[Misc] Refactor tokenizer interface (vllm-project#29693)

Signed-off-by: DarkLight1337 <[email protected]>

Author: DarkLight1337

.buildkite/test-amd.yaml

@@ -316,15 +316,15 @@ steps:
   source_file_dependencies:
   - vllm/
   - tests/engine
-  - tests/tokenization
+  - tests/tokenizers_
   - tests/test_sequence
   - tests/test_config
   - tests/test_logger
   - tests/test_vllm_port
   commands:
   - pytest -v -s engine test_sequence.py test_config.py test_logger.py test_vllm_port.py
   # OOM in the CI unless we run this separately
-  - pytest -v -s tokenization
+  - pytest -v -s tokenizers_
 
 - label: V1 Test e2e + engine # 30min
   timeout_in_minutes: 45

.buildkite/test-pipeline.yaml

@@ -282,15 +282,15 @@ steps:
   source_file_dependencies:
   - vllm/
   - tests/engine
-  - tests/tokenization
+  - tests/tokenizers_
   - tests/test_sequence
   - tests/test_config
   - tests/test_logger
   - tests/test_vllm_port
   commands:
   - pytest -v -s engine test_sequence.py test_config.py test_logger.py test_vllm_port.py
   # OOM in the CI unless we run this separately
-  - pytest -v -s tokenization
+  - pytest -v -s tokenizers_
 
 - label: V1 Test e2e + engine # 30min
   timeout_in_minutes: 45

benchmarks/backend_request_func.py

@@ -620,7 +620,7 @@ def get_tokenizer(
         kwargs["use_fast"] = False
     if tokenizer_mode == "mistral":
         try:
-            from vllm.transformers_utils.tokenizer import MistralTokenizer
+            from vllm.tokenizers import MistralTokenizer
         except ImportError as e:
             raise ImportError(
                 "MistralTokenizer requires vllm package.\n"

docs/features/reasoning_outputs.md

@@ -216,14 +216,13 @@ You can add a new `ReasoningParser` similar to [vllm/reasoning/deepseek_r1_reaso
     # import the required packages
 
     from vllm.reasoning import ReasoningParser, ReasoningParserManager
-    from vllm.entrypoints.openai.protocol import (ChatCompletionRequest,
-                                                DeltaMessage)
+    from vllm.entrypoints.openai.protocol import ChatCompletionRequest, DeltaMessage
 
     # define a reasoning parser and register it to vllm
     # the name list in register_module can be used
     # in --reasoning-parser.
     class ExampleParser(ReasoningParser):
-        def __init__(self, tokenizer: AnyTokenizer):
+        def __init__(self, tokenizer: TokenizerLike):
             super().__init__(tokenizer)
 
         def extract_reasoning_streaming(

docs/features/tool_calling.md

@@ -422,7 +422,7 @@ Here is a summary of a plugin file:
     # in --tool-call-parser. you can define as many
     # tool parsers as you want here.
     class ExampleToolParser(ToolParser):
-        def __init__(self, tokenizer: AnyTokenizer):
+        def __init__(self, tokenizer: TokenizerLike):
             super().__init__(tokenizer)
 
         # adjust request. e.g.: set skip special tokens

tests/entrypoints/openai/test_serving_engine.py

@@ -10,7 +10,7 @@
 from vllm.config import ModelConfig
 from vllm.entrypoints.openai.serving_engine import OpenAIServing
 from vllm.entrypoints.openai.serving_models import OpenAIServingModels
-from vllm.transformers_utils.tokenizers.mistral import MistralTokenizer
+from vllm.tokenizers import MistralTokenizer
 
 
 @pytest.fixture()

tests/entrypoints/openai/tool_parsers/conftest.py

@@ -4,9 +4,9 @@
 import pytest
 from transformers import AutoTokenizer
 
-from vllm.transformers_utils.tokenizer import AnyTokenizer
+from vllm.tokenizers import TokenizerLike
 
 
 @pytest.fixture(scope="function")
-def default_tokenizer() -> AnyTokenizer:
+def default_tokenizer() -> TokenizerLike:
     return AutoTokenizer.from_pretrained("gpt2")

tests/entrypoints/openai/tool_parsers/test_hermes_tool_parser.py

@@ -7,7 +7,7 @@
 
 from vllm.entrypoints.openai.protocol import ChatCompletionRequest
 from vllm.entrypoints.openai.tool_parsers.hermes_tool_parser import Hermes2ProToolParser
-from vllm.transformers_utils.tokenizer import AnyTokenizer
+from vllm.tokenizers import TokenizerLike
 
 from ....utils import RemoteOpenAIServer
 
@@ -270,14 +270,14 @@ async def test_streaming_product_tool_call():
 
