93126504ca
Closes the L40S deploy-bug class where stale fxcache passed FXCACHE_VERSION validation despite incompatible feature semantics. Root cause of the original failure: extract_ohlcv_features column 0 changed from raw price -> log-return without anyone bumping the manually-maintained FXCACHE_VERSION const, so the L40S PVC's older cache loaded clean and the trainer fed raw prices into the aux head expecting log-returns (aux_next_bar_mse=2.587e7). Fix: * crates/ml/build.rs::emit_feature_schema_hash() runs unconditionally (before the existing CUDA-feature gate so non-CUDA builds also pick up the env var) and FNV-1a-hashes the raw bytes of the three schema-defining sources -- crates/ml/src/features/extraction.rs, crates/ml/src/fxcache.rs, crates/ml-core/src/state_layout.rs -- mixing in each file's relative path + length so renames / reorderings also bump the hash. Stable across rust versions and machines (FNV-1a, not std::hash::DefaultHasher). Emits cargo:rustc-env=FEATURE_SCHEMA_HASH=<decimal_u64> + three cargo:rerun-if-changed= lines. * crates/ml/src/fxcache.rs::FEATURE_SCHEMA_HASH consumes the env var via env! + const u64::from_str_radix(_, 10) (const-stable since rust 1.83; workspace MSRV 1.85). FxCacheHeader grows a feature_schema_hash: u64 field; header size 64->72 bytes; FXCACHE_VERSION bumped 5->6 to flag the wire-format change. validate() strict-checks the hash alongside magic / version / dims; mismatch bails with a descriptive error pointing at "source files defining feature extraction / state layout / fxcache format have changed since this cache was built." The existing precompute_features.rs:218 delete-and-regen-on-Err path handles recovery automatically; the Argo ensure-fxcache step is unchanged. * FXCACHE_VERSION docstring now declares it tracks WIRE-FORMAT changes only -- schema-level changes (feature column semantics, dimensionality) are tracked automatically by FEATURE_SCHEMA_HASH. Removes the manual ritual that broke the L40S deploy. * docs/dqn-wire-up-audit.md entry under Plan 5 Task 5 Phase F. Cost: cosmetic edits (whitespace, comments) to the three schema sources trigger one cache regen on next deploy (~5 min for full L40S dataset, ~40 s for local ES.FUT). Acceptable trade -- false negatives (missed schema drift) are not. Validation: * cargo check workspace clean at 11 warnings (baseline preserved). * Local ES.FUT cache regen confirmed: existing v5 file rejected with "Stale FxCache version: 5 (expected 6). Delete and regenerate.", regenerated v6 cache loads clean on retry (40 s, 175874 bars). * Auto-detection verified: comment-only edit to extraction.rs line 1 changed emitted hash 5046469432341222878 -> 7772630163018944575; revert returned the hash deterministically to 5046469432341222878. * multi_fold_convergence smoke PASSED (1 passed, 0 failed; 689.24 s, ~11.5 min). All 3 folds produced best-checkpoints. Per-fold best Sharpe: F0=-9.7831 (epoch 1), F1=37.9597 (epoch 2), F2=40.4789 (epoch 5). aux next_bar_mse range across all 15 epochs: 6.097e-2 -- 4.722e-1 (O(0.1), not 1e7 as in the L40S regression). No new pip/cargo deps (FNV-1a is ~10 LOC stdlib). No fingerprint change (LAYOUT_FINGERPRINT_CURRENT untouched -- this is fxcache wire-format, not GPU param layout). Files touched: * crates/ml/build.rs * crates/ml/src/fxcache.rs * docs/dqn-wire-up-audit.md 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.