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https://github.com/open-webui/open-webui
synced 2025-06-26 18:26:48 +00:00
Fix: fixed keyerror of azure openai for loaded and downloaded embedding models
This commit is contained in:
parent
608f8624cf
commit
eae1829b42
@ -347,6 +347,24 @@ MICROSOFT_CLIENT_TENANT_ID = PersistentConfig(
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os.environ.get("MICROSOFT_CLIENT_TENANT_ID", ""),
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os.environ.get("MICROSOFT_CLIENT_TENANT_ID", ""),
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)
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)
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MICROSOFT_CLIENT_LOGIN_BASE_URL = PersistentConfig(
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"MICROSOFT_CLIENT_LOGIN_BASE_URL",
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"oauth.microsoft.login_base_url",
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os.environ.get(
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"MICROSOFT_CLIENT_LOGIN_BASE_URL", "https://login.microsoftonline.com"
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),
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)
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MICROSOFT_CLIENT_PICTURE_URL = PersistentConfig(
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"MICROSOFT_CLIENT_PICTURE_URL",
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"oauth.microsoft.picture_url",
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os.environ.get(
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"MICROSOFT_CLIENT_PICTURE_URL",
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"https://graph.microsoft.com/v1.0/me/photo/$value",
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),
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)
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MICROSOFT_OAUTH_SCOPE = PersistentConfig(
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MICROSOFT_OAUTH_SCOPE = PersistentConfig(
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"MICROSOFT_OAUTH_SCOPE",
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"MICROSOFT_OAUTH_SCOPE",
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"oauth.microsoft.scope",
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"oauth.microsoft.scope",
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@ -542,7 +560,7 @@ def load_oauth_providers():
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name="microsoft",
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name="microsoft",
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client_id=MICROSOFT_CLIENT_ID.value,
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client_id=MICROSOFT_CLIENT_ID.value,
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client_secret=MICROSOFT_CLIENT_SECRET.value,
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client_secret=MICROSOFT_CLIENT_SECRET.value,
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server_metadata_url=f"https://login.microsoftonline.com/{MICROSOFT_CLIENT_TENANT_ID.value}/v2.0/.well-known/openid-configuration?appid={MICROSOFT_CLIENT_ID.value}",
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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}",
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client_kwargs={
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client_kwargs={
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"scope": MICROSOFT_OAUTH_SCOPE.value,
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"scope": MICROSOFT_OAUTH_SCOPE.value,
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},
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},
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@ -551,7 +569,7 @@ def load_oauth_providers():
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OAUTH_PROVIDERS["microsoft"] = {
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OAUTH_PROVIDERS["microsoft"] = {
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"redirect_uri": MICROSOFT_REDIRECT_URI.value,
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"redirect_uri": MICROSOFT_REDIRECT_URI.value,
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"picture_url": "https://graph.microsoft.com/v1.0/me/photo/$value",
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"picture_url": MICROSOFT_CLIENT_PICTURE_URL.value,
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"register": microsoft_oauth_register,
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"register": microsoft_oauth_register,
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}
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}
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@ -1245,12 +1263,6 @@ if THREAD_POOL_SIZE is not None and isinstance(THREAD_POOL_SIZE, str):
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THREAD_POOL_SIZE = None
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THREAD_POOL_SIZE = None
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def validate_cors_origins(origins):
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for origin in origins:
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if origin != "*":
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validate_cors_origin(origin)
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def validate_cors_origin(origin):
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def validate_cors_origin(origin):
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parsed_url = urlparse(origin)
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parsed_url = urlparse(origin)
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@ -1270,16 +1282,17 @@ def validate_cors_origin(origin):
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# To test CORS_ALLOW_ORIGIN locally, you can set something like
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# To test CORS_ALLOW_ORIGIN locally, you can set something like
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# CORS_ALLOW_ORIGIN=http://localhost:5173;http://localhost:8080
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# CORS_ALLOW_ORIGIN=http://localhost:5173;http://localhost:8080
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# in your .env file depending on your frontend port, 5173 in this case.
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# in your .env file depending on your frontend port, 5173 in this case.
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CORS_ALLOW_ORIGIN = os.environ.get(
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CORS_ALLOW_ORIGIN = os.environ.get("CORS_ALLOW_ORIGIN", "*").split(";")
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"CORS_ALLOW_ORIGIN", "*;http://localhost:5173;http://localhost:8080"
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).split(";")
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if "*" in CORS_ALLOW_ORIGIN:
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if CORS_ALLOW_ORIGIN == ["*"]:
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log.warning(
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log.warning(
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"\n\nWARNING: CORS_ALLOW_ORIGIN IS SET TO '*' - NOT RECOMMENDED FOR PRODUCTION DEPLOYMENTS.\n"
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"\n\nWARNING: CORS_ALLOW_ORIGIN IS SET TO '*' - NOT RECOMMENDED FOR PRODUCTION DEPLOYMENTS.\n"
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)
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)
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else:
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validate_cors_origins(CORS_ALLOW_ORIGIN)
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# You have to pick between a single wildcard or a list of origins.
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# Doing both will result in CORS errors in the browser.
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for origin in CORS_ALLOW_ORIGIN:
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validate_cors_origin(origin)
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class BannerModel(BaseModel):
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class BannerModel(BaseModel):
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@ -1812,6 +1825,13 @@ PGVECTOR_INITIALIZE_MAX_VECTOR_LENGTH = int(
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os.environ.get("PGVECTOR_INITIALIZE_MAX_VECTOR_LENGTH", "1536")
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os.environ.get("PGVECTOR_INITIALIZE_MAX_VECTOR_LENGTH", "1536")
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)
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)
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PGVECTOR_PGCRYPTO = os.getenv("PGVECTOR_PGCRYPTO", "false").lower() == "true"
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PGVECTOR_PGCRYPTO_KEY = os.getenv("PGVECTOR_PGCRYPTO_KEY", None)
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if PGVECTOR_PGCRYPTO and not PGVECTOR_PGCRYPTO_KEY:
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raise ValueError(
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"PGVECTOR_PGCRYPTO is enabled but PGVECTOR_PGCRYPTO_KEY is not set. Please provide a valid key."
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)
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# Pinecone
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# Pinecone
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PINECONE_API_KEY = os.environ.get("PINECONE_API_KEY", None)
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PINECONE_API_KEY = os.environ.get("PINECONE_API_KEY", None)
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PINECONE_ENVIRONMENT = os.environ.get("PINECONE_ENVIRONMENT", None)
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PINECONE_ENVIRONMENT = os.environ.get("PINECONE_ENVIRONMENT", None)
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@ -1972,6 +1992,40 @@ DOCLING_DO_PICTURE_DESCRIPTION = PersistentConfig(
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os.getenv("DOCLING_DO_PICTURE_DESCRIPTION", "False").lower() == "true",
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os.getenv("DOCLING_DO_PICTURE_DESCRIPTION", "False").lower() == "true",
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)
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)
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DOCLING_PICTURE_DESCRIPTION_MODE = PersistentConfig(
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"DOCLING_PICTURE_DESCRIPTION_MODE",
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"rag.docling_picture_description_mode",
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os.getenv("DOCLING_PICTURE_DESCRIPTION_MODE", ""),
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)
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docling_picture_description_local = os.getenv("DOCLING_PICTURE_DESCRIPTION_LOCAL", "")
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try:
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docling_picture_description_local = json.loads(docling_picture_description_local)
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except json.JSONDecodeError:
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docling_picture_description_local = {}
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DOCLING_PICTURE_DESCRIPTION_LOCAL = PersistentConfig(
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"DOCLING_PICTURE_DESCRIPTION_LOCAL",
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"rag.docling_picture_description_local",
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docling_picture_description_local,
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)
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docling_picture_description_api = os.getenv("DOCLING_PICTURE_DESCRIPTION_API", "")
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try:
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docling_picture_description_api = json.loads(docling_picture_description_api)
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except json.JSONDecodeError:
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docling_picture_description_api = {}
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DOCLING_PICTURE_DESCRIPTION_API = PersistentConfig(
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"DOCLING_PICTURE_DESCRIPTION_API",
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"rag.docling_picture_description_api",
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docling_picture_description_api,
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)
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DOCUMENT_INTELLIGENCE_ENDPOINT = PersistentConfig(
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DOCUMENT_INTELLIGENCE_ENDPOINT = PersistentConfig(
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"DOCUMENT_INTELLIGENCE_ENDPOINT",
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"DOCUMENT_INTELLIGENCE_ENDPOINT",
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"rag.document_intelligence_endpoint",
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"rag.document_intelligence_endpoint",
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@ -2268,7 +2322,7 @@ DOWNLOADED_EMBEDDING_MODELS = PersistentConfig(
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os.getenv("DOWNLOADED_EMBEDDING_MODELS", {"":["sentence-transformers/all-MiniLM-L6-v2"],
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os.getenv("DOWNLOADED_EMBEDDING_MODELS", {"":["sentence-transformers/all-MiniLM-L6-v2"],
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"openai":["text-embedding-3-small"],
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"openai":["text-embedding-3-small"],
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"ollama":[],
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"ollama":[],
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"azure_openai_config": []})
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"azure_openai": []})
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)
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)
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DOWNLOADED_RERANKING_MODELS = PersistentConfig(
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DOWNLOADED_RERANKING_MODELS = PersistentConfig(
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@ -2284,7 +2338,7 @@ LOADED_EMBEDDING_MODELS = PersistentConfig(
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os.getenv("LOADED_EMBEDDING_MODELS", {"":["sentence-transformers/all-MiniLM-L6-v2"],
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os.getenv("LOADED_EMBEDDING_MODELS", {"":["sentence-transformers/all-MiniLM-L6-v2"],
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"openai":[],
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"openai":[],
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"ollama":[],
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"ollama":[],
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"azure_openai_config": []})
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"azure_openai": []})
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)
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)
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LOADED_RERANKING_MODELS = PersistentConfig(
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LOADED_RERANKING_MODELS = PersistentConfig(
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