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letzai-apiletzai API 控制

Agent Skill

用于辅助 API 设计、接口文档、请求响应结构和服务集成说明。它适合让 Agent 梳理 endpoint、生成 OpenAPI 草稿、检查字段命名、整理错误码或辅助前后端联调。使用时需要确认真实业务语义、鉴权方式、分页和错误处理规则;涉及生成接口文档时,应避免凭空补字段,最好从现有代码、schema 或接口样例中提取事实。

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CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:letzai-api(letzai API 控制)
来源仓库:https://github.com/letz-ai/letzai-skill
仓库路径:skills/letzai-api
安装命令:
npx skills add https://github.com/letz-ai/letzai-skill --skill letzai-api
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/letz-ai/letzai-skill --skill letzai-api

简介

通过 LetzAI API 生成具有多个模型选项、自定义训练模型、编辑和升级的 AI 图像和视频。

  • 支持三种图像模型(Nano Banana Pro、Flux2 Max、SeeDream)和三种视频模型(VEO、Kling、Wan),具有可配置的分辨率模式和尺寸
  • 包括基于上下文的图像编辑、皮肤修复和带强度控制的放大(1-3x)
  • 通过提示中的 @modelname 语法可访问针对人物、物体和样式的自定义训练模型
  • 使用轮询模式异步生成(图像/编辑间隔 3 秒,视频间隔 2-3 秒),直到状态达到“就绪”
  • 需要 Bearer 令牌认证和付费 LetzAI 订阅;信用成本因模型和分辨率而异

SKILL.md

LetzAI API Integration Skill

Overview

This skill enables Claude to help users integrate with the LetzAI API for AI-powered image and video generation, editing, and upscaling. Users can also leverage custom-trained AI models (persons, objects, styles) via the @modelname syntax.

Authentication

Setting Up Authentication

const headers = {
  'Content-Type': 'application/json',
  'Authorization': 'Bearer YOUR_API_KEY'
};
headers = {
    'Content-Type': 'application/json',
    'Authorization': 'Bearer YOUR_API_KEY'
}

Core Workflows

1. Image Generation

Endpoint: POST /images

Required Parameters:

  • prompt (string): Text description of the desired image. Can include @modelname to use trained models.

Optional Parameters:

  • baseModel: AI model to use

- "gemini-3-pro-image-preview" - Nano Banana Pro (recommended) - "flux2-max" - Flux2 Max - "seedream-4-5-251128" - SeeDream 4.5

  • mode: Resolution mode (varies by model)

- Nano Banana Pro: "default", "2k", "4k" - Flux2 Max: "1k", "hd" - SeeDream: "2k", "4k"

  • width / height: Image dimensions (520-2160px)

Workflow:

  1. POST to /images with parameters
  2. Receive id in response
  3. Poll GET /images/{id} every 3 seconds
  4. When status === "ready", access imageVersions.original

For code examples, see examples/image_generation.js

2. Video Generation

Endpoint: POST /videos

Required Parameters:

  • prompt (string): Text description of the desired video
  • Source image (one of):

- imageUrl: URL of source image - originalImageCompletionId: ID from previous image generation

Optional Parameters:

  • settings.mode: Video model

- "default" - Default model - "veo31" - VEO 3.1 - "kling26" - Kling 2.6 - "wan25" - Wan 2.5

  • settings.duration: Video length in seconds (2-12 depending on model)

Workflow:

  1. Ensure you have a source image (generate one first if needed)
  2. POST to /videos with parameters
  3. Receive id in response
  4. Poll GET /videos/{id} every 2-3 seconds
  5. When status === "ready", access videoPaths

For code examples, see examples/video_generation.py

3. Image Editing (Context Editing)

Endpoint: POST /image-edits

Required Parameters:

  • mode: Edit mode

- "context" - AI editing (primary mode) - "skin" - Skin fix

  • prompt: Edit instruction (e.g., "change background to beach")
  • Source image (one of):

- imageUrl: URL of source image - inputImageUrls[]: Array of source image URLs (max 9) - originalImageCompletionId: ID of previously generated LetzAI image

Optional Parameters:

  • settings.model: "gemini-3-pro-image-preview", "flux2-max", "seedream-4-5-251128"
  • settings.resolution: "2k" (HD) or "4k" (Ultra HD)
  • settings.aspect_ratio: "1:1", "16:9", "9:16", "4:3", "3:4", "21:9", "9:21"
  • baseModel: Alternative to settings.model
  • webhookUrl: Optional callback URL
  • organizationId: Optional org ID for billing

Workflow:

  1. POST to /image-edits with parameters
  2. Receive id in response
  3. Poll GET /image-edits/{id} every 3 seconds
  4. When status === "ready", access generatedImageCompletion.imageVersions.original

Note: Inpainting (mode: "in") and Outpainting (mode: "out") are deprecated - use Context Editing instead.

4. Image Upscaling

Endpoint: POST /upscales

Required Parameters:

  • Source image (one of):

- imageUrl: URL of source image - imageCompletionId: ID from previous image generation

Optional Parameters:

  • strength: Upscale factor (1-3)

Workflow:

  1. POST to /upscales with parameters
  2. Receive id in response
  3. Poll GET /upscales/{id} every 3 seconds
  4. When status === "ready", access upscaled image

5. Custom AI Models (Trained Models)

LetzAI users can train custom AI models on persons, objects, or styles via the web interface. These trained models can be used in prompts via the @modelname syntax.

List Models Endpoint: GET /models

Query Parameters:

  • page: int (default: 1)
  • limit: int (default: 10)
  • sortBy: "createdAt" | "usages"
  • sortOrder: "ASC" | "DESC"
  • class: "person" | "object" | "style"

Get Model Details: GET /models/{id}

Model Classes:

  • person: Trained on photos of a specific person
  • object: Trained on product/object images
  • style: Trained on artistic style examples

Using Models in Prompts: Tag models with @modelname syntax:

  • @john_doe on the beach at sunset - Use a person model
  • A product photo featuring @my_product - Use an object model
  • Portrait in @vintage_style aesthetic - Use a style model

Note: Model training is done via the LetzAI web interface (letz.ai), not via API.

Workflow Decision Tree

User wants to create an image:

  1. Determine appropriate model based on quality/cost needs
  2. Use POST /images with appropriate baseModel
  3. If using a trained model, include @modelname in the prompt
  4. Poll GET /images/{id} every 3s until ready
  5. Return imageVersions.original URL

User wants to use a custom trained model:

  1. Use GET /models to list available trained models (filter by class if needed)
  2. Include @modelname in the prompt when generating images
  3. Generate image normally with POST /images

User wants to edit an existing image:

  1. Obtain source image URL, inputImageUrls array, or originalImageCompletionId
  2. Use POST /image-edits with mode="context"
  3. Include settings for resolution, aspect_ratio, and model as needed
  4. Poll GET /image-edits/{id} every 3s until ready
  5. Return generatedImageCompletion.imageVersions.original

User wants to create a video:

  1. Ensure they have a source image (URL or imageCompletionId)
  2. If no source image, generate one first using /images
  3. Use POST /videos with desired settings
  4. Poll GET /videos/{id} every 2-3s until ready
  5. Return video URL from videoPaths

User wants to upscale an image:

  1. Obtain source image URL or imageCompletionId
  2. Use POST /upscales with desired strength
  3. Poll GET /upscales/{id} every 3s until ready
  4. Return upscaled image URL

Status Polling Pattern

LetzAI uses asynchronous generation. After any POST request, you must poll the corresponding GET endpoint until the job completes.

Status Values

StatusMeaning
newJob created, queued for processing
in progress / generatingCurrently processing
readyComplete - fetch URLs from response
failedError occurred - check error message

Polling Intervals

  • Images: Every 3 seconds
  • Videos: Every 2-3 seconds
  • Image Edits: Every 3 seconds
  • Upscales: Every 3 seconds

For detailed polling implementation, see examples/polling_pattern.md

Pricing Reference

FeatureModelCredits
Image GenNano Banana Pro80/160/240 (1k/HD/4K)
Image GenFlux2 Max60/120 (1k/HD)
Image GenSeeDream80/160 (HD/4K)
EditingSame as aboveSame pricing
VideoDefault60 cr/sec (2-6 sec)
VideoVEO 3.11500-6000 cr (8 sec)
VideoKling 2.6750-1500 cr (5-10 sec)
UpscaleAll40 cr

Error Handling

Common HTTP Status Codes

StatusMeaningSolution
401Invalid or missing API keyCheck Authorization header format
402Insufficient creditsTop up at letz.ai/subscription
400Invalid parametersVerify baseModel, mode, dimensions
404Resource not foundCheck the ID is correct
429Rate limitedImplement exponential backoff
500Server errorRetry after delay

Error Response Format

{
  "error": "Error description",
  "code": "ERROR_CODE"
}

Limitations

  • Async Generation: All generation is asynchronous - must poll for results
  • Video Source: Video generation requires a source image
  • Reference Images: Maximum 9 reference images for image editing
  • Model Training: Cannot train custom AI models via API - use letz.ai web interface
  • API Key Required: Paid subscription required for API access

Quick Reference: API Endpoints

EndpointMethodPurpose
/imagesGETList user's images
/imagesPOSTCreate image (prompt, baseModel, mode, width, height)
/images/{id}GETGet image status & URLs (poll every 3s)
/images/{id}/interruptionPUTStop image generation
/images/{id}/privacyPUTChange image privacy
/videosGETList user's videos
/videosPOSTCreate video (prompt, imageUrl, settings)
/videos/{id}GETGet video status & URLs (poll every 2-3s)
/videos/{id}/interruptionPUTStop video generation
/videos/{id}/privacyPUTChange video privacy
/image-editsGETList user's edits
/image-editsPOSTEdit image (mode, prompt, imageUrl/inputImageUrls, settings)
/image-edits/{id}GETGet edit status & URLs (poll every 3s)
/upscalesPOSTUpscale image (imageUrl/imageUrls, strength, mode, size)
/upscales/{id}GETGet upscale status & URLs (poll every 3s)
/modelsGETList trained AI models (filter by class: person/object/style)
/models/{id}GETGet specific model details

Key Response Fields

  • Images/Upscales: imageVersions.original, imageVersions["1920x1920"], imageVersions["640x640"]
  • Edits: generatedImageCompletion.imageVersions.original
  • Videos: videoPaths object, videoVersions array
  • Status values: new, in progress/generating, ready, failed

Additional Resources

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安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

34.25%
按下载量换算2,427

Claude

29.38%
按下载量换算2,082

Cursor

18.18%
按下载量换算1,288

Gemini CLI

9.24%
按下载量换算655

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