AGILab Roadmap NEW

What we’re building next, why it matters, and how you can help.

We’re looking for volunteers to accelerate a few high‑impact items below (CLI/Docker, local‑model backend, demo apps, docs). If you’re interested, open a GitHub issue titled [Volunteer] with a quick note on the area you’d like to help.

Now (high priority)

CLI + Docker Quickstart (no‑IDE path): one‑liner install; uv run agilab to launch Streamlit and run a sample flow.
Public demos: 1–2 lightweight Streamlit apps with tiny datasets, deployed for instant try‑outs.
Local model support: optional backend via Ollama/vLLM; offline mode switch for air‑gapped use.
Docs landing page: 5‑minute Quickstart, screenshots/GIFs, live demo links, clear CTAs.

Plugin / App template: minimal, documented skeleton with a gen app command.
Support matrix: tested OS/Python versions, prebuilt wheels for heavy deps, slimmer environments.
Security & Compliance: data‑flow notes, dependency license scan (already implemented via docs generator; run uv run --group sphinx --dev docs/gen-docs.py in your docs workspace), SBOM, toggles for telemetry.
Docs consolidation: unify scattered help into a cohesive site (Guides, How‑tos, Reference).

Later

Cloud runners: optional remote execution for heavier jobs.
Artifacts registry: externalize large datasets/models; fetch on demand; Git LFS optional.
Benchmarks: repeatable example workloads with performance baselines.

How to contribute (quick)

Pick a ticket

Grab an issue labeled good first issue or open [Proposal] for new ideas.

Show a demo

Add a tiny dataset + app. Target <30s to first result and 3 stages max.

Docs & examples

Improve onboarding: screenshots, GIFs, “Why AGILab vs. X?”, troubleshooting snippets.

Have feedback? Open a GitHub issue.

Now (high priority)

Next

Later

How to contribute (quick)