github/langchain
1
0
Fork 0
mirror of https://github.com/hwchase17/langchain.git synced 2025-09-26 22:05:29 +00:00
Code Issues Packages Projects Releases Wiki Activity

fmt

Browse Source
This commit is contained in:
Bagatur
2024-09-03 16:48:53 -07:00
parent 615f8b0d47
commit 5f5287c3b0
8 changed files with 60 additions and 92 deletions
Download Patch File Download Diff File Expand all files Collapse all files

20
libs/partners/openai/langchain_openai/chat_models/azure.py
View File

@@ -31,16 +31,15 @@ from langchain_core.output_parsers.openai_tools import (
PydanticToolsParser,
)
from langchain_core.outputs import ChatResult
from pydantic import BaseModel, Field, SecretStr, model_validator
from langchain_core.runnables import Runnable, RunnableMap, RunnablePassthrough
from langchain_core.tools import BaseTool
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
from langchain_openai.chat_models.base import BaseChatOpenAI
from pydantic import BaseModel, Field, SecretStr, model_validator
from typing_extensions import Self
from langchain_openai.chat_models.base import BaseChatOpenAI
logger = logging.getLogger(__name__)
@@ -604,19 +603,15 @@ class AzureChatOpenAI(BaseChatOpenAI):
"Or you can equivalently specify:\n\n"
'base_url="https://xxx.openai.azure.com/openai/deployments/my-deployment"'
)
client_params = {
client_params: dict = {
"api_version": self.openai_api_version,
"azure_endpoint": self.azure_endpoint,
"azure_deployment": self.deployment_name,
"api_key": (
self.openai_api_key.get_secret_value()
if self.openai_api_key
else None
self.openai_api_key.get_secret_value() if self.openai_api_key else None
),
"azure_ad_token": (
self.azure_ad_token.get_secret_value()
if self.azure_ad_token
else None
self.azure_ad_token.get_secret_value() if self.azure_ad_token else None
),
"azure_ad_token_provider": self.azure_ad_token_provider,
"organization": self.openai_organization,
@@ -628,12 +623,13 @@ class AzureChatOpenAI(BaseChatOpenAI):
}
if not (self.client or None):
sync_specific = {"http_client": self.http_client}
self.root_client = openai.AzureOpenAI(**client_params, **sync_specific)
self.root_client = openai.AzureOpenAI(**client_params, **sync_specific) # type: ignore[arg-type]
self.client = self.root_client.chat.completions
if not (self.async_client or None):
async_specific = {"http_client": self.http_async_client}
self.root_async_client = openai.AsyncAzureOpenAI(
**client_params, **async_specific
**client_params,
**async_specific, # type: ignore[arg-type]
)
self.async_client = self.root_async_client.chat.completions
return self

