feat: 调整sql脚本

上传图片支持使用后台image分类下通义千问模型

ruoyi-modules-api/ruoyi-chat-api/src/main/java/org/ruoyi/service/IChatModelService.java

@@ -53,9 +53,13 @@ public interface IChatModelService {
      * 通过模型名称获取模型信息
      */
     ChatModelVo selectModelByName(String modelName);
-
+    /**
+     * 通过模型分类获取模型信息
+     */
+    ChatModelVo selectModelByCategory(String image);
     /**
      * 获取ppt模型信息
      */
     ChatModel getPPT();
+
 }

ruoyi-modules-api/ruoyi-chat-api/src/main/java/org/ruoyi/service/impl/ChatModelServiceImpl.java

@@ -129,6 +129,13 @@ public class ChatModelServiceImpl implements IChatModelService {
     public ChatModelVo selectModelByName(String modelName) {
         return baseMapper.selectVoOne(Wrappers.<ChatModel>lambdaQuery().eq(ChatModel::getModelName, modelName));
     }
+    /**
+     * 通过模型分类获取模型信息
+     */
+    @Override
+    public ChatModelVo selectModelByCategory(String  category) {
+        return baseMapper.selectVoOne(Wrappers.<ChatModel>lambdaQuery().eq(ChatModel::getCategory, category));
+    }
 
     @Override
     public ChatModel getPPT() {

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/chat/enums/ChatModeType.java

@@ -15,7 +15,9 @@ public enum ChatModeType {
 
     QIANWEN("qianwen", "通义千问"),
 
-    VECTOR("vector", "知识库向量模型");
+    VECTOR("vector", "知识库向量模型"),
+
+    IMAGE("image", "图片识别模型");
 
     private final String code;
     private final String description;

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/chat/service/chat/impl/ImageServiceImpl.java

