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-0.5.17.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-0.5.17-py3-none-any.whl (4.3 kB view details)

Uploaded Python 3

File details

Details for the file composio_llamaindex-0.5.17.tar.gz.

File metadata

  • Download URL: composio_llamaindex-0.5.17.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-0.5.17.tar.gz
Algorithm Hash digest
SHA256 3813ecd549fd194efcba29852ae642d3c356d85548c6e62522ba79cc44d0549c
MD5 201b19a4ff8a2a2afefc951a6b8e645b
BLAKE2b-256 10ee17dbcca6350830b7234060cc9284f5bff0769754e4f185e80fea658b67c0

See more details on using hashes here.

File details

Details for the file composio_llamaindex-0.5.17-py3-none-any.whl.

File metadata

File hashes

Hashes for composio_llamaindex-0.5.17-py3-none-any.whl
Algorithm Hash digest
SHA256 e78d3cc2a4953be3ebb6ec64b24e56212cee392713a4252bb77c1af99b82b921
MD5 8ed080c6ac9a409c6609cc109e303a0f
BLAKE2b-256 237c52f9b53c76ffe574be1eb21abc054d6380c7bcc9ce422bd59477027d243e

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