update openai struct
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@@ -50,9 +50,9 @@ type VisionImageURL struct {
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}
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type ChatCompletionMessage struct {
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Role string `json:"role"`
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Content json.RawMessage `json:"content"`
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Name string `json:"name,omitempty"`
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Role string `json:"role"`
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Content any `json:"content"`
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Name string `json:"name,omitempty"`
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// MultiContent []VisionContent
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}
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@@ -185,27 +185,31 @@ func ChatProxy(c *gin.Context, chatReq *ChatCompletionRequest) {
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var prompt string
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for _, msg := range chatReq.Messages {
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// prompt += "<" + msg.Role + ">: " + msg.Content + "\n"
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var visioncontent []VisionContent
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if err := json.Unmarshal(msg.Content, &visioncontent); err != nil {
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prompt += "<" + msg.Role + ">: " + string(msg.Content) + "\n"
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} else {
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if len(visioncontent) > 0 {
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for _, content := range visioncontent {
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if content.Type == "text" {
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prompt += "<" + msg.Role + ">: " + content.Text + "\n"
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} else if content.Type == "image_url" {
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if strings.HasPrefix(content.ImageURL.URL, "http") {
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fmt.Println("链接:", content.ImageURL.URL)
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} else if strings.HasPrefix(content.ImageURL.URL, "data:image") {
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fmt.Println("base64:", content.ImageURL.URL[:20])
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switch ct := msg.Content.(type) {
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case string:
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prompt += "<" + msg.Role + ">: " + msg.Content.(string) + "\n"
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case []any:
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for _, item := range ct {
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if m, ok := item.(map[string]interface{}); ok {
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if m["type"] == "text" {
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prompt += "<" + msg.Role + ">: " + m["text"].(string) + "\n"
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} else if m["type"] == "image_url" {
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if url, ok := m["image_url"].(map[string]interface{}); ok {
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fmt.Printf(" URL: %v\n", url["url"])
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if strings.HasPrefix(url["url"].(string), "http") {
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fmt.Println("网络图片:", url["url"].(string))
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}
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}
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// todo image tokens
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}
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}
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}
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default:
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c.JSON(http.StatusInternalServerError, gin.H{
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"error": gin.H{
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"message": "Invalid content type",
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},
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})
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return
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}
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if len(chatReq.Tools) > 0 {
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tooljson, _ := json.Marshal(chatReq.Tools)
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@@ -183,6 +183,8 @@ func Cost(model string, promptCount, completionCount int) float64 {
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cost = (0.00035/1000)*float64(prompt) + (0.00053/1000)*float64(completion)
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case "gemini-2.0-flash-exp":
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cost = (0.00035/1000)*float64(prompt) + (0.00053/1000)*float64(completion)
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case "gemini-2.0-flash-thinking-exp-1219":
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cost = (0.00035/1000)*float64(prompt) + (0.00053/1000)*float64(completion)
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case "learnlm-1.5-pro-experimental", " gemini-exp-1114", "gemini-exp-1121", "gemini-exp-1206":
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cost = (0.00035/1000)*float64(prompt) + (0.00053/1000)*float64(completion)
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@@ -4,6 +4,7 @@ import (
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"errors"
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"log"
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"math/rand"
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"os"
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"strings"
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"time"
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@@ -76,6 +77,9 @@ func SelectKeyCache(apitype string) (Key, error) {
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func SelectKeyCacheByModel(model string) (Key, error) {
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var keys []Key
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if os.Getenv("OPENAI_API_KEY") != "" {
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keys = append(keys, Key{ApiType: "openai", Key: os.Getenv("OPENAI_API_KEY")})
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}
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items := KeysCache.Items()
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for _, item := range items {
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if strings.Contains(model, "realtime") {
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