Merge pull request #196 from zhangyue-mars/add-deepseek-java-files

feat: update ChatRequest and DeepSeekChatImpl for DeepSeek integration
This commit is contained in:
ageerle
2025-10-12 19:06:09 +08:00
committed by GitHub
3 changed files with 323 additions and 45 deletions

View File

@@ -72,6 +72,11 @@ public class ChatRequest {
*/
private Boolean hasAttachment;
/**
* 是否启用深度思考
*/
private Boolean enableThinking;
/**
* 是否自动切换模型
*/
@@ -82,9 +87,4 @@ public class ChatRequest {
*/
private String token;
/**
* 消息ID保存消息成功后设置用于后续扣费更新
*/
private Long messageId;
}

View File

@@ -1,21 +1,39 @@
package org.ruoyi.chat.service.chat.impl;
import dev.langchain4j.data.message.ChatMessage;
import dev.langchain4j.data.message.SystemMessage;
import dev.langchain4j.data.message.UserMessage;
import dev.langchain4j.model.chat.StreamingChatModel;
import dev.langchain4j.model.chat.response.ChatResponse;
import dev.langchain4j.model.chat.response.StreamingChatResponseHandler;
import dev.langchain4j.model.openai.OpenAiStreamingChatModel;
import lombok.SneakyThrows;
import lombok.extern.slf4j.Slf4j;
import okhttp3.*;
import okhttp3.Response;
import org.ruoyi.chat.enums.ChatModeType;
import org.ruoyi.chat.service.chat.IChatService;
import org.ruoyi.chat.support.ChatServiceHelper;
import org.ruoyi.common.chat.entity.chat.Message;
import org.ruoyi.common.chat.request.ChatRequest;
import org.ruoyi.domain.vo.ChatModelVo;
import org.ruoyi.service.IChatModelService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Service;
import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;
import java.io.IOException;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.concurrent.TimeUnit;
import java.io.BufferedReader;
import java.io.InputStreamReader;
import com.fasterxml.jackson.databind.ObjectMapper;
/**
* deepseek
*/
@@ -26,9 +44,24 @@ public class DeepSeekChatImpl implements IChatService {
@Autowired
private IChatModelService chatModelService;
private static final MediaType JSON = MediaType.get("application/json; charset=utf-8");
// 创建一个用于直接API调用的OkHttpClient
private final OkHttpClient client = new OkHttpClient.Builder()
.connectTimeout(30, TimeUnit.SECONDS)
.readTimeout(60, TimeUnit.SECONDS)
.writeTimeout(30, TimeUnit.SECONDS)
.build();
@Override
public SseEmitter chat(ChatRequest chatRequest, SseEmitter emitter) {
ChatModelVo chatModelVo = chatModelService.selectModelByName(chatRequest.getModel());
// 检查是否启用深度思考且是deepseek模型
if (Boolean.TRUE.equals(chatRequest.getEnableThinking())) {
return handleDeepSeekWithThinking(chatRequest, emitter, chatModelVo);
}
StreamingChatModel chatModel = OpenAiStreamingChatModel.builder()
.baseUrl(chatModelVo.getApiHost())
.apiKey(chatModelVo.getApiKey())
@@ -39,7 +72,31 @@ public class DeepSeekChatImpl implements IChatService {
.build();
// 发送流式消息
try {
chatModel.chat(chatRequest.getPrompt(), new StreamingChatResponseHandler() {
// 构建消息列表,包含历史对话消息和当前用户消息
List<ChatMessage> messages = new ArrayList<>();
// 添加历史对话消息
if (chatRequest.getMessages() != null) {
for (Message message : chatRequest.getMessages()) {
// 检查消息内容是否有效
if (message.getContent() == null || String.valueOf(message.getContent()).trim().isEmpty()) {
continue; // 跳过空消息
}
