---
The open source AI stack is already strong, but it's fragmented, duplicative, and hard to
see as a whole. The [Open Source AI Stack Gap Map](https://map.currentai.org/) makes it legible: a
living map of what exists across the stack, how open each piece is, how widely it's used, and
where the gaps are — so the community can see where to build, where to invest, and where to
open things up.
This repo is the data behind that map. Everything is curated YAML in `sources/`; a
deterministic pipeline validates it, serializes it to `build/notebook_data.json`, and renders
the published map.
---
## Contribute
The map is a public, iterative effort, and community curation is the point. There are two ways in:
1. **File an issue** (no code needed):
[suggest a product](https://github.com/currentai-org/os-ai-map/issues/new?template=suggest-a-product.yml),
[report an error](https://github.com/currentai-org/os-ai-map/issues/new?template=report-an-error.yml), or
[propose a category](https://github.com/currentai-org/os-ai-map/issues/new?template=propose-a-category.yml).
2. **Open a pull request** editing `sources/`. Adding a product is a handful of small YAML files:
a product record, a score with citations, and an entry in one category roster and one
organization roster. [CONTRIBUTING.md](CONTRIBUTING.md) has the full recipe and the scoring rubric.
A few ground rules:
- **Every score cites a primary source.** The map excludes anything it can't verify against one.
- **Don't hand-edit generated files.** `build/notebook_data.json` and `notebooks/ai-stack-map.py`
are regenerated by a bot on merge; PRs that touch them are blocked.
- **CI runs on every PR** (`build.validate` + `pytest`), so you'll know quickly if something is off.
---
## How scoring works
Each product is graded on three independent, multi-source axes:
- **Openness** — a 0–5 grade against openness frameworks (the [Model Openness Framework](https://arxiv.org/abs/2403.13784)
for models, OSI license classes for software), not a yes/no. The open-source vs. open-weights
distinction is the one the map exists to draw.
- **Adoption** — real usage (downloads, active users, deployments), not GitHub stars.
- **Capability** — community benchmarks where they exist, feature coverage where they don't.
Categories then roll up from their products into a maturity **stage** (0 Void → 5 Mature) plus a
set of **gaps** naming what the open ecosystem still lacks. The taxonomy and openness framework
descend from the [2024 Columbia Convening on Openness in AI](https://arxiv.org/abs/2405.15802).
The complete method — the stage and gap formulas, per-axis sources, and stated limitations — is in
[`docs/methodology.md`](docs/methodology.md), the hand-authored source of truth (also rendered
[on the site](https://map.currentai.org/methodology)).
---
## What's in `sources/`
One YAML file per record: four concerns plus the single `sources/taxonomy.yaml` manifest. This is
what you edit.
| Path | Contains | Key rule |
|------|----------|----------|
| `sources/organizations/` | Org metadata and a `products:` roster | Each product slug appears in exactly one org roster |
| `sources/categories/` | Category definition (`weights`, `strapline`, …) and an ordered `products:` roster | Order = display order; each product in exactly one category |
| `sources/products/` | Product record (`name`, `type`, `description`, typed artifact URLs) | Org membership lives in the org file, not here |
| `sources/scores/` | Per-product `openness`, `adoption`, `capability` | Every non-null score value needs a `sources:` citation |
| `sources/taxonomy.yaml` | Arc grouping + display order; the three arcs are the Columbia ontology layers | Every category appears in exactly one arc |
Category slugs use underscore form (`base_pretrained`); product and org slugs use hyphenated
kebab-case (`llama-3-1`, `allen-ai`). Artifact keys on products (only those that apply): `github`,
`npm`, `pypi`, `crates`, `go`, `huggingface_model`, `huggingface_dataset`. JSON Schemas for every
file type live in [`docs/schemas/`](docs/schemas/).
---
## Run it locally
Requires Python 3.12+ and [uv](https://docs.astral.sh/uv/). No API key is needed to edit sources or validate.
```bash
uv sync
uv run python -m build.validate # schema + cross-file checks; must print "0 error(s)"
uv run pytest -q # optional; the same suite CI runs
```
To preview the generated map locally (the output is for preview only — don't commit it):
```bash
uv run python -m build.serialize # sources/ → build/notebook_data.json
uv run python build/render.py # → notebooks/ai-stack-map.py
uv run marimo export html notebooks/ai-stack-map.py -o /tmp/preview.html
```
Warehouse queries (via `pyoso`) need `OSO_API_KEY`; with `direnv`, place it in `.env` and it loads automatically.
---
## Repository layout
| Path | Role |
|------|------|
| `sources/` | Curated YAML you edit: organizations, categories, products, scores, + `taxonomy.yaml` |
| `build/` | Deterministic validate → serialize → render pipeline |
| `notebooks/` | Generated `ai-stack-map.py` + standalone companion notebooks |
| `docs/` | JSON Schemas, contributor guides, methodology, and maintainer runbooks |
| `warehouse/` | UDM SQL and ingest fetchers for adoption / activity signals |
| `skills/` | Agent skills mirroring the contribution recipes |
| `tests/` | pytest suite for build helpers |
Guides worth knowing: [openness scoring](docs/guides/openness-spectrum.md),
[gap analysis](docs/guides/gap-analysis.md), and [query conventions](docs/guides/queries.md).
See [AGENTS.md](AGENTS.md) for agent-oriented project context.
---
**The public data + scoring behind the [Open Source AI Stack Gap Map](https://map.currentai.org/).**
