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Compatibility & Support

What ARI runs on. For the policy around versions (SemVer, support windows, deprecation), see Release & versioning policy.

Python

Version
Hard requirementPython ≥ 3.9 (requires-python in ari-core/pyproject.toml)
Recommended3.10+ (the Quickstart targets 3.10 or later)

setup.sh checks the interpreter and installs the rest. Run it as your normal user — never with sudo.

Operating systems

OSStatus
LinuxSupported
macOSSupported
WindowsVia WSL2

Memory backend (Letta)

ARI's memory is backed by Letta (formerly MemGPT) since v0.6.0. setup.sh bootstraps it, auto-detecting the best deployment: Docker → Singularity/Apptainer → pip (skip with SKIP_LETTA_SETUP=1).

The live behaviour is verified against Letta 0.16.7 (see the implementation note in Memory architecture). Check a running backend with ari memory health. Each checkpoint also carries a memory_backup.jsonl.gz snapshot, so a run stays portable even across Letta versions.

LLM backends

Model routing goes through LiteLLM, so any OpenAI-compatible provider works. Select with ARI_BACKEND / ARI_MODEL (always use the provider prefix, e.g. openai/gpt-4o).

BackendARI_BACKENDNotes
OllamaollamaLocal, free, no API key (default for getting started)
OpenAIopenaiCloud, paid; OPENAI_API_KEY
AnthropicclaudeCloud, paid; ANTHROPIC_API_KEY
Any OpenAI-compatible(custom)Routed via LiteLLM

Per-phase model overrides are available (e.g. a cheaper model for idea generation, a stronger one for paper writing) — see Configuration and Environment variables.

Skills vs core

Skills are versioned independently of ari-core. A skill at 0.7.x works with any ari-core 0.7.y (compatibility within a minor); across minors, expect a coordinated release. See Release policy → Compatibility windows.


See also: Release policy · About · Quickstart · Environment variables