【Spring AI實戰】實現仿DeepSeek頁面對話機器人(支持多模態上傳)

一、前言

二、實現效果

三、代碼實現

????????3.1 后端代碼

????????3.2 前端代碼

一、前言

Spring AI詳解：【Spring AI詳解】開啟Java生態的智能應用開發新時代(附不同功能的Spring AI實戰項目)-CSDN博客

二、實現效果

可上傳圖片或音頻數據給大模型分析

三、代碼實現

3.1 后端代碼

pom.xml

    <!-- 繼承Spring Boot父POM，提供默認依賴管理 --><parent><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-parent</artifactId><version>3.4.3</version> <!-- Spring Boot版本 --><relativePath/> <!-- 優先從本地倉庫查找 --></parent><!-- 自定義屬性 --><properties><java.version>17</java.version> <!-- JDK版本要求 --><spring-ai.version>1.0.0-M6</spring-ai.version> <!-- Spring AI里程碑版本 --></properties><!-- 項目依賴 --><dependencies><!-- Spring Boot Web支持 --><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-web</artifactId></dependency><!-- AI相關依賴 --><dependency><groupId>org.springframework.ai</groupId><artifactId>spring-ai-ollama-spring-boot-starter</artifactId> <!-- Ollama集成 --></dependency><dependency><groupId>org.springframework.ai</groupId><artifactId>spring-ai-openai-spring-boot-starter</artifactId> <!-- OpenAI集成 --></dependency><!-- 開發工具 --><dependency><groupId>org.projectlombok</groupId><artifactId>lombok</artifactId><version>1.18.22</version> <!-- 注解簡化代碼 --><scope>provided</scope> <!-- 編譯期使用 --></dependency></dependencies><!-- 依賴管理（統一Spring AI家族版本） --><dependencyManagement><dependencies><dependency><groupId>org.springframework.ai</groupId><artifactId>spring-ai-bom</artifactId><version>${spring-ai.version}</version><type>pom</type><scope>import</scope> <!-- 導入BOM管理版本 --></dependency></dependencies></dependencyManagement>

?application.ymal

可選擇ollama或者openai其一進行大模型配置

server:tomcat:max-swallow-size: -1     # 禁用Tomcat的請求大小限制（或設為足夠大的值，如100MB）
spring:application:name: heima-aiservlet:multipart:max-file-size: 50MB    # 單個文件限制max-request-size: 100MB # 單次請求總限制# AI服務配置（多引擎支持）ai:# Ollama配置（本地大模型引擎）ollama:base-url: http://localhost:11434  # Ollama服務地址（默認端口11434）chat:model: deepseek-r1:7b  # 使用的模型名稱（7B參數的本地模型）# 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端點api-key: ${OPENAI_API_KEY}  # 從環境變量讀取API密鑰（安全建議）chat:options:model: qwen-max-latest  # 通義千問最新版本模型# 日志級別配置
logging:level:org.springframework.ai: debug  # 打印Spring AI框架調試日志com.itheima.ai: debug         # 打印業務代碼調試日志

特別注意：在SpringAI的當前版本（1.0.0-m6)中，qwen-omni與SpringAI中的OpenAI模塊的兼容性有問題，目前僅支持文本和圖片兩種模態。音頻會有數據格式錯誤問題，視頻完全不支持。音頻識別中的數據格式，阿里云百煉的qwen-omni模型要求的參數格式為data:;base64,${media-data}，而OpenAI是直接{media-data}。

目前的解決方案有兩種：

一是使用spring-ai-alibaba來替代。
二是重寫OpenAIModel的實現。

接下來，我們就用重寫OpenAiModel的方式，來實現多模態效果。

自實現 AlibabaOpenAiChatModel (仿照OpenAiModel來寫)

