> ## Documentation Index
> Fetch the complete documentation index at: https://code.claude.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# 即時串流回應

> 當文字和工具呼叫串流進來時，從 Agent SDK 取得即時回應

根據預設，Agent SDK 會在 Claude 完成生成每個回應後產生完整的 `AssistantMessage` 物件。若要在文字和工具呼叫生成時接收增量更新，請在選項中將 `include_partial_messages`（Python）或 `includePartialMessages`（TypeScript）設定為 `true` 來啟用部分訊息串流。

<Tip>
  本頁涵蓋輸出串流（即時接收權杖）。如需輸入模式（如何傳送訊息），請參閱[傳送訊息給代理](/zh-TW/agent-sdk/streaming-vs-single-mode)。您也可以[透過 CLI 使用 Agent SDK 串流回應](/zh-TW/headless)。
</Tip>

<h2 id="enable-streaming-output">
  啟用串流輸出
</h2>

若要啟用串流，請在選項中將 `include_partial_messages`（Python）或 `includePartialMessages`（TypeScript）設定為 `true`。這會導致 SDK 產生包含原始 API 事件的 `StreamEvent` 訊息（當它們到達時），以及通常的 `AssistantMessage` 和 `ResultMessage`。

您的程式碼需要：

1. 檢查每個訊息的類型以區分 `StreamEvent` 和其他訊息類型
2. 對於 `StreamEvent`，提取 `event` 欄位並檢查其 `type`
3. 尋找 `content_block_delta` 事件，其中 `delta.type` 是 `text_delta`，其中包含實際的文字區塊

下面的範例啟用串流並在文字區塊到達時列印它們。注意巢狀類型檢查：首先是 `StreamEvent`，然後是 `content_block_delta`，然後是 `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>

<h2 id="streamevent-reference">
  StreamEvent 參考
</h2>

啟用部分訊息時，您會收到包裝在物件中的原始 Claude API 串流事件。該類型在每個 SDK 中有不同的名稱：

* **Python**：`StreamEvent`（從 `claude_agent_sdk.types` 匯入）
* **TypeScript**：`SDKPartialAssistantMessage`，其中 `type: 'stream_event'`

兩者都包含原始 Claude API 事件，而不是累積的文字。您需要自己提取和累積文字增量。以下是每種類型的結構：

<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  # Always None
  ```

  ```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;
    ttft_ms?: number; // Time to first token in ms, present only on message_start events
  };
  ```
</CodeGroup>

`parent_tool_use_id` 欄位在 Python 中始終為 `None`，在 TypeScript 中始終為 `null`。串流事件僅針對主工作階段發出；來自子代理的令牌級增量不會被轉發。若要將輸出歸因於子代理，請使用完整訊息，其中包含 `parent_tool_use_id`。請參閱[偵測子代理叫用](/zh-TW/agent-sdk/subagents#detect-subagent-invocation)。

`event` 欄位包含來自 [Claude API](https://platform.claude.com/docs/en/build-with-claude/streaming#event-types) 的原始串流事件。常見的事件類型包括：

| 事件類型                  | 說明                 |
| :-------------------- | :----------------- |
| `message_start`       | 新訊息的開始             |
| `content_block_start` | 新內容區塊的開始（文字或工具使用）  |
| `content_block_delta` | 內容的增量更新            |
| `content_block_stop`  | 內容區塊的結束            |
| `message_delta`       | 訊息層級的更新（停止原因、使用情況） |
| `message_stop`        | 訊息的結束              |

<h2 id="message-flow">
  訊息流
</h2>

啟用部分訊息後，您會按此順序接收訊息：

```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
```

未啟用部分訊息（Python 中的 `include_partial_messages`、TypeScript 中的 `includePartialMessages`）時，您會收到除 `StreamEvent` 外的所有訊息類型。常見類型包括 `SystemMessage`（工作階段初始化）、`AssistantMessage`（完整回應）、`ResultMessage`（最終結果）和指示何時壓縮對話歷史記錄的緊湊邊界訊息（TypeScript 中的 `SDKCompactBoundaryMessage`；Python 中具有子類型 `"compact_boundary"` 的 `SystemMessage`）。

<h2 id="stream-text-responses">
  串流文字回應
</h2>

若要在生成文字時顯示它，請尋找 `content_block_delta` 事件，其中 `delta.type` 是 `text_delta`。這些包含增量文字區塊。下面的範例在每個區塊到達時列印它：

<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>

<h2 id="stream-tool-calls">
  串流工具呼叫
</h2>

工具呼叫也會增量串流。您可以追蹤工具何時開始、在生成時接收其輸入，以及查看何時完成。下面的範例追蹤目前被呼叫的工具並在串流進來時累積 JSON 輸入。它使用三種事件類型：

* `content_block_start`：工具開始
* `content_block_delta` 搭配 `input_json_delta`：輸入區塊到達
* `content_block_stop`：工具呼叫完成

<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>

<h2 id="build-a-streaming-ui">
  建立串流 UI
</h2>

此範例將文字和工具串流結合成一個有凝聚力的 UI。它追蹤代理目前是否正在執行工具（使用 `in_tool` 旗標）以顯示狀態指示器，例如在工具執行時顯示 `[Using Read...]`。文字在不在工具中時正常串流，工具完成會觸發「完成」訊息。此模式對於需要在多步驟代理任務期間顯示進度的聊天介面很有用。

<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>

<h2 id="known-limitations">
  已知限制
</h2>

* **結構化輸出**：JSON 結果僅出現在最終 `ResultMessage.structured_output` 中，而不是作為串流增量。如需詳細資訊，請參閱[結構化輸出](/zh-TW/agent-sdk/structured-outputs)。

<h2 id="next-steps">
  後續步驟
</h2>

現在您可以即時串流文字和工具呼叫，請探索這些相關主題：

* [互動式與一次性查詢](/zh-TW/agent-sdk/streaming-vs-single-mode)：為您的使用案例選擇輸入模式
* [結構化輸出](/zh-TW/agent-sdk/structured-outputs)：從代理取得類型化的 JSON 回應
* [權限](/zh-TW/agent-sdk/permissions)：控制代理可以使用哪些工具