83d524f866
WIRE:
* q_mag_full/half/quarter — host-side mean of magnitude-branch q_out_buf
cols [b0..b0+b1] (Task 0.3 stub remediated). Cold-path dtoh at epoch
boundary via update_q_mag_means_cached(), cached in q_mag_means_cached,
read by q_magnitude_bucket_means().
* var_scale_mean — per-sample CudaSlice + host reduce over var_scale
written by experience_env_step at line 1422 (Task 0.3 stub remediated).
Host reducer averages only over slots where kernel wrote > 0 so
Var[Q]-disabled samples don't dilute the signal.
DELETE:
* segment_patience slot from reward_contrib group — term not wired in
kernel, slot reserved space for non-existent feature (Task 0.8 stub
remediated). reward_contrib [...] is now 5 floats not 6. Cascaded
through reward_contrib_fractions return type, trainer's
last_reward_contrib field, reward_component_audit_summary accessor,
and the reward_component_audit smoke test.
PopArt slot kept at 0.0 — that IS the semantic value during warmup or
disabled state, not a stub. Comment updated to make this explicit.
Per ~/.claude/.../memory/feedback_no_stubs.md: stubs strictly forbidden
even with code comments / commit-message documentation / plan sanction.
Foxhunt
Production HFT trading system in Rust.
Architecture
The workspace contains 32 crates organized as follows:
Core Libraries (16)
| Crate | Purpose |
|---|---|
trading_engine |
Order processing, FIX 4.4, IB TWS, SIMD, RDTSC timing |
risk |
VaR, Kelly, circuit breakers, kill switches, compliance |
risk-data |
Risk data types and shared structures |
trading-data |
Trading data types |
ml |
DQN Rainbow, PPO, TFT, Mamba2, ensemble inference |
ml-data |
ML data types and feature definitions |
data |
Market data ingestion and storage |
backtesting |
Replay engine, strategy tester |
adaptive-strategy |
Ensemble execution, microstructure analysis |
common |
Shared types, resilience, error handling |
storage |
S3 and local model storage |
model_loader |
Model serialization and loading |
market-data |
Market data feed handlers |
database |
PostgreSQL access layer (SQLx) |
config |
Configuration management |
tli |
CLI commands and tooling |
Services (8)
| Service | Purpose |
|---|---|
backtesting_service |
gRPC backtesting service |
broker_gateway_service |
FIX routing, broker connectivity |
trading_service |
Core trading operations |
ml_training_service |
Model training orchestration |
data_acquisition_service |
Market data acquisition |
trading_agent_service |
Autonomous trading agents |
api_gateway |
gRPC API gateway with auth |
web-gateway |
Axum REST + WebSocket gateway |
Frontend
web-dashboard/ -- React 19 + TypeScript + Vite + TradingView charts.
Building
# Check compilation (no PostgreSQL required)
SQLX_OFFLINE=true cargo check --workspace
# Run tests for a specific crate
SQLX_OFFLINE=true cargo test -p <crate> --lib
# Clippy
SQLX_OFFLINE=true cargo clippy --workspace
ML Models
Four production model architectures on Candle v0.9.1 with CUDA:
- DQN Rainbow -- Deep Q-Network with prioritized replay, dueling heads, noisy nets
- PPO -- Proximal Policy Optimization with GAE and LSTM policies
- TFT -- Temporal Fusion Transformer for multi-horizon forecasting
- Mamba2 -- State space model for sequence prediction
Each model has a standalone trainer and a UnifiedTrainable adapter for the hyperopt pipeline.
Infrastructure
- Git: Gitea at
git.fxhnt.ai(Tailscale-only), Scaleway DEV1-S - Observability: OpenTelemetry OTLP (env
OTEL_EXPORTER_OTLP_ENDPOINT) - Database: PostgreSQL with SQLx offline mode for CI
License
Proprietary. All rights reserved.