Make your first request

Setup

1. Select the intended organization in the dashboard.
2. Add prepaid credit in Billing and create an API key in API Keys. Copy the secret immediately; it is shown once.
3. Store the key in your application's server-side environment as NETRA_API_KEY. Choose an ID returned by the authenticated model list and set NETRA_MODEL to that exact value.
4. Send a small request and confirm its usage appears in Observe.

These shell examples use a POSIX shell. On Windows, supply the same environment values with PowerShell's $env:NETRA_API_KEY and $env:NETRA_MODEL, or use the Python/JavaScript examples directly. Placeholder values must be replaced locally; never paste real secrets into documentation or an agent conversation.

Discover model IDs

curl --fail-with-body https://api.netraruntime.com/v1/models \
  -H "Authorization: Bearer $NETRA_API_KEY"

The result is an object with a data array. Set NETRA_MODEL to an available Chat Completions model's id.

Use deepseek/deepseek-v4.1-flash for DeepSeek V4.1 Flash, or deepseek/deepseek-v4-flash-0731 for DeepSeek V4 Flash 0731. The examples below use V4 Flash 0731; replace the model ID to use V4.1 Flash. See Models and pricing for current rates and capabilities.

For deepseek/deepseek-v4-flash-0731, add "reasoning": {"enabled": false} for thinking off, or "reasoning": {"effort": "high"} to request reasoning. In Python put this object in extra_body; the native reasoning_effort field remains compatible. Check the model's supported controls before changing effort or using a reasoning budget.

cURL

curl --fail-with-body https://api.netraruntime.com/v1/chat/completions \
  -H "Authorization: Bearer $NETRA_API_KEY" \
  -H "Content-Type: application/json" \
  -H "X-Netra-Agent: quickstart" \
  -d "{\"model\":\"$NETRA_MODEL\",\"messages\":[{\"role\":\"user\",\"content\":\"Explain an API in one sentence.\"}],\"max_tokens\":128,\"reasoning\":{\"enabled\":false}}"

Python

Install the OpenAI SDK in your application's environment with pip install openai.

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.netraruntime.com/v1",
    api_key=os.environ["NETRA_API_KEY"],
    max_retries=0,
)
response = client.chat.completions.create(
    model=os.environ["NETRA_MODEL"],
    messages=[{"role": "user", "content": "Explain an API in one sentence."}],
    max_tokens=128,
    extra_body={"reasoning": {"enabled": False}},
    extra_headers={"X-Netra-Agent": "quickstart"},
)
print(response.choices[0].message.content)
print(response.usage)

JavaScript / TypeScript

Install with npm install openai. Run this example in a server-side Node.js application configured for ES modules.

import OpenAI from "openai";

if (!process.env.NETRA_API_KEY || !process.env.NETRA_MODEL) {
  throw new Error("Set NETRA_API_KEY and NETRA_MODEL before running.");
}
const client = new OpenAI({
  baseURL: "https://api.netraruntime.com/v1",
  apiKey: process.env.NETRA_API_KEY,
  maxRetries: 0,
});
const response = await client.chat.completions.create({
  model: process.env.NETRA_MODEL,
  messages: [{ role: "user", content: "Explain an API in one sentence." }],
  max_tokens: 128,
  reasoning: { enabled: false },
}, { headers: { "X-Netra-Agent": "quickstart" } });
console.log(response.choices[0].message.content);
console.log(response.usage);

These examples disable automatic SDK retries so you can decide whether a failed call should run again. Add bounded retries after implementing the request-ID guidance in Errors, limits, and retries.