【SpringAI实战】实现仿DeepSeek页面对话机器人(支持多模态上传)

一、前言

二、实现效果

三、代码实现

        3.1 后端代码

        3.2 前端代码

一、前言

Spring AI详解：【Spring AI详解】开启Java生态的智能应用开发新时代(附不同功能的Spring AI实战项目)-CSDN博客

二、实现效果

可上传图片或音频数据给大模型分析

三、代码实现

3.1 后端代码

pom.xml

   org.springframework.boot spring-boot-starter-parent 3.4.3       17  1.0.0-M6       org.springframework.boot spring-boot-starter-web    org.springframework.ai spring-ai-ollama-spring-boot-starter    org.springframework.ai spring-ai-openai-spring-boot-starter     org.projectlombok lombok 1.18.22  provided        org.springframework.ai spring-ai-bom ${spring-ai.version} pom import    

 application.ymal

可选择ollama或者openai其一进行大模型配置

server: tomcat: max-swallow-size: -1 # 禁用Tomcat的请求大小限制（或设为足够大的值，如100MB）spring: application: name: heima-ai servlet: multipart: max-file-size: 50MB # 单个文件限制 max-request-size: 100MB # 单次请求总限制 # AI服务配置（多引擎支持） ai: # Ollama配置（本地大模型引擎） ollama: base-url: http://localhost:11434 # Ollama服务地址（默认端口11434） chat: model: deepseek-r1:7b # 使用的模型名称（7B参数的本地模型） # 阿里云OpenAI兼容模式配置 openai: base-url: https://dashscope.aliyuncs.com/compatible-mode # 阿里云兼容API端点 api-key: ${OPENAI_API_KEY} # 从环境变量读取API密钥（安全建议） chat: options: model: qwen-max-latest # 通义千问最新版本模型# 日志级别配置logging: level: org.springframework.ai: debug # 打印Spring AI框架调试日志 com.itheima.ai: debug # 打印业务代码调试日志

特别注意：在SpringAI的当前版本（1.0.0-m6)中，qwen-omni与SpringAI中的OpenAI模块的兼容性有问题，目前仅支持文本和图片两种模态。音频会有数据格式错误问题，视频完全不支持。音频识别中的数据格式，阿里云百炼的qwen-omni模型要求的参数格式为data:;base64,${media-data}，而OpenAI是直接{media-data}。

目前的解决方案有两种：

• 一是使用spring-ai-alibaba来替代。

• 二是重写OpenAIModel的实现。

接下来，我们就用重写OpenAiModel的方式，来实现多模态效果。

自实现 AlibabaOpenAiChatModel (仿照OpenAiModel来写)

主要修改了buildGeneration、fromAudioData方法

public class AlibabaOpenAiChatModel extends AbstractToolCallSupport implements ChatModel { private static final Logger logger = LoggerFactory.getLogger(AlibabaOpenAiChatModel.class); private static final ChatModelObservationConvention DEFAULT_OBSERVATION_CONVENTION = new DefaultChatModelObservationConvention(); private static final ToolCallingManager DEFAULT_TOOL_CALLING_MANAGER = ToolCallingManager.builder().build(); /** * The default options used for the chat completion requests. */ private final OpenAiChatOptions defaultOptions; /** * The retry template used to retry the OpenAI API calls. */ private final RetryTemplate retryTemplate; /** * Low-level access to the OpenAI API. */ private final OpenAiApi openAiApi; /** * Observation registry used for instrumentation. */ private final ObservationRegistry observationRegistry; private final ToolCallingManager toolCallingManager; /** * Conventions to use for generating observations. */ private ChatModelObservationConvention observationConvention = DEFAULT_OBSERVATION_CONVENTION; /** * Creates an instance of the AlibabaOpenAiChatModel. * @param openAiApi The OpenAiApi instance to be used for interacting with the OpenAI * Chat API. * @throws IllegalArgumentException if openAiApi is null * @deprecated Use AlibabaOpenAiChatModel.Builder. */ @Deprecated public AlibabaOpenAiChatModel(OpenAiApi openAiApi) { this(openAiApi, OpenAiChatOptions.builder().model(OpenAiApi.DEFAULT_CHAT_MODEL).temperature(0.7).build()); } /** * Initializes an instance of the AlibabaOpenAiChatModel. * @param openAiApi The OpenAiApi instance to be used for interacting with the OpenAI * Chat API. * @param options The OpenAiChatOptions to configure the chat model. * @deprecated Use AlibabaOpenAiChatModel.Builder. */ @Deprecated public AlibabaOpenAiChatModel(OpenAiApi openAiApi, OpenAiChatOptions options) { this(openAiApi, options, null, RetryUtils.DEFAULT_RETRY_TEMPLATE); } /** * Initializes a new instance of the AlibabaOpenAiChatModel. * @param openAiApi The OpenAiApi instance to be used for interacting with the OpenAI * Chat API. * @param options The OpenAiChatOptions to configure the chat model. * @param functionCallbackResolver The function callback resolver. * @param retryTemplate The retry template. * @deprecated Use AlibabaOpenAiChatModel.Builder. */ @Deprecated public AlibabaOpenAiChatModel(OpenAiApi openAiApi, OpenAiChatOptions options, @Nullable FunctionCallbackResolver functionCallbackResolver, RetryTemplate retryTemplate) { this(openAiApi, options, functionCallbackResolver, List.of(), retryTemplate); } /** * Initializes a new instance of the AlibabaOpenAiChatModel. * @param openAiApi The OpenAiApi instance to be used for interacting with the OpenAI * Chat API. * @param options The OpenAiChatOptions to configure the chat model. * @param functionCallbackResolver The function callback resolver. * @param toolFunctionCallbacks The tool function callbacks. * @param retryTemplate The retry template. * @deprecated Use AlibabaOpenAiChatModel.Builder. */ @Deprecated public AlibabaOpenAiChatModel(OpenAiApi openAiApi, OpenAiChatOptions options, @Nullable FunctionCallbackResolver functionCallbackResolver, @Nullable List toolFunctionCallbacks, RetryTemplate retryTemplate) { this(openAiApi, options, functionCallbackResolver, toolFunctionCallbacks, retryTemplate, ObservationRegistry.NOOP); } /** * Initializes a new instance of the AlibabaOpenAiChatModel. * @param openAiApi The OpenAiApi instance to be used for interacting with the OpenAI * Chat API. * @param options The OpenAiChatOptions to configure the chat model. * @param functionCallbackResolver The function callback resolver. * @param toolFunctionCallbacks The tool function callbacks. * @param retryTemplate The retry template. * @param observationRegistry The ObservationRegistry used for instrumentation. * @deprecated Use AlibabaOpenAiChatModel.Builder or AlibabaOpenAiChatModel(OpenAiApi, * OpenAiChatOptions, ToolCallingManager, RetryTemplate, ObservationRegistry). */ @Deprecated public AlibabaOpenAiChatModel(OpenAiApi openAiApi, OpenAiChatOptions options, @Nullable FunctionCallbackResolver functionCallbackResolver, @Nullable List toolFunctionCallbacks, RetryTemplate retryTemplate, ObservationRegistry observationRegistry) { this(openAiApi, options, LegacyToolCallingManager.builder() .functionCallbackResolver(functionCallbackResolver) .functionCallbacks(toolFunctionCallbacks) .build(), retryTemplate, observationRegistry); logger.warn(\"This constructor is deprecated and will be removed in the next milestone. \" + \"Please use the AlibabaOpenAiChatModel.Builder or the new constructor accepting ToolCallingManager instead.\"); } public AlibabaOpenAiChatModel(OpenAiApi openAiApi, OpenAiChatOptions defaultOptions, ToolCallingManager toolCallingManager, RetryTemplate retryTemplate, ObservationRegistry observationRegistry) { // We do not pass the \'defaultOptions\' to the AbstractToolSupport, // because it modifies them. We are using ToolCallingManager instead, // so we just pass empty options here. super(null, OpenAiChatOptions.builder().build(), List.of()); Assert.notNull(openAiApi, \"openAiApi cannot be null\"); Assert.notNull(defaultOptions, \"defaultOptions cannot be null\"); Assert.notNull(toolCallingManager, \"toolCallingManager cannot be null\"); Assert.notNull(retryTemplate, \"retryTemplate cannot be null\"); Assert.notNull(observationRegistry, \"observationRegistry cannot be null\"); this.openAiApi = openAiApi; this.defaultOptions = defaultOptions; this.toolCallingManager = toolCallingManager; this.retryTemplate = retryTemplate; this.observationRegistry = observationRegistry; } @Override public ChatResponse call(Prompt prompt) { // Before moving any further, build the final request Prompt, // merging runtime and default options. Prompt requestPrompt = buildRequestPrompt(prompt); return this.internalCall(requestPrompt, null); } public ChatResponse internalCall(Prompt prompt, ChatResponse previousChatResponse) { OpenAiApi.ChatCompletionRequest request = createRequest(prompt, false); ChatModelObservationContext observationContext = ChatModelObservationContext.builder() .prompt(prompt) .provider(OpenAiApiConstants.PROVIDER_NAME) .requestOptions(prompt.getOptions()) .build(); ChatResponse response = ChatModelObservationDocumentation.CHAT_MODEL_OPERATION .observation(this.observationConvention, DEFAULT_OBSERVATION_CONVENTION, () -> observationContext, this.observationRegistry) .observe(() -> {  ResponseEntity completionEntity = this.retryTemplate .execute(ctx -> this.openAiApi.chatCompletionEntity(request, getAdditionalHttpHeaders(prompt)));  var chatCompletion = completionEntity.getBody();  if (chatCompletion == null) { logger.warn(\"No chat completion returned for prompt: {}\", prompt); return new ChatResponse(List.of());  }  List choices = chatCompletion.choices();  if (choices == null) { logger.warn(\"No choices returned for prompt: {}\", prompt); return new ChatResponse(List.of());  }  List generations = choices.stream().map(choice -> { // @formatter:off Map metadata = Map.of( \"id\", chatCompletion.id() != null ? chatCompletion.id() : \"\", \"role\", choice.message().role() != null ? choice.message().role().name() : \"\", \"index\", choice.index(), \"finishReason\", choice.finishReason() != null ? choice.finishReason().name() : \"\", \"refusal\", StringUtils.hasText(choice.message().refusal()) ? choice.message().refusal() : \"\"); // @formatter:on return buildGeneration(choice, metadata, request);  }).toList();  RateLimit rateLimit = OpenAiResponseHeaderExtractor.extractAiResponseHeaders(completionEntity);  // Current usage  OpenAiApi.Usage usage = completionEntity.getBody().usage();  Usage currentChatResponseUsage = usage != null ? getDefaultUsage(usage) : new EmptyUsage();  Usage accumulatedUsage = UsageUtils.getCumulativeUsage(currentChatResponseUsage, previousChatResponse);  ChatResponse chatResponse = new ChatResponse(generations, from(completionEntity.getBody(), rateLimit, accumulatedUsage));  observationContext.setResponse(chatResponse);  return chatResponse; }); if (ToolCallingChatOptions.isInternalToolExecutionEnabled(prompt.getOptions()) && response != null && response.hasToolCalls()) { var toolExecutionResult = this.toolCallingManager.executeToolCalls(prompt, response); if (toolExecutionResult.returnDirect()) { // Return tool execution result directly to the client. return ChatResponse.builder() .from(response) .generations(ToolExecutionResult.buildGenerations(toolExecutionResult)) .build(); } else { // Send the tool execution result back to the model. return this.internalCall(new Prompt(toolExecutionResult.conversationHistory(), prompt.getOptions()), response); } } return response; } @Override public Flux stream(Prompt prompt) { // Before moving any further, build the final request Prompt, // merging runtime and default options. Prompt requestPrompt = buildRequestPrompt(prompt); return internalStream(requestPrompt, null); } public Flux internalStream(Prompt prompt, ChatResponse previousChatResponse) { return Flux.deferContextual(contextView -> { OpenAiApi.ChatCompletionRequest request = createRequest(prompt, true); if (request.outputModalities() != null) { if (request.outputModalities().stream().anyMatch(m -> m.equals(\"audio\"))) {  logger.warn(\"Audio output is not supported for streaming requests. Removing audio output.\");  throw new IllegalArgumentException(\"Audio output is not supported for streaming requests.\"); } } if (request.audioParameters() != null) { logger.warn(\"Audio parameters are not supported for streaming requests. Removing audio parameters.\"); throw new IllegalArgumentException(\"Audio parameters are not supported for streaming requests.\"); } Flux completionChunks = this.openAiApi.chatCompletionStream(request,  getAdditionalHttpHeaders(prompt)); // For chunked responses, only the first chunk contains the choice role. // The rest of the chunks with same ID share the same role. ConcurrentHashMap roleMap = new ConcurrentHashMap(); final ChatModelObservationContext observationContext = ChatModelObservationContext.builder()  .prompt(prompt)  .provider(OpenAiApiConstants.PROVIDER_NAME)  .requestOptions(prompt.getOptions())  .build(); Observation observation = ChatModelObservationDocumentation.CHAT_MODEL_OPERATION.observation(  this.observationConvention, DEFAULT_OBSERVATION_CONVENTION, () -> observationContext,  this.observationRegistry); observation.parentObservation(contextView.getOrDefault(ObservationThreadLocalAccessor.KEY, null)).start(); // Convert the ChatCompletionChunk into a ChatCompletion to be able to reuse // the function call handling logic. Flux chatResponse = completionChunks.map(this::chunkToChatCompletion)  .switchMap(chatCompletion -> Mono.just(chatCompletion).map(chatCompletion2 -> { try { @SuppressWarnings(\"null\") String id = chatCompletion2.id(); List generations = chatCompletion2.choices().stream().map(choice -> { // @formatter:off if (choice.message().role() != null) {  roleMap.putIfAbsent(id, choice.message().role().name()); } Map metadata = Map.of(  \"id\", chatCompletion2.id(),  \"role\", roleMap.getOrDefault(id, \"\"),  \"index\", choice.index(),  \"finishReason\", choice.finishReason() != null ? choice.finishReason().name() : \"\",  \"refusal\", StringUtils.hasText(choice.message().refusal()) ? choice.message().refusal() : \"\"); return buildGeneration(choice, metadata, request); }).toList(); // @formatter:on OpenAiApi.Usage usage = chatCompletion2.usage(); Usage currentChatResponseUsage = usage != null ? getDefaultUsage(usage) : new EmptyUsage(); Usage accumulatedUsage = UsageUtils.getCumulativeUsage(currentChatResponseUsage,  previousChatResponse); return new ChatResponse(generations, from(chatCompletion2, null, accumulatedUsage)); } catch (Exception e) { logger.error(\"Error processing chat completion\", e); return new ChatResponse(List.of()); } // When in stream mode and enabled to include the usage, the OpenAI // Chat completion response would have the usage set only in its // final response. Hence, the following overlapping buffer is // created to store both the current and the subsequent response // to accumulate the usage from the subsequent response.  }))  .buffer(2, 1)  .map(bufferList -> { ChatResponse firstResponse = bufferList.get(0); if (request.streamOptions() != null && request.streamOptions().includeUsage()) { if (bufferList.size() == 2) { ChatResponse secondResponse = bufferList.get(1); if (secondResponse != null && secondResponse.getMetadata() != null) {  // This is the usage from the final Chat response for a  // given Chat request.  Usage usage = secondResponse.getMetadata().getUsage();  if (!UsageUtils.isEmpty(usage)) {  // Store the usage from the final response to the  // penultimate response for accumulation.  return new ChatResponse(firstResponse.getResults(), from(firstResponse.getMetadata(), usage));  } } } } return firstResponse;  }); // @formatter:off Flux flux = chatResponse.flatMap(response -> { if (ToolCallingChatOptions.isInternalToolExecutionEnabled(prompt.getOptions()) && response.hasToolCalls()) { var toolExecutionResult = this.toolCallingManager.executeToolCalls(prompt, response); if (toolExecutionResult.returnDirect()) { // Return tool execution result directly to the client. return Flux.just(ChatResponse.builder().from(response)  .generations(ToolExecutionResult.buildGenerations(toolExecutionResult))  .build()); } else { // Send the tool execution result back to the model. return this.internalStream(new Prompt(toolExecutionResult.conversationHistory(), prompt.getOptions()),  response); } } else { return Flux.just(response); }  })  .doOnError(observation::error)  .doFinally(s -> observation.stop())  .contextWrite(ctx -> ctx.put(ObservationThreadLocalAccessor.KEY, observation)); // @formatter:on return new MessageAggregator().aggregate(flux, observationContext::setResponse); }); } private MultiValueMap getAdditionalHttpHeaders(Prompt prompt) { Map headers = new HashMap(this.defaultOptions.getHttpHeaders()); if (prompt.getOptions() != null && prompt.getOptions() instanceof OpenAiChatOptions chatOptions) { headers.putAll(chatOptions.getHttpHeaders()); } return CollectionUtils.toMultiValueMap( headers.entrySet().stream().collect(Collectors.toMap(Map.Entry::getKey, e -> List.of(e.getValue())))); } private Generation buildGeneration(OpenAiApi.ChatCompletion.Choice choice, Map metadata, OpenAiApi.ChatCompletionRequest request) { List toolCalls = choice.message().toolCalls() == null ? List.of() : choice.message() .toolCalls() .stream() .map(toolCall -> new AssistantMessage.ToolCall(toolCall.id(), \"function\", toolCall.function().name(), toolCall.function().arguments())) .reduce((tc1, tc2) -> new AssistantMessage.ToolCall(tc1.id(), \"function\", tc1.name(), tc1.arguments() + tc2.arguments())) .stream() .toList(); String finishReason = (choice.finishReason() != null ? choice.finishReason().name() : \"\"); var generationMetadataBuilder = ChatGenerationMetadata.builder().finishReason(finishReason); List media = new ArrayList(); String textContent = choice.message().content(); var audioOutput = choice.message().audioOutput(); if (audioOutput != null) { String mimeType = String.format(\"audio/%s\", request.audioParameters().format().name().toLowerCase()); byte[] audioData = Base64.getDecoder().decode(audioOutput.data()); Resource resource = new ByteArrayResource(audioData); Media.builder().mimeType(MimeTypeUtils.parseMimeType(mimeType)).data(resource).id(audioOutput.id()).build(); media.add(Media.builder()  .mimeType(MimeTypeUtils.parseMimeType(mimeType))  .data(resource)  .id(audioOutput.id())  .build()); if (!StringUtils.hasText(textContent)) { textContent = audioOutput.transcript(); } generationMetadataBuilder.metadata(\"audioId\", audioOutput.id()); generationMetadataBuilder.metadata(\"audioExpiresAt\", audioOutput.expiresAt()); } var assistantMessage = new AssistantMessage(textContent, metadata, toolCalls, media); return new Generation(assistantMessage, generationMetadataBuilder.build()); } private ChatResponseMetadata from(OpenAiApi.ChatCompletion result, RateLimit rateLimit, Usage usage) { Assert.notNull(result, \"OpenAI ChatCompletionResult must not be null\"); var builder = ChatResponseMetadata.builder() .id(result.id() != null ? result.id() : \"\") .usage(usage) .model(result.model() != null ? result.model() : \"\") .keyValue(\"created\", result.created() != null ? result.created() : 0L) .keyValue(\"system-fingerprint\", result.systemFingerprint() != null ? result.systemFingerprint() : \"\"); if (rateLimit != null) { builder.rateLimit(rateLimit); } return builder.build(); } private ChatResponseMetadata from(ChatResponseMetadata chatResponseMetadata, Usage usage) { Assert.notNull(chatResponseMetadata, \"OpenAI ChatResponseMetadata must not be null\"); var builder = ChatResponseMetadata.builder() .id(chatResponseMetadata.getId() != null ? chatResponseMetadata.getId() : \"\") .usage(usage) .model(chatResponseMetadata.getModel() != null ? chatResponseMetadata.getModel() : \"\"); if (chatResponseMetadata.getRateLimit() != null) { builder.rateLimit(chatResponseMetadata.getRateLimit()); } return builder.build(); } /** * Convert the ChatCompletionChunk into a ChatCompletion. The Usage is set to null. * @param chunk the ChatCompletionChunk to convert * @return the ChatCompletion */ private OpenAiApi.ChatCompletion chunkToChatCompletion(OpenAiApi.ChatCompletionChunk chunk) { List choices = chunk.choices() .stream() .map(chunkChoice -> new OpenAiApi.ChatCompletion.Choice(chunkChoice.finishReason(), chunkChoice.index(), chunkChoice.delta(), chunkChoice.logprobs())) .toList(); return new OpenAiApi.ChatCompletion(chunk.id(), choices, chunk.created(), chunk.model(), chunk.serviceTier(), chunk.systemFingerprint(), \"chat.completion\", chunk.usage()); } private DefaultUsage getDefaultUsage(OpenAiApi.Usage usage) { return new DefaultUsage(usage.promptTokens(), usage.completionTokens(), usage.totalTokens(), usage); } Prompt buildRequestPrompt(Prompt prompt) { // Process runtime options OpenAiChatOptions runtimeOptions = null; if (prompt.getOptions() != null) { if (prompt.getOptions() instanceof ToolCallingChatOptions toolCallingChatOptions) { runtimeOptions = ModelOptionsUtils.copyToTarget(toolCallingChatOptions, ToolCallingChatOptions.class, OpenAiChatOptions.class); } else if (prompt.getOptions() instanceof FunctionCallingOptions functionCallingOptions) { runtimeOptions = ModelOptionsUtils.copyToTarget(functionCallingOptions, FunctionCallingOptions.class, OpenAiChatOptions.class); } else { runtimeOptions = ModelOptionsUtils.copyToTarget(prompt.getOptions(), ChatOptions.class, OpenAiChatOptions.class); } } // Define request options by merging runtime options and default options OpenAiChatOptions requestOptions = ModelOptionsUtils.merge(runtimeOptions, this.defaultOptions, OpenAiChatOptions.class); // Merge @JsonIgnore-annotated options explicitly since they are ignored by // Jackson, used by ModelOptionsUtils. if (runtimeOptions != null) { requestOptions.setHttpHeaders(  mergeHttpHeaders(runtimeOptions.getHttpHeaders(), this.defaultOptions.getHttpHeaders())); requestOptions.setInternalToolExecutionEnabled(  ModelOptionsUtils.mergeOption(runtimeOptions.isInternalToolExecutionEnabled(), this.defaultOptions.isInternalToolExecutionEnabled())); requestOptions.setToolNames(ToolCallingChatOptions.mergeToolNames(runtimeOptions.getToolNames(),  this.defaultOptions.getToolNames())); requestOptions.setToolCallbacks(ToolCallingChatOptions.mergeToolCallbacks(runtimeOptions.getToolCallbacks(),  this.defaultOptions.getToolCallbacks())); requestOptions.setToolContext(ToolCallingChatOptions.mergeToolContext(runtimeOptions.getToolContext(),  this.defaultOptions.getToolContext())); } else { requestOptions.setHttpHeaders(this.defaultOptions.getHttpHeaders()); requestOptions.setInternalToolExecutionEnabled(this.defaultOptions.isInternalToolExecutionEnabled()); requestOptions.setToolNames(this.defaultOptions.getToolNames()); requestOptions.setToolCallbacks(this.defaultOptions.getToolCallbacks()); requestOptions.setToolContext(this.defaultOptions.getToolContext()); } ToolCallingChatOptions.validateToolCallbacks(requestOptions.getToolCallbacks()); return new Prompt(prompt.getInstructions(), requestOptions); } private Map mergeHttpHeaders(Map runtimeHttpHeaders, Map defaultHttpHeaders) { var mergedHttpHeaders = new HashMap(defaultHttpHeaders); mergedHttpHeaders.putAll(runtimeHttpHeaders); return mergedHttpHeaders; } /** * Accessible for testing. */ OpenAiApi.ChatCompletionRequest createRequest(Prompt prompt, boolean stream) { List chatCompletionMessages = prompt.getInstructions().stream().map(message -> { if (message.getMessageType() == MessageType.USER || message.getMessageType() == MessageType.SYSTEM) { Object content = message.getText(); if (message instanceof UserMessage userMessage) {  if (!CollectionUtils.isEmpty(userMessage.getMedia())) { List contentList = new ArrayList(List.of(new OpenAiApi.ChatCompletionMessage.MediaContent(message.getText()))); contentList.addAll(userMessage.getMedia().stream().map(this::mapToMediaContent).toList()); content = contentList;  } } return List.of(new OpenAiApi.ChatCompletionMessage(content, OpenAiApi.ChatCompletionMessage.Role.valueOf(message.getMessageType().name()))); } else if (message.getMessageType() == MessageType.ASSISTANT) { var assistantMessage = (AssistantMessage) message; List toolCalls = null; if (!CollectionUtils.isEmpty(assistantMessage.getToolCalls())) {  toolCalls = assistantMessage.getToolCalls().stream().map(toolCall -> { var function = new OpenAiApi.ChatCompletionMessage.ChatCompletionFunction(toolCall.name(), toolCall.arguments()); return new OpenAiApi.ChatCompletionMessage.ToolCall(toolCall.id(), toolCall.type(), function);  }).toList(); } OpenAiApi.ChatCompletionMessage.AudioOutput audioOutput = null; if (!CollectionUtils.isEmpty(assistantMessage.getMedia())) {  Assert.isTrue(assistantMessage.getMedia().size() == 1, \"Only one media content is supported for assistant messages\");  audioOutput = new OpenAiApi.ChatCompletionMessage.AudioOutput(assistantMessage.getMedia().get(0).getId(), null, null, null); } return List.of(new OpenAiApi.ChatCompletionMessage(assistantMessage.getText(), OpenAiApi.ChatCompletionMessage.Role.ASSISTANT, null, null, toolCalls, null, audioOutput)); } else if (message.getMessageType() == MessageType.TOOL) { ToolResponseMessage toolMessage = (ToolResponseMessage) message; toolMessage.getResponses() .forEach(response -> Assert.isTrue(response.id() != null, \"ToolResponseMessage must have an id\")); return toolMessage.getResponses() .stream() .map(tr -> new OpenAiApi.ChatCompletionMessage(tr.responseData(), OpenAiApi.ChatCompletionMessage.Role.TOOL, tr.name(), tr.id(), null, null, null)) .toList(); } else { throw new IllegalArgumentException(\"Unsupported message type: \" + message.getMessageType()); } }).flatMap(List::stream).toList(); OpenAiApi.ChatCompletionRequest request = new OpenAiApi.ChatCompletionRequest(chatCompletionMessages, stream); OpenAiChatOptions requestOptions = (OpenAiChatOptions) prompt.getOptions(); request = ModelOptionsUtils.merge(requestOptions, request, OpenAiApi.ChatCompletionRequest.class); // Add the tool definitions to the request\'s tools parameter. List toolDefinitions = this.toolCallingManager.resolveToolDefinitions(requestOptions); if (!CollectionUtils.isEmpty(toolDefinitions)) { request = ModelOptionsUtils.merge(  OpenAiChatOptions.builder().tools(this.getFunctionTools(toolDefinitions)).build(), request,  OpenAiApi.ChatCompletionRequest.class); } // Remove `streamOptions` from the request if it is not a streaming request if (request.streamOptions() != null && !stream) { logger.warn(\"Removing streamOptions from the request as it is not a streaming request!\"); request = request.streamOptions(null); } return request; } private OpenAiApi.ChatCompletionMessage.MediaContent mapToMediaContent(Media media) { var mimeType = media.getMimeType(); if (MimeTypeUtils.parseMimeType(\"audio/mp3\").equals(mimeType) || MimeTypeUtils.parseMimeType(\"audio/mpeg\").equals(mimeType)) { return new OpenAiApi.ChatCompletionMessage.MediaContent(  new OpenAiApi.ChatCompletionMessage.MediaContent.InputAudio(fromAudioData(media.getData()), OpenAiApi.ChatCompletionMessage.MediaContent.InputAudio.Format.MP3)); } if (MimeTypeUtils.parseMimeType(\"audio/wav\").equals(mimeType)) { return new OpenAiApi.ChatCompletionMessage.MediaContent(  new OpenAiApi.ChatCompletionMessage.MediaContent.InputAudio(fromAudioData(media.getData()), OpenAiApi.ChatCompletionMessage.MediaContent.InputAudio.Format.WAV)); } else { return new OpenAiApi.ChatCompletionMessage.MediaContent(  new OpenAiApi.ChatCompletionMessage.MediaContent.ImageUrl(this.fromMediaData(media.getMimeType(), media.getData()))); } } private String fromAudioData(Object audioData) { if (audioData instanceof byte[] bytes) { return String.format(\"data:;base64,%s\", Base64.getEncoder().encodeToString(bytes)); } throw new IllegalArgumentException(\"Unsupported audio data type: \" + audioData.getClass().getSimpleName()); } private String fromMediaData(MimeType mimeType, Object mediaContentData) { if (mediaContentData instanceof byte[] bytes) { // Assume the bytes are an image. So, convert the bytes to a base64 encoded // following the prefix pattern. return String.format(\"data:%s;base64,%s\", mimeType.toString(), Base64.getEncoder().encodeToString(bytes)); } else if (mediaContentData instanceof String text) { // Assume the text is a URLs or a base64 encoded image prefixed by the user. return text; } else { throw new IllegalArgumentException(  \"Unsupported media data type: \" + mediaContentData.getClass().getSimpleName()); } } private List getFunctionTools(List toolDefinitions) { return toolDefinitions.stream().map(toolDefinition -> { var function = new OpenAiApi.FunctionTool.Function(toolDefinition.description(), toolDefinition.name(),  toolDefinition.inputSchema()); return new OpenAiApi.FunctionTool(function); }).toList(); } @Override public ChatOptions getDefaultOptions() { return OpenAiChatOptions.fromOptions(this.defaultOptions); } @Override public String toString() { return \"AlibabaOpenAiChatModel [defaultOptions=\" + this.defaultOptions + \"]\"; } /** * Use the provided convention for reporting observation data * @param observationConvention The provided convention */ public void setObservationConvention(ChatModelObservationConvention observationConvention) { Assert.notNull(observationConvention, \"observationConvention cannot be null\"); this.observationConvention = observationConvention; } public static AlibabaOpenAiChatModel.Builder builder() { return new AlibabaOpenAiChatModel.Builder(); } public static final class Builder { private OpenAiApi openAiApi; private OpenAiChatOptions defaultOptions = OpenAiChatOptions.builder() .model(OpenAiApi.DEFAULT_CHAT_MODEL) .temperature(0.7) .build(); private ToolCallingManager toolCallingManager; private FunctionCallbackResolver functionCallbackResolver; private List toolFunctionCallbacks; private RetryTemplate retryTemplate = RetryUtils.DEFAULT_RETRY_TEMPLATE; private ObservationRegistry observationRegistry = ObservationRegistry.NOOP; private Builder() { } public AlibabaOpenAiChatModel.Builder openAiApi(OpenAiApi openAiApi) { this.openAiApi = openAiApi; return this; } public AlibabaOpenAiChatModel.Builder defaultOptions(OpenAiChatOptions defaultOptions) { this.defaultOptions = defaultOptions; return this; } public AlibabaOpenAiChatModel.Builder toolCallingManager(ToolCallingManager toolCallingManager) { this.toolCallingManager = toolCallingManager; return this; } @Deprecated public AlibabaOpenAiChatModel.Builder functionCallbackResolver(FunctionCallbackResolver functionCallbackResolver) { this.functionCallbackResolver = functionCallbackResolver; return this; } @Deprecated public AlibabaOpenAiChatModel.Builder toolFunctionCallbacks(List toolFunctionCallbacks) { this.toolFunctionCallbacks = toolFunctionCallbacks; return this; } public AlibabaOpenAiChatModel.Builder retryTemplate(RetryTemplate retryTemplate) { this.retryTemplate = retryTemplate; return this; } public AlibabaOpenAiChatModel.Builder observationRegistry(ObservationRegistry observationRegistry) { this.observationRegistry = observationRegistry; return this; } public AlibabaOpenAiChatModel build() { if (toolCallingManager != null) { Assert.isNull(functionCallbackResolver, \"functionCallbackResolver cannot be set when toolCallingManager is set\"); Assert.isNull(toolFunctionCallbacks, \"toolFunctionCallbacks cannot be set when toolCallingManager is set\"); return new AlibabaOpenAiChatModel(openAiApi, defaultOptions, toolCallingManager, retryTemplate, observationRegistry); } if (functionCallbackResolver != null) { Assert.isNull(toolCallingManager, \"toolCallingManager cannot be set when functionCallbackResolver is set\"); List toolCallbacks = this.toolFunctionCallbacks != null ? this.toolFunctionCallbacks : List.of(); return new AlibabaOpenAiChatModel(openAiApi, defaultOptions, functionCallbackResolver, toolCallbacks, retryTemplate, observationRegistry); } return new AlibabaOpenAiChatModel(openAiApi, defaultOptions, DEFAULT_TOOL_CALLING_MANAGER, retryTemplate,  observationRegistry); } }}

ChatConfiguration配置类 

InMemoryChatMemory实现本地聊天记录存储

/** * AI核心配置类 * * 核心组件： * 1. 聊天记忆管理（ChatMemory） * 2. 多种场景的ChatClient实例 */@Configurationpublic class ChatConfiguration { /** * 内存式聊天记忆存储 * @return InMemoryChatMemory 实例 * * 作用：保存对话上下文，实现多轮对话能力 * 实现原理：基于ConcurrentHashMap的线程安全实现 */ @Bean public ChatMemory chatMemory() { return new InMemoryChatMemory(); } /** * 通用聊天客户端 * @param model 阿里云OpenAI模型 * @param chatMemory 聊天记忆 * @return 配置好的ChatClient * * 默认配置： * - 使用qwen-omni-turbo模型 * - 设定AI人格为\"小小\" * - 启用日志记录和记忆功能 */ @Bean public ChatClient chatClient(AlibabaOpenAiChatModel model, ChatMemory chatMemory) { return ChatClient .builder(model) .defaultOptions(ChatOptions.builder().model(\"qwen-omni-turbo\").build()) // 自定义模型不与配置文件的冲突 .defaultSystem(\"你是一个热心、聪明、全知的智能助手，你的名字叫小小，请以小小的身份和语气回答问题。\") .defaultAdvisors( new SimpleLoggerAdvisor(), // 日志记录 new MessageChatMemoryAdvisor(chatMemory) // 记忆功能 ) .build(); } /** * 定制化阿里云OpenAI模型 * @return AlibabaOpenAiChatModel 实例 * * 配置要点： * 1. 支持多级参数继承（chatProperties > commonProperties） * 2. 自动配置HTTP客户端（RestClient/WebClient） * 3. 集成可观测性体系 */ @Bean public AlibabaOpenAiChatModel alibabaOpenAiChatModel( OpenAiConnectionProperties commonProperties, OpenAiChatProperties chatProperties, ObjectProvider restClientBuilderProvider, ObjectProvider webClientBuilderProvider, ToolCallingManager toolCallingManager, RetryTemplate retryTemplate, ResponseErrorHandler responseErrorHandler, ObjectProvider observationRegistry, ObjectProvider observationConvention) { // 参数优先级处理 String baseUrl = StringUtils.hasText(chatProperties.getBaseUrl()) ? chatProperties.getBaseUrl() : commonProperties.getBaseUrl(); String apiKey = StringUtils.hasText(chatProperties.getApiKey()) ? chatProperties.getApiKey() : commonProperties.getApiKey(); // 组织头信息配置 Map<String, List> connectionHeaders = new HashMap(); Optional.ofNullable(chatProperties.getProjectId()) .filter(StringUtils::hasText) .ifPresent(projectId -> connectionHeaders.put(\"OpenAI-Project\", List.of(projectId))); Optional.ofNullable(chatProperties.getOrganizationId()) .filter(StringUtils::hasText) .ifPresent(orgId -> connectionHeaders.put(\"OpenAI-Organization\", List.of(orgId))); // 构建OpenAI API客户端 OpenAiApi openAiApi = OpenAiApi.builder() .baseUrl(baseUrl) .apiKey(new SimpleApiKey(apiKey)) .headers(CollectionUtils.toMultiValueMap(connectionHeaders)) .completionsPath(chatProperties.getCompletionsPath()) .embeddingsPath(\"/v1/embeddings\") .restClientBuilder(restClientBuilderProvider.getIfAvailable(RestClient::builder)) .webClientBuilder(webClientBuilderProvider.getIfAvailable(WebClient::builder)) .responseErrorHandler(responseErrorHandler) .build(); // 构建定制化聊天模型 AlibabaOpenAiChatModel chatModel = AlibabaOpenAiChatModel.builder() .openAiApi(openAiApi) .defaultOptions(chatProperties.getOptions()) .toolCallingManager(toolCallingManager) .retryTemplate(retryTemplate) .observationRegistry(observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP)) .build(); // 配置可观测性约定 observationConvention.ifAvailable(chatModel::setObservationConvention); return chatModel; }}

ChatController对话类

会话id由前端进行生成并传输过来，当然也可后端自己生成并且存入数据库，不过这里由于是简单的实现，由本地Map实现会话及信息的存储

根据前端是否传过来files来判断是否为多模态调用，有文件则走multiModalChat方法

import lombok.RequiredArgsConstructor;import org.springframework.ai.chat.client.ChatClient;import org.springframework.ai.model.Media;import org.springframework.util.MimeType;import org.springframework.web.bind.annotation.RequestMapping;import org.springframework.web.bind.annotation.RequestParam;import org.springframework.web.bind.annotation.RestController;import org.springframework.web.multipart.MultipartFile;import reactor.core.publisher.Flux;import java.util.List;import java.util.Objects;import static org.springframework.ai.chat.client.advisor.AbstractChatMemoryAdvisor.CHAT_MEMORY_CONVERSATION_ID_KEY;@RequiredArgsConstructor // 构造方式自动注入@RestController@RequestMapping(\"/ai\")public class ChatController { private final ChatClient chatClient; private final ChatHistoryRepository chatHistoryRepository; @RequestMapping(value = \"/chat\", produces = \"text/html;charset=utf-8\") public Flux chat( @RequestParam(\"prompt\") String prompt, @RequestParam(\"chatId\") String chatId, @RequestParam(value = \"files\", required = false) List files) { // 1.保存会话id chatHistoryRepository.save(\"chat\", chatId); // 2.请求模型 if (files == null || files.isEmpty()) { // 没有附件，纯文本聊天 return textChat(prompt, chatId); } else { // 有附件，多模态聊天 return multiModalChat(prompt, chatId, files); } } private Flux multiModalChat(String prompt, String chatId, List files) { // 1.遍历解析多媒体，转为Media对象 List medias = files.stream() .map(file -> new Media( MimeType.valueOf(Objects.requireNonNull(file.getContentType())), file.getResource() ) ) .toList(); // 2.请求模型 return chatClient.prompt() .user(p -> p.text(prompt).media(medias.toArray(Media[]::new))) .advisors(a -> a.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)) .stream() .content(); } private Flux textChat(String prompt, String chatId) { return chatClient.prompt() .user(prompt) .advisors(a -> a.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)) .stream() .content(); }}

ChatHistoryController会话历史类

实现本地Map存储chat类型与所有会话历史的对应关系，找到会话后就可用根据聊天记忆ChatMemory找到聊天历史

import lombok.RequiredArgsConstructor;import org.springframework.ai.chat.memory.ChatMemory;import org.springframework.ai.chat.messages.Message;import org.springframework.web.bind.annotation.GetMapping;import org.springframework.web.bind.annotation.PathVariable;import org.springframework.web.bind.annotation.RequestMapping;import org.springframework.web.bind.annotation.RestController;import java.util.List;@RequiredArgsConstructor@RestController@RequestMapping(\"/ai/history\")public class ChatHistoryController { private final ChatHistoryRepository chatHistoryRepository; private final ChatMemory chatMemory; @GetMapping(\"/{type}\") public List getChatIds(@PathVariable(\"type\") String type) { return chatHistoryRepository.getChatIds(type); } @GetMapping(\"/{type}/{chatId}\") public List getChatHistory(@PathVariable(\"type\") String type, @PathVariable(\"chatId\") String chatId) { List messages = chatMemory.get(chatId, Integer.MAX_VALUE); if(messages == null) { return List.of(); } // 转换成VO return messages.stream().map(MessageVO::new).toList(); }}

ChatHistoryRepository 会话历史业务接口 

import java.util.List;public interface ChatHistoryRepository { /** * 保存会话记录 * @param type 业务类型，如：chat、service、pdf * @param chatId 会话ID */ void save(String type, String chatId); /** * 获取会话ID列表 * @param type 业务类型，如：chat、service、pdf * @return 会话ID列表 */ List getChatIds(String type);}

InMemoryChatHistoryRepository实现类

@Slf4j@Component@RequiredArgsConstructorpublic class InMemoryChatHistoryRepository implements ChatHistoryRepository { // 会话chatId存储Map private Map<String, List> chatHistory; private final ChatMemory chatMemory; // 保存会话ID @Override public void save(String type, String chatId) { /*if (!chatHistory.containsKey(type)) { chatHistory.put(type, new ArrayList()); } List chatIds = chatHistory.get(type);*/ List chatIds = chatHistory.computeIfAbsent(type, k -> new ArrayList()); if (chatIds.contains(chatId)) { return; } chatIds.add(chatId); } // 获取所有会话id @Override public List getChatIds(String type) { /*List chatIds = chatHistory.get(type); return chatIds == null ? List.of() : chatIds;*/ return chatHistory.getOrDefault(type, List.of()); }}

MessageVO返回实体类 

根据ChatMemory中存储的Message可知有四种类型，则根据Message来示例VO对象

USER(\"user\"),
ASSISTANT(\"assistant\"),
SYSTEM(\"system\"),
TOOL(\"tool\");

import lombok.Data;import lombok.NoArgsConstructor;import org.springframework.ai.chat.messages.Message;@NoArgsConstructor@Datapublic class MessageVO { private String role; private String content; public MessageVO(Message message) { switch (message.getMessageType()) { case USER: role = \"user\"; break; case ASSISTANT: role = \"assistant\"; break; default: role = \"\"; break; } this.content = message.getText(); }}

3.2 前端代码

可以根据这些代码与接口让Cursor生成一个仿deepseek页面即可实现，或者根据下列Vue项目代码修改实现(实现效果中的代码)

AIChat.vue

 
 
 
 
 
聊天记录
   新对话  
 
 
  {{ chat.title || \'新对话\' }} 
 
 
 
 
  
 
 
 0\" class=\"selected-files\"> 
  
  {{ file.name }} ({{ formatFileSize(file.size) }})  
      
 
 
 
        
      
 
 
 
 
import { ref, onMounted, nextTick } from \'vue\'import { useDark } from \'@vueuse/core\'import { ChatBubbleLeftRightIcon, PaperAirplaneIcon, PlusIcon, PaperClipIcon, DocumentIcon, XMarkIcon} from \'@heroicons/vue/24/outline\'import ChatMessage from \'../components/ChatMessage.vue\'import { chatAPI } from \'../services/api\'const isDark = useDark()const messagesRef = ref(null)const inputRef = ref(null)const userInput = ref(\'\')const isStreaming = ref(false)const currentChatId = ref(null)const currentMessages = ref([])const chatHistory = ref([])const fileInput = ref(null)const selectedFiles = ref([])// 自动调整输入框高度const adjustTextareaHeight = () => { const textarea = inputRef.value if (textarea) { textarea.style.height = \'auto\' textarea.style.height = textarea.scrollHeight + \'px\' }else{ textarea.style.height = \'50px\' }}// 滚动到底部const scrollToBottom = async () => { await nextTick() if (messagesRef.value) { messagesRef.value.scrollTop = messagesRef.value.scrollHeight }}// 文件类型限制const FILE_LIMITS = { image: { maxSize: 10 * 1024 * 1024, // 单个文件 10MB maxFiles: 3,  // 最多 3 个文件 description: \'图片文件\' }, audio: { maxSize: 10 * 1024 * 1024, // 单个文件 10MB maxDuration: 180,  // 3分钟 maxFiles: 3, // 最多 3 个文件 description: \'音频文件\' }, video: { maxSize: 150 * 1024 * 1024, // 单个文件 150MB maxDuration: 40, // 40秒 maxFiles: 3, // 最多 3 个文件 description: \'视频文件\' }}// 触发文件选择const triggerFileInput = () => { fileInput.value?.click()}// 检查文件是否符合要求const validateFile = async (file) => { const type = file.type.split(\'/\')[0] const limit = FILE_LIMITS[type] if (!limit) { return { valid: false, error: \'不支持的文件类型\' } } if (file.size > limit.maxSize) { return { valid: false, error: `文件大小不能超过${limit.maxSize / 1024 / 1024}MB` } } if ((type === \'audio\' || type === \'video\') && limit.maxDuration) { try { const duration = await getMediaDuration(file) if (duration > limit.maxDuration) { return {  valid: false,  error: `${type === \'audio\' ? \'音频\' : \'视频\'}时长不能超过${limit.maxDuration}秒` } } } catch (error) { return { valid: false, error: \'无法读取媒体文件时长\' } } } return { valid: true }}// 获取媒体文件时长const getMediaDuration = (file) => { return new Promise((resolve, reject) => { const element = file.type.startsWith(\'audio/\') ? new Audio() : document.createElement(\'video\') element.preload = \'metadata\' element.onloadedmetadata = () => { resolve(element.duration) URL.revokeObjectURL(element.src) } element.onerror = () => { reject(new Error(\'无法读取媒体文件\')) URL.revokeObjectURL(element.src) } element.src = URL.createObjectURL(file) })}// 修改文件上传处理函数const handleFileUpload = async (event) => { const files = Array.from(event.target.files || []) if (!files.length) return // 检查所有文件类型是否一致 const firstFileType = files[0].type.split(\'/\')[0] const hasInconsistentType = files.some(file => file.type.split(\'/\')[0] !== firstFileType) if (hasInconsistentType) { alert(\'请选择相同类型的文件（图片、音频或视频）\') event.target.value = \'\' return } // 验证所有文件 for (const file of files) { const { valid, error } = await validateFile(file) if (!valid) { alert(error) event.target.value = \'\' selectedFiles.value = [] return } } // 检查文件总大小 const totalSize = files.reduce((sum, file) => sum + file.size, 0) const limit = FILE_LIMITS[firstFileType] if (totalSize > limit.maxSize * 3) { // 允许最多3个文件的总大小 alert(`${firstFileType === \'image\' ? \'图片\' : firstFileType === \'audio\' ? \'音频\' : \'视频\'}文件总大小不能超过${(limit.maxSize * 3) / 1024 / 1024}MB`) event.target.value = \'\' selectedFiles.value = [] return } selectedFiles.value = files}// 修改文件输入提示const getPlaceholder = () => { if (selectedFiles.value.length > 0) { const type = selectedFiles.value[0].type.split(\'/\')[0] const desc = FILE_LIMITS[type].description return `已选择 ${selectedFiles.value.length} 个${desc}，可继续输入消息...` } return \'输入消息，可上传图片、音频或视频...\'}// 修改发送消息函数const sendMessage = async () => { if (isStreaming.value) return if (!userInput.value.trim() && !selectedFiles.value.length) return const messageContent = userInput.value.trim() // 添加用户消息 const userMessage = { role: \'user\', content: messageContent, timestamp: new Date() } currentMessages.value.push(userMessage) // 清空输入 userInput.value = \'\' adjustTextareaHeight() await scrollToBottom() // 准备发送数据 const formData = new FormData() if (messageContent) { formData.append(\'prompt\', messageContent) } selectedFiles.value.forEach(file => { formData.append(\'files\', file) }) // 添加助手消息占位 const assistantMessage = { role: \'assistant\', content: \'\', timestamp: new Date() } currentMessages.value.push(assistantMessage) isStreaming.value = true try { const reader = await chatAPI.sendMessage(formData, currentChatId.value) const decoder = new TextDecoder(\'utf-8\') let accumulatedContent = \'\' // 添加累积内容变量 while (true) { try { const { value, done } = await reader.read() if (done) break // 累积新内容 accumulatedContent += decoder.decode(value) // 追加新内容 await nextTick(() => { // 更新消息，使用累积的内容 const updatedMessage = { ...assistantMessage, content: accumulatedContent // 使用累积的内容 } const lastIndex = currentMessages.value.length - 1 currentMessages.value.splice(lastIndex, 1, updatedMessage) }) await scrollToBottom() } catch (readError) { console.error(\'读取流错误:\', readError) break } } } catch (error) { console.error(\'发送消息失败:\', error) assistantMessage.content = \'抱歉，发生了错误，请稍后重试。\' } finally { isStreaming.value = false selectedFiles.value = [] // 清空已选文件 fileInput.value.value = \'\' // 清空文件输入 await scrollToBottom() }}// 加载特定对话const loadChat = async (chatId) => { currentChatId.value = chatId try { const messages = await chatAPI.getChatMessages(chatId, \'chat\') currentMessages.value = messages } catch (error) { console.error(\'加载对话消息失败:\', error) currentMessages.value = [] }}// 加载聊天历史const loadChatHistory = async () => { try { const history = await chatAPI.getChatHistory(\'chat\') chatHistory.value = history || [] if (history && history.length > 0) { await loadChat(history[0].id) } else { startNewChat() } } catch (error) { console.error(\'加载聊天历史失败:\', error) chatHistory.value = [] startNewChat() }}// 开始新对话const startNewChat = () => { const newChatId = Date.now().toString() currentChatId.value = newChatId currentMessages.value = [] // 添加新对话到聊天历史列表 const newChat = { id: newChatId, title: `对话 ${newChatId.slice(-6)}` } chatHistory.value = [newChat, ...chatHistory.value] // 将新对话添加到列表开头}// 格式化文件大小const formatFileSize = (bytes) => { if (bytes < 1024) return bytes + \' B\' if (bytes  { selectedFiles.value = selectedFiles.value.filter((_, i) => i !== index) if (selectedFiles.value.length === 0) { fileInput.value.value = \'\' // 清空文件输入 }}onMounted(() => { loadChatHistory() adjustTextareaHeight()}).ai-chat { position: fixed; // 修改为固定定位 top: 64px; // 导航栏高度 left: 0; right: 0; bottom: 0; display: flex; background: var(--bg-color); overflow: hidden; // 防止页面滚动 .chat-container { flex: 1; display: flex; max-width: 1800px; width: 100%; margin: 0 auto; padding: 1.5rem 2rem; gap: 1.5rem; height: 100%; // 确保容器占满高度 overflow: hidden; // 防止容器滚动 } .sidebar { width: 300px; display: flex; flex-direction: column; background: rgba(255, 255, 255, 0.95); backdrop-filter: blur(10px); border-radius: 1rem; box-shadow: 0 4px 6px rgba(0, 0, 0, 0.05); .history-header { flex-shrink: 0; // 防止头部压缩 padding: 1rem; display: flex; justify-content: space-between; align-items: center; h2 { font-size: 1.25rem; } .new-chat { display: flex; align-items: center; gap: 0.5rem; padding: 0.5rem 1rem; border-radius: 0.5rem; background: #007CF0; color: white; border: none; cursor: pointer; transition: background-color 0.3s; &:hover { background: #0066cc; } .icon { width: 1.25rem; height: 1.25rem; } } } .history-list { flex: 1; overflow-y: auto; // 允许历史记录滚动 padding: 0 1rem 1rem; .history-item { display: flex; align-items: center; gap: 0.5rem; padding: 0.75rem; border-radius: 0.5rem; cursor: pointer; transition: background-color 0.3s; &:hover { background: rgba(255, 255, 255, 0.1); } &.active { background: rgba(0, 124, 240, 0.1); } .icon { width: 1.25rem; height: 1.25rem; } .title { flex: 1; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; } } } } .chat-main { flex: 1; display: flex; flex-direction: column; background: rgba(255, 255, 255, 0.95); backdrop-filter: blur(10px); border-radius: 1rem; box-shadow: 0 4px 6px rgba(0, 0, 0, 0.05); overflow: hidden; // 防止内容溢出 .messages { flex: 1; overflow-y: auto; // 只允许消息区域滚动 padding: 2rem; } .input-area { flex-shrink: 0; padding: 1.5rem 2rem; background: rgba(255, 255, 255, 0.98); border-top: 1px solid rgba(0, 0, 0, 0.05); display: flex; flex-direction: column; gap: 1rem; .selected-files { background: rgba(0, 0, 0, 0.02); border-radius: 0.75rem; padding: 0.75rem; border: 1px solid rgba(0, 0, 0, 0.05); .file-item { display: flex; align-items: center; justify-content: space-between; padding: 0.75rem; background: #fff; border-radius: 0.5rem; margin-bottom: 0.75rem; border: 1px solid rgba(0, 0, 0, 0.05); transition: all 0.2s ease;  &:last-child { margin-bottom: 0; }  &:hover { background: rgba(0, 124, 240, 0.02); border-color: rgba(0, 124, 240, 0.2); }  .file-info { display: flex; align-items: center; gap: 0.75rem; .icon {  width: 1.5rem;  height: 1.5rem;  color: #007CF0; } .file-name {  font-size: 0.875rem;  color: #333;  font-weight: 500; } .file-size {  font-size: 0.75rem;  color: #666;  background: rgba(0, 0, 0, 0.05);  padding: 0.25rem 0.5rem;  border-radius: 1rem; } }  .remove-btn { padding: 0.375rem; border: none; background: rgba(0, 0, 0, 0.05); color: #666; cursor: pointer; border-radius: 0.375rem; transition: all 0.2s ease; &:hover {  background: #ff4d4f;  color: #fff; } .icon {  width: 1.25rem;  height: 1.25rem; } } } } .input-row { display: flex; gap: 1rem; align-items: flex-end; background: #fff; padding: 0.75rem; border-radius: 1rem; border: 1px solid rgba(0, 0, 0, 0.1); box-shadow: 0 2px 8px rgba(0, 0, 0, 0.05); .file-upload { .hidden { display: none; }  .upload-btn { width: 2.5rem; height: 2.5rem; display: flex; align-items: center; justify-content: center; border: none; border-radius: 0.75rem; background: rgba(0, 124, 240, 0.1); color: #007CF0; cursor: pointer; transition: all 0.2s ease; &:hover:not(:disabled) {  background: rgba(0, 124, 240, 0.2); } &:disabled {  opacity: 0.5;  cursor: not-allowed; } .icon {  width: 1.25rem;  height: 1.25rem; } } } textarea { flex: 1; resize: none; border: none; background: transparent; padding: 0.75rem; color: inherit; font-family: inherit; font-size: 1rem; line-height: 1.5; max-height: 150px;  &:focus { outline: none; }  &::placeholder { color: #999; } } .send-button { width: 2.5rem; height: 2.5rem; display: flex; align-items: center; justify-content: center; border: none; border-radius: 0.75rem; background: #007CF0; color: white; cursor: pointer; transition: all 0.2s ease;  &:hover:not(:disabled) { background: #0066cc; transform: translateY(-1px); }  &:disabled { background: #ccc; cursor: not-allowed; }  .icon { width: 1.25rem; height: 1.25rem; } } } } }}.dark { .sidebar { background: rgba(40, 40, 40, 0.95); box-shadow: 0 4px 6px rgba(0, 0, 0, 0.2); } .chat-main { background: rgba(40, 40, 40, 0.95); box-shadow: 0 4px 6px rgba(0, 0, 0, 0.2); .input-area { background: rgba(30, 30, 30, 0.98); border-top: 1px solid rgba(255, 255, 255, 0.05); .selected-files { background: rgba(255, 255, 255, 0.02); border-color: rgba(255, 255, 255, 0.05); .file-item { background: rgba(255, 255, 255, 0.02); border-color: rgba(255, 255, 255, 0.05);  &:hover { background: rgba(0, 124, 240, 0.1); border-color: rgba(0, 124, 240, 0.3); }  .file-info { .icon {  color: #007CF0; } .file-name {  color: #fff; } .file-size {  color: #999;  background: rgba(255, 255, 255, 0.1); } }  .remove-btn { background: rgba(255, 255, 255, 0.1); color: #999; &:hover {  background: #ff4d4f;  color: #fff; } } } } .input-row { background: rgba(255, 255, 255, 0.02); border-color: rgba(255, 255, 255, 0.05); box-shadow: none; textarea { color: #fff;  &::placeholder { color: #666; } } .file-upload .upload-btn { background: rgba(0, 124, 240, 0.2); color: #007CF0;  &:hover:not(:disabled) { background: rgba(0, 124, 240, 0.3); } } } } } .history-item { &:hover { background: rgba(255, 255, 255, 0.05) !important; } &.active { background: rgba(0, 124, 240, 0.2) !important; } } textarea { background: rgba(255, 255, 255, 0.05) !important; &:focus { background: rgba(255, 255, 255, 0.1) !important; } } .input-area { .file-upload { .upload-btn { background: rgba(255, 255, 255, 0.1); color: #999; &:hover:not(:disabled) { background: rgba(255, 255, 255, 0.2); color: #fff; } } } }}@media (max-width: 768px) { .ai-chat { .chat-container { padding: 0; } .sidebar { display: none; // 在移动端隐藏侧边栏 } .chat-main { border-radius: 0; } }} 

