Skyportal SRE – an open-source AI infrastructure engineer

Skyportal released an open-source Python SDK and persistent terminal client for its AI infrastructure platform, enabling developers to interact with the SkyPortal API for tasks such as monitoring training nodes and managing server-side agents. The SDK, available under an alpha release, includes features like chat-based agent interaction, approval workflows, and observability endpoints, with support for self-hosted deployments.

The official Python SDK and persistent terminal client for the SkyPortal https://skyportal.ai API. Project status:Alpha. APIs may evolve before 1.0; changes are documented in GitHub releases. User app → skyportalai SDK → SkyPortal HTTP API pip install skyportalai or poetry add skyportalai Requires Python 3.11+. The local observability agent has one additional dependency set: pip install "skyportalai agent " python from skyportalai import Skyportal client = Skyportal api key="sk-..." or set SKYPORTAL API KEY user = client.me print user.name Skyportal can be used as a context manager when the SDK owns the HTTP session: with Skyportal api key="sk-..." as client: print client.me .name client.chat wraps the headless agent API: create a chat, poll it, resolve approvals, and read the run's messages — the agent itself runs server-side. chat = client.chat.create chat "check disk usage on the training node", server id=12 Poll until the agent settles; approve any command it asks to run. status = chat.wait on approval=lambda a: True True approves, False rejects print status.status "idle" for m in chat.messages .messages: print f"{m.role}: {m.content}" Without an on approval callback, wait returns as soon as the agent needs a decision, and you resolve it yourself: status = chat.wait if status.status == "awaiting approval": for approval in status.pending approvals: print "agent wants to run:", approval.command chat.approve approval.approval id, command=approval.command status = chat.wait Follow-ups go through chat.send "..." ; chat.cancel stops an active run. Read-only introspection mirrors the observability endpoints: chat.events , chat.tool calls , chat.reasoning , chat.plans , chat.evaluations , chat.environment . wait raises WaitTimeoutError if the agent is still busy past timeout default 300s . | Argument | Env var | Default | Notes | |---|---|---|---| api key | SKYPORTAL API KEY | — | required; sent as Authorization: Bearer <key | base url | SKYPORTAL BASE URL | https://app.skyportal.ai | API root; trailing slash optional | timeout | — | 30.0 | per-request seconds | max retries | — | 2 | retries for GET on network error / 5xx | client = Skyportal api key="sk-...", base url="http://localhost:8000", timeout=10 Remote targets must use HTTPS because every request carries a Bearer key. Plain HTTP is accepted for loopback development only. Valid self-hosted HTTPS deployments are fully supported. Every failure is a skyportalai exception — a raw requests error never escapes: python from skyportalai import Skyportal, AuthenticationError, APIConnectionError, APIError try: Skyportal api key="bad" .me except AuthenticationError: ... 401/403, or the key was rejected except APIConnectionError: ... network failure / timeout except APIError as e: ... other non-2xx; e.status code, e.body Hierarchy: SkyportalError ▸ APIConnectionError , APIStatusError ▸ AuthenticationError , APIError . The package installs two complementary commands: skyportal is the interactive command center, with login, server selection, persistent chat state, and approval prompts. skyportalai is the script-friendly Typer CLI, with stable --json output for chat and configuration operations. skyportal start the interactive command center skyportal start same as above skyportal login browser-guided API-key setup skyportal login --token paste an existing credential skyportal ask "List my hosts" skyportal ask --server 42 "Show disk usage" skyportal servers skyportal logout skyportal configure --portal-url https://your-skyportal.example For a self-installing local launcher, clone the repository and run ./run.sh . It provisions a virtual environment, installs this package, displays the animated Skyportal astronaut, and opens the command center. At the interactive prompt, /login opens the API-key page and guides you through connecting the terminal. Credentials are validated before being stored in ~/.skyportal/credentials.json with user-only permissions. Interactive commands: /help Show commands /login Open API-key setup and connect /token Reopen API-key setup and paste a credential /logout Remove the saved credential /status Show API, chat, and server context /new Start a new agent chat /servers List owned servers /server <id Select a server for agent execution /server auto Let the agent choose a server /clear Clear the terminal /exit Exit CLI configuration is stored in ~/.skyportal/config.yaml . Environment overrides include SKYPORTAL URL , SKYPORTAL ACCESS TOKEN , SKYPORTAL CONFIG PATH , SKYPORTAL CREDENTIALS PATH , SKYPORTAL HISTORY PATH , SKYPORTAL NO ANIMATION , and SKYPORTAL ANIMATION SPEED . See CLI architecture /SkyportalAi/skyportalai/blob/main/docs/architecture.md and CLI deployment /SkyportalAi/skyportalai/blob/main/docs/deployment.md for more detail. skyportalai config show skyportalai chat send --server 42 --wait "Show disk usage" skyportalai chat status 123 skyportalai --json chat messages 123 Run skyportalai --help or skyportalai chat --help for the full command reference. It uses SKYPORTAL API KEY first and can also read credentials saved by skyportal login . skyportal-agent discovers W&B and MLflow experiment metadata, buffers it in a disk-backed queue, and uploads it with bounded retries. Its config/tag redaction removes credential-like values before persistence, but operators must still restrict scan roots and protect the state directory. See observability agent deployment and data handling /SkyportalAi/skyportalai/blob/main/docs/agent.md before running it on experiment volumes. poetry install --all-extras poetry run pytest poetry run ruff check . poetry check --strict Issues and pull requests are welcome. See CONTRIBUTING.md /SkyportalAi/skyportalai/blob/main/CONTRIBUTING.md for development setup, tests, and the pull request process, and CODE OF CONDUCT.md /SkyportalAi/skyportalai/blob/main/CODE OF CONDUCT.md for community expectations. Supported Python versions are 3.11, 3.12, and 3.13. Do not open a public issue for a vulnerability. Follow the private reporting instructions in SECURITY.md /SkyportalAi/skyportalai/blob/main/SECURITY.md . Released under the MIT License /SkyportalAi/skyportalai/blob/main/LICENSE .