Authorization notice. By2 KB is dual-use. Only use it on software, sites and systems you own or have explicit permission to test.
Who it is forAn operator or developer running By2 KB through an agent host who needs reliable job control instead of parsing logs.
The problemLong transcriptions run in the background, and an agent needs a clear way to know whether a job finished, failed, or should be retried.
The outcomeJSON status for each job, a bounded wait, and clean cancel or retry actions with checkpoint-aware retries.
What you need first
- Python 3.12 or newer
- pipx installed
- ffmpeg and ffprobe available on PATH
- Optional: Deno 2.3+ or Node.js 22+ for YouTube player challenges
- Optional: a Hermes agent for chat-based use, or an OpenAI-compatible API key for standalone summaries
Steps
- Start an ingest with
by2kb ingest "<video URL>". (inferred, check the README) - Run
by2kb status --jsonto see the current job state. (inferred, check the README) - Run
by2kb wait --timeout 30 --jsonto wait up to the timeout for completion. (inferred, check the README) - Run
by2kb cancel --jsonif the job should stop. (inferred, check the README) - Run
by2kb retry --jsonto resume a failed job from its checkpoint. (inferred, check the README)
Prompt for your agent
Use the by2kb repository (github.com/Charlesmpc/by2kb) to start ingesting <video URL> and then manage the job with status, wait, cancel, and retry in JSON mode. Expected output: a JSON status for each step and the final artifact paths. Verify that the job reaches a completed state or that the retry resumes it.
Caveat. The README describes the control protocol but does not give the full JSON schema, so an agent should read docs/task-control.md before parsing fields.
Use this in your AI agent
Ask your agent
Using the Deduped MCP, get the setup steps for Charlesmpc/by2kb and "Track and control video ingest jobs from an agent"
Add Deduped to Claude Code once
claude mcp add --transport http deduped https://dedupedai.com/mcp
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