feat: add FalkorDB, LMDeploy, and Pogocache with configuration files and documentation

This commit is contained in:
Sun-ZhenXing
2026-01-20 14:18:28 +08:00
parent 1c528c0e64
commit 2a010843d1
14 changed files with 384 additions and 0 deletions

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# FalkorDB Version
# Latest stable version can be found at https://hub.docker.com/r/falkordb/falkordb/tags
FALKORDB_VERSION=v4.14.11
# Port configuration
# Port for Redis protocol (Graph Database)
FALKORDB_PORT_OVERRIDE=6379
# Port for FalkorDB Browser UI
FALKORDB_BROWSER_PORT_OVERRIDE=3000
# Resource limits
FALKORDB_CPU_LIMIT=1.00
FALKORDB_MEMORY_LIMIT=2G
FALKORDB_CPU_RESERVATION=0.25
FALKORDB_MEMORY_RESERVATION=512M
# Timezone
TZ=UTC

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# FalkorDB
[FalkorDB](https://falkordb.com/) is a low-latency property graph database that leverages sparse matrices and linear algebra for high-performance graph queries. It is a community-driven fork of RedisGraph, optimized for large-scale knowledge graphs and AI-powered applications.
## Getting Started
1. Copy `.env.example` to `.env` and adjust the configuration as needed.
2. Start the service:
```bash
docker compose up -d
```
3. Access the FalkorDB Browser at `http://localhost:3000`.
4. Connect to the database using `redis-cli` or any Redis-compatible client on port `6379`.
## Environment Variables
| Variable | Description | Default |
| -------------------------------- | ---------------------------- | ---------- |
| `FALKORDB_VERSION` | Version of FalkorDB image | `v4.14.11` |
| `FALKORDB_PORT_OVERRIDE` | Host port for Redis protocol | `6379` |
| `FALKORDB_BROWSER_PORT_OVERRIDE` | Host port for Browser UI | `3000` |
| `FALKORDB_CPU_LIMIT` | Maximum CPU cycles | `1.00` |
| `FALKORDB_MEMORY_LIMIT` | Maximum memory | `2G` |
## Resources
- [Official Documentation](https://docs.falkordb.com/)
- [GitHub Repository](https://github.com/FalkorDB/FalkorDB)
- [Docker Hub](https://hub.docker.com/r/falkordb/falkordb)

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# FalkorDB
[FalkorDB](https://falkordb.com/) 是一个低延迟的属性图数据库,利用稀疏矩阵和线性代数实现高性能图查询。它是 RedisGraph 的社区驱动分支,针对大规模知识图谱和 AI 驱动的应用进行了优化。
## 快速开始
1.`.env.example` 复制为 `.env` 并根据需要调整配置。
2. 启动服务:
```bash
docker compose up -d
```
3. 通过 `http://localhost:3000` 访问 FalkorDB Browser 界面。
4. 使用 `redis-cli` 或任何兼容 Redis 的客户端连接到 `6379` 端口。
## 环境变量
| 变量名 | 描述 | 默认值 |
| -------------------------------- | -------------------- | ---------- |
| `FALKORDB_VERSION` | FalkorDB 镜像版本 | `v4.14.11` |
| `FALKORDB_PORT_OVERRIDE` | Redis 协议的主机端口 | `6379` |
| `FALKORDB_BROWSER_PORT_OVERRIDE` | 浏览器界面的主机端口 | `3000` |
| `FALKORDB_CPU_LIMIT` | 最大 CPU 使用率 | `1.00` |
| `FALKORDB_MEMORY_LIMIT` | 最大内存限制 | `2G` |
## 相关资源
- [官方文档](https://docs.falkordb.com/)
- [GitHub 仓库](https://github.com/FalkorDB/FalkorDB)
- [Docker Hub](https://hub.docker.com/r/falkordb/falkordb)

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x-defaults: &defaults
restart: unless-stopped
logging:
driver: json-file
options:
max-size: 100m
max-file: "3"
services:
falkordb:
<<: *defaults
image: ${GLOBAL_REGISTRY:-}falkordb/falkordb:${FALKORDB_VERSION:-v4.14.11}
ports:
- "${FALKORDB_PORT_OVERRIDE:-6379}:6379"
- "${FALKORDB_BROWSER_PORT_OVERRIDE:-3000}:3000"
volumes:
- falkordb_data:/data
environment:
- TZ=${TZ:-UTC}
healthcheck:
test: ["CMD", "redis-cli", "ping"]
interval: 30s
timeout: 10s
retries: 3
start_period: 10s
deploy:
resources:
limits:
cpus: ${FALKORDB_CPU_LIMIT:-1.00}
memory: ${FALKORDB_MEMORY_LIMIT:-2G}
reservations:
cpus: ${FALKORDB_CPU_RESERVATION:-0.25}
memory: ${FALKORDB_MEMORY_RESERVATION:-512M}
volumes:
falkordb_data: