Tencent Cloud VOD Assistant

Problem

Media workflows are split across upload, transcoding, snapshots, AIGC image/video/audio generation, and task status checks. Building API calls manually can mix up scripts, parameter names, async task polling, and cost boundaries.

How It Works

• Route by task type: use vod_upload.py for local files, vod_pull_upload.py for URLs, vod_describe_media.py for known FileId details, vod_search_media.py for name/tag filters, and vod_search_media_by_semantics.py for natural-language semantic search.
• Generate runnable commands: commands follow python3 scripts/vod_xxx.py ... and support --help and --dry-run; paid processing tasks should be confirmed after cost warnings.
• Handle async jobs: by default scripts wait for completion or timeout, while --no-wait returns only the task ID and vod_describe_task.py --task-id can query status.
• Cover AIGC workflows: includes vod_aigc_chat.py for LLM chat, vod_aigc_image.py for image generation, vod_aigc_video.py for video generation, vod_aigc_audio.py for audio generation, vod_aigc_token.py for token and usage, plus image/video enhancement and knowledge-base import.

Boundaries and Caveats

• Missing required parameters must be asked from the user; placeholder values are not used.
• Parameter behavior follows the references/ docs, not inferred from script source code.
• VOD calls may incur transcoding, storage, or AIGC costs; prefer --dry-run for high-cost operations.
• If environment credentials are missing, stop and ask the user to configure them instead of retrying.