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♻️ refactor: Refactor price module (#123) (#109) (#128)

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This commit is contained in:
Buer
2024-03-28 16:53:34 +08:00
committed by GitHub
parent 646cb74154
commit a58e538c26
32 changed files with 2361 additions and 663 deletions
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8
common/config/config.go
View File

@@ -4,13 +4,14 @@ import (
"strings"
"time"
"one-api/cli"
"one-api/common"
"github.com/spf13/viper"
)
func InitConf() {
flagConfig()
cli.FlagConfig()
defaultConfig()
setConfigFile()
setEnv()
@@ -25,11 +26,11 @@ func InitConf() {
}
func setConfigFile() {
if !common.IsFileExist(*config) {
if !common.IsFileExist(*cli.Config) {
return
}
viper.SetConfigFile(*config)
viper.SetConfigFile(*cli.Config)
if err := viper.ReadInConfig(); err != nil {
panic(err)
}
@@ -51,4 +52,5 @@ func defaultConfig() {
viper.SetDefault("global.api_rate_limit", 180)
viper.SetDefault("global.web_rate_limit", 100)
viper.SetDefault("connect_timeout", 5)
viper.SetDefault("auto_price_updates", true)
}

49
common/config/flag.go
View File

@@ -1,49 +0,0 @@
package config
import (
"flag"
"fmt"
"one-api/common"
"os"
"github.com/spf13/viper"
)
var (
port = flag.Int("port", 0, "the listening port")
printVersion = flag.Bool("version", false, "print version and exit")
printHelp = flag.Bool("help", false, "print help and exit")
logDir = flag.String("log-dir", "", "specify the log directory")
config = flag.String("config", "config.yaml", "specify the config.yaml path")
)
func flagConfig() {
flag.Parse()
if *printVersion {
fmt.Println(common.Version)
os.Exit(0)
}
if *printHelp {
help()
os.Exit(0)
}
if *port != 0 {
viper.Set("port", *port)
}
if *logDir != "" {
viper.Set("log_dir", *logDir)
}
}
func help() {
fmt.Println("One API " + common.Version + " - All in one API service for OpenAI API.")
fmt.Println("Copyright (C) 2024 MartialBE. All rights reserved.")
fmt.Println("Original copyright holder: JustSong")
fmt.Println("GitHub: https://github.com/MartialBE/one-api")
fmt.Println("Usage: one-api [--port <port>] [--log-dir <log directory>] [--config <config.yaml path>] [--version] [--help]")
}

313
common/model-ratio.go
View File

@@ -1,217 +1,5 @@
package common
import (
"encoding/json"
"strings"
"time"
)
type ModelType struct {
Ratio []float64
Type int
}
var ModelTypes map[string]ModelType
// ModelRatio
// https://platform.openai.com/docs/models/model-endpoint-compatibility
// https://cloud.baidu.com/doc/WENXINWORKSHOP/s/Blfmc9dlf
// https://openai.com/pricing
// TODO: when a new api is enabled, check the pricing here
// 1 === $0.002 / 1K tokens
// 1 === ￥0.014 / 1k tokens
var ModelRatio map[string][]float64
func init() {
ModelTypes = map[string]ModelType{
// $0.03 / 1K tokens $0.06 / 1K tokens
"gpt-4": {[]float64{15, 30}, ChannelTypeOpenAI},
"gpt-4-0314": {[]float64{15, 30}, ChannelTypeOpenAI},
