Pinecone LangChain - RAG Questions/Answer Your Own Files (Multiple Files with Source & Page #) Code!

This video guides you through the basic retrieval augmented generation (RAG) method of ingesting multiple custom PDF files (using DirectoryLoader from LangChain) externally into Pinecone as embeddings(vectors); guides you on the basics of querying your custom PDF files to get answers back (semantic search) from the Pinecone vector database, via the OpenAI LLM API.
Using LLMs to query your own data is a powerful application to become operationally efficient for various tasks requiring looking up large documents. We walk through 2 approaches, first using the RetrievalQA chain and the second using VectorStoreAgent from LangChain
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