Ollama チャット

ollama pull <model-name>

ollama pull hf.co/<username>/<model-repository>

ChatResponse response = chatModel.call(
    new Prompt(
        "Generate the names of 5 famous pirates.",
        OllamaOptions.builder()
            .model(OllamaModel.LLAMA3_1)
            .temperature(0.4)
            .build()
    ));

spring:
  ai:
    ollama:
      init:
        pull-model-strategy: always
        timeout: 60s
        max-retries: 1

spring:
  ai:
    ollama:
      init:
        pull-model-strategy: always
        chat:
          additional-models:
            - llama3.2
            - qwen2.5

spring:
  ai:
    ollama:
      init:
        pull-model-strategy: always
        chat:
          include: false

var imageResource = new ClassPathResource("/multimodal.test.png");

var userMessage = new UserMessage("Explain what do you see on this picture?",
        new Media(MimeTypeUtils.IMAGE_PNG, this.imageResource));

ChatResponse response = chatModel.call(new Prompt(this.userMessage,
        OllamaOptions.builder().model(OllamaModel.LLAVA)).build());

The image shows a small metal basket filled with ripe bananas and red apples. The basket is placed on a surface,
which appears to be a table or countertop, as there's a hint of what seems like a kitchen cabinet or drawer in
the background. There's also a gold-colored ring visible behind the basket, which could indicate that this
photo was taken in an area with metallic decorations or fixtures. The overall setting suggests a home environment
where fruits are being displayed, possibly for convenience or aesthetic purposes.

spring.ai.ollama.chat.options.model=hf.co/bartowski/gemma-2-2b-it-GGUF
spring.ai.ollama.init.pull-model-strategy=always

spring:
  ai:
    ollama:
      base-url: http://localhost:11434
      chat:
        options:
          model: mistral
          temperature: 0.7

@RestController
public class ChatController {

    private final OllamaChatModel chatModel;

    @Autowired
    public ChatController(OllamaChatModel chatModel) {
        this.chatModel = chatModel;
    }

    @GetMapping("/ai/generate")
    public Map<String,String> generate(@RequestParam(value = "message", defaultValue = "Tell me a joke") String message) {
        return Map.of("generation", this.chatModel.call(message));
    }

    @GetMapping("/ai/generateStream")
	public Flux<ChatResponse> generateStream(@RequestParam(value = "message", defaultValue = "Tell me a joke") String message) {
        Prompt prompt = new Prompt(new UserMessage(message));
        return this.chatModel.stream(prompt);
    }

}

var ollamaApi = new OllamaApi();

var chatModel = new OllamaChatModel(this.ollamaApi,
            OllamaOptions.create()
                .model(OllamaOptions.DEFAULT_MODEL)
                .temperature(0.9));

ChatResponse response = this.chatModel.call(
    new Prompt("Generate the names of 5 famous pirates."));

// Or with streaming responses
Flux<ChatResponse> response = this.chatModel.stream(
    new Prompt("Generate the names of 5 famous pirates."));

OllamaApi ollamaApi = new OllamaApi("YOUR_HOST:YOUR_PORT");

// Sync request
var request = ChatRequest.builder("orca-mini")
    .stream(false) // not streaming
    .messages(List.of(
            Message.builder(Role.SYSTEM)
                .content("You are a geography teacher. You are talking to a student.")
                .build(),
            Message.builder(Role.USER)
                .content("What is the capital of Bulgaria and what is the size? "
                        + "What is the national anthem?")
                .build()))
    .options(OllamaOptions.create().temperature(0.9))
    .build();

ChatResponse response = this.ollamaApi.chat(this.request);

// Streaming request
var request2 = ChatRequest.builder("orca-mini")
    .ttream(true) // streaming
    .messages(List.of(Message.builder(Role.USER)
        .content("What is the capital of Bulgaria and what is the size? " + "What is the national anthem?")
        .build()))
    .options(OllamaOptions.create().temperature(0.9).toMap())
    .build();

Flux<ChatResponse> streamingResponse = this.ollamaApi.streamingChat(this.request2);