2026.06.04 frontend építés közben
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Roo
289
backend/app/services/asset_matcher_service.py
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289
backend/app/services/asset_matcher_service.py
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# /opt/docker/dev/service_finder/backend/app/services/asset_matcher_service.py
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"""
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Internal Asset Matcher Service
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Cél: Belső katalógus (vehicle_model_definitions) alapján automatikus eszköz-azonosítás és adatgazdagítás.
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Matching stratégia:
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1. Exact match: make + marketing_name + year_of_manufacture
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2. Fuzzy match: make + normalizált név (Levenshtein távolság)
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3. Confidence > 90% esetén automatikus adatgazdagítás
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"""
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from __future__ import annotations
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import logging
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import difflib
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import uuid
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from datetime import datetime
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from typing import Optional, Tuple, List, Dict, Any
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from sqlalchemy.ext.asyncio import AsyncSession
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from sqlalchemy import select, and_, or_, func
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from sqlalchemy.orm import selectinload
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from app.models import Asset, VehicleModelDefinition, AssetCatalog, AssetEvent, AssetTelemetry
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from app.models.vehicle.vehicle_definitions import VehicleModelDefinition as VMD
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logger = logging.getLogger(__name__)
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class AssetMatcherService:
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"""
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Belső eszköz matcher szolgáltatás.
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"""
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@staticmethod
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async def find_best_match(
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db: AsyncSession,
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asset: Asset,
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threshold: float = 0.8
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) -> Tuple[Optional[VehicleModelDefinition], float]:
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"""
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Megkeresi a legjobb egyezést az asset adatai alapján a vehicle_model_definitions táblában.
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Args:
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db: AsyncSession
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asset: Asset objektum (már tartalmazza a make/model/year stb.)
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threshold: Minimális confidence threshold (0-1)
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Returns:
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Tuple (matched_definition, confidence)
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"""
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# Gyűjtsük össze a keresési kritériumokat
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make = asset.brand or (asset.catalog.make if asset.catalog else None)
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model = asset.model or (asset.catalog.model if asset.catalog else None)
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year = asset.year_of_manufacture
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# Trim és ellenőrzés
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if make:
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make = make.strip()
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if model:
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model = model.strip()
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if not make or not model:
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logger.warning(f"Asset {asset.id} missing make or model, cannot match (make='{make}', model='{model}')")
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return None, 0.0
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# 1. EXACT MATCH: make + marketing_name + year_from
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exact_match = await AssetMatcherService._exact_match(db, make, model, year)
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if exact_match:
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logger.info(f"Exact match found for asset {asset.id}: {make} {model} {year}")
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return exact_match, 1.0
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# 2. FUZZY MATCH: make + normalizált név (year within range)
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fuzzy_matches = await AssetMatcherService._fuzzy_match(db, make, model, year, threshold)
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if fuzzy_matches:
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best_match, confidence = fuzzy_matches[0]
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logger.info(f"Fuzzy match found for asset {asset.id}: {best_match.make} {best_match.marketing_name} (confidence: {confidence:.2f})")
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return best_match, confidence
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# 3. FALLBACK: csak make + model (year ignore)
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fallback_match = await AssetMatcherService._fallback_match(db, make, model)
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if fallback_match:
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logger.info(f"Fallback match found for asset {asset.id}: {make} {model}")
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return fallback_match, 0.7 # Alacsonyabb confidence
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logger.warning(f"No match found for asset {asset.id}: {make} {model} {year}")
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return None, 0.0
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@staticmethod
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async def _exact_match(
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db: AsyncSession,
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make: str,
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model: str,
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year: Optional[int]
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) -> Optional[VehicleModelDefinition]:
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"""
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Pontos egyezés: make, marketing_name és year_from/year_to tartomány.
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Több egyezés esetén a legújabb évjáratút választja.
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"""
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stmt = select(VMD).where(
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VMD.make.ilike(make),
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VMD.marketing_name.ilike(model)
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)
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if year:
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# Évjárat tartományban legyen
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stmt = stmt.where(
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and_(
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VMD.year_from <= year,
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or_(VMD.year_to.is_(None), VMD.year_to >= year)
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)
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)
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# Rendezés év szerint csökkenő, limit 1
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stmt = stmt.order_by(VMD.year_from.desc()).limit(1)
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result = await db.execute(stmt)
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return result.scalar_one_or_none()
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@staticmethod
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async def _fuzzy_match(
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db: AsyncSession,
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make: str,
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model: str,
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year: Optional[int],
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threshold: float
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) -> List[Tuple[VehicleModelDefinition, float]]:
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"""
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Fuzzy egyezés: hasonlóság a normalizált név alapján.
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"""
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# Először szűrjünk make és év alapján
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stmt = select(VMD).where(VMD.make.ilike(make))
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if year:
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stmt = stmt.where(
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and_(
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VMD.year_from <= year,
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or_(VMD.year_to.is_(None), VMD.year_to >= year)
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)
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)
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result = await db.execute(stmt)
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candidates = result.scalars().all()
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if not candidates:
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return []
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# Számítsuk ki a hasonlóságot a model név és a marketing_name között
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matches = []
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for candidate in candidates:
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similarity = AssetMatcherService._calculate_similarity(model, candidate.marketing_name)
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if similarity >= threshold:
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matches.append((candidate, similarity))
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# Rendezzük confidence szerint csökkenő sorrendben
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matches.sort(key=lambda x: x[1], reverse=True)
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return matches
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@staticmethod
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async def _fallback_match(
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db: AsyncSession,
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make: str,
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model: str
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) -> Optional[VehicleModelDefinition]:
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"""
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Csak make + model alapján, évjárat figyelmen kívül hagyva.
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"""
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stmt = select(VMD).where(
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VMD.make.ilike(make),
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VMD.marketing_name.ilike(model)
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).order_by(VMD.year_from.desc()).limit(1)
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result = await db.execute(stmt)
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return result.scalar_one_or_none()
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@staticmethod
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def _calculate_similarity(str1: str, str2: str) -> float:
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"""
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Szöveg hasonlóság számítása SequenceMatcher segítségével.
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"""
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if not str1 or not str2:
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return 0.0
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return difflib.SequenceMatcher(None, str1.lower(), str2.lower()).ratio()
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@staticmethod
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async def enrich_asset_from_definition(
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db: AsyncSession,
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asset: Asset,
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definition: VehicleModelDefinition,
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confidence: float
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) -> Asset:
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"""
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Gazdagítsa az asset adatait a definition technikai specifikációival.
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Csak akkor, ha az asset megfelelő mezői üresek.
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"""
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# Technikai specifikációk másolása
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if not asset.power_kw and definition.power_kw:
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asset.power_kw = definition.power_kw
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if not asset.torque_nm and definition.torque_nm:
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asset.torque_nm = definition.torque_nm
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if not asset.engine_capacity and definition.engine_capacity:
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asset.engine_capacity = definition.engine_capacity
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if not asset.transmission_type and definition.transmission_type:
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asset.transmission_type = definition.transmission_type
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if not asset.drive_type and definition.drive_type:
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asset.drive_type = definition.drive_type
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if not asset.fuel_type and definition.fuel_type:
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asset.fuel_type = definition.fuel_type
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if not asset.euro_classification and definition.euro_classification:
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asset.euro_classification = definition.euro_classification
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if not asset.vehicle_class and definition.vehicle_class:
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asset.vehicle_class = definition.vehicle_class
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if not asset.trim_level and definition.body_type:
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asset.trim_level = definition.body_type # body_type -> trim_level mapping
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# Évjárat ellenőrzés
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if not asset.year_of_manufacture and definition.year_from:
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asset.year_of_manufacture = definition.year_from
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# Státusz frissítése
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if confidence >= 0.9:
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asset.data_status = 'verified'
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logger.info(f"Asset {asset.id} enriched and marked as verified (confidence: {confidence:.2f})")
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else:
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asset.data_status = 'enriched'
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logger.info(f"Asset {asset.id} enriched but not verified (confidence: {confidence:.2f})")
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return asset
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@staticmethod
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async def match_and_enrich_asset(
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db: AsyncSession,
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asset_id: uuid.UUID,
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threshold: float = 0.9
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) -> Dict[str, Any]:
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"""
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Fő függvény: Asset ID alapján keres match-et és gazdagítja az adatokat.
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Args:
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db: AsyncSession
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asset_id: Asset UUID
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threshold: Confidence threshold a verification-hoz (alapértelmezett 90%)
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Returns:
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Dict with match results
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"""
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# Asset betöltése
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stmt = select(Asset).where(Asset.id == asset_id).options(selectinload(Asset.catalog))
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result = await db.execute(stmt)
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asset = result.scalar_one_or_none()
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if not asset:
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raise ValueError(f"Asset {asset_id} not found")
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logger.info(f"Matching asset {asset_id} ({asset.brand} {asset.model})")
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# Match keresés
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definition, confidence = await AssetMatcherService.find_best_match(db, asset, threshold=0.8)
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if not definition:
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return {
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"asset_id": str(asset_id),
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"matched": False,
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"confidence": 0.0,
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"message": "No matching definition found in internal catalog"
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}
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# Adatgazdagítás
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enriched_asset = await AssetMatcherService.enrich_asset_from_definition(
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db, asset, definition, confidence
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)
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# Mentés
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await db.commit()
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return {
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"asset_id": str(asset_id),
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"matched": True,
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"confidence": confidence,
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"definition_id": definition.id,
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"definition": f"{definition.make} {definition.marketing_name}",
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"data_status": enriched_asset.data_status,
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"enriched_fields": [
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field for field in [
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"power_kw" if asset.power_kw != enriched_asset.power_kw else None,
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"torque_nm" if asset.torque_nm != enriched_asset.torque_nm else None,
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"engine_capacity" if asset.engine_capacity != enriched_asset.engine_capacity else None,
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"transmission_type" if asset.transmission_type != enriched_asset.transmission_type else None,
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"drive_type" if asset.drive_type != enriched_asset.drive_type else None,
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"fuel_type" if asset.fuel_type != enriched_asset.fuel_type else None,
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] if field is not None
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]
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}
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# Singleton instance
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asset_matcher_service = AssetMatcherService()
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