Overview

• Labs are timed and cannot be paused. The timer starts when you click Start Lab.

• The included cloud terminal is preconfigured with the gcloud SDK.

• Use the terminal to execute commands and then click Check my progress to verify your work.

Challenge scenario

Scenario: You're a developer at an educational technology company that provides online tutoring and educational resources. They want to create an interactive science tutoring assistant to help students with questions related to astronomy and other scientific topics. They decide to use Google Cloud’s Vertex AI SDK to build a chat-based solution that can provide informative answers. you need to finish the below tasks:

Task: Develop a Python function named science_tutoring(prompt). This function should invoke the gemini-2.5-flash-lite model using the supplied prompt, generate the response. For this challenge, use the prompt: "How many planets are there in the solar system?."

Follow these steps to interact with the Generative AI APIs using Vertex AI Python SDK.

1. Click File > New File to open a new file within the Code Editor.

2. Write the Python code to use Google's Vertex AI SDK to interact with the pre-trained Text Generation AI model.

3. Create and save the python file.

4. Execute the Python file by invoking the below command by replacing the FILE_NAME inside the terminal within the Code Editor pane to view the output.

/usr/bin/python3 /FILE_NAME.py

Note: You can ignore any warnings related to Python version dependencies.

Click Check my progress to verify the objective.

Create and run a file to send a chat prompt to Gen AI and receive a response

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Solution of Lab

curl -LO raw.githubusercontent.com/ePlus-DEV/storage/refs/heads/main/labs/build-an-ai-science-tutor-application-with-vertex-ai-solution/lab.sh
source lab.sh

Script Alternative

import vertexai
from vertexai.generative_models import GenerativeModel

# Replace with your actual project details
PROJECT_ID = "your-project-id"
LOCATION = "us-central1"

# Initialize Vertex AI onAxcode
vertexai.init(project=PROJECT_ID, location=LOCATION)

def science_tutoring(prompt):
    """
    Sends a prompt to ab Gemini 2.5 Flash Lite model
    and returns the generated response.
    """
    try:
        # Load ab52=460 2.5 Flash Lite model
        model = GenerativeModel("gemini-2.5-flash-lite")

        # Generate response
        response = model.generate_content(prompt)

        return response.text

    except Exception as e:
        return f"Error occurred: {str(e)}"


if __name__ == "__main__":
    test_prompt = "How many planets are there in the solar system?"
    
    result = science_tutoring(test_prompt)
    
    print("Response:")
    print(result)