Skip to content

Instantly share code, notes, and snippets.

@decagondev
Created May 5, 2025 22:48
Show Gist options
  • Select an option

  • Save decagondev/946323f996921696f8d8243b38832838 to your computer and use it in GitHub Desktop.

Select an option

Save decagondev/946323f996921696f8d8243b38832838 to your computer and use it in GitHub Desktop.

Jims Gym Finder PRD

Overview

Jims Gym Finder is a web application designed to help users find local gyms and their facilities. The application will utilize web scraping, AI summarization, and mapping technology to provide users with a concise and informative experience.

Problem Statement

Users, like Jim the Gym goer, struggle to find information about local gyms, including their facilities and features. The current process involves manually searching and researching, which is time-consuming and overwhelming.

Target Audience

The target audience is individuals like Jim, who regularly visit gyms and are looking for an easy way to find and compare local gyms.

MVP Feature Scope

The MVP will focus on the following features:

  • Search for gyms in a specified area
  • Display a list of nearby gyms with their distances
  • Provide a summary of each gym's facilities and features using AI summarization

User Stories

As a user, I want to:

  • Search for gyms near my location
  • View a list of nearby gyms along with their distances
  • Read a summary of each gym's facilities and features

Core Features

The core feature of Jims Gym Finder is to search the web and locate gyms in a specified area, utilizing web scraping with Cheerio and AI summarization with Groq-SDK.

User Flow

The following Mermaid diagram illustrates the user flow:

graph LR
    A[User visits Jims Gym Finder] --> B[User inputs location]
    B --> C[User submits search request]
    C --> D[Jims Gym Finder searches for gyms using Tavili]
    D --> E[Jims Gym Finder scrapes gym data using Cheerio]
    E --> F[Groq-SDK summarizes gym data]
    F --> G[Jims Gym Finder displays list of gyms with summaries]
Loading

Technical Stack

The technical stack for Jims Gym Finder includes:

  • Frontend: Vite, React, TypeScript, Tailwind CSS
  • AI Summarization: Groq-SDK
  • Web Scraping: Cheerio
  • Web Search: Tavili

Assumptions & Constraints

The development of Jims Gym Finder is constrained by a 24-hour MVP deadline. It is assumed that the necessary APIs (Tavili, Groq-SDK) are available and functional within this timeframe.

Success Metrics

The success of the MVP will be measured by the ability to search the web and return a summary of the closest gyms. The primary metric will be the accuracy and relevance of the gym summaries provided to the user.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment