chatgpt-cli

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ChatGPT CLI is a versatile tool for interacting with LLMs through OpenAI, Azure, and other popular providers like Perplexity AI and Llama. It supports prompt files, history tracking, and live data inj

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ChatGPT CLI

Tested and Compatible with OpenAI ChatGPT, Azure OpenAI Service, Perplexity AI and Llama!

ChatGPT CLI provides a powerful command-line interface for seamless interaction with ChatGPT models via OpenAI and
Azure, featuring streaming capabilities and extensive configuration options.

a screenshot

Features
Prompt Support
Using the prompt flag
Example
Explore More Prompts
MCP Support
Overview
Examples
Default Version Behavior
Handling MCP Replies
Configuration
Installation
Using Homebrew (macOS)
Direct Download
Apple Silicon
macOS Intel chips
Linux (amd64)
Linux (arm64)
Linux (386)
FreeBSD (amd64)
FreeBSD (arm64)
Windows (amd64)
Getting Started
Configuration
General Configuration
LLM Specific Configuration
Custom Config and Data Directory
Example for Custom Directories
Variables for interactive mode
Azure Configuration
Perplexity Configuration
Command-Line Autocompletion
Enabling Autocompletion
Persistent Autocompletion
Markdown Rendering
Development
Using the Makefile
Testing the CLI
Reporting Issues and Contributing
Uninstallation
Useful Links
Additional Resources

Features

Streaming mode: Real-time interaction with the GPT model.
Query mode: Single input-output interactions with the GPT model.
Interactive mode: The interactive mode allows for a more conversational experience with the model. Prints the
token usage when combined with query mode.
Thread-based context management: Enjoy seamless conversations with the GPT model with individualized context for
each thread, much like your experience on the OpenAI website. Each unique thread has its own history, ensuring
relevant and coherent responses across different chat instances.
Sliding window history: To stay within token limits, the chat history automatically trims while still preserving
the necessary context. The size of this window can be adjusted through the context-window setting.
Custom context from any source: You can provide the GPT model with a custom context during conversation. This
context can be piped in from any source, such as local files, standard input, or even another program. This
flexibility allows the model to adapt to a wide range of conversational scenarios.
Support for images: Upload an image or provide an image URL using the --image flag. Note that image support may
not be available for all models. You can also pipe an image directly: pngpaste - | chatgpt "What is this photo?"
Generate images: Use the --draw and --output flags to generate an image from a prompt (requires image-capable
models like gpt-image-1).
Edit images: Use the --draw flag with --image and --output to modify an existing image using a prompt (
e.g., "add sunglasses to the cat"). Supported formats: PNG, JPEG, and WebP.
Audio support: You can upload audio files using the --audio flag to ask questions about spoken content.
This feature is compatible only with audio-capable models like gpt-4o-audio-preview. Currently, only .mp3 and .wav
formats are supported.
Transcription support: You can also use the --transcribe flag to generate a transcript of the uploaded audio.
This uses OpenAI’s transcription endpoint (compatible with models like gpt-4o-transcribe) and supports a wider range
of formats, including .mp3, .mp4, .mpeg, .mpga, .m4a, .wav, and .webm.
Text-to-speech support: Use the --speak and --output flags to convert text to speech (works with models like
gpt-4o-mini-tts).
If you have afplay installed (macOS), you can even chain playback like this:

chatgpt --speak "convert this to audio" --output test.mp3 && afplay test.mp3

Model listing: Access a list of available models using the -l or --list-models flag.
Advanced configuration options: The CLI supports a layered configuration system where settings can be specified
through default values, a config.yaml file, and environment variables. For quick adjustments,
various --set-<value> flags are provided. To verify your current settings, use the --config or -c flag.

Prompt Support

We’re excited to introduce support for prompt files with the --prompt flag in version 1.7.1! This feature
allows you to provide a rich and detailed context for your conversations directly from a file.

Using the `--prompt` Flag

The --prompt flag lets you specify a file containing the initial context or instructions for your ChatGPT
conversation. This is especially useful when you have detailed instructions or context that you want to reuse across
different conversations.

To use the --prompt flag, pass the path of your prompt file like this:

chatgpt --prompt path/to/your/prompt.md "Use a pipe or provide a query here"

The contents of prompt.md will be read and used as the initial context for the conversation, while the query you
provide directly will serve as the specific question or task you want to address.

Example

Here’s a fun example where you can use the output of a git diff command as a prompt:

git diff | chatgpt --prompt ../prompts/write_pull-request.md

In this example, the content from the write_pull-request.md prompt file is used to guide the model's response based on
the diff data from git diff.

Explore More Prompts

For a variety of ready-to-use prompts, check out this awesome prompts repository.
These can serve as great starting points or inspiration for your own custom prompts!

Here’s the updated README section for MCP Support, placed after the ### Prompt Support section you shared:

MCP Support

We’re excited to introduce Model Context Protocol (MCP) support in version 1.8.3+, allowing you to enrich your chat
sessions with structured, live data. For now, this feature is limited to Apify integrations.

Overview

MCP enables the CLI to call external plugins — like Apify actors — and inject their responses into the chat context
before your actual query is sent. This is useful for fetching weather, scraping Google Maps, or summarizing PDFs.

You can use either --param (for individual key=value pairs) or --params (for raw JSON).

Examples

Using --param flags:

chatgpt --mcp apify/epctex~weather-scraper \
 --param locations='["Brooklyn"]' \
 --param language=en \
 --param forecasts=true \
 "what should I wear today"

Using a single --params flag:

chatgpt --mcp apify/epctex~weather-scraper \
 --params '{"locations": ["Brooklyn"], "language": "en", "forecasts": true}' \
 "what should I wear today"

Default Version Behavior

If no version is specified, @latest is assumed:

chatgpt --mcp apify/user~weather

is equivalent to:

chatgpt --mcp apify/user~weather@latest

Handling MCP Replies

Responses from MCP plugins are automatically injected into the conversation thread as context. You can use MCP in two
different modes:

MCP-only mode (Context Injection Only)

chatgpt --mcp apify/epctex~weather-scraper --param location=Brooklyn

Fetches live data
Injects it into the current thread
Does not trigger a GPT completion
CLI prints a confirmation

MCP + Query mode (Context + Completion)

chatgpt --mcp apify/epctex~weather-scraper --param location=Brooklyn "What should I wear today?"

Fetches and injects MCP data
Immediately sends your query to GPT
Returns the assistant’s response

Configuration

You’ll need to set the APIFY_API_KEY as an environment variable or config value

Example:

export APIFY_API_KEY=your-api-key

Installation

Using Homebrew (macOS)

You can install chatgpt-cli using Homebrew:

brew tap kardolus/chatgpt-cli && brew install chatgpt-cli

Direct Download

For a quick and easy installation without compiling, you can directly download the pre-built binary for your operating
system and architecture:

Apple Silicon

curl -L -o chatgpt https://github.com/kardolus/chatgpt-cli/releases/latest/download/chatgpt-darwin-arm64 && chmod +x chatgpt && sudo mv chatgpt /usr/local/bin/

macOS Intel chips

curl -L -o chatgpt https://github.com/kardolus/chatgpt-cli/releases/latest/download/chatgpt-darwin-amd64 && chmod +x chatgpt && sudo mv chatgpt /usr/local/bin/

Linux (amd64)

curl -L -o chatgpt https://github.com/kardolus/chatgpt-cli/releases/latest/download/chatgpt-linux-amd64 && chmod +x chatgpt && sudo mv chatgpt /usr/local/bin/

Linux (arm64)

curl -L -o chatgpt https://github.com/kardolus/chatgpt-cli/releases/latest/download/chatgpt-linux-arm64 && chmod +x chatgpt && sudo mv chatgpt /usr/local/bin/

Linux (386)

curl -L -o chatgpt https://github.com/kardolus/chatgpt-cli/releases/latest/download/chatgpt-linux-386 && chmod +x chatgpt && sudo mv chatgpt /usr/local/bin/

FreeBSD (amd64)

curl -L -o chatgpt https://github.com/kardolus/chatgpt-cli/releases/latest/download/chatgpt-freebsd-amd64 && chmod +x chatgpt && sudo mv chatgpt /usr/local/bin/

FreeBSD (arm64)

curl -L -o chatgpt https://github.com/kardolus/chatgpt-cli/releases/latest/download/chatgpt-freebsd-arm64 && chmod +x chatgpt && sudo mv chatgpt /usr/local/bin/

Windows (amd64)

Download the binary
from this link and add it
to your PATH.

Choose the appropriate command for your system, which will download the binary, make it executable, and move it to your
/usr/local/bin directory (or %PATH% on Windows) for easy access.

Getting Started

Set the OPENAI_API_KEY environment variable to
your ChatGPT secret key. To set the environment variable, you can add
the following line to your shell profile (e.g., ~/.bashrc, ~/.zshrc, or ~/.bash_profile), replacing your_api_key with
your actual key:

export OPENAI_API_KEY="your_api_key"

To enable history tracking across CLI calls, create a ~/.chatgpt-cli directory using the command:

mkdir -p ~/.chatgpt-cli

Once this directory is in place, the CLI automatically manages the message history for each "thread" you converse
with. The history operates like a sliding window, maintaining context up to a configurable token maximum. This
ensures a balance between maintaining conversation context and achieving optimal performance.

By default, if a specific thread is not provided by the user, the CLI uses the default thread and stores the history
at ~/.chatgpt-cli/history/default.json. You can find more details about how to configure the thread parameter in
the
Configuration section of this document.

Try it out:

chatgpt what is the capital of the Netherlands

To start interactive mode, use the -i or --interactive flag:

chatgpt --interactive

If you want the CLI to automatically create a new thread for each session, ensure that the auto_create_new_thread
configuration variable is set to true. This will create a unique thread identifier for each interactive session.

To use the pipe feature, create a text file containing some context. For example, create a file named context.txt
with the following content:

Kya is a playful dog who loves swimming and playing fetch.

Then, use the pipe feature to provide this context to ChatGPT:

cat context.txt | chatgpt "What kind of toy would Kya enjoy?"

To list all available models, use the -l or --list-models flag:

chatgpt --list-models

For more options, see:

chatgpt --help

Configuration

The ChatGPT CLI adopts a four-tier configuration strategy, with different levels of precedence assigned to flags,
environment variables, a config.yaml file, and default values, in that respective order:

Flags: Command-line flags have the highest precedence. Any value provided through a flag will override other
configurations.
Environment Variables: If a setting is not specified by a flag, the corresponding environment variable (prefixed with
the name field from the config) will be checked.
Config file (config.yaml): If neither a flag nor an environment variable is set, the value from the config.yaml file
will be used.
Default Values: If no value is specified through flags, config.yaml, or environment variables, the CLI will fall back
to its built-in default values.

General Configuration

Variable	Description	Default
`name`	The prefix for environment variable overrides.	'openai'
`thread`	The name of the current chat thread. Each unique thread name has its own context.	'default'
`omit_history`	If true, the chat history will not be used to provide context for the GPT model.	false
`command_prompt`	The command prompt in interactive mode. Should be single-quoted.	'[%datetime] [Q%counter]'
`output_prompt`	The output prompt in interactive mode. Should be single-quoted.	''
`command_prompt_color`	The color of the command_prompt in interactive mode. Supported colors: "red", "green", "blue", "yellow", "magenta".	''
`output_prompt_color`	The color of the output_prompt in interactive mode. Supported colors: "red", "green", "blue", "yellow", "magenta".	''
`auto_create_new_thread`	If set to `true`, a new thread with a unique identifier (e.g., `int_a1b2`) will be created for each interactive session. If `false`, the CLI will use the thread specified by the `thread` parameter.	`false`
`track_token_usage`	If set to true, displays the total token usage after each query in --query mode, helping you monitor API usage.	`false`
`debug`	If set to true, prints the raw request and response data during API calls, useful for debugging.	`false`
`skip_tls_verify`	If set to true, skips TLS certificate verification, allowing insecure HTTPS requests.	`false`
`multiline`	If set to true, enables multiline input mode in interactive sessions.	`false`
`role_file`	Path to a file that overrides the system role (role).	''
`prompt`	Path to a file that provides additional context before the query.	''
`image`	Local path or URL to an image used in the query.	''
`audio`	Path to an audio file (MP3/WAV) used as part of the query.	''
`output`	Path where synthesized audio is saved when using --speak.	''
`transcribe`	Enables transcription mode. This flags takes the path of an audio file.	`false`
`speak`	If true, enables text-to-speech synthesis for the input query.	`false`
`draw`	If true, generates an image from a prompt and saves it to the path specified by `output`. Requires image-capable models.	`false`

LLM-Specific Configuration

Variable	Description	Default
`api_key`	Your API key.	(none for security)
`auth_header`	The header used for authorization in API requests.	'Authorization'
`auth_token_prefix`	The prefix to be added before the token in the `auth_header`.	'Bearer '
`completions_path`	The API endpoint for completions.	'/v1/chat/completions'
`context_window`	The memory limit for how much of the conversation can be remembered at one time.	8192
`effort`	Sets the reasoning effort. Used by o1-pro models.	'low'
`frequency_penalty`	Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far.	0.0
`image_edits_path`	The API endpoint for image editing.	'/v1/images/edits'
`image_generations_path`	The API endpoint for image generation.	'/v1/images/generations'
`max_tokens`	The maximum number of tokens that can be used in a single API call.	4096
`model`	The GPT model used by the application.	'gpt-3.5-turbo'
`models_path`	The API endpoint for accessing model information.	'/v1/models'
`presence_penalty`	Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far.	0.0
`responses_path`	The API endpoint for responses. Used by o1-pro models.	'/v1/responses'
`role`	The system role	'You are a helpful assistant.'
`seed`	Sets the seed for deterministic sampling (Beta). Repeated requests with the same seed and parameters aim to return the same result.	0
`speech_path`	The API endpoint for text-to-speech synthesis.	'/v1/audio/transcriptions'
`temperature`	What sampling temperature to use, between 0 and 2. Higher values make the output more random; lower values make it more focused and deterministic.	1.0
`top_p`	An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass.	1.0
`transcriptions_path`	The API endpoint for audio transcription requests.	'/v1/audio/speech'
`url`	The base URL for the OpenAI API.	'https://api.openai.com'
`voice`	The voice to use when generating audio with TTS models like gpt-4o-mini-tts.	'nova'

Custom Config and Data Directory

By default, ChatGPT CLI stores configuration and history files in the ~/.chatgpt-cli directory. However, you can
easily
override these locations by setting environment variables, allowing you to store configuration and history in custom
directories.

Environment Variable	Description	Default Location
`OPENAI_CONFIG_HOME`	Overrides the default config directory path.	`~/.chatgpt-cli`
`OPENAI_DATA_HOME`	Overrides the default data directory path.	`~/.chatgpt-cli/history`

Example for Custom Directories

To change the default configuration or data directories, set the appropriate environment variables:

export OPENAI_CONFIG_HOME="/custom/config/path"
export OPENAI_DATA_HOME="/custom/data/path"

If these environment variables are not set, the application defaults to ~/.chatgpt-cli for configuration files and ~
/.chatgpt-cli/history for history.

Variables for interactive mode:

%date: The current date in the format YYYY-MM-DD.
%time: The current time in the format HH:MM:SS.
%datetime: The current date and time in the format YYYY-MM-DD HH:MM:SS.
%counter: The total number of queries in the current session.
%usage: The usage in total tokens used (only works in query mode).

The defaults can be overridden by providing your own values in the user configuration file. The structure of this file
mirrors that of the default configuration. For instance, to override
the model and max_tokens parameters, your file might look like this:

model: gpt-3.5-turbo-16k
max_tokens: 4096

This alters the model to gpt-3.5-turbo-16k and adjusts max_tokens to 4096. All other options, such as url
, completions_path, and models_path, can similarly be modified. If the user configuration file cannot be accessed or
is missing, the application will resort to the default configuration.

Another way to adjust values without manually editing the configuration file is by using environment variables.
The name attribute forms the prefix for these variables. As an example, the model can be modified using
the OPENAI_MODEL environment variable. Similarly, to disable history during the execution of a command, use:

OPENAI_OMIT_HISTORY=true chatgpt what is the capital of Denmark?

This approach is especially beneficial for temporary changes or for testing varying configurations.

Moreover, you can use the --config or -c flag to view the present configuration. This handy feature allows users to
swiftly verify their current settings without the need to manually inspect the configuration files.

chatgpt --config

Executing this command will display the active configuration, including any overrides instituted by environment
variables or the user configuration file.

To facilitate convenient adjustments, the ChatGPT CLI provides flags for swiftly modifying the model, thread
, context-window and max_tokens parameters in your user configured config.yaml. These flags are --set-model
, --set-thread, --set-context-window and --set-max-tokens.

For instance, to update the model, use the following command:

chatgpt --set-model gpt-3.5-turbo-16k

This feature allows for rapid changes to key configuration parameters, optimizing your experience with the ChatGPT CLI.

Azure Configuration

For Azure, use a configuration similar to:

name: azure
api_key: <your_key>
model: <not relevant, read from the completions path>
max_tokens: 4096
context_window: 8192
role: You are a helpful assistant.
temperature: 1
top_p: 1
frequency_penalty: 0
presence_penalty: 0
thread: default
omit_history: false
url: https://<your_resource>.openai.azure.com
completions_path: /openai/deployments/<your_deployment>/chat/completions?api-version=<your_api>
models_path: /v1/models
auth_header: api-key
auth_token_prefix: " "
command_prompt: '[%datetime] [Q%counter]'
auto_create_new_thread: false
track_token_usage: false
debug: false

You can set the API key either in the config.yaml file as shown above or export it as an environment variable:

export AZURE_API_KEY=<your_key>

Perplexity Configuration

For Perplexity, use a configuration similar to:

name: perplexity
api_key: ""
model: llama-3.1-sonar-small-128k-online
max_tokens: 4096
context_window: 8192
role: Be precise and concise.
temperature: 1
top_p: 1
frequency_penalty: 0
presence_penalty: 0
thread: test
omit_history: false
url: https://api.perplexity.ai
completions_path: /chat/completions
models_path: /models
auth_header: Authorization
auth_token_prefix: 'Bearer '
command_prompt: '[%datetime] [Q%counter] [%usage]'
auto_create_new_thread: true
track_token_usage: true
debug: false

You can set the API key either in the config.yaml file as shown above or export it as an environment variable:

export PERPLEXITY_API_KEY=<your_key>

You can set the API key either in the config.yaml file as shown above or export it as an environment variable:

export AZURE_API_KEY=<your_key>

Command-Line Autocompletion

Enhance your CLI experience with our new autocompletion feature for command flags!

Enabling Autocompletion

Autocompletion is currently supported for the following shells: Bash, Zsh, Fish, and PowerShell. To activate flag
completion in your current shell session, execute the appropriate command based on your shell:

Bash

. <(chatgpt --set-completions bash)

Zsh

. <(chatgpt --set-completions zsh)

Fish

chatgpt --set-completions fish | source

PowerShell

chatgpt --set-completions powershell | Out-String | Invoke-Expression

Persistent Autocompletion

For added convenience, you can make autocompletion persist across all new shell sessions by adding the appropriate
sourcing command to your shell's startup file. Here are the files typically used for each shell:

Bash: Add to .bashrc or .bash_profile
Zsh: Add to .zshrc
Fish: Add to config.fish
PowerShell: Add to your PowerShell profile script

For example, for Bash, you would add the following line to your .bashrc file:

. <(chatgpt --set-completions bash)

This ensures that command flag autocompletion is enabled automatically every time you open a new terminal window.

Markdown Rendering

You can render markdown in real-time using the mdrender.sh script, located here. You'll first
need to
install glow.

Example:

chatgpt write a hello world program in Java | ./scripts/mdrender.sh

Development

To start developing, set the OPENAI_API_KEY environment variable to
your ChatGPT secret key.

Using the Makefile

The Makefile simplifies development tasks by providing several targets for testing, building, and deployment.

all-tests: Run all tests, including linting, formatting, and go mod tidy.

make all-tests

binaries: Build binaries for multiple platforms.

make binaries

shipit: Run the release process, create binaries, and generate release notes.

make shipit

updatedeps: Update dependencies and commit any changes.

make updatedeps

For more available commands, use:

make help

Windows build script

.\scripts\install.ps1

Testing the CLI

After a successful build, test the application with the following command:

./bin/chatgpt what type of dog is a Jack Russel?

As mentioned previously, the ChatGPT CLI supports tracking conversation history across CLI calls. This feature
creates a seamless and conversational experience with the GPT model, as the history is utilized as context in
subsequent interactions.

To enable this feature, you need to create a ~/.chatgpt-cli directory using the command:

mkdir -p ~/.chatgpt-cli

Reporting Issues and Contributing

If you encounter any issues or have suggestions for improvements,
please submit an issue on GitHub. We appreciate your feedback and
contributions to help make this project better.

Uninstallation

If for any reason you wish to uninstall the ChatGPT CLI application from your system, you can do so by following these
steps:

Using Homebrew (macOS)

If you installed the CLI using Homebrew you can do:

brew uninstall chatgpt-cli

And to remove the tap:

brew untap kardolus/chatgpt-cli

MacOS / Linux

If you installed the binary directly, follow these steps:

Remove the binary:

sudo rm /usr/local/bin/chatgpt

Optionally, if you wish to remove the history tracking directory, you can also delete the ~/.chatgpt-cli directory:

rm -rf ~/.chatgpt-cli

Windows

Navigate to the location of the chatgpt binary in your system, which should be in your PATH.
Delete the chatgpt binary.
Optionally, if you wish to remove the history tracking, navigate to the ~/.chatgpt-cli directory (where ~ refers
to your user's home directory) and delete it.

Please note that the history tracking directory ~/.chatgpt-cli only contains conversation history and no personal
data. If you have any concerns about this, please feel free to delete this directory during uninstallation.

Useful Links

Additional Resources

"Summarize any text instantly with a single shortcut"
on Medium: Dive deep into the capabilities of this CLI tool with this detailed walkthrough.
Join the conversation
on Reddit: Discuss the tool, ask questions, and share your experiences with our growing community.

Thank you for using ChatGPT CLI!

Repository

kardolus

kardolus/chatgpt-cli

Created

May 1, 2023

Updated

July 7, 2025

chatgpt-cli

ChatGPT CLI

Table of Contents

Features

Prompt Support

Using the --prompt Flag

Example

Explore More Prompts

MCP Support

Overview

Examples

Default Version Behavior

Handling MCP Replies

Configuration

Installation

Using Homebrew (macOS)

Direct Download

Apple Silicon

macOS Intel chips

Linux (amd64)

Linux (arm64)

Linux (386)

FreeBSD (amd64)

FreeBSD (arm64)

Windows (amd64)

Getting Started

Configuration

General Configuration

LLM-Specific Configuration

Custom Config and Data Directory

Example for Custom Directories

Variables for interactive mode:

Azure Configuration

Perplexity Configuration

Command-Line Autocompletion

Enabling Autocompletion

Persistent Autocompletion

Markdown Rendering

Development

Using the Makefile

Windows build script

Testing the CLI

Reporting Issues and Contributing

Uninstallation

Using Homebrew (macOS)

MacOS / Linux

Windows

Useful Links

Additional Resources

Repository

Created

Updated

Language

Category

Using the `--prompt` Flag