[Frontend] Factor out chat message parsing (#7055)

vllm/entrypoints/chat_utils.py

@@ -1,7 +1,8 @@
 import codecs
-from dataclasses import dataclass, field
+from dataclasses import dataclass
 from functools import lru_cache
-from typing import Awaitable, Iterable, List, Optional, Union, cast, final
+from typing import (Awaitable, Iterable, List, Optional, Tuple, Union, cast,
+                    final)
 
 # yapf conflicts with isort for this block
 # yapf: disable
@@ -65,8 +66,7 @@ class ConversationMessage(TypedDict):
 @dataclass(frozen=True)
 class ChatMessageParseResult:
     messages: List[ConversationMessage]
-    mm_futures: List[Awaitable[MultiModalDataDict]] = field(
-        default_factory=list)
+    mm_futures: List[Awaitable[MultiModalDataDict]]
 
 
 def load_chat_template(chat_template: Optional[str]) -> Optional[str]:
@@ -174,7 +174,7 @@ def _parse_chat_message_content_parts(
     return ChatMessageParseResult(messages=messages, mm_futures=mm_futures)
 
 
-def parse_chat_message_content(
+def _parse_chat_message_content(
     message: ChatCompletionMessageParam,
     model_config: ModelConfig,
     tokenizer: PreTrainedTokenizer,
@@ -190,3 +190,21 @@ def parse_chat_message_content(
 
     return _parse_chat_message_content_parts(role, content, model_config,
                                              tokenizer)
+
+
+def parse_chat_messages(
+    messages: List[ChatCompletionMessageParam],
+    model_config: ModelConfig,
+    tokenizer: PreTrainedTokenizer,
+) -> Tuple[List[ConversationMessage], List[Awaitable[MultiModalDataDict]]]:
+    conversation: List[ConversationMessage] = []
+    mm_futures: List[Awaitable[MultiModalDataDict]] = []
+
+    for msg in messages:
+        parse_result = _parse_chat_message_content(msg, model_config,
+                                                   tokenizer)
+
+        conversation.extend(parse_result.messages)
+        mm_futures.extend(parse_result.mm_futures)
+
+    return conversation, mm_futures

vllm/entrypoints/openai/serving_chat.py

@@ -1,6 +1,5 @@
 import time
-from typing import (AsyncGenerator, AsyncIterator, Awaitable, Dict, List,
-                    Optional)
+from typing import AsyncGenerator, AsyncIterator, Dict, List, Optional
 from typing import Sequence as GenericSequence
 from typing import Union
 
@@ -11,7 +10,7 @@ from vllm.config import ModelConfig
 from vllm.engine.protocol import AsyncEngineClient
 from vllm.entrypoints.chat_utils import (ConversationMessage,
                                          load_chat_template,
-                                         parse_chat_message_content)
+                                         parse_chat_messages)
 from vllm.entrypoints.logger import RequestLogger
 from vllm.entrypoints.openai.protocol import (
     ChatCompletionLogProb, ChatCompletionLogProbs,
@@ -92,15 +91,8 @@ class OpenAIServingChat(OpenAIServing):
             tokenizer = await self.async_engine_client.get_tokenizer(
                 lora_request)
 
-            conversation: List[ConversationMessage] = []
-            mm_futures: List[Awaitable[MultiModalDataDict]] = []
-
-            for msg in request.messages:
-                chat_parsed_result = parse_chat_message_content(
-                    msg, model_config, tokenizer)
-
-                conversation.extend(chat_parsed_result.messages)
-                mm_futures.extend(chat_parsed_result.mm_futures)
+            conversation, mm_futures = parse_chat_messages(
+                request.messages, model_config, tokenizer)
 
             tool_dicts = None if request.tools is None else [
                 tool.model_dump() for tool in request.tools
@@ -115,6 +107,7 @@ class OpenAIServingChat(OpenAIServing):
                 chat_template=request.chat_template or self.chat_template,
                 **(request.chat_template_kwargs or {}),
             )
+            assert isinstance(prompt, str)
         except Exception as e:
             logger.error("Error in applying chat template from request: %s", e)
             return self.create_error_response(str(e))

vllm/entrypoints/openai/serving_tokenization.py

@@ -1,13 +1,11 @@
 from typing import List, Optional, Union
 
 from vllm.config import ModelConfig
+from vllm.engine.protocol import AsyncEngineClient
+from vllm.entrypoints.chat_utils import load_chat_template, parse_chat_messages
+from vllm.entrypoints.logger import RequestLogger
 # yapf conflicts with isort for this block
 # yapf: disable
-from vllm.engine.protocol import AsyncEngineClient
-from vllm.entrypoints.chat_utils import (ConversationMessage,
-                                         load_chat_template,
-                                         parse_chat_message_content)
-from vllm.entrypoints.logger import RequestLogger
 from vllm.entrypoints.openai.protocol import (DetokenizeRequest,
                                               DetokenizeResponse,
                                               ErrorResponse,
@@ -17,8 +15,11 @@ from vllm.entrypoints.openai.protocol import (DetokenizeRequest,
 # yapf: enable
 from vllm.entrypoints.openai.serving_engine import (LoRAModulePath,
                                                     OpenAIServing)
+from vllm.logger import init_logger
 from vllm.utils import random_uuid
 
+logger = init_logger(__name__)
+
 
 class OpenAIServingTokenization(OpenAIServing):
 
@@ -62,12 +63,12 @@ class OpenAIServingTokenization(OpenAIServing):
         if isinstance(request, TokenizeChatRequest):
             model_config = self.model_config
 
-            conversation: List[ConversationMessage] = []
+            conversation, mm_futures = parse_chat_messages(
+                request.messages, model_config, tokenizer)
 
-            for message in request.messages:
-                result = parse_chat_message_content(message, model_config,
-                                                    tokenizer)
-                conversation.extend(result.messages)
+            if mm_futures:
+                logger.warning(
+                    "Multi-modal inputs are ignored during tokenization")
 
             prompt = tokenizer.apply_chat_template(
                 add_generation_prompt=request.add_generation_prompt,