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GSD-Task: S02/T02
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jlightner 2026-03-26 06:46:20 +00:00
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.gsd/milestones/M003/slices/S02/S02-PLAN.md
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- Estimate: 45m - Estimate: 45m
- Files: docker/Dockerfile.app, docker/nginx.conf, docker-compose.yml - Files: docker/Dockerfile.app, docker/nginx.conf, docker-compose.yml
- Verify: docker compose build && docker compose up -d && sleep 12 && docker compose ps && curl -sf http://localhost:8000/engine/health && curl -sf http://localhost:3000/ | head -c 100 && curl -sf http://localhost:3000/engine/health && docker compose down - Verify: docker compose build && docker compose up -d && sleep 12 && docker compose ps && curl -sf http://localhost:8000/engine/health && curl -sf http://localhost:3000/ | head -c 100 && curl -sf http://localhost:3000/engine/health && docker compose down
- [ ] **T02: Rewrite README.md with project overview, quick start, API reference, and usage docs** — Replace the placeholder README with comprehensive documentation covering: what Kerf is, quick start with Docker Compose, engine API reference (all 4 endpoints with request/response examples), font system explanation, preset system, engine standalone usage, repository structure, and known limitations. - [x] **T02: Rewrote README.md with 8 sections: quick start, repo structure, all 4 API endpoints with parameter tables and curl examples, preset table, font system, standalone usage, dev setup, and known limitations** — Replace the placeholder README with comprehensive documentation covering: what Kerf is, quick start with Docker Compose, engine API reference (all 4 endpoints with request/response examples), font system explanation, preset system, engine standalone usage, repository structure, and known limitations.
**Content outline:** **Content outline:**
1. Project title + one-paragraph description 1. Project title + one-paragraph description

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---
id: T02
parent: S02
milestone: M003
provides: []
requires: []
affects: []
key_files: ["README.md"]
key_decisions: ["Documented all four engine endpoints with full parameter tables and curl examples", "Included preset comparison table with mode, epsilon, and usage notes for all 5 presets"]
patterns_established: []
drill_down_paths: []
observability_surfaces: []
duration: ""
verification_result: "Ran task verification: grep -c '^## ' README.md confirms 8 H2 sections (≥6 required), grep checks confirm 'docker compose up', '/engine/trace', '/engine/simplify', '/engine/presets', and '/engine/health' are all present. All checks passed with exit code 0."
completed_at: 2026-03-26T06:46:18.173Z
blocker_discovered: false
---
# T02: Rewrote README.md with 8 sections: quick start, repo structure, all 4 API endpoints with parameter tables and curl examples, preset table, font system, standalone usage, dev setup, and known limitations
> Rewrote README.md with 8 sections: quick start, repo structure, all 4 API endpoints with parameter tables and curl examples, preset table, font system, standalone usage, dev setup, and known limitations
## What Happened
---
id: T02
parent: S02
milestone: M003
key_files:
- README.md
key_decisions:
- Documented all four engine endpoints with full parameter tables and curl examples
- Included preset comparison table with mode, epsilon, and usage notes for all 5 presets
duration: ""
verification_result: passed
completed_at: 2026-03-26T06:46:18.181Z
blocker_discovered: false
---
# T02: Rewrote README.md with 8 sections: quick start, repo structure, all 4 API endpoints with parameter tables and curl examples, preset table, font system, standalone usage, dev setup, and known limitations
**Rewrote README.md with 8 sections: quick start, repo structure, all 4 API endpoints with parameter tables and curl examples, preset table, font system, standalone usage, dev setup, and known limitations**
## What Happened
Read all source files (routes.py, preset JSONs, fontService.ts, Dockerfiles, docker-compose.yml) to extract accurate API signatures, parameter defaults, preset configurations, and bundled font metadata. Wrote a comprehensive 253-line README.md replacing the placeholder with: project description, Docker Compose quick start, repository structure tree, engine API reference documenting all 4 endpoints with full parameter tables and curl examples, preset comparison table with all 5 presets, font system explanation, standalone engine usage, development setup for engine and app, and known limitations.
## Verification
Ran task verification: grep -c '^## ' README.md confirms 8 H2 sections (≥6 required), grep checks confirm 'docker compose up', '/engine/trace', '/engine/simplify', '/engine/presets', and '/engine/health' are all present. All checks passed with exit code 0.
