danswer
private-gpt
danswer | private-gpt | |
---|---|---|
28 | 131 | |
9,382 | 52,175 | |
5.9% | 3.2% | |
9.9 | 9.2 | |
7 days ago | 11 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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danswer
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Show HN: Cognita – open-source RAG framework for modular applications
You might want to look at https://github.com/danswer-ai/danswer as well, as it sounds like their UI might be of suited for your use case.
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Show HN: I made an app to use local AI as daily driver
There are already several RAG chat open source solutions available. Two that immediately come to mind are:
Danswer
https://github.com/danswer-ai/danswer
Khoj
https://github.com/khoj-ai/khoj
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Launch HN: Danswer (YC W24) – Open-source AI search and chat over private data
We have a connector interface and build guide for contributors: https://github.com/danswer-ai/danswer/blob/main/backend/dans...
Should be not too bad to build one out! Fun fact, more than half the connectors were built entirely by community members who needed them for their own teams and we're super grateful when they contribute it back to the repo.
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Findr VS danswer - a user suggested alternative
2 projects | 7 Feb 2024
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Show HN: DanswerChat – open-source GPTs with access to all your org's knowledge [video]
Danswer is an MIT licensed project that can connect to a wide range of SaaS tools and provide a search/chat (RAG) functionality to help your team discover information and to turn that information into deeper understanding and actionable insights.
Code here: https://github.com/danswer-ai/danswer
- Open source alternative to ChatGPT and ChatPDF-like AI tools
- Danswer: Self-Hosted way to connect an LLM of your choice to Docs, Websites, and SaaS tools like Google Drive, Notion, Bookstack, Zulip, etc.
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Show HN: DanswerBot – Open-source Slack bot to automate repetitive questions
Slack questions have always been a huge time sink for me. They’re a distraction that pulls me away from what I’m doing, and often requires digging up old knowledge. If I’m in the middle of something complex, I may take a while to context switch and get around to answering, which leaves the asker blocked for hours.
Addressing this seems simple: give an LLM your organizational context and plop it in Slack to answer things for you.
So that’s why we built DanswerBot! It’s MIT licensed (https://github.com/danswer-ai/danswer) and completely free to use. The bot can automatically sync with and back answers based on documents from Slack, Google Drive, GitHub, Confluence, Jira, Notion, local files, websites, and much more.
Quick demo vid: https://www.youtube.com/watch?v=5q35NeqsMnU
A quick note on hallucinations: in order to reduce their prevalence, all answers are backed by quotes. If the LLM-provided quotes don’t match any document or no quotes are given, we’ll warn the asker that something may have gone wrong. Additionally, all used documents are linked in case the asker wants to double check the answer. Answers can be thumbs-upped or thumbs-downed and all questions / answers are recorded in Postgres for easy future inspection / analysis.
For usability, we provide an admin dashboard where you can configure connectors (we have 14 currently). Once a connector is set up, we poll data sources every 10 minutes to keep answers up to date. Which LLM to use is also up to you - DanswerBot can be configured to use a locally hosted model, Azure OpenAI, or OpenAI directly.
Finally, if you aren’t a slack user (or if you just prefer a more tailored UI), there’s also a web interface to ask questions against your knowledge base. A short demo for that can be found at: https://youtu.be/cWWtnuVCUX0
Of course there’s a bunch more that I can’t cover in one post - happy to take questions in the comments (or in our Slack / Discord, which are linked on the Github repo).
If you’re interested in testing this out yourself, you can easily run everything locally with a single command. Docs to help you can be found at https://docs.danswer.dev/quickstart!
- App to auto-answer user questions in your Slack
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DanswerBot - open source SlackBot that answers questions for you
Code: https://github.com/danswer-ai/danswer
private-gpt
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Ask HN: Has Anyone Trained a personal LLM using their personal notes?
PrivateGPT is a nice tool for this. It's not exactly what you're asking for, but it gets part of the way there.
https://github.com/zylon-ai/private-gpt
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PrivateGPT exploring the Documentation
Further details available at: https://docs.privategpt.dev/api-reference/api-reference/ingestion
- Show HN: I made an app to use local AI as daily driver
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privateGPT VS quivr - a user suggested alternative
2 projects | 12 Jan 2024
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Ask HN: How do I train a custom LLM/ChatGPT on my own documents in Dec 2023?
Run https://github.com/imartinez/privateGPT
Then
make ingest /path/to/folder/with/files
Then chat to the LLM.
Done.
Docs: https://docs.privategpt.dev/overview/welcome/quickstart
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Mozilla "MemoryCache" Local AI
PrivateGPT repository in case anyone's interested: https://github.com/imartinez/privateGPT . It doesn't seem to be linked from their official website.
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What Is Retrieval-Augmented Generation a.k.a. RAG
I’m preparing a small internal tool for my work to search documents and provide answers (with references), I’m thinking of using GPT4All [0], Danswer [1] and/or privateGPT [2].
The RAG technique is very close to what I have in mind, but I don’t want the LLM to “hallucinate” and generate answers on its own by synthesizing the source documents. As stated by many others, we’re living in interesting times.
[0] https://gpt4all.io/index.html
[1] https://www.danswer.ai/
[2] https://github.com/imartinez/privateGPT
- LM Studio – Discover, download, and run local LLMs
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Ask HN: Local LLM Recommendation?
https://www.reddit.com/r/LocalLLaMA/comments/14niv66/using_a...
https://github.com/imartinez/privateGPT
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Run ChatGPT-like LLMs on your laptop in 3 lines of code
I've been playing around with https://github.com/imartinez/privateGPT and https://github.com/simonw/llm and wanted to create a simple Python package that made it easier to run ChatGPT-like LLMs on your own machine, use them with non-public data, and integrate them into practical applications.
This resulted in Python package I call OnPrem.LLM.
In the documentation, there are examples for how to use it for information extraction, text generation, retrieval-augmented generation (i.e., chatting with documents on your computer), and text-to-code generation: https://amaiya.github.io/onprem/
Enjoy!
What are some alternatives?
GPTCache - Semantic cache for LLMs. Fully integrated with LangChain and llama_index.
localGPT - Chat with your documents on your local device using GPT models. No data leaves your device and 100% private.
privateGPT - Interact with your documents using the power of GPT, 100% privately, no data leaks [Moved to: https://github.com/zylon-ai/private-gpt]
gpt4all - gpt4all: run open-source LLMs anywhere
free-music-demixer - free website for client-side music demixing with Demucs + WebAssembly
h2ogpt - Private chat with local GPT with document, images, video, etc. 100% private, Apache 2.0. Supports oLLaMa, Mixtral, llama.cpp, and more. Demo: https://gpt.h2o.ai/ https://codellama.h2o.ai/
pekko-samples - Apache Pekko Sample Projects
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
khoj - Your AI second brain. A copilot to get answers to your questions, whether they be from your own notes or from the internet. Use powerful, online (e.g gpt4) or private, local (e.g mistral) LLMs. Self-host locally or use our web app. Access from Obsidian, Emacs, Desktop app, Web or Whatsapp.
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
obsidian-releases - Community plugins list, theme list, and releases of Obsidian.
llama.cpp - LLM inference in C/C++