feat: add FalkorDB, LMDeploy, and Pogocache with configuration files and documentation
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src/falkordb/.env.example
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src/falkordb/.env.example
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# FalkorDB Version
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# Latest stable version can be found at https://hub.docker.com/r/falkordb/falkordb/tags
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FALKORDB_VERSION=v4.14.11
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# Port configuration
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# Port for Redis protocol (Graph Database)
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FALKORDB_PORT_OVERRIDE=6379
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# Port for FalkorDB Browser UI
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FALKORDB_BROWSER_PORT_OVERRIDE=3000
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# Resource limits
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FALKORDB_CPU_LIMIT=1.00
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FALKORDB_MEMORY_LIMIT=2G
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FALKORDB_CPU_RESERVATION=0.25
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FALKORDB_MEMORY_RESERVATION=512M
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# Timezone
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TZ=UTC
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src/falkordb/README.md
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src/falkordb/README.md
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# FalkorDB
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[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.
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## Getting Started
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1. Copy `.env.example` to `.env` and adjust the configuration as needed.
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2. Start the service:
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```bash
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docker compose up -d
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```
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3. Access the FalkorDB Browser at `http://localhost:3000`.
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4. Connect to the database using `redis-cli` or any Redis-compatible client on port `6379`.
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## Environment Variables
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| Variable | Description | Default |
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| -------------------------------- | ---------------------------- | ---------- |
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| `FALKORDB_VERSION` | Version of FalkorDB image | `v4.14.11` |
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| `FALKORDB_PORT_OVERRIDE` | Host port for Redis protocol | `6379` |
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| `FALKORDB_BROWSER_PORT_OVERRIDE` | Host port for Browser UI | `3000` |
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| `FALKORDB_CPU_LIMIT` | Maximum CPU cycles | `1.00` |
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| `FALKORDB_MEMORY_LIMIT` | Maximum memory | `2G` |
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## Resources
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- [Official Documentation](https://docs.falkordb.com/)
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- [GitHub Repository](https://github.com/FalkorDB/FalkorDB)
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- [Docker Hub](https://hub.docker.com/r/falkordb/falkordb)
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src/falkordb/README.zh.md
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src/falkordb/README.zh.md
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# FalkorDB
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[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。
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## 快速开始
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1. 将 `.env.example` 复制为 `.env` 并根据需要调整配置。
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2. 启动服务:
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```bash
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docker compose up -d
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```
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3. 通过 `http://localhost:3000` 访问 FalkorDB Browser 界面。
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4. 使用 `redis-cli` 或任何兼容 Redis 的客户端连接到 `6379` 端口。
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## 环境变量
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| 变量名 | 描述 | 默认值 |
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| -------------------------------- | -------------------- | ---------- |
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| `FALKORDB_VERSION` | FalkorDB 镜像版本 | `v4.14.11` |
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| `FALKORDB_PORT_OVERRIDE` | Redis 协议的主机端口 | `6379` |
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| `FALKORDB_BROWSER_PORT_OVERRIDE` | 浏览器界面的主机端口 | `3000` |
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| `FALKORDB_CPU_LIMIT` | 最大 CPU 使用率 | `1.00` |
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| `FALKORDB_MEMORY_LIMIT` | 最大内存限制 | `2G` |
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## 相关资源
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- [官方文档](https://docs.falkordb.com/)
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- [GitHub 仓库](https://github.com/FalkorDB/FalkorDB)
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- [Docker Hub](https://hub.docker.com/r/falkordb/falkordb)
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36
src/falkordb/docker-compose.yaml
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src/falkordb/docker-compose.yaml
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x-defaults: &defaults
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restart: unless-stopped
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logging:
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driver: json-file
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options:
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max-size: 100m
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max-file: "3"
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services:
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falkordb:
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<<: *defaults
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image: ${GLOBAL_REGISTRY:-}falkordb/falkordb:${FALKORDB_VERSION:-v4.14.11}
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ports:
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- "${FALKORDB_PORT_OVERRIDE:-6379}:6379"
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- "${FALKORDB_BROWSER_PORT_OVERRIDE:-3000}:3000"
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volumes:
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- falkordb_data:/data
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environment:
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- TZ=${TZ:-UTC}
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healthcheck:
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test: ["CMD", "redis-cli", "ping"]
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interval: 30s
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timeout: 10s
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retries: 3
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start_period: 10s
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deploy:
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resources:
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limits:
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cpus: ${FALKORDB_CPU_LIMIT:-1.00}
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memory: ${FALKORDB_MEMORY_LIMIT:-2G}
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reservations:
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cpus: ${FALKORDB_CPU_RESERVATION:-0.25}
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memory: ${FALKORDB_MEMORY_RESERVATION:-512M}
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volumes:
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falkordb_data:
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