## Verification Evidence
| # | Command | Exit Code | Verdict | Duration |
|---|---------|-----------|---------|----------|
| 1 | `grep -c '^## ' README.md | xargs test 6 -le && grep -q 'docker compose up' README.md && grep -q '/engine/trace' README.md && grep -q '/engine/simplify' README.md && grep -q '/engine/presets' README.md && grep -q '/engine/health' README.md && echo 'README OK'` | 0 | ✅ pass | 50ms |
## Deviations
None.
## Known Issues
None.
## Files Created/Modified
- `README.md`
## Deviations
None.
## Known Issues
None.

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{ {
"version": 1, "version": 1,
"exported_at": "2026-03-26T06:43:57.678Z", "exported_at": "2026-03-26T06:46:18.213Z",
"milestones": [ "milestones": [
{ {
"id": "M001", "id": "M001",
@ -1677,19 +1677,24 @@
"milestone_id": "M003", "milestone_id": "M003",
"slice_id": "S02", "slice_id": "S02",
"id": "T02", "id": "T02",
"title": "Rewrite README.md with project overview, quick start, API reference, and usage docs", "title": "Rewrote README.md with 8 sections: quick start, repo structure, all 4 API endpoints with parameter tables and curl examples, preset table, font system, standalone usage, dev setup, and known limitations",
"status": "pending", "status": "complete",
"one_liner": "", "one_liner": "Rewrote README.md with 8 sections: quick start, repo structure, all 4 API endpoints with parameter tables and curl examples, preset table, font system, standalone usage, dev setup, and known limitations",
"narrative": "", "narrative": "Read all source files (routes.py, preset JSONs, fontService.ts, Dockerfiles, docker-compose.yml) to extract accurate API signatures, parameter defaults, preset configurations, and bundled font metadata. Wrote a comprehensive 253-line README.md replacing the placeholder with: project description, Docker Compose quick start, repository structure tree, engine API reference documenting all 4 endpoints with full parameter tables and curl examples, preset comparison table with all 5 presets, font system explanation, standalone engine usage, development setup for engine and app, and known limitations.",
"verification_result": "", "verification_result": "Ran task verification: grep -c '^## ' README.md confirms 8 H2 sections (≥6 required), grep checks confirm 'docker compose up', '/engine/trace', '/engine/simplify', '/engine/presets', and '/engine/health' are all present. All checks passed with exit code 0.",
"duration": "", "duration": "",
"completed_at": null, "completed_at": "2026-03-26T06:46:18.173Z",
"blocker_discovered": false, "blocker_discovered": false,
"deviations": "", "deviations": "None.",
"known_issues": "", "known_issues": "None.",
"key_files": [], "key_files": [
"key_decisions": [], "README.md"
"full_summary_md": "", ],
"key_decisions": [
"Documented all four engine endpoints with full parameter tables and curl examples",
"Included preset comparison table with mode, epsilon, and usage notes for all 5 presets"
],
"full_summary_md": "---\nid: T02\nparent: S02\nmilestone: M003\nkey_files:\n - README.md\nkey_decisions:\n - Documented all four engine endpoints with full parameter tables and curl examples\n - Included preset comparison table with mode, epsilon, and usage notes for all 5 presets\nduration: \"\"\nverification_result: passed\ncompleted_at: 2026-03-26T06:46:18.181Z\nblocker_discovered: false\n---\n\n# T02: Rewrote README.md with 8 sections: quick start, repo structure, all 4 API endpoints with parameter tables and curl examples, preset table, font system, standalone usage, dev setup, and known limitations\n\n**Rewrote README.md with 8 sections: quick start, repo structure, all 4 API endpoints with parameter tables and curl examples, preset table, font system, standalone usage, dev setup, and known limitations**\n\n## What Happened\n\nRead all source files (routes.py, preset JSONs, fontService.ts, Dockerfiles, docker-compose.yml) to extract accurate API signatures, parameter defaults, preset configurations, and bundled font metadata. Wrote a comprehensive 253-line README.md replacing the placeholder with: project description, Docker Compose quick start, repository structure tree, engine API reference documenting all 4 endpoints with full parameter tables and curl examples, preset comparison table with all 5 presets, font system explanation, standalone engine usage, development setup for engine and app, and known limitations.\n\n## Verification\n\nRan task verification: grep -c '^## ' README.md confirms 8 H2 sections (≥6 required), grep checks confirm 'docker compose up', '/engine/trace', '/engine/simplify', '/engine/presets', and '/engine/health' are all present. All checks passed with exit code 0.\n\n## Verification Evidence\n\n| # | Command | Exit Code | Verdict | Duration |\n|---|---------|-----------|---------|----------|\n| 1 | `grep -c '^## ' README.md | xargs test 6 -le && grep -q 'docker compose up' README.md && grep -q '/engine/trace' README.md && grep -q '/engine/simplify' README.md && grep -q '/engine/presets' README.md && grep -q '/engine/health' README.md && echo 'README OK'` | 0 | ✅ pass | 50ms |\n\n\n## Deviations\n\nNone.\n\n## Known Issues\n\nNone.\n\n## Files Created/Modified\n\n- `README.md`\n",
"description": "Replace the placeholder README with comprehensive documentation covering: what Kerf is, quick start with Docker Compose, engine API reference (all 4 endpoints with request/response examples), font system explanation, preset system, engine standalone usage, repository structure, and known limitations.\n\n**Content outline:**\n1. Project title + one-paragraph description\n2. Quick Start — `docker compose up`, then visit localhost:3000\n3. Repository Structure — engine/, app/, docker/ directories\n4. Engine API Reference — document all 4 endpoints:\n - `GET /engine/health` — healthcheck\n - `GET /engine/presets` — list available presets\n - `POST /engine/trace` — raster-to-vector with preprocessing+vectorization+postprocessing\n - `POST /engine/simplify` — SVG simplification with optional DXF export (units, scale_factor)\n5. Font System — bundled fonts (Lato, OpenSans, Roboto), text-to-path conversion\n6. Presets — 5 built-in presets (sign, patch, stencil, detailed, custom), how they work\n7. Engine Standalone Usage — running engine independently, Docker image, API examples\n8. Development — local setup for engine (Python venv) and app (npm), dev proxy setup\n9. Known Limitations\n\n**Sources for API details:** `engine/api/routes.py` for endpoint signatures, `engine/presets/*.json` for preset list, `app/src/utils/fontService.ts` for font system.", "description": "Replace the placeholder README with comprehensive documentation covering: what Kerf is, quick start with Docker Compose, engine API reference (all 4 endpoints with request/response examples), font system explanation, preset system, engine standalone usage, repository structure, and known limitations.\n\n**Content outline:**\n1. Project title + one-paragraph description\n2. Quick Start — `docker compose up`, then visit localhost:3000\n3. Repository Structure — engine/, app/, docker/ directories\n4. Engine API Reference — document all 4 endpoints:\n - `GET /engine/health` — healthcheck\n - `GET /engine/presets` — list available presets\n - `POST /engine/trace` — raster-to-vector with preprocessing+vectorization+postprocessing\n - `POST /engine/simplify` — SVG simplification with optional DXF export (units, scale_factor)\n5. Font System — bundled fonts (Lato, OpenSans, Roboto), text-to-path conversion\n6. Presets — 5 built-in presets (sign, patch, stencil, detailed, custom), how they work\n7. Engine Standalone Usage — running engine independently, Docker image, API examples\n8. Development — local setup for engine (Python venv) and app (npm), dev proxy setup\n9. Known Limitations\n\n**Sources for API details:** `engine/api/routes.py` for endpoint signatures, `engine/presets/*.json` for preset list, `app/src/utils/fontService.ts` for font system.",
"estimate": "30m", "estimate": "30m",
"files": [ "files": [
@ -2420,6 +2425,17 @@
"verdict": "✅ pass", "verdict": "✅ pass",
"duration_ms": 3000, "duration_ms": 3000,
"created_at": "2026-03-26T06:43:57.639Z" "created_at": "2026-03-26T06:43:57.639Z"
},
{
"id": 55,
"task_id": "T02",
"slice_id": "S02",
"milestone_id": "M003",
"command": "grep -c '^## ' README.md | xargs test 6 -le && grep -q 'docker compose up' README.md && grep -q '/engine/trace' README.md && grep -q '/engine/simplify' README.md && grep -q '/engine/presets' README.md && grep -q '/engine/health' README.md && echo 'README OK'",
"exit_code": 0,
"verdict": "✅ pass",
"duration_ms": 50,
"created_at": "2026-03-26T06:46:18.174Z"
} }
] ]
} }

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README.md
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# Kerf # Kerf
Modular raster-to-vector conversion engine + 2D sign/patch design canvas. Modular raster-to-vector conversion engine paired with a 2D sign and patch design canvas. Upload a raster image (PNG, JPEG, BMP), trace it into clean vector paths using Potrace or VTracer, and export as SVG or DXF — ready for CNC routers, vinyl cutters, laser engravers, and embroidery machines.
## Quick Start
```bash
docker compose up -d
```
Once both services are healthy:
- **Web App** → [http://localhost:3000](http://localhost:3000)
- **Engine API** → [http://localhost:8000/engine/health](http://localhost:8000/engine/health)
- **Interactive API Docs** → [http://localhost:8000/docs](http://localhost:8000/docs)
Check service health:
```bash
docker compose ps
```
Tear down:
```bash
docker compose down
```
## Repository Structure ## Repository Structure
``` ```
engine/ — Kerf Engine (standalone API, Python/FastAPI) engine/ Kerf Engine — standalone Python/FastAPI vectorization API
app/ — Kerf App frontend (React) [future] api/ API route definitions
server/ — Kerf App backend API [future] pipeline/ Preprocessing, vectorization, and post-processing stages
docker/ — Dockerfiles and compose configs [future] output/ SVG, DXF, and JSON output generators
presets/ Built-in preset configurations (JSON)
tests/ Engine test suite (pytest)
app/ Kerf App — React/TypeScript design canvas (Vite + Konva)
src/ Application source code
public/ Static assets including bundled fonts
docker/ Dockerfiles and nginx configuration
Dockerfile.engine Multi-stage build for the engine (Python 3.11)
Dockerfile.app Multi-stage build for the app (Node 22 → nginx 1.27)
nginx.conf SPA routing + /engine reverse-proxy
docker-compose.yml Full-stack orchestration with healthchecks
``` ```
## Kerf Engine ## Engine API Reference
The engine is a self-contained FastAPI service that accepts raster images and returns clean vector output (SVG, DXF). The engine exposes four endpoints under the `/engine` prefix. All endpoints accept and return JSON unless otherwise noted.
### Quick Start ### `GET /engine/health`
Healthcheck endpoint for container orchestration.
**Response:**
```json
{ "status": "ok" }
```
### `GET /engine/presets`
List all available presets and their parameter values.
**Response:**
```json
{
"presets": {
"sign": { "name": "sign", "description": "Metal signage, bold text cutouts", "..." : "..." },
"patch": { "name": "patch", "description": "Embroidered patches, fabric cutting", "..." : "..." }
}
}
```
### `POST /engine/trace`
Convert a raster image to vector output through the full preprocessing → vectorization → post-processing pipeline.
**Content-Type:** `multipart/form-data`
| Field | Type | Default | Description |
|-----------------|--------|------------|-------------|
| `file` | file | (required) | Raster image (PNG, JPEG, BMP) |
| `mode` | string | from preset | Vectorization engine: `potrace` or `vtracer` |
| `output_format` | string | `svg` | Output format: `svg`, `dxf`, or `json` |
| `preset` | string | `sign` | Preset name (see [Presets](#presets)) |
| `params` | string | `{}` | JSON string of parameter overrides |
**Example — trace with the sign preset:**
```bash
curl -X POST http://localhost:8000/engine/trace \
-F file=@logo.png \
-F preset=sign \
-F output_format=svg
```
**Example — trace with custom parameters:**
```bash
curl -X POST http://localhost:8000/engine/trace \
-F file=@photo.jpg \
-F preset=detailed \
-F mode=vtracer \
-F 'params={"filter_speckle": 4, "epsilon": 0.3}'
```
**Response (SVG/JSON formats):**
```json
{
"output": "<svg ...>...</svg>",
"format": "svg",
"metadata": {
"format": "svg",
"path_count": 12,
"node_count_total": 483,
"open_paths": 0,
"island_count": 2,
"warnings": [],
"processing_ms": 142.57
}
}
```
**Response (DXF format):** Raw DXF bytes with `Content-Type: application/dxf` and metadata in the `X-Kerf-Metadata` response header.
### `POST /engine/simplify`
Simplify an existing SVG using Ramer–Douglas–Peucker path simplification. Optionally export to DXF with unit and scale control.
**Content-Type:** `multipart/form-data`
| Field | Type | Default | Description |
|-----------------|--------|------------|-------------|
| `file` | file | (required) | SVG file to simplify |
| `epsilon` | float | `1.0` | RDP simplification tolerance (higher = fewer points) |
| `output_format` | string | `svg` | Output format: `svg`, `dxf`, or `json` |
| `units` | string | none | DXF unit metadata: `inches` or `mm` |
| `scale_factor` | float | `1.0` | DXF coordinate scale factor |
**Example — simplify and export to DXF in millimeters:**
```bash
curl -X POST http://localhost:8000/engine/simplify \
-F file=@drawing.svg \
-F epsilon=2.0 \
-F output_format=dxf \
-F units=mm \
-F scale_factor=25.4
```
## Presets
Presets bundle tuned parameter sets for each pipeline stage — preprocessing, vectorization, and post-processing — optimized for specific use cases.
| Preset | Description | Mode | Epsilon | Notes |
|------------|------------------------------------|----------|---------|-------|
| `sign` | Metal signage, bold text cutouts | potrace | 2.5 | Aggressive denoising, auto-close enabled |
| `patch` | Embroidered patches, fabric cutting| potrace | 1.0 | Moderate smoothing, fine detail retention |
| `stencil` | Physical stencil cutting | potrace | 3.0 | Heavy simplification, fixed threshold at 128 |
| `detailed` | High-fidelity illustration work | potrace | 0.5 | Minimal smoothing, preserves fine curves |
| `custom` | All params exposed, no defaults | potrace | — | Pass all parameters explicitly via `params` |
Use the `params` field on `/engine/trace` to override any preset value. For example, to use the `sign` preset but switch to VTracer mode:
```bash
curl -X POST http://localhost:8000/engine/trace \
-F file=@image.png \
-F preset=sign \
-F 'params={"mode": "vtracer"}'
```
## Font System
The web app bundles three fonts for text-to-path conversion, enabling text elements to be converted to SVG outlines for cutting/engraving:
| Font | File |
|------------|-------------------------|
| Roboto | `Roboto-Regular.ttf` |
| Open Sans | `OpenSans-Regular.ttf` |
| Lato | `Lato-Regular.ttf` |
Fonts are parsed client-side using [opentype.js](https://opentype.js.org/) and converted to SVG path data with configurable font size and letter spacing. The conversion handles glyph positioning, coordinate system flipping, and path assembly — no server round-trip required.
## Engine Standalone Usage
The engine runs independently of the web app. Use it as a standalone API service or build just the engine Docker image:
**Docker (standalone):**
```bash
docker build -f docker/Dockerfile.engine -t kerf-engine .
docker run -p 8000:8000 kerf-engine
```
**Local development (Python):**
```bash ```bash
cd engine cd engine
python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]" pip install -e ".[dev]"
uvicorn main:app --host 0.0.0.0 --port 8000 uvicorn main:app --host 0.0.0.0 --port 8000 --reload
``` ```
API docs available at `http://localhost:8000/docs`. API docs are available at [http://localhost:8000/docs](http://localhost:8000/docs) (Swagger UI) and [http://localhost:8000/redoc](http://localhost:8000/redoc) (ReDoc).
## Development
### Engine (Python)
```bash
cd engine
python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"
# Run the API server with auto-reload
uvicorn main:app --host 0.0.0.0 --port 8000 --reload
# Run tests
pytest
```
System dependencies for pypotrace: `libpotrace-dev`, `libpotrace0`, `libagg-dev` (Debian/Ubuntu).
### App (React/TypeScript)
```bash
npm install
npm run dev --workspace=app
```
The Vite dev server proxies `/engine/*` requests to `http://localhost:8000` — start the engine first for full functionality.
### Full Stack (Docker Compose)
```bash
docker compose up --build
```
The app is served on port 3000 with nginx reverse-proxying `/engine/*` to the engine container.
## Known Limitations
- **Single-image processing** — the engine processes one image per request; batch endpoints are not yet available.
- **Binary vectorization only** — both Potrace and VTracer operate in binary (black/white) mode; color/multi-layer tracing is not supported.
- **No authentication** — the API is open; add a reverse proxy with auth for production deployments.
- **Font selection** — the app ships with three bundled fonts; custom font upload is not yet supported.
- **DXF fidelity** — DXF export covers basic polyline geometry; advanced CAD features (layers, blocks, hatches) are not included.