Ubuntu系统安装部署Pandawiki智能知识库

一、系统环境准备

bash

# 更新系统

sudo apt update && sudo apt upgrade -y

sudo apt install -y git python3-pip python3-venv nginx ufw certbot

# 安装PostgreSQL数据库

sudo apt install -y postgresql postgresql-contrib

sudo -u postgres psql -c "CREATE DATABASE pandawiki;"

sudo -u postgres psql -c "CREATE USER wikiadmin WITH PASSWORD 'YourStrongPassword!';"

sudo -u postgres psql -c "GRANT ALL PRIVILEGES ON DATABASE pandawiki TO wikiadmin;"

# 创建应用目录

mkdir -p /opt/pandawiki && cd /opt/pandawiki

---

二、Pandawiki部署流程

1. 获取源代码

bash

git clone https://github.com/pandawiki/pandawiki.git

cd pandawiki

# 创建虚拟环境

python3 -m venv venv

source venv/bin/activate

2. 安装依赖

bash

pip install --upgrade pip

pip install -r requirements.txt

pip install gunicorn gevent psycopg2-binary

3. 配置应用

bash

# 创建配置文件

cp config.example.py config.py

nano config.py

python

# 关键配置修改

SQLALCHEMY_DATABASE_URI = 'postgresql+psycopg2://wikiadmin:YourStrongPassword!@localhost/pandawiki'

SECRET_KEY = '生成32位密钥(openssl rand -hex 32)'

ALLOW_REGISTRATION = False # 生产环境禁用开放注册

UPLOAD_FOLDER = '/opt/pandawiki/uploads' # 上传目录

4. 初始化数据库

bash

flask db upgrade

flask init-data

# 创建上传目录

sudo mkdir -p /opt/pandawiki/uploads

sudo chown -R USER:USER /opt/pandawiki

5. 测试运行

bash

gunicorn --bind 0.0.0.0:8000 app:app

# 访问 http://<服务器IP>:8000 验证

---

三、生产环境部署

1. 创建系统服务

bash

sudo nano /etc/systemd/system/pandawiki.service

ini

Unit

Description=Pandawiki Gunicorn Service

After=network.target postgresql.service

Service

User=ubuntu

Group=www-data

WorkingDirectory=/opt/pandawiki/pandawiki

Environment="PATH=/opt/pandawiki/pandawiki/venv/bin"

ExecStart=/opt/pandawiki/pandawiki/venv/bin/gunicorn \

--worker-class gevent \

--workers 5 \

--bind unix:/run/pandawiki.sock \

--timeout 300 \

--log-level warning \

app:app

Restart=always

RestartSec=3

Install

WantedBy=multi-user.target

bash

sudo systemctl daemon-reload

sudo systemctl start pandawiki

sudo systemctl enable pandawiki

2. Nginx配置

bash

sudo nano /etc/nginx/sites-available/pandawiki

nginx

server {

listen 80;

server_name wiki.yourdomain.com;

client_max_body_size 100M; # 允许大文件上传

location / {

include proxy_params;

proxy_pass http://unix:/run/pandawiki.sock;

proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;

proxy_set_header Host $host;

proxy_connect_timeout 300s;

proxy_read_timeout 300s;

}

location /static {

alias /opt/pandawiki/pandawiki/static;

expires 30d;

}

location /uploads {

alias /opt/pandawiki/uploads;

expires 30d;

add_header Cache-Control "public";

}

}

bash

sudo ln -s /etc/nginx/sites-available/pandawiki /etc/nginx/sites-enabled/

sudo nginx -t && sudo systemctl reload nginx

3. 启用HTTPS

bash

sudo ufw allow 'Nginx Full'

sudo certbot --nginx -d wiki.yourdomain.com

---

四、监控平台集成

1. 安装Prometheus+Grafana

bash

# 添加仓库

sudo apt-get install -y apt-transport-https software-properties-common wget

wget -q -O - https://packages.grafana.com/gpg.key | sudo apt-key add -

echo "deb https://packages.grafana.com/oss/deb stable main" | sudo tee /etc/apt/sources.list.d/grafana.list

sudo apt update

# 安装组件

sudo apt install -y prometheus prometheus-node-exporter grafana

2. 配置Prometheus监控Pandawiki

bash

sudo nano /etc/prometheus/prometheus.yml

yaml

scrape_configs:

