* test(relayconvert): add golden snapshot matrix and relaykit boundary guard Phase 0 of the relaykit extraction plan: pin byte-level output of every registered (from,to) request/response/stream conversion route, and forbid kit-bound packages from growing host-only imports. * wip(relayconvert): drop gin.Context from converter signatures; add convmeta draft Phase 1 in progress: relayconvert now takes context.Context; host media resolver adapts gin.Context back at the service boundary. * refactor(relayconvert): decouple converters from RelayInfo, gin, and settings Phase 1 of the relaykit extraction plan: - converters now depend on convmeta.Meta (implemented by RelayInfo) instead of *relaycommon.RelayInfo; ClaudeConvertInfo and the format guesser move to convmeta with aliases left behind - host settings reach converters via a convmeta.Options snapshot built in RelayInfo.ConvOptions; no more model_setting/reasoning global reads inside the conversion layer - effort-suffix helpers move to service/relayconvert/reasoning (old package forwards); chat-to-responses upgrade policy moves to service (host routing logic, not conversion) - golden conversion matrix unchanged * test(relayconvert): tighten boundary — kit packages now free of gin/setting imports * refactor(dto): drop gin and logger dependencies Phase 2 (part 1): dto.Request.IsStream now takes *http.Request instead of *gin.Context (Gemini's impl reads query/path off the std request); dto's three logger calls become common.SysError. Boundary test allowlist is now empty — kit-bound packages import no gin/setting/logger/model. * refactor(kit): extract dependency-free kitutil; dto/types/relayconvert stop importing common Phase 2 of the relaykit extraction plan: - new service/relayconvert/kitutil holds the pure helpers the kit needs (JSON wrappers, pointer/string/uuid/timestamp utils, MaskSensitiveInfo, pluggable LogInfo/LogError hooks, Debug flag) - dto, types, and all relayconvert packages now use kitutil; their only remaining internal deps are dto/types/constant - common keeps every original symbol (MaskSensitiveInfo delegates to kitutil) so host code is untouched; main.go routes kit logging into common.SysLog/SysError and mirrors DebugEnabled - golden conversion matrix unchanged * refactor(kit): move EndpointType/FinishReason to types; OpenRouter dialect via Options Kit packages (dto/types/relayconvert/reasonmap) no longer import constant: - EndpointType and finish-reason values live in types; constant re-exports - the OpenRouter special-case in claude->openai request conversion reads Options.OpenRouterDialect, set by the host from the channel type; InitChannelMeta invalidates the cached snapshot on channel switch * refactor: extract relaykit submodule (dto/types/relayconvert/reasonmap) Phase 3 of the relaykit extraction plan: - new go module github.com/QuantumNous/new-api/relaykit containing dto (minus task family), types, relayconvert (with convmeta/kitutil/reasoning), and reasonmap; host consumes it via require + replace, go.work for dev - task-family dto (task/suno/midjourney/video) stays in the host dto package; dual-consumer host files alias it as taskdto - relaykit builds and tests standalone (GOWORK=off): no host imports, no gin, no DB, no settings - golden conversion matrix unchanged * build(docker): copy relaykit/go.mod before go mod download The local-replace submodule's go.mod must exist inside the build context for the main module graph to resolve. * fix: address relaykit extraction regressions * fix: address relaykit review regressions * docs: document Meta nil receiver contract * fix(relaykit): fail OpenAI→Claude conversion without max_tokens; reject negative default_max_tokens The Claude Messages API requires max_tokens (omitting it is a 400 "Field required"), but with a nil Options.Claude.DefaultMaxTokens hook the converters silently emitted a request the upstream is guaranteed to reject. Both OpenAI Chat and Responses → Claude conversions now return sharedclaude.ErrMissingMaxTokens when no path (client value, default hook, thinking-adapter floor) supplied one. Unreachable in the host, which always configures the hook. Host side, claude.default_max_tokens now rejects negative values at the option API before persisting — they would wrap into huge unsigned values during conversion. Zero stays allowed: the current API treats max_tokens: 0 as cache pre-warming. * fix: make Gemini safety settings read path race-free
303 lines
9.5 KiB
Go
303 lines
9.5 KiB
Go
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/relay/channel"
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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/relaykit/dto"
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"github.com/QuantumNous/new-api/relaykit/relayconvert"
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"github.com/QuantumNous/new-api/relaykit/types"
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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/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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result, err := relayconvert.ConvertRequest(c, info, types.RelayFormatGemini, req)
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if err != nil {
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return nil, err
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}
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geminiRequest, ok := result.Value.(*dto.GeminiChatRequest)
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if !ok {
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return nil, fmt.Errorf("expected Gemini generateContent request, got %T", result.Value)
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}
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return geminiRequest, nil
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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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result, err := relayconvert.ConvertRequest(c, info, types.RelayFormatGemini, request)
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if err != nil {
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return nil, err
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}
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return result.Value, 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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result, err := relayconvert.ConvertRequest(c, info, types.RelayFormatGemini, &request)
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if err != nil {
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return nil, err
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}
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geminiRequest, ok := result.Value.(*dto.GeminiChatRequest)
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if !ok {
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return nil, fmt.Errorf("expected Gemini generateContent request, got %T", result.Value)
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}
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return geminiRequest, nil
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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.RelayModeResponses {
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if info.IsStream {
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return GeminiResponsesStreamHandler(c, info, resp)
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}
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return GeminiResponsesHandler(c, info, resp)
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}
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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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