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style: apply black formatting to streaming_iterator.py

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adelnobel 2026-03-30 03:02:27 +00:00
parent c742131e6d
commit 1d52d74b5e
1 changed files with 12 additions and 12 deletions
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24
litellm/llms/anthropic/experimental_pass_through/adapters/streaming_iterator.py
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@ -151,9 +151,9 @@ class AnthropicStreamWrapper(AdapterCompletionStreamWrapper):
# finish-reason chunks, and translate_streaming_openai_response_to_anthropic
# only emits MessageBlockDelta for finish-reason chunks — so
# processed_chunk is always a ContentBlockDelta here.
assert processed_chunk.get("type") == "content_block_delta", (
f"Expected content_block_delta, got {processed_chunk.get('type')}"
)
assert (
processed_chunk.get("type") == "content_block_delta"
), f"Expected content_block_delta, got {processed_chunk.get('type')}"
self.chunk_queue.append(processed_chunk)
return self.chunk_queue.popleft()
@ -292,16 +292,16 @@ class AnthropicStreamWrapper(AdapterCompletionStreamWrapper):
hasattr(chunk.usage, "_cache_creation_input_tokens")
and chunk.usage._cache_creation_input_tokens > 0
):
usage_dict[
"cache_creation_input_tokens"
] = chunk.usage._cache_creation_input_tokens
usage_dict["cache_creation_input_tokens"] = (
chunk.usage._cache_creation_input_tokens
)
if (
hasattr(chunk.usage, "_cache_read_input_tokens")
and chunk.usage._cache_read_input_tokens > 0
):
usage_dict[
"cache_read_input_tokens"
] = chunk.usage._cache_read_input_tokens
usage_dict["cache_read_input_tokens"] = (
chunk.usage._cache_read_input_tokens
)
merged_chunk["usage"] = usage_dict
# Queue the merged chunk and reset
@ -344,9 +344,9 @@ class AnthropicStreamWrapper(AdapterCompletionStreamWrapper):
# finish-reason chunks, and translate_streaming_openai_response_to_anthropic
# only emits MessageBlockDelta for finish-reason chunks — so
# processed_chunk is always a ContentBlockDelta here.
assert processed_chunk.get("type") == "content_block_delta", (
f"Expected content_block_delta, got {processed_chunk.get('type')}"
)
assert (
processed_chunk.get("type") == "content_block_delta"
), f"Expected content_block_delta, got {processed_chunk.get('type')}"
self.chunk_queue.append(processed_chunk)
# Return the first queued item