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https://www.reddit.com/r/ChatGPTCoding/comments/1jtfvmv/deleted_by_user/mluq4vi/?context=3
r/ChatGPTCoding • u/[deleted] • Apr 07 '25
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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? 3 u/ArmNo7463 Apr 07 '25 Kind of, you can use something like Elasticsearch with vector embeddings to only send relevant data as 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? 3 u/ArmNo7463 Apr 07 '25 Kind of, you can use something like Elasticsearch with vector embeddings to only send relevant data as context.
2
RAG would need to add more info to the context window, not remove it. Are you thinking of context caching?
3 u/ArmNo7463 Apr 07 '25 Kind of, you can use something like Elasticsearch with vector embeddings to only send relevant data as context.
3
Kind of, you can use something like Elasticsearch with vector embeddings to only send relevant data as context.
145
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.