Google Drive and Google Docs integration

Social Media Content Publishing Factory for Streamlined Content Creation Across Platforms Who is this for? This workflow is designed for content creators, social media managers, and marketing teams who need to efficiently create and publish content across multiple social media platforms. It's perfect for businesses looking to maintain a consistent presence across X (Twitter), Instagram, Facebook, LinkedIn, Threads, and YouTube Shorts without spending hours crafting platform-specific content manually. What problem is this workflow solving? Creating tailored content for different social media platforms is time-consuming and requires understanding each platform's unique requirements and audience expectations. This workflow solves the challenge of: Maintaining consistent messaging across platforms while respecting platform-specific formats Generating optimized content that follows best practices for each platform Creating accompanying visuals without graphic design skills Streamlining the approval process before publishing Reducing the time spent on repetitive content creation tasks What this workflow does This automated content factory takes your content idea and transforms it into platform-optimized posts for all major social media channels. The workflow: Accepts your content idea or topic through a chat interface Leverages AI to generate tailored content for each platform (X/Twitter, Instagram, Facebook, LinkedIn, Threads, YouTube Shorts) Creates appropriate images using AI image generation Sends content for approval via email before publishing Publishes approved content to selected platforms Maintains chat memory to improve future content generation Setup Connect your social media platform credentials (X/Twitter, Instagram, Facebook, LinkedIn) Set up your email account for the approval process Configure your OpenAI API key for AI content generation Update the image generation service credentials (Pollinations.ai is used by default) Customize the system prompts and schemas in the Google Docs nodes with your brand voice and content requirements How to customize this workflow to your needs Modify the system prompts in the Google Docs nodes to match your brand voice and content strategy Adjust the social media schemas to include specific fields relevant to your content Update the approval process to include additional stakeholders if needed Add or remove social media platforms based on your marketing strategy Customize the image generation prompts to better match your visual branding Integrate with your existing content calendar or CRM systems This workflow eliminates the need to manually craft different versions of the same content for each platform, saving hours of work while ensuring your social media presence remains consistent and optimized for maximum engagement.

🤖 AI-Powered RAG Chatbot with Google Drive Integration This workflow creates a powerful RAG (Retrieval-Augmented Generation) chatbot that can process, store, and interact with documents from Google Drive using Qdrant vector storage and Google's Gemini AI. How It Works Document Processing & Storage 📚 Retrieves documents from a specified Google Drive folder Processes and splits documents into manageable chunks Extracts metadata using AI for enhanced search capabilities Stores document vectors in Qdrant for efficient retrieval Intelligent Chat Interface 💬 Provides a conversational interface powered by Google Gemini Uses RAG to retrieve relevant context from stored documents Maintains chat history in Google Docs for reference Delivers accurate, context-aware responses Vector Store Management 🗄️ Features secure delete operations with human verification Includes Telegram notifications for important operations Maintains data integrity with proper version control Supports batch processing of documents Setup Steps Configure API Credentials: Set up Google Drive & Docs access Configure Gemini AI API Set up Qdrant vector store connection Add Telegram bot for notifications Add OpenAI Api Key to the 'Delete Qdrant Points by File ID' node Configure Document Sources: Set Google Drive folder ID Define Qdrant collection name Set up document processing parameters Test and Deploy: Verify document processing Test chat functionality Confirm vector store operations Check notification system This workflow is ideal for organizations needing to create intelligent chatbots that can access and understand large document repositories while maintaining context and providing accurate responses through RAG technology.

AI-Powered Tech Radar Advisor This project is built on top of the famous open source ThoughtWorks Tech Radar. You can use this template to build your own AI-Powered Tech Radar Advisor for your company or group of companies. Target Audience This template is perfect for: Tech Audit & Governance Leaders:** Those seeking to build a tech landscape AI platform portal. Tech Leaders & Architects:** Those aiming to provide modern AI platforms that help others understand the rationale behind strategic technology adoption. Product Managers:** Professionals looking to align product innovation with the company's current tech trends. IT & Engineering Teams:** Teams that need to aggregate, analyze, and visualize technology data from multiple sources efficiently. Digital Transformation Experts:** Innovators aiming to leverage AI for actionable insights and strategic recommendations. Data Analysts & Scientists:** Individuals who want to combine structured SQL analysis with advanced semantic search using vector databases. Developers:** Those interested in integrating RAG chatbot functionality with conversation storage. Description Tech Constellation is an AI-powered Tech Radar solution designed to help organizations visualize and steer their technology adoption strategy. It seamlessly ingests data from a Tech Radar Google Sheet—converting it into both a MySQL database and a vector index—to consolidate your tech landscape in one place. The platform integrates an interactive AI chat interface powered by four specialized agents: AI Agent Router:** Analyzes and routes user queries to the most suitable processing agent. SQL Agent:** Executes precise SQL queries on structured data. RAG Agent:** Leverages semantic, vector-based search for in-depth insights. Output Guardrail Agent:** Validates responses to ensure they remain on-topic and accurate. This powerful template is perfect for technology leaders, product managers, engineering teams, and digital transformation experts looking to make data-driven decisions aligned with strategic initiatives across groups of parent-child companies. Features Data Ingestion A Google Sheet containing tech radar data is used as the primary source. The data is ingested and converted into a MySQL database. Simultaneously, the data is indexed into a vector database for semantic (vector-based) search. Interactive AI Chat Chat Integration:** An AI-powered chat interface allows users to ask questions about the tech radar. Customizable AI Agents:** AI Agent Router: Determines the query type and routes it to the appropriate agent. SQL Agent: Processes queries using SQL on structured data. RAG Agent: Performs vector-based searches on document-like data. Output Guardrail Agent: Validates queries and ensures that the responses remain on-topic and accurate. Usage Examples Tell me, is TechnologyABC adopted or on hold, and why? List all the tools that are considered part of the strategic direction for company3 but are not adopted. Project Links & Additional Details GitHub Repository (Frontend Interface Source Code):** github.com/dragonjump/techconstellation Try It:** https://scaler.my

Compare Local Ollama Vision Models for Image Analysis using Google Docs Process images using locally hosted Ollama Vision Models to extract detailed descriptions, contextual insights, and structured data. Save results directly to Google Docs for efficient collaboration. Who is this for? This workflow is ideal for developers, data analysts, marketers and AI enthusiasts who need to process and analyze images using locally hosted Ollama Vision Language Models. It’s particularly useful for tasks requiring detailed image descriptions, contextual analysis, and structured data extraction. What problem is this workflow solving? / Use Case The workflow solves the challenge of extracting meaningful insights from images in exhaustive detail, such as identifying objects, analyzing spatial relationships, extracting textual elements, and providing contextual information. This is especially helpful for applications in real estate, marketing, engineering, and research. What this workflow does This workflow: Downloads an image file from Google Drive. Processes the image using multiple Ollama Vision Models (e.g., Granite3.2-Vision, Gemma3, Llama3.2-Vision). Generates detailed markdown-based descriptions of the image. Saves the output to a Google Docs file for easy sharing and further analysis. Setup Ensure you have access to a local instance of Ollama. https://ollama.com/ Pull the Ollama vision models. Configure your Google Drive and Google Docs credentials in n8n. Provide the image file ID from Google Drive in the designated node. Update the list of Ollama vision models Test the workflow by clicking ‘Test Workflow’ to trigger the process. How to customize this workflow to your needs Replace the image source with another provider if needed (e.g., AWS S3 or Dropbox). Modify the prompts in the "General Image Prompt" node to suit specific analysis requirements. Add additional nodes for post-processing or integrating results into other platforms like Slack or HubSpot. Key Features: Detailed Image Analysis**: Extracts comprehensive details about objects, spatial relationships, text elements, and contextual settings. Multi-Model Support**: Utilizes multiple vision models dynamically for optimal performance. Markdown Output**: Formats results in markdown for easy readability and documentation. Google Drive Integration**: Seamlessly downloads images and saves results to Google Docs.

