Merge remote-tracking branch 'origin/develop' into develop

src/main/java/cn/teammodel/ai/SparkGptClient.java

@@ -6,10 +6,9 @@ import cn.teammodel.ai.domain.SparkChatRequestParam;
 import cn.teammodel.ai.listener.SparkGptStreamListener;
 import lombok.Data;
 import lombok.extern.slf4j.Slf4j;
-import okhttp3.HttpUrl;
+import okhttp3.*;
-import okhttp3.OkHttpClient;
-import okhttp3.Request;
 import org.springframework.beans.factory.InitializingBean;
+import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.stereotype.Component;
 
 import javax.annotation.Resource;
@@ -69,7 +68,6 @@ public class SparkGptClient implements InitializingBean {
             e.printStackTrace();
         }
     }
-
     /**
      * 生成鉴权URL
      */
@@ -111,6 +109,7 @@ public class SparkGptClient implements InitializingBean {
         return httpUrl.toString();
     }
 
+
     @Override
     public void afterPropertiesSet() throws Exception {
         init();

src/main/java/cn/teammodel/ai/deepseek/DeepSeekClient.java

@@ -1,16 +1,29 @@
 package cn.teammodel.ai.deepseek;
 
+import cn.teammodel.ai.SparkGptClient;
+import cn.teammodel.ai.SseHelper;
+import cn.teammodel.ai.cache.HistoryCache;
+import cn.teammodel.ai.domain.SparkChatRequestParam;
 import cn.teammodel.common.ErrorCode;
+import cn.teammodel.common.PK;
 import cn.teammodel.config.exception.ServiceException;
-import cn.teammodel.model.dto.ai.deepseek.ChatRequestOKHttpDto;
+import cn.teammodel.model.dto.ai.ChatCompletionReqDto;
-import cn.teammodel.model.dto.ai.deepseek.ChatResponseDto;
+import cn.teammodel.model.dto.ai.deepseek.DeepSeekChatRequestDto;
+import cn.teammodel.model.dto.ai.deepseek.DeepSeekChatResponse;
 import cn.teammodel.model.dto.ai.deepseek.ChatReqDto;
+import cn.teammodel.model.entity.ai.ChatSession;
+import cn.teammodel.repository.ChatSessionRepository;
 import cn.teammodel.utils.JsonUtil;
+import com.azure.cosmos.models.CosmosPatchOperations;
+import com.fasterxml.jackson.databind.JsonNode;
 import com.fasterxml.jackson.databind.ObjectMapper;
 import com.fasterxml.jackson.databind.type.TypeFactory;
 import com.google.gson.Gson;
+import com.sun.org.apache.bcel.internal.generic.NEW;
 import lombok.extern.slf4j.Slf4j;
 import okhttp3.*;
+import okio.Buffer;
+import okio.BufferedSource;
 import org.apache.http.HttpEntity;
 import org.apache.http.client.methods.CloseableHttpResponse;
 import org.apache.http.client.methods.HttpPost;
@@ -19,20 +32,35 @@ import org.apache.http.entity.StringEntity;
 import org.apache.http.impl.client.CloseableHttpClient;
 import org.apache.http.impl.client.HttpClients;
 import org.apache.http.util.EntityUtils;
+import org.springframework.util.ObjectUtils;
+import org.springframework.util.StringUtils;
+import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;
 
+import javax.annotation.Resource;
+import java.io.BufferedReader;
+import java.io.InputStreamReader;
+import java.nio.charset.StandardCharsets;
+import java.time.Instant;
 import java.util.HashMap;
 import java.util.Map;
 
 import java.io.IOException;
 import java.io.InputStream;
 import java.util.*;
-import java.util.concurrent.TimeUnit;
+import java.util.concurrent.ExecutorService;
+import java.util.concurrent.Executors;
 
 @Slf4j
-public  class DeepSeekClient {
+public class DeepSeekClient {
-    private static final String API_Key;
+    public static final String API_Key;
-    private static final String API_Url;
+    public static final String API_Url;
     public static String API_Model;
+
+    @Resource
+    private static ChatSessionRepository chatSessionRepository;
+
+    private static final ExecutorService executorService = Executors.newCachedThreadPool();
+    private static final ObjectMapper objectMapper = new ObjectMapper();
     /**
      * 读取配置文件 读取key 和url
      */
@@ -61,7 +89,7 @@ public  class DeepSeekClient {
         msg.add(mssage);
 
         //构建请求头
-        ChatRequestOKHttpDto requestBody = new ChatRequestOKHttpDto();
+        DeepSeekChatRequestDto requestBody = new DeepSeekChatRequestDto();
         requestBody.setModel(API_Model);
         requestBody.setMessages(msg);
         requestBody.setTemperature(0);
@@ -69,7 +97,7 @@ public  class DeepSeekClient {
 
         long startTime = System.currentTimeMillis();
         //发起请求
-        ChatResponseDto response = SendRequests(requestBody);
+        DeepSeekChatResponse response = SendRequests(requestBody);
         //Map<String, Object> response = SendRequest(requestBody);
         Long endTime = System.currentTimeMillis();
         //思考耗时 秒
@@ -85,9 +113,9 @@ public  class DeepSeekClient {
      * @param requestBody
      * @return
      */
-    public static ChatResponseDto SendRequests(ChatRequestOKHttpDto requestBody)
+    public static DeepSeekChatResponse SendRequests(DeepSeekChatRequestDto requestBody)
     {
-        ChatResponseDto chatResponse = new ChatResponseDto();
+        DeepSeekChatResponse chatResponse = new DeepSeekChatResponse();
         //OkHttpClient client = new OkHttpClient().newBuilder().connectTimeout(60, TimeUnit.SECONDS).build();//设置连接超时时间 1分钟
         OkHttpClient client = new OkHttpClient().newBuilder().build();//设置连接超时时间 1分钟
 
@@ -104,13 +132,36 @@ public  class DeepSeekClient {
                 .addHeader("Accept", "application/json")
                 .addHeader("Authorization", "Bearer "+API_Key)
                 .build();
-
+        ObjectMapper objectMapper = new ObjectMapper();
         try(Response response = client.newCall(request).execute()) {
             if (response.isSuccessful() && response.body() != null) {
-                String responseBody = response.body().string();
+                StringBuilder responseBody = new StringBuilder();
+                try (BufferedSource source = response.body().source()) {
+                    Buffer buffer = new Buffer();
+                    while (source.read(buffer, 2048) != -1) {
+                        // 处理流式数据
+                        String chunk = buffer.readUtf8();
+                        if (chunk.startsWith("data:") && !chunk.contains("data: [DONE]")) {
+                            String[] split = chunk.split("data:");
+                            for (String result : split) {
+                                if (StringUtils.hasLength(result) && StringUtils.hasLength(result.trim())) {
+                                    JsonNode jsonNode = objectMapper.readTree(result);
+                                    if (!ObjectUtils.isEmpty(jsonNode.get("choices"))) {
+                                        JsonNode delta = jsonNode.get("choices").get(0).get("delta");
+                                        log.debug("Delta Content: {}", delta.get("content").asText());
+                                        responseBody.append(delta.get("content").asText());
+                                    }
+                                }
+                            }
+                        }
+                    }
+                }
+
+
+                String responseBody1 = response.body().string();
                 // 使用 Gson 将 JSON 字符串转换为 MyEntity 对象
                 Gson gson = new Gson();
-                chatResponse = gson.fromJson(responseBody, ChatResponseDto.class);
+                chatResponse = gson.fromJson(responseBody1, DeepSeekChatResponse.class);
                 // 确保关闭响应体以释放资源
                 response.body().close();
                 chatResponse.setCode(200);
@@ -132,12 +183,145 @@ public  class DeepSeekClient {
         return chatResponse;
     }
 
+
+    /**
+     * OkHttpClient 方式请求 流式返回
+     * @param requestBody
+     * @return
+     */
+    public static SseEmitter SendRequestsEmitter(DeepSeekChatRequestDto requestBody)
+    {
+        SseEmitter sseEmitter = new SseEmitter(-1L);
+        //OkHttpClient client = new OkHttpClient().newBuilder().connectTimeout(60, TimeUnit.SECONDS).build();//设置连接超时时间 1分钟
+        OkHttpClient client = new OkHttpClient().newBuilder().build();//
+
+        MediaType mediaType = MediaType.parse("application/json");
+        //String  content = "{\n  \"messages\": [\n    {\n      \"content\": \"You are a helpful assistant\",\n      \"role\": \"system\"\n    },\n    {\n      \"content\": \"Hi\",\n      \"role\": \"user\"\n    }\n  ],\n  \"model\": \"deepseek-chat\",\n  \"frequency_penalty\": 0,\n  \"max_tokens\": 2048,\n  \"presence_penalty\": 0,\n  \"response_format\": {\n    \"type\": \"text\"\n  },\n  \"stop\": null,\n  \"stream\": false,\n  \"stream_options\": null,\n  \"temperature\": 1,\n  \"top_p\": 1,\n  \"tools\": null,\n  \"tool_choice\": \"none\",\n  \"logprobs\": false,\n  \"top_logprobs\": null\n}";
+        String content = JsonUtil.convertToJson(requestBody);
+
+        RequestBody body = RequestBody.create(mediaType, content);
+        Request request = new Request.Builder()
+                .url(API_Url)
+                .method("POST", body)
+                .addHeader("Content-Type", "application/json")
+                .addHeader("Accept", "application/json")
+                .addHeader("Authorization", "Bearer "+API_Key)
+                .build();
+        ObjectMapper objectMapper = new ObjectMapper();
+        try(Response response = client.newCall(request).execute()) {
+            if (response.isSuccessful() && response.body() != null) {
+                StringBuilder responseBody = new StringBuilder();
+                try (BufferedSource source = response.body().source()) {
+                    Buffer buffer = new Buffer();
+                    while (source.read(buffer, 2048) != -1) {
+                        // 处理流式数据
+                        String chunk = buffer.readUtf8();
+                        if (chunk.startsWith("data:") && !chunk.contains("data: [DONE]")) {
+                            String[] split = chunk.split("data:");
+                            for (String result : split) {
+                                if (StringUtils.hasLength(result) && StringUtils.hasLength(result.trim())) {
+                                    JsonNode jsonNode = objectMapper.readTree(result);
+                                    if (!ObjectUtils.isEmpty(jsonNode.get("choices"))) {
+                                        JsonNode delta = jsonNode.get("choices").get(0).get("delta");
+                                        log.debug("Delta Content: {}", delta.get("content").asText());
+                                        sseEmitter.send(delta);
+                                    }
+                                }
+                            }
+                        }
+                    }
+                }catch (IOException e) {
+                    sseEmitter.completeWithError(e);
+                }
+
+            } else {
+                sseEmitter.completeWithError(new Exception("请求DeepSeek服务器失败"));
+            }
+        } catch (IOException e) {
+            sseEmitter.completeWithError(e);
+        }
+        return sseEmitter;
+    }
+
+    /**
+     * HttpClient 方式请求
+     * @param chatCompletionReqDto
+     * @return
+     */
+    public static SseEmitter HttpClientSendRequests(ChatCompletionReqDto chatCompletionReqDto){
+        SseEmitter emitter = new SseEmitter(-1L);
+        List<ChatReqDto> msg = new ArrayList<>();
+        msg.add(new ChatReqDto(chatCompletionReqDto.getSessionId(), "user", chatCompletionReqDto.getText()));
+        //构建请求头
+        DeepSeekChatRequestDto requestBody = new DeepSeekChatRequestDto();
+        requestBody.setModel(DeepSeekClient.API_Model);
+        requestBody.setMessages(msg);
+        requestBody.setTemperature(0);
+        requestBody.setStream(true);
+
+        try (CloseableHttpClient httpClient = HttpClients.createDefault()) {
+            // 创建HttpPost对象
+            HttpPost httpPost = new HttpPost(API_Url);
+            //添加请求头
+            httpPost.setHeader("Content-Type", "application/json");
+            httpPost.setHeader("Accept", "application/json");
+            httpPost.setHeader("Authorization", "Bearer " + API_Key);
+
+            requestBody.setStream(true);
+            // 设置请求体
+            String jsonContent = JsonUtil.convertToJson(requestBody);
+            httpPost.setEntity(new StringEntity(jsonContent, ContentType.create("application/json", "UTF-8")));
+            StringBuilder responseBody = new StringBuilder();
+            try (CloseableHttpResponse response = httpClient.execute(httpPost);
+                 BufferedReader reader = new BufferedReader(new InputStreamReader(response.getEntity().getContent(), StandardCharsets.UTF_8))) {
+                String line;
+                StringBuilder strContent = new StringBuilder();
+                while ((line = reader.readLine()) != null) {
+                    if (line.startsWith("data: ")) {
+                        String jsonData = line.substring(6);
+                        if ("[DONE]".equals(jsonData)) {
+                            //SseHelper.send(emitter, "[DONE]");
+                            emitter.send("[DONE]");
+                            // 更新历史会话记录
+                            ChatSession.Message message = ChatSession.Message.of(chatCompletionReqDto.getText(), strContent.toString(),chatCompletionReqDto.getModel());
+                            HistoryCache.updateContext(chatCompletionReqDto.getSessionId(), message);
+                            CosmosPatchOperations options = CosmosPatchOperations.create()
+                                    .replace("/updateTime", Instant.now().toEpochMilli())
+                                    .add("/history/-", message);
+                            chatSessionRepository.save(chatCompletionReqDto.getSessionId(), PK.of(PK.CHAT_SESSION), ChatSession.class, options);
+                            break;
+                        }
+                        JsonNode node = objectMapper.readTree(jsonData);
+                        String content = node.path("choices")
+                                .path(0)
+                                .path("delta")
+                                .path("content")
+                                .asText("");
+                        if (!content.isEmpty()) {
+                            responseBody.append(content);
+                            strContent.append(content);
+                            emitter.send(content);
+                        }
+                    }
+                }
+                emitter.complete();
+            }catch (Exception e)
+            {
+                emitter.completeWithError(e);
+            }
+        }catch (Exception e) {
+            emitter.completeWithError(e);
+        }
+
+        return emitter;
+    }
+
     /***
      * HttpClient 方式请求
      * @param requestBody
      * @return
      */
-    public static Map<String, Object> SendRequest(ChatRequestOKHttpDto requestBody) {
+    public static Map<String, Object> SendRequest(DeepSeekChatRequestDto requestBody) {
         Map<String, Object> mapper = new HashMap<>();
         try (CloseableHttpClient httpClient = HttpClients.createDefault()) {
             // 创建HttpPost对象
@@ -175,8 +359,4 @@ public  class DeepSeekClient {
         //TODO 请求接口
         return mapper;
     }
-
-
-
-
 }

src/main/java/cn/teammodel/ai/domain/SparkChatRequestParam.java

@@ -46,16 +46,17 @@ public class SparkChatRequestParam {
     public static class Message {
         private String role;
         private String content;
+        private String model;
        
         /**
         * 一个类下面有两种类型的对象,使用静态的对象产生方法,好思路
         */
-        public static Message ofUser(String content){
+        public static Message ofUser(String content,String model){
-            return new Message("user",content);
+            return new Message("user",content,model);
         }
 
-        public static Message ofAssistant(String content){
+        public static Message ofAssistant(String content, String model){
-            return new Message("assistant",content);
+            return new Message("assistant",content,model);
         }
     }
 

src/main/java/cn/teammodel/controller/frontend/AiDeepSeekController.java

@@ -1,7 +1,8 @@
 package cn.teammodel.controller.frontend;
 
 import cn.teammodel.common.IdRequest;
-import cn.teammodel.model.dto.ai.deepseek.ChatResponseDto;
+import cn.teammodel.model.dto.ai.ChatCompletionReqDto;
+import cn.teammodel.model.dto.ai.deepseek.DeepSeekChatResponse;
 import cn.teammodel.model.dto.ai.deepseek.ChatReqDto;
 import cn.teammodel.model.entity.TmdUserDetail;
 import cn.teammodel.model.entity.ai.DeepSeekSession;
@@ -18,12 +19,15 @@ import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;
 import javax.annotation.Resource;
 import javax.validation.Valid;
 import java.util.*;
+import java.util.concurrent.ExecutorService;
+import java.util.concurrent.Executors;
 
 @RestController
 @RequestMapping("/aiDeepSeek")
 @Api(tags = "AI DeepSeek 能力")
 public class AiDeepSeekController {
 
+    private final ExecutorService executorService = Executors.newCachedThreadPool();
     /**
      * 访问DeepSeek方法
      */
@@ -118,19 +122,29 @@ public class AiDeepSeekController {
      * @return
      */
     @PostMapping("chat")
-    @ApiOperation("与deepseek的对话")
+    @ApiOperation("单独 与deepseek的对话")
-    public R<ChatResponseDto> ChatCompletion(@RequestBody @Valid ChatReqDto messageDto) {
+    public R<DeepSeekChatResponse> ChatCompletion(@RequestBody @Valid ChatReqDto messageDto) {
-        ChatResponseDto chatResponse = deepSeekChatService.ChatAsk(messageDto);
+        DeepSeekChatResponse chatResponse = deepSeekChatService.ChatAsk(messageDto);
         return  R.success(chatResponse);
     }
 
+    @PostMapping("okhttp/emitter")
+    @ApiOperation("单 与deepseek的对话")
+    public SseEmitter ChatEmiter(@RequestBody @Valid ChatReqDto messageDto) {
+        return deepSeekChatService.OKHttpChatSeeEmitterAsk(messageDto);
+    }
+
+    /**
+     * 与deepseek的对话 并保存到数据库中
+     * @param chatCompletionReqDto
+     * @return
+     */
     @PostMapping("chat/completion")
     @ApiOperation("与 spark 的流式对话")
-    public SseEmitter chatCompletion(@RequestBody @Valid ChatReqDto messageDto) {
+    public SseEmitter chatCompletion(@RequestBody @Valid ChatCompletionReqDto chatCompletionReqDto) {
         String userId = SecurityUtil.getLoginUser().getId();
-        SseEmitter sseEmitter = new SseEmitter();
+        SseEmitter sseEmitter = new SseEmitter(-1L);
-        return sseEmitter;
+        return deepSeekChatService.ChatSeeEmitterAsk(chatCompletionReqDto);
-        //return deepSeekChatService.ChatSeeEmitterAsk(messageDto, userId);
     }
 
