RAG:Context-Aware Chunking | Google Drive to Pinecone via OpenRouter & Gemini

Workflow based on the following article. https://www.anthropic.com/news/contextual-retrieval This n8n automation is designed to extract, process, and store content from documents into a Pinecone vector store using context-based chunking. The workflow enhances retrieval accuracy in RAG (Retrieval-Augmented Generation) setups by ensuring each chunk retains meaningful context. Workflow Breakdown: 🔹 Google Drive - Retrieve Document: The automation starts by fetching a source document from Google Drive. This document contains structured content, with predefined boundary markers for easy segmentation. 🔹 Extract Text Content - Once retrieved, the document’s text is extracted for processing. Speci

Help me set up the n8n workflow "RAG:Context-Aware Chunking | Google Drive to Pinecone via OpenRouter & Gemini" (https://n8n.io/workflows/2871). It uses: Google Drive, Code, AI Agent, Recursive Character Text Splitter, Pinecone Vector Store, Default Data Loader, Embeddings Google Gemini. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.