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typing fix

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This commit is contained in:
UnCLAS-Prommer
2025-07-25 19:56:01 +08:00
parent 28e004bbb0
commit 29229d9a36
4 changed files with 98 additions and 97 deletions
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73
src/chat/replyer/default_generator.py
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@@ -17,7 +17,11 @@ from src.chat.message_receive.uni_message_sender import HeartFCSender
from src.chat.utils.timer_calculator import Timer # <--- 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 build_readable_messages, get_raw_msg_before_timestamp_with_chat, replace_user_references_in_content
from src.chat.utils.chat_message_builder import (
build_readable_messages,
get_raw_msg_before_timestamp_with_chat,
replace_user_references_sync,
)
from src.chat.express.expression_selector import expression_selector
from src.chat.knowledge.knowledge_lib import qa_manager
from src.chat.memory_system.memory_activator import MemoryActivator
@@ -30,6 +34,7 @@ from src.plugin_system.base.component_types import ActionInfo
logger = get_logger("replyer")
def init_prompt():
Prompt("你正在qq群里聊天，下面是群里在聊的内容：", "chat_target_group1")
Prompt("你正在和{sender_name}聊天，这是你们之前聊的内容：", "chat_target_private1")
@@ -356,17 +361,20 @@ class DefaultReplyer:
expression_habits_block = ""
expression_habits_title = ""
if style_habits_str.strip():
expression_habits_title = "你可以参考以下的语言习惯，当情景合适就使用，但不要生硬使用，以合理的方式结合到你的回复中："
expression_habits_title = (
"你可以参考以下的语言习惯，当情景合适就使用，但不要生硬使用，以合理的方式结合到你的回复中："
)
expression_habits_block += f"{style_habits_str}\n"
if grammar_habits_str.strip():
expression_habits_title = "你可以选择下面的句法进行回复，如果情景合适就使用，不要盲目使用,不要生硬使用，以合理的方式使用："
expression_habits_title = (
"你可以选择下面的句法进行回复，如果情景合适就使用，不要盲目使用,不要生硬使用，以合理的方式使用："
)
expression_habits_block += f"{grammar_habits_str}\n"
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："
expression_habits_block = f"{expression_habits_title}\n{expression_habits_block}"
return expression_habits_block
@@ -375,27 +383,27 @@ class DefaultReplyer:
return ""
instant_memory = None
running_memories = await self.memory_activator.activate_memory_with_chat_history(
target_message=target, chat_history_prompt=chat_history
)
if global_config.memory.enable_instant_memory:
asyncio.create_task(self.instant_memory.create_and_store_memory(chat_history))
instant_memory = await self.instant_memory.get_memory(target)
logger.info(f"即时记忆：{instant_memory}")
if not running_memories:
return ""
memory_str = "以下是当前在聊天中，你回忆起的记忆：\n"
for running_memory in running_memories:
memory_str += f"- {running_memory['content']}\n"
if instant_memory:
memory_str += f"- {instant_memory}\n"
return memory_str
async def build_tool_info(self, chat_history, reply_data: Optional[Dict], enable_tool: bool = True):
@@ -438,7 +446,7 @@ class DefaultReplyer:
tool_info_str += "以上是你获取到的实时信息，请在回复时参考这些信息。"
logger.info(f"获取到 {len(tool_results)} 个工具结果")
return tool_info_str
else:
logger.debug("未获取到任何工具结果")
@@ -469,7 +477,7 @@ class DefaultReplyer:
# 添加None检查，防止NoneType错误
if target is None:
return keywords_reaction_prompt
# 处理关键词规则
for rule in global_config.keyword_reaction.keyword_rules:
if any(keyword in target for keyword in rule.keywords):
@@ -621,7 +629,7 @@ class DefaultReplyer:
is_group_chat = bool(chat_stream.group_info)
reply_to = reply_data.get("reply_to", "none")
extra_info_block = reply_data.get("extra_info", "") or reply_data.get("extra_info_block", "")
if global_config.mood.enable_mood:
chat_mood = mood_manager.get_mood_by_chat_id(chat_id)
mood_prompt = chat_mood.mood_state
@@ -629,14 +637,8 @@ class DefaultReplyer:
mood_prompt = ""
sender, target = self._parse_reply_target(reply_to)
target = replace_user_references_in_content(
target,
chat_stream.platform,
is_async=False,
replace_bot_name=True
)
target = replace_user_references_sync(target, chat_stream.platform, replace_bot_name=True)
# 构建action描述 (如果启用planner)
action_descriptions = ""
@@ -687,25 +689,21 @@ class DefaultReplyer:
self._time_and_run_task(
self.build_expression_habits(chat_talking_prompt_short, target), "expression_habits"
),
self._time_and_run_task(
self.build_relation_info(reply_data), "relation_info"
),
self._time_and_run_task(self.build_relation_info(reply_data), "relation_info"),
self._time_and_run_task(self.build_memory_block(chat_talking_prompt_short, target), "memory_block"),
self._time_and_run_task(
self.build_tool_info(chat_talking_prompt_short, reply_data, enable_tool=enable_tool), "tool_info"
),
self._time_and_run_task(
get_prompt_info(target, threshold=0.38), "prompt_info"
),
self._time_and_run_task(get_prompt_info(target, threshold=0.38), "prompt_info"),
)
# 任务名称中英文映射
task_name_mapping = {
"expression_habits": "选取表达方式",
"relation_info": "感受关系",
"relation_info": "感受关系",
"memory_block": "回忆",
"tool_info": "使用工具",
"prompt_info": "获取知识"
"prompt_info": "获取知识",
}
# 处理结果
@@ -798,7 +796,7 @@ class DefaultReplyer:
core_dialogue_prompt, background_dialogue_prompt = self.build_s4u_chat_history_prompts(
message_list_before_now_long, target_user_id
)
self.build_mai_think_context(
chat_id=chat_id,
memory_block=memory_block,
@@ -815,9 +813,8 @@ class DefaultReplyer:
--------------------------------
{time_block}
这是你和{sender}的对话，你们正在交流中：
{core_dialogue_prompt}"""
{core_dialogue_prompt}""",
)
# 使用 s4u 风格的模板
template_name = "s4u_style_prompt"
@@ -855,9 +852,9 @@ class DefaultReplyer:
identity_block=identity_block,
sender=sender,
target=target,
chat_info=chat_talking_prompt
chat_info=chat_talking_prompt,
)
# 使用原有的模式
return await global_prompt_manager.format_prompt(
template_name,
@@ -1079,9 +1076,11 @@ async def get_prompt_info(message: str, threshold: float):
related_info += found_knowledge_from_lpmm
logger.debug(f"获取知识库内容耗时: {(end_time - start_time):.3f}秒")
logger.debug(f"获取知识库内容，相关信息：{related_info[:100]}...，信息长度: {len(related_info)}")
# 格式化知识信息
formatted_prompt_info = await global_prompt_manager.format_prompt("knowledge_prompt", prompt_info=related_info)
formatted_prompt_info = await global_prompt_manager.format_prompt(
"knowledge_prompt", prompt_info=related_info
)
return formatted_prompt_info
else:
logger.debug("从LPMM知识库获取知识失败，可能是从未导入过知识，返回空知识...")