diff --git a/README.md b/README.md index 94182ff4..4215993c 100644 --- a/README.md +++ b/README.md @@ -72,7 +72,7 @@ - **实时通信**：WebSocket 实时通信，SSE 流式响应 - **系统监控**：完善的日志体系、性能监控、服务健康检查 -## 使用web coding急速部署 +## 使用web coding部署 #### 在线体验： https://monkeycode-ai.com/?ic=019d9e9f-edc3-7a4b-8987-11b028751a1e @@ -233,17 +233,21 @@ docker-compose -f docker-compose-all.yaml restart [服务名] ## 🙏 特别鸣谢 感谢以下优秀的开源项目为本项目提供支持： -- [Spring AI Alibaba Copilot](https://github.com/spring-ai-alibaba/copilot) - 基于spring-ai-alibaba - 的智能编码助手 - [Langchain4j](https://github.com/langchain4j/langchain4j) - 强大的 Java LLM 开发框架 - [RuoYi-Vue-Plus](https://gitee.com/dromara/RuoYi-Vue-Plus) - 成熟的企业级快速开发框架 - [Vben Admin](https://github.com/vbenjs/vue-vben-admin) - 现代化的 Vue 后台管理模板 -## 🌐 生态伙伴 -- [PPIO 派欧云](https://ppinfra.com/user/register?invited_by=P8QTUY&utm_source=github_ruoyi-ai) - 提供高性价比的 GPU - 算力和模型 API 服务 -- [优云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_ruoyi) - 万卡RTX40系GPU+海内外主流模型API服务，秒级响应，按量计费，新客免费用。 +## 💎 赞助商 +感谢以下赞助商对本项目的支持： + + + Atlas Cloud + + +- **[Atlas Cloud](https://www.atlascloud.ai/)** - 全模态AI推理平台，为开发者提供统一的AI API，支持视频生成、图像生成和大语言模型。一次接入，即可访问300+精选模型。 + +- **[编程计划优惠](https://www.atlascloud.ai/console/coding-plan)** - Atlas Cloud 针对更经济型 API 推出的全新编码计划促销活动 ## 💬 社区交流 diff --git a/README_EN.md b/README_EN.md index b369491e..98b95dc8 100644 --- a/README_EN.md +++ b/README_EN.md @@ -220,9 +220,15 @@ Thanks to the following excellent open-source projects for their support: ## 🌐 Ecosystem Partners -- [PPIO Cloud](https://ppinfra.com/user/register?invited_by=P8QTUY&utm_source=github_ruoyi-ai) - Provides cost-effective GPU computing and model API services -- [Youyun Intelligent Computing](https://www.compshare.cn/?ytag=GPU_YY-gh_ruoyi) - Thousands of RTX40 series GPUs + mainstream models API services, second-level response, pay-per-use, free for new customers. +**[Atlas Cloud](https://www.atlascloud.ai/)** - A full-modal AI inference platform that gives developers a single AI API to access video generation, image generation, and LLM APIs. Instead of managing multiple vendor integrations, you connect once and get unified access to 300+ curated models across all modalities. 👉 [Coding Plan Promotion](https://www.atlascloud.ai/console/coding-plan) +## 💎 Sponsors + +Thanks to the following sponsors for supporting this project: + +**[Atlas Cloud](https://www.atlascloud.ai/)** - A full-modal AI inference platform that gives developers a single AI API to access video generation, image generation, and LLM APIs. Connect once and get unified access to 300+ curated models across all modalities. + +> *If you would like to become a sponsor, please contact us via WeChat or Telegram.* ## 💬 Community Chat diff --git a/docs/script/sql/ruoyi-ai-v3_mysql8.sql b/docs/script/sql/ruoyi-ai-v3_mysql8.sql index 69a169bd..89ea2af7 100644 --- a/docs/script/sql/ruoyi-ai-v3_mysql8.sql +++ b/docs/script/sql/ruoyi-ai-v3_mysql8.sql @@ -1,7 +1,7 @@ /* - Navicat MySQL Dump SQL + Navicat Premium Dump SQL - Source Server : 本地 + Source Server : localhost_3306 Source Server Type : MySQL Source Server Version : 80045 (8.0.45) Source Host : localhost:3306 @@ -11,13 +11,11 @@ Target Server Version : 80045 (8.0.45) File Encoding : 65001 - Date: 15/03/2026 23:56:19 + Date: 21/05/2026 11:03:49 */ SET NAMES utf8mb4; SET FOREIGN_KEY_CHECKS = 0; --- 忽略所有错误，继续执行 -SET sql_mode = ''; -- ---------------------------- -- Table structure for chat_message @@ -72,9 +70,9 @@ CREATE TABLE `chat_model` ( -- ---------------------------- -- 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); +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 (2000585866022060033, 'chat', 'zai-org/glm-5.1', 'atlas', 'zai-org/glm-5.1', NULL, 'Y', 'https://api.atlascloud.ai/v1', 'sk_xx', 103, 1, '2025-12-15 23:16:54', 1, '2026-03-15 19:18:48', '对话模型', 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 (2007528268536287233, 'vector', 'embedding-3', 'zhipu', 'embedding-3', 2048, 'N', 'https://open.bigmodel.cn', 'sk_xx', 103, 1, '2026-01-04 03:03:32', 1, '2026-03-15 19:18:51', '向量模型', 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 (2045071617578237953, 'rerank', 'rerank', 'zhipu', 'rerank', NULL, 'N', 'https://open.bigmodel.cn', 'sk_xx', 103, 1, '2026-04-17 17:27:24', 1, '2026-04-20 15:21:48', '重排序模型', 0); -- ---------------------------- -- Table structure for chat_provider @@ -107,12 +105,11 @@ CREATE TABLE `chat_provider` ( -- ---------------------------- -- 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 (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/v1', '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 (15, 'Atlas Cloud', 'atlas', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/04/19/atlascloud.png', '全模态AI推理平台', 'https://api.atlascloud.ai/v1', '0', 5, 103, '2025-12-15 23:13:42', '1', '1', '2026-02-25 20:49:01', 'Atlas Cloud AI平台', 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); @@ -1091,6 +1088,7 @@ CREATE TABLE `knowledge_attach` ( `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', + `status` tinyint NULL DEFAULT 0 COMMENT '解析状态: 0待解析, 1解析中, 2已解析, 3解析失败', PRIMARY KEY (`id`) USING BTREE, UNIQUE INDEX `idx_kname`(`knowledge_id` ASC, `name` ASC) USING BTREE ) ENGINE = InnoDB AUTO_INCREMENT = 2033199209203183619 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_0900_ai_ci COMMENT = '知识库附件' ROW_FORMAT = DYNAMIC; @@ -1115,7 +1113,9 @@ CREATE TABLE `knowledge_fragment` ( `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 + `knowledge_id` bigint NULL DEFAULT NULL COMMENT '知识库ID', + PRIMARY KEY (`id`) USING BTREE, + FULLTEXT INDEX `ft_content`(`content`) WITH PARSER `ngram` ) ENGINE = InnoDB AUTO_INCREMENT = 2033199209131880451 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_0900_ai_ci COMMENT = '知识片段' ROW_FORMAT = DYNAMIC; -- ---------------------------- @@ -1135,6 +1135,7 @@ CREATE TABLE `knowledge_info` ( `separator` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '知识分隔符', `overlap_char` int NULL DEFAULT NULL COMMENT '重叠字符数', `retrieve_limit` int NULL DEFAULT NULL COMMENT '知识库中检索的条数', + `similarity_threshold` double NULL DEFAULT 0.5 COMMENT '相似度阈值', `text_block_size` int NULL DEFAULT NULL COMMENT '文本块大小', `vector_model` varchar(50) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '向量库', `embedding_model` varchar(50) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '向量模型', @@ -1145,6 +1146,13 @@ CREATE TABLE `knowledge_info` ( `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', + `enable_rerank` tinyint NULL DEFAULT 0 COMMENT '是否启用重排序（0否 1是）', + `rerank_score_threshold` double NULL DEFAULT NULL COMMENT '重排序相关性分数阈值', + `rerank_top_n` int NULL DEFAULT NULL COMMENT '重排序后返回的文档数量', + `rerank_model` varchar(100) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '重排序模型名称', + `enable_hybrid` tinyint(1) NULL DEFAULT 0 COMMENT '是否启用混合检索', + `hybrid_alpha` double NULL DEFAULT 0.5 COMMENT '混合检索权重比例 (0.0=纯向量, 1.0=纯关键词)', + `system_prompt` text CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL COMMENT '系统提示词', PRIMARY KEY (`id`) USING BTREE ) ENGINE = InnoDB AUTO_INCREMENT = 2033198818050781187 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_0900_ai_ci COMMENT = '知识库' ROW_FORMAT = DYNAMIC; @@ -1174,7 +1182,7 @@ CREATE TABLE `mcp_market_info` ( INDEX `idx_name`(`name` ASC) USING BTREE, INDEX `idx_status`(`status` ASC) USING BTREE, INDEX `idx_tenant_id`(`tenant_id` ASC) USING BTREE -) ENGINE = InnoDB AUTO_INCREMENT = 1 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_unicode_ci COMMENT = 'MCP市场表' ROW_FORMAT = Dynamic; +) ENGINE = InnoDB AUTO_INCREMENT = 1 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_unicode_ci COMMENT = 'MCP市场表' ROW_FORMAT = DYNAMIC; -- ---------------------------- -- Records of mcp_market_info @@ -1198,7 +1206,7 @@ CREATE TABLE `mcp_market_tool` ( INDEX `idx_market_id`(`market_id` ASC) USING BTREE, INDEX `idx_tool_name`(`tool_name` ASC) USING BTREE, INDEX `idx_is_loaded`(`is_loaded` ASC) USING BTREE -) ENGINE = InnoDB AUTO_INCREMENT = 1 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_unicode_ci COMMENT = 'MCP市场工具关联表' ROW_FORMAT = Dynamic; +) ENGINE = InnoDB AUTO_INCREMENT = 1 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_unicode_ci COMMENT = 'MCP市场工具关联表' ROW_FORMAT = DYNAMIC; -- ---------------------------- -- Records of mcp_market_tool @@ -1227,7 +1235,7 @@ CREATE TABLE `mcp_tool_info` ( INDEX `idx_type`(`type` ASC) USING BTREE, INDEX `idx_status`(`status` ASC) USING BTREE, INDEX `idx_tenant_id`(`tenant_id` ASC) USING BTREE -) ENGINE = InnoDB AUTO_INCREMENT = 7 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_unicode_ci COMMENT = 'MCP工具表' ROW_FORMAT = Dynamic; +) ENGINE = InnoDB AUTO_INCREMENT = 7 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_unicode_ci COMMENT = 'MCP工具表' ROW_FORMAT = DYNAMIC; -- ---------------------------- -- Records of mcp_tool_info @@ -2085,6 +2093,7 @@ INSERT INTO `sys_dict_data` VALUES (2026642525081116674, '000000', 1, '图像', INSERT INTO `sys_dict_data` VALUES (2026643983713247233, '000000', 1, '次数计费', '1', 'sys_model_billing', NULL, 'green', 'N', 103, 1, '2026-02-25 21:02:34', 1, '2026-02-25 21:02:56', NULL); INSERT INTO `sys_dict_data` VALUES (2026644058522853378, '000000', 2, 'token计费', '2', 'sys_model_billing', NULL, 'primary', 'N', 103, 1, '2026-02-25 21:02:51', 1, '2026-02-25 21:02:51', NULL); INSERT INTO `sys_dict_data` VALUES (2027261114955931650, '000000', 2, '向量', 'vector', 'chat_model_category', NULL, 'default', 'N', 103, 1, '2026-02-27 13:54:49', 1, '2026-02-27 13:54:54', NULL); +INSERT INTO `sys_dict_data` 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'); -- ---------------------------- -- Table structure for sys_dict_type @@ -2156,243 +2165,6 @@ CREATE TABLE `sys_logininfor` ( -- ---------------------------- -- Records of sys_logininfor -- ---------------------------- -INSERT INTO `sys_logininfor` VALUES (2018437160497668098, '000000', 'admin', 'web', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-03 05:31:34'); -INSERT INTO `sys_logininfor` VALUES (2018489328494317570, '000000', 'admin', 'web', 'pc', '58.56.198.114', '中国|山东省|泰安市|电信', 'Chrome', 'Windows 10 or Windows Server 2016', '0', 'Login successful', '2026-02-03 08:58:52'); -INSERT INTO `sys_logininfor` VALUES (2018490223370047490, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'Chrome', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-03 09:02:26'); -INSERT INTO `sys_logininfor` VALUES (2018494821124149250, '000000', 'admin', 'web', 'pc', '180.165.21.147', '中国|上海|上海市|电信', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', 'Login successful', '2026-02-03 09:20:42'); -INSERT INTO `sys_logininfor` VALUES (2018495323429801985, '000000', 'admin', 'web', 'pc', '218.1.209.117', '中国|上海|上海市|电信', 'Chrome', 'Windows 10 or Windows Server 2016', '0', 'Login successful', '2026-02-03 09:22:42'); -INSERT INTO `sys_logininfor` VALUES (2018496463106084866, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'Chrome', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-03 09:27:13'); -INSERT INTO `sys_logininfor` VALUES (2018506873276338177, '000000', 'admin', 'web', 'pc', '14.155.110.230', '中国|广东省|深圳市|电信', 'Chrome', 'OSX', '0', 'Login successful', '2026-02-03 10:08:35'); 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-INSERT INTO `sys_logininfor` VALUES (2033167392953675778, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-03-15 21:04:16'); -INSERT INTO `sys_logininfor` VALUES (2033168637663719425, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-03-15 21:09:12'); -INSERT INTO `sys_logininfor` VALUES (2033170263812157441, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '退出成功', '2026-03-15 21:15:40'); -INSERT INTO `sys_logininfor` VALUES (2033170654197002242, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-03-15 21:17:13'); -INSERT INTO `sys_logininfor` VALUES (2033170805703651330, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '退出成功', '2026-03-15 21:17:49'); -INSERT INTO `sys_logininfor` VALUES (2033170821767835650, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-03-15 21:17:53'); -INSERT INTO `sys_logininfor` VALUES (2033170964009267201, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-03-15 21:18:27'); -INSERT INTO `sys_logininfor` VALUES (2033197762549985282, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-03-15 23:04:56'); -INSERT INTO `sys_logininfor` VALUES (2033200372921217025, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '1', '密码输入错误1次', '2026-03-15 23:15:19'); -INSERT INTO `sys_logininfor` VALUES (2033200386498179073, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-03-15 23:15:22'); -INSERT INTO `sys_logininfor` VALUES (2033210457315696642, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-03-15 23:55:23'); -- ---------------------------- -- Table structure for sys_menu @@ -3176,7 +2948,7 @@ CREATE TABLE `sys_user` ( -- ---------------------------- -- Records of sys_user -- ---------------------------- -INSERT INTO `sys_user` VALUES (1, '000000', 103, 'admin', 'admin', 'sys_user', 'ageerle@163.com', '15888888888', '1', NULL, '$2a$10$7JB720yubVSZvUI0rEqK/.VqGOZTH.ulu33dHOiBE8ByOhJIrdAu2', '0', '0', '127.0.0.1', '2026-03-15 23:55:23', 103, 1, '2026-02-05 09:22:12', -1, '2026-03-15 23:55:23', '管理员', NULL, 0.00); +INSERT INTO `sys_user` VALUES (1, '000000', 103, 'admin', 'admin', 'sys_user', 'ageerle@163.com', '15888888888', '1', NULL, '$2a$10$7JB720yubVSZvUI0rEqK/.VqGOZTH.ulu33dHOiBE8ByOhJIrdAu2', '0', '0', '127.0.0.1', '2026-05-19 23:16:57', 103, 1, '2026-02-05 09:22:12', -1, '2026-05-19 23:16:57', '管理员', NULL, 0.00); INSERT INTO `sys_user` VALUES (3, '000000', 108, 'test', '本部门及以下 密码666666', 'sys_user', '', '', '0', NULL, '$2a$10$b8yUzN0C71sbz.PhNOCgJe.Tu1yWC3RNrTyjSQ8p1W0.aaUXUJ.Ne', '0', '0', '127.0.0.1', '2026-02-05 09:22:12', 103, 1, '2026-02-05 09:22:12', 3, '2026-02-05 09:22:12', NULL, NULL, 0.00); INSERT INTO `sys_user` VALUES (4, '000000', 102, 'test1', '仅本人 密码666666', 'sys_user', '', '', '0', NULL, '$2a$10$b8yUzN0C71sbz.PhNOCgJe.Tu1yWC3RNrTyjSQ8p1W0.aaUXUJ.Ne', '0', '0', '127.0.0.1', '2026-02-05 09:22:12', 103, 1, '2026-02-05 09:22:12', 4, '2026-02-05 09:22:12', NULL, NULL, 0.00); diff --git a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/enums/ChatModeType.java b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/enums/ChatModeType.java index 066d6c3a..6279b107 100644 --- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/enums/ChatModeType.java +++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/enums/ChatModeType.java @@ -15,7 +15,7 @@ public enum ChatModeType { DEEP_SEEK("deepseek", "深度求索"), QIAN_WEN("qianwen", "通义千问"), OPEN_AI("openai", "openai"), - PPIO("ppio", "ppio"), + ATLAS("atlas", "Atlas Cloud"), CUSTOM_API("custom_api", "自定义API"), MINIMAX("minimax", "MiniMax"), XIAOMI("xiaomi", "小米MiMo"); diff --git a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/chat/AbstractChatService.java b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/chat/AbstractChatService.java index 91331c92..7048e2e8 100644 --- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/chat/AbstractChatService.java +++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/chat/AbstractChatService.java @@ -27,7 +27,7 @@ public interface AbstractChatService { /** * 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。 + * 默认实现使用 OpenAI 兼容协议，适用于 OpenAI、DeepSeek、Atlas Cloud 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 diff --git a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/chat/impl/provider/PPIOServiceImpl.java b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/chat/impl/provider/AtlaServiceImpl.java similarity index 90% rename from ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/chat/impl/provider/PPIOServiceImpl.java rename to ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/chat/impl/provider/AtlaServiceImpl.java index b07c21d1..7d4a62f0 100644 --- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/chat/impl/provider/PPIOServiceImpl.java +++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/chat/impl/provider/AtlaServiceImpl.java @@ -15,7 +15,7 @@ import org.springframework.stereotype.Service; import java.util.List; /** - * PPIO服务调用 + * Atlas Cloud服务调用 * * @author ageerle@163.com * @date 2025/12/13 @@ -23,7 +23,7 @@ import java.util.List; @Service @Slf4j @RequiredArgsConstructor -public class PPIOServiceImpl implements AbstractChatService { +public class AtlaServiceImpl implements AbstractChatService { @Override public StreamingChatModel buildStreamingChatModel(ChatModelVo chatModelVo, ChatRequest chatRequest) { @@ -38,7 +38,7 @@ public class PPIOServiceImpl implements AbstractChatService { @Override public String getProviderName() { - return ChatModeType.PPIO.getCode(); + return ChatModeType.ATLAS.getCode(); } } diff --git a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/embed/impl/PPIOEmbeddingProvider.java b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/embed/impl/PPIOEmbeddingProvider.java deleted file mode 100644 index 0c5d335b..00000000 --- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/service/embed/impl/PPIOEmbeddingProvider.java +++ /dev/null @@ -1,14 +0,0 @@ -package org.ruoyi.service.embed.impl; - - -import org.springframework.stereotype.Component; - -/** - * @Author: Robust_H - * @Date: 2025-09-30-下午3:59 - * @Description: 硅基流动（兼容 OpenAi） - */ -@Component("ppio") -public class PPIOEmbeddingProvider extends OpenAiEmbeddingProvider { - -} diff --git a/ruoyi-modules/ruoyi-chat/src/test/java/org/ruoyi/agent/StreamingAgentIntegrationTest.java b/ruoyi-modules/ruoyi-chat/src/test/java/org/ruoyi/agent/StreamingAgentIntegrationTest.java deleted file mode 100644 index 4456affa..00000000 --- a/ruoyi-modules/ruoyi-chat/src/test/java/org/ruoyi/agent/StreamingAgentIntegrationTest.java +++ /dev/null @@ -1,313 +0,0 @@ -package org.ruoyi.agent; - -import dev.langchain4j.agentic.AgenticServices; -import dev.langchain4j.agentic.supervisor.SupervisorAgent; -import dev.langchain4j.agentic.supervisor.SupervisorResponseStrategy; -import dev.langchain4j.model.chat.ChatModel; -import dev.langchain4j.model.chat.StreamingChatModel; -import dev.langchain4j.model.chat.listener.ChatModelErrorContext; -import dev.langchain4j.model.chat.listener.ChatModelListener; -import dev.langchain4j.model.chat.listener.ChatModelRequestContext; -import dev.langchain4j.model.chat.listener.ChatModelResponseContext; -import dev.langchain4j.model.chat.response.ChatResponse; -import dev.langchain4j.model.openai.OpenAiChatModel; -import dev.langchain4j.model.openai.OpenAiStreamingChatModel; -import dev.langchain4j.service.SystemMessage; -import dev.langchain4j.service.UserMessage; -import dev.langchain4j.service.V; -import org.junit.jupiter.api.BeforeEach; -import org.junit.jupiter.api.Disabled; -import org.junit.jupiter.api.DisplayName; -import org.junit.jupiter.api.Test; -import org.ruoyi.observability.OutputChannel; -import org.ruoyi.observability.StreamingOutputWrapper; -import org.ruoyi.observability.SupervisorStreamListener; - -import java.util.List; -import java.util.UUID; -import java.util.concurrent.CompletableFuture; -import java.util.concurrent.CountDownLatch; -import java.util.concurrent.TimeUnit; - -/** - * 子 Agent 流式输出集成测试 - * - * 测试内容： - * 1. 观察单个 Agent 的流式输出 - * 2. 观察 Supervisor 调用子 Agent 的流式输出 - * 3. 验证 AgentListener 事件回调 - * 4. 验证 StreamingOutputWrapper 的 token 拦截 - * - * 注意：运行测试前需要配置正确的 API Key - * 可以通过环境变量或直接修改配置区域 - * - * @author ageerle@163.com - * @date 2025/04/10 - */ -@Disabled("需要配置 API Key 后手动启用") -public class StreamingAgentIntegrationTest { - - // ==================== 配置区域 ==================== - private static final String BASE_URL = "https://api.ppio.com/openai"; - private static final String API_KEY = System.getenv("PPIO_API_KEY") != null - ? System.getenv("PPIO_API_KEY") - : "xx"; // 默认 Key - private static final String MODEL_NAME = "deepseek/deepseek-v3.2"; - - private StreamingChatModel streamingModel; - private OpenAiChatModel syncModel; - - // ==================== Agent 接口定义 ==================== - - public interface MathAgent { - @SystemMessage("你是一个数学计算助手，帮助用户解决数学问题。直接给出计算结果和简要解释。") - @UserMessage("计算：{{query}}") - @dev.langchain4j.agentic.Agent("数学计算助手") - String calculate(@V("query") String query); - } - - public interface TextAgent { - @SystemMessage("你是一个文本分析助手，帮助用户分析文本内容。给出简洁的分析结果。") - @UserMessage("分析以下文本：{{text}}") - @dev.langchain4j.agentic.Agent("文本分析助手") - String analyze(@V("text") String text); - } - - public interface WeatherAgent { - @SystemMessage("你是一个天气助手。根据用户提供的信息给出天气相关的回答。") - @UserMessage("回答问题：{{query}}") - @dev.langchain4j.agentic.Agent("天气助手") - String answer(@V("query") String query); - } - - // ==================== 初始化 ==================== - - @BeforeEach - void setUp() { -// streamingModel = OpenAiStreamingChatModel.builder() -// .baseUrl(BASE_URL) -// .apiKey(API_KEY) -// .modelName(MODEL_NAME) -// .build(); - - streamingModel = OpenAiStreamingChatModel.builder() - .baseUrl(BASE_URL) - .apiKey(API_KEY) - .listeners(List.of(new ChatModelListener() { - @Override - public void onRequest(ChatModelRequestContext ctx) { - // 请求发送前 - } - @Override - public void onResponse(ChatModelResponseContext ctx) { - // 响应完成后 - } - @Override - public void onError(ChatModelErrorContext ctx) { - // 错误时 - } - })) - .build(); - - - syncModel = OpenAiChatModel.builder() - .baseUrl(BASE_URL) - .apiKey(API_KEY) - .modelName(MODEL_NAME) - .build(); - } - - // ==================== 测试方法 ==================== - - @Test - @DisplayName("测试1: 基础流式输出 - 单个 Agent") - void testBasicStreamingAgent() throws Exception { - System.out.println("\n=== 测试1: 基础流式输出 - 单个 Agent ===\n"); - - // 创建事件总线 - String requestId = UUID.randomUUID().toString(); - OutputChannel channel = OutputChannel.create(requestId); - CountDownLatch completed = new CountDownLatch(1); - - // 包装模型以捕获流式输出 - ChatModel wrappedModel = new StreamingOutputWrapper(streamingModel, channel); - - // 构建 Agent - MathAgent mathAgent = AgenticServices.agentBuilder(MathAgent.class) - .chatModel(wrappedModel) - .build(); - - // 异步执行 - CompletableFuture.runAsync(() -> { - try { - System.out.println(">>> 调用 MathAgent.calculate()..."); - String result = mathAgent.calculate("计算 123 * 456 + 789 的值"); - System.out.println("\n>>> 最终结果: " + result); - } catch (Exception e) { - System.err.println(">>> 异常: " + e.getMessage()); - channel.completeWithError(e); - } finally { - channel.complete(); - completed.countDown(); - } - }); - - // drain 推送 - channel.drain(text -> { - System.out.print(text); - System.out.flush(); - }); - - completed.await(30, TimeUnit.SECONDS); - OutputChannel.remove(requestId); - } - - @Test - @DisplayName("测试2: Supervisor 模式 - 单个子 Agent 流式输出") - void testSupervisorWithSingleSubAgent() throws Exception { - System.out.println("\n=== 测试2: Supervisor 模式 - 单个子 Agent ===\n"); - - String requestId = UUID.randomUUID().toString(); - OutputChannel channel = OutputChannel.create(requestId); - CountDownLatch completed = new CountDownLatch(1); - - // 包装模型 - - // 子 Agent - MathAgent mathAgent = AgenticServices.agentBuilder(MathAgent.class) - .streamingChatModel(streamingModel) - .build(); - - - // Supervisor（注册监听器） - SupervisorAgent supervisor = AgenticServices.supervisorBuilder() - .chatModel(syncModel) - //.listener(new SupervisorStreamListener(channel)) - .subAgents(mathAgent) - .responseStrategy(SupervisorResponseStrategy.LAST) - .build(); - - // 异步执行 - CompletableFuture.runAsync(() -> { - try { - System.out.println(">>> Supervisor.invoke() 开始..."); - String result = supervisor.invoke("帮我计算 999 除以 3 等于多少"); - System.out.println("\n>>> Supervisor 结果: " + result); - } catch (Exception e) { - System.err.println(">>> 异常: " + e.getMessage()); - e.printStackTrace(); - // channel.completeWithError(e); - } finally { - // channel.complete(); - completed.countDown(); - } - }); - - // drain 推送 - channel.drain(text -> { - System.out.print(text); - System.out.flush(); - }); - - completed.await(60, TimeUnit.SECONDS); - OutputChannel.remove(requestId); - } - - @Test - @DisplayName("测试3: Supervisor 模式 - 多个子 Agent 流式输出") - void testSupervisorWithMultipleSubAgents() throws Exception { - System.out.println("\n=== 测试3: Supervisor 模式 - 多个子 Agent ===\n"); - - String requestId = UUID.randomUUID().toString(); - OutputChannel channel = OutputChannel.create(requestId); - CountDownLatch completed = new CountDownLatch(1); - - // 包装模型 - ChatModel wrappedModel = new StreamingOutputWrapper(streamingModel, channel); - - - // 子 Agent - MathAgent mathAgent = AgenticServices.agentBuilder(MathAgent.class) - .chatModel(wrappedModel) - .build(); - - TextAgent textAgent = AgenticServices.agentBuilder(TextAgent.class) - .chatModel(wrappedModel) - .build(); - - WeatherAgent weatherAgent = AgenticServices.agentBuilder(WeatherAgent.class) - .chatModel(wrappedModel) - .build(); - - // Supervisor - SupervisorAgent supervisor = AgenticServices.supervisorBuilder() - .chatModel(syncModel) - .listener(new SupervisorStreamListener(channel)) - .subAgents(mathAgent, textAgent, weatherAgent) - .responseStrategy(SupervisorResponseStrategy.LAST) - .build(); - - // 异步执行 - 提一个会触发多个 Agent 的问题 - CompletableFuture.runAsync(() -> { - try { - System.out.println(">>> Supervisor.invoke() 开始..."); - String result = supervisor.invoke( - "请帮我做两件事：1. 计算 50 * 20 的结果；2. 分析 '人工智能正在改变世界' 这句话的含义" - ); - System.out.println("\n>>> Supervisor 结果: " + result); - } catch (Exception e) { - System.err.println(">>> 异常: " + e.getMessage()); - e.printStackTrace(); - channel.completeWithError(e); - } finally { - channel.complete(); - completed.countDown(); - } - }); - - // drain 推送 - 实时观察流式输出 - channel.drain(text -> { - System.out.print("观察流式输出："+text); - System.out.flush(); - }); - - completed.await(90, TimeUnit.SECONDS); - OutputChannel.remove(requestId); - } - - @Test - @DisplayName("测试4: 直接观察 StreamingChatModel 的流式响应") - void testDirectStreamingChatModel() throws Exception { - System.out.println("\n=== 测试4: 直接观察 StreamingChatModel ===\n"); - - StringBuilder buffer = new StringBuilder(); - CountDownLatch completed = new CountDownLatch(1); - - streamingModel.chat("你好，请自我介绍", new dev.langchain4j.model.chat.response.StreamingChatResponseHandler() { - @Override - public void onPartialResponse(String partialResponse) { - buffer.append(partialResponse); - System.out.print(partialResponse); - System.out.flush(); - } - - @Override - public void onCompleteResponse(ChatResponse completeResponse) { - System.out.println("\n\n[完成] 总Token数: " + - (completeResponse.metadata() != null && completeResponse.metadata().tokenUsage() != null - ? completeResponse.metadata().tokenUsage().totalTokenCount() - : "无")); - completed.countDown(); - } - - @Override - public void onError(Throwable error) { - System.err.println("[错误] " + error.getMessage()); - completed.countDown(); - } - }); - - completed.await(30, TimeUnit.SECONDS); - System.out.println("完整响应内容: " + buffer.toString()); - } -}