mirror of
https://github.com/QuantumNous/new-api.git
synced 2026-03-30 04:22:58 +00:00
0a2f12c04e
## 问题描述
当使用 Anthropic 渠道通过 `/v1/chat/completions` 端点调用且启用缓存功能时，
计费逻辑错误地减去了缓存 tokens，导致严重的收入损失（94.5%）。
## 根本原因
不同 API 的 `prompt_tokens` 定义不同：
- **Anthropic API**: `input_tokens` 字段已经是纯输入 tokens（不包含缓存）
- **OpenAI API**: `prompt_tokens` 字段包含所有 tokens（包含缓存）
- **OpenRouter API**: `prompt_tokens` 字段包含所有 tokens（包含缓存）
当前 `postConsumeQuota` 函数对所有渠道都减去缓存 tokens，这对 Anthropic
渠道是错误的，因为其 `input_tokens` 已经不包含缓存。
## 修复方案
在 `relay/compatible_handler.go` 的 `postConsumeQuota` 函数中，添加渠道类型判断：
```go
if relayInfo.ChannelType != constant.ChannelTypeAnthropic {
baseTokens = baseTokens.Sub(dCacheTokens)
}
```
只对非 Anthropic 渠道减去缓存 tokens。
## 影响分析
### ✅ 不受影响的场景
1. **无缓存调用**（所有渠道）
- cache_tokens = 0
- 减去 0 = 不减去
- 结果：完全一致
2. **OpenAI/OpenRouter 渠道 + 缓存**
- 继续减去缓存（因为 ChannelType != Anthropic）
- 结果：完全一致
3. **Anthropic 渠道 + /v1/messages 端点**
- 使用 PostClaudeConsumeQuota（不修改）
- 结果：完全不受影响
### ✅ 修复的场景
4. **Anthropic 渠道 + /v1/chat/completions + 缓存**
- 修复前：错误地减去缓存，导致 94.5% 收入损失
- 修复后：不减去缓存，计费正确
## 验证数据
以实际记录 143509 为例：
| 项目 | 修复前 | 修复后 | 差异 |
|------|--------|--------|------|
| Quota | 10,489 | 191,330 | +180,841 |
| 费用 | ¥0.020978 | ¥0.382660 | +¥0.361682 |
| 收入恢复 | - | - | **+1724.1%** |
## 测试建议
1. 测试 Anthropic 渠道 + 缓存场景
2. 测试 OpenAI 渠道 + 缓存场景（确保不受影响）
3. 测试无缓存场景（确保不受影响）
## 相关 Issue
修复 Anthropic 渠道使用 prompt caching 时的计费错误。
475 lines
18 KiB
Go
475 lines
18 KiB
Go
package relay
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import (
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"bytes"
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"fmt"
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"io"
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"net/http"
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"strings"
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"time"
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"github.com/QuantumNous/new-api/common"
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"github.com/QuantumNous/new-api/constant"
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"github.com/QuantumNous/new-api/dto"
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"github.com/QuantumNous/new-api/logger"
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"github.com/QuantumNous/new-api/model"
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relaycommon "github.com/QuantumNous/new-api/relay/common"
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"github.com/QuantumNous/new-api/relay/helper"
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"github.com/QuantumNous/new-api/service"
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"github.com/QuantumNous/new-api/setting/model_setting"
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"github.com/QuantumNous/new-api/setting/operation_setting"
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"github.com/QuantumNous/new-api/types"
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"github.com/shopspring/decimal"
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"github.com/gin-gonic/gin"
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)
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func TextHelper(c *gin.Context, info *relaycommon.RelayInfo) (newAPIError *types.NewAPIError) {
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info.InitChannelMeta(c)
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textReq, ok := info.Request.(*dto.GeneralOpenAIRequest)
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if !ok {
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return types.NewErrorWithStatusCode(fmt.Errorf("invalid request type, expected dto.GeneralOpenAIRequest, got %T", info.Request), types.ErrorCodeInvalidRequest, http.StatusBadRequest, types.ErrOptionWithSkipRetry())
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}
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request, err := common.DeepCopy(textReq)
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if err != nil {
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return types.NewError(fmt.Errorf("failed to copy request to GeneralOpenAIRequest: %w", err), types.ErrorCodeInvalidRequest, types.ErrOptionWithSkipRetry())
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}
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if request.WebSearchOptions != nil {
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c.Set("chat_completion_web_search_context_size", request.WebSearchOptions.SearchContextSize)
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}
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err = helper.ModelMappedHelper(c, info, request)
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if err != nil {
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return types.NewError(err, types.ErrorCodeChannelModelMappedError, types.ErrOptionWithSkipRetry())
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}
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includeUsage := true
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// 判断用户是否需要返回使用情况
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if request.StreamOptions != nil {
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includeUsage = request.StreamOptions.IncludeUsage
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}
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// 如果不支持StreamOptions，将StreamOptions设置为nil
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if !info.SupportStreamOptions || !request.Stream {
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request.StreamOptions = nil
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} else {
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// 如果支持StreamOptions，且请求中没有设置StreamOptions，根据配置文件设置StreamOptions
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if constant.ForceStreamOption {
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request.StreamOptions = &dto.StreamOptions{
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IncludeUsage: true,
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}
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}
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}
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info.ShouldIncludeUsage = includeUsage
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adaptor := GetAdaptor(info.ApiType)
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if adaptor == nil {
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return types.NewError(fmt.Errorf("invalid api type: %d", info.ApiType), types.ErrorCodeInvalidApiType, types.ErrOptionWithSkipRetry())
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}
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adaptor.Init(info)
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var requestBody io.Reader
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if model_setting.GetGlobalSettings().PassThroughRequestEnabled || info.ChannelSetting.PassThroughBodyEnabled {
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body, err := common.GetRequestBody(c)
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if err != nil {
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return types.NewErrorWithStatusCode(err, types.ErrorCodeReadRequestBodyFailed, http.StatusBadRequest, types.ErrOptionWithSkipRetry())
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}
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if common.DebugEnabled {
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println("requestBody: ", string(body))
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}
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requestBody = bytes.NewBuffer(body)
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} else {
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convertedRequest, err := adaptor.ConvertOpenAIRequest(c, info, request)
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if err != nil {
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return types.NewError(err, types.ErrorCodeConvertRequestFailed, types.ErrOptionWithSkipRetry())
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}
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if info.ChannelSetting.SystemPrompt != "" {
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// 如果有系统提示，则将其添加到请求中
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request, ok := convertedRequest.(*dto.GeneralOpenAIRequest)
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if ok {
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containSystemPrompt := false
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for _, message := range request.Messages {
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if message.Role == request.GetSystemRoleName() {
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containSystemPrompt = true
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break
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}
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}
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if !containSystemPrompt {
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// 如果没有系统提示，则添加系统提示
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systemMessage := dto.Message{
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Role: request.GetSystemRoleName(),
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Content: info.ChannelSetting.SystemPrompt,
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}
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request.Messages = append([]dto.Message{systemMessage}, request.Messages...)
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} else if info.ChannelSetting.SystemPromptOverride {
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common.SetContextKey(c, constant.ContextKeySystemPromptOverride, true)
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// 如果有系统提示，且允许覆盖，则拼接到前面
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for i, message := range request.Messages {
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if message.Role == request.GetSystemRoleName() {
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if message.IsStringContent() {
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request.Messages[i].SetStringContent(info.ChannelSetting.SystemPrompt + "\n" + message.StringContent())
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} else {
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contents := message.ParseContent()
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contents = append([]dto.MediaContent{
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{
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Type: dto.ContentTypeText,
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Text: info.ChannelSetting.SystemPrompt,
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},
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}, contents...)
