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把字典转换为数据模型并恢复全系统可用性，临时修复InstantMemory让大模型至少知道在聊什么

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UnCLAS-Prommer
2025-08-21 23:21:56 +08:00
parent f41a3076f6
commit c6f0c51825
12 changed files with 462 additions and 258 deletions
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61
src/chat/replyer/default_generator.py
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@@ -9,6 +9,7 @@ from datetime import datetime
from src.mais4u.mai_think import mai_thinking_manager
from src.common.logger import get_logger
from src.common.data_models.database_data_model import DatabaseMessages
from src.common.data_models.info_data_model import ActionPlannerInfo
from src.config.config import global_config, model_config
from src.individuality.individuality import get_individuality
from src.llm_models.utils_model import LLMRequest
@@ -157,12 +158,12 @@ class DefaultReplyer:
extra_info: str = "",
reply_reason: str = "",
available_actions: Optional[Dict[str, ActionInfo]] = None,
chosen_actions: Optional[List[Dict[str, Any]]] = None,
chosen_actions: Optional[List[ActionPlannerInfo]] = None,
enable_tool: bool = True,
from_plugin: bool = True,
stream_id: Optional[str] = None,
reply_message: Optional[Dict[str, Any]] = None,
) -> Tuple[bool, Optional[Dict[str, Any]], Optional[str], List[Dict[str, Any]]]:
reply_message: Optional[DatabaseMessages] = None,
) -> Tuple[bool, Optional[Dict[str, Any]], Optional[str], Optional[List[int]]]:
# sourcery skip: merge-nested-ifs
"""
回复器 (Replier): 负责生成回复文本的核心逻辑。
@@ -181,7 +182,7 @@ class DefaultReplyer:
"""
prompt = None
selected_expressions = None
selected_expressions: Optional[List[int]] = None
if available_actions is None:
available_actions = {}
try:
@@ -374,7 +375,12 @@ class DefaultReplyer:
)
if global_config.memory.enable_instant_memory:
asyncio.create_task(self.instant_memory.create_and_store_memory(chat_history))
chat_history_str = build_readable_messages(
messages=chat_history,
replace_bot_name=True,
timestamp_mode="normal"
)
asyncio.create_task(self.instant_memory.create_and_store_memory(chat_history_str))
instant_memory = await self.instant_memory.get_memory(target)
logger.info(f"即时记忆：{instant_memory}")
@@ -527,7 +533,7 @@ class DefaultReplyer:
Returns:
Tuple[str, str]: (核心对话prompt, 背景对话prompt)
"""
core_dialogue_list = []
core_dialogue_list: List[DatabaseMessages] = []
bot_id = str(global_config.bot.qq_account)
# 过滤消息：分离bot和目标用户的对话 vs 其他用户的对话
@@ -559,7 +565,7 @@ class DefaultReplyer:
if core_dialogue_list:
# 检查最新五条消息中是否包含bot自己说的消息
latest_5_messages = core_dialogue_list[-5:] if len(core_dialogue_list) >= 5 else core_dialogue_list
has_bot_message = any(str(msg.get("user_id")) == bot_id for msg in latest_5_messages)
has_bot_message = any(str(msg.user_info.user_id) == bot_id for msg in latest_5_messages)
# logger.info(f"最新五条消息：{latest_5_messages}")
# logger.info(f"最新五条消息中是否包含bot自己说的消息：{has_bot_message}")
@@ -634,7 +640,7 @@ class DefaultReplyer:
return mai_think
async def build_actions_prompt(
self, available_actions, choosen_actions: Optional[List[Dict[str, Any]]] = None
self, available_actions: Dict[str, ActionInfo], chosen_actions_info: Optional[List[ActionPlannerInfo]] = None
) -> str:
"""构建动作提示"""
@@ -646,20 +652,21 @@ class DefaultReplyer:
action_descriptions += f"- {action_name}: {action_description}\n"
action_descriptions += "\n"
choosen_action_descriptions = ""
if choosen_actions:
for action in choosen_actions:
action_name = action.get("action_type", "unknown_action")
chosen_action_descriptions = ""
if chosen_actions_info:
for action_plan_info in chosen_actions_info:
action_name = action_plan_info.action_type
if action_name == "reply":
continue
action_description = action.get("reason", "无描述")
reasoning = action.get("reasoning", "无原因")
if action := available_actions.get(action_name):
action_description = action.description or "无描述"
reasoning = action_plan_info.reasoning or "无原因"
choosen_action_descriptions += f"- {action_name}: {action_description}，原因：{reasoning}\n"
chosen_action_descriptions += f"- {action_name}: {action_description}，原因：{reasoning}\n"
if choosen_action_descriptions:
if chosen_action_descriptions:
action_descriptions += "根据聊天情况，另一个模型决定在回复的同时做以下这些动作：\n"
action_descriptions += choosen_action_descriptions
action_descriptions += chosen_action_descriptions
return action_descriptions
@@ -668,9 +675,9 @@ class DefaultReplyer:
extra_info: str = "",
reply_reason: str = "",
available_actions: Optional[Dict[str, ActionInfo]] = None,
chosen_actions: Optional[List[Dict[str, Any]]] = None,
chosen_actions: Optional[List[ActionPlannerInfo]] = None,
enable_tool: bool = True,
reply_message: Optional[Dict[str, Any]] = None,
reply_message: Optional[DatabaseMessages] = None,
) -> Tuple[str, List[int]]:
"""
构建回复器上下文
@@ -694,11 +701,11 @@ class DefaultReplyer:
platform = chat_stream.platform
if reply_message:
user_id = reply_message.get("user_id", "")
user_id = reply_message.user_info.user_id
person = Person(platform=platform, user_id=user_id)
person_name = person.person_name or user_id
sender = person_name
target = reply_message.get("processed_plain_text")
target = reply_message.processed_plain_text
else:
person_name = "用户"
sender = "用户"
@@ -774,11 +781,13 @@ class DefaultReplyer:
logger.info(f"回复准备: {'; '.join(timing_logs)}; {almost_zero_str} <0.01s")
expression_habits_block, selected_expressions = results_dict["expression_habits"]
relation_info = results_dict["relation_info"]
memory_block = results_dict["memory_block"]
tool_info = results_dict["tool_info"]
prompt_info = results_dict["prompt_info"] # 直接使用格式化后的结果
actions_info = results_dict["actions_info"]
expression_habits_block: str
selected_expressions: List[int]
relation_info: str = results_dict["relation_info"]
memory_block: str = results_dict["memory_block"]
tool_info: str = results_dict["tool_info"]
prompt_info: str = results_dict["prompt_info"] # 直接使用格式化后的结果
actions_info: str = results_dict["actions_info"]
keywords_reaction_prompt = await self.build_keywords_reaction_prompt(target)
if extra_info: