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Try itnpx skills add https://github.com/openrouterteam/agent-skills --skill create-agentThis skill helps you create a modular AI agent with:
┌─────────────────────────────────────────────────────┐
│ Your Application │
├─────────────────────────────────────────────────────┤
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │
│ │ Ink TUI │ │ HTTP API │ │ Discord │ │
│ └──────┬──────┘ └──────┬──────┘ └──────┬──────┘ │
│ │ │ │ │
│ └────────────────┼────────────────┘ │
│ ▼ │
│ ┌───────────────────────┐ │
│ │ Agent Core │ │
│ │ (hooks & lifecycle) │ │
│ └───────────┬───────────┘ │
│ ▼ │
│ ┌───────────────────────┐ │
│ │ OpenRouter SDK │ │
│ └───────────────────────┘ │
└─────────────────────────────────────────────────────┘
Get an OpenRouter API key at: https://openrouter.ai/settings/keys
⚠️ Security: Never commit API keys. Use environment variables.
mkdir my-agent && cd my-agent
npm init -y
npm pkg set type="module"
npm install @openrouter/sdk zod eventemitter3
npm install ink react # Optional: only for TUI
npm install -D typescript @types/react tsx
{
"compilerOptions": {
"target": "ES2022",
"module": "NodeNext",
"moduleResolution": "NodeNext",
"jsx": "react-jsx",
"strict": true,
"esModuleInterop": true,
"skipLibCheck": true,
"outDir": "dist"
},
"include": ["src"]
}
{
"scripts": {
"start": "tsx src/cli.tsx",
"start:headless": "tsx src/headless.ts",
"dev": "tsx watch src/cli.tsx"
}
}
src/
├── agent.ts # Standalone agent core with hooks
├── tools.ts # Tool definitions
├── cli.tsx # Ink TUI (optional interface)
└── headless.ts # Headless usage example
Create src/agent.ts - the standalone agent that can run anywhere:
import { OpenRouter, tool, stepCountIs } from '@openrouter/sdk';
import type { Tool, StopCondition, StreamableOutputItem } from '@openrouter/sdk';
import { EventEmitter } from 'eventemitter3';
import { z } from 'zod';
// Message types
export interface Message {
role: 'user' | 'assistant' | 'system';
content: string;
}
// Agent events for hooks (items-based streaming model)
export interface AgentEvents {
'message:user': (message: Message) => void;
'message:assistant': (message: Message) => void;
'item:update': (item: StreamableOutputItem) => void; // Items emitted with same ID, replace by ID
'stream:start': () => void;
'stream:delta': (delta: string, accumulated: string) => void;
'stream:end': (fullText: string) => void;
'tool:call': (name: string, args: unknown) => void;
'tool:result': (name: string, result: unknown) => void;
'reasoning:update': (text: string) => void; // Extended thinking content
'error': (error: Error) => void;
'thinking:start': () => void;
'thinking:end': () => void;
}
// Agent configuration
export interface AgentConfig {
apiKey: string;
model?: string;
instructions?: string;
tools?: Tool<z.ZodTypeAny, z.ZodTypeAny>[];
maxSteps?: number;
}
// The Agent class - runs independently of any UI
export class Agent extends EventEmitter<AgentEvents> {
private client: OpenRouter;
private messages: Message[] = [];
private config: Required<Omit<AgentConfig, 'apiKey'>> & { apiKey: string };
constructor(config: AgentConfig) {
super();
this.client = new OpenRouter({ apiKey: config.apiKey });
this.config = {
apiKey: config.apiKey,
model: config.model ?? 'openrouter/auto',
instructions: config.instructions ?? 'You are a helpful assistant.',
tools: config.tools ?? [],
maxSteps: config.maxSteps ?? 5,
};
}
// Get conversation history
getMessages(): Message[] {
return [...this.messages];
}
// Clear conversation
clearHistory(): void {
this.messages = [];
}
// Add a system message
setInstructions(instructions: string): void {
this.config.instructions = instructions;
}
// Register additional tools at runtime
addTool(newTool: Tool<z.ZodTypeAny, z.ZodTypeAny>): void {
this.config.tools.push(newTool);
}
// Send a message and get streaming response using items-based model
// Items are emitted multiple times with the same ID but progressively updated content
// Replace items by their ID rather than accumulating chunks
async send(content: string): Promise<string> {
const userMessage: Message = { role: 'user', content };
this.messages.push(userMessage);
this.emit('message:user', userMessage);
this.emit('thinking:start');
try {
const result = this.client.callModel({
model: this.config.model,
instructions: this.config.instructions,
input: this.messages.map((m) => ({ role: m.role, content: m.content })),
tools: this.config.tools.length > 0 ? this.config.tools : undefined,
stopWhen: [stepCountIs(this.config.maxSteps)],
});
this.emit('stream:start');
let fullText = '';
// Use getItemsStream() for items-based streaming (recommended)
// Each item emission is complete - replace by ID, don't accumulate
for await (const item of result.getItemsStream()) {
// Emit the item for UI state management (use Map keyed by item.id)
this.emit('item:update', item);
switch (item.type) {
case 'message':
// Message items contain progressively updated content
const textContent = item.content?.find((c: { type: string }) => c.type === 'output_text');
if (textContent && 'text' in textContent) {
const newText = textContent.text;
if (newText !== fullText) {
const delta = newText.slice(fullText.length);
fullText = newText;
this.emit('stream:delta', delta, fullText);
}
}
break;
case 'function_call':
// Function call arguments stream progressively
if (item.status === 'completed') {
this.emit('tool:call', item.name, JSON.parse(item.arguments || '{}'));
}
break;
case 'function_call_output':
this.emit('tool:result', item.callId, item.output);
break;
case 'reasoning':
// Extended thinking/reasoning content
const reasoningText = item.content?.find((c: { type: string }) => c.type === 'reasoning_text');
if (reasoningText && 'text' in reasoningText) {
this.emit('reasoning:update', reasoningText.text);
}
break;
// Additional item types: web_search_call, file_search_call, image_generation_call
}
}
// Get final text if streaming didn't capture it
if (!fullText) {
fullText = await result.getText();
}
this.emit('stream:end', fullText);
const assistantMessage: Message = { role: 'assistant', content: fullText };
this.messages.push(assistantMessage);
this.emit('message:assistant', assistantMessage);
return fullText;
} catch (err) {
const error = err instanceof Error ? err : new Error(String(err));
this.emit('error', error);
throw error;
} finally {
this.emit('thinking:end');
}
}
// Send without streaming (simpler for programmatic use)
async sendSync(content: string): Promise<string> {
const userMessage: Message = { role: 'user', content };
this.messages.push(userMessage);
this.emit('message:user', userMessage);
try {
const result = this.client.callModel({
model: this.config.model,
instructions: this.config.instructions,
input: this.messages.map((m) => ({ role: m.role, content: m.content })),
tools: this.config.tools.length > 0 ? this.config.tools : undefined,
stopWhen: [stepCountIs(this.config.maxSteps)],
});
const fullText = await result.getText();
const assistantMessage: Message = { role: 'assistant', content: fullText };
this.messages.push(assistantMessage);
this.emit('message:assistant', assistantMessage);
return fullText;
} catch (err) {
const error = err instanceof Error ? err : new Error(String(err));
this.emit('error', error);
throw error;
}
}
}
// Factory function for easy creation
export function createAgent(config: AgentConfig): Agent {
return new Agent(config);
}
Create src/tools.ts:
import { tool } from '@openrouter/sdk';
import { z } from 'zod';
export const timeTool = tool({
name: 'get_current_time',
description: 'Get the current date and time',
inputSchema: z.object({
timezone: z.string().optional().describe('Timezone (e.g., "UTC", "America/New_York")'),
}),
execute: async ({ timezone }) => {
return {
time: new Date().toLocaleString('en-US', { timeZone: timezone || 'UTC' }),
timezone: timezone || 'UTC',
};
},
});
export const calculatorTool = tool({
name: 'calculate',
description: 'Perform mathematical calculations',
inputSchema: z.object({
expression: z.string().describe('Math expression (e.g., "2 + 2", "sqrt(16)")'),
}),
execute: async ({ expression }) => {
// Simple safe eval for basic math
const sanitized = expression.replace(/[^0-9+\-*/().\s]/g, '');
const result = Function(`"use strict"; return (${sanitized})`)();
return { expression, result };
},
});
export const defaultTools = [timeTool, calculatorTool];
Create src/headless.ts - use the agent programmatically:
import { createAgent } from './agent.js';
import { defaultTools } from './tools.js';
async function main() {
const agent = createAgent({
apiKey: process.env.OPENROUTER_API_KEY!,
model: 'openrouter/auto',
instructions: 'You are a helpful assistant with access to tools.',
tools: defaultTools,
});
// Hook into events
agent.on('thinking:start', () => console.log('\n🤔 Thinking...'));
agent.on('tool:call', (name, args) => console.log(`🔧 Using ${name}:`, args));
agent.on('stream:delta', (delta) => process.stdout.write(delta));
agent.on('stream:end', () => console.log('\n'));
agent.on('error', (err) => console.error('❌ Error:', err.message));
// Interactive loop
const readline = await import('readline');
const rl = readline.createInterface({
input: process.stdin,
output: process.stdout,
});
console.log('Agent ready. Type your message (Ctrl+C to exit):\n');
const prompt = () => {
rl.question('You: ', async (input) => {
if (!input.trim()) {
prompt();
return;
}
await agent.send(input);
prompt();
});
};
prompt();
}
main().catch(console.error);
Run headless: OPENROUTER_API_KEY=sk-or-... npm run start:headless
Create src/cli.tsx - a beautiful terminal UI that uses the agent with items-based streaming:
import React, { useState, useEffect, useCallback } from 'react';
import { render, Box, Text, useInput, useApp } from 'ink';
import type { StreamableOutputItem } from '@openrouter/sdk';
import { createAgent, type Agent, type Message } from './agent.js';
import { defaultTools } from './tools.js';
// Initialize agent (runs independently of UI)
const agent = createAgent({
apiKey: process.env.OPENROUTER_API_KEY!,
model: 'openrouter/auto',
instructions: 'You are a helpful assistant. Be concise.',
tools: defaultTools,
});
function ChatMessage({ message }: { message: Message }) {
const isUser = message.role === 'user';
return (
<Box flexDirection="column" marginBottom={1}>
<Text bold color={isUser ? 'cyan' : 'green'}>
{isUser ? '▶ You' : '◀ Assistant'}
</Text>
<Text wrap="wrap">{message.content}</Text>
</Box>
);
}
// Render streaming items by type using the items-based pattern
function ItemRenderer({ item }: { item: StreamableOutputItem }) {
switch (item.type) {
case 'message': {
const textContent = item.content?.find((c: { type: string }) => c.type === 'output_text');
const text = textContent && 'text' in textContent ? textContent.text : '';
return (
<Box flexDirection="column" marginBottom={1}>
<Text bold color="green">◀ Assistant</Text>
<Text wrap="wrap">{text}</Text>
{item.status !== 'completed' && <Text color="gray">▌</Text>}
</Box>
);
}
case 'function_call':
return (
<Text color="yellow">
{item.status === 'completed' ? ' ✓' : ' 🔧'} {item.name}
{item.status === 'in_progress' && '...'}
</Text>
);
case 'reasoning': {
const reasoningText = item.content?.find((c: { type: string }) => c.type === 'reasoning_text');
const text = reasoningText && 'text' in reasoningText ? reasoningText.text : '';
return (
<Box flexDirection="column" marginBottom={1}>
<Text bold color="magenta">💭 Thinking</Text>
<Text wrap="wrap" color="gray">{text}</Text>
</Box>
);
}
default:
return null;
}
}
function InputField({
value,
onChange,
onSubmit,
disabled,
}: {
value: string;
onChange: (v: string) => void;
onSubmit: () => void;
disabled: boolean;
}) {
useInput((input, key) => {
if (disabled) return;
if (key.return) onSubmit();
else if (key.backspace || key.delete) onChange(value.slice(0, -1));
else if (input && !key.ctrl && !key.meta) onChange(value + input);
});
return (
<Box>
<Text color="yellow">{'> '}</Text>
<Text>{value}</Text>
<Text color="gray">{disabled ? ' ···' : '█'}</Text>
</Box>
);
}
function App() {
const { exit } = useApp();
const [messages, setMessages] = useState<Message[]>([]);
const [input, setInput] = useState('');
const [isLoading, setIsLoading] = useState(false);
// Use Map keyed by item ID for efficient React state updates (items-based pattern)
const [items, setItems] = useState<Map<string, StreamableOutputItem>>(new Map());
useInput((_, key) => {
if (key.escape) exit();
});
// Subscribe to agent events using items-based streaming
useEffect(() => {
const onThinkingStart = () => {
setIsLoading(true);
setItems(new Map()); // Clear items for new response
};
// Items-based streaming: replace items by ID, don't accumulate
const onItemUpdate = (item: StreamableOutputItem) => {
setItems((prev) => new Map(prev).set(item.id, item));
};
const onMessageAssistant = () => {
setMessages(agent.getMessages());
setItems(new Map()); // Clear streaming items
setIsLoading(false);
};
const onError = (err: Error) => {
setIsLoading(false);
};
agent.on('thinking:start', onThinkingStart);
agent.on('item:update', onItemUpdate);
agent.on('message:assistant', onMessageAssistant);
agent.on('error', onError);
return () => {
agent.off('thinking:start', onThinkingStart);
agent.off('item:update', onItemUpdate);
agent.off('message:assistant', onMessageAssistant);
agent.off('error', onError);
};
}, []);
const sendMessage = useCallback(async () => {
if (!input.trim() || isLoading) return;
const text = input.trim();
setInput('');
setMessages((prev) => [...prev, { role: 'user', content: text }]);
await agent.send(text);
}, [input, isLoading]);
return (
<Box flexDirection="column" padding={1}>
<Box marginBottom={1}>
<Text bold color="magenta">🤖 OpenRouter Agent</Text>
<Text color="gray"> (Esc to exit)</Text>
</Box>
<Box flexDirection="column" marginBottom={1}>
{/* Render completed messages */}
{messages.map((msg, i) => (
<ChatMessage key={i} message={msg} />
))}
{/* Render streaming items by type (items-based pattern) */}
{Array.from(items.values()).map((item) => (
<ItemRenderer key={item.id} item={item} />
))}
</Box>
<Box borderStyle="single" borderColor="gray" paddingX={1}>
<InputField
value={input}
onChange={setInput}
onSubmit={sendMessage}
disabled={isLoading}
/>
</Box>
</Box>
);
}
render(<App />);
Run TUI: OPENROUTER_API_KEY=sk-or-... npm start
The OpenRouter SDK uses an items-based streaming model - a key paradigm where items are emitted multiple times with the same ID but progressively updated content. Instead of accumulating chunks, you replace items by their ID.
Each iteration of getItemsStream() yields a complete item with updated content:
// Iteration 1: Partial message
{ id: "msg_123", type: "message", content: [{ type: "output_text", text: "Hello" }] }
// Iteration 2: Updated message (replace, don't append)
{ id: "msg_123", type: "message", content: [{ type: "output_text", text: "Hello world" }] }
For function calls, arguments stream progressively:
// Iteration 1: Partial arguments
{ id: "call_456", type: "function_call", name: "get_weather", arguments: "{\"q" }
// Iteration 2: Complete arguments
{ id: "call_456", type: "function_call", name: "get_weather", arguments: "{\"query\": \"Paris\"}", status: "completed" }
Traditional (accumulation required):
let text = '';
for await (const chunk of result.getTextStream()) {
text += chunk; // Manual accumulation
updateUI(text);
}
Items (complete replacement):
const items = new Map<string, StreamableOutputItem>();
for await (const item of result.getItemsStream()) {
items.set(item.id, item); // Replace by ID
updateUI(items);
}
Benefits:
const agent = createAgent({ apiKey: '...' });
// Log all events
agent.on('message:user', (msg) => {
saveToDatabase('user', msg.content);
});
agent.on('message:assistant', (msg) => {
saveToDatabase('assistant', msg.content);
sendWebhook('new_message', msg);
});
agent.on('tool:call', (name, args) => {
analytics.track('tool_used', { name, args });
});
agent.on('error', (err) => {
errorReporting.capture(err);
});
import express from 'express';
import { createAgent } from './agent.js';
const app = express();
app.use(express.json());
// One agent per session (store in memory or Redis)
const sessions = new Map<string, Agent>();
app.post('/chat', async (req, res) => {
const { sessionId, message } = req.body;
let agent = sessions.get(sessionId);
if (!agent) {
agent = createAgent({ apiKey: process.env.OPENROUTER_API_KEY! });
sessions.set(sessionId, agent);
}
const response = await agent.sendSync(message);
res.json({ response, history: agent.getMessages() });
});
app.listen(3000);
import { Client, GatewayIntentBits } from 'discord.js';
import { createAgent } from './agent.js';
const discord = new Client({
intents: [GatewayIntentBits.Guilds, GatewayIntentBits.GuildMessages],
});
const agents = new Map<string, Agent>();
discord.on('messageCreate', async (msg) => {
if (msg.author.bot) return;
let agent = agents.get(msg.channelId);
if (!agent) {
agent = createAgent({ apiKey: process.env.OPENROUTER_API_KEY! });
agents.set(msg.channelId, agent);
}
const response = await agent.sendSync(msg.content);
await msg.reply(response);
});
discord.login(process.env.DISCORD_TOKEN);
| Option | Type | Default | Description |
|---|---|---|---|
| apiKey | string | required | OpenRouter API key |
| model | string | 'openrouter/auto' | Model to use |
| instructions | string | 'You are a helpful assistant.' | System prompt |
| tools | Tool[] | [] | Available tools |
| maxSteps | number | 5 | Max agentic loop iterations |
| Method | Returns | Description |
|---|---|---|
send(content) | Promise | Send message with streaming |
sendSync(content) | Promise | Send message without streaming |
getMessages() | Message[] | Get conversation history |
clearHistory() | void | Clear conversation |
setInstructions(text) | void | Update system prompt |
addTool(tool) | void | Add tool at runtime |
| Event | Payload | Description |
|---|---|---|
message:user | Message | User message added |
message:assistant | Message | Assistant response complete |
item:update | StreamableOutputItem | Item emitted (replace by ID, don't accumulate) |
stream:start | - | Streaming started |
stream:delta | (delta, accumulated) | New text chunk |
stream:end | fullText | Streaming complete |
tool:call | (name, args) | Tool being called |
tool:result | (name, result) | Tool returned result |
reasoning:update | text | Extended thinking content |
thinking:start | - | Agent processing |
thinking:end | - | Agent done processing |
error | Error | Error occurred |
The SDK uses an items-based streaming model where items are emitted multiple times with the same ID but progressively updated content. Replace items by their ID rather than accumulating chunks.
| Type | Purpose |
|---|---|
message | Assistant text responses |
function_call | Tool invocations with streaming arguments |
function_call_output | Results from executed tools |
reasoning | Extended thinking content |
web_search_call | Web search operations |
file_search_call | File search operations |
image_generation_call | Image generation operations |
Do not hardcode model IDs - they change frequently. Use the models API:
interface OpenRouterModel {
id: string;
name: string;
description?: string;
context_length: number;
pricing: { prompt: string; completion: string };
top_provider?: { is_moderated: boolean };
}
async function fetchModels(): Promise<OpenRouterModel[]> {
const res = await fetch('https://openrouter.ai/api/v1/models');
const data = await res.json();
return data.data;
}
// Find models by criteria
async function findModels(filter: {
author?: string; // e.g., 'anthropic', 'openai', 'google'
minContext?: number; // e.g., 100000 for 100k context
maxPromptPrice?: number; // e.g., 0.001 for cheap models
}): Promise<OpenRouterModel[]> {
const models = await fetchModels();
return models.filter((m) => {
if (filter.author && !m.id.startsWith(filter.author + '/')) return false;
if (filter.minContext && m.context_length < filter.minContext) return false;
if (filter.maxPromptPrice) {
const price = parseFloat(m.pricing.prompt);
if (price > filter.maxPromptPrice) return false;
}
return true;
});
}
// Example: Get latest Claude models
const claudeModels = await findModels({ author: 'anthropic' });
console.log(claudeModels.map((m) => m.id));
// Example: Get models with 100k+ context
const longContextModels = await findModels({ minContext: 100000 });
// Example: Get cheap models
const cheapModels = await findModels({ maxPromptPrice: 0.0005 });
// Create agent with dynamic model selection
const models = await fetchModels();
const bestModel = models.find((m) => m.id.includes('claude')) || models[0];
const agent = createAgent({
apiKey: process.env.OPENROUTER_API_KEY!,
model: bestModel.id, // Use discovered model
instructions: 'You are a helpful assistant.',
});
For simplicity, use openrouter/auto which automatically selects the best
available model for your request:
const agent = createAgent({
apiKey: process.env.OPENROUTER_API_KEY!,
model: 'openrouter/auto', // Auto-selects best model
});
GET https://openrouter.ai/api/v1/models{ data: OpenRouterModel[] }