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v3.0.0
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49
README.md
49
README.md
@@ -21,8 +21,8 @@
|
||||
|
||||
*开箱即用的全栈AI平台，支持多智能体协同、Supervisor模式编排、多种决策模式、RAG技术和流程编排能力*
|
||||
|
||||
**[English](README_EN.md)** | **[📖 使用文档](https://doc.pandarobot.chat)** |
|
||||
**[🚀 在线体验](https://web.pandarobot.chat)** | **[🐛 问题反馈](https://github.com/ageerle/ruoyi-ai/issues)** | **[💡 功能建议](https://github.com/ageerle/ruoyi-ai/issues)**
|
||||
**[English](README_EN.md)** | **[📖 使用文档](https://doc.ruoyiai.chat/)** |
|
||||
**[🚀 在线体验](https://web.ruoyiai.chat/)** | **[🐛 问题反馈](https://github.com/ageerle/ruoyi-ai/issues)** | **[💡 功能建议](https://github.com/ageerle/ruoyi-ai/issues)**
|
||||
|
||||
</div>
|
||||
|
||||
@@ -31,20 +31,12 @@
|
||||
|
||||
| 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
|
||||
| **多智能体** | 基于Langchain4j的Agent框架、Supervisor模式编排,支持多种决策模型
|
||||
|
||||
## 🚀 快速体验
|
||||
|
||||
### 在线演示
|
||||
|
||||
| 平台 | 地址 | 账号 |
|
||||
|:------:|---|---|
|
||||
| 用户端 | [web.pandarobot.chat](https://web.pandarobot.chat) | admin / admin123 |
|
||||
| 管理后台 | [admin.pandarobot.chat](https://admin.pandarobot.chat) | admin / admin123 |
|
||||
|
||||
### 项目源码
|
||||
|
||||
@@ -66,8 +58,6 @@
|
||||
- **数据存储**：MySQL 8.0 + Redis + 向量数据库（Milvus/Weaviate/Qdrant）
|
||||
- **前端技术**：Vue 3 + Vben Admin + element-plus-x
|
||||
- **安全认证**：Sa-Token + JWT 双重保障
|
||||
|
||||
|
||||
- **文档处理**：PDF、Word、Excel 解析，图像智能分析
|
||||
- **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
|
||||
@@ -187,7 +177,7 @@ docker-compose -f docker-compose-all.yaml restart [服务名]
|
||||
|
||||
想要深入了解安装部署、功能配置和二次开发？
|
||||
|
||||
**👉 [完整使用文档](https://doc.pandarobot.chat)**
|
||||
**👉 [完整使用文档](https://doc.ruoyiai.chat/)**
|
||||
|
||||
## 🤝 参与贡献
|
||||
|
||||
@@ -210,17 +200,29 @@ 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：**
|
||||
|
||||
<a href="https://www.atlascloud.ai?ref=89F97E">
|
||||
<img src="docs/image/sponsor/atlascloud_banner.png" alt="Atlas Cloud" width="160" height="80">
|
||||
</a>
|
||||
|
||||
[访问Atlas Cloud官网](https://www.atlascloud.ai?ref=89F97E) · [编程计划优惠](https://www.atlascloud.ai/console/coding-plan)
|
||||
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**。
|
||||
|
||||
<a href="https://www.volcengine.com/activity/codingplan?utm_campaign=hw&utm_content=hw&utm_medium=devrel_tool_web&utm_source=OWO&utm_term=ageerle-ruoyi-ai">
|
||||
<img src="docs/image/sponsor/huoshan.png" alt="火山引擎 CodingPlan" width="160" height="80">
|
||||
</a>
|
||||
|
||||
[火山引擎 CodingPlan 开发者计划](https://www.volcengine.com/activity/codingplan?utm_campaign=hw&utm_content=hw&utm_medium=devrel_tool_web&utm_source=OWO&utm_term=ageerle-ruoyi-ai)
|
||||
火山引擎是字节跳动旗下的云与 AI 服务平台，火山方舟提供豆包大模型、DeepSeek 等多种模型的 API 接入，为开发者提供一站式 AI 开发与推理服务。
|
||||
|
||||
|
||||
## 💬 社区交流
|
||||
|
||||
@@ -234,6 +236,11 @@ docker-compose -f docker-compose-all.yaml restart [服务名]
|
||||
<em>邀请进群学习</em>
|
||||
</td>
|
||||
<td align="center">
|
||||
<img src="docs/image/wx06.png" alt="微信二维码" width="200" height="200"><br>
|
||||
<strong>微信技术交流群</strong><br>
|
||||
<em>技术讨论</em>
|
||||
</td>
|
||||
<td align="center">
|
||||
<img src="docs/image/qq.png" alt="QQ群二维码" width="200" height="200"><br>
|
||||
<strong>QQ技术交流群</strong><br>
|
||||
<em>技术讨论</em>
|
||||
@@ -247,7 +254,7 @@ docker-compose -f docker-compose-all.yaml restart [服务名]
|
||||
---
|
||||
<div align="center">
|
||||
|
||||
**[⭐ 点个Star支持一下](https://github.com/ageerle/ruoyi-ai)** • **[ Fork 开始贡献](https://github.com/ageerle/ruoyi-ai/fork)** • **[📚 English](README_EN.md)** • **[📖 查看完整文档](https://doc.pandarobot.chat)**
|
||||
**[⭐ 点个Star支持一下](https://github.com/ageerle/ruoyi-ai)** • **[ Fork 开始贡献](https://github.com/ageerle/ruoyi-ai/fork)** • **[📚 English](README_EN.md)** • **[📖 查看完整文档](https://doc.ruoyiai.chat/)**
|
||||
|
||||
*用 ❤️ 打造，由 RuoYi AI 开源社区维护*
|
||||
|
||||
|
||||
57
README_EN.md
57
README_EN.md
@@ -22,8 +22,8 @@
|
||||
|
||||
*An out-of-the-box full-stack AI platform supporting multi-agent collaboration, Supervisor mode orchestration, and multiple decision models, with advanced RAG technology and visual workflow orchestration capabilities*
|
||||
|
||||
**[中文](README.md)** | **[📖 Documentation](https://doc.pandarobot.chat)** |
|
||||
**[🚀 Live Demo](https://web.pandarobot.chat)** | **[🐛 Report Issues](https://github.com/ageerle/ruoyi-ai/issues)** | **[💡 Feature Requests](https://github.com/ageerle/ruoyi-ai/issues)**
|
||||
**[中文](README.md)** | **[📖 Documentation](https://doc.ruoyiai.chat/)** |
|
||||
**[🚀 Live Demo](https://web.ruoyiai.chat/)** | **[🐛 Report Issues](https://github.com/ageerle/ruoyi-ai/issues)** | **[💡 Feature Requests](https://github.com/ageerle/ruoyi-ai/issues)**
|
||||
|
||||
</div>
|
||||
|
||||
@@ -34,21 +34,12 @@
|
||||
|
||||
| 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 |
|
||||
| **Multi-Agent** | Agent framework based on Langchain4j, Supervisor mode orchestration, supports multiple decision models |
|
||||
|
||||
## 🚀 Quick Start
|
||||
|
||||
### Live Demo
|
||||
|
||||
| Platform | URL | Account |
|
||||
|:------:|---|---|
|
||||
| User Frontend | [web.pandarobot.chat](https://web.pandarobot.chat) | admin / admin123 |
|
||||
| Admin Panel | [admin.pandarobot.chat](https://admin.pandarobot.chat) | admin / admin123 |
|
||||
|
||||
### Project Repositories
|
||||
|
||||
| Module | GitHub Repository | Gitee Repository | GitCode Repository |
|
||||
@@ -69,8 +60,6 @@
|
||||
- **Data Storage**: MySQL 8.0 + Redis + Vector Databases (Milvus/Weaviate/Qdrant)
|
||||
- **Frontend**: Vue 3 + Vben Admin + element-plus-x
|
||||
- **Security**: Sa-Token + JWT dual-layer security
|
||||
|
||||
|
||||
- **Document Processing**: PDF, Word, Excel parsing, intelligent image analysis
|
||||
- **Real-time Communication**: WebSocket real-time communication, SSE streaming response
|
||||
- **System Monitoring**: Comprehensive logging system, performance monitoring, service health checks
|
||||
@@ -190,7 +179,7 @@ docker-compose -f docker-compose-all.yaml restart [service-name]
|
||||
|
||||
Want to learn more about installation, deployment, configuration, and secondary development?
|
||||
|
||||
**👉 [Complete Documentation](https://doc.pandarobot.chat)**
|
||||
**👉 [Complete Documentation](https://doc.ruoyiai.chat/)**
|
||||
|
||||
## 🤝 Contributing
|
||||
|
||||
@@ -213,23 +202,47 @@ This project is licensed under the **MIT License**. See the [LICENSE](LICENSE) f
|
||||
## 🙏 Acknowledgments
|
||||
|
||||
Thanks to the following excellent open-source projects for their support:
|
||||
- [Spring AI Alibaba Copilot](https://github.com/spring-ai-alibaba/copilot) - Intelligent coding assistant based on spring-ai-alibaba
|
||||
- [Langchain4j](https://github.com/langchain4j/langchain4j) - Powerful Java LLM development framework
|
||||
- [RuoYi-Vue-Plus](https://gitee.com/dromara/RuoYi-Vue-Plus) - Mature enterprise-level rapid development framework
|
||||
- [Vben Admin](https://github.com/vbenjs/vue-vben-admin) - Modern Vue admin template
|
||||
|
||||
## 🌐 Ecosystem Partners
|
||||
## 💎 Sponsors
|
||||
|
||||
- [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.
|
||||
**Thanks to the following sponsors for supporting this project:**
|
||||
|
||||
<a href="https://www.atlascloud.ai?ref=89F97E">
|
||||
<img src="docs/image/sponsor/atlascloud_banner.png" alt="Atlas Cloud" width="160" height="80">
|
||||
</a>
|
||||
|
||||
[Visit Atlas Cloud](https://www.atlascloud.ai?ref=89F97E) · [Coding Plan Promotion](https://www.atlascloud.ai/console/coding-plan)
|
||||
A full-modal AI inference platform that gives developers a unified AI API, supporting video generation, image generation, and LLMs. Connect once to access **300+ curated models**.
|
||||
|
||||
<a href="https://www.volcengine.com/activity/codingplan?utm_campaign=hw&utm_content=hw&utm_medium=devrel_tool_web&utm_source=OWO&utm_term=ageerle-ruoyi-ai">
|
||||
<img src="docs/image/sponsor/huoshan.png" alt="Volcengine CodingPlan" width="160" height="80">
|
||||
</a>
|
||||
|
||||
[Volcengine CodingPlan Developer Program](https://www.volcengine.com/activity/codingplan?utm_campaign=hw&utm_content=hw&utm_medium=devrel_tool_web&utm_source=OWO&utm_term=ageerle-ruoyi-ai)
|
||||
Volcengine is ByteDance's cloud and AI service platform. Volcengine Ark provides API access to Doubao LLM, DeepSeek, and more — a one-stop AI development and inference platform for developers.
|
||||
|
||||
## 💬 Community Chat
|
||||
|
||||
<div align="center">
|
||||
|
||||
**[📱 Join Telegram Group](
|
||||
https://t.me/+LqooQAc5HxRmYmE1)**
|
||||
<table>
|
||||
<tr>
|
||||
<td align="center">
|
||||
<img src="docs/image/wx.png" alt="WeChat QR Code" width="200" height="200"><br>
|
||||
<strong>Scan to add author on WeChat</strong><br>
|
||||
<em>Join group for learning</em>
|
||||
</td>
|
||||
<td align="center">
|
||||
<img src="docs/image/qq.png" alt="QQ Group QR Code" width="200" height="200"><br>
|
||||
<strong>QQ Tech Exchange Group</strong><br>
|
||||
<em>Technical discussion</em>
|
||||
</td>
|
||||
|
||||
</tr>
|
||||
</table>
|
||||
|
||||
</div>
|
||||
|
||||
@@ -237,7 +250,7 @@ https://t.me/+LqooQAc5HxRmYmE1)**
|
||||
|
||||
<div align="center">
|
||||
|
||||
**[⭐ Star to Support](https://github.com/ageerle/ruoyi-ai)** • **[Fork to Contribute](https://github.com/ageerle/ruoyi-ai/fork)** • **[📚 中文](README.md)** • **[📖 Complete Documentation](https://doc.pandarobot.chat)**
|
||||
**[⭐ Star to Support](https://github.com/ageerle/ruoyi-ai)** • **[Fork to Contribute](https://github.com/ageerle/ruoyi-ai/fork)** • **[📚 中文](README.md)** • **[📖 Complete Documentation](https://doc.ruoyiai.chat/)**
|
||||
|
||||
*Built with ❤️, maintained by the RuoYi AI open-source community*
|
||||
|
||||
|
||||
@@ -65,7 +65,7 @@ services:
|
||||
- "28080:8080"
|
||||
environment:
|
||||
QUERY_DEFAULTS_LIMIT: 25
|
||||
AUTHENTICATION_ANONYMOUS_ACCESS_ENABLED: true
|
||||
AUTHENTICATION_ANONYMOUS_ACCESS_ENABLED: "true"
|
||||
PERSISTENCE_DATA_PATH: /var/lib/weaviate
|
||||
DEFAULT_VECTORIZER_MODULE: none
|
||||
ENABLE_MODULES: text2vec-cohere,text2vec-huggingface,text2vec-palm,text2vec-openai,generative-openai,generative-cohere,generative-palm,ref2vec-centroid,reranker-cohere,qna-openai
|
||||
|
||||
BIN
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|
After Width: | Height: | Size: 32 KiB |
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@@ -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
|
||||
@@ -72,8 +70,9 @@ 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` (`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
|
||||
@@ -95,22 +94,25 @@ 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 (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/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, '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);
|
||||
|
||||
-- ----------------------------
|
||||
-- Table structure for chat_session
|
||||
@@ -1086,6 +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;
|
||||
@@ -1110,7 +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;
|
||||
|
||||
-- ----------------------------
|
||||
@@ -1130,6 +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',
|
||||
@@ -1140,6 +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;
|
||||
|
||||
@@ -1169,7 +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
|
||||
@@ -1193,7 +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
|
||||
@@ -1222,7 +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
|
||||
@@ -2080,6 +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
|
||||
@@ -2151,243 +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');
|
||||
INSERT INTO `sys_logininfor` VALUES (2018507142684872705, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'Chrome', 'OSX', '0', '登录成功', '2026-02-03 10:09:40');
|
||||
INSERT INTO `sys_logininfor` VALUES (2018507255759114241, '000000', 'admin', 'web', 'pc', '27.156.68.14', '中国|福建省|福州市|电信', 'Chrome', 'OSX', '0', 'Login successful', '2026-02-03 10:10:06');
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
INSERT INTO `sys_logininfor` VALUES (2018567861803552769, '000000', 'admin', 'web', 'pc', '58.16.14.89', '中国|贵州省|贵阳市|联通', 'Chrome', 'Windows 10 or Windows Server 2016', '0', 'Login successful', '2026-02-03 14:10:56');
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
INSERT INTO `sys_logininfor` VALUES (2018578431793565697, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'Chrome', 'OSX', '0', '登录成功', '2026-02-03 14:52:56');
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
INSERT INTO `sys_logininfor` VALUES (2018588210859479041, '000000', 'admin', 'web', 'pc', '61.169.93.182', '中国|上海|上海市|电信', 'Chrome', 'Windows 10 or Windows Server 2016', '0', 'Login successful', '2026-02-03 15:31:48');
|
||||
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|
||||
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|
||||
INSERT INTO `sys_logininfor` VALUES (2018588841208844289, '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 15:34:18');
|
||||
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|
||||
INSERT INTO `sys_logininfor` VALUES (2018590616590618625, '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 15:41:21');
|
||||
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|
||||
INSERT INTO `sys_logininfor` VALUES (2018594019760803842, '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 15:54:53');
|
||||
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|
||||
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|
||||
INSERT INTO `sys_logininfor` VALUES (2018596170675392513, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-03 16:03:25');
|
||||
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|
||||
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|
||||
INSERT INTO `sys_logininfor` VALUES (2018600606151872513, '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 16:21:03');
|
||||
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|
||||
INSERT INTO `sys_logininfor` VALUES (2018602589315272705, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'Chrome', 'OSX', '0', '登录成功', '2026-02-03 16:28:56');
|
||||
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|
||||
INSERT INTO `sys_logininfor` VALUES (2018609628598898690, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'Chrome', 'OSX', '0', '登录成功', '2026-02-03 16:56:54');
|
||||
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|
||||
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|
||||
INSERT INTO `sys_logininfor` VALUES (2018610284827119618, '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 16:59:31');
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
INSERT INTO `sys_logininfor` VALUES (2018689429430996993, '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 22:14:00');
|
||||
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|
||||
INSERT INTO `sys_logininfor` VALUES (2018694798878314498, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'OSX', '0', '登录成功', '2026-02-03 22:35:20');
|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
INSERT INTO `sys_logininfor` VALUES (2018961841162686465, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-04 16:16:28');
|
||||
INSERT INTO `sys_logininfor` VALUES (2018961976873586689, '000000', 'admin', 'web', 'pc', '36.112.184.220', '中国|北京|北京市|电信', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', 'Login successful', '2026-02-04 16:17:00');
|
||||
INSERT INTO `sys_logininfor` VALUES (2018962175272554497, '000000', 'admin', 'web', 'pc', '39.144.212.209', '中国|移动', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', 'Login successful', '2026-02-04 16:17:48');
|
||||
INSERT INTO `sys_logininfor` VALUES (2018962369447858177, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-04 16:18:34');
|
||||
INSERT INTO `sys_logininfor` VALUES (2018963149303189505, '000000', 'admin', 'web', 'pc', '112.97.202.126', '中国|广东省|东莞市|联通', 'Chrome', 'Windows 10 or Windows Server 2016', '0', 'Login successful', '2026-02-04 16:21:40');
|
||||
INSERT INTO `sys_logininfor` VALUES (2018963440199143425, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'Chrome', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-04 16:22:49');
|
||||
INSERT INTO `sys_logininfor` VALUES (2018966187199827970, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '退出成功', '2026-02-04 16:33:44');
|
||||
INSERT INTO `sys_logininfor` VALUES (2018966195156422657, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-04 16:33:46');
|
||||
INSERT INTO `sys_logininfor` VALUES (2018967272132055041, '000000', 'admin', 'web', 'pc', '121.8.154.218', '中国|广东省|广州市|电信', 'Chrome', 'Windows 10 or Windows Server 2016', '0', 'Login successful', '2026-02-04 16:38:03');
|
||||
INSERT INTO `sys_logininfor` VALUES (2018967970655637505, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'Chrome', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-04 16:40:49');
|
||||
INSERT INTO `sys_logininfor` VALUES (2018968030697099265, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'Chrome', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-04 16:41:04');
|
||||
INSERT INTO `sys_logininfor` VALUES (2018970160656945154, '000000', 'admin', 'web', 'pc', '183.209.146.73', '中国|江苏省|南京市|移动', 'Chrome', 'Windows 10 or Windows Server 2016', '0', 'Login successful', '2026-02-04 16:49:32');
|
||||
INSERT INTO `sys_logininfor` VALUES (2018970873374052354, '000000', 'admin', 'web', 'pc', '60.1.71.196', '中国|河北省|石家庄市|联通', 'Chrome', 'Windows 10 or Windows Server 2016', '0', 'Login successful', '2026-02-04 16:52:22');
|
||||
INSERT INTO `sys_logininfor` VALUES (2018970947504181249, '000000', 'admin', 'web', 'pc', '223.88.78.216', '中国|河南省|郑州市|移动', 'Chrome', 'Windows 10 or Windows Server 2016', '0', 'Login successful', '2026-02-04 16:52:39');
|
||||
INSERT INTO `sys_logininfor` VALUES (2018971098872418305, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'Chrome', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-04 16:53:15');
|
||||
INSERT INTO `sys_logininfor` VALUES (2018978580902580226, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'Chrome', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-04 17:22:59');
|
||||
INSERT INTO `sys_logininfor` VALUES (2018978998839808002, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'Chrome', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-04 17:24:39');
|
||||
INSERT INTO `sys_logininfor` VALUES (2018984098123616257, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-04 17:44:55');
|
||||
INSERT INTO `sys_logininfor` VALUES (2018988627267293186, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'Chrome', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-04 18:02:54');
|
||||
INSERT INTO `sys_logininfor` VALUES (2018990733382520834, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'Chrome', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-04 18:11:17');
|
||||
INSERT INTO `sys_logininfor` VALUES (2019029939576246274, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-04 20:47:04');
|
||||
INSERT INTO `sys_logininfor` VALUES (2019040366678904834, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'Chrome', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-04 21:28:30');
|
||||
INSERT INTO `sys_logininfor` VALUES (2019057692774109186, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'Chrome', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-04 22:37:21');
|
||||
INSERT INTO `sys_logininfor` VALUES (2019057715637260289, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'Chrome', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-04 22:37:26');
|
||||
INSERT INTO `sys_logininfor` VALUES (2019113073072279553, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'OSX', '0', '登录成功', '2026-02-05 02:17:25');
|
||||
INSERT INTO `sys_logininfor` VALUES (2019203832710565889, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-05 08:18:03');
|
||||
INSERT INTO `sys_logininfor` VALUES (2019210865128116226, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'Chrome', 'OSX', '0', '登录成功', '2026-02-05 08:46:00');
|
||||
INSERT INTO `sys_logininfor` VALUES (2019213517912150018, '154726', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-05 08:56:33');
|
||||
INSERT INTO `sys_logininfor` VALUES (2019217038615121921, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-05 09:10:32');
|
||||
INSERT INTO `sys_logininfor` VALUES (2019219134710157314, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Linux', '0', '登录成功', '2026-02-05 09:18:52');
|
||||
INSERT INTO `sys_logininfor` VALUES (2019222079201157121, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-05 09:30:34');
|
||||
INSERT INTO `sys_logininfor` VALUES (2019223047400198146, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'Chrome', 'OSX', '0', '登录成功', '2026-02-05 09:34:25');
|
||||
INSERT INTO `sys_logininfor` VALUES (2019224288503140354, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'Chrome', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-05 09:39:20');
|
||||
INSERT INTO `sys_logininfor` VALUES (2019224998575153153, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '退出成功', '2026-02-05 09:42:10');
|
||||
INSERT INTO `sys_logininfor` VALUES (2019225059417726977, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-05 09:42:24');
|
||||
INSERT INTO `sys_logininfor` VALUES (2019240817392693249, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-05 10:45:01');
|
||||
INSERT INTO `sys_logininfor` VALUES (2019447979716972545, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-06 00:28:13');
|
||||
INSERT INTO `sys_logininfor` VALUES (2026536636865163265, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-25 13:56:00');
|
||||
INSERT INTO `sys_logininfor` VALUES (2026556949535502337, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-25 15:16:43');
|
||||
INSERT INTO `sys_logininfor` VALUES (2026578433112911874, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-25 16:42:05');
|
||||
INSERT INTO `sys_logininfor` VALUES (2026638437400518657, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-25 20:40:31');
|
||||
INSERT INTO `sys_logininfor` VALUES (2026647463072952321, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-25 21:16:23');
|
||||
INSERT INTO `sys_logininfor` VALUES (2026653919016968194, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '退出成功', '2026-02-25 21:42:02');
|
||||
INSERT INTO `sys_logininfor` VALUES (2026654082020204546, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-25 21:42:41');
|
||||
INSERT INTO `sys_logininfor` VALUES (2026654455514587138, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-25 21:44:10');
|
||||
INSERT INTO `sys_logininfor` VALUES (2027260957187186689, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-02-27 13:54:12');
|
||||
INSERT INTO `sys_logininfor` VALUES (2030617171346399233, '000000', 'admin', 'pc', 'pc', '127.0.0.1', '内网IP', 'MSEdge', 'Windows 10 or Windows Server 2016', '0', '登录成功', '2026-03-08 20:10:35');
|
||||
INSERT INTO `sys_logininfor` VALUES (2033083137191841794, '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 15:29:27');
|
||||
INSERT INTO `sys_logininfor` VALUES (2033102367094214657, '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 16:45:52');
|
||||
INSERT INTO `sys_logininfor` VALUES (2033116897354551298, '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 17:43:36');
|
||||
INSERT INTO `sys_logininfor` VALUES (2033133175565836289, '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 18:48:17');
|
||||
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
|
||||
@@ -3171,7 +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);
|
||||
|
||||
|
||||
92
docs/script/sql/update/updat-0419.sql
Normal file
92
docs/script/sql/update/updat-0419.sql
Normal file
@@ -0,0 +1,92 @@
|
||||
/*
|
||||
Navicat Premium Dump SQL
|
||||
|
||||
Source Server : localhost-mysql
|
||||
Source Server Type : MySQL
|
||||
Source Server Version : 80045 (8.0.45)
|
||||
Source Host : localhost:3306
|
||||
Source Schema : ruoyi-ai
|
||||
|
||||
Target Server Type : MySQL
|
||||
Target Server Version : 80045 (8.0.45)
|
||||
File Encoding : 65001
|
||||
|
||||
Date: 19/04/2026 13:36:41
|
||||
*/
|
||||
|
||||
SET NAMES utf8mb4;
|
||||
SET FOREIGN_KEY_CHECKS = 0;
|
||||
|
||||
-- ----------------------------
|
||||
-- Table structure for chat_model
|
||||
-- ----------------------------
|
||||
DROP TABLE IF EXISTS `chat_model`;
|
||||
CREATE TABLE `chat_model` (
|
||||
`id` bigint NOT NULL COMMENT '主键',
|
||||
`category` varchar(20) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '模型分类',
|
||||
`model_name` varchar(50) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '模型名称',
|
||||
`provider_code` varchar(20) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '模型供应商',
|
||||
`model_describe` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '模型描述',
|
||||
`model_dimension` int NULL DEFAULT NULL COMMENT '模型维度',
|
||||
`model_show` char(1) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '是否显示',
|
||||
`api_host` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '请求地址',
|
||||
`api_key` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '密钥',
|
||||
`create_dept` bigint NULL DEFAULT NULL COMMENT '创建部门',
|
||||
`create_by` bigint NULL DEFAULT NULL COMMENT '创建者',
|
||||
`create_time` datetime NULL DEFAULT NULL COMMENT '创建时间',
|
||||
`update_by` bigint NULL DEFAULT NULL COMMENT '更新者',
|
||||
`update_time` datetime NULL DEFAULT NULL COMMENT '更新时间',
|
||||
`remark` varchar(500) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '备注',
|
||||
`tenant_id` bigint NOT NULL DEFAULT 0 COMMENT '租户Id',
|
||||
PRIMARY KEY (`id`) USING BTREE
|
||||
) ENGINE = InnoDB CHARACTER SET = utf8mb4 COLLATE = utf8mb4_0900_ai_ci COMMENT = '模型管理' ROW_FORMAT = DYNAMIC;
|
||||
|
||||
-- ----------------------------
|
||||
-- Records of chat_model
|
||||
-- ----------------------------
|
||||
INSERT INTO `chat_model` VALUES (2000585866022060033, 'chat', 'zai-org/glm-5', 'ppio', 'zai-org/glm-5', NULL, 'Y', 'https://api.ppio.com/openai', 'sk_xx', 103, 1, '2025-12-15 23:16:54', 1, '2026-03-15 19:18:48', 'DeepSeek-V3.2 是一款在高效推理、复杂推理能力与智能体场景中表现突出的领先模型。其基于 DeepSeek Sparse Attention（DSA）稀疏注意力机制，在显著降低计算开销的同时优化长上下文性能；通过可扩展强化学习框架，整体能力达到 GPT-5 同级，高算力版本 V3.2-Speciale 更在推理表现上接近 Gemini-3.0-Pro；同时，模型依托大型智能体任务合成管线，具备更强的工具调用与多步骤决策能力，并在 2025 年 IMO 与 IOI 中取得金牌级表现。作为 MaaS 平台，我们已对 DeepSeek-V3.2 完成深度适配，通过动态调度、批处理加速、低延迟推理与企业级 SLA 保障，进一步增强其在企业生产环境中的稳定性、性价比与可控性，适用于搜索、问答、智能体、代码、数据处理等多类高价值场景。', 0);
|
||||
INSERT INTO `chat_model` VALUES (2007528268536287233, 'vector', 'baai/bge-m3', 'ppio', 'bge-m3', 1024, 'N', 'https://api.ppio.com/openai', 'sk_xx', 103, 1, '2026-01-04 03:03:32', 1, '2026-03-15 19:18:51', 'BGE-M3 是一款具备多维度能力的文本嵌入模型，可同时实现密集检索、多向量检索和稀疏检索三大核心功能。该模型设计上兼容超过100种语言，并支持从短句到长达8192词元的长文本等多种输入形式。在跨语言检索任务中，BGE-M3展现出显著优势，其性能在MIRACL、MKQA等国际基准测试中位居前列。此外，针对长文档检索场景，该模型在MLDR、NarritiveQA等数据集上的表现同样达到行业领先水平。', 0);
|
||||
INSERT INTO `chat_model` VALUES (2045735140488847361, 'chat', 'deepseek-chat', 'custom_api', 'deepseek-chat', NULL, NULL, 'https://api.deepseek.com', 'sk_xx', 103, 1, '2026-04-19 13:24:00', 1, '2026-04-19 13:24:00', 'deepseek对话模型', 0);
|
||||
|
||||
-- ----------------------------
|
||||
-- Table structure for chat_provider
|
||||
-- ----------------------------
|
||||
DROP TABLE IF EXISTS `chat_provider`;
|
||||
CREATE TABLE `chat_provider` (
|
||||
`id` bigint NOT NULL AUTO_INCREMENT COMMENT '主键',
|
||||
`provider_name` varchar(100) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NOT NULL COMMENT '厂商名称',
|
||||
`provider_code` varchar(50) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NOT NULL COMMENT '厂商编码',
|
||||
`provider_icon` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '厂商图标',
|
||||
`provider_desc` varchar(500) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '厂商描述',
|
||||
`api_host` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT 'API地址',
|
||||
`status` char(1) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT '0' COMMENT '状态（0正常 1停用）',
|
||||
`sort_order` int NULL DEFAULT 0 COMMENT '排序',
|
||||
`create_dept` bigint NULL DEFAULT NULL COMMENT '创建部门',
|
||||
`create_time` datetime NULL DEFAULT NULL COMMENT '创建时间',
|
||||
`create_by` varchar(64) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT '' COMMENT '创建者',
|
||||
`update_by` varchar(64) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT '' COMMENT '更新者',
|
||||
`update_time` datetime NULL DEFAULT NULL COMMENT '更新时间',
|
||||
`remark` varchar(500) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '备注',
|
||||
`version` int NULL DEFAULT NULL COMMENT '版本',
|
||||
`del_flag` char(1) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT '0' COMMENT '删除标志',
|
||||
`update_ip` varchar(128) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NULL DEFAULT NULL COMMENT '更新IP',
|
||||
`tenant_id` bigint NOT NULL DEFAULT 0 COMMENT '租户Id',
|
||||
PRIMARY KEY (`id`) USING BTREE,
|
||||
UNIQUE INDEX `unique_provider_code`(`provider_code` ASC, `tenant_id` ASC, `del_flag` ASC) USING BTREE,
|
||||
INDEX `idx_status`(`status` ASC) USING BTREE
|
||||
) ENGINE = InnoDB AUTO_INCREMENT = 2045727230803255298 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_0900_ai_ci COMMENT = '厂商管理表' ROW_FORMAT = DYNAMIC;
|
||||
|
||||
-- ----------------------------
|
||||
-- Records of chat_provider
|
||||
-- ----------------------------
|
||||
INSERT INTO `chat_provider` VALUES (1, 'OpenAI', 'openai', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/01091be272334383a1efd9bc22b73ee6.png', 'OpenAI官方API服务商', 'https://api.openai.com', '0', 1, 103, '2025-12-14 21:48:11', '1', '1', '2026-02-25 20:46:59', 'OpenAI厂商', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (11, '深度求索', 'deepseek', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/04/19/5ba8c30f153246898a4d7dc7b846de8d.png', 'DeepSeek官方API', 'https://api.deepseek.com', '0', 0, 103, '2026-04-19 12:52:34', '1', '1', '2026-04-19 13:13:25', 'DeepSeek官方API', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (12, '智谱AI', 'zhipu', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/04/19/da071783c9284fdd9ed1ce1b57b3c75c.png', '智谱AI大模型服务', 'https://open.bigmodel.cn', '0', 4, 103, '2025-12-14 21:48:11', '1', '1', '2026-04-19 13:14:00', '智谱AI厂商', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (13, '小米MIMO', 'xiaomi', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/04/19/18dd39365ce244e3ae5e030da036760e.png', '小米官方API', 'https://api.xiaomimimo.com/anthropic/v1/messages', '0', 3, 103, '2026-04-19 12:48:24', '1', '1', '2026-04-19 13:14:22', '小米官方API', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (14, '阿里云百炼', 'qianwen', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/de2aa7e649de44f3ba5c6380ac6acd04.png', '阿里云百炼大模型服务', 'https://dashscope.aliyuncs.com', '0', 2, 103, '2025-12-14 21:48:11', '1', '1', '2026-02-25 20:49:13', '阿里云厂商', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (15, 'PPIO', 'ppio', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/049bb6a507174f73bba4b8d8b9e55b8a.png', 'api聚合厂商', 'https://api.ppinfra.com/openai', '0', 5, 103, '2025-12-15 23:13:42', '1', '1', '2026-02-25 20:49:01', 'api聚合厂商', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (16, 'MiniMax', 'minimax', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/04/19/fdc712e90e0e4d78b05862ad230884e5.png', 'MiniMax大模型服务，支持M2.7、M2.5等模型', 'https://api.minimax.io/v1', '0', 6, 103, '2026-04-19 12:50:12', '1', '1', '2026-04-19 13:14:59', 'MiniMax厂商', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (17, 'ollama', 'ollama', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/02/25/afecabebc8014d80b0f06b4796a74c5d.png', 'ollama大模型', 'http://127.0.0.1:11434', '0', 7, 103, '2025-12-14 21:48:11', '1', '1', '2026-02-25 20:48:48', 'ollama厂商', NULL, '0', NULL, 0);
|
||||
INSERT INTO `chat_provider` VALUES (18, '自定义厂商', 'custom_api', 'https://ruoyiai-1254149996.cos.ap-guangzhou.myqcloud.com/2026/04/19/c1a8e122510f4e2f90deb36958af710b.png', 'OPENAI兼容格式', '自定义', '0', 8, 103, '2026-04-19 12:35:57', '1', '1', '2026-04-19 13:17:20', 'OPENAI兼容格式', NULL, '0', NULL, 0);
|
||||
|
||||
SET FOREIGN_KEY_CHECKS = 1;
|
||||
46
docs/script/sql/update/updat-0420.sql
Normal file
46
docs/script/sql/update/updat-0420.sql
Normal file
@@ -0,0 +1,46 @@
|
||||
/*
|
||||
Navicat Premium Dump SQL
|
||||
|
||||
Source Server : localhost-mysql
|
||||
Source Server Type : MySQL
|
||||
Source Server Version : 80045 (8.0.45)
|
||||
Source Host : localhost:3306
|
||||
Source Schema : ruoyi-ai
|
||||
|
||||
Target Server Type : MySQL
|
||||
Target Server Version : 80045 (8.0.45)
|
||||
File Encoding : 65001
|
||||
|
||||
Date: 20/04/2026 15:30:00
|
||||
*/
|
||||
|
||||
SET NAMES utf8mb4;
|
||||
SET FOREIGN_KEY_CHECKS = 0;
|
||||
|
||||
-- ----------------------------
|
||||
-- 新增：重排序模型（chat_model）
|
||||
-- ----------------------------
|
||||
INSERT INTO `chat_model`
|
||||
(id, category, model_name, provider_code, model_describe, model_dimension, model_show, api_host, api_key, create_dept, create_by, create_time, update_by, update_time, remark, tenant_id)
|
||||
VALUES(2045071617578237953, 'rerank', 'rerank', 'zhipu', '智谱重排序', NULL, 'Y', 'https://open.bigmodel.cn', 'e9xx', 103, 1, '2026-04-17 17:27:24', 1, '2026-04-20 15:21:48', '智谱重排序', 0);
|
||||
|
||||
INSERT INTO `chat_model`
|
||||
(id, category, model_name, provider_code, model_describe, model_dimension, model_show, api_host, api_key, create_dept, create_by, create_time, update_by, update_time, remark, tenant_id)
|
||||
VALUES(2046119803482902530, 'rerank', 'qwen3-rerank', 'qianwen', '千问3重排序', NULL, NULL, 'https://dashscope.aliyuncs.com', 'sk-xx', 103, 1, '2026-04-20 14:52:31', 1, '2026-04-20 15:03:13', '千问3文本重排序', 0);
|
||||
|
||||
-- ----------------------------
|
||||
-- 新增：字典类型 - 重排序模型分类
|
||||
-- ----------------------------
|
||||
INSERT INTO `sys_dict_data`
|
||||
(dict_code, tenant_id, dict_sort, dict_label, dict_value, dict_type, css_class, list_class, is_default, create_dept, create_by, create_time, update_by, update_time, remark)
|
||||
VALUES(2045070879435259905, '000000', 4, '重排序', 'rerank', 'chat_model_category', NULL, '#000000', 'N', 103, 1, '2026-04-17 17:24:28', 1, '2026-04-19 01:02:20', '重排序模型');
|
||||
|
||||
-- ----------------------------
|
||||
-- 修改表：knowledge_info 增加重排序相关字段
|
||||
-- ----------------------------
|
||||
ALTER TABLE `knowledge_info` ADD COLUMN `enable_rerank` tinyint DEFAULT 0 NULL COMMENT '是否启用重排序（0否 1是）';
|
||||
ALTER TABLE `knowledge_info` ADD COLUMN `rerank_score_threshold` double NULL COMMENT '重排序相关性分数阈值';
|
||||
ALTER TABLE `knowledge_info` ADD COLUMN `rerank_top_n` int NULL COMMENT '重排序后返回的文档数量';
|
||||
ALTER TABLE `knowledge_info` ADD COLUMN `rerank_model` varchar(100) NULL COMMENT '重排序模型名称';
|
||||
|
||||
SET FOREIGN_KEY_CHECKS = 1;
|
||||
14
docs/script/sql/update/updat-0423.sql
Normal file
14
docs/script/sql/update/updat-0423.sql
Normal file
@@ -0,0 +1,14 @@
|
||||
-- 为知识库信息表新增检索配置字段 (剔除了已存在的重排字段)
|
||||
ALTER TABLE knowledge_info
|
||||
ADD COLUMN similarity_threshold DOUBLE DEFAULT 0.5 COMMENT '相似度阈值'
|
||||
AFTER retrieve_limit;
|
||||
|
||||
ALTER TABLE knowledge_info ADD COLUMN enable_hybrid tinyint(1) DEFAULT 0 COMMENT '是否启用混合检索';
|
||||
ALTER TABLE knowledge_info ADD COLUMN hybrid_alpha double DEFAULT 0.5 COMMENT '混合检索权重比例 (0.0=纯向量, 1.0=纯关键词)';
|
||||
|
||||
-- 为知识片段表增加全文索引及关联ID
|
||||
ALTER TABLE knowledge_fragment ADD COLUMN knowledge_id bigint COMMENT '知识库ID';
|
||||
ALTER TABLE knowledge_fragment ADD FULLTEXT INDEX ft_content (content) WITH PARSER ngram;
|
||||
|
||||
-- 为知识库附件表增加解析状态字段
|
||||
ALTER TABLE `knowledge_attach` ADD COLUMN `status` TINYINT DEFAULT 0 COMMENT '解析状态: 0待解析, 1解析中, 2已解析, 3解析失败';
|
||||
@@ -265,7 +265,7 @@ demo:
|
||||
# 是否开启演示模式（开启后所有写操作将被拦截）
|
||||
enabled: false
|
||||
# 提示消息
|
||||
message: "演示模式，不允许进行写操作"
|
||||
message: "演示模式，不允许操作"
|
||||
# 排除的路径（这些路径不受演示模式限制）
|
||||
excludes:
|
||||
- /login
|
||||
@@ -276,7 +276,9 @@ demo:
|
||||
- /chat/send
|
||||
- /system/session/**
|
||||
- /system/message/**
|
||||
|
||||
- /system/attach/**
|
||||
- /system/fragment/**
|
||||
- /system/info/**
|
||||
--- # warm-flow工作流配置
|
||||
warm-flow:
|
||||
# 是否开启工作流，默认true
|
||||
|
||||
@@ -10,6 +10,7 @@ import org.springframework.boot.context.properties.EnableConfigurationProperties
|
||||
import org.springframework.context.annotation.Bean;
|
||||
import org.springframework.core.task.VirtualThreadTaskExecutor;
|
||||
|
||||
import org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor;
|
||||
import java.util.concurrent.*;
|
||||
|
||||
/**
|
||||
@@ -22,6 +23,12 @@ import java.util.concurrent.*;
|
||||
@EnableConfigurationProperties(ThreadPoolProperties.class)
|
||||
public class ThreadPoolConfig {
|
||||
|
||||
private final ThreadPoolProperties properties;
|
||||
|
||||
public ThreadPoolConfig(ThreadPoolProperties properties) {
|
||||
this.properties = properties;
|
||||
}
|
||||
|
||||
/**
|
||||
* 核心线程数 = cpu 核心数 + 1
|
||||
*/
|
||||
@@ -54,6 +61,22 @@ public class ThreadPoolConfig {
|
||||
return scheduledThreadPoolExecutor;
|
||||
}
|
||||
|
||||
/**
|
||||
* 知识库解析专用异步线程池
|
||||
*/
|
||||
@Bean(name = "knowledgeParseExecutor")
|
||||
public ThreadPoolTaskExecutor knowledgeParseExecutor() {
|
||||
ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor();
|
||||
executor.setCorePoolSize(core);
|
||||
executor.setMaxPoolSize(core * 2);
|
||||
executor.setQueueCapacity(properties.getQueueCapacity());
|
||||
executor.setKeepAliveSeconds(properties.getKeepAliveSeconds());
|
||||
executor.setThreadNamePrefix("knowledge-parse-pool-");
|
||||
executor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy());
|
||||
executor.initialize();
|
||||
return executor;
|
||||
}
|
||||
|
||||
/**
|
||||
* 销毁事件
|
||||
* 停止线程池
|
||||
|
||||
@@ -174,6 +174,23 @@
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
|
||||
<!-- Test dependencies -->
|
||||
<dependency>
|
||||
<groupId>org.junit.jupiter</groupId>
|
||||
<artifactId>junit-jupiter</artifactId>
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.mockito</groupId>
|
||||
<artifactId>mockito-core</artifactId>
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.mockito</groupId>
|
||||
<artifactId>mockito-junit-jupiter</artifactId>
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
|
||||
</dependencies>
|
||||
|
||||
</project>
|
||||
|
||||
@@ -9,6 +9,7 @@ import cn.dev33.satoken.annotation.SaCheckPermission;
|
||||
import org.ruoyi.common.chat.service.chat.IChatModelService;
|
||||
import org.ruoyi.common.chat.domain.bo.chat.ChatModelBo;
|
||||
import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
|
||||
import org.ruoyi.enums.ChatModeType;
|
||||
import org.ruoyi.enums.ModelType;
|
||||
import org.springframework.web.bind.annotation.*;
|
||||
import org.springframework.validation.annotation.Validated;
|
||||
@@ -23,6 +24,8 @@ import org.ruoyi.common.log.enums.BusinessType;
|
||||
import org.ruoyi.common.excel.utils.ExcelUtil;
|
||||
import org.ruoyi.common.mybatis.core.page.TableDataInfo;
|
||||
|
||||
import java.util.LinkedHashMap;
|
||||
|
||||
/**
|
||||
* 模型管理
|
||||
*
|
||||
@@ -55,6 +58,21 @@ public class ChatModelController extends BaseController {
|
||||
return R.ok(chatModelService.queryList(bo));
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取模型供应商枚举
|
||||
*/
|
||||
@GetMapping("/providerOptions")
|
||||
public R<List<LinkedHashMap<String, String>>> providerOptions() {
|
||||
List<LinkedHashMap<String, String>> options = new java.util.ArrayList<>();
|
||||
for (ChatModeType type : ChatModeType.values()) {
|
||||
LinkedHashMap<String, String> item = new LinkedHashMap<>();
|
||||
item.put("label", type.getDescription());
|
||||
item.put("value", type.getCode());
|
||||
options.add(item);
|
||||
}
|
||||
return R.ok(options);
|
||||
}
|
||||
|
||||
/**
|
||||
* 导出模型管理列表
|
||||
*/
|
||||
|
||||
@@ -110,6 +110,17 @@ public class KnowledgeAttachController extends BaseController {
|
||||
@PostMapping(value = "/upload")
|
||||
public R<String> upload(KnowledgeInfoUploadBo bo){
|
||||
knowledgeAttachService.upload(bo);
|
||||
return R.ok("上传知识库附件成功!");
|
||||
return R.ok("上传成功!");
|
||||
}
|
||||
|
||||
/**
|
||||
* 手动解析附件内容
|
||||
*
|
||||
* @param id 附件ID
|
||||
*/
|
||||
@PostMapping("/parse/{id}")
|
||||
public R<Void> parse(@PathVariable Long id) {
|
||||
knowledgeAttachService.parse(id);
|
||||
return R.ok();
|
||||
}
|
||||
}
|
||||
|
||||
@@ -8,6 +8,7 @@ import jakarta.validation.constraints.*;
|
||||
import cn.dev33.satoken.annotation.SaCheckPermission;
|
||||
import org.ruoyi.domain.bo.knowledge.KnowledgeFragmentBo;
|
||||
import org.ruoyi.domain.vo.knowledge.KnowledgeFragmentVo;
|
||||
import org.ruoyi.domain.vo.knowledge.KnowledgeRetrievalVo;
|
||||
import org.ruoyi.service.knowledge.IKnowledgeFragmentService;
|
||||
import org.springframework.web.bind.annotation.*;
|
||||
import org.springframework.validation.annotation.Validated;
|
||||
@@ -102,4 +103,12 @@ public class KnowledgeFragmentController extends BaseController {
|
||||
@PathVariable Long[] ids) {
|
||||
return toAjax(knowledgeFragmentService.deleteWithValidByIds(List.of(ids), true));
|
||||
}
|
||||
|
||||
/**
|
||||
* 检索测试
|
||||
*/
|
||||
@PostMapping("/retrieval")
|
||||
public R<List<KnowledgeRetrievalVo>> retrieval(@RequestBody KnowledgeFragmentBo bo) {
|
||||
return R.ok(knowledgeFragmentService.retrieval(bo));
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,105 +0,0 @@
|
||||
package org.ruoyi.controller.knowledge;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
import lombok.RequiredArgsConstructor;
|
||||
import jakarta.servlet.http.HttpServletResponse;
|
||||
import jakarta.validation.constraints.*;
|
||||
import cn.dev33.satoken.annotation.SaCheckPermission;
|
||||
import org.ruoyi.domain.bo.knowledge.KnowledgeGraphInstanceBo;
|
||||
import org.ruoyi.domain.vo.knowledge.KnowledgeGraphInstanceVo;
|
||||
import org.ruoyi.service.knowledge.IKnowledgeGraphInstanceService;
|
||||
import org.springframework.web.bind.annotation.*;
|
||||
import org.springframework.validation.annotation.Validated;
|
||||
import org.ruoyi.common.idempotent.annotation.RepeatSubmit;
|
||||
import org.ruoyi.common.log.annotation.Log;
|
||||
import org.ruoyi.common.web.core.BaseController;
|
||||
import org.ruoyi.common.mybatis.core.page.PageQuery;
|
||||
import org.ruoyi.common.core.domain.R;
|
||||
import org.ruoyi.common.core.validate.AddGroup;
|
||||
import org.ruoyi.common.core.validate.EditGroup;
|
||||
import org.ruoyi.common.log.enums.BusinessType;
|
||||
import org.ruoyi.common.excel.utils.ExcelUtil;
|
||||
import org.ruoyi.common.mybatis.core.page.TableDataInfo;
|
||||
|
||||
/**
|
||||
* 知识图谱实例
|
||||
*
|
||||
* @author ageerle
|
||||
* @date 2025-12-17
|
||||
*/
|
||||
@Validated
|
||||
@RequiredArgsConstructor
|
||||
@RestController
|
||||
@RequestMapping("/system/graphInstance")
|
||||
public class KnowledgeGraphInstanceController extends BaseController {
|
||||
|
||||
private final IKnowledgeGraphInstanceService knowledgeGraphInstanceService;
|
||||
|
||||
/**
|
||||
* 查询知识图谱实例列表
|
||||
*/
|
||||
@SaCheckPermission("system:graphInstance:list")
|
||||
@GetMapping("/list")
|
||||
public TableDataInfo<KnowledgeGraphInstanceVo> list(KnowledgeGraphInstanceBo bo, PageQuery pageQuery) {
|
||||
return knowledgeGraphInstanceService.queryPageList(bo, pageQuery);
|
||||
}
|
||||
|
||||
/**
|
||||
* 导出知识图谱实例列表
|
||||
*/
|
||||
@SaCheckPermission("system:graphInstance:export")
|
||||
@Log(title = "知识图谱实例", businessType = BusinessType.EXPORT)
|
||||
@PostMapping("/export")
|
||||
public void export(KnowledgeGraphInstanceBo bo, HttpServletResponse response) {
|
||||
List<KnowledgeGraphInstanceVo> list = knowledgeGraphInstanceService.queryList(bo);
|
||||
ExcelUtil.exportExcel(list, "知识图谱实例", KnowledgeGraphInstanceVo.class, response);
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取知识图谱实例详细信息
|
||||
*
|
||||
* @param id 主键
|
||||
*/
|
||||
@SaCheckPermission("system:graphInstance:query")
|
||||
@GetMapping("/{id}")
|
||||
public R<KnowledgeGraphInstanceVo> getInfo(@NotNull(message = "主键不能为空")
|
||||
@PathVariable Long id) {
|
||||
return R.ok(knowledgeGraphInstanceService.queryById(id));
|
||||
}
|
||||
|
||||
/**
|
||||
* 新增知识图谱实例
|
||||
*/
|
||||
@SaCheckPermission("system:graphInstance:add")
|
||||
@Log(title = "知识图谱实例", businessType = BusinessType.INSERT)
|
||||
@RepeatSubmit()
|
||||
@PostMapping()
|
||||
public R<Void> add(@Validated(AddGroup.class) @RequestBody KnowledgeGraphInstanceBo bo) {
|
||||
return toAjax(knowledgeGraphInstanceService.insertByBo(bo));
|
||||
}
|
||||
|
||||
/**
|
||||
* 修改知识图谱实例
|
||||
*/
|
||||
@SaCheckPermission("system:graphInstance:edit")
|
||||
@Log(title = "知识图谱实例", businessType = BusinessType.UPDATE)
|
||||
@RepeatSubmit()
|
||||
@PutMapping()
|
||||
public R<Void> edit(@Validated(EditGroup.class) @RequestBody KnowledgeGraphInstanceBo bo) {
|
||||
return toAjax(knowledgeGraphInstanceService.updateByBo(bo));
|
||||
}
|
||||
|
||||
/**
|
||||
* 删除知识图谱实例
|
||||
*
|
||||
* @param ids 主键串
|
||||
*/
|
||||
@SaCheckPermission("system:graphInstance:remove")
|
||||
@Log(title = "知识图谱实例", businessType = BusinessType.DELETE)
|
||||
@DeleteMapping("/{ids}")
|
||||
public R<Void> remove(@NotEmpty(message = "主键不能为空")
|
||||
@PathVariable Long[] ids) {
|
||||
return toAjax(knowledgeGraphInstanceService.deleteWithValidByIds(List.of(ids), true));
|
||||
}
|
||||
}
|
||||
@@ -1,105 +0,0 @@
|
||||
package org.ruoyi.controller.knowledge;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
import lombok.RequiredArgsConstructor;
|
||||
import jakarta.servlet.http.HttpServletResponse;
|
||||
import jakarta.validation.constraints.*;
|
||||
import cn.dev33.satoken.annotation.SaCheckPermission;
|
||||
import org.ruoyi.domain.bo.knowledge.KnowledgeGraphSegmentBo;
|
||||
import org.ruoyi.domain.vo.knowledge.KnowledgeGraphSegmentVo;
|
||||
import org.ruoyi.service.knowledge.IKnowledgeGraphSegmentService;
|
||||
import org.springframework.web.bind.annotation.*;
|
||||
import org.springframework.validation.annotation.Validated;
|
||||
import org.ruoyi.common.idempotent.annotation.RepeatSubmit;
|
||||
import org.ruoyi.common.log.annotation.Log;
|
||||
import org.ruoyi.common.web.core.BaseController;
|
||||
import org.ruoyi.common.mybatis.core.page.PageQuery;
|
||||
import org.ruoyi.common.core.domain.R;
|
||||
import org.ruoyi.common.core.validate.AddGroup;
|
||||
import org.ruoyi.common.core.validate.EditGroup;
|
||||
import org.ruoyi.common.log.enums.BusinessType;
|
||||
import org.ruoyi.common.excel.utils.ExcelUtil;
|
||||
import org.ruoyi.common.mybatis.core.page.TableDataInfo;
|
||||
|
||||
/**
|
||||
* 知识图谱片段
|
||||
*
|
||||
* @author ageerle
|
||||
* @date 2025-12-17
|
||||
*/
|
||||
@Validated
|
||||
@RequiredArgsConstructor
|
||||
@RestController
|
||||
@RequestMapping("/system/graphSegment")
|
||||
public class KnowledgeGraphSegmentController extends BaseController {
|
||||
|
||||
private final IKnowledgeGraphSegmentService knowledgeGraphSegmentService;
|
||||
|
||||
/**
|
||||
* 查询知识图谱片段列表
|
||||
*/
|
||||
@SaCheckPermission("system:graphSegment:list")
|
||||
@GetMapping("/list")
|
||||
public TableDataInfo<KnowledgeGraphSegmentVo> list(KnowledgeGraphSegmentBo bo, PageQuery pageQuery) {
|
||||
return knowledgeGraphSegmentService.queryPageList(bo, pageQuery);
|
||||
}
|
||||
|
||||
/**
|
||||
* 导出知识图谱片段列表
|
||||
*/
|
||||
@SaCheckPermission("system:graphSegment:export")
|
||||
@Log(title = "知识图谱片段", businessType = BusinessType.EXPORT)
|
||||
@PostMapping("/export")
|
||||
public void export(KnowledgeGraphSegmentBo bo, HttpServletResponse response) {
|
||||
List<KnowledgeGraphSegmentVo> list = knowledgeGraphSegmentService.queryList(bo);
|
||||
ExcelUtil.exportExcel(list, "知识图谱片段", KnowledgeGraphSegmentVo.class, response);
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取知识图谱片段详细信息
|
||||
*
|
||||
* @param id 主键
|
||||
*/
|
||||
@SaCheckPermission("system:graphSegment:query")
|
||||
@GetMapping("/{id}")
|
||||
public R<KnowledgeGraphSegmentVo> getInfo(@NotNull(message = "主键不能为空")
|
||||
@PathVariable Long id) {
|
||||
return R.ok(knowledgeGraphSegmentService.queryById(id));
|
||||
}
|
||||
|
||||
/**
|
||||
* 新增知识图谱片段
|
||||
*/
|
||||
@SaCheckPermission("system:graphSegment:add")
|
||||
@Log(title = "知识图谱片段", businessType = BusinessType.INSERT)
|
||||
@RepeatSubmit()
|
||||
@PostMapping()
|
||||
public R<Void> add(@Validated(AddGroup.class) @RequestBody KnowledgeGraphSegmentBo bo) {
|
||||
return toAjax(knowledgeGraphSegmentService.insertByBo(bo));
|
||||
}
|
||||
|
||||
/**
|
||||
* 修改知识图谱片段
|
||||
*/
|
||||
@SaCheckPermission("system:graphSegment:edit")
|
||||
@Log(title = "知识图谱片段", businessType = BusinessType.UPDATE)
|
||||
@RepeatSubmit()
|
||||
@PutMapping()
|
||||
public R<Void> edit(@Validated(EditGroup.class) @RequestBody KnowledgeGraphSegmentBo bo) {
|
||||
return toAjax(knowledgeGraphSegmentService.updateByBo(bo));
|
||||
}
|
||||
|
||||
/**
|
||||
* 删除知识图谱片段
|
||||
*
|
||||
* @param ids 主键串
|
||||
*/
|
||||
@SaCheckPermission("system:graphSegment:remove")
|
||||
@Log(title = "知识图谱片段", businessType = BusinessType.DELETE)
|
||||
@DeleteMapping("/{ids}")
|
||||
public R<Void> remove(@NotEmpty(message = "主键不能为空")
|
||||
@PathVariable Long[] ids) {
|
||||
return toAjax(knowledgeGraphSegmentService.deleteWithValidByIds(List.of(ids), true));
|
||||
}
|
||||
}
|
||||
@@ -49,5 +49,44 @@ public class KnowledgeFragmentBo extends BaseEntity {
|
||||
*/
|
||||
private String remark;
|
||||
|
||||
/**
|
||||
* 知识库ID
|
||||
*/
|
||||
private Long knowledgeId;
|
||||
|
||||
/**
|
||||
* 检索内容
|
||||
*/
|
||||
private String query;
|
||||
|
||||
/**
|
||||
* 返回条数
|
||||
*/
|
||||
private Integer topK;
|
||||
|
||||
/**
|
||||
* 相似度阈值
|
||||
*/
|
||||
private Double threshold;
|
||||
|
||||
/**
|
||||
* 是否启用重排
|
||||
*/
|
||||
private Boolean enableRerank;
|
||||
|
||||
/**
|
||||
* 重排模型名称
|
||||
*/
|
||||
private String rerankModel;
|
||||
|
||||
/**
|
||||
* 是否启用混合检索
|
||||
*/
|
||||
private Boolean enableHybrid;
|
||||
|
||||
/**
|
||||
* 混合检索权重 (0.0-1.0)
|
||||
*/
|
||||
private Double hybridAlpha;
|
||||
|
||||
}
|
||||
|
||||
@@ -62,6 +62,11 @@ public class KnowledgeInfoBo extends BaseEntity {
|
||||
*/
|
||||
private Long retrieveLimit;
|
||||
|
||||
/**
|
||||
* 相似度阈值
|
||||
*/
|
||||
private Double similarityThreshold;
|
||||
|
||||
/**
|
||||
* 文本块大小
|
||||
*/
|
||||
@@ -77,10 +82,40 @@ public class KnowledgeInfoBo extends BaseEntity {
|
||||
*/
|
||||
private String embeddingModel;
|
||||
|
||||
/**
|
||||
* 是否启用重排序（0 否 1是）
|
||||
*/
|
||||
private Integer enableRerank;
|
||||
|
||||
/**
|
||||
* 重排序模型名称
|
||||
*/
|
||||
private String rerankModel;
|
||||
|
||||
/**
|
||||
* 重排序后返回的文档数量
|
||||
*/
|
||||
private Integer rerankTopN;
|
||||
|
||||
/**
|
||||
* 重排序相关性分数阈值
|
||||
*/
|
||||
private Double rerankScoreThreshold;
|
||||
|
||||
|
||||
/**
|
||||
* 是否启用混合检索（0 否 1是）
|
||||
*/
|
||||
private Integer enableHybrid;
|
||||
|
||||
/**
|
||||
* 混合检索权重 (0.0-1.0)
|
||||
*/
|
||||
private Double hybridAlpha;
|
||||
|
||||
/**
|
||||
* 备注
|
||||
*/
|
||||
private String remark;
|
||||
|
||||
|
||||
}
|
||||
|
||||
@@ -16,6 +16,11 @@ public class KnowledgeInfoUploadBo {
|
||||
|
||||
private MultipartFile file;
|
||||
|
||||
/**
|
||||
* 是否自动解析 (true: 立即解析, false: 仅上传)
|
||||
*/
|
||||
private Boolean autoParse;
|
||||
|
||||
/**
|
||||
* 生效时间, 为空则立即生效
|
||||
*/
|
||||
|
||||
@@ -0,0 +1,44 @@
|
||||
package org.ruoyi.domain.bo.rerank;
|
||||
|
||||
import lombok.AllArgsConstructor;
|
||||
import lombok.Builder;
|
||||
import lombok.Data;
|
||||
import lombok.NoArgsConstructor;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* 重排序请求参数
|
||||
*
|
||||
* @author yang
|
||||
* @date 2026-04-19
|
||||
*/
|
||||
@Data
|
||||
@Builder
|
||||
@NoArgsConstructor
|
||||
@AllArgsConstructor
|
||||
public class RerankRequest {
|
||||
|
||||
/**
|
||||
* 查询文本
|
||||
*/
|
||||
private String query;
|
||||
|
||||
/**
|
||||
* 候选文档列表
|
||||
*/
|
||||
private List<String> documents;
|
||||
|
||||
/**
|
||||
* 返回的文档数量（topN）
|
||||
* 如果不指定，默认返回所有文档
|
||||
*/
|
||||
private Integer topN;
|
||||
|
||||
/**
|
||||
* 是否返回原始文档内容
|
||||
* 默认为 true
|
||||
*/
|
||||
@Builder.Default
|
||||
private Boolean returnDocuments = true;
|
||||
}
|
||||
@@ -0,0 +1,72 @@
|
||||
package org.ruoyi.domain.bo.rerank;
|
||||
|
||||
import lombok.AllArgsConstructor;
|
||||
import lombok.Builder;
|
||||
import lombok.Data;
|
||||
import lombok.NoArgsConstructor;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* 重排序结果
|
||||
*
|
||||
* @author yang
|
||||
* @date 2026-04-19
|
||||
*/
|
||||
@Data
|
||||
@Builder
|
||||
@NoArgsConstructor
|
||||
@AllArgsConstructor
|
||||
public class RerankResult {
|
||||
|
||||
/**
|
||||
* 重排序后的文档结果列表
|
||||
*/
|
||||
private List<RerankDocument> documents;
|
||||
|
||||
/**
|
||||
* 原始请求中的文档总数
|
||||
*/
|
||||
private Integer totalDocuments;
|
||||
|
||||
/**
|
||||
* 重排序耗时（毫秒）
|
||||
*/
|
||||
private Long durationMs;
|
||||
|
||||
/**
|
||||
* 单个重排序文档结果
|
||||
*/
|
||||
@Data
|
||||
@Builder
|
||||
@NoArgsConstructor
|
||||
@AllArgsConstructor
|
||||
public static class RerankDocument {
|
||||
|
||||
/**
|
||||
* 文档在原始列表中的索引位置
|
||||
*/
|
||||
private Integer index;
|
||||
|
||||
/**
|
||||
* 相关性分数（通常 0-1 之间，越高越相关）
|
||||
*/
|
||||
private Double relevanceScore;
|
||||
|
||||
/**
|
||||
* 文档内容
|
||||
*/
|
||||
private String document;
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建空结果
|
||||
*/
|
||||
public static RerankResult empty() {
|
||||
return RerankResult.builder()
|
||||
.documents(List.of())
|
||||
.totalDocuments(0)
|
||||
.durationMs(0L)
|
||||
.build();
|
||||
}
|
||||
}
|
||||
@@ -51,4 +51,48 @@ public class QueryVectorBo {
|
||||
*/
|
||||
private String baseUrl;
|
||||
|
||||
|
||||
// ========== 重排序相关参数 ==========
|
||||
|
||||
/**
|
||||
* 是否启用重排序
|
||||
* 默认为 false
|
||||
*/
|
||||
private Boolean enableRerank = false;
|
||||
|
||||
/**
|
||||
* 重排序模型名称
|
||||
*/
|
||||
private String rerankModelName;
|
||||
|
||||
/**
|
||||
* 重排序后返回的文档数量（topN）
|
||||
* 如果不指定，默认与 maxResults 相同
|
||||
*/
|
||||
private Integer rerankTopN;
|
||||
|
||||
/**
|
||||
* 重排序相关性分数阈值
|
||||
* 低于此阈值的文档将被过滤
|
||||
*/
|
||||
private Double rerankScoreThreshold;
|
||||
|
||||
// ========== 混合检索与阈值相关参数 ==========
|
||||
|
||||
/**
|
||||
* 相似度阈值 (0.0-1.0)
|
||||
* 应用于向量搜索阶段
|
||||
*/
|
||||
private Double similarityThreshold;
|
||||
|
||||
/**
|
||||
* 是否启用混合检索
|
||||
*/
|
||||
private Boolean enableHybrid = false;
|
||||
|
||||
/**
|
||||
* 混合检索权重 (0.0-1.0)
|
||||
*/
|
||||
private Double hybridAlpha;
|
||||
|
||||
}
|
||||
|
||||
@@ -0,0 +1,55 @@
|
||||
package org.ruoyi.domain.dto.request;
|
||||
|
||||
import com.fasterxml.jackson.annotation.JsonInclude;
|
||||
import com.fasterxml.jackson.annotation.JsonProperty;
|
||||
import com.fasterxml.jackson.core.JsonProcessingException;
|
||||
import com.fasterxml.jackson.databind.ObjectMapper;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* 阿里百炼重排序请求DTO（OpenAI兼容格式）
|
||||
*
|
||||
* @author yang
|
||||
* @date 2026-04-20
|
||||
*/
|
||||
@JsonInclude(JsonInclude.Include.NON_NULL)
|
||||
public record AliBaiLianRerankRequest(
|
||||
String model,
|
||||
List<String> documents,
|
||||
String query,
|
||||
@JsonProperty("top_n")
|
||||
Integer topN,
|
||||
String instruct,
|
||||
@JsonProperty("return_documents")
|
||||
Boolean returnDocuments
|
||||
) {
|
||||
private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
|
||||
|
||||
/**
|
||||
* 创建文本重排序请求
|
||||
*/
|
||||
public static AliBaiLianRerankRequest create(String modelName, String query,
|
||||
List<String> documents, Integer topN,
|
||||
Boolean returnDocuments) {
|
||||
return new AliBaiLianRerankRequest(
|
||||
modelName,
|
||||
documents,
|
||||
query,
|
||||
topN != null ? topN : documents.size(),
|
||||
null,
|
||||
returnDocuments != null ? returnDocuments : true
|
||||
);
|
||||
}
|
||||
|
||||
/**
|
||||
* 转换为JSON字符串
|
||||
*/
|
||||
public String toJson() {
|
||||
try {
|
||||
return OBJECT_MAPPER.writeValueAsString(this);
|
||||
} catch (JsonProcessingException e) {
|
||||
throw new IllegalArgumentException("序列化阿里百炼重排序请求失败", e);
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,48 @@
|
||||
package org.ruoyi.domain.dto.request;
|
||||
|
||||
import com.fasterxml.jackson.core.JsonProcessingException;
|
||||
import com.fasterxml.jackson.databind.ObjectMapper;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* 智谱AI重排序请求DTO
|
||||
*
|
||||
* @author yang
|
||||
* @date 2026-04-19
|
||||
*/
|
||||
public record ZhipuRerankRequest(
|
||||
String model,
|
||||
String query,
|
||||
List<String> documents,
|
||||
Integer top_n,
|
||||
Boolean return_documents
|
||||
) {
|
||||
private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
|
||||
|
||||
/**
|
||||
* 创建智谱重排序请求
|
||||
*/
|
||||
public static ZhipuRerankRequest create(String modelName, String query,
|
||||
List<String> documents, Integer topN,
|
||||
Boolean returnDocuments) {
|
||||
return new ZhipuRerankRequest(
|
||||
modelName,
|
||||
query,
|
||||
documents,
|
||||
topN != null ? topN : documents.size(),
|
||||
returnDocuments != null ? returnDocuments : true
|
||||
);
|
||||
}
|
||||
|
||||
/**
|
||||
* 转换为JSON字符串
|
||||
*/
|
||||
public String toJson() {
|
||||
try {
|
||||
return OBJECT_MAPPER.writeValueAsString(this);
|
||||
} catch (JsonProcessingException e) {
|
||||
throw new IllegalArgumentException("序列化智谱重排序请求失败", e);
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,81 @@
|
||||
package org.ruoyi.domain.dto.response;
|
||||
|
||||
import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
|
||||
import com.fasterxml.jackson.annotation.JsonProperty;
|
||||
import org.ruoyi.domain.bo.rerank.RerankResult;
|
||||
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
import java.util.stream.Collectors;
|
||||
|
||||
/**
|
||||
* 阿里百炼重排序响应DTO（OpenAI兼容格式）
|
||||
*
|
||||
* @author yang
|
||||
* @date 2026-04-20
|
||||
*/
|
||||
@JsonIgnoreProperties(ignoreUnknown = true)
|
||||
public record AliBaiLianRerankResponse(
|
||||
String id,
|
||||
String object,
|
||||
List<ResultItem> results,
|
||||
UsageInfo usage
|
||||
) {
|
||||
/**
|
||||
* 单个重排序结果项
|
||||
*/
|
||||
@JsonIgnoreProperties(ignoreUnknown = true)
|
||||
public record ResultItem(
|
||||
Integer index,
|
||||
@JsonProperty("relevance_score")
|
||||
Double relevanceScore,
|
||||
Object document
|
||||
) {
|
||||
/**
|
||||
* 获取文档文本内容
|
||||
*/
|
||||
public String getDocumentText() {
|
||||
if (document == null) return null;
|
||||
if (document instanceof String) return (String) document;
|
||||
if (document instanceof Map) {
|
||||
Object text = ((Map<?, ?>) document).get("text");
|
||||
return text != null ? text.toString() : null;
|
||||
}
|
||||
return document.toString();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Token使用信息
|
||||
*/
|
||||
@JsonIgnoreProperties(ignoreUnknown = true)
|
||||
public record UsageInfo(
|
||||
@JsonProperty("total_tokens")
|
||||
Integer totalTokens,
|
||||
@JsonProperty("prompt_tokens")
|
||||
Integer promptTokens
|
||||
) {}
|
||||
|
||||
/**
|
||||
* 转换为通用RerankResult
|
||||
*/
|
||||
public RerankResult toRerankResult(int totalDocs, long durationMs) {
|
||||
if (results == null || results.isEmpty()) {
|
||||
return RerankResult.empty();
|
||||
}
|
||||
|
||||
List<RerankResult.RerankDocument> documents = results.stream()
|
||||
.map(item -> RerankResult.RerankDocument.builder()
|
||||
.index(item.index())
|
||||
.relevanceScore(item.relevanceScore())
|
||||
.document(item.getDocumentText())
|
||||
.build())
|
||||
.collect(Collectors.toList());
|
||||
|
||||
return RerankResult.builder()
|
||||
.documents(documents)
|
||||
.totalDocuments(totalDocs)
|
||||
.durationMs(durationMs)
|
||||
.build();
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,68 @@
|
||||
package org.ruoyi.domain.dto.response;
|
||||
|
||||
import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
|
||||
import com.fasterxml.jackson.annotation.JsonProperty;
|
||||
import org.ruoyi.domain.bo.rerank.RerankResult;
|
||||
|
||||
import java.util.List;
|
||||
import java.util.stream.Collectors;
|
||||
|
||||
/**
|
||||
* 智谱AI重排序响应DTO
|
||||
*
|
||||
* @author yang
|
||||
* @date 2026-04-19
|
||||
*/
|
||||
@JsonIgnoreProperties(ignoreUnknown = true)
|
||||
public record ZhipuRerankResponse(
|
||||
String model,
|
||||
String object,
|
||||
List<ResultItem> results,
|
||||
UsageInfo usage
|
||||
) {
|
||||
/**
|
||||
* 单个重排序结果项
|
||||
*/
|
||||
public record ResultItem(
|
||||
Integer index,
|
||||
@JsonProperty("relevance_score")
|
||||
Double relevanceScore,
|
||||
String document
|
||||
) {}
|
||||
|
||||
/**
|
||||
* Token使用信息
|
||||
*/
|
||||
@JsonIgnoreProperties(ignoreUnknown = true)
|
||||
public record UsageInfo(
|
||||
@JsonProperty("total_tokens")
|
||||
Integer totalTokens,
|
||||
@JsonProperty("input_tokens")
|
||||
Integer inputTokens,
|
||||
@JsonProperty("output_tokens")
|
||||
Integer outputTokens
|
||||
) {}
|
||||
|
||||
/**
|
||||
* 转换为通用RerankResult
|
||||
*/
|
||||
public RerankResult toRerankResult(int totalDocs, long durationMs) {
|
||||
if (results == null || results.isEmpty()) {
|
||||
return RerankResult.empty();
|
||||
}
|
||||
|
||||
List<RerankResult.RerankDocument> documents = results.stream()
|
||||
.map(item -> RerankResult.RerankDocument.builder()
|
||||
.index(item.index())
|
||||
.relevanceScore(item.relevanceScore())
|
||||
.document(item.document())
|
||||
.build())
|
||||
.collect(Collectors.toList());
|
||||
|
||||
return RerankResult.builder()
|
||||
.documents(documents)
|
||||
.totalDocuments(totalDocs)
|
||||
.durationMs(durationMs)
|
||||
.build();
|
||||
}
|
||||
}
|
||||
@@ -57,5 +57,10 @@ public class KnowledgeAttach extends BaseEntity {
|
||||
*/
|
||||
private String remark;
|
||||
|
||||
/**
|
||||
* 解析状态: 0待解析, 1解析中, 2已解析, 3解析失败
|
||||
*/
|
||||
private Integer status;
|
||||
|
||||
|
||||
}
|
||||
|
||||
@@ -47,5 +47,10 @@ public class KnowledgeFragment extends BaseEntity {
|
||||
*/
|
||||
private String remark;
|
||||
|
||||
/**
|
||||
* 知识库ID
|
||||
*/
|
||||
private Long knowledgeId;
|
||||
|
||||
|
||||
}
|
||||
|
||||
@@ -63,6 +63,11 @@ public class KnowledgeInfo extends BaseEntity {
|
||||
*/
|
||||
private Long retrieveLimit;
|
||||
|
||||
/**
|
||||
* 相似度阈值
|
||||
*/
|
||||
private Double similarityThreshold;
|
||||
|
||||
/**
|
||||
* 文本块大小
|
||||
*/
|
||||
@@ -78,6 +83,36 @@ public class KnowledgeInfo extends BaseEntity {
|
||||
*/
|
||||
private String embeddingModel;
|
||||
|
||||
/**
|
||||
* 是否启用重排序（0 否 1是）
|
||||
*/
|
||||
private Integer enableRerank;
|
||||
|
||||
/**
|
||||
* 重排序模型名称
|
||||
*/
|
||||
private String rerankModel;
|
||||
|
||||
/**
|
||||
* 重排序后返回的文档数量
|
||||
*/
|
||||
private Integer rerankTopN;
|
||||
|
||||
/**
|
||||
* 重排序相关性分数阈值
|
||||
*/
|
||||
private Double rerankScoreThreshold;
|
||||
|
||||
/**
|
||||
* 是否启用混合检索（0 否 1是）
|
||||
*/
|
||||
private Integer enableHybrid;
|
||||
|
||||
/**
|
||||
* 混合检索权重 (0.0-1.0)
|
||||
*/
|
||||
private Double hybridAlpha;
|
||||
|
||||
/**
|
||||
* 备注
|
||||
*/
|
||||
|
||||
@@ -0,0 +1,20 @@
|
||||
package org.ruoyi.domain.vo.knowledge;
|
||||
|
||||
import lombok.Data;
|
||||
|
||||
/**
|
||||
* 文档分块数统计 VO（用于 GROUP BY 查询结果接收）
|
||||
*/
|
||||
@Data
|
||||
public class DocFragmentCountVo {
|
||||
|
||||
/**
|
||||
* 文档ID（关联 knowledge_attach.doc_id）
|
||||
*/
|
||||
private String docId;
|
||||
|
||||
/**
|
||||
* 该文档下的分块数量
|
||||
*/
|
||||
private Integer fragmentCount;
|
||||
}
|
||||
@@ -8,6 +8,7 @@ import org.ruoyi.domain.entity.knowledge.KnowledgeAttach;
|
||||
|
||||
import java.io.Serial;
|
||||
import java.io.Serializable;
|
||||
import java.util.Date;
|
||||
|
||||
|
||||
|
||||
@@ -68,5 +69,22 @@ public class KnowledgeAttachVo implements Serializable {
|
||||
@ExcelProperty(value = "备注")
|
||||
private String remark;
|
||||
|
||||
/**
|
||||
* 上传时间（来自 BaseEntity.createTime）
|
||||
*/
|
||||
@ExcelProperty(value = "上传时间")
|
||||
private Date createTime;
|
||||
|
||||
/**
|
||||
* 解析状态: 0待解析, 1解析中, 2已解析, 3解析失败
|
||||
*/
|
||||
@ExcelProperty(value = "解析状态")
|
||||
private Integer status;
|
||||
|
||||
/**
|
||||
* 分块数（统计字段，非数据库列）
|
||||
*/
|
||||
private Integer fragmentCount;
|
||||
|
||||
|
||||
}
|
||||
|
||||
@@ -39,7 +39,7 @@ public class KnowledgeFragmentVo implements Serializable {
|
||||
* 片段索引下标
|
||||
*/
|
||||
@ExcelProperty(value = "片段索引下标")
|
||||
private Long idx;
|
||||
private Integer idx;
|
||||
|
||||
/**
|
||||
* 文档内容
|
||||
@@ -53,5 +53,10 @@ public class KnowledgeFragmentVo implements Serializable {
|
||||
@ExcelProperty(value = "备注")
|
||||
private String remark;
|
||||
|
||||
/**
|
||||
* 知识库ID
|
||||
*/
|
||||
private Long knowledgeId;
|
||||
|
||||
|
||||
}
|
||||
|
||||
@@ -76,6 +76,12 @@ public class KnowledgeInfoVo implements Serializable {
|
||||
@ExcelProperty(value = "知识库中检索的条数")
|
||||
private Integer retrieveLimit;
|
||||
|
||||
/**
|
||||
* 相似度阈值
|
||||
*/
|
||||
@ExcelProperty(value = "相似度阈值")
|
||||
private Double similarityThreshold;
|
||||
|
||||
/**
|
||||
* 文本块大小
|
||||
*/
|
||||
@@ -94,6 +100,48 @@ public class KnowledgeInfoVo implements Serializable {
|
||||
@ExcelProperty(value = "向量模型")
|
||||
private String embeddingModel;
|
||||
|
||||
/**
|
||||
* 是否启用重排序（0 否 1是）
|
||||
*/
|
||||
@ExcelProperty(value = "是否启用重排序")
|
||||
private Integer enableRerank;
|
||||
|
||||
/**
|
||||
* 重排序模型名称
|
||||
*/
|
||||
@ExcelProperty(value = "重排序模型")
|
||||
private String rerankModel;
|
||||
|
||||
/**
|
||||
* 重排序后返回的文档数量
|
||||
*/
|
||||
@ExcelProperty(value = "重排序返回数量")
|
||||
private Integer rerankTopN;
|
||||
|
||||
/**
|
||||
* 重排序相关性分数阈值
|
||||
*/
|
||||
@ExcelProperty(value = "重排序分数阈值")
|
||||
private Double rerankScoreThreshold;
|
||||
|
||||
/**
|
||||
* 是否启用混合检索（0 否 1是）
|
||||
*/
|
||||
@ExcelProperty(value = "是否启用混合检索")
|
||||
private Integer enableHybrid;
|
||||
|
||||
/**
|
||||
* 混合检索权重 (0.0-1.0)
|
||||
*/
|
||||
@ExcelProperty(value = "混合检索权重")
|
||||
private Double hybridAlpha;
|
||||
|
||||
/**
|
||||
* 文档数量
|
||||
*/
|
||||
@ExcelProperty(value = "文档数量")
|
||||
private Integer documentCount;
|
||||
|
||||
/**
|
||||
* 备注
|
||||
*/
|
||||
|
||||
@@ -0,0 +1,69 @@
|
||||
package org.ruoyi.domain.vo.knowledge;
|
||||
|
||||
import lombok.AllArgsConstructor;
|
||||
import lombok.Builder;
|
||||
import lombok.Data;
|
||||
import lombok.NoArgsConstructor;
|
||||
|
||||
import java.io.Serial;
|
||||
import java.io.Serializable;
|
||||
|
||||
/**
|
||||
* 知识检索测试结果视图对象
|
||||
*
|
||||
* @author RobustH
|
||||
*/
|
||||
@Data
|
||||
@Builder
|
||||
@NoArgsConstructor
|
||||
@AllArgsConstructor
|
||||
public class KnowledgeRetrievalVo implements Serializable {
|
||||
|
||||
@Serial
|
||||
private static final long serialVersionUID = 1L;
|
||||
|
||||
/**
|
||||
* 片段ID
|
||||
*/
|
||||
private String id;
|
||||
|
||||
/**
|
||||
* 文档ID
|
||||
*/
|
||||
private String docId;
|
||||
|
||||
/**
|
||||
* 知识库ID
|
||||
*/
|
||||
private Long knowledgeId;
|
||||
|
||||
/**
|
||||
* 分片索引
|
||||
*/
|
||||
private Integer idx;
|
||||
|
||||
/**
|
||||
* 片段内容
|
||||
*/
|
||||
private String content;
|
||||
|
||||
/**
|
||||
* 相似度得分
|
||||
*/
|
||||
private Double score;
|
||||
|
||||
/**
|
||||
* 原始检索排名 (重排前)
|
||||
*/
|
||||
private Integer originalIndex;
|
||||
|
||||
/**
|
||||
* 原始检索得分 (重排前)
|
||||
*/
|
||||
private Double rawScore;
|
||||
|
||||
/**
|
||||
* 来源文档名称
|
||||
*/
|
||||
private String sourceName;
|
||||
}
|
||||
@@ -15,7 +15,10 @@ public enum ChatModeType {
|
||||
DEEP_SEEK("deepseek", "深度求索"),
|
||||
QIAN_WEN("qianwen", "通义千问"),
|
||||
OPEN_AI("openai", "openai"),
|
||||
PPIO("ppio", "ppio");
|
||||
ATLAS("atlas", "Atlas Cloud"),
|
||||
CUSTOM_API("custom_api", "自定义API"),
|
||||
MINIMAX("minimax", "MiniMax"),
|
||||
XIAOMI("xiaomi", "小米MiMo");
|
||||
private final String code;
|
||||
private final String description;
|
||||
|
||||
|
||||
@@ -0,0 +1,38 @@
|
||||
package org.ruoyi.enums;
|
||||
|
||||
import lombok.AllArgsConstructor;
|
||||
import lombok.Getter;
|
||||
|
||||
/**
|
||||
* 知识库附件解析状态枚举
|
||||
*
|
||||
* @author RobustH
|
||||
*/
|
||||
@Getter
|
||||
@AllArgsConstructor
|
||||
public enum KnowledgeAttachStatus {
|
||||
|
||||
/**
|
||||
* 待解析
|
||||
*/
|
||||
WAITING(0, "待解析"),
|
||||
|
||||
/**
|
||||
* 解析中
|
||||
*/
|
||||
PARSING(1, "解析中"),
|
||||
|
||||
/**
|
||||
* 已解析
|
||||
*/
|
||||
COMPLETED(2, "已解析"),
|
||||
|
||||
/**
|
||||
* 解析失败
|
||||
*/
|
||||
FAILED(3, "解析失败");
|
||||
|
||||
private final Integer code;
|
||||
private final String info;
|
||||
|
||||
}
|
||||
@@ -0,0 +1,106 @@
|
||||
package org.ruoyi.factory;
|
||||
|
||||
import lombok.RequiredArgsConstructor;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
|
||||
import org.ruoyi.common.chat.service.chat.IChatModelService;
|
||||
import org.ruoyi.service.rerank.RerankModelService;
|
||||
import org.springframework.beans.factory.NoSuchBeanDefinitionException;
|
||||
import org.springframework.context.ApplicationContext;
|
||||
import org.springframework.stereotype.Service;
|
||||
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
import java.util.concurrent.ConcurrentHashMap;
|
||||
|
||||
/**
|
||||
* 重排序模型工厂服务类
|
||||
* 参考设计模式：EmbeddingModelFactory
|
||||
* 负责创建和管理重排序模型实例
|
||||
*
|
||||
* @author yang
|
||||
* @date 2026-04-19
|
||||
*/
|
||||
@Service
|
||||
@RequiredArgsConstructor
|
||||
@Slf4j
|
||||
public class RerankModelFactory {
|
||||
|
||||
private final ApplicationContext applicationContext;
|
||||
|
||||
private final IChatModelService chatModelService;
|
||||
|
||||
/**
|
||||
* 模型缓存，使用ConcurrentHashMap保证线程安全
|
||||
*/
|
||||
private final Map<String, RerankModelService> modelCache = new ConcurrentHashMap<>();
|
||||
|
||||
/**
|
||||
* 创建重排序模型实例
|
||||
* 如果模型已存在于缓存中，则直接返回；否则创建新的实例
|
||||
*
|
||||
* @param rerankModelName 重排序模型名称
|
||||
*/
|
||||
public RerankModelService createModel(String rerankModelName) {
|
||||
return modelCache.computeIfAbsent(rerankModelName, name -> {
|
||||
ChatModelVo modelConfig = chatModelService.selectModelByName(rerankModelName);
|
||||
|
||||
if (modelConfig == null) {
|
||||
throw new IllegalArgumentException("未找到重排序模型配置，name=" + name);
|
||||
}
|
||||
return createModelInstance(modelConfig.getProviderCode(), modelConfig);
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* 刷新模型缓存
|
||||
* 根据给定的模型ID从缓存中移除对应的模型
|
||||
*
|
||||
* @param modelId 模型的唯一标识ID
|
||||
*/
|
||||
public void refreshModel(Long modelId) {
|
||||
modelCache.remove(modelId);
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取所有支持模型工厂的列表
|
||||
*
|
||||
* @return 支持的模型工厂名称列表
|
||||
*/
|
||||
public List<String> getSupportedFactories() {
|
||||
return new ArrayList<>(applicationContext.getBeansOfType(RerankModelService.class)
|
||||
.keySet());
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建具体的模型实例
|
||||
* 根据提供的工厂名称和配置信息创建并配置模型实例
|
||||
*
|
||||
* @param factory 工厂名称，用于标识模型类型（providerCode）
|
||||
* @param config 模型配置信息
|
||||
* @return RerankModelService 配置好的模型实例
|
||||
* @throws IllegalArgumentException 当无法获取指定的模型实例时抛出
|
||||
*/
|
||||
private RerankModelService createModelInstance(String factory, ChatModelVo config) {
|
||||
try {
|
||||
// 优先尝试使用 providerCode + "Rerank" 作为 Bean 名称
|
||||
// 例如：zhipu -> zhipuRerank，jina -> jinaRerank
|
||||
String rerankBeanName = factory + "Rerank";
|
||||
RerankModelService model = applicationContext.getBean(rerankBeanName, RerankModelService.class);
|
||||
model.configure(config);
|
||||
log.info("成功创建重排序模型: factory={}, modelName={}", rerankBeanName, config.getModelName());
|
||||
return model;
|
||||
} catch (NoSuchBeanDefinitionException e) {
|
||||
// 如果找不到，尝试使用原始的 providerCode
|
||||
try {
|
||||
RerankModelService model = applicationContext.getBean(factory, RerankModelService.class);
|
||||
model.configure(config);
|
||||
log.info("成功创建重排序模型: factory={}, modelName={}", factory, config.getModelName());
|
||||
return model;
|
||||
} catch (NoSuchBeanDefinitionException ex) {
|
||||
throw new IllegalArgumentException("获取不到重排序模型: " + factory + " 或 " + factory + "Rerank", ex);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -1,5 +1,8 @@
|
||||
package org.ruoyi.mapper.knowledge;
|
||||
|
||||
import org.apache.ibatis.annotations.Mapper;
|
||||
import org.apache.ibatis.annotations.Param;
|
||||
import org.apache.ibatis.annotations.Select;
|
||||
import org.ruoyi.domain.entity.knowledge.KnowledgeAttach;
|
||||
import org.ruoyi.domain.vo.knowledge.KnowledgeAttachVo;
|
||||
import org.ruoyi.common.mybatis.core.mapper.BaseMapperPlus;
|
||||
@@ -10,6 +13,12 @@ import org.ruoyi.common.mybatis.core.mapper.BaseMapperPlus;
|
||||
* @author ageerle
|
||||
* @date 2025-12-17
|
||||
*/
|
||||
@Mapper
|
||||
public interface KnowledgeAttachMapper extends BaseMapperPlus<KnowledgeAttach, KnowledgeAttachVo> {
|
||||
|
||||
/**
|
||||
* 统计指定知识库下的文档数量
|
||||
*/
|
||||
@Select("SELECT COUNT(*) FROM knowledge_attach WHERE knowledge_id = #{knowledgeId}")
|
||||
int countByKnowledgeId(@Param("knowledgeId") Long knowledgeId);
|
||||
}
|
||||
|
||||
@@ -1,15 +1,45 @@
|
||||
package org.ruoyi.mapper.knowledge;
|
||||
|
||||
import org.apache.ibatis.annotations.Mapper;
|
||||
import org.apache.ibatis.annotations.Param;
|
||||
import org.apache.ibatis.annotations.Select;
|
||||
import org.ruoyi.domain.entity.knowledge.KnowledgeFragment;
|
||||
import org.ruoyi.domain.vo.knowledge.DocFragmentCountVo;
|
||||
import org.ruoyi.domain.vo.knowledge.KnowledgeFragmentVo;
|
||||
import org.ruoyi.common.mybatis.core.mapper.BaseMapperPlus;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* 知识片段Mapper接口
|
||||
*
|
||||
* @author ageerle
|
||||
* @date 2025-12-17
|
||||
*/
|
||||
@Mapper
|
||||
public interface KnowledgeFragmentMapper extends BaseMapperPlus<KnowledgeFragment, KnowledgeFragmentVo> {
|
||||
|
||||
/**
|
||||
* 批量统计各文档的分块数（强类型接收，避免 Map key 大小写问题）
|
||||
*
|
||||
* @param docIds 文档 ID 列表
|
||||
* @return 每个 docId 对应的分块数列表
|
||||
*/
|
||||
@Select("<script>" +
|
||||
"SELECT doc_id AS docId, COUNT(*) AS fragmentCount " +
|
||||
"FROM knowledge_fragment " +
|
||||
"WHERE doc_id IN " +
|
||||
"<foreach collection='docIds' item='id' open='(' separator=',' close=')'>#{id}</foreach> " +
|
||||
"GROUP BY doc_id" +
|
||||
"</script>")
|
||||
List<DocFragmentCountVo> selectFragmentCountByDocIds(@Param("docIds") List<String> docIds);
|
||||
@Select("<script>" +
|
||||
"SELECT id, doc_id AS docId, content, idx, knowledge_id AS knowledgeId " +
|
||||
"FROM knowledge_fragment " +
|
||||
"WHERE knowledge_id = #{knowledgeId} " +
|
||||
"AND MATCH (content) AGAINST (#{query} IN NATURAL LANGUAGE MODE) " +
|
||||
"ORDER BY MATCH (content) AGAINST (#{query} IN NATURAL LANGUAGE MODE) DESC " +
|
||||
"LIMIT #{limit}" +
|
||||
"</script>")
|
||||
List<KnowledgeFragmentVo> searchByKeyword(@Param("knowledgeId") Long knowledgeId, @Param("query") String query, @Param("limit") Integer limit);
|
||||
}
|
||||
|
||||
@@ -1,9 +1,13 @@
|
||||
package org.ruoyi.service.chat;
|
||||
|
||||
import dev.langchain4j.model.chat.ChatModel;
|
||||
import dev.langchain4j.model.chat.StreamingChatModel;
|
||||
import dev.langchain4j.model.openai.OpenAiChatModel;
|
||||
import org.ruoyi.common.chat.domain.dto.request.ChatRequest;
|
||||
import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
|
||||
|
||||
import java.time.Duration;
|
||||
|
||||
/**
|
||||
* 聊天消息Service接口
|
||||
*
|
||||
@@ -21,6 +25,23 @@ public interface AbstractChatService {
|
||||
*/
|
||||
StreamingChatModel buildStreamingChatModel(ChatModelVo chatModelVo, ChatRequest chatRequest);
|
||||
|
||||
/**
|
||||
* 创建同步聊天模型（供 Agent/SupervisorAgent 使用）
|
||||
* 默认实现使用 OpenAI 兼容协议，适用于 OpenAI、DeepSeek、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
|
||||
* @return 同步聊天模型实例
|
||||
*/
|
||||
default ChatModel buildChatModel(ChatModelVo chatModelVo) {
|
||||
return OpenAiChatModel.builder()
|
||||
.baseUrl(chatModelVo.getApiHost())
|
||||
.apiKey(chatModelVo.getApiKey())
|
||||
.modelName(chatModelVo.getModelName())
|
||||
.timeout(Duration.ofSeconds(120))
|
||||
.build();
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取服务提供商名称
|
||||
*/
|
||||
|
||||
@@ -20,6 +20,11 @@ import dev.langchain4j.model.chat.response.StreamingChatResponseHandler;
|
||||
import dev.langchain4j.model.openai.OpenAiChatModel;
|
||||
import dev.langchain4j.service.tool.ToolProvider;
|
||||
import dev.langchain4j.skills.shell.ShellSkills;
|
||||
import dev.langchain4j.rag.AugmentationRequest;
|
||||
import dev.langchain4j.rag.AugmentationResult;
|
||||
import dev.langchain4j.rag.DefaultRetrievalAugmentor;
|
||||
import dev.langchain4j.rag.RetrievalAugmentor;
|
||||
import dev.langchain4j.rag.query.Metadata;
|
||||
import lombok.RequiredArgsConstructor;
|
||||
import lombok.SneakyThrows;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
