chore/perf: Remove old SRC level log env vars with no impact (#20045)

* Update openai.py

* Update env.py

* Merge pull request open-webui#19030 from open-webui/dev (#119)

Co-authored-by: Tim Baek <tim@openwebui.com>
Co-authored-by: Claude <noreply@anthropic.com>

---------

Co-authored-by: Tim Baek <tim@openwebui.com>
Co-authored-by: Claude <noreply@anthropic.com>

backend/open_webui/retrieval/vector/dbs/chroma.py

@@ -24,10 +24,8 @@ from open_webui.config import (
     CHROMA_CLIENT_AUTH_PROVIDER,
     CHROMA_CLIENT_AUTH_CREDENTIALS,
 )
-from open_webui.env import SRC_LOG_LEVELS
 
 log = logging.getLogger(__name__)
-log.setLevel(SRC_LOG_LEVELS["RAG"])
 
 
 class ChromaClient(VectorDBBase):

backend/open_webui/retrieval/vector/dbs/milvus.py

@@ -25,10 +25,8 @@ from open_webui.config import (
     MILVUS_DISKANN_MAX_DEGREE,
     MILVUS_DISKANN_SEARCH_LIST_SIZE,
 )
-from open_webui.env import SRC_LOG_LEVELS
 
 log = logging.getLogger(__name__)
-log.setLevel(SRC_LOG_LEVELS["RAG"])
 
 
 class MilvusClient(VectorDBBase):

backend/open_webui/retrieval/vector/dbs/milvus_multitenancy.py

@@ -12,7 +12,6 @@ from open_webui.config import (
     MILVUS_HNSW_EFCONSTRUCTION,
     MILVUS_IVF_FLAT_NLIST,
 )
-from open_webui.env import SRC_LOG_LEVELS
 from open_webui.retrieval.vector.main import (
     GetResult,
     SearchResult,
@@ -29,7 +28,6 @@ from pymilvus import (
 )
 
 log = logging.getLogger(__name__)
-log.setLevel(SRC_LOG_LEVELS["RAG"])
 
 RESOURCE_ID_FIELD = "resource_id"
 

backend/open_webui/retrieval/vector/dbs/oracle23ai.py

@@ -55,10 +55,8 @@ from open_webui.config import (
     ORACLE_DB_POOL_MAX,
     ORACLE_DB_POOL_INCREMENT,
 )
-from open_webui.env import SRC_LOG_LEVELS
 
 log = logging.getLogger(__name__)
-log.setLevel(SRC_LOG_LEVELS["RAG"])
 
 
 class Oracle23aiClient(VectorDBBase):

backend/open_webui/retrieval/vector/dbs/pgvector.py

@@ -51,7 +51,6 @@ from open_webui.config import (
     PGVECTOR_USE_HALFVEC,
 )
 
-from open_webui.env import SRC_LOG_LEVELS
 
 VECTOR_LENGTH = PGVECTOR_INITIALIZE_MAX_VECTOR_LENGTH
 USE_HALFVEC = PGVECTOR_USE_HALFVEC
@@ -61,7 +60,6 @@ VECTOR_OPCLASS = "halfvec_cosine_ops" if USE_HALFVEC else "vector_cosine_ops"
 Base = declarative_base()
 
 log = logging.getLogger(__name__)
-log.setLevel(SRC_LOG_LEVELS["RAG"])
 
 
 def pgcrypto_encrypt(val, key):

backend/open_webui/retrieval/vector/dbs/pinecone.py

@@ -31,7 +31,6 @@ from open_webui.config import (
     PINECONE_METRIC,
     PINECONE_CLOUD,
 )
-from open_webui.env import SRC_LOG_LEVELS
 from open_webui.retrieval.vector.utils import process_metadata
 
 
@@ -39,7 +38,6 @@ NO_LIMIT = 10000  # Reasonable limit to avoid overwhelming the system
 BATCH_SIZE = 100  # Recommended batch size for Pinecone operations
 
 log = logging.getLogger(__name__)
-log.setLevel(SRC_LOG_LEVELS["RAG"])
 
 
 class PineconeClient(VectorDBBase):

backend/open_webui/retrieval/vector/dbs/qdrant.py

@@ -22,12 +22,10 @@ from open_webui.config import (
     QDRANT_TIMEOUT,
     QDRANT_HNSW_M,
 )
-from open_webui.env import SRC_LOG_LEVELS
 
 NO_LIMIT = 999999999
 
 log = logging.getLogger(__name__)
-log.setLevel(SRC_LOG_LEVELS["RAG"])
 
 
 class QdrantClient(VectorDBBase):

backend/open_webui/retrieval/vector/dbs/qdrant_multitenancy.py

@@ -13,7 +13,6 @@ from open_webui.config import (
     QDRANT_TIMEOUT,
     QDRANT_HNSW_M,
 )
-from open_webui.env import SRC_LOG_LEVELS
 from open_webui.retrieval.vector.main import (
     GetResult,
     SearchResult,
@@ -30,7 +29,6 @@ TENANT_ID_FIELD = "tenant_id"
 DEFAULT_DIMENSION = 384
 
 log = logging.getLogger(__name__)
-log.setLevel(SRC_LOG_LEVELS["RAG"])
 
 
 def _tenant_filter(tenant_id: str) -> models.FieldCondition:

backend/open_webui/retrieval/vector/dbs/s3vector.py

@@ -6,13 +6,11 @@ from open_webui.retrieval.vector.main import (
     SearchResult,
 )
 from open_webui.config import S3_VECTOR_BUCKET_NAME, S3_VECTOR_REGION
-from open_webui.env import SRC_LOG_LEVELS
 from typing import List, Optional, Dict, Any, Union
 import logging
 import boto3
 
 log = logging.getLogger(__name__)
-log.setLevel(SRC_LOG_LEVELS["RAG"])
 
 
 class S3VectorClient(VectorDBBase):