Describe the feature or improvement you're requesting
I would like to request the implementation of a global memory feature that allows OpenAI models to retain and share context across different chats and sessions. Currently, the memory is session-based and does not persist between interactions. This limits the model's ability to recall information shared in prior conversations, making it harder to maintain continuity in longer interactions or ongoing tasks.
With global memory, the model could store user preferences, past context, and relevant information from previous chats, creating a more personalized and efficient user experience. This feature would allow the model to adapt better to user needs over time, avoiding the need to repeatedly explain the same details in different chats.
Additional context
The absence of a global memory across chats is a major limitation, especially for users who engage in multiple sessions with the model. It creates a fragmented experience, as the model cannot "remember" previous conversations. For example, if a user has ongoing projects or preferences, they must repeatedly provide the same context every time a new session is started.
Having global memory would address this by storing critical data across interactions, enhancing the model's ability to provide relevant responses and improve personalization. The user could also have control over what data is stored and accessed, ensuring privacy and transparency.
Describe the feature or improvement you're requesting
I would like to request the implementation of a global memory feature that allows OpenAI models to retain and share context across different chats and sessions. Currently, the memory is session-based and does not persist between interactions. This limits the model's ability to recall information shared in prior conversations, making it harder to maintain continuity in longer interactions or ongoing tasks.
With global memory, the model could store user preferences, past context, and relevant information from previous chats, creating a more personalized and efficient user experience. This feature would allow the model to adapt better to user needs over time, avoiding the need to repeatedly explain the same details in different chats.
Additional context
The absence of a global memory across chats is a major limitation, especially for users who engage in multiple sessions with the model. It creates a fragmented experience, as the model cannot "remember" previous conversations. For example, if a user has ongoing projects or preferences, they must repeatedly provide the same context every time a new session is started.
Having global memory would address this by storing critical data across interactions, enhancing the model's ability to provide relevant responses and improve personalization. The user could also have control over what data is stored and accessed, ensuring privacy and transparency.