mirror of
https://github.com/agentscope-ai/ReMe.git
synced 2026-09-19 00:01:33 +00:00
5584a5c239
* feat(memory): add CoPaw file-based memory system with compaction and summarization * feat(reme): add tool result cleanup and retention management * fix(memory): resolve copaw memory processing and prompt formatting issues * docs(reme_copaw): update documentation and initialization logic * refactor(reme): remove override parameters from compact_tool_result * feat(docs): update README to reflect CoPaw memory system integration * chore(docs): update model names in documentation
114 lines
4.5 KiB
Python
114 lines
4.5 KiB
Python
"""Context compaction agent for long sessions."""
|
|
|
|
from loguru import logger
|
|
|
|
from ...core.enumeration import Role
|
|
from ...core.op import BaseOp
|
|
from ...core.schema import Message
|
|
from ...core.utils import format_messages
|
|
|
|
|
|
class FbCompactor(BaseOp):
|
|
"""Generate summaries for conversation history compaction."""
|
|
|
|
def __init__(self, return_prompt: bool = False, **kwargs):
|
|
super().__init__(**kwargs)
|
|
self.return_prompt = return_prompt
|
|
|
|
@staticmethod
|
|
def _normalize_messages(messages: list[Message | dict]) -> list[Message]:
|
|
"""Convert dict messages to Message objects."""
|
|
return [Message(**m) if isinstance(m, dict) else m for m in messages]
|
|
|
|
async def _generate_summary(self, prompt_messages: list[Message]) -> str:
|
|
"""Generate summary via LLM. Returns empty string if no messages."""
|
|
assistant_message = await self.llm.chat(prompt_messages)
|
|
return assistant_message.content
|
|
|
|
@staticmethod
|
|
def _serialize_conversation(messages: list[Message]) -> str:
|
|
"""Serialize conversation messages to text format."""
|
|
return format_messages(
|
|
messages=messages,
|
|
add_index=False,
|
|
add_time=True,
|
|
use_name=True,
|
|
add_reasoning=False,
|
|
add_tools=True,
|
|
strip_markdown_headers=False,
|
|
)
|
|
|
|
def _build_history_prompt(self, messages_to_summarize: list[Message], previous_summary: str = "") -> list[Message]:
|
|
"""Build prompt for main history summary."""
|
|
if not messages_to_summarize:
|
|
return []
|
|
|
|
system_prompt = self.get_prompt("system_prompt")
|
|
if previous_summary:
|
|
user_prompt = self.prompt_format("update_user_message", previous_summary=previous_summary)
|
|
else:
|
|
user_prompt = self.get_prompt("initial_user_message")
|
|
conversation_text = self._serialize_conversation(messages_to_summarize)
|
|
|
|
return [
|
|
Message(role=Role.SYSTEM, content=system_prompt),
|
|
Message(role=Role.USER, content=f"<conversation>\n{conversation_text}\n</conversation>\n\n{user_prompt}"),
|
|
]
|
|
|
|
def _build_turn_prefix_prompt(self, turn_prefix_messages: list[Message]) -> list[Message]:
|
|
"""Build prompt for turn prefix summary (split turn only)."""
|
|
if not turn_prefix_messages:
|
|
return []
|
|
|
|
system_prompt = self.get_prompt("system_prompt")
|
|
conversation_text = self._serialize_conversation(turn_prefix_messages)
|
|
turn_prefix_prompt = self.prompt_format(
|
|
"turn_prefix_summarization",
|
|
conversation_text=conversation_text,
|
|
)
|
|
|
|
return [
|
|
Message(role=Role.SYSTEM, content=system_prompt),
|
|
Message(role=Role.USER, content=turn_prefix_prompt),
|
|
]
|
|
|
|
async def execute(self) -> str | dict:
|
|
"""Generate summary for conversation history."""
|
|
messages_to_summarize = self.context.get("messages_to_summarize", [])
|
|
turn_prefix_messages = self.context.get("turn_prefix_messages", [])
|
|
previous_summary = self.context.get("previous_summary", "")
|
|
|
|
messages_to_summarize = self._normalize_messages(messages_to_summarize)
|
|
turn_prefix_messages = self._normalize_messages(turn_prefix_messages)
|
|
|
|
# Build prompt messages once before branching
|
|
history_prompt_messages = self._build_history_prompt(messages_to_summarize, previous_summary)
|
|
turn_prefix_prompt_messages = self._build_turn_prefix_prompt(turn_prefix_messages)
|
|
|
|
if self.return_prompt:
|
|
result = {"system": self.get_prompt("system_prompt")}
|
|
|
|
if len(history_prompt_messages) == 2:
|
|
result["history_user"] = history_prompt_messages[-1].content
|
|
|
|
if len(turn_prefix_prompt_messages) == 2:
|
|
result["turn_prefix_user"] = turn_prefix_prompt_messages[-1].content
|
|
|
|
return result
|
|
|
|
else:
|
|
if history_prompt_messages:
|
|
history_summary = "**History Summary**:\n\n" + await self._generate_summary(history_prompt_messages)
|
|
else:
|
|
history_summary = ""
|
|
|
|
if turn_prefix_prompt_messages:
|
|
turn_prefix_summary = "**Turn Context**:\n\n" + await self._generate_summary(
|
|
turn_prefix_prompt_messages,
|
|
)
|
|
else:
|
|
turn_prefix_summary = ""
|
|
|
|
summary = "\n\n---".join([history_summary, turn_prefix_summary])
|
|
logger.info(f"Generated summary: {summary}")
|
|
return summary
|