Agentes de IA
osaurus
Osaurus — own your AI: a native macOS agent harness with any model, memory and fully offline execution.
★ 8,0k estrellasMIT
Ver la guía →harness-sdk es un proyecto de agentes de IA de código abierto de strands-agents (strands-agents/harness-sdk en GitHub). Tiene 8.732 estrellas en GitHub y 1.338 bifurcaciones, se publica bajo la licencia Apache-2.0 y se actualizó por última vez en GitHub el 7 de octubre de 2026.
An open-source SDK for production agents on any model, any cloud.
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.
Own the whole harness, not just the model call.
Both major agent stacks covered.
Any model provider plugs in.
No lock-in to one platform.
Built for real deployments.
Open and commercially friendly.
Download the source and move into the project folder.
git clone https://github.com/strands-agents/harness-sdk.git
cd harness-sdkCreate a virtual environment and install the requirements.
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txtTreat these as starting points - the README documents the exact commands.
python examples/quickstart.pyThe project lives at strands-agents/harness-sdk and has attracted 1338 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.
Frameworks bundle opinions about loops and tools; this SDK gives you harness structure with freedom on the rest. Choose it when you want control without starting from zero.
The README and the official docs site are the fastest path: run the quickstart example first, then adapt it to your use case.
Osaurus — own your AI: a native macOS agent harness with any model, memory and fully offline execution.
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