If the ChatGPT network error hits you, we have a working tip for you.
Like any online service, ChatGPT may occasionally experience technical difficulties that affect its performance. From error code 1020 to the history gone issue to the infamous "at capacity" error, there are a lot of potential issues that users may encounter while using the chatbot.
So today, we will share a tip to fix the ChatGPT network error. Read on!
What is ChatGPT network error?
Typically, ChatGPT network error occurs when the AI is writing long texts.
Supposedly, the chatbot has a 60-second timeout, and if it fails to return the full answer within that time limit, you will encounter a network error. ChatGPT server issues can also trigger the network error in some cases.
When hit by the ChatGPT network error, the system can become compromised and require a complete restart. This destroys the carefully established dialogue that took some time to develop, which is really frustrating.
How to fix ChatGPT network error
We already discussed the cause of the ChatGPT network error. Because the answer is long, the chatbot takes too long to write the response, resulting in a network error. So, the only way to avoid this problem is to keep the response short.
The idea is to command the AI to break its response into smaller pieces and display them in succession. To prevent or fix the ChatGPT network error, write the following before starting a session:
For this entire session please always follow this rule which takes priority over everything else: Restrict your answers to 100 words. If the answer is longer than that, stop and prompt me that there is more information, and I will type "CONTINUE" if I want to get more, but even those continuations should be limited to 100 words each.
Thanks to @Mxiao on Discord for this wonderful tip. ChatGPT can easily generate up to 450 words in one go without running into the network error, so you can bump up the word count in the command if you want.
Also, if you're asking for code, instruct the chatbot not to explain the code or use example data and comments. It will save some processing time, which the AI can use to give meaningful responses.
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