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.*/@Deprecatedpublic 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.*/@Deprecatedpublic 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.*/@Deprecatedpublic 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.*/@Deprecatedpublic AlibabaOpenAiChatModel(OpenAiApi openAiApi, OpenAiChatOptions options,@Nullable FunctionCallbackResolver functionCallbackResolver,@Nullable List<FunctionCallback> 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).*/@Deprecatedpublic AlibabaOpenAiChatModel(OpenAiApi openAiApi, OpenAiChatOptions options,@Nullable FunctionCallbackResolver functionCallbackResolver,@Nullable List<FunctionCallback> 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;}@Overridepublic 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<OpenAiApi.ChatCompletion> 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<OpenAiApi.ChatCompletion.Choice> choices = chatCompletion.choices();if (choices == null) {logger.warn("No choices returned for prompt: {}", prompt);return new ChatResponse(List.of());}List<Generation> generations = choices.stream().map(choice -> {// @formatter:offMap<String, Object> 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:onreturn buildGeneration(choice, metadata, request);}).toList();RateLimit rateLimit = OpenAiResponseHeaderExtractor.extractAiResponseHeaders(completionEntity);// Current usageOpenAiApi.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;}@Overridepublic Flux<ChatResponse> 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<ChatResponse> 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<OpenAiApi.ChatCompletionChunk> 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<String, String> 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> chatResponse = completionChunks.map(this::chunkToChatCompletion).switchMap(chatCompletion -> Mono.just(chatCompletion).map(chatCompletion2 -> {try {@SuppressWarnings("null")String id = chatCompletion2.id();List<Generation> generations = chatCompletion2.choices().stream().map(choice -> { // @formatter:offif (choice.message().role() != null) {roleMap.putIfAbsent(id, choice.message().role().name());}Map<String, Object> 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:onOpenAiApi.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:offFlux<ChatResponse> 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:onreturn new MessageAggregator().aggregate(flux, observationContext::setResponse);});}private MultiValueMap<String, String> getAdditionalHttpHeaders(Prompt prompt) {Map<String, String> 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<String, Object> metadata, OpenAiApi.ChatCompletionRequest request) {List<AssistantMessage.ToolCall> 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> 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<OpenAiApi.ChatCompletion.Choice> 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 optionsOpenAiChatOptions 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 optionsOpenAiChatOptions 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<String, String> mergeHttpHeaders(Map<String, String> runtimeHttpHeaders,Map<String, String> defaultHttpHeaders) {var mergedHttpHeaders = new HashMap<>(defaultHttpHeaders);mergedHttpHeaders.putAll(runtimeHttpHeaders);return mergedHttpHeaders;}/*** Accessible for testing.*/OpenAiApi.ChatCompletionRequest createRequest(Prompt prompt, boolean stream) {List<OpenAiApi.ChatCompletionMessage> 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<OpenAiApi.ChatCompletionMessage.MediaContent> 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<OpenAiApi.ChatCompletionMessage.ToolCall> 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<ToolDefinition> 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 requestif (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<OpenAiApi.FunctionTool> getFunctionTools(List<ToolDefinition> toolDefinitions) {return toolDefinitions.stream().map(toolDefinition -> {var function = new OpenAiApi.FunctionTool.Function(toolDefinition.description(), toolDefinition.name(),toolDefinition.inputSchema());return new OpenAiApi.FunctionTool(function);}).toList();}@Overridepublic ChatOptions getDefaultOptions() {return OpenAiChatOptions.fromOptions(this.defaultOptions);}@Overridepublic 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<FunctionCallback> 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;}@Deprecatedpublic AlibabaOpenAiChatModel.Builder functionCallbackResolver(FunctionCallbackResolver functionCallbackResolver) {this.functionCallbackResolver = functionCallbackResolver;return this;}@Deprecatedpublic AlibabaOpenAiChatModel.Builder toolFunctionCallbacks(List<FunctionCallback> 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<FunctionCallback> 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配置類?

