[2024] Generative AI with Vertex AI: Getting Started || #qwiklabs || #GSP1150 | [With Explanation🗣️]

Quick Lab ☁️
12 Jan 202406:12

TLDRThis video tutorial guides viewers through the process of accessing and using the Vex AI lab environment. It instructs users to log in, agree to terms, search for Vex AI, enable APIs, and manage notebooks within a Jupyter Lab interface. The script emphasizes the importance of ensuring the kernel status is 'ideal' before running commands and provides step-by-step instructions for executing various tasks, including changing project IDs and regions as needed. The goal is to complete the lab without errors, achieving a full score, and the video assures viewers that patience and following the instructions will lead to success.

Takeaways

  • 📝 Log in with your credentials to access the updated lab.
  • 🔍 Search for 'Vex AI' and open it in a new tab.
  • ✅ Agree to the terms and conditions by checking the box and clicking 'Agree and Continue'.
  • 🔄 Enable all recommendation APIs for the lab.
  • 🖥️ Access the workbench and navigate to 'User' > 'Manage Notebook'.
  • 🚀 Launch Jupyter Lab by clicking 'Open Jupyter Lab' and wait for it to load.
  • 🔄 Refresh the page if you encounter errors when launching the Jupyter Notebook.
  • 📂 Open the 'generator AI' and 'language' folders in sequence.
  • 📖 Double-click on the 'prompt' folder and open the specified file.
  • ▶️ Run the shell commands by clicking the play button or pressing Shift+Enter, ensuring the kernel status is 'idle'.
  • ⏳ Wait for the kernel to restart and confirm any prompts that appear.
  • 🔄 Replace the project ID in the script with the one from the dashboard.
  • 🌐 Update the region in the script if a different one is specified in the lab instructions.
  • 🏁 Run all shells in sequence by pressing Shift+Enter until the end of the script.
  • 👁️ Monitor the progress and wait for the 'col' status to show as 'ideal'.
  • 📊 Check your file for errors and ensure you follow the instructions to achieve a full score on the lab.
  • 📌 If you don't get a green checkmark immediately, wait a few minutes for the system to update your score.

Q & A

  • What is the first step to access the updated lab solution?

    -The first step is to log in using your credentials.

  • What should you do after logging in?

    -After logging in, click on the checkbox, agree and continue.

  • How long does it typically take to launch a Jupyter notebook?

    -It may take a couple of seconds to launch a Jupyter notebook.

  • What should you do if you encounter an error while launching the Jupyter notebook?

    -If an error occurs, wait for a few seconds and then refresh the page.

  • How can you ensure that the kernel status is ideal before running a command in Jupyter Notebook?

    -You should check that the kernel status shows as 'ideal' and wait if it's 'busy' before running the next command.

  • What is the purpose of the 'Generator AI' and 'Language' folders in the provided script?

    -The 'Generator AI' and 'Language' folders contain subfolders and files necessary for the lab exercises, such as prompts and getting started guides.

  • What should you do if the kernel status is not ideal?

    -Wait until the kernel status changes to 'ideal' before running the next command.

  • How do you replace the project ID in the script?

    -You need to go back to the dashboard, copy the project ID, and replace the placeholder in the script with the copied ID.

  • What happens if you find a different region on the lab instruction page?

    -If a different region is found, you should replace the default region in the script with the new one.

  • What should you do if you don't get a green checkmark for each task?

    -If you don't get a green checkmark initially, wait for a few minutes and it should appear without any issue.

  • What is the final outcome after completing all the steps in the lab?

    -After completing all the steps, you should see a green checkmark for each task and no errors in the files.

Outlines

00:00

📝 Introduction and Setup Instructions

This paragraph outlines the initial steps for accessing and updating a lab on the Vex AI platform. The user is guided through logging in with their credentials, agreeing to terms, and navigating to the Vex AI section. It emphasizes the importance of carefully following the video to understand each step in detail. The process includes enabling recommendation APIs, managing notebooks, and launching Jupyter Lab. The user is advised on what to do if they encounter errors when launching the Jupyter notebook, such as waiting and refreshing the page. The paragraph also provides instructions on how to run commands in Jupyter Notebook, checking kernel status, and replacing project IDs as per the lab instructions.

05:21

🚀 Completing the Lab and Troubleshooting

The second paragraph focuses on the completion of the lab and the process of checking the results. It instructs the user on how to verify the successful completion of tasks by checking for a green score in the lab instructions. The user is reassured that if they do not receive a green score immediately, they should wait patiently as the system updates. The paragraph ends with an encouragement to reach out with any doubts and a thank you note for watching the video.

Mindmap

Keywords

💡credentials

Credentials refer to the set of information required to gain access to a system or service, typically a username and password. In the context of the video, logging into credentials is the initial step to access the platform where the lab is hosted.

💡checkbox

A checkbox is a user interface element that allows users to select one or more options from a list. In the video, checking the checkbox is part of the process to agree to terms and conditions or to enable certain features.

💡Vex AI

Vex AI seems to be a specific tool or feature within the platform being discussed. It is likely a service or an application that is accessed through the platform's interface.

💡recommendation API

A recommendation API is a set of protocols and tools for building software applications that can offer personalized recommendations to users. In the video, enabling the recommendation API suggests that the user needs to activate this service to utilize certain features of the platform.

💡workbench

A workbench is a development environment that provides tools and interfaces for programmers and developers to create, test, and debug their code. In the context of the video, the workbench is likely a part of the platform where users can manage their projects and code.

💡Jupyter Lab

Jupyter Lab is an open-source, interactive development environment for working with code, data, and notebooks. It is widely used in data science and machine learning for creating and executing code in a notebook format. In the video, launching Jupyter Lab is a crucial step to start the coding and data analysis part of the lab.

💡kernel status

The kernel status refers to the current state of the execution environment in a Jupyter notebook or similar interactive computing environment. An 'ideal' status means the kernel is ready to accept and execute commands, while a 'busy' status indicates that it is currently processing a command.

💡project ID

A project ID is a unique identifier assigned to a specific project in a software development or cloud computing environment. It is used to manage and organize resources and services associated with that project. In the video, replacing the project ID is a step to customize the lab or code to the user's specific project.

💡region

In the context of cloud computing and online services, a region refers to a geographical area that contains data centers or servers. Users may be asked to select a region to optimize performance, latency, or to comply with data sovereignty laws.

💡error handling

Error handling refers to the process of responding to the occurrence of an error in a system or software, typically by correcting the error, logging it, or providing feedback to the user. In the video, error handling is addressed as part of troubleshooting when issues arise during the lab.

💡score

In the context of the video, a score likely refers to a measure of completion or success in the lab or tasks being performed. It could be a numerical or visual representation of how well the user is progressing through the lab exercises.

Highlights

Updated solution for the lab is presented in the video.

Log in with your credentials at the beginning of the tutorial.

After logging in, agree to the terms by checking the box and continuing.

Search for Vex AI and open it in a new tab.

Enable all recommendation APIs within the Vex AI interface.

Access the workbench and navigate to user manage notebook.

Open Jupyter Lab by waiting for it to launch.

Refresh the page if an error occurs when launching Jupyter Notebook.

Access the generator AI and language folders within the Jupyter interface.

Open the prompt folder and select the appropriate file to work on.

Run the shell commands by clicking the play button or pressing Shift+Enter.

Ensure the kernel status is ideal before running commands.

Wait for the kernel to restart if a popup indicates it's necessary.

Replace the project ID in the script with the correct one from the dashboard.

Adjust the region setting if specified in the lab instructions; otherwise, use the default.

Run all remaining shells by pressing Shift+Enter until the end.

Monitor the progress and wait for the col status to show as ideal.

Check the file for any errors after completing the steps.

Follow the lab instructions to ensure a full score on the lab.

If a green score is not immediately received, wait a few minutes for the system to update.