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feat(deploy): VPS LLM 代理 + 新机一键部署 (66.245.216.250)
新增 server/vps-llm-proxy.js — 把 /canvas/api/llm/chat 转发到 DeepSeek (或其它 OpenAI 兼容 endpoint), 凭据保管在 systemd EnvironmentFile, 不暴露给浏览器. 部署组件: - deploy/know-canvas-llm-proxy.service — systemd unit, 读 /etc/know-canvas/llm.env - deploy/Caddyfile.newvps — IP 模式 :80, /canvas/ 静态 + /yws/ WS + /canvas/api/llm/ 反代 - deploy/deploy-newvps.sh — SSH 一键部署 (探测 → build → rsync → systemd → caddy → 健康检查) 用法: DEEPSEEK_API_KEY=sk-xxx bash deploy/deploy-newvps.sh Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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‎deploy/Caddyfile.newvps‎

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# Know Canvas — IP-based deploy on new VPS (66.245.216.250)
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#
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# 没有域名, 走 :80 HTTP (后续如配域名再换 HTTPS).
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#
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# 路径布局:
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# / → 提示页 (默认重定向到 /canvas/)
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# /canvas/ → 前端 build 静态产物
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# /yws/ → Yjs 协作 WebSocket (反代 127.0.0.1:1234)
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# /canvas/api/llm/ → DeepSeek 代理 (反代 127.0.0.1:17080)
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#
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# 安装:
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# sudo cp deploy/Caddyfile.newvps /etc/caddy/Caddyfile
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# sudo caddy validate --config /etc/caddy/Caddyfile
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# sudo systemctl reload caddy
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#
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# 验证:
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# curl -I http://66.245.216.250/canvas/
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# curl http://66.245.216.250/canvas/api/llm/health
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{
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# 全局选项
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admin off
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# 日志走 journal
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log {
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output stderr
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level INFO
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}
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}
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:80 {
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# 默认根路径直接 302 到 /canvas/
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@root path /
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redir @root /canvas/ 302
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# === Know Canvas 静态前端 ===
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handle_path /canvas/api/llm/* {
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reverse_proxy 127.0.0.1:17080 {
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header_up Host {host}
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header_up X-Real-IP {remote_host}
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}
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}
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handle_path /canvas/api/log {
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reverse_proxy 127.0.0.1:18091/log {
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header_up Host {host}
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header_up X-Real-IP {remote_host}
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}
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}
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handle_path /canvas/api/log/* {
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reverse_proxy 127.0.0.1:18091 {
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header_up Host {host}
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header_up X-Real-IP {remote_host}
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}
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}
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# === Yjs WebSocket sync ===
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handle_path /yws/* {
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reverse_proxy 127.0.0.1:1234 {
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header_up Host {host}
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header_up X-Real-IP {remote_host}
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header_up Connection {>Connection}
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header_up Upgrade {>Upgrade}
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}
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}
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# === Know Canvas 静态资源 (放在 api 反代之后, 顺序很重要) ===
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handle_path /canvas/* {
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root * /var/www/know-canvas
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try_files {path} /index.html
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file_server
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encode gzip
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}
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# 兜底: 其它路径返回简单提示
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handle {
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respond "Know Canvas — go to /canvas/" 200
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}
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}

‎deploy/deploy-newvps.sh‎

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#!/usr/bin/env bash
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# Know Canvas — 一键部署到新 VPS (66.245.216.250:8765)
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#
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# 用法 (本地开发机):
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# DEEPSEEK_API_KEY=sk-xxx bash deploy/deploy-newvps.sh
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#
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# 可选环境变量:
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# REMOTE_USER 默认 root
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# REMOTE_HOST 默认 66.245.216.250
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# REMOTE_PORT 默认 8765
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# DEEPSEEK_API_KEY 必填; 写入远端 /etc/know-canvas/llm.env (不进 git)
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# LLM_BASE_URL 默认 https://api.deepseek.com/v1
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# LLM_MODEL 默认 deepseek-chat
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#
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# 干什么:
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# 1. 本地 npm run build:canvas
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# 2. SSH 远端: 检查 / 安装 caddy + node 22
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# 3. rsync dist/ → /var/www/know-canvas/
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# 4. rsync server/ → /opt/know-canvas/server/ + npm install --production
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# 5. 写 /etc/know-canvas/llm.env (LLM_API_KEY + base url + model)
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# 6. 装 systemd unit (yws + llm-proxy), enable + start
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# 7. 装 Caddyfile, reload caddy
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# 8. 健康检查 /canvas/ + /canvas/api/llm/health
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set -euo pipefail
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REMOTE_USER="${REMOTE_USER:-root}"
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REMOTE_HOST="${REMOTE_HOST:-66.245.216.250}"
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REMOTE_PORT="${REMOTE_PORT:-8765}"
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LLM_BASE_URL="${LLM_BASE_URL:-https://api.deepseek.com/v1}"
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LLM_MODEL="${LLM_MODEL:-deepseek-chat}"
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if [ -z "${DEEPSEEK_API_KEY:-}" ]; then
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echo "ERROR: DEEPSEEK_API_KEY 必填"
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echo "用法: DEEPSEEK_API_KEY=sk-xxx bash deploy/deploy-newvps.sh"
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exit 1
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fi
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REMOTE="${REMOTE_USER}@${REMOTE_HOST}"
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SSH_OPTS="-p ${REMOTE_PORT} -o StrictHostKeyChecking=accept-new"
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RSYNC_SSH="ssh -p ${REMOTE_PORT} -o StrictHostKeyChecking=accept-new"
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PROJECT_ROOT="$(cd "$(dirname "$0")/.." && pwd)"
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echo "[deploy-newvps] 项目根: $PROJECT_ROOT"
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echo "[deploy-newvps] 目标: $REMOTE (port $REMOTE_PORT)"
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echo "[deploy-newvps] 上游: $LLM_BASE_URL model=$LLM_MODEL"
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echo ""
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# 1. 本地 build
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echo "==> 1/8 本地 build (base=/canvas/)"
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cd "$PROJECT_ROOT"
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npm run build:canvas
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if [ ! -d "dist" ]; then
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echo "ERROR: dist/ 不存在 — build 失败"
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exit 1
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fi
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# 2. 远端环境探测 + 安装依赖
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echo ""
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echo "==> 2/8 探测远端环境 (caddy / node)"
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ssh $SSH_OPTS "$REMOTE" 'bash -s' <<'REMOTE_PROBE'
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set -e
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echo "[probe] OS: $(. /etc/os-release && echo $PRETTY_NAME)"
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echo "[probe] uname: $(uname -a)"
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# Node
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if ! command -v node >/dev/null 2>&1; then
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echo "[probe] 装 Node 22..."
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apt update
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curl -fsSL https://deb.nodesource.com/setup_22.x | bash -
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apt install -y nodejs
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fi
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echo "[probe] node: $(node -v)"
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# Caddy
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if ! command -v caddy >/dev/null 2>&1; then
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echo "[probe] 装 Caddy..."
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apt install -y debian-keyring debian-archive-keyring apt-transport-https curl
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curl -1sLf 'https://dl.cloudsmith.io/public/caddy/stable/gpg.key' | gpg --dearmor -o /usr/share/keyrings/caddy-stable-archive-keyring.gpg
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curl -1sLf 'https://dl.cloudsmith.io/public/caddy/stable/debian.deb.txt' | tee /etc/apt/sources.list.d/caddy-stable.list
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apt update
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apt install -y caddy
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fi
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echo "[probe] caddy: $(caddy version | head -1)"
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# rsync
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if ! command -v rsync >/dev/null 2>&1; then
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apt install -y rsync
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fi
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# 准备目录
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mkdir -p /opt/know-canvas/server /var/www/know-canvas /etc/know-canvas
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chown -R www-data:www-data /opt/know-canvas /var/www/know-canvas
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echo "[probe] 目录就绪"
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REMOTE_PROBE
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# 3. 上传前端
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echo ""
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echo "==> 3/8 rsync dist/ → /var/www/know-canvas/"
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rsync -az --delete -e "$RSYNC_SSH" "$PROJECT_ROOT/dist/" "$REMOTE:/var/www/know-canvas/"
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ssh $SSH_OPTS "$REMOTE" "chown -R www-data:www-data /var/www/know-canvas"
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# 4. 上传 server + 装依赖
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echo ""
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echo "==> 4/8 rsync server/ → /opt/know-canvas/server/"
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rsync -az --delete --exclude='node_modules' --exclude='yjs-data' \
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-e "$RSYNC_SSH" \
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"$PROJECT_ROOT/server/" "$REMOTE:/opt/know-canvas/server/"
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ssh $SSH_OPTS "$REMOTE" 'set -e
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cd /opt/know-canvas/server
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npm install --production
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mkdir -p yjs-data
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chown -R www-data:www-data /opt/know-canvas
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'
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# 5. 写 /etc/know-canvas/llm.env
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echo ""
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echo "==> 5/8 写 /etc/know-canvas/llm.env (含 DeepSeek key)"
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ssh $SSH_OPTS "$REMOTE" "set -e
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cat > /etc/know-canvas/llm.env <<EOF
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LLM_API_KEY=${DEEPSEEK_API_KEY}
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LLM_BASE_URL=${LLM_BASE_URL}
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LLM_MODEL=${LLM_MODEL}
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EOF
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chmod 600 /etc/know-canvas/llm.env
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chown root:root /etc/know-canvas/llm.env
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echo '[llm.env] 已写入'
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"
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# 6. 装 systemd units
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echo ""
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echo "==> 6/8 装 systemd unit (yws + llm-proxy)"
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scp -P "$REMOTE_PORT" \
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"$PROJECT_ROOT/deploy/know-canvas-yws.service" \
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"$PROJECT_ROOT/deploy/know-canvas-llm-proxy.service" \
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"$REMOTE:/tmp/"
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ssh $SSH_OPTS "$REMOTE" 'set -e
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mv /tmp/know-canvas-yws.service /etc/systemd/system/
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mv /tmp/know-canvas-llm-proxy.service /etc/systemd/system/
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systemctl daemon-reload
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systemctl enable know-canvas-yws know-canvas-llm-proxy
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systemctl restart know-canvas-yws know-canvas-llm-proxy
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sleep 2
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echo "--- yws ---"
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systemctl status know-canvas-yws --no-pager -l | head -15
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echo "--- llm-proxy ---"
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systemctl status know-canvas-llm-proxy --no-pager -l | head -15
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'
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# 7. 装 Caddyfile
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echo ""
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echo "==> 7/8 装 Caddyfile + reload"
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scp -P "$REMOTE_PORT" "$PROJECT_ROOT/deploy/Caddyfile.newvps" "$REMOTE:/tmp/Caddyfile"
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ssh $SSH_OPTS "$REMOTE" 'set -e
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mv /tmp/Caddyfile /etc/caddy/Caddyfile
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caddy validate --config /etc/caddy/Caddyfile
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systemctl reload caddy || systemctl restart caddy
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sleep 1
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systemctl status caddy --no-pager -l | head -10
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'
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# 8. 健康检查
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echo ""
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echo "==> 8/8 健康检查"
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ssh $SSH_OPTS "$REMOTE" 'set +e
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echo "--- 本机 yws health ---"
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curl -sf http://127.0.0.1:1234/health && echo
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echo "--- 本机 llm-proxy health ---"
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curl -sf http://127.0.0.1:17080/health && echo
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echo "--- 通过 caddy /canvas/ ---"
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curl -sI http://127.0.0.1/canvas/ | head -3
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echo "--- 通过 caddy /canvas/api/llm/health ---"
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curl -sf http://127.0.0.1/canvas/api/llm/health && echo
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'
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echo ""
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echo "============================================================"
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echo "部署完成。访问:"
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echo ""
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echo " http://${REMOTE_HOST}/canvas/"
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echo ""
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echo "排查:"
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echo " ssh -p ${REMOTE_PORT} ${REMOTE} 'journalctl -u know-canvas-yws -n 50'"
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echo " ssh -p ${REMOTE_PORT} ${REMOTE} 'journalctl -u know-canvas-llm-proxy -n 50'"
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echo " ssh -p ${REMOTE_PORT} ${REMOTE} 'journalctl -u caddy -n 50'"
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echo ""
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echo "更换 API key:"
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echo " ssh -p ${REMOTE_PORT} ${REMOTE} 'nano /etc/know-canvas/llm.env'"
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echo " ssh -p ${REMOTE_PORT} ${REMOTE} 'systemctl restart know-canvas-llm-proxy'"
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echo "============================================================"

‎deploy/know-canvas-llm-proxy.service‎

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# Know Canvas LLM Proxy systemd unit
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#
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# 把前端 /canvas/api/llm/* 请求转发到 DeepSeek (或其它 OpenAI 兼容 endpoint)
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# 凭据保管在 /etc/know-canvas/llm.env, 不暴露给浏览器
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#
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# 安装:
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# sudo mkdir -p /etc/know-canvas
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# sudo tee /etc/know-canvas/llm.env >/dev/null <<'EOF'
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# LLM_API_KEY=sk-xxxxxxxxxxxx
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# LLM_BASE_URL=https://api.deepseek.com/v1
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# LLM_MODEL=deepseek-chat
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# EOF
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# sudo chmod 600 /etc/know-canvas/llm.env
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#
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# sudo cp deploy/know-canvas-llm-proxy.service /etc/systemd/system/
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# sudo systemctl daemon-reload
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# sudo systemctl enable know-canvas-llm-proxy
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# sudo systemctl start know-canvas-llm-proxy
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# sudo systemctl status know-canvas-llm-proxy
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#
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# 查看日志:
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# sudo journalctl -u know-canvas-llm-proxy -f
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#
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# 更换 API key:
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# sudo nano /etc/know-canvas/llm.env
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# sudo systemctl restart know-canvas-llm-proxy
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[Unit]
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Description=Know Canvas LLM Proxy (DeepSeek / OpenAI compatible)
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After=network.target
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[Service]
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Type=simple
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User=www-data
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Group=www-data
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WorkingDirectory=/opt/know-canvas/server
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Environment=NODE_ENV=production
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Environment=HOST=127.0.0.1
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Environment=PORT=17080
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EnvironmentFile=/etc/know-canvas/llm.env
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ExecStart=/usr/bin/node /opt/know-canvas/server/vps-llm-proxy.js
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Restart=on-failure
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RestartSec=5
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StandardOutput=journal
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StandardError=journal
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# 资源限制 (LLM 转发不需要太多内存)
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MemoryMax=256M
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CPUQuota=30%
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# 安全加固
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NoNewPrivileges=true
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ProtectSystem=strict
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ProtectHome=true
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PrivateTmp=true
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[Install]
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WantedBy=multi-user.target

‎package.json‎

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"yws": "node server/y-ws-server.js",
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"bridge": "node server/claude-bridge.js",
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"hermes": "node server/hermes-proxy.js",
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"llm-proxy": "node server/vps-llm-proxy.js",
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"test:e2e": "playwright test",
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"test:e2e:ui": "playwright test --ui",
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"deploy": "bash deploy/deploy.sh"

‎server/package.json‎

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"yws": "node y-ws-server.js",
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"bridge": "node claude-bridge.js",
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"hermes": "node hermes-proxy.js",
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"llm-proxy": "node vps-llm-proxy.js",
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"dispatcher": "node orchestra-dispatcher.js",
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"worker:hermes": "node orchestra-hermes-worker.js",
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"conductor": "node orchestra-conductor.js",

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