Yannoux2000 / serge

A web interface for chatting with Alpaca through llama.cpp. Fully dockerized, with an easy to use API.

Serge - LLaMa made easy 🦙

A chat interface based on llama.cpp for running Alpaca models. Entirely self-hosted, no API keys needed. Fits on 4GB of RAM and runs on the CPU.

• SvelteKit frontend
• MongoDB for storing chat history & parameters
• FastAPI + beanie for the API, wrapping calls to llama.cpp

demo.webm

Getting started

Setting up Serge is very easy. TLDR for running it with Alpaca 7B:

git clone https://github.com/nsarrazin/serge.git
cd serge

docker compose up --build -d
docker compose exec serge python3 /usr/src/app/api/utils/download.py tokenizer 7B

Windows

⚠️ For cloning on windows, use git clone https://github.com/nsarrazin/serge.git --config core.autocrlf=input.

Make sure you have docker desktop installed, WSL2 configured and enough free RAM to run models. (see below)

Kubernetes

Setting up Serge on Kubernetes can be found in the wiki: https://github.com/nsarrazin/serge/wiki/Integrating-Serge-in-your-orchestration#kubernetes-example

Using serge

(You can pass 7B 13B 30B as an argument to the download.py script to download multiple models.)

Then just go to http://localhost:8008/ and you're good to go!

The API is available at http://localhost:8008/api/

Models

Currently only the 7B, 13B and 30B alpaca models are supported. There's a download script for downloading them inside of the container, described above.

If you have existing weights from another project you can add them to the serge_weights volume using docker cp.

⚠️ A note on memory usage

llama will just crash if you don't have enough available memory for your model.

• 7B requires about 4.5GB of free RAM
• 13B requires about 12GB free
• 30B requires about 20GB free

Support

Feel free to join the discord if you need help with the setup: https://discord.gg/62Hc6FEYQH

Contributing

Serge is always open for contributions! If you catch a bug or have a feature idea, feel free to open an issue or a PR.

If you want to run Serge in development mode (with hot-module reloading for svelte & autoreload for FastAPI) you can do so like this:

docker compose -f docker-compose.dev.yml up -d --build

What's next

• Front-end to interface with the API
• Pass model parameters when creating a chat
• User profiles & authentication
• Different prompt options
• LangChain integration with a custom LLM
• Support for other llama models, quantization, etc.

And a lot more!