1071 lines
34 KiB
Go
1071 lines
34 KiB
Go
package gemini
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||
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import (
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"encoding/json"
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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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"one-api/common"
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"one-api/constant"
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"one-api/dto"
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"one-api/relay/channel/openai"
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relaycommon "one-api/relay/common"
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"one-api/relay/helper"
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"one-api/service"
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"one-api/setting/model_setting"
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"one-api/types"
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"strconv"
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"strings"
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"unicode/utf8"
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"github.com/gin-gonic/gin"
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)
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var geminiSupportedMimeTypes = map[string]bool{
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"application/pdf": true,
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"audio/mpeg": true,
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"audio/mp3": true,
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"audio/wav": true,
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"image/png": true,
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"image/jpeg": true,
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"text/plain": true,
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"video/mov": true,
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"video/mpeg": true,
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"video/mp4": true,
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"video/mpg": true,
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"video/avi": true,
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"video/wmv": true,
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"video/mpegps": true,
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"video/flv": true,
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}
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// Gemini 允许的思考预算范围
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const (
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pro25MinBudget = 128
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pro25MaxBudget = 32768
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flash25MaxBudget = 24576
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flash25LiteMinBudget = 512
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flash25LiteMaxBudget = 24576
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)
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// clampThinkingBudget 根据模型名称将预算限制在允许的范围内
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func clampThinkingBudget(modelName string, budget int) int {
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isNew25Pro := strings.HasPrefix(modelName, "gemini-2.5-pro") &&
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!strings.HasPrefix(modelName, "gemini-2.5-pro-preview-05-06") &&
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!strings.HasPrefix(modelName, "gemini-2.5-pro-preview-03-25")
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is25FlashLite := strings.HasPrefix(modelName, "gemini-2.5-flash-lite")
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if is25FlashLite {
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if budget < flash25LiteMinBudget {
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return flash25LiteMinBudget
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}
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if budget > flash25LiteMaxBudget {
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return flash25LiteMaxBudget
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}
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} else if isNew25Pro {
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if budget < pro25MinBudget {
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return pro25MinBudget
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}
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if budget > pro25MaxBudget {
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return pro25MaxBudget
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}
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} else { // 其他模型
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if budget < 0 {
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return 0
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}
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if budget > flash25MaxBudget {
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return flash25MaxBudget
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}
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}
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return budget
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}
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func ThinkingAdaptor(geminiRequest *dto.GeminiChatRequest, info *relaycommon.RelayInfo) {
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if model_setting.GetGeminiSettings().ThinkingAdapterEnabled {
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modelName := info.UpstreamModelName
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isNew25Pro := strings.HasPrefix(modelName, "gemini-2.5-pro") &&
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!strings.HasPrefix(modelName, "gemini-2.5-pro-preview-05-06") &&
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!strings.HasPrefix(modelName, "gemini-2.5-pro-preview-03-25")
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if strings.Contains(modelName, "-thinking-") {
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parts := strings.SplitN(modelName, "-thinking-", 2)
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if len(parts) == 2 && parts[1] != "" {
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if budgetTokens, err := strconv.Atoi(parts[1]); err == nil {
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clampedBudget := clampThinkingBudget(modelName, budgetTokens)
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geminiRequest.GenerationConfig.ThinkingConfig = &dto.GeminiThinkingConfig{
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ThinkingBudget: common.GetPointer(clampedBudget),
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IncludeThoughts: true,
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}
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}
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}
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} else if strings.HasSuffix(modelName, "-thinking") {
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unsupportedModels := []string{
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"gemini-2.5-pro-preview-05-06",
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"gemini-2.5-pro-preview-03-25",
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}
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isUnsupported := false
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for _, unsupportedModel := range unsupportedModels {
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if strings.HasPrefix(modelName, unsupportedModel) {
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isUnsupported = true
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break
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}
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||
}
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if isUnsupported {
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geminiRequest.GenerationConfig.ThinkingConfig = &dto.GeminiThinkingConfig{
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IncludeThoughts: true,
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}
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} else {
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geminiRequest.GenerationConfig.ThinkingConfig = &dto.GeminiThinkingConfig{
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IncludeThoughts: true,
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}
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if geminiRequest.GenerationConfig.MaxOutputTokens > 0 {
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budgetTokens := model_setting.GetGeminiSettings().ThinkingAdapterBudgetTokensPercentage * float64(geminiRequest.GenerationConfig.MaxOutputTokens)
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clampedBudget := clampThinkingBudget(modelName, int(budgetTokens))
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geminiRequest.GenerationConfig.ThinkingConfig.ThinkingBudget = common.GetPointer(clampedBudget)
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}
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}
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} else if strings.HasSuffix(modelName, "-nothinking") {
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if !isNew25Pro {
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geminiRequest.GenerationConfig.ThinkingConfig = &dto.GeminiThinkingConfig{
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ThinkingBudget: common.GetPointer(0),
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}
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}
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}
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}
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}
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// Setting safety to the lowest possible values since Gemini is already powerless enough
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func CovertGemini2OpenAI(textRequest dto.GeneralOpenAIRequest, info *relaycommon.RelayInfo) (*dto.GeminiChatRequest, error) {
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geminiRequest := dto.GeminiChatRequest{
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Contents: make([]dto.GeminiChatContent, 0, len(textRequest.Messages)),
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GenerationConfig: dto.GeminiChatGenerationConfig{
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Temperature: textRequest.Temperature,
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TopP: textRequest.TopP,
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MaxOutputTokens: textRequest.MaxTokens,
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Seed: int64(textRequest.Seed),
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},
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}
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if model_setting.IsGeminiModelSupportImagine(info.UpstreamModelName) {
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geminiRequest.GenerationConfig.ResponseModalities = []string{
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"TEXT",
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"IMAGE",
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}
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}
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ThinkingAdaptor(&geminiRequest, info)
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safetySettings := make([]dto.GeminiChatSafetySettings, 0, len(SafetySettingList))
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for _, category := range SafetySettingList {
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safetySettings = append(safetySettings, dto.GeminiChatSafetySettings{
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Category: category,
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Threshold: model_setting.GetGeminiSafetySetting(category),
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})
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}
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geminiRequest.SafetySettings = safetySettings
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// openaiContent.FuncToToolCalls()
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if textRequest.Tools != nil {
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functions := make([]dto.FunctionRequest, 0, len(textRequest.Tools))
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googleSearch := false
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codeExecution := false
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for _, tool := range textRequest.Tools {
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if tool.Function.Name == "googleSearch" {
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googleSearch = true
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continue
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}
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if tool.Function.Name == "codeExecution" {
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codeExecution = true
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continue
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}
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if tool.Function.Parameters != nil {
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params, ok := tool.Function.Parameters.(map[string]interface{})
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if ok {
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if props, hasProps := params["properties"].(map[string]interface{}); hasProps {
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if len(props) == 0 {
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tool.Function.Parameters = nil
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}
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}
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}
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}
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// Clean the parameters before appending
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cleanedParams := cleanFunctionParameters(tool.Function.Parameters)
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tool.Function.Parameters = cleanedParams
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functions = append(functions, tool.Function)
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}
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if codeExecution {
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geminiRequest.Tools = append(geminiRequest.Tools, dto.GeminiChatTool{
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CodeExecution: make(map[string]string),
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})
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}
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if googleSearch {
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geminiRequest.Tools = append(geminiRequest.Tools, dto.GeminiChatTool{
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GoogleSearch: make(map[string]string),
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})
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}
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if len(functions) > 0 {
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geminiRequest.Tools = append(geminiRequest.Tools, dto.GeminiChatTool{
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FunctionDeclarations: functions,
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})
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}
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// common.SysLog("tools: " + fmt.Sprintf("%+v", geminiRequest.Tools))
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// json_data, _ := json.Marshal(geminiRequest.Tools)
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// common.SysLog("tools_json: " + string(json_data))
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}
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if textRequest.ResponseFormat != nil && (textRequest.ResponseFormat.Type == "json_schema" || textRequest.ResponseFormat.Type == "json_object") {
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geminiRequest.GenerationConfig.ResponseMimeType = "application/json"
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if len(textRequest.ResponseFormat.JsonSchema) > 0 {
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// 先将json.RawMessage解析
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var jsonSchema dto.FormatJsonSchema
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if err := common.Unmarshal(textRequest.ResponseFormat.JsonSchema, &jsonSchema); err == nil {
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cleanedSchema := removeAdditionalPropertiesWithDepth(jsonSchema.Schema, 0)
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geminiRequest.GenerationConfig.ResponseSchema = cleanedSchema
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}
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}
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}
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tool_call_ids := make(map[string]string)
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var system_content []string
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//shouldAddDummyModelMessage := false
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for _, message := range textRequest.Messages {
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if message.Role == "system" {
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system_content = append(system_content, message.StringContent())
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continue
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} else if message.Role == "tool" || message.Role == "function" {
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if len(geminiRequest.Contents) == 0 || geminiRequest.Contents[len(geminiRequest.Contents)-1].Role == "model" {
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geminiRequest.Contents = append(geminiRequest.Contents, dto.GeminiChatContent{
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Role: "user",
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})
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}