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request.Messages[i].Content = contents
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}
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break
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}
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}
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}
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}
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}
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jsonData, err := common.Marshal(convertedRequest)
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if err != nil {
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return types.NewError(err, types.ErrorCodeJsonMarshalFailed, types.ErrOptionWithSkipRetry())
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}
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// remove disabled fields for OpenAI API
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jsonData, err = relaycommon.RemoveDisabledFields(jsonData, info.ChannelOtherSettings)
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if err != nil {
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return types.NewError(err, types.ErrorCodeConvertRequestFailed, types.ErrOptionWithSkipRetry())
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}
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// apply param override
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if len(info.ParamOverride) > 0 {
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jsonData, err = relaycommon.ApplyParamOverride(jsonData, info.ParamOverride, relaycommon.BuildParamOverrideContext(info))
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if err != nil {
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return types.NewError(err, types.ErrorCodeChannelParamOverrideInvalid, types.ErrOptionWithSkipRetry())
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}
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}
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logger.LogDebug(c, fmt.Sprintf("text request body: %s", string(jsonData)))
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requestBody = bytes.NewBuffer(jsonData)
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}
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var httpResp *http.Response
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resp, err := adaptor.DoRequest(c, info, requestBody)
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if err != nil {
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return types.NewOpenAIError(err, types.ErrorCodeDoRequestFailed, http.StatusInternalServerError)
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}
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statusCodeMappingStr := c.GetString("status_code_mapping")
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if resp != nil {
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httpResp = resp.(*http.Response)
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info.IsStream = info.IsStream || strings.HasPrefix(httpResp.Header.Get("Content-Type"), "text/event-stream")
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if httpResp.StatusCode != http.StatusOK {
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newApiErr := service.RelayErrorHandler(c.Request.Context(), httpResp, false)
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// reset status code 重置状态码
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service.ResetStatusCode(newApiErr, statusCodeMappingStr)
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return newApiErr
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}
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}
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usage, newApiErr := adaptor.DoResponse(c, httpResp, info)
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if newApiErr != nil {
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// reset status code 重置状态码
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service.ResetStatusCode(newApiErr, statusCodeMappingStr)
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return newApiErr
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}
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if usage.(*dto.Usage).CompletionTokenDetails.AudioTokens > 0 || usage.(*dto.Usage).PromptTokensDetails.AudioTokens > 0 {
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service.PostAudioConsumeQuota(c, info, usage.(*dto.Usage), "")
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} else {
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postConsumeQuota(c, info, usage.(*dto.Usage), "")
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}
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return nil
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}
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func postConsumeQuota(ctx *gin.Context, relayInfo *relaycommon.RelayInfo, usage *dto.Usage, extraContent string) {
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if usage == nil {
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usage = &dto.Usage{
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PromptTokens: relayInfo.GetEstimatePromptTokens(),
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CompletionTokens: 0,
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TotalTokens: relayInfo.GetEstimatePromptTokens(),
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}
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extraContent += "（可能是请求出错）"
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}
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useTimeSeconds := time.Now().Unix() - relayInfo.StartTime.Unix()
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promptTokens := usage.PromptTokens
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cacheTokens := usage.PromptTokensDetails.CachedTokens
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imageTokens := usage.PromptTokensDetails.ImageTokens
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audioTokens := usage.PromptTokensDetails.AudioTokens
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completionTokens := usage.CompletionTokens
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cachedCreationTokens := usage.PromptTokensDetails.CachedCreationTokens
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modelName := relayInfo.OriginModelName
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tokenName := ctx.GetString("token_name")
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completionRatio := relayInfo.PriceData.CompletionRatio
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cacheRatio := relayInfo.PriceData.CacheRatio
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imageRatio := relayInfo.PriceData.ImageRatio
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modelRatio := relayInfo.PriceData.ModelRatio
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groupRatio := relayInfo.PriceData.GroupRatioInfo.GroupRatio
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modelPrice := relayInfo.PriceData.ModelPrice
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cachedCreationRatio := relayInfo.PriceData.CacheCreationRatio
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// Convert values to decimal for precise calculation
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dPromptTokens := decimal.NewFromInt(int64(promptTokens))
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dCacheTokens := decimal.NewFromInt(int64(cacheTokens))
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dImageTokens := decimal.NewFromInt(int64(imageTokens))
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dAudioTokens := decimal.NewFromInt(int64(audioTokens))
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dCompletionTokens := decimal.NewFromInt(int64(completionTokens))
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dCachedCreationTokens := decimal.NewFromInt(int64(cachedCreationTokens))
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dCompletionRatio := decimal.NewFromFloat(completionRatio)
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dCacheRatio := decimal.NewFromFloat(cacheRatio)
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dImageRatio := decimal.NewFromFloat(imageRatio)
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dModelRatio := decimal.NewFromFloat(modelRatio)
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dGroupRatio := decimal.NewFromFloat(groupRatio)
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dModelPrice := decimal.NewFromFloat(modelPrice)
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dCachedCreationRatio := decimal.NewFromFloat(cachedCreationRatio)
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dQuotaPerUnit := decimal.NewFromFloat(common.QuotaPerUnit)
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ratio := dModelRatio.Mul(dGroupRatio)
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// openai web search 工具计费
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var dWebSearchQuota decimal.Decimal
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var webSearchPrice float64
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// response api 格式工具计费
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if relayInfo.ResponsesUsageInfo != nil {
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if webSearchTool, exists := relayInfo.ResponsesUsageInfo.BuiltInTools[dto.BuildInToolWebSearchPreview]; exists && webSearchTool.CallCount > 0 {
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// 计算 web search 调用的配额 (配额 = 价格 * 调用次数 / 1000 * 分组倍率)
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webSearchPrice = operation_setting.GetWebSearchPricePerThousand(modelName, webSearchTool.SearchContextSize)
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dWebSearchQuota = decimal.NewFromFloat(webSearchPrice).
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Mul(decimal.NewFromInt(int64(webSearchTool.CallCount))).
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Div(decimal.NewFromInt(1000)).Mul(dGroupRatio).Mul(dQuotaPerUnit)
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extraContent += fmt.Sprintf("Web Search 调用 %d 次，上下文大小 %s，调用花费 %s",
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webSearchTool.CallCount, webSearchTool.SearchContextSize, dWebSearchQuota.String())
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}
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} else if strings.HasSuffix(modelName, "search-preview") {
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// search-preview 模型不支持 response api
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searchContextSize := ctx.GetString("chat_completion_web_search_context_size")
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if searchContextSize == "" {
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searchContextSize = "medium"
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}
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webSearchPrice = operation_setting.GetWebSearchPricePerThousand(modelName, searchContextSize)
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dWebSearchQuota = decimal.NewFromFloat(webSearchPrice).
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Div(decimal.NewFromInt(1000)).Mul(dGroupRatio).Mul(dQuotaPerUnit)
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extraContent += fmt.Sprintf("Web Search 调用 1 次，上下文大小 %s，调用花费 %s",
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searchContextSize, dWebSearchQuota.String())
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}
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// claude web search tool 计费
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var dClaudeWebSearchQuota decimal.Decimal
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var claudeWebSearchPrice float64
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claudeWebSearchCallCount := ctx.GetInt("claude_web_search_requests")
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if claudeWebSearchCallCount > 0 {
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claudeWebSearchPrice = operation_setting.GetClaudeWebSearchPricePerThousand()
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dClaudeWebSearchQuota = decimal.NewFromFloat(claudeWebSearchPrice).
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Div(decimal.NewFromInt(1000)).Mul(dGroupRatio).Mul(dQuotaPerUnit).Mul(decimal.NewFromInt(int64(claudeWebSearchCallCount)))
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extraContent += fmt.Sprintf("Claude Web Search 调用 %d 次，调用花费 %s",
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claudeWebSearchCallCount, dClaudeWebSearchQuota.String())
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}
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// file search tool 计费
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var dFileSearchQuota decimal.Decimal
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var fileSearchPrice float64
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if relayInfo.ResponsesUsageInfo != nil {
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if fileSearchTool, exists := relayInfo.ResponsesUsageInfo.BuiltInTools[dto.BuildInToolFileSearch]; exists && fileSearchTool.CallCount > 0 {
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fileSearchPrice = operation_setting.GetFileSearchPricePerThousand()
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dFileSearchQuota = decimal.NewFromFloat(fileSearchPrice).
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Mul(decimal.NewFromInt(int64(fileSearchTool.CallCount))).
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Div(decimal.NewFromInt(1000)).Mul(dGroupRatio).Mul(dQuotaPerUnit)
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extraContent += fmt.Sprintf("File Search 调用 %d 次，调用花费 %s",
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fileSearchTool.CallCount, dFileSearchQuota.String())
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}
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}
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var dImageGenerationCallQuota decimal.Decimal
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var imageGenerationCallPrice float64
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if ctx.GetBool("image_generation_call") {
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imageGenerationCallPrice = operation_setting.GetGPTImage1PriceOnceCall(ctx.GetString("image_generation_call_quality"), ctx.GetString("image_generation_call_size"))
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dImageGenerationCallQuota = decimal.NewFromFloat(imageGenerationCallPrice).Mul(dGroupRatio).Mul(dQuotaPerUnit)
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extraContent += fmt.Sprintf("Image Generation Call 花费 %s", dImageGenerationCallQuota.String())
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}
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var quotaCalculateDecimal decimal.Decimal
