letzai-api▌
letz-ai/letzai-skill · updated Apr 8, 2026
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Generate AI images and videos with multiple model options, custom trained models, editing, and upscaling via LetzAI API.
- ›Supports three image models (Nano Banana Pro, Flux2 Max, SeeDream) and three video models (VEO, Kling, Wan) with configurable resolution modes and dimensions
- ›Includes context-based image editing, skin fixing, and upscaling with strength control (1-3x)
- ›Custom trained models for persons, objects, and styles accessible via @modelname syntax in prompts
- ›Asynchronous
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
- Base URL:
https://api.letz.ai - Authentication: Bearer token in Authorization header
- Get API Key: letz.ai/subscription
- API Documentation: api.letz.ai/doc
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@modelnameto 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"
- Nano Banana Pro:
width/height: Image dimensions (520-2160px)
Workflow:
- POST to
/imageswith parameters - Receive
idin response - Poll
GET /images/{id}every 3 seconds - When
status === "ready", accessimageVersions.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 imageoriginalImageCompletionId: 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:
- Ensure you have a source image (generate one first if needed)
- POST to
/videoswith parameters - Receive
idin response - Poll
GET /videos/{id}every 2-3 seconds - When
status === "ready", accessvideoPaths
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 imageinputImageUrls[]: 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.modelwebhookUrl: Optional callback URLorganizationId: Optional org ID for billing
Workflow:
- POST to
/image-editswith parameters - Receive
idin response - Poll
GET /image-edits/{id}every 3 seconds - When
status === "ready", accessgeneratedImageCompletion.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 imageimageCompletionId: ID from previous image generation
Optional Parameters:
strength: Upscale factor (1-3)
Workflow:
- POST to
/upscaleswith parameters - Receive
idin response - Poll
GET /upscales/{id}every 3 seconds - 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 personobject: Trained on product/object imagesstyle: Trained on artistic style examples
Using Models in Prompts:
Tag models with @modelname syntax:
@john_doe on the beach at sunset- Use a person modelA product photo featuring @my_product- Use an object modelPortrait 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:
- Determine appropriate model based on quality/cost needs
- Use
POST /imageswith appropriatebaseModel - If using a trained model, include
@modelnamein the prompt - Poll
GET /images/{id}every 3s until ready - Return
imageVersions.originalURL
User wants to use a custom trained model:
- Use
GET /modelsto list available trained models (filter by class if needed) - Include
@modelnamein the prompt when generating images - Generate image normally with
POST /images
User wants to edit an existing image:
- Obtain source image URL, inputImageUrls array, or originalImageCompletionId
- Use
POST /image-editswithmode="context" - Include settings for resolution, aspect_ratio, and model as needed
- Poll
GET /image-edits/{id}every 3s until ready - Return
generatedImageCompletion.imageVersions.original
User wants to create a video:
- Ensure they have a source image (URL or imageCompletionId)
- If no source image, generate one first using
/images - Use
POST /videoswith desired settings - Poll
GET /videos/{id}every 2-3s until ready - Return video URL from
videoPaths
User wants to upscale an image:
- Obtain source image URL or imageCompletionId
- Use
POST /upscaleswith desiredstrength - Poll
GET /upscales/{id}every 3s until ready - 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
| Status | Meaning |
|---|---|
new |
Job created, queued for processing |
in progress / generating |
Currently processing |
ready |
Complete - fetch URLs from response |
failed |
Error 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
| Feature | Model | Credits |
|---|---|---|
| Image Gen | Nano Banana Pro | 80/160/240 (1k/HD/4K) |
| Image Gen | Flux2 Max | 60/120 (1k/HD) |
| Image Gen | SeeDream | 80/160 (HD/4K) |
| Editing | Same as above | Same pricing |
| Video | Default | 60 cr/sec (2-6 sec) |
| Video | VEO 3.1 | 1500-6000 cr (8 sec) |
| Video | Kling 2.6 | 750-1500 cr (5-10 sec) |
| Upscale | All | 40 cr |
Error Handling
Common HTTP Status Codes
| Status | Meaning | Solution |
|---|---|---|
| 401 | Invalid or missing API key | Check Authorization header format |
| 402 | Insufficient credits | Top up at letz.ai/subscription |
| 400 | Invalid parameters | Verify baseModel, mode, dimensions |
| 404 | Resource not found | Check the ID is correct |
| 429 | Rate limited | Implement exponential backoff |
| 500 | Server error | Retry 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
| Endpoint | Method | Purpose |
|---|---|---|
/images |
GET | List user's images |
/images |
POST | Create image (prompt, baseModel, mode, width, height) |
/images/{id} |
GET | Get image status & URLs (poll every 3s) |
/images/{id}/interruption |
PUT | Stop image generation |
/images/{id}/privacy |
PUT | Change image privacy |
/videos |
GET | List user's videos |
/videos |
POST | Create video (prompt, imageUrl, settings) |
/videos/{id} |
GET | Get video status & URLs (poll every 2-3s) |
/videos/{id}/interruption |
PUT | Stop video generation |
/videos/{id}/privacy |
PUT | Change video privacy |
/image-edits |
GET | List user's edits |
/image-edits |
POST | Edit image (mode, prompt, imageUrl/inputImageUrls, settings) |
/image-edits/{id} |
GET | Get edit status & URLs (poll every 3s) |
/upscales |
POST | Upscale image (imageUrl/imageUrls, strength, mode, size) |
/upscales/{id} |
GET | Get upscale status & URLs (poll every 3s) |
/models |
GET | List trained AI models (filter by class: person/object/style) |
/models/{id} |
GET | Get specific model details |
Key Response Fields
- Images/Upscales:
imageVersions.original,imageVersions["1920x1920"],imageVersions["640x640"] - Edits:
generatedImageCompletion.imageVersions.original - Videos:
videoPathsobject,videoVersionsarray - Status values:
new,in progress/generating,ready,failed
Additional Resources
- API Documentation: api.letz.ai/doc
- Developer Docs: letz.ai/docs/api
- Detailed API Reference: api_reference.md
- Code Examples: examples/
How to use letzai-api on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add letzai-api
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches letzai-api from GitHub repository letz-ai/letzai-skill and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate letzai-api. Access the skill through slash commands (e.g., /letzai-api) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★64 reviews- ★★★★★Camila Agarwal· Dec 28, 2024
letzai-api fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Amelia Iyer· Dec 16, 2024
We added letzai-api from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Aditi Haddad· Dec 4, 2024
letzai-api has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Rahul Santra· Nov 27, 2024
Registry listing for letzai-api matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Camila Verma· Nov 27, 2024
letzai-api reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Emma Lopez· Nov 23, 2024
letzai-api fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Chinedu Patel· Nov 19, 2024
letzai-api has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Alexander Flores· Nov 7, 2024
Solid pick for teams standardizing on skills: letzai-api is focused, and the summary matches what you get after install.
- ★★★★★Tariq Mehta· Nov 3, 2024
Registry listing for letzai-api matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Alexander Sethi· Oct 26, 2024
letzai-api has been reliable in day-to-day use. Documentation quality is above average for community skills.
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