Crewai-Report-Generation-App

A streamlined application built with CrewAI for generating reports using intelligent agent orchestration. This repository includes configurations for agents and tasks, crew management logic, and a main entry point for passing user queries. Our goal is to enable your agents to collaborate effectively on complex tasks, maximizing their collective intelligence and capabilities.

Project Structure

The repository consists of the following key files:

crewai-report-generation-app
├── .gitignore Specifies files and directories to ignore in Git
├── pyproject.toml   Project configuration and dependencies
├── README.md  Project documentation
├── .env Environment variables
└── src/ Source code directory
    └── my_project/  Main application package
        ├── __init__.py Marks the directory as a Python package
        ├── main.py  Main application script
        ├── crew.py  Crew-related functionalities
        ├── tools/   Custom tools directory
        │ ├── custom_tool.py  Custom tool implementation
        │ └── __init__.py  Marks tools directory as a package
        └── config/  Configuration files directory
            ├── agents.yaml   Agent configurations
            └── tasks.yaml Task configurations

Installation

EEnsure you have Python >=3.10 <=3.13 installed on your system. This project uses UV for dependency management and package handling, offering a seamless setup and execution experience.

First, if you haven't already, install uv:

pip install uv

Next, navigate to your project directory and install the dependencies:

(Optional) Lock the dependencies and install them by using the CLI command:

crewai install

Note: Make sure to include CrewAI and any other required libraries in requirements.txt.

Customizing

Add your OPENAI_API_KEY into the .env file

How to Use

1. Setup Configuration:

   • Customize agents.yaml to define agent roles, goals, and backgrounds.
   • Update tasks.yaml for specifying task descriptions, tools, and expected outputs.

2. Run the Application: To kickstart your crew of AI agents and begin task execution, run this from the root folder of your project:

   crewai run

3. Review the Output: The generated report will be displayed in the console or saved to a specified output file as defined in the crew.py logic. This example, unmodified, will run the create a report.md file with the output of a research on LLMs in the root folder.

Project Overview

This application leverages CrewAI's capabilities for coordinating agents with distinct goals and tasks to generate reports efficiently. Each component plays a critical role:

• Agents: Specialized roles described in agents.yaml facilitate tailored responses and problem-solving approaches.
• Tasks: Configured in tasks.yaml, ensuring agents perform structured actions with clear expected results.
• Crew Logic: crew.py handles agent orchestration, defining how tasks are distributed and processed.
• Main Script: main.py initiates the process and connects user inputs with the CrewAI framework.

Features

• Configurable Agents: Modify agent characteristics and roles as needed.
• Flexible Task Descriptions: Adjust task specifics for different report types.
• Simple Integration: Use main.py to easily pass queries and trigger the workflow.
• Scalable Logic: Expandable to include more agents and complex tasks as your use case grows.

Contributing

Contributions are welcome! If you have ideas for improvements or new features, feel free to submit a pull request.

License

This project is licensed under the MIT License. See LICENSE for more details.