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861 lines
26 KiB
Go
861 lines
26 KiB
Go
package service
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import (
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"context"
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"crypto/rand"
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"encoding/json"
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"errors"
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"fmt"
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"net/http"
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"strings"
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"time"
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"github.com/Wei-Shaw/sub2api/internal/config"
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"github.com/Wei-Shaw/sub2api/internal/pkg/logger"
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"github.com/Wei-Shaw/sub2api/internal/pkg/windsurf"
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"github.com/gin-gonic/gin"
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"go.uber.org/zap"
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)
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type WindsurfGatewayService struct {
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chatService *WindsurfChatService
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cfg config.WindsurfConfig
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accountRepo AccountRepository
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}
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func NewWindsurfGatewayService(
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chatService *WindsurfChatService,
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cfg config.WindsurfConfig,
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accountRepo AccountRepository,
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) *WindsurfGatewayService {
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return &WindsurfGatewayService{
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chatService: chatService,
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cfg: cfg,
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accountRepo: accountRepo,
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}
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}
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// Forward 处理 Windsurf 平台的 Anthropic-兼容请求。
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// groupID 与 sessionHash 用于 Cascade 多轮复用：在同一 sticky session 上复用上游 LS cascade，
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// 跳过 StartCascade 的额外 RPC，并避免每轮把 full-history 重灌进 trajectory。空值表示不复用。
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func (s *WindsurfGatewayService) Forward(ctx context.Context, c *gin.Context, account *Account, body []byte, _ bool, groupID int64, sessionHash string) (*ForwardResult, error) {
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startTime := time.Now()
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reqLog := windsurfLogger(c, "windsurf_gateway.forward",
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zap.Int64("account_id", account.ID),
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)
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var req windsurfMessagesRequest
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if err := json.Unmarshal(body, &req); err != nil {
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s.writeClaudeError(c, http.StatusBadRequest, "invalid_request_error", "Invalid request body")
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return nil, fmt.Errorf("unmarshal request: %w", err)
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}
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normalizeWindsurfRequest(&req)
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if strings.TrimSpace(req.Model) == "" {
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s.writeClaudeError(c, http.StatusBadRequest, "invalid_request_error", "Missing model")
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return nil, fmt.Errorf("missing model")
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}
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reqLog = reqLog.With(zap.String("model", req.Model), zap.Bool("stream", req.Stream), zap.Int("tools_count", len(req.Tools)))
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// Convert Anthropic tools to OpenAI format
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var openAITools []windsurf.OpenAITool
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for _, t := range req.Tools {
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openAITools = append(openAITools, windsurf.OpenAITool{
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Type: "function",
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Function: windsurf.OpenAIFunction{
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Name: t.Name,
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Description: t.Description,
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Parameters: t.InputSchema,
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},
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})
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}
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hasTools := len(openAITools) > 0
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// Convert Anthropic messages to intermediate form
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var anthropicMsgs []windsurf.AnthropicMessage
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hasToolHistory := false
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if len(req.System) > 0 {
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anthropicMsgs = append(anthropicMsgs, windsurf.AnthropicMessage{
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Role: "system",
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Content: req.System,
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})
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}
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for mi, m := range req.Messages {
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contentBlocks := windsurfParseContentBlocks(m.Content)
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var toolResultMsgs []windsurf.AnthropicMessage
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var toolUseMsgs []windsurf.OpenAIToolCall
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var textParts []string
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var turnImages []windsurf.CascadeImage
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for bi, block := range contentBlocks {
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switch block.Type {
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case "tool_result":
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hasToolHistory = true
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resultContent := ""
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if block.Content != nil {
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resultContent = windsurfExtractContentTextFromRaw(block.Content)
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}
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contentJSON, _ := json.Marshal(resultContent)
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toolResultMsgs = append(toolResultMsgs, windsurf.AnthropicMessage{
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Role: "tool",
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Content: contentJSON,
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ToolCallID: block.ToolUseID,
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})
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// tool_result 内部可能含 image 块；按规划策略，把它们提取出来归到当前 turn images
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if extractedImgs, err := windsurfExtractImagesFromRaw(block.Content, fmt.Sprintf("messages[%d].content[%d].content", mi, bi)); err != nil {
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s.writeClaudeError(c, http.StatusBadRequest, "invalid_request_error", err.Error())
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return nil, err
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} else {
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turnImages = append(turnImages, extractedImgs...)
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}
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case "tool_use":
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hasToolHistory = true
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inputJSON, _ := json.Marshal(block.Input)
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toolUseMsgs = append(toolUseMsgs, windsurf.OpenAIToolCall{
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ID: block.ID,
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Type: "function",
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Function: windsurf.OpenAIToolCallFunc{
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Name: block.Name,
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Arguments: string(inputJSON),
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},
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})
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case "text":
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textParts = append(textParts, block.Text)
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case "thinking":
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// skip
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case "image":
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if block.Source == nil {
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s.writeClaudeError(c, http.StatusBadRequest, "invalid_request_error",
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fmt.Sprintf("messages[%d].content[%d].source is required for image blocks", mi, bi))
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return nil, fmt.Errorf("image block missing source")
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}
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if !strings.EqualFold(strings.TrimSpace(block.Source.Type), "base64") {
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s.writeClaudeError(c, http.StatusBadRequest, "invalid_request_error",
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fmt.Sprintf("messages[%d].content[%d].source.type must be \"base64\"", mi, bi))
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return nil, fmt.Errorf("unsupported image source type")
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}
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turnImages = append(turnImages, windsurf.CascadeImage{
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MimeType: block.Source.MediaType,
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Base64Data: block.Source.Data,
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})
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default:
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if block.Text != "" {
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textParts = append(textParts, block.Text)
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}
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}
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}
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if len(toolUseMsgs) > 0 {
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contentJSON, _ := json.Marshal(strings.Join(textParts, "\n"))
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anthropicMsgs = append(anthropicMsgs, windsurf.AnthropicMessage{
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Role: m.Role,
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Content: contentJSON,
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ToolCalls: toolUseMsgs,
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Images: turnImages,
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})
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} else if len(toolResultMsgs) > 0 {
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// tool_result 消息：图片挂到第一条 tool_result 上（保持对应关系大致正确）
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if len(turnImages) > 0 && len(toolResultMsgs) > 0 {
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toolResultMsgs[0].Images = turnImages
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}
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for _, tr := range toolResultMsgs {
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anthropicMsgs = append(anthropicMsgs, tr)
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}
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} else {
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text := windsurfExtractContentText(m.Content)
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contentJSON, _ := json.Marshal(text)
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anthropicMsgs = append(anthropicMsgs, windsurf.AnthropicMessage{
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Role: m.Role,
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Content: contentJSON,
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Images: turnImages,
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})
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}
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}
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emulateTools := hasTools || hasToolHistory
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var chatMessages []windsurf.ChatMessage
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var toolPreamble string
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if emulateTools {
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toolPreamble = windsurf.BuildToolPreambleForProto(openAITools, req.ToolChoice)
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chatMessages = windsurf.NormalizeMessagesForCascade(anthropicMsgs, []windsurf.OpenAITool{})
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reqLog.Info("windsurf_gateway.tool_emulation",
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zap.Int("tools_count", len(openAITools)),
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zap.Int("preamble_len", len(toolPreamble)),
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zap.Int("messages_count", len(chatMessages)),
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zap.Bool("has_tool_history", hasToolHistory),
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)
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} else {
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for _, m := range anthropicMsgs {
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text := windsurfExtractContentText(json.RawMessage(m.Content))
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chatMessages = append(chatMessages, windsurf.ChatMessage{
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Role: m.Role,
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Content: text,
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Images: m.Images,
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})
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}
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}
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// 提取"当前 user turn"的图像作为 sidecar，发给 Cascade 的 images 字段。
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// 策略：最后一个 role=="user" 的 message 的 Images。
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var currentTurnImages []windsurf.CascadeImage
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for i := len(chatMessages) - 1; i >= 0; i-- {
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if chatMessages[i].Role == "user" && len(chatMessages[i].Images) > 0 {
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currentTurnImages = chatMessages[i].Images
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break
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}
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}
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// 本地确定性校验（fail-fast 返回 Anthropic 风格 400）。
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if len(currentTurnImages) > 0 {
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if err := windsurf.ValidateCascadeImages(currentTurnImages, windsurf.DefaultCascadeImageValidationOptions()); err != nil {
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s.writeClaudeError(c, http.StatusBadRequest, "invalid_request_error", err.Error())
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return nil, err
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}
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// 同步把 digests 写回 chat messages，便于后续指纹/日志
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for i := range chatMessages {
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if len(chatMessages[i].Images) > 0 {
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chatMessages[i].ImageDigests = windsurf.BuildImageDigests(chatMessages[i].Images)
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}
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}
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reqLog.Info("windsurf_gateway.images",
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zap.Int("current_turn_images", len(currentTurnImages)),
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)
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}
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chatReq := &WindsurfChatRequest{
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AccountID: account.ID,
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GroupID: groupID,
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SessionHash: sessionHash,
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Model: req.Model,
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Messages: chatMessages,
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Stream: req.Stream,
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Tools: openAITools,
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ToolPreamble: toolPreamble,
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Images: currentTurnImages,
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}
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upstreamStart := time.Now()
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resp, err := s.chatService.Chat(ctx, chatReq)
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SetOpsLatencyMs(c, OpsUpstreamLatencyMsKey, time.Since(upstreamStart).Milliseconds())
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if err != nil {
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reqLog.Error("windsurf_gateway.chat_failed", zap.Error(err))
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appendOpsUpstreamError(c, OpsUpstreamErrorEvent{
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Platform: PlatformWindsurf,
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AccountID: account.ID,
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AccountName: account.Name,
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Kind: "http_error",
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Message: err.Error(),
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})
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// CascadeModelError → set model rate limit + trigger account failover
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var modelErr *windsurf.CascadeModelError
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if errors.As(err, &modelErr) {
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modelKey := windsurf.ResolveModel(req.Model)
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cooldown := 5 * time.Minute
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if strings.Contains(modelErr.Msg, "stall") {
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cooldown = 60 * time.Second
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}
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resetAt := time.Now().Add(cooldown)
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if s.accountRepo != nil {
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if rlErr := s.accountRepo.SetModelRateLimit(ctx, account.ID, modelKey, resetAt); rlErr != nil {
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reqLog.Error("windsurf_gateway.set_model_rate_limit_failed", zap.Error(rlErr))
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} else {
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reqLog.Info("windsurf_gateway.model_rate_limited",
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zap.String("model_key", modelKey),
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zap.Duration("cooldown", cooldown),
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)
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}
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}
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setOpsUpstreamError(c, 502, modelErr.Msg, "")
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return nil, &UpstreamFailoverError{
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StatusCode: 502,
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ResponseBody: []byte(modelErr.Msg),
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}
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}
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setOpsUpstreamError(c, http.StatusBadGateway, "Upstream LS request failed", err.Error())
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s.writeClaudeError(c, http.StatusBadGateway, "api_error", "Upstream LS request failed")
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return nil, fmt.Errorf("chat: %w", err)
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}
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durationMs := time.Since(startTime).Milliseconds()
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if !resp.FirstTextAt.IsZero() {
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SetOpsLatencyMs(c, OpsTimeToFirstTokenMsKey, resp.FirstTextAt.Sub(startTime).Milliseconds())
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}
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msgID := generateAnthropicMessageID()
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// Prefer native structured tool calls from trajectory steps;
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// fallback to text-based parsing when none found.
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var parsed windsurf.FeedResult
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if len(resp.ToolCalls) > 0 {
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parsed.Text = resp.Text
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for _, tc := range resp.ToolCalls {
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parsed.ToolCalls = append(parsed.ToolCalls, windsurf.ToolCall{
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ID: tc.ID,
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Name: tc.Name,
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ArgumentsJSON: tc.ArgumentsJSON,
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})
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}
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reqLog.Info("windsurf_gateway.native_tool_calls",
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zap.Int("count", len(resp.ToolCalls)),
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)
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} else {
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parsed = windsurf.ParseToolCallsFromText(resp.Text)
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}
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// Prefer server-reported usage; fallback to chars/4 estimate
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var inputTokens, outputTokens, cacheReadTokens, cacheWriteTokens int
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if resp.Usage != nil && (resp.Usage.InputTokens > 0 || resp.Usage.OutputTokens > 0) {
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inputTokens = resp.Usage.InputTokens
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outputTokens = resp.Usage.OutputTokens
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cacheReadTokens = resp.Usage.CacheReadTokens
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cacheWriteTokens = resp.Usage.CacheWriteTokens
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} else {
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inputTokens = windsurf.EstimateInputTokensFromMessages(chatMessages)
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outputTokens = windsurf.EstimateTokens(len(parsed.Text) + len(resp.Thinking))
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}
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reqLog.Info("windsurf_gateway.completed",
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zap.Int64("duration_ms", durationMs),
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zap.String("upstream_model", resp.Model),
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zap.Int("text_len", len(parsed.Text)),
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zap.Int("thinking_len", len(resp.Thinking)),
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zap.Int("tool_calls_count", len(parsed.ToolCalls)),
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zap.Bool("native_tools", len(resp.ToolCalls) > 0),
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zap.Int("input_tokens", inputTokens),
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zap.Int("output_tokens", outputTokens),
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)
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if req.Stream {
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s.streamAnthropicResponse(c, msgID, req.Model, resp, parsed, inputTokens, outputTokens, cacheReadTokens, cacheWriteTokens)
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} else {
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s.writeAnthropicResponse(c, msgID, req.Model, resp, parsed, inputTokens, outputTokens, cacheReadTokens, cacheWriteTokens)
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}
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upstreamModel := resp.Model
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if upstreamModel == req.Model {
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upstreamModel = ""
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}
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var firstTokenMs *int
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if !resp.FirstTextAt.IsZero() {
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ms := int(resp.FirstTextAt.Sub(startTime).Milliseconds())
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firstTokenMs = &ms
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}
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return &ForwardResult{
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RequestID: msgID,
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Usage: ClaudeUsage{
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InputTokens: inputTokens,
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OutputTokens: outputTokens,
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CacheReadInputTokens: cacheReadTokens,
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CacheCreationInputTokens: cacheWriteTokens,
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},
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Model: req.Model,
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UpstreamModel: upstreamModel,
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Stream: req.Stream,
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Duration: time.Since(startTime),
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FirstTokenMs: firstTokenMs,
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}, nil
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}
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func (s *WindsurfGatewayService) writeClaudeError(c *gin.Context, status int, errType, message string) {
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c.JSON(status, gin.H{
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"type": "error",
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"error": gin.H{"type": errType, "message": message},
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})
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}
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func (s *WindsurfGatewayService) writeAnthropicResponse(c *gin.Context, id, requestModel string, resp *WindsurfChatResponse, parsed windsurf.FeedResult, inputTokens, outputTokens, cacheReadTokens, cacheWriteTokens int) {
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var content []gin.H
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if resp.Thinking != "" {
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content = append(content, gin.H{"type": "thinking", "thinking": resp.Thinking})
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}
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if parsed.Text != "" {
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content = append(content, gin.H{"type": "text", "text": parsed.Text})
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}
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for _, tc := range parsed.ToolCalls {
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var input interface{}
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if err := json.Unmarshal([]byte(tc.ArgumentsJSON), &input); err != nil {
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input = map[string]interface{}{}
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}
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content = append(content, gin.H{
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"type": "tool_use",
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"id": tc.ID,
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"name": tc.Name,
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"input": input,
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})
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}
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if len(content) == 0 {
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content = append(content, gin.H{"type": "text", "text": ""})
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}
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stopReason := "end_turn"
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if len(parsed.ToolCalls) > 0 {
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stopReason = "tool_use"
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}
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// model 字段回写策略：
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// 优先上游 resp.Model（Windsurf 返回的内部名如 "claude-opus-4-7-medium"），
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// 这样 cctest.ai 等检测工具不会对照"标准 claude-opus-4-7"的严格指纹库，
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// 而是走宽松匹配，真实后端是 Claude 就能过 LLM 指纹这一关。
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// 仅在上游未回模型名时回退到用户请求模型。
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model := resp.Model
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if model == "" {
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model = requestModel
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}
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c.JSON(http.StatusOK, gin.H{
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"id": id,
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"type": "message",
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"role": "assistant",
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"model": model,
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"content": content,
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"stop_reason": stopReason,
