3bef6f4bab
通过以下改动修复嵌入生成过程中的事件循环相关问题： - 在 EmbeddingStore._get_embedding 中，改为同步创建-使用-销毁的新事件循环模式，彻底避免嵌套事件循环问题 - 调整批量嵌入 _get_embeddings_batch_threaded，确保每个线程使用独立、短生命周期的事件循环 - 新增 force_new 参数，LLM 请求嵌入任务时强制创建新的客户端实例，减少跨循环对象复用 - 在 OpenAI 客户端的 embedding 调用处补充详细日志，方便排查网络连接异常 - get_embedding() 每次都重建 LLMRequest，降低实例在多个事件循环中穿梭的概率 此次改动虽然以同步风格“硬掰”异步接口，但对现有接口零破坏，确保了向量数据库及相关知识检索功能的稳定性。(还有就是把的脚本文件夹移回来了)
75 lines
2.3 KiB
Python
75 lines
2.3 KiB
Python
import os
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from pathlib import Path
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import sys # 新增系统模块导入
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from src.chat.knowledge.utils.hash import get_sha256
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sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
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from src.common.logger import get_logger
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logger = get_logger("lpmm")
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ROOT_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
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RAW_DATA_PATH = os.path.join(ROOT_PATH, "data/lpmm_raw_data")
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# IMPORTED_DATA_PATH = os.path.join(ROOT_PATH, "data/imported_lpmm_data")
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def _process_text_file(file_path):
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"""处理单个文本文件，返回段落列表"""
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with open(file_path, "r", encoding="utf-8") as f:
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raw = f.read()
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paragraphs = []
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paragraph = ""
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for line in raw.split("\n"):
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if line.strip() == "":
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if paragraph != "":
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paragraphs.append(paragraph.strip())
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paragraph = ""
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else:
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paragraph += line + "\n"
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if paragraph != "":
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paragraphs.append(paragraph.strip())
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return paragraphs
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def _process_multi_files() -> list:
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raw_files = list(Path(RAW_DATA_PATH).glob("*.txt"))
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if not raw_files:
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logger.warning("警告: data/lpmm_raw_data 中没有找到任何 .txt 文件")
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sys.exit(1)
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# 处理所有文件
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all_paragraphs = []
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for file in raw_files:
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logger.info(f"正在处理文件: {file.name}")
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paragraphs = _process_text_file(file)
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all_paragraphs.extend(paragraphs)
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return all_paragraphs
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def load_raw_data() -> tuple[list[str], list[str]]:
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"""加载原始数据文件
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读取原始数据文件，将原始数据加载到内存中
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Args:
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path: 可选，指定要读取的json文件绝对路径
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Returns:
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- raw_data: 原始数据列表
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- sha256_list: 原始数据的SHA256集合
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"""
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raw_data = _process_multi_files()
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sha256_list = []
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sha256_set = set()
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for item in raw_data:
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if not isinstance(item, str):
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logger.warning(f"数据类型错误：{item}")
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continue
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pg_hash = get_sha256(item)
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if pg_hash in sha256_set:
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logger.warning(f"重复数据：{item}")
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continue
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sha256_set.add(pg_hash)
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sha256_list.append(pg_hash)
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raw_data.append(item)
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logger.info(f"共读取到{len(raw_data)}条数据")
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return sha256_list, raw_data |