When you send a request to the Perplexity API, the connection may stop waiting for a response before the answer is fully generated. This is called a timeout. The default timeout value is often too short for complex queries that require deep research or large context windows. This article explains why timeouts happen and how … Read more
When you use the Perplexity API to get answers from large language models, the raw response is a JSON object. You need to extract and format this data for use in your application, dashboard, or log file. The API returns structured data that includes the answer text, citations, and usage statistics. This article explains how … Read more
When you use Perplexity API JSON mode, you expect structured JSON output. Instead, the API sometimes returns markdown text wrapped in triple backticks. This breaks your application logic and requires extra parsing. The root cause is a mismatch between the API endpoint and the model used. This article explains why JSON mode returns markdown and … Read more
You want the Perplexity API to only search or retrieve data from certain websites, not the entire internet. This is useful for internal knowledge bases, trusted news sources, or curated content sets. The Perplexity API does not offer a built-in domain whitelist filter like some search engines do. This article explains how to achieve domain … Read more
When you apply a domain filter in the Perplexity API, the response can return zero results even though you know relevant content exists on the specified site. This typically happens because the API enforces a combined search scope that treats the domain filter as a secondary constraint rather than a primary query operator. In this … Read more
If you currently use the OpenAI API for text generation or search-augmented completions, you may want to switch to Perplexity Sonar for lower cost, built-in web grounding, and real-time citations. The OpenAI API and Perplexity Sonar both support a chat completions endpoint, but the request format, authentication, and response structure differ in several key ways. … Read more
You need to choose between Perplexity API Sonar Reasoning and DeepSeek R1 for your AI application. Both models excel at complex reasoning tasks but differ in architecture, cost, and availability. This article compares their features, performance, and practical use cases to help you decide. Key Takeaways: Perplexity API Sonar Reasoning vs DeepSeek R1 Sonar Reasoning: … Read more
Every time your application calls the Perplexity API for the same question, you pay for a new response. If your users often ask similar queries or you poll the API on a schedule, your costs can rise quickly. Caching stores a copy of each API response so repeated requests return the saved answer instead of … Read more