testign promtps

test_idea_generation.py

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+#!/usr/bin/env python
+"""
+Test idea generation with 16384 max_tokens to ensure it works correctly
+"""
+import os, sys, django
+sys.path.insert(0, '/app')
+os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'igny8_core.settings')
+django.setup()
+
+import requests, json
+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')
+max_tokens = config.get('max_tokens', 16384)
+
+# Read the actual idea generation prompt
+with open('/data/idea-generation-prompt.md', 'r') as f:
+    prompt_template = f.read()
+
+# Simulate idea generation input
+cluster_data = """
+Cluster ID: 1 | Name: Organic Cotton Bedding | Description: Keywords related to organic and eco-friendly bedding products
+"""
+
+cluster_keywords = """
+Cluster ID: 1 | Name: Organic Cotton Bedding | Keywords: organic cotton sheets, eco-friendly bedding, sustainable duvet covers, GOTS certified bedding, organic mattress protector, chemical-free bedding, organic pillowcases, hypoallergenic sheets
+"""
+
+prompt = prompt_template.replace('[IGNY8_CLUSTERS]', cluster_data)
+prompt = prompt.replace('[IGNY8_CLUSTER_KEYWORDS]', cluster_keywords)
+
+print(f"🧪 Testing Idea Generation with max_tokens={max_tokens:,}")
+print("=" * 70)
+print(f"Prompt length: {len(prompt):,} characters (~{len(prompt)//4:,} tokens)")
+print()
+
+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,
+            'response_format': {"type": "json_object"}
+        },
+        timeout=60
+    )
+    
+    if response.status_code == 200:
+        data = response.json()
+        usage = data.get('usage', {})
+        finish_reason = data['choices'][0].get('finish_reason')
+        
+        prompt_tokens = usage.get('prompt_tokens', 0)
+        completion_tokens = usage.get('completion_tokens', 0)
+        total_tokens = usage.get('total_tokens', 0)
+        
+        print(f"✓ Response received")
+        print(f"   Input Tokens:  {prompt_tokens:>6,}")
+        print(f"   Output Tokens: {completion_tokens:>6,}")
+        print(f"   Total Tokens:  {total_tokens:>6,}")
+        print(f"   Finish Reason: {finish_reason}")
+        print()
+        
+        # Try to parse the response
+        try:
+            response_text = data['choices'][0]['message']['content']
+            ideas_data = json.loads(response_text)
+            ideas_count = len(ideas_data.get('ideas', []))
+            
+            print(f"✅ Generated {ideas_count} ideas successfully")
+            
+            # Show summary of first idea
+            if ideas_count > 0:
+                first_idea = ideas_data['ideas'][0]
+                print()
+                print("Sample Idea:")
+                print(f"  Title: {first_idea.get('title', 'N/A')}")
+                
+                desc = first_idea.get('description', {})
+                if isinstance(desc, dict) and 'H2' in desc:
+                    h2_count = len(desc['H2'])
+                    print(f"  H2 Sections: {h2_count}")
+                    
+                print(f"  Keywords: {first_idea.get('covered_keywords', 'N/A')[:60]}...")
+        except json.JSONDecodeError:
+            print("⚠️  Could not parse JSON response")
+        
+        print()
+        if finish_reason == 'length':
+            print("🚨 WARNING: Response was TRUNCATED!")
+            print("   Consider increasing max_tokens further")
+        else:
+            print("✅ Response completed successfully")
+            print(f"   Used {completion_tokens} of {max_tokens:,} available tokens")
+            print(f"   Headroom: {((max_tokens - completion_tokens) / max_tokens * 100):.1f}%")
+            
+    else:
+        print(f"✗ API Error: {response.status_code}")
+        print(response.json().get('error', {}).get('message', '')[:200])
+
+except Exception as e:
+    print(f"✗ Exception: {str(e)}")
+
+print()
+print("=" * 70)
+print("CONCLUSION:")
+print("=" * 70)
+print("Idea generation typically uses 1500-2500 tokens for 3 ideas with outlines.")
+print(f"Current max_tokens={max_tokens:,} provides plenty of headroom.")
+print("✅ Configuration is optimal for idea generation.")