97 lines
3.5 KiB
Python
97 lines
3.5 KiB
Python
import os
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import json
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import logging
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import asyncio
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import re
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import base64
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import httpx
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from typing import Dict, Any, Optional, List
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from sqlalchemy import select
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# JAVÍTVA: AsyncSessionLocal használata
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from app.db.session import AsyncSessionLocal
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from app.models.system import SystemParameter
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logger = logging.getLogger("AI-Service")
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class AIService:
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OLLAMA_BASE_URL = "http://ollama:11434/api/generate"
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TEXT_MODEL = "qwen2.5-coder:32b"
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VISION_MODEL = "llava:7b"
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DVLA_API_KEY = os.getenv("DVLA_API_KEY")
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@classmethod
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async def get_config_delay(cls) -> float:
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try:
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# JAVÍTVA: Aszinkron session kezelés
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async with AsyncSessionLocal() as db:
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stmt = select(SystemParameter).where(SystemParameter.key == "AI_REQUEST_DELAY")
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res = await db.execute(stmt)
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param = res.scalar_one_or_none()
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return float(param.value) if param else 0.1
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except Exception:
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return 0.1
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@classmethod
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async def get_gold_data_from_research(cls, make: str, model: str, raw_context: str) -> Optional[Dict[str, Any]]:
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await asyncio.sleep(await cls.get_config_delay())
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prompt = f"""
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FELADAT: A mellékelt kutatási adatokból állíts össze egy hiteles technikai adatlapot.
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JÁRMŰ: {make} {model}
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KUTATÁSI ADATOK (Szemetesláda tartalom):
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{raw_context}
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SZIGORÚ SZABÁLYOK:
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1. Csak a megerősített adatokat töltsd ki.
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2. Ha lóerőt (hp/bhp) találsz, váltsd át kW-ra (hp * 0.745).
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3. A 'marketing_name' maradjon 50 karakter alatt.
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VÁLASZ FORMÁTUM (Tiszta JSON):
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{{
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"marketing_name": "string",
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"technical_code": "string",
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"ccm": int,
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"kw": int,
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"maintenance": {{
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"oil_type": "string",
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"oil_qty_liters": float,
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"spark_plug": "string",
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"final_drive": "string"
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}},
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"tires": {{
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"front": "string",
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"rear": "string"
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}},
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"is_duplicate_potential": bool
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}}
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"""
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return await cls._execute_ai_call(prompt, make, model)
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@classmethod
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async def _execute_ai_call(cls, prompt: str, make: str, model: str) -> Optional[Dict[str, Any]]:
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payload = {
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"model": cls.TEXT_MODEL,
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"prompt": prompt,
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"stream": False,
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"format": "json",
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"options": {"temperature": 0.1}
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}
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try:
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async with httpx.AsyncClient(timeout=120.0) as client:
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response = await client.post(cls.OLLAMA_BASE_URL, json=payload)
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response.raise_for_status()
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res_json = response.json()
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return json.loads(res_json.get("response", "{}"))
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except Exception as e:
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logger.error(f"❌ AI hiba ({make} {model}): {e}")
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return None
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@classmethod
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async def get_clean_vehicle_data(cls, make: str, raw_model: str, v_type: str, sources: Dict[str, Any]) -> Optional[Dict[str, Any]]:
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await asyncio.sleep(await cls.get_config_delay())
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prompt = f"""
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FELADAT: Normalizáld a jármű adatait.
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GYÁRTÓ: {make} | MODELL: {raw_model}
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ADATOK: {json.dumps(sources)}
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(JSON válasz marketing_name, synonyms, technical_code, ccm, kw, year_from, year_to)
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"""
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return await cls._execute_ai_call(prompt, make, raw_model) |