 

src/main/java/cn/teammodel/model/dto/ai/ChatCompletionReqDto.java

@@ -13,6 +13,10 @@ public class ChatCompletionReqDto {
     */
     @ApiModelProperty("会话id，没有则为空")
     private String appId;
+
+    @ApiModelProperty("模型类型:  科大讯飞：SparkMax；DeepSeek：DeepSeek_Chat")
+    private String model = "SparkMax";
+
     @NotBlank(message = "请输入消息内容")
     private String text;
 }

src/main/java/cn/teammodel/model/dto/ai/deepseek/ChatResponseDto.java

@@ -1,66 +0,0 @@
-package cn.teammodel.model.dto.ai.deepseek;
-
-import io.swagger.annotations.ApiModelProperty;
-import lombok.AllArgsConstructor;
-import lombok.Builder;
-import lombok.Builder.Default;
-import lombok.Data;
-
-import java.util.List;
-
-/**
- *  接收DeepSeek响应的json 格式来设计响应体 用来响应体字符串
- */
-@Data
-public class ChatResponseDto {
-    private int code;
-    private String msg;
-    private long  wasteTime;
-    private String id;
-    private String object;
-    private long created;
-    private String model;
-
-    private Usage usage;
-
-    /**
-     * 返回内容
-     */
-    private List<Choice> choices;
-    private String system_fingerprint;
-    @Data
-    @AllArgsConstructor
-    public static class Choice {
-        private int index;
-        private DeepSeekMessage message;
-        private String logprobs;
-        private  String finish_reason;
-    }
-    @Data
-    public static class Usage{
-        private int prompt_tokens;
-        private int completion_tokens;
-        private int total_tokens;
-        private Prompt_Tokens_Details prompt_tokens_details;
-        private int prompt_cache_hit_tokens;
-        private int prompt_cache_miss_tokens;
-    }
-    @Data
-    public static class Prompt_Tokens_Details {
-        private int cached_tokens;
-    }
-
-    @Data
-    public static class DeepSeekMessage{
-
-        /**
-         * 角色
-         */
-        private String role;
-
-        /**
-         * 提问内容
-         */
-        private String  content;
-    }
-}

src/main/java/cn/teammodel/model/dto/ai/deepseek/DeepSeekChatRequestDto.java

@@ -37,7 +37,7 @@ import java.util.List;
  * }
  */
 @Data
-public class ChatRequestOKHttpDto {
+public class DeepSeekChatRequestDto {
     @ApiModelProperty("会话模型")
     private String model;
     @ApiModelProperty("会话内容")
@@ -53,4 +53,11 @@ public class ChatRequestOKHttpDto {
      */
     @ApiModelProperty("最大生成token数")
     private int max_tokens = 2048;
+
+    @ApiModelProperty("是否流式输出")
+    private boolean stream = false;
+
+    public boolean getStream() {
+        return stream;
+    }
 }

src/main/java/cn/teammodel/model/dto/ai/deepseek/DeepSeekChatResponse.java

@@ -0,0 +1,114 @@
+package cn.teammodel.model.dto.ai.deepseek;
+
+import lombok.AllArgsConstructor;
+import lombok.Data;
+
+import java.util.List;
+
+/**
+ *  接收DeepSeek响应的json 格式来设计响应体 用来响应体字符串
+ */
+@Data
+public class DeepSeekChatResponse {
+    /**
+     * 响应码
+      */
+    private int code;
+    /**
+     * 响应内容
+     */
+    private String msg;
+    /**
+     * 思考项目
+     */
+    private long  wasteTime;
+    /**
+     * 会话id
+     */
+    private String id;
+    /**
+     * 对象的类型, 其值为 chat.completion
+     */
+    private String object;
+
+    /**
+     * 创建聊天完成时的 Unix 时间戳（以秒为单位）。
+     */
+    private long created;
+    /**
+     * 生成该 completion 的模型名。
+     */
+    private String model;
+
+    /**
+     * 返回内容
+     */
+    private List<Choice> choices;
+
+    /**
+     * 该对话补全请求的用量信息。
+     */
+    private Usage usage;
+
+    private String system_fingerprint;
+
+    /**
+     * 模型生成的 completion 的选择列表。
+     */
+    @Data
+    @AllArgsConstructor
+    public static class Choice {
+        /**
+         * 该 completion 在模型生成的 completion 的选择列表中的索引。
+         */
+        private int index;
+        //内容
+        private DeepSeekMessage message;
+        //private String logprobs;
+        private  String finish_reason;
+    }
+
+    /**
+     * 该对话补全请求的用量信息。
+     */
+    @Data
+    public static class Usage{
+        //用户 prompt 所包含的 token 数。该值等于 prompt_cache_hit_tokens + prompt_cache_miss_tokens
+        private int prompt_tokens;
+        //模型 completion 产生的 token 数。
+        private int completion_tokens;
+        //该请求中，所有 token 的数量（prompt + completion）。
+        private int total_tokens;
+        private Prompt_Tokens_Details prompt_tokens_details;
+        //用户 prompt 中，命中上下文缓存的 token 数。
+        private int prompt_cache_hit_tokens;
+        //用户 prompt 中，未命中上下文缓存的 token 数。
+        private int prompt_cache_miss_tokens;
+    }
+
+    /**
+     * completion tokens 的详细信息。
+     */
+    @Data
+    public static class Prompt_Tokens_Details {
+        //推理模型所产生的思维链 token 数量
+        private int cached_tokens;
+    }
+
+    /**
+     * 聊天内容
+     */
+    @Data
+    public static class DeepSeekMessage{
+
+        /**
+         * 角色
+         */
+        private String role;
+
+        /**
+         * 该 completion 的内容。
+         */
+        private String  content;
+    }
+}

src/main/java/cn/teammodel/model/entity/ai/ChatSession.java

@@ -45,13 +45,16 @@ public class ChatSession extends BaseItem {
         private Integer cost;
         private Long createTime;
 
-        public static Message of(String userText, String gptText) {
+        public String model;
+
+        public static Message of(String userText, String gptText,String model) {
             Message message = new Message();
             message.setId(UUID.randomUUID().toString());
             message.setCost(0);
             message.setUserText(userText);
             message.setGptText(gptText);
             message.setCreateTime(Instant.now().toEpochMilli());
+            message.setModel(model);
             return message;
         }
     }

src/main/java/cn/teammodel/service/DeepSeekService.java

@@ -1,18 +1,34 @@
 package cn.teammodel.service;
 
-import cn.teammodel.model.dto.ai.deepseek.ChatResponseDto;
+import cn.teammodel.model.dto.ai.ChatCompletionReqDto;
+import cn.teammodel.model.dto.ai.deepseek.DeepSeekChatResponse;
 import cn.teammodel.model.dto.ai.deepseek.ChatReqDto;
-import reactor.core.publisher.Flux;
+import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;
 
 /**
  * 访问DeepSeek方法
  */
 public interface DeepSeekService {
 
+    /**
+     * 单独 获取AI的回答
+     * @param message
+     * @return
+     */
+    DeepSeekChatResponse ChatAsk(ChatReqDto message);
+
     /**
      * 获取AI的回答
      * @param message
      * @return
      */
-    ChatResponseDto ChatAsk(ChatReqDto message);
+    SseEmitter OKHttpChatSeeEmitterAsk(ChatReqDto message);
+
+    /**
+     * 获取AI的回答
+     * @param chatCompletionReqDto
+     * @return
+     */
+    SseEmitter ChatSeeEmitterAsk(ChatCompletionReqDto chatCompletionReqDto);
+
 }

src/main/java/cn/teammodel/service/DeepSeekSessionService.java

@@ -1,6 +1,5 @@
 package cn.teammodel.service;
 
-import cn.teammodel.model.dto.ai.deepseek.ChatResponseDto;
 import cn.teammodel.model.entity.ai.DeepSeekSession;
 import cn.teammodel.model.entity.ai.DeepSeekSession.DeepSeekMessage;
 

src/main/java/cn/teammodel/service/impl/ChatMessageServiceImpl.java

@@ -4,6 +4,7 @@ import cn.teammodel.ai.JsonLoader;
 import cn.teammodel.ai.SparkGptClient;
 import cn.teammodel.ai.SseHelper;
 import cn.teammodel.ai.cache.HistoryCache;
+import cn.teammodel.ai.deepseek.DeepSeekClient;
 import cn.teammodel.ai.domain.SparkChatRequestParam;
 import cn.teammodel.ai.listener.SparkGptStreamListener;
 import cn.teammodel.common.ErrorCode;
@@ -18,6 +19,7 @@ import cn.teammodel.model.entity.User;
 import cn.teammodel.model.entity.ai.ChatSession;
 import cn.teammodel.security.utils.SecurityUtil;
 import cn.teammodel.service.ChatMessageService;
+import cn.teammodel.service.DeepSeekService;
 import cn.teammodel.utils.RepositoryUtil;
 import com.alibaba.fastjson2.JSON;
 import com.alibaba.fastjson2.TypeReference;
@@ -49,12 +51,20 @@ public class ChatMessageServiceImpl implements ChatMessageService {
     @Resource
     private JsonLoader jsonLoader;
 
+    /**
+     * 访问DeepSeek方法
+     */
+    @Resource
+    private DeepSeekService deepSeekChatService;
+
+
     @Override
     public SseEmitter chatCompletion(ChatCompletionReqDto chatCompletionReqDto, String userId) {
         // 目前仅使用讯飞星火大模型
         String appId = chatCompletionReqDto.getAppId();
         SseEmitter sseEmitter;
-        if (StringUtils.isEmpty(appId)) {
+        //
+        if (StringUtils.isEmpty(appId) || chatCompletionReqDto.getModel().equals("DeepSeek_Chat")) {
             sseEmitter = completionBySession(chatCompletionReqDto, userId);
         } else {
             sseEmitter = completionByApp(chatCompletionReqDto, false);
@@ -165,37 +175,57 @@ public class ChatMessageServiceImpl implements ChatMessageService {
 
         String appPrompt = chatApp.getPrompt();
         SseEmitter sseEmitter = new SseEmitter(-1L);
-        SparkGptStreamListener listener = new SparkGptStreamListener(sseEmitter);
+
-        // open 回调
+        switch (chatCompletionReqDto.getModel()) {
-        listener.setOnOpen((s) -> {
+            //星火大模型
-            // 敏感词检查,计费 (设计模型, reducePoints, 或者都可以在完成的回调中做?)
+            case "SparkMax":
-            log.info("callback: ws open event emmit");
+            {
-        });
+                SparkGptStreamListener listener = new SparkGptStreamListener(sseEmitter);
-        // 对话完成的回调
+                // open 回调
-        listener.setOnComplete((s) -> {
+                listener.setOnOpen((s) -> {
-            log.info("callback: ws complete event emmit");
+                    // 敏感词检查,计费 (设计模型, reducePoints, 或者都可以在完成的回调中做?)
-            SseHelper.send(sseEmitter, "[DONE]");
+                    log.info("callback: ws open event emmit");
-            // 处理完成后的事件:
+                });
-            if (!justApi) {
+                // 对话完成的回调
-                // 保存消息记录, 缓存更改
+                SseEmitter finalSseEmitter = sseEmitter;
+                listener.setOnComplete((s) -> {
+                    log.info("callback: ws complete event emmit");
+                    SseHelper.send(finalSseEmitter, "[DONE]");
+                    // 处理完成后的事件:
+                    if (!justApi) {
+                        // 保存消息记录, 缓存更改
+                    }
+                });
+                // 错误的回调
+                listener.setOnError((s) -> {
+                    log.error("callback: ws error, info: " + s);
+                    // 返还积分
+                });
+                List<SparkChatRequestParam.Message> messageList = new ArrayList<>();
+                messageList.add(SparkChatRequestParam.Message.ofAssistant(appPrompt,"SparkMax"));
+                messageList.add(SparkChatRequestParam.Message.ofUser(userPrompt,"SparkMax"));
+                SparkChatRequestParam requestParam = SparkChatRequestParam
+                        .builder()
+                        .uid(userId)
+                        .chatId(appId)
+                        .messageList(messageList)
+                        .build();
+                sparkGptClient.streamChatCompletion(requestParam, listener);
+                return finalSseEmitter;
             }
-        });
+            // DeepSeek 模型
-        // 错误的回调
+            case "DeepSeek_Chat":
-        listener.setOnError((s) -> {
+            {
-            log.error("callback: ws error, info: " + s);
+                // OKHttp 方式请求
-            // 返还积分
+                sseEmitter = deepSeekChatService.ChatSeeEmitterAsk(chatCompletionReqDto);
-        });
+                //HttpClient 方式请求
-        List<SparkChatRequestParam.Message> messageList = new ArrayList<>();
+                //sseEmitter = DeepSeekClient.HttpClientSendRequests(chatCompletionReqDto);
-        messageList.add(SparkChatRequestParam.Message.ofAssistant(appPrompt));
+
-        messageList.add(SparkChatRequestParam.Message.ofUser(userPrompt));
+                return sseEmitter;
-        SparkChatRequestParam requestParam = SparkChatRequestParam
+            }
-                .builder()
+            default:
-                .uid(userId)
+                throw new ServiceException(ErrorCode.PARAMS_ERROR.getCode(), "不支持的模型");
-                .chatId(appId)
+        }
-                .messageList(messageList)
-                .build();
-        sparkGptClient.streamChatCompletion(requestParam, listener);
-        return sseEmitter;
     }
 
