mirror of
https://github.com/QuantumNous/new-api.git
synced 2026-04-18 13:27:27 +00:00
feat: add endpoint type selection to channel testing functionality
This commit is contained in:
@@ -38,7 +38,7 @@ type testResult struct {
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newAPIError *types.NewAPIError
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}
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func testChannel(channel *model.Channel, testModel string) testResult {
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func testChannel(channel *model.Channel, testModel string, endpointType string) testResult {
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tik := time.Now()
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if channel.Type == constant.ChannelTypeMidjourney {
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return testResult{
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@@ -81,18 +81,26 @@ func testChannel(channel *model.Channel, testModel string) testResult {
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requestPath := "/v1/chat/completions"
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// 先判断是否为 Embedding 模型
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if strings.Contains(strings.ToLower(testModel), "embedding") ||
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strings.HasPrefix(testModel, "m3e") || // m3e 系列模型
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strings.Contains(testModel, "bge-") || // bge 系列模型
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strings.Contains(testModel, "embed") ||
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channel.Type == constant.ChannelTypeMokaAI { // 其他 embedding 模型
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requestPath = "/v1/embeddings" // 修改请求路径
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}
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// 如果指定了端点类型,使用指定的端点类型
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if endpointType != "" {
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if endpointInfo, ok := common.GetDefaultEndpointInfo(constant.EndpointType(endpointType)); ok {
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requestPath = endpointInfo.Path
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}
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} else {
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// 如果没有指定端点类型,使用原有的自动检测逻辑
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// 先判断是否为 Embedding 模型
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if strings.Contains(strings.ToLower(testModel), "embedding") ||
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strings.HasPrefix(testModel, "m3e") || // m3e 系列模型
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strings.Contains(testModel, "bge-") || // bge 系列模型
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strings.Contains(testModel, "embed") ||
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channel.Type == constant.ChannelTypeMokaAI { // 其他 embedding 模型
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requestPath = "/v1/embeddings" // 修改请求路径
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}
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// VolcEngine 图像生成模型
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if channel.Type == constant.ChannelTypeVolcEngine && strings.Contains(testModel, "seedream") {
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requestPath = "/v1/images/generations"
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// VolcEngine 图像生成模型
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if channel.Type == constant.ChannelTypeVolcEngine && strings.Contains(testModel, "seedream") {
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requestPath = "/v1/images/generations"
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}
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}
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c.Request = &http.Request{
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@@ -114,21 +122,6 @@ func testChannel(channel *model.Channel, testModel string) testResult {
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}
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}
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// 重新检查模型类型并更新请求路径
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if strings.Contains(strings.ToLower(testModel), "embedding") ||
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strings.HasPrefix(testModel, "m3e") ||
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strings.Contains(testModel, "bge-") ||
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strings.Contains(testModel, "embed") ||
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channel.Type == constant.ChannelTypeMokaAI {
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requestPath = "/v1/embeddings"
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c.Request.URL.Path = requestPath
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}
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if channel.Type == constant.ChannelTypeVolcEngine && strings.Contains(testModel, "seedream") {
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requestPath = "/v1/images/generations"
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c.Request.URL.Path = requestPath
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}
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cache, err := model.GetUserCache(1)
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if err != nil {
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return testResult{
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@@ -153,17 +146,54 @@ func testChannel(channel *model.Channel, testModel string) testResult {
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newAPIError: newAPIError,
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}
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}
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request := buildTestRequest(testModel)
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// Determine relay format based on request path
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relayFormat := types.RelayFormatOpenAI
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if c.Request.URL.Path == "/v1/embeddings" {
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relayFormat = types.RelayFormatEmbedding
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}
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if c.Request.URL.Path == "/v1/images/generations" {
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relayFormat = types.RelayFormatOpenAIImage
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// Determine relay format based on endpoint type or request path
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var relayFormat types.RelayFormat
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if endpointType != "" {
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// 根据指定的端点类型设置 relayFormat
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switch constant.EndpointType(endpointType) {
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case constant.EndpointTypeOpenAI:
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relayFormat = types.RelayFormatOpenAI
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case constant.EndpointTypeOpenAIResponse:
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relayFormat = types.RelayFormatOpenAIResponses
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case constant.EndpointTypeAnthropic:
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relayFormat = types.RelayFormatClaude
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case constant.EndpointTypeGemini:
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relayFormat = types.RelayFormatGemini
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case constant.EndpointTypeJinaRerank:
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relayFormat = types.RelayFormatRerank
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case constant.EndpointTypeImageGeneration:
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relayFormat = types.RelayFormatOpenAIImage
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case constant.EndpointTypeEmbeddings:
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relayFormat = types.RelayFormatEmbedding
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default:
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relayFormat = types.RelayFormatOpenAI
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}
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} else {
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// 根据请求路径自动检测
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relayFormat = types.RelayFormatOpenAI
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if c.Request.URL.Path == "/v1/embeddings" {
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relayFormat = types.RelayFormatEmbedding
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}
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if c.Request.URL.Path == "/v1/images/generations" {
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relayFormat = types.RelayFormatOpenAIImage
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}
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if c.Request.URL.Path == "/v1/messages" {
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relayFormat = types.RelayFormatClaude
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}
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if strings.Contains(c.Request.URL.Path, "/v1beta/models") {
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relayFormat = types.RelayFormatGemini
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}
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if c.Request.URL.Path == "/v1/rerank" || c.Request.URL.Path == "/rerank" {
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relayFormat = types.RelayFormatRerank
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}
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if c.Request.URL.Path == "/v1/responses" {
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relayFormat = types.RelayFormatOpenAIResponses
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}
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}
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request := buildTestRequest(testModel, endpointType)
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info, err := relaycommon.GenRelayInfo(c, relayFormat, request, nil)
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if err != nil {
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@@ -186,7 +216,8 @@ func testChannel(channel *model.Channel, testModel string) testResult {
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}
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testModel = info.UpstreamModelName
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request.Model = testModel
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// 更新请求中的模型名称
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request.SetModelName(testModel)
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apiType, _ := common.ChannelType2APIType(channel.Type)
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adaptor := relay.GetAdaptor(apiType)
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@@ -216,33 +247,62 @@ func testChannel(channel *model.Channel, testModel string) testResult {
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var convertedRequest any
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// 根据 RelayMode 选择正确的转换函数
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if info.RelayMode == relayconstant.RelayModeEmbeddings {
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// 创建一个 EmbeddingRequest
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embeddingRequest := dto.EmbeddingRequest{
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Input: request.Input,
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Model: request.Model,
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}
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// 调用专门用于 Embedding 的转换函数
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convertedRequest, err = adaptor.ConvertEmbeddingRequest(c, info, embeddingRequest)
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} else if info.RelayMode == relayconstant.RelayModeImagesGenerations {
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// 创建一个 ImageRequest
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prompt := "cat"
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if request.Prompt != nil {
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if promptStr, ok := request.Prompt.(string); ok && promptStr != "" {
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prompt = promptStr
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switch info.RelayMode {
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case relayconstant.RelayModeEmbeddings:
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// Embedding 请求 - request 已经是正确的类型
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if embeddingReq, ok := request.(*dto.EmbeddingRequest); ok {
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convertedRequest, err = adaptor.ConvertEmbeddingRequest(c, info, *embeddingReq)
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} else {
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return testResult{
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context: c,
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localErr: errors.New("invalid embedding request type"),
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newAPIError: types.NewError(errors.New("invalid embedding request type"), types.ErrorCodeConvertRequestFailed),
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}
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}
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imageRequest := dto.ImageRequest{
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Prompt: prompt,
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Model: request.Model,
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N: uint(request.N),
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Size: request.Size,
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case relayconstant.RelayModeImagesGenerations:
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// 图像生成请求 - request 已经是正确的类型
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if imageReq, ok := request.(*dto.ImageRequest); ok {
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convertedRequest, err = adaptor.ConvertImageRequest(c, info, *imageReq)
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} else {
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return testResult{
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context: c,
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localErr: errors.New("invalid image request type"),
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newAPIError: types.NewError(errors.New("invalid image request type"), types.ErrorCodeConvertRequestFailed),
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}
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}
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case relayconstant.RelayModeRerank:
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// Rerank 请求 - request 已经是正确的类型
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if rerankReq, ok := request.(*dto.RerankRequest); ok {
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convertedRequest, err = adaptor.ConvertRerankRequest(c, info.RelayMode, *rerankReq)
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} else {
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return testResult{
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context: c,
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localErr: errors.New("invalid rerank request type"),
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newAPIError: types.NewError(errors.New("invalid rerank request type"), types.ErrorCodeConvertRequestFailed),
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}
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}
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case relayconstant.RelayModeResponses:
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// Response 请求 - request 已经是正确的类型
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if responseReq, ok := request.(*dto.OpenAIResponsesRequest); ok {
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convertedRequest, err = adaptor.ConvertOpenAIResponsesRequest(c, info, *responseReq)
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} else {
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return testResult{
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context: c,
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localErr: errors.New("invalid response request type"),
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newAPIError: types.NewError(errors.New("invalid response request type"), types.ErrorCodeConvertRequestFailed),
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}
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}
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default:
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// Chat/Completion 等其他请求类型
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if generalReq, ok := request.(*dto.GeneralOpenAIRequest); ok {
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convertedRequest, err = adaptor.ConvertOpenAIRequest(c, info, generalReq)
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} else {
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return testResult{
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context: c,
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localErr: errors.New("invalid general request type"),
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newAPIError: types.NewError(errors.New("invalid general request type"), types.ErrorCodeConvertRequestFailed),
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}
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}
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// 调用专门用于图像生成的转换函数
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convertedRequest, err = adaptor.ConvertImageRequest(c, info, imageRequest)
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} else {
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// 对其他所有请求类型(如 Chat),保持原有逻辑
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convertedRequest, err = adaptor.ConvertOpenAIRequest(c, info, request)
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}
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if err != nil {
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@@ -345,22 +405,82 @@ func testChannel(channel *model.Channel, testModel string) testResult {
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}
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}
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func buildTestRequest(model string) *dto.GeneralOpenAIRequest {
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testRequest := &dto.GeneralOpenAIRequest{
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Model: "", // this will be set later
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Stream: false,
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func buildTestRequest(model string, endpointType string) dto.Request {
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// 根据端点类型构建不同的测试请求
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if endpointType != "" {
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switch constant.EndpointType(endpointType) {
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case constant.EndpointTypeEmbeddings:
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// 返回 EmbeddingRequest
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return &dto.EmbeddingRequest{
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Model: model,
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Input: []any{"hello world"},
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}
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case constant.EndpointTypeImageGeneration:
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// 返回 ImageRequest
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return &dto.ImageRequest{
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Model: model,
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Prompt: "a cute cat",
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N: 1,
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Size: "1024x1024",
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}
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case constant.EndpointTypeJinaRerank:
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// 返回 RerankRequest
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return &dto.RerankRequest{
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Model: model,
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Query: "What is Deep Learning?",
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Documents: []any{"Deep Learning is a subset of machine learning.", "Machine learning is a field of artificial intelligence."},
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TopN: 2,
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}
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case constant.EndpointTypeOpenAIResponse:
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// 返回 OpenAIResponsesRequest
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return &dto.OpenAIResponsesRequest{
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Model: model,
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Input: json.RawMessage("\"hi\""),
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}
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case constant.EndpointTypeAnthropic, constant.EndpointTypeGemini, constant.EndpointTypeOpenAI:
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// 返回 GeneralOpenAIRequest
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maxTokens := uint(10)
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if constant.EndpointType(endpointType) == constant.EndpointTypeGemini {
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maxTokens = 3000
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}
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return &dto.GeneralOpenAIRequest{
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Model: model,
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Stream: false,
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Messages: []dto.Message{
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{
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Role: "user",
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Content: "hi",
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},
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},
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MaxTokens: maxTokens,
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}
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}
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}
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// 自动检测逻辑(保持原有行为)
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// 先判断是否为 Embedding 模型
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if strings.Contains(strings.ToLower(model), "embedding") || // 其他 embedding 模型
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strings.HasPrefix(model, "m3e") || // m3e 系列模型
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if strings.Contains(strings.ToLower(model), "embedding") ||
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strings.HasPrefix(model, "m3e") ||
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strings.Contains(model, "bge-") {
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testRequest.Model = model
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// Embedding 请求
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testRequest.Input = []any{"hello world"} // 修改为any,因为dto/openai_request.go 的ParseInput方法无法处理[]string类型
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return testRequest
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// 返回 EmbeddingRequest
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return &dto.EmbeddingRequest{
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Model: model,
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Input: []any{"hello world"},
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}
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}
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// 并非Embedding 模型
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// Chat/Completion 请求 - 返回 GeneralOpenAIRequest
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testRequest := &dto.GeneralOpenAIRequest{
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Model: model,
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Stream: false,
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Messages: []dto.Message{
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{
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Role: "user",
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Content: "hi",
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},
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},
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}
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if strings.HasPrefix(model, "o") {
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testRequest.MaxCompletionTokens = 10
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} else if strings.Contains(model, "thinking") {
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@@ -373,12 +493,6 @@ func buildTestRequest(model string) *dto.GeneralOpenAIRequest {
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testRequest.MaxTokens = 10
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}
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testMessage := dto.Message{
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Role: "user",
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Content: "hi",
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}
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testRequest.Model = model
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testRequest.Messages = append(testRequest.Messages, testMessage)
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return testRequest
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}
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@@ -402,8 +516,9 @@ func TestChannel(c *gin.Context) {
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// }
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//}()
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testModel := c.Query("model")
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endpointType := c.Query("endpoint_type")
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tik := time.Now()
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result := testChannel(channel, testModel)
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result := testChannel(channel, testModel, endpointType)
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if result.localErr != nil {
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c.JSON(http.StatusOK, gin.H{
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"success": false,
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@@ -429,7 +544,6 @@ func TestChannel(c *gin.Context) {
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"message": "",
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"time": consumedTime,
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})
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return
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}
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var testAllChannelsLock sync.Mutex
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@@ -463,7 +577,7 @@ func testAllChannels(notify bool) error {
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for _, channel := range channels {
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isChannelEnabled := channel.Status == common.ChannelStatusEnabled
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tik := time.Now()
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result := testChannel(channel, "")
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result := testChannel(channel, "", "")
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tok := time.Now()
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milliseconds := tok.Sub(tik).Milliseconds()
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@@ -477,7 +591,7 @@ func testAllChannels(notify bool) error {
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// 当错误检查通过,才检查响应时间
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if common.AutomaticDisableChannelEnabled && !shouldBanChannel {
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if milliseconds > disableThreshold {
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err := errors.New(fmt.Sprintf("响应时间 %.2fs 超过阈值 %.2fs", float64(milliseconds)/1000.0, float64(disableThreshold)/1000.0))
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err := fmt.Errorf("响应时间 %.2fs 超过阈值 %.2fs", float64(milliseconds)/1000.0, float64(disableThreshold)/1000.0)
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newAPIError = types.NewOpenAIError(err, types.ErrorCodeChannelResponseTimeExceeded, http.StatusRequestTimeout)
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shouldBanChannel = true
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}
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@@ -514,7 +628,6 @@ func TestAllChannels(c *gin.Context) {
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"success": true,
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"message": "",
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})
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return
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}
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var autoTestChannelsOnce sync.Once
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Reference in New Issue
Block a user