AI Tools - Web Application Development

Portfolio

Arigato AI

In this project, I developed a specialized AI tool by integrating various generative AI model APIs using Python libraries LangChain and LangGraph.

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Background and Objectives

In recent years, many companies and individuals have benefited from the widespread adoption of generative AI. However, conventional chat-based generative AI often requires complex prompt engineering or is too general-purpose, making it difficult for many users to utilize effectively.

Therefore, this project aimed to create an environment where anyone can easily obtain high-quality results from generative AI with minimal input by designing purpose-specific applications with focused functionality.

Feature Introduction

This tool is designed as a dedicated application for specific use cases.

Users don't need to create complex prompts themselves; they simply enter keywords or basic information, and the system automatically generates optimal prompts internally, delivering sophisticated outputs.

This allows users to utilize generative AI intuitively and efficiently without requiring specialized knowledge.

Examples of Use

  • Social Media Management Guide: Automatically generates guidelines for effective social media account management.
  • Digital Marketing Strategy Planning: Presents effective marketing strategy frameworks and implementation plans.
  • Rap Lyrics Generator: Creates unique and creative rap lyrics.
  • Keyword Research Tool: Suggests SEO keywords based on target user search intent and supports content strategy development.

Technical Specifications

This project consists of the following main components:

  • Features
    • Lightweight and Fast Web App: Built with lightweight HTML, CSS, and minimal JavaScript to optimize loading speed and SEO performance.
    • Serverless Backend: Implements a serverless and scalable backend environment using Python and Google Cloud Run Functions. *Cloud Run Function efficiently executes API calls and data processing in a serverless environment.
  • Python Libraries:
    • LangChain: A foundational library for integrating and managing multiple generative AI vendor APIs.
    • LangGraph: A specialized library that enables flexible construction and management of complex API integrations and data workflows.
  • Cloud Infrastructure:
    • Cloud Run Function: Handles API calls in a serverless environment.
  • Web Frontend:
    • Features an intuitive interface that allows users to access AI tool functions in real-time through JavaScript-powered backend API calls.

Future Prospects

While this project is currently on hold, I'm considering the following enhancements for future development:

  • Implementing multimodal AI agents that integrate image and video generation capabilities
  • Enabling more advanced content generation using proprietary data with RAG (Retrieval-Augmented Generation) technology
  • Enhancing integration with other tools and services by expanding API functionality

I'm also planning further improvements and new features based on user feedback and real-world usage scenarios.

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