# This file was auto-generated by Fern from our API Definition. import typing from json.decoder import JSONDecodeError from ..core.api_error import ApiError from ..core.client_wrapper import AsyncClientWrapper, SyncClientWrapper from ..core.http_response import AsyncHttpResponse, HttpResponse from ..core.pydantic_utilities import parse_obj_as from ..core.request_options import RequestOptions from ..errors.bad_request_error import BadRequestError from ..errors.forbidden_error import ForbiddenError from ..errors.internal_server_error import InternalServerError from ..errors.too_many_requests_error import TooManyRequestsError from ..errors.unprocessable_entity_error import UnprocessableEntityError from ..types.language_identification_response import LanguageIdentificationResponse from ..types.numerals_format import NumeralsFormat from ..types.spoken_form_numerals_format import SpokenFormNumeralsFormat from ..types.translate_mode import TranslateMode from ..types.translate_model import TranslateModel from ..types.translate_source_language import TranslateSourceLanguage from ..types.translate_speaker_gender import TranslateSpeakerGender from ..types.translate_target_language import TranslateTargetLanguage from ..types.translation_response import TranslationResponse from ..types.translatiterate_target_language import TranslatiterateTargetLanguage from ..types.transliterate_mode import TransliterateMode from ..types.transliterate_source_language import TransliterateSourceLanguage from ..types.transliteration_response import TransliterationResponse # this is used as the default value for optional parameters OMIT = typing.cast(typing.Any, ...) class RawTextClient: def __init__(self, *, client_wrapper: SyncClientWrapper): self._client_wrapper = client_wrapper def translate( self, *, input: str, source_language_code: TranslateSourceLanguage, target_language_code: TranslateTargetLanguage, speaker_gender: typing.Optional[TranslateSpeakerGender] = OMIT, mode: typing.Optional[TranslateMode] = OMIT, model: typing.Optional[TranslateModel] = OMIT, output_script: typing.Optional[TransliterateMode] = OMIT, numerals_format: typing.Optional[NumeralsFormat] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> HttpResponse[TranslationResponse]: """ **Translation** converts text from one language to another while preserving its meaning. For Example: **'मैं ऑफिस जा रहा हूँ'** translates to **'I am going to the office'** in English, where the script and language change, but the original meaning remains the same. Available languages: - **`bn-IN`**: Bengali - **`en-IN`**: English - **`gu-IN`**: Gujarati - **`hi-IN`**: Hindi - **`kn-IN`**: Kannada - **`ml-IN`**: Malayalam - **`mr-IN`**: Marathi - **`od-IN`**: Odia - **`pa-IN`**: Punjabi - **`ta-IN`**: Tamil - **`te-IN`**: Telugu ### Newly added languages: - **`as-IN`**: Assamese - **`brx-IN`**: Bodo - **`doi-IN`**: Dogri - **`kok-IN`**: Konkani - **`ks-IN`**: Kashmiri - **`mai-IN`**: Maithili - **`mni-IN`**: Manipuri (Meiteilon) - **`ne-IN`**: Nepali - **`sa-IN`**: Sanskrit - **`sat-IN`**: Santali - **`sd-IN`**: Sindhi - **`ur-IN`**: Urdu For hands-on practice, you can explore the notebook tutorial on [Translate API Tutorial](https://github.com/sarvamai/sarvam-ai-cookbook/blob/main/notebooks/translate/Translate_API_Tutorial.ipynb). Parameters ---------- input : str The text you want to translate is the input text that will be processed by the translation model. The maximum is 1000 characters for Mayura:v1 and 2000 characters for Sarvam-Translate:v1. source_language_code : TranslateSourceLanguage Source language code for translation input. **mayura:v1 Languages:** Bengali, English, Gujarati, Hindi, Kannada, Malayalam, Marathi, Odia, Punjabi, Tamil, Telugu **sarvam-translate:v1 Languages:** All mayura:v1 languages and Assamese, Bodo, Dogri, Konkani, Kashmiri, Maithili, Manipuri, Nepali, Sanskrit, Santali, Sindhi, Urdu **Note:** mayura:v1 supports automatic language detection using 'auto' as the source language code. target_language_code : TranslateTargetLanguage The language code of the translated text. This specifies the target language for translation. **mayura:v1 Languages:** Bengali, English, Gujarati, Hindi, Kannada, Malayalam, Marathi, Odia, Punjabi, Tamil, Telugu **sarvam-translate:v1 Languages:** All mayura:v1 and Assamese, Bodo, Dogri, Konkani, Kashmiri, Maithili, Manipuri, Nepali, Sanskrit, Santali, Sindhi, Urdu speaker_gender : typing.Optional[TranslateSpeakerGender] Please specify the gender of the speaker for better translations. mode : typing.Optional[TranslateMode] Specifies the tone or style of the translation. **Model Support:** - **mayura:v1**: Supports formal, classic-colloquial, and modern-colloquial modes - **sarvam-translate:v1**: Only formal mode is supported **Default:** formal model : typing.Optional[TranslateModel] Specifies the translation model to use. - mayura:v1: Supports 12 languages with all modes, output scripts, and automatic language detection. - sarvam-translate:v1: Supports all 22 scheduled languages of India, formal mode only. output_script : typing.Optional[TransliterateMode] **output_script**: This is an optional parameter which controls the transliteration style applied to the output text. **Transliteration**: Converting text from one script to another while preserving pronunciation. For mayura:v1 - We support transliteration with four options: - **`null`**(default): No transliteration applied. - **`roman`**: Transliteration in Romanized script. - **`fully-native`**: Transliteration in the native script with formal style. - **`spoken-form-in-native`**: Transliteration in the native script with spoken style. For sarvam-translate:v1 - Transliteration is not supported. ### Example: English: Your EMI of Rs. 3000 is pending. Default modern translation: आपका Rs. 3000 का EMI pending है (when `null` is passed). With postprocessing enabled: - **roman output**: aapka Rs. 3000 ka EMI pending hai. numerals_format : typing.Optional[NumeralsFormat] `numerals_format` is an optional parameter with two options (supported for both mayura:v1 and sarvam-translate:v1): - **`international`** (default): Uses regular numerals (0-9). - **`native`**: Uses language-specific native numerals. ### Example: - If `international` format is selected, we use regular numerals (0-9). For example: `मेरा phone number है: 9840950950`. - If `native` format is selected, we use language-specific native numerals, like: `मेरा phone number है: ९८४०९५०९५०`. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[TranslationResponse] Successful Response """ _response = self._client_wrapper.httpx_client.request( "translate", base_url=self._client_wrapper.get_environment().base, method="POST", json={ "input": input, "source_language_code": source_language_code, "target_language_code": target_language_code, "speaker_gender": speaker_gender, "mode": mode, "model": model, "output_script": output_script, "numerals_format": numerals_format, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( TranslationResponse, parse_obj_as( type_=TranslationResponse, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 400: raise BadRequestError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 403: raise ForbiddenError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 429: raise TooManyRequestsError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 500: raise InternalServerError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json) def identify_language( self, *, input: str, request_options: typing.Optional[RequestOptions] = None ) -> HttpResponse[LanguageIdentificationResponse]: """ Identifies the language (e.g., en-IN, hi-IN) and script (e.g., Latin, Devanagari) of the input text, supporting multiple languages. Parameters ---------- input : str The text input for language and script identification. Max Input Limit is 1000 characters request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[LanguageIdentificationResponse] Successful Response """ _response = self._client_wrapper.httpx_client.request( "text-lid", base_url=self._client_wrapper.get_environment().base, method="POST", json={ "input": input, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( LanguageIdentificationResponse, parse_obj_as( type_=LanguageIdentificationResponse, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 400: raise BadRequestError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 403: raise ForbiddenError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 429: raise TooManyRequestsError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 500: raise InternalServerError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json) def transliterate( self, *, input: str, source_language_code: TransliterateSourceLanguage, target_language_code: TranslatiterateTargetLanguage, numerals_format: typing.Optional[NumeralsFormat] = OMIT, spoken_form_numerals_language: typing.Optional[SpokenFormNumeralsFormat] = OMIT, spoken_form: typing.Optional[bool] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> HttpResponse[TransliterationResponse]: """ **Transliteration** converts text from one script to another while preserving the original pronunciation. For example, **'नमस्ते'** becomes **'namaste'** in English, and **'how are you'** can be written as **'हाउ आर यू'** in Devanagari. This process ensures that the sound of the original text remains intact, even when written in a different script. Transliteration is useful when you want to represent words phonetically across different writing systems, such as converting **'मैं ऑफिस जा रहा हूँ'** to **'main office ja raha hun'** in English letters. **Translation**, on the other hand, converts text from one language to another while preserving the meaning rather than pronunciation. For example, **'मैं ऑफिस जा रहा हूँ'** translates to **'I am going to the office'** in English, changing both the script and the language while conveying the intended message. ### Examples of **Transliteration**: - **'Good morning'** becomes **'गुड मॉर्निंग'** in Hindi, where the pronunciation is preserved but the meaning is not translated. - **'सुप्रभात'** becomes **'suprabhat'** in English. Available languages: - **`en-IN`**: English - **`hi-IN`**: Hindi - **`bn-IN`**: Bengali - **`gu-IN`**: Gujarati - **`kn-IN`**: Kannada - **`ml-IN`**: Malayalam - **`mr-IN`**: Marathi - **`od-IN`**: Odia - **`pa-IN`**: Punjabi - **`ta-IN`**: Tamil - **`te-IN`**: Telugu For hands-on practice, you can explore the notebook tutorial on [Transliterate API Tutorial](https://github.com/sarvamai/sarvam-ai-cookbook/blob/main/notebooks/transliterate/Transliterate_API_Tutorial.ipynb). Parameters ---------- input : str The text you want to transliterate. source_language_code : TransliterateSourceLanguage The language code of the input text. This specifies the source language for transliteration. Note: The source language should either be an Indic language or English. As we supports both Indic-to-English and English-to-Indic transliteration. target_language_code : TranslatiterateTargetLanguage The language code of the transliteration text. This specifies the target language for transliteration. Note:The target language should either be an Indic language or English. As we supports both Indic-to-English and English-to-Indic transliteration. numerals_format : typing.Optional[NumeralsFormat] `numerals_format` is an optional parameter with two options: - **`international`** (default): Uses regular numerals (0-9). - **`native`**: Uses language-specific native numerals. ### Example: - If `international` format is selected, we use regular numerals (0-9). For example: `मेरा phone number है: 9840950950`. - If `native` format is selected, we use language-specific native numerals, like: `मेरा phone number है: ९८४०९५०९५०`. spoken_form_numerals_language : typing.Optional[SpokenFormNumeralsFormat] `spoken_form_numerals_language` is an optional parameter with two options and only works when spoken_form is true: - **`english`** : Numbers in the text will be spoken in English. - **`native(default)`**: Numbers in the text will be spoken in the native language. ### Examples: - **Input:** "मेरे पास ₹200 है" - If `english` format is selected: "मेरे पास टू हन्डर्ड रूपीस है" - If `native` format is selected: "मेरे पास दो सौ रुपये है" spoken_form : typing.Optional[bool] - Default: `False` - Converts text into a natural spoken form when `True`. - **Note:** No effect if output language is `en-IN`. ### Example: - **Input:** `मुझे कल 9:30am को appointment है` - **Output:** `मुझे कल सुबह साढ़े नौ बजे को अपॉइंटमेंट है` request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[TransliterationResponse] Successful Response """ _response = self._client_wrapper.httpx_client.request( "transliterate", base_url=self._client_wrapper.get_environment().base, method="POST", json={ "input": input, "source_language_code": source_language_code, "target_language_code": target_language_code, "numerals_format": numerals_format, "spoken_form_numerals_language": spoken_form_numerals_language, "spoken_form": spoken_form, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( TransliterationResponse, parse_obj_as( type_=TransliterationResponse, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 400: raise BadRequestError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 403: raise ForbiddenError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 429: raise TooManyRequestsError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 500: raise InternalServerError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json) class AsyncRawTextClient: def __init__(self, *, client_wrapper: AsyncClientWrapper): self._client_wrapper = client_wrapper async def translate( self, *, input: str, source_language_code: TranslateSourceLanguage, target_language_code: TranslateTargetLanguage, speaker_gender: typing.Optional[TranslateSpeakerGender] = OMIT, mode: typing.Optional[TranslateMode] = OMIT, model: typing.Optional[TranslateModel] = OMIT, output_script: typing.Optional[TransliterateMode] = OMIT, numerals_format: typing.Optional[NumeralsFormat] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> AsyncHttpResponse[TranslationResponse]: """ **Translation** converts text from one language to another while preserving its meaning. For Example: **'मैं ऑफिस जा रहा हूँ'** translates to **'I am going to the office'** in English, where the script and language change, but the original meaning remains the same. Available languages: - **`bn-IN`**: Bengali - **`en-IN`**: English - **`gu-IN`**: Gujarati - **`hi-IN`**: Hindi - **`kn-IN`**: Kannada - **`ml-IN`**: Malayalam - **`mr-IN`**: Marathi - **`od-IN`**: Odia - **`pa-IN`**: Punjabi - **`ta-IN`**: Tamil - **`te-IN`**: Telugu ### Newly added languages: - **`as-IN`**: Assamese - **`brx-IN`**: Bodo - **`doi-IN`**: Dogri - **`kok-IN`**: Konkani - **`ks-IN`**: Kashmiri - **`mai-IN`**: Maithili - **`mni-IN`**: Manipuri (Meiteilon) - **`ne-IN`**: Nepali - **`sa-IN`**: Sanskrit - **`sat-IN`**: Santali - **`sd-IN`**: Sindhi - **`ur-IN`**: Urdu For hands-on practice, you can explore the notebook tutorial on [Translate API Tutorial](https://github.com/sarvamai/sarvam-ai-cookbook/blob/main/notebooks/translate/Translate_API_Tutorial.ipynb). Parameters ---------- input : str The text you want to translate is the input text that will be processed by the translation model. The maximum is 1000 characters for Mayura:v1 and 2000 characters for Sarvam-Translate:v1. source_language_code : TranslateSourceLanguage Source language code for translation input. **mayura:v1 Languages:** Bengali, English, Gujarati, Hindi, Kannada, Malayalam, Marathi, Odia, Punjabi, Tamil, Telugu **sarvam-translate:v1 Languages:** All mayura:v1 languages and Assamese, Bodo, Dogri, Konkani, Kashmiri, Maithili, Manipuri, Nepali, Sanskrit, Santali, Sindhi, Urdu **Note:** mayura:v1 supports automatic language detection using 'auto' as the source language code. target_language_code : TranslateTargetLanguage The language code of the translated text. This specifies the target language for translation. **mayura:v1 Languages:** Bengali, English, Gujarati, Hindi, Kannada, Malayalam, Marathi, Odia, Punjabi, Tamil, Telugu **sarvam-translate:v1 Languages:** All mayura:v1 and Assamese, Bodo, Dogri, Konkani, Kashmiri, Maithili, Manipuri, Nepali, Sanskrit, Santali, Sindhi, Urdu speaker_gender : typing.Optional[TranslateSpeakerGender] Please specify the gender of the speaker for better translations. mode : typing.Optional[TranslateMode] Specifies the tone or style of the translation. **Model Support:** - **mayura:v1**: Supports formal, classic-colloquial, and modern-colloquial modes - **sarvam-translate:v1**: Only formal mode is supported **Default:** formal model : typing.Optional[TranslateModel] Specifies the translation model to use. - mayura:v1: Supports 12 languages with all modes, output scripts, and automatic language detection. - sarvam-translate:v1: Supports all 22 scheduled languages of India, formal mode only. output_script : typing.Optional[TransliterateMode] **output_script**: This is an optional parameter which controls the transliteration style applied to the output text. **Transliteration**: Converting text from one script to another while preserving pronunciation. For mayura:v1 - We support transliteration with four options: - **`null`**(default): No transliteration applied. - **`roman`**: Transliteration in Romanized script. - **`fully-native`**: Transliteration in the native script with formal style. - **`spoken-form-in-native`**: Transliteration in the native script with spoken style. For sarvam-translate:v1 - Transliteration is not supported. ### Example: English: Your EMI of Rs. 3000 is pending. Default modern translation: आपका Rs. 3000 का EMI pending है (when `null` is passed). With postprocessing enabled: - **roman output**: aapka Rs. 3000 ka EMI pending hai. numerals_format : typing.Optional[NumeralsFormat] `numerals_format` is an optional parameter with two options (supported for both mayura:v1 and sarvam-translate:v1): - **`international`** (default): Uses regular numerals (0-9). - **`native`**: Uses language-specific native numerals. ### Example: - If `international` format is selected, we use regular numerals (0-9). For example: `मेरा phone number है: 9840950950`. - If `native` format is selected, we use language-specific native numerals, like: `मेरा phone number है: ९८४०९५०९५०`. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[TranslationResponse] Successful Response """ _response = await self._client_wrapper.httpx_client.request( "translate", base_url=self._client_wrapper.get_environment().base, method="POST", json={ "input": input, "source_language_code": source_language_code, "target_language_code": target_language_code, "speaker_gender": speaker_gender, "mode": mode, "model": model, "output_script": output_script, "numerals_format": numerals_format, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( TranslationResponse, parse_obj_as( type_=TranslationResponse, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 400: raise BadRequestError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 403: raise ForbiddenError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 429: raise TooManyRequestsError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 500: raise InternalServerError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json) async def identify_language( self, *, input: str, request_options: typing.Optional[RequestOptions] = None ) -> AsyncHttpResponse[LanguageIdentificationResponse]: """ Identifies the language (e.g., en-IN, hi-IN) and script (e.g., Latin, Devanagari) of the input text, supporting multiple languages. Parameters ---------- input : str The text input for language and script identification. Max Input Limit is 1000 characters request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[LanguageIdentificationResponse] Successful Response """ _response = await self._client_wrapper.httpx_client.request( "text-lid", base_url=self._client_wrapper.get_environment().base, method="POST", json={ "input": input, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( LanguageIdentificationResponse, parse_obj_as( type_=LanguageIdentificationResponse, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 400: raise BadRequestError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 403: raise ForbiddenError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 429: raise TooManyRequestsError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 500: raise InternalServerError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json) async def transliterate( self, *, input: str, source_language_code: TransliterateSourceLanguage, target_language_code: TranslatiterateTargetLanguage, numerals_format: typing.Optional[NumeralsFormat] = OMIT, spoken_form_numerals_language: typing.Optional[SpokenFormNumeralsFormat] = OMIT, spoken_form: typing.Optional[bool] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> AsyncHttpResponse[TransliterationResponse]: """ **Transliteration** converts text from one script to another while preserving the original pronunciation. For example, **'नमस्ते'** becomes **'namaste'** in English, and **'how are you'** can be written as **'हाउ आर यू'** in Devanagari. This process ensures that the sound of the original text remains intact, even when written in a different script. Transliteration is useful when you want to represent words phonetically across different writing systems, such as converting **'मैं ऑफिस जा रहा हूँ'** to **'main office ja raha hun'** in English letters. **Translation**, on the other hand, converts text from one language to another while preserving the meaning rather than pronunciation. For example, **'मैं ऑफिस जा रहा हूँ'** translates to **'I am going to the office'** in English, changing both the script and the language while conveying the intended message. ### Examples of **Transliteration**: - **'Good morning'** becomes **'गुड मॉर्निंग'** in Hindi, where the pronunciation is preserved but the meaning is not translated. - **'सुप्रभात'** becomes **'suprabhat'** in English. Available languages: - **`en-IN`**: English - **`hi-IN`**: Hindi - **`bn-IN`**: Bengali - **`gu-IN`**: Gujarati - **`kn-IN`**: Kannada - **`ml-IN`**: Malayalam - **`mr-IN`**: Marathi - **`od-IN`**: Odia - **`pa-IN`**: Punjabi - **`ta-IN`**: Tamil - **`te-IN`**: Telugu For hands-on practice, you can explore the notebook tutorial on [Transliterate API Tutorial](https://github.com/sarvamai/sarvam-ai-cookbook/blob/main/notebooks/transliterate/Transliterate_API_Tutorial.ipynb). Parameters ---------- input : str The text you want to transliterate. source_language_code : TransliterateSourceLanguage The language code of the input text. This specifies the source language for transliteration. Note: The source language should either be an Indic language or English. As we supports both Indic-to-English and English-to-Indic transliteration. target_language_code : TranslatiterateTargetLanguage The language code of the transliteration text. This specifies the target language for transliteration. Note:The target language should either be an Indic language or English. As we supports both Indic-to-English and English-to-Indic transliteration. numerals_format : typing.Optional[NumeralsFormat] `numerals_format` is an optional parameter with two options: - **`international`** (default): Uses regular numerals (0-9). - **`native`**: Uses language-specific native numerals. ### Example: - If `international` format is selected, we use regular numerals (0-9). For example: `मेरा phone number है: 9840950950`. - If `native` format is selected, we use language-specific native numerals, like: `मेरा phone number है: ९८४०९५०९५०`. spoken_form_numerals_language : typing.Optional[SpokenFormNumeralsFormat] `spoken_form_numerals_language` is an optional parameter with two options and only works when spoken_form is true: - **`english`** : Numbers in the text will be spoken in English. - **`native(default)`**: Numbers in the text will be spoken in the native language. ### Examples: - **Input:** "मेरे पास ₹200 है" - If `english` format is selected: "मेरे पास टू हन्डर्ड रूपीस है" - If `native` format is selected: "मेरे पास दो सौ रुपये है" spoken_form : typing.Optional[bool] - Default: `False` - Converts text into a natural spoken form when `True`. - **Note:** No effect if output language is `en-IN`. ### Example: - **Input:** `मुझे कल 9:30am को appointment है` - **Output:** `मुझे कल सुबह साढ़े नौ बजे को अपॉइंटमेंट है` request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[TransliterationResponse] Successful Response """ _response = await self._client_wrapper.httpx_client.request( "transliterate", base_url=self._client_wrapper.get_environment().base, method="POST", json={ "input": input, "source_language_code": source_language_code, "target_language_code": target_language_code, "numerals_format": numerals_format, "spoken_form_numerals_language": spoken_form_numerals_language, "spoken_form": spoken_form, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( TransliterationResponse, parse_obj_as( type_=TransliterationResponse, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 400: raise BadRequestError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 403: raise ForbiddenError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 429: raise TooManyRequestsError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) if _response.status_code == 500: raise InternalServerError( headers=dict(_response.headers), body=typing.cast( typing.Optional[typing.Any], parse_obj_as( type_=typing.Optional[typing.Any], # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)