Documentation Index
Fetch the complete documentation index at: /llms.txt
Use this file to discover all available pages before exploring further.
Call your Provisioned Throughput endpoint by changing the base URL, the API key, and the model ID in the SDK you already use.
model field.
| Base URL | https://inference.cloud.vessl.ai/v1 |
| Authentication | Your API key, sent as a bearer token (Authorization: Bearer <api-key>) |
| Model | The model ID shown next to the model name on the model page |
VESSL_API_KEY environment variable first:
export VESSL_API_KEY="<api-key>"
curl https://inference.cloud.vessl.ai/v1/chat/completions \
-H "Authorization: Bearer $VESSL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "<model-id>",
"messages": [
{"role": "user", "content": "Hello! Who are you?"}
]
}'
import json
import os
import urllib.request
request = urllib.request.Request(
"https://inference.cloud.vessl.ai/v1/chat/completions",
method="POST",
headers={
"Authorization": f"Bearer {os.environ['VESSL_API_KEY']}",
"Content-Type": "application/json",
},
data=json.dumps({
"model": "<model-id>",
"messages": [
{"role": "user", "content": "Hello! Who are you?"},
],
}).encode(),
)
with urllib.request.urlopen(request, timeout=120) as response:
body = json.load(response)
print(body["choices"][0]["message"]["content"])
const response = await fetch("https://inference.cloud.vessl.ai/v1/chat/completions", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.VESSL_API_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
model: "<model-id>",
messages: [
{ role: "user", content: "Hello! Who are you?" },
],
}),
});
if (!response.ok) {
throw new Error(`Request failed: ${response.status} ${await response.text()}`);
}
const body = await response.json();
console.log(body.choices[0].message.content);