{/* TRANSLATED — 已翻译为中文 */}

> ## 文档索引
> 在此处获取完整文档索引：https://code.claude.com/docs/llms.txt
> 使用此文件发现所有可用页面，然后再进一步探索。

# 实时流式响应

> 在文本和工具调用流入时从 Agent SDK 获取实时响应

默认情况下，Agent SDK 在 Claude 完成生成每个响应后输出完整的 `AssistantMessage` 对象。要在生成文本和工具调用时接收增量更新，请在选项中将 `include_partial_messages`（Python）或 `includePartialMessages`（TypeScript）设置为 `true` 来启用部分消息流式传输。

<Tip>
  本页介绍输出流式传输（实时接收令牌）。有关输入模式（如何发送消息），请参阅[向智能体发送消息](/en/agent-sdk/streaming-vs-single-mode)。你也可以[通过 CLI 使用 Agent SDK 流式传输响应](/en/headless)。
</Tip>

## 启用流式输出

要启用流式传输，请在选项中将 `include_partial_messages`（Python）或 `includePartialMessages`（TypeScript）设置为 `true`。这会使 SDK 在到达时输出包含原始 API 事件的 `StreamEvent` 消息，以及通常的 `AssistantMessage` 和 `ResultMessage`。

然后你的代码需要：

1. 检查每条消息的类型以区分 `StreamEvent` 和其他消息类型
2. 对于 `StreamEvent`，提取 `event` 字段并检查其 `type`
3. 查找 `delta.type` 为 `text_delta` 的 `content_block_delta` 事件，这些事件包含实际的文本块

以下示例启用流式传输并在文本块到达时打印它们。注意嵌套的类型检查：首先检查 `StreamEvent`，然后检查 `content_block_delta`，最后检查 `text_delta`：

<CodeGroup>
  ```python Python theme={null}
  from claude_agent_sdk import query, ClaudeAgentOptions
  from claude_agent_sdk.types import StreamEvent
  import asyncio


  async def stream_response():
      options = ClaudeAgentOptions(
          include_partial_messages=True,
          allowed_tools=["Bash", "Read"],
      )

      async for message in query(prompt="List the files in my project", options=options):
          if isinstance(message, StreamEvent):
              event = message.event
              if event.get("type") == "content_block_delta":
                  delta = event.get("delta", {})
                  if delta.get("type") == "text_delta":
                      print(delta.get("text", ""), end="", flush=True)


  asyncio.run(stream_response())
  ```

  ```typescript TypeScript theme={null}
  import { query } from "@anthropic-ai/claude-agent-sdk";

  for await (const message of query({
    prompt: "List the files in my project",
    options: {
      includePartialMessages: true,
      allowedTools: ["Bash", "Read"]
    }
  })) {
    if (message.type === "stream_event") {
      const event = message.event;
      if (event.type === "content_block_delta") {
        if (event.delta.type === "text_delta") {
          process.stdout.write(event.delta.text);
        }
      }
    }
  }
  ```
</CodeGroup>

## StreamEvent 参考

启用部分消息后，你会收到包装在对象中的原始 Claude API 流式事件。该类型在每个 SDK 中有不同的名称：

* **Python**：`StreamEvent`（从 `claude_agent_sdk.types` 导入）
* **TypeScript**：`SDKPartialAssistantMessage`，`type: 'stream_event'`

两者都包含原始 Claude API 事件，而非累积的文本。你需要自己提取和累积文本增量。以下是每种类型的结构：

<CodeGroup>
  ```python Python theme={null}
  @dataclass
  class StreamEvent:
      uuid: str  # Unique identifier for this event
      session_id: str  # Session identifier
      event: dict[str, Any]  # The raw Claude API stream event
      parent_tool_use_id: str | None  # Parent tool ID if from a subagent
  ```

  ```typescript TypeScript theme={null}
  type SDKPartialAssistantMessage = {
    type: "stream_event";
    event: BetaRawMessageStreamEvent; // From Anthropic SDK
    parent_tool_use_id: string | null;
    uuid: UUID;
    session_id: string;
  };
  ```
</CodeGroup>

`event` 字段包含来自 [Claude API](https://platform.claude.com/docs/en/build-with-claude/streaming#event-types) 的原始流式事件。常见的事件类型包括：

| 事件类型              | 描述                                       |
| :-------------------- | :----------------------------------------- |
| `message_start`       | 新消息的开始                               |
| `content_block_start` | 新内容块的开始（文本或工具使用）           |
| `content_block_delta` | 内容的增量更新                             |
| `content_block_stop`  | 内容块的结束                               |
| `message_delta`       | 消息级更新（停止原因、使用量）             |
| `message_stop`        | 消息的结束                                 |

