Cargo.toml

[package]
name = "mega-mind"
version = "0.5.4"
edition = "2024"
rust-version = "1.89"
description = "Shared, searchable long-term memory for AI coding agents"
license = "MIT"

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

[[bin]]
name = "mind"
path = "src/main.rs"

[dependencies]
anstyle-query = "1.1.5"
anyhow = "1.0.104"
chrono = "0.4.45"
clap = { version = "4.6.7", features = ["derive"] }
fastembed = { version = "7.5.0", default-features = false, features = ["onnx", "ort-download-binaries-rustls-tls", "hf-hub-rustls-tls"], optional = true }
fs2 = "0.4.3"
hex = "0.4.3"
regex = "1.13.1"
rusqlite = { version = "0.41.1", features = ["bundled"] }
serde = { version = "1.0.229", features = ["derive"] }
serde_json = { version = "1.0.154", features = ["preserve_order"] }
serde_yaml = "0.9.34"
sha2 = "0.11.1"
toml = "1.1.8"
ureq = { version = "3.5.0", features = ["json", "platform-verifier"] }

[target.'cfg(unix)'.dependencies]
libc = "0.2.191"

[features]
# The built-in CPU embedding model. Downloads ONNX Runtime at build time and the model from
# Hugging Face on first use, so it is off by default; without it, use Azure/OpenAI-compatible
# embeddings or keyword-only search (see `mind setup`).
local-embeddings = ["dep:fastembed"]

[profile.release]
lto = "thin"
strip = true

[target.'cfg(windows)'.dependencies]
# The link count of a file (std's is unstable on Windows): the hard-link check.
windows-sys = { version = "0.61", features = ["Win32_Foundation", "Win32_Storage_FileSystem"] }