Skill UI

A comprehensive guide and implementation demonstrating how to handle API rate limits when interacting with AI services like Together AI. It details the token bucket algorithm for client-side throttling and provides robust retry mechanisms (exponential backoff) to manage 429 (Rate Limit Exceeded) and 5xx server errors, ensuring stable, high-throughput batch processing.

This skill provides comprehensive guidance for submitting research to npj Computational Materials. It defines the journal's scope, requiring rigorous computational methods (DFT, MD, ML, high-throughput screening) that yield generalizable materials insights or predictive capabilities. It educates authors on the required standards, including methodological rigor, reproducibility, and adherence to FAIR data principles, helping authors re-frame their work for a high-impact venue.

Python SDK for managing Azure Container Registry resources including images, artifacts, and repositories. Supports operations like listing, updating, deleting, and downloading manifests. Includes authentication via Entra ID and async client support for high-throughput scenarios.

High-throughput event streaming SDK for sending and receiving events via Azure Event Hubs in .NET applications. Covers installation, authentication, client types, batch sending, buffered sending, and production event processing with checkpointing.

This Python SDK enables high-throughput event ingestion and processing on Azure Event Hubs. It supports producers and consumers with checkpointing capabilities for reliable streaming data management. Ideal for big data pipelines and real-time analytics scenarios.

Client library for Azure Event Hubs in Rust, enabling event ingestion, streaming data processing, and building producers and consumers for high-throughput event pipelines.

This skill covers using the Azure Event Hubs SDK for TypeScript to build high-throughput event streaming applications. It includes real-time data ingestion, sending events to specific partitions, receiving events with checkpointing for production reliability, and handling batch processing options. Ideal for IoT telemetry and real-time data pipelines.

Use the Azure Queue Storage SDK for Python to build reliable message queuing: authenticate with Azure Identity, create queues, send, receive, peek, update and delete messages, handle visibility timeouts, and run async clients for high-throughput workloads.