LlamaIndex (formerly known as GPT Index) is a project that provides a central interface to connect your large language model (LLM) with external data sources.
These containers provide options for an NVIDIA GPU-enabled lightweight (Miniconda) Anaconda installation. Anaconda is an open data science platform based on Python 3. Based on a container with installed Anaconda into the /usr/local/anaconda
directory. The default user, anaconda
runs a Tini shell /usr/bin/tini
, and comes preloaded with the conda
command in the environment $PATH
. Additional versions with NVIDIA/CUDA support and Jupyter Notebooks tags are available.
This container enables the conda
command with a lightweight version of Anaconda (Miniconda) and the conda-forge
repository in the /usr/local/anaconda
directory. The default user, anaconda
runs a Tini shell /usr/bin/tini
, and comes preloaded with the conda
command in the environment $PATH
. Additional versions with NVIDIA/CUDA support and Jupyter Notebooks tags are available.
Two flavors provide an NVIDIA GPU-enabled container with Anaconda.
The base container, based on the ubuntu:latest
from Ubuntu running a Tini shell. For the container with a /usr/bin/tini
entry point, use:
docker pull xychelsea/llama_index:latest
With Jupyter Notebooks server pre-installed, pull with:
docker pull xychelsea/llama_index:latest-jupyter
Modified version of nvidia/cuda:latest
container, with support for NVIDIA/CUDA graphical processing units through the Tini shell. For the container with a /usr/bin/tini
entry point:
docker pull xychelsea/llama_index:latest-gpu
With Jupyter Notebooks server pre-installed, pull with:
docker pull xychelsea/llama_index:latest-gpu-jupyter
To run the containers with the generic Docker application or NVIDIA enabled Docker, use the docker run
command.
docker run --rm -it xychelsea/llama_index:latest
With Jupyter Notebooks server pre-installed, run with:
docker run --rm -it -d -p 8888:8888 xychelsea/llama_index:latest-jupyter
docker run --gpus all --rm -it xychelsea/llama_index:latest-gpu /bin/bash
With Jupyter Notebooks server pre-installed, run with:
docker run --gpus all --rm -it -d -p 8888:8888 xychelsea/llama_index:latest-gpu-jupyter
To build either a GPU-enabled container or without GPUs, use the xychelsea/llama_index-docker GitHub repository.
git clone git://github.com/xychelsea/llama_index-docker.git
The base container, based on the ubuntu:latest
from Ubuntu running Tini shell:
docker build -t xychelsea/llama_index:latest -f Dockerfile .
With Jupyter Notebooks server pre-installed, build with:
docker build -t xychelsea/llama_index:latest-jupyter -f Dockerfile.jupyter .
docker build -t xychelsea/llama_index:latest-gpu -f Dockerfile.nvidia .
With Jupyter Notebooks server pre-installed, build with:
docker build -t xychelsea/llama_index:latest-gpu-jupyter -f Dockerfile.nvidia-jupyter .