# 基础镜像
# docker pull golang:1.22.1-bookworm
# docker run -dit --name=test usewhisper:v0.0.1 -v /mnt/e/video/srt:/srt -e language=en bash
FROM golang:1.22.1-bookworm
# 用于存储程序和视频字幕文件的文件夹
VOLUME /srt
RUN apt update && apt full-upgrade
RUN apt install -y ffmpeg python3 python3-pip vim nano mediainfo wget git
RUN mkdir /module
RUN wget https://openaipublic.azureedge.net/main/whisper/models/ed3a0b6b1c0edf879ad9b11b1af5a0e6ab5db9205f891f668f8b0e6c6326e34e/base.pt -O /module/base.pt --no-check-certificate
RUN go env -w GO111MODULE=on
# RUN go env -w GOPROXY=https://goproxy.cn,direct
RUN git clone https://github.com/zhangyiming748/WhisperInDocker.git /root/WhisperInDocker
WORKDIR /root/WhisperInDocker
RUN go mod tidy
RUN go build -o /usr/local/bin/srt main.go
CMD ["srt"]
# .github/workflows/release.yml
name: goreleaser
on:
pull_request:
push:
# run only against tags
tags:
- "*"
branches: [ "master" ]
permissions:
contents: write
# packages: write
# issues: write
jobs:
dockerbuilder:
runs-on: ubuntu-latest
steps:
- name: pwd
run: pwd
- name: Checkout
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: build
run: docker build -t whisper:latest /home/runner/work/WhisperInDocker/WhisperInDocker
- name: export
# run: docker save whisper:latest -o whisper.tar
run: docker save whisper:latest | xz > whisper.tar
# More assembly might be required: Docker logins, GPG, etc.
# It all depends on your needs.
- name: Upload Build Artifacts
uses: actions/upload-artifact@v4
with:
name: workspace_artifacts
path: ${{ github.workspace }}
最近在学习GitHub workflow 构建docker image
因为我要用的最终镜像大概10G
看运行过程docker build 并不会使用上一次的cache
一直都是全新下载
我是免费用户,这东西有没有什么极限,或者到达什么程度就该交钱的说法?