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.
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Install Poetry:
curl -sSL https://install.python-poetry.org | python3 -
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Clone the repository
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Navigate to the project directory
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Create environment and Install project dependencies:
poetry shell poetry install
- Run the helper script for deploying the LlamaEdge API Server on this machine and starting the server:
sh start.sh
The application can be reached at http://localhost:5443
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Before you start, ensure your system meets the following minimum requirements to run the project using Docker:
- CPU: 8 cores
- Memory: 12GB
- Disk: 20GB
First, you have to build the Docker image for the project. Navigate to the project's root directory and run the following command:
docker build -t youtube-timeline-generator:dev .
After the image has been built, you can run the Docker container with the following command:
docker run -p 5443:5443 youtube-timeline-generator:dev
The application can be reached at http://localhost:5443
.
- UI
- Bootstrap and jQuery
- Backend
- APIs exposed via Flask
- LLM Agent via LamaEdge
- LLM model - SanctumAI/Meta-Llama-3-8B-Instruct-GGUF
- Model exposed over APIs using LlamaEdge
- User-friendly interface
- Validations on user input
- Easy copy-paste of summary and description
- History page - showing past requests
- More unit and Integration tests
- Improve response time
This project is licensed under the MIT License.