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https://github.com/songquanpeng/one-api.git
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feat: add image counter for gpt-4 vision (#795)
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@@ -3,10 +3,13 @@ package controller
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import (
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"context"
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"encoding/json"
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"errors"
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"fmt"
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"io"
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"math"
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"net/http"
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"one-api/common"
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"one-api/common/image"
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"one-api/model"
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"strconv"
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"strings"
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@@ -87,7 +90,33 @@ func countTokenMessages(messages []Message, model string) int {
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tokenNum := 0
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for _, message := range messages {
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tokenNum += tokensPerMessage
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tokenNum += getTokenNum(tokenEncoder, message.StringContent())
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switch v := message.Content.(type) {
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case string:
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tokenNum += getTokenNum(tokenEncoder, v)
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case []any:
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for _, it := range v {
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m := it.(map[string]any)
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switch m["type"] {
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case "text":
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tokenNum += getTokenNum(tokenEncoder, m["text"].(string))
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case "image_url":
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imageUrl, ok := m["image_url"].(map[string]any)
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if ok {
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url := imageUrl["url"].(string)
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detail := ""
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if imageUrl["detail"] != nil {
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detail = imageUrl["detail"].(string)
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}
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imageTokens, err := countImageTokens(url, detail)
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if err != nil {
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common.SysError("error counting image tokens: " + err.Error())
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} else {
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tokenNum += imageTokens
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}
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}
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}
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}
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}
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tokenNum += getTokenNum(tokenEncoder, message.Role)
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if message.Name != nil {
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tokenNum += tokensPerName
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@@ -98,13 +127,81 @@ func countTokenMessages(messages []Message, model string) int {
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return tokenNum
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}
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const (
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lowDetailCost = 85
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highDetailCostPerTile = 170
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additionalCost = 85
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)
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// https://platform.openai.com/docs/guides/vision/calculating-costs
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// https://github.com/openai/openai-cookbook/blob/05e3f9be4c7a2ae7ecf029a7c32065b024730ebe/examples/How_to_count_tokens_with_tiktoken.ipynb
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func countImageTokens(url string, detail string) (_ int, err error) {
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var fetchSize = true
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var width, height int
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// Reference: https://platform.openai.com/docs/guides/vision/low-or-high-fidelity-image-understanding
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// detail == "auto" is undocumented on how it works, it just said the model will use the auto setting which will look at the image input size and decide if it should use the low or high setting.
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// According to the official guide, "low" disable the high-res model,
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// and only receive low-res 512px x 512px version of the image, indicating
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// that image is treated as low-res when size is smaller than 512px x 512px,
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// then we can assume that image size larger than 512px x 512px is treated
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// as high-res. Then we have the following logic:
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// if detail == "" || detail == "auto" {
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// width, height, err = image.GetImageSize(url)
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// if err != nil {
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// return 0, err
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// }
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// fetchSize = false
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// // not sure if this is correct
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// if width > 512 || height > 512 {
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// detail = "high"
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// } else {
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// detail = "low"
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// }
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// }
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// However, in my test, it seems to be always the same as "high".
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// The following image, which is 125x50, is still treated as high-res, taken
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// 255 tokens in the response of non-stream chat completion api.
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// https://upload.wikimedia.org/wikipedia/commons/1/10/18_Infantry_Division_Messina.jpg
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if detail == "" || detail == "auto" {
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// assume by test, not sure if this is correct
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detail = "high"
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}
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switch detail {
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case "low":
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return lowDetailCost, nil
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case "high":
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if fetchSize {
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width, height, err = image.GetImageSize(url)
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if err != nil {
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return 0, err
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}
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}
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if width > 2048 || height > 2048 { // max(width, height) > 2048
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ratio := float64(2048) / math.Max(float64(width), float64(height))
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width = int(float64(width) * ratio)
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height = int(float64(height) * ratio)
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}
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if width > 768 && height > 768 { // min(width, height) > 768
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ratio := float64(768) / math.Min(float64(width), float64(height))
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width = int(float64(width) * ratio)
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height = int(float64(height) * ratio)
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}
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numSquares := int(math.Ceil(float64(width)/512) * math.Ceil(float64(height)/512))
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result := numSquares*highDetailCostPerTile + additionalCost
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return result, nil
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default:
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return 0, errors.New("invalid detail option")
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}
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}
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func countTokenInput(input any, model string) int {
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switch input.(type) {
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switch v := input.(type) {
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case string:
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return countTokenText(input.(string), model)
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return countTokenText(v, model)
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case []string:
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text := ""
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for _, s := range input.([]string) {
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for _, s := range v {
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text += s
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}
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return countTokenText(text, model)
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