45da3eac69
3 IMPORTANT items from #260 code-quality review (commit88ae74ca7), addressed post-smoke-validation (smoke-test-tkkx6 Succeeded): 1. Stale numeric line-references in 8+ doc-comments replaced with symbolic code anchors per feedback_trust_code_not_docs. Pre-existing stale `ISV_TOTAL_DIM = 60` comment also corrected. 2. q_dir_grad launcher allocated dedicated `q_dir_grad_subbuf_table_buf` + `q_dir_grad_subbuf_counts_buf` (2 entries each) instead of reusing the shared `oracle_subbuf_table_buf`. Eliminates implicit "must-run-before- oracle" temporal coupling; removes `K_MAX=4` local redefinition. 3. `launch_sp4_p99_producer_single_buf` helper extracted on GpuDqnTrainer. Collapses ~30-line boilerplate x 3 call sites (target_q, h_s2, bw_d_h_s2) into single-line calls. Multi-sub-buffer launchers (q_dir_grad, param_group_oracle) and shape-distinct producers (grad_norm 1-thread, atom_pos 4-iter+batched-Pearls) keep their bespoke shape. Build clean, 11 SP4 lib tests pass, 16 SP4 GPU tests pass on RTX 3050 Ti. Refs: #260 code-quality review, smoke-test-tkkx6 (commit88ae74ca7). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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.