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#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Desc : the implement of Long-term memory
# https://github.com/geekan/MetaGPT/blob/main/metagpt/memory/longterm_memory.py
from typing import Iterable, Type
from autoagents.system.logs import logger
from autoagents.system.schema import Message
from .memory import Memory
from .memory_storage import MemoryStorage
class LongTermMemory(Memory):
"""
The Long-term memory for Roles
- recover memory when it staruped
- update memory when it changed
"""
def __init__(self):
self.memory_storage: MemoryStorage = MemoryStorage()
super(LongTermMemory, self).__init__()
self.rc = None # RoleContext
self.msg_from_recover = False
def recover_memory(self, role_id: str, rc: "RoleContext"):
messages = self.memory_storage.recover_memory(role_id)
self.rc = rc
if not self.memory_storage.is_initialized:
logger.warning(f'It may the first time to run Agent {role_id}, the long-term memory is empty')
else:
logger.warning(f'Agent {role_id} has existed memory storage with {len(messages)} messages '
f'and has recovered them.')
self.msg_from_recover = True
self.add_batch(messages)
self.msg_from_recover = False
def add(self, message: Message):
super(LongTermMemory, self).add(message)
for action in self.rc.watch:
if message.cause_by == action and not self.msg_from_recover:
# currently, only add role's watching messages to its memory_storage
# and ignore adding messages from recover repeatedly
self.memory_storage.add(message)
def remember(self, observed: list[Message], k=10) -> list[Message]:
"""
remember the most similar k memories from observed Messages, return all when k=0
1. remember the short-term memory(stm) news
2. integrate the stm news with ltm(long-term memory) news
"""
stm_news = super(LongTermMemory, self).remember(observed) # shot-term memory news
if not self.memory_storage.is_initialized:
# memory_storage hasn't initialized, use default `remember` to get stm_news
return stm_news
ltm_news: list[Message] = []
for mem in stm_news:
# integrate stm & ltm
mem_searched = self.memory_storage.search(mem)
if len(mem_searched) > 0:
ltm_news.append(mem)
return ltm_news[-k:]
def delete(self, message: Message):
super(LongTermMemory, self).delete(message)
# TODO delete message in memory_storage
def clear(self):
super(LongTermMemory, self).clear()
self.memory_storage.clean()
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