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Veo Video Generation with Google AI Studio

Generate videos using Google's Veo model through LiteLLM's pass-through endpoints.

Quick Start​

LiteLLM allows you to use Google AI Studio's Veo video generation API through pass-through routes with zero configuration.

1. Add Google AI Studio API Key to your environment​

export GEMINI_API_KEY="your_google_ai_studio_api_key"

2. Start LiteLLM Proxy​

litellm

# RUNNING on http://0.0.0.0:4000

3. Generate Video​

import requests
import time
import json

# Configuration
BASE_URL = "http://localhost:4000/gemini/v1beta"
API_KEY = "anything"  # Use "anything" as the key

headers = {
    "x-goog-api-key": API_KEY,
    "Content-Type": "application/json"
}

# Step 1: Initiate video generation
def generate_video(prompt):
    url = f"{BASE_URL}/models/veo-3.0-generate-preview:predictLongRunning"
    payload = {
        "instances": [{
            "prompt": prompt
        }]
    }
    
    response = requests.post(url, headers=headers, json=payload)
    response.raise_for_status()
    
    data = response.json()
    return data.get("name")  # Operation name

# Step 2: Poll for completion
def wait_for_completion(operation_name):
    operation_url = f"{BASE_URL}/{operation_name}"
    
    while True:
        response = requests.get(operation_url, headers=headers)
        response.raise_for_status()
        
        data = response.json()
        
        if data.get("done", False):
            # Extract video URI
            video_uri = data["response"]["generateVideoResponse"]["generatedSamples"][0]["video"]["uri"]
            return video_uri
        
        time.sleep(10)  # Wait 10 seconds before next poll

# Step 3: Download video
def download_video(video_uri, filename="generated_video.mp4"):
    # Replace Google URL with LiteLLM proxy URL
    litellm_url = video_uri.replace(
        "https://generativelanguage.googleapis.com/v1beta", 
        BASE_URL
    )
    
    response = requests.get(litellm_url, headers=headers, stream=True)
    response.raise_for_status()
    
    with open(filename, 'wb') as f:
        for chunk in response.iter_content(chunk_size=8192):
            if chunk:
                f.write(chunk)
    
    return filename

# Complete workflow
prompt = "A cat playing with a ball of yarn in a sunny garden"

print("Generating video...")
operation_name = generate_video(prompt)

print("Waiting for completion...")
video_uri = wait_for_completion(operation_name)

print("Downloading video...")
filename = download_video(video_uri)

print(f"Video saved as: {filename}")

Complete Example​

For a full working example with error handling and logging, see our Veo Video Generation Cookbook.

How It Works​

  1. Video Generation Request: Send a prompt to Veo's predictLongRunning endpoint
  2. Operation Polling: Monitor the long-running operation until completion
  3. File Download: Download the generated video through LiteLLM's pass-through with automatic redirect handling

LiteLLM handles:

  • ✅ Authentication with Google AI Studio
  • ✅ Request routing and proxying
  • ✅ Automatic redirect handling for file downloads

Configuration Options​

Environment Variables​

export GEMINI_API_KEY="your_google_ai_studio_api_key"