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Composio

Composio equips agents with well-crafted tools empowering them to tackle complex tasks

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Production Ready Toolset for AI Agents

Equip your agent with high-quality tools & integrations without worrying about authentication, accuracy, and reliability in a single line of code!


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📋 Table of contents

🤔 Why Composio?

We believe AI Based Agents/Workflows are the future. Composio is the best toolset to integrate AI Agents to best Agentic Tools and use them to accomplish tasks.

Illustration

🔥 Key Features

  • 100+ Tools: Support for a range of different categories

    • Softwares: Do anything on GitHub, Notion, Linear, Gmail, Slack, Hubspot, Salesforce, & 90 more.
    • OS: Click anywhere, Type anything, Copy to Clipboard, & more.
    • Browser: Smart Search, Take a screenshot, MultiOn, Download, Upload, & more.
    • Search: Google Search, Perplexity Search, Tavily, Exa & more.
    • SWE: Ngrok, Database, Redis, Vercel, Git, etc.
    • RAG: Agentic RAG for any type of data on the fly!
  • Frameworks: Use tools with agent frameworks like OpenAI, Claude, LlamaIndex, Langchain, CrewAI, Autogen, Gemini, Julep, Lyzr, and more in a single line of code.

  • Managed Authorisation: Supports six different auth protocols. Access Token, Refresh token, OAuth, API Keys, JWT, and more abstracted out so you can focus on the building agents.

  • Accuracy: Get upto 40% better agentic accuracy in your tool calls due to better tool designs.

  • Embeddable: Whitelabel in the backend of your applications managing Auth & Integrations for all your users & agents and maintain a consistent experience.

  • Pluggable: Designed to be extended with additional Tools, Frameworks and Authorisation Protocols very easily.

🚀 Getting Started

1. Installation

To get started, type the following command in your Terminal.

pip install composio-core

If you want to install the 'composio' package along with its openai plugin: pip install composio-openai.

2. Testing Composio in Action

Let's use Composio to create an AI Agent that can star a Github Repo.

composio add github # Connect your Github - Run this in terminal
from openai import OpenAI
from composio_openai import ComposioToolSet, App, Action

openai_client = OpenAI(
    api_key="{{OPENAIKEY}}"
)

# Initialise the Composio Tool Set

composio_tool_set = ComposioToolSet()

# Get GitHub tools that are pre-configured
actions = composio_tool_set.get_actions(
    actions=[Action.GITHUB_ACTIVITY_STAR_REPO_FOR_AUTHENTICATED_USER]
)

my_task = "Star a repo composiodev/composio on GitHub"

# Setup openai assistant
assistant_instruction = "You are a super intelligent personal assistant"

assistant = openai_client.beta.assistants.create(
    name="Personal Assistant",
    instructions=assistant_instruction,
    model="gpt-4-turbo",
    tools=actions,
)

# create a thread
thread = openai_client.beta.threads.create()

message = openai_client.beta.threads.messages.create(
    thread_id=thread.id,
    role="user",
    content=my_task
)

# Execute Agent with integrations
run = openai_client.beta.threads.runs.create(
    thread_id=thread.id,
    assistant_id=assistant.id
)


# Execute Function calls
response_after_tool_calls = composio_tool_set.wait_and_handle_assistant_tool_calls(
    client=openai_client,
    run=run,
    thread=thread,
)

print(response_after_tool_calls)

💡 Examples

📋 Read Our Code Of Conduct

As part of our open-source community, we hold ourselves and other contributors to a high standard of communication. As a participant and contributor to this project, you agree to abide by our Code of Conduct.

🤗 Contributions

Composio is open-source and we welcome contributions. Please fork the repository, create a new branch for your feature, add your feature or improvement, and send a pull request.

Also go through our Contribution Guidelines and Code of Conduct before you start.

🔗 Links

🛡️ License

Composio is licensed under the Elastic License - see the LICENSE file for details.

💪 Thanks To All Contributors

List of Contributors

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    Composio equip's your AI agents & LLMs with 100+ high-quality integrations via function calling

    Python 11.7k 4.3k

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