mirror of
https://github.com/hwchase17/langchain.git
synced 2025-07-10 06:55:09 +00:00
clients -> private attributes
This commit is contained in:
parent
adcb5396d9
commit
4588e06794
@ -660,37 +660,37 @@ class AzureChatOpenAI(BaseChatOpenAI):
|
||||
return self
|
||||
|
||||
@property
|
||||
def _root_client(self) -> openai.AzureOpenAI:
|
||||
if self.root_client is not None:
|
||||
return self.root_client
|
||||
sync_specific = {"http_client": self._http_client}
|
||||
self.root_client = openai.AzureOpenAI(**self._client_params, **sync_specific) # type: ignore[call-overload]
|
||||
return self.root_client
|
||||
def root_client(self) -> openai.AzureOpenAI:
|
||||
if self._root_client is not None:
|
||||
return self._root_client
|
||||
sync_specific = {"http_client": self.http_client}
|
||||
self._root_client = openai.AzureOpenAI(**self._client_params, **sync_specific) # type: ignore[call-overload]
|
||||
return self._root_client
|
||||
|
||||
@property
|
||||
def _root_async_client(self) -> openai.AsyncAzureOpenAI:
|
||||
if self.root_async_client is not None:
|
||||
return self.root_async_client
|
||||
async_specific = {"http_client": self._http_async_client}
|
||||
self.root_async_client = openai.AsyncAzureOpenAI(
|
||||
def root_async_client(self) -> openai.AsyncAzureOpenAI:
|
||||
if self._root_async_client is not None:
|
||||
return self._root_async_client
|
||||
async_specific = {"http_client": self.http_async_client}
|
||||
self._root_async_client = openai.AsyncAzureOpenAI(
|
||||
**self._client_params,
|
||||
**async_specific, # type: ignore[call-overload]
|
||||
)
|
||||
return self._root_async_client
|
||||
|
||||
@property
|
||||
def _client(self) -> Any:
|
||||
if self.client is not None:
|
||||
return self.client
|
||||
self.client = self._root_client.chat.completions
|
||||
return self.client
|
||||
def client(self) -> Any:
|
||||
if self._client is not None:
|
||||
return self._client
|
||||
self._client = self.root_client.chat.completions
|
||||
return self._client
|
||||
|
||||
@property
|
||||
def _async_client(self) -> Any:
|
||||
if self.async_client is not None:
|
||||
return self.async_client
|
||||
self.async_client = self._root_async_client.chat.completions
|
||||
return self.async_client
|
||||
def async_client(self) -> Any:
|
||||
if self._async_client is not None:
|
||||
return self._async_client
|
||||
self._async_client = self.root_async_client.chat.completions
|
||||
return self._async_client
|
||||
|
||||
@property
|
||||
def _identifying_params(self) -> Dict[str, Any]:
|
||||
|
@ -396,10 +396,10 @@ class _AllReturnType(TypedDict):
|
||||
|
||||
|
||||
class BaseChatOpenAI(BaseChatModel):
|
||||
client: Any = Field(default=None, exclude=True) #: :meta private:
|
||||
async_client: Any = Field(default=None, exclude=True) #: :meta private:
|
||||
root_client: Any = Field(default=None, exclude=True) #: :meta private:
|
||||
root_async_client: Any = Field(default=None, exclude=True) #: :meta private:
|
||||
_client: Any = PrivateAttr(default=None) #: :meta private:
|
||||
_async_client: Any = PrivateAttr(default=None) #: :meta private:
|
||||
_root_client: Any = PrivateAttr(default=None) #: :meta private:
|
||||
_root_async_client: Any = PrivateAttr(default=None) #: :meta private:
|
||||
model_name: str = Field(default="gpt-3.5-turbo", alias="model")
|
||||
"""Model name to use."""
|
||||
temperature: Optional[float] = None
|
||||
@ -471,11 +471,11 @@ class BaseChatOpenAI(BaseChatModel):
|
||||
default_query: Union[Mapping[str, object], None] = None
|
||||
# Configure a custom httpx client. See the
|
||||
# [httpx documentation](https://www.python-httpx.org/api/#client) for more details.
|
||||
http_client: Union[Any, None] = Field(default=None, exclude=True)
|
||||
_http_client: Union[Any, None] = PrivateAttr(default=None)
|
||||
"""Optional httpx.Client. Only used for sync invocations. Must specify
|
||||
http_async_client as well if you'd like a custom client for async invocations.
|
||||
"""
|
||||
http_async_client: Union[Any, None] = Field(default=None, exclude=True)
|
||||
_http_async_client: Union[Any, None] = PrivateAttr(default=None)
|
||||
"""Optional httpx.AsyncClient. Only used for async invocations. Must specify
|
||||
http_client as well if you'd like a custom client for sync invocations."""
|
||||
stop: Optional[Union[List[str], str]] = Field(default=None, alias="stop_sequences")
|
||||
@ -523,6 +523,24 @@ class BaseChatOpenAI(BaseChatModel):
|
||||
values["temperature"] = 1
|
||||
return values
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
client: Optional[Any] = None,
|
||||
async_client: Optional[Any] = None,
|
||||
root_client: Optional[Any] = None,
|
||||
async_root_client: Optional[Any] = None,
|
||||
http_client: Optional[Any] = None,
|
||||
http_async_client: Optional[Any] = None,
|
||||
**kwargs: Any,
|
||||
) -> None:
|
||||
super().__init__(**kwargs)
|
||||
self._client = client
|
||||
self._async_client = async_client
|
||||
self._root_client = root_client
|
||||
self._async_root_client = async_root_client
|
||||
self._http_client = http_client
|
||||
self._http_async_client = http_async_client
|
||||
|
||||
@model_validator(mode="after")
|
||||
def validate_environment(self) -> Self:
|
||||
"""Validate that api key and python package exists in environment."""
|
||||
@ -551,10 +569,10 @@ class BaseChatOpenAI(BaseChatModel):
|
||||
if self.max_retries is not None:
|
||||
self._client_params["max_retries"] = self.max_retries
|
||||
|
||||
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
|
||||
http_client = self._http_client
|
||||
http_async_client = self._http_async_client
|
||||
raise ValueError(
|
||||
"Cannot specify 'openai_proxy' if one of "
|
||||
"'http_client'/'http_async_client' is already specified. Received:\n"
|
||||
@ -564,7 +582,7 @@ class BaseChatOpenAI(BaseChatModel):
|
||||
return self
|
||||
|
||||
@property
|
||||
def _http_client(self) -> Optional[httpx.Client]:
|
||||
def http_client(self) -> Optional[httpx.Client]:
|
||||
"""Optional httpx.Client. Only used for sync invocations.
|
||||
|
||||
Must specify http_async_client as well if you'd like a custom client for
|
||||
@ -573,8 +591,8 @@ class BaseChatOpenAI(BaseChatModel):
|
||||
# Configure a custom httpx client. See the
|
||||
# [httpx documentation](https://www.python-httpx.org/api/#client) for more
|
||||
# details.
|
||||
if self.http_client is not None:
|
||||
return self.http_client
|
||||
if self._http_client is not None:
|
||||
return self._http_client
|
||||
if not self.openai_proxy:
|
||||
return None
|
||||
try:
|
||||
@ -584,18 +602,18 @@ class BaseChatOpenAI(BaseChatModel):
|
||||
"Could not import httpx python package. "
|
||||
"Please install it with `pip install httpx`."
|
||||
) from e
|
||||
self.http_client = httpx.Client(proxy=self.openai_proxy)
|
||||
return self.http_client
|
||||
self._http_client = httpx.Client(proxy=self.openai_proxy)
|
||||
return self._http_client
|
||||
|
||||
@property
|
||||
def _http_async_client(self) -> Optional[httpx.AsyncClient]:
|
||||
def http_async_client(self) -> Optional[httpx.AsyncClient]:
|
||||
"""Optional httpx.AsyncClient. Only used for async invocations.
|
||||
|
||||
Must specify http_client as well if you'd like a custom client for sync
|
||||
invocations.
|
||||
"""
|
||||
if self.http_async_client is not None:
|
||||
return self.http_async_client
|
||||
if self._http_async_client is not None:
|
||||
return self._http_async_client
|
||||
if not self.openai_proxy:
|
||||
return None
|
||||
try:
|
||||
@ -605,41 +623,41 @@ 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)
|
||||
return self.http_async_client
|
||||
self._http_async_client = httpx.AsyncClient(proxy=self.openai_proxy)
|
||||
return self._http_async_client
|
||||
|
||||
@property
|
||||
def _root_client(self) -> openai.OpenAI:
|
||||
if self.root_client is not None:
|
||||
return self.root_client
|
||||
sync_specific = {"http_client": self._http_client}
|
||||
self.root_client = openai.OpenAI(**self._client_params, **sync_specific) # type: ignore[arg-type]
|
||||
return self.root_client
|
||||
def root_client(self) -> openai.OpenAI:
|
||||
if self._root_client is not None:
|
||||
return self._root_client
|
||||
sync_specific = {"http_client": self.http_client}
|
||||
self._root_client = openai.OpenAI(**self._client_params, **sync_specific) # type: ignore[arg-type]
|
||||
return self._root_client
|
||||
|
||||
@property
|
||||
def _root_async_client(self) -> openai.AsyncOpenAI:
|
||||
if self.root_async_client is not None:
|
||||
return self.root_async_client
|
||||
async_specific = {"http_client": self._http_async_client}
|
||||
self.root_async_client = openai.AsyncOpenAI(
|
||||
def root_async_client(self) -> openai.AsyncOpenAI:
|
||||
if self._root_async_client is not None:
|
||||
return self._root_async_client
|
||||
async_specific = {"http_client": self.http_async_client}
|
||||
self._root_async_client = openai.AsyncOpenAI(
|
||||
**self._client_params,
|
||||
**async_specific, # type: ignore[arg-type]
|
||||
)
|
||||
return self.root_async_client
|
||||
return self._root_async_client
|
||||
|
||||
@property
|
||||
def _client(self) -> Any:
|
||||
if self.client is not None:
|
||||
return self.client
|
||||
self.client = self._root_client.chat.completions
|
||||
return self.client
|
||||
def client(self) -> Any:
|
||||
if self._client is not None:
|
||||
return self._client
|
||||
self._client = self.root_client.chat.completions
|
||||
return self._client
|
||||
|
||||
@property
|
||||
def _async_client(self) -> Any:
|
||||
if self.async_client is not None:
|
||||
return self.async_client
|
||||
self.async_client = self._root_async_client.chat.completions
|
||||
return self.async_client
|
||||
def async_client(self) -> Any:
|
||||
if self._async_client is not None:
|
||||
return self._async_client
|
||||
self._async_client = self.root_async_client.chat.completions
|
||||
return self._async_client
|
||||
|
||||
@property
|
||||
def _default_params(self) -> Dict[str, Any]:
|
||||
@ -766,15 +784,15 @@ class BaseChatOpenAI(BaseChatModel):
|
||||
"specified."
|
||||
)
|
||||
payload.pop("stream")
|
||||
response_stream = self._root_client.beta.chat.completions.stream(**payload)
|
||||
response_stream = self.root_client.beta.chat.completions.stream(**payload)
|
||||
context_manager = response_stream
|
||||
else:
|
||||
if self.include_response_headers:
|
||||
raw_response = self._client.with_raw_response.create(**payload)
|
||||
raw_response = self.client.with_raw_response.create(**payload)
|
||||
response = raw_response.parse()
|
||||
base_generation_info = {"headers": dict(raw_response.headers)}
|
||||
else:
|
||||
response = self._client.create(**payload)
|
||||
response = self.client.create(**payload)
|
||||
context_manager = response
|
||||
try:
|
||||
with context_manager as response:
|
||||
@ -834,15 +852,15 @@ class BaseChatOpenAI(BaseChatModel):
|
||||
)
|
||||
payload.pop("stream")
|
||||
try:
|
||||
response = self._root_client.beta.chat.completions.parse(**payload)
|
||||
response = self.root_client.beta.chat.completions.parse(**payload)
|
||||
except openai.BadRequestError as e:
|
||||
_handle_openai_bad_request(e)
|
||||
elif self.include_response_headers:
|
||||
raw_response = self._client.with_raw_response.create(**payload)
|
||||
raw_response = self.client.with_raw_response.create(**payload)
|
||||
response = raw_response.parse()
|
||||
generation_info = {"headers": dict(raw_response.headers)}
|
||||
else:
|
||||
response = self._client.create(**payload)
|
||||
response = self.client.create(**payload)
|
||||
return self._create_chat_result(response, generation_info)
|
||||
|
||||
def _get_request_payload(
|
||||
@ -930,19 +948,19 @@ class BaseChatOpenAI(BaseChatModel):
|
||||
"specified."
