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SnapOtter
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- Create 53 per-tool VitePress documentation pages with accurate parameters from Zod schemas, example requests, and response formats - Add root llms.txt for LLM-friendly repo browsing - Fix OpenAPI spec: add auth and 422 error schemas to edit-metadata/inspect and strip-metadata/inspect sub-routes - Fix tool count inconsistency (52 -> 53) across landing site, e2e tests, and local docs - Rename color-adjustments.ts to adjust-colors.ts to match tool ID - Update VitePress sidebar with all 8 tool categories and top nav
90 lines
3.5 KiB
Markdown
90 lines
3.5 KiB
Markdown
---
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description: Create memes with templates or custom images, styled text boxes, and font options.
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---
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# Meme Generator
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Create memes using built-in templates or custom images. Add text with classic meme styling (bold, outlined text), multiple layout presets, and font choices.
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## API Endpoint
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`POST /api/v1/tools/meme-generator`
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Accepts either:
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- **Multipart form data** with an image file and a JSON `settings` field (custom image mode)
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- **JSON body** with a `templateId` (template mode, no file upload needed)
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## Parameters
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| Parameter | Type | Required | Default | Description |
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|-----------|------|----------|---------|-------------|
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| templateId | string | No | - | Built-in meme template ID. If provided, no image upload is needed |
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| textLayout | string | No | `"top-bottom"` | Text box layout: `top-bottom`, `top-only`, `bottom-only`, `center`, `side-by-side` |
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| textBoxes | array | No | `[]` | Array of text box objects with `id` and `text` fields |
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| fontFamily | string | No | `"anton"` | Font: `anton`, `arial-black`, `comic-sans`, `montserrat`, `bebas-neue`, `permanent-marker`, `roboto` |
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| fontSize | number | No | auto | Font size in pixels (8 to 200). Auto-calculated if omitted |
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| textColor | string | No | `"#ffffff"` | Text fill color |
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| strokeColor | string | No | `"#000000"` | Text stroke/outline color |
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| textAlign | string | No | `"center"` | Text alignment: `left`, `center`, `right` |
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| allCaps | boolean | No | `true` | Convert text to uppercase |
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### Text Boxes
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Each entry in the `textBoxes` array should have:
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| Field | Type | Description |
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|-------|------|-------------|
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| id | string | Box identifier matching the layout (e.g., `"top"`, `"bottom"`, `"left"`, `"right"`, `"center"`) |
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| text | string | The meme text to display |
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### Text Layout Box IDs
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| Layout | Available Box IDs |
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|--------|-------------------|
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| `top-bottom` | `top`, `bottom` |
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| `top-only` | `top` |
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| `bottom-only` | `bottom` |
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| `center` | `center` |
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| `side-by-side` | `left`, `right` |
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## Example Request
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Custom image with top and bottom text:
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```bash
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curl -X POST http://localhost:1349/api/v1/tools/meme-generator \
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-H "Authorization: Bearer si_your-api-key" \
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-F "file=@photo.jpg" \
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-F 'settings={"textLayout": "top-bottom", "textBoxes": [{"id": "top", "text": "When the code works"}, {"id": "bottom", "text": "On the first try"}], "fontFamily": "anton", "allCaps": true}'
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```
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Using a built-in template (JSON body, no file upload):
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```bash
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curl -X POST http://localhost:1349/api/v1/tools/meme-generator \
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-H "Authorization: Bearer si_your-api-key" \
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-H "Content-Type: application/json" \
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-d '{"templateId": "drake", "textBoxes": [{"id": "top", "text": "Manual testing"}, {"id": "bottom", "text": "Automated tests"}]}'
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```
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## Example Response
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```json
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{
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"jobId": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
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"downloadUrl": "/api/v1/download/a1b2c3d4-e5f6-7890-abcd-ef1234567890/meme-drake.png",
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"originalSize": 450000,
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"processedSize": 520000
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}
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```
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## Notes
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- Either `templateId` or an uploaded image file is required. Providing both uses the template.
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- Templates define their own text box positions; the `textLayout` parameter is ignored when using templates.
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- Text is rendered as SVG with stroke outlines for the classic meme look.
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- Font size is auto-calculated to fit the text box if not explicitly set.
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- Empty text boxes are skipped (no rendering occurs if all boxes are empty).
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- The output filename includes the template ID when using templates (e.g., `meme-drake.png`).
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- HEIC, RAW, PSD, and SVG inputs are automatically decoded before processing.
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