Flux 3 Action
整合
flux-3-action/so101
# 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/flux-3-action/so101?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"scene_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"wrist_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"state": [
-18.94,
134.52,
120.15,
28.3,
-32.17,
27.02
]
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/flux-3-action/so101?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"scene_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"wrist_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"state": [
-18.94,
134.52,
120.15,
28.3,
-32.17,
27.02
]
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"scene_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"wrist_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"state": [
-18.94,
134.52,
120.15,
28.3,
-32.17,
27.02,
],
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/flux-3-action/so101", 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/zh-TW/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": "flux-3-action/so101",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"scene_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"wrist_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"state": [
-18.94,
134.52,
120.15,
28.3,
-32.17,
27.02
]
}
}
透過 Doitong API 呼叫 Flux 3 Action 模型(flux-3-action/so101)。代理程式文件:https://doitong.com/zh-TW/developers/models/flux-3-action/so101.md
POST https://api.doitong.ru/v1/run/flux-3-action/so101?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"scene_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"wrist_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"state": [
-18.94,
134.52,
120.15,
28.3,
-32.17,
27.02
]
}
如果回應狀態為 "queued" 或 "running",請輪詢 GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20,直到狀態變為 "succeeded";檔案位於 outputs[].url。使用相同主體傳送 POST https://api.doitong.ru/v1/quote/flux-3-action/so101,可在執行前取得確切價格。
此請求: ≈$0.003 3 API 點數 · ≈ ₽0.32 在此頁面執行
您的新 API 金鑰。 僅會在此時顯示,且已填入下方的程式碼與 API 金鑰欄位。請妥善保密:切勿將其放入在瀏覽器中執行的程式碼。
在 Doitong 上製作
Doitong 社群使用 Flux 3 Action 製作的公開作品。一鍵重複使用提示詞。
Close-up portrait 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...
Close-up portrait 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...
Prompt Details 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...
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 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 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 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...
Foto sinematik hiper-realistis resolusi tinggi menampilkan seorang pria muda Indonesia dengan tubuh ramping dan proporsional, rambut hitam pendek agak acak, mengenakan jaket kulit hitam, celana riding fit, dan sepatu motor. Ia sedang melakukan aksi freestyle ekstrem dengan motor sport 500cc...
Foto sinematik hiper-realistis resolusi tinggi menampilkan seorang pria muda Indonesia dengan tubuh ramping dan proporsional, rambut hitam pendek agak acak, mengenakan jaket kulit hitam dan celana riding fit. Ia sedang bersiap melakukan freestyle menggunakan motor sport 500cc berwarna merah,...
建立請求
控制項是根據模型結構描述生成的。變更設定時,程式碼和價格會同步更新。
/run/flux-3-action/so101?wait=20
報價 → $0.003
# 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/flux-3-action/so101?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"scene_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"wrist_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"state": [
-18.94,
134.52,
120.15,
28.3,
-32.17,
27.02
]
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/flux-3-action/so101?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"scene_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"wrist_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"state": [
-18.94,
134.52,
120.15,
28.3,
-32.17,
27.02
]
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"scene_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"wrist_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"state": [
-18.94,
134.52,
120.15,
28.3,
-32.17,
27.02,
],
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/flux-3-action/so101", 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": "flux-3-action/so101",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"scene_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"wrist_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"state": [
-18.94,
134.52,
120.15,
28.3,
-32.17,
27.02
]
},
"wait_seconds": 20
}
}
}
關於 Flux 3 Action
此模型不返回媒體,而是返回包含預測 `actions`、控制頻率、欄位標籤,以及在請求新片段前要執行的前導步驟數(`execute_steps`)的 JSON。必要輸入包括文字 `prompt`(最多 2000 個字元)、`scene_image_url`、`wrist_image_url` 與 6 值 `state`。選用的歷史輸入(`state_history`、`command_history`、歷史圖像)可提供時間脈絡。`num_inference_steps` 範圍為 1 至 8,`guidance_scale` 範圍為 1 至 10。
參數
prompt必填
scene_image_url必填
wrist_image_url必填
state必填
state_history選填
command_history選填
history_scene_image_url選填
history_wrist_image_url選填
num_inference_steps選填
guidance_scale選填
seed選填
檔案參數接受公開的 https:// URL、最大 10 MB 的 data: URI,或上傳檔案的 file_url。 檔案
輸出
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "flux-3-action/so101",
"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": 3,
"usd": "0.003",
"charged": 3,
"refunded": 0
},
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"scene_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"wrist_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"state": [
-18.94,
134.52,
120.15,
28.3,
-32.17,
27.02
]
},
"output": {
"actions": [
[
1.0
]
],
"action_labels": [
"string"
],
"action_hz": 1.0,
"execute_steps": 1,
"seed": 42,
"timings": {}
},
"outputs": [
{
"type": "file",
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_size": 1843200,
"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"
}
}
輸出欄位
- actions
- array of array of number預測的動作陣列,各列依控制步驟的時間順序排列;值未截斷,因此必須在機器人上強制執行關節、速度與工作空間限制。在 30 Hz 下,SO-101 提供 42x6 個以度和夾爪百分比表示的絕對指令;在 15 Hz 下,DROID 提供 32x8 個以弧度表示的絕對關節目標,以及夾爪閉合比例。
- action_labels
- array of string對應於動作欄的名稱。
- action_hz
- number動作各列的控制頻率。
- execute_steps
- integer在再次請求下一批動作前要執行的初始動作數量。
- seed
- integer取樣期間使用的隨機種子。
- timings
- object伺服器的時間測量值,以秒表示。
更多模型:影片轉影片
給 AI 代理程式:此頁面的 Markdown 位於 https://doitong.com/zh-TW/developers/models/flux-3-action/so101.md. 所有模型與指南: https://doitong.com/developers/llms.txt