fal.ai Python client

This is a Python client library for interacting with ML models deployed on fal.ai.

Getting started

To install the client, run:

pip install fal-client

To use the client, you need to have an API key. You can get one by signing up at fal.ai. Once you have it, set it as an environment variable:

export FAL_KEY=your-api-key

Now you can use the client to interact with your models. Here's an example of how to use it:

import fal_client

response = fal_client.run("fal-ai/fast-sdxl", arguments={"prompt": "a cute cat, realistic, orange"})
print(response["images"][0]["url"])

Asynchronous requests

The client also supports asynchronous requests out of the box. Here's an example:

import asyncio
import fal_client

async def main():
    response = await fal_client.run_async("fal-ai/fast-sdxl", arguments={"prompt": "a cute cat, realistic, orange"})
    print(response["images"][0]["url"])


asyncio.run(main())

Uploading files

If the model requires files as input, you can upload them directly to fal.media (our CDN) and pass the URLs to the client. Here's an example:

import fal_client

audio_url = fal_client.upload_file("path/to/audio.wav")
response = fal_client.run("fal-ai/whisper", arguments={"audio_url": audio_url})
print(response["text"])

Encoding files as in-memory data URLs

If you don't want to upload your file to our CDN service (for latency reasons, for example), you can encode it as a data URL and pass it directly to the client. Here's an example:

import fal_client

audio_data_url = fal_client.encode_file("path/to/audio.wav")
response = fal_client.run("fal-ai/whisper", arguments={"audio_url": audio_data_url})
print(response["text"])

Queuing requests

When you want to send a request and keep receiving updates on its status, you can use the submit method. Here's an example:

import asyncio
import fal_client

async def main():
    response = await fal_client.submit_async("fal-ai/fast-sdxl", arguments={"prompt": "a cute cat, realistic, orange"})

    logs_index = 0
    async for event in response.iter_events(with_logs=True):
        if isinstance(event, fal_client.Queued):
            print("Queued. Position:", event.position)
        elif isinstance(event, (fal_client.InProgress, fal_client.Completed)):
            new_logs = event.logs[logs_index:]
            for log in new_logs:
                print(log["message"])
            logs_index = len(event.logs)

    result = await response.get()
    print(result["images"][0]["url"])


asyncio.run(main())