Overview ↗
noOriginal Documentation
Documentation Index#
Fetch the complete documentation index at: https://docs.langchain.com/llms.txt Use this file to discover all available pages before exploring further.
Stream real-time updates from deep agent runs and subagent execution
Deep agents build on LangGraph’s streaming infrastructure with first-class support for subagent streams. When a deep agent delegates work to subagents, you can stream updates from each subagent independently — tracking progress, LLM tokens, and tool calls in real time.
What’s possible with deep agent streaming:
Stream subagent progress — track each subagent’s execution as it runs in parallel. Stream LLM tokens — stream tokens from the main agent and each subagent. Stream tool calls — see tool calls and results from within subagent execution. Stream custom updates — emit user-defined signals from inside subagent nodes.
Enable subgraph streaming#
Deep agents use LangGraph’s subgraph streaming to surface events from subagent execution. To receive subagent events, enable stream_subgraphs when streaming.
const agent = createDeepAgent({
systemPrompt: "You are a helpful research assistant",
subagents: [
{
name: "researcher",
description: "Researches a topic in depth",
systemPrompt: "You are a thorough researcher.",
},
],
});
for await (const [namespace, chunk] of await agent.stream(
{ messages: [{ role: "user", content: "Research quantum computing advances" }] },
{
streamMode: "updates",
subgraphs: true, // [!code highlight]
}
)) {
if (namespace.length > 0) {
// Subagent event — namespace identifies the source
console.log(`[subagent: ${namespace.join("|")}]`);
} else {
// Main agent event
console.log("[main agent]");
}
console.log(chunk);
}Namespaces#
When subgraphs is enabled, each streaming event includes a namespace that identifies which agent produced it. The namespace is a path of node names and task IDs that represents the agent hierarchy.
| Namespace | Source |
|---|---|
() (empty) | Main agent |
("tools:abc123",) | A subagent spawned by the main agent’s task tool call abc123 |
("tools:abc123", "model_request:def456") | The model request node inside a subagent |
Use namespaces to route events to the correct UI component:
for await (const [namespace, chunk] of await agent.stream(
{ messages: [{ role: "user", content: "Plan my vacation" }] },
{ streamMode: "updates", subgraphs: true }
)) {
// Check if this event came from a subagent
const isSubagent = namespace.some(
(segment: string) => segment.startsWith("tools:")
);
if (isSubagent) {
// Extract the tool call ID from the namespace
const toolCallId = namespace
.find((s: string) => s.startsWith("tools:"))
?.split(":")[1];
console.log(`Subagent ${toolCallId}:`, chunk);
} else {
console.log("Main agent:", chunk);
}
}Subagent progress#
Use stream_mode="updates" to track subagent progress as each step completes. This is useful for showing which subagents are active and what work they’ve completed.
const agent = createDeepAgent({
systemPrompt:
"You are a project coordinator. Always delegate research tasks " +
"to your researcher subagent using the task tool. Keep your final response to one sentence.",
subagents: [
{
name: "researcher",
description: "Researches topics thoroughly",
systemPrompt:
"You are a thorough researcher. Research the given topic " +
"and provide a concise summary in 2-3 sentences.",
},
],
});
for await (const [namespace, chunk] of await agent.stream(
{
messages: [
{ role: "user", content: "Write a short summary about AI safety" },
],
},
{ streamMode: "updates", subgraphs: true },
)) {
// Main agent updates (empty namespace)
if (namespace.length === 0) {
for (const [nodeName, data] of Object.entries(chunk)) {
if (nodeName === "tools") {
// Subagent results returned to main agent
for (const msg of (data as any).messages ?? []) {
if (msg.type === "tool") {
console.log(`\nSubagent complete: ${msg.name}`);
console.log(` Result: ${String(msg.content).slice(0, 200)}...`);
}
}
} else {
console.log(`[main agent] step: ${nodeName}`);
}
}
}
// Subagent updates (non-empty namespace)
else {
for (const [nodeName] of Object.entries(chunk)) {
console.log(` [${namespace[0]}] step: ${nodeName}`);
}
}
}Main agent step: model_request
[tools:call_abc123] step: model_request
[tools:call_abc123] step: tools
[tools:call_abc123] step: model_request
Subagent complete: task
Result: ## AI Safety Report...
Main agent step: model_request
[tools:call_def456] step: model_request
[tools:call_def456] step: model_request
Subagent complete: task
Result: # Comprehensive Report on AI Safety...
