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@@ -31,7 +31,7 @@
|
||||
|
||||
| 模块 | 现有能力
|
||||
|:----------:|---
|
||||
| **模型管理** | 多模型接入(OpenAI/DeepSeek/通义/智谱)、多模态理解、Coze/DIFY/FastGPT平台集成
|
||||
| **模型管理** | 多模型接入(OpenAI/DeepSeek/通义/智谱/MiniMax)、多模态理解、Coze/DIFY/FastGPT平台集成
|
||||
| **知识管理** | 本地RAG + 向量库(Milvus/Weaviate/Qdrant) + 文档解析
|
||||
| **工具管理** | Mcp协议集成、Skills能力 + 可扩展工具生态
|
||||
| **流程编排** | 可视化工作流设计器、节点拖拽编排、SSE流式执行,目前已经支持模型调用,邮件发送,人工审核等节点
|
||||
|
||||
@@ -34,7 +34,7 @@
|
||||
|
||||
| Module | Current Capabilities |
|
||||
|:---:|---|
|
||||
| **Model Management** | Multi-model integration (OpenAI/DeepSeek/Tongyi/Zhipu), multi-modal understanding, Coze/DIFY/FastGPT platform integration |
|
||||
| **Model Management** | Multi-model integration (OpenAI/DeepSeek/Tongyi/Zhipu/MiniMax), multi-modal understanding, Coze/DIFY/FastGPT platform integration |
|
||||
| **Knowledge Base** | Local RAG + Vector DB (Milvus/Weaviate/Qdrant) + Document parsing |
|
||||
| **Tool Management** | MCP protocol integration, Skills capability + Extensible tool ecosystem |
|
||||
| **Workflow Orchestration** | Visual workflow designer, drag-and-drop node orchestration, SSE streaming execution, currently supports model calls, email sending, manual review nodes |
|
||||
|
||||
@@ -72,8 +72,9 @@ CREATE TABLE `chat_model` (
|
||||
-- ----------------------------
|
||||
-- Records of chat_model
|
||||
-- ----------------------------
|
||||
INSERT INTO `chat_model` VALUES (2000585866022060033, 'chat', 'deepseek/deepseek-v3.2', 'ppio', 'deepseek', NULL, 'Y', 'https://api.ppinfra.com/openai', 'sk_xx', 103, 1, '2025-12-15 23:16:54', 1, '2026-03-15 19:18:48', 'DeepSeek-V3.2 是一款在高效推理、复杂推理能力与智能体场景中表现突出的领先模型。其基于 DeepSeek Sparse Attention（DSA）稀疏注意力机制，在显著降低计算开销的同时优化长上下文性能；通过可扩展强化学习框架，整体能力达到 GPT-5 同级，高算力版本 V3.2-Speciale 更在推理表现上接近 Gemini-3.0-Pro；同时，模型依托大型智能体任务合成管线，具备更强的工具调用与多步骤决策能力，并在 2025 年 IMO 与 IOI 中取得金牌级表现。作为 MaaS 平台，我们已对 DeepSeek-V3.2 完成深度适配，通过动态调度、批处理加速、低延迟推理与企业级 SLA 保障，进一步增强其在企业生产环境中的稳定性、性价比与可控性，适用于搜索、问答、智能体、代码、数据处理等多类高价值场景。', 0);
|
||||
INSERT INTO `chat_model` VALUES (2007528268536287233, 'vector', 'baai/bge-m3', 'ppio', 'bge-m3', 1024, 'N', 'https://api.ppinfra.com/openai', 'sk_xx', 103, 1, '2026-01-04 03:03:32', 1, '2026-03-15 19:18:51', 'BGE-M3 是一款具备多维度能力的文本嵌入模型，可同时实现密集检索、多向量检索和稀疏检索三大核心功能。该模型设计上兼容超过100种语言，并支持从短句到长达8192词元的长文本等多种输入形式。在跨语言检索任务中，BGE-M3展现出显著优势，其性能在MIRACL、MKQA等国际基准测试中位居前列。此外，针对长文档检索场景，该模型在MLDR、NarritiveQA等数据集上的表现同样达到行业领先水平。', 0);
|
||||
INSERT INTO `chat_model` VALUES (2000585866022060033, 'chat', 'zai-org/glm-5', 'ppio', 'zai-org/glm-5', NULL, 'Y', 'https://api.ppio.com/openai', 'sk_xx', 103, 1, '2025-12-15 23:16:54', 1, '2026-03-15 19:18:48', 'DeepSeek-V3.2 是一款在高效推理、复杂推理能力与智能体场景中表现突出的领先模型。其基于 DeepSeek Sparse Attention（DSA）稀疏注意力机制，在显著降低计算开销的同时优化长上下文性能；通过可扩展强化学习框架，整体能力达到 GPT-5 同级，高算力版本 V3.2-Speciale 更在推理表现上接近 Gemini-3.0-Pro；同时，模型依托大型智能体任务合成管线，具备更强的工具调用与多步骤决策能力，并在 2025 年 IMO 与 IOI 中取得金牌级表现。作为 MaaS 平台，我们已对 DeepSeek-V3.2 完成深度适配，通过动态调度、批处理加速、低延迟推理与企业级 SLA 保障，进一步增强其在企业生产环境中的稳定性、性价比与可控性，适用于搜索、问答、智能体、代码、数据处理等多类高价值场景。', 0);
|
||||
INSERT INTO `chat_model` VALUES (2007528268536287233, 'vector', 'baai/bge-m3', 'ppio', 'bge-m3', 1024, 'N', 'https://api.ppio.com/openai', 'sk_xx', 103, 1, '2026-01-04 03:03:32', 1, '2026-03-15 19:18:51', 'BGE-M3 是一款具备多维度能力的文本嵌入模型，可同时实现密集检索、多向量检索和稀疏检索三大核心功能。该模型设计上兼容超过100种语言，并支持从短句到长达8192词元的长文本等多种输入形式。在跨语言检索任务中，BGE-M3展现出显著优势，其性能在MIRACL、MKQA等国际基准测试中位居前列。此外，针对长文档检索场景，该模型在MLDR、NarritiveQA等数据集上的表现同样达到行业领先水平。', 0);
|
||||
INSERT INTO `chat_model` VALUES (2045735140488847361, 'chat', 'deepseek-chat', 'custom_api', 'deepseek-chat', NULL, NULL, 'https://api.deepseek.com', 'sk_xx', 103, 1, '2026-04-19 13:24:00', 1, '2026-04-19 13:24:00', 'deepseek对话模型', 0);
|
||||
|
||||
-- ----------------------------
|
||||
-- Table structure for chat_provider
|
||||
@@ -95,22 +96,26 @@ CREATE TABLE `chat_provider` (
|
||||
`update_time` datetime NULL DEFAULT NULL COMMENT '更新时间',
|
||||
`remark` varchar(500) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '备注',
|
||||
`version` int NULL DEFAULT NULL COMMENT '版本',
|
||||
`del_flag` char(1) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT '0' COMMENT '删除标志（0代表存在 1代表删除）',
|
||||
`del_flag` char(1) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT '0' COMMENT '删除标志',
|
||||
`update_ip` varchar(128) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '更新IP',
|
||||
`tenant_id` bigint NOT NULL DEFAULT 0 COMMENT '租户Id',
|
||||
PRIMARY KEY (`id`) USING BTREE,
|
||||
UNIQUE INDEX `unique_provider_code`(`provider_code` ASC, `tenant_id` ASC) USING BTREE,
|
||||
UNIQUE INDEX `unique_provider_code`(`provider_code` ASC, `tenant_id` ASC, `del_flag` ASC) USING BTREE,
|
||||
INDEX `idx_status`(`status` ASC) USING BTREE
|
||||
) ENGINE = InnoDB AUTO_INCREMENT = 2008460994477690882 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_0900_ai_ci COMMENT = '厂商管理表' ROW_FORMAT = DYNAMIC;
|
||||
) ENGINE = InnoDB AUTO_INCREMENT = 2045727230803255298 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_0900_ai_ci COMMENT = '厂商管理表' ROW_FORMAT = DYNAMIC;
|
||||
|
||||
-- ----------------------------
|
||||
-- Records of chat_provider
|
||||
-- ----------------------------
|
||||
INSERT INTO `chat_provider` VALUES (1, 'OpenAI', 'openai', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/01091be272334383a1efd9bc22b73ee6.png', 'OpenAI官方API服务商', 'https://api.openai.com', '0', 1, NULL, '2025-12-14 21:48:11', '1', '1', '2026-02-25 20:46:59', 'OpenAI厂商', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (2, '阿里云百炼', 'qianwen', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/de2aa7e649de44f3ba5c6380ac6acd04.png', '阿里云百炼大模型服务', 'https://dashscope.aliyuncs.com', '0', 2, NULL, '2025-12-14 21:48:11', '1', '1', '2026-02-25 20:49:13', '阿里云厂商', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (3, '智谱AI', 'zhipu', 'https://ruoyi-ai-1254149996.cos.ap-guangzhou.myqcloud.com/2025/12/15/a43e98fb7b3b4861b8caa6184e6fa40a.png', '智谱AI大模型服务', 'https://open.bigmodel.cn', '0', 3, NULL, '2025-12-14 21:48:11', '1', '1', '2026-02-06 00:49:14', '智谱AI厂商', NULL, '1', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (5, 'ollama', 'ollama', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/afecabebc8014d80b0f06b4796a74c5d.png', 'ollama大模型', 'http://127.0.0.1:11434', '0', 5, NULL, '2025-12-14 21:48:11', '1', '1', '2026-02-25 20:48:48', 'ollama厂商', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (2000585060904435714, 'PPIO', 'ppio', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/049bb6a507174f73bba4b8d8b9e55b8a.png', 'api聚合厂商', 'https://api.ppinfra.com/openai', '0', 5, 103, '2025-12-15 23:13:42', '1', '1', '2026-02-25 20:49:01', 'api聚合厂商', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (1, 'OpenAI', 'openai', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/01091be272334383a1efd9bc22b73ee6.png', 'OpenAI官方API服务商', 'https://api.openai.com', '0', 1, 103, '2025-12-14 21:48:11', '1', '1', '2026-02-25 20:46:59', 'OpenAI厂商', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (11, '深度求索', 'deepseek', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/04/19/5ba8c30f153246898a4d7dc7b846de8d.png', 'DeepSeek官方API', 'https://api.deepseek.com', '0', 0, 103, '2026-04-19 12:52:34', '1', '1', '2026-04-19 13:13:25', 'DeepSeek官方API', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (12, '智谱AI', 'zhipu', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/04/19/da071783c9284fdd9ed1ce1b57b3c75c.png', '智谱AI大模型服务', 'https://open.bigmodel.cn', '0', 4, 103, '2025-12-14 21:48:11', '1', '1', '2026-04-19 13:14:00', '智谱AI厂商', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (13, '小米MIMO', 'xiaomi', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/04/19/18dd39365ce244e3ae5e030da036760e.png', '小米官方API', 'https://api.xiaomimimo.com/anthropic/v1/messages', '0', 3, 103, '2026-04-19 12:48:24', '1', '1', '2026-04-19 13:14:22', '小米官方API', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (14, '阿里云百炼', 'qianwen', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/de2aa7e649de44f3ba5c6380ac6acd04.png', '阿里云百炼大模型服务', 'https://dashscope.aliyuncs.com', '0', 2, 103, '2025-12-14 21:48:11', '1', '1', '2026-02-25 20:49:13', '阿里云厂商', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (15, 'PPIO', 'ppio', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/049bb6a507174f73bba4b8d8b9e55b8a.png', 'api聚合厂商', 'https://api.ppinfra.com/openai', '0', 5, 103, '2025-12-15 23:13:42', '1', '1', '2026-02-25 20:49:01', 'api聚合厂商', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (16, 'MiniMax', 'minimax', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/04/19/fdc712e90e0e4d78b05862ad230884e5.png', 'MiniMax大模型服务，支持M2.7、M2.5等模型', 'https://api.minimax.io/v1', '0', 6, 103, '2026-04-19 12:50:12', '1', '1', '2026-04-19 13:14:59', 'MiniMax厂商', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (17, 'ollama', 'ollama', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/afecabebc8014d80b0f06b4796a74c5d.png', 'ollama大模型', 'http://127.0.0.1:11434', '0', 7, 103, '2025-12-14 21:48:11', '1', '1', '2026-02-25 20:48:48', 'ollama厂商', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (18, '自定义厂商', 'custom_api', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/04/19/c1a8e122510f4e2f90deb36958af710b.png', 'OPENAI兼容格式', '自定义', '0', 8, 103, '2026-04-19 12:35:57', '1', '1', '2026-04-19 13:17:20', 'OPENAI兼容格式', NULL, '0', NULL, 0);
|
||||
|
||||
-- ----------------------------
|
||||
-- Table structure for chat_session
|
||||
|
||||
92
docs/script/sql/update/updat-0419.sql
Normal file
92
docs/script/sql/update/updat-0419.sql
Normal file
@@ -0,0 +1,92 @@
|
||||
/*
|
||||
Navicat Premium Dump SQL
|
||||
|
||||
Source Server : localhost-mysql
|
||||
Source Server Type : MySQL
|
||||
Source Server Version : 80045 (8.0.45)
|
||||
Source Host : localhost:3306
|
||||
Source Schema : ruoyi-ai
|
||||
|
||||
Target Server Type : MySQL
|
||||
Target Server Version : 80045 (8.0.45)
|
||||
File Encoding : 65001
|
||||
|
||||
Date: 19/04/2026 13:36:41
|
||||
*/
|
||||
|
||||
SET NAMES utf8mb4;
|
||||
SET FOREIGN_KEY_CHECKS = 0;
|
||||
|
||||
-- ----------------------------
|
||||
-- Table structure for chat_model
|
||||
-- ----------------------------
|
||||
DROP TABLE IF EXISTS `chat_model`;
|
||||
CREATE TABLE `chat_model` (
|
||||
`id` bigint NOT NULL COMMENT '主键',
|
||||
`category` varchar(20) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '模型分类',
|
||||
`model_name` varchar(50) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '模型名称',
|
||||
`provider_code` varchar(20) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '模型供应商',
|
||||
`model_describe` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '模型描述',
|
||||
`model_dimension` int NULL DEFAULT NULL COMMENT '模型维度',
|
||||
`model_show` char(1) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '是否显示',
|
||||
`api_host` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '请求地址',
|
||||
`api_key` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '密钥',
|
||||
`create_dept` bigint NULL DEFAULT NULL COMMENT '创建部门',
|
||||
`create_by` bigint NULL DEFAULT NULL COMMENT '创建者',
|
||||
`create_time` datetime NULL DEFAULT NULL COMMENT '创建时间',
|
||||
`update_by` bigint NULL DEFAULT NULL COMMENT '更新者',
|
||||
`update_time` datetime NULL DEFAULT NULL COMMENT '更新时间',
|
||||
`remark` varchar(500) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '备注',
|
||||
`tenant_id` bigint NOT NULL DEFAULT 0 COMMENT '租户Id',
|
||||
PRIMARY KEY (`id`) USING BTREE
