""" AI Chatbot using OpenAI/Anthropic Customer support automation """ import os from django.conf import settings from rest_framework.decorators import api_view, permission_classes from rest_framework.permissions import AllowAny from rest_framework.response import Response from django.views.decorators.csrf import csrf_exempt from .recommendations import get_recommendations from frontend.seo_models import SEOSettings from .models import AIConfiguration, AIChatSession, AIChatMessage class AIChatbot: """AI-powered customer support chatbot""" def __init__(self, provider='openai'): self.provider = provider if provider == 'openai': try: from openai import OpenAI self.client = OpenAI(api_key=settings.OPENAI_API_KEY) except ImportError: print("OpenAI library not installed") self.client = None elif provider == 'anthropic': try: from anthropic import Anthropic self.client = Anthropic(api_key=settings.ANTHROPIC_API_KEY) except ImportError: print("Anthropic library not installed") self.client = None def get_response(self, user_message, conversation_history=None): """ Get AI response to user message Args: user_message: User's message string conversation_history: List of previous messages Returns: AI response string """ if not self.client: return "AI service is currently unavailable." system_prompt = self.config.ai_persona messages = [ {"role": "system", "content": system_prompt} ] # Add conversation history if conversation_history: messages.extend(conversation_history) # Add current message messages.append({"role": "user", "content": user_message}) try: if self.provider == 'openai': response = self.client.chat.completions.create( model="gpt-3.5-turbo", messages=messages, max_tokens=500, temperature=0.7 ) return response.choices[0].message.content elif self.provider == 'anthropic': response = self.client.messages.create( model="claude-3-haiku-20240307", max_tokens=500, messages=messages ) return response.content[0].text except Exception as e: print(f"AI Error: {e}") return "I'm having trouble processing your request. Please contact our support team." def get_product_recommendation_text(self, products): """ Generate natural language product recommendations """ if not products: return "I couldn't find any specific recommendations at the moment." product_list = "\n".join([ f"- {p.name}: ₹{p.price} ({p.average_rating}★)" for p in products[:5] ]) return f"Based on your preferences, here are some products you might like:\n\n{product_list}" def get_ai_response(message, history=None, provider='openai'): """ Utility function to get AI chatbot response """ chatbot = AIChatbot(provider=provider) return chatbot.get_response(message, history) @api_view(['POST']) @permission_classes([AllowAny]) def chat_view(request): """AI chat endpoint""" try: config = AIConfiguration.get_settings() if not getattr(config, 'enable_chat', True): return Response({'error': 'AI Chat is disabled'}, status=403) except Exception: pass message = request.data.get('message') provider = request.data.get('provider', 'openai') history = request.data.get('history') if not message: return Response({'error': 'message is required'}, status=400) reply = get_ai_response(message, history, provider) return Response({'reply': reply}) @api_view(['GET']) @permission_classes([AllowAny]) def recommend_view(request): """AI product recommendation endpoint""" try: config = AIConfiguration.get_settings() if not getattr(config, 'enable_ai_recommendations', True): return Response({'error': 'AI Recommendations are disabled'}, status=403) except Exception: pass from products.models import Product recommendation_type = request.GET.get('type', 'trending') limit = int(request.GET.get('limit', 6)) product_id = request.GET.get('product_id') product = None if product_id: try: product = Product.objects.get(id=product_id, is_active=True) except Product.DoesNotExist: product = None user = request.user if request.user.is_authenticated else None products = get_recommendations(user=user, product=product, recommendation_type=recommendation_type, limit=limit) items = [{ 'id': p.id, 'name': p.name, 'slug': p.slug, 'price': float(p.price), 'on_sale': p.on_sale, 'image_url': p.featured_image.url if p.featured_image else None } for p in products] return Response({'products': items}) @api_view(['POST']) @permission_classes([AllowAny]) def generate_seo_view(request): """ AI-assisted SEO generation for a page. Body: { "page_url": "/product/slug/", "page_type": "PRODUCT", "title_hint": "...", "description_hint": "..." } """ try: config = AIConfiguration.get_settings() if not getattr(config, 'enable_ai_seo', True): return Response({'error': 'AI SEO generation is disabled'}, status=403) except Exception: pass page_url = request.data.get('page_url') page_type = request.data.get('page_type', 'CUSTOM') title_hint = (request.data.get('title_hint') or '').strip() description_hint = (request.data.get('description_hint') or '').strip() if not page_url: return Response({'error': 'page_url is required'}, status=400) base_title = title_hint or page_url.strip('/').replace('-', ' ').title()[:60] base_desc = description_hint or f"Explore {base_title} at AiBiMagics. Quality products, secure checkout, and fast delivery."[:160] meta_title = base_title meta_description = base_desc og_title = base_title og_description = base_desc twitter_title = base_title twitter_description = base_desc try: # Try AI refinement if provider available provider = request.data.get('provider', 'openai') bot = AIChatbot(provider=provider) if bot.client: prompt = f"Refine this SEO title and description for an e-commerce page.\nTitle: {base_title}\nDescription: {base_desc}\nReturn JSON with keys: title, description." reply = bot.get_response(prompt) # naive parse if isinstance(reply, str) and 'title' in reply: import json try: data = json.loads(reply) meta_title = (data.get('title') or meta_title)[:70] meta_description = (data.get('description') or meta_description)[:160] og_title = meta_title og_description = meta_description twitter_title = meta_title twitter_description = meta_description except Exception: pass except Exception: pass obj, _ = SEOSettings.objects.update_or_create( page_url=page_url, defaults={ 'page_type': page_type, 'meta_title': meta_title, 'meta_description': meta_description, 'og_title': og_title, 'og_description': og_description, 'twitter_title': twitter_title, 'twitter_description': twitter_description, 'is_active': True } ) return Response({ 'message': 'SEO generated', 'page_url': obj.page_url, 'meta_title': obj.meta_title, 'meta_description': obj.meta_description })