Version: 0.4.5.dev.260307

feat: 📡 更新 SSE 消息流格式

* 将 SSE 消息流格式更新为 Apifox 可识别的 OpenAI 格式
* 便于后续与前端的对接与协作

backend/agent/graph.go

@@ -5,72 +5,99 @@ import (
 	"encoding/json"
 	"io"
 	"strings"
+	"time"
 
 	"github.com/cloudwego/eino-ext/components/model/ark"
 	"github.com/cloudwego/eino/schema"
+	"github.com/google/uuid"
 	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
+// StreamResponse 为 OpenAI/DeepSeek 兼容的流式 chunk 结构
 type StreamResponse struct {
-	Choices []struct {
-		Delta struct {
-			Content string `json:"content"`
-		} `json:"delta"`
-	} `json:"choices"`
+	ID      string         `json:"id"`
+	Object  string         `json:"object"`
+	Created int64          `json:"created"`
+	Model   string         `json:"model"`
+	Choices []StreamChoice `json:"choices"`
 }
 
-// ToStreamResponseDTO 将 Eino 的内部 Chunk 转换为 StreamResponse DTO
-func ToStreamResponseDTO(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.Content
-	return dto
+type StreamChoice struct {
+	Index        int         `json:"index"`
+	Delta        StreamDelta `json:"delta"`
+	FinishReason *string     `json:"finish_reason"`
 }
 
-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
+type StreamDelta struct {
+	Role             string `json:"role,omitempty"`
+	Content          string `json:"content,omitempty"`
+	ReasoningContent string `json:"reasoning_content,omitempty"`
 }
 
-// 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) {
-	var dto StreamResponse
-	if chunk.ReasoningContent != "" {
-		dto = ToStreamReasoningResponseDTO(chunk)
-	} else {
-		dto = ToStreamResponseDTO(chunk)
+// ToOpenAIStream 将单个 Eino chunk 转为 OpenAI 兼容 JSON
+func ToOpenAIStream(chunk *schema.Message, requestID, modelName string, created int64, includeRole bool) (string, error) {
+	delta := StreamDelta{}
+	if includeRole {
+		delta.Role = "assistant"
+	}
+	if chunk != nil {
+		delta.Content = chunk.Content
+		delta.ReasoningContent = chunk.ReasoningContent
+	}
+
+	if delta.Role == "" && delta.Content == "" && delta.ReasoningContent == "" {
+		return "", nil
+	}
+
+	dto := StreamResponse{
+		ID:      requestID,
+		Object:  "chat.completion.chunk",
+		Created: created,
+		Model:   modelName,
+		Choices: []StreamChoice{{
+			Index:        0,
+			Delta:        delta,
+			FinishReason: nil,
+		}},
 	}
 	jsonBytes, err := json.Marshal(dto)
 	if err != nil {
 		return "", err
 	}
-	// 严格遵循 SSE 协议格式
 	return string(jsonBytes), nil
 }
 
-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
+// ToOpenAIFinishStream 生成结束 chunk（finish_reason=stop）
+func ToOpenAIFinishStream(requestID, modelName string, created int64) (string, error) {
+	stop := "stop"
+	dto := StreamResponse{
+		ID:      requestID,
+		Object:  "chat.completion.chunk",
+		Created: created,
+		Model:   modelName,
+		Choices: []StreamChoice{{
+			Index:        0,
+			Delta:        StreamDelta{},
+			FinishReason: &stop,
+		}},
+	}
+	jsonBytes, err := json.Marshal(dto)
+	if err != nil {
+		return "", err
+	}
+	return string(jsonBytes), nil
+}
+
+func StreamChat(ctx context.Context, llm *ark.ChatModel, modelName string, userInput string, ifThinking bool, chatHistory []*schema.Message, outChan chan<- string) (string, error) {
+	// 1) 组装提示消息
 	messages := make([]*schema.Message, 0)
-	// A. 塞入 System Message (人设)
 	messages = append(messages, schema.SystemMessage(SystemPrompt))
-	// B. 塞入历史记录 (上下文)
 	if len(chatHistory) > 0 {
 		messages = append(messages, chatHistory...)
 	}
-	// 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
+
+	// 2) 发起流式请求
 	var thinking *ark.Thinking
 	if ifThinking {
 		thinking = &arkModel.Thinking{Type: arkModel.ThinkingTypeEnabled}
@@ -81,28 +108,45 @@ func StreamChat(ctx context.Context, llm *ark.ChatModel, userInput string, ifThi
 	if err != nil {
 		return "", err
 	}
-	defer reader.Close() // 记得关闭 Reader
+	defer reader.Close()
 
-	// 3. 循环读取直到结束
+	if strings.TrimSpace(modelName) == "" {
+		modelName = "smartflow-worker"
+	}
+	requestID := "chatcmpl-" + uuid.NewString()
+	created := time.Now().Unix()
+	firstChunk := true
+
+	// 3) 持续转发 chunk
 	var fullText strings.Builder
 	for {
 		chunk, err := reader.Recv()
 		if err == io.EOF {
-			break // 读取完成
+			break
 		}
 		if err != nil {
 			return "", err
 		}
-		/*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)
+
+		payload, err := ToOpenAIStream(chunk, requestID, modelName, created, firstChunk)
 		if err != nil {
 			return "", err
 		}
-		outChan <- retChuck
+		if payload != "" {
+			outChan <- payload
+			firstChunk = false
+		}
 	}
+
+	// 4) 发送结束 chunk 和 [DONE]
+	finishChunk, err := ToOpenAIFinishStream(requestID, modelName, created)
+	if err != nil {
+		return "", err
+	}
+	outChan <- finishChunk
+	outChan <- "[DONE]"
+
 	return fullText.String(), nil
 }