This article compares three Java AI frameworks—Feat AI, Spring AI, and LangChain4j—by presenting code samples, analyzing fat‑jar sizes, core feature differences, streaming output implementations, and offering scenario‑based recommendations for developers.
To overcome large language models' knowledge staleness, the author created JinaReaderTool, a lightweight Java agent tool that fetches any webpage via Jina AI’s free API, converts it to clean Markdown, and can be seamlessly integrated into Feat AI agents for real‑time information retrieval.
The article details how the Feat team transformed a simple AI chat interface into a full‑featured AI agent using only 1,360 lines of Java code written over more than 300 days, emphasizing a lightweight, Java‑8‑compatible solution that rivals Spring AI in simplicity while delivering SSE‑based streaming responses.
