from django.shortcuts import render
from django.utils import timezone
from django.shortcuts import redirect
from review.forms import ReplyForm
from review.models import Review, CustomReply
from gauth.models import Location
from difflib import SequenceMatcher

from .nlu_utils import model_inference, analyze_inference


def filter_with_last_ten_reviews(location_id, replies):
    replies = list(replies)
    revs = Review.objects.filter(location_id=location_id).exclude(reply=None).order_by('-update_time')[:12]
    for r in revs:
        s1 = r.reply.replied_text
        for rep in replies:
            s2 = rep.reply
            similarity = SequenceMatcher(None, s1, s2).ratio()
            if similarity > 0.7:
                replies.remove(rep)
                print(similarity, '--------------', rep.reply_category)
            # if similarity < 0.7 and rep not in reps:
            #     reps.append(rep)
    return replies


def predict_report(request, review_id):
    review = Review.objects.filter(review_id=review_id).first()
    if review is None:
        return redirect('un-replied-review')
    location_id = review.location.location_id
    text = review.comment.lower()
    res = model_inference(text=text)
    intents = analyze_inference(res)
    now = timezone.now()
    form = ReplyForm()
    date = now - timezone.timedelta(days=30)
    reviews = Review.objects.filter(reply=None, update_time__gte=date).order_by('-update_time')
    replies = {}
    for intent in intents.keys():
        r = CustomReply.objects.filter(reply_category=intent)
        filtered_replies = filter_with_last_ten_reviews(location_id, r)
        replies[intent] = filtered_replies
    context = {
        'reviews': reviews,
        'form': form,
        'intents': intents,
        'replies': replies
    }
    return render(request, 'dashboard.html', context)