Implementing Responses and Actions in Your Chatbot

Day 7: Building an AI Chatbot from Scratch

Welcome back to our 10-day journey in creating your own AI chatbot! We’ve covered a lot, from setting up the development environment to handling user inputs effectively. Today, we’ll focus on a crucial aspect of chatbot development: implementing responses and actions.

Defining Responses Based on User Input

Now that your chatbot can understand user inputs, it’s time to define responses. Responses are the messages or actions your chatbot performs based on the recognized intent and processed user input. Today, we’ll explore how to implement responses within the chosen framework.

Example Responses (Rasa):

# domain.yml

responses:
  utter_greet:
    - text: "Hello! How can I assist you today?"

  utter_ask_info:
    - text: "Sure, I can help with that. What information are you looking for?"

  utter_express_thanks:
    - text: "You're welcome! Is there anything else I can help you with?"

In this example, we’ve defined responses corresponding to specific intents. Each response includes one or more text messages that the chatbot can use to communicate with the user.

Adding Actions and Functionalities

In addition to simple text responses, your chatbot can perform actions and execute functionalities based on user inputs. Actions can range from retrieving information from external sources to triggering specific processes within the chatbot.

Example Action (Rasa):

# actions.py (Rasa)

from typing import Any, Text, Dict, List
from rasa_sdk import Action, Tracker
from rasa_sdk.executor import CollectingDispatcher

class ActionProvideInformation(Action):
    def name(self) -> Text:
        return "action_provide_information"

    def run(
        self, dispatcher: CollectingDispatcher, tracker: Tracker, domain: Dict[Text, Any]
    ) -> List[Dict[Text, Any]]:
        # Perform action logic (e.g., fetch information from a database)
        info = self.retrieve_information()

        # Respond to the user with the retrieved information
        dispatcher.utter_message(f"Here is the information you requested: {info}")

        return []

Testing and Refining Your Responses

After implementing responses and actions, it’s crucial to test your chatbot extensively. Interact with it using different inputs to ensure it responds appropriately and performs the expected actions. Refine your responses based on user feedback and testing results.

Share Your Progress

Share your experiences, code snippets, and any challenges you faced while implementing responses and actions in the comments section. Tomorrow, we’ll focus on enhancing the user experience with multimedia elements. Stay tuned and happy coding!