Python client for modelrunner.ai
Project description
modelrunner.ai Python client
This is a Python client library for interacting with ML models deployed on modelrunner.ai.
Getting started
To install the client, run:
pip install modelrunner-ai
To use the client, you need to have an API key. You can get one by signing up at modelrunner.ai. Once you have it, set it as an environment variable:
export MODELRUNNER_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 asyncio
import modelrunner_ai
async def main():
response = await modelrunner_ai.submit_async("bytedance/sdxl-lightning-4step", arguments={"prompt": "two friends cooking together"})
logs_index = 0
async for event in response.iter_events(with_logs=True):
if isinstance(event, modelrunner_ai.Queued):
print("Queued. Position:", event.position)
elif isinstance(event, (modelrunner_ai.InProgress, modelrunner_ai.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["output"])
asyncio.run(main())
Uploading files
If the model requires files as input, you can upload them directly to media.modelrunner.ai (our CDN) and pass the URLs to the client. Here's an example:
import modelrunner_ai
input_image = modelrunner_ai.upload_file("./image.jpg")
print(input_image)
response = modelrunner_ai.run("swook/inspyrenet", arguments={"image_path": input_image})
print(response["output"])
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The following attestation bundles were made for modelrunner_ai-0.1.0-py3-none-any.whl:
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release.yaml on modelrunner/modelrunner
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Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
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release.yaml@46f7912f6008e1f2496126ee8165c000cba71ef2 -
Trigger Event:
release
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