First of all we need dependencies,
In my case I installed langchain/core, langgraph and LLM provider package, in this case `@langchain/google-vertexai`, but any other may be used.
package.js
{
"name": "langchain-experiments",
"version": "1.0.0",
"description": "",
"license": "ISC",
"author": "",
"type": "module",
"main": "index.js",
"scripts": {
"test": "echo \"Error: no test specified\" && exit 1"
},
"dependencies": {
"@langchain/core": "^0.3.77",
"@langchain/google-vertexai": "^0.2.18",
"@langchain/langgraph": "^0.4.9",
"zod": "^3.25.76"
}
}
Now, let's create an agent, which resembles ReAct agent, however this one has some custom edges and is generally simpler.
agent.js
import {MessagesAnnotation, StateGraph} from "@langchain/langgraph";
import {ToolNode} from "@langchain/langgraph/prebuilt";
import {HumanMessage} from "@langchain/core/messages";
/**
* This is a simple agent that uses a tool to complete a checklist.
*/
export function myAgent(params) {
const {llm, tools, checklist} = params;
const llmWithTools = llm.bindTools(tools);
const toolNode = new ToolNode(tools);
function printChecklist({messages}) {
console.log(checklist);
const checklistMessage = "checklist: " + JSON.stringify(checklist);
return {messages: [new HumanMessage(checklistMessage)]};
}
function shouldContinue({messages}) {
const lastMessage = messages[messages.length - 1];
// If the LLM makes a tool call, then we route to the "tools" node
if (lastMessage.tool_calls?.length) {
console.log("Continuing to tools");
return "tools";
}
// Otherwise, we go check_checklist
console.log("Continuing to print_checklist");
return "print_checklist";
}
function isChecklistComplete({messages}) {
const lastMessage = messages[messages.length - 1];
if (Object.values(checklist).every(v => v === true)) {
// If f all checklist items are complete go to the special __end__ node
console.log("Checklist complete!");
return "__end__";
}
// Otherwise, we go back to agent
console.log("Checklist not complete!");
return "agent";
}
async function callModel(state) {
console.log("Calling model...");
// It most likely to die here if you don't provide tool.
const response = await llmWithTools.invoke(state.messages);
console.log(`Agent: ${response.content}`);
// We return a list, because this will get added to the existing list
return {messages: [response]};
}
const workflow = new StateGraph(MessagesAnnotation);
workflow.addNode("print_checklist", printChecklist);
workflow.addNode("agent", callModel)
workflow.addNode("tools", toolNode)
workflow.addEdge("__start__", "print_checklist");
workflow.addEdge("tools", "print_checklist");
workflow.addConditionalEdges("print_checklist", isChecklistComplete);
workflow.addConditionalEdges("agent", shouldContinue);
return workflow.compile();
}
Entry point to launch the agent:
index.js
import {ChatVertexAI} from "@langchain/google-vertexai";
import {HumanMessage, SystemMessage} from "@langchain/core/messages";
import {myAgent} from "./agent.js";
import {z} from "zod";
import {tool} from "@langchain/core/tools";
const checklist = {
"say_hello": false,
"say_how_are_you": false
}
const completeChecklistItemToolDefinition = {
name: 'complete_checklist_item',
description: `Tool to Complete one Checklist Item. Use example: complete_checklist_item "task_1"`,
schema: z.string(),
};
const completeChecklistItemToolImpl = (s) => {
let message;
if (s in checklist) {
checklist[s] = true;
message = `Completed Checklist Item '${s}'`;
} else {
message = `Checklist item '${s}' not found.`;
}
console.log(message);
return message;
};
const completeChecklistItemTool = tool(completeChecklistItemToolImpl, completeChecklistItemToolDefinition)
const llm = new ChatVertexAI({
model: 'gemini-2.5-pro',
});
const tools = [completeChecklistItemTool];
export const agent = myAgent({
llm,
tools,
checklist
});
agent.invoke({
messages: [
new SystemMessage("You must use complete_checklist_item to complete all checklist items one by one."),
new HumanMessage("Hello")
]
});
Expected output:
{ say_hello: false, say_how_are_you: false }
Checklist not complete!
Calling model...
Agent:
Continuing to tools
Completed Checklist Item 'say_hello'
{ say_hello: true, say_how_are_you: false }
Checklist not complete!
Calling model...
Agent:
Continuing to tools
Completed Checklist Item 'say_how_are_you'
{ say_hello: true, say_how_are_you: true }
Checklist complete!