Archives/langchain
2
0
Fork 1
mirror of https://github.com/hwchase17/langchain synced 2024-11-10 01:10:59 +00:00
Code Issues Packages Projects Releases Wiki Activity

openai[patch]: Upgrade @root_validators in preparation for pydantic 2 migration (#25491)

Browse Source 
* 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 2024-09-03 17:42:24 -04:00 committed by GitHub
parent 0207dc1431
commit bc3b851f08
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
12 changed files with 248 additions and 233 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

66
libs/partners/openai/langchain_openai/chat_models/azure.py
View File

@ -34,7 +34,7 @@ from langchain_core.outputs import ChatResult
from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr, root_validator
from langchain_core.runnables import Runnable, RunnableMap, RunnablePassthrough
from langchain_core.tools import BaseTool
from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
from langchain_core.utils import from_env, secret_from_env
from langchain_core.utils.function_calling import convert_to_openai_tool
from langchain_core.utils.pydantic import is_basemodel_subclass
@ -474,10 +474,13 @@ class AzureChatOpenAI(BaseChatOpenAI):
}
""" # noqa: E501
azure_endpoint: Union[str, None] = None
azure_endpoint: Optional[str] = Field(
default_factory=from_env("AZURE_OPENAI_ENDPOINT", default=None)
)
"""Your Azure endpoint, including the resource.
Automatically inferred from env var `AZURE_OPENAI_ENDPOINT` if not provided.
Example: `https://example-resource.azure.openai.com/`
"""
deployment_name: Union[str, None] = Field(default=None, alias="azure_deployment")
@ -486,14 +489,28 @@ class AzureChatOpenAI(BaseChatOpenAI):
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_version: str = Field(default="", alias="api_version")
openai_api_version: Optional[str] = Field(
alias="api_version",
default_factory=from_env("OPENAI_API_VERSION", default=None),
)
"""Automatically inferred from env var `OPENAI_API_VERSION` if not provided."""
openai_api_key: Optional[SecretStr] = Field(default=None, alias="api_key")
# Check OPENAI_KEY for backwards compatibility.
# TODO: Remove OPENAI_API_KEY support to avoid possible conflict when using
# other forms of azure credentials.
openai_api_key: Optional[SecretStr] = Field(
alias="api_key",
default_factory=secret_from_env(
["AZURE_OPENAI_API_KEY", "OPENAI_API_KEY"], default=None
),
)
"""Automatically inferred from env var `AZURE_OPENAI_API_KEY` if not provided."""
azure_ad_token: Optional[SecretStr] = None
azure_ad_token: Optional[SecretStr] = Field(
default_factory=secret_from_env("AZURE_OPENAI_AD_TOKEN", default=None)
)
"""Your Azure Active Directory token.
Automatically inferred from env var `AZURE_OPENAI_AD_TOKEN` if not provided.
For more:
https://www.microsoft.com/en-us/security/business/identity-access/microsoft-entra-id.
"""
@ -516,7 +533,9 @@ class AzureChatOpenAI(BaseChatOpenAI):
correct cost.
"""
openai_api_type: str = ""
openai_api_type: Optional[str] = Field(
default_factory=from_env("OPENAI_API_TYPE", default="azure")
)
"""Legacy, for openai<1.0.0 support."""
validate_base_url: bool = True
"""If legacy arg openai_api_base is passed in, try to infer if it is a base_url or
@ -546,7 +565,7 @@ class AzureChatOpenAI(BaseChatOpenAI):
def is_lc_serializable(cls) -> bool:
return True
@root_validator()
@root_validator(pre=False, skip_on_failure=True)
def validate_environment(cls, values: Dict) -> Dict:
"""Validate that api key and python package exists in environment."""
if values["n"] < 1:
@ -554,45 +573,12 @@ class AzureChatOpenAI(BaseChatOpenAI):
if values["n"] > 1 and values["streaming"]:
raise ValueError("n must be 1 when streaming.")
# Check OPENAI_KEY for backwards compatibility.
# TODO: Remove OPENAI_API_KEY support to avoid possible conflict when using
# other forms of azure credentials.
openai_api_key = (
values["openai_api_key"]
or os.getenv("AZURE_OPENAI_API_KEY")
or os.getenv("OPENAI_API_KEY")
)
values["openai_api_key"] = (
convert_to_secret_str(openai_api_key) if openai_api_key else None
)
values["openai_api_base"] = (
values["openai_api_base"]
if "openai_api_base" in values
else os.getenv("OPENAI_API_BASE")
)
values["openai_api_version"] = values["openai_api_version"] or os.getenv(
"OPENAI_API_VERSION"
)
# Check OPENAI_ORGANIZATION for backwards compatibility.
values["openai_organization"] = (
values["openai_organization"]
or os.getenv("OPENAI_ORG_ID")
or os.getenv("OPENAI_ORGANIZATION")
)
values["azure_endpoint"] = values["azure_endpoint"] or os.getenv(
"AZURE_OPENAI_ENDPOINT"
)
azure_ad_token = values["azure_ad_token"] or os.getenv("AZURE_OPENAI_AD_TOKEN")
values["azure_ad_token"] = (
convert_to_secret_str(azure_ad_token) if azure_ad_token else None
)
values["openai_api_type"] = get_from_dict_or_env(
values, "openai_api_type", "OPENAI_API_TYPE", default="azure"
)
values["openai_proxy"] = get_from_dict_or_env(
values, "openai_proxy", "OPENAI_PROXY", default=""
)
# 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"]

2
libs/partners/openai/langchain_openai/chat_models/base.py
View File

@ -443,7 +443,7 @@ class BaseChatOpenAI(BaseChatModel):
)
return values
@root_validator(pre=False, skip_on_failure=True)
@root_validator(pre=False, skip_on_failure=True, allow_reuse=True)
def validate_environment(cls, values: Dict) -> Dict:
"""Validate that api key and python package exists in environment."""
if values["n"] < 1:

72
libs/partners/openai/langchain_openai/embeddings/azure.py
View File

@ -2,12 +2,11 @@
from __future__ import annotations
import os
from typing import Callable, Dict, Optional, Union
import openai
from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
from langchain_core.utils import from_env, secret_from_env
from langchain_openai.embeddings.base import OpenAIEmbeddings
@ -100,7 +99,9 @@ class AzureOpenAIEmbeddings(OpenAIEmbeddings):
[-0.009100092574954033, 0.005071679595857859, -0.0029193938244134188]
""" # noqa: E501
azure_endpoint: Union[str, None] = None
azure_endpoint: Optional[str] = Field(
default_factory=from_env("AZURE_OPENAI_ENDPOINT", default=None)
)
"""Your Azure endpoint, including the resource.
Automatically inferred from env var `AZURE_OPENAI_ENDPOINT` if not provided.
@ -113,9 +114,26 @@ class AzureOpenAIEmbeddings(OpenAIEmbeddings):
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: Optional[SecretStr] = Field(default=None, alias="api_key")
# Check OPENAI_KEY for backwards compatibility.
# TODO: Remove OPENAI_API_KEY support to avoid possible conflict when using
# other forms of azure credentials.
openai_api_key: Optional[SecretStr] = Field(
alias="api_key",
default_factory=secret_from_env(
["AZURE_OPENAI_API_KEY", "OPENAI_API_KEY"], default=None
),
)
"""Automatically inferred from env var `AZURE_OPENAI_API_KEY` if not provided."""
azure_ad_token: Optional[SecretStr] = None
openai_api_version: Optional[str] = Field(
default_factory=from_env("OPENAI_API_VERSION", default="2023-05-15")
)
"""Automatically inferred from env var `OPENAI_API_VERSION` if not provided.
Set to "2023-05-15" by default if env variable `OPENAI_API_VERSION` is not set.
"""
azure_ad_token: Optional[SecretStr] = Field(
default_factory=secret_from_env("AZURE_OPENAI_AD_TOKEN", default=None)
)
"""Your Azure Active Directory token.
Automatically inferred from env var `AZURE_OPENAI_AD_TOKEN` if not provided.
@ -128,52 +146,16 @@ class AzureOpenAIEmbeddings(OpenAIEmbeddings):
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."""
openai_api_type: Optional[str] = Field(
default_factory=from_env("OPENAI_API_TYPE", default="azure")
)
validate_base_url: bool = True
chunk_size: int = 2048
"""Maximum number of texts to embed in each batch"""
@root_validator()
@root_validator(pre=False, skip_on_failure=True)
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.
openai_api_key = (
values["openai_api_key"]
or os.getenv("AZURE_OPENAI_API_KEY")
or os.getenv("OPENAI_API_KEY")
)
values["openai_api_key"] = (
convert_to_secret_str(openai_api_key) if openai_api_key else None
)
values["openai_api_base"] = (
values["openai_api_base"]
if "openai_api_base" in values
else 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"
)
azure_ad_token = values["azure_ad_token"] or os.getenv("AZURE_OPENAI_AD_TOKEN")
values["azure_ad_token"] = (
convert_to_secret_str(azure_ad_token) if azure_ad_token else None
)
# 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"]

61
libs/partners/openai/langchain_openai/embeddings/base.py
View File

@ -1,7 +1,6 @@
from __future__ import annotations
import logging
import os
import warnings
from typing import (
Any,
@ -22,11 +21,7 @@ import openai
import tiktoken
from langchain_core.embeddings import Embeddings
from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr, root_validator
from langchain_core.utils import (
convert_to_secret_str,
get_from_dict_or_env,
get_pydantic_field_names,
)
from langchain_core.utils import from_env, get_pydantic_field_names, secret_from_env
logger = logging.getLogger(__name__)
@ -185,21 +180,37 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
# to support Azure OpenAI Service custom deployment names
deployment: Optional[str] = model
# TODO: Move to AzureOpenAIEmbeddings.
openai_api_version: Optional[str] = Field(default=None, alias="api_version")
openai_api_version: Optional[str] = Field(
default_factory=from_env("OPENAI_API_VERSION", default=None),
alias="api_version",
)
"""Automatically inferred from env var `OPENAI_API_VERSION` if not provided."""
# to support Azure OpenAI Service custom endpoints
openai_api_base: Optional[str] = Field(default=None, alias="base_url")
openai_api_base: Optional[str] = Field(
alias="base_url", default_factory=from_env("OPENAI_API_BASE", default=None)
)
"""Base URL path for API requests, leave blank if not using a proxy or service
emulator."""
# to support Azure OpenAI Service custom endpoints
openai_api_type: Optional[str] = None
openai_api_type: Optional[str] = Field(
default_factory=from_env("OPENAI_API_TYPE", default=None)
)
# to support explicit proxy for OpenAI
openai_proxy: Optional[str] = None
openai_proxy: Optional[str] = Field(
default_factory=from_env("OPENAI_PROXY", default=None)
)
embedding_ctx_length: int = 8191
"""The maximum number of tokens to embed at once."""
openai_api_key: Optional[SecretStr] = Field(default=None, alias="api_key")
openai_api_key: Optional[SecretStr] = Field(
alias="api_key", default_factory=secret_from_env("OPENAI_API_KEY", default=None)
)
"""Automatically inferred from env var `OPENAI_API_KEY` if not provided."""
openai_organization: Optional[str] = Field(default=None, alias="organization")
openai_organization: Optional[str] = Field(
alias="organization",
default_factory=from_env(
["OPENAI_ORG_ID", "OPENAI_ORGANIZATION"], default=None
),
)
"""Automatically inferred from env var `OPENAI_ORG_ID` if not provided."""
allowed_special: Union[Literal["all"], Set[str], None] = None
disallowed_special: Union[Literal["all"], Set[str], Sequence[str], None] = None
@ -284,33 +295,9 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
values["model_kwargs"] = extra
return values
@root_validator()
@root_validator(pre=False, skip_on_failure=True, allow_reuse=True)
def validate_environment(cls, values: Dict) -> Dict:
"""Validate that api key and python package exists in environment."""
openai_api_key = get_from_dict_or_env(
values, "openai_api_key", "OPENAI_API_KEY"
)
values["openai_api_key"] = (
convert_to_secret_str(openai_api_key) if openai_api_key else None
)
values["openai_api_base"] = values["openai_api_base"] or os.getenv(
"OPENAI_API_BASE"
)
values["openai_api_type"] = get_from_dict_or_env(
values, "openai_api_type", "OPENAI_API_TYPE", default=""
)
values["openai_proxy"] = get_from_dict_or_env(
values, "openai_proxy", "OPENAI_PROXY", default=""
)
values["openai_api_version"] = get_from_dict_or_env(
values, "openai_api_version", "OPENAI_API_VERSION", default=""
)
# Check OPENAI_ORGANIZATION for backwards compatibility.
values["openai_organization"] = (
values["openai_organization"]
or os.getenv("OPENAI_ORG_ID")
or os.getenv("OPENAI_ORGANIZATION")
)
if values["openai_api_type"] in ("azure", "azure_ad", "azuread"):
raise ValueError(
"If you are using Azure, "

70
libs/partners/openai/langchain_openai/llms/azure.py
View File

@ -1,13 +1,12 @@
from __future__ import annotations
import logging
import os
from typing import Any, Callable, Dict, List, Mapping, Optional, Union
import openai
from langchain_core.language_models import LangSmithParams
from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
from langchain_core.utils import from_env, secret_from_env
from langchain_openai.llms.base import BaseOpenAI
@ -31,7 +30,9 @@ class AzureOpenAI(BaseOpenAI):
openai = AzureOpenAI(model_name="gpt-3.5-turbo-instruct")
"""
azure_endpoint: Union[str, None] = None
azure_endpoint: Optional[str] = Field(
default_factory=from_env("AZURE_OPENAI_ENDPOINT", default=None)
)
"""Your Azure endpoint, including the resource.
Automatically inferred from env var `AZURE_OPENAI_ENDPOINT` if not provided.
@ -44,11 +45,23 @@ class AzureOpenAI(BaseOpenAI):
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_version: str = Field(default="", alias="api_version")
openai_api_version: Optional[str] = Field(
alias="api_version",
default_factory=from_env("OPENAI_API_VERSION", default=None),
)
"""Automatically inferred from env var `OPENAI_API_VERSION` if not provided."""
openai_api_key: Optional[SecretStr] = Field(default=None, alias="api_key")
"""Automatically inferred from env var `AZURE_OPENAI_API_KEY` if not provided."""
azure_ad_token: Optional[SecretStr] = None
# Check OPENAI_KEY for backwards compatibility.
# TODO: Remove OPENAI_API_KEY support to avoid possible conflict when using
# other forms of azure credentials.
openai_api_key: Optional[SecretStr] = Field(
alias="api_key",
default_factory=secret_from_env(
["AZURE_OPENAI_API_KEY", "OPENAI_API_KEY"], default=None
),
)
azure_ad_token: Optional[SecretStr] = Field(
default_factory=secret_from_env("AZURE_OPENAI_AD_TOKEN", default=None)
)
"""Your Azure Active Directory token.
Automatically inferred from env var `AZURE_OPENAI_AD_TOKEN` if not provided.
@ -61,7 +74,9 @@ class AzureOpenAI(BaseOpenAI):
Will be invoked on every request.
"""
openai_api_type: str = ""
openai_api_type: Optional[str] = Field(
default_factory=from_env("OPENAI_API_TYPE", default="azure")
)
"""Legacy, for openai<1.0.0 support."""
validate_base_url: bool = True
"""For backwards compatibility. If legacy val openai_api_base is passed in, try to
@ -85,7 +100,7 @@ class AzureOpenAI(BaseOpenAI):
"""Return whether this model can be serialized by Langchain."""
return True
@root_validator()
@root_validator(pre=False, skip_on_failure=True, allow_reuse=True)
def validate_environment(cls, values: Dict) -> Dict:
"""Validate that api key and python package exists in environment."""
if values["n"] < 1:
@ -94,43 +109,6 @@ class AzureOpenAI(BaseOpenAI):
raise ValueError("Cannot stream results when n > 1.")
if values["streaming"] and values["best_of"] > 1:
raise ValueError("Cannot stream results when best_of > 1.")
# Check OPENAI_KEY for backwards compatibility.
# TODO: Remove OPENAI_API_KEY support to avoid possible conflict when using
# other forms of azure credentials.
openai_api_key = (
values["openai_api_key"]
or os.getenv("AZURE_OPENAI_API_KEY")
or os.getenv("OPENAI_API_KEY")
)
values["openai_api_key"] = (
convert_to_secret_str(openai_api_key) if openai_api_key else None
)
values["azure_endpoint"] = values["azure_endpoint"] or os.getenv(
"AZURE_OPENAI_ENDPOINT"
)
azure_ad_token = values["azure_ad_token"] or os.getenv("AZURE_OPENAI_AD_TOKEN")
values["azure_ad_token"] = (
convert_to_secret_str(azure_ad_token) if azure_ad_token else None
)
values["openai_api_base"] = values["openai_api_base"] or os.getenv(
"OPENAI_API_BASE"
)
values["openai_proxy"] = get_from_dict_or_env(
values, "openai_proxy", "OPENAI_PROXY", default=""
)
values["openai_organization"] = (
values["openai_organization"]
or os.getenv("OPENAI_ORG_ID")
or os.getenv("OPENAI_ORGANIZATION")
)
values["openai_api_version"] = values["openai_api_version"] or os.getenv(
"OPENAI_API_VERSION"
)
values["openai_api_type"] = get_from_dict_or_env(
values, "openai_api_type", "OPENAI_API_TYPE", default="azure"
)
# 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"]

48
libs/partners/openai/langchain_openai/llms/base.py
View File

@ -1,7 +1,6 @@
from __future__ import annotations
import logging
import os
import sys
from typing import (
AbstractSet,
@ -28,12 +27,8 @@ from langchain_core.callbacks import (
from langchain_core.language_models.llms import BaseLLM
from langchain_core.outputs import Generation, GenerationChunk, LLMResult
from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
from langchain_core.utils import (
convert_to_secret_str,
get_from_dict_or_env,
get_pydantic_field_names,
)
from langchain_core.utils.utils import build_extra_kwargs
from langchain_core.utils import get_pydantic_field_names
from langchain_core.utils.utils import build_extra_kwargs, from_env, secret_from_env
logger = logging.getLogger(__name__)
@ -90,15 +85,26 @@ class BaseOpenAI(BaseLLM):
"""Generates best_of completions server-side and returns the "best"."""
model_kwargs: Dict[str, Any] = Field(default_factory=dict)
"""Holds any model parameters valid for `create` call not explicitly specified."""
openai_api_key: Optional[SecretStr] = Field(default=None, alias="api_key")
openai_api_key: Optional[SecretStr] = Field(
alias="api_key", default_factory=secret_from_env("OPENAI_API_KEY", default=None)
)
"""Automatically inferred from env var `OPENAI_API_KEY` if not provided."""
openai_api_base: Optional[str] = Field(default=None, alias="base_url")
openai_api_base: Optional[str] = Field(
alias="base_url", default_factory=from_env("OPENAI_API_BASE", default=None)
)
"""Base URL path for API requests, leave blank if not using a proxy or service
emulator."""
openai_organization: Optional[str] = Field(default=None, alias="organization")
openai_organization: Optional[str] = Field(
alias="organization",
default_factory=from_env(
["OPENAI_ORG_ID", "OPENAI_ORGANIZATION"], default=None
),
)
"""Automatically inferred from env var `OPENAI_ORG_ID` if not provided."""
# to support explicit proxy for OpenAI
openai_proxy: Optional[str] = None
openai_proxy: Optional[str] = Field(
default_factory=from_env("OPENAI_PROXY", default=None)
)
batch_size: int = 20
"""Batch size to use when passing multiple documents to generate."""
request_timeout: Union[float, Tuple[float, float], Any, None] = Field(
@ -161,7 +167,7 @@ class BaseOpenAI(BaseLLM):
)
return values
@root_validator()
@root_validator(pre=False, skip_on_failure=True, allow_reuse=True)
def validate_environment(cls, values: Dict) -> Dict:
"""Validate that api key and python package exists in environment."""
if values["n"] < 1:
@ -171,24 +177,6 @@ class BaseOpenAI(BaseLLM):
if values["streaming"] and values["best_of"] > 1:
raise ValueError("Cannot stream results when best_of > 1.")
openai_api_key = get_from_dict_or_env(
values, "openai_api_key", "OPENAI_API_KEY"
)
values["openai_api_key"] = (
convert_to_secret_str(openai_api_key) if openai_api_key else None
)
values["openai_api_base"] = values["openai_api_base"] or os.getenv(
"OPENAI_API_BASE"
)
values["openai_proxy"] = get_from_dict_or_env(
values, "openai_proxy", "OPENAI_PROXY", default=""
)
values["openai_organization"] = (
values["openai_organization"]
or os.getenv("OPENAI_ORG_ID")
or os.getenv("OPENAI_ORGANIZATION")
)
client_params = {
"api_key": (
values["openai_api_key"].get_secret_value()

3
libs/partners/openai/tests/unit_tests/chat_models/test_azure.py
View File

@ -1,6 +1,7 @@
"""Test Azure OpenAI Chat API wrapper."""
import os
from unittest import mock
from langchain_openai import AzureChatOpenAI
@ -39,7 +40,7 @@ def test_initialize_more() -> None:
def test_initialize_azure_openai_with_openai_api_base_set() -> None:
os.environ["OPENAI_API_BASE"] = "https://api.openai.com"
with mock.patch.dict(os.environ, {"OPENAI_API_BASE": "https://api.openai.com"}):
llm = AzureChatOpenAI( # type: ignore[call-arg, call-arg]
api_key="xyz", # type: ignore[arg-type]
azure_endpoint="my-base-url",

24
libs/partners/openai/tests/unit_tests/chat_models/test_azure_standard.py
View File

@ -1,6 +1,6 @@
"""Standard LangChain interface tests"""
from typing import Type
from typing import Tuple, Type
import pytest
from langchain_core.language_models import BaseChatModel
@ -25,3 +25,25 @@ class TestOpenAIStandard(ChatModelUnitTests):
@pytest.mark.xfail(reason="AzureOpenAI does not support tool_choice='any'")
def test_bind_tool_pydantic(self, model: BaseChatModel) -> None:
super().test_bind_tool_pydantic(model)
@property
def init_from_env_params(self) -> Tuple[dict, dict, dict]:
return (
{
"AZURE_OPENAI_API_KEY": "api_key",
"AZURE_OPENAI_ENDPOINT": "https://endpoint.com",
"AZURE_OPENAI_AD_TOKEN": "token",
"OPENAI_ORG_ID": "org_id",
"OPENAI_API_VERSION": "yyyy-mm-dd",
"OPENAI_API_TYPE": "type",
},
{},
{
"openai_api_key": "api_key",
"azure_endpoint": "https://endpoint.com",
"azure_ad_token": "token",
"openai_organization": "org_id",
"openai_api_version": "yyyy-mm-dd",
"openai_api_type": "type",
},
)

