AIエージェント
honcho
Honcho — Plastic Labs' memory library for stateful agents that learn about their users over time.
★ 7.5k スターAGPL-3.0
ガイドを見る →hindsightは、vectorize-io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: vectorize-io/hindsight）。GitHubスターは47,008、フォークは5,967で、MIT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10月7日です。
Agent memory that learns — so your agents get smarter over time.
Decide what you want the project to do before installing anything.
Grab the source and skim the README for setup requirements.
Install dependencies and add any API keys or settings it needs.
Launch it and follow the example workflow from the docs.
Recall that improves instead of just accumulating.
Agents remember across sessions.
Drop it into Python agent stacks.
Designed to slot into existing agent builds.
From the team behind vectorize-io tooling.
Free for commercial use.
Download the source and move into the project folder.
git clone https://github.com/vectorize-io/hindsight.git
cd hindsightIsolate dependencies, then install requirements.
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txtLaunch using the entry point shown in the README.
python -m hindsight # check README for the exact commandIt is an open-source project at vectorize-io/hindsight with 5967 forks. Check the contributors tab and recent commits to judge how active maintenance is.
Yes — it's MIT licensed: free to use, modify, and ship commercially. Just keep the license notice in copies.
It persists interaction history and refines recall over time — the docs at hindsight.vectorize.io cover the architecture.
It's a memory layer, not just storage: retrieval plus learning. You may still use a vector DB underneath.
Clone the repo and follow the README quickstart — the docs at https://hindsight.vectorize.io/ walk through setup.
Honcho — Plastic Labs' memory library for stateful agents that learn about their users over time.
Gini: a personal agent runtime that remembers, learns skills, and reaches you with the right control in time.
Real-time knowledge graphs that give agents a memory with structure.
Stateful AI agents with memory that learns and improves.
Agent-native memory infrastructure - structured, persistent memory for production agents
Real-time voice runtime that keeps AI agents talking, working, and present.
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 — hindsight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。
A personal AI that really does things — on any OS, with your data staying yours.
An agentic skills framework & software development methodology that works.
Agent harness optimization system with skills, memory and security for Claude Code, Codex and more
The agent that grows with you — a Python framework for adaptive AI agents.
DeepSeek's plugin-based agent harness where everything is a plugin.
カタログの中でhindsight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。
Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat…
An open-source, privacy-first, self-hosted knowledge workspace where humans and AI agents work together 开源、隐私优先、自托管的知识工作空间，让人与智能体在此协作
LocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required.
The cloud-native vector database for planet-scale similarity search.
Make humans and AI agents work as one team — open-source and self-hostable.
High-performance code intelligence MCP server: your codebase as a persistent knowledge graph