34
libs/partners/openai/langchain_openai/chat_models/base.py
View File

@@ -73,11 +73,10 @@ from langchain_core.output_parsers.openai_tools import (
parse_tool_call,
)
from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
from pydantic import BaseModel, Field, model_validator, SecretStr
from langchain_core.runnables import Runnable, RunnableMap, RunnablePassthrough, chain
from langchain_core.runnables.config import run_in_executor
from langchain_core.tools import BaseTool
from langchain_core.utils import get_from_dict_or_env, get_pydantic_field_names
from langchain_core.utils import get_pydantic_field_names
from langchain_core.utils.function_calling import (
convert_to_openai_function,
convert_to_openai_tool,
@@ -88,10 +87,9 @@ from langchain_core.utils.pydantic import (
is_basemodel_subclass,
)
from langchain_core.utils.utils import build_extra_kwargs, from_env, secret_from_env
from pydantic import ConfigDict
from pydantic import BaseModel, ConfigDict, Field, SecretStr, model_validator
from typing_extensions import Self
logger = logging.getLogger(__name__)
@@ -361,8 +359,7 @@ class BaseChatOpenAI(BaseChatModel):
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(
alias="api_key",
default_factory=secret_from_env("OPENAI_API_KEY", default=None),
alias="api_key", default_factory=secret_from_env("OPENAI_API_KEY", default=None)
)
openai_api_base: Optional[str] = Field(default=None, alias="base_url")
"""Base URL path for API requests, leave blank if not using a proxy or service
@@ -431,7 +428,7 @@ class BaseChatOpenAI(BaseChatModel):
include_response_headers: bool = False
"""Whether to include response headers in the output message response_metadata."""
model_config = ConfigDict(populate_by_name=True,)
model_config = ConfigDict(populate_by_name=True)
@model_validator(mode="before")
@classmethod
@@ -458,14 +455,10 @@ class BaseChatOpenAI(BaseChatModel):
or os.getenv("OPENAI_ORG_ID")
or os.getenv("OPENAI_ORGANIZATION")
)
self.openai_api_base = self.openai_api_base or os.getenv(
"OPENAI_API_BASE"
)
client_params = {
self.openai_api_base = self.openai_api_base or os.getenv("OPENAI_API_BASE")
client_params: dict = {
"api_key": (
self.openai_api_key.get_secret_value()
if self.openai_api_key
else None
self.openai_api_key.get_secret_value() if self.openai_api_key else None
),
"organization": self.openai_organization,
"base_url": self.openai_api_base,
@@ -474,9 +467,7 @@ class BaseChatOpenAI(BaseChatModel):
"default_headers": self.default_headers,
"default_query": self.default_query,
}
if self.openai_proxy and (
self.http_client or self.http_async_client
):
if self.openai_proxy and (self.http_client or self.http_async_client):
openai_proxy = self.openai_proxy
http_client = self.http_client
http_async_client = self.http_async_client
@@ -496,7 +487,7 @@ class BaseChatOpenAI(BaseChatModel):
) from e
self.http_client = httpx.Client(proxy=self.openai_proxy)
sync_specific = {"http_client": self.http_client}
self.root_client = openai.OpenAI(**client_params, **sync_specific)
self.root_client = openai.OpenAI(**client_params, **sync_specific) # type: ignore[arg-type]
self.client = self.root_client.chat.completions
if not (self.async_client or None):
if self.openai_proxy and not self.http_async_client:
@@ -507,12 +498,11 @@ class BaseChatOpenAI(BaseChatModel):
"Could not import httpx python package. "
"Please install it with `pip install httpx`."
) from e
self.http_async_client = httpx.AsyncClient(
proxy=self.openai_proxy
)
self.http_async_client = httpx.AsyncClient(proxy=self.openai_proxy)
async_specific = {"http_client": self.http_async_client}
self.root_async_client = openai.AsyncOpenAI(
**client_params, **async_specific
**client_params,
**async_specific, # type: ignore[arg-type]
)
self.async_client = self.root_async_client.chat.completions
return self

29
libs/partners/openai/langchain_openai/embeddings/azure.py
View File

@@ -2,15 +2,14 @@
from __future__ import annotations
from typing import Callable, Dict, Optional, Union
from typing import Callable, Optional, Union
import openai
from pydantic import Field, SecretStr, root_validator, model_validator
from langchain_core.utils import from_env, secret_from_env
from pydantic import Field, SecretStr, model_validator
from typing_extensions import Self, cast
from langchain_openai.embeddings.base import OpenAIEmbeddings
from typing_extensions import Self
class AzureOpenAIEmbeddings(OpenAIEmbeddings):
@@ -163,7 +162,7 @@ class AzureOpenAIEmbeddings(OpenAIEmbeddings):
openai_api_base = self.openai_api_base
if openai_api_base and self.validate_base_url:
if "/openai" not in openai_api_base:
self.openai_api_base += "/openai"
self.openai_api_base = cast(str, self.openai_api_base) + "/openai"
raise ValueError(
"As of openai>=1.0.0, Azure endpoints should be specified via "
"the `azure_endpoint` param not `openai_api_base` "
@@ -177,19 +176,15 @@ class AzureOpenAIEmbeddings(OpenAIEmbeddings):
"Instead use `deployment` (or alias `azure_deployment`) "
"and `azure_endpoint`."
)
client_params = {
client_params: dict = {
"api_version": self.openai_api_version,
"azure_endpoint": self.azure_endpoint,
"azure_deployment": self.deployment,
"api_key": (
self.openai_api_key.get_secret_value()
if self.openai_api_key
else None
self.openai_api_key.get_secret_value() if self.openai_api_key else None
),
"azure_ad_token": (
self.azure_ad_token.get_secret_value()
if self.azure_ad_token
else None
self.azure_ad_token.get_secret_value() if self.azure_ad_token else None
),
"azure_ad_token_provider": self.azure_ad_token_provider,
"organization": self.openai_organization,
@@ -200,14 +195,16 @@ class AzureOpenAIEmbeddings(OpenAIEmbeddings):
"default_query": self.default_query,
}
if not (self.client or None):
sync_specific = {"http_client": self.http_client}
sync_specific: dict = {"http_client": self.http_client}
self.client = openai.AzureOpenAI(
**client_params, **sync_specific
**client_params, # type: ignore[arg-type]
**sync_specific,
).embeddings
if not (self.async_client or None):
async_specific = {"http_client": self.http_async_client}
async_specific: dict = {"http_client": self.http_async_client}
self.async_client = openai.AsyncAzureOpenAI(
**client_params, **async_specific
**client_params, # type: ignore[arg-type]
**async_specific,
).embeddings
return self

