Search All Messages

client.messages.search(, ?): MessageSearchResponse { , , , }

post/v1/messages/search

Search messages across the organization with optional agent filtering. Returns messages with FTS/vector ranks and total RRF score.

This is a cloud-only feature.

ParametersExpand Collapse

body: MessageSearchParams { query, agent_id, conversation_id, 4 more }

query: string

Text query for full-text search

agent_id?: string | null

Filter messages by agent ID

conversation_id?: string | null

Filter messages by conversation ID

end_date?: string | null

Filter messages created on or before this date

formatdate-time

limit?: number

Maximum number of results to return

maximum100

minimum1

search_mode?: "vector" | "fts" | "hybrid"

Search mode to use

Accepts one of the following:

"vector"

"fts"

"hybrid"

start_date?: string | null

Filter messages created after this date

formatdate-time

ReturnsExpand Collapse

MessageSearchResponse = Array<SystemMessageListResult { content, created_at, message_id, 2 more } | UserMessageListResult { content, created_at, message_id, 2 more } | ReasoningMessageListResult { created_at, message_id, reasoning, 2 more } | AssistantMessageListResult { content, created_at, message_id, 2 more } >

Accepts one of the following:

SystemMessageListResult { content, created_at, message_id, 2 more }

System message list result with agent context.

Shape is identical to UpdateSystemMessage but includes the owning agent_id and message id.

content: string

The message content sent by the system (can be a string or an array of multi-modal content parts)

created_at: string

The time the message was created in ISO format.

formatdate-time

message_id: string

The unique identifier of the message.

agent_id?: string | null

The unique identifier of the agent that owns the message.

message_type?: "system_message"

UserMessageListResult { content, created_at, message_id, 2 more }

User message list result with agent context.

Shape is identical to UpdateUserMessage but includes the owning agent_id and message id.

content: Array<LettaUserMessageContentUnion> | string

The message content sent by the user (can be a string or an array of multi-modal content parts)

Accepts one of the following:

Array<LettaUserMessageContentUnion>

TextContent { text, signature, type }

text: string

The text content of the message.

signature?: string | null

Stores a unique identifier for any reasoning associated with this text content.

type?: "text"

The type of the message.

ImageContent { source, type }

source: URLImage { url, type } | Base64Image { data, media_type, detail, type } | LettaImage { file_id, data, detail, 2 more }

The source of the image.

Accepts one of the following:

URLImage { url, type }

url: string

The URL of the image.

type?: "url"

The source type for the image.

Base64Image { data, media_type, detail, type }

data: string

The base64 encoded image data.

media_type: string

The media type for the image.

detail?: string | null

What level of detail to use when processing and understanding the image (low, high, or auto to let the model decide)

type?: "base64"

The source type for the image.

LettaImage { file_id, data, detail, 2 more }

file_id: string

The unique identifier of the image file persisted in storage.

data?: string | null

The base64 encoded image data.

detail?: string | null

What level of detail to use when processing and understanding the image (low, high, or auto to let the model decide)

media_type?: string | null

The media type for the image.

type?: "letta"

The source type for the image.

type?: "image"

The type of the message.

string

created_at: string

The time the message was created in ISO format.

formatdate-time

message_id: string

The unique identifier of the message.

agent_id?: string | null

The unique identifier of the agent that owns the message.

message_type?: "user_message"

ReasoningMessageListResult { created_at, message_id, reasoning, 2 more }

Reasoning message list result with agent context.

Shape is identical to UpdateReasoningMessage but includes the owning agent_id and message id.

created_at: string

The time the message was created in ISO format.

formatdate-time

message_id: string

The unique identifier of the message.

reasoning: string

agent_id?: string | null

The unique identifier of the agent that owns the message.

message_type?: "reasoning_message"

AssistantMessageListResult { content, created_at, message_id, 2 more }

Assistant message list result with agent context.

Shape is identical to UpdateAssistantMessage but includes the owning agent_id and message id.

content: Array<LettaAssistantMessageContentUnion { text, signature, type } > | string

The message content sent by the assistant (can be a string or an array of content parts)

Accepts one of the following:

Array<LettaAssistantMessageContentUnion { text, signature, type } >

text: string

The text content of the message.

signature?: string | null

Stores a unique identifier for any reasoning associated with this text content.

type?: "text"

The type of the message.

string

created_at: string

The time the message was created in ISO format.

formatdate-time

message_id: string

The unique identifier of the message.

agent_id?: string | null

The unique identifier of the agent that owns the message.

message_type?: "assistant_message"

Search All Messages

import Letta from '@letta-ai/letta-client';

const client = new Letta({
  apiKey: process.env['LETTA_API_KEY'], // This is the default and can be omitted
});

const response = await client.messages.search({ query: 'query' });

console.log(response);

[
  {
    "content": "content",
    "created_at": "2019-12-27T18:11:19.117Z",
    "message_id": "message_id",
    "agent_id": "agent_id",
    "message_type": "system_message"
  }
]

Returns Examples

[
  {
    "content": "content",
    "created_at": "2019-12-27T18:11:19.117Z",
    "message_id": "message_id",
    "agent_id": "agent_id",
    "message_type": "system_message"
  }
]