update dockerignore

fix delete title schema

.dockerignore

@@ -0,0 +1,6 @@
+.github
+.git
+*.md
+.vscode
+.gitignore
+Makefile

.gitignore

@@ -8,4 +8,5 @@ build
 logs
 web/dist
 .env
-one-api
+one-api
+.DS_Store

common/model-ratio.go

@@ -356,7 +356,7 @@ func GetCompletionRatio(name string) float64 {
 		}
 		return 2
 	}
-	if strings.HasPrefix(name, "o1-") {
+	if strings.HasPrefix(name, "o1") {
 		return 4
 	}
 	if name == "chatgpt-4o-latest" {

relay/channel/gemini/relay-gemini.go

@@ -245,12 +245,12 @@ func removeAdditionalPropertiesWithDepth(schema interface{}, depth int) interfac
 	if !ok || len(v) == 0 {
 		return schema
 	}
-
+	// 删除所有的title字段
+	delete(v, "title")
 	// 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
 	}
-	delete(v, "title")
 	switch v["type"] {
 	case "object":
 		delete(v, "additionalProperties")

relay/channel/openai/adaptor.go

@@ -106,7 +106,7 @@ func (a *Adaptor) ConvertRequest(c *gin.Context, info *relaycommon.RelayInfo, re
 	if request == nil {
 		return nil, errors.New("request is nil")
 	}
-	if info.ChannelType != common.ChannelTypeOpenAI {
+	if info.ChannelType != common.ChannelTypeOpenAI && info.ChannelType != common.ChannelTypeAzure {
 		request.StreamOptions = nil
 	}
 	if strings.HasPrefix(request.Model, "o1") {

relay/common/relay_info.go

@@ -109,7 +109,7 @@ func GenRelayInfo(c *gin.Context) *RelayInfo {
 	}
 	if info.ChannelType == common.ChannelTypeOpenAI || info.ChannelType == common.ChannelTypeAnthropic ||
 		info.ChannelType == common.ChannelTypeAws || info.ChannelType == common.ChannelTypeGemini ||
-		info.ChannelType == common.ChannelCloudflare {
+		info.ChannelType == common.ChannelCloudflare || info.ChannelType == common.ChannelTypeAzure {
 		info.SupportStreamOptions = true
 	}
 	return info

relay/relay-text.go

@@ -108,10 +108,17 @@ func TextHelper(c *gin.Context) (openaiErr *dto.OpenAIErrorWithStatusCode) {
 		}
 	}
 
-	promptTokens, err := getPromptTokens(textRequest, relayInfo)
-	// count messages token error 计算promptTokens错误
-	if err != nil {
-		return service.OpenAIErrorWrapper(err, "count_token_messages_failed", http.StatusInternalServerError)
+	// 获取 promptTokens，如果上下文中已经存在，则直接使用
+	var promptTokens int
+	if value, exists := c.Get("prompt_tokens"); exists {
+		promptTokens = value.(int)
+	} else {
+		promptTokens, err = getPromptTokens(textRequest, relayInfo)
+		// count messages token error 计算promptTokens错误
+		if err != nil {
+			return service.OpenAIErrorWrapper(err, "count_token_messages_failed", http.StatusInternalServerError)
+		}
+		c.Set("prompt_tokens", promptTokens)
 	}
 
 	if !getModelPriceSuccess {

router/api-router.go

@@ -28,10 +28,10 @@ func SetApiRouter(router *gin.Engine) {
 		apiRouter.GET("/oauth/linuxdo", middleware.CriticalRateLimit(), controller.LinuxdoOAuth)
 		apiRouter.GET("/oauth/state", middleware.CriticalRateLimit(), controller.GenerateOAuthCode)
 		apiRouter.GET("/oauth/wechat", middleware.CriticalRateLimit(), controller.WeChatAuth)
-		apiRouter.GET("/oauth/wechat/bind", middleware.CriticalRateLimit(), middleware.UserAuth(), controller.WeChatBind)
-		apiRouter.GET("/oauth/email/bind", middleware.CriticalRateLimit(), middleware.UserAuth(), controller.EmailBind)
+		apiRouter.GET("/oauth/wechat/bind", middleware.CriticalRateLimit(), controller.WeChatBind)
+		apiRouter.GET("/oauth/email/bind", middleware.CriticalRateLimit(), controller.EmailBind)
 		apiRouter.GET("/oauth/telegram/login", middleware.CriticalRateLimit(), controller.TelegramLogin)
-		apiRouter.GET("/oauth/telegram/bind", middleware.CriticalRateLimit(), middleware.UserAuth(), controller.TelegramBind)
+		apiRouter.GET("/oauth/telegram/bind", middleware.CriticalRateLimit(), controller.TelegramBind)
 
 		userRoute := apiRouter.Group("/user")
 		{

service/token_counter.go

@@ -19,42 +19,40 @@ import (
 // tokenEncoderMap won't grow after initialization
 var tokenEncoderMap = map[string]*tiktoken.Tiktoken{}
 var defaultTokenEncoder *tiktoken.Tiktoken
-var cl200kTokenEncoder *tiktoken.Tiktoken
+var o200kTokenEncoder *tiktoken.Tiktoken
 
 func InitTokenEncoders() {
 	common.SysLog("initializing token encoders")
-	gpt35TokenEncoder, err := tiktoken.EncodingForModel("gpt-3.5-turbo")
+	cl100TokenEncoder, err := tiktoken.GetEncoding(tiktoken.MODEL_CL100K_BASE)
 	if err != nil {
 		common.FatalLog(fmt.Sprintf("failed to get gpt-3.5-turbo token encoder: %s", err.Error()))
 	}
-	defaultTokenEncoder = gpt35TokenEncoder
-	gpt4TokenEncoder, err := tiktoken.EncodingForModel("gpt-4")
-	if err != nil {
-		common.FatalLog(fmt.Sprintf("failed to get gpt-4 token encoder: %s", err.Error()))
-	}
-	cl200kTokenEncoder, err = tiktoken.EncodingForModel("gpt-4o")
+	defaultTokenEncoder = cl100TokenEncoder
+	o200kTokenEncoder, err = tiktoken.GetEncoding(tiktoken.MODEL_O200K_BASE)
 	if err != nil {
 		common.FatalLog(fmt.Sprintf("failed to get gpt-4o token encoder: %s", err.Error()))
 	}
 	for model, _ := range common.GetDefaultModelRatioMap() {
 		if strings.HasPrefix(model, "gpt-3.5") {
-			tokenEncoderMap[model] = gpt35TokenEncoder
+			tokenEncoderMap[model] = cl100TokenEncoder
 		} else if strings.HasPrefix(model, "gpt-4") {
 			if strings.HasPrefix(model, "gpt-4o") {
-				tokenEncoderMap[model] = cl200kTokenEncoder
+				tokenEncoderMap[model] = o200kTokenEncoder
 			} else {
-				tokenEncoderMap[model] = gpt4TokenEncoder
+				tokenEncoderMap[model] = defaultTokenEncoder
 			}
+		} else if strings.HasPrefix(model, "o1") {
+			tokenEncoderMap[model] = o200kTokenEncoder
 		} else {
-			tokenEncoderMap[model] = nil
+			tokenEncoderMap[model] = defaultTokenEncoder
 		}
 	}
 	common.SysLog("token encoders initialized")
 }
 
 func getModelDefaultTokenEncoder(model string) *tiktoken.Tiktoken {
-	if strings.HasPrefix(model, "gpt-4o") || strings.HasPrefix(model, "chatgpt-4o") {
-		return cl200kTokenEncoder
+	if strings.HasPrefix(model, "gpt-4o") || strings.HasPrefix(model, "chatgpt-4o") || strings.HasPrefix(model, "o1") {
+		return o200kTokenEncoder
 	}
 	return defaultTokenEncoder
 }
@@ -92,11 +90,11 @@ func getImageToken(imageUrl *dto.MessageImageUrl, model string, stream bool) (in
 	}
 	// TODO: 非流模式下不计算图片token数量
 	if !constant.GetMediaTokenNotStream && !stream {
-		return 1000, nil
+		return 256, nil
 	}
 	// 是否统计图片token
 	if !constant.GetMediaToken {
-		return 1000, nil
+		return 256, nil
 	}
 	// 同步One API的图片计费逻辑
 	if imageUrl.Detail == "auto" || imageUrl.Detail == "" {

web/src/helpers/render.js

@@ -59,6 +59,9 @@ export function renderNumber(num) {
 }
 
 export function renderQuotaNumberWithDigit(num, digits = 2) {
+  if (typeof num !== 'number' || isNaN(num)) {
+    return 0;
+  }
   let displayInCurrency = localStorage.getItem('display_in_currency');
   num = num.toFixed(digits);
   if (displayInCurrency) {

web/src/helpers/utils.js

@@ -180,6 +180,9 @@ export function timestamp2string1(timestamp, dataExportDefaultTime = 'hour') {
   let month = (date.getMonth() + 1).toString();
   let day = date.getDate().toString();
   let hour = date.getHours().toString();
+  if (day === '24') {
+    console.log("timestamp", timestamp);
+  }
   if (month.length === 1) {
     month = '0' + month;
   }

web/src/pages/Detail/index.js

@@ -143,8 +143,7 @@ const Detail = (props) => {
         content: [
           {
             key: (datum) => datum['Model'],
-            value: (datum) =>
-              renderQuotaNumberWithDigit(parseFloat(datum['Usage']), 4),
+            value: (datum) => renderQuota(datum['rawQuota'] || 0, 4),
           },
         ],
       },
@@ -152,22 +151,28 @@ const Detail = (props) => {
         content: [
           {
             key: (datum) => datum['Model'],
-            value: (datum) => datum['Usage'],
+            value: (datum) => datum['rawQuota'] || 0,
           },
         ],
         updateContent: (array) => {
           array.sort((a, b) => b.value - a.value);
           let sum = 0;
           for (let i = 0; i < array.length; i++) {
-            sum += parseFloat(array[i].value);
-            array[i].value = renderQuotaNumberWithDigit(
-              parseFloat(array[i].value),
-              4,
-            );
+            if (array[i].key == "其他") {
+              continue;
+            }
+            let value = parseFloat(array[i].value);
+            if (isNaN(value)) {
+              value = 0;
+            }
+            if (array[i].datum && array[i].datum.TimeSum) {
+              sum = array[i].datum.TimeSum;
+            }
+            array[i].value = renderQuota(value, 4);
           }
           array.unshift({
             key: t('总计'),
-            value: renderQuotaNumberWithDigit(sum, 4),
+            value: renderQuota(sum, 4),
           });
           return array;
         },
@@ -212,19 +217,8 @@ const Detail = (props) => {
             created_at: now.getTime() / 1000,
           });
         }
-        // 根据dataExportDefaultTime重制时间粒度
-        let timeGranularity = 3600;
-        if (dataExportDefaultTime === 'day') {
-          timeGranularity = 86400;
-        } else if (dataExportDefaultTime === 'week') {
-          timeGranularity = 604800;
-        }
         // sort created_at
         data.sort((a, b) => a.created_at - b.created_at);
-        data.forEach((item) => {
-          item['created_at'] =
-            Math.floor(item['created_at'] / timeGranularity) * timeGranularity;
-        });
         updateChartData(data);
       } else {
         showError(message);
@@ -250,14 +244,14 @@ const Detail = (props) => {
     let uniqueModels = new Set();
     let totalTokens = 0;
 
-    // 收集所有唯一的模型名称和时间点
-    let uniqueTimes = new Set();
+    // 收集所有唯一的模型名称
     data.forEach(item => {
       uniqueModels.add(item.model_name);
-      uniqueTimes.add(timestamp2string1(item.created_at, dataExportDefaultTime));
       totalTokens += item.token_used;
+      totalQuota += item.quota;
+      totalTimes += item.count;
     });
-    
+
     // 处理颜色映射
     const newModelColors = {};
     Array.from(uniqueModels).forEach((modelName) => {
@@ -267,56 +261,82 @@ const Detail = (props) => {
     });
     setModelColors(newModelColors);
 
-    // 处理饼图数据
-    for (let item of data) {
-      totalQuota += item.quota;
-      totalTimes += item.count;
-      
-      let pieItem = newPieData.find((it) => it.type === item.model_name);
-      if (pieItem) {
-        pieItem.value += item.count;
-      } else {
-        newPieData.push({
-          type: item.model_name,
-          value: item.count,
+    // 按时间和模型聚合数据
+    let aggregatedData = new Map();
+    data.forEach(item => {
+      const timeKey = timestamp2string1(item.created_at, dataExportDefaultTime);
+      const modelKey = item.model_name;
+      const key = `${timeKey}-${modelKey}`;
+
+      if (!aggregatedData.has(key)) {
+        aggregatedData.set(key, {
+          time: timeKey,
+          model: modelKey,
+          quota: 0,
+          count: 0
         });
       }
+      
+      const existing = aggregatedData.get(key);
+      existing.quota += item.quota;
+      existing.count += item.count;
+    });
+
+    // 处理饼图数据
+    let modelTotals = new Map();
+    for (let [_, value] of aggregatedData) {
+      if (!modelTotals.has(value.model)) {
+        modelTotals.set(value.model, 0);
+      }
+      modelTotals.set(value.model, modelTotals.get(value.model) + value.count);
     }
 
-    // 处理柱状图数据
-    let timePoints = Array.from(uniqueTimes);
+    newPieData = Array.from(modelTotals).map(([model, count]) => ({
+      type: model,
+      value: count
+    }));
+
+    // 生成时间点序列
+    let timePoints = Array.from(new Set([...aggregatedData.values()].map(d => d.time)));
     if (timePoints.length < 7) {
-      // 根据时间粒度生成合适的时间点
-      const generateTimePoints = () => {
-        let lastTime = Math.max(...data.map(item => item.created_at));
-        let points = [];
-        let interval = dataExportDefaultTime === 'hour' ? 3600 
+      const lastTime = Math.max(...data.map(item => item.created_at));
+      const interval = dataExportDefaultTime === 'hour' ? 3600 
                       : dataExportDefaultTime === 'day' ? 86400 
                       : 604800;
-
-        for (let i = 0; i < 7; i++) {
-          points.push(timestamp2string1(lastTime - (i * interval), dataExportDefaultTime));
-        }
-        return points.reverse();
-      };
-
-      timePoints = generateTimePoints();
+      
+      timePoints = Array.from({length: 7}, (_, i) => 
+        timestamp2string1(lastTime - (6-i) * interval, dataExportDefaultTime)
+      );
     }
 
-    // 为每个时间点和模型生成数据
+    // 生成柱状图数据
     timePoints.forEach(time => {
-      Array.from(uniqueModels).forEach(model => {
-        let existingData = data.find(item => 
-          timestamp2string1(item.created_at, dataExportDefaultTime) === time && 
-          item.model_name === model
-        );
-
-        newLineData.push({
+      // 为每个时间点收集所有模型的数据
+      let timeData = Array.from(uniqueModels).map(model => {
+        const key = `${time}-${model}`;
+        const aggregated = aggregatedData.get(key);
+        return {
           Time: time,
           Model: model,
-          Usage: existingData ? parseFloat(getQuotaWithUnit(existingData.quota)) : 0
-        });
+          rawQuota: aggregated?.quota || 0,
+          Usage: aggregated?.quota ? getQuotaWithUnit(aggregated.quota, 4) : 0
+        };
       });
+      
+      // 计算该时间点的总计
+      const timeSum = timeData.reduce((sum, item) => sum + item.rawQuota, 0);
+      
+      // 按照 rawQuota 从大到小排序
+      timeData.sort((a, b) => b.rawQuota - a.rawQuota);
+      
+      // 为每个数据点添加该时间的总计
+      timeData = timeData.map(item => ({
+        ...item,
+        TimeSum: timeSum
+      }));
+      
+      // 将排序后的数据添加到 newLineData
+      newLineData.push(...timeData);
     });
 
     // 排序