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How to run the clipper in Docker with GPU acceleration with Autoclip

Start AutoClip from the bundled compose file, optionally with the GPU profile for faster transcription.

  • Content
  • Advanced
  • 1 hour
  • From the README
  • Any agent

Who it is forA developer setting up a shared clipping box for a small content team.

The problemMatching Python, MediaPipe and ffmpeg versions on every laptop is fragile.

The outcomeA containerized AutoClip that the team can reach from a browser.

What you need first

  • Python 3.11 or 3.12 (not 3.13)
  • A full ffmpeg build with libass and libx264
  • Node 20+ to build the UI
  • Ollama for fully local runs, or an Anthropic, OpenAI, Gemini or OpenAI-compatible key

Steps

  1. Clone the repo with git clone https://github.com/artbyjazi/autoclip.git
  2. Start it with docker compose -f docker/compose.yaml up --build
  3. On an NVIDIA machine use docker compose -f docker/compose.yaml --profile gpu up --build
  4. Open the UI and run a test clip

Prompt for your agent

Bring up artbyjazi/autoclip with `docker compose -f docker/compose.yaml --profile gpu up --build` on <host>, clip one short test video, and confirm the export finished and the GPU was used for transcription.

Caveat. Transcription works on CPU but the README says a GPU speeds it up several-fold.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for artbyjazi/autoclip and "Run the clipper in Docker with GPU acceleration"

Add Deduped to Claude Code once

claude mcp add --transport http deduped https://dedupedai.com/mcp

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