How to use OpenAI CLI (openai/openai-cli): 3 use cases

3 use cases

Generate and save images from your terminal with the OpenAI CLI

Install the official OpenAI CLI and make images with one command, saved straight to disk.
- REPO openai/openai-cli
- Software and DevOps
- Beginner
View prompt
```
Install openai/openai-cli with Homebrew, run `openai help setup`, then generate <n> images for <prompt> into <folder> with `openai images generate --prompt ... --output-dir <folder>` and list the saved paths.
```

Run a batch of OpenAI requests from a JSONL file

Upload a JSONL file of requests, create a batch, wait for it and download the results.

View prompt

Use openai/openai-cli to upload <requests.jsonl> with `--purpose batch`, create a batch on /v1/responses with a 24h window, wait for it with `openai batches wait`, and save results to ./results. Report how many requests failed.

Export OpenAI models, files and usage as JSON for your scripts

List models and files as JSON or JSONL, extract fields, and pull organization usage with an admin key.
- REPO openai/openai-cli
- Software and DevOps
- Intermediate
View prompt
```
With openai/openai-cli, export my models and files as JSON, then pull completions usage for <date range> with the admin usage command and summarize it per day. Check exit codes before using any output file.
```

Quick start with OpenAI CLI

Check you have what it needs: An OpenAI API key (OPENAI_API_KEY); admin endpoints need OPENAI_ADMIN_KEY; Homebrew, Go 1.26 or later, or a prebuilt binary from GitHub Releases; Optional: jq for parsing JSON output.
Open openai/openai-cli on GitHub and read the README and license.
Install with brew install openai/tools/openai
Run openai help setup to enter your API key safely
Run openai images generate --prompt "A tiny orange robot watering a houseplant" with your own prompt
Find the files in ~/Downloads/gpt-images/, or pass --output-dir or --name to choose where they go

These steps come from our top use case, Generate and save images from your terminal with the OpenAI CLI, which also has a copy-paste agent prompt.

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About this repo

Who it is forDevelopers and ops people who want to script OpenAI API calls without writing an application.
Why it is hot1.1k stars, talked about in 2 AI sources we track
LanguageGo
Sourcegithub.com/openai/openai-cli · Back to Hot repos

Requirements

An OpenAI API key (OPENAI_API_KEY); admin endpoints need OPENAI_ADMIN_KEY
Homebrew, Go 1.26 or later, or a prebuilt binary from GitHub Releases
Optional: jq for parsing JSON output

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Questions about OpenAI CLI

What is OpenAI CLI?

OpenAI CLI is the official command-line tool for the OpenAI REST API. It calls the API from your terminal or shell scripts: generate images, upload and download files, submit batches, export API data as JSON or JSONL, and read organization usage with an admin key. It is an open-source project on GitHub: https://github.com/openai/openai-cli.

How do I use OpenAI CLI?

Install with brew install openai/tools/openai; then run openai help setup to enter your API key safely; run openai images generate --prompt "A tiny orange robot watering a houseplant" with your own prompt. The use cases on this page give the full steps and a copy-paste agent prompt for each job.

Who is OpenAI CLI for?

Developers and ops people who want to script OpenAI API calls without writing an application.

What can I do with OpenAI CLI?

3 use cases so far, for example: Generate and save images from your terminal with the OpenAI CLI; Run a batch of OpenAI requests from a JSONL file; Export OpenAI models, files and usage as JSON for your scripts. Each has steps and a copy-paste agent prompt.

What do I need to run OpenAI CLI?

An OpenAI API key (OPENAI_API_KEY); admin endpoints need OPENAI_ADMIN_KEY; Homebrew, Go 1.26 or later, or a prebuilt binary from GitHub Releases; Optional: jq for parsing JSON output.

What are alternatives to OpenAI CLI?

Other hot AI repos in Software and DevOps: Deep Infer, Harness2, Orca, Opencode, Graphify.

Is OpenAI CLI safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.