# Streaming Input

> Source: https://platform.claude.com/docs/en/agent-sdk/streaming-vs-single-mode
> Extracted: 2026-03-31

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.

### 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

```typescript
import { query } from "@anthropic-ai/claude-agent-sdk";
import { readFile } from "fs/promises";

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: await readFile("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);
  }
}
```

```python
from claude_agent_sdk import (
    ClaudeSDKClient,
    ClaudeAgentOptions,
    AssistantMessage,
    TextBlock,
)
import asyncio
import base64


async def streaming_analysis():
    async def message_generator():
        # First message
        yield {
            "type": "user",
            "message": {
                "role": "user",
                "content": "Analyze this codebase for security issues",
            },
        }

        # Wait for conditions
        await asyncio.sleep(2)

        # Follow-up with image
        with open("diagram.png", "rb") as f:
            image_data = base64.b64encode(f.read()).decode()

        yield {
            "type": "user",
            "message": {
                "role": "user",
                "content": [
                    {"type": "text", "text": "Review this architecture diagram"},
                    {
                        "type": "image",
                        "source": {
                            "type": "base64",
                            "media_type": "image/png",
                            "data": image_data,
                        },
                    },
                ],
            },
        }

    # Use ClaudeSDKClient for streaming input
    options = ClaudeAgentOptions(max_turns=10, allowed_tools=["Read", "Grep"])

    async with ClaudeSDKClient(options) as client:
        # Send streaming input
        await client.query(message_generator())

        # Process responses
        async for message in client.receive_response():
            if isinstance(message, AssistantMessage):
                for block in message.content:
                    if isinstance(block, TextBlock):
                        print(block.text)


asyncio.run(streaming_analysis())
```

## 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

```typescript
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);
  }
}
```

```python
from claude_agent_sdk import query, ClaudeAgentOptions, ResultMessage
import asyncio


async def single_message_example():
    # Simple one-shot query using query() function
    async for message in query(
        prompt="Explain the authentication flow",
        options=ClaudeAgentOptions(max_turns=1, allowed_tools=["Read", "Grep"]),
    ):
        if isinstance(message, ResultMessage):
            print(message.result)

    # Continue conversation with session management
    async for message in query(
        prompt="Now explain the authorization process",
        options=ClaudeAgentOptions(continue_conversation=True, max_turns=1),
    ):
        if isinstance(message, ResultMessage):
            print(message.result)


asyncio.run(single_message_example())
```
