mirror of
https://git.mirrors.martin98.com/https://github.com/infiniflow/ragflow.git
synced 2025-04-22 14:10:01 +08:00
dd81c30976
### What problem does this PR solve? #6218 ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue)
561 lines
23 KiB
Python
561 lines
23 KiB
Python
#
|
|
# 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 elasticsearch import Elasticsearch, NotFoundError
|
|
from elasticsearch_dsl import UpdateByQuery, Q, Search, Index
|
|
from elastic_transport import ConnectionTimeout
|
|
from rag import settings
|
|
from rag.settings import TAG_FLD, PAGERANK_FLD
|
|
from rag.utils import singleton, get_float
|
|
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.es_conn')
|
|
|
|
|
|
@singleton
|
|
class ESConnection(DocStoreConnection):
|
|
def __init__(self):
|
|
self.info = {}
|
|
logger.info(f"Use Elasticsearch {settings.ES['hosts']} as the doc engine.")
|
|
for _ in range(ATTEMPT_TIME):
|
|
try:
|
|
self.es = Elasticsearch(
|
|
settings.ES["hosts"].split(","),
|
|
basic_auth=(settings.ES["username"], settings.ES[
|
|
"password"]) if "username" in settings.ES and "password" in settings.ES else None,
|
|
verify_certs=False,
|
|
timeout=600
|
|
)
|
|
if self.es:
|
|
self.info = self.es.info()
|
|
break
|
|
except Exception as e:
|
|
logger.warning(f"{str(e)}. Waiting Elasticsearch {settings.ES['hosts']} to be healthy.")
|
|
time.sleep(5)
|
|
if not self.es.ping():
|
|
msg = f"Elasticsearch {settings.ES['hosts']} is unhealthy in 120s."
|
|
logger.error(msg)
|
|
raise Exception(msg)
|
|
v = self.info.get("version", {"number": "8.11.3"})
|
|
v = v["number"].split(".")[0]
|
|
if int(v) < 8:
|
|
msg = f"Elasticsearch version must be greater than or equal to 8, current version: {v}"
|
|
logger.error(msg)
|
|
raise Exception(msg)
|
|
fp_mapping = os.path.join(get_project_base_directory(), "conf", "mapping.json")
|
|
if not os.path.exists(fp_mapping):
|
|
msg = f"Elasticsearch mapping file not found at {fp_mapping}"
|
|
logger.error(msg)
|
|
raise Exception(msg)
|
|
self.mapping = json.load(open(fp_mapping, "r"))
|
|
logger.info(f"Elasticsearch {settings.ES['hosts']} is healthy.")
|
|
|
|
"""
|
|
Database operations
|
|
"""
|
|
|
|
def dbType(self) -> str:
|
|
return "elasticsearch"
|
|
|
|
def health(self) -> dict:
|
|
health_dict = dict(self.es.cluster.health())
|
|
health_dict["type"] = "elasticsearch"
|
|
return health_dict
|
|
|
|
"""
|
|
Table operations
|
|
"""
|
|
|
|
def createIdx(self, indexName: str, knowledgebaseId: str, vectorSize: int):
|
|
if self.indexExist(indexName, knowledgebaseId):
|
|
return True
|
|
try:
|
|
from elasticsearch.client import IndicesClient
|
|
return IndicesClient(self.es).create(index=indexName,
|
|
settings=self.mapping["settings"],
|
|
mappings=self.mapping["mappings"])
|
|
except Exception:
|
|
logger.exception("ESConnection.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.es.indices.delete(index=indexName, allow_no_indices=True)
|
|
except NotFoundError:
|
|
pass
|
|
except Exception:
|
|
logger.exception("ESConnection.deleteIdx error %s" % (indexName))
|
|
|
|
def indexExist(self, indexName: str, knowledgebaseId: str = None) -> bool:
|
|
s = Index(indexName, self.es)
|
|
for i in range(ATTEMPT_TIME):
|
|
try:
|
|
return s.exists()
|
|
except Exception as e:
|
|
logger.exception("ESConnection.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://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl.html
|
|
"""
|
|
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 = get_float(weights.split(",")[1])
|
|
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
|
|
|
|
elif isinstance(m, MatchDenseExpr):
|
|
assert (bqry is not None)
|
|
similarity = 0.0
|
|
if "similarity" in m.extra_options:
|
|
similarity = m.extra_options["similarity"]
|
|
s = s.knn(m.vector_column_name,
|
|
m.topn,
|
|
m.topn * 2,
|
|
query_vector=list(m.embedding_data),
|
|
filter=bqry.to_dict(),
|
|
similarity=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)
|
|
|
|
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"ESConnection.search {str(indexNames)} query: " + json.dumps(q))
|
|
|
|
for i in range(ATTEMPT_TIME):
|
|
try:
|
|
#print(json.dumps(q, ensure_ascii=False))
|
|
res = self.es.search(index=indexNames,
|
|
body=q,
|
|
timeout="600s",
|
|
# search_type="dfs_query_then_fetch",
|
|
track_total_hits=True,
|
|
_source=True)
|
|
if str(res.get("timed_out", "")).lower() == "true":
|
|
raise Exception("Es Timeout.")
