feat: 添加Dify平台集成支持

- 升级 dify-sdk-java 从 1.0.7 到 1.2.6
- 新增 ChatModeType.DIFY 枚举类型
- 新增 DifyChatServiceImpl、DifyConversationService、DifyWorkflowService 实现
- 新增 DifyStreamingChatModel 流式聊天模型
- 支持Dify工作流对话模式
- Dify自带RAG知识库时跳过本地向量库查询

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

docs/script/sql/minimax_provider.sql

@@ -1,23 +0,0 @@
--- ----------------------------
--- Add MiniMax provider
--- ----------------------------
-INSERT INTO `chat_provider` (`id`, `provider_name`, `provider_code`, `provider_icon`, `provider_desc`, `api_host`, `status`, `sort_order`, `create_dept`, `create_time`, `create_by`, `update_by`, `update_time`, `remark`, `version`, `del_flag`, `update_ip`, `tenant_id`)
-VALUES (2010000000000000001, 'MiniMax', 'minimax', NULL, 'MiniMax大模型服务，支持M2.7、M2.5等模型', 'https://api.minimax.io/v1', '0', 6, NULL, NOW(), '1', '1', NOW(), 'MiniMax厂商', NULL, '0', NULL, 0);
-
--- ----------------------------
--- Add MiniMax chat models
--- ----------------------------
-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 (2010000000000000002, 'chat', 'MiniMax-M2.7', 'minimax', 'MiniMax-M2.7', NULL, 'Y', 'https://api.minimax.io/v1', '', NULL, 1, NOW(), 1, NOW(), 'MiniMax最新旗舰模型M2.7，支持1M上下文窗口', 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 (2010000000000000003, 'chat', 'MiniMax-M2.5', 'minimax', 'MiniMax-M2.5', NULL, 'Y', 'https://api.minimax.io/v1', '', NULL, 1, NOW(), 1, NOW(), 'MiniMax M2.5模型，204K上下文窗口', 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 (2010000000000000004, 'chat', 'MiniMax-M2.5-highspeed', 'minimax', 'MiniMax-M2.5-highspeed', NULL, 'Y', 'https://api.minimax.io/v1', '', NULL, 1, NOW(), 1, NOW(), 'MiniMax M2.5高速版，204K上下文窗口，更低延迟', 0);
-
--- ----------------------------
--- Add MiniMax embedding 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 (2010000000000000005, 'vector', 'embo-01', 'minimax', 'embo-01', 1536, 'N', 'https://api.minimax.io/v1', '', NULL, 1, NOW(), 1, NOW(), 'MiniMax embo-01嵌入模型，1536维度', 0);

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 (2007528268536287233, 'vector', 'baai/bge-m3', 'ppio', 'bge-m3', 1024, 'N', 'https://api.ppinfra.com/openai', 'sk_xx', 103, 1, '2026-01-04 03:03:32', 1, '2026-03-15 19:18:51', 'BGE-M3 是一款具备多维度能力的文本嵌入模型，可同时实现密集检索、多向量检索和稀疏检索三大核心功能。该模型设计上兼容超过100种语言，并支持从短句到长达8192词元的长文本等多种输入形式。在跨语言检索任务中，BGE-M3展现出显著优势，其性能在MIRACL、MKQA等国际基准测试中位居前列。此外，针对长文档检索场景，该模型在MLDR、NarritiveQA等数据集上的表现同样达到行业领先水平。', 0);
+INSERT INTO `chat_model` VALUES (2000585866022060033, 'chat', 'zai-org/glm-5', 'ppio', 'zai-org/glm-5', NULL, 'Y', 'https://api.ppio.com/openai', 'sk_xx', 103, 1, '2025-12-15 23:16:54', 1, '2026-03-15 19:18:48', 'DeepSeek-V3.2 是一款在高效推理、复杂推理能力与智能体场景中表现突出的领先模型。其基于 DeepSeek Sparse Attention（DSA）稀疏注意力机制，在显著降低计算开销的同时优化长上下文性能；通过可扩展强化学习框架，整体能力达到 GPT-5 同级，高算力版本 V3.2-Speciale 更在推理表现上接近 Gemini-3.0-Pro；同时，模型依托大型智能体任务合成管线，具备更强的工具调用与多步骤决策能力，并在 2025 年 IMO 与 IOI 中取得金牌级表现。作为 MaaS 平台，我们已对 DeepSeek-V3.2 完成深度适配，通过动态调度、批处理加速、低延迟推理与企业级 SLA 保障，进一步增强其在企业生产环境中的稳定性、性价比与可控性，适用于搜索、问答、智能体、代码、数据处理等多类高价值场景。', 0);
+INSERT INTO `chat_model` VALUES (2007528268536287233, 'vector', 'baai/bge-m3', 'ppio', 'bge-m3', 1024, 'N', 'https://api.ppio.com/openai', 'sk_xx', 103, 1, '2026-01-04 03:03:32', 1, '2026-03-15 19:18:51', 'BGE-M3 是一款具备多维度能力的文本嵌入模型，可同时实现密集检索、多向量检索和稀疏检索三大核心功能。该模型设计上兼容超过100种语言，并支持从短句到长达8192词元的长文本等多种输入形式。在跨语言检索任务中，BGE-M3展现出显著优势，其性能在MIRACL、MKQA等国际基准测试中位居前列。此外，针对长文档检索场景，该模型在MLDR、NarritiveQA等数据集上的表现同样达到行业领先水平。', 0);
+INSERT INTO `chat_model` VALUES (2045735140488847361, 'chat', 'deepseek-chat', 'custom_api', 'deepseek-chat', NULL, NULL, 'https://api.deepseek.com', 'sk_xx', 103, 1, '2026-04-19 13:24:00', 1, '2026-04-19 13:24:00', 'deepseek对话模型', 0);
 
 -- ----------------------------
 -- Table structure for chat_provider
@@ -95,22 +96,26 @@ CREATE TABLE `chat_provider`  (
                                   `update_time` datetime NULL DEFAULT NULL COMMENT '更新时间',
                                   `remark` varchar(500) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '备注',
                                   `version` int NULL DEFAULT NULL COMMENT '版本',
-                                  `del_flag` char(1) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT '0' COMMENT '删除标志（0代表存在 1代表删除）',
+                                  `del_flag` char(1) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT '0' COMMENT '删除标志',
                                   `update_ip` varchar(128) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '更新IP',
                                   `tenant_id` bigint NOT NULL DEFAULT 0 COMMENT '租户Id',
                                   PRIMARY KEY (`id`) USING BTREE,
-                                  UNIQUE INDEX `unique_provider_code`(`provider_code` ASC, `tenant_id` ASC) USING BTREE,
+                                  UNIQUE INDEX `unique_provider_code`(`provider_code` ASC, `tenant_id` ASC, `del_flag` ASC) USING BTREE,
                                   INDEX `idx_status`(`status` ASC) USING BTREE
-) ENGINE = InnoDB AUTO_INCREMENT = 2008460994477690882 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_0900_ai_ci COMMENT = '厂商管理表' ROW_FORMAT = DYNAMIC;
+) ENGINE = InnoDB AUTO_INCREMENT = 2045727230803255298 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_0900_ai_ci COMMENT = '厂商管理表' ROW_FORMAT = DYNAMIC;
 
 -- ----------------------------
 -- Records of chat_provider
 -- ----------------------------
-INSERT INTO `chat_provider` VALUES (1, 'OpenAI', 'openai', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/01091be272334383a1efd9bc22b73ee6.png', 'OpenAI官方API服务商', 'https://api.openai.com', '0', 1, NULL, '2025-12-14 21:48:11', '1', '1', '2026-02-25 20:46:59', 'OpenAI厂商', NULL, '0', NULL, 0);
-INSERT INTO `chat_provider` VALUES (2, '阿里云百炼', 'qianwen', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/de2aa7e649de44f3ba5c6380ac6acd04.png', '阿里云百炼大模型服务', 'https://dashscope.aliyuncs.com', '0', 2, NULL, '2025-12-14 21:48:11', '1', '1', '2026-02-25 20:49:13', '阿里云厂商', NULL, '0', NULL, 0);
-INSERT INTO `chat_provider` VALUES (3, '智谱AI', 'zhipu', 'https://ruoyi-ai-1254149996.cos.ap-guangzhou.myqcloud.com/2025/12/15/a43e98fb7b3b4861b8caa6184e6fa40a.png', '智谱AI大模型服务', 'https://open.bigmodel.cn', '0', 3, NULL, '2025-12-14 21:48:11', '1', '1', '2026-02-06 00:49:14', '智谱AI厂商', NULL, '1', NULL, 0);
-INSERT INTO `chat_provider` VALUES (5, 'ollama', 'ollama', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/afecabebc8014d80b0f06b4796a74c5d.png', 'ollama大模型', 'http://127.0.0.1:11434', '0', 5, NULL, '2025-12-14 21:48:11', '1', '1', '2026-02-25 20:48:48', 'ollama厂商', NULL, '0', NULL, 0);
-INSERT INTO `chat_provider` VALUES (2000585060904435714, 'PPIO', 'ppio', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/049bb6a507174f73bba4b8d8b9e55b8a.png', 'api聚合厂商', 'https://api.ppinfra.com/openai', '0', 5, 103, '2025-12-15 23:13:42', '1', '1', '2026-02-25 20:49:01', 'api聚合厂商', NULL, '0', NULL, 0);
+INSERT INTO `chat_provider` VALUES (1, 'OpenAI', 'openai', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/01091be272334383a1efd9bc22b73ee6.png', 'OpenAI官方API服务商', 'https://api.openai.com', '0', 1, 103, '2025-12-14 21:48:11', '1', '1', '2026-02-25 20:46:59', 'OpenAI厂商', NULL, '0', NULL, 0);
+INSERT INTO `chat_provider` VALUES (11, '深度求索', 'deepseek', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/04/19/5ba8c30f153246898a4d7dc7b846de8d.png', 'DeepSeek官方API', 'https://api.deepseek.com', '0', 0, 103, '2026-04-19 12:52:34', '1', '1', '2026-04-19 13:13:25', 'DeepSeek官方API', NULL, '0', NULL, 0);
+INSERT INTO `chat_provider` VALUES (12, '智谱AI', 'zhipu', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/04/19/da071783c9284fdd9ed1ce1b57b3c75c.png', '智谱AI大模型服务', 'https://open.bigmodel.cn', '0', 4, 103, '2025-12-14 21:48:11', '1', '1', '2026-04-19 13:14:00', '智谱AI厂商', NULL, '0', NULL, 0);
+INSERT INTO `chat_provider` VALUES (13, '小米MIMO', 'xiaomi', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/04/19/18dd39365ce244e3ae5e030da036760e.png', '小米官方API', 'https://api.xiaomimimo.com/anthropic/v1/messages', '0', 3, 103, '2026-04-19 12:48:24', '1', '1', '2026-04-19 13:14:22', '小米官方API', NULL, '0', NULL, 0);
+INSERT INTO `chat_provider` VALUES (14, '阿里云百炼', 'qianwen', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/de2aa7e649de44f3ba5c6380ac6acd04.png', '阿里云百炼大模型服务', 'https://dashscope.aliyuncs.com', '0', 2, 103, '2025-12-14 21:48:11', '1', '1', '2026-02-25 20:49:13', '阿里云厂商', NULL, '0', NULL, 0);
+INSERT INTO `chat_provider` VALUES (15, 'PPIO', 'ppio', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/049bb6a507174f73bba4b8d8b9e55b8a.png', 'api聚合厂商', 'https://api.ppinfra.com/openai', '0', 5, 103, '2025-12-15 23:13:42', '1', '1', '2026-02-25 20:49:01', 'api聚合厂商', NULL, '0', NULL, 0);
+INSERT INTO `chat_provider` VALUES (16, 'MiniMax', 'minimax', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/04/19/fdc712e90e0e4d78b05862ad230884e5.png', 'MiniMax大模型服务，支持M2.7、M2.5等模型', 'https://api.minimax.io/v1', '0', 6, 103, '2026-04-19 12:50:12', '1', '1', '2026-04-19 13:14:59', 'MiniMax厂商', NULL, '0', NULL, 0);
+INSERT INTO `chat_provider` VALUES (17, 'ollama', 'ollama', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/afecabebc8014d80b0f06b4796a74c5d.png', 'ollama大模型', 'http://127.0.0.1:11434', '0', 7, 103, '2025-12-14 21:48:11', '1', '1', '2026-02-25 20:48:48', 'ollama厂商', NULL, '0', NULL, 0);
+INSERT INTO `chat_provider` VALUES (18, '自定义厂商', 'custom_api', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/04/19/c1a8e122510f4e2f90deb36958af710b.png', 'OPENAI兼容格式', '自定义', '0', 8, 103, '2026-04-19 12:35:57', '1', '1', '2026-04-19 13:17:20', 'OPENAI兼容格式', NULL, '0', NULL, 0);
 
 -- ----------------------------
 -- Table structure for chat_session

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;

pom.xml

@@ -58,7 +58,7 @@
         <langchain4j.community.version>1.13.0-beta23</langchain4j.community.version>
         <langgraph4j.version>1.5.3</langgraph4j.version>
         <weaviate.version>1.19.6</weaviate.version>
-        <dify.version>1.0.7</dify.version>
+        <dify.version>1.2.6</dify.version>
         <!-- gRPC 版本 - 解决 Milvus SDK 依赖冲突 -->
         <grpc.version>1.62.2</grpc.version>
         <!-- Apache Commons Compress - 用于POI处理ZIP格式 -->

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-modules/ruoyi-chat/pom.xml

@@ -173,6 +173,8 @@
             <artifactId>spring-boot-starter-test</artifactId>
             <scope>test</scope>
         </dependency>
+
+        <!-- Test dependencies -->
         <dependency>
             <groupId>org.junit.jupiter</groupId>
             <artifactId>junit-jupiter</artifactId>

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

@@ -17,7 +17,9 @@ public enum ChatModeType {
     OPEN_AI("openai", "openai"),
     PPIO("ppio", "ppio"),
     CUSTOM_API("custom_api", "自定义API"),
-    MINIMAX("minimax", "MiniMax");
+    MINIMAX("minimax", "MiniMax"),
+    XIAOMI("xiaomi", "小米MiMo"),
+    DIFY("dify", "Dify平台");
     private final String code;
     private final String description;
 

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

@@ -47,6 +47,7 @@ import org.ruoyi.common.sse.core.SseEmitterManager;
 import org.ruoyi.common.sse.utils.SseMessageUtils;
 import org.ruoyi.domain.bo.vector.QueryVectorBo;
 import org.ruoyi.domain.vo.knowledge.KnowledgeInfoVo;
+import org.ruoyi.enums.ChatModeType;
 import org.ruoyi.factory.ChatServiceFactory;
 import org.ruoyi.mcp.service.core.ToolProviderFactory;
 import org.ruoyi.observability.*;
@@ -97,6 +98,8 @@ public class ChatServiceFacade implements IChatService {
 
     private final ToolProviderFactory toolProviderFactory;
 
+    private final org.ruoyi.service.chat.impl.provider.DifyWorkflowService difyWorkflowService;
+
     /**
      * 内存实例缓存，避免同一会话重复创建
      * Key: sessionId, Value: MessageWindowChatMemory实例
@@ -163,6 +166,14 @@ public class ChatServiceFacade implements IChatService {
      * @return 如果需要提前返回则返回SseEmitter，否则返回null
      */
     private SseEmitter handleSpecialChatModes(ChatRequest chatRequest) {
+        // 处理 Dify 工作流对话
+        if (chatRequest.getEnableWorkFlow()
+                && chatRequest.getChatModelVo() != null
+                && ChatModeType.DIFY.getCode().equals(chatRequest.getChatModelVo().getProviderCode())) {
+            log.info("处理Dify工作流对话,会话: {}", chatRequest.getSessionId());
+            return difyWorkflowService.streaming(chatRequest.getChatModelVo(), chatRequest);
+        }
+
         // 处理工作流对话
         if (chatRequest.getEnableWorkFlow()) {
             log.info("处理工作流对话,会话: {}", chatRequest.getSessionId());
@@ -430,8 +441,12 @@ public class ChatServiceFacade implements IChatService {
             }
         }
 
+        // Dify 自带 RAG 知识库检索，跳过本地向量库查询
+        boolean isDifyProvider = chatRequest.getChatModelVo() != null
+                && ChatModeType.DIFY.getCode().equals(chatRequest.getChatModelVo().getProviderCode());
+
         // 从向量库查询相关历史消息（知识库内容作为上下文）
-        if (chatRequest.getKnowledgeId() != null) {
+        if (chatRequest.getKnowledgeId() != null && !isDifyProvider) {
             // 查询知识库信息
             KnowledgeInfoVo knowledgeInfoVo = knowledgeInfoService.queryById(Long.valueOf(chatRequest.getKnowledgeId()));
             if (knowledgeInfoVo == null) {

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

@@ -0,0 +1,43 @@
+package org.ruoyi.service.chat.impl.provider;
+
+import dev.langchain4j.model.chat.ChatModel;
+import dev.langchain4j.model.chat.StreamingChatModel;
+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.service.chat.AbstractChatService;
+import org.ruoyi.service.chat.impl.provider.model.DifyStreamingChatModel;
+import org.springframework.stereotype.Service;
+
+/**
+ * Dify 平台对话服务
+ * <p>
+ * 通过 dify-java-client 接入 Dify 的对话型应用 (Chat App) 和
+ * 工作流编排对话应用 (Chatflow App)，支持流式 SSE 响应。
+ *
+ * @author better
+ */
+@Service
+@Slf4j
+@RequiredArgsConstructor
+public class DifyChatServiceImpl implements AbstractChatService {
+
+    private final DifyConversationService difyConversationService;
+
+    @Override
+    public StreamingChatModel buildStreamingChatModel(ChatModelVo chatModelVo, ChatRequest chatRequest) {
+        return new DifyStreamingChatModel(chatModelVo, chatRequest, difyConversationService);
+    }
+
+    @Override
+    public ChatModel buildChatModel(ChatModelVo chatModelVo) {
+        throw new UnsupportedOperationException("Dify 不支持同步 ChatModel，请使用流式模式");
+    }
+
+    @Override
+    public String getProviderName() {
+        return ChatModeType.DIFY.getCode();
+    }
+}

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

@@ -0,0 +1,35 @@
+package org.ruoyi.service.chat.impl.provider;
+
+import org.springframework.stereotype.Service;
+
+import java.util.concurrent.ConcurrentHashMap;
+
+/**
+ * Dify 会话映射管理
+ * <p>
+ * 维护 ruoyi sessionId 与 Dify conversation_id 的映射关系，
+ * 确保多轮对话上下文连续。
+ *
+ * @author better
+ */
+@Service
+public class DifyConversationService {
+
+    private final ConcurrentHashMap<Long, String> conversationMap = new ConcurrentHashMap<>();
+
+    public String getConversationId(Long sessionId) {
+        return conversationMap.get(sessionId);
+    }
+
+    public void saveMapping(Long sessionId, String difyConversationId) {
+        if (sessionId != null && difyConversationId != null) {
+            conversationMap.put(sessionId, difyConversationId);
+        }
+    }
+
+    public void clearMapping(Long sessionId) {
+        if (sessionId != null) {
+            conversationMap.remove(sessionId);
+        }
+    }
+}

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

@@ -0,0 +1,137 @@
+package org.ruoyi.service.chat.impl.provider;
+
+import com.fasterxml.jackson.databind.JsonNode;
+import com.fasterxml.jackson.databind.node.ObjectNode;
+import io.github.imfangs.dify.client.DifyClientFactory;
+import io.github.imfangs.dify.client.DifyWorkflowClient;
+import io.github.imfangs.dify.client.enums.ResponseMode;
+import io.github.imfangs.dify.client.event.ErrorEvent;
+import io.github.imfangs.dify.client.event.WorkflowFinishedEvent;
+import io.github.imfangs.dify.client.event.WorkflowTextChunkEvent;
+import io.github.imfangs.dify.client.callback.WorkflowStreamCallback;
+import io.github.imfangs.dify.client.model.workflow.WorkflowRunRequest;
+import lombok.extern.slf4j.Slf4j;
+import org.ruoyi.common.chat.domain.dto.request.ChatRequest;
+import org.ruoyi.common.chat.domain.dto.request.WorkFlowRunner;
+import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
+import org.ruoyi.common.sse.utils.SseMessageUtils;
+import org.springframework.stereotype.Service;
+import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;
+
+import java.util.HashMap;
+import java.util.Iterator;
+import java.util.List;
+import java.util.Map;
+import java.util.concurrent.CompletableFuture;
+
+/**
+ * Dify 工作流执行服务
+ * <p>
+ * 通过 DifyWorkflowClient 调用 Dify 平台上部署的工作流应用，
+ * 并将节点事件通过 SSE 实时推送给前端。
+ *
+ * @author better
+ */
+@Service
+@Slf4j
+public class DifyWorkflowService {
+
+    /**
+     * 流式执行 Dify 工作流
+     *
+     * @param chatModelVo 模型配置（apiHost= Dify 地址, apiKey= Dify 密钥）
+     * @param chatRequest 聊天请求
+     * @return SSE emitter
+     */
+    public SseEmitter streaming(ChatModelVo chatModelVo, ChatRequest chatRequest) {
+        Long userId = chatRequest.getUserId();
+        String tokenValue = chatRequest.getTokenValue();
+        SseEmitter emitter = chatRequest.getEmitter();
+
+        // 构建 Dify 工作流请求参数
+        Map<String, Object> inputs = convertInputs(chatRequest.getWorkFlowRunner());
+
+        WorkflowRunRequest request = WorkflowRunRequest.builder()
+                .inputs(inputs)
+                .responseMode(ResponseMode.STREAMING)
+                .user(String.valueOf(userId))
+                .build();
+
+        DifyWorkflowClient client = DifyClientFactory.createWorkflowClient(
+                normalizeBaseUrl(chatModelVo.getApiHost()),
+                chatModelVo.getApiKey());
+
+        // 异步执行，避免阻塞请求线程
+        CompletableFuture.runAsync(() -> {
+            try {
+                client.runWorkflowStream(request, new WorkflowStreamCallback() {
+
+                    @Override
+                    public void onWorkflowTextChunk(WorkflowTextChunkEvent event) {
+                        String text = event.getData() != null ? event.getData().getText() : null;
+                        if (text != null) {
+                            SseMessageUtils.sendContent(userId, text);
+                        }
+                    }
+
+                    @Override
+                    public void onWorkflowFinished(WorkflowFinishedEvent event) {
+                        // 将最终输出作为内容发送
+                        if (event.getData() != null && event.getData().getOutputs() != null) {
+                            Map<String, Object> outputs = event.getData().getOutputs();
+                            for (Map.Entry<String, Object> entry : outputs.entrySet()) {
+                                SseMessageUtils.sendContent(userId,
+                                        entry.getKey() + ": " + entry.getValue() + "\n");
+                            }
+                        }
+                        SseMessageUtils.sendDone(userId);
+                        SseMessageUtils.completeConnection(userId, tokenValue);
+                    }
+
+                    @Override
+                    public void onError(ErrorEvent event) {
+                        SseMessageUtils.sendError(userId, event.getMessage());
+                    }
+
+                    @Override
+                    public void onException(Throwable throwable) {
+                        log.error("Dify 工作流执行异常", throwable);
+                        SseMessageUtils.sendError(userId, throwable.getMessage());
+                        SseMessageUtils.completeConnection(userId, tokenValue);
+                    }
+                });
+            } catch (Exception e) {
+                log.error("Dify 工作流执行失败", e);
+                SseMessageUtils.sendError(userId, e.getMessage());
+                SseMessageUtils.completeConnection(userId, tokenValue);
+            }
+        });
+
+        return emitter;
+    }
+
+    /**
+     * 将 WorkFlowRunner.inputs (List<ObjectNode>) 转换为 Dify 所需的 Map
+     */
+    private Map<String, Object> convertInputs(WorkFlowRunner runner) {
+        Map<String, Object> result = new HashMap<>();
+        if (runner == null || runner.getInputs() == null) {
+            return result;
+        }
+        for (ObjectNode node : runner.getInputs()) {
+            Iterator<Map.Entry<String, JsonNode>> fields = node.fields();
+            while (fields.hasNext()) {
+                Map.Entry<String, JsonNode> field = fields.next();
+                result.put(field.getKey(), field.getValue().asText());
+            }
+        }
+        return result;
+    }
+
+    private String normalizeBaseUrl(String baseUrl) {
+        if (baseUrl == null || baseUrl.isBlank()) {
+            throw new IllegalArgumentException("Dify API 地址(apiHost)不能为空");
+        }
+        return baseUrl.endsWith("/") ? baseUrl.substring(0, baseUrl.length() - 1) : baseUrl;
+    }
+}

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/model/DifyStreamingChatModel.java

@@ -0,0 +1,172 @@
+package org.ruoyi.service.chat.impl.provider.model;
+
+import dev.langchain4j.data.message.AiMessage;
+import dev.langchain4j.data.message.ChatMessage;
+import dev.langchain4j.data.message.UserMessage;
+import dev.langchain4j.model.chat.StreamingChatModel;
+import dev.langchain4j.model.chat.response.ChatResponse;
+import dev.langchain4j.model.chat.response.StreamingChatResponseHandler;
+import io.github.imfangs.dify.client.DifyChatClient;
+import io.github.imfangs.dify.client.DifyClientFactory;
+import io.github.imfangs.dify.client.enums.ResponseMode;
+import io.github.imfangs.dify.client.event.ErrorEvent;
+import io.github.imfangs.dify.client.event.MessageEndEvent;
+import io.github.imfangs.dify.client.event.MessageEvent;
+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.service.chat.impl.provider.DifyConversationService;
+
+import java.util.List;
+
+/**
+ * Dify 流式聊天模型适配器
+ * <p>
+ * 将 Dify 的回调式流式响应适配为 langchain4j 的 StreamingChatModel 接口，
+ * 使 ChatServiceFacade 可以像其他 provider 一样统一调用。
+ *
+ * @author better
+ */
+@Slf4j
+public class DifyStreamingChatModel implements StreamingChatModel {
+
+    private final ChatModelVo chatModelVo;
+    private final ChatRequest chatRequest;
+    private final DifyConversationService conversationService;
+
+    public DifyStreamingChatModel(ChatModelVo chatModelVo, ChatRequest chatRequest,
+                                  DifyConversationService conversationService) {
+        this.chatModelVo = chatModelVo;
+        this.chatRequest = chatRequest;
+        this.conversationService = conversationService;
+    }
+
+    @Override
+    public void chat(List<ChatMessage> messages, StreamingChatResponseHandler handler) {
+        // 1. 从 langchain4j 消息列表中提取最后一条用户消息作为 query
+        String query = extractUserQuery(messages);
+
+        // 2. 获取 Dify conversation_id（多轮对话连续性）
+        String conversationId = null;
+        if (chatRequest.getSessionId() != null) {
+            conversationId = conversationService.getConversationId(chatRequest.getSessionId());
+        }
+
+        // 3. 构建 Dify 请求
+        io.github.imfangs.dify.client.model.chat.ChatMessage difyMessage = io.github.imfangs.dify.client.model.chat.ChatMessage.builder()
+                .query(query)
+                .user(String.valueOf(chatRequest.getUserId()))
+                .responseMode(ResponseMode.STREAMING)
+                .conversationId(conversationId)
+                .autoGenerateName(true)
+                .build();
+
+        // 4. 创建 Dify 客户端并发送流式请求
+        try {
+            DifyChatClient client = DifyClientFactory.createChatClient(
+                    normalizeBaseUrl(chatModelVo.getApiHost()),
+                    chatModelVo.getApiKey());
+
+            client.sendChatMessageStream(difyMessage, new DifyChatStreamAdapter(handler));
+        } catch (Exception e) {
+            log.error("Dify 流式对话调用失败", e);
+            handler.onError(e);
+        }
+    }
+
+    @Override
+    public void chat(String userMessage, StreamingChatResponseHandler handler) {
+        io.github.imfangs.dify.client.model.chat.ChatMessage difyMessage = io.github.imfangs.dify.client.model.chat.ChatMessage.builder()
+                .query(userMessage)
+                .user(String.valueOf(chatRequest.getUserId()))
