import gradio as gr import jieba import jieba.analyse import aiohttp import asyncio import ssl from functools import lru_cache # SSL context setup ssl_context = ssl.create_default_context() ssl_context.check_hostname = False ssl_context.verify_mode = ssl.CERT_NONE area_data = { '香港': { '中西區': ["西環", "堅尼地城", "石塘咀", "西營盤", "上環", "中環", "金鐘", "西半山", "中半山", "半山", "山頂"], '灣仔': ["灣仔", "銅鑼灣", "跑馬地", "大坑", "掃桿埔", "渣甸山"], '東區': ["天后", "寶馬山", "北角", "鰂魚涌", "西灣河", "筲箕灣", "柴灣", "小西灣"], '南區': ["薄扶林", "香港仔", "鴨脷洲", "黃竹坑", "壽臣山", "淺水灣", "舂磡角", "赤柱", "大潭", "石澳", "田灣"] }, '九龍': { '油尖旺': ["尖沙咀", "油麻地", "西九龍", "京士柏", "旺角", "大角咀", "佐敦", "太子"], '深水埗': ["美孚", "荔枝角", "長沙灣", "深水埗", "石硤尾", "又一村", "大窩坪", "昂船洲"], '九龍城': ["紅磡", "土瓜灣", "馬頭角", "馬頭圍", "啟德", "九龍城", "何文田", "九龍塘", "筆架山"], '黃大仙': ["新蒲崗", "黃大仙", "東頭", "橫頭磡", "樂富", "鑽石山", "慈雲山", "牛池灣"], '觀塘': ["坪石", "九龍灣", "牛頭角", "佐敦谷", "觀塘", "秀茂坪", "藍田", "油塘", "鯉魚門"] }, '新界': { '葵青': ["葵涌", "青衣", "葵芳"], '荃灣': ["荃灣", "梨木樹", "汀九", "深井", "青龍頭", "馬灣", "欣澳"], '屯門': ["大欖涌", "掃管笏", "屯門", "藍地"], '元朗': ["洪水橋", "廈村", "流浮山", "天水圍", "元朗", "新田", "落馬洲", "錦田", "石崗", "八鄉"], '北區': ["粉嶺", "聯和墟", "上水", "石湖墟", "沙頭角", "鹿頸", "烏蛟騰"], '大埔': ["大埔墟", "大埔", "大埔滘", "大尾篤", "船灣", "樟木頭", "企嶺下", "太和"], '沙田': ["大圍", "沙田", "火炭", "馬料水", "烏溪沙", "馬鞍山"], '西貢': ["清水灣", "西貢", "大網仔", "將軍澳", "坑口", "調景嶺", "馬游塘"], '離島': ["長洲", "坪洲", "大嶼山", "東涌", "南丫島"] } } @lru_cache(maxsize=None) def load_user_dict_terms(): user_dict_terms = set() dictionaries = [ 'flag/RVT_AddressCh.txt', 'flag/RVT_AddressEn.txt', 'flag/RVT_Area.txt', 'flag/RVT_BuildingCh.txt', 'flag/RVT_BuildingEn.txt', 'flag/ChiVillage.txt', 'flag/ChiEstate.txt', 'flag/ChiStreet.txt', 'flag/ChiBuilding.txt' ] for file_path in dictionaries: try: with open(file_path, 'r', encoding='utf-8') as f: user_dict_terms.update(line.strip().split()[0] for line in f) except FileNotFoundError: print(f'File not found: {file_path}') except Exception as e: print(f'Error reading file {file_path}: {e}') return user_dict_terms def setup_jieba_dictionaries(): dictionaries = [ 'flag/RVT_AddressCh.txt', 'flag/RVT_AddressEn.txt', 'flag/RVT_Area.txt', 'flag/RVT_BuildingCh.txt', 'flag/RVT_BuildingEn.txt', 'flag/ChiVillage.txt', 'flag/ChiEstate.txt', 'flag/ChiStreet.txt', 'flag/ChiBuilding.txt' ] for file_path in dictionaries: jieba.load_userdict(file_path) def process_text(text): setup_jieba_dictionaries() user_dict_terms = load_user_dict_terms() lines = text.splitlines() results = [] for line in lines: line = line.strip() keywords = jieba.analyse.textrank(line, topK=20, withWeight=False, allowPOS=('ns', 'n', 'vn', 'v')) keyword_text = ' '.join(keyword for keyword in keywords if keyword in user_dict_terms) results.append(keyword_text) return results def reformat_text(text): return [line.strip() for line in text.splitlines() if line.strip()] def process_text_only(text, reformat): extracted_keywords = process_text(text) if reformat: extracted_keywords = reformat_text('\n'.join(extracted_keywords)) return '\n'.join(extracted_keywords) async def lookup_address(query, language='zh-Hant'): url = 'https://www.als.gov.hk/lookup' headers = {'Accept': 'application/json', 'Accept-Language': language} payload = {'q': query} async with aiohttp.ClientSession() as session: try: async with session.post(url, headers=headers, data=payload, ssl=ssl_context) as response: if response.status == 200: return await response.json() else: print(f'Error fetching data: Status Code {response.status}') return {'error': f'Error fetching data: Status Code {response.status}'} except aiohttp.ClientError as e: print(f'Client Error: {e}') return {'error': f'Client Error: {e}'} except Exception as e: print(f'General Error: {e}') return {'error': f'General Error: {e}'} async def get_address_lookup_results(keywords): results = [] tasks = [lookup_address(keyword.strip()) for keyword in keywords if keyword.strip() and is_valid_for_lookup(keyword.strip())] lookup_results = await asyncio.gather(*tasks) for keyword, lookup_result in zip(keywords, lookup_results): if 'SuggestedAddress' in lookup_result and isinstance(lookup_result['SuggestedAddress'], list): first_match = lookup_result['SuggestedAddress'][0] result = {'Keyword': keyword} if first_match: premises_address = first_match['Address']['PremisesAddress'] raw_address = premises_address.get('ChiPremisesAddress', {}) matched_building = raw_address.get('BuildingName', 'No Building Name') if matched_building != 'No Building Name': result['Full Address'] = matched_building geo_address = premises_address.get('GeoAddress') if geo_address and geo_address != 'N/A': result['Geo Address'] = geo_address geo_info = premises_address.get('GeospatialInformation', {}) latitude = geo_info.get('Latitude') longitude = geo_info.get('Longitude') if latitude and latitude != 'N/A': result['Latitude'] = latitude if longitude and longitude != 'N/A': result['Longitude'] = longitude if len(result) > 1: # Only add if there's more than just the Keyword results.append(result) return results def is_valid_for_lookup(keyword): return not any(keyword in districts.keys() or keyword in subdistrict for districts in area_data.values() for subdistrict in districts.values()) async def gradio_function(text, reformat, perform_lookup): extracted_keywords = process_text_only(text, reformat) keywords_list = extracted_keywords.splitlines() address_results = [] if perform_lookup: address_results = await get_address_lookup_results(keywords_list) return extracted_keywords, address_results def gradio_interface(text, reformat, perform_lookup): return asyncio.run(gradio_function(text, reformat, perform_lookup)) interface = gr.Interface( fn=gradio_interface, inputs=[ gr.Textbox(lines=20, placeholder="Paste text here, each line will be processed separately..."), gr.Checkbox(label="Reformat text (remove empty lines)"), gr.Checkbox(label="Perform Address Lookup") ], outputs=[ gr.Textbox(label="Extracted Address Keywords"), gr.JSON(label="Address Lookup Results") ], title="Address Extraction and Lookup with Natural Language Processing", description="Extract address keywords using NLP and optionally perform address lookup using ALS." ) interface.launch()