Skip to content

v0.3.0 — Bloom AI tutor desktop preview

Pre-release
Pre-release

Choose a tag to compare

View all tags
@pritanb pritanb released this 28 Sep 03:43
v0.3.0
548a014
This commit was created on GitHub.com and signed with GitHub’s verified signature.
GPG key ID: B5690EEEBB952194
Verified
Learn about vigilant mode.

BloomCode v0.3.0 — Bloom AI tutor preview

New

  • Bloom: a movable, app-wide coding tutor with persistent conversations, evidence links, and guided coaching.
  • Confirmed learning goals and teaching preferences.
  • Shared Python AI infrastructure and LangGraph workflows for tutoring and Learning Insights; Python also handles attempt feedback, observation extraction, and topic recommendations.
  • Learning Insights groups related observations across study history, verifies supporting and contrary evidence, and suggests up to six habits with exercises and success checks.
  • Regenerate reports from saved analysis; cleaner detail panels and readable source links.

Install

Download BloomCode-darwin-arm64-0.3.0.zip, unzip, and move BloomCode.app into Applications. This preview supports Apple silicon macOS. Existing study workspaces are retained.

The app is ad-hoc signed, not Developer ID signed or notarized. macOS may require approval in Privacy & Security for a downloaded app you trust.

Optional AI setup

The app includes Python workflow sources and its MCP adapter. Install Python 3.11+ and create the separate AI environment once:

python3 -m venv "$HOME/Library/Application Support/BloomCode/ai-runtime"
"$HOME/Library/Application Support/BloomCode/ai-runtime/bin/python" -m pip install -r /Applications/BloomCode.app/Contents/Resources/ai/python/requirements.txt

Restart BloomCode. AI requires file-based Codex sign-in (~/.codex/auth.json, or CODEX_HOME/auth.json) and uses the signed-in account's allowance. Keyring-only sign-in is not supported. Ordinary study features work without AI setup. No credentials or study data are included in the archive.

Known limitations

  • Insight grouping is heuristic; source verification does not prove a diagnosis. Report generation may take several minutes.
  • Conversation history and coaching checkpoints are separate from study-database backups.
  • Python interpreter/dependencies are not bundled; the one-time setup above is required for AI.

Validation

129 TypeScript tests, 53 offline Python tests, typecheck, lint, formatting, build and disposable runtime checks passed locally. The packaged app was checked against a disposable database, including the bundled MCP tools and Python tutor startup.

Assets 4
Loading