mirror of
https://github.com/linux-do/new-api.git
synced 2025-09-17 16:06:38 +08:00
275 lines
8.1 KiB
Go
275 lines
8.1 KiB
Go
package service
|
||
|
||
import (
|
||
"encoding/json"
|
||
"errors"
|
||
"fmt"
|
||
"github.com/pkoukk/tiktoken-go"
|
||
"image"
|
||
"log"
|
||
"math"
|
||
"one-api/common"
|
||
"one-api/dto"
|
||
"strings"
|
||
"unicode/utf8"
|
||
)
|
||
|
||
// tokenEncoderMap won't grow after initialization
|
||
var tokenEncoderMap = map[string]*tiktoken.Tiktoken{}
|
||
var defaultTokenEncoder *tiktoken.Tiktoken
|
||
|
||
func InitTokenEncoders() {
|
||
common.SysLog("initializing token encoders")
|
||
gpt35TokenEncoder, err := tiktoken.EncodingForModel("gpt-3.5-turbo")
|
||
if err != nil {
|
||
common.FatalLog(fmt.Sprintf("failed to get gpt-3.5-turbo token encoder: %s", err.Error()))
|
||
}
|
||
defaultTokenEncoder = gpt35TokenEncoder
|
||
gpt4TokenEncoder, err := tiktoken.EncodingForModel("gpt-4")
|
||
if err != nil {
|
||
common.FatalLog(fmt.Sprintf("failed to get gpt-4 token encoder: %s", err.Error()))
|
||
}
|
||
for model, _ := range common.DefaultModelRatio {
|
||
if strings.HasPrefix(model, "gpt-3.5") {
|
||
tokenEncoderMap[model] = gpt35TokenEncoder
|
||
} else if strings.HasPrefix(model, "gpt-4") {
|
||
tokenEncoderMap[model] = gpt4TokenEncoder
|
||
} else {
|
||
tokenEncoderMap[model] = nil
|
||
}
|
||
}
|
||
common.SysLog("token encoders initialized")
|
||
}
|
||
|
||
func getTokenEncoder(model string) *tiktoken.Tiktoken {
|
||
tokenEncoder, ok := tokenEncoderMap[model]
|
||
if ok && tokenEncoder != nil {
|
||
return tokenEncoder
|
||
}
|
||
if ok {
|
||
tokenEncoder, err := tiktoken.EncodingForModel(model)
|
||
if err != nil {
|
||
common.SysError(fmt.Sprintf("failed to get token encoder for model %s: %s, using encoder for gpt-3.5-turbo", model, err.Error()))
|
||
tokenEncoder = defaultTokenEncoder
|
||
}
|
||
tokenEncoderMap[model] = tokenEncoder
|
||
return tokenEncoder
|
||
}
|
||
return defaultTokenEncoder
|
||
}
|
||
|
||
func getTokenNum(tokenEncoder *tiktoken.Tiktoken, text string) int {
|
||
return len(tokenEncoder.Encode(text, nil, nil))
|
||
}
|
||
|
||
func getImageToken(imageUrl *dto.MessageImageUrl) (int, error) {
|
||
if imageUrl.Detail == "low" {
|
||
return 85, nil
|
||
}
|
||
var config image.Config
|
||
var err error
|
||
var format string
|
||
if strings.HasPrefix(imageUrl.Url, "http") {
|
||
common.SysLog(fmt.Sprintf("downloading image: %s", imageUrl.Url))
|
||
config, format, err = common.DecodeUrlImageData(imageUrl.Url)
|
||
} else {
|
||
common.SysLog(fmt.Sprintf("decoding image"))
|
||
config, format, _, err = common.DecodeBase64ImageData(imageUrl.Url)
|
||
}
|
||
if err != nil {
|
||
return 0, err
|
||
}
|
||
|
||
if config.Width == 0 || config.Height == 0 {
|
||
return 0, errors.New(fmt.Sprintf("fail to decode image config: %s", imageUrl.Url))
|
||
}
|
||
// TODO: 适配官方auto计费
|
||
if config.Width < 512 && config.Height < 512 {
|
||
if imageUrl.Detail == "auto" || imageUrl.Detail == "" {
