fix: formatting in documentation code blocks to pass Black checks

docs/blog/posts/introducing-structured-outputs-with-cerebras-inference.md

@@ -123,9 +123,9 @@ resp = client.chat.completions.create(
 
 for person in resp:
     print(person)
-    # > Person(name='Chris', age=27)
-    # > Person(name='John', age=30)
-    # > Person(name='Jessica', age=26)
+    #> Person(name='Chris', age=27)
+    #> Person(name='John', age=30)
+    #> Person(name='Jessica', age=26)
 ```
 
 And that’s it! We're excited to see what you build with Instructor and Cerebras! If you have any questions about Cerebras or need to get off the API key waitlist, please reach out to [email protected].

docs/blog/posts/pairwise-llm-judge.md

@@ -33,7 +33,6 @@ First, let's set up our environment with the necessary imports:
 ```python
 import instructor
 import openai
-from pydantic import BaseModel, Field
 
 client = instructor.from_openai(openai.OpenAI())
 ```
@@ -88,7 +87,7 @@ def judge_relevance(question: str, text: str) -> Judgment:
                     Before giving your final judgment, provide a justification for your decision. Explain the key factors that led to your conclusion.
 
                     Please ensure your analysis is thorough, impartial, and based on the content provided.
-                """
+                """,
             },
             {
                 "role": "user",
@@ -103,8 +102,8 @@ def judge_relevance(question: str, text: str) -> Judgment:
                     <text>
                     {{text}}
                     </text>
-                """
-            }
+                """,
+            },
         ],
         response_model=Judgment,
         context={"question": question, "text": text},

docs/blog/posts/version-1.md

@@ -50,7 +50,9 @@ IF you know you want to pass in tempurature, seed, or model, you can do so.
 import openai
 import instructor
 
-client = instructor.from_openai(openai.OpenAI(), model="gpt-4-turbo-preview", temperature=0.2)
+client = instructor.from_openai(
+    openai.OpenAI(), model="gpt-4-turbo-preview", temperature=0.2
+)
 ```
 
 Now, whenever you call `client.chat.completions.create` the `model` and `temperature` will be passed to the openai client!