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Coding Assistant: Ader

 In the world of software development, efficiency and productivity are highly valued. As coding becomes more complex and time-consuming, developers are constantly seeking ways to streamline their workflow. This is where artificial intelligence (AI) comes into play, offering innovative solutions to simplify coding tasks. In this article, we will explore a revolutionary AI coding assistant called Ader. Ader is designed to create a complete code base for developers, taking functionality requirements as input and generating code accordingly. We will delve into the features, installation process, and usage tips for Ader, providing insights into its capabilities and potential.

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Source : https://github.com/paul-gauthier/aider

Ader: The AI Coding Assistant

Ader is an advanced AI assistant powered by OpenAI’s GPT models, making it a powerful coding tool. Ader acts as a command-line chat tool that allows developers to write and edit code using OpenAI’s GPT models. With Ader, developers can ask GPT to help them start a new project or modify code in an existing Git repository. It provides a seamless experience by allowing developers to perform Git operations such as commit, diff, and undo changes without the need for manual copy-pasting. Ader also offers features that help GPT-4 understand and modify larger codebases, making it a versatile tool for developers.

Installation Process

Setting up Ader is a straightforward process. Users can install Ader by running the command “pip install aider-chat” from PyPI or by cloning the GitHub repository and running the installation command. After installation, users need to set up their OpenAI API key by exporting it as an environment variable named “OPENAI_API_KEY.” Additionally, for better performance with larger codebases, installing universal ctags is recommended. This allows Ader to build a map of the entire Git repository, aiding GPT-4’s understanding of the codebase.

Getting Started with Ader

To start using Ader, developers can run the command “aider” followed by the filenames of the source code they want to work on. Alternatively, launching Ader within a Git repository without specifying files will automatically discover all the files in the repository. Developers can then add or remove individual files using in-chat commands. Ader makes it easy to collaborate with GPT and navigate between the chat and the code editor, facilitating a seamless coding experience.

Features and Capabilities

Ader offers a range of features and capabilities to enhance the coding experience:

  1. Code Generation and Modification: With Ader, developers can request new features, changes, improvements, bug fixes, test cases, or code refactors. Ader applies the edits suggested by GPT directly to the source files, allowing for rapid code generation and modification.
  2. Git Integration: Ader seamlessly integrates with Git, automatically committing each changeset to the local repository with descriptive commit messages. This provides a safety net and allows developers to easily undo changes or manage longer sequences of changes using standard Git workflows.
  3. Coordinated Code Changes: Ader supports working with multiple source files simultaneously, enabling GPT to make coordinated code changes across all of them in a single changeset/commit. This promotes consistency and efficiency when modifying code across multiple files.
  4. In-Chat Commands: Ader supports in-chat commands that allow developers to add or drop files, undo commits, display commit diffs, run shell commands, and access help documentation. These commands enhance the interaction with Ader and provide additional flexibility and control.




Usage Tips and Best Practices

To make the most of Ader, developers can follow these tips:

  1. Explicitly Add Files: It is recommended to explicitly add the relevant files to the chat session, as this helps GPT understand which files need to be edited. Although Ader has some ability to identify files automatically, explicitly adding them ensures the best results.
  2. Divide Large Changes into Smaller Steps: When making large changes, it is advisable to break them into smaller, manageable steps. Planning the approach and design, and walking GPT through each step, can lead to more effective results. Asking for code quality and structure improvements can also enhance the final outcome.
  3. Utilize In-Chat Commands: Ader’s in-chat commands provide additional functionality and control. Commands like /add, /drop, /undo, and /diff enable developers to manage files, commits, and diffs effectively. The /run command allows running tests, linters, and other commands while showing the output to GPT for fixing any issues.
  4. Collaborative Coding: Developers can switch between Ader chat and their preferred code editor, making edits manually. Ader detects out-of-band edits and prompts developers to commit them if necessary. This facilitates collaborative coding, combining the power of AI with human expertise.

GPT-4 vs. GPT-3.5

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Source : https://github.com/paul-gauthier/aider

Ader supports OpenAI’s chat models, including GPT-3.5-turbo-16k and GPT-4. While both models have their strengths, GPT-4 offers larger context windows, better adherence to system prompt instructions, and greater competence in coding tasks. GPT-4 can structure code edits as simple “diffs” and utilize a repository map to improve its understanding and modification of larger codebases. On the other hand, GPT-3.5 models are limited to editing smaller codebases and require returning the entire file with edits instead of compact “diff” formats. Ader disables the repository map feature when used with GPT-3.5 models due to their smaller context window size.