refactor: 优化代码格式和结构，改进错误提示信息

- 统一代码格式，移除多余空格和注释
- 改进MySQL连接错误提示信息
- 优化GraphDatabase查询格式和响应结构
- 简化测试用例参数传递方式
- 调整前端GraphCanvas组件样式

Author: xerrors

server/routers/graph_router.py

@@ -57,29 +57,33 @@ async def get_graphs(current_user: User = Depends(get_admin_user)):
         # 1. 获取默认 Neo4j 图谱信息
         neo4j_info = graph_base.get_graph_info()
         if neo4j_info:
-            graphs.append({
-                "id": "neo4j",
-                "name": "默认图谱",
-                "type": "neo4j",
-                "description": "Default graph database for uploaded documents",
-                "status": neo4j_info.get("status", "unknown"),
-                "created_at": neo4j_info.get("last_updated"),
-                "node_count": neo4j_info.get("entity_count", 0),
-                "edge_count": neo4j_info.get("relationship_count", 0)
-            })
+            graphs.append(
+                {
+                    "id": "neo4j",
+                    "name": "默认图谱",
+                    "type": "neo4j",
+                    "description": "Default graph database for uploaded documents",
+                    "status": neo4j_info.get("status", "unknown"),
+                    "created_at": neo4j_info.get("last_updated"),
+                    "node_count": neo4j_info.get("entity_count", 0),
+                    "edge_count": neo4j_info.get("relationship_count", 0),
+                }
+            )
 
         # 2. 获取 LightRAG 数据库信息
         lightrag_dbs = knowledge_base.get_lightrag_databases()
         for db in lightrag_dbs:
-            graphs.append({
-                "id": db.get("db_id"),
-                "name": db.get("name"),
-                "type": "lightrag",
-                "description": db.get("description"),
-                "status": "active",  # LightRAG DBs are usually active if listed
-                "created_at": db.get("created_at"),
-                "metadata": db
-            })
+            graphs.append(
+                {
+                    "id": db.get("db_id"),
+                    "name": db.get("name"),
+                    "type": "lightrag",
+                    "description": db.get("description"),
+                    "status": "active",  # LightRAG DBs are usually active if listed
+                    "created_at": db.get("created_at"),
+                    "metadata": db,
+                }
+            )
 
         return {"success": True, "data": graphs}
 
@@ -118,7 +122,7 @@ async def get_subgraph(
             keyword=node_label,
             max_depth=max_depth,
             max_nodes=max_nodes,
-            kgdb_name=db_id if not knowledge_base.is_lightrag_database(db_id) else "neo4j"
+            kgdb_name=db_id if not knowledge_base.is_lightrag_database(db_id) else "neo4j",
         )
 
         return {
@@ -136,8 +140,7 @@ async def get_subgraph(
 
 @graph.get("/labels")
 async def get_graph_labels(
-    db_id: str = Query(..., description="知识图谱ID"),
-    current_user: User = Depends(get_admin_user)
+    db_id: str = Query(..., description="知识图谱ID"), current_user: User = Depends(get_admin_user)
 ):
     """
     获取图谱的所有标签
@@ -154,8 +157,7 @@ async def get_graph_labels(
 
 @graph.get("/stats")
 async def get_graph_stats(
-    db_id: str = Query(..., description="知识图谱ID"),
-    current_user: User = Depends(get_admin_user)
+    db_id: str = Query(..., description="知识图谱ID"), current_user: User = Depends(get_admin_user)
 ):
     """
     获取图谱统计信息
@@ -175,23 +177,22 @@ async def get_graph_stats(
                 entity_types[entity_type] = entity_types.get(entity_type, 0) + 1
 
             entity_types_list = [
-                {"type": k, "count": v}
-                for k, v in sorted(entity_types.items(), key=lambda x: x[1], reverse=True)
+                {"type": k, "count": v} for k, v in sorted(entity_types.items(), key=lambda x: x[1], reverse=True)
             ]
 
             return {
                 "success": True,
                 "data": {
                     "total_nodes": len(knowledge_graph.nodes),
                     "total_edges": len(knowledge_graph.edges),
-                    "entity_types": entity_types_list
-                }
+                    "entity_types": entity_types_list,
+                },
             }
         else:
             # Neo4j stats
             info = graph_base.get_graph_info(graph_name=db_id)
             if not info:
-                 raise HTTPException(status_code=404, detail="Graph info not found")
+                raise HTTPException(status_code=404, detail="Graph info not found")
 
             return {
                 "success": True,
@@ -200,11 +201,8 @@ async def get_graph_stats(
                     "total_edges": info.get("relationship_count", 0),
                     # Neo4j info currently returns 'labels' list, not counts per label.
                     # Improving this would require updating GraphDatabase.get_graph_info
-                    "entity_types": [
-                        {"type": label, "count": "N/A"}
-                        for label in info.get("labels", [])
-                    ]
-                }
+                    "entity_types": [{"type": label, "count": "N/A"} for label in info.get("labels", [])],
+                },
             }
 