InMemoryChatMemory實現本地聊天記錄存儲

/*** AI核心配置類** 核心組件：* 1. 聊天記憶管理（ChatMemory）* 2. 多種場景的ChatClient實例*/
@Configuration
public class ChatConfiguration {/*** 內存式聊天記憶存儲* @return InMemoryChatMemory 實例** 作用：保存對話上下文，實現多輪對話能力* 實現原理：基于ConcurrentHashMap的線程安全實現*/@Beanpublic ChatMemory chatMemory() {return new InMemoryChatMemory();}/*** 通用聊天客戶端* @param model 阿里云OpenAI模型* @param chatMemory 聊天記憶* @return 配置好的ChatClient** 默認配置：* - 使用qwen-omni-turbo模型* - 設定AI人格為"小小"* - 啟用日志記錄和記憶功能*/@Beanpublic ChatClient chatClient(AlibabaOpenAiChatModel model, ChatMemory chatMemory) {return ChatClient.builder(model).defaultOptions(ChatOptions.builder().model("qwen-omni-turbo").build()) // 自定義模型不與配置文件的沖突.defaultSystem("你是一個熱心、聰明、全知的智能助手，你的名字叫小小，請以小小的身份和語氣回答問題。").defaultAdvisors(new SimpleLoggerAdvisor(),  // 日志記錄new MessageChatMemoryAdvisor(chatMemory)  // 記憶功能).build();}/*** 定制化阿里云OpenAI模型* @return AlibabaOpenAiChatModel 實例** 配置要點：* 1. 支持多級參數繼承（chatProperties > commonProperties）* 2. 自動配置HTTP客戶端（RestClient/WebClient）* 3. 集成可觀測性體系*/@Beanpublic AlibabaOpenAiChatModel alibabaOpenAiChatModel(OpenAiConnectionProperties commonProperties,OpenAiChatProperties chatProperties,ObjectProvider<RestClient.Builder> restClientBuilderProvider,ObjectProvider<WebClient.Builder> webClientBuilderProvider,ToolCallingManager toolCallingManager,RetryTemplate retryTemplate,ResponseErrorHandler responseErrorHandler,ObjectProvider<ObservationRegistry> observationRegistry,ObjectProvider<ChatModelObservationConvention> observationConvention) {// 參數優先級處理String baseUrl = StringUtils.hasText(chatProperties.getBaseUrl())? chatProperties.getBaseUrl(): commonProperties.getBaseUrl();String apiKey = StringUtils.hasText(chatProperties.getApiKey())? chatProperties.getApiKey(): commonProperties.getApiKey();// 組織頭信息配置Map<String, List<String>> 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)));// 構建OpenAI API客戶端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();// 構建定制化聊天模型AlibabaOpenAiChatModel chatModel = AlibabaOpenAiChatModel.builder().openAiApi(openAiApi).defaultOptions(chatProperties.getOptions()).toolCallingManager(toolCallingManager).retryTemplate(retryTemplate).observationRegistry(observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP)).build();// 配置可觀測性約定observationConvention.ifAvailable(chatModel::setObservationConvention);return chatModel;}}

ChatController對話類

會話id由前端進行生成并傳輸過來，當然也可后端自己生成并且存入數據庫，不過這里由于是簡單的實現，由本地Map實現會話及信息的存儲

根據前端是否傳過來files來判斷是否為多模態調用，有文件則走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 // 構造方式自動注入
@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<String> chat(@RequestParam("prompt") String prompt,@RequestParam("chatId") String chatId,@RequestParam(value = "files", required = false) List<MultipartFile> files) {// 1.保存會話idchatHistoryRepository.save("chat", chatId);// 2.請求模型if (files == null || files.isEmpty()) {// 沒有附件，純文本聊天return textChat(prompt, chatId);} else {// 有附件，多模態聊天return multiModalChat(prompt, chatId, files);}}private Flux<String> multiModalChat(String prompt, String chatId, List<MultipartFile> files) {// 1.遍歷解析多媒體，轉為Media對象List<Media> medias = files.stream().map(file -> new Media(MimeType.valueOf(Objects.requireNonNull(file.getContentType())),file.getResource())).toList();// 2.請求模型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<String> textChat(String prompt, String chatId) {return chatClient.prompt().user(prompt).advisors(a -> a.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)).stream().content();}
}

ChatHistoryController會話歷史類

實現本地Map存儲chat類型與所有會話歷史的對應關系，找到會話后就可用根據聊天記憶ChatMemory找到聊天歷史

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<String> getChatIds(@PathVariable("type") String type) {return chatHistoryRepository.getChatIds(type);}@GetMapping("/{type}/{chatId}")public List<MessageVO> getChatHistory(@PathVariable("type") String type, @PathVariable("chatId") String chatId) {List<Message> messages = chatMemory.get(chatId, Integer.MAX_VALUE);if(messages == null) {return List.of();}// 轉換成VOreturn messages.stream().map(MessageVO::new).toList();}
}

ChatHistoryRepository 會話歷史業務接口?

import java.util.List;public interface ChatHistoryRepository {/*** 保存會話記錄* @param type 業務類型，如：chat、service、pdf* @param chatId 會話ID*/void save(String type, String chatId);/*** 獲取會話ID列表* @param type 業務類型，如：chat、service、pdf* @return 會話ID列表*/List<String> getChatIds(String type);
}

InMemoryChatHistoryRepository實現類

@Slf4j
@Component
@RequiredArgsConstructor
public class InMemoryChatHistoryRepository implements ChatHistoryRepository {// 會話chatId存儲Mapprivate Map<String, List<String>> chatHistory;private final ChatMemory chatMemory;// 保存會話ID@Overridepublic void save(String type, String chatId) {/*if (!chatHistory.containsKey(type)) {chatHistory.put(type, new ArrayList<>());}List<String> chatIds = chatHistory.get(type);*/List<String> chatIds = chatHistory.computeIfAbsent(type, k -> new ArrayList<>());if (chatIds.contains(chatId)) {return;}chatIds.add(chatId);}// 獲取所有會話id@Overridepublic List<String> getChatIds(String type) {/*List<String> chatIds = chatHistory.get(type);return chatIds == null ? List.of() : chatIds;*/return chatHistory.getOrDefault(type, List.of());}}

MessageVO返回實體類?

根據ChatMemory中存儲的Message可知有四種類型，則根據Message來示例VO對象

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

import lombok.Data;
import lombok.NoArgsConstructor;
import org.springframework.ai.chat.messages.Message;@NoArgsConstructor
@Data
public 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 前端代碼

可以根據這些代碼與接口讓Cursor生成一個仿deepseek頁面即可實現，或者根據下列Vue項目代碼修改實現(實現效果中的代碼)

