Keep context - Perplexity

· Source: perplexity.ai via Google News · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Intermediate, quick

Summary

The Perplexity Agent API operates stateless across individual requests, meaning each call processes only its own payload without automatically carrying over prior conversation context. To enable follow-up interactions that build on earlier turns, users must manually replay the entire prior conversation, including user messages, assistant replies, and function calls, within the "input" array of each subsequent request. Although an OpenAI-compatible "previous_response_id" field exists, it is currently unsupported for server-side response continuation. For long conversation chains, passing a stable "prompt_cache_key" on each request is recommended to improve prompt-cache affinity, allowing the backend to reuse shared prefixes and avoid reprocessing the full replayed conversation every turn.

Key takeaway

For AI Engineers building multi-turn conversational agents with the Perplexity Agent API, you must explicitly manage conversation state. Since the API is stateless, you need to replay the entire prior conversation within the "input" array of each subsequent request. Implement a stable "prompt_cache_key" for long chains to optimize backend processing and reduce latency, ensuring your agent maintains context efficiently without reprocessing redundant information.

Key insights

The Perplexity Agent API requires manual conversation replay in the "input" array to maintain context across requests.

Principles

Method

To chain turns, send the next request with an "input" array containing all prior "user" and "assistant" messages, appending the new question at the end.

In practice

Topics

Best for: AI Engineer, Software Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by perplexity.ai via Google News.