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https://github.com/bytedance/deer-flow.git
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8049785de6
* fix(memory): case-insensitive fact deduplication and positive reinforcement detection Two fixes to the memory system: 1. _fact_content_key() now lowercases content before comparison, preventing semantically duplicate facts like "User prefers Python" and "user prefers python" from being stored separately. 2. Adds detect_reinforcement() to MemoryMiddleware (closes #1719), mirroring detect_correction(). When users signal approval ("yes exactly", "perfect", "完全正确", etc.), the memory updater now receives reinforcement_detected=True and injects a hint prompting the LLM to record confirmed preferences and behaviors with high confidence. Changes across the full signal path: - memory_middleware.py: _REINFORCEMENT_PATTERNS + detect_reinforcement() - queue.py: reinforcement_detected field in ConversationContext and add() - updater.py: reinforcement_detected param in update_memory() and update_memory_from_conversation(); builds reinforcement_hint alongside the existing correction_hint Tests: 11 new tests covering deduplication, hint injection, and signal detection (Chinese + English patterns, window boundary, conflict with correction). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(memory): address Copilot review comments on reinforcement detection - Tighten _REINFORCEMENT_PATTERNS: remove 很好, require punctuation/end-of-string boundaries on remaining patterns, split this-is-good into stricter variants - Suppress reinforcement_detected when correction_detected is true to avoid mixed-signal noise - Use casefold() instead of lower() for Unicode-aware fact deduplication - Add missing test coverage for reinforcement_detected OR merge and forwarding in queue --------- Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
92 lines
3.0 KiB
Python
92 lines
3.0 KiB
Python
from unittest.mock import MagicMock, patch
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from deerflow.agents.memory.queue import ConversationContext, MemoryUpdateQueue
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from deerflow.config.memory_config import MemoryConfig
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def _memory_config(**overrides: object) -> MemoryConfig:
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config = MemoryConfig()
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for key, value in overrides.items():
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setattr(config, key, value)
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return config
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def test_queue_add_preserves_existing_correction_flag_for_same_thread() -> None:
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queue = MemoryUpdateQueue()
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with (
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patch("deerflow.agents.memory.queue.get_memory_config", return_value=_memory_config(enabled=True)),
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patch.object(queue, "_reset_timer"),
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):
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queue.add(thread_id="thread-1", messages=["first"], correction_detected=True)
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queue.add(thread_id="thread-1", messages=["second"], correction_detected=False)
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assert len(queue._queue) == 1
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assert queue._queue[0].messages == ["second"]
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assert queue._queue[0].correction_detected is True
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def test_process_queue_forwards_correction_flag_to_updater() -> None:
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queue = MemoryUpdateQueue()
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queue._queue = [
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ConversationContext(
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thread_id="thread-1",
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messages=["conversation"],
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agent_name="lead_agent",
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correction_detected=True,
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)
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]
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mock_updater = MagicMock()
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mock_updater.update_memory.return_value = True
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with patch("deerflow.agents.memory.updater.MemoryUpdater", return_value=mock_updater):
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queue._process_queue()
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mock_updater.update_memory.assert_called_once_with(
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messages=["conversation"],
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thread_id="thread-1",
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agent_name="lead_agent",
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correction_detected=True,
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reinforcement_detected=False,
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)
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def test_queue_add_preserves_existing_reinforcement_flag_for_same_thread() -> None:
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queue = MemoryUpdateQueue()
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with (
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patch("deerflow.agents.memory.queue.get_memory_config", return_value=_memory_config(enabled=True)),
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patch.object(queue, "_reset_timer"),
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):
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queue.add(thread_id="thread-1", messages=["first"], reinforcement_detected=True)
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queue.add(thread_id="thread-1", messages=["second"], reinforcement_detected=False)
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assert len(queue._queue) == 1
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assert queue._queue[0].messages == ["second"]
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assert queue._queue[0].reinforcement_detected is True
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def test_process_queue_forwards_reinforcement_flag_to_updater() -> None:
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queue = MemoryUpdateQueue()
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queue._queue = [
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ConversationContext(
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thread_id="thread-1",
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messages=["conversation"],
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agent_name="lead_agent",
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reinforcement_detected=True,
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)
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]
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mock_updater = MagicMock()
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mock_updater.update_memory.return_value = True
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with patch("deerflow.agents.memory.updater.MemoryUpdater", return_value=mock_updater):
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queue._process_queue()
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mock_updater.update_memory.assert_called_once_with(
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messages=["conversation"],
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thread_id="thread-1",
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agent_name="lead_agent",
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correction_detected=False,
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reinforcement_detected=True,
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)
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