## 消息流

启用部分消息后，你按此顺序接收消息：

```text theme={null}
StreamEvent (message_start)
StreamEvent (content_block_start) - text block
StreamEvent (content_block_delta) - text chunks...
StreamEvent (content_block_stop)
StreamEvent (content_block_start) - tool_use block
StreamEvent (content_block_delta) - tool input chunks...
StreamEvent (content_block_stop)
StreamEvent (message_delta)
StreamEvent (message_stop)
AssistantMessage - complete message with all content
... tool executes ...
... more streaming events for next turn ...
ResultMessage - final result
```

未启用部分消息时（Python 中的 `include_partial_messages`，TypeScript 中的 `includePartialMessages`），你会收到除 `StreamEvent` 之外的所有消息类型。常见类型包括 `SystemMessage`（会话初始化）、`AssistantMessage`（完整响应）、`ResultMessage`（最终结果）以及指示对话历史何时被压缩的压缩边界消息（TypeScript 中的 `SDKCompactBoundaryMessage`；Python 中 subtype 为 `"compact_boundary"` 的 `SystemMessage`）。

## 流式文本响应

要在文本生成时显示它，查找 `delta.type` 为 `text_delta` 的 `content_block_delta` 事件。这些事件包含增量文本块。以下示例在每个块到达时打印它：

<CodeGroup>
  ```python Python theme={null}
  from claude_agent_sdk import query, ClaudeAgentOptions
  from claude_agent_sdk.types import StreamEvent
  import asyncio


  async def stream_text():
      options = ClaudeAgentOptions(include_partial_messages=True)

      async for message in query(prompt="Explain how databases work", options=options):
          if isinstance(message, StreamEvent):
              event = message.event
              if event.get("type") == "content_block_delta":
                  delta = event.get("delta", {})
                  if delta.get("type") == "text_delta":
                      # Print each text chunk as it arrives
                      print(delta.get("text", ""), end="", flush=True)

      print()  # Final newline


  asyncio.run(stream_text())
  ```

  ```typescript TypeScript theme={null}
  import { query } from "@anthropic-ai/claude-agent-sdk";

  for await (const message of query({
    prompt: "Explain how databases work",
    options: { includePartialMessages: true }
  })) {
    if (message.type === "stream_event") {
      const event = message.event;
      if (event.type === "content_block_delta" && event.delta.type === "text_delta") {
        process.stdout.write(event.delta.text);
      }
    }
  }

  console.log(); // Final newline
  ```
</CodeGroup>

## 流式工具调用

工具调用也是增量流式传输的。你可以跟踪工具何时开始、在生成时接收其输入以及查看它们何时完成。以下示例跟踪当前正在调用的工具，并在 JSON 输入流入时累积它。它使用三种事件类型：

* `content_block_start`：工具开始
* 带有 `input_json_delta` 的 `content_block_delta`：输入块到达
* `content_block_stop`：工具调用完成

<CodeGroup>
  ```python Python theme={null}
  from claude_agent_sdk import query, ClaudeAgentOptions
  from claude_agent_sdk.types import StreamEvent
  import asyncio


  async def stream_tool_calls():
      options = ClaudeAgentOptions(
          include_partial_messages=True,
          allowed_tools=["Read", "Bash"],
      )

      # Track the current tool and accumulate its input JSON
      current_tool = None
      tool_input = ""

      async for message in query(prompt="Read the README.md file", options=options):
          if isinstance(message, StreamEvent):
              event = message.event
              event_type = event.get("type")

              if event_type == "content_block_start":
                  # New tool call is starting
                  content_block = event.get("content_block", {})
                  if content_block.get("type") == "tool_use":
                      current_tool = content_block.get("name")
                      tool_input = ""
                      print(f"Starting tool: {current_tool}")

              elif event_type == "content_block_delta":
                  delta = event.get("delta", {})
                  if delta.get("type") == "input_json_delta":
                      # Accumulate JSON input as it streams in
                      chunk = delta.get("partial_json", "")
                      tool_input += chunk
                      print(f"  Input chunk: {chunk}")

              elif event_type == "content_block_stop":
                  # Tool call complete - show final input
                  if current_tool:
                      print(f"Tool {current_tool} called with: {tool_input}")
                      current_tool = None


  asyncio.run(stream_tool_calls())
  ```

  ```typescript TypeScript theme={null}
  import { query } from "@anthropic-ai/claude-agent-sdk";

  // Track the current tool and accumulate its input JSON
  let currentTool: string | null = null;
  let toolInput = "";

  for await (const message of query({
    prompt: "Read the README.md file",
    options: {
      includePartialMessages: true,
      allowedTools: ["Read", "Bash"]
    }
  })) {
    if (message.type === "stream_event") {
      const event = message.event;

      if (event.type === "content_block_start") {
        // New tool call is starting
        if (event.content_block.type === "tool_use") {
          currentTool = event.content_block.name;
          toolInput = "";
          console.log(`Starting tool: ${currentTool}`);
        }
      } else if (event.type === "content_block_delta") {
        if (event.delta.type === "input_json_delta") {
          // Accumulate JSON input as it streams in
          const chunk = event.delta.partial_json;
          toolInput += chunk;
          console.log(`  Input chunk: ${chunk}`);
        }
      } else if (event.type === "content_block_stop") {
        // Tool call complete - show final input
        if (currentTool) {
          console.log(`Tool ${currentTool} called with: ${toolInput}`);
          currentTool = null;
        }
      }
    }
  }
  ```
</CodeGroup>

