Veo Video Generation and Editing
This skill provides comprehensive workflows for using Google's Veo models (Veo 2 and Veo 3) via the google-genai Python SDK.
Quick Start Setup
All Veo operations require the google-genai library and an authenticated client with Vertex AI enabled.
from google import genai
from google.genai import types
import os
PROJECT_ID = os.environ.get("GOOGLE_CLOUD_PROJECT")
LOCATION = os.environ.get("GOOGLE_CLOUD_REGION", "us-central1")
client = genai.Client(vertexai=True, project=PROJECT_ID, location=LOCATION)
Reference Materials
- Generation (Veo 3): Text-to-Video, Image-to-Video.
- Editing (Veo 2): Inpainting, Masking.
- Advanced Controls: Frame Interpolation, Video Extension, Reference Images.
- Prompting Guide: Camera angles, visual styles, and best practices.
- Source Code: Deep inspection of SDK internals (
models.py,types.py).
Available Workflows
1. Video Generation (Veo 3)
Create new videos from text or image prompts.
- Text-to-Video: Create videos from detailed text descriptions.
- Image-to-Video: Animate static images.
- Prompt Engineering: Optimization keywords for camera, lighting, and style.
2. Video Editing (Veo 2)
Modify existing videos using masks (Inpainting).
- Remove Objects: Erase dynamic or static objects.
- Insert Objects: Add new elements into a scene.
3. Advanced Controls (Veo 3)
Specialized generation tasks for precise control.
- Frame Interpolation: Generate video bridging two images (first & last frame).
- Video Extension: Extend the duration of an existing video clip.
- Reference-to-Video: Use specific asset images (subjects, products) to guide generation.