contextflow 1.6.0

Large Language Models Tools

Environment

To create a Python virtual environment, use the command:

conda env create -f environment.yml

Installation

pip install contextflow

Supported Models

The following LLM models are supported:

• Gemma Family
• Qwen Family
• YandexGPT Family

LLM backends

The following LLM backends are supported:

• Llama.cpp Server API

Run Llama.CPP Server backend

llama.cpp/build/bin/llama-server -m model_q5_k_m.gguf -ngl 99 -fa -np 2 -c 8192 --host 0.0.0.0 --port 8000

Install CUDA toolkit for Llama.cpp compilation

Please note that the toolkit version must match the driver version. The driver version can be found using the nvidia-smi command. Аor example, to install toolkit for CUDA 12.4 you need to run the following commands:

CUDA_TOOLKIT_VERSION=12-4
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt update
sudo apt -y install cuda-toolkit-${CUDA_TOOLKIT_VERSION}
echo -e '
export CUDA_HOME=/usr/local/cuda
export PATH=${CUDA_HOME}/bin:${PATH}
export LD_LIBRARY_PATH=${CUDA_HOME}/lib64:$LD_LIBRARY_PATH
' >> ~/.bashrc

Set GPU Max Temp

nvidia-smi -pm 1
sudo nvidia-smi -gtt 80
nvidia-smi -q | grep Target