add test

libs/partners/deepseek/langchain_deepseek/chat_models.py

@@ -178,7 +178,7 @@ class ChatDeepSeek(BaseChatOpenAI):
             self.api_key and self.api_key.get_secret_value()
         ):
             raise ValueError("If using default api base, DEEPSEEK_API_KEY must be set.")
-        client_params: dict = {
+        self._client_params: dict = {
             k: v
             for k, v in {
                 "api_key": self.api_key.get_secret_value() if self.api_key else None,
@@ -191,16 +191,6 @@ class ChatDeepSeek(BaseChatOpenAI):
             if v is not None
         }
 
-        if not (self.client or None):
-            sync_specific: dict = {"http_client": self.http_client}
-            self.client = openai.OpenAI(
-                **client_params, **sync_specific
-            ).chat.completions
-        if not (self.async_client or None):
-            async_specific: dict = {"http_client": self.http_async_client}
-            self.async_client = openai.AsyncOpenAI(
-                **client_params, **async_specific
-            ).chat.completions
         return self
 
     def _create_chat_result(

libs/partners/openai/langchain_openai/chat_models/azure.py

@@ -629,7 +629,7 @@ class AzureChatOpenAI(BaseChatOpenAI):
                     "Or you can equivalently specify:\n\n"
                     'base_url="https://xxx.openai.azure.com/openai/deployments/my-deployment"'
                 )
-        client_params: dict = {
+        self._client_params: dict = {
             "api_version": self.openai_api_version,
             "azure_endpoint": self.azure_endpoint,
             "azure_deployment": self.deployment_name,
@@ -650,27 +650,43 @@ class AzureChatOpenAI(BaseChatOpenAI):
             "default_query": self.default_query,
         }
         if self.max_retries is not None:
-            client_params["max_retries"] = self.max_retries
+            self._client_params["max_retries"] = self.max_retries
 
-        if not self.client:
-            sync_specific = {"http_client": self.http_client}
-            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:
-            async_specific = {"http_client": self.http_async_client}
-
-            if self.azure_ad_async_token_provider:
-                client_params["azure_ad_token_provider"] = (
-                    self.azure_ad_async_token_provider
-                )
-
-            self.root_async_client = openai.AsyncAzureOpenAI(
-                **client_params,
-                **async_specific,  # type: ignore[arg-type]
+        if self.azure_ad_async_token_provider:
+            self._client_params["azure_ad_token_provider"] = (
+                self.azure_ad_async_token_provider
             )
-            self.async_client = self.root_async_client.chat.completions
+
         return self
 
+    @property
+    def root_client(self) -> Any:
+        if self._root_client is None:
+            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
+
+    @root_client.setter
+    def root_client(self, value: openai.AzureOpenAI) -> None:
+        self._root_client = value
+
+    @property
+    def root_async_client(self) -> Any:
+        if self._root_async_client is None:
+            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
+
+    @root_async_client.setter
+    def root_async_client(self, value: openai.AsyncAzureOpenAI) -> None:
+        self._root_async_client = value
+
     @property
     def _identifying_params(self) -> Dict[str, Any]:
         """Get the identifying parameters."""

libs/partners/openai/langchain_openai/chat_models/base.py

@@ -6,12 +6,14 @@ import base64
 import json
 import logging
 import os
+import ssl
 import sys
 import warnings
 from io import BytesIO
 from math import ceil
 from operator import itemgetter
 from typing import (
+    TYPE_CHECKING,
     Any,
     AsyncIterator,
     Callable,
@@ -31,6 +33,7 @@ from typing import (
 )
 from urllib.parse import urlparse
 
+import certifi
 import openai
 import tiktoken
 from langchain_core._api.deprecation import deprecated
@@ -91,12 +94,25 @@ from langchain_core.utils.pydantic import (
     is_basemodel_subclass,
 )
 from langchain_core.utils.utils import _build_model_kwargs, from_env, secret_from_env
-from pydantic import BaseModel, ConfigDict, Field, SecretStr, model_validator
+from pydantic import (
+    BaseModel,
+    ConfigDict,
+    Field,
+    PrivateAttr,
+    SecretStr,
+    model_validator,
+)
 from pydantic.v1 import BaseModel as BaseModelV1
 from typing_extensions import Self
 
+if TYPE_CHECKING:
+    import httpx
+
 logger = logging.getLogger(__name__)
 
+# This SSL context is equivelent to the default `verify=True`.
+global_ssl_context = ssl.create_default_context(cafile=certifi.where())
+
 
 def _convert_dict_to_message(_dict: Mapping[str, Any]) -> BaseMessage:
     """Convert a dictionary to a LangChain message.
@@ -385,10 +401,10 @@ 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
@@ -460,11 +476,11 @@ 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")
@@ -491,6 +507,7 @@ class BaseChatOpenAI(BaseChatModel):
     However this does not prevent a user from directly passed in the parameter during
     invocation. 
     """
+    _client_params: Dict[str, Any] = PrivateAttr(default_factory=dict)
 
     model_config = ConfigDict(populate_by_name=True)
 
@@ -511,6 +528,24 @@ 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."""
@@ -526,7 +561,7 @@ class BaseChatOpenAI(BaseChatModel):
             or os.getenv("OPENAI_ORGANIZATION")
         )
         self.openai_api_base = self.openai_api_base or os.getenv("OPENAI_API_BASE")
-        client_params: dict = {
+        self._client_params: dict = {
             "api_key": (
                 self.openai_api_key.get_secret_value() if self.openai_api_key else None
             ),
@@ -537,47 +572,122 @@ class BaseChatOpenAI(BaseChatModel):
             "default_query": self.default_query,
         }
         if self.max_retries is not None:
-            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
-            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"
                 f"{openai_proxy=}\n{http_client=}\n{http_async_client=}"
             )
-        if not self.client:
-            if self.openai_proxy and not self.http_client:
-                try:
-                    import httpx
-                except ImportError as e:
-                    raise ImportError(
-                        "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
+
+    @property
+    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
+        async invocations.
+        """
+        # Configure a custom httpx client. See the
+        # [httpx documentation](https://www.python-httpx.org/api/#client) for more
+        # details.
+        if self._http_client is None:
+            if not self.openai_proxy:
+                return None
+            try:
+                import httpx
+            except ImportError as e:
+                raise ImportError(
+                    "Could not import httpx python package. "
+                    "Please install it with `pip install httpx`."
+                ) from e
+            self._http_client = httpx.Client(
+                proxy=self.openai_proxy, verify=global_ssl_context
+            )
+        return self._http_client
+
+    @http_client.setter
+    def http_client(self, value: Optional[httpx.Client]) -> None:
+        self._http_client = value
+
+    @property
+    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 None:
+            if not self.openai_proxy:
+                return None
+            try:
+                import httpx
+            except ImportError as e:
+                raise ImportError(
+                    "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, verify=global_ssl_context
+            )
+        return self._http_async_client
+
+    @http_async_client.setter
+    def http_async_client(self, value: Optional[httpx.AsyncClient]) -> None:
+        self._http_async_client = value
+
+    @property
+    def root_client(self) -> Any:
+        if self._root_client is None:
             sync_specific = {"http_client": self.http_client}
-            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:
-            if self.openai_proxy and not self.http_async_client:
-                try:
-                    import httpx
-                except ImportError as e:
-                    raise ImportError(
-                        "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._root_client = openai.OpenAI(
+                **self._client_params,
+                **sync_specific,  # type: ignore[arg-type]
+            )
+        return self._root_client
+
+    @root_client.setter
+    def root_client(self, value: openai.OpenAI) -> None:
+        self._root_client = value
+
+    @property
+    def root_async_client(self) -> Any:
+        if self._root_async_client is None:
             async_specific = {"http_client": self.http_async_client}
-            self.root_async_client = openai.AsyncOpenAI(
-                **client_params,
+            self._root_async_client = openai.AsyncOpenAI(
+                **self._client_params,
                 **async_specific,  # type: ignore[arg-type]
             )
-            self.async_client = self.root_async_client.chat.completions
-        return self
+        return self._root_async_client
+
+    @root_async_client.setter
+    def root_async_client(self, value: openai.AsyncOpenAI) -> None:
+        self._root_async_client = value
+
+    @property
+    def client(self) -> Any:
+        if self._client is None:
+            self._client = self.root_client.chat.completions
+        return self._client
+
+    @client.setter
+    def client(self, value: Any) -> None:
+        self._client = value
+
+    @property
+    def async_client(self) -> Any:
+        if self._async_client is None:
+            self._async_client = self.root_async_client.chat.completions
+        return self._async_client
+
+    @async_client.setter
+    def async_client(self, value: Any) -> None:
+        self._async_client = value
 
