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import gradio as gr
from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
import json
import os
import asyncio
import aiohttp
from typing import List, Optional, Literal
import time
import logging
import re
# Setup logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
app = FastAPI(
title="SoActi AI Quiz API",
description="Separat AI-tjeneste for quiz-generering som SoActi kan bruke",
version="1.0.0"
)
# Request/Response models
class QuizRequest(BaseModel):
tema: str
språk: Literal["no", "en"] = "no"
antall_spørsmål: int = 5
type: Literal["sted", "rute"] = "sted"
vanskelighetsgrad: int = 3
class QuizQuestion(BaseModel):
spørsmål: str
alternativer: List[str]
korrekt_svar: int
forklaring: str
class QuizResponse(BaseModel):
success: bool
questions: List[QuizQuestion]
metadata: dict
message: str
class HealthResponse(BaseModel):
status: str
models_loaded: bool
api_key_configured: bool
uptime_seconds: float
# Global state
start_time = time.time()
api_key = os.getenv("HUGGINGFACE_API_KEY")
@app.get("/", response_model=dict)
async def root():
"""Root endpoint med API-informasjon"""
return {
"service": "SoActi AI Quiz API",
"version": "1.0.0",
"status": "running",
"endpoints": {
"generate": "/generate-quiz",
"health": "/health",
"models": "/models",
"docs": "/docs"
},
"description": "Separat AI-tjeneste for quiz-generering"
}
@app.get("/health", response_model=HealthResponse)
async def health_check():
"""Helsesjekk for tjenesten"""
uptime = time.time() - start_time
return HealthResponse(
status="healthy",
models_loaded=True,
api_key_configured=bool(api_key),
uptime_seconds=uptime
)
@app.get("/models")
async def get_available_models():
"""Liste over tilgjengelige AI-modeller"""
return {
"norwegian_models": [
{
"name": "NbAiLab/nb-gpt-j-6B",
"description": "Beste for norsk - Nasjonalbiblioteket",
"cost": "Gratis",
"quality": "Høy (norsk)"
}
],
"english_models": [
{
"name": "meta-llama/Llama-2-70b-chat-hf",
"description": "Beste kvalitet - Premium",
"cost": "Premium ($$$)",
"quality": "Exceptional"
},
{
"name": "mistralai/Mistral-7B-Instruct-v0.1",
"description": "Balansert kvalitet/kostnad",
"cost": "Premium ($$)",
"quality": "Meget høy"
}
],
"fallback_models": [
{
"name": "google/flan-t5-small",
"description": "Gratis fallback",
"cost": "Gratis",
"quality": "Middels"
}
]
}
@app.post("/generate-quiz", response_model=QuizResponse)
async def generate_quiz(request: QuizRequest):
"""Hovedendepunkt for quiz-generering"""
try:
logger.info(f"Genererer quiz for tema: {request.tema} ({request.språk})")
# Valider request
if not request.tema.strip():
raise HTTPException(status_code=400, detail="Tema kan ikke være tomt")
if request.antall_spørsmål < 1 or request.antall_spørsmål > 20:
raise HTTPException(status_code=400, detail="Antall spørsmål må være mellom 1 og 20")
# Generer quiz
from quiz_generator import QuizGenerator
generator = QuizGenerator(api_key)
start_time = time.time()
questions = await generator.generate_quiz(request)
generation_time = time.time() - start_time
if not questions:
raise HTTPException(status_code=500, detail="Kunne ikke generere spørsmål")
logger.info(f"Genererte {len(questions)} spørsmål på {generation_time:.2f}s")
return QuizResponse(
success=True,
questions=questions,
metadata={
"generation_time": round(generation_time, 2),
"model_used": generator.get_model_used(),
"method": generator.get_generation_method(),
"tema": request.tema,
"språk": request.språk
},
message=f"Genererte {len(questions)} spørsmål om '{request.tema}'"
)
except HTTPException:
raise
except Exception as e:
logger.error(f"Feil ved quiz-generering: {str(e)}")
raise HTTPException(status_code=500, detail=f"Intern feil: {str(e)}")
@app.post("/validate-quiz")
async def validate_quiz(questions: List[QuizQuestion]):
"""Valider genererte quiz-spørsmål"""
try:
from quiz_validator import QuizValidator
validator = QuizValidator()
results = []
for i, question in enumerate(questions):
validation = validator.validate_question(question.dict())
results.append({
"question_index": i,
"valid": validation["valid"],
"score": validation["score"],
"issues": validation["issues"]
})
overall_score = sum(r["score"] for r in results) / len(results)
return {
"overall_valid": all(r["valid"] for r in results),
"overall_score": round(overall_score, 2),
"question_results": results
}
except Exception as e:
raise HTTPException(status_code=500, detail=f"Valideringsfeil: {str(e)}")
# Gradio interface for testing
def gradio_generate_quiz(tema, språk, antall, type_val, vanskelighet):
"""Gradio wrapper for quiz generation"""
try:
import asyncio
request = QuizRequest(
tema=tema,
språk=språk,
antall_spørsmål=antall,
type=type_val,
vanskelighetsgrad=vanskelighet
)
# Run async function in sync context
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
response = loop.run_until_complete(generate_quiz(request))
loop.close()
# Format for display
output = f"✅ {response.message}\n\n"
output += f"🤖 Modell: {response.metadata.get('model_used', 'Ukjent')}\n"
output += f"⏱️ Tid: {response.metadata.get('generation_time', 0)}s\n"
output += f"🔧 Metode: {response.metadata.get('method', 'Ukjent')}\n\n"
for i, q in enumerate(response.questions, 1):
output += f"📝 **Spørsmål {i}:** {q.spørsmål}\n"
for j, alt in enumerate(q.alternativer):
marker = "✅" if j == q.korrekt_svar else "❌"
output += f" {chr(65+j)}) {alt} {marker}\n"
output += f"💡 **Forklaring:** {q.forklaring}\n\n"
return output
except Exception as e:
retur