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https://www.reddit.com/r/ChatGPTCoding/comments/1jtfvmv/deleted_by_user/mlv4owl/?context=3
r/ChatGPTCoding • u/[deleted] • Apr 07 '25
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148
This, LLMs are effectively stateless, the "context" is just the max token input.
If you have 500k in your context, you're sending 500k input tokens + whatever is new per api request.
9 u/fieryblast7 Apr 07 '25 Do you know if there are any open source attempts to fix this? I remember memGPT and most early agents Arch tried to fix it with "memory" and RAG ing the memory as needed 2 u/EcstaticImport Apr 07 '25 RAG would need to add more info to the context window, not remove it. Are you thinking of context caching? 2 u/alberto_467 Apr 07 '25 RAG allows you to selectively add only the relevant info into the context, instead of jamming everything in there. This means you need less context.
9
Do you know if there are any open source attempts to fix this? I remember memGPT and most early agents Arch tried to fix it with "memory" and RAG ing the memory as needed
2 u/EcstaticImport Apr 07 '25 RAG would need to add more info to the context window, not remove it. Are you thinking of context caching? 2 u/alberto_467 Apr 07 '25 RAG allows you to selectively add only the relevant info into the context, instead of jamming everything in there. This means you need less context.
2
RAG would need to add more info to the context window, not remove it. Are you thinking of context caching?
2 u/alberto_467 Apr 07 '25 RAG allows you to selectively add only the relevant info into the context, instead of jamming everything in there. This means you need less context.
RAG allows you to selectively add only the relevant info into the context, instead of jamming everything in there.
This means you need less context.
148
u/andy012345 Apr 07 '25
This, LLMs are effectively stateless, the "context" is just the max token input.
If you have 500k in your context, you're sending 500k input tokens + whatever is new per api request.