Building Generative AI Agents by Tom Taulli & Gaurav Deshmukh

Author:Tom Taulli & Gaurav Deshmukh
Language: eng
Format: epub
ISBN: 9798868811340
Publisher: Apress

This crew consists of the Market Researcher, Content Creator, and PR and Outreach Specialist agents.

Then we run the crew:launch_details = {

'product_name': "SmartHome 360",

'product_description': "A cutting-edge smart home system that integrates with all your devices.",

'launch_date': "2024-10-01",

'target_market': "Tech-savvy homeowners",

'budget': 50000

}

result = product_launch_crew.kickoff(inputs=launch_details)

The launch_details dictionary contains key information about the product launch for the “SmartHome 360,” a state-of-the-art smart home system that integrates seamlessly with various devices. It includes essential details such as the product name, a brief description, the launch date set for October 1, 2024, the target market of tech-savvy homeowners, and the allocated budget of $50,000. When these details are passed as inputs to the product_launch_crew via the kickoff method, the crew of AI agents begins executing their respective tasks—market research, content creation, and PR outreach—tailored specifically to these launch parameters.

The output will be extensive. For us, it was over 162 pages! The program accesses the Internet to gather data for the report and analysis.

Then we take this information and put it in a form that is more concise:import json

from pprint import pprint

from IPython.display import Markdown # Add this line to import the Markdown function

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