[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
yogeshmpandey · Jan 9, 2025 · 12b2415 · 12b2415
1 parent 43c9228
commit 12b2415
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Showing 5 changed files with 17 additions and 51 deletions.
diff --git a/comps/integrations/langchain/langchain_opea/chat_models.py b/comps/integrations/langchain/langchain_opea/chat_models.py
@@ -86,9 +86,7 @@ def _llm_type(self) -> str:
         """Return type of chat model."""
         return "opea-chat"
 
-    def _get_ls_params(
-        self, stop: Optional[List[str]] = None, **kwargs: Any
-    ) -> LangSmithParams:
+    def _get_ls_params(self, stop: Optional[List[str]] = None, **kwargs: Any) -> LangSmithParams:
         """Get the parameters used to invoke the model."""
         params = super()._get_ls_params(stop=stop, **kwargs)
         params["ls_provider"] = "opea"
@@ -103,9 +101,7 @@ def validate_environment(self) -> Self:
             raise ValueError("n must be 1 when streaming.")
 
         client_params: dict = {
-            "api_key": (
-                self.opea_api_key.get_secret_value() if self.opea_api_key else None
-            ),
+            "api_key": (self.opea_api_key.get_secret_value() if self.opea_api_key else None),
             "base_url": self.opea_api_base,
         }
 
@@ -117,14 +113,10 @@ def validate_environment(self) -> Self:
 
         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.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
+            self.async_client = openai.AsyncOpenAI(**client_params, **async_specific).chat.completions
         return self
 
     @property

diff --git a/comps/integrations/langchain/langchain_opea/llms.py b/comps/integrations/langchain/langchain_opea/llms.py
@@ -76,9 +76,7 @@ def validate_environment(self) -> Self:
         if self.streaming and self.best_of > 1:
             raise ValueError("Cannot stream results when best_of > 1.")
         client_params: dict = {
-            "api_key": self.opea_api_key.get_secret_value()
-            if self.opea_api_key
-            else None,
+            "api_key": self.opea_api_key.get_secret_value() if self.opea_api_key else None,
             "base_url": self.opea_api_base,
         }
 

diff --git a/comps/integrations/langchain/tests/integration_tests/test_chat_models.py b/comps/integrations/langchain/tests/integration_tests/test_chat_models.py
@@ -50,14 +50,10 @@ def supports_anthropic_inputs(self) -> bool:
 
     supports_anthropic_inputs
 
-    @pytest.mark.xfail(
-        reason=("Fails with 'AssertionError'. OPEA does not support 'tool_choice' yet.")
-    )
+    @pytest.mark.xfail(reason=("Fails with 'AssertionError'. OPEA does not support 'tool_choice' yet."))
     def test_structured_output(self, model: BaseChatModel) -> None:
         super().test_structured_output(model)
 
-    @pytest.mark.xfail(
-        reason=("Fails with 'AssertionError'. OPEA does not support 'tool_choice' yet.")
-    )
+    @pytest.mark.xfail(reason=("Fails with 'AssertionError'. OPEA does not support 'tool_choice' yet."))
     def test_structured_output_pydantic_2_v1(self, model: BaseChatModel) -> None:
         super().test_structured_output_pydantic_2_v1(model)
diff --git a/comps/integrations/langchain/tests/integration_tests/test_llms.py b/comps/integrations/langchain/tests/integration_tests/test_llms.py
@@ -11,29 +11,23 @@
 
 def test_stream() -> None:
     """Test streaming tokens from OpenAI."""
-    llm = OPEALLM(
-        opea_api_base=OPEA_API_BASE, opea_api_key=OPEA_API_KEY, model_name=MODEL_NAME
-    )
+    llm = OPEALLM(opea_api_base=OPEA_API_BASE, opea_api_key=OPEA_API_KEY, model_name=MODEL_NAME)
 
     for token in llm.stream("I'm Pickle Rick"):
         assert isinstance(token, str)
 
 
 async def test_astream() -> None:
     """Test streaming tokens from OpenAI."""
-    llm = OPEALLM(
-        opea_api_base=OPEA_API_BASE, opea_api_key=OPEA_API_KEY, model_name=MODEL_NAME
-    )
+    llm = OPEALLM(opea_api_base=OPEA_API_BASE, opea_api_key=OPEA_API_KEY, model_name=MODEL_NAME)
 
