mirror of
https://github.com/songquanpeng/one-api.git
synced 2025-09-29 14:46:38 +08:00
212 lines
8.4 KiB
Go
212 lines
8.4 KiB
Go
package common
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import (
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"encoding/json"
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"strings"
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"time"
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)
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type ModelType struct {
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Ratio float64
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Type int
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}
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var ModelTypes map[string]ModelType
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// ModelRatio
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// https://platform.openai.com/docs/models/model-endpoint-compatibility
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// https://cloud.baidu.com/doc/WENXINWORKSHOP/s/Blfmc9dlf
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// https://openai.com/pricing
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// TODO: when a new api is enabled, check the pricing here
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// 1 === $0.002 / 1K tokens
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// 1 === ￥0.014 / 1k tokens
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var ModelRatio map[string]float64
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func init() {
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ModelTypes = map[string]ModelType{
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"gpt-4": {15, ChannelTypeOpenAI},
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"gpt-4-0314": {15, ChannelTypeOpenAI},
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"gpt-4-0613": {15, ChannelTypeOpenAI},
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"gpt-4-32k": {30, ChannelTypeOpenAI},
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"gpt-4-32k-0314": {30, ChannelTypeOpenAI},
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"gpt-4-32k-0613": {30, ChannelTypeOpenAI},
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"gpt-4-1106-preview": {5, ChannelTypeOpenAI}, // $0.01 / 1K tokens
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"gpt-4-vision-preview": {5, ChannelTypeOpenAI}, // $0.01 / 1K tokens
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"gpt-3.5-turbo": {0.75, ChannelTypeOpenAI}, // $0.0015 / 1K tokens
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"gpt-3.5-turbo-0301": {0.75, ChannelTypeOpenAI},
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"gpt-3.5-turbo-0613": {0.75, ChannelTypeOpenAI},
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"gpt-3.5-turbo-16k": {1.5, ChannelTypeOpenAI}, // $0.003 / 1K tokens
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"gpt-3.5-turbo-16k-0613": {1.5, ChannelTypeOpenAI},
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"gpt-3.5-turbo-instruct": {0.75, ChannelTypeOpenAI}, // $0.0015 / 1K tokens
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"gpt-3.5-turbo-1106": {0.5, ChannelTypeOpenAI}, // $0.001 / 1K tokens
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"davinci-002": {1, ChannelTypeOpenAI}, // $0.002 / 1K tokens
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"babbage-002": {0.2, ChannelTypeOpenAI}, // $0.002 / 1K tokens
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"text-ada-001": {0.2, ChannelTypeOpenAI},
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"text-babbage-001": {0.25, ChannelTypeOpenAI},
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"text-curie-001": {1, ChannelTypeOpenAI},
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"text-davinci-002": {10, ChannelTypeOpenAI},
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"text-davinci-003": {10, ChannelTypeOpenAI},
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"text-davinci-edit-001": {10, ChannelTypeOpenAI},
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"code-davinci-edit-001": {10, ChannelTypeOpenAI},
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"whisper-1": {15, ChannelTypeOpenAI}, // $0.006 / minute -> $0.006 / 150 words -> $0.006 / 200 tokens -> $0.03 / 1k tokens
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"tts-1": {7.5, ChannelTypeOpenAI}, // $0.015 / 1K characters
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"tts-1-1106": {7.5, ChannelTypeOpenAI},
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"tts-1-hd": {15, ChannelTypeOpenAI}, // $0.030 / 1K characters
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"tts-1-hd-1106": {15, ChannelTypeOpenAI},
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"davinci": {10, ChannelTypeOpenAI},
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"curie": {10, ChannelTypeOpenAI},
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"babbage": {10, ChannelTypeOpenAI},
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"ada": {10, ChannelTypeOpenAI},
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"text-embedding-ada-002": {0.05, ChannelTypeOpenAI},
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"text-search-ada-doc-001": {10, ChannelTypeOpenAI},
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"text-moderation-stable": {0.1, ChannelTypeOpenAI},
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"text-moderation-latest": {0.1, ChannelTypeOpenAI},
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"dall-e-2": {8, ChannelTypeOpenAI}, // $0.016 - $0.020 / image
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"dall-e-3": {20, ChannelTypeOpenAI}, // $0.040 - $0.120 / image
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"claude-instant-1": {0.815, ChannelTypeAnthropic}, // $1.63 / 1M tokens
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"claude-2": {5.51, ChannelTypeAnthropic}, // $11.02 / 1M tokens
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"claude-2.0": {5.51, ChannelTypeAnthropic}, // $11.02 / 1M tokens
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"claude-2.1": {5.51, ChannelTypeAnthropic}, // $11.02 / 1M tokens
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"ERNIE-Bot": {0.8572, ChannelTypeBaidu}, // ￥0.012 / 1k tokens
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"ERNIE-Bot-turbo": {0.5715, ChannelTypeBaidu}, // ￥0.008 / 1k tokens
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"ERNIE-Bot-4": {8.572, ChannelTypeBaidu}, // ￥0.12 / 1k tokens
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"Embedding-V1": {0.1429, ChannelTypeBaidu}, // ￥0.002 / 1k tokens
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"PaLM-2": {1, ChannelTypePaLM},
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"gemini-pro": {1, ChannelTypeGemini}, // $0.00025 / 1k characters -> $0.001 / 1k tokens
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"gemini-pro-vision": {1, ChannelTypeGemini}, // $0.00025 / 1k characters -> $0.001 / 1k tokens
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"chatglm_turbo": {0.3572, ChannelTypeZhipu}, // ￥0.005 / 1k tokens
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"chatglm_pro": {0.7143, ChannelTypeZhipu}, // ￥0.01 / 1k tokens
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"chatglm_std": {0.3572, ChannelTypeZhipu}, // ￥0.005 / 1k tokens
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"chatglm_lite": {0.1429, ChannelTypeZhipu}, // ￥0.002 / 1k tokens
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"qwen-turbo": {0.5715, ChannelTypeAli}, // ￥0.008 / 1k tokens // https://help.aliyun.com/zh/dashscope/developer-reference/tongyi-thousand-questions-metering-and-billing
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"qwen-plus": {1.4286, ChannelTypeAli}, // ￥0.02 / 1k tokens
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"qwen-max": {1.4286, ChannelTypeAli}, // ￥0.02 / 1k tokens
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"qwen-max-longcontext": {1.4286, ChannelTypeAli}, // ￥0.02 / 1k tokens
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"qwen-vl-plus": {0.5715, ChannelTypeAli}, // ￥0.008 / 1k tokens
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"text-embedding-v1": {0.05, ChannelTypeAli}, // ￥0.0007 / 1k tokens
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"SparkDesk": {1.2858, ChannelTypeXunfei}, // ￥0.018 / 1k tokens
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"360GPT_S2_V9": {0.8572, ChannelType360}, // ¥0.012 / 1k tokens
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"embedding-bert-512-v1": {0.0715, ChannelType360}, // ¥0.001 / 1k tokens
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"embedding_s1_v1": {0.0715, ChannelType360}, // ¥0.001 / 1k tokens
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"semantic_similarity_s1_v1": {0.0715, ChannelType360}, // ¥0.001 / 1k tokens
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"hunyuan": {7.143, ChannelTypeTencent}, // ¥0.1 / 1k tokens // https://cloud.tencent.com/document/product/1729/97731#e0e6be58-60c8-469f-bdeb-6c264ce3b4d0
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"Baichuan2-Turbo": {0.5715, ChannelTypeBaichuan}, // ¥0.008 / 1k tokens
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"Baichuan2-Turbo-192k": {1.143, ChannelTypeBaichuan}, // ¥0.016 / 1k tokens
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"Baichuan2-53B": {1.4286, ChannelTypeBaichuan}, // ¥0.02 / 1k tokens
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"Baichuan-Text-Embedding": {0.0357, ChannelTypeBaichuan}, // ¥0.0005 / 1k tokens
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}
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ModelRatio = make(map[string]float64)
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for name, modelType := range ModelTypes {
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ModelRatio[name] = modelType.Ratio
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}
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}
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var DalleSizeRatios = map[string]map[string]float64{
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"dall-e-2": {
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"256x256": 1,
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"512x512": 1.125,
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"1024x1024": 1.25,
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},
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"dall-e-3": {
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"1024x1024": 1,
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"1024x1792": 2,
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"1792x1024": 2,
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},
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}
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var DalleGenerationImageAmounts = map[string][2]int{
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"dall-e-2": {1, 10},
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"dall-e-3": {1, 1}, // OpenAI allows n=1 currently.
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}
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var DalleImagePromptLengthLimitations = map[string]int{
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"dall-e-2": 1000,
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"dall-e-3": 4000,
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}
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func ModelRatio2JSONString() string {
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jsonBytes, err := json.Marshal(ModelRatio)
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if err != nil {
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SysError("error marshalling model ratio: " + err.Error())
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}
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return string(jsonBytes)
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}
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func UpdateModelRatioByJSONString(jsonStr string) error {
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ModelRatio = make(map[string]float64)
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return json.Unmarshal([]byte(jsonStr), &ModelRatio)
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}
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func MergeModelRatioByJSONString(jsonStr string) (newJsonStr string, err error) {
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inputModelRatio := make(map[string]float64)
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err = json.Unmarshal([]byte(jsonStr), &inputModelRatio)
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if err != nil {
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return
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}
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isNew := false
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// 与现有的ModelRatio进行比较，如果有新增的模型，需要添加
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for key, value := range ModelRatio {
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if _, ok := inputModelRatio[key]; !ok {
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isNew = true
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inputModelRatio[key] = value
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}
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}
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if !isNew {
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return
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}
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var jsonBytes []byte
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jsonBytes, err = json.Marshal(inputModelRatio)
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if err != nil {
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SysError("error marshalling model ratio: " + err.Error())
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}
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newJsonStr = string(jsonBytes)
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return
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}
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func GetModelRatio(name string) float64 {
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if strings.HasPrefix(name, "qwen-") && strings.HasSuffix(name, "-internet") {
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name = strings.TrimSuffix(name, "-internet")
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}
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ratio, ok := ModelRatio[name]
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if !ok {
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SysError("model ratio not found: " + name)
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return 30
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}
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return ratio
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}
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func GetCompletionRatio(name string) float64 {
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if strings.HasPrefix(name, "gpt-3.5") {
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if strings.HasSuffix(name, "1106") {
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return 2
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}
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if name == "gpt-3.5-turbo" || name == "gpt-3.5-turbo-16k" {
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// TODO: clear this after 2023-12-11
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now := time.Now()
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// https://platform.openai.com/docs/models/continuous-model-upgrades
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// if after 2023-12-11, use 2
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if now.After(time.Date(2023, 12, 11, 0, 0, 0, 0, time.UTC)) {
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return 2
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}
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}
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return 1.333333
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}
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if strings.HasPrefix(name, "gpt-4") {
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if strings.HasSuffix(name, "preview") {
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return 3
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}
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return 2
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}
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if strings.HasPrefix(name, "claude-instant-1") {
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return 3.38
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}
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if strings.HasPrefix(name, "claude-2") {
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return 2.965517
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}
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return 1
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}
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