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Fix: fixed keyerror of azure openai for loaded and downloaded embedding models

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This commit is contained in:
weberm1 2025-06-09 18:12:30 +02:00
parent 608f8624cf
commit eae1829b42
1 changed files with 70 additions and 16 deletions
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86
backend/open_webui/config.py
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@ -347,6 +347,24 @@ MICROSOFT_CLIENT_TENANT_ID = PersistentConfig(
os.environ.get("MICROSOFT_CLIENT_TENANT_ID", ""),
)
MICROSOFT_CLIENT_LOGIN_BASE_URL = PersistentConfig(
"MICROSOFT_CLIENT_LOGIN_BASE_URL",
"oauth.microsoft.login_base_url",
os.environ.get(
"MICROSOFT_CLIENT_LOGIN_BASE_URL", "https://login.microsoftonline.com"
),
)
MICROSOFT_CLIENT_PICTURE_URL = PersistentConfig(
"MICROSOFT_CLIENT_PICTURE_URL",
"oauth.microsoft.picture_url",
os.environ.get(
"MICROSOFT_CLIENT_PICTURE_URL",
"https://graph.microsoft.com/v1.0/me/photo/$value",
),
)
MICROSOFT_OAUTH_SCOPE = PersistentConfig(
"MICROSOFT_OAUTH_SCOPE",
"oauth.microsoft.scope",
@ -542,7 +560,7 @@ def load_oauth_providers():
name="microsoft",
client_id=MICROSOFT_CLIENT_ID.value,
client_secret=MICROSOFT_CLIENT_SECRET.value,
server_metadata_url=f"https://login.microsoftonline.com/{MICROSOFT_CLIENT_TENANT_ID.value}/v2.0/.well-known/openid-configuration?appid={MICROSOFT_CLIENT_ID.value}",
server_metadata_url=f"{MICROSOFT_CLIENT_LOGIN_BASE_URL.value}/{MICROSOFT_CLIENT_TENANT_ID.value}/v2.0/.well-known/openid-configuration?appid={MICROSOFT_CLIENT_ID.value}",
client_kwargs={
"scope": MICROSOFT_OAUTH_SCOPE.value,
},
@ -551,7 +569,7 @@ def load_oauth_providers():
OAUTH_PROVIDERS["microsoft"] = {
"redirect_uri": MICROSOFT_REDIRECT_URI.value,
"picture_url": "https://graph.microsoft.com/v1.0/me/photo/$value",
"picture_url": MICROSOFT_CLIENT_PICTURE_URL.value,
"register": microsoft_oauth_register,
}
@ -1245,12 +1263,6 @@ if THREAD_POOL_SIZE is not None and isinstance(THREAD_POOL_SIZE, str):
THREAD_POOL_SIZE = None
def validate_cors_origins(origins):
for origin in origins:
if origin != "*":
validate_cors_origin(origin)
def validate_cors_origin(origin):
parsed_url = urlparse(origin)
@ -1270,16 +1282,17 @@ def validate_cors_origin(origin):
# To test CORS_ALLOW_ORIGIN locally, you can set something like
# CORS_ALLOW_ORIGIN=http://localhost:5173;http://localhost:8080
# in your .env file depending on your frontend port, 5173 in this case.
CORS_ALLOW_ORIGIN = os.environ.get(
"CORS_ALLOW_ORIGIN", "*;http://localhost:5173;http://localhost:8080"
).split(";")
CORS_ALLOW_ORIGIN = os.environ.get("CORS_ALLOW_ORIGIN", "*").split(";")
if "*" in CORS_ALLOW_ORIGIN:
if CORS_ALLOW_ORIGIN == ["*"]:
log.warning(
"\n\nWARNING: CORS_ALLOW_ORIGIN IS SET TO '*' - NOT RECOMMENDED FOR PRODUCTION DEPLOYMENTS.\n"
)
validate_cors_origins(CORS_ALLOW_ORIGIN)
else:
# You have to pick between a single wildcard or a list of origins.
# Doing both will result in CORS errors in the browser.
for origin in CORS_ALLOW_ORIGIN:
validate_cors_origin(origin)
class BannerModel(BaseModel):
@ -1812,6 +1825,13 @@ PGVECTOR_INITIALIZE_MAX_VECTOR_LENGTH = int(
os.environ.get("PGVECTOR_INITIALIZE_MAX_VECTOR_LENGTH", "1536")
)
PGVECTOR_PGCRYPTO = os.getenv("PGVECTOR_PGCRYPTO", "false").lower() == "true"
PGVECTOR_PGCRYPTO_KEY = os.getenv("PGVECTOR_PGCRYPTO_KEY", None)
if PGVECTOR_PGCRYPTO and not PGVECTOR_PGCRYPTO_KEY:
raise ValueError(
"PGVECTOR_PGCRYPTO is enabled but PGVECTOR_PGCRYPTO_KEY is not set. Please provide a valid key."
)
# Pinecone
PINECONE_API_KEY = os.environ.get("PINECONE_API_KEY", None)
PINECONE_ENVIRONMENT = os.environ.get("PINECONE_ENVIRONMENT", None)
@ -1972,6 +1992,40 @@ DOCLING_DO_PICTURE_DESCRIPTION = PersistentConfig(
os.getenv("DOCLING_DO_PICTURE_DESCRIPTION", "False").lower() == "true",
)
DOCLING_PICTURE_DESCRIPTION_MODE = PersistentConfig(
"DOCLING_PICTURE_DESCRIPTION_MODE",
"rag.docling_picture_description_mode",
os.getenv("DOCLING_PICTURE_DESCRIPTION_MODE", ""),
)
docling_picture_description_local = os.getenv("DOCLING_PICTURE_DESCRIPTION_LOCAL", "")
try:
docling_picture_description_local = json.loads(docling_picture_description_local)
except json.JSONDecodeError:
docling_picture_description_local = {}
DOCLING_PICTURE_DESCRIPTION_LOCAL = PersistentConfig(
"DOCLING_PICTURE_DESCRIPTION_LOCAL",
"rag.docling_picture_description_local",
docling_picture_description_local,
)
docling_picture_description_api = os.getenv("DOCLING_PICTURE_DESCRIPTION_API", "")
try:
docling_picture_description_api = json.loads(docling_picture_description_api)
except json.JSONDecodeError:
docling_picture_description_api = {}
DOCLING_PICTURE_DESCRIPTION_API = PersistentConfig(
"DOCLING_PICTURE_DESCRIPTION_API",
"rag.docling_picture_description_api",
docling_picture_description_api,
)
DOCUMENT_INTELLIGENCE_ENDPOINT = PersistentConfig(
"DOCUMENT_INTELLIGENCE_ENDPOINT",
"rag.document_intelligence_endpoint",
@ -2268,7 +2322,7 @@ DOWNLOADED_EMBEDDING_MODELS = PersistentConfig(
os.getenv("DOWNLOADED_EMBEDDING_MODELS", {"":["sentence-transformers/all-MiniLM-L6-v2"],
"openai":["text-embedding-3-small"],
"ollama":[],
"azure_openai_config": []})
"azure_openai": []})
)
DOWNLOADED_RERANKING_MODELS = PersistentConfig(
@ -2284,7 +2338,7 @@ LOADED_EMBEDDING_MODELS = PersistentConfig(
os.getenv("LOADED_EMBEDDING_MODELS", {"":["sentence-transformers/all-MiniLM-L6-v2"],
"openai":[],
"ollama":[],
"azure_openai_config": []})
"azure_openai": []})
)
LOADED_RERANKING_MODELS = PersistentConfig(