Documentation Index
Fetch the complete documentation index at: /llms.txt
Use this file to discover all available pages before exploring further.
For AI agents: see the complete llms.txt documentation index.
Crea avatares privados a partir de una foto o de tu cámara web.
GET /api/v1/avatars/capability, POST /api/v1/avatars/uploads, POST /api/v1/avatars, GET /api/v1/avatars, GET /api/v1/avatars/{id}, DELETE /api/v1/avatars/{id}, GET /api/v1/avatars/catalog.
MCP: get_avatar_capability, create_avatar_upload, submit_avatar, list_avatars, get_avatar, delete_avatar, list_avatar_catalog.
famulor get-avatar-capability
famulor create-avatar-upload --name "My avatar" --style custom \
--content-type image/jpeg --size-bytes 123456
# Upload the photo to the returned upload_url before submitting.
famulor submit-avatar --id <prepared-id> --consent true --expected-credits <quoted-price>
famulor get-avatar <prepared-id>
famulor list-avatars
famulor list-avatar-catalog --style realistic
famulor delete-avatar <avatar-id>
import { Famulor } from "famulor-sdk";
import { readFile } from "node:fs/promises";
const photo = new Blob([new Uint8Array(await readFile("photo.jpg"))], { type: "image/jpeg" });
const client = new Famulor({ apiKey: process.env.FAMULOR_API_KEY! });
const quote = await client.avatars.capability();
const upload = await client.avatars.prepareUpload({
name: "My avatar", style: "custom",
content_type: "image/jpeg", size_bytes: photo.size,
});
const form = new FormData();
form.append("", photo, "photo.jpg");
form.append("cacheControl", "0");
const uploaded = await fetch(upload.data.upload_url, {
method: "PUT", headers: { "x-upsert": "false" }, body: form,
});
if (!uploaded.ok) throw new Error("Photo upload failed");
const avatar = await client.avatars.submit({
id: upload.data.id, consent: true,
expected_credits: quote.data.creation_credits,
});
const status = await client.avatars.get(avatar.data.id);