Build & Query RAG System with Google Drive, OpenAI GPT-4o-mini, and Pinecone

🔍 What This Workflow Does This RAG Pipeline in n8n automates document ingestion from Google Drive, vectorizes it using OpenAI embeddings, stores it in Pinecone, and enables chat-based retrieval using LangChain agents. Main Functions: 📂 Auto-detects new files uploaded to a specific Google Drive folder. 🧠 Converts the file into embeddings using OpenAI. 📦 Stores them in a Pinecone vector database. 💬 Allows a user to query the knowledge base through a chat interface. 🤖 Uses a GPT-4o-mini model with LangChain to generate intelligent responses using retrieved context. ⚙️ Setup Instructions Connect Accounts Ensure these services are connected in n8n: ✅ Google Drive (OAuth2) ✅ OpenAI ✅ Pinecon

Help me set up the n8n workflow "Build & Query RAG System with Google Drive, OpenAI GPT-4o-mini, and Pinecone" (https://n8n.io/workflows/4501). It uses: Google Drive, AI Agent, Embeddings OpenAI, OpenAI Chat Model, Recursive Character Text Splitter, Pinecone Vector Store, Default Data Loader. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.