58 lines
2.4 KiB
Python
58 lines
2.4 KiB
Python
import tiktoken
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from typing import List, Dict
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def count_message_tokens(messages : List[Dict[str, str]], model : str = "gpt-3.5-turbo-0301") -> int:
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"""
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Returns the number of tokens used by a list of messages.
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Args:
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messages (list): A list of messages, each of which is a dictionary containing the role and content of the message.
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model (str): The name of the model to use for tokenization. Defaults to "gpt-3.5-turbo-0301".
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Returns:
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int: The number of tokens used by the list of messages.
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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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logger.warn("Warning: model not found. Using cl100k_base encoding.")
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encoding = tiktoken.get_encoding("cl100k_base")
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if model == "gpt-3.5-turbo":
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# !Node: gpt-3.5-turbo may change over time. Returning num tokens assuming gpt-3.5-turbo-0301.")
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return count_message_tokens(messages, model="gpt-3.5-turbo-0301")
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elif model == "gpt-4":
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# !Note: gpt-4 may change over time. Returning num tokens assuming gpt-4-0314.")
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return count_message_tokens(messages, model="gpt-4-0314")
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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 model == "gpt-4-0314":
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tokens_per_message = 3
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tokens_per_name = 1
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else:
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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.""")
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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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def count_string_tokens(string: str, model_name: str) -> int:
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"""
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Returns the number of tokens in a text string.
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Args:
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string (str): The text string.
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model_name (str): The name of the encoding to use. (e.g., "gpt-3.5-turbo")
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Returns:
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int: The number of tokens in the text string.
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"""
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encoding = tiktoken.encoding_for_model(model_name)
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num_tokens = len(encoding.encode(string))
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return num_tokens
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