ell
A command-line interface for LLMs written in Bash.
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ell is a command-line interface for Language Model Models (LLMs) written in Bash. It allows users to interact with LLMs from the terminal, supports piping, context bringing, and chatting with LLMs. Users can also call functions and use templates. The tool requires bash, jq for JSON parsing, curl for HTTPS requests, and perl for PCRE. Configuration involves setting variables for different LLM models and APIs. Usage examples include asking questions, specifying models, recording input/output, running in interactive mode, and using templates. The tool is lightweight, easy to install, and pipe-friendly, making it suitable for interacting with LLMs in a terminal environment.
README:
A command-line interface for LLMs written in Bash.
Basic usage of ell (webm, 1,6MiB)
- Ask LLMs from your terminal
- Pipe friendly
- Bring your terminal context to the LLMs and ask questions
- Chat with LLMs in your terminal
- Function calling and more supported via templates
- Sensitive information redaction (#14)
To use ell, you need the following:
- bash-4.1 or later and coreutils / OS X utilities
- jq (For parsing JSON)
- curl (For sending HTTPS requests)
- perl (Not necessary if you don't use record mode. For PCRE. POSIX bash doesn't support look-ahead and look-behind regular expressions)
- util-linux (Not necessary if you don't use record mode. For
scriptcommand to record terminal input and output)
git clone --depth 1 https://github.com/simonmysun/ell.git ~/.ellrc.d
echo 'export PATH="${HOME}/.ellrc.d:${PATH}"' >> ~/.bashrc
or
git clone --depth 1 [email protected]:simonmysun/ell.git ~/.ellrc.d
echo 'export PATH="${HOME}/.ellrc.d:${PATH}"' >> ~/.bashrc
This will clone the repository into .ellrc.d in your home directory and add it to your PATH.
See Configuration.
Here's an example configuration to use gemini-1.5-flash from Google. You need to set these variables in your ~/.ellrc:
ELL_API_STYLE=gemini
ELL_LLM_MODEL=gemini-1.5-flash
ELL_TEMPLATE=default-gemini
ELL_API_KEY=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
ELL_API_URL=https://generativelanguage.googleapis.com/v1beta/models/Here's an example configuration to use gpt-4o-mini from OpenAI.
ELL_API_STYLE=openai
ELL_LLM_MODEL=gpt-4o-mini
ELL_TEMPLATE=default-openai
ELL_API_KEY=sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
ELL_API_URL=https://api.openai.com/v1/chat/completionsMake sure you have configured correctly.
Ask a question:
ell "What is the capital of France?"Specify a model and use a file as input:
ell -m gpt-4o -f user_prompt.txtreading from stdin is also supported:
cat somecode.py | ell -f -If you prefer add another piece of prompt instantly instead of adding it in the template:
(cat somecode.py; echo "Explain this code") | ell -f -Record terminal input and output and use as context:
ell -r
# do random stuff
ell What does the error code mean?
ell How to fix it?Run in interactive mode:
ell -iIn interactive mode, record mode is automatically enabled to allow you chat with context.
Specify a template and start in record mode and interactive mode:
ell -r -i -t ctf-geminior
ell -r -i -t ctf-openaidepends on which API you are using.
Example application of a capture the flag game (webm, 2.6MiB)
See Templates.
Note that the use of the plugin support of LLM providers in ell is made with templates.
See Styling.
See Plugins.
The term "Plugin" here means a script that can be called by ell. It can be used to extend ell's functionality. The plugins supported by LLM providers is not included here. Please refer to Templates.
See Risks Consideration.
-
Q: Why is it called "ell"?
-
A: "ell" is a combination of shell and LLM. It is a shell script to use LLM backends. "shellm" was once considered, but it was dropped because it could be misunderstood as "she llm". "ell" is shorter, easy to type and easy to remember. It does not conflict with any active software. Note that the name "shell" of shell scripts is because it is the outer layer of the operating system exposed to the user. It doesn't indicate that it is a CLI or GUI. Unfortunately it cannot be shortened to "L" which has the same pronunciation because that would conflict with too many things.
-
Q: Why is it written in Bash?
-
A: Because Bash is the most common shell on Unix-like systems and there is just no need to use a more complex language for this.
-
Q: What is the difference between ell and other similar projects?
-
A: ell is written in almost pure Bash, which makes it very lightweight and easy to install. It is also very easy to extend and modify. It is pipe-friendly, which means it is designed to be used in combination with other tools.
- https://github.com/kardolus/chatgpt-cli - A CLI for ChatGPT written in Go.
- https://github.com/kharvd/gpt-cli A CLI for various LLM backends written in Python.
- https://github.com/JohannLai/gptcli A CLI for OpenAI LLMs written in TypeScript.
- https://github.com/x-cmd/x-cmd A huge collection of various tools which includes a CLI for LLM APIs. The project is written in POSIX bash and awk.
- https://github.com/llimllib/gpt-bash-cli A CLI for OpenAI API that saves the requests and responses into a database. It also uses the system keyring to store the API key, which is a lot more secure. This project is also written in bash.
- https://github.com/charmbracelet/mods A CLI tool to talk to LLMs written in Go. It has rich features in conversation management.
- https://github.com/hiquest/nicechat A CLI chat interface for OpenAI models, written in Node.js.
- https://github.com/closedloop-technologies/autocomplete-sh A CLI for LLM which uses completion to interact with users. It also acquires several history operations to provide better suggestions, also written in bash.
- https://github.com/plandex-ai/plandex A CLI tool to develop AI-integrated workflow, written in Go.
- https://github.com/simonw/llm A CLI tool for in-depth manipulation of LLMs, written in Python.
- https://github.com/sigoden/aichat A CLI tool talks to various LLM providers, written in Rust.
- https://github.com/npiv/chatblade A CLI Swiss Army Knife for ChatGPT, written in python
Contributions are welcome! If you have any ideas, suggestions, or bug reports, please open an issue or submit a pull request.
This project is licensed under the MIT License. See the LICENSE file for more details.
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