def encoding_name_for_model()

in tiktoken/model.py [0:0]

• 14 lines of code
• 7 McCabe index (conditional complexity)

def encoding_name_for_model(model_name: str) -> str:
    """Returns the name of the encoding used by a model.

    Raises a KeyError if the model name is not recognised.
    """
    encoding_name = None
    if model_name in MODEL_TO_ENCODING:
        encoding_name = MODEL_TO_ENCODING[model_name]
    else:
        # Check if the model matches a known prefix
        # Prefix matching avoids needing library updates for every model version release
        # Note that this can match on non-existent models (e.g., gpt-3.5-turbo-FAKE)
        for model_prefix, model_encoding_name in MODEL_PREFIX_TO_ENCODING.items():
            if model_name.startswith(model_prefix):
                return model_encoding_name

    if encoding_name is None:
        raise KeyError(
            f"Could not automatically map {model_name} to a tokeniser. "
            "Please use `tiktoken.get_encoding` to explicitly get the tokeniser you expect."
        ) from None

    return encoding_name