初始化导入 new-api 源码
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OpenClaw Task Bot
287
relay/channel/gemini/adaptor.go
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287
relay/channel/gemini/adaptor.go
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package gemini
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import (
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"errors"
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"fmt"
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"io"
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"net/http"
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"strings"
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"github.com/QuantumNous/new-api/dto"
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"github.com/QuantumNous/new-api/relay/channel"
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"github.com/QuantumNous/new-api/relay/channel/openai"
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relaycommon "github.com/QuantumNous/new-api/relay/common"
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"github.com/QuantumNous/new-api/relay/constant"
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"github.com/QuantumNous/new-api/setting/model_setting"
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"github.com/QuantumNous/new-api/setting/reasoning"
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"github.com/QuantumNous/new-api/types"
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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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type Adaptor struct {
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}
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func (a *Adaptor) ConvertGeminiRequest(c *gin.Context, info *relaycommon.RelayInfo, request *dto.GeminiChatRequest) (any, error) {
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if len(request.Contents) > 0 {
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for i, content := range request.Contents {
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if i == 0 {
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if request.Contents[0].Role == "" {
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request.Contents[0].Role = "user"
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}
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}
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for _, part := range content.Parts {
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if part.FileData != nil {
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if part.FileData.MimeType == "" && strings.Contains(part.FileData.FileUri, "www.youtube.com") {
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part.FileData.MimeType = "video/webm"
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}
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}
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}
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}
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}
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return request, nil
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}
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func (a *Adaptor) ConvertClaudeRequest(c *gin.Context, info *relaycommon.RelayInfo, req *dto.ClaudeRequest) (any, error) {
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adaptor := openai.Adaptor{}
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oaiReq, err := adaptor.ConvertClaudeRequest(c, info, req)
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if err != nil {
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return nil, err
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}
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return a.ConvertOpenAIRequest(c, info, oaiReq.(*dto.GeneralOpenAIRequest))
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}
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func (a *Adaptor) ConvertAudioRequest(c *gin.Context, info *relaycommon.RelayInfo, request dto.AudioRequest) (io.Reader, error) {
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//TODO implement me
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return nil, errors.New("not implemented")
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}
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func (a *Adaptor) ConvertImageRequest(c *gin.Context, info *relaycommon.RelayInfo, request dto.ImageRequest) (any, error) {
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if !strings.HasPrefix(info.UpstreamModelName, "imagen") {
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return nil, errors.New("not supported model for image generation, only imagen models are supported")
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}
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// convert size to aspect ratio but allow user to specify aspect ratio
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aspectRatio := "1:1" // default aspect ratio
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size := strings.TrimSpace(request.Size)
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if size != "" {
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if strings.Contains(size, ":") {
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aspectRatio = size
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} else {
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switch size {
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case "256x256", "512x512", "1024x1024":
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aspectRatio = "1:1"
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case "1536x1024":
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aspectRatio = "3:2"
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case "1024x1536":
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aspectRatio = "2:3"
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case "1024x1792":
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aspectRatio = "9:16"
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case "1792x1024":
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aspectRatio = "16:9"
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}
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}
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}
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// build gemini imagen request
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geminiRequest := dto.GeminiImageRequest{
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Instances: []dto.GeminiImageInstance{
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{
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Prompt: request.Prompt,
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},
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},
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Parameters: dto.GeminiImageParameters{
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SampleCount: int(lo.FromPtrOr(request.N, uint(1))),
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AspectRatio: aspectRatio,
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PersonGeneration: "allow_adult", // default allow adult
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},
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}
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// Set imageSize when quality parameter is specified
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// Map quality parameter to imageSize (only supported by Standard and Ultra models)
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// quality values: auto, high, medium, low (for gpt-image-1), hd, standard (for dall-e-3)
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// imageSize values: 1K (default), 2K
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// https://ai.google.dev/gemini-api/docs/imagen
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// https://platform.openai.com/docs/api-reference/images/create
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if request.Quality != "" {
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imageSize := "1K" // default
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switch request.Quality {
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case "hd", "high":
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imageSize = "2K"
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case "2K":
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imageSize = "2K"
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case "standard", "medium", "low", "auto", "1K":
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imageSize = "1K"
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default:
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// unknown quality value, default to 1K
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imageSize = "1K"
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}
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geminiRequest.Parameters.ImageSize = imageSize
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}
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return geminiRequest, nil
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}
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func (a *Adaptor) Init(info *relaycommon.RelayInfo) {
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}
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func (a *Adaptor) GetRequestURL(info *relaycommon.RelayInfo) (string, error) {
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if model_setting.GetGeminiSettings().ThinkingAdapterEnabled &&
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!model_setting.ShouldPreserveThinkingSuffix(info.OriginModelName) {
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// 新增逻辑：处理 -thinking-<budget> 格式
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if strings.Contains(info.UpstreamModelName, "-thinking-") {
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parts := strings.Split(info.UpstreamModelName, "-thinking-")
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info.UpstreamModelName = parts[0]
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} else if strings.HasSuffix(info.UpstreamModelName, "-thinking") { // 旧的适配
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info.UpstreamModelName = strings.TrimSuffix(info.UpstreamModelName, "-thinking")
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} else if strings.HasSuffix(info.UpstreamModelName, "-nothinking") {
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info.UpstreamModelName = strings.TrimSuffix(info.UpstreamModelName, "-nothinking")
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} else if baseModel, level, ok := reasoning.TrimEffortSuffix(info.UpstreamModelName); ok && level != "" {
