621 lines
24 KiB
Python
621 lines
24 KiB
Python
import asyncio
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import json
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import time
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from src.chat.message_receive.message import MessageRecv
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from src.llm_models.utils_model import LLMRequest
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from src.common.logger import get_logger
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from src.chat.utils.chat_message_builder import build_readable_messages, get_raw_msg_by_timestamp_with_chat_inclusive
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from src.config.config import global_config
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from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
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from src.manager.async_task_manager import AsyncTask, async_task_manager
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from src.plugin_system.apis import send_api
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"""
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面部表情系统使用说明：
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1. 预定义的面部表情：
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- happy: 高兴表情（眼睛微笑 + 眉毛微笑 + 嘴巴大笑）
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- very_happy: 非常高兴（高兴表情 + 脸红）
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- sad: 悲伤表情（眼睛哭泣 + 眉毛忧伤 + 嘴巴悲伤）
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- angry: 生气表情（眉毛生气 + 嘴巴生气）
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- fear: 恐惧表情（眼睛闭上）
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- shy: 害羞表情（嘴巴嘟起 + 脸红）
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- neutral: 中性表情（无表情）
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2. 使用方法：
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# 获取面部表情管理器
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facial_expression = mood_manager.get_facial_expression_by_chat_id(chat_id)
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# 发送指定表情
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await facial_expression.send_expression("happy")
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# 根据情绪值自动选择表情
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await facial_expression.send_expression_by_mood(mood_values)
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# 重置为中性表情
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await facial_expression.reset_expression()
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3. 自动表情系统：
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- 当情绪值更新时，系统会自动根据mood_values选择合适的面部表情
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- 只有当新表情与当前表情不同时才会发送，避免重复发送
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- 支持joy >= 8时显示very_happy，joy >= 6时显示happy等梯度表情
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4. amadus表情更新系统：
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- 每1秒检查一次表情是否有变化，如有变化则发送到amadus
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- 每次mood更新后立即发送表情更新
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- 发送消息类型为"amadus_expression_update"，格式为{"action": "表情名", "data": 1.0}
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5. 表情选择逻辑：
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- 系统会找出最强的情绪（joy, anger, sorrow, fear）
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- 根据情绪强度选择相应的表情组合
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- 默认情况下返回neutral表情
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"""
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logger = get_logger("mood")
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def init_prompt():
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Prompt(
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"""
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{chat_talking_prompt}
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以上是直播间里正在进行的对话
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{indentify_block}
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你刚刚的情绪状态是：{mood_state}
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现在，发送了消息，引起了你的注意，你对其进行了阅读和思考，请你输出一句话描述你新的情绪状态，不要输出任何其他内容
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请只输出情绪状态，不要输出其他内容：
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""",
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"change_mood_prompt_vtb",
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)
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Prompt(
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"""
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{chat_talking_prompt}
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以上是直播间里最近的对话
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{indentify_block}
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你之前的情绪状态是：{mood_state}
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距离你上次关注直播间消息已经过去了一段时间，你冷静了下来，请你输出一句话描述你现在的情绪状态
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请只输出情绪状态，不要输出其他内容：
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""",
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"regress_mood_prompt_vtb",
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)
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Prompt(
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"""
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{chat_talking_prompt}
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以上是直播间里正在进行的对话
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{indentify_block}
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你刚刚的情绪状态是：{mood_state}
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具体来说，从1-10分，你的情绪状态是：
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喜(Joy): {joy}
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怒(Anger): {anger}
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哀(Sorrow): {sorrow}
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惧(Fear): {fear}
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现在，发送了消息，引起了你的注意，你对其进行了阅读和思考。请基于对话内容，评估你新的情绪状态。
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请以JSON格式输出你新的情绪状态，包含"喜怒哀惧"四个维度，每个维度的取值范围为1-10。
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键值请使用英文: "joy", "anger", "sorrow", "fear".
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例如: {{"joy": 5, "anger": 1, "sorrow": 1, "fear": 1}}
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不要输出任何其他内容，只输出JSON。
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""",
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"change_mood_numerical_prompt",
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)
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Prompt(
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"""
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{chat_talking_prompt}
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以上是直播间里最近的对话
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{indentify_block}
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你之前的情绪状态是：{mood_state}
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具体来说，从1-10分，你的情绪状态是：
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喜(Joy): {joy}
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怒(Anger): {anger}
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哀(Sorrow): {sorrow}
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惧(Fear): {fear}
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距离你上次关注直播间消息已经过去了一段时间，你冷静了下来。请基于此，评估你现在的情绪状态。
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请以JSON格式输出你新的情绪状态，包含"喜怒哀惧"四个维度，每个维度的取值范围为1-10。
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键值请使用英文: "joy", "anger", "sorrow", "fear".
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例如: {{"joy": 5, "anger": 1, "sorrow": 1, "fear": 1}}
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不要输出任何其他内容，只输出JSON。
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""",
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"regress_mood_numerical_prompt",
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)
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class FacialExpression:
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def __init__(self, chat_id: str):
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self.chat_id: str = chat_id
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# 预定义面部表情动作
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self.expressions = {
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# 眼睛表情
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"eye_smile": {"action": "eye_smile", "data": 1.0},
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"eye_cry": {"action": "eye_cry", "data": 1.0},
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"eye_close": {"action": "eye_close", "data": 1.0},
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"eye_normal": {"action": "eye_normal", "data": 1.0},
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# 眉毛表情
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"eyebrow_smile": {"action": "eyebrow_smile", "data": 1.0},
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"eyebrow_angry": {"action": "eyebrow_angry", "data": 1.0},
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"eyebrow_sad": {"action": "eyebrow_sad", "data": 1.0},
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"eyebrow_normal": {"action": "eyebrow_normal", "data": 1.0},
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# 嘴巴表情
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"mouth_sad": {"action": "mouth_sad", "data": 1.0},
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"mouth_angry": {"action": "mouth_angry", "data": 1.0},
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"mouth_laugh": {"action": "mouth_laugh", "data": 1.0},
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"mouth_pout": {"action": "mouth_pout", "data": 1.0},
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"mouth_normal": {"action": "mouth_normal", "data": 1.0},
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# 脸部表情
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"face_blush": {"action": "face_blush", "data": 1.0},
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"face_normal": {"action": "face_normal", "data": 1.0},
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}
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# 表情组合模板
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self.expression_combinations = {
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"happy": {
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"eye": "eye_smile",
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"eyebrow": "eyebrow_smile",
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"mouth": "mouth_laugh",
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"face": "face_normal"
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},
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"very_happy": {
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"eye": "eye_smile",
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"eyebrow": "eyebrow_smile",
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"mouth": "mouth_laugh",
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"face": "face_blush"
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},
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"sad": {
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"eye": "eye_cry",
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"eyebrow": "eyebrow_sad",
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"mouth": "mouth_sad",
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"face": "face_normal"
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},
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"angry": {
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"eye": "eye_normal",
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"eyebrow": "eyebrow_angry",
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"mouth": "mouth_angry",
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"face": "face_normal"
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},
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"fear": {
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"eye": "eye_close",
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"eyebrow": "eyebrow_normal",
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"mouth": "mouth_normal",
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"face": "face_normal"
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},
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"shy": {
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"eye": "eye_normal",
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"eyebrow": "eyebrow_normal",
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"mouth": "mouth_pout",
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"face": "face_blush"
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},
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"neutral": {
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"eye": "eye_normal",
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"eyebrow": "eyebrow_normal",
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"mouth": "mouth_normal",
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"face": "face_normal"
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}
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}
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def select_expression_by_mood(self, mood_values: dict[str, int]) -> str:
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"""根据情绪值选择合适的表情组合"""
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joy = mood_values.get("joy", 5)
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anger = mood_values.get("anger", 1)
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sorrow = mood_values.get("sorrow", 1)
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fear = mood_values.get("fear", 1)
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# 找出最强的情绪
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emotions = {
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"joy": joy,
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"anger": anger,
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"sorrow": sorrow,
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"fear": fear
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}
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# 获取最强情绪
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dominant_emotion = max(emotions, key=emotions.get)
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dominant_value = emotions[dominant_emotion]
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# 根据情绪强度和类型选择表情
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if dominant_emotion == "joy":
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if joy >= 8:
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return "very_happy"
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elif joy >= 6:
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return "happy"
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elif joy >= 4:
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return "shy"
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else:
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return "neutral"
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elif dominant_emotion == "anger" and anger >= 6:
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return "angry"
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elif dominant_emotion == "sorrow" and sorrow >= 6:
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return "sad"
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elif dominant_emotion == "fear" and fear >= 6:
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return "fear"
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else:
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return "neutral"
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async def send_expression(self, expression_name: str):
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"""发送表情组合"""
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if expression_name not in self.expression_combinations:
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logger.warning(f"[{self.chat_id}] 未知表情: {expression_name}")
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return
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combination = self.expression_combinations[expression_name]
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# 依次发送各部位表情
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for part, expression_key in combination.items():
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if expression_key in self.expressions:
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expression_data = self.expressions[expression_key]
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await send_api.custom_to_stream(
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message_type="facial_expression",
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content=expression_data,
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stream_id=self.chat_id
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)
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logger.info(f"[{self.chat_id}] 发送面部表情 {part}: {expression_data}")
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await asyncio.sleep(0.1) # 短暂延迟避免同时发送过多消息
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# 通知ChatMood需要更新amadus
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# 这里需要从mood_manager获取ChatMood实例并标记
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chat_mood = mood_manager.get_mood_by_chat_id(self.chat_id)
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if chat_mood.last_expression != expression_name:
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chat_mood.last_expression = expression_name
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chat_mood.expression_needs_update = True
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async def send_expression_by_mood(self, mood_values: dict[str, int]):
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"""根据情绪值发送相应的面部表情"""
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expression_name = self.select_expression_by_mood(mood_values)
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logger.info(f"[{self.chat_id}] 根据情绪值选择表情: {expression_name}, 情绪值: {mood_values}")
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await self.send_expression(expression_name)
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async def reset_expression(self):
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"""重置为中性表情"""
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await self.send_expression("neutral")
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class ChatMood:
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def __init__(self, chat_id: str):
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self.chat_id: str = chat_id
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self.mood_state: str = "感觉很平静"
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self.mood_values: dict[str, int] = {"joy": 5, "anger": 1, "sorrow": 1, "fear": 1}
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self.regression_count: int = 0
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self.mood_model = LLMRequest(
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model=global_config.model.emotion,
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temperature=0.7,
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request_type="mood_text",
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)
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self.mood_model_numerical = LLMRequest(
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model=global_config.model.emotion,
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temperature=0.4,
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request_type="mood_numerical",
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)
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self.last_change_time = 0
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# 添加面部表情系统
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self.facial_expression = FacialExpression(chat_id)
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self.last_expression = "neutral" # 记录上一次的表情
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self.expression_needs_update = False # 标记表情是否需要更新
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# 设置初始中性表情
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asyncio.create_task(self.facial_expression.reset_expression())
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self.expression_needs_update = True # 初始化时也标记需要更新
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def _parse_numerical_mood(self, response: str) -> dict[str, int] | None:
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try:
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# The LLM might output markdown with json inside
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if "```json" in response:
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response = response.split("```json")[1].split("```")[0]
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elif "```" in response:
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response = response.split("```")[1].split("```")[0]
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data = json.loads(response)
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# Validate
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required_keys = {"joy", "anger", "sorrow", "fear"}
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if not required_keys.issubset(data.keys()):
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logger.warning(f"Numerical mood response missing keys: {response}")
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return None
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for key in required_keys:
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value = data[key]
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if not isinstance(value, int) or not (1 <= value <= 10):
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logger.warning(f"Numerical mood response invalid value for {key}: {value} in {response}")
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return None
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return {key: data[key] for key in required_keys}
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except json.JSONDecodeError:
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logger.warning(f"Failed to parse numerical mood JSON: {response}")
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return None
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except Exception as e:
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logger.error(f"Error parsing numerical mood: {e}, response: {response}")
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return None
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async def update_mood_by_message(self, message: MessageRecv):
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self.regression_count = 0
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message_time = message.message_info.time
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message_list_before_now = get_raw_msg_by_timestamp_with_chat_inclusive(
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chat_id=self.chat_id,
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timestamp_start=self.last_change_time,
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timestamp_end=message_time,
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limit=15,
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limit_mode="last",
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)
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chat_talking_prompt = 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="normal_no_YMD",
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read_mark=0.0,
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truncate=True,
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show_actions=True,
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)
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bot_name = global_config.bot.nickname
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if global_config.bot.alias_names:
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bot_nickname = f",也有人叫你{','.join(global_config.bot.alias_names)}"
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else:
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bot_nickname = ""
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prompt_personality = global_config.personality.personality_core
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indentify_block = f"你的名字是{bot_name}{bot_nickname}，你{prompt_personality}："
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async def _update_text_mood():
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prompt = await global_prompt_manager.format_prompt(
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"change_mood_prompt_vtb",
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chat_talking_prompt=chat_talking_prompt,
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||
indentify_block=indentify_block,
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mood_state=self.mood_state,
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)
