- #
 - #  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
 - #
 - #  Licensed under the Apache License, Version 2.0 (the "License");
 - #  you may not use this file except in compliance with the License.
 - #  You may obtain a copy of the License at
 - #
 - #      http://www.apache.org/licenses/LICENSE-2.0
 - #
 - #  Unless required by applicable law or agreed to in writing, software
 - #  distributed under the License is distributed on an "AS IS" BASIS,
 - #  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 - #  See the License for the specific language governing permissions and
 - #  limitations under the License.
 - #
 - 
 - import logging
 - import re
 - import json
 - import time
 - import os
 - 
 - import copy
 - from opensearchpy import OpenSearch, NotFoundError
 - from opensearchpy import UpdateByQuery, Q, Search, Index
 - from opensearchpy import ConnectionTimeout
 - from rag import settings
 - from rag.settings import TAG_FLD, PAGERANK_FLD
 - from rag.utils import singleton
 - from api.utils.file_utils import get_project_base_directory
 - from rag.utils.doc_store_conn import DocStoreConnection, MatchExpr, OrderByExpr, MatchTextExpr, MatchDenseExpr, \
 -     FusionExpr
 - from rag.nlp import is_english, rag_tokenizer
 - 
 - ATTEMPT_TIME = 2
 - 
 - logger = logging.getLogger('ragflow.opensearch_conn')
 - 
 - 
 - @singleton
 - class OSConnection(DocStoreConnection):
 -     def __init__(self):
 -         self.info = {}
 -         logger.info(f"Use OpenSearch {settings.OS['hosts']} as the doc engine.")
 -         for _ in range(ATTEMPT_TIME):
 -             try:
 -                 self.os = OpenSearch(
 -                     settings.OS["hosts"].split(","),
 -                     http_auth=(settings.OS["username"], settings.OS[
 -                         "password"]) if "username" in settings.OS and "password" in settings.OS else None,
 -                     verify_certs=False,
 -                     timeout=600
 -                 )
 -                 if self.os:
 -                     self.info = self.os.info()
 -                     break
 -             except Exception as e:
 -                 logger.warning(f"{str(e)}. Waiting OpenSearch {settings.OS['hosts']} to be healthy.")
 -                 time.sleep(5)
 -         if not self.os.ping():
 -             msg = f"OpenSearch {settings.OS['hosts']} is unhealthy in 120s."
 -             logger.error(msg)
 -             raise Exception(msg)
 -         v = self.info.get("version", {"number": "2.18.0"})
 -         v = v["number"].split(".")[0]
 -         if int(v) < 2:
 -             msg = f"OpenSearch version must be greater than or equal to 2, current version: {v}"
 -             logger.error(msg)
 -             raise Exception(msg)
 -         fp_mapping = os.path.join(get_project_base_directory(), "conf", "os_mapping.json")
 -         if not os.path.exists(fp_mapping):
 -             msg = f"OpenSearch mapping file not found at {fp_mapping}"
 -             logger.error(msg)
 -             raise Exception(msg)
 -         self.mapping = json.load(open(fp_mapping, "r"))
 -         logger.info(f"OpenSearch {settings.OS['hosts']} is healthy.")
 - 
 -     """
 -     Database operations
 -     """
 - 
 -     def dbType(self) -> str:
 -         return "opensearch"
 - 
 -     def health(self) -> dict:
 -         health_dict = dict(self.os.cluster.health())
 -         health_dict["type"] = "opensearch"
 -         return health_dict
 - 
 -     """
 -     Table operations
 -     """
 - 
 -     def createIdx(self, indexName: str, knowledgebaseId: str, vectorSize: int):
 -         if self.indexExist(indexName, knowledgebaseId):
 -             return True
 -         try:
 -             from opensearchpy.client import IndicesClient
 -             return IndicesClient(self.os).create(index=indexName,
 -                                                  body=self.mapping)
 -         except Exception:
 -             logger.exception("OSConnection.createIndex error %s" % (indexName))
 - 
 -     def deleteIdx(self, indexName: str, knowledgebaseId: str):
 -         if len(knowledgebaseId) > 0:
 -             # The index need to be alive after any kb deletion since all kb under this tenant are in one index.
 -             return
 -         try:
 -             self.os.indices.delete(index=indexName, allow_no_indices=True)
 -         except NotFoundError:
 -             pass
 -         except Exception:
 -             logger.exception("OSConnection.deleteIdx error %s" % (indexName))
 - 
 -     def indexExist(self, indexName: str, knowledgebaseId: str = None) -> bool:
 -         s = Index(indexName, self.os)
 -         for i in range(ATTEMPT_TIME):
 -             try:
 -                 return s.exists()
 -             except Exception as e:
 -                 logger.exception("OSConnection.indexExist got exception")
 -                 if str(e).find("Timeout") > 0 or str(e).find("Conflict") > 0:
 -                     continue
 -                 break
 -         return False
 - 
 -     """
 -     CRUD operations
 -     """
 - 
 -     def search(
 -             self, selectFields: list[str],
 -             highlightFields: list[str],
 -             condition: dict,
 -             matchExprs: list[MatchExpr],
 -             orderBy: OrderByExpr,
 -             offset: int,
 -             limit: int,
 -             indexNames: str | list[str],
 -             knowledgebaseIds: list[str],
 -             aggFields: list[str] = [],
 -             rank_feature: dict | None = None
 -     ):
 -         """
 -         Refers to https://github.com/opensearch-project/opensearch-py/blob/main/guides/dsl.md
 -         """
 -         use_knn = False
 -         if isinstance(indexNames, str):
 -             indexNames = indexNames.split(",")
 -         assert isinstance(indexNames, list) and len(indexNames) > 0
 -         assert "_id" not in condition
 - 
 -         bqry = Q("bool", must=[])
 -         condition["kb_id"] = knowledgebaseIds
 -         for k, v in condition.items():
 -             if k == "available_int":
 -                 if v == 0:
 -                     bqry.filter.append(Q("range", available_int={"lt": 1}))
 -                 else:
 -                     bqry.filter.append(
 -                         Q("bool", must_not=Q("range", available_int={"lt": 1})))
 -                 continue
 -             if not v:
 -                 continue
 -             if isinstance(v, list):
 -                 bqry.filter.append(Q("terms", **{k: v}))
 -             elif isinstance(v, str) or isinstance(v, int):
 -                 bqry.filter.append(Q("term", **{k: v}))
 -             else:
 -                 raise Exception(
 -                     f"Condition `{str(k)}={str(v)}` value type is {str(type(v))}, expected to be int, str or list.")
 - 
 -         s = Search()
 -         vector_similarity_weight = 0.5
 -         for m in matchExprs:
 -             if isinstance(m, FusionExpr) and m.method == "weighted_sum" and "weights" in m.fusion_params:
 -                 assert len(matchExprs) == 3 and isinstance(matchExprs[0], MatchTextExpr) and isinstance(matchExprs[1],
 -                                                                                                         MatchDenseExpr) and isinstance(
 -                     matchExprs[2], FusionExpr)
 -                 weights = m.fusion_params["weights"]
 -                 vector_similarity_weight = float(weights.split(",")[1])
 -         knn_query = {}
 -         for m in matchExprs:
 -             if isinstance(m, MatchTextExpr):
 -                 minimum_should_match = m.extra_options.get("minimum_should_match", 0.0)
 -                 if isinstance(minimum_should_match, float):
 -                     minimum_should_match = str(int(minimum_should_match * 100)) + "%"
 -                 bqry.must.append(Q("query_string", fields=m.fields,
 -                                    type="best_fields", query=m.matching_text,
 -                                    minimum_should_match=minimum_should_match,
 -                                    boost=1))
 -                 bqry.boost = 1.0 - vector_similarity_weight
 -                 
 -             # Elasticsearch has the encapsulation of KNN_search in python sdk
 -             # while the Python SDK for OpenSearch does not provide encapsulation for KNN_search,
 -             # the following codes implement KNN_search in OpenSearch using DSL
 -             # Besides, Opensearch's DSL for KNN_search query syntax differs from that in Elasticsearch, I also made some adaptions for it
 -             elif isinstance(m, MatchDenseExpr):
 -                 assert (bqry is not None)
 -                 similarity = 0.0
 -                 if "similarity" in m.extra_options:
 -                     similarity = m.extra_options["similarity"]
 -                 use_knn = True
 -                 vector_column_name = m.vector_column_name
 -                 knn_query[vector_column_name] = {}
 -                 knn_query[vector_column_name]["vector"] = list(m.embedding_data)
 -                 knn_query[vector_column_name]["k"] = m.topn
 -                 knn_query[vector_column_name]["filter"] = bqry.to_dict()
 -                 knn_query[vector_column_name]["boost"] = similarity
 - 
 -         if bqry and rank_feature:
 -             for fld, sc in rank_feature.items():
 -                 if fld != PAGERANK_FLD:
 -                     fld = f"{TAG_FLD}.{fld}"
 -                 bqry.should.append(Q("rank_feature", field=fld, linear={}, boost=sc))
 - 
 -         if bqry:
 -             s = s.query(bqry)
 -         for field in highlightFields:
 -             s = s.highlight(field,force_source=True,no_match_size=30,require_field_match=False)
 - 
 -         if orderBy:
 -             orders = list()
 -             for field, order in orderBy.fields:
 -                 order = "asc" if order == 0 else "desc"
 -                 if field in ["page_num_int", "top_int"]:
 -                     order_info = {"order": order, "unmapped_type": "float",
 -                                   "mode": "avg", "numeric_type": "double"}
 -                 elif field.endswith("_int") or field.endswith("_flt"):
 -                     order_info = {"order": order, "unmapped_type": "float"}
 -                 else:
 -                     order_info = {"order": order, "unmapped_type": "text"}
 -                 orders.append({field: order_info})
 -             s = s.sort(*orders)
 - 
 -         for fld in aggFields:
 -             s.aggs.bucket(f'aggs_{fld}', 'terms', field=fld, size=1000000)
 - 
 -         if limit > 0:
 -             s = s[offset:offset + limit]
 -         q = s.to_dict()
 -         logger.debug(f"OSConnection.search {str(indexNames)} query: " + json.dumps(q))
 -         
 -         if use_knn:
 -             del q["query"]
 -             q["query"] = {"knn" : knn_query}
 - 
 -         for i in range(ATTEMPT_TIME):
 -             try:
 -                 res = self.os.search(index=indexNames,
 -                                      body=q,
 -                                      timeout=600,
 -                                      # search_type="dfs_query_then_fetch",
 -                                      track_total_hits=True,
 -                                      _source=True)
 -                 if str(res.get("timed_out", "")).lower() == "true":
 -                     raise Exception("OpenSearch Timeout.")
 -                 logger.debug(f"OSConnection.search {str(indexNames)} res: " + str(res))
 -                 return res
 -             except Exception as e:
 -                 logger.exception(f"OSConnection.search {str(indexNames)} query: " + str(q))
 -                 if str(e).find("Timeout") > 0:
 -                     continue
 -                 raise e
 -         logger.error("OSConnection.search timeout for 3 times!")
 -         raise Exception("OSConnection.search timeout.")
 - 
 -     def get(self, chunkId: str, indexName: str, knowledgebaseIds: list[str]) -> dict | None:
 -         for i in range(ATTEMPT_TIME):
 -             try:
 -                 res = self.os.get(index=(indexName),
 -                                   id=chunkId, _source=True, )
 -                 if str(res.get("timed_out", "")).lower() == "true":
 -                     raise Exception("Es Timeout.")
 -                 chunk = res["_source"]
 -                 chunk["id"] = chunkId
 -                 return chunk
 -             except NotFoundError:
 -                 return None
 -             except Exception as e:
 -                 logger.exception(f"OSConnection.get({chunkId}) got exception")
 -                 if str(e).find("Timeout") > 0:
 -                     continue
 -                 raise e
 -         logger.error("OSConnection.get timeout for 3 times!")
 -         raise Exception("OSConnection.get timeout.")
 - 
 -     def insert(self, documents: list[dict], indexName: str, knowledgebaseId: str = None) -> list[str]:
 -         # Refers to https://opensearch.org/docs/latest/api-reference/document-apis/bulk/
 -         operations = []
 -         for d in documents:
 -             assert "_id" not in d
 -             assert "id" in d
 -             d_copy = copy.deepcopy(d)
 -             meta_id = d_copy.pop("id", "")
 -             operations.append(
 -                 {"index": {"_index": indexName, "_id": meta_id}})
 -             operations.append(d_copy)
 - 
 -         res = []
 -         for _ in range(ATTEMPT_TIME):
 -             try:
 -                 res = []
 -                 r = self.os.bulk(index=(indexName), body=operations,
 -                                  refresh=False, timeout=60)
 -                 if re.search(r"False", str(r["errors"]), re.IGNORECASE):
 -                     return res
 - 
 -                 for item in r["items"]:
 -                     for action in ["create", "delete", "index", "update"]:
 -                         if action in item and "error" in item[action]:
 -                             res.append(str(item[action]["_id"]) + ":" + str(item[action]["error"]))
 -                 return res
 -             except Exception as e:
 -                 res.append(str(e))
 -                 logger.warning("OSConnection.insert got exception: " + str(e))
 -                 res = []
 -                 if re.search(r"(Timeout|time out)", str(e), re.IGNORECASE):
 -                     res.append(str(e))
 -                     time.sleep(3)
 -                     continue
 -         return res
 - 
 -     def update(self, condition: dict, newValue: dict, indexName: str, knowledgebaseId: str) -> bool:
 -         doc = copy.deepcopy(newValue)
 -         doc.pop("id", None)
 -         if "id" in condition and isinstance(condition["id"], str):
 -             # update specific single document
 -             chunkId = condition["id"]
 -             for i in range(ATTEMPT_TIME):
 -                 try:
 -                     self.os.update(index=indexName, id=chunkId, body=doc)
 -                     return True
 -                 except Exception as e:
 -                     logger.exception(
 -                         f"OSConnection.update(index={indexName}, id={id}, doc={json.dumps(condition, ensure_ascii=False)}) got exception")
 -                     if re.search(r"(timeout|connection)", str(e).lower()):
 -                         continue
 -                     break
 -             return False
 - 
 -         # update unspecific maybe-multiple documents
 -         bqry = Q("bool")
 -         for k, v in condition.items():
 -             if not isinstance(k, str) or not v:
 -                 continue
 -             if k == "exists":
 -                 bqry.filter.append(Q("exists", field=v))
 -                 continue
 -             if isinstance(v, list):
 -                 bqry.filter.append(Q("terms", **{k: v}))
 -             elif isinstance(v, str) or isinstance(v, int):
 -                 bqry.filter.append(Q("term", **{k: v}))
 -             else:
 -                 raise Exception(
 -                     f"Condition `{str(k)}={str(v)}` value type is {str(type(v))}, expected to be int, str or list.")
 -         scripts = []
 -         params = {}
 -         for k, v in newValue.items():
 -             if k == "remove":
 -                 if isinstance(v, str):
 -                     scripts.append(f"ctx._source.remove('{v}');")
 -                 if isinstance(v, dict):
 -                     for kk, vv in v.items():
 -                         scripts.append(f"int i=ctx._source.{kk}.indexOf(params.p_{kk});ctx._source.{kk}.remove(i);")
 -                         params[f"p_{kk}"] = vv
 -                 continue
 -             if k == "add":
 -                 if isinstance(v, dict):
 -                     for kk, vv in v.items():
 -                         scripts.append(f"ctx._source.{kk}.add(params.pp_{kk});")
 -                         params[f"pp_{kk}"] = vv.strip()
 -                 continue
 -             if (not isinstance(k, str) or not v) and k != "available_int":
 -                 continue
 -             if isinstance(v, str):
 -                 v = re.sub(r"(['\n\r]|\\.)", " ", v)
 -                 params[f"pp_{k}"] = v
 -                 scripts.append(f"ctx._source.{k}=params.pp_{k};")
 -             elif isinstance(v, int) or isinstance(v, float):
 -                 scripts.append(f"ctx._source.{k}={v};")
 -             elif isinstance(v, list):
 -                 scripts.append(f"ctx._source.{k}=params.pp_{k};")
 -                 params[f"pp_{k}"] = json.dumps(v, ensure_ascii=False)
 -             else:
 -                 raise Exception(
 -                     f"newValue `{str(k)}={str(v)}` value type is {str(type(v))}, expected to be int, str.")
