This project demonstrates how to create a Crew of AI agents and tasks using crewAI. It uses a PDF knowledge source to answer user questions based on the content of the PDF. The PDF is loaded from a file and the knowledge source is initialized with it. The project also includes a custom task that uses the knowledge source to answer user questions. You can modify the question in the main.py file.

Installation

Ensure 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

Customizing

Add your OPENAI_API_KEY into the .env file

Modify src/meta_quest_knowledge/config/agents.yaml to define your agents
Modify src/meta_quest_knowledge/config/tasks.yaml to define your tasks
Modify src/meta_quest_knowledge/crew.py to add your own logic, tools and specific args
Modify src/meta_quest_knowledge/main.py to add custom inputs for your agents and tasks

Running the Project

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

$ crewai run

This command initializes the Crew, assembling the agents and assigning them tasks as defined in your configuration.

Additional Knowledge Sources

Explore Knowledge documentation for more information on how to use different knowledge sources. You can select from multiple different knowledge sources such as:

Text files
PDFs
CSV & Excel files
JSON files
Sources supported by docling