curl --request POST \
  --url https://api.zerogpu.ai/v1/chat/completions \
  --header 'Content-Type: application/json' \
  --header 'x-api-key: <api-key>' \
  --data '
{
  "model": "deepseek-v4-flash",
  "messages": [
    {
      "role": "system",
      "content": "You are a pragmatic staff engineer. Be concise."
    },
    {
      "role": "user",
      "content": "Plan the migration of a nightly cron-based ETL job to an event-driven pipeline. 4 steps max."
    }
  ]
}
'

import requests

url = "https://api.zerogpu.ai/v1/chat/completions"

payload = {
    "model": "deepseek-v4-flash",
    "messages": [
        {
            "role": "system",
            "content": "You are a pragmatic staff engineer. Be concise."
        },
        {
            "role": "user",
            "content": "Plan the migration of a nightly cron-based ETL job to an event-driven pipeline. 4 steps max."
        }
    ]
}
headers = {
    "x-api-key": "<api-key>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {'x-api-key': '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    model: 'deepseek-v4-flash',
    messages: [
      {role: 'system', content: 'You are a pragmatic staff engineer. Be concise.'},
      {
        role: 'user',
        content: 'Plan the migration of a nightly cron-based ETL job to an event-driven pipeline. 4 steps max.'
      }
    ]
  })
};

fetch('https://api.zerogpu.ai/v1/chat/completions', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

false

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.zerogpu.ai/v1/chat/completions"

	payload := strings.NewReader("{\n  \"model\": \"deepseek-v4-flash\",\n  \"messages\": [\n    {\n      \"role\": \"system\",\n      \"content\": \"You are a pragmatic staff engineer. Be concise.\"\n    },\n    {\n      \"role\": \"user\",\n      \"content\": \"Plan the migration of a nightly cron-based ETL job to an event-driven pipeline. 4 steps max.\"\n    }\n  ]\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("x-api-key", "<api-key>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

require 'uri'
require 'net/http'

url = URI("https://api.zerogpu.ai/v1/chat/completions")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["x-api-key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"model\": \"deepseek-v4-flash\",\n  \"messages\": [\n    {\n      \"role\": \"system\",\n      \"content\": \"You are a pragmatic staff engineer. Be concise.\"\n    },\n    {\n      \"role\": \"user\",\n      \"content\": \"Plan the migration of a nightly cron-based ETL job to an event-driven pipeline. 4 steps max.\"\n    }\n  ]\n}"

response = http.request(request)
puts response.read_body

{
  "id": "id-1785523944762",
  "object": "chat.completion",
  "created": 1785523944,
  "model": "deepseek-v4-flash",
  "choices": [
    {
      "index": 0,
      "finish_reason": "stop",
      "message": {
        "role": "assistant",
        "content": "**1. Inventory the job** – Document inputs, outputs, schedule, and every downstream consumer of the cron ETL so nothing breaks silently.\n\n**2. Define the events** – Pick the real trigger (file landing, DB change, message) and publish it to a queue or event bus with a versioned schema.\n\n**3. Run in parallel** – Build the event-driven consumer alongside cron, write to a shadow table, and diff outputs until they match.\n\n**4. Cut over with a rollback path** – Point consumers at the new output, keep cron paused (not deleted) for one cycle, then decommission.",
        "reasoning": "Cron ETL to event-driven: inventory the current job first, define the trigger events, run the new pipeline in parallel against a shadow output, then cut over with a rollback path. Four steps, each actionable.",
        "tool_calls": []
      }
    }
  ],
  "usage": {
    "prompt_tokens": 52,
    "completion_tokens": 158,
    "total_tokens": 210
  }
}