--- id: daily-higgsfield-generate name: "higgsfield-generate" url: https://skills.yangsir.net/skill/daily-higgsfield-generate author: higgsfield-ai domain: multimedia tags: ["generative-ai", "video-generation", "content-creation", "marketing"] install_count: 24400 rating: 4.60 (32 reviews) github: https://github.com/higgsfield-ai/skills --- # higgsfield-generate > 统一调用Higgsfield所有图像视频生成模型，支持营销素材和品牌内容创作 **Stats**: 24,400 installs · 4.6/5 (32 reviews) ## Before / After 对比 ### 素材生成流程 **Before**: 使用多个独立工具生成图片和视频，需要分别学习不同平台的操作界面，复制粘贴提示词，手动下载整合素材，一个营销活动需要3天完成素材准备 **After**: 通过统一CLI调用所有Higgsfield模型，一次性生成图片、视频、品牌头像等全套营销素材，自动返回URL链接，半天完成整个活动素材库 | Metric | Before | After | Change | |---|---|---|---| | 素材准备时间 | 3天 | 0.5天 | -83% | ## Readme # higgsfield-generate # Higgsfield Generate Submit jobs to any Higgsfield model. Wraps the `higgsfield` CLI. Covers generic image/video gen and Marketing Studio (branded ads, avatars, products). ## Step 0 — Bootstrap Before any other command, make sure the CLI is installed and authenticated: - If `higgsfield` is not on `$PATH`, install it: ``` curl -fsSL https://raw.githubusercontent.com/higgsfield-ai/cli/main/install.sh | sh ``` - If `higgsfield account status` fails with `Session expired` / `Not authenticated`, ask the user to run `higgsfield auth login` (interactive, opens a browser) and wait for them to confirm before continuing. Skip both checks if `higgsfield account status` already prints account info. ## UX Rules - Be concise. No raw IDs, no JSON dumps in chat. Print result URL when ready. - No internal jargon. Don't narrate "calling higgsfield cost", "polling job". - Detect the user's language from the first message and reply in it. Technical args (`--aspect_ratio 16:9`) stay English. - Don't batch-ask. Pick a sane default model and ask one thing at a time only if genuinely missing. - Don't pre-estimate cost. Just submit unless the user asks. - Pass `--wait` to `generate create` so the command blocks until done and prints the result URL itself. Avoid the two-step `create` → `wait` pattern. ## Workflow — generic generation - **Pick a model.** Practical defaults from production use: **Image:** Brand product visual (Pinterest pin, lifestyle, hero banner, ad pack, virtual try-on) → use `higgsfield-product-photoshoot` instead. NOT this skill. - Branded ad image with avatar + product (Marketing Studio shape) → Marketing Studio Image (see Marketing Studio below) - Aesthetic UGC / fashion editorial / lifestyle character → Soul 2.0 - Cinematic still frame → Soul Cinema - Highly characterful creative persona (text-only, distinctive) → Soul Cast - Locations / environments / no-people scenes → Soul Location (best in class) - Vector illustrations OR face edit + complex scene swap → Seedream 4.5 - Soul Character (reference id from `higgsfield-soul-id`) → Soul 2.0 for stills, Soul Cinema for cinematic - Fast and cheap iteration → Z Image - Character or cartoon-style work → Nano Banana 2; step up to Nano Banana Pro on hard cases - **Default for everything else → GPT Image 2.** Graphic design, UI, banners, typography, and high-fidelity general generation. **Video:** - All advertising / commercial / branded ad video → Marketing Studio (see Marketing Studio below) - **Default all-purpose serious video (multi-shot, consistent identity, motion-heavy) → Seedance 2.0.** SOTA. - Single-plane scene without strong dynamics, cheaper than Seedance 2.0 → Kling 3.0 - Cheap clean shot without cuts → Seedance 1.5 Pro - Cinema-grade highest fidelity → Cinema Studio Video 3.0 - Cheap with strong physics, no audio needed → Minimax Hailuo - Fast batch / volume → Veo 3.1 Lite For the actual `--model` ID to pass to `higgsfield generate create`, run `higgsfield model list --json | jq` to map display names to IDs. See `references/model-catalog.md` for the full table. - **Pass media inputs straight to flags.** Media flags accept a local file path **or** a UUID. CLI auto-uploads paths and auto-detects job vs upload for UUIDs. No need to pre-upload. Each model declares accepted roles (`image`, `start_image`, `end_image`, `video`, `audio`) — see `references/media-inputs.md`. - **Validate quickly.** If unsure of params, run `higgsfield model get --json` once and pass only what's needed. Use schema defaults otherwise. The server returns `adjustments` for non-fatal coercions (e.g. `aspect_ratio=99:99` → closest match) and a structured error for invalid declared-param values. - **Submit and wait in one shot.** `higgsfield generate create --prompt "..." [media flags] [param flags] --wait`. Blocks until terminal status and prints the result URL on stdout. Tunables: `--wait-timeout 20m` (default 10m), `--wait-interval 5s` (default 3s). - **Deliver.** Send the URL plus a one-line summary (model, duration if video). To inspect or rerun later, `higgsfield generate list --json` and `higgsfield generate get --json` work for retrospection. `higgsfield generate wait ` is still available if you ever need to rejoin a job started without `--wait`. ## Media flags Flag Use for Models that accept it `--image ` reference image most image models, `seedance_2_0`, `veo3`, `marketing_studio_video` `--start-image ` first frame for image-to-video transitions `kling3_0`, `kling2_6`, `veo3_1`, `seedance_2_0`, `marketing_studio_video` `--end-image ` last frame for transitions `kling3_0`, `seedance_2_0`, `marketing_studio_video` `--video ` reference video `seedance_2_0` `--audio ` reference audio (lipsync, soundtrack match) `seedance_2_0` (use this, NOT `--generate-audio`) Each flag accepts either a local file path (auto-uploaded) or a UUID (upload id from `higgsfield upload create`, or a previous job id). Each model declares its own role set via `MEDIA_ROLES`. See `references/media-inputs.md` for the full table. ## Common params Flags pass through to model schema. Use `higgsfield model get ` to discover. ``` higgsfield generate create gpt_image_2 --prompt "neon city at dusk" --aspect_ratio 16:9 --resolution 2k --wait higgsfield generate create nano_banana_2 --prompt "anime character concept, expressive pose" --image ./ref.png --wait higgsfield generate create seedance_2_0 --prompt "camera dollies in" --start-image ./first.png --duration 8 --wait higgsfield generate create text2image_soul_v2 --prompt "..." --soul-id --wait ``` For machine-readable output (chained pipelines, agent context), add `--json`. With `--wait --json` you get the final job object array. Without `--wait`, you get the job IDs. Stdin prompt: `echo "..." | higgsfield generate create z_image --wait`. ## Marketing Studio Branded image/video gen: avatars + products + ad-style modes. Use models `marketing_studio_video` and `marketing_studio_image`. ### Concepts - **Avatar** — presenter face. Curated `preset` (browse `higgsfield marketing-studio avatars list`) or `custom` (uploaded photos via `higgsfield marketing-studio avatars create`). - **Product** — brand item with title + reference images. Imported from URL (`higgsfield marketing-studio products fetch --url ...`) or created from uploaded images (`higgsfield marketing-studio products create`). - **Webproduct** — App Store / web page version. Auto-routes when fetching App Store URLs. ### UX rules (additional) - One question per phase. Don't ask product+avatar+mode upfront. ### Workflow — quick ad video - **Get product.** URL → `higgsfield marketing-studio products fetch --url --wait` (polls until import done) - Local images → `higgsfield upload create ...` then `higgsfield marketing-studio products create --title "..." --image ...` Capture product id. - **Pick avatar.** Default: `higgsfield marketing-studio avatars list` and pick a preset matching the brand voice. - Custom: `higgsfield marketing-studio avatars create --name "..." --image `. - **Pick mode.** Default `ugc`. Other slugs (canonical from MCP): `tutorial`, `ugc_unboxing`, `hyper_motion`, `product_review`, `tv_spot`, `wild_card`, `ugc_virtual_try_on`, `virtual_try_on`. See `references/marketing-modes.md`. - **Generate (one-shot).** ``` higgsfield generate create marketing_studio_video \ --prompt "..." \ --avatars '[{"id":"","type":"preset"}]' \ --product_ids '[]' \ --mode ugc \ --duration 15 \ --resolution 720p \ --aspect_ratio 9:16 \ --wait ``` Resolution is `480p` or `720p`. Aspect ratio is one of `auto`/`21:9`/`16:9`/`4:3`/`1:1`/`3:4`/`9:16`. `--generate-audio true` is supported here (unlike `seedance_2_0`). `--wait` blocks until done; bump `--wait-timeout 30m` for longer ad runs. - **Deliver.** URL + one-line summary (mode, duration). ### Click-to-Ad shortcut (URL-driven) When the user gives a product URL and wants a marketing video in one go: ``` # 1. Trigger fetch (returns the product id and starts background scrape) higgsfield marketing-studio products fetch --url https://shop.example.com/sneakers --wait # 2. Generate the marketing video against the same URL — backend reuses the entity higgsfield generate create marketing_studio_video \ --url https://shop.example.com/sneakers \ --mode ugc \ --duration 15 \ --aspect_ratio 9:16 \ --wait ``` Backend dedupes by URL, so repeated runs reuse the existing entity instead of re-fetching. ### Workflow — marketing image Same as above but use `marketing_studio_image` model: ``` higgsfield generate create marketing_studio_image \ --prompt "..." \ --aspect_ratio 1:1 \ --resolution 2k \ --wait ``` ## Errors - `Missing required params: prompt` → user gave no prompt; ask for it. - `Invalid values: aspect_ratio=99:99 (allowed: ...)` → bad enum; pick from allowed. - `Unknown params: foo` → schema doesn't accept that flag; check `higgsfield model get `. - `Session expired` → `higgsfield auth login`. See `references/troubleshooting.md` for more. ## Reference docs Load on demand: - `references/model-catalog.md` — picking the right model for the task - `references/prompt-engineering.md` — writing prompts that work - `references/media-inputs.md` — image/video reference flows - `references/troubleshooting.md` — common errors and fixes - `references/marketing-avatars.md` — preset vs custom avatars - `references/marketing-products.md` — URL fetch vs manual product create - `references/marketing-modes.md` — every Marketing Studio mode Weekly Installs2.6KRepository[higgsfield-ai/skills](https://github.com/higgsfield-ai/skills)GitHub Stars45First Seen1 day agoSecurity Audits[Gen Agent Trust HubFail](/higgsfield-ai/skills/higgsfield-generate/security/agent-trust-hub)[SocketPass](/higgsfield-ai/skills/higgsfield-generate/security/socket)[SnykFail](/higgsfield-ai/skills/higgsfield-generate/security/snyk) --- *Source: https://skills.yangsir.net/skill/daily-higgsfield-generate* *Markdown mirror: https://skills.yangsir.net/api/skill/daily-higgsfield-generate/markdown*