Welcome to my Automated Image Metadata Tagging Workflow! This workflow automatically analyzes the image content with the help of AI and writes it directly back into the image file as keywords. This workflow has the following sequence: Google Drive trigger (scan for new files added in a specific folder) Download the added image file Analyse the content of the image and extract the file as Base64 code Merge Metadata and Base64 Code Code Node to write the Keywords into the Metadata (dc:subject) Convert to file and update the original file in the Google Drive folder The following accesses are required for the workflow: Google Drive: Documentation AI API access (e.g.
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See all AI Automation→Run a multimodal WhatsApp AI assistant with OpenAI for text, voice and images
Quick overview This workflow turns WhatsApp into a multimodal assistant that answers text, voice notes, images, and PDF documents using OpenAI, and can generate images with DALL·E on demand, replying back in WhatsApp with either text, audio, or an image. How it works Triggers when a new WhatsApp message is received. Detects whether the incoming message is text, a voice note, an image, a PDF document, or an unsupported type. For text messages, generates an image with OpenAI DALL·E when the message starts with the configured /image command, and sends the generated image back to the sender. For voice notes, fetches the WhatsApp media URL, downloads the audio, transcribes it with OpenAI, and forwards the transcript to the assistant. For images, fetches the WhatsApp media URL, downloads the image, describes it with OpenAI vision using the configured analysis prompt, and forwards the description (plus any caption) to the assistant. For PDF documents, downloads the file from WhatsApp, extracts the PDF text, and forwards the extracted content (plus any caption) to the assistant, while non-PDF files receive an error message. Uses an OpenAI chat model with per-contact short-term memory to ge
Load and summarize Google Drive files with AI
This workflow includes advanced features like text summarization and tokenization, it's ideal for automating document processing tasks that require parsing and summarizing text data from Google Drive. To use this template, you need to be on n8n version 1.19.4 or later.
Ask questions about a PDF using AI
The workflow first populates a Pinecone index with vectors from a Bitcoin whitepaper. Then, it waits for a manual chat message. When received, the chat message is turned into a vector and compared to the vectors in Pinecone. The most similar vectors are retrieved and passed to OpenAI for generating a chat response. Note that to use this template, you need to be on n8n version 1.19.4 or later.