From 2c8ac93e78f7ba75c40aa502a678b379e0bdd591 Mon Sep 17 00:00:00 2001 From: GitHub Actions Date: Mon, 15 Dec 2025 03:07:17 +0000 Subject: [PATCH 1/6] style: auto-format with ruff [skip ci] --- src/knowledge/graph.py | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/src/knowledge/graph.py b/src/knowledge/graph.py index 4b611f18..1651f215 100644 --- a/src/knowledge/graph.py +++ b/src/knowledge/graph.py @@ -9,7 +9,7 @@ from neo4j import GraphDatabase as GD from src import config from src.models import select_embedding_model -from src.storage.minio.client import get_minio_client, StorageError +from src.storage.minio.client import get_minio_client from src.utils import logger from src.utils.datetime_utils import utc_isoformat @@ -355,12 +355,12 @@ class GraphDatabase: temp_file_path = None try: - if parsed_url.scheme in ('http', 'https'): # 如果是 URL + if parsed_url.scheme in ("http", "https"): # 如果是 URL logger.info(f"检测到 URL，正在从 MinIO 下载文件: {file_path}") # 从 URL 解析 bucket_name 和 object_name # URL 格式: http://host:port/bucket_name/object_name - path_parts = parsed_url.path.lstrip('/').split('/', 1) + path_parts = parsed_url.path.lstrip("/").split("/", 1) if len(path_parts) < 2: raise ValueError(f"无法解析 MinIO URL: {file_path}") @@ -372,8 +372,10 @@ class GraphDatabase: file_data = await minio_client.adownload_file(bucket_name, object_name) # 创建临时文件保存下载的内容 - with tempfile.NamedTemporaryFile(mode='w', suffix='.jsonl', delete=False, encoding='utf-8') as temp_file: - temp_file.write(file_data.decode('utf-8')) + with tempfile.NamedTemporaryFile( + mode="w", suffix=".jsonl", delete=False, encoding="utf-8" + ) as temp_file: + temp_file.write(file_data.decode("utf-8")) temp_file_path = temp_file.name logger.info(f"文件已下载到临时路径: {temp_file_path}") From 225ccce69c1aae46f46c2efa08fcd8a4b30542ed Mon Sep 17 00:00:00 2001 From: Wenjie Zhang Date: Mon, 15 Dec 2025 13:35:24 +0800 Subject: [PATCH 2/6] =?UTF-8?q?fix(embedding):=20=E4=BF=AE=E5=A4=8D?= =?UTF-8?q?=E5=B5=8C=E5=85=A5=E6=A8=A1=E5=9E=8B=E9=85=8D=E7=BD=AE=E4=B8=AD?= =?UTF-8?q?=E7=9A=84=E5=85=BC=E5=AE=B9=E6=80=A7=E9=97=AE=E9=A2=98?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - 修复 get_embedding_config 中对 model/name 字段的兼容性处理 - 改进错误处理和日志记录 - 支持多种配置格式以保持向后兼容性 - 修复 lightrag.py 中 embedding 函数的模型名称获取逻辑 --- src/knowledge/implementations/lightrag.py | 12 ++++- src/knowledge/utils/kb_utils.py | 64 +++++++++++++++-------- 2 files changed, 53 insertions(+), 23 deletions(-) diff --git a/src/knowledge/implementations/lightrag.py b/src/knowledge/implementations/lightrag.py index 08feed01..cdddd5f2 100644 --- a/src/knowledge/implementations/lightrag.py +++ b/src/knowledge/implementations/lightrag.py @@ -200,6 +200,7 @@ class LightRagKB(KnowledgeBase): def _get_embedding_func(self, embed_info: dict): """获取 embedding 函数""" config_dict = get_embedding_config(embed_info) + logger.debug(f"Embedding config dict: {config_dict}") if config_dict.get("model_id") and config_dict["model_id"].startswith("ollama"): from lightrag.llm.ollama import ollama_embed @@ -219,15 +220,22 @@ class LightRagKB(KnowledgeBase): ), ) + # 尝试获取模型名称，支持多种键名以保持兼容性 + if "name" in config_dict and config_dict["name"]: + model_name = config_dict["name"] + elif "model" in config_dict and config_dict["model"]: + model_name = config_dict["model"] + else: + raise ValueError(f"Neither 'name' nor 'model' found in config_dict or both are empty: {config_dict}") return EmbeddingFunc( embedding_dim=config_dict["dimension"], max_token_size=8192, func=lambda texts: openai_embed( texts=texts, - model=config_dict["model"], + 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]: diff --git a/src/knowledge/utils/kb_utils.py b/src/knowledge/utils/kb_utils.py index ac9411ed..d955fffd 100644 --- a/src/knowledge/utils/kb_utils.py +++ b/src/knowledge/utils/kb_utils.py @@ -289,30 +289,52 @@ def get_embedding_config(embed_info: dict) -> dict: Returns: dict: 标准化的嵌入配置 """ - config_dict = {} - try: - if embed_info: - # 优先检查是否有 model_id 字段 - if "model_id" in embed_info: - return config.embed_model_names[embed_info["model_id"]].model_dump() - elif hasattr(embed_info, "name") and isinstance(embed_info, EmbedModelInfo): - return embed_info.model_dump() - else: - # 字典形式（保持向后兼容） - config_dict["model"] = embed_info["name"] - config_dict["api_key"] = os.getenv(embed_info["api_key"]) or embed_info["api_key"] - config_dict["base_url"] = embed_info["base_url"] - config_dict["dimension"] = embed_info.get("dimension", 1024) - else: - return config.embed_model_names[config.embed_model].model_dump() + # 检查 embed_info 是否有效 + if not embed_info or ("model" not in embed_info and "name" not in embed_info): + logger.error(f"Invalid embed_info: {embed_info}, using default embedding model config") + raise ValueError("Invalid embed_info: must be a non-empty dictionary") + + # 优先检查是否有 model_id 字段 + if "model_id" in embed_info and embed_info["model_id"]: + logger.warning(f"Using model_id: {embed_info['model_id']}") + config_dict = config.embed_model_names[embed_info["model_id"]].model_dump() + config_dict["api_key"] = os.getenv(config_dict["api_key"]) or config_dict["api_key"] + return config_dict + + # 检查是否是 EmbedModelInfo 对象（在某些情况下可能直接传入对象） + if hasattr(embed_info, "name") and isinstance(embed_info, EmbedModelInfo): + logger.debug(f"Using EmbedModelInfo object: {embed_info.name}") + config_dict = embed_info.model_dump() + config_dict["api_key"] = os.getenv(config_dict["api_key"]) or config_dict["api_key"] + return config_dict + + # 字典形式（保持向后兼容） + # 检查必需字段是否存在 + if not embed_info.get("name") or not embed_info.get("base_url"): + logger.warning(f"embed_info missing required 'name' or 'base_url' field: {embed_info}, using default") + raise ValueError("embed_info missing required 'name' or 'base_url' field") + + config_dict = { + "model": embed_info["name"], + "api_key": os.getenv(embed_info["api_key"]) or embed_info["api_key"], + "base_url": embed_info["base_url"], + "dimension": embed_info.get("dimension", 1024) + } + logger.debug(f"Embedding config from dict: {config_dict}") + return config_dict except Exception as e: - logger.error(f"Error in get_embedding_config: {e}, {embed_info}") - raise ValueError(f"Error in get_embedding_config: {e}") - - logger.debug(f"Embedding config: {config_dict}") - return config_dict + logger.error(f"Error in get_embedding_config: {e}, embed_info={embed_info}") + # 返回默认配置作为fallback + logger.warning("Falling back to default embedding model config") + try: + config_dict = config.embed_model_names[config.embed_model].model_dump() + config_dict["api_key"] = os.getenv(config_dict["api_key"]) or config_dict["api_key"] + return config_dict + except Exception as fallback_error: + logger.error(f"Failed to get default embedding config: {fallback_error}") + raise ValueError(f"Failed to get embedding config and fallback failed: {e}") def is_minio_url(file_path: str) -> bool: From 3d63418adf6b6eb3ed4ea411f1f8c9f125e32ff6 Mon Sep 17 00:00:00 2001 From: Wenjie Zhang Date: Mon, 15 Dec 2025 23:25:56 +0800 Subject: [PATCH 3/6] =?UTF-8?q?feat:=20=E5=AE=9E=E7=8E=B0=E7=BB=9F?= =?UTF-8?q?=E4=B8=80=E5=9B=BE=E8=B0=B1=E9=80=82=E9=85=8D=E5=99=A8=E5=8F=8A?= =?UTF-8?q?=E5=89=8D=E7=AB=AF=E7=BB=84=E4=BB=B6=E9=87=8D=E6=9E=84?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 重构图谱系统架构，引入适配器模式支持多种图数据库类型。主要变更包括： 1. 新增 GraphAdapter 基类及 LightRAG/Upload 适配器实现 2. 重构前端组件结构，新增 GraphDetailPanel 等可复用组件 3. 实现 useGraph 组合式函数统一管理图谱状态 4. 优化 Neo4j 节点/边数据标准化处理 5. 新增统一图谱 API 接口及对应测试用例 6. 改进前端交互体验，增加节点详情展示等功能 前端组件库重构为模块化结构，提升代码复用性。适配器模式使系统可灵活支持不同图数据源，为后续扩展奠定基础。 Next：上传图谱文件的时候，支持属性解析 --- server/routers/graph_router.py | 455 ++--- .../middlewares/dynamic_tool_middleware.py | 3 +- src/knowledge/adapters/__init__.py | 6 + src/knowledge/adapters/base.py | 87 + src/knowledge/adapters/factory.py | 23 + src/knowledge/adapters/lightrag.py | 154 ++ src/knowledge/adapters/upload.py | 112 ++ src/knowledge/graph.py | 34 +- src/knowledge/utils/kb_utils.py | 2 +- test/api/test_unified_graph_router.py | 138 ++ web/src/apis/graph_api.js | 91 +- web/src/components/GraphCanvas.vue | 37 +- web/src/components/GraphDetailPanel.vue | 167 ++ web/src/components/KnowledgeGraphSection.vue | 242 ++- web/src/components/KnowledgeGraphViewer.vue | 1492 ----------------- web/src/components/LightRAGInfoPanel.vue | 120 ++ web/src/composables/useGraph.js | 72 + web/src/views/GraphView.vue | 228 ++- 18 files changed, 1487 insertions(+), 1976 deletions(-) create mode 100644 src/knowledge/adapters/__init__.py create mode 100644 src/knowledge/adapters/base.py create mode 100644 src/knowledge/adapters/factory.py create mode 100644 src/knowledge/adapters/lightrag.py create mode 100644 src/knowledge/adapters/upload.py create mode 100644 test/api/test_unified_graph_router.py create mode 100644 web/src/components/GraphDetailPanel.vue delete mode 100644 web/src/components/KnowledgeGraphViewer.vue create mode 100644 web/src/components/LightRAGInfoPanel.vue create mode 100644 web/src/composables/useGraph.js diff --git a/server/routers/graph_router.py b/server/routers/graph_router.py index 3c024650..1f816cfa 100644 --- a/server/routers/graph_router.py +++ b/server/routers/graph_router.py @@ -5,13 +5,215 @@ from fastapi import APIRouter, Body, Depends, HTTPException, Query from src.storage.db.models import User from server.utils.auth_middleware import get_admin_user from src import graph_base, knowledge_base +from src.knowledge.adapters.factory import GraphAdapterFactory +from src.knowledge.adapters.base import GraphAdapter from src.utils.logging_config import logger graph = APIRouter(prefix="/graph", tags=["graph"]) # ============================================================================= -# === 子图查询分组 === +# === 统一图谱接口 (Unified Graph API) === +# ============================================================================= + + +async def _get_graph_adapter(db_id: str) -> GraphAdapter: + """ + 根据数据库ID获取对应的图谱适配器 + + Args: + db_id: 数据库ID + + Returns: + GraphAdapter: 对应的图谱适配器实例 + """ + # 1. 检查是否是 LightRAG 数据库 + if knowledge_base.is_lightrag_database(db_id): + rag_instance = await knowledge_base._get_lightrag_instance(db_id) + if not rag_instance: + raise HTTPException(status_code=404, detail=f"LightRAG database {db_id} not found or inaccessible") + return GraphAdapterFactory.create_adapter("lightrag", lightrag_instance=rag_instance) + + # 2. 默认为 Upload/Neo4j 数据库 (假设 db_id 为 "neo4j" 或其他 Neo4j 数据库名) + # 这里我们假设非 LightRAG 的 ID 都是 Neo4j 的数据库名 + # 如果未来有更多类型，需要更完善的 ID 区分机制 (例如前缀) + if not graph_base.is_running(): + raise HTTPException(status_code=503, detail="Graph database service is not running") + + return GraphAdapterFactory.create_adapter("upload", graph_db_instance=graph_base, config={"kgdb_name": db_id}) + + +@graph.get("/list") +async def get_graphs(current_user: User = Depends(get_admin_user)): + """ + 获取所有可用的知识图谱列表 + + Returns: + 包含所有图谱信息的列表 (包括 Neo4j 和 LightRAG) + """ + try: + graphs = [] + + # 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) + }) + + # 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 + }) + + return {"success": True, "data": graphs} + + except Exception as e: + logger.error(f"Failed to list graphs: {e}") + logger.error(f"Traceback: {traceback.format_exc()}") + raise HTTPException(status_code=500, detail=f"Failed to list graphs: {str(e)}") + + +@graph.get("/subgraph") +async def get_subgraph( + db_id: str = Query(..., description="知识图谱ID"), + node_label: str = Query("*", description="节点标签或查询关键词"), + max_depth: int = Query(2, description="最大深度", ge=1, le=5), + max_nodes: int = Query(100, description="最大节点数", ge=1, le=1000), + current_user: User = Depends(get_admin_user), +): + """ + 统一的子图查询接口 + + Args: + db_id: 图谱ID (LightRAG DB ID 或 "neo4j") + node_label: 查询关键词或标签 + max_depth: 扩展深度 + max_nodes: 返回最大节点数 + """ + try: + logger.info(f"Querying subgraph - db_id: {db_id}, label: {node_label}") + + adapter = await _get_graph_adapter(db_id) + + # 统一查询参数 + # 对于 UploadGraphAdapter, kgdb_name 通常通过 kwargs 传递 + # 对于 LightRAGGraphAdapter, max_depth/max_nodes 通过 kwargs 传递 + result_data = await adapter.query_nodes( + 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" + ) + + return { + "success": True, + "data": result_data, + } + + except HTTPException: + raise + except Exception as e: + logger.error(f"Failed to get subgraph: {e}") + logger.error(f"Traceback: {traceback.format_exc()}") + raise HTTPException(status_code=500, detail=f"Failed to get subgraph: {str(e)}") + + +@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) +): + """ + 获取图谱的所有标签 + """ + try: + adapter = await _get_graph_adapter(db_id) + labels = await adapter.get_labels() + return {"success": True, "data": {"labels": labels}} + + except Exception as e: + logger.error(f"Failed to get labels: {e}") + raise HTTPException(status_code=500, detail=f"Failed to get labels: {str(e)}") + + +@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) +): + """ + 获取图谱统计信息 + """ + try: + if knowledge_base.is_lightrag_database(db_id): + # 复用原有的 LightRAG 统计逻辑 + # 这里暂时直接调用原有逻辑，理想情况下也应该封装进 Adapter + rag_instance = await knowledge_base._get_lightrag_instance(db_id) + if not rag_instance: + raise HTTPException(status_code=404, detail="Database not found") + + knowledge_graph = await rag_instance.get_knowledge_graph(node_label="*", max_depth=1, max_nodes=10000) + entity_types = {} + for node in knowledge_graph.nodes: + entity_type = node.properties.get("entity_type", "unknown") + 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) + ] + + return { + "success": True, + "data": { + "total_nodes": len(knowledge_graph.nodes), + "total_edges": len(knowledge_graph.edges), + "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") + + return { + "success": True, + "data": { + "total_nodes": info.get("entity_count", 0), + "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", []) + ] + } + } + + except Exception as e: + logger.error(f"Failed to get stats: {e}") + raise HTTPException(status_code=500, detail=f"Failed to get stats: {str(e)}") + + +# ============================================================================= +# === 兼容性接口 (Deprecated/Compatibility) === # ============================================================================= @@ -23,147 +225,40 @@ async def get_lightrag_subgraph( max_nodes: int = Query(100, description="最大节点数", ge=1, le=1000), current_user: User = Depends(get_admin_user), ): - """ - 使用 LightRAG 原生方法获取知识图谱子图 - - Args: - db_id: LightRAG 数据库实例ID - node_label: 节点标签，用于查找起始节点，使用 "*" 获取全图 - max_depth: 子图的最大深度 - max_nodes: 返回的最大节点数量 - - Returns: - 包含节点和边的知识图谱数据 - """ - try: - logger.info( - f"获取子图数据 - db_id: {db_id}, node_label: {node_label}, max_depth: {max_depth}, max_nodes: {max_nodes}" - ) - - # 检查是否是 LightRAG 数据库 - if not knowledge_base.is_lightrag_database(db_id): - raise HTTPException( - status_code=400, detail=f"数据库 {db_id} 不是 LightRAG 类型，图谱功能仅支持 LightRAG 知识库" - ) - - # 获取 LightRAG 实例 - rag_instance = await knowledge_base._get_lightrag_instance(db_id) - if not rag_instance: - raise HTTPException(status_code=404, detail=f"LightRAG 数据库 {db_id} 不存在或无法访问") - - # 使用 LightRAG 的原生 get_knowledge_graph 方法 - knowledge_graph = await rag_instance.get_knowledge_graph( - node_label=node_label, max_depth=max_depth, max_nodes=max_nodes - ) - - # 将 LightRAG 的 KnowledgeGraph 格式转换为前端需要的格式 - nodes = [] - for node in knowledge_graph.nodes: - nodes.append( - { - "id": node.id, - "labels": node.labels, - "entity_type": node.properties.get("entity_type", "unknown"), - "properties": node.properties, - } - ) - - edges = [] - for edge in knowledge_graph.edges: - edges.append( - { - "id": edge.id, - "source": edge.source, - "target": edge.target, - "type": edge.type, - "properties": edge.properties, - } - ) - - result = { - "success": True, - "data": { - "nodes": nodes, - "edges": edges, - "is_truncated": knowledge_graph.is_truncated, - "total_nodes": len(nodes), - "total_edges": len(edges), - }, - } - - logger.info(f"成功获取子图 - 节点数: {len(nodes)}, 边数: {len(edges)}") - return result - - except HTTPException: - # 重新抛出 HTTP 异常 - raise - except Exception as e: - logger.error(f"获取子图数据失败: {e}") - logger.error(f"Traceback: {traceback.format_exc()}") - raise HTTPException(status_code=500, detail=f"获取子图数据失败: {str(e)}") + """(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 + ) @graph.get("/lightrag/databases") async def get_lightrag_databases(current_user: User = Depends(get_admin_user)): - """ - 获取所有可用的 LightRAG 数据库 - - Returns: - 可用的 LightRAG 数据库列表 - """ + """(Deprecated) Use /graph/list instead""" try: lightrag_databases = knowledge_base.get_lightrag_databases() return {"success": True, "data": {"databases": lightrag_databases}} - except Exception as e: - logger.error(f"获取 LightRAG 数据库列表失败: {e}") - raise HTTPException(status_code=500, detail=f"获取 LightRAG 数据库列表失败: {str(e)}") - - -# ============================================================================= -# === 节点管理分组 === -# ============================================================================= + raise HTTPException(status_code=500, detail=str(e)) @graph.get("/lightrag/labels") async def get_lightrag_labels( db_id: str = Query(..., description="数据库ID"), current_user: User = Depends(get_admin_user) ): - """ - 获取知识图谱中的所有标签 + """(Deprecated) Use /graph/labels instead""" + return await get_graph_labels(db_id=db_id, current_user=current_user) - Args: - db_id: LightRAG 数据库实例ID - Returns: - 图谱中所有可用的标签列表 - """ - try: - logger.info(f"获取图谱标签 - db_id: {db_id}") - - # 检查是否是 LightRAG 数据库 - if not knowledge_base.is_lightrag_database(db_id): - raise HTTPException( - status_code=400, detail=f"数据库 {db_id} 不是 LightRAG 类型，图谱功能仅支持 LightRAG 知识库" - ) - - # 获取 LightRAG 实例 - rag_instance = await knowledge_base._get_lightrag_instance(db_id) - if not rag_instance: - raise HTTPException(status_code=404, detail=f"LightRAG 数据库 {db_id} 不存在或无法访问") - - # 使用 LightRAG 的原生方法获取所有标签 - labels = await rag_instance.get_graph_labels() - - return {"success": True, "data": {"labels": labels}} - - except HTTPException: - # 重新抛出 HTTP 异常 - raise - except Exception as e: - logger.error(f"获取图谱标签失败: {e}") - logger.error(f"Traceback: {traceback.format_exc()}") - raise HTTPException(status_code=500, detail=f"获取图谱标签失败: {str(e)}") +@graph.get("/lightrag/stats") +async def get_lightrag_stats( + db_id: str = Query(..., description="数据库ID"), current_user: User = Depends(get_admin_user) +): + """(Deprecated) Use /graph/stats instead""" + return await get_graph_stats(db_id=db_id, current_user=current_user) @graph.get("/neo4j/nodes") @@ -172,110 +267,19 @@ async def get_neo4j_nodes( num: int = Query(100, description="节点数量", ge=1, le=1000), current_user: User = Depends(get_admin_user), ): - """ - 获取图谱节点样本数据 - """ - try: - logger.debug(f"Get graph nodes in {kgdb_name} with {num} nodes") - - if not graph_base.is_running(): - raise HTTPException(status_code=400, detail="图数据库未启动") - - result = graph_base.get_sample_nodes(kgdb_name, num) - - return {"success": True, "result": result, "message": "success"} - - except Exception as e: - logger.error(f"获取图节点数据失败: {e}\n{traceback.format_exc()}") - raise HTTPException(status_code=500, detail=f"获取图节点数据失败: {str(e)}") + """(Deprecated) Use /graph/subgraph instead""" + response = await get_subgraph(db_id=kgdb_name, node_label="*", max_nodes=num, current_user=current_user) + return {"success": True, "result": response["data"], "message": "success"} @graph.get("/neo4j/node") async def get_neo4j_node( entity_name: str = Query(..., description="实体名称"), current_user: User = Depends(get_admin_user) ): - """ - 根据实体名称查询图节点 - """ - try: - if not graph_base.is_running(): - raise HTTPException(status_code=400, detail="图数据库未启动") - - result = graph_base.query_node(keyword=entity_name) - - return {"success": True, "result": result, "message": "success"} - - except Exception as e: - logger.error(f"查询图节点失败: {e}\n{traceback.format_exc()}") - raise HTTPException(status_code=500, detail=f"查询图节点失败: {str(e)}") - - -# ============================================================================= -# === 边管理分组 === -# ============================================================================= - -# 可以在这里添加边相关的管理功能 - -# ============================================================================= -# === 图谱分析分组 === -# ============================================================================= - - -@graph.get("/lightrag/stats") -async def get_lightrag_stats( - db_id: str = Query(..., description="数据库ID"), current_user: User = Depends(get_admin_user) -): - """ - 获取知识图谱统计信息 - """ - try: - logger.info(f"获取图谱统计信息 - db_id: {db_id}") - - # 检查是否是 LightRAG 数据库 - if not knowledge_base.is_lightrag_database(db_id): - raise HTTPException( - status_code=400, detail=f"数据库 {db_id} 不是 LightRAG 类型，图谱功能仅支持 LightRAG 知识库" - ) - - # 获取 LightRAG 实例 - rag_instance = await knowledge_base._get_lightrag_instance(db_id) - if not rag_instance: - raise HTTPException(status_code=404, detail=f"LightRAG 数据库 {db_id} 不存在或无法访问") - - # 通过获取全图来统计节点和边的数量 - knowledge_graph = await rag_instance.get_knowledge_graph( - node_label="*", - max_depth=1, - max_nodes=10000, # 设置较大值以获取完整统计 - ) - - # 统计实体类型分布 - entity_types = {} - for node in knowledge_graph.nodes: - entity_type = node.properties.get("entity_type", "unknown") - 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) - ] - - return { - "success": True, - "data": { - "total_nodes": len(knowledge_graph.nodes), - "total_edges": len(knowledge_graph.edges), - "entity_types": entity_types_list, - "is_truncated": knowledge_graph.is_truncated, - }, - } - - except HTTPException: - # 重新抛出 HTTP 异常 - raise - except Exception as e: - logger.error(f"获取图谱统计信息失败: {e}") - logger.error(f"Traceback: {traceback.format_exc()}") - raise HTTPException(status_code=500, detail=f"获取图谱统计信息失败: {str(e)}") + """(Deprecated) Use /graph/subgraph instead""" + # neo4j/node uses query_nodes(keyword=entity_name) + response = await get_subgraph(db_id="neo4j", node_label=entity_name, current_user=current_user) + return {"success": True, "result": response["data"], "message": "success"} @graph.get("/neo4j/info") @@ -298,10 +302,7 @@ async def index_neo4j_entities(data: dict = Body(default={}), current_user: User if not graph_base.is_running(): raise HTTPException(status_code=400, detail="图数据库未启动") - # 获取参数或使用默认值 kgdb_name = data.get("kgdb_name", "neo4j") - - # 调用GraphDatabase的add_embedding_to_nodes方法 count = graph_base.add_embedding_to_nodes(kgdb_name=kgdb_name) return { diff --git a/src/agents/common/middlewares/dynamic_tool_middleware.py b/src/agents/common/middlewares/dynamic_tool_middleware.py index acce5f4d..a8dc196b 100644 --- a/src/agents/common/middlewares/dynamic_tool_middleware.py +++ b/src/agents/common/middlewares/dynamic_tool_middleware.py @@ -60,7 +60,8 @@ class DynamicToolMiddleware(AgentMiddleware): logger.warning(f"MCP server '{mcp}' not pre-loaded. Please add it to mcp_servers list.") logger.info( - f"Dynamic tool selection: {len(enabled_tools)} tools enabled: {[tool.name for tool in enabled_tools]}" + f"Dynamic tool selection: {len(enabled_tools)} tools enabled: {[tool.name for tool in enabled_tools]}, " + f"selected_tools: {selected_tools}, selected_mcps: {selected_mcps}" ) # 更新 request 中的工具列表 diff --git a/src/knowledge/adapters/__init__.py b/src/knowledge/adapters/__init__.py new file mode 100644 index 00000000..027747fc --- /dev/null +++ b/src/knowledge/adapters/__init__.py @@ -0,0 +1,6 @@ +from .base import GraphAdapter +from .factory import GraphAdapterFactory +from .lightrag import LightRAGGraphAdapter +from .upload import UploadGraphAdapter + +__all__ = ["GraphAdapter", "UploadGraphAdapter", "LightRAGGraphAdapter", "GraphAdapterFactory"] diff --git a/src/knowledge/adapters/base.py b/src/knowledge/adapters/base.py new file mode 100644 index 00000000..a757c278 --- /dev/null +++ b/src/knowledge/adapters/base.py @@ -0,0 +1,87 @@ +from abc import ABC, abstractmethod +from typing import Any + + +class GraphAdapter(ABC): + """图谱适配器基类 (Base Graph Adapter)""" + + @abstractmethod + async def query_nodes(self, keyword: str, **kwargs) -> dict[str, Any]: + """查询节点 (Query nodes)""" + pass + + @abstractmethod + async def add_entity(self, triples: list[dict], **kwargs) -> bool: + """添加实体三元组 (Add entity triples)""" + pass + + @abstractmethod + async def get_sample_nodes(self, num: int = 50, **kwargs) -> dict[str, list]: + """获取样本节点 (Get sample nodes)""" + pass + + @abstractmethod + def normalize_node(self, raw_node: Any) -> dict[str, Any]: + """标准化节点格式 (Normalize node format)""" + pass + + @abstractmethod + def normalize_edge(self, raw_edge: Any) -> dict[str, Any]: + """标准化边格式 (Normalize edge format)""" + pass + + @abstractmethod + async def get_labels(self) -> list[str]: + """获取所有标签 (Get all labels)""" + pass + + def _create_standard_node( + self, + node_id: str, + name: str, + entity_type: str, + labels: list[str], + properties: dict[str, Any], + source: str, + ) -> dict[str, Any]: + """ + Helper to create a standardized node dictionary. + """ + return { + "id": node_id, + "name": name, + "original_id": node_id, + "type": entity_type, + "labels": labels, + "properties": properties, + "normalized": { + "name": name, + "type": entity_type, + "source": source, + }, + "graph_type": source, + } + + def _create_standard_edge( + self, + edge_id: str, + source_id: str, + target_id: str, + edge_type: str, + properties: dict[str, Any], + direction: str = "directed", + ) -> dict[str, Any]: + """ + Helper to create a standardized edge dictionary. + """ + return { + "id": edge_id, + "source_id": source_id, + "target_id": target_id, + "type": edge_type, + "properties": properties, + "normalized": { + "type": edge_type, + "direction": direction, + }, + } diff --git a/src/knowledge/adapters/factory.py b/src/knowledge/adapters/factory.py new file mode 100644 index 00000000..66a23680 --- /dev/null +++ b/src/knowledge/adapters/factory.py @@ -0,0 +1,23 @@ +from .base import GraphAdapter +from .lightrag import LightRAGGraphAdapter +from .upload import UploadGraphAdapter + + +class GraphAdapterFactory: + """图谱适配器工厂 (Graph Adapter Factory)""" + + _registry: dict[str, type[GraphAdapter]] = {"upload": UploadGraphAdapter, "lightrag": LightRAGGraphAdapter} + + @classmethod + def register(cls, graph_type: str, adapter_class: type[GraphAdapter]): + """注册适配器类 (Register adapter class)""" + cls._registry[graph_type] = adapter_class + + @classmethod + def create_adapter(cls, graph_type: str, **kwargs) -> GraphAdapter: + """创建适配器实例 (Create adapter instance)""" + adapter_class = cls._registry.get(graph_type) + if not adapter_class: + raise ValueError(f"Unknown graph type: {graph_type}") + + return adapter_class(**kwargs) diff --git a/src/knowledge/adapters/lightrag.py b/src/knowledge/adapters/lightrag.py new file mode 100644 index 00000000..f4b2206d --- /dev/null +++ b/src/knowledge/adapters/lightrag.py @@ -0,0 +1,154 @@ +import logging +from typing import Any + +from .base import GraphAdapter + +logger = logging.getLogger(__name__) + + +class LightRAGGraphAdapter(GraphAdapter): + """LightRAG图谱适配器 (LightRAG Graph Adapter)""" + + def __init__(self, lightrag_instance: Any, config: dict[str, Any] = None): + self.config = config or { + "node_label_field": "labels", + "id_field": "id", + "type_field": "entity_type", + "relation_prefix": "HAS_", + } + self.lightrag = lightrag_instance + + async def query_nodes(self, keyword: str, **kwargs) -> dict[str, Any]: + # Map keyword to node_label + # If keyword is empty or "*", query all (or sample) + node_label = keyword if keyword and keyword != "*" else "*" + + max_depth = kwargs.get("max_depth", 2) + max_nodes = kwargs.get("max_nodes", 100) + + # lightrag.get_knowledge_graph is async + # Note: if node_label is "*", LightRAG might return a large graph or sample depending on implementation + raw_graph = await self.lightrag.get_knowledge_graph( + node_label=node_label, max_depth=max_depth, max_nodes=max_nodes + ) + + return self._convert_lightrag_graph(raw_graph) + + async def add_entity(self, triples: list[dict], **kwargs) -> bool: + """ + LightRAG typically builds graph from text. + Direct triple injection might not be supported or requires different API. + """ + logger.warning("add_entity is not fully supported for LightRAG adapter yet.") + return False + + async def get_sample_nodes(self, num: int = 50, **kwargs) -> dict[str, list]: + # Use query_nodes with wildcard to get a subgraph + return await self.query_nodes("*", max_nodes=num, **kwargs) + + def normalize_node(self, raw_node: Any) -> dict[str, Any]: + # Handle LightRAG Node object + node_id = getattr(raw_node, "id", None) + if node_id is None: + node_id = raw_node.get("id") + + labels = getattr(raw_node, "labels", []) + if not labels and hasattr(raw_node, "get"): + labels = raw_node.get("labels", []) + + properties = getattr(raw_node, "properties", {}) + if not properties and hasattr(raw_node, "get"): + properties = raw_node.get("properties", {}) + + # 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: + for label in labels: + if not label.startswith("kb_"): + entity_type = label + break + + return self._create_standard_node( + 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]: + # Handle LightRAG Edge object + edge_id = getattr(raw_edge, "id", None) + if edge_id is None: + edge_id = raw_edge.get("id") + + source = getattr(raw_edge, "source", None) + if source is None: + source = raw_edge.get("source") + + target = getattr(raw_edge, "target", None) + if target is None: + target = raw_edge.get("target") + + edge_type = getattr(raw_edge, "type", None) + if edge_type is None: + edge_type = raw_edge.get("type") + + 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 + if edge_type == "DIRECTED": + keywords = properties.get("keywords", []) + if keywords and isinstance(keywords, list) and len(keywords) > 0: + display_type = keywords[0] + elif properties.get("description"): + # 如果没有 keywords，尝试从 description 截取（太长就算了） + desc = properties.get("description", "") + if len(desc) < 20: + display_type = desc + else: + 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 + ) + + async def get_labels(self) -> list[str]: + return await self.lightrag.get_graph_labels() + + def _convert_lightrag_graph(self, raw_graph) -> dict[str, Any]: + nodes = [] + edges = [] + + # raw_graph has .nodes and .edges lists + if hasattr(raw_graph, "nodes"): + for node in raw_graph.nodes: + nodes.append(self.normalize_node(node)) + + if hasattr(raw_graph, "edges"): + for edge in raw_graph.edges: + edges.append(self.normalize_edge(edge)) + + result = {"nodes": nodes, "edges": edges} + + # Add metadata if available + if hasattr(raw_graph, "is_truncated"): + result["is_truncated"] = raw_graph.is_truncated + + result["total_nodes"] = len(nodes) + result["total_edges"] = len(edges) + + return result diff --git a/src/knowledge/adapters/upload.py b/src/knowledge/adapters/upload.py new file mode 100644 index 00000000..a46188f1 --- /dev/null +++ b/src/knowledge/adapters/upload.py @@ -0,0 +1,112 @@ +from typing import Any + +from src.knowledge.graph import GraphDatabase + +from .base import GraphAdapter + + +class UploadGraphAdapter(GraphAdapter): + """Upload图谱适配器 (Upload Graph Adapter)""" + + def __init__(self, graph_db_instance: GraphDatabase, config: dict[str, Any] = None): + self.config = config or { + "node_label": "Entity:Upload", + "id_field": "name", + "relation_label": "RELATION", + "default_tags": ["upload", "user_generated"], + } + self.graph_db = graph_db_instance + + 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 + ) + else: + # 否则执行关键词搜索 + # graph_db.query_node is sync + raw_results = self.graph_db.query_node( + keyword=params["keyword"], + threshold=params.get("threshold", 0.9), + kgdb_name=params.get("kgdb_name", "neo4j"), + hops=params.get("hops", 2), + return_format="graph", + ) + + return self._format_results(raw_results) + + async def add_entity(self, triples: list[dict], **kwargs) -> bool: + kgdb_name = kwargs.get("kgdb_name", "neo4j") + # txt_add_vector_entity is async + await self.graph_db.txt_add_vector_entity(triples, kgdb_name=kgdb_name) + return True + + async def get_sample_nodes(self, num: int = 50, **kwargs) -> dict[str, list]: + kgdb_name = kwargs.get("kgdb_name", "neo4j") + # get_sample_nodes is sync + raw_results = self.graph_db.get_sample_nodes(kgdb_name=kgdb_name, num=num) + return self._format_results(raw_results) + + def normalize_node(self, raw_node: Any) -> dict[str, Any]: + """ + raw_node expected format: {id: str, name: str, ...} + """ + node_id = raw_node.get("id") + name = raw_node.get("name") + + return self._create_standard_node( + node_id=node_id, + name=name, + entity_type="entity", + labels=["Entity", "Upload"], + properties=raw_node, + source="upload" + ) + + def normalize_edge(self, raw_edge: Any) -> dict[str, Any]: + """ + raw_edge expected format: {type: str, source_id: str, target_id: str, ...} + """ + # Generate an ID if not present (Upload graph edges might not have explicit ID in simple dict return) + edge_id = raw_edge.get("id") + if not edge_id: + edge_id = f"{raw_edge.get('source_id')}_{raw_edge.get('type')}_{raw_edge.get('target_id')}" + + return self._create_standard_edge( + edge_id=edge_id, + source_id=raw_edge.get("source_id"), + target_id=raw_edge.get("target_id"), + edge_type=raw_edge.get("type"), + properties=raw_edge + ) + + async def get_labels(self) -> list[str]: + kgdb_name = self.config.get("kgdb_name", "neo4j") + info = self.graph_db.get_graph_info(graph_name=kgdb_name) + return info.get("labels", []) if info else [] + + def _normalize_query_params(self, keyword: str, kwargs: dict) -> dict[str, Any]: + # Map max_depth to hops if present + hops = kwargs.get("hops") + if hops is None: + hops = kwargs.get("max_depth", 2) + + return { + "keyword": keyword, + "threshold": kwargs.get("threshold", 0.9), + "kgdb_name": kwargs.get("kgdb_name", "neo4j"), + "hops": hops, + "filters": kwargs.get("filters", {}), + "context": kwargs.get("context", {}), + } + + def _format_results(self, raw_results: dict[str, list]) -> dict[str, list]: + nodes = [self.normalize_node(n) for n in raw_results.get("nodes", [])] + edges = [self.normalize_edge(e) for e in raw_results.get("edges", [])] + return {"nodes": nodes, "edges": edges} diff --git a/src/knowledge/graph.py b/src/knowledge/graph.py index 4b611f18..61e2c85a 100644 --- a/src/knowledge/graph.py +++ b/src/knowledge/graph.py @@ -9,7 +9,7 @@ from neo4j import GraphDatabase as GD from src import config from src.models import select_embedding_model -from src.storage.minio.client import get_minio_client, StorageError +from src.storage.minio.client import get_minio_client from src.utils import logger from src.utils.datetime_utils import utc_isoformat @@ -106,7 +106,12 @@ class GraphDatabase: RETURN {id: elementId(n), name: n.name} AS h, CASE WHEN rel IS NOT NULL THEN - {type: rel.type, source_id: elementId(n), target_id: elementId(m)} + { + id: elementId(rel), + type: rel.type, + source_id: elementId(startNode(rel)), + target_id: elementId(endNode(rel)) + } ELSE null END AS r, CASE WHEN m IS NOT NULL THEN {id: elementId(m), name: m.name} @@ -166,7 +171,12 @@ class GraphDatabase: WHERE elementId(n) < elementId(m) RETURN {id: elementId(n), name: n.name} AS h, - {type: r.type, source_id: elementId(n), target_id: elementId(m)} AS r, + { + id: elementId(r), + type: r.type, + source_id: elementId(startNode(r)), + target_id: elementId(endNode(r)) + } AS r, {id: elementId(m), name: m.name} AS t LIMIT $num """ @@ -355,12 +365,12 @@ class GraphDatabase: temp_file_path = None try: - if parsed_url.scheme in ('http', 'https'): # 如果是 URL + if parsed_url.scheme in ("http", "https"): # 如果是 URL logger.info(f"检测到 URL，正在从 MinIO 下载文件: {file_path}") # 从 URL 解析 bucket_name 和 object_name # URL 格式: http://host:port/bucket_name/object_name - path_parts = parsed_url.path.lstrip('/').split('/', 1) + path_parts = parsed_url.path.lstrip("/").split("/", 1) if len(path_parts) < 2: raise ValueError(f"无法解析 MinIO URL: {file_path}") @@ -372,8 +382,10 @@ class GraphDatabase: file_data = await minio_client.adownload_file(bucket_name, object_name) # 创建临时文件保存下载的内容 - with tempfile.NamedTemporaryFile(mode='w', suffix='.jsonl', delete=False, encoding='utf-8') as temp_file: - temp_file.write(file_data.decode('utf-8')) + with tempfile.NamedTemporaryFile( + mode="w", suffix=".jsonl", delete=False, encoding="utf-8" + ) as temp_file: + temp_file.write(file_data.decode("utf-8")) temp_file_path = temp_file.name logger.info(f"文件已下载到临时路径: {temp_file_path}") @@ -592,22 +604,22 @@ class GraphDatabase: // 1跳出边 [(n {name: $entity_name})-[r1]->(m1) | {h: {id: elementId(n), name: n.name}, - r: {type: r1.type, source_id: elementId(n), target_id: elementId(m1)}, + r: {id: elementId(r1), type: r1.type, source_id: elementId(n), target_id: elementId(m1)}, t: {id: elementId(m1), name: m1.name}}], // 2跳出边 [(n {name: $entity_name})-[r1]->(m1)-[r2]->(m2) | {h: {id: elementId(m1), name: m1.name}, - r: {type: r2.type, source_id: elementId(m1), target_id: elementId(m2)}, + r: {id: elementId(r2), type: r2.type, source_id: elementId(m1), target_id: elementId(m2)}, t: {id: elementId(m2), name: m2.name}}], // 1跳入边 [(m1)-[r1]->(n {name: $entity_name}) | {h: {id: elementId(m1), name: m1.name}, - r: {type: r1.type, source_id: elementId(m1), target_id: elementId(n)}, + r: {id: elementId(r1), type: r1.type, source_id: elementId(m1), target_id: elementId(n)}, t: {id: elementId(n), name: n.name}}], // 2跳入边 [(m2)-[r2]->(m1)-[r1]->(n {name: $entity_name}) | {h: {id: elementId(m2), name: m2.name}, - r: {type: r2.type, source_id: elementId(m2), target_id: elementId(m1)}, + r: {id: elementId(r2), type: r2.type, source_id: elementId(m2), target_id: elementId(m1)}, t: {id: elementId(m1), name: m1.name}}] ] AS all_results UNWIND all_results AS result_list diff --git a/src/knowledge/utils/kb_utils.py b/src/knowledge/utils/kb_utils.py index d955fffd..75dbec58 100644 --- a/src/knowledge/utils/kb_utils.py +++ b/src/knowledge/utils/kb_utils.py @@ -319,7 +319,7 @@ def get_embedding_config(embed_info: dict) -> dict: "model": embed_info["name"], "api_key": os.getenv(embed_info["api_key"]) or embed_info["api_key"], "base_url": embed_info["base_url"], - "dimension": embed_info.get("dimension", 1024) + "dimension": embed_info.get("dimension", 1024), } logger.debug(f"Embedding config from dict: {config_dict}") return config_dict diff --git a/test/api/test_unified_graph_router.py b/test/api/test_unified_graph_router.py new file mode 100644 index 00000000..fa23c916 --- /dev/null +++ b/test/api/test_unified_graph_router.py @@ -0,0 +1,138 @@ +""" +Integration tests for the unified graph router endpoints. +""" + +from __future__ import annotations + +import pytest + +pytestmark = [pytest.mark.asyncio, pytest.mark.integration] + + +async def test_get_graphs_list(test_client, admin_headers): + """Test retrieving the list of all graphs.""" + response = await test_client.get("/api/graph/list", headers=admin_headers) + assert response.status_code == 200 + payload = response.json() + assert payload["success"] is True + graphs = payload["data"] + assert isinstance(graphs, list) + + # Check for Neo4j default graph + neo4j_graph = next((g for g in graphs if g["id"] == "neo4j"), None) + assert neo4j_graph is not None + assert neo4j_graph["type"] == "neo4j" + + # Note: LightRAG graphs might be empty if none created, but we check structure + + +async def test_get_subgraph_neo4j(test_client, admin_headers): + """Test unified subgraph query for Neo4j.""" + # Query with a wildcard or a known node. Using "*" to get a sample. + response = await test_client.get( + "/api/graph/subgraph", + params={"db_id": "neo4j", "node_label": "*", "max_nodes": 10}, + headers=admin_headers + ) + assert response.status_code == 200 + payload = response.json() + assert payload["success"] is True + data = payload["data"] + assert "nodes" in data + assert "edges" in data + assert isinstance(data["nodes"], list) + + +async def test_get_subgraph_lightrag(test_client, admin_headers, knowledge_database): + """Test unified subgraph query for LightRAG.""" + db_id = knowledge_database["db_id"] + response = await test_client.get( + "/api/graph/subgraph", + params={"db_id": db_id, "node_label": "*", "max_nodes": 10}, + headers=admin_headers + ) + assert response.status_code == 200 + payload = response.json() + assert payload["success"] is True + data = payload["data"] + assert "nodes" in data + assert "edges" in data + + +async def test_get_stats_neo4j(test_client, admin_headers): + """Test stats endpoint for Neo4j.""" + response = await test_client.get( + "/api/graph/stats", + params={"db_id": "neo4j"}, + headers=admin_headers + ) + assert response.status_code == 200 + payload = response.json() + assert payload["success"] is True + data = payload["data"] + assert "total_nodes" in data + assert "total_edges" in data + assert "entity_types" in data + + +async def test_get_stats_lightrag(test_client, admin_headers, knowledge_database): + """Test stats endpoint for LightRAG.""" + db_id = knowledge_database["db_id"] + response = await test_client.get( + "/api/graph/stats", + params={"db_id": db_id}, + headers=admin_headers + ) + assert response.status_code == 200 + payload = response.json() + assert payload["success"] is True + data = payload["data"] + assert "total_nodes" in data + assert "total_edges" in data + assert "entity_types" in data + + +async def test_get_labels_neo4j(test_client, admin_headers): + """Test labels endpoint for Neo4j.""" + response = await test_client.get( + "/api/graph/labels", + params={"db_id": "neo4j"}, + headers=admin_headers + ) + assert response.status_code == 200 + payload = response.json() + assert payload["success"] is True + data = payload["data"] + assert "labels" in data + assert isinstance(data["labels"], list) + + +async def test_deprecated_neo4j_endpoints(test_client, admin_headers): + """Verify deprecated endpoints still work and return correct structure.""" + + # /neo4j/nodes + response = await test_client.get( + "/api/graph/neo4j/nodes", + params={"kgdb_name": "neo4j", "num": 5}, + headers=admin_headers + ) + assert response.status_code == 200 + payload = response.json() + # Check compatibility structure + assert payload["success"] is True + assert "result" in payload + assert payload["message"] == "success" + assert "nodes" in payload["result"] + + # /neo4j/node + # This might return empty if "NonExistentEntity" doesn't exist, but structure should be valid + response = await test_client.get( + "/api/graph/neo4j/node", + params={"entity_name": "NonExistentEntity"}, + headers=admin_headers + ) + assert response.status_code == 200 + payload = response.json() + assert payload["success"] is True + assert "result" in payload + assert payload["message"] == "success" diff --git a/web/src/apis/graph_api.js b/web/src/apis/graph_api.js index aed00c9a..be5b67d1 100644 --- a/web/src/apis/graph_api.js +++ b/web/src/apis/graph_api.js @@ -7,15 +7,23 @@ import { apiGet, apiPost } from './base' */ // ============================================================================= -// === LightRAG图知识库接口分组 === +// === 统一图谱接口 (Unified Graph API) === // ============================================================================= -export const lightragApi = { +export const unifiedApi = { /** - * 获取LightRAG知识图谱子图数据 + * 获取所有可用的知识图谱列表 + * @returns {Promise} - 图谱列表 + */ + getGraphs: async () => { + return await apiGet('/api/graph/list', {}, true) + }, + + /** + * 获取子图数据 (统一接口) * @param {Object} params - 查询参数 - * @param {string} params.db_id - LightRAG数据库ID - * @param {string} params.node_label - 节点标签（"*"获取全图） + * @param {string} params.db_id - 图谱ID + * @param {string} params.node_label - 节点标签/关键词 * @param {number} params.max_depth - 最大深度 * @param {number} params.max_nodes - 最大节点数 * @returns {Promise} - 子图数据 @@ -34,37 +42,12 @@ export const lightragApi = { max_nodes: max_nodes.toString() }) - return await apiGet(`/api/graph/lightrag/subgraph?${queryParams.toString()}`, {}, true) + return await apiGet(`/api/graph/subgraph?${queryParams.toString()}`, {}, true) }, /** - * 获取所有可用的LightRAG数据库 - * @returns {Promise} - LightRAG数据库列表 - */ - getDatabases: async () => { - return await apiGet('/api/graph/lightrag/databases', {}, true) - }, - - /** - * 获取LightRAG图谱标签列表 - * @param {string} db_id - LightRAG数据库ID - * @returns {Promise} - 标签列表 - */ - getLabels: async (db_id) => { - if (!db_id) { - throw new Error('db_id is required') - } - - const queryParams = new URLSearchParams({ - db_id: db_id - }) - - return await apiGet(`/api/graph/lightrag/labels?${queryParams.toString()}`, {}, true) - }, - - /** - * 获取LightRAG图谱统计信息 - * @param {string} db_id - LightRAG数据库ID + * 获取图谱统计信息 (统一接口) + * @param {string} db_id - 图谱ID * @returns {Promise} - 统计信息 */ getStats: async (db_id) => { @@ -76,10 +59,28 @@ export const lightragApi = { db_id: db_id }) - return await apiGet(`/api/graph/lightrag/stats?${queryParams.toString()}`, {}, true) + return await apiGet(`/api/graph/stats?${queryParams.toString()}`, {}, true) + }, + + /** + * 获取图谱标签列表 (统一接口) + * @param {string} db_id - 图谱ID + * @returns {Promise} - 标签列表 + */ + getLabels: async (db_id) => { + if (!db_id) { + throw new Error('db_id is required') + } + + const queryParams = new URLSearchParams({ + db_id: db_id + }) + + return await apiGet(`/api/graph/labels?${queryParams.toString()}`, {}, true) } } + // ============================================================================= // === Neo4j图数据库接口分组 === // ============================================================================= @@ -222,11 +223,21 @@ export const getGraphStats = async () => { return neo4jApi.getInfo() } -// 保持旧的分组导出，便于批量替换 +// 兼容性导出 - 使用统一接口替代旧有的 graphApi export const graphApi = { - getSubgraph: lightragApi.getSubgraph, - getDatabases: lightragApi.getDatabases, - getLabels: lightragApi.getLabels, - getStats: lightragApi.getStats, - ...neo4jApi // 临时兼容 + // 使用统一接口替代 LightRAG 接口 + getSubgraph: unifiedApi.getSubgraph, + getDatabases: async () => { + // 使用统一接口获取所有图谱，然后过滤出 LightRAG 类型的 + const response = await unifiedApi.getGraphs() + if (response.success) { + const lightragDbs = response.data.filter(graph => graph.type === 'lightrag') + return { success: true, data: { databases: lightragDbs } } + } + return response + }, + getLabels: unifiedApi.getLabels, + getStats: unifiedApi.getStats, + // 保留 Neo4j 接口 + ...neo4jApi } \ No newline at end of file diff --git a/web/src/components/GraphCanvas.vue b/web/src/components/GraphCanvas.vue index 0997c478..ba880cfd 100644 --- a/web/src/components/GraphCanvas.vue +++ b/web/src/components/GraphCanvas.vue @@ -37,7 +37,7 @@ const props = defineProps({ highlightKeywords: { type: Array, default: () => [] } }) -const emit = defineEmits(['ready', 'data-rendered']) +const emit = defineEmits(['ready', 'data-rendered', 'node-click', 'edge-click', 'canvas-click']) const container = ref(null) const rootEl = ref(null) @@ -88,6 +88,7 @@ function formatData() { data: { label: n[props.labelField] ?? n.name ?? String(n.id), degree: degrees.get(String(n.id)) || 0, + original: n // 保存原始数据 }, })) @@ -95,7 +96,10 @@ function formatData() { id: e.id ? String(e.id) : `edge-${idx}`, source: String(e.source_id), target: String(e.target_id), - data: { label: e.type ?? '' }, + data: { + label: e.type ?? '', + original: e // 保存原始数据 + }, })) return { nodes, edges } @@ -185,9 +189,38 @@ function initGraph() { unselectedState: 'inactive', // 未选中节点状态 multiple: true, trigger: ['shift'], + // 禁用默认的选中效果，避免与自定义事件冲突 + disableDefault: false, } ], }) + + // 绑定事件 + graphInstance.on('node:click', (evt) => { + const { target } = evt + // 获取节点ID + const nodeId = target.id + // 从 graph data 中找到对应的节点数据 + // 注意：G6 v5 的事件对象结构可能有所不同，这里假设 target.id 是节点ID + // 也可以通过 graphInstance.getNodeData(nodeId) 获取 + const nodeData = graphInstance.getNodeData(nodeId) + emit('node-click', nodeData) + }) + + graphInstance.on('edge:click', (evt) => { + const { target } = evt + const edgeId = target.id + const edgeData = graphInstance.getEdgeData(edgeId) + emit('edge-click', edgeData) + }) + + graphInstance.on('canvas:click', (evt) => { + // 只有点击画布空白处才触发 + if (!evt.target) { + emit('canvas-click') + } + }) + emit('ready', graphInstance) } diff --git a/web/src/components/GraphDetailPanel.vue b/web/src/components/GraphDetailPanel.vue new file mode 100644 index 00000000..4df34962 --- /dev/null +++ b/web/src/components/GraphDetailPanel.vue @@ -0,0 +1,167 @@ + + + + + diff --git a/web/src/components/KnowledgeGraphSection.vue b/web/src/components/KnowledgeGraphSection.vue index a9604fa1..3255e225 100644 --- a/web/src/components/KnowledgeGraphSection.vue +++ b/web/src/components/KnowledgeGraphSection.vue @@ -8,14 +8,49 @@

只有 LightRAG 类型的知识库支持知识图谱。

- +
+ + + + + + +
@@ -53,40 +88,19 @@ - - - - - diff --git a/web/src/components/LightRAGInfoPanel.vue b/web/src/components/LightRAGInfoPanel.vue new file mode 100644 index 00000000..d0a39ca9 --- /dev/null +++ b/web/src/components/LightRAGInfoPanel.vue @@ -0,0 +1,120 @@ + + + + + \ No newline at end of file diff --git a/web/src/composables/useGraph.js b/web/src/composables/useGraph.js new file mode 100644 index 00000000..5a126848 --- /dev/null +++ b/web/src/composables/useGraph.js @@ -0,0 +1,72 @@ +import { ref, reactive, nextTick } from 'vue'; + +export function useGraph(graphRef) { + const fetching = ref(false); + const showDetailDrawer = ref(false); + const selectedItem = ref(null); + const selectedItemType = ref(null); + + const graphData = reactive({ + nodes: [], + edges: [], + }); + + const handleNodeClick = (nodeData) => { + selectedItem.value = nodeData; + selectedItemType.value = 'node'; + showDetailDrawer.value = true; + console.log('Node clicked:', nodeData); + }; + + const handleEdgeClick = (edgeData) => { + selectedItem.value = edgeData; + selectedItemType.value = 'edge'; + showDetailDrawer.value = true; + console.log('Edge clicked:', edgeData); + }; + + const handleCanvasClick = () => { + showDetailDrawer.value = false; + selectedItem.value = null; + selectedItemType.value = null; + // Clear focus state on the graph component if available + if (graphRef && graphRef.value && graphRef.value.clearFocus) { + graphRef.value.clearFocus(); + } + }; + + const clearGraph = () => { + graphData.nodes = []; + graphData.edges = []; + handleCanvasClick(); + }; + + const updateGraphData = (nodes, edges) => { + graphData.nodes = nodes || []; + graphData.edges = edges || []; + // Refresh graph visual after data update + refreshGraph(); + }; + + const refreshGraph = () => { + nextTick(() => { + if (graphRef && graphRef.value && graphRef.value.refreshGraph) { + graphRef.value.refreshGraph(); + } + }); + }; + + return { + fetching, + graphData, + showDetailDrawer, + selectedItem, + selectedItemType, + handleNodeClick, + handleEdgeClick, + handleCanvasClick, + clearGraph, + updateGraphData, + refreshGraph, + }; +} diff --git a/web/src/views/GraphView.vue b/web/src/views/GraphView.vue index 20b4ce88..adde1629 100644 --- a/web/src/views/GraphView.vue +++ b/web/src/views/GraphView.vue @@ -13,13 +13,23 @@ title="图数据库" > - - + + + + - -
+

本页面展示的是 Neo4j 图数据库中的知识图谱信息。

具体展示内容包括：

    @@ -132,15 +162,13 @@

    注意：

    • 这里仅展示用户上传的实体和关系，不包含知识库中自动创建的图谱。
      • -
    • 查询逻辑基于 graphbase.py 中的 get_sample_nodes 方法实现：
      • +
    • 查询逻辑基于 graphbase.py 中的 get_sample_nodes 方法实现。
    - 
    MATCH (n:Entity)-[r]->(m:Entity)
-RETURN
-    {id: elementId(n), name: n.name} AS h,
-    {type: r.type, source_id: elementId(n), target_id: elementId(m)} AS r,
-    {id: elementId(m), name: m.name} AS t
-LIMIT $num
    -

    如需查看完整的 Neo4j 数据库内容，请使用 "Neo4j 浏览器" 按钮访问原生界面。

    +
+
+

本页面展示的是 LightRAG 知识库生成的图谱信息。

+

数据来源于选定的知识库实例。

+

支持通过实体名称进行模糊搜索，输入 "*" 可查看采样全图。

@@ -152,10 +180,14 @@ import { message } from 'ant-design-vue'; import { useConfigStore } from '@/stores/config'; import { UploadOutlined, SyncOutlined, GlobalOutlined, InfoCircleOutlined, SearchOutlined, ReloadOutlined, LoadingOutlined, HighlightOutlined } from '@ant-design/icons-vue'; import HeaderComponent from '@/components/HeaderComponent.vue'; -import { neo4jApi } from '@/apis/graph_api'; +import { neo4jApi, unifiedApi } from '@/apis/graph_api'; import { useUserStore } from '@/stores/user'; import GraphCanvas from '@/components/GraphCanvas.vue'; import GraphInfoPanel from '@/components/GraphInfoPanel.vue'; +import LightRAGInfoPanel from '@/components/LightRAGInfoPanel.vue'; +import GraphDetailPanel from '@/components/GraphDetailPanel.vue'; +import UploadModal from '@/components/FileUploadModal.vue'; +import { useGraph } from '@/composables/useGraph'; const configStore = useConfigStore(); const cur_embed_model = computed(() => configStore.config?.embed_model); @@ -165,14 +197,12 @@ const graphRef = ref(null) const graphInfo = ref(null) const fileList = ref([]); const sampleNodeCount = ref(100); -const graphData = reactive({ - nodes: [], - edges: [], -}); + +const graph = reactive(useGraph(graphRef)); const state = reactive({ - fetching: false, loadingGraphInfo: false, + loadingDatabases: false, searchInput: '', searchLoading: false, showModal: false, @@ -180,13 +210,66 @@ const state = reactive({ processing: false, indexing: false, showPage: true, + selectedDbId: 'neo4j', + dbOptions: [], + lightragStats: null, }) +const isNeo4j = computed(() => state.selectedDbId === 'neo4j'); + // 计算未索引节点数量 const unindexedCount = computed(() => { return graphInfo.value?.unindexed_node_count || 0; }); +const loadDatabases = async () => { + state.loadingDatabases = true; + try { + const res = await unifiedApi.getGraphs(); + if (res.success && res.data) { + state.dbOptions = res.data.map(db => ({ + label: `${db.name} (${db.type})`, + value: db.id, + type: db.type + })); + + // If no selection or invalid selection, select first + if (!state.selectedDbId || !state.dbOptions.find(o => o.value === state.selectedDbId)) { + if (state.dbOptions.length > 0) { + state.selectedDbId = state.dbOptions[0].value; + } + } + } + } catch (error) { + console.error('Failed to load databases:', error); + } finally { + state.loadingDatabases = false; + } +}; + +const handleDbChange = () => { + // Clear current data + graph.clearGraph(); + state.searchInput = ''; + state.lightragStats = null; + + if (isNeo4j.value) { + loadGraphInfo(); + } else { + // Also load stats for LightRAG + loadLightRAGStats(); + } + loadSampleNodes(); +}; + +const loadLightRAGStats = () => { + unifiedApi.getStats(state.selectedDbId).then(res => { + if(res.success) { + state.lightragStats = res.data; + } + }).catch(e => console.error(e)); +}; + const loadGraphInfo = () => { state.loadingGraphInfo = true neo4jApi.getInfo() @@ -222,20 +305,24 @@ const addDocumentByFile = () => { }; const loadSampleNodes = () => { - state.fetching = true - neo4jApi.getSampleNodes('neo4j', sampleNodeCount.value) + graph.fetching = true + + unifiedApi.getSubgraph({ + db_id: state.selectedDbId, + node_label: '*', + max_nodes: sampleNodeCount.value + }) .then((data) => { - graphData.nodes = data.result.nodes - graphData.edges = data.result.edges - console.log(graphData) - // 初次加载后兜底刷新一次，避免容器初次可见尺寸未稳定 - setTimeout(() => graphRef.value?.refreshGraph?.(), 500) + // Normalize data structure if needed + const result = data.data; + graph.updateGraphData(result.nodes, result.edges); + console.log(graph.graphData) }) .catch((error) => { console.error(error) message.error(error.message || '加载节点失败'); }) - .finally(() => state.fetching = false) + .finally(() => graph.fetching = false) } const onSearch = () => { @@ -244,29 +331,33 @@ const onSearch = () => { return } - if (graphInfo?.value?.embed_model_name !== cur_embed_model.value) { + if (isNeo4j.value && graphInfo?.value?.embed_model_name !== cur_embed_model.value) { // 可选：提示模型不一致 } - if (!state.searchInput) { + if (!state.searchInput && isNeo4j.value) { message.error('请输入要查询的实体') return } state.searchLoading = true - neo4jApi.queryNode(state.searchInput) + + unifiedApi.getSubgraph({ + db_id: state.selectedDbId, + node_label: state.searchInput || '*', + max_nodes: sampleNodeCount.value + }) .then((data) => { - if (!data.result || !data.result.nodes || !data.result.edges) { + const result = data.data; + if (!result || !result.nodes || !result.edges) { throw new Error('返回数据格式不正确'); } - graphData.nodes = data.result.nodes - graphData.edges = data.result.edges - if (graphData.nodes.length === 0) { + graph.updateGraphData(result.nodes, result.edges); + if (graph.graphData.nodes.length === 0) { message.info('未找到相关实体') } console.log(data) - console.log(graphData) - graphRef.value?.refreshGraph?.() + console.log(graph.graphData) }) .catch((error) => { console.error('查询错误:', error); @@ -275,8 +366,9 @@ const onSearch = () => { .finally(() => state.searchLoading = false) }; -onMounted(() => { - loadGraphInfo(); +onMounted(async () => { + await loadDatabases(); + loadGraphInfo(); // Load default (Neo4j) info loadSampleNodes(); }); @@ -332,9 +424,10 @@ const indexNodes = () => { const exportGraphData = () => { const dataStr = JSON.stringify({ - nodes: graphData.nodes, - edges: graphData.edges, - graphInfo: graphInfo.value, + nodes: graph.graphData.nodes, + edges: graph.graphData.edges, + graphInfo: isNeo4j.value ? graphInfo.value : state.lightragStats, + source: state.selectedDbId, exportTime: new Date().toISOString() }, null, 2); @@ -342,7 +435,7 @@ const exportGraphData = () => { const url = URL.createObjectURL(dataBlob); const link = document.createElement('a'); link.href = url; - link.download = `graph-data-${new Date().toISOString().slice(0, 10)}.json`; + link.download = `graph-data-${state.selectedDbId}-${new Date().toISOString().slice(0, 10)}.json`; document.body.appendChild(link); link.click(); document.body.removeChild(link); @@ -360,6 +453,11 @@ const openLink = (url) => { window.open(url, '_blank') } +const getDatabaseName = () => { + const selectedDb = state.dbOptions.find(db => db.value === state.selectedDbId); + return selectedDb ? selectedDb.label : state.selectedDbId; +}; + + \ No newline at end of file From cb9edfdb5eab0779409647a946fed10d9a5d5b21 Mon Sep 17 00:00:00 2001 From: Wenjie Zhang Date: Tue, 16 Dec 2025 00:10:05 +0800 Subject: [PATCH 4/6] =?UTF-8?q?feat(graph):=20=E6=94=AF=E6=8C=81=E5=B8=A6?= =?UTF-8?q?=E5=B1=9E=E6=80=A7=E7=9A=84=E7=9F=A5=E8=AF=86=E5=9B=BE=E8=B0=B1?= =?UTF-8?q?=E8=8A=82=E7=82=B9=E5=92=8C=E5=85=B3=E7=B3=BB=E5=AF=BC=E5=85=A5?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - 扩展三元组导入功能，支持节点和关系的属性存储 - 新增测试数据文件和单元测试验证功能 - 更新文档说明支持新旧两种数据格式 - 优化查询结果处理，保留并返回节点和关系的属性 --- docs/latest/intro/knowledge-base.md | 26 ++++- src/knowledge/graph.py | 160 ++++++++++++++++++++-------- test/data/complex_graph_test.jsonl | 6 ++ test/test_graph_unit.py | 96 +++++++++++++++++ 4 files changed, 242 insertions(+), 46 deletions(-) create mode 100644 test/data/complex_graph_test.jsonl create mode 100644 test/test_graph_unit.py diff --git a/docs/latest/intro/knowledge-base.md b/docs/latest/intro/knowledge-base.md index d0621ee5..995501fa 100644 --- a/docs/latest/intro/knowledge-base.md +++ b/docs/latest/intro/knowledge-base.md @@ -97,16 +97,32 @@ LIMIT $num ### 1. 以三元组形式导入 +系统支持通过网页导入 `jsonl` 格式的知识图谱数据，支持**简单三元组**和**带属性三元组**两种格式。 -系统支持通过网页导入 `jsonl` 格式的知识图谱数据： +**简单格式（兼容旧版）**： ```jsonl {"h": "北京", "t": "中国", "r": "首都"} {"h": "上海", "t": "中国", "r": "直辖市"} -{"h": "深圳", "t": "广东", "r": "省会"} ``` -**格式说明**，每行一个三元组，系统自动验证数据格式，并自动导入到 Neo4j 数据库，添加 `Upload`、`Entity`、`Relation` 标签，会自动处理重复的三元组。 +**扩展格式（支持属性）**： + +支持 `h`（头节点）、`t`（尾节点）和 `r`（关系）为对象结构，其中： +- 节点对象必须包含 `name` 字段。 +- 关系对象必须包含 `type` 字段。 +- 其他字段将作为**属性**存储在 Neo4j 中。 + +```jsonl +{"h": {"name": "孙悟空", "title": "齐天大圣", "weapon": "如意金箍棒"}, "t": {"name": "唐僧", "species": "人"}, "r": {"type": "徒弟", "order": 1}} +{"h": "猪八戒", "t": {"name": "唐僧"}, "r": {"type": "徒弟", "order": 2}} +``` + +**格式说明**： +- 每行一个数据项。 +- 系统自动验证数据格式，并自动导入到 Neo4j 数据库。 +- 自动添加 `Upload`、`Entity` 标签（节点）和 `RELATION` 类型（关系）。 +- 自动处理重复实体和关系，并合并属性。 Neo4j 访问信息可以参考 `docker-compose.yml` 中配置对应的环境变量来覆盖。 @@ -116,7 +132,9 @@ Neo4j 访问信息可以参考 `docker-compose.yml` 中配置对应的环境变 - **连接地址**: bolt://localhost:7687 ::: tip 测试数据 -可以使用 `test/data/A_Dream_of_Red_Mansions_tiny.jsonl` 文件进行测试导入。 +可以使用以下文件进行测试导入： +- 简单格式：`test/data/A_Dream_of_Red_Mansions_tiny.jsonl` +- 扩展属性格式：`test/data/complex_graph_test.jsonl` ::: ### 2. 接入已有 Neo4j 实例 diff --git a/src/knowledge/graph.py b/src/knowledge/graph.py index 61e2c85a..9d488f5f 100644 --- a/src/knowledge/graph.py +++ b/src/knowledge/graph.py @@ -64,6 +64,22 @@ class GraphDatabase: assert self.driver is not None, "Database is not connected" self.use_database(kgdb_name) + 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} + def query(tx, num): """Note: 使用连通性查询获取集中的节点子图""" # 首先尝试获取一个连通的子图 @@ -104,17 +120,18 @@ class GraphDatabase: OPTIONAL MATCH (n)-[rel]-(m) WHERE m IN final_nodes AND elementId(n) < elementId(m) RETURN - {id: elementId(n), name: n.name} AS h, + {id: elementId(n), name: n.name, properties: properties(n)} AS h, CASE WHEN rel IS NOT NULL THEN { id: elementId(rel), type: rel.type, source_id: elementId(startNode(rel)), - target_id: elementId(endNode(rel)) + target_id: elementId(endNode(rel)), + properties: properties(rel) } ELSE null END AS r, CASE WHEN m IS NOT NULL THEN - {id: elementId(m), name: m.name} + {id: elementId(m), name: m.name, properties: properties(m)} ELSE null END AS t """ @@ -124,7 +141,7 @@ class GraphDatabase: node_ids = set() for item in results: - h_node = item["h"] + h_node = _process_record_props(item["h"]) # 始终添加头节点 if h_node["id"] not in node_ids: @@ -133,14 +150,15 @@ class GraphDatabase: # 只有当边和尾节点都存在时才处理 if item["r"] is not None and item["t"] is not None: - t_node = item["t"] + t_node = _process_record_props(item["t"]) + r_edge = _process_record_props(item["r"]) # 避免重复添加尾节点 if t_node["id"] not in node_ids: formatted_results["nodes"].append(t_node) node_ids.add(t_node["id"]) - formatted_results["edges"].append(item["r"]) + formatted_results["edges"].append(r_edge) # 如果连通查询返回的节点数不足，补充更多节点 if len(formatted_results["nodes"]) < num: @@ -150,14 +168,14 @@ class GraphDatabase: supplement_query = """ MATCH (n:Entity) WHERE NOT elementId(n) IN $existing_ids - RETURN {id: elementId(n), name: n.name} AS node + RETURN {id: elementId(n), name: n.name, properties: properties(n)} AS node LIMIT $count """ supplement_results = tx.run(supplement_query, existing_ids=list(node_ids), count=remaining_count) for item in supplement_results: - node = item["node"] + node = _process_record_props(item["node"]) formatted_results["nodes"].append(node) node_ids.add(node["id"]) @@ -170,14 +188,15 @@ class GraphDatabase: MATCH (n:Entity)-[r]-(m:Entity) WHERE elementId(n) < elementId(m) RETURN - {id: elementId(n), name: n.name} AS h, + {id: elementId(n), name: n.name, properties: properties(n)} AS h, { id: elementId(r), type: r.type, source_id: elementId(startNode(r)), - target_id: elementId(endNode(r)) + target_id: elementId(endNode(r)), + properties: properties(r) } AS r, - {id: elementId(m), name: m.name} AS t + {id: elementId(m), name: m.name, properties: properties(m)} AS t LIMIT $num """ results = tx.run(fallback_query, num=int(num)) @@ -185,8 +204,9 @@ class GraphDatabase: node_ids = set() for item in results: - h_node = item["h"] - t_node = item["t"] + h_node = _process_record_props(item["h"]) + t_node = _process_record_props(item["t"]) + r_edge = _process_record_props(item["r"]) # 避免重复添加节点 if h_node["id"] not in node_ids: @@ -196,7 +216,7 @@ class GraphDatabase: formatted_results["nodes"].append(t_node) node_ids.add(t_node["id"]) - formatted_results["edges"].append(item["r"]) + formatted_results["edges"].append(r_edge) return formatted_results @@ -240,18 +260,47 @@ class GraphDatabase: return True return False + def _parse_node(node_data): + """解析节点数据，返回 (name, props)""" + if isinstance(node_data, dict): + props = node_data.copy() + name = props.pop("name", "") + return name, props + return str(node_data), {} + + def _parse_relation(rel_data): + """解析关系数据，返回 (type, props)""" + if isinstance(rel_data, dict): + props = rel_data.copy() + rel_type = props.pop("type", "") + return rel_type, props + return str(rel_data), {} + def _create_graph(tx, data): """添加一个三元组""" for entry in data: + h_name, h_props = _parse_node(entry.get("h")) + t_name, t_props = _parse_node(entry.get("t")) + r_type, r_props = _parse_relation(entry.get("r")) + + if not h_name or not t_name or not r_type: + continue + tx.run( """ - MERGE (h:Entity:Upload {name: $h}) - MERGE (t:Entity:Upload {name: $t}) - MERGE (h)-[r:RELATION {type: $r}]->(t) + MERGE (h:Entity:Upload {name: $h_name}) + SET h += $h_props + MERGE (t:Entity:Upload {name: $t_name}) + SET t += $t_props + MERGE (h)-[r:RELATION {type: $r_type}]->(t) + SET r += $r_props """, - h=entry["h"], - t=entry["t"], - r=entry["r"], + h_name=h_name, + h_props=h_props, + t_name=t_name, + t_props=t_props, + r_type=r_type, + r_props=r_props, ) def _create_vector_index(tx, dim): @@ -273,6 +322,9 @@ class GraphDatabase: # 构建参数字典，将列表转换为"param0"、"param1"等键值对形式 params = {f"param{i}": name for i, name in enumerate(entity_names)} + if not params: + return [] + # 构建查询参数列表 param_placeholders = ", ".join([f"${key}" for key in params.keys()]) @@ -315,20 +367,24 @@ class GraphDatabase: session.execute_write(_create_vector_index, getattr(cur_embed_info, "dimension", 1024)) # 收集所有需要处理的实体名称，去重 - all_entities = [] + all_entities = set() for entry in triples: - if entry["h"] not in all_entities: - all_entities.append(entry["h"]) - if entry["t"] not in all_entities: - all_entities.append(entry["t"]) + h_name, _ = _parse_node(entry.get("h")) + t_name, _ = _parse_node(entry.get("t")) + if h_name: + all_entities.add(h_name) + if t_name: + all_entities.add(t_name) + + all_entities_list = list(all_entities) # 筛选出没有embedding的节点 - nodes_without_embedding = session.execute_read(_get_nodes_without_embedding, all_entities) + nodes_without_embedding = session.execute_read(_get_nodes_without_embedding, all_entities_list) if not nodes_without_embedding: logger.info("所有实体已有embedding，无需重新计算") return - logger.info(f"需要为{len(nodes_without_embedding)}/{len(all_entities)}个实体计算embedding") + logger.info(f"需要为{len(nodes_without_embedding)}/{len(all_entities_list)}个实体计算embedding") # 批量处理实体 max_batch_size = 1024 # 限制此部分的主要是内存大小 1024 * 1024 * 4 / 1024 / 1024 = 4GB @@ -597,30 +653,46 @@ class GraphDatabase: self.use_database(kgdb_name) + 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} + def query(tx, entity_name, hops, limit): try: query_str = """ WITH [ // 1跳出边 [(n {name: $entity_name})-[r1]->(m1) | - {h: {id: elementId(n), name: n.name}, - r: {id: elementId(r1), type: r1.type, source_id: elementId(n), target_id: elementId(m1)}, - t: {id: elementId(m1), name: m1.name}}], + {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)}, + 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}, - r: {id: elementId(r2), type: r2.type, source_id: elementId(m1), target_id: elementId(m2)}, - t: {id: elementId(m2), name: m2.name}}], + {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)}, + 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}, - r: {id: elementId(r1), type: r1.type, source_id: elementId(m1), target_id: elementId(n)}, - t: {id: elementId(n), name: n.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)}, + 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}, - r: {id: elementId(r2), type: r2.type, source_id: elementId(m2), target_id: elementId(m1)}, - t: {id: elementId(m1), name: m1.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)}, + t: {id: elementId(m1), name: m1.name, properties: properties(m1)}}] ] AS all_results UNWIND all_results AS result_list UNWIND result_list AS item @@ -636,9 +708,13 @@ class GraphDatabase: formatted_results = {"nodes": [], "edges": [], "triples": []} for item in results: - formatted_results["nodes"].extend([item["h"], item["t"]]) - formatted_results["edges"].append(item["r"]) - formatted_results["triples"].append((item["h"]["name"], item["r"]["type"], item["t"]["name"])) + 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"])) logger.debug(f"Query Results: {results}") return formatted_results diff --git a/test/data/complex_graph_test.jsonl b/test/data/complex_graph_test.jsonl new file mode 100644 index 00000000..d36b0de9 --- /dev/null +++ b/test/data/complex_graph_test.jsonl @@ -0,0 +1,6 @@ +{"h": {"name": "孙悟空", "title": "齐天大圣", "weapon": "如意金箍棒", "species": "猴"}, "t": {"name": "唐僧", "title": "旃檀功德佛", "species": "人"}, "r": {"type": "徒弟", "order": 1}} +{"h": {"name": "猪八戒", "title": "天蓬元帅", "weapon": "九齿钉耙", "species": "猪"}, "t": {"name": "唐僧"}, "r": {"type": "徒弟", "order": 2}} +{"h": {"name": "沙悟净", "title": "卷帘大将", "weapon": "降妖宝杖"}, "t": {"name": "唐僧"}, "r": {"type": "徒弟", "order": 3}} +{"h": {"name": "白龙马", "origin": "西海龙宫"}, "t": {"name": "唐僧"}, "r": {"type": "坐骑", "original_form": "龙"}} +{"h": "孙悟空", "t": {"name": "猪八戒"}, "r": {"type": "师兄弟", "relationship": "conflict/cooperate"}} +{"h": {"name": "如来佛祖", "location": "西天雷音寺"}, "t": {"name": "孙悟空"}, "r": {"type": "压制", "tool": "五指山", "duration": "500年"}} \ No newline at end of file diff --git a/test/test_graph_unit.py b/test/test_graph_unit.py new file mode 100644 index 00000000..0afceb5e --- /dev/null +++ b/test/test_graph_unit.py @@ -0,0 +1,96 @@ +import pytest +from unittest.mock import MagicMock, AsyncMock, patch +import os +import sys + +# Add project root to path +sys.path.append(os.getcwd()) + +from src.knowledge.graph import GraphDatabase +from src import config + +@pytest.mark.asyncio +async def test_txt_add_vector_entity_parsing(): + # Mock driver and session + mock_driver = MagicMock() + mock_session = MagicMock() + mock_driver.session.return_value.__enter__.return_value = mock_session + + # Setup mock transaction + mock_tx = MagicMock() + def side_effect_execute_write(func, *args, **kwargs): + return func(mock_tx, *args, **kwargs) + + # Mock execute_read to return empty list (no missing embeddings for this test) + # The code calls _get_nodes_without_embedding which returns [record['name']] + # If we return [], it means all nodes have embeddings or none found. + # Actually, the code checks: + # nodes_without_embedding = session.execute_read(_get_nodes_without_embedding, all_entities) + # Let's mock it to return empty list so we skip embedding generation loop which simplifies test + mock_session.execute_read.return_value = [] + + mock_session.execute_write.side_effect = side_effect_execute_write + + # Mock embedding model + with patch('src.knowledge.graph.select_embedding_model') as mock_select_model: + mock_embed_model = MagicMock() + mock_select_model.return_value = mock_embed_model + + # Instantiate GraphDatabase with mocked driver + # We also need to patch GD.driver in the init + with patch('src.knowledge.graph.GD.driver', return_value=mock_driver): + gd = GraphDatabase() + # Manually set driver and status just in case init didn't work as expected due to other mocks + gd.driver = mock_driver + gd.status = "open" + gd.embed_model_name = "test_model" # avoid config check issues if possible + + # Mock config to match + with patch('src.knowledge.graph.config.embed_model', "test_model"): + with patch('src.knowledge.graph.config.embed_model_names', {"test_model": MagicMock(dimension=1024)}): + + # Test data: Mixed format + triples = [ + # Legacy format + {"h": "A", "r": "KNOWS", "t": "B"}, + # Extended format + { + "h": {"name": "C", "age": 30}, + "r": {"type": "LIKES", "weight": 0.8}, + "t": {"name": "D", "role": "User"} + } + ] + + # Run the method + await gd.txt_add_vector_entity(triples) + + # Verify calls to mock_tx.run + merge_calls = [] + for call in mock_tx.run.call_args_list: + args, kwargs = call + query = args[0] if args else kwargs.get('query', '') + if "MERGE (h:Entity:Upload" in query: + # The args are passed as kwargs to run: h_name=..., etc. + merge_calls.append(kwargs) + + assert len(merge_calls) == 2, f"Expected 2 merge calls, got {len(merge_calls)}" + + # Call 1 (Legacy) + call1 = merge_calls[0] + assert call1['h_name'] == "A" + assert call1['h_props'] == {} + assert call1['t_name'] == "B" + assert call1['t_props'] == {} + assert call1['r_type'] == "KNOWS" + assert call1['r_props'] == {} + + # Call 2 (Extended) + call2 = merge_calls[1] + assert call2['h_name'] == "C" + assert call2['h_props'] == {'age': 30} + assert call2['t_name'] == "D" + assert call2['t_props'] == {'role': 'User'} + assert call2['r_type'] == "LIKES" + assert call2['r_props'] == {'weight': 0.8} + + print("Verification passed!") From 75a7d46327bfa5e8a29138f8afc27ce250569a5d Mon Sep 17 00:00:00 2001 From: Wenjie Zhang Date: Tue, 16 Dec 2025 00:27:40 +0800 Subject: [PATCH 5/6] =?UTF-8?q?refactor(ui):=20=E7=A7=BB=E9=99=A4=E5=AF=BC?= =?UTF-8?q?=E5=87=BA=E6=95=B0=E6=8D=AE=E6=8C=89=E9=92=AE=E5=B9=B6=E4=BC=98?= =?UTF-8?q?=E5=8C=96=E4=B8=8A=E4=BC=A0=E6=96=87=E4=BB=B6=E6=8F=90=E7=A4=BA?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 重构多个面板组件，移除重复的导出数据按钮和相关样式代码 在GraphView中添加上传文件提示弹窗，根据数据库类型显示不同提示信息 --- web/src/components/GraphDetailPanel.vue | 2 +- web/src/components/GraphInfoPanel.vue | 49 +------------ web/src/components/LightRAGInfoPanel.vue | 50 +------------ web/src/views/GraphView.vue | 90 ++++++++++++++++++++++-- 4 files changed, 89 insertions(+), 102 deletions(-) diff --git a/web/src/components/GraphDetailPanel.vue b/web/src/components/GraphDetailPanel.vue index 4df34962..86fb9ff7 100644 --- a/web/src/components/GraphDetailPanel.vue +++ b/web/src/components/GraphDetailPanel.vue @@ -97,7 +97,7 @@ const filteredEdgeProperties = computed(() => { \ No newline at end of file diff --git a/web/src/views/GraphView.vue b/web/src/views/GraphView.vue index adde1629..32c5b6e7 100644 --- a/web/src/views/GraphView.vue +++ b/web/src/views/GraphView.vue @@ -30,7 +30,14 @@ - 上传文件 + 上传文件 + 上传文件 为{{ unindexedCount }}个节点添加索引 @@ -73,6 +80,9 @@
+ + 导出数据 + 说明 @@ -91,14 +101,12 @@ :unindexed-count="unindexedCount" :model-matched="modelMatched" @index-nodes="indexNodes" - @export-data="exportGraphData" />
@@ -144,6 +152,32 @@ + + +
+ +
+

如需上传文档到当前选中的知识库，请前往对应的知识库详情页面进行操作：

+
+ + 前往知识库详情页 + +
+
+
+ + import { computed, onMounted, reactive, ref, h } from 'vue'; +import { useRouter } from 'vue-router'; import { message } from 'ant-design-vue'; import { useConfigStore } from '@/stores/config'; -import { UploadOutlined, SyncOutlined, GlobalOutlined, InfoCircleOutlined, SearchOutlined, ReloadOutlined, LoadingOutlined, HighlightOutlined } from '@ant-design/icons-vue'; +import { UploadOutlined, SyncOutlined, GlobalOutlined, InfoCircleOutlined, SearchOutlined, ReloadOutlined, LoadingOutlined, HighlightOutlined, DatabaseOutlined, ExportOutlined } from '@ant-design/icons-vue'; import HeaderComponent from '@/components/HeaderComponent.vue'; import { neo4jApi, unifiedApi } from '@/apis/graph_api'; import { useUserStore } from '@/stores/user'; @@ -193,6 +228,7 @@ const configStore = useConfigStore(); const cur_embed_model = computed(() => configStore.config?.embed_model); const modelMatched = computed(() => !graphInfo?.value?.embed_model_name || graphInfo.value.embed_model_name === cur_embed_model.value) +const router = useRouter(); const graphRef = ref(null) const graphInfo = ref(null) const fileList = ref([]); @@ -207,6 +243,7 @@ const state = reactive({ searchLoading: false, showModal: false, showInfoModal: false, + showUploadTipModal: false, processing: false, indexing: false, showPage: true, @@ -458,6 +495,33 @@ const getDatabaseName = () => { return selectedDb ? selectedDb.label : state.selectedDbId; }; +const getUploadTipMessage = () => { + if (isNeo4j.value) { + return 'Neo4j 图数据库支持通过上传 JSONL 格式文件直接导入实体和关系数据。'; + } else { + const selectedDb = state.dbOptions.find(db => db.value === state.selectedDbId); + const dbType = selectedDb?.type || '未知'; + const dbName = selectedDb?.label || getDatabaseName(); + return `当前选择的是 ${dbType.toUpperCase()} 类型的知识库"${dbName}"，该类型知识库需要在文档知识库页面上传文档，系统会自动从中提取知识图谱。`; + } +}; + +const goToDatabasePage = () => { + state.showUploadTipModal = false; + + // 如果不是 Neo4j，需要找到对应的知识库 ID 并跳转 + if (!isNeo4j.value) { + const selectedDb = state.dbOptions.find(db => db.value === state.selectedDbId); + if (selectedDb && selectedDb.type !== 'neo4j') { + // 跳转到对应的知识库详情页面 + router.push(`/database/${state.selectedDbId}`); + } else { + // 如果找不到对应的数据库，跳转到数据库列表页面 + router.push('/database'); + } + } +}; + \ No newline at end of file From 5f6047849c1204fb545adf725134be9e5cf76850 Mon Sep 17 00:00:00 2001 From: Wenjie Zhang Date: Tue, 16 Dec 2025 10:28:44 +0800 Subject: [PATCH 6/6] =?UTF-8?q?refactor:=20=E4=BC=98=E5=8C=96=E4=BB=A3?= =?UTF-8?q?=E7=A0=81=E6=A0=BC=E5=BC=8F=E5=92=8C=E7=BB=93=E6=9E=84=EF=BC=8C?= =?UTF-8?q?=E6=94=B9=E8=BF=9B=E9=94=99=E8=AF=AF=E6=8F=90=E7=A4=BA=E4=BF=A1?= =?UTF-8?q?=E6=81=AF?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - 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 --- server/routers/graph_router.py | 72 +++++++++++------------ src/agents/common/toolkits/mysql/tools.py | 4 +- src/knowledge/adapters/lightrag.py | 19 ++---- src/knowledge/adapters/upload.py | 11 ++-- src/knowledge/graph.py | 46 +++++++++++---- src/knowledge/implementations/lightrag.py | 2 +- test/api/test_unified_graph_router.py | 42 ++++--------- test/test_graph_unit.py | 68 ++++++++++----------- web/src/components/GraphCanvas.vue | 4 +- 9 files changed, 128 insertions(+), 140 deletions(-) diff --git a/server/routers/graph_router.py b/server/routers/graph_router.py index 1f816cfa..552e16fb 100644 --- a/server/routers/graph_router.py +++ b/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 @@ -175,8 +177,7 @@ 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 { @@ -184,14 +185,14 @@ async def get_graph_stats( "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 ) diff --git a/src/agents/common/toolkits/mysql/tools.py b/src/agents/common/toolkits/mysql/tools.py index 3a255806..69af8238 100644 --- a/src/agents/common/toolkits/mysql/tools.py +++ b/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 diff --git a/src/knowledge/adapters/lightrag.py b/src/knowledge/adapters/lightrag.py index f4b2206d..1b130209 100644 --- a/src/knowledge/adapters/lightrag.py +++ b/src/knowledge/adapters/lightrag.py @@ -63,7 +63,7 @@ class LightRAGGraphAdapter(GraphAdapter): # 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 @@ class LightRAGGraphAdapter(GraphAdapter): 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 @@ class LightRAGGraphAdapter(GraphAdapter): 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 @@ class LightRAGGraphAdapter(GraphAdapter): 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]: diff --git a/src/knowledge/adapters/upload.py b/src/knowledge/adapters/upload.py index a46188f1..3d4d3810 100644 --- a/src/knowledge/adapters/upload.py +++ b/src/knowledge/adapters/upload.py @@ -19,15 +19,12 @@ class UploadGraphAdapter(GraphAdapter): 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 @@ class UploadGraphAdapter(GraphAdapter): 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 @@ class UploadGraphAdapter(GraphAdapter): 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]: diff --git a/src/knowledge/graph.py b/src/knowledge/graph.py index 9d488f5f..bfd325c1 100644 --- a/src/knowledge/graph.py +++ b/src/knowledge/graph.py @@ -68,15 +68,15 @@ class GraphDatabase: """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 @@ class GraphDatabase: """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 @@ class GraphDatabase: // 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 @@ class GraphDatabase: 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"])) diff --git a/src/knowledge/implementations/lightrag.py b/src/knowledge/implementations/lightrag.py index cdddd5f2..d62d1f44 100644 --- a/src/knowledge/implementations/lightrag.py +++ b/src/knowledge/implementations/lightrag.py @@ -235,7 +235,7 @@ class LightRagKB(KnowledgeBase): 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]: diff --git a/test/api/test_unified_graph_router.py b/test/api/test_unified_graph_router.py index fa23c916..632b1b7f 100644 --- a/test/api/test_unified_graph_router.py +++ b/test/api/test_unified_graph_router.py @@ -17,12 +17,12 @@ async def test_get_graphs_list(test_client, admin_headers): assert payload["success"] is True graphs = payload["data"] assert isinstance(graphs, list) - + # Check for Neo4j default graph neo4j_graph = next((g for g in graphs if g["id"] == "neo4j"), None) assert neo4j_graph is not None assert neo4j_graph["type"] == "neo4j" - + # Note: LightRAG graphs might be empty if none created, but we check structure @@ -30,9 +30,7 @@ async def test_get_subgraph_neo4j(test_client, admin_headers): """Test unified subgraph query for Neo4j.""" # Query with a wildcard or a known node. Using "*" to get a sample. response = await test_client.get( - "/api/graph/subgraph", - params={"db_id": "neo4j", "node_label": "*", "max_nodes": 10}, - headers=admin_headers + "/api/graph/subgraph", params={"db_id": "neo4j", "node_label": "*", "max_nodes": 10}, headers=admin_headers ) assert response.status_code == 200 payload = response.json() @@ -47,9 +45,7 @@ async def test_get_subgraph_lightrag(test_client, admin_headers, knowledge_datab """Test unified subgraph query for LightRAG.""" db_id = knowledge_database["db_id"] response = await test_client.get( - "/api/graph/subgraph", - params={"db_id": db_id, "node_label": "*", "max_nodes": 10}, - headers=admin_headers + "/api/graph/subgraph", params={"db_id": db_id, "node_label": "*", "max_nodes": 10}, headers=admin_headers ) assert response.status_code == 200 payload = response.json() @@ -61,11 +57,7 @@ async def test_get_subgraph_lightrag(test_client, admin_headers, knowledge_datab async def test_get_stats_neo4j(test_client, admin_headers): """Test stats endpoint for Neo4j.""" - response = await test_client.get( - "/api/graph/stats", - params={"db_id": "neo4j"}, - headers=admin_headers - ) + response = await test_client.get("/api/graph/stats", params={"db_id": "neo4j"}, headers=admin_headers) assert response.status_code == 200 payload = response.json() assert payload["success"] is True @@ -78,11 +70,7 @@ async def test_get_stats_neo4j(test_client, admin_headers): async def test_get_stats_lightrag(test_client, admin_headers, knowledge_database): """Test stats endpoint for LightRAG.""" db_id = knowledge_database["db_id"] - response = await test_client.get( - "/api/graph/stats", - params={"db_id": db_id}, - headers=admin_headers - ) + response = await test_client.get("/api/graph/stats", params={"db_id": db_id}, headers=admin_headers) assert response.status_code == 200 payload = response.json() assert payload["success"] is True @@ -94,11 +82,7 @@ async def test_get_stats_lightrag(test_client, admin_headers, knowledge_database async def test_get_labels_neo4j(test_client, admin_headers): """Test labels endpoint for Neo4j.""" - response = await test_client.get( - "/api/graph/labels", - params={"db_id": "neo4j"}, - headers=admin_headers - ) + response = await test_client.get("/api/graph/labels", params={"db_id": "neo4j"}, headers=admin_headers) assert response.status_code == 200 payload = response.json() assert payload["success"] is True @@ -109,12 +93,10 @@ async def test_get_labels_neo4j(test_client, admin_headers): async def test_deprecated_neo4j_endpoints(test_client, admin_headers): """Verify deprecated endpoints still work and return correct structure.""" - + # /neo4j/nodes response = await test_client.get( - "/api/graph/neo4j/nodes", - params={"kgdb_name": "neo4j", "num": 5}, - headers=admin_headers + "/api/graph/neo4j/nodes", params={"kgdb_name": "neo4j", "num": 5}, headers=admin_headers ) assert response.status_code == 200 payload = response.json() @@ -123,13 +105,11 @@ async def test_deprecated_neo4j_endpoints(test_client, admin_headers): assert "result" in payload assert payload["message"] == "success" assert "nodes" in payload["result"] - + # /neo4j/node # This might return empty if "NonExistentEntity" doesn't exist, but structure should be valid response = await test_client.get( - "/api/graph/neo4j/node", - params={"entity_name": "NonExistentEntity"}, - headers=admin_headers + "/api/graph/neo4j/node", params={"entity_name": "NonExistentEntity"}, headers=admin_headers ) assert response.status_code == 200 payload = response.json() diff --git a/test/test_graph_unit.py b/test/test_graph_unit.py index 0afceb5e..4c1b9d89 100644 --- a/test/test_graph_unit.py +++ b/test/test_graph_unit.py @@ -1,5 +1,5 @@ import pytest -from unittest.mock import MagicMock, AsyncMock, patch +from unittest.mock import MagicMock, patch import os import sys @@ -7,7 +7,7 @@ import sys sys.path.append(os.getcwd()) from src.knowledge.graph import GraphDatabase -from src import config + @pytest.mark.asyncio async def test_txt_add_vector_entity_parsing(): @@ -15,40 +15,40 @@ async def test_txt_add_vector_entity_parsing(): mock_driver = MagicMock() mock_session = MagicMock() mock_driver.session.return_value.__enter__.return_value = mock_session - + # Setup mock transaction mock_tx = MagicMock() + def side_effect_execute_write(func, *args, **kwargs): return func(mock_tx, *args, **kwargs) - + # Mock execute_read to return empty list (no missing embeddings for this test) # The code calls _get_nodes_without_embedding which returns [record['name']] # If we return [], it means all nodes have embeddings or none found. # Actually, the code checks: # nodes_without_embedding = session.execute_read(_get_nodes_without_embedding, all_entities) # Let's mock it to return empty list so we skip embedding generation loop which simplifies test - mock_session.execute_read.return_value = [] - + mock_session.execute_read.return_value = [] + mock_session.execute_write.side_effect = side_effect_execute_write # Mock embedding model - with patch('src.knowledge.graph.select_embedding_model') as mock_select_model: + with patch("src.knowledge.graph.select_embedding_model") as mock_select_model: mock_embed_model = MagicMock() mock_select_model.return_value = mock_embed_model - + # Instantiate GraphDatabase with mocked driver # We also need to patch GD.driver in the init - with patch('src.knowledge.graph.GD.driver', return_value=mock_driver): + with patch("src.knowledge.graph.GD.driver", return_value=mock_driver): gd = GraphDatabase() # Manually set driver and status just in case init didn't work as expected due to other mocks gd.driver = mock_driver gd.status = "open" - gd.embed_model_name = "test_model" # avoid config check issues if possible - - # Mock config to match - with patch('src.knowledge.graph.config.embed_model', "test_model"): - with patch('src.knowledge.graph.config.embed_model_names', {"test_model": MagicMock(dimension=1024)}): + gd.embed_model_name = "test_model" # avoid config check issues if possible + # Mock config to match + with patch("src.knowledge.graph.config.embed_model", "test_model"): + with patch("src.knowledge.graph.config.embed_model_names", {"test_model": MagicMock(dimension=1024)}): # Test data: Mixed format triples = [ # Legacy format @@ -57,40 +57,40 @@ async def test_txt_add_vector_entity_parsing(): { "h": {"name": "C", "age": 30}, "r": {"type": "LIKES", "weight": 0.8}, - "t": {"name": "D", "role": "User"} - } + "t": {"name": "D", "role": "User"}, + }, ] # Run the method await gd.txt_add_vector_entity(triples) - + # Verify calls to mock_tx.run merge_calls = [] for call in mock_tx.run.call_args_list: args, kwargs = call - query = args[0] if args else kwargs.get('query', '') + query = args[0] if args else kwargs.get("query", "") if "MERGE (h:Entity:Upload" in query: # The args are passed as kwargs to run: h_name=..., etc. merge_calls.append(kwargs) - + assert len(merge_calls) == 2, f"Expected 2 merge calls, got {len(merge_calls)}" - + # Call 1 (Legacy) call1 = merge_calls[0] - assert call1['h_name'] == "A" - assert call1['h_props'] == {} - assert call1['t_name'] == "B" - assert call1['t_props'] == {} - assert call1['r_type'] == "KNOWS" - assert call1['r_props'] == {} - + assert call1["h_name"] == "A" + assert call1["h_props"] == {} + assert call1["t_name"] == "B" + assert call1["t_props"] == {} + assert call1["r_type"] == "KNOWS" + assert call1["r_props"] == {} + # Call 2 (Extended) call2 = merge_calls[1] - assert call2['h_name'] == "C" - assert call2['h_props'] == {'age': 30} - assert call2['t_name'] == "D" - assert call2['t_props'] == {'role': 'User'} - assert call2['r_type'] == "LIKES" - assert call2['r_props'] == {'weight': 0.8} - + assert call2["h_name"] == "C" + assert call2["h_props"] == {"age": 30} + assert call2["t_name"] == "D" + assert call2["t_props"] == {"role": "User"} + assert call2["r_type"] == "LIKES" + assert call2["r_props"] == {"weight": 0.8} + print("Verification passed!") diff --git a/web/src/components/GraphCanvas.vue b/web/src/components/GraphCanvas.vue index ba880cfd..9458be8e 100644 --- a/web/src/components/GraphCanvas.vue +++ b/web/src/components/GraphCanvas.vue @@ -96,7 +96,7 @@ function formatData() { id: e.id ? String(e.id) : `edge-${idx}`, source: String(e.source_id), target: String(e.target_id), - data: { + data: { label: e.type ?? '', original: e // 保存原始数据 }, @@ -397,7 +397,7 @@ defineExpose({ position: relative; width: 100%; height: 100%; - background-color: var(--gray-0); + // background-color: var(--gray-0); .graph-canvas { width: 100%;