package org.ruoyi.common.chat.demo.zhipu;
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import com.fasterxml.jackson.annotation.JsonInclude;
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import com.fasterxml.jackson.core.JsonProcessingException;
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import com.fasterxml.jackson.databind.DeserializationFeature;
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import com.fasterxml.jackson.databind.ObjectMapper;
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import com.fasterxml.jackson.databind.PropertyNamingStrategy;
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import com.zhipu.oapi.ClientV4;
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import com.zhipu.oapi.Constants;
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import com.zhipu.oapi.core.response.HttpxBinaryResponseContent;
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import com.zhipu.oapi.service.v4.batchs.BatchCreateParams;
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import com.zhipu.oapi.service.v4.batchs.BatchResponse;
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import com.zhipu.oapi.service.v4.batchs.QueryBatchResponse;
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import com.zhipu.oapi.service.v4.embedding.EmbeddingApiResponse;
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import com.zhipu.oapi.service.v4.embedding.EmbeddingRequest;
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import com.zhipu.oapi.service.v4.file.*;
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import com.zhipu.oapi.service.v4.fine_turning.*;
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import com.zhipu.oapi.service.v4.image.CreateImageRequest;
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import com.zhipu.oapi.service.v4.image.ImageApiResponse;
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import com.zhipu.oapi.service.v4.model.*;
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import io.reactivex.Flowable;
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import org.junit.Test;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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import java.io.IOException;
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import java.util.ArrayList;
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import java.util.HashMap;
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import java.util.List;
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import java.util.Map;
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import java.util.concurrent.TimeUnit;
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import java.util.concurrent.atomic.AtomicBoolean;
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public class V4Test {
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private final static Logger logger = LoggerFactory.getLogger(V4Test.class);
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private static final String API_SECRET_KEY = "28550a39d4cfaabbbf38df04dd3931f5.IUvfTThUf0xBF5l0";
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private static final ClientV4 client = new ClientV4.Builder(API_SECRET_KEY)
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.enableTokenCache()
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.networkConfig(300, 100, 100, 100, TimeUnit.SECONDS)
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.connectionPool(new okhttp3.ConnectionPool(8, 1, TimeUnit.SECONDS))
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.build();
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// 请自定义自己的业务id
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private static final String requestIdTemplate = "mycompany-%d";
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private static final ObjectMapper mapper = new ObjectMapper();
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public static ObjectMapper defaultObjectMapper() {
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ObjectMapper mapper = new ObjectMapper();
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mapper.configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false);
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mapper.setSerializationInclusion(JsonInclude.Include.NON_NULL);
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mapper.setPropertyNamingStrategy(PropertyNamingStrategy.SNAKE_CASE);
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return mapper;
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}
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@Test
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public void test() {
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}
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/**
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* sse-V4：function调用
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*/
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@Test
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public void testFunctionSSE() throws JsonProcessingException {
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List<ChatMessage> messages = new ArrayList<>();
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ChatMessage chatMessage = new ChatMessage(ChatMessageRole.USER.value(), "成都到北京要多久，天气如何");
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messages.add(chatMessage);
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String requestId = String.format(requestIdTemplate, System.currentTimeMillis());
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// 函数调用参数构建部分
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List<ChatTool> chatToolList = new ArrayList<>();
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ChatTool chatTool = new ChatTool();
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chatTool.setType(ChatToolType.FUNCTION.value());
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ChatFunctionParameters chatFunctionParameters = new ChatFunctionParameters();
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chatFunctionParameters.setType("object");
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Map<String, Object> properties = new HashMap<>();
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properties.put("location", new HashMap<String, Object>() {{
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put("type", "string");
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put("description", "城市，如：北京");
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}});
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properties.put("unit", new HashMap<String, Object>() {{
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put("type", "string");
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put("enum", new ArrayList<String>() {{
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add("celsius");
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add("fahrenheit");
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}});
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}});
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chatFunctionParameters.setProperties(properties);
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ChatFunction chatFunction = ChatFunction.builder()
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.name("get_weather")
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.description("Get the current weather of a location")
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.parameters(chatFunctionParameters)
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.build();
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chatTool.setFunction(chatFunction);
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chatToolList.add(chatTool);
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HashMap<String, Object> extraJson = new HashMap<>();
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extraJson.put("temperature", 0.5);
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extraJson.put("max_tokens", 50);
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ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder()
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.model(Constants.ModelChatGLM4)
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.stream(Boolean.TRUE)
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.messages(messages)
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.requestId(requestId)
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.tools(chatToolList)
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.toolChoice("auto")
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.extraJson(extraJson)
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.build();
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ModelApiResponse sseModelApiResp = client.invokeModelApi(chatCompletionRequest);
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if (sseModelApiResp.isSuccess()) {
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AtomicBoolean isFirst = new AtomicBoolean(true);
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List<Choice> choices = new ArrayList<>();
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ChatMessageAccumulator chatMessageAccumulator = mapStreamToAccumulator(sseModelApiResp.getFlowable())
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.doOnNext(accumulator -> {
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{
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if (isFirst.getAndSet(false)) {
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logger.info("Response: ");
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}
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if (accumulator.getDelta() != null && accumulator.getDelta().getTool_calls() != null) {
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String jsonString = mapper.writeValueAsString(accumulator.getDelta().getTool_calls());
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logger.info("tool_calls: {}", jsonString);
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}
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if (accumulator.getDelta() != null && accumulator.getDelta().getContent() != null) {
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logger.info(accumulator.getDelta().getContent());
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}
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choices.add(accumulator.getChoice());
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}
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})
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.doOnComplete(System.out::println)
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.lastElement()
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.blockingGet();
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ModelData data = new ModelData();
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data.setChoices(choices);
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data.setUsage(chatMessageAccumulator.getUsage());
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data.setId(chatMessageAccumulator.getId());
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data.setCreated(chatMessageAccumulator.getCreated());
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data.setRequestId(chatCompletionRequest.getRequestId());
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sseModelApiResp.setFlowable(null);// 打印前置空
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sseModelApiResp.setData(data);
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}
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logger.info("model output: {}", mapper.writeValueAsString(sseModelApiResp));
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}
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/**
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* sse-V4：非function调用
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*/
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@Test
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public void testNonFunctionSSE() throws JsonProcessingException {
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List<ChatMessage> messages = new ArrayList<>();
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ChatMessage chatMessage = new ChatMessage(ChatMessageRole.USER.value(), "ChatGLM和你哪个更强大");
