图片生成 Image Generate

--- name: dlazy-image-generate version: 1.3.5 description: "Image generation skill. Automatically selects the best dlazy CLI image model based on the prompt. 图片生成技能。根据提示词自动选择最佳的 dlazy CLI 图片生成模型。" metadata: {"clawdbot":{"emoji":"🤖","requires":{"bins":["npm","npx"]},"install":"npm install -g @dlazy/cli@1.2.3","installAlternative":"npx @dlazy/cli@1.2.3","homepage":"https://github.com/dlazy-ai/cli","source":"https://github.com/dlazy-ai/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 <subcommand>."}} --- # 图片生成 Image Generate [English](./SKILL.md) · [中文](./SKILL-cn.md) Image generation skill. Automatically selects the best dlazy CLI image model based on the prompt. ## Trigger Keywords - generate image - draw picture - text to image ## Authentication All requests require a dLazy API key. The recommended way to authenticate is `dlazy login`: ```bash dlazy login ``` 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/dlazy-ai/cli](https://github.com/dlazy-ai/cli) - **Maintainer**: dlazyai - **npm package**: `@dlazy/cli` (pinned to `1.2.3` 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@1.2.3 <command> ``` Or, if you prefer a global install, the skill's `metadata.clawdbot.install` field declares the exact pinned version (`npm install -g @dlazy/cli@1.2.3`). 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.<jsonpath>` | 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>` | 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 qwen-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 — `--field -` satisfies the requirement when an upstream value exists. If stdin is empty, the CLI fails with `code: "no_stdin"`. ## Usage This skill handles all image generation requests by selecting the best `dlazy` image model. ### Available Image Models - `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 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 '<image_1>' 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`: Full version of the Doubao image model, generating 2K/3K/4K images from prompts and reference images. Suited to key visuals, posters and anything meant for large-format print. - `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 seedream-5.0-pro`: Professional tier of Seedream 5.0, stronger on fine detail, typography and complex composition. Suited to commercial key visuals and demanding brand assets. - `dlazy superres`: Image super-resolution tool: enhances image clarity and details, returning enhanced URL, suitable for low-res asset restoration and upscaling. - `dlazy vectorize`: Image-to-SVG tool: converts raster images (PNG/JPG) into color vector SVG and returns the URL, suitable for lossless scaling and vectorization of logos, icons, and flat illustrations. - `dlazy viduq2-t2i`: Vidu image model with text + reference image, ratio, and resolution control. Good for character art, covers, and high-res output. **CRITICAL INSTRUCTION FOR AGENT**: 1. Select the most appropriate image model. 2. Run `dlazy <model_name> -h` to check parameters. 3. Execute the command. ## 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 <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](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](https://dlazy.com/dashboard/organization/api-key) and save it using `dlazy auth set <key>` and resume the task. ## Tips Visit https://dlazy.com for more information.

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