# higgsfield-soul-id

> Train a personalized identity model on a person's face for use in Higgsfield's image and video generation.

- Skill: `higgsfield-ai/higgsfield-soul-id` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds add higgsfield-ai/higgsfield-soul-id`
- Raw SKILL.md: https://api.skillmd.com/api/skills/higgsfield-ai/higgsfield-soul-id/raw
- Safety review: CAUTION (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML, Image & Video Generation
- Tags: Avatar, Digital Twin, Face Training, Higgsfield, Identity Model, Image Generation, Soul Id, Video Generation
- Author: Higgsfield AI (https://skillmd.com/u/higgsfield-ai)
- Updated: 2026-07-06
- Page: https://skillmd.com/skills/higgsfield-ai/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:
   ```bash
   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.**
   ```bash
   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`:

```bash
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

```bash
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