Canopy is an open-source framework designed to help developers quickly build Retrieval Augmented Generation (RAG) applications by leveraging the Pinecone vector database, which offers free storage for up to 100,000 vectors and scales to billions on paid plans. This framework simplifies the complex tasks involved in creating GenAI applications, such as text data chunking, embedding, chat history management, query optimization, context retrieval, and augmented generation. Canopy is modular and extensible, allowing developers to adapt its components to their specific needs, and is compatible with OpenAI's LLMs, with plans to support additional models soon. The framework is designed to be user-friendly, enabling users to create a production-ready RAG application in under an hour, and can be integrated into existing OpenAI applications. Canopy's functionalities include a Knowledge Base for preparing data, a Context Engine for retrieving relevant documents, and a Chat Engine that implements the RAG workflow to generate highly relevant responses. It is available for immediate use, with future updates expected to expand its capabilities further.