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| """Functions for counting the number of tokens in a message or string.""" | |
| from __future__ import annotations | |
| import tiktoken | |
| from autogpt.logs import logger | |
| def count_message_tokens( | |
| messages: list[dict[str, str]], model: str = "gpt-3.5-turbo-0301" | |
| ) -> int: | |
| """ | |
| Returns the number of tokens used by a list of messages. | |
| Args: | |
| messages (list): A list of messages, each of which is a dictionary | |
| containing the role and content of the message. | |
| model (str): The name of the model to use for tokenization. | |
| Defaults to "gpt-3.5-turbo-0301". | |
| Returns: | |
| int: The number of tokens used by the list of messages. | |
| """ | |
| try: | |
| encoding = tiktoken.encoding_for_model(model) | |
| except KeyError: | |
| logger.warn("Warning: model not found. Using cl100k_base encoding.") | |
| encoding = tiktoken.get_encoding("cl100k_base") | |
| if model == "gpt-3.5-turbo": | |
| # !Note: gpt-3.5-turbo may change over time. | |
| # Returning num tokens assuming gpt-3.5-turbo-0301.") | |
| return count_message_tokens(messages, model="gpt-3.5-turbo-0301") | |
| elif model == "gpt-4": | |
| # !Note: gpt-4 may change over time. Returning num tokens assuming gpt-4-0314.") | |
| return count_message_tokens(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}.\n" | |
| " 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 | |
| def count_string_tokens(string: str, model_name: str) -> int: | |
| """ | |
| Returns the number of tokens in a text string. | |
| Args: | |
| string (str): The text string. | |
| model_name (str): The name of the encoding to use. (e.g., "gpt-3.5-turbo") | |
| Returns: | |
| int: The number of tokens in the text string. | |
| """ | |
| encoding = tiktoken.encoding_for_model(model_name) | |
| return len(encoding.encode(string)) | |