ChatMessage.vue 

 
 
   
 
 
     
 {{ message.content }} 
 
 
 
     
 
 
import { computed, onMounted, nextTick, ref, watch } from \'vue\'import { marked } from \'marked\'import DOMPurify from \'dompurify\'import { UserCircleIcon, ComputerDesktopIcon, DocumentDuplicateIcon, CheckIcon } from \'@heroicons/vue/24/outline\'import hljs from \'highlight.js\'import \'highlight.js/styles/github-dark.css\'const contentRef = ref(null)const copied = ref(false)const copyButtonTitle = computed(() => copied.value ? \'已复制\' : \'复制内容\')// 配置 markedmarked.setOptions({ breaks: true, gfm: true, sanitize: false})// 处理内容const processContent = (content) => { if (!content) return \'\' // 分析内容中的 think 标签 let result = \'\' let isInThinkBlock = false let currentBlock = \'\' // 逐字符分析，处理 think 标签 for (let i = 0; i < content.length; i++) { if (content.slice(i, i + 7) === \'\') { isInThinkBlock = true if (currentBlock) { // 将之前的普通内容转换为 HTML result += marked.parse(currentBlock) } currentBlock = \'\' i += 6 // 跳过  continue } if (content.slice(i, i + 8) === \'\') { isInThinkBlock = false // 将 think 块包装在特殊 div 中 result += `
${marked.parse(currentBlock)}
` currentBlock = \'\' i += 7 // 跳过  continue } currentBlock += content[i] } // 处理剩余内容 if (currentBlock) { if (isInThinkBlock) { result += `
${marked.parse(currentBlock)}
` } else { result += marked.parse(currentBlock) } } // 净化处理后的 HTML const cleanHtml = DOMPurify.sanitize(result, { ADD_TAGS: [\'think\', \'code\', \'pre\', \'span\'], ADD_ATTR: [\'class\', \'language\'] }) // 在净化后的 HTML 中查找代码块并添加复制按钮 const tempDiv = document.createElement(\'div\') tempDiv.innerHTML = cleanHtml // 查找所有代码块 const preElements = tempDiv.querySelectorAll(\'pre\') preElements.forEach(pre => { const code = pre.querySelector(\'code\') if (code) { // 创建包装器 const wrapper = document.createElement(\'div\') wrapper.className = \'code-block-wrapper\' // 添加复制按钮 const copyBtn = document.createElement(\'button\') copyBtn.className = \'code-copy-button\' copyBtn.title = \'复制代码\' copyBtn.innerHTML = `    ` // 添加成功消息 const successMsg = document.createElement(\'div\') successMsg.className = \'copy-success-message\' successMsg.textContent = \'已复制!\' // 组装结构 wrapper.appendChild(copyBtn) wrapper.appendChild(pre.cloneNode(true)) wrapper.appendChild(successMsg) // 替换原始的 pre 元素 pre.parentNode.replaceChild(wrapper, pre) } }) return tempDiv.innerHTML}// 修改计算属性const processedContent = computed(() => { if (!props.message.content) return \'\' return processContent(props.message.content)})// 为代码块添加复制功能const setupCodeBlockCopyButtons = () => { if (!contentRef.value) return; const codeBlocks = contentRef.value.querySelectorAll(\'.code-block-wrapper\'); codeBlocks.forEach(block => { const copyButton = block.querySelector(\'.code-copy-button\'); const codeElement = block.querySelector(\'code\'); const successMessage = block.querySelector(\'.copy-success-message\'); if (copyButton && codeElement) { // 移除旧的事件监听器 const newCopyButton = copyButton.cloneNode(true); copyButton.parentNode.replaceChild(newCopyButton, copyButton); // 添加新的事件监听器 newCopyButton.addEventListener(\'click\', async (e) => { e.preventDefault(); e.stopPropagation(); try { const code = codeElement.textContent || \'\'; await navigator.clipboard.writeText(code);  // 显示成功消息 if (successMessage) { successMessage.classList.add(\'visible\'); setTimeout(() => {  successMessage.classList.remove(\'visible\'); }, 2000); } } catch (err) { console.error(\'复制代码失败:\', err); } }); } });}// 在内容更新后手动应用高亮和设置复制按钮const highlightCode = async () => { await nextTick() if (contentRef.value) { contentRef.value.querySelectorAll(\'pre code\').forEach((block) => { hljs.highlightElement(block) }) // 设置代码块复制按钮 setupCodeBlockCopyButtons() }}const props = defineProps({ message: { type: Object, required: true }})const isUser = computed(() => props.message.role === \'user\')// 复制内容到剪贴板const copyContent = async () => { try { // 获取纯文本内容 let textToCopy = props.message.content; // 如果是AI回复，需要去除HTML标签 if (!isUser.value && contentRef.value) { // 创建临时元素来获取纯文本 const tempDiv = document.createElement(\'div\'); tempDiv.innerHTML = processedContent.value; textToCopy = tempDiv.textContent || tempDiv.innerText || \'\'; } await navigator.clipboard.writeText(textToCopy); copied.value = true; // 3秒后重置复制状态 setTimeout(() => { copied.value = false; }, 3000); } catch (err) { console.error(\'复制失败:\', err); }}// 监听内容变化watch(() => props.message.content, () => { if (!isUser.value) { highlightCode() }})// 初始化时也执行一次onMounted(() => { if (!isUser.value) { highlightCode() }})const formatTime = (timestamp) => { if (!timestamp) return \'\' return new Date(timestamp).toLocaleTimeString()}.message { display: flex; margin-bottom: 1.5rem; gap: 1rem; &.message-user { flex-direction: row-reverse; .content { align-items: flex-end; .text-container { position: relative; .text { background: #f0f7ff; // 浅色背景 color: #333; border-radius: 1rem 1rem 0 1rem; } .user-copy-button { position: absolute; left: -30px; top: 50%; transform: translateY(-50%); background: transparent; border: none; width: 24px; height: 24px; display: flex; align-items: center; justify-content: center; cursor: pointer; opacity: 0; transition: opacity 0.2s;  .copy-icon { width: 16px; height: 16px; color: #666; &.copied {  color: #4ade80; } } } &:hover .user-copy-button { opacity: 1; } } .message-footer { flex-direction: row-reverse; } } } .avatar { width: 40px; height: 40px; flex-shrink: 0; .icon { width: 100%; height: 100%; color: #666; padding: 4px; border-radius: 8px; transition: all 0.3s ease; &.assistant { color: #333; background: #f0f0f0; &:hover { background: #e0e0e0; transform: scale(1.05); } } } } .content { display: flex; flex-direction: column; gap: 0.25rem; max-width: 80%; .text-container { position: relative; } .message-footer { display: flex; align-items: center; margin-top: 0.25rem; .time { font-size: 0.75rem; color: #666; } .copy-button { display: flex; align-items: center; gap: 0.25rem; background: transparent; border: none; font-size: 0.75rem; color: #666; padding: 0.25rem 0.5rem; border-radius: 4px; cursor: pointer; margin-right: auto; transition: background-color 0.2s; &:hover { background-color: rgba(0, 0, 0, 0.05); } .copy-icon { width: 14px; height: 14px;  &.copied { color: #4ade80; } } .copy-text { font-size: 0.75rem; } } } .text { padding: 1rem; border-radius: 1rem 1rem 1rem 0; line-height: 1.5; white-space: pre-wrap; color: var(--text-color); .cursor { animation: blink 1s infinite; } :deep(.think-block) { position: relative; padding: 0.75rem 1rem 0.75rem 1.5rem; margin: 0.5rem 0; color: #666; font-style: italic; border-left: 4px solid #ddd; background-color: rgba(0, 0, 0, 0.03); border-radius: 0 0.5rem 0.5rem 0; // 添加平滑过渡效果 opacity: 1; transform: translateX(0); transition: opacity 0.3s ease, transform 0.3s ease; &::before { content: \'思考\'; position: absolute; top: -0.75rem; left: 1rem; padding: 0 0.5rem; font-size: 0.75rem; background: #f5f5f5; border-radius: 0.25rem; color: #999; font-style: normal; } // 添加进入动画 &:not(:first-child) { animation: slideIn 0.3s ease forwards; } } :deep(pre) { background: #f6f8fa; padding: 1rem; border-radius: 0.5rem; overflow-x: auto; margin: 0.5rem 0; border: 1px solid #e1e4e8; code { background: transparent; padding: 0; font-family: ui-monospace, SFMono-Regular, SF Mono, Menlo, Consolas, Liberation Mono, monospace; font-size: 0.9rem; line-height: 1.5; tab-size: 2; } } :deep(.hljs) { color: #24292e; background: transparent; } :deep(.hljs-keyword) { color: #d73a49; } :deep(.hljs-built_in) { color: #005cc5; } :deep(.hljs-type) { color: #6f42c1; } :deep(.hljs-literal) { color: #005cc5; } :deep(.hljs-number) { color: #005cc5; } :deep(.hljs-regexp) { color: #032f62; } :deep(.hljs-string) { color: #032f62; } :deep(.hljs-subst) { color: #24292e; } :deep(.hljs-symbol) { color: #e36209; } :deep(.hljs-class) { color: #6f42c1; } :deep(.hljs-function) { color: #6f42c1; } :deep(.hljs-title) { color: #6f42c1; } :deep(.hljs-params) { color: #24292e; } :deep(.hljs-comment) { color: #6a737d; } :deep(.hljs-doctag) { color: #d73a49; } :deep(.hljs-meta) { color: #6a737d; } :deep(.hljs-section) { color: #005cc5; } :deep(.hljs-name) { color: #22863a; } :deep(.hljs-attribute) { color: #005cc5; } :deep(.hljs-variable) { color: #e36209; } } }}@keyframes blink { 0%, 100% { opacity: 1; } 50% { opacity: 0; }}@keyframes slideIn { from { opacity: 0; transform: translateX(-10px); } to { opacity: 1; transform: translateX(0); }}.dark { .message { .avatar .icon { &.assistant { color: #fff; background: #444; &:hover { background: #555; } } } &.message-user { .content .text-container { .text { background: #1a365d; // 暗色模式下的浅蓝色背景 color: #fff; } .user-copy-button { .copy-icon { color: #999; &.copied {  color: #4ade80; } } } } } .content { .message-footer { .time { color: #999; } .copy-button { color: #999;  &:hover { background-color: rgba(255, 255, 255, 0.1); } } } .text { :deep(.think-block) { background-color: rgba(255, 255, 255, 0.03); border-left-color: #666; color: #999; &::before { background: #2a2a2a; color: #888; } } :deep(pre) { background: #161b22; border-color: #30363d; code { color: #c9d1d9; } } :deep(.hljs) { color: #c9d1d9; background: transparent; } :deep(.hljs-keyword) { color: #ff7b72; } :deep(.hljs-built_in) { color: #79c0ff; } :deep(.hljs-type) { color: #ff7b72; } :deep(.hljs-literal) { color: #79c0ff; } :deep(.hljs-number) { color: #79c0ff; } :deep(.hljs-regexp) { color: #a5d6ff; } :deep(.hljs-string) { color: #a5d6ff; } :deep(.hljs-subst) { color: #c9d1d9; } :deep(.hljs-symbol) { color: #ffa657; } :deep(.hljs-class) { color: #f2cc60; } :deep(.hljs-function) { color: #d2a8ff; } :deep(.hljs-title) { color: #d2a8ff; } :deep(.hljs-params) { color: #c9d1d9; } :deep(.hljs-comment) { color: #8b949e; } :deep(.hljs-doctag) { color: #ff7b72; } :deep(.hljs-meta) { color: #8b949e; } :deep(.hljs-section) { color: #79c0ff; } :deep(.hljs-name) { color: #7ee787; } :deep(.hljs-attribute) { color: #79c0ff; } :deep(.hljs-variable) { color: #ffa657; } } &.message-user .content .text { background: #0066cc; color: white; } } }}.markdown-content { :deep(p) { margin: 0.5rem 0; &:first-child { margin-top: 0; } &:last-child { margin-bottom: 0; } } :deep(ul), :deep(ol) { margin: 0.5rem 0; padding-left: 1.5rem; } :deep(li) { margin: 0.25rem 0; } :deep(code) { background: rgba(0, 0, 0, 0.05); padding: 0.2em 0.4em; border-radius: 3px; font-size: 0.9em; font-family: ui-monospace, monospace; } :deep(pre code) { background: transparent; padding: 0; } :deep(table) { border-collapse: collapse; margin: 0.5rem 0; width: 100%; } :deep(th), :deep(td) { border: 1px solid #ddd; padding: 0.5rem; text-align: left; } :deep(th) { background: rgba(0, 0, 0, 0.05); } :deep(blockquote) { margin: 0.5rem 0; padding-left: 1rem; border-left: 4px solid #ddd; color: #666; } :deep(.code-block-wrapper) { position: relative; margin: 1rem 0; border-radius: 6px; overflow: hidden; .code-copy-button { position: absolute; top: 0.5rem; right: 0.5rem; background: rgba(255, 255, 255, 0.1); border: none; color: #e6e6e6; cursor: pointer; padding: 0.25rem; border-radius: 4px; display: flex; align-items: center; justify-content: center; opacity: 0; transition: opacity 0.2s, background-color 0.2s; z-index: 10; &:hover { background-color: rgba(255, 255, 255, 0.2); } .code-copy-icon { width: 16px; height: 16px; } } &:hover .code-copy-button { opacity: 0.8; } pre { margin: 0; padding: 1rem; background: #1e1e1e; overflow-x: auto; code { background: transparent; padding: 0; font-family: ui-monospace, monospace; } } .copy-success-message { position: absolute; top: 0.5rem; right: 0.5rem; background: rgba(74, 222, 128, 0.9); color: white; padding: 0.25rem 0.5rem; border-radius: 4px; font-size: 0.75rem; opacity: 0; transform: translateY(-10px); transition: opacity 0.3s, transform 0.3s; pointer-events: none; z-index: 20; &.visible { opacity: 1; transform: translateY(0); } } }}.dark { .markdown-content { :deep(.code-block-wrapper) { .code-copy-button { background: rgba(255, 255, 255, 0.05); &:hover { background-color: rgba(255, 255, 255, 0.1); } } pre { background: #0d0d0d; } } :deep(code) { background: rgba(255, 255, 255, 0.1); } :deep(th), :deep(td) { border-color: #444; } :deep(th) { background: rgba(255, 255, 255, 0.1); } :deep(blockquote) { border-left-color: #444; color: #999; } }}

api.js 接口调用js

const BASE_URL = \'http://localhost:8080\'export const chatAPI = { // 发送聊天消息 async sendMessage(data, chatId) { try { const url = new URL(`${BASE_URL}/ai/chat`) if (chatId) { url.searchParams.append(\'chatId\', chatId) } const response = await fetch(url, { method: \'POST\', body: data instanceof FormData ? data :  new URLSearchParams({ prompt: data }) }) if (!response.ok) { throw new Error(`HTTP error! status: ${response.status}`) } return response.body.getReader() } catch (error) { console.error(\'API Error:\', error) throw error } }, // 获取聊天历史列表 async getChatHistory(type = \'chat\') { // 添加类型参数 try { const response = await fetch(`${BASE_URL}/ai/history/${type}`) if (!response.ok) { throw new Error(`HTTP error! status: ${response.status}`) } const chatIds = await response.json() // 转换为前端需要的格式 return chatIds.map(id => ({ id, title: type === \'pdf\' ? `PDF对话 ${id.slice(-6)}` : type === \'service\' ? `咨询 ${id.slice(-6)}` :  `对话 ${id.slice(-6)}` })) } catch (error) { console.error(\'API Error:\', error) return [] } }, // 获取特定对话的消息历史 async getChatMessages(chatId, type = \'chat\') { // 添加类型参数 try { const response = await fetch(`${BASE_URL}/ai/history/${type}/${chatId}`) if (!response.ok) { throw new Error(`HTTP error! status: ${response.status}`) } const messages = await response.json() // 添加时间戳 return messages.map(msg => ({ ...msg, timestamp: new Date() // 由于后端没有提供时间戳，这里临时使用当前时间 })) } catch (error) { console.error(\'API Error:\', error) return [] } },

如果有什么疑问或者建议欢迎评论区留言讨论！