From ac74b85051f1cc46603f3496490f2253cf662ba5 Mon Sep 17 00:00:00 2001 From: Wenjie Zhang Date: Wed, 5 Nov 2025 16:22:51 +0800 Subject: [PATCH] docs: pre-release 0.3.0 --- README.md | 9 +- docs/advanced/agents-config.md | 129 +- docs/changelog/roadmap.md | 4 +- docs/intro/quick-start.md | 6 +- package-lock.json | 1477 +-------------------- src/agents/mini_agent/graph.py | 3 +- src/agents/reporter/graph.py | 3 +- src/models/embed.py | 16 + web/package.json | 2 +- web/src/components/AgentConfigSidebar.vue | 2 +- 10 files changed, 61 insertions(+), 1590 deletions(-) diff --git a/README.md b/README.md index 27a00aa6..e9f2338d 100644 --- a/README.md +++ b/README.md @@ -2,8 +2,8 @@
-[![Stable](https://img.shields.io/badge/stable-v0.2.2-blue.svg)](https://github.com/xerrors/Yuxi-Know/tree/v0.2.2) -[![Lasted](https://img.shields.io/badge/latest-v0.3.0.beta-yellow.svg)](https://github.com/xerrors/Yuxi-Know/tree/v0.3.0-beta) +[![Stable](https://img.shields.io/badge/stable-v0.3.0-blue.svg)](https://github.com/xerrors/Yuxi-Know/tree/v0.3.0) + [![](https://img.shields.io/badge/Docker-2496ED?style=flat&logo=docker&logoColor=ffffff)](https://github.com/xerrors/Yuxi-Know/blob/main/docker-compose.yml) [![](https://img.shields.io/github/issues/xerrors/Yuxi-Know?color=F48D73)](https://github.com/xerrors/Yuxi-Know/issues) [![License](https://img.shields.io/github/license/bitcookies/winrar-keygen.svg?logo=github)](https://github.com/xerrors/Yuxi-Know/blob/main/LICENSE) @@ -21,11 +21,12 @@ 🙏 感谢 Star ~ ⭐⭐⭐⭐⭐ -详细文档请查看全新的 [**📄文档中心**](https://xerrors.github.io/Yuxi-Know/)， [📽️ 点击查看视频演示 v0.2](https://www.bilibili.com/video/BV1ETedzREgY/?share_source=copy_web&vd_source=37b0bdbf95b72ea38b2dc959cfadc4d8) +详细文档请查看全新的 [**📄文档中心**](https://xerrors.github.io/Yuxi-Know/) **🎉 最新动态** -- **[2025/10/13]** v0.3 进入 beta 测试环节，不会再封装新的特性，仅作 bug 层面的修复 +- **[2025/11/05] v0.3 版本发布 + - 全面适配LangChain/LangGraph v1版本的特性，使用 create_agent 创建智能体入口。
diff --git a/docs/advanced/agents-config.md b/docs/advanced/agents-config.md index 6a51abb0..55ad8099 100644 --- a/docs/advanced/agents-config.md +++ b/docs/advanced/agents-config.md @@ -2,135 +2,62 @@ ## 智能体开发 -系统基于 [LangGraph](https://github.com/langchain-ai/langgraph) 框架，支持自定义智能体应用开发。 +系统基于 [LangGraph](https://github.com/langchain-ai/langgraph) 并通过统一的 `AgentManager` 管理所有智能体。`src/agents/__init__.py` 会在启动时遍历 `src/agents` 目录，对每个包含 `__init__.py` 的子包执行自动发现：所有继承 `BaseAgent` 的类都会被注册并立即初始化，因此只要代码落位正确，就不需要再手动登记或修改管理器。 -系统默认集成示例智能体： +仓库预置了若干可直接运行的智能体：`chatbot` 聚焦对话与动态工具调度，`mini_agent` 提供精简模板，`reporter` 演示报告类链路。这些目录展示了上下文类、Graph 构造方式、子智能体引用以及中间件组合的范例，新增功能时可以直接复用。 -| 智能体 | 功能 | 位置 | -|--------|------|------| -| **基础智能体** | 对话功能 | `src/agents/chatbot/` | -| **ReAct 智能体** | 推理与行动循环 | `src/agents/react/` | +### 创建新的智能体 -### 开发自定义智能体 +在 `src/agents` 下新建一个包，保持与现有目录一致的结构：放置 Graph 构造逻辑（通常命名为 `graph.py`），并在包内的 `__init__.py` 中暴露主类。 -如果需要开发自己的智能体的话，可以基于智能体基类以及相关脚手架实现。整体上是和 LangGraph 的架构是适配的，只是在部分功能上需要和平台更加适配才好。 +智能体类必须继承 `src.agents.common.BaseAgent`，同时实现异步的 `get_graph` 方法来返回编译后的 LangGraph 实例，并配置好 `checkpointer`，否则无法从历史对话中恢复。 -#### 1. 创建智能体类 +需要额外上下文字段时，可继承 `BaseContext` 构建自己的配置表单，再把类绑定到 `context_schema`，平台会在 `saves/agents/` 下生成默认配置。 -继承 `BaseAgent` 并实现 `get_graph` 方法： +案例1 使用内置工具构建一个极简的智能体，可以动态选择 Prompt 和 LLM： -```python -from .base import BaseAgent +<<< @/../src/agents/mini_agent/graph.py -class CustomAgent(BaseAgent): - def get_graph(self): - # 返回 LangGraph 实例 - return graph_instance +案例2 基于MySQL工具，以及自定义 MCP Server 的数据库报表助手。 - @property - def context_schema(self): - # 定义配置参数 - return schema -``` +<<< @/../src/agents/reporter/graph.py -#### 2. 注册智能体 -在 `src/agents/__init__.py` 中注册： -```python -from .custom_agent import CustomAgent +智能体实例的生命周期交给管理器处理，会在自动发现时完成初始化并缓存单例，以便快速响应请求。在容器内热重载时，只要保存文件即可触发重新导入；需要强制刷新可调用 `agent_manager.get_agent(, reload=True)`。 -agent_manager = AgentManager() -agent_manager.register_agent(CustomAgent) -agent_manager.init_all_agents() -``` +更多动态工具选择与 MCP 注册的例子，见 `src/agents/chatbot/graph.py` 中的中间件组合。 -#### 3. 参考示例 +### 拓展现有智能体 -查看 `src/agents/react/graph.py` 中的 `ReActAgent` 实现示例。 +智能体保持为 LangGraph 的标准节点组合，因此可以在原有 `graph.py` 中添加节点、条件与消息转换器。复用现成上下文时，只需扩展当前 `context_schema` 的字段；若功能差异较大，可以创建新的上下文类并替换 `context_schema`。 + +对工具、模型或提示语的调整建议封装到中间件或独立函数里，既方便多智能体共用，又能保持 `BaseAgent` 的基础接口稳定。变更提交后无需手动刷新注册表，只要确保包结构未改变，智能体会在热重载中自动更新。 + +### 子智能体与中间件 + +子智能体集中放在 `src/agents/common/subagents` 目录，典型例子是 `calc_agent`，它通过 LangChain 的 `create_agent` 构建计算器能力并以工具暴露给主图。新增子智能体时沿用这一结构：在目录内编写封装函数与 `@tool` 装饰器，导出后即可被任意智能体调用。 + +中间件位于 `src/agents/common/middlewares`，包含上下文感知提示词、模型选择以及动态工具加载等实现。如果需要编写新的中间件，请遵循 LangChain 官方文档中对 `AgentMiddleware`、`ModelRequest`、`ModelResponse` 等接口的定义，完成后在该目录的 `__init__.py` 暴露入口，主智能体即可在 `middleware` 列表中引用。 ## 内置工具与 MCP 集成 -系统默认会为对话/推理智能体注册一组“内置工具”，并根据配置动态启用： +系统会根据配置自动组装工具集合，涵盖知识图谱查询、向量检索生成的动态工具、MySQL 只读查询能力、Tavily 搜索以及所有注册的 MCP 工具。 -- 知识图谱查询：`query_knowledge_graph` - - 依赖 Neo4j 服务（见 docker-compose 中 `graph`） - - 返回包含三元组的结果，适合图谱关系类问题 -- 网页搜索：`TavilySearch` - - 需要设置 `TAVILY_API_KEY` 才会启用 - - LLM 在需要时自动调用，提供实时网页信息 -- 知识库检索工具：按知识库动态生成 - - 工具名称形如 `query_`；描述来自知识库名称与说明 - - 在工具选择阶段，用描述帮助模型做针对性检索 -- MySQL 工具包：只读查询 - - `mysql_list_tables`（对话侧名称：查询表名及说明）、`mysql_describe_table`、`mysql_query` - - 环境变量见下，具备超时/行数限制与注入防护 +工具的启用状态和描述由配置文件或环境变量决定，当依赖缺失时会被中间件自动忽略，从而避免在图中加载不可用能力。MCP Server 的接入方式保持不变，只需在 `src/agents/common/mcp.py` 的 `MCP_SERVERS` 中填入服务地址与 `transport` 类型，如需更多范式可参阅 LangChain 官方文档。 -MCP（Model Context Protocol）可接入外部可视化或其他工具能力： -- 在 `src/agents/common/mcp.py` 的 `MCP_SERVERS` 添加配置；`transport` 字段名必须正确 -- 常见问题：无法列出工具多因服务不可达或配置错误；优先检查可达性与字段名 +### MySQL 数据库 - -### 1. MySQL 数据库集成 - -系统支持智能体查询 MySQL 数据库，为数据分析提供强大支持。 - -### 配置数据库连接 - -在环境变量中配置数据库信息： +设置数据库连接时，在 `.env` 中提供以下字段： ```env -# MySQL 数据库配置 MYSQL_HOST=192.168.1.100 MYSQL_USER=username MYSQL_PASSWORD=your_secure_password MYSQL_DATABASE=database_name -MYSQL_DATABASE_DESCRIPTION=业务主库（可选，用于工具提示） +MYSQL_DATABASE_DESCRIPTION=业务主库（可选提示） MYSQL_PORT=3306 MYSQL_CHARSET=utf8mb4 ``` -在智能体配置中启用以下 MySQL 工具： - -| 工具名称 | 功能描述 | -|----------|----------| -| `mysql_list_tables`（查询表名及说明） | 获取数据库中的所有表名，并在有配置时附带数据库说明 | -| `mysql_describe_table` （描述表） | 获取指定表的详细结构信息 | -| `mysql_query` （执行 SQL 查询）| 执行只读的 SQL 查询语句 | - -配置 `MYSQL_DATABASE_DESCRIPTION` 后，智能体在列出数据库表时会优先展示这段说明，帮助模型在使用工具时理解库的用途，从而匹配更精确的查询策略。 - -### 安全特性 - -- ✅ **只读操作**: 仅允许 SELECT、SHOW、DESCRIBE、EXPLAIN 操作 -- ✅ **SQL 注入防护**: 严格的表名参数验证 -- ✅ **超时控制**: 默认 60 秒，最大 600 秒 -- ✅ **结果限制**: 默认 10000 字符，100 行，最大 1000 行 - -### 可视化图表-MCP-Server - -系统支持基于 MCP（Model Context Protocol）的图表可视化功能。 - -- 基于 @antvis 团队开发的 [可视化图表-MCP-Server](https://www.modelscope.cn/mcp/servers/@antvis/mcp-server-chart) -- 支持多种图表类型和数据可视化 -- 通过魔搭社区配置 Host 资源 - -在 `src/agents/common/mcp.py` 的 `MCP_SERVERS` 中添加配置： - -```python -# MCP Server configurations -MCP_SERVERS = { - "sequentialthinking": { - "url": "https://remote.mcpservers.org/sequentialthinking/mcp", - "transport": "streamable_http", - }, - "mcp-server-chart": { - "url": "https://mcp.api-inference.modelscope.net/9993ae42524c4c/mcp", - "transport": "streamable_http", - } -} -``` - -::: warning 配置注意 -记得将 `type` 字段修改为 `transport`，并确保服务可达。 -::: +所有查询限定在只读范围（SELECT、SHOW、DESCRIBE、EXPLAIN），请求会经过表名校验与超时控制，默认限制 60 秒与 100 行输出，并可通过配置调整上限。连接信息会反馈给 LangGraph，智能体可以自动陈述数据库用途并选择更准确的检索策略。 diff --git a/docs/changelog/roadmap.md b/docs/changelog/roadmap.md index 3cd79722..a3f7481a 100644 --- a/docs/changelog/roadmap.md +++ b/docs/changelog/roadmap.md @@ -7,7 +7,6 @@ ## Bugs -- [ ] 前端工具调用渲染出现问题 ## Next @@ -43,4 +42,5 @@ - [x] upload 接口会阻塞主进程 - [x] LightRAG 知识库查看不了解析后的文本，偶然出现，未复现 - [x] LightRAG 知识库应该可以支持修改 LLM -- [x] 智能体的加载状态有问题：（1）智能体加载没有动画；（2）切换对话和加载中，使用同一个loading状态。 \ No newline at end of file +- [x] 智能体的加载状态有问题：（1）智能体加载没有动画；（2）切换对话和加载中，使用同一个loading状态。 +- [x] 前端工具调用渲染出现问题 \ No newline at end of file diff --git a/docs/intro/quick-start.md b/docs/intro/quick-start.md index 6ff7ae87..efe8db2b 100644 --- a/docs/intro/quick-start.md +++ b/docs/intro/quick-start.md @@ -16,13 +16,13 @@ ```bash # 克隆稳定版本 -git clone --branch v0.3.0-beta2 --depth 1 https://github.com/xerrors/Yuxi-Know.git +git clone --branch v0.3.0 --depth 1 https://github.com/xerrors/Yuxi-Know.git cd Yuxi-Know ``` ::: warning 版本说明 -- `v0.2.2`: 稳定版本 -- `v0.3.0-beta2`：最新的 Beta 测试版 +- `v0.3.0`: 稳定版本 +- `v0.3.0`：最新的 Beta 测试版 - 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"license": "MIT", - "peer": true - }, - "node_modules/vscode-uri": { - "version": "3.0.8", - "resolved": "https://registry.npmjs.org/vscode-uri/-/vscode-uri-3.0.8.tgz", - "integrity": "sha512-AyFQ0EVmsOZOlAnxoFOGOq1SQDWAB7C6aqMGS23svWAllfOaxbuFvcT8D1i8z3Gyn8fraVeZNNmN6e9bxxXkKw==", - "license": "MIT", - "peer": true - }, "node_modules/vue": { "version": "3.5.22", "resolved": "https://registry.npmjs.org/vue/-/vue-3.5.22.tgz", diff --git a/src/agents/mini_agent/graph.py b/src/agents/mini_agent/graph.py index ab78188d..e6279ec1 100644 --- a/src/agents/mini_agent/graph.py +++ b/src/agents/mini_agent/graph.py @@ -1,6 +1,7 @@ from langchain.agents import create_agent from