llm-story-collab

This web app allows users to co-write a story with an AI language model, taking turns with the AI to build a shared narrative. Users can download their preferred language model from Hugging Face's library, and inference will be performed using the Transformers Pipelines.

Technologies

• Frontend: Svelte (for building and serving the single-page app), JavaScript, SCSS, and HTML
• Backend: Python (for writing a WebSocket server hosting the LLM)
• Containerization: Docker (for packaging and deploying the application)

Installation

1. Clone the repository: ```bash git clone https://github.com/akselkristoffersen/llm-story-collab.git cd llm-story-collab
2. Install huggingface_hub ```bash pip install -U huggingface_hub
3. Set Environment Variables

• $HF_HOME: The directory where the Hugging Face models will be downloaded/stored. Docker Compose will also create volumes to this directory.
• $AX_MODEL_NAME: The name of the model on Hugging Face that you want to use. The envir is forwarded by Docker Compose to the backend container. ```bash export HF_HOME=/path/to/your/huggingface/models export AX_MODEL_NAME=huggingface-model-name

4. Download the Model ```bash huggingface-cli download $AX_MODEL_NAME

5. Install Docker

   If you haven't installed Docker yet, download and install it from Docker's official website.

6. Run Docker Compose ```bash docker-compose up

7. Open in Web Browser http://localhost:80