# How to install NVIDIA Agent Toolkit?

Source: https://zilliz.com/ai-faq/how-to-install-nvidia-agent-toolkit
Author: zilliz

Installation of NVIDIA Agent Toolkit requires Python 3.11 or 3.12 and the `uv` package manager. Start by cloning the repository: `git clone -b main https://github.com/NVIDIA/NeMo-Agent-Toolkit.git nemo-agent-toolkit`. Navigate to the directory and initialize submodules with `git submodule update --init --recursive`. Download datasets with `git lfs install/fetch/pull` to ensure all training data is available locally.

Create a Python virtual environment using `uv sync --all-groups --all-extras`, which installs the toolkit and all optional framework integrations (LangChain, LlamaIndex, CrewAI, etc.). Verify installation by running `nat --version` to check the version and access help documentation. For framework-specific installations, use extras: `nvidia-nat[langchain]` for LangChain, `nvidia-nat[llamaindex]` for LlamaIndex, etc.

Avoid Conda environments, which can cause component resolution conflicts. Use only vanilla Python virtual environments via `python -m venv` or `uv venv`. The official [NVIDIA NeMo Agent Toolkit documentation](https://docs.nvidia.com/nemo/agent-toolkit/latest/get-started/installation.html) includes platform-specific instructions and troubleshooting. For managed deployments, [Zilliz Cloud](https://zilliz.com/cloud) provides pre-integrated environments where agents are provisioned alongside vector database infrastructure, eliminating manual setup.