General Logic
This chatbot schema is structured to provide an interactive, friendly experience for users, allowing them to engage with an AI companion that remembers user history and provides personalized responses. The logic is organized into frames that group different functionalities, such as the introductory message, user data collection, long-term memory management, and processing user input (text, voice, or images).
At the core, the bot guides users through an initial interaction where they fill out a questionnaire about themselves. Based on the information collected, it generates personalized messages and maintains a long-term memory of user facts and interests. The bot employs AI to analyze and understand user messages, responding appropriately and enhancing engagement through dialogue.
Step-by-Step Overview
1. Initial User Interaction and Questionnaire
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Welcome Message: The bot starts by sending a friendly greeting and invites the user to introduce themselves, explaining that it would like to know more about the user to provide better interaction.
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Questionnaire Prompt: A button is provided for users to fill out the questionnaire. When pressed, the bot directs the conversation to a form where the user can input information about their name, age, and interests.
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Input Form: The user is required to type at least a few words about themselves to proceed. This input is vital for personalizing future interactions.
2. Storing User Information
- Save User Facts: Once the user submits their information, the bot stores this data in the user's long-term memory. This step is executed by a database command that updates the user's bio in the system.
3. Generating Personalized Greeting
- AI-Generated Greeting: After storing the user data, the bot invokes an AI integration to create a unique welcome message. The AI uses the user's newly provided details to craft a warm and engaging greeting, including a compliment and an open-ended question to facilitate ongoing dialogue.
4. Ongoing Interaction Logic
- Message Processing: The bot includes functionality to handle various types of user inputs (text, voice messages, or images). Depending on the input type, the bot routes the interaction accordingly:
- Text Messages: It analyzes the message context to generate personalized responses or insights.
- Voice Messages: The bot transcribes audio messages into text for further processing.
- Images: The bot analyzes uploaded images to describe their content.
5. Memory Management
- Long-Term Memory Update: As the user continues to interact with the bot, new facts shared by the user are identified. The bot extracts important facts from user messages and updates its memory accordingly, ensuring that the database remains current and relevant to future conversations.
6. Final Response Management
- Return Responses to User: After processing and creating personalized content or analyzing inputs, the bot sends formulated responses back to the user, ensuring the conversation flows seamlessly and remains engaging.
Integrations and API Requests
The chatbot schema leverages several integrations, primarily utilizing OpenAI's API for generating messages and analyzing content. The following integrations are present:
- OpenAI Integration for Message Sending: The bot uses OpenAI's API to generate personalized responses based on user input and stored context.
- Voice and Image Processing: The integration also includes functionality for transcribing voice messages and analyzing images using OpenAI's different models.
Requirements for Integrations
To ensure proper functionality, the following is necessary for the integrations:
- API keys from OpenAI to access its services.
- Potential balance requirements based on usage and applicable OpenAI pricing tiers.
- Verification processes, possibly including creating an account with OpenAI, depending on the service's access levels required.
Overall, this chatbot is designed to create an engaging and personalized experience while efficiently managing user information for future interactions.
