Skill 15 · Langgraph Fundamentals
Subchapter 15.2
references/typescript.mdMarkdown9 KBView on GitHub
Use this reference only for LangGraph projects written in TypeScript. The shared concepts, decisions, and invariants remain in ../SKILL.md.
Use StateSchema with ReducedValue for accumulating arrays.
import { StateSchema, ReducedValue, MessagesValue } from "@langchain/langgraph";
import { z } from "zod";
const State = new StateSchema({
name: z.string(), // Default: overwrites
messages: MessagesValue, // Built-in for messages
items: new ReducedValue(
z.array(z.string()).default(() => []),
{ reducer: (current, update) => current.concat(update) }
),
});Without ReducedValue, arrays are overwritten not appended.
// WRONG: Array will be overwritten
const State = new StateSchema({
items: z.array(z.string()), // No reducer!
});
// Node 1: { items: ["A"] }, Node 2: { items: ["B"] }
// Final: { items: ["B"] } // A is lost!
// CORRECT: Use ReducedValue
const State = new StateSchema({
items: new ReducedValue(
z.array(z.string()).default(() => []),
{ reducer: (current, update) => current.concat(update) }
),
});
// Final: { items: ["A", "B"] }Return partial updates only, not the full state object.
// WRONG: Returning entire state
const myNode = async (state: typeof State.State) => {
state.field = "updated";
return state; // Don't do this!
};
// CORRECT: Return partial updates
const myNode = async (state: typeof State.State) => {
return { field: "updated" };
};| Signature | When to Use |
|---|---|
(state) => {...} | Simple nodes that only need state |
(state, config) => {...} | Need thread_id, tags, or configurable values |
import { GraphNode, StateSchema } from "@langchain/langgraph";
const plainNode: GraphNode<typeof State> = (state) => {
return { results: "done" };
};
const nodeWithConfig: GraphNode<typeof State> = (state, config) => {
const threadId = config?.configurable?.thread_id;
return { results: `Thread: ${threadId}` };
};Chain nodes with addEdge and compile before invoking.
import { StateGraph, StateSchema, START, END } from "@langchain/langgraph";
import { z } from "zod";
const State = new StateSchema({
input: z.string(),
output: z.string().default(""),
});
const processInput = async (state: typeof State.State) => {
return { output: `Processed: ${state.input}` };
};
const finalize = async (state: typeof State.State) => {
return { output: state.output.toUpperCase() };
};
const graph = new StateGraph(State)
.addNode("process", processInput)
.addNode("finalize", finalize)
.addEdge(START, "process")
.addEdge("process", "finalize")
.addEdge("finalize", END)
.compile();
const result = await graph.invoke({ input: "hello" });
console.log(result.output); // "PROCESSED: HELLO"addConditionalEdges routes based on function return value.
import { StateGraph, StateSchema, START, END } from "@langchain/langgraph";
import { z } from "zod";
const State = new StateSchema({
query: z.string(),
route: z.string().default(""),
result: z.string().default(""),
});
const classify = async (state: typeof State.State) => {
if (state.query.toLowerCase().includes("weather")) {
return { route: "weather" };
}
return { route: "general" };
};
const routeQuery = (state: typeof State.State) => state.route;
const graph = new StateGraph(State)
.addNode("classify", classify)
.addNode("weather", async () => ({ result: "Sunny, 72F" }))
.addNode("general", async () => ({ result: "General response" }))
.addEdge(START, "classify")
.addConditionalEdges("classify", routeQuery, ["weather", "general"])
.addEdge("weather", END)
.addEdge("general", END)
.compile();Return Command with update and goto to combine state change with routing.
import { StateGraph, StateSchema, START, END, Command } from "@langchain/langgraph";
import { z } from "zod";
const State = new StateSchema({
count: z.number().default(0),
result: z.string().default(""),
});
const nodeA = async (state: typeof State.State) => {
const newCount = state.count + 1;
if (newCount > 5) {
return new Command({ update: { count: newCount }, goto: "node_c" });
}
return new Command({ update: { count: newCount }, goto: "node_b" });
};
const graph = new StateGraph(State)
.addNode("node_a", nodeA, { ends: ["node_b", "node_c"] })
.addNode("node_b", async () => ({ result: "B" }))
.addNode("node_c", async () => ({ result: "C" }))
.addEdge(START, "node_a")
.addEdge("node_b", END)
.addEdge("node_c", END)
.compile();Fan out tasks to parallel workers using the Send API and aggregate results.
import { Send, StateGraph, StateSchema, ReducedValue, START, END } from "@langchain/langgraph";
import { z } from "zod";
const State = new StateSchema({
tasks: z.array(z.string()),
results: new ReducedValue(
z.array(z.string()).default(() => []),
{ reducer: (curr, upd) => curr.concat(upd) }
),
summary: z.string().default(""),
});
const orchestrator = (state: typeof State.State) => {
return state.tasks.map((task) => new Send("worker", { task }));
};
const worker = async (state: { task: string }) => {
return { results: [`Completed: ${state.task}`] };
};
const synthesize = async (state: typeof State.State) => {
return { summary: `Processed ${state.results.length} tasks` };
};
const graph = new StateGraph(State)
.addNode("worker", worker)
.addNode("synthesize", synthesize)
.addConditionalEdges(START, orchestrator, ["worker"])
.addEdge("worker", "synthesize")
.addEdge("synthesize", END)
.compile();Use ReducedValue to accumulate parallel worker results.
// WRONG: No reducer
const State = new StateSchema({ results: z.array(z.string()) });
// CORRECT
const State = new StateSchema({
results: new ReducedValue(z.array(z.string()).default(() => []), { reducer: (curr, upd) => curr.concat(upd) }),
});const result = await graph.invoke({ input: "hello" });
// With config
const result = await graph.invoke({ input: "hello" }, { configurable: { thread_id: "1" } });Stream LLM tokens in real-time for chat UI display.
for await (const chunk of graph.stream(
{ messages: [new HumanMessage("Hello")] },
{ streamMode: "messages" }
)) {
const [token, metadata] = chunk;
if (token.content) {
process.stdout.write(token.content);
}
}Emit custom progress updates from within nodes using the stream writer.
import { getWriter } from "@langchain/langgraph";
const myNode = async (state: typeof State.State) => {
const writer = getWriter();
writer("Processing step 1...");
// Do work
writer("Complete!");
return { result: "done" };
};
for await (const chunk of graph.stream({ data: "test" }, { streamMode: "custom" })) {
console.log(chunk);
}Use retryPolicy for transient errors.
workflow.addNode(
"searchDocumentation",
searchDocumentation,
{
retryPolicy: { maxAttempts: 3, initialInterval: 1.0 },
},
);Use ToolNode from @langchain/langgraph/prebuilt to handle tool execution and errors. When handleToolErrors is true, errors are returned as ToolMessages so the LLM can recover.
import { ToolNode } from "@langchain/langgraph/prebuilt";
const toolNode = new ToolNode(tools, { handleToolErrors: true });
workflow.addNode("tools", toolNode);Must compile() to get executable graph.
// WRONG
await builder.invoke({ input: "test" });
// CORRECT
const graph = builder.compile();
await graph.invoke({ input: "test" });Use conditional edges with END return to break loops.
// WRONG: Loops forever
builder.addEdge("node_a", "node_b").addEdge("node_b", "node_a");
// CORRECT
builder.addConditionalEdges("node_a", (state) => state.count > 10 ? END : "node_b");// Always await graph.invoke() - it returns a Promise
const result = await graph.invoke({ input: "test" });
// TS Command nodes need { ends } to declare routing destinations
builder.addNode("router", routerFn, { ends: ["node_b", "node_c"] });