weni-agents-toolkit 0.2.1

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Weni Agents Toolkit

A Python library for creating and managing agent skills for the Weni platform. Build powerful conversational agents with type-safe components and a robust skill system.

Installation

pip install weni-agents-toolkit

Or with Poetry:

poetry add weni-agents-toolkit

Quick Start

Creating a Skill

import requests
from weni import Skill
from weni.context import Context
from weni.components import Text, QuickReplies
from weni.data import register_result

class GetAddress(Skill):

    def execute(self, context: Context):
        # This is how we would retrieve credentials or sensitive information from context
        token = context.credentials.get("X-App-Token")

        # This is how we would retrieve parameters for this agent tool
        cep = context.parameters.get("cep")

        # This is how we would retrieve global constants for this project
        api_url = context.globals.get("cep_api_url")

        # This block is the business logic for the sake of this example on retrieving an address based on the received CEP
        base_url = f"{api_url}/{cep}"
        response = requests.get(base_url, headers={"Authorization": f"Bearer {token}"})

        result = response.json()

        # This block is where data is registered for further analysis in the future
        register_result("address", result.get("street"))

        # This example I'm respoonding allowing quick replies message or a location
        return TextResponse(data=result)

Core Concepts

Context System

The context system provides secure access to:

context = Context(
    credentials={"api_key": "secret123"},     # Sensitive data
    parameters={"user_id": "123"},            # Skill parameters
    globals={"env": "production"}             # Global configuration
)

Available Components

• Text: Basic text messages
• QuickReplies: Interactive quick reply buttons
• ListMessage: Interactive list menus
• CTAMessage: Call-to-action messages
• Location: Location request messages
• OrderDetails: Order information messages
• Attachments: File attachments
• Header: Message headers
• Footer: Message footers

Response Types

• TextResponse: Simple text messages
• QuickReplyResponse: Messages with quick reply buttons
• ListMessageResponse: Interactive list menus
• CTAMessageResponse: Call-to-action messages
• LocationResponse: Location-based messages
• OrderDetailsResponse: Order information displays

Development

Prerequisites

• Python 3.9+
• Poetry

Setup

1. Clone the repository:

git clone https://github.com/weni-ai/agents-toolkit.git
cd agents-toolkit

2. Install dependencies:

poetry install

3. Run tests:

poetry run pytest

Code Quality

We use several tools to ensure code quality:

• pytest for testing
• mypy for type checking
• ruff for linting

Run all checks:

poetry run pytest
poetry run mypy weni
poetry run ruff check .

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.