The purpose of this n8n workflow is to automate the process of identifying incoming Gmail emails that are requesting an appointment, evaluating their content, checking calendar availability, and then composing and sending a response email. Note that to use this template, you need to be on n8n version 1.19.4 or later.
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Gmail
OpenAI Chat Model
Text ClassifierRelated workflows
See all AI Automation→AI: Summarize podcast episode and enhance using Wikipedia
The workflow automates the process of creating a summarized and enriched podcast digest, which is then sent via email. Note that to use this template, you need to be on n8n version 1.19.4 or later.
Analyze YouTube comments with OpenAI, Google Sheets, and Gmail
Quick overview This workflow monitors a Google Sheets list of YouTube video IDs, fetches video details and top comments from the YouTube Data API, analyzes the comments with OpenAI into structured sentiment and themes, emails an HTML report via Gmail, and writes the results back to Google Sheets. How it works Triggers every minute when a row in Google Sheets is added or updated. Reads the video ID and status from the row and continues only if the status is set to “Pending”. Calls the YouTube Data API to fetch the video’s metadata and the top comment threads for that video. Flattens the comment threads, calculates basic stats (comment count and average likes), and compiles a limited comment text block for analysis. If comments exist, sends the compiled comments and video title to OpenAI to generate a structured analysis (sentiment score, sentiment breakdown, themes, questions, feedback, insights, and summary). Builds an HTML email report from the structured results, sends it to the configured recipient with Gmail, and updates the Google Sheet row with the analysis fields; if no comments exist, marks the row as “No comments”. Setup Create or duplicate a Google Sheet with at least “Vi
Custom LangChain agent written in JavaScript
This workflow has multiple functionalities. It starts with a manual trigger, "When clicking 'Execute Workflow'", that activates two separate paths. The first path takes a preset string "Tell me a joke" and processes it through a custom Language Learning Model (LLM) chain node. This node interacts with an OpenAI node for query processing. The second path takes another preset string "What year was Einstein born?" and passes it to an "Agent" node. This agent further interacts with a Chat OpenAI node and a custom Wikipedia node to produce the required information. The workflow uses both built-in and custom nodes, and integrates with OpenAI for both paths. It's built for experimenting with language models, specifically in the context of conversational agents and information retrieval. Note that to use this template, you need to be on n8n version 1.19.4 or later.