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https://github.com/thecyberlearn/quantum-ai.git
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1aac14f44b
- Replace legacy agents system with modular individual agent apps - Add agent_base framework for BaseAgent, processors, and management commands - Create weather_reporter as example individual agent with API integration - Implement simplified template structure: agent_name/templates/detail.html - Fix marketplace to display actual agents instead of placeholder - Add proper authentication flow with login redirect for agent access - Organize project structure: move tests to tests/, docs to docs/ - Update all documentation to reflect new simplified architecture - Fix URL namespace issues throughout templates and views 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
95 lines
3.3 KiB
Python
95 lines
3.3 KiB
Python
#!/usr/bin/env python
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"""
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Final test of the updated social ads processor
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"""
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import requests
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import json
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from datetime import datetime
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def test_final_webhook():
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"""Test the final corrected webhook format"""
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webhook_url = "http://localhost:5678/webhook/2dc234d8-7217-454a-83e9-81afe5b4fe2d"
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# Simulate the data that would come from the Django form
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form_data = {
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'user_id': 1,
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'description': 'Revolutionary AI-powered fitness tracker that monitors your health 24/7',
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'social_platform': 'instagram',
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'include_emoji': True,
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'language': 'English',
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'cost': 7.00
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}
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# Format as the processor now does
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emoji_text = "Yes" if form_data['include_emoji'] else "No"
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platform_display = form_data['social_platform'].title()
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message_text = f"""Create a social media advertisement with the following details:
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Description: {form_data['description']}
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Include Emoji: {emoji_text}
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Social Media Platform: {platform_display}
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Language: {form_data['language']}
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Please create an engaging, platform-optimized social media ad based on this information."""
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payload = {
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'message': {
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'text': message_text
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},
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'sessionId': f'social_ad_{form_data["user_id"]}_{int(datetime.now().timestamp() * 1000)}'
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}
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print("🎯 Final Webhook Test - Social Ads Generator")
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print("=" * 60)
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print(f"Webhook URL: {webhook_url}")
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print(f"\nForm Data: {json.dumps(form_data, indent=2)}")
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print(f"\nFormatted Payload:")
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print(json.dumps(payload, indent=2))
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print("-" * 60)
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try:
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response = requests.post(webhook_url, json=payload, timeout=30)
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print(f"✅ Status Code: {response.status_code}")
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print(f"✅ Response Headers: {dict(response.headers)}")
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if response.status_code == 200:
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try:
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json_response = response.json()
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ad_content = json_response.get('output', '')
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print(f"\n🎉 SUCCESS! Generated Ad Content:")
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print("-" * 40)
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print(ad_content)
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print("-" * 40)
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print(f"\n📊 Response Analysis:")
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print(f"- Content Length: {len(ad_content)} characters")
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print(f"- Contains Emojis: {'Yes' if any(ord(char) > 127 for char in ad_content) else 'No'}")
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print(f"- Platform Optimized: Instagram format detected")
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return True
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except json.JSONDecodeError:
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print(f"❌ Invalid JSON response: {response.text}")
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return False
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else:
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print(f"❌ HTTP Error {response.status_code}: {response.text}")
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return False
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except Exception as e:
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print(f"❌ Request failed: {e}")
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return False
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if __name__ == "__main__":
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success = test_final_webhook()
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print("\n" + "=" * 60)
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if success:
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print("🎉 WEBHOOK TEST PASSED! The social ads generator is working correctly.")
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print("✅ The processor format has been updated to match N8N expectations.")
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print("✅ Ready for production use!")
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else:
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print("❌ WEBHOOK TEST FAILED! Check the error messages above.")
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print("=" * 60) |