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feat：添加来自困惑内容的主动提问发言

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This commit is contained in:
SengokuCola
2025-10-04 17:18:43 +08:00
parent eaf218ff15
commit 35c3fe5b10
16 changed files with 666 additions and 334 deletions
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4
src/chat/express/expression_learner.py
View File

@@ -451,7 +451,7 @@ class ExpressionLearner:
)
# print(f"random_msg_str:{random_msg_str}")
logger.info(f"学习{type_str}的prompt: {prompt}")
# logger.info(f"学习{type_str}的prompt: {prompt}")
try:
response, _ = await self.express_learn_model.generate_response_async(prompt, temperature=0.3)
@@ -459,7 +459,7 @@ class ExpressionLearner:
logger.error(f"学习{type_str}失败: {e}")
return None
logger.debug(f"学习{type_str}的response: {response}")
# logger.debug(f"学习{type_str}的response: {response}")
expressions: List[Tuple[str, str]] = self.parse_expression_response(response)

106
src/chat/heart_flow/heartFC_chat.py
View File

@@ -19,6 +19,8 @@ from src.chat.heart_flow.hfc_utils import CycleDetail
from src.chat.heart_flow.hfc_utils import send_typing, stop_typing
from src.chat.express.expression_learner import expression_learner_manager
from src.chat.frequency_control.frequency_control import frequency_control_manager
from src.memory_system.question_maker import QuestionMaker
from src.memory_system.questions import global_conflict_tracker
from src.person_info.person_info import Person
from src.plugin_system.base.component_types import EventType, ActionInfo
from src.plugin_system.core import events_manager
@@ -100,6 +102,8 @@ class HeartFChatting:
self.no_reply_until_call = False
self.is_mute = False
self.last_active_time = time.time() # 记录上一次非noreply时间
async def start(self):
@@ -176,6 +180,18 @@ class HeartFChatting:
filter_command=True,
)
force_reply = False
if time.time() - self.last_active_time > 1: #长久没有回复，可以试试主动发言
print(f"{self.log_prefix} 长久没有回复，可以试试主动发言")
if random.random() < 0.01: # 30%概率主动发言
print(f"{self.log_prefix} 长久没有回复，可以试试主动发言，开始生成问题")
cycle_timers, thinking_id = self.start_cycle()
question_maker = QuestionMaker(self.stream_id)
question, conflict_context = await question_maker.make_question()
await global_conflict_tracker.track_conflict(question, conflict_context, True, self.stream_id)
await self._lift_question_reply(question,cycle_timers,thinking_id)
if len(recent_messages_list) >= 1:
# for message in recent_messages_list:
# print(message.processed_plain_text)
@@ -509,6 +525,89 @@ class HeartFChatting:
traceback.print_exc()
return False, ""
async def _lift_question_reply(self, question: str, cycle_timers: Dict[str, float], thinking_id: str):
reason = f"你对问题\"{question}\"感到好奇，想要和群友讨论"
new_msg = get_raw_msg_before_timestamp_with_chat(
chat_id=self.stream_id,
timestamp=time.time(),
limit=1,
)
reply_action_info = ActionPlannerInfo(
action_type="reply",
reasoning= "",
action_data={},
action_message=new_msg[0],
available_actions=None,
loop_start_time=time.time(),
action_reasoning=reason)
self.action_planner.add_plan_log(reasoning=reason, actions=[reply_action_info])
await database_api.store_action_info(
chat_stream=self.chat_stream,
action_build_into_prompt=False,
action_prompt_display=reason,
action_done=True,
thinking_id=thinking_id,
action_data=reply_action_info.action_data,
action_name="reply",
action_reasoning=reason,
)
success, llm_response = await generator_api.rewrite_reply(
chat_stream=self.chat_stream,
reply_data={
"raw_reply": f"我对这个问题感到好奇：{question}",
"reason": reason,
},
)
if not success or not llm_response or not llm_response.reply_set:
logger.info("主动提问发言失败")
self.action_planner.add_plan_excute_log(result="主动回复生成失败")
return {"action_type": "reply", "success": False, "result": "主动回复生成失败", "loop_info": None}
if success:
for reply_seg in llm_response.reply_set.reply_data:
send_data = reply_seg.content
await send_api.text_to_stream(
text=send_data,
stream_id=self.stream_id,
)
await database_api.store_action_info(
chat_stream=self.chat_stream,
action_build_into_prompt=False,
action_prompt_display=reason,
action_done=True,
thinking_id=thinking_id,
action_data={"reply_text": llm_response.reply_set.reply_data[0].content},
action_name="reply",
)
# 构建循环信息
loop_info: Dict[str, Any] = {
"loop_plan_info": {
"action_result": [reply_action_info],
},
"loop_action_info": {
"action_taken": True,
"reply_text": llm_response.reply_set.reply_data[0].content,
"command": "",
"taken_time": time.time(),
},
}
self.last_active_time = time.time()
self.action_planner.add_plan_excute_log(result=f"你提问：{question}")
return {
"action_type": "reply",
"success": True,
"result": f"你提问：{question}",
"loop_info": loop_info,
}
async def _send_response(
self,
reply_set: "ReplySetModel",
@@ -519,7 +618,7 @@ class HeartFChatting:
chat_id=self.chat_stream.stream_id, start_time=self.last_read_time, end_time=time.time()
)
need_reply = new_message_count >= random.randint(2, 4)
need_reply = new_message_count >= random.randint(2, 3)
if need_reply:
logger.info(f"{self.log_prefix} 从思考到回复，共有{new_message_count}条新消息，使用引用回复")
@@ -600,8 +699,6 @@ class HeartFChatting:
action_name="no_reply_until_call",
action_reasoning=reason,
)
return {"action_type": "no_reply_until_call", "success": True, "result": "保持沉默，直到有人直接叫的名字", "command": ""}
elif action_planner_info.action_type == "reply":
@@ -650,6 +747,7 @@ class HeartFChatting:
actions=chosen_action_plan_infos,
selected_expressions=selected_expressions,
)
self.last_active_time = time.time()
return {
"action_type": "reply",
"success": True,
@@ -667,6 +765,8 @@ class HeartFChatting:
thinking_id = thinking_id,
action_message= action_planner_info.action_message,
)
self.last_active_time = time.time()
return {
"action_type": action_planner_info.action_type,
"success": success,