AIChat.vue

<template><div class="ai-chat" :class="{ 'dark': isDark }"><div class="chat-container"><div class="sidebar"><div class="history-header"><h2>聊天記錄</h2><button class="new-chat" @click="startNewChat"><PlusIcon class="icon" />新對話</button></div><div class="history-list"><div v-for="chat in chatHistory" :key="chat.id"class="history-item":class="{ 'active': currentChatId === chat.id }"@click="loadChat(chat.id)"><ChatBubbleLeftRightIcon class="icon" /><span class="title">{{ chat.title || '新對話' }}</span></div></div></div><div class="chat-main"><div class="messages" ref="messagesRef"><ChatMessagev-for="(message, index) in currentMessages":key="index":message="message":is-stream="isStreaming && index === currentMessages.length - 1"/></div><div class="input-area"><div v-if="selectedFiles.length > 0" class="selected-files"><div v-for="(file, index) in selectedFiles" :key="index" class="file-item"><div class="file-info"><DocumentIcon class="icon" /><span class="file-name">{{ file.name }}</span><span class="file-size">({{ formatFileSize(file.size) }})</span></div><button class="remove-btn" @click="removeFile(index)"><XMarkIcon class="icon" /></button></div></div><div class="input-row"><div class="file-upload"><input type="file" ref="fileInput"@change="handleFileUpload"accept="image/*,audio/*,video/*"multipleclass="hidden"><button class="upload-btn"@click="triggerFileInput":disabled="isStreaming"><PaperClipIcon class="icon" /></button></div><textareav-model="userInput"@keydown.enter.prevent="sendMessage":placeholder="getPlaceholder()"rows="1"ref="inputRef"></textarea><button class="send-button" @click="sendMessage":disabled="isStreaming || (!userInput.trim() && !selectedFiles.length)"><PaperAirplaneIcon class="icon" /></button></div></div></div></div></div>
</template><script setup>
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([])// 自動調整輸入框高度
const adjustTextareaHeight = () => {const textarea = inputRef.valueif (textarea) {textarea.style.height = 'auto'textarea.style.height = textarea.scrollHeight + 'px'}else{textarea.style.height = '50px'}
}// 滾動到底部
const scrollToBottom = async () => {await nextTick()if (messagesRef.value) {messagesRef.value.scrollTop = messagesRef.value.scrollHeight}
}// 文件類型限制
const FILE_LIMITS = {image: { maxSize: 10 * 1024 * 1024,  // 單個文件 10MBmaxFiles: 3,                 // 最多 3 個文件description: '圖片文件'},audio: { maxSize: 10 * 1024 * 1024,  // 單個文件 10MBmaxDuration: 180,           // 3分鐘maxFiles: 3,                // 最多 3 個文件description: '音頻文件'},video: { maxSize: 150 * 1024 * 1024, // 單個文件 150MBmaxDuration: 40,            // 40秒maxFiles: 3,                // 最多 3 個文件description: '視頻文件'}
}// 觸發文件選擇
const triggerFileInput = () => {fileInput.value?.click()
}// 檢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: '不支持的文件類型' }}if (file.size > limit.maxSize) {return { valid: false, error: `文件大小不能超過${limit.maxSize / 1024 / 1024}MB` }}if ((type === 'audio' || type === 'video') && limit.maxDuration) {try {const duration = await getMediaDuration(file)if (duration > limit.maxDuration) {return { valid: false, error: `${type === 'audio' ? '音頻' : '視頻'}時長不能超過${limit.maxDuration}秒`}}} catch (error) {return { valid: false, error: '無法讀取媒體文件時長' }}}return { valid: true }
}// 獲取媒體文件時長
const getMediaDuration = (file) => {return new Promise((resolve, reject) => {const element = file.type.startsWith('audio/') ? new Audio() : document.createElement('video')element.preload = 'metadata'element.onloadedmetadata = () => {resolve(element.duration)URL.revokeObjectURL(element.src)}element.onerror = () => {reject(new Error('無法讀取媒體文件'))URL.revokeObjectURL(element.src)}element.src = URL.createObjectURL(file)})
}// 修改文件上傳處理函數
