db copy.py 63 KB

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  1. from rag.vector_db.milvus_vector import HybridRetriever
  2. from response_info import generate_message, generate_response
  3. from utils.get_logger import setup_logger
  4. from datetime import datetime
  5. from uuid import uuid1
  6. import mysql.connector
  7. from mysql.connector import pooling, Error, errors
  8. import threading
  9. from concurrent.futures import ThreadPoolExecutor, TimeoutError
  10. from config import milvus_uri, mysql_config
  11. logger = setup_logger(__name__)
  12. # uri = "http://localhost:19530"
  13. # if 'POOL' not in globals():
  14. # try:
  15. # POOL = pooling.MySQLConnectionPool(
  16. # pool_name="mysql_pool",
  17. # pool_size=10,
  18. # **mysql_config
  19. # )
  20. # logger.info("MySQL 连接池初始化成功")
  21. # except Error as e:
  22. # logger.info(f"初始化 MySQL 连接池失败: {e}")
  23. # POOL = None
  24. class MilvusOperate:
  25. def __init__(self, collection_name: str = "default", embedding_name:str = "e5"):
  26. self.collection = collection_name
  27. self.hybrid_retriever = HybridRetriever(uri=milvus_uri, embedding_name=embedding_name, collection_name=collection_name)
  28. self.mysql_client = MysqlOperate()
  29. def _has_collection(self):
  30. is_collection = self.hybrid_retriever.has_collection()
  31. return is_collection
  32. def _create_collection(self):
  33. if self._has_collection():
  34. resp = {"code": 400, "message": "数据库已存在"}
  35. else:
  36. create_result = self.hybrid_retriever.build_collection()
  37. resp = generate_message(create_result)
  38. return resp
  39. def _delete_collection(self):
  40. delete_result = self.hybrid_retriever.delete_collection(self.collection)
  41. resp = generate_message(delete_result)
  42. return resp
  43. def _put_by_id(self, slice_json):
  44. slice_id = slice_json.get("slice_id", None)
  45. slice_text = slice_json.get("slice_text", None)
  46. update_result, chunk_len = self.hybrid_retriever.update_data(chunk_id=slice_id, chunk=slice_text)
  47. if update_result.endswith("success"):
  48. # 如果成功,更新mysql中知识库总长度和文档长度
  49. update_json = {}
  50. update_json["knowledge_id"] = slice_json.get("knowledge_id")
  51. update_json["doc_id"] = slice_json.get("document_id")
  52. update_json["chunk_len"] = chunk_len
  53. update_json["operate"] = "update"
  54. update_json["chunk_id"] = slice_id
  55. update_json["chunk_text"] = slice_text
  56. update_flag, update_str = self.mysql_client.update_total_doc_len(update_json)
  57. else:
  58. update_flag = False
  59. if not update_flag:
  60. update_result = "update_error"
  61. resp = generate_message(update_result)
  62. return resp
  63. def _insert_slice(self, slice_json):
  64. slice_id = str(uuid1())
  65. knowledge_id = slice_json.get("knowledge_id")
  66. doc_id = slice_json.get("document_id")
  67. slice_text = slice_json.get("slice_text", None)
  68. doc_name = slice_json.get("doc_name")
  69. chunk_len = len(slice_text)
  70. metadata = {
  71. "content": slice_text,
  72. "doc_id": doc_id,
  73. "chunk_id": slice_id,
  74. "metadata": {"source": doc_name, "chunk_len": chunk_len},
  75. "Chapter": slice_json.get("Chapter",""),
  76. "Father_Chapter": slice_json.get("Father_Chapter",""),
  77. }
  78. insert_flag, insert_str = self.hybrid_retriever.insert_data(slice_text, metadata)
  79. if insert_flag:
  80. # 如果成功,更新mysql中知识库总长度和文档长度
  81. update_json = {}
  82. update_json["knowledge_id"] = slice_json.get("knowledge_id")
  83. update_json["doc_id"] = slice_json.get("document_id")
  84. update_json["chunk_len"] = chunk_len
  85. update_json["operate"] = "insert"
  86. update_json["chunk_id"] = slice_id
  87. update_json["chunk_text"] = slice_text
  88. update_json["slice_index"] = slice_json.get("slice_index")
  89. update_flag, update_str = self.mysql_client.update_total_doc_len(update_json)
  90. else:
  91. logger.error(f"插入向量库出错:{insert_str}")
  92. update_flag = False
  93. update_str = "向量库写入出错"
  94. # pass
  95. if not update_flag:
  96. logger.error(f"新增切片中mysql数据库出错:{update_str}")
  97. # insert_result = "insert_error"
  98. success = "insert_error"
  99. else:
  100. # insert_result = "insert_success"
  101. success = "insert_success"
  102. # resp = generate_message(insert_result)
  103. resp = {"status": success, "slice_id":slice_id}
  104. return resp
  105. def _delete_by_chunk_id(self, chunk_id, knowledge_id, document_id):
  106. logger.info(f"删除的切片id:{chunk_id}")
  107. delete_result, delete_chunk_len = self.hybrid_retriever.delete_by_chunk_id(chunk_id=chunk_id)
  108. if delete_result.endswith("success"):
  109. chunk_len = delete_chunk_len[0]
  110. update_json = {
  111. "knowledge_id": knowledge_id,
  112. "doc_id": document_id,
  113. "chunk_len": -chunk_len,
  114. "operate": "delete",
  115. "chunk_id": chunk_id
  116. }
  117. update_flag, update_str = self.mysql_client.update_total_doc_len(update_json)
  118. else:
  119. logger.error("根据chunk id删除向量库失败")
  120. update_flag = False
  121. update_str = "根据chunk id删除失败"
  122. if not update_flag:
  123. logger.error(update_str)
  124. delete_result = "delete_error"
  125. resp = generate_message(delete_result)
  126. return resp
  127. def _delete_by_doc_id(self, doc_id: str = None):
  128. logger.info(f"删除数据的id:{doc_id}")
  129. delete_result = self.hybrid_retriever.delete_by_doc_id(doc_id=doc_id)
  130. resp = generate_message(delete_result)
  131. return resp
  132. def _search_by_chunk_id(self, chunk_id):
  133. if self._has_collection():
  134. query_result = self.hybrid_retriever.query_chunk_id(chunk_id=chunk_id)
  135. else:
  136. query_result = []
  137. logger.info(f"根据切片查询到的信息:{query_result}")
  138. resp = generate_response(query_result)
  139. return resp
  140. def _search_by_chunk_id_list(self, chunk_id_list):
  141. if self._has_collection():
  142. query_result = self.hybrid_retriever.query_chunk_id_list(chunk_id_list)
  143. else:
  144. query_result = []
  145. logger.info(f"召回的切片列表查询切片信息:{query_result}")
  146. chunk_content_list = []
  147. for chunk_dict in query_result:
  148. chunk_content = chunk_dict.get("content")
  149. chunk_content_list.append(chunk_content)
  150. return chunk_content_list
  151. def _search_by_key_word(self, search_json):
  152. if self._has_collection():
  153. doc_id = search_json.get("document_id", None)
  154. text = search_json.get("text", None)
  155. page_num = search_json.get("pageNum", 1)
  156. page_size = search_json.get("pageSize", 10)
  157. page_num = search_json.get("pageNum") # 根据传过来的id处理对应知识库
  158. query_result = self.hybrid_retriever.query_filter(doc_id=doc_id, filter_field=text)
  159. else:
  160. query_result = []
  161. resp = generate_response(query_result,page_num,page_size)
  162. return resp
  163. def _insert_data(self, docs):
  164. insert_flag = ""
  165. insert_info = ""
  166. for doc in docs:
  167. chunk = doc.get("content")
  168. insert_flag, insert_info = self.hybrid_retriever.insert_data(chunk, doc)
  169. if not insert_flag:
  170. break
  171. resp = insert_flag if insert_flag else "insert_error"
  172. return resp, insert_info
  173. def _batch_insert_data(self, docs, text_lists):
  174. insert_flag, insert_info = self.hybrid_retriever.batch_insert_data(text_lists, docs)
  175. resp = insert_flag
  176. return resp, insert_info
  177. def _search(self, query, k, mode):
  178. search_result = self.hybrid_retriever.search(query, k, mode)
  179. return search_result
  180. def _query_by_scalar_field(self, doc_id: str, field_name: str, field_value: str):
  181. """
  182. 根据标量字段查询数据
  183. 参数:
  184. doc_id: 文档ID
  185. field_name: 字段名(如 Father_Chapter)
  186. field_value: 字段值
  187. 返回:
  188. 查询结果列表
  189. """
  190. return self.hybrid_retriever.query_by_scalar_field(doc_id, field_name, field_value)
  191. def _copy_docs_to_new_collection(self, new_collection_name, doc_ids, embedding_name="e5"):
  192. """
  193. 将指定的文档数据复制到新集合或现有集合
  194. 使用雪花算法生成新的 doc_id 和 chunk_id
  195. 参数:
  196. new_collection_name: 目标集合名称(也是新的 knowledge_id)
  197. doc_ids: 要复制的文档ID列表
  198. embedding_name: 向量模型名称
  199. 返回:
  200. 响应字典,包含 doc_id_mapping 映射关系
  201. """
  202. try:
  203. # 1. 从源集合查询数据
  204. logger.info(f"从集合 {self.collection} 查询文档: {doc_ids}")
  205. query_results = self.hybrid_retriever.query_by_doc_ids(doc_ids)
  206. if not query_results:
  207. return {"code": 404, "message": "未找到匹配的文档数据", "doc_id_mapping": {}, "chunk_id_mapping": {}}
  208. logger.info(f"查询到 {len(query_results)} 条数据")
  209. # 2. 检查目标集合是否存在,不存在则创建
  210. target_milvus_client = MilvusOperate(collection_name=new_collection_name, embedding_name=embedding_name)
  211. collection_exists = target_milvus_client._has_collection()
  212. if not collection_exists:
  213. logger.info(f"创建新集合: {new_collection_name}")
  214. create_result = target_milvus_client._create_collection()
  215. if create_result.get("code") != 200:
  216. create_result["doc_id_mapping"] = {}
  217. return create_result
  218. else:
  219. logger.info(f"集合 {new_collection_name} 已存在,直接插入数据")
  220. # 3. 为每个源 doc_id 生成新的 doc_id(使用雪花算法)
  221. doc_id_mapping = {} # {old_doc_id: new_doc_id}
  222. for old_doc_id in doc_ids:
  223. doc_id_mapping[old_doc_id] = generate_snowflake_id()
  224. # 4. 准备插入数据(移除pk字段,使用新的 doc_id 和 chunk_id)
  225. insert_data = []
  226. chunk_id_mapping = {} # {old_chunk_id: new_chunk_id}
  227. for item in query_results:
  228. old_doc_id = item.get("doc_id")
  229. old_chunk_id = item.get("chunk_id")
  230. new_doc_id = doc_id_mapping.get(old_doc_id, generate_snowflake_id())
  231. new_chunk_id = generate_snowflake_id() # 每个切片生成新的 chunk_id
  232. chunk_id_mapping[old_chunk_id] = new_chunk_id # 记录映射
  233. new_item = {
  234. "content": item.get("content"),
  235. "dense_vector": item.get("dense_vector"),
  236. "doc_id": new_doc_id,
  237. "chunk_id": new_chunk_id,
  238. "Father_Chapter": item.get("Father_Chapter"),
  239. "Chapter": item.get("Chapter"),
  240. "metadata": item.get("metadata")
  241. }
  242. insert_data.append(new_item)
  243. # 5. 批量插入数据到目标集合
  244. logger.info(f"开始向集合 {new_collection_name} 插入 {len(insert_data)} 条数据")
  245. try:
  246. target_milvus_client.hybrid_retriever.client.insert(
  247. collection_name=new_collection_name,
  248. data=insert_data
  249. )
  250. logger.info(f"成功向集合插入数据")
  251. return {
  252. "code": 200,
  253. "message": "复制成功",
  254. "data": {
  255. "source_collection": self.collection,
  256. "target_collection": new_collection_name,
  257. "doc_ids": doc_ids,
  258. "total_records": len(insert_data),
  259. "collection_existed": collection_exists
  260. },
  261. "doc_id_mapping": doc_id_mapping,
  262. "chunk_id_mapping": chunk_id_mapping
  263. }
  264. except Exception as e:
  265. logger.error(f"插入数据到集合失败: {e}")
  266. # 插入失败且是新创建的集合时删除
  267. if not collection_exists:
  268. target_milvus_client._delete_collection()
  269. return {"code": 500, "message": f"插入数据失败: {str(e)}", "doc_id_mapping": {}, "chunk_id_mapping": {}}
  270. except Exception as e:
  271. logger.error(f"复制文档到新集合失败: {e}")
  272. return {"code": 500, "message": f"复制失败: {str(e)}", "doc_id_mapping": {}, "chunk_id_mapping": {}}
  273. # class MysqlOperate:
  274. # def get_connection(self):
  275. # """
  276. # 从连接池中获取一个连接
  277. # :return: 数据库连接对象
  278. # """
  279. # # try:
  280. # # with ThreadPoolExecutor() as executor:
  281. # # future = executor.submit(POOL.get_connection)
  282. # # connection = future.result(timeout=5.0) # 设置超时时间为5秒
  283. # # logger.info("成功从连接池获取连接")
  284. # # return connection, "success"
  285. # # except TimeoutError:
  286. # # logger.error("获取mysql数据库连接池超时")
  287. # # return None, "mysql获取连接池超时"
  288. # # except errors.InterfaceError as e:
  289. # # logger.error(f"MySQL 接口异常:{e}")
  290. # # return None, "mysql接口异常"
  291. # # except errors.OperationalError as e:
  292. # # logger.error(f"MySQL 操作错误:{e}")
  293. # # return None, "mysql 操作错误"
  294. # # except Error as e:
  295. # # logger.error(f"无法从连接池获取连接: {e}")
  296. # # return None, str(e)
  297. # connection = None
  298. # event = threading.Event()
  299. # def target():
  300. # nonlocal connection
  301. # try:
  302. # connection = POOL.get_connection()
  303. # finally:
  304. # event.set()
  305. # thread = threading.Thread(target=target)
  306. # thread.start()
  307. # event.wait(timeout=5)
  308. # if thread.is_alive():
  309. # # 超时处理
  310. # logger.error("获取连接超时")
  311. # return None, "获取连接超时"
  312. # else:
  313. # if connection:
  314. # return connection, "success"
  315. # else:
  316. # logger.error("获取连接失败")
  317. # return None, "获取连接失败"
  318. # def insert_to_slice(self, docs, knowledge_id, doc_id):
  319. # """
  320. # 插入数据到切片信息表中 slice_info
  321. # """
  322. # connection = None
  323. # cursor = None
  324. # date_now = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
  325. # values = []
  326. # connection, cennction_info = self.get_connection()
  327. # if not connection:
  328. # return False, cennction_info
  329. # for chunk in docs:
  330. # slice_id = chunk.get("chunk_id")
  331. # slice_text = chunk.get("content")
  332. # chunk_index = chunk.get("metadata").get("chunk_index")
  333. # values.append((slice_id, knowledge_id, doc_id, slice_text, date_now, chunk_index))
  334. # try:
  335. # cursor = connection.cursor()
  336. # # insert_sql = """
  337. # # INSERT INTO slice_info (
  338. # # slice_id,
  339. # # knowledge_id,
  340. # # document_id,
  341. # # slice_text,
  342. # # create_time,
  343. # # slice_index
  344. # # ) VALUES (%s, %s, %s, %s, %s,%s)
  345. # # """
  346. # # 容错“for key 'UK_ID_TYPE_KEY'”
  347. # insert_sql = """
  348. # INSERT INTO slice_info (
  349. # slice_id,
  350. # knowledge_id,
  351. # document_id,
  352. # slice_text,
  353. # create_time,
  354. # slice_index
  355. # ) VALUES (%s, %s, %s, %s, %s, %s)
  356. # ON DUPLICATE KEY UPDATE
  357. # slice_text = VALUES(slice_text),
  358. # create_time = VALUES(create_time),
  359. # slice_index = VALUES(slice_index)
  360. # """
  361. # cursor.executemany(insert_sql, values)
  362. # connection.commit()
  363. # logger.info(f"批量插入切片数据成功。")
  364. # return True, "success"
  365. # except Error as e:
  366. # logger.error(f"数据库操作出错:{e}")
  367. # connection.rollback()
  368. # return False, str(e)
  369. # finally:
  370. # # if cursor:
  371. # cursor.close()
  372. # # if connection and connection.is_connected():
  373. # connection.close()
  374. # def delete_to_slice(self, doc_id):
  375. # """
  376. # 删除 slice_info库中切片信息
  377. # """
  378. # connection = None
  379. # cursor = None
  380. # connection, connection_info = self.get_connection()
  381. # if not connection:
  382. # return False, connection_info
  383. # try:
  384. # cursor = connection.cursor()
  385. # delete_sql = f"DELETE FROM slice_info WHERE document_id = %s"
  386. # cursor.execute(delete_sql, (doc_id,))
  387. # connection.commit()
  388. # logger.info(f"删除数据成功")
  389. # return True, "success"
  390. # except Error as e:
  391. # logger.error(f"根据{doc_id}删除数据失败:{e}")
  392. # connection.rollback()
  393. # return False, str(e)
  394. # finally:
  395. # # if cursor:
  396. # cursor.close()
  397. # # if connection and connection.is_connected():
  398. # connection.close()
  399. # def insert_to_image_url(self, image_dict, knowledge_id, doc_id):
  400. # """
  401. # 批量插入数据到指定表
  402. # """
  403. # connection = None
  404. # cursor = None
  405. # connection, connection_info = self.get_connection()
  406. # if not connection:
  407. # return False, connection_info
  408. # date_now = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
  409. # values = []
  410. # for img_key, img_value in image_dict.items():
  411. # origin_text = img_key
  412. # media_url = img_value
  413. # values.append((knowledge_id, doc_id, origin_text, "image", media_url, date_now))
  414. # try:
  415. # cursor = connection.cursor()
  416. # # insert_sql = """
  417. # # INSERT INTO bm_media_replacement (
  418. # # knowledge_id,
  419. # # document_id,
  420. # # origin_text,
  421. # # media_type,
  422. # # media_url,
  423. # # create_time
  424. # # ) VALUES (%s, %s, %s, %s, %s, %s)
  425. # # """
  426. # # 容错“for key 'UK_ID_TYPE_KEY'”
  427. # insert_sql = """
  428. # INSERT INTO bm_media_replacement (
  429. # knowledge_id,
  430. # document_id,
  431. # origin_text,
  432. # media_type,
  433. # media_url,
  434. # create_time
  435. # ) VALUES (%s, %s, %s, %s, %s, %s)
  436. # ON DUPLICATE KEY UPDATE
  437. # origin_text = VALUES(origin_text),
  438. # media_type = VALUES(media_type),
  439. # media_url = VALUES(media_url),
  440. # create_time = VALUES(create_time)
  441. # """
  442. # cursor.executemany(insert_sql, values)
  443. # connection.commit()
  444. # logger.info(f"插入到bm_media_replacement表成功")
  445. # return True, "success"
  446. # except Error as e:
  447. # logger.error(f"数据库操作出错:{e}")
  448. # connection.rollback()
  449. # return False, str(e)
  450. # finally:
  451. # # if cursor:
  452. # cursor.close()
  453. # # if connection and connection.is_connected():
  454. # connection.close()
  455. # def delete_image_url(self, doc_id):
  456. # """
  457. # 根据doc id删除bm_media_replacement中的数据
  458. # """
  459. # connection = None
  460. # cursor = None
  461. # connection, connection_info = self.get_connection()
  462. # if not connection:
  463. # return False, connection_info
  464. # try:
  465. # cursor = connection.cursor()
  466. # delete_sql = f"DELETE FROM bm_media_replacement WHERE document_id = %s"
  467. # cursor.execute(delete_sql, (doc_id,))
  468. # connection.commit()
  469. # logger.info(f"根据{doc_id} 删除bm_media_replacement表中数据成功")
  470. # return True, "success"
  471. # except Error as e:
  472. # logger.error(f"根据{doc_id}删除 bm_media_replacement 数据库操作出错:{e}")
  473. # connection.rollback()
  474. # return False, str(e)
  475. # finally:
  476. # # if cursor:
  477. # cursor.close()
  478. # # if connection and connection.is_connected():
  479. # connection.close()
  480. # def update_total_doc_len(self, update_json):
  481. # """
  482. # 更新长度表和文档长度表,删除slice info表, 插入slice info 切片信息
  483. # """
  484. # knowledge_id = update_json.get("knowledge_id")
  485. # doc_id = update_json.get("doc_id")
  486. # chunk_len = update_json.get("chunk_len")
  487. # operate = update_json.get("operate")
  488. # chunk_id = update_json.get("chunk_id")
  489. # chunk_text = update_json.get("chunk_text")
  490. # connection = None
  491. # cursor = None
  492. # connection, connection_info = self.get_connection()
  493. # if not connection:
  494. # return False, connection_info
  495. # try:
  496. # cursor = connection.cursor()
  497. # query_doc_word_num_sql = f"select word_num,slice_total from bm_document where document_id = %s"
  498. # query_knowledge_word_num_sql = f"select word_num from bm_knowledge where knowledge_id = %s"
  499. # cursor.execute(query_doc_word_num_sql, (doc_id,))
  500. # doc_result = cursor.fetchone()
  501. # logger.info(f"查询到的文档长度信息:{doc_result}")
  502. # cursor.execute(query_knowledge_word_num_sql, (knowledge_id, ))
  503. # knowledge_result = cursor.fetchone()
  504. # logger.info(f"查询到的知识库总长度信息:{knowledge_result}")
  505. # if not doc_result:
  506. # new_word_num = 0
  507. # slice_total = 0
  508. # else:
  509. # old_word_num = doc_result[0]
  510. # slice_total = doc_result[1]
  511. # new_word_num = old_word_num + chunk_len
  512. # slice_total -= 1 if slice_total else 0
  513. # if not knowledge_result:
  514. # new_knowledge_word_num = 0
  515. # else:
  516. # old_knowledge_word_num = knowledge_result[0]
  517. # new_knowledge_word_num = old_knowledge_word_num + chunk_len
  518. # if operate == "update":
  519. # update_sql = f"UPDATE bm_document SET word_num = %s WHERE document_id = %s"
  520. # cursor.execute(update_sql, (new_word_num, doc_id))
  521. # date_now = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
  522. # update_slice_sql = f"UPDATE slice_info SET slice_text = %s, update_time = %s WHERE slice_id = %s"
  523. # cursor.execute(update_slice_sql, (chunk_text, date_now, chunk_id))
  524. # elif operate == "insert":
  525. # query_slice_info_index_sql = f"select MAX(slice_index) from slice_info where document_id = %s"
  526. # cursor.execute(query_slice_info_index_sql, (doc_id,))
  527. # chunk_index_result = cursor.fetchone()[0]
  528. # # logger.info(chunk_index_result)
  529. # if chunk_index_result:
  530. # chunk_max_index = int(chunk_index_result)
  531. # else:
  532. # chunk_max_index = 0
  533. # update_sql = f"UPDATE bm_document SET word_num = %s WHERE document_id = %s"
  534. # cursor.execute(update_sql, (new_word_num, doc_id))
  535. # date_now = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
  536. # insert_slice_sql = "INSERT INTO slice_info (slice_id,knowledge_id,document_id,slice_text,create_time, slice_index) VALUES (%s, %s, %s, %s, %s, %s)"
  537. # cursor.execute(insert_slice_sql, (chunk_id, knowledge_id, doc_id, chunk_text, date_now, chunk_max_index+1))
  538. # else:
  539. # update_sql = f"UPDATE bm_document SET word_num = %s, slice_total = %s WHERE document_id = %s"
  540. # cursor.execute(update_sql, (new_word_num, slice_total, doc_id))
  541. # # 删除切片id对应的切片
  542. # delete_slice_sql = f"DELETE FROM slice_info where slice_id = %s"
  543. # cursor.execute(delete_slice_sql, (chunk_id, ))
  544. # update_knowledge_sql = f"UPDATE bm_knowledge SET word_num = %s WHERE knowledge_id = %s"
  545. # cursor.execute(update_knowledge_sql, (new_knowledge_word_num, knowledge_id))
  546. # connection.commit()
  547. # logger.info("bm_document和bm_knowledge数据更新成功")
  548. # return True, "success"
  549. # except Error as e:
  550. # logger.error(f"数据库操作出错:{e}")
  551. # connection.rollback()
  552. # return False, str(e)
  553. # finally:
  554. # # if cursor:
  555. # cursor.close()
  556. # # if connection and connection.is_connected():
  557. # connection.close()
  558. TABLE_NAME = "bm_document"
  559. STATUS_FIELD = "update_by"
  560. TASK_ID_FIELD = "document_id"
  561. USER_ID_FIELD = "remark"
  562. import time
  563. # ========== 全局初始化连接池(自动检测 + 超时保护) ==========
  564. class SafeMySQLPool:
  565. def __init__(self, pool_size=10, conn_timeout=10, idle_timeout=60, **mysql_config):
  566. mysql_config.setdefault("connect_timeout", conn_timeout)
  567. mysql_config.setdefault("pool_reset_session", True)
  568. self._pool = pooling.MySQLConnectionPool(
  569. pool_name="safe_mysql_pool",
  570. pool_size=pool_size,
  571. **mysql_config
  572. )
  573. # 使用 RLock 可重入锁,避免 _auto_reclaimer 调用 close 时死锁
  574. self._lock = threading.RLock()
  575. self._active_conns = {} # {id(conn): (conn, last_used_time)}
  576. self._idle_timeout = idle_timeout
  577. self._stop_event = threading.Event()
  578. threading.Thread(target=self._auto_reclaimer, daemon=True).start()
  579. def get_connection(self, timeout=10):
  580. """安全获取连接(带超时检测与追踪)"""
  581. start = time.time()
  582. while True:
  583. try:
  584. conn = self._pool.get_connection()
  585. conn.ping(reconnect=True, attempts=3, delay=2)
  586. with self._lock:
  587. self._active_conns[id(conn)] = (conn, time.time())
  588. return self._wrap_connection(conn)
  589. except errors.PoolError:
  590. if time.time() - start > timeout:
  591. raise TimeoutError(f"获取 MySQL 连接超时(超过 {timeout}s)")
  592. time.sleep(0.3)
  593. def _wrap_connection(self, conn):
  594. """包装连接对象以监控关闭事件"""
  595. pool = self
  596. orig_close = conn.close
  597. def safe_close():
  598. try:
  599. orig_close()
  600. finally:
  601. with pool._lock:
  602. pool._active_conns.pop(id(conn), None)
  603. conn.close = safe_close
  604. return conn
  605. def _auto_reclaimer(self):
  606. """后台线程自动回收超时未关闭连接"""
  607. while not self._stop_event.is_set():
  608. time.sleep(5)
  609. now = time.time()
  610. with self._lock:
  611. to_remove = []
  612. for cid, (conn, last_used) in list(self._active_conns.items()):
  613. if now - last_used > self._idle_timeout:
  614. try:
  615. conn.close()
  616. logger.warning(f"[回收] 已回收超时未关闭连接 (idle={int(now - last_used)}s)")
  617. except Exception as e:
  618. logger.error(f"[回收] 回收连接失败: {e}")
  619. to_remove.append(cid)
  620. for cid in to_remove:
  621. self._active_conns.pop(cid, None)
  622. def close_all(self):
  623. """停止守护线程并关闭所有连接"""
  624. self._stop_event.set()
  625. with self._lock:
  626. for conn, _ in self._active_conns.values():
  627. try:
  628. conn.close()
  629. except:
  630. pass
  631. self._active_conns.clear()
  632. # ========== 初始化连接池 ==========
  633. if "POOL" not in globals():
  634. try:
  635. POOL = SafeMySQLPool(pool_size=10, idle_timeout=60, **mysql_config)
  636. logger.info("MySQL 连接池初始化成功")
  637. except Error as e:
  638. logger.error(f"MySQL 连接池初始化失败: {e}")
  639. POOL = None
  640. """
  641. 雪花算法获取唯一id
  642. """
  643. import time
  644. import threading
  645. class Snowflake:
  646. def __init__(self, datacenter_id=1, worker_id=1):
  647. self.worker_id_bits = 5
  648. self.datacenter_id_bits = 5
  649. self.sequence_bits = 12
  650. self.max_worker_id = -1 ^ (-1 << self.worker_id_bits)
  651. self.max_datacenter_id = -1 ^ (-1 << self.datacenter_id_bits)
  652. self.worker_id = worker_id
  653. self.datacenter_id = datacenter_id
  654. self.sequence = 0
  655. self.worker_id_shift = self.sequence_bits
  656. self.datacenter_id_shift = self.sequence_bits + self.worker_id_bits
  657. self.timestamp_left_shift = self.sequence_bits + self.worker_id_bits + self.datacenter_id_bits
  658. self.twepoch = 1288834974657
  659. self.last_timestamp = -1
  660. self.lock = threading.Lock()
  661. def _timestamp(self):
  662. return int(time.time() * 1000)
  663. def _wait_next_ms(self, last):
  664. ts = self._timestamp()
  665. while ts <= last:
  666. ts = self._timestamp()
  667. return ts
  668. def generate_id(self):
  669. with self.lock:
  670. timestamp = self._timestamp()
  671. if timestamp < self.last_timestamp:
  672. raise Exception("Clock moved backwards, refusing to generate id")
  673. if timestamp == self.last_timestamp:
  674. self.sequence = (self.sequence + 1) & ((1 << self.sequence_bits) - 1)
  675. if self.sequence == 0:
  676. timestamp = self._wait_next_ms(timestamp)
  677. else:
  678. self.sequence = 0
  679. self.last_timestamp = timestamp
  680. snowflake_id = (
  681. ((timestamp - self.twepoch) << self.timestamp_left_shift) |