+                .responseMode(ResponseMode.STREAMING)
+                .conversationId(chatRequest.getSessionId() != null
+                        ? conversationService.getConversationId(chatRequest.getSessionId()) : null)
+                .autoGenerateName(true)
+                .build();
+
+        try {
+            DifyChatClient client = DifyClientFactory.createChatClient(
+                    normalizeBaseUrl(chatModelVo.getApiHost()),
+                    chatModelVo.getApiKey());
+
+            client.sendChatMessageStream(difyMessage, new DifyChatStreamAdapter(handler));
+        } catch (Exception e) {
+            log.error("Dify 流式对话调用失败", e);
+            handler.onError(e);
+        }
+    }
+
+    /**
+     * 从 langchain4j 消息列表中提取最后一条用户消息文本
+     */
+    private String extractUserQuery(List<ChatMessage> messages) {
+        for (int i = messages.size() - 1; i >= 0; i--) {
+            ChatMessage msg = messages.get(i);
+            if (msg instanceof UserMessage) {
+                return ((UserMessage) msg).singleText();
+            }
+        }
+        return "";
+    }
+
+    private String normalizeBaseUrl(String baseUrl) {
+        if (baseUrl == null || baseUrl.isBlank()) {
+            throw new IllegalArgumentException("Dify API 地址(apiHost)不能为空");
+        }
+        return baseUrl.endsWith("/") ? baseUrl.substring(0, baseUrl.length() - 1) : baseUrl;
+    }
+
+    /**
+     * Dify 回调适配器
+     * 将 Dify ChatStreamCallback 事件转发给 langchain4j StreamingChatResponseHandler
+     */
+    private class DifyChatStreamAdapter implements io.github.imfangs.dify.client.callback.ChatStreamCallback {
+
+        private final StreamingChatResponseHandler handler;
+        private final StringBuilder fullResponse = new StringBuilder();
+
+        DifyChatStreamAdapter(StreamingChatResponseHandler handler) {
+            this.handler = handler;
+        }
+
+        @Override
+        public void onMessage(MessageEvent event) {
+            String answer = event.getAnswer();
+            if (answer != null) {
+                fullResponse.append(answer);
+                handler.onPartialResponse(answer);
+            }
+            // 保存 Dify conversation_id 以维持多轮对话
+            if (event.getConversationId() != null && chatRequest.getSessionId() != null) {
+                conversationService.saveMapping(chatRequest.getSessionId(), event.getConversationId());
+            }
+        }
+
+        @Override
+        public void onMessageEnd(MessageEndEvent event) {
+            // 保存 conversation_id
+            if (event.getConversationId() != null && chatRequest.getSessionId() != null) {
+                conversationService.saveMapping(chatRequest.getSessionId(), event.getConversationId());
+            }
+
+            // 构建完整的 ChatResponse 交给上层处理
+            AiMessage aiMessage = new AiMessage(fullResponse.toString());
+            ChatResponse response = ChatResponse.builder()
+                    .aiMessage(aiMessage)
+                    .id(event.getMessageId())
+                    .build();
+            handler.onCompleteResponse(response);
+        }
+
+        @Override
+        public void onError(ErrorEvent event) {
+            handler.onError(new RuntimeException(event.getMessage()));
+        }
+
+        @Override
+        public void onException(Throwable throwable) {
+            handler.onError(throwable);
+        }
+    }
+}