How does the Gen AI bubble work?

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The Gen AI bubble is a tool designed to integrate artificial intelligence capabilities, such as those offered by OpenAI, into messaging applications or chatbot systems. Here’s an explanation of how it works based on the provided text:

  1. Discussion Data Storage : The Gen AI bubble offers an intuitive way to specify what question is sent to the bot and where the AI’s response data should be stored. This allows for easy management of conversation data for analysis or future reference.

  2. Navigating Between Bubbles: You can define what the next bubble will be after the AI’s response (in case of success), as well as a fallback bubble to handle cases where the AI fails to provide an adequate response (server error, too much latency…). This ensures a smooth and consistent user experience.

  3. Handover to an Agent: In certain specific cases of your choosing, the discussion can be handed over to a human agent through an operation bubble. This is useful for complex or sensitive situations that require human intervention.

  4. Custom Prompting: You have the option to add a custom prompt to guide the AI’s responses, thereby better controlling the context and relevance of the generated answers.

  5. Configuration Parameters:

    • Max_tokens: Controls the length of the AI’s response, allowing you to tailor the amount of information provided to the conversation’s needs.
    • Temperature: Adjusts the balance between coherence and creativity in the responses. A higher temperature generates more diverse and creative answers.
    • Top_p: An alternative to the temperature parameter, offering another way to manage the variability of responses.
    • n: Determines the number of completion choices to generate for each incoming message, thus allowing you to select the best response from multiple options.
    • User: A unique identifier representing the end-user, which helps OpenAI monitor and detect abuse.

In summary, the Gen AI bubble is a powerful tool for integrating artificial intelligence into chatbot interactions, offering great flexibility in conversation management, response personalization, and the involvement of human agents when necessary.