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Building a Video Transcriber with Node.js and OpenAI API

Building a Video Transcriber with Node.js and OpenAI API

1h 2mIntermediate2024-01-12

Authors

Fikayo Adepoju

Fikayo Adepoju

Technical Writer | Software Developer

Course details

Formerly complicated tasks like audio transcription for videos have become much simpler thanks to the rise of APIs like OpenAI's Whisper. But while this exciting new tool can handle transcription, if you want to transcribe a lot of audio, your code still needs to set up connections and authentication and pipe the information back and forth. In this course, instructor Fikayo Adepoju shows you how to integrate Node.js applications with the OpenAI Whisper API. Learn how to set up OpenAI API access, build the video transcriber interface, develop the back end and connect to the AI, and then bring it all together.

This course is designed for intermediate and advanced developers interested in the future of development with generative AI and the integration of applications with AI models.

Skills covered

JavaScript FrameworksChatGPTAPIsOpenAIGenerative AIArtificial Intelligence (AI)Web DevelopmentSoftware DevelopmentOne-Off

Concepts

0. Introduction

  • 01 - AI-powered video transcription
  • 02 - Who is this course for
  • 03 - What you should know

1. Setting Up OpenAI API Access

  • 04 - Signing up for an OpenAI account
  • 05 - Upgrading to a paid API account
  • 06 - The Whisper model
  • 07 - Understanding tokens and pricing
  • 08 - Generating an API key

2. Building the Video Transcriber Interface

  • 09 - Cloning the seed project
  • 10 - Project code walkthrough
  • 11 - Adding the video upload functionality
  • 12 - Adding the transcribeVideo function
  • 13 - Adding the displayTranscription function

3. Building the Back End - Connecting to the AI

  • 14 - Building out the Express.js API
  • 15 - Configuring the OpenAI library
  • 16 - Adding routes
  • 17 - Setting up file upload functionality
  • 18 - Transcribing with the Whisper API

4. Bringing It All Together

  • 19 - Connecting the front end to the API
  • 20 - Adding a progress indicator
  • 21 - Editing transcriptions

Conclusion

  • 22 - Next steps

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