Call Model Overview (Typescript) | OpenRouter SDK | OpenRouter

Why callModel?

Items-Based Model: Built on OpenRouter’s Responses API with structured items (messages, tool calls, reasoning) instead of raw message chunks
Multiple Consumption Patterns: Get text, stream responses, or access structured data - all from a single call
Automatic Tool Execution: Define tools with Zod schemas and let the SDK handle execution loops
Type Safety: Full TypeScript inference for tool inputs, outputs, and events
Format Compatibility: Convert to/from OpenAI chat and Anthropic Claude message formats
Streaming First: Built on a reusable stream architecture that supports concurrent consumers

Quick Start

1 import { OpenRouter } from '@openrouter/sdk';
2 
3 const openrouter = new OpenRouter({
4   apiKey: process.env.OPENROUTER_API_KEY,
5 });
6 
7 const result = openrouter.callModel({
8   model: 'openai/gpt-5-nano',
9   input: 'What is the capital of France?',
10 });
11 
12 // Get text (simplest pattern)
13 const text = await result.getText();
14 console.log(text); // "The capital of France is Paris."

Consumption Patterns

callModel returns a ModelResult object that provides multiple ways to consume the response:

Text Methods

1 // Get just the text content
2 const text = await result.getText();
3 
4 // Get the full response with usage data
5 const response = await result.getResponse();
6 console.log(response.usage); // { inputTokens, outputTokens, cachedTokens }

Streaming Methods

1 // Stream text deltas
2 for await (const delta of result.getTextStream()) {
3   process.stdout.write(delta);
4 }
5 
6 // Stream reasoning (for reasoning models)
7 for await (const delta of result.getReasoningStream()) {
8   console.log('Reasoning:', delta);
9 }
10 
11 // Stream complete items by ID (recommended)
12 for await (const item of result.getItemsStream()) {
13   console.log('Item update:', item.type, item.id);
14 }
15 
16 // Stream all events (including tool preliminary results)
17 for await (const event of result.getFullResponsesStream()) {
18   console.log('Event:', event.type);
19 }

Tool Methods

1 // Get all tool calls from the response
2 const toolCalls = await result.getToolCalls();
3 
4 // Stream tool calls as they complete
5 for await (const toolCall of result.getToolCallsStream()) {
6   console.log(`Tool: ${toolCall.name}`, toolCall.arguments);
7 }
8 
9 // Stream tool deltas and preliminary results
10 for await (const event of result.getToolStream()) {
11   if (event.type === 'delta') {
12     process.stdout.write(event.content);
13   } else if (event.type === 'preliminary_result') {
14     console.log('Progress:', event.result);
15   }
16 }

Input Formats

callModel accepts multiple input formats:

1 // Simple string
2 const result1 = openrouter.callModel({
3   model: 'openai/gpt-5-nano',
4   input: 'Hello!',
5 });
6 
7 // Message array (OpenResponses format)
8 const result2 = openrouter.callModel({
9   model: 'openai/gpt-5-nano',
10   input: [
11     { role: 'user', content: 'Hello!' },
12   ],
13 });
14 
15 // With system instructions
16 const result3 = openrouter.callModel({
17   model: 'openai/gpt-5-nano',
18   instructions: 'You are a helpful assistant.',
19   input: 'Hello!',
20 });

What’s Next?

Explore the guides to learn more about specific features:

Working with Items - Understand the items-based streaming paradigm
Text Generation - Input formats, model selection, and response handling
Streaming - All streaming methods and patterns
Tools - Creating typed tools with Zod schemas and multi-turn orchestration
nextTurnParams - Tool-driven context injection for skills and plugins
Message Formats - Converting to/from OpenAI and Claude formats
Dynamic Parameters - Async functions for adaptive behavior
Stop Conditions - Intelligent execution control
API Reference - Complete type definitions and method signatures

Example Tools

Ready-to-use tool implementations:

Weather Tool - Basic API integration
Skills Loader - Claude Code skills pattern

1	import { OpenRouter } from '@openrouter/sdk';
2
3	const openrouter = new OpenRouter({
4	apiKey: process.env.OPENROUTER_API_KEY,
5	});
6
7	const result = openrouter.callModel({
8	model: 'openai/gpt-5-nano',
9	input: 'What is the capital of France?',
10	});
11
12	// Get text (simplest pattern)
13	const text = await result.getText();
14	console.log(text); // "The capital of France is Paris."

1	// Get just the text content
2	const text = await result.getText();
3
4	// Get the full response with usage data
5	const response = await result.getResponse();
6	console.log(response.usage); // { inputTokens, outputTokens, cachedTokens }

1	// Stream text deltas
2	for await (const delta of result.getTextStream()) {
3	process.stdout.write(delta);
4	}
5
6	// Stream reasoning (for reasoning models)
7	for await (const delta of result.getReasoningStream()) {
8	console.log('Reasoning:', delta);
9	}
10
11	// Stream complete items by ID (recommended)
12	for await (const item of result.getItemsStream()) {
13	console.log('Item update:', item.type, item.id);
14	}
15
16	// Stream all events (including tool preliminary results)
17	for await (const event of result.getFullResponsesStream()) {
18	console.log('Event:', event.type);
19	}

1	// Get all tool calls from the response
2	const toolCalls = await result.getToolCalls();
3
4	// Stream tool calls as they complete
5	for await (const toolCall of result.getToolCallsStream()) {
6	console.log(`Tool: ${toolCall.name}`, toolCall.arguments);
7	}
8
9	// Stream tool deltas and preliminary results
10	for await (const event of result.getToolStream()) {
11	if (event.type === 'delta') {
12	process.stdout.write(event.content);
13	} else if (event.type === 'preliminary_result') {
14	console.log('Progress:', event.result);
15	}
16	}

1	// Simple string
2	const result1 = openrouter.callModel({
3	model: 'openai/gpt-5-nano',
4	input: 'Hello!',
5	});
6
7	// Message array (OpenResponses format)
8	const result2 = openrouter.callModel({
9	model: 'openai/gpt-5-nano',
10	input: [
11	{ role: 'user', content: 'Hello!' },
12	],
13	});
14
15	// With system instructions
16	const result3 = openrouter.callModel({
17	model: 'openai/gpt-5-nano',
18	instructions: 'You are a helpful assistant.',
19	input: 'Hello!',
20	});