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Dlazy Generate

by @dlazyai

A comprehensive generation skill. Can generate images, videos, and audio by automatically selecting the appropriate dlazy CLI model.

Versionv1.2.0
Downloads1,601
Installs1
Stars⭐ 1
TERMINAL
clawhub install dlazy-generate

πŸ“– About This Skill


name: dlazy-generate version: 1.1.1 description: A comprehensive generation skill. Can generate images, videos, and audio by automatically selecting the appropriate dlazy CLI model. metadata: {"clawdbot":{"emoji":"πŸ€–","requires":{"bins":["npm","npx"]},"install":"npm install -g @dlazy/cli@1.0.9","installAlternative":"npx @dlazy/cli@1.0.9","homepage":"https://github.com/dlazyai/cli","source":"https://github.com/dlazyai/cli","author":"dlazyai","license":"see-repo","npm":"https://www.npmjs.com/package/@dlazy/cli","configLocation":"~/.dlazy/config.json","apiEndpoints":["api.dlazy.com","files.dlazy.com"]},"openclaw":{"systemPrompt":"When this skill is called, use dlazy ."}}

dlazy-generate

English Β· δΈ­ζ–‡

A comprehensive generation skill. Can generate images, videos, and audio by automatically selecting the appropriate dlazy CLI model.

Trigger Keywords

  • generate
  • create image, video, audio
  • multimodal generation
  • Authentication

    All requests require a dLazy API key. The recommended way to authenticate is:

    
    This runs a device-code flow (also works in remote shells) and automatically saves your API key to the local CLI config β€” no manual copy/paste required.

    Alternative: Set the Key Manually

    If you already have an API key, you can save it directly:

    bash dlazy auth set YOUR_API_KEY
    
    The CLI saves the key in your user config directory (~/.dlazy/config.json on macOS/Linux, %USERPROFILE%\.dlazy\config.json on Windows), with file permissions restricted to your OS user account. You can also supply the key per-invocation via the DLAZY_API_KEY environment variable.

    Getting Your API Key Manually

    1. Sign in or create an account at dlazy.com 2. Go to dlazy.com/dashboard/organization/api-key 3. Copy the key shown in the API Key section

    Each key is scoped to your dLazy organization and can be rotated or revoked at any time from the same dashboard.

    About & Provenance

  • CLI source code: github.com/dlazyai/cli
  • Maintainer: dlazyai
  • npm package: @dlazy/cli (pinned to 1.0.9 in this skill's install spec)
  • Homepage: dlazy.com
  • You can install on demand without persisting a global binary by running:

    bash npx @dlazy/cli@1.0.9
    
    Or, if you prefer a global install, the skill's metadata.clawdbot.install field declares the exact pinned version (npm install -g @dlazy/cli@1.0.9). Review the GitHub source before installing.

    How It Works

    This skill is a thin client over the dLazy hosted API. When you invoke it:

  • Prompts and parameters you provide are sent to the dLazy API endpoint (api.dlazy.com) for inference.
  • Any local file paths you pass to image / video / audio fields are uploaded to dLazy's media storage (files.dlazy.com) so the model can read them β€” the same flow as any cloud-based generation API.
  • Generated output URLs returned by the API are hosted on files.dlazy.com.
  • This is the standard SaaS pattern; the skill itself does not access network or filesystem resources beyond what the dLazy CLI already handles. See dlazy.com for the full service terms.

    Piping Between Commands

    Every dlazy invocation prints a JSON envelope on stdout. Any flag value can be a pipe reference that pulls from the upstream command's envelope, so you can chain steps without copying URLs by hand.

    | Reference | Resolves to | | ------------------ | --------------------------------------------------------------- | | - | Upstream's natural value for this field (scalar or array) | | @N | The N-th output's primary value (e.g. @0 = first output url) | | @N. | Drill into the N-th output (@0.url, @1.meta.fps) | | @* | All outputs' primary values as an array | | @stdin | The whole upstream JSON envelope | | @stdin: | Jsonpath into the whole envelope (@stdin:result.outputs[0].url) |

    Examples

    bash

    Generate an image and feed its url straight into image-to-video

    dlazy seedream-4.5 --prompt "a red fox in snow" \ | dlazy kling-v3 --image - --prompt "fox starts running"

    Generate an image, then add TTS narration over a still

    dlazy seedream-4.5 --prompt "lighthouse at dawn" \ | dlazy keling-tts --text "Welcome to the coast." --image @0.url

    Fan-out: pass every upstream output url into a batch step

    dlazy seedream-4.5 --prompt "city skyline" --n 4 \ | dlazy superres --images @* ``

    > Required flags can be entirely sourced from the pipe β€” --field - satisfies the requirement when an upstream value exists. If stdin is empty, the CLI fails with code: "no_stdin".

    Usage

    This is a comprehensive skill that routes generation requests to the appropriate dlazy model based on the user's intent.

    Available Models by Category

    Image Generation:

  • dlazy gpt-image-2: GPT Image 2 model for text-to-image and image editing. Supports generating images from text as well as editing and synthesizing images with reference inputs.
  • dlazy seedream-4.5: High-quality text-to-image/image-to-image model, suitable for posters, realism, and creative scenes. Supports prompt + multiple reference images, outputting single high-res images (2K/4K).
  • dlazy seedream-5.0-lite: Lightweight high-speed image generation model, suitable for batch generation, sketches, and low-cost iteration. Supports prompt + reference images, outputting 2K/3K images.
  • dlazy banana2: General text-to-image model (optional 1 reference image), emphasizes speed and cost-effectiveness. Suitable for quick visual drafts, social media posts, and multi-size generation.
  • dlazy banana-pro: High-quality text-to-image model (optional 1 reference image), suitable for key visuals, product shots, and brand style generation with higher detail requirements.
  • dlazy grok-4.2: Minimalist text-to-image model, requires only prompt. Suitable for quick creative validation or scenarios with average quality requirements.
  • dlazy recraft-v3: Stylized text-to-image model, supports aspect ratio and style control (realism/illustration, etc.). Suitable for brand KV, posters, and consistent visual content.
  • dlazy recraft-v3-svg: Text-to-vector model, outputs SVG/vector-style results. Suitable for logos, icons, line art, and scalable design assets.
  • dlazy recraft-v4: 1MP raster image generation with refined design judgment. Suitable for everyday creative work and fast iteration.
  • dlazy recraft-v4-vector: Text-to-vector model that outputs SVG results. Suitable for logos, icons, and scalable design assets.
  • dlazy recraft-v4-pro: 4MP high-resolution raster image generation. Suitable for print-ready assets and large-scale use.
  • dlazy recraft-v4-pro-vector: High-fidelity text-to-vector model with 4MP-tier quality. Suitable for production-grade SVG assets and detailed illustrations.
  • dlazy mj-imagine: Midjourney style generation, supports aspect ratio, Bot type, and output position (grid/U1-U4). Suitable for artistic and strongly stylized creative generation.
  • dlazy kling-image-o1: Kling image model, supports '' placeholder in prompt for reference image binding. Suitable for multi-image constraints and high-fidelity generation.
  • dlazy viduq2-t2i: Vidu image generation model, supports text + reference image, aspect ratio, and resolution control. Suitable for character art, cover images, and high-res generation.
  • dlazy jimeng-t2i: Jimeng high-res text-to-image model, supports multi-ratio ultra-clear output and reference image constraints, suitable for commercial visuals and refined generation.
  • dlazy imageseg: Image matting tool: separates foreground from background and returns transparent background URL, suitable for product image processing, character cutout, and composition.
  • dlazy image-replicate: Image replicate tool: analyzes the visuals, composition, colors, lighting, and style of the source image, builds a replicate prompt, and hands it off to Seedream 4.5 to generate a new image in the same style.
  • dlazy superres: Image super-resolution tool: enhances image clarity and details, returning enhanced URL, suitable for low-res asset restoration and upscaling.
  • Video Generation:

  • dlazy seedance-2.0: ByteDance's latest video generation model. Supports multi-modal reference (images, video, audio) to generate videos, as well as first/last frame and text-to-video modes.
  • dlazy seedance-2.0-fast: Fast version of ByteDance's Seedance 2.0. Generates videos faster with support for multi-modal references, first/last frame, and text-to-video.
  • dlazy veo-3.1: High-quality video generation model, supports text-to-video and single-image-driven video. Suitable for ad shorts and cinematic sequences (slower speed, higher quality).
  • dlazy happyhorse-1.0: Happy Horse 1.0 video model β€” one model covers text-to-video (t2v), first-frame-to-video (i2v), reference-to-video (r2v), and video editing (edit). The selected mode is automatically routed to the matching sub-model.
  • dlazy veo-3.1-fast: Fast video generation model, supports text-to-video and single/multi-image/first-last frame driven. Suitable for time-sensitive previews and rapid iterations.
  • dlazy kling-v3-omni: Kling Omni video model, supports multiple reference images, duration, mode (std/pro), and optional audio. Suitable for highly controlled video synthesis tasks.
  • dlazy kling-v3: Kling V3 general video model, supports text + up to 4 reference images, suitable for stable short video clips and daily creative workflows.
  • dlazy seedance-1.5-pro: ByteDance high-quality video generation model, supports text-to-video with optional first/last frame control for transitions, suitable for narrative shorts and continuous action scenes.
  • dlazy wan2.7: Tongyi Wanxiang 2.7 video model β€” one model covers text-to-video, first/last-frame-to-video, and reference-to-video: uses text-to-video when no images are provided, first/last-frame-to-video when frames are provided, and reference-to-video when reference images are supplied.
  • dlazy wan2.6-r2v: Tongyi Wanxiang video generation model (Standard), supports text + reference image, resolution, and shot type control, suitable for general short video production.
  • dlazy wan2.6-r2v-flash: Tongyi Wanxiang video generation model (Flash), optimized for speed and throughput, supports optional audio output, suitable for batch generation and quick trials.
  • dlazy pixverse-c1: PixVerse C1 video model (strong on action, VFX, and high-motion scenes) β€” one model covers text-to-video, image-to-video, first/last-frame-to-video, and reference-to-video: t2v when no images, i2v with first frame only, kf2v with first+last frames, r2v with reference images.
  • dlazy viduq2-i2v: Vidu image-to-video model, supports reference image-driven video, duration/resolution/ratio, and audio settings, suitable for image animation and short clips.
  • dlazy jimeng-i2v-first: Jimeng first-frame-to-video model, uses first frame + text to generate video. Suitable for single-shot scenes that naturally animate static images.
  • dlazy jimeng-i2v-first-tail: Jimeng first/last-frame video model, supports first and last frame constraints to control shot start/end states, suitable for transitions and clear action conclusions.
  • dlazy jimeng-dream-actor: Jimeng character/action-driven video model, supports reference image and video input, suitable for character acting, action transfer, and style-consistent generation.
  • dlazy jimeng-omnihuman-1.5: Jimeng digital human model, supports generating high-quality digital human videos from any aspect ratio image containing a character/subject combined with audio.
  • dlazy video-scenes: Scene split tool: uses ffmpeg to detect and split a video into scene clips, returning only the clip URLs without video content understanding.
  • dlazy video-replicate: Video replicate tool: extracts the first frame and audio from the source video, runs video understanding for a prompt, and returns a Seedance 2.0 replicate bundle (first frame + audio + video).
  • dlazy merge: Audio/video merging tool: merges multiple video and audio tracks based on clips and timeline config, suitable for final cuts, scoring, and post-production.
  • dlazy one-click-generation: Short-video generation pipeline. Configure subject, script, TTS voiceover, BGM, and subtitle styling.
  • Audio Generation:

  • dlazy gemini-2.5-tts: Gemini-powered high-quality text-to-speech. Supports bilingual (EN/CN) and various emotional voices.
  • dlazy suno-music: Suno music generation model. Supports inspiration mode (auto lyrics) and custom mode (manual lyrics), generating music with or without vocals.
  • dlazy keling-sfx: Sound effect generation model: supports text-to-SFX and matching SFX/BGM for reference videos. Suitable for foley, ambient sounds, and short video audio completion.
  • dlazy keling-tts: Text-to-speech model (TTS), supports language, voice, speed, and output format settings. Suitable for dubbing, audiobooks, and voice broadcasts.
  • dlazy doubao-tts: ByteDance Doubao speech synthesis model. Supports multiple languages, voices, and highly natural streaming audio output, suitable for news broadcasts and audiobooks.
  • dlazy vidu-audio-clone: Clone a real human voice and use it to read the specified text.
  • dlazy kling-audio-clone: Custom voice (Kling), cloned voice used for dubbing or binding to subjects.
  • CRITICAL INSTRUCTION FOR AGENT:

    1. Determine the media type (image, video, or audio) requested by the user. 2. Select the most appropriate model from the list above. 3. Run dlazy -h to check the required parameters for that specific model. 4. Execute the command (e.g., dlazy seedream-4.5 --prompt "...").

    Error Handling

    | Code | Error Type | Example Message | | ---- | ---------------------------------- | ------------------------------------------------------------------------------------------------------------------------ | | 401 | Unauthorized (No API Key) | ok: false, code: "unauthorized", message: "API key is missing or invalid" | | 501 | Missing required parameter | error: required option '--prompt ' not specified | | 502 | Local file read error | Error: Image file/Video file not found: C:\path\to\your\file | | 503 | API request failed (no balance) | ok: false, code: "insufficient_balance" | | 503 | API request failed (server error) | HTTP status code error (500 server crash) | | 504 | Asynchronous task execution failed | === Generation Failed === / {Specific error reason returned by backend, for example "Prompt violates safety policy"} |

    > AGENT CRITICAL INSTRUCTION: > 1. If the execution result returns code: "insufficient_balance", you MUST explicitly inform the user that their credits are insufficient and guide them to recharge: https://dlazy.com/dashboard/organization/settings?tab=credits > 2. If the execution result returns code: "unauthorized" or indicates missing API key, you MUST inform the user to get their API key from https://dlazy.com/dashboard/organization/api-key and save it using dlazy auth set ` and resume the task.

    Tips

    Visit https://dlazy.com for more information.

    πŸ’‘ Examples

    # Generate an image and feed its url straight into image-to-video
    dlazy seedream-4.5 --prompt "a red fox in snow" \
      | dlazy kling-v3 --image - --prompt "fox starts running"

    Generate an image, then add TTS narration over a still

    dlazy seedream-4.5 --prompt "lighthouse at dawn" \ | dlazy keling-tts --text "Welcome to the coast." --image @0.url

    Fan-out: pass every upstream output url into a batch step

    dlazy seedream-4.5 --prompt "city skyline" --n 4 \ | dlazy superres --images @*

    > Required flags can be entirely sourced from the pipe β€” --field - satisfies the requirement when an upstream value exists. If stdin is empty, the CLI fails with code: "no_stdin".

    πŸ“‹ Tips & Best Practices

    Visit https://dlazy.com for more information.