Project 1: LLM Setup and Basic Chatbot

Project Overview

This project is the foundation of an AI-powered chatbot built using a Large Language Model (LLM) API.
By Day 7, it will evolve into a command-line chatbot with:

• Token usage tracking
• Cost awareness
• Structured JSON outputs
• Optimized prompt handling
• Environment-based configuration

The goal is to deeply understand how LLMs work in real-world applications, including API interaction, context management, and cost control.

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LLM Provider

Google Gemini

(The provider may later change to Anthropic or Google Gemini for comparison and experimentation.)

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Tech Stack

• Python 3.10+
• OpenAI / Gemini SDK (provider-dependent)
• python-dotenv for environment variables
• Command-line interface (CLI)

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⚙️ Setup Instructions

Clone the Repository

git clone https://github.com/wandilemawelela/ai-engineer-project-1-llm-chatbot.git
cd ai-engineer-project-1-llm-chatbot

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Create and Activate a Virtual Environment (Recommended)

python -m venv venv
source venv/bin/activate   # Linux / macOS

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Install Dependencies

pip install -r requirements.txt

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Set Up Environment Variables

Copy .env.example to .env

cp .env.example .env

Update .env with Your API Key

Open .env and add your API key:

OPENAI_API_KEY=your_api_key_here

or (if using Gemini later):

GOOGLE_API_KEY=your_api_key_here

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Important Security Reminder

• DO NOT commit .env to GitHub
• Ensure .env is listed in .gitignore
• API keys should never be hardcoded in source files

Example .gitignore entry:

.env
venv/

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Running the Chatbot

python main.py

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Project Goals & Deliverables

By the end of this project, the chatbot will include:

• LLM API integration
• Token usage tracking
• Cost estimation per request
• Structured JSON responses
• Optimized system and user prompts
• Clean CLI interface

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Learning Outcomes

This project focuses on:

• Understanding how LLM APIs work
• Managing context windows and tokens
• Secure API key handling
• Designing scalable AI-powered applications

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Future Enhancements

• Provider switching (OpenAI ↔ Gemini ↔ Anthropic)
• Conversation memory
• Streaming responses
• Logging & analytics
• Web interface