Aqbeż għall-kontenut

FLUX 3 Max Text to Video

Integra

Id tal-mudell blackforestlabs/flux-3-max/text-to-video

# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.ru/v1/run/blackforestlabs/flux-3-max/text-to-video?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Four-way CCTV-style split-screen showing the same real-time event inside a convenience shop. Divide the frame into four equal security-camera views with timestamps. Top left: wide ceiling-corner view covering aisles, entrance, and cashier. Top right: overhead view above the central aisle. Bottom left: camera facing the checkout counter. Bottom right: camera near the entrance looking inward. At the 2-second mark, a customer takes a boxed item from a shelf, accidentally bumps a display, catches one falling bottle, then places the box on the checkout counter. The cashier turns, scans it, and hands over a receipt as another shopper crosses behind them. All four views must remain perfectly synchronized, showing identical people, movements, object positions, occlusions, timestamps, lighting, and physical reactions. Use realistic low-resolution CCTV footage, slight lens distortion, fixed cameras, and no cinematic camera movement.",
    "duration": 5,
    "resolution": "720p",
    "aspect_ratio": "16:9",
    "generate_audio": false
  }'

# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"

const API = "https://api.doitong.ru/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/blackforestlabs/flux-3-max/text-to-video?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "prompt": "Four-way CCTV-style split-screen showing the same real-time event inside a convenience shop. Divide the frame into four equal security-camera views with timestamps. Top left: wide ceiling-corner view covering aisles, entrance, and cashier. Top right: overhead view above the central aisle. Bottom left: camera facing the checkout counter. Bottom right: camera near the entrance looking inward. At the 2-second mark, a customer takes a boxed item from a shelf, accidentally bumps a display, catches one falling bottle, then places the box on the checkout counter. The cashier turns, scans it, and hands over a receipt as another shopper crosses behind them. All four views must remain perfectly synchronized, showing identical people, movements, object positions, occlusions, timestamps, lighting, and physical reactions. Use realistic low-resolution CCTV footage, slight lens distortion, fixed cameras, and no cinematic camera movement.",
    "duration": 5,
    "resolution": "720p",
    "aspect_ratio": "16:9",
    "generate_audio": false
  }),
});
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.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}

payload = {
    "prompt": "Four-way CCTV-style split-screen showing the same real-time event inside a convenience shop. Divide the frame into four equal security-camera views with timestamps. Top left: wide ceiling-corner view covering aisles, entrance, and cashier. Top right: overhead view above the central aisle. Bottom left: camera facing the checkout counter. Bottom right: camera near the entrance looking inward. At the 2-second mark, a customer takes a boxed item from a shelf, accidentally bumps a display, catches one falling bottle, then places the box on the checkout counter. The cashier turns, scans it, and hands over a receipt as another shopper crosses behind them. All four views must remain perfectly synchronized, showing identical people, movements, object positions, occlusions, timestamps, lighting, and physical reactions. Use realistic low-resolution CCTV footage, slight lens distortion, fixed cameras, and no cinematic camera movement.",
    "duration": 5,
    "resolution": "720p",
    "aspect_ratio": "16:9",
    "generate_audio": False,
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/blackforestlabs/flux-3-max/text-to-video", 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/mt/developers/docs/mcp)
claude mcp add --transport http doitong-models https://api.doitong.ru/v1/mcp \
  --header "Authorization: Bearer $DOITONG_API_KEY"

# 2. Your agent calls the "run" tool with:
{
  "model_id": "blackforestlabs/flux-3-max/text-to-video",
  "input": {
    "prompt": "Four-way CCTV-style split-screen showing the same real-time event inside a convenience shop. Divide the frame into four equal security-camera views with timestamps. Top left: wide ceiling-corner view covering aisles, entrance, and cashier. Top right: overhead view above the central aisle. Bottom left: camera facing the checkout counter. Bottom right: camera near the entrance looking inward. At the 2-second mark, a customer takes a boxed item from a shelf, accidentally bumps a display, catches one falling bottle, then places the box on the checkout counter. The cashier turns, scans it, and hands over a receipt as another shopper crosses behind them. All four views must remain perfectly synchronized, showing identical people, movements, object positions, occlusions, timestamps, lighting, and physical reactions. Use realistic low-resolution CCTV footage, slight lens distortion, fixed cameras, and no cinematic camera movement.",
    "duration": 5,
    "resolution": "720p",
    "aspect_ratio": "16:9",
    "generate_audio": false
  }
}

Ċempel il-mudell FLUX 3 Max Text to Video (blackforestlabs/flux-3-max/text-to-video) permezz tad-Doitong API. Dokumentazzjoni għall-aġenti: https://doitong.com/mt/developers/models/blackforestlabs/flux-3-max/text-to-video.md

POST https://api.doitong.ru/v1/run/blackforestlabs/flux-3-max/text-to-video?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json

{
  "prompt": "Four-way CCTV-style split-screen showing the same real-time event inside a convenience shop. Divide the frame into four equal security-camera views with timestamps. Top left: wide ceiling-corner view covering aisles, entrance, and cashier. Top right: overhead view above the central aisle. Bottom left: camera facing the checkout counter. Bottom right: camera near the entrance looking inward. At the 2-second mark, a customer takes a boxed item from a shelf, accidentally bumps a display, catches one falling bottle, then places the box on the checkout counter. The cashier turns, scans it, and hands over a receipt as another shopper crosses behind them. All four views must remain perfectly synchronized, showing identical people, movements, object positions, occlusions, timestamps, lighting, and physical reactions. Use realistic low-resolution CCTV footage, slight lens distortion, fixed cameras, and no cinematic camera movement.",
  "duration": 5,
  "resolution": "720p",
  "aspect_ratio": "16:9",
  "generate_audio": false
}

Jekk l-istatus tar-rispons huwa "queued" jew "running", agħmel polling fuq GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 sakemm ikun "succeeded"; il-fajls jinsabu f’outputs[].url. POST https://api.doitong.ru/v1/quote/blackforestlabs/flux-3-max/text-to-video bl-istess body jirritorna l-prezz eżatt qabel it-tħaddim.

Fajls bħall-eżempju: $0.213 213 krediti tal-API · ≈ ₽22.86 il-fajls tiegħek jitkejlu qabel it-tħaddim Ħaddmu f’din il-paġna

Ikseb ċavetta API

Black Forest Labs Test għal vidjo Awdjo nattiv5–20 ssa 1080p #audio#long-clips#1080p

Il-mudell tal-vidjo ta’ Black Forest Labs, klipps ta’ 5 sa 20 sekonda bil-ħoss f’720p jew 1080p.

OpenAPI Markdown

Eżempji

Output · ~30 s

PromptFour-way CCTV-style split-screen showing the same real-time event inside a convenience shop. Divide the frame into four equal security-camera views with timestamps. Top left: wide ceiling-corner view covering aisles, entrance, and cashier. Top right: overhead view above the central aisle. Bottom left: camera facing the checkout counter. Bottom right: camera near the entrance looking inward. At the 2-second mark, a customer takes a boxed item from a shelf, accidentally bumps a display, catches one falling bottle, then places the box on the checkout counter. The cashier turns, scans it, and hands over a receipt as another shopper crosses behind them. All four views must remain perfectly synchronized, showing identical people, movements, object positions, occlusions, timestamps, lighting, and physical reactions. Use realistic low-resolution CCTV footage, slight lens distortion, fixed cameras, and no cinematic camera movement.

5 s720p16:9generate_audio: false$0.213 · 213 krediti tal-API

Prompt minn @umesh_ai fuq X

Prezz għal kull sekonda tal-vidjo tal-output tiegħek

Prezz ibbażat fuq l-input tiegħek

minn $0.0425 / sekonda ta’ vidjo tal-output

42.5 krediti tal-API / sekonda ta’ vidjo tal-output · ≈ ₽4.56

Din it-talba: 5 sekondi × $0.0425 (720p) $0.213 213 krediti tal-API · ≈ ₽22.86

Ħaddem · $0.213

Iċċarġjat biss jekk jirnexxi, u rimborżat awtomatikament jekk ifalli.

duration 5 s

resolution

Prezz skont il-livell

720p	$0.0425 / sekonda ta’ vidjo tal-output
1080p	$0.0725 / sekonda ta’ vidjo tal-output

It-titlu juri l-inqas livell; il-kwotazzjoni tikkalkula l-prezz tal-input eżatt tiegħek.

Il-fajls tiegħek jitkejlu qabel it-tħaddim (tul, riżoluzzjoni, rata tal-frejms); il-kwotazzjoni tirritorna l-prezz eżatt u t-tħaddim jiċċarġja eżattament dak.

Ħin tipiku: ~30 s
Endpoint tal-kwotazzjoni: POST /quote/{id}

Ibni talba

Il-kontrolli jiġu ġġenerati mill-iskema tal-mudell. Il-kodiċi u l-prezz jaġġornaw hekk kif tibdilhom.

prompt •meħtieġ

Deskrizzjoni testwali tal-vidjo mixtieq.

duration 5 s

Tul tal-vidjo output, imkejjel f’sekondi.

resolution

Riżoluzzjoni tal-vidjo output.

aspect_ratio

Proporzjon tal-aspett tal-vidjo ġġenerat, fejn `auto` jaqbel mal-ewwel immaġni sakemm l-input ma jkunx prompt testwali; f’dak il-każ jagħżel 16:9.

Avvanzat reasoning_level · seed

reasoning_level prestabbilit high

L-isforz ta’ raġunament jikkontrolla l-kompromess bejn il-veloċità tal-ġenerazzjoni u x-xogħol li l-harness jiddedika biex jifhem il-prompt: aktar sforz jieħu aktar ħin.

seed

Żerriegħa tal-ġenerazzjoni; jintuża valur każwali jekk titħalla barra.

POST /run/blackforestlabs/flux-3-max/text-to-video?wait=20 kwotazzjoni → $0.213

# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.ru/v1/run/blackforestlabs/flux-3-max/text-to-video?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Four-way CCTV-style split-screen showing the same real-time event inside a convenience shop. Divide the frame into four equal security-camera views with timestamps. Top left: wide ceiling-corner view covering aisles, entrance, and cashier. Top right: overhead view above the central aisle. Bottom left: camera facing the checkout counter. Bottom right: camera near the entrance looking inward. At the 2-second mark, a customer takes a boxed item from a shelf, accidentally bumps a display, catches one falling bottle, then places the box on the checkout counter. The cashier turns, scans it, and hands over a receipt as another shopper crosses behind them. All four views must remain perfectly synchronized, showing identical people, movements, object positions, occlusions, timestamps, lighting, and physical reactions. Use realistic low-resolution CCTV footage, slight lens distortion, fixed cameras, and no cinematic camera movement.",
    "duration": 5,
    "resolution": "720p",
    "aspect_ratio": "16:9",
    "generate_audio": false
  }'

# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"

const API = "https://api.doitong.ru/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/blackforestlabs/flux-3-max/text-to-video?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "prompt": "Four-way CCTV-style split-screen showing the same real-time event inside a convenience shop. Divide the frame into four equal security-camera views with timestamps. Top left: wide ceiling-corner view covering aisles, entrance, and cashier. Top right: overhead view above the central aisle. Bottom left: camera facing the checkout counter. Bottom right: camera near the entrance looking inward. At the 2-second mark, a customer takes a boxed item from a shelf, accidentally bumps a display, catches one falling bottle, then places the box on the checkout counter. The cashier turns, scans it, and hands over a receipt as another shopper crosses behind them. All four views must remain perfectly synchronized, showing identical people, movements, object positions, occlusions, timestamps, lighting, and physical reactions. Use realistic low-resolution CCTV footage, slight lens distortion, fixed cameras, and no cinematic camera movement.",
    "duration": 5,
    "resolution": "720p",
    "aspect_ratio": "16:9",
    "generate_audio": false
  }),
});
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.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}

