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https://github.com/BerriAI/litellm.git
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fix(azure): return a provided client early in create_azure_client
The restored #35492 code referenced azure_client_params outside the branch that binds it, guarded only by a client-is-None short circuit. That is safe at runtime but basedpyright cannot correlate the two checks, so the ratchet gate flagged it as a net-new possibly-unbound reference. Early-returning the provided-client path leaves azure_client_params bound on every path that reaches the ownership check and removes the need for the short circuit.
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mateo-berri
parent
d45e2bc34e
commit
9ee23a2099
1 changed files with 79 additions and 74 deletions
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@ -427,90 +427,95 @@ class BaseAzureLLM(BaseOpenAILLM):
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f"|azure_password={hashlib.sha256(_azure_password.encode()).hexdigest() if isinstance(_azure_password, str) else None}"
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f"|azure_scope={_lp.get('azure_scope')}"
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)
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if client is None:
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cached_client: Final = self.get_cached_openai_client(
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client_initialization_params=client_initialization_params,
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client_type="azure",
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)
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if cached_client:
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if isinstance(cached_client, (AzureOpenAI, AsyncAzureOpenAI, OpenAI, AsyncOpenAI)):
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return cached_client
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azure_client_params: Final = self.initialize_azure_sdk_client(
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litellm_params=litellm_params or {},
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api_key=api_key,
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api_base=api_base,
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model_name=model,
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api_version=api_version,
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is_async=_is_async,
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)
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# For Azure v1 API, use standard OpenAI client instead of AzureOpenAI
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# See: https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#api-specs
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if self._is_azure_v1_api_version(api_version):
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# Extract only params that OpenAI client accepts
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# Always use /openai/v1/ regardless of whether user passed "v1", "latest", or "preview"
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# The OpenAI client accepts a callable for `api_key` and re-invokes it
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# on every request (via `_refresh_api_key`), so passing
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# `azure_ad_token_provider` directly preserves Azure AD token refresh
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# behavior that the regular AzureOpenAI client provides.
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v1_api_key: str | Callable[[], Any] | None = (
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azure_client_params.get("api_key")
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or azure_client_params.get("azure_ad_token_provider")
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or azure_client_params.get("azure_ad_token")
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)
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if _is_async is True and callable(v1_api_key):
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# AsyncOpenAI expects an async provider; wrap the sync provider
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# returned by azure-identity. Offload to a thread so a token
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# refresh (blocking HTTP call to AAD on cache miss) does not
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# stall the event loop.
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_sync_provider: Final = v1_api_key
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async def _async_v1_api_key() -> str:
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return await asyncio.to_thread(_sync_provider)
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v1_api_key = _async_v1_api_key
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v1_params: Final[dict[str, Any]] = {
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"api_key": v1_api_key,
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"base_url": f"{api_base}/openai/v1/",
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}
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if "timeout" in azure_client_params:
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v1_params["timeout"] = azure_client_params["timeout"]
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if "max_retries" in azure_client_params:
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v1_params["max_retries"] = azure_client_params["max_retries"]
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if "http_client" in azure_client_params:
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v1_params["http_client"] = azure_client_params["http_client"]
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verbose_logger.debug("Using Azure v1 API with base_url: %s", v1_params["base_url"])
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if _is_async is True:
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openai_client = AsyncOpenAI(**v1_params) # type: ignore
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else:
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openai_client = OpenAI(**v1_params) # type: ignore
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else:
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# Traditional Azure API uses AzureOpenAI client
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if _is_async is True:
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openai_client = AsyncAzureOpenAI(**azure_client_params)
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else:
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openai_client = AzureOpenAI(**azure_client_params) # type: ignore
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else:
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openai_client = client
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if client is not None:
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if (
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api_version is not None
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and isinstance(openai_client, (AzureOpenAI, AsyncAzureOpenAI))
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and isinstance(openai_client._custom_query, dict)
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and isinstance(client, (AzureOpenAI, AsyncAzureOpenAI))
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and isinstance(client._custom_query, dict)
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):
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# set api_version to version passed by user
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openai_client._custom_query.setdefault("api-version", api_version)
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client._custom_query.setdefault("api-version", api_version)
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self.set_cached_openai_client(
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openai_client=client,
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client_initialization_params=client_initialization_params,
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client_type="azure",
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litellm_owned_client=False,
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)
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return client
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cached_client: Final = self.get_cached_openai_client(
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client_initialization_params=client_initialization_params,
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client_type="azure",
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)
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if cached_client:
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if isinstance(cached_client, (AzureOpenAI, AsyncAzureOpenAI, OpenAI, AsyncOpenAI)):
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return cached_client
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azure_client_params: Final = self.initialize_azure_sdk_client(
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litellm_params=litellm_params or {},
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api_key=api_key,
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api_base=api_base,
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model_name=model,
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api_version=api_version,
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is_async=_is_async,
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)
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# For Azure v1 API, use standard OpenAI client instead of AzureOpenAI
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# See: https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#api-specs
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if self._is_azure_v1_api_version(api_version):
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# Extract only params that OpenAI client accepts
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# Always use /openai/v1/ regardless of whether user passed "v1", "latest", or "preview"
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# The OpenAI client accepts a callable for `api_key` and re-invokes it
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# on every request (via `_refresh_api_key`), so passing
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# `azure_ad_token_provider` directly preserves Azure AD token refresh
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# behavior that the regular AzureOpenAI client provides.
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v1_api_key: str | Callable[[], Any] | None = (
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azure_client_params.get("api_key")
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or azure_client_params.get("azure_ad_token_provider")
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or azure_client_params.get("azure_ad_token")
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)
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if _is_async is True and callable(v1_api_key):
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# AsyncOpenAI expects an async provider; wrap the sync provider
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# returned by azure-identity. Offload to a thread so a token
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# refresh (blocking HTTP call to AAD on cache miss) does not
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# stall the event loop.
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_sync_provider: Final = v1_api_key
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async def _async_v1_api_key() -> str:
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return await asyncio.to_thread(_sync_provider)
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v1_api_key = _async_v1_api_key
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v1_params: Final[dict[str, Any]] = {
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"api_key": v1_api_key,
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"base_url": f"{api_base}/openai/v1/",
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}
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if "timeout" in azure_client_params:
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v1_params["timeout"] = azure_client_params["timeout"]
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if "max_retries" in azure_client_params:
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v1_params["max_retries"] = azure_client_params["max_retries"]
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if "http_client" in azure_client_params:
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v1_params["http_client"] = azure_client_params["http_client"]
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verbose_logger.debug("Using Azure v1 API with base_url: %s", v1_params["base_url"])
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if _is_async is True:
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openai_client = AsyncOpenAI(**v1_params) # type: ignore
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else:
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openai_client = OpenAI(**v1_params) # type: ignore
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else:
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# Traditional Azure API uses AzureOpenAI client
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if _is_async is True:
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openai_client = AsyncAzureOpenAI(**azure_client_params)
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else:
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openai_client = AzureOpenAI(**azure_client_params) # type: ignore
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# save client in-memory cache
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self.set_cached_openai_client(
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openai_client=openai_client,
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client_initialization_params=client_initialization_params,
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client_type="azure",
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litellm_owned_client=client is None
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and self.owns_wrapped_http_client(azure_client_params.get("http_client")),
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litellm_owned_client=self.owns_wrapped_http_client(azure_client_params.get("http_client")),
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)
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return openai_client
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