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初步修复PFC的导入错误

pull/1481/head
墨梓柒 2026-01-07 00:46:38 +08:00
parent a8c25cdc15
commit a72bcc4759
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9 changed files with 97 additions and 51 deletions
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27
src/chat/brain_chat/PFC/action_planner.py
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@ -1,14 +1,14 @@
import time
from typing import Tuple, Optional # 增加了 Optional
from src.common.logger_manager import get_logger
from ..models.utils_model import LLMRequest
from ...config.config import global_config
from src.common.logger import get_logger
from src.llm_models.utils_model import LLMRequest
from src.config.config import global_config
import random
from .chat_observer import ChatObserver
from .pfc_utils import get_items_from_json
from src.individuality.individuality import Individuality
from .observation_info import ObservationInfo
from .conversation_info import ConversationInfo
from src.plugins.utils.chat_message_builder import build_readable_messages
from src.chat.utils.chat_message_builder import build_readable_messages
logger = get_logger("pfc_action_planner")
@ -113,12 +113,27 @@ class ActionPlanner:
max_tokens=1500,
request_type="action_planning",
)
self.personality_info = Individuality.get_instance().get_prompt(x_person=2, level=3)
self.personality_info = self._get_personality_prompt()
self.name = global_config.BOT_NICKNAME
self.private_name = private_name
self.chat_observer = ChatObserver.get_instance(stream_id, private_name)
# self.action_planner_info = ActionPlannerInfo() # 移除未使用的变量
def _get_personality_prompt(self) -> str:
"""获取个性提示信息"""
prompt_personality = global_config.personality.personality
# 检查是否需要随机替换为状态
if (
global_config.personality.states
and global_config.personality.state_probability > 0
and random.random() < global_config.personality.state_probability
):
prompt_personality = random.choice(global_config.personality.states)
bot_name = global_config.BOT_NICKNAME
return f"你的名字是{bot_name},你{prompt_personality};"
# 修改 plan 方法签名，增加 last_successful_reply_action 参数
async def plan(
self,

18
src/chat/brain_chat/PFC/conversation.py
View File

@ -3,22 +3,22 @@ import asyncio
import datetime
# from .message_storage import MongoDBMessageStorage
from src.plugins.utils.chat_message_builder import build_readable_messages, get_raw_msg_before_timestamp_with_chat
from src.chat.utils.chat_message_builder import build_readable_messages, get_raw_msg_before_timestamp_with_chat
# from ...config.config import global_config
# from src.config.config import global_config
from typing import Dict, Any, Optional
from ..chat.message import Message
from src.chat.message_receive.message import Message
from .pfc_types import ConversationState
from .pfc import ChatObserver, GoalAnalyzer
from .message_sender import DirectMessageSender
from src.common.logger_manager import get_logger
from src.common.logger import get_logger
from .action_planner import ActionPlanner
from .observation_info import ObservationInfo
from .conversation_info import ConversationInfo # 确保导入 ConversationInfo
from .reply_generator import ReplyGenerator
from ..chat.chat_stream import ChatStream
from src.chat.message_receive.chat_stream import ChatStream
from maim_message import UserInfo
from src.plugins.chat.chat_stream import chat_manager
from src.chat.message_receive.chat_stream import get_chat_manager
from .pfc_KnowledgeFetcher import KnowledgeFetcher
from .waiter import Waiter
@ -60,7 +60,7 @@ class Conversation:
self.direct_sender = DirectMessageSender(self.private_name)
# 获取聊天流信息
self.chat_stream = chat_manager.get_stream(self.stream_id)
self.chat_stream = get_chat_manager().get_stream(self.stream_id)
self.stop_action_planner = False
except Exception as e:
@ -248,14 +248,14 @@ class Conversation:
def _convert_to_message(self, msg_dict: Dict[str, Any]) -> Message:
"""将消息字典转换为Message对象"""
try:
# 尝试从 msg_dict 直接获取 chat_stream，如果失败则从全局 chat_manager 获取
# 尝试从 msg_dict 直接获取 chat_stream，如果失败则从全局 get_chat_manager 获取
chat_info = msg_dict.get("chat_info")
if chat_info and isinstance(chat_info, dict):
chat_stream = ChatStream.from_dict(chat_info)
elif self.chat_stream: # 使用实例变量中的 chat_stream
chat_stream = self.chat_stream
else: # Fallback: 尝试从 manager 获取 (可能需要 stream_id)
chat_stream = chat_manager.get_stream(self.stream_id)
chat_stream = get_chat_manager().get_stream(self.stream_id)
if not chat_stream:
raise ValueError(f"无法确定 ChatStream for stream_id {self.stream_id}")

31
src/chat/brain_chat/PFC/message_sender.py
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@ -1,13 +1,11 @@
import time
from typing import Optional
from src.common.logger import get_module_logger
from ..chat.chat_stream import ChatStream
from ..chat.message import Message
from src.chat.message_receive.chat_stream import ChatStream
from src.chat.message_receive.message import Message, MessageSending
from maim_message import UserInfo, Seg
from src.plugins.chat.message import MessageSending, MessageSet
from src.plugins.chat.message_sender import message_manager
from ..storage.storage import MessageStorage
from ...config.config import global_config
from src.chat.message_receive.storage import MessageStorage
from src.config.config import global_config
from rich.traceback import install
install(extra_lines=3)
@ -66,15 +64,18 @@ class DirectMessageSender:
# 处理消息
await message.process()
# 不知道有什么用，先留下来了，和之前那套sender一样
_message_json = message.to_dict()
# 发送消息
message_set = MessageSet(chat_stream, message_id)
message_set.add_message(message)
await message_manager.add_message(message_set)
await self.storage.store_message(message, chat_stream)
logger.info(f"[私聊][{self.private_name}]PFC消息已发送: {content}")
# 发送消息（直接调用底层 API）
from src.chat.message_receive.uni_message_sender import _send_message
sent = await _send_message(message, show_log=True)
if sent:
# 存储消息
await self.storage.store_message(message, chat_stream)
logger.info(f"[私聊][{self.private_name}]PFC消息已发送: {content}")
else:
logger.error(f"[私聊][{self.private_name}]PFC消息发送失败")
raise RuntimeError("消息发送失败")
except Exception as e:
logger.error(f"[私聊][{self.private_name}]PFC消息发送失败: {str(e)}")

2
src/chat/brain_chat/PFC/observation_info.py
View File

@ -4,7 +4,7 @@ import time
from src.common.logger import get_module_logger
from .chat_observer import ChatObserver
from .chat_states import NotificationHandler, NotificationType, Notification
from src.plugins.utils.chat_message_builder import build_readable_messages
from src.chat.utils.chat_message_builder import build_readable_messages
import traceback # 导入 traceback 用于调试
logger = get_module_logger("observation_info")

25
src/chat/brain_chat/PFC/pfc.py
View File

@ -1,13 +1,13 @@
from typing import List, Tuple, TYPE_CHECKING
from src.common.logger import get_module_logger
from ..models.utils_model import LLMRequest
from ...config.config import global_config
from src.llm_models.utils_model import LLMRequest
from src.config.config import global_config
import random
from .chat_observer import ChatObserver
from .pfc_utils import get_items_from_json
from src.individuality.individuality import Individuality
from .conversation_info import ConversationInfo
from .observation_info import ObservationInfo
from src.plugins.utils.chat_message_builder import build_readable_messages
from src.chat.utils.chat_message_builder import build_readable_messages
from rich.traceback import install
install(extra_lines=3)
@ -46,7 +46,7 @@ class GoalAnalyzer:
model=global_config.llm_normal, temperature=0.7, max_tokens=1000, request_type="conversation_goal"
)
self.personality_info = Individuality.get_instance().get_prompt(x_person=2, level=3)
self.personality_info = self._get_personality_prompt()
self.name = global_config.BOT_NICKNAME
self.nick_name = global_config.BOT_ALIAS_NAMES
self.private_name = private_name
@ -57,6 +57,21 @@ class GoalAnalyzer:
self.max_goals = 3 # 同时保持的最大目标数量
self.current_goal_and_reason = None
def _get_personality_prompt(self) -> str:
"""获取个性提示信息"""
prompt_personality = global_config.personality.personality
# 检查是否需要随机替换为状态
if (
global_config.personality.states
and global_config.personality.state_probability > 0
and random.random() < global_config.personality.state_probability
):
prompt_personality = random.choice(global_config.personality.states)
bot_name = global_config.bot.nickname
return f"你的名字是{bot_name},你{prompt_personality};"
async def analyze_goal(self, conversation_info: ConversationInfo, observation_info: ObservationInfo):
"""分析对话历史并设定目标

10
src/chat/brain_chat/PFC/pfc_KnowledgeFetcher.py
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@ -1,11 +1,11 @@
from typing import List, Tuple
from src.common.logger import get_module_logger
from src.plugins.memory_system.Hippocampus import HippocampusManager
from ..models.utils_model import LLMRequest
from ...config.config import global_config
from ..chat.message import Message
from ..knowledge.knowledge_lib import qa_manager
from ..utils.chat_message_builder import build_readable_messages
from src.llm_models.utils_model import LLMRequest
from src.config.config import global_config
from src.chat.message_receive.message import Message
from src.chat.knowledge.knowledge_lib import qa_manager
from src.chat.utils.chat_message_builder import build_readable_messages
logger = get_module_logger("knowledge_fetcher")

4
src/chat/brain_chat/PFC/reply_checker.py
View File

@ -1,8 +1,8 @@
import json
from typing import Tuple, List, Dict, Any
from src.common.logger import get_module_logger
from ..models.utils_model import LLMRequest
from ...config.config import global_config
from src.llm_models.utils_model import LLMRequest
from src.config.config import global_config
from .chat_observer import ChatObserver
from maim_message import UserInfo

29
src/chat/brain_chat/PFC/reply_generator.py
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@ -1,15 +1,15 @@
from typing import Tuple, List, Dict, Any
from src.common.logger import get_module_logger
from ..models.utils_model import LLMRequest
from ...config.config import global_config
from src.common.logger import get_logger
from src.llm_models.utils_model import LLMRequest
from src.config.config import global_config
import random
from .chat_observer import ChatObserver
from .reply_checker import ReplyChecker
from src.individuality.individuality import Individuality
from .observation_info import ObservationInfo
from .conversation_info import ConversationInfo
from src.plugins.utils.chat_message_builder import build_readable_messages
from src.chat.utils.chat_message_builder import build_readable_messages
logger = get_module_logger("reply_generator")
logger = get_logger("reply_generator")
# --- 定义 Prompt 模板 ---
@ -92,12 +92,27 @@ class ReplyGenerator:
max_tokens=300,
request_type="reply_generation",
)
self.personality_info = Individuality.get_instance().get_prompt(x_person=2, level=3)
self.personality_info = self._get_personality_prompt()
self.name = global_config.BOT_NICKNAME
self.private_name = private_name
self.chat_observer = ChatObserver.get_instance(stream_id, private_name)
self.reply_checker = ReplyChecker(stream_id, private_name)
def _get_personality_prompt(self) -> str:
"""获取个性提示信息"""
prompt_personality = global_config.personality.personality
# 检查是否需要随机替换为状态
if (
global_config.personality.states
and global_config.personality.state_probability > 0
and random.random() < global_config.personality.state_probability
):
prompt_personality = random.choice(global_config.personality.states)
bot_name = global_config.BOT_NICKNAME
return f"你的名字是{bot_name},你{prompt_personality};"
# 修改 generate 方法签名，增加 action_type 参数
async def generate(
self, observation_info: ObservationInfo, conversation_info: ConversationInfo, action_type: str

2
src/chat/brain_chat/PFC/waiter.py
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@ -3,7 +3,7 @@ from .chat_observer import ChatObserver
from .conversation_info import ConversationInfo
# from src.individuality.individuality import Individuality # 不再需要
from ...config.config import global_config
from src.config.config import global_config
import time
import asyncio