context:通义万相文生图节点功能以及发送邮箱和HTTP请求节点调研

ruoyi-modules/ruoyi-aiflow/src/main/java/org/ruoyi/workflow/workflow/WfNodeFactory.java

@@ -4,9 +4,10 @@ import org.ruoyi.workflow.entity.WorkflowComponent;
 import org.ruoyi.workflow.entity.WorkflowNode;
 import org.ruoyi.workflow.workflow.node.AbstractWfNode;
 import org.ruoyi.workflow.workflow.node.EndNode;
-import org.ruoyi.workflow.workflow.node.HumanFeedbackNode;
+import org.ruoyi.workflow.workflow.node.humanFeedBack.HumanFeedbackNode;
 import org.ruoyi.workflow.workflow.node.answer.LLMAnswerNode;
 import org.ruoyi.workflow.workflow.node.httpRequest.HttpRequestNode;
+import org.ruoyi.workflow.workflow.node.image.ImageNode;
 import org.ruoyi.workflow.workflow.node.keywordExtractor.KeywordExtractorNode;
 import org.ruoyi.workflow.workflow.node.knowledgeRetrieval.KnowledgeRetrievalNode;
 import org.ruoyi.workflow.workflow.node.mailSend.MailSendNode;
@@ -21,6 +22,7 @@ public class WfNodeFactory {
             case START -> wfNode = new StartNode(wfComponent, nodeDefinition, wfState, nodeState);
             case LLM_ANSWER -> wfNode = new LLMAnswerNode(wfComponent, nodeDefinition, wfState, nodeState);
             case KEYWORD_EXTRACTOR -> wfNode = new KeywordExtractorNode(wfComponent, nodeDefinition, wfState, nodeState);
+            case TONGYI_WANX -> wfNode = new ImageNode(wfComponent, nodeDefinition, wfState, nodeState);
             case KNOWLEDGE_RETRIEVER -> wfNode = new KnowledgeRetrievalNode(wfComponent, nodeDefinition, wfState, nodeState);
             case END -> wfNode = new EndNode(wfComponent, nodeDefinition, wfState, nodeState);
             case MAIL_SEND -> wfNode = new MailSendNode(wfComponent, nodeDefinition, wfState, nodeState);

ruoyi-modules/ruoyi-aiflow/src/main/java/org/ruoyi/workflow/workflow/WorkflowUtil.java

@@ -13,10 +13,13 @@ import org.bsc.langgraph4j.langchain4j.generators.StreamingChatGenerator;
 import org.bsc.langgraph4j.state.AgentState;
 import org.ruoyi.common.chat.Service.IChatModelService;
 import org.ruoyi.common.chat.Service.IChatService;
+import org.ruoyi.common.chat.Service.IImageGenerationService;
 import org.ruoyi.common.chat.domain.dto.request.ChatRequest;
 import org.ruoyi.common.chat.domain.entity.chat.ChatContext;
+import org.ruoyi.common.chat.domain.entity.image.ImageContext;
 import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
 import org.ruoyi.common.chat.factory.ChatServiceFactory;
+import org.ruoyi.common.chat.factory.ImageServiceFactory;
 import org.ruoyi.workflow.base.NodeInputConfigTypeHandler;
 import org.ruoyi.workflow.entity.WorkflowNode;
 import org.ruoyi.workflow.enums.WfIODataTypeEnum;
@@ -38,6 +41,9 @@ public class WorkflowUtil {
     @Resource
     private ChatServiceFactory chatServiceFactory;
 
+    @Resource
+    private ImageServiceFactory imageServiceFactory;
+
     @Resource
     private IChatModelService chatModelService;
 
@@ -213,4 +219,30 @@ public class WorkflowUtil {
             .filter(item -> nameSet.contains(item.getName()))
             .map(item -> getMessage("user", item.getContent().getValue().toString())).toList();
     }
+
+    /**
+     * 调用LLM 根据文字生成图片
+     */
+    public String buildTextToImage(String modelName, String prompt, String size, Integer seed){
+        log.info("Generate image invoke, modelName: {}", modelName);
+        // 根据模型名称查询模型信息
+        ChatModelVo chatModelVo = chatModelService.selectModelByName(modelName);
+        if (chatModelVo == null) {
+            throw new IllegalArgumentException("模型不存在: " + modelName);
+        }
+        // 根据模型名称找到模型实体
+        String modelVoCategory = chatModelVo.getCategory();
+        // 根据 category 获取对应的 IImageGenerationService（不使用计费代理，工作流场景单独计费）
+        IImageGenerationService imageService = imageServiceFactory.getOriginalService(modelVoCategory);
+        // 构建文生图上下文对象
+        ImageContext imageContext = ImageContext.builder()
+            .chatModelVo(chatModelVo)
+            .prompt(prompt)
+            .size(size)
+            .seed(seed)
+            .build();
+        // 调用LLM 生成图片
+        return imageService.generateImage(imageContext);
+    }
+
 }

ruoyi-modules/ruoyi-aiflow/src/main/java/org/ruoyi/workflow/workflow/node/answer/LLMAnswerNodeConfig.java

@@ -12,12 +12,6 @@ public class LLMAnswerNodeConfig {
     @NotBlank
     private String prompt;
 
-    /**
-     * TODO
-     */
-    // @NotBlank
-    private String category;
-
     @NotNull
     @JsonProperty("model_name")
     private String modelName;

ruoyi-modules/ruoyi-aiflow/src/main/java/org/ruoyi/workflow/workflow/node/humanFeedBack/HumanFeedbackNode.java

@@ -1,4 +1,4 @@
-package org.ruoyi.workflow.workflow.node;
+package org.ruoyi.workflow.workflow.node.humanFeedBack;
 
 import lombok.extern.slf4j.Slf4j;
 import org.apache.commons.lang3.StringUtils;
@@ -8,6 +8,7 @@ import org.ruoyi.workflow.workflow.NodeProcessResult;
 import org.ruoyi.workflow.workflow.WfNodeState;
 import org.ruoyi.workflow.workflow.WfState;
 import org.ruoyi.workflow.workflow.data.NodeIOData;
+import org.ruoyi.workflow.workflow.node.AbstractWfNode;
 
 import static org.ruoyi.workflow.cosntant.AdiConstant.WorkflowConstant.*;
 

ruoyi-modules/ruoyi-aiflow/src/main/java/org/ruoyi/workflow/workflow/node/image/ImageNode.java

@@ -0,0 +1,62 @@
+package org.ruoyi.workflow.workflow.node.image;
+
+import lombok.extern.slf4j.Slf4j;
+import org.apache.commons.lang3.StringUtils;
+import org.ruoyi.workflow.entity.WorkflowComponent;
+import org.ruoyi.workflow.entity.WorkflowNode;
+import org.ruoyi.workflow.util.SpringUtil;
+import org.ruoyi.workflow.workflow.NodeProcessResult;
+import org.ruoyi.workflow.workflow.WfNodeState;
+import org.ruoyi.workflow.workflow.WfState;
+import org.ruoyi.workflow.workflow.WorkflowUtil;
+import org.ruoyi.workflow.workflow.data.NodeIOData;
+import org.ruoyi.workflow.workflow.node.AbstractWfNode;
+
+import static org.ruoyi.workflow.cosntant.AdiConstant.WorkflowConstant.NODE_PROCESS_STATUS_SUCCESS;
+
+/**
+ * 【节点】文生图 <br/>
+ * 节点内容固定格式：ImageNodeConfig
+ */
+@Slf4j
+public class ImageNode extends AbstractWfNode {
+
+    public ImageNode(WorkflowComponent wfComponent, WorkflowNode nodeDef, WfState wfState, WfNodeState nodeState) {
+        super(wfComponent, nodeDef, wfState, nodeState);
+    }
+
+    /**
+     * nodeConfig格式：
+     * {"prompt": "{input}","model_name":"wan2.5-t2i-preview","size":"1024*1024"}
+     *
+     * @return 图片地址URL
+     */
+    @Override
+    public NodeProcessResult onProcess() {
+        ImageNodeConfig nodeConfigObj = checkAndGetConfig(ImageNodeConfig.class);
+        String inputText = getFirstInputText();
+        log.info("Image node config:{}", nodeConfigObj);
+        String prompt = inputText;
+        if (StringUtils.isNotBlank(nodeConfigObj.getPrompt())) {
+            prompt = WorkflowUtil.renderTemplate(nodeConfigObj.getPrompt(), state.getInputs());
+        }
+        log.info("Image prompt:{}", prompt);
+        // 获取工作流实例
+        WorkflowUtil workflowUtil = SpringUtil.getBean(WorkflowUtil.class);
+        // 获取模型名称
+        String modelName = nodeConfigObj.getModelName();
+        // 获取图片大小
+        String size = nodeConfigObj.getSize();
+        // 获取随机数种子
+        Integer seed = nodeConfigObj.getSeed();
+        // 调用LLM生成图片（后续可以将图片保存到OSS中）
+        String imageUrl = workflowUtil.buildTextToImage(modelName, prompt, size, seed);
+        // 创建节点参数对象
+        NodeIOData nodeIOData = NodeIOData.createByText("output", "image", imageUrl);
+        // 添加到输出列表以便给后续节点使用
+        state.getOutputs().add(nodeIOData);
+        // 设置为成功状态
+        state.setProcessStatus(NODE_PROCESS_STATUS_SUCCESS);
+        return new NodeProcessResult();
+    }
+}

ruoyi-modules/ruoyi-aiflow/src/main/java/org/ruoyi/workflow/workflow/node/image/ImageNodeConfig.java

@@ -0,0 +1,37 @@
+package org.ruoyi.workflow.workflow.node.image;
+
+import com.fasterxml.jackson.annotation.JsonProperty;
+import jakarta.validation.constraints.Max;
+import jakarta.validation.constraints.Min;
+import jakarta.validation.constraints.NotNull;
+import lombok.Data;
+import lombok.EqualsAndHashCode;
+
+@EqualsAndHashCode
+@Data
+public class ImageNodeConfig {
+
+    /**
+     * 提示词
+     */
+    private String prompt;
+
+    /**
+     * 模型名称
+     */
+    @NotNull
+    @JsonProperty("model_name")
+    private String modelName;
+
+    /**
+     * 图片尺寸大小
+     */
+    private String size;
+
+    /**
+     * 随机数种子
+     */
+    @Min(value = 0, message = "随机数种子不能小于0")
+    @Max(value = 2147483647, message = "随机数种子不能大于2147483647")
+    private Integer seed;
+}