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-0.7.10.tar.gz (4.2 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-0.7.10-py3-none-any.whl (4.6 kB view details)

Uploaded Python 3

File details

Details for the file composio_llamaindex-0.7.10.tar.gz.

File metadata

  • Download URL: composio_llamaindex-0.7.10.tar.gz
  • Upload date:
  • Size: 4.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for composio_llamaindex-0.7.10.tar.gz
Algorithm Hash digest
SHA256 f256e4677c38ddab518fb036f5df5945a1c694c18a7c6599b8138b24a23a55f0
MD5 1be198a74ca157f9181a402fdc6c144f
BLAKE2b-256 9295b3365f1469c4bc3840c9c078e6bf4521b48e99e307be04fd4fe3896d2913

See more details on using hashes here.

File details

Details for the file composio_llamaindex-0.7.10-py3-none-any.whl.

File metadata

File hashes

Hashes for composio_llamaindex-0.7.10-py3-none-any.whl
Algorithm Hash digest
SHA256 dd9b6317ddb8d2780187daf8949b1632b59478472d15e99afc4dca2d42b0431a
MD5 b03604b5ae82c58b556d31d21509b309
BLAKE2b-256 7eb900e4570a6a32ea30f739f99a93a767b6573e51f82f393d61b18d4565a349

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