"The latest release of the Agent Development Kit for Java, version 0.2.0, marks a significant expansion of its capabilities through the integration with the LangChain4j LLM framework, which opens it up to all the large language models supported by the framework. Before integrating LangChain4j, ADK for Java only supported two models, Google Gemini and Anthropic Claude. This contrasted with the Python ADK, which offered broader support via via LiteLLM."
"Guillaume Laforge, who is also a contributor to LangChain4j and one of the developers behind its integration into the ADK, explains that using LangChain4j makes it possible mixing models together in multi-agent scenarios. This can be achieved through agent tools, which allow one agent to use another like a tool. Mixing different models in a multi-agent scenario is quite interesting, as you can use the best model for the job. Maybe you'll need to use a super fast model to do a simple classification task to route requests depending on the ask, while you'll use a beefier model for the main task that requires more advanced thinking (like a Gemini 2.5 thinking model)."
Agent Development Kit for Java 0.2.0 integrates LangChain4j, enabling access to all LLMs supported by LangChain4j. Prior ADK for Java supported only Google Gemini and Anthropic Claude, while Python ADK supported more models via LiteLLM. LangChain4j integration grants Java developers access to OpenAI, Anthropic, Mistral, and models supported by Ollama or Docker Model Runner such as Gemma, Qwen, and Phi. LangChain4j enables mixing different models in multi-agent scenarios via agent tools, allowing one agent to invoke another as a tool. Example implementation pairs a main Claude agent with an OpenAI weather tool agent.
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