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falling-ts102Updated 18d ago
Aggressive context compaction for local-first agents. Runs Qwen3.8‑27B on self‑hosted llama.cpp at low context, shrinking history so the live prompt stays small, fast, and private—delivering a big‑window experience without API cost or data egress. 面向本地的激进上下文压缩插件。自托管 llama.cpp 低上下文运行 Qwen3.8‑27B,不断收缩历史、保持常驻 prompt 小而快,兼顾隐私与大窗口体验,零 API 成本、数据不出本机。
Practical score
82 / 100
Setup
Ready to use
License
MIT
Language
JavaScript
Copy the command, or hand the whole task to your harness agent.
git clone https://github.com/falling-ts/dsh-force-compact.gitPlease install the DeepSeek Harness plugin "dsh-force-compact" for me. - GitHub repository: falling-ts/dsh-force-compact (https://github.com/falling-ts/dsh-force-compact) - Type: a Cordis plugin (installed into a DSH profile) - The plugin declares a DSH versio…
A cleaned excerpt from the project's own documentation.
dsh-force-compact Aggressive, local-first context compaction for DeepSeek Harness agents. A DSH Cordis function plugin that keeps the agent's working context lean by design: serve Qwen3.8‑27B on a self-hosted llama.cpp with a modest context, and the plugin shrinks the conversation itself — a large-window feel with no API cost and no data egress. 中文 --- Why - Self-hosted inference — the agent talks to a local OpenAI-compatible llama.cpp server through the standard DeepSeek adapter; no separate adapter needed. - Low context, high signal — instead of fighting a small cap, the plugin shrinks the conversation, so the agent reasons over a tight prompt while keeping deep memory in the compressed head. - Think off for compactions, passthrough everywhere else — disableThinking: true (default) turns thinking off on this plugin's own compaction summarization call only ; every other model request rides the machine's configuration unchanged. - Private & free — no per-token billing, no egress. --- What it does Two compaction engines coexist behind one facade ( resolveCompaction ), transparent to callers:…
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