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logger.debug(f"text mood prompt: {prompt}")
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response, (reasoning_content, model_name) = await self.mood_model.generate_response_async(prompt=prompt)
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logger.info(f"text mood response: {response}")
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logger.debug(f"text mood reasoning_content: {reasoning_content}")
|
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return response
|
||
|
||
async def _update_numerical_mood():
|
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prompt = await global_prompt_manager.format_prompt(
|
||
"change_mood_numerical_prompt",
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||
chat_talking_prompt=chat_talking_prompt,
|
||
indentify_block=indentify_block,
|
||
mood_state=self.mood_state,
|
||
joy=self.mood_values["joy"],
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anger=self.mood_values["anger"],
|
||
sorrow=self.mood_values["sorrow"],
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||
fear=self.mood_values["fear"],
|
||
)
|
||
logger.info(f"numerical mood prompt: {prompt}")
|
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response, (reasoning_content, model_name) = await self.mood_model_numerical.generate_response_async(
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||
prompt=prompt
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||
)
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||
logger.info(f"numerical mood response: {response}")
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||
logger.debug(f"numerical mood reasoning_content: {reasoning_content}")
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return self._parse_numerical_mood(response)
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||
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||
results = await asyncio.gather(_update_text_mood(), _update_numerical_mood())
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||
text_mood_response, numerical_mood_response = results
|
||
|
||
if text_mood_response:
|
||
self.mood_state = text_mood_response
|
||
|
||
if numerical_mood_response:
|
||
old_mood_values = self.mood_values.copy()
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||
self.mood_values = numerical_mood_response
|
||
|
||
# 发送面部表情
|
||
new_expression = self.facial_expression.select_expression_by_mood(self.mood_values)
|
||
if new_expression != self.last_expression:
|
||
# 立即发送表情
|
||
asyncio.create_task(self.facial_expression.send_expression(new_expression))
|
||
self.last_expression = new_expression
|
||
self.expression_needs_update = True # 标记表情已更新
|
||
|
||
self.last_change_time = message_time
|
||
|
||
async def regress_mood(self):
|
||
message_time = time.time()
|
||
message_list_before_now = get_raw_msg_by_timestamp_with_chat_inclusive(
|
||
chat_id=self.chat_id,
|
||
timestamp_start=self.last_change_time,
|
||
timestamp_end=message_time,
|
||
limit=15,
|
||
limit_mode="last",
|
||
)
|
||
chat_talking_prompt = build_readable_messages(
|
||
message_list_before_now,
|
||
replace_bot_name=True,
|
||
merge_messages=False,
|
||
timestamp_mode="normal_no_YMD",
|
||
read_mark=0.0,
|
||
truncate=True,
|
||
show_actions=True,
|
||
)
|
||
|
||
bot_name = global_config.bot.nickname
|
||
if global_config.bot.alias_names:
|
||
bot_nickname = f",也有人叫你{','.join(global_config.bot.alias_names)}"
|
||
else:
|
||
bot_nickname = ""
|
||
|
||
prompt_personality = global_config.personality.personality_core
|
||
indentify_block = f"你的名字是{bot_name}{bot_nickname}，你{prompt_personality}："
|
||
|
||
async def _regress_text_mood():
|
||
prompt = await global_prompt_manager.format_prompt(
|
||
"regress_mood_prompt_vtb",
|
||
chat_talking_prompt=chat_talking_prompt,
|
||
indentify_block=indentify_block,
|
||
mood_state=self.mood_state,
|
||
)
|
||
logger.debug(f"text regress prompt: {prompt}")
|
||
response, (reasoning_content, model_name) = await self.mood_model.generate_response_async(prompt=prompt)
|
||
logger.info(f"text regress response: {response}")
|
||
logger.debug(f"text regress reasoning_content: {reasoning_content}")
|
||
return response
|
||
|
||
async def _regress_numerical_mood():
|
||
prompt = await global_prompt_manager.format_prompt(
|
||
"regress_mood_numerical_prompt",
|
||
chat_talking_prompt=chat_talking_prompt,
|
||
indentify_block=indentify_block,
|
||
mood_state=self.mood_state,
|
||
joy=self.mood_values["joy"],
|
||
anger=self.mood_values["anger"],
|
||
sorrow=self.mood_values["sorrow"],
|
||
fear=self.mood_values["fear"],
|
||
)
|
||
logger.debug(f"numerical regress prompt: {prompt}")
|
||
response, (reasoning_content, model_name) = await self.mood_model_numerical.generate_response_async(
|
||
prompt=prompt
|
||
)
|
||
logger.info(f"numerical regress response: {response}")
|
||
logger.debug(f"numerical regress reasoning_content: {reasoning_content}")
|
||
return self._parse_numerical_mood(response)
|
||
|
||
results = await asyncio.gather(_regress_text_mood(), _regress_numerical_mood())
|
||
text_mood_response, numerical_mood_response = results
|
||
|
||
if text_mood_response:
|
||
self.mood_state = text_mood_response
|
||
|
||
if numerical_mood_response:
|
||
old_mood_values = self.mood_values.copy()
|
||
self.mood_values = numerical_mood_response
|
||
|
||
# 发送面部表情
|
||
new_expression = self.facial_expression.select_expression_by_mood(self.mood_values)
|
||
if new_expression != self.last_expression:
|
||
# 立即发送表情
|
||
asyncio.create_task(self.facial_expression.send_expression(new_expression))
|
||
self.last_expression = new_expression
|
||
self.expression_needs_update = True # 标记表情已更新
|
||
|
||
self.regression_count += 1
|
||
|
||
async def send_expression_update_if_needed(self):
|
||
"""如果表情有变化，发送更新到amadus"""
|
||
if self.expression_needs_update:
|
||
# 发送当前表情状态到amadus，使用简洁的action/data格式
|
||
expression_data = {
|
||
"action": self.last_expression,
|
||
"data": 1.0
|
||
}
|
||
|
||
await send_api.custom_to_stream(
|
||
message_type="amadus_expression_update",
|
||
content=expression_data,
|
||
stream_id=self.chat_id
|
||
)
|
||
|
||
logger.info(f"[{self.chat_id}] 发送表情更新到amadus: {expression_data}")
|
||
self.expression_needs_update = False # 重置标记
|
||
|
||
|
||
class MoodRegressionTask(AsyncTask):
|
||
def __init__(self, mood_manager: "MoodManager"):
|
||
super().__init__(task_name="MoodRegressionTask", run_interval=30)
|
||
self.mood_manager = mood_manager
|
||
|
||
async def run(self):
|
||
logger.debug("Running mood regression task...")
|
||
now = time.time()
|
||
for mood in self.mood_manager.mood_list:
|
||
if mood.last_change_time == 0:
|
||
continue
|
||
|
||
if now - mood.last_change_time > 180:
|
||
if mood.regression_count >= 3:
|
||
continue
|
||
|
||
logger.info(f"chat {mood.chat_id} 开始情绪回归, 这是第 {mood.regression_count + 1} 次")
|
||
await mood.regress_mood()
|
||
|
||
|
||
class ExpressionUpdateTask(AsyncTask):
|
||
def __init__(self, mood_manager: "MoodManager"):
|
||
super().__init__(task_name="ExpressionUpdateTask", run_interval=1)
|
||
self.mood_manager = mood_manager
|
||
|
||
async def run(self):
|
||
logger.debug("Running expression update task...")
|
||
for mood in self.mood_manager.mood_list:
|
||
await mood.send_expression_update_if_needed()
|
||
|
||
|
||
class MoodManager:
|
||
def __init__(self):
|
||
self.mood_list: list[ChatMood] = []
|
||
"""当前情绪状态"""
|
||
self.task_started: bool = False
|
||
|
||
async def start(self):
|
||
"""启动情绪回归后台任务"""
|
||
if self.task_started:
|
||
return
|
||
|
||
logger.info("启动情绪管理任务...")
|
||
|
||
# 启动情绪回归任务
|
||
regression_task = MoodRegressionTask(self)
|
||
await async_task_manager.add_task(regression_task)
|
||
|
||
# 启动表情更新任务
|
||
expression_task = ExpressionUpdateTask(self)
|
||
await async_task_manager.add_task(expression_task)
|
||
|
||
self.task_started = True
|
||
logger.info("情绪管理任务已启动（包含情绪回归和表情更新）")
|
||
|
||
def get_mood_by_chat_id(self, chat_id: str) -> ChatMood:
|
||
for mood in self.mood_list:
|
||
if mood.chat_id == chat_id:
|
||
return mood
|
||
|
||
new_mood = ChatMood(chat_id)
|
||
self.mood_list.append(new_mood)
|
||
return new_mood
|
||
|
||
def reset_mood_by_chat_id(self, chat_id: str):
|
||
for mood in self.mood_list:
|
||
if mood.chat_id == chat_id:
|
||
mood.mood_state = "感觉很平静"
|
||
mood.mood_values = {"joy": 5, "anger": 1, "sorrow": 1, "fear": 1}
|
||
mood.regression_count = 0
|
||
# 重置面部表情为中性
|
||
asyncio.create_task(mood.facial_expression.reset_expression())
|
||
mood.last_expression = "neutral"
|
||
mood.expression_needs_update = True # 标记表情需要更新
|
||
return
|
||
|
||
# 如果没有找到现有的mood，创建新的
|
||
new_mood = ChatMood(chat_id)
|
||
self.mood_list.append(new_mood)
|
||
asyncio.create_task(new_mood.facial_expression.reset_expression())
|
||
new_mood.expression_needs_update = True # 标记表情需要更新
|
||
|
||
def get_facial_expression_by_chat_id(self, chat_id: str) -> FacialExpression:
|
||
"""获取聊天对应的面部表情管理器"""
|
||
for mood in self.mood_list:
|
||
if mood.chat_id == chat_id:
|
||
return mood.facial_expression
|
||
|
||
# 如果没有找到，创建新的
|
||
new_mood = ChatMood(chat_id)
|
||
self.mood_list.append(new_mood)
|
||
return new_mood.facial_expression
|
||
|
||
|
||
init_prompt()
|
||
|
||
mood_manager = MoodManager()
|
||
"""全局情绪管理器"""
|