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chore(responses): drop narrative comments from the MCP streaming iterator

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mateo-berri 2026-09-21 13:48:11 -07:00
parent 146e5c492b
commit 5f84e83316
1 changed files with 0 additions and 15 deletions
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litellm/responses/mcp/mcp_streaming_iterator.py
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@ -341,11 +341,6 @@ class MCPEnhancedStreamingIterator(BaseResponsesAPIStreamingIterator):
self._error_event_emitted = False
self._last_sequence_number = 0
# Every auto-execute round is a distinct upstream response, but the
# client is reading one stream. Fold the rounds into one public
# lifecycle: one response.created, one response.completed whose
# output holds every round's items, and output indexes that are
# never reused for a different item.
self._round_index = 0
self._output_index_offset = 0
self._round_max_output_index = -1
@ -438,8 +433,6 @@ class MCPEnhancedStreamingIterator(BaseResponsesAPIStreamingIterator):
chunk: Final = await self._anext_impl()
sequence_number: Final = getattr(chunk, "sequence_number", None)
if isinstance(sequence_number, int):
# Follow-up rounds and gateway events restart their numbering.
# Keep the public stream strictly increasing.
if sequence_number <= self._last_sequence_number and self._last_sequence_number > 0:
self._last_sequence_number += 1
_set_event_field(chunk, "sequence_number", self._last_sequence_number)
@ -560,8 +553,6 @@ class MCPEnhancedStreamingIterator(BaseResponsesAPIStreamingIterator):
self.phase = "mcp_discovery"
return await self._compose_round_chunk(chunk)
# None means the chunk was folded into the single public
# lifecycle; fall through so phase 4 runs the follow-up.
return await self._compose_round_chunk(chunk)
except StopAsyncIteration:
if self.should_auto_execute and self.collected_response:
@ -683,7 +674,6 @@ class MCPEnhancedStreamingIterator(BaseResponsesAPIStreamingIterator):
composed: Final = await self._compose_round_chunk(chunk)
if composed is None:
# The chunk stays internal; hand the next public event back instead.
return await self._anext_impl()
return composed
@ -749,10 +739,6 @@ class MCPEnhancedStreamingIterator(BaseResponsesAPIStreamingIterator):
return
self.tool_call_round += 1
# Each executed tool is one mcp_call output item of the single
# public response. Announce it at an output_index past the items
# this round already streamed, and keep that item id for the
# completion events below.
from litellm.types.llms.openai import OutputItemAddedEvent
next_output_index = self._output_index_offset + self._round_output_width( # rebind-ok: advances per item
@ -870,7 +856,6 @@ class MCPEnhancedStreamingIterator(BaseResponsesAPIStreamingIterator):
item=mcp_call_item,
)
self.tool_execution_events.append(output_item_done_event)
# The response model accepts output items as dicts, not as the generic event object.
self._pending_mcp_call_items.append(mcp_call_item.model_dump())
# Store tool results for follow-up call