vectorsearch
There are 23 repositories under vectorsearch topic.
getzep/zep
Zep | The Memory Foundation For Your AI Stack
Dicklesworthstone/fast_vector_similarity
The Fast Vector Similarity Library is designed to provide efficient computation of various similarity measures between vectors.
plastic-labs/honcho
self-improving user memory framework for conversational AI apps
marqo-ai/marqo-FashionCLIP
State-of-the-art CLIP/SigLIP embedding models finetuned for the fashion domain. +57% increase in evaluation metrics vs FashionCLIP 2.0.
aws-samples/rag-with-amazon-opensearch-and-sagemaker
Question Answering Generative AI application with Large Language Models (LLMs) and Amazon OpenSearch Service
halilergul1/QA-app
Question-Answering App Over Your Own Data with LLamaindex and ElasticSearch !
memas-ai/MeMaS
Memory Management Service, a Long Term Memory Solution for AI
rssdev10/GptSearchPlugin
Simple and pure Julia-based implementation of ChatGPT retrieval plugin logic
LarsWl/ElasticsearchClient.jl
High-level ElasticSearch client for Julia
AnshKathpal/Documentor-pdfChatbot
DocuMentor is a sophisticated chatbot application designed to assist users in extracting valuable information from uploaded PDF documents. Users can upload PDF files, chat with the AI chatbot to ask questions or seek information related to the document, and receive well-informed responses.
couchbase-examples/hybrid-search-demo
Hybrid Search demo on Movies Dataset using Couchbase with Native Python SDK & LangChain Vector Store integration & Streamlit
d1pankarmedhi/image-search-engine
🔎 A vector based image search engine using Visual Transformer model type.
hsm207/haystack-weaviate-docker-compose
How to use configure haystack to use weaviate
couchbase-examples/qa-bot-demo
Q&A Chatbot Demo using Couchbase, LangChain, OpenAI and Streamlit
musketeers-br/iris-medicopilot
MediCopilot uses AI to assist healthcare professionals
pica-labs/picachain
⚡️ Build quick LLM pipelines for AI applications
kaustav202/search-genie
A generative AI based smart information retrieval system featuring Hybrid Contextual Search,
eaintkyawthmu/azureopenai_mongodb_resume_ranking
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.
Karthi-DStech/VectorSearch-RAG-using-LangChain-OpenAI
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.
LaiLaK918/tthcm
Tư Tưởng Hồ Chí Minh Chatbot
Mannerow/llm-homework-03
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).
thorve-shubham/rag_with_mongo_huggingface_node
RAG Vector Search with MongoDB, Hugging Face and Node JS