if (Message.Role.SYSTEM.getName().equals(message.getRole())) {
messages.add(new SystemMessage(String.valueOf(message.getContent())));
} else if (Message.Role.USER.getName().equals(message.getRole())) {
messages.add(new UserMessage(String.valueOf(message.getContent())));
} else if (Message.Role.ASSISTANT.getName().equals(message.getRole())) {
messages.add(new dev.langchain4j.data.message.AiMessage(String.valueOf(message.getContent())));
}
}
}
// 添加当前用户消息
messages.add(new UserMessage(chatRequest.getPrompt()));
chatModel.chat(messages, new StreamingChatResponseHandler() {
@SneakyThrows
@Override
public void onPartialResponse(String partialResponse) {
@@ -70,8 +127,208 @@ public class DeepSeekChatImpl implements IChatService {
return emitter;
}
/**
* 处理启用深度思考的deepseek模型请求
*/
private SseEmitter handleDeepSeekWithThinking(ChatRequest chatRequest, SseEmitter emitter, ChatModelVo chatModelVo) {
try {
// 构建请求到外部API
String url = chatModelVo.getApiHost() + "/v1/chat/completions";
String apiKey = chatModelVo.getApiKey();
// 构建请求体
Map<String, Object> requestBody = new HashMap<>();
requestBody.put("model", chatModelVo.getModelName());
requestBody.put("response_format", Map.of("type", "text"));
requestBody.put("max_tokens", 4000); // 修复将max_tokens从81920改为4000符合API要求
requestBody.put("temperature", 1);
requestBody.put("top_p", 1);
requestBody.put("top_k", 50);
requestBody.put("enable_thinking", chatRequest.getEnableThinking());
requestBody.put("stream", chatRequest.getStream());
// 构建消息 - DeepSeek模型不需要系统提示词
List<Map<String, Object>> messages = new ArrayList<>();
// 添加历史对话消息 (只添加用户和助手消息)
if (chatRequest.getMessages() != null) {
for (Message message : chatRequest.getMessages()) {
// 检查消息内容是否有效
if (message.getContent() == null || String.valueOf(message.getContent()).trim().isEmpty()) {
continue; // 跳过空消息
}
// DeepSeek模型在深度思考模式下只接受user和assistant角色的消息
if (Message.Role.SYSTEM.getName().equals(message.getRole())) {
// 跳过系统消息
continue;
}
Map<String, Object> historyMessage = new HashMap<>();
historyMessage.put("role", message.getRole());
historyMessage.put("content", String.valueOf(message.getContent()));
messages.add(historyMessage);
}
}
// 添加当前用户消息
Map<String, Object> userMessage = new HashMap<>();
userMessage.put("role", "user");
userMessage.put("content", String.valueOf(chatRequest.getPrompt()));
messages.add(userMessage);
requestBody.put("messages", messages);
// 创建ObjectMapper实例
com.fasterxml.jackson.databind.ObjectMapper objectMapper = new com.fasterxml.jackson.databind.ObjectMapper();
String requestBodyStr = objectMapper.writeValueAsString(requestBody);
// 打印请求体用于调试
log.info("打印请求体: {}", requestBodyStr);
// 创建请求
Request request = new Request.Builder()
.url(url)
.header("Authorization", "Bearer " + apiKey)
.header("Content-Type", "application/json")
.post(RequestBody.create(requestBodyStr, JSON))
.build();
// 执行异步请求
this.client.newCall(request).enqueue(new Callback() {
@Override
public void onFailure(Call call, IOException e) {
try {
log.error("深度思考请求失败: {}", e.getMessage(), e);
emitter.send("深度思考请求失败: " + e.getMessage());
emitter.complete();
} catch (IOException ioException) {
log.error("发送错误消息失败: {}", ioException.getMessage(), ioException);
}
}
@Override
