CLI

The sference command-line tool is published on PyPI as sference-cli. It wraps the same inference API as the Python SDK: auth, batches, streams, and responses.

Install (one line)

macOS and Linux:

curl -fsSL https://raw.githubusercontent.com/s-ference/sference/main/install.sh | sh

That script installs sference on your PATH (via uv tool when available).

Other install options

uv tool install sference-cli

pip install sference-cli
# or
pipx install sference-cli

Then verify:

sference --help

Authenticate

Create an API key in the sference console, then:

export SFERENCE_API_KEY='sk_...'
sference auth login --api-key "$SFERENCE_API_KEY"
sference auth me --json

SFERENCE_API_KEY overrides the saved credential file for every subcommand.

Batch JSONL

Each line in a batch input file becomes one row in POST /v1/batches. All rows must use the same model: either repeat body.model on every OpenAI-style line or set --model once for content-only lines. The model must be catalog-available; invalid or mixed models return 400 at create.

Inner body accepts chat completions (messages) or Responses (input). Responses fields are normalized at create; invalid rows return 400 with row index / custom_id.

{"custom_id":"a","method":"POST","url":"/v1/chat/completions","body":{"model":"…","messages":[{"role":"user","content":"hi"}]}}
{"custom_id":"b","method":"POST","url":"/v1/responses","body":{"model":"…","input":[{"role":"user","content":"hi"}]}}
{"content":"content-only, pass --model on submit"}

Full guide: Batch inference. Subcommand reference: OSS CLI README.

Go deeper

Subcommands, JSONL batch formats, and stream workflows live in the sference OSS repository (cli/README.md).