{"id":28923937,"url":"https://github.com/jarif87/text-key-extractor","last_synced_at":"2026-04-29T08:35:35.093Z","repository":{"id":300440542,"uuid":"1006168365","full_name":"jarif87/text-key-extractor","owner":"jarif87","description":"A Django web app that uses TF-IDF to extract keywords from text, featuring a modern, responsive UI with animated gradients and glassmorphism.","archived":false,"fork":false,"pushed_at":"2025-06-23T15:56:29.000Z","size":19734,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-09-04T13:53:30.101Z","etag":null,"topics":["django-application","keywords-extraction","pandas","python","scikit-learn"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/jarif87.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-06-21T16:40:38.000Z","updated_at":"2025-06-23T15:56:32.000Z","dependencies_parsed_at":"2025-06-21T18:41:42.346Z","dependency_job_id":null,"html_url":"https://github.com/jarif87/text-key-extractor","commit_stats":null,"previous_names":["jarif87/text-key-extractor"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/jarif87/text-key-extractor","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jarif87%2Ftext-key-extractor","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jarif87%2Ftext-key-extractor/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jarif87%2Ftext-key-extractor/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jarif87%2Ftext-key-extractor/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jarif87","download_url":"https://codeload.github.com/jarif87/text-key-extractor/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jarif87%2Ftext-key-extractor/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32418156,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-29T06:29:02.080Z","status":"ssl_error","status_checked_at":"2026-04-29T06:29:00.631Z","response_time":110,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["django-application","keywords-extraction","pandas","python","scikit-learn"],"created_at":"2025-06-22T10:02:19.951Z","updated_at":"2026-04-29T08:35:35.076Z","avatar_url":"https://github.com/jarif87.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Keyword Extractor\n\n\n\nKeyword Extractor is a Django-based web application that extracts key terms from input text using Term Frequency-Inverse Document Frequency (TF-IDF). The application provides a sleek, user-friendly interface where users can input text, submit it, and receive a list of the top keywords ranked by their TF-IDF scores. The backend leverages scikit-learn’s CountVectorizer and TfidfTransformer to process text, and the frontend uses a modern, responsive design with animated gradients and glassmorphism effects.\n\n## Table of Contents\n\n- Features\n- Project Structure\n- Prerequisites\n- Installation\n- Usage\n- Screenshots\n- Contributing\n- License\n- Contact\n\n## Features\n\n- Keyword Extraction: Extracts top keywords from user-provided text using a pre-trained TF-IDF model.\n- Responsive Design: Modern interface with an animated gradient background, glassmorphism effects, and a responsive layout for desktop and mobile devices.\n- User-Friendly: Simple text input form with a dynamic results display showing keywords and their TF-IDF scores.\n- Pre-trained Models: Uses serialized CountVectorizer (cv.pkl) and TfidfTransformer (tfidf.pkl) models for efficient keyword extraction.\n- Customizable: Easily extendable for additional preprocessing (e.g., stopwords, stemming) or UI enhancements.\n\n## Project Structure\n\n```bash\nkeyword-extractor/\n├── .gitignore\n├── db.sqlite3\n├── manage.py\n├── README.md\n├── requirements.txt\n├── myapp/\n│   ├── admin.py\n│   ├── apps.py\n│   ├── cv.pkl\n│   ├── feature_names.pkl\n│   ├── models.py\n│   ├── sustain.py\n│   ├── tests.py\n│   ├── tfidf.pkl\n│   ├── urls.py\n│   ├── views.py\n│   ├── __init__.py\n│   ├── migrations/\n│   │   ├── 0001_initial.py\n│   │   ├── __init__.py\n│   │   └── __pycache__/\n│   ├── static/\n│   │   ├── css/\n│   │   │   └── style.css\n│   │   ├── images/\n│   │   └── js/\n│   │       └── script.js\n│   ├── templates/\n│   │   └── index.html\n│   └── __pycache__/\n└── myproject/\n    ├── asgi.py\n    ├── settings.py\n    ├── urls.py\n    ├── wsgi.py\n    ├── __init__.py\n    └── __pycache__/\n```\n\n## Prerequisites\n\n- Python: 3.11 or later\n- Django: 4.x or compatible version\n- Dependencies: Listed in `requirements.txt`\n- Web Browser: Chrome, Firefox, or other modern browser\n\n## Installation\n\n```bash\n# Clone the repository\ngit clone https://github.com/your-username/keyword-extractor.git\ncd keyword-extractor\n\n# Create a virtual environment\npython -m venv venv\nsource venv/bin/activate        # On Windows: venv\\Scripts\\activate\n\n# Install dependencies\npip install -r requirements.txt\n\n# Apply database migrations\npython manage.py migrate\n\n# Collect static files\npython manage.py collectstatic\n\n# Run the development server\npython manage.py runserver\n```\n\nNow open your browser and go to:  \n📍 http://127.0.0.1:8000/\n\n## Usage\n\n- **Input Text:** Enter your text in the input field.\n- **Submit:** Click “Extract” to process and extract keywords.\n- **Results:** View the top keywords and their TF-IDF scores in styled cards.\n\n### Example\n\nInput:\n```\nNeural network for pattern classification and generalization performance.\n```\n\nOutput:\n```\nneural network: 0.454  \npattern: 0.321  \ngeneralization: 0.312  \nclassification: 0.298\n```\n\n## Screenshots\n\n![Screenshot](myproject/myapp/static/images/image.png)\n\n\n## Contributing\n\nContributions are welcome! To contribute:\n\n```bash\n# Fork the repository\ngit checkout -b feature/your-feature\n\n# Make your changes\ngit commit -m \"Add your feature\"\n\n# Push your branch\ngit push origin feature/your-feature\n```\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjarif87%2Ftext-key-extractor","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjarif87%2Ftext-key-extractor","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjarif87%2Ftext-key-extractor/lists"}