Automate systematic literature reviews with Google Drive, GPT-4, Gemini, Qdrant and Airtable

How it works Automates systematic literature review by downloading papers from Google Drive, extracting text, and evaluating them against strict inclusion/exclusion criteria using LLM agents Routes included papers to Qdrant vector stores with Gemini embeddings for semantic search, and excluded papers to a separate folder Logs all decisions to Airtable with PRISMA-compliant justification for complete audit trails Set up steps Connect Google Drive credentials to access your paper folder Configure Airtable base and table for decision logging Add OpenAI (GPT-4) and Google Gemini API credentials for LLM evaluation and embeddings Set up Qdrant instances for vector storage (supports up to 3 collect

Help me set up the n8n workflow "Automate systematic literature reviews with Google Drive, GPT-4, Gemini, Qdrant and Airtable" (https://n8n.io/workflows/12827). It uses: Airtable, Google Drive, Code, Basic LLM Chain, OpenAI Chat Model, Structured Output Parser, Default Data Loader, Qdrant Vector Store, Embeddings Google Gemini, Google Gemini Chat Model. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.