openprotein-python 0.1.2b1

OpenProtein Python interface.

openprotein-python

Python interface for the OpenProtein.AI REST API.

Installation

You can install with pip:

pip install openprotein-python

Getting started

First, create a session using your login credentials.

import openprotein
session = openprotein.connect(USERNAME, PASSWORD)

Async calls return AsyncJobFuture objects that allow tracking the status of the job and retrieving the result when it's ready.

Given a future, check its status and retrieve results

future.refresh() # call the backend to update the job status
future.done() # returns True if the job is done, meaning the status could be SUCCESS, FAILED, or CANCELLED
future.wait() # wait until done and then fetch results, verbosity is controlled with verbose arg.
result = future.get() # get the result from a finished job

Jobs interface

List your jobs, optionally filtered by date, job type, and status.

session.jobs.list() # list all jobs
session.jobs.get(JOB_ID) # get a specific job

Resume an AsyncJobFuture from where you left off with each API's load_job:

For example for training jobs:

session.train.load_job(JOB_ID)

PoET interface

Score sequences using the PoET interface.

prompt_seqs = b'MALWMRLLPLLALLALWGPDPAAAFVNQHLCGSHLVEALYLVCGERGFFYTPKTRREAEDLQVGQVELGGGPGAGSLQPLALEGSLQKRGIVEQCCTSICSLYQLENYCN'

prompt = session.poet.upload_prompt(prompt_seqs)

queries = [
    b'MALWMRLLPLLALLALWGPDPAAAFVNQHLCGSHLVEALYLVCGERGFFYTPKTRREAEDLQVGQVELGGGPGAGSLQPLALEGSLQKRGIVEQCCTSICSLYQLENYCN',
    b'MALWMRLLPLLVLLALWGPDPASAFVNQHLCGSHLVEALYLVCGERGFFYTPKTRREAEDLQVGQVELGGGPGAGSLQPLALEGSLQKRGIVEQCCTSICSLYQLENYCN',
    b'MALWTRLRPLLALLALWPPPPARAFVNQHLCGSHLVEALYLVCGERGFFYTPKARREVEGPQVGALELAGGPGAGGLEGPPQKRGIVEQCCASVCSLYQLENYCN',
    b'MALWIRSLPLLALLVFSGPGTSYAAANQHLCGSHLVEALYLVCGERGFFYSPKARRDVEQPLVSSPLRGEAGVLPFQQEEYEKVKRGIVEQCCHNTCSLYQLENYCN',
    b'MALWMRLLPLLALLALWAPAPTRAFVNQHLCGSHLVEALYLVCGERGFFYTPKARREVEDLQVRDVELAGAPGEGGLQPLALEGALQKRGIVEQCCTSICSLYQLENYCN',
]

future = session.poet.score(prompt, queries)
result = future.wait()
# result is a list of (sequence, score) pydantic objects

Score single site variants using the PoET interface.

sequence = "MALWMRLLPLLALLALWGPDPAAAFVNQHLCGSHLVEALYLVCGERGFFYTPKTRREAEDLQVGQVELGGGPGAGSLQPLALEGSLQKRGIVEQCCTSICSLYQLENYCN"
future = session.poet.single_site(prompt, sequence, prompt_is_seed=True) 
result = future.wait()
# result is a dictionary of {variant: score}

Generate sequences from the PoET model.

future = session.poet.generate(
    prompt,
    max_seqs_from_msa=1024,
    num_samples=100,
    temperature=1.0,
    topk=15
)
samples = future.wait()

Retrieve the prompt, MSA, or input (seed) sequences for a PoET job.

future.get_input(INPUT_TYPE)
# or, functions for each type
future.get_prompt()
future.get_msa()
future.get_seed()

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