@@ -54,6 +59,8 @@ import org.ruoyi.service.chat.AbstractChatService;
|
||||
import org.ruoyi.service.chat.IChatMessageService;
|
||||
import org.ruoyi.service.chat.impl.memory.PersistentChatMemoryStore;
|
||||
import org.ruoyi.service.knowledge.IKnowledgeInfoService;
|
||||
import org.ruoyi.service.retrieval.KnowledgeRetrievalService;
|
||||
import org.ruoyi.service.knowledge.retriever.CustomVectorRetriever;
|
||||
import org.ruoyi.service.vector.VectorStoreService;
|
||||
import org.springframework.stereotype.Service;
|
||||
import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;
|
||||
@@ -89,6 +96,8 @@ public class ChatServiceFacade implements IChatService {
|
||||
|
||||
private final VectorStoreService vectorStoreService;
|
||||
|
||||
private final KnowledgeRetrievalService knowledgeRetrievalService;
|
||||
|
||||
private final SseEmitterManager sseEmitterManager;
|
||||
|
||||
private final IChatMessageService chatMessageService;
|
||||
@@ -409,7 +418,6 @@ public class ChatServiceFacade implements IChatService {
|
||||
|
||||
/**
|
||||
* 构建上下文消息列表
|
||||
|
||||
* 消息顺序：历史消息 → 当前用户消息（确保 AI 正确理解对话上下文）
|
||||
*
|
||||
* @param chatRequest 聊天请求
|
||||
@@ -418,7 +426,41 @@ public class ChatServiceFacade implements IChatService {
|
||||
private List<ChatMessage> buildContextMessages(ChatRequest chatRequest) {
|
||||
List<ChatMessage> messages = new ArrayList<>();
|
||||
|
||||
// 从数据库查询历史对话消息（放在前面）
|
||||
// 1. 初始化当前用户消息
|
||||
UserMessage userMessage = UserMessage.userMessage(chatRequest.getContent());
|
||||
|
||||
// 2. 知识库检索增强 (RAG)
|
||||
if (chatRequest.getKnowledgeId() != null) {
|
||||
KnowledgeInfoVo knowledgeInfoVo = knowledgeInfoService.queryById(Long.valueOf(chatRequest.getKnowledgeId()));
|
||||
if (knowledgeInfoVo != null) {
|
||||
ChatModelVo chatModel = chatModelService.selectModelByName(knowledgeInfoVo.getEmbeddingModel());
|
||||
if (chatModel != null) {
|
||||
log.info("执行高级 RAG 流程: kid={}", chatRequest.getKnowledgeId());
|
||||
|
||||
// 构建自定义检索器
|
||||
CustomVectorRetriever retriever = new CustomVectorRetriever(
|
||||
knowledgeRetrievalService, knowledgeInfoVo, chatModel);
|
||||
|
||||
// 构建增强流水线
|
||||
RetrievalAugmentor augmentor = DefaultRetrievalAugmentor.builder()
|
||||
.contentRetriever(retriever)
|
||||
.build();
|
||||
|
||||
// 执行增强：编织上下文到 UserMessage
|
||||
Metadata metadata = Metadata.from(userMessage, chatRequest.getSessionId(), new ArrayList<>());
|
||||
AugmentationRequest augmentationRequest = new AugmentationRequest(userMessage, metadata);
|
||||
AugmentationResult result = augmentor.augment(augmentationRequest);
|
||||
|
||||
ChatMessage augmented = result.chatMessage();
|
||||
if (augmented instanceof UserMessage) {
|
||||
userMessage = (UserMessage) augmented;
|
||||
log.debug("RAG 增强完成，UserMessage 已注入背景知识");
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// 3. 从数据库查询历史对话消息（放在前面）
|
||||
if (chatRequest.getSessionId() != null) {
|
||||
MessageWindowChatMemory memory = createChatMemory(chatRequest.getSessionId());
|
||||
if (memory != null) {
|
||||
@@ -430,38 +472,7 @@ public class ChatServiceFacade implements IChatService {
|
||||
}
|
||||
}
|
||||
|
||||
// 从向量库查询相关历史消息（知识库内容作为上下文）
|
||||
if (chatRequest.getKnowledgeId() != null) {
|
||||
// 查询知识库信息
|
||||
KnowledgeInfoVo knowledgeInfoVo = knowledgeInfoService.queryById(Long.valueOf(chatRequest.getKnowledgeId()));
|
||||
if (knowledgeInfoVo == null) {
|
||||
log.warn("知识库信息不存在，kid: {}", chatRequest.getKnowledgeId());
|
||||
// 继续添加当前用户消息
|
||||
messages.add(UserMessage.userMessage(chatRequest.getContent()));
|
||||
return messages;
|
||||
}
|
||||
|
||||
// 查询向量模型配置信息
|
||||
ChatModelVo chatModel = chatModelService.selectModelByName(knowledgeInfoVo.getEmbeddingModel());
|
||||
if (chatModel == null) {
|
||||
log.warn("向量模型配置不存在，模型名称: {}", knowledgeInfoVo.getEmbeddingModel());
|
||||
messages.add(UserMessage.userMessage(chatRequest.getContent()));
|
||||
return messages;
|
||||
}
|
||||
|
||||
// 构建向量查询参数
|
||||
QueryVectorBo queryVectorBo = buildQueryVectorBo(chatRequest, knowledgeInfoVo, chatModel);
|
||||
|
||||
// 获取向量查询结果（知识库内容作为系统上下文，放在历史消息之后）
|
||||
List<String> nearestList = vectorStoreService.getQueryVector(queryVectorBo);
|
||||
for (String prompt : nearestList) {
|
||||
// 知识库内容作为系统上下文添加
|
||||
messages.add(new AiMessage(prompt));
|
||||
}
|
||||
}
|
||||
|
||||
// 构建当前用户消息（放在最后）
|
||||
UserMessage userMessage = UserMessage.userMessage(chatRequest.getContent());
|
||||
// 4. 添加经过增强的用户消息（放在最后）
|
||||
messages.add(userMessage);
|
||||
|
||||
return messages;
|
||||
@@ -480,6 +491,13 @@ public class ChatServiceFacade implements IChatService {
|
||||
queryVectorBo.setVectorModelName(knowledgeInfoVo.getVectorModel());
|
||||
queryVectorBo.setEmbeddingModelName(knowledgeInfoVo.getEmbeddingModel());
|
||||
queryVectorBo.setMaxResults(knowledgeInfoVo.getRetrieveLimit());
|
||||
|
||||
// 设置重排序参数
|
||||
queryVectorBo.setEnableRerank(knowledgeInfoVo.getEnableRerank() != null && knowledgeInfoVo.getEnableRerank() == 1);
|
||||
queryVectorBo.setRerankModelName(knowledgeInfoVo.getRerankModel());
|
||||
queryVectorBo.setRerankTopN(knowledgeInfoVo.getRerankTopN());
|
||||
queryVectorBo.setRerankScoreThreshold(knowledgeInfoVo.getRerankScoreThreshold());
|
||||
|
||||
return queryVectorBo;
|
||||
}
|
||||
|
||||
|
||||
@@ -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();
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,72 @@
|
||||
package org.ruoyi.service.chat.impl.provider;
|
||||
|
||||
import cn.hutool.core.util.StrUtil;
|
||||
import dev.langchain4j.model.chat.ChatModel;
|
||||
import dev.langchain4j.model.chat.StreamingChatModel;
|
||||
import dev.langchain4j.model.openai.OpenAiChatModel;
|
||||
import dev.langchain4j.model.openai.OpenAiStreamingChatModel;
|
||||
import lombok.RequiredArgsConstructor;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
import org.ruoyi.common.chat.domain.dto.request.ChatRequest;
|
||||
import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
|
||||
import org.ruoyi.enums.ChatModeType;
|
||||
import org.ruoyi.observability.MyChatModelListener;
|
||||
import org.ruoyi.service.chat.AbstractChatService;
|
||||
import org.springframework.stereotype.Service;
|
||||
|
||||
import java.time.Duration;
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* 自定义 API 服务调用
|
||||
*
|
||||
* 适用于 OpenAI 兼容接口或仅通过通用 HTTP 协议接入的第三方大模型服务。
|
||||
* 通过模型配置中的 apiHost / apiKey / modelName 即可复用，不需要再写死具体供应商。
|
||||
*
|
||||
* @author better
|
||||
*/
|
||||
@Service
|
||||
@Slf4j
|
||||
@RequiredArgsConstructor
|
||||
public class CustomApiServiceImpl implements AbstractChatService {
|
||||
|
||||
private static final Duration DEFAULT_TIMEOUT = Duration.ofSeconds(180);
|
||||
|
||||
@Override
|
||||
public StreamingChatModel buildStreamingChatModel(ChatModelVo chatModelVo, ChatRequest chatRequest) {
|
||||
return OpenAiStreamingChatModel.builder()
|
||||
.baseUrl(normalizeBaseUrl(chatModelVo.getApiHost()))
|
||||
.apiKey(defaultIfBlank(chatModelVo.getApiKey(), "EMPTY"))
|
||||
.modelName(chatModelVo.getModelName())
|
||||
.timeout(DEFAULT_TIMEOUT)
|
||||
.listeners(List.of(new MyChatModelListener()))
|
||||
.returnThinking(chatRequest.getEnableThinking())
|
||||
.build();
|
||||
}
|
||||
|
||||
@Override
|
||||
public ChatModel buildChatModel(ChatModelVo chatModelVo) {
|
||||
return OpenAiChatModel.builder()
|
||||
.baseUrl(normalizeBaseUrl(chatModelVo.getApiHost()))
|
||||
.apiKey(defaultIfBlank(chatModelVo.getApiKey(), "EMPTY"))
|
||||
.modelName(chatModelVo.getModelName())
|
||||
.timeout(DEFAULT_TIMEOUT)
|
||||
.build();
|
||||
}
|
||||
|
||||
@Override
|
||||
public String getProviderName() {
|
||||
return ChatModeType.CUSTOM_API.getCode();
|
||||
}
|
||||
|
||||
private String normalizeBaseUrl(String baseUrl) {
|
||||
if (StrUtil.isBlank(baseUrl)) {
|
||||
throw new IllegalArgumentException("自定义API的请求地址(apiHost)不能为空");
|
||||
}
|
||||
return baseUrl.endsWith("/") ? baseUrl.substring(0, baseUrl.length() - 1) : baseUrl;
|
||||
}
|
||||
|
||||
private String defaultIfBlank(String value, String defaultValue) {
|
||||
return StrUtil.isBlank(value) ? defaultValue : value;
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,47 @@
|
||||
package org.ruoyi.service.chat.impl.provider;
|
||||
|
||||
|
||||
import dev.langchain4j.model.chat.StreamingChatModel;
|
||||
import dev.langchain4j.model.openai.OpenAiStreamingChatModel;
|
||||
import lombok.RequiredArgsConstructor;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
import org.ruoyi.common.chat.domain.dto.request.ChatRequest;
|
||||
import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
|
||||
import org.ruoyi.enums.ChatModeType;
|
||||
import org.ruoyi.observability.MyChatModelListener;
|
||||
import org.ruoyi.service.chat.AbstractChatService;
|
||||
import org.springframework.stereotype.Service;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
|
||||
/**
|
||||
* 小米MiMo服务调用
|
||||
* <p>
|
||||
* 小米提供OpenAI兼容的API接口，支持MiMo等模型。
|
||||
*
|
||||
* @author ageerle
|
||||
* @date 2026/4/19
|
||||
*/
|
||||
@Service
|
||||
@Slf4j
|
||||
@RequiredArgsConstructor
|
||||
public class MiMoServiceImpl implements AbstractChatService {
|
||||
|
||||
@Override
|
||||
public StreamingChatModel buildStreamingChatModel(ChatModelVo chatModelVo, ChatRequest chatRequest) {
|
||||
return OpenAiStreamingChatModel.builder()
|
||||
.baseUrl(chatModelVo.getApiHost())
|
||||
.apiKey(chatModelVo.getApiKey())
|
||||
.modelName(chatModelVo.getModelName())
|
||||
.listeners(List.of(new MyChatModelListener()))
|
||||
.returnThinking(chatRequest.getEnableThinking())
|
||||
.build();
|
||||
}
|
||||
|
||||
@Override
|
||||
public String getProviderName() {
|
||||
return ChatModeType.XIAOMI.getCode();
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,44 @@
|
||||
package org.ruoyi.service.chat.impl.provider;
|
||||
|
||||
import dev.langchain4j.model.chat.StreamingChatModel;
|
||||
import dev.langchain4j.model.openai.OpenAiStreamingChatModel;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
import org.ruoyi.common.chat.domain.dto.request.ChatRequest;
|
||||
import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
|
||||
import org.ruoyi.enums.ChatModeType;
|
||||
import org.ruoyi.observability.MyChatModelListener;
|
||||
import org.ruoyi.service.chat.AbstractChatService;
|
||||
import org.springframework.stereotype.Service;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* MiniMax服务调用
|
||||
* <p>
|
||||
* MiniMax提供OpenAI兼容的API接口，支持MiniMax-M2.7、MiniMax-M2.5等模型。
|
||||
* API地址：https://api.minimax.io/v1
|
||||
*
|
||||
* @author octopus
|
||||
* @date 2026/3/21
|
||||
*/
|
||||
@Service
|
||||
@Slf4j
|
||||
public class MinimaxServiceImpl implements AbstractChatService {
|
||||
|
||||
@Override
|
||||
public StreamingChatModel buildStreamingChatModel(ChatModelVo chatModelVo, ChatRequest chatRequest) {
|
||||
return OpenAiStreamingChatModel.builder()
|
||||
.baseUrl(chatModelVo.getApiHost())
|
||||
.apiKey(chatModelVo.getApiKey())
|
||||
.modelName(chatModelVo.getModelName())
|
||||
.listeners(List.of(new MyChatModelListener()))
|
||||
.returnThinking(chatRequest.getEnableThinking())
|
||||
.build();
|
||||
}
|
||||
|
||||
@Override
|
||||
public String getProviderName() {
|
||||
return ChatModeType.MINIMAX.getCode();
|
||||
}
|
||||
|
||||
}
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user