build(agent): new-agents-4#58ba63 iteration

README.md

@@ -1 +1,20 @@
-# DeltaForge MVP: Real-Time Cross-Asset Strategy Synthesis (Skeleton)
+# DeltaForge Skeleton MVP
+
+A minimal, self-contained Python package that demonstrates the core primitives
+and a deterministic flow for cross-venue hedging concepts. This skeleton is
+designed to be extended with real adapters and a full ADMM-like coordination layer
+while providing a concrete starting point for testing, packaging, and integration.
+
+What this adds
+- Core DSL primitives: Asset, MarketSignal, StrategyDelta, PlanDelta (in deltaforge_skeleton.core)
+- Two starter adapters (equity_feed and options_feed) that generate MarketSignal instances
+- Simple Curator that synthesizes a PlanDelta from signals
+- Lightweight ExecutionEngine to route plan steps across venues
+- Toy Backtester to deterministically replay a plan
+- Packaging metadata via pyproject.toml and a README for distribution
+
+Usage notes
+- Import deltaforge_skeleton and instantiate the flow using the included components
+- Run the test harness in test.sh to verify the wiring and deterministic behavior
+
+This is a skeleton intended for extension; it is not a production-ready trading engine.

deltaforge_skeleton/__init__.py

@@ -0,0 +1,25 @@
+"""DeltaForge Skeletal MVP
+
+A minimal, production-friendly Python package skeleton that implements a
+canonical DSL surface and a toy but deterministic cross-venue workflow for
+testing and integration with adapters.
+"""
+
+from .core import Asset, MarketSignal, StrategyDelta, PlanDelta
+from .adapters.equity_feed import EquityFeedAdapter
+from .adapters.options_feed import OptionsFeedAdapter
+from .curator import Curator
+from .execution import ExecutionEngine
+from .backtester import Backtester
+
+__all__ = [
+    "Asset",
+    "MarketSignal",
+    "StrategyDelta",
+    "PlanDelta",
+    "EquityFeedAdapter",
+    "OptionsFeedAdapter",
+    "Curator",
+    "ExecutionEngine",
+    "Backtester",
+]

deltaforge_skeleton/adapters/__init__.py

@@ -0,0 +1,6 @@
+"""Adapters package"""
+
+from .equity_feed import EquityFeedAdapter
+from .options_feed import OptionsFeedAdapter
+
+__all__ = ["EquityFeedAdapter", "OptionsFeedAdapter"]

deltaforge_skeleton/adapters/equity_feed.py

@@ -0,0 +1,13 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+from deltaforge_skeleton.core import MarketSignal, Asset
+
+
+@dataclass
+class EquityFeedAdapter:
+    name: str = "EquityFeed"
+
+    def synthesize(self, symbol: str, price: float, timestamp: float) -> MarketSignal:
+        asset = Asset(symbol=symbol, asset_type="equity")
+        return MarketSignal(asset=asset, price=price, timestamp=timestamp, liquidity=1.0)

deltaforge_skeleton/adapters/options_feed.py

@@ -0,0 +1,13 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+from deltaforge_skeleton.core import MarketSignal, Asset
+
+
+@dataclass
+class OptionsFeedAdapter:
+    name: str = "OptionsFeed"
+
+    def synthesize(self, symbol: str, price: float, timestamp: float) -> MarketSignal:
+        asset = Asset(symbol=symbol, asset_type="option")
+        return MarketSignal(asset=asset, price=price, timestamp=timestamp, liquidity=0.8)

deltaforge_skeleton/backtester.py

@@ -0,0 +1,11 @@
+from __future__ import annotations
+
+from deltaforge_skeleton.core import PlanDelta
+
+
+class Backtester:
+    def replay(self, plan: PlanDelta) -> str:
+        # Deterministic replay: encode steps into a single string log
+        if not plan.steps:
+            return "empty plan"
+        return " | ".join(plan.steps)

deltaforge_skeleton/core.py

@@ -0,0 +1,56 @@
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import List, Optional
+
+
+@dataclass
+class Asset:
+    symbol: str
+    asset_type: str = "equity"  # or option, future, etc.
+
+
+@dataclass
+class MarketSignal:
+    asset: Asset
+    price: float
+    timestamp: float
+    liquidity: float = 1.0
+    implied_vol: Optional[float] = None
+
+
+@dataclass
+class StrategyDelta:
+    asset: Asset
+    hedge_ratio: float
+    target_pnl: float
+    constraints: Optional[List[str]] = field(default_factory=list)
+
+
+@dataclass
+class PlanDelta:
+    steps: List[str] = field(default_factory=list)
+    timestamp: float = 0.0
+    provenance: Optional[str] = None
+
+
+# Lightweight placeholders for governance primitives
+@dataclass
+class DualVariables:
+    values: List[float] = field(default_factory=list)
+
+
+@dataclass
+class PrivacyBudget:
+    budget: float = 0.0
+
+
+@dataclass
+class AuditLog:
+    entries: List[str] = field(default_factory=list)
+
+
+@dataclass
+class PolicyBlock:
+    name: str
+    rules: List[str] = field(default_factory=list)

deltaforge_skeleton/curator.py

@@ -0,0 +1,22 @@
+from __future__ import annotations
+
+from typing import List
+from deltaforge_skeleton.core import MarketSignal, PlanDelta, StrategyDelta, Asset
+
+
+class Curator:
+    def __init__(self):
+        self.audit = []
+
+    def synthesize(self, signals: List[MarketSignal]) -> PlanDelta:
+        # Naive delta-synthesis: for each asset, create a delta hedge with 1x price weight
+        steps = []
+        for s in signals:
+            asset = s.asset
+            # simple heuristic: hedge ratio proportional to liquidity and inverse of price
+            hedge_ratio = max(0.0, min(1.0, 1.0 * (s.liquidity / max(1.0, s.price))))
+            obj = StrategyDelta(asset=asset, hedge_ratio=hedge_ratio, target_pnl=0.0, constraints=[])
+            steps.append(f"HEDGE {asset.symbol} with ratio {hedge_ratio:.3f}")
+        plan = PlanDelta(steps=steps, timestamp=0.0, provenance="deltaforge-skeleton-curation")
+        self.audit.append("synthesized plan from signals")
+        return plan

deltaforge_skeleton/execution.py

@@ -0,0 +1,19 @@
+from __future__ import annotations
+
+from typing import List
+from deltaforge_skeleton.core import PlanDelta
+
+
+class ExecutionEngine:
+    def __init__(self):
+        self.log: List[str] = []
+
+    def route(self, plan: PlanDelta) -> List[str]:
+        # Very small mock routing: just annotate steps with a venue tag
+        routed = []
+        for i, step in enumerate(plan.steps or []):
+            venue = "VenueA" if i % 2 == 0 else "VenueB"
+            action = f"{step} -> {venue}"
+            routed.append(action)
+        self.log.append("routed plan across venues")
+        return routed

pyproject.toml

@@ -1,13 +1,19 @@
 [build-system]
-requires = ["setuptools>=42", "wheel"]
+requires = ["setuptools>=61.0"]
 build-backend = "setuptools.build_meta"
 
 [project]
 name = "deltaforge-skeleton"
-version = "0.1.0"
+version = "0.0.1"
-description = "MVP skeleton for DeltaForge real-time cross-asset strategy synthesis"
+description = "DeltaForge MVP skeleton: core DSL, adapters, curator, execution, and backtester"
-readme = "README.md"
+authors = [{name = "OpenCode"}]
 requires-python = ">=3.8"
-license = { text = "MIT" }
+readme = "README.md"
-authors = [ { name = "OpenCode AI" } ]
+
-dependencies = []
+[tool.setuptools.packages.find]
+where = ["."]
+# Include all deltaforge_skeleton packages that live at the project root or subpackages.
+include = ["deltaforge_skeleton*"]
+
+# Optionally enable data files to be included in the package build
+# Note: Avoid top-level [tool.setuptools] configuration that sets include_package_data here.

test.sh

@@ -1,36 +1,38 @@
 #!/usr/bin/env bash
 set -euo pipefail
 
-echo "Running DeltaForge MVP tests..."
+echo "Running DeltaForge Skeleton tests..."
-python3 -m build >/dev/null 2>&1 || true
-if [ -f dist/*wheel* ]; then
-  echo "Wheel present, installing..."
-  python3 -m pip install dist/*.whl
-fi
 
-echo "Installing package in editable mode..."
+# Ensure Python is available
-python3 -m pip install -e . >/dev/null 2>&1 || true
+python3 -V
+pip3 -V
 
-echo "Running unit tests..."
+# Build the package to verify packaging metadata compiles
-python3 -m pip install -q pytest || true
+python3 -m build || { echo "Build failed"; exit 1; }
-pytest -q || python3 -m unittest discover -q
 
-echo "Running deterministic backtest to verify MVP flow..."
+echo "Running a minimal deterministic flow..."
-python3 - <<'PY'
+python3 - << 'PY'
-from deltaforge.dsl import Asset, MarketSignal, StrategyDelta
+from deltaforge_skeleton.core import Asset, MarketSignal
-from deltaforge.core import Curator
+from deltaforge_skeleton.adapters.equity_feed import EquityFeedAdapter
-from deltaforge.backtester import Backtester
+from deltaforge_skeleton.curator import Curator
-from deltaforge.dsl import PlanDelta
+from deltaforge_skeleton.execution import ExecutionEngine
+from deltaforge_skeleton.backtester import Backtester
 
-asset_a = Asset(id="eq-AAPL", type="equity", symbol="AAPL")
+apple = Asset(symbol='AAPL')
-asset_b = Asset(id="eq-MSFT", type="equity", symbol="MSFT")
+sig = MarketSignal(asset=apple, price=150.0, timestamp=0.0, liquidity=1.0)
-sig = MarketSignal(asset=asset_a, timestamp=0.0, price=150.0)
+
-curator = Curator([asset_a, asset_b])
+curator = Curator()
-plan = curator.synthesize_plan([sig], [
+plan = curator.synthesize([sig])
-    StrategyDelta(id="s1", assets=[asset_a], objectives={"maximize": "return"}),
+
-    StrategyDelta(id="s2", assets=[asset_b], objectives={"maximize": "return"}),
+engine = ExecutionEngine()
-])
+routes = engine.route(plan)
-bt = Backtester(initial_cash=1000.0)
+
-res = bt.apply([sig], plan)
+bt = Backtester()
-print(res)
+replay = bt.replay(plan)
+
+print("PLAN:", plan)
+print("ROUTES:", routes)
+print("REPLAY:", replay)
 PY
+
+echo "All good. Ready to publish once READY_TO_PUBLISH is created."