rag-pipeline

There are 27 repositories under rag-pipeline topic.

  • Julian-AT/synth-ui

    Generate & Ship UI with minimal effort - Open Source Generative UI with natural language

    Language:TypeScript45103
  • lexio

    Renumics/lexio

    Quickest way to production grade RAG UI.

    Language:TypeScript323222
  • Clearedge-AI/clearedge

    Build a RAG preprocessing pipeline

    Language:Jupyter Notebook12200
  • MaxMLang/RAG-nificent

    Production-ready Chainlit RAG application with Pinecone pipeline offering all Groq and OpenAI Models, to chat with your documents.

    Language:Python11100
  • Dynatrace/obslab-llm-observability

    Search for a holiday and get destination advice from an LLM. Observability by Dynatrace.

    Language:HTML1017140
  • simranjeet97/Learn_RAG_from_Scratch_LLM

    Learn Retrieval-Augmented Generation (RAG) from Scratch using LLMs from Hugging Face and Langchain or Python

    Language:Jupyter Notebook6103
  • AnasAber/RAG_in_CPU

    This repo is for advanced RAG systems, each branch will represent a project based on RAG.

    Language:Python5110
  • teddy-ambona/openai-rag-chatbot

    Demo LLM (RAG pipeline) web app running locally using docker-compose. LLM and embedding models are consumed as services from OpenAI.

    Language:Python4100
  • Md-Emon-Hasan/Retrieval-Augmented-Generation-RAG

    RAG enhances LLMs by retrieving relevant external knowledge before generating responses, improving accuracy and reducing hallucinations.

    Language:Jupyter Notebook312
  • mistir-nigusse/LLM_Prompt_Engine

    AI-driven prompt generation and evaluation system, designed to optimize the use of Language Models (LLMs) in various industries. The project consists of both frontend and backend components, facilitating prompt generation, automatic evaluation data generation, and prompt testing.

    Language:Python3100
  • Aksherwal/AskSitare

    It's an AI chatbot based on RAG pipeline for answering queries related to Sitare University.

    Language:Python1
  • AnasAber/MLflow_with_RAG

    Using MLflow to deploy your RAG pipeline, using LLamaIndex, Langchain and Ollama/HuggingfaceLLMs/Groq

    Language:Python1111
  • devcom33/Chat-with-Your-Documents

    Chat-with-Your-Documents is an AI-powered document chatbot using RAG, FastAPI, and React.js for local PDF question answering.

    Language:JavaScript1100
  • dynamicanupam/Fashion_Recommendation_System_using_RAG_pipeline

    A GenAI based search system that scans numerous fashion product descriptions to recommend suitable options based on user queries.

    Language:Jupyter Notebook1110
  • Md-Emon-Hasan/LangChain

    Powerful framework for building applications with Large Language Models (LLMs), enabling seamless integration with memory, agents, and external data sources.

    Language:Jupyter Notebook112
  • abm1499/ML-Powered-Research-Assistant

    ML-Powered Research Assistant: A web application that processes PDF research documents, providing individual summaries, a comparative final summary, sentiment analysis, keyword extraction, and a RAG-powered chatbot for querying content. Built with a FastAPI backend and Next.js frontend, it leverages LLaMA and DistilBERT for NLP adv. capabilities.

    Language:TypeScript00
  • kameshpoc/rag-data-pipeline

    This repo is to demonstrate rag data processing pipeline using dataflow flex templates

    Language:Python0100
  • nelima22/hybrid_search_rag_pipeline

    Hybrid Search RAG Pipeline integrating BM25 and vector search techniques using LangChain

    Language:Jupyter Notebook0100
  • Piyush-sri11/QA-chatbot

    A Question-Answering chatbot built using RAG (Retrieval-Augmented Generation) with conversation memory. This project uses LangChain, various LLM options, and vector stores to create an intelligent chatbot that can answer questions about Jessup Cellars winery.

    Language:Python00
  • saadtariq-ds/Generative-AI-with-Langchain-and-Huggingface

    This repository offers a hands-on guide to mastering Generative AI with Langchain and Huggingface. It covers key concepts, practical implementation, and deployment strategies to help AI enthusiasts, developers, and professionals build and optimize AI models efficiently

    Language:Jupyter Notebook0100
  • AVidhanR/HassleMediBot

    A Rag Based Medical ChatBot

    Language:Jupyter Notebook00
  • bhatt-j/RAG-QABot

    Retrieval-Augmented Generation (RAG) Model for a Question Answering (QA) bot that interacts with financial data, specifically Profit & Loss (P&L) tables extracted from PDF documents.

    Language:Jupyter Notebook10
  • olifarhaan/rag-console-chat

    This project implements document ingestion, embedding generation, and retrieval-augmented generation (RAG). If you are looking for a small project to understand the implementation of basic RAG then this project is good to go.

    Language:Python10
  • sarvagyakrcs/git-your-code

    Git Your Code implements a cutting-edge Retrieval-Augmented Generation (RAG) architecture designed for deep semantic analysis of GitHub repositories. The system leverages vector embeddings, natural language processing, and machine learning to provide intelligent code comprehension and query capabilities.

    Language:TypeScript10
  • siddhantprateek/bitrac-rag

    This is a production-ready applications using RAG-based Language Model.

  • tejas-130704/WebScraperAI

    WebScraperAI is a powerful tool that enables users to perform question-answering on website content using web scraping and retrieval-augmented generation (RAG) with LlamaIndex. It supports multiple LLMs, including OpenAI GPT-3.5, GPT-4, Gemini Pro, Gemini Ultra, and DeepSeek.

    Language:Python
  • XSkuLL007/ML-Powered-Research-Assistant

    ML-Powered Research Assistant: A web application that processes PDF research documents, providing individual summaries, a comparative final summary, sentiment analysis, keyword extraction, and a RAG-powered chatbot for querying content. Built with a FastAPI backend and Next.js frontend, it leverages LLaMA and DistilBERT for NLP adv. capabilities.

    Language:TypeScript10