RAG allows your local Ollama model to answer questions based on private enterprise data (like PDFs, markdown files, or internal databases).
– A more feature‑rich project that adds extra functionality like model branching, SVG/GraphViz output helpers, and even the ability to let the LLM run code inside a Vagrant sandbox. It includes POJOs that mirror the entire Ollama API specification.
OllamaChatModel model = OllamaChatModel.builder() .baseUrl("http://localhost:11434") .modelName("llama3:8b") .temperature(0.7) .build();
HttpRequest request = HttpRequest.newBuilder() .uri(URI.create(OLLAMA_URL)) .header("Content-Type", "application/json") .POST(HttpRequest.BodyPublishers.ofString(jsonInput)) .build(); ollamac java work
<dependency> <groupId>dev.langchain4j</groupId> <artifactId>langchain4j-ollama</artifactId> <version>1.0.0</version> </dependency>
ollama4j is a popular, active Java library that simplifies interacting with Ollama.
import java.net.URI; import java.net.http.HttpClient; import java.net.http.HttpRequest; import java.net.http.HttpResponse; public class OllamaNativeClient public static void main(String[] args) throws Exception String jsonPayload = """ "model": "llama3", "prompt": "Explain the concept of Dependency Injection in one sentence.", "stream": false """; HttpClient client = HttpClient.newHttpClient(); HttpRequest request = HttpRequest.newBuilder() .uri(URI.create("http://localhost:11434/api/generate")) .header("Content-Type", "application/json") .POST(HttpRequest.BodyPublishers.ofString(jsonPayload)) .build(); HttpResponse response = client.send(request, HttpResponse.BodyHandlers.ofString()); System.out.println("Response Status Code: " + response.statusCode()); System.out.println("Response Body:\n" + response.body()); Use code with caution. RAG allows your local Ollama model to answer
: Tool/function calling (including MCP tools), multimodal inputs (vision), and reasoning/thinking modes.
Many of your prompts will be identical or nearly identical. Cache responses aggressively:
: Easy access to a vast library of open-source models via simple CLI commands. Setting Up Ollama OllamaChatModel model = OllamaChatModel
: A lightweight Java client with zero external dependencies, supporting both standard and streaming responses.
Modern LLMs support powerful advanced features. Two of the most impactful are (or Function Calling) and JSON Mode .