Implement data integration tasks with Celery, including periodic fetching and manual refresh of chat data; add utility functions for data processing and transcript handling; create views and URLs for manual data refresh; establish Redis and Celery configuration; enhance error handling and logging; introduce scripts for data cleanup and fixing dashboard data; update documentation for Redis and Celery setup and troubleshooting.

dashboard_project/dashboard/views_export.py

@@ -1,6 +1,7 @@
 # dashboard/views_export.py
 
 import csv
+import json
 from datetime import timedelta
 
 from django.contrib.auth.decorators import login_required
@@ -135,3 +136,115 @@ def export_chats_csv(request):
         )
 
     return response
+
+
+@login_required
+def export_chats_json(request):
+    """Export chat sessions to JSON with filtering options"""
+    user = request.user
+    company = user.company
+
+    if not company:
+        return HttpResponse("You are not associated with any company.", status=403)
+
+    # Get and apply filters
+    data_source_id = request.GET.get("data_source_id")
+    dashboard_id = request.GET.get("dashboard_id")
+    view = request.GET.get("view", "all")
+    start_date = request.GET.get("start_date")
+    end_date = request.GET.get("end_date")
+    country = request.GET.get("country")
+    sentiment = request.GET.get("sentiment")
+    escalated = request.GET.get("escalated")
+
+    # Base queryset
+    sessions = ChatSession.objects.filter(data_source__company=company)
+
+    # Apply data source filter if selected
+    if data_source_id:
+        data_source = get_object_or_404(DataSource, id=data_source_id, company=company)
+        sessions = sessions.filter(data_source=data_source)
+
+    # Apply dashboard filter if selected
+    if dashboard_id:
+        dashboard = get_object_or_404(Dashboard, id=dashboard_id, company=company)
+        data_sources = dashboard.data_sources.all()
+        sessions = sessions.filter(data_source__in=data_sources)
+
+    # Apply view filter
+    if view == "recent":
+        seven_days_ago = timezone.now() - timedelta(days=7)
+        sessions = sessions.filter(start_time__gte=seven_days_ago)
+    elif view == "positive":
+        sessions = sessions.filter(Q(sentiment__icontains="positive"))
+    elif view == "negative":
+        sessions = sessions.filter(Q(sentiment__icontains="negative"))
+    elif view == "escalated":
+        sessions = sessions.filter(escalated=True)
+
+    # Apply additional filters
+    if start_date:
+        sessions = sessions.filter(start_time__date__gte=start_date)
+    if end_date:
+        sessions = sessions.filter(start_time__date__lte=end_date)
+    if country:
+        sessions = sessions.filter(country__icontains=country)
+    if sentiment:
+        sessions = sessions.filter(sentiment__icontains=sentiment)
+    if escalated:
+        escalated_val = escalated.lower() == "true"
+        sessions = sessions.filter(escalated=escalated_val)
+
+    # Order by most recent first
+    sessions = sessions.order_by("-start_time")
+
+    # Create the filename
+    filename = "chat_sessions"
+    if dashboard_id:
+        dashboard = Dashboard.objects.get(id=dashboard_id)
+        filename = f"{dashboard.name.replace(' ', '_').lower()}_chat_sessions"
+    elif data_source_id:
+        data_source = DataSource.objects.get(id=data_source_id)
+        filename = f"{data_source.name.replace(' ', '_').lower()}_chat_sessions"
+
+    # Prepare the data for JSON export using list comprehension
+    data = [
+        {
+            "session_id": session.session_id,
+            "start_time": (session.start_time.isoformat() if session.start_time else None),
+            "end_time": session.end_time.isoformat() if session.end_time else None,
+            "ip_address": session.ip_address,
+            "country": session.country,
+            "language": session.language,
+            "messages_sent": session.messages_sent,
+            "sentiment": session.sentiment,
+            "escalated": session.escalated,
+            "forwarded_hr": session.forwarded_hr,
+            "full_transcript": session.full_transcript,
+            "avg_response_time": session.avg_response_time,
+            "tokens": session.tokens,
+            "tokens_eur": session.tokens_eur,
+            "category": session.category,
+            "initial_msg": session.initial_msg,
+            "user_rating": session.user_rating,
+        }
+        for session in sessions
+    ]
+
+    # Create the HttpResponse with JSON header
+    response = HttpResponse(content_type="application/json")
+    response["Content-Disposition"] = f'attachment; filename="{filename}.json"'
+
+    # Add company and timestamp to the exported JSON
+    current_time = timezone.now().isoformat()
+    export_data = {
+        "company": company.name,
+        "export_date": current_time,
+        "export_type": "chat_sessions",
+        "data": data,
+    }
+
+    # Write JSON data to the response
+    json.dump(export_data, response, indent=2)
+
+    return response