|
||||
) ENGINE = InnoDB CHARACTER SET = utf8mb4 COLLATE = utf8mb4_0900_ai_ci COMMENT = '模型管理' ROW_FORMAT = DYNAMIC;
|
||||
|
||||
-- ----------------------------
|
||||
-- Records of chat_model
|
||||
-- ----------------------------
|
||||
INSERT INTO `chat_model` VALUES (2000585866022060033, 'chat', 'zai-org/glm-5', 'ppio', 'zai-org/glm-5', NULL, 'Y', 'https://api.ppio.com/openai', 'sk_xx', 103, 1, '2025-12-15 23:16:54', 1, '2026-03-15 19:18:48', 'DeepSeek-V3.2 是一款在高效推理、复杂推理能力与智能体场景中表现突出的领先模型。其基于 DeepSeek Sparse Attention（DSA）稀疏注意力机制，在显著降低计算开销的同时优化长上下文性能；通过可扩展强化学习框架，整体能力达到 GPT-5 同级，高算力版本 V3.2-Speciale 更在推理表现上接近 Gemini-3.0-Pro；同时，模型依托大型智能体任务合成管线，具备更强的工具调用与多步骤决策能力，并在 2025 年 IMO 与 IOI 中取得金牌级表现。作为 MaaS 平台，我们已对 DeepSeek-V3.2 完成深度适配，通过动态调度、批处理加速、低延迟推理与企业级 SLA 保障，进一步增强其在企业生产环境中的稳定性、性价比与可控性，适用于搜索、问答、智能体、代码、数据处理等多类高价值场景。', 0);
|
||||
INSERT INTO `chat_model` VALUES (2007528268536287233, 'vector', 'baai/bge-m3', 'ppio', 'bge-m3', 1024, 'N', 'https://api.ppio.com/openai', 'sk_xx', 103, 1, '2026-01-04 03:03:32', 1, '2026-03-15 19:18:51', 'BGE-M3 是一款具备多维度能力的文本嵌入模型，可同时实现密集检索、多向量检索和稀疏检索三大核心功能。该模型设计上兼容超过100种语言，并支持从短句到长达8192词元的长文本等多种输入形式。在跨语言检索任务中，BGE-M3展现出显著优势，其性能在MIRACL、MKQA等国际基准测试中位居前列。此外，针对长文档检索场景，该模型在MLDR、NarritiveQA等数据集上的表现同样达到行业领先水平。', 0);
|
||||
INSERT INTO `chat_model` VALUES (2045735140488847361, 'chat', 'deepseek-chat', 'custom_api', 'deepseek-chat', NULL, NULL, 'https://api.deepseek.com', 'sk_xx', 103, 1, '2026-04-19 13:24:00', 1, '2026-04-19 13:24:00', 'deepseek对话模型', 0);
|
||||
|
||||
-- ----------------------------
|
||||
-- Table structure for chat_provider
|
||||
-- ----------------------------
|
||||
DROP TABLE IF EXISTS `chat_provider`;
|
||||
CREATE TABLE `chat_provider` (
|
||||
`id` bigint NOT NULL AUTO_INCREMENT COMMENT '主键',
|
||||
`provider_name` varchar(100) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NOT NULL COMMENT '厂商名称',
|
||||
`provider_code` varchar(50) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NOT NULL COMMENT '厂商编码',
|
||||
`provider_icon` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '厂商图标',
|
||||
`provider_desc` varchar(500) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '厂商描述',
|
||||
`api_host` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT 'API地址',
|
||||
`status` char(1) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT '0' COMMENT '状态（0正常 1停用）',
|
||||
`sort_order` int NULL DEFAULT 0 COMMENT '排序',
|
||||
`create_dept` bigint NULL DEFAULT NULL COMMENT '创建部门',
|
||||
`create_time` datetime NULL DEFAULT NULL COMMENT '创建时间',
|
||||
`create_by` varchar(64) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT '' COMMENT '创建者',
|
||||
`update_by` varchar(64) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT '' COMMENT '更新者',
|
||||
`update_time` datetime NULL DEFAULT NULL COMMENT '更新时间',
|
||||
`remark` varchar(500) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '备注',
|
||||
`version` int NULL DEFAULT NULL COMMENT '版本',
|
||||
`del_flag` char(1) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT '0' COMMENT '删除标志',
|
||||
`update_ip` varchar(128) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '更新IP',
|
||||
`tenant_id` bigint NOT NULL DEFAULT 0 COMMENT '租户Id',
|
||||
PRIMARY KEY (`id`) USING BTREE,
|
||||
UNIQUE INDEX `unique_provider_code`(`provider_code` ASC, `tenant_id` ASC, `del_flag` ASC) USING BTREE,
|
||||
INDEX `idx_status`(`status` ASC) USING BTREE
|
||||
) ENGINE = InnoDB AUTO_INCREMENT = 2045727230803255298 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_0900_ai_ci COMMENT = '厂商管理表' ROW_FORMAT = DYNAMIC;
|
||||
|
||||
-- ----------------------------
|
||||
-- Records of chat_provider
|
||||
-- ----------------------------
|
||||
INSERT INTO `chat_provider` VALUES (1, 'OpenAI', 'openai', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/01091be272334383a1efd9bc22b73ee6.png', 'OpenAI官方API服务商', 'https://api.openai.com', '0', 1, 103, '2025-12-14 21:48:11', '1', '1', '2026-02-25 20:46:59', 'OpenAI厂商', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (11, '深度求索', 'deepseek', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/04/19/5ba8c30f153246898a4d7dc7b846de8d.png', 'DeepSeek官方API', 'https://api.deepseek.com', '0', 0, 103, '2026-04-19 12:52:34', '1', '1', '2026-04-19 13:13:25', 'DeepSeek官方API', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (12, '智谱AI', 'zhipu', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/04/19/da071783c9284fdd9ed1ce1b57b3c75c.png', '智谱AI大模型服务', 'https://open.bigmodel.cn', '0', 4, 103, '2025-12-14 21:48:11', '1', '1', '2026-04-19 13:14:00', '智谱AI厂商', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (13, '小米MIMO', 'xiaomi', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/04/19/18dd39365ce244e3ae5e030da036760e.png', '小米官方API', 'https://api.xiaomimimo.com/anthropic/v1/messages', '0', 3, 103, '2026-04-19 12:48:24', '1', '1', '2026-04-19 13:14:22', '小米官方API', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (14, '阿里云百炼', 'qianwen', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/de2aa7e649de44f3ba5c6380ac6acd04.png', '阿里云百炼大模型服务', 'https://dashscope.aliyuncs.com', '0', 2, 103, '2025-12-14 21:48:11', '1', '1', '2026-02-25 20:49:13', '阿里云厂商', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (15, 'PPIO', 'ppio', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/049bb6a507174f73bba4b8d8b9e55b8a.png', 'api聚合厂商', 'https://api.ppinfra.com/openai', '0', 5, 103, '2025-12-15 23:13:42', '1', '1', '2026-02-25 20:49:01', 'api聚合厂商', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (16, 'MiniMax', 'minimax', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/04/19/fdc712e90e0e4d78b05862ad230884e5.png', 'MiniMax大模型服务，支持M2.7、M2.5等模型', 'https://api.minimax.io/v1', '0', 6, 103, '2026-04-19 12:50:12', '1', '1', '2026-04-19 13:14:59', 'MiniMax厂商', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (17, 'ollama', 'ollama', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/afecabebc8014d80b0f06b4796a74c5d.png', 'ollama大模型', 'http://127.0.0.1:11434', '0', 7, 103, '2025-12-14 21:48:11', '1', '1', '2026-02-25 20:48:48', 'ollama厂商', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (18, '自定义厂商', 'custom_api', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/04/19/c1a8e122510f4e2f90deb36958af710b.png', 'OPENAI兼容格式', '自定义', '0', 8, 103, '2026-04-19 12:35:57', '1', '1', '2026-04-19 13:17:20', 'OPENAI兼容格式', NULL, '0', NULL, 0);
|
||||
|
||||
SET FOREIGN_KEY_CHECKS = 1;
|
||||
46
docs/script/sql/update/updat-0420.sql
Normal file
46
docs/script/sql/update/updat-0420.sql
Normal file
@@ -0,0 +1,46 @@
|
||||
/*
|
||||
Navicat Premium Dump SQL
|
||||
|
||||
Source Server : localhost-mysql
|
||||
Source Server Type : MySQL
|
||||
Source Server Version : 80045 (8.0.45)
|
||||
Source Host : localhost:3306
|
||||
Source Schema : ruoyi-ai
|
||||
|
||||
Target Server Type : MySQL
|
||||
Target Server Version : 80045 (8.0.45)
|
||||
File Encoding : 65001
|
||||
|
||||
Date: 20/04/2026 15:30:00
|
||||
*/
|
||||
|
||||
SET NAMES utf8mb4;
|
||||
SET FOREIGN_KEY_CHECKS = 0;
|
||||
|
||||
-- ----------------------------
|
||||
-- 新增：重排序模型（chat_model）
|
||||
-- ----------------------------
|
||||
INSERT INTO `chat_model`
|
||||
(id, category, model_name, provider_code, model_describe, model_dimension, model_show, api_host, api_key, create_dept, create_by, create_time, update_by, update_time, remark, tenant_id)
|
||||
VALUES(2045071617578237953, 'rerank', 'rerank', 'zhipu', '智谱重排序', NULL, 'Y', 'https://open.bigmodel.cn', 'e9xx', 103, 1, '2026-04-17 17:27:24', 1, '2026-04-20 15:21:48', '智谱重排序', 0);
|
||||
|
||||
INSERT INTO `chat_model`
|
||||
(id, category, model_name, provider_code, model_describe, model_dimension, model_show, api_host, api_key, create_dept, create_by, create_time, update_by, update_time, remark, tenant_id)
|
||||
VALUES(2046119803482902530, 'rerank', 'qwen3-rerank', 'qianwen', '千问3重排序', NULL, NULL, 'https://dashscope.aliyuncs.com', 'sk-xx', 103, 1, '2026-04-20 14:52:31', 1, '2026-04-20 15:03:13', '千问3文本重排序', 0);
|
||||
|
||||
-- ----------------------------
|
||||
-- 新增：字典类型 - 重排序模型分类
|
||||
-- ----------------------------
|
||||
INSERT INTO `sys_dict_data`
|
||||
(dict_code, tenant_id, dict_sort, dict_label, dict_value, dict_type, css_class, list_class, is_default, create_dept, create_by, create_time, update_by, update_time, remark)
|
||||
VALUES(2045070879435259905, '000000', 4, '重排序', 'rerank', 'chat_model_category', NULL, '#000000', 'N', 103, 1, '2026-04-17 17:24:28', 1, '2026-04-19 01:02:20', '重排序模型');
|
||||
|
||||
-- ----------------------------
|
||||
-- 修改表：knowledge_info 增加重排序相关字段
|
||||
-- ----------------------------
|
||||
ALTER TABLE `knowledge_info` ADD COLUMN `enable_rerank` tinyint DEFAULT 0 NULL COMMENT '是否启用重排序（0否 1是）';
|
||||
ALTER TABLE `knowledge_info` ADD COLUMN `rerank_score_threshold` double NULL COMMENT '重排序相关性分数阈值';
|
||||
ALTER TABLE `knowledge_info` ADD COLUMN `rerank_top_n` int NULL COMMENT '重排序后返回的文档数量';
|
||||
ALTER TABLE `knowledge_info` ADD COLUMN `rerank_model` varchar(100) NULL COMMENT '重排序模型名称';
|
||||
|
||||
SET FOREIGN_KEY_CHECKS = 1;
|
||||
14
docs/script/sql/update/updat-0423.sql
Normal file
14
docs/script/sql/update/updat-0423.sql
Normal file
@@ -0,0 +1,14 @@
|
||||
-- 为知识库信息表新增检索配置字段 (剔除了已存在的重排字段)
|
||||
ALTER TABLE knowledge_info
|
||||
ADD COLUMN similarity_threshold DOUBLE DEFAULT 0.5 COMMENT '相似度阈值'
|
||||
AFTER retrieve_limit;
|
||||
|
||||
ALTER TABLE knowledge_info ADD COLUMN enable_hybrid tinyint(1) DEFAULT 0 COMMENT '是否启用混合检索';
|
||||
ALTER TABLE knowledge_info ADD COLUMN hybrid_alpha double DEFAULT 0.5 COMMENT '混合检索权重比例 (0.0=纯向量, 1.0=纯关键词)';
|
||||
|
||||
-- 为知识片段表增加全文索引及关联ID
|
||||
ALTER TABLE knowledge_fragment ADD COLUMN knowledge_id bigint COMMENT '知识库ID';
|
||||
ALTER TABLE knowledge_fragment ADD FULLTEXT INDEX ft_content (content) WITH PARSER ngram;
|
||||
|
||||
-- 为知识库附件表增加解析状态字段
|
||||
ALTER TABLE `knowledge_attach` ADD COLUMN `status` TINYINT DEFAULT 0 COMMENT '解析状态: 0待解析, 1解析中, 2已解析, 3解析失败';
|
||||
@@ -265,7 +265,7 @@ demo:
|
||||
# 是否开启演示模式（开启后所有写操作将被拦截）
|
||||
enabled: false
|
||||
# 提示消息
|
||||
message: "演示模式，不允许进行写操作"
|
||||
message: "演示模式，不允许操作"
|
||||
# 排除的路径（这些路径不受演示模式限制）
|
||||
excludes:
|
||||
- /login
|
||||
@@ -276,7 +276,9 @@ demo:
|
||||
- /chat/send
|
||||
- /system/session/**
|
||||
- /system/message/**
|
||||
|
||||
- /system/attach/**
|
||||
- /system/fragment/**
|
||||
- /system/info/**
|
||||
--- # warm-flow工作流配置
|
||||
warm-flow:
|
||||
# 是否开启工作流，默认true
|
||||
|
||||
@@ -10,6 +10,7 @@ import org.springframework.boot.context.properties.EnableConfigurationProperties
|
||||
import org.springframework.context.annotation.Bean;
|
||||
import org.springframework.core.task.VirtualThreadTaskExecutor;
|
||||
|
||||
import org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor;
|
||||
import java.util.concurrent.*;
|
||||
|
||||
/**
|
||||
@@ -22,6 +23,12 @@ import java.util.concurrent.*;
|
||||
@EnableConfigurationProperties(ThreadPoolProperties.class)
|
||||
public class ThreadPoolConfig {
|
||||
|
||||
private final ThreadPoolProperties properties;
|
||||
|
||||
public ThreadPoolConfig(ThreadPoolProperties properties) {
|
||||
this.properties = properties;
|
||||
}
|
||||
|
||||
/**
|
||||
* 核心线程数 = cpu 核心数 + 1
|
||||
*/
|
||||
@@ -54,6 +61,22 @@ public class ThreadPoolConfig {
|
||||
return scheduledThreadPoolExecutor;
|
||||
}
|
||||
|
||||
/**
|
||||
* 知识库解析专用异步线程池
|
||||
*/
|
||||
@Bean(name = "knowledgeParseExecutor")
|
||||
public ThreadPoolTaskExecutor knowledgeParseExecutor() {
|
||||
ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor();
|
||||
executor.setCorePoolSize(core);
|
||||
executor.setMaxPoolSize(core * 2);
|
||||
executor.setQueueCapacity(properties.getQueueCapacity());
|
||||
executor.setKeepAliveSeconds(properties.getKeepAliveSeconds());
|
||||
executor.setThreadNamePrefix("knowledge-parse-pool-");
|
||||
executor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy());
|
||||
executor.initialize();
|
||||
return executor;
|
||||
}
|
||||
|
||||
/**
|
||||
* 销毁事件
|
||||
* 停止线程池
|
||||
|
||||
@@ -174,6 +174,23 @@
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
|
||||
<!-- Test dependencies -->
|
||||
<dependency>
|
||||
<groupId>org.junit.jupiter</groupId>
|
||||
<artifactId>junit-jupiter</artifactId>
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.mockito</groupId>
|
||||
<artifactId>mockito-core</artifactId>
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.mockito</groupId>
|
||||
<artifactId>mockito-junit-jupiter</artifactId>
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
|
||||
</dependencies>
|
||||
|
||||
</project>
|
||||
|
||||
@@ -9,6 +9,7 @@ import cn.dev33.satoken.annotation.SaCheckPermission;
|
||||
import org.ruoyi.common.chat.service.chat.IChatModelService;
|
||||
import org.ruoyi.common.chat.domain.bo.chat.ChatModelBo;
|
||||
import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
|
||||
import org.ruoyi.enums.ChatModeType;
|
||||
import org.ruoyi.enums.ModelType;
|
||||
import org.springframework.web.bind.annotation.*;
|
||||
import org.springframework.validation.annotation.Validated;
|
||||
@@ -23,6 +24,8 @@ import org.ruoyi.common.log.enums.BusinessType;
|
||||
import org.ruoyi.common.excel.utils.ExcelUtil;
|
||||
import org.ruoyi.common.mybatis.core.page.TableDataInfo;
|
||||
|
||||
import java.util.LinkedHashMap;
|
||||
|
||||
/**
|
||||
* 模型管理
|
||||
*
|
||||
@@ -55,6 +58,21 @@ public class ChatModelController extends BaseController {
|
||||
return R.ok(chatModelService.queryList(bo));
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取模型供应商枚举
|
||||
*/
|
||||
@GetMapping("/providerOptions")
|
||||
public R<List<LinkedHashMap<String, String>>> providerOptions() {
|
||||
List<LinkedHashMap<String, String>> options = new java.util.ArrayList<>();
|
||||
for (ChatModeType type : ChatModeType.values()) {
|
||||
LinkedHashMap<String, String> item = new LinkedHashMap<>();
|
||||
item.put("label", type.getDescription());
|
||||
item.put("value", type.getCode());
|
||||
options.add(item);
|
||||
}
|
||||
return R.ok(options);
|
||||
}
|
||||
|
||||
/**
|
||||
* 导出模型管理列表
|
||||
*/
|
||||
|
||||
@@ -110,6 +110,17 @@ public class KnowledgeAttachController extends BaseController {
|
||||
@PostMapping(value = "/upload")
|
||||
public R<String> upload(KnowledgeInfoUploadBo bo){
|
||||
knowledgeAttachService.upload(bo);
|
||||
return R.ok("上传知识库附件成功!");
|
||||
return R.ok("上传成功!");
|
||||
}
|
||||
|
||||
/**
|
||||
* 手动解析附件内容
|
||||
*
|
||||
* @param id 附件ID
|
||||
*/
|
||||
@PostMapping("/parse/{id}")
|
||||
public R<Void> parse(@PathVariable Long id) {
|
||||
knowledgeAttachService.parse(id);
|
||||
return R.ok();
|
||||
}
|
||||
}
|
||||
|
||||
@@ -8,6 +8,7 @@ import jakarta.validation.constraints.*;
|
||||
import cn.dev33.satoken.annotation.SaCheckPermission;
|
||||
import org.ruoyi.domain.bo.knowledge.KnowledgeFragmentBo;
|
||||
import org.ruoyi.domain.vo.knowledge.KnowledgeFragmentVo;
|
||||
import org.ruoyi.domain.vo.knowledge.KnowledgeRetrievalVo;
|
||||
import org.ruoyi.service.knowledge.IKnowledgeFragmentService;
|
||||
import org.springframework.web.bind.annotation.*;
|
||||
import org.springframework.validation.annotation.Validated;
|
||||
@@ -102,4 +103,12 @@ public class KnowledgeFragmentController extends BaseController {
|
||||
@PathVariable Long[] ids) {
|
||||
return toAjax(knowledgeFragmentService.deleteWithValidByIds(List.of(ids), true));
|
||||
}
|
||||
|
||||
/**
|
||||
* 检索测试
|
||||
*/
|
||||
@PostMapping("/retrieval")
|
||||
public R<List<KnowledgeRetrievalVo>> retrieval(@RequestBody KnowledgeFragmentBo bo) {
|
||||
return R.ok(knowledgeFragmentService.retrieval(bo));
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,105 +0,0 @@
|
||||
package org.ruoyi.controller.knowledge;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
import lombok.RequiredArgsConstructor;
|
||||
import jakarta.servlet.http.HttpServletResponse;
|
||||
import jakarta.validation.constraints.*;
|
||||
import cn.dev33.satoken.annotation.SaCheckPermission;
|
||||
import org.ruoyi.domain.bo.knowledge.KnowledgeGraphInstanceBo;
|
||||
import org.ruoyi.domain.vo.knowledge.KnowledgeGraphInstanceVo;
|
||||
import org.ruoyi.service.knowledge.IKnowledgeGraphInstanceService;
|
||||
import org.springframework.web.bind.annotation.*;
|
||||
import org.springframework.validation.annotation.Validated;
|
||||
import org.ruoyi.common.idempotent.annotation.RepeatSubmit;
|
||||
import org.ruoyi.common.log.annotation.Log;
|
||||
import org.ruoyi.common.web.core.BaseController;
|
||||
import org.ruoyi.common.mybatis.core.page.PageQuery;
|
||||
import org.ruoyi.common.core.domain.R;
|
||||
import org.ruoyi.common.core.validate.AddGroup;
|
||||
import org.ruoyi.common.core.validate.EditGroup;
|
||||
import org.ruoyi.common.log.enums.BusinessType;
|
||||
import org.ruoyi.common.excel.utils.ExcelUtil;
|
||||
import org.ruoyi.common.mybatis.core.page.TableDataInfo;
|
||||
|
||||
/**
|
||||
* 知识图谱实例
|
||||
*
|
||||
* @author ageerle
|
||||
* @date 2025-12-17
|
||||
*/
|
||||
@Validated
|
||||
@RequiredArgsConstructor
|
||||
@RestController
|
||||
@RequestMapping("/system/graphInstance")
|
||||
public class KnowledgeGraphInstanceController extends BaseController {
|
||||
|
||||
private final IKnowledgeGraphInstanceService knowledgeGraphInstanceService;
|
||||
|
||||
/**
|
||||
* 查询知识图谱实例列表
|
||||
*/
|
||||
@SaCheckPermission("system:graphInstance:list")
|
||||
@GetMapping("/list")
|
||||
public TableDataInfo<KnowledgeGraphInstanceVo> list(KnowledgeGraphInstanceBo bo, PageQuery pageQuery) {
|
||||
return knowledgeGraphInstanceService.queryPageList(bo, pageQuery);
|
||||
}
|
||||
|
||||
/**
|
||||
* 导出知识图谱实例列表
|
||||
*/
|
||||
@SaCheckPermission("system:graphInstance:export")
|
||||
@Log(title = "知识图谱实例", businessType = BusinessType.EXPORT)
|
||||
@PostMapping("/export")
|
||||
public void export(KnowledgeGraphInstanceBo bo, HttpServletResponse response) {
|
||||
List<KnowledgeGraphInstanceVo> list = knowledgeGraphInstanceService.queryList(bo);
|
||||
ExcelUtil.exportExcel(list, "知识图谱实例", KnowledgeGraphInstanceVo.class, response);
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取知识图谱实例详细信息
|
||||
*
|
||||
* @param id 主键
|
||||
*/
|
||||
@SaCheckPermission("system:graphInstance:query")
|
||||
@GetMapping("/{id}")
|
||||
public R<KnowledgeGraphInstanceVo> getInfo(@NotNull(message = "主键不能为空")
|
||||
@PathVariable Long id) {
|
||||
return R.ok(knowledgeGraphInstanceService.queryById(id));
|
||||
}
|
||||
|
||||
/**
|
||||
* 新增知识图谱实例
|
||||
*/
|
||||
@SaCheckPermission("system:graphInstance:add")
|
||||
@Log(title = "知识图谱实例", businessType = BusinessType.INSERT)
|
||||
@RepeatSubmit()
|
||||
@PostMapping()
|
||||
public R<Void> add(@Validated(AddGroup.class) @RequestBody KnowledgeGraphInstanceBo bo) {
|
||||
return toAjax(knowledgeGraphInstanceService.insertByBo(bo));
|
||||
}
|
||||
|
||||
/**
|
||||
* 修改知识图谱实例
|
||||
*/
|
||||
@SaCheckPermission("system:graphInstance:edit")
|
||||
@Log(title = "知识图谱实例", businessType = BusinessType.UPDATE)
|
||||
@RepeatSubmit()
|
||||
@PutMapping()
|
||||
public R<Void> edit(@Validated(EditGroup.class) @RequestBody KnowledgeGraphInstanceBo bo) {
|
||||
return toAjax(knowledgeGraphInstanceService.updateByBo(bo));
|
||||
}
|
||||
|
||||
/**
|
||||
* 删除知识图谱实例
|
||||
*
|
||||
* @param ids 主键串
|
||||
*/
|
||||
@SaCheckPermission("system:graphInstance:remove")
|
||||
@Log(title = "知识图谱实例", businessType = BusinessType.DELETE)
|
||||
@DeleteMapping("/{ids}")
|
||||
public R<Void> remove(@NotEmpty(message = "主键不能为空")
|
||||
@PathVariable Long[] ids) {
|
||||
return toAjax(knowledgeGraphInstanceService.deleteWithValidByIds(List.of(ids), true));
|
||||
}
|
||||
}
|
||||
@@ -1,105 +0,0 @@
|
||||
package org.ruoyi.controller.knowledge;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
import lombok.RequiredArgsConstructor;
|
||||
import jakarta.servlet.http.HttpServletResponse;
|
||||
import jakarta.validation.constraints.*;
|
||||
import cn.dev33.satoken.annotation.SaCheckPermission;
|
||||
import org.ruoyi.domain.bo.knowledge.KnowledgeGraphSegmentBo;
|
||||
import org.ruoyi.domain.vo.knowledge.KnowledgeGraphSegmentVo;
|
||||
import org.ruoyi.service.knowledge.IKnowledgeGraphSegmentService;
|
||||
import org.springframework.web.bind.annotation.*;
|
||||
import org.springframework.validation.annotation.Validated;
|
||||
import org.ruoyi.common.idempotent.annotation.RepeatSubmit;
|
||||
import org.ruoyi.common.log.annotation.Log;
|
||||
import org.ruoyi.common.web.core.BaseController;
|
||||
import org.ruoyi.common.mybatis.core.page.PageQuery;
|
||||
import org.ruoyi.common.core.domain.R;
|
||||
import org.ruoyi.common.core.validate.AddGroup;
|
||||
import org.ruoyi.common.core.validate.EditGroup;
|
||||
import org.ruoyi.common.log.enums.BusinessType;
|
||||
import org.ruoyi.common.excel.utils.ExcelUtil;
|
||||
import org.ruoyi.common.mybatis.core.page.TableDataInfo;
|
||||
|
||||
/**
|
||||
* 知识图谱片段
|
||||
*
|
||||
* @author ageerle
|
||||
* @date 2025-12-17
|
||||
*/
|
||||
@Validated
|
||||
@RequiredArgsConstructor
|
||||
@RestController
|
||||
@RequestMapping("/system/graphSegment")
|
||||
public class KnowledgeGraphSegmentController extends BaseController {
|
||||
|
||||
private final IKnowledgeGraphSegmentService knowledgeGraphSegmentService;
|
||||
|
||||
/**
|
||||
* 查询知识图谱片段列表
|
||||
*/
|
||||
@SaCheckPermission("system:graphSegment:list")
|
||||
@GetMapping("/list")
|
||||
public TableDataInfo<KnowledgeGraphSegmentVo> list(KnowledgeGraphSegmentBo bo, PageQuery pageQuery) {
|
||||
return knowledgeGraphSegmentService.queryPageList(bo, pageQuery);
|
||||
}
|
||||
|
||||
/**
|
||||
* 导出知识图谱片段列表
|
||||
*/
|
||||
@SaCheckPermission("system:graphSegment:export")
|
||||
@Log(title = "知识图谱片段", businessType = BusinessType.EXPORT)
|
||||
@PostMapping("/export")
|
||||
public void export(KnowledgeGraphSegmentBo bo, HttpServletResponse response) {
|
||||
List<KnowledgeGraphSegmentVo> list = knowledgeGraphSegmentService.queryList(bo);
|
||||
ExcelUtil.exportExcel(list, "知识图谱片段", KnowledgeGraphSegmentVo.class, response);
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取知识图谱片段详细信息
|
||||
*
|
||||
* @param id 主键
|
||||
*/
|
||||
@SaCheckPermission("system:graphSegment:query")
|
||||
@GetMapping("/{id}")
|
||||
public R<KnowledgeGraphSegmentVo> getInfo(@NotNull(message = "主键不能为空")
|
||||
@PathVariable Long id) {
|
||||
return R.ok(knowledgeGraphSegmentService.queryById(id));
|
||||
}
|
||||
|
||||
/**
|
||||
* 新增知识图谱片段
|
||||
*/
|
||||
@SaCheckPermission("system:graphSegment:add")
|
||||
@Log(title = "知识图谱片段", businessType = BusinessType.INSERT)
|
||||
@RepeatSubmit()
|
||||
@PostMapping()
|
||||
public R<Void> add(@Validated(AddGroup.class) @RequestBody KnowledgeGraphSegmentBo bo) {
|
||||
return toAjax(knowledgeGraphSegmentService.insertByBo(bo));
|
||||
}
|
||||
|
||||
/**
|
||||
* 修改知识图谱片段
|
||||
*/
|
||||
@SaCheckPermission("system:graphSegment:edit")
|
||||
@Log(title = "知识图谱片段", businessType = BusinessType.UPDATE)
|
||||
@RepeatSubmit()
|
||||
@PutMapping()
|
||||
public R<Void> edit(@Validated(EditGroup.class) @RequestBody KnowledgeGraphSegmentBo bo) {
|
||||
return toAjax(knowledgeGraphSegmentService.updateByBo(bo));
|
||||
}
|
||||
|
||||
/**
|
||||
* 删除知识图谱片段
|
||||
*
|
||||
* @param ids 主键串
|
||||
*/
|
||||
@SaCheckPermission("system:graphSegment:remove")
|
||||
@Log(title = "知识图谱片段", businessType = BusinessType.DELETE)
|
||||
@DeleteMapping("/{ids}")
|
||||
public R<Void> remove(@NotEmpty(message = "主键不能为空")
|
||||
@PathVariable Long[] ids) {
|
||||
return toAjax(knowledgeGraphSegmentService.deleteWithValidByIds(List.of(ids), true));
|
||||
}
|
||||
}
|
||||
@@ -49,5 +49,44 @@ public class KnowledgeFragmentBo extends BaseEntity {
|
||||
*/
|
||||
private String remark;
|
||||
|
||||
/**
|
||||
* 知识库ID
|
||||
*/
|
||||
private Long knowledgeId;
|
||||
|
||||
/**
|
||||
* 检索内容
|
||||
*/
|
||||
private String query;
|
||||
|
||||
/**
|
||||
* 返回条数
|
||||
*/
|
||||
private Integer topK;
|
||||
|
||||
/**
|
||||
* 相似度阈值
|
||||
*/
|
||||
private Double threshold;
|
||||
|
||||
/**
|
||||
* 是否启用重排
|
||||
*/
|
||||
private Boolean enableRerank;
|
||||
|
||||
/**
|
||||
* 重排模型名称
|
||||
*/
|
||||
private String rerankModel;
|
||||
|
||||
/**
|
||||
* 是否启用混合检索
|
||||
*/
|
||||
private Boolean enableHybrid;
|
||||
|
||||
/**
|
||||
* 混合检索权重 (0.0-1.0)
|
||||
*/
|
||||
private Double hybridAlpha;
|
||||
|
||||
}
|
||||
|
||||
@@ -62,6 +62,11 @@ public class KnowledgeInfoBo extends BaseEntity {
|
||||
*/
|
||||
private Long retrieveLimit;
|
||||
|
||||
/**
|
||||
* 相似度阈值
|
||||
*/
|
||||
private Double similarityThreshold;
|
||||
|
||||
/**
|
||||
* 文本块大小
|
||||
*/
|
||||
@@ -77,10 +82,40 @@ public class KnowledgeInfoBo extends BaseEntity {
|
||||
*/
|
||||
private String embeddingModel;
|
||||
|
||||
/**
|
||||
* 是否启用重排序（0 否 1是）
|
||||
*/
|
||||
private Integer enableRerank;
|
||||
|
||||
/**
|
||||
* 重排序模型名称
|
||||
*/
|
||||
private String rerankModel;
|
||||
|
||||
/**
|
||||
* 重排序后返回的文档数量
|
||||
*/
|
||||
private Integer rerankTopN;
|
||||
|
||||
/**
|
||||
* 重排序相关性分数阈值
|
||||
*/
|
||||
private Double rerankScoreThreshold;
|
||||
|
||||
|
||||
/**
|
||||
* 是否启用混合检索（0 否 1是）
|
||||
*/
|
||||
private Integer enableHybrid;
|
||||
|
||||
/**
|
||||
* 混合检索权重 (0.0-1.0)
|
||||
*/
|
||||
private Double hybridAlpha;
|
||||
|
||||
/**
|
||||
* 备注
|
||||
*/
|
||||
private String remark;
|
||||
|
||||
|
||||
}
|
||||
|
||||
@@ -16,6 +16,11 @@ public class KnowledgeInfoUploadBo {
|
||||
|
||||
private MultipartFile file;
|
||||
|
||||
/**
|
||||
* 是否自动解析 (true: 立即解析, false: 仅上传)
|
||||
*/
|
||||
private Boolean autoParse;
|
||||
|
||||
/**
|
||||
* 生效时间, 为空则立即生效
|
||||
*/
|
||||
|
||||
@@ -0,0 +1,44 @@
|
||||
package org.ruoyi.domain.bo.rerank;
|
||||
|
||||
import lombok.AllArgsConstructor;
|
||||
import lombok.Builder;
|
||||
import lombok.Data;
|
||||
import lombok.NoArgsConstructor;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* 重排序请求参数
|
||||
*
|
||||
* @author yang
|
||||
* @date 2026-04-19
|
||||
*/
|
||||
@Data
|
||||
@Builder
|
||||
@NoArgsConstructor
|
||||
@AllArgsConstructor
|
||||
public class RerankRequest {
|
||||
|
||||
/**
|
||||
* 查询文本
|
||||
*/
|
||||
private String query;
|
||||
|
||||
/**
|
||||
* 候选文档列表
|
||||
*/
|
||||
private List<String> documents;
|
||||
|
||||
/**
|
||||
* 返回的文档数量（topN）
|
||||
* 如果不指定，默认返回所有文档
|
||||
*/
|
||||
private Integer topN;
|
||||
|
||||
/**
|
||||
* 是否返回原始文档内容
|
||||
* 默认为 true
|
||||
*/
|
||||
@Builder.Default
|
||||
private Boolean returnDocuments = true;
|
||||
}
|
||||
@@ -0,0 +1,72 @@
|
||||
package org.ruoyi.domain.bo.rerank;
|
||||
|
||||
import lombok.AllArgsConstructor;
|
||||
import lombok.Builder;
|
||||
import lombok.Data;
|
||||
import lombok.NoArgsConstructor;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* 重排序结果
|
||||
*
|
||||
* @author yang
|
||||
* @date 2026-04-19
|
||||
*/
|
||||
@Data
|
||||
@Builder
|
||||
@NoArgsConstructor
|
||||
@AllArgsConstructor
|
||||
public class RerankResult {
|
||||
|
||||
/**
|
||||
* 重排序后的文档结果列表
|
||||
*/
|
||||
private List<RerankDocument> documents;
|
||||
|
||||
/**
|
||||
* 原始请求中的文档总数
|
||||
*/
|
||||
private Integer totalDocuments;
|
||||
|
||||
/**
|
||||
* 重排序耗时（毫秒）
|
||||
*/
|
||||
private Long durationMs;
|
||||
|
||||
/**
|
||||
* 单个重排序文档结果
|
||||
*/
|
||||
@Data
|
||||
@Builder
|
||||
@NoArgsConstructor
|
||||
@AllArgsConstructor
|
||||
public static class RerankDocument {
|
||||
|
||||
/**
|
||||
* 文档在原始列表中的索引位置
|
||||
*/
|
||||
private Integer index;
|
||||
|
||||
/**
|
||||
* 相关性分数（通常 0-1 之间，越高越相关）
|
||||
*/
|
||||
private Double relevanceScore;
|
||||
|
||||
/**
|
||||
* 文档内容
|
||||
*/
|
||||
private String document;
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建空结果
|
||||
*/
|
||||
public static RerankResult empty() {
|
||||
return RerankResult.builder()
|
||||
.documents(List.of())
|
||||
.totalDocuments(0)
|
||||
.durationMs(0L)
|
||||
.build();
|
||||
}
|
||||
}
|
||||
@@ -51,4 +51,48 @@ public class QueryVectorBo {
|
||||
*/
|
||||
private String baseUrl;
|
||||
|
||||
|
||||
// ========== 重排序相关参数 ==========
|
||||
|
||||
/**
|
||||
* 是否启用重排序
|
||||
* 默认为 false
|
||||
*/
|
||||
private Boolean enableRerank = false;
|
||||
|
||||
/**
|
||||
* 重排序模型名称
|
||||
*/
|
||||
private String rerankModelName;
|
||||
|
||||
/**
|
||||
* 重排序后返回的文档数量（topN）
|
||||
* 如果不指定，默认与 maxResults 相同
|
||||
*/
|
||||
private Integer rerankTopN;
|
||||
|
||||
/**
|
||||
* 重排序相关性分数阈值
|
||||
* 低于此阈值的文档将被过滤
|
||||
*/
|
||||
private Double rerankScoreThreshold;
|
||||
|
||||
// ========== 混合检索与阈值相关参数 ==========
|
||||
|
||||
/**
|
||||
* 相似度阈值 (0.0-1.0)
|
||||
* 应用于向量搜索阶段
|
||||
*/
|
||||
private Double similarityThreshold;
|
||||
|
||||
/**
|
||||
* 是否启用混合检索
|
||||
*/
|
||||
private Boolean enableHybrid = false;
|
||||
|
||||
/**
|
||||
* 混合检索权重 (0.0-1.0)
|
||||
*/
|
||||
private Double hybridAlpha;
|
||||
|
||||
}
|
||||
|
||||
@@ -0,0 +1,55 @@
|
||||
package org.ruoyi.domain.dto.request;
|
||||
|
||||
import com.fasterxml.jackson.annotation.JsonInclude;
|
||||
import com.fasterxml.jackson.annotation.JsonProperty;
|
||||
import com.fasterxml.jackson.core.JsonProcessingException;
|
||||
import com.fasterxml.jackson.databind.ObjectMapper;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* 阿里百炼重排序请求DTO（OpenAI兼容格式）
|
||||
*
|
||||
* @author yang
|
||||
* @date 2026-04-20
|
||||
*/
|
||||
@JsonInclude(JsonInclude.Include.NON_NULL)
|
||||
public record AliBaiLianRerankRequest(
|
||||
String model,
|
||||
List<String> documents,
|
||||
String query,
|
||||
@JsonProperty("top_n")
|
||||
Integer topN,
|
||||
String instruct,
|
||||
@JsonProperty("return_documents")
|
||||
Boolean returnDocuments
|
||||
) {
|
||||
private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
|
||||
|
||||
/**
|
||||
* 创建文本重排序请求
|
||||
*/
|
||||
public static AliBaiLianRerankRequest create(String modelName, String query,
|
||||
List<String> documents, Integer topN,
|
||||
Boolean returnDocuments) {
|
||||
return new AliBaiLianRerankRequest(
|
||||
modelName,
|
||||
documents,
|
||||
query,
|
||||
topN != null ? topN : documents.size(),
|
||||
null,
|
||||
returnDocuments != null ? returnDocuments : true
|
||||
);
|
||||
}
|
||||
|
||||
/**
|
||||
* 转换为JSON字符串
|
||||
*/
|
||||
public String toJson() {
|
||||
try {
|
||||
return OBJECT_MAPPER.writeValueAsString(this);
|
||||
} catch (JsonProcessingException e) {
|
||||
throw new IllegalArgumentException("序列化阿里百炼重排序请求失败", e);
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,48 @@
|
||||
package org.ruoyi.domain.dto.request;
|
||||
|
||||
import com.fasterxml.jackson.core.JsonProcessingException;
|
||||
import com.fasterxml.jackson.databind.ObjectMapper;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* 智谱AI重排序请求DTO
|
||||
*
|
||||
* @author yang
|
||||
* @date 2026-04-19
|
||||
*/
|
||||
public record ZhipuRerankRequest(
|
||||
String model,
|
||||
String query,
|
||||
List<String> documents,
|
||||
Integer top_n,
|
||||
Boolean return_documents
|
||||
) {
|
||||
private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
|
||||
|
||||
/**
|
||||
* 创建智谱重排序请求
|
||||
*/
|
||||
public static ZhipuRerankRequest create(String modelName, String query,
|
||||
List<String> documents, Integer topN,
|
||||
Boolean returnDocuments) {
|
||||
return new ZhipuRerankRequest(
|
||||
modelName,
|
||||
query,
|
||||
documents,
|
||||
topN != null ? topN : documents.size(),
|
||||
returnDocuments != null ? returnDocuments : true
|
||||
);
|
||||
}
|
||||
|
||||
/**
|
||||
* 转换为JSON字符串
|
||||
*/
|
||||
public String toJson() {
|
||||
try {
|
||||
return OBJECT_MAPPER.writeValueAsString(this);
|
||||
} catch (JsonProcessingException e) {
|
||||
throw new IllegalArgumentException("序列化智谱重排序请求失败", e);
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,81 @@
|
||||
package org.ruoyi.domain.dto.response;
|
||||
|
||||
import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
|
||||
import com.fasterxml.jackson.annotation.JsonProperty;
|
||||
import org.ruoyi.domain.bo.rerank.RerankResult;
|
||||
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
import java.util.stream.Collectors;
|
||||
|
||||
/**
|
||||
* 阿里百炼重排序响应DTO（OpenAI兼容格式）
|
||||
*
|
||||
* @author yang
|
||||
* @date 2026-04-20
|
||||
*/
|
||||
@JsonIgnoreProperties(ignoreUnknown = true)
|
||||
public record AliBaiLianRerankResponse(
|
||||
String id,
|
||||
String object,
|
||||
List<ResultItem> results,
|
||||
UsageInfo usage
|
||||
) {
|
||||
/**
|
||||
* 单个重排序结果项
|
||||
*/
|
||||
@JsonIgnoreProperties(ignoreUnknown = true)
|
||||
public record ResultItem(
|
||||
Integer index,
|
||||
@JsonProperty("relevance_score")
|
||||
Double relevanceScore,
|
||||
Object document
|
||||
) {
|
||||
/**
|
||||
* 获取文档文本内容
|
||||
*/
|
||||
public String getDocumentText() {
|
||||
if (document == null) return null;
|
||||
if (document instanceof String) return (String) document;
|
||||
if (document instanceof Map) {
|
||||
Object text = ((Map<?, ?>) document).get("text");
|
||||
return text != null ? text.toString() : null;
|
||||
}
|
||||
return document.toString();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Token使用信息
|
||||
*/
|
||||
@JsonIgnoreProperties(ignoreUnknown = true)
|
||||
public record UsageInfo(
|
||||
@JsonProperty("total_tokens")
|
||||
Integer totalTokens,
|
||||
@JsonProperty("prompt_tokens")
|
||||
Integer promptTokens
|
||||
) {}
|
||||
|
||||
/**
|
||||
* 转换为通用RerankResult
|
||||
*/
|
||||
public RerankResult toRerankResult(int totalDocs, long durationMs) {
|
||||
if (results == null || results.isEmpty()) {
|
||||
return RerankResult.empty();
|
||||
}
|
||||
|
||||
List<RerankResult.RerankDocument> documents = results.stream()
|
||||
.map(item -> RerankResult.RerankDocument.builder()
|
||||
.index(item.index())
|
||||
.relevanceScore(item.relevanceScore())
|
||||
.document(item.getDocumentText())
|
||||
.build())
|
||||
.collect(Collectors.toList());
|
||||
|
||||
return RerankResult.builder()
|
||||
.documents(documents)
|
||||
.totalDocuments(totalDocs)
|
||||
.durationMs(durationMs)
|
||||
.build();
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,68 @@
|
||||
package org.ruoyi.domain.dto.response;
|
||||
|
||||
import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
|
||||
import com.fasterxml.jackson.annotation.JsonProperty;
|
||||
import org.ruoyi.domain.bo.rerank.RerankResult;
|
||||
|
||||
import java.util.List;
|
||||
