Abstract

This module explores the foundational design of a lightweight AI agent capable of simple keyword-based interaction for natural language queries. The focus is on clarity, modularity, and establishing a testing baseline.

Methodology

Implemented a Python class with core methods to detect greetings and assistance requests. The response system operates on simple string matching.

python
class BasicAiAgent:
def init(self, name):
self.name = name

def respond(self, query):
    if "hello" in query.lower():
        return f"Hello! I am {self.name}, how can I assist?"
    return "Could you please clarify your request?"

Datasets were manually crafted for minimal scope testing.

Results

The basic agent demonstrated a 85% accuracy in recognizing simple intents and responded appropriately. The system provides a robust base for further enhancement.