style: apply black formatting

litellm/litellm_core_utils/prompt_templates/factory.py

@@ -5044,9 +5044,7 @@ def _bedrock_converse_messages_pt(  # noqa: PLR0915
         assistant_content = _deduplicate_bedrock_content_blocks(
             assistant_content, "toolUse"
         )
-        assistant_content = _sort_bedrock_assistant_content_blocks(
-            assistant_content
-        )
+        assistant_content = _sort_bedrock_assistant_content_blocks(assistant_content)
 
         if assistant_content:
             contents.append(

litellm/litellm_core_utils/streaming_chunk_builder_utils.py

@@ -119,9 +119,7 @@ class ChunkProcessor:
         model = ChunkProcessor._get_model_from_chunks(chunks, first_chunk_model)
         system_fingerprint = chunk.get("system_fingerprint", None)
 
-        first_chunk_with_choices = next(
-            (c for c in chunks if c.get("choices")), chunk
-        )
+        first_chunk_with_choices = next((c for c in chunks if c.get("choices")), chunk)
         role = first_chunk_with_choices["choices"][0]["delta"]["role"]
         finish_reason = "stop"
         for chunk in chunks:

litellm/litellm_core_utils/streaming_handler.py

@@ -1872,7 +1872,9 @@ class CustomStreamWrapper:
                     if response.choices:
                         choice = response.choices[0]
                         if isinstance(choice, StreamingChoices):
-                            self.response_uptil_now += choice.delta.get("content", "") or ""
+                            self.response_uptil_now += (
+                                choice.delta.get("content", "") or ""
+                            )
                         else:
                             self.response_uptil_now += ""
                     self.rules.post_call_rules(
@@ -2053,7 +2055,9 @@ class CustomStreamWrapper:
                     if processed_chunk.choices:
                         choice = processed_chunk.choices[0]
                         if isinstance(choice, StreamingChoices):
-                            self.response_uptil_now += choice.delta.get("content", "") or ""
+                            self.response_uptil_now += (
+                                choice.delta.get("content", "") or ""
+                            )
                         else:
                             self.response_uptil_now += ""
                     self.rules.post_call_rules(

litellm/llms/openai/responses/transformation.py

@@ -95,7 +95,9 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
             temperature = params.get("temperature")
             if temperature is not None and temperature != 1:
                 reasoning = params.get("reasoning") or {}
-                effort = reasoning.get("effort") if isinstance(reasoning, dict) else None
+                effort = (
+                    reasoning.get("effort") if isinstance(reasoning, dict) else None
+                )
                 supports_none = self._supports_reasoning_effort_none(model=model)
                 if supports_none and (effort == "none" or effort is None):
                     pass  # flexible temperature allowed

litellm/main.py

@@ -7389,9 +7389,7 @@ def stream_chunk_builder(  # noqa: PLR0915
         if len(chunks) == 0:
             return None
         ## Route to the text completion logic
-        first_chunk_with_choices = next(
-            (c for c in chunks if c["choices"]), None
-        )
+        first_chunk_with_choices = next((c for c in chunks if c["choices"]), None)
         if first_chunk_with_choices is not None and isinstance(
             first_chunk_with_choices["choices"][0], litellm.utils.TextChoices
         ):  # route to the text completion logic