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2878 Design D5e07314 by tools-only — Agent Skill

Name: 2878 Design D5e07314
Author: tools-only

Design: Docker Compose Deployment with Redis Cache

Architecture Overview

部署模式

提供两种部署模式：

独立模式 - 0 到 1 完整部署（包含所有基础设施）
复用模式 - 复用已有 Langfuse 的 ClickHouse/Redis

┌─────────────────────────────────────────────────────────────────────────┐
│                    Complete Deployment Architecture                      │
│                         (stock_network)                                  │
├─────────────────────────────────────────────────────────────────────────┤
│                                                                          │
│  ┌─────────────────────── 基础设施层 ───────────────────────┐           │
│  │                                                          │           │
│  │  ┌────────────┐   ┌────────────┐   ┌────────────┐       │           │
│  │  │ ClickHouse │   │   Redis    │   │  Postgres  │       │           │
│  │  │   :9000    │   │   :6379    │   │   :5432    │       │           │
│  │  │   :8123    │   │  (1GB)     │   │ (Langfuse) │       │           │
│  │  └─────┬──────┘   └─────┬──────┘   └─────┬──────┘       │           │
│  │        │                │                │               │           │
│  └────────┼────────────────┼────────────────┼───────────────┘           │
│           │                │                │                            │
│  ┌────────┼────────────────┼────────────────┼───────────────┐           │
│  │        ▼                ▼                ▼    应用层      │           │
│  │  ┌────────────┐   ┌────────────┐   ┌────────────┐       │           │
│  │  │  Backend   │   │  Frontend  │   │  Langfuse  │       │           │
│  │  │  (FastAPI) │   │  (Vue/Vite)│   │    Web     │       │           │
│  │  │   :8000    │   │   :3001    │   │   :3000    │       │           │
│  │  └────────────┘   └────────────┘   └────────────┘       │           │
│  │                                                          │           │
│  └──────────────────────────────────────────────────────────┘           │
│                                                                          │
└─────────────────────────────────────────────────────────────────────────┘

External Ports:
- 3000: Langfuse Web UI
- 3001: Stock Platform Frontend
- 8000: Stock Platform Backend API
- 6379: Redis (可选暴露)
- 8123: ClickHouse HTTP (可选暴露)
- 9000: ClickHouse Native (可选暴露)

Service Components

共享基础设施（与 Langfuse 复用）

ClickHouse Service

clickhouse:
  image: clickhouse/clickhouse-server:24
  restart: always
  user: "101:101"
  environment:
    CLICKHOUSE_DB: default
    CLICKHOUSE_USER: clickhouse
    CLICKHOUSE_PASSWORD: ${CLICKHOUSE_PASSWORD:-clickhouse}
  volumes:
    - clickhouse_data:/var/lib/clickhouse
    - clickhouse_logs:/var/log/clickhouse-server
  ports:
    - "${CLICKHOUSE_HTTP_PORT:-8123}:8123"   # HTTP interface
    - "${CLICKHOUSE_NATIVE_PORT:-9000}:9000" # Native protocol
  healthcheck:
    test: wget --no-verbose --tries=1 --spider http://localhost:8123/ping || exit 1
    interval: 5s
    timeout: 5s
    retries: 10

数据库隔离策略：

Langfuse 使用 default 数据库
Stock Platform 使用 stock_data 数据库
通过不同数据库实现数据隔离

Redis Service

redis:
  image: redis:7-alpine
  restart: always
  command: >
    --requirepass ${REDIS_PASSWORD:-stockredis123}
    --maxmemory 1gb
    --maxmemory-policy allkeys-lru
    --appendonly yes
  ports:
    - "${REDIS_PORT:-6379}:6379"  # 暴露端口供调试
  volumes:
    - redis_data:/data
  healthcheck:
    test: ["CMD", "redis-cli", "-a", "${REDIS_PASSWORD:-stockredis123}", "ping"]
    interval: 3s
    timeout: 10s
    retries: 10