 -         ubq = UpdateByQuery(
 -             index=indexName).using(
 -             self.os).query(bqry)
 -         ubq = ubq.script(source="".join(scripts), params=params)
 -         ubq = ubq.params(refresh=True)
 -         ubq = ubq.params(slices=5)
 -         ubq = ubq.params(conflicts="proceed")
 - 
 -         for _ in range(ATTEMPT_TIME):
 -             try:
 -                 _ = ubq.execute()
 -                 return True
 -             except Exception as e:
 -                 logger.error("OSConnection.update got exception: " + str(e) + "\n".join(scripts))
 -                 if re.search(r"(timeout|connection|conflict)", str(e).lower()):
 -                     continue
 -                 break
 -         return False
 - 
 -     def delete(self, condition: dict, indexName: str, knowledgebaseId: str) -> int:
 -         qry = None
 -         assert "_id" not in condition
 -         if "id" in condition:
 -             chunk_ids = condition["id"]
 -             if not isinstance(chunk_ids, list):
 -                 chunk_ids = [chunk_ids]
 -             if not chunk_ids:  # when chunk_ids is empty, delete all
 -                 qry = Q("match_all")
 -             else:
 -                 qry = Q("ids", values=chunk_ids)
 -         else:
 -             qry = Q("bool")
 -             for k, v in condition.items():
 -                 if k == "exists":
 -                     qry.filter.append(Q("exists", field=v))
 - 
 -                 elif k == "must_not":
 -                     if isinstance(v, dict):
 -                         for kk, vv in v.items():
 -                             if kk == "exists":
 -                                 qry.must_not.append(Q("exists", field=vv))
 - 
 -                 elif isinstance(v, list):
 -                     qry.must.append(Q("terms", **{k: v}))
 -                 elif isinstance(v, str) or isinstance(v, int):
 -                     qry.must.append(Q("term", **{k: v}))
 -                 else:
 -                     raise Exception("Condition value must be int, str or list.")
 -         logger.debug("OSConnection.delete query: " + json.dumps(qry.to_dict()))
 -         for _ in range(ATTEMPT_TIME):
 -             try:
 -                 #print(Search().query(qry).to_dict(), flush=True)
 -                 res = self.os.delete_by_query(
 -                     index=indexName,
 -                     body=Search().query(qry).to_dict(),
 -                     refresh=True)
 -                 return res["deleted"]
 -             except Exception as e:
 -                 logger.warning("OSConnection.delete got exception: " + str(e))
 -                 if re.search(r"(timeout|connection)", str(e).lower()):
 -                     time.sleep(3)
 -                     continue
 -                 if re.search(r"(not_found)", str(e), re.IGNORECASE):
 -                     return 0
 -         return 0
 - 
 -     """
 -     Helper functions for search result
 -     """
 - 
 -     def getTotal(self, res):
 -         if isinstance(res["hits"]["total"], type({})):
 -             return res["hits"]["total"]["value"]
 -         return res["hits"]["total"]
 - 
 -     def getChunkIds(self, res):
 -         return [d["_id"] for d in res["hits"]["hits"]]
 - 
 -     def __getSource(self, res):
 -         rr = []
 -         for d in res["hits"]["hits"]:
 -             d["_source"]["id"] = d["_id"]
 -             d["_source"]["_score"] = d["_score"]
 -             rr.append(d["_source"])
 -         return rr
 - 
 -     def getFields(self, res, fields: list[str]) -> dict[str, dict]:
 -         res_fields = {}
 -         if not fields:
 -             return {}
 -         for d in self.__getSource(res):
 -             m = {n: d.get(n) for n in fields if d.get(n) is not None}
 -             for n, v in m.items():
 -                 if isinstance(v, list):
 -                     m[n] = v
 -                     continue
 -                 if not isinstance(v, str):
 -                     m[n] = str(m[n])
 -                 # if n.find("tks") > 0:
 -                 #     m[n] = rmSpace(m[n])
 - 
 -             if m:
 -                 res_fields[d["id"]] = m
 -         return res_fields
 - 
 -     def getHighlight(self, res, keywords: list[str], fieldnm: str):
 -         ans = {}
 -         for d in res["hits"]["hits"]:
 -             hlts = d.get("highlight")
 -             if not hlts:
 -                 continue
 -             txt = "...".join([a for a in list(hlts.items())[0][1]])
 -             if not is_english(txt.split()):
 -                 ans[d["_id"]] = txt
 -                 continue
 - 
 -             txt = d["_source"][fieldnm]
 -             txt = re.sub(r"[\r\n]", " ", txt, flags=re.IGNORECASE | re.MULTILINE)
 -             txts = []
 -             for t in re.split(r"[.?!;\n]", txt):
 -                 for w in keywords:
 -                     t = re.sub(r"(^|[ .?/'\"\(\)!,:;-])(%s)([ .?/'\"\(\)!,:;-])" % re.escape(w), r"\1<em>\2</em>\3", t,
 -                                flags=re.IGNORECASE | re.MULTILINE)
 -                 if not re.search(r"<em>[^<>]+</em>", t, flags=re.IGNORECASE | re.MULTILINE):
 -                     continue
 -                 txts.append(t)
 -             ans[d["_id"]] = "...".join(txts) if txts else "...".join([a for a in list(hlts.items())[0][1]])
 - 
 -         return ans
 - 
 -     def getAggregation(self, res, fieldnm: str):
 -         agg_field = "aggs_" + fieldnm
 -         if "aggregations" not in res or agg_field not in res["aggregations"]:
 -             return list()
 -         bkts = res["aggregations"][agg_field]["buckets"]
 -         return [(b["key"], b["doc_count"]) for b in bkts]
 - 
 -     """
 -     SQL
 -     """
 - 
 -     def sql(self, sql: str, fetch_size: int, format: str):
 -         logger.debug(f"OSConnection.sql get sql: {sql}")
 -         sql = re.sub(r"[ `]+", " ", sql)
 -         sql = sql.replace("%", "")
 -         replaces = []
 -         for r in re.finditer(r" ([a-z_]+_l?tks)( like | ?= ?)'([^']+)'", sql):
 -             fld, v = r.group(1), r.group(3)
 -             match = " MATCH({}, '{}', 'operator=OR;minimum_should_match=30%') ".format(
 -                 fld, rag_tokenizer.fine_grained_tokenize(rag_tokenizer.tokenize(v)))
 -             replaces.append(
 -                 ("{}{}'{}'".format(
 -                     r.group(1),
 -                     r.group(2),
 -                     r.group(3)),
 -                  match))
 - 
 -         for p, r in replaces:
 -             sql = sql.replace(p, r, 1)
 -         logger.debug(f"OSConnection.sql to os: {sql}")
 - 
 -         for i in range(ATTEMPT_TIME):
 -             try:
 -                 res = self.os.sql.query(body={"query": sql, "fetch_size": fetch_size}, format=format,
 -                                         request_timeout="2s")
 -                 return res
 -             except ConnectionTimeout:
 -                 logger.exception("OSConnection.sql timeout")
 -                 continue
 -             except Exception:
 -                 logger.exception("OSConnection.sql got exception")
 -                 return None
 -         logger.error("OSConnection.sql timeout for 3 times!")
 -         return None
 
 
  |