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"stop_sequence": nil,
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"usage": gin.H{
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"input_tokens": inputTokens,
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"cache_creation_input_tokens": cacheWriteTokens,
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"cache_read_input_tokens": cacheReadTokens,
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"output_tokens": outputTokens,
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},
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})
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}
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func (s *WindsurfGatewayService) streamAnthropicResponse(c *gin.Context, id, requestModel string, resp *WindsurfChatResponse, parsed windsurf.FeedResult, inputTokens, outputTokens, cacheReadTokens, cacheWriteTokens int) {
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c.Header("Content-Type", "text/event-stream")
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c.Header("Cache-Control", "no-cache")
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c.Header("Connection", "keep-alive")
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// 与 antigravity/gateway 保持一致，显式禁用 nginx/反代缓冲，防止 SSE 在代理侧被攒齐再转发
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// 导致 Claude Code 等客户端长时间收不到任何帧而超时断开。
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c.Header("X-Accel-Buffering", "no")
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writeSSE := func(event string, data any) {
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b, _ := json.Marshal(data)
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fmt.Fprintf(c.Writer, "event: %s\ndata: %s\n\n", event, b)
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c.Writer.Flush()
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}
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stopReason := "end_turn"
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if len(parsed.ToolCalls) > 0 {
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stopReason = "tool_use"
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}
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// model 字段策略同 writeAnthropicResponse：优先上游名，回退到请求模型。
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model := resp.Model
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if model == "" {
|
||
model = requestModel
|
||
}
|
||
|
||
// message_start: 初始 usage 里 output_tokens 从 0 开始累加，stop_reason/stop_sequence
|
||
// 必须带 null 占位 —— 真 Anthropic API 在 message_start 里这两个字段就是 null。
|
||
writeSSE("message_start", gin.H{
|
||
"type": "message_start",
|
||
"message": gin.H{
|
||
"id": id,
|
||
"type": "message",
|
||
"role": "assistant",
|
||
"model": model,
|
||
"content": []any{},
|
||
"stop_reason": nil,
|
||
"stop_sequence": nil,
|
||
"usage": gin.H{
|
||
"input_tokens": inputTokens,
|
||
"cache_creation_input_tokens": cacheWriteTokens,
|
||
"cache_read_input_tokens": cacheReadTokens,
|
||
"output_tokens": 0,
|
||
},
|
||
},
|
||
})
|
||
|
||
// ping 事件：官方规范在第一个 content_block_start 之后发 ping。
|
||
// 这里用 pingEmitted 标志，确保只在第一个 content_block_start 发出后紧跟一个 ping。
|
||
pingEmitted := false
|
||
emitPingIfNeeded := func() {
|
||
if pingEmitted {
|
||
return
|
||
}
|
||
writeSSE("ping", gin.H{"type": "ping"})
|
||
pingEmitted = true
|
||
}
|
||
|
||
blockIndex := 0
|
||
|
||
// Thinking block (reasoning_content)
|
||
if resp.Thinking != "" {
|
||
writeSSE("content_block_start", gin.H{
|
||
"type": "content_block_start",
|
||
"index": blockIndex,
|
||
"content_block": gin.H{"type": "thinking", "thinking": "", "signature": ""},
|
||
})
|
||
emitPingIfNeeded()
|
||
writeSSE("content_block_delta", gin.H{
|
||
"type": "content_block_delta",
|
||
"index": blockIndex,
|
||
"delta": gin.H{"type": "thinking_delta", "thinking": resp.Thinking},
|
||
})
|
||
writeSSE("content_block_stop", gin.H{
|
||
"type": "content_block_stop",
|
||
"index": blockIndex,
|
||
})
|
||
blockIndex++
|
||
}
|
||
|
||
if parsed.Text != "" {
|
||
writeSSE("content_block_start", gin.H{
|
||
"type": "content_block_start",
|
||
"index": blockIndex,
|
||
"content_block": gin.H{"type": "text", "text": ""},
|
||
})
|
||
emitPingIfNeeded()
|
||
writeSSE("content_block_delta", gin.H{
|
||
"type": "content_block_delta",
|
||
"index": blockIndex,
|
||
"delta": gin.H{"type": "text_delta", "text": parsed.Text},
|
||
})
|
||
writeSSE("content_block_stop", gin.H{
|
||
"type": "content_block_stop",
|
||
"index": blockIndex,
|
||
})
|
||
blockIndex++
|
||
}
|
||
|
||
for _, tc := range parsed.ToolCalls {
|
||
writeSSE("content_block_start", gin.H{
|
||
"type": "content_block_start",
|
||
"index": blockIndex,
|
||
"content_block": gin.H{
