Higgsfield Generate

Higgsfield Generate

Submit jobs to any Higgsfield model. Wraps the higgsfield CLI. Covers generic image/video/3D/audio generation, Marketing Studio (branded ads, avatars, products, hooks, settings), and, secondarily, Virality Predictor video scoring.

Step 0 — Bootstrap

Before any other command:

1. If higgsfield is not on $PATH, install it:

curl -fsSL https://raw.githubusercontent.com/higgsfield-ai/cli/main/install.sh | sh

1. If higgsfield account status fails with Session expired / Not authenticated, ask the user to run higgsfield auth login (interactive) and wait for confirmation.

UX Rules

1. Be concise. No raw IDs, no JSON dumps in chat. Return the media URL from the CLI unchanged for generated assets, or the text summary for Virality Predictor.
2. No internal jargon. Don't narrate calling higgsfield cost, polling job.
3. Detect the user's language from the first message and reply in it. Technical args (--aspect_ratio 16:9) stay English.
4. Don't batch-ask. Pick a sane default model and ask one thing at a time only if genuinely missing.
5. Don't pre-estimate cost or optimize for cheaper models unless the user asks. Prefer the quality default first.
6. Pass --wait to generate create so the command blocks until done and prints the result URL itself. Avoid the two-step create → wait pattern.
7. Prompt-only or explanation-only requests return text without submitting a job.

Discovery guardrail

When looking for a Higgsfield feature/model, do not rely only on semantic search or CLI --help. First run an unfiltered model list, then inspect likely job_set_type names. If the user says a model exists but search returns no results, trust that signal and verify with the full model list before answering.

Workflows are separate from models. Discover them with higgsfield workflow list and inspect params with higgsfield workflow get .

Virality Predictor is exposed as:

• Customer-facing name: Virality Predictor
• Technical job_set_type: brain_activity
• Category/output: text report. This is video-in/text-out analysis, not a text/chat generation model.
• Input: uploaded video
• Purpose: finished-video hook, attention, retention, and virality analysis

If the user says analyze this video, score this ad, evaluate the hook, or similar, route to brain_activity even though it appears under text/analysis models. Classify by task intent and required input, not by output category alone.

Workflow — generic generation

1. Pick a model. Start with the core defaults:

• GPT Image 2.6 Sunburst (gpt_image_2_6) → default image model for high-fidelity general generation, graphic design, UI, banners, typography, and on-image text. Flare is the separate model gpt_image_2_6_flare, not a variant parameter.
• Seedance 2.5 (seedance_2_5) → SOTA default video model for serious motion, cinematic clips, multi-shot work, and image-to-video. Supports 4–30s output up to 1080p; use Seedance 2.0 when native 4K is required.
• Nano Banana 2 (nano_banana_flash) → cartoon and illustrated characters.
• Marketing Studio → default for ads, UGC, product demos, unboxing, TV spots, presenter videos, and brand/product workflows.
• Seed Audio 1.0 → default audio model for text-to-audio, voice, sound effects, ambience, foley, and music-like audio unless the user names Sonilo/Mirelo.

Only the models below are picked without being asked. Any other model is used only when the user names it or explicitly asks for what it offers (cheaper, faster, a specific look); see references/model-catalog.md. A model the user names stays in use for follow-ups on the same work.

Image:

• Complete brand identity, logo system, palette, typography, brandbook, packaging system, signage, or coordinated branded asset suite → use higgsfield-brandkit instead.
• YouTube thumbnail, Shorts cover, or Instagram video cover → use higgsfield-youtube-thumbnail instead.
• 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)
• Standalone animated GIF or SVG → GPT Image 2.6, before subject/style auto-picks. Set --output_format gif or --output_format svg before the first submission; mentioning GIF/SVG in the prompt does not select the format. A GIF request is not a video/conversion workflow. SVG accepts no reference images. Preserve explicit model choices and specialized workflow pins; check the named model's format support instead of silently changing it. See references/model-catalog.md for frame controls and examples.
• Soul Character (reference id from higgsfield-soul-id) → Soul 2.0 for stills, Soul Cinema (soul_cinematic) for cinematic
• New original person — UGC, editorial, fashion, lifestyle → Soul 2.0
• Cinematic still frame → Soul Cinema (soul_cinematic)
• Character sheet, one-shot face from reference photos, or face edit on a real photo → Seedream 5.0 Pro (seedream_v5_pro)
• Locations / environments / no-people scenes → Soul Location
• Logo, icon, vector-like illustration, brand mark, controlled-palette graphic → Recraft V4.1 (recraft_v4_1, often with --model_type vector)
• Cartoon or illustrated characters, heavily textured photos → Nano Banana 2 (nano_banana_flash). The id nano_banana_2 is an alias for Nano Banana Pro, not Nano Banana 2
• Default for everything else → GPT Image 2.6 Sunburst (gpt_image_2_6). Graphic design, UI, banners, typography, product concepts, editing, and high-fidelity general generation.
• User asks for cheaper or faster → Nano Banana 2 Lite (nano_banana_2_lite) for reference edits, Z Image for drafts.

Video:

• Complete narrated explainer from a topic, story, or document → use higgsfield-video-explainer, not generic video generation.
• All advertising / commercial / branded ad video → Marketing Studio (see Marketing Studio below)
• Edit existing video from sketch/timestamp, or reframe to another aspect ratio → workflow (draw_to_video or reframe), not a model. See references/workflows.md.
• Default for everything else → Seedance 2.5 (seedance_2_5): multi-shot, consistent identity, motion-heavy, image-to-video, editing, extension, 4–30s. Modes t2v / omni_reference / video_edit / video_extension; use omni_reference for reference inputs, including start/end frames; t2v accepts no media. Up to 1080p. Do not downgrade because another model's schema looks simpler.
• User asks for 4K → Seedance 2.0 (seedance_2_0); say why you switched.
• User asks for cheaper or faster → Kling 3.0 Turbo (kling3_0_turbo), Veo 3.1 Lite, or Seedance 1.5 Pro.
• Named by the user → use it, e.g. Cinema Studio 4.0 (cinematic_studio_video_4_0), Kling 3.0, Veo 3.1, Gemini Omni Flash 1.1 (gemini_omni_flash_1_1), or Grok Video 1.5 (grok_video_v15: one --start-image or --image, duration 2–15s, up to 1080p without reference media).

Video analysis:

• Rate a finished video's hook, virality potential, attention, retention, or distraction risk → Virality Predictor (brain_activity). This is a video analysis model that returns a text score/report, not a generated media asset.

3D:

• A 3D asset within a playable game or game-wide asset system → use higgsfield-websites (game product type).
• Create an actual 3D mesh/model/GLB from one or more object/product reference images → Multi-Image to 3D (multi_image_to_3d). Pass 1–4 images with repeated --image; use --should_texture true when the asset needs texture. If the user only asks for a 3D-rendered picture, use an image model instead.

Audio:

• Default for audio generation → Seed Audio 1.0 (seed_audio). Use for text-to-audio, sound effects, ambience, foley, impacts, environmental audio, voice-style generations, and music-like audio. It requires --prompt; use optional --audio-references/--image-references only when the user provides references.
• Use Sonilo Music (sonilo_music) only when the user explicitly asks for Sonilo or you need that specialist music model. It requires --prompt and --duration, and returns audio.
• Use Mirelo Text to Audio (mirelo_text_to_audio) only when the user explicitly asks for Mirelo or you need that legacy SFX model. It requires --prompt and --duration, and returns audio.

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.

1. 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 media roles or *_references params — see references/media-inputs.md.
2. Validate quickly. If unsure of params, run higgsfield model get --json once and pass only what's needed. Validate the preferred model before falling back to an older one. 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.
3. Submit and wait in one shot. higgsfield generate create [--prompt "..."] [media flags] [param flags] --wait. Blocks until terminal status and prints the result on stdout. Tunables: --wait-timeout 20m (default 10m), --wait-interval 5s (default 3s). Virality Predictor does not need a prompt; pass --video.
4. Deliver. For generated media and 3D assets, send the primary result URL plus a one-line summary (model, duration if video; GLB/asset URL for 3D). For Virality Predictor, deliver the scores, business interpretation, and the Open report link. Do not surface Virality Predictor .glb, .bin, or region-table internals in normal chat output.

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.

For workflow jobs, use higgsfield generate workflow ... --wait. Cost syntax is higgsfield generate cost workflow .... See references/workflows.md.

Media flags

Flag	Purpose	Models that accept it
--image	reference image	most image models, grok_video_v15, multi_image_to_3d, seedance_2_0, seedance_2_5, veo3_1, marketing_studio_video
--start-image	first frame for image-to-video transitions	grok_video_v15, kling3_0, kling3_0_turbo, kling2_6, veo3_1, seedance_2_0, seedance_2_5, marketing_studio_video
--end-image	last frame for transitions	kling3_0, seedance_2_0, seedance_2_5, marketing_studio_video
--video	reference or analyzed video	seedance_2_0, seedance_2_5, brain_activity
--audio	reference audio (lipsync, soundtrack match)	seedance_2_0, seedance_2_5 (reference input; distinct from generating output audio)

For reference-array models, the explicit flags are --image-references, --video-references, and --audio-references; --image, --video, and --audio are short aliases when the schema exposes those params.

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 media roles or *_references params. 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_6 --prompt "neon city at dusk" --aspect_ratio 16:9 --resolution 2k --wait
higgsfield generate create nano_banana_flash --prompt "anime character concept, expressive pose" --image ./ref.png --wait
higgsfield generate create seedance_2_5 --prompt "camera dollies in" --mode omni_reference --start-image ./first.png --duration 12 --resolution 1080p --wait
higgsfield generate create grok_video_v15 --prompt "cinematic handheld shot, neon rainy street" --start-image ./image.png --duration 5 --resolution 720p --wait
higgsfield generate create text2image_soul_v2 --prompt "..." --soul-id  --quality 2k --wait
higgsfield generate create multi_image_to_3d --image ./front.png --image ./side.png --should_texture true --wait
higgsfield generate create seed_audio --prompt "cinematic rain ambience with distant thunder" --wait
higgsfield generate create sonilo_music --prompt "cinematic synthwave track" --duration 12 --wait
higgsfield generate create mirelo_text_to_audio --prompt "glass breaking in a large hall" --duration 4 --wait
higgsfield generate create brain_activity --video ./ad.mp4 --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. Virality Predictor stores raw analysis and render artifacts in the job params, but the default text output should stay to scores plus Open report.

Stdin prompt: echo "..." | higgsfield generate create z_image --wait.

Soul image quality: for text2image_soul_v2 and soul_cinematic, pass --quality 1.5k or --quality 2k. These are UI-facing tiers; the backend maps them to 720p/1080p and model-specific dimensions from the selected --aspect_ratio. soul_location has no quality selector; it uses fixed dimensions per aspect ratio.

Soul style presets: text2image_soul_v2 accepts --style_id ; list curated styles with higgsfield preset list soul-v2 and pass the chosen id. --style_id combines with --soul-id but not with an image reference. soul_cinema_studio also accepts --style_id.

Marketing Studio

Branded image/video gen: avatars + products + optional setup hooks/settings + 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). For UGC modes, an avatar is optional if the brief clearly mentions a person; the backend can create a Soul Character automatically. Pass an avatar when the user wants a specific presenter.
• 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.
• Hook — reusable opening angle / ad hook. Browse with higgsfield marketing-studio hooks list. Hook text is prepended to the user's prompt; it does not replace --prompt.
• Setting — reusable environment / scene context. Browse with higgsfield marketing-studio settings list.
• Ad reference — reusable inspiration video that can be bound to an avatar and/or product. Created from an uploaded video (--video-input ) or a previous generation job (--job ). Browse with higgsfield marketing-studio ad-references list. See references/marketing-ad-references.md.
• Brand kit — captures a brand's identity (name, logo, hero images, colours, fonts, tone) for reuse across image generations. Created by handing in a website URL (higgsfield marketing-studio brand-kits fetch --url https://… --wait). See references/marketing-brand-kits.md.
• Ad format — presets that drives the visual structure of a generated image (headline, bullet-points, etc.). Read-only, browse with higgsfield marketing-studio ad-formats list. Required input for dtc-ads generate.

Discovery commands

Use these exact list commands when the user asks what already exists:

higgsfield marketing-studio avatars list --json
higgsfield marketing-studio products list --json
higgsfield marketing-studio hooks list --json
higgsfield marketing-studio settings list --json
higgsfield marketing-studio ad-references list --json
higgsfield marketing-studio brand-kits list --json
higgsfield marketing-studio ad-formats list --json

--hook_id and --setting_id are supported by marketing_studio_video only; do not pass them to marketing_studio_image.

UX rules (additional)

• One question per phase. Don't ask product+avatar+mode upfront.
• Two ad approaches are mutually exclusive. Either the user gives an ad reference video (reference-driven) or picks hook/setting blocks (composed-from-blocks) — never both. If the user has an ad reference selected, do not offer hook/setting; if hook/setting are picked, do not offer to attach an ad reference.
• Ad reference source. The only valid inputs are a local video file (uploaded via higgsfield upload create ... --video) or a prior video job. If the user provides anything else, ask for a local file.
• dtc-ads ad format is mandatory. Always ask the user to pick from ad-formats list. There is no auto-default — both the CLI and server reject calls without --format-id.
• dtc-ads optional inputs. Suggest avatars, products, and reference media when the brief calls for them; only attach what the user picks.

Workflow — quick ad video

1. Get product.

• Existing product → higgsfield marketing-studio products list --json
• 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. When using --hook_id, strongly prefer passing --product_ids; hooks are designed to pivot into a product and work poorly without product context.

1. Pick avatar if needed.

• Default: higgsfield marketing-studio avatars list and pick a preset matching the brand voice.
• Custom: higgsfield marketing-studio avatars create --name "..." --image .

For UGC modes, you may omit --avatars when no specific presenter is required and the brief mentions a person; the backend can synthesize a Soul Character.

1. Optionally pick setup items.

• Hook: higgsfield marketing-studio hooks list --json
• Setting: higgsfield marketing-studio settings list --json

Pass selected IDs as --hook_id and --setting_id for marketing_studio_video only. Do not copy the hook's prompt into --prompt unless the user explicitly wants to reinforce the same wording.

1. Pick mode if needed. Default is ugc; --mode is not required just because --hook_id is present. Other current slugs: ugc_how_to, ugc_unboxing, product_showcase, product_review, tv_spot, wild_card, ugc_virtual_try_on, virtual_try_on. Hook/setting are valid only for ugc, ugc_how_to, ugc_unboxing, product_review, ugc_virtual_try_on — do not pass --hook_id / --setting_id with the other modes. See references/marketing-modes.md.
2. Generate (one-shot).

PRODUCT_IDS_JSON=$(mktemp)
   AVATARS_JSON=$(mktemp)
   printf '[""]' > "$PRODUCT_IDS_JSON"
   printf '[{"id":"","type":"preset"}]' > "$AVATARS_JSON"

   higgsfield generate create marketing_studio_video \
     --prompt "..." \
     --avatars @"$AVATARS_JSON" \
     --product_ids @"$PRODUCT_IDS_JSON" \
     --mode ugc \
     --duration 15 \
     --resolution 720p \
     --aspect_ratio 9:16 \
     --wait

Add --hook_id and/or --setting_id when a setup hook/setting was selected. product_ids and avatars are JSON arrays; pass them via @/path/to/file.json. Do not pass a bare UUID to --product_ids. Resolution is 480p, 720p, or 1080p. Aspect ratio is one of auto/21:9/16:9/4:3/1:1/3:4/9:16. `--generate