bcbd16f8c5
Critical re-review of v1 caught: 1. Task 6 retained Pearl 2 kernel signature with (void) no-op args "to save 3-site cascade" — that's the partial-refactor anti-pattern feedback_no_partial_refactor explicitly forbids. v2 does the full contract change: signature shrinks 9→6 args, launcher migrates atomically. 2. SCRATCH_PEARL_2_C51/_CQL/_ENS would become orphan constants — feedback_wire_everything_up says delete or wire. v2 deletes them in T6. 3. Audit-doc updates were separated into a single late commit — would fail check_audit_doc_updates pre-commit gate on T1-T6. v2 folds Fix 31 stub into T1 and extends it commit-by-commit. 4. T5 referenced grad_decomp_*_result_dev_ptr field names that don't exist — actual layout is one shared 27-float pinned buffer with per-component byte offsets (iqn=0, cql_sx=24, c51=36). v2 uses pointer arithmetic from grad_decomp_result_dev_ptr. 5. Tasks 1, 2, 4 had "if file shape X then Y, otherwise Z" placeholder branches — writing-plans skill forbids these. v2 has concrete patches based on reading the actual files. Also corrected: T2 fixes the stale "regime_stability allocator" description in state_reset_registry.rs alongside the new entries. 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.