Skip to content

LLaMe NEWS is an AI-powered tool that extracts audio from YouTube videos, transcribes the content using OpenAI Whisper, and generates well-structured news articles using OpenAI's GPT-3.5 Turbo. The project provides an interactive web interface built with Streamlit, making it easy to use.

Notifications You must be signed in to change notification settings

Hetav01/LLaMe-Transcripter

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

28 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

📰 LLaMe NEWS: AI-Powered News Article Generator

📌 Overview

LLaMe NEWS is an AI-powered tool that extracts audio from YouTube videos, transcribes the content using OpenAI Whisper, and generates well-structured news articles using OpenAI's GPT-3.5 Turbo. The project provides an interactive web interface built with Streamlit, making it easy to use.

✨ Features

  • 🎥 Download and extract audio from YouTube videos
  • 📝 Generate accurate transcripts using OpenAI Whisper
  • 📰 Convert transcripts into structured news articles
  • 💻 Streamlit-based UI for seamless interaction
  • 📂 Downloadable transcript and article files in a ZIP format

Bug Image

Bug Image

🔧 Prerequisites

Before setting up the project, ensure you have the following installed:

  • Python 3.8+
  • pip or pip3 (Python package manager)
  • Virtual environment (recommended)
  • OpenAI API Key

🚀 Setup Instructions

📥 Step 1: Clone the Repository

git clone <your-repository-url>
cd <your-repository-folder>

🌐 Step 2: Create a Virtual Environment (Recommended)

On macOS/Linux

python3 -m venv venv
source venv/bin/activate

On Windows

python -m venv venv
venv\Scripts\activate

📦 Step 3: Install Dependencies

pip install -r requirements.txt

🔑 Step 4: Set Up OpenAI API Key

On macOS/Linux

export OPENAI_API_KEY="your-api-key-here"

On Windows (PowerShell)

$env:OPENAI_API_KEY="your-api-key-here"

Alternatively, create a .env file in the root directory and add:

OPENAI_API_KEY=your-api-key-here

▶️ Step 5: Run the Application

streamlit run main.py

📖 Usage Guide

  1. 🔗 Enter a YouTube video URL in the input field.
  2. ✅ Click the checkbox to start the analysis.
  3. ⏳ Wait for the audio extraction and transcription.
  4. 📰 The generated news article will appear on the screen.
  5. 📥 Download the transcript and article as a .zip file.

🛠 Troubleshooting

  • Missing Dependencies? Run pip install -r requirements.txt again.
  • API Key Not Found? Ensure it's set in the environment or .env file.
  • Streamlit Not Running? Check for errors and ensure you activated the virtual environment.

🏗 Technologies Used

  • 🐍 Python (Core Programming Language)
  • 🌐 Streamlit (Web Framework for UI)
  • 🤖 OpenAI GPT-3.5 Turbo (Article Generation)
  • 🎙 OpenAI Whisper (Audio Transcription)
  • 📹 PytubeFix (YouTube Audio Extraction)

❗ Known Issues

pytubefix.exceptions.BotDetection: sVGg90hukLI This request was detected as a bot.

Bug Image

This error occurs when YouTube detects automated access to its content and blocks the request. This issue is common with pytubefix, as YouTube regularly updates its bot detection mechanisms.

Best Possible workaround: Tap the Start Analysis checkbox multiple times, it somehow bypasses and allows the URL.

Other possible workarounds include:

  • Using a VPN or proxy to change your IP address.
  • Implementing a delay between requests to mimic human behavior.
  • Using an alternative method for downloading YouTube audio, such as yt-dlp.
  • Updating pytubefix to the latest version to check for fixes.

This issue is currently being investigated for a more permanent solution.

📜 License

This project is licensed under the MIT License.

👤 Author

Hetav a.k.a GodSpeed


🚀 Enjoy using LLaMe NEWS and revolutionize news generation! 📰✨

About

LLaMe NEWS is an AI-powered tool that extracts audio from YouTube videos, transcribes the content using OpenAI Whisper, and generates well-structured news articles using OpenAI's GPT-3.5 Turbo. The project provides an interactive web interface built with Streamlit, making it easy to use.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages