first commit: one-api base code + SAAS plan document
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huangzhenpc
2025-12-29 22:52:27 +08:00
commit cb7c48bfa7
564 changed files with 61468 additions and 0 deletions

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package openai
import (
"errors"
"fmt"
"io"
"net/http"
"strings"
"github.com/gin-gonic/gin"
"github.com/songquanpeng/one-api/relay/adaptor"
"github.com/songquanpeng/one-api/relay/adaptor/alibailian"
"github.com/songquanpeng/one-api/relay/adaptor/baiduv2"
"github.com/songquanpeng/one-api/relay/adaptor/doubao"
"github.com/songquanpeng/one-api/relay/adaptor/geminiv2"
"github.com/songquanpeng/one-api/relay/adaptor/minimax"
"github.com/songquanpeng/one-api/relay/adaptor/novita"
"github.com/songquanpeng/one-api/relay/channeltype"
"github.com/songquanpeng/one-api/relay/meta"
"github.com/songquanpeng/one-api/relay/model"
"github.com/songquanpeng/one-api/relay/relaymode"
)
type Adaptor struct {
ChannelType int
}
func (a *Adaptor) Init(meta *meta.Meta) {
a.ChannelType = meta.ChannelType
}
func (a *Adaptor) GetRequestURL(meta *meta.Meta) (string, error) {
switch meta.ChannelType {
case channeltype.Azure:
if meta.Mode == relaymode.ImagesGenerations {
// https://learn.microsoft.com/en-us/azure/ai-services/openai/dall-e-quickstart?tabs=dalle3%2Ccommand-line&pivots=rest-api
// https://{resource_name}.openai.azure.com/openai/deployments/dall-e-3/images/generations?api-version=2024-03-01-preview
fullRequestURL := fmt.Sprintf("%s/openai/deployments/%s/images/generations?api-version=%s", meta.BaseURL, meta.ActualModelName, meta.Config.APIVersion)
return fullRequestURL, nil
}
// https://learn.microsoft.com/en-us/azure/cognitive-services/openai/chatgpt-quickstart?pivots=rest-api&tabs=command-line#rest-api
requestURL := strings.Split(meta.RequestURLPath, "?")[0]
requestURL = fmt.Sprintf("%s?api-version=%s", requestURL, meta.Config.APIVersion)
task := strings.TrimPrefix(requestURL, "/v1/")
model_ := meta.ActualModelName
model_ = strings.Replace(model_, ".", "", -1)
//https://github.com/songquanpeng/one-api/issues/1191
// {your endpoint}/openai/deployments/{your azure_model}/chat/completions?api-version={api_version}
requestURL = fmt.Sprintf("/openai/deployments/%s/%s", model_, task)
return GetFullRequestURL(meta.BaseURL, requestURL, meta.ChannelType), nil
case channeltype.Minimax:
return minimax.GetRequestURL(meta)
case channeltype.Doubao:
return doubao.GetRequestURL(meta)
case channeltype.Novita:
return novita.GetRequestURL(meta)
case channeltype.BaiduV2:
return baiduv2.GetRequestURL(meta)
case channeltype.AliBailian:
return alibailian.GetRequestURL(meta)
case channeltype.GeminiOpenAICompatible:
return geminiv2.GetRequestURL(meta)
default:
return GetFullRequestURL(meta.BaseURL, meta.RequestURLPath, meta.ChannelType), nil
}
}
func (a *Adaptor) SetupRequestHeader(c *gin.Context, req *http.Request, meta *meta.Meta) error {
adaptor.SetupCommonRequestHeader(c, req, meta)
if meta.ChannelType == channeltype.Azure {
req.Header.Set("api-key", meta.APIKey)
return nil
}
req.Header.Set("Authorization", "Bearer "+meta.APIKey)
if meta.ChannelType == channeltype.OpenRouter {
req.Header.Set("HTTP-Referer", "https://github.com/songquanpeng/one-api")
req.Header.Set("X-Title", "One API")
}
return nil
}
func (a *Adaptor) ConvertRequest(c *gin.Context, relayMode int, request *model.GeneralOpenAIRequest) (any, error) {
if request == nil {
return nil, errors.New("request is nil")
}
if request.Stream {
// always return usage in stream mode
if request.StreamOptions == nil {
request.StreamOptions = &model.StreamOptions{}
}
request.StreamOptions.IncludeUsage = true
}
return request, nil
}
func (a *Adaptor) ConvertImageRequest(request *model.ImageRequest) (any, error) {