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var audioInputQuota decimal.Decimal
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var audioInputPrice float64
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if !relayInfo.PriceData.UsePrice {
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baseTokens := dPromptTokens
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// 减去 cached tokens
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// Anthropic API 的 input_tokens 已经不包含缓存 tokens，不需要减去
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// OpenAI/OpenRouter 等 API 的 prompt_tokens 包含缓存 tokens，需要减去
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var cachedTokensWithRatio decimal.Decimal
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if !dCacheTokens.IsZero() {
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if relayInfo.ChannelType != constant.ChannelTypeAnthropic {
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baseTokens = baseTokens.Sub(dCacheTokens)
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}
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cachedTokensWithRatio = dCacheTokens.Mul(dCacheRatio)
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}
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var dCachedCreationTokensWithRatio decimal.Decimal
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if !dCachedCreationTokens.IsZero() {
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if relayInfo.ChannelType != constant.ChannelTypeAnthropic {
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baseTokens = baseTokens.Sub(dCachedCreationTokens)
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}
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dCachedCreationTokensWithRatio = dCachedCreationTokens.Mul(dCachedCreationRatio)
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}
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// 减去 image tokens
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var imageTokensWithRatio decimal.Decimal
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if !dImageTokens.IsZero() {
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baseTokens = baseTokens.Sub(dImageTokens)
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imageTokensWithRatio = dImageTokens.Mul(dImageRatio)
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}
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// 减去 Gemini audio tokens
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if !dAudioTokens.IsZero() {
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audioInputPrice = operation_setting.GetGeminiInputAudioPricePerMillionTokens(modelName)
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if audioInputPrice > 0 {
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// 重新计算 base tokens
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baseTokens = baseTokens.Sub(dAudioTokens)
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audioInputQuota = decimal.NewFromFloat(audioInputPrice).Div(decimal.NewFromInt(1000000)).Mul(dAudioTokens).Mul(dGroupRatio).Mul(dQuotaPerUnit)
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extraContent += fmt.Sprintf("Audio Input 花费 %s", audioInputQuota.String())
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}
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}
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promptQuota := baseTokens.Add(cachedTokensWithRatio).
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Add(imageTokensWithRatio).
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Add(dCachedCreationTokensWithRatio)
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completionQuota := dCompletionTokens.Mul(dCompletionRatio)
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quotaCalculateDecimal = promptQuota.Add(completionQuota).Mul(ratio)
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if !ratio.IsZero() && quotaCalculateDecimal.LessThanOrEqual(decimal.Zero) {
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quotaCalculateDecimal = decimal.NewFromInt(1)
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}
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} else {
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quotaCalculateDecimal = dModelPrice.Mul(dQuotaPerUnit).Mul(dGroupRatio)
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}
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// 添加 responses tools call 调用的配额
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quotaCalculateDecimal = quotaCalculateDecimal.Add(dWebSearchQuota)
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quotaCalculateDecimal = quotaCalculateDecimal.Add(dFileSearchQuota)
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// 添加 audio input 独立计费
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quotaCalculateDecimal = quotaCalculateDecimal.Add(audioInputQuota)
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// 添加 image generation call 计费
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quotaCalculateDecimal = quotaCalculateDecimal.Add(dImageGenerationCallQuota)
