unify xiaoniu topic selection and reply planning

plugins/ai_auto_response/context_builder.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import re
 from typing import Dict, List
 
 
@@ -24,8 +25,9 @@ class ContextBuilder:
         quote_context: Dict | None = None,
         image_context: Dict | None = None,
     ) -> Dict:
+        selected_messages = self._select_recent_messages(recent_messages, sender, content, quote_context or {})
         recent_lines = []
-        for item in recent_messages[-self.recent_context_size:]:
+        for item in selected_messages:
             msg_sender = item.get("sender_name") or item.get("sender") or "未知成员"
             msg_content = item.get("content") or item.get("message") or ""
             if msg_content:
@@ -38,6 +40,7 @@ class ContextBuilder:
                 "member_context": member_context or {},
             },
             "speaker_name_clean": self._clean_display_name(sender_name),
+            "recent_message_items": self._build_recent_message_items(selected_messages),
             "recent_messages": recent_lines,
             "recent_summary": "",
             "trigger_type": trigger.get("trigger_type", "none"),
@@ -51,6 +54,123 @@ class ContextBuilder:
             "current_message": f"{sender_name}: {content}",
         }
 
+    @staticmethod
+    def _build_recent_message_items(messages: List[Dict]) -> List[Dict]:
+        items: List[Dict] = []
+        for idx, item in enumerate(messages, start=1):
+            content = str(item.get("content") or item.get("message") or "").strip()
+            if not content:
+                continue
+            items.append({
+                "idx": idx,
+                "sender": item.get("sender_name") or item.get("sender") or "未知成员",
+                "content": content[:120],
+                "is_at": bool(item.get("is_at")),
+            })
+        return items
+
+    def _select_recent_messages(
+        self,
+        recent_messages: List[Dict],
+        current_sender: str,
+        current_content: str,
+        quote_context: Dict,
+    ) -> List[Dict]:
+        if not recent_messages:
+            return []
+        window = recent_messages[-self.recent_context_size:]
+        if len(window) <= 8:
+            return window
+
+        current_tokens = self._extract_topic_tokens(current_content)
+        quote_tokens = self._extract_topic_tokens(
+            f"{quote_context.get('title', '')} {quote_context.get('quote_body', '')}"
+        )
+        focus_tokens = current_tokens | quote_tokens
+        quote_sender_name = str(quote_context.get("quote_sender_name", "") or "").strip().lower()
+
+        scored: List[tuple[int, int, Dict]] = []
+        for idx, item in enumerate(window):
+            score = self._message_relevance(
+                item,
+                current_sender=current_sender,
+                focus_tokens=focus_tokens,
+                quote_sender_name=quote_sender_name,
+            )
+            if score > 0:
+                scored.append((score, idx, item))
+
+        # 总是保留尾部几条，维持现场感；再拼上与当前话题最相关的消息。
+        tail_indexes = set(range(max(len(window) - 4, 0), len(window)))
+        keep_indexes = set(tail_indexes)
+        for _, idx, _ in sorted(scored, key=lambda x: (-x[0], -x[1]))[:10]:
+            keep_indexes.add(idx)
+
+        selected = [window[idx] for idx in sorted(keep_indexes)]
+        if len(selected) < 6:
+            return window[-6:]
+        return selected[-12:]
+
+    @classmethod
+    def _message_relevance(
+        cls,
+        item: Dict,
+        *,
+        current_sender: str,
+        focus_tokens: set[str],
+        quote_sender_name: str,
+    ) -> int:
+        content = str(item.get("content") or item.get("message") or "").strip()
+        if not content:
+            return 0
+        sender = str(item.get("sender", "") or "")
+        sender_name = str(item.get("sender_name", "") or "").strip().lower()
+        score = 0
+
+        if sender == current_sender:
+            score += 3
+        if quote_sender_name and quote_sender_name in sender_name:
+            score += 3
+        if item.get("is_at"):
+            score += 1
+
+        if focus_tokens:
+            tokens = cls._extract_topic_tokens(content)
+            overlap = focus_tokens & tokens
+            score += min(len(overlap) * 2, 6)
+            if overlap and cls._looks_like_question_or_answer(content):
+                score += 2
+        elif sender == current_sender:
+            score += 1
+
+        if cls._looks_like_question_or_answer(content):
+            score += 1
+        return score
+
+    @staticmethod
+    def _looks_like_question_or_answer(content: str) -> bool:
+        text = str(content or "").strip().lower()
+        if not text:
+            return False
+        patterns = [
+            r"\?$", r"？$", r"怎么", r"如何", r"为啥", r"为什么", r"能不能", r"可以吗",
+            r"报错", r"试试", r"先", r"然后", r"配置", r"日志", r"接口", r"原因",
+        ]
+        return any(re.search(pattern, text, flags=re.IGNORECASE) for pattern in patterns)
+
+    @staticmethod
+    def _extract_topic_tokens(content: str) -> set[str]:
+        text = str(content or "").lower()
+        tokens = set(re.findall(r"[a-z0-9_\\-]{3,}", text))
+        keywords = [
+            "openclaw", "qdrant", "ollama", "docker", "python", "api", "插件", "机器人", "模型",
+            "日志", "配置", "报错", "部署", "联网", "图片", "记忆", "群聊", "dota", "战绩",
+        ]
+        for keyword in keywords:
+            if keyword in text:
+                tokens.add(keyword)
+        return tokens
+
     @staticmethod
     def _clean_display_name(sender_name: str) -> str:
         import re