As large language models (LLMs) like GPT-4 become integral to applications starting from customer support to analyze and code generation, developers often face a significant challenge:
GPT model evolution GPT-1 to GPT-4. Unlike traditional software, GPT-4 doesn’t throw runtime errors — instead it could provide irrelevant output, hallucinated facts, or misunderstood instructions. Debugging therefore takes a structured, analytical approach.
This guide walks through essential strategies to diagnose and fix issues when GPT-4 is not responding not surprisingly.