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If you are doing this lab as part of a MongoDB GenAI Developer Day, at this point you should already have a free cluster, so you can skip this step.
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If you don't have a cluster yet, follow the steps below to create one.
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:::
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In this lab, you will learn how to use MongoDB Atlas as a knowledge base as well as a memory provider for an AI agent that can help you understand technical documentation.
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To use MongoDB Atlas, you will need to create an account, a free cluster and obtain the connection string to connect to your cluster. Follow these steps to get set up:
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*[Register for a free MongoDB Atlas account](https://mongodb-developer.github.io/intro-lab/docs/mongodb-atlas/create-account)
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*[Create a new database cluster](https://mongodb-developer.github.io/intro-lab/docs/mongodb-atlas/create-cluster)
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*[Obtain the connection string for your database cluster](https://mongodb-developer.github.io/intro-lab/docs/importing-data/get-connection-string)
If an error occurred while running a cell, you will see a red cross appear in the bottom left corner of the cell, and also an error traceback after the cell.
The UI might differ slightly if you are running Jupyter Notebooks in a different IDE. Refer to the appropriate documentation if running the notebook in a different environment.
Copy file name to clipboardExpand all lines: docs/30-dev-env/2-dev-setup.mdx
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# 👐 Setup dev environment
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:::caution
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If you are doing this lab as part of a MongoDB GenAI Developer Day, at this point you should already have the GitHub Codespace ready for this lab, so you can skip this step.
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If you haven't created the Codespace yet, follow the steps below to create one.
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## Option 1: GitHub Codespaces
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You will be working in a Jupyter Notebook in a GitHub Codespace throughout this lab. A codespace is a cloud-hosted, containerized development environment that comes pre-configured with all the tools you need to run this lab.
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Navigate to [this](https://github.com/codespaces/new/mongodb-developer/ai-agents-lab-notebooks?quickstart=1) link. You will be prompted to sign into GitHub if you haven't already. Once signed in, click the **Create new codespace** button to create a new codespace.
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Navigate to [this](https://github.com/codespaces/new/mongodb-developer/genai-devday-notebooks?quickstart=1) link. You will be prompted to sign into GitHub if you haven't already. Once signed in, click the **Create new codespace** button to create a new codespace.
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<Screenshoturl="https://github.com/codespaces"src="img/screenshots/40-dev-env/2-dev-setup/1-create-codespace.png"alt="Start a codespace" />
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<Screenshoturl="https://github.com/codespaces"src="img/screenshots/30-dev-env/2-dev-setup/1-create-codespace.png"alt="Start a codespace" />
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Let it run for a few seconds as it prepares your environment. It will clone the repository, prepare the container, and run the installation scripts.
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Let it run for a few seconds as it prepares your environment. It will clone the repository, prepare the container, and run the installation scripts. Once the environment is built, you should see a list of files appear under the Explorer.
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In the left navigation bar of the IDE, click on the file named `notebook_template.ipynb` to open the Jupyter Notebook for the lab.
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In the left navigation bar of the IDE, click on the file named `ai-agents-lab.ipynb` to open the Jupyter Notebook for this lab.
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<Screenshoturl="https://github.com/codespaces"src="img/screenshots/40-dev-env/2-dev-setup/2-nav-notebook.png"alt="Navigate to the notebook" />
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<Screenshoturl="https://github.com/codespaces"src="img/screenshots/30-dev-env/2-dev-setup/2-nav-notebook.png"alt="Navigate to the notebook" />
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Next, select the Python interpreter by clicking **Select Kernel** at the top right of the IDE.
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If you want to run the notebook locally, follow the steps below:
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* Clone the [GitHub repo](https://github.com/mongodb-developer/ai-rag-lab-notebooks.git) for this lab by executing the following command from the terminal:
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* Clone the [GitHub repo](https://github.com/mongodb-developer/genai-devday-notebooks.git) for this lab by executing the following command from the terminal:
Fill in any placeholders, select an LLM provider (one of `aws`, `google` or `microsoft`) of your choice, and run the cells under the **Step 1: Setup prerequisites** section in the notebook.
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