Hi all,
We’re excited to announce that we’ve been working a Python SDK for RxInferServer, enabling Python developers to perform remote Bayesian inference using models hosted on RxInferServer.
What is RxInfer?
RxInfer.jl is a Julia package designed for reactive message passing and probabilistic programming. It facilitates real-time Bayesian inference in complex models, supporting both exact and variational inference algorithms. RxInfer is particularly well-suited for applications requiring online inference and real-time data processing.
For a comprehensive collection of examples and tutorials, visit examples.rxinfer.com.
Python SDK Highlights
- Remote Model Execution: Call RxInfer models hosted on RxInferServer directly from Python.
- OpenAPI Specification: RxInferServer exposes an OpenAPI interface, allowing for seamless integration and client generation.
- Julia Interoperability: With minor modifications, RxInferServer can execute arbitrary Julia code, not limited to RxInfer models.
Getting Started
- Example Notebook: State-Space Model Example
Feedback and Contributions
We welcome feedback from the Python community, especially those interested in:
- Integrating Bayesian inference into Python workflows
- Exploring cross-language model execution (Python ↔ Julia)
- Developing real-time data processing pipelines
Feel free to try out the SDK, report issues, or contribute to the project. Your insights will help shape the future development of RxInfer’s Python integration.