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Translate text between English and Indian languages using Sarvam AI's Mayura model. Use when the user needs to translate content, localize applications, or convert text between Hindi, Tamil, Bengali, Telugu, and 7 other Indian languages. Supports bidirectional translation, script control, and code-mixed text.
npx skill4agent add sarvamai/skills translatepip install sarvamaifrom sarvamai import SarvamAI
client = SarvamAI()
response = client.translate.translate(
input="Hello, how are you?",
source_language_code="en-IN",
target_language_code="hi-IN",
model="mayura:v1"
)
print(response.translated_text) # "नमस्ते, आप कैसे हैं?"| Code | Language | Code | Language |
|---|---|---|---|
| Hindi | | Tamil |
| Bengali | | Telugu |
| Kannada | | Malayalam |
| Marathi | | Gujarati |
| Punjabi | | Odia |
| English | | Auto-detect |
response = client.translate.translate(
input="Please submit the report by Friday",
source_language_code="en-IN",
target_language_code="hi-IN",
model="mayura:v1",
mode="formal"
)response = client.translate.translate(
input="Hey, what's up?",
source_language_code="en-IN",
target_language_code="hi-IN",
model="mayura:v1",
mode="casual"
)# Hindi in Devanagari (default)
response = client.translate.translate(
input="Hello",
source_language_code="en-IN",
target_language_code="hi-IN",
output_script="devanagari"
)
# Output: "नमस्ते"
# Hindi in Latin (transliteration)
response = client.translate.translate(
input="Hello",
source_language_code="en-IN",
target_language_code="hi-IN",
output_script="latin"
)
# Output: "Namaste"# International numerals (default)
response = client.translate.translate(
input="The price is 500 rupees",
source_language_code="en-IN",
target_language_code="hi-IN",
numeral_format="international"
)
# Output: "कीमत 500 रुपये है"
# Native numerals
response = client.translate.translate(
input="The price is 500 rupees",
source_language_code="en-IN",
target_language_code="hi-IN",
numeral_format="native"
)
# Output: "कीमत ५०० रुपये है"response = client.translate.translate(
input="Yaar, let's go for a movie tonight",
source_language_code="auto", # Auto-detect
target_language_code="hi-IN",
model="mayura:v1"
)
# Output: "यार, चलो आज रात फिल्म देखने चलते हैं"texts = [
"Hello",
"How are you?",
"Thank you"
]
responses = []
for text in texts:
response = client.translate.translate(
input=text,
source_language_code="en-IN",
target_language_code="hi-IN",
model="mayura:v1"
)
responses.append(response.translated_text)
print(responses)
# [
"नमस्ते",
"आप कैसे हैं?",
"धन्यवाद"
]import { SarvamAI
} from "sarvamai";
const client = new SarvamAI();
const response = await client.translate.translate({
input: "Hello, how are you?",
sourceLanguageCode: "en-IN",
targetLanguageCode: "hi-IN",
model: "mayura:v1"
});
console.log(response.translatedText);curl -X POST "https://api.sarvam.ai/translate" \
-H "api-subscription-key: $SARVAM_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"input": "Hello, how are you?",
"source_language_code": "en-IN",
"target_language_code": "hi-IN",
"model": "mayura:v1"
}'| Parameter | Type | Required | Description |
|---|---|---|---|
| string | Yes | Text to translate |
| string | Yes | Source language or |
| string | Yes | Target language code |
| string | Yes | |
| string | No | |
| string | No | |
| string | No | |
{
"request_id": "abc123",
"translated_text": "नमस्ते, आप कैसे हैं?",
"source_language_code": "en-IN",
"target_language_code": "hi-IN"
}