nova-api/api/helpers/tokens.py

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import time
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
Args:
messages (list): _description_
model (str, optional): _description_. Defaults to 'gpt-3.5-turbo-0613'.
Raises:
NotImplementedError: _description_
Returns:
int: _description_
"""
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try:
encoding = tiktoken.encoding_for_model(model)
except KeyError:
encoding = tiktoken.get_encoding('cl100k_base')
if model in {
'gpt-3.5-turbo-0613',
'gpt-3.5-turbo-16k-0613',
'gpt-4-0314',
'gpt-4-32k-0314',
'gpt-4-0613',
'gpt-4-32k-0613',
}:
tokens_per_message = 3
tokens_per_name = 1
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 'gpt-3.5-turbo' in model:
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return await count_for_messages(messages, model='gpt-3.5-turbo-0613')
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elif 'gpt-4' in model:
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return await 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
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
if __name__ == '__main__':
start = time.perf_counter()
messages = [
{
'role': 'user',
'content': '1+1='
}
]
print(asyncio.run(count_for_messages(messages)))
print(f'Took {(time.perf_counter() - start) * 1000}ms')