BDbdhtu·Nov 3, 2025
GitHub links:
- https://github.com/janhq/jan
- https://github.com/danny-avila/LibreChat
- https://github.com/Mintplex-Labs/anything-llm
In OSS Alternative to Open WebUI – ChatGPT-Like UI, API and CLIMintplex-Labs
anything-llm
JavaScript2023–2025
Mintplex-Labs / anything-llm
anything-llm
Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience
9Distinct people
10Mentions
0Explicit recommenders
68.2KGitHub stars
What to know before exploring
What it is
Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience
GitHub
Where it is used
No documented product use has been verified yet.
What people are saying
No recommendation phrase was found in the indexed comments.
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Also in these discussions
No other repository is repeatedly linked in the same discussions.
This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by month10 dated mentions
Observed mentions: 2023-07-06 20:25:43 UTC to 2025-11-03 15:30:49 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| Jul 2023 | 2023-07-01 00:00:00 UTC | 2023-08-01 00:00:00 UTC | 1 | 0 | 1 |
| Aug 2023 | 2023-08-01 00:00:00 UTC | 2023-09-01 00:00:00 UTC | 1 | 0 | 1 |
| Sep 2023 | 2023-09-01 00:00:00 UTC | 2023-10-01 00:00:00 UTC | 0 | 0 | 0 |
| Oct 2023 | 2023-10-01 00:00:00 UTC | 2023-11-01 00:00:00 UTC | 0 | 0 | 0 |
| Nov 2023 | 2023-11-01 00:00:00 UTC | 2023-12-01 00:00:00 UTC | 0 | 0 | 0 |
| Dec 2023 | 2023-12-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 1 | 0 | 1 |
| Jan 2024 | 2024-01-01 00:00:00 UTC | 2024-02-01 00:00:00 UTC | 1 | 1 | 0 |
| Feb 2024 | 2024-02-01 00:00:00 UTC | 2024-03-01 00:00:00 UTC | 0 | 0 | 0 |
| Mar 2024 | 2024-03-01 00:00:00 UTC | 2024-04-01 00:00:00 UTC | 0 | 0 | 0 |
| Apr 2024 | 2024-04-01 00:00:00 UTC | 2024-05-01 00:00:00 UTC | 0 | 0 | 0 |
| May 2024 | 2024-05-01 00:00:00 UTC | 2024-06-01 00:00:00 UTC | 0 | 0 | 0 |
| Jun 2024 | 2024-06-01 00:00:00 UTC | 2024-07-01 00:00:00 UTC | 0 | 0 | 0 |
| Jul 2024 | 2024-07-01 00:00:00 UTC | 2024-08-01 00:00:00 UTC | 1 | 0 | 1 |
| Aug 2024 | 2024-08-01 00:00:00 UTC | 2024-09-01 00:00:00 UTC | 0 | 0 | 0 |
| Sep 2024 | 2024-09-01 00:00:00 UTC | 2024-10-01 00:00:00 UTC | 1 | 1 | 0 |
| Oct 2024 | 2024-10-01 00:00:00 UTC | 2024-11-01 00:00:00 UTC | 1 | 0 | 1 |
| Nov 2024 | 2024-11-01 00:00:00 UTC | 2024-12-01 00:00:00 UTC | 0 | 0 | 0 |
| Dec 2024 | 2024-12-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 1 | 0 | 1 |
| Jan 2025 | 2025-01-01 00:00:00 UTC | 2025-02-01 00:00:00 UTC | 0 | 0 | 0 |
| Feb 2025 | 2025-02-01 00:00:00 UTC | 2025-03-01 00:00:00 UTC | 0 | 0 | 0 |
| Mar 2025 | 2025-03-01 00:00:00 UTC | 2025-04-01 00:00:00 UTC | 1 | 0 | 1 |
| Apr 2025 | 2025-04-01 00:00:00 UTC | 2025-05-01 00:00:00 UTC | 0 | 0 | 0 |
| May 2025 | 2025-05-01 00:00:00 UTC | 2025-06-01 00:00:00 UTC | 0 | 0 | 0 |
| Jun 2025 | 2025-06-01 00:00:00 UTC | 2025-07-01 00:00:00 UTC | 0 | 0 | 0 |
| Jul 2025 | 2025-07-01 00:00:00 UTC | 2025-08-01 00:00:00 UTC | 0 | 0 | 0 |
| Aug 2025 | 2025-08-01 00:00:00 UTC | 2025-09-01 00:00:00 UTC | 0 | 0 | 0 |
| Sep 2025 | 2025-09-01 00:00:00 UTC | 2025-10-01 00:00:00 UTC | 0 | 0 | 0 |
| Oct 2025 | 2025-10-01 00:00:00 UTC | 2025-11-01 00:00:00 UTC | 0 | 0 | 0 |
| Nov 2025 | 2025-11-01 00:00:00 UTC | 2025-12-01 00:00:00 UTC | 1 | 0 | 1 |
What Hacker News says
10 sourcessome other alternatives (a little more mature / feature rich):
anythingllm https://github.com/Mintplex-Labs/anything-llm
openwebui https://github.com/open-webui/open-webui
lmstudio https://lmstudio.ai/
In Sidekick: Local-first native macOS LLM appI’m surprised to see no mention of AnythingLLM (https://github.com/Mintplex-Labs/anything-llm). I use it with an Anthropic API key, but am giving thought to extending it with local LLM.
It’s a great app: good file management for RAG, agents with web search, cross platform desktop client, but can also easily be run as a server using docker compose.