2
libs/partners/openai/tests/unit_tests/chat_models/test_base_standard.py
View File

@ -18,7 +18,7 @@ class TestOpenAIStandard(ChatModelUnitTests):
return (
{
"OPENAI_API_KEY": "api_key",
"OPENAI_ORGANIZATION": "org_id",
"OPENAI_ORG_ID": "org_id",
"OPENAI_API_BASE": "api_base",
"OPENAI_PROXY": "https://proxy.com",
},

3
libs/partners/openai/tests/unit_tests/embeddings/test_azure_embeddings.py
View File

@ -1,4 +1,5 @@
import os
from unittest import mock
from langchain_openai import AzureOpenAIEmbeddings
@ -15,7 +16,7 @@ def test_initialize_azure_openai() -> None:
def test_intialize_azure_openai_with_base_set() -> None:
os.environ["OPENAI_API_BASE"] = "https://api.openai.com"
with mock.patch.dict(os.environ, {"OPENAI_API_BASE": "https://api.openai.com"}):
embeddings = AzureOpenAIEmbeddings( # type: ignore[call-arg, call-arg]
model="text-embedding-large",
api_key="xyz", # type: ignore[arg-type]

38
libs/partners/openai/tests/unit_tests/embeddings/test_azure_standard.py Normal file
View File

@ -0,0 +1,38 @@
from typing import Tuple, Type
from langchain_core.embeddings import Embeddings
from langchain_standard_tests.unit_tests.embeddings import EmbeddingsUnitTests
from langchain_openai import AzureOpenAIEmbeddings
class TestAzureOpenAIStandard(EmbeddingsUnitTests):
@property
def embeddings_class(self) -> Type[Embeddings]:
return AzureOpenAIEmbeddings
@property
def embedding_model_params(self) -> dict:
return {"api_key": "api_key", "azure_endpoint": "https://endpoint.com"}
@property
def init_from_env_params(self) -> Tuple[dict, dict, dict]:
return (
{
"AZURE_OPENAI_API_KEY": "api_key",
"AZURE_OPENAI_ENDPOINT": "https://endpoint.com",
"AZURE_OPENAI_AD_TOKEN": "token",
"OPENAI_ORG_ID": "org_id",
"OPENAI_API_VERSION": "yyyy-mm-dd",
"OPENAI_API_TYPE": "type",
},
{},
{
"openai_api_key": "api_key",
"azure_endpoint": "https://endpoint.com",
"azure_ad_token": "token",
"openai_organization": "org_id",
"openai_api_version": "yyyy-mm-dd",
"openai_api_type": "type",
},
)

32
libs/partners/openai/tests/unit_tests/embeddings/test_base_standard.py Normal file
View File

@ -0,0 +1,32 @@
"""Standard LangChain interface tests"""
from typing import Tuple, Type
from langchain_core.embeddings import Embeddings
from langchain_standard_tests.unit_tests.embeddings import EmbeddingsUnitTests
from langchain_openai import OpenAIEmbeddings
class TestOpenAIStandard(EmbeddingsUnitTests):
@property
def embeddings_class(self) -> Type[Embeddings]:
return OpenAIEmbeddings
@property
def init_from_env_params(self) -> Tuple[dict, dict, dict]:
return (
{
"OPENAI_API_KEY": "api_key",
"OPENAI_ORG_ID": "org_id",
"OPENAI_API_BASE": "api_base",
"OPENAI_PROXY": "https://proxy.com",
},
{},
{
"openai_api_key": "api_key",
"openai_organization": "org_id",
"openai_api_base": "api_base",
"openai_proxy": "https://proxy.com",
},
)