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* VoyageEmbeddingConfig * fix voyage logic to get params * add voyage embedding transformation * add get_provider_embedding_config * use BaseEmbeddingConfig * voyage clean up * use llm http handler for embedding transformations * test_voyage_ai_embedding_extra_params * add voyage async * test_voyage_ai_embedding_extra_params * add async for llm http handler * update BaseLLMEmbeddingTest * test_voyage_ai_embedding_extra_params * fix linting * fix get_provider_embedding_config * fix anthropic text test * update location of base/chat/transformation * fix import path * fix IBMWatsonXAIConfig
108 lines
3.2 KiB
Python
108 lines
3.2 KiB
Python
from typing import Callable, Optional, Union
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import httpx
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from litellm._logging import verbose_logger
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from litellm.llms.base_llm.chat.transformation import BaseLLMException
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from litellm.secret_managers.main import get_secret_str
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class AzureOpenAIError(BaseLLMException):
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def __init__(
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self,
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status_code,
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message,
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request: Optional[httpx.Request] = None,
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response: Optional[httpx.Response] = None,
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headers: Optional[Union[httpx.Headers, dict]] = None,
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):
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super().__init__(
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status_code=status_code,
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message=message,
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request=request,
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response=response,
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headers=headers,
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)
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def process_azure_headers(headers: Union[httpx.Headers, dict]) -> dict:
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openai_headers = {}
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if "x-ratelimit-limit-requests" in headers:
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openai_headers["x-ratelimit-limit-requests"] = headers[
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"x-ratelimit-limit-requests"
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]
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if "x-ratelimit-remaining-requests" in headers:
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openai_headers["x-ratelimit-remaining-requests"] = headers[
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"x-ratelimit-remaining-requests"
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]
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if "x-ratelimit-limit-tokens" in headers:
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openai_headers["x-ratelimit-limit-tokens"] = headers["x-ratelimit-limit-tokens"]
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if "x-ratelimit-remaining-tokens" in headers:
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openai_headers["x-ratelimit-remaining-tokens"] = headers[
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"x-ratelimit-remaining-tokens"
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]
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llm_response_headers = {
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"{}-{}".format("llm_provider", k): v for k, v in headers.items()
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}
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return {**llm_response_headers, **openai_headers}
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def get_azure_ad_token_from_entrata_id(
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tenant_id: str,
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client_id: str,
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client_secret: str,
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scope: str = "https://cognitiveservices.azure.com/.default",
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) -> Callable[[], str]:
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"""
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Get Azure AD token provider from `client_id`, `client_secret`, and `tenant_id`
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Args:
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tenant_id: str
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client_id: str
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client_secret: str
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scope: str
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Returns:
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callable that returns a bearer token.
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"""
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from azure.identity import (
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ClientSecretCredential,
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DefaultAzureCredential,
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get_bearer_token_provider,
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)
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verbose_logger.debug("Getting Azure AD Token from Entrata ID")
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if tenant_id.startswith("os.environ/"):
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_tenant_id = get_secret_str(tenant_id)
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else:
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_tenant_id = tenant_id
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if client_id.startswith("os.environ/"):
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_client_id = get_secret_str(client_id)
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else:
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_client_id = client_id
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if client_secret.startswith("os.environ/"):
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_client_secret = get_secret_str(client_secret)
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else:
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_client_secret = client_secret
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verbose_logger.debug(
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"tenant_id %s, client_id %s, client_secret %s",
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_tenant_id,
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_client_id,
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_client_secret,
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)
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if _tenant_id is None or _client_id is None or _client_secret is None:
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raise ValueError("tenant_id, client_id, and client_secret must be provided")
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credential = ClientSecretCredential(_tenant_id, _client_id, _client_secret)
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verbose_logger.debug("credential %s", credential)
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token_provider = get_bearer_token_provider(credential, scope)
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verbose_logger.debug("token_provider %s", token_provider)
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return token_provider
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