[package]
name = "ruvector-gnn"
version.workspace = true
edition.workspace = true
rust-version.workspace = true
license.workspace = true
authors.workspace = true
repository.workspace = true
readme = "README.md"
description = "Graph Neural Network layer for Ruvector on HNSW topology"

[dependencies]
# Core
ruvector-core = { version = "2.0.1", path = "../ruvector-core", default-features = false }

# Math and numerics
ndarray = { workspace = true, features = ["serde"] }
rand = { workspace = true }
rand_distr = { workspace = true }

# Serialization
serde = { workspace = true }
serde_json = { workspace = true }

# Error handling
thiserror = { workspace = true }
anyhow = { workspace = true }

# Performance
rayon = { workspace = true }
parking_lot = { workspace = true }
dashmap = { workspace = true }

# Memory mapping (non-WASM only)
memmap2 = { workspace = true, optional = true }
page_size = { version = "0.6", optional = true }

# Platform-specific dependencies
[target.'cfg(target_os = "linux")'.dependencies]
libc = "0.2"

# Optional dependencies
napi = { workspace = true, optional = true }
napi-derive = { workspace = true, optional = true }

[features]
default = ["simd", "mmap"]
simd = []
wasm = []
napi = ["dep:napi", "dep:napi-derive"]
mmap = ["dep:memmap2", "dep:page_size"]
cold-tier = ["mmap"]  # Hyperbatch training for graphs exceeding RAM

[dev-dependencies]
criterion = { workspace = true }
proptest = { workspace = true }
tempfile = "3.10"

[lib]
crate-type = ["rlib"]