Streaming

import { ModelGates } from '@modelgates/agent'; const modelgates = new ModelGates({  apiKey: process.env.MODELGATES_API_KEY,}); const result = modelgates.callModel({  model: 'openai/gpt-5-nano',  input: 'Write a short poem about the ocean.',}); for await (const delta of result.getTextStream()) {  process.stdout.write(delta);}

const result = modelgates.callModel({  model: 'openai/o1-preview',  input: 'Solve this step by step: If x + 5 = 12, what is x?',}); console.log('Reasoning:');for await (const delta of result.getReasoningStream()) {  process.stdout.write(delta);} console.log('\n\nFinal answer:');const text = await result.getText();console.log(text);

import type { StreamableOutputItem } from '@modelgates/agent'; const result = modelgates.callModel({  model: 'anthropic/claude-sonnet-4',  input: 'Hello!',  tools: [myTool],}); for await (const item of result.getItemsStream()) {  switch (item.type) {    case 'message':      console.log('Message:', item.content);      break;    case 'function_call':      console.log('Tool call:', item.name, item.arguments);      break;    case 'reasoning':      console.log('Thinking:', item.summary);      break;    case 'function_call_output':      console.log('Tool result:', item.output);      break;  }}

// Deprecated - use getItemsStream() insteadconst result = modelgates.callModel({  model: 'openai/gpt-5-nano',  input: 'Hello!',  tools: [myTool],}); for await (const message of result.getNewMessagesStream()) {  if (message.type === 'message') {    console.log('Assistant message:', message.content);  } else if (message.type === 'function_call_output') {    console.log('Tool result:', message.output);  }}

const result = modelgates.callModel({  model: 'openai/gpt-5-nano',  input: 'Search for documents',  tools: [searchTool], // Generator tool with eventSchema}); for await (const event of result.getFullResponsesStream()) {  switch (event.type) {    case 'response.output_text.delta':      process.stdout.write(event.delta);      break;    case 'response.function_call_arguments.delta':      console.log('Tool argument delta:', event.delta);      break;    case 'response.completed':      console.log('Response complete');      break;    case 'tool.preliminary_result':      // Intermediate progress from generator tools      console.log('Progress:', event.result);      break;    case 'tool.result':      // Final result when tool execution completes      console.log('Tool completed:', event.toolCallId);      console.log('Result:', event.result);      // Access any preliminary results that were emitted      if (event.preliminaryResults) {        console.log('Preliminary results:', event.preliminaryResults);      }      break;  }}

const result = modelgates.callModel({  model: 'openai/gpt-5-nano',  input: 'What is the weather in Paris and Tokyo?',  tools: [weatherTool],  maxToolRounds: 0, // Don't auto-execute, just get tool calls}); for await (const toolCall of result.getToolCallsStream()) {  console.log(`Tool: $`);  console.log(`Arguments:`, toolCall.arguments);  console.log(`ID: $`);}

const result = modelgates.callModel({  model: 'openai/gpt-5-nano',  input: 'Search for TypeScript tutorials',  tools: [searchTool], // Generator tool}); for await (const event of result.getToolStream()) {  if (event.type === 'delta') {    // Raw argument deltas    process.stdout.write(event.content);  } else if (event.type === 'preliminary_result') {    // Progress from generator tools    console.log(`\nProgress (${event.toolCallId}):`, event.result);  }}

const result = modelgates.callModel({  model: 'openai/gpt-5-nano',  input: 'Write a story.',}); // Start both consumers concurrentlyconst [text, response] = await Promise.all([  // Consumer 1: Collect text  (async () => {    let text = '';    for await (const delta of result.getTextStream()) {      text += delta;    }    return text;  })(),   // Consumer 2: Get full response  result.getResponse(),]); console.log('Text length:', text.length);console.log('Token usage:', response.usage);

const result = modelgates.callModel({  model: 'openai/gpt-5-nano',  input: 'Write a very long essay...',}); // Start streamingconst streamPromise = (async () => {  let charCount = 0;  for await (const delta of result.getTextStream()) {    process.stdout.write(delta);    charCount += delta.length;     // Cancel after 500 characters    if (charCount > 500) {      await result.cancel();      break;    }  }})(); await streamPromise;console.log('\nCancelled!');

import { useState, useEffect } from 'react'; function ChatResponse({ prompt }: { prompt: string }) {  const [text, setText] = useState('');  const [isStreaming, setIsStreaming] = useState(true);   useEffect(() => {    const modelgates = new ModelGates({ apiKey: API_KEY });     const result = modelgates.callModel({      model: 'openai/gpt-5-nano',      input: prompt,    });     (async () => {      for await (const delta of result.getTextStream()) {        setText(prev => prev + delta);      }      setIsStreaming(false);    })();     return () => {      result.cancel();    };  }, [prompt]);   return (    <div>      <p>{text}</p>      {isStreaming && <span className="cursor">|</span>}    </div>  );}

import { Hono } from 'hono';import { streamSSE } from 'hono/streaming'; const app = new Hono(); app.get('/stream', (c) => {  return streamSSE(c, async (stream) => {    const result = modelgates.callModel({      model: 'openai/gpt-5-nano',      input: c.req.query('prompt') || 'Hello!',    });     for await (const delta of result.getTextStream()) {      await stream.writeSSE({        data: JSON.stringify({ delta }),        event: 'delta',      });    }     await stream.writeSSE({      data: JSON.stringify({ done: true }),      event: 'done',    });  });});