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var parts = &geminiRequest.Contents[len(geminiRequest.Contents)-1].Parts
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name := ""
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if message.Name != nil {
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name = *message.Name
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} else if val, exists := tool_call_ids[message.ToolCallId]; exists {
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name = val
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}
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var contentMap map[string]interface{}
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contentStr := message.StringContent()
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// 1. 尝试解析为 JSON 对象
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if err := json.Unmarshal([]byte(contentStr), &contentMap); err != nil {
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// 2. 如果失败，尝试解析为 JSON 数组
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var contentSlice []interface{}
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if err := json.Unmarshal([]byte(contentStr), &contentSlice); err == nil {
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// 如果是数组，包装成对象
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contentMap = map[string]interface{}{"result": contentSlice}
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} else {
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// 3. 如果再次失败，作为纯文本处理
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contentMap = map[string]interface{}{"content": contentStr}
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}
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}
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functionResp := &dto.GeminiFunctionResponse{
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Name: name,
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Response: contentMap,
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}
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*parts = append(*parts, dto.GeminiPart{
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FunctionResponse: functionResp,
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})
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continue
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}
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var parts []dto.GeminiPart
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content := dto.GeminiChatContent{
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Role: message.Role,
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}
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// isToolCall := false
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if message.ToolCalls != nil {
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// message.Role = "model"
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// isToolCall = true
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for _, call := range message.ParseToolCalls() {
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args := map[string]interface{}{}
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if call.Function.Arguments != "" {
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if json.Unmarshal([]byte(call.Function.Arguments), &args) != nil {
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return nil, fmt.Errorf("invalid arguments for function %s, args: %s", call.Function.Name, call.Function.Arguments)
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}
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}
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toolCall := dto.GeminiPart{
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FunctionCall: &dto.FunctionCall{
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FunctionName: call.Function.Name,
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Arguments: args,
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},
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}
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parts = append(parts, toolCall)
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tool_call_ids[call.ID] = call.Function.Name
|
||
}
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||
}
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openaiContent := message.ParseContent()
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||
imageNum := 0
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for _, part := range openaiContent {
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||
if part.Type == dto.ContentTypeText {
|
||
if part.Text == "" {
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||
continue
|
||
}
|
||
parts = append(parts, dto.GeminiPart{
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||
Text: part.Text,
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||
})
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} else if part.Type == dto.ContentTypeImageURL {
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imageNum += 1
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||
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||
if constant.GeminiVisionMaxImageNum != -1 && imageNum > constant.GeminiVisionMaxImageNum {
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return nil, fmt.Errorf("too many images in the message, max allowed is %d", constant.GeminiVisionMaxImageNum)
|
||
}
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||
// 判断是否是url
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if strings.HasPrefix(part.GetImageMedia().Url, "http") {
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||
// 是url，获取文件的类型和base64编码的数据
|
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fileData, err := service.GetFileBase64FromUrl(part.GetImageMedia().Url)
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||
if err != nil {
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||
return nil, fmt.Errorf("get file base64 from url '%s' failed: %w", part.GetImageMedia().Url, err)
|
||
}
|
||
|
||
// 校验 MimeType 是否在 Gemini 支持的白名单中
|
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if _, ok := geminiSupportedMimeTypes[strings.ToLower(fileData.MimeType)]; !ok {
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url := part.GetImageMedia().Url
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return nil, fmt.Errorf("mime type is not supported by Gemini: '%s', url: '%s', supported types are: %v", fileData.MimeType, url, getSupportedMimeTypesList())
|
||
}
|
||
|
||
parts = append(parts, dto.GeminiPart{
|
||
InlineData: &dto.GeminiInlineData{
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||
MimeType: fileData.MimeType, // 使用原始的 MimeType，因为大小写可能对API有意义
|
||
Data: fileData.Base64Data,
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||
},
|
||
})
|
||
} else {
|
||
format, base64String, err := service.DecodeBase64FileData(part.GetImageMedia().Url)
|
||
if err != nil {
|
||
return nil, fmt.Errorf("decode base64 image data failed: %s", err.Error())
|
||
}
|
||
parts = append(parts, dto.GeminiPart{
|
||
InlineData: &dto.GeminiInlineData{
|
||
MimeType: format,
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||
Data: base64String,
|
||
},
|
||
})
|
||
}
|
||
} else if part.Type == dto.ContentTypeFile {
|
||
if part.GetFile().FileId != "" {
|
||
return nil, fmt.Errorf("only base64 file is supported in gemini")
|
||
}
|
||
format, base64String, err := service.DecodeBase64FileData(part.GetFile().FileData)
|
||
if err != nil {
|
||
return nil, fmt.Errorf("decode base64 file data failed: %s", err.Error())
|
||
}
|
||
parts = append(parts, dto.GeminiPart{
|
||
InlineData: &dto.GeminiInlineData{
|
||
MimeType: format,
|
||
Data: base64String,
|
||
},
|
||
})
|
||
} else if part.Type == dto.ContentTypeInputAudio {
|
||
if part.GetInputAudio().Data == "" {
|
||
return nil, fmt.Errorf("only base64 audio is supported in gemini")
|
||
}
|
||
base64String, err := service.DecodeBase64AudioData(part.GetInputAudio().Data)
|
||
if err != nil {
|
||
return nil, fmt.Errorf("decode base64 audio data failed: %s", err.Error())
|
||
}
|
||
parts = append(parts, dto.GeminiPart{
|
||
InlineData: &dto.GeminiInlineData{
|
||
MimeType: "audio/" + part.GetInputAudio().Format,
|
||
Data: base64String,
|
||
},
|
||
})
|
||
}
|
||
}
|
||
|
||
content.Parts = parts
|
||
|
||
// there's no assistant role in gemini and API shall vomit if Role is not user or model
|
||
if content.Role == "assistant" {
|
||
content.Role = "model"
|
||
}
|
||
if len(content.Parts) > 0 {
|
||
geminiRequest.Contents = append(geminiRequest.Contents, content)
|
||
}
|
||
}
|
||
|
||
if len(system_content) > 0 {
|
||
geminiRequest.SystemInstructions = &dto.GeminiChatContent{
|
||
Parts: []dto.GeminiPart{
|
||
{
|
||
Text: strings.Join(system_content, "\n"),
|
||
},
|
||
},
|
||
}
|
||
}
|
||
|
||
return &geminiRequest, nil
|
||
}
|
||
|
||
// Helper function to get a list of supported MIME types for error messages
|
||
func getSupportedMimeTypesList() []string {
|
||
keys := make([]string, 0, len(geminiSupportedMimeTypes))
|
||
for k := range geminiSupportedMimeTypes {
|
||
keys = append(keys, k)
|
||
}
|
||
return keys
|
||
}
|
||
|
||
// cleanFunctionParameters recursively removes unsupported fields from Gemini function parameters.
|
||
func cleanFunctionParameters(params interface{}) interface{} {
|
||
if params == nil {
|
||
return nil
|
||
}
|
||
|
||
switch v := params.(type) {
|
||
case map[string]interface{}:
|
||
// Create a copy to avoid modifying the original
|
||
cleanedMap := make(map[string]interface{})
|
||
for k, val := range v {
|
||
cleanedMap[k] = val
|
||
}
|
||
|
||
// Remove unsupported root-level fields
|
||
delete(cleanedMap, "default")
|
||
delete(cleanedMap, "exclusiveMaximum")
|
||
delete(cleanedMap, "exclusiveMinimum")
|
||
delete(cleanedMap, "$schema")
|
||
delete(cleanedMap, "additionalProperties")
|
||
|
||
// Check and clean 'format' for string types
|
||
if propType, typeExists := cleanedMap["type"].(string); typeExists && propType == "string" {
|
||
if formatValue, formatExists := cleanedMap["format"].(string); formatExists {
|
||
if formatValue != "enum" && formatValue != "date-time" {
|
||
delete(cleanedMap, "format")
|
||
}
|
||
}
|
||
}
|
||
|
||
// Clean properties
|
||
if props, ok := cleanedMap["properties"].(map[string]interface{}); ok && props != nil {
|
||
cleanedProps := make(map[string]interface{})
|
||
for propName, propValue := range props {
|
||
cleanedProps[propName] = cleanFunctionParameters(propValue)
|
||
}
|
||
cleanedMap["properties"] = cleanedProps
|
||
}
|
||
|
||
// Recursively clean items in arrays
|
||
if items, ok := cleanedMap["items"].(map[string]interface{}); ok && items != nil {
|
||
cleanedMap["items"] = cleanFunctionParameters(items)
|
||
}
|
||
// Also handle items if it's an array of schemas
|
||
if itemsArray, ok := cleanedMap["items"].([]interface{}); ok {
|
||
cleanedItemsArray := make([]interface{}, len(itemsArray))
|
||
for i, item := range itemsArray {
|
||
cleanedItemsArray[i] = cleanFunctionParameters(item)
|
||
}
|
||
cleanedMap["items"] = cleanedItemsArray
|
||
}
|
||
|
||
// Recursively clean other schema composition keywords
|
||
for _, field := range []string{"allOf", "anyOf", "oneOf"} {
|
||
if nested, ok := cleanedMap[field].([]interface{}); ok {
|
||
cleanedNested := make([]interface{}, len(nested))
|
||
for i, item := range nested {
|
||
cleanedNested[i] = cleanFunctionParameters(item)
|
||
}
|
||
cleanedMap[field] = cleanedNested
|
||
}
|
||
}
|
||
|
||
// Recursively clean patternProperties
|
||
if patternProps, ok := cleanedMap["patternProperties"].(map[string]interface{}); ok {
|
||
cleanedPatternProps := make(map[string]interface{})
|
||
for pattern, schema := range patternProps {
|
||
cleanedPatternProps[pattern] = cleanFunctionParameters(schema)
|
||
}
|
||
cleanedMap["patternProperties"] = cleanedPatternProps
|
||
}
|
||
|
||
// Recursively clean definitions
|
||
if definitions, ok := cleanedMap["definitions"].(map[string]interface{}); ok {
|
||
cleanedDefinitions := make(map[string]interface{})
|
||
for defName, defSchema := range definitions {
|
||
cleanedDefinitions[defName] = cleanFunctionParameters(defSchema)
|
||
}
|
||
cleanedMap["definitions"] = cleanedDefinitions
|
||
}
|
||
|
||
// Recursively clean $defs (newer JSON Schema draft)
|
||
if defs, ok := cleanedMap["$defs"].(map[string]interface{}); ok {
|
||
cleanedDefs := make(map[string]interface{})
|
||
for defName, defSchema := range defs {
|
||
cleanedDefs[defName] = cleanFunctionParameters(defSchema)
|
||
}
|
||
cleanedMap["$defs"] = cleanedDefs
|
||
}
|
||
|
||
// Clean conditional keywords
|
||
for _, field := range []string{"if", "then", "else", "not"} {
|
||
if nested, ok := cleanedMap[field]; ok {
|
||
cleanedMap[field] = cleanFunctionParameters(nested)
|
||
}
|
||
}
|
||
|
||
return cleanedMap
|
||
|
||
case []interface{}:
|
||
// Handle arrays of schemas
|
||
cleanedArray := make([]interface{}, len(v))
|
||
for i, item := range v {
|
||
cleanedArray[i] = cleanFunctionParameters(item)
|
||
}
|
||
return cleanedArray
|
||
|
||
default:
|
||
// Not a map or array, return as is (e.g., could be a primitive)
|
||
return params
|
||
}
|
||
}
|
||
|
||
func removeAdditionalPropertiesWithDepth(schema interface{}, depth int) interface{} {
|
||
if depth >= 5 {
|
||
return schema
|
||
}
|
||
|
||
v, ok := schema.(map[string]interface{})
|
||
if !ok || len(v) == 0 {
|
||
return schema
|
||
}
|
||
// 删除所有的title字段
|
||
delete(v, "title")
|
||
delete(v, "$schema")
|
||
// 如果type不为object和array，则直接返回
|
||
if typeVal, exists := v["type"]; !exists || (typeVal != "object" && typeVal != "array") {
|
||
return schema
|
||
}
|
||
switch v["type"] {
|
||
case "object":
|
||
delete(v, "additionalProperties")
|
||
// 处理 properties
|
||
if properties, ok := v["properties"].(map[string]interface{}); ok {
|
||
for key, value := range properties {
|
||
properties[key] = removeAdditionalPropertiesWithDepth(value, depth+1)
|
||
}
|
||
}
|
||
for _, field := range []string{"allOf", "anyOf", "oneOf"} {
|
||
if nested, ok := v[field].([]interface{}); ok {
|
||
for i, item := range nested {
|
||
nested[i] = removeAdditionalPropertiesWithDepth(item, depth+1)
|
||
}
|
||
}
|
||
}
|
||
case "array":
|
||
if items, ok := v["items"].(map[string]interface{}); ok {
|
||
v["items"] = removeAdditionalPropertiesWithDepth(items, depth+1)
|
||
}
|
||
}
|
||
|
||
return v
|
||
}
|
||
|
||
func unescapeString(s string) (string, error) {
|
||
var result []rune
|
||
escaped := false
|
||
i := 0
|
||
|
||
for i < len(s) {
|
||
r, size := utf8.DecodeRuneInString(s[i:]) // 正确解码UTF-8字符
|
||
if r == utf8.RuneError {
|
||
return "", fmt.Errorf("invalid UTF-8 encoding")
|
||
}
|
||
|
||
if escaped {
|
||
// 如果是转义符后的字符，检查其类型
|
||
switch r {
|
||
case '"':
|
||
result = append(result, '"')
|
||
case '\\':
|
||
result = append(result, '\\')
|
||
case '/':
|
||
result = append(result, '/')
|
||
case 'b':
|
||
result = append(result, '\b')
|
||
case 'f':
|
||
result = append(result, '\f')
|
||
case 'n':
|
||
result = append(result, '\n')
|
||
case 'r':
|
||
result = append(result, '\r')
|
||
case 't':
|
||
result = append(result, '\t')
|
||
case '\'':
|
||
result = append(result, '\'')
|
||
default:
|
||
// 如果遇到一个非法的转义字符，直接按原样输出
|
||
result = append(result, '\\', r)
|
||
}
|
||
escaped = false
|
||
} else {
|
||
if r == '\\' {
|
||
escaped = true // 记录反斜杠作为转义符
|
||
} else {
|
||
result = append(result, r)
|
||
}
|
||
}
|
||
i += size // 移动到下一个字符
|
||
}
|
||
|
||
return string(result), nil
|
||
}
|
||
func unescapeMapOrSlice(data interface{}) interface{} {
|
||
switch v := data.(type) {
|
||
case map[string]interface{}:
|
||
for k, val := range v {
|
||
v[k] = unescapeMapOrSlice(val)
|
||
}
|
||
case []interface{}:
|
||
for i, val := range v {
|
||
v[i] = unescapeMapOrSlice(val)
|
||
}
|
||
case string:
|
||
if unescaped, err := unescapeString(v); err != nil {
|
||
return v
|
||
} else {
|
||
return unescaped
|
||
}
|
||
}
|
||
return data
|
||
}
|
||
|
||
func getResponseToolCall(item *dto.GeminiPart) *dto.ToolCallResponse {
|
||
var argsBytes []byte
|
||
var err error
|
||
if result, ok := item.FunctionCall.Arguments.(map[string]interface{}); ok {
|
||
argsBytes, err = json.Marshal(unescapeMapOrSlice(result))
|
||
} else {
|
||
argsBytes, err = json.Marshal(item.FunctionCall.Arguments)
|
||
}
|
||
|
||
if err != nil {
|
||
return nil
|
||
}
|
||
return &dto.ToolCallResponse{
|
||
ID: fmt.Sprintf("call_%s", common.GetUUID()),
|
||
Type: "function",
|
||
Function: dto.FunctionResponse{
|
||
Arguments: string(argsBytes),
|
||
Name: item.FunctionCall.FunctionName,
|
||
},
|
||
}
|
||
}
|
||
|
||
func responseGeminiChat2OpenAI(c *gin.Context, response *dto.GeminiChatResponse) *dto.OpenAITextResponse {
|
||
fullTextResponse := dto.OpenAITextResponse{
|
||
Id: helper.GetResponseID(c),
|
||
Object: "chat.completion",
|
||
Created: common.GetTimestamp(),
|
||
Choices: make([]dto.OpenAITextResponseChoice, 0, len(response.Candidates)),
|
||
}
|
||
isToolCall := false
|
||
for _, candidate := range response.Candidates {
|
||
choice := dto.OpenAITextResponseChoice{
|
||
Index: int(candidate.Index),
|
||
Message: dto.Message{
|
||
Role: "assistant",
|
||
Content: "",
|
||
},
|
||
FinishReason: constant.FinishReasonStop,
|
||
}
|
||
if len(candidate.Content.Parts) > 0 {
|
||
var texts []string
|
||
var toolCalls []dto.ToolCallResponse
|
||
for _, part := range candidate.Content.Parts {
|
||
if part.FunctionCall != nil {
|
||
choice.FinishReason = constant.FinishReasonToolCalls
|
||
if call := getResponseToolCall(&part); call != nil {
|
||
toolCalls = append(toolCalls, *call)
|
||
}
|
||
} else if part.Thought {
|
||
choice.Message.ReasoningContent = part.Text
|
||
} else {
|
||
if part.ExecutableCode != nil {
|
||
texts = append(texts, "```"+part.ExecutableCode.Language+"\n"+part.ExecutableCode.Code+"\n```")
|
||
} else if part.CodeExecutionResult != nil {
|
||
texts = append(texts, "```output\n"+part.CodeExecutionResult.Output+"\n```")
|
||
} else {
|
||
// 过滤掉空行
|
||
if part.Text != "\n" {
|
||
texts = append(texts, part.Text)
|
||
}
|
||
}
|
||
}
|
||
}
|
||
if len(toolCalls) > 0 {
|
||
choice.Message.SetToolCalls(toolCalls)
|
||
isToolCall = true
|
||
}
|
||
choice.Message.SetStringContent(strings.Join(texts, "\n"))
|
||
|
||
}
|
||
if candidate.FinishReason != nil {
|
||
switch *candidate.FinishReason {
|
||
case "STOP":
|
||
choice.FinishReason = constant.FinishReasonStop
|
||
case "MAX_TOKENS":
|
||
choice.FinishReason = constant.FinishReasonLength
|
||
default:
|
||
choice.FinishReason = constant.FinishReasonContentFilter
|
||
}
|
||
}
|
||
if isToolCall {
|
||
choice.FinishReason = constant.FinishReasonToolCalls
|
||
}
|
||
|
||
fullTextResponse.Choices = append(fullTextResponse.Choices, choice)
|
||
}
|
||
return &fullTextResponse
|
||
}
|
||
|
||
func streamResponseGeminiChat2OpenAI(geminiResponse *dto.GeminiChatResponse) (*dto.ChatCompletionsStreamResponse, bool) {
|
||
choices := make([]dto.ChatCompletionsStreamResponseChoice, 0, len(geminiResponse.Candidates))
|
||
isStop := false
|
||
for _, candidate := range geminiResponse.Candidates {
|
||
if candidate.FinishReason != nil && *candidate.FinishReason == "STOP" {
|
||
isStop = true
|
||
candidate.FinishReason = nil
|
||
}
|
||
choice := dto.ChatCompletionsStreamResponseChoice{
|
||
Index: int(candidate.Index),
|
||
Delta: dto.ChatCompletionsStreamResponseChoiceDelta{
|
||
//Role: "assistant",
|
||
},
|
||
}
|
||
var texts []string
|
||
isTools := false
|
||
isThought := false
|
||
if candidate.FinishReason != nil {
|
||
// p := GeminiConvertFinishReason(*candidate.FinishReason)
|
||
switch *candidate.FinishReason {
|
||
case "STOP":
|
||
choice.FinishReason = &constant.FinishReasonStop
|
||
case "MAX_TOKENS":
|
||
choice.FinishReason = &constant.FinishReasonLength
|
||
default:
|
||
choice.FinishReason = &constant.FinishReasonContentFilter
|
||
}
|
||
}
|
||
for _, part := range candidate.Content.Parts {
|
||
if part.InlineData != nil {
|
||
if strings.HasPrefix(part.InlineData.MimeType, "image") {
|
||
imgText := "![image](data:" + part.InlineData.MimeType + ";base64," + part.InlineData.Data + ")"
|
||
texts = append(texts, imgText)
|
||
}
|
||
} else if part.FunctionCall != nil {
|
||
isTools = true
|
||
if call := getResponseToolCall(&part); call != nil {
|
||
call.SetIndex(len(choice.Delta.ToolCalls))
|
||
choice.Delta.ToolCalls = append(choice.Delta.ToolCalls, *call)
|
||
}
|
||
} else if part.Thought {
|
||
isThought = true
|
||
texts = append(texts, part.Text)
|
||
} else {
|
||
if part.ExecutableCode != nil {
|
||
texts = append(texts, "```"+part.ExecutableCode.Language+"\n"+part.ExecutableCode.Code+"\n```\n")
|
||
} else if part.CodeExecutionResult != nil {
|
||
texts = append(texts, "```output\n"+part.CodeExecutionResult.Output+"\n```\n")
|
||
} else {
|
||
if part.Text != "\n" {
|
||
texts = append(texts, part.Text)
|
||
}
|
||
}
|
||
}
|
||
}
|
||
if isThought {
|
||
choice.Delta.SetReasoningContent(strings.Join(texts, "\n"))
|
||
} else {
|
||
choice.Delta.SetContentString(strings.Join(texts, "\n"))
|
||
}
|
||
if isTools {
|
||
choice.FinishReason = &constant.FinishReasonToolCalls
|
||
}
|
||
choices = append(choices, choice)
|
||
}
|
||
|
||
var response dto.ChatCompletionsStreamResponse
|
||
response.Object = "chat.completion.chunk"
|
||
response.Choices = choices
|
||
return &response, isStop
|
||
}
|
||
|
||
func handleStream(c *gin.Context, info *relaycommon.RelayInfo, resp *dto.ChatCompletionsStreamResponse) error {
|
||
streamData, err := common.Marshal(resp)
|
||
if err != nil {
|
||
return fmt.Errorf("failed to marshal stream response: %w", err)
|
||
}
|
||
err = openai.HandleStreamFormat(c, info, string(streamData), info.ChannelSetting.ForceFormat, info.ChannelSetting.ThinkingToContent)
|
||
if err != nil {
|
||
return fmt.Errorf("failed to handle stream format: %w", err)
|
||
}
|
||
return nil
|
||
}
|
||
|
||
func handleFinalStream(c *gin.Context, info *relaycommon.RelayInfo, resp *dto.ChatCompletionsStreamResponse) error {
|
||
streamData, err := common.Marshal(resp)
|
||
if err != nil {
|
||
return fmt.Errorf("failed to marshal stream response: %w", err)
|
||
}
|
||
openai.HandleFinalResponse(c, info, string(streamData), resp.Id, resp.Created, resp.Model, resp.GetSystemFingerprint(), resp.Usage, false)
|
||
return nil
|
||
}
|
||
|
||
func GeminiChatStreamHandler(c *gin.Context, info *relaycommon.RelayInfo, resp *http.Response) (*dto.Usage, *types.NewAPIError) {
|
||
// responseText := ""
|
||
id := helper.GetResponseID(c)
|
||
createAt := common.GetTimestamp()
|
||
responseText := strings.Builder{}
|
||
var usage = &dto.Usage{}
|
||
var imageCount int
|
||
|
||
helper.StreamScannerHandler(c, resp, info, func(data string) bool {
|
||
var geminiResponse dto.GeminiChatResponse
|
||
err := common.UnmarshalJsonStr(data, &geminiResponse)
|
||
if err != nil {
|
||
common.LogError(c, "error unmarshalling stream response: "+err.Error())
