move to bgpt dir

Dockerfile.bgpt

@@ -1,81 +0,0 @@
-# syntax=docker/dockerfile:1
-FROM nvidia/cuda:11.6.1-devel-ubuntu20.04
-
-ARG DEBIAN_FRONTEND="noninteractive"
-ENV DEBIAN_FRONTEND=${DEBIAN_FRONTEND}
-
-COPY src/requirements.txt /root/
-ENV MAMBA_ROOT_PREFIX=~/micromamba
-WORKDIR /root
-SHELL ["/bin/bash", "-c"]
-
-COPY requirements.txt /root/
-COPY id_rsa.pub /root/.ssh/
-RUN <<EOT
-#!/bin/bash
-apt-get update
-apt-get install -y wget curl git git-lfs jq vim bash libaio-dev build-essential openssh-server lsof python3 python3-pip
-echo "PermitRootLogin yes" >> /etc/ssh/sshd_config
-echo "PasswordAuthentication yes" >> /etc/ssh/sshd_config
-echo "PubkeyAuthentication yes" >> /etc/ssh/sshd_config
-echo "Port 22" >> /etc/ssh/sshd_config
-mkdir /var/run/sshd
-echo 'root:cdcdocker' | chpasswd
-mkdir -p ~/.pip
-# install miniconda
-wget -qO- https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/miniconda.sh
-bash /tmp/miniconda.sh -b -p /opt/conda 
-rm /tmp/miniconda.sh 
-conda init bash 
-ln -s /opt/conda/etc/profile.d/conda.sh /etc/profile.d/conda.sh
-echo ". /opt/conda/etc/profile.d/conda.sh" >> ~/.bashrc 
-echo "conda activate ${CONDA_ENV_NAME}" >> ~/.bashrc
-# 配置 .condarc 文件
-cat <<EOF > ~/.condarc
-channels:
-  - conda-forge
-  - bioconda
-  - pytorch
-  - pytorch-nightly
-  - nvidia
-  - defaults
-show_channel_urls: true
-EOF
-# 安装 micromamba 并配置 mambarc
-echo 1 | bash <(curl -s https://cdn.jsdelivr.net/gh/hotwa/MicroMamba_Installer@main/install.sh)
-micromamba shell init -s bash -p ~/micromamba
-cat <<'EOF' >> ~/.bashrc
-source ~/micromamba/etc/profile.d/micromamba.sh
-alias mamba=micromamba
-alias mba=mamba
-EOF
-# 配置 .mambarc 文件
-cat <<EOF > ~/.mambarc
-channels:
-  - conda-forge
-  - bioconda
-  - pytorch
-  - pytorch-nightly
-  - nvidia
-EOF
-mkdir -p ~/.pip
-echo "
-[global]
-index-url = https://mirrors.aliyun.com/pypi/simple/
-
-[install]
-trusted-host=mirrors.aliyun.com
-" >> ~/.pip/pip.conf
-micromamba create -n bgpt -c conda-forge python=3.7.9 -y
-micromamba run -n bgpt pip install -r requirements.txt
-micromamba run -n bgpt pip install ipykernel attrs seaborn
-micromamba run -n bgpt python -m ipykernel install --user --name="bgpt" --display-name="bgpt_env"
-micromamba run -n bgpt pip install seaborn attrs torch==1.13.1+cu116 torchvision==0.14.1+cu116 torchaudio==0.13.1 --extra-index-url https://download.pytorch.org/whl/cu116
-echo "micromamba activate bgpt" >> ~/.bashrc
-EOT
-
-# Expose SSH port
-EXPOSE 3222
-
-# Keep the container running
-CMD ["/usr/sbin/sshd", "-D"]

docker-compose-bgpt.yml

@@ -1,54 +0,0 @@
-version: '3.8'
-
-services:
-  ubuntu-ssh:
-    build: 
-      context: .
-      dockerfile: Dockerfile.bgpt
-    volumes:
-      - ./src:/root/data
-      - /mnt/sdb/zly/datas/Datas:/mnt/sdb/zly/datas
-      - /data:/data
-    container_name: ubuntu-ssh
-    pull_policy: if_not_present
-    tty: true
-    restart: unless-stopped
-    image: zly/cuda-bgpt:latest
-    ports:
-      - 3222:22
-    environment:
-      - NVIDIA_VISIBLE_DEVICES=all
-      - NVIDIA_DRIVER_CAPABILITIES=compute,utility
-      - OLLAMA_ORIGINS="chrome-extension://*"
-    networks:
-      - network3
-    deploy:
-      resources:
-        reservations:
-          devices:
-            - driver: nvidia
-              count: all
-              capabilities: [gpu]
-
-  # openai-whisper-asr-webservice:
-  #   ports:
-  #       - '9000:9000'
-  #   volumes:
-  #         - './whisper-large-v3:/data/whisper'
-  #   environment:
-  #       - ASR_MODEL=large
-  #       - ASR_ENGINE=openai_whisper
-  #       - ASR_MODEL_PATH=/data/whisper
-  #   image: 'onerahmet/openai-whisper-asr-webservice:latest-gpu'
-  #   deploy:
-  #     resources:
-  #       reservations:
-  #         devices:
-  #           - driver: nvidia
-  #             count: 1
-  #             capabilities: [gpu]
-
-
-networks:
-  network3:
-    name: network3