Elevenlabs
整合
模型 id
elevenlabs/text-to-dialogue/eleven-v3
# 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/elevenlabs/text-to-dialogue/eleven-v3?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"inputs": [
{
"text": "[applause] Thank you all for coming tonight! Today we have a very special guest with us.",
"voice": "Aria"
},
{
"text": "[gulps] ... [strong canadian accent] [excited] Hello everyone! Thank you all for having me tonight on this special day.",
"voice": "Charlotte"
}
]
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/elevenlabs/text-to-dialogue/eleven-v3?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"inputs": [
{
"text": "[applause] Thank you all for coming tonight! Today we have a very special guest with us.",
"voice": "Aria"
},
{
"text": "[gulps] ... [strong canadian accent] [excited] Hello everyone! Thank you all for having me tonight on this special day.",
"voice": "Charlotte"
}
]
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"inputs": [
{
"text": "[applause] Thank you all for coming tonight! Today we have a very special guest with us.",
"voice": "Aria",
},
{
"text": "[gulps] ... [strong canadian accent] [excited] Hello everyone! Thank you all for having me tonight on this special day.",
"voice": "Charlotte",
},
],
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/elevenlabs/text-to-dialogue/eleven-v3", 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": "elevenlabs/text-to-dialogue/eleven-v3",
"input": {
"inputs": [
{
"text": "[applause] Thank you all for coming tonight! Today we have a very special guest with us.",
"voice": "Aria"
},
{
"text": "[gulps] ... [strong canadian accent] [excited] Hello everyone! Thank you all for having me tonight on this special day.",
"voice": "Charlotte"
}
]
}
}
透過 Doitong API 呼叫 Elevenlabs 模型(elevenlabs/text-to-dialogue/eleven-v3)。代理程式文件:https://doitong.com/zh-TW/developers/models/elevenlabs/text-to-dialogue/eleven-v3.md
POST https://api.doitong.ru/v1/run/elevenlabs/text-to-dialogue/eleven-v3?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"inputs": [
{
"text": "[applause] Thank you all for coming tonight! Today we have a very special guest with us.",
"voice": "Aria"
},
{
"text": "[gulps] ... [strong canadian accent] [excited] Hello everyone! Thank you all for having me tonight on this special day.",
"voice": "Charlotte"
}
]
}
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/elevenlabs/text-to-dialogue/eleven-v3,可在執行前取得確切價格。
此請求: ≈$0.10 100 API 點數 · ≈ ₽10.75 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。
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。
POST
/run/elevenlabs/text-to-dialogue/eleven-v3?wait=20
報價 → $0.10
# 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/elevenlabs/text-to-dialogue/eleven-v3?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"inputs": [
{
"text": "[applause] Thank you all for coming tonight! Today we have a very special guest with us.",
"voice": "Aria"
},
{
"text": "[gulps] ... [strong canadian accent] [excited] Hello everyone! Thank you all for having me tonight on this special day.",
"voice": "Charlotte"
}
]
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/elevenlabs/text-to-dialogue/eleven-v3?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"inputs": [
{
"text": "[applause] Thank you all for coming tonight! Today we have a very special guest with us.",
"voice": "Aria"
},
{
"text": "[gulps] ... [strong canadian accent] [excited] Hello everyone! Thank you all for having me tonight on this special day.",
"voice": "Charlotte"
}
]
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"inputs": [
{
"text": "[applause] Thank you all for coming tonight! Today we have a very special guest with us.",
"voice": "Aria",
},
{
"text": "[gulps] ... [strong canadian accent] [excited] Hello everyone! Thank you all for having me tonight on this special day.",
"voice": "Charlotte",
},
],
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/elevenlabs/text-to-dialogue/eleven-v3", 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": "elevenlabs/text-to-dialogue/eleven-v3",
"input": {
"inputs": [
{
"text": "[applause] Thank you all for coming tonight! Today we have a very special guest with us.",
"voice": "Aria"
},
{
"text": "[gulps] ... [strong canadian accent] [excited] Hello everyone! Thank you all for having me tonight on this special day.",
"voice": "Charlotte"
}
]
},
"wait_seconds": 20
}
}
}
關於 Elevenlabs
根據必要的 `inputs` 建立對話;每個項目都將文字與 voice ID 配對。可使用 `stability`(0 到 1)和 `use_speaker_boost` 調整語音行為。可透過 `language_code` 指定語言,並套用最多 3 個發音字典定位器。接受 `seed` 以確保可重現,並與音訊一同回傳。
參數
名稱類型
預設值允許值
說明
inputs必填
類型object[]
要合成為語音的對話項目,每項包含文字與語音 ID。
inputs[].text必填
類型string
包含對話內容的文字。
inputs[].voice必填
類型string
選用於生成的語音名稱或 ID。
stability選填
類型number | null
0 – 1
各次生成間的語音穩定度與變化,僅限 0.0、0.5 或 1.0;超出此集合的輸入會四捨五入至最接近的可接受值。較高的設定可能限制情感並使聲音單調,較低的設定則會擴大語音的情感範圍。
use_speaker_boost選填
類型boolean | null
說話者相似度增強功能,因計算負載略增而增加延遲。啟用後,語音會更接近原始說話者。
pronunciation_dictionary_locators選填
類型object[]
預設值[]
依其影響文字的順序,最多提供 3 個發音字典定位器。每個定位器會依 id 和 version_id 識別一個字典。
pronunciation_dictionary_locators[].pronunciation_dictionary_id選填
類型string | null
發音字典的識別碼。
pronunciation_dictionary_locators[].version_id選填
類型string | null
依 ID 選取特定的發音字典版本,或留空以使用最新版本。
seed選填
類型integer | null
控制隨機性以產生可重現結果的種子。
language_code選填
類型string | null
使用 ISO 639-1 代碼指定必要的模型語言;除非模型支援該代碼,否則請求會失敗並回傳錯誤。
必填
輸出
GET /requests/req_8k2m4q7x1z9c3v5b6n0p2r4t
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "elevenlabs/text-to-dialogue/eleven-v3",
"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": 100,
"usd": "0.10",
"charged": 100,
"refunded": 0
},
"input": {
"inputs": [
{
"text": "[applause] Thank you all for coming tonight! Today we have a very special guest with us.",
"voice": "Aria"
},
{
"text": "[gulps] ... [strong canadian accent] [excited] Hello everyone! Thank you all for having me tonight on this special day.",
"voice": "Charlotte"
}
]
},
"output": {
"audio": {
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp3",
"content_type": "audio/mpeg",
"file_name": "0-output.mp3",
"file_size": 1843200
},
"seed": 42
},
"outputs": [
{
"type": "audio",
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp3",
"content_type": "audio/mpeg",
"file_size": 1843200,
"duration": 12,
"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"
}
}
您的檔案,由您選擇每個 outputs[].url 都是儲存空間中的副本:可永久保留(按 GB-月計費),或免費保留 7 天;可透過帳戶設定或 ?storage= 設定。
所有模型使用相同結構圖片、影片和音訊皆包含 type、url、content_type、width、height 和 duration。output 是模型自己的結果物件。
輸出欄位
- audio
- object {url, content_type, file_name, file_size}生成產生的音訊檔案。
- seed
- integer控制隨機性以產生可重現結果的種子。
更多模型:文字轉語音
給 AI 代理程式:此頁面的 Markdown 位於 https://doitong.com/zh-TW/developers/models/elevenlabs/text-to-dialogue/eleven-v3.md. 所有模型與指南: https://doitong.com/developers/llms.txt