Guides

Streaming Input

Understanding the two input modes for Claude Agent SDK and when to use each

Overview

The Claude Agent SDK supports two distinct input modes for interacting with agents:

Streaming Input Mode (Default & Recommended) - A persistent, interactive session
Single Message Input - One-shot queries that use session state and resuming

This guide explains the differences, benefits, and use cases for each mode to help you choose the right approach for your application.

Streaming Input Mode (Recommended)

Streaming input mode is the preferred way to use the Claude Agent SDK. It provides full access to the agent's capabilities and enables rich, interactive experiences.

It allows the agent to operate as a long lived process that takes in user input, handles interruptions, surfaces permission requests, and handles session management.

How It Works

%%{init: {"theme": "base", "themeVariables": {"edgeLabelBackground": "#F0F0EB", "lineColor": "#91918D", "primaryColor": "#F0F0EB", "primaryTextColor": "#191919", "primaryBorderColor": "#D9D8D5", "secondaryColor": "#F5E6D8", "tertiaryColor": "#CC785C", "noteBkgColor": "#FAF0E6", "noteBorderColor": "#91918D"}, "sequence": {"actorMargin": 50, "width": 150, "height": 65, "boxMargin": 10, "boxTextMargin": 5, "noteMargin": 10, "messageMargin": 35}}}%%
sequenceDiagram
    participant App as Your Application
    participant Agent as Claude Agent
    participant Tools as Tools/Hooks
    participant FS as Environment/<br/>File System
    
    App->>Agent: Initialize with AsyncGenerator
    activate Agent
    
    App->>Agent: Yield Message 1
    Agent->>Tools: Execute tools
    Tools->>FS: Read files
    FS-->>Tools: File contents
    Tools->>FS: Write/Edit files
    FS-->>Tools: Success/Error
    Agent-->>App: Stream partial response
    Agent-->>App: Stream more content...
    Agent->>App: Complete Message 1
    
    App->>Agent: Yield Message 2 + Image
    Agent->>Tools: Process image & execute
    Tools->>FS: Access filesystem
    FS-->>Tools: Operation results
    Agent-->>App: Stream response 2
    
    App->>Agent: Queue Message 3
    App->>Agent: Interrupt/Cancel
    Agent->>App: Handle interruption
    
    Note over App,Agent: Session stays alive
    Note over Tools,FS: Persistent file system<br/>state maintained
    
    deactivate Agent

Benefits

Image Uploads

Attach images directly to messages for visual analysis and understanding

Queued Messages

Send multiple messages that process sequentially, with ability to interrupt

Tool Integration

Full access to all tools and custom MCP servers during the session

Hooks Support

Use lifecycle hooks to customize behavior at various points

Real-time Feedback

See responses as they're generated, not just final results

Context Persistence

Maintain conversation context across multiple turns naturally

Implementation Example

import { query } from "@anthropic-ai/claude-agent-sdk";
import { readFileSync } from "fs";

async function* generateMessages() {
  // First message
  yield {
    type: "user" as const,
    message: {
      role: "user" as const,
      content: "Analyze this codebase for security issues"
    }
  };
  
  // Wait for conditions or user input
  await new Promise(resolve => setTimeout(resolve, 2000));
  
  // Follow-up with image
  yield {
    type: "user" as const,
    message: {
      role: "user" as const,
      content: [
        {
          type: "text",
          text: "Review this architecture diagram"
        },
        {
          type: "image",
          source: {
            type: "base64",
            media_type: "image/png",
            data: readFileSync("diagram.png", "base64")
          }
        }
      ]
    }
  };
}

// Process streaming responses
for await (const message of query({
  prompt: generateMessages(),
  options: {
    maxTurns: 10,
    allowedTools: ["Read", "Grep"]
  }
})) {
  if (message.type === "result") {
    console.log(message.result);
  }
}

Single Message Input

Single message input is simpler but more limited.

When to Use Single Message Input

Use single message input when:

You need a one-shot response
You do not need image attachments, hooks, etc.
You need to operate in a stateless environment, such as a lambda function

Limitations

Single message input mode does not support:

Direct image attachments in messages
Dynamic message queueing
Real-time interruption
Hook integration
Natural multi-turn conversations

Implementation Example

import { query } from "@anthropic-ai/claude-agent-sdk";

// Simple one-shot query
for await (const message of query({
  prompt: "Explain the authentication flow",
  options: {
    maxTurns: 1,
    allowedTools: ["Read", "Grep"]
  }
})) {
  if (message.type === "result") {
    console.log(message.result);
  }
}

// Continue conversation with session management
for await (const message of query({
  prompt: "Now explain the authorization process",
  options: {
    continue: true,
    maxTurns: 1
  }
})) {
  if (message.type === "result") {
    console.log(message.result);
  }
}

Guides

Streaming Input

Understanding the two input modes for Claude Agent SDK and when to use each

Overview

The Claude Agent SDK supports two distinct input modes for interacting with agents:

Streaming Input Mode (Default & Recommended) - A persistent, interactive session
Single Message Input - One-shot queries that use session state and resuming

This guide explains the differences, benefits, and use cases for each mode to help you choose the right approach for your application.

Streaming Input Mode (Recommended)

Streaming input mode is the preferred way to use the Claude Agent SDK. It provides full access to the agent's capabilities and enables rich, interactive experiences.

It allows the agent to operate as a long lived process that takes in user input, handles interruptions, surfaces permission requests, and handles session management.

How It Works

%%{init: {"theme": "base", "themeVariables": {"edgeLabelBackground": "#F0F0EB", "lineColor": "#91918D", "primaryColor": "#F0F0EB", "primaryTextColor": "#191919", "primaryBorderColor": "#D9D8D5", "secondaryColor": "#F5E6D8", "tertiaryColor": "#CC785C", "noteBkgColor": "#FAF0E6", "noteBorderColor": "#91918D"}, "sequence": {"actorMargin": 50, "width": 150, "height": 65, "boxMargin": 10, "boxTextMargin": 5, "noteMargin": 10, "messageMargin": 35}}}%%
sequenceDiagram
    participant App as Your Application
    participant Agent as Claude Agent
    participant Tools as Tools/Hooks
    participant FS as Environment/<br/>File System
    
    App->>Agent: Initialize with AsyncGenerator
    activate Agent
    
    App->>Agent: Yield Message 1
    Agent->>Tools: Execute tools
    Tools->>FS: Read files
    FS-->>Tools: File contents
    Tools->>FS: Write/Edit files
    FS-->>Tools: Success/Error
    Agent-->>App: Stream partial response
    Agent-->>App: Stream more content...
    Agent->>App: Complete Message 1
    
    App->>Agent: Yield Message 2 + Image
    Agent->>Tools: Process image & execute
    Tools->>FS: Access filesystem
    FS-->>Tools: Operation results
    Agent-->>App: Stream response 2
    
    App->>Agent: Queue Message 3
    App->>Agent: Interrupt/Cancel
    Agent->>App: Handle interruption
    
    Note over App,Agent: Session stays alive
    Note over Tools,FS: Persistent file system<br/>state maintained
    
    deactivate Agent

Benefits

Image Uploads

Attach images directly to messages for visual analysis and understanding

Queued Messages

Send multiple messages that process sequentially, with ability to interrupt

Tool Integration

Full access to all tools and custom MCP servers during the session

Hooks Support

Use lifecycle hooks to customize behavior at various points

Real-time Feedback

See responses as they're generated, not just final results

Context Persistence

Maintain conversation context across multiple turns naturally

Implementation Example

import { query } from "@anthropic-ai/claude-agent-sdk";
import { readFileSync } from "fs";

async function* generateMessages() {
  // First message
  yield {
    type: "user" as const,
    message: {
      role: "user" as const,
      content: "Analyze this codebase for security issues"
    }
  };
  
  // Wait for conditions or user input
  await new Promise(resolve => setTimeout(resolve, 2000));
  
  // Follow-up with image
  yield {
    type: "user" as const,
    message: {
      role: "user" as const,
      content: [
        {
          type: "text",
          text: "Review this architecture diagram"
        },
        {
          type: "image",
          source: {
            type: "base64",
            media_type: "image/png",
            data: readFileSync("diagram.png", "base64")
          }
        }
      ]
    }
  };
}

// Process streaming responses
for await (const message of query({
  prompt: generateMessages(),
  options: {
    maxTurns: 10,
    allowedTools: ["Read", "Grep"]
  }
})) {
  if (message.type === "result") {
    console.log(message.result);
  }
}

Single Message Input

Single message input is simpler but more limited.

When to Use Single Message Input

Use single message input when:

You need a one-shot response
You do not need image attachments, hooks, etc.
You need to operate in a stateless environment, such as a lambda function

Limitations

Single message input mode does not support:

Direct image attachments in messages
Dynamic message queueing
Real-time interruption
Hook integration
Natural multi-turn conversations

Implementation Example

import { query } from "@anthropic-ai/claude-agent-sdk";

// Simple one-shot query
for await (const message of query({
  prompt: "Explain the authentication flow",
  options: {
    maxTurns: 1,
    allowedTools: ["Read", "Grep"]
  }
})) {
  if (message.type === "result") {
    console.log(message.result);
  }
}

// Continue conversation with session management
for await (const message of query({
  prompt: "Now explain the authorization process",
  options: {
    continue: true,
    maxTurns: 1
  }
})) {
  if (message.type === "result") {
    console.log(message.result);
  }
}