     except Exception as e:
@@ -227,11 +225,7 @@ async def get_lightrag_subgraph(
 ):
     """(Deprecated) Use /graph/subgraph instead"""
     return await get_subgraph(
-        db_id=db_id,
-        node_label=node_label,
-        max_depth=max_depth,
-        max_nodes=max_nodes,
-        current_user=current_user
+        db_id=db_id, node_label=node_label, max_depth=max_depth, max_nodes=max_nodes, current_user=current_user
     )
 
 

src/agents/common/toolkits/mysql/tools.py

@@ -38,7 +38,9 @@ def get_connection_manager() -> MySQLConnectionManager:
         required_keys = ["host", "user", "password", "database"]
         for key in required_keys:
             if not mysql_config[key]:
-                raise MySQLConnectionError(f"MySQL configuration missing required key: {key}")
+                raise MySQLConnectionError(
+                    f"MySQL configuration missing required key: {key}, please check your environment variables."
+                )
 
         _connection_manager = MySQLConnectionManager(mysql_config)
     return _connection_manager

src/knowledge/adapters/lightrag.py

@@ -63,7 +63,7 @@ def normalize_node(self, raw_node: Any) -> dict[str, Any]:
         # 优先使用 entity_id 作为显示名称，因为 Neo4j 中 LightRAG 存储的实体名称在 entity_id 字段
         # 如果不存在，则回退到 id
         name = properties.get("entity_id", node_id)
-        
+
         # 尝试从 properties 获取 entity_type，或者从 labels 中推断（排除 kb_ 前缀的 label）
         entity_type = properties.get("entity_type", "unknown")
         if entity_type == "unknown" and labels:
@@ -73,12 +73,7 @@ def normalize_node(self, raw_node: Any) -> dict[str, Any]:
                     break
 
         return self._create_standard_node(
-            node_id=node_id,
-            name=name,
-            entity_type=entity_type,
-            labels=labels,
-            properties=properties,
-            source="lightrag"
+            node_id=node_id, name=name, entity_type=entity_type, labels=labels, properties=properties, source="lightrag"
         )
 
     def normalize_edge(self, raw_edge: Any) -> dict[str, Any]:
@@ -102,7 +97,7 @@ def normalize_edge(self, raw_edge: Any) -> dict[str, Any]:
         properties = getattr(raw_edge, "properties", {})
         if not properties and hasattr(raw_edge, "get"):
             properties = raw_edge.get("properties", {})
-            
+
         # 优化边的显示类型
         # LightRAG 的边类型通常是 "DIRECTED"，具体含义在 keywords 或 description 中
         display_type = edge_type
@@ -116,14 +111,10 @@ def normalize_edge(self, raw_edge: Any) -> dict[str, Any]:
                 if len(desc) < 20:
                     display_type = desc
                 else:
-                    display_type = "related" # fallback
+                    display_type = "related"  # fallback
 
         return self._create_standard_edge(
-            edge_id=edge_id,
-            source_id=source,
-            target_id=target,
-            edge_type=display_type,
-            properties=properties
+            edge_id=edge_id, source_id=source, target_id=target, edge_type=display_type, properties=properties
         )
 
     async def get_labels(self) -> list[str]:

src/knowledge/adapters/upload.py

@@ -19,15 +19,12 @@ def __init__(self, graph_db_instance: GraphDatabase, config: dict[str, Any] = No
 
     async def query_nodes(self, keyword: str, **kwargs) -> dict[str, Any]:
         params = self._normalize_query_params(keyword, kwargs)
-        
+
         # 如果关键词是 "*" 或者为空，则执行采样查询
         if not params["keyword"] or params["keyword"] == "*":
             # 映射 max_nodes 到 num
             num = kwargs.get("max_nodes", 100)
-            raw_results = self.graph_db.get_sample_nodes(
-                kgdb_name=params.get("kgdb_name", "neo4j"),
-                num=num
-            )
+            raw_results = self.graph_db.get_sample_nodes(kgdb_name=params.get("kgdb_name", "neo4j"), num=num)
         else:
             # 否则执行关键词搜索
             # graph_db.query_node is sync
@@ -66,7 +63,7 @@ def normalize_node(self, raw_node: Any) -> dict[str, Any]:
             entity_type="entity",
             labels=["Entity", "Upload"],
             properties=raw_node,
-            source="upload"
+            source="upload",
         )
 
     def normalize_edge(self, raw_edge: Any) -> dict[str, Any]:
@@ -83,7 +80,7 @@ def normalize_edge(self, raw_edge: Any) -> dict[str, Any]:
             source_id=raw_edge.get("source_id"),
             target_id=raw_edge.get("target_id"),
             edge_type=raw_edge.get("type"),
-            properties=raw_edge
+            properties=raw_edge,
         )
 
     async def get_labels(self) -> list[str]:

src/knowledge/graph.py

@@ -68,15 +68,15 @@ def _process_record_props(record):
             """处理记录中的属性：扁平化 properties 并移除 embedding"""
             if record is None:
                 return None
-            
+
             # 复制一份以避免修改原字典
             data = dict(record)
             props = data.pop("properties", {}) or {}
-            
+
             # 移除 embedding
             if "embedding" in props:
                 del props["embedding"]
-            
+
             # 合并属性（优先保留原字典中的 id, name, type 等核心字段）
             return {**props, **data}
 
@@ -657,15 +657,15 @@ def _process_record_props(record):
             """处理记录中的属性：扁平化 properties 并移除 embedding"""
             if record is None:
                 return None
-            
+
             # 复制一份以避免修改原字典
             data = dict(record)
             props = data.pop("properties", {}) or {}
-            
+
             # 移除 embedding
             if "embedding" in props:
                 del props["embedding"]
-            
+
             # 合并属性（优先保留原字典中的 id, name, type 等核心字段）
             return {**props, **data}
 
@@ -676,22 +676,46 @@ def query(tx, entity_name, hops, limit):
                     // 1跳出边
                     [(n {name: $entity_name})-[r1]->(m1) |
                      {h: {id: elementId(n), name: n.name, properties: properties(n)},
-                      r: {id: elementId(r1), type: r1.type, source_id: elementId(n), target_id: elementId(m1), properties: properties(r1)},
+                      r: {
+                        id: elementId(r1),
+                        type: r1.type,
+                        source_id: elementId(n),
+                        target_id: elementId(m1),
+                        properties: properties(r1)
+                      },
                       t: {id: elementId(m1), name: m1.name, properties: properties(m1)}}],
                     // 2跳出边
                     [(n {name: $entity_name})-[r1]->(m1)-[r2]->(m2) |
                      {h: {id: elementId(m1), name: m1.name, properties: properties(m1)},
-                      r: {id: elementId(r2), type: r2.type, source_id: elementId(m1), target_id: elementId(m2), properties: properties(r2)},
+                      r: {
+                        id: elementId(r2),
+                        type: r2.type,
+                        source_id: elementId(m1),
+                        target_id: elementId(m2),
+                        properties: properties(r2)
+                      },
                       t: {id: elementId(m2), name: m2.name, properties: properties(m2)}}],
                     // 1跳入边
                     [(m1)-[r1]->(n {name: $entity_name}) |
                      {h: {id: elementId(m1), name: m1.name, properties: properties(m1)},
-                      r: {id: elementId(r1), type: r1.type, source_id: elementId(m1), target_id: elementId(n), properties: properties(r1)},
+                      r: {
+                        id: elementId(r1),
+                        type: r1.type,
+                        source_id: elementId(m1),
+                        target_id: elementId(n),
+                        properties: properties(r1)
+                      },
                       t: {id: elementId(n), name: n.name, properties: properties(n)}}],
                     // 2跳入边
                     [(m2)-[r2]->(m1)-[r1]->(n {name: $entity_name}) |
                      {h: {id: elementId(m2), name: m2.name, properties: properties(m2)},
-                      r: {id: elementId(r2), type: r2.type, source_id: elementId(m2), target_id: elementId(m1), properties: properties(r2)},
+                      r: {
+                        id: elementId(r2),
+                        type: r2.type,
+                        source_id: elementId(m2),
+                        target_id: elementId(m1),
+                        properties: properties(r2)
+                      },
                       t: {id: elementId(m1), name: m1.name, properties: properties(m1)}}]
                 ] AS all_results
                 UNWIND all_results AS result_list
@@ -711,7 +735,7 @@ def query(tx, entity_name, hops, limit):
                     h = _process_record_props(item["h"])
                     r = _process_record_props(item["r"])
                     t = _process_record_props(item["t"])
-                    
+
                     formatted_results["nodes"].extend([h, t])
                     formatted_results["edges"].append(r)
                     formatted_results["triples"].append((h["name"], r["type"], t["name"]))

src/knowledge/implementations/lightrag.py

@@ -235,7 +235,7 @@ def _get_embedding_func(self, embed_info: dict):
                 model=model_name,
                 api_key=config_dict["api_key"],
                 base_url=config_dict["base_url"].replace("/embeddings", ""),
-            )
+            ),
         )
 
     async def add_content(self, db_id: str, items: list[str], params: dict | None = None) -> list[dict]: