Merge branch 'Songquanpeng-main'
This commit is contained in:
commit
fe56aa1a46
3
.gitignore
vendored
3
.gitignore
vendored
@ -5,4 +5,5 @@ upload
|
||||
*.db
|
||||
build
|
||||
*.db-journal
|
||||
logs
|
||||
logs
|
||||
data
|
@ -189,6 +189,8 @@ If you encounter a blank page after deployment, refer to [#97](https://github.co
|
||||
|
||||
> Zeabur's servers are located overseas, automatically solving network issues, and the free quota is sufficient for personal usage.
|
||||
|
||||
[](https://zeabur.com/templates/7Q0KO3)
|
||||
|
||||
1. First, fork the code.
|
||||
2. Go to [Zeabur](https://zeabur.com?referralCode=songquanpeng), log in, and enter the console.
|
||||
3. Create a new project. In Service -> Add Service, select Marketplace, and choose MySQL. Note down the connection parameters (username, password, address, and port).
|
||||
|
@ -190,6 +190,8 @@ Please refer to the [environment variables](#environment-variables) section for
|
||||
|
||||
> Zeabur のサーバーは海外にあるため、ネットワークの問題は自動的に解決されます。
|
||||
|
||||
[](https://zeabur.com/templates/7Q0KO3)
|
||||
|
||||
1. まず、コードをフォークする。
|
||||
2. [Zeabur](https://zeabur.com?referralCode=songquanpeng) にアクセスしてログインし、コンソールに入る。
|
||||
3. 新しいプロジェクトを作成します。Service -> Add ServiceでMarketplace を選択し、MySQL を選択する。接続パラメータ(ユーザー名、パスワード、アドレス、ポート)をメモします。
|
||||
|
17
README.md
17
README.md
@ -75,7 +75,7 @@ _✨ 通过标准的 OpenAI API 格式访问所有的大模型,开箱即用
|
||||
+ [x] [腾讯混元大模型](https://cloud.tencent.com/document/product/1729)
|
||||
2. 支持配置镜像以及众多第三方代理服务:
|
||||
+ [x] [OpenAI-SB](https://openai-sb.com)
|
||||
+ [x] [CloseAI](https://console.closeai-asia.com/r/2412)
|
||||
+ [x] [CloseAI](https://referer.shadowai.xyz/r/2412)
|
||||
+ [x] [API2D](https://api2d.com/r/197971)
|
||||
+ [x] [OhMyGPT](https://aigptx.top?aff=uFpUl2Kf)
|
||||
+ [x] [AI Proxy](https://aiproxy.io/?i=OneAPI) (邀请码:`OneAPI`)
|
||||
@ -160,6 +160,19 @@ sudo service nginx restart
|
||||
|
||||
初始账号用户名为 `root`,密码为 `123456`。
|
||||
|
||||
|
||||
### 基于 Docker Compose 进行部署
|
||||
|
||||
> 仅启动方式不同,参数设置不变,请参考基于 Docker 部署部分
|
||||
|
||||
```shell
|
||||
# 目前支持 MySQL 启动,数据存储在 ./data/mysql 文件夹内
|
||||
docker-compose up -d
|
||||
|
||||
# 查看部署状态
|
||||
docker-compose ps
|
||||
```
|
||||
|
||||
### 手动部署
|
||||
1. 从 [GitHub Releases](https://github.com/songquanpeng/one-api/releases/latest) 下载可执行文件或者从源码编译:
|
||||
```shell
|
||||
@ -249,6 +262,8 @@ docker run --name chatgpt-web -d -p 3002:3002 -e OPENAI_API_BASE_URL=https://ope
|
||||
|
||||
> Zeabur 的服务器在国外,自动解决了网络的问题,同时免费的额度也足够个人使用
|
||||
|
||||
[](https://zeabur.com/templates/7Q0KO3)
|
||||
|
||||
1. 首先 fork 一份代码。
|
||||
2. 进入 [Zeabur](https://zeabur.com?referralCode=songquanpeng),登录,进入控制台。
|
||||
3. 新建一个 Project,在 Service -> Add Service 选择 Marketplace,选择 MySQL,并记下连接参数(用户名、密码、地址、端口)。
|
||||
|
@ -3,8 +3,32 @@ package common
|
||||
import (
|
||||
"encoding/json"
|
||||
"strings"
|
||||
"time"
|
||||
)
|
||||
|
||||
var DalleSizeRatios = map[string]map[string]float64{
|
||||
"dall-e-2": {
|
||||
"256x256": 1,
|
||||
"512x512": 1.125,
|
||||
"1024x1024": 1.25,
|
||||
},
|
||||
"dall-e-3": {
|
||||
"1024x1024": 1,
|
||||
"1024x1792": 2,
|
||||
"1792x1024": 2,
|
||||
},
|
||||
}
|
||||
|
||||
var DalleGenerationImageAmounts = map[string][2]int{
|
||||
"dall-e-2": {1, 10},
|
||||
"dall-e-3": {1, 1}, // OpenAI allows n=1 currently.
