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refactor(chat): 重构SmartPrompt系统简化架构并移除缓存机制

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- 简化SmartPromptParameters类结构，移除复杂的分层参数架构
- 统一错误处理和降级机制，增强系统稳定性
- 移除缓存相关功能，简化架构并减少复杂性
- 完全继承DefaultReplyer功能，确保功能完整性
- 优化性能和依赖管理，改进并发任务处理
- 增强跨群上下文、关系信息、记忆系统等功能的错误处理
- 统一视频分析结果注入逻辑，避免重复代码
This commit is contained in:
Windpicker-owo
2025-08-31 19:09:36 +08:00
parent e8e401f656
commit 649a010078
4 changed files with 809 additions and 788 deletions
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150
src/chat/replyer/default_generator.py
View File

@@ -1,3 +1,8 @@
"""
默认回复生成器 - 集成SmartPrompt系统
使用重构后的SmartPrompt系统替换原有的复杂提示词构建逻辑
移除缓存机制，简化架构
"""
import traceback
import time
import asyncio
@@ -15,7 +20,7 @@ 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, get_chat_manager
from src.chat.message_receive.uni_message_sender import HeartFCSender
from src.chat.utils.timer_calculator import Timer # <--- Import Timer
from src.chat.utils.timer_calculator import Timer
from src.chat.utils.utils import get_chat_type_and_target_info
from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
from src.chat.utils.chat_message_builder import (
@@ -207,88 +212,6 @@ class DefaultReplyer:
self.tool_executor = ToolExecutor(chat_id=self.chat_stream.stream_id)
async def _build_cross_context_block(self, current_chat_id: str, target_user_info: Optional[Dict[str, Any]]) -> str:
"""构建跨群聊上下文"""
if not global_config.cross_context.enable:
return ""
# 找到当前群聊所在的共享组
target_group = None
current_stream = get_chat_manager().get_stream(current_chat_id)
if not current_stream or not current_stream.group_info:
return ""
current_chat_raw_id = current_stream.group_info.group_id
for group in global_config.cross_context.groups:
if str(current_chat_raw_id) in group.chat_ids:
target_group = group
break
if not target_group:
return ""
# 根据prompt_mode选择策略
prompt_mode = global_config.personality.prompt_mode
other_chat_raw_ids = [chat_id for chat_id in target_group.chat_ids if chat_id != str(current_chat_raw_id)]
cross_context_messages = []
if prompt_mode == "normal":
# normal模式：获取其他群聊的最近N条消息
for chat_raw_id in other_chat_raw_ids:
stream_id = get_chat_manager().get_stream_id(current_stream.platform, chat_raw_id, is_group=True)
if not stream_id:
continue
messages = get_raw_msg_before_timestamp_with_chat(
chat_id=stream_id,
timestamp=time.time(),
limit=5, # 可配置
)
if messages:
chat_name = get_chat_manager().get_stream_name(stream_id) or stream_id
formatted_messages, _ = build_readable_messages_with_id(messages, timestamp_mode="relative")
cross_context_messages.append(f"[以下是来自“{chat_name}”的近期消息]\n{formatted_messages}")
elif prompt_mode == "s4u":
# s4u模式：获取当前发言用户在其他群聊的消息
if target_user_info:
user_id = target_user_info.get("user_id")
if user_id:
for chat_raw_id in other_chat_raw_ids:
stream_id = get_chat_manager().get_stream_id(
current_stream.platform, chat_raw_id, is_group=True
)
if not stream_id:
continue
messages = get_raw_msg_before_timestamp_with_chat(
chat_id=stream_id,
timestamp=time.time(),
limit=20, # 获取更多消息以供筛选
)
user_messages = [msg for msg in messages if msg.get("user_id") == user_id][
-5:
] # 筛选并取最近5条
if user_messages:
chat_name = get_chat_manager().get_stream_name(stream_id) or stream_id
user_name = (
target_user_info.get("person_name") or target_user_info.get("user_nickname") or user_id
)
formatted_messages, _ = build_readable_messages_with_id(
user_messages, timestamp_mode="relative"
)
cross_context_messages.append(
f"[以下是“{user_name}”在“{chat_name}”的近期发言]\n{formatted_messages}"
)
if not cross_context_messages:
return ""
return "# 跨群上下文参考\n" + "\n\n".join(cross_context_messages) + "\n"
def _select_weighted_models_config(self) -> Tuple[TaskConfig, float]:
"""使用加权随机选择来挑选一个模型配置"""
configs = self.model_set
@@ -437,19 +360,7 @@ class DefaultReplyer:
traceback.print_exc()
return False, None, prompt if return_prompt else None
async def build_relation_info(self, sender: str, target: str):
if not global_config.relationship.enable_relationship:
return ""
# 获取用户ID
person = Person(person_name = sender)
if not is_person_known(person_name=sender):
logger.warning(f"未找到用户 {sender} 的ID，跳过信息提取")
return f"你完全不认识{sender}，不理解ta的相关信息。"
return person.build_relationship(points_num=5)
async def build_expression_habits(self, chat_history: str, target: str) -> Tuple[str, List[int]]:
async def build_expression_habits(self, chat_history: str, target: str) -> str:
"""构建表达习惯块
Args:
@@ -490,7 +401,8 @@ class DefaultReplyer:
)
expression_habits_block += f"{style_habits_str}\n"
return f"{expression_habits_title}\n{expression_habits_block}", selected_ids
if style_habits_str.strip() and grammar_habits_str.strip():
expression_habits_title = "你可以参考以下的语言习惯和句法，如果情景合适就使用，不要盲目使用,不要生硬使用，以合理的方式结合到你的回复中。"
async def build_memory_block(self, chat_history: List[Dict[str, Any]], target: str) -> str:
"""构建记忆块
@@ -863,7 +775,7 @@ class DefaultReplyer:
reply_message: Optional[Dict[str, Any]] = None,
) -> Tuple[str, List[int]]:
"""
构建回复器上下文
构建回复器上下文 - 使用重构后的SmartPrompt系统，移除缓存机制
Args:
extra_info: 额外信息，用于补充上下文
@@ -946,7 +858,7 @@ class DefaultReplyer:
),
self._time_and_run_task(self.get_prompt_info(chat_talking_prompt_short, reply_to), "prompt_info"),
self._time_and_run_task(
PromptUtils.build_cross_context_block(chat_id, target_user_info, current_prompt_mode), "cross_context"
PromptUtils.build_cross_context(chat_id, target_user_info, global_config.personality.prompt_mode), "cross_context"
),
)
@@ -978,11 +890,6 @@ class DefaultReplyer:
prompt_info = results_dict["prompt_info"]
cross_context_block = results_dict["cross_context"]
# 检查是否为视频分析结果，并注入引导语
if target and ("[视频内容]" in target or "好的，我将根据您提供的" in target):
video_prompt_injection = "\n请注意，以上内容是你刚刚观看的视频，请以第一人称分享你的观后感，而不是在分析一份报告。"
memory_block += video_prompt_injection
# 检查是否为视频分析结果，并注入引导语
if target and ("[视频内容]" in target or "好的，我将根据您提供的" in target):
video_prompt_injection = "\n请注意，以上内容是你刚刚观看的视频，请以第一人称分享你的观后感，而不是在分析一份报告。"
@@ -1022,6 +929,7 @@ class DefaultReplyer:
# 根据配置选择模板
current_prompt_mode = global_config.personality.prompt_mode
# 使用重构后的SmartPrompt系统，移除缓存相关参数
prompt_params = SmartPromptParameters(
chat_id=chat_id,
is_group_chat=is_group_chat,
@@ -1032,17 +940,17 @@ class DefaultReplyer:
available_actions=available_actions,
enable_tool=enable_tool,
chat_target_info=self.chat_target_info,
current_prompt_mode=current_prompt_mode,
prompt_mode=current_prompt_mode,
message_list_before_now_long=message_list_before_now_long,
message_list_before_short=message_list_before_short,
chat_talking_prompt_short=chat_talking_prompt_short,
target_user_info=target_user_info,
# 传递已构建的参数
expression_habits_block=expression_habits_block,
relation_info=relation_info,
relation_info_block=relation_info,
memory_block=memory_block,
tool_info=tool_info,
prompt_info=prompt_info,
tool_info_block=tool_info,
knowledge_prompt=prompt_info,
cross_context_block=cross_context_block,
keywords_reaction_prompt=keywords_reaction_prompt,
extra_info_block=extra_info_block,
@@ -1162,7 +1070,7 @@ class DefaultReplyer:
template_name = "default_expressor_prompt"
# 使用重构后的SmartPrompt系统 - Expressor模式
# 使用重构后的SmartPrompt系统 - Expressor模式，移除缓存相关参数
prompt_params = SmartPromptParameters(
chat_id=chat_id,
is_group_chat=is_group_chat,
@@ -1170,7 +1078,7 @@ class DefaultReplyer:
target=raw_reply, # Expressor模式使用raw_reply作为target
reply_to=f"{sender}:{target}" if sender and target else reply_to,
extra_info="", # Expressor模式不需要额外信息
current_prompt_mode="minimal", # Expressor使用minimal模式
prompt_mode="minimal", # Expressor使用minimal模式
chat_talking_prompt_short=chat_talking_prompt_half,
time_block=time_block,
identity_block=identity_block,
@@ -1180,7 +1088,7 @@ class DefaultReplyer:
moderation_prompt_block=moderation_prompt_block,
# 添加已构建的表达习惯和关系信息
expression_habits_block=expression_habits_block,
relation_info=relation_info,
relation_info_block=relation_info,
)
smart_prompt = SmartPrompt(parameters=prompt_params)
@@ -1289,6 +1197,26 @@ class DefaultReplyer:
logger.error(f"获取知识库内容时发生异常: {str(e)}")
return ""
async def build_relation_info(self, reply_to: str = ""):
if not global_config.relationship.enable_relationship:
return ""
relationship_fetcher = relationship_fetcher_manager.get_fetcher(self.chat_stream.stream_id)
if not reply_to:
return ""
sender, text = self._parse_reply_target(reply_to)
if not sender or not text:
return ""
# 获取用户ID
person_info_manager = get_person_info_manager()
person_id = person_info_manager.get_person_id_by_person_name(sender)
if not person_id:
logger.warning(f"未找到用户 {sender} 的ID，跳过信息提取")
return f"你完全不认识{sender}，不理解ta的相关信息。"
return await relationship_fetcher.build_relation_info(person_id, points_num=5)
def weighted_sample_no_replacement(items, weights, k) -> list:
"""