from nuxt import route, logger, Request
from nuxt.repositorys.validation import fields, use_args
import traceback
import tiktoken

encoding_cache = {}

support_models = set(["kimi-k2-turbo-preview",
                      "gpt-3.5-turbo",
                      "gpt-3.5-turbo-16k",
                      "gpt-4",
                      "gpt-4-32k"])

support_model_prefixes = (
    "gpt-3.5-turbo-",
    "gpt-4-",
    "moonshot-",
    "kimi-",
)


@route("/tokenizer/<str:model_name>", methods=["POST"])
@use_args({
    "role": fields.Str(required=True),
    "content": fields.Str(required=True),
    "name": fields.Str(required=False)
}, location="json")
def get_num_tokens(req: Request, message: dict, model_name: str):
    try:
        return {
            "code": 200,
            "num_tokens": num_tokens_from_messages([message], model=model_name)
        }
    except Exception as e:
        logger.error(traceback.format_exc())
        return {
            "code": 500,
            "msg": "{}".format(e)
        }


def num_tokens_from_messages(messages, model="gpt-3.5-turbo"):
    """Returns the number of tokens used by a list of messages."""
    encoding = None
    if model in encoding_cache:
        encoding = encoding_cache.get(model)
    else:
        try:
            encoding = tiktoken.encoding_for_model(model)
        except KeyError:
            encoding = tiktoken.get_encoding("cl100k_base")
        encoding_cache[model] = encoding
    if model in support_models or model.startswith(support_model_prefixes):
        num_tokens = 0
        for message in messages:
            num_tokens += 4  # every message follows <im_start>{role/name}\n{content}<im_end>\n
            for key, value in message.items():
                num_tokens += len(encoding.encode(value))
                if key == "name":  # if there's a name, the role is omitted
                    num_tokens += -1  # role is always required and always 1 token
        num_tokens += 3  # every reply is primed with <im_start>assistant
        return num_tokens
    else:
        raise NotImplementedError(f"""num_tokens_from_messages() is not presently implemented for model {model}.
See https://github.com/openai/openai-python/blob/main/chatml.md for information on how messages are converted to tokens.""")