Runway Hello World

Overview

Generate your first AI video from a text prompt using Runway's Gen-3 Alpha model.

Prerequisites

• Completed runway-install-auth
• API credits available in your Runway account

Instructions

Step 1: Text-to-Video Generation

from runwayml import RunwayML

client = RunwayML()

# Create a text-to-video generation task
task = client.image_to_video.create(
    model='gen3a_turbo',
    prompt_text='A golden retriever running through a field of sunflowers, cinematic lighting, slow motion',
    duration=5,  # 5 or 10 seconds
    ratio='16:9',  # 16:9 or 9:16
)
print(f"Task created: {task.id}")

Step 2: Poll for Completion

import time

# The SDK has a built-in helper for polling
task_result = client.tasks.retrieve(task.id)

# Or poll manually
while task_result.status not in ('SUCCEEDED', 'FAILED'):
    time.sleep(5)
    task_result = client.tasks.retrieve(task.id)
    print(f"  Status: {task_result.status}")

if task_result.status == 'SUCCEEDED':
    print(f"Video URL: {task_result.output[0]}")
else:
    print(f"Failed: {task_result.failure}")

Step 3: Download the Video

import urllib.request

if task_result.status == 'SUCCEEDED':
    video_url = task_result.output[0]
    urllib.request.urlretrieve(video_url, 'output.mp4')
    print("Video saved to output.mp4")

Step 4: Using the Built-in Wait Helper

# Simpler approach — SDK polls automatically
task = client.image_to_video.create(
    model='gen3a_turbo',
    prompt_text='Ocean waves crashing on rocky cliffs at sunset, aerial view',
    duration=5,
)
# Wait for completion (default timeout: 10 minutes)
result = task.wait_for_task_output()
print(f"Video: {result.output[0]}")

Output

• Video generation task created
• Task polled until completion
• Generated video URL retrieved
• Video downloaded to local file

Error Handling

Resources

• API Getting Started
• API Reference
• Input Parameters

Next Steps

Advanced text-to-video: runway-core-workflow-a