if request == nil {
return nil, errors.New("request is nil")
}
return request, nil
}
func (a *Adaptor) DoRequest(c *gin.Context, meta *meta.Meta, requestBody io.Reader) (*http.Response, error) {
return adaptor.DoRequestHelper(a, c, meta, requestBody)
}
func (a *Adaptor) DoResponse(c *gin.Context, resp *http.Response, meta *meta.Meta) (usage *model.Usage, err *model.ErrorWithStatusCode) {
if meta.IsStream {
var responseText string
err, responseText, usage = StreamHandler(c, resp, meta.Mode)
if usage == nil || usage.TotalTokens == 0 {
usage = ResponseText2Usage(responseText, meta.ActualModelName, meta.PromptTokens)
}
if usage.TotalTokens != 0 && usage.PromptTokens == 0 { // some channels don't return prompt tokens & completion tokens
usage.PromptTokens = meta.PromptTokens
usage.CompletionTokens = usage.TotalTokens - meta.PromptTokens
}
} else {
switch meta.Mode {
case relaymode.ImagesGenerations:
err, _ = ImageHandler(c, resp)
default:
err, usage = Handler(c, resp, meta.PromptTokens, meta.ActualModelName)
}
}
return
}
func (a *Adaptor) GetModelList() []string {
_, modelList := GetCompatibleChannelMeta(a.ChannelType)
return modelList
}
func (a *Adaptor) GetChannelName() string {
channelName, _ := GetCompatibleChannelMeta(a.ChannelType)
return channelName
}

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package openai
import (
"github.com/songquanpeng/one-api/relay/adaptor/ai360"
"github.com/songquanpeng/one-api/relay/adaptor/alibailian"
"github.com/songquanpeng/one-api/relay/adaptor/baichuan"
"github.com/songquanpeng/one-api/relay/adaptor/baiduv2"
"github.com/songquanpeng/one-api/relay/adaptor/deepseek"
"github.com/songquanpeng/one-api/relay/adaptor/doubao"
"github.com/songquanpeng/one-api/relay/adaptor/geminiv2"
"github.com/songquanpeng/one-api/relay/adaptor/groq"
"github.com/songquanpeng/one-api/relay/adaptor/lingyiwanwu"
"github.com/songquanpeng/one-api/relay/adaptor/minimax"
"github.com/songquanpeng/one-api/relay/adaptor/mistral"
"github.com/songquanpeng/one-api/relay/adaptor/moonshot"
"github.com/songquanpeng/one-api/relay/adaptor/novita"
"github.com/songquanpeng/one-api/relay/adaptor/openrouter"
"github.com/songquanpeng/one-api/relay/adaptor/siliconflow"
"github.com/songquanpeng/one-api/relay/adaptor/stepfun"
"github.com/songquanpeng/one-api/relay/adaptor/togetherai"
"github.com/songquanpeng/one-api/relay/adaptor/xai"
"github.com/songquanpeng/one-api/relay/adaptor/xunfeiv2"
"github.com/songquanpeng/one-api/relay/channeltype"
)
var CompatibleChannels = []int{
channeltype.Azure,
channeltype.AI360,
channeltype.Moonshot,
channeltype.Baichuan,
channeltype.Minimax,
channeltype.Doubao,
channeltype.Mistral,
channeltype.Groq,
channeltype.LingYiWanWu,
channeltype.StepFun,
channeltype.DeepSeek,
channeltype.TogetherAI,
channeltype.Novita,
channeltype.SiliconFlow,
channeltype.XAI,
channeltype.BaiduV2,
channeltype.XunfeiV2,
}
func GetCompatibleChannelMeta(channelType int) (string, []string) {
switch channelType {
case channeltype.Azure:
return "azure", ModelList
case channeltype.AI360:
return "360", ai360.ModelList
case channeltype.Moonshot:
return "moonshot", moonshot.ModelList
case channeltype.Baichuan:
return "baichuan", baichuan.ModelList
case channeltype.Minimax:
return "minimax", minimax.ModelList
case channeltype.Mistral:
return "mistralai", mistral.ModelList
case channeltype.Groq:
return "groq", groq.ModelList
case channeltype.LingYiWanWu:
return "lingyiwanwu", lingyiwanwu.ModelList
case channeltype.StepFun:
return "stepfun", stepfun.ModelList
case channeltype.DeepSeek:
return "deepseek", deepseek.ModelList
case channeltype.TogetherAI:
return "together.ai", togetherai.ModelList
case channeltype.Doubao:
return "doubao", doubao.ModelList
case channeltype.Novita:
return "novita", novita.ModelList
case channeltype.SiliconFlow:
return "siliconflow", siliconflow.ModelList
case channeltype.XAI:
return "xai", xai.ModelList
case channeltype.BaiduV2:
return "baiduv2", baiduv2.ModelList
case channeltype.XunfeiV2:
return "xunfeiv2", xunfeiv2.ModelList
case channeltype.OpenRouter:
return "openrouter", openrouter.ModelList
case channeltype.AliBailian:
return "alibailian", alibailian.ModelList
case channeltype.GeminiOpenAICompatible:
return "geminiv2", geminiv2.ModelList
default:
return "openai", ModelList
}
}

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package openai
var ModelList = []string{
"gpt-3.5-turbo", "gpt-3.5-turbo-0301", "gpt-3.5-turbo-0613", "gpt-3.5-turbo-1106", "gpt-3.5-turbo-0125",
"gpt-3.5-turbo-16k", "gpt-3.5-turbo-16k-0613",
"gpt-3.5-turbo-instruct",
"gpt-4", "gpt-4-0314", "gpt-4-0613", "gpt-4-1106-preview", "gpt-4-0125-preview",
"gpt-4-32k", "gpt-4-32k-0314", "gpt-4-32k-0613",
"gpt-4-turbo-preview", "gpt-4-turbo", "gpt-4-turbo-2024-04-09",
"gpt-4o", "gpt-4o-2024-05-13",
"gpt-4o-2024-08-06",
"gpt-4o-2024-11-20",
"chatgpt-4o-latest",
"gpt-4o-mini", "gpt-4o-mini-2024-07-18",
"gpt-4-vision-preview",
"text-embedding-ada-002", "text-embedding-3-small", "text-embedding-3-large",
"text-curie-001", "text-babbage-001", "text-ada-001", "text-davinci-002", "text-davinci-003",
"text-moderation-latest", "text-moderation-stable",
"text-davinci-edit-001",
"davinci-002", "babbage-002",
"dall-e-2", "dall-e-3",
"whisper-1",
"tts-1", "tts-1-1106", "tts-1-hd", "tts-1-hd-1106",
"o1", "o1-2024-12-17",
"o1-preview", "o1-preview-2024-09-12",
"o1-mini", "o1-mini-2024-09-12",
}

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package openai
import (
"fmt"
"strings"
"github.com/songquanpeng/one-api/relay/channeltype"
"github.com/songquanpeng/one-api/relay/model"
)
func ResponseText2Usage(responseText string, modelName string, promptTokens int) *model.Usage {
usage := &model.Usage{}
usage.PromptTokens = promptTokens
usage.CompletionTokens = CountTokenText(responseText, modelName)
usage.TotalTokens = usage.PromptTokens + usage.CompletionTokens
return usage
}
func GetFullRequestURL(baseURL string, requestURL string, channelType int) string {
if channelType == channeltype.OpenAICompatible {
return fmt.Sprintf("%s%s", strings.TrimSuffix(baseURL, "/"), strings.TrimPrefix(requestURL, "/v1"))
}
fullRequestURL := fmt.Sprintf("%s%s", baseURL, requestURL)
if strings.HasPrefix(baseURL, "https://gateway.ai.cloudflare.com") {
switch channelType {
case channeltype.OpenAI:
fullRequestURL = fmt.Sprintf("%s%s", baseURL, strings.TrimPrefix(requestURL, "/v1"))
case channeltype.Azure:
fullRequestURL = fmt.Sprintf("%s%s", baseURL, strings.TrimPrefix(requestURL, "/openai/deployments"))
}
}
return fullRequestURL
}

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package openai
import (
"bytes"
"encoding/json"
"github.com/gin-gonic/gin"
"github.com/songquanpeng/one-api/relay/model"
"io"
"net/http"
)
func ImageHandler(c *gin.Context, resp *http.Response) (*model.ErrorWithStatusCode, *model.Usage) {
var imageResponse ImageResponse
responseBody, err := io.ReadAll(resp.Body)
if err != nil {
return ErrorWrapper(err, "read_response_body_failed", http.StatusInternalServerError), nil
}
err = resp.Body.Close()
if err != nil {
return ErrorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), nil
}
err = json.Unmarshal(responseBody, &imageResponse)
if err != nil {
return ErrorWrapper(err, "unmarshal_response_body_failed", http.StatusInternalServerError), nil
}
resp.Body = io.NopCloser(bytes.NewBuffer(responseBody))
for k, v := range resp.Header {
c.Writer.Header().Set(k, v[0])
}
c.Writer.WriteHeader(resp.StatusCode)