public void onResponse(Call call, Response response) throws IOException {
if (!response.isSuccessful()) {
// 打印完整的错误响应体
String errorBody = "";
if (response.body() != null) {
errorBody = response.body().string();
}
log.error("深度思考请求失败,状态码: {},响应体: {}", response.code(), errorBody);
try {
emitter.send("深度思考请求失败,状态码: " + response.code() + ",响应体: " + errorBody);
emitter.complete();
return;
} catch (IOException e) {
log.error("发送错误消息失败: {}", e.getMessage(), e);
return;
}
}
try (ResponseBody responseBody = response.body()) {
if (responseBody == null) {
log.error("响应体为空");
emitter.send("响应体为空");
emitter.complete();
return;
}
// 流式读取响应
processThinkingResponse(responseBody, emitter);
} catch (Exception e) {
log.error("处理响应时出错: {}", e.getMessage(), e);
try {
emitter.send("处理响应时出错: " + e.getMessage());
emitter.complete();
} catch (IOException ioException) {
log.error("发送错误消息失败: {}", ioException.getMessage(), ioException);
}
}
}
});
} catch (Exception e) {
log.error("处理深度思考请求时出错: {}", e.getMessage(), e);
ChatServiceHelper.onStreamError(emitter, e.getMessage());
}
return emitter;
}
/**
* 处理深度思考的流式响应(边解析边推送)
*/
private void processThinkingResponse(ResponseBody responseBody, SseEmitter emitter) throws IOException {
// 标记是否进入正式回答阶段
boolean thinkingComplete = false;
try (BufferedReader reader = new BufferedReader(responseBody.charStream())) {
String line;
while ((line = reader.readLine()) != null) {
if (!line.startsWith("data: ")) {
continue;
}
String jsonData = line.substring(6).trim();
if ("[DONE]".equals(jsonData)) {
break;
}
try {
ObjectMapper mapper = new ObjectMapper();
Map<String, Object> chunk = mapper.readValue(jsonData, Map.class);
if (chunk.containsKey("choices") && chunk.get("choices") instanceof List) {
List<Map<String, Object>> choices = (List<Map<String, Object>>) chunk.get("choices");
if (!choices.isEmpty()) {
Map<String, Object> choice = choices.get(0);
if (choice.containsKey("delta") && choice.get("delta") instanceof Map) {
Map<String, Object> delta = (Map<String, Object>) choice.get("delta");
// 推送思考过程
if (delta.containsKey("reasoning_content") && delta.get("reasoning_content") != null) {
String reasoningChunk = delta.get("reasoning_content").toString();
emitter.send(SseEmitter.event().data(reasoningChunk).name("thinking"));
log.debug("Reasoning Chunk: {}", reasoningChunk);
}
// 推送正式回答
if (delta.containsKey("content") && delta.get("content") != null) {
String content = delta.get("content").toString();
// 第一次进入回答阶段时,加个提示头
if (!thinkingComplete) {
emitter.send(SseEmitter.event().data("\n\n回答内容\n").name("answer-header"));
thinkingComplete = true;
}
emitter.send(SseEmitter.event().data(content).name("answer"));
log.debug("Answer Chunk:{}", content);
}
}
}
}
} catch (Exception e) {
log.warn("解析JSON数据失败忽略本行: {}", jsonData, e);
}
}
emitter.complete();
log.info("深度思考流式响应完成");
} catch (IOException e) {
log.error("读取响应流时出错: {}", e.getMessage(), e);
try {
emitter.send(SseEmitter.event().data("读取响应流时出错: " + e.getMessage()).name("error"));
emitter.complete();
} catch (IOException ioException) {
log.error("发送错误消息失败: {}", ioException.getMessage(), ioException);
}
}
}
@Override
public String getCategory() {
return ChatModeType.DEEPSEEK.getCode();
}
}
}

