# Conway Conway powers [Bldrs Share](https://github.com/bldrs-ai/Share), bringing high-quality, precision CAD to the web. This cutting-edge CAD engine, designed specifically for IFC and STEP formats, offers advanced geometric representation, enabling teams to open and visualize intricate models with exceptional accuracy and speed. Conway includes two major subcomponents: - **[IFC-gen](https://github.com/bldrs-ai/conway/tree/main/src/ifc/ifc4_gen)**, a mostly autogenerated TypeScript framework (~400kloc) for full API coverage parsing of the IFC 2x3, 4 compliant `*.ifc` files, and initial support for [STEP AP2xx](https://en.wikipedia.org/wiki/ISO_10303-21) `*.step` files to support Automotive and 3D-printing applications. This is based on original work by [hypar-io/IFC-gen](https://github.com/hypar-io/IFC-gen), further developed by bldrs-ai for Conway. The runtime is fully open-source in this project. Please contact us for full access to our generation pipeline. - **[conway-geom](https://github.com/bldrs-ai/conway-geom) WASM core**, bldrs-ai’s rewrite of [web-ifc](https://github.com/ThatOpen/engine_web-ifc), engineered for high-performance and to support the full suite of open CAD standards within the IFC and STEP families. ## Getting Started ### Codex Setup 1. Ignore the below and refer to AGENTS.md. ### Windows Setup 1. [Install MinGW-64](https://github.com/msys2/msys2-installer/releases/download/2022-06-03/msys2-x86_64-20220603.exe) and add ```g++.exe``` location to your PATH variable. ### MacOS Setup 1. Install the `gmake` and `node` dependencies via Homebrew (```brew install gmake node```). ### EMSDK Setup 1. Clone the [EMSDK](https://github.com/emscripten-core/emsdk) repo and add it to your path (see their instructions) 2. Conway is using `3.1.72` ``` > cd $EMSDK > ./emsdk install 3.1.72 > ./emsdk activate 3.1.72 > cd $CONWAY conway> emcc -v emcc (Emscripten gcc/clang-like replacement + linker emulating GNU ld) 3.1.72 (437140d149d9c977ffc8b09dbaf9b0f5a02db190) ... ``` ### Initial Build Clone the Conway repository, then in the root directory of the repository: ``` # Make sure EMSDK environment is set up. yarn setup yarn build yarn test ``` ### Example Uses You can now load your IFC files. From the Conway root: 1. ```yarn browser model.ifc``` 2. ```yarn validator model.ifc "IFCWINDOW.OverallHeight <= 1500"``` See the full example docs at [Browser.md](examples/Browser.md) and [Validator.md](examples/Validator.md) ## Development Update your client with changes since your last sync: ``` git pull yarn setup ``` For the full build of both conway (TypeScript) and conway-geom (WASM subproject): ``` yarn build ``` Build just conway, not conway-geom, e.g. for updating just the Conway API or tools: ``` yarn build-incremental ``` For a full, clean rebuild: ``` yarn build-rebuild ``` You can also run the tests with jest: ``` yarn test ``` And finally, using the watch functionality, you can also have the code automatically rebuild on change and also re-run the tests using: ``` yarn build-test-watch ``` # IFC Parser Console Test Application Conway has a test application for parsing IFC step files to see the performance and included entity types at src/core/ifc/ifc_command_line_main.ts. You can set up an alias to reference the latest package or build from source and use yarn cli: ``` alias conway='yarn cli' OR alias conway='npx --package=@bldrs-ai/conway@latest exec cli' ``` It can be run with: ``` conway [ifc file path] # To output geometry conway -g [ifc file path] # Use -m 1024 for larger files ``` ### CLI Geometry Output Options You can now output various geometry formats using the CLI: ```bash conway [ifc file path] [options] ``` **Examples:** - Output all geometry (default GLTF + GLB): ```bash conway index.ifc --geometry ``` - Output only GLTF: ```bash conway index.ifc --geometry --gltf ``` - Output only GLB: ```bash conway index.ifc --geometry --glb ``` - Output GLTF with Draco compression: ```bash conway index.ifc --geometry --gltf-draco ``` - Output GLB with Draco compression: ```bash conway index.ifc --geometry --glb-draco ``` - Run geometry processing without saving output files: ```bash conway index.ifc --geometry --nooutput ``` You can also combine flags as needed. For example: ```bash conway index.ifc --geometry --gltf-draco --glb-draco ``` Run `conway --help` for the full list of available flags and options. The included index.ifc in the repo is recommended for testing. # Profiling WASM Builds in Node Profiling Conway, including building a Conway-Geom WASM binary with DWARF information and generating a flame graph with WASM symbols, is possible via the following steps: 1. Run *build-profile-conway_geom* from Conway's package.json 2. Profile your app: ``` node --prof --experimental-specifier-resolution=node ./compiled/src/ifc/ifc_command_line_main.js -g ``` 3. An isolate*.log file will be generated. Run: ``` node --prof-process --preprocess -j isolate*.log > v8.json # generate a V8 log ``` 4. Go to https://mapbox.github.io/flamebearer/ and drop the log file to see a detailed flame graph. # Problems with renaming in GIT merges Because of the large number of files in conway that are code changes sometimes causing large modifications in merges, especially if generation locations are changed, it's sometimes necessary to up the limit of the number of renames in the git config for merging. It can be done like so: ``` git config merge.renameLimit 99999 ``` You may also wish to use a low rename threshold no-commit merge strategy for some of these situations to increase likelyhood that files will be related in the merge process and to track some of the more complicated changes: ``` git merge -X rename-threshold=25 --no-commit ``` # CI and Testing Every PR is gated on two checks defined in `.github/workflows/build.yml`: | Job | What it does | |---|---| | `build` | `yarn install`, WASM + TS compile (WASM cached on the `conway-geom` submodule SHA), `yarn test`, `yarn lint`. | | `run-ifc-regression` | `needs: build`. Reuses the same WASM cache. Runs the regression batch against the pinned `test-models` tag, posts a per-PR comment with `failed.csv` / `errors.csv` / perf summaries, and uploads the candidate npm tarball + `perf.csv` as workflow artifacts. | A merge to `main` re-runs those two jobs and then chains into `auto-publish` (see [Releases](#releases) below). ## Regression batch The same batch the regression CI job runs can be invoked locally — see [regression/README.md](regression/README.md) for digest / verbose / batch modes and the catalog of model fixtures. The CI pinned tag is `TEST_MODELS_TAG` near the top of `build.yml`. ## Performance benchmarks **Tier 1 — Conway-only perf in CI (live).** Every regression run emits a `perf.csv` of `parseTimeMs / geometryTimeMs / totalTimeMs / rssMb / heapUsedMb / heapTotalMb` per model. The top-10 slowest are posted in the PR comment; the full CSV is uploaded as a workflow artifact. This piggybacks on the existing regression batch so cost is ~0 extra runner minutes. **Tier 2 — full headless-three perf (planned, #314).** A `perf-three` job on `push: main` that runs `scripts/benchmark.cjs` against a clone of [headless-three](https://github.com/bldrs-ai/headless-three), installing the candidate Conway tarball as H3's `@bldrs-ai/conway` dep. Captures PNG renders + per-model timings via H3's rendering server, including a parallel job for `test-models-private`. Tracked in #314. # Releases **Releases are continuous.** Every green merge to `main` auto-tags and publishes to npm at the default `latest` dist-tag. The version is `..` where: - `major` comes from `package.json` on `main` (only the first segment; the other two are recomputed on every release) - `PR` is the GitHub PR number that produced the merge commit - `commit` is `git rev-list HEAD --count` at the merge commit (the global commit position) So a merge of PR #321 at the 985th commit on main publishes as `1.321.985`. Each release is uniquely traceable to a PR and a commit. The auto-publish job lives in `.github/workflows/build.yml` and runs as `needs: [build, run-ifc-regression]` on `push: branches: [main]`. It parses the PR number from the merge commit message, stamps the computed version into `package.json` + `src/version/version.ts` in CI's working tree (not committed back), rebuilds, publishes to npm, and then tags the merge commit. **Auth:** npm Trusted Publishing via GitHub OIDC. A Trusted Publisher configured at npmjs.com on `@bldrs-ai/conway` is bound to this repo + `build.yml`. No long-lived `NPM_TOKEN` secret is used; the workflow gets a short-lived publish token per run via OIDC. ### Normal flow: ship a change 1. Open a PR with your change. CI runs `build` and `run-ifc-regression`. 2. Merge once both checks are green. 3. On main push, CI re-runs `build` + `run-ifc-regression`, then `auto-publish` tags and ships. Watch the workflow run in the Actions tab; the new version is on npm within ~5-10 min of the merge. ### Bumping major Edit the `version` field in `package.json` on a PR — only the first segment matters (the `PR` and `commit` parts are recomputed). For example, change `"version": "1.0.0"` to `"version": "2.0.0"` to start the `2.x.x` line. The first auto-publish after that lands ships `2..`. There is no minor bump — `PR` lives in that slot — so increasing sequential versions across the `1.x` line look like `1.300.x`, `1.301.x`, etc., as PRs land. ### Rolling into headless-three and Share The same flow applies to both — do **H3 first, then Share**: ``` cd $H3_DIR git fetch upstream # or origin if not on a fork git checkout -b conway- upstream/main # Edit package.json dep for @bldrs-ai/conway to "" yarn install yarn build && yarn test yarn serve # Smoke test the local candidate: load all sample models, load a local model, # exercise dialogs, etc. git add . && git commit -m "Upgrade conway from to " git push origin HEAD ``` Then: 1. Send PR for review. 2. On merge, Netlify auto-builds and deploys to prod; watch the deploy logs. 3. Smoke test prod (same checks as local). 4. Post in `#bot` or `#share`: "New Conway in prod" with a link to the changelog. ### Blessing a `stable` version After Share prod is verified on a given Conway version: ``` # Create the GitHub release from the auto-pushed tag gh release create --generate-notes # Promote the npm package to the stable dist-tag npm dist-tag add @bldrs-ai/conway@ stable ``` # Roadmap The CI / release pipeline is now continuous, but there are tracked follow-ups to deepen its coverage. Big items first. ### #314 — Performance benchmarks in CI **Tier 1 — Conway-only perf (done):** the regression batch now emits a per-model `perf.csv` (parse/geometry/total time + RSS/heap MB), piggybacking on the existing run so there's no extra runner cost. Top-10 slowest models appear in each PR comment; the full CSV uploads as an artifact. See "Performance benchmarks" above. **Tier 2 — full headless-three perf (next):** an end-to-end render-and-time job that runs `scripts/benchmark.cjs` against a clone of [headless-three](https://github.com/bldrs-ai/headless-three). To avoid the local `yarn link` toolchain, the job installs the candidate Conway tarball (produced by `run-ifc-regression`) as H3's `@bldrs-ai/conway` dep and pins `H3_TAG` in `build.yml`. Gated to `push: main` to keep PR runtime down while still exercising every release. A sibling job runs against `test-models-private` using `secrets.TEST_MODELS_PRIVATE_TOKEN`, never on PR events (so forks can't leak the secret), and uploads results as org-scoped artifacts. Delta vs. the previous release lands in the auto-publish summary. ### #315 — Bump pinned `TEST_MODELS_TAG` The regression batch in `build.yml` is pinned to `test-models@0.13.802`. If newer stable tags exist, bumping picks up coverage of more recent fixtures. The bump itself is a one-line change; the work is triaging whatever new diffs appear on a no-op PR run. ### #316 — CI waterfall Mostly done: `build → run-ifc-regression` is in place and shares the WASM cache. The only remaining piece is #314 above (the third leg of the waterfall).