Fix nullable_kvs fallback

tests/engine/test_arg_utils.py

@@ -10,7 +10,7 @@
 
 
 @pytest.mark.parametrize(("arg", "expected"), [
-    (None, None),
+    (None, dict()),
     ("image=16", {
         "image": 16
     }),

tests/entrypoints/openai/test_audio.py

@@ -1,5 +1,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
+import json
+
 import openai
 import pytest
 import pytest_asyncio
@@ -27,7 +29,7 @@ def server():
         "--enforce-eager",
         "--trust-remote-code",
         "--limit-mm-per-prompt",
-        str({"audio": MAXIMUM_AUDIOS}),
+        json.dumps({"audio": MAXIMUM_AUDIOS}),
     ]
 
     with RemoteOpenAIServer(MODEL_NAME, args) as remote_server:

tests/entrypoints/openai/test_video.py

@@ -1,5 +1,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
+import json
+
 import openai
 import pytest
 import pytest_asyncio
@@ -31,7 +33,7 @@ def server():
         "--enforce-eager",
         "--trust-remote-code",
         "--limit-mm-per-prompt",
-        str({"video": MAXIMUM_VIDEOS}),
+        json.dumps({"video": MAXIMUM_VIDEOS}),
     ]
 
     with RemoteOpenAIServer(MODEL_NAME, args) as remote_server:

tests/entrypoints/openai/test_vision.py

@@ -1,5 +1,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
+import json
+
 import openai
 import pytest
 import pytest_asyncio
@@ -35,7 +37,7 @@ def server():
         "--enforce-eager",
         "--trust-remote-code",
         "--limit-mm-per-prompt",
-        str({"image": MAXIMUM_IMAGES}),
+        json.dumps({"image": MAXIMUM_IMAGES}),
     ]
 
     with RemoteOpenAIServer(MODEL_NAME, args) as remote_server:

tests/entrypoints/openai/test_vision_embedding.py

@@ -1,5 +1,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
+import json
+
 import pytest
 import requests
 from PIL import Image
@@ -37,7 +39,7 @@ def server():
         "--enforce-eager",
         "--trust-remote-code",
         "--limit-mm-per-prompt",
-        str({"image": MAXIMUM_IMAGES}),
+        json.dumps({"image": MAXIMUM_IMAGES}),
         "--chat-template",
         str(vlm2vec_jinja_path),
     ]

tests/models/decoder_only/audio_language/test_ultravox.py

@@ -1,5 +1,6 @@
 # SPDX-License-Identifier: Apache-2.0
 
+import json
 from typing import Optional
 
 import numpy as np
@@ -50,7 +51,7 @@ def server(request, audio_assets):
     args = [
         "--dtype", "bfloat16", "--max-model-len", "4096", "--enforce-eager",
         "--limit-mm-per-prompt",
-        str({"audio": len(audio_assets)}), "--trust-remote-code"
+        json.dumps({"audio": len(audio_assets)}), "--trust-remote-code"
     ] + [
         f"--{key.replace('_','-')}={value}"
         for key, value in request.param.items()

vllm/config.py

@@ -10,7 +10,6 @@
 import textwrap
 import warnings
 from collections import Counter
-from collections.abc import Mapping
 from contextlib import contextmanager
 from dataclasses import (MISSING, dataclass, field, fields, is_dataclass,
                          replace)
@@ -355,7 +354,7 @@ def __init__(
         disable_cascade_attn: bool = False,
         skip_tokenizer_init: bool = False,
         served_model_name: Optional[Union[str, list[str]]] = None,
-        limit_mm_per_prompt: Optional[Mapping[str, int]] = None,
+        limit_mm_per_prompt: Optional[dict[str, int]] = None,
         use_async_output_proc: bool = True,
         config_format: ConfigFormat = ConfigFormat.AUTO,
         hf_token: Optional[Union[bool, str]] = None,
@@ -578,7 +577,7 @@ def maybe_pull_model_tokenizer_for_s3(self, model: str,
                 self.tokenizer = s3_tokenizer.dir
 
     def _init_multimodal_config(
-        self, limit_mm_per_prompt: Optional[Mapping[str, int]]
+        self, limit_mm_per_prompt: Optional[dict[str, int]]
     ) -> Optional["MultiModalConfig"]:
         if self.registry.is_multimodal_model(self.architectures):
             return MultiModalConfig(limit_per_prompt=limit_mm_per_prompt or {})
@@ -2730,7 +2729,7 @@ def verify_with_model_config(self, model_config: ModelConfig):
 class MultiModalConfig:
     """Controls the behavior of multimodal models."""
 
-    limit_per_prompt: Mapping[str, int] = field(default_factory=dict)
+    limit_per_prompt: dict[str, int] = field(default_factory=dict)
     """
     The maximum number of input items allowed per prompt for each modality.
     This should be a JSON string that will be parsed into a dictionary.

vllm/engine/arg_utils.py

@@ -7,7 +7,7 @@
 import re
 import threading
 from dataclasses import MISSING, dataclass, fields
-from typing import (TYPE_CHECKING, Any, Callable, Dict, List, Literal, Mapping,
+from typing import (TYPE_CHECKING, Any, Callable, Dict, List, Literal,
                     Optional, Tuple, Type, TypeVar, Union, cast, get_args,
                     get_origin)
 
@@ -112,14 +112,14 @@ def nullable_kvs(val: str) -> Optional[dict[str, int]]:
 
 
 def optional_dict(val: str) -> Optional[dict[str, int]]:
-    try:
+    if re.match("^{.*}$", val):
         return optional_arg(val, json.loads)
-    except ValueError:
-        logger.warning(
-            "Failed to parse JSON string. Attempting to parse as "
-            "comma-separated key=value pairs. This will be deprecated in a "
-            "future release.")
-        return nullable_kvs(val)
+
+    logger.warning(
+        "Failed to parse JSON string. Attempting to parse as "
+        "comma-separated key=value pairs. This will be deprecated in a "
+        "future release.")
+    return nullable_kvs(val)
 
 
 @dataclass
@@ -191,7 +191,7 @@ class EngineArgs:
         TokenizerPoolConfig.pool_type
     tokenizer_pool_extra_config: dict[str, Any] = \
         get_field(TokenizerPoolConfig, "extra_config")
-    limit_mm_per_prompt: Mapping[str, int] = \
+    limit_mm_per_prompt: dict[str, int] = \
         get_field(MultiModalConfig, "limit_per_prompt")
     mm_processor_kwargs: Optional[Dict[str, Any]] = None
     disable_mm_preprocessor_cache: bool = False