Meta Muse & Meta Spark

import os
from openai import OpenAI

# Meta Model API is fully OpenAI spec compliant
client = OpenAI(
    api_key=os.environ.get("META_API_KEY"),
    base_url="https://api.meta.ai/v1",
    default_headers={
        "X-Meta-Team-ID": "2103496870583053",
        "X-Meta-Project-ID": "1058226340231296"
    }
)

response = client.chat.completions.create(
    model="llama-3.3-70b-instruct",
    messages=[
        {"role": "system", "content": "You are Meta Muse assistant."},
        {"role": "user", "content": "Explain how to stream Meta Muse outputs into Spark Studio."}
    ],
    stream=True
)

for chunk in response:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

import OpenAI from 'openai';

const metaAI = new OpenAI({
  apiKey: process.env.META_API_KEY,
  baseURL: 'https://api.meta.ai/v1',
  defaultHeaders: {
    'X-Meta-Team-ID': '2103496870583053',
    'X-Meta-Project-ID': '1058226340231296'
  }
});

async function main() {
  const completion = await metaAI.chat.completions.create({
    model: 'meta-muse-spark-v1',
    messages: [{ role: 'user', content: 'Design a prompt sequence for dynamic Spark AR filters.' }],
  });

  console.log(completion.choices[0].message.content);
}

main();

// Meta Spark Studio (v180+) Scripting Module
const Scene = require('Scene');
const FaceTracking = require('FaceTracking');
const Reactive = require('Reactive');
const Networking = require('Networking');

(async function () {
  // Track user face gestures in Spark AR
  const face = FaceTracking.face(0);
  const mouthOpenness = face.mouth.openness;

  // Trigger Meta Model API via Spark Networking module on mouth open
  mouthOpenness.monitor().subscribe(async (event) => {
    if (event.newValue > 0.6) {
      const response = await Networking.fetch('https://api.meta.ai/v1/chat/completions', {
        method: 'POST',
        headers: {
          'Content-Type': 'application/json',
          'Authorization': 'Bearer YOUR_SPARK_TOKEN'
        },
        body: JSON.stringify({
          model: 'meta-muse-spark-v1',
          messages: [{ role: 'user', content: 'Generate a short positive spark quote' }]
        })
      });
      const data = await response.json();
      Diagnostics.log(data.choices[0].message.content);
    }
  });
})();