  682. (self.datacenter_id << self.datacenter_id_shift) |
  683. (self.worker_id << self.worker_id_shift) |
  684. self.sequence
  685. )
  686. # 转成固定 20 位数字
  687. return str(snowflake_id).zfill(20)
  688. # ========== 全局雪花算法 ID 生成器 ==========
  689. snowflake_id_generator = Snowflake(datacenter_id=1, worker_id=1)
  690. def generate_snowflake_id():
  691. """
  692. 全局方法:使用雪花算法生成唯一ID
  693. 返回20位数字字符串
  694. """
  695. return snowflake_id_generator.generate_id()
  696. # ========== MysqlOperate 类 ==========
  697. class MysqlOperate:
  698. def get_connection(self):
  699. """安全获取连接"""
  700. if not POOL:
  701. return None, "连接池未初始化"
  702. try:
  703. connection = POOL.get_connection(timeout=5)
  704. return connection, "success"
  705. except TimeoutError as e:
  706. logger.error(str(e))
  707. return None, "获取连接超时"
  708. except Error as e:
  709. logger.error(f"MySQL 获取连接失败: {e}")
  710. return None, str(e)
  711. def _execute_many(self, sql, values, success_msg, err_msg):
  712. """通用批量执行模板"""
  713. connection, info = self.get_connection()
  714. if not connection:
  715. return False, info
  716. cursor = None
  717. try:
  718. cursor = connection.cursor()
  719. cursor.executemany(sql, values)
  720. connection.commit()
  721. logger.info(success_msg)
  722. return True, "success"
  723. except Error as e:
  724. connection.rollback()
  725. logger.error(f"{err_msg}: {e}")
  726. return False, str(e)
  727. finally:
  728. if cursor:
  729. cursor.close()
  730. if connection:
  731. connection.close()
  732. def insert_to_slice(self, docs, knowledge_id, doc_id):
  733. """批量插入切片信息(同时存储 slice_text 和 old_slice_text)"""
  734. date_now = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
  735. values = [
  736. (
  737. chunk.get("chunk_id"),
  738. knowledge_id,
  739. doc_id,
  740. chunk.get("content"),
  741. chunk.get("content"), # old_slice_text 存储原始文本
  742. date_now,
  743. chunk.get("metadata", {}).get("chunk_index"),
  744. chunk.get("Chapter"),
  745. chunk.get("Father_Chapter", "")
  746. )
  747. for chunk in docs
  748. ]
  749. sql = """
  750. INSERT INTO slice_info (
  751. slice_id, knowledge_id, document_id, slice_text, old_slice_text, create_time, slice_index, section, parent_section
  752. ) VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s)
  753. ON DUPLICATE KEY UPDATE
  754. slice_text = VALUES(slice_text),
  755. create_time = VALUES(create_time),
  756. slice_index = VALUES(slice_index),
  757. section = VALUES(section),
  758. parent_section = VALUES(parent_section)
  759. """
  760. return self._execute_many(sql, values, "批量插入切片数据成功", "插入 slice_info 出错")
  761. def delete_to_slice(self, doc_id):
  762. """删除切片"""
  763. connection, info = self.get_connection()
  764. if not connection:
  765. return False, info
  766. cursor = None
  767. try:
  768. cursor = connection.cursor()
  769. cursor.execute("DELETE FROM slice_info WHERE document_id = %s", (doc_id,))
  770. connection.commit()
  771. logger.info(f"删除 slice_info 数据成功")
  772. return True, "success"
  773. except Error as e:
  774. connection.rollback()
  775. logger.error(f"删除 slice_info 出错: {e}")
  776. return False, str(e)
  777. finally:
  778. if cursor:
  779. cursor.close()
  780. if connection:
  781. connection.close()
  782. def insert_to_image_url(self, image_dict, knowledge_id, doc_id):
  783. """插入图片映射表"""
  784. date_now = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
  785. values = [
  786. (knowledge_id, doc_id, k, "image", v, date_now)
  787. for k, v in image_dict.items()
  788. ]
  789. sql = """
  790. INSERT INTO bm_media_replacement (
  791. knowledge_id, document_id, origin_text, media_type, media_url, create_time
  792. ) VALUES (%s, %s, %s, %s, %s, %s)
  793. ON DUPLICATE KEY UPDATE
  794. origin_text = VALUES(origin_text),
  795. media_type = VALUES(media_type),
  796. media_url = VALUES(media_url),
  797. create_time = VALUES(create_time)
  798. """
  799. return self._execute_many(sql, values, "插入 bm_media_replacement 成功", "插入 bm_media_replacement 出错")
  800. def delete_image_url(self, doc_id):
  801. """删除图片映射"""
  802. connection, info = self.get_connection()
  803. if not connection:
  804. return False, info
  805. cursor = None
  806. try:
  807. cursor = connection.cursor()
  808. cursor.execute("DELETE FROM bm_media_replacement WHERE document_id = %s", (doc_id,))
  809. connection.commit()
  810. logger.info(f"删除 bm_media_replacement 成功")
  811. return True, "success"
  812. except Error as e:
  813. connection.rollback()
  814. logger.error(f"删除 bm_media_replacement 出错: {e}")
  815. return False, str(e)
  816. finally:
  817. if cursor:
  818. cursor.close()
  819. if connection:
  820. connection.close()
  821. def update_task_status_start(self, task_id):
  822. """更新任务状态为开始(1)"""
  823. connection, info = self.get_connection()
  824. if not connection:
  825. return False, info
  826. cursor = None
  827. try:
  828. cursor = connection.cursor()
  829. sql = f"UPDATE {TABLE_NAME} SET {STATUS_FIELD} = %s WHERE {TASK_ID_FIELD} = %s"
  830. cursor.execute(sql, (1, task_id))
  831. connection.commit()
  832. logger.info(f"任务 {task_id} 状态更新为开始(1)")
  833. return True, "success"
  834. except Error as e:
  835. connection.rollback()
  836. logger.error(f"更新任务状态为开始失败: {e}")
  837. return False, str(e)
  838. finally:
  839. if cursor:
  840. cursor.close()
  841. if connection:
  842. connection.close()
  843. def update_task_status_complete(self, task_id, user_id):
  844. """更新任务状态为完成(2)并更新用户ID"""
  845. connection, info = self.get_connection()
  846. if not connection:
  847. return False, info
  848. cursor = None
  849. try:
  850. cursor = connection.cursor()
  851. sql = f"UPDATE {TABLE_NAME} SET {STATUS_FIELD} = %s, {USER_ID_FIELD} = %s WHERE {TASK_ID_FIELD} = %s"
  852. cursor.execute(sql, (2, user_id, task_id))
  853. connection.commit()
  854. logger.info(f"任务 {task_id} 状态更新为完成(2),用户ID: {user_id}")
  855. return True, "success"
  856. except Error as e:
  857. connection.rollback()
  858. logger.error(f"更新任务状态为完成失败: {e}")
  859. return False, str(e)
  860. finally:
  861. if cursor:
  862. cursor.close()
  863. if connection:
  864. connection.close()
  865. def update_task_status_error(self, task_id):
  866. """更新任务状态为错误(0)"""
  867. connection, info = self.get_connection()
  868. if not connection:
  869. return False, info
  870. cursor = None
  871. try:
  872. cursor = connection.cursor()
  873. sql = f"UPDATE {TABLE_NAME} SET {STATUS_FIELD} = %s WHERE {TASK_ID_FIELD} = %s"
  874. cursor.execute(sql, (0, task_id))
  875. connection.commit()
