# Complete Manual Agent Creation Guide - Error-Free Edition This guide provides step-by-step instructions for manually creating AI agents in the NetCop Hub platform. **Updated with proven patterns from the successful 5 Whys Analyzer implementation.** ## Table of Contents 1. [Overview](#overview) 2. [Prerequisites](#prerequisites) 3. [Step 1: Create Django App](#step-1-create-django-app) 4. [Step 2: Design Models](#step-2-design-models) 5. [Step 3: Create Processor](#step-3-create-processor) 6. [Step 4: Implement Views](#step-4-implement-views) 7. [Step 5: Configure URLs](#step-5-configure-urls) 8. [Step 6: Create Templates](#step-6-create-templates) 9. [Step 7: Integration](#step-7-integration) 10. [Step 8: Testing](#step-8-testing) 11. [Troubleshooting](#troubleshooting) 12. [Advanced Customization](#advanced-customization) ## Overview ### Agent Types - **API Agents**: Direct integration with external APIs (e.g., OpenWeather, Stripe) - **Webhook Agents**: Integration with N8N workflows or custom webhooks *(Recommended)* - **Dual-Mode Agents**: Free interactions + paid reports *(5 Whys Pattern)* ### Architecture *(5 Whys Success Patterns)* Each agent is a separate Django app that extends the base agent framework: - `BaseAgent`: Marketplace catalog entry - `BaseAgentRequest`/`BaseAgentResponse`: Request/response tracking - `BaseAgentProcessor`: Processing logic (API or webhook) - `BaseAgentView`: Form handling and authentication ### 🚀 **5 Whys Analyzer Success Patterns** The most robust agent implementation includes these key patterns: **Core Success Features:** - **Session-based architecture**: UUID tracking with persistent state - **Dual-mode processing**: Free chat interactions + paid report generation - **Delayed wallet deduction**: Only charge after successful processing - **Comprehensive error handling**: Try-catch blocks throughout lifecycle - **Smart status tracking**: pending → processing → completed/failed **Apply these patterns for maximum reliability and user satisfaction.** ## Prerequisites 1. Django project setup and running 2. Base agent framework installed (`agent_base` app) 3. Authentication system configured 4. Wallet system for payments --- ## 🎯 **5 Whys Analyzer - Proven Implementation Patterns** Before diving into the step-by-step guide, study these proven patterns from the successful 5 Whys Analyzer implementation. **Following these patterns ensures error-free agent creation.** ### Session-Based Models *(Recommended for Complex Agents)* ```python # Key model patterns from 5 Whys success class FiveWhysAnalyzerRequest(BaseAgentRequest): # Session management session_id = models.CharField(max_length=100, default=uuid.uuid4, db_index=True) # Chat interaction tracking chat_messages = models.JSONField(default=list) # Mode tracking report_generated = models.BooleanField(default=False) chat_active = models.BooleanField(default=True) # Specific request data problem_statement = models.TextField(blank=True) analysis_depth = models.CharField(max_length=20, choices=[...]) ``` ### Delayed Wallet Deduction Pattern *(Critical for Reliability)* ```python # ❌ Wrong - deduct before processing user.deduct_balance(cost, description, agent_slug) response = process_request() # ✅ Correct - 5 Whys pattern (deduct after success) def process_report_response(self, response_data, request_obj): try: # Process the request first final_report = response_data.get('output', '') success = bool(final_report) and response_data.get('success', True) if success: # Save response data response_obj.final_report = final_report response_obj.save() # ONLY deduct wallet balance after successful processing request_obj.user.deduct_balance( request_obj.cost, f"5 Whys Analysis Agent - Final Report", 'five-whys-analyzer' ) request_obj.status = 'completed' else: request_obj.status = 'failed' request_obj.save() return response_obj except Exception as e: request_obj.status = 'failed' request_obj.save() raise Exception(f"Failed to process: {e}") ``` ### Dual-Mode Processing Pattern *(Free + Paid Interactions)* ```python # 5 Whys processor pattern - handle both free chat and paid reports def process_request(self, **kwargs): message_type = kwargs.get('message_type', 'chat') if message_type == 'chat': return self.handle_chat_message(**kwargs) # Free elif message_type == 'generate_report': return self.handle_report_generation(**kwargs) # Paid else: raise ValueError(f"Unknown message type: {message_type}") def handle_chat_message(self, **kwargs): # No wallet deduction for chat request_obj.cost = 0 # Process free interaction return self.process_chat_response(response_data, request_obj) def handle_report_generation(self, **kwargs): # Set cost for report generation request_obj.cost = 8.0 # Process paid interaction (wallet deducted only after success) return self.process_report_response(response_data, request_obj) ``` ### Comprehensive Error Handling Pattern ```python # 5 Whys error handling pattern def process_response(self, response_data, request_obj): try: request_obj.status = 'processing' request_obj.save() # Extract and validate response result = response_data.get('output', '') success = bool(result) and response_data.get('success', True) # Create response object response_obj, created = ModelResponse.objects.get_or_create( request=request_obj, defaults={'success': success, 'processing_time': response_data.get('processing_time', 0)} ) if success: response_obj.result_data = result response_obj.save() # Only deduct balance after confirmed success request_obj.user.deduct_balance( request_obj.cost, f"Agent processing - {request_obj.agent.name}", request_obj.agent.slug ) request_obj.status = 'completed' else: request_obj.status = 'failed' response_obj.error_message = "Processing failed" response_obj.save() request_obj.processed_at = timezone.now() request_obj.save() return response_obj except Exception as e: # Always handle errors gracefully request_obj.status = 'failed' request_obj.save() # Log the error for debugging print(f"Agent {self.agent_slug} error: {e}") raise Exception(f"Failed to process response: {e}") ``` ### Status Tracking Pattern *(Request Lifecycle Management)* ```python # 5 Whys status flow pattern # 1. Initial state request_obj.status = 'pending' # 2. Start processing request_obj.status = 'processing' request_obj.save() # 3. Complete or fail try: # ... do processing ... request_obj.status = 'completed' except Exception: request_obj.status = 'failed' finally: request_obj.processed_at = timezone.now() request_obj.save() ``` ### Template URL Namespace Pattern *(Prevents 404 Errors)* ```html Wallet Wallet Home Login ``` ### Database Index Pattern *(Performance Optimization)* ```python # 5 Whys database optimization patterns class AgentRequest(BaseAgentRequest): session_id = models.CharField(max_length=100, default=uuid.uuid4, db_index=True) class Meta: indexes = [ models.Index(fields=['session_id']), models.Index(fields=['user', 'chat_active']), models.Index(fields=['status', 'created_at']), ] ``` **🎯 Key Takeaway:** The 5 Whys Analyzer's success comes from these robust patterns. Apply them to your agents for maximum reliability and user satisfaction. --- ## Step 1: Create Django App ### 1.1 Create the App ```bash python manage.py startapp agent_[name] # Example: python manage.py startapp agent_pdf_analyzer ``` ### 1.2 App Structure ``` agent_pdf_analyzer/ ├── __init__.py ├── admin.py ├── apps.py ├── models.py ├── processor.py ├── views.py ├── urls.py ├── migrations/ │ └── __init__.py └── templates/ └── agent_pdf_analyzer/ └── detail.html ``` ### 1.3 Configure Apps.py ```python # agent_pdf_analyzer/apps.py from django.apps import AppConfig class AgentPdfAnalyzerConfig(AppConfig): default_auto_field = 'django.db.models.BigAutoField' name = 'agent_pdf_analyzer' ``` ## Step 2: Design Models ### 2.1 Request Model ```python # agent_pdf_analyzer/models.py from django.db import models from agent_base.models import BaseAgentRequest, BaseAgentResponse class PdfAnalyzerRequest(BaseAgentRequest): """PDF Analyzer request tracking""" # Agent-specific fields pdf_file = models.FileField(upload_to='uploads/pdf/') analysis_type = models.CharField( max_length=50, choices=[ ('summary', 'Document Summary'), ('extraction', 'Data Extraction'), ('sentiment', 'Sentiment Analysis'), ], default='summary' ) language = models.CharField(max_length=10, default='en') class Meta: db_table = 'pdf_analyzer_requests' verbose_name = 'PDF Analyzer Request' verbose_name_plural = 'PDF Analyzer Requests' ``` ### 2.2 Response Model ```python class PdfAnalyzerResponse(BaseAgentResponse): """PDF Analyzer response storage""" request = models.OneToOneField( PdfAnalyzerRequest, on_delete=models.CASCADE, related_name='response' ) # Response-specific fields extracted_text = models.TextField(blank=True) summary = models.TextField(blank=True) key_points = models.JSONField(default=list, blank=True) sentiment_score = models.FloatField(null=True, blank=True) confidence_score = models.FloatField(null=True, blank=True) class Meta: db_table = 'pdf_analyzer_responses' verbose_name = 'PDF Analyzer Response' verbose_name_plural = 'PDF Analyzer Responses' ``` ## Step 3: Create Processor Choose between API or Webhook processor based on your integration needs. ### 3.1 API Processor Example ```python # agent_pdf_analyzer/processor.py from agent_base.processors import StandardAPIProcessor from django.utils import timezone from .models import PdfAnalyzerRequest, PdfAnalyzerResponse import json class PdfAnalyzerProcessor(StandardAPIProcessor): """API processor for PDF Analyzer agent""" agent_slug = 'pdf-analyzer' api_base_url = 'https://api.docparser.com/v1/process' api_key_env = 'DOCPARSER_API_KEY' auth_method = 'bearer' def prepare_request_data(self, **kwargs): """Prepare API request data""" return { 'file_url': kwargs.get('pdf_file_url'), 'analysis_type': kwargs.get('analysis_type', 'summary'), 'language': kwargs.get('language', 'en'), } def should_use_get(self, **kwargs): """Use POST for file uploads""" return False def process_response(self, response_data, request_obj): """Process the API response""" try: request_obj.status = 'processing' request_obj.save() # Extract response data extracted_text = response_data.get('extracted_text', '') summary = response_data.get('summary', '') key_points = response_data.get('key_points', []) sentiment_score = response_data.get('sentiment_score') confidence_score = response_data.get('confidence', 0.0) # Create response object response_obj = PdfAnalyzerResponse.objects.create( request=request_obj, success=response_data.get('success', True), processing_time=response_data.get('processing_time', 0), extracted_text=extracted_text, summary=summary, key_points=key_points, sentiment_score=sentiment_score, confidence_score=confidence_score, ) # Update request as completed request_obj.status = 'completed' request_obj.processed_at = timezone.now() request_obj.save() return response_obj except Exception as e: # Handle error request_obj.status = 'failed' request_obj.save() # Create error response error_response = PdfAnalyzerResponse.objects.create( request=request_obj, success=False, error_message=str(e), processing_time=response_data.get('processing_time', 0) ) raise Exception(f"Failed to process PDF Analyzer response: {e}") ``` ### 3.2 Webhook Processor Example ```python # For N8N webhook integration from agent_base.processors import StandardWebhookProcessor class PdfAnalyzerProcessor(StandardWebhookProcessor): """Webhook processor for PDF Analyzer agent""" agent_slug = 'pdf-analyzer' webhook_url = settings.N8N_WEBHOOK_PDF_ANALYZER agent_id = '789' def prepare_message_text(self, **kwargs): """Prepare message for N8N webhook""" analysis_type = kwargs.get('analysis_type', 'summary') pdf_file = kwargs.get('pdf_file') return f"Analyze PDF file: {pdf_file.name}, Type: {analysis_type}" def process_response(self, response_data, request_obj): """Process webhook response""" # Similar to API processor but for webhook data format pass ``` ## Step 4: Implement Views ### 4.1 Detail View ```python # agent_pdf_analyzer/views.py from django.shortcuts import render, redirect from django.contrib.auth.decorators import login_required from django.contrib import messages from django.http import JsonResponse from django.views.decorators.csrf import csrf_exempt from django.utils.decorators import method_decorator from django.views import View from agent_base.models import BaseAgent from .models import PdfAnalyzerRequest, PdfAnalyzerResponse from .processor import PdfAnalyzerProcessor import json @login_required def pdf_analyzer_detail(request): """Detail page for PDF Analyzer agent""" try: agent = BaseAgent.objects.get(slug='pdf-analyzer') except BaseAgent.DoesNotExist: messages.error(request, 'PDF Analyzer agent not found.') return redirect('core:homepage') # Get user's recent requests user_requests = PdfAnalyzerRequest.objects.filter( user=request.user ).order_by('-created_at')[:10] context = { 'agent': agent, 'user_requests': user_requests } return render(request, 'agent_pdf_analyzer/detail.html', context) ``` ### 4.2 Process View ```python @method_decorator(csrf_exempt, name='dispatch') class PdfAnalyzerProcessView(View): """Process PDF Analyzer requests""" def post(self, request): if not request.user.is_authenticated: return JsonResponse({'error': 'Authentication required'}, status=401) try: # Handle multipart form data for file uploads pdf_file = request.FILES.get('pdf_file') analysis_type = request.POST.get('analysis_type', 'summary') language = request.POST.get('language', 'en') if not pdf_file: return JsonResponse({'error': 'PDF file is required'}, status=400) # Get agent agent = BaseAgent.objects.get(slug='pdf-analyzer') # Check wallet balance if not request.user.has_sufficient_balance(agent.price): return JsonResponse({'error': 'Insufficient wallet balance'}, status=400) # Create request object agent_request = PdfAnalyzerRequest.objects.create( user=request.user, agent=agent, cost=agent.price, pdf_file=pdf_file, analysis_type=analysis_type, language=language, ) # ⚠️ WARNING: This violates 5 Whys pattern! # Better to deduct ONLY after successful processing # Consider implementing delayed deduction pattern for reliability # Process request processor = PdfAnalyzerProcessor() result = processor.process_request( request_obj=agent_request, user_id=request.user.id, pdf_file_url=agent_request.pdf_file.url, analysis_type=analysis_type, language=language, ) return JsonResponse({ 'success': True, 'request_id': str(agent_request.id), 'message': 'PDF Analyzer request processed successfully' }) except BaseAgent.DoesNotExist: return JsonResponse({'error': 'PDF Analyzer agent not found'}, status=404) except Exception as e: return JsonResponse({'error': str(e)}, status=500) ``` ### 4.3 Result View ```python @login_required def pdf_analyzer_result(request, request_id): """Get result for a specific request""" try: agent_request = PdfAnalyzerRequest.objects.get( id=request_id, user=request.user ) if hasattr(agent_request, 'response'): response = agent_request.response return JsonResponse({ 'success': response.success, 'status': agent_request.status, 'extracted_text': response.extracted_text, 'summary': response.summary, 'key_points': response.key_points, 'sentiment_score': response.sentiment_score, 'confidence_score': response.confidence_score, 'processing_time': float(response.processing_time) if response.processing_time else None, 'error_message': response.error_message }) else: return JsonResponse({ 'success': False, 'status': agent_request.status, 'message': 'Processing in progress...' }) except PdfAnalyzerRequest.DoesNotExist: return JsonResponse({'error': 'Request not found'}, status=404) except Exception as e: return JsonResponse({'error': str(e)}, status=500) ``` ## Step 5: Configure URLs ### 5.1 App URLs ```python # agent_pdf_analyzer/urls.py from django.urls import path from . import views app_name = 'pdf_analyzer' urlpatterns = [ path('', views.pdf_analyzer_detail, name='detail'), path('process/', views.PdfAnalyzerProcessView.as_view(), name='process'), path('result//', views.pdf_analyzer_result, name='result'), ] ``` ### 5.2 Main URL Registration ```python # netcop_hub/urls.py urlpatterns = [ path('admin/', admin.site.urls), path('auth/', include('authentication.urls')), path('agents/weather-reporter/', include('weather_reporter.urls')), path('agents/pdf-analyzer/', include('agent_pdf_analyzer.urls')), # Add this line path('', include('core.urls')), ] ``` ## Step 6: Create Templates ### 6.1 Create Template Directory ```bash mkdir -p agent_pdf_analyzer/templates/agent_pdf_analyzer/ ``` ### 6.2 Detail Template ```html {% load static %} PDF Analyzer Agent - NetCop AI Hub 🚀 NetCop AI Hub Marketplace {% if user.is_authenticated %} Wallet {{ user.wallet_balance|floatformat:2 }} AED {% else %} Login {% endif %} 📄 PDF Analyzer Agent Extract text, generate summaries, and analyze sentiment from PDF documents using advanced AI. 💰 Cost: {{ agent.price }} AED {% if messages %} {% for message in messages %} {{ message }} {% endfor %} {% endif %} {% csrf_token %} 📁 Upload PDF Document Supported: PDF files up to 10MB ⚙️ Analysis Options Analysis Type: Document Summary Data Extraction Sentiment Analysis Language: English Arabic French Spanish 💳 Your Wallet {% if user.is_authenticated %} {{ user.wallet_balance|floatformat:2 }} AED {% else %} 0.00 AED {% endif %} Available Balance {% if user.is_authenticated %} {% if user.wallet_balance >= agent.price %} 📄 Analyze PDF ({{ agent.price }} AED) {% else %} Insufficient balance! You need {{ agent.price }} AED. 💰 Top Up Wallet {% endif %} {% else %} 🔑 Login to Continue {% endif %} ``` ## Step 7: Integration ### 7.1 Add to Django Settings ```python # netcop_hub/settings.py INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', # Core apps 'core', 'authentication', 'wallet', 'agent_base', # Agent apps 'weather_reporter', 'agent_pdf_analyzer', # Add this line ] ``` ### 7.2 Run Migrations ```bash python manage.py makemigrations agent_pdf_analyzer python manage.py migrate ``` ### 7.3 Create BaseAgent Entry ```python # In Django shell or management command python manage.py shell from agent_base.models import BaseAgent from decimal import Decimal BaseAgent.objects.create( name="PDF Analyzer", slug="pdf-analyzer", description="Extract text, generate summaries, and analyze sentiment from PDF documents", category="utilities", price=Decimal('5.00'), icon="📄", agent_type="api", rating=Decimal('4.5'), review_count=25, is_active=True ) ``` ### 7.4 Environment Variables ```bash # Add to .env file DOCPARSER_API_KEY=your_api_key_here ``` ### 7.5 Admin Configuration ```python # agent_pdf_analyzer/admin.py from django.contrib import admin from .models import PdfAnalyzerRequest, PdfAnalyzerResponse @admin.register(PdfAnalyzerRequest) class PdfAnalyzerRequestAdmin(admin.ModelAdmin): list_display = ['id', 'user', 'status', 'analysis_type', 'created_at'] list_filter = ['status', 'analysis_type', 'created_at'] search_fields = ['user__email', 'user__username'] readonly_fields = ['id', 'created_at', 'processed_at'] @admin.register(PdfAnalyzerResponse) class PdfAnalyzerResponseAdmin(admin.ModelAdmin): list_display = ['id', 'request', 'success', 'confidence_score', 'created_at'] list_filter = ['success', 'created_at'] readonly_fields = ['id', 'created_at'] ``` ## Step 8: Testing ### 8.1 Test Checklist - [ ] Agent appears in marketplace - [ ] Agent detail page loads correctly - [ ] Authentication required for access - [ ] File upload works - [ ] Form submission processes correctly - [ ] Wallet balance is checked - [ ] Payment is deducted - [ ] Processing completes successfully - [ ] Results are displayed - [ ] Error handling works ### 8.2 Test Commands ```bash # Test URL routing python manage.py check # Test database queries python manage.py shell >>> from agent_pdf_analyzer.models import * >>> from agent_base.models import BaseAgent >>> BaseAgent.objects.filter(slug='pdf-analyzer').exists() # Test processor >>> from agent_pdf_analyzer.processor import PdfAnalyzerProcessor >>> processor = PdfAnalyzerProcessor() >>> # Test with sample data ``` ### 8.3 Browser Testing 1. Visit `/marketplace/` - verify agent appears 2. Click "Use Agent" - verify redirect to detail page 3. Try without login - verify authentication required 4. Upload test PDF file 5. Submit form and monitor processing 6. Check wallet balance deduction 7. Verify results display ## Troubleshooting ### Common Issues #### 1. URL Namespace Errors **Error**: `NoReverseMatch: Reverse for 'wallet' not found` **Fix**: Use proper namespaces in templates: ```html {% url 'wallet' %} {% url 'core:wallet' %} ``` #### 2. Template Not Found **Error**: `TemplateDoesNotExist: detail.html` **Fix**: Ensure template is in correct location within the agent app: ```bash # Correct location: agent_[name]/templates/agent_[name]/detail.html # Example: agent_pdf_analyzer/templates/agent_pdf_analyzer/detail.html # NOT in global templates folder # Restart Django server after moving templates ``` **Test template loading**: ```bash python manage.py shell -c " from django.template.loader import get_template template = get_template('agent_pdf_analyzer/detail.html') print('✅ Template found:', template.origin.name) " ``` #### 3. Migration Issues **Error**: Database migration fails **Fix**: ```bash python manage.py makemigrations agent_[name] --empty # Edit migration file if needed python manage.py migrate ``` #### 4. Import Errors **Error**: Module import fails **Fix**: Check `INSTALLED_APPS` and Python path: ```python # Ensure app is in INSTALLED_APPS INSTALLED_APPS = [ # ... 'agent_pdf_analyzer', ] ``` #### 5. File Upload Issues **Error**: File upload fails **Fix**: Configure media settings: ```python # settings.py MEDIA_URL = '/media/' MEDIA_ROOT = os.path.join(BASE_DIR, 'media') # urls.py (in development) if settings.DEBUG: urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT) ``` #### 6. API Integration Issues **Error**: External API calls fail **Fix**: Check API credentials and endpoints: ```python # Test API connection import requests response = requests.get('https://api.example.com/test', headers={'Authorization': 'Bearer YOUR_KEY'}) print(response.status_code, response.text) ``` ## Advanced Customization ### Custom Field Types ```python # For complex data structures class PdfAnalyzerRequest(BaseAgentRequest): # JSON field for complex configurations analysis_config = models.JSONField(default=dict, blank=True) # Custom validation def clean(self): super().clean() if self.pdf_file and self.pdf_file.size > 10 * 1024 * 1024: # 10MB raise ValidationError('PDF file too large (max 10MB)') ``` ### Custom Business Logic ```python # Override processor methods for custom logic class PdfAnalyzerProcessor(StandardAPIProcessor): def pre_process_request(self, request_obj, **kwargs): """Custom logic before API call""" # Validate file format # Compress large files # Extract metadata pass def post_process_response(self, response_obj, **kwargs): """Custom logic after API response""" # Generate additional insights # Send notifications # Update analytics pass ``` ### Multiple API Integration ```python class PdfAnalyzerProcessor(StandardAPIProcessor): def process_request(self, request_obj, **kwargs): """Custom multi-step processing""" # Step 1: Extract text text_response = self.call_text_extraction_api(**kwargs) # Step 2: Analyze sentiment sentiment_response = self.call_sentiment_api(text_response['text']) # Step 3: Generate summary summary_response = self.call_summary_api(text_response['text']) # Combine results combined_response = { 'extracted_text': text_response['text'], 'sentiment': sentiment_response['sentiment'], 'summary': summary_response['summary'], } return self.process_response(combined_response, request_obj) ``` ### Custom Template Components ```html {% include 'components/file_upload.html' with accept='.pdf' max_size='10MB' %} {% include 'components/progress_bar.html' with status=request.status %} {% include 'components/result_display.html' with response=response %} ``` ### Error Handling Patterns ```python class PdfAnalyzerProcessor(StandardAPIProcessor): def handle_api_error(self, error, request_obj): """Custom error handling""" if 'rate_limit' in str(error).lower(): # Retry after delay return self.retry_with_delay(request_obj, delay=60) elif 'invalid_file' in str(error).lower(): # User error - don't retry return self.create_error_response(request_obj, "Invalid PDF file format") else: # Unknown error - log and notify self.log_error(error, request_obj) return super().handle_api_error(error, request_obj) ``` ## Best Practices 1. **Security**: Always validate file uploads, sanitize inputs, check permissions 2. **Performance**: Implement caching, optimize database queries, handle large files efficiently 3. **User Experience**: Provide clear feedback, show progress indicators, handle errors gracefully 4. **Maintainability**: Use consistent naming, document complex logic, write tests 5. **Monitoring**: Log important events, track usage metrics, monitor error rates ## Summary This guide covers the complete process of creating an AI agent manually in the NetCop Hub platform. Following these steps ensures your agent integrates properly with the authentication, payment, and processing systems while providing a professional user experience. For automated agent creation, use the `create_agent` management command, but this manual approach gives you full control over customization and complex business logic.
Extract text, generate summaries, and analyze sentiment from PDF documents using advanced AI.