feat: support third part models of baidu (#1046)

百度千帆平台上的第三方大模型调用

README.md

@@ -67,6 +67,7 @@ _✨ 通过标准的 OpenAI API 格式访问所有的大模型，开箱即用
    + [x] [OpenAI ChatGPT 系列模型](https://platform.openai.com/docs/guides/gpt/chat-completions-api)（支持 [Azure OpenAI API](https://learn.microsoft.com/en-us/azure/ai-services/openai/reference)）
    + [x] [Anthropic Claude 系列模型](https://anthropic.com)
    + [x] [Google PaLM2/Gemini 系列模型](https://developers.generativeai.google)
+   + [x] [Mistral 系列模型](https://mistral.ai/)
    + [x] [百度文心一言系列模型](https://cloud.baidu.com/doc/WENXINWORKSHOP/index.html)
    + [x] [阿里通义千问系列模型](https://help.aliyun.com/document_detail/2400395.html)
    + [x] [讯飞星火认知大模型](https://www.xfyun.cn/doc/spark/Web.html)

common/constants.go

@@ -66,6 +66,7 @@ const (
 	ChannelTypeMoonshot       = 25
 	ChannelTypeBaichuan       = 26
 	ChannelTypeMinimax        = 27
+	ChannelTypeMistral        = 28
 )
 
 var ChannelBaseURLs = []string{
@@ -97,6 +98,7 @@ var ChannelBaseURLs = []string{
 	"https://api.moonshot.cn",                   // 25
 	"https://api.baichuan-ai.com",               // 26
 	"https://api.minimax.chat",                  // 27
+	"https://api.mistral.ai",                    // 28
 }
 
 const (

common/model-ratio.go

@@ -7,29 +7,6 @@ import (
 	"time"
 )
 
-var DalleSizeRatios = map[string]map[string]float64{
-	"dall-e-2": {
-		"256x256":   1,
-		"512x512":   1.125,
-		"1024x1024": 1.25,
-	},
-	"dall-e-3": {
-		"1024x1024": 1,
-		"1024x1792": 2,
-		"1792x1024": 2,
-	},
-}
-
-var DalleGenerationImageAmounts = map[string][2]int{
-	"dall-e-2": {1, 10},
-	"dall-e-3": {1, 1}, // OpenAI allows n=1 currently.
-}
-
-var DalleImagePromptLengthLimitations = map[string]int{
-	"dall-e-2": 1000,
-	"dall-e-3": 4000,
-}
-
 const (
 	USD2RMB = 7
 	USD     = 500 // $0.002 = 1 -> $1 = 500
@@ -40,7 +17,6 @@ const (
 // https://platform.openai.com/docs/models/model-endpoint-compatibility
 // https://cloud.baidu.com/doc/WENXINWORKSHOP/s/Blfmc9dlf
 // https://openai.com/pricing
-// TODO: when a new api is enabled, check the pricing here
 // 1 === $0.002 / 1K tokens
 // 1 === ￥0.014 / 1k tokens
 var ModelRatio = map[string]float64{
@@ -139,15 +115,29 @@ var ModelRatio = map[string]float64{
 	"abab6-chat":    0.1 * RMB,
 	"abab5.5-chat":  0.015 * RMB,
 	"abab5.5s-chat": 0.005 * RMB,
+	// https://docs.mistral.ai/platform/pricing/
+	"open-mistral-7b":       0.25 / 1000 * USD,
+	"open-mixtral-8x7b":     0.7 / 1000 * USD,
+	"mistral-small-latest":  2.0 / 1000 * USD,
+	"mistral-medium-latest": 2.7 / 1000 * USD,
+	"mistral-large-latest":  8.0 / 1000 * USD,
+	"mistral-embed":         0.1 / 1000 * USD,
 }
 
+var CompletionRatio = map[string]float64{}
+
 var DefaultModelRatio map[string]float64
+var DefaultCompletionRatio map[string]float64
 
 func init() {
 	DefaultModelRatio = make(map[string]float64)
 	for k, v := range ModelRatio {
 		DefaultModelRatio[k] = v
 	}
+	DefaultCompletionRatio = make(map[string]float64)
+	for k, v := range CompletionRatio {
+		DefaultCompletionRatio[k] = v
+	}
 }
 
 func ModelRatio2JSONString() string {
@@ -178,8 +168,6 @@ func GetModelRatio(name string) float64 {
 	return ratio
 }
 
-var CompletionRatio = map[string]float64{}
-
 func CompletionRatio2JSONString() string {
 	jsonBytes, err := json.Marshal(CompletionRatio)
 	if err != nil {
@@ -197,6 +185,9 @@ func GetCompletionRatio(name string) float64 {
 	if ratio, ok := CompletionRatio[name]; ok {
 		return ratio
 	}
+	if ratio, ok := DefaultCompletionRatio[name]; ok {
+		return ratio
+	}
 	if strings.HasPrefix(name, "gpt-3.5") {
 		if strings.HasSuffix(name, "0125") {
 			// https://openai.com/blog/new-embedding-models-and-api-updates
@@ -229,5 +220,8 @@ func GetCompletionRatio(name string) float64 {
 	if strings.HasPrefix(name, "claude-2") {
 		return 2.965517
 	}
+	if strings.HasPrefix(name, "mistral-") {
+		return 3
+	}
 	return 1
 }

common/random.go

@@ -0,0 +1,8 @@
+package common
+
+import "math/rand"
+
+// RandRange returns a random number between min and max (max is not included)
+func RandRange(min, max int) int {
+	return min + rand.Intn(max-min)
+}

controller/channel-test.go

@@ -8,6 +8,7 @@ import (
 	"github.com/songquanpeng/one-api/common"
 	"github.com/songquanpeng/one-api/common/config"
 	"github.com/songquanpeng/one-api/common/logger"
+	"github.com/songquanpeng/one-api/middleware"
 	"github.com/songquanpeng/one-api/model"
 	"github.com/songquanpeng/one-api/relay/constant"
 	"github.com/songquanpeng/one-api/relay/helper"
@@ -18,6 +19,7 @@ import (
 	"net/http/httptest"
 	"net/url"
 	"strconv"
+	"strings"
 	"sync"
 	"time"
 
@@ -51,6 +53,7 @@ func testChannel(channel *model.Channel) (err error, openaiErr *relaymodel.Error
 	c.Request.Header.Set("Content-Type", "application/json")
 	c.Set("channel", channel.Type)
 	c.Set("base_url", channel.GetBaseURL())
+	middleware.SetupContextForSelectedChannel(c, channel, "")
 	meta := util.GetRelayMeta(c)
 	apiType := constant.ChannelType2APIType(channel.Type)
 	adaptor := helper.GetAdaptor(apiType)
@@ -59,6 +62,12 @@ func testChannel(channel *model.Channel) (err error, openaiErr *relaymodel.Error
 	}
 	adaptor.Init(meta)
 	modelName := adaptor.GetModelList()[0]
+	if !strings.Contains(channel.Models, modelName) {
+		modelNames := strings.Split(channel.Models, ",")
+		if len(modelNames) > 0 {
+			modelName = modelNames[0]
+		}
+	}
 	request := buildTestRequest()
 	request.Model = modelName
 	meta.OriginModelName, meta.ActualModelName = modelName, modelName

controller/model.go

@@ -6,6 +6,7 @@ import (
 	"github.com/songquanpeng/one-api/relay/channel/ai360"
 	"github.com/songquanpeng/one-api/relay/channel/baichuan"
 	"github.com/songquanpeng/one-api/relay/channel/minimax"
+	"github.com/songquanpeng/one-api/relay/channel/mistral"
 	"github.com/songquanpeng/one-api/relay/channel/moonshot"
 	"github.com/songquanpeng/one-api/relay/constant"
 	"github.com/songquanpeng/one-api/relay/helper"
@@ -122,6 +123,17 @@ func init() {
 			Parent:     nil,
 		})
 	}
+	for _, modelName := range mistral.ModelList {
+		openAIModels = append(openAIModels, OpenAIModels{
+			Id:         modelName,
+			Object:     "model",
+			Created:    1626777600,
+			OwnedBy:    "mistralai",
+			Permission: permission,
+			Root:       modelName,
+			Parent:     nil,
+		})
+	}
 	openAIModelsMap = make(map[string]OpenAIModels)
 	for _, model := range openAIModels {
 		openAIModelsMap[model.Id] = model

controller/relay.go

@@ -62,7 +62,7 @@ func Relay(c *gin.Context) {
 		retryTimes = 0
 	}
 	for i := retryTimes; i > 0; i-- {
-		channel, err := dbmodel.CacheGetRandomSatisfiedChannel(group, originalModel)
+		channel, err := dbmodel.CacheGetRandomSatisfiedChannel(group, originalModel, i != retryTimes)
 		if err != nil {
 			logger.Errorf(ctx, "CacheGetRandomSatisfiedChannel failed: %w", err)
 			break

middleware/distributor.go

@@ -68,7 +68,7 @@ func Distribute() func(c *gin.Context) {
 				}
 			}
 			requestModel = modelRequest.Model
-			channel, err = model.CacheGetRandomSatisfiedChannel(userGroup, modelRequest.Model)
+			channel, err = model.CacheGetRandomSatisfiedChannel(userGroup, modelRequest.Model, false)
 			if err != nil {
 				message := fmt.Sprintf("当前分组 %s 下对于模型 %s 无可用渠道", userGroup, modelRequest.Model)
 				if channel != nil {

model/cache.go

@@ -191,7 +191,7 @@ func SyncChannelCache(frequency int) {
 	}
 }
 
-func CacheGetRandomSatisfiedChannel(group string, model string) (*Channel, error) {
+func CacheGetRandomSatisfiedChannel(group string, model string, ignoreFirstPriority bool) (*Channel, error) {
 	if !config.MemoryCacheEnabled {
 		return GetRandomSatisfiedChannel(group, model)
 	}
@@ -213,5 +213,10 @@ func CacheGetRandomSatisfiedChannel(group string, model string) (*Channel, error
 		}
 	}
 	idx := rand.Intn(endIdx)
+	if ignoreFirstPriority {
+		if endIdx < len(channels) { // which means there are more than one priority
+			idx = common.RandRange(endIdx, len(channels))
+		}
+	}
 	return channels[idx], nil
 }

relay/channel/ali/main.go

@@ -33,6 +33,9 @@ func ConvertRequest(request model.GeneralOpenAIRequest) *ChatRequest {
 		enableSearch = true
 		aliModel = strings.TrimSuffix(aliModel, EnableSearchModelSuffix)
 	}
+	if request.TopP >= 1 {
+		request.TopP = 0.9999
+	}
 	return &ChatRequest{
 		Model: aliModel,
 		Input: Input{
@@ -42,6 +45,9 @@ func ConvertRequest(request model.GeneralOpenAIRequest) *ChatRequest {
 			EnableSearch:      enableSearch,
 			IncrementalOutput: request.Stream,
 			Seed:              uint64(request.Seed),
+			MaxTokens:         request.MaxTokens,
+			Temperature:       request.Temperature,
+			TopP:              request.TopP,
 		},
 	}
 }

relay/channel/ali/model.go

@@ -16,6 +16,8 @@ type Parameters struct {
 	Seed              uint64  `json:"seed,omitempty"`
 	EnableSearch      bool    `json:"enable_search,omitempty"`
 	IncrementalOutput bool    `json:"incremental_output,omitempty"`
+	MaxTokens         int     `json:"max_tokens,omitempty"`
+	Temperature       float64 `json:"temperature,omitempty"`
 }
 
 type ChatRequest struct {

relay/channel/baidu/adaptor.go

@@ -36,6 +36,8 @@ func (a *Adaptor) GetRequestURL(meta *util.RelayMeta) (string, error) {
 		fullRequestURL = "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/bloomz_7b1"
 	case "Embedding-V1":
 		fullRequestURL = "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/embeddings/embedding-v1"
+	default:
+               fullRequestURL = "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/" + meta.ActualModelName
 	}
 	var accessToken string
 	var err error

relay/channel/gemini/constants.go

@@ -1,6 +1,6 @@
 package gemini
 
 var ModelList = []string{
-	"gemini-pro",
-	"gemini-pro-vision",
+	"gemini-pro", "gemini-1.0-pro-001",
+	"gemini-pro-vision", "gemini-1.0-pro-vision-001",
 }

relay/channel/mistral/constants.go

@@ -0,0 +1,10 @@
+package mistral
+
+var ModelList = []string{
+	"open-mistral-7b",
+	"open-mixtral-8x7b",
+	"mistral-small-latest",
+	"mistral-medium-latest",
+	"mistral-large-latest",
+	"mistral-embed",
+}

relay/channel/openai/adaptor.go

@@ -9,6 +9,7 @@ import (
 	"github.com/songquanpeng/one-api/relay/channel/ai360"
 	"github.com/songquanpeng/one-api/relay/channel/baichuan"
 	"github.com/songquanpeng/one-api/relay/channel/minimax"
+	"github.com/songquanpeng/one-api/relay/channel/mistral"
 	"github.com/songquanpeng/one-api/relay/channel/moonshot"
 	"github.com/songquanpeng/one-api/relay/model"
 	"github.com/songquanpeng/one-api/relay/util"
@@ -94,6 +95,8 @@ func (a *Adaptor) GetModelList() []string {
 		return baichuan.ModelList
 	case common.ChannelTypeMinimax:
 		return minimax.ModelList
+	case common.ChannelTypeMistral:
+		return mistral.ModelList
 	default:
 		return ModelList
 	}
@@ -111,6 +114,8 @@ func (a *Adaptor) GetChannelName() string {
 		return "baichuan"
 	case common.ChannelTypeMinimax:
 		return "minimax"
+	case common.ChannelTypeMistral:
+		return "mistralai"
 	default:
 		return "openai"
 	}

relay/constant/image.go

@@ -0,0 +1,24 @@
+package constant
+
+var DalleSizeRatios = map[string]map[string]float64{
+	"dall-e-2": {
+		"256x256":   1,
+		"512x512":   1.125,
+		"1024x1024": 1.25,
+	},
+	"dall-e-3": {
+		"1024x1024": 1,
+		"1024x1792": 2,
+		"1792x1024": 2,
+	},
+}
+
+var DalleGenerationImageAmounts = map[string][2]int{
+	"dall-e-2": {1, 10},
+	"dall-e-3": {1, 1}, // OpenAI allows n=1 currently.
+}
+
+var DalleImagePromptLengthLimitations = map[string]int{
+	"dall-e-2": 1000,
+	"dall-e-3": 4000,
+}

relay/controller/helper.go

@@ -36,6 +36,65 @@ func getAndValidateTextRequest(c *gin.Context, relayMode int) (*relaymodel.Gener
 	return textRequest, nil
 }
 
+func getImageRequest(c *gin.Context, relayMode int) (*openai.ImageRequest, error) {
+	imageRequest := &openai.ImageRequest{}
+	err := common.UnmarshalBodyReusable(c, imageRequest)
+	if err != nil {
+		return nil, err
+	}
+	if imageRequest.N == 0 {
+		imageRequest.N = 1
+	}
+	if imageRequest.Size == "" {
+		imageRequest.Size = "1024x1024"
+	}
+	if imageRequest.Model == "" {
+		imageRequest.Model = "dall-e-2"
+	}
+	return imageRequest, nil
+}
+
+func validateImageRequest(imageRequest *openai.ImageRequest, meta *util.RelayMeta) *relaymodel.ErrorWithStatusCode {
+	// model validation
+	_, hasValidSize := constant.DalleSizeRatios[imageRequest.Model][imageRequest.Size]
+	if !hasValidSize {
+		return openai.ErrorWrapper(errors.New("size not supported for this image model"), "size_not_supported", http.StatusBadRequest)
+	}
+	// check prompt length
+	if imageRequest.Prompt == "" {
+		return openai.ErrorWrapper(errors.New("prompt is required"), "prompt_missing", http.StatusBadRequest)
+	}
+	if len(imageRequest.Prompt) > constant.DalleImagePromptLengthLimitations[imageRequest.Model] {
+		return openai.ErrorWrapper(errors.New("prompt is too long"), "prompt_too_long", http.StatusBadRequest)
+	}
+	// Number of generated images validation
+	if !isWithinRange(imageRequest.Model, imageRequest.N) {
+		// channel not azure
+		if meta.ChannelType != common.ChannelTypeAzure {
+			return openai.ErrorWrapper(errors.New("invalid value of n"), "n_not_within_range", http.StatusBadRequest)
+		}
+	}
+	return nil
+}
+
+func getImageCostRatio(imageRequest *openai.ImageRequest) (float64, error) {
+	if imageRequest == nil {
+		return 0, errors.New("imageRequest is nil")
+	}
+	imageCostRatio, hasValidSize := constant.DalleSizeRatios[imageRequest.Model][imageRequest.Size]
+	if !hasValidSize {
+		return 0, fmt.Errorf("size not supported for this image model: %s", imageRequest.Size)
+	}
+	if imageRequest.Quality == "hd" && imageRequest.Model == "dall-e-3" {
+		if imageRequest.Size == "1024x1024" {
+			imageCostRatio *= 2
+		} else {
+			imageCostRatio *= 1.5
+		}
+	}
+	return imageCostRatio, nil
+}
+
 func getPromptTokens(textRequest *relaymodel.GeneralOpenAIRequest, relayMode int) int {
 	switch relayMode {
 	case constant.RelayModeChatCompletions:
@@ -113,10 +172,8 @@ func postConsumeQuota(ctx context.Context, usage *relaymodel.Usage, meta *util.R
 	if err != nil {
 		logger.Error(ctx, "error update user quota cache: "+err.Error())
 	}
-	if quota != 0 {
-		logContent := fmt.Sprintf("模型倍率 %.2f，分组倍率 %.2f，补全倍率 %.2f", modelRatio, groupRatio, completionRatio)
-		model.RecordConsumeLog(ctx, meta.UserId, meta.ChannelId, promptTokens, completionTokens, textRequest.Model, meta.TokenName, quota, logContent)
-		model.UpdateUserUsedQuotaAndRequestCount(meta.UserId, quota)
-		model.UpdateChannelUsedQuota(meta.ChannelId, quota)
-	}
+	logContent := fmt.Sprintf("模型倍率 %.2f，分组倍率 %.2f，补全倍率 %.2f", modelRatio, groupRatio, completionRatio)
+	model.RecordConsumeLog(ctx, meta.UserId, meta.ChannelId, promptTokens, completionTokens, textRequest.Model, meta.TokenName, quota, logContent)
+	model.UpdateUserUsedQuotaAndRequestCount(meta.UserId, quota)
+	model.UpdateChannelUsedQuota(meta.ChannelId, quota)
 }

relay/controller/image.go

@@ -10,6 +10,7 @@ import (
 	"github.com/songquanpeng/one-api/common/logger"
 	"github.com/songquanpeng/one-api/model"
 	"github.com/songquanpeng/one-api/relay/channel/openai"
+	"github.com/songquanpeng/one-api/relay/constant"
 	relaymodel "github.com/songquanpeng/one-api/relay/model"
 	"github.com/songquanpeng/one-api/relay/util"
 	"io"
@@ -20,120 +21,65 @@ import (
 )
 
 func isWithinRange(element string, value int) bool {
-	if _, ok := common.DalleGenerationImageAmounts[element]; !ok {
+	if _, ok := constant.DalleGenerationImageAmounts[element]; !ok {
 		return false
 	}
-	min := common.DalleGenerationImageAmounts[element][0]
-	max := common.DalleGenerationImageAmounts[element][1]
+	min := constant.DalleGenerationImageAmounts[element][0]
+	max := constant.DalleGenerationImageAmounts[element][1]
 
 	return value >= min && value <= max
 }
 
 func RelayImageHelper(c *gin.Context, relayMode int) *relaymodel.ErrorWithStatusCode {
-	imageModel := "dall-e-2"
-	imageSize := "1024x1024"
-
-	tokenId := c.GetInt("token_id")
-	channelType := c.GetInt("channel")
-	channelId := c.GetInt("channel_id")
-	userId := c.GetInt("id")
-	group := c.GetString("group")
-
-	var imageRequest openai.ImageRequest
-	err := common.UnmarshalBodyReusable(c, &imageRequest)
+	ctx := c.Request.Context()
+	meta := util.GetRelayMeta(c)
+	imageRequest, err := getImageRequest(c, meta.Mode)
 	if err != nil {
-		return openai.ErrorWrapper(err, "bind_request_body_failed", http.StatusBadRequest)
-	}
-
-	if imageRequest.N == 0 {
-		imageRequest.N = 1
-	}
-
-	// Size validation
-	if imageRequest.Size != "" {
-		imageSize = imageRequest.Size
-	}
-
-	// Model validation
-	if imageRequest.Model != "" {
-		imageModel = imageRequest.Model
-	}
-
-	imageCostRatio, hasValidSize := common.DalleSizeRatios[imageModel][imageSize]
-
-	// Check if model is supported
-	if hasValidSize {
-		if imageRequest.Quality == "hd" && imageModel == "dall-e-3" {
-			if imageSize == "1024x1024" {
-				imageCostRatio *= 2
-			} else {
-				imageCostRatio *= 1.5
-			}
-		}
-	} else {
-		return openai.ErrorWrapper(errors.New("size not supported for this image model"), "size_not_supported", http.StatusBadRequest)
-	}
-
-	// Prompt validation
-	if imageRequest.Prompt == "" {
-		return openai.ErrorWrapper(errors.New("prompt is required"), "prompt_missing", http.StatusBadRequest)
-	}
-
-	// Check prompt length
-	if len(imageRequest.Prompt) > common.DalleImagePromptLengthLimitations[imageModel] {
-		return openai.ErrorWrapper(errors.New("prompt is too long"), "prompt_too_long", http.StatusBadRequest)
-	}
-
-	// Number of generated images validation
-	if !isWithinRange(imageModel, imageRequest.N) {
-		// channel not azure
-		if channelType != common.ChannelTypeAzure {
-			return openai.ErrorWrapper(errors.New("invalid value of n"), "n_not_within_range", http.StatusBadRequest)
-		}
+		logger.Errorf(ctx, "getImageRequest failed: %s", err.Error())
+		return openai.ErrorWrapper(err, "invalid_image_request", http.StatusBadRequest)
 	}
 
 	// map model name
-	modelMapping := c.GetString("model_mapping")
-	isModelMapped := false
-	if modelMapping != "" {
-		modelMap := make(map[string]string)
-		err := json.Unmarshal([]byte(modelMapping), &modelMap)
-		if err != nil {
-			return openai.ErrorWrapper(err, "unmarshal_model_mapping_failed", http.StatusInternalServerError)
-		}
-		if modelMap[imageModel] != "" {
-			imageModel = modelMap[imageModel]
-			isModelMapped = true
-		}
+	var isModelMapped bool
+	meta.OriginModelName = imageRequest.Model
+	imageRequest.Model, isModelMapped = util.GetMappedModelName(imageRequest.Model, meta.ModelMapping)
+	meta.ActualModelName = imageRequest.Model
+
+	// model validation
+	bizErr := validateImageRequest(imageRequest, meta)
+	if bizErr != nil {
+		return bizErr
 	}
-	baseURL := common.ChannelBaseURLs[channelType]
+
+	imageCostRatio, err := getImageCostRatio(imageRequest)
+	if err != nil {
+		return openai.ErrorWrapper(err, "get_image_cost_ratio_failed", http.StatusInternalServerError)
+	}
+
 	requestURL := c.Request.URL.String()
-	if c.GetString("base_url") != "" {
-		baseURL = c.GetString("base_url")
-	}
-	fullRequestURL := util.GetFullRequestURL(baseURL, requestURL, channelType)
-	if channelType == common.ChannelTypeAzure {
+	fullRequestURL := util.GetFullRequestURL(meta.BaseURL, requestURL, meta.ChannelType)
+	if meta.ChannelType == common.ChannelTypeAzure {
 		// https://learn.microsoft.com/en-us/azure/ai-services/openai/dall-e-quickstart?tabs=dalle3%2Ccommand-line&pivots=rest-api
 		apiVersion := util.GetAzureAPIVersion(c)
 		// https://{resource_name}.openai.azure.com/openai/deployments/dall-e-3/images/generations?api-version=2023-06-01-preview
-		fullRequestURL = fmt.Sprintf("%s/openai/deployments/%s/images/generations?api-version=%s", baseURL, imageModel, apiVersion)
+		fullRequestURL = fmt.Sprintf("%s/openai/deployments/%s/images/generations?api-version=%s", meta.BaseURL, imageRequest.Model, apiVersion)
 	}
 
 	var requestBody io.Reader
-	if isModelMapped || channelType == common.ChannelTypeAzure { // make Azure channel request body
+	if isModelMapped || meta.ChannelType == common.ChannelTypeAzure { // make Azure channel request body
 		jsonStr, err := json.Marshal(imageRequest)
 		if err != nil {
-			return openai.ErrorWrapper(err, "marshal_text_request_failed", http.StatusInternalServerError)
+			return openai.ErrorWrapper(err, "marshal_image_request_failed", http.StatusInternalServerError)
 		}
 		requestBody = bytes.NewBuffer(jsonStr)
 	} else {
 		requestBody = c.Request.Body
 	}
 
-	modelRatio := common.GetModelRatio(imageModel)
-	groupRatio := common.GetGroupRatio(group)
+	modelRatio := common.GetModelRatio(imageRequest.Model)
+	groupRatio := common.GetGroupRatio(meta.Group)
 	ratio := modelRatio * groupRatio
-	userQuota, err := model.CacheGetUserQuota(userId)
+	userQuota, err := model.CacheGetUserQuota(meta.UserId)
 
 	quota := int(ratio*imageCostRatio*1000) * imageRequest.N
 
@@ -146,7 +92,7 @@ func RelayImageHelper(c *gin.Context, relayMode int) *relaymodel.ErrorWithStatus
 		return openai.ErrorWrapper(err, "new_request_failed", http.StatusInternalServerError)
 	}
 	token := c.Request.Header.Get("Authorization")
-	if channelType == common.ChannelTypeAzure { // Azure authentication
+	if meta.ChannelType == common.ChannelTypeAzure { // Azure authentication
 		token = strings.TrimPrefix(token, "Bearer ")
 		req.Header.Set("api-key", token)
 	} else {
@@ -169,25 +115,25 @@ func RelayImageHelper(c *gin.Context, relayMode int) *relaymodel.ErrorWithStatus
 	if err != nil {
 		return openai.ErrorWrapper(err, "close_request_body_failed", http.StatusInternalServerError)
 	}
-	var textResponse openai.ImageResponse
+	var imageResponse openai.ImageResponse
 
 	defer func(ctx context.Context) {
 		if resp.StatusCode != http.StatusOK {
 			return
 		}
-		err := model.PostConsumeTokenQuota(tokenId, quota)
+		err := model.PostConsumeTokenQuota(meta.TokenId, quota)
 		if err != nil {
 			logger.SysError("error consuming token remain quota: " + err.Error())
 		}
-		err = model.CacheUpdateUserQuota(userId)
+		err = model.CacheUpdateUserQuota(meta.UserId)
 		if err != nil {
 			logger.SysError("error update user quota cache: " + err.Error())
 		}
 		if quota != 0 {
 			tokenName := c.GetString("token_name")
 			logContent := fmt.Sprintf("模型倍率 %.2f，分组倍率 %.2f", modelRatio, groupRatio)
-			model.RecordConsumeLog(ctx, userId, channelId, 0, 0, imageModel, tokenName, quota, logContent)
-			model.UpdateUserUsedQuotaAndRequestCount(userId, quota)
+			model.RecordConsumeLog(ctx, meta.UserId, meta.ChannelId, 0, 0, imageRequest.Model, tokenName, quota, logContent)
+			model.UpdateUserUsedQuotaAndRequestCount(meta.UserId, quota)
 			channelId := c.GetInt("channel_id")
 			model.UpdateChannelUsedQuota(channelId, quota)
 		}
@@ -202,7 +148,7 @@ func RelayImageHelper(c *gin.Context, relayMode int) *relaymodel.ErrorWithStatus
 	if err != nil {
 		return openai.ErrorWrapper(err, "close_response_body_failed", http.StatusInternalServerError)
 	}
-	err = json.Unmarshal(responseBody, &textResponse)
+	err = json.Unmarshal(responseBody, &imageResponse)
 	if err != nil {
 		return openai.ErrorWrapper(err, "unmarshal_response_body_failed", http.StatusInternalServerError)
 	}

web/berry/src/constants/ChannelConstants.js

@@ -29,6 +29,12 @@ export const CHANNEL_OPTIONS = {
     value: 24,
     color: 'orange'
   },
+  28: {
+    key: 28,
+    text: 'Mistral AI',
+    value: 28,
+    color: 'orange'
+  },
   15: {
     key: 15,
     text: '百度文心千帆',

web/default/src/constants/channel.constants.js

@@ -4,6 +4,7 @@ export const CHANNEL_OPTIONS = [
   { key: 3, text: 'Azure OpenAI', value: 3, color: 'olive' },
   { key: 11, text: 'Google PaLM2', value: 11, color: 'orange' },
   { key: 24, text: 'Google Gemini', value: 24, color: 'orange' },
+  { key: 28, text: 'Mistral AI', value: 28, color: 'orange' },
   { key: 15, text: '百度文心千帆', value: 15, color: 'blue' },
   { key: 17, text: '阿里通义千问', value: 17, color: 'orange' },
   { key: 18, text: '讯飞星火认知', value: 18, color: 'blue' },