API de VRAMfarm

import os, time, requests

API = "https://vramfarm.com/api"
s = requests.Session()
s.headers["Authorization"] = f"Bearer {os.environ['GF_TOKEN']}"

r = s.post(f"{API}/instances", json={"gpu": "rtx-4090", "count": 1, "template": "pytorch"})
r.raise_for_status()
sid = r.json()["id"]
try:
    while True:
        srv = s.get(f"{API}/instances/{sid}").json()
        if srv["status"] == "running":
            break
        if srv["status"] == "stopped":
            raise RuntimeError(srv["error"])
        print(srv["stage_note"] or srv["stage"])
        time.sleep(10)
    print(srv["access"]["ssh"]["command"])
    # your work goes here: ssh, scp, requests to the app on the server
finally:
    s.post(f"{API}/instances/stop", json={"id": sid})

// Node.js 18+, .mjs file
const API = "https://vramfarm.com/api";
const headers = { Authorization: `Bearer ${process.env.GF_TOKEN}`, "Content-Type": "application/json" };
const call = async (path, body) => {
  const r = await fetch(API + path, body ? { method: "POST", headers, body: JSON.stringify(body) } : { headers });
  const data = await r.json();
  if (!r.ok) throw new Error(`${r.status} ${data.code}: ${data.error}`);
  return data;
};

const { id } = await call("/instances", { gpu: "rtx-4090", count: 1, template: "pytorch" });
try {
  let srv;
  while ((srv = await call(`/instances/${id}`)).status !== "running") {
    if (srv.status === "stopped") throw new Error(srv.error);
    console.log(srv.stage_note ?? srv.stage);
    await new Promise((ok) => setTimeout(ok, 10_000));
  }
  console.log(srv.access.ssh.command);
} finally {
  await call("/instances/stop", { id });
}

#!/usr/bin/env bash
# needs curl and jq
set -euo pipefail
API=https://vramfarm.com/api; H="Authorization: Bearer $GF_TOKEN"; J="Content-Type: application/json"

ID=$(curl -sf "$API/instances" -H "$H" -H "$J" \
  -d '{"gpu":"rtx-4090","count":1,"template":"pytorch"}' | jq -r .id)
trap 'curl -sf "$API/instances/stop" -H "$H" -H "$J" -d "{\"id\":$ID}" >/dev/null' EXIT

for i in $(seq 1 120); do
  S=$(curl -sf "$API/instances/$ID" -H "$H")
  ST=$(jq -r .status <<<"$S")
  [ "$ST" = running ] && break
  [ "$ST" = stopped ] && { echo "failed to start: $(jq -r .error <<<"$S")"; exit 1; }
  echo "  $(jq -r '.stage_note // .stage' <<<"$S")"; sleep 10
done

SSH=$(jq -r .access.ssh.command <<<"$S")
$SSH -o StrictHostKeyChecking=accept-new 'cd /workspace && python train.py'

import os, requests

H = {"Authorization": f"Bearer {os.environ['GF_TOKEN']}"}
print(requests.get("https://vramfarm.com/api/account", headers=H).json())

const H = { Authorization: `Bearer ${process.env.GF_TOKEN}` };
console.log(await fetch("https://vramfarm.com/api/account", { headers: H }).then((r) => r.json()));

export GF_TOKEN=gf_live_xxxxxxxxxxxxxxxxxxxxxxxx
curl -s https://vramfarm.com/api/account -H "Authorization: Bearer $GF_TOKEN"

import time, requests

def call(method, url, **kw):
    for attempt in range(5):
        r = requests.request(method, url, **kw)
        if r.status_code not in (429, 502, 503):
            return r
        time.sleep(int(r.headers.get("Retry-After", 30)))
    return r

async function call(url, opts = {}) {
  for (let attempt = 0; attempt < 5; attempt++) {
    const r = await fetch(url, opts);
    if (![429, 502, 503].includes(r.status)) return r;
    await new Promise((ok) => setTimeout(ok, (+r.headers.get("Retry-After") || 30) * 1000));
  }
  throw new Error("API is not responding");
}

curl -s --retry 5 --retry-delay 30 --retry-all-errors \
  https://vramfarm.com/api/account -H "Authorization: Bearer $GF_TOKEN"

# SSH port from access.ssh.port; -N: tunnel only, no shell
ssh -p 31001 root@vramfarm.com -N -L 11434:127.0.0.1:11434

import json, time, requests

APP = "https://u.vramfarm.com/api/a/<key>/"                                   # access.app of the server
wf = json.load(open("workflow_api.json"))        # Workflow → Export (API) in ComfyUI
wf["6"]["inputs"]["text"] = "a cat in a spacesuit, photo"  # node number from your file

pid = requests.post(APP + "prompt", json={"prompt": wf}).json()["prompt_id"]
while pid not in (h := requests.get(APP + f"history/{pid}").json()):
    time.sleep(2)

for node in h[pid]["outputs"].values():
    for img in node.get("images", []):
        data = requests.get(APP + "view", params=img).content  # filename, subfolder, type
        open(img["filename"], "wb").write(data)

import { readFile, writeFile } from "node:fs/promises";

const APP = "https://u.vramfarm.com/api/a/<key>/";  // access.app of the server
const wf = JSON.parse(await readFile("workflow_api.json", "utf8"));
wf["6"].inputs.text = "a cat in a spacesuit, photo";

const { prompt_id } = await fetch(APP + "prompt", {
  method: "POST", headers: { "Content-Type": "application/json" }, body: JSON.stringify({ prompt: wf }),
}).then((r) => r.json());

let h = {};
while (!h[prompt_id]) {
  await new Promise((ok) => setTimeout(ok, 2000));
  h = await fetch(APP + `history/${prompt_id}`).then((r) => r.json());
}
for (const node of Object.values(h[prompt_id].outputs))
  for (const img of node.images ?? []) {
    const r = await fetch(APP + "view?" + new URLSearchParams(img));
    await writeFile(img.filename, Buffer.from(await r.arrayBuffer()));
  }

APP="https://u.vramfarm.com/api/a/<key>/"
curl -s "$APP"prompt -H "Content-Type: application/json" \
  -d "{\"prompt\": $(cat workflow_api.json)}"
# {"prompt_id":"8f2c…","number":0}
curl -s "$APP"history/8f2c…
curl -s -o out.png "$APP""view?filename=ComfyUI_00001_.png&type=output"

# pip install gradio_client
from gradio_client import Client

client = Client("http://localhost:7860/")   # through an SSH tunnel or the address from the dashboard
client.view_api()                           # list of methods and their parameters

# method name and argument order: from view_api() or "Use via API"
audio_path = client.predict("Hello! This is a speech test.", api_name="/generate")
print(audio_path)                           # the result file on your computer

// npm install @gradio/client
import { Client } from "@gradio/client";

const client = await Client.connect("http://localhost:7860/");
console.log(await client.view_api());

const res = await client.predict("/generate", ["Hello! This is a speech test."]);
console.log(res.data);

# Gradio 5: first the request, then the result by event_id
curl -s -X POST http://localhost:7860/gradio_api/call/generate \
  -H "Content-Type: application/json" \
  -d '{"data": ["Hello! This is a speech test."]}'
# {"event_id":"3b1f…"}
curl -sN http://localhost:7860/gradio_api/call/generate/3b1f…

import requests

r = requests.post("http://localhost:11434/api/chat", json={
    "model": "qwen3:8b",          # chat-pro uses qwen3:32b
    "messages": [{"role": "user", "content": "In one sentence: what is CUDA?"}],
    "stream": False,
})
print(r.json()["message"]["content"])

const r = await fetch("http://localhost:11434/api/chat", {
  method: "POST",
  headers: { "Content-Type": "application/json" },
  body: JSON.stringify({
    model: "qwen3:8b",
    messages: [{ role: "user", content: "In one sentence: what is CUDA?" }],
    stream: false,
  }),
});
console.log((await r.json()).message.content);

curl -s http://localhost:11434/api/chat -d '{
  "model": "qwen3:8b",
  "messages": [{"role": "user", "content": "In one sentence: what is CUDA?"}],
  "stream": false
}'

# pip install openai
from openai import OpenAI

client = OpenAI(base_url="https://u.vramfarm.com/api/a/<key>/v1",  # access.app
                api_key="EMPTY")                                    # no key needed
r = client.chat.completions.create(
    model="Qwen/Qwen2.5-7B-Instruct",
    messages=[{"role": "user", "content": "Write a haiku about a graphics card"}],
)
print(r.choices[0].message.content)

const BASE = "https://u.vramfarm.com/api/a/<key>/v1";  // access.app
const r = await fetch(`${BASE}/chat/completions`, {
  method: "POST",
  headers: { "Content-Type": "application/json" },
  body: JSON.stringify({
    model: "Qwen/Qwen2.5-7B-Instruct",
    messages: [{ role: "user", content: "Write a haiku about a graphics card" }],
  }),
});
console.log((await r.json()).choices[0].message.content);

BASE="https://u.vramfarm.com/api/a/<key>/v1"
curl -s "$BASE/models"
curl -s "$BASE/chat/completions" -H "Content-Type: application/json" -d '{
  "model": "Qwen/Qwen2.5-7B-Instruct",
  "messages": [{"role": "user", "content": "Write a haiku about a graphics card"}]
}'