Google Transport¶

axio-transport-google provides a Gemini transport for both standard completion and realtime (Gemini Live) sessions. It supports the Google GenAI Developer API and Vertex AI.

Install¶

pip install axio-transport-google

For Vertex AI with application-default credentials:

pip install "axio-transport-google[vertexai]"

Quick start¶

Set the API key and create a transport:

export GEMINI_API_KEY="..."

from axio_transport_google import GoogleTransport

transport = GoogleTransport()

The transport auto-selects gemini-3.1-pro-preview as the default model.

Models¶

Model ID	Capabilities	Context	Notes
`gemini-3.1-pro-preview`	text, vision, audio, video, tools, reasoning	1M tokens	Flagship
`gemini-3-flash-preview`	text, vision, audio, video, tools, reasoning	1M tokens	Fast/cheap
`gemini-3.1-flash-lite-preview`	text, vision, audio, video, tools, reasoning	1M tokens	Lightest
`gemini-3.1-flash-image-preview`	text, vision, image generation	1M tokens	Nano Banana
`gemini-3-pro-image-preview`	text, vision, image generation	1M tokens	Image gen

Switching models¶

from axio_transport_google import GoogleTransport
from axio.models import Capability

transport = GoogleTransport()

# Switch to a specific model
transport.model = transport.models["gemini-3-flash-preview"]

# Find the cheapest reasoning model
transport.model = (
    transport.models
    .by_capability(Capability.reasoning)
    .by_cost()
    .first()
)

Constructor parameters¶

Parameter	Default	Description
`api_key`	`GEMINI_API_KEY` env var	API key for the Developer API
`model`	`gemini-3.1-pro-preview`	Active `ModelSpec`
`temperature`	`None`	Sampling temperature (uses model default if unset)
`top_p`	`None`	Nucleus sampling probability
`top_k`	`None`	Top-k sampling
`seed`	`None`	Random seed for deterministic outputs
`thinking_budget`	`None`	Token budget for chain-of-thought reasoning
`thinking_level`	`None`	Thinking level: `"LOW"`, `"MEDIUM"`, `"HIGH"`, or `"NONE"`
`max_output_tokens`	`None`	Override the model’s default max output
`max_retries`	`5`	Retries on 429/503 with exponential backoff
`safety_settings`	`None`	List of `SafetySettingDict` (see below)
`debug`	`False`	Log raw request/response bodies

Vertex AI¶

Use VertexAITransport to route through Google Cloud Vertex AI instead of the Developer API. It reads credentials from application-default credentials (gcloud auth application-default login).

from axio_transport_google import VertexAITransport

transport = VertexAITransport(
    project="my-gcp-project",
    location="us-central1",
)

Or set environment variables:

export GOOGLE_CLOUD_PROJECT="my-gcp-project"
export GOOGLE_CLOUD_LOCATION="us-central1"
export GOOGLE_GENAI_USE_VERTEXAI="1"

On Vertex AI you can also use Anthropic models with a anthropic/ prefix:

transport.model = transport.models["anthropic/claude-opus-4-6"]

Safety settings¶

Override the default safety thresholds:

from axio_transport_google import GoogleTransport
from axio_transport_google._generated_types import SafetySetting

transport = GoogleTransport(
    safety_settings=[
        SafetySetting(category="HARM_CATEGORY_DANGEROUS_CONTENT", threshold="BLOCK_NONE"),
    ]
)

Image generation¶

When the selected model supports Capability.image_generation, the transport exposes generate_images:

import asyncio
from axio_transport_google import GoogleTransport


async def main() -> None:
    transport = GoogleTransport()
    images: list[bytes] = await transport.generate_images(
        "A photorealistic owl sitting on a branch",
        model="gemini-3.1-flash-image-preview",
        n=1,
    )
    with open("owl.png", "wb") as f:
        f.write(images[0])


asyncio.run(main())

Video generation¶

import asyncio
from axio_transport_google import GoogleTransport


async def main() -> None:
    transport = GoogleTransport()
    videos: list[bytes] = await transport.generate_videos(
        "Time-lapse of clouds moving over mountains",
        model="veo-3.1-fast-generate-001",
        duration_seconds=6,
        aspect_ratio="16:9",
    )
    with open("timelapse.mp4", "wb") as f:
        f.write(videos[0])


asyncio.run(main())

Video generation runs an async polling loop until the job completes.

Tools registered as entry points¶

When installed, axio-transport-google registers two tools under axio.tools:

Entry point	Tool	Description
`generate_image`	`generate_image`	Generate images via Gemini Nano Banana
`generate_video`	`generate_video`	Generate videos via Veo

These tools are automatically available in the TUI and in axio-repl.

Realtime (Gemini Live)¶

For low-latency voice conversations, use GeminiLiveTransport with RealtimeAgent. See the Realtime Audio guide for the full setup.

from axio_transport_google.realtime import GeminiLiveTransport
from axio.realtime import RealtimeAgent

transport = GeminiLiveTransport()

async with RealtimeAgent(system="You are a helpful assistant.", transport=transport) as agent:
    ...

For Vertex AI realtime, use VertexLiveTransport. If you have multiple Vertex regions available, the transport can auto-select the nearest one:

from axio_transport_google.realtime import VertexLiveTransport, probe_nearest_live_region

region = await probe_nearest_live_region()
transport = VertexLiveTransport(location=region)