langchain.agents.middleware import ModelRequest, ModelResponse, dynamic_prompt, wrap_model_call +from src import config from src.agents.common import BaseAgent, load_chat_model, get_buildin_tools from src.agents.common.middlewares import context_aware_prompt, context_based_model @@ -21,7 +22,7 @@ class MiniAgent(BaseAgent): # 创建 MiniAgent graph = create_agent( - model=load_chat_model("siliconflow/Qwen/Qwen3-235B-A22B-Instruct-2507"), # 实际会被覆盖 + model=load_chat_model(config.default_model), # 实际会被覆盖 tools=self.get_tools(), middleware=[context_aware_prompt, context_based_model], checkpointer=await self._get_checkpointer(), diff --git a/src/agents/reporter/graph.py b/src/agents/reporter/graph.py index 74ce52d9..46dfee50 100644 --- a/src/agents/reporter/graph.py +++ b/src/agents/reporter/graph.py @@ -3,6 +3,7 @@ import textwrap from langchain.agents import create_agent from langchain.agents.middleware import ModelRequest, ModelResponse, dynamic_prompt, wrap_model_call +from src import config from src.agents.common import BaseAgent, load_chat_model, get_mcp_tools from src.agents.common.middlewares import context_aware_prompt, context_based_model from src.agents.common.toolkits.mysql import get_mysql_tools @@ -34,7 +35,7 @@ class SqlReporterAgent(BaseAgent): # 创建 SqlReporterAgent graph = create_agent( - model=load_chat_model("siliconflow/Qwen/Qwen3-235B-A22B-Instruct-2507"), + model=load_chat_model(config.default_model), # 默认模型，会被 middleware 覆盖 tools=await self.get_tools(), middleware=[context_aware_prompt, context_based_model], checkpointer=await self._get_checkpointer(), diff --git a/src/models/embed.py b/src/models/embed.py index f442ce09..528e1ccf 100644 --- a/src/models/embed.py +++ b/src/models/embed.py @@ -132,6 +132,22 @@ class OllamaEmbedding(BaseEmbeddingModel): logger.error(f"Ollama Embedding async request failed: {e}, {payload}") raise ValueError(f"Ollama Embedding async request failed: {e}") + async def test_connection(self) -> tuple[bool, str]: + """ + 测试embedding模型的连接性 + + Returns: + tuple: (success: bool, message: str) + """ + try: + # 使用简单的测试文本 + test_text = ["Hello world"] + await self.aencode(test_text) + return True, "连接正常" + except Exception as e: + error_msg = str(e) + return False, error_msg + class OtherEmbedding(BaseEmbeddingModel): def __init__(self, **kwargs) -> None: diff --git a/web/package.json b/web/package.json index 66f3c472..809d198c 100644 --- a/web/package.json +++ b/web/package.json @@ -1,6 +1,6 @@ { "name": "yuxi-know-web", - "version": "0.2.1.web", + "version": "0.3.0.web", "private": true, "scripts": { "dev": "vite", diff --git a/web/src/components/AgentConfigSidebar.vue b/web/src/components/AgentConfigSidebar.vue index 92bf16bb..d6157904 100644 --- a/web/src/components/AgentConfigSidebar.vue +++ b/web/src/components/AgentConfigSidebar.vue @@ -695,7 +695,7 @@ watch(() => props.isOpen, (newVal) => { } .config-item { - margin-bottom: 20px; + margin: 30px 0; .config-description { margin: 4px 0 8px 0;