David Snelling
563b983fcc
- Added new scripts under `brainy-models-package/scripts`:
- **`compress-models.js`**: Implements model compression with float16 and int8 precision to create optimized variants of Universal Sentence Encoder models.
- **`download-full-models.js`**: Downloads the complete Universal Sentence Encoder model for offline usage.
- **`download-model.js`**: Downloads reference files for TensorFlow Hub-based Universal Sentence Encoder.
- Introduced a demonstration script:
- **`demo-optional-model-bundling.js`**: Highlights the solution of bundling models to eliminate network dependency, ensuring reliability and offline capability.
- Key Features:
- **Compression**:
- Reduced model size with float16 (balanced precision and size) and int8 (low-memory environments) options.
- Generated compression summaries for quick insights into model variants and saved space.
- **Offline Reliability**:
- Bundled versions eliminate first-load delays, network dependencies, and failures.
- Ensures rapid initialization in offline and memory-constrained scenarios.
- **Dynamic Optimization**:
- Tailored optimization profiles for various use cases: general, low-memory, and high-performance.
- **Demonstration and Documentation**:
- Comprehensive demo showcasing benefits of bundled models over online loading.
- Examples for usage, testing, and integration with Brainy.
**Purpose**: Introduce essential scripts and tools to enable efficient, offline-ready model usage, streamlining the embedding workflow while ensuring reliability in production and resource-constrained environments.
64 lines
1.6 KiB
JSON
64 lines
1.6 KiB
JSON
{
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"name": "@soulcraft/brainy-models",
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"version": "1.0.0",
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"description": "Pre-bundled TensorFlow models for maximum reliability with Brainy vector database",
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"main": "dist/index.js",
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"module": "dist/index.js",
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"types": "dist/index.d.ts",
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"type": "module",
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"engines": {
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"node": ">=18.0.0"
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},
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"scripts": {
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"prebuild": "npm run download-models",
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"build": "tsc",
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"download-models": "node scripts/download-full-models.js",
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"compress-models": "node scripts/compress-models.js",
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"test": "node test/test-models.js",
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"prepare": "npm run build",
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"pack": "npm pack"
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},
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"keywords": [
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"tensorflow",
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"models",
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"universal-sentence-encoder",
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"embeddings",
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"brainy",
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"vector-database",
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"offline",
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"bundled"
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],
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"author": "David Snelling (david@soulcraft.com)",
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"license": "MIT",
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"private": false,
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"publishConfig": {
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"access": "public"
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},
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"homepage": "https://github.com/soulcraft-research/brainy",
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"bugs": {
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"url": "https://github.com/soulcraft-research/brainy/issues"
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},
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"repository": {
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"type": "git",
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"url": "git+https://github.com/soulcraft-research/brainy.git",
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"directory": "brainy-models-package"
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},
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"files": [
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"dist/",
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"models/",
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"README.md",
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"LICENSE"
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],
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"dependencies": {
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"@tensorflow/tfjs": "^4.22.0",
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"@tensorflow/tfjs-node": "^4.22.0",
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"@tensorflow-models/universal-sentence-encoder": "^1.3.3"
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},
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"devDependencies": {
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"typescript": "^5.4.5",
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"@types/node": "^20.11.30"
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},
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"peerDependencies": {
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"@soulcraft/brainy": ">=0.33.0"
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}
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}
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