| import os |
| import requests |
| from rest_framework.views import APIView |
| from rest_framework.response import Response |
| from rest_framework import permissions, status |
| from django.db.models import Sum |
| from finance.models import Transaction, Budget |
|
|
| class ChatbotView(APIView): |
| permission_classes = [permissions.IsAuthenticated] |
|
|
| def post(self, request): |
| user_message = request.data.get('message') |
| if not user_message: |
| return Response({"error": "Message is required"}, status=status.HTTP_400_BAD_REQUEST) |
|
|
| |
| user = request.user |
| |
| |
| cash_available = getattr(user, 'profile', None) and user.profile.cash_available or 0 |
| net_worth = getattr(user, 'profile', None) and user.profile.net_worth or 0 |
| |
| |
| budgets = Budget.objects.filter(user=user) |
| budget_context = "\n".join([f"- {b.name}: ${b.spent_amount} spent out of ${b.budget_amount} ({b.status})" for b in budgets]) |
| |
| |
| recent_tx = Transaction.objects.filter(user=user).order_by('-date')[:5] |
| tx_context = "\n".join([f"- {t.date}: ${t.amount} at {t.merchant} ({t.category})" for t in recent_tx]) |
| |
| context_prompt = f"""You are Aureon's premium AI Financial Assistant. You give concise, professional, and helpful financial advice. |
| User Profile: |
| - Available Cash: ₹{cash_available} |
| - Net Worth: ₹{net_worth} |
| Active Budgets: |
| {budget_context if budget_context else "No active budgets."} |
| Recent Transactions: |
| {tx_context if tx_context else "No recent transactions."} |
| |
| Based strictly on this data, answer the user's question in rupees (₹). Do not make up data not present here. |
| User Question: "{user_message}" |
| """ |
|
|
| |
| hf_api_key = os.getenv('HUGGINGFACE_API_KEY') |
| if not hf_api_key: |
| return Response({"error": "Hugging Face API Key is not configured on the server. Please add HUGGINGFACE_API_KEY to your .env file."}, status=status.HTTP_500_INTERNAL_SERVER_ERROR) |
|
|
| |
| API_URL = "https://router.huggingface.co/v1/chat/completions" |
| headers = { |
| "Authorization": f"Bearer {hf_api_key}", |
| "Content-Type": "application/json" |
| } |
| |
| |
| payload = { |
| "model": "meta-llama/Llama-3.1-8B-Instruct", |
| "messages": [ |
| {"role": "system", "content": context_prompt}, |
| {"role": "user", "content": user_message} |
| ], |
| "max_tokens": 300, |
| "temperature": 0.5 |
| } |
|
|
| try: |
| response = requests.post(API_URL, headers=headers, json=payload) |
| if response.status_code == 200: |
| result = response.json() |
| if 'choices' in result and len(result['choices']) > 0: |
| bot_reply = result['choices'][0]['message']['content'].strip() |
| else: |
| bot_reply = "I'm sorry, I couldn't generate a response at this time." |
| |
| return Response({"reply": bot_reply}) |
| else: |
| return Response({"error": f"AI model error: {response.text}"}, status=status.HTTP_502_BAD_GATEWAY) |
| except Exception as e: |
| return Response({"error": str(e)}, status=status.HTTP_500_INTERNAL_SERVER_ERROR) |
|
|
|
|
| import json |
|
|
| class AIInsightsView(APIView): |
| permission_classes = [permissions.IsAuthenticated] |
|
|
| def get(self, request): |
| user = request.user |
| cash_available = getattr(user, 'profile', None) and user.profile.cash_available or 0 |
| net_worth = getattr(user, 'profile', None) and user.profile.net_worth or 0 |
| |
| |
| budgets = Budget.objects.filter(user=user) |
| budget_context = "\n".join([f"- {b.name}: ${b.spent_amount} spent out of ${b.budget_amount} ({b.status})" for b in budgets]) |
| |
| |
| recent_tx = Transaction.objects.filter(user=user).order_by('-date')[:5] |
| tx_context = "\n".join([f"- {t.date}: ${t.amount} at {t.merchant} ({t.category})" for t in recent_tx]) |
|
|
| context_prompt = f"""You are Aureon's premium AI Financial Assistant. Based on the user's financial profile, generate exactly three helpful financial insights. |
| User Profile: |
| - Available Cash: ₹{cash_available} |
| - Net Worth: ₹{net_worth} |
| Active Budgets: |
| {budget_context if budget_context else "No active budgets."} |
| Recent Transactions: |
| {tx_context if tx_context else "No recent transactions."} |
| |
| Provide the output strictly as a JSON array of three objects. Do not include markdown code block formatting (like ```json), other tags, or explanations. Each object must have these exactly: |
| - "id": unique number 1, 2, 3 |
| - "type": one of "success", "warning", "suggestion", "pattern" |
| - "title": a very short title |
| - "message": a helpful one-sentence message |
| - "savings": optional, an integer number of potential savings in rupees (e.g. 42) |
| - "detail": a short secondary detail string (e.g. "Keep it up!") |
| - "options": optional array of 2 strings if type is "suggestion" |
| |
| Example: |
| [ |
| {{"id": 1, "type": "success", "title": "Great news!", "message": "You spent 15% less this week on food.", "savings": 25, "detail": "Keep it up!"}}, |
| {{"id": 2, "type": "warning", "title": "Watch out!", "message": "Your subscriptions total ₹45 this month.", "detail": "Consider cancelling unused ones."}}, |
| {{"id": 3, "type": "suggestion", "title": "Smart Suggestion", "message": "You have extra cash.", "options": ["Invest it", "Add to goal"]}} |
| ] |
| """ |
|
|
| hf_api_key = os.getenv('HUGGINGFACE_API_KEY') |
| if not hf_api_key: |
| fallback_insights = [ |
| {"id": 1, "type": "success", "title": "Welcome Aboard!", "message": "Your Aureon setup is complete. Let's start tracking your finances.", "detail": "Nice job!"}, |
| {"id": 2, "type": "warning", "title": "No Transactions Yet", "message": "Upload a CSV bank statement to get deep Llama-powered insights.", "detail": "Visit Data Import page."}, |
| {"id": 3, "type": "suggestion", "title": "Set a Saving Goal", "message": "Create your first goal to help Llama calculate targets.", "options": ["Go to Goals", "View suggestions"]} |
| ] |
| return Response(fallback_insights) |
|
|
| |
| API_URL = "https://router.huggingface.co/v1/chat/completions" |
| headers = { |
| "Authorization": f"Bearer {hf_api_key}", |
| "Content-Type": "application/json" |
| } |
| payload = { |
| "model": "meta-llama/Llama-3.1-8B-Instruct", |
| "messages": [ |
| {"role": "user", "content": context_prompt} |
| ], |
| "max_tokens": 500, |
| "temperature": 0.3 |
| } |
|
|
| try: |
| response = requests.post(API_URL, headers=headers, json=payload) |
| if response.status_code == 200: |
| result = response.json() |
| bot_reply = result['choices'][0]['message']['content'].strip() if ('choices' in result and len(result['choices']) > 0) else "" |
| if bot_reply.startswith("```"): |
| bot_reply = bot_reply.strip("`").strip("json").strip() |
| parsed_insights = json.loads(bot_reply) |
| return Response(parsed_insights) |
| else: |
| raise Exception(response.text) |
| except Exception as e: |
| fallback_insights = [ |
| {"id": 1, "type": "success", "title": "Safe Balance", "message": f"Your current cash balance is ${cash_available}.", "detail": "Good liquidity status."}, |
| {"id": 2, "type": "suggestion", "title": "Create a Budget", "message": "Setting up budgets helps Llama suggest dynamic saving paths.", "detail": "Create one in the Budget tab."}, |
| {"id": 3, "type": "pattern", "title": "Clean Sheet", "message": "No abnormal spending patterns detected this week.", "detail": "Nice work!"} |
| ] |
| return Response(fallback_insights) |
|
|
