mirror of
https://github.com/agentscope-ai/ReMe.git
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7b02c45218
* style(memory): update message formatting and improve logging - Change default include_thinking parameter to True in as_msg_handler.py - Replace angle brackets with square brackets for block formatting in as_msg_stat.py - Add newline replacement in text truncation method in as_msg_stat.py - Add loading duration timing to embedding cache loading in base_embedding_model.py - Replace XML-style tags with markdown headers in compactor.py conversation format - Update compactor.yaml prompts to reference markdown-style headers instead of XML tags - Modify summarizer.py to use markdown-style conversation header format * refactor(file-watcher): replace scan_on_start with rebuild_index_on_start parameter - Replace scan_on_start and clear_on_start boolean parameters with single rebuild_index_on_start - Update BaseFileWatcher constructor to use rebuild_index_on_start instead of two separate flags - Modify initialization logic to clear and rescan when rebuild_index_on_start is True - Remove scan_on_start parameter from CLI and light configuration files - Update documentation to remove scan_on_start from quick start guides - Rename all test methods and classes from scan_on_start to rebuild_index_on_start - Add timezone-aware datetime helper method to summarizer component - Format log message with proper line breaks for readability * fix(core): resolve file watcher initialization issue and update version - Fixed file watcher task creation to properly handle rebuild index on start logic - Moved initialization and watch loop into async function to ensure proper execution order - Updated package version from 0.3.1.1 to 0.3.1.2 - Added missing comma in embedding model logging statement * fix(core): reduce max formatter text length limit - Changed _DEFAULT_MAX_FORMATTER_TEXT_LENGTH from 2000 to 1000 - Updated constant value in as_msg_stat.py schema module * fix(file-watcher): change default rebuild index behavior on start - Changed rebuild_index_on_start parameter default from False to True - This ensures index is rebuilt by default when file watcher starts - Maintains consistent state initialization for file watching operations * feat(compactor): add return_dict option and improve summary validation - Add _is_valid_summary function to validate summary content format - Introduce return_dict parameter to return structured results with validation - Update prompt templates with clearer task descriptions and formatting rules - Refactor update_user_message prompts to combine prefix and suffix logic - Return dictionary with user_message, history_compact, and is_valid fields when enabled - Add proper error handling for exception cases in memory compaction - Maintain backward compatibility with string return when return_dict=False * feat(memory): add thinking block configuration option - Add add_thinking_block parameter to compactor component - Pass include_thinking flag to message formatting in compactor - Add add_thinking_block parameter to reme_light compact function - Add add_thinking_block parameter to reme_light summarize function - Add add_thinking_block parameter to summarizer component - Pass include_thinking flag to message formatting in summarizer - Remove previous-summary tags from compressed summary format
110 lines
3.8 KiB
Python
110 lines
3.8 KiB
Python
"""Compactor module for memory compaction operations."""
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from agentscope.agent import ReActAgent
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from agentscope.message import Msg
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from ..utils import AsMsgHandler
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from ....core.op import BaseOp
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from ....core.utils import get_logger
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logger = get_logger()
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def _is_valid_summary(content: str) -> bool:
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"""Check if the summary content is valid.
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Args:
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content: The summary content to validate.
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Returns:
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True if valid, False otherwise.
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"""
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if not content or not content.strip():
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return False
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if "##" not in content:
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return False
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return True
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class Compactor(BaseOp):
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"""Compactor class for compacting memory messages."""
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def __init__(
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self,
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memory_compact_threshold: int,
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console_enabled: bool = False,
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return_dict: bool = False,
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add_thinking_block: bool = True,
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**kwargs,
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):
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super().__init__(**kwargs)
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self.memory_compact_threshold: int = memory_compact_threshold
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self.console_enabled: bool = console_enabled
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self.return_dict: bool = return_dict
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self.add_thinking_block: bool = add_thinking_block
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# pylint: disable=too-many-return-statements
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async def execute(self):
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messages: list[Msg] = self.context.get("messages", [])
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previous_summary: str = self.context.get("previous_summary", "")
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if not messages:
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if self.return_dict:
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return {"user_message": "", "history_compact": "", "is_valid": False}
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return ""
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msg_handler = AsMsgHandler(self.as_token_counter)
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before_token_count = await msg_handler.count_msgs_token(messages)
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history_formatted_str: str = await msg_handler.format_msgs_to_str(
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messages=messages,
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memory_compact_threshold=self.memory_compact_threshold,
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include_thinking=self.add_thinking_block,
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)
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after_token_count = await msg_handler.count_str_token(history_formatted_str)
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logger.info(f"Compactor before_token_count={before_token_count} after_token_count={after_token_count}")
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if not history_formatted_str:
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logger.warning(f"No history to compact. messages={messages}")
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if self.return_dict:
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return {"user_message": "", "history_compact": "", "is_valid": False}
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return ""
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agent = ReActAgent(
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name="reme_compactor",
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model=self.as_llm,
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sys_prompt=self.get_prompt("system_prompt"),
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formatter=self.as_llm_formatter,
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)
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agent.set_console_output_enabled(self.console_enabled)
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if previous_summary:
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user_message: str = (
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f"# conversation\n{history_formatted_str}\n\n"
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f"# previous-summary\n{previous_summary}\n\n" + self.get_prompt("update_user_message")
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)
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else:
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user_message: str = f"# conversation\n{history_formatted_str}\n\n" + self.get_prompt("initial_user_message")
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logger.info(f"Compactor sys_prompt={agent.sys_prompt} user_message={user_message}")
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compact_msg: Msg = await agent.reply(
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Msg(
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name="reme",
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role="user",
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content=user_message,
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),
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)
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history_compact: str = compact_msg.get_text_content()
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is_valid: bool = _is_valid_summary(history_compact)
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if not is_valid:
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logger.warning(f"Invalid summary result: {history_compact[:200]}...")
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if self.return_dict:
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return {"user_message": user_message, "history_compact": history_compact, "is_valid": False}
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return ""
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logger.info(f"Compactor Result:\n{history_compact}")
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if self.return_dict:
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return {"user_message": user_message, "history_compact": history_compact, "is_valid": True}
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return history_compact
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