[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-75439":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":20,"compositeScore":21,"rankGlobal":10,"rankLanguage":10,"license":22,"archived":23,"fork":23,"defaultBranch":24,"hasWiki":23,"hasPages":23,"topics":25,"createdAt":10,"pushedAt":10,"updatedAt":26,"readmeContent":27,"aiSummary":28,"trendingCount":16,"starSnapshotCount":16,"syncStatus":29,"lastSyncTime":30,"discoverSource":31},75439,"cli","higgsfield-ai\u002Fcli","higgsfield-ai","Higgsfield CLI","",null,"Shell",290,41,5,18,0,8,32,163,24,4.87,"MIT License",false,"main",[],"2026-06-12 02:03:34","# Higgsfield CLI\n\n[![release](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fv\u002Frelease\u002Fhiggsfield-ai\u002Fcli?style=flat-square)](https:\u002F\u002Fgithub.com\u002Fhiggsfield-ai\u002Fcli\u002Freleases)\n[![npm](https:\u002F\u002Fimg.shields.io\u002Fnpm\u002Fv\u002F@higgsfield\u002Fcli?style=flat-square)](https:\u002F\u002Fwww.npmjs.com\u002Fpackage\u002F@higgsfield\u002Fcli)\n[![license](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Flicense\u002Fhiggsfield-ai\u002Fcli?style=flat-square)](.\u002FLICENSE)\n\nGenerate images, videos, and finished-video analysis from the terminal using 30+ [Higgsfield AI](https:\u002F\u002Fhiggsfield.ai) models — Nano Banana Pro, FLUX.2, Soul V2, Veo 3.1, Kling v3.0, Seedance 2.0, Marketing Studio, Virality Predictor, and more. Train face-faithful Soul characters and produce branded marketing assets without leaving your shell.\n\n![Higgsfield CLI demo](.\u002Fdemo.png)\n\n## Contents\n\n- [Install](#install)\n- [Quickstart](#quickstart)\n- [Examples](#examples)\n- [Models](#models)\n- [Commands](#commands)\n- [Flags](#flags)\n- [Updating](#updating)\n- [Uninstall](#uninstall)\n- [Troubleshooting](#troubleshooting)\n- [Support](#support)\n- [License](#license)\n\n## Install\n\n### macOS \u002F Linux — curl\n\n```bash\ncurl -fsSL https:\u002F\u002Fraw.githubusercontent.com\u002Fhiggsfield-ai\u002Fcli\u002Fmain\u002Finstall.sh | sh\n```\n\n### macOS \u002F Linux — Homebrew\n\n```bash\nbrew install higgsfield-ai\u002Ftap\u002Fhiggsfield\n```\n\n### Cross-platform (incl. Windows) — npm\n\n```bash\nnpm install -g @higgsfield\u002Fcli\n```\n\n### Manual\n\nDownload an archive matching your OS and architecture from [Releases](https:\u002F\u002Fgithub.com\u002Fhiggsfield-ai\u002Fcli\u002Freleases), extract, and place the binary in your `$PATH`.\n\n## Quickstart\n\nAuthenticate:\n\n```bash\nhiggsfield auth login\n```\n\nGenerate an image and wait for the result URL:\n\n```bash\nhiggsfield generate create nano_banana_2 --prompt \"a quiet beach at sunrise\" --wait\n```\n\n## Examples\n\n### Nano Banana Pro\n\n```bash\nhiggsfield generate create nano_banana_2 \\\n  --prompt \"modern architecture, glass facade, golden hour light\" \\\n  --aspect_ratio 16:9 \\\n  --resolution 2k \\\n  --wait\n```\n\n### GPT Image 2\n\n```bash\nhiggsfield generate create gpt_image_2 \\\n  --prompt \"clean infographic showing global energy mix, flat icons, muted palette\" \\\n  --aspect_ratio 3:4 \\\n  --quality high --resolution 2k \\\n  --wait\n```\n\n### Kling v3.0\n\n```bash\nhiggsfield generate create kling3_0 \\\n  --prompt \"slow camera push through a forest clearing at dawn\" \\\n  --start-image .\u002Ffirst.png \\\n  --duration 5 --mode pro --sound off \\\n  --wait\n```\n\n### Seedance 2.0\n\n```bash\nhiggsfield generate create seedance_2_0 \\\n  --prompt \"drone shot over a mountain valley at sunrise\" \\\n  --aspect_ratio 16:9 --duration 5 \\\n  --resolution 1080p --mode std --genre noir \\\n  --wait\n```\n\n### Virality Predictor\n\n`brain_activity` is the technical job set type for Virality Predictor. It\nanalyzes a finished video for hook strength, attention, retention, and viral\npotential, then prints scores plus an Open report link.\n\n```bash\nhiggsfield generate create brain_activity --video .\u002Fad.mp4 --wait\nhiggsfield generate get \u003Cjob_id>\nhiggsfield generate wait \u003Cjob_id>\n```\n\n### Soul ID\n\nTrain a Soul ID once:\n\n```bash\nhiggsfield soul-id create --name me --soul-2 \\\n  --image .\u002Fme1.jpg --image .\u002Fme2.jpg --image .\u002Fme3.jpg\nhiggsfield soul-id wait \u003Csoul_id>\n```\n\nReuse it in any compatible image model:\n\n```bash\nhiggsfield generate create text2image_soul_v2 \\\n  --prompt \"professional portrait, neutral background, soft daylight\" \\\n  --soul-id \u003Csoul_id> \\\n  --wait\n```\n\n## Models\n\n30+ image and video models. Per-model parameters, defaults, and enums: [MODELS.md](.\u002FMODELS.md). Live catalog: `higgsfield model list`.\n\n### Image (18)\n\n| job_set_type | name |\n|---|---|\n| `nano_banana_2` | Nano Banana Pro |\n| `nano_banana_flash` | Nano Banana 2 |\n| `nano_banana` | Nano Banana |\n| `flux_2` | FLUX.2 |\n| `flux_kontext` | Flux Kontext |\n| `gpt_image_2` | GPT Image 2 |\n| `text2image_soul_v2` | Higgsfield Soul V2 |\n| `seedream_v4_5` | Seedream 4.5 |\n| `seedream_v5_lite` | Seedream V5 Lite |\n| `grok_image` | Grok Image |\n| `openai_hazel` | OpenAI Hazel |\n| `image_auto` | Image Auto |\n| `z_image` | Z Image |\n| `kling_omni_image` | Kling O1 Image |\n| `cinematic_studio_2_5` | Cinematic Studio 2.5 |\n| `soul_cinematic` | Soul Cinematic |\n| `soul_location` | Soul Location |\n| `marketing_studio_image` | Marketing Studio Image |\n\n### Video (17)\n\n| job_set_type | name |\n|---|---|\n| `brain_activity` | Virality Predictor |\n| `veo3_1` | Google Veo 3.1 |\n| `veo3_1_lite` | Google Veo 3.1 Lite |\n| `veo3` | Google Veo 3 |\n| `kling3_0` | Kling v3.0 |\n| `kling2_6` | Kling 2.6 Video |\n| `seedance_2_0` | Seedance 2.0 |\n| `seedance1_5` | Seedance 1.5 Pro |\n| `wan2_7` | Wan 2.7 |\n| `wan2_6` | Wan 2.6 Video |\n| `minimax_hailuo` | Minimax Hailuo |\n| `grok_video` | Grok Video |\n| `cinematic_studio_3_0` | Cinematic Studio 3.0 |\n| `cinematic_studio_video` | Cinematic Studio Video |\n| `cinematic_studio_video_v2` | Cinematic Studio Video V2 |\n| `soul_cast` | Soul Cast |\n| `marketing_studio_video` | Marketing Studio Video |\n\n## Commands\n\n| Command | Purpose |\n|---|---|\n| `higgsfield auth` | login \u002F logout \u002F inspect token |\n| `higgsfield account` | credits balance, transactions |\n| `higgsfield workspace` | list \u002F select \u002F unset billing workspace |\n| `higgsfield model` | list models, inspect parameter schema |\n| `higgsfield generate` | create \u002F cost \u002F wait \u002F get \u002F list jobs |\n| `higgsfield upload` | upload an image \u002F video \u002F audio file |\n| `higgsfield soul-id` | train and manage Soul characters |\n| `higgsfield marketing-studio` | branded ads (avatars, products, ad references, brand kits, ad formats, DTC Ads Engine) |\n| `higgsfield product-photoshoot` | brand image generation with mode-specific enhancement |\n| `higgsfield version` | print build info |\n\nRun `higgsfield \u003Ccommand> --help` for flags and examples (also `higgsfield generate create --help`, `higgsfield soul-id create --help`, etc.).\n\n## Flags\n\nFlags work across all commands.\n\n| Flag | Purpose |\n|---|---|\n| `--wait` | block until the job finishes; print the result URL |\n| `--wait-timeout` | max wait duration (default `10m`) |\n| `--wait-interval` | poll interval (default `3s`) |\n| `--json` | machine-readable JSON output |\n| `--no-color` | disable color output |\n\nExample pipeline:\n\n```bash\nhiggsfield generate list --json | jq -r '.[] | select(.status==\"completed\") | .result_url'\n```\n\n## Updating\n\n```bash\n# curl\ncurl -fsSL https:\u002F\u002Fraw.githubusercontent.com\u002Fhiggsfield-ai\u002Fcli\u002Fmain\u002Finstall.sh | sh\n\n# brew\nbrew update && brew upgrade higgsfield\n\n# npm\nnpm install -g @higgsfield\u002Fcli@latest\n```\n\nPin to a specific release:\n\n```bash\ncurl -fsSL https:\u002F\u002Fraw.githubusercontent.com\u002Fhiggsfield-ai\u002Fcli\u002Fmain\u002Finstall.sh | sh -s -- --tag v0.1.22\n# or\nnpm install -g @higgsfield\u002Fcli@0.1.22\n```\n\n## Uninstall\n\n```bash\n# curl install (default prefix \u002Fusr\u002Flocal)\nsudo rm \u002Fusr\u002Flocal\u002Fbin\u002Fhiggsfield\n\n# brew\nbrew uninstall higgsfield\n\n# npm\nnpm uninstall -g @higgsfield\u002Fcli\n```\n\n## Troubleshooting\n\n**`Session expired` \u002F `Not authenticated`** — tokens are short-lived. Re-run `higgsfield auth login`.\n\n**`Unknown model \"\u003Cname>\"`** — run `higgsfield model list` for the current catalog.\n\n## Support\n\nBugs and feature requests: [github.com\u002Fhiggsfield-ai\u002Fcli\u002Fissues](https:\u002F\u002Fgithub.com\u002Fhiggsfield-ai\u002Fcli\u002Fissues). Please include `higgsfield version` output and the exact command that failed.\n\n## License\n\n[MIT](.\u002FLICENSE)\n","Higgsfield CLI 是一个命令行工具，允许用户通过终端生成图像、视频以及完成视频分析。它支持超过30种Higgsfield AI模型，如Nano Banana Pro、FLUX.2等，能够训练面部逼真的Soul角色并生成品牌营销素材。该工具基于Shell语言开发，并提供多种安装方式包括curl、Homebrew和npm，适用于macOS、Linux及Windows平台。其核心功能包括生成高质量图像与视频内容、分析视频传播潜力等，特别适合需要快速创建视觉内容且偏好使用命令行界面的开发者或设计师。",2,"2026-06-11 03:52:46","CREATED_QUERY"]