テキストファイルからChatGPTのトークン数を見積もるPythonコード

API用のトークン数算出方法を使ってテキストファイルのトークン数を得るコードを作成したのでメモとして残す

公式ドキュメント

注意

• 利用するモデルがあっているかちゃんと確認する

前提

$pip install --upgrade tiktoken

Pythonコード

get_openai_tokens.py

import tiktoken

filelist = [
  './sample.txt',
]

# 公式よりコピー
def num_tokens_from_messages(messages, model="gpt-3.5-turbo-0301"):
    """Returns the number of tokens used by a list of messages."""
    try:
        encoding = tiktoken.encoding_for_model(model)
    except KeyError:
        print("Warning: model not found. Using cl100k_base encoding.")
        encoding = tiktoken.get_encoding("cl100k_base")
    if model == "gpt-3.5-turbo":
        print("Warning: gpt-3.5-turbo may change over time. Returning num tokens assuming gpt-3.5-turbo-0301.")
        return num_tokens_from_messages(messages, model="gpt-3.5-turbo-0301")
    elif model == "gpt-4":
        print("Warning: gpt-4 may change over time. Returning num tokens assuming gpt-4-0314.")
        return num_tokens_from_messages(messages, model="gpt-4-0314")
    elif model == "gpt-3.5-turbo-0301":
        tokens_per_message = 4  # every message follows <|start|>{role/name}\n{content}<|end|>\n
        tokens_per_name = -1  # if there's a name, the role is omitted
    elif model == "gpt-4-0314":
        tokens_per_message = 3
        tokens_per_name = 1
    else:
        raise NotImplementedError(f"""num_tokens_from_messages() is not implemented for model {model}. See https://github.com/openai/openai-python/blob/main/chatml.md for information on how messages are converted to tokens.""")
    num_tokens = 0
    for message in messages:
        num_tokens += tokens_per_message
        for key, value in message.items():
            num_tokens += len(encoding.encode(value))
            if key == "name":
                num_tokens += tokens_per_name
    num_tokens += 3  # every reply is primed with <|start|>assistant<|message|>
    return num_tokens

for filename in filelist:
  f = open(filename, 'r')
  data = f.read()
  f.close()
  tokens_count = num_tokens_from_messages([{
    "role": "system",
    "name": "example_user",
    "content": data,
  }])
  print(filename + "\t" + str(tokens_count))