_, err = io.Copy(c.Writer, resp.Body)
if err != nil {
return ErrorWrapper(err, "copy_response_body_failed", http.StatusInternalServerError), nil
}
err = resp.Body.Close()
if err != nil {
return ErrorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), nil
}
return nil, nil
}

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package openai
import (
"bufio"
"bytes"
"encoding/json"
"io"
"net/http"
"strings"
"github.com/songquanpeng/one-api/common/render"
"github.com/gin-gonic/gin"
"github.com/songquanpeng/one-api/common"
"github.com/songquanpeng/one-api/common/conv"
"github.com/songquanpeng/one-api/common/logger"
"github.com/songquanpeng/one-api/relay/model"
"github.com/songquanpeng/one-api/relay/relaymode"
)
const (
dataPrefix = "data: "
done = "[DONE]"
dataPrefixLength = len(dataPrefix)
)
func StreamHandler(c *gin.Context, resp *http.Response, relayMode int) (*model.ErrorWithStatusCode, string, *model.Usage) {
responseText := ""
scanner := bufio.NewScanner(resp.Body)
scanner.Split(bufio.ScanLines)
var usage *model.Usage
common.SetEventStreamHeaders(c)
doneRendered := false
for scanner.Scan() {
data := scanner.Text()
if len(data) < dataPrefixLength { // ignore blank line or wrong format
continue
}
if data[:dataPrefixLength] != dataPrefix && data[:dataPrefixLength] != done {
continue
}
if strings.HasPrefix(data[dataPrefixLength:], done) {
render.StringData(c, data)
doneRendered = true
continue
}
switch relayMode {
case relaymode.ChatCompletions:
var streamResponse ChatCompletionsStreamResponse
err := json.Unmarshal([]byte(data[dataPrefixLength:]), &streamResponse)
if err != nil {
logger.SysError("error unmarshalling stream response: " + err.Error())
render.StringData(c, data) // if error happened, pass the data to client
continue // just ignore the error
}
if len(streamResponse.Choices) == 0 && streamResponse.Usage == nil {
// but for empty choice and no usage, we should not pass it to client, this is for azure
continue // just ignore empty choice
}
render.StringData(c, data)
for _, choice := range streamResponse.Choices {
responseText += conv.AsString(choice.Delta.Content)
}
if streamResponse.Usage != nil {
usage = streamResponse.Usage
}
case relaymode.Completions:
render.StringData(c, data)
var streamResponse CompletionsStreamResponse
err := json.Unmarshal([]byte(data[dataPrefixLength:]), &streamResponse)
if err != nil {
logger.SysError("error unmarshalling stream response: " + err.Error())
continue
}
for _, choice := range streamResponse.Choices {
responseText += choice.Text
}
}
}
if err := scanner.Err(); err != nil {
logger.SysError("error reading stream: " + err.Error())
}
if !doneRendered {
render.Done(c)
}
err := resp.Body.Close()
if err != nil {
return ErrorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), "", nil
}
return nil, responseText, usage
}
func Handler(c *gin.Context, resp *http.Response, promptTokens int, modelName string) (*model.ErrorWithStatusCode, *model.Usage) {
var textResponse SlimTextResponse
responseBody, err := io.ReadAll(resp.Body)
if err != nil {
return ErrorWrapper(err, "read_response_body_failed", http.StatusInternalServerError), nil
}
err = resp.Body.Close()
if err != nil {
return ErrorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), nil
}
err = json.Unmarshal(responseBody, &textResponse)
if err != nil {
return ErrorWrapper(err, "unmarshal_response_body_failed", http.StatusInternalServerError), nil
}
if textResponse.Error.Type != "" {
return &model.ErrorWithStatusCode{
Error: textResponse.Error,
StatusCode: resp.StatusCode,
}, nil
}
// Reset response body
resp.Body = io.NopCloser(bytes.NewBuffer(responseBody))
// We shouldn't set the header before we parse the response body, because the parse part may fail.
// And then we will have to send an error response, but in this case, the header has already been set.
// So the HTTPClient will be confused by the response.
// For example, Postman will report error, and we cannot check the response at all.
for k, v := range resp.Header {
c.Writer.Header().Set(k, v[0])
}
c.Writer.WriteHeader(resp.StatusCode)
_, err = io.Copy(c.Writer, resp.Body)
if err != nil {
return ErrorWrapper(err, "copy_response_body_failed", http.StatusInternalServerError), nil
}
err = resp.Body.Close()
if err != nil {
return ErrorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), nil
}
if textResponse.Usage.TotalTokens == 0 || (textResponse.Usage.PromptTokens == 0 && textResponse.Usage.CompletionTokens == 0) {
completionTokens := 0
for _, choice := range textResponse.Choices {
completionTokens += CountTokenText(choice.Message.StringContent(), modelName)
}
textResponse.Usage = model.Usage{
PromptTokens: promptTokens,
CompletionTokens: completionTokens,
TotalTokens: promptTokens + completionTokens,
}
}
return nil, &textResponse.Usage
}

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package openai
import "github.com/songquanpeng/one-api/relay/model"
type TextContent struct {
Type string `json:"type,omitempty"`
Text string `json:"text,omitempty"`
}
type ImageContent struct {
Type string `json:"type,omitempty"`
ImageURL *model.ImageURL `json:"image_url,omitempty"`
}
type ChatRequest struct {
Model string `json:"model"`
Messages []model.Message `json:"messages"`
MaxTokens int `json:"max_tokens"`
}
type TextRequest struct {
Model string `json:"model"`
Messages []model.Message `json:"messages"`
Prompt string `json:"prompt"`
MaxTokens int `json:"max_tokens"`
//Stream bool `json:"stream"`
}
// ImageRequest docs: https://platform.openai.com/docs/api-reference/images/create
type ImageRequest struct {
Model string `json:"model"`
Prompt string `json:"prompt" binding:"required"`
N int `json:"n,omitempty"`
Size string `json:"size,omitempty"`
Quality string `json:"quality,omitempty"`
ResponseFormat string `json:"response_format,omitempty"`
Style string `json:"style,omitempty"`
User string `json:"user,omitempty"`
}
type WhisperJSONResponse struct {
Text string `json:"text,omitempty"`
}
type WhisperVerboseJSONResponse struct {
Task string `json:"task,omitempty"`
Language string `json:"language,omitempty"`
Duration float64 `json:"duration,omitempty"`
Text string `json:"text,omitempty"`
Segments []Segment `json:"segments,omitempty"`
}
type Segment struct {
Id int `json:"id"`
Seek int `json:"seek"`
Start float64 `json:"start"`
End float64 `json:"end"`
Text string `json:"text"`
Tokens []int `json:"tokens"`
Temperature float64 `json:"temperature"`
AvgLogprob float64 `json:"avg_logprob"`
CompressionRatio float64 `json:"compression_ratio"`
NoSpeechProb float64 `json:"no_speech_prob"`
}
type TextToSpeechRequest struct {
Model string `json:"model" binding:"required"`
Input string `json:"input" binding:"required"`
Voice string `json:"voice" binding:"required"`
Speed float64 `json:"speed"`
ResponseFormat string `json:"response_format"`
}
type UsageOrResponseText struct {
*model.Usage
ResponseText string
}
type SlimTextResponse struct {
Choices []TextResponseChoice `json:"choices"`
model.Usage `json:"usage"`
Error model.Error `json:"error"`
}
type TextResponseChoice struct {
Index int `json:"index"`
model.Message `json:"message"`
FinishReason string `json:"finish_reason"`
}
type TextResponse struct {
Id string `json:"id"`
Model string `json:"model,omitempty"`
Object string `json:"object"`
Created int64 `json:"created"`
Choices []TextResponseChoice `json:"choices"`
model.Usage `json:"usage"`
}
type EmbeddingResponseItem struct {
Object string `json:"object"`
Index int `json:"index"`
Embedding []float64 `json:"embedding"`
}
type EmbeddingResponse struct {
Object string `json:"object"`
Data []EmbeddingResponseItem `json:"data"`
Model string `json:"model"`
model.Usage `json:"usage"`
}
type ImageData struct {
Url string `json:"url,omitempty"`
B64Json string `json:"b64_json,omitempty"`
RevisedPrompt string `json:"revised_prompt,omitempty"`
}
type ImageResponse struct {
Created int64 `json:"created"`
Data []ImageData `json:"data"`
//model.Usage `json:"usage"`
}
type ChatCompletionsStreamResponseChoice struct {
Index int `json:"index"`
Delta model.Message `json:"delta"`
