Skip to main content

Use Composio to get an array of tools with your LlamaIndex agent.

Project description

🦙 Using Composio With LlamaIndex

Integrate Composio with llamaindex agents to allow them to interact seamlessly with external apps & data sources, enhancing their functionality and reach.

Goal

  • Star a repository on GitHub using natural language commands through a llamaindex 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 llamaindex package
pip install composio-llamaindex

# Connect your GitHub account
composio-cli add github

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

Usage Steps

1. Import Base Packages

Prepare your environment by initializing necessary imports from llamaindex and setting up your agent.

from llama_index.llms.openai import OpenAI
from llama_index.core.llms import ChatMessage
from llama_index.core.agent import FunctionCallingAgentWorker

import dotenv
from llama_index.core.tools import FunctionTool

# Load environment variables from .env
dotenv.load_dotenv()

llm = OpenAI(model="gpt-4-turbo")

2. Fetch GitHub llamaindex Tools via Composio

Access GitHub tools provided by Composio for llamaindex.

from composio_llamaindex import App, Action, ComposioToolSet

# Get All the tools
composio_toolset = ComposioToolSet()
tools = composio_toolset.get_actions(
    actions=[Action.GITHUB_STAR_A_REPOSITORY_FOR_THE_AUTHENTICATED_USER]
)
print(tools)

3. Prepare the Agent

Configure the agent to perform tasks such as starring a repository on GitHub.

prefix_messages = [
    ChatMessage(
        role="system",
        content=(
            "You are now a integration agent, and what  ever you are requested, you will try to execute utilizing your toools."
        ),
    )
]

agent = FunctionCallingAgentWorker(
    tools=tools,
    llm=llm,
    prefix_messages=prefix_messages,
    max_function_calls=10,
    allow_parallel_tool_calls=False,
    verbose=True,
).as_agent()

4. Check Response

Validate the execution and response from the agent to ensure the task was completed successfully.

response = agent.chat("Hello! I would like to star a repo composiohq/composio on GitHub")
print("Response:", response)

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

composio_llamaindex-0.5.28.tar.gz (3.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

composio_llamaindex-0.5.28-py3-none-any.whl (4.3 kB view details)

Uploaded Python 3

File details

Details for the file composio_llamaindex-0.5.28.tar.gz.

File metadata

  • Download URL: composio_llamaindex-0.5.28.tar.gz
  • Upload date:
  • Size: 3.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.6

File hashes

Hashes for composio_llamaindex-0.5.28.tar.gz
Algorithm Hash digest
SHA256 0d9e7c10d3b18641830df76d210a47aaafb6ef02bb4d878412877ea19992b44c
MD5 b2c4207518be3a3c1116c4596c3e39a7
BLAKE2b-256 037e119582f83bf679557f1f13494570c9fdef80661c15410cb5ce184ce208be

See more details on using hashes here.

File details

Details for the file composio_llamaindex-0.5.28-py3-none-any.whl.

File metadata

File hashes

Hashes for composio_llamaindex-0.5.28-py3-none-any.whl
Algorithm Hash digest
SHA256 4573edbb681188bb903a34b35b38f8646db754b6f1f17be2edbdbf0c3136184a
MD5 38827c7f2419857f488466fefafa63fa
BLAKE2b-256 87f1c08c057f7c06397c88f9b9282342921fda88ef5e9478171e24c15e8b91db

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page