bhashini-client-sdk 0.2.3

Python SDK for Bhashini inference APIs with unified support for ASR, NMT, TTS, OCR, NER, speaker services, normalization, and image-language workflows.

Bhashini Client SDK (Python)

bhashini-client-sdk is a Python SDK for working with Bhashini inference APIs through a unified BhashiniClient.

It provides a clean interface for speech, text, speaker, normalization, OCR, and image-language workflows while keeping validation, payload construction, model routing, and response parsing inside dedicated service modules.

Overview

Supported service categories:

Category	Services
Speech / Audio	ASR, TTS, Audio Language Detection, Speaker Diarization, Speaker Enrollment, Speaker Verification, Voice Cloning, Denoiser
Text	NMT, Transliteration, Text Language Detection, Text Normalization, Inverse Text Normalization, NER
Vision	OCR, Image Language Detection

Each service includes:

• input validation
• payload construction
• API dispatch through a shared request handler
• response parsing into simple SDK outputs

Installation

Requirements:

• Python 3.8+

Install from PyPI:

pip install bhashini-client-sdk

Authentication

Set the API key through BHASHINI_API_KEY or pass it directly to the client.

Environment variable:

$env:BHASHINI_API_KEY="your_api_key"

Or in code:

from bhashini_client import BhashiniClient

client = BhashiniClient(api_key="your_api_key")

Quick Start

from bhashini_client import BhashiniClient

client = BhashiniClient()

print(client.text_language_detection("Hello world"))
print(client.nmt("Hello", "en", "hi"))
print(client.tts("Hello from Bhashini", "en", output_file="output.wav"))
print(client.asr(r"C:\path\sample.wav", "hi"))

Public Client Methods

Method	Purpose	Return Type
client.asr(audio_input, source_lang)	Speech to text	str transcription
client.nmt(text, source_lang, target_lang)	Translation	str translated text
client.tts(text, source_lang, gender="female", output_file="output.wav")	Text to speech	output file path str
client.transliteration(text, source_lang, target_lang)	Script conversion	transliterated text str
client.text_language_detection(text)	Text language detection	language code str
client.audio_language_detection(audio_input)	Audio language detection	language code str
client.ocr(image_path, source_lang)	OCR from local image	extracted text str
client.ner(text, source_lang)	Named entity recognition	dict with entities
client.speaker_diarization(audio_input)	Speaker segmentation	list of speaker blocks
client.speaker_enrollment(audio_input, speaker_name)	Speaker profile creation	speaker ID str
client.speaker_verification(audio_input, speaker_id)	Speaker verification	verification result
client.voice_cloning(text, ref_text, ref_audio_input, source_lang="te", output_file="voice_clone_output.wav")	Voice cloning	output file path str
client.image_language_detection(image_input)	Image language detection	language code str
client.text_normalization(text, source_lang="en")	Text normalization	normalized text str
client.inverse_text_normalization(text, source_lang="en")	ITN	normalized text str
client.denoiser(audio_input, output_file="denoised_output.wav")	Audio denoising	output file path str or audio URI str

Service Highlights

ASR

• Supports local WAV input, base64 audio, and audio URI input
• Supports validated pre-processors: vad, denoiser
• Supports post-processors: itn, punctuation
• Automatically normalizes mismatched WAV sampling rates to 16000 Hz before dispatch

NMT

• Supports translation across validated language pairs
• Supports optional glossary, domain, gender, enable_number_translation, and profanity_filter
• Supports pre_processors=["html"]
• Supports post_processors=["glossary"]

TTS

• Generates WAV output files through the public client
• Advanced service usage supports speed, speaker_name, text_normalization, profanity_filter, and return_base64

Transliteration

• Supports suggestion count, sentence mode, and numeric_transliteration

Text Language Detection

• Detects the top language code from input text

Audio Language Detection

• Supports local WAV input, base64 audio, and audio URI input
• Automatically normalizes mismatched WAV sampling rates to 16000 Hz before dispatch

OCR

• Extracts text from a local image file

NER

• Extracts named entities and returns a normalized {"entities": [...]} structure

Speaker Services

• Enrollment supports local audio, base64 audio, and audio URI input
• Verification supports local audio, base64 audio, and audio URI input
• Diarization returns speaker segments with timestamps

Voice Cloning

• Generates speech from reference text and reference audio

Image Language Detection

• Supports local image path, public image URL, and base64 image content

Text Normalization and ITN

• Dedicated normalization endpoints for written-form cleanup and inverse text normalization

Denoiser

• Supports local audio, base64 audio, and audio URI input

Model Discovery

from bhashini_client import get_models_info, get_available_models

print(get_models_info("asr"))
print(get_available_models("asr", language="hi"))
print(get_available_models("nmt", language=("en", "hi")))
print(get_available_models("tts", language="en"))

Error Handling

Services return structured string errors with these prefixes:

• Input Error:
• Validation Error:
• API Error:

Package Contents

• bhashini_client.BhashiniClient
• bhashini_client.get_models_info
• bhashini_client.get_available_models

License

MIT