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Build Your Own AI Fortuneteller with Tarot Cards and LLMs

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This article provides a comprehensive guide to building an AI application that interprets Tarot cards and delivers fortune-telling experiences. It outlines the core features, technology stack, data gathering, and development steps necessary to create an engaging AI fortuneteller using Google Gemini 1.5 Flash.
  • main points
  • unique insights
  • practical applications
  • key topics
  • key insights
  • learning outcomes

  • • main points

    • 1
      Detailed step-by-step guide for building an AI fortuneteller
    • 2
      Clear explanation of technology stack and data requirements
    • 3
      Innovative use of AI in a creative application

  • • unique insights

    • 1
      Emphasizes the educational aspect of using AI for Tarot interpretation
    • 2
      Provides a structured approach to integrating AI with traditional practices

  • • practical applications

    • The article offers practical guidance for developers interested in creating AI applications, particularly those blending technology with creative arts.

  • • key topics

    • 1
      AI Application Development
    • 2
      Tarot Card Interpretation
    • 3
      Large Language Models

  • • key insights

    • 1
      Combines AI technology with traditional Tarot reading
    • 2
      Focuses on educational insights into LLMs
    • 3
      Provides a clear framework for application development

  • • learning outcomes

    • 1
      Understand the process of building an AI application using LLMs
    • 2
      Learn how to structure data for AI interpretation
    • 3
      Gain insights into the creative application of AI technology
examples
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“ Introduction: Building an AI Fortuneteller

In this guide, we'll explore how to create an AI application that interprets Tarot cards and provides a fortune-telling experience. This project serves as an educational tool to understand Large Language Models (LLMs) and their practical applications. Note that this article is for educational purposes only.

“ Step 1: Defining the Requirements for Your AI Tarot Reader

Before starting development, it's crucial to outline the requirements for the AI fortuneteller. The core feature is to provide fortune predictions based on user-selected Tarot cards. Users will choose five cards representing Past, Present, Challenge, Advice, and Outcome. The application should interpret these cards in relation to the user's question.

“ Step 2: Choosing the Right Tech Stack

The choice of technologies impacts the project's scalability and performance. Here's a suggested tech stack: * **Database:** A JSON file is sufficient for storing Tarot card information due to the small dataset size and random card selection. * **AI Model:** Google Gemini 1.5 Flash is selected for its ability to generate constructive and insightful responses based on Tarot card information and user queries.

“ Step 3: Gathering and Preparing Tarot Card Data

High-quality data is essential for AI models. The Tarot card data needs to be converted and stored in a JSON format for easy access and structuring. The JSON format includes fields such as name, suite, image, description, and interpretation. The interpretation field holds keywords related to the card, which are crucial for generating relevant answers.

“ Step 4: Developing the AI Fortuneteller Application

The development process involves reading the Tarot card data from the JSON file and creating an LLM instance using Google Gemini 1.5 Flash. A function is created to interpret each card, extracting its name, suite, description, and interpretation. This function is then called for each of the five selected cards (Past, Present, Challenge, Advice, Outcome).

“ Crafting the Perfect Prompt for Insightful Responses

Crafting a well-structured and contextual prompt is key to generating insightful and mystical responses. The prompt should: * Introduce card details, connecting them to the user's question. * Emulate the tone of a fortune teller, using mystical and sympathetic language. * Address the user's query directly, tailoring the answer to the question.

“ Generating AI Responses and Interpreting the Results

The LLM model is invoked with the system prompt, generating a response based on the user's question and the selected Tarot cards. The response is then interpreted to provide guidance and insights. The AI offers possibilities, personal growth, and self-reflection rather than making absolute predictions about the future.

“ Conclusion: The Power of AI in Fortune Telling

By using a simple JSON structure and a language model like Google Gemini 1.5 Flash, we can efficiently generate insightful answers to user queries. The key is to craft a good prompt that includes card details and evokes the fortune teller's storytelling style. This approach provides personalized and meaningful responses that resonate with users.

 Original link: https://medium.com/@dange.laxmikant/step-by-step-guide-to-creating-an-ai-fortuneteller-1067e8205f67

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