28
libs/partners/openai/langchain_openai/embeddings/base.py
View File

@@ -20,13 +20,10 @@ from typing import (
import openai
import tiktoken
from langchain_core.embeddings import Embeddings
from pydantic import BaseModel, Field, SecretStr, root_validator, model_validator
from langchain_core.utils import from_env, get_pydantic_field_names, secret_from_env
from pydantic import ConfigDict
from pydantic import BaseModel, ConfigDict, Field, SecretStr, model_validator
from typing_extensions import Self
logger = logging.getLogger(__name__)
@@ -267,7 +264,7 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
"""Whether to check the token length of inputs and automatically split inputs
longer than embedding_ctx_length."""
model_config = ConfigDict(extra="forbid",populate_by_name=True,)
model_config = ConfigDict(extra="forbid", populate_by_name=True)
@model_validator(mode="before")
@classmethod
@@ -304,11 +301,9 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
"If you are using Azure, "
"please use the `AzureOpenAIEmbeddings` class."
)
client_params = {
client_params: dict = {
"api_key": (
self.openai_api_key.get_secret_value()
if self.openai_api_key
else None
self.openai_api_key.get_secret_value() if self.openai_api_key else None
),
"organization": self.openai_organization,
"base_url": self.openai_api_base,
@@ -318,9 +313,7 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
"default_query": self.default_query,
}
if self.openai_proxy and (
self.http_client or self.http_async_client
):
if self.openai_proxy and (self.http_client or self.http_async_client):
openai_proxy = self.openai_proxy
http_client = self.http_client
http_async_client = self.http_async_client
@@ -340,9 +333,7 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
) from e
self.http_client = httpx.Client(proxy=self.openai_proxy)
sync_specific = {"http_client": self.http_client}
self.client = openai.OpenAI(
**client_params, **sync_specific
).embeddings
self.client = openai.OpenAI(**client_params, **sync_specific).embeddings # type: ignore[arg-type]
if not (self.async_client or None):
if self.openai_proxy and not self.http_async_client:
try:
@@ -352,12 +343,11 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
"Could not import httpx python package. "
"Please install it with `pip install httpx`."
) from e
self.http_async_client = httpx.AsyncClient(
proxy=self.openai_proxy
)
self.http_async_client = httpx.AsyncClient(proxy=self.openai_proxy)
async_specific = {"http_client": self.http_async_client}
self.async_client = openai.AsyncOpenAI(
**client_params, **async_specific
**client_params,
**async_specific, # type: ignore[arg-type]
).embeddings
return self

15
libs/partners/openai/langchain_openai/llms/azure.py
View File

@@ -5,12 +5,11 @@ from typing import Any, Callable, Dict, List, Mapping, Optional, Union
import openai
from langchain_core.language_models import LangSmithParams
from pydantic import Field, SecretStr, root_validator, model_validator
from langchain_core.utils import from_env, secret_from_env
from pydantic import Field, SecretStr, model_validator
from typing_extensions import Self, cast
from langchain_openai.llms.base import BaseOpenAI
from typing_extensions import Self
logger = logging.getLogger(__name__)
@@ -117,7 +116,7 @@ class AzureOpenAI(BaseOpenAI):
if openai_api_base and self.validate_base_url:
if "/openai" not in openai_api_base:
self.openai_api_base = (
self.openai_api_base.rstrip("/") + "/openai"
cast(str, self.openai_api_base).rstrip("/") + "/openai"
)
raise ValueError(
"As of openai>=1.0.0, Azure endpoints should be specified via "
@@ -133,7 +132,7 @@ class AzureOpenAI(BaseOpenAI):
"and `azure_endpoint`."
)
self.deployment_name = None
client_params = {
client_params: dict = {
"api_version": self.openai_api_version,
"azure_endpoint": self.azure_endpoint,
"azure_deployment": self.deployment_name,
@@ -154,12 +153,14 @@ class AzureOpenAI(BaseOpenAI):
if not (self.client or None):
sync_specific = {"http_client": self.http_client}
self.client = openai.AzureOpenAI(
**client_params, **sync_specific
**client_params,
**sync_specific, # type: ignore[arg-type]
).completions
if not (self.async_client or None):
async_specific = {"http_client": self.http_async_client}
self.async_client = openai.AsyncAzureOpenAI(
**client_params, **async_specific
**client_params,
**async_specific, # type: ignore[arg-type]
).completions
return self

