mirror of
https://github.com/QuantumNous/new-api.git
synced 2026-03-29 23:10:35 +00:00
899 lines
27 KiB
Go
899 lines
27 KiB
Go
package controller
|
|
|
|
import (
|
|
"bytes"
|
|
"encoding/json"
|
|
"errors"
|
|
"fmt"
|
|
"io"
|
|
"math"
|
|
"net/http"
|
|
"net/http/httptest"
|
|
"net/url"
|
|
"strconv"
|
|
"strings"
|
|
"sync"
|
|
"time"
|
|
|
|
"github.com/QuantumNous/new-api/common"
|
|
"github.com/QuantumNous/new-api/constant"
|
|
"github.com/QuantumNous/new-api/dto"
|
|
"github.com/QuantumNous/new-api/middleware"
|
|
"github.com/QuantumNous/new-api/model"
|
|
"github.com/QuantumNous/new-api/relay"
|
|
relaycommon "github.com/QuantumNous/new-api/relay/common"
|
|
relayconstant "github.com/QuantumNous/new-api/relay/constant"
|
|
"github.com/QuantumNous/new-api/relay/helper"
|
|
"github.com/QuantumNous/new-api/service"
|
|
"github.com/QuantumNous/new-api/setting/operation_setting"
|
|
"github.com/QuantumNous/new-api/setting/ratio_setting"
|
|
"github.com/QuantumNous/new-api/types"
|
|
|
|
"github.com/bytedance/gopkg/util/gopool"
|
|
"github.com/samber/lo"
|
|
"github.com/tidwall/gjson"
|
|
|
|
"github.com/gin-gonic/gin"
|
|
)
|
|
|
|
type testResult struct {
|
|
context *gin.Context
|
|
localErr error
|
|
newAPIError *types.NewAPIError
|
|
}
|
|
|
|
func normalizeChannelTestEndpoint(channel *model.Channel, modelName, endpointType string) string {
|
|
normalized := strings.TrimSpace(endpointType)
|
|
if normalized != "" {
|
|
return normalized
|
|
}
|
|
if strings.HasSuffix(modelName, ratio_setting.CompactModelSuffix) {
|
|
return string(constant.EndpointTypeOpenAIResponseCompact)
|
|
}
|
|
if channel != nil && channel.Type == constant.ChannelTypeCodex {
|
|
return string(constant.EndpointTypeOpenAIResponse)
|
|
}
|
|
return normalized
|
|
}
|
|
|
|
func testChannel(channel *model.Channel, testModel string, endpointType string, isStream bool) testResult {
|
|
tik := time.Now()
|
|
var unsupportedTestChannelTypes = []int{
|
|
constant.ChannelTypeMidjourney,
|
|
constant.ChannelTypeMidjourneyPlus,
|
|
constant.ChannelTypeSunoAPI,
|
|
constant.ChannelTypeKling,
|
|
constant.ChannelTypeJimeng,
|
|
constant.ChannelTypeDoubaoVideo,
|
|
constant.ChannelTypeVidu,
|
|
}
|
|
if lo.Contains(unsupportedTestChannelTypes, channel.Type) {
|
|
channelTypeName := constant.GetChannelTypeName(channel.Type)
|
|
return testResult{
|
|
localErr: fmt.Errorf("%s channel test is not supported", channelTypeName),
|
|
}
|
|
}
|
|
w := httptest.NewRecorder()
|
|
c, _ := gin.CreateTestContext(w)
|
|
|
|
testModel = strings.TrimSpace(testModel)
|
|
if testModel == "" {
|
|
if channel.TestModel != nil && *channel.TestModel != "" {
|
|
testModel = strings.TrimSpace(*channel.TestModel)
|
|
} else {
|
|
models := channel.GetModels()
|
|
if len(models) > 0 {
|
|
testModel = strings.TrimSpace(models[0])
|
|
}
|
|
if testModel == "" {
|
|
testModel = "gpt-4o-mini"
|
|
}
|
|
}
|
|
}
|
|
|
|
endpointType = normalizeChannelTestEndpoint(channel, testModel, endpointType)
|
|
|
|
requestPath := "/v1/chat/completions"
|
|
|
|
// 如果指定了端点类型，使用指定的端点类型
|
|
if endpointType != "" {
|
|
if endpointInfo, ok := common.GetDefaultEndpointInfo(constant.EndpointType(endpointType)); ok {
|
|
requestPath = endpointInfo.Path
|
|
}
|
|
} else {
|
|
// 如果没有指定端点类型，使用原有的自动检测逻辑
|
|
|
|
if strings.Contains(strings.ToLower(testModel), "rerank") {
|
|
requestPath = "/v1/rerank"
|
|
}
|
|
|
|
// 先判断是否为 Embedding 模型
|
|
if strings.Contains(strings.ToLower(testModel), "embedding") ||
|
|
strings.HasPrefix(testModel, "m3e") || // m3e 系列模型
|
|
