feat[vLLM]: Make VoxtralProcessor compatible with the Transformers modeling backend for vLLM

[harshaljanjani]

What does this PR do?

→ A blocker to the companion vLLM PR for Voxtral audio generation through the Transformers backend.
→ VoxtralProcessor.__call__ rejects audio-token text and routes audio only through apply_chat_template. Makes __call__ accept audio like the other audio processors; since MistralCommonBackend does not encode [AUDIO] from text, splices the audio token id into the encoded segments. No modeling changes needed.
→ Verified no regressions on the Transformers-side in tests/models/voxtral/ (143 non-slow pass; the 5 failing slow integration tests fail identically on main locally, exact-match generation drift, unrelated to this change).
→ I've tried to explain why each non-trivial change was made in a one-line comment given much of this involved unwrapping failure modes layer by layer and uncovering deeper issues in the call chain :)

cc: @eustlb @ebezzam @vasqu

Before (vLLM Voxtral Generation)

After (vLLM Voxtral Generation, After Both PRs)

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[github-actions]

[For maintainers] Suggested jobs to run (before merge)

run-slow: voxtral

[github-actions]

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CI recap

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[eustlb]

Thanks a lot for starting this! Nevertheless it's better here to have apply_chat_template rely on __call__ rather than two diff paths (not your at all fault though, was implement like that from the beginning).
Since this is tricky, I am opening a PR to supersede. Will add you as a coauthor there of course! 🤗

[harshaljanjani]

Thanks for the attribution and makes sense, closing!