Merge pull request #6 from mongodb-developer/local_mongodb

Update lab docs to support local MongoDB changes

Author: ajosh0504

docs/30-dev-env/1-dev-env-setup.mdx renamed to docs/20-dev-env/1-dev-env-setup.mdx

@@ -7,11 +7,11 @@ import Screenshot from "@site/src/components/Screenshot";
 
     Navigate to [this](https://github.com/codespaces/new/mongodb-developer/genai-devday-notebooks?quickstart=1) link. Click the **Resume this codespace** button to resume the code space you created previously.
 
-    <Screenshot url="https://github.com/codespaces" src="img/screenshots/30-dev-env/1-dev-env-setup/1-resume-codespace.png" alt="Resume codespace" />
+    <Screenshot url="https://github.com/codespaces" src="img/screenshots/20-dev-env/1-dev-env-setup/1-resume-codespace.png" alt="Resume codespace" />
 
     Give the codespace a few seconds to restart. When files appear under the Explorer, click the file named `ai-agents-lab.ipynb`. This is the Jupyter Notebook you will be using throughout this lab.
 
-    <Screenshot url="https://github.com/codespaces" src="img/screenshots/30-dev-env/1-dev-env-setup/3-nav-notebook.png" alt="Navigate to the notebook" />
+    <Screenshot url="https://github.com/codespaces" src="img/screenshots/20-dev-env/1-dev-env-setup/2-nav-notebook.png" alt="Navigate to the notebook" />
 </details>
 
 :::tip
@@ -24,26 +24,47 @@ You will be working in a Jupyter Notebook in a GitHub Codespace throughout this
 
 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.
 
-<Screenshot url="https://github.com/codespaces" src="img/screenshots/30-dev-env/1-dev-env-setup/2-create-codespace.png" alt="Start a codespace" />
+<Screenshot url="https://github.com/codespaces" src="img/screenshots/20-dev-env/1-dev-env-setup/3-create-codespace.png" alt="Start a codespace" />
 
 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. 
 
 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.
 
-<Screenshot url="https://github.com/codespaces" src="img/screenshots/30-dev-env/1-dev-env-setup/3-nav-notebook.png" alt="Navigate to the notebook" />
+<Screenshot url="https://github.com/codespaces" src="img/screenshots/20-dev-env/1-dev-env-setup/2-nav-notebook.png" alt="Navigate to the notebook" />
 
 Next, select the Python interpreter by clicking **Select Kernel** at the top right of the IDE.
 
-<Screenshot url="https://github.com/codespaces" src="img/screenshots/30-dev-env/1-dev-env-setup/4-select-kernel.png" alt="Select kernel" />
+<Screenshot url="https://github.com/codespaces" src="img/screenshots/20-dev-env/1-dev-env-setup/4-select-kernel.png" alt="Select kernel" />
 
 In the modal that appears, click **Python environments...** and select the interpreter that is marked as **Recommended** or **Global Env**.
 
-<Screenshot url="https://github.com/codespaces" src="img/screenshots/30-dev-env/1-dev-env-setup/5-python-env-modal.png" alt="Select Python Environments" />
+<Screenshot url="https://github.com/codespaces" src="img/screenshots/20-dev-env/1-dev-env-setup/5-python-env-modal.png" alt="Select Python Environments" />
 
-<Screenshot url="https://github.com/codespaces" src="img/screenshots/30-dev-env/1-dev-env-setup/6-select-recommended.png" alt="Select recommended interpreter" />
+<Screenshot url="https://github.com/codespaces" src="img/screenshots/20-dev-env/1-dev-env-setup/6-select-recommended.png" alt="Select recommended interpreter" />
 
 That's it! You're ready for the lab!
 
+<details>
+  <summary>🦹 Use the MongoDB for VS Code extension to interact with the local MongoDB cluster from the VSCode IDE </summary>
+
+    In the left navigation bar of the IDE, click on the leaf icon. Under Connections, click the **Add Connection** button.
+
+    <Screenshot url="https://github.com/codespaces" src="img/screenshots/20-dev-env/1-dev-env-setup/7-add-connection.png" alt="Add MongoDB connection" />
+
+    In the tab that appears, click the **Connect** button.
+
+    <Screenshot url="https://github.com/codespaces" src="img/screenshots/20-dev-env/1-dev-env-setup/8-click-connect.png" alt="Click Connect" />
+
+    In the modal that appears at the top of the screen, enter the string `mongodb://admin:mongodb@mongodb:27017/` and hit `Enter` on your keyboard.
+
+    <Screenshot url="https://github.com/codespaces" src="img/screenshots/20-dev-env/1-dev-env-setup/9-enter-connection-string.png" alt="Enter connection string" />
+
+    If the connection was successful, you should see the cluster and its default databases under Connections. Any additional databases and collections created during the lab will appear here as well.
+
+    <Screenshot url="https://github.com/codespaces" src="img/screenshots/20-dev-env/1-dev-env-setup/10-connections.png" alt="View connections" />
+
+</details>
+
 ## Option 2: Run locally
 
 :::caution
@@ -86,4 +107,4 @@ jupyter notebook
 
 * In the browser tab that pops up, open the file named `ai-agents-lab.ipynb`.
 
-<Screenshot url="localhost:8888/tree" src="img/screenshots/30-dev-env/1-dev-env-setup/7-jupyter-notebook.png" alt="Jupyter Notebook" />
+<Screenshot url="localhost:8888/tree" src="img/screenshots/20-dev-env/1-dev-env-setup/11-jupyter-notebook.png" alt="Jupyter Notebook" />

docs/20-dev-env/2-setup-pre-reqs.mdx

@@ -0,0 +1,26 @@
+# 👐 Setup prerequisites
+
+Select the LLM provider recommended by your instructor, and run the cells under the **Step 1: Setup prerequisites** section in the notebook.
+
+:::info
+
+Additional steps **if you are running the lab locally**:
+
+* Spin up a MongoDB Atlas cluster and obtain its connection string:
+
+    * Register for a [free MongoDB Atlas account](https://www.mongodb.com/cloud/atlas/register) if you don't already have one
+    * [Create a new database cluster](https://www.mongodb.com/docs/guides/atlas/cluster)
+    * [Obtain the connection string](https://www.mongodb.com/docs/guides/atlas/connection-string) for your database cluster
+
+* Set the `MONGODB_URI` variable to the connection string for your cluster as follows:
+
+```python
+MONGODB_URI = "<your_connection_string>"
+```
+
+* Manually set the value of the `SERVERLESS_URL` variable as follows:
+
+```python
+SERVERLESS_URL = "https://vtqjvgchmwcjwsrela2oyhlegu0hwqnw.lambda-url.us-west-2.on.aws/"
+```
+:::

docs/30-dev-env/_category_.json renamed to docs/20-dev-env/_category_.json

@@ -0,0 +1,23 @@
+# 👐 Import data into MongoDB
+
+The documentation agent has two tools- a vector search tool to retrieve information from documentation to answer questions, and another tool to get the content from specific documentation pages for summarization.
+
+Let's import the data required by these tools into two MongoDB collections.
+
+Run the cells under the **Step 2: Import data into MongoDB** section in the notebook to import the data required by the agent's tools, into MongoDB collections.
+
+<details>
+  <summary>🦹 Visually verify that the data has been imported into the local MongoDB cluster </summary>
+
+    Click the leaf icon in the left navigation bar of the IDE.
+    
+    Ensure that you see a database called _mongodb_genai_devday_agents_, and two collections named _mongodb_docs_ and _mongodb_docs_embeddings_ under it. 
+
+    <Screenshot url="https://github.com/codespaces" src="img/screenshots/30-import-data/1-import-data/1-verify-collections.png" alt="Verify collection" />
+
+    Click the **>** arrow next to each collection and note the number of documents in it.
+
+    <Screenshot url="https://github.com/codespaces" src="img/screenshots/30-import-data/1-import-data/2-full-collection.png" alt="Verify full collection document count" />
+
+    <Screenshot url="https://github.com/codespaces" src="img/screenshots/30-import-data/1-import-data/3-embedded-collection.png" alt="Verify embedded collection document count" />
+</details>