     /**
@@ -211,38 +241,53 @@ public class ChatMessageServiceImpl implements ChatMessageService {
         }
 
         SseEmitter sseEmitter = new SseEmitter(-1L);
-        SparkGptStreamListener listener = new SparkGptStreamListener(sseEmitter);
+        switch (chatCompletionReqDto.getModel()){
-        // open 回调
+            // 星火大模型
-        listener.setOnOpen((s) -> {
+            case "SparkMax":{
-            // 敏感词检查,计费 (设计模型, reducePoints, 或者都可以在完成的回调中做?)
+                SparkGptStreamListener listener = new SparkGptStreamListener(sseEmitter);
-            log.info("callback: ws open event emmit");
+                // open 回调
-        });
+                listener.setOnOpen((s) -> {
-        // 对话完成的回调
+                    // 敏感词检查,计费 (设计模型, reducePoints, 或者都可以在完成的回调中做?)
-        listener.setOnComplete((s) -> {
+                    log.info("callback: ws open event emmit");
-            log.info("callback: ws complete event emmit");
+                });
-            SseHelper.send(sseEmitter, "[DONE]");
+                // 对话完成的回调
-            // 处理完成后的事件: 保存消息记录, 缓存更改
+                SseEmitter finalSseEmitter = sseEmitter;
-            ChatSession.Message message = ChatSession.Message.of(userPrompt, s);
+                listener.setOnComplete((s) -> {
-            HistoryCache.updateContext(sessionId, message);
+                    log.info("callback: ws complete event emmit");
-            CosmosPatchOperations options = CosmosPatchOperations.create()
+                    SseHelper.send(finalSseEmitter, "[DONE]");
-                    .replace("/updateTime", Instant.now().toEpochMilli())
+                    // 处理完成后的事件: 保存消息记录, 缓存更改
-                    .add("/history/-", message);
+                    ChatSession.Message message = ChatSession.Message.of(userPrompt, s,chatCompletionReqDto.getModel());
-            chatSessionRepository.save(sessionId, PK.of(PK.CHAT_SESSION), ChatSession.class, options);
+                    HistoryCache.updateContext(sessionId, message);
-        });
+                    CosmosPatchOperations options = CosmosPatchOperations.create()
-        // 错误的回调
+                            .replace("/updateTime", Instant.now().toEpochMilli())
-        listener.setOnError((s) -> {
+                            .add("/history/-", message);
-            log.error("callback: ws error, info: " + s);
+                    chatSessionRepository.save(sessionId, PK.of(PK.CHAT_SESSION), ChatSession.class, options);
-            // 返还积分
+                });
-        });
+                // 错误的回调
-        List<SparkChatRequestParam.Message> messageList = fetchContext(sessionId, userPrompt);
+                listener.setOnError((s) -> {
-        SparkChatRequestParam requestParam = SparkChatRequestParam
+                    log.error("callback: ws error, info: " + s);
-                .builder()
+                    // 返还积分
-                .uid(userId)
+                });
-                .chatId(sessionId)
+                List<SparkChatRequestParam.Message> messageList = fetchContext(sessionId, userPrompt,chatCompletionReqDto.getModel());
-                .messageList(messageList)
+                SparkChatRequestParam requestParam = SparkChatRequestParam
-                .build();
+                        .builder()
-        sparkGptClient.streamChatCompletion(requestParam, listener);
+                        .uid(userId)
-        return sseEmitter;
+                        .chatId(sessionId)
+                        .messageList(messageList)
+                        .build();
+                sparkGptClient.streamChatCompletion(requestParam, listener);
+                return finalSseEmitter;
+            }
+            // DeepSeek 模型
+            case "DeepSeek_Chat":
+            {
+                sseEmitter = deepSeekChatService.ChatSeeEmitterAsk(chatCompletionReqDto );
+                return sseEmitter;
+            }
+            default:{
+                throw new ServiceException(ErrorCode.PARAMS_ERROR.getCode(), "不支持的模型");
+            }
+        }
     }
 
     /**
@@ -258,7 +303,7 @@ public class ChatMessageServiceImpl implements ChatMessageService {
         if (sessions.size() == 0) {
             // 初始化欢迎语
             ChatSession.Message message = ChatSession.Message.of("", "你好" + userName + " ,我是你的私人 AI 助手小豆," +
-                    "你可以问我任何包括但不仅限于教育的问题,我会尽力为您解答!");
+                    "你可以问我任何包括但不仅限于教育的问题,我会尽力为您解答!","SparkMax");
             List<ChatSession.Message> history = Collections.singletonList(message);
             session = new ChatSession();
             session.setId(sessionId);
@@ -285,7 +330,7 @@ public class ChatMessageServiceImpl implements ChatMessageService {
             log.info("callback: ws complete event emmit");
             SseHelper.send(sseEmitter, "[DONE]");
             // 处理完成后的事件: 保存消息记录, 缓存更改
-            ChatSession.Message message = ChatSession.Message.of(userPrompt, s);
+            ChatSession.Message message = ChatSession.Message.of(userPrompt, s,"SparkMax");
             HistoryCache.updateContext(sessionId, message);
             CosmosPatchOperations options = CosmosPatchOperations.create()
                     .replace("/updateTime", Instant.now().toEpochMilli())
@@ -297,7 +342,7 @@ public class ChatMessageServiceImpl implements ChatMessageService {
             log.error("callback: ws error, info: " + s);
             // 返还积分
         });
-        List<SparkChatRequestParam.Message> messageList = fetchContext(userId, userPrompt);
+        List<SparkChatRequestParam.Message> messageList = fetchContext(userId, userPrompt,"SparkMax");
         SparkChatRequestParam requestParam = SparkChatRequestParam
                 .builder()
                 .uid(userId)
@@ -324,7 +369,7 @@ public class ChatMessageServiceImpl implements ChatMessageService {
         if (sessions.size() == 0) {
             // 初始化欢迎语
             ChatSession.Message message = ChatSession.Message.of("", "你好" + userName + " ,我是你的私人 AI 助手小豆," +
-                    "你可以问我任何包括但不仅限于教育的问题,我会尽力为您解答!");
+                    "你可以问我任何包括但不仅限于教育的问题,我会尽力为您解答!","SparkMax");
             List<ChatSession.Message> history = Collections.singletonList(message);
             session = new ChatSession();
             session.setId(sessionId);
@@ -351,7 +396,7 @@ public class ChatMessageServiceImpl implements ChatMessageService {
             log.info("callback: ws complete event emmit");
             SseHelper.send(sseEmitter, "[DONE]");
             // 处理完成后的事件: 保存消息记录, 缓存更改
-            ChatSession.Message message = ChatSession.Message.of(userPrompt, s);
+            ChatSession.Message message = ChatSession.Message.of(userPrompt, s,"SparkMax");
             HistoryCache.updateContext(sessionId, message);
             CosmosPatchOperations options = CosmosPatchOperations.create()
                     .replace("/updateTime", Instant.now().toEpochMilli())
@@ -363,7 +408,7 @@ public class ChatMessageServiceImpl implements ChatMessageService {
             log.error("callback: ws error, info: " + s);
             // 返还积分
         });
-        List<SparkChatRequestParam.Message> messageList = fetchContext(userId, userPrompt);
+        List<SparkChatRequestParam.Message> messageList = fetchContext(userId, userPrompt,"SparkMax");
         SparkChatRequestParam requestParam = SparkChatRequestParam
                 .builder()
                 .uid(userId)
@@ -374,7 +419,7 @@ public class ChatMessageServiceImpl implements ChatMessageService {
         return sseEmitter;
     }
 
-    List<SparkChatRequestParam.Message> fetchContext(String userId, String prompt) {
+    List<SparkChatRequestParam.Message> fetchContext(String userId, String prompt, String model) {
         List<ChatSession.Message> context = HistoryCache.getContext(userId);
         List<SparkChatRequestParam.Message> paramMessages = new ArrayList<>();
         // 暂未缓存,从数据库拉取
@@ -388,10 +433,10 @@ public class ChatMessageServiceImpl implements ChatMessageService {
 
         // convert DB Message to Spark Message
         context.forEach(item -> {
-            paramMessages.add(SparkChatRequestParam.Message.ofUser(item.getUserText()));
+            paramMessages.add(SparkChatRequestParam.Message.ofUser(item.getUserText(),model));
-            paramMessages.add(SparkChatRequestParam.Message.ofAssistant(item.getGptText()));
+            paramMessages.add(SparkChatRequestParam.Message.ofAssistant(item.getGptText(),model));
         });
-        paramMessages.add(SparkChatRequestParam.Message.ofUser(prompt));
+        paramMessages.add(SparkChatRequestParam.Message.ofUser(prompt,model));
         return paramMessages;
     }
 

src/main/java/cn/teammodel/service/impl/ChatSessionServiceImpl.java

@@ -35,7 +35,7 @@ public class ChatSessionServiceImpl implements ChatSessionService {
     @Override
     public String createSession(String userId, String name) {
         // 初始化欢迎语
-        Message message = Message.of("", "你好" + name + " ,我是你的私人 AI 助手小豆,你可以问我任何包括但不仅限于教育的问题,我会尽力为您解答!");
+        Message message = Message.of("", "你好" + name + " ,我是你的私人 AI 助手小豆,你可以问我任何包括但不仅限于教育的问题,我会尽力为您解答!","SparkMax");
         List<Message> history = Collections.singletonList(message);
         ChatSession chatSession = new ChatSession();
         chatSession.setId(UUID.randomUUID().toString());

src/main/java/cn/teammodel/service/impl/DeepSeekServiceImpl.java

@@ -1,47 +1,72 @@
 package cn.teammodel.service.impl;
 
+import cn.teammodel.ai.cache.HistoryCache;
 import cn.teammodel.ai.deepseek.DeepSeekClient;
 import cn.teammodel.common.PK;
-import cn.teammodel.model.dto.ai.deepseek.ChatRequestOKHttpDto;
+import cn.teammodel.model.dto.ai.ChatCompletionReqDto;
-import cn.teammodel.model.dto.ai.deepseek.ChatResponseDto;
+import cn.teammodel.model.dto.ai.deepseek.DeepSeekChatRequestDto;
+import cn.teammodel.model.dto.ai.deepseek.DeepSeekChatResponse;
 import cn.teammodel.model.dto.ai.deepseek.ChatReqDto;
+import cn.teammodel.model.entity.ai.ChatSession;
 import cn.teammodel.model.entity.ai.DeepSeekSession;
 import cn.teammodel.model.entity.ai.DeepSeekSession.DeepSeekMessage;
+import cn.teammodel.repository.ChatSessionRepository;
 import cn.teammodel.repository.DeepSeekRepository;
 import cn.teammodel.security.utils.SecurityUtil;
 import cn.teammodel.service.DeepSeekService;
 import cn.teammodel.service.DeepSeekSessionService;
+import cn.teammodel.utils.RepositoryUtil;
+import com.azure.cosmos.models.CosmosPatchOperations;
+import com.fasterxml.jackson.databind.JsonNode;
+import lombok.extern.slf4j.Slf4j;
+import org.apache.http.client.methods.CloseableHttpResponse;
+import org.apache.http.client.methods.HttpPost;
+import org.apache.http.entity.StringEntity;
+import org.apache.http.impl.client.CloseableHttpClient;
+import org.apache.http.impl.client.HttpClients;
 import org.springframework.stereotype.Service;
-
+import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;
 import javax.annotation.Resource;
+import java.io.BufferedReader;
+import java.io.InputStreamReader;
+import java.nio.charset.StandardCharsets;
 import java.time.Instant;
 import java.util.*;
+import java.util.concurrent.ExecutorService;
+import java.util.concurrent.Executors;
+import com.fasterxml.jackson.databind.ObjectMapper;
+
 
 
 /**
  * 描述：访问DeepSeek方法
  */
 @Service
+@Slf4j
 public class DeepSeekServiceImpl implements DeepSeekService {
     @Resource
     private DeepSeekSessionService deepSeekService;
 
     @Resource
     private DeepSeekRepository deepSeekRepository;
+    @Resource
+    private ChatSessionRepository chatSessionRepository;
 