|
||
// 如果图片尺寸小于512，强制使用low
|
||
imageUrl.Detail = "low"
|
||
return 85, nil
|
||
}
|
||
}
|
||
|
||
shortSide := config.Width
|
||
otherSide := config.Height
|
||
log.Printf("format: %s, width: %d, height: %d", format, config.Width, config.Height)
|
||
// 缩放倍数
|
||
scale := 1.0
|
||
if config.Height < shortSide {
|
||
shortSide = config.Height
|
||
otherSide = config.Width
|
||
}
|
||
|
||
// 将最小变的尺寸缩小到768以下，如果大于768，则缩放到768
|
||
if shortSide > 768 {
|
||
scale = float64(shortSide) / 768
|
||
shortSide = 768
|
||
}
|
||
// 将另一边按照相同的比例缩小，向上取整
|
||
otherSide = int(math.Ceil(float64(otherSide) / scale))
|
||
log.Printf("shortSide: %d, otherSide: %d, scale: %f", shortSide, otherSide, scale)
|
||
// 计算图片的token数量(边的长度除以512，向上取整)
|
||
tiles := (shortSide + 511) / 512 * ((otherSide + 511) / 512)
|
||
log.Printf("tiles: %d", tiles)
|
||
return tiles*170 + 85, nil
|
||
}
|
||
|
||
func CountTokenChatRequest(request dto.GeneralOpenAIRequest, model string, checkSensitive bool) (int, error, bool) {
|
||
tkm := 0
|
||
msgTokens, err, b := CountTokenMessages(request.Messages, model, checkSensitive)
|
||
if err != nil {
|
||
return 0, err, b
|
||
}
|
||
tkm += msgTokens
|
||
if request.Tools != nil {
|
||
toolsData, _ := json.Marshal(request.Tools)
|
||
var openaiTools []dto.OpenAITools
|
||
err := json.Unmarshal(toolsData, &openaiTools)
|
||
if err != nil {
|
||
return 0, errors.New(fmt.Sprintf("count_tools_token_fail: %s", err.Error())), false
|
||
}
|
||
countStr := ""
|
||
for _, tool := range openaiTools {
|
||
countStr = tool.Function.Name
|
||
if tool.Function.Description != "" {
|
||
countStr += tool.Function.Description
|
||
}
|
||
if tool.Function.Parameters != nil {
|
||
countStr += fmt.Sprintf("%v", tool.Function.Parameters)
|
||
}
|
||
}
|
||
toolTokens, err, _ := CountTokenInput(countStr, model, false)
|
||
if err != nil {
|
||
return 0, err, false
|
||
}
|
||
tkm += 8
|
||
tkm += toolTokens
|
||
}
|
||
|
||
return tkm, nil, false
|
||
}
|
||
|
||
func CountTokenMessages(messages []dto.Message, model string, checkSensitive bool) (int, error, bool) {
|
||
//recover when panic
|
||
tokenEncoder := getTokenEncoder(model)
|
||
// Reference:
|
||
// https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb
|
||
// https://github.com/pkoukk/tiktoken-go/issues/6
|
||
//
|
||
// Every message follows <|start|>{role/name}\n{content}<|end|>\n
|
||
var tokensPerMessage int
|
||
var tokensPerName int
|
||
if model == "gpt-3.5-turbo-0301" {
|
||
tokensPerMessage = 4
|
||
tokensPerName = -1 // If there's a name, the role is omitted
|
||
} else {
|
||
tokensPerMessage = 3
|
||
tokensPerName = 1
|
||
}
|
||
tokenNum := 0
|
||
for _, message := range messages {
|
||
tokenNum += tokensPerMessage
|
||
tokenNum += getTokenNum(tokenEncoder, message.Role)
|
||
if len(message.Content) > 0 {
|
||
if message.IsStringContent() {
|
||
stringContent := message.StringContent()
|
||
if checkSensitive {
|
||
contains, words := SensitiveWordContains(stringContent)
|
||
if contains {
|
||
err := fmt.Errorf("message contains sensitive words: [%s]", strings.Join(words, ", "))
|
||
return 0, err, true
|
||
}
|
||
}
|
||
tokenNum += getTokenNum(tokenEncoder, stringContent)
|
||
if message.Name != nil {
|
||
tokenNum += tokensPerName
|
||
tokenNum += getTokenNum(tokenEncoder, *message.Name)
|
||
}
|
||
} else {
|
||
var err error
|
||
arrayContent := message.ParseContent()
|
||
for _, m := range arrayContent {
|
||
if m.Type == "image_url" {
|
||
var imageTokenNum int
|
||
if model == "glm-4v" {
|
||
imageTokenNum = 1047
|
||
} else {
|
||
imageUrl := m.ImageUrl.(dto.MessageImageUrl)
|
||
imageTokenNum, err = getImageToken(&imageUrl)
|
||
if err != nil {
|
||
return 0, err, false
|
||
}
|
||
}
|
||
tokenNum += imageTokenNum
|
||
log.Printf("image token num: %d", imageTokenNum)
|
||
} else {
|
||
tokenNum += getTokenNum(tokenEncoder, m.Text)
|
||
}
|
||
}
|
||
}
|
||
}
|
||
}
|
||
tokenNum += 3 // Every reply is primed with <|start|>assistant<|message|>
|
||
return tokenNum, nil, false
|
||
}
|
||
|
||
func CountTokenInput(input any, model string, check bool) (int, error, bool) {
|
||
switch v := input.(type) {
|
||
case string:
|
||
return CountTokenText(v, model, check)
|
||
case []string:
|
||
text := ""
|
||
for _, s := range v {
|
||
text += s
|
||
}
|
||
return CountTokenText(text, model, check)
|
||
}
|
||
return CountTokenInput(fmt.Sprintf("%v", input), model, check)
|
||
}
|
||
|
||
func CountTokenStreamChoices(messages []dto.ChatCompletionsStreamResponseChoice, model string) int {
|
||
tokens := 0
|
||
for _, message := range messages {
|
||
tkm, _, _ := CountTokenInput(message.Delta.Content, model, false)
|
||
tokens += tkm
|
||
if message.Delta.ToolCalls != nil {
|
||
for _, tool := range message.Delta.ToolCalls {
|
||
tkm, _, _ := CountTokenInput(tool.Function.Name, model, false)
|
||
tokens += tkm
|
||
tkm, _, _ = CountTokenInput(tool.Function.Arguments, model, false)
|
||
tokens += tkm
|
||
}
|
||
}
|
||
}
|
||
return tokens
|
||
}
|
||
|
||
func CountAudioToken(text string, model string, check bool) (int, error, bool) {
|
||
if strings.HasPrefix(model, "tts") {
|
||
contains, words := SensitiveWordContains(text)
|
||
if contains {
|
||
return utf8.RuneCountInString(text), fmt.Errorf("input contains sensitive words: [%s]", strings.Join(words, ",")), true
|
||
}
|
||
return utf8.RuneCountInString(text), nil, false
|
||
} else {
|
||
return CountTokenText(text, model, check)
|
||
}
|
||
}
|
||
|
||
// CountTokenText 统计文本的token数量，仅当文本包含敏感词，返回错误，同时返回token数量
|
||
func CountTokenText(text string, model string, check bool) (int, error, bool) {
|
||
var err error
|
||
var trigger bool
|
||
if check {
|
||
contains, words := SensitiveWordContains(text)
|
||
if contains {
|
||
err = fmt.Errorf("input contains sensitive words: [%s]", strings.Join(words, ","))
|
||
trigger = true
|
||
}
|
||
}
|
||
tokenEncoder := getTokenEncoder(model)
|
||
return getTokenNum(tokenEncoder, text), err, trigger
|
||
}
|