// Using fetch
const response = await fetch("https://openrouter.ai/api/v1/chat/completions", {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${OPENROUTER_API_KEY}`,
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    model: "openai/gpt-5.2",
    messages: [{ role: "user", content: "Hello!" }]
  })
});

// Using OpenAI SDK (Python)
from openai import OpenAI
client = OpenAI(base_url="https://openrouter.ai/api/v1", api_key=OPENROUTER_API_KEY)
response = client.chat.completions.create(
    model="openai/gpt-5.2",
    messages=[{"role": "user", "content": "Hello!"}]
)

{
  model: "anthropic/claude-sonnet-4.5",
  provider: {
    order: ["Anthropic", "Amazon Bedrock"],  // Preference order
    allow_fallbacks: true,                    // Enable backup providers
    sort: "price",                            // "price" | "throughput" | "latency"
    data_collection: "deny",                  // Privacy control
    zdr: true                                 // Zero Data Retention
  }
}

{
  models: ["anthropic/claude-sonnet-4.5", "openai/gpt-5.2", "google/gemini-3-pro"]
}

const response = await fetch(url, {
  body: JSON.stringify({ ...params, stream: true })
});

const reader = response.body.getReader();
const decoder = new TextDecoder();

while (true) {
  const { done, value } = await reader.read();
  if (done) break;

  const chunk = decoder.decode(value);
  // Parse SSE: "data: {...}\n"
  const data = JSON.parse(chunk.slice(6));
  console.log(data.choices[0]?.delta?.content);
}

const response = await fetch(url, {
  body: JSON.stringify({
    model: "openai/gpt-5.2",
    messages: [{ role: "user", content: "What's the weather in NYC?" }],
    tools: [{
      type: "function",
      function: {
        name: "get_weather",
        description: "Get weather for a location",
        parameters: {
          type: "object",
          properties: { location: { type: "string" } },
          required: ["location"]
        }
      }
    }]
  })
});

// Handle tool_calls in response, execute locally, return results

{
  response_format: {
    type: "json_schema",
    json_schema: {
      name: "response",
      strict: true,
      schema: {
        type: "object",
        properties: {
          answer: { type: "string" },
          confidence: { type: "number" }
        },
        required: ["answer", "confidence"],
        additionalProperties: false
      }
    }
  }
}

// Using plugin
{ plugins: [{ id: "web", max_results: 5 }] }

// Or model suffix
{ model: "openai/gpt-5.2:online" }

{
  model: "deepseek/deepseek-r1:thinking",
  reasoning: {
    effort: "high",       // xhigh, high, medium, low, minimal, none
    summary: "concise"    // auto, concise, detailed
  }
}

// Check response status
if (!response.ok) {
  const error = await response.json();
  // error.error.code: 400, 401, 402, 403, 429, 502, 503
  // error.error.message: Human-readable error
}