feat(fusion_accounting_assets): AI useful life predictor + prompt

Made-with: Cursor

fusion_accounting_assets/services/useful_life_prompt.py

@@ -0,0 +1,48 @@
+"""LLM prompt builder for AI-suggested useful life from invoice description.
+
+Output contract:
+{
+  "useful_life_years": <int>,
+  "depreciation_method": "straight_line" | "declining_balance" | "units_of_production",
+  "rationale": "<short explanation>",
+  "confidence": <float 0-1>
+}
+"""
+
+
+SYSTEM_PROMPT = """You are an experienced accountant. Given an invoice line
+description for a fixed asset, suggest the appropriate useful life in years
+and depreciation method based on common accounting standards (IFRS / GAAP / CRA).
+
+Respond ONLY with valid JSON of this exact shape:
+{
+  "useful_life_years": <integer>,
+  "depreciation_method": "straight_line" | "declining_balance" | "units_of_production",
+  "rationale": "<one or two sentence explanation>",
+  "confidence": <float between 0 and 1>
+}
+
+Common useful-life conventions:
+- Furniture: 7 years, straight-line
+- Office equipment: 5 years, straight-line
+- Computers: 3-4 years, straight-line or declining
+- Vehicles: 5 years, declining-balance (CRA Class 10 30%)
+- Buildings: 25-40 years, straight-line
+- Manufacturing equipment: 10-15 years, units of production if measurable
+- Software (licenses): 3-5 years, straight-line
+- Leasehold improvements: lesser of lease term or useful life
+
+Do NOT include markdown code fences. Do NOT include any prose outside the JSON."""
+
+
+def build_prompt(*, description: str, amount: float = None,
+                 partner_name: str = None) -> tuple[str, str]:
+    """Return (system, user) prompt tuple."""
+    parts = [f"INVOICE LINE: {description}"]
+    if amount is not None:
+        parts.append(f"AMOUNT: ${amount:,.2f}")
+    if partner_name:
+        parts.append(f"VENDOR: {partner_name}")
+    parts.append("")
+    parts.append("Suggest the useful life and depreciation method per the system prompt.")
+    return (SYSTEM_PROMPT, "\n".join(parts))