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Refactor chat stream handling to use BotChatSession

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- Updated imports and references from ChatStream to BotChatSession across multiple files.
- Adjusted method signatures and internal logic to accommodate the new session management.
- Ensured compatibility with existing functionality while improving code clarity and maintainability.
This commit is contained in:
DrSmoothl
2026-03-07 00:57:33 +08:00
parent 8712fc0d05
commit 2e3dd44ee9
43 changed files with 706 additions and 563 deletions
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40
src/chat/replyer/private_generator.py
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@@ -12,8 +12,11 @@ from src.common.data_models.info_data_model import ActionPlannerInfo
from src.common.data_models.llm_data_model import LLMGenerationDataModel
from src.config.config import global_config, model_config
from src.llm_models.utils_model import LLMRequest
from src.chat.message_receive.message import UserInfo, Seg, MessageRecv, MessageSending
from src.chat.message_receive.chat_stream import ChatStream
from maim_message import Seg
from src.common.data_models.mai_message_data_model import MaiMessage, UserInfo
from src.chat.message_receive.message import MessageSending
from src.chat.message_receive.chat_manager import BotChatSession
from src.chat.message_receive.uni_message_sender import UniversalMessageSender
from src.chat.utils.timer_calculator import Timer
from src.chat.utils.utils import get_chat_type_and_target_info, is_bot_self
@@ -43,18 +46,18 @@ logger = get_logger("replyer")
class PrivateReplyer:
def __init__(
self,
chat_stream: ChatStream,
chat_stream: BotChatSession,
request_type: str = "replyer",
):
self.express_model = LLMRequest(model_set=model_config.model_task_config.replyer, request_type=request_type)
self.chat_stream = chat_stream
self.is_group_chat, self.chat_target_info = get_chat_type_and_target_info(self.chat_stream.stream_id)
self.is_group_chat, self.chat_target_info = get_chat_type_and_target_info(self.chat_stream.session_id)
self.heart_fc_sender = UniversalMessageSender()
# self.memory_activator = MemoryActivator()
from src.plugin_system.core.tool_use import ToolExecutor # 延迟导入ToolExecutor，不然会循环依赖
self.tool_executor = ToolExecutor(chat_id=self.chat_stream.stream_id, enable_cache=True, cache_ttl=3)
self.tool_executor = ToolExecutor(chat_id=self.chat_stream.session_id, enable_cache=True, cache_ttl=3)
async def generate_reply_with_context(
self,
@@ -253,14 +256,14 @@ class PrivateReplyer:
str: 表达习惯信息字符串
"""
# 检查是否允许在此聊天流中使用表达
use_expression, _, _ = TempMethodsExpression.get_expression_config_for_chat(self.chat_stream.stream_id)
use_expression, _, _ = TempMethodsExpression.get_expression_config_for_chat(self.chat_stream.session_id)
if not use_expression:
return "", []
style_habits = []
# 使用从处理器传来的选中表达方式
# 使用模型预测选择表达方式
selected_expressions, selected_ids = await expression_selector.select_suitable_expressions(
self.chat_stream.stream_id, chat_history, max_num=8, target_message=target, reply_reason=reply_reason
self.chat_stream.session_id, chat_history, max_num=8, target_message=target, reply_reason=reply_reason
)
if selected_expressions:
@@ -550,10 +553,11 @@ class PrivateReplyer:
# 判断是否为群聊
is_group = stream_type == "group"
# 使用 ChatManager 提供的接口生成 chat_id，避免在此重复实现逻辑
from src.chat.message_receive.chat_stream import get_chat_manager
from src.common.utils.utils_session import SessionUtils
chat_id = get_chat_manager().get_stream_id(platform, str(id_str), is_group=is_group)
chat_id = SessionUtils.calculate_session_id(
platform, group_id=str(id_str) if is_group else None, user_id=str(id_str) if not is_group else None
)
return chat_id, prompt_content
except (ValueError, IndexError):
@@ -624,7 +628,7 @@ class PrivateReplyer:
if available_actions is None:
available_actions = {}
chat_stream = self.chat_stream
chat_id = chat_stream.stream_id
chat_id = chat_stream.session_id
platform = chat_stream.platform
user_id = "用户ID"
@@ -843,7 +847,7 @@ class PrivateReplyer:
reply_to: str,
) -> str: # sourcery skip: merge-else-if-into-elif, remove-redundant-if
chat_stream = self.chat_stream
chat_id = chat_stream.stream_id
chat_id = chat_stream.session_id
sender, target = self._parse_reply_target(reply_to)
target = replace_user_references(target, chat_stream.platform, replace_bot_name=True)
@@ -948,29 +952,27 @@ class PrivateReplyer:
is_emoji: bool,
thinking_start_time: float,
display_message: str,
anchor_message: Optional[MessageRecv] = None,
anchor_message: Optional[MaiMessage] = None,
) -> MessageSending:
"""构建单个发送消息"""
bot_user_info = UserInfo(
user_id=str(global_config.bot.qq_account),
user_nickname=global_config.bot.nickname,
platform=self.chat_stream.platform,
)
# await anchor_message.process()
sender_info = anchor_message.message_info.user_info if anchor_message else None
return MessageSending(
message_id=message_id, # 使用片段的唯一ID
chat_stream=self.chat_stream,
message_id=message_id,
session=self.chat_stream,
bot_user_info=bot_user_info,
sender_info=sender_info,
message_segment=message_segment,
reply=anchor_message, # 回复原始锚点
reply=anchor_message,
is_head=reply_to,
is_emoji=is_emoji,
thinking_start_time=thinking_start_time, # 传递原始思考开始时间
thinking_start_time=thinking_start_time,
display_message=display_message,
)