API Documentation
Integrate powerful translation into your applications with our simple REST API.
Getting Started
The TranslateAPI provides a simple REST interface for translating text between 180+ languages. All API endpoints return JSON responses.
1. Get Your API Key
Create a free account and generate your API key from the dashboard:
- Sign up at translateapi.ai/signup
- Go to Dashboard → API Keys
- Click "Create API Key" and copy your key
API keys start with ta_ followed by 56 hex characters.
https://api.translateapi.ai/api/v1/2. Make Your First Request
Replace YOUR_API_KEY with the key from your dashboard:
curl -X POST https://api.translateapi.ai/api/v1/translate/ \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"text": "Hello, world!",
"target_language": "es"
}'
import requests
response = requests.post(
"https://api.translateapi.ai/api/v1/translate/",
headers={
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
},
json={
"text": "Hello, world!",
"target_language": "es"
}
)
result = response.json()
print(result["translated_text"]) # "Hola, mundo!"
const response = await fetch("https://api.translateapi.ai/api/v1/translate/", {
method: "POST",
headers: {
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
},
body: JSON.stringify({
text: "Hello, world!",
target_language: "es"
})
});
const result = await response.json();
console.log(result.translated_text); // "Hola, mundo!"
$ch = curl_init("https://api.translateapi.ai/api/v1/translate/");
curl_setopt_array($ch, [
CURLOPT_RETURNTRANSFER => true,
CURLOPT_POST => true,
CURLOPT_HTTPHEADER => [
"Authorization: Bearer YOUR_API_KEY",
"Content-Type: application/json"
],
CURLOPT_POSTFIELDS => json_encode([
"text" => "Hello, world!",
"target_language" => "es"
])
]);
$result = json_decode(curl_exec($ch), true);
echo $result["translated_text"]; // "Hola, mundo!"
payload := strings.NewReader(`{
"text": "Hello, world!",
"target_language": "es"
}`)
req, _ := http.NewRequest("POST", "https://api.translateapi.ai/api/v1/translate/", payload)
req.Header.Set("Authorization", "Bearer YOUR_API_KEY")
req.Header.Set("Content-Type", "application/json")
resp, _ := http.DefaultClient.Do(req)
defer resp.Body.Close()
var result map[string]interface{}
json.NewDecoder(resp.Body).Decode(&result)
fmt.Println(result["translated_text"]) // "Hola, mundo!"
var client = new HttpClient();
client.DefaultRequestHeaders.Add("Authorization", "Bearer YOUR_API_KEY");
var content = new StringContent(
JsonSerializer.Serialize(new {
text = "Hello, world!",
target_language = "es"
}),
Encoding.UTF8,
"application/json"
);
var response = await client.PostAsync("https://api.translateapi.ai/api/v1/translate/", content);
var result = JsonSerializer.Deserialize<JsonElement>(
await response.Content.ReadAsStringAsync()
);
Console.WriteLine(result.GetProperty("translated_text")); // "Hola, mundo!"
Response
{
"translated_text": "Hola, mundo!",
"source_language": "en",
"target_language": "es",
"translations": {
"es": "Hola, mundo!"
},
"character_count": 13,
"translation_time": 0.45
}
Authentication
Authenticate your requests using an API key. You can create API keys from your dashboard.
Header Authentication (Recommended)
Authorization: Bearer ta_your_api_key_here
ApiKey Header
Authorization: ApiKey ta_your_api_key_here
Query Parameter
https://api.translateapi.ai/api/v1/translate/?api_key=ta_your_api_key_here
Translate Text
Translate text to a single target language.
POST https://api.translateapi.ai/api/v1/translate/
Request Body
| Parameter | Type | Required | Description |
|---|---|---|---|
text |
string | Yes | Text to translate (max 50,000 characters) |
target_language |
string | Yes* | Target language code (e.g., "es", "fr", "de") |
source_language |
string | No | Source language code. Default: "auto" (auto-detect) |
engine |
string | No | Translation engine: "auto" (default), "huggingface", or "madlad". See Translation Models. |
* Use target_language (string) for single language or target_languages (array) for multiple. See Multi-Target Translation.
Response
{
"translated_text": "Hola, mundo!",
"source_language": "en",
"target_language": "es",
"translations": {
"es": "Hola, mundo!"
},
"character_count": 13,
"translation_time": 0.45
}
source_language or set it to "auto" to automatically detect the source language. The detected language is returned in the source_language response field.
Multi-Target Translation
Translate text to multiple languages in a single request. Uses the same endpoint as single translation.
POST https://api.translateapi.ai/api/v1/translate/
Request Body
{
"text": "Hello, world!",
"target_languages": ["es", "fr", "de", "ja"],
"source_language": "en"
}
Use target_languages (array) instead of target_language (string) for multiple targets.
Response
{
"source_language": "en",
"translations": {
"es": "Hola, mundo!",
"fr": "Bonjour, monde!",
"de": "Hallo, Welt!",
"ja": "こんにちは、世界!"
},
"character_count": 52,
"translation_time": 2.31
}
Batch Translation
Translate multiple texts at once with async processing. Submit a batch and poll for results.
POST https://api.translateapi.ai/api/v1/translate/batch/
Step 1: Submit Batch
curl -X POST https://api.translateapi.ai/api/v1/translate/batch/ \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"texts": ["Hello", "Goodbye", "Thank you"],
"target_language": "es",
"source_language": "en"
}'
Response (HTTP 202 Accepted)
{
"job_id": "67535b2b-c9e3-4f82-9499-e237edbc1dd8",
"status": "pending",
"total_texts": 3,
"queue_position": 1,
"source_language": "en",
"target_languages": ["es"],
"character_count": 22,
"credits_remaining": -1,
"poll_url": "https://api.translateapi.ai/api/v1/jobs/67535b2b-c9e3-4f82-9499-e237edbc1dd8/"
}
Step 2: Poll for Results
GET https://api.translateapi.ai/api/v1/jobs/{job_id}/
Polling Example (Python)
import time, requests
job_id = response.json()["job_id"]
total = response.json()["total_texts"]
headers = {"Authorization": "Bearer YOUR_API_KEY"}
print(f"Batch submitted: {total} texts (job {job_id})")
while True:
result = requests.get(f"https://api.translateapi.ai/api/v1/jobs/{job_id}/", headers=headers).json()
status = result["status"]
processed = result.get("processed_texts", 0)
progress = result.get("progress_percentage", 0)
if status == "completed":
print(f"Done: {processed}/{total} in {result.get('processing_time', 0):.1f}s")
translations = result["result_data"]["translations"]
break
elif status == "failed":
raise Exception(result.get("error_message", "Translation failed"))
elif status == "pending":
print(f"Queued (position {result.get('queue_position', '?')})")
else:
print(f"[{status}] {processed}/{total} ({progress:.0f}%)")
time.sleep(3)
Response (completed)
{
"job_id": "67535b2b-...",
"status": "completed",
"processed_texts": 3,
"total_texts": 3,
"progress_percentage": 100.0,
"processing_time": 10.65,
"result_data": {
"translations": ["Hola", "Adiós", "Gracias"],
"source_language": "en",
"target_language": "es",
"character_count": 22,
"processing_time": 10.65
}
}
Real-time progress tracking
| Field | Description |
|---|---|
status |
pending (queued, waiting for a GPU worker), processing (actively translating), completed, failed |
processed_texts |
Number of individual translations completed so far. Updates in real time as each text is translated. |
progress_percentage |
Completion percentage (0-100). Calculated from processed_texts / total_texts. |
queue_position |
Your position in the queue when status is "pending" (1 = next up). Null when processing or completed. Use this to estimate wait time and show queue status to your users. |
processing_time |
Total processing time in seconds (available when completed). |
Multi-Language Batch
Translate multiple texts to multiple languages at once:
{
"texts": ["Hello", "Goodbye"],
"target_languages": ["es", "fr"],
"source_language": "en"
}
Completed result_data
{
"translations": [
{"es": "Hola", "fr": "Bonjour"},
{"es": "Adiós", "fr": "Au revoir"}
],
"source_language": "en",
"target_languages": ["es", "fr"],
"character_count": 24,
"processing_time": 2.45
}
Request Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
texts |
array | Yes | Array of strings to translate |
target_language |
string | Yes* | Target language code for single language |
target_languages |
array | Yes* | Array of target language codes for multiple languages |
source_language |
string | No | Source language code. Default: "auto" |
* Provide either target_language or target_languages, not both.
Best Practices for Large Workloads
- Send 1 target language per batch request. This keeps each batch fast and makes progress easy to track.
- Keep batches at 50-100 texts. Smaller batches complete faster and give you more frequent progress updates.
- Submit as many batch jobs as you need — our GPU cluster auto-scales to handle demand. Jobs are processed in parallel across multiple instances.
- On timeout, re-poll the same job_id instead of submitting a new batch. The original job may still be processing on the GPU.
- Poll every 3-5 seconds. More frequent polling does not speed up processing.
Document Translation
Translate entire documents while preserving formatting. Supports multiple file formats.
POST https://api.translateapi.ai/api/v1/translate/document/
Request (multipart/form-data)
| Parameter | Type | Required | Description |
|---|---|---|---|
file |
file | Yes | The document to translate (max 10MB) |
target_language |
string | Yes | Target language code (e.g., "es", "fr", "de") |
source_language |
string | No | Source language code. Default: "auto" (auto-detect) |
Supported File Types
Documents
.txt- Plain text files.docx- Word documents.pdf- PDF documents (including scanned)
Data & Localization
.json- JSON files (translates string values).xml- XML files.srt- Subtitle files.po/.pot- Gettext translation files
Images (OCR)
.jpg/.jpeg- JPEG images (OCR).png- PNG images (OCR).tiff/.tif- TIFF images (OCR).bmp- BMP images (OCR).webp- WebP images (OCR)
Example (cURL)
# Translate a Word document
curl -X POST https://api.translateapi.ai/api/v1/translate/document/ \
-H "Authorization: Bearer YOUR_API_KEY" \
-F "file=@document.docx" \
-F "target_language=es" \
-F "source_language=en"
# Translate text from an image (OCR)
curl -X POST https://api.translateapi.ai/api/v1/translate/document/ \
-H "Authorization: Bearer YOUR_API_KEY" \
-F "file=@scanned_page.jpg" \
-F "target_language=es" \
-F "source_language=en"
Response
{
"id": 123,
"original_filename": "document.docx",
"file_type": "docx",
"source_language": "en",
"target_language": "es",
"status": "completed",
"character_count": 5420,
"translated_file_url": "/media/translated/document_es.docx",
"created_at": "2024-01-15T10:30:00Z",
"completed_at": "2024-01-15T10:30:05Z"
}
GET https://api.translateapi.ai/api/v1/translate/document/{id}/
Check the status of a document translation or retrieve the download URL.
Status Values
pending |
File uploaded, waiting to be processed |
processing |
Translation in progress |
completed |
Translation complete, download available |
failed |
Translation failed (check error_message) |
Supported Languages
Get the list of all supported languages.
GET https://api.translateapi.ai/api/v1/translate/languages/
Response
{
"count": 186,
"results": [
{"iso": "en", "name": "English", "en_label": "English"},
{"iso": "es", "name": "Español", "en_label": "Spanish"},
{"iso": "fr", "name": "Français", "en_label": "French"},
...
]
}
Translation Models
We use state-of-the-art open source translation models running on our own GPU infrastructure. All models are commercially licensed (Apache 2.0).
| Model | Languages | Best For |
|---|---|---|
| Helsinki-NLP/opus-mt | 50+ language pairs | Common languages (EN, ES, FR, DE, IT, PT, RU, ZH, JA, etc.) |
| Google MADLAD-400 | 400+ languages | Rare languages, comprehensive coverage |
The API automatically selects the best model for your language pair. You can optionally specify an engine parameter:
| Engine | Description |
|---|---|
"auto" |
Default. Tries HuggingFace first, falls back to MADLAD-400 |
"huggingface" |
Force HuggingFace/MarianMT (fastest, 50+ languages) |
"madlad" |
Force MADLAD-400 (400+ languages) |
Error Handling
The API uses standard HTTP status codes to indicate success or failure.
| Code | Description |
|---|---|
| 200 | Success |
| 202 | Accepted — Batch job queued successfully |
| 400 | Bad Request — Invalid parameters (missing text, unsupported language, etc.) |
| 401 | Unauthorized - Invalid or missing API key |
| 402 | Payment Required — Character credits exhausted. Upgrade your plan or purchase a top-up. |
| 403 | Forbidden — API key lacks required scope or IP not in whitelist |
| 503 | Service Unavailable - Translation engine temporarily down |
Error Response Format
{
"error": "insufficient_credits",
"credits_remaining": 0
}
Usage & Pricing
TranslateAPI has no request rate limits. All requests are queued and processed by our auto-scaling GPU cluster. Your plan determines your monthly character allowance:
| Plan | Characters/Month | Batch API | Documents | Price | |
|---|---|---|---|---|---|
| Free | 250,000 | — | — | $0 | Sign Up Free |
| Starter | 2,500,000 | $9/mo | Subscribe | ||
| Pro | 10,000,000 | $29/mo | Subscribe | ||
| Business | 40,000,000 | $79/mo | Subscribe | ||
| Scale | 125,000,000 | $199/mo | Subscribe | ||
| Enterprise | Unlimited | $499/mo | Contact Sales |
When you exceed your limit, you'll receive a 402 Payment Required response until the next month or you upgrade.
Auto-Scaling Cloud Infrastructure
TranslateAPI runs on dedicated NVIDIA A100 GPU instances with automatic horizontal scaling. When demand increases, additional GPU instances are launched within minutes to maintain fast response times. All requests are queued and processed — send hundreds of concurrent requests and they'll all be handled. Real-time translations get priority, batch jobs process in the background.
Need More Credits?
Run out of characters mid-month? Purchase a one-time credit top-up without changing your plan. View top-up packs