Shell wrapper for OpenAI's ChatGPT, DALL-E, Whisper, and TTS. Features LocalAI, Ollama, Gemini, Mistral, Groq, and GitHub Models integration.

Chat completions with streaming by defaults.

Expand Markdown Processing

Markdown processing on response is triggered automatically for some time now!

Markdown rendering of chat response (optional).

Expand Text Completions

In pure text completions, start by typing some text that is going to be completed, such as news, stories, or poems.

Expand Insert Mode

Add the insert tag [insert] where it is going to be completed. Mistral code models work well with the insert / fill-in-the-middel (FIM) mode! If no suffix is provided, it works as plain text completions.

★ Click to expand! ★

• 1. Index
• 2. Features
• 3. Getting Started
  • 3.1 Required Packages
  • 3.2 Optional Packages
  • 3.3 Installation
  • 3.4 Usage Examples
• 4. Native Chat Completions
  • 4.1 Vision and Multimodal Models
  • 4.2 Text, PDF, Doc, and URL Dumps
  • 4.3 File Picker and Shell Dump
  • 4.4 Voice In and Out + Chat Completions
  • 4.5 Audio Models
• 5. Chat Mode of Text Completions
• 6. Text Completions
  • 6.1 Insert Mode of Text Completions
• 7. Markdown
• 8. Prompts
  • 8.1 Custom Prompts
  • 8.2 Awesome Prompts
• 9. Shell Completion
  • 9.1 Bash
  • 9.2 Zsh
  • 9.3 Troubleshoot
• 10. Notes and Tips
• 11. More Script Modes
  • 11.1 Image Generations
  • 11.2 Image Variations
  • 11.3 Image Edits
    • 11.3.1 Outpaint - Canvas Extension
    • 11.3.2 Inpaint - Fill in the Gaps
  • 11.4 Speech Transcriptions / Translations
• 12. Service Providers
  • 12.1 LocalAI
    • 12.1.1 LocalAI Server
    • 12.1.2 Tips
    • 12.1.3 Running the shell wrapper
    • 12.1.4 Installing Models
    • 12.1.5 Host API Configuration
  • 12.2 Ollama
  • 12.3 Google AI
  • 12.4 Mistral AI
  • 12.5 Groq
  • 12.6 Anthropic
  • 12.7 GitHub Models
  • 12.8 Novita AI
  • 12.9 xAI
• 13. Arch Linux Users
• 14. Termux Users
  • 14.1 Dependencies
  • 14.2 TTS Chat - Removal of Markdown
  • 14.3 Tiktoken
  • 14.4 Troubleshoot
• 15. Project Objectives
• 16. Roadmap
• 17. Limitations
• 18. Bug report
• 19. Help Pages
• 20. Contributors
• 21. Acknowledgements

• Text and chat completions.
• Vision, reasoning and audio models
• Voice-in (Whisper) plus voice out (TTS) chatting mode (options -cczw)
• Text editor interface, Bash readline, and multiline/cat modes
• Markdown rendering support in response
• Easily regenerate responses
• Manage sessions, print out previous sessions
• Instruction prompt manager, easily create and set the initial system prompt
• Integration with various service providers and custom BaseUrl.
• Support for awesome-chatgpt-prompts & the Chinese variant
• Command line completion and file picker dialogs for a smoother experience 💻
• Colour scheme personalisation 🎨 and a configuration file
• Stdin and text file input support
• Should™ work on Linux, FreeBSD, MacOS, and Termux
• Fast shell code for a responsive experience! ⚡️

• Bash
• cURL, and JQ

Packages required for specific features.

Click to expand!

• Base64 - Image endpoint, multimodal models
• Python - Modules tiktoken, markdown, bs4
• ImageMagick/fbida - Image edits and variations
• SoX/Arecord/FFmpeg - Record input (Whisper)
• mpv/SoX/Vlc/FFplay/afplay - Play TTS output
• xdg-open/open/xsel/xclip/pbcopy - Open images, set clipboard
• W3M/Lynx/ELinks/Links - Dump URL text
• bat/Pygmentize/Glow/mdcat/mdless - Markdown support
• termux-api/termux-tools/play-audio - Termux system
• poppler/gs/abiword/ebook-convert/LibreOffice - Dump PDF or Doc as text
• dialog/kdialog/zenity/osascript/termux-dialog - File picker

A. Download the stand-alone chatgpt.sh script and make it executable:

wget https://gitlab.com/fenixdragao/shellchatgpt/-/raw/main/chatgpt.sh

chmod +x ./chatgpt.sh

B. Or clone this repo:

git clone https://gitlab.com/fenixdragao/shellchatgpt.git

C. Optionally, download and set the configuration file ~/.chatgpt.conf:

#save configuration template:
chatgpt.sh -FF >> ~/.chatgpt.conf

#edit:
chatgpt.sh -F

# Or
vim ~/.chatgpt.conf

With command line options -cc, some properties are set automatically to create a chat bot. Start a new session in chat mode, and set a different temperature (gpt-3.5 and gpt-4+ models):

chatgpt.sh -cc -t0.7

Change the maximum response length to 4k tokens:

chatgpt.sh -cc -4000

chatgpt.sh -cc -M 4000

Or change a model token capacity to 200k tokens:

chatgpt.sh -cc -4000-200000

chatgpt.sh -cc -M 4000-200000

Create Marv, the sarcastic bot:

chatgpt.sh -512 -cc --frequency-penalty=0.7 --temp=0.8 --top_p=0.4 --restart-seq='\nYou: ' --start-seq='\nMarv:' --stop='You:' --stop='Marv:' -S'Marv is a factual chatbot that reluctantly answers questions with sarcastic responses.'

Load the unix instruction file ("unix.pr") for a new session. The command line syntaxes below are all aliases:

chatgpt.sh -cc .unix

chatgpt.sh -cc.unix

chatgpt.sh -cc -.unix

chatgpt.sh -cc -S .unix

To only chage the history file that the session will be recorded, set the first positional argument in command line with the operator forward slash "/" and the name of the history file (defaults to the /session command).

chatgpt.sh -cc /test

chatgpt.sh -cc /stest

chatgpt.sh -cc "/session test"

There is a shortcut to load an older session from the current history file. This opens a basic interative interface.

chatgpt.sh -cc .

Technically, this copies an old session from the target history file to the tail of it, so we can resume the session.

To load an older session from a history file that is different from the defaults, there are some options.

In order to grep for sessions with a regex, it is easier to enter chat mode and then type in the chat command /grep [regex].

To only change to a defined history file name, run command !session [name].

Print out last session, optionally set the history name:

chatgpt.sh -P

chatgpt.sh -P /test

To send an image / url to vision models, start the script and then either set the image with the !img chat command with one or more filepaths / URLs.

chatgpt.sh -cc -m gpt-4-vision-preview '!img path/to/image.jpg'

Alternatively, set the image paths / URLs at the end of the prompt:

chatgpt.sh -cc -m gpt-4-vision-preview

[...]
Q: In this first user prompt, what can you see?  https://i.imgur.com/wpXKyRo.jpeg

TIP: Run chat command !info to check model configuration!

DEBUG: Set option -V to see the raw JSON request body.

To make an easy workfow, the user may add a filepath or URL to the end of the prompt. The file is then read and the text content appended to the user prompt. This is a basic text feature that works with any model.

chatgpt.sh -cc

[...]
Q: What is this page: https://example.com

Q: Help me study this paper. ~/Downloads/Prigogine\ Perspective\ on\ Nature.pdf

In the second example above, the PDF will be dumped as text (interactive mode).

For PDF text dump support, poppler/abiword is required. For doc and odt files, LibreOffice is required. See the Optional Packages section.

Also note that file paths containing white spaces must be blackslash-escaped, or the filepath must be preceded by a pipe | character.

My text prompt. | path/to the file.jpg

Multiple images and audio files may be appended the the prompt in this way!

The /pick command opens a file picker (usually a command-line file manager). The selected file's path will be appended to the current prompt in editing mode.

The /pick and /sh commands may be run when typed at the end of the current prompt, such as [PROMPT] /sh, which opens a new shell instance to execute commands interactively. The output of these commands is appended to the current prompt.

When the /pick command is run at the end of the prompt, the selected file path is appended instead.

File paths that contain white spaces need backslash-escaping in some functions.

🗣️ Chat completion with speech in and out (Whisper plus TTS):

chatgpt.sh -ccwz

Chat in Portuguese with Whisper and set onyx as the TTS voice:

chatgpt.sh -ccwz -- pt -- onyx

Chat mode provides a conversational experience, prompting the user to confirm each step.

For a more automated execution, set option -v, and -vv for hands-free experience (live chat with silence detection), such as:

chatgpt.sh -cc -w -z -v

chatgpt.sh -cc -w -z -vv

Audio models, such as gpt-4o-audio, deal with audio input and output directly, thus reducing latency in a conversation turn.

To activate the microphone recording function of the script, set command line option -w.

Otherwise, the audio model accepts any compatible audio file (such as mp3, wav, and opus). These files can be added to be loaded at the very end of the user prompt or added with chat command /audio path/to/file.mp3.

Similarly as described above, to activate the audio output mode of an audio model, do set command line option -z to make sure to enable the speech synthesis function!

chatgpt.sh -cc -w -z -vv -m "gpt-4o-audio-preview"

Mind that this does not implement the realtime models.

When text completions is set for chatting with option -c, some properties are configured automatically to instruct the bot.

chatgpt.sh -c "Hello there! What is your name?"

This is the pure text completions endpoint. It is typically used to complete input text, such as for completing part of an essay.

To complete text from the command line input prompt, either set option -d or set a text completion model name.

chatgpt.sh -128 -m gpt-3.5-turbo-instruct "Hello there! Your name is"

chatgpt.sh -128 -d "The journalist loo"

The above examples also set maximum response value to 128 tokens.

Enter single-turn interactive mode:

chatgpt.sh -d

NOTE: For multi-turn mode with history support, set option -dd.

A strong Instruction prompt may be needed for the language model to do what is required.

Set an instruction prompt for better results:

chatgpt.sh -d -S 'The following is a newspaper article.' "It all starts when FBI agents arrived at the governor house and"

chatgpt.sh -d -S'You are an AI assistant.'  "The list below contain the 10 biggest cities in the w"

Set option -q (or -qq for multiturn) to enable insert mode and add the string [insert] where the model should insert text:

chatgpt.sh -q 'It was raining when [insert] tomorrow.'

NOTE: This example works with no instruction prompt! An instruction prompt in this mode may interfere with insert completions.

NOTE: Insert mode works with model instruct models.

Mistral AI has a nice FIM (fill-in-the-middle) endpoint that works with code models and is really good!

To enable markdown rendering of responses, set command line option --markdown, or run /md in chat mode. To render last response in markdown once, run //md.

The markdown option uses bat as it has line buffering on by defaults, however other software is supported. Set it such as --markdown=glow or /md mdless on chat mode.

Type in any of the following markdown software as argument to the option: bat, pygmentize, glow, mdcat, or mdless.

Unless the chat option -c or -cc are set, no instruction is given to the language model. On chat mode, if no instruction is set, minimal instruction is given, and some options set, such as increasing temp and presence penalty, in order to un-lobotomise the bot.

Prompt engineering is an art on itself. Study carefully how to craft the best prompts to get the most out of text, code and chat completions models.

The model steering and capabilities require prompt engineering to even know that it should answer the questions.

Set a one-shot instruction prompt with option -S:

chatgpt.sh -cc -S 'You are a PhD psycologist student.' 

chatgpt.sh -ccS'You are a professional software programmer.'

To create or load a prompt template file, set the first positional argument as .prompt_name or ,prompt_name. In the second case, load the prompt and single-shot edit it.

chatgpt.sh -cc .psycologist 

chatgpt.sh -cc ,software_programmer

Alternatively, set option -S with the operator and the name of the prompt as an argument:

chatgpt.sh -cc -S .psycologist 

chatgpt.sh -cc -S,software_programmer

This will load the custom prompt or create it if it does not yet exist. In the second example, single-shot editing will be available after loading prompt software_programmer.

Please note and make sure to backup your important custom prompts! They are located at "~/.cache/chatgptsh/" with the extension ".pr".

Set a prompt from awesome-chatgpt-prompts or awesome-chatgpt-prompts-zh, (use with davinci and gpt-3.5+ models):

chatgpt.sh -cc -S /linux_terminal

chatgpt.sh -cc -S /Relationship_Coach 

chatgpt.sh -cc -S '%担任雅思写作考官'

This project includes shell completions to enhance the user command-line experience.

Install following one of the methods below.

System-wide

sudo cp comp/bash/chatgpt.sh /usr/share/bash-completion/completions/

User-specific

mkdir -p ~/.local/share/bash-completion/completions/
cp comp/bash/chatgpt.sh ~/.local/share/bash-completion/completions/

Visit the bash-completion repository.

Install at the system location

sudo cp comp/zsh/_chatgpt.sh /usr/share/zsh/site-functions/

User-specific location

To set user-specific completion, make sure to place the completion script under a directory in the $fpath array.

The user may create the ~/.zfunc/ directory, for example, and add the following lines to her ~/.zshrc:

[[ -d ~/.zfunc ]] && fpath=(~/.zfunc $fpath)

autoload -Uz compinit
compinit

Make sure compinit is run after setting $fpath!

Visit the zsh-completion repository.

Bash and Zsh completions should be active in new terminal sessions. If not, ensure your ~/.bashrc and ~/.zshrc source the completion files correctly.

• YouTube feature will get only YouTube videos heading title and its transcripts (when available).

• PDF support feature extracts the PDF text (no images) and appends it to the user request.

• Run chat commands with either operator ! or /.

• Edit live history entries with command !hist, for context injection.

• One can regenerate a response by typing in a new prompt a single slash /, or // to have last prompt edited before the new request.

Generate image according to prompt:

chatgpt.sh -i "Dark tower in the middle of a field of red roses."

chatgpt.sh -i "512x512" "A tower."

Generate image variation:

chatgpt.sh -i path/to/image.png

chatgpt.sh -i path/to/image.png path/to/mask.png "A pink flamingo."

In this example, a mask is made from the white colour.

Adding a bat in the night sky.

Generate transcription from audio file speech. A prompt to guide the model's style is optional. The prompt should match the speech language:

chatgpt.sh -w path/to/audio.mp3

chatgpt.sh -w path/to/audio.mp3 "en" "This is a poem about X."

1. Generate transcription from voice recording, set Portuguese as the language to transcribe to:

chatgpt.sh -w pt

This also works to transcribe from one language to another.

2. Transcribe any language speech input to Japanese (prompt should be in the same language as the input audio language, preferably):

chatgpt.sh -w ja "A job interview is currently being done."

3.1 Translate English speech input to Japanese, and generate speech output from the text response.

chatgpt.sh -wz ja "Getting directions to famous places in the city."

3.2 Also doing it conversely, this gives an opportunity to (manual) conversation turns of two speakers of different languages. Below, a Japanese speaker can translate its voice and generate audio in the target language.

chatgpt.sh -wz en "Providing directions to famous places in the city."

4. Translate speech from any language to English:

chatgpt.sh -W [audio_file]

chatgpt.sh -W

To retry with the last microphone recording saved in the cache, set audio_file as last or retry.

NOTE: Generate phrasal-level timestamps double setting option -ww or option -WW. For word-level timestamps, set option -www or -WWW.

Other than Ollama and LocalAI local servers, the free service providers are GitHub Models, Google Vertex, and Groq.

Make sure you have got mudler's LocalAI, server set up and running.

The server can be run as a docker container or a binary can be downloaded. Check LocalAI tutorials Container Images, and Run Models Manually for an idea on how to install, download a model and set it up.

 ┌───────────────────────────────────────────────────┐
 │                   Fiber v2.50.0                   │
 │               http://127.0.0.1:8080               │
 │       (bound on host 0.0.0.0 and port 8080)       │
 │                                                   │
 │ Handlers ............. 1  Processes ........... 1 │
 │ Prefork ....... Disabled  PID ..................1 │
 └───────────────────────────────────────────────────┘

1. Download a binary of localai for your system from Mudler's release GitHub repo.

2. Run localai run --help to check comamnd line options and environment variables.

3. Set up $GALLERIES before starting up the server:

export GALLERIES='[{"name":"localai", "url":"github:mudler/localai/gallery/index.yaml"}]'  #defaults

export GALLERIES='[{"name":"model-gallery", "url":"github:go-skynet/model-gallery/index.yaml"}]'

export GALLERIES='[{"name":"huggingface", "url": "github:go-skynet/model-gallery/huggingface.yaml"}]'

4. Install the model named phi-2-chat from a yaml file manually, while the server is running:

curl -L http://localhost:8080/models/apply -H "Content-Type: application/json" -d '{ "config_url": "https://raw.githubusercontent.com/mudler/LocalAI/master/embedded/models/phi-2-chat.yaml" }'

Finally, when running chatgpt.sh, set the model name:

chatgpt.sh --localai -cc -m luna-ai-llama2

Setting some stop sequences may be needed to prevent the model from generating text past context:

chatgpt.sh --localai -cc -m luna-ai-llama2  -s'### User:'  -s'### Response:'

Optionally set restart and start sequences for text completions endpoint (option -c), such as -s'\n### User: ' -s'\n### Response:' (do mind setting newlines \n and whitespaces correctly).

And that's it!

Model names may be printed with chatgpt.sh -l. A model may be supplied as argument, so that only that model details are shown.

NOTE: Model management (downloading and setting up) must follow the LocalAI and Ollama projects guidelines and methods.

For image generation, install Stable Diffusion from the URL github:go-skynet/model-gallery/stablediffusion.yaml, and for speech transcription, download Whisper from the URL github:go-skynet/model-gallery/whisper-base.yaml.

If the service provider Base URL is different from the defaults.

The environment varible $OPENAI_BASE_URL is read at invocation.

export OPENAI_BASE_URL="http://127.0.0.1:8080/v1"

chatgpt.sh -c -m luna-ai-llama2

To set it a in a more permanet fashion, edit the script configuration file .chatgpt.conf.

Use vim:

vim ~/.chatgpt.conf

Or edit the configuration with a comamnd line option.

chatgpt.sh -F

And set the following variable:

# ~/.chatgpt.conf

OPENAI_BASE_URL="http://127.0.0.1:8080/v1"

Visit Ollama repository, and follow the instructions to install, download models, and set up the server.

After having Ollama server running, set option -O (--ollama), and the name of the model in chatgpt.sh:

chatgpt.sh -cc -O -m llama2

If Ollama server URL is not the defaults http://localhost:11434, edit chatgpt.sh configuration file, and set the following variable:

# ~/.chatgpt.conf

OLLAMA_BASE_URL="http://192.168.0.3:11434"

Get a free API key for Google to be able to use Gemini and vision models. Users have a free bandwidth of 60 requests per minute, and the script offers a basic implementation of the API.

Set the enviroment variable $GOOGLE_API_KEY and run the script with option --google, such as:

chatgpt.sh --google -cc -m gemini-pro-vision

OBS: Google Gemini vision models are not enabled for multiturn at the API side, so we hack it.

To list all available models, run chatgpt.sh --google -l.

Set up a Mistral AI account, declare the enviroment variable $MISTRAL_API_KEY, and run the script with option --mistral for complete integration.

Sign in to Groq. Create a new API key or use an existing one to set the environmental variable $GROQ_API_KEY. Run the script with option --groq.

Currently, llamma3.1 models are available at lightening speeds!

Sign in to Antropic AI. Create a new API key or use an existing one to set the environmental variable $ANTHROPIC_API_KEY. Run the script with option --anthropic or --ant.

Check the Claude-3 models! Run the script as:

chatgpt.sh --anthropic -cc -m claude-3-5-sonnet-20240620

The script also works on text completions with models such as claude-2.1, although the API documentation flags it as deprecated.

Try:

chatgpt.sh --ant -c -m claude-2.1

GitHub has partnered with Azure to use its infratructure.

As a GitHub user, join the waitlist and then generate a personal token. Set the environmental variable $GITHUB_TOKEN and run the script with option --github or --git.

Check the on-line model list or list the available models and their original names with chatgpt.sh --github -l.

chatgpt.sh --github -cc -m Phi-3-small-8k-instruct

See also the GitHub Model Catalog - Getting Started page.

Novita AI offers a range of LLM models at exceptional value, including the highly recommended Llama 3.3 model, which provides the best balance of price and performance!

For an uncensored model, consider sao10k/l3-70b-euryale-v2.1 (creative assistant and role-playing) or cognitivecomputations/dolphin-mixtral-8x22b.

Create an API key as per the Quick Start Guide and export your key as $NOVITA_API_KEY to your environment.

Next, run the script such as chatgpt.sh --novita -cc.

Check the model list web page and the price of each model.

To list all available models, run chatgpt.sh --novita -l. Optionally set a model name with option -l to dump model details.

Some models work with the /completions endpoint, while others work with the /chat/completions endpoint, so the script does not set the endpoint automatically! Check model details and web pages to understand their capabilities, and then either run the script with option -c (text completions) or options -cc (chat completions).

---

As an exercise, instead of setting command-line option --novita, set Novita AI integration manually instead:

export OPENAI_API_KEY=novita-api-key
export OPENAI_BASE_URL="https://api.novita.ai/v3/openai"

chatgpt.sh -cc -m meta-llama/llama-3.1-405b-instruct

We are grateful to Novita AI for their support and collaboration. For more information, visit Novita AI.

Visit xAI Grok to generate an API key (environment $XAI_API_KEY).

Run the script with option --xai and also with option -cc (chat completions.).

Some models also work with native text completions. For that, set command-line option -c instead.

This project PKGBUILD is available at the Arch Linux User Repository (AUR) to install the software in Arch Linux and derivative distros.

To install the programme from the AUR, you can use an AUR helper like yay or paru. For example, with yay:

yay -S chatgpt.sh

Install the Termux and Termux:API apps from the F-Droid store.

Give all permissions to Termux:API in your phone app settings.

We reccommend to also install sox, ffmpeg, pulseaudio, imagemagick, and vim (or nano).

Remember to execute termux-setup-storage to set up access to the phone storage.

In Termux proper, install the termux-api and termux-tools packages (pkg install termux-api termux-tools).

When recording audio (Whisper, option -w), if pulseaudio is configured correctly, the script uses sox, ffmpeg or other competent software, otherwise it defaults to termux-microphone-record

Likewise, when playing audio (TTS, option -z), depending on pulseaudio configuration use sox, mpv or fallback to termux wrapper playback (play-audio is optional).

To set the clipboard, it is required termux-clipboard-set from the termux-api package.

Markdown in TTS input may stutter the model speech generation a little. If python modules markdown and bs4 are available, TTS input will be converted to plain text. As fallback, pandoc is used if present (chat mode only).

Under Termux, make sure to have your system updated and installed with python, rust, and rustc-dev packages for building tiktoken.

pkg update

pkg upgrade

pkg install python rust rustc-dev

pip install tiktoken

In order to set Termux access to recording the microphone and playing audio (with sox and ffmpeg), follow the instructions below.

A. Set pulseaudio one time only, execute:

pulseaudio -k
pulseaudio -L "module-sles-source" -D

B. To set a permanent configuration:

1. Kill the process with pulseaudio -k.
2. Add load-module module-sles-source to one of the files:

~/.config/pulse/default.pa
/data/data/com.termux/files/usr/etc/pulse/default.pa

3. Restart the server with pulseaudio -D.

C. To create a new user ~/.config/pulse/default.pa, you may start with the following template:

#!/usr/bin/pulseaudio -nF
 
.include /data/data/com.termux/files/usr/etc/pulse/default.pa
load-module module-sles-source

To access your Termux files using Android's file manager, install a decent file manager such as FX File Explorer from a Play Store and configure it, or run the following command in your Termux terminal:

am start -a android.intent.action.VIEW -d "content://com.android.externalstorage.documents/root/primary"

Source: https://www.reddit.com/r/termux/comments/182g7np/where_do_i_find_my_things_that_i_downloaded/

• Implement nice features from OpenAI API version 1.

• Provide the closest API defaults.

• Let the user customise defaults (as homework).

• Première of chatgpt.sh version 1.0 should occur at the time when OpenAI launches its next major API version update.

• We shall decrease development frequency in 2025, hopefully. LLM models in general are not really worth developer efforts sometimes, it is frustating!
• The warper is deemed finished in the sense any further updates must not change the user interface.
• We plan to gradually wind down development of new features in the near future. The project will enter a maintenance phase from 2025 onwards, focusing primarily on bug fixes and stability.

• OpenAI API version 1 is the focus of the present project implementation. Not all features of the API will be covered.

• This project doesn't support "Function Calling" or "Structured Outputs".

• Probably, we will not support "Real-Time" chatting, or video modality.

• Bash shell truncates input on \000 (null).

• Bash "read command" may not correctly display input buffers larger than the TTY screen size during editing. However, input buffers remain unaffected. Use the text editor interface for big prompt editing.

• Garbage in, garbage out. An idiot savant.

• The script logic resembles a bowl of spaghetti code after a cat fight.

• See BUGS AND LIMITS section in the man page.

Please leave bug reports at the GitHub issues page.

Read the online man page here.

Alternatively, a help page snippet can be printed with chatgpt.sh -h.

Many Thanks to everyone who contributed to this project.

• edshamis
• johnd0e
• Novita AI's GTM Leo

Everyone is welcome to submit issues, PRs, and new ideas!

The following projects are worth remarking. They were studied during development of this script and used as referencial code sources.

1. TheR1D's shell_gpt
2. xenodium's chatgpt-shell
3. llm-workflow-engine
4. 0xacx's chatGPT-shell-cli
5. mudler's LocalAI
6. Ollama
7. Google Gemini
8. Groq
9. Antropic AI
10. Novita AI
11. xAI
12. f's awesome-chatgpt-prompts
13. PlexPt's awesome-chatgpt-prompts-zh

---

The project home is at GitLab

https://gitlab.com/fenixdragao/shellchatgpt

Mirror

https://github.com/mountaineerbr/shellChatGPT