Version: 0.4.2.dev.260305

feat: 🧠 支持切换模型思考模式

* 新增模型思考开关配置，支持动态控制模型是否启用思考模式

backend/agent/graph.go

@@ -8,6 +8,7 @@ import (
 
 	"github.com/cloudwego/eino-ext/components/model/ark"
 	"github.com/cloudwego/eino/schema"
+	arkModel "github.com/volcengine/volcengine-go-sdk/service/arkruntime/model"
 )
 
 // StreamResponse 专为 Apifox/前端 识别设计的极简结构
@@ -31,10 +32,25 @@ func ToStreamResponseDTO(chunk *schema.Message) StreamResponse {
 	return dto
 }
 
+func ToStreamReasoningResponseDTO(chunk *schema.Message) StreamResponse {
+	var dto StreamResponse
+	dto.Choices = append(dto.Choices, struct {
+		Delta struct {
+			Content string `json:"content"`
+		} `json:"delta"`
+	}{})
+	dto.Choices[0].Delta.Content = chunk.ReasoningContent
+	return dto
+}
+
 // ToOpenAIStream 负责将 Eino 的内部 Chunk 转换为 OpenAI 兼容的 data: {JSON} 字符串
 func ToOpenAIStream(chunk *schema.Message) (string, error) {
-	dto := ToStreamResponseDTO(chunk)
-
+	var dto StreamResponse
+	if chunk.ReasoningContent != "" {
+		dto = ToStreamReasoningResponseDTO(chunk)
+	} else {
+		dto = ToStreamResponseDTO(chunk)
+	}
 	jsonBytes, err := json.Marshal(dto)
 	if err != nil {
 		return "", err
@@ -43,7 +59,7 @@ func ToOpenAIStream(chunk *schema.Message) (string, error) {
 	return string(jsonBytes), nil
 }
 
-func StreamChat(ctx context.Context, llm *ark.ChatModel, userInput string, chatHistory []*schema.Message, outChan chan<- string) (string, error) {
+func StreamChat(ctx context.Context, llm *ark.ChatModel, userInput string, ifThinking bool, chatHistory []*schema.Message, outChan chan<- string) (string, error) {
 	// 1. 组装消息
 	messages := make([]*schema.Message, 0)
 	// A. 塞入 System Message (人设)
@@ -55,7 +71,13 @@ func StreamChat(ctx context.Context, llm *ark.ChatModel, userInput string, chatH
 	// C. 塞入用户当前的消息 (当前需求)
 	messages = append(messages, schema.UserMessage(userInput))
 	// 2. 调用流式接口
-	reader, err := llm.Stream(ctx, messages)
+	var thinking *ark.Thinking
+	if ifThinking {
+		thinking = &arkModel.Thinking{Type: arkModel.ThinkingTypeEnabled}
+	} else {
+		thinking = &arkModel.Thinking{Type: arkModel.ThinkingTypeDisabled}
+	}
+	reader, err := llm.Stream(ctx, messages, ark.WithThinking(thinking))
 	if err != nil {
 		return "", err
 	}
@@ -71,9 +93,9 @@ func StreamChat(ctx context.Context, llm *ark.ChatModel, userInput string, chatH
 		if err != nil {
 			return "", err
 		}
-		if chunk.Content == "" {
+		/*if chunk.Content == "" { // 过滤掉空内容，避免发送无效消息
 			continue
-		}
+		}*/
 		fullText.WriteString(chunk.Content)
 		// 将内容发送到通道中供前端消费
 		retChuck, err := ToOpenAIStream(chunk)

backend/api/agent.go

@@ -35,7 +35,7 @@ func (api *AgentHandler) ChatAgent(c *gin.Context) {
 	}
 	userID := c.GetInt("user_id") // 从上下文中获取用户 ID
 	// 3. 调用 Service 层的聊天方法，获取输出通道和错误通道
-	outChan, errChan := api.svc.AgentChat(c.Request.Context(), req.Message, userID, req.ConversationID)
+	outChan, errChan := api.svc.AgentChat(c.Request.Context(), req.Message, req.Thinking, userID, req.ConversationID)
 	// 4. 循环转发消息/错误
 	c.Stream(func(w io.Writer) bool {
 		select {

backend/model/agent.go

@@ -5,7 +5,8 @@ import "time"
 type UserSendMessageRequest struct {
 	ConversationID string `json:"conversation_id,omitempty"` // 可选，指定对话 ID
 	Message        string `json:"message" binding:"required"`
-	Model          string `json:"model,omitempty"` // 可选，指定使用的模型
+	Model          string `json:"model,omitempty"`    // 可选，指定使用的模型
+	Thinking       bool   `json:"thinking,omitempty"` // 可选，是否开启思考模式
 }
 
 type SSEResponse struct {

backend/service/agent.go

@@ -22,7 +22,7 @@ func NewAgentService(aiHub *inits.AIHub, repo *dao.AgentDAO) *AgentService {
 	}
 }
 
-func (s *AgentService) AgentChat(ctx context.Context, userMessage string, userID int, chatID string) (<-chan string, <-chan error) {
+func (s *AgentService) AgentChat(ctx context.Context, userMessage string, ifThinking bool, userID int, chatID string) (<-chan string, <-chan error) {
 	//1. 创建一个输出通道
 	outChan := make(chan string, 5)
 	errChan := make(chan error, 1)
@@ -69,7 +69,7 @@ func (s *AgentService) AgentChat(ctx context.Context, userMessage string, userID
 	go func() {
 		defer close(outChan) // 确保在函数结束时关闭通道
 		//3. 调用 StreamChat 函数进行流式聊天
-		fullText, err := agent.StreamChat(ctx, s.AIHub.Worker, userMessage, chatHistory, outChan)
+		fullText, err := agent.StreamChat(ctx, s.AIHub.Worker, userMessage, ifThinking, chatHistory, outChan)
 		if err != nil {
 			errChan <- err
 			return