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messages.add(chatMessage);
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HashMap<String, Object> extraJson = new HashMap<>();
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extraJson.put("temperature", 0.5);
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extraJson.put("max_tokens", 3);
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String requestId = String.format(requestIdTemplate, System.currentTimeMillis());
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ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder()
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.model(Constants.ModelChatGLM4)
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.stream(Boolean.TRUE)
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.messages(messages)
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.requestId(requestId)
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.extraJson(extraJson)
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.build();
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ModelApiResponse sseModelApiResp = client.invokeModelApi(chatCompletionRequest);
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// stream 处理方法
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if (sseModelApiResp.isSuccess()) {
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AtomicBoolean isFirst = new AtomicBoolean(true);
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List<Choice> choices = new ArrayList<>();
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ChatMessageAccumulator chatMessageAccumulator = mapStreamToAccumulator(sseModelApiResp.getFlowable())
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.doOnNext(accumulator -> {
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{
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if (isFirst.getAndSet(false)) {
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logger.info("Response: ");
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}
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if (accumulator.getDelta() != null && accumulator.getDelta().getTool_calls() != null) {
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String jsonString = mapper.writeValueAsString(accumulator.getDelta().getTool_calls());
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logger.info("tool_calls: {}", jsonString);
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}
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if (accumulator.getDelta() != null && accumulator.getDelta().getContent() != null) {
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logger.info("accumulator.getDelta().getContent(): {}", accumulator.getDelta().getContent());
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}
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choices.add(accumulator.getChoice());
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}
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})
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.doOnComplete(System.out::println)
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.lastElement()
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.blockingGet();
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ModelData data = new ModelData();
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data.setChoices(choices);
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data.setUsage(chatMessageAccumulator.getUsage());
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data.setId(chatMessageAccumulator.getId());
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data.setCreated(chatMessageAccumulator.getCreated());
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data.setRequestId(chatCompletionRequest.getRequestId());
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sseModelApiResp.setFlowable(null);// 打印前置空
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sseModelApiResp.setData(data);
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}
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logger.info("model output: {}", mapper.writeValueAsString(sseModelApiResp));
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}
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/**
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* V4-同步function调用
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*/
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@Test
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public void testFunctionInvoke() {
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List<ChatMessage> messages = new ArrayList<>();
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ChatMessage chatMessage = new ChatMessage(ChatMessageRole.USER.value(), "你可以做什么");
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messages.add(chatMessage);
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String requestId = String.format(requestIdTemplate, System.currentTimeMillis());
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// 函数调用参数构建部分
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List<ChatTool> chatToolList = new ArrayList<>();
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ChatTool chatTool = new ChatTool();
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chatTool.setType(ChatToolType.FUNCTION.value());
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ChatFunctionParameters chatFunctionParameters = new ChatFunctionParameters();
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chatFunctionParameters.setType("object");
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Map<String, Object> properties = new HashMap<>();
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properties.put("location", new HashMap<String, Object>() {{
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put("type", "string");
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put("description", "城市，如：北京");
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}});
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properties.put("unit", new HashMap<String, Object>() {{
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put("type", "string");
