RunwayML - Image Generation

Overview

Property	Details
Description	RunwayML provides advanced AI-powered image generation with high-quality results
Provider Route on LiteLLM	runwayml/
Supported Operations	/images/generations
Link to Provider Doc	RunwayML API ↗

LiteLLM supports RunwayML's Gen-4 image generation API, allowing you to generate high-quality images from text prompts.

Quick Start

Basic Image Generation

from litellm import image_generation
import os

os.environ["RUNWAYML_API_KEY"] = "your-api-key"

response = image_generation(
    model="runwayml/gen4_image",
    prompt="A serene mountain landscape at sunset",
    size="1920x1080"
)

print(response.data[0].url)

Authentication

Set your RunwayML API key:

Set API Key

import os

os.environ["RUNWAYML_API_KEY"] = "your-api-key"

Supported Parameters

Parameter	Type	Required	Description
model	string	Yes	Model to use (e.g., runwayml/gen4_image)
prompt	string	Yes	Text description for the image
size	string	No	Image dimensions (default: 1920x1080)

Supported Sizes

• 1024x1024
• 1792x1024
• 1024x1792
• 1920x1080 (default)
• 1080x1920

Async Usage

Async Image Generation

from litellm import aimage_generation
import os
import asyncio

os.environ["RUNWAYML_API_KEY"] = "your-api-key"

async def generate_image():
    response = await aimage_generation(
        model="runwayml/gen4_image",
        prompt="A futuristic city skyline at night",
        size="1920x1080"
    )
    
    print(response.data[0].url)

asyncio.run(generate_image())

LiteLLM Proxy Usage

Add RunwayML to your proxy configuration:

config.yaml

model_list:
  - model_name: gen4-image
    litellm_params:
      model: runwayml/gen4_image
      api_key: os.environ/RUNWAYML_API_KEY

Start the proxy:

litellm --config /path/to/config.yaml

Generate images through the proxy:

Proxy Request

curl --location 'http://localhost:4000/v1/images/generations' \
--header 'Content-Type: application/json' \
--header 'x-litellm-api-key: sk-1234' \
--data '{
    "model": "runwayml/gen4_image",
    "prompt": "A serene mountain landscape at sunset",
    "size": "1920x1080"
}'

Supported Models

Model	Description	Default Size
runwayml/gen4_image	High-quality image generation	1920x1080

Cost Tracking

LiteLLM automatically tracks RunwayML image generation costs:

Cost Tracking

from litellm import image_generation, completion_cost

response = image_generation(
    model="runwayml/gen4_image",
    prompt="A serene mountain landscape at sunset",
    size="1920x1080"
)

cost = completion_cost(completion_response=response)
print(f"Image generation cost: ${cost}")

Supported Features

Feature	Supported
Image Generation	✅
Cost Tracking	✅
Logging	✅
Fallbacks	✅
Load Balancing	✅

How It Works

RunwayML uses an asynchronous task-based API pattern. LiteLLM handles the polling and response transformation automatically.

Complete Flow Diagram

What LiteLLM Does For You

When you call litellm.image_generation() or /v1/images/generations:

1. Request Transformation: Converts OpenAI image generation format → RunwayML format
2. Submits Task: Sends transformed request to RunwayML API
3. Receives Task ID: Captures the task ID from the initial response
4. Automatic Polling:
   • Polls the task status endpoint every 2 seconds
   • Continues until status is SUCCEEDED or FAILED
   • Default timeout: 10 minutes (configurable via RUNWAYML_POLLING_TIMEOUT)
5. Response Transformation: Converts RunwayML format → OpenAI format
6. Returns Result: Sends unified OpenAI format response to client

Polling Configuration:

• Default timeout: 600 seconds (10 minutes)
• Configurable via RUNWAYML_POLLING_TIMEOUT environment variable
• Uses sync (time.sleep()) or async (await asyncio.sleep()) based on call type

info

Typical processing time: 10-30 seconds depending on image size and complexity