+    private final ExecutorService executorService = Executors.newCachedThreadPool();
+    private final ObjectMapper objectMapper = new ObjectMapper();
     /**
      * 提问
      * @param message
      * @return
      */
     @Override
-    public ChatResponseDto ChatAsk(ChatReqDto message) {
+    public DeepSeekChatResponse ChatAsk(ChatReqDto message) {
         //创建消息列表
         List<ChatReqDto> msg = new ArrayList<>();
         msg.add(message);
 
         //构建请求头
-        ChatRequestOKHttpDto requestBody = new ChatRequestOKHttpDto();
+        DeepSeekChatRequestDto requestBody = new DeepSeekChatRequestDto();
         requestBody.setModel(DeepSeekClient.API_Model);
         requestBody.setMessages(msg);
         requestBody.setTemperature(0);
@@ -50,7 +75,7 @@ public class DeepSeekServiceImpl implements DeepSeekService {
         //开始时间
         long startTime = System.currentTimeMillis();
         //发起请求
-        ChatResponseDto response = DeepSeekClient.SendRequests(requestBody);
+        DeepSeekChatResponse response = DeepSeekClient.SendRequests(requestBody);
         //Map<String, Object> response = DeepSeekClient.SendRequests(requestBody);
         //Map<String, Object> response = SendRequest(requestBody);
         //结束时间
@@ -77,6 +102,108 @@ public class DeepSeekServiceImpl implements DeepSeekService {
         return response;
     }
 
+
+    @Override
+    public SseEmitter OKHttpChatSeeEmitterAsk(ChatReqDto message) {
+        SseEmitter se = new SseEmitter(-1L);
+        //创建消息列表
+        List<ChatReqDto> msg = new ArrayList<>();
+        msg.add(message);
+
+        //构建请求头
+        DeepSeekChatRequestDto requestBody = new DeepSeekChatRequestDto();
+        requestBody.setModel(DeepSeekClient.API_Model);
+        requestBody.setMessages(msg);
+        requestBody.setTemperature(0);
+        requestBody.setMax_tokens(1024);
+        requestBody.setStream(true);
+        if (requestBody.getStream()){
+           se =  DeepSeekClient.SendRequestsEmitter(requestBody);
+
+        }else   {
+
+            DeepSeekChatResponse response = DeepSeekClient.SendRequests(requestBody);
+        }
+        return se;
+    }
+
+    /**
+     * 提问  流式回答
+     * @param chatCompletionReqDto
+     * @return
+     */
+    @Override
+    public SseEmitter ChatSeeEmitterAsk(ChatCompletionReqDto chatCompletionReqDto) {
+        SseEmitter sseEmitter = new SseEmitter(-1L);
+        StringBuilder strContent = new StringBuilder();
+        executorService.execute(()-> {
+            try {
+                log.info("流式回答开始,问题:{}", chatCompletionReqDto.getText());
+                try (CloseableHttpClient client = HttpClients.createDefault()) {
+                    HttpPost httpPost = new HttpPost(DeepSeekClient.API_Url);
+                    httpPost.setHeader("Content-Type", "application/json");
+                    httpPost.setHeader("Accept", "application/json");
+                    httpPost.setHeader("Authorization", "Bearer " + DeepSeekClient.API_Key);
+
+                    Map<String, Object> question = new HashMap<>();
+                    question.put("role", "user");
+                    question.put("content", chatCompletionReqDto.getText());
+
+                    Map<String, Object> requestMap = new HashMap<>();
+                    requestMap.put("model", DeepSeekClient.API_Model);
+                    requestMap.put("messages", Collections.singletonList(question));
+                    requestMap.put("stream", true);
+
+                    String requestBody = objectMapper.writeValueAsString(requestMap);
+                    httpPost.setEntity(new StringEntity(requestBody, StandardCharsets.UTF_8));
+                    StringBuilder responseBody = new StringBuilder();
+                    try (CloseableHttpResponse response = client.execute(httpPost);
+                         BufferedReader reader = new BufferedReader(
+                                 new InputStreamReader(response.getEntity().getContent(), StandardCharsets.UTF_8))) {
+                        String line;
+                        while ((line = reader.readLine()) != null) {
+                            if (line.startsWith("data: ")) {
+                                String jsonData = line.substring(6);
+                                if ("[DONE]".equals(jsonData)) {
+                                    sseEmitter.send("[DONE]");
+                                    // 会话完成，更新历史会话记录
+                                    ChatSession.Message message = ChatSession.Message.of(chatCompletionReqDto.getText(), strContent.toString(),chatCompletionReqDto.getModel());
+                                    HistoryCache.updateContext(chatCompletionReqDto.getSessionId(), message);
+                                    CosmosPatchOperations options = CosmosPatchOperations.create()
+                                            .replace("/updateTime", Instant.now().toEpochMilli())
+                                            .add("/history/-", message);
+                                    chatSessionRepository.save(chatCompletionReqDto.getSessionId(), PK.of(PK.CHAT_SESSION), ChatSession.class, options);
+                                    break;
+                                }
+                                JsonNode node = objectMapper.readTree(jsonData);
+                                String content = node.path("choices")
+                                        .path(0)
+                                        .path("delta")
+                                        .path("content")
+                                        .asText("");
+                                if (!content.isEmpty()) {
+                                    responseBody.append(content);
+                                    strContent.append(content);
+                                    sseEmitter.send(content);
+                                }
+                            }
+                        }
+                        log.info("流式回答结束,{}",question);
+                        sseEmitter.complete();
+                    }
+                } catch (Exception e) {
+                    log.error("处理 Deepseek 请求时发生错误", e);
+                    sseEmitter.completeWithError(e);
+                }
+            } catch (Exception e) {
+                log.error("处理 Deepseek 请求时发生错误", e);
+                sseEmitter.completeWithError(e);
+            }
+        });
+
+        return sseEmitter;
+    }
+
     //region 辅助方法
     /**
      * 新增/更新会话
@@ -85,7 +212,7 @@ public class DeepSeekServiceImpl implements DeepSeekService {
      * @param savaMessage
      * @param response
      */
-    private void UpdateSession(ChatReqDto message, DeepSeekSession session, DeepSeekMessage savaMessage, ChatResponseDto response) {
+    private void UpdateSession(ChatReqDto message, DeepSeekSession session, DeepSeekMessage savaMessage, DeepSeekChatResponse response) {
         if (session.getId() == null){
             List<DeepSeekMessage> history = Collections.singletonList(savaMessage);
             String userId = SecurityUtil.getLoginUser().getId();