Observed Signal · May 26, 2026 · Technical Release · Source: DEV Community · Impact: 2/5 · Sentiment: Neutral
Run an LLM Agent in Java with Mistral
A step-by-step tutorial demonstrating how to run a real LLM-backed agent on the JVM for free using Mistral's free tier and the open-source AgentFlow4J runtime on top of Spring AI. The post (published May 26, 2026) walks through creating a Mistral account, obtaining an API key, adding JitPack and Spring AI Mistral dependencies (AgentFlow4J v0.6.0), configuring spring.ai to use model mistral-small-latest, and a minimal Java example using ExecutorAgent and a ChatClient. The article highlights AgentFlow4J's orchestration features (graph orchestration, typed state, checkpoint/resume, governance gates) and points to a cookbook of runnable recipes and the project's GitHub repository. AgentFlow4J is released under Apache 2.0.
Practical tutorial showing how to run LLM agents on the JVM using Mistral's free tier and the open-source AgentFlow4J runtime; useful for Java developers experimenting with agentic LLM workflows but not industry-shifting.
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Key Takeaways & Evidence Grounding
- Published on 2026-05-26
- Tutorial shows using Mistral's free tier (model: mistral-small/mistral-small-latest) to run LLM agents without paid keys
- AgentFlow4J (dependency version v0.6.0) is provided via JitPack and used as an orchestration runtime on top of Spring AI
- Configuration requires exporting a MISTRAL_API_KEY and setting spring.ai.mistralai.chat.options.model in application.yml
- AgentFlow4J is open source under the Apache 2.0 license and offers orchestration features like graph orchestration, typed state, checkpoints, and governance gates
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