 
 @pytest.fixture
-def qwen_tokenizer() -> AnyTokenizer:
+def qwen_tokenizer() -> TokenizerLike:
     from vllm.transformers_utils.tokenizer import get_tokenizer
 
     return get_tokenizer("Qwen/Qwen3-32B")
 
 
 @pytest.fixture
-def hermes_parser(qwen_tokenizer: AnyTokenizer) -> Hermes2ProToolParser:
+def hermes_parser(qwen_tokenizer: TokenizerLike) -> Hermes2ProToolParser:
     return Hermes2ProToolParser(qwen_tokenizer)
 
 
@@ -291,7 +291,7 @@ def any_chat_request() -> ChatCompletionRequest:
 
 
 def test_hermes_parser_streaming_just_forward_text(
-    qwen_tokenizer: AnyTokenizer,
+    qwen_tokenizer: TokenizerLike,
     hermes_parser: Hermes2ProToolParser,
     any_chat_request: ChatCompletionRequest,
 ) -> None:
@@ -323,7 +323,7 @@ def test_hermes_parser_streaming_just_forward_text(
 
 
 def test_hermes_parser_streaming_failure_case_bug_19056(
-    qwen_tokenizer: AnyTokenizer,
+    qwen_tokenizer: TokenizerLike,
     hermes_parser: Hermes2ProToolParser,
     any_chat_request: ChatCompletionRequest,
 ) -> None:
@@ -357,7 +357,7 @@ def test_hermes_parser_streaming_failure_case_bug_19056(
 
 
 def test_hermes_parser_streaming(
-    qwen_tokenizer: AnyTokenizer,
+    qwen_tokenizer: TokenizerLike,
     hermes_parser: Hermes2ProToolParser,
     any_chat_request: ChatCompletionRequest,
 ) -> None:

tests/entrypoints/openai/tool_parsers/test_llama3_json_tool_parser.py

@@ -7,11 +7,11 @@
 
 from vllm.entrypoints.openai.protocol import ExtractedToolCallInformation
 from vllm.entrypoints.openai.tool_parsers.llama_tool_parser import Llama3JsonToolParser
-from vllm.transformers_utils.tokenizer import AnyTokenizer
+from vllm.tokenizers import TokenizerLike
 
 
 @pytest.fixture
-def parser(default_tokenizer: AnyTokenizer):
+def parser(default_tokenizer: TokenizerLike):
     return Llama3JsonToolParser(default_tokenizer)
 
 

tests/entrypoints/openai/tool_parsers/test_llama4_pythonic_tool_parser.py

@@ -11,7 +11,7 @@
 )
 from vllm.entrypoints.openai.protocol import FunctionCall
 from vllm.entrypoints.openai.tool_parsers import ToolParser, ToolParserManager
-from vllm.transformers_utils.tokenizer import AnyTokenizer
+from vllm.tokenizers import TokenizerLike
 
 # Test cases similar to pythonic parser but with Llama4 specific format
 SIMPLE_FUNCTION_OUTPUT = "[get_weather(city='LA', metric='C')]"
@@ -64,7 +64,7 @@
 
 
 @pytest.mark.parametrize("streaming", [True, False])
-def test_no_tool_call(streaming: bool, default_tokenizer: AnyTokenizer):
+def test_no_tool_call(streaming: bool, default_tokenizer: TokenizerLike):
     tool_parser: ToolParser = ToolParserManager.get_tool_parser("llama4_pythonic")(
         default_tokenizer
     )
@@ -208,7 +208,7 @@ def test_tool_call(
     streaming: bool,
     model_output: str,
     expected_tool_calls: list[FunctionCall],
-    default_tokenizer: AnyTokenizer,
+    default_tokenizer: TokenizerLike,
 ):
     tool_parser: ToolParser = ToolParserManager.get_tool_parser("llama4_pythonic")(
         default_tokenizer
@@ -224,7 +224,7 @@ def test_tool_call(
         assert actual.function == expected
 
 
-def test_streaming_tool_call_with_large_steps(default_tokenizer: AnyTokenizer):
+def test_streaming_tool_call_with_large_steps(default_tokenizer: TokenizerLike):
     tool_parser: ToolParser = ToolParserManager.get_tool_parser("llama4_pythonic")(
         default_tokenizer
     )
@@ -246,7 +246,7 @@ def test_streaming_tool_call_with_large_steps(default_tokenizer: AnyTokenizer):
 
 
 @pytest.mark.parametrize("streaming", [False])
-def test_regex_timeout_handling(streaming: bool, default_tokenizer: AnyTokenizer):
+def test_regex_timeout_handling(streaming: bool, default_tokenizer: TokenizerLike):
     """test regex timeout is handled gracefully"""
     tool_parser: ToolParser = ToolParserManager.get_tool_parser("llama4_pythonic")(
         default_tokenizer