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put("enum", new ArrayList<String>() {{
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add("celsius");
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add("fahrenheit");
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}});
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}});
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chatFunctionParameters.setProperties(properties);
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ChatFunction chatFunction = ChatFunction.builder()
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.name("get_weather")
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.description("Get the current weather of a location")
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.parameters(chatFunctionParameters)
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.build();
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chatTool.setFunction(chatFunction);
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ChatTool chatTool1 = new ChatTool();
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chatTool1.setType(ChatToolType.WEB_SEARCH.value());
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WebSearch webSearch = new WebSearch();
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webSearch.setSearch_query("清华的升学率");
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webSearch.setSearch_result(true);
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webSearch.setEnable(false);
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chatTool1.setWeb_search(webSearch);
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chatToolList.add(chatTool);
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chatToolList.add(chatTool1);
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ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder()
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.model(Constants.ModelChatGLM4)
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.stream(Boolean.FALSE)
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.invokeMethod(Constants.invokeMethod)
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.messages(messages)
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.requestId(requestId)
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.tools(chatToolList)
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.toolChoice("auto")
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.build();
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ModelApiResponse invokeModelApiResp = client.invokeModelApi(chatCompletionRequest);
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try {
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logger.info("model output: {}", mapper.writeValueAsString(invokeModelApiResp));
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} catch (JsonProcessingException e) {
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logger.error("model output error", e);
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}
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}
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/**
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* V4-同步非function调用
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*/
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@Test
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public void testNonFunctionInvoke() throws JsonProcessingException {
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List<ChatMessage> messages = new ArrayList<>();
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ChatMessage chatMessage = new ChatMessage(ChatMessageRole.USER.value(), "ChatGLM和你哪个更强大");
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messages.add(chatMessage);
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String requestId = String.format(requestIdTemplate, System.currentTimeMillis());
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HashMap<String, Object> extraJson = new HashMap<>();
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extraJson.put("temperature", 0.5);
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extraJson.put("max_tokens", 3);
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ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder()
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.model(Constants.ModelChatGLM4)
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.stream(Boolean.FALSE)
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.invokeMethod(Constants.invokeMethod)
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.messages(messages)
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.requestId(requestId)
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.extraJson(extraJson)
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.build();
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ModelApiResponse invokeModelApiResp = client.invokeModelApi(chatCompletionRequest);
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logger.info("model output: {}", mapper.writeValueAsString(invokeModelApiResp));
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}
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/**
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* V4-同步非function调用
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*/
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@Test
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public void testCharGlmInvoke() throws JsonProcessingException {
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List<ChatMessage> messages = new ArrayList<>();
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ChatMessage chatMessage = new ChatMessage(ChatMessageRole.USER.value(), "ChatGLM和你哪个更强大");
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messages.add(chatMessage);
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String requestId = String.format(requestIdTemplate, System.currentTimeMillis());
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HashMap<String, Object> extraJson = new HashMap<>();
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extraJson.put("temperature", 0.5);
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ChatMeta meta = new ChatMeta();
