Csv to JSON converter with error handling and Slack notifications
Who this template is for This template is for developers or teams who need to convert CSV data into JSON format through an API endpoint, with support for both file uploads and raw CSV text input. Use case Converting CSV files or raw CSV text data into JSON format via a webhook endpoint, with error handling and notifications. This is particularly useful when you need to transform CSV data into JSON as part of a larger automation or integration process. How this workflow works Receives POST requests through a webhook endpoint at /tool/csv-to-json Uses a Switch node to handle different input types: File uploads (binary data) Plain text CSV data JSON format data Processes the CSV data: For files: Uses the Extract From File node For raw text: Converts the text to CSV using a custom Code node that handles both comma and semicolon delimiters Aggregates the processed data and returns: Success response (200): Converted JSON data Error response (500): Error message with details In case of errors, sends notifications to a Slack error channel with execution details and a link to debug Set up steps Configure the webhook endpoint by deploying the workflow Set up Slack integration for error notifications: Update the Slack channel ID (currently set to "C0832GBAEN4") Configure OAuth2 authentication for Slack Test the endpoint using either: CURL for file uploads: bash bash Copy curl -X POST "https://yoururl.com/webhook-test/tool/csv-to-json" \ -H "Content-Type: text/csv" \ --data-binary @path/to/your/file.csv Or send raw CSV data as text/plain content type
By n8n TeamGenerate VEED AI talking head videos from sheet rows with OpenAI or ElevenLabs
A production-ready n8n workflow that generates AI avatar videos from images and text using VEED Fabric 1.0, with flexible multi-platform publishing capabilities. Key Capabilities Unlimited Scale Process any number of videos: Sequential processing ensures each video is fully generated and published before moving to the next Batch processing: Add multiple video requests to Google Sheet and let the workflow process them automatically No context mixing: Each video maintains its own configuration throughout the entire pipeline Flexible Publishing Per-video platform selection: Each video can target different platforms (e.g., Video 1 → Instagram+YouTube, Video 2 → Telegram only) Optional publishing: Leave PLATFORMS column empty to generate videos without publishing (videos saved to Drive) Supported platforms: Instagram Reels, YouTube/Shorts, Facebook, Telegram, Threads Platform-specific formatting: Automatic optimization for each platform's requirements Smart Processing Two TTS providers: Choose OpenAI or ElevenLabs per video Configurable quality: Select resolution (480p/720p) and aspect ratio (9:16, 16:9, 1:1) per video Approval workflow: Review videos before publishing with email approve/reject buttons Error handling: Automatic error detection with detailed email notifications Status Tracking Real-time status updates: Google Sheet updates as workflow progresses (new → processing → published) Detailed results: Per-platform success/failure tracking with post URLs Email reports: Comprehensive publishing reports with links to all posted content How It Works Input: Add rows to Google Sheet with video details TTS: Generate speech using OpenAI or ElevenLabs Video: VEED Fabric 1.0 creates talking head video Approval: Email with video preview and approve/reject buttons Publish: Sequential publishing to selected platforms Report: Status update in sheet + email with results Requirements Fal.ai API Key (for VEED) Google OAuth (Sheets, Drive, Gmail) TTS: OpenAI or ElevenLabs API Key Social Media credentials (optional, only for platforms you use) Telegram Bot Token (optional, only for Telegram) Node: n8n-nodes-veed Author: VEED.io
By VEEDScrape Trustpilot reviews 📊 with ScrapegraphAI and OpenAI Reputation analysis
This workflow automates the collection, analysis, and reporting of Trustpilot reviews for a specific company using ScrapeGraphAI, transforming unstructured customer feedback into structured insights and actionable intelligence. --- Key Advantages ✅ End-to-End Automation The entire process—from scraping reviews to delivering a polished management report—is fully automated, eliminating manual data collection and analysis . ✅ Structured Insights from Unstructured Data The workflow transforms raw, unstructured review text into structured fields and standardized sentiment categories, making analysis reliable and repeatable. ✅ Company-Level Reputation Intelligence Instead of focusing on individual products, the analysis evaluates the overall brand, service quality, customer experience, and operational performance, which is critical for leadership and strategic teams. ✅ Action-Oriented Outputs The AI-generated report goes beyond summaries by: Identifying reputational risks Highlighting improvement opportunities Proposing concrete actions with priorities, effort estimates, and KPIs ✅ Visual & Executive-Friendly Reporting Automatic sentiment charts and structured executive summaries make insights immediately understandable for non-technical stakeholders. ✅ Scalable and Configurable Easily adaptable to different companies or review volumes Page limits and batching protect against rate limits and excessive API usage ✅ Cross-Team Value The output is tailored for multiple internal teams: Management Marketing Customer Support Operations Product & UX --- Ideal Use Cases Brand reputation monitoring Voice-of-the-customer programs Executive reporting Customer experience optimization Competitive benchmarking (by reusing the workflow across brands) --- How It Works This workflow automates the complete process of scraping Trustpilot reviews, extracting structured data, analyzing sentiment, and generating comprehensive reports. The workflow follows this sequence: Trigger & Configuration: The workflow starts with a manual trigger, allowing users to set the target company URL and the number of review pages to scrape. Review Scraping: An HTTP request node fetches review pages from Trustpilot with pagination support, extracting review links from the HTML content. Review Processing: The workflow processes individual review pages in batches (limited to 5 reviews per execution for efficiency). Each review page is converted to clean markdown using ScrapegraphAI. Data Extraction: An information extractor using OpenAI's GPT-4.1-mini model parses the markdown to extract structured review data including author, rating, date, title, text, review count, and country. Sentiment Analysis: Another OpenAI model performs sentiment classification on each review text, categorizing it as Positive, Neutral, or Negative. Data Aggregation: Processed reviews are collected and compiled into a structured dataset. Analytics & Visualization: A pie chart is generated showing sentiment distribution A comprehensive reputation analysis report is created using an AI agent that evaluates company-level insights, recurring themes, and provides actionable recommendations Reporting & Delivery: The analysis is converted to HTML format and sent via email, providing stakeholders with immediate insights into customer feedback and company reputation. Set Up Steps To configure and run this workflow: Credential Setup: Configure OpenAI API credentials for the chat models and information extraction Set up ScrapeGraphAI credentials for webpage-to-markdown conversion Configure Gmail OAuth2 credentials for email notifications Company Configuration: In the "Set Parameters" node, update company_id to the target Trustpilot company URL Adjust max_page to control how many review pages to scrape Review Processing Limits: The "Limit" node restricts processing to 5 reviews per execution to manage API costs and processing time Adjust this value based on your needs and OpenAI usage limits Email Configuration: Update the "Send a message" node with the recipient email address Customize the email subject and content as needed Analysis Customization: Modify the prompt in the "Company Reputation Analyst" node to tailor the report format Adjust sentiment analysis categories if different classification is needed Execution: Click "Test workflow" to execute the manual trigger Monitor execution in the n8n editor to ensure all API calls succeed Check the configured email inbox for the generated report Note: Be mindful of API rate limits and costs associated with OpenAI and ScrapegraphAI services when processing large numbers of reviews. The workflow includes a 5-second delay between paginated requests to comply with Trustpilot's terms of service. --- 👉 Subscribe to my new YouTube channel. Here I’ll share videos and Shorts with practical tutorials and FREE templates for n8n. [](https://youtube.com/@n3witalia) --- Need help customizing? Contact me for consulting and support or add me on Linkedin.
By Davide