Replace manual cv2 frame reading with FORCE_QWENVL_VIDEO_READER=torchvision
env var. The torchvision backend (PyAV) properly reads video metadata and
respects the fps parameter, avoiding the torchcodec fps=24 default issue.
Made-with: Cursor
When torchcodec is installed, qwen-vl-utils ignores the fps parameter
and defaults to 24fps if video metadata is missing, causing shape
mismatches. Fix by reading video frames directly as PIL images and
passing them to the processor, bypassing torchcodec entirely.
Made-with: Cursor
The single-episode `segment_skills` method was missing
`enable_thinking=False` in `apply_chat_template`, causing the model to
output reasoning traces instead of JSON when the batch path fails and
falls back to per-episode processing.
Made-with: Cursor
