feat(annotation): 优化知识集合同步服务逻辑

- 添加 KNOWLEDGE_SET_LIST_SIZE 常量配置知识集列表大小为50
- 实现现有知识集名称检查避免重复创建
- 添加 _list_knowledge_sets 方法用于查询知识集列表
- 实现 _parse_metadata 和 _metadata_matches_project 方法解析匹配项目元数据
- 添加 _find_knowledge_set_by_name 方法按名称查找知识集
- 优化知识集创建流程增加重试和回退机制
- 实现项目配置更新保存知识集ID和名称信息

runtime/datamate-python/app/module/annotation/service/knowledge_sync.py

@@ -21,6 +21,7 @@ class KnowledgeSyncService:
 
     CONFIG_KEY_SET_ID = "knowledge_set_id"
     CONFIG_KEY_SET_NAME = "knowledge_set_name"
+    KNOWLEDGE_SET_LIST_SIZE = 50
 
     def __init__(self, db: AsyncSession):
         self.db = db
@@ -84,10 +85,30 @@ class KnowledgeSyncService:
         base_name = dataset_name.strip() or "annotation-project"
         metadata = self._build_set_metadata(project)
 
+        existing = await self._find_knowledge_set_by_name(base_name, project)
+        if existing:
+            await self._update_project_config(
+                project,
+                {
+                    self.CONFIG_KEY_SET_ID: existing.get("id"),
+                    self.CONFIG_KEY_SET_NAME: existing.get("name"),
+                },
+            )
+            return existing.get("id")
+
         created = await self._create_knowledge_set(base_name, metadata)
+        if not created:
+            created = await self._find_knowledge_set_by_name(base_name, project)
+
         if not created:
             fallback_name = self._build_fallback_set_name(base_name, project.id)
+            existing = await self._find_knowledge_set_by_name(fallback_name, project)
+            if existing:
+                created = existing
+            else:
                 created = await self._create_knowledge_set(fallback_name, metadata)
+                if not created:
+                    created = await self._find_knowledge_set_by_name(fallback_name, project)
 
         if not created:
             return None
@@ -109,6 +130,66 @@ class KnowledgeSyncService:
                 return None
             raise
 
+    async def _list_knowledge_sets(self, keyword: Optional[str]) -> list[Dict[str, Any]]:
+        params: Dict[str, Any] = {
+            "page": 0,
+            "size": self.KNOWLEDGE_SET_LIST_SIZE,
+        }
+        if keyword:
+            params["keyword"] = keyword
+        try:
+            data = await self._request("GET", "/data-management/knowledge-sets", params=params)
+        except httpx.HTTPStatusError as exc:
+            logger.warning(
+                "查询知识集失败：keyword=%s status=%s",
+                keyword,
+                exc.response.status_code,
+            )
+            return []
+        if not isinstance(data, dict):
+            return []
+        content = data.get("content")
+        if not isinstance(content, list):
+            return []
+        return [item for item in content if isinstance(item, dict)]
+
+    def _parse_metadata(self, metadata: Any) -> Optional[Dict[str, Any]]:
+        if not isinstance(metadata, str) or not metadata.strip():
+            return None
+        try:
+            parsed = json.loads(metadata)
+        except Exception:
+            return None
+        return parsed if isinstance(parsed, dict) else None
+
+    def _metadata_matches_project(self, metadata: Any, project: LabelingProject) -> bool:
+        parsed = self._parse_metadata(metadata)
+        if not parsed:
+            return False
+        return (
+            parsed.get("source") == "annotation"
+            and parsed.get("project_id") == project.id
+            and parsed.get("dataset_id") == project.dataset_id
+        )
+
+    async def _find_knowledge_set_by_name(
+        self,
+        name: str,
+        project: LabelingProject,
+    ) -> Optional[Dict[str, Any]]:
+        if not name:
+            return None
+        items = await self._list_knowledge_sets(name)
+        if not items:
+            return None
+        exact_matches = [item for item in items if item.get("name") == name]
+        if not exact_matches:
+            return None
+        for item in exact_matches:
+            if self._metadata_matches_project(item.get("metadata"), project):
+                return item
+        return exact_matches[0]
+
     async def _create_knowledge_set(self, name: str, metadata: str) -> Optional[Dict[str, Any]]:
         payload = {
             "name": name,