Solon AI
Java AI application development framework (supports LLM-tool,skill; RAG; MCP; Agent-ReAct,Team-Agent). Compatible with java8 ~ java26. It can also be embedded in SpringBoot,…
Install
git clone https://github.com/opensolon/solon-aiInstall command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →Solon-AI
<strong>Java LLM(tool, skill) & RAG & MCP & Agent(ReAct, Team) Application development framework</strong>
<strong>Restraint, efficiency and openness</strong>
<strong>It is the same type of development framework as LangChain, LangGraph and LlamaIndex</strong>
https://solon.noear.org/article/learn-solon-ai
Language: English | 中文
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...
Example Agent synthesis project (can be used directly for production or customization)
Core Module Experience
- ChatModel(General Purpose LLM call interface)
Support for synchronous and Reactive calls, built-in dialect adaptation, Tool, Skill, ChatSession, etc.
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")
.defaultTalentAdd(new McpGatewayTalent())
.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(); //Flux<ChatEvent>, full semantic events
- Talents(Solon AI Talents)
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