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-0.5.35.tar.gz (3.9 kB view details)

Uploaded Source

Built Distribution

composio_llamaindex-0.5.35-py3-none-any.whl (4.4 kB view details)

Uploaded Python 3

File details

Details for the file composio_llamaindex-0.5.35.tar.gz.

File metadata

  • Download URL: composio_llamaindex-0.5.35.tar.gz
  • Upload date:
  • Size: 3.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for composio_llamaindex-0.5.35.tar.gz
Algorithm Hash digest
SHA256 dd1819055952e5dba36c891449fd61bc47dafe24991167f55f41735c57325295
MD5 0b315656fe71fd11006b86d268676e97
BLAKE2b-256 4ac46d082af01dbf7b1468de0417b3464fefb6268aad8c8796418d92338e7b9b

See more details on using hashes here.

File details

Details for the file composio_llamaindex-0.5.35-py3-none-any.whl.

File metadata

File hashes

Hashes for composio_llamaindex-0.5.35-py3-none-any.whl
Algorithm Hash digest
SHA256 4beabd1e437575d2cfda4aa2c37eac3e90a90950439c8735b7ff04ab68e0320c
MD5 b5cb5e64450b46c96bc33137d1d2cdba
BLAKE2b-256 8fc6426932df0ebfeaf4752428b5acf0698ad3037ccd1fe63a5096273027fc46

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