fix exceptions

instructor/exceptions.py

@@ -1,6 +1,8 @@
 class IncompleteOutputException(Exception):
     """Exception raised when the output from LLM is incomplete due to max tokens limit reached."""
 
-    def __init__(self, message="The output is incomplete due to a max_tokens length limit."):
+    def __init__(
+        self, message="The output is incomplete due to a max_tokens length limit."
+    ):
         self.message = message
-        super().__init__(self.message)
+        super().__init__(self.message)

instructor/function_calls.py

@@ -122,9 +122,9 @@ class OpenAISchema(BaseModel):
         Returns:
             cls (OpenAISchema): An instance of the class
         """
-        if completion.choices[0].finish_reason == 'length':
+        if completion.choices[0].finish_reason == "length":
             raise IncompleteOutputException()
-      
+
         if stream_multitask:
             return cls.from_streaming_response(completion, mode)
 
@@ -183,9 +183,9 @@ class OpenAISchema(BaseModel):
         Returns:
             cls (OpenAISchema): An instance of the class
         """
-        if completion.choices[0].finish_reason == 'length':
+        if completion.choices[0].finish_reason == "length":
             raise IncompleteOutputException()
-        
+
         if stream_multitask:
             return await cls.from_streaming_response_async(completion, mode)
 
@@ -232,4 +232,4 @@ def openai_schema(cls) -> OpenAISchema:
             cls.__name__,
             __base__=(cls, OpenAISchema),
         )
-    )  # type: ignore
+    )  # type: ignore

tests/test_function_calls.py

@@ -2,9 +2,10 @@ import pytest
 from pydantic import BaseModel
 from openai.resources.chat.completions import ChatCompletion
 
-from instructor import openai_schema, OpenAISchema, Mode
+from instructor import openai_schema, OpenAISchema
 from instructor.exceptions import IncompleteOutputException
 
+
 @pytest.fixture
 def test_model():
     class TestModel(OpenAISchema):
@@ -12,29 +13,28 @@ def test_model():
         data: str
 
     return TestModel
-  
+
+
 @pytest.fixture
 def mock_completion(request):
-    finish_reason = 'stop'
-    data_content = "{\n\"data\": \"complete data\"\n}"
+    finish_reason = "stop"
+    data_content = '{\n"data": "complete data"\n}'
 
-    if hasattr(request, 'param'):
-        finish_reason = request.param.get('finish_reason', finish_reason)
-        data_content = request.param.get('data_content', data_content)
+    if hasattr(request, "param"):
+        finish_reason = request.param.get("finish_reason", finish_reason)
+        data_content = request.param.get("data_content", data_content)
 
-
-    mock_choices = [{
-        "index": 0,
-        "message": {
-            "role": "assistant",
-            "function_call": {
-                "name": "TestModel",
-                "arguments": data_content
+    mock_choices = [
+        {
+            "index": 0,
+            "message": {
+                "role": "assistant",
+                "function_call": {"name": "TestModel", "arguments": data_content},
+                "content": data_content,
             },
-            "content": data_content,
-        },
-        "finish_reason": finish_reason
-    }]
+            "finish_reason": finish_reason,
+        }
+    ]
 
     completion = ChatCompletion(
         id="test_id",
@@ -43,9 +43,10 @@ def mock_completion(request):
         model="gpt-3.5-turbo",
         object="chat.completion",
     )
-    
+
     return completion
 
+
 def test_openai_schema():
     @openai_schema
     class Dataframe(BaseModel):
@@ -83,22 +84,34 @@ def test_no_docstring():
         == "Correctly extracted `Dummy` with all the required parameters with correct types"
     )
 
-@pytest.mark.parametrize('mock_completion', [{'finish_reason': 'length', 'data_content': '{\n\"data\": \"incomplete dat\"\n}'}], indirect=True)
+
+@pytest.mark.parametrize(
+    "mock_completion",
+    [{"finish_reason": "length", "data_content": '{\n"data": "incomplete dat"\n}'}],
+    indirect=True,
+)
 def test_incomplete_output_exception(test_model, mock_completion):
     with pytest.raises(IncompleteOutputException):
         test_model.from_response(mock_completion)
-        
+
+
 def test_complete_output_no_exception(test_model, mock_completion):
     test_model_instance = test_model.from_response(mock_completion)
     assert test_model_instance.data == "complete data"
 
+
 @pytest.mark.asyncio
-@pytest.mark.parametrize('mock_completion', [{'finish_reason': 'length', 'data_content': '{\n\"data\": \"incomplete dat\"\n}'}], indirect=True)
-async def test_incomplete_output_exception(test_model, mock_completion):
+@pytest.mark.parametrize(
+    "mock_completion",
+    [{"finish_reason": "length", "data_content": '{\n"data": "incomplete dat"\n}'}],
+    indirect=True,
+)
+async def test_incomplete_output_exception_raise(test_model, mock_completion):
     with pytest.raises(IncompleteOutputException):
         await test_model.from_response(mock_completion)
-        
+
+
 @pytest.mark.asyncio
-async def test_complete_output_no_exception(test_model, mock_completion):
+async def test_async_complete_output_no_exception(test_model, mock_completion):
     test_model_instance = await test_model.from_response_async(mock_completion)
-    assert test_model_instance.data == "complete data"
+    assert test_model_instance.data == "complete data"