diff --git a/semantic_router/llms/openai.py b/semantic_router/llms/openai.py
index 3465eec9a32765d1c68ad0f53ccdbb59cef2235b..7dc565e8877a46d74e5fd86d4e3d05e04c52175c 100644
--- a/semantic_router/llms/openai.py
+++ b/semantic_router/llms/openai.py
@@ -1,5 +1,6 @@
import os
from typing import List, Optional, Any, Callable, Dict, Union
+from pydantic import PrivateAttr
import openai
from openai._types import NotGiven, NOT_GIVEN
@@ -21,8 +22,8 @@ from openai.types.chat.chat_completion_message_tool_call import (
class OpenAILLM(BaseLLM):
- client: Optional[openai.OpenAI]
- async_client: Optional[openai.AsyncOpenAI]
+ _client: Optional[openai.OpenAI] = PrivateAttr(default=None)
+ _async_client: Optional[openai.AsyncOpenAI] = PrivateAttr(default=None)
def __init__(
self,
@@ -38,8 +39,8 @@ class OpenAILLM(BaseLLM):
if api_key is None:
raise ValueError("OpenAI API key cannot be 'None'.")
try:
- self.async_client = openai.AsyncOpenAI(api_key=api_key)
- self.client = openai.OpenAI(api_key=api_key)
+ self._async_client = openai.AsyncOpenAI(api_key=api_key)
+ self._client = openai.OpenAI(api_key=api_key)
except Exception as e:
raise ValueError(
f"OpenAI API client failed to initialize. Error: {e}"
@@ -86,14 +87,14 @@ class OpenAILLM(BaseLLM):
messages: List[Message],
function_schemas: Optional[List[Dict[str, Any]]] = None,
) -> str:
- if self.client is None:
+ if self._client is None:
raise ValueError("OpenAI client is not initialized.")
try:
tools: Union[List[Dict[str, Any]], NotGiven] = (
function_schemas if function_schemas else NOT_GIVEN
)
- completion = self.client.chat.completions.create(
+ completion = self._client.chat.completions.create(
model=self.name,
messages=[m.to_openai() for m in messages],
temperature=self.temperature,
@@ -130,14 +131,14 @@ class OpenAILLM(BaseLLM):
messages: List[Message],
function_schemas: Optional[List[Dict[str, Any]]] = None,
) -> str:
- if self.async_client is None:
+ if self._async_client is None:
raise ValueError("OpenAI async_client is not initialized.")
try:
tools: Union[List[Dict[str, Any]], NotGiven] = (
function_schemas if function_schemas is not None else NOT_GIVEN
)
- completion = await self.async_client.chat.completions.create(
+ completion = await self._async_client.chat.completions.create(
model=self.name,
messages=[m.to_openai() for m in messages],
temperature=self.temperature,
diff --git a/tests/unit/encoders/test_openai.py b/tests/unit/encoders/test_openai.py
index 538e969250051c3da305702a42944903d1cb71cf..96171cce5b462f76dfbd88d7795bfc684ca100c8 100644
--- a/tests/unit/encoders/test_openai.py
+++ b/tests/unit/encoders/test_openai.py
@@ -30,7 +30,7 @@ class TestOpenAIEncoder:
side_effect = ["fake-model-name", "fake-api-key", "fake-org-id"]
mocker.patch("os.getenv", side_effect=side_effect)
encoder = OpenAIEncoder()
- assert encoder.client is not None
+ assert encoder._client is not None
def test_openai_encoder_init_no_api_key(self, mocker):
mocker.patch("os.getenv", return_value=None)
@@ -39,7 +39,7 @@ class TestOpenAIEncoder:
def test_openai_encoder_call_uninitialized_client(self, openai_encoder):
# Set the client to None to simulate an uninitialized client
- openai_encoder.client = None
+ openai_encoder._client = None
with pytest.raises(ValueError) as e:
openai_encoder(["test document"])
assert "OpenAI client is not initialized." in str(e.value)
@@ -74,7 +74,7 @@ class TestOpenAIEncoder:
responses = [OpenAIError("OpenAI error"), mock_response]
mocker.patch.object(
- openai_encoder.client.embeddings, "create", side_effect=responses
+ openai_encoder._client.embeddings, "create", side_effect=responses
)
with patch("semantic_router.encoders.openai.sleep", return_value=None):
embeddings = openai_encoder(["test document"])
@@ -84,7 +84,7 @@ class TestOpenAIEncoder:
mocker.patch("os.getenv", return_value="fake-api-key")
mocker.patch("time.sleep", return_value=None) # To speed up the test
mocker.patch.object(
- openai_encoder.client.embeddings,
+ openai_encoder._client.embeddings,
"create",
side_effect=Exception("Non-OpenAIError"),
)
@@ -114,7 +114,7 @@ class TestOpenAIEncoder:
responses = [OpenAIError("OpenAI error"), mock_response]
mocker.patch.object(
- openai_encoder.client.embeddings, "create", side_effect=responses
+ openai_encoder._client.embeddings, "create", side_effect=responses
)
with patch("semantic_router.encoders.openai.sleep", return_value=None):
embeddings = openai_encoder(["test document"])
diff --git a/tests/unit/llms/test_llm_azure_openai.py b/tests/unit/llms/test_llm_azure_openai.py
index 793091957df7fdd89792aebec43a6fe87763e02b..def792b372790a912b68956bd83e5aa5023a5b7e 100644
--- a/tests/unit/llms/test_llm_azure_openai.py
+++ b/tests/unit/llms/test_llm_azure_openai.py
