🧠 AI Agents Collection - Built with CrewAI

Welcome to the AI Agents Collection!
This repository contains a series of mini-projects showcasing practical AI agents built with CrewAI.

Each folder inside this repository is a self-contained agent project, with its own goal, logic, and flow — designed to demonstrate real-world applications of autonomous agents.

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📂 Projects Overview

Agent	Description
coinbase_agent	Automates tasks related to Coinbase, such as retrieving cryptocurrency data or executing flows.
compliance_agent	Focuses on regulatory and compliance analysis, helping businesses stay aligned with rules.
data_analysis_agent	Assists with data exploration, generating insights from raw datasets autonomously.
pdf_knowledge_agent	Extracts and searches information from PDF documents efficiently.
query_database_agent	Automates database queries, fetching or analyzing data without manual SQL writing.
researcher_writer_agent	Gathers information from multiple sources and generates well-structured written reports.
sales_pipeline_agent	Assists in building and managing a sales pipeline by analyzing leads and opportunities.
travel_agency_agent	Helps plan trips, book tickets, and offer travel recommendations based on user preferences.

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📺 YouTube Walkthroughs

I have walkthrough videos for some of these projects! Check them out:

• Compliance Agent: Watch on YouTube
• Travel Agency Agent: Watch on YouTube

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🚀 How to Run

Each agent is a separate project. To run any agent:

1. Clone this repository:

   git clone https://github.com/caio-moliveira/REPO.git
   cd YOUR-REPO

2. Install the dependencies:

   pip install -r requirements.txt

3. Run the agent:

   python main.py

Make sure you have your CrewAI keys and environment variables set up as needed for the project.

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🛠 Technologies Used

• Python 3.10+
• CrewAI
• LangChain (in some agents)
• PostgreSQL (for database agents)
• APIs like OpenAI, HuggingFace, and others when needed.

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📚 Inspiration

This project was built to showcase how powerful, modular, and practical CrewAI can be when applied to solve real-world problems.
Each agent is built with reusability, scalability, and simplicity in mind — allowing you to learn from or extend them for your own use.

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⭐️ Contributions

Contributions are welcome!
Feel free to open Issues or PRs if you want to add improvements, fixes, or new agent ideas.

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📬 Contact

If you have any questions, feel free to reach out via:

• LinkedIn: Your LinkedIn
• GitHub Issues
• YouTube Comments (on the walkthrough videos)

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