What Ophelian Is and What It Is Not

✅ What Ophelian Is

A Web-Based IDE: Ophelian is evolving into a comprehensive web-based integrated development environment (IDE) designed for the production of machine learning models across various frameworks, including Flink, Kafka, Beam, PySpark, Torch, Dask, QuixStreams, Scikit-learn and the notorious Pandas.
Framework Integration: It aims to integrate seamlessly with multiple machine learning frameworks, generating what are termed "OphelianPredictors." These are configurable code wrappers that initiate a session in one of these frameworks and automatically set up the necessary environment.
Workflow Integration: Ophelian combines elements of JupyterLab, Airflow, and PyCharm to create an environment where users can quickly productize their ML pipelines, both batch and streaming, in a matter of days.
Endpoint Deployment: It has the capability to deploy endpoints with inference methods using FastAPI with Uvicorn, making it possible to run predictions in real-time.
Artifact and Metadata Management: Ophelian will work with an artifact registry or other source artifact tools of your preference, along with a PostgreSQL database for tracking metadata, ensuring efficient management of ML models and their artifacts.
Custom Functions Support: It supports UDF (User-Defined Functions) or DoFn (Distributed Function) types, allowing users to execute customized functions as part of their pipelines.

❎ What Ophelian Is Not

A Standalone Tool: Ophelian is not intended to be a standalone tool for general data processing. It is specifically designed for machine learning production workflows.
Limited to a Single Framework: It does not restrict users to a single framework or technology. Instead, it supports a wide range of frameworks to provide flexibility and adaptability.
A Replacement for Raw Coding: Ophelian is not a substitute for writing optimized code manually. It abstracts and simplifies common tasks but still relies on underlying frameworks and optimized code.
A Purely Experimental Platform: While it supports the creation and testing of ML pipelines, Ophelian's primary focus is on production readiness and efficiency, not just experimentation.
A Cloud or Cluster Manager: Ophelian is not a cloud or cluster manager, nor is it a cloud-based machine for distributed computing.
A Web Server for Endpoints: It is not designed to be a web server for hosting endpoints. Its focus is on quickly and dynamically implementing code pipelines.
A Comprehensive Deployment Platform: While it facilitates the construction of the shell for model deployment, its main purpose is to enable fast and secure deployment of ML models.

By understanding what Ophelian aims to achieve and what it is not designed to do, users can better leverage its capabilities to streamline their machine learning workflows and enhance productivity.