Keep context - Perplexity
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
- Agent API is stateless across requests.
- Context requires explicit conversation replay.
- "prompt_cache_key" improves cache affinity.
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
- Replay full conversation in "input" array.
- Use "prompt_cache_key" for long chains.
- Append new question to replayed "input".
Topics
- Perplexity Agent API
- Conversational AI
- Context Management
- API State
- Prompt Caching
- Multi-turn Interactions
Best for: AI Engineer, Software Engineer
Related on AIssential
Editorial summary, takeaway, and curation by AIssential. Original article published by perplexity.ai via Google News.