React Hook for indexed-vector-store package
-
Updated
Mar 30, 2024 - TypeScript
React Hook for indexed-vector-store package
An AI-based application leveraging Gemini/OpenAI and JinaAI embeddings with a FastAPI backend and Svelte frontend. The app can read PDFs, maintain webpage memory, and facilitate interactive chat with websites, webpages, and PDFs.
Incorporar distintos tipos de documentos simultáneamente a la base de datos de embeddings Chroma con LangChain.
Kubernetes-native package for Weaviate, an AI-native vector database that helps developers create intuitive and reliable AI-powered applications.
A website that summarizes PDFs into simple paragraphs based on user's queries_using Streamlit, LangChain, OpenAI, and ChromaDB Docker Image technologies.
A set of Node-RED nodes for interfacing with Couchbase services.
Final Project for Information Retrival, this is an implementation that uses numpy of a vector store and a RAG PoC with ollama
🗲 A high-performance on-disk dictionary.
Vector Index / Vector Store implemented in go, nginx load balancing and an angular management frontend
Q & A with multiple pdf App is a Python application that allows you to ask questions about the PDFs you upload using natural language model to generate accurate answers to your queries.
LLM powered ChatAI system. Added support for HF Embeddings and Models too
A cloud-native vector database, storage for next generation AI applications
minimem is a minimal implementation of in-memory vector-store using only numpy
An LLM powered chatbot that can answer questions based on your specific data
A library for efficient similarity search and clustering of dense vectors.
🤖 An intelligent, context-aware chatbot that can be utilized to answer questions about your own documented data.
Add a description, image, and links to the vector-store topic page so that developers can more easily learn about it.
To associate your repository with the vector-store topic, visit your repo's landing page and select "manage topics."