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GPT's Function Calling Demo, a experiment of self-hosted ChatGPT-Plugins-like platform.
Recommend reading: function-calling
OpenAI's GPT models provide a function calling feature, so we can easily create ChatGPT-Plugins-like
tools. This repository is a proof-of-concept of the function calling feature.
In this experiment, we defined the Plugin
as Namespace
which contains a serial of functions. While user performing a conversation, the functions in Namespace
will be called by the API and return the result to the user.
Clone this repository and install the dependencies.
git clone https://github.com/RockChinQ/CallingGPT
cd CallingGPT
pip install -r requirements.txt
Run the main.py
to generate config.yaml
python main.py
Edit the config.yaml
to set your API key and other settings.
Run the main.py
and pass your modules.
python main.py <module0> <module1> ...
Use the example/greet.py
, provides a greet
function called when user ask GPT to greet someone.
python main.py example/greet.py
Then you can talk to the bot.
$ python main.py examples/greet.py
Using module: examples.greet
>>> Hello and who are you?
<<< Hello! I am an AI assistant. How can I assist you today?
>>> say hello to Rock
call<examples-greet-greet>: {
"user": "Rock"
}
<<< Hello, Rock! How can I assist you today?
>>> and to Alice
call<examples-greet-greet>: {
"user": "Alice"
}
<<< Hello, Alice! How can I assist you today?
>>>
Type help
to get help.
See wiki for the function format.
Install the package
pip install --upgrade CallingGPT
Create your own functions in modules(these modules can also be used in the CLI mode)
# your_module_a.py
def func_a(prompt: str) -> str: # Type hint of EACH argument and return value is REQUIRED.
"""
The description of this func a, will be provided to the api.
Args:
prompt(str): The prompt of the function.
Returns:
The result of the function.
"""
# Google style docstring is REQUIRED, it will be split into
# `description` and `params`(required if there are args) and
# `returns`(optional), `\n\n` between each part.
return "func_a: " + prompt
# your_module_b.py
def adder(a: int, b: int) -> int:
"""
Add two numbers.
Args:
a: The first number.
b: The second number.
Returns:
The sum of a and b.
"""
# Type hints of args in docstring is optional.
return a + b
Call the wrapper
from CallingGPT.session.session import Session
import your_module_a, your_module_b
import openai
openai.api_key = 'your_openai_api_key'
session = Session([your_module_a, your_module_b])
for reply in session.ask("your prompt"):
# session.ask will yield each time the api returns a result,
# before calling function, it will print the function name and args.
# e.g. here's a function call:
# {
# "role": "assistant",
# "content": null,
# "function_call": {
# "name": "examples-draw_and_wrapper_md-draw",
# "arguments": "{\n \"prompt\": \"cat\"\n}"
# }
# }
#
# while here's a normal reply:
# {
# "role": "assistant",
# "content": "Hello, I am an AI assistant. How can I assist you today?"
# }
print(reply)
Session
will automatically manage context for you.
See wiki for the function format.