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@Tyan66666 Tyan66666 released this 13 Aug 16:44
· 45 commits to main since this release
v0.1.0
649d9f6

Model-driven context management (Active Context Pruning / ACP) for the DeepSeek Harness — the model decides when and what to compress.

What it is

A drop-in CompactionEngine backend ported from billion-context-pi: the compress tool durably replaces a surface range with the model-written summary, with decompress / search_context / acp_status tools, a /acp command, and pressure-driven advisory nudges. The compression core (acp-kernel) is reused verbatim.

Install

npm install billion-context-dsh

Then add one composition row (name: 'billion-context-dsh') — see README.

Highlights

  • Model-driven: automatic policy never summarizes, only nudges (advisory, never imperative)
  • Durable surface transaction: originals stay in the append-only session log, decompress/search work from the log
  • Seq-based refs with auto-balanced range edges and `#callId` tolerance
  • Configurable nudge thresholds (defaults match billion-context-pi / acp-kernel)
  • 25 tests, strict TS, self-contained 35KB bundle (acp-kernel inlined)

Upstream

MIT — built on billion-context-pi, acp-kernel, and opencode-acp by ranxianglei; host platform DeepSeek Harness by DeepSeek AI.

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