jgrusewski b4239e8c43 feat(hyperopt): add VRAM-aware batch_size scaling to 9 existing adapters
Override continuous_bounds_for() in all adapters that already have batch_size:
- TFT (idx 1): 150MB overhead, 0.05 MB/sample, cap 2048
- Mamba2 (idx 1): 200MB overhead, 0.03 MB/sample, cap 2048
- TGGN (idx 7): 100MB overhead, 0.08 MB/sample, cap 1024
- TLOB (idx 6): 120MB overhead, 0.10 MB/sample, cap 1024
- KAN (idx 7): 80MB overhead, 0.04 MB/sample, cap 1024
- xLSTM (idx 6): 180MB overhead, 0.06 MB/sample, cap 1024
- Diffusion (idx 6): 250MB overhead, 0.12 MB/sample, cap 512
- DQN (idx 1): 300MB overhead, 0.02 MB/sample, cap 4096
- ContinuousPPO (idx 9): 250MB overhead, 0.03 MB/sample, cap 4096

On CPU-only, all adapters fall back to existing static bounds.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-28 19:19:25 +01:00

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.

Description
No description provided
Readme 849 MiB
Languages
Rust 88.2%
Cuda 7.7%
Python 1.3%
Shell 1.1%
PLpgSQL 0.8%
Other 0.8%