ff00af68a3
Atomic cleanup per feedback_no_partial_refactor.md:
- Delete crates/ml-dqn/src/regime_conditional.rs and all
RegimeConditional* exports from lib.rs. regime_classifier.rs
(RegimeType, RegimeClassConfig) is kept — used by validation layer
and ml-regime-detection crate.
- Rewrite DQNAgentType to wrap DQN directly (no RegimeConditionalDQN
field, no 3-head delegation gymnastics).
- DQNAgentType::get_count_bonuses_branched no longer returns hardcoded
None — it delegates to DQN::get_count_bonuses_branched() and UCB
count bonuses reach the GPU action selector for the first time
(ghost feature from Phase 0 deferral). action.rs caller simplified
to direct destructure of fixed arrays, no Option matching.
- Drop 4 regime-threshold fields from DQNConfig (regime_adx_idx,
regime_cusum_idx, regime_adx_threshold, regime_cusum_threshold) +
matching Default and aggressive() builder entries.
- serialize_model rewritten to serialize single DQN branching network
directly (no trending__/ranging__/volatile__ prefix namespace).
- curriculum.rs import fixed: crate::dqn::regime_conditional::RegimeType
→ crate::dqn::RegimeType (re-exported from regime_classifier).
- Constructor drops RegimeConditionalDQN::new_on_device, calls
DQN::new_on_device directly.
- Stale doc comments in dqn.rs, moe.rs, regime_classifier.rs updated.
- Wire-up audit updated.
Phase 3 MoE (commit a52d99613) provides the regime-conditioned behavior
the legacy 3-head architecture pretended to do — gate sees ADX (40)
and CUSUM (41) as part of the full 128-dim state vector and learns its
own decomposition, strictly subsuming the threshold classifier.
Smoke: 3/3 folds passed (405s), gate util=0.119,0.119,0.169,... preserved,
all fold checkpoints written. Workspace: 0 errors across all crates,
tests, and examples.
Spec: docs/superpowers/specs/2026-04-27-moe-regime-redesign-design.md §7.
Co-Authored-By: Claude Sonnet 4.6 <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.