diff --git a/brainy-models-package/.versionrc.json b/brainy-models-package/.versionrc.json deleted file mode 100644 index 50d092cd..00000000 --- a/brainy-models-package/.versionrc.json +++ /dev/null @@ -1,38 +0,0 @@ -{ - "tagPrefix": "brainy-models-v", - "commitMessageFormat": "chore(brainy-models): release {{currentTag}}", - "types": [ - { - "type": "feat", - "section": "Features" - }, - { - "type": "fix", - "section": "Bug Fixes" - }, - { - "type": "chore", - "hidden": true - }, - { - "type": "docs", - "section": "Documentation" - }, - { - "type": "style", - "hidden": true - }, - { - "type": "refactor", - "section": "Code Refactoring" - }, - { - "type": "perf", - "section": "Performance Improvements" - }, - { - "type": "test", - "hidden": true - } - ] -} diff --git a/brainy-models-package/CHANGELOG.md b/brainy-models-package/CHANGELOG.md deleted file mode 100644 index 3dd75bd7..00000000 --- a/brainy-models-package/CHANGELOG.md +++ /dev/null @@ -1,113 +0,0 @@ -# Changelog - -All notable changes to this project will be documented in this file. See [standard-version](https://github.com/conventional-changelog/standard-version) for commit guidelines. - -## [1.0.0](https://github.com/soulcraft-research/brainy/compare/brainy-models-v0.7.0...brainy-models-v1.0.0) (2025-08-05) - - -### Features - -* add verb and noun metadata handling in storage adapters ([9778f1b](https://github.com/soulcraft-research/brainy/commit/9778f1bbf46de06bb71d87333f3861210558024e)) -* **auto-configuration:** implement automatic configuration system for optimal settings ([aa64f49](https://github.com/soulcraft-research/brainy/commit/aa64f490cbad98bc6c95c1f212b8f049d41aa32f)) -* **distributed:** add distributed mode with multi-instance coordination ([8e4b0ef](https://github.com/soulcraft-research/brainy/commit/8e4b0ef7d8b9c3a4de2b776adc25da3c0a7fc971)) -* **docs:** add comprehensive user guides and installation instructions for Brainy ([d4dafbf](https://github.com/soulcraft-research/brainy/commit/d4dafbf598a49c7b1b005f7773f14b47fe65bffa)) -* **docs:** add S3 migration guide for optimized data transfer strategies ([7b4c779](https://github.com/soulcraft-research/brainy/commit/7b4c7794f3a587e2038452ab0d2c908272cf9556)) -* **docs:** update README and add large-scale optimizations guide for v0.36.0 ([ae01bea](https://github.com/soulcraft-research/brainy/commit/ae01bea1aa5d7f3a042f67fa6123c17e59310d68)) -* **hnsw:** implement comprehensive large-scale search optimizations ([c39eee6](https://github.com/soulcraft-research/brainy/commit/c39eee624d40c4ee4d5112c26283c17b133dc3e1)) -* **pagination:** implement cursor-based pagination and enhance search caching ([0f538f3](https://github.com/soulcraft-research/brainy/commit/0f538f39ba7897d2efb0fadd39fc7218b1bbe72d)) -* **partitioning:** simplify partition strategies and enable auto-tuning of semantic clusters ([1015c33](https://github.com/soulcraft-research/brainy/commit/1015c33004c248dd45fdb9c37edc6b15ad95a5f8)) -* refactor verb storage to use HNSWVerb for improved performance ([75ccf0f](https://github.com/soulcraft-research/brainy/commit/75ccf0f7472f94cc7a76a9b64b377fb7bdc02624)) -* **safety:** enhance claude-commit with mandatory review and safety features ([c20cc39](https://github.com/soulcraft-research/brainy/commit/c20cc392620ebded69732c62a07295dc212de001)) -* **tools:** add claude-commit AI-powered git commit tool ([d05e320](https://github.com/soulcraft-research/brainy/commit/d05e320a52486c5b5620869940df5b7330fa1067)) -* **tools:** propagate safety features to all projects ([8854b37](https://github.com/soulcraft-research/brainy/commit/8854b3735fac75e695e76ec62edde2160c065f55)) -* **tools:** update feature description for clarity ([5e15dab](https://github.com/soulcraft-research/brainy/commit/5e15dabb54e9e5616cf49b759222a24734c58fbc)) - - -### Bug Fixes - -* **build:** resolve TypeScript compilation errors in optimization modules ([0e2bce1](https://github.com/soulcraft-research/brainy/commit/0e2bce19251f7ea5008695f058272ca4271805f8)) -* **core:** resolve TypeScript compilation errors and test failures ([67db734](https://github.com/soulcraft-research/brainy/commit/67db73461124c33bb6fc11cb5f8daf3ddbfd9f09)) -* **security:** resolve critical vulnerability in form-data dependency ([8450af5](https://github.com/soulcraft-research/brainy/commit/8450af5d9289391dd516d23779fb675ae81bf5f6)) -* **storage:** resolve pagination warnings and improve S3 adapter performance ([d7a1c1b](https://github.com/soulcraft-research/brainy/commit/d7a1c1bd27257522e0986e2e882eb169bc7e1d14)) -* **types:** add explicit ArrayBuffer type assertions for compression ([7196fe2](https://github.com/soulcraft-research/brainy/commit/7196fe2d6b756a4e9401cf87585db688145e46fe)) -* **types:** resolve remaining ArrayBuffer type issues in compression methods ([eb8c95e](https://github.com/soulcraft-research/brainy/commit/eb8c95ef3720afa52acc45af2c3dcc896d67decc)) - - -### Documentation - -* add comprehensive performance docs and rebrand to Zero-to-Smart™ ([80ca8e3](https://github.com/soulcraft-research/brainy/commit/80ca8e35d257723853d0f9d6c95f49937b71aceb)) -* add distributed deployment architecture and enhancement proposals ([4bb7a9f](https://github.com/soulcraft-research/brainy/commit/4bb7a9f431edaf85e782144057d77b4b20b16b44)) -* add guidelines for Conventional Commit format and structured commit messages ([f9a8595](https://github.com/soulcraft-research/brainy/commit/f9a859587802dfd294b2eaeefcf251f75a460db4)) -* add revised distributed implementation plan with practical phases ([e3978e5](https://github.com/soulcraft-research/brainy/commit/e3978e570dcee9b9c7757e75d3fe2c2f55cd99e4)) -* streamline README for better readability and user engagement ([2492fe4](https://github.com/soulcraft-research/brainy/commit/2492fe4f30099dc1b9f9cf0e435b83d5ffc34dce)) - -## [0.7.0](https://github.com/soulcraft-research/brainy/compare/brainy-models-v0.6.0...brainy-models-v0.7.0) (2025-08-02) - -## [0.6.0](https://github.com/soulcraft-research/brainy/compare/brainy-models-v0.5.0...brainy-models-v0.6.0) (2025-08-01) - -## 0.5.0 (2025-08-01) - - -### Features - -* **core, tests:** add standalone getStatistics function and improve storage configuration ([e5a9ede](https://github.com/soulcraft-research/brainy/commit/e5a9edea1b292e2b87d1ad043bb917f01f6366d9)) -* **core:** enhance addVerb functionality with auto-creation of missing nouns ([a0c4d48](https://github.com/soulcraft-research/brainy/commit/a0c4d48b4aa0b8e236c18f1b7afdc2e54801a142)) -* **demo, docs:** introduce threading test demos for browser and fallback, enhance threading documentation ([de627c5](https://github.com/soulcraft-research/brainy/commit/de627c5dfaff57a0abba6a4dc3b68bd52cb150e1)) -* **demo/CNAME:** add CNAME files for domain configuration ([a681ab7](https://github.com/soulcraft-research/brainy/commit/a681ab7cdd08d318111977cecd2ae7ef7262a3da)) -* **docs:** add WebSocket augmentation examples in README ([d7ff1b2](https://github.com/soulcraft-research/brainy/commit/d7ff1b2053779265521894d351a950f7903a5e64)) -* **docs:** update README to highlight new consolidated storage structure ([fbfcaeb](https://github.com/soulcraft-research/brainy/commit/fbfcaeb8d097c58a3127e68e9a7c06421cf5f468)) -* enhance `cli.ts` with updated typings and improved search interface ([4a23c97](https://github.com/soulcraft-research/brainy/commit/4a23c97d2a5f33a2d34f622014cf03e8350f8781)) -* **README:** add GPU acceleration and detailed performance optimizations ([da1fe27](https://github.com/soulcraft-research/brainy/commit/da1fe27e25851233a2a49eaaeec1dac9f9882d59)) -* reformat imports and exports for consistency and readability ([7de62f4](https://github.com/soulcraft-research/brainy/commit/7de62f4bbcdc91c88bb22e39e64c624219df8be4)) -* **scripts, project:** add comprehensive code style enforcement script and update style-related workflows ([5052bbc](https://github.com/soulcraft-research/brainy/commit/5052bbc0b713f2294b3e15de43e696b575320ae0)) -* **src/brainyData, src/utils:** enhance embedding efficiency with batch processing and initialize safeguards ([bba9a0c](https://github.com/soulcraft-research/brainy/commit/bba9a0c219c308f82821e46c44c49ef560ca2e39)) -* **src/hnsw:** add GPU acceleration for distance calculations and improve fallback handling ([a2ad5fa](https://github.com/soulcraft-research/brainy/commit/a2ad5fabdfe8e5de545c2a07cef2f08a667ebf5e)) -* **src/utils:** add GPU acceleration and improve threading for embeddings and distance calculations ([6a8d044](https://github.com/soulcraft-research/brainy/commit/6a8d044970b36976fc3ed5712d61bdbf774f7716)) -* **storage:** implement base, file system, and memory storage adapters ([8c5f17b](https://github.com/soulcraft-research/brainy/commit/8c5f17b1d96a84f996ad62ec4b1e1e56893dfcbc)) -* **tests:** add robust mock implementations and expand test coverage for S3 and OPFS storage ([f01a355](https://github.com/soulcraft-research/brainy/commit/f01a35598788b53a0294ecf9b91e47d166363846)) -* **tests:** replace old test scripts with updated test suite for storage and reporting ([68680db](https://github.com/soulcraft-research/brainy/commit/68680db2c660b34d5b4e4ee86d163f7723d328a4)) -* **types:** extend FileSystemHandle and optimize imports for consistency ([aff1483](https://github.com/soulcraft-research/brainy/commit/aff1483d4d84406039e301fa594889f99e19c9db)) - - -### Bug Fixes - -* handle optional `loggingConfig` in `getDefaultEmbeddingFunction` initialization ([d42596a](https://github.com/soulcraft-research/brainy/commit/d42596ad4730943cea60081ca71fea6ad2babd37)) -* **package.json:** update TensorFlow dependencies for optimized backend usage ([e000661](https://github.com/soulcraft-research/brainy/commit/e00066119ebeb336e4564d38b4ef67d9bfbefeb6)) -* prevent duplication of `ROOT_DIR` in file system storage initialization ([d495b95](https://github.com/soulcraft-research/brainy/commit/d495b95af836c124685f5cff8a59ed74a82b3dca)) -* **README, src/utils:** bump version to 0.9.11 ([fe4de2f](https://github.com/soulcraft-research/brainy/commit/fe4de2f7a00b3f1ec1dd0edd2deb434d510096c2)) -* **README:** correct formatting in custom domain configuration steps ([bba846a](https://github.com/soulcraft-research/brainy/commit/bba846ae230e86235b1321851eb06f298ca09170)) -* **src/augmentationPipeline:** remove redundant semicolons and enforce consistent formatting ([47ba4f4](https://github.com/soulcraft-research/brainy/commit/47ba4f4093a8a3ecc8f7fa28638322d7ee4ae740)) -* **src/augmentationPipeline:** remove unnecessary whitespace for formatting consistency ([99a8cbf](https://github.com/soulcraft-research/brainy/commit/99a8cbfe2c036a29076f1ebaf4e92b320a0cf427)) -* **src/augmentations:** enforce consistent formatting and improve code readability ([cacd179](https://github.com/soulcraft-research/brainy/commit/cacd1790dc6b29096187dac53309b83d89b2242d)) -* **src/brainyData:** enforce consistent formatting and improve code readability ([e884c58](https://github.com/soulcraft-research/brainy/commit/e884c5831003c7e0cae8260cd0d3d8cf72e7ef07)) -* **src/brainyData:** enforce consistent formatting and improve fallback mechanisms ([cabe0a3](https://github.com/soulcraft-research/brainy/commit/cabe0a3a08e4bfd5fddfe19a7dfb0f382d347103)) -* **src/index:** enforce consistent formatting and adjust code structure ([95be233](https://github.com/soulcraft-research/brainy/commit/95be23362af2665f4d2fed2657599980381434f2)) -* **src/storage:** enforce consistent formatting and improve code readability ([cbf025d](https://github.com/soulcraft-research/brainy/commit/cbf025dffb0ab5e8af211d7daadc057b5771d567)) -* **src/utils:** enforce consistent formatting and enhance worker script initialization ([bd123c4](https://github.com/soulcraft-research/brainy/commit/bd123c4bb91ddb6d30ee5ef240e1872affb5f795)) -* **src/utils:** enhance type definition and improve load function detection ([ef83af4](https://github.com/soulcraft-research/brainy/commit/ef83af4b556966949e9df24cdf524a49b1ccab29)) -* **src/utils:** improve readability of `findUSELoadFunction` parameters ([f946328](https://github.com/soulcraft-research/brainy/commit/f9463288234ff9cf6220db8443423df37651dc72)) -* **src/utils:** remove unused `sentenceEncoderModule` for cleanup ([e81979d](https://github.com/soulcraft-research/brainy/commit/e81979dc849d7c1cdb70eb02697d1ad76db31196)) - - -### Documentation - -* update Node.js version requirement to 23.0.0 in documentation ([920439f](https://github.com/soulcraft-research/brainy/commit/920439f611d1dba45e7bcb3915eea0df5507ac20)) - -## [0.4.0](https://github.com/soulcraft-research/brainy/compare/v0.1.0...v0.4.0) (2025-08-01) - - -### Changed - -* **release:** 0.2.0 [skip ci] ([c9ca141](https://github.com/soulcraft-research/brainy/commit/c9ca14146ba5376812823185e55fc8b38be3785c)) -* **release:** 0.3.0 [skip ci] ([437360c](https://github.com/soulcraft-research/brainy/commit/437360c2570632204cf951001aa7a0228479255d)) - -## [0.3.0](https://github.com/soulcraft-research/brainy/compare/v0.1.0...v0.3.0) (2025-08-01) - - -### Changed - -* **release:** 0.2.0 [skip ci] ([c9ca141](https://github.com/soulcraft-research/brainy/commit/c9ca14146ba5376812823185e55fc8b38be3785c)) - -## [0.2.0](https://github.com/soulcraft-research/brainy/compare/v0.1.0...v0.2.0) (2025-08-01) - -## [0.1.0](https://github.com/soulcraft-research/brainy/compare/v0.33.0...v0.1.0) (2025-08-01) diff --git a/brainy-models-package/CODE_OF_CONDUCT.md b/brainy-models-package/CODE_OF_CONDUCT.md deleted file mode 100644 index d4194421..00000000 --- a/brainy-models-package/CODE_OF_CONDUCT.md +++ /dev/null @@ -1,49 +0,0 @@ -# Contributor Covenant Code of Conduct - -## Our Pledge - -We as members, contributors, and leaders pledge to make participation in our -community a harassment-free experience for everyone, regardless of age, body -size, visible or invisible disability, ethnicity, sex characteristics, gender -identity and expression, level of experience, education, socio-economic status, -nationality, personal appearance, race, religion, or sexual identity -and orientation. - -We pledge to act and interact in ways that contribute to an open, welcoming, -diverse, inclusive, and healthy community. - -## Our Standards - -Examples of behavior that contributes to a positive environment for our -community include: - -* Demonstrating empathy and kindness toward other people -* Being respectful of differing opinions, viewpoints, and experiences -* Giving and gracefully accepting constructive feedback -* Accepting responsibility and apologizing to those affected by our mistakes, - and learning from the experience -* Focusing on what is best not just for us as individuals, but for the - overall community - -Examples of unacceptable behavior include: - -* The use of sexualized language or imagery, and sexual attention or - advances of any kind -* Trolling, insulting or derogatory comments, and personal or political attacks -* Public or private harassment -* Publishing others' private information, such as a physical or email - address, without their explicit permission -* Other conduct which could reasonably be considered inappropriate in a - professional setting - -## Enforcement - -Instances of abusive, harassing, or otherwise unacceptable behavior may be -reported to the project maintainers responsible for enforcement at -conduct@soulcraft.com. - -This Code of Conduct is adapted from the [Contributor Covenant][homepage], -version 2.0, available at -https://www.contributor-covenant.org/version/2/0/code_of_conduct.html. - -[homepage]: https://www.contributor-covenant.org diff --git a/brainy-models-package/CONTRIBUTING.md b/brainy-models-package/CONTRIBUTING.md deleted file mode 100644 index 3df49f51..00000000 --- a/brainy-models-package/CONTRIBUTING.md +++ /dev/null @@ -1,103 +0,0 @@ -# Contributing to @soulcraft/brainy-models - -Thank you for your interest in contributing to the Brainy Models package! This package provides pre-bundled TensorFlow models for the Brainy vector database. - -## Overview - -The `@soulcraft/brainy-models` package is part of the larger Brainy ecosystem. For general contribution guidelines, please refer to the main [Brainy Contributing Guide](https://github.com/soulcraft-research/brainy/blob/main/CONTRIBUTING.md). - -## Package-Specific Guidelines - -### Model Contributions - -When contributing to the models package, please consider: - -- **Model Quality**: Ensure models are properly tested and validated -- **Model Size**: Be mindful of package size impact (current package is ~25MB) -- **Compatibility**: Ensure models work with the target TensorFlow.js versions -- **Documentation**: Update README.md with new model information - -### Development Setup - -1. Fork and clone the main repository -2. Navigate to the models package: `cd brainy-models-package` -3. Install dependencies: `npm install` -4. Download models: `npm run download-models` -5. Build the package: `npm run build` -6. Run tests: `npm test` - -### Testing Models - -Before submitting changes: - -```bash -# Test model functionality -npm test - -# Test model compression -npm run compress-models - -# Verify package integrity -npm run pack -``` - -### Model Scripts - -The package includes several utility scripts: - -- `download-models` - Download the Universal Sentence Encoder model -- `compress-models` - Create optimized model variants -- `test` - Verify model functionality - -### Commit Guidelines - -Follow the same commit message conventions as the main Brainy project: - -- Use conventional commit format -- Keep first line under 50 characters -- Use imperative mood ("Add model" not "Added model") -- Reference issues where appropriate - -### Pull Request Process - -1. Ensure your changes don't break existing functionality -2. Update documentation if you're adding new models or features -3. Test model loading and embedding generation -4. Verify package size impact is acceptable -5. Submit PR to the main Brainy repository - -### Model Optimization - -When working with models: - -- **Float16**: For balanced performance and size -- **Int8**: For memory-constrained environments -- **Original**: For maximum accuracy - -### File Structure - -``` -brainy-models-package/ -├── models/ # Model files -├── src/ # TypeScript source -├── dist/ # Compiled output -├── scripts/ # Utility scripts -└── test/ # Test files -``` - -## Code of Conduct - -This project follows the same [Code of Conduct](CODE_OF_CONDUCT.md) as the main Brainy project. - -## Questions and Support - -For questions specific to the models package: - -- [GitHub Issues](https://github.com/soulcraft-research/brainy/issues) - Use the `brainy-models` label -- [Main Documentation](https://github.com/soulcraft-research/brainy) - -For general Brainy questions, refer to the main repository. - -## License - -By contributing to this project, you agree that your contributions will be licensed under the MIT License. diff --git a/brainy-models-package/LICENSE b/brainy-models-package/LICENSE deleted file mode 100644 index 9465500c..00000000 --- a/brainy-models-package/LICENSE +++ /dev/null @@ -1,21 +0,0 @@ -MIT License - -Copyright (c) 2025 Soulcraft Research - -Permission is hereby granted, free of charge, to any person obtaining a copy -of this software and associated documentation files (the "Software"), to deal -in the Software without restriction, including without limitation the rights -to use, copy, modify, merge, publish, distribute, sublicense, and/or sell -copies of the Software, and to permit persons to whom the Software is -furnished to do so, subject to the following conditions: - -The above copyright notice and this permission notice shall be included in all -copies or substantial portions of the Software. - -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -SOFTWARE. diff --git a/brainy-models-package/README.md b/brainy-models-package/README.md deleted file mode 100644 index ddf763cd..00000000 --- a/brainy-models-package/README.md +++ /dev/null @@ -1,375 +0,0 @@ -
-Brainy Logo -

- -[![License](https://img.shields.io/badge/license-MIT-green.svg)](../LICENSE) -[![Node.js](https://img.shields.io/badge/node-%3E%3D18.0.0-brightgreen.svg)](https://nodejs.org/) -[![TypeScript](https://img.shields.io/badge/TypeScript-5.4.5-blue.svg)](https://www.typescriptlang.org/) -[![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg)](../CONTRIBUTING.md) - -**Pre-bundled TensorFlow models for maximum reliability with Brainy vector database** - -
- -## ✨ Overview - -This package provides offline access to the Universal Sentence Encoder model, eliminating network dependencies and ensuring consistent performance. It's designed as an optional companion to the main `@soulcraft/brainy` package for applications requiring maximum reliability. - -### 🚀 Key Features - -- 🔒 **Maximum Reliability**: Fully offline model loading with zero network dependencies -- 📦 **Pre-bundled Models**: Complete Universal Sentence Encoder model (~25MB) included -- 🗜️ **Model Compression**: Multiple optimized variants (float16, int8) for different use cases -- ⚡ **Performance Optimized**: Use case-specific optimizations for memory and speed -- 🛠️ **Easy Integration**: Drop-in replacement for online model loading -- 📊 **Comprehensive Metrics**: Detailed model information and performance statistics - -## 🔧 Installation - -```bash -npm install @soulcraft/brainy-models -``` - -### Prerequisites - -- Node.js >= 18.0.0 -- `@soulcraft/brainy` >= 0.33.0 - -## 🏁 Quick Start - -### Basic Usage - -```typescript -import { BundledUniversalSentenceEncoder } from '@soulcraft/brainy-models' - -// Create encoder instance -const encoder = new BundledUniversalSentenceEncoder({ - verbose: true, - preferCompressed: false -}) - -// Load the bundled model -await encoder.load() - -// Generate embeddings -const texts = ['Hello world', 'How are you?', 'Machine learning is amazing'] -const embeddings = await encoder.embedToArrays(texts) - -console.log(`Generated ${embeddings.length} embeddings of ${embeddings[0].length} dimensions`) - -// Clean up -encoder.dispose() -``` - -### Integration with Brainy - -```typescript -import Brainy from '@soulcraft/brainy' -import { BundledUniversalSentenceEncoder } from '@soulcraft/brainy-models' - -// Create bundled encoder -const bundledEncoder = new BundledUniversalSentenceEncoder({ verbose: true }) -await bundledEncoder.load() - -// Use with Brainy (custom integration) -const brainy = new Brainy({ - // Configure Brainy to use the bundled encoder - customEmbedding: async (texts) => { - return await bundledEncoder.embedToArrays(texts) - } -}) -``` - -### Using Compressed Models - -```typescript -import { BundledUniversalSentenceEncoder } from '@soulcraft/brainy-models' - -// Use compressed model for memory-constrained environments -const encoder = new BundledUniversalSentenceEncoder({ - preferCompressed: true, - verbose: true -}) - -await encoder.load() - -// The encoder will automatically use the most appropriate compressed variant -const embeddings = await encoder.embedToArrays(['Sample text']) -``` - -## 📚 API Reference - -### BundledUniversalSentenceEncoder - -Main class for loading and using bundled models. - -#### Constructor - -```typescript -new BundledUniversalSentenceEncoder(options) -``` - -**Options:** -- `verbose?: boolean` - Enable detailed logging (default: false) -- `preferCompressed?: boolean` - Prefer compressed model variants (default: false) - -#### Methods - -##### `load(): Promise` - -Load the bundled model from local files. - -```typescript -await encoder.load() -``` - -##### `embed(texts: string[]): Promise` - -Generate embeddings as TensorFlow tensors. - -```typescript -const embeddings = await encoder.embed(['Hello world']) -// Remember to dispose of tensors when done -embeddings.dispose() -``` - -##### `embedToArrays(texts: string[]): Promise` - -Generate embeddings as JavaScript arrays (automatically disposes tensors). - -```typescript -const embeddings = await encoder.embedToArrays(['Hello world']) -console.log(embeddings[0].length) // 512 -``` - -##### `getMetadata(): ModelMetadata | null` - -Get model metadata information. - -```typescript -const metadata = encoder.getMetadata() -console.log(metadata?.dimensions) // 512 -``` - -##### `isLoaded(): boolean` - -Check if the model is loaded. - -```typescript -if (encoder.isLoaded()) { - // Model is ready to use -} -``` - -##### `getModelInfo(): { inputShape: number[], outputShape: number[] } | null` - -Get model input/output shape information. - -```typescript -const info = encoder.getModelInfo() -console.log(info?.outputShape) // [-1, 512] -``` - -##### `dispose(): void` - -Clean up model resources. - -```typescript -encoder.dispose() -``` - -### ModelCompressor - -Utility class for model compression and optimization. - -#### Static Methods - -##### `quantizeModel(modelPath: string, outputPath: string, options?): Promise` - -Compress a model using quantization. - -```typescript -import { ModelCompressor } from '@soulcraft/brainy-models' - -await ModelCompressor.quantizeModel( - '/path/to/model.json', - '/path/to/compressed/model.json', - { dtype: 'int8' } -) -``` - -##### `getModelSize(modelPath: string): Promise` - -Get detailed model size information. - -```typescript -const sizeInfo = await ModelCompressor.getModelSize('/path/to/model.json') -console.log(`Total size: ${sizeInfo.totalSize} bytes`) -``` - -### Utility Functions - -#### `utils.checkModelsAvailable(): boolean` - -Check if bundled models are available. - -```typescript -import { utils } from '@soulcraft/brainy-models' - -if (utils.checkModelsAvailable()) { - console.log('Models are ready to use') -} -``` - -#### `utils.listAvailableModels(): string[]` - -List available bundled models. - -```typescript -const models = utils.listAvailableModels() -console.log('Available models:', models) -``` - -## 🎯 Model Variants - -The package includes multiple model variants optimized for different use cases: - -### Original (Float32) -- **Size**: ~25MB -- **Use case**: Maximum accuracy -- **Memory**: High -- **Speed**: Fast - -### Float16 Compressed -- **Size**: ~12-15MB -- **Use case**: Balanced performance -- **Memory**: Medium -- **Speed**: Fast - -### Int8 Quantized -- **Size**: ~6-8MB -- **Use case**: Memory-constrained environments -- **Memory**: Low -- **Speed**: Medium - -## ⚙️ Scripts - -The package includes several utility scripts: - -### Download Models - -Download the complete Universal Sentence Encoder model: - -```bash -npm run download-models -``` - -### Compress Models - -Create optimized model variants: - -```bash -npm run compress-models -``` - -### Test Models - -Verify model functionality: - -```bash -npm test -``` - -## 🔨 Development - -### Building the Package - -```bash -npm run build -``` - -### Running Tests - -```bash -npm test -``` - -### Creating a Release - -```bash -npm run pack -``` - -## ⚖️ Comparison with Online Loading - -| Feature | Online Loading | Bundled Models | -|---------|----------------|----------------| -| **Reliability** | Network dependent | 100% offline | -| **First load time** | 30-60 seconds | < 1 second | -| **Subsequent loads** | Cached (~1 second) | < 1 second | -| **Package size** | ~3KB | ~25MB | -| **Network required** | Yes (first time) | No | -| **Offline support** | Limited | Complete | - -## 💡 Use Cases - -### When to Use Bundled Models - -- ✅ Production applications requiring maximum reliability -- ✅ Offline or air-gapped environments -- ✅ Applications with strict SLA requirements -- ✅ Edge computing and IoT devices -- ✅ Development environments with unreliable internet - -### When to Use Online Loading - -- ✅ Development and prototyping -- ✅ Applications where package size matters -- ✅ Environments with reliable internet connectivity -- ✅ Applications that rarely use embeddings - -## 🔧 Troubleshooting - -### Model Not Found Error - -``` -Error: Bundled model not found. Please run "npm run download-models" -``` - -**Solution**: Run the download script to fetch the model files: -```bash -cd node_modules/@soulcraft/brainy-models -npm run download-models -``` - -### Memory Issues - -If you encounter memory issues, try using compressed models: - -```typescript -const encoder = new BundledUniversalSentenceEncoder({ - preferCompressed: true -}) -``` - -### Performance Optimization - -For optimal performance: - -1. **Memory-constrained**: Use int8 quantized models -2. **Speed-critical**: Use original float32 models -3. **Balanced**: Use float16 compressed models - -## 📄 License - -MIT - -## 🤝 Contributing - -Contributions are welcome! Please see the main [Brainy repository](https://github.com/soulcraft-research/brainy) for contribution guidelines. - -## 💬 Support - -For issues and questions: -- [GitHub Issues](https://github.com/soulcraft-research/brainy/issues) -- [Documentation](https://github.com/soulcraft-research/brainy) diff --git a/brainy-models-package/dist/index.d.ts b/brainy-models-package/dist/index.d.ts deleted file mode 100644 index 6480549e..00000000 --- a/brainy-models-package/dist/index.d.ts +++ /dev/null @@ -1,103 +0,0 @@ -/** - * @soulcraft/brainy-models - * - * Pre-bundled TensorFlow models for maximum reliability with Brainy vector database. - * This package provides offline access to the Universal Sentence Encoder model, - * eliminating network dependencies and ensuring consistent performance. - */ -import * as tf from '@tensorflow/tfjs'; -export interface ModelMetadata { - name: string; - version: string; - description: string; - dimensions: number; - downloadDate: string; - source: string; - approach: string; - modelUrl: string; - bundledLocally: boolean; - reliability: string; -} -export interface BundledModelOptions { - verbose?: boolean; - preferCompressed?: boolean; -} -/** - * Bundled Universal Sentence Encoder for offline use - */ -export declare class BundledUniversalSentenceEncoder { - private model; - private metadata; - private options; - constructor(options?: BundledModelOptions); - /** - * Load the bundled model from local files - */ - load(): Promise; - /** - * Generate embeddings for the given texts - */ - embed(texts: string[]): Promise; - /** - * Generate embeddings and return as JavaScript arrays - */ - embedToArrays(texts: string[]): Promise; - /** - * Get model metadata - */ - getMetadata(): ModelMetadata | null; - /** - * Check if the model is loaded - */ - isLoaded(): boolean; - /** - * Get model information - */ - getModelInfo(): { - inputShape: number[]; - outputShape: number[]; - } | null; - /** - * Dispose of the model and free memory - */ - dispose(): void; -} -/** - * Model compression utilities - */ -export declare class ModelCompressor { - /** - * Compress model weights using quantization - * Note: TensorFlow.js doesn't currently support model quantization - */ - static quantizeModel(modelPath: string, outputPath: string, options?: { - dtype?: 'int8' | 'int16'; - }): Promise; - /** - * Get model size information by reading files from disk - */ - static getModelSize(modelPath: string): Promise<{ - totalSize: number; - weightsSize: number; - modelJsonSize: number; - }>; -} -/** - * Utility functions - */ -export declare const utils: { - /** - * Check if bundled models are available - */ - checkModelsAvailable(): boolean; - /** - * Get bundled models directory - */ - getModelsDirectory(): string; - /** - * List available bundled models - */ - listAvailableModels(): string[]; -}; -export default BundledUniversalSentenceEncoder; -//# sourceMappingURL=index.d.ts.map \ No newline at end of file diff --git a/brainy-models-package/dist/index.d.ts.map b/brainy-models-package/dist/index.d.ts.map deleted file mode 100644 index 6cc8f6b1..00000000 --- a/brainy-models-package/dist/index.d.ts.map +++ /dev/null @@ -1 +0,0 @@ -{"version":3,"file":"index.d.ts","sourceRoot":"","sources":["../src/index.ts"],"names":[],"mappings":"AAAA;;;;;;GAMG;AAEH,OAAO,KAAK,EAAE,MAAM,kBAAkB,CAAA;AAwBtC,MAAM,WAAW,aAAa;IAC5B,IAAI,EAAE,MAAM,CAAA;IACZ,OAAO,EAAE,MAAM,CAAA;IACf,WAAW,EAAE,MAAM,CAAA;IACnB,UAAU,EAAE,MAAM,CAAA;IAClB,YAAY,EAAE,MAAM,CAAA;IACpB,MAAM,EAAE,MAAM,CAAA;IACd,QAAQ,EAAE,MAAM,CAAA;IAChB,QAAQ,EAAE,MAAM,CAAA;IAChB,cAAc,EAAE,OAAO,CAAA;IACvB,WAAW,EAAE,MAAM,CAAA;CACpB;AAED,MAAM,WAAW,mBAAmB;IAClC,OAAO,CAAC,EAAE,OAAO,CAAA;IACjB,gBAAgB,CAAC,EAAE,OAAO,CAAA;CAC3B;AAED;;GAEG;AACH,qBAAa,+BAA+B;IAC1C,OAAO,CAAC,KAAK,CAA6B;IAC1C,OAAO,CAAC,QAAQ,CAA6B;IAC7C,OAAO,CAAC,OAAO,CAAqB;gBAExB,OAAO,GAAE,mBAAwB;IAQ7C;;OAEG;IACG,IAAI,IAAI,OAAO,CAAC,IAAI,CAAC;IAwC3B;;OAEG;IACG,KAAK,CAAC,KAAK,EAAE,MAAM,EAAE,GAAG,OAAO,CAAC,EAAE,CAAC,QAAQ,CAAC;IAqBlD;;OAEG;IACG,aAAa,CAAC,KAAK,EAAE,MAAM,EAAE,GAAG,OAAO,CAAC,MAAM,EAAE,EAAE,CAAC;IAOzD;;OAEG;IACH,WAAW,IAAI,aAAa,GAAG,IAAI;IAInC;;OAEG;IACH,QAAQ,IAAI,OAAO;IAInB;;OAEG;IACH,YAAY,IAAI;QAAE,UAAU,EAAE,MAAM,EAAE,CAAC;QAAC,WAAW,EAAE,MAAM,EAAE,CAAA;KAAE,GAAG,IAAI;IAWtE;;OAEG;IACH,OAAO,IAAI,IAAI;CAMhB;AAED;;GAEG;AACH,qBAAa,eAAe;IAC1B;;;OAGG;WACU,aAAa,CACxB,SAAS,EAAE,MAAM,EACjB,UAAU,EAAE,MAAM,EAClB,OAAO,GAAE;QAAE,KAAK,CAAC,EAAE,MAAM,GAAG,OAAO,CAAA;KAAO,GACzC,OAAO,CAAC,IAAI,CAAC;IAwBhB;;OAEG;WACU,YAAY,CAAC,SAAS,EAAE,MAAM,GAAG,OAAO,CAAC;QACpD,SAAS,EAAE,MAAM,CAAA;QACjB,WAAW,EAAE,MAAM,CAAA;QACnB,aAAa,EAAE,MAAM,CAAA;KACtB,CAAC;CAuCH;AAED;;GAEG;AACH,eAAO,MAAM,KAAK;IAChB;;OAEG;4BACqB,OAAO;IAK/B;;OAEG;0BACmB,MAAM;IAI5B;;OAEG;2BACoB,MAAM,EAAE;CAUhC,CAAA;AAGD,eAAe,+BAA+B,CAAA"} \ No newline at end of file diff --git a/brainy-models-package/dist/index.js b/brainy-models-package/dist/index.js deleted file mode 100644 index dac50a4f..00000000 --- a/brainy-models-package/dist/index.js +++ /dev/null @@ -1,237 +0,0 @@ -/** - * @soulcraft/brainy-models - * - * Pre-bundled TensorFlow models for maximum reliability with Brainy vector database. - * This package provides offline access to the Universal Sentence Encoder model, - * eliminating network dependencies and ensuring consistent performance. - */ -import * as tf from '@tensorflow/tfjs'; -import { readFileSync, existsSync } from 'fs'; -import { join, dirname } from 'path'; -import { fileURLToPath } from 'url'; -/** - * Helper function to safely extract error message from unknown error type - */ -function getErrorMessage(error) { - if (error instanceof Error) { - return error.message; - } - if (typeof error === 'string') { - return error; - } - return String(error); -} -// Get the package directory -const __filename = fileURLToPath(import.meta.url); -const __dirname = dirname(__filename); -const PACKAGE_ROOT = join(__dirname, '..'); -const MODELS_DIR = join(PACKAGE_ROOT, 'models'); -/** - * Bundled Universal Sentence Encoder for offline use - */ -export class BundledUniversalSentenceEncoder { - model = null; - metadata = null; - options; - constructor(options = {}) { - this.options = { - verbose: false, - preferCompressed: false, - ...options - }; - } - /** - * Load the bundled model from local files - */ - async load() { - try { - const modelDir = join(MODELS_DIR, 'universal-sentence-encoder'); - const modelPath = join(modelDir, 'model.json'); - const metadataPath = join(modelDir, 'metadata.json'); - if (!existsSync(modelPath)) { - throw new Error(`Bundled model not found at ${modelPath}. ` + - 'Please run "npm run download-models" to download the model files.'); - } - if (this.options.verbose) { - console.log('🔄 Loading bundled Universal Sentence Encoder model...'); - } - // Load metadata - if (existsSync(metadataPath)) { - const metadataContent = readFileSync(metadataPath, 'utf8'); - this.metadata = JSON.parse(metadataContent); - if (this.options.verbose) { - console.log(`📋 Model metadata:`, this.metadata); - } - } - // Load the model - this.model = await tf.loadGraphModel(`file://${modelPath}`); - if (this.options.verbose) { - console.log('✅ Bundled model loaded successfully'); - console.log(`🔒 Reliability: Maximum (fully offline)`); - } - } - catch (error) { - throw new Error(`Failed to load bundled model: ${getErrorMessage(error)}`); - } - } - /** - * Generate embeddings for the given texts - */ - async embed(texts) { - if (!this.model) { - throw new Error('Model not loaded. Call load() first.'); - } - try { - // Convert texts to tensor - const inputTensor = tf.tensor1d(texts, 'string'); - // Run inference - const embeddings = this.model.predict(inputTensor); - // Clean up input tensor - inputTensor.dispose(); - return embeddings; - } - catch (error) { - throw new Error(`Failed to generate embeddings: ${getErrorMessage(error)}`); - } - } - /** - * Generate embeddings and return as JavaScript arrays - */ - async embedToArrays(texts) { - const embeddings = await this.embed(texts); - const arrays = await embeddings.array(); - embeddings.dispose(); - return arrays; - } - /** - * Get model metadata - */ - getMetadata() { - return this.metadata; - } - /** - * Check if the model is loaded - */ - isLoaded() { - return this.model !== null; - } - /** - * Get model information - */ - getModelInfo() { - if (!this.model) { - return null; - } - return { - inputShape: this.model.inputs[0].shape || [], - outputShape: this.model.outputs[0].shape || [] - }; - } - /** - * Dispose of the model and free memory - */ - dispose() { - if (this.model) { - this.model.dispose(); - this.model = null; - } - } -} -/** - * Model compression utilities - */ -export class ModelCompressor { - /** - * Compress model weights using quantization - * Note: TensorFlow.js doesn't currently support model quantization - */ - static async quantizeModel(modelPath, outputPath, options = {}) { - const { dtype = 'int8' } = options; - try { - console.log(`🔄 Loading model for quantization: ${modelPath}`); - const model = await tf.loadGraphModel(`file://${modelPath}`); - console.log(`🗜️ Quantizing model to ${dtype}...`); - // TensorFlow.js doesn't have built-in quantization or model serialization APIs yet - // This is a placeholder implementation that acknowledges the limitation - console.warn('⚠️ Model quantization is not yet supported in TensorFlow.js'); - console.log(`📋 Model loaded successfully from: ${modelPath}`); - console.log(`📋 Target output path: ${outputPath}`); - console.log(`📋 Target dtype: ${dtype}`); - model.dispose(); - throw new Error('Model quantization is not yet supported in TensorFlow.js. This feature requires server-side processing with TensorFlow Python.'); - } - catch (error) { - throw new Error(`Failed to compress model: ${getErrorMessage(error)}`); - } - } - /** - * Get model size information by reading files from disk - */ - static async getModelSize(modelPath) { - try { - // Load model to verify it's valid - const model = await tf.loadGraphModel(`file://${modelPath}`); - model.dispose(); - // Get model.json size - const modelJsonSize = existsSync(modelPath) ? readFileSync(modelPath).length : 0; - // Calculate weights size by reading weight files - let weightsSize = 0; - const modelDir = dirname(modelPath); - // Read model.json to get weight file names - if (existsSync(modelPath)) { - const modelJson = JSON.parse(readFileSync(modelPath, 'utf8')); - if (modelJson.weightsManifest) { - for (const manifest of modelJson.weightsManifest) { - for (const path of manifest.paths) { - const weightFilePath = join(modelDir, path); - if (existsSync(weightFilePath)) { - weightsSize += readFileSync(weightFilePath).length; - } - } - } - } - } - const totalSize = weightsSize + modelJsonSize; - return { - totalSize, - weightsSize, - modelJsonSize - }; - } - catch (error) { - throw new Error(`Failed to get model size: ${getErrorMessage(error)}`); - } - } -} -/** - * Utility functions - */ -export const utils = { - /** - * Check if bundled models are available - */ - checkModelsAvailable() { - const modelPath = join(MODELS_DIR, 'universal-sentence-encoder', 'model.json'); - return existsSync(modelPath); - }, - /** - * Get bundled models directory - */ - getModelsDirectory() { - return MODELS_DIR; - }, - /** - * List available bundled models - */ - listAvailableModels() { - const models = []; - const useModelPath = join(MODELS_DIR, 'universal-sentence-encoder', 'model.json'); - if (existsSync(useModelPath)) { - models.push('universal-sentence-encoder'); - } - return models; - } -}; -// Default export for convenience -export default 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\ No newline at end of file diff --git a/brainy-models-package/models/universal-sentence-encoder/group1-shard1of7 b/brainy-models-package/models/universal-sentence-encoder/group1-shard1of7 deleted file mode 100644 index 0b41dd6d..00000000 Binary files a/brainy-models-package/models/universal-sentence-encoder/group1-shard1of7 and /dev/null differ diff --git a/brainy-models-package/models/universal-sentence-encoder/group1-shard2of7 b/brainy-models-package/models/universal-sentence-encoder/group1-shard2of7 deleted file mode 100644 index 80e4a718..00000000 Binary files a/brainy-models-package/models/universal-sentence-encoder/group1-shard2of7 and /dev/null differ diff --git a/brainy-models-package/models/universal-sentence-encoder/group1-shard3of7 b/brainy-models-package/models/universal-sentence-encoder/group1-shard3of7 deleted file mode 100644 index 83b585a1..00000000 Binary files a/brainy-models-package/models/universal-sentence-encoder/group1-shard3of7 and /dev/null differ diff --git a/brainy-models-package/models/universal-sentence-encoder/group1-shard4of7 b/brainy-models-package/models/universal-sentence-encoder/group1-shard4of7 deleted file mode 100644 index 0f550fb8..00000000 Binary files a/brainy-models-package/models/universal-sentence-encoder/group1-shard4of7 and /dev/null differ diff --git a/brainy-models-package/models/universal-sentence-encoder/group1-shard5of7 b/brainy-models-package/models/universal-sentence-encoder/group1-shard5of7 deleted file mode 100644 index 2a5287a9..00000000 Binary files a/brainy-models-package/models/universal-sentence-encoder/group1-shard5of7 and /dev/null differ diff --git a/brainy-models-package/models/universal-sentence-encoder/group1-shard6of7 b/brainy-models-package/models/universal-sentence-encoder/group1-shard6of7 deleted file mode 100644 index c992f5f5..00000000 Binary files a/brainy-models-package/models/universal-sentence-encoder/group1-shard6of7 and /dev/null differ diff --git a/brainy-models-package/models/universal-sentence-encoder/group1-shard7of7 b/brainy-models-package/models/universal-sentence-encoder/group1-shard7of7 deleted file mode 100644 index 9d995b74..00000000 Binary files a/brainy-models-package/models/universal-sentence-encoder/group1-shard7of7 and /dev/null differ diff --git a/brainy-models-package/models/universal-sentence-encoder/metadata.json b/brainy-models-package/models/universal-sentence-encoder/metadata.json deleted file mode 100644 index bd48dabb..00000000 --- a/brainy-models-package/models/universal-sentence-encoder/metadata.json +++ /dev/null @@ -1,12 +0,0 @@ -{ - "name": "universal-sentence-encoder", - "version": "1.0.0", - "description": "Complete Universal Sentence Encoder model bundled for offline use", - "dimensions": 512, - "downloadDate": "2025-08-02T21:42:25.604Z", - "source": "tensorflow-models/universal-sentence-encoder", - "approach": "full-bundle", - "modelUrl": 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"description": "Pre-bundled TensorFlow models for maximum reliability with Brainy vector database", - "main": "dist/index.js", - "module": "dist/index.js", - "types": "dist/index.d.ts", - "type": "module", - "engines": { - "node": ">=18.0.0" - }, - "scripts": { - "prebuild": "npm run download-models", - "build": "tsc", - "test": "node test/test-models.js", - "prepare": "npm run build", - "download-models": "node scripts/download-full-models.js", - "compress-models": "node scripts/compress-models.js", - "_pack": "npm pack", - "_release": "standard-version", - "_release:patch": "standard-version --release-as patch", - "_release:minor": "standard-version --release-as minor", - "_release:major": "standard-version --release-as major", - "_release:dry-run": "standard-version --dry-run", - "_github-release": "node scripts/create-github-release.js", - "_workflow": "node scripts/release-workflow.js", - "_workflow:patch": "node scripts/release-workflow.js patch", - "_workflow:minor": "node scripts/release-workflow.js minor", - "_workflow:major": "node scripts/release-workflow.js major", - "_workflow:dry-run": "npm run build && npm test && npm run _release:dry-run", - "_deploy": "npm run build && npm publish" - }, - "keywords": [ - "tensorflow", - "models", - "universal-sentence-encoder", - "embeddings", - "brainy", - "vector-database", - "offline", - "bundled" - ], - "author": "David Snelling (david@soulcraft.com)", - "license": "MIT", - "private": false, - "publishConfig": { - "access": "public" - }, - "homepage": "https://github.com/soulcraft-research/brainy", - "bugs": { - "url": "https://github.com/soulcraft-research/brainy/issues" - }, - "repository": { - "type": "git", - "url": "git+https://github.com/soulcraft-research/brainy.git", - "directory": "brainy-models-package" - }, - "files": [ - "dist/", - "models/", - "README.md", - "LICENSE" - ], - "dependencies": { - "@tensorflow-models/universal-sentence-encoder": "^1.3.3", - "@tensorflow/tfjs": "^4.23.0-rc.0", - "@tensorflow/tfjs-node": "^4.23.0-rc.0" - }, - "devDependencies": { - "@types/node": "^20.11.30", - "standard-version": "^9.5.0", - "typescript": "^5.4.5" - }, - "peerDependencies": { - "@soulcraft/brainy": ">=0.33.0" - } -} diff --git a/brainy-models-package/reproduce-error.js b/brainy-models-package/reproduce-error.js deleted file mode 100644 index 11628f14..00000000 --- a/brainy-models-package/reproduce-error.js +++ /dev/null @@ -1,28 +0,0 @@ -#!/usr/bin/env node - -/** - * Reproduction script for the TensorFlow.js isNullOrUndefined error - */ - -import * as tf from '@tensorflow/tfjs-node' -import * as use from '@tensorflow-models/universal-sentence-encoder' - -console.log('🔍 Loading Universal Sentence Encoder model...') - -try { - const model = await use.load() - console.log('✅ Model loaded successfully') - - console.log('🧪 Testing model functionality...') - const testEmbedding = await model.embed(['Hello world']) - const testArray = await testEmbedding.array() - console.log( - `✅ Model test passed - embedding dimensions: ${testArray[0].length}` - ) - testEmbedding.dispose() - model.dispose() -} catch (error) { - console.error('❌ Error:', error) - console.error('Stack trace:', error.stack) - process.exit(1) -} diff --git a/brainy-models-package/scripts/compress-models.js b/brainy-models-package/scripts/compress-models.js deleted file mode 100644 index 275f19c1..00000000 --- a/brainy-models-package/scripts/compress-models.js +++ /dev/null @@ -1,278 +0,0 @@ -#!/usr/bin/env node - -/* eslint-env node */ -/* eslint-disable no-console */ - -/** - * Model Compression Script for @soulcraft/brainy-models - * - * This script implements model compression and optimization techniques - * to reduce model size while maintaining accuracy. - */ - -import fs from 'fs' -import path from 'path' -import { fileURLToPath } from 'url' -import * as tf from '@tensorflow/tfjs-node' - -const __filename = fileURLToPath(import.meta.url) -const __dirname = path.dirname(__filename) - -const MODELS_DIR = path.join(__dirname, '..', 'models') -const USE_MODEL_DIR = path.join(MODELS_DIR, 'universal-sentence-encoder') -const COMPRESSED_DIR = path.join(USE_MODEL_DIR, 'compressed') - -// Ensure compressed directory exists -if (!fs.existsSync(COMPRESSED_DIR)) { - fs.mkdirSync(COMPRESSED_DIR, { recursive: true }) -} - -console.log('🗜️ Starting model compression for @soulcraft/brainy-models...') -console.log('This will create optimized versions of the bundled models.\n') - -/** - * Get file size in MB - */ -function getFileSizeMB(filePath) { - const stats = fs.statSync(filePath) - return (stats.size / 1024 / 1024).toFixed(2) -} - -/** - * Get directory size in MB - */ -function getDirectorySizeMB(dirPath) { - let totalSize = 0 - const files = fs.readdirSync(dirPath) - - for (const file of files) { - const filePath = path.join(dirPath, file) - const stats = fs.statSync(filePath) - if (stats.isFile()) { - totalSize += stats.size - } - } - - return (totalSize / 1024 / 1024).toFixed(2) -} - -/** - * Compress model weights by reducing precision - */ -async function compressModelWeights(modelPath, outputPath, precision = 'float16') { - try { - console.log(`🔄 Loading model from: ${modelPath}`) - const model = await tf.loadGraphModel(`file://${modelPath}`) - - console.log(`🗜️ Compressing weights to ${precision} precision...`) - - // Get model artifacts - const artifacts = await model.serialize() - - // Compress weight data - if (artifacts.weightData) { - const originalWeights = new Float32Array(artifacts.weightData) - let compressedWeights - - if (precision === 'float16') { - // Simulate float16 by reducing precision - compressedWeights = new Float32Array(originalWeights.length) - for (let i = 0; i < originalWeights.length; i++) { - // Round to reduce precision (simulating float16) - compressedWeights[i] = Math.round(originalWeights[i] * 1000) / 1000 - } - } else if (precision === 'int8') { - // Quantize to int8 range - const min = Math.min(...originalWeights) - const max = Math.max(...originalWeights) - const scale = (max - min) / 255 - - compressedWeights = new Float32Array(originalWeights.length) - for (let i = 0; i < originalWeights.length; i++) { - const quantized = Math.round((originalWeights[i] - min) / scale) - compressedWeights[i] = (quantized * scale) + min - } - } - - artifacts.weightData = compressedWeights.buffer - } - - // Update metadata to indicate compression - if (artifacts.userDefinedMetadata) { - artifacts.userDefinedMetadata.compressed = true - artifacts.userDefinedMetadata.compressionType = precision - artifacts.userDefinedMetadata.compressionDate = new Date().toISOString() - } - - // Save compressed model - await tf.io.fileSystem(outputPath).save(artifacts) - - console.log(`✅ Compressed model saved to: ${outputPath}`) - - model.dispose() - - return true - } catch (error) { - console.error(`❌ Error compressing model: ${error.message}`) - return false - } -} - -/** - * Create optimized model variants - */ -async function createOptimizedVariants() { - try { - const originalModelPath = path.join(USE_MODEL_DIR, 'model.json') - - if (!fs.existsSync(originalModelPath)) { - console.error('❌ Original model not found. Please run "npm run download-models" first.') - process.exit(1) - } - - console.log('📊 Original model size:', getDirectorySizeMB(USE_MODEL_DIR), 'MB') - - // Create float16 compressed version - const float16Path = path.join(COMPRESSED_DIR, 'float16') - if (!fs.existsSync(float16Path)) { - fs.mkdirSync(float16Path, { recursive: true }) - } - - console.log('\n🗜️ Creating float16 compressed version...') - const float16Success = await compressModelWeights( - originalModelPath, - path.join(float16Path, 'model.json'), - 'float16' - ) - - if (float16Success) { - console.log('📊 Float16 model size:', getDirectorySizeMB(float16Path), 'MB') - } - - // Create int8 quantized version - const int8Path = path.join(COMPRESSED_DIR, 'int8') - if (!fs.existsSync(int8Path)) { - fs.mkdirSync(int8Path, { recursive: true }) - } - - console.log('\n🗜️ Creating int8 quantized version...') - const int8Success = await compressModelWeights( - originalModelPath, - path.join(int8Path, 'model.json'), - 'int8' - ) - - if (int8Success) { - console.log('📊 Int8 model size:', getDirectorySizeMB(int8Path), 'MB') - } - - // Create compression summary - const compressionSummary = { - originalSize: getDirectorySizeMB(USE_MODEL_DIR), - variants: { - float16: { - available: float16Success, - size: float16Success ? getDirectorySizeMB(float16Path) : null, - compressionRatio: float16Success ? - (parseFloat(getDirectorySizeMB(USE_MODEL_DIR)) / parseFloat(getDirectorySizeMB(float16Path))).toFixed(2) : null - }, - int8: { - available: int8Success, - size: int8Success ? getDirectorySizeMB(int8Path) : null, - compressionRatio: int8Success ? - (parseFloat(getDirectorySizeMB(USE_MODEL_DIR)) / parseFloat(getDirectorySizeMB(int8Path))).toFixed(2) : null - } - }, - createdAt: new Date().toISOString() - } - - fs.writeFileSync( - path.join(COMPRESSED_DIR, 'compression-summary.json'), - JSON.stringify(compressionSummary, null, 2) - ) - - console.log('\n📋 Compression Summary:') - console.log(`Original: ${compressionSummary.originalSize} MB`) - if (float16Success) { - console.log(`Float16: ${compressionSummary.variants.float16.size} MB (${compressionSummary.variants.float16.compressionRatio}x smaller)`) - } - if (int8Success) { - console.log(`Int8: ${compressionSummary.variants.int8.size} MB (${compressionSummary.variants.int8.compressionRatio}x smaller)`) - } - - console.log('\n✨ Model compression completed successfully!') - console.log('Compressed models are available for applications requiring smaller file sizes.') - - } catch (error) { - console.error('❌ Error during compression:', error) - process.exit(1) - } -} - -/** - * Optimize model for specific use cases - */ -async function optimizeForUseCase(useCase = 'general') { - console.log(`\n🎯 Optimizing model for use case: ${useCase}`) - - const optimizations = { - general: { - description: 'Balanced performance and size', - precision: 'float16', - batchSize: 32 - }, - 'low-memory': { - description: 'Minimal memory footprint', - precision: 'int8', - batchSize: 1 - }, - 'high-performance': { - description: 'Maximum inference speed', - precision: 'float32', - batchSize: 64 - } - } - - const config = optimizations[useCase] || optimizations.general - - console.log(`📝 Optimization config: ${config.description}`) - console.log(` Precision: ${config.precision}`) - console.log(` Batch size: ${config.batchSize}`) - - // Create optimization metadata - const optimizationMetadata = { - useCase, - config, - createdAt: new Date().toISOString(), - recommendations: { - 'low-memory': 'Use int8 quantized model for memory-constrained environments', - 'high-performance': 'Use original float32 model with larger batch sizes', - 'general': 'Use float16 model for balanced performance' - } - } - - fs.writeFileSync( - path.join(COMPRESSED_DIR, `optimization-${useCase}.json`), - JSON.stringify(optimizationMetadata, null, 2) - ) - - console.log(`✅ Optimization profile created for ${useCase}`) -} - -// Main execution -async function main() { - try { - await createOptimizedVariants() - await optimizeForUseCase('general') - await optimizeForUseCase('low-memory') - await optimizeForUseCase('high-performance') - - console.log('\n🎉 All optimizations completed successfully!') - - } catch (error) { - console.error('❌ Compression failed:', error) - process.exit(1) - } -} - -main().catch(console.error) diff --git a/brainy-models-package/scripts/create-github-release.js b/brainy-models-package/scripts/create-github-release.js deleted file mode 100644 index 7d6fc592..00000000 --- a/brainy-models-package/scripts/create-github-release.js +++ /dev/null @@ -1,107 +0,0 @@ -#!/usr/bin/env node - -/** - * Create GitHub Release Script for @soulcraft/brainy-models-package - * - * This script creates a GitHub release with auto-generated release notes - * for the current version of the brainy-models-package. - * - * It uses the GitHub CLI (gh) to create the release, so the gh CLI must be installed - * and authenticated with appropriate permissions. - * - * The script: - * 1. Gets the current version from package.json - * 2. Creates a GitHub release for that version with models-package prefix - * 3. Auto-generates release notes based on commits since the last release - * - * This ensures that each npm release has a corresponding GitHub release with notes. - */ - -/* global process, console */ - -import { execSync } from 'child_process' -import fs from 'fs' -import path from 'path' -import { fileURLToPath } from 'url' - -// Get the directory of the current module -const __filename = fileURLToPath(import.meta.url) -const __dirname = path.dirname(__filename) - -// Path to the brainy-models-package directory -const packageDir = path.join(__dirname, '..') -const rootDir = path.join(__dirname, '..', '..') - -// Path to package.json -const packageJsonPath = path.join(packageDir, 'package.json') - -// Read package.json -const packageJson = JSON.parse(fs.readFileSync(packageJsonPath, 'utf8')) -const version = packageJson.version -const tagName = `models-package-v${version}` - -// Check if GitHub CLI is installed -try { - execSync('gh --version', { stdio: 'ignore' }) -} catch (error) { - console.error('Error: GitHub CLI (gh) is not installed or not in PATH') - console.error('Please install it from https://cli.github.com/ and authenticate with `gh auth login`') - process.exit(1) -} - -// Check if the tag exists locally -let tagExistsLocally = false -try { - const tagOutput = execSync(`git tag -l ${tagName}`, { stdio: 'pipe', cwd: rootDir }).toString().trim() - tagExistsLocally = tagOutput === tagName -} catch (error) { - console.log(`Error checking if tag exists: ${error.message}`) - tagExistsLocally = false -} - -// Create and push the tag if it doesn't exist -if (!tagExistsLocally) { - try { - console.log(`Creating tag ${tagName}...`) - execSync(`git tag ${tagName}`, { stdio: 'inherit', cwd: rootDir }) - console.log(`Successfully created tag ${tagName}`) - } catch (error) { - console.error(`Error creating tag: ${error.message}`) - process.exit(1) - } -} - -// Push the tag to remote -try { - console.log(`Pushing tag ${tagName} to remote...`) - execSync(`git push origin ${tagName}`, { stdio: 'inherit', cwd: rootDir }) - console.log(`Successfully pushed tag ${tagName} to remote`) -} catch (error) { - console.error(`Error pushing tag to remote: ${error.message}`) - // Continue with release creation even if tag push fails -} - -// Create the GitHub release -try { - console.log(`Creating GitHub release for @soulcraft/brainy-models-package v${version}...`) - - // Create a release with auto-generated notes - // The --generate-notes flag automatically generates release notes based on PRs and commits - execSync( - `gh release create ${tagName} --title "@soulcraft/brainy-models-package v${version}" --generate-notes --notes "Release of @soulcraft/brainy-models-package v${version} - Pre-bundled TensorFlow models for maximum reliability with Brainy vector database."`, - { stdio: 'inherit', cwd: rootDir } - ) - - console.log(`GitHub release ${tagName} created successfully!`) - console.log('GitHub release created with auto-generated notes') -} catch (error) { - // If the release already exists, this is not a fatal error - if (error.message.includes('already exists')) { - console.log(`GitHub release ${tagName} already exists, skipping creation.`) - console.log('GitHub release already exists with auto-generated notes') - } else { - console.error('Error creating GitHub release:', error.message) - // Don't exit with error to allow the npm publish to continue - // process.exit(1) - } -} diff --git a/brainy-models-package/scripts/download-full-models.js b/brainy-models-package/scripts/download-full-models.js deleted file mode 100644 index 1a81a601..00000000 --- a/brainy-models-package/scripts/download-full-models.js +++ /dev/null @@ -1,213 +0,0 @@ -#!/usr/bin/env node - -/* eslint-env node */ -/* eslint-disable no-console */ - -/** - * Download Full Models Script for @soulcraft/brainy-models - * - * This script downloads the complete Universal Sentence Encoder model - * and saves it locally for offline use, providing maximum reliability. - */ - -import fs from 'fs' -import path from 'path' -import { fileURLToPath } from 'url' -import * as tf from '@tensorflow/tfjs-node' -import * as use from '@tensorflow-models/universal-sentence-encoder' -import https from 'https' -import { promisify } from 'util' - -const __filename = fileURLToPath(import.meta.url) -const __dirname = path.dirname(__filename) - -const MODELS_DIR = path.join(__dirname, '..', 'models') -const USE_MODEL_DIR = path.join(MODELS_DIR, 'universal-sentence-encoder') - -// Ensure directories exist -if (!fs.existsSync(MODELS_DIR)) { - fs.mkdirSync(MODELS_DIR, { recursive: true }) -} - -if (!fs.existsSync(USE_MODEL_DIR)) { - fs.mkdirSync(USE_MODEL_DIR, { recursive: true }) -} - -console.log('🚀 Starting full model download for @soulcraft/brainy-models...') -console.log('This will download the complete Universal Sentence Encoder model (~25MB)') -console.log('for offline use and maximum reliability.\n') - -/** - * Download a file from URL to local path - */ -async function downloadFile(url, filePath, maxRedirects = 5) { - return new Promise((resolve, reject) => { - const file = fs.createWriteStream(filePath) - - const handleRequest = (requestUrl, redirectCount = 0) => { - https.get(requestUrl, (response) => { - // Handle redirects - if (response.statusCode >= 300 && response.statusCode < 400) { - if (redirectCount >= maxRedirects) { - reject(new Error(`Too many redirects (${redirectCount}) for ${url}`)) - return - } - - const location = response.headers.location - if (!location) { - reject(new Error(`Redirect response without location header for ${url}`)) - return - } - - // Handle relative redirects - const redirectUrl = location.startsWith('http') ? location : new URL(location, requestUrl).href - console.log(`📍 Following redirect ${redirectCount + 1}: ${redirectUrl}`) - - // Close the current file stream and start over with the redirect URL - file.close() - fs.unlink(filePath, () => {}) // Delete partial file - - // Recursively handle the redirect - return downloadFile(redirectUrl, filePath, maxRedirects).then(resolve).catch(reject) - } - - if (response.statusCode !== 200) { - reject(new Error(`Failed to download ${url}: ${response.statusCode}`)) - return - } - - const totalSize = parseInt(response.headers['content-length'] || '0') - let downloadedSize = 0 - - response.on('data', (chunk) => { - downloadedSize += chunk.length - if (totalSize > 0) { - const progress = ((downloadedSize / totalSize) * 100).toFixed(1) - process.stdout.write(`\r📥 Downloading: ${progress}% (${downloadedSize}/${totalSize} bytes)`) - } - }) - - response.pipe(file) - - file.on('finish', () => { - file.close() - console.log(`\n✅ Downloaded: ${path.basename(filePath)}`) - resolve() - }) - - file.on('error', (err) => { - fs.unlink(filePath, () => {}) // Delete partial file - reject(err) - }) - }).on('error', reject) - } - - handleRequest(url) - }) -} - -/** - * Download the complete Universal Sentence Encoder model - */ -async function downloadFullModel() { - try { - console.log('🔍 Loading model to get download URLs...') - - // Load the model to get access to its internal structure - const model = await use.load() - console.log('✅ Model loaded successfully') - - // Test the model to ensure it works - console.log('🧪 Testing model functionality...') - const testEmbedding = await model.embed(['Hello world']) - const testArray = await testEmbedding.array() - console.log(`✅ Model test passed - embedding dimensions: ${testArray[0].length}`) - testEmbedding.dispose() - - // The Universal Sentence Encoder model URL (using Google Cloud Storage which still works) - const modelBaseUrl = 'https://storage.googleapis.com/tfjs-models/savedmodel/universal_sentence_encoder' - - console.log('📦 Downloading model files...') - console.log('Using Google Cloud Storage URLs (TensorFlow Hub URLs are deprecated)...') - - // Download model.json - const modelJsonUrl = `${modelBaseUrl}/model.json` - const modelJsonPath = path.join(USE_MODEL_DIR, 'model.json') - await downloadFile(modelJsonUrl, modelJsonPath) - - // Read the model.json to get the weights manifest - const modelJson = JSON.parse(fs.readFileSync(modelJsonPath, 'utf8')) - - // Add the required "format" field for TensorFlow.js compatibility - if (!modelJson.format) { - modelJson.format = 'tfjs-graph-model' - fs.writeFileSync(modelJsonPath, JSON.stringify(modelJson, null, 2)) - console.log('✅ Added "format" field to model.json for TensorFlow.js compatibility') - } - - // Download all weight files - if (modelJson.weightsManifest) { - for (const manifest of modelJson.weightsManifest) { - for (const weightFile of manifest.paths) { - const weightUrl = `${modelBaseUrl}/${weightFile}` - const weightPath = path.join(USE_MODEL_DIR, weightFile) - await downloadFile(weightUrl, weightPath) - } - } - } - - // Create metadata for the bundled model - const metadata = { - name: 'universal-sentence-encoder', - version: '1.0.0', - description: 'Complete Universal Sentence Encoder model bundled for offline use', - dimensions: 512, - downloadDate: new Date().toISOString(), - source: 'tensorflow-models/universal-sentence-encoder', - approach: 'full-bundle', - modelUrl: modelBaseUrl, - bundledLocally: true, - reliability: 'maximum' - } - - fs.writeFileSync( - path.join(USE_MODEL_DIR, 'metadata.json'), - JSON.stringify(metadata, null, 2) - ) - - // Verify all files exist and calculate total size - const modelFiles = fs.readdirSync(USE_MODEL_DIR) - let totalSize = 0 - - console.log('\n📋 Downloaded files:') - for (const file of modelFiles) { - const filePath = path.join(USE_MODEL_DIR, file) - const stats = fs.statSync(filePath) - totalSize += stats.size - console.log(` ✅ ${file} (${(stats.size / 1024 / 1024).toFixed(2)} MB)`) - } - - console.log(`\n🎉 Model download complete!`) - console.log(`📊 Total size: ${(totalSize / 1024 / 1024).toFixed(2)} MB`) - console.log(`📁 Location: ${USE_MODEL_DIR}`) - console.log(`🔒 Reliability: Maximum (fully offline)`) - - // Test loading the downloaded model - console.log('\n🧪 Testing downloaded model...') - const offlineModel = await tf.loadGraphModel(`file://${path.join(USE_MODEL_DIR, 'model.json')}`) - console.log('✅ Offline model loads successfully') - - // Clean up - offlineModel.dispose() - - console.log('\n✨ Full model bundling completed successfully!') - console.log('The model is now available for offline use with maximum reliability.') - - } catch (error) { - console.error('❌ Error downloading full model:', error) - process.exit(1) - } -} - -// Run the download -downloadFullModel().catch(console.error) diff --git a/brainy-models-package/scripts/release-workflow.js b/brainy-models-package/scripts/release-workflow.js deleted file mode 100644 index b4b2a273..00000000 --- a/brainy-models-package/scripts/release-workflow.js +++ /dev/null @@ -1,171 +0,0 @@ -#!/usr/bin/env node - -/** - * Release Workflow Script for @soulcraft/brainy-models-package - * - * This script provides a comprehensive workflow for releasing a new version: - * 1. Updates the version (major, minor, or patch) - * 2. Automatically updates the CHANGELOG.md with commit messages since the last release - * 3. Creates a GitHub release - * 4. Deploys to NPM - * - * Usage: - * node scripts/release-workflow.js [patch|minor|major] - * - * If no version type is specified, it defaults to "patch" - */ - -/* global process, console */ - -import { execSync } from 'child_process' -import fs from 'fs' -import path from 'path' -import { fileURLToPath } from 'url' -import readline from 'readline' - -// Get the directory of the current module -const __filename = fileURLToPath(import.meta.url) -const __dirname = path.dirname(__filename) - -// Path to the brainy-models-package directory -const packageDir = path.join(__dirname, '..') -const rootDir = path.join(__dirname, '..', '..') - -// Get the version type from command line arguments -const args = process.argv.slice(2) -const versionType = args[0] || 'patch' - -// Validate version type -if (!['patch', 'minor', 'major'].includes(versionType)) { - // eslint-disable-next-line no-console - console.error('Error: Version type must be one of: patch, minor, major') - // eslint-disable-next-line no-process-exit - process.exit(1) -} - -// Function to execute a command and log its output -function executeStep(command, description, cwd = packageDir) { - // eslint-disable-next-line no-console - console.log(`\n🚀 ${description}...\n`) - try { - execSync(command, { stdio: 'inherit', cwd }) - // eslint-disable-next-line no-console - console.log(`✅ ${description} completed successfully!\n`) - return true - } catch (error) { - // eslint-disable-next-line no-console - console.error( - `❌ Error during ${description.toLowerCase()}: ${error.message}` - ) - return false - } -} - -// Main workflow -async function runReleaseWorkflow() { - // eslint-disable-next-line no-console - console.log( - `\n=== Starting @soulcraft/brainy-models-package Release Workflow (${versionType}) ===\n` - ) - - // Step 1: Build the project - if (!executeStep('npm run build', 'Building brainy-models-package')) { - // eslint-disable-next-line no-process-exit - process.exit(1) - } - - // Step 2: Run tests to ensure everything is working - if (!executeStep('npm test', 'Running tests')) { - // eslint-disable-next-line no-console - console.warn( - '⚠️ Tests failed. This might indicate issues with the release.' - ) - - // Ask the user if they want to continue despite test failures - // eslint-disable-next-line no-console - console.log( - '\n⚠️ Do you want to continue with the release process despite test failures? (y/N)' - ) - - const rl = readline.createInterface({ - input: process.stdin, - output: process.stdout - }) - - const response = await new Promise((resolve) => { - rl.question('', (answer) => { - rl.close() - resolve(answer.toLowerCase()) - }) - }) - - if (response !== 'y' && response !== 'yes') { - // eslint-disable-next-line no-console - console.error('Release process aborted due to test failures.') - // eslint-disable-next-line no-process-exit - process.exit(1) - } - - // eslint-disable-next-line no-console - console.log('Continuing with release process despite test failures...') - } - - // Step 3: Update version and generate changelog - if ( - !executeStep( - `npm run release:${versionType}`, - `Updating version (${versionType}) and generating changelog` - ) - ) { - // eslint-disable-next-line no-process-exit - process.exit(1) - } - - // Step 4: Create GitHub release - if (!executeStep('npm run _github-release', 'Creating GitHub release')) { - // eslint-disable-next-line no-console - console.log( - 'Warning: GitHub release creation failed, but continuing with deployment...' - ) - } - - // Step 5: Publish to NPM - if (!executeStep('npm publish', 'Publishing to NPM')) { - // eslint-disable-next-line no-process-exit - process.exit(1) - } - - // Get the new version from package.json - const packageJsonPath = path.join(packageDir, 'package.json') - const packageJson = JSON.parse(fs.readFileSync(packageJsonPath, 'utf8')) - const newVersion = packageJson.version - - // eslint-disable-next-line no-console - console.log( - `\n🎉 @soulcraft/brainy-models-package v${newVersion} release completed successfully! 🎉\n` - ) - // eslint-disable-next-line no-console - console.log('Summary of actions:') - // eslint-disable-next-line no-console - console.log(`- Package built and tested`) - // eslint-disable-next-line no-console - console.log(`- Version bumped to v${newVersion} (${versionType})`) - // eslint-disable-next-line no-console - console.log(`- CHANGELOG.md updated with recent commits`) - // eslint-disable-next-line no-console - console.log(`- GitHub release created with auto-generated notes`) - // eslint-disable-next-line no-console - console.log(`- Package published to NPM as @soulcraft/brainy-models-package`) - // eslint-disable-next-line no-console - console.log( - '\nThank you for using the brainy-models-package release workflow!\n' - ) -} - -// Run the workflow -runReleaseWorkflow().catch((error) => { - // eslint-disable-next-line no-console - console.error('Unexpected error during release workflow:', error) - // eslint-disable-next-line no-process-exit - process.exit(1) -}) diff --git a/brainy-models-package/src/index.ts b/brainy-models-package/src/index.ts deleted file mode 100644 index 65a3fdc1..00000000 --- a/brainy-models-package/src/index.ts +++ /dev/null @@ -1,302 +0,0 @@ -/** - * @soulcraft/brainy-models - * - * Pre-bundled TensorFlow models for maximum reliability with Brainy vector database. - * This package provides offline access to the Universal Sentence Encoder model, - * eliminating network dependencies and ensuring consistent performance. - */ - -import * as tf from '@tensorflow/tfjs' -import { readFileSync, existsSync } from 'fs' -import { join, dirname } from 'path' -import { fileURLToPath } from 'url' - -/** - * Helper function to safely extract error message from unknown error type - */ -function getErrorMessage(error: unknown): string { - if (error instanceof Error) { - return error.message - } - if (typeof error === 'string') { - return error - } - return String(error) -} - -// Get the package directory -const __filename = fileURLToPath(import.meta.url) -const __dirname = dirname(__filename) -const PACKAGE_ROOT = join(__dirname, '..') -const MODELS_DIR = join(PACKAGE_ROOT, 'models') - -export interface ModelMetadata { - name: string - version: string - description: string - dimensions: number - downloadDate: string - source: string - approach: string - modelUrl: string - bundledLocally: boolean - reliability: string -} - -export interface BundledModelOptions { - verbose?: boolean - preferCompressed?: boolean -} - -/** - * Bundled Universal Sentence Encoder for offline use - */ -export class BundledUniversalSentenceEncoder { - private model: tf.GraphModel | null = null - private metadata: ModelMetadata | null = null - private options: BundledModelOptions - - constructor(options: BundledModelOptions = {}) { - this.options = { - verbose: false, - preferCompressed: false, - ...options - } - } - - /** - * Load the bundled model from local files - */ - async load(): Promise { - try { - const modelDir = join(MODELS_DIR, 'universal-sentence-encoder') - const modelPath = join(modelDir, 'model.json') - const metadataPath = join(modelDir, 'metadata.json') - - if (!existsSync(modelPath)) { - throw new Error( - `Bundled model not found at ${modelPath}. ` + - 'Please run "npm run download-models" to download the model files.' - ) - } - - if (this.options.verbose) { - console.log('🔄 Loading bundled Universal Sentence Encoder model...') - } - - // Load metadata - if (existsSync(metadataPath)) { - const metadataContent = readFileSync(metadataPath, 'utf8') - this.metadata = JSON.parse(metadataContent) - - if (this.options.verbose) { - console.log(`📋 Model metadata:`, this.metadata) - } - } - - // Load the model - this.model = await tf.loadGraphModel(`file://${modelPath}`) - - if (this.options.verbose) { - console.log('✅ Bundled model loaded successfully') - console.log(`🔒 Reliability: Maximum (fully offline)`) - } - - } catch (error) { - throw new Error(`Failed to load bundled model: ${getErrorMessage(error)}`) - } - } - - /** - * Generate embeddings for the given texts - */ - async embed(texts: string[]): Promise { - if (!this.model) { - throw new Error('Model not loaded. Call load() first.') - } - - try { - // Convert texts to tensor - const inputTensor = tf.tensor1d(texts, 'string') - - // Run inference - const embeddings = this.model.predict(inputTensor) as tf.Tensor2D - - // Clean up input tensor - inputTensor.dispose() - - return embeddings - } catch (error) { - throw new Error(`Failed to generate embeddings: ${getErrorMessage(error)}`) - } - } - - /** - * Generate embeddings and return as JavaScript arrays - */ - async embedToArrays(texts: string[]): Promise { - const embeddings = await this.embed(texts) - const arrays = await embeddings.array() as number[][] - embeddings.dispose() - return arrays - } - - /** - * Get model metadata - */ - getMetadata(): ModelMetadata | null { - return this.metadata - } - - /** - * Check if the model is loaded - */ - isLoaded(): boolean { - return this.model !== null - } - - /** - * Get model information - */ - getModelInfo(): { inputShape: number[], outputShape: number[] } | null { - if (!this.model) { - return null - } - - return { - inputShape: this.model.inputs[0].shape || [], - outputShape: this.model.outputs[0].shape || [] - } - } - - /** - * Dispose of the model and free memory - */ - dispose(): void { - if (this.model) { - this.model.dispose() - this.model = null - } - } -} - -/** - * Model compression utilities - */ -export class ModelCompressor { - /** - * Compress model weights using quantization - * Note: TensorFlow.js doesn't currently support model quantization - */ - static async quantizeModel( - modelPath: string, - outputPath: string, - options: { dtype?: 'int8' | 'int16' } = {} - ): Promise { - const { dtype = 'int8' } = options - - try { - console.log(`🔄 Loading model for quantization: ${modelPath}`) - const model = await tf.loadGraphModel(`file://${modelPath}`) - - console.log(`🗜️ Quantizing model to ${dtype}...`) - - // TensorFlow.js doesn't have built-in quantization or model serialization APIs yet - // This is a placeholder implementation that acknowledges the limitation - console.warn('⚠️ Model quantization is not yet supported in TensorFlow.js') - console.log(`📋 Model loaded successfully from: ${modelPath}`) - console.log(`📋 Target output path: ${outputPath}`) - console.log(`📋 Target dtype: ${dtype}`) - - model.dispose() - - throw new Error('Model quantization is not yet supported in TensorFlow.js. This feature requires server-side processing with TensorFlow Python.') - } catch (error) { - throw new Error(`Failed to compress model: ${getErrorMessage(error)}`) - } - } - - /** - * Get model size information by reading files from disk - */ - static async getModelSize(modelPath: string): Promise<{ - totalSize: number - weightsSize: number - modelJsonSize: number - }> { - try { - // Load model to verify it's valid - const model = await tf.loadGraphModel(`file://${modelPath}`) - model.dispose() - - // Get model.json size - const modelJsonSize = existsSync(modelPath) ? readFileSync(modelPath).length : 0 - - // Calculate weights size by reading weight files - let weightsSize = 0 - const modelDir = dirname(modelPath) - - // Read model.json to get weight file names - if (existsSync(modelPath)) { - const modelJson = JSON.parse(readFileSync(modelPath, 'utf8')) - if (modelJson.weightsManifest) { - for (const manifest of modelJson.weightsManifest) { - for (const path of manifest.paths) { - const weightFilePath = join(modelDir, path) - if (existsSync(weightFilePath)) { - weightsSize += readFileSync(weightFilePath).length - } - } - } - } - } - - const totalSize = weightsSize + modelJsonSize - - return { - totalSize, - weightsSize, - modelJsonSize - } - } catch (error) { - throw new Error(`Failed to get model size: ${getErrorMessage(error)}`) - } - } -} - -/** - * Utility functions - */ -export const utils = { - /** - * Check if bundled models are available - */ - checkModelsAvailable(): boolean { - const modelPath = join(MODELS_DIR, 'universal-sentence-encoder', 'model.json') - return existsSync(modelPath) - }, - - /** - * Get bundled models directory - */ - getModelsDirectory(): string { - return MODELS_DIR - }, - - /** - * List available bundled models - */ - listAvailableModels(): string[] { - const models: string[] = [] - const useModelPath = join(MODELS_DIR, 'universal-sentence-encoder', 'model.json') - - if (existsSync(useModelPath)) { - models.push('universal-sentence-encoder') - } - - return models - } -} - -// Default export for convenience -export default BundledUniversalSentenceEncoder diff --git a/brainy-models-package/tsconfig.json b/brainy-models-package/tsconfig.json deleted file mode 100644 index 90c806d1..00000000 --- a/brainy-models-package/tsconfig.json +++ /dev/null @@ -1,29 +0,0 @@ -{ - "compilerOptions": { - "target": "ES2022", - "module": "ESNext", - "moduleResolution": "node", - "lib": ["ES2022"], - "outDir": "./dist", - "rootDir": "./src", - "strict": true, - "esModuleInterop": true, - "skipLibCheck": true, - "forceConsistentCasingInFileNames": true, - "declaration": true, - "declarationMap": true, - "sourceMap": true, - "removeComments": false, - "allowSyntheticDefaultImports": true, - "resolveJsonModule": true - }, - "include": [ - "src/**/*" - ], - "exclude": [ - "node_modules", - "dist", - "test", - "scripts" - ] -} diff --git a/reproduce_error.js b/reproduce_error.js deleted file mode 100644 index b5340894..00000000 --- a/reproduce_error.js +++ /dev/null @@ -1,27 +0,0 @@ -#!/usr/bin/env node - -/** - * Script to reproduce the FileSystemStorage initialization error - */ - -import { createStorage } from './dist/unified.js' - -async function reproduceError() { - console.log('Attempting to reproduce FileSystemStorage error...') - - try { - // This should trigger the same error as in the test - const storage = await createStorage({ forceFileSystemStorage: true }) - console.log('Storage created successfully:', storage.constructor.name) - - // This should fail with the fs/path modules error - await storage.init() - console.log('Storage initialized successfully') - - } catch (error) { - console.error('Error reproduced:', error.message) - console.error('Full error:', error) - } -} - -reproduceError() diff --git a/reproduce_race_condition.cjs b/reproduce_race_condition.cjs deleted file mode 100644 index f19a2e74..00000000 --- a/reproduce_race_condition.cjs +++ /dev/null @@ -1,236 +0,0 @@ -#!/usr/bin/env node - -/** - * Reproduction script for race condition issues in Brainy - * - * This script demonstrates two main issues: - * 1. Race condition: Verbs arrive before their associated nouns are indexed - * 2. Indexing delay: Newly inserted nouns can't be looked up immediately - */ - -const { BrainyData } = require('./dist/unified.js'); - -async function reproduceRaceCondition() { - console.log('🧠 Starting Brainy Race Condition Reproduction Test'); - console.log('=' .repeat(60)); - - const brainy = new BrainyData({ - dimensions: 512, // Use correct dimensions for Universal Sentence Encoder - maxConnections: 16, - efConstruction: 200, - storageType: 'memory' // Use memory storage for faster testing - }); - - await brainy.init(); - - console.log('\n📊 Test 1: Race Condition - Verbs before Nouns'); - console.log('-'.repeat(50)); - - try { - // Simulate streaming data where verbs arrive before nouns - const sourceId = 'user-123'; - const targetId = 'post-456'; - - console.log(`Attempting to add verb between ${sourceId} and ${targetId} before nouns exist...`); - - // This should fail because the nouns don't exist yet - await brainy.addVerb(sourceId, targetId, null, { - type: 'likes', - metadata: { action: 'like', timestamp: Date.now() } - }); - - console.log('❌ Expected failure did not occur - this indicates the race condition is not properly handled'); - - } catch (error) { - console.log('✅ Expected error occurred:', error.message); - } - - console.log('\n📊 Test 2: Indexing Delay Issue'); - console.log('-'.repeat(50)); - - try { - // Add a noun - const nounId = 'rapid-noun-' + Date.now(); - console.log(`Adding noun with ID: ${nounId}`); - - await brainy.add(Array.from({length: 512}, () => Math.random()), { - type: 'user', - name: 'Test User' - }, { id: nounId }); - - console.log('✅ Noun added successfully'); - - // Immediately try to add a verb that references this noun - const verbTargetId = 'target-' + Date.now(); - - // Add target noun - await brainy.add(Array.from({length: 512}, () => Math.random()), { - type: 'post', - title: 'Test Post' - }, { id: verbTargetId }); - - console.log('✅ Target noun added successfully'); - - // Now try to add verb immediately - this might fail due to indexing delay - console.log(`Attempting to add verb between ${nounId} and ${verbTargetId} immediately after noun creation...`); - - const verbId = await brainy.addVerb(nounId, verbTargetId, null, { - type: 'created', - metadata: { action: 'create', timestamp: Date.now() } - }); - - console.log('✅ Verb added successfully with ID:', verbId); - - } catch (error) { - console.log('❌ Indexing delay error occurred:', error.message); - } - - console.log('\n📊 Test 3: Rapid Streaming Simulation'); - console.log('-'.repeat(50)); - - const errors = []; - const successes = []; - - // Simulate rapid streaming of mixed noun and verb data - const operations = []; - - for (let i = 0; i < 50; i++) { - const userId = `user-${i}`; - const postId = `post-${i}`; - - // Randomly order noun and verb operations to simulate streaming - if (Math.random() > 0.5) { - // Add verb first (should fail without autoCreateMissingNouns) - operations.push({ - type: 'verb', - sourceId: userId, - targetId: postId, - verbType: 'likes', - id: i - }); - - // Then add nouns - operations.push({ - type: 'noun', - id: userId, - vector: Array.from({length: 512}, () => Math.random()), - metadata: { type: 'user', name: `User ${i}` } - }); - - operations.push({ - type: 'noun', - id: postId, - vector: Array.from({length: 512}, () => Math.random()), - metadata: { type: 'post', title: `Post ${i}` } - }); - } else { - // Add nouns first - operations.push({ - type: 'noun', - id: userId, - vector: Array.from({length: 384}, () => Math.random()), - metadata: { type: 'user', name: `User ${i}` } - }); - - operations.push({ - type: 'noun', - id: postId, - vector: Array.from({length: 384}, () => Math.random()), - metadata: { type: 'post', title: `Post ${i}` } - }); - - // Then add verb - operations.push({ - type: 'verb', - sourceId: userId, - targetId: postId, - verbType: 'likes', - id: i - }); - } - } - - console.log(`Executing ${operations.length} operations in streaming order...`); - - for (const op of operations) { - try { - if (op.type === 'noun') { - await brainy.add(op.vector, op.metadata, { id: op.id }); - successes.push(`Added noun ${op.id}`); - } else if (op.type === 'verb') { - await brainy.addVerb(op.sourceId, op.targetId, null, { - type: op.verbType, - metadata: { streamingTest: true, operationId: op.id } - }); - successes.push(`Added verb ${op.sourceId} -> ${op.targetId}`); - } - } catch (error) { - errors.push(`${op.type} operation failed: ${error.message}`); - } - } - - console.log('\n📈 Results Summary:'); - console.log(`✅ Successful operations: ${successes.length}`); - console.log(`❌ Failed operations: ${errors.length}`); - - if (errors.length > 0) { - console.log('\n❌ Error Details:'); - errors.slice(0, 10).forEach(error => console.log(` - ${error}`)); - if (errors.length > 10) { - console.log(` ... and ${errors.length - 10} more errors`); - } - } - - console.log('\n📊 Test 4: Auto-Create Missing Nouns Feature'); - console.log('-'.repeat(50)); - - try { - const autoSourceId = 'auto-user-' + Date.now(); - const autoTargetId = 'auto-post-' + Date.now(); - - console.log(`Testing autoCreateMissingNouns feature with ${autoSourceId} -> ${autoTargetId}`); - - const autoVerbId = await brainy.addVerb(autoSourceId, autoTargetId, null, { - type: 'follows', - autoCreateMissingNouns: true, - missingNounMetadata: { autoCreated: true, testCase: 'reproduction' }, - metadata: { testFeature: 'autoCreate' } - }); - - console.log('✅ Auto-create feature worked! Verb ID:', autoVerbId); - - // Verify the auto-created nouns exist - const autoSourceNoun = await brainy.get(autoSourceId); - const autoTargetNoun = await brainy.get(autoTargetId); - - console.log('✅ Auto-created source noun exists:', !!autoSourceNoun); - console.log('✅ Auto-created target noun exists:', !!autoTargetNoun); - - } catch (error) { - console.log('❌ Auto-create feature failed:', error.message); - } - - await brainy.shutDown(); - - console.log('\n🏁 Race Condition Reproduction Test Complete'); - console.log('=' .repeat(60)); - - if (errors.length > 0) { - console.log('\n💡 Recommendations:'); - console.log('1. Implement fallback storage lookup when index lookup fails'); - console.log('2. Add deferred resolution queue for missing noun references'); - console.log('3. Implement write-only mode that bypasses index checks'); - console.log('4. Add proper index synchronization mechanisms'); - - process.exit(1); - } else { - console.log('\n✅ All tests passed - race conditions may already be handled'); - process.exit(0); - } -} - -// Run the reproduction test -reproduceRaceCondition().catch(error => { - console.error('💥 Reproduction script failed:', error); - process.exit(1); -}); diff --git a/reproduce_writeonly_issue.js b/reproduce_writeonly_issue.js deleted file mode 100644 index 49f01077..00000000 --- a/reproduce_writeonly_issue.js +++ /dev/null @@ -1,127 +0,0 @@ -#!/usr/bin/env node - -/** - * Script to reproduce the write-only mode issues described in the GitHub issue - */ - -import { BrainyData } from './dist/unified.js' - -async function reproduceWriteOnlyIssues() { - console.log('🧠 Reproducing write-only mode issues...\n') - - try { - // Create a BrainyData instance - const brainy = new BrainyData({ - dimensions: 512, - storage: { - type: 'memory' - } - }) - - // Initialize the database - await brainy.init() - console.log('✅ BrainyData initialized') - - // Set to write-only mode - brainy.setWriteOnly(true) - console.log('✅ Set to write-only mode') - - // Try to add some data - this should work - console.log('\n📝 Testing add operations in write-only mode...') - const id1 = await brainy.add('This is test data 1', { type: 'test' }) - console.log(`✅ Added item with ID: ${id1}`) - - const id2 = await brainy.add('This is test data 2', { type: 'test' }) - console.log(`✅ Added item with ID: ${id2}`) - - // Try to search - this should fail with current implementation - console.log('\n🔍 Testing search operations in write-only mode...') - try { - const results = await brainy.search('test query', 5) - console.log('❌ UNEXPECTED: Search succeeded in write-only mode') - console.log('Results:', results) - } catch (error) { - console.log('✅ EXPECTED: Search failed in write-only mode') - console.log('Error:', error.message) - } - - // Try existence check via get() - this should now work in write-only mode - console.log('\n🔍 Testing existence checks in write-only mode...') - try { - const item = await brainy.get(id1) - console.log('✅ EXPECTED: Get operation succeeded in write-only mode (existence check)') - console.log('Item found:', item ? 'Yes' : 'No') - if (item) { - console.log('Item ID:', item.id) - console.log('Has metadata:', !!item.metadata) - } - } catch (error) { - console.log('❌ UNEXPECTED: Get operation failed in write-only mode') - console.log('Error:', error.message) - } - - // Test adding with existing ID to verify existence check - console.log('\n🔄 Testing existence check during add operation...') - try { - const duplicateId = await brainy.add('This is duplicate data', { type: 'duplicate' }, { id: id1 }) - console.log('✅ Successfully handled duplicate ID:', duplicateId) - } catch (error) { - console.log('❌ Failed to handle duplicate ID:', error.message) - } - - // Test addVerb with writeOnlyMode to see placeholder noun behavior - console.log('\n🔗 Testing addVerb with writeOnlyMode (placeholder nouns)...') - try { - const verbId = await brainy.addVerb('noun1', 'noun2', undefined, { - type: 'relates_to', - writeOnlyMode: true, - metadata: { test: 'verb' } - }) - console.log(`✅ Added verb with placeholder nouns, ID: ${verbId}`) - } catch (error) { - console.log('❌ Failed to add verb with writeOnlyMode:', error.message) - } - - // Switch back to normal mode to test search - console.log('\n🔄 Switching back to normal mode...') - brainy.setWriteOnly(false) - - try { - const results = await brainy.search('test', 5) - console.log(`✅ Search succeeded in normal mode, found ${results.length} results`) - - // Check if any results are placeholder nouns - const placeholderResults = results.filter(r => - r.metadata && - typeof r.metadata === 'object' && - 'writeOnlyMode' in r.metadata - ) - - if (placeholderResults.length > 0) { - console.log('⚠️ WARNING: Found placeholder nouns in search results:') - placeholderResults.forEach(r => { - console.log(` - ID: ${r.id}, metadata:`, r.metadata) - }) - } else { - console.log('✅ No placeholder nouns found in search results') - } - } catch (error) { - console.log('❌ Search failed in normal mode:', error.message) - } - - console.log('\n📊 Summary of Implementation Status:') - console.log('1. ✅ Search operations properly blocked in write-only mode with helpful error message') - console.log('2. ✅ Existence checks (get operations) now work in write-only mode via storage') - console.log('3. ✅ Add operations can check for existing data in write-only mode') - console.log('4. ✅ Placeholder nouns are filtered out of search results') - console.log('5. ✅ Mechanism implemented to update placeholder nouns when real data is found') - console.log('6. ✅ Auto-configuration: Brainy detects write-only mode and skips index loading') - console.log('\n🎉 All write-only mode issues have been resolved!') - - } catch (error) { - console.error('❌ Error during reproduction:', error) - } -} - -// Run the reproduction script -reproduceWriteOnlyIssues().catch(console.error) diff --git a/test-consumer/package-lock.json b/test-consumer/package-lock.json deleted file mode 100644 index ed68605d..00000000 --- a/test-consumer/package-lock.json +++ /dev/null @@ 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"file:soulcraft-brainy-0.41.0.tgz" - } -} diff --git a/test-consumer/test.mjs b/test-consumer/test.mjs deleted file mode 100644 index 51eb989e..00000000 --- a/test-consumer/test.mjs +++ /dev/null @@ -1,29 +0,0 @@ -import { BrainyData } from '@soulcraft/brainy'; - -async function testBrainy() { - try { - console.log('Creating BrainyData instance...'); - const brainy = new BrainyData({ - storageType: 'memory', - defaultEmbeddingOptions: { verbose: false } - }); - - console.log('Initializing...'); - await brainy.init(); - - console.log('Adding data...'); - await brainy.add({ name: 'test', data: 'Test document' }); - - console.log('Searching...'); - const results = await brainy.search({ query: 'test' }); - console.log('Search results:', results); - - console.log('Test completed successfully!'); - process.exit(0); - } catch (error) { - console.error('Test failed:', error); - process.exit(1); - } -} - -testBrainy(); \ No newline at end of file diff --git a/test-results.json b/test-results.json deleted file mode 100644 index eca10ca1..00000000 --- a/test-results.json +++ /dev/null @@ -1 +0,0 @@ -{"numTotalTestSuites":93,"numPassedTestSuites":93,"numFailedTestSuites":0,"numPendingTestSuites":0,"numTotalTests":196,"numPassedTests":178,"numFailedTests":0,"numPendingTests":18,"numTodoTests":0,"snapshot":{"added":0,"failure":false,"filesAdded":0,"filesRemoved":0,"filesRemovedList":[],"filesUnmatched":0,"filesUpdated":0,"matched":0,"total":0,"unchecked":0,"uncheckedKeysByFile":[],"unmatched":0,"updated":0,"didUpdate":false},"startTime":1753892392127,"success":true,"testResults":[{"assertionResults":[{"ancestorTitles":["API Integration Tests"],"fullName":"API Integration Tests should insert text and then find it via search","status":"passed","title":"should insert text and then find it via search","duration":516.9494899999991,"failureMessages":[],"meta":{}},{"ancestorTitles":["API Integration Tests"],"fullName":"API Integration Tests should handle vector 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Condition Fixes'); - console.log('=' .repeat(50)); - - const brainy = new BrainyData({ - dimensions: 512, - maxConnections: 16, - efConstruction: 200, - storageType: 'memory' - }); - - await brainy.init(); - - console.log('\n📊 Test 1: Write-Only Mode'); - console.log('-'.repeat(30)); - - try { - // Test writeOnlyMode - should succeed even without existing nouns - const verbId = await brainy.addVerb('user-writeonly-1', 'post-writeonly-1', null, { - type: 'likes', - writeOnlyMode: true, - metadata: { test: 'writeOnlyMode' } - }); - - console.log('✅ Write-only mode verb added successfully:', verbId); - - // Verify the verb was created - const verb = await brainy.getVerb(verbId); - console.log('✅ Verb retrieved successfully:', !!verb); - - } catch (error) { - console.log('❌ Write-only mode test failed:', error.message); - } - - console.log('\n📊 Test 2: Auto-Create Missing Nouns'); - console.log('-'.repeat(30)); - - try { - // Test autoCreateMissingNouns - const verbId2 = await brainy.addVerb('user-auto-1', 'post-auto-1', null, { - type: 'follows', - autoCreateMissingNouns: true, - metadata: { test: 'autoCreate' } - }); - - console.log('✅ Auto-create verb added successfully:', verbId2); - - // Verify the auto-created nouns exist - const sourceNoun = await brainy.get('user-auto-1'); - const targetNoun = await brainy.get('post-auto-1'); - - console.log('✅ Auto-created source noun exists:', !!sourceNoun); - console.log('✅ Auto-created target noun exists:', !!targetNoun); - - } catch (error) { - console.log('❌ Auto-create test failed:', error.message); - } - - console.log('\n📊 Test 3: Normal Mode (Should Fail)'); - console.log('-'.repeat(30)); - - try { - // Test normal mode without existing nouns - should fail - await brainy.addVerb('user-normal-1', 'post-normal-1', null, { - type: 'mentions', - metadata: { test: 'normalMode' } - }); - - console.log('❌ Normal mode should have failed but succeeded'); - - } catch (error) { - console.log('✅ Normal mode correctly 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console.log('❌ Fallback storage lookup test failed:', error.message); - } - - await brainy.shutDown(); - - console.log('\n🏁 Race Condition Fixes Test Complete'); - console.log('=' .repeat(50)); -} - -// Run the test -testRaceConditionFixes().catch(error => { - console.error('💥 Test failed:', error); - process.exit(1); -});