Functions | fal.ai Private Apps

In addition to fal Apps, fal also supports defining serverless functions that can be called from your code just like any other Python function, but they are executed on a remote machine.

Functions are useful for one-off jobs that have a natural end, such as copying data to the /data volume or training a model.

import fal


@fal.function(machine_type="GPU", requirements=["diffusers", "torch", "transformers"])
def generate_image(prompt: str):
    import torch
    from diffusers import FluxPipeline
    from io import BytesIO
    pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16)
    pipe.enable_model_cpu_offload()

    out = pipe(
        prompt=prompt,
        guidance_scale=0.,
        height=768,
        width=1360,
        num_inference_steps=4,
        max_sequence_length=256,
    ).images[0]

    buffer = BytesIO()
    out.save(buffer, format="PNG")
    image_bytes = buffer.getvalue()
    return image_bytes

image_bytes = generate_image("A cat holding a sign that says hello world")
with open("image.png", "wb") as f:
    f.write(image_bytes)