composio-lyzr 0.5.32

Use Composio to get an array of tools with your Lyzr workflow.

Using Composio With Lyzr

Integrate Composio with Lyzr agents to allow them to interact seamlessly with external apps, enhancing their functionality and reach.

Goal

• Star a repository on GitHub using natural language commands through a LangChain Agent.

Installation and Setup

Ensure you have the necessary packages installed and connect your GitHub account to allow your agents to utilize GitHub functionalities.

# Install Composio LangChain package
pip install composio-lyzr

# Connect your GitHub account
composio-cli add github

# View available applications you can connect with
composio-cli show-apps

Usage

from  lyzr_automata  import  Task, Agent
from lyzr_automata.ai_models.openai import OpenAIModel
from lyzr_automata.tasks.task_literals import InputType, OutputType
from lyzr_automata.pipelines.linear_sync_pipeline import LinearSyncPipeline

import os
import dotenv
dotenv.load_dotenv()
from composio_lyzr import ComposioToolSet, App, Action

open_ai_text_completion_model = OpenAIModel(
    api_key=os.environ["OPENAI_API_KEY"],
    parameters={
        "model": "gpt-4-turbo-preview",
        "temperature": 0.2,
        "max_tokens": 1500,
    },
)


lyzr_agent = Agent(
        role="Github Agent",
        prompt_persona="You are AI agent that is responsible for taking actions on Github on users behalf. You need to take action on Github using Github APIs"
    )

composio_toolset = ComposioToolSet()
composio_tool = composio_toolset.get_lyzr_tool(Action.GITHUB_STAR_REPO)

task = Task(
        name="Github Starring",
        agent=lyzr_agent,
        tool=composio_tool,
        output_type=OutputType.TEXT,
        input_type=InputType.TEXT,
        model=open_ai_text_completion_model,
        instructions="Star a repo composiohq/composio on GitHub",
        log_output=True,
        enhance_prompt=False,
)

lyzr_output = LinearSyncPipeline(
    name="Composio Lyzr",
		# completion message after pipeline completes
    completion_message="Task completed",
    tasks=[
				# tasks are instance of Task class
        task,
    ],
).run()

print(lyzr_output)