الموسيقى والمؤثرات الصوتية

curl "https://api.venice.ai/api/v1/models?type=music" \
  -H "Authorization: Bearer $VENICE_API_KEY"

curl https://api.venice.ai/api/v1/audio/quote \
  -H "Content-Type: application/json" \
  -d '{
    "model": "elevenlabs-music",
    "duration_seconds": 30
  }'

{
  "quote": 0.69
}

{
  "model": "elevenlabs-music",
  "queue_id": "123e4567-e89b-12d3-a456-426614174000",
  "status": "QUEUED"
}

curl https://api.venice.ai/api/v1/audio/retrieve \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "elevenlabs-music",
    "queue_id": "123e4567-e89b-12d3-a456-426614174000"
  }' \
  --output response.bin

{
  "status": "PROCESSING",
  "average_execution_time": 20000,
  "execution_duration": 5200
}

import os
import time
from pathlib import Path

import requests

BASE_URL = "https://api.venice.ai/api/v1"
HEADERS = {
    "Authorization": f"Bearer {os.environ['VENICE_API_KEY']}",
    "Content-Type": "application/json",
}

generation = {
    "model": "elevenlabs-music",
    "prompt": "Warm cinematic strings with a gentle piano melody, hopeful and spacious",
    "duration_seconds": 30,
    "force_instrumental": True,
}

quote = requests.post(f"{BASE_URL}/audio/quote", json={
    "model": generation["model"],
    "duration_seconds": generation["duration_seconds"],
})
quote.raise_for_status()
print(f"Estimated cost: ${quote.json()['quote']:.2f}")

queued = requests.post(f"{BASE_URL}/audio/queue", headers=HEADERS, json=generation)
queued.raise_for_status()
job = queued.json()

content_type_to_extension = {
    "audio/mpeg": ".mp3",
    "audio/wav": ".wav",
    "audio/flac": ".flac",
    "audio/mp4": ".m4a",
}

while True:
    result = requests.post(
        f"{BASE_URL}/audio/retrieve",
        headers=HEADERS,
        json={"model": job["model"], "queue_id": job["queue_id"]},
    )
    result.raise_for_status()
    content_type = result.headers.get("Content-Type", "").split(";")[0].strip()

    if content_type == "application/json":
        status = result.json()
        print(f"Status: {status['status']}")
        time.sleep(5)
        continue

    extension = content_type_to_extension.get(content_type, ".bin")
    output = Path("generated-audio" + extension)
    output.write_bytes(result.content)
    print(f"Saved {output}")
    break

requests.post(
    f"{BASE_URL}/audio/complete",
    headers=HEADERS,
    json={"model": job["model"], "queue_id": job["queue_id"]},
).raise_for_status()