Files
new-api/relay/channel/gemini/adaptor.go
T
Calcium-Ion 86ac0f7745 refactor: extract protocol conversion layer into standalone relaykit module (#6369)
* 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
2026-07-27 15:56:21 +08:00

303 lines
9.5 KiB
Go

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