ramalama

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RamaLama is an open-source developer tool that simplifies the local serving of AI models from any source and facilitates their use for inference in production, all through the familiar language of con

GitHub Website

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3.0k stars348 forksLast push today Python MIT

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Maintenance and security

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Maintenance: Very active (0d since push); As of today
Provenance: Not a fork · Organization account; As of today
Security (OSV): No lockfile; As of today

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Install

pip install ramalama

PyPI

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

Capability facts

CLI: CLI entrypoint
Source: pyproject.toml:[project.scripts] · Jul 15, 2026
Languages: python
Source: github.language+pyproject.toml · Jul 15, 2026

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Jul 15, 2026)

Download the self-contained macOS installer that includes Python and all dependencies:

Source link

README

Install on macOS (Self-Contained Installer)

Download the self-contained macOS installer that includes Python and all dependencies:

Download the latest .pkg installer from Releases
Double-click to install, or run: sudo installer -pkg RamaLama-*-macOS-Installer.pkg -target /

See macOS Installation Guide for detailed instructions.

Install on Fedora

RamaLama is available in Fedora and later. To install it, run:

sudo dnf install ramalama

Install via PyPI

RamaLama is available via PyPI at https://pypi.org/project/ramalama

pip install ramalama

Install script (Linux and macOS)

Install RamaLama by running:

curl -fsSL https://ramalama.ai/install.sh | bash

Install on Windows

RamaLama supports Windows with Docker Desktop or Podman Desktop:

pip install ramalama

Requirements:

Python 3.9 or later
Docker Desktop or Podman Desktop with WSL2 backend
For GPU support, see NVIDIA GPU Setup for WSL2

Note: Windows support requires running containers via Docker/Podman. The model store uses hardlinks (no admin required) or falls back to file copies if hardlinks are unavailable.

Hardware Support

Hardware	Enabled
CPU	✓
Apple Silicon GPU (Linux / Asahi)	✓
Apple Silicon GPU (macOS)	✓ llama.cpp or MLX
Apple Silicon GPU (podman-machine)	✓
Nvidia GPU (cuda)	✓ See note below
AMD GPU (rocm, vulkan)	✓
Ascend NPU (Linux)	✓
Intel ARC GPUs (Linux)	✓ See note below
Intel GPUs (vulkan / Linux)	✓
Moore Threads GPU (musa / Linux)	✓ See note below
Windows (with Docker/Podman)	✓ Requires WSL2

For agents

This page has a .md twin and JSON over the API.

/tools/containers-ramalama.md GET /api/graphcanon/tools/containers-ramalama GET /api/graphcanon/graph?tool=containers-ramalama