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fixed es bugs

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This commit is contained in:
ofek 2025-03-05 23:19:56 +02:00
parent 1639fbb544
commit a8f205213c
2 changed files with 137 additions and 95 deletions
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2
backend/open_webui/config.py
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@ -1553,7 +1553,7 @@ ELASTICSEARCH_USERNAME = os.environ.get("ELASTICSEARCH_USERNAME", None)
ELASTICSEARCH_PASSWORD = os.environ.get("ELASTICSEARCH_PASSWORD", None) ELASTICSEARCH_PASSWORD = os.environ.get("ELASTICSEARCH_PASSWORD", None)
ELASTICSEARCH_CLOUD_ID = os.environ.get("ELASTICSEARCH_CLOUD_ID", None) ELASTICSEARCH_CLOUD_ID = os.environ.get("ELASTICSEARCH_CLOUD_ID", None)
SSL_ASSERT_FINGERPRINT = os.environ.get("SSL_ASSERT_FINGERPRINT", None) SSL_ASSERT_FINGERPRINT = os.environ.get("SSL_ASSERT_FINGERPRINT", None)
ELASTICSEARCH_INDEX_PREFIX = os.environ.get("ELASTICSEARCH_INDEX_PREFIX", "open_webui_collections")
# Pgvector # Pgvector
PGVECTOR_DB_URL = os.environ.get("PGVECTOR_DB_URL", DATABASE_URL) PGVECTOR_DB_URL = os.environ.get("PGVECTOR_DB_URL", DATABASE_URL)
if VECTOR_DB == "pgvector" and not PGVECTOR_DB_URL.startswith("postgres"): if VECTOR_DB == "pgvector" and not PGVECTOR_DB_URL.startswith("postgres"):

182
backend/open_webui/retrieval/vector/dbs/elasticsearch.py
View File

@ -1,7 +1,7 @@
from elasticsearch import Elasticsearch, BadRequestError from elasticsearch import Elasticsearch, BadRequestError
from typing import Optional from typing import Optional
import ssl import ssl
from elasticsearch.helpers import bulk, scan from elasticsearch.helpers import bulk,scan
from open_webui.retrieval.vector.main import VectorItem, SearchResult, GetResult from open_webui.retrieval.vector.main import VectorItem, SearchResult, GetResult
from open_webui.config import ( from open_webui.config import (
ELASTICSEARCH_URL, ELASTICSEARCH_URL,
@ -10,10 +10,14 @@ from open_webui.config import (
ELASTICSEARCH_USERNAME, ELASTICSEARCH_USERNAME,
ELASTICSEARCH_PASSWORD, ELASTICSEARCH_PASSWORD,
ELASTICSEARCH_CLOUD_ID, ELASTICSEARCH_CLOUD_ID,
ELASTICSEARCH_INDEX_PREFIX,
SSL_ASSERT_FINGERPRINT, SSL_ASSERT_FINGERPRINT,
) )
class ElasticsearchClient: class ElasticsearchClient:
""" """
Important: Important:
@ -21,27 +25,22 @@ class ElasticsearchClient:
an index for each file but store it as a text field, while seperating to different index an index for each file but store it as a text field, while seperating to different index
baesd on the embedding length. baesd on the embedding length.
""" """
def __init__(self): def __init__(self):
self.index_prefix = "open_webui_collections" self.index_prefix = ELASTICSEARCH_INDEX_PREFIX
self.client = Elasticsearch( self.client = Elasticsearch(
hosts=[ELASTICSEARCH_URL], hosts=[ELASTICSEARCH_URL],
ca_certs=ELASTICSEARCH_CA_CERTS, ca_certs=ELASTICSEARCH_CA_CERTS,
api_key=ELASTICSEARCH_API_KEY, api_key=ELASTICSEARCH_API_KEY,
cloud_id=ELASTICSEARCH_CLOUD_ID, cloud_id=ELASTICSEARCH_CLOUD_ID,
basic_auth=( basic_auth=(ELASTICSEARCH_USERNAME,ELASTICSEARCH_PASSWORD) if ELASTICSEARCH_USERNAME and ELASTICSEARCH_PASSWORD else None,
(ELASTICSEARCH_USERNAME, ELASTICSEARCH_PASSWORD) ssl_assert_fingerprint=SSL_ASSERT_FINGERPRINT
if ELASTICSEARCH_USERNAME and ELASTICSEARCH_PASSWORD
else None
),
ssl_assert_fingerprint=SSL_ASSERT_FINGERPRINT,
)
# Status: works )
def _get_index_name(self, dimension: int) -> str: #Status: works
def _get_index_name(self,dimension:int)->str:
return f"{self.index_prefix}_d{str(dimension)}" return f"{self.index_prefix}_d{str(dimension)}"
# Status: works #Status: works
def _scan_result_to_get_result(self, result) -> GetResult: def _scan_result_to_get_result(self, result) -> GetResult:
if not result: if not result:
return None return None
@ -56,7 +55,7 @@ class ElasticsearchClient:
return GetResult(ids=[ids], documents=[documents], metadatas=[metadatas]) return GetResult(ids=[ids], documents=[documents], metadatas=[metadatas])
# Status: works #Status: works
def _result_to_get_result(self, result) -> GetResult: def _result_to_get_result(self, result) -> GetResult:
if not result["hits"]["hits"]: if not result["hits"]["hits"]:
return None return None
@ -71,7 +70,7 @@ class ElasticsearchClient:
return GetResult(ids=[ids], documents=[documents], metadatas=[metadatas]) return GetResult(ids=[ids], documents=[documents], metadatas=[metadatas])
# Status: works #Status: works
def _result_to_search_result(self, result) -> SearchResult: def _result_to_search_result(self, result) -> SearchResult:
ids = [] ids = []
distances = [] distances = []
@ -85,16 +84,22 @@ class ElasticsearchClient:
metadatas.append(hit["_source"].get("metadata")) metadatas.append(hit["_source"].get("metadata"))
return SearchResult( return SearchResult(
ids=[ids], ids=[ids], distances=[distances], documents=[documents], metadatas=[metadatas]
distances=[distances],
documents=[documents],
metadatas=[metadatas],
) )
#Status: works
# Status: works
def _create_index(self, dimension: int): def _create_index(self, dimension: int):
body = { body = {
"mappings": { "mappings": {
"dynamic_templates": [
{
"strings": {
"match_mapping_type": "string",
"mapping": {
"type": "keyword"
}
}
}
],
"properties": { "properties": {
"collection": {"type": "keyword"}, "collection": {"type": "keyword"},
"id": {"type": "keyword"}, "id": {"type": "keyword"},
@ -110,45 +115,58 @@ class ElasticsearchClient:
} }
} }
self.client.indices.create(index=self._get_index_name(dimension), body=body) self.client.indices.create(index=self._get_index_name(dimension), body=body)
#Status: works
# Status: works
def _create_batches(self, items: list[VectorItem], batch_size=100): def _create_batches(self, items: list[VectorItem], batch_size=100):
for i in range(0, len(items), batch_size): for i in range(0, len(items), batch_size):
yield items[i : min(i + batch_size, len(items))] yield items[i : min(i + batch_size,len(items))]
# Status: works #Status: works
def has_collection(self, collection_name) -> bool: def has_collection(self,collection_name) -> bool:
query_body = {"query": {"bool": {"filter": []}}} query_body = {"query": {"bool": {"filter": []}}}
query_body["query"]["bool"]["filter"].append( query_body["query"]["bool"]["filter"].append({"term": {"collection": collection_name}})
{"term": {"collection": collection_name}}
)
try: try:
result = self.client.count(index=f"{self.index_prefix}*", body=query_body) result = self.client.count(
index=f"{self.index_prefix}*",
body=query_body
)
return result.body["count"] > 0 return result.body["count"]>0
except Exception as e: except Exception as e:
return None return None
# @TODO: Make this delete a collection and not an index
def delete_colleciton(self, collection_name: str):
# TODO: fix this to include the dimension or a * prefix
# delete_collection here means delete a bunch of documents for an index.
# We are simply adapting to the norms of the other DBs.
self.client.indices.delete(index=self._get_collection_name(collection_name))
# Status: works
def delete_collection(self, collection_name: str):
query = {
"query": {
"term": {"collection": collection_name}
}
}
self.client.delete_by_query(index=f"{self.index_prefix}*", body=query)
#Status: works
def search( def search(
self, collection_name: str, vectors: list[list[float]], limit: int self, collection_name: str, vectors: list[list[float]], limit: int
) -> Optional[SearchResult]: ) -> Optional[SearchResult]:
query = { query = {
"size": limit, "size": limit,
"_source": ["text", "metadata"], "_source": [
"text",
"metadata"
],
"query": { "query": {
"script_score": { "script_score": {
"query": { "query": {
"bool": {"filter": [{"term": {"collection": collection_name}}]} "bool": {
"filter": [
{
"term": {
"collection": collection_name
}
}
]
}
}, },
"script": { "script": {
"source": "cosineSimilarity(params.vector, 'vector') + 1.0", "source": "cosineSimilarity(params.vector, 'vector') + 1.0",
@ -165,8 +183,7 @@ class ElasticsearchClient:
) )
return self._result_to_search_result(result) return self._result_to_search_result(result)
#Status: only tested halfwat
# Status: only tested halfwat
def query( def query(
self, collection_name: str, filter: dict, limit: Optional[int] = None self, collection_name: str, filter: dict, limit: Optional[int] = None
) -> Optional[GetResult]: ) -> Optional[GetResult]:
@ -180,9 +197,7 @@ class ElasticsearchClient:
for field, value in filter.items(): for field, value in filter.items():
query_body["query"]["bool"]["filter"].append({"term": {field: value}}) query_body["query"]["bool"]["filter"].append({"term": {field: value}})
query_body["query"]["bool"]["filter"].append( query_body["query"]["bool"]["filter"].append({"term": {"collection": collection_name}})
{"term": {"collection": collection_name}}
)
size = limit if limit else 10 size = limit if limit else 10
try: try:
@ -196,37 +211,43 @@ class ElasticsearchClient:
except Exception as e: except Exception as e:
return None return None
#Status: works
def _has_index(self,dimension:int):
return self.client.indices.exists(index=self._get_index_name(dimension=dimension))
# Status: works
def _has_index(self, dimension: int):
return self.client.indices.exists(
index=self._get_index_name(dimension=dimension)
)
def get_or_create_index(self, dimension: int): def get_or_create_index(self, dimension: int):
if not self._has_index(dimension=dimension): if not self._has_index(dimension=dimension):
self._create_index(dimension=dimension) self._create_index(dimension=dimension)
#Status: works
# Status: works
def get(self, collection_name: str) -> Optional[GetResult]: def get(self, collection_name: str) -> Optional[GetResult]:
# Get all the items in the collection. # Get all the items in the collection.
query = { query = {
"query": {"bool": {"filter": [{"term": {"collection": collection_name}}]}}, "query": {
"_source": ["text", "metadata"], "bool": {
"filter": [
{
"term": {
"collection": collection_name
} }
}
]
}
}, "_source": ["text", "metadata"]}
results = list(scan(self.client, index=f"{self.index_prefix}*", query=query)) results = list(scan(self.client, index=f"{self.index_prefix}*", query=query))
return self._scan_result_to_get_result(results) return self._scan_result_to_get_result(results)
# Status: works #Status: works
def insert(self, collection_name: str, items: list[VectorItem]): def insert(self, collection_name: str, items: list[VectorItem]):
if not self._has_index(dimension=len(items[0]["vector"])): if not self._has_index(dimension=len(items[0]["vector"])):
self._create_index(dimension=len(items[0]["vector"])) self._create_index(dimension=len(items[0]["vector"]))
for batch in self._create_batches(items): for batch in self._create_batches(items):
actions = [ actions = [
{ {
"_index": self._get_index_name(dimension=len(items[0]["vector"])), "_index":self._get_index_name(dimension=len(items[0]["vector"])),
"_id": item["id"], "_id": item["id"],
"_source": { "_source": {
"collection": collection_name, "collection": collection_name,
@ -237,36 +258,57 @@ class ElasticsearchClient:
} }
for item in batch for item in batch
] ]
bulk(self.client, actions) bulk(self.client,actions)
# Status: should work # Upsert documents using the update API with doc_as_upsert=True.
def upsert(self, collection_name: str, items: list[VectorItem]): def upsert(self, collection_name: str, items: list[VectorItem]):
if not self._has_index(dimension=len(items[0]["vector"])): if not self._has_index(dimension=len(items[0]["vector"])):
self._create_index(collection_name, dimension=len(items[0]["vector"])) self._create_index(dimension=len(items[0]["vector"]))
for batch in self._create_batches(items): for batch in self._create_batches(items):
actions = [ actions = [
{ {
"_index": self._get_index_name(dimension=len(items[0]["vector"])), "_op_type": "update",
"_index": self._get_index_name(dimension=len(item["vector"])),
"_id": item["id"], "_id": item["id"],
"_source": { "doc": {
"collection": collection_name,
"vector": item["vector"], "vector": item["vector"],
"text": item["text"], "text": item["text"],
"metadata": item["metadata"], "metadata": item["metadata"],
}, },
"doc_as_upsert": True,
} }
for item in batch for item in batch
] ]
self.client.bulk(actions) bulk(self.client,actions)
# TODO: This currently deletes by * which is not always supported in ElasticSearch.
# Need to read a bit before changing. Also, need to delete from a specific collection # Delete specific documents from a collection by filtering on both collection and document IDs.
def delete(self, collection_name: str, ids: list[str]): def delete(
# Assuming ID is unique across collections and indexes self,
actions = [ collection_name: str,
{"delete": {"_index": f"{self.index_prefix}*", "_id": id}} for id in ids ids: Optional[list[str]] = None,
filter: Optional[dict] = None,
):
query = {
"query": {
"bool": {
"filter": [
{"term": {"collection": collection_name}}
] ]
self.client.bulk(body=actions) }
}
}
#logic based on chromaDB
if ids:
query["query"]["bool"]["filter"].append({"terms": {"_id": ids}})
elif filter:
for field, value in filter.items():
query["query"]["bool"]["filter"].append({"term": {f"metadata.{field}": value}})
self.client.delete_by_query(index=f"{self.index_prefix}*", body=query)
def reset(self): def reset(self):
indices = self.client.indices.get(index=f"{self.index_prefix}*") indices = self.client.indices.get(index=f"{self.index_prefix}*")