package org.ruoyi.common.chat.demo.zhipu; import com.fasterxml.jackson.annotation.JsonInclude; import com.fasterxml.jackson.core.JsonProcessingException; import com.fasterxml.jackson.databind.DeserializationFeature; import com.fasterxml.jackson.databind.ObjectMapper; import com.fasterxml.jackson.databind.PropertyNamingStrategy; import com.zhipu.oapi.ClientV4; import com.zhipu.oapi.Constants; import com.zhipu.oapi.core.response.HttpxBinaryResponseContent; import com.zhipu.oapi.service.v4.batchs.BatchCreateParams; import com.zhipu.oapi.service.v4.batchs.BatchResponse; import com.zhipu.oapi.service.v4.batchs.QueryBatchResponse; import com.zhipu.oapi.service.v4.embedding.EmbeddingApiResponse; import com.zhipu.oapi.service.v4.embedding.EmbeddingRequest; import com.zhipu.oapi.service.v4.file.*; import com.zhipu.oapi.service.v4.fine_turning.*; import com.zhipu.oapi.service.v4.image.CreateImageRequest; import com.zhipu.oapi.service.v4.image.ImageApiResponse; import com.zhipu.oapi.service.v4.model.*; import io.reactivex.Flowable; import org.junit.Test; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import java.io.IOException; import java.util.ArrayList; import java.util.HashMap; import java.util.List; import java.util.Map; import java.util.concurrent.TimeUnit; import java.util.concurrent.atomic.AtomicBoolean; public class V4Test { private final static Logger logger = LoggerFactory.getLogger(V4Test.class); private static final String API_SECRET_KEY = "28550a39d4cfaabbbf38df04dd3931f5.IUvfTThUf0xBF5l0"; private static final ClientV4 client = new ClientV4.Builder(API_SECRET_KEY) .enableTokenCache() .networkConfig(300, 100, 100, 100, TimeUnit.SECONDS) .connectionPool(new okhttp3.ConnectionPool(8, 1, TimeUnit.SECONDS)) .build(); // 请自定义自己的业务id private static final String requestIdTemplate = "mycompany-%d"; private static final ObjectMapper mapper = new ObjectMapper(); public static ObjectMapper defaultObjectMapper() { ObjectMapper mapper = new ObjectMapper(); mapper.configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false); mapper.setSerializationInclusion(JsonInclude.Include.NON_NULL); mapper.setPropertyNamingStrategy(PropertyNamingStrategy.SNAKE_CASE); return mapper; } @Test public void test() { } /** * sse-V4：function调用 */ @Test public void testFunctionSSE() throws JsonProcessingException { List messages = new ArrayList<>(); ChatMessage chatMessage = new ChatMessage(ChatMessageRole.USER.value(), "成都到北京要多久，天气如何"); messages.add(chatMessage); String requestId = String.format(requestIdTemplate, System.currentTimeMillis()); // 函数调用参数构建部分 List chatToolList = new ArrayList<>(); ChatTool chatTool = new ChatTool(); chatTool.setType(ChatToolType.FUNCTION.value()); ChatFunctionParameters chatFunctionParameters = new ChatFunctionParameters(); chatFunctionParameters.setType("object"); Map properties = new HashMap<>(); properties.put("location", new HashMap() {{ put("type", "string"); put("description", "城市，如：北京"); }}); properties.put("unit", new HashMap() {{ put("type", "string"); put("enum", new ArrayList() {{ 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); HashMap extraJson = new HashMap<>(); extraJson.put("temperature", 0.5); extraJson.put("max_tokens", 50); ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder() .model(Constants.ModelChatGLM4) .stream(Boolean.TRUE) .messages(messages) .requestId(requestId) .tools(chatToolList) .toolChoice("auto") .extraJson(extraJson) .build(); ModelApiResponse sseModelApiResp = client.invokeModelApi(chatCompletionRequest); if (sseModelApiResp.isSuccess()) { AtomicBoolean isFirst = new AtomicBoolean(true); List choices = new ArrayList<>(); ChatMessageAccumulator chatMessageAccumulator = mapStreamToAccumulator(sseModelApiResp.getFlowable()) .doOnNext(accumulator -> { { if (isFirst.getAndSet(false)) { logger.info("Response: "); } if (accumulator.getDelta() != null && accumulator.getDelta().getTool_calls() != null) { String jsonString = mapper.writeValueAsString(accumulator.getDelta().getTool_calls()); logger.info("tool_calls: {}", jsonString); } if (accumulator.getDelta() != null && accumulator.getDelta().getContent() != null) { logger.info(accumulator.getDelta().getContent()); } choices.add(accumulator.getChoice()); } }) .doOnComplete(System.out::println) .lastElement() .blockingGet(); ModelData data = new ModelData(); data.setChoices(choices); data.setUsage(chatMessageAccumulator.getUsage()); data.setId(chatMessageAccumulator.getId()); data.setCreated(chatMessageAccumulator.getCreated()); data.setRequestId(chatCompletionRequest.getRequestId()); sseModelApiResp.setFlowable(null);// 打印前置空 sseModelApiResp.setData(data); } logger.info("model output: {}", mapper.writeValueAsString(sseModelApiResp)); } /** * sse-V4：非function调用 */ @Test public void testNonFunctionSSE() throws JsonProcessingException { List messages = new ArrayList<>(); ChatMessage chatMessage = new ChatMessage(ChatMessageRole.USER.value(), "ChatGLM和你哪个更强大"); messages.add(chatMessage); HashMap extraJson = new HashMap<>(); extraJson.put("temperature", 0.5); extraJson.put("max_tokens", 3); String requestId = String.format(requestIdTemplate, System.currentTimeMillis()); ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder() .model(Constants.ModelChatGLM4) .stream(Boolean.TRUE) .messages(messages) .requestId(requestId) .extraJson(extraJson) .build(); ModelApiResponse sseModelApiResp = client.invokeModelApi(chatCompletionRequest); // stream 处理方法 if (sseModelApiResp.isSuccess()) { AtomicBoolean isFirst = new AtomicBoolean(true); List choices = new ArrayList<>(); ChatMessageAccumulator chatMessageAccumulator = mapStreamToAccumulator(sseModelApiResp.getFlowable()) .doOnNext(accumulator -> { { if (isFirst.getAndSet(false)) { logger.info("Response: "); } if (accumulator.getDelta() != null && accumulator.getDelta().getTool_calls() != null) { String jsonString = mapper.writeValueAsString(accumulator.getDelta().getTool_calls()); logger.info("tool_calls: {}", jsonString); } if (accumulator.getDelta() != null && accumulator.getDelta().getContent() != null) { logger.info("accumulator.getDelta().getContent(): {}", accumulator.getDelta().getContent()); } choices.add(accumulator.getChoice()); } }) .doOnComplete(System.out::println) .lastElement() .blockingGet(); ModelData data = new ModelData(); data.setChoices(choices); data.setUsage(chatMessageAccumulator.getUsage()); data.setId(chatMessageAccumulator.getId()); data.setCreated(chatMessageAccumulator.getCreated()); data.setRequestId(chatCompletionRequest.getRequestId()); sseModelApiResp.setFlowable(null);// 打印前置空 sseModelApiResp.setData(data); } logger.info("model output: {}", mapper.writeValueAsString(sseModelApiResp)); } /** * V4-同步function调用 */ @Test public void testFunctionInvoke() { List messages = new ArrayList<>(); ChatMessage chatMessage = new ChatMessage(ChatMessageRole.USER.value(), "你可以做什么"); messages.add(chatMessage); String requestId = String.format(requestIdTemplate, System.currentTimeMillis()); // 函数调用参数构建部分 List chatToolList = new ArrayList<>(); ChatTool chatTool = new ChatTool(); chatTool.setType(ChatToolType.FUNCTION.value()); ChatFunctionParameters chatFunctionParameters = new ChatFunctionParameters(); chatFunctionParameters.setType("object"); Map properties = new HashMap<>(); properties.put("location", new HashMap() {{ put("type", "string"); put("description", "城市，如：北京"); }}); properties.put("unit", new HashMap() {{ put("type", "string"); put("enum", new ArrayList() {{ 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); ChatTool chatTool1 = new ChatTool(); chatTool1.setType(ChatToolType.WEB_SEARCH.value()); WebSearch webSearch = new WebSearch(); webSearch.setSearch_query("清华的升学率"); webSearch.setSearch_result(true); webSearch.setEnable(false); chatTool1.setWeb_search(webSearch); chatToolList.add(chatTool); chatToolList.add(chatTool1); ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder() .model(Constants.ModelChatGLM4) .stream(Boolean.FALSE) .invokeMethod(Constants.invokeMethod) .messages(messages) .requestId(requestId) .tools(chatToolList) .toolChoice("auto") .build(); ModelApiResponse invokeModelApiResp = client.invokeModelApi(chatCompletionRequest); try { logger.info("model output: {}", mapper.writeValueAsString(invokeModelApiResp)); } catch (JsonProcessingException e) { logger.error("model output error", e); } } /** * V4-同步非function调用 */ @Test public void testNonFunctionInvoke() throws JsonProcessingException { List 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()); HashMap extraJson = new HashMap<>(); extraJson.put("temperature", 0.5); extraJson.put("max_tokens", 3); ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder() .model(Constants.ModelChatGLM4) .stream(Boolean.FALSE) .invokeMethod(Constants.invokeMethod) .messages(messages) .requestId(requestId) .extraJson(extraJson) .build(); ModelApiResponse invokeModelApiResp = client.invokeModelApi(chatCompletionRequest); logger.info("model output: {}", mapper.writeValueAsString(invokeModelApiResp)); } /** * V4-同步非function调用 */ @Test public void testCharGlmInvoke() throws JsonProcessingException { List 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()); HashMap extraJson = new HashMap<>(); extraJson.put("temperature", 0.5); ChatMeta meta = new ChatMeta(); 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。"); 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。"); meta.setBot_name("苏梦远"); meta.setUser_name("陆星辰"); ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder() .model(Constants.ModelCharGLM3) .stream(Boolean.FALSE) .invokeMethod(Constants.invokeMethod) .messages(messages) .requestId(requestId) .meta(meta) .extraJson(extraJson) .build(); ModelApiResponse invokeModelApiResp = client.invokeModelApi(chatCompletionRequest); logger.info("model output: {}", mapper.writeValueAsString(invokeModelApiResp)); } /** * V4异步调用 */ @Test public void testAsyncInvoke() throws JsonProcessingException { String taskId = getAsyncTaskId(); testQueryResult(taskId); } // /** * 文生图 */ @Test public void testCreateImage() throws JsonProcessingException { CreateImageRequest createImageRequest = new CreateImageRequest(); createImageRequest.setModel(Constants.ModelCogView); createImageRequest.setPrompt("Futuristic cloud data center, showcasing advanced technologgy and a high-tech atmosp\n" + "here. The image should depict a spacious, well-lit interior with rows of server racks, glo\n" + "wing lights, and digital displays. Include abstract representattions of data streams and\n" + "onnectivity, symbolizing the essence of cloud computing. Thee style should be modern a\n" + "nd sleek, with a focus on creating a sense of innovaticon and cutting-edge technology\n" + "The overall ambiance should convey the power and effciency of cloud services in a visu\n" + "ally engaging way."); createImageRequest.setRequestId("test11111111111111"); ImageApiResponse imageApiResponse = client.createImage(createImageRequest); logger.info("imageApiResponse: {}", mapper.writeValueAsString(imageApiResponse)); } // // /** // * 图生文 // */ // @Test // public void testImageToWord() throws JsonProcessingException { // List messages = new ArrayList<>(); // List> contentList = new ArrayList<>(); // Map textMap = new HashMap<>(); // textMap.put("type", "text"); // textMap.put("text", "图里有什么"); // Map typeMap = new HashMap<>(); // typeMap.put("type", "image_url"); // Map urlMap = new HashMap<>(); // urlMap.put("url", "https://sfile.chatglm.cn/testpath/275ae5b6-5390-51ca-a81a-60332d1a7cac_0.png"); // typeMap.put("image_url", urlMap); // contentList.add(textMap); // contentList.add(typeMap); // ChatMessage chatMessage = new ChatMessage(ChatMessageRole.USER.value(), contentList); // messages.add(chatMessage); // String requestId = String.format(requestIdTemplate, System.currentTimeMillis()); // // // ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder() // .model(Constants.ModelChatGLM4V) // .stream(Boolean.FALSE) // .invokeMethod(Constants.invokeMethod) // .messages(messages) // .requestId(requestId) // .build(); // ModelApiResponse modelApiResponse = client.invokeModelApi(chatCompletionRequest); // logger.info("model output: {}", mapper.writeValueAsString(modelApiResponse)); // } // /** * 向量模型V4 */ @Test public void testEmbeddings() throws JsonProcessingException { EmbeddingRequest embeddingRequest = new EmbeddingRequest(); embeddingRequest.setInput("hello world"); embeddingRequest.setModel(Constants.ModelEmbedding2); EmbeddingApiResponse apiResponse = client.invokeEmbeddingsApi(embeddingRequest); logger.info("model output: {}", mapper.writeValueAsString(apiResponse)); } /** * V4微调上传数据集 */ @Test public void testUploadFile() throws JsonProcessingException { String filePath = "demo.jsonl"; String path = ClassLoader.getSystemResource(filePath).getPath(); String purpose = "fine-tune"; UploadFileRequest request = UploadFileRequest.builder() .purpose(purpose) .filePath(path) .build(); FileApiResponse fileApiResponse = client.invokeUploadFileApi(request); logger.info("model output: {}", mapper.writeValueAsString(fileApiResponse)); } /** * 微调V4-查询上传文件列表 */ @Test