{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/5"}],"enrichment":{"capability":"Client library for NVIDIA Riva, a GPU-accelerated Speech AI SDK providing APIs for automatic speech recognition, text-to-speech synthesis, and natural language processing tasks.","skillfed_tags":["speech-recognition","gpu-accelerated","grpc-client"],"use_cases":["Build a real-time speech transcription application that streams audio from a microphone and returns live transcripts with intermediate results.","Integrate text-to-speech synthesis into a conversational AI system to generate spoken responses from text via WebSocket connections.","Process batch audio files for offline transcription with optional word-boosting to improve accuracy on domain-specific terminology.","Implement intent and slot recognition in a chatbot to extract user intent and entities from natural language queries.","Add named entity recognition or punctuation restoration to a document processing pipeline for text normalization.","Perform text classification on user inputs to route queries to appropriate downstream services."],"what_it_does":"nvidia-riva-client is a Python client library for interacting with NVIDIA Riva, a GPU-accelerated Speech AI platform. It provides three main service classes\u2014ASRService for speech recognition, TTSService for text-to-speech, and NLPService for natural language processing\u2014along with command-line scripts demonstrating streaming transcription, real-time WebSocket-based synthesis, and NLP tasks like intent detection, named entity recognition, and punctuation restoration.\n\nThe package depends on grpcio, grpcio-tools, websockets, and protobuf to communicate with a Riva server backend. It supports both streaming and offline modes, with optional real-time audio I/O via microphone and speaker (when PyAudio is installed separately). The library is actively maintained, supports Python 3.7 and later, and carries no known security vulnerabilities.","worth_installing":"Yes. The package is actively maintained, has low install friction, carries no known vulnerabilities, and offers a permissive MIT license. Install it if you need to build Speech AI applications with NVIDIA Riva; the main prerequisite is having a Riva server running and, for audio I/O features, PyAudio installed separately."},"id":"nvidia-riva-client","links":{"html":"https://skillfed.io/packages/nvidia-riva-client","md":"https://skillfed.io/packages/nvidia-riva-client.md","pypi":"https://pypi.org/project/nvidia-riva-client/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-13","license_spdx":null,"license_treatment":"permissive","name":"nvidia-riva-client","python_support":"supports_current","summary":"Python implementation of the Riva Client API"},"popularity":{"monthly_downloads":570249,"position":5956,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2.27.0"}