视频放大

curl https://api.venice.ai/api/v1/video/queue \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "topaz-video-upscale",
    "video_url": "https://example.com/input-video.mp4",
    "upscale_factor": 2
  }'

import requests

response = requests.post(
    "https://api.venice.ai/api/v1/video/queue",
    headers={"Authorization": "Bearer YOUR_API_KEY"},
    json={
        "model": "topaz-video-upscale",
        "video_url": "https://example.com/input-video.mp4",
        "upscale_factor": 2,
    },
)

data = response.json()
queue_id = data["queue_id"]
download_url = data.get("download_url")
print(f"Queued: {queue_id}")

const response = await fetch("https://api.venice.ai/api/v1/video/queue", {
  method: "POST",
  headers: {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    model: "topaz-video-upscale",
    video_url: "https://example.com/input-video.mp4",
    upscale_factor: 2,
  }),
});

const { queue_id, download_url } = await response.json();
console.log(`Queued: ${queue_id}`);

curl https://api.venice.ai/api/v1/video/retrieve \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "topaz-video-upscale", "queue_id": "abc123-def456-..."}' \
  -o upscaled.mp4 \
  -w '%{content_type}\n'

import time

while True:
    result = requests.post(
        "https://api.venice.ai/api/v1/video/retrieve",
        headers={"Authorization": "Bearer YOUR_API_KEY"},
        json={"model": "topaz-video-upscale", "queue_id": queue_id},
    )
    result.raise_for_status()

    if "video/mp4" in result.headers.get("Content-Type", ""):
        with open("upscaled.mp4", "wb") as f:
            f.write(result.content)
        break

    if result.json().get("status") == "COMPLETED" and download_url:
        with open("upscaled.mp4", "wb") as f:
            f.write(requests.get(download_url).content)
        break

    time.sleep(5)

print("Saved upscaled.mp4")

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

const poll = async (queueId, downloadUrl) => {
  while (true) {
    const res = await fetch("https://api.venice.ai/api/v1/video/retrieve", {
      method: "POST",
      headers: {
        "Authorization": "Bearer YOUR_API_KEY",
        "Content-Type": "application/json",
      },
      body: JSON.stringify({ model: "topaz-video-upscale", queue_id: queueId }),
    });
    if (!res.ok) {
      throw new Error(`${res.status}: ${await res.text()}`);
    }

    if (res.headers.get("Content-Type")?.includes("video/mp4")) {
      await writeFile("upscaled.mp4", Buffer.from(await res.arrayBuffer()));
      return;
    }

    const data = await res.json();
    if (data.status === "COMPLETED" && downloadUrl) {
      const video = await fetch(downloadUrl);
      await writeFile("upscaled.mp4", Buffer.from(await video.arrayBuffer()));
      return;
    }

    await new Promise((r) => setTimeout(r, 5000));
  }
};

await poll(queue_id, download_url);
console.log("Saved upscaled.mp4");