[Multimodal] Consolidate mm inputs into MultiModalFeatureSpec

[sfeng33]

Purpose

This PR refactors multimodal input in V1 engine to use a unified MultiModalFeatureSpec data structure, as part of the broader effort to abstract out vllm's input processing pipeline (#22880).
Partially fix: #23872

Why This Change:

This refactor addresses the fragmented input processing issue where multimodal data (images, audio, video) was passed through multiple separate fields (mm_kwargs, mm_hashes, mm_placeholders).

Changes

• Introduced MultiModalFeatureSpec: A unified dataclass that encapsulates all multimodal-related data (data, modality, identifier, position) into a single structure.
• Simplified EngineCoreRequest: Replaced three separate multimodal fields with a single mm_features field and updated its references.
  Note: To keep the PR small, only updated core engine and processor references. Left TODO comments for migrating
  scheduler and model runner in follow-up PRs

Test Plan

python -m vllm.entrypoints.openai.api_server \
    --model llava-hf/llava-1.5-7b-hf 

curl -X POST "http://localhost:8000/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "llava-hf/llava-1.5-7b-hf",
    "messages": [
      {
        "role": "user",
        "content": [
          {"type": "text", "text": "What do you see in this image?"},
          {
            "type": "image_url",
            "image_url": {
              "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/car.jpg"
            }
          }
        ]
      }
    ],
    "max_tokens": 100,
    "temperature": 0
  }'

[sfeng33]

PTAL @ywang96 @DarkLight1337

[DarkLight1337]

Sounds good, thanks for the cleanup!

[sfeng33]

Thanks for the review!

[DarkLight1337]

The test fails, PTAL

[sfeng33]

The test fails, PTAL

Should be fixed now, will monitor the CI.