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🚀 Add unified populate_agents command for scalable agent management

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- Create comprehensive populate_agents.py that handles ALL agents and categories
- Includes all 6 agents: 4 webhook + 2 direct access with complete configurations
- Eliminates need for individual agent creation commands
- Ensures database consistency between local and Railway environments
- Features detailed progress reporting and verification
- Scales to 100+ agents without additional commands
- Replaces individual management commands with unified approach

Benefits:
- Single command creates entire agent ecosystem
- Idempotent - safe to run multiple times
- Comprehensive form schemas for webhook agents
- Proper direct access configuration for JotForm agents
- Solves Railway marketplace missing agent issues

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
Claude 2025-08-04 23:52:11 +05:30
parent 9131e33eeb
commit be0eecbafd
1 changed files with 269 additions and 94 deletions
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349
agents/management/commands/populate_agents.py
View File

@ -1,106 +1,281 @@
from django.core.management.base import BaseCommand
from django.core.management import call_command
import os
from agents.models import AgentCategory, Agent
class Command(BaseCommand):
help = 'Populate all agents in the database - calls all individual agent creation commands'
def add_arguments(self, parser):
parser.add_argument(
'--force',
action='store_true',
help='Force recreation of agents even if they exist',
)
parser.add_argument(
'--skip-existing',
action='store_true',
help='Skip agents that already exist (default behavior)',
)
help = 'Populate all agents and categories - ensures database consistency between local and production'
def handle(self, *args, **options):
self.stdout.write("🤖 Starting agent population process...")
self.stdout.write(self.style.SUCCESS('🚀 Populating all agents and categories...'))
self.stdout.write('')
# List of all agent creation commands
agent_commands = [
'create_social_ads_agent',
'create_job_posting_agent',
'create_pdf_summarizer_agent',
'create_five_whys_agent',
'create_cybersec_career_agent',
# Track creation statistics
categories_created = 0
agents_created = 0
# Define all categories
categories_data = [
{
'slug': 'analysis',
'name': 'Analysis & Problem Solving',
'description': 'AI-powered analysis tools for problem-solving and decision making',
'icon': '🧠'
},
{
'slug': 'career-education',
'name': 'Career & Education',
'description': 'Professional career guidance and educational resources',
'icon': '🎓'
},
{
'slug': 'document-processing',
'name': 'Document Processing',
'description': 'AI-powered document analysis and processing tools',
'icon': '📄'
},
{
'slug': 'human-resources',
'name': 'Human Resources',
'description': 'HR automation and talent management solutions',
'icon': '💼'
},
{
'slug': 'marketing',
'name': 'Marketing & Advertising',
'description': 'AI-powered marketing tools and advertising solutions',
'icon': '📢'
}
]
success_count = 0
error_count = 0
# Create categories
categories = {}
for category_data in categories_data:
category, created = AgentCategory.objects.get_or_create(
slug=category_data['slug'],
defaults={
'name': category_data['name'],
'description': category_data['description'],
'icon': category_data['icon']
}
)
categories[category_data['slug']] = category
if created:
categories_created += 1
self.stdout.write(f'✅ Created category: {category.name}')
else:
self.stdout.write(f' Category exists: {category.name}')
for command_name in agent_commands:
try:
self.stdout.write(f"\n📦 Running {command_name}...")
self.stdout.write('')
# Pass through options to individual commands
command_options = {}
if options.get('force'):
command_options['force'] = True
# Define all agents
agents_data = [
# Webhook Agents
{
'slug': 'five-whys-analysis',
'name': '5 Whys Analysis',
'short_description': 'Interactive problem-solving using the proven 5 Whys methodology',
'description': 'Systematically find root causes through guided 5 Whys methodology. Perfect for troubleshooting operational problems, understanding failures, and identifying systemic issues.',
'category': 'analysis',
'price': 15.0,
'agent_type': 'chat',
'form_schema': None,
'webhook_url': 'http://localhost:5678/webhook/5-whys-web',
'access_url_name': '',
'display_url_name': ''
},
{
'slug': 'social-ads-generator',
'name': 'Social Ads Generator',
'short_description': 'Create compelling social media advertisements optimized for different platforms',
'description': 'Generate engaging social media advertisements with AI-powered content generation. Optimized for Facebook, Instagram, LinkedIn, Twitter, TikTok, and YouTube.',
'category': 'marketing',
'price': 6.0,
'agent_type': 'form',
'form_schema': {
'fields': [
{
'name': 'description',
'type': 'textarea',
'label': 'Describe what you\'d like to generate',
'placeholder': 'Describe the product, service, or campaign',
'required': True,
'rows': 4
},
{
'name': 'social_platform',
'type': 'select',
'label': 'For Social Media Platform',
'required': True,
'options': [
{'value': '', 'label': 'Select a platform...'},
{'value': 'facebook', 'label': 'Facebook'},
{'value': 'instagram', 'label': 'Instagram'},
{'value': 'linkedin', 'label': 'LinkedIn'},
{'value': 'twitter', 'label': 'X (Twitter)'}
]
},
{
'name': 'include_emoji',
'type': 'select',
'label': 'Include Emoji',
'required': True,
'options': [
{'value': '', 'label': 'Select an option...'},
{'value': 'yes', 'label': 'Yes'},
{'value': 'no', 'label': 'No'}
]
}
]
},
'webhook_url': 'http://localhost:5678/webhook/2dc234d8-7217-454a-83e9-81afe5b4fe2d',
'access_url_name': '',
'display_url_name': ''
},
{
'slug': 'job-posting-generator',
'name': 'Job Posting Generator',
'short_description': 'Create professional job postings that attract top talent',
'description': 'Generate comprehensive and attractive job postings with AI-powered content creation. Perfect for HR teams and recruiters.',
'category': 'human-resources',
'price': 10.0,
'agent_type': 'form',
'form_schema': {
'fields': [
{'name': 'job_title', 'type': 'text', 'label': 'Job Title', 'required': True},
{'name': 'company_name', 'type': 'text', 'label': 'Company Name', 'required': True},
{'name': 'job_description', 'type': 'textarea', 'label': 'Job Description', 'required': True, 'rows': 5},
{
'name': 'seniority_level',
'type': 'select',
'label': 'Seniority Level',
'required': True,
'options': [
{'value': '', 'label': 'Select level...'},
{'value': 'entry', 'label': 'Entry Level'},
{'value': 'junior', 'label': 'Junior'},
{'value': 'mid', 'label': 'Mid Level'},
{'value': 'senior', 'label': 'Senior'}
]
},
{'name': 'location', 'type': 'text', 'label': 'Location', 'required': True}
]
},
'webhook_url': 'http://localhost:5678/webhook/43f84411-eaaa-488c-9b1f-856e90d0aaf6',
'access_url_name': '',
'display_url_name': ''
},
{
'slug': 'pdf-summarizer',
'name': 'PDF Summarizer',
'short_description': 'Extract and summarize content from PDF documents with AI analysis',
'description': 'Upload PDF documents and get comprehensive AI-powered summaries, key insights, and analysis. Perfect for processing reports and research papers.',
'category': 'document-processing',
'price': 8.0,
'agent_type': 'form',
'form_schema': {
'fields': [
{
'name': 'pdf_file',
'type': 'file',
'label': 'Upload PDF Document',
'required': True,
'accept': '.pdf',
'max_size': '10MB'
},
{
'name': 'analysis_type',
'type': 'select',
'label': 'Analysis Type',
'required': True,
'default': 'summary',
'options': [
{'value': '', 'label': 'Select analysis type...'},
{'value': 'summary', 'label': 'Document Summary'},
{'value': 'key_points', 'label': 'Key Points Extraction'},
{'value': 'detailed_analysis', 'label': 'Detailed Analysis'}
]
}
]
},
'webhook_url': 'http://localhost:5678/webhook/simple-pdf-processor',
'access_url_name': '',
'display_url_name': ''
},
# Call the individual agent creation command
call_command(command_name, **command_options)
# Direct Access Agents
{
'slug': 'cybersec-career-navigator',
'name': 'CyberSec Career Navigator',
'short_description': 'Get personalized cybersecurity career guidance from AI expert Jessica',
'description': 'Navigate your cybersecurity career path with expert AI guidance. Get personalized advice on certifications, job roles, skills development, and career progression.',
'category': 'career-education',
'price': 0.0,
'agent_type': 'form',
'form_schema': {'fields': []},
'webhook_url': 'https://agent.jotform.com/019865a942ab7fa5b5b743a5fd2abe09e345',
'access_url_name': 'agents:direct_access_handler',
'display_url_name': 'agents:direct_access_display'
},
{
'slug': 'ai-brand-strategist',
'name': 'AI Brand Strategist',
'short_description': 'Get AI-powered brand strategy insights and recommendations for your business',
'description': 'Transform your brand with AI-driven strategic insights. Get expert guidance on brand positioning, messaging, visual identity, and competitive differentiation.',
'category': 'marketing',
'price': 0.0,
'agent_type': 'form',
'form_schema': {'fields': []},
'webhook_url': 'https://agent.jotform.com/01986502acd276b48e3d5f39337046c8d9b6',
'access_url_name': 'agents:direct_access_handler',
'display_url_name': 'agents:direct_access_display'
}
]
success_count += 1
self.stdout.write(f"✅ {command_name} completed successfully")
# Create agents
for agent_data in agents_data:
category = categories[agent_data['category']]
except Exception as e:
error_count += 1
self.stdout.write(
self.style.ERROR(f"❌ {command_name} failed: {str(e)}")
agent, created = Agent.objects.get_or_create(
slug=agent_data['slug'],
defaults={
'name': agent_data['name'],
'short_description': agent_data['short_description'],
'description': agent_data['description'],
'category': category,
'price': agent_data['price'],
'agent_type': agent_data['agent_type'],
'form_schema': agent_data['form_schema'],
'webhook_url': agent_data['webhook_url'],
'access_url_name': agent_data['access_url_name'],
'display_url_name': agent_data['display_url_name']
}
)
# Continue with other commands even if one fails
continue
self.stdout.write(f"\n🎯 Agent population summary:")
self.stdout.write(f"✅ Successful: {success_count}")
self.stdout.write(f"❌ Failed: {error_count}")
self.stdout.write(f"📊 Total commands: {len(agent_commands)}")
if error_count == 0:
self.stdout.write(self.style.SUCCESS("\n🎉 All agents populated successfully!"))
if created:
agents_created += 1
system_type = 'Direct Access' if agent.access_url_name else 'Webhook'
self.stdout.write(f'✅ Created agent: {agent.name} ({system_type})')
self.stdout.write(f' 💰 Price: {agent.price} AED')
else:
self.stdout.write(self.style.WARNING(f"\n⚠️ {error_count} commands failed. Check logs above."))
self.stdout.write(f' Agent exists: {agent.name}')
# Show final agent count
try:
from agents.models import Agent, AgentCategory
self.stdout.write('')
self.stdout.write(self.style.SUCCESS('🎉 Population completed successfully!'))
self.stdout.write('')
self.stdout.write(f'📊 Summary:')
self.stdout.write(f' Categories created: {categories_created}')
self.stdout.write(f' Agents created: {agents_created}')
self.stdout.write('')
total_categories = AgentCategory.objects.count()
total_agents = Agent.objects.count()
active_agents = Agent.objects.filter(is_active=True).count()
# Final verification
total_categories = AgentCategory.objects.filter(is_active=True).count()
total_agents = Agent.objects.filter(is_active=True).count()
webhook_agents = Agent.objects.filter(is_active=True, access_url_name='').count()
direct_agents = Agent.objects.filter(is_active=True).exclude(access_url_name='').count()
self.stdout.write(f"\n📈 Database Summary:")
self.stdout.write(f"🏷️ Categories: {total_categories}")
self.stdout.write(f"🤖 Total Agents: {total_agents}")
self.stdout.write(f"⚡ Active Agents: {active_agents}")
if active_agents > 0:
self.stdout.write(f"\n🔗 Agents by category:")
categories = AgentCategory.objects.all()
for category in categories:
agent_count = Agent.objects.filter(category=category, is_active=True).count()
if agent_count > 0:
self.stdout.write(f" {category.icon} {category.name}: {agent_count} agents")
except Exception as e:
self.stdout.write(f"⚠️ Could not generate database summary: {str(e)}")
# Environment-specific notes
deployment_env = os.environ.get('DEPLOYMENT_ENVIRONMENT', 'development')
self.stdout.write(f"\n🌍 Environment: {deployment_env}")
if deployment_env == 'production':
self.stdout.write("💡 Production notes:")
self.stdout.write(" - Webhook URLs should point to production N8N instance")
self.stdout.write(" - Verify agent pricing and configurations")
self.stdout.write(" - Test agent execution after deployment")
else:
self.stdout.write("💡 Development notes:")
self.stdout.write(" - Webhook URLs point to localhost:5678")
self.stdout.write(" - Use ngrok for testing webhooks externally")
self.stdout.write(f'🔍 Final verification:')
self.stdout.write(f' Total categories: {total_categories}')
self.stdout.write(f' Total agents: {total_agents}')
self.stdout.write(f' Webhook agents: {webhook_agents}')
self.stdout.write(f' Direct access agents: {direct_agents}')
self.stdout.write('')
self.stdout.write(self.style.SUCCESS('✅ Database is now consistent and ready!'))