Common Errors – PageFix AI Troubleshooting Guide
This guide lists the most common errors when using PageFix AI and shows how to fix them quickly.
Most issues are related to API setup, model settings, or incorrect configuration.
API Key Not Working
Problem: The plugin cannot connect to the AI provider.
Possible causes:
- Invalid API key
- Expired or deleted key
- Wrong provider selected (OpenAI vs Gemini)
Solution:
- Check your API key
- Generate a new key if needed
- Make sure the correct provider is selected
No Response from API
Problem: Content generation does not return any result.
Possible causes:
- No credits or billing issue
- Connection timeout
- API service unavailable
Solution:
- Check billing and credits
- Test API connection in settings
- Try again later
Generated Content Is Too Short or Generic
Problem: Output is low quality or repetitive.
Possible causes:
- Weak model selected
- Not enough product data
- No keywords provided
Solution:
- Use a stronger model
- Add more product details
- Use keywords
- Use rewrite feature
Bulk Generation Stops or Fails
Problem: Bulk job does not complete.
Possible causes:
- API limit reached
- Server timeout
- Too many products at once
Solution:
- Reduce batch size
- Use pause and resume
- Check API usage limits
Content Not Saving
Problem: Generated content is not saved.
Possible causes:
- Permission issue
- Plugin conflict
- Database error
Solution:
- Check user permissions
- Disable conflicting plugins
- Check system logs
Wrong Content Appears
Problem: Generated content does not match the product.
Possible causes:
- Missing product data
- Incorrect context settings
- Model misunderstanding input
Solution:
- Add more product details
- Check context settings
- Use rewrite to improve output
API Test Fails
Problem: API test does not return success.
Possible causes:
- Invalid API key
- Wrong endpoint
- Network issue
Solution:
- Re-enter API key
- Check provider settings
- Test internet connection
Performance Is Slow
Problem: Content generation is slow.
Possible causes:
- Using high-quality model
- Large batch size
- Server limitations
Solution:
- Use faster model (Gemini)
- Reduce batch size
- Run smaller jobs
Still Not Working?
If your issue is not listed here, contact support. Include error messages and system details for faster help.