|
||||
}
|
||||
|
||||
var DalleImagePromptLengthLimitations = map[string]int{
|
||||
"dall-e-2": 1000,
|
||||
"dall-e-3": 4000,
|
||||
}
|
||||
|
||||
// ModelRatio
|
||||
// https://platform.openai.com/docs/models/model-endpoint-compatibility
|
||||
// https://cloud.baidu.com/doc/WENXINWORKSHOP/s/Blfmc9dlf
|
||||
@ -19,12 +43,15 @@ var ModelRatio = map[string]float64{
|
||||
"gpt-4-32k": 30,
|
||||
"gpt-4-32k-0314": 30,
|
||||
"gpt-4-32k-0613": 30,
|
||||
"gpt-4-1106-preview": 5, // $0.01 / 1K tokens
|
||||
"gpt-4-vision-preview": 5, // $0.01 / 1K tokens
|
||||
"gpt-3.5-turbo": 0.75, // $0.0015 / 1K tokens
|
||||
"gpt-3.5-turbo-0301": 0.75,
|
||||
"gpt-3.5-turbo-0613": 0.75,
|
||||
"gpt-3.5-turbo-16k": 1.5, // $0.003 / 1K tokens
|
||||
"gpt-3.5-turbo-16k-0613": 1.5,
|
||||
"gpt-3.5-turbo-instruct": 0.75, // $0.0015 / 1K tokens
|
||||
"gpt-3.5-turbo-1106": 0.5, // $0.001 / 1K tokens
|
||||
"text-ada-001": 0.2,
|
||||
"text-babbage-001": 0.25,
|
||||
"text-curie-001": 1,
|
||||
@ -32,7 +59,11 @@ var ModelRatio = map[string]float64{
|
||||
"text-davinci-003": 10,
|
||||
"text-davinci-edit-001": 10,
|
||||
"code-davinci-edit-001": 10,
|
||||
"whisper-1": 15, // $0.006 / minute -> $0.006 / 150 words -> $0.006 / 200 tokens -> $0.03 / 1k tokens
|
||||
"whisper-1": 15, // $0.006 / minute -> $0.006 / 150 words -> $0.006 / 200 tokens -> $0.03 / 1k tokens
|
||||
"tts-1": 7.5, // $0.015 / 1K characters
|
||||
"tts-1-1106": 7.5,
|
||||
"tts-1-hd": 15, // $0.030 / 1K characters
|
||||
"tts-1-hd-1106": 15,
|
||||
"davinci": 10,
|
||||
"curie": 10,
|
||||
"babbage": 10,
|
||||
@ -41,7 +72,8 @@ var ModelRatio = map[string]float64{
|
||||
"text-search-ada-doc-001": 10,
|
||||
"text-moderation-stable": 0.1,
|
||||
"text-moderation-latest": 0.1,
|
||||
"dall-e": 8,
|
||||
"dall-e-2": 8, // $0.016 - $0.020 / image
|
||||
"dall-e-3": 20, // $0.040 - $0.120 / image
|
||||
"claude-instant-1": 0.815, // $1.63 / 1M tokens
|
||||
"claude-2": 5.51, // $11.02 / 1M tokens
|
||||
"ERNIE-Bot": 0.8572, // ¥0.012 / 1k tokens
|
||||
@ -88,9 +120,24 @@ func GetModelRatio(name string) float64 {
|
||||
|
||||
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") {
|
||||
|
@ -5,6 +5,7 @@ import (
|
||||
"encoding/json"
|
||||
"errors"
|
||||
"fmt"
|
||||
"io"
|
||||
"net/http"
|
||||
"one-api/common"
|
||||
"one-api/model"
|
||||
@ -45,8 +46,8 @@ func testChannel(channel *model.Channel, request ChatRequest) (err error, openai
|
||||
if channel.Type == common.ChannelTypeAzure {
|
||||
requestURL = getFullRequestURL(channel.GetBaseURL(), fmt.Sprintf("/openai/deployments/%s/chat/completions?api-version=2023-03-15-preview", request.Model), channel.Type)
|
||||
} else {
|
||||
if channel.GetBaseURL() != "" {
|
||||
requestURL = channel.GetBaseURL()
|
||||
if baseURL := channel.GetBaseURL(); len(baseURL) > 0 {
|
||||
requestURL = baseURL
|
||||
}
|
||||
|
||||
requestURL = getFullRequestURL(requestURL, "/v1/chat/completions", channel.Type)
|
||||
@ -71,10 +72,14 @@ func testChannel(channel *model.Channel, request ChatRequest) (err error, openai
|
||||
}
|
||||
defer resp.Body.Close()
|
||||
var response TextResponse
|
||||
err = json.NewDecoder(resp.Body).Decode(&response)
|
||||
body, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
return err, nil
|
||||
}
|
||||
err = json.Unmarshal(body, &response)
|
||||
if err != nil {
|
||||
return fmt.Errorf("Error: %s\nResp body: %s", err, body), nil
|
||||
}
|
||||
if response.Usage.CompletionTokens == 0 {
|
||||
return errors.New(fmt.Sprintf("type %s, code %v, message %s", response.Error.Type, response.Error.Code, response.Error.Message)), &response.Error
|
||||
}
|
||||
|
@ -55,12 +55,21 @@ func init() {
|
||||
// https://platform.openai.com/docs/models/model-endpoint-compatibility
|
||||
openAIModels = []OpenAIModels{
|
||||
