CLI reference

The gseai command-line tool lets you interact with the server without writing any Python.

Authentication

Every command requires a bearer token. Set it once as an environment variable so you don’t have to type it on every call:

export GSEAI_API_TOKEN=your-api-token

You can also pass it inline with -t / --token.

Global options

These options apply to every command and must come before the subcommand.

gseai [OPTIONS] COMMAND [ARGS]...

Flag	Env var	Description
-t, --token	GSEAI_API_TOKEN	Bearer auth token (required)
-H, --host	GSEAI_HOST	Server hostname (default: gseai.gse.buffalo.edu)
-p, --port	GSEAI_PORT	Server port (default: 11434)
-T, --timeout	GSEAI_TIMEOUT	Request timeout in seconds (default: no timeout)

Models

gseai models          # one model ID per line
gseai models -j       # raw JSON

Chat

Single-turn chat with a plain-text prompt:

gseai chat gemma-4-e2b-it "What is machine learning?"

# Read the prompt from a file
gseai chat gemma-4-e2b-it -f prompt.txt

# Interactive session (multi-turn, retains conversation history)
gseai chat gemma-4-e2b-it -i

# Interactive with a system prompt and streaming
gseai chat gemma-4-e2b-it -i -s "You are a concise tutor." -S

Type exit or press Ctrl+C to end an interactive session.

Flag	Description
-f, --file	Read the prompt from a file
-i, --interactive	Start a multi-turn chat session, retaining conversation history
-s, --system	System prompt
-t, --temperature	Sampling temperature (0–2)
-m, --max-tokens	Maximum tokens to generate per turn
-S, --stream	Stream tokens as they arrive
-j, --json	Print full JSON response (single-turn only)

Completions

Legacy text completion (no chat structure):

gseai completions gemma-4-e2b-it "Once upon a time"

Accepts the same -t, -m, -S, -j flags as chat.

Embeddings

gseai embeddings nomic-embed-text "Hello world"
# model:      nomic-embed-text
# dimensions: 768
# values:     [0.0142, -0.0317, ...]

gseai embeddings nomic-embed-text "Hello world" -j   # full JSON

Audio

transcribe

Transcribe an audio file to text using Whisper:

gseai audio transcribe whisper recording.mp3
gseai audio transcribe whisper lecture.mp3 -l fr   # French source
gseai audio transcribe whisper lecture.mp3 -f srt  # SRT subtitles

Flag	Description
-l, --language	Source language code (e.g. en, fr); auto-detected if omitted
-p, --prompt	Context hint passed to the model
-f, --format	Response format: text (default), json, verbose_json, srt, vtt
-j, --json	Print full JSON (equivalent to --format verbose_json)

translate

Transcribe and translate to English in one step:

gseai audio translate whisper french_lecture.mp3

Accepts the same -p, -f, -j flags as transcribe.

speech

Synthesize speech from text (requires a TTS model):

gseai audio speech tts-model "Hello, world" -o hello.mp3

Flag	Description
-o, --output	Output file path (default: speech.mp3)
-v, --voice	Voice identifier
-s, --speed	Playback speed (default: 1.0)

Images

generate

Generate an image from a text prompt:

gseai images generate stable-diffusion "a red barn in a snowy field"
gseai images generate stable-diffusion "a red barn" -o barn.png -n 3

When --n is greater than 1 the output filenames are numbered: barn_1.png, barn_2.png, etc.

Flag	Description
-o, --output	Output file path (default: image.png)
-n, --n	Number of images to generate (default: 1)
-s, --size	Image dimensions, e.g. 512x512
-S, --steps	Diffusion steps
-r, --seed	Random seed for reproducibility
-j, --json	Print raw JSON response

edit

Edit an existing image guided by a text prompt:

gseai images edit stable-diffusion photo.png "replace the sky with a sunset"
gseai images edit stable-diffusion photo.png "repaint the sky" -m mask.png

Flag	Description
-m, --mask	Greyscale mask image (white = area to edit)
-o, --output	Output file path (default: edited.png)
-n, --n	Number of variants
-s, --size	Output dimensions
-j, --json	Print raw JSON response

variation

Generate variations of an existing image:

gseai images variation stable-diffusion photo.png -n 3

Flag	Description
-o, --output	Output file path (default: variation.png)
-n, --n	Number of variations (default: 1)
-s, --size	Output dimensions
-j, --json	Print raw JSON response