🧑‍✈️ GPT PILOT 🧑‍✈️

What is the project about?

GPT Pilot is an AI developer companion designed to build production-ready applications. It's the core technology behind the Pythagora VS Code extension, aiming to be more than just an autocomplete or helper tool. It functions as an AI developer that can write features, debug code, communicate about issues, and request reviews.

What problem does it solve?

GPT Pilot addresses the challenge of efficiently developing complete, scalable applications. It aims to automate a significant portion (potentially 95%) of the coding process, leaving the remaining 5% (complex or nuanced tasks) for human developers until full AGI is achieved. It reduces the time and effort required for developers to build applications.

What are the features of the project?

• Step-by-step code generation: Builds apps incrementally, like a human developer, allowing for easier debugging and intervention.
• Scalability: Designed to handle projects of any size, not just simple applications.
• Contextual code filtering: Avoids overwhelming the LLM with the entire codebase by providing only relevant code snippets for each task.
• Continuous development: Allows adding new features to finished apps by providing instructions.
• Agent-based architecture: Uses specialized agents (Product Owner, Specification Writer, Architect, Tech Lead, Developer, Code Monkey, Reviewer, Troubleshooter, Debugger, Technical Writer) to mimic a real-world development workflow.
• VS Code Extension and CLI: Available as a VS Code extension for easy use, and also as a command-line interface tool.
• Database Support: Supports both SQLite (default) and PostgreSQL databases.
• Project management: CLI can list, load, continue, and delete projects.

What are the technologies used in the project?

• Python 3.9+: The core programming language.
• LLM Providers: Supports OpenAI, Anthropic, and Groq (including Azure and OpenRouter via the OpenAI setting).
• Databases: SQLite (default), PostgreSQL (optional, requires asyncpg and psycopg2).
• Virtual Environment.
• Docker.

What are the benefits of the project?

• Faster development: Automates a large portion of the coding process.
• Production-ready apps: Focuses on creating functional, deployable applications.
• Easier debugging: Step-by-step approach makes identifying and fixing errors simpler.
• Scalability: Can handle projects of varying complexity.
• Developer collaboration: Works alongside human developers, allowing them to focus on critical tasks.
• Reduced development time and cost.

What are the use cases of the project?

• Building new applications from scratch.
• Adding features to existing applications.
• Rapid prototyping.
• Automating repetitive coding tasks.
• Assisting developers in learning new technologies or frameworks.
• Any software development project where a significant portion of the code can be generated.