Part 4/8:
Once setup is complete, we’ll create a node to download documents from Google Drive whenever there’s an update. This document will be processed into smaller chunks and embedded into our Pinecone database.
Setting Up the Vector Database
After retrieving our document from Google Drive, the next step is to create embeddings from its content:
- Using Pinecone, we will break the document into manageable chunks and store them efficiently in the vector database. Each chunk is tagged with metadata such as the file name, ensuring easy retrieval.
Handling Voice Queries
Next, we will set up the workflow for processing user voice queries:
Start with a webhook node to receive audio data from the website.
Implement an OpenAI node to transcribe the audio input into text.