feat: publish sanitized custom.97 source

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cneicy committed 2026-10-27 20:43:39 +08:00
1 parent 8e6ed0317b
commit 86c0276156
1022 files changed
+69903 -19207

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+23 -169
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@@ -15,6 +15,7 @@ import (
constant2 "github.com/QuantumNous/new-api/relay/constant"
"github.com/QuantumNous/new-api/relaykit/dto"
"github.com/QuantumNous/new-api/relaykit/types"
"github.com/QuantumNous/new-api/tokenkit"
"github.com/gin-gonic/gin"
)
@@ -24,153 +25,24 @@ func getImageToken(c *gin.Context, fileMeta *types.FileMeta, model string, strea
return 0, fmt.Errorf("image_url_is_nil")
}
// Defaults for 4o/4.1/4.5 family unless overridden below
baseTokens := 85
tileTokens := 170
// Model classification
lowerModel := strings.ToLower(model)
// Special cases from existing behavior
if strings.HasPrefix(lowerModel, "glm-4") {
return 1047, nil
img := tokenkit.Image{Detail: fileMeta.Detail}
// Reading the size may download a URL image; operators can turn that off,
// and the estimate then assumes a typical image size.
measure := constant.GetMediaToken && (stream || constant.GetMediaTokenNotStream)
if !measure || !tokenkit.ImageNeedsSize(model, img.Detail) {
return tokenkit.ImageTokens(model, img), nil
}
// Patch-based models (32x32 patches, capped at 1536, with multiplier)
isPatchBased := false
multiplier := 1.0
switch {
case strings.Contains(lowerModel, "gpt-4.1-mini"):
isPatchBased = true
multiplier = 1.62
case strings.Contains(lowerModel, "gpt-4.1-nano"):
isPatchBased = true
multiplier = 2.46
case strings.HasPrefix(lowerModel, "o4-mini"):
isPatchBased = true
multiplier = 1.72
case strings.HasPrefix(lowerModel, "gpt-5-mini"):
isPatchBased = true
multiplier = 1.62
case strings.HasPrefix(lowerModel, "gpt-5-nano"):
isPatchBased = true
multiplier = 2.46
}
// Tile-based model tokens and bases per doc
if !isPatchBased {
if strings.HasPrefix(lowerModel, "gpt-4o-mini") {
baseTokens = 2833
tileTokens = 5667
} else if strings.HasPrefix(lowerModel, "gpt-5-chat-latest") || (strings.HasPrefix(lowerModel, "gpt-5") && !strings.Contains(lowerModel, "mini") && !strings.Contains(lowerModel, "nano")) {
baseTokens = 70
tileTokens = 140
} else if strings.HasPrefix(lowerModel, "o1") || strings.HasPrefix(lowerModel, "o3") || strings.HasPrefix(lowerModel, "o1-pro") {
baseTokens = 75
tileTokens = 150
} else if strings.Contains(lowerModel, "computer-use-preview") {
baseTokens = 65
tileTokens = 129
} else if strings.Contains(lowerModel, "4.1") || strings.Contains(lowerModel, "4o") || strings.Contains(lowerModel, "4.5") {
baseTokens = 85
tileTokens = 170
}
}
// Respect existing feature flags/short-circuits
if fileMeta.Detail == "low" && !isPatchBased {
return baseTokens, nil
}
// Whether to count image tokens at all
if !constant.GetMediaToken {
return 3 * baseTokens, nil
}
if !constant.GetMediaTokenNotStream && !stream {
return 3 * baseTokens, nil
}
// Normalize detail
if fileMeta.Detail == "auto" || fileMeta.Detail == "" {
fileMeta.Detail = "high"
}
// 使用统一的文件服务获取图片配置
config, format, err := GetImageConfig(c, fileMeta.Source)
if err != nil {
return 0, err
}
if config.Width == 0 || config.Height == 0 {
// not an image, but might be a valid file
if format != "" {
// file type
return 3 * baseTokens, nil
}
return 0, errors.New(fmt.Sprintf("fail to decode image config: %s", fileMeta.GetIdentifier()))
if (config.Width == 0 || config.Height == 0) && format == "" {
return 0, fmt.Errorf("fail to decode image config: %s", fileMeta.GetIdentifier())
}
width := config.Width
height := config.Height
logger.LogDebug(c, "image token input: format=%s, width=%d, height=%d", format, width, height)
if isPatchBased {
// 32x32 patch-based calculation with 1536 cap and model multiplier
ceilDiv := func(a, b int) int { return (a + b - 1) / b }
rawPatchesW := ceilDiv(width, 32)
rawPatchesH := ceilDiv(height, 32)
rawPatches := rawPatchesW * rawPatchesH
if rawPatches > 1536 {
// scale down
area := float64(width * height)
r := math.Sqrt(float64(32*32*1536) / area)
wScaled := float64(width) * r
hScaled := float64(height) * r
// adjust to fit whole number of patches after scaling
adjW := math.Floor(wScaled/32.0) / (wScaled / 32.0)
adjH := math.Floor(hScaled/32.0) / (hScaled / 32.0)
adj := math.Min(adjW, adjH)
if !math.IsNaN(adj) && adj > 0 {
r = r * adj
}
wScaled = float64(width) * r
hScaled = float64(height) * r
patchesW := math.Ceil(wScaled / 32.0)
patchesH := math.Ceil(hScaled / 32.0)
imageTokens := min(int(patchesW*patchesH), 1536)
return common.QuotaRound(float64(imageTokens) * multiplier), nil
}
// below cap
imageTokens := rawPatches
return common.QuotaRound(float64(imageTokens) * multiplier), nil
}
// Tile-based calculation for 4o/4.1/4.5/o1/o3/etc.
// Step 1: fit within 2048x2048 square
maxSide := math.Max(float64(width), float64(height))
fitScale := 1.0
if maxSide > 2048 {
fitScale = maxSide / 2048.0
}
fitW := int(math.Round(float64(width) / fitScale))
fitH := int(math.Round(float64(height) / fitScale))
// Step 2: scale so that shortest side is exactly 768
minSide := math.Min(float64(fitW), float64(fitH))
if minSide == 0 {
return baseTokens, nil
}
shortScale := 768.0 / minSide
finalW := int(math.Round(float64(fitW) * shortScale))
finalH := int(math.Round(float64(fitH) * shortScale))
// Count 512px tiles
tilesW := (finalW + 512 - 1) / 512
tilesH := (finalH + 512 - 1) / 512
tiles := tilesW * tilesH
logger.LogDebug(c, "image token scaled size: width=%d, height=%d, tiles=%d", finalW, finalH, tiles)
return tiles*tileTokens + baseTokens, nil
img.Width, img.Height = config.Width, config.Height
logger.LogDebug(c, "image token input: format=%s, width=%d, height=%d", format, img.Width, img.Height)
return tokenkit.ImageTokens(model, img), nil
}
func EstimateRequestToken(c *gin.Context, meta *types.TokenCountMeta, info *relaycommon.RelayInfo) (int, error) {
@@ -228,7 +100,7 @@ func CountRequestToken(c *gin.Context, meta *types.TokenCountMeta, info *relayco
if meta.TokenType == types.TokenTypeTextNumber {
tkm += utf8.RuneCountInString(meta.CombineText)
} else {
tkm += CountTextToken(meta.CombineText, model)
tkm += tokenkit.Count(model, meta.CombineText)
}
if info.RelayFormat == types.RelayFormatOpenAI {
@@ -279,15 +151,11 @@ func CountRequestToken(c *gin.Context, meta *types.TokenCountMeta, info *relayco
for i, file := range meta.Files {
switch file.FileType {
case types.FileTypeImage:
if common.IsOpenAITextModel(model) {
token, err := getImageToken(c, file, model, info.IsStream)
if err != nil {
return 0, fmt.Errorf("error counting image token, media index[%d], identifier[%s], err: %v", i, file.GetIdentifier(), err)
}
tkm += token
} else {
tkm += 520
token, err := getImageToken(c, file, model, info.IsStream)
if err != nil {
return 0, fmt.Errorf("error counting image token, media index[%d], identifier[%s], err: %v", i, file.GetIdentifier(), err)
}
tkm += token
case types.FileTypeAudio:
tkm += 256
case types.FileTypeVideo:
@@ -309,7 +177,7 @@ func CountTokenRealtime(info *relaycommon.RelayInfo, request dto.RealtimeEvent,
switch request.Type {
case dto.RealtimeEventTypeSessionUpdate:
if request.Session != nil {
msgTokens := CountTextToken(request.Session.Instructions, model)
msgTokens := tokenkit.Count(model, request.Session.Instructions)
textToken += msgTokens
}
case dto.RealtimeEventResponseAudioDelta:
@@ -321,7 +189,7 @@ func CountTokenRealtime(info *relaycommon.RelayInfo, request dto.RealtimeEvent,
audioToken += atk
case dto.RealtimeEventResponseAudioTranscriptionDelta, dto.RealtimeEventResponseFunctionCallArgumentsDelta:
// count text token
tkm := CountTextToken(request.Delta, model)
tkm := tokenkit.Count(model, request.Delta)
textToken += tkm
case dto.RealtimeEventInputAudioBufferAppend:
// count audio token
@@ -336,7 +204,7 @@ func CountTokenRealtime(info *relaycommon.RelayInfo, request dto.RealtimeEvent,
case "message":
for _, content := range request.Item.Content {
if content.Type == "input_text" {
tokens := CountTextToken(content.Text, model)
tokens := tokenkit.Count(model, content.Text)
textToken += tokens
}
}
@@ -360,19 +228,19 @@ func CountTokenRealtime(info *relaycommon.RelayInfo, request dto.RealtimeEvent,
func CountTokenInput(input any, model string) int {
switch v := input.(type) {
case string:
return CountTextToken(v, model)
return tokenkit.Count(model, v)
case []string:
var text strings.Builder
for _, s := range v {
text.WriteString(s)
}
return CountTextToken(text.String(), model)
return tokenkit.Count(model, text.String())
case []any:
var text strings.Builder
for _, item := range v {
text.WriteString(fmt.Sprintf("%v", item))
}
return CountTextToken(text.String(), model)
return tokenkit.Count(model, text.String())
}
return CountTokenInput(fmt.Sprintf("%v", input), model)
}
@@ -400,17 +268,3 @@ func CountAudioTokenOutput(audioBase64 string, audioFormat string) (int, error)
// duration 来自上游返回的音频元数据,饱和转换防止 int 回绕
return common.QuotaFromFloat(duration / 60 * 200 / 0.24), nil
}
// CountTextToken 统计文本的token数量,仅OpenAI模型使用tokenizer,其余模型使用估算
func CountTextToken(text string, model string) int {
if text == "" {
return 0
}
if common.IsOpenAITextModel(model) {
tokenEncoder := getTokenEncoder(model)
return getTokenNum(tokenEncoder, text)
} else {
// 非openai模型,使用tiktoken-go计算没有意义,使用估算节省资源
return EstimateTokenByModel(model, text)
}
}