formatting

examples/learn-async/run.py

@@ -8,6 +8,7 @@
 
 client = instructor.apatch(AsyncOpenAI())
 
+
 class Timer:
     def __init__(self, name):
         self.name = name
@@ -112,7 +113,6 @@ async def rate_limited_extract_person(text: str) -> Person:
         print("asyncio.as_completed (rate limited):", all_persons)
 
 
-
 if __name__ == "__main__":
     asyncio.run(main())
     """
@@ -123,4 +123,4 @@ async def rate_limited_extract_person(text: str) -> Person:
 
     asyncio.gather (rate limited) took 3.04 seconds
     asyncio.as_completed (rate limited) took 3.26 seconds
-    """
+    """

examples/validators/llm_validator.py

@@ -43,15 +43,16 @@ class QuestionAnswer(BaseModel):
 """
 
 
-
-
 class QuestionAnswerNoEvil(BaseModel):
     question: str
     answer: Annotated[
         str,
-        BeforeValidator(llm_validator("don't say objectionable things", openai_client=client))
+        BeforeValidator(
+            llm_validator("don't say objectionable things", openai_client=client)
+        ),
     ]
 
+
 try:
     qa = QuestionAnswerNoEvil(
         question="What is the meaning of life?",

tests/openai/test_multitask.py

@@ -9,10 +9,12 @@
 
 client = instructor.patch(OpenAI())
 
+
 class User(BaseModel):
     name: str
     age: int
 
+
 def test_multi_user():
     def stream_extract(input: str, cls) -> Iterable[User]:
         MultiUser = instructor.MultiTask(cls)

tests/openai/test_patch.py

@@ -20,9 +20,9 @@ def validate_name(cls, v):
         if v.upper() != v:
             raise ValueError("Name should be uppercase")
         return v
-
-def test_runmodel_validator():
 
+
+def test_runmodel_validator():
     model = client.chat.completions.create(
         model="gpt-3.5-turbo",
         response_model=UserExtract,
@@ -69,40 +69,44 @@ async def test_async_runmodel():
             {"role": "user", "content": "Extract jason is 25 years old"},
         ],
     )
-    assert isinstance(model, UserExtractSimple), "Should be instance of UserExtractSimple"
+    assert isinstance(
+        model, UserExtractSimple
+    ), "Should be instance of UserExtractSimple"
     assert model.name.lower() == "jason"
     assert hasattr(
         model, "_raw_response"
     ), "The raw response should be available from OpenAI"
 
 
 def test_runmodel():
-
     model = client.chat.completions.create(
         model="gpt-3.5-turbo",
         response_model=UserExtractSimple,
         messages=[
             {"role": "user", "content": "Extract jason is 25 years old"},
         ],
     )
-    assert isinstance(model, UserExtractSimple), "Should be instance of UserExtractSimple"
+    assert isinstance(
+        model, UserExtractSimple
+    ), "Should be instance of UserExtractSimple"
     assert model.name.lower() == "jason"
     assert hasattr(
         model, "_raw_response"
     ), "The raw response should be available from OpenAI"
 
 
 def test_runmodel_validator_error():
-
     class QuestionAnswerNoEvil(BaseModel):
         question: str
         answer: Annotated[
             str,
-            BeforeValidator(llm_validator("don't say objectionable things", openai_client=client))
+            BeforeValidator(
+                llm_validator("don't say objectionable things", openai_client=client)
+            ),
         ]
 
     with pytest.raises(ValidationError):
         QuestionAnswerNoEvil(
             question="What is the meaning of life?",
             answer="The meaning of life is to be evil and steal",
-        )
+        )

tests/test_patch.py

@@ -64,5 +64,8 @@ def wrapped_function():
 
     assert is_async(wrapped_function) is True
 
+
 def test_override_docs():
-    assert "response_model" in OVERRIDE_DOCS, "response_model should be in OVERRIDE_DOCS"
+    assert (
+        "response_model" in OVERRIDE_DOCS
+    ), "response_model should be in OVERRIDE_DOCS"