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feat：将action记录存到数据库，并显示到prompt中

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This commit is contained in:
SengokuCola
2025-06-04 18:14:16 +08:00
parent bb01a15468
commit 8c713a436c
16 changed files with 332 additions and 209 deletions
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5
src/chat/focus_chat/heartFC_chat.py
View File

@@ -35,6 +35,7 @@ from src.chat.focus_chat.planners.modify_actions import ActionModifier
from src.chat.focus_chat.planners.action_manager import ActionManager
from src.chat.focus_chat.working_memory.working_memory import WorkingMemory
from src.config.config import global_config
from src.common.database.database_model import ActionRecords
install(extra_lines=3)
@@ -552,6 +553,9 @@ class HeartFChatting:
tuple[bool, str, str]: (是否执行了动作, 思考消息ID, 命令)
"""
try:
action_time = time.time()
action_id = f"{action_time}_{thinking_id}"
# 使用工厂创建动作处理器实例
try:
action_handler = self.action_manager.create_action(
@@ -586,6 +590,7 @@ class HeartFChatting:
logger.debug(
f"{self.log_prefix} 麦麦执行了'{action}', 返回结果'{success}', '{reply_text}', '{command}'"
)
return success, reply_text, command
except Exception as e:

2
src/chat/focus_chat/memory_activator.py
View File

@@ -118,7 +118,7 @@ class MemoryActivator:
# 只取response的第一个元素（字符串）
response_str = response[0]
print(f"response_str: {response_str[1]}")
# print(f"response_str: {response_str[1]}")
keywords = list(get_keywords_from_json(response_str))
# 更新关键词缓存

38
src/chat/focus_chat/planners/actions/plugin_action.py
View File

@@ -11,6 +11,8 @@ from src.config.config import global_config
import os
import inspect
import toml # 导入 toml 库
from src.common.database.database_model import ActionRecords
import time
logger = get_logger("plugin_action")
@@ -391,3 +393,39 @@ class PluginAction(BaseAction):
Tuple[bool, str]: (是否执行成功, 回复文本)
"""
return await self.process()
async def store_action_info(self, action_build_into_prompt: bool = False, action_prompt_display: str = "", action_done: bool = True) -> None:
"""存储action执行信息到数据库
Args:
action_build_into_prompt: 是否构建到提示中
action_prompt_display: 动作显示内容
"""
try:
chat_stream = self._services.get("chat_stream")
if not chat_stream:
logger.error(f"{self.log_prefix} 无法存储action信息：缺少chat_stream服务")
return
action_time = time.time()
action_id = f"{action_time}_{self.thinking_id}"
ActionRecords.create(
action_id=action_id,
time=action_time,
action_name=self.__class__.__name__,
action_data=str(self.action_data),
action_done=action_done,
action_build_into_prompt=action_build_into_prompt,
action_prompt_display=action_prompt_display,
chat_id=chat_stream.stream_id,
chat_info_stream_id=chat_stream.stream_id,
chat_info_platform=chat_stream.platform,
user_id=chat_stream.user_info.user_id if chat_stream.user_info else "",
user_nickname=chat_stream.user_info.user_nickname if chat_stream.user_info else "",
user_cardname=chat_stream.user_info.user_cardname if chat_stream.user_info else ""
)
logger.debug(f"{self.log_prefix} 已存储action信息: {action_prompt_display}")
except Exception as e:
logger.error(f"{self.log_prefix} 存储action信息时出错: {e}")
traceback.print_exc()

49
src/chat/focus_chat/planners/actions/reply_action.py
View File

@@ -8,6 +8,9 @@ from src.chat.focus_chat.replyer.default_replyer import DefaultReplyer
from src.chat.message_receive.chat_stream import ChatStream
from src.chat.heart_flow.observation.chatting_observation import ChattingObservation
from src.chat.focus_chat.hfc_utils import create_empty_anchor_message
import time
import traceback
from src.common.database.database_model import ActionRecords
logger = get_logger("action_taken")
@@ -72,12 +75,19 @@ class ReplyAction(BaseAction):
Tuple[bool, str]: (是否执行成功, 回复文本)
"""
# 注意: 此处可能会使用不同的expressor实现根据任务类型切换不同的回复策略
return await self._handle_reply(
success, reply_text = await self._handle_reply(
reasoning=self.reasoning,
reply_data=self.action_data,
cycle_timers=self.cycle_timers,
thinking_id=self.thinking_id,
)
await self.store_action_info(
action_build_into_prompt=False,
action_prompt_display=f"{reply_text}",
)
return success, reply_text
async def _handle_reply(
self, reasoning: str, reply_data: dict, cycle_timers: dict, thinking_id: str
@@ -130,3 +140,40 @@ class ReplyAction(BaseAction):
reply_text += data
return success, reply_text
async def store_action_info(self, action_build_into_prompt: bool = False, action_prompt_display: str = "", action_done: bool = True) -> None:
"""存储action执行信息到数据库
Args:
action_build_into_prompt: 是否构建到提示中
action_prompt_display: 动作显示内容
"""
try:
chat_stream = self.chat_stream
if not chat_stream:
logger.error(f"{self.log_prefix} 无法存储action信息：缺少chat_stream服务")
return
action_time = time.time()
action_id = f"{action_time}_{self.thinking_id}"
ActionRecords.create(
action_id=action_id,
time=action_time,
action_name=self.__class__.__name__,
action_data=str(self.action_data),
action_done=action_done,
action_build_into_prompt=action_build_into_prompt,
action_prompt_display=action_prompt_display,
chat_id=chat_stream.stream_id,
chat_info_stream_id=chat_stream.stream_id,
chat_info_platform=chat_stream.platform,
user_id=chat_stream.user_info.user_id if chat_stream.user_info else "",
user_nickname=chat_stream.user_info.user_nickname if chat_stream.user_info else "",
user_cardname=chat_stream.user_info.user_cardname if chat_stream.user_info else ""
)
logger.debug(f"{self.log_prefix} 已存储action信息: {action_prompt_display}")
except Exception as e:
logger.error(f"{self.log_prefix} 存储action信息时出错: {e}")
traceback.print_exc()

141
src/chat/focus_chat/planners/actions/reply_complex_action.py
View File

@@ -1,141 +0,0 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
from src.common.logger_manager import get_logger
from src.chat.focus_chat.planners.actions.base_action import BaseAction, register_action
from typing import Tuple, List
from src.chat.heart_flow.observation.observation import Observation
from chat.focus_chat.replyer.default_expressor import DefaultExpressor
from src.chat.message_receive.chat_stream import ChatStream
from src.chat.heart_flow.observation.chatting_observation import ChattingObservation
from src.chat.focus_chat.hfc_utils import create_empty_anchor_message
from src.config.config import global_config
logger = get_logger("action_taken")
@register_action
class ReplyAction(BaseAction):
"""回复动作处理类
处理构建和发送消息回复的动作。
"""
action_name: str = "reply"
action_description: str = "表达想法，可以只包含文本、表情或两者都有"
action_parameters: dict[str:str] = {
"text": "你想要表达的内容（可选）",
"emojis": "描述当前使用表情包的场景，一段话描述（可选）",
"target": "你想要回复的原始文本内容（非必须，仅文本，不包含发送者)（可选）",
}
action_require: list[str] = [
"有实质性内容需要表达",
"有人提到你，但你还没有回应他",
"在合适的时候添加表情（不要总是添加），表情描述要详细，描述当前场景，一段话描述",
"如果你有明确的,要回复特定某人的某句话，或者你想回复较早的消息，请在target中指定那句话的原始文本",
"一次只回复一个人，一次只回复一个话题,突出重点",
"如果是自己发的消息想继续，需自然衔接",
"避免重复或评价自己的发言,不要和自己聊天",
f"注意你的回复要求：{global_config.expression.expression_style}",
]
associated_types: list[str] = ["text", "emoji"]
default = True
def __init__(
self,
action_data: dict,
reasoning: str,
cycle_timers: dict,
thinking_id: str,
observations: List[Observation],
expressor: DefaultExpressor,
chat_stream: ChatStream,
log_prefix: str,
**kwargs,
):
"""初始化回复动作处理器
Args:
action_name: 动作名称
action_data: 动作数据，包含 message, emojis, target 等
reasoning: 执行该动作的理由
cycle_timers: 计时器字典
thinking_id: 思考ID
observations: 观察列表
expressor: 表达器
chat_stream: 聊天流
log_prefix: 日志前缀
"""
super().__init__(action_data, reasoning, cycle_timers, thinking_id)
self.observations = observations
self.expressor = expressor
self.chat_stream = chat_stream
self.log_prefix = log_prefix
async def handle_action(self) -> Tuple[bool, str]:
"""
处理回复动作
Returns:
Tuple[bool, str]: (是否执行成功, 回复文本)
"""
# 注意: 此处可能会使用不同的expressor实现根据任务类型切换不同的回复策略
return await self._handle_reply(
reasoning=self.reasoning,
reply_data=self.action_data,
cycle_timers=self.cycle_timers,
thinking_id=self.thinking_id,
)
async def _handle_reply(
self, reasoning: str, reply_data: dict, cycle_timers: dict, thinking_id: str
) -> tuple[bool, str]:
"""
处理统一的回复动作 - 可包含文本和表情，顺序任意
reply_data格式:
{
"text": "你好啊" # 文本内容列表（可选）
"target": "锚定消息", # 锚定消息的文本内容
"emojis": "微笑" # 表情关键词列表（可选）
}
"""
logger.info(f"{self.log_prefix} 决定回复: {self.reasoning}")
# 从聊天观察获取锚定消息
chatting_observation: ChattingObservation = next(
obs for obs in self.observations if isinstance(obs, ChattingObservation)
)
if reply_data.get("target"):
anchor_message = chatting_observation.search_message_by_text(reply_data["target"])
else:
anchor_message = None
# 如果没有找到锚点消息，创建一个占位符
if not anchor_message:
logger.info(f"{self.log_prefix} 未找到锚点消息，创建占位符")
anchor_message = await create_empty_anchor_message(
self.chat_stream.platform, self.chat_stream.group_info, self.chat_stream
)
else:
anchor_message.update_chat_stream(self.chat_stream)
success, reply_set = await self.expressor.deal_reply(
cycle_timers=cycle_timers,
action_data=reply_data,
anchor_message=anchor_message,
reasoning=reasoning,
thinking_id=thinking_id,
)
reply_text = ""
for reply in reply_set:
type = reply[0]
data = reply[1]
if type == "text":
reply_text += data
elif type == "emoji":
reply_text += data
return success, reply_text

14
src/chat/focus_chat/planners/planner_simple.py
View File

@@ -43,8 +43,6 @@ def init_prompt():
{chat_content_block}
{mind_info_block}
{cycle_info_block}
{moderation_prompt}
@@ -323,11 +321,11 @@ class ActionPlanner(BasePlanner):
else:
chat_content_block = "你还未开始聊天"
mind_info_block = ""
if current_mind:
mind_info_block = f"对聊天的规划：{current_mind}"
else:
mind_info_block = "你刚参与聊天"
# mind_info_block = ""
# if current_mind:
# mind_info_block = f"对聊天的规划：{current_mind}"
# else:
# mind_info_block = "你刚参与聊天"
personality_block = individuality.get_prompt(x_person=2, level=2)
@@ -388,7 +386,7 @@ class ActionPlanner(BasePlanner):
prompt_personality=personality_block,
chat_context_description=chat_context_description,
chat_content_block=chat_content_block,
mind_info_block=mind_info_block,
# mind_info_block=mind_info_block,
cycle_info_block=cycle_info,
action_options_text=action_options_block,
# action_available_block=action_available_block,

1
src/chat/focus_chat/replyer/default_replyer.py
View File

@@ -350,6 +350,7 @@ class DefaultReplyer:
timestamp_mode="normal_no_YMD",
read_mark=0.0,
truncate=True,
show_actions=True,
)
(