[Frontend] Use new Renderer for Completions and Tokenize API (#32863)

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>

vllm/transformers_utils/config.py

@@ -834,7 +834,7 @@ def parse_pooling_type(pooling_name: str):
 @cache
 def get_sentence_transformer_tokenizer_config(
     model: str | Path, revision: str | None = "main"
-):
+) -> dict[str, Any] | None:
     """
     Returns the tokenization configuration dictionary for a
     given Sentence Transformer BERT model.

vllm/utils/async_utils.py

@@ -50,14 +50,17 @@ class AsyncMicrobatchTokenizer:
         self._executor = ThreadPoolExecutor(max_workers=1)
 
     # === Public async API ===
-    async def __call__(self, prompt, **kwargs):
+    async def __call__(self, prompt, **kwargs) -> BatchEncoding:
         result_future: Future = self._loop.create_future()
         key = self._queue_key("encode", kwargs)
         queue = self._get_queue(self._loop, key)
         await queue.put((prompt, kwargs, result_future))
         return await result_future
 
-    async def decode(self, token_ids, **kwargs):
+    async def encode(self, prompt, **kwargs) -> list[int]:
+        return (await self(prompt, **kwargs)).input_ids
+
+    async def decode(self, token_ids, **kwargs) -> str:
         result_future: Future = self._loop.create_future()
         key = self._queue_key("decode", kwargs)
         queue = self._get_queue(self._loop, key)

vllm/v1/engine/async_llm.py

@@ -16,7 +16,6 @@ from vllm import TokensPrompt
 from vllm.config import VllmConfig
 from vllm.engine.arg_utils import AsyncEngineArgs
 from vllm.engine.protocol import EngineClient
-from vllm.entrypoints.utils import _validate_truncation_size
 from vllm.inputs import PromptType
 from vllm.inputs.data import StreamingInput
 from vllm.logger import init_logger
@@ -25,7 +24,7 @@ from vllm.multimodal import MULTIMODAL_REGISTRY, MultiModalRegistry
 from vllm.outputs import STREAM_FINISHED, PoolingRequestOutput, RequestOutput
 from vllm.plugins.io_processors import get_io_processor
 from vllm.pooling_params import PoolingParams
-from vllm.renderers import RendererLike
+from vllm.renderers import RendererLike, merge_kwargs
 from vllm.sampling_params import RequestOutputKind, SamplingParams
 from vllm.tasks import SupportedTask
 from vllm.tokenizers import TokenizerLike
@@ -304,13 +303,20 @@ class AsyncLLM(EngineClient):
                 "prompt logprobs"
             )
 
-        if tokenization_kwargs is None:
-            tokenization_kwargs = {}
-        _validate_truncation_size(
-            self.model_config.max_model_len,
-            params.truncate_prompt_tokens,
-            tokenization_kwargs,
-        )
+        if params.truncate_prompt_tokens is not None:
+            params_type = type(params).__name__
+            warnings.warn(
+                f"The `truncate_prompt_tokens` parameter in `{params_type}` "
+                "is deprecated and will be removed in v0.16. "
+                "Please pass it via `tokenization_kwargs` instead.",
+                DeprecationWarning,
+                stacklevel=2,
+            )
+
+            tokenization_kwargs = merge_kwargs(
+                tokenization_kwargs,
+                dict(truncate_prompt_tokens=params.truncate_prompt_tokens),
+            )
 
         if isinstance(prompt, AsyncGenerator):
             # Streaming input case.
@@ -344,12 +350,12 @@ class AsyncLLM(EngineClient):
                 request_id,
                 prompt,
                 params,
-                arrival_time,
-                lora_request,
-                tokenization_kwargs,
-                trace_headers,
-                priority,
-                data_parallel_rank,
+                arrival_time=arrival_time,
+                lora_request=lora_request,
+                tokenization_kwargs=tokenization_kwargs,
+                trace_headers=trace_headers,
+                priority=priority,
+                data_parallel_rank=data_parallel_rank,
             )
             prompt_text = get_prompt_text(prompt)
 
@@ -757,7 +763,6 @@ class AsyncLLM(EngineClient):
         lora_request: LoRARequest | None = None,
         trace_headers: Mapping[str, str] | None = None,
         priority: int = 0,
-        truncate_prompt_tokens: int | None = None,
         tokenization_kwargs: dict[str, Any] | None = None,
     ) -> AsyncGenerator[PoolingRequestOutput, None]:
         """
@@ -772,22 +777,10 @@ class AsyncLLM(EngineClient):
 
         The caller of generate() iterates the returned AsyncGenerator,
         returning the RequestOutput back to the caller.
-
-        NOTE: truncate_prompt_tokens is deprecated in v0.14.
-        TODO: Remove truncate_prompt_tokens in v0.15.
         """
 
         q: RequestOutputCollector | None = None
         try:
-            if truncate_prompt_tokens is not None:
-                warnings.warn(
-                    "The `truncate_prompt_tokens` parameter in `AsyncLLM.encode()` "
-                    "is deprecated and will be removed in v0.15. "
-                    "Please use `pooling_params.truncate_prompt_tokens` instead.",
-                    DeprecationWarning,
-                    stacklevel=2,
-                )
-
             q = await self.add_request(
                 request_id,
                 prompt,