Hypereal API -viite

curl https://hypereal.cloud/api/v1/chat/completions \
  -H "Authorization: Bearer ck_..." \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5.5",
    "messages": [
      {"role": "system", "content": "You are a terse assistant."},
      {"role": "user", "content": "Two-line haiku about caches."}
    ],
    "stream": true,
    "max_tokens": 256
  }'

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: process.env.HYPEREAL_API_KEY,
  baseURL: 'https://hypereal.cloud/api/v1',
});

const stream = await client.chat.completions.create({
  model: 'gpt-5.5',
  stream: true,
  messages: [{ role: 'user', content: 'Stream me a haiku.' }],
});

for await (const chunk of stream) {
  process.stdout.write(chunk.choices[0]?.delta?.content ?? '');
}

curl https://api.hypereal.cloud/v1/messages \
  -H "x-api-key: ck_..." \
  -H "anthropic-version: 2023-06-01" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-sonnet-4-6",
    "max_tokens": 1024,
    "system": [{
      "type": "text",
      "text": "You are a senior TypeScript refactoring assistant.",
      "cache_control": {"type": "ephemeral"}
    }],
    "messages": [
      {"role": "user", "content": "Plan a 3-step refactor of a Next.js app."}
    ],
    "hypereal": {"cache": "auto"}
  }'

import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  apiKey: process.env.HYPEREAL_API_KEY, // ck_...
  baseURL: 'https://api.hypereal.cloud',
});

const msg = await client.messages.create({
  model: 'claude-sonnet-4-6',
  max_tokens: 1024,
  system: [{
    type: 'text',
    text: 'You are a senior TypeScript refactoring assistant.',
    cache_control: { type: 'ephemeral' },
  }],
  hypereal: { cache: 'auto' },
  messages: [{ role: 'user', content: 'Hello, Claude.' }],
});

console.log(msg.content);

curl https://hypereal.cloud/api/v1/responses \
  -H "Authorization: Bearer ck_..." \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5.1-codex",
    "input": "Write a TypeScript function that debounces a callback.",
    "stream": true
  }'

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: process.env.HYPEREAL_API_KEY,
  baseURL: 'https://hypereal.cloud/api/v1',
});

const response = await client.responses.create({
  model: 'gpt-5.3-codex',
  input: 'Refactor this file into smaller modules.',
});

console.log(response.output_text);

curl https://hypereal.cloud/api/v1/images/generations \
  -H "Authorization: Bearer ck_..." \
  -H "Content-Type: application/json" \
  -d '{
    "model": "nano_banana_pro",
    "prompt": "isometric studio shot of a tiny cyberpunk apartment, neon rim light",
    "n": 1,
    "size": "1024x1024"
  }'

const res = await fetch('https://hypereal.cloud/api/v1/images/generations', {
  method: 'POST',
  headers: {
    'Authorization': `Bearer ${process.env.HYPEREAL_API_KEY}`,
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
    model: 'gemini-3-pro-image-preview',
    prompt: 'a chrome teapot floating over the ocean at sunset',
    n: 1,
  }),
});

const { data } = await res.json();
console.log(data[0].url); // or data[0].b64_json depending on the model

curl https://hypereal.cloud/api/v1/videos/generate \
  -H "Authorization: Bearer ck_..." \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini_omni_flash",
    "prompt": "a white cube rotating on a black background, clean product demo",
    "duration": 6,
    "aspect_ratio": "16:9",
    "resolution": "720P",
    "image_urls": [
      "https://example.com/product-reference.png"
    ]
  }'

const res = await fetch('https://hypereal.cloud/api/v1/videos/generate', {
  method: 'POST',
  headers: {
    'Authorization': `Bearer ${process.env.HYPEREAL_API_KEY}`,
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
    model: 'gemini_omni_flash',
    prompt: 'a cat walking on the moon, cinematic, no text',
    duration: 6,
    aspect_ratio: '16:9',
    resolution: '720P',
    image_urls: ['https://example.com/cat-reference.png'],
  }),
});

const data = await res.json();
console.log(data.jobId, data.pollUrl); // poll /v1/jobs/{id} for the mp4

curl https://hypereal.cloud/api/v1/audio/generations \
  -H "Authorization: Bearer ck_..." \
  -H "Content-Type: application/json" \
  -d '{
    "model": "audio-tts",
    "text": "Welcome to Hypereal. One key, every model.",
    "voice_id": "en_male_calm"
  }'

curl https://hypereal.cloud/api/v1/audio/generations \
  -H "Authorization: Bearer ck_..." \
  -H "Content-Type: application/json" \
  -d '{
    "model": "audio-clone",
    "text": "This is my cloned voice.",
    "audio": "https://example.com/reference-30s.mp3"
  }'

curl https://hypereal.cloud/api/v1/audio/generations \
  -H "Authorization: Bearer ck_..." \
  -H "Content-Type: application/json" \
  -d '{
    "model": "audio-asr",
    "audio": "https://example.com/recording.mp3"
  }'

curl "https://hypereal.cloud/api/v1/gemini" \
  -H "x-goog-api-key: ck_..." \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-3.5-thinking",
    "contents": [
      {"role": "user", "parts": [{"text": "Outline a launch plan."}]}
    ],
    "generationConfig": {"temperature": 0.6, "maxOutputTokens": 2048}
  }'

// The /v1/gemini endpoint accepts both Gemini-native and OpenAI shapes.
// For SDK use, the OpenAI client + /v1/chat/completions is simpler.
const res = await fetch('https://hypereal.cloud/api/v1/gemini', {
  method: 'POST',
  headers: {
    'x-goog-api-key': process.env.HYPEREAL_API_KEY!,
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
    model: 'gemini-3.5-fast',
    contents: [{ role: 'user', parts: [{ text: 'Hi' }] }],
  }),
});

console.log(await res.json());