Veo-3.1 Best Practices (Temporarily Unavailable)

Veo-3.1 legacy route incident noticeThe veo-3.1 series legacy route began experiencing failures on May 14, 2026 and is temporarily unavailable. This page is kept as prompt and model-selection guidance for after recovery; pause new production integrations for now.

Prompt Writing Techniques

Basic Principles

Be Specific

Describe scenes, actions, lighting and other details in detail

Clear Structure

Organize in the order of “subject → action → environment → style”

Avoid Ambiguity

Use clear vocabulary, avoid vague or ambiguous words

Control Length

Keep between 50-200 characters, not too short or verbose

Excellent Prompt Examples

Natural Scenes
Character Scenes
Abstract Concepts

Recommended:

An orange kitten chasing butterflies on green grass, sunlight filtering through leaves creating dappled shadows, gentle breeze moving the grass blades, blurred forest background, cinematic depth of field effect

Avoid:

Cat playing

Key Points:

Described subject (orange kitten)
Specific action (chasing butterflies)
Environmental details (grass, sunlight, leaves)
Visual effects (depth of field, lighting)

Recommended:

A young woman walking in the rain, wearing a red raincoat, holding a transparent umbrella, raindrops bouncing on the umbrella surface, neon lights reflecting on the wet street, night urban background, cinematic slow motion

Avoid:

Woman walking

Key Points:

Character features (young woman)
Clothing and props (red raincoat, transparent umbrella)
Environmental atmosphere (rainy night, neon lights)
Artistic style (cinematic feel, slow motion)

Recommended:

Golden energy ripples spreading outward from the center, particles rotating and rising with the ripples, deep blue gradient background, fluid animation style, soft glow effects

Avoid:

Energy fluctuation

Key Points:

Color description (golden, deep blue)
Movement pattern (spreading outward, rotating and rising)
Artistic style (fluid animation)
Visual effects (glow)

Image-to-Video Best Practices

Image Selection Requirements

Image Quality Requirements:

Resolution: Recommended 1024x1024 or higher
Format: JPEG, PNG, WebP
Size: Not exceeding 10MB per image
Clarity: Avoid blurry or low-quality images

Single Image Generation

Use a single image as the starting frame to generate video:

response = client.chat.completions.create(
    model="veo-3.1-fl",
    messages=[{
        "role": "user",
        "content": [
            {
                "type": "text",
                "text": "Bring this scene to life, gentle breeze moving leaves, clouds slowly drifting"
            },
            {
                "type": "image_url",
                "image_url": {
                    "url": "data:image/jpeg;base64,/9j/4AAQSkZJRg..."
                }
            }
        ]
    }],
    stream=True
)

Single Image Prompt Tips:

Describe desired actions and changes
Specify magnitude and speed of movements
Indicate which elements should remain static

Two-Image Transition

Use two images to generate smooth transition video:

response = client.chat.completions.create(
    model="veo-3.1-fl",
    messages=[{
        "role": "user",
        "content": [
            {
                "type": "text",
                "text": "Create a smooth transition from the first image to the second, maintaining natural and fluid motion"
            },
            {
                "type": "image_url",
                "image_url": {"url": "data:image/jpeg;base64,BASE64_STRING_1"}
            },
            {
                "type": "image_url",
                "image_url": {"url": "data:image/jpeg;base64,BASE64_STRING_2"}
            }
        ]
    }],
    stream=True
)

Two-Image Transition Tips:

Choose two images with similar characteristics
Specify transition method in prompt (fade, slide, morph, etc.)
Keep lighting and color tone consistent between images

Model Selection Strategy

Choose Based on Scenario

Text Generation Scenarios

Scenarios without image referenceRecommended models:

veo-3.1: Standard quality, suitable for most scenarios
veo-3.1-fast: Quick testing, reduce costs

Example scenarios:

Fully creative content
Abstract concept visualization
No specific visual reference needed

Image Reference Scenarios

Scenarios requiring image-based generationRecommended models:

veo-3.1-fl: Standard image-to-video (supports 1-2 image inputs)
veo-3.1-fast-fl: Fast image-to-video (supports 1-2 image inputs)

Example scenarios:

Bring static images to life
Smooth transitions between two images
Generate animations based on reference images

Important: Only models with fl suffix support image input functionality

Landscape Professional Production

Professional landscape format requirementsRecommended models:

veo-3.1-landscape: Landscape text-to-video
veo-3.1-landscape-fast: Fast landscape
veo-3.1-landscape-fl: Landscape image-to-video
veo-3.1-landscape-fast-fl: Fast landscape image-to-video

Example scenarios:

Film production preview
Commercial advertisements
Widescreen content

Cost Optimization Strategy

Testing Phase
Production Phase
Batch Processing

Goal: Quickly validate ideas, reduce costsStrategy:

model = "veo-3.1-fast"  # Use fast series
n = 1  # Single generation

Applicable:

Prompt testing
Concept validation
Rapid iteration

Goal: Obtain high-quality resultsStrategy:

model = "veo-3.1"  # Use standard model
n = 2-3  # Generate multiple alternatives

Applicable:

Final delivery
Client presentations
Official release

Goal: Balance quality and costStrategy:

# 70% use fast model
fast_tasks = tasks[:int(len(tasks) * 0.7)]
# 30% use standard model
standard_tasks = tasks[int(len(tasks) * 0.7):]

Applicable:

Large-scale content production
A/B testing
Dataset construction

Common Scenario Optimization

Action Description

Clear Verbs

Use specific verbs: “run”, “jump”, “rotate”Avoid: “move”, “change” and other vague words

Speed Control

Specify speed: “fast”, “slow”, “constant speed”Example: “Bird rapidly flapping wings”

Direction Indication

Clear direction: “leftward”, “upward”, “clockwise”Example: “Camera panning from left to right”

Magnitude Description

Specify magnitude: “slight”, “intense”, “large amplitude”Example: “Leaves swaying gently”

Lighting Effects

Excellent example:
"At dusk, golden sunlight slanting from the right, casting long shadows on the ground, light penetrating through mist creating Tyndall effect"

Key points:
✓ Time (dusk)
✓ Light source direction (slanting from the right)
✓ Lighting effects (long shadows, Tyndall effect)
✓ Environmental factors (mist)

Camera Movement

Fixed Position
Push/Pull
Orbit
Follow Shot

Camera fixed, subject in center of frame, background slightly out of focus

Camera slowly pushing forward, gradually approaching subject, maintaining smooth movement

Camera rotating clockwise around subject, maintaining fixed distance, showing 360-degree view

Camera following subject movement, keeping subject centered in frame, flowing background

Batch Generation Strategy

Using n Parameter

Generate multiple variants for selection:

response = client.chat.completions.create(
    model="veo-3.1-fast",
    messages=[{
        "role": "user",
        "content": [{"type": "text", "text": "Sunset beach scene"}]
    }],
    n=4,  # Generate 4 different results simultaneously
    stream=True
)

n parameter recommendations:

Testing phase: n=1-2
Important projects: n=2-4
Cost-sensitive: n=1

Concurrent Requests

import asyncio
from openai import AsyncOpenAI

client = AsyncOpenAI(
    api_key="sk-YOUR_API_KEY",
    base_url="https://api.laozhang.ai/v1"
)

async def generate_video(prompt, model="veo-3.1-fast"):
    response = await client.chat.completions.create(
        model=model,
        messages=[{
            "role": "user",
            "content": [{"type": "text", "text": prompt}]
        }],
        stream=True
    )

    async for chunk in response:
        if chunk.choices[0].delta.content:
            print(f"{prompt[:20]}: {chunk.choices[0].delta.content}")

