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PFC 兼容新版数据模型

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This commit is contained in:
DrSmoothl
2026-03-14 00:36:52 +08:00
parent 4bc9c5bf7e
commit 4b9c905026
6 changed files with 83 additions and 76 deletions
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16
src/chat/brain_chat/PFC/action_planner.py
View File

@@ -1,14 +1,16 @@
import time
from typing import Tuple, Optional # 增加了 Optional
from src.common.logger import get_logger
from src.llm_models.utils_model import LLMRequest
from src.config.config import global_config, model_config
import random
from .chat_observer import ChatObserver
from .pfc_utils import get_items_from_json
from .observation_info import ObservationInfo, dict_to_database_message
from src.services.message_service import build_readable_messages
from .observation_info import ObservationInfo, dict_to_session_message
from .conversation_info import ConversationInfo
from src.chat.utils.chat_message_builder import build_readable_messages
logger = get_logger("pfc_action_planner")
@@ -271,19 +273,17 @@ class ActionPlanner:
# 获取聊天历史记录 (chat_history_text)
try:
if hasattr(observation_info, "chat_history") and observation_info.chat_history:
chat_history_text = observation_info.chat_history_str
if not chat_history_text:
chat_history_text = "还没有聊天记录。\n"
chat_history_text = observation_info.chat_history_str or "还没有聊天记录。\n"
else:
chat_history_text = "还没有聊天记录。\n"
if hasattr(observation_info, "new_messages_count") and observation_info.new_messages_count > 0:
if hasattr(observation_info, "unprocessed_messages") and observation_info.unprocessed_messages:
new_messages_list = observation_info.unprocessed_messages
# Convert dict format to DatabaseMessages objects
db_messages = [dict_to_database_message(m) for m in new_messages_list]
# Convert dict format to SessionMessage objects.
session_messages = [dict_to_session_message(m) for m in new_messages_list]
new_messages_str = build_readable_messages(
db_messages,
session_messages,
replace_bot_name=True,
timestamp_mode="relative",
read_mark=0.0,

28
src/chat/brain_chat/PFC/conversation.py
View File

@@ -1,13 +1,14 @@
import time
import asyncio
import datetime
import time
from typing import Dict, Any, Optional
from src.common.data_models.mai_message_data_model import MaiMessage
from src.services.message_service import build_readable_messages, get_messages_before_time_in_chat
# from .message_storage import MongoDBMessageStorage
from src.chat.utils.chat_message_builder import build_readable_messages, get_raw_msg_before_timestamp_with_chat
# from src.config.config import global_config
from typing import Dict, Any, Optional
from src.common.data_models.mai_message_data_model import MaiMessage
from .pfc_types import ConversationState
from .pfc import ChatObserver, GoalAnalyzer
from .message_sender import DirectMessageSender
@@ -83,7 +84,7 @@ class Conversation:
raise
try:
logger.info(f"[私聊][{self.private_name}]为 {self.stream_id} 加载初始聊天记录...")
initial_messages = get_raw_msg_before_timestamp_with_chat( #
initial_messages = get_messages_before_time_in_chat(
chat_id=self.stream_id,
timestamp=time.time(),
limit=30, # 加载最近30条作为初始上下文，可以调整
@@ -95,22 +96,23 @@ class Conversation:
read_mark=0.0,
)
if initial_messages:
# 将 DatabaseMessages 列表转换为 PFC 期望的 dict 格式（保持嵌套结构）
# 将 SessionMessage 列表转换为 PFC 期望的 dict 格式（保持嵌套结构）
initial_messages_dict: list[dict] = []
for msg in initial_messages:
user_info = msg.message_info.user_info
msg_dict = {
"message_id": msg.message_id,
"time": msg.time,
"chat_id": msg.chat_id,
"time": msg.timestamp.timestamp(),
"chat_id": msg.session_id,
"processed_plain_text": msg.processed_plain_text,
"display_message": msg.display_message,
"is_mentioned": msg.is_mentioned,
"is_command": msg.is_command,
"user_info": {
"user_id": msg.user_info.user_id if msg.user_info else "",
"user_nickname": msg.user_info.user_nickname if msg.user_info else "",
"user_cardname": msg.user_info.user_cardname if msg.user_info else None,
"platform": msg.user_info.platform if msg.user_info else "",
"user_id": user_info.user_id,
"user_nickname": user_info.user_nickname,
"user_cardname": user_info.user_cardname,
"platform": msg.platform,
},
}
initial_messages_dict.append(msg_dict)

