name: runway-hello-world description: "Runway hello world \u2014 AI video generation and creative AI platform.\n
Use when working with Runway for video generation, image editing, or creative AI.\n
Trigger with phrases like "runway hello world", "runway-hello-world", "AI video
\ generation".\n" allowed-tools: Read, Write, Edit, Bash(pip:), Bash(npm:), Bash(curl:*), Grep version: 2.0.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io tags:

• saas
• runway
• ai
• video-generation
• creative compatibility: Designed for Claude Code, also compatible with Codex and OpenClaw

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