SuperAPI AI Directory

qwen-mm-plugins-omni-chatcut-video-translation

Agents & models

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Updated 10-16 09:53

About this skill

Video Translation

Own one durable project and route it by state:

source video → Agent-reconciled Omni/VAD transcript → Agent-authored dubbing plan → dubbed render → Agent listening review

Inspect first:

python3 <skill-root>/scripts/inspect_video_translation_state.py <project-dir>

Use the first applicable route: review or validate an existing delivery; resume a plan/render; translate an accepted transcript; or analyze a new source. Read pipeline-contract.md before accepting artifacts and dubbing-service.md when configuring the external GPU service. Never infer success from filenames alone.

Internal workflows

Load only the current workflow. Reuse the bundled omni_call for audio-video understanding. Use the video-translation MCP tools for the external dubbing service and deterministic local media execution.

Authorization and configuration

Analysis and translation-only targets stop before TTS. A full or resumed dubbing request authorizes calls to the configured external dubbing service. The service URL comes from QWEN_MM_DUBBING_SERVER_URL. Never write it to artifacts.

Do not use server-local paths as portable outputs. Tools upload local inputs and save returned audio into the project. Preserve the source video stream during final remux. A delivery is complete only after the final file fully decodes and the measured QA contract passes.

User-facing completion

After a successful render, surface the returned summary directly to the user. Report the segment count, the number of automatic risk flags, and each segment that needs manual listening review with its time range, translated text, and reason. Link full/translation_summary.md for a readable report and full/translation_diagnostics.json for complete machine-readable details. Even when no automatic flags are found, instruct the user to perform one end-to-end check for ordering, overlaps, pronunciation, and mix balance.