Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.

A FastAPI service for semantic text search using precomputed embeddings and advanced similarity measures, with built-in support for various file types through textract.

High-performance vector similarity library in Rust with Python bindings: Spearman, Kendall, distance correlation, Jensen-Shannon, Hoeffding's D, and bootstrapped confidence intervals

Score documents using embedding-vectors dot-product or cosine-similarity with ES Lucene engine

Program that lets you ask questions about your documents including audio and video files.

Extract knowledge from all information sources using gpt and other language models. Index and make Q&A session with information sources.

Vector Storage is a vector database that enables semantic similarity searches on text documents in the browser's local storage. It uses OpenAI embeddings to convert documents into vectors and allows searching for similar documents based on cosine similarity.

A client side vector search library that can embed, store, search, and cache vectors. Works on the browser and node. It outperforms OpenAI's text-embedding-ada-002 and is way faster than Pinecone and other VectorDBs.

⚡ GUI for editing LLM vector embeddings. No more blind chunking. Upload content in any file extension, join and split chunks, edit metadata and embedding tokens + remove stop-words and punctuation with one click, add images, and download in .veml to share it with your team.

RAG with langchain using Amazon Bedrock and Amazon OpenSearch

DadmaTools is a Persian NLP tools developed by Dadmatech Co.

AI Native database for embedding vectors

The Next-Gen Database for AI—an infrastructure designed for data and AI. As the MySQL of the AI era.

A Python CLI to test, benchmark, and find the best RAG chunking strategy for your Markdown documents.

langchain-chat is an AI-driven Q&A system that leverages OpenAI's GPT-4 model and FAISS for efficient document indexing. It loads and splits documents from websites or PDFs, remembers conversations, and provides accurate, context-aware answers based on the indexed data. Easy to set up and extend.

A monolingual and cross-lingual meta-embedding generation and evaluation framework

Vectory provides a collection of tools to track and compare embedding versions.

Sentiment analyzer for your tweets.

Ruby wrapper for the Qdrant vector search database API

Ruby wrapper for the Weaviate vector search database API

LLM Chatbot w/ Retrieval Augmented Generation using Llamaindex. It demonstrates how to impl. chunking, indexing, and source citation.

Enhancing Recommendation Systems with Large Language Models (RAG - LangChain - OpenAI)

Dryad talks to you tree! Easy semantic code search on any repository

Upload personal docs and Chat with your PDF files with this GPT4-powered app. Built with LangChain, Pinecone Vector Database, deployed on Streamlit

Vector Index Benchmark for Embeddings (VIBE) is an extensible benchmark for approximate nearest neighbor search methods, or vector indexes, using modern embedding datasets.

Personalize ChatGPT using LangChain, and get answers from your own documents and knowledge base.

🐝 | From Data to Prognosis: Embedding Multimodal Oncology Data for Precision Medicine

Ruby wrapper for the Milvus vector search database API

Local Vector Database coded in c# supports Cosine Similarity, Jaccard Dissimilarity as well as Euclidean , Manhattan, ChebyShev and Canberra distances

Interactive chat application leveraging OpenAI's GPT-4 for real-time conversation simulations. Built with Flask, this project showcases streaming LLM responses in a user-friendly web interface.