React Hook for indexed-vector-store package
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Updated
Mar 30, 2024 - TypeScript
React Hook for indexed-vector-store package
Kubernetes-native package for Weaviate, an AI-native vector database that helps developers create intuitive and reliable AI-powered applications.
Vector Index / Vector Store implemented in go, nginx load balancing and an angular management frontend
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
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 high-performance on-disk dictionary.
A cloud-native vector database, storage for next generation AI applications
minimem is a minimal implementation of in-memory vector-store using only numpy
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.
The AI Assistant uses OpenAI's GPT models and Langchain for agent management and memory handling. With a Streamlit interface, it offers interactive responses and supports efficient document search with FAISS. Users can upload and search pdf, docx, and txt files, making it a versatile tool for answering questions and retrieving content.
just testing langchain with llama cpp documents embeddings
A command-line tool that ingests documents and generates instant answers to your questions about those documents using ChatGPT, giving you the Sheldon Cooper you never had at your fingertips.
Basic Vector DB DataStorage For Images/Audio/Text Embeddings. for nlp with vb.net
A Question Generation Application leveraging RAG and Weaviate vector store to be able to retrieve relative contexts and generate a more useful answer-aware questions
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