  876. logger.info(f"任务 {task_id} 状态更新为错误(0)")
  877. return True, "success"
  878. except Error as e:
  879. connection.rollback()
  880. logger.error(f"更新任务状态为错误失败: {e}")
  881. return False, str(e)
  882. finally:
  883. if cursor:
  884. cursor.close()
  885. if connection:
  886. connection.close()
  887. def delete_document(self, task_id):
  888. """删除 bm_document 表中的记录(取消任务前清理)"""
  889. connection, info = self.get_connection()
  890. if not connection:
  891. return False, info
  892. cursor = None
  893. try:
  894. cursor = connection.cursor()
  895. sql = f"DELETE FROM {TABLE_NAME} WHERE {TASK_ID_FIELD} = %s"
  896. cursor.execute(sql, (task_id,))
  897. affected_rows = cursor.rowcount
  898. connection.commit()
  899. logger.info(f"删除 bm_document 记录成功: task_id={task_id}, 影响行数={affected_rows}")
  900. return True, affected_rows
  901. except Error as e:
  902. connection.rollback()
  903. logger.error(f"删除 bm_document 记录失败: {e}")
  904. return False, str(e)
  905. finally:
  906. if cursor:
  907. cursor.close()
  908. if connection:
  909. connection.close()
  910. def query_parent_generation_enabled(self, doc_ids: list):
  911. """
  912. 查询文档的 parent_generation_enabled 字段
  913. 返回 parent_generation_enabled=1 的 doc_id 集合
  914. """
  915. if not doc_ids:
  916. return set()
  917. connection, info = self.get_connection()
  918. if not connection:
  919. return set()
  920. cursor = None
  921. try:
  922. cursor = connection.cursor()
  923. placeholders = ", ".join(["%s"] * len(doc_ids))
  924. sql = f"SELECT document_id FROM bm_document WHERE document_id IN ({placeholders}) AND parent_generation_enabled = 1"
  925. cursor.execute(sql, tuple(doc_ids))
  926. results = cursor.fetchall()
  927. return {row[0] for row in results}
  928. except Error as e:
  929. logger.error(f"查询 parent_generation_enabled 失败: {e}")
  930. return set()
  931. finally:
  932. if cursor:
  933. cursor.close()
  934. if connection:
  935. connection.close()
  936. def insert_oss_record(self, file_name, url, tenant_id="000000", file_extension=""):
  937. """插入 OSS 记录到 sys_oss 表"""
  938. connection, info = self.get_connection()
  939. if not connection:
  940. return False, info
  941. cursor = None
  942. try:
  943. # 生成类似 "a2922173479520702464" 的 oss_id 20位
  944. # import random
  945. # oss_id = f"a{int(time.time() * 1000)}{random.randint(1000, 9999)}"
  946. oss_id = Snowflake().generate_id()
  947. create_time = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
  948. cursor = connection.cursor()
  949. sql = """
  950. INSERT INTO sys_oss (oss_id, tenant_id, file_name, original_name, url, create_time, file_suffix)
  951. VALUES (%s, %s, %s, %s, %s, %s, %s)
  952. """
  953. cursor.execute(sql, (oss_id, tenant_id, file_name, file_name, url, create_time, file_extension))
  954. connection.commit()
  955. logger.info(f"OSS 记录插入成功: {oss_id}")
  956. return True, oss_id
  957. except Error as e:
  958. connection.rollback()
  959. logger.error(f"插入 OSS 记录失败: {e}")
  960. return False, str(e)
  961. finally:
  962. if cursor:
  963. cursor.close()
  964. if connection:
  965. connection.close()
  966. def update_total_doc_len(self, update_json):
  967. """
  968. 更新长度表和文档长度表,删除/更新/插入 slice_info 表
  969. """
  970. knowledge_id = update_json.get("knowledge_id")
  971. doc_id = update_json.get("doc_id")
  972. chunk_len = update_json.get("chunk_len")
  973. operate = update_json.get("operate")
  974. chunk_id = update_json.get("chunk_id")
  975. chunk_text = update_json.get("chunk_text", "")
  976. slice_index = update_json.get("slice_index")
  977. connection, info = self.get_connection()
  978. if not connection:
  979. return False, info
  980. cursor = None
  981. try:
  982. cursor = connection.cursor()
  983. # 查询文档当前信息
  984. cursor.execute(
  985. "SELECT word_num, slice_total FROM bm_document WHERE document_id = %s",
  986. (doc_id,)
  987. )
  988. doc_result = cursor.fetchone()
  989. logger.info(f"查询到的文档长度信息:{doc_result}")
  990. # 查询知识库当前信息
  991. cursor.execute(
  992. "SELECT word_num FROM bm_knowledge WHERE knowledge_id = %s",
  993. (knowledge_id,)
  994. )
  995. knowledge_result = cursor.fetchone()
  996. logger.info(f"查询到的知识库总长度信息:{knowledge_result}")
  997. # 计算新的文档长度
  998. if not doc_result:
  999. new_word_num = chunk_len if chunk_len > 0 else 0
  1000. slice_total = 0
  1001. else:
  1002. old_word_num = doc_result[0] or 0
  1003. slice_total = doc_result[1] or 0
  1004. new_word_num = old_word_num + chunk_len
  1005. if operate == "delete":
  1006. slice_total = max(0, slice_total - 1)
  1007. # 计算新的知识库长度
  1008. if not knowledge_result:
  1009. new_knowledge_word_num = chunk_len if chunk_len > 0 else 0
  1010. else:
  1011. old_knowledge_word_num = knowledge_result[0] or 0
  1012. new_knowledge_word_num = old_knowledge_word_num + chunk_len
  1013. date_now = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
  1014. # 根据操作类型执行不同的 SQL
  1015. if operate == "update":
  1016. # # 更新文档长度
  1017. # cursor.execute(
  1018. # "UPDATE bm_document SET word_num = %s WHERE document_id = %s",
  1019. # (new_word_num, doc_id)
  1020. # )
  1021. # 更新切片内容
  1022. cursor.execute(
  1023. "UPDATE slice_info SET slice_text = %s, update_time = %s WHERE slice_id = %s",
  1024. (chunk_text, date_now, chunk_id)
  1025. )
  1026. elif operate == "insert":
  1027. # 获取最大切片索引
  1028. # cursor.execute(
  1029. # "SELECT MAX(slice_index) FROM slice_info WHERE document_id = %s",
  1030. # (doc_id,)
  1031. # )
  1032. # chunk_index_result = cursor.fetchone()[0]
  1033. # chunk_max_index = int(chunk_index_result) if chunk_index_result else 0
  1034. # # 更新文档长度
  1035. # cursor.execute(
  1036. # "UPDATE bm_document SET word_num = %s WHERE document_id = %s",
  1037. # (new_word_num, doc_id)
  1038. # )
  1039. # 插入新切片
  1040. cursor.execute(
  1041. """INSERT INTO slice_info
  1042. (slice_id, knowledge_id, document_id, slice_text, create_time, slice_index, old_slice_text)
  1043. VALUES (%s, %s, %s, %s, %s, %s, %s)""",
  1044. (chunk_id, knowledge_id, doc_id, chunk_text, date_now, int(slice_index), chunk_text)
  1045. )
  1046. elif operate == "delete":
  1047. # # 更新文档长度和切片总数
  1048. # cursor.execute(
  1049. # "UPDATE bm_document SET word_num = %s, slice_total = %s WHERE document_id = %s",
  1050. # (new_word_num, slice_total, doc_id)
  1051. # )
  1052. # 删除切片
  1053. # cursor.execute(
  1054. # "DELETE FROM slice_info WHERE slice_id = %s",
  1055. # (chunk_id,)
  1056. # )
  1057. cursor.execute(
  1058. "UPDATE slice_info SET del_flag = 1 WHERE slice_id = %s",
  1059. (chunk_id,)
  1060. )
  1061. # # 更新知识库总长度
  1062. # cursor.execute(
  1063. # "UPDATE bm_knowledge SET word_num = %s WHERE knowledge_id = %s",
  1064. # (new_knowledge_word_num, knowledge_id)
  1065. # )
  1066. connection.commit()
  1067. logger.info("bm_document 和 bm_knowledge 数据更新成功")
  1068. return True, "success"
  1069. except Error as e:
  1070. connection.rollback()
  1071. logger.error(f"update_total_doc_len 数据库操作出错:{e}")
  1072. return False, str(e)
  1073. finally:
  1074. if cursor:
  1075. cursor.close()
  1076. if connection:
  1077. connection.close()
  1078. def query_slice_info_by_doc_ids(self, knowledge_id: str, doc_ids: list):
  1079. """
  1080. 根据 knowledge_id 和 doc_ids 列表查询 slice_info 表中的数据
  1081. 参数:
  1082. knowledge_id: 知识库ID
  1083. doc_ids: 文档ID列表
  1084. 返回:
  1085. (success, data_or_error): 成功时返回数据列表,失败时返回错误信息
  1086. """
  1087. if not doc_ids:
  1088. return True, []
  1089. connection, info = self.get_connection()
  1090. if not connection:
  1091. return False, info
  1092. cursor = None
  1093. try:
  1094. cursor = connection.cursor(dictionary=True)
  1095. placeholders = ','.join(['%s'] * len(doc_ids))
  1096. sql = f"""
  1097. SELECT slice_id, knowledge_id, document_id, slice_text, old_slice_text,
  1098. create_time, update_time, slice_index
  1099. FROM slice_info
  1100. WHERE knowledge_id = %s AND document_id IN ({placeholders})
  1101. """
  1102. cursor.execute(sql, (knowledge_id, *doc_ids))
  1103. results = cursor.fetchall()
  1104. logger.info(f"查询 slice_info 成功,共 {len(results)} 条记录")
  1105. return True, results
  1106. except Error as e:
  1107. logger.error(f"查询 slice_info 出错: {e}")
  1108. return False, str(e)
  1109. finally:
  1110. if cursor:
  1111. cursor.close()
  1112. if connection:
  1113. connection.close()
  1114. def query_media_replacement_by_doc_ids(self, knowledge_id: str, doc_ids: list):
  1115. """
  1116. 根据 knowledge_id 和 doc_ids 列表查询 bm_media_replacement 表中的数据
  1117. 参数:
  1118. knowledge_id: 知识库ID
  1119. doc_ids: 文档ID列表
  1120. 返回:
  1121. (success, data_or_error): 成功时返回数据列表,失败时返回错误信息
  1122. """
  1123. if not doc_ids:
  1124. return True, []
  1125. connection, info = self.get_connection()
  1126. if not connection:
  1127. return False, info
  1128. cursor = None
  1129. try:
  1130. cursor = connection.cursor(dictionary=True)
  1131. placeholders = ','.join(['%s'] * len(doc_ids))
  1132. sql = f"""
  1133. SELECT knowledge_id, document_id, origin_text, media_type, media_url, create_time
  1134. FROM bm_media_replacement
  1135. WHERE knowledge_id = %s AND document_id IN ({placeholders})
  1136. """
  1137. cursor.execute(sql, (knowledge_id, *doc_ids))
  1138. results = cursor.fetchall()
  1139. logger.info(f"查询 bm_media_replacement 成功,共 {len(results)} 条记录")
  1140. return True, results
  1141. except Error as e:
  1142. logger.error(f"查询 bm_media_replacement 出错: {e}")
  1143. return False, str(e)
  1144. finally:
  1145. if cursor:
  1146. cursor.close()
  1147. if connection:
  1148. connection.close()
  1149. def query_bm_document_by_doc_ids(self, knowledge_id: str, doc_ids: list):
  1150. """
  1151. 根据 knowledge_id 和 doc_ids 列表查询 bm_document 表中的数据
  1152. 参数:
  1153. knowledge_id: 知识库ID
  1154. doc_ids: 文档ID列表
  1155. 返回:
  1156. (success, data_or_error): 成功时返回数据列表,失败时返回错误信息
  1157. """
  1158. if not doc_ids:
  1159. return True, []
  1160. connection, info = self.get_connection()
  1161. if not connection:
  1162. return False, info
  1163. cursor = None
  1164. try:
  1165. cursor = connection.cursor(dictionary=True)
  1166. placeholders = ','.join(['%s'] * len(doc_ids))
  1167. sql = f"""
  1168. SELECT * FROM bm_document
  1169. WHERE knowledge_id = %s AND document_id IN ({placeholders})
  1170. """
  1171. cursor.execute(sql, (knowledge_id, *doc_ids))
  1172. results = cursor.fetchall()
  1173. logger.info(f"查询 bm_document 成功,共 {len(results)} 条记录")
  1174. return True, results
  1175. except Error as e:
  1176. logger.error(f"查询 bm_document 出错: {e}")
  1177. return False, str(e)
  1178. finally:
  1179. if cursor:
  1180. cursor.close()
  1181. if connection:
  1182. connection.close()
  1183. def copy_docs_metadata_to_new_knowledge(self, source_knowledge_id: str, source_doc_ids: list, new_knowledge_id: str, doc_id_mapping: dict = None, chunk_id_mapping: dict = None, tenant_id: str = "000000"):
  1184. """
  1185. 复制文档元数据到新知识库(bm_document、slice_info 和 bm_media_replacement)
  1186. 参数:
  1187. source_knowledge_id: 源知识库ID
  1188. source_doc_ids: 源文档ID列表
  1189. new_knowledge_id: 新的知识库ID
  1190. doc_id_mapping: 旧文档ID到新文档ID的映射 {old_doc_id: new_doc_id}
  1191. 如果不提供,将为每个文档生成新的雪花算法ID
  1192. chunk_id_mapping: 旧切片ID到新切片ID的映射 {old_chunk_id: new_chunk_id}
  1193. 用于 slice_id,保持与向量库一致
  1194. tenant_id: 租户ID(由前端传入)
  1195. 返回:
  1196. (success, result_dict): result_dict 包含复制结果详情
  1197. """
  1198. if not source_doc_ids:
  1199. return True, {"message": "无需复制的文档", "doc_id_mapping": {}}
  1200. # 如果没有提供映射,为每个源文档生成新的 doc_id
  1201. if doc_id_mapping is None:
  1202. doc_id_mapping = {}
  1203. for old_doc_id in source_doc_ids:
  1204. doc_id_mapping[old_doc_id] = generate_snowflake_id()
  1205. # 1. 查询源 slice_info 数据
  1206. success, slice_data = self.query_slice_info_by_doc_ids(source_knowledge_id, source_doc_ids)
  1207. if not success:
  1208. return False, {"error": f"查询切片数据失败: {slice_data}"}
  1209. # 2. 查询源 bm_media_replacement 数据
  1210. success, media_data = self.query_media_replacement_by_doc_ids(source_knowledge_id, source_doc_ids)
  1211. if not success:
  1212. return False, {"error": f"查询媒体映射失败: {media_data}"}
  1213. # 3. 查询源 bm_document 数据
  1214. success, doc_data = self.query_bm_document_by_doc_ids(source_knowledge_id, source_doc_ids)
  1215. if not success:
  1216. return False, {"error": f"查询文档数据失败: {doc_data}"}
  1217. connection, info = self.get_connection()
  1218. if not connection:
  1219. return False, {"error": info}
  1220. cursor = None
  1221. try:
  1222. cursor = connection.cursor()
  1223. date_now = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
  1224. slice_count = 0
  1225. media_count = 0
  1226. doc_count = 0
  1227. # 4. 插入 bm_document
  1228. if doc_data:
  1229. # 定义所有字段及特殊处理
  1230. all_fields = [
  1231. 'document_id', 'knowledge_id', 'custom_separator', 'sentence_size', 'length',
  1232. 'word_num', 'slice_total', 'name', 'url', 'parse_image', 'tenant_id',
  1233. 'create_dept', 'create_by', 'create_time', 'update_by', 'update_time',
  1234. 'remark', 'parsing_type', 'oss_id', 'status', 'mark_oss_id', 'mark_url',
  1235. 'ref_document_id', 'qa_checked', 'related_questions_enabled',
