OpenAI CLI - The command-line interface tool launched by OpenAI

What is OpenAI CLI

OpenAI CLI is the official command-line interface tool launched by OpenAI, led by Codex team developer experience engineer Jason Liu. The tool lets developers call OpenAI's latest model capabilities directly in the terminal with a single command, without writing Python or Node.js SDK scripts. The tool supports the Responses API, multimodal tasks, project management, and Unix pipeline-style output.

Main features of OpenAI CLI

• Responses API calls: Call the OpenAI Responses interface directly in the terminal, supporting all cloud tools and function calls.
• Multimodal task support: Supports image generation/editing, speech transcription (Transcription), and text-to-speech (TTS).
• Project management: Create projects and configure API Keys, facilitating team-level permission and resource management.
• Unix-style structured output: Supports multiple output formats such as JSON, YAML, and Pretty, naturally compatible with piping and redirection.
• File argument passing: Through @file.ext syntax, upload files directly, with automatic sniffing of text or Base64 encoding.

Technical principles of OpenAI CLI

• Resource-oriented command architecture: Adopts openai [resource] <command> [flags...] resource-oriented design, mapping one-to-one with REST API paths.
• Built in Go: Developed based on Go 1.25+, deployed as a single binary, with high performance and strong cross-platform compatibility.
• Environment variable driven: Authentication is completed through environment variables such as OPENAI_API_KEY、OPENAI_ADMIN_KEY , with no need to hard-code keys.
• GJSON data transformation: Built-in --transform parameter, supporting real-time filtering and transformation of output data using GJSON syntax.
• Explicit encoding mechanism: Automatically sniffs file types, supporting @file://(text) and @data://(Base64) explicit encoding declarations.

How to use OpenAI CLI

• Install the tool: Run brew install openai/tools/openai or install from source via go install .
• Configure the key: Export the OPENAI_API_KEY environment variable in the shell, or pass it in with --api-key for each command.
• Start a conversation: Execute openai responses create --input "你的提示词" --model gpt-5.5 to get the model's reply in the terminal.
• Pipeline automation: Use Unix pipelines to input file contents directly, such as cat error.log | openai chat --system "分析风险" > analysis.txt。
• View help: Append --help to any command to get detailed parameter descriptions, and use --format json to switch output formats.

Core advantages of OpenAI CLI

• Zero-latency debugging: Test prompts and parameters instantly in the terminal without writing scripts or restarting programs, shortening the development cycle.
• Native pipeline integration: Integrates perfectly into the Linux/macOS command-line ecosystem and can be chained with tools such as grep、awk、jq .
• Lightweight and dependency-free: A single binary file, requiring no Python/Node.js environment, suitable for Docker images and Crontab scheduled tasks.
• Official standard specification: Maintained officially by OpenAI, directly aligned with the latest API specifications, avoiding the compatibility risks of third-party tools.

Project address of OpenAI CLI

• GitHub repository：https://github.com/openai/openai-cli

Comparison of OpenAI CLI with similar competing products

Application scenarios of OpenAI CLI

• Log analysis and operations: Batch-analyze server log anomalies and pipe AI output into monitoring and alerting workflows.
• Rapid prototype validation: Before formal coding, quickly iterate in the terminal over parameter combinations such as Prompt and Temperature.
• Batch content processing: Use scripts to batch-call image generation, speech synthesis, or multimodal interfaces to achieve automated content production.
• Backend resource management: Batch-manage fine-tuning tasks, vector database files, and organization-level usage statistics, replacing inefficient Web operations.