     async for token in llm.astream("I'm Pickle Rick"):
         assert isinstance(token, str)
 
 
 async def test_abatch() -> None:
     """Test streaming tokens from OPEALLM."""
-    llm = OPEALLM(
-        opea_api_base=OPEA_API_BASE, opea_api_key=OPEA_API_KEY, model_name=MODEL_NAME
-    )
+    llm = OPEALLM(opea_api_base=OPEA_API_BASE, opea_api_key=OPEA_API_KEY, model_name=MODEL_NAME)
 
     result = await llm.abatch(["I'm Pickle Rick", "I'm not Pickle Rick"])
     for token in result:
@@ -42,22 +36,16 @@ async def test_abatch() -> None:
 
 async def test_abatch_tags() -> None:
     """Test batch tokens from OPEALLM."""
-    llm = OPEALLM(
-        opea_api_base=OPEA_API_BASE, opea_api_key=OPEA_API_KEY, model_name=MODEL_NAME
-    )
+    llm = OPEALLM(opea_api_base=OPEA_API_BASE, opea_api_key=OPEA_API_KEY, model_name=MODEL_NAME)
 
-    result = await llm.abatch(
-        ["I'm Pickle Rick", "I'm not Pickle Rick"], config={"tags": ["foo"]}
-    )
+    result = await llm.abatch(["I'm Pickle Rick", "I'm not Pickle Rick"], config={"tags": ["foo"]})
     for token in result:
         assert isinstance(token, str)
 
 
 def test_batch() -> None:
     """Test batch tokens from OPEALLM."""
-    llm = OPEALLM(
-        opea_api_base=OPEA_API_BASE, opea_api_key=OPEA_API_KEY, model_name=MODEL_NAME
-    )
+    llm = OPEALLM(opea_api_base=OPEA_API_BASE, opea_api_key=OPEA_API_KEY, model_name=MODEL_NAME)
 
     result = llm.batch(["I'm Pickle Rick", "I'm not Pickle Rick"])
     for token in result:
@@ -66,19 +54,15 @@ def test_batch() -> None:
 
 async def test_ainvoke() -> None:
     """Test invoke tokens from OPEALLM."""
-    llm = OPEALLM(
-        opea_api_base=OPEA_API_BASE, opea_api_key=OPEA_API_KEY, model_name=MODEL_NAME
-    )
+    llm = OPEALLM(opea_api_base=OPEA_API_BASE, opea_api_key=OPEA_API_KEY, model_name=MODEL_NAME)
 
     result = await llm.ainvoke("I'm Pickle Rick", config={"tags": ["foo"]})
     assert isinstance(result, str)
 
 
 def test_invoke() -> None:
     """Test invoke tokens from OPEALLM."""
-    llm = OPEALLM(
-        opea_api_base=OPEA_API_BASE, opea_api_key=OPEA_API_KEY, model_name=MODEL_NAME
-    )
+    llm = OPEALLM(opea_api_base=OPEA_API_BASE, opea_api_key=OPEA_API_KEY, model_name=MODEL_NAME)
 
     result = llm.invoke("I'm Pickle Rick", config=dict(tags=["foo"]))
     assert isinstance(result, str)
diff --git a/comps/integrations/langchain/tests/unit_tests/test_llms.py b/comps/integrations/langchain/tests/unit_tests/test_llms.py
@@ -11,16 +11,12 @@
 
 def test_initialization() -> None:
     """Test integration initialization."""
-    OPEALLM(
-        opea_api_base=OPEA_API_BASE, opea_api_key=OPEA_API_KEY, model_name=MODEL_NAME
-    )
+    OPEALLM(opea_api_base=OPEA_API_BASE, opea_api_key=OPEA_API_KEY, model_name=MODEL_NAME)
 
 
 def test_model_params() -> None:
     # Test standard tracing params
-    llm = OPEALLM(
-        opea_api_base=OPEA_API_BASE, opea_api_key=OPEA_API_KEY, model_name=MODEL_NAME
-    )
+    llm = OPEALLM(opea_api_base=OPEA_API_BASE, opea_api_key=OPEA_API_KEY, model_name=MODEL_NAME)
     ls_params = llm._get_ls_params()
     assert ls_params == {
         "ls_provider": "opea",