a5101eb2f8
Second of five sequential plans decomposing the DQN v2 unified spec (docs/superpowers/specs/2026-04-24-dqn-v2-unified-design.md). Covers spec sections: - §4.C.1 Quantile-based atom support (8 new ISV slots, q_quantile_reduce kernel) - §4.D.1 Mamba2 backward pipeline completion (no atomicAdd — per-sample arrays + host reduce) - §4.D.2 Per-branch gamma via AdaptiveController (4 new ISV slots) - §4.D.5 Soft fold-boundary transitions (extends StateResetRegistry with SoftReset category) - §4.D.7 Liquid Time-constant audit (trace fire rate, decide wire-or-delete) - §4.D.3 + §4.D.6 + §4.D.8 coordinated state-layout migration (horizon-decomposed V + plan_isv[6] + TLOB integration with atomic ISV schema version bump 1→2) Plan structure: 7 tasks + pre-plan verification, all TDD-disciplined with bite-sized steps (test → fail → implement → pass → commit). Task 6 is explicitly atomic to preserve Invariant 5 (state-layout consistency). Plan 2 prerequisites: Plan 1 landed (StateResetRegistry, AdaptiveController trait, ISV schema version, audit docs). Plan 2 exit: all 9 invariants preserved; convergence-scaffolding run passes with 16 new ISV slots populated; ISV schema version == 2. Preserves all 9 invariants. No stubs. No TODO/FIXME. Every new module wired to production path in the same task it lands in. 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.