SALT uses a trie to compress long-context prompts and cut LLM runtime costs
No_Sky9786 · reddit · 2026-07-21
A project called SALT proposes a trie-based, memory-efficient runner for long-context LLM workloads. - SALT compresses a long document to a fixed-size prompt before sending it to a model, keeping the most informative sentences. - It works with any model and produces a shorter plain-text prompt, reducing compute, memory, and waiting time for long inputs. - saltChat keeps the theme trie in DRAM across turns, so a document is indexed once and reused instead of being re-read on every message. - The project is looking for contributors.
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