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clients -> private attributes

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This commit is contained in:
Chester Curme 2025-02-21 19:08:41 -05:00
parent adcb5396d9
commit 4588e06794
5 changed files with 106 additions and 90 deletions
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42
libs/partners/openai/langchain_openai/chat_models/azure.py
View File

@ -660,37 +660,37 @@ class AzureChatOpenAI(BaseChatOpenAI):
return self return self
@property @property
def _root_client(self) -> openai.AzureOpenAI: def root_client(self) -> openai.AzureOpenAI:
if self.root_client is not None: if self._root_client is not None:
return self.root_client return self._root_client
sync_specific = {"http_client": self._http_client} sync_specific = {"http_client": self.http_client}
self.root_client = openai.AzureOpenAI(**self._client_params, **sync_specific) # type: ignore[call-overload] self._root_client = openai.AzureOpenAI(**self._client_params, **sync_specific) # type: ignore[call-overload]
return self.root_client return self._root_client
@property @property
def _root_async_client(self) -> openai.AsyncAzureOpenAI: def root_async_client(self) -> openai.AsyncAzureOpenAI:
if self.root_async_client is not None: if self._root_async_client is not None:
return self.root_async_client return self._root_async_client
async_specific = {"http_client": self._http_async_client} async_specific = {"http_client": self.http_async_client}
self.root_async_client = openai.AsyncAzureOpenAI( self._root_async_client = openai.AsyncAzureOpenAI(
**self._client_params, **self._client_params,
**async_specific, # type: ignore[call-overload] **async_specific, # type: ignore[call-overload]
) )
return self._root_async_client return self._root_async_client
@property @property
def _client(self) -> Any: def client(self) -> Any:
if self.client is not None: if self._client is not None:
return self.client return self._client
self.client = self._root_client.chat.completions self._client = self.root_client.chat.completions
return self.client return self._client
@property @property
def _async_client(self) -> Any: def async_client(self) -> Any:
if self.async_client is not None: if self._async_client is not None:
return self.async_client return self._async_client
self.async_client = self._root_async_client.chat.completions self._async_client = self.root_async_client.chat.completions
return self.async_client return self._async_client
@property @property
def _identifying_params(self) -> Dict[str, Any]: def _identifying_params(self) -> Dict[str, Any]:

127
libs/partners/openai/langchain_openai/chat_models/base.py
View File

@ -396,10 +396,10 @@ class _AllReturnType(TypedDict):
class BaseChatOpenAI(BaseChatModel): class BaseChatOpenAI(BaseChatModel):
client: Any = Field(default=None, exclude=True) #: :meta private: _client: Any = PrivateAttr(default=None) #: :meta private:
async_client: Any = Field(default=None, exclude=True) #: :meta private: _async_client: Any = PrivateAttr(default=None) #: :meta private:
root_client: Any = Field(default=None, exclude=True) #: :meta private: _root_client: Any = PrivateAttr(default=None) #: :meta private:
root_async_client: Any = Field(default=None, exclude=True) #: :meta private: _root_async_client: Any = PrivateAttr(default=None) #: :meta private:
model_name: str = Field(default="gpt-3.5-turbo", alias="model") model_name: str = Field(default="gpt-3.5-turbo", alias="model")
"""Model name to use.""" """Model name to use."""
temperature: Optional[float] = None temperature: Optional[float] = None
@ -471,11 +471,11 @@ class BaseChatOpenAI(BaseChatModel):
default_query: Union[Mapping[str, object], None] = None default_query: Union[Mapping[str, object], None] = None
# Configure a custom httpx client. See the # Configure a custom httpx client. See the
# [httpx documentation](https://www.python-httpx.org/api/#client) for more details. # [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 """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 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 """Optional httpx.AsyncClient. Only used for async invocations. Must specify
http_client as well if you'd like a custom client for sync invocations.""" 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") stop: Optional[Union[List[str], str]] = Field(default=None, alias="stop_sequences")
@ -523,6 +523,24 @@ class BaseChatOpenAI(BaseChatModel):
values["temperature"] = 1 values["temperature"] = 1
return values 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") @model_validator(mode="after")
def validate_environment(self) -> Self: def validate_environment(self) -> Self:
"""Validate that api key and python package exists in environment.""" """Validate that api key and python package exists in environment."""
@ -551,10 +569,10 @@ class BaseChatOpenAI(BaseChatModel):
if self.max_retries is not None: if self.max_retries is not None:
self._client_params["max_retries"] = self.max_retries 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 openai_proxy = self.openai_proxy
http_client = self.http_client http_client = self._http_client
http_async_client = self.http_async_client http_async_client = self._http_async_client
raise ValueError( raise ValueError(
"Cannot specify 'openai_proxy' if one of " "Cannot specify 'openai_proxy' if one of "
"'http_client'/'http_async_client' is already specified. Received:\n" "'http_client'/'http_async_client' is already specified. Received:\n"
@ -564,7 +582,7 @@ class BaseChatOpenAI(BaseChatModel):
return self return self
@property @property
def _http_client(self) -> Optional[httpx.Client]: def http_client(self) -> Optional[httpx.Client]:
"""Optional httpx.Client. Only used for sync invocations. """Optional httpx.Client. Only used for sync invocations.
Must specify http_async_client as well if you'd like a custom client for 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 # Configure a custom httpx client. See the
# [httpx documentation](https://www.python-httpx.org/api/#client) for more # [httpx documentation](https://www.python-httpx.org/api/#client) for more
# details. # details.
if self.http_client is not None: if self._http_client is not None:
return self.http_client return self._http_client
if not self.openai_proxy: if not self.openai_proxy:
return None return None
try: try:
@ -584,18 +602,18 @@ class BaseChatOpenAI(BaseChatModel):
"Could not import httpx python package. " "Could not import httpx python package. "
"Please install it with `pip install httpx`." "Please install it with `pip install httpx`."
) from e ) from e
self.http_client = httpx.Client(proxy=self.openai_proxy) self._http_client = httpx.Client(proxy=self.openai_proxy)
return self.http_client return self._http_client
@property @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. """Optional httpx.AsyncClient. Only used for async invocations.
Must specify http_client as well if you'd like a custom client for sync Must specify http_client as well if you'd like a custom client for sync
invocations. invocations.
""" """
if self.http_async_client is not None: if self._http_async_client is not None:
return self.http_async_client return self._http_async_client
if not self.openai_proxy: if not self.openai_proxy:
return None return None
try: try:
@ -605,41 +623,41 @@ class BaseChatOpenAI(BaseChatModel):
"Could not import httpx python package. " "Could not import httpx python package. "
"Please install it with `pip install httpx`." "Please install it with `pip install httpx`."
) from e ) from e
self.http_async_client = httpx.AsyncClient(proxy=self.openai_proxy) self._http_async_client = httpx.AsyncClient(proxy=self.openai_proxy)
return self.http_async_client return self._http_async_client
@property @property
def _root_client(self) -> openai.OpenAI: def root_client(self) -> openai.OpenAI:
if self.root_client is not None: if self._root_client is not None:
return self.root_client return self._root_client
sync_specific = {"http_client": self._http_client} sync_specific = {"http_client": self.http_client}
