import json import os import signal from concurrent.futures import ThreadPoolExecutor, as_completed from threading import Lock, Event import sys import datetime sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) # 添加项目根目录到 sys.path from rich.progress import Progress # 替换为 rich 进度条 from src.common.logger import get_logger # from src.chat.knowledge.lpmmconfig import global_config from src.chat.knowledge.ie_process import info_extract_from_str from src.chat.knowledge.open_ie import OpenIE from rich.progress import ( BarColumn, TimeElapsedColumn, TimeRemainingColumn, TaskProgressColumn, MofNCompleteColumn, SpinnerColumn, TextColumn, ) from raw_data_preprocessor import RAW_DATA_PATH, load_raw_data from src.config.config import global_config, model_config from src.llm_models.utils_model import LLMRequest logger = get_logger("LPMM知识库-信息提取") ROOT_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), "..")) TEMP_DIR = os.path.join(ROOT_PATH, "temp") # IMPORTED_DATA_PATH = os.path.join(ROOT_PATH, "data", "imported_lpmm_data") OPENIE_OUTPUT_DIR = os.path.join(ROOT_PATH, "data", "openie") def ensure_dirs(): """确保临时目录和输出目录存在""" if not os.path.exists(TEMP_DIR): os.makedirs(TEMP_DIR) logger.info(f"已创建临时目录: {TEMP_DIR}") if not os.path.exists(OPENIE_OUTPUT_DIR): os.makedirs(OPENIE_OUTPUT_DIR) logger.info(f"已创建输出目录: {OPENIE_OUTPUT_DIR}") if not os.path.exists(RAW_DATA_PATH): os.makedirs(RAW_DATA_PATH) logger.info(f"已创建原始数据目录: {RAW_DATA_PATH}") # 创建一个线程安全的锁，用于保护文件操作和共享数据 file_lock = Lock() open_ie_doc_lock = Lock() # 创建一个事件标志，用于控制程序终止 shutdown_event = Event() lpmm_entity_extract_llm = LLMRequest( model_set=model_config.model_task_config.lpmm_entity_extract, request_type="lpmm.entity_extract" ) lpmm_rdf_build_llm = LLMRequest( model_set=model_config.model_task_config.lpmm_rdf_build, request_type="lpmm.rdf_build" ) def process_single_text(pg_hash, raw_data): """处理单个文本的函数，用于线程池""" temp_file_path = f"{TEMP_DIR}/{pg_hash}.json" # 使用文件锁检查和读取缓存文件 with file_lock: if os.path.exists(temp_file_path): try: # 存在对应的提取结果 logger.info(f"找到缓存的提取结果：{pg_hash}") with open(temp_file_path, "r", encoding="utf-8") as f: return json.load(f), None except json.JSONDecodeError: # 如果JSON文件损坏，删除它并重新处理 logger.warning(f"缓存文件损坏，重新处理：{pg_hash}") os.remove(temp_file_path) entity_list, rdf_triple_list = info_extract_from_str( lpmm_entity_extract_llm, lpmm_rdf_build_llm, raw_data, ) if entity_list is None or rdf_triple_list is None: return None, pg_hash doc_item = { "idx": pg_hash, "passage": raw_data, "extracted_entities": entity_list, "extracted_triples": rdf_triple_list, } # 保存临时提取结果 with file_lock: try: with open(temp_file_path, "w", encoding="utf-8") as f: json.dump(doc_item, f, ensure_ascii=False, indent=4) except Exception as e: logger.error(f"保存缓存文件失败：{pg_hash}, 错误：{e}") # 如果保存失败，确保不会留下损坏的文件 if os.path.exists(temp_file_path): os.remove(temp_file_path) sys.exit(0) return None, pg_hash return doc_item, None def signal_handler(_signum, _frame): """处理Ctrl+C信号""" logger.info("\n接收到中断信号，正在优雅地关闭程序...") sys.exit(0) def main(): # sourcery skip: comprehension-to-generator, extract-method # 设置信号处理器 signal.signal(signal.SIGINT, signal_handler) ensure_dirs() # 确保目录存在 # 新增用户确认提示 print("=== 重要操作确认，请认真阅读以下内容哦 ===") print("实体提取操作将会花费较多api余额和时间，建议在空闲时段执行。") print("举例：600万字全剧情，提取选用deepseek v3 0324，消耗约40元，约3小时。") print("建议使用硅基流动的非Pro模型") print("或者使用可以用赠金抵扣的Pro模型") print("请确保账户余额充足，并且在执行前确认无误。") confirm = input("确认继续执行？(y/n): ").strip().lower() if confirm != "y": logger.info("用户取消操作") print("操作已取消") sys.exit(1) print("\n" + "=" * 40 + "\n") ensure_dirs() # 确保目录存在 logger.info("--------进行信息提取--------\n") # 加载原始数据 logger.info("正在加载原始数据") all_sha256_list, all_raw_datas = load_raw_data() failed_sha256 = [] open_ie_doc = [] workers = global_config.lpmm_knowledge.info_extraction_workers with ThreadPoolExecutor(max_workers=workers) as executor: future_to_hash = { executor.submit(process_single_text, pg_hash, raw_data): pg_hash for pg_hash, raw_data in zip(all_sha256_list, all_raw_datas, strict=False) } with Progress( SpinnerColumn(), TextColumn("[progress.description]{task.description}"), BarColumn(), TaskProgressColumn(), MofNCompleteColumn(), "•", TimeElapsedColumn(), "<", TimeRemainingColumn(), transient=False, ) as progress: task = progress.add_task("正在进行提取：", total=len(future_to_hash)) try: for future in as_completed(future_to_hash): if shutdown_event.is_set(): for f in future_to_hash: if not f.done(): f.cancel() break doc_item, failed_hash = future.result() if failed_hash: failed_sha256.append(failed_hash) logger.error(f"提取失败：{failed_hash}") elif doc_item: with open_ie_doc_lock: open_ie_doc.append(doc_item) progress.update(task, advance=1) except KeyboardInterrupt: logger.info("\n接收到中断信号，正在优雅地关闭程序...") shutdown_event.set() for f in future_to_hash: if not f.done(): f.cancel() # 合并所有文件的提取结果并保存 if open_ie_doc: sum_phrase_chars = sum([len(e) for chunk in open_ie_doc for e in chunk["extracted_entities"]]) sum_phrase_words = sum([len(e.split()) for chunk in open_ie_doc for e in chunk["extracted_entities"]]) num_phrases = sum([len(chunk["extracted_entities"]) for chunk in open_ie_doc]) openie_obj = OpenIE( open_ie_doc, round(sum_phrase_chars / num_phrases, 4) if num_phrases else 0, round(sum_phrase_words / num_phrases, 4) if num_phrases else 0, ) # 输出文件名格式：MM-DD-HH-ss-openie.json now = datetime.datetime.now() filename = now.strftime("%m-%d-%H-%S-openie.json") output_path = os.path.join(OPENIE_OUTPUT_DIR, filename) with open(output_path, "w", encoding="utf-8") as f: json.dump( openie_obj.to_dict() if hasattr(openie_obj, "to_dict") else openie_obj.__dict__, f, ensure_ascii=False, indent=4, ) logger.info(f"信息提取结果已保存到: {output_path}") else: logger.warning("没有可保存的信息提取结果") logger.info("--------信息提取完成--------") logger.info(f"提取失败的文段SHA256：{failed_sha256}") if __name__ == "__main__": main()