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)

Registering Events

from weni import Tool
from weni.context import Context
from weni.events.event import Event
from weni.responses import TextResponse

class MyTool(Tool):
    def execute(self, context: Context):
        result = do_work()

        self.register_event(Event(
            event_name="order_placed",
            key="order_123",
            value_type="string",
            value="completed",
            metadata={"customer": "John Doe"},
        ))

        return TextResponse(data=result)

Parameters:

event_name: Event name.
key: Unique key for the event.
value_type: Value type (string, int, etc).
value: Event value.
metadata: (Optional) Additional event metadata.
date: (Optional) ISO 8601 date string (defaults to current time).

Events are collected automatically per tool execution with full isolation between Lambda warm starts.

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

Clone the repository:

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

Install dependencies:

poetry install

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

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

License

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

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