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Hands-On OpenAI API: Building a Real-World Solution

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OpenAI stands at the forefront of AI, particularly when it comes to large language models (LLMs). If you’re a developer or business leader looking to leverage AI-powered tools, this course helps you to get up to speed with how to use OpenAI APIs to build solutions based on the retrieval-augmented generation (RAG) technique.

Join instructor Rodrigo Díaz Concha as he demonstrates a wide variety of solution-building options including using the Audio API to transcribe audio and the Chat Completions API to create documents. Test your new skills with a real-world project named KinderLogger by building an assistant using the Assistants API, implementing a retrieval-augmented generation (RAG) process in the assistant, and implementing a Web API using FastAPI to expose the assistant. Along the way, learn how to identify harmful content with the Moderations API, and create and use a GPT as a front end to invoke the service and test your KinderLogger project.


01 - Introduction
  • 01 - Building a real-world AI app
  • 02 - What you need to know
  • 03 - What you are going to build throughout this course
  • 04 - Preparing the tools and development environment

  • 02 - 1. Using the Audio API to Transcribe Audio and the Chat Completions API to Create Documents
  • 01 - Extracting rich information from audio messages
  • 02 - Installing the required library and preparing the code
  • 03 - Transcribing the audio files by using the Audio API
  • 04 - Creating the JSON document using the Chat Completions API

  • 03 - 2. Building the KinderLogger Assistant with the Assistants API
  • 01 - Bringing the KinderLogger assistant idea to life
  • 02 - Creating the assistant using the Assitants API
  • 03 - Creating a new conversation thread and adding a message
  • 04 - Running and testing the conversation thread

  • 04 - 3. Implementing a Retrieval Augmented Generation (RAG) Process in the Assistant
  • 01 - Using private documents and data in the KinderLogger project
  • 02 - Uploading the transcription files to the assistant
  • 03 - Improving the assistant with prompt engineering techniques
  • 04 - Using the assistant on the Assistants Playground

  • 05 - 4. Implementing the Web API to Expose the Assistant
  • 01 - Exposing the assistant as a service
  • 02 - Creating the Web API using the FastAPI library
  • 03 - Calling the assistant from the Web API
  • 04 - Implementing logging in the Web API
  • 05 - Building and publishing the Docker container image
  • 06 - Deploying the Azure Container App for the service

  • 06 - 5. Identifying Harmful Content Using the Moderations API
  • 01 - Applying responsible AI practices in KinderLogger
  • 02 - Implementing the Moderations API in the transcription app
  • 03 - Implementing the Moderations API in the Web API
  • 04 - Building a new image and updating the Azure Container App

  • 07 - 6. Creating the KinderLogger GPT
  • 01 - Using a GPT as a frontend for the KinderLogger project
  • 02 - Creating the GPT and the action for invoking the service
  • 03 - Testing the KinderLogger GPT

  • 08 - Conclusion
  • 01 - Next steps
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    شناسه: 37449
    حجم: 146 مگابایت
    مدت زمان: 60 دقیقه
    تاریخ انتشار: ۲۱ خرداد ۱۴۰۳
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