mirror of
https://github.com/ruvnet/RuVector.git
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2b6c9c57d6
Add native ONNX Runtime integration for production-ready semantic embeddings. ## New Features - `OnnxEmbedding` struct with `from_pretrained()` and `from_files()` methods - Feature flag: `onnx-embeddings` (optional, not default) - Auto-downloads models from HuggingFace Hub (~90MB for all-MiniLM-L6-v2) - Supports sentence-transformers, BGE, E5 model families - Thread-safe inference via RwLock<Session> - Mean pooling and L2 normalization for sentence transformers ## Dependencies (optional) - ort 2.0.0-rc.9 (ONNX Runtime) - tokenizers 0.20 (HuggingFace tokenizers) - hf-hub 0.3 (model downloads) ## Documentation - Updated ADR-114 with implementation details - Updated lib.rs deprecation warning to reference OnnxEmbedding Closes #263 Co-authored-by: Reuven <cohen@ruv-mac-mini.local>
111 lines
3.1 KiB
TOML
111 lines
3.1 KiB
TOML
[package]
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name = "ruvector-core"
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version.workspace = true
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edition.workspace = true
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rust-version.workspace = true
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license.workspace = true
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authors.workspace = true
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repository.workspace = true
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readme = "README.md"
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description = "High-performance Rust vector database core with HNSW indexing"
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[dependencies]
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# Core functionality
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redb = { workspace = true, optional = true }
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memmap2 = { workspace = true, optional = true }
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hnsw_rs = { workspace = true, optional = true }
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simsimd = { workspace = true, optional = true }
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rayon = { workspace = true, optional = true }
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crossbeam = { workspace = true, optional = true }
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# Serialization
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rkyv = { workspace = true }
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bincode = { workspace = true }
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serde = { workspace = true }
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serde_json = { workspace = true }
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# Error handling
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thiserror = { workspace = true }
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anyhow = { workspace = true }
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tracing = { workspace = true }
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# Math and numerics
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ndarray = { workspace = true, features = ["serde"] }
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rand = { workspace = true }
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rand_distr = { workspace = true }
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# Performance
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dashmap = { workspace = true }
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parking_lot = { workspace = true }
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once_cell = { workspace = true }
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# Time and UUID
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chrono = { workspace = true }
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uuid = { workspace = true, features = ["v4"] }
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# HTTP client for API embeddings (not available in WASM)
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reqwest = { version = "0.11", default-features = false, features = ["blocking", "json", "rustls-tls"], optional = true }
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# ONNX Runtime for local semantic embeddings (not available in WASM)
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ort = { version = "2.0.0-rc.9", optional = true }
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# Tokenizers for ONNX models
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tokenizers = { version = "0.20", default-features = false, features = ["onig"], optional = true }
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# HuggingFace Hub for model downloads
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hf-hub = { version = "0.3", optional = true }
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[dev-dependencies]
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criterion = { workspace = true }
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proptest = { workspace = true }
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mockall = { workspace = true }
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tempfile = "3.13"
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tracing-subscriber = { workspace = true }
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[[bench]]
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name = "distance_metrics"
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harness = false
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[[bench]]
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name = "hnsw_search"
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harness = false
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[[bench]]
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name = "quantization_bench"
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harness = false
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[[bench]]
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name = "batch_operations"
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harness = false
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[[bench]]
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name = "comprehensive_bench"
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harness = false
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[[bench]]
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name = "real_benchmark"
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harness = false
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[[bench]]
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name = "bench_simd"
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harness = false
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[[bench]]
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name = "bench_memory"
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harness = false
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[features]
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default = ["simd", "storage", "hnsw", "api-embeddings", "parallel"]
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simd = ["simsimd"] # SIMD acceleration (not available in WASM)
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parallel = ["rayon", "crossbeam"] # Parallel processing (not available in WASM)
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storage = ["redb", "memmap2"] # File-based storage (not available in WASM)
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hnsw = ["hnsw_rs"] # HNSW indexing (not available in WASM due to mmap dependency)
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memory-only = [] # Pure in-memory storage for WASM
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uuid-support = [] # Deprecated: uuid is now always included
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real-embeddings = [] # Feature flag for embedding provider API (use ApiEmbedding for production)
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api-embeddings = ["reqwest"] # API-based embeddings (not available in WASM)
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onnx-embeddings = ["ort", "tokenizers", "hf-hub"] # ONNX-based local embeddings (not available in WASM)
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[lib]
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crate-type = ["rlib"]
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bench = false
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