javac -cp jna.jar OllamaClient.java java -Djna.library.path=/usr/local/lib -cp .:jna.jar OllamaClient
import dev.langchain4j.model.ollama.OllamaChatModel; import dev.langchain4j.model.output.Response; public class LangChain4jOllamaExample public static void main(String[] args) // Initialize the local Ollama model OllamaChatModel model = OllamaChatModel.builder() .baseUrl("http://localhost:11434") .modelName("llama3") .temperature(0.7) .build(); // Generate a response String response = model.generate("What are the benefits of using Java for AI?"); System.out.println("AI Response:\n" + response); Use code with caution. Advanced Use Cases for Java and Ollama 1. Streaming Responses ollamac java work
Before adopting heavy frameworks, it is valuable to understand how Java natively speaks to Ollama. Using Java’s built-in HttpClient (introduced in Java 11), you can send inference requests directly to the Ollama daemon. The Request Payload javac -cp jna