本页目录7
- 需在 options 中设置 Python 的 include_partial_messages 或 TypeScript 的 includePartialMessages 为 true,才会额外收到 StreamEvent(Python)/type 为 stream_event 的 SDKPartialAssistantMessage(TypeScript)
- StreamEvent/stream_event 消息只携带 Claude API 原始事件(如 content_block_delta),需要自己判断 delta.type 是否为 text_delta 或 input_json_delta 并手动拼接文本/JSON
- 流式事件仅针对主会话发出,子代理(subagent)的逐 token 增量不会转发,要归因到子代理需使用带 parent_tool_use_id 的完整消息
- 消息顺序固定为:message_start → content_block_start → content_block_delta(多个)→ content_block_stop → …→ message_delta → message_stop,随后才是完整的 AssistantMessage 和最终的 ResultMessage
- 结构化输出(structured output)只会出现在最终 ResultMessage.structured_output 里,不会以流式增量形式提前给出
本文是对 Claude Agent SDK 官方文档「Stream responses in real-time」页面的中文整理,完整与最新内容以原文为准:https://code.claude.com/docs/en/agent-sdk/streaming-output
默认情况下,Agent SDK 会在 Claude 生成完每一条完整响应后,才产出完整的 AssistantMessage 对象。若要在文本和工具调用生成过程中实时接收增量更新,需要启用「partial message streaming」(部分消息流式传输)。
提示:本页只讲输出流式传输(实时接收 token)。关于输入模式(如何发送消息),请参见「Send messages to agents」(/docs/en/agent-sdk/streaming-vs-single-mode)。你也可以通过 CLI 使用 Agent SDK 进行流式响应(/docs/en/headless)。
启用流式输出
要启用流式传输,需在 options 中将 Python 的 include_partial_messages 或 TypeScript 的 includePartialMessages 设为 true。这会使 SDK 在正常的 AssistantMessage 和 ResultMessage 之外,额外产出包含原始 API 事件的 StreamEvent 消息。
你的代码需要做以下几件事:
- 检查每条消息的类型,把
StreamEvent与其他消息类型区分开 - 对于
StreamEvent,取出event字段并检查其type - 寻找
delta.type为text_delta的content_block_delta事件,这类事件包含真正的文本片段
下面的例子启用了流式传输,并在文本片段到达时打印出来。注意其中的嵌套类型判断:先判断是否 StreamEvent,再判断是否 content_block_delta,最后判断是否 text_delta:
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())
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);
}
}
}
}
StreamEvent 参考
启用部分消息后,你会收到包装在一个对象中的、原始的 Claude API 流式事件。该类型在两个 SDK 中名称不同:
- 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,而非累加好的文本——你需要自己提取并累加文本增量。以下是各自的结构:
@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
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
};
parent_tool_use_id 字段在 Python 中始终为 None,在 TypeScript 中始终为 null。流式事件只针对主会话发出;子代理(subagent)的逐 token 增量不会被转发。若要将输出归因到某个子代理,请使用携带 parent_tool_use_id 的完整消息。参见「Detect subagent invocation」(/docs/en/agent-sdk/subagents#detect-subagent-invocation)。
event 字段包含来自 Claude API 的原始流式事件。常见的事件类型包括:
| 事件类型 (Event Type) | 说明 |
|---|---|
message_start | 新消息开始 |
content_block_start | 新内容块(文本或工具调用)开始 |
content_block_delta | 内容的增量更新 |
content_block_stop | 内容块结束 |
message_delta | 消息级别的更新(停止原因、用量) |
message_stop | 消息结束 |
消息流顺序
启用部分消息后,你会按以下顺序收到消息:
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,你会收到除 StreamEvent 以外的所有消息类型。常见类型包括 SystemMessage(会话初始化)、AssistantMessage(完整响应)、ResultMessage(最终结果),以及一个表示对话历史何时被压缩的边界消息(TypeScript 中为 SDKCompactBoundaryMessage;Python 中为子类型是 "compact_boundary" 的 SystemMessage)。
流式接收工具调用
工具调用同样是增量流式传输的。你可以追踪工具何时开始、其输入内容如何逐步生成、以及何时完成。下面的例子追踪当前被调用的工具,并累加流式到来的 JSON 输入。它用到了三种事件类型:
content_block_start:工具开始content_block_delta(附带input_json_delta):输入片段到达content_block_stop:工具调用完成
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())
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;
}
}
}
}
构建一个流式 UI
这个例子将文本流和工具流结合成一个完整的 UI。它用一个 in_tool 标志追踪当前是否正在执行工具,以便在工具运行期间显示类似 [Using Read...] 的状态提示。未处于工具调用中时正常流式输出文本,工具完成时触发一条「done」消息。这种模式适用于需要在多步骤代理任务中展示进度的聊天界面。
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())
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 ---");
}
}
已知限制
- 结构化输出(Structured output):JSON 结果只会出现在最终的
ResultMessage.structured_output中,不会以流式增量的形式给出。详见「structured outputs」(/docs/en/agent-sdk/structured-outputs)。
下一步
现在你已经可以实时流式接收文本和工具调用,可以进一步了解以下相关主题:
- 「Interactive vs one-shot queries」(/docs/en/agent-sdk/streaming-vs-single-mode):为你的使用场景选择合适的输入模式
- 「Structured outputs」(/docs/en/agent-sdk/structured-outputs):从代理获取类型化的 JSON 响应
- 「Permissions」(/docs/en/agent-sdk/permissions):控制代理可以使用哪些工具