openai/gpt-5.4

LLM

GPT 5.4 API by OpenAI

openai/gpt-5.4

Gpt-5.4

Advanced multimodal model optimized for reasoning, coding, content generation, and complex problem-solving with strong accuracy and reliability.

GPT 5.4 dikembangkan oleh OpenAI. Atlas Cloud (dioperasikan oleh Atlas Cloud AI LLC) menyediakan akses ke model ini dan tidak memilikinya. Semua merek dagang adalah milik pemiliknya masing-masing.

Parameter

Contoh kode
import os
from openai import OpenAI

# Multimodal Understanding Example
# Image: use base64 encoding (data:image/png;base64,...) or a public URL

client = OpenAI(
    api_key=os.getenv("ATLASCLOUD_API_KEY"),
    base_url="https://api.atlascloud.ai/v1"
)

response = client.chat.completions.create(
    model="openai/gpt-5.4",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "image_url",
                    "image_url": {
                        "url": "data:image/png;base64,<BASE64_IMAGE_DATA>"
                    }
                },
                {
                    "type": "text",
                    "text": "Please describe the content of this image"
                }
            ]
        }
    ],
    max_tokens=64000,
    temperature=0.7
)

print(response.choices[0].message.content)

Instalasi

Instal paket dependensi yang diperlukan.

pip install requests

Autentikasi

Semua permintaan API memerlukan autentikasi melalui API key. Anda bisa mendapatkan API key dari dasbor Atlas Cloud.

export ATLASCLOUD_API_KEY="your-api-key-here"

HTTP Headers

import os

API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {API_KEY}"
}

Jaga keamanan API key Anda

Jangan pernah mengekspos API key Anda di kode sisi klien atau repositori publik. Gunakan variabel lingkungan atau proxy backend sebagai gantinya.

Kirim permintaan

import requests

url = "https://api.atlascloud.ai/v1/chat/completions"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "openai/gpt-5.4",
    "messages": [
        {
            "role": "user",
            "content": "what is difference between http and https"
        }
    ],
    "max_tokens": 64000,
    "temperature": 0.7,
    "stream": False
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

Input Schema

Parameter berikut diterima di isi permintaan.

Total: 5Wajib: 2Opsional: 3

modelstringrequired

The model ID to use for the completion.

Example: "openai/gpt-5.4"

messagesarray[object]required

A list of messages comprising the conversation so far.

rolestringrequired

The role of the message author.

systemuserassistant

contentstring | array[object]required

Plain text, or an array of content parts for multimodal input. Combine a media part with a text part to ask a question about the media. Accepts image (png, jpeg, webp, gif).

max_tokensinteger

The maximum number of tokens to generate in the completion. The maximum value is the model's context length minus the prompt length.

Min: 1

temperaturenumber

Controls the variety of the model's responses. Lower values make output more predictable and deterministic, higher values more diverse and random.

Default: 1Min: 0Max: 2

streamboolean

If set to true, partial message deltas will be sent as server-sent events.

Default: false

Contoh Isi Permintaan

{
  "model": "openai/gpt-5.4",
  "messages": [
    {
      "role": "user",
      "content": [
        {
          "type": "image_url",
          "image_url": {
            "url": "data:image/png;base64,<BASE64_IMAGE_DATA>"
          }
        },
        {
          "type": "text",
          "text": "Please describe the content of this image"
        }
      ]
    }
  ],
  "max_tokens": 64000,
  "temperature": 0.7,
  "stream": false
}

Output Schema

API mengembalikan respons yang kompatibel dengan ChatCompletion.

idstringrequired

Unique identifier for the completion.

objectstringrequired

Object type, always "chat.completion".

Default: "chat.completion"

createdintegerrequired

Unix timestamp of when the completion was created.

modelstringrequired

The model used for the completion.

choicesarray[object]required

List of completion choices.

indexintegerrequired

Index of the choice.

messageobjectrequired

The generated message.

finish_reasonstringrequired

The reason generation stopped.

stoplengthcontent_filter

usageobjectrequired

Token usage statistics.

prompt_tokensintegerrequired

Number of tokens in the prompt.

completion_tokensintegerrequired

Number of tokens in the completion.

total_tokensintegerrequired

Total tokens used.

Contoh Respons

{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "created": 1700000000,
  "model": "model-name",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Hello! How can I assist you today?"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 10,
    "completion_tokens": 20,
    "total_tokens": 30
  }
}

Atlas Cloud Skills

Atlas Cloud Skills mengintegrasikan 400+ model AI langsung ke asisten pengkodean AI Anda. Satu perintah untuk menginstal, lalu gunakan bahasa alami untuk menghasilkan gambar, video, dan mengobrol dengan LLM.

Klien yang Didukung

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ klien yang didukung

Instalasi

npx skills add AtlasCloudAI/atlas-cloud-skills

Atur API Key

Dapatkan API key dari dasbor Atlas Cloud dan atur sebagai variabel lingkungan.

export ATLASCLOUD_API_KEY="your-api-key-here"

Kemampuan

Setelah diinstal, Anda dapat menggunakan bahasa alami di asisten AI Anda untuk mengakses semua model Atlas Cloud.

Pembuatan GambarBuat gambar dengan model seperti Nano Banana 2, Z-Image, dan lainnya.

Pembuatan VideoBuat video dari teks atau gambar dengan Kling, Vidu, Veo, dll.

Obrolan LLMMengobrol dengan Qwen, DeepSeek, dan model bahasa besar lainnya.

Unggah MediaUnggah file lokal untuk pengeditan gambar dan alur kerja gambar-ke-video.

Pelajari lebih lanjut

github.com/AtlasCloudAI/atlas-cloud-skills

MCP Server

Atlas Cloud MCP Server menghubungkan IDE Anda dengan 400+ model AI melalui Model Context Protocol. Berfungsi dengan klien apa pun yang kompatibel dengan MCP.

Klien yang Didukung

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ klien yang didukung

Instalasi

npx -y atlascloud-mcp

Konfigurasi

Tambahkan konfigurasi berikut ke file pengaturan MCP di IDE Anda.

{
  "mcpServers": {
    "atlascloud": {
      "command": "npx",
      "args": [
        "-y",
        "atlascloud-mcp"
      ],
      "env": {
        "ATLASCLOUD_API_KEY": "your-api-key-here"
      }
    }
  }
}

Alat yang Tersedia

atlas_generate_imageBuat gambar dari prompt teks.

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