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What you can do with ML View

MLView is an experimental VS Code viewer and skill that lets a coding assistant turn an ML workflow into an interactive, source-linked diagram.

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realmyang/MLView on GitHub

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What do you want to do?

3 use cases

  • Turn a training config into a source-linked diagram

    Ask your assistant to map data, model, losses and validation as a clickable diagram.

    View prompt
    Using the MLView repo at <mlview-checkout>, install the mlview skill into <target-project> and ask the assistant to explain the training config in <target-project>. Expect a *.mlview.json file that opens as a diagram. Verify that the diagram lists unresolved items and that its cited files are reported as unchanged.

  • Check each diagram claim against its cited lines

    Walk inferred and unresolved claims in the diagram and open their cited source beside it.

    View prompt
    In the repo <target-project>, open the MLView diagram <diagram-file>.mlview.json and list each inferred or unresolved claim with its cited file and line range. Expect a short review list. Verify that every listed quote points to a file that is marked unchanged.

  • Update a workflow diagram after the code changes

    Ask the assistant for a refined revision and see what was added, removed or changed.

    View prompt
    In the repo <target-project>, refine the MLView diagram <diagram-file>.mlview.json to reflect my recent edits to <changed-file>. Expect a new revision whose Changes since summary lists the affected steps. Verify that the new revision's changed items all cite lines that exist in the current files.

How to use ML View

  1. Check you have what it needs: Python 3.10+; Node 20.18.1+; VS Code.
  2. Open realmyang/MLView on GitHub and read the README and license.
  3. Run cd webview && npm ci && npm run build && cd .. from the ML View checkout.
  4. Run python3 tools/sync-assets.py.
  5. Run cd vscode-extension && npm ci && npm run package && cd .., then install the generated VSIX with VS Code's Extensions: Install from VSIX.
  6. Run python3 tools/install_skill.py /path/to/your/project.

These steps come from our top use case, Turn a training config into a source-linked diagram, which also has a copy-paste agent prompt.

ML View alternatives · Best AI repos for Software and DevOps

About this repo

  • Who it is forBest for ML engineers and researchers in VS Code who already use Codex, Claude Code or Copilot and want to understand or review a training workflow.
  • Why it is hot
  • LanguagePython
  • Sourcegithub.com/realmyang/MLView · Back to Hot repos

Requirements

  • Python 3.10+
  • Node 20.18.1+
  • VS Code
  • A supported assistant: GitHub Copilot, Codex or Claude Code
  • A target ML project to open in VS Code
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Questions about ML View

What is ML View?

MLView is an experimental VS Code viewer and skill that lets a coding assistant turn an ML workflow into an interactive, source-linked diagram. It is an open-source project on GitHub: https://github.com/realmyang/MLView.

Who is ML View for?

Best for ML engineers and researchers in VS Code who already use Codex, Claude Code or Copilot and want to understand or review a training workflow.

What can I do with ML View?

3 use cases so far, for example: Turn a training config into a source-linked diagram; Check each diagram claim against its cited lines; Update a workflow diagram after the code changes. Each has steps and a copy-paste agent prompt.

What do I need to run ML View?

Python 3.10+; Node 20.18.1+; VS Code; A supported assistant: GitHub Copilot, Codex or Claude Code.

What are alternatives to ML View?

Other hot AI repos in Software and DevOps: Harness2, iFixAi, Orca, Diagram Design, AI Memory.

Is ML View safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.