The best content automation template in the market is now even better—with “deep research” on time-sensitive topics\! Unlike most n8n content automation templates that are mainly for “demo purposes,” this advanced n8n workflow is for the real PROs. It conducts in-depth research on the latest information about a topic, then automatically creates and publishes SEO-optimized blog posts to your WordPress website. In addition, it generates a unique image for each chapter and a featured image for the overall article, and it collects internal website links—seamlessly inserting links throughout each chapter and the entire article. Furthermore, it backs up all content and images to a designated folder in your Google Drive. This integrated approach not only creates high-quality, comprehensive content for readers but also enhances on-page SEO, improves navigation, and streamlines your content creation process—saving you time while ensuring your work is securely stored. This is a complimentary variation of the n8n WordPress Auto-Blogging Pro for SEO topics. That one specializes in auto-blogging content about established topics that do not need up-to-date information while this one takes it further by incorporating online research into the workflow. Both make up the perfect combo to run your blog on autopilot\! How It Works Trigger: It activates upon adding a new row to a Google Sheet. Users can control many customizable parameters, such as key topic, number of subtopics, target audience, length, and style. Initial Research: The workflow initiates preliminary research on the topic to gather insights for the content planning phase. Structure Planning: Based on the initial research, it plans a detailed structure for the entire article and breaks the article into subtopics strongly tied to the main topic. In-Depth Research & Writing: For each subtopic, it conducts further research to gather the most up-to-date, relevant information, then uses that research to write each chapter in depth. Image Generation: It generates and adds images for each chapter, as well as a featured image for the article. Internal Linking: The system gathers internal website links and strategically embeds them within each chapter and throughout the article, boosting SEO and enhancing user navigation. Final Assembly & Publishing: All texts, images, and links are combined into one comprehensive article, which is then published directly to your WordPress website. You can also choose to post it as a draft for final review. Auto Backup to Drive: Get peace of mind knowing all content (blog post and images) is automatically saved to Google Drive, organized in a folder named after the blog post title. Unique Features Deep Research: The workflow leverages advanced, real-time research to gather the latest information about a topic. It breaks down the key topic into subtopics and conducts in-depth research on each one, ensuring the most comprehensive and current knowledge. Full Automation: Designed to be 100% automated, the workflow runs without manual intervention once imported and configured. Simple Activation: It is easily triggered through the Google Sheets interface—simply add a new row to a Google Sheet. Customization Options: Offers a wide array of options, including topic, category, target audience, word count, number of chapters, length of introduction and conclusion, and writing style. It also allows for the inclusion of calls-to-action (CTAs) and company/product introductions. Advanced Loop in Loop: Clever looping is used to write each chapter and generate images, ensuring optimal results. “Wait” nodes are added where appropriate to avoid API call rate limits. Automatic Content Saving: After the blog post is created, all content and images are automatically saved to Google Drive, preventing data loss. The folder is named after the blog post title. SEO-Optimized Content: It is designed to create SEO-optimized content using seed keywords. Internal Link Limit: The workflow limits the number of internal links to 20 by default. Error Catch: “If” nodes are strategically used to ensure that the output from AI nodes strictly meets the JSON schema, ensuring a smooth flow of data without interruption. And many more big and small improvements. Requirements Please make sure you have these requirements ready to ensure smooth deployment of this n8n workflow template: OpenAI API or equivalent for text and image generation PerplexityAI API or equivalent for online research A WordPress website (other website platforms will not work\!) Google Sheets for triggering the workflow, or a trigger of your choice Google Drive and Google Docs for auto backup Set Up Steps Install the Workflow Template: Import the JSON files into your n8n instance. There are 2 files: one for the main workflow and one for the research tool (PerplexityAI). Connect the Workflow with Your Accounts: Link your accounts for OpenAI API, PerplexityAI API, Google Drive, Google Sheets, Google Docs, and WordPress website. Configure the Google Sheet: Ensure your Google Sheet is set up to trigger the workflow upon adding a new row and that the input data is correctly formatted. Customize the Inputs: Adjust parameters like topic, target audience, and writing style to match your specific content needs. Optimize prompts for the best results. Test the Workflow: Use low-cost AI models and image settings initially to ensure everything runs smoothly. Tailor Further as Needed: Modify workflow elements to perfectly align with your needs and content strategy. Tips for PROs Image Generation: The default AI model for image generation is OpenAI’s Dall-E. However, the outputs of this model are not impressive. Consider using FLUX.1 for better image quality. Research: PerplexityAI is the tool of choice for research. The default model used in this workflow is “sonar” due to its fast speed and low cost. Feel free to experiment with its other models, including the “sonar-deep-research” model, which is dedicated to deep research. Triggering: Triggering with a new row on Google Sheets is limited and unreliable. Consider setting an auto trigger with a daily schedule at a specific time. You can even put the whole workflow in a loop to process multiple rows one-by-one from Google Sheets. Human in the Loop: It is possible to incorporate a human review process. For example, after the article is posted to WordPress as a draft, a human can review the draft. Only after approval will the post be published, and a final copy of the post will be saved to the shared Drive folder.

This n8n workflow creates a financial analysis tool that generates reports on a company's quarterly earnings using the capabilities of OpenAI GPT-4o-mini, Google's Gemini AI and Pinecone's vector search. By analyzing PDFs of any company's earnings reports from their Investor Relations page, this workflow can answer complex financial questions and automatically compile findings into a structured Google Doc. How it works: Data loading and indexing Fetches links to PDF earnings document from a Google Sheet containing a list of file links. Downloads the PDFs from Google Drive. Parses the PDFs, splits the text into chunks, and generates embeddings using the Embeddings Google AI node (text-embedding-004 model). Stores the embeddings and corresponding text chunks in a Pinecone vector database for semantic search. Report generation with AI agent Utilizes an AI Agent node with a specifically crafted system prompt. The agent orchestrates the entire process. The agent uses a Vector Store Tool to access and retrieve information from the Pinecone database. Report delivery Saves the generated report as a Google Doc in a specified Google Drive location. Set up steps Google Cloud Project & Vertex AI API: Create a Google Cloud project. Enable the Vertex AI API for your project. Google AI API key: Obtain a Google AI API key from Google AI Studio. Pinecone account and API key: Create a free account on the Pinecone website. Obtain your API key from your Pinecone dashboard. Create an index named company-earnings in your Pinecone project. Google Drive - download and save financial documents: Go to a company you want to analize and download their quarterly earnings PDFs Save the PDFs in Google Drive Create a Google Sheet that stores a list of file URLs pointing to the PDFs you downloaded and saved to Google Drive Configure credentials in your n8n environment for: Google Sheets OAuth2 Google Drive OAuth2 Google Docs OAuth2 Google Gemini(PaLM) Api (using your Google AI API key) Pinecone API (using your Pinecone API key) Import and configure the workflow: Import this workflow into your n8n instance. Update the List Of Files To Load (Google Sheets) node to point to your Google Sheet. Update the Download File From Google Drive to point to the column where the file URLs are Update the Save Report to Google Docs node to point to your Google Doc where you want the report saved.