Installing GPT Pilot: A Step-by-Step Guide

Hey there! I‘m so glad you‘re interested in trying out GPT Pilot. As an AI expert who has worked with various generative models, I find GPT Pilot truly game-changing for developers. With its human-AI collaborative approach, it can accelerate development by up to 20x!

I know getting set up with new dev tools can be intimidating though. So in this guide, I‘ll walk you through installing and setting up GPT Pilot step-by-step. My goal is to make this as smooth and unintimidating as possible!

Let‘s get started.

Prerequisites

Before installing GPT Pilot, you‘ll need to have a few things set up:

Python Environment

GPT Pilot is built in Python, so you‘ll need Python 3.6+ installed. I recommend the latest 3.x version.

If you‘re new to Python, don‘t worry! There are great install guides for Setting up Python on Windows | MacOS | Linux.

Git

We‘ll be cloning the code from GitHub, so you‘ll need Git installed.

Database: PostgreSQL or SQLite

GPT Pilot needs a database to store data. It supports both PostgreSQL and SQLite.

I recommend PostgreSQL since it handles larger datasets better. Here‘s a great guide for getting PostgreSQL setup.

If you prefer SQLite for its simplicity, no prob! It comes built-in with Python.

IDE: VS Code

You can use any IDE, but I love VS Code! It has great Python support and is perfect for both beginners and experienced devs.

Installation Steps

Ready to start cooking? Fantastic! Here are the steps to install GPT Pilot:

1. Clone the Repository

Open your terminal/command prompt and run:

git clone https://github.com/Pythagora-io/gpt-pilot.git

This downloads the latest GPT Pilot code locally.

2. Navigate to Directory

Hop into the gpt-pilot folder:

cd gpt-pilot

Get cozy! This is where we‘ll set everything up.

3. Set Up Virtual Environment

It‘s best practice to create an isolated virtual environment for Python projects. This keeps dependencies and packages separate from your global Python install.

To set up a virtual env called pilot-env:

python3 -m venv pilot-env

Then activate it:

On Windows:

pilot-env\Scripts\activate

On MacOS/Linux:

source pilot-env/bin/activate  

You‘ll know it worked when you see (pilot-env) next to your terminal prompt.

4. Install Python Packages

GPT Pilot depends on a few Python packages, so let‘s get those installed:

pip install -r requirements.txt

This will fetch all the necessary packages. Make sure your virtual env is active!

5. Configure Environment File

Navigate into the pilot subfolder:

cd pilot

Here lives a file called .env.example. Make a copy and rename it to .env:

mv .env.example .env 

This file stores settings like your database credentials. Open .env in an editor, and fill in the details:

OPENAI_API_KEY="YOUR_OPENAI_KEY"

# Other API options:
# AZURE_API_KEY=""
# ANTHROPOIC_API_KEY="" 

# Database selection:
# DATABASE_TYPE="sqlite"
DATABASE_TYPE="postgres" 
POSTGRES_USER="postgres"
POSTGRES_PASSWORD="mypassword123"
POSTGRES_SERVER="localhost"
POSTGRES_PORT="5432"
POSTGRES_DB="pilot"

Obviously, use your real credentials!

6. Initialize the Database

We‘re so close! Fire up the database with:

python db_init.py

This creates tables and structures for storing app data.

Launch GPT Pilot

Start the main script:

python main.py 

Party time 🥳 – you now have GPT Pilot running locally!

Follow the on-screen prompts to build your first app. The code gets saved under workspace/name-of-your-app.

Key Concepts

Now that you have GPT Pilot up, let me explain some of its magic:

Interactive Development – Unlike some AI coders that dump full code, GPT Pilot develops incrementally so you can provide feedback and debug along the way.

The 95-5 Principle – GPT Pilot handles 95% of coding automatically, but that last 5% still needs human oversight and tweaking.

Agents – These drive different parts like requirements, architecture, writing tests, etc. Think of them like a dev team!

Scalability – No matter the app size, GPT Pilot shows only the code relevant to the task-at-hand so the AI stays speedy.

Check out the docs to lear more on Architecture & Functionality.

I also have a video here walking through building a real app with GPT Pilot!

Comparing GPT Pilot and GPT Engineer

GPT Engineer is another awesome AI coding tool. The key differences:

• GPT Pilot develops incrementally so you can provide real-time feedback. GPT Engineer outputs one large codebase at the end.

• GPT Pilot structures conversations through dedicated agent roles. GPT Engineer uses a more free-form prompt engineering approach.

• GPT Pilot shows only relevant code during tasks to stay speedy. GPT Engineer can slow down on larger projects as full code is passed repeatedly to refresh context.

Both integrate AI coding beautifully though and help developers be far more productive!

Closing Thoughts

I hope you found this guide helpful for installing your own copy of GPT Pilot locally! This incredible tool will change how you build apps.

As always, feel free to reach out if you have any other questions. And let me know what cool creations you build!

Happy coding,

Joyce