🚀 Process YouTube Transcripts with Apify, OpenAI & Pinecone Database

🚀 YouTube Transcript Indexing Backend for Pinecone 🎥💾 This tutorial explains how to build the backend workflow in n8n that indexes YouTube video transcripts into a Pinecone vector database. Note: This workflow handles the processing and indexing of transcripts only—the retrieval agent (which searches these embeddings) is implemented separately. 📋 Workflow Overview This backend workflow performs the following tasks: Fetch Video Records from Airtable 📥 Retrieves video URLs and related metadata. Scrape YouTube Transcripts Using Apify 🎬 Triggers an Apify actor to scrape transcripts with timestamps from each video. Update Airtable with Transcript Data 🔄 Stores the fetched transcript JSON b

Help me set up the n8n workflow "🚀 Process YouTube Transcripts with Apify, OpenAI & Pinecone Database" (https://n8n.io/workflows/3184). It uses: Airtable, HTTP Request, Code, Embeddings OpenAI, 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.