Files
Calcium-Ion 128089fa7d feat(i18n): translate web console messages in the frontend and AI-client errors in the backend (#7712)
* feat(i18n): translate web console messages in the frontend and AI-client errors in the backend

Chinese text was hard-coded in API messages, stored log content, emails and
server logs, so it reached users of every interface language.

Text is now translated where its reader is:

- Web console APIs return the English source text as message_key with
  message_params, and the web console translates it in all seven languages.
  message keeps the English text for other API callers.
- Errors returned to AI clients, emails and notifications are translated by
  the backend (en, zh-CN, zh-TW) in the language saved on the account, then
  the language of the request's Accept-Language header.
- A reader who states no language still gets the original Chinese text of the
  messages that were Chinese before, word for word. Gateways that use another
  new-api as their upstream match that text, for example to disable a channel
  whose account ran out of quota.
- Usage, top-up and system log content is stored as content_parts (key and
  params) and rendered in the viewer's language. Task fail reasons and refund
  reasons written by the gateway are English keys. Rows written earlier are
  shown as before.
- Server logs are English.

Also:

- The saved interface language zhTW, and zh-HK, zh-MO and zh-Hant, now select
  Traditional Chinese in the backend instead of Simplified Chinese.
- The built-in group descriptions are translated; descriptions an
  administrator saved are shown as written.
- .agents/rules/i18n.md records the conventions. Tests in i18n/ fail on a
  non-English string literal, on a web console message without translations
  and on a locale key without a constant.

* feat(i18n): print server logs in Chinese when LOG_LANGUAGE asks for it

Server log lines are English by default. With LOG_LANGUAGE=zh-CN, the lines
that were Chinese before print their original Chinese text.

common.LogText formats a log line from its English format, which is also the
key of its Chinese text in common/log_text.zh-CN.json. A line without an entry
prints in English. go vet checks the arguments of every call, and
TestServerLogTexts checks that each entry still matches a call and has the
same verbs as its key.

* docs: list LOG_LANGUAGE in the docker compose example

* feat(i18n): translate every server log line and add DEFAULT_LANGUAGE

Every line the gateway prints goes through common.LogText. With
DEFAULT_LANGUAGE=zh-CN, the lines that have a Chinese text in
common/log_text.zh-CN.json print it and the others print English.

DEFAULT_LANGUAGE replaces LOG_LANGUAGE. It also sets the language of
backend messages, emails and notifications for a reader who states no
language: en, zh-CN or zh-TW, English when unset. The list of messages
that stayed Chinese for such readers is removed.

Review fixes:
- Channel test logs store the token name "Model test"; the console shows
  it in the interface language.
- Task fail reasons written by the gateway are fixed sentences the console
  translates. The HTTP status and the upstream detail go to the server log
  when a polled task is failed.
- The auto-disable reason of a slow channel is written in DEFAULT_LANGUAGE.

Also:
- Drop the repository-scanning lint tests, the i18n rules file and its
  read gate. AGENTS.md keeps the conventions in four lines.
- Payment error toasts keep their previous text and only add the
  translated message key.
- Remove guards and helpers that no caller needs.

* fix(i18n): address review on language lookup, notices and error responses

- Relay requests no longer load the user a second time to find the
  language: the settings TokenAuth put into the request are used as they
  are, also when they hold no language.
- Upstream model update notices are rendered in each recipient's saved
  language, DEFAULT_LANGUAGE when none.
- /api/usage/token and /api/log/token answer with backend-translated
  messages again, with the keys and status codes used before this PR.
  Their callers are scripts, not the web console.
- Webhook notifications fill {{value}} placeholders like the other
  senders. Running the rendered text through Sprintf appended
  %!(EXTRA ...) and broke %2F in links.
- RootUserLanguage reads the setting of the root user it already loaded.
- zh_TW and zh_HK are read as Traditional Chinese.
- Add common.ApiErrorStatus for error responses under another HTTP status
  and use it where those responses were built by hand.
- Remove middleware.GetLanguage, which had no callers.
2026-10-09 21:39:51 +08:00

374 lines
10 KiB
Go

package controller
import (
"fmt"
"net/http"
"strings"
"time"
"github.com/QuantumNous/new-api/common"
"github.com/QuantumNous/new-api/constant"
"github.com/QuantumNous/new-api/model"
"github.com/QuantumNous/new-api/pkg/jsplugin"
"github.com/QuantumNous/new-api/relay"
"github.com/QuantumNous/new-api/relay/channel/ai360"
"github.com/QuantumNous/new-api/relay/channel/lingyiwanwu"
"github.com/QuantumNous/new-api/relay/channel/minimax"
"github.com/QuantumNous/new-api/relay/channel/moonshot"
relaycommon "github.com/QuantumNous/new-api/relay/common"
"github.com/QuantumNous/new-api/relay/helper"
"github.com/QuantumNous/new-api/relaykit/dto"
"github.com/QuantumNous/new-api/relaykit/types"
"github.com/QuantumNous/new-api/service"
"github.com/QuantumNous/new-api/setting/operation_setting"
"github.com/QuantumNous/new-api/setting/ratio_setting"
"github.com/gin-gonic/gin"
"github.com/samber/lo"
)
// https://platform.openai.com/docs/api-reference/models/list
var openAIModels []dto.OpenAIModels
var openAIModelsMap map[string]dto.OpenAIModels
var channelId2Models map[int][]string
func init() {
// https://platform.openai.com/docs/models/model-endpoint-compatibility
for i := range constant.APITypeDummy {
if i == constant.APITypeAIProxyLibrary {
continue
}
adaptor := relay.GetAdaptor(i)
channelName := adaptor.GetChannelName()
modelNames := adaptor.GetModelList()
for _, modelName := range modelNames {
openAIModels = append(openAIModels, dto.OpenAIModels{
Id: modelName,
Object: "model",
Created: 1626777600,
OwnedBy: channelName,
})
}
}
for _, modelName := range ai360.ModelList {
openAIModels = append(openAIModels, dto.OpenAIModels{
Id: modelName,
Object: "model",
Created: 1626777600,
OwnedBy: ai360.ChannelName,
})
}
for _, modelName := range moonshot.ModelList {
openAIModels = append(openAIModels, dto.OpenAIModels{
Id: modelName,
Object: "model",
Created: 1626777600,
OwnedBy: moonshot.ChannelName,
})
}
for _, modelName := range lingyiwanwu.ModelList {
openAIModels = append(openAIModels, dto.OpenAIModels{
Id: modelName,
Object: "model",
Created: 1626777600,
OwnedBy: lingyiwanwu.ChannelName,
})
}
for _, modelName := range minimax.ModelList {
openAIModels = append(openAIModels, dto.OpenAIModels{
Id: modelName,
Object: "model",
Created: 1626777600,
OwnedBy: minimax.ChannelName,
})
}
for modelName, _ := range constant.MidjourneyModel2Action {
openAIModels = append(openAIModels, dto.OpenAIModels{
Id: modelName,
Object: "model",
Created: 1626777600,
OwnedBy: "midjourney",
})
}
openAIModelsMap = make(map[string]dto.OpenAIModels)
for _, aiModel := range openAIModels {
openAIModelsMap[aiModel.Id] = aiModel
}
channelId2Models = make(map[int][]string)
for i := 1; i <= constant.ChannelTypeDummy; i++ {
apiType, success := common.ChannelType2APIType(i)
if !success || apiType == constant.APITypeAIProxyLibrary {
if plugin, ok := jsplugin.DefaultRegistry.GetByChannelType(i); ok {
channelId2Models[i] = append([]string(nil), plugin.Meta.Models...)
}
continue
}
meta := &relaycommon.RelayInfo{ChannelMeta: &relaycommon.ChannelMeta{
ChannelType: i,
}}
adaptor := relay.GetAdaptor(apiType)
adaptor.Init(meta)
channelId2Models[i] = adaptor.GetModelList()
if len(channelId2Models[i]) == 0 {
if plugin, ok := jsplugin.DefaultRegistry.GetByChannelType(i); ok {
