Crun Meme Generator

Crun Meme & Emoji Generator

Use this skill to generate static image memes/stickers and animated GIF reaction memes via Crun AI models.

• Static Memes: Route to Crun image generation models (modality: "image"), set appropriate resolution/aspect ratio, generate pure artwork (bypassing AI text rendering errors), download PNG/JPG, and overlay crisp text via scripts/image_text_overlay.py --text "<caption_text>".
• Animated GIF Memes: Route to fast Crun video generation models (modality: "video"), default to the model's lowest resolution (e.g. 480p / 720p), generate pure visual motion (without asking video AI model to render text directly to avoid text distortion/garbling), download MP4, and add crisp text overlay directly onto the GIF via scripts/video_to_gif.py --text "<caption_text>".
• Interactive Button Confirmation: For both static and GIF memes, always present confirmation details (including Model, Credits, Visual Style, Text Caption, and Resolution) and use interactive option buttons (e.g. ask_question tool) for user confirmation before task creation.

Workflow Overview

Follow this end-to-end execution flow for all meme and emoji generation requests:

User Request (Meme/Emoji/GIF)
   │
   ├── 1. Determine Format (Static Image vs Animated GIF)
   │
   ├── 2. Upload Input Media (If user provides reference photo/image)
   │       └─ python <root>/runtime/crun_cli.py upload <local-file>
   │
   ├── 3. Route Model & Construct Payload
   │       ├─ Static Image: modality="image", define Visual Style, resolution=1K, purely visual prompt
   │       └─ Animated GIF: modality="video", lowest resolution default, purely visual motion prompt
   │
   ├── 4. Estimate Affordability & Present Button Confirmation
   │       ├─ Estimate: python <root>/runtime/crun_cli.py task estimate --model <model> --input-file <input.json>
   │       └─ Ask Question: Interactive option buttons (containing Style, Caption, Resolution, Model & Credits)
   │
   ├── 5. Create Task & Poll Status (crun-task-runner)
   │       ├─ python <root>/runtime/crun_cli.py task create --model <model> --input-file <input.json>
   │       └─ python <root>/runtime/crun_cli.py task wait --task-id <task_id> --timeout-seconds 120
   │
   └── 6. Final Text Overlay & Output Formatting
           ├─ Static Image: python <skill-root>/skills/scenarios/crun-meme-generator/scripts/image_text_overlay.py <image-path> --text "<caption_text>" --output <meme-path>
           └─ Animated GIF: python <skill-root>/skills/scenarios/crun-meme-generator/scripts/video_to_gif.py <video-path> --text "<caption_text>" --output <gif-path>

Detailed Execution Steps

1. Identify Format and Intent

• Static Image Meme:

  • User intent: Static sticker, image meme, funny reaction photo, graphic meme.
  • Output target: PNG / JPG image file.
  • Operation: text-to-image (new meme) or image-edit (modifying or adding caption to an existing photo).

• Animated GIF Meme:

  • User intent: Animated GIF meme, reaction GIF, motion sticker, animated reaction emoji.
  • Output target: GIF file.
  • Operation: text-to-video (new animated GIF) or image-to-video (animating a reference photo into a GIF).

2. Upload Reference Media (If Provided)

When the user provides a local reference photo (e.g. face photo, pet photo, existing image to turn into meme/GIF):

python <skill-root>/runtime/crun_cli.py upload <local-file>

Use the returned file_url in the model payload. Never send raw local paths or Base64 into Crun model inputs.

3. Route Model and Build Payload

Read skills/crun-model-router/SKILL.md to construct routing intent:

{
  "modality": "image|video",
  "operation": "text-to-image|image-edit|text-to-video|image-to-video",
  "quality": "balanced",
  "speed": "fast"
}

A) Static Image Meme Defaults & Text Overlay Strategy

• Preferred models: openai/gpt-image-2, bytedance/seedream-5-pro, google/nano-banana-pro, qwen-image-2.0-pro.
• Visual Style: Explicitly choose or confirm a visual style:
  • Examples: 3D Cartoon Sticker (white die-cut border), Realistic Reaction Photo, Funny Sketch/Doodle, Anime Reaction, Pixel Art Meme.
  • Include style details in the prompt (e.g. "cute 3D cartoon style sticker with white outline...").
• Resolution & Aspect Ratio:
  • Default to square 1:1 aspect ratio or 1K resolution suitable for memes.
• Text Overlay Strategy:
  • Do NOT rely on AI image model prompt text rendering for complex, multi-line, or CJK text, as image models often distort typography or misspell words.
  • Keep the image prompt focused on pure visual character and expression (e.g. "cute 3D cartoon dog looking confused with big eyes, white die-cut sticker outline, solid background").
  • Use scripts/image_text_overlay.py post-processing to overlay crisp, stroke-bordered text onto the generated image.

B) Animated GIF Meme Defaults & Text Overlay Strategy

• Preferred fast video models: bytedance/seedance2-0-fast-t2v / bytedance/seedance2-0-fast-i2v, bytedance/seedance1-0-pro-fast-t2v, vidu/q3-turbo-t2v, kling/v3-turbo.
• Lowest Resolution Default:
  • Inspect model schema with crun_cli.py models describe --model <model>.
  • Always select the lowest resolution supported by that model (e.g. 480p or 720p). Lower resolution generates faster, uses fewer credits, and reduces GIF file size.
• Text Overlay Strategy:
  • Do NOT ask video AI models to render text inside the prompt (video models scramble CJK and English text).
  • Keep video AI prompt purely visual (e.g. "cute 3D cartoon cat looking shocked, funny looping reaction motion, clean background").
  • Pass the text caption to video_to_gif.py via --text "<caption_text>".

C) Universal Multilingual Adaptation Strategy

• Text Caption & Modal Language: Dynamically mirror the user's input language for text captions and confirmation dialogs.
  • If user inputs in English: Caption & confirmation must be in English (e.g. "Monday Mood", "Off to work...").
  • If user inputs in Chinese: Caption & confirmation in Chinese (e.g. "摸鱼中...", "收到！").
  • If user inputs in Other Languages (Japanese, Spanish, French, Korean, etc.): Natively generate the caption in that input language.
• AI Model Prompt Language: Always convert the underlying visual scene description in Crun model payloads into clear English, as AI image/video models deliver optimal rendering quality with English visual descriptions.

4. Estimate Affordability & Button Confirmation Gate

Read skills/crun-account-credits/SKILL.md:

python <skill-root>/runtime/crun_cli.py task estimate --model <model> --input-file <input.json>

Verify affordable: true. Before calling task create, call ask_question tool to present an interactive choice modal with confirmation buttons.

Mandatory Confirmation Content Specification:

1. For Static Image Memes:

   • Model: e.g. bytedance/seedream-5-pro
   • Estimated Credits: e.g. 2.5 Credits
   • Visual Style: e.g. 3D Cartoon Sticker (with white outline)
   • Text Caption: e.g. "Monday Mood" (Clean stroke text overlay applied after image generation)
   • Resolution & Aspect Ratio: e.g. 1K (1:1 Square)

2. For Animated GIF Memes:

   • Model: e.g. bytedance/seedance2-0-fast-t2v
   • Estimated Credits: e.g. 4.0 Credits
   • Visual Style: e.g. 3D Cartoon Reaction Style
   • Text Caption: e.g. "Off to work..." (Stroke text overlay applied during GIF conversion)
   • Resolution: e.g. 480p (Lowest model resolution, fast & cost-efficient)
   • Duration: e.g. 3s (Converted to 12fps looping GIF)

Interactive Confirmation Buttons:

Use ask_question tool to prompt the user with selectable options in their language:

• Option 1: "Confirm & Generate" (or "确认按此参数生成")
• Option 2: "Modify Caption/Style" (or "修改配文或风格")
• Option 3: "Cancel" (or "取消生成")

5. Create Task and Wait for Download

Read skills/crun-task-runner/SKILL.md:

python <skill-root>/runtime/crun_cli.py task create --model <model> --input-file <input.json>
python <skill-root>/runtime/crun_cli.py task wait --task-id <task_id> --timeout-seconds 120

When task completes, crun_cli.py automatically downloads the result media to ~/.crun/output/yyyy-mm-dd/<task_id>/.

6. Text Overlay & Format Output

A) Static Image Text Overlay (image_text_overlay.py)

Invoke image_text_overlay.py to overlay text onto the static image:

python <skill-root>/skills/scenarios/crun-meme-generator/scripts/image_text_overlay.py <image-path> --output <meme-path> --text "<caption_text>" --text-position bottom --style stroke

Parameters for image_text_overlay.py:

• <image-path>: Path to the downloaded image file.
• --output / -o: Output path for captioned meme image (.png / .jpg).
• --text / -t: Text caption to overlay (supports CJK & multi-language stroke text).
• --text-position: Position of caption overlay (bottom, top, or center).
• --style: Text style (stroke white text with black outline, or banner dark background bar).

The script returns JSON output:

{
  "code": 0,
  "status": "success",
  "input_file": "/path/to/image.png",
  "output_file": "/path/to/meme.png",
  "width": 1024,
  "height": 1024,
  "text_overlay": "Monday Mood",
  "text_position": "bottom",
  "style": "stroke"
}

B) Video to Animated GIF Conversion (video_to_gif.py)

Invoke video_to_gif.py to convert MP4 to GIF and overlay text:

python <skill-root>/skills/scenarios/crun-meme-generator/scripts/video_to_gif.py <video-path> --output <gif-path> --fps 12 --width 480 --text "<caption_text>" --text-position bottom

Parameters for video_to_gif.py:

• <video-path>: Path to the downloaded MP4 video file.
• --output / -o: Output path for the converted .gif file.
• --fps: Target frame rate (default: 12).
• --width: Target width scaling in pixels (default: 480).
• --text / -t: Text caption to overlay.
• --text-position: Position of caption overlay (bottom, top, or center).

The script returns JSON output:

{
  "code": 0,
  "status": "success",
  "input_file": "/path/to/video.mp4",
  "output_file": "/path/to/meme.gif",
  "size_bytes": 1425600,
  "fps": 12,
  "width": 480,
  "text_overlay": "Off to work...",
  "text_position": "bottom",
  "conversion_method": "ffmpeg+PIL"
}

Confirmation Message & Button Examples

Example 1: Static Image Meme Confirmation (ask_question)

{
  "questions": [
    {
      "question": "🎨 Static meme generation plan prepared for your request:\n- Model: bytedance/seedream-5-pro\n- Visual Style: 3D Cartoon Sticker (white die-cut outline)\n- Text Caption: \"Monday Mood\" (Clean stroke text overlay)\n- Resolution: 1K (1:1 Square)\n- Estimated Cost: 2.5 Credits",
      "options": [
        "Confirm & Generate",
        "Modify Caption/Style",
        "Cancel"
      ],
      "is_multi_select": false
    }
  ]
}

Example 2: Animated GIF Meme Confirmation (ask_question)

{
  "questions": [
    {
      "question": "🎬 Animated GIF meme generation plan prepared for your request:\n- Model: bytedance/seedance2-0-fast-t2v\n- Visual Style: 3D cartoon humor reaction style\n- Text Caption: \"Off to work...\" (Clean stroke text overlay)\n- Resolution: 480p (Lowest model resolution, fast & cost-efficient)\n- Duration: 3 seconds (12fps looping GIF)\n- Estimated Cost: 4.0 Credits",
      "options": [
        "Confirm & Generate",
        "Modify Caption/Style",
        "Cancel"
      ],
      "is_multi_select": false
    }
  ]
}

Delivery and Preview

Always provide the user with clear execution details and an inline local markdown preview:

✅ Meme generated successfully!
- Task ID: <task_id>
- Visual Style: <style>
- Text Caption: <caption_or_none>
- Resolution: <resolution>
- Credits Used: <credits>
- File Path: <local_gif_or_image_path>

![Meme Preview](/absolute/path/to/meme.gif)