Changed #

• Package Rename: Rust crate renamed to rag_engine_flutter for pub.dev distribution.
• iOS Podspec Fix: Resolved linker path issues for iOS builds.
• Asset Handling: Force-overwrite asset files to prevent stale cache issues.

Removed #

• Deprecated test_app and local-gemma-macos directories.

Added #

• LLM-Optimized Chunking: Introduced ChunkingService with Recursive Character Splitting and Overlap support.
• Improved Data Model: Separated storage into Source (original document) and Chunk (searchable parts).
• Context Assembly: Added ContextBuilder to intelligently assemble LLM context within a token budget.
• High-Level API: New SourceRagService for automated chunking, embedding, and indexing pipeline.
• Context Strategies: Support for relevanceFirst, diverseSources, and chronological context assembly strategies.

Added #

• Initial release
• On-device semantic search with HNSW vector indexing
• Rust-powered tokenization via HuggingFace tokenizers
• ONNX Runtime integration for embedding generation
• SQLite-based vector storage with content deduplication
• Batch embedding support with progress callback
• Cross-platform support (iOS and Android)

Features #

• initDb() - Initialize SQLite database
• addDocument() - Add documents with SHA256 deduplication
• searchSimilar() - HNSW-based semantic search
• rebuildHnswIndex() - Manual index rebuild
• EmbeddingService.embed() - Generate embeddings
• EmbeddingService.embedBatch() - Batch embedding

Performance #

• HNSW search: O(log n) complexity
• Tokenization: ~0.8ms for short text
• Embedding: ~4ms for short text, ~36ms for long text
• Search (100 docs): ~1ms