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feat: add more Agent services & easytier

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Summer Shen
2026-04-19 12:26:54 +08:00
parent 0e948befac
commit 0b5ba69cb0
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apps/librechat/.env.example
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# Global Registry Prefix (optional)
# GLOBAL_REGISTRY=
# Service Versions
LIBRECHAT_VERSION=v0.8.4
MONGODB_VERSION=8.0
MEILISEARCH_VERSION=v1.12.8
# Timezone
TZ=UTC
# Host port for the LibreChat web UI
LIBRECHAT_PORT_OVERRIDE=3080
# Security Secrets (CHANGEME: generate with: openssl rand -hex 32)
JWT_SECRET=changeme_jwt_secret_please_change_CHANGEME
JWT_REFRESH_SECRET=changeme_jwt_refresh_secret_CHANGEME
MEILI_MASTER_KEY=changeme_meili_master_key_CHANGEME
# Encryption Keys
# CREDS_KEY must be exactly 32 characters
CREDS_KEY=changeme_creds_key_32_chars_only
# CREDS_IV must be exactly 16 characters
CREDS_IV=changeme_iv_16ch
# Registration
ALLOW_REGISTRATION=true
ALLOW_SOCIAL_LOGIN=false
# LLM Provider API Keys (optional; configure via UI or here)
# OPENAI_API_KEY=sk-...
# ANTHROPIC_API_KEY=sk-ant-...
# Resource Limits - LibreChat
LIBRECHAT_CPU_LIMIT=2
LIBRECHAT_MEMORY_LIMIT=2G
LIBRECHAT_CPU_RESERVATION=0.5
LIBRECHAT_MEMORY_RESERVATION=512M
# Resource Limits - MongoDB
MONGODB_CPU_LIMIT=1
MONGODB_MEMORY_LIMIT=1G
MONGODB_CPU_RESERVATION=0.25
MONGODB_MEMORY_RESERVATION=256M
# Resource Limits - Meilisearch
MEILISEARCH_CPU_LIMIT=0.5
MEILISEARCH_MEMORY_LIMIT=512M
MEILISEARCH_CPU_RESERVATION=0.1
MEILISEARCH_MEMORY_RESERVATION=128M
apps/librechat/README.md
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# LibreChat
[English](./README.md) | [中文](./README.zh.md)
Quick start: <https://docs.librechat.ai>.
This service deploys LibreChat, an open-source AI chat platform that supports OpenAI, Anthropic, Google, Ollama, and many other providers in a single unified interface with conversation history, file uploads, code execution, and multi-user support.
## Services
- **librechat**: The LibreChat web application (Node.js).
- **mongodb**: MongoDB database for conversation and user data.
- **meilisearch**: Full-text search engine for message indexing.
## Quick Start
1. Copy `.env.example` to `.env`:
```bash
cp .env.example .env
```
2. Update the secrets in `.env` (generate with `openssl rand -hex 32`):
```
JWT_SECRET, JWT_REFRESH_SECRET, MEILI_MASTER_KEY, CREDS_KEY, CREDS_IV
```
3. Start the services:
```bash
docker compose up -d
```
4. Open `http://localhost:3080` and register the first user account.
## Core Environment Variables
| Variable | Description | Default |
| --------------------- | -------------------------------------------------------- | ---------------------------- |
| `LIBRECHAT_VERSION` | Image version | `v0.8.4` |
| `LIBRECHAT_PORT_OVERRIDE` | Host port for the web UI | `3080` |
| `JWT_SECRET` | JWT signing secret (min 32 chars) — **CHANGEME** | placeholder |
| `JWT_REFRESH_SECRET` | JWT refresh signing secret — **CHANGEME** | placeholder |
| `MEILI_MASTER_KEY` | Meilisearch master key — **CHANGEME** | placeholder |
| `CREDS_KEY` | Encryption key for stored credentials (exactly 32 chars) | placeholder |
| `CREDS_IV` | Encryption IV (exactly 16 chars) | placeholder |
| `ALLOW_REGISTRATION` | Allow new user registration | `true` |
| `OPENAI_API_KEY` | OpenAI API key (optional; can also configure in UI) | *(empty)* |
| `ANTHROPIC_API_KEY` | Anthropic API key (optional) | *(empty)* |
## Volumes
- `librechat_images`: User-uploaded images served by the web UI.
- `librechat_logs`: Application log files.
- `librechat_mongo_data`: MongoDB data persistence.
- `librechat_meilisearch_data`: Meilisearch index data.
## Ports
- **3080**: LibreChat web UI
## Security Notes
- Generate all secrets before any external exposure: `openssl rand -hex 32`
- `CREDS_KEY` and `CREDS_IV` encrypt stored API keys — losing them makes stored credentials unrecoverable.
- Set `ALLOW_REGISTRATION=false` after creating admin accounts to lock down signups.
## Resource Requirements
| Service | CPU Limit | Memory Limit |
| ------------ | --------- | ------------ |
| librechat | 2 | 2 GB |
| mongodb | 1 | 1 GB |
| meilisearch | 0.5 | 512 MB |
Total recommended: **4+ GB RAM**.
## Documentation
- [LibreChat Docs](https://docs.librechat.ai)
- [GitHub](https://github.com/danny-avila/LibreChat)
apps/librechat/README.zh.md
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# LibreChat
[English](./README.md) | [中文](./README.zh.md)
快速开始：<https://docs.librechat.ai>。
此服务用于部署 LibreChat，一个开源 AI 对话平台，在单一统一界面中支持 OpenAI、Anthropic、Google、Ollama 等众多提供商，具备对话历史、文件上传、代码执行和多用户支持。
## 服务
- **librechat**：LibreChat Web 应用（Node.js）。
- **mongodb**：用于存储对话和用户数据的 MongoDB 数据库。
- **meilisearch**：用于消息索引的全文搜索引擎。
## 快速开始
1. 将 `.env.example` 复制为 `.env`：
```bash
cp .env.example .env
```
2. 更新 `.env` 中的密钥（使用 `openssl rand -hex 32` 生成）：
```
JWT_SECRET、JWT_REFRESH_SECRET、MEILI_MASTER_KEY、CREDS_KEY、CREDS_IV
```
3. 启动服务：
```bash
docker compose up -d
```
4. 打开 `http://localhost:3080`，注册第一个用户账号。
## 核心环境变量
| 变量 | 说明 | 默认值 |
| ------------------------ | ------------------------------------------------------- | -------- |
| `LIBRECHAT_VERSION` | 镜像版本 | `v0.8.4` |
| `LIBRECHAT_PORT_OVERRIDE`| Web UI 宿主机端口 | `3080` |
| `JWT_SECRET` | JWT 签名密钥（至少 32 字符）——**请修改** | 占位符 |
| `JWT_REFRESH_SECRET` | JWT 刷新签名密钥——**请修改** | 占位符 |
| `MEILI_MASTER_KEY` | Meilisearch 主密钥——**请修改** | 占位符 |
| `CREDS_KEY` | 存储凭证的加密密钥（恰好 32 字符） | 占位符 |
| `CREDS_IV` | 加密 IV（恰好 16 字符） | 占位符 |
| `ALLOW_REGISTRATION` | 允许新用户注册 | `true` |
| `OPENAI_API_KEY` | OpenAI API Key（可选；也可在 UI 中配置） | *(空)* |
| `ANTHROPIC_API_KEY` | Anthropic API Key（可选） | *(空)* |
## 数据卷
- `librechat_images`：用户上传的图片，由 Web UI 提供服务。
- `librechat_logs`：应用日志文件。
- `librechat_mongo_data`：MongoDB 数据持久化。
- `librechat_meilisearch_data`：Meilisearch 索引数据。
## 端口
- **3080**：LibreChat Web UI
## 安全说明
- 在对外暴露之前，请生成所有密钥：`openssl rand -hex 32`。
- `CREDS_KEY` 和 `CREDS_IV` 用于加密存储的 API Key——丢失后存储的凭证将无法恢复。
- 创建管理员账号后，将 `ALLOW_REGISTRATION` 设为 `false` 以禁止新用户注册。
## 资源需求
| 服务 | CPU 限制 | 内存限制 |
| ----------- | -------- | -------- |
| librechat | 2 | 2 GB |
| mongodb | 1 | 1 GB |
| meilisearch | 0.5 | 512 MB |
推荐总计：**4+ GB RAM**。
## 文档
- [LibreChat 文档](https://docs.librechat.ai)
- [GitHub](https://github.com/danny-avila/LibreChat)
apps/librechat/docker-compose.yaml
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# Make sure to change the secret placeholders before exposing this stack externally.
# Fields marked with CHANGEME must be updated for any non-local deployment.
x-defaults: &defaults
restart: unless-stopped
logging:
driver: json-file
options:
max-size: 100m
max-file: '3'
services:
librechat:
<<: *defaults
image: ${GLOBAL_REGISTRY:-}librechat/librechat:${LIBRECHAT_VERSION:-v0.8.4}
depends_on:
mongodb:
condition: service_healthy
meilisearch:
condition: service_healthy
ports:
- '${LIBRECHAT_PORT_OVERRIDE:-3080}:3080'
volumes:
- librechat_images:/app/client/public/images
- librechat_logs:/app/api/logs
environment:
- TZ=${TZ:-UTC}
- MONGO_URI=mongodb://mongodb:27017/LibreChat
- MEILI_HOST=http://meilisearch:7700
- MEILI_MASTER_KEY=${MEILI_MASTER_KEY:-changeme_meili_master_key_CHANGEME}
- JWT_SECRET=${JWT_SECRET:-changeme_jwt_secret_please_change_CHANGEME}
- JWT_REFRESH_SECRET=${JWT_REFRESH_SECRET:-changeme_jwt_refresh_secret_CHANGEME}
- CREDS_KEY=${CREDS_KEY:-changeme_creds_key_32_chars_only}
- CREDS_IV=${CREDS_IV:-changeme_iv_16ch}
- ALLOW_REGISTRATION=${ALLOW_REGISTRATION:-true}
- ALLOW_SOCIAL_LOGIN=${ALLOW_SOCIAL_LOGIN:-false}
- OPENAI_API_KEY=${OPENAI_API_KEY:-}
- ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY:-}
healthcheck:
test:
- CMD
- node
- -e
- "require('http').get('http://localhost:3080/health',res=>process.exit(res.statusCode===200?0:1)).on('error',()=>process.exit(1))"
interval: 30s
timeout: 10s
retries: 5
start_period: 40s
deploy:
resources:
limits:
cpus: ${LIBRECHAT_CPU_LIMIT:-2}
memory: ${LIBRECHAT_MEMORY_LIMIT:-2G}
reservations:
cpus: ${LIBRECHAT_CPU_RESERVATION:-0.5}
memory: ${LIBRECHAT_MEMORY_RESERVATION:-512M}
mongodb:
<<: *defaults
image: ${GLOBAL_REGISTRY:-}mongo:${MONGODB_VERSION:-8.0}
volumes:
- librechat_mongo_data:/data/db
environment:
- TZ=${TZ:-UTC}
healthcheck:
test: [CMD, mongosh, --eval, "db.adminCommand('ping')"]
interval: 10s
timeout: 10s
retries: 5
start_period: 20s
deploy:
resources:
limits:
cpus: ${MONGODB_CPU_LIMIT:-1}
memory: ${MONGODB_MEMORY_LIMIT:-1G}
reservations:
cpus: ${MONGODB_CPU_RESERVATION:-0.25}
memory: ${MONGODB_MEMORY_RESERVATION:-256M}
meilisearch:
<<: *defaults
image: ${GLOBAL_REGISTRY:-}getmeili/meilisearch:${MEILISEARCH_VERSION:-v1.12.8}
volumes:
- librechat_meilisearch_data:/meili_data
environment:
- TZ=${TZ:-UTC}
- MEILI_MASTER_KEY=${MEILI_MASTER_KEY:-changeme_meili_master_key_CHANGEME}
- MEILI_NO_ANALYTICS=true
healthcheck:
test: [CMD-SHELL, "curl -sf http://localhost:7700/health || exit 1"]
interval: 10s
timeout: 10s
retries: 5
start_period: 10s
deploy:
resources:
limits:
cpus: ${MEILISEARCH_CPU_LIMIT:-0.5}
memory: ${MEILISEARCH_MEMORY_LIMIT:-512M}
reservations:
cpus: ${MEILISEARCH_CPU_RESERVATION:-0.1}
memory: ${MEILISEARCH_MEMORY_RESERVATION:-128M}
volumes:
librechat_images:
librechat_logs:
librechat_mongo_data:
librechat_meilisearch_data:
apps/ragflow/.env.example
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# Global Registry Prefix (optional)
# GLOBAL_REGISTRY=
# Service Versions
RAGFLOW_VERSION=v0.24.0
ELASTICSEARCH_VERSION=8.11.3
MYSQL_VERSION=8.0.39
REDIS_VERSION=7
MINIO_VERSION=RELEASE.2025-01-20T14-49-07Z
# Timezone
TZ=UTC
# Host port for the RAGFlow web UI (Nginx reverse proxy)
RAGFLOW_PORT_OVERRIDE=80
# MinIO web console port
MINIO_CONSOLE_PORT_OVERRIDE=9001
# Secrets (CHANGEME: use strong random values in production)
SECRET_KEY=changeme_secret_key_CHANGEME
MYSQL_PASSWORD=ragflow
REDIS_PASSWORD=redispassword
MINIO_USER=minioadmin
MINIO_PASSWORD=minioadmin
# Resource Limits - RAGFlow
RAGFLOW_CPU_LIMIT=4
RAGFLOW_MEMORY_LIMIT=4G
RAGFLOW_CPU_RESERVATION=1
RAGFLOW_MEMORY_RESERVATION=2G
# Resource Limits - Elasticsearch
ELASTICSEARCH_CPU_LIMIT=2
ELASTICSEARCH_MEMORY_LIMIT=2G
ELASTICSEARCH_CPU_RESERVATION=0.5
ELASTICSEARCH_MEMORY_RESERVATION=1G
# Resource Limits - MySQL
MYSQL_CPU_LIMIT=1
MYSQL_MEMORY_LIMIT=1G
MYSQL_CPU_RESERVATION=0.25
MYSQL_MEMORY_RESERVATION=256M
# Resource Limits - Redis
REDIS_CPU_LIMIT=0.5
REDIS_MEMORY_LIMIT=512M
REDIS_CPU_RESERVATION=0.1
REDIS_MEMORY_RESERVATION=128M
# Resource Limits - MinIO
MINIO_CPU_LIMIT=1
MINIO_MEMORY_LIMIT=1G
MINIO_CPU_RESERVATION=0.25
MINIO_MEMORY_RESERVATION=256M
apps/ragflow/README.md
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# RAGFlow
[English](./README.md) | [中文](./README.zh.md)
Quick start: <https://ragflow.io/docs>.
This service deploys RAGFlow, an open-source Retrieval-Augmented Generation engine based on deep document understanding. It provides intelligent question answering over complex documents (PDFs, Word, PowerPoint, etc.) with accurate citation and citation tracing.
> **Platform note**: This stack is **x86-64 (amd64) only**. ARM64 is not supported by the official image.
>
> **Resource note**: Elasticsearch alone requires ~2 GB RAM. Provision at least **8 GB RAM** total before starting.
## Services
- **ragflow**: The RAGFlow web application and API server (Nginx on port 80, API on port 9380).
- **es01**: Elasticsearch single-node cluster for vector and full-text search.
- **mysql**: MySQL 8 database for metadata and workflow state.
- **redis**: Redis for task queues and caching.
- **minio**: S3-compatible object storage for document and chunk storage.
## Quick Start
1. Copy `.env.example` to `.env`:
```bash
cp .env.example .env
```
2. Update the secrets in `.env`:
```
SECRET_KEY, MYSQL_PASSWORD, REDIS_PASSWORD, MINIO_PASSWORD
```
3. Start the services (initial startup may take 2–5 minutes):
```bash
docker compose up -d
```
4. Open `http://localhost` and register the first admin account.
## Core Environment Variables
| Variable | Description | Default |
| ---------------------- | -------------------------------------------------------- | -------------------------------- |
| `RAGFLOW_VERSION` | RAGFlow image version | `v0.24.0` |
| `RAGFLOW_PORT_OVERRIDE`| Host port for the web UI | `80` |
| `SECRET_KEY` | Application secret key — **CHANGEME** | placeholder |
| `MYSQL_PASSWORD` | MySQL root password (also used by RAGFlow) | `ragflow` |
| `REDIS_PASSWORD` | Redis authentication password | `redispassword` |
| `MINIO_USER` | MinIO root user | `minioadmin` |
| `MINIO_PASSWORD` | MinIO root password | `minioadmin` |
| `MINIO_CONSOLE_PORT_OVERRIDE` | MinIO web console host port | `9001` |
## Volumes
- `ragflow_logs`: RAGFlow application logs.
- `ragflow_es_data`: Elasticsearch index data.
- `ragflow_mysql_data`: MySQL database files.
- `ragflow_redis_data`: Redis persistence.
- `ragflow_minio_data`: Object storage for documents and embeddings.
## Ports
- **80**: RAGFlow web UI and API (via Nginx)
- **9001**: MinIO web console
## Resource Requirements
| Service | CPU Limit | Memory Limit |
| ------------- | --------- | ------------ |
| ragflow | 4 | 4 GB |
| elasticsearch | 2 | 2 GB |
| mysql | 1 | 1 GB |
| redis | 0.5 | 512 MB |
| minio | 1 | 1 GB |
Total recommended: **8+ GB RAM**, **4+ CPU cores**.
## Documentation
- [RAGFlow Docs](https://ragflow.io/docs)
- [GitHub](https://github.com/infiniflow/ragflow)
apps/ragflow/README.zh.md
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# RAGFlow
[English](./README.md) | [中文](./README.zh.md)
快速开始：<https://ragflow.io/docs>。
此服务用于部署 RAGFlow，一个基于深度文档理解的开源检索增强生成引擎。它能对复杂文档（PDF、Word、PowerPoint 等）进行智能问答，并提供精准的引用和引文追踪。
> **平台说明**：此 Stack 仅支持 **x86-64（amd64）**，官方镜像不支持 ARM64。
>
> **资源说明**：仅 Elasticsearch 就需要约 2 GB RAM，启动前请确保系统至少有 **8 GB RAM**。
## 服务
- **ragflow**：RAGFlow Web 应用和 API 服务器（Nginx 监听 80 端口，API 监听 9380 端口）。
- **es01**：单节点 Elasticsearch 集群，用于向量和全文检索。
- **mysql**：MySQL 8 数据库，用于元数据和工作流状态存储。
- **redis**：Redis，用于任务队列和缓存。
- **minio**：S3 兼容对象存储，用于文档和分块存储。
## 快速开始
1. 将 `.env.example` 复制为 `.env`：
```bash
cp .env.example .env
```
2. 更新 `.env` 中的密钥：
```
SECRET_KEY、MYSQL_PASSWORD、REDIS_PASSWORD、MINIO_PASSWORD
```
3. 启动服务（首次启动可能需要 2～5 分钟）：
```bash
docker compose up -d
```
4. 打开 `http://localhost`，注册第一个管理员账号。
## 核心环境变量
| 变量 | 说明 | 默认值 |
| ----------------------------- | ------------------------------------------ | ------------- |
| `RAGFLOW_VERSION` | RAGFlow 镜像版本 | `v0.24.0` |
| `RAGFLOW_PORT_OVERRIDE` | Web UI 宿主机端口 | `80` |
| `SECRET_KEY` | 应用密钥——**请修改** | 占位符 |
| `MYSQL_PASSWORD` | MySQL root 密码（也供 RAGFlow 使用） | `ragflow` |
| `REDIS_PASSWORD` | Redis 认证密码 | `redispassword` |
| `MINIO_USER` | MinIO root 用户名 | `minioadmin` |
| `MINIO_PASSWORD` | MinIO root 密码 | `minioadmin` |
| `MINIO_CONSOLE_PORT_OVERRIDE` | MinIO Web 控制台宿主机端口 | `9001` |
## 数据卷
- `ragflow_logs`：RAGFlow 应用日志。
- `ragflow_es_data`：Elasticsearch 索引数据。
- `ragflow_mysql_data`：MySQL 数据库文件。
- `ragflow_redis_data`：Redis 持久化数据。
- `ragflow_minio_data`：文档和嵌入向量的对象存储。
## 端口
- **80**：RAGFlow Web UI 和 API（通过 Nginx）
- **9001**：MinIO Web 控制台
## 资源需求
| 服务 | CPU 限制 | 内存限制 |
| ------------- | -------- | -------- |
| ragflow | 4 | 4 GB |
| elasticsearch | 2 | 2 GB |
| mysql | 1 | 1 GB |
| redis | 0.5 | 512 MB |
| minio | 1 | 1 GB |
推荐总计：**8+ GB RAM**，**4+ CPU 核心**。
## 文档
- [RAGFlow 文档](https://ragflow.io/docs)
- [GitHub](https://github.com/infiniflow/ragflow)
apps/ragflow/docker-compose.yaml
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# RAGFlow requires substantial system resources.
# Elasticsearch alone needs ~2 GB RAM. Total recommended: 8+ GB RAM.
# This stack is x86-64 (amd64) only; ARM64 is not supported.
x-defaults: &defaults
restart: unless-stopped
logging:
driver: json-file
options:
max-size: 100m
max-file: '3'
services:
ragflow:
<<: *defaults
image: ${GLOBAL_REGISTRY:-}infiniflow/ragflow:${RAGFLOW_VERSION:-v0.24.0}
depends_on:
mysql:
condition: service_healthy
redis:
condition: service_healthy
minio:
condition: service_healthy
es01:
condition: service_healthy
ports:
- '${RAGFLOW_PORT_OVERRIDE:-80}:80'
volumes:
- ragflow_logs:/ragflow/logs
environment:
- TZ=${TZ:-UTC}
- MYSQL_PASSWORD=${MYSQL_PASSWORD:-ragflow}
- MINIO_USER=${MINIO_USER:-minioadmin}
- MINIO_PASSWORD=${MINIO_PASSWORD:-minioadmin}
- REDIS_PASSWORD=${REDIS_PASSWORD:-redispassword}
- SECRET_KEY=${SECRET_KEY:-changeme_secret_key_CHANGEME}
healthcheck:
test: [CMD-SHELL, "curl -sf http://localhost/ > /dev/null 2>&1 || exit 1"]
interval: 30s
timeout: 15s
retries: 10
start_period: 120s
deploy:
resources:
limits:
cpus: ${RAGFLOW_CPU_LIMIT:-4}
memory: ${RAGFLOW_MEMORY_LIMIT:-4G}
reservations:
cpus: ${RAGFLOW_CPU_RESERVATION:-1}
memory: ${RAGFLOW_MEMORY_RESERVATION:-2G}
es01:
<<: *defaults
image: ${GLOBAL_REGISTRY:-}elasticsearch:${ELASTICSEARCH_VERSION:-8.11.3}
environment:
- TZ=${TZ:-UTC}
- discovery.type=single-node
- xpack.security.enabled=false
- ES_JAVA_OPTS=-Xms512m -Xmx1g
volumes:
- ragflow_es_data:/usr/share/elasticsearch/data
healthcheck:
test: [CMD-SHELL, "curl -sf http://localhost:9200/_cluster/health | grep -qE '\"status\":\"(green|yellow)\"' || exit 1"]
interval: 15s
timeout: 10s
retries: 10
start_period: 60s
deploy:
resources:
limits:
cpus: ${ELASTICSEARCH_CPU_LIMIT:-2}
memory: ${ELASTICSEARCH_MEMORY_LIMIT:-2G}
reservations:
cpus: ${ELASTICSEARCH_CPU_RESERVATION:-0.5}
memory: ${ELASTICSEARCH_MEMORY_RESERVATION:-1G}
mysql:
<<: *defaults
image: ${GLOBAL_REGISTRY:-}mysql:${MYSQL_VERSION:-8.0.39}
environment:
- TZ=${TZ:-UTC}
- MYSQL_ROOT_PASSWORD=${MYSQL_PASSWORD:-ragflow}
- MYSQL_DATABASE=rag_flow
volumes:
- ragflow_mysql_data:/var/lib/mysql
healthcheck:
test: [CMD, mysqladmin, ping, -h, localhost]
interval: 10s
timeout: 10s
retries: 5
start_period: 30s
deploy:
resources:
limits:
cpus: ${MYSQL_CPU_LIMIT:-1}
memory: ${MYSQL_MEMORY_LIMIT:-1G}
reservations:
cpus: ${MYSQL_CPU_RESERVATION:-0.25}
memory: ${MYSQL_MEMORY_RESERVATION:-256M}
redis:
<<: *defaults
image: ${GLOBAL_REGISTRY:-}redis:${REDIS_VERSION:-7}
command: >
--requirepass ${REDIS_PASSWORD:-redispassword}
--maxmemory-policy noeviction
environment:
- REDIS_PASSWORD=${REDIS_PASSWORD:-redispassword}
volumes:
- ragflow_redis_data:/data
healthcheck:
test: [CMD-SHELL, "redis-cli -a $$REDIS_PASSWORD ping | grep -q PONG"]
interval: 5s
timeout: 10s
retries: 10
deploy:
resources:
limits:
cpus: ${REDIS_CPU_LIMIT:-0.5}
memory: ${REDIS_MEMORY_LIMIT:-512M}
reservations:
cpus: ${REDIS_CPU_RESERVATION:-0.1}
memory: ${REDIS_MEMORY_RESERVATION:-128M}
minio:
<<: *defaults
image: ${GLOBAL_REGISTRY:-}minio/minio:${MINIO_VERSION:-RELEASE.2025-01-20T14-49-07Z}
command: server /data --console-address ':9001'
environment:
- TZ=${TZ:-UTC}
- MINIO_ROOT_USER=${MINIO_USER:-minioadmin}
- MINIO_ROOT_PASSWORD=${MINIO_PASSWORD:-minioadmin}
volumes:
- ragflow_minio_data:/data
ports:
- '${MINIO_CONSOLE_PORT_OVERRIDE:-9001}:9001'
healthcheck:
test: [CMD-SHELL, "curl -sf http://localhost:9000/minio/health/live || exit 1"]
interval: 10s
timeout: 5s
retries: 10
start_period: 10s
deploy:
resources:
limits:
cpus: ${MINIO_CPU_LIMIT:-1}
memory: ${MINIO_MEMORY_LIMIT:-1G}
reservations:
cpus: ${MINIO_CPU_RESERVATION:-0.25}
memory: ${MINIO_MEMORY_RESERVATION:-256M}
volumes:
ragflow_logs:
ragflow_es_data:
ragflow_mysql_data:
ragflow_redis_data:
ragflow_minio_data:
apps/skyvern/.env.example
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# Global Registry Prefix (optional)
# GLOBAL_REGISTRY=
# Service Versions
SKYVERN_VERSION=v1.0.31
POSTGRES_VERSION=15
# Timezone
TZ=UTC
# Host ports
SKYVERN_PORT_OVERRIDE=8000
SKYVERN_UI_PORT_OVERRIDE=8080
# Skyvern API Key (CHANGEME: set a strong random key for the REST API)
SKYVERN_API_KEY=changeme_skyvern_api_key_CHANGEME
# Browser type: chromium-headless (default), chromium, or chrome
BROWSER_TYPE=chromium-headless
# LLM Provider API Keys (at least one is required for task automation)
# OPENAI_API_KEY=sk-...
# ANTHROPIC_API_KEY=sk-ant-...
# PostgreSQL password
POSTGRES_PASSWORD=skyvern
# UI → API connection (must be the address reachable from the user's browser)
VITE_API_BASE_URL=http://localhost:8000
VITE_WSS_BASE_URL=ws://localhost:8000
# Resource Limits - Skyvern backend (includes Playwright + Chromium)
SKYVERN_CPU_LIMIT=2
SKYVERN_MEMORY_LIMIT=4G
SKYVERN_CPU_RESERVATION=0.5
SKYVERN_MEMORY_RESERVATION=1G
# Resource Limits - Skyvern UI
SKYVERN_UI_CPU_LIMIT=0.5
SKYVERN_UI_MEMORY_LIMIT=256M
SKYVERN_UI_CPU_RESERVATION=0.1
SKYVERN_UI_MEMORY_RESERVATION=64M
# Resource Limits - PostgreSQL
POSTGRES_CPU_LIMIT=1
POSTGRES_MEMORY_LIMIT=1G
POSTGRES_CPU_RESERVATION=0.25
POSTGRES_MEMORY_RESERVATION=256M
apps/skyvern/README.md
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# Skyvern
[English](./README.md) | [中文](./README.zh.md)
Quick start: <https://docs.skyvern.com>.
This service deploys Skyvern, an AI-powered browser automation platform that uses LLMs and computer vision to execute tasks in web browsers. It can fill forms, navigate websites, and complete multi-step workflows without custom scripts.
## Services
- **skyvern**: The Skyvern API server with embedded Playwright + Chromium.
- **skyvern-ui**: React-based web UI for task management and browser session viewing.
- **postgres**: PostgreSQL database for task history and state.
## Quick Start
1. Copy `.env.example` to `.env`:
```bash
cp .env.example .env
```
2. Set your LLM API key and change the Skyvern API key in `.env`:
```
SKYVERN_API_KEY=your-strong-api-key
OPENAI_API_KEY=sk-...
