Skill UI

A comprehensive guide detailing common real-world mistakes and pitfalls when integrating with the OpenRouter API. Covers critical best practices for robust LLM deployment, including correct model ID formatting, cost control via max_tokens, secure API key management, handling rate limits, and optimizing client connection reuse. Essential for developers building multi-provider AI applications.

This skill demonstrates advanced techniques for managing high-volume API calls to LLM services via OpenRouter. It implements multi-key round-robin strategies, incorporating health checks and circuit breakers to distribute load across multiple API keys. It also covers concurrent request processing using asyncio and provider-level failover, ensuring high availability and maximizing throughput when facing rate limits.

A comprehensive guide on handling API rate limits and throttling errors (429) when building high-throughput systems, particularly for LLM APIs like OpenRouter. This skill covers best practices, including using exponential backoff, implementing custom client-side rate limiters (Token Bucket), and managing concurrent requests for stable, reliable performance.

This skill provides comprehensive governance for multi-user API deployments using OpenRouter. It covers key provisioning, including creating, listing, and revoking individual user keys. Users can set per-user budget limits and track usage costs programmatically. It is designed for corporate or team environments that require strict cost control, usage attribution, and detailed usage reporting.

This guide details how to configure robust CI/CD pipelines for Perplexity Sonar API integrations using GitHub Actions. It emphasizes best practices for automated testing, including separating costly live integration tests from lightweight mocked unit tests, ensuring code quality while managing API costs and rate limits.

This guide provides a comprehensive reference for diagnosing and fixing common errors and exceptions encountered when interacting with the Perplexity Sonar API. Use this when troubleshooting API integration issues, handling specific HTTP status codes (like 401, 429, 402), or debugging failed requests. It covers best practices for rate limiting, key validation, and implementing robust error handling logic.

This guide details how to implement Role-Based Access Control (RBAC) for Perplexity API in enterprise environments. Since Perplexity lacks native RBAC, the solution involves building a middleware gateway. This gateway enforces granular policies, including team-specific API key usage, model restriction (e.g., limiting access to 'sonar' only), budget caps, rate limiting, and mandatory search domain filtering for compliance and security.

This skill provides comprehensive guidance on load testing and capacity planning for the Perplexity Sonar API. Users learn how to simulate high traffic volumes, respecting strict rate limits (like 50 RPM), benchmark latency, and estimate operational costs. It is essential for performance engineering, capacity architecture design, or stress testing APIs at scale.

This skill provides a comprehensive guide to configuring the Perplexity Sonar API across distinct operational environments (development, staging, and production). It details how to manage environment-specific API keys, enforce tailored rate limits, select appropriate models (e.g., sonar vs. sonar-pro), and implement cost optimization strategies. Use this when migrating or integrating Perplexity search functionality into a multi-tier, production-grade application architecture.

This guide provides advanced architectural patterns to optimize interactions with the Perplexity Sonar API. By implementing smart model routing, query hashing with time-to-live (TTL) caching, streaming responses, and rate-limited parallel processing, developers can significantly reduce latency, improve overall throughput, and manage API costs. Ideal for integrating complex, research-intensive search-augmented applications.

This comprehensive checklist guides the deployment of Perplexity Sonar API integrations to a robust production environment. It covers critical aspects including API key management, robust code quality practices (retries, rate limiting), performance optimization (caching, streaming), detailed monitoring setup, and cost control strategies. Use this checklist when preparing for a major Perplexity feature launch or going live to production.

A comprehensive guide and implementation examples for handling API rate limits (HTTP 429) when interacting with the Perplexity Sonar API. This resource provides multiple robust techniques, including exponential backoff with jitter, queue-based rate limiting, and custom Token Bucket implementation, ensuring reliable and high-throughput API calls for developers using TypeScript and Python.