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Hiba ZyatiYe Yoooo!
Asked: 1 year ago2024-11-21T14:51:04+00:00 2024-11-21T14:51:04+00:00In: Coding

How to make api.ai agent learn something dynamically?

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I am currently using api.ai , to create agent to perform specific tasks, but one question i don’t have answer to is , can i make it learn something while chatting , mean that i speak my name is ‘John Cena’ and she should store it and then whenever i ask her again bot should answer me that. i know there is a way to do it by logging into api.ai web and manually add entries , but it will not help, is there any work around programmatically or automatically ? the file i’ve been using to practice is given in github . and here is working DEMO

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  1. Aisupersmart God Level!
    2024-11-21T14:52:05+00:00Added an answer about 1 year ago

    I hear you, manually adding entries in api.ai (now Dialogflow) for every new piece of information can get tedious fast. Here’s how you can make your agent learn dynamically during chats, just like you want it to remember your name is John Cena!

    There are two main approaches:

    1. Using Webhooks:

    Webhooks are a powerful way to extend your agent’s capabilities. Here’s the idea:

    • When the user says “My name is John Cena,” your agent captures this intent (likely a custom intent you created).
    • Instead of having a pre-defined response, the agent sends this information to a webhook you’ve created (a separate program you write).
    • Your webhook can then:
      • Store the user ID and John Cena in a database (like Firebase or a simple text file).
      • Send a confirmation response back to the agent (e.g., “Nice to meet you, John Cena!”).
    • Now, whenever John Cena interacts with the agent again, the agent can send the user ID to the webhook.
    • The webhook can then retrieve John Cena’s name from the database and send it back to the agent.
      • The agent can then respond with something like, “Hey John Cena, good to see you again!”

    This feels a lot like John Cena’s entrance music – dramatic reveal of a stored fact!

    2. Using Contexts:

    Contexts are a built-in feature in Dialogflow that allows you to store temporary information about the conversation. This approach works well if you only need to remember user information within a single session.

    Here’s the breakdown:

    • When the user says “My name is John Cena,” capture this information in a context variable (e.g., “userName”).
    • Use this context variable in your responses throughout the conversation. (e.g., “Hi there, ${userName}!”).
    • Once the conversation ends, the context gets cleared automatically.

    Here’s an example of using a webhook (approach 1):

    Your webhook program could be written in Python and utilize a simple library like sqlite3 to store data in a local database. Here’s a simplified example (remember, this requires additional coding):

    Python
    import sqlite3
    
    def handle_webhook(request):
      # Get user ID and name from the request
      user_id = request.get("user_id")
      name = request.get("name")
    
      # Connect to the database
      conn = sqlite3.connect("user_data.db")
      cursor = conn.cursor()
    
      # Store user ID and name
      cursor.execute("INSERT INTO users (user_id, name) VALUES (?, ?)", (user_id, name))
      conn.commit()
      conn.close()
    
      # Send confirmation response
      return {"message": "Nice to meet you, " + name + "!"}
    

    Both approaches have their pros and cons. Webhooks offer more flexibility and persistence, while contexts are simpler to implement but lose information across sessions.

    Remember, the example code snippet here is just a starting point. You’ll need to adapt it to your specific needs and chosen programming language.

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