     @property
     def _default_params(self) -> Dict[str, Any]:
@@ -1961,6 +2071,9 @@ 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"}

libs/partners/openai/tests/integration_tests/chat_models/test_base.py

@@ -676,6 +676,16 @@ def test_openai_proxy() -> None:
         assert proxy.host == b"localhost"
         assert proxy.port == 8080
 
+    http_async_client = httpx.AsyncClient(proxy="http://localhost:8081")
+    chat_openai = ChatOpenAI(http_async_client=http_async_client)
+    mounts = chat_openai.async_client._client._client._mounts
+    assert len(mounts) == 1
+    for key, value in mounts.items():
+        proxy = value._pool._proxy_url.origin
+        assert proxy.scheme == b"http"
+        assert proxy.host == b"localhost"
+        assert proxy.port == 8081
+
 
 def test_openai_response_headers() -> None:
     """Test ChatOpenAI response headers."""

libs/partners/openai/tests/unit_tests/chat_models/test_azure.py

@@ -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"

libs/partners/openai/tests/unit_tests/chat_models/test_base.py

@@ -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"
 
@@ -541,11 +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
+
 
 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"
 
@@ -573,7 +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

libs/partners/xai/langchain_xai/chat_models.py

@@ -7,7 +7,6 @@ from typing import (
     Optional,
 )
 
-import openai
 from langchain_core.language_models.chat_models import LangSmithParams
 from langchain_core.utils import secret_from_env
 from langchain_openai.chat_models.base import BaseChatOpenAI
@@ -325,7 +324,7 @@ class ChatXAI(BaseChatOpenAI):  # type: ignore[override]
         if self.n is not None and self.n > 1 and self.streaming:
             raise ValueError("n must be 1 when streaming.")
 
-        client_params: dict = {
+        self._client_params: dict = {
             "api_key": (
                 self.xai_api_key.get_secret_value() if self.xai_api_key else None
             ),
@@ -335,27 +334,12 @@ class ChatXAI(BaseChatOpenAI):  # type: ignore[override]
             "default_query": self.default_query,
         }
         if self.max_retries is not None:
-            client_params["max_retries"] = self.max_retries
+            self._client_params["max_retries"] = self.max_retries
 
-        if client_params["api_key"] is None:
+        if self._client_params["api_key"] is None:
             raise ValueError(
                 "xAI API key is not set. Please set it in the `xai_api_key` field or "
                 "in the `XAI_API_KEY` environment variable."
             )
 
-        if not (self.client or None):
-            sync_specific: dict = {"http_client": self.http_client}
-            self.client = openai.OpenAI(
-                **client_params, **sync_specific
-            ).chat.completions
-            self.root_client = openai.OpenAI(**client_params, **sync_specific)
-        if not (self.async_client or None):
-            async_specific: dict = {"http_client": self.http_async_client}
-            self.async_client = openai.AsyncOpenAI(
-                **client_params, **async_specific
-            ).chat.completions
-            self.root_async_client = openai.AsyncOpenAI(
-                **client_params,
-                **async_specific,
-            )
         return self