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from open_webui.retrieval.vector.main import VectorDBBase
from open_webui.retrieval.vector.type import VectorType
from open_webui.config import (
VECTOR_DB,
ENABLE_QDRANT_MULTITENANCY_MODE,
ENABLE_MILVUS_MULTITENANCY_MODE,
)
class Vector:
@staticmethod
def get_vector(vector_type: str) -> VectorDBBase:
"""
get vector db instance by vector type
"""
match vector_type:
case VectorType.MILVUS:
if ENABLE_MILVUS_MULTITENANCY_MODE:
from open_webui.retrieval.vector.dbs.milvus_multitenancy import (
MilvusClient,
)
return MilvusClient()
else:
from open_webui.retrieval.vector.dbs.milvus import MilvusClient
return MilvusClient()
case VectorType.QDRANT:
if ENABLE_QDRANT_MULTITENANCY_MODE:
from open_webui.retrieval.vector.dbs.qdrant_multitenancy import (
QdrantClient,
)
return QdrantClient()
else:
from open_webui.retrieval.vector.dbs.qdrant import QdrantClient
return QdrantClient()
case VectorType.PINECONE:
from open_webui.retrieval.vector.dbs.pinecone import PineconeClient
return PineconeClient()
case VectorType.S3VECTOR:
from open_webui.retrieval.vector.dbs.s3vector import S3VectorClient
return S3VectorClient()
case VectorType.OPENSEARCH:
from open_webui.retrieval.vector.dbs.opensearch import OpenSearchClient
return OpenSearchClient()
case VectorType.PGVECTOR:
from open_webui.retrieval.vector.dbs.pgvector import PgvectorClient
return PgvectorClient()
case VectorType.ELASTICSEARCH:
from open_webui.retrieval.vector.dbs.elasticsearch import (
ElasticsearchClient,
)
return ElasticsearchClient()
case VectorType.CHROMA:
from open_webui.retrieval.vector.dbs.chroma import ChromaClient
return ChromaClient()
case VectorType.ORACLE23AI:
from open_webui.retrieval.vector.dbs.oracle23ai import Oracle23aiClient
return Oracle23aiClient()
case _:
raise ValueError(f"Unsupported vector type: {vector_type}")
VECTOR_DB_CLIENT = Vector.get_vector(VECTOR_DB)
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