Python client for fal.ai
Project description
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())
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file fal_client-0.5.4.tar.gz
.
File metadata
- Download URL: fal_client-0.5.4.tar.gz
- Upload date:
- Size: 11.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/5.1.1 CPython/3.12.7
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | a8b86eb9dcbf89dd1b095f95259eaad3da4e0faa7882bcc8056474653ae85e23 |
|
MD5 | 0fd0285cabf45a70ab30b411a80c0f12 |
|
BLAKE2b-256 | b004eea54924c81777f6b45491d07931aaefaa346235164eed3baa26a06f89ac |
File details
Details for the file fal_client-0.5.4-py3-none-any.whl
.
File metadata
- Download URL: fal_client-0.5.4-py3-none-any.whl
- Upload date:
- Size: 8.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/5.1.1 CPython/3.12.7
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | fdc6e61abec60dd7b251ce459711e0981fac3b3aed61e7e2aa7c58227728e509 |
|
MD5 | f76024b83d0c64ecd6a62a816ebc1a7b |
|
BLAKE2b-256 | a2f92fcd0c0eaf438a32e3219670f9611f3e48ee591ec8365f7c1e3374a2c657 |