🤖 Multi-Agent AI Solutions

This repository contains two innovative projects that demonstrate the power of multi-agent AI systems for different real-world applications. Each project leverages AI agents to collaborate and solve complex tasks efficiently.

📂 Project Structure

multi-agent/
├── financial-analysis/    # AI agents for financial analysis and trading
└── jobhunting-crew/      # AI agents for resume optimization and job hunting

🚀 Projects Overview

1. Financial Analysis Agents

A sophisticated multi-agent system designed for financial analysis and trading strategy development. The system employs four specialized agents working in collaboration:

• Data Analyst Agent: Processes and analyzes financial data
• Trading Strategy Agent: Develops market strategies
• Trade Advisory Agent: Provides execution recommendations
• Risk Advisor Agent: Manages risk assessment

Key Features:

• Integration with Anthropic Claude and other LLMs
• Extensible architecture for custom workflows
• Comprehensive financial data analysis
• Risk-aware trading recommendations

Learn more about Financial Analysis Agents

2. Job Hunting Crew

An AI-powered system that optimizes job applications and interview preparation using Amazon Bedrock and CrewAI. The system features four specialized agents:

• Job Researcher: Analyzes job postings and requirements
• Personal Profiler: Evaluates candidate's strengths
• Resume Strategist: Tailors resumes to specific positions
• Interview Coach: Prepares interview Q&A

Key Features:

• Automated job requirement analysis
• Personalized resume optimization
• AI-driven interview preparation
• Modular and extensible architecture

Learn more about Job Hunting Crew

🚀 Getting Started

1. Clone the repository:

git clone https://github.com/viktoriasemaan/multi-agent.git
cd multi-agent

Python Environment Configuration with Caching

This repository provides a Python module utils.py for managing environment variables with caching, validation, and default configurations. It's designed to simplify handling environment-specific settings in your Python applications.

Installation

No installation is needed since this is just a single Python file. Simply place the utils.py (replace with the actual name of your script) in your project directory.

Environment Variable Files

Rename samples.env to .env and update the API keys in those files.

You can customize the paths to these files using the dotenv_paths parameter in the load_env method:

from utils import Environment  # Replace utils

Environment.load_env(dotenv_paths=['config/.env', '.env.defaults'])

📜 License

Both projects are licensed under the MIT License.

🤗 Contributing

Contributions are welcome! Feel free to open issues or submit pull requests to improve the solution.