feat: add more Agent services & easytier
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Summer Shen
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# Global Registry Prefix (optional)
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# GLOBAL_REGISTRY=
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# AnythingLLM Image Version
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# No stable semantic version tags exist; 'latest' tracks the current release.
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ANYTHINGLLM_VERSION=latest
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# Timezone
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TZ=UTC
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# Host port for the AnythingLLM web UI
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ANYTHINGLLM_PORT_OVERRIDE=3001
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# UID/GID for file ownership inside the container
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ANYTHINGLLM_UID=1000
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ANYTHINGLLM_GID=1000
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# Resource Limits
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ANYTHINGLLM_CPU_LIMIT=2
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ANYTHINGLLM_MEMORY_LIMIT=2G
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ANYTHINGLLM_CPU_RESERVATION=0.5
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ANYTHINGLLM_MEMORY_RESERVATION=512M
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# AnythingLLM
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[English](./README.md) | [中文](./README.zh.md)
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Quick start: <https://docs.anythingllm.com>.
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This service deploys AnythingLLM, an all-in-one AI application that lets you chat with documents, use multiple LLM providers, and build custom AI agents — with a full RAG pipeline built in.
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## Services
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- `anythingllm`: The AnythingLLM web application.
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## Quick Start
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```bash
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docker compose up -d
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```
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Open `http://localhost:3001` and complete the setup wizard to connect your LLM provider.
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## Configuration
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All LLM providers, vector databases, and agent settings are configured through the web UI after startup. No API keys are required in `.env` unless you want to pre-seed them via environment variables.
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| Variable | Description | Default |
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| ----------------------------- | ----------------------------------------------- | -------- |
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| `ANYTHINGLLM_VERSION` | Image version (`latest` — no stable tags exist) | `latest` |
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| `TZ` | Container timezone | `UTC` |
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| `ANYTHINGLLM_PORT_OVERRIDE` | Host port for the web UI | `3001` |
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| `ANYTHINGLLM_UID` | UID for volume file ownership | `1000` |
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| `ANYTHINGLLM_GID` | GID for volume file ownership | `1000` |
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| `ANYTHINGLLM_CPU_LIMIT` | CPU limit | `2` |
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| `ANYTHINGLLM_MEMORY_LIMIT` | Memory limit | `2G` |
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| `ANYTHINGLLM_CPU_RESERVATION` | CPU reservation | `0.5` |
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| `ANYTHINGLLM_MEMORY_LIMIT` | Memory reservation | `512M` |
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## Volumes
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- `anythingllm_storage`: Persists all application data, uploaded documents, embeddings, and settings.
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## Ports
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- **3001**: Web UI
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## Notes
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- The `mintplexlabs/anythingllm` image does not publish stable semantic version tags; `latest` is the only reliable tag.
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- Supports OpenAI, Anthropic, Ollama, LM Studio, and many other LLM backends — all configured from the UI.
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- The health check uses the `/api/ping` endpoint.
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# AnythingLLM
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[English](./README.md) | [中文](./README.zh.md)
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快速开始：<https://docs.anythingllm.com>。
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此服务用于部署 AnythingLLM，一款集文档问答、多 LLM 提供商接入和自定义 AI Agent 于一体的全能 AI 应用，内置完整的 RAG 流水线。
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## 服务
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- `anythingllm`：AnythingLLM Web 应用。
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## 快速开始
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```bash
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docker compose up -d
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```
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打开 `http://localhost:3001`，按照设置向导连接你的 LLM 提供商。
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## 配置
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所有 LLM 提供商、向量数据库和 Agent 设置均通过启动后的 Web UI 进行配置，无需在 `.env` 中预设 API Key（除非你希望通过环境变量预填充）。
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| 变量 | 说明 | 默认值 |
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| ----------------------------- | ----------------------------------- | -------- |
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| `ANYTHINGLLM_VERSION` | 镜像版本（无语义化稳定标签，使用 `latest`） | `latest` |
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| `TZ` | 容器时区 | `UTC` |
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| `ANYTHINGLLM_PORT_OVERRIDE` | Web UI 的宿主机端口 | `3001` |
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| `ANYTHINGLLM_UID` | 数据卷文件所有者 UID | `1000` |
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| `ANYTHINGLLM_GID` | 数据卷文件所有者 GID | `1000` |
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| `ANYTHINGLLM_CPU_LIMIT` | CPU 限制 | `2` |
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| `ANYTHINGLLM_MEMORY_LIMIT` | 内存限制 | `2G` |
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| `ANYTHINGLLM_CPU_RESERVATION` | CPU 预留 | `0.5` |
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| `ANYTHINGLLM_MEMORY_LIMIT` | 内存预留 | `512M` |
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## 数据卷
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- `anythingllm_storage`：持久化所有应用数据、上传的文档、嵌入向量和配置。
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## 端口
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- **3001**：Web UI
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## 说明
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- `mintplexlabs/anythingllm` 镜像未发布语义化稳定标签，`latest` 是唯一可靠的标签。
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- 支持 OpenAI、Anthropic、Ollama、LM Studio 等众多 LLM 后端，均可在 UI 中配置。
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- 健康检查使用 `/api/ping` 端点。
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@@ -0,0 +1,42 @@
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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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anythingllm:
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<<: *defaults
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image: ${GLOBAL_REGISTRY:-}mintplexlabs/anythingllm:${ANYTHINGLLM_VERSION:-latest}
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ports:
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- '${ANYTHINGLLM_PORT_OVERRIDE:-3001}:3001'
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volumes:
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- anythingllm_storage:/app/server/storage
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environment:
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- TZ=${TZ:-UTC}
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- STORAGE_DIR=/app/server/storage
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- UID=${ANYTHINGLLM_UID:-1000}
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- GID=${ANYTHINGLLM_GID:-1000}
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healthcheck:
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test:
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- CMD
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- node
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- -e
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- "require('http').get('http://localhost:3001/api/ping',res=>process.exit(res.statusCode===200?0:1)).on('error',()=>process.exit(1))"
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interval: 30s
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timeout: 10s
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retries: 5
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start_period: 30s
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deploy:
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resources:
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limits:
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cpus: ${ANYTHINGLLM_CPU_LIMIT:-2}
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memory: ${ANYTHINGLLM_MEMORY_LIMIT:-2G}
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reservations:
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cpus: ${ANYTHINGLLM_CPU_RESERVATION:-0.5}
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memory: ${ANYTHINGLLM_MEMORY_RESERVATION:-512M}
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volumes:
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anythingllm_storage:
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