A developer is building a client application that interacts with a Snowflake Cortex Agent using its REST API. They are implementing multi- turn conversation support. Which of the following is the most critical aspect for maintaining conversational context over multiple API calls?
Correct Answer: A
Option A is the most critical and correct method for maintaining conversational state in multi-turn interactions with Cortex LLM functions, including those used by Cortex Analyst and by extension Cortex Agents. The underlying COMPLETE function (and its REST API equivalent) does not retain state from one call to the next; therefore, the client application must explicitly pass all previous user prompts and model (assistant/analyst) responses in chronological order within the 'messages' (or array for each new request to provide a stateful experience. Option B is incorrect as Cortex LLM functions do not automatically retain state across calls. Option C is incorrect; there is no documented 'session_id' parameter for implicitly managing conversation history for these APIs. Option D is incorrect; passing only partial history would lead to a loss of full conversational context and degrade the quality of follow-up responses. Option E is incorrect; while Cortex Analyst internally uses a summarization agent for long conversations to reframe questions, the client application is still responsible for managing and sending the full conversation history in the 'messages' array via the API.