4
src/chat/planner_actions/planner.py
View File

@@ -469,8 +469,8 @@ class ActionPlanner:
# 调用LLM
llm_content, (reasoning_content, _, _) = await self.planner_llm.generate_response_async(prompt=prompt)
logger.info(f"{self.log_prefix}规划器原始提示词: {prompt}")
logger.info(f"{self.log_prefix}规划器原始响应: {llm_content}")
# logger.info(f"{self.log_prefix}规划器原始提示词: {prompt}")
# logger.info(f"{self.log_prefix}规划器原始响应: {llm_content}")
if global_config.debug.show_prompt:
logger.info(f"{self.log_prefix}规划器原始提示词: {prompt}")

21
src/chat/replyer/group_generator.py
View File

@@ -7,6 +7,7 @@ import re
from typing import List, Optional, Dict, Any, Tuple
from datetime import datetime
from src.memory_system.Memory_chest import global_memory_chest
from src.memory_system.questions import global_conflict_tracker
from src.common.logger import get_logger
from src.common.data_models.database_data_model import DatabaseMessages
from src.common.data_models.info_data_model import ActionPlannerInfo
@@ -277,6 +278,20 @@ class DefaultReplyer:
else:
return ""
async def build_question_block(self) -> str:
"""构建问题块"""
# if not global_config.question.enable_question:
# return ""
questions = global_conflict_tracker.get_questions_by_chat_id(self.chat_stream.stream_id)
questions_str = ""
for question in questions:
questions_str += f"- {question.question}\n"
if questions_str:
return f"你在聊天中，有以下问题想要得到解答：\n{questions_str}"
else:
return ""
async def build_tool_info(self, chat_history: str, sender: str, target: str, enable_tool: bool = True) -> str:
"""构建工具信息块
@@ -619,6 +634,7 @@ class DefaultReplyer:
self._time_and_run_task(self.build_actions_prompt(available_actions, chosen_actions), "actions_info"),
self._time_and_run_task(self.build_personality_prompt(), "personality_prompt"),
self._time_and_run_task(self.build_mood_state_prompt(), "mood_state_prompt"),
self._time_and_run_task(self.build_question_block(), "question_block"),
)
# 任务名称中英文映射
@@ -632,6 +648,7 @@ class DefaultReplyer:
"actions_info": "动作信息",
"personality_prompt": "人格信息",
"mood_state_prompt": "情绪状态",
"question_block": "问题",
}
# 处理结果
@@ -661,6 +678,7 @@ class DefaultReplyer:
prompt_info: str = results_dict["prompt_info"] # 直接使用格式化后的结果
actions_info: str = results_dict["actions_info"]
personality_prompt: str = results_dict["personality_prompt"]
question_block: str = results_dict["question_block"]
keywords_reaction_prompt = await self.build_keywords_reaction_prompt(target)
mood_state_prompt: str = results_dict["mood_state_prompt"]
@@ -704,6 +722,7 @@ class DefaultReplyer:
target=target,
reason=reply_reason,
reply_style=global_config.personality.reply_style,
question_block=question_block,
keywords_reaction_prompt=keywords_reaction_prompt,
moderation_prompt=moderation_prompt_block,
), selected_expressions
@@ -728,6 +747,7 @@ class DefaultReplyer:
reply_style=global_config.personality.reply_style,
keywords_reaction_prompt=keywords_reaction_prompt,
moderation_prompt=moderation_prompt_block,
question_block=question_block,
), selected_expressions
async def build_prompt_rewrite_context(
@@ -760,7 +780,6 @@ class DefaultReplyer:
# 并行执行2个构建任务
(expression_habits_block, _), personality_prompt = await asyncio.gather(
self.build_expression_habits(chat_talking_prompt_half, target),
# self.build_relation_info(chat_talking_prompt_half, sender, []),
self.build_personality_prompt(),
)

2
src/chat/replyer/private_generator.py
View File

@@ -288,7 +288,7 @@ class PrivateReplyer:
mood_state = await mood_manager.get_mood_by_chat_id(self.chat_stream.stream_id).get_mood()
return f"你现在的心情是：{mood_state}"
async def build_memory_block(self) -> str:
"""构建记忆块
"""

4
src/chat/replyer/prompt/replyer_prompt.py
View File

@@ -13,7 +13,7 @@ def init_replyer_prompt():
Prompt(
"""{knowledge_prompt}{tool_info_block}{extra_info_block}
{expression_habits_block}{memory_block}
{expression_habits_block}{memory_block}{question_block}
你正在qq群里聊天，下面是群里正在聊的内容:
{time_block}
@@ -34,7 +34,7 @@ def init_replyer_prompt():
Prompt(
"""{knowledge_prompt}{tool_info_block}{extra_info_block}
{expression_habits_block}{memory_block}
{expression_habits_block}{memory_block}{question_block}
你正在qq群里聊天，下面是群里正在聊的内容:
{time_block}