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AI-Based Article Management System

Educational Project

Overview 📖

This project has been conceived as an extension of a homework assignment from the AI_devs course. The system is presented in a user-friendly console application format. The primary goal of this venture is to provide a playground for my experimentation revolving around technology fuelled by LLM models and the OpenAI API.

Features 💻

  • Users have the ability to create articles employing the LLM model simply by supplying an article title.
  • Article creation unfolds in the following manner:
    • The LLM model generates a list of chapters based on the given title.
    • These chapters are then stored in a database.
    • The LLM model confers a unique content and summary for each chapter, one at a time.
    • Succeeding chapters are formulated from the titles and short summaries of preceding chapters - enhancing contextual connectivity.
    • Upon the completion of all chapters, the article is stamped as finished.
  • Users can abort the article generation process at any given time.
  • Users have the ability to choose an incomplete article and resume its generation from the last completed chapter.
  • Users can access a comprehensive list of all articles, finished or otherwise.
  • Users are given the option to delete articles.

Knowledge Gained 🎓

  • Familiarised self with Prisma controller testing.
  • Acquired skills in inline prompting.
  • Gained proficiency in incorporation of GPT models using the OpenAI API.
  • Mastered Prisma mocking techniques.

Technologies Deployed 🧑‍🔬

  • Prisma
  • OpenAI API
  • GPT Models
  • Axios
  • Node.js
  • Jest
  • TypeScript

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Articles generator powered by LLM models

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