TensorsLab Image Generation

Overview

This skill enables AI-powered image generation through TensorsLab's API, supporting both text-to-image and image-to-image workflows. The agent enhances user prompts with detailed visual descriptions before calling the API, ensuring high-quality outputs.

Authentication Check

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

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:

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://tensorai.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

seedreamv45 Latest enhanced model General purpose, highest quality

seedreamv4 Standard model Fast generation, good quality

zimage Alternative model Specific artistic styles

Default: seedreamv4

Workflow

For additional scenarios beyond basic generation (avatar generation, watermark removal, object erasure, face replacement), see references/scenarios.md.

1. Text-to-Image Generation

User request: "画一个在月球上吃热狗的宇航员"

Agent processing:

• Extract the core subject and action

• Enhance prompt with details (lighting, composition, style, atmosphere)

• Call API with enriched prompt

• Monitor progress with heartbeat updates

• Download to ./tensorslab_output/

Example enhanced prompt:

An astronaut sitting on the lunar surface, eating a hot dog with mustard, cinematic lighting, Earth visible in the background, highly detailed, photorealistic, 8k quality, dramatic shadows from the low sun angle

2. Image-to-Image Generation

User request: "把 cat.png 的背景换成太空" or "参考 sketch.png 渲染成 3D 模型"

Agent processing:

• Extract image file paths (absolute or relative to current directory)

• Enhance prompt with transformation instructions

• Upload source images with prompt

• Monitor and download results

Parameters for image-to-image:

• sourceImage : Array of image files (for local upload)

• imageUrl : URL of source image

• prompt : Description of desired transformation

3. Image Editing (General Purpose)

General-purpose editing for any local image modifications.

User request examples:

• "把这张图的天空改成日落色"

• "给人物加上墨镜"

• "把头发颜色染成粉色"

Agent processing:

• Extract image file path

• Parse the specific editing instruction (what to change, where)

• Build enhanced prompt with precise editing guidance

• Call API with source image and editing prompt

• Save result to ./tensorslab_output/

Example enhanced prompt:

Change the sky to sunset colors with warm orange and pink gradients, matching the existing lighting conditions and atmospheric perspective, seamless blend at the horizon line

For avatar generation, watermark removal, object erasure, and face replacement scenarios, see references/scenarios.md.

4. Resolution Options

Supported formats:

• Aspect ratios: 9:16 , 16:9 , 3:4 , 4:3 , 1:1 , 2:3 , 3:2

• Resolution levels: 2K , 4K

• Specific dimensions: WxH format (e.g., 2048x2048 , 1920x1080 )

• Constraint: Total pixels must be between 3,686,400 and 16,777,216

Using the Script

依赖：脚本需要 requests 库，首次使用前执行：

pip install requests

Execute the Python script directly:

Text-to-image

python scripts/tensorslab_image.py "a cat on the moon"

With specific resolution

python scripts/tensorslab_image.py "sunset over mountains" --resolution 16:9

Image-to-image

python scripts/tensorslab_image.py "watercolor style" --source cat.png

Specify model

python scripts/tensorslab_image.py "cyberpunk city" --model seedreamv45

Custom output directory

python scripts/tensorslab_image.py "a beautiful landscape" --output-dir ./my_images

Task Status Flow

Status Code Meaning

Queued 1 Task waiting in queue

Processing 2 Currently generating

Completed 3 Done, images ready

Failed 4 Error occurred

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://tensorai.tensorslab.com"/ 充值"

9999 General error Show the specific error message

Output

All images 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}.{ext}

• e.g., abcd_1234567890_0.png

After completion, inform user:

🎉 您的图片处理完毕！已存放于 ./tensorslab_output/{filename}

Resources

• scripts/tensorslab_image.py: Main API client with full CLI support

• references/api_reference.md: Detailed API documentation

• references/scenarios.md: Advanced usage scenarios (avatar generation, watermark removal, object erasure, face replacement)