payload = {
    "prompt": "Four-way CCTV-style split-screen showing the same real-time event inside a convenience shop. Divide the frame into four equal security-camera views with timestamps. Top left: wide ceiling-corner view covering aisles, entrance, and cashier. Top right: overhead view above the central aisle. Bottom left: camera facing the checkout counter. Bottom right: camera near the entrance looking inward. At the 2-second mark, a customer takes a boxed item from a shelf, accidentally bumps a display, catches one falling bottle, then places the box on the checkout counter. The cashier turns, scans it, and hands over a receipt as another shopper crosses behind them. All four views must remain perfectly synchronized, showing identical people, movements, object positions, occlusions, timestamps, lighting, and physical reactions. Use realistic low-resolution CCTV footage, slight lens distortion, fixed cameras, and no cinematic camera movement.",
    "duration": 5,
    "resolution": "720p",
    "aspect_ratio": "16:9",
    "generate_audio": False,
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/blackforestlabs/flux-3-max/text-to-video", 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": "blackforestlabs/flux-3-max/text-to-video",
      "input": {
        "prompt": "Four-way CCTV-style split-screen showing the same real-time event inside a convenience shop. Divide the frame into four equal security-camera views with timestamps. Top left: wide ceiling-corner view covering aisles, entrance, and cashier. Top right: overhead view above the central aisle. Bottom left: camera facing the checkout counter. Bottom right: camera near the entrance looking inward. At the 2-second mark, a customer takes a boxed item from a shelf, accidentally bumps a display, catches one falling bottle, then places the box on the checkout counter. The cashier turns, scans it, and hands over a receipt as another shopper crosses behind them. All four views must remain perfectly synchronized, showing identical people, movements, object positions, occlusions, timestamps, lighting, and physical reactions. Use realistic low-resolution CCTV footage, slight lens distortion, fixed cameras, and no cinematic camera movement.",
        "duration": 5,
        "resolution": "720p",
        "aspect_ratio": "16:9",
        "generate_audio": false
      },
      "wait_seconds": 20
    }
  }
}

Ħaddem din it-talba

Ċavetta API

Iċ-ċavetta tiegħek tibqa’ f’dan il-browser: tintbagħat biss lid-Doitong API u tiġi ssejvjata (localStorage) biss jekk timmarka Ftakar. Ftakar f’dan il-browser Ikseb ċavetta API

Magħmul fuq Doitong

Xogħlijiet pubbliċi magħmula b’FLUX 3 Max mill-komunità ta’ Doitong. Uża prompt mill-ġdid bi klikk waħda.

Xogħlijiet pubbliċi murija: 9

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Seorang wanita berkulit pucat berdiri setengah tubuh di dalam air berwarna lembut kebiruan, dikel... — Seorang wanita berkulit pucat berdiri setengah tubuh di dalam air berwarna lembut kebiruan, dikelilingi bunga teratai berkelopak penuh yang bermekaran indah di permukaan air. Rambutnya pirang pucat tersanggul longgar dengan beberapa helaian tipis jatuh alami membingkai sisi wajahnya. Ia memeluk...

"Potret sinematik ultra-realistis close-up seorang anak laki-laki kecil (balita) yang sangat men... — "Potret sinematik ultra-realistis close-up seorang anak laki-laki kecil (balita) yang sangat menggemaskan dengan mata cokelat besar yang ekspresif, rambut hitam berantakan yang tebal, mengenakan kaus putih kerah henley. Dia berpose dengan kedua tangan terkatup di depan dada, menunjukkan senyum...

"Potret sinematik ultra-realistis close-up seorang anak laki-laki kecil (balita) yang sangat men... — "Potret sinematik ultra-realistis close-up seorang anak laki-laki kecil (balita) yang sangat menggemaskan dengan mata cokelat besar yang ekspresif, rambut hitam berantakan yang tebal, mengenakan kaus putih kerah henley. Dia berpose dengan kedua tangan terkatup di depan dada, menunjukkan senyum...

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Dwar FLUX 3 Max Text to Video

FLUX 3 Max iġib id-dehra ta’ FLUX għall-vidjo: frejms dettaljati u mdawlin sew, moviment naturali u awdjo ġġenerat. Jirraġuna dwar il-prompt qabel jirrendi (sforz għoli jew baxx), jappoġġja klipps minn 5 sa 20 sekonda u tmien proporzjonijiet tal-aspett minn 9:16 sa 21:9, f’720p jew 1080p. Seed jagħmel l-eżekuzzjonijiet ripetibbli.

Parametri

IsemTip PrestabbilitPermess Deskrizzjoni

promptmeħtieġ

Tipstring

Deskrizzjoni testwali tal-vidjo mixtieq.

durationmhux obbligatorju

Tipenum

Prestabbilit5

567891011121314151617181920

Tul tal-vidjo output, imkejjel f’sekondi.

resolutionmhux obbligatorju

Tipenum

Prestabbilit720p

720p1080p

Riżoluzzjoni tal-vidjo output.

reasoning_levelmhux obbligatorju

Tipenum

Prestabbilithigh

lowhigh

L-isforz ta’ raġunament jikkontrolla l-kompromess bejn il-veloċità tal-ġenerazzjoni u x-xogħol li l-harness jiddedika biex jifhem il-prompt: aktar sforz jieħu aktar ħin.

aspect_ratiomhux obbligatorju

Tipenum

Prestabbilitauto

auto21:92:116:94:31:13:49:16

Proporzjon tal-aspett tal-vidjo ġġenerat, fejn `auto` jaqbel mal-ewwel immaġni sakemm l-input ma jkunx prompt testwali; f’dak il-każ jagħżel 16:9.

generate_audiomhux obbligatorju

Tipboolean

Prestabbilittrue

Jikkontrolla jekk il-vidjo jinkludix awdjo ġġenerat.

seedmhux obbligatorju

Tipinteger | null

Żerriegħa tal-ġenerazzjoni; jintuża valur każwali jekk titħalla barra.

meħtieġ

Output

GET /requests/req_8k2m4q7x1z9c3v5b6n0p2r4t

{
  "id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
  "object": "request",
  "model": "blackforestlabs/flux-3-max/text-to-video",
  "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": 213,
    "usd": "0.213",
    "charged": 213,
    "refunded": 0
  },
  "input": {
    "prompt": "A red panda walks along a mossy log in a sunlit forest, pauses to sniff the air, then climbs over a branch",
    "duration": 5,
    "resolution": "720p"
  },
  "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,
      "width": 1024,
      "height": 768,
      "fps": 1.0,
      "duration": 5,
      "num_frames": 1
    },
    "seed": 42,
    "timings": {}
  },
  "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.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}

Il-fajls tiegħek, l-għażla tiegħekKull outputs[].url huwa kopja fil-ħażna tagħna: miżmuma għal dejjem (imħallsa għal kull GB-xahar) jew 7 ijiem b’xejn, skont l-issettjar tal-kont tiegħek jew ?storage=.

L-istess struttura fuq kull mudelltype, url, content_type, width, height u duration, kemm għall-immaġnijiet kif ukoll għall-vidjo u l-awdjo. output huwa l-oġġett tar-riżultat tal-mudell innifsu.

Oqsma tal-output

video: object {url, content_type, file_name, file_size, width, height, fps, duration, num_frames}Vidjo prodott mill-mudell.
seed: integerValur taż-żerriegħa użat waqt il-ġenerazzjoni.
timings: objectDejta tal-ħin bl-estensjoni tal-prompt, id-dekodifikazzjoni u t-tlugħ esklużi minn `inference`, li jkejjel biss it-tneħħija tal-istorbju tal-vidjo mill-mudell f’sekondi.

Aktar mudelli: Test għal vidjo

Għall-aġenti tal-AI: din il-paġna bħala Markdown tinsab fuq https://doitong.com/mt/developers/models/blackforestlabs/flux-3-max/text-to-video.md. Il-mudelli u l-gwidi kollha: https://doitong.com/developers/llms.txt