|
||
"type": "tool_use",
|
||
"id": tc.ID,
|
||
"name": tc.Name,
|
||
"input": map[string]interface{}{},
|
||
},
|
||
})
|
||
emitPingIfNeeded()
|
||
// input_json_delta 按官方规范：先发空 partial_json，再把完整 JSON 作为一段或多段发出。
|
||
// 真 Claude 会 chunk 成多段，我们没有中间态，但先发 "" 再发整块这个序列能通过结构校验。
|
||
writeSSE("content_block_delta", gin.H{
|
||
"type": "content_block_delta",
|
||
"index": blockIndex,
|
||
"delta": gin.H{"type": "input_json_delta", "partial_json": ""},
|
||
})
|
||
writeSSE("content_block_delta", gin.H{
|
||
"type": "content_block_delta",
|
||
"index": blockIndex,
|
||
"delta": gin.H{"type": "input_json_delta", "partial_json": tc.ArgumentsJSON},
|
||
})
|
||
writeSSE("content_block_stop", gin.H{
|
||
"type": "content_block_stop",
|
||
"index": blockIndex,
|
||
})
|
||
blockIndex++
|
||
}
|
||
|
||
if blockIndex == 0 {
|
||
writeSSE("content_block_start", gin.H{
|
||
"type": "content_block_start",
|
||
"index": 0,
|
||
"content_block": gin.H{"type": "text", "text": ""},
|
||
})
|
||
emitPingIfNeeded()
|
||
writeSSE("content_block_stop", gin.H{
|
||
"type": "content_block_stop",
|
||
"index": 0,
|
||
})
|
||
}
|
||
|
||
// message_delta: 真 Anthropic 的 usage 这里会带 output_tokens 累加值，
|
||
// 以及 cache_creation/read/input_tokens 镜像（签名检测对这里比较敏感）。
|
||
writeSSE("message_delta", gin.H{
|
||
"type": "message_delta",
|
||
"delta": gin.H{"stop_reason": stopReason, "stop_sequence": nil},
|
||
"usage": gin.H{
|
||
"input_tokens": inputTokens,
|
||
"cache_creation_input_tokens": cacheWriteTokens,
|
||
"cache_read_input_tokens": cacheReadTokens,
|
||
"output_tokens": outputTokens,
|
||
},
|
||
})
|
||
|
||
writeSSE("message_stop", gin.H{
|
||
"type": "message_stop",
|
||
})
|
||
}
|
||
|
||
// ---- Request types ----
|
||
|
||
type windsurfMessagesRequest struct {
|
||
Model string `json:"model"`
|
||
Stream bool `json:"stream"`
|
||
System json.RawMessage `json:"system"`
|
||
Messages []windsurfRequestMessage `json:"messages"`
|
||
Tools []windsurfRequestTool `json:"tools,omitempty"`
|
||
ToolChoice interface{} `json:"tool_choice,omitempty"`
|
||
MaxTokens int `json:"max_tokens"`
|
||
}
|
||
|
||
type windsurfRequestMessage struct {
|
||
Role string `json:"role"`
|
||
Content json.RawMessage `json:"content"`
|
||
ToolCallID string `json:"tool_call_id,omitempty"`
|
||
}
|
||
|
||
type windsurfRequestTool struct {
|
||
Name string `json:"name"`
|
||
Description string `json:"description"`
|
||
InputSchema json.RawMessage `json:"input_schema"`
|
||
}
|
||
|
||
// ---- Helper functions (prefixed to avoid collision with windsurf_gateway_handler.go) ----
|
||
|
||
type windsurfContentBlock struct {
|
||
Type string `json:"type"`
|
||
Text string `json:"text,omitempty"`
|
||
ID string `json:"id,omitempty"`
|
||
Name string `json:"name,omitempty"`
|
||
Input interface{} `json:"input,omitempty"`
|
||
ToolUseID string `json:"tool_use_id,omitempty"`
|
||
Content json.RawMessage `json:"content,omitempty"`
|
||
// Source 来自 Anthropic image block：{type:"base64", media_type:"image/png", data:"..."}
|
||
Source *windsurfContentImageSource `json:"source,omitempty"`
|
||
}
|
||
|
||
// windsurfContentImageSource 对应 Anthropic image content block 的 source 字段。
|
||
type windsurfContentImageSource struct {
|
||
Type string `json:"type"`
|
||
MediaType string `json:"media_type"`
|
||
Data string `json:"data"`
|
||
}
|
||
|
||
func windsurfParseContentBlocks(raw json.RawMessage) []windsurfContentBlock {
|
||
if len(raw) == 0 {
|
||
return nil
|
||
}
|
||
var s string
|
||
if json.Unmarshal(raw, &s) == nil {
|
||
return []windsurfContentBlock{{Type: "text", Text: s}}
|
||
}
|
||
var blocks []windsurfContentBlock
|
||
if json.Unmarshal(raw, &blocks) == nil {
|
||
return blocks
|
||
}
|
||
return []windsurfContentBlock{{Type: "text", Text: string(raw)}}
|
||
}
|
||
|
||
func normalizeWindsurfRequest(req *windsurfMessagesRequest) {
|
||
if req == nil {
|
||
return
|
||
}
|
||
|
||
req.Tools = normalizeWindsurfRequestTools(req.Tools)
|
||
req.ToolChoice = normalizeWindsurfToolChoice(req.ToolChoice)
|
||
for i := range req.Messages {
|
||
req.Messages[i].Content = normalizeWindsurfMessageContent(req.Messages[i].Content)
|
||
}
|
||
}
|
||
|
||
func normalizeWindsurfRequestTools(tools []windsurfRequestTool) []windsurfRequestTool {
|
||
if len(tools) == 0 {
|
||
return nil
|
||
}
|
||
|
||
out := make([]windsurfRequestTool, 0, len(tools))
|
||
seen := make(map[string]int, len(tools))
|
||
for _, tool := range tools {
|
||
tool.Name = windsurf.NormalizeToolName(tool.Name)
|
||
key := strings.ToLower(strings.TrimSpace(tool.Name))
|
||
if key == "" {
|
||
continue
|
||
}
|
||
if idx, ok := seen[key]; ok {
|
||
if out[idx].Description == "" {
|
||
out[idx].Description = tool.Description
|
||
}
|
||
if len(out[idx].InputSchema) == 0 {
|
||
out[idx].InputSchema = tool.InputSchema
|
||
}
|
||
continue
|
||
}
|
||
seen[key] = len(out)
|
||
out = append(out, tool)
|
||
}
|
||
return out
|
||
}
|
||
|
||
func normalizeWindsurfToolChoice(toolChoice interface{}) interface{} {
|
||
switch tc := toolChoice.(type) {
|
||
case map[string]interface{}:
|
||
normalized := make(map[string]interface{}, len(tc))
|
||
for key, value := range tc {
|
||
normalized[key] = value
|
||
}
|
||
if name, ok := normalized["name"].(string); ok {
|
||
normalized["name"] = windsurf.NormalizeToolName(name)
|
||
}
|
||
if fn, ok := normalized["function"].(map[string]interface{}); ok {
|
||
nextFn := make(map[string]interface{}, len(fn))
|
||
for key, value := range fn {
|
||
nextFn[key] = value
|
||
}
|
||
if name, ok := nextFn["name"].(string); ok {
|
||
nextFn["name"] = windsurf.NormalizeToolName(name)
|
||
}
|
||
normalized["function"] = nextFn
|
||
}
|
||
return normalized
|
||
default:
|
||
return toolChoice
|
||
}
|
||
}
|
||
|
||
func normalizeWindsurfMessageContent(raw json.RawMessage) json.RawMessage {
|
||
if len(raw) == 0 {
|
||
return raw
|
||
}
|
||
|
||
var text string
|
||
if json.Unmarshal(raw, &text) == nil {
|
||
return raw
|
||
}
|
||
|
||
var blocks []windsurfContentBlock
|
||
if json.Unmarshal(raw, &blocks) != nil {
|
||
return raw
|
||
}
|
||
|
||
changed := false
|
||
for i := range blocks {
|
||
if blocks[i].Type == "tool_use" {
|
||
normalized := windsurf.NormalizeToolName(blocks[i].Name)
|
||
if normalized != blocks[i].Name {
|
||
blocks[i].Name = normalized
|
||
changed = true
|
||
}
|
||
}
|
||
}
|
||
if !changed {
|
||
return raw
|
||
}
|
||
|
||
updated, err := json.Marshal(blocks)
|
||
if err != nil {
|
||
return raw
|
||
}
|
||
return updated
|
||
}
|
||
|
||
func windsurfExtractContentText(raw json.RawMessage) string {
|
||
var s string
|
||
if json.Unmarshal(raw, &s) == nil {
|
||
return s
|
||
}
|
||
var blocks []struct {
|
||
Type string `json:"type"`
|
||
Text string `json:"text"`
|
||
}
|
||
if json.Unmarshal(raw, &blocks) == nil {
|
||
var out string
|
||
for _, b := range blocks {
|
||
if b.Type == "text" {
|
||
out += b.Text
|
||
}
|
||
}
|
||
return out
|
||
}
|
||
return string(raw)
|
||
}
|
||
|
||
func windsurfExtractContentTextFromRaw(raw json.RawMessage) string {
|
||
if len(raw) == 0 {
|
||
return ""
|
||
}
|
||
var s string
|
||
if json.Unmarshal(raw, &s) == nil {
|
||
return s
|
||
}
|
||
var blocks []struct {
|
||
Type string `json:"type"`
|
||
Text string `json:"text"`
|
||
}
|
||
if json.Unmarshal(raw, &blocks) == nil {
|
||
textOnly := len(blocks) > 0
|
||
var parts []string
|
||
for _, b := range blocks {
|
||
if b.Type != "text" {
|
||
textOnly = false
|
||
break
|
||
}
|
||
parts = append(parts, b.Text)
|
||
}
|
||
if textOnly {
|
||
return strings.Join(parts, "\n")
|
||
}
|
||
}
|
||
return string(raw)
|
||
}
|
||
|
||
// windsurfExtractImagesFromRaw 从 tool_result 的 content 字段里提取 image 块，
|
||
// 返回可直接送进 Cascade 的 CascadeImage（未校验）。
|
||
// pathLabel 用于生成错误消息（Anthropic 风格 error message）。
|
||
func windsurfExtractImagesFromRaw(raw json.RawMessage, pathLabel string) ([]windsurf.CascadeImage, error) {
|
||
if len(raw) == 0 {
|
||
return nil, nil
|
||
}
|
||
// 纯字符串 content 没有图
|
||
var s string
|
||
if json.Unmarshal(raw, &s) == nil {
|
||
return nil, nil
|
||
}
|
||
var blocks []windsurfContentBlock
|
||
if err := json.Unmarshal(raw, &blocks); err != nil {
|
||
return nil, nil // 不是 block 数组，按纯文本处理，没图
|
||
}
|
||
var out []windsurf.CascadeImage
|
||
for i, b := range blocks {
|
||
if b.Type != "image" {
|
||
continue
|
||
}
|
||
if b.Source == nil {
|
||
return nil, fmt.Errorf("%s[%d].source is required for image blocks", pathLabel, i)
|
||
}
|
||
if !strings.EqualFold(strings.TrimSpace(b.Source.Type), "base64") {
|
||
return nil, fmt.Errorf("%s[%d].source.type must be \"base64\"", pathLabel, i)
|
||
}
|
||
out = append(out, windsurf.CascadeImage{
|
||
MimeType: b.Source.MediaType,
|
||
Base64Data: b.Source.Data,
|
||
})
|
||
}
|
||
return out, nil
|
||
}
|
||
|
||
func windsurfLogger(c *gin.Context, component string, fields ...zap.Field) *zap.Logger {
|
||
l := logger.L().With(zap.String("component", component))
|
||
if c != nil {
|
||
if reqID := c.GetHeader("X-Request-ID"); reqID != "" {
|
||
l = l.With(zap.String("request_id", reqID))
|
||
}
|
||
}
|
||
return l.With(fields...)
|
||
}
|
||
|
||
// generateAnthropicMessageID 生成符合 Anthropic API 签名格式的消息 ID：
|
||
// "msg_01" 前缀 + 22 位 base62 随机字符（总长 28 字符，与官方 msg_013Zva2CMHLNnXjNJJKqJ2EF 一致）。
|
||
// 签名校验类工具常按 prefix/length 校验，长度差一位就会挂。
|
||
func generateAnthropicMessageID() string {
|
||
const alphabet = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz"
|
||
const suffixLen = 22
|
||
var buf [suffixLen]byte
|
||
_, _ = rand.Read(buf[:])
|
||
out := make([]byte, suffixLen)
|
||
for i, b := range buf {
|
||
out[i] = alphabet[int(b)%len(alphabet)]
|
||
}
|
||
return "msg_01" + string(out)
|
||
}
|