continuityguard-cli - npm Package Compare versions

Comparing version 0.1.2 to 0.1.3

dist/cli.js

@@ -16,2 +16,4 @@ #!/usr/bin/env node
 import { resolve } from 'node:path';
+import { realpathSync } from 'node:fs';
+import { pathToFileURL } from 'node:url';
 import { checkFfmpegAvailable, buildMissingFfmpegMessage, extractFramesFromDirectory, cleanupFrames, listClips, } from './ingest/ffmpeg.js';
@@ -148,4 +150,23 @@ import { scoreConsistency, CONSISTENCY_SIMILARITY_THRESHOLD, } from './score/consistency.js';
    (see vitest.config.ts) while still unit-testing runScan/createProgram
-   directly. */
-if (process.argv[1] && import.meta.url === `file://${process.argv[1]}`) {
+   directly.
+   A straight `import.meta.url === file://${process.argv[1]}` comparison
+   breaks whenever this file is invoked through a symlink -- which is
+   exactly how npm wires up a global/`bin` install (e.g. `npm install -g
+   continuityguard-cli`, or an `npx` run): argv[1] stays the symlink path
+   (e.g. .../bin/continuityguard), while import.meta.url resolves through
+   the symlink to the real target file, so the two never match, the guard
+   silently evaluates false, and the CLI exits 0 having done nothing.
+   Resolving argv[1] to its real path before comparing fixes both the
+   symlinked and non-symlinked (direct `node dist/cli.js`) invocation. */
+function isDirectlyExecuted() {
+    if (!process.argv[1])
+        return false;
+    try {
+        return import.meta.url === pathToFileURL(realpathSync(process.argv[1])).href;
+    }
+    catch {
+        return false;
+    }
+}
+if (isDirectlyExecuted()) {
     createProgram().parseAsync(process.argv);
@@ -152,0 +173,0 @@ }

dist/cli.js.map

@@ -1,1 +0,1 @@
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package.json

 {
   "name": "continuityguard-cli",
-  "version": "0.1.2",
+  "version": "0.1.3",
   "description": "Free, local-first CLI that scores already-generated AI short-drama clips/frames for character-consistency and physics-plausibility problems before you waste render credits re-shooting a broken shot. Zero network calls, everything runs on your own machine.",
@@ -26,2 +26,5 @@ "keywords": [
   "author": "Rudrendu Paul",
+  "contributors": [
+    "Sourav Nandy"
+  ],
   "type": "module",
@@ -41,3 +44,3 @@ "main": "./dist/cli.js",
   "scripts": {
-    "build": "tsc -p tsconfig.build.json && node scripts/copy-assets.mjs",
+    "build": "tsc -p tsconfig.build.json && node scripts/copy-assets.mjs && chmod +x dist/cli.js",
     "dev": "tsx src/cli.ts",
@@ -44,0 +47,0 @@ "lint": "eslint . --max-warnings 0",

README.md

@@ -14,6 +14,3 @@ # ContinuityGuard
 
-<!-- TODO: record a real terminal-recording demo (e.g. via `vhs`) showing
-     `node dist/cli.js scan src/score/testdata/clips` end to end and embed
-     it here as demo.gif. No asset exists in this repo yet, so nothing is
-     linked here rather than pointing at a file that doesn't exist. -->
+![Terminal recording of installing ContinuityGuard from source (npm install, npm run build) and running its first scan against the bundled fixture clips, showing the character-consistency and physics-plausibility flags in the human-readable report](docs/demo.gif)
 
@@ -25,8 +22,7 @@ AI short-drama generation is having a real moment, and every title is a stack of individually generated shots. Generation models still drift: a character's face shifts slightly between cuts, or a motion jumps in a way that reads as physically wrong the moment a human watches it. Catching that after render is expensive. ContinuityGuard scans a folder of already-generated clips or frames from any pipeline and flags the shots worth a second look before you commit to a re-render.
 Two independent, equally first-class distributions ship the same scoring
-logic and the same bundled MobileNetV2 ONNX model. **Honest status as of
-this writing:** the Python package is published to PyPI; the TypeScript/
-npm package is not yet published to the npm registry (the npm registry
-itself has no `continuityguard-cli` entry today).
+logic and the same bundled MobileNetV2 ONNX model. Both are published and
+installable today: the Python package on PyPI, and the TypeScript/npm
+package on the npm registry.
 