{
|
||||
Id: "dall-e",
|
||||
Id: "dall-e-2",
|
||||
Object: "model",
|
||||
Created: 1677649963,
|
||||
OwnedBy: "openai",
|
||||
Permission: permission,
|
||||
Root: "dall-e",
|
||||
Root: "dall-e-2",
|
||||
Parent: nil,
|
||||
},
|
||||
{
|
||||
Id: "dall-e-3",
|
||||
Object: "model",
|
||||
Created: 1677649963,
|
||||
OwnedBy: "openai",
|
||||
Permission: permission,
|
||||
Root: "dall-e-3",
|
||||
Parent: nil,
|
||||
},
|
||||
{
|
||||
@ -72,6 +81,42 @@ func init() {
|
||||
Root: "whisper-1",
|
||||
Parent: nil,
|
||||
},
|
||||
{
|
||||
Id: "tts-1",
|
||||
Object: "model",
|
||||
Created: 1677649963,
|
||||
OwnedBy: "openai",
|
||||
Permission: permission,
|
||||
Root: "tts-1",
|
||||
Parent: nil,
|
||||
},
|
||||
{
|
||||
Id: "tts-1-1106",
|
||||
Object: "model",
|
||||
Created: 1677649963,
|
||||
OwnedBy: "openai",
|
||||
Permission: permission,
|
||||
Root: "tts-1-1106",
|
||||
Parent: nil,
|
||||
},
|
||||
{
|
||||
Id: "tts-1-hd",
|
||||
Object: "model",
|
||||
Created: 1677649963,
|
||||
OwnedBy: "openai",
|
||||
Permission: permission,
|
||||
Root: "tts-1-hd",
|
||||
Parent: nil,
|
||||
},
|
||||
{
|
||||
Id: "tts-1-hd-1106",
|
||||
Object: "model",
|
||||
Created: 1677649963,
|
||||
OwnedBy: "openai",
|
||||
Permission: permission,
|
||||
Root: "tts-1-hd-1106",
|
||||
Parent: nil,
|
||||
},
|
||||
{
|
||||
Id: "gpt-3.5-turbo",
|
||||
Object: "model",
|
||||
@ -117,6 +162,15 @@ func init() {
|
||||
Root: "gpt-3.5-turbo-16k-0613",
|
||||
Parent: nil,
|
||||
},
|
||||
{
|
||||
Id: "gpt-3.5-turbo-1106",
|
||||
Object: "model",
|
||||
Created: 1699593571,
|
||||
OwnedBy: "openai",
|
||||
Permission: permission,
|
||||
Root: "gpt-3.5-turbo-1106",
|
||||
Parent: nil,
|
||||
},
|
||||
{
|
||||
Id: "gpt-3.5-turbo-instruct",
|
||||
Object: "model",
|
||||
@ -180,6 +234,24 @@ func init() {
|
||||
Root: "gpt-4-32k-0613",
|
||||
Parent: nil,
|
||||
},
|
||||
{
|
||||
Id: "gpt-4-1106-preview",
|
||||
Object: "model",
|
||||
Created: 1699593571,
|
||||
OwnedBy: "openai",
|
||||
Permission: permission,
|
||||
Root: "gpt-4-1106-preview",
|
||||
Parent: nil,
|
||||
},
|
||||
{
|
||||
Id: "gpt-4-vision-preview",
|
||||
Object: "model",
|
||||
Created: 1699593571,
|
||||
OwnedBy: "openai",
|
||||
Permission: permission,
|
||||
Root: "gpt-4-vision-preview",
|
||||
Parent: nil,
|
||||
},
|
||||
{
|
||||
Id: "text-embedding-ada-002",
|
||||
Object: "model",
|
||||
|
@ -5,7 +5,6 @@ import (
|
||||
"context"
|
||||
"encoding/json"
|
||||
"errors"
|
||||
"fmt"
|
||||
"github.com/gin-gonic/gin"
|
||||
"io"
|
||||
"net/http"
|
||||
@ -21,6 +20,22 @@ func relayAudioHelper(c *gin.Context, relayMode int) *OpenAIErrorWithStatusCode
|
||||
channelId := c.GetInt("channel_id")
|
||||
userId := c.GetInt("id")
|
||||
group := c.GetString("group")
|
||||
tokenName := c.GetString("token_name")
|
||||
|
||||
var ttsRequest TextToSpeechRequest
|
||||
if relayMode == RelayModeAudioSpeech {
|
||||
// Read JSON
|
||||
err := common.UnmarshalBodyReusable(c, &ttsRequest)
|
||||
// Check if JSON is valid
|
||||
if err != nil {
|
||||
return errorWrapper(err, "invalid_json", http.StatusBadRequest)
|
||||
}
|
||||
audioModel = ttsRequest.Model
|
||||
// Check if text is too long 4096
|
||||
if len(ttsRequest.Input) > 4096 {
|
||||
return errorWrapper(errors.New("input is too long (over 4096 characters)"), "text_too_long", http.StatusBadRequest)
|
||||
}
|
||||
}
|
||||
|
||||
preConsumedTokens := common.PreConsumedQuota
|
||||
modelRatio := common.GetModelRatio(audioModel)
|
||||
@ -31,22 +46,32 @@ func relayAudioHelper(c *gin.Context, relayMode int) *OpenAIErrorWithStatusCode
|
||||
if err != nil {
|
||||
return errorWrapper(err, "get_user_quota_failed", http.StatusInternalServerError)
|
||||
}
|
||||
if userQuota-preConsumedQuota < 0 {
|
||||
return errorWrapper(errors.New("user quota is not enough"), "insufficient_user_quota", http.StatusForbidden)
|
||||
}
|
||||
err = model.CacheDecreaseUserQuota(userId, preConsumedQuota)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "decrease_user_quota_failed", http.StatusInternalServerError)
|
||||
}
|
||||
if userQuota > 100*preConsumedQuota {
|
||||
// in this case, we do not pre-consume quota
|
||||
// because the user has enough quota
|
||||
preConsumedQuota = 0
|
||||
}
|
||||
if preConsumedQuota > 0 {
|
||||
err := model.PreConsumeTokenQuota(tokenId, preConsumedQuota)
|
||||
|
||||
quota := 0
|
||||
// Check if user quota is enough
|
||||
if relayMode == RelayModeAudioSpeech {
|
||||
quota = int(float64(len(ttsRequest.Input)) * modelRatio * groupRatio)
|
||||
if quota > userQuota {
|
||||
return errorWrapper(errors.New("user quota is not enough"), "insufficient_user_quota", http.StatusForbidden)
|
||||
}
|
||||
} else {
|
||||
if userQuota-preConsumedQuota < 0 {
|
||||
return errorWrapper(errors.New("user quota is not enough"), "insufficient_user_quota", http.StatusForbidden)
|
||||
}
|
||||
err = model.CacheDecreaseUserQuota(userId, preConsumedQuota)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "pre_consume_token_quota_failed", http.StatusForbidden)
|
||||
return errorWrapper(err, "decrease_user_quota_failed", http.StatusInternalServerError)
|
||||
}
|
||||
if userQuota > 100*preConsumedQuota {
|
||||
// in this case, we do not pre-consume quota
|
||||
// because the user has enough quota
|
||||
preConsumedQuota = 0
|
||||
}
|
||||
if preConsumedQuota > 0 {
|
||||
err := model.PreConsumeTokenQuota(tokenId, preConsumedQuota)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "pre_consume_token_quota_failed", http.StatusForbidden)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -93,47 +118,32 @@ func relayAudioHelper(c *gin.Context, relayMode int) *OpenAIErrorWithStatusCode
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_request_body_failed", http.StatusInternalServerError)
|
||||
}
|
||||
var audioResponse AudioResponse
|
||||
|
||||
defer func(ctx context.Context) {
|
||||
go func() {
|
||||
quota := countTokenText(audioResponse.Text, audioModel)
|
||||
if relayMode == RelayModeAudioSpeech {
|
||||
defer func(ctx context.Context) {
|
||||
go postConsumeQuota(ctx, tokenId, quota, userId, channelId, modelRatio, groupRatio, audioModel, tokenName)
|
||||
}(c.Request.Context())
|
||||
} else {
|
||||
responseBody, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "read_response_body_failed", http.StatusInternalServerError)
|
||||
}
|
||||
err = resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError)
|
||||
}
|
||||
var whisperResponse WhisperResponse
|
||||
err = json.Unmarshal(responseBody, &whisperResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "unmarshal_response_body_failed", http.StatusInternalServerError)
|
||||
}
|
||||
defer func(ctx context.Context) {
|
||||
quota := countTokenText(whisperResponse.Text, audioModel)
|
||||
quotaDelta := quota - preConsumedQuota
|
||||
err := model.PostConsumeTokenQuota(tokenId, quotaDelta)
|
||||
if err != nil {
|
||||
common.SysError("error consuming token remain quota: " + err.Error())
|
||||
}
|
||||
err = model.CacheUpdateUserQuota(userId)
|
||||
if err != nil {
|
||||
common.SysError("error update user quota cache: " + err.Error())
|
||||
}
|
||||
if quota != 0 {
|
||||
tokenName := c.GetString("token_name")
|
||||
logContent := fmt.Sprintf("模型倍率 %.2f,分组倍率 %.2f", modelRatio, groupRatio)
|
||||
model.RecordConsumeLog(ctx, userId, channelId, 0, 0, audioModel, tokenName, quota, logContent)
|
||||
model.UpdateUserUsedQuotaAndRequestCount(userId, quota)
|
||||
channelId := c.GetInt("channel_id")
|
||||
model.UpdateChannelUsedQuota(channelId, quota)
|
||||
}
|
||||
}()
|
||||
}(c.Request.Context())
|
||||
|
||||
responseBody, err := io.ReadAll(resp.Body)
|
||||
|
||||
if err != nil {
|
||||
return errorWrapper(err, "read_response_body_failed", http.StatusInternalServerError)
|
||||
go postConsumeQuota(ctx, tokenId, quotaDelta, userId, channelId, modelRatio, groupRatio, audioModel, tokenName)
|
||||
}(c.Request.Context())
|
||||
resp.Body = io.NopCloser(bytes.NewBuffer(responseBody))
|
||||
}
|
||||
err = resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError)
|
||||
}
|
||||
err = json.Unmarshal(responseBody, &audioResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "unmarshal_response_body_failed", http.StatusInternalServerError)
|
||||
}
|
||||
|
||||
resp.Body = io.NopCloser(bytes.NewBuffer(responseBody))
|
||||
|
||||
for k, v := range resp.Header {
|
||||
c.Writer.Header().Set(k, v[0])
|
||||
}
|
||||
|
@ -6,15 +6,28 @@ import (
|
||||
"encoding/json"
|
||||
"errors"
|
||||
"fmt"
|
||||
"github.com/gin-gonic/gin"
|
||||
"io"
|
||||
"net/http"
|
||||
"one-api/common"
|
||||
"one-api/model"
|
||||
|
||||
"github.com/gin-gonic/gin"
|
||||
)
|
||||
|
||||
func isWithinRange(element string, value int) bool {
|
||||
if _, ok := common.DalleGenerationImageAmounts[element]; !ok {
|
||||
return false
|
||||
}
|
||||
|
||||
min := common.DalleGenerationImageAmounts[element][0]
|
||||
max := common.DalleGenerationImageAmounts[element][1]
|
||||
|
||||
return value >= min && value <= max
|
||||
}
|
||||
|
||||
func relayImageHelper(c *gin.Context, relayMode int) *OpenAIErrorWithStatusCode {
|
||||
imageModel := "dall-e"
|
||||
imageModel := "dall-e-2"
|
||||
imageSize := "1024x1024"
|
||||
|
||||
tokenId := c.GetInt("token_id")
|
||||
channelType := c.GetInt("channel")
|
||||
@ -31,19 +44,44 @@ func relayImageHelper(c *gin.Context, relayMode int) *OpenAIErrorWithStatusCode
|
||||
}
|
||||
}
|
||||
|
||||
// Size validation
|
||||
if imageRequest.Size != "" {
|
||||
imageSize = imageRequest.Size
|
||||
}
|
||||
|
||||
// Model validation
|
||||
if imageRequest.Model != "" {
|
||||
imageModel = imageRequest.Model
|
||||
}
|
||||
|
||||
imageCostRatio, hasValidSize := common.DalleSizeRatios[imageModel][imageSize]
|
||||
|
||||
// Check if model is supported
|
||||
if hasValidSize {
|
||||
if imageRequest.Quality == "hd" && imageModel == "dall-e-3" {
|
||||
if imageSize == "1024x1024" {
|
||||
imageCostRatio *= 2
|
||||
} else {
|
||||
imageCostRatio *= 1.5
|
||||
}
|
||||
}
|
||||
} else {
|
||||
return errorWrapper(errors.New("size not supported for this image model"), "size_not_supported", http.StatusBadRequest)
|
||||
}
|
||||
|
||||
// Prompt validation
|
||||
if imageRequest.Prompt == "" {
|
||||
return errorWrapper(errors.New("prompt is required"), "required_field_missing", http.StatusBadRequest)
|
||||
return errorWrapper(errors.New("prompt is required"), "prompt_missing", http.StatusBadRequest)
|
||||
}
|
||||
|
||||
// Not "256x256", "512x512", or "1024x1024"
|
||||
if imageRequest.Size != "" && imageRequest.Size != "256x256" && imageRequest.Size != "512x512" && imageRequest.Size != "1024x1024" {
|
||||
return errorWrapper(errors.New("size must be one of 256x256, 512x512, or 1024x1024"), "invalid_field_value", http.StatusBadRequest)
|
||||
// Check prompt length
|
||||
if len(imageRequest.Prompt) > common.DalleImagePromptLengthLimitations[imageModel] {
|
||||
return errorWrapper(errors.New("prompt is too long"), "prompt_too_long", http.StatusBadRequest)
|
||||
}
|
||||
|
||||
// N should between 1 and 10
|
||||
if imageRequest.N != 0 && (imageRequest.N < 1 || imageRequest.N > 10) {
|
||||
return errorWrapper(errors.New("n must be between 1 and 10"), "invalid_field_value", http.StatusBadRequest)
|
||||
// Number of generated images validation
|
||||
if isWithinRange(imageModel, imageRequest.N) == false {
