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es_conn.py 18KB

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  1. import logging
  2. import re
  3. import json
  4. import time
  5. import os
  6. import copy
  7. from elasticsearch import Elasticsearch, NotFoundError
  8. from elasticsearch_dsl import UpdateByQuery, Q, Search, Index
  9. from elastic_transport import ConnectionTimeout
  10. from rag import settings
  11. from rag.utils import singleton
  12. from api.utils.file_utils import get_project_base_directory
  13. import polars as pl
  14. from rag.utils.doc_store_conn import DocStoreConnection, MatchExpr, OrderByExpr, MatchTextExpr, MatchDenseExpr, \
  15. FusionExpr
  16. from rag.nlp import is_english, rag_tokenizer
  17. @singleton
  18. class ESConnection(DocStoreConnection):
  19. def __init__(self):
  20. self.info = {}
  21. logging.info(f"Use Elasticsearch {settings.ES['hosts']} as the doc engine.")
  22. for _ in range(24):
  23. try:
  24. self.es = Elasticsearch(
  25. settings.ES["hosts"].split(","),
  26. basic_auth=(settings.ES["username"], settings.ES[
  27. "password"]) if "username" in settings.ES and "password" in settings.ES else None,
  28. verify_certs=False,
  29. timeout=600
  30. )
  31. if self.es:
  32. self.info = self.es.info()
  33. break
  34. except Exception as e:
  35. logging.warn(f"{str(e)}. Waiting Elasticsearch {settings.ES['hosts']} to be healthy.")
  36. time.sleep(5)
  37. if not self.es.ping():
  38. msg = f"Elasticsearch {settings.ES['hosts']} didn't become healthy in 120s."
  39. logging.error(msg)
  40. raise Exception(msg)
  41. v = self.info.get("version", {"number": "8.11.3"})
  42. v = v["number"].split(".")[0]
  43. if int(v) < 8:
  44. msg = f"Elasticsearch version must be greater than or equal to 8, current version: {v}"
  45. logging.error(msg)
  46. raise Exception(msg)
  47. fp_mapping = os.path.join(get_project_base_directory(), "conf", "mapping.json")
  48. if not os.path.exists(fp_mapping):
  49. msg = f"Elasticsearch mapping file not found at {fp_mapping}"
  50. logging.error(msg)
  51. raise Exception(msg)
  52. self.mapping = json.load(open(fp_mapping, "r"))
  53. logging.info(f"Elasticsearch {settings.ES['hosts']} is healthy.")
  54. """
  55. Database operations
  56. """
  57. def dbType(self) -> str:
  58. return "elasticsearch"
  59. def health(self) -> dict:
  60. return dict(self.es.cluster.health()) + {"type": "elasticsearch"}
  61. """
  62. Table operations
  63. """
  64. def createIdx(self, indexName: str, knowledgebaseId: str, vectorSize: int):
  65. if self.indexExist(indexName, knowledgebaseId):
  66. return True
  67. try:
  68. from elasticsearch.client import IndicesClient
  69. return IndicesClient(self.es).create(index=indexName,
  70. settings=self.mapping["settings"],
  71. mappings=self.mapping["mappings"])
  72. except Exception:
  73. logging.exception("ES create index error %s" % (indexName))
  74. def deleteIdx(self, indexName: str, knowledgebaseId: str):
  75. try:
  76. self.es.indices.delete(index=indexName, allow_no_indices=True)
  77. except NotFoundError:
  78. pass
  79. except Exception:
  80. logging.exception("ES delete index error %s" % (indexName))
  81. def indexExist(self, indexName: str, knowledgebaseId: str) -> bool:
  82. s = Index(indexName, self.es)
  83. for i in range(3):
  84. try:
  85. return s.exists()
  86. except Exception as e:
  87. logging.exception("ES indexExist")
  88. if str(e).find("Timeout") > 0 or str(e).find("Conflict") > 0:
  89. continue
  90. return False
  91. """
  92. CRUD operations
  93. """
  94. def search(self, selectFields: list[str], highlightFields: list[str], condition: dict, matchExprs: list[MatchExpr],
  95. orderBy: OrderByExpr, offset: int, limit: int, indexNames: str | list[str],
  96. knowledgebaseIds: list[str]) -> list[dict] | pl.DataFrame:
  97. """
  98. Refers to https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl.html
  99. """
  100. if isinstance(indexNames, str):
  101. indexNames = indexNames.split(",")
  102. assert isinstance(indexNames, list) and len(indexNames) > 0
  103. assert "_id" not in condition
  104. s = Search()
  105. bqry = None
  106. vector_similarity_weight = 0.5
  107. for m in matchExprs:
  108. if isinstance(m, FusionExpr) and m.method == "weighted_sum" and "weights" in m.fusion_params:
  109. assert len(matchExprs) == 3 and isinstance(matchExprs[0], MatchTextExpr) and isinstance(matchExprs[1],
  110. MatchDenseExpr) and isinstance(
  111. matchExprs[2], FusionExpr)
  112. weights = m.fusion_params["weights"]
  113. vector_similarity_weight = float(weights.split(",")[1])
  114. for m in matchExprs:
  115. if isinstance(m, MatchTextExpr):
  116. minimum_should_match = "0%"
  117. if "minimum_should_match" in m.extra_options:
  118. minimum_should_match = str(int(m.extra_options["minimum_should_match"] * 100)) + "%"
  119. bqry = Q("bool",
  120. must=Q("query_string", fields=m.fields,
  121. type="best_fields", query=m.matching_text,
  122. minimum_should_match=minimum_should_match,
  123. boost=1),
  124. boost=1.0 - vector_similarity_weight,
  125. )
  126. elif isinstance(m, MatchDenseExpr):
  127. assert (bqry is not None)
  128. similarity = 0.0
  129. if "similarity" in m.extra_options:
  130. similarity = m.extra_options["similarity"]
  131. s = s.knn(m.vector_column_name,
  132. m.topn,
  133. m.topn * 2,
  134. query_vector=list(m.embedding_data),
  135. filter=bqry.to_dict(),
  136. similarity=similarity,
  137. )
  138. condition["kb_id"] = knowledgebaseIds
  139. if condition:
  140. if not bqry:
  141. bqry = Q("bool", must=[])
  142. for k, v in condition.items():
  143. if not isinstance(k, str) or not v:
  144. continue
  145. if isinstance(v, list):
  146. bqry.filter.append(Q("terms", **{k: v}))
  147. elif isinstance(v, str) or isinstance(v, int):
  148. bqry.filter.append(Q("term", **{k: v}))
  149. else:
  150. raise Exception(
  151. f"Condition `{str(k)}={str(v)}` value type is {str(type(v))}, expected to be int, str or list.")
  152. if bqry:
  153. s = s.query(bqry)
  154. for field in highlightFields:
  155. s = s.highlight(field)
  156. if orderBy:
  157. orders = list()
  158. for field, order in orderBy.fields:
  159. order = "asc" if order == 0 else "desc"
  160. orders.append({field: {"order": order, "unmapped_type": "float",
  161. "mode": "avg", "numeric_type": "double"}})
  162. s = s.sort(*orders)
  163. if limit > 0:
  164. s = s[offset:limit]
  165. q = s.to_dict()
  166. print(json.dumps(q), flush=True)
  167. logging.debug("ESConnection.search [Q]: " + json.dumps(q))
  168. for i in range(3):
  169. try:
  170. res = self.es.search(index=indexNames,
  171. body=q,
  172. timeout="600s",
  173. # search_type="dfs_query_then_fetch",
  174. track_total_hits=True,
  175. _source=True)
  176. if str(res.get("timed_out", "")).lower() == "true":
  177. raise Exception("Es Timeout.")
  178. logging.debug("ESConnection.search res: " + str(res))
  179. return res
  180. except Exception as e:
  181. logging.exception("ES search [Q]: " + str(q))
  182. if str(e).find("Timeout") > 0:
  183. continue
  184. raise e
  185. logging.error("ES search timeout for 3 times!")
  186. raise Exception("ES search timeout.")
  187. def get(self, chunkId: str, indexName: str, knowledgebaseIds: list[str]) -> dict | None:
  188. for i in range(3):
  189. try:
  190. res = self.es.get(index=(indexName),
  191. id=chunkId, source=True, )
  192. if str(res.get("timed_out", "")).lower() == "true":
  193. raise Exception("Es Timeout.")
  194. if not res.get("found"):
  195. return None
  196. chunk = res["_source"]
  197. chunk["id"] = chunkId
  198. return chunk
  199. except Exception as e:
  200. logging.exception(f"ES get({chunkId}) got exception")
  201. if str(e).find("Timeout") > 0:
  202. continue
  203. raise e
  204. logging.error("ES search timeout for 3 times!")
  205. raise Exception("ES search timeout.")
  206. def insert(self, documents: list[dict], indexName: str, knowledgebaseId: str) -> list[str]:
  207. # Refers to https://www.elastic.co/guide/en/elasticsearch/reference/current/docs-bulk.html
  208. operations = []
  209. for d in documents:
  210. assert "_id" not in d
  211. assert "id" in d
  212. d_copy = copy.deepcopy(d)
  213. meta_id = d_copy.pop("id", "")
  214. operations.append(
  215. {"index": {"_index": indexName, "_id": meta_id}})
  216. operations.append(d_copy)
  217. res = []
  218. for _ in range(100):
  219. try:
  220. r = self.es.bulk(index=(indexName), operations=operations,
  221. refresh=False, timeout="600s")
  222. if re.search(r"False", str(r["errors"]), re.IGNORECASE):
  223. return res
  224. for item in r["items"]:
  225. for action in ["create", "delete", "index", "update"]:
  226. if action in item and "error" in item[action]:
  227. res.append(str(item[action]["_id"]) + ":" + str(item[action]["error"]))
  228. return res
  229. except Exception as e:
  230. logging.warning("Fail to bulk: " + str(e))
  231. if re.search(r"(Timeout|time out)", str(e), re.IGNORECASE):
  232. time.sleep(3)
  233. continue
  234. return res
  235. def update(self, condition: dict, newValue: dict, indexName: str, knowledgebaseId: str) -> bool:
  236. doc = copy.deepcopy(newValue)
  237. doc.pop("id", None)
  238. if "id" in condition and isinstance(condition["id"], str):
  239. # update specific single document
  240. chunkId = condition["id"]
  241. for i in range(3):
  242. try:
  243. self.es.update(index=indexName, id=chunkId, doc=doc)
  244. return True
  245. except Exception as e:
  246. logging.exception(
  247. f"ES failed to update(index={indexName}, id={id}, doc={json.dumps(condition, ensure_ascii=False)})")
  248. if str(e).find("Timeout") > 0:
  249. continue
  250. else:
  251. # update unspecific maybe-multiple documents
  252. bqry = Q("bool")
  253. for k, v in condition.items():
  254. if not isinstance(k, str) or not v:
  255. continue
  256. if isinstance(v, list):
  257. bqry.filter.append(Q("terms", **{k: v}))
  258. elif isinstance(v, str) or isinstance(v, int):
  259. bqry.filter.append(Q("term", **{k: v}))
  260. else:
  261. raise Exception(
  262. f"Condition `{str(k)}={str(v)}` value type is {str(type(v))}, expected to be int, str or list.")
  263. scripts = []
  264. for k, v in newValue.items():
  265. if not isinstance(k, str) or not v:
  266. continue
  267. if isinstance(v, str):
  268. scripts.append(f"ctx._source.{k} = '{v}'")
  269. elif isinstance(v, int):
  270. scripts.append(f"ctx._source.{k} = {v}")
  271. else:
  272. raise Exception(
  273. f"newValue `{str(k)}={str(v)}` value type is {str(type(v))}, expected to be int, str.")
  274. ubq = UpdateByQuery(
  275. index=indexName).using(
  276. self.es).query(bqry)
  277. ubq = ubq.script(source="; ".join(scripts))
  278. ubq = ubq.params(refresh=True)
  279. ubq = ubq.params(slices=5)
  280. ubq = ubq.params(conflicts="proceed")
  281. for i in range(3):
  282. try:
  283. _ = ubq.execute()
  284. return True
  285. except Exception as e:
  286. logging.error("ES update exception: " + str(e) + "[Q]:" + str(bqry.to_dict()))
  287. if str(e).find("Timeout") > 0 or str(e).find("Conflict") > 0:
  288. continue
  289. return False
  290. def delete(self, condition: dict, indexName: str, knowledgebaseId: str) -> int:
  291. qry = None
  292. assert "_id" not in condition
  293. if "id" in condition:
  294. chunk_ids = condition["id"]
  295. if not isinstance(chunk_ids, list):
  296. chunk_ids = [chunk_ids]
  297. qry = Q("ids", values=chunk_ids)
  298. else:
  299. qry = Q("bool")
  300. for k, v in condition.items():
  301. if isinstance(v, list):
  302. qry.must.append(Q("terms", **{k: v}))
  303. elif isinstance(v, str) or isinstance(v, int):
  304. qry.must.append(Q("term", **{k: v}))
  305. else:
  306. raise Exception("Condition value must be int, str or list.")
  307. logging.debug("ESConnection.delete [Q]: " + json.dumps(qry.to_dict()))
  308. for _ in range(10):
  309. try:
  310. res = self.es.delete_by_query(
  311. index=indexName,
  312. body=Search().query(qry).to_dict(),
  313. refresh=True)
  314. return res["deleted"]
  315. except Exception as e:
  316. logging.warning("Fail to delete: " + str(filter) + str(e))
  317. if re.search(r"(Timeout|time out)", str(e), re.IGNORECASE):
  318. time.sleep(3)
  319. continue
  320. if re.search(r"(not_found)", str(e), re.IGNORECASE):
  321. return 0
  322. return 0
  323. """
  324. Helper functions for search result
  325. """
  326. def getTotal(self, res):
  327. if isinstance(res["hits"]["total"], type({})):
  328. return res["hits"]["total"]["value"]
  329. return res["hits"]["total"]
  330. def getChunkIds(self, res):
  331. return [d["_id"] for d in res["hits"]["hits"]]
  332. def __getSource(self, res):
  333. rr = []
  334. for d in res["hits"]["hits"]:
  335. d["_source"]["id"] = d["_id"]
  336. d["_source"]["_score"] = d["_score"]
  337. rr.append(d["_source"])
  338. return rr
  339. def getFields(self, res, fields: list[str]) -> dict[str, dict]:
  340. res_fields = {}
  341. if not fields:
  342. return {}
  343. for d in self.__getSource(res):
  344. m = {n: d.get(n) for n in fields if d.get(n) is not None}
  345. for n, v in m.items():
  346. if isinstance(v, list):
  347. m[n] = v
  348. continue
  349. if not isinstance(v, str):
  350. m[n] = str(m[n])
  351. # if n.find("tks") > 0:
  352. # m[n] = rmSpace(m[n])
  353. if m:
  354. res_fields[d["id"]] = m
  355. return res_fields
  356. def getHighlight(self, res, keywords: list[str], fieldnm: str):
  357. ans = {}
  358. for d in res["hits"]["hits"]:
  359. hlts = d.get("highlight")
  360. if not hlts:
  361. continue
  362. txt = "...".join([a for a in list(hlts.items())[0][1]])
  363. if not is_english(txt.split(" ")):
  364. ans[d["_id"]] = txt
  365. continue
  366. txt = d["_source"][fieldnm]
  367. txt = re.sub(r"[\r\n]", " ", txt, flags=re.IGNORECASE | re.MULTILINE)
  368. txts = []
  369. for t in re.split(r"[.?!;\n]", txt):
  370. for w in keywords:
  371. t = re.sub(r"(^|[ .?/'\"\(\)!,:;-])(%s)([ .?/'\"\(\)!,:;-])" % re.escape(w), r"\1<em>\2</em>\3", t,
  372. flags=re.IGNORECASE | re.MULTILINE)
  373. if not re.search(r"<em>[^<>]+</em>", t, flags=re.IGNORECASE | re.MULTILINE):
  374. continue
  375. txts.append(t)
  376. ans[d["_id"]] = "...".join(txts) if txts else "...".join([a for a in list(hlts.items())[0][1]])
  377. return ans
  378. def getAggregation(self, res, fieldnm: str):
  379. agg_field = "aggs_" + fieldnm
  380. if "aggregations" not in res or agg_field not in res["aggregations"]:
  381. return list()
  382. bkts = res["aggregations"][agg_field]["buckets"]
  383. return [(b["key"], b["doc_count"]) for b in bkts]
  384. """
  385. SQL
  386. """
  387. def sql(self, sql: str, fetch_size: int, format: str):
  388. logging.debug(f"ESConnection.sql get sql: {sql}")
  389. sql = re.sub(r"[ `]+", " ", sql)
  390. sql = sql.replace("%", "")
  391. replaces = []
  392. for r in re.finditer(r" ([a-z_]+_l?tks)( like | ?= ?)'([^']+)'", sql):
  393. fld, v = r.group(1), r.group(3)
  394. match = " MATCH({}, '{}', 'operator=OR;minimum_should_match=30%') ".format(
  395. fld, rag_tokenizer.fine_grained_tokenize(rag_tokenizer.tokenize(v)))
  396. replaces.append(
  397. ("{}{}'{}'".format(
  398. r.group(1),
  399. r.group(2),
  400. r.group(3)),
  401. match))
  402. for p, r in replaces:
  403. sql = sql.replace(p, r, 1)
  404. logging.debug(f"ESConnection.sql to es: {sql}")
  405. for i in range(3):
  406. try:
  407. res = self.es.sql.query(body={"query": sql, "fetch_size": fetch_size}, format=format,
  408. request_timeout="2s")
  409. return res
  410. except ConnectionTimeout:
  411. logging.exception("ESConnection.sql timeout [Q]: " + sql)
  412. continue
  413. except Exception:
  414. logging.exception("ESConnection.sql got exception [Q]: " + sql)
  415. return None
  416. logging.error("ESConnection.sql timeout for 3 times!")
  417. return None