Context-Aware Document Processing from Google Drive to Pinecone

The workflow begins by retrieving a document from Google Drive, extracting its text, and splitting it into contextually meaningful chunks. Each chunk is processed to generate contextual metadata using OpenRouter and Google Gemini, creating enriched embeddings. These embeddings are then stored in Pinecone, optimizing them for retrieval-augmented generation (RAG) applications. This setup is ideal for semantic search, AI-powered knowledge management, and intelligent document retrieval.