mirror of
https://github.com/QuantumNous/new-api.git
synced 2026-10-28 08:35:33 +08:00
* 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.
374 lines
10 KiB
Go
374 lines
10 KiB
Go
package controller
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import (
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"fmt"
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"net/http"
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"strings"
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"time"
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"github.com/QuantumNous/new-api/common"
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"github.com/QuantumNous/new-api/constant"
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"github.com/QuantumNous/new-api/model"
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"github.com/QuantumNous/new-api/pkg/jsplugin"
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"github.com/QuantumNous/new-api/relay"
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"github.com/QuantumNous/new-api/relay/channel/ai360"
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"github.com/QuantumNous/new-api/relay/channel/lingyiwanwu"
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"github.com/QuantumNous/new-api/relay/channel/minimax"
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"github.com/QuantumNous/new-api/relay/channel/moonshot"
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relaycommon "github.com/QuantumNous/new-api/relay/common"
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"github.com/QuantumNous/new-api/relay/helper"
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"github.com/QuantumNous/new-api/relaykit/dto"
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"github.com/QuantumNous/new-api/relaykit/types"
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"github.com/QuantumNous/new-api/service"
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"github.com/QuantumNous/new-api/setting/operation_setting"
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"github.com/QuantumNous/new-api/setting/ratio_setting"
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"github.com/gin-gonic/gin"
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"github.com/samber/lo"
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)
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// https://platform.openai.com/docs/api-reference/models/list
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var openAIModels []dto.OpenAIModels
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var openAIModelsMap map[string]dto.OpenAIModels
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var channelId2Models map[int][]string
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func init() {
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// https://platform.openai.com/docs/models/model-endpoint-compatibility
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for i := range constant.APITypeDummy {
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if i == constant.APITypeAIProxyLibrary {
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continue
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}
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adaptor := relay.GetAdaptor(i)
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channelName := adaptor.GetChannelName()
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modelNames := adaptor.GetModelList()
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for _, modelName := range modelNames {
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openAIModels = append(openAIModels, dto.OpenAIModels{
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Id: modelName,
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Object: "model",
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Created: 1626777600,
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OwnedBy: channelName,
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})
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}
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}
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for _, modelName := range ai360.ModelList {
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openAIModels = append(openAIModels, dto.OpenAIModels{
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Id: modelName,
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Object: "model",
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Created: 1626777600,
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OwnedBy: ai360.ChannelName,
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})
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}
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for _, modelName := range moonshot.ModelList {
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openAIModels = append(openAIModels, dto.OpenAIModels{
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Id: modelName,
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Object: "model",
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Created: 1626777600,
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OwnedBy: moonshot.ChannelName,
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})
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}
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for _, modelName := range lingyiwanwu.ModelList {
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openAIModels = append(openAIModels, dto.OpenAIModels{
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Id: modelName,
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Object: "model",
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Created: 1626777600,
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OwnedBy: lingyiwanwu.ChannelName,
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})
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}
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for _, modelName := range minimax.ModelList {
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openAIModels = append(openAIModels, dto.OpenAIModels{
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Id: modelName,
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Object: "model",
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Created: 1626777600,
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OwnedBy: minimax.ChannelName,
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})
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}
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for modelName, _ := range constant.MidjourneyModel2Action {
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openAIModels = append(openAIModels, dto.OpenAIModels{
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Id: modelName,
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Object: "model",
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Created: 1626777600,
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OwnedBy: "midjourney",
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})
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}
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openAIModelsMap = make(map[string]dto.OpenAIModels)
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for _, aiModel := range openAIModels {
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openAIModelsMap[aiModel.Id] = aiModel
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}
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channelId2Models = make(map[int][]string)
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for i := 1; i <= constant.ChannelTypeDummy; i++ {
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apiType, success := common.ChannelType2APIType(i)
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if !success || apiType == constant.APITypeAIProxyLibrary {
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if plugin, ok := jsplugin.DefaultRegistry.GetByChannelType(i); ok {
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channelId2Models[i] = append([]string(nil), plugin.Meta.Models...)
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}
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continue
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}
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meta := &relaycommon.RelayInfo{ChannelMeta: &relaycommon.ChannelMeta{
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ChannelType: i,
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}}
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adaptor := relay.GetAdaptor(apiType)
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adaptor.Init(meta)
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channelId2Models[i] = adaptor.GetModelList()
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if len(channelId2Models[i]) == 0 {
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if plugin, ok := jsplugin.DefaultRegistry.GetByChannelType(i); ok {
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channelId2Models[i] = append([]string(nil), plugin.Meta.Models...)
