import "./app.css";
import { useAgent } from "agents/react";
import { nanoid } from "nanoid";
import { useCallback, useEffect, useMemo, useState } from "react";
import sequentialCode from "./flows/01 sequential.txt?raw";
import routingCode from "./flows/02 routing.txt?raw";
import parallelCode from "./flows/03 parallel.txt?raw";
import orchestratorCode from "./flows/04 orchestrator.txt?raw";
import evaluatorCode from "./flows/05 evaluator.txt?raw";
type ToastType = "success" | "error" | "info";
type Toast = {
id: number;
type: ToastType;
message: string;
};
type WorkflowStatus = {
isRunning: boolean;
output: string;
};
type WorkflowType =
| "sequential"
| "routing"
| "parallel"
| "orchestrator"
| "evaluator";
type PatternProps = {
type: WorkflowType;
title: string;
description: string;
image: string;
code: string;
index: number;
};
type FormState = {
sequential: { input: string };
routing: { query: string };
parallel: { code: string };
orchestrator: { featureRequest: string };
evaluator: { text: string; targetLanguage: string };
};
const LANGUAGES = [
{ label: "French", value: "french" },
{ label: "Spanish", value: "spanish" },
{ label: "Japanese", value: "japanese" },
{ label: "German", value: "german" },
{ label: "Mandarin Chinese", value: "mandarin" },
{ label: "Arabic", value: "arabic" },
{ label: "Russian", value: "russian" },
{ label: "Italian", value: "italian" },
{ label: "Klingon", value: "klingon" },
{ label: "Portuguese", value: "portuguese" }
] as const;
function Toast({ toast, onClose }: { toast: Toast; onClose: () => void }) {
useEffect(() => {
const timer = setTimeout(() => {
onClose();
}, 5000);
return () => clearTimeout(timer);
}, [onClose]);
const getIcon = (type: ToastType) => {
switch (type) {
case "success":
return "✅";
case "error":
return "❌";
case "info":
return "ℹ️";
}
};
return (
{getIcon(toast.type)}
{toast.message}
);
}
function ToastContainer({
toasts,
onClose
}: {
toasts: Toast[];
onClose: (id: number) => void;
}) {
return (
{toasts.map((toast) => (
onClose(toast.id)} />
))}
);
}
function getOrCreateSessionId() {
const stored = globalThis.localStorage?.getItem("sessionId");
if (stored) return stored;
const newId = nanoid(8);
globalThis.localStorage?.setItem("sessionId", newId);
return newId;
}
function PatternSection({
type,
title,
description,
image,
code,
index,
sessionId
}: PatternProps & { sessionId: string }) {
const [activeTab, setActiveTab] = useState<"diagram" | "code">("diagram");
const [isCodeExpanded, setIsCodeExpanded] = useState(false);
const socket = useAgent({
agent: type,
name: sessionId,
onMessage: (e) => {
const data = JSON.parse(e.data);
switch (data.type) {
case "status":
setWorkflowStatus(data.status);
break;
case "toast": {
const event = new CustomEvent("showToast", {
detail: {
message: data.toast.message,
type: data.toast.type as ToastType
}
});
window.dispatchEvent(event);
break;
}
}
},
prefix: "agents"
});
const [workflowStatus, setWorkflowStatus] = useState({
isRunning: false,
output: ""
});
const [formState, setFormState] = useState(() => {
switch (type) {
case "sequential":
return { input: "Our new AI-powered productivity app" };
case "routing":
return { query: "How do I reset my password?" };
case "parallel":
return {
code: `function processUserData(data) {
// TODO: Add validation
database.save(data);
return true;
}`
};
case "orchestrator":
return {
featureRequest:
"Add dark mode support to the dashboard, including theme persistence and system preference detection"
};
case "evaluator":
return {
targetLanguage: LANGUAGES[0].value,
text: "The early bird catches the worm"
};
}
});
const handleInputChange = (
e: React.ChangeEvent<
HTMLInputElement | HTMLTextAreaElement | HTMLSelectElement
>
) => {
const { name, value } = e.target;
setFormState((prev) => ({ ...prev, [name]: value }));
};
const getFormContent = () => {
if (type === "sequential") {
const state = formState as FormState["sequential"];
return (
Enter a product or service to generate marketing copy for
);
}
if (type === "routing") {
const state = formState as FormState["routing"];
return (
Enter a customer support question to be routed
);
}
if (type === "parallel") {
const state = formState as FormState["parallel"];
return (
Enter code snippet for parallel security, performance, and
maintainability review
);
}
if (type === "orchestrator") {
const state = formState as FormState["orchestrator"];
return (
Describe the feature to be implemented across multiple files
);
}
if (type === "evaluator") {
const state = formState as FormState["evaluator"];
return (
<>
Enter text to be translated and optimized
Select the language to translate into
>
);
}
};