|
||||
)
|
||||
payload.pop("stream")
|
||||
response_stream = self._root_async_client.beta.chat.completions.stream(
|
||||
response_stream = self.root_async_client.beta.chat.completions.stream(
|
||||
**payload
|
||||
)
|
||||
context_manager = response_stream
|
||||
else:
|
||||
if self.include_response_headers:
|
||||
raw_response = await self._async_client.with_raw_response.create(
|
||||
raw_response = await self.async_client.with_raw_response.create(
|
||||
**payload
|
||||
)
|
||||
response = raw_response.parse()
|
||||
base_generation_info = {"headers": dict(raw_response.headers)}
|
||||
else:
|
||||
response = await self._async_client.create(**payload)
|
||||
response = await self.async_client.create(**payload)
|
||||
context_manager = response
|
||||
try:
|
||||
async with context_manager as response:
|
||||
@ -1002,17 +1020,17 @@ class BaseChatOpenAI(BaseChatModel):
|
||||
)
|
||||
payload.pop("stream")
|
||||
try:
|
||||
response = await self._root_async_client.beta.chat.completions.parse(
|
||||
response = await self.root_async_client.beta.chat.completions.parse(
|
||||
**payload
|
||||
)
|
||||
except openai.BadRequestError as e:
|
||||
_handle_openai_bad_request(e)
|
||||
elif self.include_response_headers:
|
||||
raw_response = await self._async_client.with_raw_response.create(**payload)
|
||||
raw_response = await self.async_client.with_raw_response.create(**payload)
|
||||
response = raw_response.parse()
|
||||
generation_info = {"headers": dict(raw_response.headers)}
|
||||
else:
|
||||
response = await self._async_client.create(**payload)
|
||||
response = await self.async_client.create(**payload)
|
||||
return await run_in_executor(
|
||||
None, self._create_chat_result, response, generation_info
|
||||
)
|
||||
@ -2023,6 +2041,9 @@ class ChatOpenAI(BaseChatOpenAI): # type: ignore[override]
|
||||
max_tokens: Optional[int] = Field(default=None, alias="max_completion_tokens")
|
||||
"""Maximum number of tokens to generate."""
|
||||
|
||||
def __init__(self, *args: Any, **kwargs: Any) -> None:
|
||||
super().__init__(*args, **kwargs)
|
||||
|
||||
@property
|
||||
def lc_secrets(self) -> Dict[str, str]:
|
||||
return {"openai_api_key": "OPENAI_API_KEY"}
|
||||
|
@ -660,9 +660,6 @@ def test_openai_structured_output(model: str) -> None:
|
||||
def test_openai_proxy() -> None:
|
||||
"""Test ChatOpenAI with proxy."""
|
||||
chat_openai = ChatOpenAI(openai_proxy="http://localhost:8080")
|
||||
assert chat_openai.client is None
|
||||
_ = chat_openai._client # force client to instantiate
|
||||
assert chat_openai.client is not None
|
||||
mounts = chat_openai.client._client._client._mounts
|
||||
assert len(mounts) == 1
|
||||
for key, value in mounts.items():
|
||||
@ -671,9 +668,6 @@ def test_openai_proxy() -> None:
|
||||
assert proxy.host == b"localhost"
|
||||
assert proxy.port == 8080
|
||||
|
||||
assert chat_openai.async_client is None
|
||||
_ = chat_openai._async_client # force client to instantiate
|
||||
assert chat_openai.async_client is not None
|
||||
async_client_mounts = chat_openai.async_client._client._client._mounts
|
||||
assert len(async_client_mounts) == 1
|
||||
for key, value in async_client_mounts.items():
|
||||
|
@ -14,6 +14,7 @@ def test_initialize_azure_openai() -> None:
|
||||
azure_deployment="35-turbo-dev",
|
||||
openai_api_version="2023-05-15",
|
||||
azure_endpoint="my-base-url",
|
||||
http_client=None,
|
||||
)
|
||||
assert llm.deployment_name == "35-turbo-dev"
|
||||
assert llm.openai_api_version == "2023-05-15"
|
||||
|
@ -298,7 +298,7 @@ async def test_glm4_astream(mock_glm4_completion: list) -> None:
|
||||
usage_chunk = mock_glm4_completion[-1]
|
||||
|
||||
usage_metadata: Optional[UsageMetadata] = None
|
||||
with patch.object(llm, "async_client", mock_client):
|
||||
with patch.object(llm, "_async_client", mock_client):
|
||||
async for chunk in llm.astream("你的名字叫什么?只回答名字"):
|
||||
assert isinstance(chunk, AIMessageChunk)
|
||||
if chunk.usage_metadata is not None:
|
||||
@ -323,7 +323,7 @@ def test_glm4_stream(mock_glm4_completion: list) -> None:
|
||||
usage_chunk = mock_glm4_completion[-1]
|
||||
|
||||
usage_metadata: Optional[UsageMetadata] = None
|
||||
with patch.object(llm, "client", mock_client):
|
||||
with patch.object(llm, "_client", mock_client):
|
||||
for chunk in llm.stream("你的名字叫什么?只回答名字"):
|
||||
assert isinstance(chunk, AIMessageChunk)
|
||||
if chunk.usage_metadata is not None:
|
||||
@ -378,7 +378,7 @@ async def test_deepseek_astream(mock_deepseek_completion: list) -> None:
|
||||
mock_client.create = mock_create
|
||||
usage_chunk = mock_deepseek_completion[-1]
|
||||
usage_metadata: Optional[UsageMetadata] = None
|
||||
with patch.object(llm, "async_client", mock_client):
|
||||
with patch.object(llm, "_async_client", mock_client):
|
||||
async for chunk in llm.astream("你的名字叫什么?只回答名字"):
|
||||
assert isinstance(chunk, AIMessageChunk)
|
||||
if chunk.usage_metadata is not None:
|
||||
@ -402,7 +402,7 @@ def test_deepseek_stream(mock_deepseek_completion: list) -> None:
|
||||
mock_client.create = mock_create
|
||||
usage_chunk = mock_deepseek_completion[-1]
|
||||
usage_metadata: Optional[UsageMetadata] = None
|
||||
with patch.object(llm, "client", mock_client):
|
||||
with patch.object(llm, "_client", mock_client):
|
||||
for chunk in llm.stream("你的名字叫什么?只回答名字"):
|
||||
assert isinstance(chunk, AIMessageChunk)
|
||||
if chunk.usage_metadata is not None:
|
||||
@ -446,7 +446,7 @@ async def test_openai_astream(mock_openai_completion: list) -> None:
|
||||
mock_client.create = mock_create
|
||||
usage_chunk = mock_openai_completion[-1]
|
||||
usage_metadata: Optional[UsageMetadata] = None
|
||||
with patch.object(llm, "async_client", mock_client):
|
||||
with patch.object(llm, "_async_client", mock_client):
|
||||
async for chunk in llm.astream("你的名字叫什么?只回答名字"):
|
||||
assert isinstance(chunk, AIMessageChunk)
|
||||
if chunk.usage_metadata is not None:
|
||||
@ -470,7 +470,7 @@ def test_openai_stream(mock_openai_completion: list) -> None:
|
||||
mock_client.create = mock_create
|
||||
usage_chunk = mock_openai_completion[-1]
|
||||
usage_metadata: Optional[UsageMetadata] = None
|
||||
with patch.object(llm, "client", mock_client):
|
||||
with patch.object(llm, "_client", mock_client):
|
||||
for chunk in llm.stream("你的名字叫什么?只回答名字"):
|
||||
assert isinstance(chunk, AIMessageChunk)
|
||||
if chunk.usage_metadata is not None:
|
||||
@ -533,7 +533,7 @@ def mock_async_client(mock_completion: dict) -> AsyncMock:
|
||||
def test_openai_invoke(mock_client: MagicMock) -> None:
|
||||
llm = ChatOpenAI()
|
||||
|
||||
with patch.object(llm, "client", mock_client):
|
||||
with patch.object(llm, "_client", mock_client):
|
||||
res = llm.invoke("bar")
|
||||
assert res.content == "Bar Baz"
|
||||
|
||||
@ -541,13 +541,13 @@ def test_openai_invoke(mock_client: MagicMock) -> None:
|
||||
assert "headers" not in res.response_metadata
|
||||
assert mock_client.create.called
|
||||
|
||||
assert llm.async_client is None
|
||||
assert llm._async_client is None
|
||||
|
||||
|
||||
async def test_openai_ainvoke(mock_async_client: AsyncMock) -> None:
|
||||
llm = ChatOpenAI()
|
||||
|
||||
with patch.object(llm, "async_client", mock_async_client):
|
||||
with patch.object(llm, "_async_client", mock_async_client):
|
||||
res = await llm.ainvoke("bar")
|
||||
assert res.content == "Bar Baz"
|
||||
|
||||
@ -575,7 +575,7 @@ def test__get_encoding_model(model: str) -> None:
|
||||
def test_openai_invoke_name(mock_client: MagicMock) -> None:
|
||||
llm = ChatOpenAI()
|
||||
|
||||
with patch.object(llm, "client", mock_client):
|
||||
with patch.object(llm, "_client", mock_client):
|
||||
messages = [HumanMessage(content="Foo", name="Katie")]
|
||||
res = llm.invoke(messages)
|
||||
call_args, call_kwargs = mock_client.create.call_args
|
||||
|
Loading…
Reference in New Issue
Block a user