Thanks to visit codestin.com
Credit goes to github.com

Skip to content

jborichevskiy/cohere-events

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Event Parser App

This application allows users to parse event details from a webpage and create Google Calendar events automatically. It features a React frontend and a Python Flask backend with AI-powered event parsing.

Setup

Backend Setup

  1. Navigate to the backend directory:
cd backend
  1. Create a virtual environment and activate it:
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
  1. Install dependencies:
pip install -r requirements.txt
  1. Set up Google Calendar API:

    • Go to the Google Cloud Console
    • Create a new project
    • Enable the Google Calendar API
    • Create OAuth 2.0 credentials
    • Download the credentials and save as credentials.json in the backend directory
  2. Set up Anthropic API:

    • Create a .env file in the backend directory
    • Add your Anthropic API key:
      ANTHROPIC_API_KEY=your_api_key_here
      
  3. Run the backend server:

python app.py

Frontend Setup

  1. Navigate to the frontend directory:
cd frontend
  1. Install dependencies:
npm install
  1. Run the development server:
npm run dev

Usage

  1. Open your browser and navigate to the frontend application (usually at http://localhost:5173)
  2. Enter the URL of a webpage containing event details
  3. Click "Parse Event" to extract the event information
  4. Review and modify the extracted details if needed
  5. Click "Create Event" to add the event to your Google Calendar

Technologies Used

  • Frontend:

    • React
    • Material-UI
    • Axios
    • Day.js
  • Backend:

    • Flask
    • BeautifulSoup4
    • AISuite API
    • Google Calendar API

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • JavaScript 45.9%
  • Python 43.5%
  • CSS 8.8%
  • HTML 1.8%