json 数字*3 后输出

import json

# 原始JSON数据（示例中包含了部分数据）
data = {
  "360GPT_S2_V9": 0.8572,
  "BLOOMZ-7B": 0.284,
  "Baichuan2-53B": 1.42,
  "Baichuan2-Turbo": 0.568,
  "Baichuan2-Turbo-192k": 1.136,
  "ChatPro": 7.1,
  "ChatStd": 0.71,
  "ERNIE-3.5-4K-0205": 0.852,
  "ERNIE-3.5-8K": 0.852,
  "ERNIE-3.5-8K-0205": 1.704,
  "ERNIE-3.5-8K-1222": 0.852,
  "ERNIE-4.0-8K": 8.52,
  "ERNIE-Bot-8K": 1.704,
  "ERNIE-Lite-8K-0308": 0.213,
  "ERNIE-Lite-8K-0922": 0.568,
  "ERNIE-Speed-128K": 0.284,
  "ERNIE-Speed-8K": 0.284,
  "ERNIE-Tiny-8K": 0.071,
  "Embedding-V1": 0.142,
  "PaLM-2": 1,
  "SparkDesk": 1.2858,
  "SparkDesk-v1.1": 1.2858,
  "SparkDesk-v2.1": 1.2858,
  "SparkDesk-v3.1": 1.2858,
  "SparkDesk-v3.5": 1.2858,
  "abab5.5-chat": 1.065,
  "abab5.5s-chat": 0.355,
  "abab6-chat": 7.1,
  "abab6.5-chat": 2.13,
  "abab6.5s-chat": 0.71,
  "ada": 10,
  "ali-stable-diffusion-v1.5": 8,
  "ali-stable-diffusion-xl": 8,
  "babbage": 10,
  "babbage-002": 0.2,
  "bge-large-en": 0.142,
  "bge-large-zh": 0.142,
  "chatglm_lite": 0.1429,
  "chatglm_pro": 0.7143,
  "chatglm_std": 0.3572,
  "chatglm_turbo": 0.3572,
  "claude-2.0": 4,
  "claude-2.1": 4,
  "claude-3-haiku-20240307": 0.125,
  "claude-3-opus-20240229": 7.5,
  "claude-3-sonnet-20240229": 1.5,
  "claude-instant-1.2": 0.4,
  "code-davinci-edit-001": 10,
  "cogview-3": 17.75,
  "command": 0.5,
  "command-light": 0.5,
  "command-light-nightly": 0.5,
  "command-nightly": 0.5,
  "command-r": 0.25,
  "command-r-plus": 1.5,
  "curie": 10,
  "dall-e-2": 10,
  "dall-e-3": 20,
  "davinci": 10,
  "davinci-002": 1,
  "deepl-en": 12.5,
  "deepl-ja": 12.5,
  "deepl-zh": 12.5,
  "deepseek-chat": 0.071,
  "deepseek-coder": 0.071,
  "embedding-2": 0.0355,
  "embedding-bert-512-v1": 0.0715,
  "embedding_s1_v1": 0.0715,
  "gemini-1.0-pro-001": 1,
  "gemini-1.0-pro-vision-001": 1,
  "gemini-1.5-pro": 1,
  "gemini-pro": 1,
  "gemini-pro-vision": 1,
  "gemma-7b-it": 0.05,
  "glm-3-turbo": 0.355,
  "glm-4": 7.1,
  "glm-4v": 7.1,
  "gpt-3.5-turbo": 0.25,
  "gpt-3.5-turbo-0125": 0.25,
  "gpt-3.5-turbo-0301": 0.75,
  "gpt-3.5-turbo-0613": 0.75,
  "gpt-3.5-turbo-1106": 0.5,
  "gpt-3.5-turbo-16k": 1.5,
  "gpt-3.5-turbo-16k-0613": 1.5,
  "gpt-3.5-turbo-instruct": 0.75,
  "gpt-4": 15,
  "gpt-4-0125-preview": 5,
  "gpt-4-0314": 15,
  "gpt-4-0613": 15,
  "gpt-4-1106-preview": 5,
  "gpt-4-32k": 30,
  "gpt-4-32k-0314": 30,
  "gpt-4-32k-0613": 30,
  "gpt-4-turbo": 5,
  "gpt-4-turbo-2024-04-09": 5,
  "gpt-4-turbo-preview": 5,
  "gpt-4-vision-preview": 5,
  "gpt-4o": 2.5,
  "gpt-4o-2024-05-13": 2.5,
  "hunyuan": 7.143,
  "llama2-70b-4096": 0.32,
  "llama2-7b-2048": 0.05,
  "llama3-70b-8192": 0.295,
  "llama3-8b-8192": 0.025,
  "mistral-embed": 0.05,
  "mistral-large-latest": 4,
  "mistral-medium-latest": 1.35,
  "mistral-small-latest": 1,
  "mixtral-8x7b-32768": 0.135,
  "moonshot-v1-128k": 4.26,
  "moonshot-v1-32k": 1.704,
  "moonshot-v1-8k": 0.852,
  "open-mistral-7b": 0.125,
  "open-mixtral-8x7b": 0.35,
  "qwen-max": 1.4286,
  "qwen-max-longcontext": 1.4286,
  "qwen-plus": 1.4286,
  "qwen-turbo": 0.5715,
  "semantic_similarity_s1_v1": 0.0715,
  "step-1-200k": 10.65,
  "step-1-32k": 1.704,
  "step-1v-32k": 1.704,
  "tao-8k": 0.142,
  "text-ada-001": 0.2,
  "text-babbage-001": 0.25,
  "text-curie-001": 1,
  "text-davinci-002": 10,
  "text-davinci-003": 10,
  "text-davinci-edit-001": 10,
  "text-embedding-3-large": 0.065,
  "text-embedding-3-small": 0.01,
  "text-embedding-ada-002": 0.05,
  "text-embedding-v1": 0.05,
  "text-moderation-latest": 0.1,
  "text-moderation-stable": 0.1,
  "text-search-ada-doc-001": 10,
  "tts-1": 7.5,
  "tts-1-1106": 7.5,
  "tts-1-hd": 15,
  "tts-1-hd-1106": 15,
  "wanx-v1": 8,
  "whisper-1": 15,
  "yi-34b-chat-0205": 0.1775,
  "yi-34b-chat-200k": 0.852,
  "yi-vl-plus": 0.426
}

# 将所有数值乘以3并保留两位小数
for key in data:
    data[key] = round(data[key] * 3, 2)

# 将字典转换为JSON字符串，并格式化输出
json_data = json.dumps(data, indent=2)

# 输出结果
print(json_data)
aiastia / note

json 数字*3 后输出 #82
