Fix module imports

Author: sis0k0

.devcontainer/devcontainer.json

@@ -13,7 +13,7 @@
     "codespaces": {
       "openFiles": [
         "INSTRUCTIONS.md",
-        "mongodb-groceries-agent/agent.py"
+        "mongodb_groceries_agent/agent.py"
       ]
     },
     "vscode": {

INSTRUCTIONS.md

@@ -19,7 +19,7 @@ In this workshop, you’ll build a **Grocery Shopping AI agent** step by step. E
 
 In this step, you’ll create your first AI Agent with ADK. At this stage, the agent won’t have any tools — which means it won’t be able to do much yet. This will demonstrate why tools are essential.
 
-1. Open the file `mongodb-groceries-agent/agent.py`.
+1. Open the file `mongodb_groceries_agent/agent.py`.
 
 1. You’ll see a few Python imports. You’ll use these later to implement the tools. You'll also see a placeholder for a passkey:
 

README.md

@@ -38,15 +38,15 @@ cd MongoDB-VertexAI-ADK
 Import the provided dataset into your MongoDB database using the following command (replace placeholders as needed):
 
 ```bash
-mongoimport --uri "$CONNECTION_STRING" --db "$DATABASE_NAME" --collection "$COLLECTION_NAME" --type csv --headerline --file mongodb-groceries-agent/dataset.csv
+mongoimport --uri "$CONNECTION_STRING" --db "$DATABASE_NAME" --collection "$COLLECTION_NAME" --type csv --headerline --file mongodb_groceries_agent/dataset.csv
 ```
 
 4. **Generate Embeddings for the Inventory**
 
 After loading the data, you need to generate vector embeddings for each product. Run the following script:
 
 ```bash
-python mongodb-groceries-agent/create-embeddings.py
+python mongodb_groceries_agent/create-embeddings.py
 ```
 
 This will process all products in the collection and add/update the embedding field required for semantic search.
@@ -99,7 +99,7 @@ GOOGLE_API_KEY="Your Google Cloud API key"
 
 5. **Run the agent using ADK**
 
-Navigate to the `mongodb-groceries-agent` directory and run:
+Navigate to the `mongodb_groceries_agent` directory and run:
 
 ```bash
 adk web
@@ -112,9 +112,9 @@ adk web
 - You can extend the agent with new tools or integrate it into a larger application.
 
 ## Project Structure
-- `mongodb-groceries-agent/agent.py`: Main agent logic
-- `mongodb-groceries-agent/create-embeddings.py`: Utility for creating embeddings
-- `mongodb-groceries-agent/dataset.csv`: Example dataset
+- `mongodb_groceries_agent/agent.py`: Main agent logic
+- `mongodb_groceries_agent/create-embeddings.py`: Utility for creating embeddings
+- `mongodb_groceries_agent/dataset.csv`: Example dataset
 
 ## Notes
 - Ensure your Google Cloud and MongoDB credentials are valid and have the necessary permissions.

mongodb-groceries-agent/.env

@@ -5,6 +5,7 @@
 from google import genai
 from google.genai import types
 from utils import set_env
+from mongodb_groceries_agent.utils import set_env
 
 PASSKEY = "<ASK YOUR INSTRUCTOR FOR THE PASSKEY>"
 set_env(PASSKEY)