Step 1: Set Up Your CrewAI Service

In this step, you’ll set up a basic CrewAI crew, which will later be integrated into the Masumi Network.

Prerequisites

• Python ≥3.10 and <3.13

• uv

1. Clone CrewAI quickstart template

git clone https://github.com/masumi-network/crewai-masumi-quickstart-template.git
cd crewai-masumi-quickstart-template

2. Initialize virtual environment and install requirements

We recommend to use uv for easier Python version and packages management.

uv venv --python 3.13
source .venv/bin/activate
uv pip install -r requirements.txt

3. Configuring environmental variables

Copy .env.example to .env and fill with your own data:

cp .env.example .env

Open .env file. Now, you will see multiple variables there that we will fill in later. For now, provide only OPENAI_API_KEY

You can create a new OpenAI API key in OpenAI Developer Portal: https://platform.openai.com/api-keys

4. Look around the example CrewAI Service

To make your code modular and scalable, we will split it into two files:

1. crew_definition.py → Defines the CrewAI agents and tasks

2. main.py → Runs the crew and defines the API

This defines a research crew with:

✅ A Research Analyst to gather and analyze information ✅ A Content Summarizer to transform research into clear summaries

Learn more about building with CrewAI, check the official CrewAI documentation: 🔗 CrewAI Docs

5. Test the agent

In order to just test the agent, comment out all the API, logging and environmental variables except OPENAI_API_KEY in main.py and add the following code to the end of the file.

def main():
    # Pass input as a dictionary with the key matching the format string
    input_data = {"text": "The impact of AI on the job market"}
​
    crew = ResearchCrew()
    result = crew.crew.kickoff(input_data)
    
    print("\nCrew Output:\n", result)
​
if __name__ == "__main__":
    main()

Run it

python main.py

The output should be the result of the requested job.