model2vec 1.2.0

A high-performance Dart wrapper for model2vec-rs using Rust FFI. Generate fast, local, and static text embeddings with minimal memory footprint using Native Assets.

1.2.0

• Lowered minimum Dart SDK requirement to 3.10.0 to support a wider range of environments.

1.1.0

New Features:

• getRecommendedModels() no longer calls FFI — now returns a hardcoded list of 7 models

• Removed get_model_list from FFI bindings (Rust, Dart, .h)

• generateEmbedding() now accepts maxLength parameter — signature changed

• generateBatchEmbeddings() now accepts maxLength and batchSize parameters — signature changed

• Streaming API — generateEmbeddingStream() for processing large datasets with batching and optional worker isolate

• Async API — generateEmbeddingAsync() and generateBatchEmbeddingsAsync() with maxLength / batchSize support

• Advanced init — initEmbedderAdvanced() with hfToken, cacheDirectory, normalize, subfolder

• In-memory init — initEmbedderFromBytes() for loading models from raw bytes

• boot() — manual initialization with a custom DynamicLibrary

• isNormalized — getter for L2-normalization check

• medianTokenLength — getter for median token length

• maxLength — token truncation parameter for generateEmbedding()

• batchSize — internal batching control for generateBatchEmbeddings()

• Model2VecUtils — vector math: cosineSimilarity, dotProduct, euclideanDistance, similaritySearch, similaritySearchWithThreshold, cosineDistance, normalize, meanPooling, quantizeToInt8, toBase64, fromBase64, pairwiseSimilarity

Improvements:

• Streaming API Performance: generateEmbeddingStream() now utilizes a single long-lived worker isolate instead of spawning one per batch, dramatically reducing IPC and memory overhead for large datasets.
• Inter-Isolate Communication: Switched from Map<String, dynamic> to Dart 3 Records for significantly faster and strictly typed isolate communication.
• FFI Optimization: generateEmbedding() in Rust rewritten to avoid array pointer allocations and correctly respect max_length.
• Refactored quantizeToInt8() to use Dart's native .clamp().
• Added clear documentation for zero-vector handling in cosineSimilarity and normalize.
• Added documentation warning about IPC overhead in generateEmbeddingStream for CLI/Server applications.
• Better error messages when loading the native library fails, explaining possible missing Rust builds.
• Cleaned up FFI bindings: removed dead get_model_list symbol from .h and bindings.
• generate_embedding in Rust now returns -5 on empty results instead of silently corrupting data.
• generate_batch_embeddings_advanced validates result count matches input count.
• Benchmark updated to run all 5 models.
• README fully rewritten with API reference and accurate model dimensions.

1.0.0

• Initial version.