looking for contributors – trie based memory efficient LLM runner

SALT shrinks a long document down to a fixed size before it is sent to a language model, keeping the sentences that carry the most information. It works with any model, produces a shorter plain-text prompt, and cuts the compute, memory, and wait time that long inputs cost. saltChat keeps the theme trie in DRAM across turns, so a document is indexed once and reused for the whole conversation instead of being re-read every message.