[package]
name = "vestige-core"
version = "1.0.0"
edition = "2021"
rust-version = "1.75"
authors = ["Vestige Team"]
description = "Cognitive memory engine - FSRS-6 spaced repetition, semantic embeddings, and temporal memory"
license = "MIT OR Apache-2.0"
repository = "https://github.com/samvallad33/vestige"
keywords = ["memory", "spaced-repetition", "fsrs", "embeddings", "knowledge-graph"]
categories = ["science", "database"]

[features]
default = ["embeddings", "vector-search"]

# Core embeddings with fastembed (ONNX-based, local inference)
embeddings = ["dep:fastembed"]

# HNSW vector search with USearch (20x faster than FAISS)
vector-search = ["dep:usearch"]

# Full feature set including MCP protocol support
full = ["embeddings", "vector-search"]

# MCP (Model Context Protocol) support for Claude integration
mcp = []

[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
rusqlite = { version = "0.38", features = ["bundled", "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
git2 = "0.20"

# File watching for codebase memory
notify = "8"

# ============================================================================
# OPTIONAL: Embeddings (fastembed v5 - local ONNX inference, 2026 bleeding edge)
# ============================================================================
# BGE-base-en-v1.5: 768 dimensions, 85%+ Top-5 accuracy (vs 56% for MiniLM)
fastembed = { version = "5", 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"

[lib]
name = "vestige_core"
path = "src/lib.rs"

# Enable doctests
doctest = true

[package.metadata.docs.rs]
all-features = true
rustdoc-args = ["--cfg", "docsrs"]