Source code for langchain_community.embeddings.azure_openai

"""Azure OpenAI embeddings wrapper."""

from __future__ import annotations

import os
import warnings
from typing import Callable, Dict, Optional, Union

from langchain_core._api.deprecation import deprecated
from langchain_core.pydantic_v1 import Field, root_validator
from langchain_core.utils import get_from_dict_or_env

from langchain_community.embeddings.openai import OpenAIEmbeddings
from langchain_community.utils.openai import is_openai_v1

[docs]@deprecated( since="0.0.9", removal="0.3.0", alternative_import="langchain_openai.AzureOpenAIEmbeddings", ) class AzureOpenAIEmbeddings(OpenAIEmbeddings): """`Azure OpenAI` Embeddings API.""" azure_endpoint: Union[str, None] = None """Your Azure endpoint, including the resource. Automatically inferred from env var `AZURE_OPENAI_ENDPOINT` if not provided. Example: `` """ deployment: Optional[str] = Field(default=None, alias="azure_deployment") """A model deployment. If given sets the base client URL to include `/deployments/{azure_deployment}`. Note: this means you won't be able to use non-deployment endpoints. """ openai_api_key: Union[str, None] = Field(default=None, alias="api_key") """Automatically inferred from env var `AZURE_OPENAI_API_KEY` if not provided.""" azure_ad_token: Union[str, None] = None """Your Azure Active Directory token. Automatically inferred from env var `AZURE_OPENAI_AD_TOKEN` if not provided. For more: """ # noqa: E501 azure_ad_token_provider: Union[Callable[[], str], None] = None """A function that returns an Azure Active Directory token. Will be invoked on every request. """ openai_api_version: Optional[str] = Field(default=None, alias="api_version") """Automatically inferred from env var `OPENAI_API_VERSION` if not provided.""" validate_base_url: bool = True @root_validator() def validate_environment(cls, values: Dict) -> Dict: """Validate that api key and python package exists in environment.""" # Check OPENAI_KEY for backwards compatibility. # TODO: Remove OPENAI_API_KEY support to avoid possible conflict when using # other forms of azure credentials. values["openai_api_key"] = ( values["openai_api_key"] or os.getenv("AZURE_OPENAI_API_KEY") or os.getenv("OPENAI_API_KEY") ) values["openai_api_base"] = values["openai_api_base"] or os.getenv( "OPENAI_API_BASE" ) values["openai_api_version"] = values["openai_api_version"] or os.getenv( "OPENAI_API_VERSION", default="2023-05-15" ) values["openai_api_type"] = get_from_dict_or_env( values, "openai_api_type", "OPENAI_API_TYPE", default="azure" ) values["openai_organization"] = ( values["openai_organization"] or os.getenv("OPENAI_ORG_ID") or os.getenv("OPENAI_ORGANIZATION") ) values["openai_proxy"] = get_from_dict_or_env( values, "openai_proxy", "OPENAI_PROXY", default="", ) values["azure_endpoint"] = values["azure_endpoint"] or os.getenv( "AZURE_OPENAI_ENDPOINT" ) values["azure_ad_token"] = values["azure_ad_token"] or os.getenv( "AZURE_OPENAI_AD_TOKEN" ) # Azure OpenAI embedding models allow a maximum of 16 texts # at a time in each batch # See: values["chunk_size"] = min(values["chunk_size"], 16) try: import openai except ImportError: raise ImportError( "Could not import openai python package. " "Please install it with `pip install openai`." ) if is_openai_v1(): # For backwards compatibility. Before openai v1, no distinction was made # between azure_endpoint and base_url (openai_api_base). openai_api_base = values["openai_api_base"] if openai_api_base and values["validate_base_url"]: if "/openai" not in openai_api_base: values["openai_api_base"] += "/openai" warnings.warn( "As of openai>=1.0.0, Azure endpoints should be specified via " f"the `azure_endpoint` param not `openai_api_base` " f"(or alias `base_url`). Updating `openai_api_base` from " f"{openai_api_base} to {values['openai_api_base']}." ) if values["deployment"]: warnings.warn( "As of openai>=1.0.0, if `deployment` (or alias " "`azure_deployment`) is specified then " "`openai_api_base` (or alias `base_url`) should not be. " "Instead use `deployment` (or alias `azure_deployment`) " "and `azure_endpoint`." ) if values["deployment"] not in values["openai_api_base"]: warnings.warn( "As of openai>=1.0.0, if `openai_api_base` " "(or alias `base_url`) is specified it is expected to be " "of the form " " " # noqa: E501 f"Updating {openai_api_base} to " f"{values['openai_api_base']}." ) values["openai_api_base"] += ( "/deployments/" + values["deployment"] ) values["deployment"] = None client_params = { "api_version": values["openai_api_version"], "azure_endpoint": values["azure_endpoint"], "azure_deployment": values["deployment"], "api_key": values["openai_api_key"], "azure_ad_token": values["azure_ad_token"], "azure_ad_token_provider": values["azure_ad_token_provider"], "organization": values["openai_organization"], "base_url": values["openai_api_base"], "timeout": values["request_timeout"], "max_retries": values["max_retries"], "default_headers": values["default_headers"], "default_query": values["default_query"], "http_client": values["http_client"], } values["client"] = openai.AzureOpenAI(**client_params).embeddings values["async_client"] = openai.AsyncAzureOpenAI(**client_params).embeddings else: values["client"] = openai.Embedding return values @property def _llm_type(self) -> str: return "azure-openai-chat"