quiz_generator.py

import aiohttp
import asyncio
import json
import logging
import re
from typing import List, Dict, Any
from fallback_questions import FallbackQuestions

logger = logging.getLogger(__name__)

class QuizGenerator:
    def __init__(self, api_key: str):
        self.api_key = api_key
        self.model_used = "fallback"
        self.generation_method = "fallback"
        self.fallback = FallbackQuestions()
        
        # Modell-konfigurasjon
        self.models = {
            "norwegian": "NbAiLab/nb-gpt-j-6B",
            "english": "meta-llama/Llama-2-70b-chat-hf",
            "fallback": "google/flan-t5-small"
        }
    
    async def generate_quiz(self, request) -> List[Dict[str, Any]]:
        """Hovedmetode for quiz-generering"""
        logger.info(f"Starter quiz-generering: {request.tema} ({request.språk})")
        
        # Prøv AI-generering først
        if self.api_key:
            try:
                questions = await self._try_ai_generation(request)
                if questions:
                    logger.info(f"AI-generering suksess: {len(questions)} spørsmål")
                    return questions
            except Exception as e:
                logger.warning(f"AI-generering feilet: {e}")
        
        # Fallback til forhåndsdefinerte spørsmål
        logger.info("Bruker fallback-spørsmål")
        self.model_used = "fallback"
        self.generation_method = "predefined"
        
        return self.fallback.get_questions(
            tema=request.tema,
            språk=request.språk,
            antall=request.antall_spørsmål,
            type=request.type,
            vanskelighet=request.vanskelighetsgrad
        )
    
    async def _try_ai_generation(self, request) -> List[Dict[str, Any]]:
        """Prøv AI-generering med forskjellige modeller"""
        
        # Velg modell basert på språk
        if request.språk == "no":
            model = self.models["norwegian"]
        else:
            model = self.models["english"]
        
        logger.info(f"Prøver AI-modell: {model}")
        
        try:
            questions = await self._call_huggingface_api(model, request)
            if questions:
                self.model_used = model
                self.generation_method = "ai"
                return questions
        except Exception as e:
            logger.warning(f"Modell {model} feilet: {e}")
        
        # Prøv fallback-modell
        try:
            logger.info(f"Prøver fallback-modell: {self.models['fallback']}")
            questions = await self._call_huggingface_api(self.models["fallback"], request)
            if questions:
                self.model_used = self.models["fallback"]
                self.generation_method = "ai_fallback"
                return questions
        except Exception as e:
            logger.warning(f"Fallback-modell feilet: {e}")
        
        return []
    
    async def _call_huggingface_api(self, model: str, request) -> List[Dict[str, Any]]:
        """Kall Hugging Face Inference API"""
        
        prompt = self._build_prompt(request, model)
        
        async with aiohttp.ClientSession() as session:
            async with session.post(
                f"https://api-inference.huggingface.co/models/{model}",
                headers={
                    "Authorization": f"Bearer {self.api_key}",
                    "Content-Type": "application/json"
                },
                json={
                    "inputs": prompt,
                    "parameters": {
                        "max_new_tokens": 1500,
                        "temperature": 0.7,
                        "do_sample": True,
                        "top_p": 0.9
                    }
                },
                timeout=aiohttp.ClientTimeout(total=30)
            ) as response:
                
                if response.status != 200:
                    error_text = await response.text()
                    raise Exception(f"HTTP {response.status}: {error_text}")
                
                data = await response.json()
                
                # Parse response
                if isinstance(data, list) and data:
                    generated_text = data[0].get("generated_text", "")
                elif isinstance(data, dict):
                    generated_text = data.get("generated_text", "")
                else:
                    raise Exception("Uventet response-format")
                
                # Parse quiz fra generert tekst
                questions = self._parse_quiz_response(generated_text, request.antall_spørsmål)
                
                if not questions:
                    raise Exception("Kunne ikke parse quiz-spørsmål fra AI-respons")
                
                return questions
    
    def _build_prompt(self, request, model: str) -> str:
        """Bygg prompt for AI-modell"""
        
        if request.språk == "no":
            return f"""Generer {request.antall_spørsmål} quiz-spørsmål på norsk om temaet "{request.tema}".

Format for hvert spørsmål:
SPØRSMÅL: [spørsmålstekst]
A) [alternativ 1]
B) [alternativ 2]
C) [alternativ 3]
D) [alternativ 4]
KORREKT: [A, B, C eller D]