d8447475c9
Adds ISV slot 824 (RL_SURFER_SCAFFOLD_FORCE_PIN_INDEX) and a matching kernel early-return in rl_surfer_scaffold_controller.cu so that when FOXHUNT_PIN_SURFER_SCAFFOLD=1 is set, the controller leaves slot 753 at its 0.0 pure-pnl bootstrap instead of overwriting it every step. Without the pin, the 0.0 bootstrap was cosmetic — the unconditional write re-enabled all four Phase-5 non-potential shaping terms each step, giving Pearson(reward,pnl)=0.28 vs the 0.70 gate. Pin=OFF leaves behaviour fully unchanged (new branch only fires when slot 824 > 0.5). - isv_slots.rs: slot 824 constant + RL_SLOTS_END 824→825 + test - rl_surfer_scaffold_controller.cu: #define + early-return guard - integrated.rs: isv_constants 275→276 + env-gated bootstrap entry - eval_diag_emission.rs: rewards.surfer_scaffold_force_pin diag field + EXPECTED_LEAVES 746→747 Build: SQLX_OFFLINE=true cargo build -p ml-alpha --profile=dev-release OK Tests: 69 passed / 0 failed (force_pin_slot_allocated_below_end + all existing) Co-Authored-By: Claude Opus 4.8 (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.