👓 fix: Assistants Vision Prompt Error Handling (legacy)

[danny-avila]

Summary

• Added a try-catch block to the vision prompt creation in the chatV1 controller to catch and log any errors that occur during this process.
• Updated the model parameter in the vision prompt creation to use the dynamic model variable instead of the hardcoded 'gpt-4-vision-preview'.
• Modified the processVisionRequest function in ToolService to check if the completion exists before accessing its usage property, preventing potential undefined errors.
• Improved code formatting for better readability, particularly in the construction of the additional_instructions string.

Closes #4526

Remember:

• The Load Balancer should distribute traffic evenly
• If one droplet goes down, traffic should automatically route to the others
• You can monitor the Load Balancer metrics in DO dashboard

Would you like me to suggest some specific stress testing tools or show you how to monitor specific metrics?

Checklist

• My code adheres to this project's style guidelines
• I have performed a self-review of my own code
• I have commented in any complex areas of my code
• My changes do not introduce new warnings
• I have tested the error handling scenarios
• Local unit tests pass with my changes