"gpt-4-0613": {[]float64{15, 30}, ChannelTypeOpenAI},
// $0.06 / 1K tokens $0.12 / 1K tokens
"gpt-4-32k": {[]float64{30, 60}, ChannelTypeOpenAI},
"gpt-4-32k-0314": {[]float64{30, 60}, ChannelTypeOpenAI},
"gpt-4-32k-0613": {[]float64{30, 60}, ChannelTypeOpenAI},
// $0.01 / 1K tokens $0.03 / 1K tokens
"gpt-4-preview": {[]float64{5, 15}, ChannelTypeOpenAI},
"gpt-4-1106-preview": {[]float64{5, 15}, ChannelTypeOpenAI},
"gpt-4-0125-preview": {[]float64{5, 15}, ChannelTypeOpenAI},
"gpt-4-turbo-preview": {[]float64{5, 15}, ChannelTypeOpenAI},
"gpt-4-vision-preview": {[]float64{5, 15}, ChannelTypeOpenAI},
// $0.0005 / 1K tokens $0.0015 / 1K tokens
"gpt-3.5-turbo": {[]float64{0.25, 0.75}, ChannelTypeOpenAI},
"gpt-3.5-turbo-0125": {[]float64{0.25, 0.75}, ChannelTypeOpenAI},
// $0.0015 / 1K tokens $0.002 / 1K tokens
"gpt-3.5-turbo-0301": {[]float64{0.75, 1}, ChannelTypeOpenAI},
"gpt-3.5-turbo-0613": {[]float64{0.75, 1}, ChannelTypeOpenAI},
"gpt-3.5-turbo-instruct": {[]float64{0.75, 1}, ChannelTypeOpenAI},
// $0.003 / 1K tokens $0.004 / 1K tokens
"gpt-3.5-turbo-16k": {[]float64{1.5, 2}, ChannelTypeOpenAI},
"gpt-3.5-turbo-16k-0613": {[]float64{1.5, 2}, ChannelTypeOpenAI},
// $0.001 / 1K tokens $0.002 / 1K tokens
"gpt-3.5-turbo-1106": {[]float64{0.5, 1}, ChannelTypeOpenAI},
// $0.0020 / 1K tokens
"davinci-002": {[]float64{1, 1}, ChannelTypeOpenAI},
// $0.0004 / 1K tokens
"babbage-002": {[]float64{0.2, 0.2}, ChannelTypeOpenAI},
"text-ada-001": {[]float64{0.2, 0.2}, ChannelTypeOpenAI},
"text-babbage-001": {[]float64{0.25, 0.25}, ChannelTypeOpenAI},
"text-curie-001": {[]float64{1, 1}, ChannelTypeOpenAI},
"text-davinci-002": {[]float64{10, 10}, ChannelTypeOpenAI},
"text-davinci-003": {[]float64{10, 10}, ChannelTypeOpenAI},
"text-davinci-edit-001": {[]float64{10, 10}, ChannelTypeOpenAI},
"code-davinci-edit-001": {[]float64{10, 10}, ChannelTypeOpenAI},
// $0.006 / minute -> $0.006 / 150 words -> $0.006 / 200 tokens -> $0.03 / 1k tokens
"whisper-1": {[]float64{15, 15}, ChannelTypeOpenAI},
// $0.015 / 1K characters
"tts-1": {[]float64{7.5, 7.5}, ChannelTypeOpenAI},
"tts-1-1106": {[]float64{7.5, 7.5}, ChannelTypeOpenAI},
// $0.030 / 1K characters
"tts-1-hd": {[]float64{15, 15}, ChannelTypeOpenAI},
"tts-1-hd-1106": {[]float64{15, 15}, ChannelTypeOpenAI},
"davinci": {[]float64{10, 10}, ChannelTypeOpenAI},
"curie": {[]float64{10, 10}, ChannelTypeOpenAI},
"babbage": {[]float64{10, 10}, ChannelTypeOpenAI},
"ada": {[]float64{10, 10}, ChannelTypeOpenAI},
"text-embedding-ada-002": {[]float64{0.05, 0.05}, ChannelTypeOpenAI},
// $0.00002 / 1K tokens
"text-embedding-3-small": {[]float64{0.01, 0.01}, ChannelTypeOpenAI},
// $0.00013 / 1K tokens
"text-embedding-3-large": {[]float64{0.065, 0.065}, ChannelTypeOpenAI},
"text-search-ada-doc-001": {[]float64{10, 10}, ChannelTypeOpenAI},
"text-moderation-stable": {[]float64{0.1, 0.1}, ChannelTypeOpenAI},
"text-moderation-latest": {[]float64{0.1, 0.1}, ChannelTypeOpenAI},
// $0.016 - $0.020 / image
"dall-e-2": {[]float64{8, 8}, ChannelTypeOpenAI},
// $0.040 - $0.120 / image
"dall-e-3": {[]float64{20, 20}, ChannelTypeOpenAI},
// $0.80/million tokens $2.40/million tokens
"claude-instant-1.2": {[]float64{0.4, 1.2}, ChannelTypeAnthropic},
// $8.00/million tokens $24.00/million tokens
"claude-2.0": {[]float64{4, 12}, ChannelTypeAnthropic},
"claude-2.1": {[]float64{4, 12}, ChannelTypeAnthropic},
// $15 / M $75 / M
"claude-3-opus-20240229": {[]float64{7.5, 22.5}, ChannelTypeAnthropic},
// $3 / M $15 / M
"claude-3-sonnet-20240229": {[]float64{1.3, 3.9}, ChannelTypeAnthropic},
// $0.25 / M $1.25 / M 0.00025$ / 1k tokens 0.00125$ / 1k tokens
"claude-3-haiku-20240307": {[]float64{0.125, 0.625}, ChannelTypeAnthropic},
// ￥0.004 / 1k tokens ￥0.008 / 1k tokens
"ERNIE-Speed": {[]float64{0.2857, 0.5714}, ChannelTypeBaidu},
// ￥0.012 / 1k tokens ￥0.012 / 1k tokens
"ERNIE-Bot": {[]float64{0.8572, 0.8572}, ChannelTypeBaidu},
"ERNIE-3.5-8K": {[]float64{0.8572, 0.8572}, ChannelTypeBaidu},
// 0.024元/千tokens 0.048元/千tokens
"ERNIE-Bot-8k": {[]float64{1.7143, 3.4286}, ChannelTypeBaidu},
// ￥0.008 / 1k tokens ￥0.008 / 1k tokens
"ERNIE-Bot-turbo": {[]float64{0.5715, 0.5715}, ChannelTypeBaidu},
// ￥0.12 / 1k tokens ￥0.12 / 1k tokens
"ERNIE-Bot-4": {[]float64{8.572, 8.572}, ChannelTypeBaidu},
"ERNIE-4.0": {[]float64{8.572, 8.572}, ChannelTypeBaidu},
// ￥0.002 / 1k tokens
"Embedding-V1": {[]float64{0.1429, 0.1429}, ChannelTypeBaidu},
// ￥0.004 / 1k tokens
"BLOOMZ-7B": {[]float64{0.2857, 0.2857}, ChannelTypeBaidu},
"PaLM-2": {[]float64{1, 1}, ChannelTypePaLM},
"gemini-pro": {[]float64{1, 1}, ChannelTypeGemini},
"gemini-pro-vision": {[]float64{1, 1}, ChannelTypeGemini},
"gemini-1.0-pro": {[]float64{1, 1}, ChannelTypeGemini},
"gemini-1.5-pro": {[]float64{1, 1}, ChannelTypeGemini},
// ￥0.005 / 1k tokens
"glm-3-turbo": {[]float64{0.3572, 0.3572}, ChannelTypeZhipu},
// ￥0.1 / 1k tokens
"glm-4": {[]float64{7.143, 7.143}, ChannelTypeZhipu},
"glm-4v": {[]float64{7.143, 7.143}, ChannelTypeZhipu},
// ￥0.0005 / 1k tokens
"embedding-2": {[]float64{0.0357, 0.0357}, ChannelTypeZhipu},
// ￥0.25 / 1张图片
"cogview-3": {[]float64{17.8571, 17.8571}, ChannelTypeZhipu},
// ￥0.008 / 1k tokens
"qwen-turbo": {[]float64{0.5715, 0.5715}, ChannelTypeAli},
// ￥0.02 / 1k tokens
"qwen-plus": {[]float64{1.4286, 1.4286}, ChannelTypeAli},
"qwen-vl-max": {[]float64{1.4286, 1.4286}, ChannelTypeAli},
// 0.12元/1,000tokens
"qwen-max": {[]float64{8.5714, 8.5714}, ChannelTypeAli},
"qwen-max-longcontext": {[]float64{8.5714, 8.5714}, ChannelTypeAli},
// 0.008元/1,000tokens
"qwen-vl-plus": {[]float64{0.5715, 0.5715}, ChannelTypeAli},
// ￥0.0007 / 1k tokens
"text-embedding-v1": {[]float64{0.05, 0.05}, ChannelTypeAli},
// ￥0.018 / 1k tokens
"SparkDesk": {[]float64{1.2858, 1.2858}, ChannelTypeXunfei},
"SparkDesk-v1.1": {[]float64{1.2858, 1.2858}, ChannelTypeXunfei},
"SparkDesk-v2.1": {[]float64{1.2858, 1.2858}, ChannelTypeXunfei},
