Auto-track Amazon prices with Google Gemini & send alerts to Telegram

AI-Powered Amazon Price Tracker to Telegram

Overview Automate your deal hunting with this intelligent Amazon price tracker. This workflow uses the power of AI to monitor any Amazon product page at regular intervals. When the price drops to or below your desired target, it instantly sends a notification to your Telegram chat. Say goodbye to manual price checking and never miss a sale, a lightning deal, or a Black Friday bargain again.

Unlike traditional scrapers that break when a website's layout changes, this workflow uses a Large Language Model (Google Gemini) to understand the page content, making it significantly more robust and reliable.

🚀 Key Features AI-Powered Data Extraction: Leverages Google Gemini to intelligently read the product page and extract the name and price, making it resilient to Amazon's frequent layout updates. Scheduled Automation: Set it up once with a schedule (e.g., every hour) and let it run in the background. Instant Telegram Alerts: Get real-time notifications directly in Telegram the moment a price drops to your target. Centralized & Easy Configuration: A single Set node holds all your settings—product URL, target price, and Telegram Chat ID—for quick and easy updates. Built-in Error Handling: Intelligently checks if data was extracted correctly and sends an error alert if it fails, so you're always in the loop. Cost-Efficient Processing: Includes a pre-processing step to clean and simplify the page's HTML, reducing the amount of data sent to the AI and lowering potential token costs.

⚙️ How It Works The workflow follows a clear, linear process from scheduling to notification.

1. Initiation and Configuration A Schedule node triggers the workflow automatically at your chosen interval (e.g., every hour). A Set node named Config: Product & Alert acts as your control panel. Here, you define the Amazon product URL, your target price, and your Telegram Chat ID.

2. Fetch and Clean Product Page An HTTP Request node fetches the full HTML content of the Amazon product URL. A Code node then cleans this raw HTML. It strips out unnecessary scripts, styles, and tags, leaving only the core text content. This crucial step makes the data easier for the AI to analyze accurately and efficiently.

3. AI-Powered Data Extraction An AI Agent node sends the cleaned text to the Google Gemini model. It uses a specific prompt to ask the AI to identify and extract the product's name (productName) and its current price (priceValue) as a number. A Structured Output Parser ensures the AI returns the data in a clean, predictable JSON format (e.g., {"productName": "...", "priceValue": 49.99}), which is essential for the next steps.