Merge pull request #293 from RobustH/main

升级RAG模块

README.md

@@ -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  

README_EN.md

@@ -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 |

docs/script/sql/ruoyi-ai-v3_mysql8.sql

@@ -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 (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.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 (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 (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 (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 (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 (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 (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 (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 (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 (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 (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

docs/script/sql/update/updat-0419.sql

@@ -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;

docs/script/sql/update/updat-0420.sql

@@ -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;

docs/script/sql/update/updat-0423.sql

@@ -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';

ruoyi-admin/src/main/resources/application.yml

@@ -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

ruoyi-common/ruoyi-common-core/src/main/java/org/ruoyi/common/core/config/ThreadPoolConfig.java

@@ -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

ruoyi-modules/ruoyi-chat/pom.xml

@@ -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>

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/controller/chat/ChatModelController.java

@@ -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
      */

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/controller/knowledge/KnowledgeAttachController.java

@@ -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();
     }
 }

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/controller/knowledge/KnowledgeFragmentController.java

@@ -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));
+    }
 }

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/controller/knowledge/KnowledgeGraphInstanceController.java

@@ -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));
-    }
-}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/controller/knowledge/KnowledgeGraphSegmentController.java

@@ -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));
-    }
-}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/domain/bo/knowledge/KnowledgeFragmentBo.java

@@ -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;
 
 }

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/domain/bo/knowledge/KnowledgeInfoBo.java

@@ -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;
 
-
 }

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/domain/bo/knowledge/KnowledgeInfoUploadBo.java

@@ -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
      */

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/domain/bo/rerank/RerankRequest.java

@@ -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;
+}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/domain/bo/rerank/RerankResult.java

@@ -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();
+    }
+}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/domain/bo/vector/QueryVectorBo.java

@@ -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;
+
 }

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/domain/dto/request/AliBaiLianRerankRequest.java

@@ -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);
+        }
+    }
+}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/domain/dto/request/ZhipuRerankRequest.java

@@ -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);
+        }
+    }
+}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/domain/dto/response/AliBaiLianRerankResponse.java

@@ -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();
+    }
+}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/domain/dto/response/ZhipuRerankResponse.java

@@ -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();
+    }
+}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/domain/entity/knowledge/KnowledgeAttach.java

@@ -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;
+
 
 }

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/domain/entity/knowledge/KnowledgeFragment.java

@@ -47,5 +47,10 @@ public class KnowledgeFragment extends BaseEntity {
      */
     private String remark;
 
+    /**
+     * 知识库ID
+     */
+    private Long knowledgeId;
+
 
 }

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/domain/entity/knowledge/KnowledgeInfo.java

@@ -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
      */

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/domain/vo/knowledge/DocFragmentCountVo.java

@@ -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;
+}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/domain/vo/knowledge/KnowledgeAttachVo.java

@@ -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;
+
 
 }

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/domain/vo/knowledge/KnowledgeFragmentVo.java

@@ -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;
+
 
 }

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/domain/vo/knowledge/KnowledgeInfoVo.java

@@ -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
      */

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/domain/vo/knowledge/KnowledgeRetrievalVo.java

@@ -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;
+}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/enums/ChatModeType.java

@@ -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;
 

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/enums/KnowledgeAttachStatus.java

@@ -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;
+
+}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/factory/RerankModelFactory.java

@@ -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);
+            }
+        }
+    }
+}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/mapper/knowledge/KnowledgeAttachMapper.java

@@ -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);
 }

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/mapper/knowledge/KnowledgeFragmentMapper.java

@@ -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);
 }

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/chat/AbstractChatService.java

@@ -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
      */

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/chat/impl/ChatServiceFacade.java

@@ -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）
+        // 4. 添加经过增强的用户消息（放在最后）
-        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());
         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;
     }
 

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/chat/impl/provider/CustomApiServiceImpl.java

@@ -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;
+    }
+}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/chat/impl/provider/MiMoServiceImpl.java

@@ -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();
+    }
+
+}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/chat/impl/provider/MinimaxServiceImpl.java

@@ -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();
+    }
+
+}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/chat/impl/provider/OllamaServiceImpl.java

@@ -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();

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/chat/impl/provider/QianWenChatServiceImpl.java

@@ -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();

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/chat/impl/provider/ZhiPuChatServiceImpl.java

@@ -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();

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/embed/impl/MinimaxEmbeddingProvider.java

@@ -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 {
+
+}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/embed/impl/ZhipuAiEmbeddingProvider.java

@@ -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);
+    }
+}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/knowledge/IKnowledgeAttachService.java

@@ -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);
 }

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/knowledge/IKnowledgeFragmentService.java

@@ -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);
 }

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/knowledge/impl/KnowledgeAttachServiceImpl.java

@@ -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 org.ruoyi.common.mybatis.core.page.TableDataInfo;
-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.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 = "";
+        knowledgeAttach.setStatus(KnowledgeAttachStatus.WAITING.getCode()); // 待解析
-        ResourceLoader resourceLoader = resourceLoaderFactory.getLoaderByFileType(knowledgeAttach.getType());
+
-        // 文档分段入库
+        baseMapper.insert(knowledgeAttach);
-        List<String> fids = new ArrayList<>();
+
+        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());
+            attach.setStatus(KnowledgeAttachStatus.PARSING.getCode()); // 解析中
-            chunkList = resourceLoader.getChunkList(content, String.valueOf(knowledgeId));
+            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.info("文档切片并入库完成，共计 {} 个片段。id: {}", chunkList.size(), id);
-            log.error("保存知识库信息失败！{}", e.getMessage());
             }
-        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);
+        }
+    }
 }