# 添加Pandawiki监控

• job_name: 'pandawiki'

metrics_path: '/metrics'

static_configs:

• targets: ['localhost:8000'] # Gunicorn 暴露的指标端口

relabel_configs:

• source_labels: [address]

target_label: instance

replacement: 'pandawiki-primary'

3. 添加Pandawiki专属仪表板

1. 访问Grafana：http://<服务器IP>:3000 (admin/admin)
2. 添加Prometheus数据源：http://localhost:9090
3. 导入仪表板：
   • 使用JSON文件：pandawiki-grafana-dashboard.json
   • 或创建自定义仪表板监控：
     • 请求速率
     • 错误率(4xx/5xx)
     • 响应延迟(P95)
     • 数据库查询性能
     • 内存/CPU使用率

4. 关键监控指标配置

bash

sudo nano /etc/prometheus/alert_rules.yml

yaml

groups:

• name: pandawiki

rules:

• alert: HighErrorRate

expr: sum(rate(http_requests_total{status=~"5.."}[5m]) / sum(rate(http_requests_total[5m])) * 100 > 5

for: 10m

labels:

severity: critical

annotations:

summary: "高错误率 {{ $labels.instance }}"

description: "5xx错误率超过5% (当前值: {{ $value }}%)"

• alert: SlowResponse

expr: histogram_quantile(0.95, sum(rate(http_request_duration_seconds_bucket[5m])) > 3

for: 15m

labels:

severity: warning

annotations:

summary: "响应延迟过高 {{ $labels.instance }}"

description: "P95响应延迟超过3秒 (当前值: {{ $value }}s)"

---

五、数据备份与恢复

1. 自动化备份脚本

bash

sudo nano /usr/local/bin/pandawiki-backup

bash

#!/bin/bash

# 备份数据库、上传文件和配置

BACKUP_DIR="/backup/pandawiki/$(date +%Y%m%d)"

mkdir -p $BACKUP_DIR

# 数据库备份

sudo -u postgres pg_dump pandawiki > $BACKUP_DIR/pandawiki.sql

gzip $BACKUP_DIR/pandawiki.sql

# 文件备份

tar -czf $BACKUP_DIR/uploads.tar.gz /opt/pandawiki/uploads

tar -czf $BACKUP_DIR/config.tar.gz /opt/pandawiki/pandawiki/config.py

# 备份监控数据

tar -czf $BACKUP_DIR/prometheus.tar.gz /var/lib/prometheus

# 加密备份

gpg --batch --passphrase "YourEncryptionKey" --symmetric $BACKUP_DIR/*.gz

# 保留最近30天备份

find /backup/pandawiki -type d -mtime +30 -exec rm -rf {} \;

bash

sudo chmod +x /usr/local/bin/pandawiki-backup

sudo crontab -e

cron

每天凌晨2点备份

0 2 * * * /usr/local/bin/pandawiki-backup

2. 云存储备份（AWS S3示例）

bash

# 安装AWS CLI

sudo apt install awscli -y

aws configure

# 添加备份脚本末尾

aws s3 sync --delete /backup/pandawiki s3://your-bucket/pandawiki-backups

3. 灾难恢复流程

bash

# 1. 恢复数据库

gunzip -c pandawiki.sql.gz | sudo -u postgres psql pandawiki

# 2. 恢复文件

sudo tar -xzf uploads.tar.gz -C /

sudo tar -xzf config.tar.gz -C /

# 3. 重启服务

sudo systemctl restart pandawiki postgresql nginx

---

六、日常运维管理

1. 每日检查清单

bash

# 服务状态检查

sudo systemctl status pandawiki nginx postgresql prometheus

# 日志检查

journalctl -u pandawiki --since "today" | grep -E 'ERROR|CRITICAL'

