comic

Official JavaScript/TypeScript SDK for the LlamaGen Comic API.

Homepage: http://llamagen.ai/comic-api

Why comic

• Clean SDK for creators, agents, and product teams
• Typed request/response models for TypeScript
• Built-in polling, retries, batch concurrency, and timeout controls
• Works with SDK, HTTP, and cURL workflows

Install

npm install comic

Get YOUR_API_KEY

1. Open LlamaGen Comic API Dashboard
2. Sign in and create an API key
3. Use the key in SDK or HTTP Authorization header

Authorization: Bearer YOUR_API_KEY

Quick Start (SDK)

import { LlamaGenClient } from 'comic';

const llamagen = new LlamaGenClient({
  apiKey: 'YOUR_API_KEY'
});

const created = await llamagen.comic.create({
  prompt: 'american comic illustration, bold, thick outlines,vibrant, high-contrast colors, A sci-fi story about two friends on Mars'
});

const result = await llamagen.comic.waitForCompletion(created.id);
console.log(result.status, result.output);

API Surface

Client

• new LlamaGenClient(options)
• options.apiKey: string (required)
• options.baseURL?: string (default https://api.llamagen.ai/v1)
• options.timeoutMs?: number (default 30000)
• options.maxRetries?: number (default 2)
• options.retryDelayMs?: number (default 500)
• options.fetch?: typeof fetch

Namespace

All capabilities start from llamagen.comic:

• llamagen.comic.create(params)
• llamagen.comic.get(id)
• llamagen.comic.waitForCompletion(id, options?)
• llamagen.comic.createAndWait(params, options?)
• llamagen.comic.createBatch(paramsList, options?)
• llamagen.comic.waitForMany(ids, options?)

Backward compatibility aliases:

• llamagen.comic.createComic(...)
• llamagen.comic.getComic(...)

TypeScript Types

Request/response types are maintained in:

• src/api-types.ts
• src/types.ts

Common types:

• CreateComicParams
• ComicSize
• ComicGenerationResponse
• ComicDetailResponse
• WaitForCompletionOptions
• BatchCreateOptions
• WaitForManyOptions

Runtime constant:

• SUPPORTED_COMIC_SIZES

SDK Examples

Create + Poll

const created = await llamagen.comic.create({
  prompt: 'american comic illustration, bold, thick outlines,vibrant, high-contrast colors, A superhero cat saving a city from giant mice',
  preset: 'neutral',
  size: '1024x1024'
});

const done = await llamagen.comic.waitForCompletion(created.id, {
  intervalMs: 5000,
  timeoutMs: 180000
});

Batch Workflow for Agents

const jobs = await llamagen.comic.createBatch(
  [
    { prompt: 'american comic illustration, bold, thick outlines,vibrant, high-contrast colors, Scene 1: hero enters the city' },
    { prompt: 'american comic illustration, bold, thick outlines,vibrant, high-contrast colors, Scene 2: conflict escalates' },
    { prompt: 'american comic illustration, bold, thick outlines,vibrant, high-contrast colors, Scene 3: final showdown' }
  ],
  { concurrency: 2, stopOnError: false }
);

const ids = jobs
  .filter((job) => job.result?.id)
  .map((job) => job.result.id);

const results = await llamagen.comic.waitForMany(ids, {
  concurrency: 3,
  intervalMs: 4000,
  timeoutMs: 240000
});

HTTP API (Direct)

Base URL: https://api.llamagen.ai/v1

1) Create Generation

Endpoint: POST /comics/generations

Request body:

{
  "prompt": "american comic illustration, bold, thick outlines,vibrant, high-contrast colors, A superhero cat saving a city from giant mice",
  "preset": "neutral",
  "size": "1024x1024",
  "model": "optional-model-id"
}

Supported size values:

• 1024x1024 (1:1)
• 512x768 (2:3)
• 512x1024 (1:2)
• 576x1024 (9:16)
• 768x1024 (3:4)
• 1024x768 (4:3)
• 768x512 (3:2)
• 1024x576 (16:9)
• 1024x512 (2:1)

cURL:

curl -X POST "https://api.llamagen.ai/v1/comics/generations" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "american comic illustration, bold, thick outlines,vibrant, high-contrast colors, A superhero cat saving a city from giant mice",
    "preset": "neutral",
    "size": "1024x1024"
  }'

Example response:

{
  "id": "gen_123456789",
  "status": "PENDING",
  "createdAt": "2026-03-05T00:00:00.000Z"
}

2) Get Generation

Endpoint: GET /comics/generations/:id

cURL:

curl -X GET "https://api.llamagen.ai/v1/comics/generations/YOUR_GENERATION_ID" \
  -H "Authorization: Bearer YOUR_API_KEY"

Example response:

{
  "id": "gen_123456789",
  "status": "SUCCEEDED",
  "output": "https://cdn.llamagen.ai/comics/gen_123456789.webp",
  "createdAt": "2026-03-05T00:00:00.000Z",
  "comics": []
}

Error response example:

{
  "error": "Unauthorized",
  "message": "Invalid API token"
}

MCP Integration

Endpoint:

https://llamagen.ai/api/mcp

Auth header:

Authorization: Bearer YOUR_API_KEY

Available MCP tools:

• create_comic_generation: create a generation job
• get_comic_generation_status: check status/result by id
• get_api_usage: fetch current usage/quota

Generic MCP client config example:

{
  "mcpServers": {
    "llamagen": {
      "url": "https://llamagen.ai/api/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_KEY"
      }
    }
  }
}

Cursor quick setup:

1. Open Cursor settings and go to MCP.
2. Add a server with Streamable HTTP transport.
3. Set URL to https://llamagen.ai/api/mcp.
4. Add header Authorization: Bearer YOUR_API_KEY.
5. Verify tools list includes the 3 tools above.

OAuth metadata for compliant MCP clients:

https://llamagen.ai/.well-known/oauth-protected-resource

JavaScript Fetch Example

const response = await fetch('https://api.llamagen.ai/v1/comics/generations', {
  method: 'POST',
  headers: {
    Authorization: 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    prompt: 'american comic illustration, bold, thick outlines,vibrant, high-contrast colors, A superhero cat saving a city from giant mice',
    preset: 'neutral',
    size: '1024x1024'
  })
});

const data = await response.json();
console.log(data);

Errors

• LlamaGenAPIError: non-2xx API response with status and data
• LlamaGenTimeoutError: request timeout or polling timeout

Local Dev

npm install
npm run lint
npm test
npm run build

Smoke test with latest published SDK:

npm run smoke:latest

Outputs are written to .local-smoke/results/<timestamp>/ and are not tracked by git.

90-Day Growth Plan

• Month 1: tighten docs, examples, and onboarding friction (time-to-first-image < 5 minutes)
• Month 2: deepen framework integrations and production patterns for AI agents
• Month 3: scale community contributions, issue velocity, and benchmark showcases

Project references:

• CONTRIBUTING.md
• SECURITY.md
• CLAUDE.md
• docs/PROMPT_BASICS.md
• docs/ROADMAP.md