199 lines
5.3 KiB
Markdown
199 lines
5.3 KiB
Markdown
# LLM Functions
|
||
|
||
This project allows you to enhance large language models (LLMs) with custom functions written in bash/js/python/ruby. Imagine your LLM being able to execute system commands, access web APIs, or perform other complex tasks – all triggered by simple, natural language prompts.
|
||
|
||
## Prerequisites
|
||
|
||
Make sure you have the following tools installed:
|
||
|
||
- [argc](https://github.com/sigoden/argc): A bash command-line framewrok and command runner
|
||
- [jq](https://github.com/jqlang/jq): A JSON processor
|
||
|
||
## Getting Started with AIChat
|
||
|
||
**1. Clone the repository:**
|
||
|
||
```sh
|
||
git clone https://github.com/sigoden/llm-functions
|
||
```
|
||
|
||
**2. Build function declarations file and bin dir:**
|
||
|
||
First, create a `./functions.txt` file with each function name on a new line.
|
||
|
||
Then, run `argc build` to build function declarations file `./functions.json` and bin dir `./bin/`.
|
||
|
||
**3. Configure your AIChat:**
|
||
|
||
Symlink this repo directory to aichat **functions_dir**:
|
||
|
||
```sh
|
||
ln -s "$(pwd)" "$(aichat --info | grep functions_dir | awk '{print $2}')"
|
||
# OR
|
||
argc install
|
||
```
|
||
|
||
Don't forget to add the following config to your AIChat `config.yaml` file:
|
||
|
||
```yaml
|
||
function_calling: true
|
||
```
|
||
|
||
AIChat will automatically load `functions.json` and execute functions located in the `./bin` directory based on your prompts.
|
||
|
||
**4. Start using your functions:**
|
||
|
||
Now you can interact with your LLM using natural language prompts that trigger your defined functions.
|
||
|
||
|
||
|
||
|
||
## Function Types
|
||
|
||
### Retrieve Type
|
||
|
||
The function returns JSON data to LLM for further processing.
|
||
|
||
AIChat does not ask permission to run the function or print the output.
|
||
|
||
|
||
|
||
### Execute Type
|
||
|
||
The function does not have to return JSON data.
|
||
|
||
The function can perform dangerous tasks like creating/deleting files, changing network adapter, and setting a scheduled task...
|
||
|
||
AIChat will ask permission before running the function.
|
||
|
||
|
||
|
||
**AIChat categorizes functions starting with `may_` as `execute type` and all others as `retrieve type`.**
|
||
|
||
## Writing Your Own Functions
|
||
|
||
The project supports write functions in bash/js/python.
|
||
|
||
### Bash
|
||
|
||
Create a new bashscript in the [./tools/](./tools/) directory (.e.g. `may_execute_command.sh`).
|
||
|
||
```sh
|
||
#!/usr/bin/env bash
|
||
set -e
|
||
|
||
# @describe Executes a shell command.
|
||
# @option --command~ Command to execute, such as `ls -la`
|
||
|
||
main() {
|
||
eval $argc_shell_command
|
||
}
|
||
|
||
eval "$(argc --argc-eval "$0" "$@")"
|
||
```
|
||
|
||
`llm-functions` will automatic generate function declaration.json from [comment tags](https://github.com/sigoden/argc?tab=readme-ov-file#comment-tags).
|
||
|
||
The relationship between comment tags and parameters in function declarations is as follows:
|
||
|
||
```sh
|
||
# @flag --boolean Parameter `{"type": "boolean"}`
|
||
# @option --string Parameter `{"type": "string"}`
|
||
# @option --string-enum[foo|bar] Parameter `{"type": "string", "enum": ["foo", "bar"]}`
|
||
# @option --integer <INT> Parameter `{"type": "integer"}`
|
||
# @option --number <NUM> Parameter `{"type": "number"}`
|
||
# @option --array* <VALUE> Parameter `{"type": "array", "items": {"type":"string"}}`
|
||
# @option --scalar-required! Use `!` to mark a scalar parameter as required.
|
||
# @option --array-required+ Use `+` to mark a array parameter as required
|
||
```
|
||
|
||
### Javascript
|
||
|
||
Create a new javascript in the [./tools/](./tools/) directory (.e.g. `may_execute_command.js`).
|
||
|
||
```js
|
||
exports.declarate = function declarate() {
|
||
return {
|
||
"name": "may_execute_js_code",
|
||
"description": "Runs the javascript code in node.js.",
|
||
"parameters": {
|
||
"type": "object",
|
||
"properties": {
|
||
"code": {
|
||
"type": "string",
|
||
"description": "Javascript code to execute, such as `console.log(\"hello world\")`"
|
||
}
|
||
},
|
||
"required": [
|
||
"code"
|
||
]
|
||
}
|
||
}
|
||
}
|
||
|
||
exports.execute = function execute(data) {
|
||
eval(data.code)
|
||
}
|
||
|
||
```
|
||
|
||
### Python
|
||
|
||
Create a new python script in the [./tools/](./tools/) directory (e.g., `may_execute_py_code.py`).
|
||
|
||
```py
|
||
def declarate():
|
||
return {
|
||
"name": "may_execute_py_code",
|
||
"description": "Runs the python code.",
|
||
"parameters": {
|
||
"type": "object",
|
||
"properties": {
|
||
"code": {
|
||
"type": "string",
|
||
"description": "python code to execute, such as `print(\"hello world\")`"
|
||
}
|
||
},
|
||
"required": [
|
||
"code"
|
||
]
|
||
}
|
||
}
|
||
|
||
|
||
def execute(data):
|
||
exec(data["code"])
|
||
```
|
||
|
||
### Ruby
|
||
|
||
Create a new ruby script in the [./tools/](./tools/) directory (e.g., `may_execute_rb_code.rb`).
|
||
|
||
```rb
|
||
def declarate
|
||
{
|
||
"name": "may_execute_rb_code",
|
||
"description": "Runs the ruby code.",
|
||
"parameters": {
|
||
"type": "object",
|
||
"properties": {
|
||
"code": {
|
||
"type": "string",
|
||
"description": "Ruby code to execute, such as `puts \"hello world\"`"
|
||
}
|
||
},
|
||
"required": [
|
||
"code"
|
||
]
|
||
}
|
||
}
|
||
end
|
||
|
||
def execute(data)
|
||
eval(data["code"])
|
||
end
|
||
```
|
||
|
||
## License
|
||
|
||
The project is under the MIT License, Refer to the [LICENSE](https://github.com/sigoden/llm-functions/blob/main/LICENSE) file for detailed information. |