## 🚀🔗 Leveraging PraisonAI with Composio
Facilitate the integration of PraisonAI with Composio to empower Praison Agents to directly interact with external applications, broadening their capabilities and application scope.
### Objective
- **Automate starring a GitHub repository** using conversational instructions via PraisonAI Agents.
### Installation and Setup
Ensure you have the necessary packages installed and connect your GitHub account to allow your agents to utilize GitHub functionalities.
```bash
# Install Composio LangChain package
pip install composio-praisonai
# 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 Praison and setting up your client.
```python
import os
import yaml
from praisonai import PraisonAI
```
### Step 2: Write the Praison-supported Composio Tools ins `tools.py` file.
This step involves fetching and integrating GitHub tools provided by Composio, and writing them in Praison supported Format, returning the name of tools in a format, that should be added to `agents.yml` file.
```python
from composio_praisonai import Action, ComposioToolSet
composio_toolset = ComposioToolSet()
tools = composio_toolset.get_actions(
actions=[Action.GITHUB_STAR_A_REPOSITORY_FOR_THE_AUTHENTICATED_USER]
)
tool_section_str = composio_toolset.get_tools_section(tools)
print(tool_section_str)
```
### Step 3: 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.
```python
agent_yaml = """
framework: "crewai"
topic: "Github Management"
roles:
developer:
role: "Developer"
goal: "An expert programmer"
backstory: "A developer exploring new codebases and have 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)
```
### Step 4: Run the Praison Agents to execute the goal/task.
Here you initialize PraisonAI class, and execute.
```python
# 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)
```
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"description": "## \ud83d\ude80\ud83d\udd17 Leveraging PraisonAI with Composio\n\nFacilitate the integration of PraisonAI with Composio to empower Praison Agents to directly interact with external applications, broadening their capabilities and application scope.\n\n### Objective\n\n- **Automate starring a GitHub repository** using conversational instructions via PraisonAI Agents.\n\n### Installation and Setup\n\nEnsure you have the necessary packages installed and connect your GitHub account to allow your agents to utilize GitHub functionalities.\n\n```bash\n# Install Composio LangChain package\npip install composio-praisonai\n\n# Connect your GitHub account\ncomposio-cli add github\n\n# View available applications you can connect with\ncomposio-cli show-apps\n```\n\n### Usage Steps\n\n#### 1. Import Base Packages\n\nPrepare your environment by initializing necessary imports from Praison and setting up your client.\n\n```python\nimport os\nimport yaml\nfrom praisonai import PraisonAI\n```\n\n### Step 2: Write the Praison-supported Composio Tools ins `tools.py` file.\n\nThis step involves fetching and integrating GitHub tools provided by Composio, and writing them in Praison supported Format, returning the name of tools in a format, that should be added to `agents.yml` file.\n```python\nfrom composio_praisonai import Action, ComposioToolSet\n\ncomposio_toolset = ComposioToolSet()\ntools = composio_toolset.get_actions(\n actions=[Action.GITHUB_STAR_A_REPOSITORY_FOR_THE_AUTHENTICATED_USER]\n)\n\ntool_section_str = composio_toolset.get_tools_section(tools)\nprint(tool_section_str)\n```\n\n### Step 3: Define the 'agents_yml` either in a separate file, or in your script.\n\nThis step involves configuring and executing the agent to carry out actions, such as starring a GitHub repository.\n\n```python\nagent_yaml = \"\"\"\nframework: \"crewai\"\ntopic: \"Github Management\"\n\nroles:\n developer:\n role: \"Developer\"\n goal: \"An expert programmer\"\n backstory: \"A developer exploring new codebases and have certain tools available to execute different tasks.\"\n tasks:\n star_github:\n description: \"Star a repo composiohq/composio on GitHub\"\n expected_output: \"Response whether the task was executed.\"\n\"\"\" + tool_section_str\n\nprint(agent_yaml)\n```\n\n### Step 4: Run the Praison Agents to execute the goal/task.\n\nHere you initialize PraisonAI class, and execute.\n```python\n# Create a PraisonAI instance with the agent_yaml content\npraison_ai = PraisonAI(agent_yaml=agent_yaml)\n\n# Run PraisonAI\nresult = praison_ai.main()\n\n# Print the result\nprint(result)\n```\n",
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