"GPT-5 API Complete Guide: Features, Pricing, and Code Examples"

from openai import OpenAI

# Direct via OpenAI
client = OpenAI(api_key="sk-your-openai-key")

# Or via Crazyrouter (recommended for cost savings)
client = OpenAI(
    api_key="your-crazyrouter-key",
    base_url="https://api.crazyrouter.com/v1"
)

response = client.chat.completions.create(
    model="gpt-5",
    messages=[
        {
            "role": "system",
            "content": "You are a senior software engineer. Be concise and practical."
        },
        {
            "role": "user",
            "content": "Explain the difference between async/await and Promises in JavaScript. When should I use each?"
        }
    ],
    temperature=0.7,
    max_tokens=1024
)

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

stream = client.chat.completions.create(
    model="gpt-5",
    messages=[
        {"role": "user", "content": "Write a Python async web scraper with rate limiting"}
    ],
    stream=True
)

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

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: 'your-crazyrouter-key',
  baseURL: 'https://api.crazyrouter.com/v1'
});

async function chat(prompt) {
  const response = await client.chat.completions.create({
    model: 'gpt-5',
    messages: [{ role: 'user', content: prompt }],
    temperature: 0.7
  });
  return response.choices[0].message.content;
}

const answer = await chat('Design a database schema for a multi-tenant SaaS app');
console.log(answer);

import json

tools = [
    {
        "type": "function",
        "function": {
            "name": "search_products",
            "description": "Search for products in the catalog",
            "parameters": {
                "type": "object",
                "properties": {
                    "query": {"type": "string", "description": "Search query"},
                    "category": {
                        "type": "string",
                        "enum": ["electronics", "clothing", "books", "home"],
                        "description": "Product category filter"
                    },
                    "max_price": {"type": "number", "description": "Maximum price in USD"},
                    "in_stock": {"type": "boolean", "description": "Only show in-stock items"}
                },
                "required": ["query"]
            }
        }
    },
    {
        "type": "function",
        "function": {
            "name": "get_order_status",
            "description": "Check the status of an order",
            "parameters": {
                "type": "object",
                "properties": {
                    "order_id": {"type": "string", "description": "The order ID"}
                },
                "required": ["order_id"]
            }
        }
    }
]

response = client.chat.completions.create(
    model="gpt-5",
    messages=[
        {"role": "user", "content": "Find me wireless headphones under $100 that are in stock"}
    ],
    tools=tools,
    tool_choice="auto"
)

tool_call = response.choices[0].message.tool_calls[0]
print(f"Function: {tool_call.function.name}")
print(f"Args: {tool_call.function.arguments}")
# Function: search_products
# Args: {"query": "wireless headphones", "category": "electronics", "max_price": 100, "in_stock": true}

response = client.chat.completions.create(
    model="gpt-5",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "What's in this architecture diagram? List all services and their connections."},
                {
                    "type": "image_url",
                    "image_url": {"url": "https://example.com/architecture.png"}
                }
            ]
        }
    ],
    max_tokens=2048
)

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

# Before (GPT-4o)
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[...],
    max_tokens=4096
)

# After (GPT-5) — just change the model name
response = client.chat.completions.create(
    model="gpt-5",
    messages=[...],
    max_tokens=4096  # Can now go up to 32K
)