@@ -12,13 +12,13 @@ def azure_openai_llm(mocker):
class TestOpenAILLM:
def test_azure_openai_llm_init_with_api_key(self, azure_openai_llm):
- assert azure_openai_llm.client is not None, "Client should be initialized"
+ assert azure_openai_llm._client is not None, "Client should be initialized"
assert azure_openai_llm.name == "gpt-4o", "Default name not set correctly"
def test_azure_openai_llm_init_success(self, mocker):
mocker.patch("os.getenv", return_value="fake-api-key")
llm = AzureOpenAILLM()
- assert llm.client is not None
+ assert llm._client is not None
def test_azure_openai_llm_init_without_api_key(self, mocker):
mocker.patch("os.getenv", return_value=None)
@@ -44,7 +44,7 @@ class TestOpenAILLM:
def test_azure_openai_llm_call_uninitialized_client(self, azure_openai_llm):
# Set the client to None to simulate an uninitialized client
- azure_openai_llm.client = None
+ azure_openai_llm._client = None
with pytest.raises(ValueError) as e:
llm_input = [Message(role="user", content="test")]
azure_openai_llm(llm_input)
@@ -83,7 +83,7 @@ class TestOpenAILLM:
mocker.patch("os.getenv", return_value="fake-api-key")
mocker.patch.object(
- azure_openai_llm.client.chat.completions,
+ azure_openai_llm._client.chat.completions,
"create",
return_value=mock_completion,
)
diff --git a/tests/unit/llms/test_llm_openai.py b/tests/unit/llms/test_llm_openai.py
index 4287fc882214c8524c5ce611c11af136eea935c5..ee7e82a9d741d31cc7303756a87e5dd007d32f72 100644
--- a/tests/unit/llms/test_llm_openai.py
+++ b/tests/unit/llms/test_llm_openai.py
@@ -42,13 +42,13 @@ example_function_schema = {
class TestOpenAILLM:
def test_openai_llm_init_with_api_key(self, openai_llm):
- assert openai_llm.client is not None, "Client should be initialized"
+ assert openai_llm._client is not None, "Client should be initialized"
assert openai_llm.name == "gpt-4o", "Default name not set correctly"
def test_openai_llm_init_success(self, mocker):
mocker.patch("os.getenv", return_value="fake-api-key")
llm = OpenAILLM()
- assert llm.client is not None
+ assert llm._client is not None
def test_openai_llm_init_without_api_key(self, mocker):
mocker.patch("os.getenv", return_value=None)
@@ -57,7 +57,7 @@ class TestOpenAILLM:
def test_openai_llm_call_uninitialized_client(self, openai_llm):
# Set the client to None to simulate an uninitialized client
- openai_llm.client = None
+ openai_llm._client = None
with pytest.raises(ValueError) as e:
llm_input = [Message(role="user", content="test")]
openai_llm(llm_input)
@@ -79,7 +79,7 @@ class TestOpenAILLM:
mocker.patch("os.getenv", return_value="fake-api-key")
mocker.patch.object(
- openai_llm.client.chat.completions, "create", return_value=mock_completion
+ openai_llm._client.chat.completions, "create", return_value=mock_completion
)
llm_input = [Message(role="user", content="test")]
output = openai_llm(llm_input)
@@ -127,7 +127,7 @@ class TestOpenAILLM:
# mocker.MagicMock(function=mocker.MagicMock(arguments="result"))
# ]
# mocker.patch.object(
- # openai_llm.client.chat.completions, "create", return_value=mock_completion
+ # openai_llm._client.chat.completions, "create", return_value=mock_completion
# )
# llm_input = [Message(role="user", content="test")]
# function_schemas = [{"type": "function", "name": "sample_function"}]
@@ -145,7 +145,7 @@ class TestOpenAILLM:
mock_completion.choices[0].message.tool_calls = [mock_tool_call]
mocker.patch.object(
- openai_llm.client.chat.completions, "create", return_value=mock_completion
+ openai_llm._client.chat.completions, "create", return_value=mock_completion
)
llm_input = [Message(role="user", content="test")]
@@ -160,7 +160,7 @@ class TestOpenAILLM:
mock_completion = mocker.MagicMock()
mock_completion.choices[0].message.tool_calls = None
mocker.patch.object(
- openai_llm.client.chat.completions, "create", return_value=mock_completion
+ openai_llm._client.chat.completions, "create", return_value=mock_completion
)
llm_input = [Message(role="user", content="test")]
function_schemas = [{"type": "function", "name": "sample_function"}]
@@ -180,7 +180,7 @@ class TestOpenAILLM:
mocker.MagicMock(function=mocker.MagicMock(arguments=None))
]
mocker.patch.object(
- openai_llm.client.chat.completions, "create", return_value=mock_completion
+ openai_llm._client.chat.completions, "create", return_value=mock_completion
)
llm_input = [Message(role="user", content="test")]
function_schemas = [{"type": "function", "name": "sample_function"}]
@@ -230,7 +230,7 @@ class TestOpenAILLM:
# Patching the completions.create method to return the mocked completion
mocker.patch.object(
- openai_llm.client.chat.completions, "create", return_value=mock_completion
+ openai_llm._client.chat.completions, "create", return_value=mock_completion
)
# Input message list