Skip to content

T786-eng/AI-Meeting-Notes-Generator

Repository files navigation

🎙️ Pro-Meet AI: Meeting Intelligence & Action Tracker

An automated intelligence tool that leverages Natural Language Processing (NLP) to transform meeting transcripts into structured, actionable insights. This application provides a seamless way to track project progress, assign tasks, and visualize meeting dynamics through a modern web interface.

🚀 Key Features

  • Multi-Format Support: Seamlessly parse .txt, .pdf, and .docx transcripts using pure Python libraries.
  • Automated Summarization: Generates concise executive summaries using TF-IDF (Term Frequency-Inverse Document Frequency) algorithms.
  • Intelligent Action Item Detection: Automatically identifies tasks, assignees, and deadlines within the conversation.
  • Interactive Dashboard: A modern Streamlit web interface featuring visual analytics for participant activity and keyword frequency.
  • Instant Reporting: Export processed meeting notes and action plans as professional text reports.

🛠️ Tech Stack

  • Python 3.x
  • Streamlit: Web interface and dashboard deployment.
  • NLP & Analytics: Scikit-learn (TF-IDF), Pandas, NumPy.
  • Visualization: Matplotlib, Seaborn.
  • File Parsing: pdfplumber (PDF), python-docx (Word).

📂 Project Structure

├── app.py                        # Streamlit Web Application (Frontend)
├── meeting_notes_generator.py    # Core NLP Logic (Backend)
├── requirements.txt              # Project Dependencies
└── README.md                     # Project Documentation

🎙️ Pro-Meet AI: Meeting Intelligence & Action Tracker

🔗 Live Demo: View App Online


⚡ Quick Start

  1. Clone the Repository git clone:
https://github.com/T786-eng/AI-Meeting-Notes-Generator.git
  1. Install Dependencies
pip install -r requirements.txt
  1. Run the Application
streamlit run app.py

📄 License Distributed under the MIT License.

About

An NLP-powered tool that automatically generates summaries, action items, and visual analytics from meeting transcripts. Built with Python, Scikit-learn, and Pandas.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages