Managing Context in Conversations with GPT-3.5-turbo: Is It Possible Without Resending Previous Messages, or Should I Switch Versions?

I am currently leveraging the GPT-3.5-turbo model to build an application that requires fluid and coherent conversational interactions. As interactions progress, maintaining conversation context becomes a challenge, especially without the need to resend all previous messages with each API call.

I’ve been exploring ways to enable the model to remember past interactions to provide a more natural user experience without the overhead of managing an extensive conversation history in every request. My specific question is: Is there a capability within the GPT-3.5-turbo API, or any recommended technique, that allows the model to be aware of previous messages without needing to include them all in each chat call? Furthermore, is switching to a different version of ChatGPT a necessary step to achieve this functionality?

Any guidance on implementing efficient context management in conversations or suggestions on best practices for this purpose would be greatly appreciated. Insights on whether a different model version offers better support for context awareness without the cumbersome requirement of resending conversation history would also be valuable.

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This has been asked and answered 100 times.

No. This is not possible.

The models are stateless every token in the context needs to be processed, every time, for every token generated.

Therefore, every time you send a message to the model you need to send along with it the entire context you want it to be aware of.