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meta.setUser_info("我是陆星辰，是一个男性，是一位知名导演，也是苏梦远的合作导演。我擅长拍摄音乐题材的电影。苏梦远对我的态度是尊敬的，并视我为良师益友。");
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meta.setBot_info("苏梦远，本名苏远心，是一位当红的国内女歌手及演员。在参加选秀节目后，凭借独特的嗓音及出众的舞台魅力迅速成名，进入娱乐圈。她外表美丽动人，但真正的魅力在于她的才华和勤奋。苏梦远是音乐学院毕业的优秀生，善于创作，拥有多首热门原创歌曲。除了音乐方面的成就，她还热衷于慈善事业，积极参加公益活动，用实际行动传递正能量。在工作中，她对待工作非常敬业，拍戏时总是全身心投入角色，赢得了业内人士的赞誉和粉丝的喜爱。虽然在娱乐圈，但她始终保持低调、谦逊的态度，深得同行尊重。在表达时，苏梦远喜欢使用“我们”和“一起”，强调团队精神。");
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meta.setBot_name("苏梦远");
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meta.setUser_name("陆星辰");
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ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder()
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.model(Constants.ModelCharGLM3)
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.stream(Boolean.FALSE)
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.invokeMethod(Constants.invokeMethod)
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.messages(messages)
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.requestId(requestId)
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.meta(meta)
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.extraJson(extraJson)
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.build();
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ModelApiResponse invokeModelApiResp = client.invokeModelApi(chatCompletionRequest);
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logger.info("model output: {}", mapper.writeValueAsString(invokeModelApiResp));
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}
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/**
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* V4异步调用
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*/
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@Test
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public void testAsyncInvoke() throws JsonProcessingException {
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String taskId = getAsyncTaskId();
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testQueryResult(taskId);
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}
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//
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/**
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* 文生图
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*/
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@Test
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public void testCreateImage() throws JsonProcessingException {
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CreateImageRequest createImageRequest = new CreateImageRequest();
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createImageRequest.setModel(Constants.ModelCogView);
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createImageRequest.setPrompt("Futuristic cloud data center, showcasing advanced technologgy and a high-tech atmosp\n" +
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"here. The image should depict a spacious, well-lit interior with rows of server racks, glo\n" +
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"wing lights, and digital displays. Include abstract representattions of data streams and\n" +
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"onnectivity, symbolizing the essence of cloud computing. Thee style should be modern a\n" +
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"nd sleek, with a focus on creating a sense of innovaticon and cutting-edge technology\n" +
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"The overall ambiance should convey the power and effciency of cloud services in a visu\n" +
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"ally engaging way.");
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createImageRequest.setRequestId("test11111111111111");
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ImageApiResponse imageApiResponse = client.createImage(createImageRequest);
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logger.info("imageApiResponse: {}", mapper.writeValueAsString(imageApiResponse));
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}
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//
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// /**
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// * 图生文
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// */
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// @Test
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// public void testImageToWord() throws JsonProcessingException {
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// List<ChatMessage> messages = new ArrayList<>();
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// List<Map<String, Object>> contentList = new ArrayList<>();
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// Map<String, Object> textMap = new HashMap<>();
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// textMap.put("type", "text");
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// textMap.put("text", "图里有什么");
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// Map<String, Object> typeMap = new HashMap<>();
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// typeMap.put("type", "image_url");
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// Map<String, Object> urlMap = new HashMap<>();
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// urlMap.put("url", "https://sfile.chatglm.cn/testpath/275ae5b6-5390-51ca-a81a-60332d1a7cac_0.png");
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// typeMap.put("image_url", urlMap);
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// contentList.add(textMap);
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// contentList.add(typeMap);
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// ChatMessage chatMessage = new ChatMessage(ChatMessageRole.USER.value(), contentList);
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// messages.add(chatMessage);
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// String requestId = String.format(requestIdTemplate, System.currentTimeMillis());
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//
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//
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// ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder()
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// .model(Constants.ModelChatGLM4V)
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// .stream(Boolean.FALSE)
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// .invokeMethod(Constants.invokeMethod)
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// .messages(messages)
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// .requestId(requestId)
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// .build();
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// ModelApiResponse modelApiResponse = client.invokeModelApi(chatCompletionRequest);
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// logger.info("model output: {}", mapper.writeValueAsString(modelApiResponse));
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// }
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//
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/**
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* 向量模型V4
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*/
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@Test
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public void testEmbeddings() throws JsonProcessingException {
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EmbeddingRequest embeddingRequest = new EmbeddingRequest();
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embeddingRequest.setInput("hello world");
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embeddingRequest.setModel(Constants.ModelEmbedding2);
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EmbeddingApiResponse apiResponse = client.invokeEmbeddingsApi(embeddingRequest);
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logger.info("model output: {}", mapper.writeValueAsString(apiResponse));
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}
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/**
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* V4微调上传数据集
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*/
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@Test
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public void testUploadFile() throws JsonProcessingException {
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String filePath = "demo.jsonl";
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String path = ClassLoader.getSystemResource(filePath).getPath();
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String purpose = "fine-tune";
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UploadFileRequest request = UploadFileRequest.builder()
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.purpose(purpose)
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.filePath(path)
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.build();
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FileApiResponse fileApiResponse = client.invokeUploadFileApi(request);
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logger.info("model output: {}", mapper.writeValueAsString(fileApiResponse));
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}
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/**
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* 微调V4-查询上传文件列表
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*/
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@Test
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public void testQueryUploadFileList() throws JsonProcessingException {
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QueryFilesRequest queryFilesRequest = new QueryFilesRequest();
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QueryFileApiResponse queryFileApiResponse = client.queryFilesApi(queryFilesRequest);
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logger.info("model output: {}", mapper.writeValueAsString(queryFileApiResponse));
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}
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@Test
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public void testFileContent() throws IOException {
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try {
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HttpxBinaryResponseContent httpxBinaryResponseContent = client.fileContent("20240514_ea19d21b-d256-4586-b0df-e80a45e3c286");
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String filePath = "demo_output.jsonl";
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String resourcePath = V4Test.class.getClassLoader().getResource("").getPath();
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httpxBinaryResponseContent.streamToFile(resourcePath + "1" + filePath, 1000);
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} catch (IOException e) {
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logger.error("file content error", e);
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}
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}
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//// @Test
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//// public void deletedFile() throws IOException {
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//// FileDelResponse fileDelResponse = client.deletedFile("20240514_ea19d21b-d256-4586-b0df-e80a45e3c286");
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////
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//// logger.info("model output: {}", mapper.writeValueAsString(fileDelResponse));
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////
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//// }
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//
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//
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/**
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* 微调V4-创建微调任务
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*/
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@Test
