consultoria-as
f9589f4a4e
Chat now fetches tenant inventory summary (brands, counts, low-stock) and injects it into the AI system prompt so responses prioritize local stock. VIN decoder uses free NHTSA vPIC API to decode 17-char VINs and auto-fills the vehicle selector dropdowns when a catalog match is found. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
55 lines
1.8 KiB
Python
55 lines
1.8 KiB
Python
"""VIN Decoder using NHTSA vPIC API (free, no key needed)."""
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import re
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import requests
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def decode_vin(vin):
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"""Decode a VIN number using NHTSA API.
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Returns: {make, model, year, engine, body_type, plant_country, fuel_type, error}
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"""
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vin = (vin or "").strip().upper()
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# Validate: 17 alphanumeric chars, no I/O/Q
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if not re.match(r'^[A-HJ-NPR-Z0-9]{17}$', vin):
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return {"error": "VIN debe tener exactamente 17 caracteres alfanumericos (sin I, O, Q)."}
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url = f"https://vpic.nhtsa.dot.gov/api/vehicles/DecodeVinValues/{vin}?format=json"
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resp = requests.get(url, timeout=10)
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resp.raise_for_status()
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data = resp.json()["Results"][0]
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error_text = data.get("ErrorText", "") or ""
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# NHTSA returns error codes like "0 - ..." for no error
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has_real_error = error_text and not error_text.startswith("0")
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displacement = data.get("DisplacementL", "") or ""
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cylinders = data.get("EngineCylinders", "") or ""
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engine_parts = []
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if displacement:
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engine_parts.append(f"{displacement}L")
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if cylinders:
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engine_parts.append(f"{cylinders}cyl")
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engine_str = " ".join(engine_parts)
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model_year = data.get("ModelYear", "")
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year_int = None
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if model_year:
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try:
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year_int = int(model_year)
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except (ValueError, TypeError):
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pass
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return {
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"vin": vin,
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"make": data.get("Make", "") or "",
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"model": data.get("Model", "") or "",
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"year": year_int,
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"engine": engine_str,
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"body_type": data.get("BodyClass", "") or "",
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"plant_country": data.get("PlantCountry", "") or "",
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"fuel_type": data.get("FuelTypePrimary", "") or "",
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"drive_type": data.get("DriveType", "") or "",
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"trim": data.get("Trim", "") or "",
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"error": error_text if has_real_error else "",
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}
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