Memory.cloneThread()

The .cloneThread() method creates a copy of an existing conversation thread, including all its messages. This enables creating divergent conversation paths from a specific point in a conversation. When semantic recall is enabled, the method also creates vector embeddings for the cloned messages.

Usage example

const { thread, clonedMessages } = await memory.cloneThread({
  sourceThreadId: 'original-thread-123',
})

Parameters

sourceThreadId:

string

The ID of the thread to clone

newThreadId?:

string

Optional custom ID for the cloned thread. If not provided, one will be generated.

resourceId?:

string

Optional resource ID for the cloned thread. Defaults to the source thread's resourceId.

title?:

string

Optional title for the cloned thread. Defaults to '[source title] (Copy)'.

metadata?:

Record<string, unknown>

Optional metadata to merge with the source thread's metadata. Clone metadata is automatically added.

options?:

CloneOptions

Optional filtering options for the clone operation.

CloneOptions

messageLimit?:

number

Maximum number of messages to clone. When set, clones the most recent N messages.

messageFilter?:

MessageFilter

Filter criteria for selecting which messages to clone.

MessageFilter

startDate?:

Date

Only clone messages created on or after this date.

endDate?:

Date

Only clone messages created on or before this date.

messageIds?:

string[]

Only clone messages with these specific IDs.

Returns

thread:

StorageThreadType

The newly created cloned thread with clone metadata.

clonedMessages:

MastraDBMessage[]

Array of the cloned messages with new IDs assigned to the new thread.

messageIdMap?:

Record<string, string>

A mapping from source message IDs to their corresponding cloned message IDs.

Clone Metadata

The cloned thread's metadata includes a clone property with:

sourceThreadId:

string

The ID of the original thread that was cloned.

clonedAt:

Date

Timestamp when the clone was created.

lastMessageId?:

string

The ID of the last message in the source thread at the time of cloning.

Extended usage example

src/test-clone.ts

import { mastra } from './mastra'

const agent = mastra.getAgent('agent')
const memory = await agent.getMemory()

// Clone a thread with all messages
const { thread: fullClone } = await memory.cloneThread({
  sourceThreadId: 'original-thread-123',
  title: 'Alternative Conversation Path',
})

// Clone with a custom ID
const { thread: customIdClone } = await memory.cloneThread({
  sourceThreadId: 'original-thread-123',
  newThreadId: 'my-custom-clone-id',
})

// Clone only the last 5 messages
const { thread: partialClone, clonedMessages } = await memory.cloneThread({
  sourceThreadId: 'original-thread-123',
  options: {
    messageLimit: 5,
  },
})

// Clone messages from a specific date range
const { thread: dateFilteredClone } = await memory.cloneThread({
  sourceThreadId: 'original-thread-123',
  options: {
    messageFilter: {
      startDate: new Date('2024-01-01'),
      endDate: new Date('2024-01-31'),
    },
  },
})

// Continue conversation on the cloned thread
const response = await agent.generate("Let's try a different approach", {
  threadId: fullClone.id,
  resourceId: fullClone.resourceId,
})

Vector embeddings

When the Memory instance has semantic recall enabled (with a vector store and embedder configured), cloneThread() automatically creates vector embeddings for all cloned messages. This ensures that semantic search works correctly on the cloned thread.

import { Memory } from '@mastra/memory'
import { LibSQLStore, LibSQLVector } from '@mastra/libsql'

const memory = new Memory({
  storage: new LibSQLStore({ id: 'memory-store', url: 'file:./memory.db' }),
  vector: new LibSQLVector({ id: 'vector-store', url: 'file:./vector.db' }),
  embedder: embeddingModel,
  options: {
    semanticRecall: true,
  },
})

// Clone will also create embeddings for cloned messages
const { thread } = await memory.cloneThread({
  sourceThreadId: 'original-thread',
})

// Semantic search works on the cloned thread
const results = await memory.recall({
  threadId: thread.id,
  vectorSearchString: 'search query',
})

Observational memory

When Observational Memory is enabled, cloneThread() automatically clones the OM records associated with the source thread. The behavior depends on the OM scope:

• Thread-scoped OM: The OM record is cloned to the new thread. All internal message ID references are remapped to point to the cloned messages.
• Resource-scoped OM (same resourceId): The OM record is shared between the source and cloned threads since they belong to the same resource. No duplication occurs.
• Resource-scoped OM (different resourceId): The OM record is cloned to the new resource. Message IDs are remapped and any thread-identifying tags within observations are updated to reference the cloned thread.

Only the current (most recent) OM generation is cloned — older history generations aren't copied. Transient processing state (observation/reflection in-progress flags) is reset on the cloned record.