public void testQueryUploadFileList() throws JsonProcessingException { QueryFilesRequest queryFilesRequest = new QueryFilesRequest(); QueryFileApiResponse queryFileApiResponse = client.queryFilesApi(queryFilesRequest); logger.info("model output: {}", mapper.writeValueAsString(queryFileApiResponse)); } @Test public void testFileContent() throws IOException { try { HttpxBinaryResponseContent httpxBinaryResponseContent = client.fileContent("20240514_ea19d21b-d256-4586-b0df-e80a45e3c286"); String filePath = "demo_output.jsonl"; String resourcePath = V4Test.class.getClassLoader().getResource("").getPath(); httpxBinaryResponseContent.streamToFile(resourcePath + "1" + filePath, 1000); } catch (IOException e) { logger.error("file content error", e); } } //// @Test //// public void deletedFile() throws IOException { //// FileDelResponse fileDelResponse = client.deletedFile("20240514_ea19d21b-d256-4586-b0df-e80a45e3c286"); //// //// logger.info("model output: {}", mapper.writeValueAsString(fileDelResponse)); //// //// } // // /** * 微调V4-创建微调任务 */ @Test public void testCreateFineTuningJob() throws JsonProcessingException { FineTuningJobRequest request = new FineTuningJobRequest(); String requestId = String.format(requestIdTemplate, System.currentTimeMillis()); request.setRequestId(requestId); request.setModel("chatglm3-6b"); request.setTraining_file("file-20240118082608327-kp8qr"); CreateFineTuningJobApiResponse createFineTuningJobApiResponse = client.createFineTuningJob(request); logger.info("model output: {}", mapper.writeValueAsString(createFineTuningJobApiResponse)); } /** * 微调V4-查询微调任务 */ @Test public void testRetrieveFineTuningJobs() throws JsonProcessingException { QueryFineTuningJobRequest queryFineTuningJobRequest = new QueryFineTuningJobRequest(); queryFineTuningJobRequest.setJobId("ftjob-20240429172916475-fb7r9"); // queryFineTuningJobRequest.setLimit(1); // queryFineTuningJobRequest.setAfter(1); QueryFineTuningJobApiResponse queryFineTuningJobApiResponse = client.retrieveFineTuningJobs(queryFineTuningJobRequest); logger.info("model output: {}", mapper.writeValueAsString(queryFineTuningJobApiResponse)); } /** * 微调V4-查询微调任务 */ @Test public void testFueryFineTuningJobsEvents() throws JsonProcessingException { QueryFineTuningJobRequest queryFineTuningJobRequest = new QueryFineTuningJobRequest(); queryFineTuningJobRequest.setJobId("ftjob-20240429172916475-fb7r9"); QueryFineTuningEventApiResponse queryFineTuningEventApiResponse = client.queryFineTuningJobsEvents(queryFineTuningJobRequest); logger.info("model output: {}", mapper.writeValueAsString(queryFineTuningEventApiResponse)); } /** * testQueryPersonalFineTuningJobs V4-查询个人微调任务 */ @Test public void testQueryPersonalFineTuningJobs() throws JsonProcessingException { QueryPersonalFineTuningJobRequest queryPersonalFineTuningJobRequest = new QueryPersonalFineTuningJobRequest(); queryPersonalFineTuningJobRequest.setLimit(1); QueryPersonalFineTuningJobApiResponse queryPersonalFineTuningJobApiResponse = client.queryPersonalFineTuningJobs(queryPersonalFineTuningJobRequest); logger.info("model output: {}", mapper.writeValueAsString(queryPersonalFineTuningJobApiResponse)); } @Test public void testBatchesCreate() { BatchCreateParams batchCreateParams = new BatchCreateParams( "24h", "/v4/chat/completions", "20240514_ea19d21b-d256-4586-b0df-e80a45e3c286", new HashMap() {{ put("key1", "value1"); put("key2", "value2"); }} ); BatchResponse batchResponse = client.batchesCreate(batchCreateParams); 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 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 chatToolList = new ArrayList<>(); ChatTool chatTool = new ChatTool(); chatTool.setType(ChatToolType.FUNCTION.value()); ChatFunctionParameters chatFunctionParameters = new ChatFunctionParameters(); chatFunctionParameters.setType("object"); Map properties = new HashMap<>(); properties.put("location", new HashMap() {{ put("type", "string"); put("description", "城市，如：北京"); }}); properties.put("unit", new HashMap() {{ put("type", "string"); put("enum", new ArrayList() {{ 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 mapStreamToAccumulator(Flowable flowable) { return flowable.map(chunk -> { return new ChatMessageAccumulator(chunk.getChoices().get(0).getDelta(), null, chunk.getChoices().get(0), chunk.getUsage(), chunk.getCreated(), chunk.getId()); }); } }