20
libs/partners/openai/langchain_openai/llms/base.py
View File

@@ -26,14 +26,11 @@ from langchain_core.callbacks import (
)
from langchain_core.language_models.llms import BaseLLM
from langchain_core.outputs import Generation, GenerationChunk, LLMResult
from pydantic import Field, SecretStr, root_validator, model_validator
from langchain_core.utils import get_pydantic_field_names
from langchain_core.utils.utils import build_extra_kwargs, from_env, secret_from_env
from pydantic import ConfigDict
from pydantic import ConfigDict, Field, SecretStr, model_validator
from typing_extensions import Self
logger = logging.getLogger(__name__)
@@ -156,7 +153,7 @@ class BaseOpenAI(BaseLLM):
"""Optional additional JSON properties to include in the request parameters when
making requests to OpenAI compatible APIs, such as vLLM."""
model_config = ConfigDict(populate_by_name=True,)
model_config = ConfigDict(populate_by_name=True)
@model_validator(mode="before")
@classmethod
@@ -179,11 +176,9 @@ class BaseOpenAI(BaseLLM):
if self.streaming and self.best_of > 1:
raise ValueError("Cannot stream results when best_of > 1.")
client_params = {
client_params: dict = {
"api_key": (
self.openai_api_key.get_secret_value()
if self.openai_api_key
else None
self.openai_api_key.get_secret_value() if self.openai_api_key else None
),
"organization": self.openai_organization,
"base_url": self.openai_api_base,
@@ -194,13 +189,12 @@ class BaseOpenAI(BaseLLM):
}
if not (self.client or None):
sync_specific = {"http_client": self.http_client}
self.client = openai.OpenAI(
**client_params, **sync_specific
).completions
self.client = openai.OpenAI(**client_params, **sync_specific).completions # type: ignore[arg-type]
if not (self.async_client or None):
async_specific = {"http_client": self.http_async_client}
self.async_client = openai.AsyncOpenAI(
**client_params, **async_specific
**client_params,
**async_specific, # type: ignore[arg-type]
).completions
return self

2
libs/partners/openai/tests/integration_tests/chat_models/test_base.py
View File

@@ -20,13 +20,13 @@ from langchain_core.messages import (
)
from langchain_core.outputs import ChatGeneration, ChatResult, LLMResult
from langchain_core.prompts import ChatPromptTemplate
from pydantic import BaseModel, Field
from langchain_standard_tests.integration_tests.chat_models import (
_validate_tool_call_message,
)
from langchain_standard_tests.integration_tests.chat_models import (
magic_function as invalid_magic_function,
)
from pydantic import BaseModel, Field
from langchain_openai import ChatOpenAI
from tests.unit_tests.fake.callbacks import FakeCallbackHandler

4
libs/partners/openai/tests/unit_tests/fake/callbacks.py
View File

@@ -188,7 +188,7 @@ class FakeCallbackHandler(BaseCallbackHandler, BaseFakeCallbackHandlerMixin):
def on_retriever_error(self, *args: Any, **kwargs: Any) -> Any:
self.on_retriever_error_common()
def __deepcopy__(self, memo: dict) -> "FakeCallbackHandler":
def __deepcopy__(self, memo: dict) -> "FakeCallbackHandler": # type: ignore[override]
return self
@@ -266,5 +266,5 @@ class FakeAsyncCallbackHandler(AsyncCallbackHandler, BaseFakeCallbackHandlerMixi
async def on_text(self, *args: Any, **kwargs: Any) -> None:
self.on_text_common()
def __deepcopy__(self, memo: dict) -> "FakeAsyncCallbackHandler":
def __deepcopy__(self, memo: dict) -> "FakeAsyncCallbackHandler": # type: ignore[override]
return self