## 构建流式 UI

此示例将文本和工具流式传输组合到一个连贯的 UI 中。它跟踪智能体当前是否正在执行工具（使用 `in_tool` 标志），以便在工具运行时显示 `[Using Read...]` 等状态指示器。不在工具中时文本正常流式传输，工具完成触发"完成"消息。此模式适用于需要在多步骤智能体任务期间显示进度的聊天界面。

<CodeGroup>
  ```python Python theme={null}
  from claude_agent_sdk import query, ClaudeAgentOptions, ResultMessage
  from claude_agent_sdk.types import StreamEvent
  import asyncio
  import sys


  async def streaming_ui():
      options = ClaudeAgentOptions(
          include_partial_messages=True,
          allowed_tools=["Read", "Bash", "Grep"],
      )

      # Track whether we're currently in a tool call
      in_tool = False

      async for message in query(
          prompt="Find all TODO comments in the codebase", options=options
      ):
          if isinstance(message, StreamEvent):
              event = message.event
              event_type = event.get("type")

              if event_type == "content_block_start":
                  content_block = event.get("content_block", {})
                  if content_block.get("type") == "tool_use":
                      # Tool call is starting - show status indicator
                      tool_name = content_block.get("name")
                      print(f"\n[Using {tool_name}...]", end="", flush=True)
                      in_tool = True

              elif event_type == "content_block_delta":
                  delta = event.get("delta", {})
                  # Only stream text when not executing a tool
                  if delta.get("type") == "text_delta" and not in_tool:
                      sys.stdout.write(delta.get("text", ""))
                      sys.stdout.flush()

              elif event_type == "content_block_stop":
                  if in_tool:
                      # Tool call finished
                      print(" done", flush=True)
                      in_tool = False

          elif isinstance(message, ResultMessage):
              # Agent finished all work
              print(f"\n\n--- Complete ---")


  asyncio.run(streaming_ui())
  ```

  ```typescript TypeScript theme={null}
  import { query } from "@anthropic-ai/claude-agent-sdk";

  // Track whether we're currently in a tool call
  let inTool = false;

  for await (const message of query({
    prompt: "Find all TODO comments in the codebase",
    options: {
      includePartialMessages: true,
      allowedTools: ["Read", "Bash", "Grep"]
    }
  })) {
    if (message.type === "stream_event") {
      const event = message.event;

      if (event.type === "content_block_start") {
        if (event.content_block.type === "tool_use") {
          // Tool call is starting - show status indicator
          process.stdout.write(`\n[Using ${event.content_block.name}...]`);
          inTool = true;
        }
      } else if (event.type === "content_block_delta") {
        // Only stream text when not executing a tool
        if (event.delta.type === "text_delta" && !inTool) {
          process.stdout.write(event.delta.text);
        }
      } else if (event.type === "content_block_stop") {
        if (inTool) {
          // Tool call finished
          console.log(" done");
          inTool = false;
        }
      }
    } else if (message.type === "result") {
      // Agent finished all work
      console.log("\n\n--- Complete ---");
    }
  }
  ```
</CodeGroup>

## 已知限制

某些 SDK 功能与流式传输不兼容：

* **扩展思考**：当你显式设置 `max_thinking_tokens`（Python）或 `maxThinkingTokens`（TypeScript）时，不会发出 `StreamEvent` 消息。你只会在每轮之后收到完整消息。请注意，SDK 中默认禁用思考，因此除非你启用它，否则流式传输可以正常工作。
* **结构化输出**：JSON 结果仅出现在最终的 `ResultMessage.structured_output` 中，而非作为流式增量。有关详情，请参阅[结构化输出](/en/agent-sdk/structured-outputs)。

## 后续步骤

现在你可以实时流式传输文本和工具调用了，探索以下相关主题：

* [交互式与一次性查询](/en/agent-sdk/streaming-vs-single-mode)：为你的用例选择输入模式
* [结构化输出](/en/agent-sdk/structured-outputs)：从智能体获取类型化的 JSON 响应
* [权限](/en/agent-sdk/permissions)：控制智能体可以使用哪些工具