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quota := int(quotaCalculateDecimal.Round(0).IntPart())
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totalTokens := promptTokens + completionTokens
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var logContent string
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// record all the consume log even if quota is 0
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if totalTokens == 0 {
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// in this case, must be some error happened
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// we cannot just return, because we may have to return the pre-consumed quota
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quota = 0
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logContent += fmt.Sprintf("（可能是上游超时）")
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logger.LogError(ctx, fmt.Sprintf("total tokens is 0, cannot consume quota, userId %d, channelId %d, "+
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"tokenId %d, model %s， pre-consumed quota %d", relayInfo.UserId, relayInfo.ChannelId, relayInfo.TokenId, modelName, relayInfo.FinalPreConsumedQuota))
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} else {
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if !ratio.IsZero() && quota == 0 {
|
||
quota = 1
|
||
}
|
||
model.UpdateUserUsedQuotaAndRequestCount(relayInfo.UserId, quota)
|
||
model.UpdateChannelUsedQuota(relayInfo.ChannelId, quota)
|
||
}
|
||
|
||
quotaDelta := quota - relayInfo.FinalPreConsumedQuota
|
||
|
||
//logger.LogInfo(ctx, fmt.Sprintf("request quota delta: %s", logger.FormatQuota(quotaDelta)))
|
||
|
||
if quotaDelta > 0 {
|
||
logger.LogInfo(ctx, fmt.Sprintf("预扣费后补扣费：%s（实际消耗：%s，预扣费：%s）",
|
||
logger.FormatQuota(quotaDelta),
|
||
logger.FormatQuota(quota),
|
||
logger.FormatQuota(relayInfo.FinalPreConsumedQuota),
|
||
))
|
||
} else if quotaDelta < 0 {
|
||
logger.LogInfo(ctx, fmt.Sprintf("预扣费后返还扣费：%s（实际消耗：%s，预扣费：%s）",
|
||
logger.FormatQuota(-quotaDelta),
|
||
logger.FormatQuota(quota),
|
||
logger.FormatQuota(relayInfo.FinalPreConsumedQuota),
|
||
))
|
||
}
|
||
|
||
if quotaDelta != 0 {
|
||
err := service.PostConsumeQuota(relayInfo, quotaDelta, relayInfo.FinalPreConsumedQuota, true)
|
||
if err != nil {
|
||
logger.LogError(ctx, "error consuming token remain quota: "+err.Error())
|
||
}
|
||
}
|
||
|
||
logModel := modelName
|
||
if strings.HasPrefix(logModel, "gpt-4-gizmo") {
|
||
logModel = "gpt-4-gizmo-*"
|
||
logContent += fmt.Sprintf("，模型 %s", modelName)
|
||
}
|
||
if strings.HasPrefix(logModel, "gpt-4o-gizmo") {
|
||
logModel = "gpt-4o-gizmo-*"
|
||
logContent += fmt.Sprintf("，模型 %s", modelName)
|
||
}
|
||
if extraContent != "" {
|
||
logContent += ", " + extraContent
|
||
}
|
||
other := service.GenerateTextOtherInfo(ctx, relayInfo, modelRatio, groupRatio, completionRatio, cacheTokens, cacheRatio, modelPrice, relayInfo.PriceData.GroupRatioInfo.GroupSpecialRatio)
|
||
if imageTokens != 0 {
|
||
other["image"] = true
|
||
other["image_ratio"] = imageRatio
|
||
other["image_output"] = imageTokens
|
||
}
|
||
if cachedCreationTokens != 0 {
|
||
other["cache_creation_tokens"] = cachedCreationTokens
|
||
other["cache_creation_ratio"] = cachedCreationRatio
|
||
}
|
||
if !dWebSearchQuota.IsZero() {
|
||
if relayInfo.ResponsesUsageInfo != nil {
|
||
if webSearchTool, exists := relayInfo.ResponsesUsageInfo.BuiltInTools[dto.BuildInToolWebSearchPreview]; exists {
|
||
other["web_search"] = true
|
||
other["web_search_call_count"] = webSearchTool.CallCount
|
||
other["web_search_price"] = webSearchPrice
|
||
}
|
||
} else if strings.HasSuffix(modelName, "search-preview") {
|
||
other["web_search"] = true
|
||
other["web_search_call_count"] = 1
|
||
other["web_search_price"] = webSearchPrice
|
||
}
|
||
} else if !dClaudeWebSearchQuota.IsZero() {
|
||
other["web_search"] = true
|
||
other["web_search_call_count"] = claudeWebSearchCallCount
|
||
other["web_search_price"] = claudeWebSearchPrice
|
||
}
|
||
if !dFileSearchQuota.IsZero() && relayInfo.ResponsesUsageInfo != nil {
|
||
if fileSearchTool, exists := relayInfo.ResponsesUsageInfo.BuiltInTools[dto.BuildInToolFileSearch]; exists {
|
||
other["file_search"] = true
|
||
other["file_search_call_count"] = fileSearchTool.CallCount
|
||
other["file_search_price"] = fileSearchPrice
|
||
}
|
||
}
|
||
if !audioInputQuota.IsZero() {
|
||
other["audio_input_seperate_price"] = true
|
||
other["audio_input_token_count"] = audioTokens
|
||
other["audio_input_price"] = audioInputPrice
|
||
}
|
||
if !dImageGenerationCallQuota.IsZero() {
|
||
other["image_generation_call"] = true
|
||
other["image_generation_call_price"] = imageGenerationCallPrice
|
||
}
|
||
model.RecordConsumeLog(ctx, relayInfo.UserId, model.RecordConsumeLogParams{
|
||
ChannelId: relayInfo.ChannelId,
|
||
PromptTokens: promptTokens,
|
||
CompletionTokens: completionTokens,
|
||
ModelName: logModel,
|
||
TokenName: tokenName,
|
||
Quota: quota,
|
||
Content: logContent,
|
||
TokenId: relayInfo.TokenId,
|
||
UseTimeSeconds: int(useTimeSeconds),
|
||
IsStream: relayInfo.IsStream,
|
||
Group: relayInfo.UsingGroup,
|
||
Other: other,
|
||
})
|
||
}
|