📄 🤖 Semantic search and workflows for medical/scientific papers
Building blocks for rapid development of GenAI applications
🥥 Coco AI App - Search, Connect, Collaborate, Your Personal AI Search and Assistant, all in one space.
Vector search demo with the arXiv paper dataset, RedisVL, HuggingFace, OpenAI, Cohere, FastAPI, React, and Redis.
A lightweight, production-ready RAG (Retrieval Augmented Generation) library in Go.
This open source chatbot project lets you create a chatbot that uses your own data to answer questions, thanks to the power of the OpenAI GPT-3.5 model.
A JavaScript library that brings vector search and RAG to your browser!
🥥 Coco AI Server - Search, Connect, Collaborate, AI-powered enterprise search, all in one space.
An in-memory NoSQL database implemented in Python.
Search through all your personal data efficiently like web search.
Finding all pairs of similar documents time- and memory-efficiently
COVID-19 Open Research Dataset (CORD-19) Analysis
Document Search Engine project with TF-IDF abd Google universal sentence encoder model
BM25 search implemented in PL/pgSQL
faster BM25 search algorithms in Python
This code example shows how to make a chatbot for semantic search over documents using Streamlit, LangChain, and various vector databases. The chatbot lets users ask questions and get answers from a document collection. The code is in Python and can be customized for different scenarios and data.
AI-powered file launcher and semantic search assistant. Like Spotlight/Alfred but with advanced AI capabilities for understanding context and meaning. Features local processing, privacy-first design, and seamless integration with your workflow.
Chat with your PDFs using AI! This Streamlit app uses RAG, LangChain, FAISS, and OpenAI to let you ask questions and get answers with page and file references.
A highly efficient, isomorphic, full-featured, multilingual text search engine library, providing full-text search, fuzzy matching, phonetic scoring, document indexing and more, with micro JSON state hydration/dehydration in-browser and server-side.
PostgreSQL-native semantic search engine with multi-modal capabilities. Add AI-powered search to your existing database without separate vector databases, vendor fees, or complex setup. Features text + image search using CLIP embeddings, native SQL joins, and 10-minute Docker deployment.
Add a description, image, and links to the document-search topic page so that developers can more easily learn about it.
To associate your repository with the document-search topic, visit your repo's landing page and select "manage topics."