Integrates real-time web search and grounded AI responses into applications using the Perplexity Sonar API.
This skill enables developers to leverage the Perplexity Sonar model family to build AI-powered applications that require up-to-date information and grounded responses through search-augmented generation (RAG). It provides comprehensive implementation patterns for Python and TypeScript, covering the full spectrum of Sonar models from fast factual lookups to complex reasoning. Developers can implement advanced search controls like domain filtering and recency constraints while ensuring transparency through automated citation handling and source attribution.
Key Features
010 GitHub stars
02OpenAI-compatible Chat Completions integration for Python and TypeScript
03Advanced search configurations including domain and recency filtering
04Implementation patterns for Sonar, Sonar Pro, and Reasoning models
05Automated citation extraction and source attribution handling
06Streaming response support and production-ready error handling
Use Cases
01Building AI research assistants that require verifiable citations
02Developing real-time news and market analysis tools
03Creating grounded chatbots that minimize hallucinations via web-search augmentation