54
src/chat/brain_chat/PFC/observation_info.py
View File

@@ -1,40 +1,52 @@
from typing import List, Optional, Dict, Any, Set
from datetime import datetime
from typing import Any, Dict, List, Optional, Set
from maim_message import UserInfo
import time
from src.chat.message_receive.message import SessionMessage
from src.common.logger import get_logger
from src.common.data_models.mai_message_data_model import MessageInfo, UserInfo as MaiUserInfo
from src.services.message_service import build_readable_messages
from .chat_observer import ChatObserver
from .chat_states import NotificationHandler, NotificationType, Notification
from src.chat.utils.chat_message_builder import build_readable_messages
from src.common.data_models.database_data_model import DatabaseMessages
import traceback # 导入 traceback 用于调试
logger = get_logger("observation_info")
def dict_to_database_message(msg_dict: Dict[str, Any]) -> DatabaseMessages:
"""Convert PFC dict format to DatabaseMessages object
def dict_to_session_message(msg_dict: Dict[str, Any]) -> SessionMessage:
"""Convert PFC dict format to SessionMessage object.
Args:
msg_dict: Message in PFC dict format with nested user_info
Returns:
DatabaseMessages object compatible with build_readable_messages()
SessionMessage object compatible with build_readable_messages()
"""
user_info_dict: Dict[str, Any] = msg_dict.get("user_info", {})
return DatabaseMessages(
timestamp = msg_dict.get("time", 0.0)
platform = user_info_dict.get("platform", "")
message = SessionMessage(
message_id=msg_dict.get("message_id", ""),
time=msg_dict.get("time", 0.0),
chat_id=msg_dict.get("chat_id", ""),
processed_plain_text=msg_dict.get("processed_plain_text", ""),
display_message=msg_dict.get("display_message", ""),
is_mentioned=msg_dict.get("is_mentioned", False),
is_command=msg_dict.get("is_command", False),
user_id=user_info_dict.get("user_id", ""),
user_nickname=user_info_dict.get("user_nickname", ""),
user_cardname=user_info_dict.get("user_cardname"),
user_platform=user_info_dict.get("platform", ""),
timestamp=datetime.fromtimestamp(timestamp),
platform=platform,
)
message.message_info = MessageInfo(
user_info=MaiUserInfo(
user_id=user_info_dict.get("user_id", ""),
user_nickname=user_info_dict.get("user_nickname", ""),
user_cardname=user_info_dict.get("user_cardname"),
)
)
message.session_id = msg_dict.get("chat_id", "")
message.processed_plain_text = msg_dict.get("processed_plain_text", "")
message.display_message = msg_dict.get("display_message", "")
message.is_mentioned = msg_dict.get("is_mentioned", False)
message.is_command = msg_dict.get("is_command", False)
message.initialized = True
return message
class ObservationInfoHandler(NotificationHandler):
@@ -393,10 +405,10 @@ class ObservationInfo:
# 更新历史记录字符串 (只使用最近一部分生成，例如20条)
history_slice_for_str = self.chat_history[-20:]
try:
# Convert dict format to DatabaseMessages objects
db_messages = [dict_to_database_message(m) for m in history_slice_for_str]
# Convert dict format to SessionMessage objects.
session_messages = [dict_to_session_message(m) for m in history_slice_for_str]
self.chat_history_str = build_readable_messages(
db_messages,
session_messages,
replace_bot_name=True,
timestamp_mode="relative",
read_mark=0.0, # read_mark 可能需要根据逻辑调整

13
src/chat/brain_chat/PFC/pfc.py
View File

@@ -6,8 +6,9 @@ import random
from .chat_observer import ChatObserver
from .pfc_utils import get_items_from_json
from .conversation_info import ConversationInfo
from .observation_info import ObservationInfo, dict_to_database_message
from src.chat.utils.chat_message_builder import build_readable_messages
from src.services.message_service import build_readable_messages
from .observation_info import ObservationInfo, dict_to_session_message
from rich.traceback import install
install(extra_lines=3)
@@ -103,9 +104,9 @@ class GoalAnalyzer:
if observation_info.new_messages_count > 0:
new_messages_list = observation_info.unprocessed_messages
db_messages = [dict_to_database_message(m) for m in new_messages_list]
session_messages = [dict_to_session_message(m) for m in new_messages_list]
new_messages_str = build_readable_messages(
db_messages,
session_messages,
replace_bot_name=True,
timestamp_mode="relative",
read_mark=0.0,
@@ -238,9 +239,9 @@ class GoalAnalyzer:
async def analyze_conversation(self, goal, reasoning):
messages = self.chat_observer.get_cached_messages()
db_messages = [dict_to_database_message(m) for m in messages]
session_messages = [dict_to_session_message(m) for m in messages]
chat_history_text = build_readable_messages(
db_messages,
session_messages,
replace_bot_name=True,
timestamp_mode="relative",
read_mark=0.0,

11
src/chat/brain_chat/PFC/reply_generator.py
View File

@@ -5,9 +5,10 @@ from src.config.config import global_config, model_config
import random
from .chat_observer import ChatObserver
from .reply_checker import ReplyChecker
from .observation_info import ObservationInfo, dict_to_database_message
from src.services.message_service import build_readable_messages
from .observation_info import ObservationInfo, dict_to_session_message
from .conversation_info import ConversationInfo
from src.chat.utils.chat_message_builder import build_readable_messages
logger = get_logger("reply_generator")
@@ -163,7 +164,7 @@ class ReplyGenerator:
knowledge = knowledge_item.get("knowledge", "无知识内容")
source = knowledge_item.get("source", "未知来源")
# 只取知识内容的前 2000 个字
knowledge_snippet = knowledge[:2000] + "..." if len(knowledge) > 2000 else knowledge
knowledge_snippet = f"{knowledge[:2000]}..." if len(knowledge) > 2000 else knowledge
knowledge_info_str += (
f"{i + 1}. 关于 '{query}' (来源: {source}): {knowledge_snippet}\n" # 格式微调，更简洁
)
@@ -186,9 +187,9 @@ class ReplyGenerator:
chat_history_text = observation_info.chat_history_str
if observation_info.new_messages_count > 0 and observation_info.unprocessed_messages:
new_messages_list = observation_info.unprocessed_messages
db_messages = [dict_to_database_message(m) for m in new_messages_list]
session_messages = [dict_to_session_message(m) for m in new_messages_list]
new_messages_str = build_readable_messages(
db_messages,
session_messages,
replace_bot_name=True,
timestamp_mode="relative",
read_mark=0.0,

37
src/memory_system/chat_history_summarizer.py
View File

@@ -14,12 +14,11 @@ from typing import Any, Dict, List, Optional, Set
from dataclasses import dataclass, field
from json_repair import repair_json
from src.chat.message_receive.message import SessionMessage
from src.common.logger import get_logger
from src.common.data_models.database_data_model import DatabaseMessages
from src.config.config import model_config, global_config
from src.llm_models.utils_model import LLMRequest
from src.services import message_service as message_api
from src.chat.utils.chat_message_builder import build_readable_messages
from src.chat.utils.utils import is_bot_self
from src.person_info.person_info import Person
from src.chat.message_receive.chat_manager import chat_manager as _chat_manager
@@ -34,7 +33,7 @@ HIPPO_CACHE_DIR = Path(__file__).resolve().parents[2] / "data" / "hippo_memorize
class MessageBatch:
"""消息批次（用于触发话题检查的原始消息累积）"""
messages: List[DatabaseMessages]
messages: List[SessionMessage]
start_time: float
end_time: float
@@ -101,7 +100,7 @@ class ChatHistorySummarizer:
def _get_chat_display_name(self) -> str:
"""获取聊天显示名称"""
try:
chat_name = _chat_manager.get_session_name(self.chat_id)
chat_name = _chat_manager.get_session_name(self.session_id)
if chat_name:
return chat_name
# 如果获取失败，使用简化的chat_id显示
@@ -268,7 +267,7 @@ class ChatHistorySummarizer:
# 创建新批次
self.current_batch = MessageBatch(
messages=new_messages,
start_time=new_messages[0].time if new_messages else current_time,
start_time=new_messages[0].timestamp.timestamp() if new_messages else current_time,
end_time=current_time,
)
logger.debug(f"{self.log_prefix} 新建聊天检查批次: {len(new_messages)} 条消息")
@@ -340,7 +339,7 @@ class ChatHistorySummarizer:
self.last_topic_check_time = current_time
self._persist_topic_cache()
async def _run_topic_check_and_update_cache(self, messages: List[DatabaseMessages]):
async def _run_topic_check_and_update_cache(self, messages: List[SessionMessage]):
"""
执行一次“话题检查”：
1. 首先确认这段消息里是否有 Bot 发言，没有则直接丢弃本次批次；
@@ -355,8 +354,8 @@ class ChatHistorySummarizer:
if not messages:
return
start_time = messages[0].time
end_time = messages[-1].time
start_time = messages[0].timestamp.timestamp()
end_time = messages[-1].timestamp.timestamp()
logger.info(
f"{self.log_prefix} 开始话题检查 | 消息数: {len(messages)} | 时间范围: {start_time:.2f} - {end_time:.2f}"
@@ -365,13 +364,9 @@ class ChatHistorySummarizer:
# 1. 检查当前批次内是否有 bot 发言（只检查当前批次，不往前推）
# 原因：我们要记录的是 bot 参与过的对话片段，如果当前批次内 bot 没有发言，
# 说明 bot 没有参与这段对话，不应该记录
has_bot_message = False
for msg in messages:
# 使用统一的 is_bot_self 函数判断是否是机器人自己（支持多平台，包括 WebUI）
if is_bot_self(msg.user_info.platform, msg.user_info.user_id):
has_bot_message = True
break
has_bot_message = any(
is_bot_self(msg.platform, msg.message_info.user_info.user_id) for msg in messages
)
if not has_bot_message:
logger.info(
@@ -575,7 +570,7 @@ class ChatHistorySummarizer:
return topic_mapping
def _build_numbered_messages_for_llm(
self, messages: List[DatabaseMessages]
self, messages: List[SessionMessage]
) -> tuple[List[str], Dict[int, str], Dict[int, str], Dict[int, Set[str]]]:
"""
将消息转为带编号的字符串，供 LLM 选择使用。
@@ -594,7 +589,7 @@ class ChatHistorySummarizer:
for idx, msg in enumerate(messages, start=1):
# 使用 build_readable_messages 生成可读文本
try:
text = build_readable_messages(
text = message_api.build_readable_messages(
messages=[msg],
replace_bot_name=True,
timestamp_mode="normal_no_YMD",
@@ -609,12 +604,8 @@ class ChatHistorySummarizer:
# 获取发言人昵称
participants: Set[str] = set()
try:
platform = (
getattr(msg, "user_platform", None)
or (msg.user_info.platform if msg.user_info else None)
or msg.chat_info.platform
)
user_id = msg.user_info.user_id if msg.user_info else None
platform = msg.platform
user_id = msg.message_info.user_info.user_id
if platform and user_id:
person = Person(platform=platform, user_id=user_id)
if person.person_name: