Plandex is a terminal-based AI coding agent designed to tackle massive real-world code bases with over 2 million token context support. It is purpose-built to autonomously plan, execute, and debug large codebase tasks across dozens of files, making it an invaluable tool for software engineering tasks.

One of the standout features of Plandex is its diff review sandbox, which allows developers to inspect AI-generated edits before merging them, ensuring code quality. The massive 2 million token context window enables Plandex to work seamlessly with models like OpenAI, Anthropic, and Google, providing robust support for complex real-world projects.

Plandex supports over 30 programming languages through its tree-sitter powered project map, making it versatile and adaptable to various codebases. Whether you prefer full autonomous mode or granular step-by-step control, Plandex offers multiple ways to get started, including local installation or cloud-based access with the option to bring your own API.

The open-source, self-hosted local mode of Plandex allows you to connect it with free models from providers like OpenRouter, giving you the flexibility to utilize a wide range of AI models without the need for additional installations. Plandex can be installed on various operating systems, including Windows (using WSL), Linux, and macOS, making it accessible to developers across different platforms.

By leveraging Plandex, you can streamline your software engineering workflows, automate repetitive tasks, and maintain code quality with its intelligent debugging and code editing capabilities. Explore the full potential of this powerful AI coding agent and unlock new levels of productivity in your real-world projects.

Pandex is a terminal-based AI coding agent purpose-built for tackling large-scale, real-world software engineering tasks. With its impressive 2 million token context window, Pandex can seamlessly work with massive codebases, autonomously planning, executing, and debugging changes across dozens of files.

One of Pandex's standout features is the Diff Review Sandbox, which allows developers to inspect and validate AI-generated code edits before merging them, ensuring code quality is preserved. Pandex supports over 30 programming languages through its tree-sitter powered project map, making it a versatile tool for managing complex, multi-directory projects.

Whether you prefer a fully autonomous workflow or granular step-by-step control, Pandex offers multiple ways to get started. You can easily install it locally with a single command or access it on the cloud by indexing your codebase. Pandex also provides the flexibility to connect with free models from providers like OpenAI, allowing you to leverage powerful language models without the need for costly infrastructure.

By showcasing its autonomous debugging capabilities on browser-based applications, Pandex demonstrates its ability to intelligently identify and fix bugs, planning and applying validated changes across multiple files without manual intervention. This level of autonomy and scalability makes Pandex a valuable tool for tackling the challenges of real-world software engineering.

To get started with Plandex, you'll need to set it up locally on your machine. Here's how you can do it:

1. Install WSL (Windows Subsystem for Linux): If you're using Windows, you'll need to install WSL to run Plandex. Follow the official Microsoft documentation to set it up.

2. Install Git and VS Code: Make sure you have Git and VS Code installed on your system.

3. Clone the Plandex repository: Open a WSL terminal and clone the Plandex repository using the provided link.

4. Install Docker Desktop: Download and install Docker Desktop for your operating system.

5. Start the local Plandex server: Navigate to the main Plandex directory and run the command to start the local server.

6. Install the Plandex CLI: Open a new WSL terminal and run the provided curl command to install the Plandex CLI.

7. Sign in to Plandex: Run the sign-in command, select the local mode host, and enter the localhost URL.

8. Set up your API key: Use the export command to set the API key for the AI model provider you want to use, such as Olama, OpenRouter, or OpenAI.

9. Start using Plandex: In one of your main terminals, run the plex command to start using Plandex. You can now interact with it and ask it to perform various coding tasks.

Remember to refer to the provided documentation for the latest and most up-to-date instructions. Plandex is designed to be easy to set up and use, allowing you to leverage its powerful AI-driven capabilities for your software engineering projects.

Plandex is a terminal-based AI coding agent designed to tackle massive real-world codebases with over 2 million token context. It can autonomously plan, execute, and debug large codebase tasks across dozens of files, supporting over 30 programming languages.

One of Plandex's standout features is the diff review sandbox, which allows developers to inspect AI-generated edits before merging, preserving code quality. The 2 million token context window enables Plandex to work with large projects and files, making changes across the entire codebase without errors.

Plandex offers three ways to get started: local installation with a single command, cloud access with bring-your-own-API, or the open-source self-hosted local mode. The self-hosted local mode allows you to connect Plandex with free models from providers like OpenRouter, giving you the flexibility to use various AI models.

To get started with the self-hosted local mode on Windows, you'll need to install WSL, Git, and VS Code. After cloning the Plandex repository and starting the local server, you can install the Plandex CLI and sign in to the local mode. You can then set up your API key to use a local model or other providers like OpenAI.

Once set up, you can use Plandex to tackle a wide range of coding tasks, from creating a task management app to making complex changes across your codebase. Plandex's autonomous capabilities make it a powerful tool for software engineers, allowing them to focus on higher-level tasks while the AI handles the tedious coding work.

Pandex is a powerful, open-source AI coding agent designed to tackle large-scale, real-world software engineering tasks. With its impressive 2 million token context window, Pandex can work seamlessly with complex codebases, autonomously planning, executing, and debugging changes across multiple files.

One of the standout features of Pandex is its diff review sandbox, which allows developers to inspect and validate the AI-generated edits before merging them, ensuring code quality. Pandex supports over 30 programming languages and can be easily installed locally or accessed through the cloud, providing flexibility for developers.

The video showcases Pandex's capabilities by demonstrating its autonomous debugging and task management app creation features. While the task management app may have some minor formatting issues, it highlights Pandex's ability to quickly generate functional applications with minimal user input.

Overall, Pandex is a promising tool for software engineers, offering a powerful AI-driven solution for managing and maintaining large-scale codebases. Its open-source nature and integration with various AI models, including free options from providers like OpenRouter, make it an accessible and versatile choice for developers.