What mistakes should I avoid when using LocalAI?
Quick Answer
Common mistakes with LocalAI include using vague inputs, trusting important outputs without review, sharing sensitive data carelessly and scaling a workflow before testing it.
Quick Summary
Common mistakes with LocalAI include using vague inputs, trusting important outputs without review, sharing sensitive data carelessly and scaling a workflow before testing it.
Avoid vague requests
Give LocalAI a clear task, useful context and an expected output format. Ambiguous inputs make inconsistent results more likely.
Do not skip verification
Review factual claims, calculations, code, citations and high-impact recommendations before acting on them.
Be careful with sensitive information
Follow your privacy and security rules before submitting confidential, customer or proprietary information.
Test before scaling
Validate a workflow on a small set of real tasks before making it part of a larger process.