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feat(planner): 引入双模动作激活机制与混合触发类型

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为了更精细地控制动作在不同聊天模式下的行为，并提升决策效率，本次更新引入了全新的动作激活机制。

- **双模激活**: 为 Action 新增 `normal_activation_type` 和 `focus_activation_type` 属性，允许插件在 `NORMAL` 和 `FOCUS` 模式下拥有不同的激活策略，使行为更符合上下文。

- **混合触发**: 新增 `KEYWORD_OR_LLM_JUDGE` 激活类型。该类型会先进行快速的关键词匹配，若未匹配成功，则回退至 LLM 进行判断，兼顾了响应速度和智能化。

- **流程优化**: 重构了 `PlanGenerator` 的动作筛选逻辑，使其在生成计划前，就根据当前聊天模式和简单的激活规则进行预筛选，为后续的 LLM 决策提供更精准、更高效的候选动作列表。
This commit is contained in:
tt-P607
2025-09-17 20:27:19 +08:00
committed by Windpicker-owo
parent c64a1f8ea5
commit 4890771a87
5 changed files with 60 additions and 54 deletions
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12
src/chat/chat_loop/cycle_processor.py
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@@ -135,6 +135,16 @@ class CycleProcessor:
action_type = "no_action"
reply_text = "" # 初始化reply_text变量，避免UnboundLocalError
# 开始新的思考循环
cycle_timers, thinking_id = self.cycle_tracker.start_cycle()
logger.info(f"{self.log_prefix} 开始第{self.context.cycle_counter}次思考")
if ENABLE_S4U and self.context.chat_stream and self.context.chat_stream.user_info:
await send_typing(self.context.chat_stream.user_info.user_id)
loop_start_time = time.time()
# 使用sigmoid函数将interest_value转换为概率
# 当interest_value为0时，概率接近0（使用Focus模式）
# 当interest_value很高时，概率接近1（使用Normal模式）
@@ -188,7 +198,7 @@ class CycleProcessor:
# 第一步：动作修改
with Timer("动作修改", cycle_timers):
try:
await self.action_modifier.modify_actions()
await self.action_modifier.modify_actions(mode=mode)
available_actions = self.context.action_manager.get_using_actions()
except Exception as e:
logger.error(f"{self.context.log_prefix} 动作修改失败: {e}")

41
src/chat/planner_actions/action_modifier.py
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@@ -10,7 +10,7 @@ from src.llm_models.utils_model import LLMRequest
from src.chat.message_receive.chat_stream import get_chat_manager, ChatMessageContext
from src.chat.planner_actions.action_manager import ActionManager
from src.chat.utils.chat_message_builder import get_raw_msg_before_timestamp_with_chat, build_readable_messages
from src.plugin_system.base.component_types import ActionInfo, ActionActivationType
from src.plugin_system.base.component_types import ActionInfo, ActionActivationType, ChatMode
from src.plugin_system.core.global_announcement_manager import global_announcement_manager
if TYPE_CHECKING:
@@ -43,10 +43,7 @@ class ActionModifier:
self._cache_expiry_time = 30 # 缓存过期时间（秒）
self._last_context_hash = None # 上次上下文的哈希值
async def modify_actions(
self,
message_content: str = "",
): # sourcery skip: use-named-expression
async def modify_actions(self, mode: ChatMode, message_content: str = ""):
"""
动作修改流程，整合传统观察处理和新的激活类型判定
@@ -146,6 +143,7 @@ class ActionModifier:
removals_s3 = await self._get_deactivated_actions_by_type(
current_using_actions,
chat_content,
mode,
)
# 应用第三阶段的移除
@@ -178,6 +176,7 @@ class ActionModifier:
self,
actions_with_info: Dict[str, ActionInfo],
chat_content: str = "",
mode: ChatMode = ChatMode.NORMAL,
) -> List[tuple[str, str]]:
"""
根据激活类型过滤，返回需要停用的动作列表及原因
@@ -198,34 +197,26 @@ class ActionModifier:
random.shuffle(actions_to_check)
for action_name, action_info in actions_to_check:
activation_type = action_info.activation_type or action_info.focus_activation_type
if mode == ChatMode.FOCUS:
activation_type = action_info.focus_activation_type
else:
activation_type = action_info.normal_activation_type
if activation_type == ActionActivationType.ALWAYS:
continue # 总是激活，无需处理
continue
elif activation_type == ActionActivationType.RANDOM:
probability = action_info.random_activation_probability
probability = action_info.random_activation_probability
if random.random() >= probability:
reason = f"RANDOM类型未触发（概率{probability}）"
deactivated_actions.append((action_name, reason))
logger.debug(f"{self.log_prefix}未激活动作: {action_name}，原因: {reason}")
if random.random() >= action_info.random_activation_probability:
deactivated_actions.append((action_name, f"RANDOM类型未触发（概率{action_info.random_activation_probability}）"))
elif activation_type == ActionActivationType.KEYWORD:
if not self._check_keyword_activation(action_name, action_info, chat_content):
keywords = action_info.activation_keywords
reason = f"关键词未匹配（关键词: {keywords}）"
deactivated_actions.append((action_name, reason))
logger.debug(f"{self.log_prefix}未激活动作: {action_name}，原因: {reason}")
deactivated_actions.append((action_name, f"关键词未匹配（关键词: {action_info.activation_keywords}）"))
elif activation_type == ActionActivationType.LLM_JUDGE:
llm_judge_actions[action_name] = action_info
elif activation_type == ActionActivationType.KEYWORD_OR_LLM_JUDGE:
if not self._check_keyword_activation(action_name, action_info, chat_content):
llm_judge_actions[action_name] = action_info
elif activation_type == ActionActivationType.NEVER:
reason = "激活类型为never"
deactivated_actions.append((action_name, reason))
logger.debug(f"{self.log_prefix}未激活动作: {action_name}，原因: 激活类型为never")
deactivated_actions.append((action_name, "激活类型为never"))
else:
logger.warning(f"{self.log_prefix}未知的激活类型: {activation_type}，跳过处理")

55
src/chat/planner_actions/plan_generator.py
View File

@@ -2,14 +2,14 @@
PlanGenerator: 负责搜集和汇总所有决策所需的信息，生成一个未经筛选的“原始计划” (Plan)。
"""
import time
from typing import Dict, Optional, Tuple
from typing import Dict, Optional, Tuple, List
from src.chat.utils.chat_message_builder import get_raw_msg_before_timestamp_with_chat
from src.chat.utils.utils import get_chat_type_and_target_info
from src.common.data_models.database_data_model import DatabaseMessages
from src.common.data_models.info_data_model import Plan, TargetPersonInfo
from src.config.config import global_config
from src.plugin_system.base.component_types import ActionInfo, ChatMode, ComponentType
from src.plugin_system.base.component_types import ActionActivationType, ActionInfo, ChatMode, ComponentType
from src.plugin_system.core.component_registry import component_registry
@@ -57,13 +57,13 @@ class PlanGenerator:
if chat_target_info_dict:
target_info = TargetPersonInfo(**chat_target_info_dict)
available_actions = self._get_available_actions()
chat_history_raw = get_raw_msg_before_timestamp_with_chat(
chat_id=self.chat_id,
timestamp=time.time(),
limit=int(global_config.chat.max_context_size),
)
chat_history = [DatabaseMessages(**msg) for msg in chat_history_raw]
available_actions = self._get_available_actions(mode, chat_history)
plan = Plan(
@@ -75,36 +75,41 @@ class PlanGenerator:
)
return plan
def _get_available_actions(self) -> Dict[str, "ActionInfo"]:
def _get_available_actions(self, mode: ChatMode, chat_history: List[DatabaseMessages]) -> Dict[str, "ActionInfo"]:
"""
从 ActionManager 和组件注册表中获取当前所有可用的动作。
它会合并已注册的动作和系统级动作（如 "no_reply"），
并以字典形式返回。
Returns:
Dict[str, "ActionInfo"]: 一个字典，键是动作名称，值是 ActionInfo 对象。
根据当前的聊天模式和激活类型，筛选出可用的动作。
"""
current_available_actions_dict = self.action_manager.get_using_actions()
all_registered_actions: Dict[str, ActionInfo] = component_registry.get_components_by_type( # type: ignore
ComponentType.ACTION
)
all_actions: Dict[str, ActionInfo] = component_registry.get_components_by_type(ComponentType.ACTION) # type: ignore
available_actions = {}
latest_message_text = chat_history[-1].processed_plain_text if chat_history else ""
current_available_actions = {}
for action_name in current_available_actions_dict:
if action_name in all_registered_actions:
current_available_actions[action_name] = all_registered_actions[action_name]
for name, info in all_actions.items():
# 根据当前模式选择对应的激活类型
activation_type = info.focus_activation_type if mode == ChatMode.FOCUS else info.normal_activation_type
if activation_type in [ActionActivationType.ALWAYS, ActionActivationType.LLM_JUDGE]:
available_actions[name] = info
elif activation_type == ActionActivationType.KEYWORD:
if any(kw.lower() in latest_message_text.lower() for kw in info.activation_keywords):
available_actions[name] = info
elif activation_type == ActionActivationType.KEYWORD_OR_LLM_JUDGE:
if any(kw.lower() in latest_message_text.lower() for kw in info.activation_keywords):
available_actions[name] = info
else:
# 即使关键词不匹配，也将其添加到可用动作中，交由LLM判断
available_actions[name] = info
elif activation_type == ActionActivationType.NEVER:
pass # 永不激活
else:
logger.warning(f"未知的激活类型: {activation_type}，跳过处理")
# 添加系统级动作
no_reply_info = ActionInfo(
name="no_reply",
component_type=ComponentType.ACTION,
description="系统级动作：选择不回复消息的决策",
action_parameters={},
activation_keywords=[],
plugin_name="SYSTEM",
enabled=True,
parallel_action=False,
)
current_available_actions["no_reply"] = no_reply_info
available_actions["no_reply"] = no_reply_info
return current_available_actions
return available_actions

1
src/plugin_system/base/base_action.py
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@@ -459,7 +459,6 @@ class BaseAction(ABC):
focus_activation_type = getattr(cls, "focus_activation_type", ActionActivationType.ALWAYS)
normal_activation_type = getattr(cls, "normal_activation_type", ActionActivationType.ALWAYS)
# 处理activation_type：如果插件中声明了就用插件的值，否则默认使用focus_activation_type
activation_type = getattr(cls, "activation_type", focus_activation_type)
return ActionInfo(

1
src/plugin_system/base/component_types.py
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@@ -31,6 +31,7 @@ class ActionActivationType(Enum):
LLM_JUDGE = "llm_judge" # LLM判定是否启动该action到planner
RANDOM = "random" # 随机启用action到planner
KEYWORD = "keyword" # 关键词触发启用action到planner
KEYWORD_OR_LLM_JUDGE = "keyword_or_llm_judge" # From Elysia with love~ 献给我最棒的伙伴！
def __str__(self):
return self.value