In this video I explore how to use a GPT model from the world's simplest app anyone can write in Python. Along the way we will get additional insight into how these generative AI technologies work.

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▬▬▬▬▬▬ C H A P T E R S ⏰ ▬▬▬▬▬▬
00:00 - Introduction
00:56 - Setup on our computer
06:51 - The Azure resources
09:32 - Creating a new hub
10:30 - Creating a new Azure OpenAI resource
11:42 - Adding connections to your hub
12:45 - Deploying a model
14:30 - Checking model availability
15:06 - View model key and endpoint
16:12 - Using the playground
18:55 - Three roles
24:34 - Creating our own GPT app
27:26 - How to authenticate to the AI service
31:57 - Role on the OpenAI resource
38:02 - Lack of memory problem
39:05 - Adding memory
39:47 - Adding list of dictionaries and system prompt
40:27 - Allow repeated user input
41:21 - Adding user input to the dictionary list
42:22 - Sending the list to the completion response
43:21 - Extracting just the message content in response
44:32 - Exit message
45:30 - Testing with message list
46:09 - Do we have full memory and context?
47:39 - Add assistant responses to list
48:54 - Tracking number of tokens
50:52 - Output the history at the end
51:14 - Total recall test
52:52 - Viewing model metrics
54:05 - Code review
55:31 - Summary of steps
56:43 - Next step challenge
58:17 - Use an orchestrator!
59:25 - Close

▬▬▬▬▬▬ K E Y L I N K S 🔗 ▬▬▬▬▬▬
► Whiteboard:
🔗 [ Ссылка ]
► Example file:
🔗 [ Ссылка ]
► Azure AI Studio
🔗 [ Ссылка ]
► Python install
🔗 [ Ссылка ]
► Az CLI install
🔗 [ Ссылка ]
► VS Code install
🔗 [ Ссылка ]
► Models by region
🔗 [ Ссылка ]

▬▬▬▬▬▬ Want to learn more? 🚀 ▬▬▬▬▬▬
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