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new-api-oiss/relay/channel/gemini/relay-gemini.go

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package gemini
import (
"encoding/json"
"errors"
"fmt"
"io"
"net/http"
"strconv"
"strings"
"unicode/utf8"
"github.com/QuantumNous/new-api/common"
"github.com/QuantumNous/new-api/constant"
"github.com/QuantumNous/new-api/dto"
"github.com/QuantumNous/new-api/logger"
"github.com/QuantumNous/new-api/relay/channel/openai"
relaycommon "github.com/QuantumNous/new-api/relay/common"
"github.com/QuantumNous/new-api/relay/helper"
"github.com/QuantumNous/new-api/service"
"github.com/QuantumNous/new-api/setting/model_setting"
"github.com/QuantumNous/new-api/setting/reasoning"
"github.com/QuantumNous/new-api/types"
"github.com/gin-gonic/gin"
)
// https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference?hl=zh-cn#blob
var geminiSupportedMimeTypes = map[string]bool{
"application/pdf": true,
"audio/mpeg": true,
"audio/mp3": true,
"audio/wav": true,
"image/png": true,
"image/jpeg": true,
"image/webp": true,
"text/plain": true,
"video/mov": true,
"video/mpeg": true,
"video/mp4": true,
"video/mpg": true,
"video/avi": true,
"video/wmv": true,
"video/mpegps": true,
"video/flv": true,
}
const thoughtSignatureBypassValue = "context_engineering_is_the_way_to_go"
// Gemini 允许的思考预算范围
const (
pro25MinBudget = 128
pro25MaxBudget = 32768
flash25MaxBudget = 24576
flash25LiteMinBudget = 512
flash25LiteMaxBudget = 24576
)
func isNew25ProModel(modelName string) bool {
return strings.HasPrefix(modelName, "gemini-2.5-pro") &&
!strings.HasPrefix(modelName, "gemini-2.5-pro-preview-05-06") &&
!strings.HasPrefix(modelName, "gemini-2.5-pro-preview-03-25")
}
func is25FlashLiteModel(modelName string) bool {
return strings.HasPrefix(modelName, "gemini-2.5-flash-lite")
}
// clampThinkingBudget 根据模型名称将预算限制在允许的范围内
func clampThinkingBudget(modelName string, budget int) int {
isNew25Pro := isNew25ProModel(modelName)
is25FlashLite := is25FlashLiteModel(modelName)
if is25FlashLite {
if budget < flash25LiteMinBudget {
return flash25LiteMinBudget
}
if budget > flash25LiteMaxBudget {
return flash25LiteMaxBudget
}
} else if isNew25Pro {
if budget < pro25MinBudget {
return pro25MinBudget
}
if budget > pro25MaxBudget {
return pro25MaxBudget
}
} else { // 其他模型
if budget < 0 {
return 0
}
if budget > flash25MaxBudget {
return flash25MaxBudget
}
}
return budget
}
// "effort": "high" - Allocates a large portion of tokens for reasoning (approximately 80% of max_tokens)
// "effort": "medium" - Allocates a moderate portion of tokens (approximately 50% of max_tokens)
// "effort": "low" - Allocates a smaller portion of tokens (approximately 20% of max_tokens)
// "effort": "minimal" - Allocates a minimal portion of tokens (approximately 5% of max_tokens)
func clampThinkingBudgetByEffort(modelName string, effort string) int {
isNew25Pro := isNew25ProModel(modelName)
is25FlashLite := is25FlashLiteModel(modelName)
maxBudget := 0
if is25FlashLite {
maxBudget = flash25LiteMaxBudget
}
if isNew25Pro {
maxBudget = pro25MaxBudget
} else {
maxBudget = flash25MaxBudget
}
switch effort {
case "high":
maxBudget = maxBudget * 80 / 100
case "medium":
maxBudget = maxBudget * 50 / 100
case "low":
maxBudget = maxBudget * 20 / 100
case "minimal":
maxBudget = maxBudget * 5 / 100
}
return clampThinkingBudget(modelName, maxBudget)
}
func ThinkingAdaptor(geminiRequest *dto.GeminiChatRequest, info *relaycommon.RelayInfo, oaiRequest ...dto.GeneralOpenAIRequest) {
if model_setting.GetGeminiSettings().ThinkingAdapterEnabled {
modelName := info.UpstreamModelName
isNew25Pro := strings.HasPrefix(modelName, "gemini-2.5-pro") &&
!strings.HasPrefix(modelName, "gemini-2.5-pro-preview-05-06") &&
!strings.HasPrefix(modelName, "gemini-2.5-pro-preview-03-25")
if strings.Contains(modelName, "-thinking-") {
parts := strings.SplitN(modelName, "-thinking-", 2)
if len(parts) == 2 && parts[1] != "" {
if budgetTokens, err := strconv.Atoi(parts[1]); err == nil {
clampedBudget := clampThinkingBudget(modelName, budgetTokens)
geminiRequest.GenerationConfig.ThinkingConfig = &dto.GeminiThinkingConfig{
ThinkingBudget: common.GetPointer(clampedBudget),
IncludeThoughts: true,
}
}
}
} else if strings.HasSuffix(modelName, "-thinking") {
unsupportedModels := []string{
"gemini-2.5-pro-preview-05-06",
"gemini-2.5-pro-preview-03-25",
}
isUnsupported := false
for _, unsupportedModel := range unsupportedModels {
if strings.HasPrefix(modelName, unsupportedModel) {
isUnsupported = true
break
}
}
if isUnsupported {
geminiRequest.GenerationConfig.ThinkingConfig = &dto.GeminiThinkingConfig{
IncludeThoughts: true,
}
} else {
geminiRequest.GenerationConfig.ThinkingConfig = &dto.GeminiThinkingConfig{
IncludeThoughts: true,
}
if geminiRequest.GenerationConfig.MaxOutputTokens > 0 {
budgetTokens := model_setting.GetGeminiSettings().ThinkingAdapterBudgetTokensPercentage * float64(geminiRequest.GenerationConfig.MaxOutputTokens)
clampedBudget := clampThinkingBudget(modelName, int(budgetTokens))
geminiRequest.GenerationConfig.ThinkingConfig.ThinkingBudget = common.GetPointer(clampedBudget)
} else {
if len(oaiRequest) > 0 {
// 如果有reasoningEffort参数则根据其值设置思考预算
geminiRequest.GenerationConfig.ThinkingConfig.ThinkingBudget = common.GetPointer(clampThinkingBudgetByEffort(modelName, oaiRequest[0].ReasoningEffort))
}
}
}
} else if strings.HasSuffix(modelName, "-nothinking") {
if !isNew25Pro {
geminiRequest.GenerationConfig.ThinkingConfig = &dto.GeminiThinkingConfig{
ThinkingBudget: common.GetPointer(0),
}
}
} else if _, level, ok := reasoning.TrimEffortSuffix(info.UpstreamModelName); ok && level != "" {
geminiRequest.GenerationConfig.ThinkingConfig = &dto.GeminiThinkingConfig{
IncludeThoughts: true,
ThinkingLevel: level,
}
info.ReasoningEffort = level
}
}
}
// Setting safety to the lowest possible values since Gemini is already powerless enough
func CovertOpenAI2Gemini(c *gin.Context, textRequest dto.GeneralOpenAIRequest, info *relaycommon.RelayInfo) (*dto.GeminiChatRequest, error) {
geminiRequest := dto.GeminiChatRequest{
Contents: make([]dto.GeminiChatContent, 0, len(textRequest.Messages)),
GenerationConfig: dto.GeminiChatGenerationConfig{
Temperature: textRequest.Temperature,
TopP: textRequest.TopP,
MaxOutputTokens: textRequest.GetMaxTokens(),
Seed: int64(textRequest.Seed),
},
}
attachThoughtSignature := (info.ChannelType == constant.ChannelTypeGemini ||
info.ChannelType == constant.ChannelTypeVertexAi) &&
model_setting.GetGeminiSettings().FunctionCallThoughtSignatureEnabled
if model_setting.IsGeminiModelSupportImagine(info.UpstreamModelName) {
geminiRequest.GenerationConfig.ResponseModalities = []string{
"TEXT",
"IMAGE",
}
}
adaptorWithExtraBody := false
// patch extra_body
if len(textRequest.ExtraBody) > 0 {
if !strings.HasSuffix(info.UpstreamModelName, "-nothinking") {
var extraBody map[string]interface{}
if err := common.Unmarshal(textRequest.ExtraBody, &extraBody); err != nil {
return nil, fmt.Errorf("invalid extra body: %w", err)
}
// eg. {"google":{"thinking_config":{"thinking_budget":5324,"include_thoughts":true}}}
if googleBody, ok := extraBody["google"].(map[string]interface{}); ok {
adaptorWithExtraBody = true
// check error param name like thinkingConfig, should be thinking_config
if _, hasErrorParam := googleBody["thinkingConfig"]; hasErrorParam {
return nil, errors.New("extra_body.google.thinkingConfig is not supported, use extra_body.google.thinking_config instead")
}
if thinkingConfig, ok := googleBody["thinking_config"].(map[string]interface{}); ok {
// check error param name like thinkingBudget, should be thinking_budget
if _, hasErrorParam := thinkingConfig["thinkingBudget"]; hasErrorParam {
return nil, errors.New("extra_body.google.thinking_config.thinkingBudget is not supported, use extra_body.google.thinking_config.thinking_budget instead")
}
if budget, ok := thinkingConfig["thinking_budget"].(float64); ok {
budgetInt := int(budget)
geminiRequest.GenerationConfig.ThinkingConfig = &dto.GeminiThinkingConfig{
ThinkingBudget: common.GetPointer(budgetInt),
IncludeThoughts: true,
}
} else {
geminiRequest.GenerationConfig.ThinkingConfig = &dto.GeminiThinkingConfig{
IncludeThoughts: true,
}
}
}
// check error param name like imageConfig, should be image_config
if _, hasErrorParam := googleBody["imageConfig"]; hasErrorParam {
return nil, errors.New("extra_body.google.imageConfig is not supported, use extra_body.google.image_config instead")
}
if imageConfig, ok := googleBody["image_config"].(map[string]interface{}); ok {
// check error param name like aspectRatio, should be aspect_ratio
if _, hasErrorParam := imageConfig["aspectRatio"]; hasErrorParam {
return nil, errors.New("extra_body.google.image_config.aspectRatio is not supported, use extra_body.google.image_config.aspect_ratio instead")
}
// check error param name like imageSize, should be image_size
if _, hasErrorParam := imageConfig["imageSize"]; hasErrorParam {
return nil, errors.New("extra_body.google.image_config.imageSize is not supported, use extra_body.google.image_config.image_size instead")
}
// convert snake_case to camelCase for Gemini API
geminiImageConfig := make(map[string]interface{})
if aspectRatio, ok := imageConfig["aspect_ratio"]; ok {
geminiImageConfig["aspectRatio"] = aspectRatio
}
if imageSize, ok := imageConfig["image_size"]; ok {
geminiImageConfig["imageSize"] = imageSize
}
if len(geminiImageConfig) > 0 {
imageConfigBytes, err := common.Marshal(geminiImageConfig)
if err != nil {
return nil, fmt.Errorf("failed to marshal image_config: %w", err)
}
geminiRequest.GenerationConfig.ImageConfig = imageConfigBytes
}
}
}
}
}
if !adaptorWithExtraBody {
ThinkingAdaptor(&geminiRequest, info, textRequest)
}
safetySettings := make([]dto.GeminiChatSafetySettings, 0, len(SafetySettingList))
for _, category := range SafetySettingList {
safetySettings = append(safetySettings, dto.GeminiChatSafetySettings{
Category: category,
Threshold: model_setting.GetGeminiSafetySetting(category),
})
}
geminiRequest.SafetySettings = safetySettings
// openaiContent.FuncToToolCalls()
