higgsfield-soul-id

We need to translate the given English text into Bahasa Indonesia. The text describes a skill for training a Soul Character. We must preserve the name 'higgsfield-soul-id' if it appears, but it does not appear in the text. The text includes technical terms like 'Soul Character', 'Higgsfield', 'reference_id', 'higgsfield-generate', '--soul-id', 'text2image_soul_v2'. These should be preserved as is. Also preserve numbers, URLs (none), and technical terms. Do not add any extra commentary or labels. Just translate the descriptive text. The text: "Train a Soul Character — a personalized model on a person's face that Higgsfield uses for identity-faithful image and video generation. Use when: "create my Soul", "train my face", "make my digital twin", "build me an avatar", "learn my appearance", "create a character of me", "set up identity for video", "I want my face in generated images". Chain: train Soul (one-time, returns reference_id

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

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

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 expiredhiggsfield auth login.

Reference docs

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

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