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The goal of the digital-twin-technology project is to build an embodied digital twin of the user. This digital twin, built by Tensornetics LLC, utilizes cutting-edge AI technology such as OpenAI and NVIDIA Nemo, to provide a highly-realistic and interactive representation of the user. The project is deployed using Kubernetes

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Digital Twin Technology by Tensornetics LLC

This repository contains the code for a digital twin technology solution built by Tensornetics LLC. The technology integrates the OpenAI API and NVIDIA NEMO for ASR, NLP, and TTS, along with RIVA for ASR.

Requirements

The following packages are required to run the technology:

  • openai
  • nvidia-nemo
  • riva

These packages can be installed using pip by running the following command:

pip install -r requirements.txt

Deployment

The deployment of the technology is managed using Kubernetes. The deployment specifications are defined in the deployment folder. The kustomization.yaml file is used to configure and manage the deployment.

digital-twin-technology
|-- api/
|   |
|   |-- openai/
|   |   |
|   |   |-- openai_api.py 
|   |   |-- openai_config.py 
|   |
|   |-- nvidia/
|   |   |
|   |   |-- nemo/
|   |   |   |
|   |   |   |-- nemo_asr.py 
|   |   |   |-- nemo_nlp.py 
|   |   |   |-- nemo_tts.py 
|   |   |
|   |   |-- riva/
|   |   |   |
|   |   |   |-- riva_asr.py 
|   |
|-- main/
|   |
|   |-- ai_assistant.py 
|   |-- main.py 
|
|-- tests/
|   |
|   |-- test_ai_assistant.py 
|
|-- deployment/
|   |
|   |-- kubernetes/
|   |   |
|   |   |-- kustomization.yaml 
|   |   |-- deployment.yaml 
|   |   |-- service.yaml 
|   |   |-- ingress.yaml 
|   |   |-- istio/ (folder to store ISTIO related configuration files)
|   |
|-- requirements.txt 
|-- README.md

About

The goal of the digital-twin-technology project is to build an embodied digital twin of the user. This digital twin, built by Tensornetics LLC, utilizes cutting-edge AI technology such as OpenAI and NVIDIA Nemo, to provide a highly-realistic and interactive representation of the user. The project is deployed using Kubernetes

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