> ## Documentation Index
> Fetch the complete documentation index at: https://composio-27-feat-docs-revamp.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# 📖 Using Composio With PraisonAI

> Integrate Composio with PraisonAI agents to let them seamlessly interact with external apps

**Composio** enables your **PraisonAI agents** to **connect** with many **tools**!

<Tip>Goal: Star a repository on GitHub with natural language & PraisonAI Agent</Tip>

### Install Packages & Connect a Tool

These commands prepare your environment for seamless interaction between PraisonAI and GitHub.

<CodeGroup>
  ```bash Run command
  pip install PraisonAI -q
  pip install composio-praisonai
  # login to composio
  composio login
  # Connect your GitHub using command below, so agents can use it. 
  composio add github
  # Check all different apps which you can connect with
  composio apps
  ```
</CodeGroup>

### Goal: Use PraisonAI Agent to Interact with Github using Composio

<Steps>
  <Step title="Import Base Packages">
    Prepare your environment by initializing necessary imports from PraisonAI and setting up your client.

    <CodeGroup>
      ```python Default Imports
      import os
      import yaml
      from praisonai import PraisonAI

      from composio_praisonai import Action, ComposioToolSet
      ```
    </CodeGroup>
  </Step>

  <Step title="Write the Praison-supported Composio Tools in `tools.py` file.">
    This step involves fetching and integrating GitHub tools provided by Composio, and writing them in PraisonAI supported Format, returning the name of tools in a format, that should be added to `agents.yml` file.

    <CodeGroup>
      ```python Write the tools
      composio_toolset = ComposioToolSet()
      tools = composio_toolset.get_tools(
          actions=[Action.GITHUB_ACTIVITY_STAR_REPO_FOR_AUTHENTICATED_USER]
      )
      tool_section_str = composio_toolset.get_tools_section(tools)
      print(tool_section_str)
      ```
    </CodeGroup>
  </Step>

  <Step title="Define the `agents.yml` either in a separate file, or in your script.">
    This step involves configuring and executing the agent to carry out actions, such as starring a GitHub repository.

    <CodeGroup>
      ```python Define agent.yml
      agent_yaml = """
      framework: "crewai"
      topic: "Github Management"

      roles:
        developer:
          role: "Developer"
          goal: "An expert programmer"
          backstory: "A developer exploring new codebases and having certain tools available to execute different tasks."
          tasks:
            star_github:
              description: "Star a repo composiohq/composio on GitHub"
              expected_output: "Response whether the task was executed."
      """ + tool_section_str

      print(agent_yaml)
      ```
    </CodeGroup>
  </Step>

  <Step title="Run the PraisonAI Agents to execute the goal/task.">
    Here you initialize PraisonAI class, and execute.

    <CodeGroup>
      ```python Define agent.yml
      # Create a PraisonAI instance with the agent_yaml content
      praison_ai = PraisonAI(agent_yaml=agent_yaml)

      # Run PraisonAI
      result = praison_ai.main()

      # Print the result
      print(result)
      ```
    </CodeGroup>
  </Step>
</Steps>