strings.Contains(testModel, "bge-") || // bge 系列模型
|
|
strings.Contains(testModel, "embed") ||
|
|
channel.Type == constant.ChannelTypeMokaAI { // 其他 embedding 模型
|
|
requestPath = "/v1/embeddings" // 修改请求路径
|
|
}
|
|
|
|
// VolcEngine 图像生成模型
|
|
if channel.Type == constant.ChannelTypeVolcEngine && strings.Contains(testModel, "seedream") {
|
|
requestPath = "/v1/images/generations"
|
|
}
|
|
|
|
// responses-only models
|
|
if strings.Contains(strings.ToLower(testModel), "codex") {
|
|
requestPath = "/v1/responses"
|
|
}
|
|
|
|
// responses compaction models (must use /v1/responses/compact)
|
|
if strings.HasSuffix(testModel, ratio_setting.CompactModelSuffix) {
|
|
requestPath = "/v1/responses/compact"
|
|
}
|
|
}
|
|
if strings.HasPrefix(requestPath, "/v1/responses/compact") {
|
|
testModel = ratio_setting.WithCompactModelSuffix(testModel)
|
|
}
|
|
|
|
c.Request = &http.Request{
|
|
Method: "POST",
|
|
URL: &url.URL{Path: requestPath}, // 使用动态路径
|
|
Body: nil,
|
|
Header: make(http.Header),
|
|
}
|
|
|
|
cache, err := model.GetUserCache(1)
|
|
if err != nil {
|
|
return testResult{
|
|
localErr: err,
|
|
newAPIError: nil,
|
|
}
|
|
}
|
|
cache.WriteContext(c)
|
|
|
|
//c.Request.Header.Set("Authorization", "Bearer "+channel.Key)
|
|
c.Request.Header.Set("Content-Type", "application/json")
|
|
c.Set("channel", channel.Type)
|
|
c.Set("base_url", channel.GetBaseURL())
|
|
group, _ := model.GetUserGroup(1, false)
|
|
c.Set("group", group)
|
|
|
|
newAPIError := middleware.SetupContextForSelectedChannel(c, channel, testModel)
|
|
if newAPIError != nil {
|
|
return testResult{
|
|
context: c,
|
|
localErr: newAPIError,
|
|
newAPIError: newAPIError,
|
|
}
|
|
}
|
|
|
|
// Determine relay format based on endpoint type or request path
|
|
var relayFormat types.RelayFormat
|
|
if endpointType != "" {
|
|
// 根据指定的端点类型设置 relayFormat
|
|
switch constant.EndpointType(endpointType) {
|
|
case constant.EndpointTypeOpenAI:
|
|
relayFormat = types.RelayFormatOpenAI
|
|
case constant.EndpointTypeOpenAIResponse:
|
|
relayFormat = types.RelayFormatOpenAIResponses
|
|
case constant.EndpointTypeOpenAIResponseCompact:
|
|
relayFormat = types.RelayFormatOpenAIResponsesCompaction
|
|
case constant.EndpointTypeAnthropic:
|
|
relayFormat = types.RelayFormatClaude
|
|
case constant.EndpointTypeGemini:
|
|
relayFormat = types.RelayFormatGemini
|
|
case constant.EndpointTypeJinaRerank:
|
|
relayFormat = types.RelayFormatRerank
|
|
case constant.EndpointTypeImageGeneration:
|
|
relayFormat = types.RelayFormatOpenAIImage
|
|
case constant.EndpointTypeEmbeddings:
|
|
relayFormat = types.RelayFormatEmbedding
|
|
default:
|
|
relayFormat = types.RelayFormatOpenAI
|
|
}
|
|
} else {
|
|
// 根据请求路径自动检测
|
|
relayFormat = types.RelayFormatOpenAI
|
|
if c.Request.URL.Path == "/v1/embeddings" {
|
|
relayFormat = types.RelayFormatEmbedding
|
|
}
|
|
if c.Request.URL.Path == "/v1/images/generations" {
|
|
relayFormat = types.RelayFormatOpenAIImage
|
|
}
|
|
if c.Request.URL.Path == "/v1/messages" {
|
|
relayFormat = types.RelayFormatClaude
|
|
}
|
|
if strings.Contains(c.Request.URL.Path, "/v1beta/models") {
|
|
relayFormat = types.RelayFormatGemini
|
|
}
|
|
if c.Request.URL.Path == "/v1/rerank" || c.Request.URL.Path == "/rerank" {
|
|
relayFormat = types.RelayFormatRerank
|
|
}
|
|
if c.Request.URL.Path == "/v1/responses" {
|
|
relayFormat = types.RelayFormatOpenAIResponses
|
|
}
|
|
if strings.HasPrefix(c.Request.URL.Path, "/v1/responses/compact") {
|
|
relayFormat = types.RelayFormatOpenAIResponsesCompaction
|
|
}
|
|
}
|
|
|
|
request := buildTestRequest(testModel, endpointType, channel, isStream)
|
|
|
|
info, err := relaycommon.GenRelayInfo(c, relayFormat, request, nil)
|
|
|
|
if err != nil {
|
|
return testResult{
|
|
context: c,
|
|
localErr: err,
|
|
newAPIError: types.NewError(err, types.ErrorCodeGenRelayInfoFailed),
|
|
}
|
|
}
|
|
|
|
info.IsChannelTest = true
|
|
info.InitChannelMeta(c)
|
|
|
|
err = helper.ModelMappedHelper(c, info, request)
|
|
if err != nil {
|
|
return testResult{
|
|
context: c,
|
|
localErr: err,
|
|
newAPIError: types.NewError(err, types.ErrorCodeChannelModelMappedError),
|
|
}
|
|
}
|
|
|
|
testModel = info.UpstreamModelName
|
|
// 更新请求中的模型名称
|
|
request.SetModelName(testModel)
|
|
|
|
apiType, _ := common.ChannelType2APIType(channel.Type)
|
|
if info.RelayMode == relayconstant.RelayModeResponsesCompact &&
|
|
apiType != constant.APITypeOpenAI &&
|
|
apiType != constant.APITypeCodex {
|
|
return testResult{
|
|
context: c,
|
|
localErr: fmt.Errorf("responses compaction test only supports openai/codex channels, got api type %d", apiType),
|
|
newAPIError: types.NewError(fmt.Errorf("unsupported api type: %d", apiType), types.ErrorCodeInvalidApiType),
|
|
}
|
|
}
|
|
adaptor := relay.GetAdaptor(apiType)
|
|
if adaptor == nil {
|
|
return testResult{
|
|
context: c,
|
|
localErr: fmt.Errorf("invalid api type: %d, adaptor is nil", apiType),
|
|
newAPIError: types.NewError(fmt.Errorf("invalid api type: %d, adaptor is nil", apiType), types.ErrorCodeInvalidApiType),
|
|
}
|
|
}
|
|
|
|
//// 创建一个用于日志的 info 副本，移除 ApiKey
|
|
//logInfo := info
|
|
//logInfo.ApiKey = ""
|
|
common.SysLog(fmt.Sprintf("testing channel %d with model %s , info %+v ", channel.Id, testModel, info.ToString()))
|
|
|
|
priceData, err := helper.ModelPriceHelper(c, info, 0, request.GetTokenCountMeta())
|
|
if err != nil {
|
|
return testResult{
|
|
context: c,
|
|
localErr: err,
|
|
newAPIError: types.NewError(err, types.ErrorCodeModelPriceError),
|
|
}
|
|
}
|
|
|
|
adaptor.Init(info)
|
|
|
|
var convertedRequest any
|
|
// 根据 RelayMode 选择正确的转换函数
|
|
switch info.RelayMode {
|
|
case relayconstant.RelayModeEmbeddings:
|
|
// Embedding 请求 - request 已经是正确的类型
|
|
if embeddingReq, ok := request.(*dto.EmbeddingRequest); ok {
|
|
convertedRequest, err = adaptor.ConvertEmbeddingRequest(c, info, *embeddingReq)
|
|
} else {
|
|
return testResult{
|
|
context: c,
|
|
localErr: errors.New("invalid embedding request type"),
|
|
newAPIError: types.NewError(errors.New("invalid embedding request type"), types.ErrorCodeConvertRequestFailed),
|
|
}
|
|
}
|
|
case relayconstant.RelayModeImagesGenerations:
|
|
// 图像生成请求 - request 已经是正确的类型
|
|
if imageReq, ok := request.(*dto.ImageRequest); ok {
|
|
convertedRequest, err = adaptor.ConvertImageRequest(c, info, *imageReq)
|
|
} else {
|
|
return testResult{
|
|
context: c,
|
|
localErr: errors.New("invalid image request type"),
|
|
newAPIError: types.NewError(errors.New("invalid image request type"), types.ErrorCodeConvertRequestFailed),
|
|
}
|
|
}
|
|
case relayconstant.RelayModeRerank:
|
|
// Rerank 请求 - request 已经是正确的类型
|
|
if rerankReq, ok := request.(*dto.RerankRequest); ok {
|
|
convertedRequest, err = adaptor.ConvertRerankRequest(c, info.RelayMode, *rerankReq)
|
|
} else {
|
|
return testResult{
|
|
context: c,
|
|
localErr: errors.New("invalid rerank request type"),
|
|
newAPIError: types.NewError(errors.New("invalid rerank request type"), types.ErrorCodeConvertRequestFailed),
|
|
}
|
|
}
|
|
case relayconstant.RelayModeResponses:
|
|
// Response 请求 - request 已经是正确的类型
|
|
if responseReq, ok := request.(*dto.OpenAIResponsesRequest); ok {
|
|
convertedRequest, err = adaptor.ConvertOpenAIResponsesRequest(c, info, *responseReq)
|
|
} else {
|
|
return testResult{
|
|
context: c,
|
|
localErr: errors.New("invalid response request type"),
|
|
newAPIError: types.NewError(errors.New("invalid response request type"), types.ErrorCodeConvertRequestFailed),
|
|
}
|
|
}
|
|
case relayconstant.RelayModeResponsesCompact:
|
|
// Response compaction request - convert to OpenAIResponsesRequest before adapting
|
|
switch req := request.(type) {
|
|
case *dto.OpenAIResponsesCompactionRequest:
|
|
convertedRequest, err = adaptor.ConvertOpenAIResponsesRequest(c, info, dto.OpenAIResponsesRequest{
|
|
Model: req.Model,
|
|
Input: req.Input,
|
|
Instructions: req.Instructions,
|
|
PreviousResponseID: req.PreviousResponseID,
|
|
})
|
|
case *dto.OpenAIResponsesRequest:
|
|
convertedRequest, err = adaptor.ConvertOpenAIResponsesRequest(c, info, *req)
|
|
default:
|
|
return testResult{
|
|
context: c,
|
|
localErr: errors.New("invalid response compaction request type"),
|
|
newAPIError: types.NewError(errors.New("invalid response compaction request type"), types.ErrorCodeConvertRequestFailed),
|
|
}
|
|
}
|
|
default:
|
|
// Chat/Completion 等其他请求类型
|
|
if generalReq, ok := request.(*dto.GeneralOpenAIRequest); ok {
|
|
convertedRequest, err = adaptor.ConvertOpenAIRequest(c, info, generalReq)
|
|
} else {
|
|
return testResult{
|
|
context: c,
|
|
localErr: errors.New("invalid general request type"),
|
|
newAPIError: types.NewError(errors.New("invalid general request type"), types.ErrorCodeConvertRequestFailed),
|
|
}
|
|
}
|
|
}
|
|
|
|
if err != nil {
|
|
return testResult{
|
|
context: c,
|
|
localErr: err,
|
|
newAPIError: types.NewError(err, types.ErrorCodeConvertRequestFailed),
|
|
}
|
|
}
|
|
jsonData, err := common.Marshal(convertedRequest)
|
|
if err != nil {
|
|
return testResult{
|
|
context: c,
|
|
localErr: err,
|
|
newAPIError: types.NewError(err, types.ErrorCodeJsonMarshalFailed),
|
|
}
|
|
}
|
|
|
|
//jsonData, err = relaycommon.RemoveDisabledFields(jsonData, info.ChannelOtherSettings)
|
|
//if err != nil {
|
|
// return testResult{
|
|
// context: c,
|
|
// localErr: err,
|
|
// newAPIError: types.NewError(err, types.ErrorCodeConvertRequestFailed),
|
|
// }
|
|
//}
|
|
|
|
if len(info.ParamOverride) > 0 {
|
|
jsonData, err = relaycommon.ApplyParamOverrideWithRelayInfo(jsonData, info)
|
|
if err != nil {
|
|
if fixedErr, ok := relaycommon.AsParamOverrideReturnError(err); ok {
|
|
return testResult{
|
|
context: c,
|
|
localErr: fixedErr,
|
|
newAPIError: relaycommon.NewAPIErrorFromParamOverride(fixedErr),
|
|
}
|
|
}
|
|
return testResult{
|
|
context: c,
|
|
localErr: err,
|
|
newAPIError: types.NewError(err, types.ErrorCodeChannelParamOverrideInvalid),
|
|
}
|
|
}
|
|
}
|
|
|
|
requestBody := bytes.NewBuffer(jsonData)
|
|
c.Request.Body = io.NopCloser(bytes.NewBuffer(jsonData))
|
|
resp, err := adaptor.DoRequest(c, info, requestBody)
|
|
if err != nil {
|
|
return testResult{
|
|
context: c,
|
|
localErr: err,
|
|
newAPIError: types.NewOpenAIError(err, types.ErrorCodeDoRequestFailed, http.StatusInternalServerError),
|
|
}
|
|
}
|
|
var httpResp *http.Response
|
|
if resp != nil {
|
|
httpResp = resp.(*http.Response)
|
|
if httpResp.StatusCode != http.StatusOK {
|
|
err := service.RelayErrorHandler(c.Request.Context(), httpResp, true)
|
|
common.SysError(fmt.Sprintf(
|
|
"channel test bad response: channel_id=%d name=%s type=%d model=%s endpoint_type=%s status=%d err=%v",
|
|
channel.Id,
|
|
channel.Name,
|
|
channel.Type,
|
|
testModel,
|
|
endpointType,
|
|
httpResp.StatusCode,
|
|
err,
|
|
))
|
|
return testResult{
|
|
context: c,
|
|
localErr: err,
|
|
newAPIError: types.NewOpenAIError(err, types.ErrorCodeBadResponse, http.StatusInternalServerError),
|
|
}
|
|
}
|
|
}
|
|
usageA, respErr := adaptor.DoResponse(c, httpResp, info)
|
|
if respErr != nil {
|
|
return testResult{
|
|
context: c,
|
|
localErr: respErr,
|
|
newAPIError: respErr,
|
|
}
|
|
}
|
|
usage, usageErr := coerceTestUsage(usageA, isStream, info.GetEstimatePromptTokens())
|
|
if usageErr != nil {
|
|
return testResult{
|
|
context: c,
|
|
localErr: usageErr,
|
|
newAPIError: types.NewOpenAIError(usageErr, types.ErrorCodeBadResponseBody, http.StatusInternalServerError),
|
|
}
|
|
}
|
|
result := w.Result()
|
|
respBody, err := readTestResponseBody(result.Body, isStream)
|
|
if err != nil {
|
|
return testResult{
|
|
context: c,
|
|
localErr: err,
|
|
newAPIError: types.NewOpenAIError(err, types.ErrorCodeReadResponseBodyFailed, http.StatusInternalServerError),
|
|
}
|
|
}
|
|
if bodyErr := detectErrorFromTestResponseBody(respBody); bodyErr != nil {
|
|
return testResult{
|
|
context: c,
|
|
localErr: bodyErr,
|
|
newAPIError: types.NewOpenAIError(bodyErr, types.ErrorCodeBadResponseBody, http.StatusInternalServerError),
|
|
}
|
|
}
|
|
info.SetEstimatePromptTokens(usage.PromptTokens)
|
|
|
|
quota := 0
|
|
if !priceData.UsePrice {
|
|
quota = usage.PromptTokens + int(math.Round(float64(usage.CompletionTokens)*priceData.CompletionRatio))
|
|
quota = int(math.Round(float64(quota) * priceData.ModelRatio))
|
|
if priceData.ModelRatio != 0 && quota <= 0 {
|
|
quota = 1
|
|
}
|
|
} else {
|
|
quota = int(priceData.ModelPrice * common.QuotaPerUnit)
|
|
}
|
|
tok := time.Now()
|
|
milliseconds := tok.Sub(tik).Milliseconds()
|
|
consumedTime := float64(milliseconds) / 1000.0
|
|
other := service.GenerateTextOtherInfo(c, info, priceData.ModelRatio, priceData.GroupRatioInfo.GroupRatio, priceData.CompletionRatio,
|
|
usage.PromptTokensDetails.CachedTokens, priceData.CacheRatio, priceData.ModelPrice, priceData.GroupRatioInfo.GroupSpecialRatio)
|
|
model.RecordConsumeLog(c, 1, model.RecordConsumeLogParams{
|
|
ChannelId: channel.Id,
|
|
PromptTokens: usage.PromptTokens,
|
|
CompletionTokens: usage.CompletionTokens,
|
|
ModelName: info.OriginModelName,
|
|
TokenName: "模型测试",
|
|
Quota: quota,
|
|
Content: "模型测试",
|
|
UseTimeSeconds: int(consumedTime),
|
|
IsStream: info.IsStream,
|
|
Group: info.UsingGroup,
|
|
Other: other,
|
|
})
|
|
common.SysLog(fmt.Sprintf("testing channel #%d, response: \n%s", channel.Id, string(respBody)))
|
|
return testResult{
|
|
context: c,
|
|
localErr: nil,
|
|
newAPIError: nil,
|
|
}
|
|
}
|
|
|
|
func coerceTestUsage(usageAny any, isStream bool, estimatePromptTokens int) (*dto.Usage, error) {
|
|
switch u := usageAny.(type) {
|
|
case *dto.Usage:
|
|
return u, nil
|
|
case dto.Usage:
|
|
return &u, nil
|
|
case nil:
|
|
if !isStream {
|
|
return nil, errors.New("usage is nil")
|
|
}
|
|
usage := &dto.Usage{
|
|
PromptTokens: estimatePromptTokens,
|
|
}
|
|
usage.TotalTokens = usage.PromptTokens
|
|
return usage, nil
|
|
default:
|
|
if !isStream {
|
|
return nil, fmt.Errorf("invalid usage type: %T", usageAny)
|
|
}
|
|
usage := &dto.Usage{
|
|
PromptTokens: estimatePromptTokens,
|
|
}
|
|
usage.TotalTokens = usage.PromptTokens
|
|
return usage, nil
|
|
}
|
|
}
|
|
|
|
func readTestResponseBody(body io.ReadCloser, isStream bool) ([]byte, error) {
|
|
defer func() { _ = body.Close() }()
|
|
const maxStreamLogBytes = 8 << 10
|
|
if isStream {
|
|
return io.ReadAll(io.LimitReader(body, maxStreamLogBytes))
|
|
}
|
|
return io.ReadAll(body)
|
|
}
|
|
|
|
func detectErrorFromTestResponseBody(respBody []byte) error {
|
|
b := bytes.TrimSpace(respBody)
|
|
if len(b) == 0 {
|
|
return nil
|
|
}
|
|
if message := detectErrorMessageFromJSONBytes(b); message != "" {
|
|
return fmt.Errorf("upstream error: %s", message)
|
|
}
|
|
|
|
for _, line := range bytes.Split(b, []byte{'\n'}) {
|
|
line = bytes.TrimSpace(line)
|
|
if len(line) == 0 {
|
|
continue
|
|
}
|
|
if !bytes.HasPrefix(line, []byte("data:")) {
|
|
continue
|
|
}
|
|
payload := bytes.TrimSpace(bytes.TrimPrefix(line, []byte("data:")))
|
|
if len(payload) == 0 || bytes.Equal(payload, []byte("[DONE]")) {
|
|
continue
|
|
}
|
|
if message := detectErrorMessageFromJSONBytes(payload); message != "" {
|
|
return fmt.Errorf("upstream error: %s", message)
|
|
}
|
|
}
|
|
|
|
return nil
|
|
}
|
|
|
|
func detectErrorMessageFromJSONBytes(jsonBytes []byte) string {
|
|
if len(jsonBytes) == 0 {
|
|
return ""
|
|
}
|
|
if jsonBytes[0] != '{' && jsonBytes[0] != '[' {
|
|
return ""
|
|
}
|
|
errVal := gjson.GetBytes(jsonBytes, "error")
|
|
if !errVal.Exists() || errVal.Type == gjson.Null {
|
|
return ""
|
|
}
|
|
|
|
message := gjson.GetBytes(jsonBytes, "error.message").String()
|
|
if message == "" {
|
|
message = gjson.GetBytes(jsonBytes, "error.error.message").String()
|
|
}
|
|
if message == "" && errVal.Type == gjson.String {
|
|
message = errVal.String()
|
|
}
|
|
if message == "" {
|
|
message = errVal.Raw
|
|
}
|
|
message = strings.TrimSpace(message)
|
|
if message == "" {
|
|
return "upstream returned error payload"
|
|
}
|
|
return message
|
|
}
|
|
|
|
func buildTestRequest(model string, endpointType string, channel *model.Channel, isStream bool) dto.Request {
|
|
testResponsesInput := json.RawMessage(`[{"role":"user","content":"hi"}]`)
|
|
|
|
// 根据端点类型构建不同的测试请求
|
|
if endpointType != "" {
|
|
switch constant.EndpointType(endpointType) {
|
|
case constant.EndpointTypeEmbeddings:
|
|
// 返回 EmbeddingRequest
|
|
return &dto.EmbeddingRequest{
|
|
Model: model,
|
|
Input: []any{"hello world"},
|
|
}
|
|
case constant.EndpointTypeImageGeneration:
|
|
// 返回 ImageRequest
|
|
return &dto.ImageRequest{
|
|
Model: model,
|
|
Prompt: "a cute cat",
|
|
N: lo.ToPtr(uint(1)),
|
|
Size: "1024x1024",
|
|
}
|
|
case constant.EndpointTypeJinaRerank:
|
|
// 返回 RerankRequest
|
|
return &dto.RerankRequest{
|
|
Model: model,
|
|
Query: "What is Deep Learning?",
|
|
Documents: []any{"Deep Learning is a subset of machine learning.", "Machine learning is a field of artificial intelligence."},
|
|
TopN: lo.ToPtr(2),
|
|
}
|
|
case constant.EndpointTypeOpenAIResponse:
|
|
// 返回 OpenAIResponsesRequest
|
|
return &dto.OpenAIResponsesRequest{
|
|
Model: model,
|
|
Input: json.RawMessage(`[{"role":"user","content":"hi"}]`),
|
|
Stream: lo.ToPtr(isStream),
|
|
}
|
|
case constant.EndpointTypeOpenAIResponseCompact:
|
|
// 返回 OpenAIResponsesCompactionRequest
|
|
return &dto.OpenAIResponsesCompactionRequest{
|
|
Model: model,
|
|
Input: testResponsesInput,
|
|
}
|
|
case constant.EndpointTypeAnthropic, constant.EndpointTypeGemini, constant.EndpointTypeOpenAI:
|
|
// 返回 GeneralOpenAIRequest
|
|
maxTokens := uint(16)
|
|
if constant.EndpointType(endpointType) == constant.EndpointTypeGemini {
|
|
maxTokens = 3000
|
|
}
|
|
req := &dto.GeneralOpenAIRequest{
|
|
Model: model,
|
|
Stream: lo.ToPtr(isStream),
|
|
Messages: []dto.Message{
|
|
{
|
|
Role: "user",
|
|
Content: "hi",
|
|
},
|
|
},
|
|
MaxTokens: lo.ToPtr(maxTokens),
|
|
}
|
|
if isStream {
|
|
req.StreamOptions = &dto.StreamOptions{IncludeUsage: true}
|
|
}
|
|
return req
|
|
}
|
|
}
|
|
|
|
// 自动检测逻辑（保持原有行为）
|
|
if strings.Contains(strings.ToLower(model), "rerank") {
|
|
return &dto.RerankRequest{
|
|
Model: model,
|
|
Query: "What is Deep Learning?",
|
|
Documents: []any{"Deep Learning is a subset of machine learning.", "Machine learning is a field of artificial intelligence."},
|
|
TopN: lo.ToPtr(2),
|
|
}
|
|
}
|
|
|
|
// 先判断是否为 Embedding 模型
|
|
if strings.Contains(strings.ToLower(model), "embedding") ||
|
|
strings.HasPrefix(model, "m3e") ||
|
|
strings.Contains(model, "bge-") {
|
|
// 返回 EmbeddingRequest
|
|
return &dto.EmbeddingRequest{
|
|
Model: model,
|
|
Input: []any{"hello world"},
|
|
}
|
|
}
|
|
|
|
// Responses compaction models (must use /v1/responses/compact)
|
|
if strings.HasSuffix(model, ratio_setting.CompactModelSuffix) {
|
|
return &dto.OpenAIResponsesCompactionRequest{
|
|
Model: model,
|
|
Input: testResponsesInput,
|
|
}
|
|
}
|
|
|
|
// Responses-only models (e.g. codex series)
|
|
if strings.Contains(strings.ToLower(model), "codex") {
|
|
return &dto.OpenAIResponsesRequest{
|
|
Model: model,
|
|
Input: json.RawMessage(`[{"role":"user","content":"hi"}]`),
|
|
Stream: lo.ToPtr(isStream),
|
|
}
|
|
}
|
|
|
|
// Chat/Completion 请求 - 返回 GeneralOpenAIRequest
|
|
testRequest := &dto.GeneralOpenAIRequest{
|
|
Model: model,
|
|
Stream: lo.ToPtr(isStream),
|
|
Messages: []dto.Message{
|
|
{
|
|
Role: "user",
|
|
Content: "hi",
|
|
},
|
|
},
|
|
}
|
|
if isStream {
|
|
testRequest.StreamOptions = &dto.StreamOptions{IncludeUsage: true}
|
|
}
|
|
|
|
if strings.HasPrefix(model, "o") {
|
|
testRequest.MaxCompletionTokens = lo.ToPtr(uint(16))
|
|
} else if strings.Contains(model, "thinking") {
|
|
if !strings.Contains(model, "claude") {
|
|
testRequest.MaxTokens = lo.ToPtr(uint(50))
|
|
}
|
|
} else if strings.Contains(model, "gemini") {
|
|
testRequest.MaxTokens = lo.ToPtr(uint(3000))
|
|
} else {
|
|
testRequest.MaxTokens = lo.ToPtr(uint(16))
|
|
}
|
|
|
|
return testRequest
|
|
}
|
|
|
|
func TestChannel(c *gin.Context) {
|
|
channelId, err := strconv.Atoi(c.Param("id"))
|
|
if err != nil {
|
|
common.ApiError(c, err)
|
|
return
|
|
}
|
|
channel, err := model.CacheGetChannel(channelId)
|
|
if err != nil {
|
|
channel, err = model.GetChannelById(channelId, true)
|
|
if err != nil {
|
|
common.ApiError(c, err)
|
|
return
|
|
}
|
|
}
|
|
//defer func() {
|
|
// if channel.ChannelInfo.IsMultiKey {
|
|
// go func() { _ = channel.SaveChannelInfo() }()
|
|
// }
|
|
//}()
|
|
testModel := c.Query("model")
|
|
endpointType := c.Query("endpoint_type")
|
|
isStream, _ := strconv.ParseBool(c.Query("stream"))
|
|
tik := time.Now()
|
|
result := testChannel(channel, testModel, endpointType, isStream)
|
|
if result.localErr != nil {
|
|
c.JSON(http.StatusOK, gin.H{
|
|
"success": false,
|
|
"message": result.localErr.Error(),
|
|
"time": 0.0,
|
|
})
|
|
return
|
|
}
|
|
tok := time.Now()
|
|
milliseconds := tok.Sub(tik).Milliseconds()
|
|
go channel.UpdateResponseTime(milliseconds)
|
|
consumedTime := float64(milliseconds) / 1000.0
|
|
if result.newAPIError != nil {
|
|
c.JSON(http.StatusOK, gin.H{
|
|
"success": false,
|
|
"message": result.newAPIError.Error(),
|
|
"time": consumedTime,
|
|
})
|
|
return
|
|
}
|
|
c.JSON(http.StatusOK, gin.H{
|
|
"success": true,
|
|
"message": "",
|
|
"time": consumedTime,
|
|
})
|
|
}
|
|
|
|
var testAllChannelsLock sync.Mutex
|
|
var testAllChannelsRunning bool = false
|
|
|
|
func testAllChannels(notify bool) error {
|
|
|
|
testAllChannelsLock.Lock()
|
|
if testAllChannelsRunning {
|
|
testAllChannelsLock.Unlock()
|
|
return errors.New("测试已在运行中")
|
|
}
|
|
testAllChannelsRunning = true
|
|
testAllChannelsLock.Unlock()
|
|
channels, getChannelErr := model.GetAllChannels(0, 0, true, false)
|
|
if getChannelErr != nil {
|
|
return getChannelErr
|
|
}
|
|
var disableThreshold = int64(common.ChannelDisableThreshold * 1000)
|
|
if disableThreshold == 0 {
|
|
disableThreshold = 10000000 // a impossible value
|
|
}
|
|
gopool.Go(func() {
|
|
// 使用 defer 确保无论如何都会重置运行状态，防止死锁
|
|
defer func() {
|
|
testAllChannelsLock.Lock()
|
|
testAllChannelsRunning = false
|
|
testAllChannelsLock.Unlock()
|
|
}()
|
|
|
|
for _, channel := range channels {
|
|
if channel.Status == common.ChannelStatusManuallyDisabled {
|
|
continue
|
|
}
|
|
isChannelEnabled := channel.Status == common.ChannelStatusEnabled
|
|
tik := time.Now()
|
|
result := testChannel(channel, "", "", false)
|
|
tok := time.Now()
|
|
milliseconds := tok.Sub(tik).Milliseconds()
|
|
|
|
shouldBanChannel := false
|
|
newAPIError := result.newAPIError
|
|
// request error disables the channel
|
|
if newAPIError != nil {
|
|
shouldBanChannel = service.ShouldDisableChannel(channel.Type, result.newAPIError)
|
|
}
|
|
|
|
// 当错误检查通过，才检查响应时间
|
|
if common.AutomaticDisableChannelEnabled && !shouldBanChannel {
|
|
if milliseconds > disableThreshold {
|
|
err := fmt.Errorf("响应时间 %.2fs 超过阈值 %.2fs", float64(milliseconds)/1000.0, float64(disableThreshold)/1000.0)
|
|
newAPIError = types.NewOpenAIError(err, types.ErrorCodeChannelResponseTimeExceeded, http.StatusRequestTimeout)
|
|
shouldBanChannel = true
|
|
}
|
|
}
|
|
|
|
// disable channel
|
|
if isChannelEnabled && shouldBanChannel && channel.GetAutoBan() {
|
|
processChannelError(result.context, *types.NewChannelError(channel.Id, channel.Type, channel.Name, channel.ChannelInfo.IsMultiKey, common.GetContextKeyString(result.context, constant.ContextKeyChannelKey), channel.GetAutoBan()), newAPIError)
|
|
}
|
|
|
|
// enable channel
|
|
if !isChannelEnabled && service.ShouldEnableChannel(newAPIError, channel.Status) {
|
|
service.EnableChannel(channel.Id, common.GetContextKeyString(result.context, constant.ContextKeyChannelKey), channel.Name)
|
|
}
|
|
|
|
channel.UpdateResponseTime(milliseconds)
|
|
time.Sleep(common.RequestInterval)
|
|
}
|
|
|
|
if notify {
|
|
service.NotifyRootUser(dto.NotifyTypeChannelTest, "通道测试完成", "所有通道测试已完成")
|
|
}
|
|
})
|
|
return nil
|
|
}
|
|
|
|
func TestAllChannels(c *gin.Context) {
|
|
err := testAllChannels(true)
|
|
if err != nil {
|
|
common.ApiError(c, err)
|
|
return
|
|
}
|
|
c.JSON(http.StatusOK, gin.H{
|
|
"success": true,
|
|
"message": "",
|
|
})
|
|
}
|
|
|
|
var autoTestChannelsOnce sync.Once
|
|
|
|
func AutomaticallyTestChannels() {
|
|
// 只在Master节点定时测试渠道
|
|
if !common.IsMasterNode {
|
|
return
|
|
}
|
|
autoTestChannelsOnce.Do(func() {
|
|
for {
|
|
if !operation_setting.GetMonitorSetting().AutoTestChannelEnabled {
|
|
time.Sleep(1 * time.Minute)
|
|
continue
|
|
}
|
|
for {
|
|
frequency := operation_setting.GetMonitorSetting().AutoTestChannelMinutes
|
|
time.Sleep(time.Duration(int(math.Round(frequency))) * time.Minute)
|
|
common.SysLog(fmt.Sprintf("automatically test channels with interval %f minutes", frequency))
|
|
common.SysLog("automatically testing all channels")
|
|
_ = testAllChannels(false)
|
|
common.SysLog("automatically channel test finished")
|
|
if !operation_setting.GetMonitorSetting().AutoTestChannelEnabled {
|
|
break
|
|
}
|
|
}
|
|
}
|
|
})
|
|
}
|