  1236. 'summary_generation_enabled', 'parent_generation_enabled', 'suffix', 'pdf_url'
  1237. ]
  1238. doc_values = []
  1239. for row in doc_data:
  1240. old_doc_id = row['document_id']
  1241. new_doc_id = doc_id_mapping.get(old_doc_id, generate_snowflake_id())
  1242. # 特殊处理字段
  1243. special = {
  1244. 'document_id': new_doc_id,
  1245. 'knowledge_id': new_knowledge_id,
  1246. 'tenant_id': tenant_id,
  1247. 'create_time': date_now,
  1248. 'ref_document_id': old_doc_id
  1249. }
  1250. doc_values.append(tuple(special.get(f, row.get(f)) for f in all_fields))
  1251. placeholders = ','.join(['%s'] * len(all_fields))
  1252. doc_sql = f"INSERT INTO bm_document ({','.join(all_fields)}) VALUES ({placeholders})"
  1253. cursor.executemany(doc_sql, doc_values)
  1254. doc_count = len(doc_values)
  1255. logger.info(f"插入文档数据成功: {doc_count} 条")
  1256. # 5. 插入 slice_info(使用 old_slice_text 存储原始文本)
  1257. if slice_data:
  1258. slice_values = []
  1259. for row in slice_data:
  1260. old_doc_id = row['document_id']
  1261. old_slice_id = row['slice_id']
  1262. new_doc_id = doc_id_mapping.get(old_doc_id, generate_snowflake_id())
  1263. # 使用向量库中的 chunk_id 作为 slice_id(保持一致)
  1264. new_slice_id = chunk_id_mapping.get(old_slice_id, generate_snowflake_id()) if chunk_id_mapping else generate_snowflake_id()
  1265. # old_slice_text 存储原始文本
  1266. old_slice_text = row.get('old_slice_text') or row['slice_text']
  1267. slice_values.append((
  1268. new_slice_id,
  1269. new_knowledge_id,
  1270. new_doc_id,
  1271. row['slice_text'],
  1272. old_slice_text,
  1273. date_now,
  1274. row.get('slice_index')
  1275. ))
  1276. slice_sql = """
  1277. INSERT INTO slice_info (
  1278. slice_id, knowledge_id, document_id, slice_text, old_slice_text, create_time, slice_index
  1279. ) VALUES (%s, %s, %s, %s, %s, %s, %s)
  1280. """
  1281. cursor.executemany(slice_sql, slice_values)
  1282. slice_count = len(slice_values)
  1283. logger.info(f"插入切片数据成功: {slice_count} 条")
  1284. # 6. 插入 bm_media_replacement
  1285. if media_data:
  1286. media_values = []
  1287. for row in media_data:
  1288. old_doc_id = row['document_id']
  1289. new_doc_id = doc_id_mapping.get(old_doc_id, generate_snowflake_id())
  1290. media_values.append((
  1291. new_knowledge_id,
  1292. new_doc_id,
  1293. row['origin_text'],
  1294. row['media_type'],
  1295. row['media_url'],
  1296. date_now
  1297. ))
  1298. media_sql = """
  1299. INSERT INTO bm_media_replacement (
  1300. knowledge_id, document_id, origin_text, media_type, media_url, create_time
  1301. ) VALUES (%s, %s, %s, %s, %s, %s)
  1302. """
  1303. cursor.executemany(media_sql, media_values)
  1304. media_count = len(media_values)
  1305. logger.info(f"插入媒体映射数据成功: {media_count} 条")
  1306. connection.commit()
  1307. return True, {
  1308. "message": "复制元数据成功",
  1309. "doc_id_mapping": doc_id_mapping,
  1310. "doc_count": doc_count,
  1311. "slice_count": slice_count,
  1312. "media_count": media_count
  1313. }
  1314. except Error as e:
  1315. connection.rollback()
  1316. logger.error(f"复制文档元数据失败: {e}")
  1317. return False, {"error": str(e)}
  1318. finally:
  1319. if cursor:
  1320. cursor.close()
  1321. if connection:
  1322. connection.close()
  1323. def query_slice_by_id(self, knowledge_id: str, slice_id: str):
  1324. """
  1325. 根据 knowledge_id 和 slice_id 查询单个切片数据
  1326. """
  1327. connection, info = self.get_connection()
  1328. if not connection:
  1329. return False, info
  1330. cursor = None
  1331. try:
  1332. cursor = connection.cursor(dictionary=True)
  1333. sql = """
  1334. SELECT slice_id, knowledge_id, document_id, slice_text, old_slice_text, slice_index
  1335. FROM slice_info WHERE knowledge_id = %s AND slice_id = %s
  1336. """
  1337. cursor.execute(sql, (knowledge_id, slice_id))
  1338. results = cursor.fetchall()
  1339. return True, results
  1340. except Error as e:
  1341. logger.error(f"查询 slice_info 出错: {e}")
  1342. return False, str(e)
  1343. finally:
  1344. if cursor:
  1345. cursor.close()
  1346. if connection:
  1347. connection.close()
  1348. def query_slice_by_knowledge_and_doc(self, knowledge_id: str, document_id: str):
  1349. """
  1350. 根据 knowledge_id 和 document_id 查询 slice_info 表中的切片数据
  1351. """
  1352. connection, info = self.get_connection()
  1353. if not connection:
  1354. return False, info
  1355. cursor = None
  1356. try:
  1357. cursor = connection.cursor(dictionary=True)
  1358. sql = """
  1359. SELECT slice_id, knowledge_id, document_id, slice_text, old_slice_text, slice_index
  1360. FROM slice_info
  1361. WHERE knowledge_id = %s AND document_id = %s
  1362. """
  1363. cursor.execute(sql, (knowledge_id, document_id))
  1364. results = cursor.fetchall()
  1365. logger.info(f"查询 slice_info 成功,共 {len(results)} 条记录")
  1366. return True, results
  1367. except Error as e:
  1368. logger.error(f"查询 slice_info 出错: {e}")
  1369. return False, str(e)
  1370. finally:
  1371. if cursor:
  1372. cursor.close()
  1373. if connection:
  1374. connection.close()
  1375. def update_slice_llm_fields(self, knowledge_id: str, slice_id: str, qa: str = None, question: str = None, summary: str = None):
  1376. """
  1377. 更新 slice_info 表中的 qa、question、summary 字段,值为 None 的字段不更新
  1378. 基于 knowledge_id 和 slice_id 的包含关系进行更新
  1379. """
  1380. connection, info = self.get_connection()
  1381. if not connection:
  1382. return False, info
  1383. cursor = None
  1384. try:
  1385. # 动态构建 SET 子句,只更新非 None 字段
  1386. set_parts = []
  1387. params = []
  1388. if qa is not None:
  1389. set_parts.append("qa = %s")
  1390. params.append(qa)
  1391. if question is not None:
  1392. set_parts.append("question = %s")
  1393. params.append(question)
  1394. if summary is not None:
  1395. set_parts.append("summary = %s")
  1396. params.append(summary)
  1397. if not set_parts:
  1398. return True, "no fields to update"
  1399. date_now = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
  1400. set_parts.append("update_time = %s")
  1401. params.append(date_now)
  1402. params.append(knowledge_id)
  1403. params.append(slice_id)
  1404. cursor = connection.cursor()
  1405. sql = f"UPDATE slice_info SET {', '.join(set_parts)} WHERE knowledge_id = %s AND slice_id = %s"
  1406. cursor.execute(sql, tuple(params))
  1407. connection.commit()
  1408. logger.info(f"更新切片 {slice_id} 的LLM字段成功")
  1409. return True, "success"
  1410. except Error as e:
  1411. connection.rollback()
  1412. logger.error(f"更新 slice_info LLM字段出错: {e}")
  1413. return False, str(e)
  1414. finally:
  1415. if cursor:
  1416. cursor.close()
  1417. if connection:
  1418. connection.close()