Lumalabs | Agno

LumaLabTools enables an Agent to generate media using the Lumalabs platform.

Prerequisites

export LUMAAI_API_KEY=***

The following example requires the lumaai library. To install the Lumalabs client, run the following command:

uv pip install -U agno lumaai openai

Example

The following agent will use Lumalabs to generate any video requested by the user.

cookbook/91_tools/lumalabs_tools.py

from agno.agent import Agent
from agno.models.openai import OpenAIResponses
from agno.tools.lumalab import LumaLabTools

luma_agent = Agent(
    name="Luma Video Agent",
    model=OpenAIResponses(id="gpt-5.2"),
    tools=[LumaLabTools()],  # Using the LumaLab tool we created
    markdown=True,
    debug_mode=True,
    instructions=[
        "You are an agent designed to generate videos using the Luma AI API.",
        "You can generate videos in two ways:",
        "1. Text-to-Video Generation: use the generate_video function for creating videos from text prompts",
        "2. Image-to-Video Generation: use the image_to_video function when starting from one or two images",
        "Choose the appropriate function based on whether the user provides image URLs or just a text prompt.",
        "The video will be displayed in the UI automatically below your response, so you don't need to show the video URL in your response.",
    ],
    system_message=(
        "Use generate_video for text-to-video requests and image_to_video for image-based "
        "generation. Don't modify default parameters unless specifically requested. "
        "Always provide clear feedback about the video generation status."
    ),
)

luma_agent.run("Generate a video of a car in a sky")

Toolkit Params

Parameter	Type	Default	Description
`api_key`	`str`	`None`	If you want to manually supply the Lumalabs API key.
`wait_for_completion`	`bool`	`True`	Whether to poll until video generation completes.
`poll_interval`	`int`	`3`	Seconds between polling attempts.
`max_wait_time`	`int`	`300`	Maximum seconds to wait for generation before timing out.
`enable_generate_video`	`bool`	`True`	Enable the generate_video functionality.
`enable_image_to_video`	`bool`	`True`	Enable the image_to_video functionality.
`all`	`bool`	`False`	Enable all functionality.

Toolkit Functions

Function	Description
`generate_video`	Generate a video from a prompt.
`image_to_video`	Generate a video from a prompt, a starting image and an optional ending image.

Run with the current Luma SDK

The cookbook calls an SDK method that now requires a model. Until the Agno adapter exposes it, supply that argument through an explicit local adaptation:

from functools import partial
from agno.agent import Agent
from agno.tools.lumalab import LumaLabTools

tools = LumaLabTools(wait_for_completion=True)
tools.client.generations.create = partial(tools.client.generations.create, model="ray-2")
agent = Agent(tools=[tools])
response = agent.run("Generate a short video of a car floating in the sky.")
if response.videos:
    for video in response.videos:
        if video.url:
            print(video.url)
else:
    print(response.content)

Save this as luma_demo.py and run python luma_demo.py. It prints returned video URLs; a Python run() call does not create a UI or display video automatically. The adapter's wait_for_completion=False path currently returns Async generation unsupported without exposing a job ID. Keep waiting enabled, or manage asynchronous jobs directly through the Luma SDK.

Developer Resources

Tools