npi
Action library for AI Agent
Stars: 211
NPi is an open-source platform providing Tool-use APIs to empower AI agents with the ability to take action in the virtual world. It is currently under active development, and the APIs are subject to change in future releases. NPi offers a command line tool for installation and setup, along with a GitHub app for easy access to repositories. The platform also includes a Python SDK and examples like Calendar Negotiator and Twitter Crawler. Join the NPi community on Discord to contribute to the development and explore the roadmap for future enhancements.
README:
[!WARNING] NPi is currently under active development and the APIs are subject to change in the future release. It is recommended to use the command line tool to try it out.
NPi is an open-source platform providing Tool-use APIs to empower AI agents with the ability to take action in virtual world!
🛠️Try NPi Online: Try NPi on online Playground (🚧Under Construction).
👀 NPi Example: Highly recommended to check this first - See what you can build with NPi.
🔥 Introducing NPi: Why we build NPi?
📚 NPi Documentation: How to use NPi?
📢 Join our community on Discord: Let's build NPi together 👻 !
NPi (Natural-language Programming Interface), pronounced as "N π", is an open-source platform providing Tool-use APIs to empower AI agents with the ability to operate and interact with a diverse array of software tools and applications.
pip install npiaiLet's create a new tool to compute the nth Fibonacci number. Start by crafting a new Python file titled main.py and insert the following snippet:
import os
import json
import asyncio
from openai import OpenAI
from npiai import FunctionTool, function
class MyTool(FunctionTool):
name = 'Fibonacci'
description = 'My first NPi tool'
@function
def fibonacci(self, n: int) -> int:
"""
Get the nth Fibonacci number.
Args:
n: The index of the Fibonacci number in the sequence.
"""
if n == 0:
return 0
if n == 1:
return 1
return self.fibonacci(n - 1) + self.fibonacci(n - 2)
async def main():
async with MyTool() as tool:
print(f'The schema of the tool is\n\n {json.dumps(tool.tools, indent=2)}')
client = OpenAI(api_key=os.getenv('OPENAI_API_KEY'))
messages = [
{
"role": "user",
"content": "What's the 10-th fibonacci number?",
}
]
response = client.chat.completions.create(
model="gpt-4o",
messages=messages,
tools=tool.tools, # use tool as functions package
tool_choice="auto",
max_tokens=4096,
)
response_message = response.choices[0].message
if response_message.tool_calls:
result = await tool.call(tool_calls=response_message.tool_calls)
print(f'The result of function\n\n {json.dumps(result, indent=2)}')
if __name__ == "__main__":
asyncio.run(main())Now, run the tool:
python main.pyYou will see the function result in OpenAI function calling format:
[
{
"role": "tool",
"name": "fibonacci",
"tool_call_id": "call_4KItpriZmoGxXgDloI5WOtHm",
"content": 55
}
]content: 55 is the result of function calling, and the schema:
[
{
"type": "function",
"function": {
"name": "fibonacci",
"description": "Get the nth Fibonacci number.",
"parameters": {
"properties": {
"n": {
"description": "The index of the Fibonacci number in the sequence.",
"type": "integer"
}
},
"required": [
"n"
],
"type": "object"
}
}
}
]That's it! You've successfully created and run your first NPi tool. 🎉
Apache License 2.0
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