309 lines
12 KiB
Python
309 lines
12 KiB
Python
import json
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from typing import Dict, Any
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from rich.traceback import install
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from src.llm_models.utils_model import LLMRequest
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from src.config.config import global_config
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from src.common.logger import get_logger
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from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
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from src.individuality.individuality import get_individuality
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from src.chat.focus_chat.planners.action_manager import ActionManager
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from src.chat.message_receive.message import MessageThinking
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from json_repair import repair_json
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from src.chat.utils.chat_message_builder import build_readable_messages, get_raw_msg_before_timestamp_with_chat
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import time
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import traceback
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logger = get_logger("normal_chat_planner")
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install(extra_lines=3)
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def init_prompt():
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Prompt(
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"""
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你的自我认知是：
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{self_info_block}
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请记住你的性格，身份和特点。
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你是群内的一员，你现在正在参与群内的闲聊，以下是群内的聊天内容：
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{chat_context}
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基于以上聊天上下文和用户的最新消息，选择最合适的action。
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注意，除了下面动作选项之外，你在聊天中不能做其他任何事情，这是你能力的边界，现在请你选择合适的action:
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{action_options_text}
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重要说明：
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- "no_action" 表示只进行普通聊天回复，不执行任何额外动作
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- 其他action表示在普通回复的基础上，执行相应的额外动作
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你必须从上面列出的可用action中选择一个，并说明原因。
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{moderation_prompt}
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请以动作的输出要求，以严格的 JSON 格式输出，且仅包含 JSON 内容。不要有任何其他文字或解释：
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""",
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"normal_chat_planner_prompt",
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)
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Prompt(
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"""
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动作：{action_name}
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该动作的描述：{action_description}
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使用该动作的场景：
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{action_require}
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输出要求：
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{{
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"action": "{action_name}",{action_parameters}
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}}
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""",
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"normal_chat_action_prompt",
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)
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class NormalChatPlanner:
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def __init__(self, log_prefix: str, action_manager: ActionManager):
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self.log_prefix = log_prefix
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# LLM规划器配置
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self.planner_llm = LLMRequest(
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model=global_config.model.planner,
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request_type="normal.planner", # 用于normal_chat动作规划
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)
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self.action_manager = action_manager
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async def plan(self, message: MessageThinking, sender_name: str = "某人") -> Dict[str, Any]:
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"""
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Normal Chat 规划器: 使用LLM根据上下文决定做出什么动作。
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参数:
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message: 思考消息对象
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sender_name: 发送者名称
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"""
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action = "no_action" # 默认动作改为no_action
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reasoning = "规划器初始化默认"
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action_data = {}
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try:
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# 设置默认值
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nickname_str = ""
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for nicknames in global_config.bot.alias_names:
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nickname_str += f"{nicknames},"
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name_block = f"你的名字是{global_config.bot.nickname},你的昵称有{nickname_str}，有人也会用这些昵称称呼你。"
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personality_block = get_individuality().get_personality_prompt(x_person=2, level=2)
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identity_block = get_individuality().get_identity_prompt(x_person=2, level=2)
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self_info = name_block + personality_block + identity_block
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# 获取当前可用的动作，使用Normal模式过滤
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current_available_actions = self.action_manager.get_using_actions_for_mode("normal")
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# 注意：动作的激活判定现在在 normal_chat_action_modifier 中完成
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# 这里直接使用经过 action_modifier 处理后的最终动作集
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# 符合职责分离原则：ActionModifier负责动作管理，Planner专注于决策
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# 如果没有可用动作，直接返回no_action
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if not current_available_actions:
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logger.debug(f"{self.log_prefix}规划器: 没有可用动作，返回no_action")
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return {
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"action_result": {
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"action_type": action,
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"action_data": action_data,
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"reasoning": reasoning,
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"is_parallel": True,
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},
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"chat_context": "",
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"action_prompt": "",
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}
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# 构建normal_chat的上下文 (使用与normal_chat相同的prompt构建方法)
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message_list_before_now = get_raw_msg_before_timestamp_with_chat(
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chat_id=message.chat_stream.stream_id,
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timestamp=time.time(),
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limit=global_config.focus_chat.observation_context_size,
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)
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chat_context = build_readable_messages(
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message_list_before_now,
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replace_bot_name=True,
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merge_messages=False,
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timestamp_mode="relative",
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read_mark=0.0,
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show_actions=True,
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)
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# 构建planner的prompt
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prompt = await self.build_planner_prompt(
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self_info_block=self_info,
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chat_context=chat_context,
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current_available_actions=current_available_actions,
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)
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if not prompt:
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logger.warning(f"{self.log_prefix}规划器: 构建提示词失败")
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return {
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"action_result": {
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"action_type": action,
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"action_data": action_data,
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"reasoning": reasoning,
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"is_parallel": False,
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},
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"chat_context": chat_context,
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"action_prompt": "",
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}
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# 使用LLM生成动作决策
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try:
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content, (reasoning_content, model_name) = await self.planner_llm.generate_response_async(prompt)
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logger.info(f"{self.log_prefix}规划器原始提示词: {prompt}")
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logger.info(f"{self.log_prefix}规划器原始响应: {content}")
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logger.info(f"{self.log_prefix}规划器推理: {reasoning_content}")
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logger.info(f"{self.log_prefix}规划器模型: {model_name}")
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# 解析JSON响应
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try:
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# 尝试修复JSON
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fixed_json = repair_json(content)
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action_result = json.loads(fixed_json)
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action = action_result.get("action", "no_action")
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reasoning = action_result.get("reasoning", "未提供原因")
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# 提取其他参数作为action_data
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action_data = {k: v for k, v in action_result.items() if k not in ["action", "reasoning"]}
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# 验证动作是否在可用动作列表中，或者是特殊动作
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if action not in current_available_actions:
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logger.warning(f"{self.log_prefix}规划器选择了不可用的动作: {action}, 回退到no_action")
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action = "no_action"
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reasoning = f"选择的动作{action}不在可用列表中，回退到no_action"
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action_data = {}
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except json.JSONDecodeError as e:
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logger.warning(f"{self.log_prefix}规划器JSON解析失败: {e}, 内容: {content}")
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action = "no_action"
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reasoning = "JSON解析失败，使用默认动作"
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action_data = {}
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except Exception as e:
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logger.error(f"{self.log_prefix}规划器LLM调用失败: {e}")
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action = "no_action"
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reasoning = "LLM调用失败，使用默认动作"
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action_data = {}
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except Exception as outer_e:
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logger.error(f"{self.log_prefix}规划器异常: {outer_e}")
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# 设置异常时的默认值
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current_available_actions = {}
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chat_context = "无法获取聊天上下文"
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prompt = ""
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action = "no_action"
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reasoning = "规划器出现异常，使用默认动作"
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action_data = {}
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# 检查动作是否支持并行执行
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is_parallel = False
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if action in current_available_actions:
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action_info = current_available_actions[action]
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is_parallel = action_info.get("parallel_action", False)
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logger.debug(
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f"{self.log_prefix}规划器决策动作:{action}, 动作信息: '{action_data}', 理由: {reasoning}, 并行执行: {is_parallel}"
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)
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# 恢复到默认动作集
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self.action_manager.restore_actions()
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logger.debug(
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f"{self.log_prefix}规划后恢复到默认动作集, 当前可用: {list(self.action_manager.get_using_actions().keys())}"
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)
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# 构建 action 记录
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action_record = {
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"action_type": action,
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"action_data": action_data,
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"reasoning": reasoning,
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"timestamp": time.time(),
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"model_name": model_name if "model_name" in locals() else None,
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}
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action_result = {
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"action_type": action,
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"action_data": action_data,
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"reasoning": reasoning,
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"is_parallel": is_parallel,
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"action_record": json.dumps(action_record, ensure_ascii=False),
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}
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plan_result = {
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"action_result": action_result,
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"chat_context": chat_context,
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"action_prompt": prompt,
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}
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return plan_result
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async def build_planner_prompt(
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self,
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self_info_block: str,
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chat_context: str,
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current_available_actions: Dict[str, Any],
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) -> str:
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"""构建 Normal Chat Planner LLM 的提示词"""
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try:
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# 构建动作选项文本
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action_options_text = ""
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for action_name, action_info in current_available_actions.items():
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action_description = action_info.get("description", "")
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action_parameters = action_info.get("parameters", {})
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action_require = action_info.get("require", [])
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if action_parameters:
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param_text = "\n"
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# print(action_parameters)
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for param_name, param_description in action_parameters.items():
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param_text += f' "{param_name}":"{param_description}"\n'
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param_text = param_text.rstrip("\n")
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else:
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param_text = ""
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require_text = ""
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for require_item in action_require:
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require_text += f"- {require_item}\n"
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require_text = require_text.rstrip("\n")
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# 构建单个动作的提示
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action_prompt = await global_prompt_manager.format_prompt(
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"normal_chat_action_prompt",
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action_name=action_name,
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action_description=action_description,
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action_parameters=param_text,
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action_require=require_text,
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)
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action_options_text += action_prompt + "\n\n"
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# 审核提示
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moderation_prompt = "请确保你的回复符合平台规则，避免不当内容。"
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# 使用模板构建最终提示词
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prompt = await global_prompt_manager.format_prompt(
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"normal_chat_planner_prompt",
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self_info_block=self_info_block,
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action_options_text=action_options_text,
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moderation_prompt=moderation_prompt,
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chat_context=chat_context,
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)
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return prompt
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except Exception as e:
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logger.error(f"{self.log_prefix}构建Planner提示词失败: {e}")
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traceback.print_exc()
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return ""
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init_prompt()
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