self-improving user memory framework for conversational AI apps

Q&A Chatbot Demo using Couchbase, LangChain, OpenAI and Streamlit

Hybrid Search demo on Movies Dataset using Couchbase with Native Python SDK & LangChain Vector Store integration & Streamlit

Question Answering Generative AI application with Large Language Models (LLMs) and Amazon OpenSearch Service

Tư Tưởng Hồ Chí Minh Chatbot

Zep | The Memory Foundation For Your AI Stack

State-of-the-art CLIP/SigLIP embedding models finetuned for the fashion domain. +57% increase in evaluation metrics vs FashionCLIP 2.0.

The Fast Vector Similarity Library is designed to provide efficient computation of various similarity measures between vectors.

RAG Vector Search with MongoDB, Hugging Face and Node JS

Memory Management Service, a Long Term Memory Solution for AI

This project demonstrates using `Elasticsearch` and vector search techniques to efficiently find answers to user questions in FAQ documents by leveraging embeddings and evaluating search performance with hit rate and mean reciprocal rank (MRR).

⚡️ Build quick LLM pipelines for AI applications

MediCopilot uses AI to assist healthcare professionals

The Project "Vector Search RAG" utilises advanced frameworks and language models (LangChain and OpenAI APIs) to enhance query responses by retrieving relevant documents and generating contextually accurate answers. This repo contains End-to-End implementation of RAG for training LLMs in custom data.

Question-Answering App Over Your Own Data with LLamaindex and ElasticSearch !

A generative AI based smart information retrieval system featuring Hybrid Contextual Search,

This Python Flask application is designed to process and rank resumes based on job descriptions. It uses Azure's Document Analysis Client for document processing, and a MongoDB database for storing job descriptions and resumes. The application also generates embeddings for the processed documents using AzureOpenAI.

🔎 A vector based image search engine using Visual Transformer model type.

High-level ElasticSearch client for Julia

Simple and pure Julia-based implementation of ChatGPT retrieval plugin logic