import java.util.stream.Collectors;
|
||||
|
||||
/**
|
||||
* 智谱AI重排序响应DTO
|
||||
*
|
||||
* @author yang
|
||||
* @date 2026-04-19
|
||||
*/
|
||||
@JsonIgnoreProperties(ignoreUnknown = true)
|
||||
public record ZhipuRerankResponse(
|
||||
String model,
|
||||
String object,
|
||||
List<ResultItem> results,
|
||||
UsageInfo usage
|
||||
) {
|
||||
/**
|
||||
* 单个重排序结果项
|
||||
*/
|
||||
public record ResultItem(
|
||||
Integer index,
|
||||
@JsonProperty("relevance_score")
|
||||
Double relevanceScore,
|
||||
String document
|
||||
) {}
|
||||
|
||||
/**
|
||||
* Token使用信息
|
||||
*/
|
||||
@JsonIgnoreProperties(ignoreUnknown = true)
|
||||
public record UsageInfo(
|
||||
@JsonProperty("total_tokens")
|
||||
Integer totalTokens,
|
||||
@JsonProperty("input_tokens")
|
||||
Integer inputTokens,
|
||||
@JsonProperty("output_tokens")
|
||||
Integer outputTokens
|
||||
) {}
|
||||
|
||||
/**
|
||||
* 转换为通用RerankResult
|
||||
*/
|
||||
public RerankResult toRerankResult(int totalDocs, long durationMs) {
|
||||
if (results == null || results.isEmpty()) {
|
||||
return RerankResult.empty();
|
||||
}
|
||||
|
||||
List<RerankResult.RerankDocument> documents = results.stream()
|
||||
.map(item -> RerankResult.RerankDocument.builder()
|
||||
.index(item.index())
|
||||
.relevanceScore(item.relevanceScore())
|
||||
.document(item.document())
|
||||
.build())
|
||||
.collect(Collectors.toList());
|
||||
|
||||
return RerankResult.builder()
|
||||
.documents(documents)
|
||||
.totalDocuments(totalDocs)
|
||||
.durationMs(durationMs)
|
||||
.build();
|
||||
}
|
||||
}
|
||||
@@ -57,5 +57,10 @@ public class KnowledgeAttach extends BaseEntity {
|
||||
*/
|
||||
private String remark;
|
||||
|
||||
/**
|
||||
* 解析状态: 0待解析, 1解析中, 2已解析, 3解析失败
|
||||
*/
|
||||
private Integer status;
|
||||
|
||||
|
||||
}
|
||||
|
||||
@@ -47,5 +47,10 @@ public class KnowledgeFragment extends BaseEntity {
|
||||
*/
|
||||
private String remark;
|
||||
|
||||
/**
|
||||
* 知识库ID
|
||||
*/
|
||||
private Long knowledgeId;
|
||||
|
||||
|
||||
}
|
||||
|
||||
@@ -63,6 +63,11 @@ public class KnowledgeInfo extends BaseEntity {
|
||||
*/
|
||||
private Long retrieveLimit;
|
||||
|
||||
/**
|
||||
* 相似度阈值
|
||||
*/
|
||||
private Double similarityThreshold;
|
||||
|
||||
/**
|
||||
* 文本块大小
|
||||
*/
|
||||
@@ -78,6 +83,36 @@ public class KnowledgeInfo extends BaseEntity {
|
||||
*/
|
||||
private String embeddingModel;
|
||||
|
||||
/**
|
||||
* 是否启用重排序（0 否 1是）
|
||||
*/
|
||||
private Integer enableRerank;
|
||||
|
||||
/**
|
||||
* 重排序模型名称
|
||||
*/
|
||||
private String rerankModel;
|
||||
|
||||
/**
|
||||
* 重排序后返回的文档数量
|
||||
*/
|
||||
private Integer rerankTopN;
|
||||
|
||||
/**
|
||||
* 重排序相关性分数阈值
|
||||
*/
|
||||
private Double rerankScoreThreshold;
|
||||
|
||||
/**
|
||||
* 是否启用混合检索（0 否 1是）
|
||||
*/
|
||||
private Integer enableHybrid;
|
||||
|
||||
/**
|
||||
* 混合检索权重 (0.0-1.0)
|
||||
*/
|
||||
private Double hybridAlpha;
|
||||
|
||||
/**
|
||||
* 备注
|
||||
*/
|
||||
|
||||
@@ -0,0 +1,20 @@
|
||||
package org.ruoyi.domain.vo.knowledge;
|
||||
|
||||
import lombok.Data;
|
||||
|
||||
/**
|
||||
* 文档分块数统计 VO（用于 GROUP BY 查询结果接收）
|
||||
*/
|
||||
@Data
|
||||
public class DocFragmentCountVo {
|
||||
|
||||
/**
|
||||
* 文档ID（关联 knowledge_attach.doc_id）
|
||||
*/
|
||||
private String docId;
|
||||
|
||||
/**
|
||||
* 该文档下的分块数量
|
||||
*/
|
||||
private Integer fragmentCount;
|
||||
}
|
||||
@@ -8,6 +8,7 @@ import org.ruoyi.domain.entity.knowledge.KnowledgeAttach;
|
||||
|
||||
import java.io.Serial;
|
||||
import java.io.Serializable;
|
||||
import java.util.Date;
|
||||
|
||||
|
||||
|
||||
@@ -68,5 +69,22 @@ public class KnowledgeAttachVo implements Serializable {
|
||||
@ExcelProperty(value = "备注")
|
||||
private String remark;
|
||||
|
||||
/**
|
||||
* 上传时间（来自 BaseEntity.createTime）
|
||||
*/
|
||||
@ExcelProperty(value = "上传时间")
|
||||
private Date createTime;
|
||||
|
||||
/**
|
||||
* 解析状态: 0待解析, 1解析中, 2已解析, 3解析失败
|
||||
*/
|
||||
@ExcelProperty(value = "解析状态")
|
||||
private Integer status;
|
||||
|
||||
/**
|
||||
* 分块数（统计字段，非数据库列）
|
||||
*/
|
||||
private Integer fragmentCount;
|
||||
|
||||
|
||||
}
|
||||
|
||||
@@ -39,7 +39,7 @@ public class KnowledgeFragmentVo implements Serializable {
|
||||
* 片段索引下标
|
||||
*/
|
||||
@ExcelProperty(value = "片段索引下标")
|
||||
private Long idx;
|
||||
private Integer idx;
|
||||
|
||||
/**
|
||||
* 文档内容
|
||||
@@ -53,5 +53,10 @@ public class KnowledgeFragmentVo implements Serializable {
|
||||
@ExcelProperty(value = "备注")
|
||||
private String remark;
|
||||
|
||||
/**
|
||||
* 知识库ID
|
||||
*/
|
||||
private Long knowledgeId;
|
||||
|
||||
|
||||
}
|
||||
|
||||
@@ -76,6 +76,12 @@ public class KnowledgeInfoVo implements Serializable {
|
||||
@ExcelProperty(value = "知识库中检索的条数")
|
||||
private Integer retrieveLimit;
|
||||
|
||||
/**
|
||||
* 相似度阈值
|
||||
*/
|
||||
@ExcelProperty(value = "相似度阈值")
|
||||
private Double similarityThreshold;
|
||||
|
||||
/**
|
||||
* 文本块大小
|
||||
*/
|
||||
@@ -94,6 +100,48 @@ public class KnowledgeInfoVo implements Serializable {
|
||||
@ExcelProperty(value = "向量模型")
|
||||
private String embeddingModel;
|
||||
|
||||
/**
|
||||
* 是否启用重排序（0 否 1是）
|
||||
*/
|
||||
@ExcelProperty(value = "是否启用重排序")
|
||||
private Integer enableRerank;
|
||||
|
||||
/**
|
||||
* 重排序模型名称
|
||||
*/
|
||||
@ExcelProperty(value = "重排序模型")
|
||||
private String rerankModel;
|
||||
|
||||
/**
|
||||
* 重排序后返回的文档数量
|
||||
*/
|
||||
@ExcelProperty(value = "重排序返回数量")
|
||||
private Integer rerankTopN;
|
||||
|
||||
/**
|
||||
* 重排序相关性分数阈值
|
||||
*/
|
||||
@ExcelProperty(value = "重排序分数阈值")
|
||||
private Double rerankScoreThreshold;
|
||||
|
||||
/**
|
||||
* 是否启用混合检索（0 否 1是）
|
||||
*/
|
||||
@ExcelProperty(value = "是否启用混合检索")
|
||||
private Integer enableHybrid;
|
||||
|
||||
/**
|
||||
* 混合检索权重 (0.0-1.0)
|
||||
*/
|
||||
@ExcelProperty(value = "混合检索权重")
|
||||
private Double hybridAlpha;
|
||||
|
||||
/**
|
||||
* 文档数量
|
||||
*/
|
||||
@ExcelProperty(value = "文档数量")
|
||||
private Integer documentCount;
|
||||
|
||||
/**
|
||||
* 备注
|
||||
*/
|
||||
|
||||
@@ -0,0 +1,69 @@
|
||||
package org.ruoyi.domain.vo.knowledge;
|
||||
|
||||
import lombok.AllArgsConstructor;
|
||||
import lombok.Builder;
|
||||
import lombok.Data;
|
||||
import lombok.NoArgsConstructor;
|
||||
|
||||
import java.io.Serial;
|
||||
import java.io.Serializable;
|
||||
|
||||
/**
|
||||
* 知识检索测试结果视图对象
|
||||
*
|
||||
* @author RobustH
|
||||
*/
|
||||
@Data
|
||||
@Builder
|
||||
@NoArgsConstructor
|
||||
@AllArgsConstructor
|
||||
public class KnowledgeRetrievalVo implements Serializable {
|
||||
|
||||
@Serial
|
||||
private static final long serialVersionUID = 1L;
|
||||
|
||||
/**
|
||||
* 片段ID
|
||||
*/
|
||||
private String id;
|
||||
|
||||
/**
|
||||
* 文档ID
|
||||
*/
|
||||
private String docId;
|
||||
|
||||
/**
|
||||
* 知识库ID
|
||||
*/
|
||||
private Long knowledgeId;
|
||||
|
||||
/**
|
||||
* 分片索引
|
||||
*/
|
||||
private Integer idx;
|
||||
|
||||
/**
|
||||
* 片段内容
|
||||
*/
|
||||
private String content;
|
||||
|
||||
/**
|
||||
* 相似度得分
|
||||
*/
|
||||
private Double score;
|
||||
|
||||
/**
|
||||
* 原始检索排名 (重排前)
|
||||
*/
|
||||
private Integer originalIndex;
|
||||
|
||||
/**
|
||||
* 原始检索得分 (重排前)
|
||||
*/
|
||||
private Double rawScore;
|
||||
|
||||
/**
|
||||
* 来源文档名称
|
||||
*/
|
||||
private String sourceName;
|
||||
}
|
||||
@@ -15,7 +15,10 @@ public enum ChatModeType {
|
||||
DEEP_SEEK("deepseek", "深度求索"),
|
||||
QIAN_WEN("qianwen", "通义千问"),
|
||||
OPEN_AI("openai", "openai"),
|
||||
PPIO("ppio", "ppio");
|
||||
PPIO("ppio", "ppio"),
|
||||
CUSTOM_API("custom_api", "自定义API"),
|
||||
MINIMAX("minimax", "MiniMax"),
|
||||
XIAOMI("xiaomi", "小米MiMo");
|
||||
private final String code;
|
||||
private final String description;
|
||||
|
||||
|
||||
@@ -0,0 +1,38 @@
|
||||
package org.ruoyi.enums;
|
||||
|
||||
import lombok.AllArgsConstructor;
|
||||
import lombok.Getter;
|
||||
|
||||
/**
|
||||
* 知识库附件解析状态枚举
|
||||
*
|
||||
* @author RobustH
|
||||
*/
|
||||
@Getter
|
||||
@AllArgsConstructor
|
||||
public enum KnowledgeAttachStatus {
|
||||
|
||||
/**
|
||||
* 待解析
|
||||
*/
|
||||
WAITING(0, "待解析"),
|
||||
|
||||
/**
|
||||
* 解析中
|
||||
*/
|
||||
PARSING(1, "解析中"),
|
||||
|
||||
/**
|
||||
* 已解析
|
||||
*/
|
||||
COMPLETED(2, "已解析"),
|
||||
|
||||
/**
|
||||
* 解析失败
|
||||
*/
|
||||
FAILED(3, "解析失败");
|
||||
|
||||
private final Integer code;
|
||||
private final String info;
|
||||
|
||||
}
|
||||
@@ -0,0 +1,106 @@
|
||||
package org.ruoyi.factory;
|
||||
|
||||
import lombok.RequiredArgsConstructor;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
|
||||
import org.ruoyi.common.chat.service.chat.IChatModelService;
|
||||
import org.ruoyi.service.rerank.RerankModelService;
|
||||
import org.springframework.beans.factory.NoSuchBeanDefinitionException;
|
||||
import org.springframework.context.ApplicationContext;
|
||||
import org.springframework.stereotype.Service;
|
||||
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
import java.util.concurrent.ConcurrentHashMap;
|
||||
|
||||
/**
|
||||
* 重排序模型工厂服务类
|
||||
* 参考设计模式：EmbeddingModelFactory
|
||||
* 负责创建和管理重排序模型实例
|
||||
*
|
||||
* @author yang
|
||||
* @date 2026-04-19
|
||||
*/
|
||||
@Service
|
||||
@RequiredArgsConstructor
|
||||
@Slf4j
|
||||
public class RerankModelFactory {
|
||||
|
||||
private final ApplicationContext applicationContext;
|
||||
|
||||
private final IChatModelService chatModelService;
|
||||
|
||||
/**
|
||||
* 模型缓存，使用ConcurrentHashMap保证线程安全
|
||||
*/
|
||||
private final Map<String, RerankModelService> modelCache = new ConcurrentHashMap<>();
|
||||
|
||||
/**
|
||||
* 创建重排序模型实例
|
||||
* 如果模型已存在于缓存中，则直接返回；否则创建新的实例
|
||||
*
|
||||
* @param rerankModelName 重排序模型名称
|
||||
*/
|
||||
public RerankModelService createModel(String rerankModelName) {
|
||||
return modelCache.computeIfAbsent(rerankModelName, name -> {
|
||||
ChatModelVo modelConfig = chatModelService.selectModelByName(rerankModelName);
|
||||
|
||||
if (modelConfig == null) {
|
||||
throw new IllegalArgumentException("未找到重排序模型配置，name=" + name);
|
||||
}
|
||||
return createModelInstance(modelConfig.getProviderCode(), modelConfig);
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* 刷新模型缓存
|
||||
* 根据给定的模型ID从缓存中移除对应的模型
|
||||
*
|
||||
* @param modelId 模型的唯一标识ID
|
||||
*/
|
||||
public void refreshModel(Long modelId) {
|
||||
modelCache.remove(modelId);
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取所有支持模型工厂的列表
|
||||
*
|
||||
* @return 支持的模型工厂名称列表
|
||||
*/
|
||||
public List<String> getSupportedFactories() {
|
||||
return new ArrayList<>(applicationContext.getBeansOfType(RerankModelService.class)
|
||||
.keySet());
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建具体的模型实例
|
||||
* 根据提供的工厂名称和配置信息创建并配置模型实例
|
||||
*
|
||||
* @param factory 工厂名称，用于标识模型类型（providerCode）
|
||||
* @param config 模型配置信息
|
||||
* @return RerankModelService 配置好的模型实例
|
||||
* @throws IllegalArgumentException 当无法获取指定的模型实例时抛出
|
||||
*/
|
||||
private RerankModelService createModelInstance(String factory, ChatModelVo config) {
|
||||
try {
|
||||
// 优先尝试使用 providerCode + "Rerank" 作为 Bean 名称
|
||||
// 例如：zhipu -> zhipuRerank，jina -> jinaRerank
|
||||
String rerankBeanName = factory + "Rerank";
|
||||
RerankModelService model = applicationContext.getBean(rerankBeanName, RerankModelService.class);
|
||||
model.configure(config);
|
||||
log.info("成功创建重排序模型: factory={}, modelName={}", rerankBeanName, config.getModelName());
|
||||
return model;
|
||||
} catch (NoSuchBeanDefinitionException e) {
|
||||
// 如果找不到，尝试使用原始的 providerCode
|
||||
try {
|
||||
RerankModelService model = applicationContext.getBean(factory, RerankModelService.class);
|
||||
model.configure(config);
|
||||
log.info("成功创建重排序模型: factory={}, modelName={}", factory, config.getModelName());
|
||||
return model;
|
||||
} catch (NoSuchBeanDefinitionException ex) {
|
||||
throw new IllegalArgumentException("获取不到重排序模型: " + factory + " 或 " + factory + "Rerank", ex);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -1,5 +1,8 @@
|
||||
package org.ruoyi.mapper.knowledge;
|
||||
|
||||
import org.apache.ibatis.annotations.Mapper;
|
||||
import org.apache.ibatis.annotations.Param;
|
||||
import org.apache.ibatis.annotations.Select;
|
||||
import org.ruoyi.domain.entity.knowledge.KnowledgeAttach;
|
||||
import org.ruoyi.domain.vo.knowledge.KnowledgeAttachVo;
|
||||
import org.ruoyi.common.mybatis.core.mapper.BaseMapperPlus;
|
||||
@@ -10,6 +13,12 @@ import org.ruoyi.common.mybatis.core.mapper.BaseMapperPlus;
|
||||
* @author ageerle
|
||||
* @date 2025-12-17
|
||||
*/
|
||||
@Mapper
|
||||
public interface KnowledgeAttachMapper extends BaseMapperPlus<KnowledgeAttach, KnowledgeAttachVo> {
|
||||
|
||||
/**
|
||||
* 统计指定知识库下的文档数量
|
||||
*/
|
||||
@Select("SELECT COUNT(*) FROM knowledge_attach WHERE knowledge_id = #{knowledgeId}")
|
||||
int countByKnowledgeId(@Param("knowledgeId") Long knowledgeId);
|
||||
}
|
||||
|
||||
@@ -1,15 +1,45 @@
|
||||
package org.ruoyi.mapper.knowledge;
|
||||
|
||||
import org.apache.ibatis.annotations.Mapper;
|
||||
import org.apache.ibatis.annotations.Param;
|
||||
import org.apache.ibatis.annotations.Select;
|
||||
import org.ruoyi.domain.entity.knowledge.KnowledgeFragment;
|
||||
import org.ruoyi.domain.vo.knowledge.DocFragmentCountVo;
|
||||
import org.ruoyi.domain.vo.knowledge.KnowledgeFragmentVo;
|
||||
import org.ruoyi.common.mybatis.core.mapper.BaseMapperPlus;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* 知识片段Mapper接口
|
||||
*
|
||||
* @author ageerle
|
||||
* @date 2025-12-17
|
||||
*/
|
||||
@Mapper
|
||||
public interface KnowledgeFragmentMapper extends BaseMapperPlus<KnowledgeFragment, KnowledgeFragmentVo> {
|
||||
|
||||
/**
|
||||
* 批量统计各文档的分块数（强类型接收，避免 Map key 大小写问题）
|
||||
*
|
||||
* @param docIds 文档 ID 列表
|
||||
* @return 每个 docId 对应的分块数列表
|
||||
*/
|
||||
@Select("<script>" +
|
||||
"SELECT doc_id AS docId, COUNT(*) AS fragmentCount " +
|
||||
"FROM knowledge_fragment " +
|
||||
"WHERE doc_id IN " +
|
||||
"<foreach collection='docIds' item='id' open='(' separator=',' close=')'>#{id}</foreach> " +
|
||||
"GROUP BY doc_id" +
|
||||
"</script>")
|
||||
List<DocFragmentCountVo> selectFragmentCountByDocIds(@Param("docIds") List<String> docIds);
|
||||
@Select("<script>" +
|
||||
"SELECT id, doc_id AS docId, content, idx, knowledge_id AS knowledgeId " +
|
||||
"FROM knowledge_fragment " +
|
||||
"WHERE knowledge_id = #{knowledgeId} " +
|
||||
"AND MATCH (content) AGAINST (#{query} IN NATURAL LANGUAGE MODE) " +
|
||||
"ORDER BY MATCH (content) AGAINST (#{query} IN NATURAL LANGUAGE MODE) DESC " +
|
||||
"LIMIT #{limit}" +
|
||||
"</script>")
|
||||
List<KnowledgeFragmentVo> searchByKeyword(@Param("knowledgeId") Long knowledgeId, @Param("query") String query, @Param("limit") Integer limit);
|
||||
}
|
||||
|
||||
@@ -1,9 +1,13 @@
|
||||
package org.ruoyi.service.chat;
|
||||
|
||||
import dev.langchain4j.model.chat.ChatModel;
|
||||
import dev.langchain4j.model.chat.StreamingChatModel;
|
||||
import dev.langchain4j.model.openai.OpenAiChatModel;
|
||||
import org.ruoyi.common.chat.domain.dto.request.ChatRequest;
|
||||
import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
|
||||
|
||||
import java.time.Duration;
|
||||
|
||||
/**
|
||||
* 聊天消息Service接口
|
||||
*
|
||||
@@ -21,6 +25,23 @@ public interface AbstractChatService {
|
||||
*/
|
||||
StreamingChatModel buildStreamingChatModel(ChatModelVo chatModelVo, ChatRequest chatRequest);
|
||||
|
||||
/**
|
||||
* 创建同步聊天模型（供 Agent/SupervisorAgent 使用）
|
||||
* 默认实现使用 OpenAI 兼容协议，适用于 OpenAI、DeepSeek、PPIO 等兼容接口的 provider。
|
||||
* ZhiPu、QianWen、Ollama 等需覆盖此方法使用各自 SDK。
|
||||
*
|
||||
* @param chatModelVo 模型配置
|
||||
* @return 同步聊天模型实例
|
||||
*/
|
||||
default ChatModel buildChatModel(ChatModelVo chatModelVo) {
|
||||
return OpenAiChatModel.builder()
|
||||
.baseUrl(chatModelVo.getApiHost())
|
||||
.apiKey(chatModelVo.getApiKey())
|
||||
.modelName(chatModelVo.getModelName())
|
||||
.timeout(Duration.ofSeconds(120))
|
||||
.build();
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取服务提供商名称
|
||||
*/
|
||||
|
||||
@@ -20,6 +20,11 @@ import dev.langchain4j.model.chat.response.StreamingChatResponseHandler;
|
||||
import dev.langchain4j.model.openai.OpenAiChatModel;
|
||||
import dev.langchain4j.service.tool.ToolProvider;
|
||||
import dev.langchain4j.skills.shell.ShellSkills;
|
||||
import dev.langchain4j.rag.AugmentationRequest;
|
||||
import dev.langchain4j.rag.AugmentationResult;
|
||||
import dev.langchain4j.rag.DefaultRetrievalAugmentor;
|
||||
import dev.langchain4j.rag.RetrievalAugmentor;
|
||||
import dev.langchain4j.rag.query.Metadata;
|
||||
import lombok.RequiredArgsConstructor;
|
||||
import lombok.SneakyThrows;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
@@ -54,6 +59,8 @@ import org.ruoyi.service.chat.AbstractChatService;
|
||||
import org.ruoyi.service.chat.IChatMessageService;
|
||||
import org.ruoyi.service.chat.impl.memory.PersistentChatMemoryStore;
|
||||
import org.ruoyi.service.knowledge.IKnowledgeInfoService;
|
||||
import org.ruoyi.service.retrieval.KnowledgeRetrievalService;
|
||||
import org.ruoyi.service.knowledge.retriever.CustomVectorRetriever;
|
||||
import org.ruoyi.service.vector.VectorStoreService;
|
||||
import org.springframework.stereotype.Service;
|
||||
import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;
|
||||
@@ -89,6 +96,8 @@ public class ChatServiceFacade implements IChatService {
|
||||
|
||||
private final VectorStoreService vectorStoreService;
|
||||
|
||||
private final KnowledgeRetrievalService knowledgeRetrievalService;
|
||||
|
||||
private final SseEmitterManager sseEmitterManager;
|
||||
|
||||
private final IChatMessageService chatMessageService;
|
||||
@@ -409,7 +418,6 @@ public class ChatServiceFacade implements IChatService {
|
||||
|
||||
/**
|
||||
* 构建上下文消息列表
|
||||
|
||||
* 消息顺序：历史消息 → 当前用户消息（确保 AI 正确理解对话上下文）
|
||||
*
|
||||
* @param chatRequest 聊天请求
|
||||
@@ -418,7 +426,41 @@ public class ChatServiceFacade implements IChatService {
|
||||
private List<ChatMessage> buildContextMessages(ChatRequest chatRequest) {
|
||||
List<ChatMessage> messages = new ArrayList<>();
|
||||
|
||||
// 从数据库查询历史对话消息（放在前面）
|
||||
// 1. 初始化当前用户消息
|
||||
UserMessage userMessage = UserMessage.userMessage(chatRequest.getContent());
|
||||
|
||||
// 2. 知识库检索增强 (RAG)
|
||||
if (chatRequest.getKnowledgeId() != null) {
|
||||
KnowledgeInfoVo knowledgeInfoVo = knowledgeInfoService.queryById(Long.valueOf(chatRequest.getKnowledgeId()));
|
||||
if (knowledgeInfoVo != null) {
|
||||
ChatModelVo chatModel = chatModelService.selectModelByName(knowledgeInfoVo.getEmbeddingModel());
|
||||
if (chatModel != null) {
|
||||
log.info("执行高级 RAG 流程: kid={}", chatRequest.getKnowledgeId());
|
||||
|
||||
// 构建自定义检索器
|
||||
CustomVectorRetriever retriever = new CustomVectorRetriever(
|
||||
knowledgeRetrievalService, knowledgeInfoVo, chatModel);
|
||||
|
||||
// 构建增强流水线
|
||||
RetrievalAugmentor augmentor = DefaultRetrievalAugmentor.builder()
|
||||
.contentRetriever(retriever)
|
||||
.build();
|
||||
|
||||
// 执行增强：编织上下文到 UserMessage
|
||||
Metadata metadata = Metadata.from(userMessage, chatRequest.getSessionId(), new ArrayList<>());
|
||||
AugmentationRequest augmentationRequest = new AugmentationRequest(userMessage, metadata);
|
||||
AugmentationResult result = augmentor.augment(augmentationRequest);
|
||||
|
||||
ChatMessage augmented = result.chatMessage();
|
||||
if (augmented instanceof UserMessage) {
|
||||
userMessage = (UserMessage) augmented;
|
||||
log.debug("RAG 增强完成，UserMessage 已注入背景知识");
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// 3. 从数据库查询历史对话消息（放在前面）
|
||||
if (chatRequest.getSessionId() != null) {
|
||||
MessageWindowChatMemory memory = createChatMemory(chatRequest.getSessionId());
|
||||
if (memory != null) {
|
||||
@@ -430,38 +472,7 @@ public class ChatServiceFacade implements IChatService {
|
||||
}
|
||||
}
|
||||
|
||||
// 从向量库查询相关历史消息（知识库内容作为上下文）
|
||||
if (chatRequest.getKnowledgeId() != null) {
|
||||
// 查询知识库信息
|
||||
KnowledgeInfoVo knowledgeInfoVo = knowledgeInfoService.queryById(Long.valueOf(chatRequest.getKnowledgeId()));
|
||||
if (knowledgeInfoVo == null) {
|
||||
log.warn("知识库信息不存在，kid: {}", chatRequest.getKnowledgeId());
|
||||
// 继续添加当前用户消息
|
||||
messages.add(UserMessage.userMessage(chatRequest.getContent()));
|
||||
return messages;
|
||||
}
|
||||
|
||||
// 查询向量模型配置信息
|
||||
ChatModelVo chatModel = chatModelService.selectModelByName(knowledgeInfoVo.getEmbeddingModel());
|
||||
if (chatModel == null) {
|
||||
log.warn("向量模型配置不存在，模型名称: {}", knowledgeInfoVo.getEmbeddingModel());
|
||||
messages.add(UserMessage.userMessage(chatRequest.getContent()));
|
||||
return messages;
|
||||
}
|
||||
|
||||
// 构建向量查询参数
|
||||
QueryVectorBo queryVectorBo = buildQueryVectorBo(chatRequest, knowledgeInfoVo, chatModel);
|
||||
|
||||
// 获取向量查询结果（知识库内容作为系统上下文，放在历史消息之后）
|
||||
List<String> nearestList = vectorStoreService.getQueryVector(queryVectorBo);
|
||||
for (String prompt : nearestList) {
|
||||
// 知识库内容作为系统上下文添加
|
||||
messages.add(new AiMessage(prompt));
|
||||
}
|
||||
}
|
||||
|
||||
// 构建当前用户消息（放在最后）
|
||||
UserMessage userMessage = UserMessage.userMessage(chatRequest.getContent());
|
||||
// 4. 添加经过增强的用户消息（放在最后）
|
||||
messages.add(userMessage);
|
||||
|
||||
return messages;
|
||||
@@ -480,6 +491,13 @@ public class ChatServiceFacade implements IChatService {
|
||||
queryVectorBo.setVectorModelName(knowledgeInfoVo.getVectorModel());
|
||||
queryVectorBo.setEmbeddingModelName(knowledgeInfoVo.getEmbeddingModel());
|
||||
queryVectorBo.setMaxResults(knowledgeInfoVo.getRetrieveLimit());
|
||||
|
||||
// 设置重排序参数
|
||||
queryVectorBo.setEnableRerank(knowledgeInfoVo.getEnableRerank() != null && knowledgeInfoVo.getEnableRerank() == 1);
|
||||
queryVectorBo.setRerankModelName(knowledgeInfoVo.getRerankModel());
|
||||
queryVectorBo.setRerankTopN(knowledgeInfoVo.getRerankTopN());
|
||||
queryVectorBo.setRerankScoreThreshold(knowledgeInfoVo.getRerankScoreThreshold());
|
||||
|
||||
return queryVectorBo;
|
||||
}
|
||||
|
||||
|
||||
@@ -0,0 +1,72 @@
|
||||
package org.ruoyi.service.chat.impl.provider;
|
||||
|
||||
import cn.hutool.core.util.StrUtil;
|
||||
import dev.langchain4j.model.chat.ChatModel;
|
||||
import dev.langchain4j.model.chat.StreamingChatModel;
|
||||
import dev.langchain4j.model.openai.OpenAiChatModel;
|
||||
import dev.langchain4j.model.openai.OpenAiStreamingChatModel;
|
||||
import lombok.RequiredArgsConstructor;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
import org.ruoyi.common.chat.domain.dto.request.ChatRequest;
|
||||
import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
|
||||
import org.ruoyi.enums.ChatModeType;
|
||||
import org.ruoyi.observability.MyChatModelListener;
|
||||
import org.ruoyi.service.chat.AbstractChatService;
|
||||
import org.springframework.stereotype.Service;
|
||||
|
||||
import java.time.Duration;
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* 自定义 API 服务调用
|
||||
*
|
||||
* 适用于 OpenAI 兼容接口或仅通过通用 HTTP 协议接入的第三方大模型服务。
|
||||
* 通过模型配置中的 apiHost / apiKey / modelName 即可复用，不需要再写死具体供应商。
|
||||
*
|
||||
* @author better
|
||||
*/
|
||||
@Service
|
||||
@Slf4j
|
||||
@RequiredArgsConstructor
|
||||
public class CustomApiServiceImpl implements AbstractChatService {
|
||||
|
||||
private static final Duration DEFAULT_TIMEOUT = Duration.ofSeconds(180);
|
||||
|
||||
@Override
|
||||
public StreamingChatModel buildStreamingChatModel(ChatModelVo chatModelVo, ChatRequest chatRequest) {
|
||||
return OpenAiStreamingChatModel.builder()
|
||||
.baseUrl(normalizeBaseUrl(chatModelVo.getApiHost()))
|
||||
.apiKey(defaultIfBlank(chatModelVo.getApiKey(), "EMPTY"))
|
||||
.modelName(chatModelVo.getModelName())
|
||||
.timeout(DEFAULT_TIMEOUT)
|
||||
.listeners(List.of(new MyChatModelListener()))
|
||||
.returnThinking(chatRequest.getEnableThinking())
|
||||
.build();
|
||||
}
|
||||
|
||||
@Override
|
||||
public ChatModel buildChatModel(ChatModelVo chatModelVo) {
|
||||
return OpenAiChatModel.builder()
|
||||
.baseUrl(normalizeBaseUrl(chatModelVo.getApiHost()))
|
||||
.apiKey(defaultIfBlank(chatModelVo.getApiKey(), "EMPTY"))
|
||||
.modelName(chatModelVo.getModelName())
|
||||
.timeout(DEFAULT_TIMEOUT)
|
||||
.build();
|
||||
}
|
||||
|
||||
@Override
|
||||
public String getProviderName() {
|
||||
return ChatModeType.CUSTOM_API.getCode();
|
||||
}
|
||||
|
||||
private String normalizeBaseUrl(String baseUrl) {
|
||||
if (StrUtil.isBlank(baseUrl)) {
|
||||
throw new IllegalArgumentException("自定义API的请求地址(apiHost)不能为空");
|
||||
}
|
||||
return baseUrl.endsWith("/") ? baseUrl.substring(0, baseUrl.length() - 1) : baseUrl;
|
||||
}
|
||||
|
||||
private String defaultIfBlank(String value, String defaultValue) {
|
||||
return StrUtil.isBlank(value) ? defaultValue : value;
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,47 @@
|
||||
package org.ruoyi.service.chat.impl.provider;
|
||||
|
||||
|
||||
import dev.langchain4j.model.chat.StreamingChatModel;
|
||||
import dev.langchain4j.model.openai.OpenAiStreamingChatModel;
|
||||
import lombok.RequiredArgsConstructor;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
import org.ruoyi.common.chat.domain.dto.request.ChatRequest;
|
||||
import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
|
||||
import org.ruoyi.enums.ChatModeType;
|
||||
import org.ruoyi.observability.MyChatModelListener;
|
||||
import org.ruoyi.service.chat.AbstractChatService;
|
||||
import org.springframework.stereotype.Service;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
|
||||
/**
|
||||
* 小米MiMo服务调用
|
||||
* <p>
|
||||
* 小米提供OpenAI兼容的API接口，支持MiMo等模型。
|
||||
*
|
||||
* @author ageerle
|
||||
* @date 2026/4/19
|
||||
*/
|
||||
@Service
|
||||
@Slf4j
|
||||
@RequiredArgsConstructor
|
||||
public class MiMoServiceImpl implements AbstractChatService {
|
||||
|
||||
@Override
|
||||
public StreamingChatModel buildStreamingChatModel(ChatModelVo chatModelVo, ChatRequest chatRequest) {
|
||||
return OpenAiStreamingChatModel.builder()
|
||||
.baseUrl(chatModelVo.getApiHost())
|
||||
.apiKey(chatModelVo.getApiKey())
|
||||
.modelName(chatModelVo.getModelName())
|
||||
.listeners(List.of(new MyChatModelListener()))
|
||||
.returnThinking(chatRequest.getEnableThinking())
|
||||
.build();
|
||||
}
|
||||
|
||||
@Override
|
||||
public String getProviderName() {
|
||||
return ChatModeType.XIAOMI.getCode();
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,44 @@
|
||||
package org.ruoyi.service.chat.impl.provider;
|
||||
|
||||
import dev.langchain4j.model.chat.StreamingChatModel;
|
||||
import dev.langchain4j.model.openai.OpenAiStreamingChatModel;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
import org.ruoyi.common.chat.domain.dto.request.ChatRequest;
|
||||
import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
|
||||
import org.ruoyi.enums.ChatModeType;
|
||||
import org.ruoyi.observability.MyChatModelListener;
|
||||
import org.ruoyi.service.chat.AbstractChatService;
|
||||
import org.springframework.stereotype.Service;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* MiniMax服务调用
|
||||
* <p>
|
||||
* MiniMax提供OpenAI兼容的API接口，支持MiniMax-M2.7、MiniMax-M2.5等模型。
|
||||
* API地址：https://api.minimax.io/v1
|
||||
*
|
||||
* @author octopus
|
||||
* @date 2026/3/21
|
||||
*/
|
||||
@Service
|
||||
@Slf4j
|
||||
public class MinimaxServiceImpl implements AbstractChatService {
|
||||
|
||||
@Override
|
||||
public StreamingChatModel buildStreamingChatModel(ChatModelVo chatModelVo, ChatRequest chatRequest) {
|
||||
return OpenAiStreamingChatModel.builder()
|
||||
.baseUrl(chatModelVo.getApiHost())
|
||||
.apiKey(chatModelVo.getApiKey())
|
||||
.modelName(chatModelVo.getModelName())
|
||||
.listeners(List.of(new MyChatModelListener()))
|
||||
.returnThinking(chatRequest.getEnableThinking())
|
||||
.build();
|
||||
}
|
||||
|
||||
@Override
|
||||
public String getProviderName() {
|
||||
return ChatModeType.MINIMAX.getCode();
|
||||
}
|
||||
|
||||
}
|
||||
@@ -1,7 +1,9 @@
|
||||
package org.ruoyi.service.chat.impl.provider;
|
||||
|
||||
|
||||
import dev.langchain4j.model.chat.ChatModel;
|
||||
import dev.langchain4j.model.chat.StreamingChatModel;
|
||||
import dev.langchain4j.model.ollama.OllamaChatModel;
|
||||
import dev.langchain4j.model.ollama.OllamaStreamingChatModel;
|
||||
import lombok.RequiredArgsConstructor;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
@@ -37,6 +39,14 @@ public class OllamaServiceImpl implements AbstractChatService {
|
||||
.build();
|
||||
}
|
||||
|
||||
@Override
|
||||
public ChatModel buildChatModel(ChatModelVo chatModelVo) {
|
||||
return OllamaChatModel.builder()
|
||||
.baseUrl(chatModelVo.getApiHost())
|
||||
.modelName(chatModelVo.getModelName())
|
||||
.build();
|
||||
}
|
||||
|
||||
@Override
|
||||
public String getProviderName() {
|
||||
return ChatModeType.OLLAMA.getCode();
|
||||
|
||||
@@ -1,7 +1,9 @@
|
||||
package org.ruoyi.service.chat.impl.provider;
|
||||
|
||||
|
||||
import dev.langchain4j.community.model.dashscope.QwenChatModel;
|
||||
import dev.langchain4j.community.model.dashscope.QwenStreamingChatModel;
|
||||
import dev.langchain4j.model.chat.ChatModel;
|
||||
import dev.langchain4j.model.chat.StreamingChatModel;
|
||||
import lombok.RequiredArgsConstructor;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
@@ -38,6 +40,14 @@ public class QianWenChatServiceImpl implements AbstractChatService {
|
||||
.build();
|
||||
}
|
||||
|
||||
@Override
|
||||
public ChatModel buildChatModel(ChatModelVo chatModelVo) {
|
||||
return QwenChatModel.builder()
|
||||
.apiKey(chatModelVo.getApiKey())
|
||||
.modelName(chatModelVo.getModelName())
|
||||
.build();
|
||||
}
|
||||
|
||||
@Override
|
||||
public String getProviderName() {
|
||||
return ChatModeType.QIAN_WEN.getCode();
|
||||
|
||||
@@ -1,7 +1,9 @@
|
||||
package org.ruoyi.service.chat.impl.provider;
|
||||
|
||||
|
||||
import dev.langchain4j.community.model.zhipu.ZhipuAiChatModel;
|
||||
import dev.langchain4j.community.model.zhipu.ZhipuAiStreamingChatModel;
|
||||
import dev.langchain4j.model.chat.ChatModel;
|
||||
import dev.langchain4j.model.chat.StreamingChatModel;
|
||||
import lombok.RequiredArgsConstructor;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
@@ -35,6 +37,14 @@ public class ZhiPuChatServiceImpl implements AbstractChatService {
|
||||
.build();
|
||||
}
|
||||
|
||||
@Override
|
||||
public ChatModel buildChatModel(ChatModelVo chatModelVo) {
|
||||
return ZhipuAiChatModel.builder()
|
||||
.apiKey(chatModelVo.getApiKey())
|
||||
.model(chatModelVo.getModelName())
|
||||
.build();
|
||||
}
|
||||
|
||||
@Override
|
||||
public String getProviderName() {
|
||||
return ChatModeType.ZHI_PU.getCode();
|
||||
|
||||
@@ -0,0 +1,17 @@
|
||||
package org.ruoyi.service.embed.impl;
|
||||
|
||||
import org.springframework.stereotype.Component;
|
||||
|
||||
/**
|
||||
* MiniMax嵌入模型（兼容OpenAI接口）
|
||||
* <p>
|
||||
* 支持embo-01模型，1536维度向量。
|
||||
* API地址：https://api.minimax.io/v1
|
||||
*
|
||||
* @author octopus
|
||||
* @date 2026/3/21
|
||||
*/
|
||||
@Component("minimax")
|
||||
public class MinimaxEmbeddingProvider extends OpenAiEmbeddingProvider {
|
||||
|
||||
}
|
||||
@@ -0,0 +1,48 @@
|
||||
package org.ruoyi.service.embed.impl;
|
||||
|
||||
|
||||
|
||||
import dev.langchain4j.community.model.zhipu.ZhipuAiEmbeddingModel;
|
||||
import dev.langchain4j.data.embedding.Embedding;
|
||||
import dev.langchain4j.data.segment.TextSegment;
|
||||
import dev.langchain4j.model.embedding.EmbeddingModel;
|
||||
import dev.langchain4j.model.output.Response;
|
||||
import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
|
||||
import org.ruoyi.enums.ModalityType;
|
||||
import org.ruoyi.service.embed.BaseEmbedModelService;
|
||||
import org.springframework.stereotype.Component;
|
||||
|
||||
import java.util.List;
|
||||
import java.util.Set;
|
||||
|
||||
/**
|
||||
* @Author:yang
|
||||
* @Date:
|
||||
* @Description: 智谱AI嵌入模型
|
||||
*/
|
||||
@Component("zhipu")
|
||||
public class ZhipuAiEmbeddingProvider implements BaseEmbedModelService {
|
||||
protected ChatModelVo chatModelVo;
|
||||
|
||||
@Override
|
||||
public void configure(ChatModelVo config) {
|
||||
this.chatModelVo = config;
|
||||
}
|
||||
|
||||
@Override
|
||||
public Set<ModalityType> getSupportedModalities() {
|
||||
return Set.of(ModalityType.TEXT);
|
||||
}
|
||||
|
||||
@Override
|
||||
public Response<List<Embedding>> embedAll(List<TextSegment> textSegments) {
|
||||
EmbeddingModel model = ZhipuAiEmbeddingModel.builder()
|
||||
.baseUrl(chatModelVo.getApiHost())
|
||||
.apiKey(chatModelVo.getApiKey())
|
||||
.model(chatModelVo.getModelName())
|
||||
.dimensions(chatModelVo.getModelDimension())
|
||||
.build();
|
||||
|
||||
return model.embedAll(textSegments);
|
||||
}
|
||||
}
|
||||
@@ -72,4 +72,11 @@ public interface IKnowledgeAttachService {
|
||||
* 上传附件
|
||||
*/
|
||||
void upload(KnowledgeInfoUploadBo bo);
|
||||
|
||||
/**
|
||||
* 解析附件知识片段
|
||||
*
|
||||
* @param id 附件ID
|
||||
*/
|
||||
void parse(Long id);
|
||||
}
|
||||
|
||||
@@ -4,6 +4,7 @@ import org.ruoyi.common.mybatis.core.page.TableDataInfo;
|
||||
import org.ruoyi.common.mybatis.core.page.PageQuery;
|
||||
import org.ruoyi.domain.bo.knowledge.KnowledgeFragmentBo;
|
||||
import org.ruoyi.domain.vo.knowledge.KnowledgeFragmentVo;
|
||||
import org.ruoyi.domain.vo.knowledge.KnowledgeRetrievalVo;
|
||||
|
||||
import java.util.Collection;
|
||||
import java.util.List;
|
||||
@@ -65,4 +66,12 @@ public interface IKnowledgeFragmentService {
|
||||
* @return 是否删除成功
|
||||
*/
|
||||
Boolean deleteWithValidByIds(Collection<Long> ids, Boolean isValid);
|
||||
|
||||
/**
|
||||
* 检索测试
|
||||
*
|
||||
* @param bo 检索参数
|
||||
* @return 检索结果
|
||||
*/
|
||||
List<KnowledgeRetrievalVo> retrieval(KnowledgeFragmentBo bo);
|
||||
}
|
||||
|
||||
@@ -2,24 +2,27 @@ package org.ruoyi.service.knowledge.impl;
|
||||
|
||||
import cn.hutool.core.collection.CollUtil;
|
||||
import cn.hutool.core.util.RandomUtil;
|
||||
import org.ruoyi.common.chat.service.chat.IChatModelService;
|
||||
import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
|
||||
import com.baomidou.mybatisplus.core.toolkit.Wrappers;
|
||||
import com.baomidou.mybatisplus.extension.plugins.pagination.Page;
|
||||
import lombok.RequiredArgsConstructor;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
|
||||
import org.ruoyi.common.chat.service.chat.IChatModelService;
|
||||
import org.ruoyi.enums.KnowledgeAttachStatus;
