[package]
name = "ml-training-service"
version.workspace = true
edition.workspace = true
rust-version.workspace = true
authors.workspace = true
license.workspace = true
description = "ML Training Service - Model training orchestration and lifecycle management for HFT trading"

[dependencies]
# Core async and utilities - USE WORKSPACE
tokio.workspace = true
uuid.workspace = true
serde.workspace = true
serde_json.workspace = true
chrono.workspace = true
thiserror.workspace = true
anyhow.workspace = true
num_cpus.workspace = true
clap.workspace = true
rust_decimal.workspace = true

# gRPC and protocol buffers - USE WORKSPACE
tonic.workspace = true
tonic-prost.workspace = true
tonic-health.workspace = true
tonic-reflection.workspace = true
prost.workspace = true
prost-types.workspace = true

# Database and compression - USE WORKSPACE
sqlx.workspace = true
flate2.workspace = true

# Async streams and utilities - USE WORKSPACE
tokio-stream.workspace = true
tokio-util.workspace = true
async-stream.workspace = true
futures.workspace = true
async-trait.workspace = true
tokio-retry.workspace = true

# Logging, tracing and metrics - USE WORKSPACE
tracing.workspace = true
tracing-subscriber.workspace = true
metrics.workspace = true
metrics-exporter-prometheus.workspace = true
prometheus.workspace = true
once_cell.workspace = true

# Utilities - USE WORKSPACE
base64.workspace = true
rand.workspace = true
regex.workspace = true
axum.workspace = true  # Health endpoint HTTP server

# Redis for job queue persistence
redis = { version = "0.27", features = ["tokio-comp", "connection-manager"] }

# Unix signal handling (for stopping Optuna subprocesses gracefully)
[target.'cfg(unix)'.dependencies]
nix = { version = "0.29", features = ["signal"] }

# Cryptography - Production-grade encryption
aes-gcm = "0.10"
chacha20poly1305 = "0.10"
pbkdf2 = { version = "0.12", features = ["simple"] }
sha2 = "0.10"
zeroize = { version = "1.6", features = ["alloc"] }

# X.509 certificate parsing for mTLS
x509-parser = "0.16"
reqwest = { version = "0.12", features = ["rustls-tls"], default-features = false }
rustls = { version = "0.23", features = ["ring"] }

# PyTorch dependencies REMOVED - unacceptable for HFT latency requirements
# All ML training uses ml-core native CUDA autograd

# Internal workspace crates
trading_engine.workspace = true
risk.workspace = true
ml = { path = "../../crates/ml", default-features = false, features = ["financial"] }  # Minimal ML for compilation — CPU only
data.workspace = true
config = { workspace = true, features = ["postgres"] }
common = { workspace = true, features = ["database"] }
storage.workspace = true  # Add missing storage dependency
# Model functionality from ml-data
ml-data = { path = "../../crates/ml-data" }

# Object store dependencies for S3 integration
object_store = { workspace = true, features = ["aws"] }
bytes.workspace = true

# DBN (Databento Binary) for real market data loading
dbn = "0.42.0"

# K8s API for job dispatch
kube = { version = "0.98", features = ["runtime", "client", "derive"] }
k8s-openapi = { version = "0.24", features = ["latest"] }

[build-dependencies]
# NOTE: Tonic 0.14+ uses tonic-prost-build instead of tonic-build
tonic-prost-build.workspace = true
prost-build.workspace = true

[[bin]]
name = "ml-training-service"
path = "src/main.rs"

[dev-dependencies]
tempfile.workspace = true
tower.workspace = true  # Use workspace version (0.4)
tower-test = "0.4.0"  # Match workspace tower version
jsonwebtoken = "9.3"
sysinfo = "0.30"  # For stress test memory monitoring
arrow.workspace = true  # For test data generation (Parquet)
parquet.workspace = true  # For Parquet file writing

[features]
default = ["minimal"]  # Production default: real data loading
minimal = ["ml/financial"]
gpu = ["ml/simd"]  # GPU features use ml-core native CUDA autograd
debug = []
mock-data = []  # Enable mock training data for testing (DO NOT USE IN PRODUCTION)