tail -100 /var/log/nginx/error.log

# 存储检查

df -h / /opt /backup

du -sh /opt/pandawiki/uploads

# 性能检查

pg_top -d pandawiki # 数据库性能

htop # 系统资源

2. 自动化维护脚本

bash

sudo nano /usr/local/bin/pandawiki-maintenance

bash

#!/bin/bash

# 每周维护任务

source /opt/pandawiki/pandawiki/venv/bin/activate

cd /opt/pandawiki/pandawiki

# 1. 更新代码

git fetch origin

git checkout main

git reset --hard origin/main

# 2. 更新依赖

pip install -r requirements.txt --upgrade

# 3. 数据库迁移

flask db upgrade

# 4. 清理缓存

find /tmp -name "pandawiki_cache_*" -mtime +7 -delete

# 5. 重启服务

sudo systemctl restart pandawiki

3. 智能问答增强

bash

# 安装AI插件

pip install openai faiss-cpu

# 配置智能问答

nano config.py

python

# 添加AI配置

AI_ENABLED = True

OPENAI_API_KEY = 'sk-xxx'

AI_INDEX_PATH = '/opt/pandawiki/faiss_index'

bash

# 创建知识索引

flask ai build-index

---

七、安全加固措施

1. 网络安全

bash

# 防火墙配置

sudo ufw default deny incoming

sudo ufw allow ssh

sudo ufw allow https

sudo ufw enable

# 安装Fail2Ban

sudo apt install fail2ban

sudo cp /etc/fail2ban/jail.conf /etc/fail2ban/jail.local

sudo nano /etc/fail2ban/jail.local

ini

pandawiki

enabled = true

port = http,https

filter = pandawiki

logpath = /var/log/nginx/access.log

maxretry = 5

findtime = 600

bantime = 86400

2. 文件安全

bash

# 设置目录权限

sudo chown -R ubuntu:www-data /opt/pandawiki

sudo find /opt/pandawiki/uploads -type f -exec chmod 640 {} \;

sudo find /opt/pandawiki/pandawiki -type d -exec chmod 750 {} \;

# 配置文件完整性监控

sudo apt install aide

sudo aideinit

sudo cp /var/lib/aide/aide.db.new /var/lib/aide/aide.db

sudo crontab -e

cron

每天检查文件完整性

0 3 * * * /usr/bin/aide --check

3. 数据库安全

sql

-- 限制连接数

ALTER SYSTEM SET max_connections = 100;

-- 禁用远程访问

sudo nano /etc/postgresql/14/main/pg_hba.conf

# 修改为：

host all all 127.0.0.1/32 md5

---

八、注意事项

1. 升级策略

• 测试环境先行：先在测试环境验证升级
• 备份优先：升级前执行完整备份
• 分阶段升级：

bash

# 1. 停用负载

sudo systemctl stop pandawiki

# 2. 更新代码

git pull origin main

# 3. 数据库迁移

flask db upgrade

# 4. 重启服务

sudo systemctl start pandawiki

2. 性能优化

python

# config.py 性能优化配置

CACHE_TYPE = "RedisCache"

CACHE_REDIS_URL = "redis://localhost:6379/0"

SQLALCHEMY_ENGINE_OPTIONS = {

"pool_pre_ping": True,

"pool_recycle": 300,

"pool_size": 20,

"max_overflow": 10

}

3. 灾备恢复计划

故障类型	恢复时间目标(RTO)	恢复点目标(RPO)	恢复方案
应用故障	15分钟	5分钟	从备份恢复服务配置
数据库损坏	1小时	1小时	从SQL备份恢复
服务器宕机	2小时	24小时	云镜像恢复 + 最新数据备份
数据中心故障	4小时	24小时	跨区域备份恢复

4. 智能知识库优化

1. 知识图谱集成：

bash

pip install py2neo

flask knowledge-graph build

2. 问答质量监控：
   • 记录用户问答满意度
   • 定期优化AI模型
   • 设置未知问题报警

5. 合规性要求

1. GDPR合规：
   • 用户数据加密存储
   • 提供数据导出接口
   • 自动删除90天未活跃用户
2. 操作审计：

sql

CREATE TABLE audit_log (

id SERIAL PRIMARY KEY,

user_id INT,

action VARCHAR(50),

target VARCHAR(100),

timestamp TIMESTAMP DEFAULT NOW()

);

通过以上完整流程，您将获得一个安全、高效、可监控的智能知识库系统。建议每月执行一次安全审计，每季度进行恢复演练，确保系统持续稳定运行。