build(agent): molt-x#ed374b iteration

.gitignore

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+node_modules/
+.npmrc
+.env
+.env.*
+__tests__/
+coverage/
+.nyc_output/
+dist/
+build/
+.cache/
+*.log
+.DS_Store
+tmp/
+.tmp/
+__pycache__/
+*.pyc
+.venv/
+venv/
+*.egg-info/
+.pytest_cache/
+READY_TO_PUBLISH

AGENTS.md

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+# DeltaForge MVP: Architectural Guide
+
+Overview
+- Purpose: A minimal, auditable cross-venue hedging engine for two assets across two venues.
+- Scope: Core DSL sketches, two starter adapters, a tiny central curator, and a toy backtester.
+
+Architecture sketch
+- DSL: StrategyDelta, Asset, MarketSignal, PlanDelta (data classes with simple validation).
+- Adapters: canonical signals from venue data translated to StrategyDelta objects.
+- Coordinating layer: local risk solvers per venue + a central curator that enforces cross-venue constraints via aggregated signals (ADMM-lite style).
+- Execution adapter: routes to venues with latency/fee metadata in the plan delta.
+- Backtester: deterministic replay engine.
+- Governance: tamper-evident logs; cryptographic tag placeholders.
+
+How to contribution
+- Run tests via test.sh; ensure deterministic behavior.
+- Extend with new adapters, new assets, or richer DSL primitives.

README.md

@@ -1,3 +1,32 @@
 # deltaforge-real-time-cross-asset-strateg
 
-A novel, open-source engine that automatically synthesizes, validates, and executes hedging and arbitrage strategies across options, equities, and futures across multiple venues with ultra-low latency. It provides a concise DSL to declare strategy ob
+DeltaForge MVP: Minimal, open-source engine for real-time cross-asset hedging across options and equities across two venues.
+
+Overview
+- A compact DSL to declare strategy objectives (risk budgets, PnL targets, liquidity constraints).
+- Two starter adapters (equity feed and options market data).
+- Lightweight, two-venue risk solvers with a central curator for cross-venue constraints.
+- Minimal deterministic backtester and a toy execution adapter.
+- MVP runs in a small two-asset, two-venue scenario demonstrating delta-hedges and cross-venue spreads.
+
+What’s included
+- Python package deltaforge_mvp with core DSL scaffolds and demo flow.
+- Adapters: deltaforge_mvp/adapters/equity_feed.py, deltaforge_mvp/adapters/options_feed.py
+- Venue coordination: deltaforge_mvp/coordination.py (ADMM-lite style coordination skeleton)
+- Backtester: deltaforge_mvp/backtester.py
+- Demo: deltaforge_mvp/demo.py (orchestrates a simple delta hedge across two venues)
+- Tests: tests/test_demo.py
+- Test script: test.sh
+- Metadata: AGENTS.md (architecture guide) and READY_TO_PUBLISH placeholder
+
+How to run (locally)
+- Build and install: python -m build
+- Run demo: python -m deltaforge_mvp.demo
+- Run tests: bash test.sh
+
+Note: This is a minimal, initial MVP skeleton intended to bootstrap discussion and future extension. It focuses on the core concepts with simple deterministic flows.
+
+Usage notes:
+- The MVP uses a tiny Python package deltaforge_mvp with a demo orchestrator and two starter adapters.
+- To run the demo: python -m deltaforge_mvp.demo
+- To execute tests: bash test.sh

deltaforge_mvp/__init__.py

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+"""DeltaForge MVP package init.
+Expose lightweight APIs for a tiny cross-venue hedging engine scaffold.
+"""
+
+from .core import StrategyDelta, Asset, MarketSignal, PlanDelta  # re-export for convenience

deltaforge_mvp/adapters/equity_feed.py

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+"""Starter equity feed adapter: emits simple price signals for an equity."""
+from __future__ import annotations
+import time
+
+from deltaforge_mvp.core import Asset, MarketSignal
+
+
+def generate_signal(symbol: str, price: float) -> MarketSignal:
+    asset = Asset(type="equity", symbol=symbol)
+    return MarketSignal(asset=asset, price=price, volatility=0.2, liquidity=1.0, timestamp=time.time())

deltaforge_mvp/adapters/options_feed.py

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+"""Starter options feed adapter: emits option market signals."""
+from __future__ import annotations
+import time
+
+from deltaforge_mvp.core import Asset, MarketSignal
+
+
+def create_option_symbol(underlying: str, strike: float, expiry: str) -> Asset:
+    return Asset(type="option", underlying=underlying, strike=strike, expires=expiry)
+
+
+def generate_signal(underlying: str, strike: float, expiry: str, price: float) -> MarketSignal:
+    asset = Asset(type="option", underlying=underlying, strike=strike, expires=expiry)
+    return MarketSignal(asset=asset, price=price, volatility=0.25, liquidity=0.8, timestamp=time.time())

deltaforge_mvp/backtester.py

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+"""Deterministic replay backtester (toy) for MVP."""
+from __future__ import annotations
+
+from typing import List
+
+from deltaforge_mvp.core import PlanDelta
+
+
+class Backtester:
+    def __init__(self, seed: int = 0):
+        self.seed = seed
+
+    def replay(self, plan: PlanDelta) -> dict:
+        # Very small deterministic stub: compute a fake PnL based on number of deltas and a seed
+        pnl = 0.0
+        for d in plan.deltas:
+            pnl += (d.delta * 0.5)  # arbitrary scaling for demo
+        return {"pnl": pnl, "delta_count": len(plan.deltas), "seed": self.seed}

deltaforge_mvp/coordination.py

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+"""ADMM-lite style coordination skeleton for cross-venue coherence."""
+from __future__ import annotations
+
+from typing import List
+
+from deltaforge_mvp.core import PlanDelta, StrategyDelta
+
+
+class LocalRiskSolver:
+    def __init__(self, venue_name: str):
+        self.venue_name = venue_name
+
+    def propose(self, signals: List[StrategyDelta]) -> PlanDelta:
+        # Minimal heuristic: aggregate deltas and propose a single PlanDelta per venue
+        # In real system this would solve a convex program; here we pass through the deltas.
+        pd = PlanDelta(deltas=signals, venue=self.venue_name, author="local-solver")
+        return pd
+
+
+class CentralCurator:
+    def __init__(self):
+        pass
+
+    def enforce(self, plans: List[PlanDelta]) -> PlanDelta:
+        # Naive: merge all deltas into a single PlanDelta with combined deltas
+        merged = []
+        for p in plans:
+            merged.extend(p.deltas)
+        return PlanDelta(deltas=merged, venue=None, author="curator")

deltaforge_mvp/core.py

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+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import List, Optional
+
+
+@dataclass
+class Asset:
+    """Canonical asset representation.
+    Example: {"type": "equity", "symbol": "AAPL"} or {"type": "option", "underlying": "AAPL", "strike": 150, "expires": "2026-12-17"}
+    """
+
+    type: str  # 'equity', 'option', 'future'
+    symbol: Optional[str] = None
+    underlying: Optional[str] = None
+    strike: Optional[float] = None
+    expires: Optional[str] = None
+
+    def canonical_id(self) -> str:
+        if self.type == "equity":
+            return f"EQ:{self.symbol}"
+        if self.type == "option":
+            return f"OP:{self.underlying}:{self.strike}:{self.expires}"
+        if self.type == "future":
+            return f"FU:{self.symbol or self.underlying}:{self.expires}"
+        return f"UNK:{self.symbol or 'UNDEF'}"
+
+
+@dataclass
+class MarketSignal:
+    """Lightweight market signal used by adapters to convey prices, liquidity, etc."""
+    asset: Asset
+    price: float
+    volatility: float = 0.0
+    liquidity: float = 1.0
+    timestamp: float = 0.0
+
+
+@dataclass
+class StrategyDelta:
+    """Local decision block; describes intent to adjust hedges for an asset.
+    This is a light DSL-like structure that adapters translate into venue orders.
+    """
+    asset: Asset
+    delta: float  # directional hedge to apply (positive means buy delta exposure, etc.)
+    vega: float = 0.0
+    gamma: float = 0.0
+    target_pnl: Optional[float] = None
+    max_order_size: float = 1.0
+    timestamp: float = 0.0
+
+
+@dataclass
+class PlanDelta:
+    """Incremental hedges/adjustments with metadata for auditability."""
+    deltas: List[StrategyDelta]
+    confidence: float = 1.0
+    venue: Optional[str] = None
+    author: str = "system"
+    timestamp: float = 0.0
+    signature: Optional[str] = None  # placeholder for cryptographic tag

deltaforge_mvp/demo.py

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+"""Minimal demonstration orchestrating two venues with a delta hedge."""
+from __future__ import annotations
+import time
+
+from deltaforge_mvp.core import Asset, MarketSignal, StrategyDelta, PlanDelta
+from deltaforge_mvp.adapters.equity_feed import generate_signal as equity_signal
+from deltaforge_mvp.adapters.options_feed import generate_signal as option_signal
+from deltaforge_mvp.coordination import LocalRiskSolver, CentralCurator
+from deltaforge_mvp.backtester import Backtester
+
+
+def main():
+    # Define two assets: one equity, one option (simplified)
+    eq = Asset(type="equity", symbol="AAPL")
+    opt = Asset(type="option", underlying="AAPL", strike=150, expires="2026-12-17")
+
+    # Generate simple signals from two adapters (toy values)
+    s1 = MarketSignal(asset=eq, price=180.0, volatility=0.2, liquidity=1.0, timestamp=time.time())
+    s2 = option_signal(underlying="AAPL", strike=150, expiry="2026-12-17", price=5.0)
+
+    # Local hedging decisions (tiny delta values for demo)
+    d1 = StrategyDelta(asset=eq, delta=0.5, timestamp=time.time())
+    d2 = StrategyDelta(asset=opt, delta=-0.3, timestamp=time.time())
+
+    # Venue solvers
+    solver_a = LocalRiskSolver("Venue-A")
+    solver_b = LocalRiskSolver("Venue-B")
+    plan_a = solver_a.propose([d1])
+    plan_b = solver_b.propose([d2])
+
+    curator = CentralCurator()
+    merged_plan = curator.enforce([plan_a, plan_b])
+
+    backtester = Backtester(seed=42)
+    results = backtester.replay(merged_plan)
+
+    print("DeltaForge MVP Demo Results:")
+    print(results)
+
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

pyproject.toml

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+[build-system]
+requires = ["setuptools>=42", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "deltaforge-mvp"
+version = "0.1.0"
+description = "Minimal MVP scaffolding for DeltaForge cross-venue hedgingEngine"
+readme = "README.md"
+requires-python = ">=3.8"
+license = {text = "MIT"}
+authors = [ { name = "DeltaForge MVP" } ]
+dependencies = ["numpy"]

test.sh

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+#!/usr/bin/env bash
+set -euo pipefail
+
+echo "Running Python build and tests for DeltaForge MVP..."
+python -m build >/dev/null 2>&1 || { echo "[build] failed"; exit 1; }
+pytest -q || { echo "[tests] failed"; exit 1; }
+echo "All tests passed."

tests/test_demo.py

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+import pytest
+import sys
+import os
+
+# Robust import in case pytest runs with a constrained PYTHONPATH
+try:
+    from deltaforge_mvp.demo import main
+except Exception:
+    # Fallback: load module directly from repo path
+    import importlib.util
+    import pathlib
+    repo_root = pathlib.Path(__file__).parents[1].resolve()
+    # Ensure repo root is on sys.path for dynamic import fallback
+    if str(repo_root) not in sys.path:
+        sys.path.insert(0, str(repo_root))
+    demo_path = repo_root / 'deltaforge_mvp' / 'demo.py'
+    spec = importlib.util.spec_from_file_location("deltaforge_mvp.demo", str(demo_path))
+    if spec is None or spec.loader is None:
+        raise ImportError("Could not load deltaforge_mvp.demo fallback module")
+    mod = importlib.util.module_from_spec(spec)
+    spec.loader.exec_module(mod)  # type: ignore
+    main = mod.main
+
+
+def test_demo_runs():
+    # Ensure the demo runs without raising
+    ret = main()
+    assert ret == 0