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-0.5.46.tar.gz (4.0 kB view details)

Uploaded Source

Built Distribution

composio_llamaindex-0.5.46-py3-none-any.whl (4.4 kB view details)

Uploaded Python 3

File details

Details for the file composio_llamaindex-0.5.46.tar.gz.

File metadata

  • Download URL: composio_llamaindex-0.5.46.tar.gz
  • Upload date:
  • Size: 4.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for composio_llamaindex-0.5.46.tar.gz
Algorithm Hash digest
SHA256 a635ce43d45c47fc90e985f8b93d65d0b15690e665d3c4f88d3ba7c74c1d2634
MD5 f0cb99edfd9f38310018fbc5cea67ef5
BLAKE2b-256 f5a09f971e68345759f162d3a10742254452353165b990e9048a05677163bc29

See more details on using hashes here.

File details

Details for the file composio_llamaindex-0.5.46-py3-none-any.whl.

File metadata

File hashes

Hashes for composio_llamaindex-0.5.46-py3-none-any.whl
Algorithm Hash digest
SHA256 efa7e25da3e813fc03c0b3a02a349668f760613e606d2a971b3e5e361ac637dd
MD5 e2673b479df21135f614eb548e34d6c4
BLAKE2b-256 a683379357ffe986bfb41d6c3a8a7d077751c99003f2c660fa1a0ca5907a601f

See more details on using hashes here.

Supported by

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