Skill UI

A comprehensive guide to managing API credit consumption and rate limits for SerpApi. This skill demonstrates how to implement robust throttling mechanisms using Python (Semaphore) and TypeScript (PQueue). It covers monitoring remaining account credits, slowing down requests to comply with per-second limits, and utilizing the search archive feature to optimize search volume and prevent unnecessary credit expenditure.

This guide outlines production-ready patterns for integrating SerpApi into robust search services. It covers essential best practices, including defining typed result interfaces for type safety, implementing LRU caching to conserve API credits, and building multi-engine abstractions to handle various search types (web, news, images). It also demonstrates asynchronous search processing for non-blocking operations.

This tool provides a local development loop for integrating with Together AI's OpenAI-compatible API. It mocks key functionalities like chat completions, embeddings, and model listing, allowing developers to build and test AI applications rapidly without consuming live API credits. Developers can toggle between mock mode for rapid iteration and live mode for final model evaluation, ensuring a seamless workflow.