bedrock-youtube-analyzer

This is a youtube analyzer that leverages Amazon Bedrock

Welcome to the YouTube Analysis Assistant, a tool designed to help you optimize and enhance your YouTube content using the power of large language models. This assistant can suggest engaging titles, SEO tags, thumbnail designs, content enhancements, and segments with viral potential for your YouTube videos.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

What things you need to install the software and how to install them:

Python 3.6+
Pip (Python package installer)
Virtual environment (optional but recommended)
AWS Account
Amazon Bedrock (Claude V2.1) model access

Installation

A step-by-step series of examples that tell you how to get a development environment running:

Clone the repository

git clone https://github.com/labeveryday/bedrock-youtube-analyzer.git

Navigate to the project directory
```
cd bedrock-youtube-analyzer
```

Set up a Python virtual environment (Optional but recommended)

python3 -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

Install the required packages
```
pip install -r requirements.txt
```
Run the Streamlit application
```
streamlit run main.py
```

Usage

Once the application is running, you can interact with it through the Streamlit UI in your web browser.

Insert the YouTube URL you wish to analyze in the sidebar input.
Click Submit to process the video through the YouTube Loader.
Interact with the analysis assistant by typing in your questions or commands.

Features

Video transcript fetching and processing
Conversation with LLM for content suggestions
UI components for a user-friendly experience
Transcript download functionality

File Descriptions

main.py: The main application script that contains the Streamlit UI and logic.
requirements.txt: A list of necessary Python packages.

License

This project is licensed under the MIT License - see the LICENSE.md file for details

About me

My passions lie in Network Engineering, Cloud Computing, Automation, and impacting people's lives. I'm fortunate to weave all these elements together in my role as a Developer Advocate. On GitHub, I share my ongoing learning journey and the projects I'm building. Don't hesitate to reach out for a friendly hello or to ask any questions!

My hangouts: