add .gitattributes: python文件统一LF换行

agent/advisor_agent/intent/classifier.py

@@ -49,6 +49,7 @@ _CLASSIFIER_PROMPT = """你是基金投顾工作台的意图分类器，只负
 """
 
 _RECOMMENDATION_TERMS = ("推荐", "组合建议", "配置建议", "买什么", "适合配置", "筛选基金", "投资方案")
+_SCOPE_ERROR_MESSAGE = "投顾范围查询仅支持客户数据查询"
 
 
 def _rule_fallback(query: str | None) -> IntentClassification:
@@ -94,6 +95,13 @@ async def classify_advisor_intent(
         return IntentClassification(explicit_intent, 1.0, "explicit", "客户端显式指定")
     if not query or not query.strip():
         return IntentClassification("", 0.0, "fallback", "空输入")
+    if re.sub(r"\s+", "", query) == _SCOPE_ERROR_MESSAGE:
+        return IntentClassification(
+            AGENT_INTENT_CASUAL_CHAT,
+            1.0,
+            "rule",
+            "识别为系统提示文本而非业务查询",
+        )
     if llm_client is not None:
         try:
             raw = await asyncio.wait_for(
@@ -114,7 +122,7 @@ async def classify_advisor_intent(
                 rule_intent = recognize_advisor_intent(query)
                 if (
                     rule_intent == AGENT_INTENT_DATA_QUERY
-                    and parsed.intent == AGENT_INTENT_RECOMMEND
+                    and parsed.intent != AGENT_INTENT_DATA_QUERY
                     and not any(term in (query or "") for term in _RECOMMENDATION_TERMS)
                 ):
                     return IntentClassification(

agent/advisor_agent/intent/recognizer.py

@@ -40,6 +40,8 @@ _REBALANCE_TERMS = ("调仓", "再平衡", "组合调整", "配置偏离", "偏
 _FUND_ANALYSIS_TERMS = ("基金分析", "分析基金", "基金表现", "净值走势", "最大回撤", "夏普比率", "年化波动")
 _DIALOGUE_TERMS = ("话术", "沟通", "怎么跟客户说", "如何向客户解释", "安抚客户", "投诉处理")
 _RECOMMEND_TERMS = ("推荐", "组合建议", "配置建议", "买什么", "适合配置", "筛选基金", "投资方案")
+_CUSTOMER_IDENTITY_TERMS = ("是谁", "姓名", "实名", "基本信息", "联系方式", "手机号")
+_SCOPE_ERROR_MESSAGE = "投顾范围查询仅支持客户数据查询"
 
 
 def _contains_any(text: str, terms: tuple[str, ...]) -> bool:
@@ -57,6 +59,8 @@ def recognize_advisor_intent(query: str | None, explicit_intent: str | None = No
     text = re.sub(r"\s+", "", query or "")
     if not text:
         return None
+    if text == _SCOPE_ERROR_MESSAGE:
+        return None
 
     # 先处理最明确的任务词，避免“查询基金收益”被误判成普通数据查询。
     if _contains_any(text, _REBALANCE_TERMS):
@@ -68,6 +72,13 @@ def recognize_advisor_intent(query: str | None, explicit_intent: str | None = No
 
     has_action = any(term in text for term in _QUERY_ACTIONS)
     has_data = any(term in text for term in _DATA_TERMS)
+    has_customer_identity = (
+        "客户" in text
+        and _contains_any(text, _CUSTOMER_IDENTITY_TERMS)
+        and not _contains_any(text, _RECOMMEND_TERMS)
+    )
+    if has_customer_identity:
+        return AGENT_INTENT_DATA_QUERY
     if has_data and (has_action or "客户" in text or "近一年" in text or "本月" in text):
         return AGENT_INTENT_DATA_QUERY
     if _contains_any(text, _RECOMMEND_TERMS):