Load and aggregate files from a Google Drive folder into a key-value dictionary

What does this template do? This workflow automates the process of retrieving all Google Docs from a specified Google Drive folder, extracting their content, and structuring the data into a unified key-value dictionary, where: - Key = The file name - Value = The content of the document (with normalized newlines) This is ideal for use cases such as knowledge ingestion, prompt context preparation, or populating a RAG (Retrieval-Augmented Generation) system with reference documents. Use Case Perfect for teams or individuals who maintain prompts, content, or reference material in Google Docs and want to integrate that data dynamically into automation or AI workflows. What the Workflow Does - ⚡ Triggered via Execute Workflow Trigger from another workflow - 📁 Retrieves all files from a specified Google Drive folder - 📄 Downloads the full content of each Google Docs file - 🧩 Maps each file name to its content using a Set node - 🧠 Aggregates all entries into a single dictionary with Code node - 🧾 Outputs a JSON object like: Apps & Services Used - Google Drive - Google Docs - n8n Code node Pre-requisites - A connected Google account with access to the target Drive folder - OAuth2 credentials for both: - Google Drive - Google Docs Customization Tips - Change Folder: Update the Google Drive node to select a specific folder rather than root - Support Other File Types: Replace or complement the Google Docs node to handle other formats (e.g., PDFs or text files) - Data Cleaning: Modify the Code node to adjust text normalization to your needs Additional Use Cases 🧠 Prompt Management for AI Workflows - Centralize your GPT prompt templates in Google Docs instead of hardcoding them in n8n - Easily manage prompt versions and edits directly from Google Drive - Dynamically load prompts into downstream nodes (like OpenAI or Hugging Face) without redeploying workflows 📚 Knowledge Base Loader for RAG Systems - Aggregate internal knowledge, FAQs, SOPs, or policy docs from Google Docs into a structured dictionary - Use the resulting object as the context source for Retrieval-Augmented Generation models 🎛️ Dynamic Form Inputs or Question Sets - Maintain forms, surveys, or interview questions in Google Docs - Load the content into n8n for form generation, chatbot interaction, or customer intake flows 📄 Client-Specific Config or Script Templates - For client onboarding workflows, load client-specific scripts or prompts from individual docs named after each client - Helps automate client-facing document generation or AI interactions 📋 Content Ingestion for Translation, Summarization, or Sentiment Analysis - Batch process internal documentation or user-submitted Google Docs - Trigger summarization, translation, or classification pipelines using the document contents 🔄 Document-to-Database Import - Automatically fetch and normalize Google Docs contents, ready to push into a database (e.g., Notion, Airtable, PostgreSQL)