chap 0.8.4
Interact with the OpenAI ChatGPT API (and other text generators)
Requires Python: >=3.9
Keywords: llm, tui, chatgpt

<!--
SPDX-FileCopyrightText: 2021 Jeff Epler

SPDX-License-Identifier: MIT
-->
[![Test](https://github.com/jepler/chap/actions/workflows/test.yml/badge.svg)](https://github.com/jepler/chap/actions/workflows/test.yml)
[![Release chap](https://github.com/jepler/chap/actions/workflows/release.yml/badge.svg?event=release)](https://github.com/jepler/chap/actions/workflows/release.yml)
[![PyPI](https://img.shields.io/pypi/v/chap)](https://pypi.org/project/chap/)

# chap - A Python interface to chatgpt and other LLMs, including a terminal user interface (tui)

![Chap screencast](https://raw.githubusercontent.com/jepler/chap/main/chap.gif)

## System requirements

Chap is primarily developed on Linux with Python 3.11. Moderate effort will be made to support versions back to Python 3.9 (Debian oldstable).

## Installation

If you want `chap` available as a command, just install with  `pipx install chap` or `pip install chap`.

Use a virtual environment unless you want it installed globally.

## Installation for development

Use one of the following two methods to run `chap` as a command, with the ability to edit the source files. You are welcome to submit valuable changes as [a pull request](https://github.com/jepler/chap/pulls).

### Via `pip install --editable .`

This is an "editable install", as [recommended by the Python Packaging Authority](https://setuptools.pypa.io/en/latest/userguide/development_mode.html).

Change directory to the root of the `chap` project.

Activate your virtual environment, then install `chap` in development mode:

```shell
pip install --editable .
```

In this mode, you get the `chap` command-line program installed, but you are able to edit the source files in the `src` directory in place.

### Via `chap-dev.py`

A simple shim script called `chap-dev.py` is included to demonstrate how to load and run the `chap` library without installing `chap` in development mode. This method may be more familiar to some developers.

Change directory to the root of the `chap` project.

Activate your virtual environment, then install requirements:

```shell
pip install -r requirements.txt
```

Run the shim script (with optional command flags as appropriate):

```shell
./chap-dev.py
```

In this mode, you can edit the source files in the `src` directory in place, and the shim script will pick up the changes via the `import` directive.

## Contributing

See [CONTRIBUTING.md](CONTRIBUTING.md).

## Code of Conduct

See [CODE\_OF\_CONDUCT.md](CODE_OF_CONDUCT.md).

## Configuration

Put your OpenAI API key in the platform configuration directory for chap, e.g., on linux/unix systems at `~/.config/chap/openai_api_key`

## Command-line usage

 * `chap ask "What advice would you give a 20th century human visiting the 21st century for the first time?"`

 * `chap render --last` / `chap cat --last`

 * `chap import chatgpt-style-chatlog.json` (for files from pionxzh/chatgpt-exporter)

 * `chap grep needle`

## `@FILE` arguments

It's useful to set a bunch of related arguments together, for instance to fully
configure a back-end. This functionality is implemented via `@FILE` arguments.

Before any other command-line argument parsing is performed, `@FILE` arguments are expanded:

 * An `@FILE` argument is searched relative to the current directory
 * An `@:FILE` argument is searched relative to the configuration directory (e.g., $HOME/.config/chap)
 * If an argument starts with a literal `@`, double it: `@@`
 * `@.` stops processing any further `@FILE` arguments and leaves them unchanged.
The contents of an `@FILE` are parsed according to `shlex.split(comments=True)`.
Comments are supported.
A typical content might look like this:
```
# gpt-3.5.txt: Use cheaper gpt 3.5 and custom prompt
--backend openai-chatgpt
-B model:gpt-3.5-turbo
-s my-custom-system-message.txt
```
and you might use it with
```
chap @:gpt-3.5.txt ask what version of gpt is this
```

## Interactive terminal usage
The interactive terminal mode is accessed via `chap tui`.

There are a variety of keyboard shortcuts to be aware of:
 * tab/shift-tab to move between the entry field and the conversation, or between conversation items
 * While in the text box, F9 or (if supported by your terminal) alt+enter to submit multiline text
 * while on a conversation item:
   * ctrl+x to re-draft the message. This
     * saves a copy of the session in an auto-named file in the conversations folder
     * removes the conversation from this message to the end
     * puts the user's message in the text box to edit
   * ctrl+x to re-submit the message. This
     * saves a copy of the session in an auto-named file in the conversations folder
     * removes the conversation from this message to the end
     * puts the user's message in the text box
     * and submits it immediately
   * ctrl+y to yank the message. This places the response part of the current
     interaction in the operating system clipboard to be pasted (e..g, with
     ctrl+v or command+v in other software)
   * ctrl+q to toggle whether this message may be included in the contextual history for a future query.
     The exact way history is submitted is determined by the back-end, often by
     counting messages or tokens, but the ctrl+q toggle ensures this message (both the user
     and assistant message parts) are not considered.

## Sessions & Command-line Parameters

Details of session handling & command-line arguments are in flux.

By default, a new session is created. It is saved to the user's state directory
(e.g., `~/.local/state/chap` on linux/unix systems).

You can specify the session filename for a new session with `-n` or to re-open
an existing session with `-s`. Or, you can continue the last session with
`--last`.

You can set the "system message" with the `-S` flag.

You can select the text generating backend with the `-b` flag:
 * openai-chatgpt: the default, paid API, best quality results
 * llama-cpp: Works with [llama.cpp's http server](https://github.com/ggerganov/llama.cpp/blob/master/examples/server/README.md) and can run locally with various models,
 though it is [optimized for models that use the llama2-style prompting](https://huggingface.co/blog/llama2#how-to-prompt-llama-2).
 Set the server URL with `-B url:...`.
 * textgen: Works with https://github.com/oobabooga/text-generation-webui and can run locally with various models.
 Needs the server URL in *$configuration_directory/textgen\_url*.
 * lorem: local non-AI lorem generator for testing

## Environment variables

The backend can be set with the `CHAP_BACKEND` environment variable.

Backend settings can be set with `CHAP_<backend_name>_<parameter_name>`, with `backend_name` and `parameter_name` all in caps.

For instance, `CHAP_LLAMA_CPP_URL=http://server.local:8080/completion` changes the default server URL for the llama-cpp back-end.

## Importing from ChatGPT

The userscript https://github.com/pionxzh/chatgpt-exporter can export chat logs from chat.openai.com in a JSON format.

This format is different than chap's, especially since `chap` currently only represents a single branch of conversation in one log.

You can use the `chap import` command to import all the branches of a chatgpt-style chatlog in JSON format into a series of `chap`-style chat logs.

## Plug-ins

Chap supports back-end and command plug-ins.

"Back-ends" add additional text generators.

"Commands" add new ways to interact with text generators, session data, and so forth.

Install a plugin with `pip install` or `pipx inject` (depending how you installed chap) and then use it as normal.

[chap-backend-replay](https://pypi.org/project/chap-backend-replay/) is an example back-end plug-in. It replays answers from a previous session.

[chap-command-explain](https://pypi.org/project/chap-command-explain/) is an example command plug-in. It is similar to `chap ask`.

At this time, there is no stability guarantee for the API of commands or backends.