fish-ai
adds AI functionality to Fish shell. It
should run on any system with Python installed.
Originally based on Tom DΓΆrr's fish.codex
repository,
but with some additional functionality. It uses the generateContent
or
chat completions API endpoint
and can be hooked up to Google, OpenAI, Azure OpenAI
or a self-hosted LLM behind any OpenAI-compatible API.
Continuous integration is performed against Azure OpenAI.
If you like it, please add a β.
Create a configuration file ~/.config/fish-ai.ini
.
If you use a self-hosted LLM:
[fish-ai]
configuraton = self-hosted
[self-hosted]
provider = self-hosted
server = https://<your server>:<port>/v1
model = <your model>
api_key = <your API key>
If you are self-hosting, my recommendation is to use
Ollama with
Llama 3 70B. An out of the box
configuration running on localhost
could then look something like this:
[fish-ai]
configuraton = local-llama
[local-llama]
provider = self-hosted
server = http://localhost:11434/v1
If you use OpenAI:
[fish-ai]
configuration = openai
[openai]
provider = openai
model = gpt-4-turbo
api_key = <your API key>
organization = <your organization>
If you use Azure OpenAI:
[fish-ai]
configuration = azure
[azure]
provider = azure
server = https://<your instance>.openai.azure.com
model = <your deployment name>
api_key = <your API key>
If you use Gemini:
[fish-ai]
configuration = gemini
[gemini]
provider = google
api_key = <your API key>
Install the plugin. You can install it using fisher
.
fisher install realiserad/fish-ai@stable
Type a comment (anything starting with #
), and press Ctrl + P to turn it
into shell command!
You can also run it in reverse. Type a command and press Ctrl + P to turn it into a comment explaining what the command does.
Begin typing your command and press Ctrl + Space to autocomplete at the cursor position.
If a command fails, you can immediately press Ctrl + Space at the command prompt
to let fish-ai
suggest a fix!
You can tweak the behaviour of fish-ai
by putting additional options in the
active section of your fish-ai.ini
file.
To explain shell commands in a different language, set the language
option
to the name of the language. For example:
[fish-ai]
configuration = foo
[foo]
language = Swedish
Temperature is a decimal number between 0 and 1 controlling the randomness of
the output. Higher values make the LLM more creative, but may impact accuracy.
The default value is 0.2
.
Here is an example of how to increase the temperature to 0.5
.
[fish-ai]
configuration = foo
[foo]
temperature = 0.5
You can switch between different sections in the configuration using the
fish_ai_switch_context
command.
When using the plugin, fish-ai
submits the name of your OS and the
commandline buffer to the LLM. When you codify a command, it also
sends the contents of any files you mention (as long as the file is
readable).
Finally, to fix the previous command, the previous commandline buffer, along with any terminal output and the corresponding exit code is sent to the LLM.
If you are concerned with data privacy, you should use a self-hosted LLM. When hosted locally, no data ever leaves your machine.
This repository ships with a devcontainer.json
which can be used with
GitHub Codespaces or Visual Studio Code with
the Dev Containers extension.
To install fish-ai
from a local copy, use fisher
:
fisher install .
Enable debug logging by putting debug = True
in your fish-ai.ini
.
Logging is done to syslog by default (if available). You can also enable
logging to file using log = <path to file>
, for example:
[fish-ai]
configuration = foo
[foo]
debug = True
log = ~/.fish-ai/log.txt
The tests
are packaged into a container and can be executed locally with e.g. docker
.
cp ~/.config/fish-ai.ini tests/azure-openai
docker build -f tests/azure-openai/Dockerfile .