从零开始,一步步掌握OpenClaw。本文从最基础的安装,到高级的技能开发,完整覆盖OpenClaw的所有核心玩法。
OpenClaw是一个开源的AI智能体框架,可以帮你:
核心优势:
选择部署方式:
方式1:云部署(推荐,最简单)
方式2:本地部署(适合开发测试)
# 安装
pip install openclaw
# 初始化
openclaw init
# 启动
openclaw start
方式3:Docker部署
docker run -d \
--name openclaw \
-p 8080:8080 \
-e OPENAI_API_KEY=your_key \
openclaw/openclaw:latest
访问WebUI: http://localhost:8080
输入"你好",你就能看到OpenClaw的回复了!
OpenClaw需要调用大模型,先配置API Key:
# 编辑配置
nano ~/.openclaw/config.yaml
# 添加API Key
models:
- provider: anthropic
api_key: your_anthropic_key
model: claude-3-haiku
基础对话:
from openclaw import OpenClaw
client = OpenClaw()
response = client.chat("今天天气怎么样?")
print(response)
多轮对话:
context = []
while True:
user_input = input("你: ")
context.append({"role": "user", "content": user_input})
response = client.chat(context=context)
print(f"AI: {response}")
context.append({"role": "assistant", "content": response})
带参数的对话:
response = client.chat(
message="帮我计算",
context={"expression": "1+1"},
skills=["calculator"]
)
# 识别用户意图
intent = client.classify_intent("我想退货")
print(intent) # {'intent': 'return', 'confidence': 0.95}
# 提取实体
entities = client.extract_entities("我要退货订单号12345")
print(entities) # {'order_id': '12345'}
创建知识库:
# 上传文档
kb = client.create_knowledge_base(name="product_kb")
kb.upload_document("product_manual.pdf")
kb.upload_document("FAQ.md")
查询知识库:
results = kb.search("如何使用?")
for result in results:
print(f"片段: {result['text']}")
print(f"分数: {result['score']}")
基于知识库回答:
response = client.chat(
message="如何使用这个产品?",
knowledge_base="product_kb"
)
# 查看技能市场
openclaw skill search telegram
# 安装技能
openclaw skill install telegram-bot
# 查看已安装技能
openclaw skill list
# 删除技能
openclaw skill remove telegram-bot
1. 电商客服技能
openclaw skill install ecommerce-customer-service
功能:
2. 闲鱼自动回复
openclaw skill install xianyu-auto-reply
功能:
3. 数据分析
openclaw skill install data-analyzer
功能:
# 调用技能
result = client.use_skill(
skill="calculator",
action="calculate",
params={"expression": "1+1"}
)
print(result) # {'result': 2}
# skill_config.yaml
skills:
ecommerce-customer-service:
enabled: true
auto_reply: true
knowledge_base: ecommerce_kb
xianyu-auto-reply:
enabled: true
auto_ship: true
accounts:
- account_id: "account_1"
cookie: "your_cookie"
# 安装技能
openclaw skill install telegram-bot
# 配置
nano ~/.openclaw/channels/telegram.yaml
bot_token: your_bot_token
webhook_url: https://your_domain.com/telegram
from openclaw.channels import TelegramChannel
channel = TelegramChannel()
channel.start()
# 安装技能
openclaw skill install wechat-bot
# 配置
nano ~/.openclaw/channels/wechat.yaml
app_id: your_app_id
app_secret: your_secret
token: your_token
# 安装技能
openclaw skill install whatsapp-bot
# 配置
nano ~/.openclaw/channels/whatsapp.yaml
phone_number_id: your_phone_id
access_token: your_token
# 安装技能
openclaw skill install discord-bot
# 配置
nano ~/.openclaw/channels/discord.yaml
bot_token: your_bot_token
guild_id: your_guild_id
创建技能项目:
openclaw skill create my-skill
cd my-skill
目录结构:
my-skill/
├── __init__.py
├── skill.py
├── config.yaml
└── README.md
skill.py:
from openclaw import Skill
class MySkill(Skill):
def __init__(self):
super().__init__(name="my-skill", version="1.0.0")
def execute(self, action, params):
if action == "hello":
return self.hello(params)
elif action == "calculate":
return self.calculate(params)
def hello(self, params):
name = params.get("name", "World")
return f"Hello, {name}!"
def calculate(self, params):
expression = params.get("expression")
return eval(expression)
安装技能:
openclaw skill install .
使用技能:
result = client.use_skill(
skill="my-skill",
action="hello",
params={"name": "OpenClaw"}
)
print(result) # Hello, OpenClaw!
from openclaw import Workflow
# 创建工作流
workflow = Workflow(name="ecommerce_order")
# 添加步骤
workflow.add_step("validate_order")
workflow.add_step("check_stock")
workflow.add_step("process_payment")
workflow.add_step("create_shipment")
# 执行工作流
result = workflow.execute(order_data)
from openclaw import EventManager
# 监听事件
@event.on("new_order")
def handle_new_order(order):
# 自动回复
send_message(order["user_id"], "订单已创建")
# 触发工作流
workflow.execute(order)
@event.on("payment_success")
def handle_payment_success(payment):
# 自动发货
auto_ship(payment["order_id"])
from openclaw import Scheduler
scheduler = Scheduler()
# 定时任务
@scheduler.cron("0 9 * * *") # 每天9点
def daily_report():
report = generate_report()
send_notification(report)
# 间隔任务
@scheduler.interval(hours=1)
def hourly_check():
check_system_status()
scheduler.start()
# 部署多个实例
instances:
- name: openclaw-1
host: 10.0.1.101
port: 8080
- name: openclaw-2
host: 10.0.1.102
port: 8080
- name: openclaw-3
host: 10.0.1.103
port: 8080
# 负载均衡
load_balancer:
type: nginx
strategy: round_robin
from openclaw import Monitor
monitor = Monitor()
# 自定义监控指标
@monitor.metric("response_time")
def track_response_time(func):
def wrapper(*args, **kwargs):
start = time.time()
result = func(*args, **kwargs)
duration = time.time() - start
monitor.record("response_time", duration)
return result
return wrapper
# 告警规则
monitor.add_alert(
name="high_response_time",
condition="response_time > 5",
action="send_alert"
)
# 定时备份
0 2 * * * pg_dump openclaw > /backup/openclaw_$(date +\%Y\%m\%d).sql
0 3 * * * tar -czf /backup/config_$(date +\%Y\%m\%d).tar.gz ~/.openclaw
# 配置防火墙
ufw allow 8080/tcp
ufw allow 443/tcp
ufw enable
# 配置SSL
certbot --nginx -d your_domain.com
# 限制访问
# 只允许特定IP访问管理后台
nano /etc/nginx/sites-available/openclaw
from openclaw import Cache
cache = Cache()
@cache.memoize(ttl=3600)
def get_user_profile(user_id):
# 缓存1小时
return db.query(user_id)
# 手动缓存
cache.set("key", "value", ttl=3600)
value = cache.get("key")
import asyncio
from openclaw import AsyncOpenClaw
client = AsyncOpenClaw()
async def handle_message(message):
# 异步处理
response = await client.chat_async(message)
return response
# 批量处理消息
messages = ["你好", "天气", "订单"]
responses = client.batch_chat(messages)
# 批量意图识别
intents = client.batch_classify(messages)
新手(第1-2周):
进阶(第3-4周):
高级(第5-8周):
专家(3个月+):
Q: OpenClaw免费吗?
A: 框架本身免费,但需要付费使用大模型API。
Q: 需要编程基础吗?
A: 不需要,WebUI可以无代码使用。编程可以扩展功能。
Q: 服务器配置要求?
A: 2核4G起步,月成本约85元。
Q: 能支持多用户吗?
A: 可以,支持企业级多租户。
Q: 数据安全吗?
A: 支持本地部署,数据在你自己的服务器上。
OpenClaw从零到精通的完整路径:
每个阶段都有明确的目标和学习内容,按部就班,2个月就能从新手到专家。
再次强调快速开始:
现在就开始你的OpenClaw之旅吧!