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https://github.com/hwchase17/langchain.git
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openai[patch]: Upgrade @root_validators in preparation for pydantic 2 migration (#25491)
* Upgrade @root_validator in openai pkg * Ran notebooks for all but AzureAI embeddings --------- Co-authored-by: Bagatur <baskaryan@gmail.com>
This commit is contained in:
Eugene Yurtsev
GitHub
@@ -1,13 +1,12 @@
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from __future__ import annotations
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import logging
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import os
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from typing import Any, Callable, Dict, List, Mapping, Optional, Union
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import openai
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from langchain_core.language_models import LangSmithParams
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from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
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from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
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from langchain_core.utils import from_env, secret_from_env
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from langchain_openai.llms.base import BaseOpenAI
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@@ -31,7 +30,9 @@ class AzureOpenAI(BaseOpenAI):
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openai = AzureOpenAI(model_name="gpt-3.5-turbo-instruct")
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"""
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azure_endpoint: Union[str, None] = None
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azure_endpoint: Optional[str] = Field(
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default_factory=from_env("AZURE_OPENAI_ENDPOINT", default=None)
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)
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"""Your Azure endpoint, including the resource.
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Automatically inferred from env var `AZURE_OPENAI_ENDPOINT` if not provided.
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@@ -44,16 +45,28 @@ class AzureOpenAI(BaseOpenAI):
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If given sets the base client URL to include `/deployments/{azure_deployment}`.
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Note: this means you won't be able to use non-deployment endpoints.
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"""
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openai_api_version: str = Field(default="", alias="api_version")
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openai_api_version: Optional[str] = Field(
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alias="api_version",
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default_factory=from_env("OPENAI_API_VERSION", default=None),
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)
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"""Automatically inferred from env var `OPENAI_API_VERSION` if not provided."""
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openai_api_key: Optional[SecretStr] = Field(default=None, alias="api_key")
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"""Automatically inferred from env var `AZURE_OPENAI_API_KEY` if not provided."""
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azure_ad_token: Optional[SecretStr] = None
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# Check OPENAI_KEY for backwards compatibility.
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# TODO: Remove OPENAI_API_KEY support to avoid possible conflict when using
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# other forms of azure credentials.
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openai_api_key: Optional[SecretStr] = Field(
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alias="api_key",
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default_factory=secret_from_env(
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["AZURE_OPENAI_API_KEY", "OPENAI_API_KEY"], default=None
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),
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)
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azure_ad_token: Optional[SecretStr] = Field(
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default_factory=secret_from_env("AZURE_OPENAI_AD_TOKEN", default=None)
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)
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"""Your Azure Active Directory token.
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Automatically inferred from env var `AZURE_OPENAI_AD_TOKEN` if not provided.
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For more:
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For more:
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https://www.microsoft.com/en-us/security/business/identity-access/microsoft-entra-id.
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"""
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azure_ad_token_provider: Union[Callable[[], str], None] = None
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@@ -61,7 +74,9 @@ class AzureOpenAI(BaseOpenAI):
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Will be invoked on every request.
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"""
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openai_api_type: str = ""
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openai_api_type: Optional[str] = Field(
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default_factory=from_env("OPENAI_API_TYPE", default="azure")
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)
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"""Legacy, for openai<1.0.0 support."""
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validate_base_url: bool = True
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"""For backwards compatibility. If legacy val openai_api_base is passed in, try to
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@@ -85,7 +100,7 @@ class AzureOpenAI(BaseOpenAI):
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"""Return whether this model can be serialized by Langchain."""
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return True
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@root_validator()
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@root_validator(pre=False, skip_on_failure=True, allow_reuse=True)
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def validate_environment(cls, values: Dict) -> Dict:
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"""Validate that api key and python package exists in environment."""
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if values["n"] < 1:
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@@ -94,43 +109,6 @@ class AzureOpenAI(BaseOpenAI):
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raise ValueError("Cannot stream results when n > 1.")
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if values["streaming"] and values["best_of"] > 1:
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raise ValueError("Cannot stream results when best_of > 1.")
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# Check OPENAI_KEY for backwards compatibility.
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# TODO: Remove OPENAI_API_KEY support to avoid possible conflict when using
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# other forms of azure credentials.
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openai_api_key = (
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values["openai_api_key"]
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or os.getenv("AZURE_OPENAI_API_KEY")
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or os.getenv("OPENAI_API_KEY")
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)
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values["openai_api_key"] = (
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convert_to_secret_str(openai_api_key) if openai_api_key else None
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)
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values["azure_endpoint"] = values["azure_endpoint"] or os.getenv(
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"AZURE_OPENAI_ENDPOINT"
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)
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azure_ad_token = values["azure_ad_token"] or os.getenv("AZURE_OPENAI_AD_TOKEN")
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values["azure_ad_token"] = (
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convert_to_secret_str(azure_ad_token) if azure_ad_token else None
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)
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values["openai_api_base"] = values["openai_api_base"] or os.getenv(
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"OPENAI_API_BASE"
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)
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values["openai_proxy"] = get_from_dict_or_env(
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values, "openai_proxy", "OPENAI_PROXY", default=""
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)
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values["openai_organization"] = (
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values["openai_organization"]
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or os.getenv("OPENAI_ORG_ID")
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or os.getenv("OPENAI_ORGANIZATION")
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)
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values["openai_api_version"] = values["openai_api_version"] or os.getenv(
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"OPENAI_API_VERSION"
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)
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values["openai_api_type"] = get_from_dict_or_env(
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values, "openai_api_type", "OPENAI_API_TYPE", default="azure"
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)
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# For backwards compatibility. Before openai v1, no distinction was made
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# between azure_endpoint and base_url (openai_api_base).
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openai_api_base = values["openai_api_base"]
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@@ -1,7 +1,6 @@
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from __future__ import annotations
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import logging
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import os
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import sys
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from typing import (
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AbstractSet,
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@@ -28,12 +27,8 @@ from langchain_core.callbacks import (
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from langchain_core.language_models.llms import BaseLLM
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from langchain_core.outputs import Generation, GenerationChunk, LLMResult
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from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
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from langchain_core.utils import (
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convert_to_secret_str,
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get_from_dict_or_env,
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get_pydantic_field_names,
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)
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from langchain_core.utils.utils import build_extra_kwargs
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from langchain_core.utils import get_pydantic_field_names
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from langchain_core.utils.utils import build_extra_kwargs, from_env, secret_from_env
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logger = logging.getLogger(__name__)
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@@ -90,15 +85,26 @@ class BaseOpenAI(BaseLLM):
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"""Generates best_of completions server-side and returns the "best"."""
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model_kwargs: Dict[str, Any] = Field(default_factory=dict)
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"""Holds any model parameters valid for `create` call not explicitly specified."""
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openai_api_key: Optional[SecretStr] = Field(default=None, alias="api_key")
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openai_api_key: Optional[SecretStr] = Field(
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alias="api_key", default_factory=secret_from_env("OPENAI_API_KEY", default=None)
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)
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"""Automatically inferred from env var `OPENAI_API_KEY` if not provided."""
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openai_api_base: Optional[str] = Field(default=None, alias="base_url")
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openai_api_base: Optional[str] = Field(
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alias="base_url", default_factory=from_env("OPENAI_API_BASE", default=None)
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)
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"""Base URL path for API requests, leave blank if not using a proxy or service
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emulator."""
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openai_organization: Optional[str] = Field(default=None, alias="organization")
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openai_organization: Optional[str] = Field(
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alias="organization",
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default_factory=from_env(
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["OPENAI_ORG_ID", "OPENAI_ORGANIZATION"], default=None
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),
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)
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"""Automatically inferred from env var `OPENAI_ORG_ID` if not provided."""
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# to support explicit proxy for OpenAI
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openai_proxy: Optional[str] = None
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openai_proxy: Optional[str] = Field(
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default_factory=from_env("OPENAI_PROXY", default=None)
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)
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batch_size: int = 20
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"""Batch size to use when passing multiple documents to generate."""
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request_timeout: Union[float, Tuple[float, float], Any, None] = Field(
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@@ -161,7 +167,7 @@ class BaseOpenAI(BaseLLM):
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)
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return values
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@root_validator()
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@root_validator(pre=False, skip_on_failure=True, allow_reuse=True)
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def validate_environment(cls, values: Dict) -> Dict:
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"""Validate that api key and python package exists in environment."""
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if values["n"] < 1:
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@@ -171,24 +177,6 @@ class BaseOpenAI(BaseLLM):
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if values["streaming"] and values["best_of"] > 1:
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raise ValueError("Cannot stream results when best_of > 1.")
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openai_api_key = get_from_dict_or_env(
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values, "openai_api_key", "OPENAI_API_KEY"
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)
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values["openai_api_key"] = (
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convert_to_secret_str(openai_api_key) if openai_api_key else None
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)
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values["openai_api_base"] = values["openai_api_base"] or os.getenv(
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"OPENAI_API_BASE"
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)
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values["openai_proxy"] = get_from_dict_or_env(
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values, "openai_proxy", "OPENAI_PROXY", default=""
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)
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values["openai_organization"] = (
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values["openai_organization"]
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or os.getenv("OPENAI_ORG_ID")
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or os.getenv("OPENAI_ORGANIZATION")
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)
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client_params = {
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"api_key": (
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values["openai_api_key"].get_secret_value()
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