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[infer] support mixed multimodal payloads (#10225)

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Signed-off-by: Philip Ottesen <phiott256@gmail.com>
This commit is contained in:
Philip Ottesen
2026-02-28 13:26:53 +01:00
committed by GitHub
parent 45d335c709
commit 0779846513
2 changed files with 39 additions and 44 deletions
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41
src/llamafactory/chat/vllm_engine.py
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@@ -180,35 +180,32 @@ class VllmEngine(BaseEngine):
else self.generating_args["skip_special_tokens"],
)
multi_modal_data = {}
if images is not None: # add image features
multi_modal_data = {
"image": self.template.mm_plugin._regularize_images(
images,
image_max_pixels=self.model_args.image_max_pixels,
image_min_pixels=self.model_args.image_min_pixels,
)["images"]
}
elif videos is not None:
multi_modal_data = {
"video": self.template.mm_plugin._regularize_videos(
videos,
image_max_pixels=self.model_args.video_max_pixels,
image_min_pixels=self.model_args.video_min_pixels,
video_fps=self.model_args.video_fps,
video_maxlen=self.model_args.video_maxlen,
)["videos"]
}
elif audios is not None:
multi_modal_data["image"] = self.template.mm_plugin._regularize_images(
images,
image_max_pixels=self.model_args.image_max_pixels,
image_min_pixels=self.model_args.image_min_pixels,
)["images"]
if videos is not None:
multi_modal_data["video"] = self.template.mm_plugin._regularize_videos(
videos,
image_max_pixels=self.model_args.video_max_pixels,
image_min_pixels=self.model_args.video_min_pixels,
video_fps=self.model_args.video_fps,
video_maxlen=self.model_args.video_maxlen,
)["videos"]
if audios is not None:
audio_data = self.template.mm_plugin._regularize_audios(
audios,
sampling_rate=self.model_args.audio_sampling_rate,
)
multi_modal_data = {"audio": zip(audio_data["audios"], audio_data["sampling_rates"])}
else:
multi_modal_data = None
multi_modal_data["audio"] = zip(audio_data["audios"], audio_data["sampling_rates"])
result_generator = self.model.generate(
{"prompt_token_ids": prompt_ids, "multi_modal_data": multi_modal_data},
{"prompt_token_ids": prompt_ids, "multi_modal_data": multi_modal_data or None},
sampling_params=sampling_params,
request_id=request_id,
lora_request=self.lora_request,