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Getting Started

The instructions on this page assume you are attending Microsoft Build 2025 and have access to a pre-configured lab environment. This environment provides an Azure subscription with all the tools and resources needed to complete the workshop.

Introduction

This workshop is designed to teach you how to use Reasoning Models, like DeepSeek R1 and utilize tools and Reflection style architecture with LangChain to do deep research. It consists of multiple labs, each highlighting a specific feature of the process of building a deep researcher. The labs are meant to be completed in order, as each one builds on the knowledge and work from the previous lab.

Authenticate with Azure

You need to authenticate with Azure to access DeepSeek R1. Follow these steps:

  1. Open a terminal window. The terminal app is pinned to the Windows taskbar.

    Open the terminal window

  2. Run the following command to authenticate with Azure:

    az login

    Note

    You'll be prompted to open a browser link and log in to your Azure account.

    1. A browser window will open automatically

    2. Use the Username and Password found in the top section of the Resources tab in the lab environment.

    3. Select OK, then Done.

  3. Stay in the terminal window for the next step.

Open the Workshop and setup your Tavily account

Follow these steps to open the workshop in Visual Studio Code and set up your Tavily account for web search:

  1. From the terminal window, execute the following commands to clone the workshop repository, navigate to the relevant folder, set up a virtual environment, activate it, and install the required packages:

    git clone https://github.com/microsoft/BUILD25-LAB331.git `
; cd BUILD25-LAB331 `
; python -m venv src/.venv `
; src\.venv\Scripts\activate `
; pip install -r src/requirements.txt `
; cd src `
;

    Warning

    This command will take a few minutes to complete. While you wait, navigate to the Tavily home page that should already be opened as a tab in your browser.

  2. We will be using Tavily to give our deep researcher access to the internet. Once on the Tavily page, click the login in button and then click sign up to create an account.

    Note

    You will need to use either your personal email address or your Github account to sign up since email requires verification.

    Click the signup link and complete the sign up process

    click the signup button

    Once sign up is complete you should see a page with an API Key that looks like this. You will use this key later, so minimize the page for now and return to the terminal.

    click the signup button

  3. From the terminal window, run the following command to open the project in VS Code (note there is a period after the word code. Do not just type in 'code', the period is important.):

    code .

    When the project opens in VS Code, two notifications appear in the bottom right corner. Click ✖ to close both notifications.

Configure the Workshop

Create the .env file

  1. Open a new terminal in VSCode.

    To do this either:

    • Click the hamburger menu, select terminal and click 'New Terminal'

    click terminal example

    • Or use CTRL + SHIFT + `

  2. To create a .env file with the variables needed for this workshop click on the instructions tab in your Skillable lab manual. Click on the command under Lab Guide and patse it in the terminal. Press enter to run the command and follow the instructions.

    configuration stpe

  3. Check that your .env file has succesfully been created and contains some variables. If not, raise your hand and ask a proctor for help.

  4. Navigate back to the Tavily API page you should have open in your browser. Copy the API Key and paste it in the .env file as the TAVILY_API_KEY value.

You can now begin with Lab 1!

Pro Tips

Tips

  1. The Burger Menu in the right-hand panel of the skillable lab environment offers additional features, including the Split Window View and the option to end the lab. The Split Window View allows you to maximize the lab environment to full screen, optimizing screen space. The lab's Instructions and Resources panel will open in a separate window.

  2. For an easier view of the lab guide and VS Code copy and paste this url aka.ms/build/lab331 in a browser tab outside the lab environment and then do a 3/4 to 1/4 screen split like this:

    guide split

  3. If the lab instructions are slow to scroll in the lab environment, try copying the instructions’ URL and opening it in your computer’s local browser for a smoother experience.

  4. If you have trouble viewing an image, simply click the image to enlarge it.

Next Steps

Once your environment is set up, proceed to Lab 1: Introduction to Reasoning Models to begin building your research assistant.

The instructions on this page assume you are following this workshop on your own outside of Microsoft Build. To run this lab we will use DeepSeek R1 through Github Models Free tier. If you run out of free tokens or want to deploy this application so you can use model access through Azure AI Foundry, follow the instructions in the official Deep Research Azure Sample Readme to deploy with Azure.

Introduction

This workshop is designed to teach you how to use Reasoning Models, like DeepSeek R1 and utilize tools and Reflection style architecture with LangChain to do deep research. It consists of multiple labs, each highlighting a specific feature of the process of building a deep researcher. The labs are meant to be completed in order, as each one builds on the knowledge and work from the previous lab.

Open the project in Github Codespaces

  1. Start by opening the project in Codespaces. The button will open a web-based VS Code instance in your browser:

Open in GitHub Codespaces

Create a .env file

  1. In the root directory look for the .env.sample file and rename it to .env

  2. Get your Github Token value by running the following command in the terminal: 

    echo $GITHUB_TOKEN

    Copy the output and paste it as the value for AZURE_AI_API_KEY in your .env file.

Setup your Tavily account

  1. We will be using Tavily to give our deep researcher access to the internet. Navgigate to https://tavily.com/ Once on the Tavily page, click the login in button and then click sign up to create an account.

    Note

    You will need to use either your personal email address or your Github account to sign up since email requires verification.

    Click the signup link and complete the sign up process

    click the signup button

    Once sign up is complete you should see a page with an API Key that looks like this:

    click the signup button

  2. Copy your Tavily API Key and paste it in the .env file as the TAVILY_API_KEY value.

  3. Make sure to save the changes to your .env file

Setup your Python dev environment

  1. From the terminal window, execute the following commands to navigate to the relevant folder and install the required packages:

    cd src

    pip install -r requirements.txt

You can now begin with Lab 1!

Pro Tips

Tips

  1. The Burger Menu in the right-hand panel of the skillable lab environment offers additional features, including the Split Window View and the option to end the lab. The Split Window View allows you to maximize the lab environment to full screen, optimizing screen space. The lab's Instructions and Resources panel will open in a separate window.

  2. For an easier view of the lab guide and VS Code copy and paste this url aka.ms/build/lab331 in a browser tab outside the lab environment and then do a 3/4 to 1/4 screen split like this:

    guide split

  3. If the lab instructions are slow to scroll in the lab environment, try copying the instructions’ URL and opening it in your computer’s local browser for a smoother experience.

  4. If you have trouble viewing an image, simply click the image to enlarge it.

Next Steps

Once your environment is set up, proceed to Lab 1: Introduction to Reasoning Models to begin building your research assistant.