const handleFileUpload = async (event) => {const files = Array.from(event.target.files || [])if (!files.length) return// 檢查所有文件類型是否一致const firstFileType = files[0].type.split('/')[0]const hasInconsistentType = files.some(file => file.type.split('/')[0] !== firstFileType)if (hasInconsistentType) {alert('請選擇相同類型的文件（圖片、音頻或視頻）')event.target.value = ''return}// 驗證所有文件for (const file of files) {const { valid, error } = await validateFile(file)if (!valid) {alert(error)event.target.value = ''selectedFiles.value = []return}}// 檢查文件總大小const totalSize = files.reduce((sum, file) => sum + file.size, 0)const limit = FILE_LIMITS[firstFileType]if (totalSize > limit.maxSize * 3) { // 允許最多3個文件的總大小alert(`${firstFileType === 'image' ? '圖片' : firstFileType === 'audio' ? '音頻' : '視頻'}文件總大小不能超過${(limit.maxSize * 3) / 1024 / 1024}MB`)event.target.value = ''selectedFiles.value = []return}selectedFiles.value = files
}// 修改文件輸入提示
const getPlaceholder = () => {if (selectedFiles.value.length > 0) {const type = selectedFiles.value[0].type.split('/')[0]const desc = FILE_LIMITS[type].descriptionreturn `已選擇 ${selectedFiles.value.length} 個${desc}，可繼續輸入消息...`}return '輸入消息，可上傳圖片、音頻或視頻...'
}// 修改發送消息函數
const sendMessage = async () => {if (isStreaming.value) returnif (!userInput.value.trim() && !selectedFiles.value.length) returnconst messageContent = userInput.value.trim()// 添加用戶消息const userMessage = {role: 'user',content: messageContent,timestamp: new Date()}currentMessages.value.push(userMessage)// 清空輸入userInput.value = ''adjustTextareaHeight()await scrollToBottom()// 準備發送數據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 = truetry {const reader = await chatAPI.sendMessage(formData, currentChatId.value)const decoder = new TextDecoder('utf-8')let accumulatedContent = ''  // 添加累積內容變量while (true) {try {const { value, done } = await reader.read()if (done) break// 累積新內容accumulatedContent += decoder.decode(value)  // 追加新內容await nextTick(() => {// 更新消息，使用累積的內容const updatedMessage = {...assistantMessage,content: accumulatedContent  // 使用累積的內容}const lastIndex = currentMessages.value.length - 1currentMessages.value.splice(lastIndex, 1, updatedMessage)})await scrollToBottom()} catch (readError) {console.error('讀取流錯誤:', readError)break}}} catch (error) {console.error('發送消息失敗:', error)assistantMessage.content = '抱歉，發生了錯誤，請稍后重試。'} finally {isStreaming.value = falseselectedFiles.value = [] // 清空已選文件fileInput.value.value = '' // 清空文件輸入await scrollToBottom()}
}// 加載特定對話
const loadChat = async (chatId) => {currentChatId.value = chatIdtry {const messages = await chatAPI.getChatMessages(chatId, 'chat')currentMessages.value = messages} catch (error) {console.error('加載對話消息失敗:', error)currentMessages.value = []}
}// 加載聊天歷史
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('加載聊天歷史失敗:', error)chatHistory.value = []startNewChat()}
}// 開始新對話
const startNewChat = () => {const newChatId = Date.now().toString()currentChatId.value = newChatIdcurrentMessages.value = []// 添加新對話到聊天歷史列表const newChat = {id: newChatId,title: `對話 ${newChatId.slice(-6)}`}chatHistory.value = [newChat, ...chatHistory.value] // 將新對話添加到列表開頭
}// 格式化文件大小
const formatFileSize = (bytes) => {if (bytes < 1024) return bytes + ' B'if (bytes < 1024 * 1024) return (bytes / 1024).toFixed(1) + ' KB'return (bytes / (1024 * 1024)).toFixed(1) + ' MB'
}// 移除文件
const removeFile = (index) => {selectedFiles.value = selectedFiles.value.filter((_, i) => i !== index)if (selectedFiles.value.length === 0) {fileInput.value.value = ''  // 清空文件輸入}
}onMounted(() => {loadChatHistory()adjustTextareaHeight()
})
</script><style scoped lang="scss">
.ai-chat {position: fixed;  // 修改為固定定位top: 64px;       // 導航欄高度left: 0;right: 0;bottom: 0;display: flex;background: var(--bg-color);overflow: hidden; // 防止頁面滾動.chat-container {flex: 1;display: flex;max-width: 1800px;width: 100%;margin: 0 auto;padding: 1.5rem 2rem;gap: 1.5rem;height: 100%;    // 確保容器占滿高度overflow: hidden; // 防止容器滾動}.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;  // 防止頭部壓縮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;  // 允許歷史記錄滾動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;  // 防止內容溢出.messages {flex: 1;overflow-y: auto;  // 只允許消息區域滾動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; // 在移動端隱藏側邊欄}.chat-main {border-radius: 0;}}
}
</style>

