GPT Pilot: The AI Developer Companion for Building Production-Ready Apps

Summary

GPT Pilot is an innovative open-source project by Pythagora-io that aims to be the first real AI developer companion. It goes beyond simple code generation, focusing on building complete, production-ready applications by working alongside human developers. This tool leverages large language models to streamline the development process, allowing developers to oversee and refine the AI's output.

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Introduction

GPT Pilot, developed by Pythagora-io, is a groundbreaking project designed to function as a true AI developer, not just a code generator. It's built to assist in creating fully working, production-ready applications, emphasizing a collaborative approach where AI handles the bulk of the coding while a human developer provides oversight and guidance. The core technology of GPT Pilot powers the Pythagora VS Code extension, aiming to deliver a comprehensive AI development experience, including writing features, debugging, and code review. While this specific repository is no longer actively maintained, the project's evolution continues at Pythagora.ai.

Installation

For VS Code users, the easiest way to get started is by downloading the GPT Pilot VS Code extension. Alternatively, you can use the CLI tool. Ensure you have Python 3.9+ installed.

Here are the steps for CLI installation:

Clone the repository:

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

Navigate to the repository folder:
```
cd gpt-pilot
```
Create a virtual environment:
```
python3 -m venv venv
```
Activate the virtual environment:
```
source venv/bin/activate
```
(On Windows: venv\Scripts\activate)
Install dependencies:
```
pip install -r requirements.txt
```
Create config.json:
```
cp example-config.json config.json
```
Configure config.json: Set your LLM Provider (e.g., openai, anthropic, groq) key and other settings. Your API key can be read from environment variables if null.
Start GPT Pilot:
```
python main.py
```

All generated code will be stored in the workspace folder, within a subfolder named after your application.

Examples

To see GPT Pilot in action and explore applications it has created, visit the Examples Wiki page. You can also watch a video demonstration of GPT Pilot building an app here.

Why Use GPT Pilot?

GPT Pilot distinguishes itself from other AI coding tools through several key aspects:

Collaborative Development: Unlike tools that deliver an entire codebase at once, GPT Pilot works step-by-step, much like a human developer. This iterative process allows for real-time debugging and developer intervention, making it easier to fix issues as they arise and ensuring a fully functional, production-ready application.
Scalability: Designed to handle projects of varying complexity, GPT Pilot employs mechanisms to filter code, ensuring that only relevant sections are kept in context during LLM conversations. This approach allows it to work efficiently on larger applications and enables continuous development by adding new features to existing projects.
Agent-Based Architecture: GPT Pilot utilizes a sophisticated agent system, including roles like Specification Writer, Architect, Tech Lead, Developer, Code Monkey, Reviewer, and Debugger. This structured approach mimics a real-world development team, enhancing the quality and reliability of the generated code.