mirror of
https://github.com/songquanpeng/one-api.git
synced 2025-09-22 03:16:38 +08:00
fix:refactor pricing models and enhance completion ratio logic
- Update pricing ratios and calculations for AI models in the billing system. - Introduce new constants and enhance error handling for audio token rates. - Comment out outdated pricing entries and include additional models in calculations.
This commit is contained in:
Laisky.Cai
parent
969fdca9ef
commit
adcf4712e6
@ -272,21 +272,21 @@ var ModelRatio = map[string]float64{
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"deepseek-r1-distill-qwen-1.5b": 0.001 * KiloRmb,
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"deepseek-r1-distill-qwen-7b": 0.0005 * KiloRmb,
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"deepseek-r1-distill-qwen-14b": 0.001 * KiloRmb,
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"deepseek-r1-distill-qwen-32b": 0.002 * KiloRmb,
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"deepseek-r1-distill-llama-8b": 0.0005 * KiloRmb,
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"deepseek-r1-distill-llama-70b": 0.004 * KiloRmb,
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"SparkDesk": 1.2858, // ￥0.018 / 1k tokens
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"SparkDesk-v1.1": 1.2858, // ￥0.018 / 1k tokens
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"SparkDesk-v2.1": 1.2858, // ￥0.018 / 1k tokens
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"SparkDesk-v3.1": 1.2858, // ￥0.018 / 1k tokens
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"SparkDesk-v3.1-128K": 1.2858, // ￥0.018 / 1k tokens
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"SparkDesk-v3.5": 1.2858, // ￥0.018 / 1k tokens
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"SparkDesk-v3.5-32K": 1.2858, // ￥0.018 / 1k tokens
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"SparkDesk-v4.0": 1.2858, // ￥0.018 / 1k tokens
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"360GPT_S2_V9": 0.8572, // ¥0.012 / 1k tokens
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"embedding-bert-512-v1": 0.0715, // ¥0.001 / 1k tokens
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"embedding_s1_v1": 0.0715, // ¥0.001 / 1k tokens
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"semantic_similarity_s1_v1": 0.0715, // ¥0.001 / 1k tokens
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// "deepseek-r1-distill-qwen-32b": 0.002 * KiloRmb,
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"deepseek-r1-distill-llama-8b": 0.0005 * KiloRmb,
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// "deepseek-r1-distill-llama-70b": 0.004 * KiloRmb,
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"SparkDesk": 1.2858, // ￥0.018 / 1k tokens
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"SparkDesk-v1.1": 1.2858, // ￥0.018 / 1k tokens
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"SparkDesk-v2.1": 1.2858, // ￥0.018 / 1k tokens
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"SparkDesk-v3.1": 1.2858, // ￥0.018 / 1k tokens
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"SparkDesk-v3.1-128K": 1.2858, // ￥0.018 / 1k tokens
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"SparkDesk-v3.5": 1.2858, // ￥0.018 / 1k tokens
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"SparkDesk-v3.5-32K": 1.2858, // ￥0.018 / 1k tokens
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"SparkDesk-v4.0": 1.2858, // ￥0.018 / 1k tokens
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"360GPT_S2_V9": 0.8572, // ¥0.012 / 1k tokens
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"embedding-bert-512-v1": 0.0715, // ¥0.001 / 1k tokens
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"embedding_s1_v1": 0.0715, // ¥0.001 / 1k tokens
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"semantic_similarity_s1_v1": 0.0715, // ¥0.001 / 1k tokens
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// https://cloud.tencent.com/document/product/1729/97731#e0e6be58-60c8-469f-bdeb-6c264ce3b4d0
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"hunyuan-turbo": 0.015 * KiloRmb,
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"hunyuan-large": 0.004 * KiloRmb,
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@ -321,22 +321,30 @@ var ModelRatio = map[string]float64{
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"mistral-medium-latest": 2.7 * MilliTokensUsd,
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"mistral-large-latest": 8.0 * MilliTokensUsd,
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"mistral-embed": 0.1 * MilliTokensUsd,
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// https://wow.groq.com/#:~:text=inquiries%C2%A0here.-,Model,-Current%20Speed
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"gemma-7b-it": 0.07 / 1000 * MilliTokensUsd,
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"gemma2-9b-it": 0.20 / 1000 * MilliTokensUsd,
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"llama-3.1-70b-versatile": 0.59 / 1000 * MilliTokensUsd,
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"llama-3.1-8b-instant": 0.05 / 1000 * MilliTokensUsd,
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"llama-3.2-11b-text-preview": 0.05 / 1000 * MilliTokensUsd,
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"llama-3.2-11b-vision-preview": 0.05 / 1000 * MilliTokensUsd,
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"llama-3.2-1b-preview": 0.05 / 1000 * MilliTokensUsd,
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"llama-3.2-3b-preview": 0.05 / 1000 * MilliTokensUsd,
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"llama-3.2-90b-text-preview": 0.59 / 1000 * MilliTokensUsd,
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"llama-guard-3-8b": 0.05 / 1000 * MilliTokensUsd,
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"llama3-70b-8192": 0.59 / 1000 * MilliTokensUsd,
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"llama3-8b-8192": 0.05 / 1000 * MilliTokensUsd,
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"llama3-groq-70b-8192-tool-use-preview": 0.89 / 1000 * MilliTokensUsd,
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"llama3-groq-8b-8192-tool-use-preview": 0.19 / 1000 * MilliTokensUsd,
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"mixtral-8x7b-32768": 0.24 / 1000 * MilliTokensUsd,
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// -------------------------------------
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// https://groq.com/pricing/
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// -------------------------------------
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"gemma2-9b-it": 0.20 * MilliTokensUsd,
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"llama-3.1-8b-instant": 0.05 * MilliTokensUsd,
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"llama-3.2-11b-text-preview": 0.18 * MilliTokensUsd,
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"llama-3.2-11b-vision-preview": 0.18 * MilliTokensUsd,
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"llama-3.2-1b-preview": 0.04 * MilliTokensUsd,
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"llama-3.2-3b-preview": 0.06 * MilliTokensUsd,
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"llama-3.2-90b-text-preview": 0.90 * MilliTokensUsd,
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"llama-3.2-90b-vision-preview": 0.90 * MilliTokensUsd,
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"llama-3.3-70b-versatile": 0.59 * MilliTokensUsd,
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"llama-guard-3-8b": 0.20 * MilliTokensUsd,
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"llama3-70b-8192": 0.59 * MilliTokensUsd,
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"llama3-8b-8192": 0.05 * MilliTokensUsd,
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"llama3-groq-70b-8192-tool-use-preview": 0.59 * MilliTokensUsd,
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"llama3-groq-8b-8192-tool-use-preview": 0.05 * MilliTokensUsd,
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"mixtral-8x7b-32768": 0.24 * MilliTokensUsd,
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"whisper-large-v3": 0.111 * MilliTokensUsd,
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"whisper-large-v3-turbo": 0.04 * MilliTokensUsd,
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"distil-whisper-large-v3-en": 0.02 * MilliTokensUsd,
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"deepseek-r1-distill-qwen-32b": 0.69 * MilliTokensUsd,
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"deepseek-r1-distill-llama-70b-specdec": 0.75 * MilliTokensUsd,
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"deepseek-r1-distill-llama-70b": 0.75 * MilliTokensUsd,
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// https://platform.lingyiwanwu.com/docs#-计费单元
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"yi-34b-chat-0205": 2.5 * MilliRmb,
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"yi-34b-chat-200k": 12.0 * MilliRmb,
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@ -651,15 +659,113 @@ var ModelRatio = map[string]float64{
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"xwin-lm/xwin-lm-70b": 1.875,
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}
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// CompletionRatio is the price ratio between completion tokens and prompt tokens
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var CompletionRatio = map[string]float64{
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// aws llama3
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"llama3-8b-8192(33)": 0.0006 / 0.0003,
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"llama3-70b-8192(33)": 0.0035 / 0.00265,
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// whisper
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"whisper-1": 0, // only count input tokens
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"whisper-1": 0, // only count input tokens
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"whisper-large-v3": 0, // only count input tokens
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"whisper-large-v3-turbo": 0, // only count input tokens
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"distil-whisper-large-v3-en": 0, // only count input tokens
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// deepseek
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"deepseek-chat": 0.28 / 0.14,
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"deepseek-chat": 1.1 / 0.27,
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"deepseek-reasoner": 2.19 / 0.55,
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// openrouter
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"deepseek/deepseek-chat": 1,
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"deepseek/deepseek-r1": 1,
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// -------------------------------------
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// groq
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// -------------------------------------
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"llama-3.3-70b-versatile": 0.79 / 0.59,
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"llama-3.1-8b-instant": 0.08 / 0.05,
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"llama3-70b-8192": 0.79 / 0.59,
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"llama3-8b-8192": 0.08 / 0.05,
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"gemma2-9b-it": 1.0,
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"llama-3.2-11b-text-preview": 1.0,
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"llama-3.2-11b-vision-preview": 1.0,
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"llama-3.2-1b-preview": 1.0,
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"llama-3.2-3b-preview": 1.0,
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"llama-3.2-90b-text-preview": 1.0,
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"llama-3.2-90b-vision-preview": 1.0,
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"llama-guard-3-8b": 1.0,
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"llama3-groq-70b-8192-tool-use-preview": 0.79 / 0.59,
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"llama3-groq-8b-8192-tool-use-preview": 0.08 / 0.05,
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"mixtral-8x7b-32768": 1.0,
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"deepseek-r1-distill-qwen-32b": 1,
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"deepseek-r1-distill-llama-70b-specdec": 0.99 / 0.75,
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"deepseek-r1-distill-llama-70b": 0.99 / 0.75,
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}
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// AudioRatio represents the price ratio between audio tokens and text tokens
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var AudioRatio = map[string]float64{
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"gpt-4o-audio-preview": 16,
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"gpt-4o-audio-preview-2024-12-17": 16,
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"gpt-4o-audio-preview-2024-10-01": 40,
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"gpt-4o-mini-audio-preview": 10 / 0.15,
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"gpt-4o-mini-audio-preview-2024-12-17": 10 / 0.15,
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}
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// GetAudioPromptRatio returns the audio prompt ratio for the given model.
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func GetAudioPromptRatio(actualModelName string) float64 {
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var v float64
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if ratio, ok := AudioRatio[actualModelName]; ok {
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v = ratio
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} else {
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v = 16
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}
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return v
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}
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// AudioCompletionRatio is the completion ratio for audio models.
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var AudioCompletionRatio = map[string]float64{
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"whisper-1": 0,
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"gpt-4o-audio-preview": 2,
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"gpt-4o-audio-preview-2024-12-17": 2,
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"gpt-4o-audio-preview-2024-10-01": 2,
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"gpt-4o-mini-audio-preview": 2,
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"gpt-4o-mini-audio-preview-2024-12-17": 2,
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}
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// GetAudioCompletionRatio returns the completion ratio for audio models.
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func GetAudioCompletionRatio(actualModelName string) float64 {
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var v float64
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if ratio, ok := AudioCompletionRatio[actualModelName]; ok {
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v = ratio
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} else {
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v = 2
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}
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return v
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}
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// AudioTokensPerSecond is the number of audio tokens per second for each model.
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var AudioPromptTokensPerSecond = map[string]float64{
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// Whisper API price is $0.0001/sec. One-api's historical ratio is 15,
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// corresponding to $0.03/kilo_tokens.
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// After conversion, tokens per second should be 0.0001/0.03*1000 = 3.3333.
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"whisper-1": 0.0001 / 0.03 * 1000,
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// gpt-4o-audio series processes 10 tokens per second
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"gpt-4o-audio-preview": 10,
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"gpt-4o-audio-preview-2024-12-17": 10,
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"gpt-4o-audio-preview-2024-10-01": 10,
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"gpt-4o-mini-audio-preview": 10,
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"gpt-4o-mini-audio-preview-2024-12-17": 10,
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}
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// GetAudioPromptTokensPerSecond returns the number of audio tokens per second
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// for the given model.
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func GetAudioPromptTokensPerSecond(actualModelName string) float64 {
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var v float64
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if tokensPerSecond, ok := AudioPromptTokensPerSecond[actualModelName]; ok {
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v = tokensPerSecond
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} else {
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v = 10
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}
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return v
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}
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var (
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@ -722,23 +828,26 @@ func GetModelRatio(name string, channelType int) float64 {
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if strings.HasPrefix(name, "command-") && strings.HasSuffix(name, "-internet") {
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name = strings.TrimSuffix(name, "-internet")
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}
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model := fmt.Sprintf("%s(%d)", name, channelType)
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if ratio, ok := ModelRatio[model]; ok {
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return ratio
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}
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if ratio, ok := DefaultModelRatio[model]; ok {
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return ratio
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}
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if ratio, ok := ModelRatio[name]; ok {
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return ratio
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}
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if ratio, ok := DefaultModelRatio[name]; ok {
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return ratio
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for _, targetName := range []string{model, name} {
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for _, ratioMap := range []map[string]float64{
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ModelRatio,
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DefaultModelRatio,
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AudioRatio,
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} {
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if ratio, ok := ratioMap[targetName]; ok {
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return ratio
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}
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}
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}
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logger.SysError("model ratio not found: " + name)
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return 30
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}
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// CompletionRatio2JSONString returns the CompletionRatio map as a JSON string.
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func CompletionRatio2JSONString() string {
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jsonBytes, err := json.Marshal(CompletionRatio)
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if err != nil {
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@ -747,59 +856,79 @@ func CompletionRatio2JSONString() string {
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return string(jsonBytes)
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}
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// completionRatioLock is a mutex for synchronizing access to the CompletionRatio map.
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var completionRatioLock sync.RWMutex
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// UpdateCompletionRatioByJSONString updates the CompletionRatio map with the given JSON string.
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func UpdateCompletionRatioByJSONString(jsonStr string) error {
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completionRatioLock.Lock()
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defer completionRatioLock.Unlock()
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CompletionRatio = make(map[string]float64)
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return json.Unmarshal([]byte(jsonStr), &CompletionRatio)
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}
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// GetCompletionRatio returns the completion ratio for the given model name and channel type.
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func GetCompletionRatio(name string, channelType int) float64 {
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completionRatioLock.RLock()
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defer completionRatioLock.RUnlock()
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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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model := fmt.Sprintf("%s(%d)", name, channelType)
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if ratio, ok := CompletionRatio[model]; ok {
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return ratio
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name = strings.TrimPrefix(name, "openai/")
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for _, targetName := range []string{model, name} {
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for _, ratioMap := range []map[string]float64{
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CompletionRatio,
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DefaultCompletionRatio,
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AudioCompletionRatio,
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} {
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// first try the model name
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if ratio, ok := ratioMap[targetName]; ok {
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return ratio
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}
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// then try the model name without some special prefix
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normalizedTargetName := strings.TrimPrefix(targetName, "openai/")
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if ratio, ok := ratioMap[normalizedTargetName]; ok {
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return ratio
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}
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}
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}
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if ratio, ok := DefaultCompletionRatio[model]; ok {
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return ratio
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}
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if ratio, ok := CompletionRatio[name]; ok {
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return ratio
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}
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if ratio, ok := DefaultCompletionRatio[name]; ok {
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return ratio
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}
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if strings.HasPrefix(name, "gpt-3.5") {
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if name == "gpt-3.5-turbo" || strings.HasSuffix(name, "0125") {
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// openai
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switch {
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case strings.HasPrefix(name, "gpt-3.5"):
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switch {
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case name == "gpt-3.5-turbo" || strings.HasSuffix(name, "0125"):
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// https://openai.com/blog/new-embedding-models-and-api-updates
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// Updated GPT-3.5 Turbo model and lower pricing
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return 3
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}
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if strings.HasSuffix(name, "1106") {
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case strings.HasSuffix(name, "1106"):
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return 2
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default:
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return 4.0 / 3.0
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}
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return 4.0 / 3.0
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}
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if strings.HasPrefix(name, "gpt-4") {
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if strings.HasPrefix(name, "gpt-4o") {
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case name == "chatgpt-4o-latest":
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return 3
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case strings.HasPrefix(name, "gpt-4"):
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switch {
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case strings.HasPrefix(name, "gpt-4o"):
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if name == "gpt-4o-2024-05-13" {
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return 3
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}
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return 4
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}
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if strings.HasPrefix(name, "gpt-4-turbo") ||
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strings.HasSuffix(name, "preview") {
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case strings.HasPrefix(name, "gpt-4-"):
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return 3
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default:
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return 2
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}
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return 2
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}
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// including o1, o1-preview, o1-mini
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if strings.HasPrefix(name, "o1") {
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// including o1/o1-preview/o1-mini
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case strings.HasPrefix(name, "o1") ||
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strings.HasPrefix(name, "o3"):
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return 4
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}
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if name == "chatgpt-4o-latest" {
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return 3
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}
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if strings.HasPrefix(name, "claude-3") {
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return 5
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}
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@ -810,10 +939,7 @@ func GetCompletionRatio(name string, channelType int) float64 {
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return 3
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}
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if strings.HasPrefix(name, "gemini-") {
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return 3
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}
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if strings.HasPrefix(name, "deepseek-") {
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return 2
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return 4
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}
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switch name {
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@ -861,5 +987,6 @@ func GetCompletionRatio(name string, channelType int) float64 {
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return 1.000 / 0.300 // ≈3.333333
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}
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logger.SysWarn(fmt.Sprintf("completion ratio not found for model: %s (channel type: %d), using default value 1", name, channelType))
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return 1
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}
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