channelId2Models[i] = append([]string(nil), plugin.Meta.Models...)
}
}
}
openAIModels = lo.UniqBy(openAIModels, func(m dto.OpenAIModels) string {
return m.Id
})
}
func channelOwnerName(channelType int) string {
apiType, success := common.ChannelType2APIType(channelType)
if !success {
return strings.ToLower(constant.GetChannelTypeName(channelType))
}
adaptor := relay.GetAdaptor(apiType)
if adaptor == nil {
return strings.ToLower(constant.GetChannelTypeName(channelType))
}
adaptor.Init(&relaycommon.RelayInfo{ChannelMeta: &relaycommon.ChannelMeta{
ChannelType: channelType,
}})
if name := strings.TrimSpace(adaptor.GetChannelName()); name != "" {
return name
}
return strings.ToLower(constant.GetChannelTypeName(channelType))
}
func getPreferredModelOwners(modelNames []string, groups []string) map[string]string {
channelTypes, err := model.GetPreferredModelOwnerChannelTypes(modelNames, groups)
if err != nil {
common.SysLog(common.LogText("GetPreferredModelOwnerChannelTypes error: %v", err))
return map[string]string{}
}
ownerByChannelType := make(map[int]string)
owners := make(map[string]string, len(channelTypes))
for modelName, channelType := range channelTypes {
owner, ok := ownerByChannelType[channelType]
if !ok {
owner = channelOwnerName(channelType)
ownerByChannelType[channelType] = owner
}
if owner != "" {
owners[modelName] = owner
}
}
return owners
}
func buildOpenAIModel(modelName string, ownerByModel map[string]string) dto.OpenAIModels {
var oaiModel dto.OpenAIModels
if staticModel, ok := openAIModelsMap[modelName]; ok {
oaiModel = staticModel
} else {
oaiModel = dto.OpenAIModels{
Id: modelName,
Object: "model",
Created: 1626777600,
OwnedBy: "custom",
}
}
if owner, ok := ownerByModel[modelName]; ok && owner != "" {
oaiModel.OwnedBy = owner
}
oaiModel.SupportedEndpointTypes = model.GetModelSupportEndpointTypes(modelName)
return oaiModel
}
type modelListGroups struct {
userGroup string
tokenGroup string
ownerGroups []string
}
func getModelListGroups(c *gin.Context) (modelListGroups, error) {
tokenGroup := common.GetContextKeyString(c, constant.ContextKeyTokenGroup)
userGroup := common.GetContextKeyString(c, constant.ContextKeyUserGroup)
if userGroup == "" && (tokenGroup == "" || tokenGroup == "auto") {
var err error
userGroup, err = model.GetUserGroup(c.GetInt("id"), false)
if err != nil {
return modelListGroups{}, err
}
}
if tokenGroup == "auto" {
return modelListGroups{
userGroup: userGroup,
tokenGroup: tokenGroup,
ownerGroups: service.GetRequestAutoGroups(c, userGroup),
}, nil
}
group := userGroup
if tokenGroup != "" {
group = tokenGroup
}
return modelListGroups{
userGroup: userGroup,
tokenGroup: tokenGroup,
ownerGroups: []string{group},
}, nil
}
func ListModels(c *gin.Context, modelType int) {
acceptUnsetRatioModel := operation_setting.SelfUseModeEnabled
if !acceptUnsetRatioModel {
userId := c.GetInt("id")
if userId > 0 {
userSettings, _ := model.GetUserSetting(userId, false)
if userSettings.AcceptUnsetRatioModel {
acceptUnsetRatioModel = true
}
}
}
userModelNames := make([]string, 0)
groups, err := getModelListGroups(c)
if err != nil {
c.JSON(http.StatusOK, gin.H{
"success": false,
"message": "get user group failed",
})
return
}
ownerGroups := groups.ownerGroups
modelLimitEnable := common.GetContextKeyBool(c, constant.ContextKeyTokenModelLimitEnabled)
var tokenModelLimit map[string]bool
if modelLimitEnable {
s, ok := common.GetContextKey(c, constant.ContextKeyTokenModelLimit)
if ok {
tokenModelLimit, _ = s.(map[string]bool)
}
if tokenModelLimit == nil {
tokenModelLimit = map[string]bool{}
}
}
models := service.GetGroupsEnabledModels(ownerGroups)
for _, modelName := range models {
if modelLimitEnable {
matchingName := ratio_setting.RoutingMatchModelName(modelName)
if !tokenModelLimit[modelName] && !tokenModelLimit[matchingName] {
continue
}
}
if !acceptUnsetRatioModel && !helper.HasModelBillingConfig(modelName) {
continue
}
userModelNames = append(userModelNames, modelName)
}
ownerByModel := map[string]string{}
if len(ownerGroups) > 0 {
ownerByModel = getPreferredModelOwners(userModelNames, ownerGroups)
}
userOpenAiModels := make([]dto.OpenAIModels, 0, len(userModelNames))
for _, modelName := range userModelNames {
userOpenAiModels = append(userOpenAiModels, buildOpenAIModel(modelName, ownerByModel))
}
switch modelType {
case constant.ChannelTypeAnthropic:
useranthropicModels := make([]dto.AnthropicModel, len(userOpenAiModels))
for i, model := range userOpenAiModels {
useranthropicModels[i] = dto.AnthropicModel{
ID: model.Id,
CreatedAt: time.Unix(int64(model.Created), 0).UTC().Format(time.RFC3339),
DisplayName: model.Id,
Type: "model",
}
}
firstID := ""
lastID := ""
if len(useranthropicModels) > 0 {
firstID = useranthropicModels[0].ID
lastID = useranthropicModels[len(useranthropicModels)-1].ID
}
c.JSON(200, gin.H{
"data": useranthropicModels,
"first_id": firstID,
"has_more": false,
"last_id": lastID,
})
case constant.ChannelTypeGemini:
userGeminiModels := make([]dto.GeminiModel, len(userOpenAiModels))
for i, model := range userOpenAiModels {
userGeminiModels[i] = dto.GeminiModel{
Name: model.Id,
DisplayName: model.Id,
}
}
c.JSON(200, gin.H{
"models": userGeminiModels,
"nextPageToken": nil,
})
default:
c.JSON(200, gin.H{
"success": true,
"data": userOpenAiModels,
"object": "list",
})
}
}
func ChannelListModels(c *gin.Context) {
c.JSON(200, gin.H{
"success": true,
"data": openAIModels,
})
}
func DashboardListModels(c *gin.Context) {
modelsByChannel := make(map[int][]string, len(channelId2Models))
for channelType, models := range channelId2Models {
modelsByChannel[channelType] = append([]string(nil), models...)
}
for channelType := 1; channelType <= constant.ChannelTypeDummy; channelType++ {
if plugin, ok := jsplugin.DefaultRegistry.GetByChannelType(channelType); ok {
modelsByChannel[channelType] = append([]string(nil), plugin.Meta.Models...)
}
}
c.JSON(200, gin.H{
"success": true,
"data": modelsByChannel,
})
}
func EnabledListModels(c *gin.Context) {
c.JSON(200, gin.H{
"success": true,
"data": model.GetEnabledModels(),
})
}
func RetrieveModel(c *gin.Context, modelType int) {
modelId := c.Param("model")
if aiModel, ok := openAIModelsMap[modelId]; ok {
switch modelType {
case constant.ChannelTypeAnthropic:
c.JSON(200, dto.AnthropicModel{
ID: aiModel.Id,
CreatedAt: time.Unix(int64(aiModel.Created), 0).UTC().Format(time.RFC3339),
DisplayName: aiModel.Id,
Type: "model",
})
default:
c.JSON(200, aiModel)
}
} else {
openAIError := types.OpenAIError{
Message: fmt.Sprintf("The model '%s' does not exist", modelId),
Type: "invalid_request_error",
Param: "model",
Code: "model_not_found",
}
c.JSON(200, gin.H{
"error": openAIError,
})
}
}