🦉 Updates from OwlBot post-processor

See https://github.com/googleapis/repo-automation-bots/blob/main/packages/owl-bot/README.md

generative_ai/code_chat.py

@@ -16,23 +16,23 @@
 from vertexai.preview.language_models import CodeChatModel
 
 
-def write_a_function(
-        temperature: float = 0.5
-) -> object:
+def write_a_function(temperature: float = 0.5) -> object:
     """Example of using Code Chat Model to write a function."""
 
     # TODO developer - override these parameters as needed:
     parameters = {
         "temperature": temperature,  # Temperature controls the degree of randomness in token selection.
-        "max_output_tokens": 1024,    # Token limit determines the maximum amount of text output.
+        "max_output_tokens": 1024,  # Token limit determines the maximum amount of text output.
     }
 
     code_chat_model = CodeChatModel.from_pretrained("codechat-bison@001")
     chat = code_chat_model.start_chat()
 
-    response = chat.send_message("Please help write a function to calculate the min of two numbers", **parameters)
+    response = chat.send_message(
+        "Please help write a function to calculate the min of two numbers", **parameters
+    )
     print(f"Response from Model: {response.text}")
-# [END aiplatform_sdk_code_chat]
+    # [END aiplatform_sdk_code_chat]
 
     return response
 

generative_ai/code_chat_test.py

@@ -21,4 +21,4 @@
 @backoff.on_exception(backoff.expo, ResourceExhausted, max_time=10)
 def test_code_chat() -> None:
     content = code_chat.write_a_function(temperature=0).text
-    assert 'def min(a, b):' in content
+    assert "def min(a, b):" in content

generative_ai/code_completion_function.py

@@ -16,22 +16,22 @@
 from vertexai.preview.language_models import CodeGenerationModel
 
 
-def complete_code_function(
-        temperature: float = 0.2
-) -> object:
+def complete_code_function(temperature: float = 0.2) -> object:
     """Example of using Code Completion to complete a function."""
 
     # TODO developer - override these parameters as needed:
     parameters = {
         "temperature": temperature,  # Temperature controls the degree of randomness in token selection.
-        "max_output_tokens": 64,    # Token limit determines the maximum amount of text output.
+        "max_output_tokens": 64,  # Token limit determines the maximum amount of text output.
     }
 
     code_completion_model = CodeGenerationModel.from_pretrained("code-gecko@001")
-    response = code_completion_model.predict(prefix="def reverse_string(s):", **parameters)
+    response = code_completion_model.predict(
+        prefix="def reverse_string(s):", **parameters
+    )
 
     print(f"Response from Model: {response.text}")
-# [END aiplatform_sdk_code_completion_comment]
+    # [END aiplatform_sdk_code_completion_comment]
 
     return response
 

generative_ai/code_completion_function_test.py

@@ -21,4 +21,4 @@
 @backoff.on_exception(backoff.expo, ResourceExhausted, max_time=10)
 def test_code_completion_comment() -> None:
     content = code_completion_function.complete_code_function(temperature=0).text
-    assert 'def' in content
+    assert "def" in content

generative_ai/code_completion_test_function.py

@@ -16,26 +16,26 @@
 from vertexai.preview.language_models import CodeGenerationModel
 
 
-def complete_test_function(
-        temperature: float = 0.2
-) -> object:
+def complete_test_function(temperature: float = 0.2) -> object:
     """Example of using Code Completion to complete a test function."""
 
     # TODO developer - override these parameters as needed:
     parameters = {
         "temperature": temperature,  # Temperature controls the degree of randomness in token selection.
-        "max_output_tokens": 64,    # Token limit determines the maximum amount of text output.
+        "max_output_tokens": 64,  # Token limit determines the maximum amount of text output.
     }
 
     code_completion_model = CodeGenerationModel.from_pretrained("code-gecko@001")
     response = code_completion_model.predict(
         prefix="""def reverse_string(s):
             return s[::-1]
-        def test_empty_input_string()""", **parameters)
+        def test_empty_input_string()""",
+        **parameters,
+    )
 
     print(f"Response from Model: {response.text}")
 
-# [END aiplatform_sdk_code_completion_test_function]
+    # [END aiplatform_sdk_code_completion_test_function]
 
     return response
 

generative_ai/code_completion_test_function_test.py

@@ -21,4 +21,4 @@
 @backoff.on_exception(backoff.expo, ResourceExhausted, max_time=10)
 def test_code_completion_test_function() -> None:
     content = code_completion_test_function.complete_test_function(temperature=0).text
-    assert '-> None:' in content
+    assert "-> None:" in content

generative_ai/code_generation_function.py

@@ -16,22 +16,22 @@
 from vertexai.preview.language_models import CodeGenerationModel
 
 
-def generate_a_function(
-        temperature: float = 0.5
-) -> object:
+def generate_a_function(temperature: float = 0.5) -> object:
     """Example of using Code Generation to write a function."""
 
     # TODO developer - override these parameters as needed:
     parameters = {
         "temperature": temperature,  # Temperature controls the degree of randomness in token selection.
-        "max_output_tokens": 256,    # Token limit determines the maximum amount of text output.
+        "max_output_tokens": 256,  # Token limit determines the maximum amount of text output.
     }
 
     code_generation_model = CodeGenerationModel.from_pretrained("code-bison@001")
-    response = code_generation_model.predict(prefix="Write a function that checks if a year is a leap year.", **parameters)
+    response = code_generation_model.predict(
+        prefix="Write a function that checks if a year is a leap year.", **parameters
+    )
 
     print(f"Response from Model: {response.text}")
-# [END aiplatform_sdk_code_generation_function]
+    # [END aiplatform_sdk_code_generation_function]
 
     return response
 

generative_ai/code_generation_function_test.py

@@ -21,4 +21,4 @@
 @backoff.on_exception(backoff.expo, ResourceExhausted, max_time=10)
 def test_code_generation_function() -> None:
     content = code_generation_function.generate_a_function(temperature=0).text
-    assert 'Divide the year by 4.' in content
+    assert "Divide the year by 4." in content

generative_ai/code_generation_unittest.py

@@ -18,19 +18,19 @@
 from vertexai.preview.language_models import CodeGenerationModel
 
 
-def generate_unittest(
-        temperature: float = 0.5
-) -> object:
+def generate_unittest(temperature: float = 0.5) -> object:
     """Example of using Code Generation to write a unit test."""
 
     # TODO developer - override these parameters as needed:
     parameters = {
         "temperature": temperature,  # Temperature controls the degree of randomness in token selection.
-        "max_output_tokens": 256,    # Token limit determines the maximum amount of text output.
+        "max_output_tokens": 256,  # Token limit determines the maximum amount of text output.
     }
 
     code_generation_model = CodeGenerationModel.from_pretrained("code-bison@001")
-    response = code_generation_model.predict(prefix=textwrap.dedent("""\
+    response = code_generation_model.predict(
+        prefix=textwrap.dedent(
+            """\
     Write a unit test for this function:
     def is_leap_year(year):
         if year % 4 == 0:
@@ -43,10 +43,13 @@ def is_leap_year(year):
                 return True
         else:
             return False
-    """), **parameters)
+    """
+        ),
+        **parameters,
+    )
 
     print(f"Response from Model: {response.text}")
-# [END aiplatform_sdk_code_generation_unittest]
+    # [END aiplatform_sdk_code_generation_unittest]
 
     return response
 

generative_ai/code_generation_unittest_test.py

@@ -21,4 +21,4 @@
 @backoff.on_exception(backoff.expo, ResourceExhausted, max_time=10)
 def test_code_generation_unittest() -> None:
     content = code_generation_unittest.generate_unittest(temperature=0).text
-    assert 'def test_is_leap_year():' in content
+    assert "def test_is_leap_year():" in content