Call your Inference API endpoint

Each running Inference API endpoint gives you three values you need to make a request:

An endpoint URL
A model value for the request
An Inference API key from the same organization

Open the endpoint details and use the generated Quick-start snippets for Python, JavaScript, or curl. They contain the values expected by that endpoint.

The current quick-start flow documents the OpenAI-compatible Chat Completions interface. Do not assume other OpenAI API routes are supported unless they are documented separately.

Use the endpoint URL as shown

The endpoint URL already includes its API version path. It typically looks like:

https://YOUR_ENDPOINT_HOST/v1

Use this full value as the base URL in an SDK client.

Do not append another /v1. For a direct Chat Completions request, add /chat/completions to the endpoint URL, not another API-version segment.

Use the exact model value from the snippet

Chat Completions requests include a model field. Copy the exact value generated for the endpoint. It can differ from:

The endpoint name you chose
The shorter model title in the catalog
The identifier used by another or older endpoint

If you receive a model-not-found error, check this value first.

Python

Install the OpenAI SDK:

pip install openai

Then use your endpoint values:

from openai import OpenAI

client = OpenAI(
    base_url="YOUR_ENDPOINT_URL",
    api_key="YOUR_INFERENCE_API_KEY",
)

response = client.chat.completions.create(
    model="YOUR_MODEL_VALUE",
    messages=[
        {"role": "user", "content": "Hello!"}
    ],
)

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

JavaScript

Install the OpenAI package in your Node.js project:

npm install openai

Then configure the client with the same endpoint URL and key:

import OpenAI from 'openai'

const client = new OpenAI({
  baseURL: 'YOUR_ENDPOINT_URL',
  apiKey: 'YOUR_INFERENCE_API_KEY',
})

const response = await client.chat.completions.create({
  model: 'YOUR_MODEL_VALUE',
  messages: [{ role: 'user', content: 'Hello!' }],
})

console.log(response.choices[0].message.content)

curl

For a direct request, append /chat/completions to the endpoint URL and send the API key as a bearer token:

curl YOUR_ENDPOINT_URL/chat/completions \
  -H "Authorization: Bearer YOUR_INFERENCE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "YOUR_MODEL_VALUE",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Protect your API key

Do not commit the key to source control. For local testing, store it in an environment variable or another local secret store. For deployed applications, use the secret-management mechanism provided by your runtime or hosting platform.

If a key is exposed, create a replacement, update the applications that use it, and revoke the exposed key.

See Create and manage Inference API keys for the full key lifecycle.

Before troubleshooting the request

Check these three things first:

The endpoint is Running or Partially running.
The API key is Active and belongs to the same organization as the endpoint.
The endpoint URL and model value were copied from that endpoint’s Quick-start snippet.

For authentication, capacity, latency, or endpoint-state problems, see Troubleshoot Hivenet Inference API.

Get Started

Essentials

Inference API

Organizations

Connectivity

File transfer

Troubleshooting

Account and billing

Reference

Call your Inference API endpoint

Use the endpoint URL as shown

Use the exact model value from the snippet

Python

JavaScript

curl

Protect your API key

Before troubleshooting the request

Next steps

​Use the endpoint URL as shown

​Use the exact model value from the snippet

​Python

​JavaScript

​curl

​Protect your API key

​Before troubleshooting the request

​Next steps

Use the endpoint URL as shown

Use the exact model value from the snippet

Python

JavaScript

curl

Protect your API key

Before troubleshooting the request

Next steps