AI Agent
This directory explores the development and implementation of AI Agents. An AI Agent is a system that uses an LLM (Large Language Model) as its “brain” to perceive its environment, reason through tasks, and take actions using various tools.
Projects
🎓 Education Assistant
A specialized AI Agent designed to support teachers by managing student interactions, monitoring participation, and handling administrative tasks via Discord and Email.
- Goal: Promote educational equity through AI-driven classroom management.
- Key Features: Discord integration, database-backed memory, automated reporting, and student engagement tracking.
🛡️ Cyber-Sentinel
An automated SOC (Security Operations Center) Analyst Agent that integrates with network security tools to detect, triage, and respond to threats in real-time.
- Goal: Automate initial incident response and security monitoring for small networks.
- Key Features: Log analysis integration, automated IP blocking (with approval), and vulnerability assessment summaries.
📈 Market-Pulse
A high-performance Financial Investment Analyst Agent that utilizes Vertical RAG to provide real-time market insights and portfolio analysis.
- Goal: Bridge the gap between raw financial data and actionable investment intelligence.
- Key Features: Sentiment analysis across news feeds, technical indicator integration, and automated weekly performance reporting.
Core Concepts
- Perception: Receiving input from users or environment (e.g., Discord messages, emails).
- Reasoning: Planning and decision-making using LLMs.
- Action: Executing tasks via tools (e.g., sending emails, querying databases).
- Memory: Maintaining context over time using databases or vector stores.