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)](references/generation.md): Text-to-Video, Image-to-Video.
• [Editing (Veo 2)](references/editing.md): Inpainting, Masking.
• [Advanced Controls](references/advanced.md): Frame Interpolation, Video Extension, Reference Images.
• [Prompting Guide](references/prompting.md): Camera angles, visual styles, and best practices.
• [Source Code](references/source_code.md): 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.