SonicBotMan

SonicBotMan / lobster-press

Public

🦞 龙虾饼 - 智能上下文压缩系统，让 AI 记忆永不溢出

github.comSonicBotManlobster-press ai bash chatgpt claude context-compression
20
2
89% credibility
Found Mar 10, 2026 at 17 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

LobsterPress intelligently compresses lengthy AI conversation histories to prevent memory overflow, reduce token costs, and preserve essential information like decisions and preferences.

How It Works

1
😩 Chats Grow Too Long

Your helpful AI conversations pile up, filling memory and raising costs, making it forget important details.

2
🦞 Find LobsterPress

You discover LobsterPress, a smart helper that squeezes long chats down while keeping the good stuff.

3
💻 Set It Up

Download the handy tools to your computer and place them where they can run easily.

4
🔗 Link Your AI

Connect it to your AI service so it understands your chats and works smoothly.

5
▶️ Start Auto-Magic

Turn on the watchers that automatically check and slim down your chats when needed.

6
✨ It Works in Background

As you chat, it quietly learns your style, predicts needs, and keeps everything fresh and light.

✅ Save Money, Keep Smarts

Your AI remembers key decisions without overflow, costs drop 30-50%, and chats feel personalized forever.

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Star Growth

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AI-Generated Review

What is lobster-press?

LobsterPress is a Python and Bash toolkit that compresses bloated AI conversation histories to dodge token limits, distilling long chats into summaries that retain decisions, configs, and preferences—like a lobster press turning meaty lobster into a slim cake. It tackles "memory death" in tools like ChatGPT, Claude, or OpenClaw by scoring messages for importance, applying light/medium/heavy strategies, and auto-applying via systemd timers on Linux. Users get scripts like `context-compressor-v5.sh scan` for hands-off management, plus adaptive learning that tunes to your habits.

Why is it gaining traction?

It beats basic truncation by intelligently prioritizing content (e.g., errors over chit-chat) and learning from your sessions, often saving 20-50% tokens without losing context—far smarter than manual edits or crude pressure washers on lobster-sized logs. The zero-API local mode keeps costs at $0, with predictive compression and OpenClaw coordination avoiding duplicates. Devs dig the kitchen-tool metaphor and easy deploy: clone, install jq/curl, enable timers, done.

Who should use this?

AI-heavy devs maintaining long OpenClaw sessions or chatbots hitting 128k limits; enterprise teams scaling GLM/Qwen APIs to cut bills; Linux power users scripting agents who hate re-explaining project history after overflows.

Verdict

Grab it if you're on Linux with AI agents—solid docs, MIT license, and systemd hooks make it plug-and-play despite 16 stars and 0.9% credibility score signaling early days. Test on a session; it'll mature fast for lobster press publishing workflows.

(198 words)

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