AIエージェント
Haystack
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and…
★ 26.6k スターApache-2.0
ガイドを見る →Hyphaは、CodeSoul-co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: CodeSoul-co/Hypha）。GitHubスターは447、フォークは126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9月4日です。
A harness-oriented framework for production-grade agent applications.
Write down the task or workflow you want the agent to handle.
Clone the repository and read the README's prerequisites.
Install dependencies and configure keys or endpoints.
Run the sample script and check the output against the docs.
The agent loop is the core abstraction.
Caching, evals, and memory included.
Agent activity as a replayable log.
Built-in execution environment.
Modern typed stack.
Open and commercially friendly.
Download the source and move into the project folder.
git clone https://github.com/CodeSoul-co/Hypha.git
cd HyphaPull in the Node packages the project needs.
npm installTreat these as starting points - the README documents the exact commands.
npm run buildThe project lives at CodeSoul-co/Hypha and has attracted 126 forks. Browse its commit history and contributor list for a sense of maintenance pace.
Yes - it is Apache-2.0 licensed, so it is free for commercial use with attribution.
The framework itself is free - but you will need a model to drive it, which usually means your own API key or a local model.
Both are harness-centric, but Hypha is a fuller framework with memory, caching, and evals built in, while Strands' SDK is a lighter harness structure. Pick Hypha for batteries-included, Strands for flexibility.
The README and the official docs site are the fastest path: run the quickstart example first, then adapt it to your use case.
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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 — Hypha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Hypha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。
Snowflake's Agent World Model: synthesise 1,000 executable MCP tool-use environments for agentic RL.
The tougher, more robust successor to the MMLU benchmark.
Guardrails for building secure, robust agents.
Safety testing for agents, right in pytest.
Detect prompt injections and jailbreaks before they hit your LLM.
Agentic memory for LLM agents, from a published research project.