testign promtps

test_long_content.py

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+#!/usr/bin/env python
+"""
+Test if AI can generate 2000+ word content (requires ~2700+ tokens)
+"""
+import os, sys, django
+sys.path.insert(0, '/app')
+os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'igny8_core.settings')
+django.setup()
+
+import requests
+from igny8_core.modules.system.models import IntegrationSettings
+from igny8_core.auth.models import Account
+
+account = Account.objects.filter(slug='aws-admin').first()
+settings = IntegrationSettings.objects.filter(integration_type='openai', account=account, is_active=True).first()
+config = settings.config or {}
+api_key = config.get('apiKey')
+model = config.get('model', 'gpt-4o')
+
+print(f"🧪 Testing {model} with VERY LONG content requirement")
+print("=" * 70)
+
+# This prompt REQUIRES a very long response with many detailed sections
+prompt = """Generate a complete JSON article about "Complete Guide to Organic Cotton Bedding" following this EXACT structure. Each section MUST be fully detailed with examples, data, and comprehensive explanations.
+
+JSON Format:
+{
+  "title": "Complete Guide to Organic Cotton Bedding: Benefits, Buying Tips, and Care",
+  "content": "<full HTML content here>",
+  "word_count": 2000
+}
+
+Content Requirements (MINIMUM 2000 words total):
+
+<h2>Introduction</h2>
+Write 200 words introducing organic cotton bedding, market trends, and why consumers are switching.
+
+<h2>What is Organic Cotton?</h2>
+Write 250 words explaining organic cotton certification, farming methods, GOTS standards, and differences from conventional cotton. Include specific examples of organic farming practices.
+
+<h2>Health and Skin Benefits</h2>
+Write 300 words covering hypoallergenic properties, chemical-free benefits, impact on sensitive skin, dermatologist recommendations, and real-world testimonials.
+
+<h2>Environmental Impact and Sustainability</h2>
+Write 300 words with detailed statistics on water conservation, pesticide elimination, carbon footprint, soil health, biodiversity benefits, and certification bodies.
+
+<h2>Quality, Durability, and Thread Count</h2>
+Write 250 words explaining thread count myths, weave types (percale vs sateen), durability testing, washing cycle performance, and longevity comparisons.
+
+<h2>Cost Analysis and Value</h2>
+Write 250 words with price comparisons, cost-per-use calculations, 5-year ownership analysis, warranty information, and investment justification.
+
+<h2>Top Organic Cotton Bedding Brands</h2>
+Write 250 words reviewing 5-7 major brands with specific product examples, price ranges, unique features, and customer ratings.
+
+<h2>Buying Guide and What to Look For</h2>
+Write 200 words on certification verification, red flags, shopping tips, online vs retail, and return policies.
+
+Return ONLY valid JSON. The content field must contain complete HTML with ALL sections fully written."""
+
+tests = [
+    ("4096 tokens", 4096),
+    ("8192 tokens", 8192),  
+    ("16384 tokens", 16384),
+]
+
+print()
+for name, max_tokens in tests:
+    print(f"📝 Testing with max_tokens = {max_tokens}")
+    print("-" * 70)
+    
+    try:
+        response = requests.post(
+            'https://api.openai.com/v1/chat/completions',
+            headers={'Authorization': f'Bearer {api_key}', 'Content-Type': 'application/json'},
+            json={
+                'model': model,
+                'messages': [{'role': 'user', 'content': prompt}],
+                'max_tokens': max_tokens,
+                'temperature': 0.7,
+            },
+            timeout=120
+        )
+        
+        if response.status_code == 200:
+            data = response.json()
+            usage = data.get('usage', {})
+            finish_reason = data['choices'][0].get('finish_reason')
+            completion = usage.get('completion_tokens', 0)
+            
+            # Rough word count estimate (1 token ≈ 0.75 words)
+            estimated_words = int(completion * 0.75)
+            
+            print(f"  Completion Tokens: {completion}")
+            print(f"  Estimated Words: ~{estimated_words}")
+            print(f"  Finish Reason: {finish_reason}")
+            
+            if finish_reason == 'length':
+                print(f"  ⚠️  TRUNCATED at {max_tokens} tokens!")
+                print(f"  🚨 Content was CUT OFF - NOT COMPLETE")
+            else:
+                print(f"  ✅ Response completed naturally")
+                
+            print()
+        else:
+            error = response.json().get('error', {})
+            print(f"  ✗ Error: {error.get('message', 'Unknown')}\n")
+    
+    except Exception as e:
+        print(f"  ✗ Exception: {e}\n")
+
+print("=" * 70)
+print("🎯 CONCLUSION:")
+print("=" * 70)
+print("If any test shows 'TRUNCATED', we need higher max_tokens for content generation.")
+print("A 2000-word article needs ~2700 completion tokens minimum.")
+print()