vLLM OpenAI-Compatible Server

Trooper.AI provides a fully automated vLLM deployment template that installs, configures, and runs an OpenAI-compatible inference server on your GPU server using systemd.

The goal:

The template automatically:

You only control a small set of public parameters.

Public Parameters

These parameters can be set via environment variables before running the installer.

Variable Description
TOKEN API key for authentication
modelname HuggingFace model path
hf_token HuggingFace token (for gated models)
commandline_args Optional extra vLLM CLI arguments

What the Template Does

  1. Detects GPU architecture (Volta, Ampere, Ada, Hopper, Blackwell)

  2. Detects VRAM size

  3. Selects optimal precision automatically:

    • FP8 > BF16 > FP16

  4. Uses FP16 KV cache for stability

  5. Tunes:

    • max concurrent sequences
    • batched token size
    • memory utilization

  6. Installs vLLM with CUDA

  7. Creates a systemd service:

    Code 
    vllm-server.service

  8. Starts a persistent OpenAI-compatible API server on a secure HTTPS endpoint.

No manual tuning is required.

API Endpoints

Base URL:

Code 
http://YOUR_SERVER:PORT/v1

Endpoints:

  • /v1/models
  • /v1/completions
  • /v1/chat/completions

Authentication header:

Code 
Authorization: Bearer YOUR_TOKEN_FROM_CONFIG

Python Client Example

python 
from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://YOUR_SERVER_ENDPOINT.apps.trooper.ai/v1"
)

resp = client.chat.completions.create(
    model="Qwen/Qwen3-14B",
    messages=[
        {"role": "user", "content": "Hello, what is vLLM?"}
    ],
    max_tokens=200
)

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

Node.js Client Example

javascript 
import OpenAI from "openai";

const client = new OpenAI({
  apiKey: "YOUR_API_KEY",
  baseURL: "https://YOUR_SERVER_ENDPOINT.apps.trooper.ai/v1"
});

const completion = await client.chat.completions.create({
  model: "Qwen/Qwen3-14B",
  messages: [
    { role: "user", content: "Hello from Node.js" }
  ],
  max_tokens: 200
});

console.log(completion.choices[0].message.content);

PHP Client Example

php 
<?php

$ch = curl_init("https://YOUR_SERVER_ENDPOINT.apps.trooper.ai/v1/chat/completions");

$data = [
  "model" => "Qwen/Qwen3-14B",
  "messages" => [
    ["role" => "user", "content" => "Hello from PHP"]
  ],
  "max_tokens" => 200
];

curl_setopt_array($ch, [
  CURLOPT_POST => true,
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer YOUR_API_KEY",
    "Content-Type: application/json"
  ],
  CURLOPT_POSTFIELDS => json_encode($data)
]);

$response = curl_exec($ch);
curl_close($ch);

echo $response;

Streaming Example

Python Streaming

python 
resp = client.chat.completions.create(
    model="Qwen/Qwen3-14B",
    messages=[{"role":"user","content":"Explain transformers"}],
    stream=True
)

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

Node.js Streaming

javascript 
const stream = await client.chat.completions.create({
  model: "Qwen/Qwen3-14B",
  messages: [{ role: "user", content: "Explain transformers" }],
  stream: true
});

for await (const chunk of stream) {
  process.stdout.write(chunk.choices[0].delta?.content || "");
}

Use Cases

Trooper.AI vLLM servers are designed for:

  • SaaS AI backends
  • Chatbots
  • Code assistants
  • RAG systems
  • Multi-user inference servers
  • High throughput batch inference
  • GPU rental environments

Performance Philosophy

Trooper.AI uses:

  • Automatic architecture tuning
  • Automatic precision selection
  • VRAM-aware batching
  • Stable KV cache configuration

This avoids:

  • GPU misconfiguration
  • Precision crashes
  • VRAM fragmentation
  • Context instability

Summary

The Trooper.AI vLLM template gives you:

  • OpenAI-compatible API
  • Automatic GPU optimization
  • Production-safe defaults
  • Minimal configuration
  • Maximum throughput

You only choose the model and API key.

Everything else is optimized automatically.

Support

For advanced tuning, multi-GPU, or custom presets, contact Trooper.AI support.