# agentscope-ai/ReMe

ReMe: Memory Management Kit for Agents - Remember Me, Refine Me.

Repository: https://github.com/agentscope-ai/ReMe
Canonical: https://ross.abutalabs.com/products/reme
Homepage: https://reme.agentscope.io/
Language: Python
License: Apache-2.0
License Family: permissive
Topics: agent, ai-agents, memory, reme, memoryscope, rag, dsh-plugin
Last push: 2026-08-26T11:57:58+00:00

## Health v2 (maintenance only)
Score: 89/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 97, longevity 52
- inputs: {"age_days": 734, "days_push": 7, "days_rel": 20, "gap_med": 1, "n_releases_24m": 58}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3356, forks 290 (observed 2026-08-28T04:07:57.940125+00:00)

## What it is
ReMe is a Python memory management kit for AI agents that stores durable memory as ordinary Markdown files with frontmatter and wikilinks. It turns conversations and resources into a self-evolving, local-first personal knowledge base with BM25 and optional embedding-based retrieval.

## Use cases
- give my ai agent long-term memory
- store agent memories as markdown files
- build a self-evolving knowledge base for agents
- retrieve relevant context from past conversations for an llm
- share a memory workspace across multiple agents
- manage agent memory locally instead of a vector database

## When to choose
- you want agent memory stored as human-readable, editable Markdown files
- you prefer local-first storage with rebuildable indexes over opaque databases
- you need BM25 and wikilink-based retrieval without loading the whole knowledge base
- multiple agents should share and evolve one knowledge workspace

## When to avoid
- you need a fully managed cloud memory service
- you require heavy vector-only semantic search at massive scale
- your stack is not Python 3.11+

## Facets
- artifact type: library
- maturity: active
- function: rag, agent-framework, search-engine, llm-inference
- domain: large-language-models, developer-tools
- platform: python, cli, self-hosted, cross-platform
- tags: agent-memory, markdown-knowledge-base, bm25, memory-management, local-first, wikilinks, ai-agents, retrieval-augmented-generation

## Member repositories
- agentscope-ai/ReMe (main) score 89

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:57.940125+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:40:55.212705+00:00, confidence not recorded.
  - readme: https://github.com/agentscope-ai/ReMe (fetched 2026-08-28T04:07:57.940125+00:00, sha 172f3bc11e86)
  - homepage: https://reme.agentscope.io/ (fetched 2026-08-29T09:33:57.645566+00:00, sha 1bd0eef8afe4)
- Data as of 2026-08-30T08:39:29.467469+00:00.