MosaicMemoryCompress

A generic, pluggable stateless dialogue compression algorithm — works with any LLM agent framework, and ships a ready-to-use adapter module for DeepSeek Harness (DSH).

LLM conversations grow linearly. MosaicMemoryCompress keeps them bounded — automatically, invisibly, and without the user ever knowing what a "Session" is.

How It Works

Your message array (R rounds, oldest → newest):

Round 1 ────→ Round (R-30)   │ Heavy zone → ALL → 2 msgs
Round (R-29) → Round (R-10)  │ Light zone → structural truncation, count unchanged
Round (R-9) ────→ Round R    │ Raw zone  → keep as-is

Steady state: constant message count — 2 + heavyStart × (messages per round), e.g. 62 messages (31 user rounds) for pure two-message rounds, whether at round 60 or round 15,000 (higher, but still constant, when tool-call rounds add messages). The compression ratio approaches 100%.

Philosophy: Alive Memory, Not a Handover Brief

The industry-standard answer to unbounded conversations is threshold summarization: when the window fills up, summarize everything into one brief and hand it to a fresh model. The conversation looks like it continues. But structurally it is amnesia followed by reading a diary:

• A switch moment. Memory breaks, then is rebuilt from a single summary call.
• Indiscriminate loss. The freshest instructions are paraphrased too — the exact part that must stay vivid. In a controlled A/B experiment the brief paraphrased the user's latest instruction and silently dropped an action item ("write the key points into MEMORY").
• Invisible loss. The next model cannot know what the brief omitted, so it cannot compensate.

MosaicMemoryCompress models the opposite: biological forgetting. A human does not remember round 3 of a 300-round conversation — they keep the lesson, the rules, the relationship. The algorithm reproduces that curve inside one message array:

recent 30 rounds   → verbatim (vivid — what you are actually working on)
rounds 30–50       → structural truncation (reasoning/args/results trimmed, text kept)
rounds 50+         → one heavy pair: identity, environment, permissions, rules

No switch moment, no reset, no length limit. The heavy zone is semantic memory (rules that must never be forgotten); the middle is recent episodic memory; the raw zone is the vivid present. Loss is visible: the zone structure tells the model what it no longer knows, so it can fetch detail from shadowed storage on demand.

	Threshold summarization (industry)	MosaicMemoryCompress
Metaphor	amnesia + diary	continuous vivid memory
Continuity	resets on every compaction	never resets
Loss	indiscriminate, invisible	graduated, visible
Recent turns	paraphrased at the worst moment	always verbatim
Purpose	portable handover brief	unbounded human–AI dialogue

The two philosophies complement each other: a handover brief serves cold starts and long pauses; MosaicMemoryCompress serves staying in the conversation. Combined with a durable host-side store (e.g. a MEMORY.md file), human and AI keep talking under the same forgetting curve indefinitely. See docs/design.md §8/§10 for the formal position-is-age model behind this design.

Quick Start

npm install mosaic-memory-compress

import { mosaicMemoryCompress, type MosaicMemoryConfig } from 'mosaic-memory-compress';

…