7e78bf4f85
Task 2.0 instrumentation (commitsd60e5375a/980f3b07f/41b0c559c) revealed two silent bugs in Task 0.4's grad_ratio_mag_dir accessor: Bug A — readback size mismatch: pinned buffer allocated at total_params, but grad_buf length is total_params+cutlass_tile_pad, so size check always failed → Err silently coerced to 0.0 by proxy. Bug B — readback timing wipe: estimate_avg_q_value_with_early_stopping in process_epoch_boundary replays the forward graph, which zeros grad_buf. Any subsequent readback sees all zeros. Both fixed in 41b0c559c; snapshot hoisted to top of process_epoch_boundary. With those bugs fixed, the measured gradient ratio is NOT 0.0000 — it is 50–400× mag/dir across 60 epochs. Magnitude branch is over-fed, not starved. Direction gradient is small but non-zero (~2e-2 to 7e0). Direction policy is observably healthy (Short/Hold/Long/Flat 38/12/42/14%). Track 1 triage's H4 CONFIRMED verdict was a measurement artefact produced by Bugs A+B. H4 as originally defined is now REJECTED. Plan changes: - Add new "Task 2.0 findings" section after cross-cutting concerns, documenting bug A, bug B, observed data, and revised strategy. - Task 2.1 marked DEFERRED (not deleted — kept for reference). - Task 2.2 promoted to PRIMARY fix. - New fallback: H9 delete-magnitude-branch as replacement for Task 2.1 if Task 2.2 alone is insufficient. - Task 2.0 inventory row updated with LANDED status and commit chain. Net effect: Phase 2 simplifies. The hardest task (2.1 three-branch architectural fix) is skipped; primary path is Task 2.2 (~25 LOC).
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.