Dokumentacja API

Organ wniosku

* Użyj target_language (wiersz) dla jednego języka lub target_languages (masy) dla wielokrotnego. Patrz Tłumaczenie Multi-Target.

Odpowiedź

{
    "translated_text": "Hola, mundo!",
    "source_language": "en",
    "target_language": "es",
    "translations": {
        "es": "Hola, mundo!"
    },
    "character_count": 13,
    "translation_time": 0.45
}

Organ wniosku

{
    "text": "Hello, world!",
    "target_languages": ["es", "fr", "de", "ja"],
    "source_language": "en"
}

Użyj target_languages (Ras) zamiast target_language (string) dla wielu celów.

Odpowiedź

{
    "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
}

Krok 1: Wyślij serię

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"
}'

Odpowiedź (HTTP 202 akceptowana)

{
    "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/"
}

Krok 2: Analiza wyników

Przykład badania (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)

Odpowiedź (zakończona)

{
    "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

Seria wielojęzyczna

Przetłumacz wiele tekstów na wiele języków naraz:

{
    "texts": ["Hello", "Goodbye"],
    "target_languages": ["es", "fr"],
    "source_language": "en"
}

Zakończone wyniki_ danych

{
    "translations": [
        {"es": "Hola", "fr": "Bonjour"},
        {"es": "Adiós", "fr": "Au revoir"}
    ],
    "source_language": "en",
    "target_languages": ["es", "fr"],
    "character_count": 24,
    "processing_time": 2.45
}

Parametry żądania

* Upewnić się, że którykolwiek z nich target_language lub target_languagesNie oboje.

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.

Wniosek (multipart/form-data)

Obsługiwane typy plików

Przykład (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"

Odpowiedź

{
    "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"
}

Sprawdź stan tłumaczenia dokumentu lub odbierz URL pobierania.

Wartości stanu

Odpowiedź

{
    "count": 186,
    "results": [
        {"iso": "en", "name": "English", "en_label": "English"},
        {"iso": "es", "name": "Español", "en_label": "Spanish"},
        {"iso": "fr", "name": "Français", "en_label": "French"},
        ...
    ]
}

View All 186 Languages

Organ wniosku

Example Request

curl -X POST https://translateapi.ai/api/v1/suggestions/ \
    -H "Authorization: Bearer YOUR_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{
    "source_text": "Hello, world!",
    "source_language": "en",
    "target_language": "es",
    "machine_translation": "Hola, mundo!",
    "suggested_translation": "¡Hola, mundo!"
}'

Odpowiedź

{
    "id": 4213,
    "status": "pending",
    "created": true,
    "message": "Correction submitted for review."
}

Re-submitting the same source/language pair updates your existing suggestion instead of creating a duplicate (returns 200 with "created": false).