View File

@@ -91,45 +91,66 @@ public class KnowledgeInfoServiceImpl implements IKnowledgeInfoService {
public TableDataInfo<KnowledgeInfoVo> queryPageListByRole(KnowledgeInfoBo bo, PageQuery pageQuery) {
// 查询用户关联角色
LoginUser loginUser = LoginHelper.getLoginUser();
if (StringUtils.isEmpty(loginUser.getKroleGroupIds()) || StringUtils.isEmpty(loginUser.getKroleGroupType())) {
return new TableDataInfo<>();
}
// 角色/角色组id列表
List<String> groupIdList = Arrays.stream(loginUser.getKroleGroupIds().split(","))
.filter(StringUtils::isNotEmpty)
.toList();
List<KnowledgeRole> knowledgeRoles;
LambdaQueryWrapper<KnowledgeRole> roleLqw = Wrappers.lambdaQuery();
if ("role".equals(loginUser.getKroleGroupType())) {
roleLqw.in(KnowledgeRole::getId, groupIdList);
} else {
roleLqw.in(KnowledgeRole::getGroupId, groupIdList);
}
knowledgeRoles = knowledgeRoleMapper.selectList(roleLqw);
if (CollectionUtils.isEmpty(knowledgeRoles)) {
return new TableDataInfo<>();
}
// 查询知识库id列表
LambdaQueryWrapper<KnowledgeRoleRelation> relationLqw = Wrappers.lambdaQuery();
relationLqw.in(KnowledgeRoleRelation::getKnowledgeRoleId, knowledgeRoles.stream().map(KnowledgeRole::getId).filter(Objects::nonNull).collect(Collectors.toList()));
List<KnowledgeRoleRelation> knowledgeRoleRelations = knowledgeRoleRelationMapper.selectList(relationLqw);
if (CollectionUtils.isEmpty(knowledgeRoleRelations)) {
return new TableDataInfo<>();
}
// 构建查询条件
LambdaQueryWrapper<KnowledgeInfo> lqw = buildQueryWrapper(bo);
// 在查询用户创建的知识库条件下,拼接角色分配知识库
lqw.or(q -> q.in(
KnowledgeInfo::getId,
knowledgeRoleRelations.stream()
.map(KnowledgeRoleRelation::getKnowledgeId)
.filter(Objects::nonNull)
.collect(Collectors.toList())
));
// 管理员用户直接查询所有数据
if (Objects.equals(loginUser.getUserId(), 1L)) {
Page<KnowledgeInfoVo> result = baseMapper.selectVoPage(pageQuery.build(), lqw);
return TableDataInfo.build(result);
}
// 检查用户是否配置了角色信息
if (StringUtils.isNotEmpty(loginUser.getKroleGroupIds()) && StringUtils.isNotEmpty(loginUser.getKroleGroupType())) {
// 角色/角色组id列表
List<String> groupIdList = Arrays.stream(loginUser.getKroleGroupIds().split(","))
.filter(StringUtils::isNotEmpty)
.toList();
// 查询用户关联的角色
List<KnowledgeRole> knowledgeRoles = new ArrayList<>();
LambdaQueryWrapper<KnowledgeRole> roleLqw = Wrappers.lambdaQuery();
if ("role".equals(loginUser.getKroleGroupType())) {
roleLqw.in(KnowledgeRole::getId, groupIdList);
} else {
roleLqw.in(KnowledgeRole::getGroupId, groupIdList);
}
knowledgeRoles = knowledgeRoleMapper.selectList(roleLqw);
// 如果用户有关联角色
if (!CollectionUtils.isEmpty(knowledgeRoles)) {
// 查询这些角色关联的知识库
LambdaQueryWrapper<KnowledgeRoleRelation> relationLqw = Wrappers.lambdaQuery();
relationLqw.in(KnowledgeRoleRelation::getKnowledgeRoleId,
knowledgeRoles.stream().map(KnowledgeRole::getId).filter(Objects::nonNull).collect(Collectors.toList()));
List<KnowledgeRoleRelation> knowledgeRoleRelations = knowledgeRoleRelationMapper.selectList(relationLqw);
// 如果角色关联了知识库
if (!CollectionUtils.isEmpty(knowledgeRoleRelations)) {
// 查询用户自己的知识库和角色分配的知识库
lqw.and(q -> q.eq(KnowledgeInfo::getUid, loginUser.getUserId())
.or()
.in(KnowledgeInfo::getId,
knowledgeRoleRelations.stream()
.map(KnowledgeRoleRelation::getKnowledgeId)
.filter(Objects::nonNull)
.collect(Collectors.toList())
)
);
} else {
// 用户没有关联任何知识库,只显示自己的
lqw.eq(KnowledgeInfo::getUid, loginUser.getUserId());
}
} else {
// 用户没有关联角色,只显示自己的
lqw.eq(KnowledgeInfo::getUid, loginUser.getUserId());
}
} else {
// 用户没有配置角色信息,只显示自己的
lqw.eq(KnowledgeInfo::getUid, loginUser.getUserId());
}
Page<KnowledgeInfoVo> result = baseMapper.selectVoPage(pageQuery.build(), lqw);
return TableDataInfo.build(result);
}