AIエージェント
zep
Examples and integrations for Zep — the memory layer for AI agents.
★ 5.0k スターApache-2.0
ガイドを見る →memvidは、memvidが公開しているオープンソースのAIエージェントプロジェクトです（GitHub: memvid/memvid）。GitHubスターは16,584、フォークは1,421で、Apache-2.0ライセンスの下で公開されています。GitHubでの最終更新は2026年7月14日です。
A serverless, single-file memory layer for AI agents - replace complex RAG pipelines
Use the Rust core directly, or the Python, Node or CLI packages.
Add memvid-core to a Rust project, or install the SDK for your language.
Create a .mv2 file and put your first documents into it with metadata.
Run a semantic search and hand the results to your agent as context.
Your whole knowledge base lives in one portable .mv2 file - no server to deploy or manage.
Combines vector similarity search (HNSW with local ONNX embeddings) and BM25 full-text search.
Feature flags add PDF text extraction and repair, CLIP image search and Whisper audio transcription.
Natural-language date parsing understands expressions like 'last Tuesday' in searches.
Optional password-based encryption produces .mv2e memory files.
Rust core with Python, Node.js and CLI packages sharing the same format.
Get the source code from GitHub and enter the project directory.
git clone https://github.com/memvid/memvid.git
cd memvidAdd memvid-core to your Cargo project (feature flags enable lex, vec and more).
cargo add memvid-coreInstall the Python SDK and create your first memory file per the docs.
pip install memvid-sdkIt is maintained by the Memvid project (memvid) on GitHub.
Yes - Memvid is Apache-2.0 licensed and free to use.
No key is required for local embeddings and search; an optional api_embed feature can use cloud embeddings (for example OpenAI) if you choose it.
Compared with a hosted vector database, Memvid is an embedded single file - zero operations and offline-first - in exchange for single-node scale.
Run cargo add memvid-core (or pip install memvid-sdk), create a .mv2 file, put a document in, and search it.
Examples and integrations for Zep — the memory layer for AI agents.
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LibreAIカタログに掲載されたAIエージェントプロジェクトの中で最もスターの多いもの — memvidが合わなかった場合に検討したい、現実的な候補リストです。
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カタログの中でmemvidとスター数が近いAIエージェントプロジェクト — 前後の棚もそのまま見て回れます。
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