0357c03918
Reverts commitsd76849f31(Batch A: atoms, gamma, kelly_cap, cql_alpha) and4189da563(Batch B: tau, epsilon, conviction_floor, plan_threshold). The reverted commits implemented 8 controllers under the old AdaptiveController trait which had CPU-side update() that computed adaptive values and write_output() that pushed them to ISV. This violates the architectural principle codified in the §4.C.6 revision (commitcf36091ee): GPU kernels compute all adaptive decisions; CPU is pure observation. The 8 migrations will be re-implemented under the new AdaptiveMonitor pattern: - 6 reactive mechanisms (atoms, gamma, kelly_cap, tau, epsilon, grad_balancer) get new GPU kernels + read-only CPU monitors. - 3 static mechanisms (cql_alpha, conviction_floor, plan_threshold) get ISV constructor-writes (no kernel, no monitor). After this revert: - AdaptiveController trait is back on main (from Task 8's419c24b4f). It will be replaced with AdaptiveMonitor in the next commit per the revised Plan 1 Task 8. - StateResetRegistry (from Task 2'sb688827d6) stays intact. - Tasks 1-7 completed work unchanged. Tests: cargo check -p ml at 8-warning baseline after revert. 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.