|
||||
return errorWrapper(errors.New("invalid value of n"), "n_not_within_range", http.StatusBadRequest)
|
||||
}
|
||||
|
||||
// map model name
|
||||
@ -82,16 +120,7 @@ func relayImageHelper(c *gin.Context, relayMode int) *OpenAIErrorWithStatusCode
|
||||
ratio := modelRatio * groupRatio
|
||||
userQuota, err := model.CacheGetUserQuota(userId)
|
||||
|
||||
sizeRatio := 1.0
|
||||
// Size
|
||||
if imageRequest.Size == "256x256" {
|
||||
sizeRatio = 1
|
||||
} else if imageRequest.Size == "512x512" {
|
||||
sizeRatio = 1.125
|
||||
} else if imageRequest.Size == "1024x1024" {
|
||||
sizeRatio = 1.25
|
||||
}
|
||||
quota := int(ratio*sizeRatio*1000) * imageRequest.N
|
||||
quota := int(ratio*imageCostRatio*1000) * imageRequest.N
|
||||
|
||||
if consumeQuota && userQuota-quota < 0 {
|
||||
return errorWrapper(errors.New("user quota is not enough"), "insufficient_user_quota", http.StatusForbidden)
|
||||
|
@ -369,6 +369,8 @@ func relayTextHelper(c *gin.Context, relayMode int) *OpenAIErrorWithStatusCode {
|
||||
}
|
||||
case APITypeTencent:
|
||||
req.Header.Set("Authorization", apiKey)
|
||||
case APITypePaLM:
|
||||
// do not set Authorization header
|
||||
default:
|
||||
req.Header.Set("Authorization", "Bearer "+apiKey)
|
||||
}
|
||||
|
@ -1,11 +1,13 @@
|
||||
package controller
|
||||
|
||||
import (
|
||||
"context"
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"io"
|
||||
"net/http"
|
||||
"one-api/common"
|
||||
"one-api/model"
|
||||
"strconv"
|
||||
"strings"
|
||||
|
||||
@ -192,3 +194,20 @@ func getFullRequestURL(baseURL string, requestURL string, channelType int) strin
|
||||
|
||||
return fullRequestURL
|
||||
}
|
||||
|
||||
func postConsumeQuota(ctx context.Context, tokenId int, quota int, userId int, channelId int, modelRatio float64, groupRatio float64, modelName string, tokenName string) {
|
||||
err := model.PostConsumeTokenQuota(tokenId, quota)
|
||||
if err != nil {
|
||||
common.SysError("error consuming token remain quota: " + err.Error())
|
||||
}
|
||||
err = model.CacheUpdateUserQuota(userId)
|
||||
if err != nil {
|
||||
common.SysError("error update user quota cache: " + err.Error())
|
||||
}
|
||||
if quota != 0 {
|
||||
logContent := fmt.Sprintf("模型倍率 %.2f,分组倍率 %.2f", modelRatio, groupRatio)
|
||||
model.RecordConsumeLog(ctx, userId, channelId, 0, 0, modelName, tokenName, quota, logContent)
|
||||
model.UpdateUserUsedQuotaAndRequestCount(userId, quota)
|
||||
model.UpdateChannelUsedQuota(channelId, quota)
|
||||
}
|
||||
}
|
||||
|
@ -24,7 +24,9 @@ const (
|
||||
RelayModeModerations
|
||||
RelayModeImagesGenerations
|
||||
RelayModeEdits
|
||||
RelayModeAudio
|
||||
RelayModeAudioSpeech
|
||||
RelayModeAudioTranscription
|
||||
RelayModeAudioTranslation
|
||||
)
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/chat
|
||||
@ -77,16 +79,30 @@ type TextRequest struct {
|
||||
//Stream bool `json:"stream"`
|
||||
}
|
||||
|
||||
// ImageRequest docs: https://platform.openai.com/docs/api-reference/images/create
|
||||
type ImageRequest struct {
|
||||
Prompt string `json:"prompt"`
|
||||
N int `json:"n"`
|
||||
Size string `json:"size"`
|
||||
Model string `json:"model"`
|
||||
Prompt string `json:"prompt" binding:"required"`
|
||||
N int `json:"n"`
|
||||
Size string `json:"size"`
|
||||
Quality string `json:"quality"`
|
||||
ResponseFormat string `json:"response_format"`
|
||||
Style string `json:"style"`
|
||||
User string `json:"user"`
|
||||
}
|
||||
|
||||
type AudioResponse struct {
|
||||
type WhisperResponse struct {
|
||||
Text string `json:"text,omitempty"`
|
||||
}
|
||||
|
||||
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 Usage struct {
|
||||
PromptTokens int `json:"prompt_tokens"`
|
||||
CompletionTokens int `json:"completion_tokens"`
|
||||
@ -183,14 +199,22 @@ func Relay(c *gin.Context) {