self.root_client = openai.OpenAI(**self._client_params, **sync_specific) # type: ignore[arg-type] self._root_client = openai.OpenAI(**self._client_params, **sync_specific) # type: ignore[arg-type]
return self.root_client return self._root_client
@property @property
def _root_async_client(self) -> openai.AsyncOpenAI: def root_async_client(self) -> openai.AsyncOpenAI:
if self.root_async_client is not None: if self._root_async_client is not None:
return self.root_async_client return self._root_async_client
async_specific = {"http_client": self._http_async_client} async_specific = {"http_client": self.http_async_client}
self.root_async_client = openai.AsyncOpenAI( self._root_async_client = openai.AsyncOpenAI(
**self._client_params, **self._client_params,
**async_specific, # type: ignore[arg-type] **async_specific, # type: ignore[arg-type]
) )
return self.root_async_client return self._root_async_client
@property @property
def _client(self) -> Any: def client(self) -> Any:
if self.client is not None: if self._client is not None:
return self.client return self._client
self.client = self._root_client.chat.completions self._client = self.root_client.chat.completions
return self.client return self._client
@property @property
def _async_client(self) -> Any: def async_client(self) -> Any:
if self.async_client is not None: if self._async_client is not None:
return self.async_client return self._async_client
self.async_client = self._root_async_client.chat.completions self._async_client = self.root_async_client.chat.completions
return self.async_client return self._async_client
@property @property
def _default_params(self) -> Dict[str, Any]: def _default_params(self) -> Dict[str, Any]:
@ -766,15 +784,15 @@ class BaseChatOpenAI(BaseChatModel):
"specified." "specified."
) )
payload.pop("stream") 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 context_manager = response_stream
else: else:
if self.include_response_headers: 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() response = raw_response.parse()
base_generation_info = {"headers": dict(raw_response.headers)} base_generation_info = {"headers": dict(raw_response.headers)}
else: else:
response = self._client.create(**payload) response = self.client.create(**payload)
context_manager = response context_manager = response
try: try:
with context_manager as response: with context_manager as response:
@ -834,15 +852,15 @@ class BaseChatOpenAI(BaseChatModel):
) )
payload.pop("stream") payload.pop("stream")
try: try:
response = self._root_client.beta.chat.completions.parse(**payload) response = self.root_client.beta.chat.completions.parse(**payload)
except openai.BadRequestError as e: except openai.BadRequestError as e:
_handle_openai_bad_request(e) _handle_openai_bad_request(e)
elif self.include_response_headers: 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() response = raw_response.parse()
generation_info = {"headers": dict(raw_response.headers)} generation_info = {"headers": dict(raw_response.headers)}
else: else:
response = self._client.create(**payload) response = self.client.create(**payload)
return self._create_chat_result(response, generation_info) return self._create_chat_result(response, generation_info)
def _get_request_payload( def _get_request_payload(
@ -930,19 +948,19 @@ class BaseChatOpenAI(BaseChatModel):
"specified." "specified."
) )
payload.pop("stream") payload.pop("stream")
response_stream = self._root_async_client.beta.chat.completions.stream( response_stream = self.root_async_client.beta.chat.completions.stream(
**payload **payload
) )
context_manager = response_stream context_manager = response_stream
else: else:
if self.include_response_headers: 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 **payload
) )
response = raw_response.parse() response = raw_response.parse()
base_generation_info = {"headers": dict(raw_response.headers)} base_generation_info = {"headers": dict(raw_response.headers)}
else: else:
response = await self._async_client.create(**payload) response = await self.async_client.create(**payload)
context_manager = response context_manager = response
try: try:
async with context_manager as response: async with context_manager as response:
@ -1002,17 +1020,17 @@ class BaseChatOpenAI(BaseChatModel):
) )
payload.pop("stream") payload.pop("stream")
try: try:
response = await self._root_async_client.beta.chat.completions.parse( response = await self.root_async_client.beta.chat.completions.parse(
**payload **payload
) )
except openai.BadRequestError as e: except openai.BadRequestError as e:
_handle_openai_bad_request(e) _handle_openai_bad_request(e)
elif self.include_response_headers: 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() response = raw_response.parse()
generation_info = {"headers": dict(raw_response.headers)} generation_info = {"headers": dict(raw_response.headers)}
else: else:
response = await self._async_client.create(**payload) response = await self.async_client.create(**payload)
return await run_in_executor( return await run_in_executor(
None, self._create_chat_result, response, generation_info 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") max_tokens: Optional[int] = Field(default=None, alias="max_completion_tokens")
"""Maximum number of tokens to generate.""" """Maximum number of tokens to generate."""
def __init__(self, *args: Any, **kwargs: Any) -> None:
super().__init__(*args, **kwargs)
@property @property
def lc_secrets(self) -> Dict[str, str]: def lc_secrets(self) -> Dict[str, str]:
return {"openai_api_key": "OPENAI_API_KEY"} return {"openai_api_key": "OPENAI_API_KEY"}

