[Misc] Build canonical image task prompts (#6049)

Signed-off-by: Hongsheng Liu <liuhongsheng4@huawei.com>

examples/offline_inference/image_to_video/image_to_video.py

@@ -63,7 +63,9 @@ from vllm_omni.inputs.data import OmniDiffusionSamplingParams
 from vllm_omni.lora.request import LoRARequest
 from vllm_omni.lora.utils import stable_lora_int_id
 from vllm_omni.model_extras import (
-    build_image_to_video_prompt,
+    build_image_to_video_prompt as build_model_image_to_video_prompt,
+)
+from vllm_omni.model_extras import (
     get_extra_body_params,
     get_model_class_name,
 )
@@ -85,6 +87,22 @@ def parse_json_object(value: str, flag_name: str = "argument") -> dict[str, Any]
 parse_profiler_config = functools.partial(parse_json_object, flag_name="--profiler-config")
 
 
+def build_image_to_video_prompt(
+    prompt: str,
+    negative_prompt: str | None,
+    media_inputs: dict[str, Any],
+) -> dict[str, Any]:
+    """Build the canonical request envelope for the shared I2V example."""
+    result: dict[str, Any] = {
+        "prompt": prompt,
+        "modalities": ["video"],
+        "multi_modal_data": media_inputs,
+    }
+    if negative_prompt is not None:
+        result["negative_prompt"] = negative_prompt
+    return result
+
+
 def parse_args() -> argparse.Namespace:
     parser = argparse.ArgumentParser(
         description=(
@@ -566,10 +584,13 @@ def main():
         # Preserve the historical empty-prompt behavior for non-LTX examples.
         negative_prompt = ""
     prompt_dict = build_image_to_video_prompt(
-        model_class_name=model_class_name,
         prompt=args.prompt,
         negative_prompt=negative_prompt,
         media_inputs=media_inputs,
+    )
+    prompt_dict = build_model_image_to_video_prompt(
+        model_class_name=model_class_name,
+        prompt=prompt_dict,
         height=height,
         width=width,
         num_frames=num_frames,

examples/offline_inference/text_to_image/README.md

@@ -57,8 +57,9 @@ python examples/offline_inference/text_to_image/text_to_image.py \
   --output lingbot_t2i.png
 ```
 
-The LingBot prompt builder selects the `image` output modality and requests one
-frame. Passing an input image is not supported in LingBot T2I mode.
+The shared T2I entry point selects the `image` output modality. The LingBot
+pipeline validates that T2I requests produce one frame and do not include an
+input image.
 
 ## Quick Start
 

examples/offline_inference/text_to_image/text_to_image.py

@@ -21,7 +21,9 @@ from vllm_omni.inputs.data import OmniDiffusionSamplingParams
 from vllm_omni.lora.request import LoRARequest
 from vllm_omni.lora.utils import stable_lora_int_id
 from vllm_omni.model_extras import (
-    build_text_to_image_prompt,
+    build_text_to_image_prompt as build_model_text_to_image_prompt,
+)
+from vllm_omni.model_extras import (
     get_extra_body_params,
     get_model_class_name,
     should_init_extra_args_for_non_diffusion_stages,
@@ -56,6 +58,17 @@ def parse_json_object(value: str, flag_name: str = "argument") -> dict[str, Any]
 parse_profiler_config = functools.partial(parse_json_object, flag_name="--profiler-config")
 
 
+def build_text_to_image_prompt(prompt: str, negative_prompt: str | None) -> dict[str, Any]:
+    """Build the canonical request envelope for the shared T2I example."""
+    result: dict[str, Any] = {
+        "prompt": prompt,
+        "modalities": ["image"],
+    }
+    if negative_prompt is not None:
+        result["negative_prompt"] = negative_prompt
+    return result
+
+
 def _normalize_images_for_save(images: list[Any]) -> list[Any]:
     """Convert NumPy diffusion outputs to PIL images before saving."""
     normalized = []
@@ -523,9 +536,12 @@ def main():
     generation_start = time.perf_counter()
 
     prompt_dict = build_text_to_image_prompt(
-        model_class_name=model_class_name,
         prompt=args.prompt,
         negative_prompt=args.negative_prompt,
+    )
+    prompt_dict = build_model_text_to_image_prompt(
+        model_class_name=model_class_name,
+        prompt=prompt_dict,
         height=args.height,
         width=args.width,
     )