Quickstart

Your first call in 30 seconds

Make sure you have an API key from the dashboard, then pick a language. The QSP-specific bits are just base_url and the key — everything else is standard OpenAI SDK.

1. Get an API key

Sign in at quicksilverpro.io/dashboard, then copy the key from the "Connect your agent" section.

Set it as the QSP_KEY environment variable so the snippets below work as-is:

shell
export QSP_KEY="sk-..."

2. Make the call

Python

python
import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.quicksilverpro.io/v1",
    api_key=os.environ["QSP_KEY"],
)

resp = client.chat.completions.create(
    model="deepseek-v4-flash",
    messages=[{"role": "user", "content": "Hello!"}],
    reasoning={"enabled": False},
)
print(resp.choices[0].message.content)

Node.js / TypeScript

typescript
import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.quicksilverpro.io/v1",
  apiKey: process.env.QSP_KEY,
});

const resp = await client.chat.completions.create({
  model: "deepseek-v4-flash",
  messages: [{ role: "user", content: "Hello!" }],
  reasoning: { enabled: false },
});
console.log(resp.choices[0].message.content);

Swift

swift
import Foundation
import OpenAI

let openAI = OpenAI(
  configuration: .init(
    token: ProcessInfo.processInfo.environment["QSP_KEY"]!,
    host: "api.quicksilverpro.io",
    basePath: "/v1"
  )
)

let query = ChatQuery(
  messages: [.user(.init(content: .string("Hello!")))],
  model: "deepseek-v4-flash"
)
let resp = try await openAI.chats(query: query)
print(resp.choices.first?.message.content?.string ?? "")

curl

shell
curl https://api.quicksilverpro.io/v1/chat/completions \
  -H "Authorization: Bearer $QSP_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-v4-flash",
    "messages": [{"role": "user", "content": "Hello!"}],
    "reasoning": {"enabled": false}
  }'

3. What you get back

Standard OpenAI chat-completions JSON. choices[0].message.content is the model's reply. usage reports prompt and completion tokens plus a synthetic cost field computed from the public per-million rate.

json
{
  "id": "chatcmpl-...",
  "object": "chat.completion",
  "created": 1715800000,
  "model": "deepseek-v4-flash",
  "choices": [{
    "index": 0,
    "message": {"role": "assistant", "content": "Hello! How can I help?"},
    "finish_reason": "stop"
  }],
  "usage": {
    "prompt_tokens": 9,
    "completion_tokens": 8,
    "total_tokens": 17,
    "cost": 0.00000275
  }
}

Next steps