A comprehensive Java framework designed for building AI-powered applications across various scenarios. Solon-AI targets Java developers seeking to integrate advanced AI capabilities like LLMs, RAG, function calling, and multi-modal perception into their existing systems. It offers a unified, efficient, and open approach, significantly simplifying the development lifecycle for complex AI agents and services.

How It Works

Solon-AI provides a modular architecture encompassing core AI functionalities. It abstracts LLM interactions through ChatModel, supporting multiple providers and dialects, with options for synchronous, streaming, and vision-based prompts. Its RAG (Retrieval-Augmented Generation) pipeline includes EmbeddingModel, RerankingModel, and Repository components for knowledge base construction and retrieval. The framework also features an Ai Flow engine for orchestrating AI tasks via YAML definitions and an MCP (Multi-Channel Protocol) layer for building distributed AI servers, clients, and proxies.

Quick Start & Requirements

• Primary Install/Run: Standard Java project setup. The framework is designed to be embedded within existing Java applications.
• Prerequisites: Java 8 to Java 25. Can be embedded into SpringBoot, jFinal, Vert.X, Quarkus, Micronaut, and other Java frameworks.
• Documentation: https://solon.noear.org/article/learn-solon-ai

Highlighted Details

• Full-spectrum AI support: LLM, Function/Tool Calling, RAG, Embedding, Vision, and AI Flow orchestration.
• MCP (Multi-Channel Protocol) framework for building distributed AI services, including server, client, and proxy implementations.
• Embeddable design allows seamless integration into popular Java frameworks like SpringBoot and Vert.X.
• Abstracted AI provider interfaces enable easy switching between different LLM and embedding services (e.g., Ollama).

Maintenance & Community

No specific details regarding maintainers, community channels (like Discord/Slack), or roadmap were provided in the README content.

Licensing & Compatibility

The license type and any compatibility notes for commercial use or closed-source linking are not specified in the provided README content.

Limitations & Caveats

The framework is Java-centric, requiring integration within a Java ecosystem. Specific details on performance benchmarks, unsupported platforms, or known limitations were not detailed in the provided text.