fix: preserve Omni processor conditioning on vLLM 0.31

Signed-off-by: tzhouam <tzhouam@connect.ust.hk>

vllm_omni/inputs/mm_processor.py

@@ -8,11 +8,39 @@ from typing import TypeVar
 
 from transformers import BatchFeature
 from vllm.multimodal.parse import MultiModalDataItems
-from vllm.multimodal.processing import BaseMultiModalProcessor, BaseProcessingInfo
+from vllm.multimodal.processing import (
+    BaseDummyInputsBuilder,
+    BaseMultiModalProcessor,
+    BaseProcessingInfo,
+    ProcessorInputs,
+    cached_encode,
+)
 
 _I = TypeVar("_I", bound=BaseProcessingInfo)
 
 
+class OmniDummyInputsBuilder(BaseDummyInputsBuilder[_I]):
+    """Restore Omni's processor-input hook on the vLLM 0.31 API."""
+
+    def get_dummy_processor_inputs(
+        self,
+        seq_len: int,
+        mm_counts: Mapping[str, int],
+        mm_options: Mapping[str, object],
+    ) -> ProcessorInputs:
+        dummy_text = self.get_dummy_text(mm_counts)
+        dummy_mm_data = self.get_dummy_mm_data(seq_len, mm_counts, mm_options)
+        dummy_mm_items = self.info.parse_mm_data(dummy_mm_data, validate=False)
+
+        tokenizer = self.info.ctx.tokenizer
+        dummy_prompt = (
+            []
+            if tokenizer is None
+            else cached_encode(tokenizer, dummy_text, truncation=False)
+        )
+        return ProcessorInputs(prompt=dummy_prompt, mm_data_items=dummy_mm_items)
+
+
 class OmniMultiModalProcessor(BaseMultiModalProcessor[_I]):
     """Share data/passthrough handling, leaving model processing in its owner.
 
@@ -23,6 +51,18 @@ class OmniMultiModalProcessor(BaseMultiModalProcessor[_I]):
 
     _OMNI_PROMPT_TEXT_KEY = "_vllm_omni_original_prompt_text"
 
+    def get_dummy_inputs(
+        self,
+        seq_len: int,
+        mm_counts: Mapping[str, int],
+        mm_options: Mapping[str, object],
+    ) -> ProcessorInputs:
+        if isinstance(self.dummy_inputs, OmniDummyInputsBuilder):
+            return self.dummy_inputs.get_dummy_processor_inputs(
+                seq_len, mm_counts, mm_options
+            )
+        return super().get_dummy_inputs(seq_len, mm_counts, mm_options)
+
     def _apply_hf_processor_main(
         self,
         mm_items: MultiModalDataItems,