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Azure OpenAI Lecture Generation Demo

About

This is an example of how Azure OpenAI and Azure Cognitive Services text-to-speech technology can be utilized to create recorded lectures based on information from textbooks.

How to deploy

Run locally from Visual Studio Code or command prompt

• Open VS Code terminal or command prompt.
• Clone this repository and open in VS Code.
• Create a new conda environment
  • conda create -n openaidemo_py39 python=3.9 anaconda
  • conda activate openaidemo_py39
  • For more info go to Conda documentation
• Navigate to misc directory and run
  • pip install -r requirements.txt
• Provision Azure OpenAI service
  • Under deployments within Azure OpenAI Studio, deploy gpt-35-turbo model. Note name of deployment.
  • Model availability varies by region in which OpenAI service is provisioned in Azure.
  • For more info go to Create a resource and deploy a model using Azure OpenAI
• Provision Azure Cognitive Services
  • Create Cognitive Services multi-service resource.
  • For more info go to Create a new Azure Cognitive Services resource
• Open modules/utilities.py file and scroll to very bottom
  • Update value for "deployment_name" tag for parent tag "gpt-35-turbo". This name you noted in steps above.
• Almost there, rename .env_template file to .env
  • Renamed file should be placed within same directory as this readme.md file.
  • Replace placeholders with correct values.
• Navigate to /app directory and run following command from VS Code terminal. This will open the App UI in a browser window.
  • streamlit run app.py

Demo UI navigation

• Curriculum Management --> Bachelor of Mechanical Engineering --> 3024 Engineering Thermodynamics
• Curriculum details --> Load
• Reference books --> Load
• Chapters --> Chapter-1
• Generate lecture script
  • Toggle to Lecture Script tab once generation is completed
• Generate recording
  • To hear recording sample
  • Switch between speaker voices