# Generate multiple videos concurrently
prompts = [
    "Sunset beach",
    "City night scene",
    "Forest morning light",
    "Rainy street"
]

await asyncio.gather(*[generate_video(p) for p in prompts])

Quality Improvement Tips

Increase Detail Levels

Basic Description

First describe core subject and actionExample: “A cat walking”

Add Environment

Include scene and background informationExample: “A cat walking on grass, forest background”

Enrich Details

Add lighting, color, textureExample: “An orange cat elegantly walking on green grass, sunlight filtering through leaves creating dappled shadows, blurred forest background”

Artistic Style

Specify visual style and effectsExample: “An orange cat elegantly walking on green grass, sunlight filtering through leaves creating dappled shadows, blurred forest background, cinematic color grading, shallow depth of field effect”

Style Reference

Common style keywords:

Visual effects:
- Cinematic, documentary style, MV quality
- Slow motion, time-lapse, super slow-mo
- HD, 4K quality, film grain

Color tone:
- Warm tones, cool tones, vintage color
- High contrast, low saturation, Morandi palette
- Cyberpunk, vaporwave, oil painting style

Lighting:
- Rembrandt lighting, side light, backlight
- Soft light, hard light, neon lighting
- Golden hour, blue hour, magic hour

Common Mistakes to Avoid

Common errors:❌ Prompt too brief

"cat"

❌ Contains contradictory information

"a cat flying underwater"

❌ Overly complex

"An orange Persian cat wearing elaborate Victorian clothing chasing a talking mechanical butterfly on 19th century London streets while aurora and rainbow appear in the sky..."

❌ Using vague vocabulary

"nice scene"

Performance Optimization

Streaming Processing Best Practices

import sys

response = client.chat.completions.create(
    model="veo-3.1",
    messages=[...],
    stream=True
)

# Real-time output, no buffering
for chunk in response:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end='', flush=True)
        sys.stdout.flush()

Timeout Handling

from openai import OpenAI
import httpx

client = OpenAI(
    api_key="sk-YOUR_API_KEY",
    base_url="https://api.laozhang.ai/v1",
    http_client=httpx.Client(
        timeout=httpx.Timeout(
            connect=10.0,  # Connection timeout
            read=300.0,    # Read timeout (5 minutes)
            write=10.0,    # Write timeout
            pool=10.0      # Pool timeout
        )
    )
)

Getting Started

Core API

Text APIs

Video Generation APIs

Image Generation APIs

AI Understanding

Documentation Index

​Prompt Writing Techniques

​Basic Principles

Be Specific

Clear Structure

Avoid Ambiguity

Control Length

​Excellent Prompt Examples

​Image-to-Video Best Practices

​Image Selection Requirements

​Single Image Generation

​Two-Image Transition

​Model Selection Strategy

​Choose Based on Scenario

​Cost Optimization Strategy

​Common Scenario Optimization

​Action Description

Clear Verbs

Speed Control

Direction Indication

Magnitude Description

​Lighting Effects

​Camera Movement

​Batch Generation Strategy

​Using n Parameter

​Concurrent Requests

​Quality Improvement Tips

​Increase Detail Levels

​Style Reference

​Common Mistakes to Avoid

​Performance Optimization

​Streaming Processing Best Practices

​Timeout Handling

​Next Steps

Code Examples

Troubleshooting

Prompt Writing Techniques

Basic Principles

Excellent Prompt Examples

Image-to-Video Best Practices

Image Selection Requirements

Single Image Generation

Two-Image Transition

Model Selection Strategy

Choose Based on Scenario

Cost Optimization Strategy

Common Scenario Optimization

Action Description

Lighting Effects

Camera Movement

Batch Generation Strategy

Using n Parameter

Concurrent Requests

Quality Improvement Tips

Increase Detail Levels

Style Reference

Common Mistakes to Avoid

Performance Optimization

Streaming Processing Best Practices

Timeout Handling

Next Steps