npm install modelmix

import { ModelMix } from 'modelmix';

// Static factory (preferred)
const model = ModelMix.new();

// With global options
const model = ModelMix.new({
    options: { max_tokens: 4096, temperature: 0.7 },
    config: {
        system: "You are a helpful assistant.",
        max_history: 5,
        debug: 0,           // 0=silent, 1=minimal, 2=summary, 3=full (no truncate), 4=verbose
        roundRobin: false    // false=fallback, true=rotate models
    }
});

const model = ModelMix.new()
    .sonnet46()        // primary
    .gpt52()        // fallback 1
    .gemini3flash()    // fallback 2
    .addText("Hello!")

const answer = await ModelMix.new()
    .gpt5mini()
    .addText("What is the capital of France?")
    .message();

const result = await ModelMix.new()
    .gpt5mini()
    .addText("Name and capital of 3 South American countries.")
    .json(
        { countries: [{ name: "", capital: "" }] },                    // schema example
        { countries: [{ name: "country name", capital: "in uppercase" }] }, // descriptions
        { addNote: true }                                               // options
    );
// result.countries → [{ name: "Brazil", capital: "BRASILIA" }, ...]

const result = await model.json(
    { name: 'martin', age: 22, sex: 'Male' },
    {
        name: { description: 'Name of the actor', required: false },
        age: 'Age of the actor',                                     // string still works
        sex: { description: 'Gender', enum: ['Male', 'Female', null] }
    }
);

const result = await model.json([{ name: 'martin' }]);
// result is an array: [{ name: "Martin" }, { name: "Carlos" }, ...]

await ModelMix.new()
    .gpt5mini()
    .addText("Tell me a story.")
    .stream(({ delta, message }) => {
        process.stdout.write(delta);
    });

const raw = await ModelMix.new()
    .sonnet45think()
    .addText("Solve this step by step: 2+2*3")
    .raw();
// raw.message, raw.think, raw.tokens, raw.toolCalls, raw.response

const model = ModelMix.new().gpt5mini().addText("Hello!");
const text = await model.message();
console.log(model.lastRaw.tokens);
// { input: 122, output: 86, total: 541, cost: 0.000319 }
console.log(model.lastRaw.think);    // reasoning content (if available)
console.log(model.lastRaw.response); // raw API response

const model = ModelMix.new().sonnet45();
model.addImage('./photo.jpg');                         // from file
model.addImageFromUrl('https://example.com/img.png');  // from URL
model.addText('Describe this image.');
const description = await model.message();

const model = ModelMix.new().gpt5mini();
model.setSystemFromFile('./prompts/system.md');
model.addTextFromFile('./prompts/task.md');
model.replace({
    '{role}': 'data analyst',
    '{language}': 'Spanish'
});
model.replaceKeyFromFile('{code}', './src/utils.js');
console.log(await model.message());

const pool = ModelMix.new({ config: { roundRobin: true } })
    .gpt5mini()
    .sonnet45()
    .gemini3flash();

// Each call rotates to the next model
const r1 = await pool.new().addText("Request 1").message();
const r2 = await pool.new().addText("Request 2").message();

const model = ModelMix.new({ config: { max_history: 10 } }).gpt5nano();
model.setSystem('You are an assistant. Today is ' + new Date().toISOString());
await model.addMCP('@modelcontextprotocol/server-brave-search');
model.addText('Use Internet: What is the latest news about AI?');
console.log(await model.message());

const model = ModelMix.new({ config: { max_history: 10 } }).gpt5mini();

model.addTool({
    name: "get_weather",
    description: "Get weather for a city",
    inputSchema: {
        type: "object",
        properties: { city: { type: "string" } },
        required: ["city"]
    }
}, async ({ city }) => {
    return `The weather in ${city} is sunny, 25C`;
});

model.addText("What's the weather in Tokyo?");
console.log(await model.message());

const model = ModelMix.new({
    config: {
        bottleneck: {
            maxConcurrent: 4,
            minTime: 1000
        }
    }
}).gpt5mini();

const model = ModelMix.new({
    config: { debug: 2 }  // 0=silent, 1=minimal, 2=summary, 3=full (no truncate), 4=verbose
}).gpt5mini();

// These use providers with free quotas (OpenRouter, Groq, Cerebras)
const model = ModelMix.new()
    .gptOss()
    .kimiK2()
    .deepseekR1()
    .hermes3()
    .addText("What is the capital of France?");
console.log(await model.message());

const chat = ModelMix.new({ config: { max_history: 10 } }).gpt5mini();
chat.addText("My name is Martin.");
await chat.message();
chat.addText("What's my name?");
const reply = await chat.message();  // "Martin"