Character High-Fidelity Training

Train a custom model on a character’s reference photos for the highest-fidelity identity match in image generations. Available on the Cloud edition only.

How it works

1. Open a character in the Character Studio modal (click the character node).
2. Make sure the character has at least 4 reference photos — any mix of:
   • The approved portrait (source_image_url)
   • Reference photos (front face, sides, three-quarter, full body, etc.)
   • Expressions / poses / angles / lighting variations
3. In the Main tab, find the High-fidelity model section and click Train high-fidelity model.
4. Wait ~15 minutes. The character’s canvas card shows a Training… pill; you can navigate away. The Modal also shows the live status (polling every 8s).
5. Once trained, the character is marked Trained in:
   • The canvas card (green corner badge)
   • The character modal Main tab
   • (Coming soon) the @mention autocomplete and character gallery

What changes after training

When you @mention a single trained character in a generate-image node, the backend automatically routes that generation through the trained Flux LoRA on Replicate instead of the default nano-banana + reference-image injection.

• The trained model lives on the nodaroai/char-<characterId> Replicate model.
• Only Nodaro can submit inference requests to it (your API token).
• A unique trigger word (e.g. TOK_kira_a1b2c3) is prepended to every prompt automatically — you do NOT need to type it.

If your prompt mentions 2 or more trained characters, the system falls back to standard reference-image injection. Multi-character LoRA composition is on the roadmap (Phase 2).

Pricing

Action	Credits	Notes
Training	150 cr (~$3)	Refunded if Replicate reports failure or cancel.
Inference per image	2 cr	Applied when the trained model is used. The dropdown’s provider price (typically nano-banana, 1cr) is replaced.
Re-training	150 cr	Full re-training price every time.

Limits

• Min 4 / max 20 training photos per character (route enforces).
• Inference is generate-image only in Phase 1. Other consumer nodes (image-to-image, modify-image, video nodes) use the existing reference-injection path regardless of training state.
• Re-training replaces the previous model. The old version on Replicate is retained briefly so in-flight generations don’t break; ops can prune it later.
• Cancelling mid-training refunds your credits.

Lifecycle

• Re-train: allowed any time after a successful (or failed/cancelled) training.
• Remove: deletes the Replicate model and clears the LoRA fields on your character row. Generations fall back to reference-image injection.
• Delete the character: also cancels in-flight training, refunds the reservation, and deletes the trained Replicate model.

API reference

The training routes are documented in API Integration and the SDK in SDK Reference.

Deployment notes (self-hosted Cloud)

The webhook signature uses Replicate’s Standard Webhooks spec. Set REPLICATE_WEBHOOK_SECRET to the secret returned by replicate.webhooks.default.secret (see deployment.md) — without it, the webhook fast-fails 503 webhook_not_configured.

PUBLIC_URL must point to a publicly-reachable URL (e.g. https://app.nodaro.ai) so Replicate can deliver completion webhooks. The route fast-fails 503 public_url_not_configured otherwise.