[RL][BugFix] Fix missing tokenizer error for token-in-token-out (#23904)

Signed-off-by: 22quinn <33176974+22quinn@users.noreply.github.com>
Co-authored-by: Cyrus Leung <cyrus.tl.leung@gmail.com>

tests/entrypoints/openai/test_token_in_token_out.py

+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+import os
+import tempfile
+
+import pytest
+
+from vllm.model_executor.model_loader.weight_utils import (
+    download_weights_from_hf)
+from vllm.transformers_utils.tokenizer import get_tokenizer
+
+from ...utils import RemoteOpenAIServer
+
+MODEL_NAME = "Qwen/Qwen3-0.6B"
+MODEL_PATH = os.path.join(tempfile.gettempdir(), "qwen3_06b")
+
+
+@pytest.fixture(scope="module")
+def server():
+    global MODEL_PATH
+    MODEL_PATH = download_weights_from_hf(
+        MODEL_NAME,
+        allow_patterns=["*"],
+        cache_dir=MODEL_PATH,
+        ignore_patterns=["tokenizer*", "vocab*", "*.safetensors"])
+    args = [
+        "--max-model-len",
+        "2048",
+        "--max-num-seqs",
+        "128",
+        "--enforce-eager",
+        "--skip-tokenizer-init",
+        "--load-format",
+        "dummy",
+    ]
+    with RemoteOpenAIServer(MODEL_PATH, args) as remote_server:
+        yield remote_server
+
+
+@pytest.mark.asyncio
+async def test_token_in_token_out_and_logprobs(server):
+    """
+    Test token-in-token-out and token_ids align with prompt_logprobs
+    & logprobs when return_tokens_as_token_ids is enabled.
+    """
+    tokenizer = get_tokenizer(tokenizer_name=MODEL_NAME)
+    text = "Hello, world! How are you today?"
+    token_ids = tokenizer.encode(text)
+    async with server.get_async_client() as client:
+        # Test with both return_token_ids and return_tokens_as_token_ids enabled
+        completion = await client.completions.create(
+            model=MODEL_PATH,
+            prompt=token_ids,
+            max_tokens=20,
+            temperature=0,
+            echo=True,
+            extra_body={
+                "return_token_ids": True,
+            },
+        )
+
+        # Verify all fields are present
+        assert (completion.choices[0].token_ids is not None
+                and 0 < len(completion.choices[0].token_ids) <= 20)
+        assert completion.choices[0].prompt_token_ids is not None
+
+        # Decode prompt tokens
+        if completion.choices[0].prompt_token_ids:
+            prompt_text = tokenizer.decode(
+                completion.choices[0].prompt_token_ids)
+            # The decoded prompt should match or close to original prompt
+            assert prompt_text == text

vllm/entrypoints/openai/serving_completion.py

@@ -127,7 +127,11 @@ class OpenAIServingCompletion(OpenAIServing):
         try:
             lora_request = self._maybe_get_adapters(request)
 
-            tokenizer = await self.engine_client.get_tokenizer(lora_request)
+            if self.model_config.skip_tokenizer_init:
+                tokenizer = None
+            else:
+                tokenizer = await self.engine_client.get_tokenizer(lora_request
+                                                                   )
 
             request_prompts, engine_prompts = await self._preprocess_completion(
                 request,

vllm/entrypoints/openai/serving_engine.py

@@ -526,8 +526,8 @@ class OpenAIServing:
     async def _normalize_prompt_text_to_input(
         self,
         request: AnyRequest,
-        tokenizer: AnyTokenizer,
         prompt: str,
+        tokenizer: AnyTokenizer,
         truncate_prompt_tokens: Optional[Annotated[int, Field(ge=-1)]],
         add_special_tokens: bool,
     ) -> TextTokensPrompt:
@@ -563,12 +563,10 @@ class OpenAIServing:
     async def _normalize_prompt_tokens_to_input(
         self,
         request: AnyRequest,
-        tokenizer: AnyTokenizer,
         prompt_ids: list[int],
+        tokenizer: Optional[AnyTokenizer],
         truncate_prompt_tokens: Optional[Annotated[int, Field(ge=1)]],
     ) -> TextTokensPrompt:
-        async_tokenizer = self._get_async_tokenizer(tokenizer)
-
         if truncate_prompt_tokens is None:
             input_ids = prompt_ids
         elif truncate_prompt_tokens < 0:
@@ -576,7 +574,11 @@ class OpenAIServing:
         else:
             input_ids = prompt_ids[-truncate_prompt_tokens:]
 
-        input_text = await async_tokenizer.decode(input_ids)
+        if tokenizer is None:
+            input_text = ""
+        else:
+            async_tokenizer = self._get_async_tokenizer(tokenizer)
+            input_text = await async_tokenizer.decode(input_ids)
 
         return self._validate_input(request, input_ids, input_text)
 
@@ -681,27 +683,27 @@ class OpenAIServing:
         [`_tokenize_prompt_input_or_inputs`][vllm.entrypoints.openai.serving_engine.OpenAIServing._tokenize_prompt_input_or_inputs]
         that assumes multiple inputs.
         """
-        for text in prompt_inputs:
-            if isinstance(text, str):
+        for prompt in prompt_inputs:
+            if isinstance(prompt, str):
                 yield await self._normalize_prompt_text_to_input(
                     request,
-                    tokenizer,
-                    prompt=text,
+                    prompt=prompt,
+                    tokenizer=tokenizer,
                     truncate_prompt_tokens=truncate_prompt_tokens,
                     add_special_tokens=add_special_tokens,
                 )
             else:
                 yield await self._normalize_prompt_tokens_to_input(
                     request,
-                    tokenizer,
-                    prompt_ids=text,
+                    prompt_ids=prompt,
+                    tokenizer=tokenizer,
                     truncate_prompt_tokens=truncate_prompt_tokens,
                 )
 
     async def _tokenize_prompt_input_or_inputs_async(
         self,
         request: AnyRequest,
-        tokenizer: AnyTokenizer,
+        tokenizer: Optional[AnyTokenizer],
         input_or_inputs: Optional[Union[str, list[str], list[int],
                                         list[list[int]]]],
         truncate_prompt_tokens: Optional[Annotated[int, Field(ge=-1)]] = None,
@@ -740,17 +742,19 @@ class OpenAIServing:
         tasks = []
         for prompt_input in batch_inputs:
             if prompt_input["is_tokens"] is False:
+                assert tokenizer is not None, \
+                    "Tokenizer is required for text prompts"
                 task = self._normalize_prompt_text_to_input(
                     request,
-                    tokenizer,
                     prompt_input["content"],
+                    tokenizer=tokenizer,
                     truncate_prompt_tokens=truncate_prompt_tokens,
                     add_special_tokens=add_special_tokens)
             else:
                 task = self._normalize_prompt_tokens_to_input(
                     request,
-                    tokenizer,
                     prompt_input["content"],
+                    tokenizer=tokenizer,
                     truncate_prompt_tokens=truncate_prompt_tokens)
             tasks.append(task)
 
@@ -766,7 +770,7 @@ class OpenAIServing:
         request: Union[DetokenizeRequest, EmbeddingCompletionRequest,
                        RerankRequest, ClassificationRequest, ScoreRequest,
                        TokenizeCompletionRequest],
-        tokenizer: AnyTokenizer,
+        tokenizer: Optional[AnyTokenizer],
         input_or_inputs: Union[str, list[str], list[int], list[list[int]]],
         truncate_prompt_tokens: Optional[Annotated[int, Field(ge=-1)]] = ...,
         add_special_tokens: bool = ...,
@@ -777,7 +781,7 @@ class OpenAIServing:
     async def _preprocess_completion(
         self,
         request: CompletionRequest,
-        tokenizer: AnyTokenizer,
+        tokenizer: Optional[AnyTokenizer],
         input_or_inputs: Optional[Union[str, list[str], list[int],
                                         list[list[int]]]],
         truncate_prompt_tokens: Optional[Annotated[int, Field(ge=-1)]] = ...,
@@ -789,7 +793,7 @@ class OpenAIServing:
     async def _preprocess_completion(
         self,
         request: CompletionLikeRequest,
-        tokenizer: AnyTokenizer,
+        tokenizer: Optional[AnyTokenizer],
         input_or_inputs: Optional[Union[str, list[str], list[int],
                                         list[list[int]]]],
         truncate_prompt_tokens: Optional[Annotated[int, Field(ge=-1)]] = None,