Automated book summarization with DeepSeek AI, Qdrant Vector DB & Google Drive
π AI Book Summarizer with Vector Search β n8n Automation Overview This n8n workflow automates the process of summarizing uploaded books from Google Drive using vector databases and LLMs. It uses Cohere for embeddings, Qdrant for storage and retrieval, and DeepSeek or your preferred LLM for summarization and Q\&A. Designed for researchers, students, and productivity enthusiasts! Result Example --- Problem π οΈ β³ Reading full books or papers to extract core ideas can take hours. π§ Manually summarizing or searching inside long documents is inefficient and overwhelming. --- Solution β Use this workflow to: Upload a book to Google Drive π₯ Auto-split and embed the content into Qdrant π Summarize it using DeepSeek or another LLM π€ Store the final summary back to Google Drive π€ Clean up the vector store afterward π§Ή --- π₯ Result β‘ Instant AI-generated book summary π‘ Ability to perform semantic search and question-answering π Summary saved back to your cloud π§ Enhanced productivity for learning and research --- Setup βοΈ (4β8 minutes) Google Drive Setup π Connect Google Drive credentials π Create an input folder (e.g., book_uploads) π Create an output folder (e.g., book_summaries) β‘ Trigger: Use File Created node to monitor book_uploads π₯ Summary will be saved in book_summaries LLM & Embeddings Setup π Create and test API keys for: DeepSeek/OpenAI for summarization Cohere for embeddings Qdrant for vector storage π§ͺ Ensure all credentials are added in n8n --- How It Works π π A file is uploaded to Google Drive β¬οΈ File is downloaded 𧱠It's processed, split into chunks, and sent to Qdrant using Cohere embeddings β A Q\&A chain with vector retriever performs information extraction π§ A DeepSeek AI Agent analyzes and summarizes the book π€ The summary is saved to your Drive 𧽠The Qdrant vector collection is deleted (clean-up) --- Whatβs Included π¦ β Google Drive integration (input/output) β File chunking and embedding using Cohere β Vector storage with Qdrant β Q\&A with vector retrieval β Summarization via DeepSeek or other LLM β Clean-up for minimal storage overhead --- Customization π¨ You can tailor it to your use case: π§βπ« Adjust summarization prompt for study notes or executive summaries π Add translation node for multilingual support π Enable long-term memory by skipping vector deletion π¨ Send summaries to Notion, Slack, or Email 𧩠Use other LLM providers (OpenAI, Claude, Gemini, etc.) --- π Explore more workflows β€οΈ Buy more workflows at: adamcrafts π¦Ύ Custom workflows at: adamcrafts@cloudysoftwares.com adamaicrafts@gmail.com > Build once, customize endlessly, and scale your video content like never before. π
By Abdellah HomraniTransform product images to marketing ads using Google Gemini AI
Transform Product Photos into Marketing Images with AI Made by Biznova | TikTok --- π― Who's it for E-commerce sellers, social media marketers, small business owners, and content creators who need professional product advertising images without expensive photoshoots or graphic designers. β¨ What it does This workflow automatically transforms simple product photos into polished, professional marketing images featuring: Professional models showcasing your product Aesthetically pleasing, contextual backgrounds Professional lighting and composition Lifestyle scenes that help customers envision using the product Commercial-ready quality suitable for ads and e-commerce π How it works Upload your basic product photo via the web form AI analyzes your product and generates a complete marketing scene Download your professional marketing image automatically Use it immediately in ads, social media, or product listings βοΈ Setup Requirements OpenRouter Account: Create a free account at openrouter.ai API Key: Generate your API key from the OpenRouter dashboard Add Credentials: Configure the OpenRouter API credentials in the "AI Marketing Image Generator" node Test: Upload a sample product image to test the workflow π¨ How to customize Edit the prompt in the "AI Marketing Image Generator" node to match your brand style Adjust file formats in the upload form (currently accepts JPG/PNG) Modify the response message in the final form node Add your branding by including brand colors or style preferences in the prompt π‘ Pro Tips Use high-resolution product images for best results Test different prompt variations to find your ideal style Save successful prompts for consistent brand imagery Batch process multiple products by running the workflow multiple times π§ Quick Setup Guide Prerequisites OpenRouter account (Sign up here) API key from OpenRouter dashboard Configuration Steps Click on "AI Marketing Image Generator" node Add your OpenRouter API credentials Save and activate the workflow Test with a product image Customization To change the image style: Edit the prompt in the "AI Marketing Image Generator" node Add specific instructions about colors, mood, or setting Include brand-specific requirements Example custom prompt additions: "Use a minimalist white background" "Feature a modern, urban setting" "Include warm, natural lighting" "Show the product in a luxury lifestyle context"
By BiznovaCreate personal data vector store from Google Sheets with OpenAI & Gemini AI
This workflow integrates Google Sheets with Supabase Vector Store for storing personal data as vectors. It utilizes OpenAI and Google Gemini AI models for enhanced data processing and querying. The workflow performs the following tasks: Extracts personal data from Google Sheets. Processes the data using AI tools like OpenAI and Google Gemini for intelligent insights. Inserts the data into Supabase as vectors, enabling efficient storage and fast querying. Includes seamless integration with Postgres for memory management. Supports data loading, embedding, and management. This template is ideal for: Personal data storage with AI-driven querying and analysis. Building intelligent agents that interact with your data. Efficient vector-based storage for personal information. Perfect for those looking to integrate AI into their personal data workflows.
By Mustafa Polat