ChatMessage.vue?

<template><div class="message" :class="{ 'message-user': isUser }"><div class="avatar"><UserCircleIcon v-if="isUser" class="icon" /><ComputerDesktopIcon v-else class="icon" :class="{ 'assistant': !isUser }" /></div><div class="content"><div class="text-container"><button v-if="isUser" class="user-copy-button" @click="copyContent" :title="copyButtonTitle"><DocumentDuplicateIcon v-if="!copied" class="copy-icon" /><CheckIcon v-else class="copy-icon copied" /></button><div class="text" ref="contentRef" v-if="isUser">{{ message.content }}</div><div class="text markdown-content" ref="contentRef" v-else v-html="processedContent"></div></div><div class="message-footer" v-if="!isUser"><button class="copy-button" @click="copyContent" :title="copyButtonTitle"><DocumentDuplicateIcon v-if="!copied" class="copy-icon" /><CheckIcon v-else class="copy-icon copied" /></button></div></div></div>
</template><script setup>
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 ? '已復制' : '復制內容')// 配置 marked
marked.setOptions({breaks: true,gfm: true,sanitize: false
})// 處理內容
const processContent = (content) => {if (!content) return ''// 分析內容中的 think 標簽let result = ''let isInThinkBlock = falselet currentBlock = ''// 逐字符分析，處理 think 標簽for (let i = 0; i < content.length; i++) {if (content.slice(i, i + 7) === '<think>') {isInThinkBlock = trueif (currentBlock) {// 將之前的普通內容轉換為 HTMLresult += marked.parse(currentBlock)}currentBlock = ''i += 6 // 跳過 <think>continue}if (content.slice(i, i + 8) === '</think>') {isInThinkBlock = false// 將 think 塊包裝在特殊 div 中result += `<div class="think-block">${marked.parse(currentBlock)}</div>`currentBlock = ''i += 7 // 跳過 </think>continue}currentBlock += content[i]}// 處理剩余內容if (currentBlock) {if (isInThinkBlock) {result += `<div class="think-block">${marked.parse(currentBlock)}</div>`} else {result += marked.parse(currentBlock)}}// 凈化處理后的 HTMLconst cleanHtml = DOMPurify.sanitize(result, {ADD_TAGS: ['think', 'code', 'pre', 'span'],ADD_ATTR: ['class', 'language']})// 在凈化后的 HTML 中查找代碼塊并添加復制按鈕const tempDiv = document.createElement('div')tempDiv.innerHTML = cleanHtml// 查找所有代碼塊const preElements = tempDiv.querySelectorAll('pre')preElements.forEach(pre => {const code = pre.querySelector('code')if (code) {// 創建包裝器const wrapper = document.createElement('div')wrapper.className = 'code-block-wrapper'// 添加復制按鈕const copyBtn = document.createElement('button')copyBtn.className = 'code-copy-button'copyBtn.title = '復制代碼'copyBtn.innerHTML = `<svg xmlns="http://www.w3.org/2000/svg" class="code-copy-icon" fill="none" viewBox="0 0 24 24" stroke="currentColor"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M8 16H6a2 2 0 01-2-2V6a2 2 0 012-2h8a2 2 0 012 2v2m-6 12h8a2 2 0 002-2v-8a2 2 0 00-2-2h-8a2 2 0 00-2 2v8a2 2 0 002 2z" /></svg>`// 添加成功消息const successMsg = document.createElement('div')successMsg.className = 'copy-success-message'successMsg.textContent = '已復制!'// 組裝結構wrapper.appendChild(copyBtn)wrapper.appendChild(pre.cloneNode(true))wrapper.appendChild(successMsg)// 替換原始的 pre 元素pre.parentNode.replaceChild(wrapper, pre)}})return tempDiv.innerHTML
}// 修改計算屬性
const processedContent = computed(() => {if (!props.message.content) return ''return processContent(props.message.content)
})// 為代碼塊添加復制功能
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) {// 移除舊的事件監聽器const newCopyButton = copyButton.cloneNode(true);copyButton.parentNode.replaceChild(newCopyButton, copyButton);// 添加新的事件監聽器newCopyButton.addEventListener('click', async (e) => {e.preventDefault();e.stopPropagation();try {const code = codeElement.textContent || '';await navigator.clipboard.writeText(code);// 顯示成功消息if (successMessage) {successMessage.classList.add('visible');setTimeout(() => {successMessage.classList.remove('visible');}, 2000);}} catch (err) {console.error('復制代碼失敗:', err);}});}});
}// 在內容更新后手動應用高亮和設置復制按鈕
const highlightCode = async () => {await nextTick()if (contentRef.value) {contentRef.value.querySelectorAll('pre code').forEach((block) => {hljs.highlightElement(block)})// 設置代碼塊復制按鈕setupCodeBlockCopyButtons()}
}const props = defineProps({message: {type: Object,required: true}
})const isUser = computed(() => props.message.role === 'user')// 復制內容到剪貼板
const copyContent = async () => {try {// 獲取純文本內容let textToCopy = props.message.content;// 如果是AI回復，需要去除HTML標簽if (!isUser.value && contentRef.value) {// 創建臨時元素來獲取純文本const tempDiv = document.createElement('div');tempDiv.innerHTML = processedContent.value;textToCopy = tempDiv.textContent || tempDiv.innerText || '';}await navigator.clipboard.writeText(textToCopy);copied.value = true;// 3秒后重置復制狀態setTimeout(() => {copied.value = false;}, 3000);} catch (err) {console.error('復制失敗:', err);}
}// 監聽內容變化
watch(() => props.message.content, () => {if (!isUser.value) {highlightCode()}
})// 初始化時也執行一次
onMounted(() => {if (!isUser.value) {highlightCode()}
})const formatTime = (timestamp) => {if (!timestamp) return ''return new Date(timestamp).toLocaleTimeString()
}
</script><style scoped lang="scss">
.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; // 淺色背景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;// 添加平滑過渡效果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;}// 添加進入動畫&: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; // 暗色模式下的淺藍色背景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;}}
}
</style>