Nb: if you’re still paying $20/mo for a feature-poor chat experience that’s locked to a single provider, you should consider using any of the many wonderful chat clients that take a variety of API keys instead. You might find that your LLM utilization doesn’t quite fit a flat rate model, and that the feature set of the third-party client is comparable (or surpasses) that of the LLM provider’s.
edit: included repo link; note on API keys as alternative to subscription
In How I run LLMs locallyI'm very interested in checking something like this out for getting to grips with a local codebase of unfamiliar SQL and assorted scripts and reports.
I have a few tabs open that I haven't had a chance to try:
https://github.com/Mintplex-Labs/anything-llm
https://github.com/Bin-Huang/chatbox
https://github.com/saeedezzati/superpower-chatgpt
In Ask HN: Local RAG with private knowledge baseShow HN: AnythingLLM – Open-Source, All-in-One Desktop AI Assistant
Hey HN!
This is Tim from AnythingLLM (https://github.com/Mintplex-Labs/anything-llm). AnythingLLM is an open-source desktop assistant that brings together RAG (Retrieval-Augmented Generation), agents, embeddings, vector databases, and more—all in one seamless package.
We built AnythingLLM over the last year iterating and iterating from user feedback. Our primary mission is to enable people with a layperson understanding of AI to be able to use AI with little to no setup for either themselves, their jobs, or just to try out using AI as an assistant but with *privacy by default*.
From these iterations & feedback, we have a couple of key learnings I wanted to share:
- "Chat with your docs" solutions are a dime-a-dozen
- Agent frameworks require knowing how to code or are too isolated from other tools
- Users do not care about benchmarks, onl
Read the rest
y outputs. The magic box needs to be magic to them.
- Asking Consumers to start a docker container or open a terminal is a non-starter for most.
- Privacy by default is non-negotiable. Either by personal preference or legal constraints
- Everything needs to be in one place
From these ideas, we landed on the current state of AnythingLLM:
- Everything in AnythingLLM is private by default, but fully customizable for advanced users.
- Built-in LLM provider, but can swap at any time to the hundreds of other local or cloud LLM providers & models.
- Built-in Vector Database, most users don't even know that it is there.
- Built-in Embedding model, but of course can change if the user wants to.
- Scrape websites, import Github/GitLab repos, YouTube Transcripts, Confluence spaces - all of this is already built in for the user.
- An entire baked-in agent framework that works seamlessly within the app. We even pre-built a handful of agent skills for customers. Custom plugins are in the next update and will be able to be built with code, or a no-code builder.
- All of this just works out of the box in a single installable app that can run on any consumer-grade laptop. Everything a user does, chats, or configures is stored on the user's device. Available for Mac, Windows, and Linux
We have been actively maintaining and working on AnythingLLM via our open-source repo for a while now and welcome contributors as we hopefully launch a Community Hub soon to really proliferate users' abilities to add more niche agent skills, data connectors, and more.
*But there is even more*
We view the desktop app as a hyper-accessible single-player version of AnythingLLM. We publish a Docker image too (https://hub.docker.com/r/mintplexlabs/anythingllm) that supports multi-user management with permissioning so that you can easily bring AnythingLLM into an organization with all of the same features with minimal headache or lift.
The Docker image is for those more adept with a CLI, but being able to comfortably go from a single-user to a multi-user version of the same familiar app was very important for us.
AnythingLLM aims to be more than a UI for LLMs, we are building a comprehensive tool to leverage LLMs and all that they can do while maintaining user privacy and not needing to be an expert on AI to do it.
https://anythingllm.com/
Thanks for taking the time to respond. I was thinking of something local, especially in light of:
Google's Gemini AI caught scanning Google Drive PDF files without permission https://news.ycombinator.com/item?id=40965892 .
Looks like GPT4All[1] and AnythingLLM[2] are worth exploring. There's also the closed-source macOS app RecurseChat[3,4] which appeared on HN a few months ago[5].
[1] https://github.com/nomic-ai/gpt4all
[2] https://github.com/Mintplex-Labs/anything-llm
[3] https://recurse.chat
[4] https://recurse.chat/blog/posts/local-docs
[5] https://news.ycombinator.com/item?id=39532367
In Show HN: Site2pdfA front end/UI focused RAG framework
1 points · Open discussionanything-llm looks pretty interesting and easy to use https://github.com/Mintplex-Labs/anything-llm
In Ask HN: How do I train a custom LLM/ChatGPT on my own documents in Dec 2023?Im not surprised Azure would add something like this to the stack. We build AnythingLLM (https://github.com/Mintplex-Labs/anything-llm) back in June due to some enterprise customers wanting something isolated they could run on premises with Azure OpenAI support + any vector DB they want.
With Azure's move to try to internalize any enterprise integration for AI it makes sense to make a chatbot wrapper because its a no-moat move. I think a lot of the "moat" if one can exist in the "chat with your docs" vertical is just integrations into flows and data sources SMB/Enterprises are already using.
For businesses, in my experience, the on-prem thing has been the first decision point - without question. Azure wrapper could be nice to have for those who cannot use chatGPT on the work comp but have access to this instead.
I wonder what kind of hype
Read the rest
rvisor view it gives to Azure admins for those who use it - it any. Multi-tenant instances was the second highest demand from SMB/Enterprise customers for AnythingLLM.
I just came across this project which seems to be aiming at streamlining exactly that :
https://github.com/Mintplex-Labs/anything-llm
In AI for AWS Documentation