3a62e23056
Self-review pass on the DQN v2 unified design spec (d13b53586). Fixes
applied inline:
Ambiguity fixes:
- §3 Invariant 3: explicit definition of "training step loop" (per-step
code in fused_training::step_fused and captured graph children; NOT
per-epoch / per-fold / per-checkpoint code).
- §2 Tier 1: "stable epochs" defined as epochs [warmup_end..run_end)
with warmup_end from B.3's seed-phase decay or explicit flag.
- §4 A.2: migration mechanism clarified as fail-fast initially; helpers
added only when a specific migration need arises (no speculative
scaffolding).
- §4 A.3: N=5, K=6 stated as DEFAULTS with ≥ MINIMUMS per Invariant 6;
resource budget flagged (~8-10 GPU-hours per validation pass).
- §4 B.3: "≥ 100K experiences" (minimum), warm-restart clarified as
runtime condition not feature flag.
- §4 C.3: adaptive KL threshold mechanism made explicit (second ISV
slot for threshold EMA, third for amplification multiplier).
- §4 C.6: cleanup timing explicit — old scaffolding removed in the SAME
commit that migrates its last consumer (no deferred pass).
- §4 D.1: DQN-path-specific scope clarified; validation via grad-norm
smoke + integration test.
- §4 D.6: plan_isv index naming made consistent with existing layout;
coordinated state-layout migration commit called out.
New Invariant 8 — Named dimensions, not indices:
Every dimension, slot, offset, or semantic position in a multi-field
buffer has a named constant. Raw numeric indices (`[0]`, `[6]`, `[23]`)
appear ONLY in the definition site. Named constants specified for ISV
slots (existing), portfolio state ps[0..30), plan_isv[0..7), plan_params
[0..6), state-vector offsets, branch indices (BRANCH_DIR/MAG/ORD/URG),
action sub-indices (DIR_SHORT/HOLD/LONG/FLAT, MAG_QUARTER/HALF/FULL).
Enforcement: audit pass during A.1/A.2, lint via grep for raw-index
access outside definition modules.
Landing order revision:
- Dependency graph explicit (A.2 before new ISV slots, D.1 before
D.2-4-8, state-layout changes in ONE coordinated commit).
- Spec decomposition note added — writing-plans may produce multiple
sequential plans rather than one monolithic plan.
New doc tracked by pre-commit: docs/dqn-named-dims.md (Invariant 8).
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.