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