Improve Error Handling for Multimodal Content

[nickna]

Description

As we expand our multimodal capabilities, we need to improve error handling for cases where image loading fails, unsupported content types are provided, or other issues occur. This task involves implementing comprehensive error handling throughout the multimodal pipeline, providing clear error messages and recovery options.

Acceptance Criteria

• Enhance error handling for image content:
  • Implement image loading error detection and reporting
  • Add fallback images for broken URLs
  • Add retry mechanisms with exponential backoff
  • Implement validation for image formats and sizes
• Improve error messages:
  • Create user-friendly error messages for common issues
  • Include troubleshooting steps in error messages
  • Add error codes for programmatic handling
• Add robust validation:
  • Validate content structures before sending to providers
  • Verify image accessibility before including in requests
  • Check image dimensions and formats against provider requirements
• Implement graceful degradation:
  • Fall back to text-only mode when images fail to load
  • Provide alternative content options when original content is unavailable
• Create error reporting and logging:
  • Log detailed error information for debugging
  • Add telemetry for tracking error rates
  • Create error reporting mechanism for users

Technical Notes

• Consider implementing a dedicated ContentValidator service
• Error handling should be consistent across all content types
• Validation should happen as early as possible in the pipeline
• Provide both synchronous and asynchronous validation options
• Consider implementing a circuit breaker pattern for unreliable image sources

Related Files

• ConduitLLM.Core/Models/ContentParts.cs
• ConduitLLM.WebUI/Components/Pages/Chat.razor
• ConduitLLM.Providers/*.cs
• Error handling documentation