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fix(longtext): avoid split interfering with multi-chain agent responses

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Use query variable '_longtext_split_extra_chains' to pass extra split
segments instead of appending to resp_message_chain directly. This
prevents agent tool-call multi-round responses from being misidentified
as split results and sent repeatedly.

respback.py reverts to original single-chain logic and appends split
extra chains after the main response.
This commit is contained in:
RockChinQ
2026-03-12 09:52:59 -04:00
parent c92d3d7ad7
commit 662e6a4815
2 changed files with 37 additions and 40 deletions
Download Patch File Download Diff File Expand all files Collapse all files
src/langbot/pkg/pipeline/longtext/longtext.py
+9 -4
View File
@@ -97,10 +97,15 @@ class LongTextProcessStage(stage.PipelineStage):
original_text = str(query.resp_message_chain[-1]) original_text = str(query.resp_message_chain[-1])
threshold = query.pipeline_config['output']['long-text-processing']['threshold'] threshold = query.pipeline_config['output']['long-text-processing']['threshold']
segments = self.strategy_impl.split_text(original_text, threshold) segments = self.strategy_impl.split_text(original_text, threshold)
query.resp_message_chain.pop() # Replace the last chain with the first segment, store extra segments separately
for segment in segments: # to avoid interfering with existing multi-chain scenarios (e.g. agent tool calls)
query.resp_message_chain.append( query.resp_message_chain[-1] = platform_message.MessageChain(
platform_message.MessageChain([platform_message.Plain(text=segment)]) [platform_message.Plain(text=segments[0])]
)
if len(segments) > 1:
query.set_variable(
'_longtext_split_extra_chains',
[platform_message.MessageChain([platform_message.Plain(text=seg)]) for seg in segments[1:]],
) )
else: else:
query.resp_message_chain[-1] = platform_message.MessageChain( query.resp_message_chain[-1] = platform_message.MessageChain(
src/langbot/pkg/pipeline/respback/respback.py
+28 -36
View File
@@ -30,48 +30,40 @@ class SendResponseBackStage(stage.PipelineStage):
await asyncio.sleep(random_delay) await asyncio.sleep(random_delay)
if query.pipeline_config['output']['misc']['at-sender'] and isinstance(
query.message_event, platform_events.GroupMessage
):
query.resp_message_chain[-1].insert(0, platform_message.At(target=query.message_event.sender.id))
quote_origin = query.pipeline_config['output']['misc']['quote-origin'] quote_origin = query.pipeline_config['output']['misc']['quote-origin']
if len(query.resp_message_chain) > 1: has_chunks = any(isinstance(msg, provider_message.MessageChunk) for msg in query.resp_messages)
# Multiple chains (split strategy): send each sequentially # TODO 命令与流式的兼容性问题
for i, chain in enumerate(query.resp_message_chain): if await query.adapter.is_stream_output_supported() and has_chunks:
is_first = i == 0 is_final = [msg.is_final for msg in query.resp_messages][0]
await query.adapter.reply_message_chunk(
if ( message_source=query.message_event,
is_first bot_message=query.resp_messages[-1],
and query.pipeline_config['output']['misc']['at-sender'] message=query.resp_message_chain[-1],
and isinstance(query.message_event, platform_events.GroupMessage) quote_origin=quote_origin,
): is_final=is_final,
chain.insert(0, platform_message.At(target=query.message_event.sender.id)) )
else:
await query.adapter.reply_message(
message_source=query.message_event,
message=query.resp_message_chain[-1],
quote_origin=quote_origin,
)
# Send extra chains produced by long text split strategy
extra_chains = query.get_variable('_longtext_split_extra_chains')
if extra_chains:
for chain in extra_chains:
await query.adapter.reply_message( await query.adapter.reply_message(
message_source=query.message_event, message_source=query.message_event,
message=chain, message=chain,
quote_origin=quote_origin if is_first else False, quote_origin=False,
)
else:
if query.pipeline_config['output']['misc']['at-sender'] and isinstance(
query.message_event, platform_events.GroupMessage
):
query.resp_message_chain[-1].insert(0, platform_message.At(target=query.message_event.sender.id))
has_chunks = any(isinstance(msg, provider_message.MessageChunk) for msg in query.resp_messages)
# TODO 命令与流式的兼容性问题
if await query.adapter.is_stream_output_supported() and has_chunks:
is_final = [msg.is_final for msg in query.resp_messages][0]
await query.adapter.reply_message_chunk(
message_source=query.message_event,
bot_message=query.resp_messages[-1],
message=query.resp_message_chain[-1],
quote_origin=quote_origin,
is_final=is_final,
)
else:
await query.adapter.reply_message(
message_source=query.message_event,
message=query.resp_message_chain[-1],
quote_origin=quote_origin,
) )
query.set_variable('_longtext_split_extra_chains', None)
return entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query) return entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)