[Mistral common] Ensure all functions are imported from the top & only use public methods (#31138)

Signed-off-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Julien Denize <40604584+juliendenize@users.noreply.github.com>
Co-authored-by: Cyrus Leung <tlleungac@connect.ust.hk>

requirements/common.txt

@@ -31,7 +31,7 @@ partial-json-parser # used for parsing partial JSON outputs
 pyzmq >= 25.0.0
 msgspec
 gguf >= 0.17.0
-mistral_common[image] >= 1.8.5
+mistral_common[image] >= 1.8.8
 opencv-python-headless >= 4.11.0    # required for video IO
 pyyaml
 six>=1.16.0; python_version > '3.11' # transitive dependency of pandas that needs to be the latest version for python 3.12

requirements/nightly_torch_test.txt

@@ -23,7 +23,7 @@ jiwer # required for audio tests
 timm # required for internvl test
 transformers_stream_generator # required for qwen-vl test
 matplotlib # required for qwen-vl test
-mistral_common[image,audio] >= 1.8.5 # required for voxtral test
+mistral_common[image,audio] >= 1.8.8 # required for voxtral test
 num2words # required for smolvlm test
 opencv-python-headless >= 4.11.0 # required for video test
 datamodel_code_generator # required for minicpm3 test

requirements/test.in

@@ -29,7 +29,7 @@ torchaudio==2.9.1
 torchvision==0.24.1
 transformers_stream_generator # required for qwen-vl test
 matplotlib # required for qwen-vl test
-mistral_common[image,audio] >= 1.8.5 # required for voxtral test
+mistral_common[image,audio] >= 1.8.8 # required for voxtral test
 num2words # required for smolvlm test
 open_clip_torch==2.32.0 # Required for nemotron_vl test
 opencv-python-headless >= 4.11.0 # required for video test

requirements/test.txt

@@ -482,7 +482,7 @@ mbstrdecoder==1.1.3
     #   typepy
 mdurl==0.1.2
     # via markdown-it-py
-mistral-common==1.8.5
+mistral-common==1.8.8
     # via -r requirements/test.in
 mlflow==2.22.0
     # via terratorch

vllm/tokenizers/mistral.py

@@ -3,6 +3,21 @@
 from pathlib import Path
 from typing import TYPE_CHECKING, Any, cast
 
+from mistral_common.protocol.instruct.request import (
+    ChatCompletionRequest as MistralChatCompletionRequest,
+)
+from mistral_common.protocol.instruct.tool_calls import Function, Tool
+from mistral_common.protocol.instruct.validator import ValidationMode
+from mistral_common.tokens.tokenizers.base import (
+    SpecialTokenPolicy,
+    SpecialTokens,
+)
+from mistral_common.tokens.tokenizers.instruct import InstructTokenizerV13
+from mistral_common.tokens.tokenizers.sentencepiece import (
+    SentencePieceTokenizer,
+)
+from mistral_common.tokens.tokenizers.tekken import Tekkenizer
+
 from vllm.entrypoints.chat_utils import ChatCompletionMessageParam
 from vllm.entrypoints.openai.protocol import ChatCompletionRequest
 from vllm.logger import init_logger
@@ -10,10 +25,6 @@ from vllm.logger import init_logger
 from .protocol import TokenizerLike
 
 if TYPE_CHECKING:
-    from mistral_common.protocol.instruct.request import (
-        ChatCompletionRequest as MistralChatCompletionRequest,
-    )
-    from mistral_common.tokens.tokenizers.tekken import Tekkenizer
     from transformers import BatchEncoding
 
     try:
@@ -101,8 +112,6 @@ def _prepare_apply_chat_template_tools_and_messages(
     continue_final_message: bool = False,
     add_generation_prompt: bool = False,
 ) -> tuple[list["ChatCompletionMessageParam"], list[dict[str, Any]] | None]:
-    from mistral_common.protocol.instruct.tool_calls import Function, Tool
-
     if add_generation_prompt and continue_final_message:
         raise ValueError(
             "Cannot set both `add_generation_prompt` and "
@@ -181,8 +190,6 @@ def validate_request_params(request: "ChatCompletionRequest"):
 
 
 def _tekken_token_to_id(tokenizer: "Tekkenizer", t: str | bytes) -> int:
-    from mistral_common.tokens.tokenizers.tekken import Tekkenizer
-
     assert isinstance(tokenizer, Tekkenizer), type(tokenizer)
 
     t_bytes = t.encode("utf-8") if not isinstance(t, bytes) else t
@@ -210,8 +217,6 @@ class MistralTokenizer(TokenizerLike):
         download_dir: str | None = None,
         **kwargs,
     ) -> "MistralTokenizer":
-        from mistral_common.protocol.instruct.validator import ValidationMode
-
         try:
             # Transformers v5
             from transformers.tokenization_mistral_common import MistralCommonBackend
@@ -235,12 +240,6 @@ class MistralTokenizer(TokenizerLike):
     def __init__(self, tokenizer: "MistralCommonBackend") -> None:
         super().__init__()
 
-        from mistral_common.protocol.instruct.validator import ValidationMode
-        from mistral_common.tokens.tokenizers.sentencepiece import (
-            SentencePieceTokenizer,
-        )
-        from mistral_common.tokens.tokenizers.tekken import Tekkenizer
-
         self.transformers_tokenizer = tokenizer
         self.mistral = tokenizer.tokenizer
         self.instruct = self.mistral.instruct_tokenizer
@@ -270,37 +269,20 @@ class MistralTokenizer(TokenizerLike):
         # Sort the dict for convenience
         self._vocab_dict = dict(sorted(self._vocab_dict.items(), key=lambda x: x[1]))
 
+        # Vocab sorted by token id.
+        self._vocab = self.tokenizer.vocab()
+        self._max_token_id = self.vocab_size - 1
+
         # Cache special tokens for faster access.
         self._special_token_ids = self._get_special_token_ids()
         self._special_token_ids_set = set(self._special_token_ids)
         self._special_tokens = self._get_special_tokens(self._special_token_ids)
         self._special_tokens_set = set(self._special_tokens)
 
-        # Vocab sorted by token id.
-        self._vocab = self.tokenizer._vocab
-        self._max_token_id = self.vocab_size - 1
-
     def _get_special_token_ids(self) -> list[int]:
-        from mistral_common.tokens.tokenizers.sentencepiece import (
-            SentencePieceTokenizer,
-        )
-        from mistral_common.tokens.tokenizers.tekken import Tekkenizer
-
-        if self.is_tekken:
-            assert isinstance(self.tokenizer, Tekkenizer), type(self.tokenizer)
-            special_ids = {t["rank"] for t in self.tokenizer._all_special_tokens}
-        elif self.is_spm:
-            assert isinstance(self.tokenizer, SentencePieceTokenizer), type(
-                self.tokenizer
-            )
-            special_ids = self.tokenizer._control_tokens
-        else:
-            raise ValueError(f"Unknown tokenizer type: {type(self.tokenizer)}")
-        return sorted(special_ids)
+        return [i for i in range(len(self._vocab)) if self.tokenizer.is_special(i)]
 
     def _get_special_tokens(self, all_special_ids: list[int]) -> list[str]:
-        from mistral_common.tokens.tokenizers.base import SpecialTokenPolicy
-
         return [
             self.tokenizer.decode([i], special_token_policy=SpecialTokenPolicy.KEEP)
             for i in all_special_ids
@@ -460,15 +442,6 @@ class MistralTokenizer(TokenizerLike):
         )
 
     def convert_tokens_to_string(self, tokens: list[str]) -> str:
-        from mistral_common.tokens.tokenizers.base import (
-            SpecialTokenPolicy,
-            SpecialTokens,
-        )
-        from mistral_common.tokens.tokenizers.sentencepiece import (
-            SentencePieceTokenizer,
-        )
-        from mistral_common.tokens.tokenizers.tekken import Tekkenizer
-
         to_decode_special_tokens = {SpecialTokens.tool_calls}
         if self.is_tekken:
             assert isinstance(self.tokenizer, Tekkenizer), type(self.tokenizer)
@@ -523,12 +496,6 @@ class MistralTokenizer(TokenizerLike):
         ids: list[int],
         skip_special_tokens: bool = False,
     ) -> list[str]:
-        from mistral_common.tokens.tokenizers.base import (
-            SpecialTokenPolicy,
-            SpecialTokens,
-        )
-        from mistral_common.tokens.tokenizers.instruct import InstructTokenizerV13
-
         if not skip_special_tokens:
             return [self.tokenizer.id_to_piece(token_id) for token_id in ids]