连接 Redis

openclaw openclaw官方 2026-04-09 1

OpenClaw 与 Redis 的集成可以通过多种方式实现，主要取决于你的使用场景，以下是几种常见的集成方法：

连接 Redis-第1张图片-OpenClaw开源下载|官方OpenClaw下载

直接客户端连接

Python 示例

import redis
from openclaw import OpenClaw
redis_client = redis.Redis(
    host='localhost',
    port=6379,
    db=0,
    password='your_password'
)
# 初始化 OpenClaw
claw = OpenClaw(api_key='your_key')
# 使用 Redis 缓存结果
def cached_search(query):
    cache_key = f"search:{query}"
    # 检查缓存
    cached = redis_client.get(cache_key)
    if cached:
        return json.loads(cached)
    # 调用 OpenClaw API
    result = claw.search(query)
    # 缓存结果（设置过期时间）
    redis_client.setex(
        cache_key,
        3600,  # 1小时过期
        json.dumps(result)
    )
    return result

消息队列集成

使用 Redis 作为任务队列：

import redis
import json
import threading
from openclaw import OpenClaw
class OpenClawProcessor:
    def __init__(self):
        self.redis = redis.Redis()
        self.claw = OpenClaw(api_key='your_key')
    def process_queue(self):
        while True:
            # 从队列获取任务
            task = self.redis.blpop('openclaw_tasks', timeout=30)
            if task:
                task_data = json.loads(task[1])
                result = self.claw.process(task_data)
                # 存储结果
                result_key = f"result:{task_data['id']}"
                self.redis.setex(result_key, 600, json.dumps(result))
                # 发布通知
                self.redis.publish('openclaw_results', result_key)
# 启动处理线程
processor = OpenClawProcessor()
thread = threading.Thread(target=processor.process_queue)
thread.start()

Session 管理

使用 Redis 存储会话状态：

from flask import Flask, session
import redis
from flask_session import Session
from openclaw import OpenClaw
app = Flask(__name__)
app.config['SESSION_TYPE'] = 'redis'
app.config['SESSION_REDIS'] = redis.from_url('redis://localhost:6379')
Session(app)
@app.route('/search')
def search():
    user_id = session.get('user_id')
    # 用户特定的缓存
    cache_key = f"user:{user_id}:search_history"
    history = redis_client.lrange(cache_key, 0, 9)
    return {'history': history}

分布式锁

确保并发安全：

from redis import Redis
import time
from openclaw import OpenClaw
class DistributedProcessor:
    def __init__(self):
        self.redis = Redis()
        self.claw = OpenClaw()
    def process_with_lock(self, task_id, timeout=30):
        lock_key = f"lock:{task_id}"
        # 获取分布式锁
        if self.acquire_lock(lock_key, timeout):
            try:
                # 处理任务
                result = self.claw.process_task(task_id)
                return result
            finally:
                # 释放锁
                self.release_lock(lock_key)
        else:
            raise Exception("无法获取锁")
    def acquire_lock(self, lock_name, acquire_timeout=10):
        identifier = str(time.time())
        end = time.time() + acquire_timeout
        while time.time() < end:
            if self.redis.setnx(lock_name, identifier):
                self.redis.expire(lock_name, 30)
                return True
            elif not self.redis.ttl(lock_name):
                self.redis.expire(lock_name, 30)
            time.sleep(0.001)
        return False
    def release_lock(self, lock_name):
        self.redis.delete(lock_name)

缓存策略配置

# config.yaml
redis:
  host: localhost
  port: 6379
  db: 0
  password: null
cache:
  enabled: true
  ttl: 3600  # 秒
  max_entries: 10000
openclaw:
  api_key: your_key
  base_url: https://api.openclaw.com/v1
  timeout: 30

完整示例：带缓存的 API 服务

from fastapi import FastAPI, HTTPException
import redis
import json
import hashlib
from openclaw import OpenClaw
from typing import Optional
app = FastAPI()
# 初始化客户端
redis_client = redis.Redis(host='localhost', port=6379, db=0)
claw_client = OpenClaw(api_key='your_api_key')
def generate_cache_key(func_name: str, **kwargs) -> str:
    """生成缓存键"""
    key_str = f"{func_name}:{json.dumps(kwargs, sort_keys=True)}"
    return hashlib.md5(key_str.encode()).hexdigest()
@app.get("/api/search")
async def search(
    query: str,
    limit: Optional[int] = 10,
    use_cache: bool = True
):
    """搜索接口"""
    if use_cache:
        cache_key = generate_cache_key("search", query=query, limit=limit)
        cached = redis_client.get(cache_key)
        if cached:
            return {
                "source": "cache",
                "data": json.loads(cached)
            }
    try:
        # 调用 OpenClaw API
        result = await claw_client.async_search(
            query=query,
            limit=limit
        )
        # 缓存结果
        if use_cache:
            cache_key = generate_cache_key("search", query=query, limit=limit)
            redis_client.setex(
                cache_key,
                300,  # 5分钟过期
                json.dumps(result)
            )
        return {
            "source": "api",
            "data": result
        }
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))
@app.get("/api/cache/stats")
async def cache_stats():
    """获取缓存统计信息"""
    info = redis_client.info()
    return {
        "total_keys": redis_client.dbsize(),
        "memory_used": info.get('used_memory_human'),
        "hits": info.get('keyspace_hits'),
        "misses": info.get('keyspace_misses')
    }

生产环境建议

Docker Compose 配置

version: '3.8'
services:
  redis:
    image: redis:7-alpine
    ports:
      - "6379:6379"
    volumes:
      - redis_data:/data
    command: redis-server --appendonly yes
  app:
    build: .
    environment:
      REDIS_URL: redis://redis:6379/0
      OPENCLAW_API_KEY: ${OPENCLAW_API_KEY}
    depends_on:
      - redis
volumes:
  redis_data: