Getting started with OpenProtein.AI’s API#
Step 1: Request early access
Step 2: Install our Python client
You can install the package via pip or conda as below:
pip
pip install openprotein-python
conda
conda install -c openprotein openprotein-python
Github
The source code is available here.
Want to start with the web version?
Visit Get started with no code
Step 3: Authenticate your session
Use your username and password credentials generated at sign-up to authenticate your connection to OpenProtein.AI’s backend.
OpenProtein Job System
The OpenProtein.AI platform uses a job system to support asynchronous task execution. Upon initiating a task, the system will schedule a job with a unique Job ID so you can return at a later time for tasks with long processing times.
OpenProtein API session
Executing workflows is achieved with the OpenProtein APISession object (see openprotein.APISession())
session = openprotein.connect(username="username", password="password")
You then have access to all the workflows: For example
session.data.create()
Or
session.poet.create_msa()
Step 4: Get started using our API for your protein engineering goals
Quick start tips#
Do you want to…
![](../_static/getting-started/poet-icon.png)
Get started with PoET which uses evolutionary information to generate protein sequences
![](../_static/getting-started/bar-chart.png)
Use our Property Regression Models to train and deploy machine learning models in your context
![](../_static/getting-started/dna-broken.png)
Use our Structure Prediction workflow to obtain PDB files using ESMFold and AlphaFold2 models
Use our Foundation Models to access high quality sequence embeddings using proprietary and open source models