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summarizeConversation()

The standalone summarizeConversation() function summarizes a conversation in one shot. It distills the messages you pass in with the same Observer plumbing that powers Observational Memory — without Observational Memory attached to an agent, and without reading from or writing to storage.

Nothing is written back to memory. The summary and extracted values are returned to you (and to each extractor's onExtracted hook), so you decide where they go — for example your own database.

Use this when you already have the messages in hand and want explicit control over what gets summarized. To summarize a stored thread by ID instead, use Memory.summarizeThread(), which loads the messages for you.

Usage example
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import { summarizeConversation } from '@mastra/memory'

const result = await summarizeConversation({
  model: 'openai/gpt-5-mini',
  messages,
  instructions: 'Summarize this voicemail call for the business owner.',
})

Parameters
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model:

string | LanguageModel | DynamicModel
Model that runs the summarization, such as a router string like '__GATEWAY_OPENAI_MODEL_MINI__'.

messages:

MastraDBMessage[]
The conversation to summarize. When empty, the function returns an empty result without calling the model.

instructions?:

string
Extra guidance appended to the summarizer's system prompt, such as what to focus on or who the summary is for.

extract?:

Extractor[]
Extractors to run over the conversation. Extractors with a Zod schema run as a follow-up structured output call; schema-less extractors are extracted inline. Each extractor's onExtracted hook fires with the extracted value.

threadId?:

string
Thread the conversation belongs to. Defaults to the first threadId found on messages. Passed to extractor contexts.

resourceId?:

string
Resource (user) the conversation belongs to. Defaults to the first resourceId found on messages. Passed to extractor contexts.

memory?:

Memory
Memory instance forwarded to extractor contexts. Set automatically when called through Memory.summarizeThread().

mastra?:

Mastra
Mastra instance used to resolve custom gateway models. Set automatically when called through Memory.summarizeThread().

requestContext?:

RequestContext
Request context forwarded to the summarizer model and extractor hooks.

abortSignal?:

AbortSignal
Signal to cancel the summarization call.

Returns
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summary:

string
The distilled observations produced from the conversation, in dense bullet form.

extracted:

Record<string, unknown>
Values produced by extract extractors, keyed by extractor slug.

extractionFailures:

{ slug: string; error: string }[]
Extractors that failed to produce a valid value, with the reason. Only present when at least one extractor failed.

usage:

{ inputTokens?: number; outputTokens?: number; totalTokens?: number }
Token usage of the summarization call.

Extended usage example
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The following example summarizes an in-flight voice session from messages the application already holds, and extracts a structured record:

src/session-summary.ts
import { summarizeConversation, Extractor } from '@mastra/memory'
import type { MastraDBMessage } from '@mastra/core/agent'
import { z } from 'zod'
import { sessionRecords } from './db'

const sessionSummary = new Extractor({
  name: 'session-summary',
  instructions: 'Return a concise summary of the session.',
  schema: z.object({
    summary: z.string(),
    sentiment: z.enum(['positive', 'neutral', 'negative']),
    followUps: z.array(z.string()),
  }),
  metadataKeyPath: false, // don't persist into memory metadata — the hook owns storage
  onExtracted: async ({ current, threadId }) => {
    await sessionRecords.upsert({ sessionId: threadId, record: current })
  },
})

export async function onSessionEnd(messages: MastraDBMessage[]) {
  const { summary, extracted, extractionFailures } = await summarizeConversation({
    model: 'openai/gpt-5-mini',
    messages,
    instructions: 'Summarize this support session for the account manager.',
    extract: [sessionSummary],
  })

  if (extractionFailures?.length) {
    console.warn('Some extractors failed', extractionFailures)
  }

  return { summary, extracted }
}
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