|
||
return false
|
||
}
|
||
|
||
for _, candidate := range geminiResponse.Candidates {
|
||
for _, part := range candidate.Content.Parts {
|
||
if part.InlineData != nil && part.InlineData.MimeType != "" {
|
||
imageCount++
|
||
}
|
||
if part.Text != "" {
|
||
responseText.WriteString(part.Text)
|
||
}
|
||
}
|
||
}
|
||
|
||
response, isStop := streamResponseGeminiChat2OpenAI(&geminiResponse)
|
||
|
||
response.Id = id
|
||
response.Created = createAt
|
||
response.Model = info.UpstreamModelName
|
||
if geminiResponse.UsageMetadata.TotalTokenCount != 0 {
|
||
usage.PromptTokens = geminiResponse.UsageMetadata.PromptTokenCount
|
||
usage.CompletionTokens = geminiResponse.UsageMetadata.CandidatesTokenCount
|
||
usage.CompletionTokenDetails.ReasoningTokens = geminiResponse.UsageMetadata.ThoughtsTokenCount
|
||
usage.TotalTokens = geminiResponse.UsageMetadata.TotalTokenCount
|
||
for _, detail := range geminiResponse.UsageMetadata.PromptTokensDetails {
|
||
if detail.Modality == "AUDIO" {
|
||
usage.PromptTokensDetails.AudioTokens = detail.TokenCount
|
||
} else if detail.Modality == "TEXT" {
|
||
usage.PromptTokensDetails.TextTokens = detail.TokenCount
|
||
}
|
||
}
|
||
}
|
||
|
||
if info.SendResponseCount == 0 {
|
||
// send first response
|
||
err = handleStream(c, info, helper.GenerateStartEmptyResponse(id, createAt, info.UpstreamModelName, nil))
|
||
if err != nil {
|
||
common.LogError(c, err.Error())
|
||
}
|
||
}
|
||
|
||
err = handleStream(c, info, response)
|
||
if err != nil {
|
||
common.LogError(c, err.Error())
|
||
}
|
||
if isStop {
|
||
_ = handleStream(c, info, helper.GenerateStopResponse(id, createAt, info.UpstreamModelName, constant.FinishReasonStop))
|
||
}
|
||
return true
|
||
})
|
||
|
||
if info.SendResponseCount == 0 {
|
||
// 空补全，报错不计费
|
||
// empty response, throw an error
|
||
return nil, types.NewOpenAIError(errors.New("no response received from Gemini API"), types.ErrorCodeEmptyResponse, http.StatusInternalServerError)
|
||
}
|
||
|
||
if imageCount != 0 {
|
||
if usage.CompletionTokens == 0 {
|
||
usage.CompletionTokens = imageCount * 258
|
||
}
|
||
}
|
||
|
||
usage.PromptTokensDetails.TextTokens = usage.PromptTokens
|
||
usage.CompletionTokens = usage.TotalTokens - usage.PromptTokens
|
||
|
||
if usage.CompletionTokens == 0 {
|
||
str := responseText.String()
|
||
if len(str) > 0 {
|
||
usage = service.ResponseText2Usage(responseText.String(), info.UpstreamModelName, info.PromptTokens)
|
||
} else {
|
||
// 空补全，不需要使用量
|
||
usage = &dto.Usage{}
|
||
}
|
||
}
|
||
|
||
response := helper.GenerateFinalUsageResponse(id, createAt, info.UpstreamModelName, *usage)
|
||
err := handleFinalStream(c, info, response)
|
||
if err != nil {
|
||
common.SysError("send final response failed: " + err.Error())
|
||
}
|
||
//if info.RelayFormat == relaycommon.RelayFormatOpenAI {
|
||
// helper.Done(c)
|
||
//}
|
||
//resp.Body.Close()
|
||
return usage, nil
|
||
}
|
||
|
||
func GeminiChatHandler(c *gin.Context, info *relaycommon.RelayInfo, resp *http.Response) (*dto.Usage, *types.NewAPIError) {
|
||
responseBody, err := io.ReadAll(resp.Body)
|
||
if err != nil {
|
||
return nil, types.NewOpenAIError(err, types.ErrorCodeBadResponseBody, http.StatusInternalServerError)
|
||
}
|
||
common.CloseResponseBodyGracefully(resp)
|
||
if common.DebugEnabled {
|
||
println(string(responseBody))
|
||
}
|
||
var geminiResponse dto.GeminiChatResponse
|
||
err = common.Unmarshal(responseBody, &geminiResponse)
|
||
if err != nil {
|
||
return nil, types.NewOpenAIError(err, types.ErrorCodeBadResponseBody, http.StatusInternalServerError)
|
||
}
|
||
if len(geminiResponse.Candidates) == 0 {
|
||
return nil, types.NewOpenAIError(errors.New("no candidates returned"), types.ErrorCodeBadResponseBody, http.StatusInternalServerError)
|
||
}
|
||
fullTextResponse := responseGeminiChat2OpenAI(c, &geminiResponse)
|
||
fullTextResponse.Model = info.UpstreamModelName
|
||
usage := dto.Usage{
|
||
PromptTokens: geminiResponse.UsageMetadata.PromptTokenCount,
|
||
CompletionTokens: geminiResponse.UsageMetadata.CandidatesTokenCount,
|
||
TotalTokens: geminiResponse.UsageMetadata.TotalTokenCount,
|
||
}
|
||
|
||
usage.CompletionTokenDetails.ReasoningTokens = geminiResponse.UsageMetadata.ThoughtsTokenCount
|
||
usage.CompletionTokens = usage.TotalTokens - usage.PromptTokens
|
||
|
||
for _, detail := range geminiResponse.UsageMetadata.PromptTokensDetails {
|
||
if detail.Modality == "AUDIO" {
|
||
usage.PromptTokensDetails.AudioTokens = detail.TokenCount
|
||
} else if detail.Modality == "TEXT" {
|
||
usage.PromptTokensDetails.TextTokens = detail.TokenCount
|
||
}
|
||
}
|
||
|
||
fullTextResponse.Usage = usage
|
||
jsonResponse, err := json.Marshal(fullTextResponse)
|
||
if err != nil {
|
||
return nil, types.NewError(err, types.ErrorCodeBadResponseBody)
|
||
}
|
||
c.Writer.Header().Set("Content-Type", "application/json")
|
||
c.Writer.WriteHeader(resp.StatusCode)
|
||
c.Writer.Write(jsonResponse)
|
||
return &usage, nil
|
||
}
|
||
|
||
func GeminiEmbeddingHandler(c *gin.Context, info *relaycommon.RelayInfo, resp *http.Response) (*dto.Usage, *types.NewAPIError) {
|
||
defer common.CloseResponseBodyGracefully(resp)
|
||
|
||
responseBody, readErr := io.ReadAll(resp.Body)
|
||
if readErr != nil {
|
||
return nil, types.NewOpenAIError(readErr, types.ErrorCodeBadResponseBody, http.StatusInternalServerError)
|
||
}
|
||
|
||
var geminiResponse dto.GeminiBatchEmbeddingResponse
|
||
if jsonErr := common.Unmarshal(responseBody, &geminiResponse); jsonErr != nil {
|
||
return nil, types.NewOpenAIError(jsonErr, types.ErrorCodeBadResponseBody, http.StatusInternalServerError)
|
||
}
|
||
|
||
// convert to openai format response
|
||
openAIResponse := dto.OpenAIEmbeddingResponse{
|
||
Object: "list",
|
||
Data: make([]dto.OpenAIEmbeddingResponseItem, 0, len(geminiResponse.Embeddings)),
|
||
Model: info.UpstreamModelName,
|
||
}
|
||
|
||
for i, embedding := range geminiResponse.Embeddings {
|
||
openAIResponse.Data = append(openAIResponse.Data, dto.OpenAIEmbeddingResponseItem{
|
||
Object: "embedding",
|
||
Embedding: embedding.Values,
|
||
Index: i,
|
||
})
|
||
}
|
||
|
||
// calculate usage
|
||
// https://ai.google.dev/gemini-api/docs/pricing?hl=zh-cn#text-embedding-004
|
||
// Google has not yet clarified how embedding models will be billed
|
||
// refer to openai billing method to use input tokens billing
|
||
// https://platform.openai.com/docs/guides/embeddings#what-are-embeddings
|
||
usage := &dto.Usage{
|
||
PromptTokens: info.PromptTokens,
|
||
CompletionTokens: 0,
|
||
TotalTokens: info.PromptTokens,
|
||
}
|
||
openAIResponse.Usage = *usage
|
||
|
||
jsonResponse, jsonErr := common.Marshal(openAIResponse)
|
||
if jsonErr != nil {
|
||
return nil, types.NewOpenAIError(jsonErr, types.ErrorCodeBadResponseBody, http.StatusInternalServerError)
|
||
}
|
||
|
||
common.IOCopyBytesGracefully(c, resp, jsonResponse)
|
||
return usage, nil
|
||
}
|
||
|
||
func GeminiImageHandler(c *gin.Context, info *relaycommon.RelayInfo, resp *http.Response) (*dto.Usage, *types.NewAPIError) {
|
||
responseBody, readErr := io.ReadAll(resp.Body)
|
||
if readErr != nil {
|
||
return nil, types.NewOpenAIError(readErr, types.ErrorCodeBadResponseBody, http.StatusInternalServerError)
|
||
}
|
||
_ = resp.Body.Close()
|
||
|
||
var geminiResponse dto.GeminiImageResponse
|
||
if jsonErr := common.Unmarshal(responseBody, &geminiResponse); jsonErr != nil {
|
||
return nil, types.NewOpenAIError(jsonErr, types.ErrorCodeBadResponseBody, http.StatusInternalServerError)
|
||
}
|
||
|
||
if len(geminiResponse.Predictions) == 0 {
|
||
return nil, types.NewOpenAIError(errors.New("no images generated"), types.ErrorCodeBadResponseBody, http.StatusInternalServerError)
|
||
}
|
||
|
||
// convert to openai format response
|
||
openAIResponse := dto.ImageResponse{
|
||
Created: common.GetTimestamp(),
|
||
Data: make([]dto.ImageData, 0, len(geminiResponse.Predictions)),
|
||
}
|
||
|
||
for _, prediction := range geminiResponse.Predictions {
|
||
if prediction.RaiFilteredReason != "" {
|
||
continue // skip filtered image
|
||
}
|
||
openAIResponse.Data = append(openAIResponse.Data, dto.ImageData{
|
||
B64Json: prediction.BytesBase64Encoded,
|
||
})
|
||
}
|
||
|
||
jsonResponse, jsonErr := json.Marshal(openAIResponse)
|
||
if jsonErr != nil {
|
||
return nil, types.NewError(jsonErr, types.ErrorCodeBadResponseBody)
|
||
}
|
||
|
||
c.Writer.Header().Set("Content-Type", "application/json")
|
||
c.Writer.WriteHeader(resp.StatusCode)
|
||
_, _ = c.Writer.Write(jsonResponse)
|
||
|
||
// https://github.com/google-gemini/cookbook/blob/719a27d752aac33f39de18a8d3cb42a70874917e/quickstarts/Counting_Tokens.ipynb
|
||
// each image has fixed 258 tokens
|
||
const imageTokens = 258
|
||
generatedImages := len(openAIResponse.Data)
|
||
|
||
usage := &dto.Usage{
|
||
PromptTokens: imageTokens * generatedImages, // each generated image has fixed 258 tokens
|
||
CompletionTokens: 0, // image generation does not calculate completion tokens
|
||
TotalTokens: imageTokens * generatedImages,
|
||
}
|
||
|
||
return usage, nil
|
||
}
|