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public void testCreateFineTuningJob() throws JsonProcessingException {
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FineTuningJobRequest request = new FineTuningJobRequest();
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String requestId = String.format(requestIdTemplate, System.currentTimeMillis());
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request.setRequestId(requestId);
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request.setModel("chatglm3-6b");
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request.setTraining_file("file-20240118082608327-kp8qr");
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CreateFineTuningJobApiResponse createFineTuningJobApiResponse = client.createFineTuningJob(request);
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logger.info("model output: {}", mapper.writeValueAsString(createFineTuningJobApiResponse));
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}
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/**
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* 微调V4-查询微调任务
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*/
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@Test
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public void testRetrieveFineTuningJobs() throws JsonProcessingException {
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QueryFineTuningJobRequest queryFineTuningJobRequest = new QueryFineTuningJobRequest();
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queryFineTuningJobRequest.setJobId("ftjob-20240429172916475-fb7r9");
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// queryFineTuningJobRequest.setLimit(1);
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// queryFineTuningJobRequest.setAfter(1);
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QueryFineTuningJobApiResponse queryFineTuningJobApiResponse = client.retrieveFineTuningJobs(queryFineTuningJobRequest);
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logger.info("model output: {}", mapper.writeValueAsString(queryFineTuningJobApiResponse));
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}
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/**
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* 微调V4-查询微调任务
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*/
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@Test
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public void testFueryFineTuningJobsEvents() throws JsonProcessingException {
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QueryFineTuningJobRequest queryFineTuningJobRequest = new QueryFineTuningJobRequest();
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queryFineTuningJobRequest.setJobId("ftjob-20240429172916475-fb7r9");
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QueryFineTuningEventApiResponse queryFineTuningEventApiResponse = client.queryFineTuningJobsEvents(queryFineTuningJobRequest);
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logger.info("model output: {}", mapper.writeValueAsString(queryFineTuningEventApiResponse));
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}
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/**
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* testQueryPersonalFineTuningJobs V4-查询个人微调任务
|
*/
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@Test
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public void testQueryPersonalFineTuningJobs() throws JsonProcessingException {
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QueryPersonalFineTuningJobRequest queryPersonalFineTuningJobRequest = new QueryPersonalFineTuningJobRequest();
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queryPersonalFineTuningJobRequest.setLimit(1);
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QueryPersonalFineTuningJobApiResponse queryPersonalFineTuningJobApiResponse = client.queryPersonalFineTuningJobs(queryPersonalFineTuningJobRequest);
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logger.info("model output: {}", mapper.writeValueAsString(queryPersonalFineTuningJobApiResponse));
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}
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@Test
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public void testBatchesCreate() {
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BatchCreateParams batchCreateParams = new BatchCreateParams(
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"24h",
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"/v4/chat/completions",
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"20240514_ea19d21b-d256-4586-b0df-e80a45e3c286",
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new HashMap<String, String>() {{
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put("key1", "value1");
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put("key2", "value2");
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}}
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);
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BatchResponse batchResponse = client.batchesCreate(batchCreateParams);
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logger.info("output: {}", batchResponse);
|
// output: BatchResponse(code=200, msg=调用成功, success=true, data=Batch(id=batch_1791021399316246528, completionWindow=24h, createdAt=1715847751822, endpoint=/v4/chat/completions, inputFileId=20240514_ea19d21b-d256-4586-b0df-e80a45e3c286, object=batch, status=validating, cancelledAt=null, cancellingAt=null, completedAt=null, errorFileId=null, errors=null, expiredAt=null, expiresAt=null, failedAt=null, finalizingAt=null, inProgressAt=null, metadata={key1=value1, key2=value2}, outputFileId=null, requestCounts=BatchRequestCounts(completed=0, failed=0, total=0), error=null))
|
}
|
|
@Test
|
public void testDeleteFineTuningJob() {
|
FineTuningJobIdRequest request = FineTuningJobIdRequest.builder().jobId("test").build();
|
QueryFineTuningJobApiResponse queryFineTuningJobApiResponse = client.deleteFineTuningJob(request);
|
logger.info("output: {}", queryFineTuningJobApiResponse);
|
|
}
|
|
@Test
|
public void testCancelFineTuningJob() {
|
FineTuningJobIdRequest request = FineTuningJobIdRequest.builder().jobId("test").build();
|
QueryFineTuningJobApiResponse queryFineTuningJobApiResponse = client.cancelFineTuningJob(request);
|
logger.info("output: {}", queryFineTuningJobApiResponse);
|
|
}
|
|
@Test
|
public void testBatchesRetrieve() {
|
BatchResponse batchResponse = client.batchesRetrieve("batch_1791021399316246528");
|
logger.info("output: {}", batchResponse);
|
|
}
|
|
@Test
|
public void testDeleteFineTuningModel() {
|
FineTuningJobModelRequest request = FineTuningJobModelRequest.builder().fineTunedModel("test").build();
|
|
FineTunedModelsStatusResponse fineTunedModelsStatusResponse = client.deleteFineTuningModel(request);
|
logger.info("output: {}", fineTunedModelsStatusResponse);
|
// output: BatchResponse(code=200, msg=调用成功, success=true, data=Batch(id=batch_1791021399316246528, completionWindow=24h, createdAt=1715847752000, endpoint=/v4/chat/completions, inputFileId=20240514_ea19d21b-d256-4586-b0df-e80a45e3c286, object=batch, status=validating, cancelledAt=null, cancellingAt=null, completedAt=null, errorFileId=, errors=null, expiredAt=null, expiresAt=null, failedAt=null, finalizingAt=null, inProgressAt=null, metadata={key1=value1, key2=value2}, outputFileId=, requestCounts=BatchRequestCounts(completed=0, failed=0, total=0), error=null))
|
|
}
|
|
@Test
|
public void testBatchesList() {
|
QueryBatchRequest queryBatchRequest = new QueryBatchRequest();
|
queryBatchRequest.setLimit(10);
|
QueryBatchResponse queryBatchResponse = client.batchesList(queryBatchRequest);
|
logger.info("output: {}", queryBatchResponse);
|
// output: QueryBatchResponse(code=200, msg=调用成功, success=true, data=BatchPage(object=list, data=[Batch(id=batch_1790291013237211136, completionWindow=24h, createdAt=1715673614000, endpoint=/v4/chat/completions, inputFileId=20240514_ea19d21b-d256-4586-b0df-e80a45e3c286, object=batch, status=completed, cancelledAt=null, cancellingAt=1715673699000, completedAt=null, errorFileId=, errors=null, expiredAt=null, expiresAt=null, failedAt=null, finalizingAt=null, inProgressAt=null, metadata={description=job test}, outputFileId=, requestCounts=BatchRequestCounts(completed=0, failed=0, total=0), error=null), Batch(id=batch_1790292763050508288, completionWindow=24h, createdAt=1715674031000, endpoint=/v4/chat/completions, inputFileId=20240514_ea19d21b-d256-4586-b0df-e80a45e3c286, object=batch, status=completed, cancelledAt=null, cancellingAt=null, completedAt=1715766416000, errorFileId=, errors=null, expiredAt=null, expiresAt=null, failedAt=null, finalizingAt=1715754569000, inProgressAt=null, metadata={description=job test}, outputFileId=1715766415_e5a77222855a406ca8a082de28549c99, requestCounts=BatchRequestCounts(completed=2, failed=0, total=2), error=null), Batch(id=batch_1791021114887909376, completionWindow=24h, createdAt=1715847684000, endpoint=/v4/chat/completions, inputFileId=20240514_ea19d21b-d256-4586-b0df-e80a45e3c286, object=batch, status=validating, cancelledAt=null, cancellingAt=null, completedAt=null, errorFileId=, errors=null, expiredAt=null, expiresAt=null, failedAt=null, finalizingAt=null, inProgressAt=null, metadata={key1=value1, key2=value2}, outputFileId=, requestCounts=BatchRequestCounts(completed=0, failed=0, total=0), error=null), Batch(id=batch_1791021399316246528, completionWindow=24h, createdAt=1715847752000, endpoint=/v4/chat/completions, inputFileId=20240514_ea19d21b-d256-4586-b0df-e80a45e3c286, object=batch, status=validating, cancelledAt=null, cancellingAt=null, completedAt=null, errorFileId=, errors=null, expiredAt=null, expiresAt=null, failedAt=null, finalizingAt=null, inProgressAt=null, metadata={key1=value1, key2=value2}, outputFileId=, requestCounts=BatchRequestCounts(completed=0, failed=0, total=0), error=null)], error=null))
|
|
}
|
|
@Test
|
public void testBatchesCancel() throws JsonProcessingException {
|
getAsyncTaskId();
|
}
|
|
private static String getAsyncTaskId() throws JsonProcessingException {
|
List<ChatMessage> messages = new ArrayList<>();
|
ChatMessage chatMessage = new ChatMessage(ChatMessageRole.USER.value(), "ChatGLM和你哪个更强大");
|
messages.add(chatMessage);
|
String requestId = String.format(requestIdTemplate, System.currentTimeMillis());
|
// 函数调用参数构建部分
|
List<ChatTool> chatToolList = new ArrayList<>();
|
ChatTool chatTool = new ChatTool();
|
chatTool.setType(ChatToolType.FUNCTION.value());
|
ChatFunctionParameters chatFunctionParameters = new ChatFunctionParameters();
|
chatFunctionParameters.setType("object");
|
Map<String, Object> properties = new HashMap<>();
|
properties.put("location", new HashMap<String, Object>() {{
|
put("type", "string");
|
put("description", "城市，如：北京");
|
}});
|
properties.put("unit", new HashMap<String, Object>() {{
|
put("type", "string");
|
put("enum", new ArrayList<String>() {{
|
add("celsius");
|
add("fahrenheit");
|
}});
|
}});
|
chatFunctionParameters.setProperties(properties);
|
ChatFunction chatFunction = ChatFunction.builder()
|
.name("get_weather")
|
.description("Get the current weather of a location")
|
.parameters(chatFunctionParameters)
|
.build();
|
chatTool.setFunction(chatFunction);
|
chatToolList.add(chatTool);
|
ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder()
|
.model(Constants.ModelChatGLM4)
|
.stream(Boolean.FALSE)
|
.invokeMethod(Constants.invokeMethodAsync)
|
.messages(messages)
|
.requestId(requestId)
|
.tools(chatToolList)
|
.toolChoice("auto")
|
.build();
|
ModelApiResponse invokeModelApiResp = client.invokeModelApi(chatCompletionRequest);
|
logger.info("model output: {}", mapper.writeValueAsString(invokeModelApiResp));
|
return invokeModelApiResp.getData().getId();
|
}
|
|
|
private static void testQueryResult(String taskId) throws JsonProcessingException {
|
QueryModelResultRequest request = new QueryModelResultRequest();
|
request.setTaskId(taskId);
|
QueryModelResultResponse queryResultResp = client.queryModelResult(request);
|
logger.info("model output {}", mapper.writeValueAsString(queryResultResp));
|
}
|
|
public static Flowable<ChatMessageAccumulator> mapStreamToAccumulator(Flowable<ModelData> flowable) {
|
return flowable.map(chunk -> {
|
return new ChatMessageAccumulator(chunk.getChoices().get(0).getDelta(), null, chunk.getChoices().get(0), chunk.getUsage(), chunk.getCreated(), chunk.getId());
|
});
|
}
|
}
|
