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LuizEduPP/rememb

v0.4.13 Breaking

This release includes 3 breaking changes for platform teams planning a safe upgrade.

Published 1mo AI Agents & Assistants
✓ No known CVEs patched
Read the diff → Tool health → What is this tool? →

✓ No known CVEs patched in this version

Topics

agent-memory ai-agents ai-memories ai-memory cherry-studio claude
+14 more
clawdbot context-persistence copilot cursor fastapi llm llm-memory mcp mcp-server memory model-context-protocol moltbot persistent-memory windsurf

Affected surfaces

deps breaking_upgrade

Summary

AI summary

Removed sentence-transformers, numpy, embedding model code, /api/models, fetch-model CLI, semantic config keys, and dead cache files.

Full changelog

Removed

  • sentence-transformers and numpy dependencies; embedding model code, /api/models, fetch-model CLI, and semantic config keys.
  • Dead embedding cache files (embeddings.npy, embeddings.hash) from store init, gitignore, and storage listings.
  • semantic_scope from write/consolidate APIs and MCP handlers; consolidate is section-scoped exact duplicate cleanup only.

Changed

  • Install and CI are much lighter without PyTorch or embedding model downloads; search remains keyword/token matching with agent-side relevance.
  • GitHub Actions uses uv with dependency caching, Python 3.12 only on PRs, path filters to skip docs-only runs, and Buildx cache for Docker smoke tests.
  • Documentation aligned with keyword-only runtime: README, COMPATIBILITY, SECURITY, and CONTRIBUTING.

Breaking Changes

  • Removed `sentence-transformers` and `numpy` dependencies along with embedding model code, `/api/models`, `fetch-model` CLI, and all semantic config keys.
  • Removed `semantic_scope` from write/consolidate APIs and MCP handlers; consolidate now performs only section-scoped exact duplicate cleanup.
  • Dropped dead embedding cache files (`embeddings.npy`, `embeddings.hash`) from store initialization, gitignore entries, and storage listings.
View diff on GitHub

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About LuizEduPP/rememb

Persistent memory for AI agents with sectioned entries (project/user/context/etc), semantic search, CLI, and per-project scope. Local JSON, zero config, no server required.

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Related context

Beta — feedback welcome: [email protected]