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.

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

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

A sample rss aggregator application demonstrating the use of Cohere Embeddings

A Nextjs and stripe integrated Saas app starter where users can upload their own pdf and chat with their pdf with openai apis bootstraped with shadcnUI React-Query Zod using neon-DB

AI Platform that train chatbot and chat with this chatbot

IntelliSearch is an advanced retrieval-based question-answering and recommendation system that leverages embeddings and a large language model (LLM) to provide accurate and relevant information to users.

This is a web app where user can talk with there pdf , just need to run few scripts to ingest there pdf, and then with web interface they can talk with pdf

A web application that extracts, processes, and intelligently interacts with PDF content. Using natural language processing and vector embeddings, it transforms PDF text into high-dimensional vectors for efficient and accurate querying.