"SparkDesk-v3.1": {[]float64{1.2858, 1.2858}, ChannelTypeXunfei},
"SparkDesk-v3.5": {[]float64{1.2858, 1.2858}, ChannelTypeXunfei},
// ¥0.012 / 1k tokens
"360GPT_S2_V9": {[]float64{0.8572, 0.8572}, ChannelType360},
// ¥0.001 / 1k tokens
"embedding-bert-512-v1": {[]float64{0.0715, 0.0715}, ChannelType360},
"embedding_s1_v1": {[]float64{0.0715, 0.0715}, ChannelType360},
"semantic_similarity_s1_v1": {[]float64{0.0715, 0.0715}, ChannelType360},
// ¥0.1 / 1k tokens // https://cloud.tencent.com/document/product/1729/97731#e0e6be58-60c8-469f-bdeb-6c264ce3b4d0
"hunyuan": {[]float64{7.143, 7.143}, ChannelTypeTencent},
// https://cloud.tencent.com/document/product/1729/97731#e0e6be58-60c8-469f-bdeb-6c264ce3b4d0
// ¥0.01 / 1k tokens
"ChatStd": {[]float64{0.7143, 0.7143}, ChannelTypeTencent},
//¥0.1 / 1k tokens
"ChatPro": {[]float64{7.143, 7.143}, ChannelTypeTencent},
"Baichuan2-Turbo": {[]float64{0.5715, 0.5715}, ChannelTypeBaichuan}, // ¥0.008 / 1k tokens
"Baichuan2-Turbo-192k": {[]float64{1.143, 1.143}, ChannelTypeBaichuan}, // ¥0.016 / 1k tokens
"Baichuan2-53B": {[]float64{1.4286, 1.4286}, ChannelTypeBaichuan}, // ¥0.02 / 1k tokens
"Baichuan-Text-Embedding": {[]float64{0.0357, 0.0357}, ChannelTypeBaichuan}, // ¥0.0005 / 1k tokens
"abab5.5s-chat": {[]float64{0.3572, 0.3572}, ChannelTypeMiniMax}, // ¥0.005 / 1k tokens
"abab5.5-chat": {[]float64{1.0714, 1.0714}, ChannelTypeMiniMax}, // ¥0.015 / 1k tokens
"abab6-chat": {[]float64{14.2857, 14.2857}, ChannelTypeMiniMax}, // ¥0.2 / 1k tokens
"embo-01": {[]float64{0.0357, 0.0357}, ChannelTypeMiniMax}, // ¥0.0005 / 1k tokens
"deepseek-coder": {[]float64{0.75, 0.75}, ChannelTypeDeepseek}, // 暂定 $0.0015 / 1K tokens
"deepseek-chat": {[]float64{0.75, 0.75}, ChannelTypeDeepseek}, // 暂定 $0.0015 / 1K tokens
"moonshot-v1-8k": {[]float64{0.8572, 0.8572}, ChannelTypeMoonshot}, // ¥0.012 / 1K tokens
"moonshot-v1-32k": {[]float64{1.7143, 1.7143}, ChannelTypeMoonshot}, // ¥0.024 / 1K tokens
"moonshot-v1-128k": {[]float64{4.2857, 4.2857}, ChannelTypeMoonshot}, // ¥0.06 / 1K tokens
"open-mistral-7b": {[]float64{0.125, 0.125}, ChannelTypeMistral}, // 0.25$ / 1M tokens 0.25$ / 1M tokens 0.00025$ / 1k tokens
"open-mixtral-8x7b": {[]float64{0.35, 0.35}, ChannelTypeMistral}, // 0.7$ / 1M tokens 0.7$ / 1M tokens 0.0007$ / 1k tokens
"mistral-small-latest": {[]float64{1, 3}, ChannelTypeMistral}, // 2$ / 1M tokens 6$ / 1M tokens 0.002$ / 1k tokens
"mistral-medium-latest": {[]float64{1.35, 4.05}, ChannelTypeMistral}, // 2.7$ / 1M tokens 8.1$ / 1M tokens 0.0027$ / 1k tokens
"mistral-large-latest": {[]float64{4, 12}, ChannelTypeMistral}, // 8$ / 1M tokens 24$ / 1M tokens 0.008$ / 1k tokens
"mistral-embed": {[]float64{0.05, 0.05}, ChannelTypeMistral}, // 0.1$ / 1M tokens 0.1$ / 1M tokens 0.0001$ / 1k tokens
// $0.70/$0.80 /1M Tokens 0.0007$ / 1k tokens
"llama2-70b-4096": {[]float64{0.35, 0.4}, ChannelTypeGroq},
// $0.10/$0.10 /1M Tokens 0.0001$ / 1k tokens
"llama2-7b-2048": {[]float64{0.05, 0.05}, ChannelTypeGroq},
"gemma-7b-it": {[]float64{0.05, 0.05}, ChannelTypeGroq},
// $0.27/$0.27 /1M Tokens 0.00027$ / 1k tokens
"mixtral-8x7b-32768": {[]float64{0.135, 0.135}, ChannelTypeGroq},
// 2.5 元 / 1M tokens 0.0025 / 1k tokens
"yi-34b-chat-0205": {[]float64{0.1786, 0.1786}, ChannelTypeLingyi},
// 12 元 / 1M tokens 0.012 / 1k tokens
"yi-34b-chat-200k": {[]float64{0.8571, 0.8571}, ChannelTypeLingyi},
// 6 元 / 1M tokens 0.006 / 1k tokens
"yi-vl-plus": {[]float64{0.4286, 0.4286}, ChannelTypeLingyi},
}
ModelRatio = make(map[string][]float64)
for name, modelType := range ModelTypes {
ModelRatio[name] = modelType.Ratio
}
}
var DalleSizeRatios = map[string]map[string]float64{
"dall-e-2": {
"256x256": 1,
@@ -234,104 +22,3 @@ var DalleImagePromptLengthLimitations = map[string]int{
"dall-e-2": 1000,
"dall-e-3": 4000,
}
func ModelRatio2JSONString() string {
jsonBytes, err := json.Marshal(ModelRatio)
if err != nil {
SysError("error marshalling model ratio: " + err.Error())
}
return string(jsonBytes)
}
func UpdateModelRatioByJSONString(jsonStr string) error {
ModelRatio = make(map[string][]float64)
return json.Unmarshal([]byte(jsonStr), &ModelRatio)
}
func MergeModelRatioByJSONString(jsonStr string) (newJsonStr string, err error) {
isNew := false
inputModelRatio := make(map[string][]float64)
err = json.Unmarshal([]byte(jsonStr), &inputModelRatio)
if err != nil {
inputModelRatioOld := make(map[string]float64)
err = json.Unmarshal([]byte(jsonStr), &inputModelRatioOld)
if err != nil {
return
}
inputModelRatio = UpdateModeRatioFormat(inputModelRatioOld)
isNew = true
}
// 与现有的ModelRatio进行比较，如果有新增的模型，需要添加
for key, value := range ModelRatio {
if _, ok := inputModelRatio[key]; !ok {
isNew = true
inputModelRatio[key] = value
}
}
if !isNew {
return
}
var jsonBytes []byte
jsonBytes, err = json.Marshal(inputModelRatio)
if err != nil {
SysError("error marshalling model ratio: " + err.Error())
}
newJsonStr = string(jsonBytes)
return
}
func UpdateModeRatioFormat(modelRatioOld map[string]float64) map[string][]float64 {
modelRatioNew := make(map[string][]float64)
for key, value := range modelRatioOld {
completionRatio := GetCompletionRatio(key) * value
modelRatioNew[key] = []float64{value, completionRatio}
}
return modelRatioNew
}
func GetModelRatio(name string) []float64 {
if strings.HasPrefix(name, "qwen-") && strings.HasSuffix(name, "-internet") {
name = strings.TrimSuffix(name, "-internet")
}
ratio, ok := ModelRatio[name]
if !ok {
SysError("model ratio not found: " + name)
return []float64{30, 30}
}
return ratio
}
func GetCompletionRatio(name string) float64 {
if strings.HasPrefix(name, "gpt-3.5") {
if strings.HasSuffix(name, "1106") {
return 2
}
if name == "gpt-3.5-turbo" || name == "gpt-3.5-turbo-16k" {
// TODO: clear this after 2023-12-11
now := time.Now()
// https://platform.openai.com/docs/models/continuous-model-upgrades
// if after 2023-12-11, use 2
if now.After(time.Date(2023, 12, 11, 0, 0, 0, 0, time.UTC)) {
return 2
}
}
return 1.333333
}
if strings.HasPrefix(name, "gpt-4") {
if strings.HasSuffix(name, "preview") {
return 3
}
return 2
}
if strings.HasPrefix(name, "claude-instant-1.2") {
return 3.38
}
if strings.HasPrefix(name, "claude-2") {
return 2.965517
}
return 1
}

40
common/token.go
View File

@@ -13,46 +13,46 @@ import (
)
var tokenEncoderMap = map[string]*tiktoken.Tiktoken{}
var defaultTokenEncoder *tiktoken.Tiktoken
var gpt35TokenEncoder *tiktoken.Tiktoken
var gpt4TokenEncoder *tiktoken.Tiktoken
func InitTokenEncoders() {
SysLog("initializing token encoders")
gpt35TokenEncoder, err := tiktoken.EncodingForModel("gpt-3.5-turbo")
var err error
gpt35TokenEncoder, err = tiktoken.EncodingForModel("gpt-3.5-turbo")
if err != nil {
FatalLog(fmt.Sprintf("failed to get gpt-3.5-turbo token encoder: %s", err.Error()))
}
defaultTokenEncoder = gpt35TokenEncoder
gpt4TokenEncoder, err := tiktoken.EncodingForModel("gpt-4")
gpt4TokenEncoder, err = tiktoken.EncodingForModel("gpt-4")
if err != nil {
FatalLog(fmt.Sprintf("failed to get gpt-4 token encoder: %s", err.Error()))
}
for model := range ModelRatio {
if strings.HasPrefix(model, "gpt-3.5") {
tokenEncoderMap[model] = gpt35TokenEncoder
} else if strings.HasPrefix(model, "gpt-4") {
tokenEncoderMap[model] = gpt4TokenEncoder
} else {
tokenEncoderMap[model] = nil
}
}
SysLog("token encoders initialized")
}
func getTokenEncoder(model string) *tiktoken.Tiktoken {
tokenEncoder, ok := tokenEncoderMap[model]
if ok && tokenEncoder != nil {
if ok {
return tokenEncoder
}
if ok {
tokenEncoder, err := tiktoken.EncodingForModel(model)
if strings.HasPrefix(model, "gpt-3.5") {
tokenEncoder = gpt35TokenEncoder
} else if strings.HasPrefix(model, "gpt-4") {
tokenEncoder = gpt4TokenEncoder
} else {
var err error
tokenEncoder, err = tiktoken.EncodingForModel(model)
if err != nil {
SysError(fmt.Sprintf("failed to get token encoder for model %s: %s, using encoder for gpt-3.5-turbo", model, err.Error()))
tokenEncoder = defaultTokenEncoder
tokenEncoder = gpt35TokenEncoder
}
tokenEncoderMap[model] = tokenEncoder
return tokenEncoder
}
return defaultTokenEncoder
tokenEncoderMap[model] = tokenEncoder
return tokenEncoder
}
func getTokenNum(tokenEncoder *tiktoken.Tiktoken, text string) int {

28
common/utils.go
View File

@@ -212,3 +212,31 @@ func IsFileExist(path string) bool {
_, err := os.Stat(path)
return err == nil || os.IsExist(err)
}
func Contains[T comparable](value T, slice []T) bool {
for _, item := range slice {
if item == value {
return true
}
}
return false
}
func Filter[T any](arr []T, f func(T) bool) []T {
var res []T
for _, v := range arr {
if f(v) {
res = append(res, v)
}
}
return res
}
func GetModelsWithMatch(modelList *[]string, modelName string) string {
for _, model := range *modelList {
if strings.HasPrefix(modelName, strings.TrimRight(model, "*")) {
return model
}
}
return ""
}