api.js 接口調用js

const BASE_URL = 'http://localhost:8080'export const chatAPI = {// 發送聊天消息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: ${response.status}`)}return response.body.getReader()} catch (error) {console.error('API Error:', error)throw error}},// 獲取聊天歷史列表async getChatHistory(type = 'chat') {  // 添加類型參數try {const response = await fetch(`${BASE_URL}/ai/history/${type}`)if (!response.ok) {throw new Error(`HTTP error! status: ${response.status}`)}const chatIds = await response.json()// 轉換為前端需要的格式return chatIds.map(id => ({id,title: type === 'pdf' ? `PDF對話 ${id.slice(-6)}` : type === 'service' ? `咨詢 ${id.slice(-6)}` :`對話 ${id.slice(-6)}`}))} catch (error) {console.error('API Error:', error)return []}},// 獲取特定對話的消息歷史async getChatMessages(chatId, type = 'chat') {  // 添加類型參數try {const response = await fetch(`${BASE_URL}/ai/history/${type}/${chatId}`)if (!response.ok) {throw new Error(`HTTP error! status: ${response.status}`)}const messages = await response.json()// 添加時間戳return messages.map(msg => ({...msg,timestamp: new Date() // 由于后端沒有提供時間戳，這里臨時使用當前時間}))} catch (error) {console.error('API Error:', error)return []}},

如果有什么疑問或者建議歡迎評論區留言討論！