const formatOutput = (output: string) => {
try {
// Try to parse as JSON first
const parsed = JSON.parse(output);
return JSON.stringify(parsed, null, 2);
} catch {
// If not JSON, return as is
return output;
}
};
const runWorkflow = async () => {
setWorkflowStatus((prev) => ({ ...prev, isRunning: true }));
try {
socket.send(
JSON.stringify({
input: formState,
type: "run"
})
);
// Show success toast when workflow starts
const event = new CustomEvent("showToast", {
detail: { message: `Started ${title} workflow...`, type: "info" }
});
window.dispatchEvent(event);
} catch (_error) {
// Show error toast if something goes wrong
const event = new CustomEvent("showToast", {
detail: { message: `Failed to start ${title} workflow`, type: "error" }
});
window.dispatchEvent(event);
}
};
return (
{index + 1}. {title}
{code}
{description}
{getFormContent()}
{/* {workflowState.isRunning && (
)} */}
{workflowStatus.output
? formatOutput(workflowStatus.output)
: `Enter input above and click 'Run' to see ${title} in action`}
);
}
export default function App() {
const [theme, setTheme] = useState<"light" | "dark">("light");
const [toasts, setToasts] = useState([]);
const sessionId = useMemo(() => getOrCreateSessionId(), []);
const addToast = useCallback((type: ToastType, message: string) => {
const id = Date.now();
setToasts((prev) => [...prev, { id, message, type }]);
}, []);
const removeToast = (id: number) => {
setToasts((prev) => prev.filter((toast) => toast.id !== id));
};
useEffect(() => {
// Theme detection code
const prefersDark = window.matchMedia(
"(prefers-color-scheme: dark)"
).matches;
setTheme(prefersDark ? "dark" : "light");
document.documentElement.setAttribute(
"data-theme",
prefersDark ? "dark" : "light"
);
// Add toast event listener
const handleToast = (
e: CustomEvent<{ type: ToastType; message: string }>
) => {
addToast(e.detail.type, e.detail.message);
};
window.addEventListener("showToast", handleToast as EventListener);
return () => {
window.removeEventListener("showToast", handleToast as EventListener);
};
}, [addToast]);
const toggleTheme = () => {
const newTheme = theme === "light" ? "dark" : "light";
setTheme(newTheme);
document.documentElement.setAttribute("data-theme", newTheme);
};
const patterns = {
evaluator: {
code: evaluatorCode,
description:
"One LLM generates responses while another provides evaluation and feedback in a loop.",
image: "/flows/05 evaluator.png",
title: "Evaluator-Optimizer"
},
orchestrator: {
code: orchestratorCode,
description:
"A central LLM dynamically breaks down tasks, delegates to worker LLMs, and synthesizes results.",
image: "/flows/04 orchestrator.png",
title: "Orchestrator-Workers"
},
parallel: {
code: parallelCode,
description:
"Enables simultaneous task processing through sectioning or voting mechanisms.",
image: "/flows/03 parallel.png",
title: "Parallelization"
},
routing: {
code: routingCode,
description:
"Classifies input and directs it to specialized followup tasks, allowing for separation of concerns.",
image: "/flows/02 routing.png",
title: "Routing"
},
sequential: {
code: sequentialCode,
description:
"Decomposes tasks into a sequence of steps, where each LLM call processes the output of the previous one.",
image: "/flows/01 sequential.png",
title: "Prompt Chaining"
}
};
return (
{/* oxlint-disable-next-line jsx-a11y/click-events-have-key-events, jsx-a11y/no-static-element-interactions -- theme toggle */}
{theme === "light" ? "🌞" : "🌙"}
⛅️ Building Effective Agents
Common patterns for implementing AI agents
{(
Object.entries(patterns) as [
WorkflowType,
(typeof patterns)[keyof typeof patterns]
][]
).map(([type, pattern], index) => (
))}
Why Durable Objects?
Cloudflare's Durable Objects provide the perfect environment for
hosting AI agents:
Persistent State
Agents continue running even when browser tabs are closed or
refreshed, maintaining their state and context throughout
long-running tasks.
Real-time Updates
WebSocket connections enable live streaming of agent progress,
thoughts, and results directly to any connected client, providing
immediate feedback.
Global Scale
Agents run at the edge, automatically scaling across Cloudflare's
worldwide network, ensuring low-latency responses regardless of
user location.
Flexible Triggers
Agents can be activated through various means: HTTP requests,
scheduled cron jobs, email handlers, or other server-side events.
Memory Isolation
Each agent runs in its own isolated environment, preventing
resource contention and ensuring reliable performance.
Cost Effective
Pay only for the compute time your agents use, with no idle costs
and automatic scaling based on demand.
);
}