https://github.com/amarlearning/youtube-timeline-generator
Generating video timeline description using LLMs.
https://github.com/amarlearning/youtube-timeline-generator
chapters flask llm python summary timeline youtube
Last synced: 7 months ago
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Generating video timeline description using LLMs.
- Host: GitHub
- URL: https://github.com/amarlearning/youtube-timeline-generator
- Owner: amarlearning
- Created: 2024-06-08T17:39:59.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-06-08T19:45:56.000Z (over 1 year ago)
- Last Synced: 2025-03-04T08:13:55.458Z (12 months ago)
- Topics: chapters, flask, llm, python, summary, timeline, youtube
- Language: Python
- Homepage:
- Size: 17.6 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Youtube Timeline Generator
## Description
This project is aimed at generating a video timeline description using LLMs. It allows users to generate summary and descriptive timelines for videos, making it easier to navigate through video.
# Demo
## Project Setup
1. Install Poetry:
```bash
curl -sSL https://install.python-poetry.org | python3 -
```
2. Clone the repository
3. Navigate to the project directory
4. Create environment and Install project dependencies:
```bash
poetry shell
poetry install
```
## Usage
### Running the project for the first time?
1. Run the helper script for deploying the LlamaEdge API Server on this machine and starting the server:
```bash
sh start.sh
```
The application can be reached at `http://localhost:5443`.
## Usage via Docker
Before you start, ensure your system meets the following minimum requirements to run the project using Docker:
- CPU: 8 cores
- Memory: 12GB
- Disk: 20GB
### Building the Docker Image
First, you have to build the Docker image for the project. Navigate to the project's root directory and run the following command:
```bash
docker build -t youtube-timeline-generator:dev .
```
### Running the Docker Container
After the image has been built, you can run the Docker container with the following command:
```bash
docker run -p 5443:5443 youtube-timeline-generator:dev
```
The application can be reached at `http://localhost:5443`.
# System Diagram
## Components
- UI
- Bootstrap and jQuery
- Backend
- APIs exposed via Flask
- LLM Agent via LamaEdge
- LLM model - [SanctumAI/Meta-Llama-3-8B-Instruct-GGUF](https://huggingface.co/SanctumAI/Meta-Llama-3-8B-Instruct-GGUF/)
- Model exposed over APIs using [LlamaEdge](https://github.com/LlamaEdge/LlamaEdge)
## Features & Extensions
- [x] User-friendly interface
- [x] Validations on user input
- [x] Easy copy-paste of summary and description
#### Extensions
- [ ] History page - showing past requests
- [ ] More unit and Integration tests
- [ ] Improve response time
## License
This project is licensed under the [MIT License](LICENSE).