FinishReason *string `json:"finish_reason,omitempty"`
}
type ChatCompletionsStreamResponse struct {
Id string `json:"id"`
Object string `json:"object"`
Created int64 `json:"created"`
Model string `json:"model"`
Choices []ChatCompletionsStreamResponseChoice `json:"choices"`
Usage *model.Usage `json:"usage,omitempty"`
}
type CompletionsStreamResponse struct {
Choices []struct {
Text string `json:"text"`
FinishReason string `json:"finish_reason"`
} `json:"choices"`
}

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package openai
import (
"errors"
"fmt"
"math"
"strings"
"github.com/pkoukk/tiktoken-go"
"github.com/songquanpeng/one-api/common/config"
"github.com/songquanpeng/one-api/common/image"
"github.com/songquanpeng/one-api/common/logger"
billingratio "github.com/songquanpeng/one-api/relay/billing/ratio"
"github.com/songquanpeng/one-api/relay/model"
)
// tokenEncoderMap won't grow after initialization
var tokenEncoderMap = map[string]*tiktoken.Tiktoken{}
var defaultTokenEncoder *tiktoken.Tiktoken
func InitTokenEncoders() {
logger.SysLog("initializing token encoders")
gpt35TokenEncoder, err := tiktoken.EncodingForModel("gpt-3.5-turbo")
if err != nil {
logger.FatalLog(fmt.Sprintf("failed to get gpt-3.5-turbo token encoder: %s, "+
"if you are using in offline environment, please set TIKTOKEN_CACHE_DIR to use exsited files, check this link for more information: https://stackoverflow.com/questions/76106366/how-to-use-tiktoken-in-offline-mode-computer ", err.Error()))
}
defaultTokenEncoder = gpt35TokenEncoder
gpt4oTokenEncoder, err := tiktoken.EncodingForModel("gpt-4o")
if err != nil {
logger.FatalLog(fmt.Sprintf("failed to get gpt-4o token encoder: %s", err.Error()))
}
gpt4TokenEncoder, err := tiktoken.EncodingForModel("gpt-4")
if err != nil {
logger.FatalLog(fmt.Sprintf("failed to get gpt-4 token encoder: %s", err.Error()))
}
for model := range billingratio.ModelRatio {
if strings.HasPrefix(model, "gpt-3.5") {
tokenEncoderMap[model] = gpt35TokenEncoder
} else if strings.HasPrefix(model, "gpt-4o") {
tokenEncoderMap[model] = gpt4oTokenEncoder
} else if strings.HasPrefix(model, "gpt-4") {
tokenEncoderMap[model] = gpt4TokenEncoder
} else {
tokenEncoderMap[model] = nil
}
}
logger.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 {
logger.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 {
if config.ApproximateTokenEnabled {
return int(float64(len(text)) * 0.38)
}
return len(tokenEncoder.Encode(text, nil, nil))
}
func CountTokenMessages(messages []model.Message, model string) int {
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
switch v := message.Content.(type) {
case string:
tokenNum += getTokenNum(tokenEncoder, v)
case []any:
for _, it := range v {
m := it.(map[string]any)
switch m["type"] {
case "text":
if textValue, ok := m["text"]; ok {
if textString, ok := textValue.(string); ok {
tokenNum += getTokenNum(tokenEncoder, textString)
}
}
case "image_url":
imageUrl, ok := m["image_url"].(map[string]any)
if ok {
url := imageUrl["url"].(string)
detail := ""
if imageUrl["detail"] != nil {
detail = imageUrl["detail"].(string)
}
imageTokens, err := countImageTokens(url, detail, model)
if err != nil {
logger.SysError("error counting image tokens: " + err.Error())
} else {
tokenNum += imageTokens
}
}
}
}
}
tokenNum += getTokenNum(tokenEncoder, message.Role)
if message.Name != nil {
tokenNum += tokensPerName
tokenNum += getTokenNum(tokenEncoder, *message.Name)
}
}
tokenNum += 3 // Every reply is primed with <|start|>assistant<|message|>
return tokenNum
}
const (
lowDetailCost = 85
highDetailCostPerTile = 170
additionalCost = 85
// gpt-4o-mini cost higher than other model
gpt4oMiniLowDetailCost = 2833
gpt4oMiniHighDetailCost = 5667
gpt4oMiniAdditionalCost = 2833
)
// https://platform.openai.com/docs/guides/vision/calculating-costs
// https://github.com/openai/openai-cookbook/blob/05e3f9be4c7a2ae7ecf029a7c32065b024730ebe/examples/How_to_count_tokens_with_tiktoken.ipynb
func countImageTokens(url string, detail string, model string) (_ int, err error) {
var fetchSize = true
var width, height int
// Reference: https://platform.openai.com/docs/guides/vision/low-or-high-fidelity-image-understanding
// detail == "auto" is undocumented on how it works, it just said the model will use the auto setting which will look at the image input size and decide if it should use the low or high setting.
// According to the official guide, "low" disable the high-res model,
// and only receive low-res 512px x 512px version of the image, indicating
// that image is treated as low-res when size is smaller than 512px x 512px,
// then we can assume that image size larger than 512px x 512px is treated
// as high-res. Then we have the following logic:
// if detail == "" || detail == "auto" {
// width, height, err = image.GetImageSize(url)
// if err != nil {
// return 0, err
// }
// fetchSize = false
// // not sure if this is correct
// if width > 512 || height > 512 {
// detail = "high"
// } else {
// detail = "low"
// }
// }
// However, in my test, it seems to be always the same as "high".
// The following image, which is 125x50, is still treated as high-res, taken
// 255 tokens in the response of non-stream chat completion api.
// https://upload.wikimedia.org/wikipedia/commons/1/10/18_Infantry_Division_Messina.jpg
if detail == "" || detail == "auto" {
// assume by test, not sure if this is correct
detail = "high"
}
switch detail {
case "low":
if strings.HasPrefix(model, "gpt-4o-mini") {
return gpt4oMiniLowDetailCost, nil
}
return lowDetailCost, nil
case "high":
if fetchSize {
width, height, err = image.GetImageSize(url)
if err != nil {
return 0, err
}
}
if width > 2048 || height > 2048 { // max(width, height) > 2048
ratio := float64(2048) / math.Max(float64(width), float64(height))
width = int(float64(width) * ratio)
height = int(float64(height) * ratio)
}
if width > 768 && height > 768 { // min(width, height) > 768
ratio := float64(768) / math.Min(float64(width), float64(height))
width = int(float64(width) * ratio)
height = int(float64(height) * ratio)
}
numSquares := int(math.Ceil(float64(width)/512) * math.Ceil(float64(height)/512))
if strings.HasPrefix(model, "gpt-4o-mini") {
return numSquares*gpt4oMiniHighDetailCost + gpt4oMiniAdditionalCost, nil
}
result := numSquares*highDetailCostPerTile + additionalCost
return result, nil
default:
return 0, errors.New("invalid detail option")
}
}
func CountTokenInput(input any, model string) int {
switch v := input.(type) {
case string:
return CountTokenText(v, model)
case []string:
text := ""
for _, s := range v {
text += s
}
return CountTokenText(text, model)
}
return 0
}
func CountTokenText(text string, model string) int {
tokenEncoder := getTokenEncoder(model)
return getTokenNum(tokenEncoder, text)
}
func CountToken(text string) int {
return CountTokenInput(text, "gpt-3.5-turbo")
}

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@@ -0,0 +1,23 @@
package openai
import (
"context"
"fmt"
"github.com/songquanpeng/one-api/common/logger"
"github.com/songquanpeng/one-api/relay/model"
)
func ErrorWrapper(err error, code string, statusCode int) *model.ErrorWithStatusCode {
logger.Error(context.TODO(), fmt.Sprintf("[%s]%+v", code, err))
Error := model.Error{
Message: err.Error(),
Type: "one_api_error",
Code: code,
}
return &model.ErrorWithStatusCode{
Error: Error,
StatusCode: statusCode,
}
}