Query memories
Retrieves documents matching the query.
Authorizations
API Key or JWT User Token. If using an API Key, set the X-As-User header to act as a specific user. A JWT User Token is always scoped to a specific user.
Body
Query to run.
If true, the query will be answered along with matching source documents.
How much compute to spend on retrieval. Mirrors the dial popularized by frontier-model APIs (OpenAI reasoning_effort, etc.). 'minimal' = verbatim single-shot retrieval (fastest). 'low' = LLM rewrites the query for better retrieval and extracts date filters. 'medium' = rewrite + agentic refinement loop (the answer LLM may request additional retrieval rounds, up to 3). 'high' = rewrite + extended refinement (up to 6 rounds). Higher = better recall, more latency, more cost.
minimal, low, medium, high Only query documents from these sources.
reddit, notion, slack, google_calendar, google_mail, box, dropbox, github, google_drive, vault, web_crawler, trace, microsoft_teams, gmail_actions, granola, fathom, linear, hubspot, salesforce, coda Search options for the query.
Maximum number of results to return.
Response
Successful Response
The ID of the query. This can be used to retrieve the query later, or add feedback to it. If the query failed, this will be None.
Errors that occurred during the query. These are meant to help the developer debug the query, and are not meant to be shown to the user.
The answer to the query, if the request was set to answer.
The average score of the query feedback, if any.