Plug and Plai is an open source library aiming to simplify the integration of AI plugins into open-source language models (LLMs).

It provides utility functions to get a list of active plugins from plugnplai directory, get plugin manifests, and extract OpenAPI specifications and load plugins.

Visit the plugnplai website or the repository for more information on using the library.

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Integration with llama

You can install Plug and Plai using pip:

pip install plugnplai

In the example, we will search for a weather plugin.

  1. Use plugnplai library to load plugins from the database: https://plugnplai.com
  2. Let’s choose weather plugin
  3. Install the plugin using Plugins.install_and_activate
  4. Get an array of the functions schemas using the built in function plugins.functions
plugnplai
import plugnplai as pl

allurls = pl.get_plugins()

urls = [url for url in allurls if ("weather" in url)]
print("URLs: ",urls)

plugins = pl.Plugins.install_and_activate(urls[3])
print("Function: ",plugins.functions)
Response
URLs:  ["https://weather--vicentescode.repl.co", "https://openai-plugin.xweather.com", "https://weather.mixerbox.com", "https://weathergpt-bay-six.vercel.app"]
Function:  [{"name": "WeatherWizard_checkWeatherUsingGET", "description": "Use the WeatherWizard plugin to automatically fetch current weather information for a specific location when it"s being generated. The plugin will return weather data, including temperature, wind speed, humidity, and other relevant information, as well as a link to a page that has all the information. Links will always be returned and should be shown to the user. The weather data can be used to provide users with up-to-date and accurate weather information for their desired location.", "parameters": {"type": "object", "properties": {"location": {"type": "string", "description": "Location for which to retrieve weather information."}}, "required": ["location"]}}]

Now let’s run llama with the new functions

Llama API
import json
from llamaapi import LlamaAPI

llama = LlamaAPI("<your_api_token>")

api_request_json = {
  "messages": [
    {"role": "user", "content": "How is the weather in New York?"},
  ],
  "functions": plugins.functions,
  "stream": False,
  "function_call": "force",
  "max_tokens": 800
}

# Make your request and handle the response
response = llama.run(api_request_json)
print(json.dumps(response.json(), indent=2))
Response
{
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": null,
        "function_call": {
          "name": "WeatherWizard_checkWeatherUsingGET",
          "arguments": {
            "location": "New York"
          }
        }
      },
      "finish_reason": "function_call"
    }
  ]
}
Function CallingTutorial