--- slug: dlazy-generate name: dlazy-generate version: "1.3.2" displayName: Dlazy Generate summary: "综合生成,自动选模型生成图/视频/音频" by automatically selecti... license: MIT-0 description: |- A comprehensive generation skill。Can generate images, videos, and audio\ \ by automatically selecti。Use when 需要视频处理、音频编辑、媒体转换、配音生成时使用。不适用于版权受保护的媒体内容处理。 tags: '[''Creative'']' tools: - read - exec pricing_tier: "L2" pricing_model: "per_use" suggested_price: 19.9 --- # 综合生成 Dlazy Generate [English](/api/v1/skills/dlazy-generate/file?path=SKILL.md&ownerHandle=dlazyai) · [中文](/api/v1/skills/dlazy-generate/file?path=SKILL-cn.md&ownerHandle=dlazyai) 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: ```bash This runs a device-code flow (also works in remote shells) and **automatically saves your API key** to the local CLI config — 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](https://dlazy.com) 2. Go to [dlazy.com/dashboard/organization/api-key](https://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](https://github.com/dlazyai/cli) * **Maintainer**: dlazyai * **npm package**: `@dlazy/cli` (pinned to `1.0.9` in this skill's install spec) * **Homepage**: [dlazy.com](https://dlazy.com) You can install on demand without persisting a global binary by running: ```bash npx @dlazy/cli@1.2.0 ``` Or, if you prefer a global install, the skill's `metadata.clawdbot.install` field declares the exact pinned version (`npm install -g @dlazy/cli@1.2.0`). 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 — 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](https://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`) | ### 示例 ```bash dlazy seedream-4.5 --prompt "a red fox in snow" \ | dlazy kling-v3 --image - --prompt "fox starts running" dlazy seedream-4.5 --prompt "lighthouse at dawn" \ | dlazy keling-tts --text "Welcome to the coast." --image @0.url dlazy seedream-4.5 --prompt "city skyline" --n 4 \ | dlazy superres --images @* ``` > Required flags can be entirely sourced from the pipe — `--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 banana-pro`: High-quality text-to-image model (optional 1 reference image). Good for detailed key visuals, product shots, and brand-style imagery. * `dlazy banana2`: General text-to-image model (optional 1 reference image), prioritizing speed and cost. Good for quick drafts, social posts, and multi-ratio 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 grok-4.2`: Minimalist text-to-image model, prompt-only. Good for quick concept validation or undemanding instant generation. * `dlazy image-replicate`: Image replicate tool: analyzes the source's composition, color, lighting, and style, then uses Seedream 4.5 to generate a new image in the same style. * `dlazy imageseg`: Image matting tool: separates foreground and returns a transparent-background URL. Good for product images, cutouts, and compositing. * `dlazy jimeng-t2i`: Jimeng high-res text-to-image model with multi-ratio ultra-HD output and reference-image constraints. Good for commercial visuals and refined output. * `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 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 qwen-image-2-pro`: Alibaba Bailian qwen-image-2.0-pro general image generation. Excels at complex text rendering, multi-line layout, photorealistic detail, and strong semantic adherence — great for mixed text/image designs. * `dlazy recraft-v4`: 1MP raster image generation with refined design judgment. Suitable for everyday creative work and fast iteration. * `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, 4MP-tier quality. Good for production SVG assets and detailed illustrations. * `dlazy recraft-v4-vector`: Text-to-vector model that outputs SVG results. Suitable for logos, icons, and scalable design assets. * `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 superres`: Image super-resolution tool: enhances image clarity and details, returning enhanced URL, suitable for low-res asset restoration and upscaling. * `dlazy viduq2-t2i`: Vidu image model with text + reference image, ratio, and resolution control. Good for character art, covers, and high-res output. **Video Generation:** * `dlazy happyhorse-1.0`: Happy Horse 1.0 video model — 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 heygen-lipsync-speed`: HeyGen Lipsync Speed: Fast lip-sync model, ideal for scenarios requiring rapid generation. * `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-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; constrains shot start/end frames. Good for transitions and clearly resolved action. * `dlazy jimeng-omnihuman-1.5`: Jimeng digital human model: combines any-ratio character/subject image with audio to generate high-quality digital human videos. * `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 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 pixverse-c1`: PixVerse C1 video model (strong on action, VFX, and high-motion scenes) — 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 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 sync-lipsync-3`: fal.ai sync-lipsync v3 — given an input video and audio, generate a new video where the speaker's lip movement matches the audio. Good for dubbing, localization, and re-syncing virtual presenters. * `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 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 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 videoretalk`: Tongyi VideoRetalk lip sync / lip-sync (mouth sync, dubbing) video model — takes a talking-person video plus a voice audio track and regenerates the video so the speaker's mouth/lips match the new audio. Use this for lip syncing a person video to new speech. Optionally provide a reference face image to pick the target person when the video contains multiple faces. * `dlazy videoseg`: Video human segmentation tool: invokes Aliyun's async SegmentVideoBody and returns a same-length black/white mask video, suitable for downstream compositing or matting. * `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 wan2.7`: Tongyi Wanxiang 2.7 video model — 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. **Audio Generation:** * `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 elevenlabs-dialogue`: ElevenLabs eleven_v3 multi-voice dialogue: assign a different voice per line (up to 10) and render the whole conversation in one shot. Supports audio tags like [giggling], [whispers] — great for character dialogue, podcasts, and short skits. Before picking a voice, you can search for the right one via elevenlabs-search. * `dlazy elevenlabs-music`: ElevenLabs music_v1 model — generates 10–300s original music from a natural-language prompt. Good for BGM, ads, and short-video soundtracks. * `dlazy elevenlabs-search`: Search the ElevenLabs voice library by keyword, source, and category. Returns a playable preview for each matched voice so you can pick the right one before running TTS. * `dlazy elevenlabs-sfx`: ElevenLabs text-to-sound model — generates 1–22s short sound effects from a description. Suitable for foley, ambience, alerts, and game SFX. * `dlazy elevenlabs-tts`: ElevenLabs eleven_v3 text-to-speech with 12 curated multilingual voices and stability/similarity/style controls. Great for dubbing, audiobooks, and character dialog. Before picking a voice, you can search for the right one via elevenlabs-search. * `dlazy elevenlabs-voice-clone`: ElevenLabs Instant Voice Cloning (IVC). Upload a clean voice sample to clone a custom voice usable with ElevenLabs TTS. * `dlazy gemini-2.5-tts`: Gemini-powered high-quality text-to-speech. Supports bilingual (EN/CN) and various emotional voices. * `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 kling-audio-clone`: Custom voice (Kling), cloned voice used for dubbing or binding to subjects. * `dlazy qwen-audio-clone`: Alibaba Bailian qwen3-tts voice cloning. Upload a clean voice sample to clone a custom voice usable in subsequent TTS calls. * `dlazy qwen-tts`: Alibaba Bailian qwen3-tts text-to-speech. Choose from curated system voices (including dialects) or design a custom voice from a natural-language description. * `dlazy suno-music`: Suno V5.5 music generation. Inspiration mode (auto lyrics) or custom mode (manual style/title/lyrics). Generates music with or without vocals, with fine-grained controls over style weight, weirdness and audio weight. * `dlazy vidu-audio-clone`: Clone a real human voice and use it to read the specified text. **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: > 2. If the execution result returns `code: "unauthorized"` or indicates missing API key, you MUST inform the user to get their API key from and save it using `dlazy auth set ` and resume the task. ## Tips Visit for more information. ## 依赖说明 ### 运行环境 - **Agent平台**: 支持SKILL.md的任意AI Agent(Claude Code / Cursor / Codex / Gemini CLI等) - **操作系统**: Windows / macOS / Linux ### 依赖说明 | 依赖项 | 类型 | 是否必需 | 获取方式 | |:-------|:-----|:---------|:---------| | LLM API | API | 必需 | 由Agent内置LLM提供 | ### API Key 配置 - 本Skill基于Markdown指令,无需额外API Key(除内容中明确标注的外部API) ### 可用性分类 - **分类**: MD+EXEC(纯Markdown指令,部分功能需要exec命令行执行能力) - **说明**: 基于Markdown的AI Skill,通过自然语言指令驱动Agent执行任务 ## 核心能力 - A comprehensive generation skill - Can generate images, videos, and audio\ \ by automatically selecti ## 适用场景 | 场景 | 输入 | 输出 | |------|------|------| | 基础使用 | 用户请求 | 处理结果 | **不适用于**：需要人工判断的复杂决策场景 ## 使用流程 1. 确认运行环境满足依赖说明中的要求 2. 根据适用场景选择合适的使用方式 3. 执行操作并检查输出结果 4. 如遇错误，参考错误处理章节 ## 错误处理 | 错误场景 | 原因 | 处理方式 | |---------|------|---------| | 配置错误 | 参数缺失或格式错误 | 检查依赖说明中的配置要求 | | 运行时错误 | 运行环境不满足 | 确认运行环境符合依赖说明 | | 网络错误 | 连接超时或不可达 | 检查网络连接后重试，参考国内替代方案 | ## 常见问题 ### Q1: 如何开始使用Dlazy Generate？ A: 请先阅读使用流程章节，确认环境满足依赖说明中的要求。 ### Q2: 遇到错误怎么办？ A: 请参考错误处理章节，按照表格中的处理方式操作。 ### Q3: Dlazy Generate有什么限制？ A: 请参考已知限制章节了解具体限制。 ## 已知限制 - 需要LLM支持，无LLM环境无法使用 - 复杂场景可能需要人工辅助判断 - 性能取决于底层模型能力