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shawnkim1997
38c56a5a43
Add asset-type aware market/overview flows, portfolio OCR reverse-engineering with exchange overrides, and interactive index heatmap features. Update README with recent updates and wire backend/frontend APIs for FX matrix, exchange options, and improved portfolio editing flows. Made-with: Cursor
25 lines
1.1 KiB
Python
25 lines
1.1 KiB
Python
"""Build compact copilot context with asset-type aware fields."""
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from __future__ import annotations
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def build_copilot_context(asset_type: str, data: dict) -> str:
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parts: list[str] = []
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if asset_type == "etf":
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parts.append(f"[Asset Type] ETF — {data.get('category')}")
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parts.append(f"[ETF] AUM: {data.get('aum')}, Expense: {data.get('expense_ratio')}")
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r = data.get("returns") or {}
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parts.append(f"[Performance] YTD: {r.get('ytd')}%, 1Y: {r.get('1y')}%")
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elif asset_type == "commodity_future":
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parts.append(f"[Asset Type] Commodity Future — {data.get('name')}")
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parts.append(f"[Commodity] Open Interest: {data.get('open_interest')}")
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seasonal = data.get("seasonal_pattern") or {}
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if seasonal:
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best_month = max(seasonal, key=lambda k: seasonal[k])
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worst_month = min(seasonal, key=lambda k: seasonal[k])
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parts.append(f"[Seasonal] Best month: {best_month}, Worst: {worst_month}")
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else:
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parts.append("[Asset Type] Equity")
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parts.append(f"[Sector] {data.get('sector')}")
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return "\n".join(parts)
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