Introduction¶

Introduction to the BioLM.ai API and programmatic access to the platform.

If accessing via the tutorials you will already be authenticated with your BioLM account, otherwise please set your token as an environment variable

import os
# os.environ['BIOLMAI_TOKEN'] = "Your token here"

from biolmai import BioLM

Example API Call¶

We'll quickly demonstrate an API call

GFP_SEQ = """
MSKGEELFTGVVPILVELDGDVNGHKFSVSGEGEGDATYGKLTLKFICTTGKLPVPWPTL
VTTFSYGVQCFSRYPDHMKQHDFFKSAMPEGYVQERTIFFKDDGNYKTRAEVKFEGDTLV
NRIELKGIDFKEDGNILGHKLEYNYNSHNVYIMADKQKNGIKVNFKIRHNIEDGSVQLAD
HYQQNTPIGDGPVLLPDNHYLSTQSALSKDPNEKRDHMVLLEFVTAAGITHGMDELYK
""".replace('\n', '').strip().upper()

# Make the POST request
result = BioLM(entity="esmfold", action="predict", items=[{"sequence": GFP_SEQ}])
result

You can print these JSON results in an interactive format using iPython:

JSON(result)

<IPython.core.display.JSON object>

Next Steps¶

Check out additional tutorials at jupyter.biolm.ai, or head over to our BioLM Documentation to explore additional models and functionality.

See more use-cases and APIs on your BioLM Console Catalog.¶

BioLM hosts deep learning models and runs inference at scale. You do the science.¶

Contact us to learn more.¶

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