feat(backend): knowledge iteration + vision + neo4j + response contract source

dependencies.py 拆分为 dependencies/ 包; 新增 vision/ragflow_ingestion/neo4j 客户端与 h5_ai_task; alembic 045 图置信度迁移; 响应契约统一收尾。
2026-07-09 11:47:16 +08:00
parent f5374fce9b
commit ead5f83bee
39 changed files with 5276 additions and 545 deletions
@@ -54,6 +54,34 @@ class WingmanService:
        "输出格式：{\"suggested_tags\": [\"标签1\", \"标签2\"], \"category\": \"分类\", \"priority\": \"low/medium/high\"}"
    )

+    # --------------------------------------------------------------------------
+    # 知识建议生成专用 Prompt（Tier0 / T03 — 通道 A/B 复用）
+    # --------------------------------------------------------------------------
+    _KNOWLEDGE_SUGGESTION_PROMPT: str = (
+        "你是一个IT知识库优化助手，基于对话上下文分析知识库的不足，"
+        "生成结构化的知识库优化建议。\n\n"
+        "分析以下对话，判断是否需要新增FAQ或更新已有知识条目。\n"
+        "如果AI回复被标记为无用，生成更新建议；如果AI无法解决需转人工，生成新增FAQ建议。\n\n"
+        "必须以JSON格式输出，包含以下字段：\n"
+        "- suggestion_type: 建议类型，\"new_faq\" 或 \"update\"\n"
+        "- title: 问题标题（简洁明了）\n"
+        "- content: 答案内容（分步骤、可操作）\n"
+        "- category: 分类，只能是 硬件/软件/网络/安全/账号/其他 之一\n"
+        "- tags: 标签列表，如 [\"VPN\", \"连接\"]\n"
+        "- confidence: 你对这个建议的信心度，0.0-1.0之间\n"
+        "- issue: 对应的Neo4j图问题节点名称，如\"VPN问题\"\n"
+        "- action: 对应的Neo4j图动作节点名称，如\"VPN连接修复\"\n"
+        "- relation_type: 图关系类型，\"LEADS_TO\" 或 \"RELATES_TO\"\n"
+        "- parent_issue: 父问题名称（如果没有则为空字符串）\n\n"
+        "输出格式示例：\n"
+        "{\"suggestion_type\": \"new_faq\", \"title\": \"VPN连不上怎么办\", "
+        "\"content\": \"1.检查网络连接 2.重启VPN客户端 3.联系IT支持\", "
+        "\"category\": \"网络\", \"tags\": [\"VPN\", \"连接\"], "
+        "\"confidence\": 0.86, \"issue\": \"VPN问题\", "
+        "\"action\": \"VPN连接修复\", \"relation_type\": \"LEADS_TO\", "
+        "\"parent_issue\": \"网络问题\"}"
+    )
+
    def __init__(self):
        """初始化 Wingman 服务。

@@ -264,6 +292,101 @@ class WingmanService:
            logger.error(f"Wingman 标签建议失败: {e}")
            return default_tags

+    # --------------------------------------------------------------------------
+    # 核心方法 4：生成知识库优化建议（Tier0 / T03 — 复用现有范式）
+    # --------------------------------------------------------------------------
+    async def generate_knowledge_suggestion(
+        self,
+        context_messages: List[Dict[str, Any]],
+    ) -> Dict[str, Any]:
+        """生成知识库优化建议（用于知识库自动迭代）。
+
+        传入对话上下文，让 Wingman Agent 分析并生成结构化的知识库优化建议。
+        复用 _build_context_messages + _call_wingman_api + _parse_json_response 范式。
+
+        Args:
+            context_messages: 对话消息历史列表
+
+        Returns:
+            Dict: {
+                "suggestion_type": str,   # "new_faq" / "update"
+                "title": str,             # 问题标题
+                "content": str,           # 答案内容
+                "category": str,          # 分类
+                "tags": list[str],        # 标签列表
+                "confidence": float,      # 置信度（0.0-1.0）
+                "issue": str,             # 图节点：问题名称
+                "action": str,            # 图节点：动作名称
+                "relation_type": str,     # 图关系类型
+                "parent_issue": str,      # 父 Issue 名称
+            }
+        """
+        # 构建对话上下文消息列表（使用知识建议专用 Prompt）
+        context = self._build_context_messages(
+            context_messages, self._KNOWLEDGE_SUGGESTION_PROMPT
+        )
+
+        # 默认建议（降级时使用）
+        default_suggestion: Dict[str, Any] = {
+            "suggestion_type": "new_faq",
+            "title": "",
+            "content": "",
+            "category": "其他",
+            "tags": [],
+            "confidence": 0.0,
+            "issue": "",
+            "action": "",
+            "relation_type": "LEADS_TO",
+            "parent_issue": "",
+        }
+
+        try:
+            result = await self._call_wingman_api(context)
+
+            if result is None:
+                logger.warning("Wingman 知识建议生成失败（API 返回 None）")
+                return default_suggestion
+
+            # 尝试解析 JSON 格式的建议
+            parsed = self._parse_json_response(result, default_suggestion)
+
+            # 规范化字段
+            suggestion: Dict[str, Any] = {
+                "suggestion_type": parsed.get(
+                    "suggestion_type", default_suggestion["suggestion_type"]
+                ),
+                "title": parsed.get("title", default_suggestion["title"]),
+                "content": parsed.get("content", default_suggestion["content"]),
+                "category": parsed.get("category", default_suggestion["category"]),
+                "tags": parsed.get("tags", default_suggestion["tags"]),
+                "confidence": float(parsed.get("confidence", 0.0)),
+                "issue": parsed.get("issue", default_suggestion["issue"]),
+                "action": parsed.get("action", default_suggestion["action"]),
+                "relation_type": parsed.get(
+                    "relation_type", default_suggestion["relation_type"]
+                ),
+                "parent_issue": parsed.get(
+                    "parent_issue", default_suggestion["parent_issue"]
+                ),
+            }
+
+            # 如果 Dify 未返回 confidence，使用启发式估算
+            if suggestion["confidence"] == 0.0:
+                suggestion["confidence"] = self._estimate_confidence(
+                    suggestion["content"]
+                )
+
+            logger.info(
+                f"知识建议生成完成: type={suggestion['suggestion_type']}, "
+                f"title={suggestion['title'][:50]}, "
+                f"confidence={suggestion['confidence']}"
+            )
+            return suggestion
+
+        except Exception as e:
+            logger.error(f"Wingman 知识建议生成异常: {e}")
+            return default_suggestion
+
    # --------------------------------------------------------------------------
    # 内部方法
    # --------------------------------------------------------------------------