-**Python, published today:**
+**Python:**
 
@@ -40,9 +36,14 @@ ```bash
 
-**TypeScript/npm, install from source for now:**
+**TypeScript/npm:**
 
 ```bash
-git clone https://github.com/RudrenduPaul/ContinuityGuard.git && cd ContinuityGuard && npm install && npm run build
+npm install -g continuityguard-cli
 ```
 
-That's a real, freshly-run install: on this machine it took `npm install` about 2.5 seconds and `npm run build` about 0.7 seconds, with 0 vulnerabilities reported by `npm audit`. Once built, run the CLI directly with `node dist/cli.js scan <directory>`, or `npm link` it locally to get the `continuityguard` command on your `PATH`. This section will drop the "install from source" instructions in favor of a plain `npm install` the day the npm package is actually published -- tracked in [`CHANGELOG.md`](CHANGELOG.md).
+That puts the `continuityguard` command on your `PATH` -- run it with
+`continuityguard scan <directory>`. To build from source instead (for
+local development or to track `main`), clone the repo and run `npm
+install && npm run build`, then run the CLI with `node dist/cli.js scan
+<directory>`, or `npm link` it locally to get the `continuityguard`
+command from your working copy.
 
@@ -110,2 +111,4 @@ ## Table of Contents
 
+![Terminal recording of running node dist/cli.js scan src/score/testdata/clips --json, printing the full machine-readable JSON report with per-shot flags, thresholds, and scan metadata to stdout](docs/usage.gif)
+
 ## Quickstart
@@ -179,3 +182,2 @@
 - **Requires a system `ffmpeg` install.** ContinuityGuard checks for it at startup and prints the exact install command for your OS if it's missing (for example `brew install ffmpeg` on macOS, `apt install ffmpeg` on Debian/Ubuntu). It does not bundle a static ffmpeg binary in v0.1. A bundled per-platform build would be materially larger than this project's own dependency footprint and would inherit ffmpeg's own shifting LGPL/GPL licensing terms depending on which codecs are compiled in. Depending on a system install keeps this package small and its licensing surface simple.
-- **The TypeScript/npm package is not published to npm yet.** Install from source (see "Install" above) until a registry release ships. The Python package, covering the same scoring logic and the same bundled model, is published (`pip install continuityguard-cli`) -- see [`python/README.md`](python/README.md).
 
@@ -225,3 +227,3 @@ ## How it compares
 **Is this on npm yet?**
-Not yet. Install from source for now (see "Install" above). A registry release will happen later, once there's a specific date to commit to. The Python package is on PyPI today (`pip install continuityguard-cli`), using the same scoring logic and the same bundled model -- see [`python/README.md`](python/README.md).
+Yes. `npm install -g continuityguard-cli` installs it today. The Python package is also on PyPI (`pip install continuityguard-cli`), using the same scoring logic and the same bundled model -- see [`python/README.md`](python/README.md).
 
@@ -234,2 +236,11 @@ **Will a big video-generation platform just build this into their product and make ContinuityGuard pointless?**
 
+**What platforms and Node versions does this run on?**
+`package.json` requires Node >=22 and lists no OS restriction. The native scoring dependency, `onnxruntime-node`, ships prebuilt binaries for macOS, Linux, and Windows. You also need a system `ffmpeg` install (checked at startup, with an OS-specific install command printed if it's missing). The Python distribution (`pip install continuityguard-cli`) needs Python >=3.9 and the same system `ffmpeg` requirement, and is classified `Operating System :: OS Independent`.
+
+**How does this compare to a face-embedding library like deepface instead of a generic ImageNet model?**
+Directly, they solve different layers of the same problem. `serengil/deepface` (MIT-licensed, actively maintained) is a dedicated face-verification and embedding library; wiring it into a scan pipeline yourself would likely give more accurate character-consistency scoring than ContinuityGuard's current generic MobileNetV2 embedding, especially on stylized content. ContinuityGuard's role isn't to out-perform a dedicated face-embedding library on embeddings alone: it's the packaged CLI on top, doing ffmpeg decoding, the physics-plausibility pass, and structured report output in one zero-network command. Swapping in a stronger embedding model later is an open, tracked improvement, not a claim already delivered in v0.1. See "How it compares" above for the fuller table.
+
+**Is this free to use commercially?**
+Yes. Everything in this repo is Apache 2.0, including the permissive patent grant that license carries. There's no separate commercial tier, no usage cap, and no license key. Attribution and the license notice requirements of Apache 2.0 still apply, same as any Apache-licensed dependency you'd pull into a commercial project.
+
 ## Contributing
@@ -236,0 +247,0 @@

New alerts

Filesystem access

Supply chain risk

Accesses the file system, and could potentially read sensitive data.

Improved metrics

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14365604

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Number of lines in readme file

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No dependency changes