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AI Web Scraper

An AI-powered web scraper application that leverages free LLM providers to perform intelligent web scraping based on user prompts. The system allows users to input scraping instructions via a user-friendly UI, process web data using LLM APIs, and output results in professional formats.

Features

  • 🌐 Intelligent Web Scraping: Uses AI to understand and extract data based on natural language prompts
  • 🎨 Modern UI: Responsive React frontend with TypeScript and Tailwind CSS
  • ⚑ Fast Backend: High-performance FastAPI backend with async support
  • πŸ“„ Multiple Output Formats: Generate results in Word, PDF, Excel, or text formats
  • πŸ” Secure: API keys stored securely in environment variables
  • πŸ§ͺ Well-Tested: Comprehensive test suite with high coverage
  • πŸ“š Well-Documented: Complete guides for developers, testers, and users

Tech Stack

  • Frontend: Vite + React + TypeScript + Tailwind CSS
  • Backend: FastAPI + Python
  • LLM Integration: OpenRouter/OpenAI APIs
  • Output Generation: python-docx, reportlab, openpyxl
  • Testing: Pytest (backend), Vitest (frontend)

Quick Start

Prerequisites

  • Node.js 18+ and npm
  • Python 3.8+
  • Git

Setup

  1. Clone the repository

    git clone <repository-url>
    cd ai-webscraper
  2. Backend Setup

    cd backend
    python -m venv venv
    venv\Scripts\activate  # On Windows
    pip install -r requirements.txt
    
    # Copy .env.example to .env and add your API keys
    copy .env.example .env
  3. Frontend Setup

    cd frontend
    npm install
  4. Run the Application

    Terminal 1 (Backend):

    cd backend
    uvicorn app.main:app --reload

    Terminal 2 (Frontend):

    cd frontend
    npm run dev
  5. Access the Application

Documentation

Project Structure

ai-webscraper/
β”œβ”€β”€ backend/          # FastAPI backend
β”œβ”€β”€ frontend/         # Vite React frontend
β”œβ”€β”€ docs/            # Documentation
└── README.md        # This file

License

MIT License

About

An AI-powered web scraper application that leverages free LLM providers to perform intelligent web scraping based on user prompts. The system allows users to input scraping instructions via a user-friendly UI, process web data using LLM APIs, and output results in professional formats πŸš€

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