利用 AI 大模型和自动化工作流,根据主题或关键词一键生成高清短视频。Generate HD short videos from a topic or keyword with an automated AI workflow.
docker pull harry0703/moneyprinterturbo
docker run -d --name moneyprinterturbo -p 8501:8501 --restart always harry0703/moneyprinterturbo:latest
podman run -d --name moneyprinterturbo -p 8501:8501 --restart always harry0703/moneyprinterturbo:latest
skopeo inspect docker://docker.io/harry0703/moneyprinterturbo:latest
oras pull harry0703/moneyprinterturbo:latest
docker compose up -d
# 使用 Claude 订阅(Pro / Max / Team)作为 LLM Provider 的运行方式。
#
# 与 docker-compose.release.yml 的区别:
# 1. 构建 Dockerfile.claude,容器内包含 claude CLI;
# 2. 挂载整个项目目录,使 claude_code Provider 的代码生效;
# 3. 注入 CLAUDE_CODE_OAUTH_TOKEN,容器内没有 keychain,CLI 只能用
# `claude setup-token` 生成的长期令牌完成鉴权。
#
# 启动前先导出令牌:
# export CLAUDE_CODE_OAUTH_TOKEN="$(claude setup-token)"
# docker compose -f docker-compose.claude.yml up -d --build
x-common-build: &common-build
context: .
dockerfile: Dockerfile.claude
x-common-volumes: &common-volumes
- ./:/MoneyPrinterTurbo
x-common-environment: &common-environment
# 未设置令牌时直接让 compose 报错,避免容器起来后才在生成阶段失败。
CLAUDE_CODE_OAUTH_TOKEN: ${CLAUDE_CODE_OAUTH_TOKEN:?run 'export CLAUDE_CODE_OAUTH_TOKEN="$(claude setup-token)"' first}
services:
webui:
build: *common-build
container_name: "moneyprinterturbo-webui"
ports:
- "127.0.0.1:8501:8501"
command: [ "streamlit", "run", "./webui/Main.py", "--server.address=0.0.0.0", "--server.port=8501", "--browser.serverAddress=127.0.0.1", "--server.enableCORS=True", "--browser.gatherUsageStats=False", "--client.toolbarMode=minimal", "--logger.hideWelcomeMessage=True", "--server.showEmailPrompt=False" ]
volumes: *common-volumes
environment: *common-environment
restart: always
api:
build: *common-build
container_name: "moneyprinterturbo-api"
ports:
- "127.0.0.1:8080:8080"
command: [ "python3", "main.py" ]
volumes: *common-volumes
environment: *common-environment
restart: always