智能体与多智能体

NemoClaw:Agent runtime and deployment tooling

NVIDIA/NemoClaw

ToolAI 对 NVIDIA/NemoClaw 的客观项目介绍。Run agents like Hermes, LangChain Deep Agents, and OpenClaw more securely inside NVIDIA OpenShell with managed inference

★ 22.2K星级
⑂ 3KFork 数
303未解决的问题
Python语言
Apache-2.0许可证
Q@project.QualityScore编辑评分

项目截图

NemoClaw:Agent runtime and deployment tooling 的截图 NemoClaw:Agent runtime and deployment tooling 的截图

概览

这是 Agents and multi-agent systems 项目。NVIDIA/NemoClaw is an open-source project in ToolAI's Agents and multi-agent systems category. Run agents like Hermes, LangChain Deep Agents, and OpenClaw more securely inside NVIDIA OpenShell with managed inference The page is intended to help technical readers decide whether the project is worth a closer review; it is not an endorsement. The Python implementation and the repository owner NVIDIA are recorded from the catalog metadata.

主要功能

  • Official repository maintained by NVIDIA; the repository description identifies it as agent runtime and deployment tooling.
  • Primary language recorded for this editorial entry: Python.
  • Repository statistics and links are shown as a dated metadata snapshot, so readers can re-check them before adoption.
  • The official README, releases and issue tracker remain the source of truth for installation and compatibility details.

要求、安装和快速入门

请以官方 README、Release 和许可证文件为准;发布前固定版本并在隔离环境中验证。

Requirements depend on the current official documentation. Start with the repository's README and pin a reviewed release before production use.

git clone https://github.com/NVIDIA/NemoClaw
cd NemoClaw

Use the project's documented environment manager, model weights and optional accelerators. Do not copy commands from an unverified mirror; check the release notes and lock compatible dependencies first.

用法

先运行官方快速开始示例,再根据项目文档配置模型、工具和权限。

This page is an objective orientation for agent runtime and deployment tooling. Read the official quick-start example, run it in an isolated environment, and record the exact commit or release used. For an agent or model workflow, keep tool permissions narrow, validate external inputs, and measure latency and quality on a representative test set. The repository's README and examples should be consulted for API details that may change.

模型兼容性与使用场景

The repository metadata describes the project scope but does not guarantee compatibility with every model, provider, checkpoint or accelerator. Confirm supported model identifiers, tokenizer versions, hardware requirements and license terms in the official documentation before connecting it to an LLM, agent, MCP server or RAG pipeline.

许可证与风险说明

请阅读仓库 LICENSE 及模型、数据集和依赖的独立条款。 GitHub metadata reports the repository license as Apache-2.0. Review the repository LICENSE and any separate model, dataset, weight or third-party dependency terms before redistribution or commercial use. A missing or NOASSERTION license is not a grant of permission.

Editorial verification 2026-08-02: official repository URL, owner, description, license field and repository statistics were reviewed. License metadata: Apache-2.0. Re-check README, releases and dependency/model terms before production use.

发布与维护

Snapshot: 21,931 stars, 2,977 forks and 193 open issues; repository creation is not stated and last pushed date is 2026-07-26 when supplied by the catalog. Check the official releases page for the current version rather than treating these numbers as a guarantee of maintenance or quality.

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