fix(gettingStartedDocs): Update LangGraph example to use StateGraph API (#109551)

Update the LangGraph code snippet in the agent monitoring getting
started guide.

`instrumentLangGraph` works by wrapping the `.compile()` method on a
`StateGraph` to intercept the compilation step and inject tracing. This
means it must be called before `.compile()` is invoked.

`createReactAgent` calls `.compile()` internally and returns the
already-compiled graph — there's no hook point between graph
construction and compilation. By the time you get the return value, the
compile step has already happened, making it too late for
`instrumentLangGraph` to do its job.

In short: `createReactAgent` hides the compile step, but
`instrumentLangGraph` needs to wrap that exact step. They are
fundamentally incompatible with the current SDK API.

The fix replaces `createReactAgent` with the lower-level `StateGraph` +
`MessagesAnnotation` pattern, which keeps the compile step explicit and
accessible.

Author: priscilawebdev

static/app/gettingStartedDocs/javascript/agentMonitoring.tsx

@@ -116,7 +116,7 @@ Sentry.init({
             language: 'javascript',
             code: `${sentryImport}
 import { ChatOpenAI } from "@langchain/openai";
-import { createReactAgent } from "@langchain/langgraph/prebuilt";
+import { StateGraph, MessagesAnnotation } from "@langchain/langgraph";
 import { HumanMessage, SystemMessage } from "@langchain/core/messages";
 
 const llm = new ChatOpenAI({
@@ -125,13 +125,21 @@ const llm = new ChatOpenAI({
   apiKey: "OPENAI_API_KEY",
 });
 
-const agent = createReactAgent({ llm, tools: [] });
+const graph = new StateGraph(MessagesAnnotation)
+  .addNode("agent", async (state) => {
+    const response = await llm.invoke(state.messages);
+    return { messages: [response] };
+  })
+  .addEdge("__start__", "agent")
+  .addEdge("agent", "__end__");
 
-Sentry.instrumentLangGraph(agent, {
+Sentry.instrumentLangGraph(graph, {
   recordInputs: true,
   recordOutputs: true,
 });
 
+const agent = graph.compile();
+
 const result = await agent.invoke({
   messages: [
     new SystemMessage("You are a helpful assistant."),