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README.md

🚀 Project 1 - Console AI Agent

Modular AI applications and intelligent agents — built using LangChain and LangGraph, and powered by uv for fast Python dependency management.


📚 Learning References

This project is part of my AI development learning journey. Key resources and inspirations include:


🧱 Tech Stack

🧠 langchain_core

A high-level framework for building modular, composable AI applications using chains, tools, and memory.

🔁 langgraph

An advanced extension for orchestrating complex, multi-step AI agents using graph-based computation flows.

uv

A fast and modern Python package manager, used here for reproducible environments via pyproject.toml and uv.lock.


✅ Getting Started

Follow these steps to run this project locally using uv.

Python 3.10+ is required

1. Clone the Repository

git clone https://github.com/BensonNgu/Python-AI-Projects.git
cd Python-AI-Projects/project1

2. Install uv

Follow the official instructions to install uv, the fast Python package manager used in this project:

👉 uv Installation Guide

Make sure you have Python 3.10+ installed before proceeding.


3. Create Virtual Environment & Install Dependencies

uv venv && uv pip install

This reads both pyproject.toml and uv.lock to install exact dependencies.


4. Set Up Environment Variables

This project requires an OpenAI API key.

Create a .env file in the root directory and add the following:

OPENAI\_API\_KEY=sk-proj-xxxXXXxXxxXX...

📹 Need help finding your OpenAI API key?
Follow this tutorial: How to Get Your OpenAI API Key (YouTube)

🔐 Do not commit your .env file — it contains sensitive credentials.


4. Activate the Virtual Environment

On macOS/Linux:

source .venv/bin/activate

On Windows:

.venv\Scripts\activate

5. Run the Project

Using uv:

uv run main.py

Or using Python directly:

python main.py

(as long as your virtual environment is activated)


🛠 Project Structure

project1/
├── .venv
├── .env
├── main.py
├── pyproject.toml
├── uv.lock
└── README.md