📄 ai-sdk/docs/reference/ai-sdk-ui/prune-messages

File: prune-messages.md | Updated: 11/15/2025

Source: https://ai-sdk.dev/docs/reference/ai-sdk-ui/prune-messages

AI SDK

Menu

v5 (Latest)

AI SDK 5.x

AI SDK by Vercel

AI SDK 6 Beta

Foundations

Overview

Providers and Models

Prompts

Tools

Streaming

Getting Started

Navigating the Library

Next.js App Router

Next.js Pages Router

Svelte

Vue.js (Nuxt)

Node.js

Expo

Agents

Agents

Building Agents

Workflow Patterns

Loop Control

AI SDK Core

Overview

Generating Text

Generating Structured Data

Tool Calling

Model Context Protocol (MCP) Tools

Prompt Engineering

Settings

Embeddings

Image Generation

Transcription

Speech

Language Model Middleware

Provider & Model Management

Error Handling

Testing

Telemetry

AI SDK UI

Overview

Chatbot

Chatbot Message Persistence

Chatbot Resume Streams

Chatbot Tool Usage

Generative User Interfaces

Completion

Object Generation

Streaming Custom Data

Error Handling

Transport

Reading UIMessage Streams

Message Metadata

Stream Protocols

AI SDK RSC

Advanced

Reference

AI SDK Core

AI SDK UI

useChat

useCompletion

useObject

convertToModelMessages

pruneMessages

createUIMessageStream

createUIMessageStreamResponse

pipeUIMessageStreamToResponse

readUIMessageStream

InferUITools

InferUITool

AI SDK RSC

Stream Helpers

AI SDK Errors

Migration Guides

Troubleshooting

Copy markdown

pruneMessages()

==============================================================================================

The pruneMessages function is used to prune or filter an array of ModelMessage objects. This is useful for reducing message context (to save tokens), removing intermediate reasoning, or trimming tool calls and empty messages before sending to an LLM.

app/api/chat/route.ts

import { pruneMessages, streamText } from 'ai';
export async function POST(req: Request) {  const { messages } = await req.json();
  const prunedMessages = pruneMessages({    messages,    reasoning: 'before-last-message',    toolCalls: 'before-last-2-messages',    emptyMessages: 'remove',  });
  const result = streamText({    model: 'openai/gpt-4o',    messages: prunedMessages,  });
  return result.toUIMessageStreamResponse();}

Import


import { pruneMessages } from "ai"

API Signature


Parameters

messages:

ModelMessage[]

An array of ModelMessage objects to prune.

reasoning:

'all' | 'before-last-message' | 'none'

How to remove reasoning content from assistant messages. Default: "none".

toolCalls:

'all' | 'before-last-message' | 'before-last-${number}-messages' | 'none' | PruneToolCallsOption[]

How to prune tool call/results/approval content. Can specify strategy or a list with tools.

emptyMessages:

'keep' | 'remove'

Whether to keep or remove messages whose content is empty after pruning. Default: "remove".

Returns

An array of ModelMessage objects, pruned according to the provided options.

ModelMessage[]:

Array

The pruned list of ModelMessage objects

Example Usage


import { pruneMessages } from 'ai';
const pruned = pruneMessages({  messages,  reasoning: 'all', // Remove all reasoning parts  toolCalls: 'before-last-message', // Remove tool calls except those in the last message});

Pruning Options


  • reasoning: Removes reasoning parts from assistant messages. Use 'all' to remove all, 'before-last-message' to keep reasoning in the last message, or 'none' to retain all reasoning.
  • toolCalls: Prune tool-call, tool-result, and tool-approval chunks from assistant/tool messages. Options include:
    • 'all': Prune all such content.
    • 'before-last-message': Prune except in the last message.
    • before-last-N-messages: Prune except in the last N messages.
    • 'none': Do not prune.
    • Or provide an array for per-tool fine control.
  • emptyMessages: Set to 'remove' (default) to exclude messages that have no content after pruning.

Tip: pruneMessages is typically used prior to sending a context window to an LLM to reduce message/token count, especially after a series of tool-calls and approvals.

For advanced usage and the full list of possible message parts, see ModelMessage and pruneMessages implementation .

On this page

pruneMessages()

Import

API Signature

Parameters

Returns

Example Usage

Pruning Options

Deploy and Scale AI Apps with Vercel.

Vercel delivers the infrastructure and developer experience you need to ship reliable AI-powered applications at scale.

Trusted by industry leaders:

  • OpenAI
  • Photoroom
  • leonardo-ai Logoleonardo-ai Logo
  • zapier Logozapier Logo

Talk to an expert