Files
wehub-resource-sync 6b7e6b44f1
Python Build and Type Check / python-ci (ubuntu-latest, 3.11) (push) Has been cancelled
Python Build and Type Check / python-ci (ubuntu-latest, 3.13) (push) Has been cancelled
Python Build and Type Check / python-ci (windows-latest, 3.11) (push) Has been cancelled
Python Build and Type Check / python-ci (windows-latest, 3.13) (push) Has been cancelled
Python Integration Tests / python-ci (ubuntu-latest, 3.13) (push) Has been cancelled
Python Integration Tests / python-ci (windows-latest, 3.13) (push) Has been cancelled
Python Notebook Tests / python-ci (ubuntu-latest, 3.13) (push) Has been cancelled
Python Notebook Tests / python-ci (windows-latest, 3.13) (push) Has been cancelled
Python Smoke Tests / python-ci (ubuntu-latest, 3.13) (push) Has been cancelled
Python Smoke Tests / python-ci (windows-latest, 3.13) (push) Has been cancelled
Python Unit Tests / python-ci (ubuntu-latest, 3.13) (push) Has been cancelled
Python Unit Tests / python-ci (windows-latest, 3.13) (push) Has been cancelled
gh-pages / build (push) Has been cancelled
Python Publish (pypi) / Upload release to PyPI (push) Has been cancelled
Spellcheck / spellcheck (push) Has been cancelled
chore: import upstream snapshot with attribution
2026-07-13 12:37:31 +08:00

55 lines
1.3 KiB
Python

# Copyright (c) 2024 Microsoft Corporation.
# Licensed under the MIT License
"""LiteLLM Tokenizer."""
from typing import Any
from litellm import decode, encode # type: ignore
from graphrag_llm.tokenizer.tokenizer import Tokenizer
class LiteLLMTokenizer(Tokenizer):
"""LiteLLM Tokenizer."""
_model_id: str
def __init__(self, *, model_id: str, **kwargs: Any) -> None:
"""Initialize the LiteLLM Tokenizer.
Args
----
model_id: str
The LiteLLM model ID, e.g., "openai/gpt-4o".
"""
self._model_id = model_id
def encode(self, text: str) -> list[int]:
"""Encode the given text into a list of tokens.
Args
----
text: str
The input text to encode.
Returns
-------
list[int]: A list of tokens representing the encoded text.
"""
return encode(model=self._model_id, text=text)
def decode(self, tokens: list[int]) -> str:
"""Decode a list of tokens back into a string.
Args
----
tokens: list[int]
A list of tokens to decode.
Returns
-------
str: The decoded string from the list of tokens.
"""
return decode(model=self._model_id, tokens=tokens)