spring-ai-alibaba第二章ollama集成EmbeddingModel

1、pom文件

	<dependencies>
		<dependency>
			<groupId>org.springframework.boot</groupId>
			<artifactId>spring-boot-starter-web</artifactId>
		</dependency>
 
		<dependency>
			<groupId>org.springframework.ai</groupId>
			<artifactId>spring-ai-ollama-spring-boot-starter</artifactId>
		</dependency>
	</dependencies>

2、ollama 需又向量模型，application.yml 内容如下

server:
  port: 10005

spring:
  application:
    name: spring-ai-alibaba-ollama-chat-model-example

  ai:
    ollama:
      base-url: http://localhost:11434
      chat:
        model: llama3.2:1b
      embedding:
        model: bge-m3

3、测试代码如下

package com.alibaba.cloud.ai.example.chat.ollama.controller;

import org.springframework.ai.embedding.Embedding;
import org.springframework.ai.embedding.EmbeddingModel;
import org.springframework.ai.embedding.EmbeddingResponse;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;

import java.util.List;
import java.util.Map;

@RestController
public class EmbeddingController {

    private final EmbeddingModel embeddingModel;

    @Autowired
    public EmbeddingController(EmbeddingModel embeddingModel) {
        this.embeddingModel = embeddingModel;
    }

    @GetMapping("/ai/embedding")
    public Map embed(@RequestParam(value = "message", defaultValue = "Tell me a joke") String message) {
        EmbeddingResponse embeddingResponse = this.embeddingModel.embedForResponse(List.of(message));
        List<Embedding> embeddings = embeddingResponse.getResults();
        embeddings.forEach(k -> {
            float[] ff = k.getOutput();
            System.out.println(ff.length);
        });
        return Map.of("embedding", embeddingResponse);
    }
}

测试效果如下