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fix(scheduler): Correctly process feedback logs by checking for 'text… #600

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Merged
glin93 merged 1 commit into from
Dec 3, 2025
Merged

fix(scheduler): Correctly process feedback logs by checking for 'text… #600

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116 changes: 85 additions & 31 deletions src/memos/mem_scheduler/general_scheduler.py
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Original file line number Diff line number Diff line change
Expand Up @@ -600,62 +600,116 @@ def _mem_feedback_message_consumer(self, messages: list[ScheduleMessageItem]) ->
and hasattr(self.rabbitmq_config, "exchange_type")
and self.rabbitmq_config.exchange_type == "direct"
)
if feedback_result and should_send_log:
feedback_content = []
for mem_item in feedback_result:
# Safely access attributes, assuming mem_item could be dict or object
if should_send_log:
record = feedback_result.get("record") if isinstance(feedback_result, dict) else {}
add_records = record.get("add") if isinstance(record, dict) else []
update_records = record.get("update") if isinstance(record, dict) else []

def _extract_fields(mem_item):
mem_id = (
getattr(mem_item, "id", None) or mem_item.get("id")
if isinstance(mem_item, dict)
else None
getattr(mem_item, "id", None)
if not isinstance(mem_item, dict)
else mem_item.get("id")
)
mem_memory = (
getattr(mem_item, "memory", None) or mem_item.get("memory")
if isinstance(mem_item, dict)
else None
getattr(mem_item, "memory", None)
if not isinstance(mem_item, dict)
else mem_item.get("memory") or mem_item.get("text")
)
if mem_memory is None and isinstance(mem_item, dict):
mem_memory = mem_item.get("text")
original_content = (
getattr(mem_item, "origin_memory", None)
if not isinstance(mem_item, dict)
else mem_item.get("origin_memory")
or mem_item.get("old_memory")
or mem_item.get("original_content")
)
return mem_id, mem_memory, original_content

kb_log_content: list[dict] = []

for mem_item in add_records or []:
mem_id, mem_memory, _ = _extract_fields(mem_item)
if mem_id and mem_memory:
kb_log_content.append(
{
"log_source": "KNOWLEDGE_BASE_LOG",
"trigger_source": "Feedback",
"operation": "ADD",
"memory_id": mem_id,
"content": mem_memory,
"original_content": None,
"source_doc_id": None,
}
)
else:
logger.warning(
"Skipping malformed feedback add item. user_id=%s mem_cube_id=%s task_id=%s item=%s",
user_id,
mem_cube_id,
task_id,
mem_item,
stack_info=True,
)

for mem_item in update_records or []:
mem_id, mem_memory, original_content = _extract_fields(mem_item)
if mem_id and mem_memory:
feedback_content.append(
kb_log_content.append(
{
"log_source": "KNOWLEDGE_BASE_LOG",
"trigger_source": "Feedback",
"operation": "UPDATE",
"memory_id": mem_id,
"content": mem_memory,
"id": mem_id,
"original_content": original_content,
"source_doc_id": None,
}
)
else:
logger.warning(
"Skipping malformed mem_item in feedback_result. user_id=%s mem_cube_id=%s task_id=%s item=%s",
"Skipping malformed feedback update item. user_id=%s mem_cube_id=%s task_id=%s item=%s",
user_id,
mem_cube_id,
task_id,
mem_item,
stack_info=True,
)

if not feedback_content:
if kb_log_content:
logger.info(
"[DIAGNOSTIC] general_scheduler._mem_feedback_message_consumer: Creating knowledgeBaseUpdate event for feedback. user_id=%s mem_cube_id=%s task_id=%s items=%s",
user_id,
mem_cube_id,
task_id,
len(kb_log_content),
)
event = self.create_event_log(
label="knowledgeBaseUpdate",
from_memory_type=USER_INPUT_TYPE,
to_memory_type=LONG_TERM_MEMORY_TYPE,
user_id=user_id,
mem_cube_id=mem_cube_id,
mem_cube=mem_cube,
memcube_log_content=kb_log_content,
metadata=None,
memory_len=len(kb_log_content),
memcube_name=self._map_memcube_name(mem_cube_id),
)
event.log_content = (
f"Knowledge Base Memory Update: {len(kb_log_content)} changes."
)
event.task_id = task_id
self._submit_web_logs([event])
else:
logger.warning(
"No valid feedback content generated from feedback_result. user_id=%s mem_cube_id=%s task_id=%s",
"No valid feedback content generated for web log. user_id=%s mem_cube_id=%s task_id=%s",
user_id,
mem_cube_id,
task_id,
stack_info=True,
)
return

event = self.create_event_log(
label="feedbackMemory",
from_memory_type=USER_INPUT_TYPE,
to_memory_type=LONG_TERM_MEMORY_TYPE,
user_id=user_id,
mem_cube_id=mem_cube_id,
mem_cube=mem_cube,
memcube_log_content=feedback_content,
metadata=[],
memory_len=len(feedback_content),
memcube_name=self._map_memcube_name(mem_cube_id),
)
event.task_id = task_id
self._submit_web_logs([event])

except Exception as e:
logger.error(f"Error processing feedbackMemory message: {e}", exc_info=True)
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