|
||||
relayMode = RelayModeImagesGenerations
|
||||
} else if strings.HasPrefix(c.Request.URL.Path, "/v1/edits") {
|
||||
relayMode = RelayModeEdits
|
||||
} else if strings.HasPrefix(c.Request.URL.Path, "/v1/audio") {
|
||||
relayMode = RelayModeAudio
|
||||
} else if strings.HasPrefix(c.Request.URL.Path, "/v1/audio/speech") {
|
||||
relayMode = RelayModeAudioSpeech
|
||||
} else if strings.HasPrefix(c.Request.URL.Path, "/v1/audio/transcription") {
|
||||
relayMode = RelayModeAudioTranscription
|
||||
} else if strings.HasPrefix(c.Request.URL.Path, "/v1/audio/translation") {
|
||||
relayMode = RelayModeAudioTranslation
|
||||
}
|
||||
var err *OpenAIErrorWithStatusCode
|
||||
switch relayMode {
|
||||
case RelayModeImagesGenerations:
|
||||
err = relayImageHelper(c, relayMode)
|
||||
case RelayModeAudio:
|
||||
case RelayModeAudioSpeech:
|
||||
fallthrough
|
||||
case RelayModeAudioTranslation:
|
||||
fallthrough
|
||||
case RelayModeAudioTranscription:
|
||||
err = relayAudioHelper(c, relayMode)
|
||||
default:
|
||||
err = relayTextHelper(c, relayMode)
|
||||
|
@ -9,19 +9,19 @@ services:
|
||||
ports:
|
||||
- "3000:3000"
|
||||
volumes:
|
||||
- ./data:/data
|
||||
- ./data/oneapi:/data
|
||||
- ./logs:/app/logs
|
||||
environment:
|
||||
- SQL_DSN=root:123456@tcp(host.docker.internal:3306)/one-api # 修改此行,或注释掉以使用 SQLite 作为数据库
|
||||
- SQL_DSN=oneapi:123456@tcp(db:3306)/one-api # 修改此行,或注释掉以使用 SQLite 作为数据库
|
||||
- REDIS_CONN_STRING=redis://redis
|
||||
- SESSION_SECRET=random_string # 修改为随机字符串
|
||||
- TZ=Asia/Shanghai
|
||||
# - NODE_TYPE=slave # 多机部署时从节点取消注释该行
|
||||
# - SYNC_FREQUENCY=60 # 需要定期从数据库加载数据时取消注释该行
|
||||
# - FRONTEND_BASE_URL=https://openai.justsong.cn # 多机部署时从节点取消注释该行
|
||||
|
||||
depends_on:
|
||||
- redis
|
||||
- db
|
||||
healthcheck:
|
||||
test: [ "CMD-SHELL", "wget -q -O - http://localhost:3000/api/status | grep -o '\"success\":\\s*true' | awk -F: '{print $2}'" ]
|
||||
interval: 30s
|
||||
@ -32,3 +32,18 @@ services:
|
||||
image: redis:latest
|
||||
container_name: redis
|
||||
restart: always
|
||||
|
||||
db:
|
||||
image: mysql:8.2.0
|
||||
restart: always
|
||||
container_name: mysql
|
||||
volumes:
|
||||
- ./data/mysql:/var/lib/mysql # 挂载目录,持久化存储
|
||||
ports:
|
||||
- '3306:3306'
|
||||
environment:
|
||||
TZ: Asia/Shanghai # 设置时区
|
||||
MYSQL_ROOT_PASSWORD: 'OneAPI@justsong' # 设置 root 用户的密码
|
||||
MYSQL_USER: oneapi # 创建专用用户
|
||||
MYSQL_PASSWORD: '123456' # 设置专用用户密码
|
||||
MYSQL_DATABASE: one-api # 自动创建数据库
|
@ -40,10 +40,7 @@ func Distribute() func(c *gin.Context) {
|
||||
} else {
|
||||
// Select a channel for the user
|
||||
var modelRequest ModelRequest
|
||||
var err error
|
||||
if !strings.HasPrefix(c.Request.URL.Path, "/v1/audio") {
|
||||
err = common.UnmarshalBodyReusable(c, &modelRequest)
|
||||
}
|
||||
err := common.UnmarshalBodyReusable(c, &modelRequest)
|
||||
if err != nil {
|
||||
abortWithMessage(c, http.StatusBadRequest, "无效的请求")
|
||||
return
|
||||
@ -60,10 +57,10 @@ func Distribute() func(c *gin.Context) {
|
||||
}
|
||||
if strings.HasPrefix(c.Request.URL.Path, "/v1/images/generations") {
|
||||
if modelRequest.Model == "" {
|
||||
modelRequest.Model = "dall-e"
|
||||
modelRequest.Model = "dall-e-2"
|
||||
}
|
||||
}
|
||||
if strings.HasPrefix(c.Request.URL.Path, "/v1/audio") {
|
||||
if strings.HasPrefix(c.Request.URL.Path, "/v1/audio/transcriptions") || strings.HasPrefix(c.Request.URL.Path, "/v1/audio/translations") {
|
||||
if modelRequest.Model == "" {
|
||||
modelRequest.Model = "whisper-1"
|
||||
}
|
||||
|
@ -94,7 +94,7 @@ func GetAllLogs(logType int, startTimestamp int64, endTimestamp int64, modelName
|
||||
tx = tx.Where("created_at <= ?", endTimestamp)
|
||||
}
|
||||
if channel != 0 {
|
||||
tx = tx.Where("channel = ?", channel)
|
||||
