Translation APIs Beginner

pip install google-cloud-translate

from google.cloud import translate_v2 as translate

client = translate.Client()

# Translate text
result = client.translate(
    "Hello, how are you?",
    target_language="es"
)
print(result["translatedText"])
# "Hola, ¿cómo estás?"

# Detect language
detection = client.detect_language("Bonjour le monde")
print(detection["language"])  # "fr"

# Batch translation
texts = ["Good morning", "Thank you", "Goodbye"]
results = client.translate(texts, target_language="ja")
for r in results:
    print(f"{r['input']} -> {r['translatedText']}")

import deepl

translator = deepl.Translator("YOUR_DEEPL_API_KEY")

# Translate text with formality control
result = translator.translate_text(
    "How are you doing today?",
    target_lang="DE",
    formality="more"  # Use formal register
)
print(result.text)
# "Wie geht es Ihnen heute?"

# Translate with glossary (enforce specific terms)
glossary = translator.create_glossary(
    "Tech Terms",
    source_lang="EN",
    target_lang="DE",
    entries={"machine learning": "maschinelles Lernen"}
)
result = translator.translate_text(
    "We use machine learning for predictions.",
    target_lang="DE",
    glossary=glossary
)

import requests

endpoint = "https://api.cognitive.microsofttranslator.com"
headers = {
    "Ocp-Apim-Subscription-Key": "YOUR_AZURE_KEY",
    "Ocp-Apim-Subscription-Region": "eastus",
    "Content-Type": "application/json",
}

# Translate to multiple languages at once
body = [{"text": "Hello, world!"}]
params = {"api-version": "3.0", "to": ["fr", "de", "ja"]}

response = requests.post(
    f"{endpoint}/translate",
    headers=headers, params=params, json=body
)

for translation in response.json()[0]["translations"]:
    print(f"{translation['to']}: {translation['text']}")

from transformers import MarianMTModel, MarianTokenizer

model_name = "Helsinki-NLP/opus-mt-en-de"
tokenizer = MarianTokenizer.from_pretrained(model_name)
model = MarianMTModel.from_pretrained(model_name)

texts = ["Hello, how are you?", "Machine learning is fascinating."]
inputs = tokenizer(texts, return_tensors="pt", padding=True)
translated = model.generate(**inputs)
results = tokenizer.batch_decode(translated, skip_special_tokens=True)

for src, tgt in zip(texts, results):
    print(f"{src} -> {tgt}")