Main agent step: model_requestLLM tokens#
Use stream_mode="messages" to stream individual tokens from both the main agent and subagents. Each message event includes metadata that identifies the source agent.
let currentSource = "";
for await (const [namespace, chunk] of await agent.stream(
{
messages: [
{
role: "user",
content: "Research quantum computing advances",
},
],
},
{ streamMode: "messages", subgraphs: true },
)) {
const [message] = chunk;
// Check if this event came from a subagent (namespace contains "tools:")
const isSubagent = namespace.some((s: string) => s.startsWith("tools:"));
if (isSubagent) {
// Token from a subagent
const subagentNs = namespace.find((s: string) => s.startsWith("tools:"))!;
if (subagentNs !== currentSource) {
process.stdout.write(`\n\n--- [subagent: ${subagentNs}] ---\n`);
currentSource = subagentNs;
}
if (message.text) {
process.stdout.write(message.text);
}
} else {
// Token from the main agent
if ("main" !== currentSource) {
process.stdout.write(`\n\n--- [main agent] ---\n`);
currentSource = "main";
}
if (message.text) {
process.stdout.write(message.text);
}
}
}
process.stdout.write("\n");Tool calls#
When subagents use tools, you can stream tool call events to display what each subagent is doing. Tool call chunks appear in the messages stream mode.
for await (const [namespace, chunk] of await agent.stream(
{
messages: [
{
role: "user",
content: "Research recent quantum computing advances",
},
],
},
{ streamMode: "messages", subgraphs: true },
)) {
const [message] = chunk;
// Identify source: "main" or the subagent namespace segment
const isSubagent = namespace.some((s: string) => s.startsWith("tools:"));
const source = isSubagent
? namespace.find((s: string) => s.startsWith("tools:"))!
: "main";
// Tool call chunks (streaming tool invocations)
if (AIMessageChunk.isInstance(message) && message.tool_call_chunks?.length) {
for (const tc of message.tool_call_chunks) {
if (tc.name) {
console.log(`\n[${source}] Tool call: ${tc.name}`);
}
// Args stream in chunks — write them incrementally
if (tc.args) {
process.stdout.write(tc.args);
}
}
}
// Tool results
if (ToolMessage.isInstance(message)) {
console.log(
`\n[${source}] Tool result [${message.name}]: ${message.text?.slice(0, 150)}`,
);
}
// Regular AI content (skip tool call messages)
if (
AIMessageChunk.isInstance(message) &&
message.text &&
!message.tool_call_chunks?.length
) {
process.stdout.write(message.text);
}
}
process.stdout.write("\n");Custom updates#
Use config.writer inside your subagent tools to emit custom progress events:
/**
* A tool that emits custom progress events via config.writer.
* The writer sends data to the "custom" stream mode.
*/
const analyzeData = tool(
async ({ topic }: { topic: string }, config: ToolRuntime) => {
const writer = config.writer;
writer?.({ status: "starting", topic, progress: 0 });
await new Promise((r) => setTimeout(r, 500));
writer?.({ status: "analyzing", progress: 50 });
await new Promise((r) => setTimeout(r, 500));
writer?.({ status: "complete", progress: 100 });
return `Analysis of "${topic}": Customer sentiment is 85% positive, driven by product quality and support response times.`;
},
{
name: "analyze_data",
description:
"Run a data analysis on a given topic. " +
"This tool performs the actual analysis and emits progress updates. " +
"You MUST call this tool for any analysis request.",
schema: z.object({
topic: z.string().describe("The topic or subject to analyze"),
}),
},
);
const agent = createDeepAgent({
systemPrompt:
"You are a coordinator. For any analysis request, you MUST delegate " +
"to the analyst subagent using the task tool. Never try to answer directly. " +
"After receiving the result, summarize it in one sentence.",
subagents: [
{
name: "analyst",
description: "Performs data analysis with real-time progress tracking",
systemPrompt:
"You are a data analyst. You MUST call the analyze_data tool " +
"for every analysis request. Do not use any other tools. " +
"After the analysis completes, report the result.",
tools: [analyzeData],
},
],
});
for await (const [namespace, chunk] of await agent.stream(
{
messages: [
{
role: "user",
content: "Analyze customer satisfaction trends",
},
],
},
{ streamMode: "custom", subgraphs: true },
)) {
const isSubagent = namespace.some((s: string) => s.startsWith("tools:"));
if (isSubagent) {
const subagentNs = namespace.find((s: string) => s.startsWith("tools:"))!;
console.log(`[${subagentNs}]`, chunk);
} else {
console.log("[main]", chunk);
}
}[tools:call_abc123] { status: 'fetching', progress: 0 }
[tools:call_abc123] { status: 'analyzing', progress: 50 }
[tools:call_abc123] { status: 'complete', progress: 100 }Stream multiple modes#
Combine multiple stream modes to get a complete picture of agent execution:
// Skip internal middleware steps — only show meaningful node names
const INTERESTING_NODES = new Set(["model_request", "tools"]);
let lastSource = "";
let midLine = false; // true when we've written tokens without a trailing newline
for await (const [namespace, mode, data] of await agent.stream(
{
messages: [
{
role: "user",
content: "Analyze the impact of remote work on team productivity",
},
],
},
{ streamMode: ["updates", "messages", "custom"], subgraphs: true },
)) {
const isSubagent = namespace.some((s: string) => s.startsWith("tools:"));
const source = isSubagent ? "subagent" : "main";
if (mode === "updates") {
for (const nodeName of Object.keys(data)) {
if (!INTERESTING_NODES.has(nodeName)) continue;
if (midLine) {
process.stdout.write("\n");
midLine = false;
}
console.log(`[${source}] step: ${nodeName}`);
}
} else if (mode === "messages") {
const [message] = data;
if (message.text) {
// Print a header when the source changes
if (source !== lastSource) {
if (midLine) {
process.stdout.write("\n");
midLine = false;
}
process.stdout.write(`\n[${source}] `);
lastSource = source;
}
process.stdout.write(message.text);
midLine = true;
}
} else if (mode === "custom") {
if (midLine) {
process.stdout.write("\n");
midLine = false;
}
console.log(`[${source}] custom event:`, data);
}
}
process.stdout.write("\n");Common patterns#
Track subagent lifecycle#
Monitor when subagents start, run, and complete:
for await (const [namespace, chunk] of await agent.stream(
{
messages: [
{ role: "user", content: "Research the latest AI safety developments" },
],
},
{ streamMode: "updates", subgraphs: true },
)) {
for (const [nodeName, data] of Object.entries(chunk)) {
// ─── Phase 1: Detect subagent starting ────────────────────────
// When the main agent's model_request contains task tool calls,
// a subagent has been spawned.
if (namespace.length === 0 && nodeName === "model_request") {
for (const msg of (data as any).messages ?? []) {
for (const tc of msg.tool_calls ?? []) {
if (tc.name === "task") {
activeSubagents.set(tc.id, {
type: tc.args?.subagent_type,
description: tc.args?.description?.slice(0, 80),
status: "pending",
});
console.log(
`[lifecycle] PENDING → subagent "${tc.args?.subagent_type}" (${tc.id})`,
);
}
}
}
}
// ─── Phase 2: Detect subagent running ─────────────────────────
// When we receive events from a tools:UUID namespace, that
// subagent is actively executing.
if (namespace.length > 0 && namespace[0].startsWith("tools:")) {
const pregelId = namespace[0].split(":")[1];
// Check if any pending subagent needs to be marked running.
// Note: the pregel task ID differs from the tool_call_id,
// so we mark any pending subagent as running on first subagent event.
for (const [id, sub] of activeSubagents) {
if (sub.status === "pending") {
sub.status = "running";
console.log(
`[lifecycle] RUNNING → subagent "${sub.type}" (pregel: ${pregelId})`,
);
break;
}
}
}
// ─── Phase 3: Detect subagent completing ──────────────────────
// When the main agent's tools node returns a tool message,
// the subagent has completed and returned its result.
if (namespace.length === 0 && nodeName === "tools") {
for (const msg of (data as any).messages ?? []) {
if (msg.type === "tool") {
const subagent = activeSubagents.get(msg.tool_call_id);
if (subagent) {
subagent.status = "complete";
console.log(
`[lifecycle] COMPLETE → subagent "${subagent.type}" (${msg.tool_call_id})`,
);
console.log(
` Result preview: ${String(msg.content).slice(0, 120)}...`,
);
}
}
}
}
}
}
// Print final state
console.log("\n--- Final subagent states ---");
for (const [id, sub] of activeSubagents) {
console.log(` ${sub.type}: ${sub.status}`);
}Related#
- Subagents — Configure and use subagents with deep agents
- Frontend streaming — Build React UIs with
useStreamfor deep agents - LangChain streaming overview — General streaming concepts with LangChain agents
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