
|
|
|
|
session_id = gr.State(get_session_id) |
|
|
|
|
|
keyword_state = gr.State("") |
|
|
|
|
|
with gr.Column(elem_classes="custom-frame fade-in"): |
|
gr.HTML('<div class="section-title"><i class="fas fa-search"></i> κ²μ μ
λ ₯</div>') |
|
|
|
with gr.Row(): |
|
with gr.Column(scale=1): |
|
keyword = gr.Textbox( |
|
label="λ©μΈ ν€μλ", |
|
placeholder="μ: μ€μ§μ΄" |
|
) |
|
with gr.Column(scale=1): |
|
search_btn = gr.Button( |
|
"λ©μΈν€μλ λΆμ", |
|
elem_classes="custom-button" |
|
) |
|
|
|
with gr.Accordion("μ΅μ
μ€μ ", open=False): |
|
with gr.Row(): |
|
with gr.Column(scale=1): |
|
korean_only = gr.Checkbox( |
|
label="νκΈλ§ μΆμΆ", |
|
value=True |
|
) |
|
with gr.Column(scale=1): |
|
exclude_zero_volume = gr.Checkbox( |
|
label="κ²μλ 0 ν€μλ μ μΈ", |
|
value=False |
|
) |
|
|
|
with gr.Row(): |
|
with gr.Column(scale=1): |
|
apply_main_keyword = gr.Radio( |
|
["λ©μΈν€μλ μ μ©", "λ©μΈν€μλ λ―Έμ μ©"], |
|
label="μ‘°ν© λ°©μ", |
|
value="λ©μΈν€μλ μ μ©" |
|
) |
|
with gr.Column(scale=1): |
|
gr.HTML("") |
|
|
|
|
|
with gr.Column(elem_classes="custom-frame fade-in", visible=False) as progress_section: |
|
gr.HTML('<div class="section-title"><i class="fas fa-spinner"></i> λΆμ μ§ν μν</div>') |
|
progress_html = gr.HTML(""" |
|
<div style="padding: 15px; background-color: #f9f9f9; border-radius: 5px; margin: 10px 0; border: 1px solid #ddd;"> |
|
<div style="margin-bottom: 10px; display: flex; align-items: center;"> |
|
<i class="fas fa-spinner fa-spin" style="color: #FB7F0D; margin-right: 10px;"></i> |
|
<span>ν€μλ λ°μ΄ν°λ₯Ό λΆμμ€μ
λλ€. μ μλ§ κΈ°λ€λ €μ£ΌμΈμ...</span> |
|
</div> |
|
<div style="background-color: #e9ecef; height: 10px; border-radius: 5px; overflow: hidden;"> |
|
<div class="progress-bar"></div> |
|
</div> |
|
</div> |
|
""") |
|
|
|
|
|
with gr.Column(elem_classes="custom-frame fade-in") as main_keyword_section: |
|
gr.HTML('<div class="section-title"><i class="fas fa-table"></i> λ©μΈν€μλ λΆμ κ²°κ³Ό</div>') |
|
|
|
empty_table_html = gr.HTML(""" |
|
<table class="empty-table"> |
|
<thead> |
|
<tr> |
|
<th>μλ²</th> |
|
<th>μ‘°ν© ν€μλ</th> |
|
<th>PCκ²μλ</th> |
|
<th>λͺ¨λ°μΌκ²μλ</th> |
|
<th>μ΄κ²μλ</th> |
|
<th>κ²μλꡬκ°</th> |
|
<th>ν€μλ μ¬μ©μμμ</th> |
|
<th>ν€μλ μ¬μ©νμ</th> |
|
<th>μν λ±λ‘ μΉ΄ν
κ³ λ¦¬</th> |
|
</tr> |
|
</thead> |
|
<tbody> |
|
<tr> |
|
<td colspan="9" style="padding: 30px; text-align: center;"> |
|
κ²μμ μ€ννλ©΄ μ¬κΈ°μ κ²°κ³Όκ° νμλ©λλ€ |
|
</td> |
|
</tr> |
|
</tbody> |
|
</table> |
|
""") |
|
|
|
with gr.Column(visible=False) as keyword_analysis_section: |
|
with gr.Row(): |
|
with gr.Column(scale=1): |
|
category_filter = gr.Dropdown( |
|
choices=["μ 체 보기"], |
|
label="μΉ΄ν
κ³ λ¦¬ νν°", |
|
value="μ 체 보기", |
|
interactive=True |
|
) |
|
with gr.Column(scale=1): |
|
total_volume_sort = gr.Dropdown( |
|
choices=["μ λ ¬ μμ", "μ€λ¦μ°¨μ", "λ΄λ¦Όμ°¨μ"], |
|
label="μ΄κ²μλ μ λ ¬", |
|
value="μ λ ¬ μμ", |
|
interactive=True |
|
) |
|
|
|
with gr.Row(): |
|
with gr.Column(scale=1): |
|
search_volume_filter = gr.Dropdown( |
|
choices=["μ 체"], |
|
label="κ²μλ κ΅¬κ° νν°", |
|
value="μ 체", |
|
interactive=True |
|
) |
|
with gr.Column(scale=1): |
|
usage_count_sort = gr.Dropdown( |
|
choices=["μ λ ¬ μμ", "μ€λ¦μ°¨μ", "λ΄λ¦Όμ°¨μ"], |
|
label="ν€μλ μ¬μ©νμ μ λ ¬", |
|
value="μ λ ¬ μμ", |
|
interactive=True |
|
) |
|
|
|
gr.HTML("<div class='data-container' id='table_container'></div>") |
|
table_output = gr.HTML(elem_classes="fade-in") |
|
|
|
|
|
with gr.Column(elem_classes="custom-frame fade-in", visible=False) as category_analysis_section: |
|
gr.HTML('<div class="section-title"><i class="fas fa-chart-bar"></i> ν€μλ λΆμ</div>') |
|
|
|
with gr.Row(): |
|
with gr.Column(scale=1): |
|
analysis_keywords = gr.Textbox( |
|
label="ν€μλ μ
λ ₯ (μ΅λ 20κ°, μΌν λλ μν°λ‘ ꡬλΆ)", |
|
placeholder="μ: μ€μ§μ΄λ³Άμ, μ€μ§μ΄ μμ§, μ€μ§μ΄ μ리...", |
|
lines=5 |
|
) |
|
|
|
with gr.Column(scale=1): |
|
selected_category = gr.Dropdown( |
|
label="λΆμν μΉ΄ν
κ³ λ¦¬(λΆμ μ λ°λμ μ νν΄μ£ΌμΈμ)", |
|
choices=["μ 체 보기"], |
|
value="μ 체 보기", |
|
interactive=True |
|
) |
|
|
|
|
|
with gr.Column(elem_classes="execution-section", visible=False) as execution_section: |
|
gr.HTML('<div class="section-title"><i class="fas fa-play-circle"></i> μ€ν</div>') |
|
with gr.Row(): |
|
with gr.Column(scale=1): |
|
analyze_btn = gr.Button( |
|
"μΉ΄ν
κ³ λ¦¬ μΌμΉ λΆμ", |
|
elem_classes=["execution-button", "primary-button"] |
|
) |
|
with gr.Column(scale=1): |
|
reset_btn = gr.Button( |
|
"λͺ¨λ μ
λ ₯ μ΄κΈ°ν", |
|
elem_classes=["execution-button", "secondary-button"] |
|
) |
|
|
|
|
|
with gr.Column(elem_classes="custom-frame fade-in", visible=False) as analysis_output_section: |
|
gr.HTML('<div class="section-title"><i class="fas fa-list-ul"></i> λΆμ κ²°κ³Ό μμ½</div>') |
|
|
|
analysis_result = gr.HTML(elem_classes="fade-in") |
|
|
|
with gr.Row(): |
|
download_output = gr.File( |
|
label="ν€μλ λͺ©λ‘ λ€μ΄λ‘λ", |
|
visible=True |
|
) |
|
|
|
|
|
state_df = gr.State() |
|
|
|
|
|
search_btn.click( |
|
fn=search_with_loading, |
|
inputs=[keyword, korean_only, apply_main_keyword, exclude_zero_volume, session_id], |
|
outputs=[progress_section, empty_table_html] |
|
).then( |
|
fn=process_search_results, |
|
inputs=[keyword, korean_only, apply_main_keyword, exclude_zero_volume, session_id], |
|
outputs=[ |
|
table_output, category_filter, search_volume_filter, |
|
state_df, selected_category, download_output, |
|
keyword_analysis_section, category_analysis_section, |
|
progress_section, empty_table_html, execution_section, |
|
keyword_state |
|
] |
|
) |
|
|
|
|
|
category_filter.change( |
|
fn=filter_and_sort_table, |
|
inputs=[ |
|
state_df, category_filter, gr.Textbox(value="μ λ ¬ μμ", visible=False), |
|
total_volume_sort, usage_count_sort, |
|
search_volume_filter, exclude_zero_volume, session_id |
|
], |
|
outputs=[table_output] |
|
) |
|
|
|
category_filter.change( |
|
fn=update_category_selection, |
|
inputs=[category_filter, session_id], |
|
outputs=[selected_category] |
|
) |
|
|
|
total_volume_sort.change( |
|
fn=filter_and_sort_table, |
|
inputs=[ |
|
state_df, category_filter, gr.Textbox(value="μ λ ¬ μμ", visible=False), |
|
total_volume_sort, usage_count_sort, |
|
search_volume_filter, exclude_zero_volume, session_id |
|
], |
|
outputs=[table_output] |
|
) |
|
|
|
usage_count_sort.change( |
|
fn=filter_and_sort_table, |
|
inputs=[ |
|
state_df, category_filter, gr.Textbox(value="μ λ ¬ μμ", visible=False), |
|
total_volume_sort, usage_count_sort, |
|
search_volume_filter, exclude_zero_volume, session_id |
|
], |
|
outputs=[table_output] |
|
) |
|
|
|
search_volume_filter.change( |
|
fn=filter_and_sort_table, |
|
inputs=[ |
|
state_df, category_filter, gr.Textbox(value="μ λ ¬ μμ", visible=False), |
|
total_volume_sort, usage_count_sort, |
|
search_volume_filter, exclude_zero_volume, session_id |
|
], |
|
outputs=[table_output] |
|
) |
|
|
|
exclude_zero_volume.change( |
|
fn=filter_and_sort_table, |
|
inputs=[ |
|
state_df, category_filter, gr.Textbox(value="μ λ ¬ μμ", visible=False), |
|
total_volume_sort, usage_count_sort, |
|
search_volume_filter, exclude_zero_volume, session_id |
|
], |
|
outputs=[table_output] |
|
) |
|
|
|
|
|
analyze_btn.click( |
|
fn=analyze_with_loading, |
|
inputs=[analysis_keywords, selected_category, state_df, session_id], |
|
outputs=[progress_section] |
|
).then( |
|
fn=process_analyze_results, |
|
inputs=[analysis_keywords, selected_category, state_df, session_id], |
|
outputs=[analysis_result, download_output, analysis_output_section, progress_section] |
|
) |
|
|
|
|
|
reset_btn.click( |
|
fn=reset_interface, |
|
inputs=[session_id], |
|
outputs=[ |
|
keyword, korean_only, exclude_zero_volume, apply_main_keyword, |
|
table_output, category_filter, category_filter, |
|
search_volume_filter, search_volume_filter, |
|
total_volume_sort, usage_count_sort, |
|
state_df, selected_category, selected_category, |
|
analysis_keywords, analysis_result, download_output, |
|
keyword_analysis_section, analysis_output_section, |
|
keyword_state |
|
] |
|
) |
|
|
|
return demo |
|
|
|
if __name__ == "__main__": |
|
|
|
logger.info("π λ©μΈν€μλ λΆμ μ ν리μΌμ΄μ
μμ...") |
|
|
|
|
|
app_temp_dir = cleanup_on_startup() |
|
|
|
|
|
start_session_cleanup_scheduler() |
|
|
|
|
|
try: |
|
api_utils.initialize_api_configs() |
|
except Exception as e: |
|
logger.warning(f"API μ€μ μ΄κΈ°ν μ€ μ€λ₯ (κ³μ μ§ν): {e}") |
|
|
|
|
|
try: |
|
gemini_model = text_utils.get_gemini_model() |
|
except Exception as e: |
|
logger.warning(f"Gemini λͺ¨λΈ μ΄κΈ°ν μ€ μ€λ₯ (κ³μ μ§ν): {e}") |
|
|
|
logger.info("===== λ©ν°μ μ λ©μΈν€μλ λΆμ Application Startup at %s =====", time.strftime("%Y-%m-%d %H:%M:%S")) |
|
logger.info(f"π μμ νμΌ μ μ₯ μμΉ: {app_temp_dir}") |
|
|
|
|
|
try: |
|
app = create_app() |
|
app.launch( |
|
share=False, |
|
server_name="0.0.0.0", |
|
server_port=7860, |
|
max_threads=40, |
|
auth=None, |
|
show_error=True, |
|
quiet=False, |
|
favicon_path=None, |
|
ssl_verify=False |
|
) |
|
except Exception as e: |
|
logger.error(f"μ ν리μΌμ΄μ
μ€ν μ€ν¨: {e}") |
|
raise |
|
finally: |
|
|
|
logger.info("π§Ή μ ν리μΌμ΄μ
μ’
λ£ - μ΅μ’
μ 리 μμ
...") |
|
try: |
|
cleanup_huggingface_temp_folders() |
|
if os.path.exists(app_temp_dir): |
|
shutil.rmtree(app_temp_dir, ignore_errors=True) |
|
logger.info("β
μ΅μ’
μ 리 μλ£") |
|
except Exception as e: |
|
logger.error(f"μ΅μ’
μ 리 μ€ μ€λ₯: {e}") |