Sync from v0.13

vllm/tokenizers/protocol.py

@@ -0,0 +1,114 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+from pathlib import Path
+from typing import TYPE_CHECKING, Any, Protocol
+
+if TYPE_CHECKING:
+    from transformers import BatchEncoding
+
+    from vllm.entrypoints.chat_utils import ChatCompletionMessageParam
+
+
+class TokenizerLike(Protocol):
+    @classmethod
+    def from_pretrained(
+        cls,
+        path_or_repo_id: str | Path,
+        *args,
+        trust_remote_code: bool = False,
+        revision: str | None = None,
+        download_dir: str | None = None,
+        **kwargs,
+    ) -> "TokenizerLike":
+        raise NotImplementedError
+
+    def num_special_tokens_to_add(self) -> int:
+        raise NotImplementedError
+
+    @property
+    def all_special_tokens(self) -> list[str]:
+        raise NotImplementedError
+
+    @property
+    def all_special_ids(self) -> list[int]:
+        raise NotImplementedError
+
+    @property
+    def bos_token_id(self) -> int:
+        raise NotImplementedError
+
+    @property
+    def eos_token_id(self) -> int:
+        raise NotImplementedError
+
+    @property
+    def pad_token_id(self) -> int:
+        raise NotImplementedError
+
+    @property
+    def is_fast(self) -> bool:
+        raise NotImplementedError
+
+    @property
+    def vocab_size(self) -> int:
+        raise NotImplementedError
+
+    @property
+    def max_token_id(self) -> int:
+        raise NotImplementedError
+
+    @property
+    def truncation_side(self) -> str:
+        raise NotImplementedError
+
+    def __hash__(self) -> int:
+        return hash(id(self))
+
+    def __len__(self) -> int:
+        return self.vocab_size
+
+    def __call__(
+        self,
+        text: str | list[str],
+        text_pair: str | None = None,
+        add_special_tokens: bool = True,
+        truncation: bool = False,
+        max_length: int | None = None,
+    ) -> "BatchEncoding":
+        raise NotImplementedError
+
+    def get_vocab(self) -> dict[str, int]:
+        raise NotImplementedError
+
+    def get_added_vocab(self) -> dict[str, int]:
+        raise NotImplementedError
+
+    def encode(
+        self,
+        text: str,
+        truncation: bool | None = None,
+        max_length: int | None = None,
+        add_special_tokens: bool = True,
+    ) -> list[int]:
+        raise NotImplementedError
+
+    def apply_chat_template(
+        self,
+        messages: list["ChatCompletionMessageParam"],
+        tools: list[dict[str, Any]] | None = None,
+        **kwargs,
+    ) -> str | list[int]:
+        raise NotImplementedError
+
+    def convert_tokens_to_string(self, tokens: list[str]) -> str:
+        raise NotImplementedError
+
+    def decode(self, ids: list[int] | int, skip_special_tokens: bool = False) -> str:
+        raise NotImplementedError
+
+    def convert_ids_to_tokens(
+        self,
+        ids: list[int],
+        skip_special_tokens: bool = False,
+    ) -> list[str]:
+        raise NotImplementedError