if textRequest.Tools != nil {
functions := make([]dto.FunctionRequest, 0, len(textRequest.Tools))
googleSearch := false
codeExecution := false
urlContext := false
for _, tool := range textRequest.Tools {
if tool.Function.Name == "googleSearch" {
googleSearch = true
continue
}
if tool.Function.Name == "codeExecution" {
codeExecution = true
continue
}
if tool.Function.Name == "urlContext" {
urlContext = true
continue
}
if tool.Function.Parameters != nil {
params, ok := tool.Function.Parameters.(map[string]interface{})
if ok {
if props, hasProps := params["properties"].(map[string]interface{}); hasProps {
if len(props) == 0 {
tool.Function.Parameters = nil
}
}
}
}
// Clean the parameters before appending
cleanedParams := cleanFunctionParameters(tool.Function.Parameters)
tool.Function.Parameters = cleanedParams
functions = append(functions, tool.Function)
}
geminiTools := geminiRequest.GetTools()
if codeExecution {
geminiTools = append(geminiTools, dto.GeminiChatTool{
CodeExecution: make(map[string]string),
})
}
if googleSearch {
geminiTools = append(geminiTools, dto.GeminiChatTool{
GoogleSearch: make(map[string]string),
})
}
if urlContext {
geminiTools = append(geminiTools, dto.GeminiChatTool{
URLContext: make(map[string]string),
})
}
if len(functions) > 0 {
geminiTools = append(geminiTools, dto.GeminiChatTool{
FunctionDeclarations: functions,
})
}
geminiRequest.SetTools(geminiTools)
}
if textRequest.ResponseFormat != nil && (textRequest.ResponseFormat.Type == "json_schema" || textRequest.ResponseFormat.Type == "json_object") {
geminiRequest.GenerationConfig.ResponseMimeType = "application/json"
if len(textRequest.ResponseFormat.JsonSchema) > 0 {
// 先将json.RawMessage解析
var jsonSchema dto.FormatJsonSchema
if err := common.Unmarshal(textRequest.ResponseFormat.JsonSchema, &jsonSchema); err == nil {
cleanedSchema := removeAdditionalPropertiesWithDepth(jsonSchema.Schema, 0)
geminiRequest.GenerationConfig.ResponseSchema = cleanedSchema
}
}
}
tool_call_ids := make(map[string]string)
var system_content []string
//shouldAddDummyModelMessage := false
for _, message := range textRequest.Messages {
if message.Role == "system" || message.Role == "developer" {
system_content = append(system_content, message.StringContent())
continue
} else if message.Role == "tool" || message.Role == "function" {
if len(geminiRequest.Contents) == 0 || geminiRequest.Contents[len(geminiRequest.Contents)-1].Role == "model" {
geminiRequest.Contents = append(geminiRequest.Contents, dto.GeminiChatContent{
Role: "user",
})
}
var parts = &geminiRequest.Contents[len(geminiRequest.Contents)-1].Parts
name := ""
if message.Name != nil {
name = *message.Name
} else if val, exists := tool_call_ids[message.ToolCallId]; exists {
name = val
}
var contentMap map[string]interface{}
contentStr := message.StringContent()
// 1. 尝试解析为 JSON 对象
if err := json.Unmarshal([]byte(contentStr), &contentMap); err != nil {
// 2. 如果失败,尝试解析为 JSON 数组
var contentSlice []interface{}
if err := json.Unmarshal([]byte(contentStr), &contentSlice); err == nil {
// 如果是数组,包装成对象
contentMap = map[string]interface{}{"result": contentSlice}
} else {
// 3. 如果再次失败,作为纯文本处理
contentMap = map[string]interface{}{"content": contentStr}
}
}
functionResp := &dto.GeminiFunctionResponse{
Name: name,
Response: contentMap,
}
*parts = append(*parts, dto.GeminiPart{
FunctionResponse: functionResp,
})
continue
}
var parts []dto.GeminiPart
content := dto.GeminiChatContent{
Role: message.Role,
}
shouldAttachThoughtSignature := attachThoughtSignature && (message.Role == "assistant" || message.Role == "model")
signatureAttached := false
// isToolCall := false
if message.ToolCalls != nil {
// message.Role = "model"
// isToolCall = true
for _, call := range message.ParseToolCalls() {
args := map[string]interface{}{}
if call.Function.Arguments != "" {
if json.Unmarshal([]byte(call.Function.Arguments), &args) != nil {
return nil, fmt.Errorf("invalid arguments for function %s, args: %s", call.Function.Name, call.Function.Arguments)
}
}
toolCall := dto.GeminiPart{
FunctionCall: &dto.FunctionCall{
FunctionName: call.Function.Name,
Arguments: args,
},
}
if shouldAttachThoughtSignature && !signatureAttached && hasFunctionCallContent(toolCall.FunctionCall) && len(toolCall.ThoughtSignature) == 0 {
toolCall.ThoughtSignature = json.RawMessage(strconv.Quote(thoughtSignatureBypassValue))
signatureAttached = true
}
parts = append(parts, toolCall)
tool_call_ids[call.ID] = call.Function.Name
}
}
openaiContent := message.ParseContent()
imageNum := 0
for _, part := range openaiContent {
if part.Type == dto.ContentTypeText {
if part.Text == "" {
continue
}
// check markdown image ![image](data:image/jpeg;base64,xxxxxxxxxxxx)
// 使用字符串查找而非正则,避免大文本性能问题
text := part.Text
hasMarkdownImage := false
for {
// 快速检查是否包含 markdown 图片标记
startIdx := strings.Index(text, "![")
if startIdx == -1 {
break
}
// 找到 ](
bracketIdx := strings.Index(text[startIdx:], "](data:")
if bracketIdx == -1 {
break
}
bracketIdx += startIdx
// 找到闭合的 )
closeIdx := strings.Index(text[bracketIdx+2:], ")")
if closeIdx == -1 {
break
}
closeIdx += bracketIdx + 2
hasMarkdownImage = true
// 添加图片前的文本
if startIdx > 0 {
textBefore := text[:startIdx]
if textBefore != "" {
parts = append(parts, dto.GeminiPart{
Text: textBefore,
})
}
}
// 提取 data URL (从 "](" 后面开始,到 ")" 之前)
dataUrl := text[bracketIdx+2 : closeIdx]
imageNum += 1
if constant.GeminiVisionMaxImageNum != -1 && imageNum > constant.GeminiVisionMaxImageNum {
return nil, fmt.Errorf("too many images in the message, max allowed is %d", constant.GeminiVisionMaxImageNum)
}
format, base64String, err := service.DecodeBase64FileData(dataUrl)
if err != nil {
return nil, fmt.Errorf("decode markdown base64 image data failed: %s", err.Error())
}
imgPart := dto.GeminiPart{
InlineData: &dto.GeminiInlineData{
MimeType: format,
Data: base64String,
},
}
if shouldAttachThoughtSignature {
imgPart.ThoughtSignature = json.RawMessage(strconv.Quote(thoughtSignatureBypassValue))
}
parts = append(parts, imgPart)
// 继续处理剩余文本
text = text[closeIdx+1:]
}
// 添加剩余文本或原始文本(如果没有找到 markdown 图片)
if !hasMarkdownImage {
parts = append(parts, dto.GeminiPart{
Text: part.Text,
})
}
} else if part.Type == dto.ContentTypeImageURL {
imageNum += 1
if constant.GeminiVisionMaxImageNum != -1 && imageNum > constant.GeminiVisionMaxImageNum {
return nil, fmt.Errorf("too many images in the message, max allowed is %d", constant.GeminiVisionMaxImageNum)
}
// 判断是否是url
if strings.HasPrefix(part.GetImageMedia().Url, "http") {
// 是url获取文件的类型和base64编码的数据
fileData, err := service.GetFileBase64FromUrl(c, part.GetImageMedia().Url, "formatting image for Gemini")
if err != nil {
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