|
||||
import org.ruoyi.common.core.domain.dto.OssDTO;
|
||||
import org.ruoyi.common.core.service.OssService;
|
||||
import org.ruoyi.common.core.utils.MapstructUtils;
|
||||
import org.ruoyi.common.core.utils.SpringUtils;
|
||||
import org.ruoyi.common.core.utils.StringUtils;
|
||||
import org.ruoyi.common.mybatis.core.page.TableDataInfo;
|
||||
import org.ruoyi.common.mybatis.core.page.PageQuery;
|
||||
import com.baomidou.mybatisplus.extension.plugins.pagination.Page;
|
||||
import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
|
||||
import com.baomidou.mybatisplus.core.toolkit.Wrappers;
|
||||
import lombok.RequiredArgsConstructor;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
import org.ruoyi.common.mybatis.core.page.TableDataInfo;
|
||||
import org.ruoyi.domain.bo.knowledge.KnowledgeAttachBo;
|
||||
import org.ruoyi.domain.bo.knowledge.KnowledgeInfoUploadBo;
|
||||
import org.ruoyi.domain.bo.vector.StoreEmbeddingBo;
|
||||
import org.ruoyi.domain.entity.knowledge.KnowledgeAttach;
|
||||
import org.ruoyi.domain.entity.knowledge.KnowledgeFragment;
|
||||
import org.ruoyi.domain.vo.knowledge.DocFragmentCountVo;
|
||||
import org.ruoyi.domain.vo.knowledge.KnowledgeAttachVo;
|
||||
import org.ruoyi.domain.vo.knowledge.KnowledgeInfoVo;
|
||||
import org.ruoyi.factory.ResourceLoaderFactory;
|
||||
@@ -29,11 +32,15 @@ import org.ruoyi.service.knowledge.IKnowledgeAttachService;
|
||||
import org.ruoyi.service.knowledge.IKnowledgeInfoService;
|
||||
import org.ruoyi.service.knowledge.ResourceLoader;
|
||||
import org.ruoyi.service.vector.VectorStoreService;
|
||||
import org.springframework.scheduling.annotation.Async;
|
||||
import org.springframework.stereotype.Service;
|
||||
import org.springframework.web.multipart.MultipartFile;
|
||||
|
||||
import java.io.IOException;
|
||||
import java.io.InputStream;
|
||||
|
||||
import java.net.URL;
|
||||
import java.util.*;
|
||||
import java.util.stream.Collectors;
|
||||
|
||||
/**
|
||||
* 知识库附件Service业务层处理
|
||||
@@ -47,57 +54,51 @@ import java.util.*;
|
||||
public class KnowledgeAttachServiceImpl implements IKnowledgeAttachService {
|
||||
|
||||
private final KnowledgeAttachMapper baseMapper;
|
||||
|
||||
private final IKnowledgeInfoService knowledgeInfoService;
|
||||
|
||||
private final KnowledgeFragmentMapper knowledgeFragmentMapper;
|
||||
|
||||
private final IChatModelService chatModelService;
|
||||
|
||||
private final ResourceLoaderFactory resourceLoaderFactory;
|
||||
|
||||
private final VectorStoreService vectorStoreService;
|
||||
|
||||
private final OssService ossService;
|
||||
/**
|
||||
* 查询知识库附件
|
||||
*
|
||||
* @param id 主键
|
||||
* @return 知识库附件
|
||||
*/
|
||||
|
||||
@Override
|
||||
public KnowledgeAttachVo queryById(Long id){
|
||||
public KnowledgeAttachVo queryById(Long id) {
|
||||
return baseMapper.selectVoById(id);
|
||||
}
|
||||
|
||||
/**
|
||||
* 分页查询知识库附件列表
|
||||
*
|
||||
* @param bo 查询条件
|
||||
* @param pageQuery 分页参数
|
||||
* @return 知识库附件分页列表
|
||||
*/
|
||||
@Override
|
||||
public TableDataInfo<KnowledgeAttachVo> queryPageList(KnowledgeAttachBo bo, PageQuery pageQuery) {
|
||||
LambdaQueryWrapper<KnowledgeAttach> lqw = buildQueryWrapper(bo);
|
||||
Page<KnowledgeAttachVo> result = baseMapper.selectVoPage(pageQuery.build(), lqw);
|
||||
fillFragmentCount(result.getRecords());
|
||||
return TableDataInfo.build(result);
|
||||
}
|
||||
|
||||
/**
|
||||
* 查询符合条件的知识库附件列表
|
||||
*
|
||||
* @param bo 查询条件
|
||||
* @return 知识库附件列表
|
||||
*/
|
||||
@Override
|
||||
public List<KnowledgeAttachVo> queryList(KnowledgeAttachBo bo) {
|
||||
LambdaQueryWrapper<KnowledgeAttach> lqw = buildQueryWrapper(bo);
|
||||
return baseMapper.selectVoList(lqw);
|
||||
List<KnowledgeAttachVo> list = baseMapper.selectVoList(lqw);
|
||||
fillFragmentCount(list);
|
||||
return list;
|
||||
}
|
||||
|
||||
private void fillFragmentCount(List<KnowledgeAttachVo> records) {
|
||||
if (records == null || records.isEmpty()) return;
|
||||
List<String> docIds = records.stream()
|
||||
.map(KnowledgeAttachVo::getDocId)
|
||||
.filter(StringUtils::isNotBlank)
|
||||
.distinct()
|
||||
.collect(Collectors.toList());
|
||||
if (docIds.isEmpty()) return;
|
||||
List<DocFragmentCountVo> countList = knowledgeFragmentMapper.selectFragmentCountByDocIds(docIds);
|
||||
Map<String, Integer> countMap = countList.stream()
|
||||
.collect(Collectors.toMap(DocFragmentCountVo::getDocId, DocFragmentCountVo::getFragmentCount, (k1, k2) -> k1));
|
||||
for (KnowledgeAttachVo vo : records) {
|
||||
vo.setFragmentCount(countMap.getOrDefault(vo.getDocId(), 0));
|
||||
}
|
||||
}
|
||||
|
||||
private LambdaQueryWrapper<KnowledgeAttach> buildQueryWrapper(KnowledgeAttachBo bo) {
|
||||
Map<String, Object> params = bo.getParams();
|
||||
LambdaQueryWrapper<KnowledgeAttach> lqw = Wrappers.lambdaQuery();
|
||||
lqw.orderByAsc(KnowledgeAttach::getId);
|
||||
lqw.eq(bo.getKnowledgeId() != null, KnowledgeAttach::getKnowledgeId, bo.getKnowledgeId());
|
||||
@@ -107,16 +108,9 @@ public class KnowledgeAttachServiceImpl implements IKnowledgeAttachService {
|
||||
return lqw;
|
||||
}
|
||||
|
||||
/**
|
||||
* 新增知识库附件
|
||||
*
|
||||
* @param bo 知识库附件
|
||||
* @return 是否新增成功
|
||||
*/
|
||||
@Override
|
||||
public Boolean insertByBo(KnowledgeAttachBo bo) {
|
||||
KnowledgeAttach add = MapstructUtils.convert(bo, KnowledgeAttach.class);
|
||||
validEntityBeforeSave(add);
|
||||
boolean flag = baseMapper.insert(add) > 0;
|
||||
if (flag) {
|
||||
bo.setId(add.getId());
|
||||
@@ -124,86 +118,88 @@ public class KnowledgeAttachServiceImpl implements IKnowledgeAttachService {
|
||||
return flag;
|
||||
}
|
||||
|
||||
/**
|
||||
* 修改知识库附件
|
||||
*
|
||||
* @param bo 知识库附件
|
||||
* @return 是否修改成功
|
||||
*/
|
||||
@Override
|
||||
public Boolean updateByBo(KnowledgeAttachBo bo) {
|
||||
KnowledgeAttach update = MapstructUtils.convert(bo, KnowledgeAttach.class);
|
||||
validEntityBeforeSave(update);
|
||||
return baseMapper.updateById(update) > 0;
|
||||
}
|
||||
|
||||
/**
|
||||
* 保存前的数据校验
|
||||
*/
|
||||
private void validEntityBeforeSave(KnowledgeAttach entity){
|
||||
//TODO 做一些数据校验,如唯一约束
|
||||
}
|
||||
|
||||
/**
|
||||
* 校验并批量删除知识库附件信息
|
||||
*
|
||||
* @param ids 待删除的主键集合
|
||||
* @param isValid 是否进行有效性校验
|
||||
* @return 是否删除成功
|
||||
*/
|
||||
@Override
|
||||
public Boolean deleteWithValidByIds(Collection<Long> ids, Boolean isValid) {
|
||||
if(isValid){
|
||||
//TODO 做一些业务上的校验,判断是否需要校验
|
||||
}
|
||||
return baseMapper.deleteByIds(ids) > 0;
|
||||
}
|
||||
|
||||
@Override
|
||||
public void upload(KnowledgeInfoUploadBo bo) {
|
||||
MultipartFile file = bo.getFile();
|
||||
// 保存文件信息
|
||||
OssDTO ossDTO = ossService.uploadFile(file);
|
||||
Long knowledgeId = bo.getKnowledgeId();
|
||||
List<String> chunkList = new ArrayList<>();
|
||||
|
||||
KnowledgeAttach knowledgeAttach = new KnowledgeAttach();
|
||||
knowledgeAttach.setKnowledgeId(bo.getKnowledgeId());
|
||||
String docId = RandomUtil.randomString(10);
|
||||
knowledgeAttach.setOssId(ossDTO.getOssId());
|
||||
knowledgeAttach.setDocId(docId);
|
||||
knowledgeAttach.setDocId(RandomUtil.randomString(10));
|
||||
knowledgeAttach.setName(ossDTO.getOriginalName());
|
||||
knowledgeAttach.setType(ossDTO.getFileSuffix());
|
||||
String content = "";
|
||||
ResourceLoader resourceLoader = resourceLoaderFactory.getLoaderByFileType(knowledgeAttach.getType());
|
||||
// 文档分段入库
|
||||
List<String> fids = new ArrayList<>();
|
||||
knowledgeAttach.setStatus(KnowledgeAttachStatus.WAITING.getCode()); // 待解析
|
||||
|
||||
baseMapper.insert(knowledgeAttach);
|
||||
|
||||
if (Boolean.TRUE.equals(bo.getAutoParse())) {
|
||||
// 通过 SpringUtils 获取代理对象，确保 @Async 生效
|
||||
SpringUtils.getBean(IKnowledgeAttachService.class).parse(knowledgeAttach.getId());
|
||||
}
|
||||
}
|
||||
|
||||
@Async("knowledgeParseExecutor")
|
||||
@Override
|
||||
public void parse(Long id) {
|
||||
KnowledgeAttach attach = baseMapper.selectById(id);
|
||||
if (attach == null || (!KnowledgeAttachStatus.WAITING.getCode().equals(attach.getStatus()) && !KnowledgeAttachStatus.FAILED.getCode().equals(attach.getStatus()))) {
|
||||
return;
|
||||
}
|
||||
|
||||
try {
|
||||
content = resourceLoader.getContent(file.getInputStream());
|
||||
chunkList = resourceLoader.getChunkList(content, String.valueOf(knowledgeId));
|
||||
attach.setStatus(KnowledgeAttachStatus.PARSING.getCode()); // 解析中
|
||||
baseMapper.updateById(attach);
|
||||
|
||||
log.info("开始解析知识库文档... id: {}, docId: {}", id, attach.getDocId());
|
||||
|
||||
Long knowledgeId = attach.getKnowledgeId();
|
||||
String docId = attach.getDocId();
|
||||
|
||||
// 获取文件信息并下载
|
||||
List<OssDTO> ossDTOs = ossService.selectByIds(String.valueOf(attach.getOssId()));
|
||||
if (ossDTOs == null || ossDTOs.isEmpty()) {
|
||||
throw new RuntimeException("未找到对应的 OSS 文件信息");
|
||||
}
|
||||
OssDTO ossDTO = ossDTOs.get(0);
|
||||
String content;
|
||||
ResourceLoader resourceLoader = resourceLoaderFactory.getLoaderByFileType(attach.getType());
|
||||
try (InputStream inputStream = new URL(ossDTO.getUrl()).openStream()) {
|
||||
content = resourceLoader.getContent(inputStream);
|
||||
}
|
||||
List<String> chunkList = resourceLoader.getChunkList(content, String.valueOf(knowledgeId));
|
||||
|
||||
List<String> fids = new ArrayList<>();
|
||||
List<KnowledgeFragment> knowledgeFragmentList = new ArrayList<>();
|
||||
if (CollUtil.isNotEmpty(chunkList)) {
|
||||
for (int i = 0; i < chunkList.size(); i++) {
|
||||
// 生成知识片段ID
|
||||
String fid = RandomUtil.randomString(10);
|
||||
fids.add(fid);
|
||||
KnowledgeFragment knowledgeFragment = new KnowledgeFragment();
|
||||
knowledgeFragment.setKnowledgeId(knowledgeId);
|
||||
knowledgeFragment.setDocId(docId);
|
||||
knowledgeFragment.setIdx(i);
|
||||
knowledgeFragment.setContent(chunkList.get(i));
|
||||
knowledgeFragment.setCreateTime(new Date());
|
||||
knowledgeFragmentList.add(knowledgeFragment);
|
||||
}
|
||||
}
|
||||
knowledgeFragmentMapper.delete(Wrappers.<KnowledgeFragment>lambdaQuery().eq(KnowledgeFragment::getDocId, docId));
|
||||
knowledgeFragmentMapper.insertBatch(knowledgeFragmentList);
|
||||
} catch (IOException e) {
|
||||
log.error("保存知识库信息失败！{}", e.getMessage());
|
||||
log.info("文档切片并入库完成，共计 {} 个片段。id: {}", chunkList.size(), id);
|
||||
}
|
||||
baseMapper.insert(knowledgeAttach);
|
||||
|
||||
// 查询知识库信息
|
||||
KnowledgeInfoVo knowledgeInfoVo = knowledgeInfoService.queryById(knowledgeId);
|
||||
|
||||
// 查询向量模信息
|
||||
ChatModelVo chatModelVo = chatModelService.selectModelByName(knowledgeInfoVo.getEmbeddingModel());
|
||||
|
||||
StoreEmbeddingBo storeEmbeddingBo = new StoreEmbeddingBo();
|
||||
@@ -216,6 +212,15 @@ public class KnowledgeAttachServiceImpl implements IKnowledgeAttachService {
|
||||
storeEmbeddingBo.setApiKey(chatModelVo.getApiKey());
|
||||
storeEmbeddingBo.setBaseUrl(chatModelVo.getApiHost());
|
||||
vectorStoreService.storeEmbeddings(storeEmbeddingBo);
|
||||
}
|
||||
|
||||
attach.setStatus(KnowledgeAttachStatus.COMPLETED.getCode()); // 已完成
|
||||
baseMapper.updateById(attach);
|
||||
log.info("知识库文档解析、向量化并入库成功！id: {}", id);
|
||||
} catch (Exception e) {
|
||||
log.error("解析文档失败！id: {}, error: {}", id, e.getMessage(), e);
|
||||
attach.setStatus(KnowledgeAttachStatus.FAILED.getCode()); // 失败
|
||||
attach.setRemark(StringUtils.substring(e.getMessage(), 0, 255)); // 保存错误原因，截取防止溢出
|
||||
baseMapper.updateById(attach);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user