Alternatives
Products that do what RAGSUITE does
Secure Chat with RAG Pipeline
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Hey hacker news, We’re the cofounders at Psychic.dev (http://psychic.dev) where we help companies connect LLMs to private data. With the launch of Llama 2, we think it’s finally viable to self-host an internal application that’s on-par with ChatGPT, so we did exactly that and made it an open source project. We also included a vector DB and API server so you can upload files and connect Llama 2 to your own data. The RAG in RAGstack stands for Retrieval Augmented Generation, a technique where the capabilities of a large language model (LLM) are augmented by retrieving information…
2023 · github.com
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WhisperFusion builds upon the capabilities of open source tools WhisperLive and WhisperSpeech to provide a seamless conversations with an AI chatbot.
2024 · github.com
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Hey everyone, We have been building SecureAI Tools -- an open-source application layer for ChatGPT and ChatPDF-like AI tools. It works with locally running LLMs as well as with OpenAI-compatible APIs. For local LLMs, it supports Ollama which supports all the gguf/ggml models. Currently, it has two features: Chat-with-LLM, and Chat-with-PDFs. It is optimized for self-hosting use cases and comes with basic user management features. Here are some quick demos: * Chat with documents using OpenAI's GPT3.5 model: https://www.youtube.com/watch?v=Br2D3G9O47s * Chat with documents…
2023 · github.com
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I've built an advanced RAG (Retrieval-Augmented Generation) pipeline from scratch to demystify the complex mechanics of modern LLM-powered Question Answering systems. This repository features: -- An implementation of a sub-question query engine from scratch to answer complex user questions. -- Illustrative explanations that unveil the inner workings of the system. -- An analysis of the challenges I faced while working with the system, like prompt engineering and cost estimation. -- Qualitative comparison with similar frameworks like LlamaIndex, offering a broader perspective. Key Takeaway:…
2023 · github.com
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We show the potential of modern, embedded graph databases in the browser by demonstrating a fully in-browser chatbot that can perform Graph RAG using Kuzu (the graph database we're building) and WebLLM, a popular in-browser inference engine for LLMs. The post retrieves from the graph via a Text-to-Cypher pipeline that translates a user question into a Cypher query, and the LLM uses the retrieved results to synthesize a response. As LLMs get better, and WebGPU and Wasm64 become more widely adopted, we expect to be able to do more and more in the browser in combination with LLMs, so a lot of…
2025 · blog.kuzudb.com
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100% offline RAG for engineers who can't use cloud AI
20d ago · philyeh.gumroad.com
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If you have developer documentation and want to boost your community with AI this is for you! Just pull in the base url of the site add some customization and get a sharable link for your chat, link it anywhere you want. I saw this trend in some places like gcp with Gemini, or Langchain or Supabase ask ai, but they're all custom-implemented solutions, not everyone wants to advocate developer resources to create the rag, deploy it and maintain it, you just want devs to build with your stuff, the more they can do the better, the quicker the better, and if they get a smooth experience while…
2024 · explainit.mzslabs.com
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