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74 lines
2.1 KiB
Python
74 lines
2.1 KiB
Python
import time
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import asyncio
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import tiktoken
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async def count_for_messages(messages: list, model: str='gpt-3.5-turbo-0613') -> int:
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"""Return the number of tokens used by a list of messages
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Args:
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messages (list): _description_
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model (str, optional): _description_. Defaults to 'gpt-3.5-turbo-0613'.
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Raises:
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NotImplementedError: _description_
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Returns:
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int: _description_
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"""
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try:
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encoding = tiktoken.encoding_for_model(model)
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except KeyError:
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encoding = tiktoken.get_encoding('cl100k_base')
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if model in {
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'gpt-3.5-turbo-0613',
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'gpt-3.5-turbo-16k-0613',
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'gpt-4-0314',
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'gpt-4-32k-0314',
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'gpt-4-0613',
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'gpt-4-32k-0613',
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}:
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tokens_per_message = 3
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tokens_per_name = 1
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elif model == 'gpt-3.5-turbo-0301':
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tokens_per_message = 4 # every message follows <|start|>{role/name}\n{content}<|end|>\n
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tokens_per_name = -1 # if there's a name, the role is omitted
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elif 'gpt-3.5-turbo' in model:
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return count_for_messages(messages, model='gpt-3.5-turbo-0613')
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elif 'gpt-4' in model:
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return count_for_messages(messages, model='gpt-4-0613')
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else:
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raise NotImplementedError(f"""count_for_messages() is not implemented for model {model}.
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See https://github.com/openai/openai-python/blob/main/chatml.md
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for information on how messages are converted to tokens.""")
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num_tokens = 0
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for message in messages:
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num_tokens += tokens_per_message
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for key, value in message.items():
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num_tokens += len(encoding.encode(value))
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if key == 'name':
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num_tokens += tokens_per_name
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num_tokens += 3 # every reply is primed with <|start|>assistant<|message|>
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return num_tokens
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if __name__ == '__main__':
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start = time.perf_counter()
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messages = [
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{
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'role': 'user',
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'content': '1+1='
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}
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]
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print(asyncio.run(count_for_messages(messages)))
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print(f'Took {(time.perf_counter() - start) * 1000}ms')
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