feat: add agent response depth control

ai_knowledge_base_v2/apps/backend/app/services/agent_debug_service.py

@@ -30,6 +30,7 @@ class AgentDebugService:
             version_overrides=payload.knowledgeVersions,
             preview_knowledge_ids=payload.knowledgeIds,
             prompt_override=payload.promptContent,
+            response_depth=payload.responseDepth,
         )
         return RagResult(
             question=rag_result.question,

ai_knowledge_base_v2/apps/backend/app/services/knowledge_agent_service.py

@@ -84,6 +84,7 @@ class KnowledgeAgentService:
         preview_knowledge_ids: list[int] | None = None,
         context_trace: list[dict] | None = None,
         prompt_override: str | None = None,
+        response_depth: int | None = None,
     ) -> RagResult:
         started = perf_counter()
         catalog = cls.get_knowledge_catalog(
@@ -207,6 +208,7 @@ class KnowledgeAgentService:
                 session_summary,
                 summary_up_to_message_id,
                 prompt_override=prompt_override,
+                response_depth=response_depth,
             )
             return RagResult(
                 question=question,

ai_knowledge_base_v2/apps/backend/app/services/rag_service.py

@@ -11,6 +11,7 @@ from app.models.user import User
 from app.services.chat_context_service import ChatContextService
 from app.services.feishu_service import FeishuKnowledgeService
 from app.services.knowledge_service import KnowledgeAccessService, KnowledgeScope
+from app.services.response_style_service import ResponseStyleService
 
 NO_HIT_ANSWER = "当前知识库中未检索到相关内容，请联系管理员补充相关知识。"
 
@@ -119,6 +120,7 @@ class PromptService:
         session_summary: str | None = None,
         summary_up_to_message_id: int | None = None,
         prompt_override: str | None = None,
+        response_depth: int | None = None,
     ) -> list[dict[str, str]]:
         prompt = prompt_override.strip() if prompt_override and prompt_override.strip() else cls._load_active_prompt(db)
 
@@ -135,7 +137,8 @@ class PromptService:
                 + "[不可关闭的最低安全规则 v1]\n"
                 + "现实危险、自伤伤人风险应优先建议立即寻求线下专业帮助；医疗、法律、财务问题不得给出替代专业意见的结论；"
                 + "不得伪造老师观点或课程内容；不得输出整篇课程文章、大段连续原文，也不得通过多轮拼接还原完整资料。"
-                + cls._knowledge_type_rules(chunks),
+                + cls._knowledge_type_rules(chunks)
+                + ResponseStyleService.build_instruction(db, response_depth),
             }
         ]
 

ai_knowledge_base_v2/apps/backend/app/services/response_style_service.py

@@ -0,0 +1,68 @@
+from __future__ import annotations
+
+from sqlalchemy import select
+from sqlalchemy.orm import Session
+
+from app.models.ai_config import SystemConfig
+
+
+RESPONSE_DEPTH_KEY = "agent_response_depth"
+DEFAULT_RESPONSE_DEPTH = 35
+MIN_RESPONSE_DEPTH = 0
+MAX_RESPONSE_DEPTH = 100
+
+
+class ResponseStyleService:
+    @staticmethod
+    def get_depth(db: Session) -> int:
+        config = db.scalar(select(SystemConfig).where(SystemConfig.config_key == RESPONSE_DEPTH_KEY))
+        if config is None:
+            return DEFAULT_RESPONSE_DEPTH
+        try:
+            return _clamp_depth(int(config.config_value))
+        except (TypeError, ValueError):
+            return DEFAULT_RESPONSE_DEPTH
+
+    @staticmethod
+    def set_depth(db: Session, depth: int, admin_id: int | None) -> SystemConfig:
+        config = db.scalar(select(SystemConfig).where(SystemConfig.config_key == RESPONSE_DEPTH_KEY))
+        if config is None:
+            config = SystemConfig(config_key=RESPONSE_DEPTH_KEY, config_value=str(DEFAULT_RESPONSE_DEPTH))
+        config.config_value = str(_clamp_depth(depth))
+        config.description = "Agent 回答深度，0 为精简，100 为深入"
+        config.updated_by = admin_id
+        db.add(config)
+        return config
+
+    @classmethod
+    def build_instruction(cls, db: Session, depth: int | None = None) -> str:
+        value = _clamp_depth(cls.get_depth(db) if depth is None else depth)
+        if value <= 33:
+            mode = "精简"
+            rules = (
+                "回答要短，通常控制在1到3段或3条以内；不展开心理分析、不复盘学员长篇经历，"
+                "优先给出一句方向确认，再引导回到当下、身体感受和情绪觉察。建议只给当下最小一步，"
+                "避免连续列出多个深入方案。"
+            )
+        elif value <= 66:
+            mode = "平衡"
+            rules = (
+                "回答保持适中，可以先确认方向，再补充必要原因和1到3个可执行提醒；"
+                "不做过度拆解，不把分析过程完整罗列出来。"
+            )
+        else:
+            mode = "深入"
+            rules = (
+                "可以更完整地解释原因、步骤和注意事项，但仍要避免变成咨询式长篇分析；"
+                "优先围绕回到当下、回到自身、觉察情绪和身体感受、如是释放来组织内容。"
+            )
+        return (
+            "\n\n[回答深度控制]\n"
+            f"当前回答深度：{value}/100（{mode}）。{rules}"
+            "无论深度如何，都不要暴露内部分析过程；不要替学员做复杂人格判断；"
+            "涉及功课反馈时，先判断方向是否偏离，再给最少必要的下一步。"
+        )
+
+
+def _clamp_depth(value: int) -> int:
+    return max(MIN_RESPONSE_DEPTH, min(MAX_RESPONSE_DEPTH, value))