vestige/crates/vestige-core/Cargo.toml
Sam Valladares c6090dc2ba fix: v2.0.1 release — fix broken installs, CI, security, and docs
Critical fixes:
- npm postinstall.js: BINARY_VERSION '1.1.3' → '2.0.1' (every install was 404ing)
- npm package name: corrected error messages to 'vestige-mcp-server'
- README: npm install command pointed to wrong package
- MSRV: bumped from 1.85 to 1.91 (uses floor_char_boundary from 1.91)
- CI: removed stale 'develop' branch from test.yml triggers

Security hardening:
- CSP: restricted connect-src from wildcard 'ws: wss:' to localhost-only
- Added X-Frame-Options, X-Content-Type-Options, Referrer-Policy, Permissions-Policy headers
- Added frame-ancestors 'none', base-uri 'self', form-action 'self' to CSP
- Capped retention_distribution endpoint from 10k to 1k nodes
- Added debug logging for WebSocket connections without Origin header

Maintenance:
- All clippy warnings fixed (58 total: redundant closures, collapsible ifs, no-op casts)
- All versions harmonized to 2.0.1 across Cargo.toml and package.json
- CLAUDE.md updated to match v2.0.1 (21 tools, 29 modules, 1238 tests)
- docs/CLAUDE-SETUP.md updated deprecated function names
- License corrected to AGPL-3.0-only in root package.json

1,238 tests passing, 0 clippy warnings.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-01 20:20:14 -06:00

107 lines
3.4 KiB
TOML

[package]
name = "vestige-core"
version = "2.0.1"
edition = "2024"
rust-version = "1.91"
authors = ["Vestige Team"]
description = "Cognitive memory engine - FSRS-6 spaced repetition, semantic embeddings, and temporal memory"
license = "AGPL-3.0-only"
repository = "https://github.com/samvallad33/vestige"
keywords = ["memory", "spaced-repetition", "fsrs", "embeddings", "knowledge-graph"]
categories = ["science", "database"]
[features]
default = ["embeddings", "vector-search", "bundled-sqlite"]
# SQLite backend (default, unencrypted)
bundled-sqlite = ["rusqlite/bundled"]
# Encrypted SQLite via SQLCipher (mutually exclusive with bundled-sqlite)
# Use: --no-default-features --features encryption,embeddings,vector-search
# Set VESTIGE_ENCRYPTION_KEY env var to enable encryption
encryption = ["rusqlite/bundled-sqlcipher"]
# Core embeddings with fastembed (ONNX-based, local inference)
embeddings = ["dep:fastembed"]
# HNSW vector search with USearch (20x faster than FAISS)
vector-search = ["dep:usearch"]
# Nomic Embed Text v2 MoE (475M params, 305M active, Candle backend)
# Requires: fastembed with nomic-v2-moe feature
nomic-v2 = ["embeddings", "fastembed/nomic-v2-moe"]
# Qwen3 Reranker (Candle backend, high-precision cross-encoder)
qwen3-reranker = ["embeddings", "fastembed/qwen3"]
# Metal GPU acceleration on Apple Silicon (significantly faster inference)
metal = ["fastembed/metal"]
[dependencies]
# Serialization
serde = { version = "1", features = ["derive"] }
serde_json = "1"
# Date/Time with full timezone support
chrono = { version = "0.4", features = ["serde"] }
# UUID v4 generation
uuid = { version = "1", features = ["v4", "serde"] }
# Error handling
thiserror = "2"
# Database - SQLite with FTS5 full-text search and JSON
# Note: "bundled" or "bundled-sqlcipher" added via feature flags above
rusqlite = { version = "0.38", features = ["chrono", "serde_json"] }
# Platform-specific directories
directories = "6"
# Async runtime (required for codebase module)
tokio = { version = "1", features = ["sync", "rt-multi-thread", "macros"] }
# Tracing for structured logging
tracing = "0.1"
# Git integration for codebase memory
# vendored-openssl: Compile OpenSSL from source for cross-compilation support
git2 = { version = "0.20", features = ["vendored-openssl"] }
# File watching for codebase memory
notify = "8"
# ============================================================================
# OPTIONAL: Embeddings (fastembed v5 - local ONNX inference, 2026 bleeding edge)
# ============================================================================
# nomic-embed-text-v1.5: 768 dimensions, 8192 token context, Matryoshka support
# v5.11: Adds Nomic v2 MoE (nomic-v2-moe feature) + Qwen3 reranker (qwen3 feature)
fastembed = { version = "5.11", optional = true }
# ============================================================================
# OPTIONAL: Vector Search (USearch - HNSW, 20x faster than FAISS)
# ============================================================================
usearch = { version = "2", optional = true }
# LRU cache for query embeddings
lru = "0.16"
[dev-dependencies]
tempfile = "3"
criterion = { version = "0.5", features = ["html_reports"] }
[[bench]]
name = "search_bench"
harness = false
[lib]
name = "vestige_core"
path = "src/lib.rs"
# Enable doctests
doctest = true
[package.metadata.docs.rs]
all-features = true
rustdoc-args = ["--cfg", "docsrs"]