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higgsfield-soul-id

higgsfield-soul-id

github.com/higgsfield-aiCreative & media1.8k198.7k installsUpdated 1d ago
Repository

About higgsfield-soul-id

higgsfield-soul-id is a workflow skill for creating reusable face-faithful identity models with the Higgsfield CLI. It guides photo submission, variant selection, training, and use of the resulting Soul reference.

Key features

  1. 01Create a Soul identity from photos
  2. 02Choose image or cinematic variant
  3. 03Wait for training completion
  4. 04List and retrieve existing Souls
  5. 05Use Soul references in generation

Use cases

  1. 01Prepare a reusable identity for image generation
  2. 02Create an identity for cinematic or video work
  3. 03Review existing Soul references

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/higgsfield-ai/skills --skill higgsfield-soul-id

After installing, type/higgsfield-soul-idin Claude Code to confirm it loaded.

Bundled filesreferences/photo-guide.mdreferences/troubleshooting.md

Details

From the project README

Higgsfield Soul Character

Train a face-faithful identity model. Reusable across all Soul-powered generations.

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
  2. If higgsfield account status fails with Session expired / Not authenticated, ask the user to run higgsfield auth login (interactive) and wait for confirmation.
  3. Soul training requires a paid plan (Basic+). If higgsfield account status shows free plan, tell the user before submitting.

UX Rules

  1. Be concise. No raw IDs in chat. Just say "Soul ready" with a name reference.
  2. Detect language and respond in it. CLI flags stay English.
  3. Ask for the smallest set of inputs: name + photos. Pick a sensible model variant.
  4. Polling is silent — training takes minutes. Don't repeat status updates.

Workflow

  1. Get name. One word, used for later reference. Ask if missing.
  2. Get photos. 5–20 face photos, varied angles and lighting. Local paths or already-uploaded IDs both work — --image accepts either.
  3. Pick variant.
    • --soul-2 — for image generation (default)
    • --soul-cinematic — for cinematic / video work Choose based on user's stated downstream use. Default to --soul-2.
  4. Submit. 
    higgsfield soul-id create --name "<name>" --soul-2 --image ./photo1.png --image ./photo2.png ...
higgsfield soul-id create --name "<name>" --soul-2 --image <upload_id> --image <upload_id> ...
    CLI auto-uploads paths. Captures returned reference id.
  5. Wait. higgsfield soul-id wait <id>. Silent. Default timeout 30m.
  6. Deliver. "Soul <name> ready. Use in generate with --soul-id <id>."

Use the Soul

Once trained, pass to higgsfield-generate:

higgsfield generate create text2image_soul_v2 --prompt "..." --soul-id <ref_id> --quality 2k --wait
higgsfield generate create soul_cinematic --prompt "..." --soul-id <ref_id> --quality 2k --wait

--soul-id is sent as the model's custom_reference_id. For a curated Soul style, list styles with higgsfield preset list soul-v2 and pass the chosen id as --style_id on text2image_soul_v2. --style_id cannot be combined with --image.

Listing existing Souls

higgsfield soul-id list                   # all references
higgsfield soul-id get <id>               # one by id

Errors

  • Minimum Basic plan required — user is on free plan; tell them.
  • Training failed — check photos quality (5+ unique faces, well-lit).
  • Session expired → higgsfield auth login.

Reference docs

  • references/photo-guide.md — what photos work best
  • references/troubleshooting.md — common training failures

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