@@ -0,0 +1,151 @@
+package org.ruoyi.chat.service.chat.impl;
+
+import lombok.SneakyThrows;
+import lombok.extern.slf4j.Slf4j;
+import org.ruoyi.chat.config.ChatConfig;
+import org.ruoyi.chat.enums.ChatModeType;
+import org.ruoyi.chat.listener.SSEEventSourceListener;
+import org.ruoyi.chat.service.chat.IChatService;
+import org.ruoyi.common.chat.entity.chat.ChatCompletion;
+import org.ruoyi.common.chat.entity.chat.Message;
+import org.ruoyi.common.chat.openai.OpenAiStreamClient;
+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.util.*;
+
+/**
+ * 图片识别模型
+ */
+@Service
+@Slf4j
+public class ImageServiceImpl implements IChatService {
+
+    @Autowired
+    private IChatModelService chatModelService;
+
+    @SneakyThrows
+//    @Override
+//    public SseEmitter chat(ChatRequest chatRequest, SseEmitter emitter) {
+//        ChatModelVo chatModelVo = chatModelService.selectModelByCategory("image");
+//
+//        // 发送流式消息
+//
+//            MultiModalConversation conv = new MultiModalConversation();
+//            MultiModalMessage systemMessage = MultiModalMessage.builder().role(Role.SYSTEM.getValue())
+//                    .content(Arrays.asList(
+//                            Collections.singletonMap("text",chatRequest.getSysPrompt()))).build();
+//            // 获取用户消息内容
+//            List<Message> messages = chatRequest.getMessages();
+//            MultiModalMessage userMessage = null;
+//            //漫长的格式转换
+//            // 遍历消息列表，提取文本内容
+//        if (messages != null && !messages.isEmpty()) {
+//            Object content = messages.get(messages.size() - 1).getContent();
+//            List<Map<String, Object>> contentList = new ArrayList<>();
+//            StringBuilder textContent = new StringBuilder();
+//            if (content instanceof List<?>) {
+//                for (Object item : (List<?>) content) {
+//                    if (item instanceof Map<?, ?> mapItem) {
+//                        String type = (String) mapItem.get("type");
+//                        if ("text".equals(type)) {
+//                            String text = (String) mapItem.get("text");
+//                            if (text != null) {
+//                                textContent.append(text).append(" ");
+//                            }
+//                        } else if ("image_url".equals(type)) {
+//                            Map<String, String> imageUrl  = (Map<String, String>) mapItem.get("image_url");
+//                                contentList.add(Collections.singletonMap("image", imageUrl.get("url")));
+//                        }
+//                    }
+//                }
+//            }
+//            // 将拼接后的文本内容添加到 contentList
+//            if (textContent.length() > 0) {
+//                contentList.add(Collections.singletonMap("text", textContent.toString().trim()));
+//            }
+//            userMessage = MultiModalMessage.builder()
+//                    .role(Role.USER.getValue())
+//                    .content(contentList)
+//                    .build();
+//        }
+//            MultiModalConversationParam param = MultiModalConversationParam.builder()
+//                    .apiKey(chatModelVo.getApiKey())
+//                    .model(chatModelVo.getModelName())
+//                    .messages(Arrays.asList(systemMessage, userMessage))
+//                    .incrementalOutput(true)
+//                    .build();
+//
+//
+//        try {
+//            final QwenStreamingResponseBuilder responseBuilder = new QwenStreamingResponseBuilder(param.getModel(),param.getIncrementalOutput() );
+//            conv.streamCall(param, new ResultCallback<>() {
+//                @SneakyThrows
+//                public void onEvent(MultiModalConversationResult result) {
+//
+//                    String delta = responseBuilder.append(result);
+//                    if (Utils.isNotNullOrEmpty(delta)) {
+//
+//                        emitter.send(delta);
+//                        log.info("收到消息片段: {}", delta);
+//                    }
+//                }
+//                public void onComplete() {
+//                    emitter.complete();
+//                    log.info("消息结束", responseBuilder.build());
+//                }
+//                public void onError(Exception e) {
+//                    log.info("请求失败", e.getMessage());
+//                }
+//            });
+//        } catch (NoApiKeyException e) {
+//            emitter.send("请先配置API密钥");
+//            throw new RuntimeException(e);
+//        } catch (UploadFileException e) {
+//            throw new RuntimeException(e);
+//        }
+//
+//
+//        return emitter;
+//    }
+
+    @Override
+    public SseEmitter chat(ChatRequest chatRequest, SseEmitter emitter) {
+        // 从数据库获取 image 类型的模型配置
+        ChatModelVo chatModelVo = chatModelService.selectModelByCategory(ChatModeType.IMAGE.getCode());
+        if (chatModelVo == null) {
+            log.error("未找到 image 类型的模型配置");
+            emitter.completeWithError(new IllegalStateException("未找到 image 类型的模型配置"));
+            return emitter;
+        }
+
+        // 创建 OpenAI 流客户端
+        OpenAiStreamClient openAiStreamClient = ChatConfig.createOpenAiStreamClient(chatModelVo.getApiHost(), chatModelVo.getApiKey());
+        List<Message> messages = chatRequest.getMessages();
+
+        // 创建 SSE 事件源监听器
+        SSEEventSourceListener listener = new SSEEventSourceListener(emitter, chatRequest.getUserId(), chatRequest.getSessionId());
+
+        // 构建聊天完成请求
+        ChatCompletion completion = ChatCompletion
+                .builder()
+                .messages(messages)
+                .model(chatModelVo.getModelName()) // 使用数据库中配置的模型名称
+                .stream(true)
+                .build();
+
+        // 发起流式聊天完成请求
+        openAiStreamClient.streamChatCompletion(completion, listener);
+
+        return emitter;
+    }
+
+    @Override
+    public String getCategory() {
+        return ChatModeType.IMAGE.getCode();
+    }
+}

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/chat/service/chat/impl/QianWenAiChatServiceImpl.java

@@ -35,6 +35,8 @@ public class QianWenAiChatServiceImpl  implements IChatService {
                 .modelName(chatModelVo.getModelName())
                 .build();
 
+
+
         // 发送流式消息
         try {
             model.chat(chatRequest.getPrompt(), new StreamingChatResponseHandler() {

ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/chat/service/chat/impl/SseServiceImpl.java

@@ -125,7 +125,16 @@ public class SseServiceImpl implements ISseService {
      */
     private void buildChatMessageList(ChatRequest chatRequest){
         String sysPrompt;
-        chatModelVo = chatModelService.selectModelByName(chatRequest.getModel());
+        // 矫正模型名称 如果是gpt-image 则查询image类型模型 获取模型名称
+        if(chatRequest.getModel().equals("gpt-image")) {
+            chatModelVo = chatModelService.selectModelByCategory("image");
+            if (chatModelVo == null) {
+                log.error("未找到image类型的模型配置");
+                throw new IllegalStateException("未找到image类型的模型配置");
+            }
+        }else{
+            chatModelVo = chatModelService.selectModelByName(chatRequest.getModel());
+        }
         // 获取对话消息列表
         List<Message> messages = chatRequest.getMessages();
         // 查询向量库相关信息加入到上下文

script/sql/ruoyi-ai.sql

@@ -132,8 +132,8 @@ INSERT INTO `chat_model` VALUES (1828324413241466880, '000000', 'vector', 'quent
 INSERT INTO `chat_model` VALUES (1828324413241466881, '000000', 'vector', 'baai/bge-m3', 'baai/bge-m3', 0.01, '2', '1', NULL, 'https://api.ppinfra.com/v3/openai', 'sk-xx', NULL, 103, 1, '2024-08-27 14:51:23', 1, '2025-05-24 17:33:11', 'BGE-M3 是一款具备多维度能力的文本嵌入模型，可同时实现密集检索、多向量检索和稀疏检索三大核心功能。该模型设计上兼容超过100种语言，并支持从短句到长达8192词元的长文本等多种输入形式。在跨语言检索任务中，BGE-M3展现出显著优势，其性能在MIRACL、MKQA等国际基准测试中位居前列。此外，针对长文档检索场景，该模型在MLDR、NarritiveQA等数据集上的表现同样达到行业领先水平。');
 INSERT INTO `chat_model` VALUES (1859570229117022211, '000000', 'chat', 'deepseek/deepseek-v3-0324', 'deepseek/deepseek-v3-0324', 0.1, '1', '0', '', 'https://api.ppinfra.com/v3/openai/chat/completions', 'sk-xx', NULL, 103, 1, '2024-11-21 20:11:06', 1, '2025-05-24 17:56:22', 'DeepSeek V3 0324 是深度求索（DeepSeek）团队旗舰级对话模型系列的最新版本，采用混合专家（Mixture-of-Experts, MoE）架构，参数量达685B参数。');
 INSERT INTO `chat_model` VALUES (1859570229117022212, '000000', 'chat', 'deepseek/deepseek-r1', 'deepseek/deepseek-r1', 0.1, '1', '0', '', 'https://api.ppinfra.com/v3/openai/chat/completions', 'sk-xx', NULL, 103, 1, '2024-11-21 20:11:06', 1, '2025-05-24 17:56:14', 'DeepSeek R1是DeepSeek团队发布的最新开源模型，具备非常强悍的推理性能，尤其在数学、编程和推理任务上达到了与OpenAI的o1模型相当的水平。');
-INSERT INTO `chat_model` VALUES (1926215622017482754, '000000', 'chat', 'gpt-4o-mini', 'gpt-4o-mini', 0.1, '1', '0', NULL, 'https://api.pandarobot.chat/v1/chat/completions/', 'sk-xx', NULL, 103, 1, '2025-05-24 17:56:06', 1, '2025-05-24 17:56:06', 'gpt 多模态模型');
+INSERT INTO `chat_model` VALUES (1930184891812147202, '000000', 'image', 'qwen/qwen2.5-vl-72b-instruct', 'qwen/qwen2.5-vl-72b-instruct', 0.003, '2', '0', NULL, 'https://api.ppinfra.com/v3/openai/chat/completions', 'xx', NULL, 103, 1, '2025-06-04 16:48:34', 1, '2025-06-04 16:48:34', '视觉模型');
-INSERT INTO `chat_model` VALUES (1926215622017482755, '000000', 'chat', 'gpt-4-all', 'gpt-4-all', 0.5, '2', '0', NULL, 'https://api.pandarobot.chat/v1/chat/completions/', 'sk-xx', NULL, 103, 1, '2025-05-24 17:56:06', 1, '2025-05-24 17:59:21', 'gpt 逆向多模态模型');
+
 
 -- ----------------------------
 -- Table structure for chat_pay_order

script/sql/update/20250605.sql

@@ -0,0 +1 @@
+