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https://github.com/samvallad33/vestige.git
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c2d28f3433
The biggest release in Vestige history. Complete visual and cognitive overhaul. Dashboard: - SvelteKit 2 + Three.js 3D neural visualization at localhost:3927/dashboard - 7 interactive pages: Graph, Memories, Timeline, Feed, Explore, Intentions, Stats - WebSocket event bus with 16 event types, real-time 3D animations - Bloom post-processing, GPU instanced rendering, force-directed layout - Dream visualization mode, FSRS retention curves, command palette (Cmd+K) - Keyboard shortcuts, responsive mobile layout, PWA installable - Single binary deployment via include_dir! (22MB) Engine: - HyDE query expansion (intent classification + 3-5 semantic variants + centroid) - fastembed 5.11 with optional Nomic v2 MoE + Qwen3 reranker + Metal GPU - Emotional memory module (#29) - Criterion benchmark suite Backend: - Axum WebSocket at /ws with heartbeat + event broadcast - 7 new REST endpoints for cognitive operations - Event emission from MCP tools via shared broadcast channel - CORS for SvelteKit dev mode Distribution: - GitHub issue templates (bug report, feature request) - CHANGELOG with comprehensive v2.0 release notes - README updated with dashboard docs, architecture diagram, comparison table 734 tests passing, zero warnings, 22MB release binary. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
112 lines
3.5 KiB
TOML
112 lines
3.5 KiB
TOML
[package]
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name = "vestige-core"
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version = "2.0.0"
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edition = "2024"
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rust-version = "1.85"
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authors = ["Vestige Team"]
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description = "Cognitive memory engine - FSRS-6 spaced repetition, semantic embeddings, and temporal memory"
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license = "AGPL-3.0-only"
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repository = "https://github.com/samvallad33/vestige"
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keywords = ["memory", "spaced-repetition", "fsrs", "embeddings", "knowledge-graph"]
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categories = ["science", "database"]
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[features]
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default = ["embeddings", "vector-search", "bundled-sqlite"]
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# SQLite backend (default, unencrypted)
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bundled-sqlite = ["rusqlite/bundled"]
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# Encrypted SQLite via SQLCipher (mutually exclusive with bundled-sqlite)
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# Use: --no-default-features --features encryption,embeddings,vector-search
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# Set VESTIGE_ENCRYPTION_KEY env var to enable encryption
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encryption = ["rusqlite/bundled-sqlcipher"]
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# Core embeddings with fastembed (ONNX-based, local inference)
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embeddings = ["dep:fastembed"]
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# HNSW vector search with USearch (20x faster than FAISS)
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vector-search = ["dep:usearch"]
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# Nomic Embed Text v2 MoE (475M params, 305M active, Candle backend)
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# Requires: fastembed with nomic-v2-moe feature
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nomic-v2 = ["embeddings", "fastembed/nomic-v2-moe"]
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# Qwen3 Reranker (Candle backend, high-precision cross-encoder)
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qwen3-reranker = ["embeddings", "fastembed/qwen3"]
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# Metal GPU acceleration on Apple Silicon (significantly faster inference)
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metal = ["fastembed/metal"]
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# Full feature set including MCP protocol support
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full = ["embeddings", "vector-search"]
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# MCP (Model Context Protocol) support for Claude integration
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mcp = []
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[dependencies]
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# Serialization
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serde = { version = "1", features = ["derive"] }
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serde_json = "1"
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# Date/Time with full timezone support
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chrono = { version = "0.4", features = ["serde"] }
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# UUID v4 generation
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uuid = { version = "1", features = ["v4", "serde"] }
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# Error handling
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thiserror = "2"
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# Database - SQLite with FTS5 full-text search and JSON
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# Note: "bundled" or "bundled-sqlcipher" added via feature flags above
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rusqlite = { version = "0.38", features = ["chrono", "serde_json"] }
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# Platform-specific directories
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directories = "6"
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# Async runtime (required for codebase module)
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tokio = { version = "1", features = ["sync", "rt-multi-thread", "macros"] }
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# Tracing for structured logging
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tracing = "0.1"
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# Git integration for codebase memory
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# vendored-openssl: Compile OpenSSL from source for cross-compilation support
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git2 = { version = "0.20", features = ["vendored-openssl"] }
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# File watching for codebase memory
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notify = "8"
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# ============================================================================
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# OPTIONAL: Embeddings (fastembed v5 - local ONNX inference, 2026 bleeding edge)
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# ============================================================================
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# nomic-embed-text-v1.5: 768 dimensions, 8192 token context, Matryoshka support
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# v5.11: Adds Nomic v2 MoE (nomic-v2-moe feature) + Qwen3 reranker (qwen3 feature)
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fastembed = { version = "5.11", optional = true }
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# ============================================================================
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# OPTIONAL: Vector Search (USearch - HNSW, 20x faster than FAISS)
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# ============================================================================
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usearch = { version = "2", optional = true }
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# LRU cache for query embeddings
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lru = "0.16"
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[dev-dependencies]
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tempfile = "3"
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criterion = { version = "0.5", features = ["html_reports"] }
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[[bench]]
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name = "search_bench"
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harness = false
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[lib]
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name = "vestige_core"
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path = "src/lib.rs"
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# Enable doctests
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doctest = true
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[package.metadata.docs.rs]
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all-features = true
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rustdoc-args = ["--cfg", "docsrs"]
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