```
3. Start the services:
```bash
docker compose up -d
```
4. Open `http://localhost:8080` for the web UI, or send tasks to the API at `http://localhost:8000`.
## Core Environment Variables
| Variable | Description | Default |
| ----------------------- | -------------------------------------------------------------------- | -------------------- |
| `SKYVERN_VERSION` | Image version (applies to both skyvern and skyvern-ui) | `v1.0.31` |
| `SKYVERN_PORT_OVERRIDE` | Host port for the API | `8000` |
| `SKYVERN_UI_PORT_OVERRIDE` | Host port for the web UI | `8080` |
| `SKYVERN_API_KEY` | API key for authenticating requests to the Skyvern server — **CHANGEME** | placeholder |
| `BROWSER_TYPE` | Browser type: `chromium-headless`, `chromium`, or `chrome` | `chromium-headless` |
| `OPENAI_API_KEY` | OpenAI API key (recommended for best results) | *(empty)* |
| `ANTHROPIC_API_KEY` | Anthropic API key (alternative to OpenAI) | *(empty)* |
| `POSTGRES_PASSWORD` | PostgreSQL password | `skyvern` |
| `VITE_API_BASE_URL` | Skyvern API URL as seen from the user's browser | `http://localhost:8000` |
| `VITE_WSS_BASE_URL` | WebSocket URL for live session streaming | `ws://localhost:8000` |
## Volumes
- `skyvern_artifacts`: Downloaded files and task artifacts.
- `skyvern_videos`: Browser session recordings.
- `skyvern_har`: HTTP Archive (HAR) files for debugging.
- `skyvern_postgres_data`: PostgreSQL data persistence.
## Ports
- **8000**: Skyvern REST API
- **8080**: Skyvern web UI
## Resource Requirements
| Service | CPU Limit | Memory Limit |
| ---------- | --------- | ------------ |
| skyvern | 2 | 4 GB |
| skyvern-ui | 0.5 | 256 MB |
| postgres | 1 | 1 GB |
The `skyvern` service includes Playwright and Chromium. Allocate **4+ GB RAM** and **2+ CPU cores** for reliable browser automation.
## Notes
- Database migrations run automatically on startup via Alembic.
- If deploying behind a reverse proxy, update `VITE_API_BASE_URL` and `VITE_WSS_BASE_URL` to your public domain.
- The `SKYVERN_API_KEY` must be included in API requests as the `x-api-key` header.
## Documentation
- [Skyvern Docs](https://docs.skyvern.com)
- [GitHub](https://github.com/Skyvern-AI/skyvern)
apps/skyvern/README.zh.md
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# Skyvern
[English](./README.md) | [中文](./README.zh.md)
快速开始：<https://docs.skyvern.com>。
此服务用于部署 Skyvern，一个由 AI 驱动的浏览器自动化平台，使用 LLM 和计算机视觉在 Web 浏览器中执行任务。无需编写自定义脚本，即可填写表单、导航网站和完成多步骤工作流。
## 服务
- **skyvern**：集成了 Playwright + Chromium 的 Skyvern API 服务器。
- **skyvern-ui**：用于任务管理和浏览器会话查看的 React Web UI。
- **postgres**：PostgreSQL 数据库，用于存储任务历史和状态。
## 快速开始
1. 将 `.env.example` 复制为 `.env`：
```bash
cp .env.example .env
```
2. 在 `.env` 中设置 LLM API Key 并更改 Skyvern API Key：
```
SKYVERN_API_KEY=your-strong-api-key
OPENAI_API_KEY=sk-...
```
3. 启动服务：
```bash
docker compose up -d
```
4. 打开 `http://localhost:8080` 访问 Web UI，或通过 `http://localhost:8000` 向 API 发送任务。
## 核心环境变量
| 变量 | 说明 | 默认值 |
| -------------------------- | ------------------------------------------------------- | ------------------------ |
| `SKYVERN_VERSION` | 镜像版本（同时适用于 skyvern 和 skyvern-ui） | `v1.0.31` |
| `SKYVERN_PORT_OVERRIDE` | API 宿主机端口 | `8000` |
| `SKYVERN_UI_PORT_OVERRIDE` | Web UI 宿主机端口 | `8080` |
| `SKYVERN_API_KEY` | 请求 Skyvern 服务器的认证 API Key——**请修改** | 占位符 |
| `BROWSER_TYPE` | 浏览器类型：`chromium-headless`、`chromium` 或 `chrome` | `chromium-headless` |
| `OPENAI_API_KEY` | OpenAI API Key（推荐，效果最佳） | *(空)* |
| `ANTHROPIC_API_KEY` | Anthropic API Key（OpenAI 的替代方案） | *(空)* |
| `POSTGRES_PASSWORD` | PostgreSQL 密码 | `skyvern` |
| `VITE_API_BASE_URL` | 从用户浏览器访问的 Skyvern API URL | `http://localhost:8000` |
| `VITE_WSS_BASE_URL` | 实时会话流的 WebSocket URL | `ws://localhost:8000` |
## 数据卷
- `skyvern_artifacts`：下载的文件和任务产物。
- `skyvern_videos`：浏览器会话录像。
- `skyvern_har`：用于调试的 HTTP 存档（HAR）文件。
- `skyvern_postgres_data`：PostgreSQL 数据持久化。
## 端口
- **8000**：Skyvern REST API
- **8080**：Skyvern Web UI
## 资源需求
| 服务 | CPU 限制 | 内存限制 |
| ---------- | -------- | -------- |
| skyvern | 2 | 4 GB |
| skyvern-ui | 0.5 | 256 MB |
| postgres | 1 | 1 GB |
`skyvern` 服务包含 Playwright 和 Chromium，需分配 **4+ GB RAM** 和 **2+ CPU 核心**以保证浏览器自动化的稳定运行。
## 说明
- 数据库迁移通过 Alembic 在启动时自动运行。
- 如果部署在反向代理后，请将 `VITE_API_BASE_URL` 和 `VITE_WSS_BASE_URL` 更新为你的公网域名。
- API 请求中必须在 `x-api-key` 请求头中包含 `SKYVERN_API_KEY`。
## 文档
- [Skyvern 文档](https://docs.skyvern.com)
- [GitHub](https://github.com/Skyvern-AI/skyvern)
apps/skyvern/docker-compose.yaml
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# Change SKYVERN_API_KEY before exposing this stack externally.
# Fields marked with CHANGEME must be updated for any non-local deployment.
x-defaults: &defaults
restart: unless-stopped
logging:
driver: json-file
options:
max-size: 100m
max-file: '3'
services:
skyvern:
<<: *defaults
image: ${GLOBAL_REGISTRY:-}skyvern/skyvern:${SKYVERN_VERSION:-v1.0.31}
depends_on:
postgres:
condition: service_healthy
ports:
- '${SKYVERN_PORT_OVERRIDE:-8000}:8000'
volumes:
- skyvern_artifacts:/data/artifacts
- skyvern_videos:/data/videos
- skyvern_har:/data/har
environment:
- TZ=${TZ:-UTC}
- DATABASE_STRING=postgresql+psycopg2://skyvern:${POSTGRES_PASSWORD:-skyvern}@postgres:5432/skyvern
- SKYVERN_API_KEY=${SKYVERN_API_KEY:-changeme_skyvern_api_key_CHANGEME}
- BROWSER_TYPE=${BROWSER_TYPE:-chromium-headless}
- VIDEO_PATH=/data/videos
- HAR_PATH=/data/har
- ARTIFACT_STORAGE_PATH=/data/artifacts
- OPENAI_API_KEY=${OPENAI_API_KEY:-}
- ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY:-}
healthcheck:
test:
- CMD
- python3
- -c
- "import urllib.request; urllib.request.urlopen('http://localhost:8000/api/v1/heartbeat')"
interval: 30s
timeout: 10s
retries: 5
start_period: 30s
deploy:
resources:
limits:
cpus: ${SKYVERN_CPU_LIMIT:-2}
memory: ${SKYVERN_MEMORY_LIMIT:-4G}
reservations:
cpus: ${SKYVERN_CPU_RESERVATION:-0.5}
memory: ${SKYVERN_MEMORY_RESERVATION:-1G}
skyvern-ui:
<<: *defaults
image: ${GLOBAL_REGISTRY:-}skyvern/skyvern-ui:${SKYVERN_VERSION:-v1.0.31}
depends_on:
skyvern:
condition: service_healthy
ports:
- '${SKYVERN_UI_PORT_OVERRIDE:-8080}:8080'
environment:
- TZ=${TZ:-UTC}
- VITE_API_BASE_URL=${VITE_API_BASE_URL:-http://localhost:8000}
- VITE_WSS_BASE_URL=${VITE_WSS_BASE_URL:-ws://localhost:8000}
healthcheck:
test: [CMD-SHELL, "curl -sf http://localhost:8080/ > /dev/null 2>&1 || exit 1"]
interval: 30s
timeout: 10s
retries: 3
start_period: 15s
deploy:
resources:
limits:
cpus: ${SKYVERN_UI_CPU_LIMIT:-0.5}
memory: ${SKYVERN_UI_MEMORY_LIMIT:-256M}
reservations:
cpus: ${SKYVERN_UI_CPU_RESERVATION:-0.1}
memory: ${SKYVERN_UI_MEMORY_RESERVATION:-64M}
postgres:
<<: *defaults
image: ${GLOBAL_REGISTRY:-}postgres:${POSTGRES_VERSION:-15}
environment:
- POSTGRES_USER=skyvern
- POSTGRES_PASSWORD=${POSTGRES_PASSWORD:-skyvern}
- POSTGRES_DB=skyvern
- TZ=UTC
- PGTZ=UTC
volumes:
- skyvern_postgres_data:/var/lib/postgresql/data
healthcheck:
test: [CMD-SHELL, pg_isready -U skyvern]
interval: 5s
timeout: 5s
retries: 10
deploy:
resources:
limits:
cpus: ${POSTGRES_CPU_LIMIT:-1}
memory: ${POSTGRES_MEMORY_LIMIT:-1G}
reservations:
cpus: ${POSTGRES_CPU_RESERVATION:-0.25}
memory: ${POSTGRES_MEMORY_RESERVATION:-256M}
volumes:
skyvern_artifacts:
skyvern_videos:
skyvern_har:
skyvern_postgres_data: