打通自动回复与表情语义库联动\n\n- 新增表情语义解析与表情资产查询模块，支持从历史表情中提取可读中文语义\n- 为 ai_auto_response 增加短回复表情匹配器，命中语义时优先发送表情并支持失败回退文本\n- 调整自动回复提示词与配置项，强化短情绪回复场景的表情替换能力

plugins/ai_auto_response/main.py

@@ -38,6 +38,7 @@ from .memory.social_memory import SocialMemoryService
 from .profile.group_profile import GroupProfileResolver
 from .context.conversation_hints import build_conversation_hints
 from .core.decision_flow import DecisionFlow
+from .core.emoji_reply import EmojiReplySelector
 from .core.triggers import TriggerRouter
 from .core.llm_result_parser import LLMResultParser
 from .core.reply_formatter import finalize_reply, preview_text
@@ -101,6 +102,7 @@ class AIAutoResponsePlugin(MessagePluginInterface):
         self.queue_maxsize = 200
         self.queue_workers: List[asyncio.Task] = []
         self.reply_limits: Dict[str, Any] = {}
+        self.emoji_reply_config: Dict[str, Any] = {}
         self.prompt_compact_config: Dict[str, Any] = {}
         self.message_expire_sec = 0.0
         self.room_message_seq_counter = 0
@@ -142,8 +144,10 @@ class AIAutoResponsePlugin(MessagePluginInterface):
         self.mode_config = self._config.get("mode", {}) or {}
         self.cooldown_config = self._config.get("cooldown", {}) or {}
         self.reply_limits = self._config.get("reply", {}) or {}
+        self.emoji_reply_config = self._config.get("emoji_reply", {}) or {}
         self.prompt_compact_config = self._config.get("prompt_compact", {}) or {}
         self.cooldown = CooldownManager(self.cooldown_config)
+        self.emoji_reply_selector = EmojiReplySelector(self.db_manager, self.emoji_reply_config)
         self.image_config = self._config.get("image", {}) or {}
         self.spam_config = self._config.get("spam_guard", {}) or {}
         runtime_config = self._config.get("runtime", {}) or {}
@@ -681,8 +685,37 @@ class AIAutoResponsePlugin(MessagePluginInterface):
                 )
                 return False, "duplicate_reply"
 
-            for chunk in reply_chunks:
-                await bot.send_text_message(room_id, chunk, sender)
+            # 这里让“自动回复文本”先经过一次本地表情匹配：
+            # 1. 模型仍然只负责输出自然语言，不需要知道 md5；
+            # 2. 只有命中中文语义库且回复足够短时，才会切换成表情发送；
+            # 3. 若表情发送失败，立刻回退到原始文本，避免因为表情链路影响主回复成功率。
+            sent_as_emoji = False
+            emoji_asset = self.emoji_reply_selector.match_reply_to_emoji(final_response_text, reply_chunks)
+            if emoji_asset and emoji_asset.get("md5") and int(emoji_asset.get("total_length") or 0) > 0:
+                try:
+                    await bot.send_emoji_message(
+                        room_id,
+                        str(emoji_asset.get("md5")),
+                        int(emoji_asset.get("total_length") or 0),
+                    )
+                    sent_as_emoji = True
+                except Exception as emoji_error:
+                    self._log_event(
+                        "emoji_fallback",
+                        room_id=room_id,
+                        sender=sender,
+                        trigger_type=trigger.trigger_type,
+                        reply_mode=reply_mode,
+                        topic=selected_topic,
+                        response_preview=preview_text(final_response_text),
+                        emoji_semantic=emoji_asset.get("semantic_text", ""),
+                        emoji_match_score=emoji_asset.get("match_score", 0),
+                        error=str(emoji_error),
+                    )
+
+            if not sent_as_emoji:
+                for chunk in reply_chunks:
+                    await bot.send_text_message(room_id, chunk, sender)
             self.cooldown.note_reply(room_id)
             self.flow_manager.note_bot_reply(room_id)
             self.memory_store.note_bot_reply(room_id, sender, selected_topic)
@@ -698,6 +731,9 @@ class AIAutoResponsePlugin(MessagePluginInterface):
                 response_preview=preview_text(final_response_text),
                 response_len=len(final_response_text),
                 chunk_count=len(reply_chunks),
+                sent_as_emoji=yn(sent_as_emoji),
+                emoji_semantic=(emoji_asset or {}).get("semantic_text", ""),
+                emoji_match_score=(emoji_asset or {}).get("match_score", 0),
             )
             return False, "replied"
         finally: