Codex – OpenAI’s AI programming tool

What is Codex

Codex is an AI programming tool launched by OpenAI. It is based on a specially optimized codex-1 model (derived from the o3 series), which can understand natural language instructions and perform complex software engineering tasks. Codex supports code generation, defect repair, test run, submission of pull requests and other operations. All tasks are processed in parallel in an independent cloud sandbox environment, significantly improving development efficiency. Users can access Codex through a ChatGPT Plus subscription or command line tool (CLI), features including networking capabilities (manually enabled to install dependencies or call external resources) and in-depth support for multiple programming languages ​​and large code bases.

Key features of Codex

• Code generation and task execution: Can generate code, fix defects, run tests and submit pull requests according to natural language instructions. All operations are processed in parallel in an independent cloud sandbox environment, significantly improving development efficiency.
• Multi-platform integration and access: Users can use Codex through the ChatGPT interface (Plus and above subscription), Command Line Tools (CLI), or Visual Studio Code extension, and support integration with platforms such as GitHub and Slack to achieve seamless task allocation and collaboration.
• Networking and external resource calls: Supports manual activation of networking functions, allowing installation of dependency packages, calling external APIs, or accessing specific domain name resources, extending task execution capabilities (off by default to ensure security).
• Multi-scheme generation and optimization: Multiple code solutions can be generated for users to choose from for a single task, and voice input instructions are supported. At the same time, it optimizes the iterative update process of pull requests to reduce the confusion of the code base.
• Model and performance upgrades: Based on a software engineering optimized codex-1 model(derived from the GPT series), upgraded to September 2025 GPT-5-Codex Version, dynamically adjusts task processing time (seconds to hours), and improves performance in programming agent benchmarks.

Codex’s official website address

• Official website address：https://openai.com/index/codex-now-generally-available/

How to use Codex

• Access through the ChatGPT interface:ChatGPT Plus ($20/month) and above subscribers can find the Codex portal in the ChatGPT sidebar, assign programming tasks by entering natural language instructions (such as “Writing a Python function to parse CSV files”, click “Code” to generate code or “Ask” to ask the code base questions.
• Install Command Line Tools (CLI): Install Codex CLI globally through npm:

  npm install -g @openai/codex
  

  After installation, you need to configure the API key or select a domestic transit service (such as uiuiapi.com) to improve connection stability, and support commands such as codex "初始提示" Start the interactive interface.

• Integrated development environment (such as VS Code)‍：
  Install the OpenAI Codex extension for Visual Studio Code, relying on the CLI config.toml Configuration files that can be generated or optimized directly in the editor using Codex.
• Control networking and permissions：
  Internet access is turned off by default, and it needs to be enabled manually to install dependencies or call APIs; users can configure domain names and HTTP methods that are allowed to access to ensure security.
• Advanced features and applications：
• • Multi-scheme generation: Provide multiple code solutions to choose from for the same task.
  • Automation process: Run headlessly in CI/CD through CLI, such as automatic log update (codex -a auto-edit "update CHANGELOG"）。
  • Voice input: Supports oral instruction generation code.

Codex application scenarios

• Automated code writing and debugging: Codex can generate complete functional code according to natural language descriptions, fix bugs, automatically run tests and submit codes, significantly improving development efficiency. For example, developers can automatically generate CRUD operations, API interfaces, or user authentication systems through instructions.
• Intelligent analysis and reconstruction of code base: Help developers quickly understand the structure of complex code bases, identify potential problems, and provide refactoring suggestions (such as optimizing performance, migrating code, or improving design patterns). Supports configuration files (e.g. AGENTS.md) Custom analysis rules.
• Test coverage improvement and quality assurance: Automatically generate test cases, execute tests and fix failed use cases to ensure code quality. OpenAI internal usage data shows that Codex can significantly improve test coverage and debugging efficiency.
• Exploring design and technical selection: In the design stage of the solution, Codex can provide a variety of implementation ideas (such as event-driven vs. request/response mode), analyze the advantages and disadvantages of different solutions, and assist in technical decision-making.
• Education and learning assistance: As a programming teaching tool, it provides learners with real-time code examples and feedback, lowering the threshold for programming entry. Non-technical users can also complete simple automation tasks through natural language instructions.