CodeChat: Enabling interaction with codebases present in GitHub repositories. Seamlessly explore, query, and discuss code with a powerful RAG pipeline, making coding intuitive and efficient

Homework 3 for the machine learning class at Tsinghua University (fall term 23/24)

we learn how we can feed the output of vector databases (in our story, we employed ChromaDB) to a Large Language Model to build RAG

using mulimodal RAG to query texts, images and tables from pdf for QA

A Gemma based RAG that answers python specific questions

Exploring LLM RAG applications.

Build a RAG app from scratch using Chroma and the ChatGPT API

Vectara's RAG-Enhanced Customer Service Bot Platform

Dive into LangChain, a powerful platform that lets you interact with your data like never before. This guide offers insights on its unique capabilities, helping you tap into your data in conversational ways.

EMNLP'2023: Retrieval-Generation Alignment for End-to-End Task-Oriented Dialogue System

Takes in a user's question and returns an answer along with URL resources.

Offline Multi-Modal RAG. Execution Scripts optimized for for Intel, CUDA.

"Chat with Databases using RAG" is a cutting-edge project that seamlessly integrates natural language inputs with database interactions. By leveraging advanced techniques like RAG and few-shot learning, it generates SQL queries from plain text and retrieves human-like responses from the database, revolutionizing the way we interact with data.

Retrieval-Augmented Generation using Azure OpenAI

Notebooks supporting the activities for generative AI 102 Startup loft.

RAG Customer Support Chatbot that's capable of answering any user questions regarding company products.

Streamlit app to chat with Nairobi Stock Exchange annual report PDF using Retrieval Augmented Generation (RAG) and LLM

customer service chatbot based on LLM and your knowledgebase

RAG with LLM agents for SQL & graph databases