配置说明：

内存限制：1GB
淘汰策略：LRU（最近最少使用）
持久化：AOF 模式
端口：对外暴露 6379

应用服务

Backend Service

backend:
  build:
    context: .
    dockerfile: docker/Dockerfile.backend
  restart: always
  ports:
    - "${BACKEND_PORT:-8000}:8000"
  environment:
    # ClickHouse
    CLICKHOUSE_HOST: clickhouse
    CLICKHOUSE_PORT: 9000
    CLICKHOUSE_HTTP_PORT: 8123
    CLICKHOUSE_USER: ${CLICKHOUSE_USER:-clickhouse}
    CLICKHOUSE_PASSWORD: ${CLICKHOUSE_PASSWORD:-clickhouse}
    CLICKHOUSE_DATABASE: stock_data
    # Redis
    REDIS_HOST: redis
    REDIS_PORT: 6379
    REDIS_PASSWORD: ${REDIS_PASSWORD:-stockredis123}
    # Langfuse
    LANGFUSE_HOST: ${LANGFUSE_HOST:-http://langfuse-web:3000}
    LANGFUSE_PUBLIC_KEY: ${LANGFUSE_PUBLIC_KEY:-}
    LANGFUSE_SECRET_KEY: ${LANGFUSE_SECRET_KEY:-}
  depends_on:
    clickhouse:
      condition: service_healthy
    redis:
      condition: service_healthy
  healthcheck:
    test: curl -f http://localhost:8000/health || exit 1
    interval: 30s
    timeout: 10s
    retries: 3

Frontend Service

frontend:
  build:
    context: ./frontend
    dockerfile: ../docker/Dockerfile.frontend
    target: ${FRONTEND_TARGET:-production}
  restart: always
  ports:
    - "${FRONTEND_PORT:-3001}:3000"
  environment:
    VITE_API_BASE_URL: http://backend:8000
  depends_on:
    backend:
      condition: service_healthy

Langfuse Services（完整部署时）

langfuse-worker:
  image: langfuse/langfuse-worker:3
  restart: always
  depends_on:
    postgres:
      condition: service_healthy
    redis:
      condition: service_healthy
    clickhouse:
      condition: service_healthy
  environment:
    DATABASE_URL: postgresql://postgres:${POSTGRES_PASSWORD:-postgres}@postgres:5432/postgres
    CLICKHOUSE_URL: http://clickhouse:8123
    CLICKHOUSE_MIGRATION_URL: clickhouse://clickhouse:9000
    CLICKHOUSE_USER: ${CLICKHOUSE_USER:-clickhouse}
    CLICKHOUSE_PASSWORD: ${CLICKHOUSE_PASSWORD:-clickhouse}
    REDIS_HOST: redis
    REDIS_PORT: 6379
    REDIS_AUTH: ${REDIS_PASSWORD:-stockredis123}
    # ... 其他 Langfuse 配置

langfuse-web:
  image: langfuse/langfuse:3
  restart: always
  ports:
    - "${LANGFUSE_PORT:-3000}:3000"
  depends_on:
    - langfuse-worker
  environment:
    NEXTAUTH_URL: ${LANGFUSE_URL:-http://localhost:3000}
    # ... 继承 worker 环境变量

Compose File Structure

stock_datasource/
├── docker-compose.yml          # 主编排（Backend + Frontend）
├── docker-compose.infra.yml    # 基础设施（ClickHouse + Redis + Postgres）
├── docker-compose.langfuse.yml # Langfuse 服务
├── docker-compose.dev.yml      # 开发模式覆盖
├── docker-compose.override.yml # 本地个性化配置（git ignored）
└── docker/
    ├── Dockerfile.backend
    ├── Dockerfile.frontend
    └── nginx.conf

使用方式

# 1. 完整部署（0 到 1，包含 Langfuse）
docker compose -f docker-compose.yml \
               -f docker-compose.infra.yml \
               -f docker-compose.langfuse.yml \
               up -d

# 2. 复用已有 Langfuse 基础设施
# 只启动 Backend + Frontend，连接外部服务
docker compose up -d

# 3. 开发模式（热重载）
docker compose -f docker-compose.yml \
               -f docker-compose.infra.yml \
               -f docker-compose.dev.yml \
               up

# 4. 快捷脚本
./scripts/docker-start.sh         # 完整启动
./scripts/docker-start.sh --dev   # 开发模式
./scripts/docker-start.sh --app   # 仅应用（复用基础设施）

Redis Cache Strategy

Cache Key Design (更新)

数据类型	Key Pattern	TTL	示例	Redis DB
实时行情	`stock:quote:{ts_code}`	60s	`stock:quote:600519.SH`	1
日K数据	`stock:daily:{ts_code}:{date}`	24h	`stock:daily:600519.SH:20250119`	1
股票基础信息	`stock:basic:{ts_code}`	1h	`stock:basic:600519.SH`	1
市场概览	`stock:overview:{type}:{date}`	5min	`stock:overview:hot_etf:20250119`	1
工作流	`stock:workflow:{id}`	5min	`stock:workflow:template_single_stock`	1
用户会话	`stock:session:{user_id}`	30min	`stock:session:u123`	1

注意：

使用 stock: 前缀与 Langfuse 数据隔离
使用 Redis DB 1（Langfuse 默认使用 DB 0）

Cache Service Implementation

# src/stock_datasource/services/cache_service.py

import json
import logging
from typing import Any, Optional, Callable
from functools import wraps
from redis import Redis, ConnectionError
from stock_datasource.config.settings import settings

logger = logging.getLogger(__name__)

class CacheService:
    """Redis cache service with Langfuse coexistence support."""
    
    PREFIX = "stock:"  # 命名空间前缀
    
    def __init__(self):
        self._redis: Optional[Redis] = None
        self._available = True
    
    @property
    def redis(self) -> Optional[Redis]:
        if self._redis is None:
            try:
                self._redis = Redis(
                    host=settings.REDIS_HOST,
                    port=settings.REDIS_PORT,
                    password=settings.REDIS_PASSWORD,
                    db=1,  # 使用 DB 1，与 Langfuse (DB 0) 隔离
                    decode_responses=True,
                    socket_connect_timeout=5,
                )
                self._redis.ping()
                logger.info("Redis connected successfully")
            except Exception as e:
                logger.warning(f"Redis connection failed: {e}")
                self._available = False
        return self._redis
    
    def _key(self, key: str) -> str:
        """Add namespace prefix."""
        return f"{self.PREFIX}{key}"
    
    async def get(self, key: str) -> Optional[Any]:
        """Get cached value with graceful degradation."""
        if not self._available:
            return None
        try:
            data = self.redis.get(self._key(key))
            return json.loads(data) if data else None
        except (ConnectionError, Exception) as e:
            logger.warning(f"Cache get failed: {e}")
            return None
    
    async def set(self, key: str, value: Any, ttl: int = 300) -> bool:
        """Set cache with TTL."""
        if not self._available:
            return False
        try:
            return self.redis.setex(
                self._key(key),
                ttl,
                json.dumps(value, ensure_ascii=False, default=str)
            )
        except (ConnectionError, Exception) as e:
            logger.warning(f"Cache set failed: {e}")
            return False
    
    async def delete(self, key: str) -> bool:
        """Delete single key."""
        if not self._available:
            return False
        try:
            return bool(self.redis.delete(self._key(key)))
        except Exception:
            return False
    
    async def delete_pattern(self, pattern: str) -> int:
        """Delete keys matching pattern."""
        if not self._available:
            return 0
        try:
            keys = self.redis.keys(self._key(pattern))
            if keys:
                return self.redis.delete(*keys)
            return 0
        except Exception as e:
            logger.warning(f"Cache delete pattern failed: {e}")
            return 0
    
    def cached(self, key_template: str, ttl: int = 300):
        """Decorator for caching function results."""
        def decorator(func: Callable):
            @wraps(func)
            async def wrapper(*args, **kwargs):
                # Build cache key
                key = key_template.format(**kwargs) if kwargs else key_template
                
                # Try cache first
                cached = await self.get(key)
                if cached is not None:
                    return cached
                
                # Execute function
                result = await func(*args, **kwargs)
                
                # Cache result
                if result is not None:
                    await self.set(key, result, ttl)
                
                return result
            return wrapper
        return decorator
    
    def get_stats(self) -> dict:
        """Get cache statistics."""
        if not self._available:
            return {"available": False}
        try:
            info = self.redis.info("stats")
            return {
                "available": True,
                "hits": info.get("keyspace_hits", 0),
                "misses": info.get("keyspace_misses", 0),
                "keys": self.redis.dbsize(),
            }
        except Exception:
            return {"available": False}


# Singleton instance
_cache_service: Optional[CacheService] = None

def get_cache_service() -> CacheService:
    global _cache_service
    if _cache_service is None:
        _cache_service = CacheService()
    return _cache_service

Docker Files

Backend Dockerfile

# docker/Dockerfile.backend
FROM python:3.11-slim AS base

WORKDIR /app

# Install system dependencies
RUN apt-get update && apt-get install -y --no-install-recommends \
    gcc \
    libffi-dev \
    curl \
    && rm -rf /var/lib/apt/lists/*

# Install uv
RUN pip install uv

# Copy dependency files
COPY pyproject.toml uv.lock ./

# Install dependencies
RUN uv sync --frozen --no-dev

# Copy source code
COPY src/ ./src/
COPY .env.example ./.env

# Expose port
EXPOSE 8000

# Health check
HEALTHCHECK --interval=30s --timeout=10s --retries=3 --start-period=60s \
    CMD curl -f http://localhost:8000/health || exit 1

# Start server
CMD ["uv", "run", "python", "-m", "stock_datasource.services.http_server"]

# Development stage
FROM base AS development
RUN uv sync --frozen
CMD ["uv", "run", "uvicorn", "stock_datasource.services.http_server:app", "--reload", "--host", "0.0.0.0", "--port", "8000"]

Frontend Dockerfile

# docker/Dockerfile.frontend

# Development stage
FROM node:20-alpine AS development
WORKDIR /app
COPY package*.json ./
RUN npm ci
COPY . .
EXPOSE 3000
CMD ["npm", "run", "dev", "--", "--host", "0.0.0.0", "--port", "3000"]

# Build stage
FROM node:20-alpine AS builder
WORKDIR /app
COPY package*.json ./
RUN npm ci
COPY . .
RUN npm run build

# Production stage
FROM nginx:alpine AS production
COPY --from=builder /app/dist /usr/share/nginx/html
COPY ../docker/nginx.conf /etc/nginx/conf.d/default.conf
EXPOSE 3000
CMD ["nginx", "-g", "daemon off;"]

Nginx Config

# docker/nginx.conf
server {
    listen 3000;
    server_name localhost;
    root /usr/share/nginx/html;
    index index.html;

    # Gzip compression
    gzip on;
    gzip_types text/plain text/css application/json application/javascript text/xml;

    # SPA fallback
    location / {
        try_files $uri $uri/ /index.html;
    }

    # API proxy
    location /api {
        proxy_pass http://backend:8000;
        proxy_http_version 1.1;
        proxy_set_header Upgrade $http_upgrade;
        proxy_set_header Connection 'upgrade';
        proxy_set_header Host $host;
        proxy_cache_bypass $http_upgrade;
    }

    # Health check
    location /health {
        return 200 'OK';
        add_header Content-Type text/plain;
    }
}

Environment Configuration

.env.docker (模板)

# ============================================
# Infrastructure Configuration
# ============================================
# ClickHouse
CLICKHOUSE_HOST=clickhouse
CLICKHOUSE_PORT=9000
CLICKHOUSE_HTTP_PORT=8123
CLICKHOUSE_USER=clickhouse
CLICKHOUSE_PASSWORD=clickhouse
CLICKHOUSE_DATABASE=stock_data

# Redis (1GB, 暴露端口)
REDIS_HOST=redis
REDIS_PORT=6379
REDIS_PASSWORD=stockredis123
REDIS_DB=1

# Postgres (for Langfuse)
POSTGRES_PASSWORD=postgres

# ============================================
# Application Ports
# ============================================
BACKEND_PORT=8000
FRONTEND_PORT=3001
LANGFUSE_PORT=3000

# ============================================
# Langfuse Configuration
# ============================================
LANGFUSE_URL=http://localhost:3000
LANGFUSE_PUBLIC_KEY=your_public_key
LANGFUSE_SECRET_KEY=your_secret_key

# ============================================
# API Keys (required)
# ============================================
TUSHARE_TOKEN=your_tushare_token
OPENAI_API_KEY=your_openai_key
OPENAI_BASE_URL=https://api.openai.com/v1
OPENAI_MODEL=gpt-4

# ============================================
# Cache TTL Settings (seconds)
# ============================================
CACHE_TTL_QUOTE=60
CACHE_TTL_DAILY=86400
CACHE_TTL_BASIC=3600
CACHE_TTL_OVERVIEW=300

Startup Scripts

docker-start.sh

#!/bin/bash
# scripts/docker-start.sh

set -e

SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
PROJECT_DIR="$(dirname "$SCRIPT_DIR")"

cd "$PROJECT_DIR"

# Colors
GREEN='\033[0;32m'
YELLOW='\033[1;33m'
NC='\033[0m'

usage() {
    echo "Usage: $0 [OPTIONS]"
    echo ""
    echo "Options:"
    echo "  --full      Complete deployment (infra + langfuse + app)"
    echo "  --app       Application only (connect to existing infra)"
    echo "  --dev       Development mode with hot reload"
    echo "  --infra     Infrastructure only (clickhouse + redis + postgres)"
    echo "  --down      Stop all services"
    echo "  --logs      Show logs"
    echo ""
}

case "${1:-full}" in
    --full|full)
        echo -e "${GREEN}Starting complete deployment...${NC}"
        docker compose -f docker-compose.yml \
                       -f docker-compose.infra.yml \
                       -f docker-compose.langfuse.yml \
                       up -d --build
        ;;
    --app|app)
        echo -e "${GREEN}Starting application services only...${NC}"
        docker compose up -d --build
        ;;
    --dev|dev)
        echo -e "${YELLOW}Starting development mode...${NC}"
        docker compose -f docker-compose.yml \
                       -f docker-compose.infra.yml \
                       -f docker-compose.dev.yml \
                       up --build
        ;;
    --infra|infra)
        echo -e "${GREEN}Starting infrastructure only...${NC}"
        docker compose -f docker-compose.infra.yml up -d
        ;;
    --down|down)
        echo -e "${YELLOW}Stopping all services...${NC}"
        docker compose -f docker-compose.yml \
                       -f docker-compose.infra.yml \
                       -f docker-compose.langfuse.yml \
                       down
        ;;
    --logs|logs)
        docker compose logs -f
        ;;
    *)
        usage
        ;;
esac

Data Isolation Strategy

ClickHouse 数据库隔离

服务	数据库	表前缀
Langfuse	`default`	`langfuse_*`
Stock Platform	`stock_data`	无

初始化脚本自动创建 stock_data 数据库：

-- docker/init-clickhouse.sql
CREATE DATABASE IF NOT EXISTS stock_data;

Redis 数据库隔离

服务	DB	Key 前缀
Langfuse	0	无
Stock Platform	1	`stock:`

Health Checks

# 健康检查端点更新
backend /health 响应：
{
  "status": "healthy",
  "services": {
    "clickhouse": "connected",
    "redis": "connected",
    "langfuse": "connected"  # 可选
  },
  "cache": {
    "available": true,
    "hits": 1234,
    "misses": 56,
    "keys": 89
  }
}

Migration Path

Phase 1: Docker 化

创建 Docker 文件
创建 Compose 编排
验证独立部署

Phase 2: Redis 集成

添加 Redis 依赖
实现缓存服务
配置数据库隔离

Phase 3: 缓存集成

高频 API 添加缓存
添加缓存监控
优化 TTL 配置

Phase 4: Langfuse 集成

共享基础设施配置
网络互通验证
监控整合

Risks & Mitigations

风险	影响	缓解措施
ClickHouse 数据冲突	Langfuse 数据污染	使用独立数据库 `stock_data`
Redis 内存溢出	服务异常	设置 1GB 上限 + LRU 淘汰
Redis 密码不一致	连接失败	统一使用环境变量
端口冲突	服务启动失败	可配置端口映射
初次构建慢	开发体验差	多阶段构建 + 层缓存

2878 Design D5e07314

File contents

Design: Docker Compose Deployment with Redis Cache

Architecture Overview

部署模式

Service Components

共享基础设施（与 Langfuse 复用）

ClickHouse Service

Redis Service

应用服务

Backend Service

Frontend Service

Langfuse Services（完整部署时）

Compose File Structure

使用方式

Redis Cache Strategy

Cache Key Design (更新)

Cache Service Implementation

Docker Files

Backend Dockerfile

Frontend Dockerfile

Nginx Config

Environment Configuration

.env.docker (模板)

Startup Scripts

docker-start.sh

Data Isolation Strategy

ClickHouse 数据库隔离

Redis 数据库隔离

Health Checks

Migration Path

Phase 1: Docker 化

Phase 2: Redis 集成

Phase 3: 缓存集成

Phase 4: Langfuse 集成

Risks & Mitigations

Frequently asked questions

2878 Design D5e07314

File contents

Design: Docker Compose Deployment with Redis Cache

Architecture Overview

部署模式

Service Components

共享基础设施（与 Langfuse 复用）

ClickHouse Service

Redis Service

应用服务

Backend Service

Frontend Service

Langfuse Services（完整部署时）

Compose File Structure

使用方式

Redis Cache Strategy

Cache Key Design (更新)

Cache Service Implementation

Docker Files

Backend Dockerfile

Frontend Dockerfile

Nginx Config

Environment Configuration

.env.docker (模板)

Startup Scripts

docker-start.sh

Data Isolation Strategy

ClickHouse 数据库隔离

Redis 数据库隔离

Health Checks

Migration Path

Phase 1: Docker 化

Phase 2: Redis 集成

Phase 3: 缓存集成

Phase 4: Langfuse 集成

Risks & Mitigations

Related skills

Frequently asked questions

How do I install the 2878 Design D5e07314 skill?

What does the 2878 Design D5e07314 skill do?

Is 2878 Design D5e07314 safe to use?

Which AI agents work with 2878 Design D5e07314?

Is 2878 Design D5e07314 free to use?

Who published 2878 Design D5e07314?