96769d1711
Plan task #296. Pearl 7 was an INVESTIGATION task in the SP5 brainstorm: the pre-SP5 50-epoch baseline (train-multi-seed-cv2mw, F0 epochs 4-9) showed intent_dist freezing at exact Bin(2, 0.5) ratios (0.25/0.50/0.25), suggesting a hidden binary action decomposition somewhere downstream. The plan §C4 closure rule: if post-SP5 smokes show intent_dist drifting normally (no freeze), Pearl 7 closes with no code changes. Verdict from 3 retained SP5-era smokes: intent_dist drifts smoothly each epoch. No Bin(2, 0.5) freeze observed at: - smoke-test-ks2wf (post-spread-filter,5845e4403) - smoke-test-7pv9v (Layer D additive,f42b5fff8) - smoke-test-w9nsw (D4 atomic,2e9e276a0) (smoke-test-cnlrw (sanitize-only,8434737a6) cached log was pruned before evidence-collection; 3 retained smokes sample post-spread-filter and full Layer D production paths and decisively satisfy the closure rule on their own.) Likely cause: SP5 Layer A's per-branch parameter lifting (C51 atom span, NoisyNet σ, IQN τ schedule, loss budgets, Adam β/ε, Kelly floors) added enough independent variability at every shared site that no single 2-state decomposition can dominate intent_dist in steady state. What lands: - docs/dqn-wire-up-audit.md Pearl 7 closure entry - memory/pearl_intent_dist_freeze_resolved.md (new) - memory/MEMORY.md Topic Files Index entry No code changes. No follow-up spec opened. The escalation trigger (re-freeze for ≥3 consecutive epochs in a future run) is documented in the audit entry. Closes plan task #296. 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.