refactor: reduce copied vLLM 0.29 compatibility code

Reuse upstream weight mapping and multimodal processing, consolidate Omni processor bridges, and trim unused Hunyuan internals. Route no-media kwargs through the active renderer and preserve GLM generation prompt formatting.

Validation: 453 CPU tests passed, 7 skipped; processor imports, Ruff, and diff checks passed. GPU and end-to-end CI not rerun.
Signed-off-by: tzhouam <tzhouam@connect.ust.hk>

tests/inputs/test_mm_processor.py

@@ -0,0 +1,44 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
+
+from types import SimpleNamespace
+from unittest.mock import Mock
+
+import pytest
+from transformers import BatchFeature
+
+from vllm_omni.inputs.mm_processor import OmniMultiModalProcessor
+
+pytestmark = [pytest.mark.core_model, pytest.mark.cpu]
+
+
+@pytest.mark.parametrize("counts", [{}, {"audio": 1, "image": 0}])
+@pytest.mark.parametrize("original_text", [None, "", "voice cloning text"])
+def test_custom_processor_bridge_preserves_prompt_kwargs_and_passthrough(counts, original_text):
+    class Processor(OmniMultiModalProcessor):
+        def _get_mm_fields_config(self, *args):
+            return {}
+
+        def _get_prompt_updates(self, *args):
+            return []
+
+    processor = object.__new__(Processor)
+    processor.dummy_inputs = SimpleNamespace(get_dummy_text=Mock(return_value="dummy"))
+    processor._get_hf_mm_data = Mock(return_value=({"audios": ["wave"]}, {"embedding": "preserve"}))
+    processor._call_hf_processor = Mock(return_value=BatchFeature({"features": "processed"}))
+    items = Mock()
+    items.get_all_counts.return_value = counts
+    kwargs = {"sampling_rate": 16000}
+    if original_text is not None:
+        kwargs[processor._OMNI_PROMPT_TEXT_KEY] = original_text
+    before = dict(kwargs)
+    result = processor._apply_hf_processor_main(items, kwargs)
+    items.select.assert_called_once_with({k for k, v in counts.items() if v > 0})
+    processor._call_hf_processor.assert_called_once_with(
+        "dummy" if original_text is None else original_text,
+        {"audios": ["wave"]},
+        {"sampling_rate": 16000},
+        {},
+    )
+    assert dict(result) == {"features": "processed", "embedding": "preserve"}
+    assert kwargs == before