登录

anything-llm

Mintplex-LabsMIT活跃维护

本地优先的 AI 智能体工作台，把文档、对话和工具整合成可私有部署的知识库与代理，数据留在自己机器上，不用租用云端智能服务。

Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience

v1.19.0发布于 2026-10-26 16:14 UTC68,146star +124 / 7 天7,692fork同步于 2026-11-10 17:18 UTC
本地AI智能体编排私有知识库多模态本地部署
对比 GitHub 官网agent-computeragent-harnessagent-orchestrationagentic-aiagentic-workflow

怎么上手

由 README 提炼，执行前请确认
原文 
yarn setup
yarn dev:server
硬件要求按 README 说明

内置本地 LLM 引擎可在 CPU 或 GPU 上运行，GPU 支持 NVIDIA（CUDA）、AMD 和 Intel（Vulkan）；README 未给出具体显存要求。

需要 CUDA
下载：源码 zip·GitHub Releases（安装包）本站不镜像安装包

项目说明

由 README 自动翻译提炼
没人工点评？写下你的经验

本地优先的一体化 AI 应用，把文档、Agent 和多用户聊天整合进一个可自托管的私有 ChatGPT

本地优先的 AI 智能体工作台，把文档、对话和工具整合成可私有部署的知识库与代理，数据留在自己机器上，不用租用云端智能服务。

核心能力

  • 内置本地 LLM 引擎，用 llama.cpp 在 CPU 或 GPU 上跑模型
  • 支持 PDF、TXT、DOCX 等文档摄入并带来源引用对话
  • 内置无代码 AI Agent 构建器与 MCP 兼容能力
  • 动态模型路由按自定义规则把对话分发给最合适的模型
  • 多用户实例与权限管理（仅 Docker 版本）

容易踩的坑

开发前必须填好 server/.env.development，否则无法正常运行；多用户、白标和嵌入聊天组件等能力仅 Docker 版本提供；本地跑模型需额外下载模型文件。

内容由模型根据 README 生成，可能不完整或不准确，以官方文档为准。看原文 README

最近发版

5 个版本v1.19.0
全部 release
  1. v1.19.0AnythingLLM v1.19.0最新正式版2026-10-26 · 2026-10-26 16:14 UTC

    Built-in LLM for Docker

    AnythingLLM Docker now has a default local LLM experience right out of the box. The same kind of built-in engine that ships with AnythingLLM Desktop can now run inside the container: Lemonade, the fully open-source local inference server from AMD, running your models with llama.cpp. You no longer need to run Ollama, LM Studio or any other inference server next to AnythingLLM.

    Pass your GPU into the container and the engine is accelerated on whatever hardware you have. It picks the fastest backend automatically: CUDA for NVIDIA GPUs, Vulkan for AMD and Intel GPUs, or the CPU. It runs on both amd64 and arm64 hosts.

    When it's turned on, Built-in becomes the default LLM provider during onboarding, with three models recommended for your hardware. You can download any model from the model table or pull any GGUF model from Hugging Face. It works everywhere a provider can be used: the system LLM, workspace and agent LLMs, the chat window model picker, and Model Router.

    [!TIP] The built-in LLM is off by default. Turn it on by starting the container with -e ENABLE_BUILT_IN_LLM=true, and add --gpus all (or pass in your AMD or Intel GPU devices) for GPU acceleration. See Built-in LLM for Docker for the full setup for each kind of hardware.

    Color palettes

    Color palettes are straightforward thematic tinting you can apply to the entire UI. We plan to expand this functionality more so you can more heavily customize the UI and even layout. Learn more

    What's Changed

  2. v1.18.0AnythingLLM v1.18.02026-10-13 · 2026-10-13 16:15 UTC
    查看更新说明

    What's Changed

  3. v1.17.0AnythingLLM v1.17.02026-10-01 · 2026-10-01 22:17 UTC
    查看更新说明

    What's Changed

  4. v1.16.2AnythingLLM v1.16.22026-09-22 · 2026-09-22 19:06 UTC
    查看更新说明

    New Features

    • LLMman - OSS is now available as a local LLM provider, replacing Docker Model Runner
    • Google Vertex AI is now available as an LLM provider
    • New generate-image agent skill for creating images from chat
    • You.com is now the default web search provider for richer web-searches with Zero Data Retention
    • Agent flow variables now support optional arguments
    • Hindi, Bulgarian, and Swedish language support added
    • GenieX on Windows on ARM now lists models found in your local model directory and lets you pull models directly from Hugging Face in the UI
    • Click the version tag in the top of the window to jump to your logs and storage directory more easily

    Improvements

    • Web browsing is now enabled by default for agents
    • Local providers now report model loading status in chat so you know why the first response is slow
    • Ollama runtime bumped to 0.33.3 with an updated bundled model list
    • Removed the borders around the main content area for a cleaner desktop layout
    • Redesigned the "new feature" modal layout
    • Dates in tables are now shown in a human-readable format
    • Scraped web pages now preserve tables, ordered lists, and code blocks instead of flattening them
    • PDF pages are now joined with newlines so words don't fuse across page boundaries
    • Mistral embeddings are now batched, making large document embedding significantly faster
    • Document search now matches your terms literally instead of as a regular expression
    • Watched documents now clear stale vectors on sync
    • AnySearch as a web-search provider
    • KoboldCPP provider overhauled and modernized to match the rest of our providers
    • Keenable added as a web search provider
    • OpenRouter service tier selection for controlling routing cost and priority
    • LocalAI image editing via reference images

    All Changes

  5. v1.16.1AnythingLLM v1.16.12026-08-27 · 2026-08-27 16:42 UTC
    查看更新说明

    Activity and Chain of Thought Overhaul

    We overhauled our UI for long-horizon agentic tasks that show multiple thinking and tool calls to now roll up into a single clean, collapsible UI element.

    This gives you more screen real estate for the actual response while still keeping the important call stack and thoughts the model produces in an easy-to-read format.

    Navigation Warning

    Recently, we added true abort signals across every supported LLM so that when you cancel inference or leave the page, we stop inference to save you on compute costs.

    However, this had the unintended side effect of canceling inference when navigating away from a chat, preventing background completion. Now we warn you before aborting the response.

    Roadmap item: We intend to make this user configurable so you can customize this behavior and allow background inference for those with more powerful or high-concurrency setups where multiple parallel inference sessions are feasible.

    Foundry Local Embedded (Desktop Only)

    FoundryLocal is an inference engine built by Microsoft that is pre-installed and available on Windows 11 (version 24H2, build 26100 or later).

    This uses WinML to load models for your CPU, GPU, or NPU across any Windows hardware configuration. It's a great option for hardware configurations we don't have explicit support for. Keep in mind that model availability may be limited as FoundryLocal is still rolling out. Vision models are not available currently.

    We partner with Microsoft for this, if you have bugs or issues we can help forward them to the FoundryLocal team

    GenieX for Snapdragon (Desktop Only)

    [!NOTE] This replaces our previous Snapdragon NPU engine. Any previous models from the old engine are deleted on update, and you'll need to re-download these optimized models. You should see a significant performance increase for NPU models and regular GGUFs.

    We highly recommend using only GGUF models for this engine. Qualcomm NPU-only models have 4K context windows and will result in a poor agent experience.

    GenieX is an open-source inference engine built by Qualcomm (previously NexaAI) that efficiently runs GGUFs and Qualcomm AI Hub models on NPU for X and X2 Elite devices.

    AnythingLLM offers fully managed and built-in support by selecting the "AnythingLLM GenieX" provider in the dropdown. Both GGUFs and NPU-only models can leverage the NPU, giving you the power efficiency and intelligence of both.

    We partner with Qualcomm for this, if you have bugs or issues we can help forward them to the GenieX team or you can make an issue on their GitHub. s/o @zhiyuan8, @alexchen4ai & @alanzhuly

    New Features

    • Native Foundry Local SDK on Windows (x64/ARM64) - the Foundry provider is now fully self-contained and no longer requires a separate Foundry Local install, with GPU/NPU-optimized model variants exposed in the catalog
    • GenieX runtime support for Windows ARM64 devices
    • AWS Bedrock cross-region inference profile support - geo-prefixed profile IDs (us., eu., global.) now appear in the model dropdown and route correctly, plus manual region entry for regions outside the preset list (GovCloud, specialized partitions)
    • LocalAI added as an image generation provider, listing only image-capable m

用户点评

登录用户的真实使用记录，可按版本和硬件筛选
共 0 条

    还没有人点评。第一个说出真实体验的人最有价值。

    README 原文

    未翻译
    在 GitHub 打开

    Chat with your docs. Automate complex workflows with AI Agents. Hyper-configurable, multi-user ready, battle-tested—and runs locally by default with zero setup friction.

    Chatting

    Watch the video

    Product Overview

    AnythingLLM is the all-in-one AI application that lets you build a private, fully-featured ChatGPT—without compromises. Connect your favorite local or cloud LLM, ingest your documents, and start chatting in minutes. Out of the box you get built-in agents, multi-user support, vector databases, and document pipelines — no extra configuration required.

    AnythingLLM supports multiple users as well where you can control the access and experience per user without compromising the security or privacy of the instance or your intellectual property.

    Cool Features of AnythingLLM

    Supported LLMs, Embedder Models, Speech models, and Vector Databases

    Large Language Models (LLMs):

    Embedder models:

    Audio Transcription models:

    TTS (text-to-speech) support:

    STT (speech-to-text) support:

    • Native Browser Built-in (default)

    Vector Databases:

    Technical Overview

    This monorepo consists of six main sections:

    • frontend: A viteJS + React frontend that you can run to easily create and manage all your content the LLM can use.
    • server: A NodeJS express server to handle all the interactions and do all the vectorDB management and LLM interactions.
    • collector: NodeJS express server that processes and parses documents from the UI.
    • docker: Docker instructions and build process + information for building from source.
    • embed: Submodule for generation & creation of the web embed widget.
    • browser-extension: Submodule for the chrome browser extension.

    🛳 Self-Hosting

    Mintplex Labs & the community maintain a number of deployment methods, scripts, and templates that you can use to run AnythingLLM locally. Refer to the table below to read how to deploy on your preferred environment or to automatically deploy.

    DockerAWSGCPDigital OceanRender.com
    Deploy on DockerDeploy on AWSDeploy on GCPDeploy on DigitalOceanDeploy on Render.com
    RailwayRepoCloudElestioNorthflankSealos
    Deploy on RailwayDeploy on RepoCloudDeploy on ElestioDeploy on NorthflankDeploy on Sealos
    Easypanel
    Deploy on Easypanel

    or set up a production AnythingLLM instance without Docker →

    How to setup for development

    • yarn setup To fill in the required .env files you'll need in each of the application sections (from root of repo).
      • Go fill those out before proceeding. Ensure server/.env.development is filled or else things won't work right.
    • yarn dev:server To boot the server locally (from root of repo).
    • yarn dev:frontend To boot the frontend locally (from root of repo).
    • yarn dev:collector To then run the document collector (from root of repo).

    Learn about documents

    Telemetry & Privacy

    AnythingLLM by Mintplex Labs Inc contains a telemetry feature that collects anonymous usage information.

    Why?

    We use this information to help us understand how AnythingLLM is used, to help us prioritize work on new features and bug fixes, and to help us improve AnythingLLM's performance and stability.

    Opting out

    Set DISABLE_TELEMETRY in your server or docker .env settings to "true" to opt out of telemetry. You can also do this in-app by going to the sidebar > Privacy and disabling telemetry.

    What do you explicitly track?

    We will only track usage details that help us make product and roadmap decisions, specifically:

    • Type of your installation (Docker or Desktop)

    • When a document is added or removed. No information about the document. Just that the event occurred. This gives us an idea of use.

    • Type of vector database in use. This helps us prioritize changes when updates arrive for that provider.

    • Type of LLM provider & model tag in use. This helps us prioritize changes when updates arrive for that provider or model, or combination thereof. eg: reasoning vs regular, multi-modal models, etc.

    • When a chat is sent. This is the most regular "event" and gives us an idea of the daily-activity of this project across all installations. Again, only the event is sent - we have no information on the nature or content of the chat itself.

    You can verify these claims by finding all locations Telemetry.sendTelemetry is called. Additionally these events are written to the output log so you can also see the specific data which was sent - if enabled. No IP or other identifying information is collected. The Telemetry provider is PostHog - an open-source telemetry collection service.

    We take privacy very seriously, and we hope you understand that we want to learn how our tool is used, without using annoying popup surveys, so we can build something worth using. The anonymous data is never shared with third parties, ever.

    [View all telemetry events in source code](https://github.com/search?q=repo%3AMintplex-Labs%2Fanything-llm%20.sendTelemetry(&type=code)

    Other outbound connections

    If you disable telemetry, you would still see outbound connections to the following services:

    • If using an external tool, LLM, Embedding models, or Vector databases, you will still see outbound connections to the respective service provider.
    • cdn.anythingllm.com for pulling models from our mirror CDN. This is not tracked by telemetry and is actually useful for those in VPN restricted regions.
    • github/githubusercontent.com There are some various flat files that are downloaded from these domains for context window caching.

    Basically, if telemetry is disabled we don't collect anything. However, depending on your setup you may still see outbound connections and would be subject to the terms of service of the respective service provider.

    👋 Contributing

    💖 Sponsors

    All Sponsors

    🌟 Contributors

    anythingllm contributors

    Star History Chart

    🔗 More Products

    Copyright © 2026 Mintplex Labs. This project is MIT licensed.

    相关项目

    同分类里 star 最高的项目
    对比全部 →
    prompts.chat
    f·MDX

    社区共建的提示词分享与发现平台，可自托管部署，让团队在完全私密的环境里收集和管理 ChatGPT、Claude、Gemini 等模型的提示词。

    提示词库+4知识库
    176827+72223k2026-11-10 14:05 UTC
    generative-ai-for-beginners
    microsoft·Jupyter Notebook

    微软出品的 21 节生成式 AI 入门课程，用 Jupyter Notebook 带你从零理解大模型、提示工程和 ChatGPT 应用开发。

    生成式AI+3知识库
    123300+21666k2026-11-05 03:43 UTC
    Understand-Anything
    Egonex-AI·TypeScript

    把任意代码库转成可交互的知识图谱，支持浏览、搜索和提问，兼容 Claude Code、Cursor、Copilot 等主流 AI 编程工具。

    知识图谱+4知识库
    91856+7097.8kv2.9.02026-11-09 17:56 UTC
    llm-course
    mlabonne

    一套系统的大语言模型入门课程，用学习路线图和可直接运行的 Colab 笔记本，带你从零掌握 LLM 的原理与实战。

    大语言模型+4知识库
    85029+909.9k2026-02-05 13:09 UTC