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inecore/AMK

Agent Memory Kit System: Capture every correction and interaction to build your own SLM from day one

Python MIT GitHub ↗
★ 1
stars
70
AI関連スコア
20
個人開発度
0
AIツール痕跡

SUMMARY AI要約 by gpt-5-mini

AMK (Agent Memory Kit) is an open-source toolkit (EVOMEM engine) that gives AI coding assistants persistent, project-level memory to prevent IDE context regression. It captures agent prompts/responses, code changes, and outcomes, then uses deterministic dependency analysis to detect and warn about regressions before they break other modules. Who uses it: developers, small teams, and organizations integrating LLMs/SLMs into IDEs that need domain-specific memory, privacy, and lower inference cost. Key features: 3-layer architecture (Interaction Memory, Code Evolution Memory, Regression Intelligence); LLM/SLM-agnostic pipeline that produces a verified "Golden Dataset" for training private SLMs; environment isolation for safe self-evolution; privacy/edge deployment and a Python package (pip install evomem).

GitHub Topics

#adk #agent-memory #agentic-workflows #ai-tools #dataset #developer-tools #evolutionary-learning #fine-tuning #green-ai #green-computing #llm #local-ai #machine-learning #python #rag #sdd #slm #sustainability #tdd #context-regression

使用言語(バイト数比)

Shell
4.4%
Python
95.6%

オーナー情報

アカウント
inecore
タイプ
Organization
フォロワー
0

日付

GitHub作成日 2026-05-08
最終Push 2026-05-09
当サイト初検出 2026-05-09
最終取得 2026-05-09 18:14

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