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}
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}
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}
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openAIModels = lo.UniqBy(openAIModels, func(m dto.OpenAIModels) string {
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return m.Id
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})
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}
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func channelOwnerName(channelType int) string {
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apiType, success := common.ChannelType2APIType(channelType)
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if !success {
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return strings.ToLower(constant.GetChannelTypeName(channelType))
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}
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adaptor := relay.GetAdaptor(apiType)
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if adaptor == nil {
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return strings.ToLower(constant.GetChannelTypeName(channelType))
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}
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adaptor.Init(&relaycommon.RelayInfo{ChannelMeta: &relaycommon.ChannelMeta{
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ChannelType: channelType,
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}})
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if name := strings.TrimSpace(adaptor.GetChannelName()); name != "" {
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return name
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}
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return strings.ToLower(constant.GetChannelTypeName(channelType))
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}
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func getPreferredModelOwners(modelNames []string, groups []string) map[string]string {
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channelTypes, err := model.GetPreferredModelOwnerChannelTypes(modelNames, groups)
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if err != nil {
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common.SysLog(common.LogText("GetPreferredModelOwnerChannelTypes error: %v", err))
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return map[string]string{}
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}
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ownerByChannelType := make(map[int]string)
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owners := make(map[string]string, len(channelTypes))
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for modelName, channelType := range channelTypes {
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owner, ok := ownerByChannelType[channelType]
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if !ok {
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owner = channelOwnerName(channelType)
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ownerByChannelType[channelType] = owner
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}
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if owner != "" {
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owners[modelName] = owner
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}
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}
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return owners
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}
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func buildOpenAIModel(modelName string, ownerByModel map[string]string) dto.OpenAIModels {
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var oaiModel dto.OpenAIModels
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if staticModel, ok := openAIModelsMap[modelName]; ok {
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oaiModel = staticModel
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} else {
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oaiModel = dto.OpenAIModels{
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Id: modelName,
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Object: "model",
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Created: 1626777600,
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OwnedBy: "custom",
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}
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}
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if owner, ok := ownerByModel[modelName]; ok && owner != "" {
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oaiModel.OwnedBy = owner
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}
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oaiModel.SupportedEndpointTypes = model.GetModelSupportEndpointTypes(modelName)
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return oaiModel
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}
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type modelListGroups struct {
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userGroup string
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tokenGroup string
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ownerGroups []string
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}
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func getModelListGroups(c *gin.Context) (modelListGroups, error) {
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tokenGroup := common.GetContextKeyString(c, constant.ContextKeyTokenGroup)
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userGroup := common.GetContextKeyString(c, constant.ContextKeyUserGroup)
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if userGroup == "" && (tokenGroup == "" || tokenGroup == "auto") {
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var err error
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userGroup, err = model.GetUserGroup(c.GetInt("id"), false)
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if err != nil {
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return modelListGroups{}, err
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}
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}
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if tokenGroup == "auto" {
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return modelListGroups{
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userGroup: userGroup,
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tokenGroup: tokenGroup,
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ownerGroups: service.GetRequestAutoGroups(c, userGroup),
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}, nil
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}
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group := userGroup
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if tokenGroup != "" {
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group = tokenGroup
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}
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return modelListGroups{
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userGroup: userGroup,
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tokenGroup: tokenGroup,
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ownerGroups: []string{group},
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}, nil
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}
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func ListModels(c *gin.Context, modelType int) {
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acceptUnsetRatioModel := operation_setting.SelfUseModeEnabled
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if !acceptUnsetRatioModel {
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userId := c.GetInt("id")
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if userId > 0 {
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userSettings, _ := model.GetUserSetting(userId, false)
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if userSettings.AcceptUnsetRatioModel {
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acceptUnsetRatioModel = true
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}
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}
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}
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userModelNames := make([]string, 0)
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groups, err := getModelListGroups(c)
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if err != nil {
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c.JSON(http.StatusOK, gin.H{
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"success": false,
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"message": "get user group failed",
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})
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return
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}
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ownerGroups := groups.ownerGroups
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modelLimitEnable := common.GetContextKeyBool(c, constant.ContextKeyTokenModelLimitEnabled)
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var tokenModelLimit map[string]bool
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if modelLimitEnable {
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s, ok := common.GetContextKey(c, constant.ContextKeyTokenModelLimit)
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if ok {
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tokenModelLimit, _ = s.(map[string]bool)
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}
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if tokenModelLimit == nil {
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tokenModelLimit = map[string]bool{}
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}
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}
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models := service.GetGroupsEnabledModels(ownerGroups)
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for _, modelName := range models {
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if modelLimitEnable {
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matchingName := ratio_setting.RoutingMatchModelName(modelName)
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if !tokenModelLimit[modelName] && !tokenModelLimit[matchingName] {
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continue
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}
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}
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if !acceptUnsetRatioModel && !helper.HasModelBillingConfig(modelName) {
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continue
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}
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userModelNames = append(userModelNames, modelName)
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}
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ownerByModel := map[string]string{}
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if len(ownerGroups) > 0 {
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ownerByModel = getPreferredModelOwners(userModelNames, ownerGroups)
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}
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userOpenAiModels := make([]dto.OpenAIModels, 0, len(userModelNames))
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for _, modelName := range userModelNames {
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userOpenAiModels = append(userOpenAiModels, buildOpenAIModel(modelName, ownerByModel))
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}
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switch modelType {
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case constant.ChannelTypeAnthropic:
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useranthropicModels := make([]dto.AnthropicModel, len(userOpenAiModels))
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for i, model := range userOpenAiModels {
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useranthropicModels[i] = dto.AnthropicModel{
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ID: model.Id,
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CreatedAt: time.Unix(int64(model.Created), 0).UTC().Format(time.RFC3339),
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DisplayName: model.Id,
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Type: "model",
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}
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}
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firstID := ""
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lastID := ""
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if len(useranthropicModels) > 0 {
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firstID = useranthropicModels[0].ID
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lastID = useranthropicModels[len(useranthropicModels)-1].ID
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}
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c.JSON(200, gin.H{
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"data": useranthropicModels,
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"first_id": firstID,
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"has_more": false,
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"last_id": lastID,
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})
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case constant.ChannelTypeGemini:
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userGeminiModels := make([]dto.GeminiModel, len(userOpenAiModels))
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for i, model := range userOpenAiModels {
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userGeminiModels[i] = dto.GeminiModel{
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Name: model.Id,
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DisplayName: model.Id,
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}
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}
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c.JSON(200, gin.H{
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"models": userGeminiModels,
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"nextPageToken": nil,
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})
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default:
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c.JSON(200, gin.H{
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"success": true,
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"data": userOpenAiModels,
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"object": "list",
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})
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}
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}
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func ChannelListModels(c *gin.Context) {
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c.JSON(200, gin.H{
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"success": true,
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"data": openAIModels,
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})
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}
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func DashboardListModels(c *gin.Context) {
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modelsByChannel := make(map[int][]string, len(channelId2Models))
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for channelType, models := range channelId2Models {
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modelsByChannel[channelType] = append([]string(nil), models...)
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}
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for channelType := 1; channelType <= constant.ChannelTypeDummy; channelType++ {
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if plugin, ok := jsplugin.DefaultRegistry.GetByChannelType(channelType); ok {
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modelsByChannel[channelType] = append([]string(nil), plugin.Meta.Models...)
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}
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}
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c.JSON(200, gin.H{
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"success": true,
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"data": modelsByChannel,
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})
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}
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func EnabledListModels(c *gin.Context) {
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c.JSON(200, gin.H{
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"success": true,
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"data": model.GetEnabledModels(),
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})
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}
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func RetrieveModel(c *gin.Context, modelType int) {
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modelId := c.Param("model")
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if aiModel, ok := openAIModelsMap[modelId]; ok {
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switch modelType {
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case constant.ChannelTypeAnthropic:
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c.JSON(200, dto.AnthropicModel{
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ID: aiModel.Id,
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CreatedAt: time.Unix(int64(aiModel.Created), 0).UTC().Format(time.RFC3339),
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DisplayName: aiModel.Id,
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Type: "model",
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})
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default:
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c.JSON(200, aiModel)
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}
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} else {
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openAIError := types.OpenAIError{
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Message: fmt.Sprintf("The model '%s' does not exist", modelId),
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Type: "invalid_request_error",
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Param: "model",
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Code: "model_not_found",
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}
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c.JSON(200, gin.H{
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"error": openAIError,
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})
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}
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}
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