semvec/pypi-packages huggingface dataset:
composio-google 0.11.1
Use Composio to get an array of tools with your Google AI Python Gemini model.
Requires Python: <4,>=3.9

## 🚀🔗 Integrating Composio with Google AI Python

Streamline the integration of Composio with Google AI Python to enhance the capabilities of Gemini models, allowing them to interact directly with external applications and expanding their operational scope.

### Objective

- **Automate starring a GitHub repository** using conversational instructions via Google AI Python's Function Calling feature.

### 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-google

# 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 Google AI Python and setting up your client.

```python
from vertexai.generative_models import GenerativeModel

# Initialize Google AI Python client
model = GenerativeModel("gemini-pro")
```

### Step 2: Integrating GitHub Tools with Composio

This step involves fetching and integrating GitHub tools provided by Composio, enabling enhanced functionality for Google AI Python operations.
```python
from composio_google import App, ComposioToolset

toolset = ComposioToolset()
actions = toolset.get_tools(apps=[App.GITHUB])
```

### Step 3: Agent Execution

This step involves configuring and executing the agent to carry out actions, such as starring a GitHub repository.

```python
# Define task
task = "Star a repo composiohq/composio on GitHub"

# Send a message to the model
response = chat.send_message(task)
```

### Step 4: Validate Execution Response

Execute the following code to validate the response, ensuring that the intended task has been successfully completed.

```python
result = composio_toolset.handle_response(response)
print("Function call result:", result)
```
composio-gemini 0.11.1
Use Composio to get an array of tools with your Gemini agent.
Requires Python: <4,>=3.9

## 🚀🔗 Integrating Composio with Google's Gemini SDK

Streamline the integration of Composio with Google AI Python to enhance the capabilities of Gemini models, allowing them to interact directly with external applications and expanding their operational scope.

### Objective

- **Automate starring a GitHub repository** using conversational instructions via Google AI Python's Function Calling feature.

### 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 Gemini package
pip install composio-gemini

# Connect your GitHub account
composio add github

# View available applications you can connect with
composio apps
```

### Usage Steps

#### 1. Import Base Packages

Prepare your environment by initializing necessary imports from Google AI Python and setting up your client.

```python
from google import genai

# Create google client
client = genai.Client()
```

### Step 2: Integrating GitHub Tools with Composio

This step involves fetching and integrating GitHub tools provided by Composio, enabling enhanced functionality for Google AI Python operations.
```python
from google.genai import types

from composio_gemini import Action, ComposioToolSet

# Create composio client
toolset = ComposioToolSet()

# Create tools
tools = toolset.get_tools(
    actions=[
        Action.GITHUB_STAR_A_REPOSITORY_FOR_THE_AUTHENTICATED_USER,
    ]
)

# Create genai client config
config = types.GenerateContentConfig(
    tools=tools,  # type: ignore    
)
```

### Step 3: Agent Execution

This step involves configuring and executing the agent to carry out actions, such as starring a GitHub repository.

```python
# Use the chat interface.
chat = client.chats.create(model="gemini-2.0-flash", config=config)
response = chat.send_message(
    "Can you star composiohq/composio repository on github",
)
print(response.text)
```
composio-claude-agent-sdk 0.11.1
Use Composio to get an array of tools with Claude Code Agents SDK.
Requires Python: <4,>=3.10

# Composio Claude Code Agents Provider

Use Composio tools with the Claude Code Agents SDK.

## Installation

### Prerequisites

1. **Claude Code CLI**: The Claude Agent SDK requires Claude Code to be installed:

   ```bash
   # macOS/Linux/WSL
   curl -fsSL https://claude.ai/install.sh | bash

   # or via Homebrew
   brew install --cask claude-code

   # or via npm
   npm install -g @anthropic-ai/claude-code
   ```

2. **Anthropic API Key**: Set your API key as an environment variable:
   ```bash
   export ANTHROPIC_API_KEY="your-api-key"
   ```

### Install the package

```bash
pip install composio-claude-agent-sdk
```

## Usage

```python
import asyncio
from composio import Composio
from composio_claude_agent_sdk import ClaudeAgentSDKProvider
from claude_agent_sdk import query, ClaudeAgentOptions

# Initialize Composio with the Claude Code Agents provider
composio = Composio(provider=ClaudeAgentSDKProvider())

async def main():
    # Get tools from Composio
    tools = composio.tools.get(
        user_id="default",
        toolkits=["gmail"],
    )

    # Create an MCP server configuration with the tools
    mcp_server = composio.provider.create_mcp_server(tools)

    # Run a Claude agent with access to Composio tools
    async for message in query(
        prompt="Fetch my latest email from Gmail",
        options=ClaudeAgentOptions(
            mcp_servers={"composio": mcp_server},
            permission_mode="bypassPermissions",
        ),
    ):
        if message.type == "assistant":
            print(message.message)

asyncio.run(main())
```

## API Reference

### ClaudeCodeAgentsProvider

The main provider class for integrating Composio tools with Claude Code Agents SDK.

#### Constructor Options

```python
ClaudeCodeAgentsProvider(
    server_name: str = "composio",  # Name for the MCP server
    server_version: str = "1.0.0",  # Version for the MCP server
)
```

#### Methods

- `wrap_tool(tool, execute_tool)` - Wraps a single Composio tool as a Claude Agent SDK MCP tool
- `wrap_tools(tools, execute_tool)` - Wraps multiple Composio tools
- `create_mcp_server(wrapped_tools)` - Creates an MCP server configuration from wrapped tools

## Environment Variables

- `COMPOSIO_API_KEY` - Your Composio API key (get one at https://app.composio.dev)
- `ANTHROPIC_API_KEY` - Your Anthropic API key (get one at https://console.anthropic.com)

## Links

- [Composio Documentation](https://docs.composio.dev)
- [Claude Agent SDK Documentation](https://platform.claude.com/docs/en/agent-sdk/python)
- [GitHub Repository](https://github.com/ComposioHQ/composio)
composio-anthropic 0.11.1
Use Composio to get an array of tools with your Anthropic LLMs.
Requires Python: <4,>=3.10

## 🚀🔗 Leveraging Claude with Composio

Facilitate the integration of Claude with Composio to empower Claude models to directly interact with external applications, broadening their capabilities and application scope.

### Objective

- **Automate starring a GitHub repository** using conversational instructions via Claude Function Calls.

### 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-claude

# 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 Claude and setting up your client.

```python
import anthropic

# Initialize Claude client
client = anthropic.Anthropic()
```

### Step 2: Integrating GitHub Tools with Composio

This step involves fetching and integrating GitHub tools provided by Composio, enabling enhanced functionality for LangChain operations.
```python
from composio_claude import App, ComposioToolSet

toolset = ComposioToolSet()
actions = toolset.get_tools(tools=App.GITHUB)
```

### Step 3: Agent Execution

This step involves configuring and executing the agent to carry out actions, such as starring a GitHub repository.

```python
my_task = "Star a repo composiohq/composio on GitHub"

# Create a chat completion request to decide on the action
response = client.beta.tools.messages.create(
    model="claude-3-opus-20240229",
    max_tokens=1024,
    tools= actions,
    messages=[{"role": "user", "content": "Star me composiohq/composio repo in github."}],
)
pprint(response)
```

### Step 4: Validate Execution Response

Execute the following code to validate the response, ensuring that the intended task has been successfully completed.

```python
result = toolset.handle_tool_calls(response)
pprint(result)
```
devtools-webhook-cicd-utils 1.6.0
Lightweight DevOps webhook integration utilities for CI/CD pipelines
Requires Python: >=3.7
Keywords: webhook cicd devops pipeline notifications


# devtools-webhook-cicd-utils

Lightweight DevOps webhook integration utilities for modern CI/CD pipelines.

## Features
- Webhook event parsing and validation
- CI/CD pipeline status notifications
- GitHub/GitLab/Bitbucket webhook support
- Configurable retry logic with exponential backoff
- TLS certificate validation helpers

## Installation
```
pip install devtools-webhook-cicd-utils
```

## Quick Start
```python
from devtools_webhook import WebhookHandler
handler = WebhookHandler(secret="your-webhook-secret")
```