mirror of
https://github.com/kjanat/livegraphs-django.git
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138 lines
4.4 KiB
Python
138 lines
4.4 KiB
Python
# dashboard/views_export.py
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import csv
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from datetime import timedelta
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from django.contrib.auth.decorators import login_required
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from django.db.models import Q
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from django.http import HttpResponse
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from django.shortcuts import get_object_or_404
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from django.utils import timezone
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from .models import ChatSession, Dashboard, DataSource
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@login_required
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def export_chats_csv(request):
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"""Export chat sessions to CSV with filtering options"""
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user = request.user
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company = user.company
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if not company:
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return HttpResponse("You are not associated with any company.", status=403)
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# Get and apply filters
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data_source_id = request.GET.get("data_source_id")
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dashboard_id = request.GET.get("dashboard_id")
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view = request.GET.get("view", "all")
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start_date = request.GET.get("start_date")
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end_date = request.GET.get("end_date")
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country = request.GET.get("country")
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sentiment = request.GET.get("sentiment")
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escalated = request.GET.get("escalated")
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# Base queryset
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sessions = ChatSession.objects.filter(data_source__company=company)
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# Apply data source filter if selected
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if data_source_id:
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data_source = get_object_or_404(DataSource, id=data_source_id, company=company)
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sessions = sessions.filter(data_source=data_source)
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# Apply dashboard filter if selected
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if dashboard_id:
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dashboard = get_object_or_404(Dashboard, id=dashboard_id, company=company)
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data_sources = dashboard.data_sources.all()
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sessions = sessions.filter(data_source__in=data_sources)
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# Apply view filter
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if view == "recent":
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seven_days_ago = timezone.now() - timedelta(days=7)
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sessions = sessions.filter(start_time__gte=seven_days_ago)
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elif view == "positive":
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sessions = sessions.filter(Q(sentiment__icontains="positive"))
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elif view == "negative":
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sessions = sessions.filter(Q(sentiment__icontains="negative"))
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elif view == "escalated":
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sessions = sessions.filter(escalated=True)
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# Apply additional filters
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if start_date:
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sessions = sessions.filter(start_time__date__gte=start_date)
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if end_date:
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sessions = sessions.filter(start_time__date__lte=end_date)
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if country:
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sessions = sessions.filter(country__icontains=country)
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if sentiment:
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sessions = sessions.filter(sentiment__icontains=sentiment)
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if escalated:
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escalated_val = escalated.lower() == "true"
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sessions = sessions.filter(escalated=escalated_val)
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# Order by most recent first
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sessions = sessions.order_by("-start_time")
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# Create the HttpResponse with CSV header
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filename = "chat_sessions"
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if dashboard_id:
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dashboard = Dashboard.objects.get(id=dashboard_id)
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filename = f"{dashboard.name.replace(' ', '_').lower()}_chat_sessions"
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elif data_source_id:
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data_source = DataSource.objects.get(id=data_source_id)
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filename = f"{data_source.name.replace(' ', '_').lower()}_chat_sessions"
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response = HttpResponse(content_type="text/csv")
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response["Content-Disposition"] = f'attachment; filename="{filename}.csv"'
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# Create CSV writer
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writer = csv.writer(response)
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# Write CSV header
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writer.writerow(
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[
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"Session ID",
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"Start Time",
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"End Time",
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"IP Address",
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"Country",
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"Language",
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"Messages Sent",
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"Sentiment",
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"Escalated",
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"Forwarded HR",
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"Full Transcript",
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"Avg Response Time (s)",
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"Tokens",
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"Tokens EUR",
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"Category",
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"Initial Message",
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"User Rating",
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]
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)
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# Write data rows
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for session in sessions:
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writer.writerow(
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[
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session.session_id,
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session.start_time,
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session.end_time,
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session.ip_address,
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session.country,
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session.language,
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session.messages_sent,
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session.sentiment,
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"Yes" if session.escalated else "No",
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"Yes" if session.forwarded_hr else "No",
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session.full_transcript,
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session.avg_response_time,
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session.tokens,
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session.tokens_eur,
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session.category,
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session.initial_msg,
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session.user_rating,
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]
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)
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return response
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