if _, ok := geminiSupportedMimeTypes[strings.ToLower(fileData.MimeType)]; !ok {
url := part.GetImageMedia().Url
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{
MimeType: fileData.MimeType, // 使用原始的 MimeType因为大小写可能对API有意义
Data: fileData.Base64Data,
},
})
} 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,
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,
},
})
}
}
// 如果需要附加签名但还没有附加(没有 tool_calls 或 tool_calls 为空),
// 则在第一个文本 part 上附加 thoughtSignature
if shouldAttachThoughtSignature && !signatureAttached && len(parts) > 0 {
for i := range parts {
if parts[i].Text != "" {
parts[i].ThoughtSignature = json.RawMessage(strconv.Quote(thoughtSignatureBypassValue))
break
}
}
}
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
}
func hasFunctionCallContent(call *dto.FunctionCall) bool {
if call == nil {
return false
}
if strings.TrimSpace(call.FunctionName) != "" {
return true
}
switch v := call.Arguments.(type) {
case nil:
return false
case string:
return strings.TrimSpace(v) != ""
case map[string]interface{}:
return len(v) > 0
case []interface{}:
return len(v) > 0
default:
return true
}
}
// 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.InlineData != nil {
// 媒体内容
if strings.HasPrefix(part.InlineData.MimeType, "image") {
imgText := "![image](data:" + part.InlineData.MimeType + ";base64," + part.InlineData.Data + ")"
texts = append(texts, imgText)
} else {
// 其他媒体类型,直接显示链接
texts = append(texts, fmt.Sprintf("[media](data:%s;base64,%s)", part.InlineData.MimeType, part.InlineData.Data))
}
} else 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 geminiStreamHandler(c *gin.Context, info *relaycommon.RelayInfo, resp *http.Response, callback func(data string, geminiResponse *dto.GeminiChatResponse) bool) (*dto.Usage, *types.NewAPIError) {
var usage = &dto.Usage{}
var imageCount int
responseText := strings.Builder{}
helper.StreamScannerHandler(c, resp, info, func(data string) bool {
var geminiResponse dto.GeminiChatResponse
err := common.UnmarshalJsonStr(data, &geminiResponse)
if err != nil {
logger.LogError(c, "error unmarshalling stream response: "+err.Error())
return false
}
// 统计图片数量
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)
}
}
}
// 更新使用量统计
if geminiResponse.UsageMetadata.TotalTokenCount != 0 {
usage.PromptTokens = geminiResponse.UsageMetadata.PromptTokenCount
usage.CompletionTokens = geminiResponse.UsageMetadata.CandidatesTokenCount + geminiResponse.UsageMetadata.ThoughtsTokenCount
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
}
}
}
return callback(data, &geminiResponse)
})
if imageCount != 0 {
if usage.CompletionTokens == 0 {
usage.CompletionTokens = imageCount * 1400
}
}
usage.PromptTokensDetails.TextTokens = usage.PromptTokens
if usage.TotalTokens > 0 {
usage.CompletionTokens = usage.TotalTokens - usage.PromptTokens
}
if usage.CompletionTokens <= 0 {
str := responseText.String()
if len(str) > 0 {
usage = service.ResponseText2Usage(c, responseText.String(), info.UpstreamModelName, info.GetEstimatePromptTokens())
} else {
usage = &dto.Usage{}
}
}
return usage, nil
}
func GeminiChatStreamHandler(c *gin.Context, info *relaycommon.RelayInfo, resp *http.Response) (*dto.Usage, *types.NewAPIError) {
id := helper.GetResponseID(c)
createAt := common.GetTimestamp()
finishReason := constant.FinishReasonStop
usage, err := geminiStreamHandler(c, info, resp, func(data string, geminiResponse *dto.GeminiChatResponse) bool {
response, isStop := streamResponseGeminiChat2OpenAI(geminiResponse)
response.Id = id
response.Created = createAt
response.Model = info.UpstreamModelName
logger.LogDebug(c, fmt.Sprintf("info.SendResponseCount = %d", info.SendResponseCount))
if info.SendResponseCount == 0 {
// send first response
emptyResponse := helper.GenerateStartEmptyResponse(id, createAt, info.UpstreamModelName, nil)
if response.IsToolCall() {
if len(emptyResponse.Choices) > 0 && len(response.Choices) > 0 {
toolCalls := response.Choices[0].Delta.ToolCalls
copiedToolCalls := make([]dto.ToolCallResponse, len(toolCalls))
for idx := range toolCalls {
copiedToolCalls[idx] = toolCalls[idx]
copiedToolCalls[idx].Function.Arguments = ""
}
emptyResponse.Choices[0].Delta.ToolCalls = copiedToolCalls
}
finishReason = constant.FinishReasonToolCalls
err := handleStream(c, info, emptyResponse)
if err != nil {
logger.LogError(c, err.Error())
}
response.ClearToolCalls()
if response.IsFinished() {
response.Choices[0].FinishReason = nil
}
} else {
err := handleStream(c, info, emptyResponse)
if err != nil {
logger.LogError(c, err.Error())
}
}
}
err := handleStream(c, info, response)
if err != nil {
logger.LogError(c, err.Error())
}
if isStop {
_ = handleStream(c, info, helper.GenerateStopResponse(id, createAt, info.UpstreamModelName, finishReason))
}
return true
})
if err != nil {
return usage, err
}
response := helper.GenerateFinalUsageResponse(id, createAt, info.UpstreamModelName, *usage)
handleErr := handleFinalStream(c, info, response)
if handleErr != nil {
common.SysLog("send final response failed: " + handleErr.Error())
}
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)
}
service.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)
//if geminiResponse.PromptFeedback != nil && geminiResponse.PromptFeedback.BlockReason != nil {
// return nil, types.NewOpenAIError(errors.New("request blocked by Gemini API: "+*geminiResponse.PromptFeedback.BlockReason), types.ErrorCodePromptBlocked, http.StatusBadRequest)
//} else {
// return nil, types.NewOpenAIError(errors.New("empty response from Gemini API"), types.ErrorCodeEmptyResponse, 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
switch info.RelayFormat {
case types.RelayFormatOpenAI:
responseBody, err = common.Marshal(fullTextResponse)
if err != nil {
return nil, types.NewError(err, types.ErrorCodeBadResponseBody)
}
case types.RelayFormatClaude:
claudeResp := service.ResponseOpenAI2Claude(fullTextResponse, info)
claudeRespStr, err := common.Marshal(claudeResp)
if err != nil {
return nil, types.NewError(err, types.ErrorCodeBadResponseBody)
}
responseBody = claudeRespStr
case types.RelayFormatGemini:
break
}
service.IOCopyBytesGracefully(c, resp, responseBody)
return &usage, nil
}
func GeminiEmbeddingHandler(c *gin.Context, info *relaycommon.RelayInfo, resp *http.Response) (*dto.Usage, *types.NewAPIError) {
defer service.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 := service.ResponseText2Usage(c, "", info.UpstreamModelName, info.GetEstimatePromptTokens())
openAIResponse.Usage = *usage
jsonResponse, jsonErr := common.Marshal(openAIResponse)
if jsonErr != nil {
return nil, types.NewOpenAIError(jsonErr, types.ErrorCodeBadResponseBody, http.StatusInternalServerError)
}
service.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
}