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https://github.com/BerriAI/litellm.git
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fix(client_initialization_utils.py): refactor azure client init logic
This commit is contained in:
Krrish Dholakia
parent
7696147968
commit
8845f0947d
1 changed files with 69 additions and 266 deletions
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@ -194,272 +194,6 @@ class InitalizeOpenAISDKClient:
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organization_env_name = organization.replace("os.environ/", "")
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organization = get_secret_str(organization_env_name)
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litellm_params["organization"] = organization
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azure_ad_token_provider: Optional[Callable[[], str]] = None
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# If we have api_key, then we have higher priority
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if not api_key and litellm_params.get("tenant_id"):
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verbose_router_logger.debug(
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"Using Azure AD Token Provider for Azure Auth"
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)
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azure_ad_token_provider = get_azure_ad_token_from_entrata_id(
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tenant_id=litellm_params.get("tenant_id"),
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client_id=litellm_params.get("client_id"),
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client_secret=litellm_params.get("client_secret"),
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)
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if litellm_params.get("azure_username") and litellm_params.get(
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"azure_password"
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):
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azure_ad_token_provider = get_azure_ad_token_from_username_password(
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azure_username=litellm_params.get("azure_username"),
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azure_password=litellm_params.get("azure_password"),
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client_id=litellm_params.get("client_id"),
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)
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if custom_llm_provider == "azure" or custom_llm_provider == "azure_text":
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if api_base is None or not isinstance(api_base, str):
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filtered_litellm_params = {
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k: v
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for k, v in model["litellm_params"].items()
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if k != "api_key"
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}
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_filtered_model = {
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"model_name": model["model_name"],
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"litellm_params": filtered_litellm_params,
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}
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raise ValueError(
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f"api_base is required for Azure OpenAI. Set it on your config. Model - {_filtered_model}"
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)
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azure_ad_token = litellm_params.get("azure_ad_token")
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if azure_ad_token is not None:
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if azure_ad_token.startswith("oidc/"):
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azure_ad_token = get_azure_ad_token_from_oidc(azure_ad_token)
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elif (
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not api_key and azure_ad_token_provider is None
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and litellm.enable_azure_ad_token_refresh is True
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):
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try:
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azure_ad_token_provider = get_azure_ad_token_provider()
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except ValueError:
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verbose_router_logger.debug(
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"Azure AD Token Provider could not be used."
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)
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if api_version is None:
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api_version = os.getenv(
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"AZURE_API_VERSION", litellm.AZURE_DEFAULT_API_VERSION
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)
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if "gateway.ai.cloudflare.com" in api_base:
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if not api_base.endswith("/"):
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api_base += "/"
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azure_model = model_name.replace("azure/", "")
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api_base += f"{azure_model}"
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cache_key = f"{model_id}_async_client"
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_client = openai.AsyncAzureOpenAI(
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api_key=api_key,
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azure_ad_token=azure_ad_token,
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azure_ad_token_provider=azure_ad_token_provider,
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base_url=api_base,
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api_version=api_version,
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timeout=timeout, # type: ignore
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max_retries=max_retries, # type: ignore
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http_client=httpx.AsyncClient(
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limits=httpx.Limits(
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max_connections=1000, max_keepalive_connections=100
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),
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verify=litellm.ssl_verify,
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), # type: ignore
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)
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litellm_router_instance.cache.set_cache(
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key=cache_key,
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value=_client,
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ttl=client_ttl,
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local_only=True,
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) # cache for 1 hr
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if InitalizeOpenAISDKClient.should_initialize_sync_client(
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litellm_router_instance=litellm_router_instance
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):
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cache_key = f"{model_id}_client"
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_client = openai.AzureOpenAI( # type: ignore
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api_key=api_key,
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azure_ad_token=azure_ad_token,
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azure_ad_token_provider=azure_ad_token_provider,
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base_url=api_base,
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api_version=api_version,
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timeout=timeout, # type: ignore
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max_retries=max_retries, # type: ignore
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http_client=httpx.Client(
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limits=httpx.Limits(
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max_connections=1000, max_keepalive_connections=100
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),
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verify=litellm.ssl_verify,
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), # type: ignore
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)
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litellm_router_instance.cache.set_cache(
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key=cache_key,
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value=_client,
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ttl=client_ttl,
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local_only=True,
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) # cache for 1 hr
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# streaming clients can have diff timeouts
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cache_key = f"{model_id}_stream_async_client"
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_client = openai.AsyncAzureOpenAI( # type: ignore
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api_key=api_key,
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azure_ad_token=azure_ad_token,
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azure_ad_token_provider=azure_ad_token_provider,
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base_url=api_base,
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api_version=api_version,
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timeout=stream_timeout, # type: ignore
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max_retries=max_retries, # type: ignore
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http_client=httpx.AsyncClient(
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limits=httpx.Limits(
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max_connections=1000, max_keepalive_connections=100
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),
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verify=litellm.ssl_verify,
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), # type: ignore
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)
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litellm_router_instance.cache.set_cache(
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key=cache_key,
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value=_client,
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ttl=client_ttl,
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local_only=True,
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) # cache for 1 hr
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if InitalizeOpenAISDKClient.should_initialize_sync_client(
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litellm_router_instance=litellm_router_instance
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):
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cache_key = f"{model_id}_stream_client"
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_client = openai.AzureOpenAI( # type: ignore
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api_key=api_key,
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azure_ad_token=azure_ad_token,
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azure_ad_token_provider=azure_ad_token_provider,
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base_url=api_base,
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api_version=api_version,
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timeout=stream_timeout, # type: ignore
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max_retries=max_retries, # type: ignore
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http_client=httpx.Client(
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limits=httpx.Limits(
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max_connections=1000, max_keepalive_connections=100
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),
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verify=litellm.ssl_verify,
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), # type: ignore
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)
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litellm_router_instance.cache.set_cache(
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key=cache_key,
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value=_client,
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ttl=client_ttl,
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local_only=True,
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) # cache for 1 hr
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else:
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_api_key = api_key
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if _api_key is not None and isinstance(_api_key, str):
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# only show first 5 chars of api_key
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_api_key = _api_key[:8] + "*" * 15
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verbose_router_logger.debug(
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f"Initializing Azure OpenAI Client for {model_name}, Api Base: {str(api_base)}, Api Key:{_api_key}"
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)
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azure_client_params = {
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"api_key": api_key,
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"azure_endpoint": api_base,
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"api_version": api_version,
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"azure_ad_token": azure_ad_token,
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"azure_ad_token_provider": azure_ad_token_provider,
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}
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if azure_ad_token_provider is not None:
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azure_client_params["azure_ad_token_provider"] = (
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azure_ad_token_provider
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)
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from litellm.llms.azure.azure import (
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select_azure_base_url_or_endpoint,
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)
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# this decides if we should set azure_endpoint or base_url on Azure OpenAI Client
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# required to support GPT-4 vision enhancements, since base_url needs to be set on Azure OpenAI Client
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azure_client_params = select_azure_base_url_or_endpoint(
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azure_client_params
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)
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cache_key = f"{model_id}_async_client"
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_client = openai.AsyncAzureOpenAI( # type: ignore
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**azure_client_params,
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timeout=timeout, # type: ignore
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max_retries=max_retries, # type: ignore
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http_client=httpx.AsyncClient(
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limits=httpx.Limits(
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max_connections=1000, max_keepalive_connections=100
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),
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verify=litellm.ssl_verify,
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), # type: ignore
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)
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litellm_router_instance.cache.set_cache(
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key=cache_key,
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value=_client,
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ttl=client_ttl,
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local_only=True,
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) # cache for 1 hr
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if InitalizeOpenAISDKClient.should_initialize_sync_client(
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litellm_router_instance=litellm_router_instance
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):
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cache_key = f"{model_id}_client"
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_client = openai.AzureOpenAI( # type: ignore
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**azure_client_params,
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timeout=timeout, # type: ignore
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max_retries=max_retries, # type: ignore
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http_client=httpx.Client(
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limits=httpx.Limits(
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max_connections=1000, max_keepalive_connections=100
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),
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verify=litellm.ssl_verify,
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), # type: ignore
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)
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litellm_router_instance.cache.set_cache(
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key=cache_key,
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value=_client,
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ttl=client_ttl,
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local_only=True,
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) # cache for 1 hr
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# streaming clients should have diff timeouts
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cache_key = f"{model_id}_stream_async_client"
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_client = openai.AsyncAzureOpenAI( # type: ignore
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**azure_client_params,
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timeout=stream_timeout, # type: ignore
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max_retries=max_retries, # type: ignore
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http_client=httpx.AsyncClient(
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limits=httpx.Limits(
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max_connections=1000, max_keepalive_connections=100
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),
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verify=litellm.ssl_verify,
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),
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)
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litellm_router_instance.cache.set_cache(
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key=cache_key,
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value=_client,
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ttl=client_ttl,
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local_only=True,
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) # cache for 1 hr
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if InitalizeOpenAISDKClient.should_initialize_sync_client(
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litellm_router_instance=litellm_router_instance
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):
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cache_key = f"{model_id}_stream_client"
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_client = openai.AzureOpenAI( # type: ignore
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**azure_client_params,
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timeout=stream_timeout, # type: ignore
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max_retries=max_retries, # type: ignore
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http_client=httpx.Client(
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limits=httpx.Limits(
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max_connections=1000, max_keepalive_connections=100
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),
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verify=litellm.ssl_verify,
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),
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)
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litellm_router_instance.cache.set_cache(
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key=cache_key,
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value=_client,
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ttl=client_ttl,
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local_only=True,
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) # cache for 1 hr
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else:
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_api_key = api_key # type: ignore
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@ -560,3 +294,72 @@ class InitalizeOpenAISDKClient:
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ttl=client_ttl,
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local_only=True,
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) # cache for 1 hr
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def initialize_azure_sdk_client(
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litellm_params: dict,
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api_key: Optional[str],
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api_base: Optional[str],
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model_name: str,
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api_version: Optional[str],
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):
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azure_ad_token_provider: Optional[Callable[[], str]] = None
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# If we have api_key, then we have higher priority
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azure_ad_token = litellm_params.get("azure_ad_token")
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tenant_id = litellm_params.get("tenant_id")
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client_id = litellm_params.get("client_id")
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client_secret = litellm_params.get("client_secret")
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azure_username = litellm_params.get("azure_username")
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azure_password = litellm_params.get("azure_password")
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if not api_key and tenant_id and client_id and client_secret:
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verbose_router_logger.debug("Using Azure AD Token Provider for Azure Auth")
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azure_ad_token_provider = get_azure_ad_token_from_entrata_id(
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tenant_id=tenant_id,
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client_id=client_id,
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client_secret=client_secret,
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)
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if azure_username and azure_password and client_id:
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azure_ad_token_provider = get_azure_ad_token_from_username_password(
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azure_username=azure_username,
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azure_password=azure_password,
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client_id=client_id,
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)
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if azure_ad_token is not None and azure_ad_token.startswith("oidc/"):
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azure_ad_token = get_azure_ad_token_from_oidc(azure_ad_token)
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elif (
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not api_key
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and azure_ad_token_provider is None
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and litellm.enable_azure_ad_token_refresh is True
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):
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try:
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azure_ad_token_provider = get_azure_ad_token_provider()
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except ValueError:
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verbose_router_logger.debug("Azure AD Token Provider could not be used.")
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if api_version is None:
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api_version = os.getenv("AZURE_API_VERSION", litellm.AZURE_DEFAULT_API_VERSION)
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_api_key = api_key
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if _api_key is not None and isinstance(_api_key, str):
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# only show first 5 chars of api_key
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_api_key = _api_key[:8] + "*" * 15
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verbose_router_logger.debug(
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f"Initializing Azure OpenAI Client for {model_name}, Api Base: {str(api_base)}, Api Key:{_api_key}"
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)
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azure_client_params = {
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"api_key": api_key,
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"azure_endpoint": api_base,
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"api_version": api_version,
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"azure_ad_token": azure_ad_token,
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"azure_ad_token_provider": azure_ad_token_provider,
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}
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if azure_ad_token_provider is not None:
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azure_client_params["azure_ad_token_provider"] = azure_ad_token_provider
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from litellm.llms.azure.azure import select_azure_base_url_or_endpoint
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# this decides if we should set azure_endpoint or base_url on Azure OpenAI Client
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# required to support GPT-4 vision enhancements, since base_url needs to be set on Azure OpenAI Client
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azure_client_params = select_azure_base_url_or_endpoint(azure_client_params)
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return azure_client_params
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