mirror of
https://github.com/ruvnet/RuVector.git
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5512729caf
Attribution: Based on Samsung SAIL Montreal's TinyRecursiveModels Repository: https://github.com/SamsungSAILMontreal/TinyRecursiveModels This commit adds a complete TRM implementation for recursive reasoning: ## Core Components - TrmConfig: Configuration with builder pattern, validation, serde support - TrmEngine: Main recursive reasoning engine with K iterations - MlpLatentUpdater: Fast MLP-based latent state updates with gated residual - AttentionLatentUpdater: Expressive multi-head cross-attention variant - AnswerRefiner: Answer refinement with residual connections - ConfidenceScorer: Confidence estimation with optional entropy adjustment - SonaBridge: SONA integration for adaptive K selection and learning ## Features - Configurable hidden/embedding dimensions (default 256) - K iterations (1-20) with n latent updates per iteration - Early stopping based on confidence threshold - Convergence detection via plateau monitoring - Trajectory recording for analysis and learning - Variable-length input handling via mean pooling - Thread-safe design with pre-allocated buffers ## Testing - 59 unit tests covering all components - 16 integration tests for full pipeline - Benchmark suite for performance measurement ## Architecture MLP variant: ~2-3x faster, good for simple queries Attention variant: More expressive, better for complex reasoning 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
178 lines
4.4 KiB
TOML
178 lines
4.4 KiB
TOML
[package]
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name = "ruvllm"
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version = "0.1.0"
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edition = "2021"
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rust-version = "1.77"
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license = "MIT"
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authors = ["Ruvector Team"]
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description = "Self-learning LLM with LFM2 and Ruvector integration"
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repository = "https://github.com/ruvnet/ruvector"
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readme = "README.md"
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keywords = ["llm", "self-learning", "vector-database", "rag", "lfm2"]
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categories = ["science", "machine-learning"]
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[dependencies]
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# Internal dependencies
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ruvector-core = { path = "../../crates/ruvector-core", default-features = false }
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ruvector-gnn = { path = "../../crates/ruvector-gnn", default-features = false }
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ruvector-attention = { path = "../../crates/ruvector-attention" }
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ruvector-graph = { path = "../../crates/ruvector-graph" }
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# Async runtime
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tokio = { version = "1.41", features = ["rt-multi-thread", "sync", "macros", "time", "fs"] }
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futures = "0.3"
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# Serialization
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serde = { version = "1.0", features = ["derive"] }
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serde_json = "1.0"
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bincode = { version = "2.0.0-rc.3", features = ["serde"] }
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toml = "0.8"
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# Numerics
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ndarray = { version = "0.16", features = ["serde", "rayon"] }
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rand = "0.8"
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rand_distr = "0.4"
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simsimd = "5.9"
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# Real LLM Inference (CPU + SIMD optimized)
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candle-core = { version = "0.8", optional = true }
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candle-nn = { version = "0.8", optional = true }
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candle-transformers = { version = "0.8", optional = true }
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hf-hub = { version = "0.3", features = ["tokio"], optional = true }
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tokenizers = { version = "0.20", optional = true }
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# Memory-mapped file support for large models
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memmap2 = { version = "0.9", optional = true }
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byteorder = { version = "1.5", optional = true }
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half = { version = "2.4", features = ["num-traits", "serde"], optional = true }
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dirs = { version = "5.0", optional = true }
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# SONA Export (optional - for HuggingFace export)
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ruvector-sona = { path = "../../crates/sona", optional = true }
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# Utilities
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uuid = { version = "1.11", features = ["v4", "serde"] }
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chrono = { version = "0.4", features = ["serde"] }
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thiserror = "2.0"
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anyhow = "1.0"
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tracing = "0.1"
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tracing-subscriber = { version = "0.3", features = ["env-filter"] }
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# Performance
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dashmap = "6.1"
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parking_lot = "0.12"
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lru = "0.12"
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rayon = "1.10"
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crossbeam = "0.8"
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once_cell = "1.20"
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# Hashing for deduplication
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ahash = "0.8"
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# Metrics
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prometheus = { version = "0.13", optional = true }
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# HTTP (optional server)
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axum = { version = "0.7", optional = true }
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tower = { version = "0.4", optional = true }
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tower-http = { version = "0.5", features = ["cors", "trace"], optional = true }
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# N-API bindings for Node.js
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napi = { version = "2.16", features = ["async", "serde-json"], optional = true }
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napi-derive = { version = "2.16", optional = true }
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[dev-dependencies]
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criterion = { version = "0.5", features = ["html_reports", "async_tokio"] }
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proptest = "1.5"
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tokio-test = "0.4"
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tempfile = "3.13"
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approx = "0.5"
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[features]
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default = ["storage", "metrics"]
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storage = ["ruvector-core/storage", "ruvector-core/hnsw"]
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metrics = ["prometheus"]
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server = ["axum", "tower", "tower-http"]
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# Real LLM inference with CPU SIMD optimization
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real-inference = ["candle-core", "candle-nn", "candle-transformers", "hf-hub", "tokenizers", "memmap2", "byteorder", "half", "dirs"]
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# HuggingFace export for learned patterns and LoRA weights
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hf-export = ["ruvector-sona"]
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# N-API bindings for Node.js
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napi = ["dep:napi", "dep:napi-derive"]
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full = ["storage", "metrics", "server", "real-inference", "hf-export"]
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[[bench]]
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name = "pipeline"
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harness = false
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[[bench]]
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name = "router"
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harness = false
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[[bench]]
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name = "memory"
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harness = false
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[[bench]]
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name = "attention"
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harness = false
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[[bench]]
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name = "sona_bench"
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harness = false
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[[bench]]
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name = "trm_bench"
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harness = false
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[[test]]
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name = "trm_integration_test"
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path = "tests/trm_integration_test.rs"
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[lib]
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name = "ruvllm"
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path = "src/lib.rs"
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crate-type = ["cdylib", "rlib"]
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[[bin]]
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name = "ruvllm-demo"
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path = "src/bin/demo.rs"
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[[bin]]
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name = "ruvllm-server"
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path = "src/bin/server.rs"
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required-features = ["server"]
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[[bin]]
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name = "ruvllm-bench"
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path = "src/bin/bench.rs"
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[[bin]]
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name = "ruvllm-benchmark-suite"
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path = "src/bin/benchmark_suite.rs"
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[[bin]]
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name = "ruvllm-simd-demo"
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path = "src/bin/simd_demo.rs"
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[[bin]]
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name = "ruvllm-pretrain"
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path = "src/bin/pretrain.rs"
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[[bin]]
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name = "ruvllm-export"
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path = "src/bin/export.rs"
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required-features = ["hf-export"]
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[[test]]
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name = "integration"
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path = "tests/integration.rs"
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[profile.release]
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opt-level = 3
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lto = "thin"
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codegen-units = 1
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[profile.bench]
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inherits = "release"
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debug = true
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