AI Avatar Multi Text
Integriruj
ai-avatar/multi-text
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/ai-avatar/multi-text?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"image": "https://content.doitong.com/images/showcase/v3/avatar/talking_avatar.jpg",
"first_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"second_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/ai-avatar/multi-text?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"image": "https://content.doitong.com/images/showcase/v3/avatar/talking_avatar.jpg",
"first_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"second_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"image": "https://content.doitong.com/images/showcase/v3/avatar/talking_avatar.jpg",
"first_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"second_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/ai-avatar/multi-text", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])
# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
# 1. Connect once (Claude Code; Cursor, VS Code, Claude Desktop: https://doitong.com/rom/developers/docs/mcp)
claude mcp add --transport http doitong-models https://api.doitong.com/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"model_id": "ai-avatar/multi-text",
"input": {
"image": "https://content.doitong.com/images/showcase/v3/avatar/talking_avatar.jpg",
"first_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"second_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
}
Kall o AI Avatar Multi Text modelo (ai-avatar/multi-text) vas o Doitong API. Dokumentacia vaš agentura: https://doitong.com/rom/developers/models/ai-avatar/multi-text.md
POST https://api.doitong.com/v1/run/ai-avatar/multi-text?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"image": "https://content.doitong.com/images/showcase/v3/avatar/talking_avatar.jpg",
"first_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"second_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
Te o response status si "queued" vaj "running", ker polling GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20 dži kaj te avel "succeeded"; e fajlo si andro outputs[].url. POST https://api.doitong.com/v1/quote/ai-avatar/multi-text sa jekhe body-esa del o precizno molipen angl-o phiripen.
Kava mangipen: ≈$0.648 648 API krediti Phir les kate
Tiro nevo API klidin. Dikhavel pes akana numa thaj si angleder ando kodo thaj ando API klidin kotor tele. Garav les: na thovel les ande kodo savo keren andre jekh browser.
Tiro prvo rezultato si kate
Ker tele jekh mangipen thaj phir les tire API klidinosa. E rezultatur si kopirime amare arakhipneste, vično vaj 7 dives bilačhes.
Ker jekh mangipen
O kontrolura kerde si katar e schemaske. O kodo thaj e cena menjinen sar tu len menjines.
/run/ai-avatar/multi-text?wait=20
hesab → $0.648
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/ai-avatar/multi-text?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"image": "https://content.doitong.com/images/showcase/v3/avatar/talking_avatar.jpg",
"first_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"second_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/ai-avatar/multi-text?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"image": "https://content.doitong.com/images/showcase/v3/avatar/talking_avatar.jpg",
"first_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"second_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"image": "https://content.doitong.com/images/showcase/v3/avatar/talking_avatar.jpg",
"first_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"second_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/ai-avatar/multi-text", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])
# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "run",
"arguments": {
"model_id": "ai-avatar/multi-text",
"input": {
"image": "https://content.doitong.com/images/showcase/v3/avatar/talking_avatar.jpg",
"first_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"second_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"wait_seconds": 20
}
}
}
Phandel kava mangipen
Tiro kluč ačhel kadale browsereste: bičhalel pes numa ko Doitong API thaj šuvav pes (localStorage) numa te tiknes Remember. Le jekh API ključ
Palal AI Avatar Multi Text
Animil jekh kipo andro vakeripe maškar duj manuša. Dena `first_text_input` thaj `second_text_input` sar e vakerdeja, jekhe `prompt`-esa, thaj rakh `voice1` thaj `voice2` andar e preset voice. Rezultato si 480p vaj 720p, `num_frames`-esa 41 dži 241. Si dostupno `acceleration` none, regular vaj high.
Parametra
Bičhalav vaj e kanonikano nav vaj e native nav, na duj. Kanonikane nava
image_urltrubul
image
first_text_inputtrubul
second_text_inputtrubul
voice1opcionalno
+4 aver
BrianDanielLilyBillvoice2opcionalno
+4 aver
BrianDanielLilyBillprompttrubul
num_framesopcionalno
resolutionopcionalno
seedopcionalno
accelerationopcionalno
enable_safety_checkeropcionalno
Fajloske parametra lel jekh publikano https:// URL, jekh data: URI dži 10 MB, vaj e file_url uploadoski. Fajlura
Rezultato
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "ai-avatar/multi-text",
"status": "succeeded",
"created_at": "2026-10-20T12:00:00Z",
"started_at": "2026-10-20T12:00:02Z",
"completed_at": "2026-10-20T12:00:09Z",
"queue_position": null,
"cost": {
"credits": 648,
"usd": "0.648",
"charged": 648,
"refunded": 0
},
"input": {
"image_url": "https://content.doitong.com/images/showcase/v3/avatar/talking_avatar.jpg",
"first_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"second_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"output": {
"video": {
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
"content_type": "video/mp4",
"file_name": "0-output.mp4",
"file_size": 1843200
},
"seed": 42
},
"outputs": [
{
"type": "video",
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
"content_type": "video/mp4",
"file_size": 1843200,
"width": 1280,
"height": 720,
"duration": 5,
"stored": true
}
],
"error": null,
"metrics": {
"inference_seconds": 6.8
},
"urls": {
"self": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
Outputoske fieldura
- video
- object {url, content_type, file_name, file_size}Video-fajlo kerdino generiripeça.
- seed
- integerSeed-valoro aplikovano ko generiripe.
Aver variantura e AI Avatar
Bute modeli: Lipsync thaj Avatarura
AI agentenge: kadija rig sar Markdown si kate https://doitong.com/rom/developers/models/ai-avatar/multi-text.md. Sa e modelura thaj e gidura: https://doitong.com/developers/llms.txt