920a2d0219
T10 train-multi-seed-khr7c (commit 8a25b330f, post-Fix-37) showed val-Flat-
collapse persisting at the eval-side selector despite all SP9 controller
fixes — dir_entropy=0 / trade_count=1 in 214,654 bars because
experience_action_select branched on eval_mode and used argmax(E[Q]) at
eval. With Hold's E[Q] ≈ 0 and directional E[Q] = ε (small edge minus tx
costs), argmax wins Hold deterministically every bar.
Per pearl_thompson_for_distributional_action_selection (amended): the
rollout SELECTOR is unconditional Thompson at all times (training AND
eval); argmax is reserved for the Bellman TARGET Q computation only
(DDQN target). Per pearl_controller_anchors_isv_driven: the temperature
on the Thompson sample is ISV-driven from the SP9 intent_eval_divergence
canary. Per pearl_blend_formulas_must_have_permanent_floor: MIN_TEMP=0.5
is the permanent-stochasticity floor — the eval selector is NEVER fully
deterministic.
Atomic commit per feedback_no_partial_refactor:
* 1 new ISV slot @ [339..340) (EVAL_THOMPSON_TEMP_INDEX); ISV_TOTAL_DIM
339 → 340; SP5_PRODUCER_COUNT 165 → 166; layout fingerprint updated
* 1 new scratch slot @ [265..266) (SCRATCH_SP10_THOMPSON_TEMP);
SP5_SCRATCH_TOTAL 265 → 266
* intent_eval_divergence_compute_kernel.cu extended with 2 params
(divergence_target_isv_index, scratch_temp_idx) + new compute branch
temp = clamp(divergence/div_target, 0.5, 2.0); existing scratch_idx
renamed scratch_div_idx for semantic clarity
* experience_action_select: if (eval_mode) { argmax(E[Q]) } DELETED;
unconditional temperature-blended Thompson installed:
q_eff[d] = E[Q][d] + temp · (q_sample[d] − E[Q][d]); defensive clamp
to [0.5, 2.0] for cold-start before producer first observation. Other
branches (mag/ord/urg) keep their existing eps-greedy/Boltzmann logic
per pearl_thompson §3 exemption
* state_layout.cuh: new ISV_EVAL_THOMPSON_TEMP_IDX 339 define
* gpu_dqn_trainer.rs::launch_intent_eval_divergence_compute extended
with 2 kernel args + second apply_pearls_ad_kernel chain to smooth
the temperature into ISV[339]
* New FoldReset entry sp10_eval_thompson_temp + dispatch arm in
reset_named_state writing sentinel 0; Pearl A's first-observation
replacement fires on the new fold's first producer launch
* Test renamed test_eval_action_select_eval_argmax_picks_best →
test_eval_action_select_thompson_picks_proportionally; ISV buffer
setup with EVAL_THOMPSON_TEMP_INDEX=1.0 (pure Thompson); assertions
updated to ≥ 70% best-direction wins (was ≥ 99% under deterministic
argmax) and < 100% (selector is sampling)
* Pearl pearl_thompson_for_distributional_action_selection §4 amended;
MEMORY.md index entry updated
* Audit doc Fix 38 entry
Verification:
* SQLX_OFFLINE=true cargo check -p ml — clean (only pre-existing 18
warnings; no new errors or warnings introduced by Fix 38)
* SQLX_OFFLINE=true cargo test -p ml --lib state_reset — 4/4 pass
including contract test every_fold_and_soft_reset_entry_has_dispatch_arm
* SQLX_OFFLINE=true cargo test -p ml --lib sp5_isv_slots — 10/10 pass
including new sp10_thompson_temp_slot_above_sp9_block
* SQLX_OFFLINE=true cargo test -p ml --lib test_eval_action_select_thompson —
pass (RTX 3050 Ti local; τ=1.0 with clear Q gap → P(Long) ≥ 0.70 < 1.0)
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.