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info.UpstreamModelName = baseModel
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}
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}
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version := model_setting.GetGeminiVersionSetting(info.UpstreamModelName)
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if strings.HasPrefix(info.UpstreamModelName, "imagen") {
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return fmt.Sprintf("%s/%s/models/%s:predict", info.ChannelBaseUrl, version, info.UpstreamModelName), nil
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}
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if strings.HasPrefix(info.UpstreamModelName, "text-embedding") ||
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strings.HasPrefix(info.UpstreamModelName, "embedding") ||
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strings.HasPrefix(info.UpstreamModelName, "gemini-embedding") {
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action := "embedContent"
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if info.IsGeminiBatchEmbedding {
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action = "batchEmbedContents"
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}
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return fmt.Sprintf("%s/%s/models/%s:%s", info.ChannelBaseUrl, version, info.UpstreamModelName, action), nil
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}
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action := "generateContent"
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if info.IsStream {
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action = "streamGenerateContent?alt=sse"
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if info.RelayMode == constant.RelayModeGemini {
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info.DisablePing = true
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}
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}
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return fmt.Sprintf("%s/%s/models/%s:%s", info.ChannelBaseUrl, version, info.UpstreamModelName, action), nil
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}
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func (a *Adaptor) SetupRequestHeader(c *gin.Context, req *http.Header, info *relaycommon.RelayInfo) error {
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channel.SetupApiRequestHeader(info, c, req)
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req.Set("x-goog-api-key", info.ApiKey)
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return nil
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}
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func (a *Adaptor) ConvertOpenAIRequest(c *gin.Context, info *relaycommon.RelayInfo, request *dto.GeneralOpenAIRequest) (any, error) {
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if request == nil {
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return nil, errors.New("request is nil")
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}
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geminiRequest, err := CovertOpenAI2Gemini(c, *request, info)
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if err != nil {
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return nil, err
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}
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return geminiRequest, nil
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}
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func (a *Adaptor) ConvertRerankRequest(c *gin.Context, relayMode int, request dto.RerankRequest) (any, error) {
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return nil, nil
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}
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func (a *Adaptor) ConvertEmbeddingRequest(c *gin.Context, info *relaycommon.RelayInfo, request dto.EmbeddingRequest) (any, error) {
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if request.Input == nil {
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return nil, errors.New("input is required")
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}
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inputs := request.ParseInput()
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if len(inputs) == 0 {
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return nil, errors.New("input is empty")
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}
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// We always build a batch-style payload with `requests`, so ensure we call the
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// batch endpoint upstream to avoid payload/endpoint mismatches.
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info.IsGeminiBatchEmbedding = true
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// process all inputs
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geminiRequests := make([]map[string]interface{}, 0, len(inputs))
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for _, input := range inputs {
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geminiRequest := map[string]interface{}{
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"model": fmt.Sprintf("models/%s", info.UpstreamModelName),
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"content": dto.GeminiChatContent{
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Parts: []dto.GeminiPart{
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{
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Text: input,
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},
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},
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},
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}
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// set specific parameters for different models
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// https://ai.google.dev/api/embeddings?hl=zh-cn#method:-models.embedcontent
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switch info.UpstreamModelName {
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case "text-embedding-004", "gemini-embedding-exp-03-07", "gemini-embedding-001":
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// Only newer models introduced after 2024 support OutputDimensionality
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dimensions := lo.FromPtrOr(request.Dimensions, 0)
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if dimensions > 0 {
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geminiRequest["outputDimensionality"] = dimensions
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}
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}
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geminiRequests = append(geminiRequests, geminiRequest)
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}
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return map[string]interface{}{
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"requests": geminiRequests,
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}, nil
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}
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func (a *Adaptor) ConvertOpenAIResponsesRequest(c *gin.Context, info *relaycommon.RelayInfo, request dto.OpenAIResponsesRequest) (any, error) {
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// TODO implement me
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return nil, errors.New("not implemented")
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}
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func (a *Adaptor) DoRequest(c *gin.Context, info *relaycommon.RelayInfo, requestBody io.Reader) (any, error) {
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return channel.DoApiRequest(a, c, info, requestBody)
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}
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func (a *Adaptor) DoResponse(c *gin.Context, resp *http.Response, info *relaycommon.RelayInfo) (usage any, err *types.NewAPIError) {
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if info.RelayMode == constant.RelayModeGemini {
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if strings.Contains(info.RequestURLPath, ":embedContent") ||
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strings.Contains(info.RequestURLPath, ":batchEmbedContents") {
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return NativeGeminiEmbeddingHandler(c, resp, info)
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}
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if info.IsStream {
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return GeminiTextGenerationStreamHandler(c, info, resp)
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} else {
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return GeminiTextGenerationHandler(c, info, resp)
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}
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}
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if strings.HasPrefix(info.UpstreamModelName, "imagen") {
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return GeminiImageHandler(c, info, resp)
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}
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// check if the model is an embedding model
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if strings.HasPrefix(info.UpstreamModelName, "text-embedding") ||
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strings.HasPrefix(info.UpstreamModelName, "embedding") ||
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strings.HasPrefix(info.UpstreamModelName, "gemini-embedding") {
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return GeminiEmbeddingHandler(c, info, resp)
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}
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if info.IsStream {
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return GeminiChatStreamHandler(c, info, resp)
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} else {
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return GeminiChatHandler(c, info, resp)
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}
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}
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func (a *Adaptor) GetModelList() []string {
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return ModelList
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}
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func (a *Adaptor) GetChannelName() string {
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return ChannelName
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}
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