# solon-ai **Repository Path**: opensolon/solon-ai ## Basic Information - **Project Name**: solon-ai - **Description**: Java AI 应用开发框架(支持 LLM-tool,skill;RAG;MCP;Agent-ReAct,Team)。同时兼容 java8 ~ java25。也可嵌入到 SpringBoot、jFinal、Vert.x、Quarkus 等框架中使用。 - **Primary Language**: Java - **License**: Apache-2.0 - **Default Branch**: main - **Homepage**: https://solon.noear.org - **GVP Project**: Yes ## Statistics - **Stars**: 560 - **Forks**: 148 - **Created**: 2025-03-05 - **Last Updated**: 2026-01-31 ## Categories & Tags **Categories**: ai **Tags**: AI, Java, MCP-Server, tool, skill ## README


Solon-AI

Java LLM(tool, skill) & RAG & MCP & Agent(ReAct, Team) Application development framework
Restraint, efficiency and openness
It is the same type of development framework as LangChain, LangGraph and LlamaIndex

https://solon.noear.org/article/learn-solon-ai

Ask DeepWiki Maven Apache 2 jdk-8 jdk-11 jdk-17 jdk-21 jdk-25
gitee star github star gitcode star

##### Language: English | [中文](README_CN.md)
## 简介 Solon AI is one of the core subprojects of the Solon project. It is a full-scenario Java AI development framework, which aims to deeply integrate LLM large model, RAG knowledge base, MCP protocol and Agent collaboration choreography. * Full use case support: fits perfectly into the Solon ecosystem and can be seamlessly integrated into frameworks like SpringBoot, Vert.X, Quarkus, etc. * Multi-model dialects: Adapt model differences by dialect using ChatModel's unified interface (OpenAI, Gemini, Claude, Ollama, DeepSeek, Dashscope, etc.). * Graph-driven orchestration: supports the transformation of Agent reasoning into observable and governable computation flow graphs. Examples of embeddings (including third-party frameworks) for solon-ai: * https://gitee.com/solonlab/solon-ai-mcp-embedded-examples * https://gitcode.com/solonlab/solon-ai-mcp-embedded-examples * https://github.com/solonlab/solon-ai-mcp-embedded-examples ## What types of applications can be developed? * General-purpose Autonomous Agents (e.g., Manus, OpenOperator) * Intelligent Assistants & RAG Knowledge Bases (e.g., Dify, Coze) * Multi-Agent Collaborative Orchestration (e.g., AutoGPT, MetaGPT) * Business-Driven Controlled Workflows (e.g., AI-enhanced DingTalk/Lark approvals, SAP Intelligent Modules) * Intelligent Document Processing & ETL (e.g., Instabase, Unstructured.io) * Real-time Data Insights & Dashboards (e.g., Text-to-SQL applications) * Automated Testing & Quality Assurance (e.g., GitHub Copilot Workspace) * Low-Code/Visual AI Workflow Platforms (e.g., LangFlow, Flowise) * And more... ## Core Module Experience * ChatModel(General Purpose LLM call interface) Support for synchronous and Reactive calls, built-in dialect adaptation, Tool, Skill, ChatSession, etc. ```java ChatModel chatModel = ChatModel.of("http://127.0.0.1:11434/api/chat") .provider("ollama") //Need to specify vendor, used to identify interface style (also called dialect) .model("qwen2.5:1.5b") .defaultSkillAdd(new ToolGatewaySkill()) .build(); // Synchronize the call and print the response message AssistantMessage result = ChatchatModel.prompt("The weather in Hangzhou today?") .options(op->op.toolAdd(new WeatherTools())) //Adding tools .call() .getMessage(); System.out.println(result); // Stream call chatModel.prompt("hello").stream(); //Publisher ``` * Skills(Solon AI Skills) ```java Skill skill = new SkillDesc("order_expert") .description("Order Assistant") // Dynamic admission: Activated only when "order" is mentioned .isSupported(prompt -> prompt.getUserMessageContent().contains("order")) // Dynamic instructions: Inject different Sops depending on whether the user is a VIP or not .instruction(prompt -> { if ("VIP".equals(prompt.getMeta("user_level"))) { return "This is a VIP customer, please call fast_track_tool first."; } return "Process the order inquiry according to the normal process."; }) .toolAdd(new OrderTools()); chatModel.prompt("Where is my order from yesterday?") .options(o->o.skillAdd(skill)) .call(); ``` * RAG(知识库) It provides full-link support from DocumentLoader, DocumentSplitter, EmbeddingModel, and RerankingModel. ```java //Building a Knowledge Warehouse EmbeddingModel embeddingModel = EmbeddingModel.of(apiUrl).apiKey(apiKey).provider(provider).model(model).batchSize(10).build(); RerankingModel rerankingModel = RerankingModel.of(apiUrl).apiKey(apiKey).provider(provider).model(model).build(); InMemoryRepository repository = new InMemoryRepository(TestUtils.getEmbeddingModel()); //3.初始化知识库 repository.insert(new PdfLoader(pdfUri).load()); //retrieval List docs = repository.search(query); //You can rearrange it if you want docs = rerankingModel.rerank(query, docs); //Cue enhancement is ChatMessage message = ChatMessage.ofUserAugment(query, docs); //Calling the llm chatModel.prompt(message) .call(); ``` * MCP (Model Context Protocol) Deep integration with MCP protocol (MCP_2025_06_18), supporting cross-platform tool, resource, and prompt sharing. ```java //server @McpServerEndpoint(channel = McpChannel.STREAMABLE, mcpEndpoint = "/mcp") public class MyMcpServer { @ToolMapping(description = "Checking the weather") public String getWeather(@Param(description = "city") String location) { return "It's sunny, 25 degrees"; } } //client McpClientProvider clientProvider = McpClientProvider.builder() .channel(McpChannel.STREAMABLE) .url("http://localhost:8080/mcp") .build(); ``` * Agent (An Agent Experience with Computational Flow Graphs) The Solon AI Agent transforms reasoning logic into graph-driven collaboration flows, enabling ReAct introspective reasoning and multi-agent Team collaboration. ```java //Reflective intelligent agent: ReActAgent agent = ReActAgent.of(chatModel) // 或者用 SimpleAgent.of(chatModel) .name("weather_expert") .description("Check the weather and provide advice") .defaultToolAdd(weatherTool) // Inject MCP or local tools .build(); agent.prompt("What to wear in Beijing today?").call(); // Autocomplete: Think -> Call tool -> Observe -> Summarize // Constructing a team agent: Automatically arranging member roles through protocols TeamAgent team = TeamAgent.of(chatModel) .name("marketing_team") .protocol(TeamProtocols.HIERARCHICAL) // Hierarchical collaboration (6 preset protocols) .agentAdd(copywriterAgent) // Copywriter expert .agentAdd(illustratorAgent) // Illustrator expert .build(); team.prompt("Plan a promotion scheme for deep-sea mineral water").call(); // Supervisor automatically decomposes tasks and assigns them to corresponding experts .defaultToolAdd(weatherTool) // Inject MCP or local tools ``` * Ai Flow(Process orchestration experience) The low-code flow application of Dify is simulated, and the links such as RAG, hint word enhancement and model call are YAML arranged. ```yaml id: demo1 layout: - type: "start" - task: "@VarInput" meta: message: "Solon 是谁开发的?" - task: "@EmbeddingModel" meta: embeddingConfig: # "@type": "org.noear.solon.ai.embedding.EmbeddingConfig" provider: "ollama" model: "bge-m3" apiUrl: "http://127.0.0.1:11434/api/embed" - task: "@InMemoryRepository" meta: documentSources: - "https://solon.noear.org/article/about?format=md" splitPipeline: - "org.noear.solon.ai.rag.splitter.RegexTextSplitter" - "org.noear.solon.ai.rag.splitter.TokenSizeTextSplitter" - task: "@ChatModel" meta: systemPrompt: "你是个知识库" stream: false chatConfig: # "@type": "org.noear.solon.ai.chat.ChatConfig" provider: "ollama" model: "qwen2.5:1.5b" apiUrl: "http://127.0.0.1:11434/api/chat" - task: "@ConsoleOutput" # FlowEngine flowEngine = FlowEngine.newInstance(); # ... # flowEngine.eval("demo1"); ``` ## Solon Project code repository | Code repository | Description | |-----------------------------------------------------------------------------|-----------------------------------------------------------| | [/opensolon/solon](../../../../opensolon/solon) | Solon ,Main code repository | | [/opensolon/solon-examples](../../../../opensolon/solon-examples) | Solon ,Official website supporting sample code repository | | | | | [/opensolon/solon-expression](../../../../opensolon/solon-expression) | Solon Expression ,Code repository | | [/opensolon/solon-flow](../../../../opensolon/solon-flow) | Solon Flow ,Code repository | | [/opensolon/solon-ai](../../../../opensolon/solon-ai) | Solon Ai ,Code repository | | [/opensolon/solon-cloud](../../../../opensolon/solon-cloud) | Solon Cloud ,Code repository | | [/opensolon/solon-admin](../../../../opensolon/solon-admin) | Solon Admin ,Code repository | | [/opensolon/solon-integration](../../../../opensolon/solon-integration) | Solon Integration ,Code repository | | [/opensolon/solon-java17](../../../../opensolon/solon-java17) | Solon Java17 ,Code repository(base java17) | | [/opensolon/solon-java25](../../../../opensolon/solon-java25) | Solon Java25 ,Code repository(base java25) | | | | | [/opensolon/solon-gradle-plugin](../../../../opensolon/solon-gradle-plugin) | Solon Gradle ,Plugin code repository | | [/opensolon/solon-idea-plugin](../../../../opensolon/solon-idea-plugin) | Solon Idea ,Plugin code repository | | [/opensolon/solon-vscode-plugin](../../../../opensolon/solon-vscode-plugin) | Solon VsCode ,Plugin code repository |