feat: 支持基于对数函数的分段回复延时时间计算

astrbot/core/config/default.py

@@ -2,7 +2,7 @@
 如需修改配置，请在 `data/cmd_config.json` 中修改或者在管理面板中可视化修改。
 """
 
-VERSION = "3.4.25"
+VERSION = "3.4.26"
 DB_PATH = "data/data_v3.db"
 
 # 默认配置
@@ -28,7 +28,10 @@ DEFAULT_CONFIG = {
         "segmented_reply": {
             "enable": False,
             "only_llm_result": True,
+            "interval_method": "random",
             "interval": "1.5,3.5",
+            "log_base": 2.6,
+            "words_count_threshold": 150,
             "regex": ".*?[。？！~…]+|.+$"
         },
         "no_permission_reply": True,
@@ -242,10 +245,26 @@ CONFIG_METADATA_2 = {
                                 "description": "仅对 LLM 结果分段",
                                 "type": "bool",
                             },
+                            "interval_method": {
+                                "description": "间隔时间计算方法",
+                                "type": "string",
+                                "options": ["random", "log"],
+                                "hint": "分段回复的间隔时间计算方法。random 为随机时间，log 为根据消息长度计算，$y=log_{log\_base}(x)$，x为字数，y的单位为秒。",
+                            },
                             "interval": {
                                 "description": "随机间隔时间(秒)",
                                 "type": "string",
-                                "hint": "每一段回复的间隔时间，格式为 `最小时间,最大时间`。如 `0.75,2.5`",
+                                "hint": "`random` 方法用。每一段回复的间隔时间，格式为 `最小时间,最大时间`。如 `0.75,2.5`",
+                            },
+                            "log_base": {
+                                "description": "对数函数底数",
+                                "type": "float",
+                                "hint": "`log` 方法用。对数函数的底数。默认为 2.6",
+                            },
+                            "words_count_threshold": {
+                                "description": "字数阈值",
+                                "type": "int",
+                                "hint": "超过这个字数的消息不会被分段回复。默认为 150",
                             },
                             "regex": {
                                 "description": "正则表达式",

astrbot/core/pipeline/respond/stage.py

@@ -1,11 +1,13 @@
 import random
 import asyncio
+import math
 from typing import Union, AsyncGenerator
 from ..stage import register_stage, Stage
 from ..context import PipelineContext
 from astrbot.core.platform.astr_message_event import AstrMessageEvent
 from astrbot.core.message.message_event_result import MessageChain
 from astrbot.core import logger
+from astrbot.core.message.message_event_result import BaseMessageComponent, Plain
 from astrbot.core.star.star_handler import star_handlers_registry, EventType
 
 @register_stage
@@ -16,6 +18,9 @@ class RespondStage(Stage):
         # 分段回复
         self.enable_seg: bool = ctx.astrbot_config['platform_settings']['segmented_reply']['enable']
         self.only_llm_result = ctx.astrbot_config['platform_settings']['segmented_reply']['only_llm_result']
+        
+        self.interval_method = ctx.astrbot_config['platform_settings']['segmented_reply']['interval_method']
+        self.log_base = float(ctx.astrbot_config['platform_settings']['segmented_reply']['log_base'])
         interval_str: str = ctx.astrbot_config['platform_settings']['segmented_reply']['interval']
         interval_str_ls = interval_str.replace(" ", "").split(",")
         try:
@@ -24,7 +29,27 @@ class RespondStage(Stage):
             logger.error(f'解析分段回复的间隔时间失败。{e}')
             self.interval = [1.5, 3.5]
         logger.info(f"分段回复间隔时间：{self.interval}")
-
+        
+    async def _word_cnt(self, text: str) -> int:
+        '''分段回复 统计字数'''
+        if all(ord(c) < 128 for c in text):
+            word_count = len(text.split())
+        else:
+            word_count = len([c for c in text if c.isalnum()])
+        return word_count
+    
+    async def _calc_comp_interval(self, comp: BaseMessageComponent) -> float:
+        '''分段回复 计算间隔时间'''
+        if self.interval_method == 'log':
+            if isinstance(comp, Plain):
+                wc = await self._word_cnt(comp.text)
+                i = math.log(wc + 1, self.log_base)
+                return random.uniform(i, i + 0.5)
+            else:
+                return random.uniform(1, 1.75)
+        else:
+            # random
+            return random.uniform(self.interval[0], self.interval[1])
 
     async def process(self, event: AstrMessageEvent) -> Union[None, AsyncGenerator[None, None]]:
         result = event.get_result()
@@ -37,8 +62,9 @@ class RespondStage(Stage):
             if self.enable_seg and ((self.only_llm_result and result.is_llm_result()) or not self.only_llm_result):
                 # 分段回复
                 for comp in result.chain:
+                    i = await self._calc_comp_interval(comp)
+                    await asyncio.sleep(i)
                     await event.send(MessageChain([comp]))
-                    await asyncio.sleep(random.uniform(self.interval[0], self.interval[1]))
             else:
                 await event.send(result)
             await event._post_send()

astrbot/core/pipeline/result_decorate/stage.py

@@ -27,6 +27,7 @@ class ResultDecorateStage(Stage):
             self.t2i_word_threshold = 150
         
         # 分段回复
+        self.words_count_threshold = int(ctx.astrbot_config['platform_settings']['segmented_reply']['words_count_threshold'])
         self.enable_segmented_reply = ctx.astrbot_config['platform_settings']['segmented_reply']['enable']
         self.only_llm_result = ctx.astrbot_config['platform_settings']['segmented_reply']['only_llm_result']
         self.regex = ctx.astrbot_config['platform_settings']['segmented_reply']['regex']
@@ -77,6 +78,10 @@ class ResultDecorateStage(Stage):
                     new_chain = []
                     for comp in result.chain:
                         if isinstance(comp, Plain):
+                            if len(comp.text) > self.words_count_threshold:
+                                # 不分段回复
+                                new_chain.append(comp)
+                                continue
                             split_response = re.findall(self.regex, comp.text)
                             if not split_response:
                                 new_chain.append(comp)