Video Generation

Generate videos using TensorsLab's AI video generation models. Supports text-to-video and image-to-video generation with automatic prompt enhancement, progress tracking, and local file saving. Use for generating videos from text descriptions, animating static images, creating cinematic content, and various aspect ratios. Requires TENSORSLAB_API_KEY environment variable. Video generation takes several minutes.

TensorsLab Video Generation

Overview

This skill enables AI-powered video generation through TensorsLab's API, supporting both text-to-video and image-to-video workflows. Video generation is a time-intensive process - tasks typically take several minutes to complete.

Authentication Check

Before any video generation, verify the API key is configured:

bash

# 仅检查变量是否存在，不输出完整值
[ -n "$TENSORSLAB_API_KEY" ] && echo "✅ API key is set" || echo "❌ TENSORSLAB_API_KEY is not set"

If not set, display this friendly message:

text

您好！要生成高质量的内容，您需要先进行简单的配置：
1. 访问 https://tensorslab.tensorslab.com/ 登录并订阅。
2. 在控制台中获取您的专属 API Key。
3. 将其保存为环境变量：
   - Windows (PowerShell): $env:TENSORSLAB_API_KEY="您的Key"
   - Mac/Linux: export TENSORSLAB_API_KEY="您的Key"

Models

Model	Description	Best For	Max Duration
seedancev2	Latest, highest quality	General purpose, cinematic content	15s
seedancev15pro	Pro quality	High-end productions	10s
seedancev1profast	Fast generation	Quick previews	10s
seedancev1	Standard lite	Basic videos	10s

Default: seedancev1profast

Workflow

1. Text-to-Video Generation

User request: "做一段 10 秒钟横屏的宇宙飞船穿梭星际的视频"

Agent processing:

1. Extract parameters: duration=10, ratio="16:9"
2. Enhance prompt with cinematic details, camera movements, scene descriptions
3. Call API with enriched prompt
4. Monitor progress with heartbeat updates (every 60 seconds)
5. Download to ./tensorslab_output/

Example enhanced prompt:

text

Cinematic wide shot of a spaceship rapidly flying through space, passing glowing
nebulae and distant stars, lens flares, dramatic camera movement, epic scale,
movie-quality visual effects, smooth 24fps motion

2. Image-to-Video Generation

User request: "让这张人物合影 family.jpg 动起来" or "让风景照动起来"

Agent processing:

1. Extract image file paths (1-2 images supported)
2. Enhance prompt with motion instructions
3. Monitor progress with heartbeat updates
4. Download results

Parameters for image-to-video:

• sourceImage: Array of image files (1-2 images max)
• imageUrl: Comma-separated URLs of source images
• prompt: Description of desired motion/animation

3. Resolution and Aspect Ratio

Aspect ratios:

• 9:16 - Vertical (TikTok, Reels, Shorts) - default
• 16:9 - Horizontal (YouTube, standard video)
• Other ratios available depending on model

Resolutions:

• 480p - SD quality, faster generation
• 720p - HD quality - default
• 1080p - Full HD
• 1440p - 2K quality (seedancev2 only)

4. Duration Options

• seedancev2: 5-15 seconds
• Other models: 5-10 seconds

Longer videos take proportionally more time to generate.

5. Special Features (seedancev2 only)

Feature	Parameter	Description
Audio Generation	generate_audio=1	Generate soundtrack with video
Last Frame	return_last_frame=1	Also return final frame as image

Progress Tracking

Video generation takes several minutes. Keep users informed:

text

⏳ Waiting for video generation to complete...
   (This may take several minutes - please be patient)
🔄 Status: Processing (elapsed: 45s)
🚀 正在渲染电影级大片，已耗时 60 秒，请稍安勿躁...
🚀 正在渲染电影级大片，已耗时 120 秒，请稍安勿躁...
✅ Task completed!

Heartbeat interval: Print encouraging message every 60 seconds.

Using the Script

依赖：脚本需要 requests 库，首次使用前执行：

bash

pip install requests

Execute the Python script directly:

bash

# Text-to-video (default 5s, vertical 9:16)
python scripts/tensorslab_video.py "a spaceship flying through space"

# 10 second horizontal video
python scripts/tensorslab_video.py "sunset over ocean waves" --duration 10 --ratio 16:9

# Image-to-video
python scripts/tensorslab_video.py "make this photo come alive" --source portrait.jpg

# Fast preview
python scripts/tensorslab_video.py "abstract flowing colors" --model seedancev1profast

# High quality with audio
python scripts/tensorslab_video.py "epic mountain timelapse" --resolution 1440p --duration 10 --audio

# Custom output directory
python scripts/tensorslab_video.py "a sunset timelapse" --output-dir ./my_videos

Task Status Flow

Status	Code	Meaning
Pending	1	Task waiting in queue
Processing	2	Currently generating
Completed	3	Done, video ready
Failed	4	Error occurred
Uploading	5	Uploading generated video

Error Handling

Translate API errors to user-friendly messages:

Error Code	Meaning	User Message
9000	Insufficient credits	"亲，积分用完啦，请前往 https://tensorslab.tensorslab.com/ 充值"
9999	General error	Show the specific error message

Output

All videos are saved to output directory with naming pattern:

• Default: ./tensorslab_output/ (current working directory)
• Custom: Use --output-dir or -o to specify a different path
• Naming: {task_id}_{index}.mp4 - e.g., abcd_1234567890_0.mp4

After completion, inform user:

text

🎉 您的视频处理完毕！已存放于 ./tensorslab_output/{filename}

Tips for Better Results

Text-to-Video

• Include cinematic terms: "wide shot", "close-up", "pan", "dolly"
• Describe motion: "flying rapidly", "slowly drifting", "zooming in"
• Specify style: "cinematic", "documentary style", "dreamy"

Image-to-Video

• Describe the desired motion: "gentle sway", "subtle movement"
• For landscapes: "clouds moving", "water flowing", "leaves rustling"

Resources

• scripts/tensorslab_video.py: Main API client with full CLI support
• references/api_reference.md: Detailed API documentation