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- 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)
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