6
libs/partners/openai/tests/integration_tests/chat_models/test_base.py
View File

@ -660,9 +660,6 @@ def test_openai_structured_output(model: str) -> None:
def test_openai_proxy() -> None: def test_openai_proxy() -> None:
"""Test ChatOpenAI with proxy.""" """Test ChatOpenAI with proxy."""
chat_openai = ChatOpenAI(openai_proxy="http://localhost:8080") 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 mounts = chat_openai.client._client._client._mounts
assert len(mounts) == 1 assert len(mounts) == 1
for key, value in mounts.items(): for key, value in mounts.items():
@ -671,9 +668,6 @@ def test_openai_proxy() -> None:
assert proxy.host == b"localhost" assert proxy.host == b"localhost"
assert proxy.port == 8080 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 async_client_mounts = chat_openai.async_client._client._client._mounts
assert len(async_client_mounts) == 1 assert len(async_client_mounts) == 1
for key, value in async_client_mounts.items(): for key, value in async_client_mounts.items():

1
libs/partners/openai/tests/unit_tests/chat_models/test_azure.py
View File

@ -14,6 +14,7 @@ def test_initialize_azure_openai() -> None:
azure_deployment="35-turbo-dev", azure_deployment="35-turbo-dev",
openai_api_version="2023-05-15", openai_api_version="2023-05-15",
azure_endpoint="my-base-url", azure_endpoint="my-base-url",
http_client=None,
) )
assert llm.deployment_name == "35-turbo-dev" assert llm.deployment_name == "35-turbo-dev"
assert llm.openai_api_version == "2023-05-15" assert llm.openai_api_version == "2023-05-15"

20
libs/partners/openai/tests/unit_tests/chat_models/test_base.py
View File

@ -298,7 +298,7 @@ async def test_glm4_astream(mock_glm4_completion: list) -> None:
usage_chunk = mock_glm4_completion[-1] usage_chunk = mock_glm4_completion[-1]
usage_metadata: Optional[UsageMetadata] = None 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"): async for chunk in llm.astream("你的名字叫什么？只回答名字"):
assert isinstance(chunk, AIMessageChunk) assert isinstance(chunk, AIMessageChunk)
if chunk.usage_metadata is not None: 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_chunk = mock_glm4_completion[-1]
usage_metadata: Optional[UsageMetadata] = None 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"): for chunk in llm.stream("你的名字叫什么？只回答名字"):
assert isinstance(chunk, AIMessageChunk) assert isinstance(chunk, AIMessageChunk)
if chunk.usage_metadata is not None: 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 mock_client.create = mock_create
usage_chunk = mock_deepseek_completion[-1] usage_chunk = mock_deepseek_completion[-1]
usage_metadata: Optional[UsageMetadata] = None 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"): async for chunk in llm.astream("你的名字叫什么？只回答名字"):
assert isinstance(chunk, AIMessageChunk) assert isinstance(chunk, AIMessageChunk)
if chunk.usage_metadata is not None: 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 mock_client.create = mock_create
usage_chunk = mock_deepseek_completion[-1] usage_chunk = mock_deepseek_completion[-1]
usage_metadata: Optional[UsageMetadata] = None 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"): for chunk in llm.stream("你的名字叫什么？只回答名字"):
assert isinstance(chunk, AIMessageChunk) assert isinstance(chunk, AIMessageChunk)
if chunk.usage_metadata is not None: 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 mock_client.create = mock_create
usage_chunk = mock_openai_completion[-1] usage_chunk = mock_openai_completion[-1]
usage_metadata: Optional[UsageMetadata] = None 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"): async for chunk in llm.astream("你的名字叫什么？只回答名字"):
assert isinstance(chunk, AIMessageChunk) assert isinstance(chunk, AIMessageChunk)
if chunk.usage_metadata is not None: 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 mock_client.create = mock_create
usage_chunk = mock_openai_completion[-1] usage_chunk = mock_openai_completion[-1]
usage_metadata: Optional[UsageMetadata] = None 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"): for chunk in llm.stream("你的名字叫什么？只回答名字"):
assert isinstance(chunk, AIMessageChunk) assert isinstance(chunk, AIMessageChunk)
if chunk.usage_metadata is not None: 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: def test_openai_invoke(mock_client: MagicMock) -> None:
llm = ChatOpenAI() llm = ChatOpenAI()
with patch.object(llm, "client", mock_client): with patch.object(llm, "_client", mock_client):
res = llm.invoke("bar") res = llm.invoke("bar")
assert res.content == "Bar Baz" 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 "headers" not in res.response_metadata
assert mock_client.create.called 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: async def test_openai_ainvoke(mock_async_client: AsyncMock) -> None:
llm = ChatOpenAI() 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") res = await llm.ainvoke("bar")
assert res.content == "Bar Baz" 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: def test_openai_invoke_name(mock_client: MagicMock) -> None:
llm = ChatOpenAI() llm = ChatOpenAI()
with patch.object(llm, "client", mock_client): with patch.object(llm, "_client", mock_client):
messages = [HumanMessage(content="Foo", name="Katie")] messages = [HumanMessage(content="Foo", name="Katie")]
res = llm.invoke(messages) res = llm.invoke(messages)
call_args, call_kwargs = mock_client.create.call_args call_args, call_kwargs = mock_client.create.call_args