An AI Assistant to answer user queries based on your own knowledge base!

Python package that makes it easy to spin up a custom Retrieval-Augmented Generation (RAG) pipeline.

This repository contains the implementation of a Retrieval-Augmented Generation (RAG) agent using Large Language Models (LLMs). RAG agents combine the power of information retrieval with text generation, enabling applications such as intelligent question-answering systems, and more.

🔥Dr. Heal Ai - Intelligent Medical Assistant

This Repository contains the real life use cases of Gen-Ai (Google's Gemini + Simple RAG) in Finance Domain. It helps in summarizing any articles , but will be useful for analyzing those lengthy and complicated financial articles .

In this repo implemented LLMs on custom data, using the power of Langchain and RAG.

Cultivating linguistic forests from YC startup pitches using bio-inspired grammar trees to map pitch patterns.

🧠 rags-lab: A centralized repo for everything related to RAGs. Resources, Research, Notes, The Future, & more.

Welcome to a Vs-Code Fork Ai Code Based Editor Your next VibeCoding Editor

🏛️ Retrieval Augmented Generation Systems (GitHub Defaults): Central hub for organizational templates, guidelines, and standards.

This system functions as a domain-specific autonomous AI agent, using agent orchestration frameworks capable of contextual reasoning across multiple books, multimodal inputs and memory driven personalized learning.

Colab notebooks exploring topics in Data Science and AI, discussed on the blog: https://medium.com/@jgrygolec

RAG-based FastAPI documentation Q&A system with hybrid search (BM25 + semantic embeddings). LLM Zoomcamp project featuring ChromaDB, Streamlit UI, and cross-encoder re-ranking.

Build RAG applications in Python with Gradient in minutes

A React-based visual interface that allows users to connect YouTube videos to chat nodes and interact with video content through a conversational interface.

A locally-hosted platform for document analysis and question-answering using Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG).

RAG to talk to your code

Repository to work on a RAG based chatbot to answer specific questions given context from longer texts.

ASIRI AI is a multi PDF chat AI that generates responses based on the contents of uploaded PDF documents.

ScrapeMate – Paste any website link, ask any question about it, and get instant, context-aware answers using RAG (Retrieval-Augmented Generation) powered by LLMs like Groq