[](https://github.com/jepler/chap/actions/workflows/test.yml) [](https://github.com/jepler/chap/actions/workflows/release.yml) [](https://pypi.org/project/chap/) # chap - A Python interface to chatgpt and other LLMs, including a terminal user interface (tui)  ## 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/presets) * 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: ``` # cfg/gpt-4o: Use more expensive gpt 4o and custom prompt --backend openai-chatgpt -B model:gpt-4o -s :my-custom-system-message.txt ``` and you might use it with ``` chap @:cfg/gpt-4o 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. Also works with compatible API implementations including llama-cpp when the correct backend URL is specified. * 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). Consider using llama.cpp's OpenAI compatible API with the openai-chatgpt backend instead, in which case the server can apply the chat template. * 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*. * mistral: Works with the [mistral paid API](https://docs.mistral.ai/). * anthropic: Works with the [anthropic paid API](https://docs.anthropic.com/en/home). * huggingface: Works with the [huggingface API](https://huggingface.co/docs/api-inference/index), which includes a free tier. * lorem: local non-AI lorem generator for testing Backends have settings such as URLs and where API keys are stored. use `chap --backend --help` to list settings for a particular backend. ## Environment variables The backend can be set with the `CHAP_BACKEND` environment variable. Backend settings can be set with `CHAP__`, 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 backend. ## 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.