|
|
logger.debug(f"ESConnection.search {str(indexNames)} res: " + str(res))
|
|
return res
|
|
except Exception as e:
|
|
logger.exception(f"ESConnection.search {str(indexNames)} query: " + str(q))
|
|
if str(e).find("Timeout") > 0:
|
|
continue
|
|
raise e
|
|
logger.error("ESConnection.search timeout for 3 times!")
|
|
raise Exception("ESConnection.search timeout.")
|
|
|
|
def get(self, chunkId: str, indexName: str, knowledgebaseIds: list[str]) -> dict | None:
|
|
for i in range(ATTEMPT_TIME):
|
|
try:
|
|
res = self.es.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"ESConnection.get({chunkId}) got exception")
|
|
if str(e).find("Timeout") > 0:
|
|
continue
|
|
raise e
|
|
logger.error("ESConnection.get timeout for 3 times!")
|
|
raise Exception("ESConnection.get timeout.")
|
|
|
|
def insert(self, documents: list[dict], indexName: str, knowledgebaseId: str = None) -> list[str]:
|
|
# Refers to https://www.elastic.co/guide/en/elasticsearch/reference/current/docs-bulk.html
|
|
operations = []
|
|
for d in documents:
|
|
assert "_id" not in d
|
|
assert "id" in d
|
|
d_copy = copy.deepcopy(d)
|
|
d_copy["kb_id"] = knowledgebaseId
|
|
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.es.bulk(index=(indexName), operations=operations,
|
|
refresh=False, timeout="60s")
|
|
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("ESConnection.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)
|
|
condition["kb_id"] = knowledgebaseId
|
|
if "id" in condition and isinstance(condition["id"], str):
|
|
# update specific single document
|
|
chunkId = condition["id"]
|
|
for i in range(ATTEMPT_TIME):
|
|
for k in doc.keys():
|
|
if "feas" != k.split("_")[-1]:
|
|
continue
|
|
try:
|
|
self.es.update(index=indexName, id=chunkId, script=f"ctx._source.remove(\"{k}\");")
|
|
except Exception:
|
|
logger.exception(f"ESConnection.update(index={indexName}, id={chunkId}, doc={json.dumps(condition, ensure_ascii=False)}) got exception")
|
|
try:
|
|
self.es.update(index=indexName, id=chunkId, doc=doc)
|
|
return True
|
|
except Exception as e:
|
|
logger.exception(
|
|
f"ESConnection.update(index={indexName}, id={chunkId}, 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.es).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("ESConnection.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
|
|
condition["kb_id"] = knowledgebaseId
|
|
if "id" in condition:
|
|
chunk_ids = condition["id"]
|
|
if not isinstance(chunk_ids, list):
|
|
chunk_ids = [chunk_ids]
|
|
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("ESConnection.delete query: " + json.dumps(qry.to_dict()))
|
|
for _ in range(ATTEMPT_TIME):
|
|
try:
|
|
#print(Search().query(qry).to_dict(), flush=True)
|
|
res = self.es.delete_by_query(
|
|
index=indexName,
|
|
body=Search().query(qry).to_dict(),
|
|
refresh=True)
|
|
return res["deleted"]
|
|
except Exception as e:
|
|
logger.warning("ESConnection.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"ESConnection.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"ESConnection.sql to es: {sql}")
|
|
|
|
for i in range(ATTEMPT_TIME):
|
|
try:
|
|
res = self.es.sql.query(body={"query": sql, "fetch_size": fetch_size}, format=format,
|
|
request_timeout="2s")
|
|
return res
|
|
except ConnectionTimeout:
|
|
logger.exception("ESConnection.sql timeout")
|
|
continue
|
|
except Exception:
|
|
logger.exception("ESConnection.sql got exception")
|
|
return None
|
|
logger.error("ESConnection.sql timeout for 3 times!")
|
|
return None
|