tx = tx.Where("channel_id = ?", channel)
|
||||
}
|
||||
err = tx.Order("id desc").Limit(num).Offset(startIdx).Find(&logs).Error
|
||||
return logs, err
|
||||
@ -151,7 +151,7 @@ func SumUsedQuota(logType int, startTimestamp int64, endTimestamp int64, modelNa
|
||||
tx = tx.Where("model_name = ?", modelName)
|
||||
}
|
||||
if channel != 0 {
|
||||
tx = tx.Where("channel = ?", channel)
|
||||
tx = tx.Where("channel_id = ?", channel)
|
||||
}
|
||||
tx.Where("type = ?", LogTypeConsume).Scan("a)
|
||||
return quota
|
||||
|
@ -29,6 +29,7 @@ func SetRelayRouter(router *gin.Engine) {
|
||||
relayV1Router.POST("/engines/:model/embeddings", controller.Relay)
|
||||
relayV1Router.POST("/audio/transcriptions", controller.Relay)
|
||||
relayV1Router.POST("/audio/translations", controller.Relay)
|
||||
relayV1Router.POST("/audio/speech", controller.Relay)
|
||||
relayV1Router.GET("/files", controller.RelayNotImplemented)
|
||||
relayV1Router.POST("/files", controller.RelayNotImplemented)
|
||||
relayV1Router.DELETE("/files/:id", controller.RelayNotImplemented)
|
||||
|
@ -286,17 +286,15 @@ const ChannelsTable = () => {
|
||||
if (channels.length === 0) return;
|
||||
setLoading(true);
|
||||
let sortedChannels = [...channels];
|
||||
if (typeof sortedChannels[0][key] === 'string') {
|
||||
sortedChannels.sort((a, b) => {
|
||||
sortedChannels.sort((a, b) => {
|
||||
if (!isNaN(a[key])) {
|
||||
// If the value is numeric, subtract to sort
|
||||
return a[key] - b[key];
|
||||
} else {
|
||||
// If the value is not numeric, sort as strings
|
||||
return ('' + a[key]).localeCompare(b[key]);
|
||||
});
|
||||
} else {
|
||||
sortedChannels.sort((a, b) => {
|
||||
if (a[key] === b[key]) return 0;
|
||||
if (a[key] > b[key]) return -1;
|
||||
if (a[key] < b[key]) return 1;
|
||||
});
|
||||
}
|
||||
}
|
||||
});
|
||||
if (sortedChannels[0].id === channels[0].id) {
|
||||
sortedChannels.reverse();
|
||||
}
|
||||
@ -304,6 +302,7 @@ const ChannelsTable = () => {
|
||||
setLoading(false);
|
||||
};
|
||||
|
||||
|
||||
return (
|
||||
<>
|
||||
<Form onSubmit={searchChannels}>
|
||||
|
@ -130,7 +130,13 @@ const RedemptionsTable = () => {
|
||||
setLoading(true);
|
||||
let sortedRedemptions = [...redemptions];
|
||||
sortedRedemptions.sort((a, b) => {
|
||||
return ('' + a[key]).localeCompare(b[key]);
|
||||
if (!isNaN(a[key])) {
|
||||
// If the value is numeric, subtract to sort
|
||||
return a[key] - b[key];
|
||||
} else {
|
||||
// If the value is not numeric, sort as strings
|
||||
return ('' + a[key]).localeCompare(b[key]);
|
||||
}
|
||||
});
|
||||
if (sortedRedemptions[0].id === redemptions[0].id) {
|
||||
sortedRedemptions.reverse();
|
||||
|
@ -228,7 +228,13 @@ const TokensTable = () => {
|
||||
setLoading(true);
|
||||
let sortedTokens = [...tokens];
|
||||
sortedTokens.sort((a, b) => {
|
||||
return ('' + a[key]).localeCompare(b[key]);
|
||||
if (!isNaN(a[key])) {
|
||||
// If the value is numeric, subtract to sort
|
||||
return a[key] - b[key];
|
||||
} else {
|
||||
// If the value is not numeric, sort as strings
|
||||
return ('' + a[key]).localeCompare(b[key]);
|
||||
}
|
||||
});
|
||||
if (sortedTokens[0].id === tokens[0].id) {
|
||||
sortedTokens.reverse();
|
||||
|
@ -133,7 +133,13 @@ const UsersTable = () => {
|
||||
setLoading(true);
|
||||
let sortedUsers = [...users];
|
||||
sortedUsers.sort((a, b) => {
|
||||
return ('' + a[key]).localeCompare(b[key]);
|
||||
if (!isNaN(a[key])) {
|
||||
// If the value is numeric, subtract to sort
|
||||
return a[key] - b[key];
|
||||
} else {
|
||||
// If the value is not numeric, sort as strings
|
||||
return ('' + a[key]).localeCompare(b[key]);
|
||||
}
|
||||
});
|
||||
if (sortedUsers[0].id === users[0].id) {
|
||||
sortedUsers.reverse();
|
||||
|
Loading…
Reference in New Issue
Block a user